Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer 3030688437, 9783030688431

Citation preview

Paul Holvoet

Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer

Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer

Paul Holvoet

Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer

Paul Holvoet Experimental Cardiology KU Leuven Leuven, Belgium Illustrations by Pieterjan Ginckels Faculty of Architecture KU Leuven Ghent, Belgium

ISBN 978-3-030-68843-1 ISBN 978-3-030-68844-8 (eBook) https://doi.org/10.1007/978-3-030-68844-8 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

For: Catherine Tine & Pieterjan Xanne & Pol Polly Pau & Umi

Preface

Protein-coding sequences occupy less than 2% of the genome, and 98% of the genome is transcribed into non-coding RNAs, of which many display regulatory functions. Our first objective was to give insight into the functional role of non-coding RNAs in the development of cardiometabolic diseases: obesity, type 2 diabetes, non-alcoholic fatty liver disease, atherosclerosis, myocardial infarction, cardiomyopathy, and heart failure. Our second goal was to investigate the relationship of this cluster with cancer. We started this review because tumor growth and metastasis require tight regulation of oxidative stress, immune response and inflammation, glucose uptake, and insulin signaling. Our PubMed survey learned that the number of published non-coding RNArelated studies is overwhelming. More than 1,800 papers are related to non-coding RNAs with obesity, more than 1,400 with type 2 diabetes, more than 300 with nonalcoholic fatty liver disease, more than 2,000 with atherosclerosis (of which more than 200 related to acute myocardial infarction), and more than 1,400 with cardiomyopathy and heart failure. More than 80,000 papers dealt with the association of non-coding RNAs and cancer. Only when I became an emeritus professor, I got the time to embark on an exhaustive and time-consuming analysis of the literature about non-coding RNAs that are functionally and clinically related to metabolic and cardiovascular diseases, and metabolic diseases and cancer. We followed current guidance on producing high-quality systematic reviews and meta-analyses. In following these standards, we provided quality evidence for the rational choice of a cluster of non-coding RNAs to focus on in future research, identifying non-coding RNAs with high potential for clinical applicability. Bold, functional data further supported this rational choice. Most of the original studies claimed a single non-coding RNA’s unique role as a treatment or biomarker target. In healthy subjects, tight control of this cluster of non-coding RNAs regulates oxidative stress in adipose tissues, the pancreas, the liver, and vascular and cardiac tissues to the degree that is just enough to ignite immune response to resolve the infection and disease attacks. A proper balance of oxidative stress is needed to retain glucose uptake, insulin signaling, and energy homeostasis. However, this cluster’s dysregulation ignites the development of cardiometabolic diseases. Besides, these non-coding RNAs’ expression profiles in cardiometabolic diseases shared similarities vii

viii

Preface

with other inflammatory diseases like Alzheimer’s disease, asthma, arthritis, and renal failure. Interestingly, we found that tumor cells can regulate this cluster of non-coding RNAs to escape from oxidative stress and anti-tumor immunity and maintain insulin sensitivity by shifting oxidative phosphorylation to glycolysis, facilitating cancer progression. Notably, the depth and breadth of discussion of non-coding RNAs, presenting current mechanistic and clinical evidence, in a broad spectrum of diseases in one book expose researchers studying one disease to new knowledge or new ways of thinking from other fields of research. With this information, they may avoid claiming a novel mechanistic role or diagnostic property in their field, which was established long before in another field. Clinical staff and epidemiologists may test the proposed cluster’s strength in predicting disease progression from early to a late stage in large cohorts and in identifying new therapies using emerging machine learning approaches to predict disease risk. This book emphasizes the need to consider comorbidities, disease stages, and behavioral and therapeutic changes in assessing the clinical value of non-coding RNAs. Polypharmacy interactions should be considered, especially in older people. Leuven, Belgium

Paul Holvoet

Acknowledgments

I thank Karin Sipido, the head of the Experimental Cardiology group at KU Leuven, to support me in this endeavor and keep facilities available at KU Leuven after becoming an emeritus professor. Warm thanks to Tine for helping me get goals clear and keeping me on track. The illustrations within this book significantly differ from these in research papers or even most review papers. In the latter, only small fragments of pathways in which the target non-coding RNAs are active are illustrated. In contrast, in this book, we not only present each pathway with a full list of functionally characterized non-coding RNAs, but we also emphasize the interactions between different pathways involved in disease progression, very often in vicious circles. It was a difficult task to present vast amounts of data in yet eligible figures. For this, collaboration with Pieterjan has been essential. Because he is an artist/architect with no background in biomedicine, I had to educate him step-by-step, enhancing my insight in a very complicated matter. I thank Springer Nature for accepting this book for publication. Immensely, I thank Tanja Weyandt for editorial guidance and Divya Meiyazhagan for production assistance. Most of all I thank Catherine, my long-life partner, for putting up with me and letting me fill in retirement in a rather unexpected way.

ix

Introduction

The Move Towards Cellular Risk Markers According to the World Health Organization, the prevalence of obesity has nearly tripled since 1975. In 2016, more than 1.9 billion adults were overweight. Of these, over 650 million were obese; 340 million children and adolescents aged 5–19 were overweight or obese. This increasing prevalence of obesity has significant healthcare implications, mainly since it is a considerable risk factor for type 2 diabetes and non-alcoholic fatty liver disease [1, 2]. These metabolic diseases individually and interdependently increase the incidence of cardiovascular diseases and cancer [3, 4]. However, personalized risk estimation accounts for inter-individual differences in a complex interplay between high body mass index, high blood pressure, high glucose, high triglycerides, low HDL cholesterol, physical inactivity, and smoking. Even after addressing above mentioned conventional risk factors, some patients still have a high residual risk. In light of these limitations and to improve risk-predicting algorithms, proteins mainly associated with inflammation [5, 6] or oxidative stress [7, 8] were proposed as risk stratifying proteins. However, the inclusion of these protein markers still did not allow efficient individual risk estimation [9, 10]. Therefore, attention shifted from the coding RNA, which translates into the proteins, to noncoding RNA.

Why Non-coding RNA? Protein-coding sequences occupy less than 2% of the genome, and 98% of the genome is transcribed into non-coding RNAs, of which many display regulatory functions [11–13]. They compass small non-coding RNAs or microRNAs or miRs, circular (circ-) RNAs, and long non-coding (lnc)RNAs. MiRs are highly conserved non-coding RNA molecules of around 22 nucleotides that exert post-transcriptional effects on gene expression [14, 15]. Unlike the better known linear RNA, circ-RNAs form a covalently closed continuous loop so that the 3’ and 5’ ends are joined together. xi

xii

Introduction

Although they are considered as non-coding RNAs, many circ-RNAs arise from protein-coding genes [16–20]. LncRNAs are longer than 200 nucleotides, which coincide with the cut-off for many RNA extraction protocols [21–25]. Upon exposure to stress conditions, non-coding RNAs’ expression changes more rapidly than protein transcription factors. A change in their expression levels is reversible in contrast to that of inherited genome mutations [26, 27]. PIWI-interacting RNAs (PiRs) derive from single-stranded RNA, like lncRNAs. Their activity may be more similar in cancer cells and germline and stem cells than in somatic cells in cardiometabolic tissues [28, 29]. The main message is that a single non-coding RNA is not specific for one target but may affect several targets within one or several crucial pathways in one cell type or several cell types within one or several tissues. The same target may also be affected by several non-coding RNAs, which may influence each other’s expression or action. Further, they may be secreted in extracellular vesicles or exosomes, contributing to the communication between several cell types within one tissue or between several tissues. The packing in microvesicles may prevent degradation and facilitate cell-specific delivery, thereby increasing intracellular levels without increasing the production by that cell type [30–40]. The immune response and inflammation are also tightly related to cancer. Therefore, we considered the role of tumor cell-derived microvesicles or oncosomes in cellular transformation, phenotypic reprogramming, and functional re-education of recipient cells [30]. This book now summarizes growing evidence in support of this hypothesis.

Objectives Our first goal was to give insight into the functional role of non-coding RNAs in central pathways contributing to the development of obesity, type 2 diabetes, non-alcoholic fatty liver disease, atherosclerosis, myocardial infarction, cardiomyopathy, and heart failure. We will demonstrate that tight control of a cluster of non-coding RNAs regulates oxidative stress in adipose tissues, the pancreas, the liver, and vascular and cardiac tissues to the degree that is just enough to ignite immune response to resolve the infection and disease attacks. However, this cluster’s dysregulation results in cells’ adverse metabolic programming in adipose tissues, the pancreas, liver, and vascular and cardiac tissues. Our second goal was to investigate the relationship of this cluster with cancer. We will demonstrate that tumor cells can regulate this cluster of non-coding RNAs to escape from oxidative stress and anti-tumor immunity and maintain insulin sensitivity by shifting oxidative phosphorylation to glycolysis, facilitating cancer progression. Overall, we will thus identify a cluster of non-coding RNAs that lay at the intersection between cancer and cardiovascular disease, contributing to the emerging field of cardio-oncology [41– 49]. Ultimately, this cluster of non-coding RNAs may be prospectively analyzed in extensive cohort studies to determine their value in risk-predicting algorithms.

Introduction

xiii

Approach In preparing this book, the authors followed current guidance on producing highquality systematic reviews and meta-analyses of diagnostic test accuracy by both the Cochrane Collaboration [50] and the QUADUAS Group [51], as we have done before [52]. When studies that lack methodological rigor or have a high risk of bias are combined in a meta-analysis, the uninformative or erroneous results can waste further resources on future research or even lead to a wrong diagnosis. In following these standards, we aimed at providing quality evidence for the rational choice of non-coding RNAs to focus on in future research, identifying the non-coding RNAs with high potential for clinical applicability. This rational choice was further supported by bold data strongly suggesting that non-coding RNAs take part in the pathogenesis of a single or a multitude of diseases. Thereby, the author’s expertise as an active scientist, reviewer, and editor of scientific journals was instrumental. He engaged in not withholding any information that could favor one or another non-coding RNA as a sensitive and specific disease marker or target for intervention. Given the massive amount of data available, the reference list of published papers is not exhaustive. However, the reader will find a fair review of all non-coding RNA functions concerning all target diseases. The original paper supporting a particular function was mostly selected, except when later articles gave a more detailed mechanistic insight. Also, the quality of the papers was considered. Performing this kind of retrospective meta-analysis allows us to propose a selected cluster of non-coding RNAs that clinicians and epidemiologists may include in their future large cohort studies. Machine-learning is needed to include extensive data in disease-predicting algorithms or algorithms that help improve treatment [53–55]. Notably, the dynamics of expression according to the disease stage, fluctuating risk factor profile, and changes in therapies have to be considered [52]. For example, fluctuation in non-coding RNAs with variation in body mass index may be substantial because this fluctuation rather than baseline body mass index is related to coronary atherosclerosis [56]. Therefore, we wanted to include available information about disease stage-specific expression of non-coding RNAs. This information is, however, very scarce. Disruptive in kind, this is not a traditional scientific paper written for academic peer review and Journal selection, but a generous invitation to experts across industries and specializations to solve a significant global challenge.

Take Home Message • Around 98% of all transcriptional output in humans is non-coding RNA. Although genome-wide analysis has identified thousands of non-coding RNAs, only a shortlist of non-coding RNAs have been adequately functionally characterized.

xiv

Introduction

• Every non-coding RNA has several functions, and several non-coding RNAs share the same function. • We did not find any single non-coding RNA with a unique role in developing metabolic and cardiovascular diseases or cancer. Importantly, we have identified a cluster of non-coding RNAs at the cross-road between metabolic and cardiovascular diseases and cancer (Fig. 1). • Differences in non-coding RNA profiles between cardiometabolic tissues and tumors are often related to energy homeostasis, insulin signaling, mitochondrial dysfunction, oxidative and endoplasmic reticulum stress, and macrophage polarization and inflammation. All together, they are responsible for differences in metabolic programming of cardiometabolic tissues and tumors.

Fig. 1 Cluster of non-coding RNAs of which the imbalance is related to cardiometabolic diseases and cancer development. Within the pink circle, we show a cluster of non-coding RNAs common in the progression of cardiometabolic diseases, which are also related to cancer. The non-coding RNAs within the blue circle, up-regulated explicitly in tumors, may be responsible for the different relationship miRs with cardiometabolic diseases and cancer, allowing a specific reprogramming of tumor cells directed to survival. The small dots represent microvesicles in which miRs are actively and specifically loaded, which play a critical role in the communication between tumor-adjacent tissue, inflammatory cells, and tumor

Introduction

xv

• PiR’s activities may be more similar in cancer cells and germline and stem cells than in somatic cells in cardiometabolic tissues. • A cell type’s behavior depends on non-coding RNAs expressed by this cell and non-coding RNAs enriched in microvesicles secreted by other cells, even in other tissues. Tumors secrete microvesicles containing non-coding RNAs, which induce healthy cells to convert to glycolysis. Inflammatory cells secrete microvesicles containing non-coding RNAs, which induce proliferation and migration of cancer cells. Finally, cancer cells may selectively shuttle anti-oncogenic noncoding RNAs to microvesicles and remove them to preserve proliferation and metastasis. • Overall, we present a list of non-coding RNAs, which are candidates for inclusion in machine learning approaches, considering changes in their expression profiles according to disease stage and behavioral and therapeutic changes. Considering all data, we present a model explaining why miR-155 is the main target for preventing cardiometabolic diseases and cancer.

References 1. 2. 3. 4.

5.

6.

7.

8.

9.

10.

Tilg, H., Moschen, A. R. & Roden, M. (2017). NAFLD and diabetes mellitus. Nature Reviews Gastroenterology & Hepatology, 14, 32–42, doi:10.1038/nrgastro.2016.147. Schetz, M. et al. (2019). Obesity in the critically ill: a narrative review. Intensive Care Medicine, 45, 757–769, doi:10.1007/s00134-019-05594-1. Dechamethakun, S. & Muramatsu, M. (2017). Long noncoding RNA variations in cardiometabolic diseases. Journal of Human Genetics, 62, 97–104, doi:10.1038/jhg.2016.70. Stefan, N., Haring, H. U., Hu, F. B. & Schulze, M. B. (2016). Divergent associations of height with cardiometabolic disease and cancer: epidemiology, pathophysiology, and global implications. Lancet Diabetes Endocrinology, 4, 457–467, doi:10.1016/S2213-8587(15)00474-X. Ridker, P. M., MacFadyen, J., Libby, P. & Glynn, R. J. (2010). Relation of baseline high-sensitivity C-reactive protein level to cardiovascular outcomes with rosuvastatin in the Justification for Use of statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER). The American Journal of Cardiology, 106, 204–209, doi:10.1016/j.amjcard.2010.03.018. Hirata, Y. et al. (2011). Coronary atherosclerosis is associated with macrophage polarization in epicardial adipose tissue. Journal of the American College of Cardiology, 58, 248–255, doi:S0735-1097(11)01549-X [pii];10.1016/j.jacc.2011.01.048 [doi]. Geeraert, B. et al. (2010). Stevioside inhibits atherosclerosis by improving insulin signaling and antioxidant defense in obese insulin-resistant mice. International Journal of Obesity, 34, 569–577. Hulsmans, M. & Holvoet, P. (2010). The vicious circle between oxidative stress and inflammation in atherosclerosis. Journal of Cellular and Molecular Medicine, 14, 70–78, doi:10.1111/j.1582-4934.2009.00978.x. Graversen, P., Abildstrom, S. Z., Jespersen, L., Borglykke, A. & Prescott, E. (2016). Cardiovascular risk prediction: Can Systematic Coronary Risk Evaluation (SCORE) be improved by adding simple risk markers? Results from the Copenhagen City Heart Study. European Journal of Preventive Cardiology, 23, 1546–1556, doi:10.1177/2047487316638201. Swerdlow, A. J. et al. (2018). The National Cancer Institute Cohort Consortium: An International Pooling Collaboration of 58 Cohorts from 20 Countries. Cancer Epidemiology, Biomarkers & Prevention, 27, 1307–1319, doi:10.1158/1055-9965.EPI-18-0182.

xvi

Introduction

11.

Consortium, E. P. (2012). An integrated encyclopedia of DNA elements in the human genome. Nature, 489, 57–74, doi:10.1038/nature11247. Clark, M. B., Choudhary, A., Smith, M. A., Taft, R. J. & Mattick, J. S. (2013). The dark matter rises: the expanding world of regulatory RNAs. Essays Biochemistry, 54, 1–16, doi:10.1042/bse0540001. Derrien, T. et al. (2012). The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression. Genome Research, 22, 1775– 1789, doi:10.1101/gr.132159.111. Djuranovic, S., Nahvi, A. & Green, R. (2011). A parsimonious model for gene regulation by miRNAs. Science, 331, 550–553, doi:10.1126/science.1191138. Bartel, D. P. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell, 116, 281–297. Salzman, J., Gawad, C., Wang, P. L., Lacayo, N. & Brown, P. O. (2012). Circular RNAs are the predominant transcript isoform from hundreds of human genes in diverse cell types. PLoS One, 7, e30733, doi:10.1371/journal.pone.0030733. Jeck, W. R. et al. (2013). Circular RNAs are abundant, conserved, and associated with ALU repeats. RNA, 19, 141–157, doi:10.1261/rna.035667.112. Zhang, X. O. et al. (2014). Complementary sequence-mediated exon circularization. Cell, 159, 134–147, doi:10.1016/j.cell.2014.09.001. Memczak, S. et al. (2013). Circular RNAs are a large class of animal RNAs with regulatory potency. Nature, 495, 333–338, doi:10.1038/nature11928. Abe, N. et al. (2015). Rolling Circle Translation of Circular RNA in Living Human Cells. Scientific Reports, 5, 16435, doi:10.1038/srep16435. Rinn, J. L. & Chang, H. Y. (2012). Genome regulation by long noncoding RNAs. Annual Review of Biochemistry, 81, 145–166, doi:10.1146/annurev-biochem-051410-092902. Cech, T. R. & Steitz, J. A. (2014). The noncoding RNA revolution-trashing old rules to forge new ones. Cell, 157, 77–94, doi:10.1016/j.cell.2014.03.008. Kowalczyk, M. S., Higgs, D. R. & Gingeras, T. R. (2012). Molecular biology: RNA discrimination. Nature, 482, 310–311, doi:10.1038/482310a. Zuckerkandl, E. (1981). A general function of noncoding polynucleotide sequences. Mass binding of transconformational proteins. Molecular Biology Reports, 7, 149–158. Knoll, M., Lodish, H. F. & Sun, L. (2015). Long non-coding RNAs as regulators of the endocrine system. Nature Reviews Endocrinology, 11, 151–160, doi:10.1038/nrendo.2014.229. Holvoet, P. (2012). Stress in obesity and associated metabolic and cardiovascular disorders. Scientifica (Cairo), 2012, 205027, doi:10.6064/2012/205027. Costantino, S. et al. (2018). Epigenetics and precision medicine in cardiovascular patients: from basic concepts to the clinical arena. European Heart Journal, 39, 4150–4158, doi:10.1093/eurheartj/ehx568. Aravin, A. et al. (2006). A novel class of small RNAs bind to MILI protein in mouse testes. Nature, 442, 203–207, doi:10.1038/nature04916. Girard, A., Sachidanandam, R., Hannon, G. J. & Carmell, M. A. (2006). A germlinespecific class of small RNAs binds mammalian Piwi proteins. Nature, 442, 199–202, doi:10.1038/nature04917. Hulsmans, M. & Holvoet, P. (2013). MicroRNA-containing microvesicles regulating inflammation in association with atherosclerotic disease. Cardiovascular Research, 100, 7–18, doi:10.1093/cvr/cvt161. Huber, H. J. & Holvoet, P. (2015). Exosomes: emerging roles in communication between blood cells and vascular tissues during atherosclerosis. Current Opinion in Lipidology, 26, 412–419, doi:10.1097/MOL.0000000000000214. Vanhaverbeke, M., Gal, D. & Holvoet, P. (2017). Functional Role of Cardiovascular Exosomes in Myocardial Injury and Atherosclerosis. Advances in Experimental Medicine and Biology, 998, 45–58, doi:10.1007/978-981-10-4397-0_3.

12.

13.

14. 15. 16.

17. 18. 19. 20. 21. 22. 23. 24. 25.

26. 27.

28. 29.

30.

31.

32.

Introduction 33. 34.

35.

36.

37. 38.

39.

40.

41.

42. 43.

44. 45.

46.

47. 48. 49.

50.

51.

52.

xvii

Bei, Y. et al. (2017). Extracellular Vesicles in Cardiovascular Theranostics. Theranostics, 7, 4168–4182, doi:10.7150/thno.21274. Chen, X. et al. (2008). Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Research, 18, 997–1006, doi:10.1038/cr.2008.282. Lawrie, C. H. et al. (2008). Detection of elevated levels of tumour-associated microRNAs in serum of patients with diffuse large B-cell lymphoma. British Journal of Haematology, 141, 672–675, doi:10.1111/j.1365-2141.2008.07077.x. Mitchell, P. S. et al. (2008). Circulating microRNAs as stable blood-based markers for cancer detection. Proceedings of the National Academy of Sciences of the United States of America, 105, 10513–10518, doi:10.1073/pnas.0804549105. Small, E. M. & Olson, E. N. (2011). Pervasive roles of microRNAs in cardiovascular biology. Nature, 469, 336–342, doi:10.1038/nature09783. Vickers, K. C., Palmisano, B. T., Shoucri, B. M., Shamburek, R. D. & Remaley, A. T. (2011). MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nature Cell Biology, 13, 423–433, doi:10.1038/ncb2210. Nishimura, Y. et al. (2013). Targeting cancer cell-specific RNA interference by siRNA delivery using a complex carrier of affibody-displaying bio-nanocapsules and liposomes. Journal of Nanobiotechnology, 11, 19, doi:10.1186/1477-3155-11-19. Nazarenko, I., Rupp, A. K. & Altevogt, P. (2013). Exosomes as a potential tool for a specific delivery of functional molecules. Methods in Molecular Biology, 1049, 495–511, doi:10.1007/978-1-62703-547-7_37. Zarzour, A., Kim, H. W. & Weintraub, N. L. (2019). Epigenetic Regulation of Vascular Diseases. Arteriosclerosis, Thrombosis, and Vascular Biology, 39, 984–990, doi:10.1161/ATVBAHA.119.312193. Anker, M. S., von Haehling, S. & Anker, S. D. (2019). Novel biomarkers in heart failure and cardio-oncology. Kardiologia Polska, 77, 329–330, doi:10.5603/KP.2019.0051. Ameri, P. et al. (2018). Cancer diagnosis in patients with heart failure: epidemiology, clinical implications and gaps in knowledge. European Journal of Heart Failure, 20, 879–887, doi:10.1002/ejhf.1165. Argolo, D. F., Hudis, C. A. & Iyengar, N. M. (2018). The Impact of Obesity on Breast Cancer. Current Oncology Reports, 20, 47, doi:10.1007/s11912-018-0688-8. Mehta, L. S. et al. (2018). Cardiovascular Disease and Breast Cancer: Where These Entities Intersect: A Scientific Statement From the American Heart Association. Circulation, 137, e30–e66, doi:10.1161/CIR.0000000000000556. Kitson, S. et al. (2018). Interventions for weight reduction in obesity to improve survival in women with endometrial cancer. Cochrane Database of Systematic Reviews, 2, CD012513, doi:10.1002/14651858.CD012513.pub2. Leonardi, G. C., Accardi, G., Monastero, R., Nicoletti, F. & Libra, M. (2018). Ageing: from inflammation to cancer. Immunity & Ageing, 15, 1, doi:10.1186/s12979-017-0112-5. Mastropasqua, F., Girolimetti, G. & Shoshan, M. (2018). PGC1alpha: Friend or Foe in Cancer? Genes (Basel), 9, doi:10.3390/genes9010048. Xuan, Y. et al. (2019). Association of Serum Markers of Oxidative Stress With Incident Major Cardiovascular Events, Cancer Incidence and All-Cause Mortality in Type 2 Diabetes Patients: Pooled Results From Two Cohort Studies. Diabetes Care, doi:10.2337/dc19-0292. Cumpston, M. et al. (2019). Updated guidance for trusted systematic reviews: a new edition of the Cochrane Handbook for Systematic Reviews of Interventions. Cochrane Database of Systematic Reviews, 10, ED000142, doi:10.1002/14651858.ED000142. Whiting, P. F. et al. (2011). QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Annals of Internal Medicine, 155, 529–536, doi:10.7326/0003-4819-1558-201110180-00009. Navickas, R. et al. (2016). Identifying circulating microRNAs as biomarkers of cardiovascular disease: a systematic review. Cardiovascular Research, 111, 322–337, doi:10.1093/cvr/cvw174.

xviii 53.

54.

55. 56.

Introduction Goldstein, B. A., Navar, A. M. & Carter, R. E. (2017). Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges. European Heart Journal, 38, 1805–1814, doi:10.1093/eurheartj/ehw302. Weng, S. F., Reps, J., Kai, J., Garibaldi, J. M. & Qureshi, N. (2017). Can machine-learning improve cardiovascular risk prediction using routine clinical data? PLoS One, 12, e0174944, doi:10.1371/journal.pone.0174944. Delgado-Rodriguez, M. & Sillero-Arenas, M. (2018). Systematic review and meta-analysis. Medicina Intensiva, 42, 444–453, doi:10.1016/j.medin.2017.10.003. Lee, D. H.et al. (2010). Differential associations of weight dynamics with coronary artery calcium versus common carotid artery intima-media thickness: The CARDIA Study. American Journal of Epidemiology, 172, 180–189, doi:10.1093/aje/kwq093.

Contents

1

2

Biogenesis and Modes of Action of miRs and Circular and Long Non-coding RNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 MiRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 Biogenesis of miRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.2 MiR Modes of Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.3 Naming of miRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.4 Useful Resources on miRs . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Circular RNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Biogenesis of Circular RNAs . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2 Circular RNAs Modes of Action . . . . . . . . . . . . . . . . . . . . . 1.2.3 Useful Resources on Circ-RNAs . . . . . . . . . . . . . . . . . . . . . 1.3 lncRNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.1 Biogenesis of lncRNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.2 Modes of Action of lncRNAs . . . . . . . . . . . . . . . . . . . . . . . . 1.4 piRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.1 Biogenesis of piRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.2 Modes of Action of piRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.3 Useful Resources on piRs . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Non-coding RNAs Related to Obesity . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Mechanisms in White Adipogenesis . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 Role of Non-coding RNAs in White Adipogenesis . . . . . . 2.2 Inflammation and Insulin Resistance in Obese White Adipose Tissue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Role of Non-coding RNAs in Inflammation and Insulin Resistance in Obese White Adipose Tissue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Mechanisms in Brown Adipogenesis and Thermogenesis . . . . . . . 2.3.1 Role of Non-coding RNAs in Brown Adipogenesis and Thermogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Mechanisms in Browning of White Adipose Tissues . . . . . . . . . . .

1 1 1 3 3 4 4 4 4 7 7 7 8 11 11 11 13 13 21 21 24 25

29 30 32 33 xix

xx

Contents

2.4.1 Role of Non-coding RNAs in Browning of White Adipose Tissue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Leptin and Insulin in the Hypothalamus . . . . . . . . . . . . . . . . . . . . . 2.5.1 Non-coding RNAs Related to Leptin and Insulin in the Hypothalamus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

4

Non-coding RNAS Related to Type 2 Diabetes . . . . . . . . . . . . . . . . . . . 3.1 Mechanisms in β Cell Maturation . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1 Non-coding RNAs Related to β Cell Maturation . . . . . . . . 3.2 Mechanisms in Insulin Signaling in the Pancreas . . . . . . . . . . . . . . 3.2.1 Non-coding RNAs in Insulin Signaling in Type 2 Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Inflammation in the Pancreas, Insulin Resistance, and Type 2 Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Non-coding RNAs Related to Inflammation in the Pancreas, with Insulin Resistance and Type 2 Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Non-coding RNAs Related to Lipid Metabolism and Non-alcoholic Fatty Liver Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Cholesterol and Lipids in the Liver . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1 Non-coding RNAs and Cholesterol in the Liver . . . . . . . . 4.2 Fatty Acids and Triglycerides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Non-coding RNAs and Fatty Acids and Triglycerides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Non-alcoholic Fatty Liver Disease . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Non-coding RNAs Related to Non-alcoholic Fatty Liver Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

34 35 36 36 53 53 55 56 59 60

61 62 73 73 75 76 77 77 79 81

5

Non-coding RNAs Related to Atherosclerosis . . . . . . . . . . . . . . . . . . . . 89 5.1 Endothelial Injury, Inflammation, and Apoptosis . . . . . . . . . . . . . . 89 5.1.1 Non-coding RNAs in Endothelial Injury, Inflammation, and Apoptosis . . . . . . . . . . . . . . . . . . . . . . . . 94 5.2 Fibroproliferative Remodeling and Plaque Destabilization . . . . . . 98 5.2.1 Non-coding RNAs in Fibroproliferative Remodeling and Plaque Destabilization . . . . . . . . . . . . . . . 101 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

6

Non-coding RNAs in Cardiomyopathy and Heart Failure . . . . . . . . . 6.1 Mechanisms in Cardiomyopathy and Heart Failure . . . . . . . . . . . . 6.2 Non-coding RNAs in Cardiomyopathy and Heart Failure . . . . . . . 6.2.1 Non-coding RNAs in Cardiac Hypertrophy . . . . . . . . . . . . 6.2.2 Non-coding RNAs in Cardiac Fibrosis and ECM Deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

119 119 123 123 124

Contents

6.2.3 Non-coding RNAs in Cardiac Inflammation . . . . . . . . . . . 6.2.4 Non-coding RNAs in Cardiac Angiogenesis . . . . . . . . . . . 6.2.5 Non-coding RNAs in Cardiac Apoptosis . . . . . . . . . . . . . . 6.3 Metabolic Syndrome: The Link Between Metabolic and Cardiovascular Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 Definition of Metabolic Syndrome . . . . . . . . . . . . . . . . . . . 6.3.2 Oxidative Stress and Metabolic Syndrome . . . . . . . . . . . . . 6.3.3 Metabolic Syndrome and Cardiovascular Risk . . . . . . . . . 6.3.4 Non-coding RNAs and Metabolic Syndrome Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

8

Non-coding RNAs Related to Cardiometabolic Diseases and Associated to Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Mechanisms of Cancer Progression . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.1 Induction of Stemness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.2 Induction of EMT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.3 Induction of Insulin Sensitized State, Cancer Cell Proliferation, and Protection Against Apoptosis . . . . . . . . 7.1.4 Induction of Glycolysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.5 Induction of Angiogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.6 Repression of Anti-tumor Immunity and Apoptosis . . . . . 7.1.7 Cancer Cell Proliferation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.8 EGFR Signaling and Cancer Progression . . . . . . . . . . . . . . 7.1.9 BMI1 and EZH2 in Cancer Progression . . . . . . . . . . . . . . . 7.2 Non-coding RNAs Related to Metabolic and Cardiovascular Diseases Are also Involved in Cancer Progression . . . . . . . . . . . . . 7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic Diseases and Cancer . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Regulation of miRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.1 Hypoxia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.2 Glucose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.3 Oxidative Stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.4 Inflammation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.5 TGF-β . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.6 MYC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.7 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Differences in miR-Profiles in Cardiometabolic Tissues and Tumors May be Due to the Typical Action of lncRNAs and circ-RNAs in Tumors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Action of piRs Particularly in Tumors . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xxi

126 126 127 128 128 129 129 130 131 149 149 149 153 155 156 157 158 162 164 166 167 167 187 213 213 215 216 219 219 220 221 221

223 224 226

xxii

9

Contents

Communication Between Tumor-Adjacent Tissues and Tumors with Emphasis on Role of Inflammatory Cells . . . . . . . . 9.1 Exchange of miR-Enriched Microvesicles . . . . . . . . . . . . . . . . . . . . 9.2 MiR-155 as a Link Between M1 Macrophage-Mediated Inflammation in Tumor-Adjacent Tissue and Tumor Growth and Metastasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

10 The Impact of Non-coding RNA Networks on Disease Comorbidity: Cardiometabolic Diseases, Inflammatory Diseases, and Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.1 Identification of Non-coding RNAs at Cross-Road of Metabolic and Cardiovascular Diseases . . . . . . . . . . . . . . . . . . . 10.2 Many Non-coding RNAs at Cross-Road of Metabolic and Cardiovascular Diseases are also Related to Inflammatory Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3 Differences Between Non-coding RNAs in Cardiometabolic Tissues and Tumors . . . . . . . . . . . . . . . . . . . . . 10.4 Expected Technical Developments Underlying the Use of Non-coding RNAs as Biomarkers . . . . . . . . . . . . . . . . . . . . . . . . 10.5 The Need for Measuring Fluctuation of Non-coding RNAs . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

241 241

242 244

247 247

248 253 254 255 256

Abbreviations

4EBP2 ABC ACAT ACE2 ACSL1 AD ADAM ADINR ADIPOQ ADIPOR AFAP1-AS1 AGE AI AKT AMPK ANG II ANRIL AOX APO ARF3 AS160 or TBC1D4 ASC AT1R or AGTR1 ATP B4GALT1-AS1 BABAM2-AS1 or BRE-AS1

Eukaryotic translation initiation factor 4E binding protein ATP-binding cassette Acetyl-CoA C-acetyltransferase Angiotensin I converting enzyme 2 Acyl-CoA synthetase 1 Alzheimer’s disease ADAM metallopeptidase domain Adipogenic differentiation induced non-coding RNA Adiponectin Adiponectin receptor Actin filament associated protein 1 antisense RNA Advanced glycation end product Artificial intelligence AKT serine/threonine kinase AMP-Activated catalytic Angiotensinogen Cyclin-dependent kinase inhibitor 2B antisense RNA 1 Fatty acyl-CoA oxidase Apolipoprotein ADP-ribosylation factor 3 TBC1 domain family, member 4 Adipocyte stem cell Angiotensin II receptor type 1 Adenosine triphosphate Suppressor of hepatic gluconeogenesis and lipogenesis (lncSHGL in mice) BRISC and BRCA1 A complex member 2 antisense RNA 1 xxiii

xxiv

BACE1 BAK BANF or BAF BAT BAX BCL2 BCL2L11 or BIM bFGF BLACAT1 BMI1 BMP BRCA1 CASC11 CCL2 or MCP-1 CCN CCR2 or MCP-1 receptor CD206 or MRC1 CDK CDKN1A or P21 CDKN2B CDKN2B-AS1 CETP CHRF circ-ANAPC7 circ-CDR1as or ciRs-7 circCHFR circ-FOXM1 circ-HIPK3 circ-ITCH circ-MTO1 circ-RNA circ-WDR77 circ-ZNF609 CM COL COX1 or MTCOI CPE CREB

Abbreviations

Beta-site amyloid precursor protein cleaving enzyme 1 BCL2 antagonist/killer Barrier to autointegration factor 1 Brown adipose tissue Pro-apoptotic BCL2 associated X, apoptosis regulator BCL2 apoptosis regulator BCL2 like 11 Basic fibroblast growth factor Bladder cancer-associated transcript one BMI proto-oncogene, polycombing ring finger 1 Bone morphogenetic protein BRCA1 DNA repair associated protein 1 Cancer susceptibility 11 lncRNA C-C motif chemokine ligand 2 Cyclin C-C motif chemokine receptor 2 Mannose receptor Cyclin-dependent kinase Cyclin dependent kinase inhibitor 1A Cyclin-dependent kinase inhibitor 2B CDKN2B antisense RNA 1 Cholesteryl ester transfer protein Cardiac hypertrophy related factor Anaphase-promoting complex subunit 7 circ-RNA Circular cerebellar degeneration related protein 1 (CDR1) antisense RNA Checkpoint with forkhead and ring finger domains circ-RNA Forkhead box M1 circ-RNA Homeodomain interacting protein kinase three circ-RNA Itchy E3 ubiquitin-protein ligase circ-RNA Mitochondrial tRNA translation optimization one circ-RNA Circular RNA WD repeat domain 77 circ-RNA Zinc finger protein 609 circ-RNA Cardiomyocyte Collagen Cytochrome oxidase 1 Carboxypeptidase cAMP-responsive element-binding

Abbreviations

cSMARCA4

CXCL CXCR DAMP DKK2 DLK1 E2F1 EBF EC ECM EDN EGF EID EIF ELK EMT EPC ER ERK ERRα EZH2 FA FABP4 or aP2 FAT or CD36 FB FBXW7 FEZF1 FEZF1-AS1 FGD5-AS1 FGF FOXO G6PD GAS5 GH GLP GLUT GSK3β H19 HGF

xxv

SWI/SNF related, matrix associated, actin-dependent regulator of chromatin, subfamily a, member 4 C-X-C motif chemokine ligand C-X-C motif chemokine receptor; dendritic cell Danger-associated molecular pattern Dickkopf associated protein 2 Delta-like non-canonical NOTCH ligand E2F transcription factor 1 Early B cell factor Endothelial cell Extracellular matrix Endothelin-1 Epidermal growth factor EP300 interacting inhibitor of differentiation Eukaryotic translation initiation factor ETS transcription factor Epithelial-mesenchymal transition Endothelial progenitor cells Endoplasmic reticulum Extracellular signal-regulated kinase Estrogen related receptor alpha Enhancer of the zeste two polycomb repressive complex two subunit Fatty acids Fatty acid-binding protein four FA translocase Fibroblast F-box and WD repeat domain containing 7 Fasciculation and elongation protein zeta 1 FEZF1 antisense RNA 1 FYVE, RhoGEF and PH domain containing 5 antisense RNA 1 Fibroblast growth factor Forkhead box O3 Glucose-6-phosphate-dehydrogenase Growth arrest-specific 5 Growth hormone Glucagon-like peptide Solute carrier family or facilitated glucose transporter Glycogen synthase kinase three beta H19 imprinted maternally expressed transcript lncRNA Hepatocyte growth factor

xxvi

HIF HIPK HK2 HMGA, Formerly HMG-I/Y HMGB1 HMGCR HNF or MODY HNF1A-AS1 HOTAIR HOX HOXC-AS1 HSF HULC ICAM IDOL or MYLIP IFN Ig IGF IGFR IL ILC2 IR IRAK3 or IRAK-M IRF IRS ITCH ITG JAK KCNQ1OT1 KLF KRAS LCAT LDLR LIN28 LINC00341 lincRNA-p21 LINC-ROR lncARSR lnc-HC lncRNA

Abbreviations

Hypoxia-induced hypoxia-inducible factor Homeodomain interacting protein kinase Hexokinase two High mobility group AT-hook1 High-mobility group B1 Hydroxy-3-methylglutaryl coenzyme A reductase HNF homeobox HNF1 homeobox A antisense RNA 1 Homeobox transcript antisense lncRNA Homeobox HOXC cluster antisense RNA 1 Heat shock transcription factor Hepatocellular carcinoma up-regulated long non-coding RNA Intercellular adhesion molecule 1 Ubiquitin ligase inducible degrader of LDLR Interferon Immunoglobulin Insulin-like growth factor Insulin-like growth factor receptor Interleukin Innate lymphoid type 2 cells Insulin receptor Interleukin-1 receptor-associated kinase-3 Interferon regulatory factor Insulin substrate receptor Itchy E3 ubiquitin protein ligase Integrin Janus kinase Potassium voltage-gated channel subfamily Q member 1 opposite strand/antisense transcript 1 Krüppel-like zinc finger transcription factor KRAS proto-oncogene, GTPase Lecithin-cholesterol acyltransferase Low-density lipoprotein receptor Lin-28 homolog Spectrin-repeat containing nuclear envelope family member 3 Tumor protein p53 pathway corepressor 1 Long intergenic non-protein coding RNA regulator of reprogramming Regulator of Akt signaling associated with HCC and RCC lncRNA lncRNA derived from hepatocytes Long non-coding RNA

Abbreviations

lncRNA-ATB LncRNA-ES1 LOX-1 LXR MACC1-AS1 MAFA MALAT1 MAPK MCL1 MDSC MEG3 MetS MHC MIAT MIF miR MIR155HG MIR31HG MIRT1 MMP MPO MRPL39 MSC mTOR MYC MYF NAFLD NALP3 NANOG NEAT1 NFκB NIFK NIFK-AS1 NK NKX NLRP3 NOD2 NORAD NOS NOX NQO1

xxvii

Long non-coding RNA activated by TGF-β Long intergenic non-protein coding RNA 1108 Lectin-like oxidized low-density lipoprotein receptor-1 Liver X receptor MET transcriptional regulator MACC1 antisense Maf transcription factor Metastasis-associated lung adenocarcinoma transcript one Mitogen-activated protein kinase MCL1 apoptosis regulator, BCL2 family member M2 myeloid suppressor cell Maternally expressed 3 lncRNA Metabolic syndrome Major histocompatibility complex Myocardial infarction associated transcript Migration inhibitory factor MicroRNA MIR155 host gene MIR31 host gene Myocardial infarction associated with transcript 1 Metalloproteinases Myeloperoxidase Mitochondrial ribosomal protein L19 Mesenchymal cell Mammalian (or mechanistic) target of rapamycin MYC oncogene Myogenic factor Non-alcoholic fatty liver disease NACHT, LRR, and PYD domains containing protein Nanog homeobox Nuclear paraspeckle assembly transcript Nuclear factor kappa B Nucleolar protein interacting with the FHA domain of MKI67 NIFK antisense RNA 1 Natural killer NK6 homeobox NLR family pyrin domain containing 3 Nucleotide-binding oligomerization domain 2 Non-coding RNA activated by DNA damage Nitric oxide synthase NADPH oxidase NAD (P) H quinone dehydrogenase 1

xxviii

NRF OA ObR OCT4 OIP5-AS1 ox-LDL OXPHOS p70S6K or RPS6KB1 PCNA PCSK9 PD1 PDCD PDGF PDK PD-L1 PDX1 PFKFB3

PGC-1α PI3K PiR PIWIL PlGF PLUTO PNLDC1 POMC PPAR PRC2 PRDM PRL PTEN PVT1 RA RAAS Rab-GAP RALY RASSF1 RBP RF RISC ROS RUNX

Abbreviations

Necrosis related factor Osteoarthritis Leptin receptor POU class 5 homeobox one or POU5F1 Opa interacting protein 5 (OIP5) antisense RNA 1 Oxidized LDL Oxidative phosphorylation Ribosomal protein S6 kinase Proliferating cell nuclear antigen Proprotein convertase subtilisin/kexin type 9 Programmed cell death-1 Programmed cell death Platelet-derived growth factor Pyruvate dehydrogenase kinase Programmed death-ligand 1 Pancreatic and duodenal homeobox 1 6-phosphofructo-2-kinase/fructose-2,6biphosphatase 3 PPAR-γ co-activator 1α Phosphatidylinositol 3-kinase Piwi like RNA-mediated gene silencing PIWI-interacting RNA Placental growth factor PDX1 associated lncRNA, up-regulator of transcription PARN like, ribonuclease domain containing 1 Pro-opiomelanocortin Peroxisome proliferator-activated receptor Polycomb repressive complex 2 PR/SET domain Prolactin Phosphatase and tensin homolog PVT oncogene 1 Rheumatoid arthritis Renin-angiotensin-aldosterone system Rab-GTPase activating protein RALY heterogeneous nuclear ribonucleoprotein Ras association domain family member 1 RNA binding protein Regulatory factor Ribonucleoprotein RNA-induced silencing complex Reactive oxygen species RUNX family transcription factor

Abbreviations

SELENOW or SEPW1 SIRT SMARCA4 or BRG1

SMC SMMHC SNAI2 or SLUG SNAIL or SNAI1 SNHG SOCS3 SOD SOX SOX21-AS1 SPROUTY4 or SPRY4 SR-A SRA SR-B1 or SCARB1 SRC SREBF1 or SREBP1 STAT TAM TBX21 or TBET TDG TET TF TG TGF TIMP TINCR TLR TMEM26 TNF TRAF TRAIL TRIF or TICAM1 TUG1 TWIST UCA1 UCP UPR VCAM VEGF VSMC

xxix

Selenoprotein W pseudogene 1 Sirtuin SWI/SNF related, matrix associated, actin-dependent regulator of chromatin, subfamily a, member 4 Smooth muscle cell Smooth muscle myosin heavy chain Snail family transcriptional repressor 2 Snail family transcriptional repressor 1 Small nucleolar RNA host gene Suppressor of cytokine signaling 3 Superoxide dismutase SRY-box transcription factor SOX-21 antisense divergent transcript 1 Sprouty four Scavenger receptor A Steroid receptor RNA activator Scavenger receptor BI SRC proto-oncogene, non-receptor tyrosine kinase Sterol regulatory element-binding transcription factor 1 Signal transducer and activator of transcription Tumor-associated macrophage T-box transcription factor 21 Thymine DNA glycosylase Ten-eleven translocation Tissue factor Triglycerides Transforming growth factor TIMP metallopeptidase inhibitor TINCR ubiquitin domain-containing Toll-like receptor Transmembrane protein 26 Tumor necrosis factor TNF receptor associated factor TNF-related apoptosis-inducing ligand Toll-like receptor adaptor molecule 1 Taurine up-regulated 1 Twist family bHLH transcription factor Urothelial cancer-associated 1 Uncoupling proteinUCP Unfolded protein response Vascular cell adhesion molecule Vascular endothelial growth factor Vascular smooth muscle cell

xxx

WAT WISPER XIST ZEB ZEB1-AS1 ZFAS1 ZFR

Abbreviations

White adipose tissue WNT1 inducible signaling pathway protein 2 (WISP2) super-enhancer-associated RNA X inactive specific transcript zinc finger E-box binding homeobox zinc finger E-box-binding homeobox two antisense RNA 1 ZNFX1 antisense RNA 1 Zinc finger RNA binding protein

Chapter 1

Biogenesis and Modes of Action of miRs and Circular and Long Non-coding RNAs

Abstract Short non-coding miRs induce mRNA degradation or repress mRNA translation leading to less protein. Several long and circular non-coding RNAs target the same miR that targets several RNAs. Most circular RNAs silence different miRs; others may stimulate transcription or inhibit translation. Long non-coding RNAs act as signals not requiring mRNA translation; their action is like transcription factors. Alternatively, they act as decoys of miRs and proteins, or guide proteins to their target genes or act as scaffolds bringing proteins together. Their expression with temporal changes is most sensitive to pathophysiological stimuli. The short halflife of miRs and lncRNAs is like that of regulatory messenger RNAs. However, the packing of miRs in microvesicles avoids degradation and prolongs their half-life. PiRs are Dicer-independent, PIWI protein-associated small silencing RNAs derived from single-stranded, coding or non-coding RNA. They guide PIWI proteins to target sequences in the genome by sequence complementarity, where PIWI proteins silence transcription.

1.1 MiRs 1.1.1 Biogenesis of miRs MiRs are endogenous, non-coding, and small (18–22 nucleotides) RNA molecules produced by all cell types. Seventy percent of miRs locate in introns or exons, and approximately 30% in intergenic regions [1] (Fig. 1.1). Intronic and exonic miRs are part of annotated genes. They need to be spliced from the host by the spliceosome and a branching enzyme. Intergenic miRs are transcribed from intergenic regions or gene deserts; they form independent transcription units [2–4]. Tightly linked miRs are transcribed as polycistronic messengers. However, miR genes separated by more than 50 kb tend to represent independent transcription units [5]. Illustrations by Pieterjan Ginckels, Faculty of Architecture, KU Leuven, Ghent, Belgium. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 P. Holvoet, Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer, https://doi.org/10.1007/978-3-030-68844-8_1

1

2

1 Biogenesis and Modes of Action of miRs and Circular …

Fig. 1.1 Biogenesis and mode of action of miRs. The majority of miRs are in introns or exons, derived from the processing of non-protein-coding regions of gene transcripts. Others are intergenic and are transcribed from non-coding DNA sequences between protein-coding genes as independent transcription units. Polycistronic miR genes may contain up to seven miR precursors. RNA polymerases II and III are responsible for miR transcription. MiRs with an ‘in sense’ orientation compared to annotated coding genes are transcribed as parts of longer molecules processed in the nucleus into hairpin RNAs of 70–100 nucleotides by the dsRNA-specific ribonuclease Drosha. The hairpin RNAs are transported to the cytoplasm by exportin 5, where they are digested by a second, double-strand specific ribonuclease called Dicer. The cleavage product becomes incorporated as single-stranded RNA into the ribonucleoprotein RNA-induced silencing complex RISC. In animals, single-stranded miR binds specific mRNA through sequences that, in most cases, are significant, though not wholly complementary to the target mRNA. As a result, these mRNA molecules are silenced by one or more of the following processes: cleavage of the mRNA strand into two pieces; destabilization of the mRNA through shortening of its poly(A) tail; and less efficient translation of the mRNA into proteins by ribosomes

1.1 MiRs

3

The specific half-life of each mRNA is closely related to its physiological function. Short-lived mRNAs are mostly regulatory genes, while long-lived mRNAs are often housekeeping genes. The half-life of miRs is comparable to that of regulatory mRNAs [6]. However, they may survive longer in the circulation when packed in exosomes or associated with lipoproteins [7–15]. RNA polymerase II transcribes miR genes [16–20]. In animals, the first step in miR maturation is the nuclear cleavage of the several-kb-long pri-miR, which releases an approximately 70 nucleotides, cropped, hairpin-shaped intermediate known as a miR precursor or pre-miR. The Drosha RNase III endonuclease is responsible for this nuclear processing [4, 21, 22]. Drosha is not active without a partner, forming a complex with the DiGeorge syndrome critical region gene 8, which contains two double-stranded RNA-binding domains [23, 24]. The hairpin precursor is actively transported from the nucleus to the cytoplasm by exportin 5 [25, 26]. A second enzyme, an RNase III endonuclease called Dicer, is responsible for generating a single-stranded RNA of about 21 nucleotides, the mature miR [27, 28]. After cleavage in the cytoplasm, the cleavage products become incorporated as single-stranded RNAs into the ribonucleoprotein RNA-induced silencing (RISC) complex [29]. RISC has been purified from human cells and contains a member of the Argonaute protein family, a core component of the complex [29, 30].

1.1.2 MiR Modes of Action Once incorporated in the cytoplasmic RISC complex, miRs regulate protein-coding genes’ output through diverse mechanisms [31]. The interaction of miRs with the 3 untranslated region (3 UTR) of protein-coding genes, considered the primary mechanism, leads to decreased protein output either by mRNA degradation or by translational repression [21] (Fig. 1.1). Interaction of miRs with the 5 UTR of protein-coding genes causes translational repression [32] or activation of the targeted proteins [33]. Besides targeting untranslated regions, miRs can also target the coding sequence and repress the translation of targeted genes [34]. Moreover, some miRs can interact with regulatory protein complexes, such as the argonaute RISC catalytic component 2 and fragile X mental retardation-related protein 1, and indirectly up-regulate the target’s translation gene [35].

1.1.3 Naming of miRs According to a standard nomenclature system, names are assigned to experimentally confirmed miRs before publication [36, 37]. A dash and a number follow the prefix “miR,” the latter often indicating the order of naming. For example, miR-124 was likely discovered and named before miR-126. A capitalized “miR-” refers to the mature form of the miR, while the uncapitalized “mir-” refers to the pre-miR and the pri-miR, and “MIR” refers to the gene that encodes them [38]. MiRs with nearly identical sequences except for one or two nucleotides are annotated with an additional

4

1 Biogenesis and Modes of Action of miRs and Circular …

lower-case letter. For example, miR-124a is closely related to miR-124b. When about the same amount of two mature miRs originate from the same pre-miR’s opposite arms, they are denoted with a -3p or -5p suffix. However, the mature miR from one arm of the hairpin is usually much more abundant than that from the other arm, in which case, an asterisk following the name indicates the mature species found at low levels from the opposite wing of a hairpin. For example, miR-124 and miR-124* share a pre-miR hairpin, but much more miR-124 is in a cell.

1.1.4 Useful Resources on miRs Tools 4 miRs (https://tools4mirs.org/software/target_prediction) predict targets of miRs in several species.

1.2 Circular RNAs 1.2.1 Biogenesis of Circular RNAs Circular (circ-) RNA is a type of RNA which, unlike the better known linear RNA, forms a covalently closed continuous loop, i.e., in circ-RNA, the 3 and 5 ends have been joined together [39–42]. Eukaryotic circ-RNA molecules are produced by splicing, catalyzed by the spliceosome machinery or ribozymes. Typically, the split coding exonic sequences are reattached together in a continuous coding transcript. Therefore, circ-RNAs are distinct from their linear counterparts because they are devoid of free ends and, therefore, resistant toward exonucleases and escape RNA degradation, thereby prolonging their half-life [43, 44]. The introns are removed through a spliceosome to generate circular RNA (Fig. 1.2). Circ-RNAs are often expressed at low levels, arguing for the possibility that the majority of circ-RNAs are inert splicing by-products [40, 41]. However, many circRNAs are expressed more abundantly than their linear isoforms in each examined cell line [45] and expressed in a cell type-specific or tissue-specific manner [46].

1.2.2 Circular RNAs Modes of Action Circ-RNAs may serve as sponges for miRs [42, 47]. A circ-RNA can act as a sponge and bind specific miR or groups of miRs, sequestering them and suppressing their function [48–50]. The circular cerebellar degeneration-related protein 1 (CDR1) antisense RNA (Circ-RNA CDR1as or ciRs-7) contains up to 74 binding sites for miR-7 and binds Argonaute proteins of RISC, which regulate miR production [42,

1.2 Circular RNAs

5

Fig. 1.2 Biogenesis of circular RNA. The linear primary transcript contains exons (blue boxes), introns (black lines), and possibly repetitive elements or sequence motifs (red boxes). Circular exons are generated from back-splicing events between the splice donor site of a downstream exon and the splice acceptor site of an upstream exon mediated by specific sequence elements (red boxes) or interacting with RNA binding proteins (RBPs). The introns are removed through a spliceosome to generate circular RNA

51]. The circular RNA PVT1 oncogene (PVT1) silences miR-17 [52], miR-26b [53], miR-29a [54], miR-143 [55], miR-455 [56]. The homeodomain interacting protein kinase three circ-RNA (circ-HIPK3) and the mitochondrial tRNA translation optimization one circ-RNA (circ-MTO1) also silences miR-17 [57, 58]. PVT1 not only sponge miR-143 directly [55] but inhibits miR-143 indirectly through binding with the enhancer of the zeste two polycomb repressive complex two subunit (EZH2), a histone methyltransferase catalyzing histone H3K27me3 to mediate gene silence [59]. Circ-RNAs may also enhance the transcription of target genes by recruiting RNA polymerase II to the promoter region. For example, PVT1 functions as an oncogene in ovarian cancer via up-regulating SRY-box transcription factor 2 (SOX2) [60]. It also promotes the activation of the signal transducer and activator of transcription (STAT)-3, which leads to the transcriptional activation of downstream targets

6

1 Biogenesis and Modes of Action of miRs and Circular …

Fig. 1.3 Modes of action of circular RNAs. Circular RNAs acts as sponges of miRs, thereby inducing miR degradation. They recruit RNA polymerase to the promoter of cognate mRNA, thereby increasing transcription. In contrast, they may compete with cognate mRNA for RBPs, thereby inhibiting transcription. Finally, they may assist in protein binding, thereby increasing stability or prevent protein interactions

involved in cell cycle progression [61]. Alternatively, they compete for their cognate mRNA for RNA binding proteins and modulate target mRNAs’ translation rates. For example, the promoters of PVT1 and the MYC oncogene (MYC), located 55 kb apart on chromosome 8q24, compete for engagement with four intragenic enhancers in the PVT1 locus, thereby allowing the PVT1 promoter to regulate pause release of MYC transcription. Finally, they mediate protein binding. PVT1 binds to Krüppel-like zinc finger transcription factor (KLF)-5 and increases its stability via the deubiquitinase BRCA1 associated protein 1, promoting breast cancer cell proliferation and tumor metastasis [62, 63]. The forkhead box O3 circ-RNA (circ-Foxo3) binds cyclin-dependent kinase 2 (CDK2) and cyclin dependent kinase inhibitor 1A (CDKN1A or P21), forming an RNA–protein complex that disrupts the interactions of CDK2 with cyclins (CCN) A and E, required for cell cycle progression [64]. Some circ-RNAs containing internal ribosome entry site elements [65] or prokaryotic ribosome-binding sites [66] might encode proteins, unlike their canonical counterparts. Ribosome footprinting studies in vivo in Drosophila demonstrate that circ-RNAs are associated with translating polysomes. For example, the F-box and WD repeat domain containing 7 (FBXW7) circ-RNA encodes a protein that plays an essential role in tumorigenesis [67, 68] (Fig. 1.3).

1.2 Circular RNAs

7

1.2.3 Useful Resources on Circ-RNAs CIRCexplorer2 (https://circexplorer2.readthedocs.io) is a comprehensive and integrative circular RNA analysis toolset.

1.3 lncRNAs 1.3.1 Biogenesis of lncRNAs LncRNAs are longer than 200 nucleotides, which coincide with the cut-off for many RNA extraction protocols [69–71]. LncRNAs show cell type-specific expression that varies with time and responds to diverse physiological stimuli, suggesting that their expression is under considerable transcriptional control [72–74]. Expression of lncRNAs seems to be more cell- and tissue-specific than protein-coding genes. Temporal changes in their expression correlate better with the differentiation and developmental stage than protein-coding genes. LncRNAs are developmentally regulated and operate in conserved gene regulatory networks [75]. Particular changes in lncRNA patterns underlie the differentiation of mesenchymal stem cells into cardiomyocyte-like cells [76]. Also, the interaction of several lncRNAs with differences in expression in time and space is needed to orchestrate development [77]. LncRNAs are transcribed from intergenic (indicated with linc) or intragenic regions of protein-coding genes. Intragenic lncRNAs overlap with the intron or exon of a protein-coding gene. Alternatively, they can be exonic, including sequences with the spliced mRNA of the overlapping protein-coding gene. Intergenic and intronic lncRNAs are transcribed in sense or antisense or both orientations relative to the protein-coding gene. Exonic lncRNAs are transcribed antisense. The tumor protein p53 pathway corepressor 1 (lincRNA-p21) is an intergenic lncRNA induced by p53, repressing the p21 gene in response to p53 [78, 79]. LincRNA-p21 predominantly functions in cis to activate the expression of its neighboring gene, p21. Mechanistically, lincRNAp21, in concert with the heterogeneous nuclear ribonucleoprotein K, coactivates p53dependent transcription of p21 (Fig. 1.4). The Ras association domain family member 1 (RASSF1) antisense lncRNA 1 (ANRASSF1) is an endogenous un-spliced lncRNA that is transcribed from the opposite strand on RASSF1 and binds the polycomb repressive complex 2 (PRC2). ANRASSF1 overexpression increases PRC2 occupancy and histone H3K27 methylase (H3K27me3) repressive marks, specifically at the RASSF1A promoter region [80] (Fig. 1.4). Like miRs, lncRNAs are relatively short-lived RNA molecules except when packed in microvesicles.

8

1 Biogenesis and Modes of Action of miRs and Circular …

Fig. 1.4 Classification of lncRNAs based on their genomic localization to protein-coding genes. a Intergenic lincRNAs are non-overlapping lncRNAs. LincRNA-p21 is a large intergenic noncoding RNA induced by p53 that mediates global gene expression in response to p53. For example, lincRNA-p21 predominantly functions in cis to activate the expression of its neighboring gene, p21. Mechanistically, lincRNA-p21 acts in concert with hnRNP-K as a coactivator for p53-dependent p21 transcription. P21 then regulates the expression of PRC2 that is important for maintaining the chromatin state. b Intragenic lncRNAs overlap with the intron or exon of a protein-coding gene. For example, ANRASSF1 is an endogenous unspliced lncRNA transcribed from the opposite strand on RASSF1. ANRASSF1 overexpression causes a marked increase in PRC2 occupancy and histone H3K27me3 repressive marks, specifically at the RASSF1A promoter region

1.3.2 Modes of Action of lncRNAs Compared to miRs, which act through mRNA degradation and translational repression, lncRNAs have more diverse modes of action [81] (Fig. 1.5). First, lncRNAs can serve as molecular signals that act in a time- and a site-dependent way to respond to diverse stimuli. The advantage of using RNA as a medium is that potential regulatory functions can be performed quickly without protein translation [82]. For

1.3 lncRNAs

9

Fig. 1.5 Classification of lncRNAs based on modes of action. Type I lncRNAs act as signals. LncRNA expression reflects one or more combinatorial actions of transcription factors (blue oval). Hypoxia-induced HIF-1α induces lincRNA-p21 that facilitates transcription of the GLUT1 gene promoting glucose transport inti pancreatic β cells. Type II lncRNAs act as decoys by titrating away transcription factors, regulatory proteins, or miRs. TGF-β-induced GAS5 acts as a sponge of SMAD3, thereby blocking the transcription of smooth muscle cell differentiation genes such as SMMHC. Type III lncRNAs act as guides recruiting chromatin-modifying enzymes to target genes that are in cis (near the site of lncRNA production) or trans. HOTAIR guides PRC2 that silences HOX transcription factors leading to repression of stem cell differentiation and cancer. Type IV lncRNAs act as scaffolds that bring together multiple proteins to form ribonucleoprotein complexes. The intergenic lincRNA-1614 is a specific partner of SOX2 and maintains pluripotency by repression of developmental genes. However, it is also a partner to PRC2 responsible for H3K27me3 modification, which primarily correlates with gene repression in embryonic stem cells

10

1 Biogenesis and Modes of Action of miRs and Circular …

example, hypoxia-induced hypoxia-inducible factor (HIF)-1α induces the expression of lincRNA-p21 required for transcription of the glucose transporter (GLUT) [83]. Second, lncRNAs can act as decoys. These lncRNAs are transcribed and then bind and titrate away a protein target but do not exert any additional regulatory function. The RNAs act as a “molecular sink” or sponge for RNA-binding proteins, transcription factors, chromatin modifiers, or other regulatory factors [84–86]. The transforming growth factor (TGF)-β induces the growth arrest-specific five lncRNA (GAS5), suppressing TGF-β/SMAD family member three (SMAD3) signaling in smooth muscle cells (SMC) by binding SMAD3 protein via multiple RNA SMADbinding elements. This binding prevents SMAD3 from binding to SBE DNA in the TGF-β-responsive smooth muscle myosin heavy chain (SMMHC) gene promoter [87]. Mostly this type of lncRNAs acts as sponges of miRs through near-perfect sequence complementarity [88]. Third, a lncRNA can act as a guide for recruiting chromatin-modifying enzymes to target genes. Thereby, lncRNAs can guide gene expression changes either in cis (on neighboring genes) or in trans (distantly located genes) in a manner that is not easily predicted based on lncRNA sequence [89]. They can even mediate the transcription of multiple genes by interacting with chromatin and recruiting the chromatin-modifying machinery [90, 91]. For example, the homeobox (HOX) transcript antisense lncRNA (HOTAIR) interacts with PRC2. This complex has histone methyltransferase activity. It primarily trimethylates histone three on lysine 27 (i.e., H3K27me3), a mark of transcriptionally silent chromatin. In this way, HOTAIR silences the transcription of homeobox (HOX) genes [92]. Fourth, lncRNAs can serve as scaffolds upon which relevant molecular components are assembled to precisely control the specificity and dynamics of intermolecular interactions and signaling events [93, 94]. These RNAs bring specific regulatory components into proximity with each other, resulting in the formation of a unique functional complex. These RNA regulatory complexes are formed by interaction with proteins and extend to RNA–DNA and RNA–RNA interactions [95, 96]. Such lncRNAs can even localize to two specific DNA sites by forming an RNA: DNA triplex, even at remote positions in the human genome [89, 96, 97]. Through extended base-pairing, lncRNAs stabilize or promote the translation of target mRNAs, while through partial base-pairing, they can facilitate mRNA decay or inhibit target mRNA translation [98]. The intergenic lincRNA-1614 coordinates SOX2/PRC2-mediated repression of developmental genes in pluripotency and thus maintains self-renewal. However, it is also a partner to PRC2 responsible for H3K27me3 modification, primarily repressing genes in embryonic stem cells [99]. In addition, PRC2-interacting sequences on maternally expressed 3 lncRNA (MEG3) lncRNA facilitate PRC2 recruitment. Chromatin-interacting sequences of MEG3 then guides MEG3 to G-A rich DNA sequences by DNA-RNA–DNA triplex formation, thereby establishing H3K27me3 marks to modulate the expression of genes important in cell differentiation [100, 101] (Fig. 1.5). As indicated above, lncRNAs can act as decoys of miRs, thereby indirectly inhibiting miR negative gene regulation by competing for binding to the 3 -UTR of

1.3 lncRNAs

11

target genes [102]. Also, dicer cleavage of lncRNAs can generate silencing RNAs, which serve as competitive ‘endogenous miRs.’ For example, HOTAIR functions as a sponge for miR-34a, miR-124, and miR-221–222 [103–105]. Thirdly, some lncRNAs are like protein-coding genes. The H19 imprinted maternally expressed transcript lncRNA (H19), located near the insulin-like growth factor (IGF)-2, gives rise to miR-675-3p and miR-675-5p [106]. Of interest, a single lncRNA may display several of these functions, which may differ according to the gene to be regulated. For example, the metastasis-associated lung adenocarcinoma transcript one lncRNA (MALAT1) regulates hyperglycemiainduced inflammatory processes [107], cell proliferation, and apoptosis [108].

1.4 piRs 1.4.1 Biogenesis of piRs PIWI-interacting RNAs (piRNAs or piRs) are large families of small (21–35 nucleotides in length), single-stranded, non-coding RNAs processed from long single-stranded precursor transcripts, for example, lncRNAs. In contrast, miRs derive from double-stranded RNA precursors [109, 110]. Vagin et al. demonstrated that they are Dicer-independent, PIWI protein-associated small silencing RNAs derived from single-stranded RNA and bearing a chemically modified 3 end [111]. PiR biogenesis requires specialized machinery that converts long single-stranded precursors into small RNAs of ∼25-nucleotides in length. These long precursor transcripts are fragmented by endonucleolytic cleavage—hypothesized to be catalyzed by the mitochondrial protein Zucchini/PLD6—producing tail-to-head, phased precursor piRs (pre-piRs) [112–114]. Each pre-piR begins with a 5 monophosphate, a prerequisite for loading nearly all Argonaute proteins [115–117]. Once bound to a PIWI protein, the 3 ends of pre-piRs are trimmed by the single-stranded-RNA exonuclease, Trimmer/ PARN like, ribonuclease domain containing 1 (PNLDC1) [118, 119]. Finally, Hen1/2 -O-methylates the 3 ends of the mature piRs [120, 121]. Alternatively, PIWI-catalyzed slicing of a target transcript creates an RNA fragment bearing a 5 monophosphate. This fragment acts as a pre-piR precursor (pre-pre-piR) and binds to a PIWI protein, ultimately generating a new secondary piRA [122, 123].

1.4.2 Modes of Action of piRs PiRs form a small RNA-based immune system that silences mobile genetic elements in animal germlines. Somatic piRs form complexes with the piwi-like RNA-mediated gene silencing 1 group of Argonaute proteins (PIWI). They guide these proteins to cleave target RNA, promote heterochromatin assembly, and methylate DNA [124].

12

1 Biogenesis and Modes of Action of miRs and Circular …

There are four human PIWIs: HIWI (also known as PIWIL1), HILI (also known as PIWIL2), HIWI2 (also known as PIWIL4), and HIWI3 (also known as PIWIL3). HIWI is expressed in human CD34(+) marrow cells. The human HIWI protein is 52% homologous to the Drosophila protein PIWI at the amino acid level. Hypermethylation of PIWIL1, PIWIL2, and PIWIL4 genes occurred in testicular cancer cells, associated with decreased piRNA expression [125]. The transient expression of HIWI in the human leukemia cell line KG1 resulted in a dramatic reduction in cellular proliferation and programmed cell death [126]. Figure 1.6 illustrates how piRs guide PIWI proteins to complementary gene sequences to silence their transcription. The oncogene OIP5 antisense RNA 1 (OIP5-AS1) lncRNA promotes cancer cell proliferation by inducing CCAAT/enhancer-binding protein alpha (c/EBP-α), phosphatidylinositol 3-kinase (PI3K)/ AKT serine/threonine kinase (AKT), and Wnt/βcatenin signaling [127, 128]. PiR-30188 may guide PIWIL3 to OIP5 antisense RNA 1 (OIP5-AS1), silencing it and reducing the sponging of miR-367-3p that silences c/EBP-α, which otherwise would induce proliferation, migration, and invasion, and protect against apoptosis by inducing TNF receptor associated factor 4 (TRAF4).

Fig. 1.6 Modes of action of piRNAs. PiRs guide PIWI proteins to coding RNA or lncRNA, resulting in their transcriptional silencing. a PiR-932 guides PIWIL2 to the GSK3β gene, silencing it. The silencing of GSK3β activates β-catenin, which induces cyclin CCND1, which increases the expression of miR-21 and miR-93. These miRs then activate the toll-like receptor (TLR)-8. Besides, CCND1 may induce the production of piR-016658 and piR-016975, which induce stemness. b PiR30188 guides PIWIL3 to the OIP5-AS1 lncRNA. Its silencing results in the de-repression of miR367-3p, which inhibits the expression of CCAAT enhancer-binding protein (c/EBP-α). Its silencing results in loss of activation of the TNF receptor-associated factor 4 (TRAF4), inhibiting proliferation and migration and inducing apoptosis. Besides, the decrease in c/EBP-α leads to overexpression of PIWIL3, closing a vicious circle

1.4 piRs

13

The inhibition of c/EBP-α leads to over-expression of PIWIL3, forming a positive feedback loop in the growth regulation of glioma cells [128]. PiR-932 induces epithelial-mesenchymal transition (EMT) of breast cancer cells by guiding PIWIL2 to glycogen synthase kinase three beta (GSK3β), stabilizing β-catenin, and inducing the β-catenin/CCND1 pathway [129]. CCN1 induces miR-21 and miR-93, which bind Toll-Like Receptor 8 to trigger vascular endothelial growth factor (VEGF) and BCL2 apoptosis regulator (BCL-2) [130]. Besides, CCND1 induces the PIWI-interacting RNAs, piR-016658 piR-016975, related to stem cell expansion and increased the abundance of PIWIL2 in estrogen related receptor alpha (ERRα)- positive breast cancer cells [131].

1.4.3 Useful Resources on piRs PiRBase (https://www.regulatoryrna.org/database/piRNA/) aims to provide comprehensive piR sequence data, annotation, and targets.

References 1. Rodriguez, A., Griffiths-Jones, S., Ashurst, J. L., & Bradley, A. (2004). Identification of mammalian microRNA host genes and transcription units. Genome Research, 14, 1902–1910. https://doi.org/10.1101/gr.2722704. 2. Lagos-Quintana, M., Rauhut, R., Meyer, J., Borkhardt, A., & Tuschl, T. (2003). New microRNAs from mouse and human. RNA, 9, 175–179. 3. Lau, N. C., Lim, L. P., Weinstein, E. G., & Bartel, D. P. (2001). An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science, 294, 858–862. https://doi. org/10.1126/science.1065062. 4. Lee, R. C., & Ambros, V. (2001). An extensive class of small RNAs in Caenorhabditis elegans. Science, 294, 862–864. https://doi.org/10.1126/science.1065329. 5. Baskerville, S., & Bartel, D. P. (2005). Microarray profiling of microRNAs reveals frequent coexpression with neighboring miRNAs and host genes. RNA, 11, 241–247. https://doi.org/ 10.1261/rna.7240905. 6. Tani, H., & Akimitsu, N. (2012). Genome-wide technology for determining RNA stability in mammalian cells: Historical perspective and recent advantages based on modified nucleotide labeling. RNA Biology, 9, 1233–1238. https://doi.org/10.4161/rna.22036. 7. Hulsmans, M., & Holvoet, P. (2013). MicroRNA-containing microvesicles regulating inflammation in association with atherosclerotic disease. Cardiovascular Research, 100, 7–18. https://doi.org/10.1093/cvr/cvt161. 8. Huber, H. J., & Holvoet, P. (2015). Exosomes: Emerging roles in communication between blood cells and vascular tissues during atherosclerosis. Current Opinion in Lipidology, 26, 412–419. https://doi.org/10.1097/MOL.0000000000000214. 9. Vanhaverbeke, M., Gal, D., & Holvoet, P. (2017). Functional role of cardiovascular exosomes in myocardial injury and atherosclerosis. Advances in Experimental Medicine and Biology, 998, 45–58. https://doi.org/10.1007/978-981-10-4397-0_3. 10. Bei, Y., et al. (2017). Extracellular vesicles in cardiovascular theranostics. Theranostics, 7, 4168–4182. https://doi.org/10.7150/thno.21274.

14

1 Biogenesis and Modes of Action of miRs and Circular …

11. Chen, X., et al. (2008). Characterization of microRNAs in serum: A novel class of biomarkers for diagnosis of cancer and other diseases. Cell Research, 18, 997–1006. https://doi.org/10. 1038/cr.2008.282. 12. Lawrie, C. H., et al. (2008). Detection of elevated levels of tumour-associated microRNAs in serum of patients with diffuse large B-cell lymphoma. British Journal of Haematology, 141, 672–675. https://doi.org/10.1111/j.1365-2141.2008.07077.x. 13. Mitchell, P. S., et al. (2008). Circulating microRNAs as stable blood-based markers for cancer detection. Proceedings of the National Academy of Sciences of the United States of America, 105, 10513–10518. https://doi.org/10.1073/pnas.0804549105. 14. Small, E. M., & Olson, E. N. (2011). Pervasive roles of microRNAs in cardiovascular biology. Nature, 469, 336–342. https://doi.org/10.1038/nature09783. 15. Vickers, K. C., Palmisano, B. T., Shoucri, B. M., Shamburek, R. D., & Remaley, A. T. (2011). MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nature Cell Biology, 13, 423–433. https://doi.org/10.1038/ncb2210. 16. Lee, Y., et al. (2004). MicroRNA genes are transcribed by RNA polymerase II. EMBO Journal, 23, 4051–4060. https://doi.org/10.1038/sj.emboj.7600385. 17. Zhou, X., Ruan, J., Wang, G., & Zhang, W. (2007). Characterization and identification of microRNA core promoters in four model species. PLoS Computational Biology, 3, e37. https:// doi.org/10.1371/journal.pcbi.0030037. 18. Kawahara, Y., et al. (2008). Frequency and fate of microRNA editing in human brain. Nucleic Acids Research, 36, 5270–5280. https://doi.org/10.1093/nar/gkn479. 19. Winter, J., Jung, S., Keller, S., Gregory, R. I., & Diederichs, S. (2009). Many roads to maturity: MicroRNA biogenesis pathways and their regulation. Nature Cell Biology, 11, 228–234. https://doi.org/10.1038/ncb0309-228. 20. Ohman, M. (2007). A-to-I editing challenger or ally to the microRNA process. Biochimie, 89, 1171–1176. https://doi.org/10.1016/j.biochi.2007.06.002. 21. Bartel, D. P. (2004). MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell, 116, 281–297. 22. Zeng, Y., Yi, R., & Cullen, B. R. (2005). Recognition and cleavage of primary microRNA precursors by the nuclear processing enzyme Drosha. EMBO Journal, 24, 138–148. https:// doi.org/10.1038/sj.emboj.7600491. 23. Han, J., et al. (2004). The Drosha-DGCR8 complex in primary microRNA processing. Genes & Development, 18, 3016–3027. https://doi.org/10.1101/gad.1262504. 24. Tomari, Y., & Zamore, P. D. (2005). MicroRNA biogenesis: Drosha can’t cut it without a partner. Current Biology, 15, R61-64. https://doi.org/10.1016/j.cub.2004.12.057. 25. Yi, R., Qin, Y., Macara, I. G., & Cullen, B. R. (2003). Exportin-5 mediates the nuclear export of pre-microRNAs and short hairpin RNAs. Genes & Development, 17, 3011–3016. https:// doi.org/10.1101/gad.1158803. 26. Lund, E., Guttinger, S., Calado, A., Dahlberg, J. E., & Kutay, U. (2004). Nuclear export of microRNA precursors. Science, 303, 95–98. https://doi.org/10.1126/science.1090599. 27. Lee, Y., et al. (2003). The nuclear RNase III Drosha initiates microRNA processing. Nature, 425, 415–419. https://doi.org/10.1038/nature01957. 28. Bernstein, E., Caudy, A. A., Hammond, S. M., & Hannon, G. J. (2001). Role for a bidentate ribonuclease in the initiation step of RNA interference. Nature, 409, 363–366. https://doi.org/ 10.1038/35053110. 29. Hammond, S. M., Caudy, A. A., & Hannon, G. J. (2001). Post-transcriptional gene silencing by double-stranded RNA. Nature Reviews Genetics, 2, 110–119. https://doi.org/10.1038/350 52556. 30. Mourelatos, Z., et al. (2002). miRNPs: A novel class of ribonucleoproteins containing numerous microRNAs. Genes & Development, 16, 720–728. https://doi.org/10.1101/gad. 974702. 31. Ling, H., Fabbri, M., & Calin, G. A. (2013). MicroRNAs and other non-coding RNAs as targets for anticancer drug development. Nature Reviews Drug Discovery, 12, 847–865. https://doi. org/10.1038/nrd4140.

References

15

32. Lytle, J. R., Yario, T. A., & Steitz, J. A. (2007). Target mRNAs are repressed as efficiently by microRNA-binding sites in the 5’ UTR as in the 3’ UTR. Proceedings of the National Academy of Sciences of the United States of America, 104, 9667–9672. https://doi.org/10. 1073/pnas.0703820104. 33. Orom, U. A., Nielsen, F. C., & Lund, A. H. (2008). MicroRNA-10a binds the 5’UTR of ribosomal protein mRNAs and enhances their translation. Molecular Cell, 30, 460–471. https:// doi.org/10.1016/j.molcel.2008.05.001. 34. Tay, Y., Zhang, J., Thomson, A. M., Lim, B., & Rigoutsos, I. (2008). MicroRNAs to Nanog, Oct4 and Sox2 coding regions modulate embryonic stem cell differentiation. Nature, 455, 1124–1128. https://doi.org/10.1038/nature07299. 35. Vasudevan, S., Tong, Y., & Steitz, J. A. (2007). Switching from repression to activation: MicroRNAs can up-regulate translation. Science, 318, 1931–1934. https://doi.org/10.1126/ science.1149460. 36. Ambros, V., et al. (2003). A uniform system for microRNA annotation. RNA, 9, 277–279. 37. Griffiths-Jones, S., Grocock, R. J., van Dongen, S., Bateman, A., & Enright, A. J. (2006). miRBase: MicroRNA sequences, targets and gene nomenclature. Nucleic Acids Research, 34, D140-144. https://doi.org/10.1093/nar/gkj112. 38. Wright, M. W., & Bruford, E. A. (2011). Naming ‘junk’: Human non-protein coding RNA (ncRNA) gene nomenclature. Human Genomics, 5, 90–98. 39. Salzman, J., Gawad, C., Wang, P. L., Lacayo, N., & Brown, P. O. (2012). Circular RNAs are the predominant transcript isoform from hundreds of human genes in diverse cell types. PLoS ONE, 7, e30733. https://doi.org/10.1371/journal.pone.0030733. 40. Jeck, W. R., et al. (2013). Circular RNAs are abundant, conserved, and associated with ALU repeats. RNA, 19, 141–157. https://doi.org/10.1261/rna.035667.112. 41. Zhang, X. O., et al. (2014). Complementary sequence-mediated exon circularization. Cell, 159, 134–147. https://doi.org/10.1016/j.cell.2014.09.001. 42. Memczak, S., et al. (2013). Circular RNAs are a large class of animal RNAs with regulatory potency. Nature, 495, 333–338. https://doi.org/10.1038/nature11928. 43. Vicens, Q., & Westhof, E. (2014). Biogenesis of Circular RNAs. Cell, 159, 13–14. https:// doi.org/10.1016/j.cell.2014.09.005. 44. Haque, S., & Harries, L. W. (2017). Circular RNAs (circRNAs) in health and disease. Genes (Basel), 8. https://doi.org/10.3390/genes812035. 45. Salzman, J., Chen, R. E., Olsen, M. N., Wang, P. L., & Brown, P. O. (2013). Cell-type specific features of circular RNA expression. PLoS Genetics, 9, e1003777. https://doi.org/10.1371/ journal.pgen.1003777. 46. Starke, S., et al. (2015). Exon circularization requires canonical splice signals. Cell Reports, 10, 103–111. https://doi.org/10.1016/j.celrep.2014.12.002. 47. Hansen, T. B., Kjems, J., & Damgaard, C. K. (2013). Circular RNA and miR-7 in cancer. Cancer Research, 73, 5609–5612. https://doi.org/10.1158/0008-5472.CAN-13-1568. 48. van Rossum, D., Verheijen, B. M., & Pasterkamp, R. J. (2016). Circular RNAs: Novel regulators of neuronal development. Frontiers in Molecular Neuroscience, 9, 74. https://doi.org/ 10.3389/fnmol.2016.00074. 49. Guo, J. U., Agarwal, V., Guo, H., & Bartel, D. P. (2014). Expanded identification and characterization of mammalian circular RNAs. Genome Biology, 15, 409. https://doi.org/10.1186/ s13059-014-0409-z. 50. Tay, Y., Rinn, J., & Pandolfi, P. P. (2014). The multilayered complexity of ceRNA crosstalk and competition. Nature, 505, 344–352. https://doi.org/10.1038/nature12986. 51. Weichenhan, D., & Plass, C. (2013). The evolving epigenome. Human Molecular Genetics, 22, R1–6. https://doi.org/10.1093/hmg/ddt348. 52. Liu, G., Liu, S., Xing, G., & Wang, F. (2020). lncRNA PVT1/MicroRNA-17-5p/PTEN axis regulates secretion of E2 and P4, proliferation, and apoptosis of ovarian granulosa cells in PCOS. Mol Ther Nucleic Acids, 20, 205–216. https://doi.org/10.1016/j.omtn.2020.02.007. 53. Zheng, J., et al. (2018). lncRNA PVT1 promotes the angiogenesis of vascular endothelial cell by targeting miR26b to activate CTGF/ANGPT2. International Journal of Molecular Medicine, 42, 489–496. https://doi.org/10.3892/ijmm.2018.3595.

16

1 Biogenesis and Modes of Action of miRs and Circular …

54. Liu, Y. Y., Zhang, L. Y., & Du, W. Z. (2019) Circular RNA circ-PVT1 contributes to paclitaxel resistance of gastric cancer cells through the regulation of ZEB1 expression by sponging miR-124-3p. Bioscience Reports, 39. https://doi.org/10.1042/BSR20193045. 55. Chen, J., et al. (2019). Long non-coding RNA PVT1 promotes tumor progression by regulating the miR-143/HK2 axis in gallbladder cancer. Molecular Cancer, 18, 33. https://doi.org/10. 1186/s12943-019-0947-9. 56. Chai, J., et al. (2018). A feedback loop consisting of RUNX2/LncRNA-PVT1/miR-455 is involved in the progression of colorectal cancer. American Journal of Cancer Research, 8, 538–550. 57. Deng, Y., Wang, J., Xie, G., Zeng, X., & Li, H. (2019). Circ-HIPK3 strengthens the effects of adrenaline in heart failure by MiR-17-3p - ADCY6 Axis. International Journal of Biological Sciences, 15, 2484–2496. https://doi.org/10.7150/ijbs.36149. 58. Hu, Y., & Guo, B. (2020). Circ-MTO1 correlates with favorable prognosis and inhibits cell proliferation, invasion as well as miR-17-5p expression in prostate cancer. Journal of Clinical Laboratory Analysis, 34, e23086. https://doi.org/10.1002/jcla.23086. 59. Xu, Y., et al. (2018). The long non-coding RNA PVT1 represses ANGPTL4 transcription through binding with EZH2 in trophoblast cell. Journal of Cellular and Molecular Medicine, 22, 1272–1282. https://doi.org/10.1111/jcmm.13405. 60. Zou, M. F., Ling, J., Wu, Q. Y., & Zhang, C. X. (2018). Long non-coding RNA PVT1 functions as an oncogene in ovarian cancer via upregulating SOX2. European Review for Medical and Pharmacological Sciences, 22, 7183–7188. https://doi.org/10.26355/eurrev_201811_16251. 61. Luo, Z., & Cao, P. (2019). Long noncoding RNA PVT1 promotes hepatoblastoma cell proliferation through activating STAT3. Cancer Management and Research, 11, 8517–8527. https:// doi.org/10.2147/CMAR.S213707. 62. Tang, J., et al. (2018). LncRNA PVT1 regulates triple-negative breast cancer through KLF5/beta-catenin signaling. Oncogene, 37, 4723–4734. https://doi.org/10.1038/s41388018-0310-4. 63. Qin, J., et al. (2015). BAP1 promotes breast cancer cell proliferation and metastasis by deubiquitinating KLF5. Nature Communications, 6, 8471. https://doi.org/10.1038/ncomms 9471. 64. Du, W. W., et al. (2016). Foxo3 circular RNA retards cell cycle progression via forming ternary complexes with p21 and CDK2. Nucleic Acids Research, 44, 2846–2858. https://doi. org/10.1093/nar/gkw027. 65. Chen, C. Y., & Sarnow, P. (1995). Initiation of protein synthesis by the eukaryotic translational apparatus on circular RNAs. Science, 268, 415–417. 66. Perriman, R., & Ares, M., Jr. (1998). Circular mRNA can direct translation of extremely long repeating-sequence proteins in vivo. RNA, 4, 1047–1054. 67. Pamudurti, N. R. et al. (2017). Translation of CircRNAs. Molecular Cell, 66, 9–21 e27. https:// doi.org/10.1016/j.molcel.2017.02.021. 68. Yang, Y., et al. (2018). Novel role of FBXW7 circular RNA in repressing glioma tumorigenesis. Journal of the National Cancer Institute, 110. https://doi.org/10.1093/jnci/djx166. 69. Rinn, J. L., & Chang, H. Y. (2012). Genome regulation by long noncoding RNAs. Annual Review of Biochemistry, 81, 145–166. https://doi.org/10.1146/annurev-biochem-051410092902. 70. Cech, T. R., & Steitz, J. A. (2014). The noncoding RNA revolution-trashing old rules to forge new ones. Cell, 157, 77–94. https://doi.org/10.1016/j.cell.2014.03.008. 71. Kowalczyk, M. S., Higgs, D. R., & Gingeras, T. R. (2012). Molecular biology: RNA discrimination. Nature, 482, 310–311. https://doi.org/10.1038/482310a. 72. Ingolia, N. T., Lareau, L. F., & Weissman, J. S. (2011). Ribosome profiling of mouse embryonic stem cells reveals the complexity and dynamics of mammalian proteomes. Cell, 147, 789–802. https://doi.org/10.1016/j.cell.2011.10.002. 73. Guttman, M., Russell, P., Ingolia, N. T., Weissman, J. S., & Lander, E. S. (2013). Ribosome profiling provides evidence that large noncoding RNAs do not encode proteins. Cell, 154, 240–251. https://doi.org/10.1016/j.cell.2013.06.009.

References

17

74. Ruiz-Orera, J., Messeguer, X., Subirana, J. A., & Alba, M. M. (2014). Long non-coding RNAs as a source of new peptides. Elife, 3, e03523. https://doi.org/10.7554/eLife.03523. 75. Gaiti, F., Hatleberg, W. L., Tanurdzic, M., & Degnan, B. M. (2018). Sponge long non-coding RNAs are expressed in specific cell types and conserved networks. Noncoding RNA, 4. https:// doi.org/10.3390/ncrna4010006. 76. Ruan, Z. B., Chen, G. C., Ren, Y., & Zhu, L. (2018). Expression profile of long non-coding RNAs during the differentiation of human umbilical cord derived mesenchymal stem cells into cardiomyocyte-like cells. Cytotechnology. https://doi.org/10.1007/s10616-018-0217-5. 77. Tang, Z., et al. (2017). Comprehensive analysis of long non-coding RNAs highlights their spatio-temporal expression patterns and evolutional conservation in Sus scrofa. Science Report, 7, 43166. https://doi.org/10.1038/srep43166. 78. Huarte, M., et al. (2010). A large intergenic noncoding RNA induced by p53 mediates global gene repression in the p53 response. Cell, 142, 409–419. https://doi.org/10.1016/j.cell.2010. 06.040. 79. Dimitrova, N., et al. (2014). LincRNA-p21 activates p21 in cis to promote Polycomb target gene expression and to enforce the G1/S checkpoint. Molecular Cell, 54, 777–790. https:// doi.org/10.1016/j.molcel.2014.04.025. 80. Beckedorff, F. C., et al. (2013). The intronic long noncoding RNA ANRASSF1 recruits PRC2 to the RASSF1A promoter, reducing the expression of RASSF1A and increasing cell proliferation. PLoS Genetics, 9, e1003705. https://doi.org/10.1371/journal.pgen.1003705. 81. Wang, K. C., & Chang, H. Y. (2011). Molecular mechanisms of long noncoding RNAs. Molecular Cell, 43, 904–914. https://doi.org/10.1016/j.molcel.2011.08.018. 82. Guttman, M., & Rinn, J. L. (2012). Modular regulatory principles of large non-coding RNAs. Nature, 482, 339–346. https://doi.org/10.1038/nature10887. 83. Shen, Y., Liu, Y., Sun, T., & Yang, W. (2017). LincRNA-p21 knockdown enhances radiosensitivity of hypoxic tumor cells by reducing autophagy through HIF-1/Akt/mTOR/P70S6K pathway. Experimental Cell Research, 358, 188–198. https://doi.org/10.1016/j.yexcr.2017. 06.016. 84. Hung, T., et al. (2011). Extensive and coordinated transcription of noncoding RNAs within cell-cycle promoters. Nature Genetics, 43, 621–629. https://doi.org/10.1038/ng.848. 85. Kino, T., Hurt, D. E., Ichijo, T., Nader, N., & Chrousos, G. P. (2010). Noncoding RNA gas5 is a growth arrest- and starvation-associated repressor of the glucocorticoid receptor. Science Signal, 3, ra8. https://doi.org/10.1126/scisignal.2000568. 86. Bernard, D., et al. (2010). A long nuclear-retained non-coding RNA regulates synaptogenesis by modulating gene expression. EMBO Journal, 29, 3082–3093. https://doi.org/10.1038/ emboj.2010.199. 87. Tang, R., Zhang, G., Wang, Y. C., Mei, X., & Chen, S. Y. (2017). The long non-coding RNA GAS5 regulates transforming growth factor beta (TGF-beta)-induced smooth muscle cell differentiation via RNA Smad-binding elements. Journal of Biological Chemistry, 292, 14270–14278. https://doi.org/10.1074/jbc.M117.790030. 88. Franco-Zorrilla, J. M., et al. (2007). Target mimicry provides a new mechanism for regulation of microRNA activity. Nature Genetics, 39, 1033–1037. https://doi.org/10.1038/ng2079. 89. Grote, P., & Herrmann, B. G. (2013). The long non-coding RNA Fendrr links epigenetic control mechanisms to gene regulatory networks in mammalian embryogenesis. RNA Biology, 10, 1579–1585. https://doi.org/10.4161/rna.26165. 90. Pandey, R. R., et al. (2008). Kcnq1ot1 antisense noncoding RNA mediates lineage-specific transcriptional silencing through chromatin-level regulation. Molecular Cell, 32, 232–246. https://doi.org/10.1016/j.molcel.2008.08.022. 91. Mohammad, F., et al. (2008). Kcnq1ot1/Lit1 noncoding RNA mediates transcriptional silencing by targeting to the perinucleolar region. Molecular and Cellular Biology, 28, 3713–3728. https://doi.org/10.1128/MCB.02263-07. 92. Rinn, J. L., et al. (2007). Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs. Cell, 129, 1311–1323. https://doi.org/10.1016/j.cell. 2007.05.022.

18

1 Biogenesis and Modes of Action of miRs and Circular …

93. Guttman, M., et al. (2011). lincRNAs act in the circuitry controlling pluripotency and differentiation. Nature, 477, 295–300. https://doi.org/10.1038/nature10398. 94. Spitale, R. C., Tsai, M. C., & Chang, H. Y. (2011). RNA templating the epigenome: Long noncoding RNAs as molecular scaffolds. Epigenetics, 6, 539–543. 95. Jalali, S., Singh, A., Maiti, S., & Scaria, V. (2017). Genome-wide computational analysis of potential long noncoding RNA mediated DNA:DNA:RNA triplexes in the human genome. Journal of Translational Medicine, 15, 186. https://doi.org/10.1186/s12967-017-1282-9. 96. O’Leary, V. B., et al. (2015). PARTICLE, a triplex-forming long ncRNA, regulates locusspecific methylation in response to low-dose irradiation. Cell Reports 11, 474–485. https:// doi.org/10.1016/j.celrep.2015.03.043. 97. Li, Y., Syed, J., & Sugiyama, H. (2016). RNA-DNA triplex formation by long noncoding RNAs. Cell Chemical Biology, 23, 1325–1333. https://doi.org/10.1016/j.chembiol.2016. 09.011. 98. Yoon, J. H., Abdelmohsen, K., & Gorospe, M. (2013). Posttranscriptional gene regulation by long noncoding RNA. Journal of Molecular Biology, 425, 3723–3730. https://doi.org/10. 1016/j.jmb.2012.11.024. 99. Guo, X., et al. (2017). LincRNA-1614 coordinates Sox2/PRC2-mediated repression of developmental genes in pluripotency maintenance. Journal of Molecular Cell Biology. https://doi. org/10.1093/jmcb/mjx041. 100. Kim, J. M., et al. (2015). Linker histone H1.2 establishes chromatin compaction and gene silencing through recognition of H3K27me3. Science Report, 5, 16714. https://doi.org/10. 1038/srep16714. 101. Mondal, T., et al. (2015). MEG3 long noncoding RNA regulates the TGF-beta pathway genes through formation of RNA-DNA triplex structures. Nature Communincations, 6, 7743. https:// doi.org/10.1038/ncomms8743. 102. Faghihi, M. A., et al. (2008). Expression of a noncoding RNA is elevated in Alzheimer’s disease and drives rapid feed-forward regulation of beta-secretase. Nature Medicine, 14, 723– 730. https://doi.org/10.1038/nm1784. 103. Gao, L., et al. (2019). LncRNA HOTAIR functions as a competing endogenous RNA to upregulate SIRT1 by sponging miR-34a in diabetic cardiomyopathy. Journal of Cellular Physiology, 234, 4944–4958. https://doi.org/10.1002/jcp.27296. 104. Sun, Y. J., Li, J., & Chen, C. H. (2019). Effects of miR-221 on the apoptosis of non-small cell lung cancer cells by lncRNA HOTAIR. European Review for Medical and Pharmacological Sciences, 23, 4226–4233. https://doi.org/10.26355/eurrev_201905_17927. 105. Zhou, H., et al. (2019). LncRNA HOTAIR promotes renal interstitial fibrosis by regulating Notch1 pathway via the modulation of miR-124. Nephrology (Carlton), 24, 472–480. https:// doi.org/10.1111/nep.13394. 106. Dey, B. K., Pfeifer, K., & Dutta, A. (2014). The H19 long noncoding RNA gives rise to microRNAs miR-675-3p and miR-675-5p to promote skeletal muscle differentiation and regeneration. Genes & Development, 28, 491–501. https://doi.org/10.1101/gad.234419.113. 107. Puthanveetil, P., Chen, S., Feng, B., Gautam, A., & Chakrabarti, S. (2015). Long non-coding RNA MALAT1 regulates hyperglycaemia induced inflammatory process in the endothelial cells. Journal of Cellular and Molecular Medicine, 19, 1418–1425. https://doi.org/10.1111/ jcmm.12576. 108. Michalik, K. M., et al. (2014). Long noncoding RNA MALAT1 regulates endothelial cell function and vessel growth. Circulation Research, 114, 1389–1397. https://doi.org/10.1161/ CIRCRESAHA.114.303265. 109. Aravin, A., et al. (2006). A novel class of small RNAs bind to MILI protein in mouse testes. Nature, 442, 203–207. https://doi.org/10.1038/nature04916. 110. Girard, A., Sachidanandam, R., Hannon, G. J., & Carmell, M. A. (2006). A germline-specific class of small RNAs binds mammalian Piwi proteins. Nature, 442, 199–202. https://doi.org/ 10.1038/nature04917. 111. Vagin, V. V., et al. (2006). A distinct small RNA pathway silences selfish genetic elements in the germline. Science, 313, 320–324. https://doi.org/10.1126/science.1129333.

References

19

112. Ipsaro, J. J., Haase, A. D., Knott, S. R., Joshua-Tor, L., & Hannon, G. J. (2012). The structural biochemistry of Zucchini implicates it as a nuclease in piRNA biogenesis. Nature, 491, 279– 283. https://doi.org/10.1038/nature11502. 113. Nishimasu, H., et al. (2012). Structure and function of Zucchini endoribonuclease in piRNA biogenesis. Nature, 491, 284–287. https://doi.org/10.1038/nature11509. 114. Mohn, F., Handler, D., & Brennecke, J. (2015). Noncoding RNA. piRNA-guided slicing specifies transcripts for Zucchini-dependent, phased piRNA biogenesis. Science, 348, 812– 817. https://doi.org/10.1126/science.aaa1039. 115. Kawaoka, S., et al. (2012). A role for transcription from a piRNA cluster in de novo piRNA production. RNA, 18, 265–273. https://doi.org/10.1261/rna.029777.111. 116. Xiol, J., et al. (2014). RNA clamping by Vasa assembles a piRNA amplifier complex on transposon transcripts. Cell, 157, 1698–1711. https://doi.org/10.1016/j.cell.2014.05.018. 117. Matsumoto, N. et al. (2016). Crystal Structure of Silkworm PIWI-Clade Argonaute Siwi Bound to piRNA. Cell, 167, 484–497 e489. https://doi.org/10.1016/j.cell.2016.09.002. 118. Tang, W., Tu, S., Lee, H. C., Weng, Z., & Mello, C. C. (2016). The RNase PARN-1 trims piRNA 3’ ends to promote transcriptome surveillance in C. elegans. Cell, 164, 974–984. https://doi.org/10.1016/j.cell.2016.02.008. 119. Izumi, N., et al. (2016). Identification and functional analysis of the pre-piRNA 3’ trimmer in silkworms. Cell, 164, 962–973. https://doi.org/10.1016/j.cell.2016.01.008. 120. Horwich, M. D., et al. (2007). The Drosophila RNA methyltransferase, DmHen1, modifies germline piRNAs and single-stranded siRNAs in RISC. Current Biology, 17, 1265–1272. https://doi.org/10.1016/j.cub.2007.06.030. 121. Kirino, Y., & Mourelatos, Z. (2007). Mouse Piwi-interacting RNAs are 2’-O-methylated at their 3’ termini. Nature Structural & Molecular Biology, 14, 347–348. https://doi.org/10.1038/ nsmb1218. 122. Brennecke, J., et al. (2007). Discrete small RNA-generating loci as master regulators of transposon activity in Drosophila. Cell, 128, 1089–1103. https://doi.org/10.1016/j.cell.2007. 01.043. 123. Gunawardane, L. S., et al. (2007). A slicer-mediated mechanism for repeat-associated siRNA 5’ end formation in Drosophila. Science, 315, 1587–1590. https://doi.org/10.1126/science. 1140494. 124. Moyano, M., & Stefani, G. (2015). piRNA involvement in genome stability and human cancer. Journal of Hematology & Oncology , 8, 38. https://doi.org/10.1186/s13045-015-0133-5. 125. Ferreira, H. J., et al. (2014). Epigenetic loss of the PIWI/piRNA machinery in human testicular tumorigenesis. Epigenetics, 9, 113–118. https://doi.org/10.4161/epi.27237. 126. Sharma, A. K., et al. (2001). Human CD34(+) stem cells express the hiwi gene, a human homologue of the Drosophila gene piwi. Blood, 97, 426–434. https://doi.org/10.1182/blood. v97.2.426. 127. Tao, Y., et al. (2020). Long non-coding RNA OIP5-AS1 promotes the growth of gastric cancer through the miR-367-3p/HMGA2 axis. Digestive and Liver Disease, 52, 773–779. https://doi. org/10.1016/j.dld.2019.11.017. 128. Liu, X., et al. (2018). PIWIL3/OIP5-AS1/miR-367-3p/CEBPA feedback loop regulates the biological behavior of glioma cells. Theranostics, 8, 1084–1105. https://doi.org/10.7150/thno. 21740. 129. Wu, D., et al. (2015). Effects of novel ncRNA molecules, p15-piRNAs, on the methylation of DNA and histone H3 of the CDKN2B promoter region in U937 cells. Journal of Cellular Biochemistry, 116, 2744–2754. https://doi.org/10.1002/jcb.25199. 130. Zhang, Y., et al. (2014). The expression of Toll-like receptor 8 and its relationship with VEGF and Bcl-2 in cervical cancer. International Journal of Medical Sciences, 11, 608–613. https:// doi.org/10.7150/ijms.8428. 131. Lu, J., et al. (2020). Cyclin D1 promotes secretion of pro-oncogenic immuno-miRNAs and piRNAs. Clinical science (London), 134, 791–805. https://doi.org/10.1042/CS20191318.

Chapter 2

Non-coding RNAs Related to Obesity

Abstract Obesity results from hampered stem cell proliferation and epithelialmesenchymal transition, and white and brown and beige adipocyte maturation. Obesity is associated with impaired glucose uptake and insulin signaling leading to adipocyte hypertrophy by lipid accumulation and oxidative stress and inflammation. Impaired beige and brown adipogenesis results in blunted thermogenesis, an important defense against obesity. Obesity results from and is associated with changes in expression of let-7, miR-9, miR-17, miR-21, miR-26a, miR-27a/b, miR29, miR-30a/b/c, miR-31, miR-32, miR-34a, miR-103, miR-124, miR-125, miR130a/b, miR-133, miR-138, miR-142, miR-143-145, miR-144, miR-146a/b, miR150, miR-155, miR-181, miR-193b, miR-196a, miR-199a-214, miR-206, miR-221, miR-223, miR-326, miR-335, miR-361-5p, miR-377, miR-378, miR-448, miR-455, miR-494-3p, miR-519d, miR-574-5p, NEAT1/miR-140/MEG3 paraspeckles, and lncRNAs βLINC, GAS5, HOTAIR, H19, PLNC1 and TNCR, and circular RNA PVT1. Importantly, no single non-coding RNA has a function that is not reinforced or hampered by other non-coding RNAs. Let-7a, miR-7, mir-9, mir-30b, mir-100a, mir-145, miR-200, miR-385, miR-384, miR-142, and miR-488 may be linked to leptin and insulin signaling in the hypothalamus, controlling weight.

2.1 Mechanisms in White Adipogenesis White adipocytes arise from myogenic factor 5 (MYF5)-negative precursor cells in the stromal vascular fraction of adipose tissue. Wnt/β-catenin signaling is crucial in maintaining adipocyte stem cells (ASC) and adipocyte differentiation. Wnt ligands stabilize β-catenin through inhibiting the destruction complex consisting of casein kinase 1α, glycogen synthase kinase 3β (GSK3β), and the tumor suppressor APC regulator of the Wnt signaling pathway. Then β-catenin enters the nucleus and turns on transcription via binding to members of the lymphoid enhancer factor family of transcription factors. Besides, β-catenin induces epithelial to mesenchymal transition (EMT) and retains pluripotency involving the snail family transcriptional repressor 1 Illustrations by Pieterjan Ginckels, Faculty of Architecture, KU Leuven, Ghent, Belgium. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 P. Holvoet, Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer, https://doi.org/10.1007/978-3-030-68844-8_2

21

22

2 Non-coding RNAs Related to Obesity

(SNAI1 or SNAIL), snail family transcriptional repressor 2 (SLUG or SNAI2), and twist family bHLH transcription factor (TWIST) [1, 2]. However, in the absence of Wnts, cytoplasmic β-catenin is degraded [3]. Next, Wnt/β-catenin cooperates with fibroblast growth factor (FGF) to regulate the proliferation and differentiation of stem cells [4] (Fig. 2.1). FGF1 promotes proliferation and differentiation of preadipocytes. FGF2 induces self-renewal of ASCs and insulin sensitization [5–7]. However, FGF2 may also suppress the differentiation of ASCs by inducing TWIST2 and sprouty RTK signaling antagonist 4 (SPROUTY4 or SPRY4) in a concentration-dependent manner [8–10]. Further, cyclins (CCNs) induce proliferation of precursor cells and adipogenesis [11–15] (Fig. 2.1). Bone morphogenetic protein (BMP)-2 and BMP4 stimulate precursor cells to differentiate to committed white preadipocytes [16]. Peroxisome proliferatoractivated receptor (PPAR)-γ and CCAAT enhancer-binding protein (c/EBP)-α induce maturation of white adipocytes [17, 18]. The activation of the PPAR-γ and the c/EBP-α promoter depends on early B cell factor (EBF)-1, which exerts positive feedback on c/EBP-δ expression [19]. Krüppel-like zinc finger transcription factors (KLFs), especially KLF4, KLF5, and KLF15, regulate adipogenesis by transactivating c/EBP-β and c/EBP–δ [20–24]. EBF1 regulates white adipocyte differentiation and induces inflammation by inhibiting phosphatidylinositol 3-kinase (PI3K)/AKT serine/threonine kinase 1 (AKT)/mitogen-activated protein kinase (MAPK) signaling [25, 26]. Deregulation of PI3K/AKT/MAPK and protein kinase AMP-activated catalytic (AMPK) pathways essential for glucose homeostasis often results in obesity and type 2 diabetes [27]. Tumor necrosis factor (TNF-α), basic fibroblast growth factor (BFG), and transforming growth factor (TGF)-β down-regulate PPAR-γ expression, with a concomitant decrease in adipocyte-specific gene expression [28]. However, the steroid receptor RNA activator (SRA) restores adipocyte differentiation, improving insulin-stimulated glucose uptake, and inhibiting TNF-α-mediated inflammation [29, 30]. Mature adipocytes secrete the fatty acid-binding protein (FABP)-4, or adipocyte protein 2 (aP2), chaperoning lipids and maintaining glucose homeostasis. A population of aP2-expressing progenitors in the stromal vascular fraction of both WAT and BAT reside in the adipose stem cell niche and proliferate and differentiate into adipocytes upon induction. Conversely, ablation of the aP2 lineage significantly reduces the adipogenic potential of stromal vascular fraction cells [31]. However, calorie excess in obesity is associated with decreased FABP4 leading to endoplasmic reticulum (ER) stress and reactive oxygen species (ROS) secretion. However, a sustained increase of FABP4 under conditions of immune-metabolic stress exacerbates type 2 diabetes-associated atherosclerosis and cancer [32–35]. Another marker of mature adipocytes is the solute carrier family 2 (facilitated glucose transporter), member 4 (GLUT4) that is up-regulated by BMPs via PPAR-γ. BMPs thereby act as insulin sensitizers [36, 37]. Calorie excess decreases PPAR-γ coactivator 1α (PGC-1α)/GLUT4 signaling, while weight reduction is associated with increased PGC-1α/GLUT4 signaling [38]. Leptin-induced decrease of PGC-1α leads to the repression of the estrogen-related receptor (ERR)-α. FABP4 usually blocks this leptin action, however it is low in obesity [35, 39, 40]. Repression of ERR-α

2.1 Mechanisms in White Adipogenesis

23

Fig. 2.1 Non-coding RNAs in white adipogenesis. White adipocytes derive from MYF5-negative precursor cells. Their proliferation depends on Wnt/β-catenin, FGF, TWIST and SPRY, and CCNs. Wnt/β-catenin signaling induces EMT involving SNAI1, SNAI2, and TWIST1, increasing the number of stem cells. However, Wnt/β-catenin signaling is low in obesity. Besides, high levels of let-7, miR-21, that needs to be balanced by GAS5, miR-34a, miR-145, and miR-146a, limit the number of white adipocyte precursors. MiR-124, miR-181a, miR-221, and HOTAIR may restore stem cell proliferation. Next, BMP2 and BMP4 stimulate adipocyte precursors to differentiate to committed white preadipocytes. The decrease of miR-181d impairs BMP action, reduces the number of committed preadipocytes, and reduces insulin sensitivity. In contrast, miR-30a retains insulin sensitivity. BMP2, BMP4, FGF1, FGF2, and c/EBPs and PPAR-γ differentiate preadipocytes to committed white adipocytes. PPAR-γ action depends on EBF1 and KLFs. The increase of miR-27b, miR-130a, miR-138, miR-361-5p, miR-519 d, miR-574-5p, and H19-miR-675, and the decrease of miR-103, miR-124, and miR-140/NEAT1/MEG3 paraspeckles inhibit adipocyte maturation. MiR-30a, miR-144, lncRNA PLNC1, and circ-RNA PVT1 and the decrease of miR-29 and miR-448 may partially prevent this impairment. Mature adipocytes release FABP4 (aP2) and GLUT4, and adiponectin (ADIPOQ), which regulate insulin signaling and glucose uptake. However, calorie excess decreases FABP4, GLUT4, and adiponectin, by reducing miR-103 and miR-124 and increasing miR-138. In obesity, increased leptin also reduces GLUT4, enhanced by the lack of FABP4 (aP2) that otherwise blocks this leptin action. The reduction of FABP4 leads to ER stress and ROS secretion. The decrease of GLUT4 reduces glucose uptake and decreases PGC-1α and ERR-α, resulting in mitochondrial ROS release and increased secretion by adipocytes of CCL2

24

2 Non-coding RNAs Related to Obesity

 that attracts monocytes and induces inflammation further enhanced by ERR-α’s target gene PDK2. Besides, calorie excess causes adipocyte hypertrophy and insulin resistance by increasing miR-155 and decreasing NEAT1/miR-140/MEG3 paraspeckles. MiR-34a may revert lipid accumulation. In healthy WAT, FABP4 and GLUT4 induce de-differentiation to aP2 progenitors, which become MYF5- precursors through the action of c/EBP-α, and CCNs, and CDKs. However, miR-34a inhibits this de-differentiation in obese WAT. The increase of EBF1, required for white adipogenesis, is also associated with impaired PI3K/AKT/MAPK signaling, leading to the release of inflammatory TNFα, which inhibits the maturation of β cells. However, SRA mediated activation of FOXO1 and the decrease of miR-361-5p and miR-574-5p inhibit inflammation may overcome this. Inflammatory cytokine-induced miR-34a accelerates cellular senescence. Increased non-coding RNAs are in red, decreased in green

results in higher levels of mitochondrial membrane potential, and ROS production, and secretion of the C-C motif chemokine ligand 2 (CCL2 or MCP-1) that exacerbates macrophage accumulation and inflammation [41–45]. When pyruvate dehydrogenase kinase 2 (PDK2), an ERR-α target, is suppressed, the tricarboxylic acid cycle is activated. This activation increases the mitochondrial membrane potential and the ROS release [41]. Further, the decrease of FABP4 may reduce hydrogen peroxide scavenging, resulting in increased ROS production [46]. Calorie excess is also associated with unhealthy expansion or hypertrophy of WAT by lipid accumulation that promotes the obesity-associated glucose intolerance and insulin resistance and inflammation [47] (Fig. 2.1).

2.1.1 Role of Non-coding RNAs in White Adipogenesis MiR-124 and miR-221 induce the differentiation of ASCs [48, 49]. High levels of expression let-7, miR-21, miR-34a, miR-145-5p and miR-146a-5p block ASC proliferation [50–53]. However, overexpression of growth arrest-specific 5 (GAS5) also impairs mesenchymal cells’ differentiation to adipocytes by silencing miR-21 [54, 55]. Thus, miR-21 needs to be tightly balanced. In contrast, miR-181a and homeobox transcript antisense RNA (HOTAIR) increase circadian rhythm-modulated proliferation of ASCs [56, 57]. A decrease in miR-181d is associated with the repression of BMP4-induced differentiation of precursors to committed white adipocytes [58]. MiR-30a is a crucial regulator of adipogenesis by targeting the principal regulator of osteogenesis, RUNX2 [59]. MiR-30a-5p and lncRNA PLNC1, transcribed from the PPAR-γ2 gene, contribute to adipocyte differentiation, reflected by the enrichment of PPAR-γ, c/EBP-α, and FABP4. Sirtuin (SIRT)-1 is another target of miR-30a-5p, and a supplement of SIRT1 blocks adipogenesis [60, 61]. In addition to miR-30a, miR-144-3p increases c/EBP-α activity by releasing corepressors KLF3 and C-terminal binding protein two from its promoter region [62]. MiR30a targets the transcription factor STAT1 to increase insulin sensitivity [63]. The circ-RNA derived from PVT1 oncogene (PVT1) up-regulates PPAR-γ, c/EBP-α, and adiponectin, promoting adipocyte differentiation [64]. Down-regulation of miR-29 and miR-448 increases the expression of c/EBP-α, PPAR-γ, and FABP4 and protects against loss of adipogenesis [65–67].

2.1 Mechanisms in White Adipogenesis

25

The increase of miR-27b in obesity blunts the induction of PPAR-γ and c/EBP-α [68–70]. Overexpression of miR-130a in obesity only suppresses PPAR-γ expression, while that of miR-138 suppresses PPAR-γ and c/EBP and FABP4 expression [71– 73]. MiR-361-5p and miR-574-5p impair white adipocyte maturation by repressing EBF1 but thereby may inhibit inflammation [74, 75]. MiR-519d suppresses the translation of the PPAR-α protein [76]. Overexpression of the H19 imprinted maternally expressed transcript lncRNA (H19) and miR-675, encoded by H19, inhibits adipogenic differentiation. H19 blocks histone deacetylases, thereby mimicking the effects of hypoxia, leading to impairment of insulin-induced glucose uptake [77, 78]. Tumor necrosis factor (TNF)-α impairs adipocyte differentiation by decreasing miR-103, PPAR-γ and FABP4, GLUT4, and adiponectin [79, 80]. Downregulation of mir-124 and the miR-140/nuclear paraspeckle assembly transcript (NEAT1)/maternally expressed 3 (MEG3) also inhibits adipocyte maturation [81–84]. MiR-155 is associated with adipocyte hypertrophy and lipid deposition, WAT inflammation, and obesity-associated with calorie excess [85]. Also, repression of MEG3 in NEAT1/miR-140/MEG3 paraspeckles results in fat cell hypertrophy [86]. Unexpectedly, the deficiency of miR-34a in mice was associated with obesity-associated with increased lipid deposition in white adipocytes [87, 88] (Fig. 2.1). The adipogenic differentiation induced non-coding RNA (ADINR) is transcribed from a ∼450 bp upstream of the c/EBP-α gene. ADINR recruits histone methyltransferase complexes to increase histone modification in the c/EBP-α locus [89]. The knockdown of the MIR31 host gene (MIR31HG) inhibits adipocyte differentiation by reducing active histone markers in the promoter of FABP4 [90]. LncRNA RP1120G13.3 attenuates adipogenesis by blunting the expression of PPAR-γ, c/EBP-α, and adiponectin [91]. However, it is unknown how their expressions change during the development of obesity.

2.2 Inflammation and Insulin Resistance in Obese White Adipose Tissue White fat cells secrete important hormone-like molecules such as leptin and adiponectin, influencing food intake and insulin secretion to increase glucose and insulin sensitivity [92]. Obesity and higher WAT mass are associated with increased secretion of leptin but decreased expression of leptin receptors (ObRs), leading to leptin resistance. ObRb is the only receptor that includes binding domains for MAPK8 (or JNK) and signal-transducing and activator of transcription (STAT) [93]. Besides, it phosphorylates PI3K and MAPK1, and MAPK2 [94–96]. Thus, impairment of ObRb ultimately leads to insulin resistance, implying an essential association between food intake and maintenance of energy balance by leptin and glucose metabolism. Leptin directly inhibits insulin secretion from the pancreas, whereas

26

2 Non-coding RNAs Related to Obesity

prolonged exposure to high insulin stimulates leptin expression [97]. Further, leptin significantly increases the suppressor of cytokine signaling 3 (SOCS3), inhibiting autophosphorylation of insulin receptors (IRs) and responsiveness to leptin [98–100]. Leptin also increases local expression of the inflammatory TNF-α, which induces insulin resistance by downregulating the tyrosine kinase activity of IR and decreasing the expression of GLUT4 [101, 102]. Angiotensin I converting enzyme 2 (ACE2) deficiency in obesity leads to an increase of inflammatory angiotensinogen (ANG II or AGT) and up-regulation of Ras proteins, binary switches, cycling between ON and OFF states during signal transduction, associated with increased ROS, glucose intolerance, and insulin resistance (Fig. 2.2). Obesity is associated with increased infiltration in WAT of monocytes, which differentiate into macrophages. This infiltration is a normal response to the growing mass associated with WAT hyperplasia. Insulin resistance shifts the balance from proinflammatory to anti-inflammatory cytokines and M2 to M1 macrophage polarization [103–105]. However, one must be aware that these two macrophage phenotypes are extremes of a continuum of functional states [106, 107]. Classical M1 activation of macrophages occurs following injury or infection dependent on interferon (IFN)-γ or TNF-α. M1 macrophages produce pro-inflammatory cytokines like interleukin (IL)1β, and IL12, and TNF-α. They also produce high ROS and nitrogen species [108]. IL4 and IL13, toll-like receptor (TLR), induce M2 macrophage polarization [109], together with IL1 receptor ligands and IL10 [110]. M2 macrophages produce meager amounts of pro-inflammatory cytokines but abundantly secrete anti-inflammatory cytokines like IL10, CCL18, and CCL22. Besides, M2 macrophages express the mannose receptor CD206 (or MRC1), the scavenging receptor CD163, and dendritic cell (DC)-specific intercellular adhesion molecule-3-grabbing non-integrin [111]. Also, the metabolic signature of M2 macrophages is different from that in M1 macrophages. Hypoxia, inducing hypoxia-inducible factor (HIF)-1α, AMPK, and nuclear factor kappa B (NFκB) signaling in M1 macrophages favor glycolysis and inhibit oxidative phosphorylation (OXPHOS). On the contrary, M2 cells are more dependent on OXPHOS and fatty acid oxidation [112, 113] (Fig. 2.2). Infiltrated monocytes differentiate into macrophages or dendritic cells (DCs) in obese WAT [114, 115]. Adipose tissue-derived high-mobility group B1 (HMGB1) protein activates TLR9 in the adipose-recruited DCs by transporting extracellular DNA through receptor for advanced glycation end products (AGEs) and induces production of IFN-α and IFN-β. They, in turn, help in M1 macrophage polarization of adipose-resident macrophages [116]. Like M1 macrophages, DCs undergo metabolic reprogramming from a predominantly OXPHOS to glycolysis required to mount immune response [116, 117] (Fig. 2.2). This immune response also involves T cells [118], natural killer (NK) cells, possibly interacting with macrophages [119], type 2 innate lymphoid cells [120], and mast cells [121]. During obesity, WAT is infiltrated by T cells, which along with the adipocytes themselves, secrete various cytokines and chemokines [122– 124]. Th1 polarization is associated with increased IFN-α and IL2 and decreased Th2-specific cytokines IL4, IL5, IL10, and IL13 [125–127]. This change in cytokine profile leads to M1 macrophage polarization and inflammation. Reduced Th2-like

2.2 Inflammation and Insulin Resistance in Obese White Adipose Tissue

27

Fig. 2.2 Non-coding RNAs in inflammation and insulin signaling in obese white adipose tissues. In obesity, the increase of lnc-leptin leads to a rise in leptin. In healthy white adipocytes, leptin, by interacting with ObR, induces JAK/STAT signaling, resulting in phosphorylation of PI3K and MAPK, and insulin receptor substrates IRS1 and IRS2 required for regulating food intake and energy expenditure and retaining insulin sensitivity. In obesity, the leptin/ObR interaction and downstream signaling is impaired, leading to leptin resistance and ultimately, insulin resistance. The increase of leptin also induces SOCS3 that reduces leptin signaling and induces inflammatory TNFα, thereby impairing GLUT4 expression and glucose uptake, forcing cells to use other energy sources like fatty acids. Increased leptin and ANG II are also associated with increased Ras and ROS, which increase insulin resistance. Insulin resistance is associated with increased infiltration of monocytes, macrophage accumulation, and macrophage M1 polarization, particularly induced by AGEs in patients with uncontrolled type 2 diabetes. Macrophage polarization and inflammation are due to the increase of miR-17, miR-27a, miR-34a, miR-103, miR-130b, miR-143-145, miR-146a/b, miR-155, miR-221, miR-335 and miR-377, and the decrease of miR-181b. The increase of miR-30a and miR223 may prevent this. Monocytes can also differentiate to DCs, dependent on miR-142. Activated M1 macrophages and DCs induce a shift in T cell immune response. The numbers of anti-inflammatory Th2, Treg, and ILC2 cells decrease while the numbers of inflammatory Th1 and Th17 cells increase. The latter is dependent on miR-326. The shift to inflammatory macrophages and T cells decreases

28

2 Non-coding RNAs Related to Obesity

 anti-inflammatory IL4, IL5, IL9, IL10, IL13, CCL18, and CCL22, and increases inflammatory IL-1β, IL2, IL17, and TNF-α and IFN-γ. The increase in inflammatory cells increases ROS release, exacerbating inflammation. TNF-α and AGEs impair SIRT1/FOXO1/c/EBP-α signaling in obese WAT and reduce adiponectin signaling. Adiponectin resistance may be due to increased miR-146b and miR-221 and decreased miR-21 and miR-193b. The reduction of adiponectin is associated with a decline of miR-146b and increased mitochondrial ROS and inflammation without affecting insulin sensitivity. The increase of miR-876-3p links insulin resistance to inflammation when adiponectin is low. Let-7 impairs mTORC1 in Tregs, leading to lipid deposition. Increased non-coding RNAs are in red, decreased in green

immune responses are also due to decreased innate lymphoid type 2 cells (ILC2), which upon activation by tissue-derived IL33 and IL25, secrete mostly IL4, IL5, IL9, and IL13 [128]. The lower number of T reg cells in obesity induces the infiltration of effector T cells and hampers the IL33-mediated shift from M1 to M2 macrophages in WAT and lipids’ metabolism [104, 129–139]. Besides, Th17 polarization increases IL17, impairing adipocyte differentiation, and causing glucose intolerance and insulin resistance [140, 141]. Activated DCs promote Th1/Th17 response by secreting IFN-γ, IL2, and IL17 [142–146] (Fig. 2.2). Natural Killer (NK) cells are a unique subset of T cells that recognize lipid antigens in the context of CD1d, which is mainly expressed by antigen-presenting cells, such as macrophages, DCs, and B cells [147–149]. Some groups reported a protective role of NK cells because obesity developed when invariant NK (iNK) cells were deficient. They demonstrated that iNK cells in adipose tissue produce anti-inflammatory cytokines, such as IL4 and IL10, in contrast to those in the spleen and liver [150– 152]. These Th2 cytokines induce M2 macrophages and suppress obesity-associated inflammation [153]. NK cells secrete the anti-inflammatory cytokine IL4, which substantially contributes to the improvement of glucose tolerance [154]. However, other groups have reported that obesity did not develop in the absence of NK cells. iNT cells produce pro-inflammatory cytokines, such as IFN-γ, associated with glucose intolerance in response to lipid excess in the body. Type II NK cells also exacerbate diet-induced obesity in the absence of iNKT cells [155, 156]. Finally, another study reported a neutral role of NK cells with no exact active role for skewing the environment toward either a Th1 or Th2 phenotype during the development of obesity [157] (Fig. 2.2). More mast cells occur in obese WAT, and lower mast cells protect against dietinduced obesity and diabetes. The deficiency of mast cells reduces body weight and inflammation, adipose angiogenesis, and apoptosis, thereby preventing diet-induced obesity and glucose intolerance [158]. In contrast, another study showed that mast cell number was not different between obese and lean humans, but that the degree of mast cell activation was only higher in patients with type 2 diabetes [159]. Also, mast cells may protect against obesity by stimulating WAT’s browning, discussed in the next section [160]. In contrast to leptin, adiponectin is inversely proportional to body fat content. Adiponectin levels already low in obese persons decreases further in subjects with diabetes and coronary artery disease. TNF-α and AGEs repress SIRT1, forkhead box (FOXO)-1, PGC-1α, adiponectin, and adiponectin receptor (ADIPOR1/R2).

2.2 Inflammation and Insulin Resistance in Obese White Adipose Tissue

29

The resulting adiponectin resistance leads to obesity-associated hyperglycemia and insulin resistance and inflammation [161–167]. A decrease of adiponectin may also lead to mitochondrial dysfunction associated with decreased mitochondrial antioxidant enzyme cytochrome oxidase 1 (MTCOI or COX1), PGC-1α, and OXPHOS, impairing fatty acid oxidation and inducing ROS generation and inflammation even when insulin sensitivity is normal [168] (Fig. 2.2).

2.2.1 Role of Non-coding RNAs in Inflammation and Insulin Resistance in Obese White Adipose Tissue Lnc-leptin, which is transcribed from an enhancer region upstream of leptin, increases leptin expression [169]. Increased expression of miR-17 [170], miR-103 [171], miR143-145 cluster [172], miR-146a [173–175], miR-146b [176], miR-221 [177] and miR-377 [178] are associated with obesity-associated insulin resistance and inflammation. The ADP-ribosylation factor 3 circular RNA (circARF3) may act as an endogenous miR-103 sponge, thereby restraining the NFκB-signaling pathway and suppressing the NLR family pyrin domain containing 3 (NLRP3) inflammasome activation. However, as mentioned above, this results in impaired adipocyte maturation [171]. MiR-130b, up-regulated in macrophages of high-fat diet mice, and miR-27a especially increased in obese diabetic patients, induce M1 macrophage polarization and adipose tissue inflammation by targeting PPAR-γ that is associated with glucose intolerance [179, 180]. Adipocyte-derived exosomes enriched in miR-34a inhibit M2 macrophage polarization and induce inflammation [88]. MiR-155 induces adipocyte hypertrophy and WAT inflammation, and insulin resistance. However, it may inhibit the secondary wave inflammation induced by the adipokine resistin in obesity [85, 181, 182]. The decrease in miR-181b also induces macrophage activation in adipose tissue via inhibiting PPAR-γ associated with IR [183–186]. The increase of miR-335 by leptin, resistin, and TNF-α in mature adipocytes is associated with adipose tissue inflammation, closing a vicious circle [187]. MiR-30a targets the transcription factor STAT1 to limit the pro-inflammatory cytokine interferon-γ (IFN-γ) actions that would otherwise restrict WAT expansion and decrease insulin sensitivity [63]. The increase in miR-223 in macrophages in obese WAT reduced TLR4 response and protected against M1 macrophage polarization [188, 189] (Fig. 2.2). Dendritic cells undergo metabolic reprogramming from OXPHOS to glycolysis to mount an immunogenic response. MiR-142 increased in obesity, regulates the immunogenic responses of DCs [190]. In the absence of miR-142, DCs fail to switch and show reduced production of pro-inflammatory cytokines and the ability to activate T cells [191]. MiR-326 participates in the polarization towards Th17, promoting the inflammatory state in the obesity-induced adipose tissue [192] (Fig. 2.2). The decrease of miR-21 is associated with decreased adiponectin mRNA and protein expression [193]. The decrease of miR-193b is associated with a decrease

30

2 Non-coding RNAs Related to Obesity

of both adiponectin and adiponectin regulators [193, 194]. An increase of miR-146b may block SIRT1/FOXO signaling [176]. MiR-221, up-regulated by leptin, directly down-regulates ADIPOR1 and impairs adiponectin action [195]. The decrease of miR-146b-5p in monocytes is associated with loss of the anti-inflammatory but not insulin signaling action of adiponectin [168]. The increase of miR-876-3p causes inflammation by inducing insulin resistance when adiponectin is low [196]. Let-7 represses the mammalian (or mechanistic) target of rapamycin complex 1 (mTORC1). This repression causes insulin resistance with increased NLR family pyrin domain containing 3 (NLRP3) inflammasome activation [197] (Fig. 2.2).

2.3 Mechanisms in Brown Adipogenesis and Thermogenesis In contrast to WAT, BAT functions to dissipate energy in response to cold exposure or overfeeding. BAT oxidizes fatty acids for thermogenesis, and the induction of BAT is part of combating obesity and associated metabolic diseases. Brown adipocytes derive from MYF5-positive MSCs. BMP4 and BMP7 induce them to differentiate to committed brown preadipocytes [198–200]. BMP4 and BMP7 activate a full brown adipogenesis program, including induction of early regulators of the PR/SET domain (PRDM)-4 [201] and PRDM16 [202], and PGC-1α [203]. SRYbox transcription factor (SOX) genes, which in MSCs increase c/EBP-β expression and favor adipogenesis, explain part of the BMP 7 response [204]. Further differentiation depends on adipogenic transcription factors c/EBPs and PPAR-γ [205]. PPAR-γ is the master transcription regulator of the general differentiation program of both brown and white adipocytes and therefore needs a fat lineage-specific regulation. EBF2 regulates PPAR-γ binding activity, favoring brown adipogenesis. Adipose tissue from EBF2-deficient mice displayed a loss of brown-specific characteristics and thermogenic capacity [206]. Besides, EBF2 regulates chromatin remodeling by interacting with the SWI/SNF related, matrix associated, actin-dependent regulator of chromatin, subfamily a, member 4 (SMARCA4 or BRG1), and the barrier to autointegration factor 1 (BANF or BAF [206, 207]. The EP300 interacting inhibitor of differentiation (EID)-1 codes for the adenovirus E1A-associated cellular p300 transcriptional co-activator protein that remodels chromatin and differentiates brown adipocytes. It is essential in the processes of cell proliferation and differentiation. EID1 mediates 3 -5 -cyclic adenosine monophosphate (cyclic AMP or cAMP) gene regulation by binding phosphorylated cAMP-responsive element-binding (CREB) protein (Fig. 2.3). BAT oxidizes fatty acids produced by triglyceride hydrolysis to generate heat and protect against hypothermia and obesity through non-shivering thermogenesis. Mechanistically, EBF1 and EBF2 promote thermogenesis by increasing the expression and activity of ERR-α and PGC1-α [208]. ERR-γ contributes to mitochondrial biogenesis, mitochondrial maintenance, vascularity, energy expenditure, and

2.3 Mechanisms in Brown Adipogenesis and Thermogenesis

31

Fig. 2.3 Non-coding RNAs in brown adipogenesis and thermogenesis. The decrease in miR193b-365 in obesity inhibits lineage determination to MYF5+ precursor cells. Precursors differentiate to committed brown preadipocytes through the action of BMP4, BMP7, ERR, PRDM16, PGC-1α, and SOX. Further differentiation to mature brown adipocytes involves BMP4, BMP7, SOX2, PRDM4 and PRDM16, PGC-1α, c/EBP-β, PPAR-γ, EBF2, EID1, and CREB, leading to the release of UCP1. In response to cold exposure, induction of β3-adrenergic signaling activates a thermogenesis program. This program involves NE/β-3 adrenergic receptor signaling and activation of PGC-1α, PPAR-γ, PRDM16, EBF1, EBF2, ERR-α, and ERR-γ, leading to the release of UCP1. UCP1 requires fatty acid oxidation to increase mitochondrial respiration. High levels of miR-27, miR-34a, miR-150, and miR-199a-214, and low miR-26a and miR30b/30c block full differentiation to brown adipocytes, including expression of UCP1. MiR-378, increased by leptin and TNF-α to block inflammation-associated obesity, miR-455, induced by BMP7, and the ROS-induced decrease of miR-133 restores full adipocyte differentiation. The increase of mir-32, miR-378, miR-455, and H19 responding to cold stimulates thermogenesis, while miR-199-214 block thermogenesis. Increased non-coding RNAs are in red, decreased in green

32

2 Non-coding RNAs Related to Obesity

mitochondrial uncoupling [209]. Mice deficient in ERR-γ in adipose tissue display whitening of BAT blunted thermogenic capacity, and failure to survive an acute cold challenge [210, 211]. Mechanistically, EBF1 and EBF2 promote thermogenesis by increasing the expression and activity of ERR-α and PGC1-α [208]. PGC-1α is the master regulator of mitochondrial biogenesis through its interaction with PPAR-γ [203, 212, 213]. Mice with a fat-specific knock-out of PGC-1α have increased cold sensitivity and decreased RNA expression of uncoupling protein (UCP)-1, mitochondrial genes, and substrate utilization genes [214]. PGC-1α is dependent on estrogenrelated receptors (ERRs). Thermogenesis is impaired in mice lacking adipose ERRs [211]. PRDM16 is another transcription factor required for thermogenesis. PPAR-γ stabilizes PRDM16 and diminishes responsiveness to IFN-α and IFN-β in adipose cells to promote thermogenic and mitochondrial function [215, 216]. Interestingly, brown adipocytes derived from PRDM16-knockout BAT had decreased expression of ERR-γ and BAT-selective ERR-γ target genes, including UCP1 and PPAR-α. Therefore, some PRDM16 effects are due to ERR-γ responsible for the synergy between PGC-1α and PRDM16 to maintain BAT identity (Fig. 2.3). Fatty acid oxidation is thus critical for this process as it increases mitochondrial respiration via the uncoupling of the mitochondrial electrochemical gradient via UCP1 [217, 218]. Fatty acids are required for UCP1-induced uncoupling. BAT thermogenesis and glucose uptake can, however, be uncoupled [219]. Consequently, mice with an adipose-specific deficit in fatty acid oxidation are severely cold intolerant, demonstrating an autonomous requirement for adipose fatty acid oxidation in cold-induced thermogenesis [220]. Cold exposure also increases UCP1-dependent thermogenesis. It involves OXPHOS, which ensures a higher supply of adenosine triphosphate (ATP) by increasing UCP1. [221] (Fig. 2.3).

2.3.1 Role of Non-coding RNAs in Brown Adipogenesis and Thermogenesis The decrease of miR-193b-365 impairs the differentiation of MSCs to brown adipocyte progenitor cells [222, 223]. MiR-27, up-regulated in obesity, represses PRDM16, PPAR-α, CREB, and in part, PGC-1α [224–226]. The increase of miR34a inhibits brown (and beige) fat formation in obesity by suppressing FGF21 and SIRT1 signaling leading to down-regulation of PRDM16, c/EBP-α, and c/EBP-β, PGC-1α, and UCP1 [87, 227]. MiR-150 increased in obesity directly represses PRDM16 and PGC-1α [228, 229]. The miR-199a-214 cluster suppresses PRDM16 and PGC-1α [230, 231]. MiR26a typically increases UCP1, down-regulated in obesity [232]. Decrease of miR30b and miR-30c leads to reduced UCP1 expression, without significant effects on the expression of PRDM16, PGC-1α, PPAR-γ, c/EBP-α, c/EBP-β, FABP4, and adiponectin [233, 234]. The ROS/NFκB-induced brown adipogenesis requires the down-regulation of miR-133, which results in increased expression of PRDM16

2.3 Mechanisms in Brown Adipogenesis and Thermogenesis

33

[235]. MiR-378 increased by TNF-α and leptin in obesity promotes thermogenesis in BAT and controls classical brown fat expansion to counteract inflammationinduced obesity [236–238]. MiR-455 induced by cold and BMP7 enhances brown adipocyte differentiation and thermogenesis [239]. MiR-32 and H19 also increase cold-induced brown adipogenesis, oxidative metabolism, mitochondrial respiration, and thermogenesis [240–242] (Fig. 2.3).

2.4 Mechanisms in Browning of White Adipose Tissues In adult humans, BAT is mainly composed of brown-like or beige adipocytes. However, some data indicate the persistence of classical BAT at some anatomical sites [243]. The total mass and activity of BAT are tightly linked to systemic energy and nutrient homeostasis. Brown adipocytes arise from progenitors expressing transmembrane protein 26 (TMEM26) and CD137 [244]. A percentage of these beige cells derive from smooth muscle cell-like cells that once expressed myosin heavy chain 11. Other brown-like cells originate from white adipocytes following exposure to PPAR-γ ligands [245–247]. This differentiation depends on the SIRT1 dependent deacetylation of PPAR-γ [248]. As in BAT, the emergence of cold-induced brown adipocytes in WAT depends on the β3-adrenergic receptor signaling [249]. Caloric restriction may also lead to white adipocytes’ browning by inducing eosinophil infiltration, Th2 cytokine signaling, and M2 macrophage polarization. However, Th2 cytokine signaling and M2 macrophage polarization are low in obesity [250]. Repression of IFN-signaling and activation of hedgehog signaling promote a white-to-brown metabolic conversion in human adipocytes [251]. Prolonged glucocorticoid suppresses the function of human BAT [252]. Despite originating from distinct progenitors, brown and beige adipocytes acquire remarkably similar molecular and metabolic characteristics during further differentiation through the action of a network of transcription factors and cofactors. It involves PRDM16, c/EBP-β, PGC-1α, and PPAR-γ signaling as in BAT, but also blocking of TGF-β/SMAD family member (SMAD)-3 signaling [253]. Transfection of FABP4-EID1 matures white adipocytes to beige adipocytes with a higher expression of PGC1-α and UCP1 [254]. Activation of cAMP and AMPK signaling pathways results in the “browning” phenotype, with smaller increases in body weight under a high-fat diet, lower fat deposits, increased β-oxidation of fatty acids, and oxygen consumption [255] (Fig. 2.4). Brown and beige adipocytes are structurally different. Mature beige adipocytes are paucilocular; they contain only a few lipid droplets. In contrast, brown adipocytes are multilocular; they include multiple lipid droplets [256]. Besides, beige and brown adipocytes differ in gene expression patterns. Corneodesmosin, Rh family B glycoprotein, and glutathione peroxidase 8 are highly expressed in beige adipocytes. Tripartite motif-containing 17 is even beige cell-specific. MAGE family member A1, NLR family, pyrin domain-containing 9C, solute carrier family 22 member 29, and kininogen 2 are brown cell-specific (Fig. 2.4).

34

2 Non-coding RNAs Related to Obesity

Fig. 2.4 Non-coding RNAs in browning of white adipocyte differentiation and thermogenesis. Brown-like or beige adipocytes derive from TMEM26+ and CD137+ precursor cells, induced by miR-133b, miR-196a, and miR-206, which block TGF-β and induce c/EBP-β expression. Other brown-like cells originate from white adipocytes following exposure to PPAR-γ ligands and SIRT1. Cold exposure, caloric restriction, Th2, and M2 macrophage infiltration, and repression of IFNγ signaling stimulates those white adipocytes to undergo browning. However, Th2 cells and M2 macrophages are reduced in obesity, impairing brown adipogenesis. Maturation of beige adipocytes involves BMP4, BMP7, PRDM16, c/EBP-β, PGC-1α, PPAR-γ. Besides, TGF-β/SMAD3 signaling needs to be blocked since SMAD3 blocks PGC-1α. It also involves cAMP/AMK signaling, all leading to the release of UCP1 and activation of mitochondrial genes. MiR-9 and miR-31, increased by the loss of silencing TINCR, and miR-155 impairs brown/beige adipocytes’ differentiation. The reduction of miR-125 and miR-494-3p may restore this differentiation. Cold exposure induces thermogenesis in the same way as in brown adipocytes. Increased non-coding RNAs are in red, decreased in green

2.4.1 Role of Non-coding RNAs in Browning of White Adipose Tissue MiR-133b, miR-196a, and miR-206 induce TMEM26+ and CD137+ precursors to differentiate to beige adipocytes by indirectly decreasing TGF-β1 and inducing c/EBP-β signaling by inhibiting homeobox (HOX)-C8 and HOXC9, which are reduced by fasting [257–259]. The increase of miR-9 impairs β3-adrenergic stimulated browning of WAT, thereby decreasing UCP1 [260]. The decrease of the lncRNA TINCR ubiquitin domain-containing (TINCR) may increase miR-31 that blocks browning of WAT [261, 262]. The rise of miR-155 blocks browning of WAT by silencing c/EBP-β [263]. The decrease of miR-125b-5p in obesity may lead to β3adrenoceptor-mediated induction of UCP1 [180, 264]. Interestingly, it did not alter

2.4 Mechanisms in Browning of White Adipose Tissues

35

the number/frequency of macrophage and DCs in the total stromal vascular fraction or intraperitoneal fluid [239]. Mild cold exposure of mice induced PGC1-α along with UCP1 in inguinal WAT by downregulating miR-494-3p [265, 266] (Fig. 2.4).

2.5 Leptin and Insulin in the Hypothalamus The hypothalamus monitors the modifications in metabolic parameters (blood glucose and lipids) and hormones (insulin or leptin). It elicits adaptive responses like food intake regulation or autonomic nervous system modulation. Within the hypothalamus, pro-opiomelanocortin (POMC) neurons are the first to respond to the circulating signals of hunger and satiety such as leptin, insulin, ghrelin, or glucose [267]. Insulin and leptin directly act on POMC neurons [268, 269]. The steroid receptor coactivator-1 interacts with phosphorylated STAT3, an activator of the leptin receptor, to potentiate POMC transcription [270, 271]. Leptindependent STAT3 phosphorylation is low within POMC neurons of high fat diet-fed mice. The expression of leptin receptor and SOCS3 was elevated, associated with increased susceptibility to obesity [272]. Of interest, the anti-inflammatory IL10 may substitute for leptin to activating STAT3 in the case of leptin deficiency [273]. Besides, leptin acts through the PI3K/AKT/MAPK pathways within POMC neurons [274]. PI3K coordinates the actions of leptin and insulin on POMC neurons [275]. Activated dynamin-related protein (pDRP1) suppresses leptin and glucose sensing of POMC neurons. The deletion of DRP1 increased mitochondrial size, ROS production, and neuronal activation, involving PPAR [276, 277]. POMC-specific ablation of mitofusin 2 (Mfn2) in mice resulted in a loss of mitochondria-endoplasmic reticulum (ER) contacts, defective POMC processing, ER stress-induced leptin resistance, reduced energy expenditure, and obesity [278]. Loss of transient receptor potential cation 5 in POMC neurons decreases energy expenditure and increases food intake resulting in elevated body weight [279]. ROS and leptin require mTORC1 in POMC neurons to increase POMC neurons’ oxidant levels and consequently decrease food intake [280]. Chronic stimulation of the leptin receptor and saturated fatty acid-induced inflammation causes leptin resistance in the hypothalamus [281]. Insulin and leptin act together on POMC neurons to promote WAT browning and weight loss [282]. The neuronal inositol-requiring enzyme 1 in POMC neurons is necessary for protection against ER stress, insulin resistance, and thermogenesis in brown adipose tissue [283]. The response of POMC neurons to insulin depends on the number of insulin receptors [284]. Mitofusin 1-mediated mitochondrial activity in POMC neurons is required for glucose-sensing and insulin release control [285]. Besides, insulin receptor (IR) expression in POMC neurons is linked to insulin action in adipose tissue [286]. Attenuation of (HIF)-2α in the high fat diet-fed mice is associated with impaired activation of the hypothalamic IR/insulin receptor substrate 2 (IRS2)/AKT/FOXO1 pathway in response to insulin [287].

36

2 Non-coding RNAs Related to Obesity

2.5.1 Non-coding RNAs Related to Leptin and Insulin in the Hypothalamus The Dicer loss in POMC neurons causes metabolic defects, an age-dependent decline in the number of Pomc mRNA-expressing cells. Mainly, miR-103 and miR-107 may be involved in the maturation of POMC progenitors [288]. MiR-7a, highly expressed in hypothalamic neurons, may regulate genes involved in body weight control [289]. Let-7a, mir-9*, mir-30b, mir-100a, mir-145, miR-200, and miR-208 are increased in the hypothalamus of high fat diet-fed rats. Their targets regulate insulin, leptin, adiponectin signaling, fatty acid and lipid metabolism, and inflammation [290]. MiR-200a, miR-200b, and miR-429 were highly expressed in the hypothalamus of obese ob/ob mice, associated with decreased IRS2 and leptin receptor expression, but were decreased by leptin [291]. Leptin inhibits the expression of miR-383, miR-384-3p, and miR-488 that bind to the 3’ untranslated regions of POMC mRNA [292]. Mir-383, mir-384-3p, and mir-488 are increased in diabetic mice with a non-functional leptin receptor [293].

References 1. Perez-Mancera, P. A., et al. (2007). Adipose tissue mass is modulated by SLUG (SNAI2). Human Molecular Genetics, 16, 2972–2986. https://doi.org/10.1093/hmg/ddm278. 2. Lv, J. W., et al. (2017). Inhibition of microRNA-214 promotes epithelial-mesenchymal transition process and induces interstitial cystitis in postmenopausal women by upregulating Mfn2. Experimental & Molecular Medicine, 49, e357. https://doi.org/10.1038/emm.2017.98. 3. Chen, Y., & Song, W. (2018). Wnt/catenin beta1/microRNA 183 predicts recurrence and prognosis of patients with colorectal cancer. Oncology Letters, 15, 4451–4456. https://doi. org/10.3892/ol.2018.7886. 4. Bikfalvi, A., Klein, S., Pintucci, G., & Rifkin, D. B. (1997). Biological roles of fibroblast growth factor-2. Endocrine Reviews, 18, 26–45. https://doi.org/10.1210/edrv.18.1.0292. 5. Widberg, C. H., et al. (2009). Fibroblast growth factor receptor 1 is a key regulator of early adipogenic events in human preadipocytes. American Journal of Physiology. Endocrinology and Metabolism, 296, E121–E131. https://doi.org/10.1152/ajpendo.90602.2008. 6. Jonker, J. W., et al. (2012). A PPARgamma-FGF1 axis is required for adaptive adipose remodelling and metabolic homeostasis. Nature, 485, 391–394. https://doi.org/10.1038/nat ure10998. 7. Zaragosi, L. E., Ailhaud, G., & Dani, C. (2006). Autocrine fibroblast growth factor 2 signaling is critical for self-renewal of human multipotent adipose-derived stem cells. Stem Cells, 24, 2412–2419. https://doi.org/10.1634/stemcells.2006-0006. 8. Lai, W. T., Krishnappa, V., & Phinney, D. G. (2011). Fibroblast growth factor 2 (Fgf2) inhibits differentiation of mesenchymal stem cells by inducing Twist2 and Spry4, blocking extracellular regulated kinase activation, and altering Fgf receptor expression levels. Stem Cells, 29, 1102–1111. https://doi.org/10.1002/stem.661. 9. Xiao, L., et al. (2010). Disruption of the Fgf2 gene activates the adipogenic and suppresses the osteogenic program in mesenchymal marrow stromal stem cells. Bone, 47, 360–370. https:// doi.org/10.1016/j.bone.2010.05.021. 10. Kim, S., Ahn, C., Bong, N., Choe, S., & Lee, D. K. (2015). Biphasic effects of FGF2 on adipogenesis. PLoS ONE, 10, e0120073. https://doi.org/10.1371/journal.pone.0120073.

References

37

11. Song, Z., et al. (2017). Cyclin C regulates adipogenesis by stimulating transcriptional activity of CCAAT/enhancer-binding protein alpha. Journal of Biological Chemistry, 292, 8918–8932. https://doi.org/10.1074/jbc.M117.776229. 12. Mitterberger, M. C., Lechner, S., Mattesich, M., & Zwerschke, W. (2014). Adipogenic differentiation is impaired in replicative senescent human subcutaneous adipose-derived stromal/progenitor cells. Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 69, 13–24. https://doi.org/10.1093/gerona/glt043. 13. Alcorta, D. A., et al. (1996). Involvement of the cyclin-dependent kinase inhibitor p16 (INK4a) in replicative senescence of normal human fibroblasts. Proceedings of the National Academy of Sciences of the United States of America, 93, 13742–13747. 14. Stein, G. H., Drullinger, L. F., Soulard, A., & Dulic, V. (1999). Differential roles for cyclindependent kinase inhibitors p21 and p16 in the mechanisms of senescence and differentiation in human fibroblasts. Molecular and Cellular Biology, 19, 2109–2117. 15. Wang, G. L., et al. (2006). Cyclin D3 maintains growth-inhibitory activity of C/EBPalpha by stabilizing C/EBPalpha-cdk2 and C/EBPalpha-Brm complexes. Molecular and Cellular Biology, 26, 2570–2582. https://doi.org/10.1128/MCB.26.7.2570-2582.2006. 16. Macotela, Y., et al. (2012). Intrinsic differences in adipocyte precursor cells from different white fat depots. Diabetes, 61, 1691–1699. https://doi.org/10.2337/db11-1753. 17. Lefterova, M. I., Haakonsson, A. K., Lazar, M. A., & Mandrup, S. (2014). PPARgamma and the global map of adipogenesis and beyond. Trends in Endocrinology and Metabolism, 25, 293–302. https://doi.org/10.1016/j.tem.2014.04.001. 18. Wang, Q. A., et al. (2015). Distinct regulatory mechanisms governing embryonic versus adult adipocyte maturation. Nature Cell Biology, 17, 1099–1111. https://doi.org/10.1038/ncb3217. 19. Kang, S., et al. (2012). Regulation of early adipose commitment by Zfp521. PLoS Biology, 10, e1001433. https://doi.org/10.1371/journal.pbio.1001433. 20. Oishi, Y., et al. (2005). Kruppel-like transcription factor KLF5 is a key regulator of adipocyte differentiation. Cell Metabolism, 1, 27–39. https://doi.org/10.1016/j.cmet.2004.11.005. 21. Mori, T., et al. (2005). Role of Kruppel-like factor 15 (KLF15) in transcriptional regulation of adipogenesis. Journal of Biological Chemistry, 280, 12867–12875. https://doi.org/10.1074/ jbc.M410515200. 22. Birsoy, K., Chen, Z., & Friedman, J. (2008). Transcriptional regulation of adipogenesis by KLF4. Cell Metabolism, 7, 339–347. https://doi.org/10.1016/j.cmet.2008.02.001. 23. Chen, Z., Torrens, J. I., Anand, A., Spiegelman, B. M., & Friedman, J. M. (2005). Krox20 stimulates adipogenesis via C/EBPbeta-dependent and -independent mechanisms. Cell Metabolism, 1, 93–106. https://doi.org/10.1016/j.cmet.2004.12.009. 24. Li, D., et al. (2005). Kruppel-like factor-6 promotes preadipocyte differentiation through histone deacetylase 3-dependent repression of DLK1. Journal of Biological Chemistry, 280, 26941–26952. https://doi.org/10.1074/jbc.M500463200. 25. Griffin, M. J., et al. (2013). Early B-cell factor-1 (EBF1) is a key regulator of metabolic and inflammatory signaling pathways in mature adipocytes. Journal of Biological Chemistry, 288, 35925–35939. https://doi.org/10.1074/jbc.M113.491936. 26. Mercken, E. M., et al. (2013). Calorie restriction in humans inhibits the PI3K/AKT pathway and induces a younger transcription profile. Aging Cell, 12, 645–651. https://doi.org/10.1111/ acel.12088. 27. Schultze, S. M., Hemmings, B. A., Niessen, M., & Tschopp, O. (2012). PI3K/AKT, MAPK and AMPK signalling: Protein kinases in glucose homeostasis. Expert Reviews in Molecular Medicine, 14, e1. https://doi.org/10.1017/S1462399411002109. 28. Xing, H., et al. (1997). TNF alpha-mediated inhibition and reversal of adipocyte differentiation is accompanied by suppressed expression of PPARgamma without effects on Pref-1 expression. Endocrinology, 138, 2776–2783. https://doi.org/10.1210/endo.138.7.5242. 29. Xu, B., et al. (2010). Multiple roles for the non-coding RNA SRA in regulation of adipogenesis and insulin sensitivity. PLoS ONE, 5, e14199. https://doi.org/10.1371/journal.pone.0014199. 30. Chen, G., et al. (2016). LncRNA SRA promotes hepatic steatosis through repressing the expression of adipose triglyceride lipase (ATGL). Scientific Reports, 6, 35531. https://doi. org/10.1038/srep35531.

38

2 Non-coding RNAs Related to Obesity

31. Shan, T., Liu, W., & Kuang, S. (2013). Fatty acid binding protein 4 expression marks a population of adipocyte progenitors in white and brown adipose tissues. The FASEB Journal, 27, 277–287. https://doi.org/10.1096/fj.12-211516. 32. Prentice, K. J., Saksi, J., & Hotamisligil, G. S. (2019). Adipokine FABP4 integrates energy stores and counterregulatory metabolic responses. Journal of Lipid Research, 60, 734–740. https://doi.org/10.1194/jlr.S091793. 33. Furuhashi, M., Saitoh, S., Shimamoto, K., & Miura, T. (2014). Fatty acid-binding protein 4 (FABP4): Pathophysiological insights and potent clinical biomarker of metabolic and cardiovascular diseases. Clinical Medicine Insights: Cardiology, 8, 23–33. https://doi.org/10.4137/ CMC.S17067. 34. Steen, K. A., Xu, H. & Bernlohr, D. A. (2017). FABP4/aP2 regulates macrophage redox signaling and inflammasome activation via control of UCP2. Molecular and Cellular Biology, 37. https://doi.org/10.1128/mcb.00282-16. 35. Gan, L., Liu, Z., Cao, W., Zhang, Z., & Sun, C. (2015). FABP4 reversed the regulation of leptin on mitochondrial fatty acid oxidation in mice adipocytes. Scientific Reports, 5, 13588. https://doi.org/10.1038/srep13588. 36. van Harmelen, V., Ryden, M., Sjolin, E., & Hoffstedt, J. (2007). A role of lipin in human obesity and insulin resistance: Relation to adipocyte glucose transport and GLUT4 expression. Journal of Lipid Research, 48, 201–206. https://doi.org/10.1194/jlr.M600272-JLR200. 37. Schreiber, I., et al. (2017). BMPs as new insulin sensitizers: Enhanced glucose uptake in mature 3T3-L1 adipocytes via PPARgamma and GLUT4 upregulation. Scientific Reports, 7, 17192. https://doi.org/10.1038/s41598-017-17595-5. 38. Fang, P., et al. (2017). Baicalin against obesity and insulin resistance through activation of AKT/AS160/GLUT4 pathway. Molecular and Cellular Endocrinology, 448, 77–86. https:// doi.org/10.1016/j.mce.2017.03.027. 39. Bonnelye, E., & Aubin, J. E. (2013). An energetic orphan in an endocrine tissue: A revised perspective of the function of estrogen receptor-related receptor alpha in bone and cartilage. Journal of Bone and Mineral Research, 28, 225–233. https://doi.org/10.1002/jbmr.1836. 40. Schreiber, S. N., Knutti, D., Brogli, K., Uhlmann, T., & Kralli, A. (2003). The transcriptional coactivator PGC-1 regulates the expression and activity of the orphan nuclear receptor estrogen-related receptor alpha (ERRalpha). Journal of Biological Chemistry, 278, 9013–9018. https://doi.org/10.1074/jbc.M212923200. 41. Nie, Y., & Wong, C. (2009). Suppressing the activity of ERRalpha in 3T3-L1 adipocytes reduces mitochondrial biogenesis but enhances glycolysis and basal glucose uptake. Journal of Cellular and Molecular Medicine, 13, 3051–3060. https://doi.org/10.1111/j.1582-4934. 2008.00382.x. 42. Wessels, B., et al. (2019). Adipose mitochondrial respiratory capacity in obesity is impaired independently of glycemic status of tissue donors. Obesity (Silver Spring), 27, 756–766. https://doi.org/10.1002/oby.22435. 43. Schottl, T., Kappler, L., Fromme, T., & Klingenspor, M. (2015). Limited OXPHOS capacity in white adipocytes is a hallmark of obesity in laboratory mice irrespective of the glucose tolerance status. Molecular Metabolism, 4, 631–642. https://doi.org/10.1016/j.molmet.2015. 07.001. 44. Keuper, M., et al. (2014). Spare mitochondrial respiratory capacity permits human adipocytes to maintain ATP homeostasis under hypoglycemic conditions. The FASEB Journal, 28, 761– 770. https://doi.org/10.1096/fj.13-238725. 45. Han, C. Y., et al. (2012). NADPH oxidase-derived reactive oxygen species increases expression of monocyte chemotactic factor genes in cultured adipocytes. Journal of Biological Chemistry, 287, 10379–10393. https://doi.org/10.1074/jbc.M111.304998. 46. Kajimoto, K., Minami, Y., & Harashima, H. (2014). Cytoprotective role of the fatty acid binding protein 4 against oxidative and endoplasmic reticulum stress in 3T3-L1 adipocytes. FEBS Open Bio, 4, 602–610. https://doi.org/10.1016/j.fob.2014.06.008. 47. Longo, M., et al. (2019). Adipose tissue dysfunction as determinant of obesity-associated metabolic complications. International Journal of Molecular Sciences, 20. https://doi.org/10. 3390/ijms20092358.

References

39

48. Mondanizadeh, M., et al. (2015). MicroRNA-124 regulates neuronal differentiation of mesenchymal stem cells by targeting Sp1 mRNA. Journal of Cellular Biochemistry, 116, 943–953. https://doi.org/10.1002/jcb.25045. 49. Hoseinzadeh, S., Atashi, A., Soleimani, M., Alizadeh, E., & Zarghami, N. (2016). MiR-221inhibited adipose tissue-derived mesenchymal stem cells bioengineered in a nano-hydroxy apatite scaffold. In Vitro Cellular & Developmental Biology—Animal, 52, 479–487. https:// doi.org/10.1007/s11626-015-9992-x. 50. Liu, X., et al. (2019). miR-145-5p suppresses osteogenic differentiation of adipose-derived stem cells by targeting semaphorin 3A. In Vitro Cellular & Developmental Biology—Animal, 55, 189–202. https://doi.org/10.1007/s11626-019-00318-7. 51. Alt, E. U., et al. (2012). Aging alters tissue resident mesenchymal stem cell properties. Stem Cell Research, 8, 215–225. https://doi.org/10.1016/j.scr.2011.11.002. 52. Kim, Y. J., et al. (2012). MicroRNA 21 regulates the proliferation of human adipose tissuederived mesenchymal stem cells and high-fat diet-induced obesity alters microRNA 21 expression in white adipose tissues. Journal of Cellular Physiology, 227, 183–193. https://doi.org/ 10.1002/jcp.22716. 53. Alicka, M., Major, P., Wysocki, M., & Marycz, K. (2019). Adipose-derived mesenchymal stem cells isolated from patients with Type 2 diabetes show reduced “Stemness” through an altered secretome profile, impaired anti-oxidative protection, and mitochondrial dynamics deterioration. Journal of Clinical Medicine, 8. https://doi.org/10.3390/jcm8060765. 54. Liu, H., et al. (2018). Long noncoding RNA GAS5 suppresses 3T3-L1 cells adipogenesis through miR-21a-5p/PTEN signal pathway. DNA and Cell Biology, 37, 767–777. https://doi. org/10.1089/dna.2018.4264. 55. Li, M., et al. (2018). The long noncoding RNA GAS5 negatively regulates the adipogenic differentiation of MSCs by modulating the miR-18a/CTGF axis as a ceRNA. Cell Death and Disease, 9, 554. https://doi.org/10.1038/s41419-018-0627-5. 56. Knarr, M., Nagaraj, A. B., Kwiatkowski, L. J., & DiFeo, A. (2019). miR-181a modulates circadian rhythm in immortalized bone marrow and adipose derived stromal cells and promotes differentiation through the regulation of PER3. Scientific Reports, 9, 307. https://doi.org/10. 1038/s41598-018-36425-w. 57. Divoux, A., et al. (2014). Identification of a novel lncRNA in gluteal adipose tissue and evidence for its positive effect on preadipocyte differentiation. Obesity (Silver Spring), 22, 1781–1785. https://doi.org/10.1002/oby.20793. 58. Chen, S. Z., et al. (2016). The miR-181d-regulated metalloproteinase Adamts1 enzymatically impairs adipogenesis via ECM remodeling. Cell Death and Differentiation, 23, 1778–1791. https://doi.org/10.1038/cdd.2016.66. 59. Zaragosi, L. E., et al. (2011). Small RNA sequencing reveals miR-642a-3p as a novel adipocyte-specific microRNA and miR-30 as a key regulator of human adipogenesis. Genome Biology, 12, R64. https://doi.org/10.1186/gb-2011-12-7-r64. 60. Cui, S., et al. (2018). MiR-30a-5p accelerates adipogenesis by negatively regulating Sirtuin 1. International Journal of Clinical and Experimental Pathology, 11, 5203–5212. 61. Zhu, E., et al. (2019). Long noncoding RNA Plnc1 controls adipocyte differentiation by regulating peroxisome proliferator-activated receptor gamma. The FASEB Journal, 33, 2396– 2408. https://doi.org/10.1096/fj.201800739RRR. 62. Shen, L., et al. (2018). miR-144-3p Promotes Adipogenesis Through Releasing C/EBPalpha From Klf3 and CtBP2. Frontiers in Genetics, 9, 677. https://doi.org/10.3389/fgene.2018. 00677. 63. Koh, E. H., et al. (2018). miR-30a remodels subcutaneous adipose tissue inflammation to improve insulin sensitivity in obesity. Diabetes, 67, 2541–2553. https://doi.org/10.2337/db171378. 64. Zhang, L., Zhang, D., Qin, Z. Y., Li, J., & Shen, Z. Y. (2020). The role and possible mechanism of long noncoding RNA PVT1 in modulating 3T3-L1 preadipocyte proliferation and differentiation. IUBMB Life. https://doi.org/10.1002/iub.2269.

40

2 Non-coding RNAs Related to Obesity

65. Pescador, N., et al. (2013). Serum circulating microRNA profiling for identification of potential type 2 diabetes and obesity biomarkers. PLoS ONE, 8, e77251. https://doi.org/10.1371/ journal.pone.0077251. 66. Kinoshita, M., et al. (2010). Regulation of adipocyte differentiation by activation of serotonin (5-HT) receptors 5-HT2AR and 5-HT2CR and involvement of microRNA-448-mediated repression of KLF5. Molecular Endocrinology, 24, 1978–1987. https://doi.org/10.1210/me. 2010-0054. 67. Glantschnig, C., et al. (2019). A miR-29a-driven negative feedback loop regulates peripheral glucocorticoid receptor signaling. The FASEB Journal, 33, 5924–5941. https://doi.org/10. 1096/fj.201801385RR. 68. Lin, Q., Gao, Z., Alarcon, R. M., Ye, J., & Yun, Z. (2009). A role of miR-27 in the regulation of adipogenesis. FEBS Journal, 276, 2348–2358. 69. Katada, T., et al. (2009). microRNA expression profile in undifferentiated gastric cancer. International Journal of Oncology, 34, 537–542. 70. Karbiener, M., et al. (2009). microRNA miR-27b impairs human adipocyte differentiation and targets PPARgamma. Biochemical and Biophysical Research Communications, 390, 247–251. https://doi.org/10.1016/j.bbrc.2009.09.098. 71. Perri, R., Nares, S., Zhang, S., Barros, S. P., & Offenbacher, S. (2012). MicroRNA modulation in obesity and periodontitis. Journal of Dental Research, 91, 33–38. https://doi.org/10.1177/ 0022034511425045. 72. Wei, W., et al. (2017). miR-130a regulates differential lipid accumulation between intramuscular and subcutaneous adipose tissues of pigs via suppressing PPARG expression. Gene, 636, 23–29. https://doi.org/10.1016/j.gene.2017.08.036. 73. Yang, Z., et al. (2011). MicroRNA hsa-miR-138 inhibits adipogenic differentiation of human adipose tissue-derived mesenchymal stem cells through adenovirus EID-1. Stem Cells and Development, 20, 259–267. https://doi.org/10.1089/scd.2010.0072. 74. Mazzu, Y. Z., et al. (2017). miR-193b-regulated signaling networks serve as tumor suppressors in liposarcoma and promote adipogenesis in adipose-derived stem cells. Cancer Research, 77, 5728–5740. https://doi.org/10.1158/0008-5472.CAN-16-2253. 75. Belarbi, Y., et al. (2017). MicroRNAs-361-5p and miR-574-5p associate with human adipose morphology and regulate EBF1 expression in white adipose tissue. Molecular and Cellular Endocrinology. https://doi.org/10.1016/j.mce.2017.11.018. 76. Martinelli, R., et al. (2010). miR-519d overexpression is associated with human obesity. Obesity (Silver Spring), 18, 2170–2176. https://doi.org/10.1038/oby.2009.474. 77. Bricambert, J., et al. (2016). Impaired histone deacetylases 5 and 6 expression mimics the effects of obesity and hypoxia on adipocyte function. Molecular Metabolism, 5, 1200–1207. https://doi.org/10.1016/j.molmet.2016.09.011. 78. Huang, Y., et al. (2016). Long non-coding RNA H19 inhibits adipocyte differentiation of bone marrow mesenchymal stem cells through epigenetic modulation of histone deacetylases. Scientific Reports, 6, 28897. https://doi.org/10.1038/srep28897. 79. Xie, H., Lim, B., & Lodish, H. F. (2009). MicroRNAs induced during adipogenesis that accelerate fat cell development are downregulated in obesity. Diabetes, 58, 1050–1057. https:// doi.org/10.2337/db08-1299. 80. Chou, W. W., et al. (2013). Decreased microRNA-221 is associated with high levels of TNFalpha in human adipose tissue-derived mesenchymal stem cells from obese woman. Cellular Physiology and Biochemistry, 32, 127–137. https://doi.org/10.1159/000350131. 81. Qadir, A. S., Woo, K. M., Ryoo, H. M., & Baek, J. H. (2013). Insulin suppresses distalless homeobox 5 expression through the up-regulation of microRNA-124 in 3T3-L1 cells. Experimental Cell Research, 319, 2125–2134. https://doi.org/10.1016/j.yexcr.2013.04.020. 82. Dallagiovanna, B., et al. (2017). lncRNAs are associated with polysomes during adiposederived stem cell differentiation. Gene, 610, 103–111. https://doi.org/10.1016/j.gene.2017. 02.004. 83. Gernapudi, R., et al. (2016). MicroRNA 140 promotes expression of long noncoding RNA NEAT1 in adipogenesis. Molecular and Cellular Biology, 36, 30–38. https://doi.org/10.1128/ MCB.00702-15.

References

41

84. Li, Z., et al. (2017). Long non-coding RNA MEG3 inhibits adipogenesis and promotes osteogenesis of human adipose-derived mesenchymal stem cells via miR-140-5p. Molecular and Cellular Biochemistry. https://doi.org/10.1007/s11010-017-3015-z. 85. Gaudet, A. D., et al. (2016). miR-155 deletion in female mice prevents diet-induced obesity. Scientific Reports, 6, 22862. https://doi.org/10.1038/srep22862. 86. Parekh, V. I., Modali, S. D., Desai, S. S., & Agarwal, S. K. (2015). Consequence of menin deficiency in mouse adipocytes derived by in vitro differentiation. International Journal of Endocrinology, 2015, 149826. https://doi.org/10.1155/2015/149826. 87. Lavery, C. A., et al. (2016). miR-34a(-/-) mice are susceptible to diet-induced obesity. Obesity (Silver Spring), 24, 1741–1751. https://doi.org/10.1002/oby.21561. 88. Pan, Y., et al. (2019). Adipocyte-secreted exosomal microRNA-34a inhibits M2 macrophage polarization to promote obesity-induced adipose inflammation. Journal of Clinical Investigation, 129, 834–849. https://doi.org/10.1172/JCI123069. 89. Xiao, T., et al. (2015). Long noncoding RNA ADINR regulates adipogenesis by transcriptionally activating C/EBPalpha. Stem Cell Reports, 5, 856–865. https://doi.org/10.1016/j.ste mcr.2015.09.007. 90. Huang, Y., et al. (2017). Knockdown of lncRNA MIR31HG inhibits adipocyte differentiation of human adipose-derived stem cells via histone modification of FABP4. Scientific Reports, 7, 8080. https://doi.org/10.1038/s41598-017-08131-6. 91. Liu, Y., et al. (2018). Integrated analysis of long noncoding RNA and mRNA expression profile in children with obesity by microarray analysis. Scientific Reports, 8, 8750. https:// doi.org/10.1038/s41598-018-27113-w. 92. Cohen, P., & Spiegelman, B. M. (2016). Cell biology of fat storage. Molecular Biology of the Cell, 27, 2523–2527. https://doi.org/10.1091/mbc.E15-10-0749. 93. Ghilardi, N., et al. (1996). Defective STAT signaling by the leptin receptor in diabetic mice. Proceedings of the National Academy of Sciences of the United States of America, 93, 6231– 6235. 94. Niswender, K. D., et al. (2001). Intracellular signalling. Key enzyme in leptin-induced anorexia. Nature, 413, 794–795. https://doi.org/10.1038/35101657. 95. Banks, A. S., Davis, S. M., Bates, S. H., & Myers, M. G., Jr. (2000). Activation of downstream signals by the long form of the leptin receptor. Journal of Biological Chemistry, 275, 14563– 14572. 96. Kim, Y. B., Uotani, S., Pierroz, D. D., Flier, J. S., & Kahn, B. B. (2000). In vivo administration of leptin activates signal transduction directly in insulin-sensitive tissues: Overlapping but distinct pathways from insulin. Endocrinology, 141, 2328–2339. https://doi.org/10.1210/ endo.141.7.7536. 97. Shimomura, I., Hammer, R. E., Ikemoto, S., Brown, M. S., & Goldstein, J. L. (1999). Leptin reverses insulin resistance and diabetes mellitus in mice with congenital lipodystrophy. Nature, 401, 73–76. https://doi.org/10.1038/43448. 98. Perez, C., et al. (2004). Leptin impairs insulin signaling in rat adipocytes. Diabetes, 53, 347–353. 99. Bjorbaek, C., El-Haschimi, K., Frantz, J. D., & Flier, J. S. (1999). The role of SOCS-3 in leptin signaling and leptin resistance. Journal of Biological Chemistry, 274, 30059–30065. 100. Senn, J. J., et al. (2003). Suppressor of cytokine signaling-3 (SOCS-3), a potential mediator of interleukin-6-dependent insulin resistance in hepatocytes. Journal of Biological Chemistry, 278, 13740–13746. https://doi.org/10.1074/jbc.M210689200. 101. Abel, E. D., et al. (2001). Adipose-selective targeting of the GLUT4 gene impairs insulin action in muscle and liver. Nature, 409, 729–733. https://doi.org/10.1038/35055575. 102. Shepherd, P. R., & Kahn, B. B. (1999). Glucose transporters and insulin action–implications for insulin resistance and diabetes mellitus. New England Journal of Medicine, 341, 248–257. https://doi.org/10.1056/NEJM199907223410406. 103. Thomas, D., & Apovian, C. (2017). Macrophage functions in lean and obese adipose tissue. Metabolism, 72, 120–143. https://doi.org/10.1016/j.metabol.2017.04.005.

42

2 Non-coding RNAs Related to Obesity

104. Lumeng, C. N., Bodzin, J. L., & Saltiel, A. R. (2007). Obesity induces a phenotypic switch in adipose tissue macrophage polarization. Journal of Clinical Investigation, 117, 175–184. https://doi.org/10.1172/JCI29881. 105. Lumeng, C. N., Deyoung, S. M., Bodzin, J. L., & Saltiel, A. R. (2007). Increased inflammatory properties of adipose tissue macrophages recruited during diet-induced obesity. Diabetes, 56, 16–23. https://doi.org/10.2337/db06-1076. 106. Mantovani, A., Sozzani, S., Locati, M., Allavena, P., & Sica, A. (2002). Macrophage polarization: tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes. Trends in Immunology, 23, 549–555. 107. Genin, M., Clement, F., Fattaccioli, A., Raes, M., & Michiels, C. (2015). M1 and M2 macrophages derived from THP-1 cells differentially modulate the response of cancer cells to etoposide. BMC Cancer, 15, 577. https://doi.org/10.1186/s12885-015-1546-9. 108. Gordon, S. (2003). Alternative activation of macrophages. Nature Reviews Immunology, 3, 23–35. https://doi.org/10.1038/nri978. 109. Bosisio, D., et al. (2002). Stimulation of toll-like receptor 4 expression in human mononuclear phagocytes by interferon-gamma: A molecular basis for priming and synergism with bacterial lipopolysaccharide. Blood, 99, 3427–3431. 110. Mantovani, A., et al. (2004). The chemokine system in diverse forms of macrophage activation and polarization. Trends in Immunology, 25, 677–686. https://doi.org/10.1016/j.it.2004. 09.015. 111. Martinez, F. O., Helming, L., & Gordon, S. (2009). Alternative activation of macrophages: an immunologic functional perspective. Annual Review of Immunology, 27, 451–483. https:// doi.org/10.1146/annurev.immunol.021908.132532. 112. Viola, A., Munari, F., Sanchez-Rodriguez, R., Scolaro, T., & Castegna, A. (2019). The metabolic signature of macrophage responses. Frontiers in Immunology, 10, 1462. https:// doi.org/10.3389/fimmu.2019.01462. 113. Smolkova, K., et al. (2011). Waves of gene regulation suppress and then restore oxidative phosphorylation in cancer cells. International Journal of Biochemistry & Cell Biology, 43, 950–968. https://doi.org/10.1016/j.biocel.2010.05.003. 114. Brake, D. K., Smith, E. O., Mersmann, H., Smith, C. W., & Robker, R. L. (2006). ICAM1 expression in adipose tissue: Effects of diet-induced obesity in mice. American Journal of Physiology. Cell Physiology, 291, C1232–C1239. https://doi.org/10.1152/ajpcell.00008. 2006. 115. Wu, H., et al. (2010). CD11c expression in adipose tissue and blood and its role in diet-induced obesity. Arteriosclerosis, Thrombosis, and Vascular Biology, 30, 186–192. https://doi.org/10. 1161/ATVBAHA.109.198044. 116. Ghosh, A. R., et al. (2016). Adipose recruitment and activation of plasmacytoid dendritic cells fuel metaflammation. Diabetes, 65, 3440–3452. https://doi.org/10.2337/db16-0331. 117. Kelly, B., & O’Neill, L. A. (2015). Metabolic reprogramming in macrophages and dendritic cells in innate immunity. Cell Research, 25, 771–784. https://doi.org/10.1038/cr.2015.68. 118. Mathis, D. (2013). Immunological goings-on in visceral adipose tissue. Cell Metabolism, 17, 851–859. https://doi.org/10.1016/j.cmet.2013.05.008. 119. Zhang, H., et al. (2017). M2-specific reduction of CD1d switches NKT cell-mediated immune responses and triggers metaflammation in adipose tissue. Cellular & Molecular Immunology. https://doi.org/10.1038/cmi.2017.11. 120. Molofsky, A. B., et al. (2013). Innate lymphoid type 2 cells sustain visceral adipose tissue eosinophils and alternatively activated macrophages. Journal of Experimental Medicine, 210, 535–549. https://doi.org/10.1084/jem.20121964. 121. Hirai, S., et al. (2014). Involvement of mast cells in adipose tissue fibrosis. American Journal of Physiology. Endocrinology and Metabolism, 306, E247–E255. https://doi.org/10.1152/ajp endo.00056.2013. 122. Wu, H., et al. (2007). T-cell accumulation and regulated on activation, normal T cell expressed and secreted upregulation in adipose tissue in obesity. Circulation, 115, 1029–1038. https:// doi.org/10.1161/CIRCULATIONAHA.106.638379.

References

43

123. Kintscher, U., et al. (2008). T-lymphocyte infiltration in visceral adipose tissue: A primary event in adipose tissue inflammation and the development of obesity-mediated insulin resistance. Arteriosclerosis, Thrombosis, and Vascular Biology, 28, 1304–1310. https://doi.org/10. 1161/ATVBAHA.108.165100. 124. Lago, F., Dieguez, C., Gomez-Reino, J., & Gualillo, O. (2007). Adipokines as emerging mediators of immune response and inflammation. Nature Clinical Practice Rheumatology, 3, 716–724. https://doi.org/10.1038/ncprheum0674. 125. Mattioli, B., Straface, E., Quaranta, M. G., Giordani, L., & Viora, M. (2005). Leptin promotes differentiation and survival of human dendritic cells and licenses them for Th1 priming. Journal of Immunology, 174, 6820–6828. 126. Martin-Romero, C., Santos-Alvarez, J., Goberna, R., & Sanchez-Margalet, V. (2000). Human leptin enhances activation and proliferation of human circulating T lymphocytes. Cellular Immunology, 199, 15–24. https://doi.org/10.1006/cimm.1999.1594. 127. Batra, A., et al. (2010). Leptin: A critical regulator of CD4+ T-cell polarization in vitro and in vivo. Endocrinology, 151, 56–62. https://doi.org/10.1210/en.2009-0565. 128. Chalubinski, M., Luczak, E., Wojdan, K., Gorzelak-Pabis, P., & Broncel, M. (2016). Innate lymphoid cells type 2—Emerging immune regulators of obesity and atherosclerosis. Immunology Letters, 179, 43–46. https://doi.org/10.1016/j.imlet.2016.09.007. 129. Rocha, V. Z., et al. (2008). Interferon-gamma, a Th1 cytokine, regulates fat inflammation: A role for adaptive immunity in obesity. Circulation Research, 103, 467–476. https://doi.org/ 10.1161/CIRCRESAHA.108.177105. 130. Nishimura, S., et al. (2009). CD8+ effector T cells contribute to macrophage recruitment and adipose tissue inflammation in obesity. Nature Medicine, 15, 914–920. https://doi.org/10. 1038/nm.1964. 131. Winer, S., et al. (2009). Normalization of obesity-associated insulin resistance through immunotherapy. Nature Medicine, 15, 921–929. https://doi.org/10.1038/nm.2001. 132. Feuerer, M., et al. (2009). Lean, but not obese, fat is enriched for a unique population of regulatory T cells that affect metabolic parameters. Nature Medicine, 15, 930–939. https:// doi.org/10.1038/nm.2002. 133. Miller, A. M., et al. (2010). Interleukin-33 induces protective effects in adipose tissue inflammation during obesity in mice. Circulation Research, 107, 650–658. https://doi.org/10.1161/ CIRCRESAHA.110.218867. 134. Onodera, T., et al. (2015). Adipose tissue macrophages induce PPARgamma-high FOXP3(+) regulatory T cells. Scientific Reports, 5, 16801. https://doi.org/10.1038/srep16801. 135. Eller, K., et al. (2011). Potential role of regulatory T cells in reversing obesity-linked insulin resistance and diabetic nephropathy. Diabetes, 60, 2954–2962. https://doi.org/10.2337/db110358. 136. Feuerer, M., Hill, J. A., Mathis, D., & Benoist, C. (2009). Foxp3+ regulatory T cells: Differentiation, specification, subphenotypes. Nature Immunology, 10, 689–695. https://doi.org/10. 1038/ni.1760. 137. Kolodin, D., et al. (2015). Antigen- and cytokine-driven accumulation of regulatory T cells in visceral adipose tissue of lean mice. Cell Metabolism, 21, 543–557. https://doi.org/10.1016/ j.cmet.2015.03.005. 138. Layman, A. A. K., et al. (2017). Ndfip1 restricts mTORC1 signalling and glycolysis in regulatory T cells to prevent autoinflammatory disease. Nature Communications, 8, 15677. https:// doi.org/10.1038/ncomms15677. 139. Zeng, H., et al. (2013). mTORC1 couples immune signals and metabolic programming to establish T(reg)-cell function. Nature, 499, 485–490. https://doi.org/10.1038/nature12297. 140. Zuniga, L. A., et al. (2010). IL-17 regulates adipogenesis, glucose homeostasis, and obesity. Journal of Immunology, 185, 6947–6959. https://doi.org/10.4049/jimmunol.1001269. 141. Eljaafari, A., et al. (2015). Adipose tissue-derived stem cells from obese subjects contribute to inflammation and reduced insulin response in adipocytes through differential regulation of the Th1/Th17 balance and monocyte activation. Diabetes, 64, 2477–2488. https://doi.org/10. 2337/db15-0162.

44

2 Non-coding RNAs Related to Obesity

142. Chamilos, G., et al. (2010). Generation of IL-23 producing dendritic cells (DCs) by airborne fungi regulates fungal pathogenicity via the induction of T(H)-17 responses. PLoS ONE, 5, e12955. https://doi.org/10.1371/journal.pone.0012955. 143. Fransen, J. H., et al. (2009). Mouse dendritic cells matured by ingestion of apoptotic blebs induce T cells to produce interleukin-17. Arthritis and Rheumatism, 60, 2304–2313. https:// doi.org/10.1002/art.24719. 144. Han, J. W., et al. (2008). Vessel wall-embedded dendritic cells induce T-cell autoreactivity and initiate vascular inflammation. Circulation Research, 102, 546–553. https://doi.org/10. 1161/CIRCRESAHA.107.161653. 145. Chen, Y., et al. (2014). Adipose tissue dendritic cells enhances inflammation by prompting the generation of Th17 cells. PLoS ONE, 9, e92450. https://doi.org/10.1371/journal.pone.009 2450. 146. Ghosh, S., & Lora, J. M. (2016). Suppression of TH17-mediated pathology through BET bromodomain inhibition. Drug Discovery Today: Technologies, 19, 39–44. https://doi.org/10. 1016/j.ddtec.2016.06.002. 147. Satoh, M., & Iwabuchi, K. (2016). Communication between natural killer T cells and adipocytes in obesity. Adipocyte, 5, 389–393. https://doi.org/10.1080/21623945.2016.124 1913. 148. Van Kaer, L. (2007). NKT cells: T lymphocytes with innate effector functions. Current Opinion in Immunology, 19, 354–364. https://doi.org/10.1016/j.coi.2007.03.001. 149. Bendelac, A., Savage, P. B., & Teyton, L. (2007). The biology of NKT cells. Annual Review of Immunology, 25, 297–336. https://doi.org/10.1146/annurev.immunol.25.022106.141711. 150. Lynch, L., et al. (2012). Adipose tissue invariant NKT cells protect against diet-induced obesity and metabolic disorder through regulatory cytokine production. Immunity, 37, 574– 587. https://doi.org/10.1016/j.immuni.2012.06.016. 151. Schipper, H. S., et al. (2012). Natural killer T cells in adipose tissue prevent insulin resistance. Journal of Clinical Investigation, 122, 3343–3354. https://doi.org/10.1172/JCI62739. 152. Sag, D., Krause, P., Hedrick, C. C., Kronenberg, M., & Wingender, G. (2014). IL-10producing NKT10 cells are a distinct regulatory invariant NKT cell subset. Journal of Clinical Investigation, 124, 3725–3740. https://doi.org/10.1172/JCI72308. 153. Lynch, L., et al. (2015). Regulatory iNKT cells lack expression of the transcription factor PLZF and control the homeostasis of T(reg) cells and macrophages in adipose tissue. Nature Immunology, 16, 85–95. https://doi.org/10.1038/ni.3047. 154. Saito, M., Kaburagi, M., Otokuni, K., & Takahashi, G. (2017). Functional role of natural killer T cells in non-obese pre-diabetes model mice. Cytotechnology. https://doi.org/10.1007/s10 616-017-0157-5. 155. Wu, L., et al. (2012). Activation of invariant natural killer T cells by lipid excess promotes tissue inflammation, insulin resistance, and hepatic steatosis in obese mice. Proceedings of the National Academy of Sciences of the United States of America, 109, E1143–E1152. https:// doi.org/10.1073/pnas.1200498109. 156. Ohmura, K., et al. (2010). Natural killer T cells are involved in adipose tissues inflammation and glucose intolerance in diet-induced obese mice. Arteriosclerosis, Thrombosis, and Vascular Biology, 30, 193–199. https://doi.org/10.1161/ATVBAHA.109.198614. 157. Mantell, B. S., et al. (2011). Mice lacking NKT cells but with a complete complement of CD8+ T-cells are not protected against the metabolic abnormalities of diet-induced obesity. PLoS ONE, 6, e19831. https://doi.org/10.1371/journal.pone.0019831. 158. Liu, J., et al. (2009). Genetic deficiency and pharmacological stabilization of mast cells reduce diet-induced obesity and diabetes in mice. Nature Medicine, 15, 940–945. https://doi.org/10. 1038/nm.1994. 159. Divoux, A., et al. (2012). Mast cells in human adipose tissue: link with morbid obesity, inflammatory status, and diabetes. Journal of Clinical Endocrinology and Metabolism, 97, E1677–E1685. https://doi.org/10.1210/jc.2012-1532. 160. Finlin, B. S., et al. (2017). Mast cells promote seasonal white adipose beiging in humans. Diabetes, 66, 1237–1246. https://doi.org/10.2337/db16-1057.

References

45

161. Uribarri, J., et al. (2011). Restriction of advanced glycation end products improves insulin resistance in human type 2 diabetes: Potential role of AGER1 and SIRT1. Diabetes Care, 34, 1610–1616. https://doi.org/10.2337/dc11-0091. 162. Nakae, J., et al. (2008). Forkhead transcription factor FoxO1 in adipose tissue regulates energy storage and expenditure. Diabetes, 57, 563–576. https://doi.org/10.2337/db07-0698. 163. Whitehead, J. P., Richards, A. A., Hickman, I. J., Macdonald, G. A., & Prins, J. B. (2006). Adiponectin—A key adipokine in the metabolic syndrome. Diabetes, Obesity & Metabolism, 8, 264–280. https://doi.org/10.1111/j.1463-1326.2005.00510.x. 164. Ryden, M., & Arner, P. (2007). Tumour necrosis factor-alpha in human adipose tissue—From signalling mechanisms to clinical implications. Journal of Internal Medicine, 262, 431–438. https://doi.org/10.1111/j.1365-2796.2007.01854.x. 165. van Stijn, C. M., Kim, J., Lusis, A. J., Barish, G. D., & Tangirala, R. K. (2015). Macrophage polarization phenotype regulates adiponectin receptor expression and adiponectin antiinflammatory response. The FASEB Journal, 29, 636–649. https://doi.org/10.1096/fj.14253831. 166. Lin, Z., et al. (2013). Adiponectin mediates the metabolic effects of FGF21 on glucose homeostasis and insulin sensitivity in mice. Cell Metabolism, 17, 779–789. https://doi.org/10.1016/ j.cmet.2013.04.005. 167. Xia, J. Y., et al. (2018). Acute loss of adipose tissue-derived adiponectin triggers immediate metabolic deterioration in mice. Diabetologia, 61, 932–941. https://doi.org/10.1007/s00125017-4516-8. 168. Hulsmans, M., Van Dooren, E., Mathieu, C., & Holvoet, P. (2012). Decrease of miR-146b-5p in monocytes during obesity is associated with loss of the anti-inflammatory but not insulin signaling action of adiponectin. PLoS ONE, 7, e32794. https://doi.org/10.1371/journal.pone. 0032794. 169. Lo, K. A., et al. (2018). Adipocyte long-noncoding RNA transcriptome analysis of obese mice identified lnc-leptin, which regulates leptin. Diabetes, 67, 1045–1056. https://doi.org/ 10.2337/db17-0526. 170. Heneghan, H. M., Miller, N., McAnena, O. J., O’Brien, T., & Kerin, M. J. (2011). Differential miRNA expression in omental adipose tissue and in the circulation of obese patients identifies novel metabolic biomarkers. Journal of Clinical Endocrinology and Metabolism, 96, E846– E850. https://doi.org/10.1210/jc.2010-2701. 171. Zhang, Z., et al. (2019). circARF3 alleviates mitophagy-mediated inflammation by targeting miR-103/TRAF3 in mouse adipose tissue. Molecular Therapy. Nucleic Acids, 14, 192–203. https://doi.org/10.1016/j.omtn.2018.11.014. 172. Lorente-Cebrian, S., et al. (2014). MicroRNAs regulate human adipocyte lipolysis: effects of miR-145 are linked to TNF-alpha. PLoS ONE, 9, e86800. https://doi.org/10.1371/journal. pone.0086800. 173. Jordan, S. D., et al. (2011). Obesity-induced overexpression of miRNA-143 inhibits insulinstimulated AKT activation and impairs glucose metabolism. Nature Cell Biology, 13, 434–446. https://doi.org/10.1038/ncb2211. 174. Nunez Lopez, Y. O., Garufi, G., Pasarica, M., & Seyhan, A. A. (2018). Elevated and correlated expressions of miR-24, miR-30d, miR-146a, and SFRP-4 in human abdominal adipose tissue play a role in adiposity and insulin resistance. International Journal of Endocrinology, 2018, 7351902. https://doi.org/10.1155/2018/7351902. 175. Wu, D., et al. (2016). miR-146a-5p inhibits TNF-alpha-induced adipogenesis via targeting insulin receptor in primary porcine adipocytes. Journal of Lipid Research, 57, 1360–1372. https://doi.org/10.1194/jlr.M062497. 176. Ahn, J., Lee, H., Jung, C. H., Jeon, T. I., & Ha, T. Y. (2013). MicroRNA-146b promotes adipogenesis by suppressing the SIRT1-FOXO1 cascade. EMBO Molecular Medicine, 5, 1602–1612. https://doi.org/10.1002/emmm.201302647. 177. Peng, J., et al. (2017). miR-221 negatively regulates inflammation and insulin sensitivity in white adipose tissue by repression of sirtuin-1 (SIRT1). Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb.26589.

46

2 Non-coding RNAs Related to Obesity

178. Peng, J., et al. (2017). MiR-377 promotes white adipose tissue inflammation and decreases insulin sensitivity in obesity via suppression of sirtuin-1 (SIRT1). Oncotarget, 8, 70550– 70563. https://doi.org/10.18632/oncotarget.19742. 179. Zhang, M., Zhou, Z., Wang, J., & Li, S. (2016). MiR-130b promotes obesity associated adipose tissue inflammation and insulin resistance in diabetes mice through alleviating M2 macrophage polarization via repression of PPAR-gamma. Immunology Letters, 180, 1–8. https://doi.org/10.1016/j.imlet.2016.10.004. 180. Villard, A., Marchand, L., Thivolet, C. & Rome, S. (2015). Diagnostic value of cell-free circulating microRNAs for obesity and type 2 diabetes: A meta-analysis. Journal of Molecular Biomarkers & Diagnosis, 6. https://doi.org/10.4172/2155-9929.1000251. 181. Ying, W., et al. (2017). Adipose tissue macrophage-derived exosomal miRNAs can modulate in vivo and in vitro insulin sensitivity. Cell, 171, 372–384 e312. https://doi.org/10.1016/j.cell. 2017.08.035. 182. Johnson, C., et al. (2018). Increased expression of resistin in microRNA-155-deficient white adipose tissues may be a possible driver of metabolically healthy obesity transition to classical obesity. Frontiers in Physiology, 9, 1297. https://doi.org/10.3389/fphys.2018.01297. 183. Sun, X., et al. (2016). MicroRNA-181b improves glucose homeostasis and insulin sensitivity by regulating endothelial function in white adipose tissue. Circulation Research, 118, 810– 821. https://doi.org/10.1161/CIRCRESAHA.115.308166. 184. Yao, F., et al. (2017). Adipogenic miR-27a in adipose tissue upregulates macrophage activation via inhibiting PPARgamma of insulin resistance induced by high-fat diet-associated obesity. Experimental Cell Research, 355, 105–112. https://doi.org/10.1016/j.yexcr.2017.03.060. 185. Yu, Y., et al. (2018). Adipocyte-derived exosomal MiR-27a induces insulin resistance in skeletal muscle through repression of PPARgamma. Theranostics, 8, 2171–2188. https://doi. org/10.7150/thno.22565. 186. Virtue, A. T., et al. (2019). The gut microbiota regulates white adipose tissue inflammation and obesity via a family of microRNAs. Science Translational Medicine, 11. https://doi.org/ 10.1126/scitranslmed.aav1892. 187. Zhu, L., et al. (2014). MiR-335, an adipogenesis-related microRNA, is involved in adipose tissue inflammation. Cell Biochemistry and Biophysics, 68, 283–290. https://doi.org/10.1007/ s12013-013-9708-3. 188. Zhuang, G., et al. (2012). A novel regulator of macrophage activation: miR-223 in obesityassociated adipose tissue inflammation. Circulation, 125, 2892–2903. https://doi.org/10.1161/ CIRCULATIONAHA.111.087817. 189. Deiuliis, J. A., et al. (2016). Visceral adipose microRNA 223 Is upregulated in human and murine obesity and modulates the inflammatory phenotype of macrophages. PLoS ONE, 11, e0165962. https://doi.org/10.1371/journal.pone.0165962. 190. Prats-Puig, A., et al. (2013). Changes in circulating microRNAs are associated with childhood obesity. Journal of Clinical Endocrinology and Metabolism, 98, E1655–E1660. https://doi. org/10.1210/jc.2013-1496. 191. Sun, Y., et al. (2019). miR-142 controls metabolic reprogramming that regulates dendritic cell activation. Journal of Clinical Investigation, 130, 2029–2042. https://doi.org/10.1172/ JCI123839. 192. Vega-Cardenas, M., et al. (2019). Increased levels of adipose tissue-resident Th17 cells in obesity associated with miR-326. Immunology Letters. https://doi.org/10.1016/j.imlet.2019. 05.010. 193. Kang, M., et al. (2013). Role of microRNA-21 in regulating 3T3-L1 adipocyte differentiation and adiponectin expression. Molecular Biology Reports, 40, 5027–5034. https://doi.org/10. 1007/s11033-013-2603-6. 194. Belarbi, Y., et al. (2015). MicroRNA-193b controls adiponectin production in human white adipose tissue. Journal of Clinical Endocrinology and Metabolism, 100, E1084–E1088. https://doi.org/10.1210/jc.2015-1530. 195. Meerson, A., et al. (2013). Human adipose microRNA-221 is upregulated in obesity and affects fat metabolism downstream of leptin and TNF-alpha. Diabetologia, 56, 1971–1979. https://doi.org/10.1007/s00125-013-2950-9.

References

47

196. Rajan, S., et al. (2018). miR-876-3p regulates glucose homeostasis and insulin sensitivity by targeting adiponectin. Journal of Endocrinology, 239, 1–17. https://doi.org/10.1530/JOE-170387. 197. Dubinsky, A. N., et al. (2014). Let-7 coordinately suppresses components of the amino acid sensing pathway to repress mTORC1 and induce autophagy. Cell Metabolism, 20, 626–638. https://doi.org/10.1016/j.cmet.2014.09.001. 198. Hoffmann, J. M., et al. (2017). BMP4 gene therapy in mature mice reduces BAT activation but protects from obesity by browning subcutaneous adipose tissue. Cell Reports, 20, 1038–1049. https://doi.org/10.1016/j.celrep.2017.07.020. 199. Boon, M. R., et al. (2013). BMP7 activates brown adipose tissue and reduces diet-induced obesity only at subthermoneutrality. PLoS ONE, 8, e74083. https://doi.org/10.1371/journal. pone.0074083. 200. Elsen, M., et al. (2014). BMP4 and BMP7 induce the white-to-brown transition of primary human adipose stem cells. American Journal of Physiology. Cell Physiology, 306, C431–C440. https://doi.org/10.1152/ajpcell.00290.2013. 201. Song, N. J., et al. (2016). Prdm4 induction by the small molecule butein promotes white adipose tissue browning. Nature Chemical Biology, 12, 479–481. https://doi.org/10.1038/nch embio.2081. 202. Seale, P., et al. (2007). Transcriptional control of brown fat determination by PRDM16. Cell Metabolism, 6, 38–54. https://doi.org/10.1016/j.cmet.2007.06.001. 203. Puigserver, P., et al. (1998). A cold-inducible coactivator of nuclear receptors linked to adaptive thermogenesis. Cell, 92, 829–839. 204. Stockl, S., et al. (2013). Sox9 modulates cell survival and adipogenic differentiation of multipotent adult rat mesenchymal stem cells. Journal of Cell Science, 126, 2890–2902. https:// doi.org/10.1242/jcs.124305. 205. Kong, X., et al. (2014). IRF4 is a key thermogenic transcriptional partner of PGC-1alpha. Cell, 158, 69–83. https://doi.org/10.1016/j.cell.2014.04.049. 206. Rajakumari, S., et al. (2013). EBF2 determines and maintains brown adipocyte identity. Cell Metabolism, 17, 562–574. https://doi.org/10.1016/j.cmet.2013.01.015. 207. Shapira, S. N., et al. (2017). EBF2 transcriptionally regulates brown adipogenesis via the histone reader DPF3 and the BAF chromatin remodeling complex. Genes & Development, 31, 660–673. https://doi.org/10.1101/gad.294405.116. 208. Angueira, A. R., et al. (2020). Early B cell factor activity controls developmental and adaptive thermogenic gene programming in adipocytes. Cell Reports, 30, 2869–2878 e2864. https:// doi.org/10.1016/j.celrep.2020.02.023. 209. Eichner, L. J., & Giguere, V. (2011). Estrogen related receptors (ERRs): A new dawn in transcriptional control of mitochondrial gene networks. Mitochondrion, 11, 544–552. https:// doi.org/10.1016/j.mito.2011.03.121. 210. Ahmadian, M., et al. (2018). ERRgamma preserves brown fat innate thermogenic activity. Cell Reports, 22, 2849–2859. https://doi.org/10.1016/j.celrep.2018.02.061. 211. Brown, E. L., et al. (2018). Estrogen-related receptors mediate the adaptive response of brown adipose tissue to adrenergic stimulation. iScience, 2, 221–237. https://doi.org/10.1016/j.isci. 2018.03.005. 212. Wu, Z., et al. (1999). Mechanisms controlling mitochondrial biogenesis and respiration through the thermogenic coactivator PGC-1. Cell, 98, 115–124. https://doi.org/10.1016/ S0092-8674(00)80611-X. 213. Uldry, M., et al. (2006). Complementary action of the PGC-1 coactivators in mitochondrial biogenesis and brown fat differentiation. Cell Metabolism, 3, 333–341. https://doi.org/10. 1016/j.cmet.2006.04.002. 214. Kleiner, S., et al. (2012). Development of insulin resistance in mice lacking PGC-1alpha in adipose tissues. Proceedings of the National Academy of Sciences of the United States of America, 109, 9635–9640. https://doi.org/10.1073/pnas.1207287109. 215. Kissig, M., et al. (2017). PRDM16 represses the type I interferon response in adipocytes to promote mitochondrial and thermogenic programing. EMBO Journal, 36, 1528–1542. https:// doi.org/10.15252/embj.201695588.

48

2 Non-coding RNAs Related to Obesity

216. Ohno, H., Shinoda, K., Spiegelman, B. M., & Kajimura, S. (2012). PPARgamma agonists induce a white-to-brown fat conversion through stabilization of PRDM16 protein. Cell Metabolism, 15, 395–404. https://doi.org/10.1016/j.cmet.2012.01.019. 217. Guerra, C., et al. (1998). Abnormal nonshivering thermogenesis in mice with inherited defects of fatty acid oxidation. Journal of Clinical Investigation, 102, 1724–1731. https://doi.org/10. 1172/JCI4532. 218. Fedorenko, A., Lishko, P. V., & Kirichok, Y. (2012). Mechanism of fatty-acid-dependent UCP1 uncoupling in brown fat mitochondria. Cell, 151, 400–413. https://doi.org/10.1016/j. cell.2012.09.010. 219. Olsen, J. M., et al. (2017). beta3-Adrenergically induced glucose uptake in brown adipose tissue is independent of UCP1 presence or activity: Mediation through the mTOR pathway. Molecular Metabolism, 6, 611–619. https://doi.org/10.1016/j.molmet.2017.02.006. 220. Ellis, J. M., et al. (2010). Adipose acyl-CoA synthetase-1 directs fatty acids toward betaoxidation and is required for cold thermogenesis. Cell Metabolism, 12, 53–64. https://doi.org/ 10.1016/j.cmet.2010.05.012. 221. Madreiter-Sokolowski, C. T., Sokolowski, A. A., Waldeck-Weiermair, M., Malli, R. & Graier, W. F. (2018). Targeting mitochondria to counteract age-related cellular dysfunction. Genes (Basel), 9. https://doi.org/10.3390/genes9030165. 222. Sun, L., et al. (2011). Mir193b-365 is essential for brown fat differentiation. Nature Cell Biology, 13, 958–965. https://doi.org/10.1038/ncb2286. 223. Arner, E., et al. (2012). Adipose tissue microRNAs as regulators of CCL2 production in human obesity. Diabetes, 61, 1986–1993. https://doi.org/10.2337/db11-1508. 224. Sun, L., & Trajkovski, M. (2014). MiR-27 orchestrates the transcriptional regulation of brown adipogenesis. Metabolism, 63, 272–282. https://doi.org/10.1016/j.metabol.2013.10.004. 225. Kong, X., et al. (2015). Glucocorticoids transcriptionally regulate miR-27b expression promoting body fat accumulation via suppressing the browning of white adipose tissue. Diabetes, 64, 393–404. https://doi.org/10.2337/db14-0395. 226. Chen, S. Z., et al. (2015). miR-27 impairs the adipogenic lineage commitment via targeting lysyl oxidase. Obesity (Silver Spring), 23, 2445–2453. https://doi.org/10.1002/oby.21319. 227. Hijmans, J. G., et al. (2018). Influence of overweight and obesity on circulating inflammationrelated microrna. Microrna. https://doi.org/10.2174/2211536607666180402120806. 228. Carreras-Badosa, G., et al. (2015). Altered circulating miRNA expression profile in pregestational and gestational obesity. Journal of Clinical Endocrinology and Metabolism, 100, E1446–E1456. https://doi.org/10.1210/jc.2015-2872. 229. Chou, C. F., et al. (2014). KSRP ablation enhances brown fat gene program in white adipose tissue through reduced miR-150 expression. Diabetes, 63, 2949–2961. https://doi.org/10. 2337/db13-1901. 230. He, L., et al. (2018). Obesity-associated miR-199a/214 cluster inhibits adipose browning via PRDM16-PGC-1alpha transcriptional network. Diabetes, 67, 2585–2600. https://doi.org/10. 2337/db18-0626. 231. Gao, Y., et al. (2018). miR-199a-3p regulates brown adipocyte differentiation through mTOR signaling pathway. Molecular and Cellular Endocrinology, 476, 155–164. https://doi.org/10. 1016/j.mce.2018.05.005. 232. Karbiener, M., et al. (2014). MicroRNA-26 family is required for human adipogenesis and drives characteristics of brown adipocytes. Stem Cells, 32, 1578–1590. https://doi.org/10. 1002/stem.1603. 233. Hsieh, C. H., et al. (2015). Weight-reduction through a low-fat diet causes differential expression of circulating microRNAs in obese C57BL/6 mice. BMC Genomics, 16, 699. https://doi. org/10.1186/s12864-015-1896-3. 234. Hu, F., et al. (2015). miR-30 promotes thermogenesis and the development of beige fat by targeting RIP140. Diabetes, 64, 2056–2068. https://doi.org/10.2337/db14-1117. 235. Morozzi, G., et al. (2017). Oxidative stress-induced S100B accumulation converts myoblasts into brown adipocytes via an NF-kappaB/YY1/miR-133 axis and NF-kappaB/YY1/BMP-7 axis. Cell Death and Differentiation, 24, 2077–2088. https://doi.org/10.1038/cdd.2017.132.

References

49

236. Pan, D., et al. (2014). MicroRNA-378 controls classical brown fat expansion to counteract obesity. Nature Communications, 5, 4725. https://doi.org/10.1038/ncomms5725. 237. Kim, J., et al. (2016). Eicosapentaenoic acid potentiates brown thermogenesis through FFAR4dependent Up-regulation of miR-30b and miR-378. Journal of Biological Chemistry, 291, 20551–20562. https://doi.org/10.1074/jbc.M116.721480. 238. Xu, L. L., et al. (2014). TNF-alpha, IL-6, and leptin increase the expression of miR-378, an adipogenesis-related microRNA in human adipocytes. Cell Biochemistry and Biophysics, 70, 771–776. https://doi.org/10.1007/s12013-014-9980-x. 239. Zhang, H., et al. (2015). MicroRNA-455 regulates brown adipogenesis via a novel HIF1anAMPK-PGC1alpha signaling network. EMBO Reports, 16, 1378–1393. https://doi.org/10. 15252/embr.201540837. 240. Ng, R., et al. (2017). miRNA-32 drives brown fat thermogenesis and trans-activates subcutaneous white fat browning in mice. Cell Reports, 19, 1229–1246. https://doi.org/10.1016/j.cel rep.2017.04.035. 241. Schmidt, E., et al. (2018). LincRNA H19 protects from dietary obesity by constraining expression of monoallelic genes in brown fat. Nature Communications, 9, 3622. https://doi.org/10. 1038/s41467-018-05933-8. 242. Shamsi, F., Zhang, H. & Tseng, Y. H. (2017). MicroRNA regulation of brown adipogenesis and thermogenic energy expenditure. Frontiers in Endocrinology (Lausanne), 8, 205. https:// doi.org/10.3389/fendo.2017.00205. 243. Giralt, M., & Villarroya, F. (2013). White, brown, beige/brite: Different adipose cells for different functions? Endocrinology, 154, 2992–3000. https://doi.org/10.1210/en.2013-1403. 244. Wu, J., et al. (2012). Beige adipocytes are a distinct type of thermogenic fat cell in mouse and human. Cell, 150, 366–376. https://doi.org/10.1016/j.cell.2012.05.016. 245. Vernochet, C., et al. (2009). C/EBPalpha and the corepressors CtBP1 and CtBP2 regulate repression of select visceral white adipose genes during induction of the brown phenotype in white adipocytes by peroxisome proliferator-activated receptor gamma agonists. Molecular and Cellular Biology, 29, 4714–4728. https://doi.org/10.1128/MCB.01899-08. 246. Rosen, E. D., & Spiegelman, B. M. (2014). What we talk about when we talk about fat. Cell, 156, 20–44. https://doi.org/10.1016/j.cell.2013.12.012. 247. Lazar, M. A. (2008). Developmental biology. How now, brown fat? Science, 321, 1048– 1049.https://doi.org/10.1126/science.1164094 (2008). 248. Qiang, L., et al. (2012). Brown remodeling of white adipose tissue by SirT1-dependent deacetylation of Ppargamma. Cell, 150, 620–632. https://doi.org/10.1016/j.cell.2012.06.027. 249. Barbatelli, G., et al. (2010). The emergence of cold-induced brown adipocytes in mouse white fat depots is determined predominantly by white to brown adipocyte transdifferentiation. American Journal of Physiology. Endocrinology and Metabolism, 298, E1244–E1253. https:// doi.org/10.1152/ajpendo.00600.2009. 250. Fabbiano, S., et al. (2016). Caloric restriction leads to browning of white adipose tissue through type 2 immune signaling. Cell Metabolism, 24, 434–446. https://doi.org/10.1016/j. cmet.2016.07.023. 251. Moisan, A., et al. (2015). White-to-brown metabolic conversion of human adipocytes by JAK inhibition. Nature Cell Biology, 17, 57–67. https://doi.org/10.1038/ncb3075. 252. Thuzar, M., et al. (2017). Glucocorticoids suppress brown adipose tissue function in humans: a double-blind placebo-controlled study. Diabetes, Obesity & Metabolism. https://doi.org/10. 1111/dom.13157. 253. Yadav, H., et al. (2011). Protection from obesity and diabetes by blockade of TGF-beta/Smad3 signaling. Cell Metabolism, 14, 67–79. https://doi.org/10.1016/j.cmet.2011.04.013. 254. Vargas, D., et al. (2016). Regulation of human subcutaneous adipocyte differentiation by EID1. Journal of Molecular Endocrinology, 56, 113–122. https://doi.org/10.1530/JME-150148. 255. Chung, Y. W., et al. (2017). White to beige conversion in PDE3B KO adipose tissue through activation of AMPK signaling and mitochondrial function. Scientific Reports, 7, 40445. https:// doi.org/10.1038/srep40445.

50

2 Non-coding RNAs Related to Obesity

256. Wang, H., Liu, L., Lin, J. Z., Aprahamian, T. R., & Farmer, S. R. (2016). Browning of white adipose tissue with roscovitine induces a distinct population of UCP1(+) adipocytes. Cell Metabolism, 24, 835–847. https://doi.org/10.1016/j.cmet.2016.10.005. 257. Jespersen, N. Z., et al. (2013). A classical brown adipose tissue mRNA signature partly overlaps with brite in the supraclavicular region of adult humans. Cell Metabolism, 17, 798– 805. https://doi.org/10.1016/j.cmet.2013.04.011. 258. Yamamoto, Y., et al. (2010). Adipose depots possess unique developmental gene signatures. Obesity (Silver Spring), 18, 872–878. https://doi.org/10.1038/oby.2009.512. 259. Kang, T., et al. (2013). MicroRNA-27 (miR-27) targets prohibitin and impairs adipocyte differentiation and mitochondrial function in human adipose-derived stem cells. Journal of Biological Chemistry, 288, 34394–34402. https://doi.org/10.1074/jbc.M113.514372. 260. Zheng, Z., et al. (2014). Regulation of UCP1 in the browning of epididymal adipose tissue by beta3-adrenergic agonist: A role for microRNAs. International Journal of Endocrinology, 2014, 530636. https://doi.org/10.1155/2014/530636. 261. Liu, Y., et al. (2018). LncRNA TINCR/miR-31-5p/C/EBP-alpha feedback loop modulates the adipogenic differentiation process in human adipose tissue-derived mesenchymal stem cells. Stem Cell Research, 32, 35–42. https://doi.org/10.1016/j.scr.2018.08.016. 262. Gottmann, P., et al. (2018). A computational biology approach of a genome-wide screen connected miRNAs to obesity and type 2 diabetes. Molecular Metabolism, 11, 145–159. https://doi.org/10.1016/j.molmet.2018.03.005. 263. Chen, Y., et al. (2013). miR-155 regulates differentiation of brown and beige adipocytes via a bistable circuit. Nature Communications, 4, 1769. https://doi.org/10.1038/ncomms2742. 264. Giroud, M., et al. (2016). miR-125b affects mitochondrial biogenesis and impairs brite adipocyte formation and function. Molecular Metabolism, 5, 615–625. https://doi.org/10. 1016/j.molmet.2016.06.005. 265. Lemecha, M., et al. (2018). MiR-494-3p regulates mitochondrial biogenesis and thermogenesis through PGC1-alpha signalling in beige adipocytes. Scientific Reports, 8, 15096. https:// doi.org/10.1038/s41598-018-33438-3. 266. Shah, S. C., et al. (2017). Low baseline awareness of gastric cancer risk factors amongst at-risk multiracial/ethnic populations in New York City: Results of a targeted, culturally sensitive pilot gastric cancer community outreach program. Ethnicity & Health, 1–17. https://doi.org/ 10.1080/13557858.2017.1398317. 267. Derghal, A., Djelloul, M., Trouslard, J., & Mounien, L. (2017). The role of MicroRNA in the modulation of the melanocortinergic system. Frontiers in Neuroscience, 11, 181. https://doi. org/10.3389/fnins.2017.00181. 268. Hill, J. W., et al. (2010). Direct insulin and leptin action on pro-opiomelanocortin neurons is required for normal glucose homeostasis and fertility. Cell Metabolism, 11, 286–297. https:// doi.org/10.1016/j.cmet.2010.03.002. 269. Berglund, E. D., et al. (2012). Direct leptin action on POMC neurons regulates glucose homeostasis and hepatic insulin sensitivity in mice. Journal of Clinical Investigation, 122, 1000–1009. https://doi.org/10.1172/JCI59816. 270. Yang, Y., et al. (2019). Steroid receptor coactivator-1 modulates the function of Pomc neurons and energy homeostasis. Nature Communications, 10, 1718. https://doi.org/10.1038/s41467019-08737-6. 271. Ernst, M. B., et al. (2009). Enhanced Stat3 activation in POMC neurons provokes negative feedback inhibition of leptin and insulin signaling in obesity. Journal of Neuroscience, 29, 11582–11593. https://doi.org/10.1523/JNEUROSCI.5712-08.2009. 272. Gamber, K. M., et al. (2012). Over-expression of leptin receptors in hypothalamic POMC neurons increases susceptibility to diet-induced obesity. PLoS ONE, 7, e30485. https://doi. org/10.1371/journal.pone.0030485. 273. Nakata, M., Yamamoto, S., Okada, T., & Yada, T. (2017). AAV-mediated IL-10 gene transfer counteracts inflammation in the hypothalamic arcuate nucleus and obesity induced by high-fat diet. Neuropeptides, 62, 87–92. https://doi.org/10.1016/j.npep.2016.11.009.

References

51

274. Myers, M. G., Cowley, M. A., & Munzberg, H. (2008). Mechanisms of leptin action and leptin resistance. Annual Review of Physiology, 70, 537–556. https://doi.org/10.1146/annurev.phy siol.70.113006.100707. 275. Xu, A. W., et al. (2005). PI3K integrates the action of insulin and leptin on hypothalamic neurons. Journal of Clinical Investigation, 115, 951–958. https://doi.org/10.1172/JCI24301. 276. Santoro, A., et al. (2017). DRP1 Suppresses Leptin and Glucose Sensing of POMC Neurons. Cell Metabolism, 25, 647–660. https://doi.org/10.1016/j.cmet.2017.01.003. 277. Long, L., Toda, C., Jeong, J. K., Horvath, T. L., & Diano, S. (2014). PPARgamma ablation sensitizes proopiomelanocortin neurons to leptin during high-fat feeding. Journal of Clinical Investigation, 124, 4017–4027. https://doi.org/10.1172/JCI76220. 278. Schneeberger, M., et al. (2013). Mitofusin 2 in POMC neurons connects ER stress with leptin resistance and energy imbalance. Cell, 155, 172–187. https://doi.org/10.1016/j.cell. 2013.09.003. 279. Gao, Y., et al. (2017). TrpC5 Mediates Acute Leptin and Serotonin Effects via Pomc Neurons. Cell Reports, 18, 583–592. https://doi.org/10.1016/j.celrep.2016.12.072. 280. Haissaguerre, M., et al. (2018). mTORC1-dependent increase in oxidative metabolism in POMC neurons regulates food intake and action of leptin. Molecular Metabolism, 12, 98–106. https://doi.org/10.1016/j.molmet.2018.04.002. 281. Engin, A. (2017). Diet-Induced obesity and the mechanism of leptin resistance. Advances in Experimental Medicine and Biology, 960, 381–397. https://doi.org/10.1007/978-3-31948382-5_16. 282. Dodd, G. T., et al. (2015). Leptin and insulin act on POMC neurons to promote the browning of white fat. Cell, 160, 88–104. https://doi.org/10.1016/j.cell.2014.12.022. 283. Yao, T., et al. (2017). Ire1alpha in POMC neurons is required for thermogenesis and glycemia. Diabetes, 66, 663–673. https://doi.org/10.2337/db16-0533. 284. Dodd, G. T., et al. (2018). Insulin regulates POMC neuronal plasticity to control glucose metabolism. Elife, 7. https://doi.org/10.7554/elife.38704. 285. Ramirez, S., et al. (2017). Mitochondrial dynamics mediated by mitofusin 1 is required for POMC neuron glucose-sensing and insulin release control. Cell Metabolism, 25, 1390–1399 e1396. https://doi.org/10.1016/j.cmet.2017.05.010. 286. Shin, A. C., et al. (2017). Insulin receptor signaling in POMC, but not AgRP, neurons controls adipose tissue insulin action. Diabetes, 66, 1560–1571. https://doi.org/10.2337/db16-1238. 287. Wang, Z., Khor, S., & Cai, D. (2019). Age-dependent decline of hypothalamic HIF2alpha in response to insulin and its contribution to advanced age-associated metabolic disorders in mice. Journal of Biological Chemistry, 294, 4946–4955. https://doi.org/10.1074/jbc.RA118. 005429. 288. Croizier, S., Park, S., Maillard, J. & Bouret, S. G. (2018). Central Dicer-miR-103/107 controls developmental switch of POMC progenitors into NPY neurons and impacts glucose homeostasis. Elife, 7. https://doi.org/10.7554/elife.40429. 289. Herzer, S., Silahtaroglu, A., & Meister, B. (2012). Locked nucleic acid-based in situ hybridisation reveals miR-7a as a hypothalamus-enriched microRNA with a distinct expression pattern. Journal of Neuroendocrinology, 24, 1492–1504. https://doi.org/10.1111/j.1365-2826.2012. 02358.x. 290. Sangiao-Alvarellos, S., Pena-Bello, L., Manfredi-Lozano, M., Tena-Sempere, M., & Cordido, F. (2014). Perturbation of hypothalamic microRNA expression patterns in male rats after metabolic distress: Impact of obesity and conditions of negative energy balance. Endocrinology, 155, 1838–1850. https://doi.org/10.1210/en.2013-1770. 291. Crepin, D., et al. (2014). The over-expression of miR-200a in the hypothalamus of ob/ob mice is linked to leptin and insulin signaling impairment. Molecular and Cellular Endocrinology, 384, 1–11. https://doi.org/10.1016/j.mce.2013.12.016.

52

2 Non-coding RNAs Related to Obesity

292. Derghal, A., et al. (2019). Leptin modulates the expression of miRNAs-targeting POMC mRNA by the JAK2-STAT3 and PI3K-Akt pathways. Journal of Clinical Medicine, 8. https:// doi.org/10.3390/jcm8122213. 293. Derghal, A., et al. (2015). Leptin is required for hypothalamic regulation of miRNAs targeting POMC 3’UTR. Frontiers in Cellular Neuroscience, 9, 172. https://doi.org/10.3389/fncel. 2015.00172.

Chapter 3

Non-coding RNAS Related to Type 2 Diabetes

Abstract Type 2 diabetes more often develops in obese persons. Impaired β cell precursor proliferation, β cell maturation, glucose uptake, and insulin secretion in response to high glucose result in mitochondrial and endoplasmic reticulum stress associated with ROS release, inflammation, and β cell death. The multiple-hit pathogenesis models of obesity and type 2 diabetes share an imbalance in the expression of let-7, miR-9, miR-17, miR-21, miR-26a, miR-27, miR-29, miR-30, miR-34a, miR124, miR-130, miR-138, miR-145, miR-146a, miR-150, miR-181, miR-221–222, miR-223, miR-375, miR-378 and miR-455, and lncRNAs βLINC, GAS5, HOTAIR, H19, MEG3, NEAT1 and TINCR, and circ-RNA PVT1. Typically for the pancreas, the up-regulation of miR-7 due to loss of silencing circular RNA ciRs-7 protects against diabetes by inducing differentiation of stem cells to β cells but exacerbates the diabetic phenotype by decreasing β cell mass and impairing insulin signaling. High glucose-induced miR-375 is essential for retaining β cell mass but inhibited PI3K and thereby insulin signaling. The PDX1 associated lncRNA, up-regulator of transcription (PLUTO), is a tissue-specific inhibitor of β cell maturation and insulin production.

3.1 Mechanisms in β Cell Maturation Insulin regulates the body’s energy. Well-functioning pancreatic β cells secrete insulin in response to increases in glucose after a meal [1]. Insulin instructs the body’s cells to translocate glucose transporters to the cell membrane to absorb the sugar for the cell’s energy needs and convert the excess into energy-storage molecules, such as glycogen in the liver. Insulin-producing β cells derive from progenitors co-expressing pancreatic and duodenal homeobox 1 (PDX1) and NK6 homeobox (NKX)-6.1, which have a high self-replicating capacity. Fibroblast growth factor (FGF) and epidermal growth factor (EGF) induce expansion of the PDX1 and NKX-6.1-expressing progenitor cells and islet neogenesis [2–9]. Differentiation of progenitor cells starts when sirtuin (SIRT)6 deacetylates forkhead box O1 (FOXO1) to trigger its nuclear export and releases Illustrations by Pieterjan Ginckels, Faculty of Architecture, KU Leuven, Ghent, Belgium. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 P. Holvoet, Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer, https://doi.org/10.1007/978-3-030-68844-8_3

53

54

3 Non-coding RNAS Related to Type 2 Diabetes

Fig. 3.1 Non-coding RNAs in β cell maturation and insulin production. In response to increasing glucose, growth factors FGF and EGF induce proliferation of pancreatic progenitors co-expressing PDX1 and NKX6.1 in the pancreas. Typically, this response is impaired in type 2 diabetes, likely by down-regulation of miR-26a, but miR-7 and miR-130b may restore it. Differentiation of precursor cells to mature β cells requires the coordinated action of PDX1 and MAFA, RFX6, HNFs (or MODYs), and MEIS1. They are typically activated during the differentiation process as revealed by the active chromatin marker H3K27a and mRNA expression profiling, suggesting that autoregulatory feedback regulation maintains PDX1 expression and initiates a pancreatic transcription program. IGF1, GLP-1, exendin, EGF, and FGF21 cause the maturation of β cells, reverted by TGF-β and miR-9, and the decrease of miR-26a, GAS5, MEG3, PLUTO, and βLINC. MiR-223, miR-375, and H19 silencing let-7, and of lncRNA-3134 may prevent this inhibition. GH and IGF1 induce β cell proliferation involving Wnt/β-catenin and mediated by SIRT1 and BCL2, MAFA, CCNs, and CDKs. The increase of IL1-β, miR-9, miR-34a, miR-124a, and HOTAIR impair β cell proliferation. PDX1, MAFA, and KLF11 regulate insulin production. LncRNA-3134 facilitates insulin secretion, whereas the increase of PDGF, TGF-β, and miR-9, and the decrease of miR-26a, GAS5, MEG3, PLUTO, and βLINC impair insulin secretion in type 2 diabetes. OCT4, SOX2, MYC, and KLF4 de-differentiate β cells to pluripotent stem cells. This reprogramming is blocked by increased miR-145 due to decreased silencing LINC-ROR. Increased non-coding RNAs are in red, decreased in green

its transcriptional repression of critical glucose-sensing genes such as PDX1 [10]. PDX1 targets important pancreatic tissue factors such as PDX1 itself, the regulatory factor (RF)-X6, HNF homeobox (HNF)-1β (MODY 5), HNF-4α (MODY1), and HNF-1α (MODY3), and Meis homeobox (MEIS)-1 [11, 12] (Fig. 3.1).

3.1 Mechanisms in β Cell Maturation

55

Several extrinsic factors such as insulin-like growth factor 1 (IGF1), glucagon-like peptide (GLP)-1 and exendin, and EGF and FGF21 contribute to β cell differentiation and proliferation [13–17]. GLP-1 promotes α to β cell differentiation and compensates for the stress-related loss of β cells [18]. Growth hormone (GH), prolactin (PRL), and IGF1 and their receptors (GHR, PRLR, and IGF1R) regulate the proliferation of mature β cells [19]. Like in adipocyte proliferation, Wnt signaling plays a significant role in β cell proliferation mediated by SIRT1 and the BCL2, apoptosis regulator (BCL2). Wnt signaling is activated by binding Wnt ligands to the Frizzled receptor and induced by the GLP-1 receptor activation. Still, this receptor is low in diabetic β cells. This impairment leads to reduced cyclin (CCN) and cyclin-dependent kinase (CDK) expression and impaired β cell proliferation [20–23]. Decreased insulin-regulated mitotic cell-cycle progression and reduced expression of the Maf transcription factor MAFA may reduce proliferation. These decreases impair not only CDK-1/2 expression in the pancreas of diabetic patients but also the interaction of p27 (Kip1) with CCND3 and its cognate kinase partners CDK4 and CDK6, leading to β cell quiescence [24–26] (Fig. 3.1). PDX1 and MAFA are crucial for insulin production [27–29]. Krüppel-like zinc finger transcription factor (KLF)-11 regulates insulin promoter activity only in β cells and not in non-β cells through PDX1 [30]. PDX1 even induces adipose-tissue derived stem cells to differentiate to insulin-producing cells in diabetic mice [31]. However, platelet-derived growth factor (PDGF) decreases insulin production in type 2 diabetes [32]. Further, inflammatory interleukin (IL)-1β inhibits β cell replication while transforming growth factor (TGF)-β inhibits β cell differentiation [33] (Fig. 3.1). The POU class 5 homeobox one or POU5F1 (OCT4), SRY-box transcription factor 2 (SOX2), MYC proto-oncogene (MYC), and KLF4 play an essential role in reprogramming pancreatic β cells in pluripotent stem cells [34, 35] (Fig. 3.1).

3.1.1 Non-coding RNAs Related to β Cell Maturation MiR-7 can induce differentiation of human embryonic stem cells into β cell precursors [36]. MiR-130b protects precursor cells against senescence induced by high glucose [37]. MiR-26a in mice increases islet cell number by inhibiting the teneleven translocation (TET) enzymes TET1 and TET2 and thymine DNA glycosylase (TDG). TET and TDG play crucial roles in early embryonic and germ cell development by mediating DNA demethylation [38]. MiR-26a increases insulin secretion and β cell replication in an autocrine manner. Exosomal miR-26a regulates peripheral insulin sensitivity in a paracrine manner [39]. TGF-β/Smad signaling triggers the differentiation of β cells from adult stem cells by enhancing the transcription of miR-375 and miR-26a [40]. However, miR-26a is reduced in obesity and hyperglycemia [39]. Up-regulation of miR-223 in islets from people with diabetes increases PDX1 and cell cycle-related genes such as CCND1 and CCNE1 [41]. Glucose upregulates mir-375, which is crucial for maintaining β cell mass [42, 43]. Increasing H19 imprinted maternally expressed transcript lncRNA (H19) may restore β cell

56

3 Non-coding RNAS Related to Type 2 Diabetes

expansion by antagonizing let-7 [44]. A glucose-induced increase of lncRNA-3134 in type 2 diabetes retains β cell maturation and insulin secretion by promoting PDX1 and MAFA in β cells [45]. In contrast, TGF-β and mir-9 impair β cells’ differentiation and reduce exocytosis of insulin elicited by glucose, while miR-9 also blocks proliferation [46–48]. The decrease of miR-26a and lncRNAs growth arrestspecific 5 (GAS5), maternally expressed three lncRNA (MEG3), the PDX1 associated lncRNA, up-regulator of transcription (PLUTO), and βLINC in the pancreas is associated with a significant decline in the differentiation of β cells and insulin secretion, mainly through loss of PDX1 and MAFA. Further, down-regulation of maternally expressed 3 (MEG3) renders β cells more sensitive to cytokine-mediated oxidative stress [49–59] (Fig. 3.1). IL-1β and miR-9 impair β cell proliferation. MiR-34a also impairs β cell proliferation by interacting with CCND1 and CCNE2 and CDK4 and CDK6 [60–63]. High levels of miR-124a in the diabetic pancreas decrease proliferation by blocking SIRT1 expression and increase release of reactive oxygen species (ROS) [64, 65]. Homeobox transcript antisense RNA (HOTAIR) induces preadipocyte differentiation but inhibits β cell proliferation and insulin secretion and promotes insulin resistance [66–68]. The decrease of long intergenic non-protein coding RNA regulator of reprogramming (LINC-ROR) up-regulates miR-145 that silences SOX2 essential for reprogramming pancreatic β cells in pluripotent stem cells [69, 70] (Fig. 3.1).

3.2 Mechanisms in Insulin Signaling in the Pancreas Proper insulin signaling requires the binding of insulin to insulin receptors (IRs). Optimal processing of proinsulin to insulin. However, the disruption of IR expression in diabetic β cells leads to low expression of the eukaryotic translation initiation factor (EIF)-4G1 mediated by the sterol regulatory element-binding transcription factor 1 (SREBF1 or SREBP1), carboxypeptidase (CPE) and PDX1, and reduced proinsulin processing and biosynthesis of insulin. Re-expression of IR or restoring CPE expression each independently restores proinsulin processing [71–75]. Inhibition of SREBF1 expression increases PDX1 and GLP-1-mediated insulin secretion from β cells [76, 77]. Metformin counteracts impairment of GLP-1 receptor signaling induced by saturated fatty acids [78, 79]. IGF1 is like insulin in function and structure and is a member of a family of proteins involved in mediating growth and development. In contrast to impaired insulin signaling resulting in a decrease in β cell mass, reduced IGF1 signaling lowers glucose-induced insulin secretion without loss of β cell mass [80] (Fig. 3.2). Insulin binding to IRs leads to phosphorylation and activation of insulin substrate receptor (IRS) proteins. Phosphorylated IRS proteins activate and target phosphatidylinositol 3-kinase (PI3K) to the plasma membrane. The phosphatase and tensin homolog (PTEN) and the suppressor of cytokine signaling (SOCS) family regulate PI3K [81–86]. PI3K generates phosphatidylinositol (3,4,5)-trisphosphate (PIP3 ) that recruits pyruvate dehydrogenase kinase (PDK)-1, which phosphorylates and activates AKT serine/threonine kinase 1 (AKT) [87, 88]. PIP3 mediates the

3.2 Mechanisms in Insulin Signaling in the Pancreas

57

Fig. 3.2 Non-coding RNAs in insulin signaling. Proper insulin signaling requires enough insulin to respond to high glucose levels and insulin to bind to IR molecules. However, in type 2 diabetes, the up-regulation of SREBF1 or SREBP1 leads to decreased EIF4G1, CPE, GLP-1, and PDX1, impairing proinsulin processing. The increase of miR-7 and miR-29a and the decrease of miR26a and miR-132 blocks the response of insulin production to glucose. When insulin binds to IR molecules in cell membranes, those receptors activate several IRS proteins by phosphorylating them. Upon tyrosine phosphorylation, IRS proteins interact with PI3K, leading to the enzyme’s activation and targeting the plasma membrane. The increase of miR-29a, miR-144, and miR-145a, possibly due to decreased LINC-ROR, blocks IRS signaling. The binding of growth factors and cytokines to IGF1R also activates IRS and PI3K. However, the increase of miR-223 and the decrease of miR181b inhibit IGF1R signaling. PI3K recruits PDK1, which phosphorylates and activates several downstream kinases, including AKT, that phosphorylates AS160. However, high levels of miR-375 inhibit PDK1, while miR-124a increased by the down-regulation of circ-HIPK3 and the decrease of miR-26a and PVT1 block AKT. MiR-378 and H19, silencing let-7, may prevent this. In the basal state, AS160 binds to GLUT4 vesicles, negatively regulating its target Rab(s). In response to insulin, AS160 dissociates from Rab/Rip11 vesicles, leading to the activation of the target Rab(s) necessary to translate GLUT4 vesicles. The increase of miR-17 impairs GLUT4 signaling. GLUT4 aids the translocation of glucose through Rag that activates mTORC1. The mTORC1 complex consists of mTOR, Raptor, and GβL. It induces proteasomal degradation of IRS1 to constitute a negative feedback loop to balance insulin signaling to glucose uptake. Also, mTOR phosphorylates and

58

3 Non-coding RNAS Related to Type 2 Diabetes

 activates the p70S6K accompanied by the release of free S6K1 that, together with EIF4B, induces β cell size and mass and insulin production, protecting against apoptosis. The mTORC1/4EBP2/EIF4E pathway regulates proinsulin processing. The increase of miR-7, possibly due to a decrease of ciRs7, blocks p70SK and EIF4E, leading to β cell loss, impaired proinsulin processing, and decreased insulin secretion. Additionally, glucose activates the mTORC2 complex. It consists of mTOR, GβL, and Rictor. It directly phosphorylates AKT resulting in translocation of GLUT4 to the plasma membrane and increased glucose transport, and regulates β cell proliferation and insulin secretion. However, mir-7 blocks mTORC2 signaling, thereby inhibiting β cell proliferation, insulin secretion, and glucose transport. The increase of proinsulin and inflammatory ANG II induces mitochondrial dysfunction through miR-15, compromising SIRTs, FOXO3a, and NQO1. Proinsulin and ANG II also cause ER stress and β cell death through miR-491-5p. MiR-24a may prevent ER stress, but at the same time, blocks MAFA and thereby insulin production by surviving β cells. ROS associated with mitochondrial and ER stress causes β cell death by increased miR-34a, due to loss of silencing NEAT1, miR-138, and miR-145, and decreased miR-19a-3p and the DLK-MEG3-miR-376a-miR432 complex. The increase of miR-21, due to reduced silencing GAS5 and the decrease of miR-181b, may prevent apoptosis. However, the reduction of miR-181b leads to insulin resistance. Increased non-coding RNAs are in red, decreased in green

translocation of AKT to the plasma membrane [89]. One of the substrates of AKT is the Rab-GTPase activating protein (Rab-GAP), which undergoes phosphorylation in response to insulin and is essential for the retention of the solute carrier family two-member four (GLUT4 or SLC2A4) in intracellular vesicles [90–92]. In the basal state, AS160 binds to GLUT4 vesicles, negatively regulating its target Rab(s). In response to insulin, AS160 dissociates from Rab/Rip11 vesicles leading to the activation of the target Rab(s) necessary to translocate GLUT4 vesicles [93–96]. However, insulin-stimulated AS160 phosphorylation and GLUT4 translocation are impaired in patients with type 2 diabetes [97] (Fig. 3.2). The mammalian target of rapamycin complex 1 (mTORC-1) regulates insulin signaling downstream of AKT. The mTORC-1 complex consists of the regulatory associated protein of mTOR complex 1 (Raptor) and the mTOR associated protein LST8 homolog (MLST8 or GβL) [98–102]. Activation of the mTORC1 complex induces proteasomal degradation of IRS1 to constitute a negative feedback loop [103]. Also, mTOR phosphorylates and activates the ribosomal protein S6 kinase (p70S6K or RPS6KB1) accompanied by the release of free S6K1 [104, 105]. S6K1 and the eukaryotic translation initiation factor 4B (EIF4B) control β cell size and mass and insulin production and protects β cells from apoptosis [106–108]. The mTORC1/eukaryotic translation initiation factor 4E binding protein (4EBP)-2 and EIF4E regulate proinsulin processing [109]. However, in type 2 diabetes, the activity of the mTORC1 complex is impaired. Additionally, glucose activates the rapamycin-insensitive protein complex formed by serine/threonine kinase mTOR (mTORC2), consisting of mTOR, GβL, and Raptor-independent companion of mTOR complex 2 (Rictor) [110]. It directly phosphorylates AKT and facilitates phosphorylation by PDK1, resulting in translocation of GLUT4 to the plasma membrane and increased glucose transport [111]. Besides, mTORC2 and, in particular, Rictor is essential for maintaining a balanced β cell proliferation and glucose-stimulated insulin secretion by regulation of cytoplasmic translocation of PDX1, the nuclear accumulation of FOXO1, and insulin exocytosis

3.2 Mechanisms in Insulin Signaling in the Pancreas

59

[112]. However, mTORC2 signaling is diminished in pancreatic islets from humans with type 2 diabetes [113]. Excessive proinsulin and inflammatory angiotensinogen (ANG) II, increased by a deficiency in angiotensin I converting enzyme (ACE)-2, cause mitochondrial dysfunction associated with impaired β cell proliferation and reduced β cell mass [114–117]. Mitochondrial dysfunction is associated with increased mitochondrial ROS production by compromising cellular defense systems such as SIRTs and NAD (P) H quinone dehydrogenase 1 (NQO1) [118–123]. SIRT1-3 and FOXO increase insulin and improve glucose uptake. Improved insulin signaling reduces mitochondrial oxidative stress, inflammation, and lipid accumulation. In addition to mitochondrial stress, β cells are susceptible to endoplasmic reticulum (ER) stress due to their high rate of proinsulin biosynthesis in response to glucose stimulation [124– 126]. Unfolded protein response (UPR), which is activated to restore ER homeostasis, is vital for maintaining the functional β cell mass [127]. However, in type 2 diabetes, UPR activation fails to restore ER homeostasis and leads to β cell dysfunction and death by activating pro-inflammatory and pro-apoptotic signaling pathways [128–130] (Fig. 3.2).

3.2.1 Non-coding RNAs in Insulin Signaling in Type 2 Diabetes MiR-7, abundantly expressed in islet cells and even higher in patients with type 2 diabetes, not only protects against diabetes by inducing differentiation of stem cell to β cells but exacerbates the diabetic phenotype by blocking insulin granule exocytosis [131–135]. MiR-29a inhibits glucose-stimulated insulin secretion by inhibiting Wnt/β-catenin signaling [136]. The decrease of miR-132 also impairs insulin response to high glucose [137, 138] (Fig. 3.2). Further, miR-29a impairs IRS signaling and GLUT4 mediated glucose uptake [139]. MiR-144 and miR-145, the latter possibly by a decrease of sponging LINCROR, impair insulin signaling by direct targeting of IRS1 [140–142]. Hyperglycemiainduced miR-223 represses IGF1R and downstream PI3K/AKT/mTOR/p70S6K signaling [143, 144]. The decrease of mir-181b in obesity reinforces this inhibition [51, 145]. The increase of miR-375 blocks PI3K by targeting PDK1 [146]. Higher expression of miR-124a, due to the loss of the homeodomain interacting protein kinase three circ-RNA (circ-HIPK3), decreases AKT [64, 65, 147, 148], which may be reverted by H19 that silences let-7 [44, 149, 150]. Decrease of miR-26a by high glucose reduced insulin-stimulated AKT activation by increasing phosphatase and tensin homolog (PTEN) [39, 151]. Down-regulation of PVT1 oncogene (PVT1) in type 2 diabetes also blocks PI3K/AKT signaling [152]. Overexpression of miR-378 restores PI3K/AKT signaling and down-regulates the pro-apoptotic BCL2 associated X, apoptosis regulator (BAX) [153]. High levels of miR-17 in diabetes decrease GLUT4-mediated glucose uptake [154] (Fig. 3.2).

60

3 Non-coding RNAS Related to Type 2 Diabetes

MiR-7 targets components of the mTORC1 complex, p70S6K, and EIF4E, thereby disrupting feedback on IRS signaling and reducing β cell size and mass, proinsulin processing, insulin production, and protection against cell death in type 2 diabetes. It also targets the mTORC2 complex, thereby stimulating the diabetic phenotype by repressing β cell proliferation and insulin production. The circular cerebellar degeneration-related protein 1 antisense RNA (Cdr1as or CiRs-7) may sponge miR-7, but it is low in diabetic β cells [132, 148] (Fig. 3.2). MiR-15 induces mitochondrial oxidative damage associated with increased ROS release, and miR-491-5p then causes mitochondrial dysfunction-associated β cell death [155, 156]. MiR-24a inhibits ER stress, but it also silences MAFA, thereby decreasing insulin secretion in surviving β cells [157] (Fig. 3.2). The increase of miR-34a-5p, by down-regulation of nuclear paraspeckle assembly transcript 1 (NEAT1), results in β cell death through the EIF2AK3 (or PERK)/p53dependent pathway [149]. Elevated expression levels of mir-138 and miR-145 induce cell senescence and death in insulin-producing β cells [158, 159]. A decrease of miR19a-3p leads to SOCS3 overexpression and apoptosis [160]. Repression of a delta-like non-canonical NOTCH ligand (DLK)-1-MEG3 miR cluster containing miR-376a and miR-432 is also associated with increased β cell apoptosis [161]. In contrast, the decrease of GAS5 and the resulting increase of miR-21 in type 2 diabetes reduce apoptosis by directly targeting programmed cell death (PDCD)-4. Still, it may also increase apoptosis by directly inhibiting the apoptosis regulator BCL2 [162–165]. The decrease of miR-181b may protect against cell death by increasing BCL2, and MCL1 apoptosis regulator, BCL2 family member (MCL1) proteins but may increase cell death by impairing insulin signaling [166] (Fig. 3.2).

3.3 Inflammation in the Pancreas, Insulin Resistance, and Type 2 Diabetes High levels of glucose and ROS impair IRS-mediated PI3K activity in macrophages resulting in overexpression of suppressor of cytokine signaling 3 (SOCS3). SOCS3 reduces energy expenditure and increases food intake and adiposity, insulin and leptin resistance, M1 macrophage polarization, and a state of cytokine resistance to IL4, leading to inflammation [167–169]. SOCS3 also increases food intake and decreases energy expenditure, and impairs leptin signaling in obesity [168]. High glucose and ROS disrupt the balance between pro-inflammatory Th17 and Th1 and antiinflammatory Treg and Th2 cells. They increase inflammatory cytokines IL-1β, tumor necrosis factor (TNF)-α, interferon (IFN)-γ, and IL6 and decrease anti-inflammatory cytokines IL4 and IL13 [170–173]. Impaired IL13 anti-inflammatory function in type 2 diabetes is associated with an additional increase of M1 macrophages and derived IL6, IL-1β, TNF-α, which induce β cell death [174–177] (Fig. 3.3).

3.3 Inflammation in the Pancreas, Insulin Resistance, and Type 2 Diabetes

61

Fig. 3.3 Non-coding RNAs in inflammation and insulin resistance. Hyperglycemia and ROS in type 2 diabetes decrease IRS/PI3K/AKT signaling, likely due to an increase of miR-146a. The associated rise in SOCS3, possibly due to the decline of miR-19a-3p and miR-455-5p, impairs response to anti-inflammatory IL4 and increases M1 macrophage polarization and inflammation. SOCS3 also increases food intake and decreases energy expenditure, and reduces leptin signaling in obesity. Hyperglycemia and ROS in type 2 diabetes change the T cell profile. Th1 and Th17 cells increase, and Th2 and Treg cells decrease, thereby increasing pro-inflammatory TNF-α, IL6, IL-1β, and IFN-γ while decreasing anti-inflammatory IL4 and IL13. MiR-30a may temporally block IL1β and IFN-γ secretion. Ultimately, the excess of inflammatory cytokines causes M1 macrophage polarization due to increased expression of miR-221–222 and secretion of macrophage-derived inflammatory cytokines TNF-α, IL-1β, and IL6. Inflammatory cytokines induce miR-34a, possibly due to loss of sponging NEAT1, and miR-146a leading to decreased β cell proliferation and to β cell senescence and death. MiR-221/222 is associated with inflammation-induced insulin resistance. Increased non-coding RNAs are in red, decreased in green

3.3.1 Non-coding RNAs Related to Inflammation in the Pancreas, with Insulin Resistance and Type 2 Diabetes Mir-146a represses PI3K/AKT signaling indirectly by targeting C-X-C motif chemokine receptor 4 (CXCR4) [178]. The reduction of miR-19a-3p and miR-455 in type 2 diabetes increases SOCS3 expression [160, 179]. The increase of miR30a blocks inflammation-inducing IL-1β in immune cells and islet cells and IFN-γ in inflammatory cells, thereby retaining insulin sensitivity [180, 181]. However,

62

3 Non-coding RNAS Related to Type 2 Diabetes

high levels of miR-221–222 counteract this action of miR-30a associated with M1 macrophage polarization and inflammation, and insulin resistance [182, 183]. Further, M1 macrophage polarization up-regulates inflammatory mediators IL-1β, IL6, and TNF-α, which induce mir-34a and miR-146a, leading to increased cytokinetriggered cell death [53, 184–186]. The increase of miR-34a may be due to the repression of NEAT1 in type 2 diabetes [187, 188]. Because we showed above that it also impairs β cell proliferation, miR-34a is a crucial link between inflammation and a reduced number of β cells (Fig. 3.3).

References 1. Saltiel, A. R., & Kahn, C. R. (2001). Insulin signalling and the regulation of glucose and lipid metabolism. Nature, 414, 799–806. https://doi.org/10.1038/414799a. 2. Kemp, D. M., Thomas, M. K., & Habener, J. F. (2003). Developmental aspects of the endocrine pancreas. Reviews in Endocrine and Metabolic Disorders, 4, 5–17. 3. Habener, J. F., Kemp, D. M., & Thomas, M. K. (2005). Minireview: Transcriptional regulation in pancreatic development. Endocrinology, 146, 1025–1034. https://doi.org/10.1210/en.20041576. 4. Johannesson, M., et al. (2009). FGF4 and retinoic acid direct differentiation of hESCs into PDX1-expressing foregut endoderm in a time- and concentration-dependent manner. PLoS ONE, 4, e4794. https://doi.org/10.1371/journal.pone.0004794. 5. Song, S. Y., et al. (1999). Expansion of Pdx1-expressing pancreatic epithelium and islet neogenesis in transgenic mice overexpressing transforming growth factor alpha. Gastroenterology, 117, 1416–1426. 6. Hakonen, E., et al. (2011). Epidermal growth factor (EGF)-receptor signalling is needed for murine beta cell mass expansion in response to high-fat diet and pregnancy but not after pancreatic duct ligation. Diabetologia, 54, 1735–1743. https://doi.org/10.1007/s00125-0112153-1. 7. Memon, B., Karam, M., Al-Khawaga, S., & Abdelalim, E. M. (2018). Enhanced differentiation of human pluripotent stem cells into pancreatic progenitors co-expressing PDX1 and NKX6.1. Stem Cell Res Ther, 9, 15. doi:https://doi.org/10.1186/s13287-017-0759-z. 8. Tiwari, S., et al. (2015). Early and late G1/S Cyclins and Cdks act complementarily to enhance authentic human beta-cell proliferation and expansion. Diabetes, 64, 3485–3498. https://doi. org/10.2337/db14-1885. 9. 9Rezania, A. et al. (2013). Enrichment of human embryonic stem cell-derived NKX6.1expressing pancreatic progenitor cells accelerates the maturation of insulin-secreting cells in vivo. Stem Cells, 31, 2432–2442. doi:https://doi.org/10.1002/stem.1489. 10. Song, M. Y., Wang, J., Ka, S. O., Bae, E. J., & Park, B. H. (2016). Insulin secretion impairment in Sirt6 knockout pancreatic beta cells is mediated by suppression of the FoxO1-Pdx1-Glut2 pathway. Scientific Reports, 6, 30321. https://doi.org/10.1038/srep30321. 11. Wang, X., et al. (2018). Genome-wide analysis of PDX1 target genes in human pancreatic progenitors. Molecular Metabolism, 9, 57–68. https://doi.org/10.1016/j.molmet.2018.01.011. 12. Nammo, T., et al. (2008). Expression of HNF-4alpha (MODY1), HNF-1beta (MODY5), and HNF-1alpha (MODY3) proteins in the developing mouse pancreas. Gene Expression Patterns, 8, 96–106. https://doi.org/10.1016/j.modgep.2007.09.006. 13. Ueki, K., et al. (2006). Total insulin and IGF-I resistance in pancreatic beta cells causes overt diabetes. Nature Genetics, 38, 583–588. https://doi.org/10.1038/ng1787. 14. Zhang, Z., et al. (2019). A new way for beta cell neogenesis: Transdifferentiation from alpha cells induced by glucagon-like peptide 1. Journal of Diabetes Research, 2019, 2583047. https://doi.org/10.1155/2019/2583047.

References

63

15. Movassat, J., Beattie, G. M., Lopez, A. D., & Hayek, A. (2002). Exendin 4 up-regulates expression of PDX 1 and hastens differentiation and maturation of human fetal pancreatic cells. Journal of Clinical Endocrinology and Metabolism, 87, 4775–4781. https://doi.org/10. 1210/jc.2002-020137. 16. Lemper, M., De Groef, S., Stange, G., Baeyens, L., & Heimberg, H. (2016). A combination of cytokines EGF and CNTF protects the functional beta cell mass in mice with short-term hyperglycaemia. Diabetologia, 59, 1948–1958. https://doi.org/10.1007/s00125-016-4023-3. 17. Wente, W., et al. (2006). Fibroblast growth factor-21 improves pancreatic beta-cell function and survival by activation of extracellular signal-regulated kinase 1/2 and Akt signaling pathways. Diabetes, 55, 2470–2478. https://doi.org/10.2337/db05-1435. 18. Lee, Y. S., Lee, C., Choung, J. S., Jung, H. S., & Jun, H. S. (2018). Glucagon-like peptide 1 increases beta-cell regeneration by promoting alpha- to beta-cell transdifferentiation. Diabetes, 67, 2601–2614. https://doi.org/10.2337/db18-0155. 19. Huang, Y., & Chang, Y. (2014). Regulation of pancreatic islet beta-cell mass by growth factor and hormone signaling. Progress in Molecular Biology Translational Science, 121, 321–349. https://doi.org/10.1016/B978-0-12-800101-1.00010-7. 20. Kim, S. Y., et al. (2017). Loss of cyclin-dependent kinase 2 in the pancreas links primary betacell dysfunction to progressive depletion of beta-cell mass and diabetes. Journal of Biological Chemistry, 292, 3841–3853. https://doi.org/10.1074/jbc.M116.754077. 21. Welters, H. J., & Kulkarni, R. N. (2008). Wnt signaling: Relevance to beta-cell biology and diabetes. Trends in Endocrinology and Metabolism, 19, 349–355. https://doi.org/10.1016/j. tem.2008.08.004. 22. Wu, X., et al. (2017). Exendin-4 promotes pancreatic beta-cell proliferation via inhibiting the expression of Wnt5a. Endocrine, 55, 398–409. https://doi.org/10.1007/s12020-016-1160-x. 23. Liu, Z., & Habener, J. F. (2008). Glucagon-like peptide-1 activation of TCF7L2-dependent Wnt signaling enhances pancreatic beta cell proliferation. Journal of Biological Chemistry, 283, 8723–8735. https://doi.org/10.1074/jbc.M706105200. 24. Shirakawa, J. et al. (2017). Insulin signaling regulates the FoxM1/PLK1/CENP-a pathway to promote adaptive pancreatic beta cell proliferation. Cell Metab, 25, 868–882 e865, doi:https:// doi.org/10.1016/j.cmet.2017.02.004. 25. Hang, Y., et al. (2014). The MafA transcription factor becomes essential to islet beta-cells soon after birth. Diabetes, 63, 1994–2005. https://doi.org/10.2337/db13-1001. 26. Stein, J., Milewski, W. M., & Dey, A. (2013). The negative cell cycle regulators, p27(Kip1), p18(Ink4c), and GSK-3, play critical role in maintaining quiescence of adult human pancreatic beta-cells and restrict their ability to proliferate. Islets, 5, 156–169. https://doi.org/10.4161/ isl.25605. 27. Chun, S. Y., et al. (2015). Pdx1 and controlled culture conditions induced differentiation of human amniotic fluid-derived stem cells to insulin-producing clusters. Journal of Tissue Engineering and Regenerative Medicine, 9, 540–549. https://doi.org/10.1002/term.1631. 28. Walczak, M. P., Drozd, A. M., Stoczynska-Fidelus, E., Rieske, P., & Grzela, D. P. (2016). Directed differentiation of human iPSC into insulin producing cells is improved by induced expression of PDX1 and NKX6.1 factors in IPC progenitors. Journal of Translational Medicine, 14, 341. doi:https://doi.org/10.1186/s12967-016-1097-0. 29. Rezania, A., et al. (2014). Reversal of diabetes with insulin-producing cells derived in vitro from human pluripotent stem cells. Nature Biotechnology, 32, 1121–1133. https://doi.org/10. 1038/nbt.3033. 30. Perakakis, N., et al. (2012). Human Kruppel-like factor 11 differentially regulates human insulin promoter activity in beta-cells and non-beta-cells via p300 and PDX1 through the regulatory sites A3 and CACCC box. Molecular and Cellular Endocrinology, 363, 20–26. https://doi.org/10.1016/j.mce.2012.07.003. 31. Kajiyama, H., et al. (2010). Pdx1-transfected adipose tissue-derived stem cells differentiate into insulin-producing cells in vivo and reduce hyperglycemia in diabetic mice. International Journal of Developmental Biology, 54, 699–705. https://doi.org/10.1387/ijdb.092953hk.

64

3 Non-coding RNAS Related to Type 2 Diabetes

32. Chen, H., et al. (2011). PDGF signalling controls age-dependent proliferation in pancreatic beta-cells. Nature, 478, 349–355. https://doi.org/10.1038/nature10502. 33. Soria, B. (2001). In-vitro differentiation of pancreatic beta-cells. Differentiation, 68, 205–219. https://doi.org/10.1046/j.1432-0436.2001.680408.x. 34. Stadtfeld, M., Brennand, K., & Hochedlinger, K. (2008). Reprogramming of pancreatic beta cells into induced pluripotent stem cells. Current Biology, 18, 890–894. https://doi.org/10. 1016/j.cub.2008.05.010. 35. Zhao, M., et al. (2007). Evidence for the presence of stem cell-like progenitor cells in human adult pancreas. Journal of Endocrinology, 195, 407–414. https://doi.org/10.1677/JOE-070436. 36. Lopez-Beas, J., et al. (2018). miR-7 modulates hESC differentiation into insulin-producing beta-like cells and contributes to cell maturation. Mol Ther Nucleic Acids, 12, 463–477. https:// doi.org/10.1016/j.omtn.2018.06.002. 37. Xu, J., et al. (2015). miRNA-130b is required for the ERK/FOXM1 pathway activationmediated protective effects of isosorbide dinitrate against mesenchymal stem cell senescence induced by high glucose. International Journal of Molecular Medicine, 35, 59–71. https:// doi.org/10.3892/ijmm.2014.1985. 38. Fu, X., et al. (2013). MicroRNA-26a targets ten eleven translocation enzymes and is regulated during pancreatic cell differentiation. Proceedings of the National Academy of Sciences of the United States of America, 110, 17892–17897. https://doi.org/10.1073/pnas.1317397110. 39. Xu, H., et al. (2020). Pancreatic beta cell microRNA-26a alleviates type 2 diabetes by improving peripheral insulin sensitivity and preserving beta cell function. PLoS Biology, 18, e3000603. https://doi.org/10.1371/journal.pbio.3000603. 40. Gao, Y., et al. (2019). Role of TGF-beta/Smad pathway in the transcription of pancreasspecific genes during beta cell differentiation. Front Cell Dev Biol, 7, 351. https://doi.org/10. 3389/fcell.2019.00351. 41. Li, Y., et al. (2019). MicroRNA-223 is essential for maintaining functional beta-cell mass during diabetes through inhibiting both FOXO1 and SOX6 pathways. Journal of Biological Chemistry. https://doi.org/10.1074/jbc.RA119.007755. 42. Eliasson, L. (2017). The small RNA miR-375—A pancreatic islet abundant miRNA with multiple roles in endocrine beta cell function. Molecular and Cellular Endocrinology, 456, 95–101. https://doi.org/10.1016/j.mce.2017.02.043. 43. Poy, M. N., et al. (2009). miR-375 maintains normal pancreatic alpha- and beta-cell mass. Proceedings of the National Academy of Sciences of the United States of America, 106, 5813–5818. https://doi.org/10.1073/pnas.0810550106. 44. Sanchez-Parra, C., et al. (2018). Contribution of the long noncoding RNA H19 to beta-cell mass expansion in neonatal and adult rodents. Diabetes, 67, 2254–2267. https://doi.org/10. 2337/db18-0201. 45. Ruan, Y., et al. (2018). Circulating LncRNAs analysis in patients with type 2 diabetes reveals novel genes influencing glucose metabolism and islet beta-cell function. Cellular Physiology and Biochemistry, 46, 335–350. https://doi.org/10.1159/000488434. 46. Plaisance, V., et al. (2006). MicroRNA-9 controls the expression of Granuphilin/Slp4 and the secretory response of insulin-producing cells. Journal of Biological Chemistry, 281, 26932– 26942. https://doi.org/10.1074/jbc.M601225200. 47. Ramachandran, D., et al. (2011). Sirt1 and mir-9 expression is regulated during glucosestimulated insulin secretion in pancreatic beta-islets. FEBS Journal, 278, 1167–1174. https:// doi.org/10.1111/j.1742-4658.2011.08042.x. 48. Yu, L., et al. (2016). Artesunate protects pancreatic beta cells against cytokine-induced damage via SIRT1 inhibiting NF-kappaB activation. Journal of Endocrinological Investigation, 39, 83–91. https://doi.org/10.1007/s40618-015-0328-1. 49. Akerman, I., et al. (2017). Human pancreatic beta cell lncRNAs control cell-specific regulatory networks. Cell Metabolism, 25, 400–411. https://doi.org/10.1016/j.cmet.2016.11.016. 50. Arnes, L., Akerman, I., Balderes, D. A., Ferrer, J., & Sussel, L. (2016). Betalinc1 encodes a long noncoding RNA that regulates islet beta-cell formation and function. Genes & Development, 30, 502–507. https://doi.org/10.1101/gad.273821.115.

References

65

51. Hulsmans, M., et al. (2012). Decreased miR-181a expression in monocytes of obese patients is associated with the occurrence of metabolic syndrome and coronary artery disease. Journal of Clinical Endocrinology and Metabolism, 97, E1213-1218. https://doi.org/10.1210/jc.20121008. 52. You, L., et al. (2016). Downregulation of long noncoding RNA Meg3 affects insulin synthesis and secretion in mouse pancreatic beta cells. Journal of Cellular Physiology, 231, 852–862. https://doi.org/10.1002/jcp.25175. 53. Puthanveetil, P., Chen, S., Feng, B., Gautam, A., & Chakrabarti, S. (2015). Long non-coding RNA MALAT1 regulates hyperglycaemia induced inflammatory process in the endothelial cells. Journal of Cellular and Molecular Medicine, 19, 1418–1425. https://doi.org/10.1111/ jcmm.12576. 54. Jin, F., et al. (2017). Downregulation of long noncoding RNA Gas5 affects cell cycle and insulin secretion in mouse pancreatic beta cells. Cellular Physiology and Biochemistry, 43, 2062–2073. https://doi.org/10.1159/000484191. 55. Spohrer, S., et al. (2017). Functional interplay between the transcription factors USF1 and PDX-1 and protein kinase CK2 in pancreatic beta-cells. Scientific Reports, 7, 16367. https:// doi.org/10.1038/s41598-017-16590-0. 56. Grieco, F. A., et al. (2017). MicroRNAs miR-23a-3p, miR-23b-3p, and miR-149-5p regulate the expression of proapoptotic BH3-only proteins DP5 and PUMA in human pancreatic beta-cells. Diabetes, 66, 100–112. https://doi.org/10.2337/db16-0592. 57. Wang, N., et al. (2018). Long noncoding RNA Meg3 regulates Mafa expression in mouse beta cells by inactivating Rad21, Smc3 or Sin3alpha. Cellular Physiology and Biochemistry, 45, 2031–2043. https://doi.org/10.1159/000487983. 58. Kameswaran, V., et al. (2018). The dysregulation of the DLK1-MEG3 locus in islets from patients with type 2 diabetes is mimicked by targeted epimutation of its promoter with TALEDNMT constructs. Diabetes, 67, 1807–1815. https://doi.org/10.2337/db17-0682. 59. Melkman-Zehavi, T., et al. (2011). miRNAs control insulin content in pancreatic beta-cells via downregulation of transcriptional repressors. EMBO Journal, 30, 835–845. https://doi. org/10.1038/emboj.2010.361. 60. Navarro, F., et al. (2009). miR-34a contributes to megakaryocytic differentiation of K562 cells independently of p53. Blood, 114, 2181–2192. https://doi.org/10.1182/blood-2009-02205062. 61. Fan, C., et al. (2016). MiR-34a promotes osteogenic differentiation of human adipose-derived stem cells via the RBP2/NOTCH1/CYCLIN D1 coregulatory network. Stem Cell Reports, 7, 236–248. https://doi.org/10.1016/j.stemcr.2016.06.010. 62. Liu, C., et al. (2015). Upregulation of miR-34a-5p antagonizes AFB1-induced genotoxicity in F344 rat liver. Toxicon, 106, 46–56. https://doi.org/10.1016/j.toxicon.2015.09.016. 63. Gao, L., et al. (2019). LncRNA HOTAIR functions as a competing endogenous RNA to upregulate SIRT1 by sponging miR-34a in diabetic cardiomyopathy. Journal of Cellular Physiology, 234, 4944–4958. https://doi.org/10.1002/jcp.27296. 64. Sebastiani, G., et al. (2015). MicroRNA-124a is hyperexpressed in type 2 diabetic human pancreatic islets and negatively regulates insulin secretion. Acta Diabetologica, 52, 523–530. https://doi.org/10.1007/s00592-014-0675-y. 65. Baroukh, N., et al. (2007). MicroRNA-124a regulates Foxa2 expression and intracellular signaling in pancreatic beta-cell lines. Journal of Biological Chemistry, 282, 19575–19588. https://doi.org/10.1074/jbc.M611841200. 66. Divoux, A., et al. (2014). Identification of a novel lncRNA in gluteal adipose tissue and evidence for its positive effect on preadipocyte differentiation. Obesity (Silver Spring), 22, 1781–1785. https://doi.org/10.1002/oby.20793. 67. Zhu, H. P. (2020). Silence of HOTAIR inhibits insulin secretion and proliferation in pancreatic beta cells. European Review for Medical and Pharmacological Sciences, 24, 784–792. https:// doi.org/10.26355/eurrev_202001_20061. 68. Li, M., Guo, Y., Wang, X. J., Duan, B. H., & Li, L. (2018). HOTAIR participates in hepatic insulin resistance via regulating SIRT1. European Review for Medical and Pharmacological Sciences, 22, 7883–7890. https://doi.org/10.26355/eurrev_201811_16414.

66

3 Non-coding RNAS Related to Type 2 Diabetes

69. Zou, G., et al. (2016). miR-145 modulates lncRNA-ROR and Sox2 expression to maintain human amniotic epithelial stem cell pluripotency and beta islet-like cell differentiation efficiency. Gene, 591, 48–57. https://doi.org/10.1016/j.gene.2016.06.047. 70. Cheng, C. W. et al. (2017). Fasting-mimicking diet promotes Ngn3-driven beta-cell regeneration to reverse diabetes. Cell, 168, 775–788 e712, doi:https://doi.org/10.1016/j.cell.2017. 01.040. 71. Liew, C. W., et al. (2014). Insulin regulates carboxypeptidase E by modulating translation initiation scaffolding protein eIF4G1 in pancreatic beta cells. Proceedings of the National Academy of Sciences of the United States of America, 111, E2319-2328. https://doi.org/10. 1073/pnas.1323066111. 72. Francis, J., et al. (2006). Role of chromatin accessibility in the occupancy and transcription of the insulin gene by the pancreatic and duodenal homeobox factor 1. Molecular Endocrinology, 20, 3133–3145. https://doi.org/10.1210/me.2006-0126. 73. Mosley, A. L., & Ozcan, S. (2004). The pancreatic duodenal homeobox-1 protein (Pdx-1) interacts with histone deacetylases Hdac-1 and Hdac-2 on low levels of glucose. Journal of Biological Chemistry, 279, 54241–54247. https://doi.org/10.1074/jbc.M410379200. 74. Davidson, H. W., & Hutton, J. C. (1987). The insulin-secretory-granule carboxypeptidase H. Purification and demonstration of involvement in proinsulin processing. Biochem Journal, 245, 575–582. 75. Bailyes, E. M., et al. (1992). A member of the eukaryotic subtilisin family (PC3) has the enzymic properties of the type 1 proinsulin-converting endopeptidase. The Biochemical Journal, 285(Pt 2), 391–394. 76. Hall, E., et al. (2013). DNA methylation of the glucagon-like peptide 1 receptor (GLP1R) in human pancreatic islets. BMC Medical Genetics, 14, 76. https://doi.org/10.1186/1471-235014-76. 77. Hong, S. W., et al. (2012). Repression of sterol regulatory element-binding protein 1-c is involved in the protective effects of exendin-4 in pancreatic beta-cell line. Molecular and Cellular Endocrinology, 362, 242–252. https://doi.org/10.1016/j.mce.2012.07.004. 78. Natalicchio, A., et al. (2016). Long-term exposure of pancreatic beta-cells to palmitate results in SREBP-1C-dependent decreases in GLP-1 receptor signaling via CREB and AKT and insulin secretory response. Endocrinology, 157, 2243–2258. https://doi.org/10.1210/en.20152003. 79. McClelland Descalzo, D. L. et al. (2016). Glucose-induced oxidative stress reduces proliferation in embryonic stem cells via FOXO3A/beta-catenin-dependent transcription of p21(cip1). Stem Cell Reports, 7, 55–68. doi:https://doi.org/10.1016/j.stemcr.2016.06.006. 80. Xuan, S., et al. (2010). Genetic analysis of type-1 insulin-like growth factor receptor signaling through insulin receptor substrate-1 and -2 in pancreatic beta cells. Journal of Biological Chemistry, 285, 41044–41050. https://doi.org/10.1074/jbc.M110.144790. 81. Watson, R. T., Kanzaki, M., & Pessin, J. E. (2004). Regulated membrane trafficking of the insulin-responsive glucose transporter 4 in adipocytes. Endocrine Reviews, 25, 177–204. https://doi.org/10.1210/er.2003-0011. 82. Saltiel, A. R., & Pessin, J. E. (2003). Insulin signaling in microdomains of the plasma membrane. Traffic, 4, 711–716. 83. Chang, L., Chiang, S. H., & Saltiel, A. R. (2004). Insulin signaling and the regulation of glucose transport. Molecular Medicine, 10, 65–71. https://doi.org/10.2119/2005-00029.Sal tiel. 84. Shepherd, P. R. (2005). Mechanisms regulating phosphoinositide 3-kinase signalling in insulin-sensitive tissues. Acta Physiologica Scandinavica, 183, 3–12. https://doi.org/10.1111/ j.1365-201X.2004.01382.x. 85. Maehama, T., & Dixon, J. E. (1999). PTEN: A tumour suppressor that functions as a phospholipid phosphatase. Trends in Cell Biology, 9, 125–128. 86. Pesesse, X., Deleu, S., De Smedt, F., Drayer, L., & Erneux, C. (1997). Identification of a second SH2-domain-containing protein closely related to the phosphatidylinositol polyphosphate 5phosphatase SHIP. Biochemical and Biophysical Research Communications, 239, 697–700. https://doi.org/10.1006/bbrc.1997.7538.

References

67

87. Brachmann, S. M., Ueki, K., Engelman, J. A., Kahn, R. C., & Cantley, L. C. (2005). Phosphoinositide 3-kinase catalytic subunit deletion and regulatory subunit deletion have opposite effects on insulin sensitivity in mice. Molecular and Cellular Biology, 25, 1596–1607. https:// doi.org/10.1128/MCB.25.5.1596-1607.2005. 88. Yamaoka, M., et al. (2016). PI3K regulates endocytosis after insulin secretion by mediating signaling crosstalk between Arf6 and Rab27a. Journal of Cell Science, 129, 637–649. https:// doi.org/10.1242/jcs.180141. 89. Mora, A., Komander, D., van Aalten, D. M., & Alessi, D. R. (2004). PDK1, the master regulator of AGC kinase signal transduction. Seminars in Cell & Developmental Biology, 15, 161–170. 90. Sano, H., et al. (2003). Insulin-stimulated phosphorylation of a Rab GTPase-activating protein regulates GLUT4 translocation. Journal of Biological Chemistry, 278, 14599–14602. https:// doi.org/10.1074/jbc.C300063200. 91. Bouzakri, K., et al. (2008). Rab GTPase-activating protein AS160 is a major downstream effector of protein kinase B/Akt signaling in pancreatic beta-cells. Diabetes, 57, 1195–1204. https://doi.org/10.2337/db07-1469. 92. Chadt, A. et al. (2015). Deletion of both Rab-GTPase-activating proteins TBC14KO and TBC1D4 in mice eliminates insulin- and AICAR-stimulated glucose transport. Diabetes 2015;64:746–759. Diabetes, 64, 1492, doi:https://doi.org/10.2337/db15-er04. 93. Larance, M., et al. (2005). Characterization of the role of the Rab GTPase-activating protein AS160 in insulin-regulated GLUT4 trafficking. Journal of Biological Chemistry, 280, 37803– 37813. https://doi.org/10.1074/jbc.M503897200. 94. Welsh, G. I., et al. (2007). Rip11 is a Rab11- and AS160-RabGAP-binding protein required for insulin-stimulated glucose uptake in adipocytes. Journal of Cell Science, 120, 4197–4208. https://doi.org/10.1242/jcs.007310. 95. Martin, S., Slot, J. W., & James, D. E. (1999). GLUT4 trafficking in insulin-sensitive cells. A morphological review. Cell Biochem Biophys, 30, 89–113. doi: 10.1007/BF02737886. 96. Sharma, P. M., et al. (1998). Inhibition of phosphatidylinositol 3-kinase activity by adenovirusmediated gene transfer and its effect on insulin action. Journal of Biological Chemistry, 273, 18528–18537. 97. Karlsson, H. K., et al. (2005). Insulin-stimulated phosphorylation of the Akt substrate AS160 is impaired in skeletal muscle of type 2 diabetic subjects. Diabetes, 54, 1692–1697. 98. Accili, D., & Arden, K. C. (2004). FoxOs at the crossroads of cellular metabolism, differentiation, and transformation. Cell, 117, 421–426. 99. Tsunekawa, S., et al. (2011). FoxO feedback control of basal IRS-2 expression in pancreatic beta-cells is distinct from that in hepatocytes. Diabetes, 60, 2883–2891. https://doi.org/10. 2337/db11-0340. 100. Huo, X., et al. (2014). GSK3 protein positively regulates type I insulin-like growth factor receptor through forkhead transcription factors FOXO1/3/4. Journal of Biological Chemistry, 289, 24759–24770. https://doi.org/10.1074/jbc.M114.580738. 101. Manning, B. D., & Toker, A. (2017). AKT/PKB signaling: Navigating the network. Cell, 169, 381–405. https://doi.org/10.1016/j.cell.2017.04.001. 102. Long, X., Lin, Y., Ortiz-Vega, S., Yonezawa, K., & Avruch, J. (2005). Rheb binds and regulates the mTOR kinase. Current Biology, 15, 702–713. https://doi.org/10.1016/j.cub.2005.02.053. 103. Yoneyama, Y. et al. (2018). Serine phosphorylation by mTORC1 promotes IRS-1 degradation through SCFbeta-TRCP E3 Ubiquitin Ligase. iScience, 5, 1–18. doi:https://doi.org/10.1016/ j.isci.2018.06.006. 104. Holz, M. K., Ballif, B. A., Gygi, S. P., & Blenis, J. (2005). mTOR and S6K1 mediate assembly of the translation preinitiation complex through dynamic protein interchange and ordered phosphorylation events. Cell, 123, 569–580. https://doi.org/10.1016/j.cell.2005.10.024. 105. Isotani, S., et al. (1999). Immunopurified mammalian target of rapamycin phosphorylates and activates p70 S6 kinase alpha in vitro. Journal of Biological Chemistry, 274, 34493–34498. 106. Raught, B., et al. (2004). Phosphorylation of eucaryotic translation initiation factor 4B Ser422 is modulated by S6 kinases. EMBO Journal, 23, 1761–1769. https://doi.org/10.1038/sj.emboj. 7600193.

68

3 Non-coding RNAS Related to Type 2 Diabetes

107. Um, S. H., et al. (2015). S6K1 controls pancreatic beta cell size independently of intrauterine growth restriction. Journal of Clinical Investigation, 125, 2736–2747. https://doi.org/10.1172/ JCI77030. 108. Pende, M., et al. (2000). Hypoinsulinaemia, glucose intolerance and diminished beta-cell size in S6K1-deficient mice. Nature, 408, 994–997. https://doi.org/10.1038/35050135. 109. Blandino-Rosano, M., et al. (2017). Loss of mTORC1 signalling impairs beta-cell homeostasis and insulin processing. Nature Communications, 8, 16014. https://doi.org/10.1038/ncomms 16014. 110. Sarbassov, D. D., Guertin, D. A., Ali, S. M., & Sabatini, D. M. (2005). Phosphorylation and regulation of Akt/PKB by the rictor-mTOR complex. Science, 307, 1098–1101. https://doi. org/10.1126/science.1106148. 111. Kohn, A. D., Summers, S. A., Birnbaum, M. J., & Roth, R. A. (1996). Expression of a constitutively active Akt Ser/Thr kinase in 3T3-L1 adipocytes stimulates glucose uptake and glucose transporter 4 translocation. Journal of Biological Chemistry, 271, 31372–31378. 112. Gu, Y., Lindner, J., Kumar, A., Yuan, W., & Magnuson, M. A. (2011). Rictor/mTORC2 is essential for maintaining a balance between beta-cell proliferation and cell size. Diabetes, 60, 827–837. https://doi.org/10.2337/db10-1194. 113. Yuan, T., et al. (2017). Reciprocal regulation of mTOR complexes in pancreatic islets from humans with type 2 diabetes. Diabetologia, 60, 668–678. https://doi.org/10.1007/s00125016-4188-9. 114. Shoemaker, R., Yiannikouris, F., Thatcher, S., & Cassis, L. (2015). ACE2 deficiency reduces beta-cell mass and impairs beta-cell proliferation in obese C57BL/6 mice. American Journal of Physiology. Endocrinology and Metabolism, 309, E621-631. https://doi.org/10.1152/ajp endo.00054.2015. 115. Shi, T. T., et al. (2018). Angiotensin-converting enzyme 2 regulates mitochondrial function in pancreatic beta-cells. Biochemical and Biophysical Research Communications, 495, 860–866. https://doi.org/10.1016/j.bbrc.2017.11.055. 116. Wang, L., Liang, J., & Leung, P. S. (2015). The ACE2/Ang-(1–7)/Mas axis regulates the development of pancreatic endocrine cells in mouse embryos. PLoS ONE, 10, e0128216. https://doi.org/10.1371/journal.pone.0128216. 117. Wang, L., & Leung, P. S. (2013). The role of renin-angiotensin system in cellular differentiation: Implications in pancreatic islet cell development and islet transplantation. Molecular and Cellular Endocrinology, 381, 261–271. https://doi.org/10.1016/j.mce.2013.08.008. 118. Wu, J., et al. (2017). Pancreatic mitochondrial complex I exhibits aberrant hyperactivity in diabetes. Biochemistry and Biophysics Reports, 11, 119–129. https://doi.org/10.1016/j.bbrep. 2017.07.007. 119. Houtkooper, R. H., Pirinen, E., & Auwerx, J. (2012). Sirtuins as regulators of metabolism and healthspan. Nature Reviews Molecular Cell Biology, 13, 225–238. https://doi.org/10.1038/ nrm3293. 120. Eijkelenboom, A., & Burgering, B. M. (2013). FOXOs: Signalling integrators for homeostasis maintenance. Nature Reviews Molecular Cell Biology, 14, 83–97. https://doi.org/10.1038/nrm 3507. 121. Kobayashi, Y., et al. (2005). SIRT1 is critical regulator of FOXO-mediated transcription in response to oxidative stress. International Journal of Molecular Medicine, 16, 237–243. 122. Tseng, A. H., Shieh, S. S., & Wang, D. L. (2013). SIRT3 deacetylates FOXO3 to protect mitochondria against oxidative damage. Free Radical Biology and Medicine, 63, 222–234. https://doi.org/10.1016/j.freeradbiomed.2013.05.002. 123. Wang, N., et al. (2017). Amelioration of streptozotocininduced pancreatic beta cell damage by morin: Involvement of the AMPKFOXO3catalase signaling pathway. International Journal of Molecular Medicine. https://doi.org/10.3892/ijmm.2017.3357. 124. Kataoka, H. U., & Noguchi, H. (2013). ER stress and beta-cell pathogenesis of type 1 and type 2 diabetes and islet transplantation. Cell Med, 5, 53–57. https://doi.org/10.3727/215517 913X666512.

References

69

125. Eizirik, D. L., Cardozo, A. K., & Cnop, M. (2008). The role for endoplasmic reticulum stress in diabetes mellitus. Endocrine Reviews, 29, 42–61. https://doi.org/10.1210/er.2007-0015. 126. Li, Y., et al. (2019). Gymnemic acid alleviates type 2 diabetes mellitus and suppresses endoplasmic reticulum stress in vivo and in vitro. Journal of Agriculture and Food Chemistry, 67, 3662–3669. https://doi.org/10.1021/acs.jafc.9b00431. 127. Herbert, T. P., & Laybutt, D. R. (2016). A reevaluation of the role of the unfolded protein response in islet dysfunction: Maladaptation or a failure to adapt? Diabetes, 65, 1472–1480. https://doi.org/10.2337/db15-1633. 128. Chan, S. M. H., et al. (2017). Angiotensin II causes beta-cell dysfunction through an ER stress-induced proinflammatory response. Endocrinology, 158, 3162–3173. https://doi.org/ 10.1210/en.2016-1879. 129. Chen, J., et al. (2018). Glucagon-like peptide-1 receptor regulates endoplasmic reticulum stress-induced apoptosis and the associated inflammatory response in chondrocytes and the progression of osteoarthritis in rat. Cell Death Disease, 9, 212. https://doi.org/10.1038/s41 419-017-0217-y. 130. Solinas, G., & Becattini, B. (2017). JNK at the crossroad of obesity, insulin resistance, and cell stress response. Molecular Metabolism, 6, 174–184. https://doi.org/10.1016/j.molmet. 2016.12.001. 131. Wan, S., et al. (2017). Increased serum miR-7 is a promising biomarker for type 2 diabetes mellitus and its microvascular complications. Diabetes Research and Clinical Practice, 130, 171–179. https://doi.org/10.1016/j.diabres.2017.06.005. 132. Xu, H., Guo, S., Li, W., & Yu, P. (2015). The circular RNA Cdr1as, via miR-7 and its targets, regulates insulin transcription and secretion in islet cells. Scientific Reports, 5, 12453. https:// doi.org/10.1038/srep12453. 133. Latreille, M., et al. (2014). MicroRNA-7a regulates pancreatic beta cell function. Journal of Clinical Investigation, 124, 2722–2735. https://doi.org/10.1172/JCI73066. 134. Wang, Y., Liu, J., Liu, C., Naji, A., & Stoffers, D. A. (2013). MicroRNA-7 regulates the mTOR pathway and proliferation in adult pancreatic beta-cells. Diabetes, 62, 887–895. https://doi. org/10.2337/db12-0451. 135. Giles, K. M., Brown, R. A., Epis, M. R., Kalinowski, F. C., & Leedman, P. J. (2013). miRNA7-5p inhibits melanoma cell migration and invasion. Biochemical and Biophysical Research Communications, 430, 706–710. https://doi.org/10.1016/j.bbrc.2012.11.086. 136. Duan, J., et al. (2019). miR-29a negatively affects glucose-stimulated insulin secretion and MIN6 cell proliferation via Cdc42/beta-catenin signaling. International Journal Endocrinology, 2019, 5219782. https://doi.org/10.1155/2019/5219782. 137. Mollet, I. G., Malm, H. A., Wendt, A., Orho-Melander, M., & Eliasson, L. (2016). Integrator of stress responses calmodulin binding transcription activator 1 (Camta1) regulates miR212/miR-132 expression and insulin secretion. Journal of Biological Chemistry, 291, 18440– 18452. https://doi.org/10.1074/jbc.M116.716860. 138. Shang, J., et al. (2015). Induction of miR-132 and miR-212 expression by glucagon-like peptide 1 (GLP-1) in rodent and human pancreatic beta-cells. Molecular Endocrinology, 29, 1243–1253. https://doi.org/10.1210/me.2014-1335. 139. Massart, J., et al. (2017). Altered miR-29 expression in type 2 diabetes influences glucose and lipid metabolism in skeletal muscle. Diabetes, 66, 1807–1818. https://doi.org/10.2337/db170141. 140. Karolina, D. S., et al. (2011). MicroRNA 144 impairs insulin signaling by inhibiting the expression of insulin receptor substrate 1 in type 2 diabetes mellitus. PLoS ONE, 6, e22839. https://doi.org/10.1371/journal.pone.0022839. 141. Jones, A., et al. (2017). miRNA signatures of insulin resistance in obesity. Obesity (Silver Spring), 25, 1734–1744. https://doi.org/10.1002/oby.21950. 142. Wen, F., et al. (2014). MiRNA-145 is involved in the development of resistin-induced insulin resistance in HepG2 cells. Biochemical and Biophysical Research Communications, 445, 517–523. https://doi.org/10.1016/j.bbrc.2014.02.034.

70

3 Non-coding RNAS Related to Type 2 Diabetes

143. Simionescu, N., et al. (2016). Hyperglycemia determines increased specific MicroRNAs levels in Sera and HDL of acute coronary syndrome patients and stimulates MicroRNAs production in human macrophages. PLoS ONE, 11, e0161201. https://doi.org/10.1371/journal.pone.016 1201. 144. Jia, C. Y., et al. (2011). MiR-223 suppresses cell proliferation by targeting IGF-1R. PLoS ONE, 6, e27008. https://doi.org/10.1371/journal.pone.0027008. 145. Sun, X., et al. (2016). MicroRNA-181b improves glucose homeostasis and insulin sensitivity by regulating endothelial function in white adipose tissue. Circulation Research, 118, 810– 821. https://doi.org/10.1161/CIRCRESAHA.115.308166. 146. El Ouaamari, A., et al. (2008). miR-375 targets 3’-phosphoinositide-dependent protein kinase1 and regulates glucose-induced biological responses in pancreatic beta-cells. Diabetes, 57, 2708–2717. https://doi.org/10.2337/db07-1614. 147. Xin, Y., et al. (2018). Resveratrol improves uric acid-induced pancreatic beta-cells injury and dysfunction through regulation of miR-126. Biomedicine & Pharmacotherapy, 102, 1120– 1126. https://doi.org/10.1016/j.biopha.2018.03.172. 148. Stoll, L., et al. (2018). Circular RNAs as novel regulators of beta-cell functions in normal and disease conditions. Molecular Metabolism, 9, 69–83. https://doi.org/10.1016/j.molmet.2018. 01.010. 149. Backe, M. B., Novotny, G. W., Christensen, D. P., Grunnet, L. G., & Mandrup-Poulsen, T. (2014). Altering beta-cell number through stable alteration of miR-21 and miR-34a expression. Islets, 6, e27754. https://doi.org/10.4161/isl.27754. 150. Lu, H., et al. (2016). Elevated circulating stearic acid leads to a major lipotoxic effect on mouse pancreatic beta cells in hyperlipidaemia via a miR-34a-5p-mediated PERK/p53-dependent pathway. Diabetologia, 59, 1247–1257. https://doi.org/10.1007/s00125-016-3900-0. 151. Song, Y., Jin, D., Jiang, X., Lv, C., & Zhu, H. (2018). Overexpression of microRNA-26a protects against deficient beta-cell function via targeting phosphatase with tensin homology in mouse models of type 2 diabetes. Biochemical and Biophysical Research Communications, 495, 1312–1316. https://doi.org/10.1016/j.bbrc.2017.11.170. 152. Chen, L., Gong, H. Y., & Xu, L. (2018). PVT1 protects diabetic peripheral neuropathy via PI3K/AKT pathway. European Review for Medical Pharmacological Sciences, 22, 6905– 6911. https://doi.org/10.26355/eurrev_201810_16160. 153. You, L., et al. (2014). MiR-378 overexpression attenuates high glucose-suppressed osteogenic differentiation through targeting CASP3 and activating PI3K/Akt signaling pathway. International Journal of Clinical and Experimental Pathology, 7, 7249–7261. 154. Xiao, D., et al. (2018). MicroRNA-17 impairs glucose metabolism in insulin-resistant skeletal muscle via repressing glucose transporter 4 expression. European Journal of Pharmacology, 838, 170–176. https://doi.org/10.1016/j.ejphar.2018.08.036. 155. Guo, R., et al. (2012). MicroRNA miR-491-5p targeting both TP53 and Bcl-XL induces cell apoptosis in SW1990 pancreatic cancer cells through mitochondria mediated pathway. Molecules, 17, 14733–14747. https://doi.org/10.3390/molecules171214733. 156. Cadenas, S. (1859). Mitochondrial uncoupling, ROS generation and cardioprotection. Biochim Biophys Acta Bioenerg, 940–950, 2018. https://doi.org/10.1016/j.bbabio.2018.05.019. 157. Zhu, Y., et al. (2019). MicroRNA-24 promotes pancreatic beta cells toward dedifferentiation to avoid endoplasmic reticulum stress-induced apoptosis. Journal of Molecular Cell Biology. https://doi.org/10.1093/jmcb/mjz004. 158. Liang, J., et al. (2013). MiR-138 induces renal carcinoma cell senescence by targeting EZH2 and is downregulated in human clear cell renal cell carcinoma. Oncology Research, 21, 83–91. https://doi.org/10.3727/096504013X13775486749218. 159. Law, P. T., et al. (2012). MiR-145 modulates multiple components of the insulin-like growth factor pathway in hepatocellular carcinoma. Carcinogenesis, 33, 1134–1141. https://doi.org/ 10.1093/carcin/bgs130. 160. Li, Y., Luo, T., Wang, L., Wu, J., & Guo, S. (2016). MicroRNA-19a-3p enhances the proliferation and insulin secretion, while it inhibits the apoptosis of pancreatic beta cells via the inhibition of SOCS3. International Journal of Molecular Medicine, 38, 1515–1524. https:// doi.org/10.3892/ijmm.2016.2748.

References

71

161. Kameswaran, V., et al. (2014). Epigenetic regulation of the DLK1-MEG3 microRNA cluster in human type 2 diabetic islets. Cell Metabolism, 19, 135–145. https://doi.org/10.1016/j.cmet. 2013.11.016. 162. Sims, E. K., et al. (2017). MicroRNA 21 targets BCL2 mRNA to increase apoptosis in rat and human beta cells. Diabetologia, 60, 1057–1065. https://doi.org/10.1007/s00125-017-4237-z. 163. Ruan, Q., et al. (2011). The microRNA-21-PDCD4 axis prevents type 1 diabetes by blocking pancreatic beta cell death. Proceedings of the National Academy of Sciences of the United States of America, 108, 12030–12035. https://doi.org/10.1073/pnas.1101450108. 164. Wang, J., et al. (2017). Metformin ameliorates skeletal muscle insulin resistance by inhibiting miR-21 expression in a high-fat dietary rat model. Oncotarget, 8, 98029–98039. https://doi. org/10.18632/oncotarget.20442. 165. Zhang, Z., et al. (2013). Negative regulation of lncRNA GAS5 by miR-21. Cell Death and Differentiation, 20, 1558–1568. https://doi.org/10.1038/cdd.2013.110. 166. Bresin, A., et al. (2015). miR-181b as a therapeutic agent for chronic lymphocytic leukemia in the Emicro-TCL1 mouse model. Oncotarget, 6, 19807–19818. https://doi.org/10.18632/ oncotarget.4415. 167. O’Connor, J. C., Sherry, C. L., Guest, C. B., & Freund, G. G. (2007). Type 2 diabetes impairs insulin receptor substrate-2-mediated phosphatidylinositol 3-kinase activity in primary macrophages to induce a state of cytokine resistance to IL-4 in association with overexpression of suppressor of cytokine signaling-3. The Journal of Immunology, 178, 6886–6893. 168. Pedroso, J. A. B., Ramos-Lobo, A. M., & Donato, J., Jr. (2019). SOCS3 as a future target to treat metabolic disorders. Hormones (Athens), 18, 127–136. https://doi.org/10.1007/s42000018-0078-5. 169. Gordon, P., Okai, B., Hoare, J. I., Erwig, L. P., & Wilson, H. M. (2016). SOCS3 is a modulator of human macrophage phagocytosis. Journal of Leukocyte Biology, 100, 771–780. https://doi. org/10.1189/jlb.3A1215-554RR. 170. Donath, M. Y., Boni-Schnetzler, M., Ellingsgaard, H., Halban, P. A., & Ehses, J. A. (2010). Cytokine production by islets in health and diabetes: Cellular origin, regulation and function. Trends in Endocrinology and Metabolism, 21, 261–267. https://doi.org/10.1016/j.tem.2009. 12.010. 171. Rutti, S., et al. (2014). Fractalkine (CX3CL1), a new factor protecting beta-cells against TNFalpha. Molecular Metabolism, 3, 731–741. https://doi.org/10.1016/j.molmet.2014. 07.007. 172. Jagannathan-Bogdan, M., et al. (2011). Elevated proinflammatory cytokine production by a skewed T cell compartment requires monocytes and promotes inflammation in type 2 diabetes. The Journal of Immunology, 186, 1162–1172. https://doi.org/10.4049/jimmunol.1002615. 173. Russell, M. A., & Morgan, N. G. (2014). The impact of anti-inflammatory cytokines on the pancreatic beta-cell. Islets, 6, e950547. https://doi.org/10.4161/19382014.2014.950547. 174. Kelly-Welch, A. E., Hanson, E. M., Boothby, M. R., & Keegan, A. D. (2003). Interleukin-4 and interleukin-13 signaling connections maps. Science, 300, 1527–1528. https://doi.org/10. 1126/science.1085458. 175. Wills-Karp, M., & Finkelman, F. D. (2008). Untangling the complex web of IL-4- and IL13-mediated signaling pathways. Science Signaling, 1, pe55. doi:https://doi.org/10.1126/sci signal.1.51.pe55. 176. Rutti, S., et al. (2016). IL-13 improves beta-cell survival and protects against IL-1beta-induced beta-cell death. Molecular Metabolism, 5, 122–131. https://doi.org/10.1016/j.molmet.2015. 11.003. 177. Kwon, H., et al. (2014). Adipocyte-specific IKKbeta signaling suppresses adipose tissue inflammation through an IL-13-dependent paracrine feedback pathway. Cell Reports, 9, 1574– 1583. https://doi.org/10.1016/j.celrep.2014.10.068. 178. Sun, T., et al. (2017). MiR-146a aggravates LPS-induced inflammatory injury by targeting CXCR4 in the articular chondrocytes. Cellular Physiology and Biochemistry, 44, 1282–1294. https://doi.org/10.1159/000485488.

72

3 Non-coding RNAS Related to Type 2 Diabetes

179. Chen, P., et al. (2019). MiR-455-5p ameliorates HG-induced apoptosis, oxidative stress and inflammatory via targeting SOCS3 in retinal pigment epithelial cells. Journal of Cellular Physiology, 234, 21915–21924. https://doi.org/10.1002/jcp.28755. 180. Jiang, X., et al. (2017). MiR-30a targets IL-1alpha and regulates islet functions as an inflammation buffer and response factor. Scientific Reports, 7, 5270. https://doi.org/10.1038/s41598017-05560-1. 181. Koh, E. H., et al. (2018). miR-30a remodels subcutaneous adipose tissue inflammation to improve insulin sensitivity in obesity. Diabetes, 67, 2541–2553. https://doi.org/10.2337/db171378. 182. Bao, F., Slusher, A. L., Whitehurst, M., & Huang, C. J. (2018). Circulating microRNAs are upregulated following acute aerobic exercise in obese individuals. Physiology & Behavior, 197, 15–21. https://doi.org/10.1016/j.physbeh.2018.09.011. 183. Yan, H. et al. (2016). Expression profile analysis of miR-221 and miR-222 in different tissues and head kidney cells of cynoglossus semilaevis, following pathogen infection. Mar Biotechnol (NY), 18, 37−48. doi:https://doi.org/10.1007/s10126-015-9668-2. 184. Roggli, E., et al. (2010). Involvement of microRNAs in the cytotoxic effects exerted by proinflammatory cytokines on pancreatic beta-cells. Diabetes, 59, 978–986. https://doi.org/ 10.2337/db09-0881. 185. Alipoor, B., et al. (2017). Association of MiR-146a expression and type 2 diabetes mellitus: A meta-analysis. International Journal of Molecular and Cellular Medicine, 6, 156–163. https:// doi.org/10.22088/acadpub.BUMS.6.3.156. 186. Choi, S. E., et al. (2013). Elevated microRNA-34a in obesity reduces NAD+ levels and SIRT1 activity by directly targeting NAMPT. Aging Cell, 12, 1062–1072. https://doi.org/10.1111/ acel.12135. 187. Ding, N., Wu, H., Tao, T., & Peng, E. (2017). NEAT1 regulates cell proliferation and apoptosis of ovarian cancer by miR-34a-5p/BCL2. Onco Targets Ther, 10, 4905–4915. https://doi.org/ 10.2147/OTT.S142446. 188. Kesherwani, V., Shahshahan, H. R., & Mishra, P. K. (2017). Cardiac transcriptome profiling of diabetic Akita mice using microarray and next generation sequencing. PLoS ONE, 12, e0182828. https://doi.org/10.1371/journal.pone.0182828.

Chapter 4

Non-coding RNAs Related to Lipid Metabolism and Non-alcoholic Fatty Liver Disease

Abstract MiR-24, miR-122, down-regulating miR-21, and lncARSR, and the decrease of miR-98 are associated with increased liver cholesterol synthesis. In contrast, miR-29a/b/c, miR-185, miR-195 and miR-223 inhibit cholesterol synthesis. MiR-140-5p, miR-148, and miR-185 block the uptake of LDL via the LDL receptor. MiR-27 up-regulates PCSK9, inducing the degradation of the LDL receptor. MiR223, CHROME, and MeXiS stimulate cholesterol efflux through ABCA1 and ABCG1. The decrease of miR-613 exacerbates cholesterol efflux. In contrast, miR19b, miR-26, miR-27, miR-33a/b, miR-34a, miR-101, miR-128-2, miR-144, miR145, miR-148, miR-302a, miR-758, and lnc-HC block this efflux. MiR-24, miR-96, miR-185, and miR-223 block uptake of HDL-cholesteryl esters via SR-B1. LeXiS increases LDL and HDL cholesterol. MiR-26a and miR-133a prevent CD36 lipid uptake. LncRNA HULC, silencing miR-9, induces FA oxidation inhibited by miR27a, miR-30a, miR-34a, and miR-222. Impaired expression of miR-17, miR-21, miR-29, miR-30a/b/c, miR-34a, miR-124, miR-130, miR-138, miR-150, miR-155, miR-181, miR-221, miR-223, miR-375, miR-378, and miR-455, and lncRNAs H19, MALAT1, MEG3, and NEAT1 is associated with non-alcoholic fatty liver disease. They are linking obesity and type 2 diabetes with non-alcoholic fatty liver disease.

4.1 Cholesterol and Lipids in the Liver A tightly regulated and complex mechanism involving de novo biosynthesis, internalization of exogenous cholesterol, and efflux of excess cholesterol determines cellular cholesterol levels. Cholesterol synthesis from acetyl-CoA involves a series of approximately 30 reactions. 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) and squalene monooxygenase are the rate-limiting enzymes [1]. Another essential regulator is the endoplasmic reticulum (ER)-bound sterol regulatory element-binding protein (SREBP)-2 that coordinates cholesterol synthesis by activating HMGCR. SREBP2 also regulates the low-density lipoprotein receptor (LDLR), which imports cholesterol from the blood [1–3]. The forkhead box (FOXO)-3 down-regulates SREBP2 by recruiting sirtuin (SIRT)-6, which deacetylates histone H3 [4] (Fig. 4.1).

Illustrations by Pieterjan Ginckels, Faculty of Architecture, KU Leuven, Ghent, Belgium. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 P. Holvoet, Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer, https://doi.org/10.1007/978-3-030-68844-8_4

73

74

4 Non-coding RNAs Related to Lipid Metabolism …

Fig. 4.1 Non-coding RNAs in cholesterol metabolism. LeXiS increases LDL and HDL cholesterol. SREBP2, HMGCR, and SM regulate cholesterol synthesis. The increase of miR-24, miR-122 by down-regulating miR-21, and lncARSR, and the decrease of miR-98 is associated with increased cholesterol synthesis. In contrast, miR-29a/b/c, miR-185, miR-195 and miR-223 inhibit cholesterol synthesis. MiR-140-5p, miR-148, and miR-185 block the uptake of LDL via the LDL receptor. MiR27a up-regulates PCSK9, which induces the degradation of the LDL receptor. MiR-223, CHROME, and MeXiS stimulate cholesterol efflux through ABCA1 and ABCG1. The decrease of miR-623 exacerbates this efflux. In contrast, miR-19b, miR-26, miR-27, miR-33a/b, miR-34a, miR-101, miR128-2, miR-144, miR-145, miR-148, miR-302a, miR-758, and lnc-HC block cholesterol efflux. LCAT esterifies cholesterol to cholesteryl esters, converting pre-β to mature HDL. Cholesteryl esters may be taken up through SR-B1. MiR-24, miR-96, miR-185, and miR-223 block uptake of HDL-cholesteryl esters via SR-B1. Alternatively, CETP transfers cholesteryl esters from HDL to (V)LDL, taken up via the LDL receptor. Finally, ER-bound ACAT esterifies cholesterol. Cholesteryl esters accumulate as lipid droplets. MiR-26a and miR-133a block the CD36-mediated uptake of FA, while miR-27a, miR-30a, miR-34a, and miR-222 block FA oxidation in the liver. HULC, silencing miR-9, may stimulate FA oxidation

Besides de novo biosynthesis, cholesterol in the blood can be taken up by LDLR at the hepatocytes’ basal surface. Lack of functional LDLR in the liver leads to a massive accumulation of LDL in the artery wall and atherosclerosis [5]. The FOXO3–SIRT6 complex represses proprotein convertase subtilisin/kexin type 9 (PCSK9). PCSK9 is an SREBP2 target that binds LDLR on the plasma membrane and is internalized with the LDLR protein in clathrin-coated vesicles, preventing LDLR from recycling back to the surface. The PCSK9–LDLR complex is eventually degraded in lysosomes,

4.1 Cholesterol and Lipids in the Liver

75

involving the ubiquitin ligase inducible degrader of LDLR (IDOL or MYLIP) and liver X receptor (LXR) [6, 7] (Fig. 4.1). Excess cholesterol in peripheral tissues is exported to the blood by ATP-binding cassette subfamily A member 1 (ABCA1) or ABCG1 or to the intestinal lumen and bile ducts by the ABCG5 and ABCG8 heterodimer [8]. Cholesterol blocks the nuclear entry of nuclear factor erythroid two related factor one (NRF1) and subsequently de-represses the activity of LXR, regulating the expression of ABCA1, ABCG1, ABCG5, and ABCG8. Lipid-poor pre-beta high-density lipoproteins (HDL), rich in apolipoprotein (APO)A1, are synthesized by the liver or intestinal mucosa and released into circulation. ABCA1 facilitates the efflux of phospholipids and cholesterol to APOA1 to generate nascent, discoidal HDL particles. Lecithin-cholesterol acyltransferase (LCAT) esterifies free cholesterol and converts pre-beta HDL to mature HDL. Mature HDL takes up ABCG1-effluxed cholesterol. Cholesteryl esters may also be taken up directly through scavenger receptor class B type 1 (SR-B1) (Fig. 4.1). Alternatively, esters are transferred to apoB-containing lipoproteins (VLDL/LDL) through cholesteryl ester transfer protein (CETP) and then transported to the liver through the LDL receptor [9–11]. Excess cholesterol can also allosterically activate acetyl-CoA C-acetyltransferase (ACAT) in the ER. Active ACAT esterifies cholesterol. Cholesteryl esters are stored as lipid droplets or secreted as chylomicrons and very-low-density lipoproteins (VLDLs) [12].

4.1.1 Non-coding RNAs and Cholesterol in the Liver Hepatic expression of lncRNAs LeXis elevated in response to a high fat and cholesterol diet, increases LDL and HDL cholesterol, independently of LDL receptor and ABCA1. LeXis interacts with and affects the DNA interactions of RALY heterogeneous nuclear ribonucleoprotein (RALY). This heterogeneous ribonucleoprotein acts as a transcriptional cofactor for cholesterol biosynthesis in the mouse liver [13]. Obesity-induced miR-24 increases the expression of HMGCR [14]. MiR-122 downregulates miR-21 increasing HMGCR transcription and translation [15, 16]. The lncRNA regulator of Akt signaling associated with HCC and RCC (lncARSR) activates the PI3K/AKT pathway and increases the expression of mature SREBP2 and HMGCR [17]. The decrease of miR-98 in hypercholesterolemic patients is associated with increased SREBP2 [18]. MiR-29a/b/c significantly suppresses HMGCR expression [19]. MiR-185 decreases the transcription of SREBP2 and HMGCR [20]. MiR-195 down-regulates SREBF2, HMGCR, and LDLR and up-regulates PCSK9 by reverting the action of nuclear factor kappa B (NFκB) [21]. MiR-223 inhibits cholesterol biosynthesis through the direct repression of sterol enzymes 3-hydroxy-3-methylglutaryl-CoA synthase 1 and methylsterol monooxygenase 1.

76

4 Non-coding RNAs Related to Lipid Metabolism …

MiR-27a induces PCSK9, degrading LDLR [22]. MiR-140-5p and miR-185 directly repress LDLR expression [23, 24]. MiR-148a decreases hepatic LDLR and ABCA1 expression [25]. MiR-223 indirectly promotes ABCA1 through Sp3 transcription factor (SP3) [26]. LncRNA CHROME promotes cholesterol efflux and HDL biogenesis by curbing the actions of miR-27b, miR-33a, miR-33b, and miR-128 [27]. LncRNA MeXis in mouse peritoneal macrophages increases ABCA1 transcript [28]. PPARγ suppresses miR-613, thereby increasing LXRα and ABCA1 [29]. MiR-19b, miR-26, miR-27, miR-33a/b, miR-34a, miR-101, miR-128-2, miR-144, miR-145, miR-148, miR-302a, and miR-758 repress ABCA1 and/or ABCG1 [30– 43]. The lncRNA derived from hepatocytes (lnc-HC) silences ABCA1 by binding to the heterogeneous nuclear ribonucleoprotein A2/B1 [44]. MiR-24, miR-96, miR-185, and miR-223 repress uptake of HDL-associated cholesteryl esters through SR-BI [14, 45] (Fig. 4.1). MiR-378a-3p stabilizes apoB100, the predominant lipoprotein in LDL [46].

4.2 Fatty Acids and Triglycerides Metabolism of fatty acids (FA) and their storage in triglycerides (TG) occurs primarily in hepatocytes. Daily, the liver processes large quantities of FA but stores less than 5% in TG [47]. Naturally, the FA oxidation rates and secretion balance FA’s acquisition by uptake from the plasma and de novo synthesis within the liver into plasma as TG-enriched VLDL. The relatively small quantities of TG are stored in cytoplasmic lipid droplets in the liver. FA within the liver originates from either dietary or endogenous sources. Insulin resistance in WAT increases lipolysis and the entry of non-esterified fatty acids in the liver. Hyperinsulinemia resulting from insulin resistance promotes hepatic de novo lipogenesis [48, 49]. Plasma insulin activates the ER-bound SREBP-1c that up-regulates all genes in the FA biosynthetic pathway [50]. The hepatic uptake of excess plasma glucose promotes the nuclear translocation of the carbohydrate response element-binding protein that up-regulates most FA biosynthetic genes plus pyruvate kinase that increases the availability of citrate for FA synthesis [51]. When plasma insulin concentrations are low under fasting conditions, a lipolytic program is initiated in WAT, which increases the plasma FA pool that is available for uptake by the liver [52]. Bile acids emulsify dietary TG within the intestinal lumen following their hydrolysis primarily by pancreatic lipase, yielding sn-2-monoacylglycerols, and free FA [53]. Following emulsification, these lipid molecules are taken by enterocytes and resynthesized into TG. TG are packaged into chylomicrons, secreted into the lymphatic system, and ultimately reach the plasma [54]. TG remaining within the chylomicron remnants undergo receptor-mediated endocytosis in the liver, releasing FA [55]. Hepatocytes take up FA via plasma membrane-associated FA-binding

4.2 Fatty Acids and Triglycerides

77

protein, FA translocase (FAT)/CD36, caveolin-1, and FATP/solute carrier family 27A1–6) [56–58]. In the outer membrane of mitochondria, long-chain acyl-CoA synthetase 1 (ACSL1) converts long-chain FA to acyl-coAs. ACSL1 interacts with carnitine palmitoyltransferase. Additionally, acyl-coAs can undergo β oxidation in peroxisomes regulated by the fatty acyl-CoA oxidase (AOX), or α and ω oxidation in ERmediated by family members. The expression of genes involved in mitochondrial and extramitochondrial FA oxidation is regulated by PPARα [59–62] (Fig. 4.1).

4.2.1 Non-coding RNAs and Fatty Acids and Triglycerides MiR-26a and miR-133a suppress CD36-mediated FA uptake [63, 64]. The hepatocellular carcinoma up-regulated long non-coding RNA (HULC) correlates positively with ACSL1 by silencing miR-9, thereby de-repressing PPARα that induces ACSL1 [65]. MiR-27a-3p, miR-34a-5p and miR-205, silencing ACSL1, miR-30a-3p and miR-34a, silencing CPT1, and miR-222, silencing ACOX1 expression, inhibit FA oxidation and promote TG accumulation [66–71] (Fig. 4.1).

4.3 Non-alcoholic Fatty Liver Disease Above, we have discussed the contribution of nutrient excess and low physical activity in obesity and type 2 diabetes. Nutrient excess and low physical activity are also associated with increased lipid uptake and lipogenesis in the liver. Increased intrahepatic triglyceride levels leading to hepatic steatosis are the hallmark features of non-alcoholic fatty liver disease (NAFLD). Increased gluconeogenesis is associated with increased intrahepatic glucose and insulin resistance. Weight loss reduces NAFLD [72, 73] (Fig. 4.2). The deposition of glucose and lipids in the liver is associated with mitochondrial dysfunction and increased mitochondrial reactive oxygen species (ROS), promoting inflammation, insulin resistance, and cell death, thereby aggravating NAFLD development [74–80]. Lipotoxic hepatocellular injury attracts inflammatory cells, mainly activated M1 macrophages. They surround ballooned hepatocytes as crown-like structures. Some macrophages derive from circulating monocytes, but Kupffer cells are the most highly represented macrophages in the liver [81–83]. An increase of M1-polarized macrophages, possibly induced by interferon regulatory factor (IRF)-5, promotes or exacerbates fibrosis, cirrhosis, and eventual liver failure [84, 85]. The 12lipoxygenase converts polyunsaturated fatty acids to oxidized pro-inflammatory lipid intermediates. The latter link inflammation, oxidative stress, and insulin resistance [86, 87] (Fig. 4.2). Lipotoxicity is also associated with the release of danger-associated molecular patterns (DAMPs). They stimulate innate immunity by binding Toll-like receptor

78

4 Non-coding RNAs Related to Lipid Metabolism …

Fig. 4.2 Non-coding RNAs in non-alcoholic fatty liver disease, a comorbid complication of obesity, and type 2 diabetes. Nutrient excess and low physical activity lead to obesity and type 2 diabetes, associated with increased liver uptake of lipids and de novo lipogenesis, increasing blood triglyceride levels. Lipid accumulation is facilitated by the increase of miR-17, miR-21, miR-29, miR-30a, miR-34a, miR-124, by loss of sponging NEAT1, miR-141-200c, miR-150, miR-181a/b, miR-190b, miR-221-222, ARSR, HULC, and NEAT1/miR-140 paraspeckles. The decrease of miR30c-5p, miR-130a, silenced by H19, miR-138, miR-455, and lncRNA B4GALT1 exacerbates lipid accumulation. Nutrient excess and low physical activity are also associated with increased gluconeogenesis and glucose uptake induced by the increase of miR-21, miR-150, and miR-190b, and the decrease of B4GALT1, leading to high glucose levels. High lipid and glucose levels induced miR-34a expression associated with mitochondrial stress and increased ROS. High glucose and lipids also induce ER stress-mediated by miR-17 and miR-155, associated with increased ROS. ROS causes M1 macrophage polarization exacerbated by miR-141 and miR-155, and inflammation by an increase of miR-34a, miR-122, miR-141-200c, miR-155, miR-221-222, and HULC. Low levels of miR-146a and miR-223 exacerbate inflammation, possibly reverted by the decrease of miR-375. The rise of miR-17, miR-21, miR-150, miR-190b, and MALAT1 causes inflammationassociated insulin resistance. MiR-378 may prevent insulin resistance. Further, ROS induce cell death mediated by miR-34a, miR-150, and HULC. Inflammation, apoptosis, and ECM deposition lead to liver fibrosis. The miR-130-miR-301 family, miR-221-222, and HULC induce fibrosis, while overexpression of miR-378 may prevent it. Increased non-coding RNAs are in red, decreased in green

4.3 Non-alcoholic Fatty Liver Disease

79

4 (TLR4) and release pro-inflammatory chemokines and cytokines through NLR family pyrin domain containing 3 (NLRP3) activation leading to cell death [88]. High lipids often coincide with insulin resistance in steatotic livers and are associated with ER stress in hepatocytes. As in the pancreas and adipose tissue, chronic ER stress can lead to an adaptive unfolded protein response, causing inflammation and cell death [89]. The p53 ortholog p63 and Janus kinase (JAK) link ER stress to inflammation, partially by interplay with nuclear factor kappa B (NFκB) [90–92]. BCL2 family members, BCL2 antagonist/killer (BAK), and BCL2 associated X, apoptosis regulator (BAX) promote apoptosis in response to ER stress [93] (Fig. 4.2). Activated stellate cells in injured liver differentiate to proliferating α smooth muscle actin-expressing contractile myofibroblasts, increasing vascular resistance, and promoting portal hypertension. Besides, the connective tissue growth factor and TGF-β1 drive fibrogenesis, amplify inflammation and increase extracellular matrix deposition and degradation [94]. All these processes and apoptosis contribute to liver fibrosis [95].

4.3.1 Non-coding RNAs Related to Non-alcoholic Fatty Liver Disease Type 2 diabetes with NAFLD complication is associated with increased expression of miR-17 and thereby increased free fatty acids-induced hepatocyte steatosis and decreased insulin sensitivity [96]. MiR-17 also contributes to steatosis by reducing the expression of cytochrome P450 family seven subfamily A member 1, an ER membrane protein that converts cholesterol to bile acids [97]. High miR-21 and low peroxisome proliferator-activated receptor (PPAR)-α increases fatty acid uptake, lipogenesis, gluconeogenesis, and insulin resistance [98–100]. MiR-29 increases lipogenesis in the liver and increases circulating triglyceride levels in a SIRT1dependent manner [101]. The rise of miR-30a is associated with a decrease of PPAR-α and lipid deposition [102]. MiR-34a that is induced in the liver by the inflammatory adipokine resistin is associated with increased triglyceride content, decreased mitochondrial content, and impaired mitochondrial function [103]. Direct and indirect targets of miR-34a are SIRT1, receptor tyrosine kinase, KLF4, and FGFR1 and FGFR4, which are all decreased by saturated fatty acids [104]. MiR-124, no longer silenced by NEAT1, silences tribbles homolog 3, resulting in increased AKT signaling and activation of lipogenic genes [105, 106]. High levels of hepatic miR-141 and miR-200c are related to higher liver weights and triglyceride levels and activation of pro-inflammatory and pro-fibrotic genes [107]. MiR-150 is associated with hepatic steatosis and insulin resistance by regulating the expression of genes related to gluconeogenesis, fatty acid uptake, and FA oxidation [108]. MiR-181a/b overexpression decreases PPAR-α and SIRT1, thereby increasing lipid accumulation in hepatocytes [109, 110]. MiR-190b increases triglyceride and total cholesterol levels and induces glucose intolerance and insulin resistance by repressing IRS2/AKT signaling [111].

80

4 Non-coding RNAs Related to Lipid Metabolism …

Up-regulated expression of miR-221-222 is associated with lipid deposition, inflammation, extracellular matrix (ECM) deposition, and fibrosis by targeting TIMP metallopeptidase inhibitor 3 (TIMP3) [112]. The regulator of AKT signaling associated with HCC and RCC (ARSR) lncRNA up-regulates SREBP-1c and enhances hepatic lipogenesis. NEAT1/miR-140 paraspeckles decrease the phosphorylation of protein kinase AMP-activated catalytic (AMPK) and increase the expression of SREBP1 and fatty acid synthase [113–115]. The hepatocellular carcinoma up-regulated lncRNA (HULC) stimulates lipid deposition, hepatic fibrosis, and apoptosis [116]. MiR-378 increases epithelial-to-mesenchymal transition (EMT), improves insulin sensitivity and inhibits liver fibrosis [117–119] (Fig. 4.2). Lipid accumulation may also result from a decrease of miR-30c-5p that directly targets fatty acid synthase [120]. MiR-130a has the potential to inhibit lipid accumulation by down-regulating NAFLD-related genes PPAR-γ, SREBP1, and fatty acid synthase, but H19 silences miR-130a [121, 122]. Low miR-138 elevates the leptinregulated carnitine palmitoyltransferase, limiting fatty acid β-oxidation [123, 124]. Low levels of expression of miR-455 are associated with increased lipid deposition by up-regulating SOCS3. Of interest, miR-19a and miR-125a could replace miR-455 in targeting SOCS3 [125–127]. Low levels of the suppressor of hepatic gluconeogenesis and lipogenesis (lncSHGL in mice or B4GALT1-AS1 in humans) associate with gluconeogenesis and lipogenesis [128] (Fig. 4.2). Next to miR-34a and miR-141-200c, high levels of miR-122 in NAFLD patients’ liver are also associated with inflammation [129]. MiR-155 is associated with decreased binding of peroxisome proliferator-activated receptor response element (PPRE) and PPAR-α and increased C-C motif chemokine ligand 2 (CCL2 or MCP1) production. Alcohol causes M1 macrophage polarization by inducing miR-155 and repressing CCAAT enhancer-binding protein (c/EBP)-β [130]. Low levels of miR146a are associated with obesity-induced inflammation [131], in which the decrease of anti-inflammatory miR-223 exacerbates [132]. In contrast, the decrease of miR375 during NAFLD progression may be an anti-inflammatory protective mechanism [133, 134]. High glucose and insulin levels induce MALAT1. MALAT1 up-regulates C-X-C motif chemokine ligand 5 (CXCL5) that blocks insulin signaling by activating the Janus kinase signal transducer and activator of transcription (JAK/STAT)/SOCS2 pathway [135, 136] (Fig. 4.2). Next to HULC and miR-221-222, the miR-130/301 family prevents hepatitis C virus infection but induces ECM deposition and fibrosis [121, 137]. As indicated above, miR-378 inhibits fibrosis.

References

81

References 1. Luo, J., Yang, H., & Song, B. L. (2020). Mechanisms and regulation of cholesterol homeostasis. Nature Reviews Molecular Cell Biology, 21, 225–245. https://doi.org/10.1038/s41 580-019-0190-7. 2. Osborne, T. F. (2000). Sterol regulatory element-binding proteins (SREBPs): Key regulators of nutritional homeostasis and insulin action. Journal of Biological Chemistry, 275, 32379– 32382. https://doi.org/10.1074/jbc.R000017200. 3. Horton, J. D., Goldstein, J. L., & Brown, M. S. (2002). SREBPs: Activators of the complete program of cholesterol and fatty acid synthesis in the liver. Journal of Clinical Investigation, 109, 1125–1131. https://doi.org/10.1172/JCI15593. 4. Sato, R., et al. (1996). Sterol-dependent transcriptional regulation of sterol regulatory elementbinding protein-2. Journal of Biological Chemistry, 271, 26461–26464. https://doi.org/10. 1074/jbc.271.43.26461. 5. Mertens, A., & Holvoet, P. (2001). Oxidized LDL and HDL: Antagonists in atherothrombosis. The FASEB Journal, 15, 2073–2084. https://doi.org/10.1096/fj.01-0273rev. 6. Tao, R., Xiong, X., DePinho, R. A., Deng, C. X., & Dong, X. C. (2013). FoxO3 transcription factor and Sirt6 deacetylase regulate low density lipoprotein (LDL)-cholesterol homeostasis via control of the proprotein convertase subtilisin/kexin type 9 (Pcsk9) gene expression. Journal of Biological Chemistry, 288, 29252–29259. https://doi.org/10.1074/jbc.M113. 481473. 7. Seidah, N. G., Awan, Z., Chretien, M., & Mbikay, M. (2014). PCSK9: A key modulator of cardiovascular health. Circulation Research, 114, 1022–1036. https://doi.org/10.1161/CIR CRESAHA.114.301621. 8. Tall, A. R., Yvan-Charvet, L., Terasaka, N., Pagler, T., & Wang, N. (2008). HDL, ABC transporters, and cholesterol efflux: implications for the treatment of atherosclerosis. Cell Metabolism, 7, 365–375. https://doi.org/10.1016/j.cmet.2008.03.001. 9. Phillips, M. C., et al. (1998). Mechanisms of high density lipoprotein-mediated efflux of cholesterol from cell plasma membranes. Atherosclerosis, 137(Suppl), S13–S17. https://doi. org/10.1016/s0021-9150(97)00312-2. 10. Lund-Katz, S., Liu, L., Thuahnai, S. T., & Phillips, M. C. (2003). High density lipoprotein structure. Frontiers in Bioscience, 8, d1044–d1054. https://doi.org/10.2741/1077. 11. Fidge, N. H. (1999). High density lipoprotein receptors, binding proteins, and ligands. Journal of Lipid Research, 40, 187–201. 12. Rudel, L. L., Lee, R. G., & Cockman, T. L. (2001). Acyl coenzyme A: Cholesterol acyltransferase types 1 and 2: Structure and function in atherosclerosis. Current Opinion in Lipidology, 12, 121–127. https://doi.org/10.1097/00041433-200104000-00005. 13. Sallam, T., et al. (2016). Feedback modulation of cholesterol metabolism by the lipidresponsive non-coding RNA LeXis. Nature, 534, 124–128. https://doi.org/10.1038/nature 17674. 14. Wang, M., et al. (2018). Obesity-induced overexpression of miRNA-24 regulates cholesterol uptake and lipid metabolism by targeting SR-B1. Gene, 668, 196–203. https://doi.org/10. 1016/j.gene.2018.05.072. 15. Valdmanis, P. N., et al. (2018). miR-122 removal in the liver activates imprinted microRNAs and enables more effective microRNA-mediated gene repression. Nature Communications, 9, 5321. https://doi.org/10.1038/s41467-018-07786-7. 16. Sun, C., et al. (2015). miR-21 regulates triglyceride and cholesterol metabolism in nonalcoholic fatty liver disease by targeting HMGCR. International Journal of Molecular Medicine, 35, 847–853. https://doi.org/10.3892/ijmm.2015.2076. 17. Huang, J., Chen, S., Cai, D., Bian, D., & Wang, F. (2018). Long non-coding RNA lncARSR promotes hepatic cholesterol biosynthesis via modulating Akt/SREBP-2/HMGCR pathway. Life Sciences, 203, 48–53. https://doi.org/10.1016/j.lfs.2018.04.028.

82

4 Non-coding RNAs Related to Lipid Metabolism …

18. Geng, C., et al. (2018). MicroRNA-98 regulates hepatic cholesterol metabolism via targeting sterol regulatory element-binding protein 2. Biochemical and Biophysical Research Communications, 504, 422–426. https://doi.org/10.1016/j.bbrc.2018.08.205. 19. Liu, M. X., et al. (2017). Dicer1/miR-29/HMGCR axis contributes to hepatic free cholesterol accumulation in mouse non-alcoholic steatohepatitis. Acta Pharmacologica Sinica, 38, 660– 671. https://doi.org/10.1038/aps.2016.158. 20. Wang, X. C., Zhan, X. R., Li, X. Y., Yu, J. J., & Liu, X. M. (2014). MicroRNA-185 regulates expression of lipid metabolism genes and improves insulin sensitivity in mice with nonalcoholic fatty liver disease. World Journal of Gastroenterology, 20, 17914–17923. https:// doi.org/10.3748/wjg.v20.i47.17914. 21. He, M., et al. (2017). Pro-inflammation NF-kappaB signaling triggers a positive feedback via enhancing cholesterol accumulation in liver cancer cells. Journal of Experimental & Clinical Cancer Research, 36, 15. https://doi.org/10.1186/s13046-017-0490-8. 22. Alvarez, M. L., Khosroheidari, M., Eddy, E., & Done, S. C. (2015). MicroRNA-27a decreases the level and efficiency of the LDL receptor and contributes to the dysregulation of cholesterol homeostasis. Atherosclerosis, 242, 595–604. https://doi.org/10.1016/j.atherosclerosis.2015. 08.023. 23. Jiang, H., et al. (2015). microRNA-185 modulates low density lipoprotein receptor expression as a key posttranscriptional regulator. Atherosclerosis, 243, 523–532. https://doi.org/10.1016/ j.atherosclerosis.2015.10.026. 24. Xu, Y., et al. (2020). Hsa-miR-140-5p down-regulates LDL receptor and attenuates LDL-C uptake in human hepatocytes. Atherosclerosis, 297, 111–119. https://doi.org/10.1016/j.athero sclerosis.2020.02.004. 25. Goedeke, L., et al. (2015). MicroRNA-148a regulates LDL receptor and ABCA1 expression to control circulating lipoprotein levels. Nature Medicine, 21, 1280–1289. https://doi.org/10. 1038/nm.3949. 26. Vickers, K. C., et al. (2014). MicroRNA-223 coordinates cholesterol homeostasis. Proceedings of the National Academy of Sciences of the United States of America, 111, 14518–14523. https://doi.org/10.1073/pnas.1215767111. 27. Hennessy, E. J., et al. (2019). The long non-coding RNA CHROME regulates cholesterol homeostasis in primate. Nature Metabolism, 1, 98–110. https://doi.org/10.1038/s42255-0180004-9. 28. Sallam, T., et al. (2018). Transcriptional regulation of macrophage cholesterol efflux and atherogenesis by a long non-coding RNA. Nature Medicine, 24, 304–312. https://doi.org/10. 1038/nm.4479. 29. Zhao, R., Feng, J., & He, G. (2014). miR-613 regulates cholesterol efflux by targeting LXRalpha and ABCA1 in PPARgamma activated THP-1 macrophages. Biochemical and Biophysical Research Communications, 448, 329–334. https://doi.org/10.1016/j.bbrc.2014. 04.052. 30. Ramirez, C. M., et al. (2013). Control of cholesterol metabolism and plasma high-density lipoprotein levels by microRNA-144. Circulation Research, 112, 1592–1601. https://doi.org/ 10.1161/CIRCRESAHA.112.300626. 31. Adlakha, Y. K., et al. (2013). Pro-apoptotic miRNA-128-2 modulates ABCA1, ABCG1 and RXRalpha expression and cholesterol homeostasis. Cell Death and Disease, 4, e780. https:// doi.org/10.1038/cddis.2013.301. 32. Sun, D., et al. (2012). MiR-26 controls LXR-dependent cholesterol efflux by targeting ABCA1 and ARL7. FEBS Letters, 586, 1472–1479. https://doi.org/10.1016/j.febslet.2012.03.068. 33. Rayner, K. J., et al. (2010). MiR-33 contributes to the regulation of cholesterol homeostasis. Science, 328, 1570–1573. https://doi.org/10.1126/science.1189862. 34. Najafi-Shoushtari, S. H., et al. (2010). MicroRNA-33 and the SREBP host genes cooperate to control cholesterol homeostasis. Science, 328, 1566–1569. https://doi.org/10.1126/science. 1189123. 35. Tarling, E. J., Ahn, H., & de Aguiar Vallim, T. Q. (2015). The nuclear receptor FXR uncouples the actions of miR-33 from SREBP-2. Arteriosclerosis, Thrombosis, and Vascular Biology, 35, 787–795. https://doi.org/10.1161/atvbaha.114.304179.

References

83

36. Xu, Y., et al. (2020). Macrophage miR-34a Is a Key Regulator of Cholesterol Efflux and Atherosclerosis. Molecular Therapy, 28, 202–216. https://doi.org/10.1016/j.ymthe.2019. 09.008. 37. Kang, M. H., et al. (2013). Regulation of ABCA1 protein expression and function in hepatic and pancreatic islet cells by miR-145. Arteriosclerosis, Thrombosis, and Vascular Biology, 33, 2724–2732. https://doi.org/10.1161/ATVBAHA.113.302004. 38. Lv, Y. C., et al. (2015). Diosgenin inhibits atherosclerosis via suppressing the MiR-19binduced downregulation of ATP-binding cassette transporter A1. Atherosclerosis, 240, 80–89. https://doi.org/10.1016/j.atherosclerosis.2015.02.044. 39. Meiler, S., Baumer, Y., Toulmin, E., Seng, K., & Boisvert, W. A. (2015). MicroRNA 302a is a novel modulator of cholesterol homeostasis and atherosclerosis. Arteriosclerosis, Thrombosis, and Vascular Biology, 35, 323–331. https://doi.org/10.1161/ATVBAHA.114.304878. 40. Zhang, N., et al. (2015). MicroRNA-101 overexpression by IL-6 and TNF-alpha inhibits cholesterol efflux by suppressing ATP-binding cassette transporter A1 expression. Experimental Cell Research, 336, 33–42. https://doi.org/10.1016/j.yexcr.2015.05.023. 41. Ramirez, C. M., et al. (2011). MicroRNA-758 regulates cholesterol efflux through posttranscriptional repression of ATP-binding cassette transporter A1. Arteriosclerosis, Thrombosis, and Vascular Biology, 31, 2707–2714. https://doi.org/10.1161/ATVBAHA.111.232066. 42. Yao, Y., et al. (2018). Glucagon-like peptide-1 modulates cholesterol homeostasis by suppressing the miR-19b-induced downregulation of ABCA1. Cellular Physiology and Biochemistry, 50, 679–693. https://doi.org/10.1159/000494235. 43. Sala, F., et al. (2014). MiR-143/145 deficiency attenuates the progression of atherosclerosis in Ldlr-/-mice. Thrombosis and Haemostasis, 112, 796–802. https://doi.org/10.1160/TH1311-0905. 44. Lan, X., et al. (2016). A novel long non-coding RNA Lnc-HC binds hnRNPA2B1 to regulate expressions of Cyp7a1 and Abca1 in hepatocytic cholesterol metabolism. Hepatology, 64, 58–72. https://doi.org/10.1002/hep.28391. 45. Wang, L., et al. (2013). MicroRNAs 185, 96, and 223 repress selective high-density lipoprotein cholesterol uptake through posttranscriptional inhibition. Molecular and Cellular Biology, 33, 1956–1964. https://doi.org/10.1128/MCB.01580-12. 46. Zhang, T., et al. (2020). Activation of microRNA-378a-3p biogenesis promotes hepatic secretion of VLDL and hyperlipidemia by modulating ApoB100-Sortilin1 axis. Theranostics, 10, 3952–3966. https://doi.org/10.7150/thno.39578. 47. Alves-Bezerra, M., & Cohen, D. E. (2017). Triglyceride metabolism in the liver. Comprehensive Physiology, 8, 1–8. https://doi.org/10.1002/cphy.c170012. 48. Lambert, J. E., Ramos-Roman, M. A., Browning, J. D., & Parks, E. J. (2014). Increased de novo lipogenesis is a distinct characteristic of individuals with nonalcoholic fatty liver disease. Gastroenterology, 146, 726–735. https://doi.org/10.1053/j.gastro.2013.11.049. 49. Petersen, M. C., & Shulman, G. I. (2018). Mechanisms of insulin action and insulin resistance. Physiological Reviews, 98, 2133–2223. https://doi.org/10.1152/physrev.00063.2017. 50. Hannah, V. C., Ou, J., Luong, A., Goldstein, J. L., & Brown, M. S. (2001). Unsaturated fatty acids down-regulate srebp isoforms 1a and 1c by two mechanisms in HEK-293 cells. Journal of Biological Chemistry, 276, 4365–4372. https://doi.org/10.1074/jbc.M007273200. 51. Ortega-Prieto, P., & Postic, C. (2019). Carbohydrate sensing through the transcription factor ChREBP. Frontiers in Genetics, 10, 472. https://doi.org/10.3389/fgene.2019.00472. 52. Zimmermann, R., et al. (2003). Decreased fatty acid esterification compensates for the reduced lipolytic activity in hormone-sensitive lipase-deficient white adipose tissue. Journal of Lipid Research, 44, 2089–2099. https://doi.org/10.1194/jlr.M300190-JLR200. 53. Chatterjee, C., & Sparks, D. L. (2011). Hepatic lipase, high density lipoproteins, and hypertriglyceridemia. American Journal of Pathology, 178, 1429–1433. https://doi.org/10.1016/j. ajpath.2010.12.050. 54. Krapp, A., et al. (1996). Hepatic lipase mediates the uptake of chylomicrons and beta-VLDL into cells via the LDL receptor-related protein (LRP). Journal of Lipid Research, 37, 926–936.

84

4 Non-coding RNAs Related to Lipid Metabolism …

55. Jones, A. L., et al. (1984). Uptake and processing of remnants of chylomicrons and very low density lipoproteins by rat liver. Journal of Lipid Research, 25, 1151–1158. 56. Jain, S. S., et al. (2009). Additive effects of insulin and muscle contraction on fatty acid transport and fatty acid transporters, FAT/CD36, FABPpm, FATP1, 4 and 6. FEBS Letters, 583, 2294–2300. https://doi.org/10.1016/j.febslet.2009.06.020. 57. Wilson, C. G., et al. (2016). Hepatocyte-specific disruption of CD36 attenuates fatty liver and improves insulin sensitivity in HFD-fed mice. Endocrinology, 157, 570–585. https://doi.org/ 10.1210/en.2015-1866. 58. Stahl, A. (2004). A current review of fatty acid transport proteins (SLC27). Pflugers Archiv. European Journal of Physiology, 447, 722–727. https://doi.org/10.1007/s00424-003-1106-z. 59. Young, P. A., et al. (2018). Long-chain acyl-CoA synthetase 1 interacts with key proteins that activate and direct fatty acids into niche hepatic pathways. Journal of Biological Chemistry, 293, 16724–16740. https://doi.org/10.1074/jbc.RA118.004049. 60. Bonnefont, J. P., et al. (2004). Carnitine palmitoyltransferases 1 and 2: biochemical, molecular and medical aspects. Molecular Aspects of Medicine, 25, 495–520. https://doi.org/10.1016/j. mam.2004.06.004. 61. Choudhary, N. S., Kumar, N., & Duseja, A. (2019). Peroxisome proliferator-activated receptors and their agonists in nonalcoholic fatty liver disease. Journal of Clinical and Experimental Hepatology, 9, 731–739. https://doi.org/10.1016/j.jceh.2019.06.004. 62. Jin, Z., et al. (2014). Catabolism of (2E)-4-hydroxy-2-nonenal via omega- and omega-1oxidation stimulated by ketogenic diet. Journal of Biological Chemistry, 289, 32327–32338. https://doi.org/10.1074/jbc.M114.602458. 63. Ding, D., et al. (2019). MicroRNA-26a-CD36 signaling pathway: Pivotal role in lipid accumulation in hepatocytes induced by PM2.5 liposoluble extracts. Environmental Pollution, 248, 269–278. https://doi.org/10.1016/j.envpol.2019.01.112. 64. Peng, X. P., Huang, L., & Liu, Z. H. (2016). miRNA-133a attenuates lipid accumulation via TR4-CD36 pathway in macrophages. Biochimie, 127, 79–85. https://doi.org/10.1016/j.biochi. 2016.04.012. 65. Cui, M., et al. (2015). Long non-coding RNA HULC modulates abnormal lipid metabolism in hepatoma cells through an miR-9-mediated RXRA signaling pathway. Cancer Research, 75, 846–857. https://doi.org/10.1158/0008-5472.CAN-14-1192. 66. Wang, J. J., Zhang, Y. T., Tseng, Y. J., & Zhang, J. (2019). miR-222 targets ACOX1, promotes triglyceride accumulation in hepatocytes. Hepatobiliary & Pancreatic Diseases International, 18, 360–365. https://doi.org/10.1016/j.hbpd.2019.05.002. 67. Tian, W. H., et al. (2019). miR-34a-5p increases hepatic triglycerides and total cholesterol levels by regulating ACSL1 protein expression in laying hens. International Journal of Molecular Sciences, 20. https://doi.org/10.3390/ijms20184420. 68. Cui, M., et al. (2014). MiR-205 modulates abnormal lipid metabolism of hepatoma cells via targeting acyl-CoA synthetase long-chain family member 1 (ACSL1) mRNA. Biochemical and Biophysical Research Communications, 444, 270–275. https://doi.org/10.1016/j.bbrc. 2014.01.051. 69. Sun, Y., et al. (2020). Multigenerational maternal obesity increases the incidence of HCC in offspring via miR-27a-3p. Journal of Hepatology, 73, 603–615. https://doi.org/10.1016/j. jhep.2020.03.050. 70. Wang, D. R., et al. (2020). Suppression of miR-30a-3p attenuates hepatic steatosis in nonalcoholic fatty liver disease. Biochemical Genetics, 58, 691–704. https://doi.org/10.1007/s10 528-020-09971-0. 71. Li, X., Lian, F., Liu, C., Hu, K. Q., & Wang, X. D. (2015). Isocaloric pair-fed high-carbohydrate diet induced more hepatic steatosis and inflammation than high-fat diet mediated by miR34a/SIRT1 axis in mice. Scientific Reports, 5, 16774. https://doi.org/10.1038/srep16774. 72. Kim, K. S., et al. (2019). Nonalcoholic fatty liver disease and diabetes: Part II: treatment. Diabetes & Metabolism Journal, 43, 127–143. https://doi.org/10.4093/dmj.2019.0034. 73. Cho, H. J., et al. (2019). Improvement of nonalcoholic fatty liver disease reduces the risk of type 2 diabetes mellitus. Gut and Liver. https://doi.org/10.5009/gnl18382.

References

85

74. Stahl, E. P., et al. (2019). Nonalcoholic fatty liver disease and the heart: JACC state-of-the-art review. Journal of the American College of Cardiology, 73, 948–963. https://doi.org/10.1016/ j.jacc.2018.11.050. 75. Bai, L., & Li, H. (2019). Innate immune regulatory networks in hepatic lipid metabolism. Journal of Molecular Medicine (Berl), 97, 593–604. https://doi.org/10.1007/s00109-019-017 65-1. 76. Srivastava, R. A. K. (2018). Life-style-induced metabolic derangement and epigenetic changes promote diabetes and oxidative stress leading to NASH and atherosclerosis severity. Journal of Diabetes and Metabolic Disorders, 17, 381–391. https://doi.org/10.1007/s40200-018-0378-y. 77. Piccinin, E., Villani, G., & Moschetta, A. (2019). Metabolic aspects in NAFLD, NASH and hepatocellular carcinoma: The role of PGC1 coactivators. Nature Reviews Gastroenterology & Hepatology, 16, 160–174. https://doi.org/10.1038/s41575-018-0089-3. 78. Mansouri, A., Gattolliat, C. H., & Asselah, T. (2018). Mitochondrial dysfunction and signaling in chronic liver diseases. Gastroenterology, 155, 629–647. https://doi.org/10.1053/j.gastro. 2018.06.083. 79. Garcia-Ruiz, I., et al. (2016). NADPH oxidase is implicated in the pathogenesis of oxidative phosphorylation dysfunction in mice fed a high-fat diet. Scientific Reports, 6, 23664. https:// doi.org/10.1038/srep23664. 80. Finck, B. N., & Kelly, D. P. (2006). PGC-1 coactivators: Inducible regulators of energy metabolism in health and disease. Journal of Clinical Investigation, 116, 615–622. https:// doi.org/10.1172/JCI27794. 81. Yona, S., et al. (2013). Fate mapping reveals origins and dynamics of monocytes and tissue macrophages under homeostasis. Immunity, 38, 79–91. https://doi.org/10.1016/j.immuni. 2012.12.001. 82. Stahl, E. C., Haschak, M. J., Popovic, B., & Brown, B. N. (2018). Macrophages in the aging liver and age-related liver disease. Frontiers in Immunology, 9, 2795. https://doi.org/10.3389/ fimmu.2018.02795. 83. Bilzer, M., Roggel, F., & Gerbes, A. L. (2006). Role of Kupffer cells in host defense and liver disease. Liver International, 26, 1175–1186. https://doi.org/10.1111/j.1478-3231.2006. 01342.x. 84. Liaskou, E., et al. (2013). Monocyte subsets in human liver disease show distinct phenotypic and functional characteristics. Hepatology, 57, 385–398. https://doi.org/10.1002/hep.26016. 85. Alzaid, F., et al. (2016). IRF5 governs liver macrophage activation that promotes hepatic fibrosis in mice and humans. JCI Insight, 1, e88689. https://doi.org/10.1172/jci.insight.88689. 86. Samala, N., Tersey, S. A., Chalasani, N., Anderson, R. M., & Mirmira, R. G. (2017). Molecular mechanisms of nonalcoholic fatty liver disease: Potential role for 12-lipoxygenase. Journal of Diabetes and Its Complications, 31, 1630–1637. https://doi.org/10.1016/j.jdiacomp.2017. 07.014. 87. Han, Y. H., et al. (2019). A maresin 1/RORalpha/12-lipoxygenase autoregulatory circuit prevents inflammation and progression of nonalcoholic steatohepatitis. Journal of Clinical Investigation, 130, 1684–1698. https://doi.org/10.1172/JCI124219. 88. Farrell, G. C., Haczeyni, F., & Chitturi, S. (2018). Pathogenesis of NASH: How metabolic complications of overnutrition favour lipotoxicity and pro-inflammatory fatty liver disease. Advances in Experimental Medicine and Biology, 1061, 19–44. https://doi.org/10.1007/978981-10-8684-7_3. 89. Lebeaupin, C., et al. (2018). Endoplasmic reticulum stress signalling and the pathogenesis of non-alcoholic fatty liver disease. Journal of Hepatology, 69, 927–947. https://doi.org/10. 1016/j.jhep.2018.06.008. 90. Kondylis, V., Kumari, S., Vlantis, K., & Pasparakis, M. (2017). The interplay of IKK, NF-kappaB and RIPK1 signaling in the regulation of cell death, tissue homeostasis and inflammation. Immunological Reviews, 277, 113–127. https://doi.org/10.1111/imr.12550. 91. Porteiro, B., et al. (2017). Hepatic p63 regulates steatosis via IKKbeta/ER stress. Nature Communications, 8, 15111. https://doi.org/10.1038/ncomms15111.

86

4 Non-coding RNAs Related to Lipid Metabolism …

92. Urano, F., et al. (2000). Coupling of stress in the ER to activation of JNK protein kinases by transmembrane protein kinase IRE1. Science, 287, 664–666. 93. Hetz, C., et al. (2006). Proapoptotic BAX and BAK modulate the unfolded protein response by a direct interaction with IRE1alpha. Science, 312, 572–576. https://doi.org/10.1126/sci ence.1123480. 94. Puche, J. E., Saiman, Y., & Friedman, S. L. (2013). Hepatic stellate cells and liver fibrosis. Comprehensive Physiology, 3, 1473–1492. https://doi.org/10.1002/cphy.c120035. 95. Schuster, S., Cabrera, D., Arrese, M., & Feldstein, A. E. (2018). Triggering and resolution of inflammation in NASH. Nature Reviews Gastroenterology & Hepatology, 15, 349–364. https://doi.org/10.1038/s41575-018-0009-6. 96. Ye, D., Lou, G., Zhang, T., Dong, F., & Liu, Y. (2018). MiR-17 family-mediated regulation of Pknox1 influences hepatic steatosis and insulin signaling. Journal of Cellular and Molecular Medicine, 22, 6167–6175. https://doi.org/10.1111/jcmm.13902. 97. Gong, R., Lv, X., & Liu, F. (2018). MiRNA-17 encoded by the miR-17-92 cluster increases the potential for steatosis in hepatoma cells by targeting CYP7A1. Cellular & Molecular Biology Letters, 23, 16. https://doi.org/10.1186/s11658-018-0083-3. 98. Rodrigues, P. M., et al. (2017). miR-21 ablation and obeticholic acid ameliorate nonalcoholic steatohepatitis in mice. Cell Death and Disease, 8, e2748. https://doi.org/10.1038/cddis.201 7.172. 99. Calo, N., et al. (2016). Stress-activated miR-21/miR-21* in hepatocytes promotes lipid and glucose metabolic disorders associated with high-fat diet consumption. Gut, 65, 1871–1881. https://doi.org/10.1136/gutjnl-2015-310822. 100. Wang, X., & Wang, J. (2018). High-content hydrogen water-induced downregulation of miR-136 alleviates non-alcoholic fatty liver disease by regulating Nrf2 via targeting MEG3. Biological Chemistry, 399, 397–406. https://doi.org/10.1515/hsz-2017-0303. 101. Hung, Y. H., et al. (2019). MiR-29 regulates de novo lipogenesis in the liver and circulating triglyceride levels in a Sirt1-dependent manner. Frontiers in Physiology, 10, 1367. https://doi. org/10.3389/fphys.2019.01367. 102. Wang, D. R., et al. (2020). Suppression of miR-30a-3p attenuates hepatic steatosis in nonalcoholic fatty liver disease. Biochemical Genetics. https://doi.org/10.1007/s10528-020-099 71-0. 103. Wen, F., et al. (2018). MiR-34a regulates mitochondrial content and fat ectopic deposition induced by resistin through the AMPK/PPARalpha pathway in HepG2 cells. International Journal of Biochemistry & Cell Biology, 94, 133–145. https://doi.org/10.1016/j.biocel.2017. 11.008. 104. Natarajan, S. K., et al. (2017). FoxO3 increases miR-34a to cause palmitate-induced cholangiocyte lipoapoptosis. Journal of Lipid Research, 58, 866–875. https://doi.org/10.1194/jlr. M071357. 105. Liu, X., et al. (2016). MicroRNA-124 promotes hepatic triglyceride accumulation through targeting tribbles homolog 3. Scientific Reports, 6, 37170. https://doi.org/10.1038/srep37170. 106. Liu, X., et al. (2018). Long non-coding RNA NEAT1-modulated abnormal lipolysis via ATGL drives hepatocellular carcinoma proliferation. Molecular Cancer, 17, 90. https://doi.org/10. 1186/s12943-018-0838-5. 107. Tran, M., Lee, S. M., Shin, D. J., & Wang, L. (2017). Loss of miR-141/200c ameliorates hepatic steatosis and inflammation by reprogramming multiple signaling pathways in NASH. JCI Insight, 2. https://doi.org/10.1172/jci.insight.96094. 108. Zhuge, B., & Li, G. (2017). MiR-150 deficiency ameliorated hepatosteatosis and insulin resistance in nonalcoholic fatty liver disease via targeting CASP8 and FADD-like apoptosis regulator. Biochemical and Biophysical Research Communications, 494, 687–692. https:// doi.org/10.1016/j.bbrc.2017.10.149. 109. Huang, R., et al. (2019). Upregulation of miR-181a impairs lipid metabolism by targeting PPARalpha expression in nonalcoholic fatty liver disease. Biochemical and Biophysical Research Communications, 508, 1252–1258. https://doi.org/10.1016/j.bbrc.2018.12.061.

References

87

110. Wang, Y., et al. (2017). MiR-181b regulates steatosis in nonalcoholic fatty liver disease via targeting SIRT1. Biochemical and Biophysical Research Communications, 493, 227–232. https://doi.org/10.1016/j.bbrc.2017.09.042. 111. Xu, M., Zheng, X. M., Jiang, F., & Qiu, W. Q. (2018). MicroRNA-190b regulates lipid metabolism and insulin sensitivity by targeting IGF-1 and ADAMTS9 in non-alcoholic fatty liver disease. Journal of Cellular Biochemistry, 119, 5864–5874. https://doi.org/10.1002/jcb. 26776. 112. Jiang, X., et al. (2018). Targeting hepatic miR-221/222 for therapeutic intervention of nonalcoholic steatohepatitis in mice. EBioMedicine, 37, 307–321. https://doi.org/10.1016/j.ebiom. 2018.09.051. 113. Sun, Y., Song, Y., Liu, C., & Geng, J. (2019). LncRNA NEAT1-MicroRNA-140 axis exacerbates nonalcoholic fatty liver through interrupting AMPK/SREBP-1 signaling. Biochemical and Biophysical Research Communications, 516, 584–590. https://doi.org/10.1016/j.bbrc. 2019.06.104. 114. Zhang, M., Chi, X., Qu, N., & Wang, C. (2018). Long non-coding RNA lncARSR promotes hepatic lipogenesis via Akt/SREBP-1c pathway and contributes to the pathogenesis of nonalcoholic steatohepatitis. Biochemical and Biophysical Research Communications, 499, 66–70. https://doi.org/10.1016/j.bbrc.2018.03.127. 115. Li, Y., et al. (2011). AMPK phosphorylates and inhibits SREBP activity to attenuate hepatic steatosis and atherosclerosis in diet-induced insulin-resistant mice. Cell Metabolism, 13, 376– 388. https://doi.org/10.1016/j.cmet.2011.03.009. 116. Shen, X., Guo, H., Xu, J., & Wang, J. (2019). Inhibition of lncRNA HULC improves hepatic fibrosis and hepatocyte apoptosis by inhibiting the MAPK signaling pathway in rats with nonalcoholic fatty liver disease. Journal of Cellular Physiology. https://doi.org/10.1002/jcp. 28450. 117. Liu, W., et al. (2014). Hepatic miR-378 targets p110alpha and controls glucose and lipid homeostasis by modulating hepatic insulin signalling. Nature Communications, 5, 5684. https:// doi.org/10.1038/ncomms6684. 118. Kim, J., Hyun, J., Wang, S., Lee, C., & Jung, Y. (2018). MicroRNA-378 is involved in hedgehog-driven epithelial-to-mesenchymal transition in hepatocytes of regenerating liver. Cell Death and Disease, 9, 721. https://doi.org/10.1038/s41419-018-0762-z. 119. Hyun, J., et al. (2016). MicroRNA-378 limits activation of hepatic stellate cells and liver fibrosis by suppressing Gli3 expression. Nature Communications, 7, 10993. https://doi.org/ 10.1038/ncomms10993. 120. Fan, J., et al. (2017). MiR-30c-5p ameliorates hepatic steatosis in leptin receptor-deficient (db/db) mice via down-regulating FASN. Oncotarget, 8, 13450–13463. https://doi.org/10. 18632/oncotarget.14561. 121. Bertero, T., et al. (2015). A YAP/TAZ-miR-130/301 molecular circuit exerts systems-level control of fibrosis in a network of human diseases and physiologic conditions. Scientific Reports, 5, 18277. https://doi.org/10.1038/srep18277. 122. Liu, J., Tang, T., Wang, G. D., & Liu, B. (2019). LncRNA-H19 promotes hepatic lipogenesis by directly regulating miR-130a/PPARgamma axis in non-alcoholic fatty liver disease. Bioscience Reports, 39. https://doi.org/10.1042/bsr20181722. 123. van Weeghel, M., et al. (2018). Increased cardiac fatty acid oxidation in a mouse model with decreased malonyl-CoA sensitivity of CPT1B. Cardiovascular Research, 114, 1324–1334. https://doi.org/10.1093/cvr/cvy089. 124. Dang, Y., et al. (2020). Gan-Jiang-Ling-Zhu decoction alleviates hepatic steatosis in rats by the miR-138-5p/CPT1B axis. Biomedicine & Pharmacotherapy, 127, 110127. https://doi.org/ 10.1016/j.biopha.2020.110127. 125. Fang, S., et al. (2020). MiR-455 targeting SOCS3 improve liver lipid disorders in diabetic mice. Adipocyte, 9, 179–188. https://doi.org/10.1080/21623945.2020.1749495. 126. Li, Y., Luo, T., Wang, L., Wu, J., & Guo, S. (2016). MicroRNA-19a-3p enhances the proliferation and insulin secretion, while it inhibits the apoptosis of pancreatic beta cells via the inhibition of SOCS3. International Journal of Molecular Medicine, 38, 1515–1524. https:// doi.org/10.3892/ijmm.2016.2748.

88

4 Non-coding RNAs Related to Lipid Metabolism …

127. Xu, L., et al. (2018). miR-125a-5p ameliorates hepatic glycolipid metabolism disorder in type 2 diabetes mellitus through targeting of STAT3. Theranostics, 8, 5593–5609. https://doi.org/ 10.7150/thno.27425. 128. Wang, J., et al. (2018). Long noncoding RNA lncSHGL recruits hnRNPA1 to suppress hepatic gluconeogenesis and lipogenesis. Diabetes, 67, 581–593. https://doi.org/10.2337/db17-0799. 129. Akuta, N., et al. (2016). Analysis of association between circulating miR-122 and histopathological features of nonalcoholic fatty liver disease in patients free of hepatocellular carcinoma. BMC Gastroenterology, 16, 141. https://doi.org/10.1186/s12876-016-0557-6. 130. Bala, S., et al. (2016). The pro-inflammatory effects of miR-155 promote liver fibrosis and alcohol-induced steatohepatitis. Journal of Hepatology, 64, 1378–1387. https://doi.org/10. 1016/j.jhep.2016.01.035. 131. Javidan, A., et al. (2019). miR-146a deficiency accelerates hepatic inflammation without influencing diet-induced obesity in mice. Scientific Reports, 9, 12626. https://doi.org/10.1038/ s41598-019-49090-4. 132. He, Y., et al. (2019). MicroRNA-223 ameliorates nonalcoholic steatohepatitis and cancer by targeting multiple inflammatory and oncogenic genes in hepatocytes. Hepatology, 70, 1150–1167. https://doi.org/10.1002/hep.30645. 133. Garikipati, V. N. S., et al. (2017). Therapeutic inhibition of miR-375 attenuates postmyocardial infarction inflammatory response and left ventricular dysfunction via PDK-1AKT signalling axis. Cardiovascular Research, 113, 938–949. https://doi.org/10.1093/cvr/ cvx052. 134. Lei, L., Zhou, C., Yang, X., & Li, L. (2018). Down-regulation of microRNA-375 regulates adipokines and inhibits inflammatory cytokines by targeting AdipoR2 in non-alcoholic fatty liver disease. Clinical and Experimental Pharmacology and Physiology, 45, 819–831. https:// doi.org/10.1111/1440-1681.12940. 135. Chavey, C., & Fajas, L. (2009). CXCL5 drives obesity to diabetes, and further. Aging (Albany NY), 1, 674–677. https://doi.org/10.18632/aging.100064. 136. Leti, F., et al. (2017). Altered expression of MALAT1 lncRNA in nonalcoholic steatohepatitis fibrosis regulates CXCL5 in hepatic stellate cells. Translational Research, 190, 25–39 e21. https://doi.org/10.1016/j.trsl.2017.09.001. 137. Li, Q., et al. (2017). Cellular microRNA networks regulate host dependency of hepatitis C virus infection. Nature Communications, 8, 1789. https://doi.org/10.1038/s41467-017-019 54-x.

Chapter 5

Non-coding RNAs Related to Atherosclerosis

Abstract The onset of atherosclerosis is caused by endothelial dysfunction through mechanical shear stress and chemical stress induced by high glucose, ox-LDL, and ANG II. Injured endothelium attracts inflammatory cells. Among them, macrophages that accumulate lipids and differentiate into foam cells. Cytokines induce vascular smooth muscle cell proliferation and secretion of matrix proteins. Disrupted angiogenesis leads to oxygen deprivation. However, angiogenesis also facilitates the infiltration of inflammatory cells. They secrete cytokines and ROS, which induce cell death, thereby destabilizing atherosclerotic plaques. The multiple-hit pathogenesis model of atherosclerosis shares with obesity and type 2 diabetes an imbalance in the expression of let-7, miR-7, miR-9, miR-17, miR-21, miR-26, miR-27, miR29, miR-30, miR-33, miR-34, miR-124, miR-130, miR-132, miR-133, miR-143– 145, miR-146a, miR-150, miR-181, miR-221–222, miR-223, and miR-378, and lncRNAs GAS5, H19, HOTAIR, MALAT1, MEG3 and NEAT1, and circ-RNA PVT1. Typically, lncRNAs ATB, CASC11, HOXC-AS1, LEF1-AS1, lincRNA-p21, MANTIS, MIAT, TUG1, UCA1, and ZEB1-AS1, and circ-RNAs ANRIL regulate miR-expression in atherosclerotic plaques, in addition to lncRNAs and circ-RNAs related to metabolic diseases.

5.1 Endothelial Injury, Inflammation, and Apoptosis Endothelial cells (ECs) prefer not to maximize energy (ATP) production by shunting all glucose they take up into oxidative phosphorylation (OXPHOS) but rely on glycolysis instead of OXPHOS [1]. This shift results in a low-level release of mitochondrial reactive oxygen species (ROS)[2], enough to enhance EC migration and sprouting, ROS inducing VEGF [2]. VEGF increases glycolysis by increasing 6-phosphofructo2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3), and fibroblast growth factor (FGF) activates hexokinase 2 (HK2) and PFKFB3 [3, 4]. VEGF also induces glucose transporter 1 (GLUT1), improving glucose uptake [5].

Illustrations by Pieterjan Ginckels, Faculty of Architecture, KU Leuven, Ghent, Belgium. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 P. Holvoet, Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer, https://doi.org/10.1007/978-3-030-68844-8_5

89

90

5 Non-coding RNAs Related to Atherosclerosis

Besides, the monocyte cross-talk to ECs triggers tissue factor (TF) expression by ECs, resulting in microvessel formation, involving Wnt signaling, the release of intracellular Ca (2 + ), and an increase of inflammatory NFκB activity [6–10]. Atherosclerosis develops in medium and large arteries at sites of high shear stress. Exposure of endothelial cells (ECs) to shear stress, high glucose, angiotensinogen (ANG II), and oxidized LDL (ox-LDL) causes endothelium dysfunction. Dysfunction is due to impaired non-canonical Wnt and phosphatidylinositol 3-kinase (PI3K) / AKT serine/threonine kinase 1 (AKT) / nitric oxide synthase (NOS) signaling, [11–13]. Reduced PI3K/AKT signaling leads to insulin resistance [14] Endothelial dysfunction is associated with the secretion of adhesion molecules: vascular cell adhesion molecule 1 (VCAM-1), intercellular adhesion molecule 1 (ICAM-1), and the C–C motif chemokine receptor 2 (CCR2; or MCP-1 receptor). They facilitate adhesion and infiltration of monocytes, which differentiate into macrophages [6, 15]. They release pro-angiogenic factors, such as VEGF, hepatocyte growth factor (HGF), fibroblast growth factor (FGF), tumor necrosis factor (TNF)-α, and interleukin (IL)-8. Angiogenesis may thus be beneficial because pro-angiogenic factors stimulate the proliferation of ECs and mobilize and home bone-marrowderived endothelial progenitor cells allowing repair of the endothelium. However, angiogenesis may be harmful because it facilitates the infiltration and accumulation of inflammatory cells (Fig. 5.1). Infiltrated monocytes differentiate into anti-inflammatory M2 macrophages. They secrete transforming growth factor (TGF)-β and interleukin (IL)-10, which counteract vascular inflammation and immune cell activation. Endothelial injury and subsequent adhesion of inflammatory cells result in ROS release, which polarizes M2 towards pro-inflammatory M1 macrophages [16–19]. This activation involves increased expression of toll-like receptors (TLRs) and downstream nuclear factor kappa B (NFκB), which elicit the release of pro-inflammatory cytokines, such as IL6 and tumor necrosis factor (TNF)-α [20]. Negative regulation of macrophage activation and cytokine secretion primarily occurs at the TLR signaling level, for example, by the interleukin-1 receptor-associated kinase-3 (IRAK3 or IRAK-M) [21–24]. IRAK3 negatively regulates signaling by preventing dissociation of IRAK1 and IRAK4 from MyD88 and the formation of IRAK - TNF receptor-associated factor-6 (TRAF6) complexes [25]. Low IRAK3 is associated with high superoxide dismutase (SOD)-2, a mitochondrial oxidative stress marker [24] (Fig. 5.1). Activated macrophages secrete myeloperoxidase (MPO) and NADPH oxidase (NOX), oxidizing LDL. Ox-LDL damages the endothelium, closing a vicious circle [26–30]. Macrophages express scavenger receptors such as scavenger receptor A (SR-A), scavenger receptor BI (SR-B1 or SCARB1), CD36, and lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) [31–33]. Uptake of ox-LDL via these scavenger receptors is not harmful if levels of ATP-binding cassette transporters ABCA1 and ABCG1 are adequate. Then macrophages can transfer the surplus of cholesterol to HDL that facilitates further transport from the arterial wall to the liver, ultimately leading to bile release. Suppose this reverse cholesterol transport is not adequate. In that case, excess lipid accumulation leads to foam cell formation, ultimately leading to cell burst exposing extracellular debris that causes microthrombi,

5.1 Endothelial Injury, Inflammation, and Apoptosis

91

Fig. 5.1 Non-coding RNAs in endothelial injury, inflammation, and apoptosis. ECs prefer not to maximize energy (ATP) production by shunting all glucose they take up into oxidative phosphorylation (OXPHOS) but rely on glycolysis instead of OXPHOS. This shift results in a low-level release of mitochondrial reactive oxygen species (ROS), enough to enhance EC migration and sprouting, ROS inducing VEGF induced by the hypoxia-inducible factor (HIF)-1α. VEGF increases glycolysis by increasing PFKFB3 and FGF. VEGF also induces GLUT1, increasing glucose uptake. Shear stress and chemical stress caused by high glucose, ox-LDL, and ANG II initiate atherosclerosis. These stresses impair Wnt/PI3K/AKT/NOS signaling and cause endothelial dysfunction, mediated by the increase of lncRNA ZEB-AS1 and the decrease of MALAT1, subsequently increasing miR-155 and miR-200c. High levels of miR-130a and circ-0068087 by silencing miR-197 may prevent this. Decreased PI3K/AKT signaling reduces insulin sensitivity, involving miR-7, associated with cell death. The repair of endothelium depends on EC progenitor attraction to the injury site and EC differentiation and proliferation. MiR-9, miR-21, miR-29, and XIST promote repair. In contrast, the increase of H19 and the decrease of MALAT1 and MEG3 impairs this. EC proliferation and angiogenesis maintain O2 supply into the growing atherosclerotic plaque. The increase

92

5 Non-coding RNAs Related to Atherosclerosis

 of let-7a, miR-9, miR-17, miR-21, miR-27b, miR-132, miR-210, lncRNA-ATB, silencing miR195, MIAT, and SNHG12, silencing miR-150, and XIST and PVT1, silencing miR-26b, and the decrease of miR-221–222 in late lesions induce angiogenesis. The increase of miR-16, miR-34a, miR-92, miR-221–222 in early atherosclerotic plaques, miR-223, miR-424, and miR-615-5p blocks angiogenesis. The decrease of miR-126 and MANTIS further inhibits angiogenesis. Angiogenesis may thus allow repair of the endothelium. However, angiogenesis may be harmful because it facilitates the infiltration and accumulation of inflammatory cells. They release pro-angiogenic factors, such as VEGF, hepatocyte growth factor (HGF), fibroblast growth factor (FGF), tumor necrosis factor (TNF)-α, and interleukin (IL)-8. However, angiogenesis also facilitates the infiltration of inflammatory cells. High levels of miR-17a and miR-20a and low levels of NEXN-AS1 facilitate the recruitment of monocytes by increasing the expression of ICAM-1, VCAM-1, and MCP-1, which may be blocked by LINC00341. MiR-21 and MiR-424 and miR-503 induce the differentiation of infiltrated monocytes to M2 macrophages by lowering miR-9, exacerbated by the decrease of miR-223. ANRIL may, however, prevent the decrease of miR-9. Activation of macrophages in the vascular wall is associated with rapid changes in the expression of numerous inflammationrelated genes to undergo polarization from the M2 towards the M1 phenotype. High levels of let-7e, miR-9, miR-29b-1-5p, miR-34a, miR-155, HOTAIR, silencing miR-330-5p, TUG1, silencing miR133, and ZFAS1 induce M1 macrophage polarization and inflammation. The decrease of let-7d, inhibited by LIN28, miR-10a, miR-124a, miR-126, miR-132, miR-150, miR-223, and MALAT1, exacerbates M1 macrophage polarization and inflammation. Let7-c-1-3p, miR-125b, miR-146a, and miR-181a inhibit M1 macrophage polarization. Activated macrophages release oxidative enzymes such as MPO and NOX resulting in oxidation of infiltrated LDL producing ox-LDL. Activated macrophages express scavenger receptors SR-A, SR-B1, CD36, and LOX-1, through which they take up ox-LDL leading to intracellular lipid accumulation in foam cells. Ox-LDL induces LOX-1, thereby inducing miR-146a that represses inflammation. The decrease of NEAT induces CD36 and foam cells. Usually, ABCA1 and ABCG1 offload the excess of cholesterol by mediating the reverse cholesterol transport to the liver, thereby neutralizing ox-LDL’s hazardous effects. The increase of miR-9, miR-378, and ZFAS1 and the decrease of lncRNAs HOXC-AS1 block the reverse cholesterol transport. However, this inhibition may be prevented by let-7 g, which silences miR-33 and by lncRNA CDKN2B-AS1. Impaired reverse cholesterol transport and unregulated lipid accumulation covert macrophages to foam cells, which ultimately burst, exposing extracellular debris that induces microthrombi formation, possibly due to a decrease of miR-181b, leading to even more inflammation. Monocytes may also differentiate into DCs. DC differentiation occurs in association with impaired PI3K/AKT/ERK signaling and an increase of let-7c and miR-17, miR-20a, and miR-106a. Activated DCs release IFN-γ that induces M2 to M1 polarization and secretion of inflammatory cytokines, inducing apoptosis of ECs. Microvesicles secreted by DCs deliver miR-155 to enhance M1 macrophage polarization and inflammation. However, miR-146a and MALAT1 may block miR-155. IL12 and IL18 released by M1 macrophages induce a shift from anti-inflammatory Treg and Th2 to inflammatory Th1 and Th17 cells. MiR-146a increases inflammatory Th1 cells, while the lack of miR-146a and the increase of miR-155 and CASC11 promotes Th17 cell differentiation. High levels of miR-21 may decrease Tregs, but let-7 g may block this decrease by silencing miR-33. NEAT1 prevents the decrease of Th2 cells. Th1 and Th17 cells activate DCs, but T-cell derived extracellular vesicles enriched in miR-150-5p and miR-142-3p may block this. Inflammatory cytokines induce cell senescence and death in ECs and macrophages involving the increase of miR-34a, miR-124a, miR-155, GAS5, H19, silencing let-7b, and TUG1, silencing mir-125, and the decrease of miR-126. MiR-21, miR-130a, and MIAT by sponging miR-150 and miR-181b, may prevent apoptosis. Increased non-coding RNAs are in red, decreased in green

5.1 Endothelial Injury, Inflammation, and Apoptosis

93

which exacerbate inflammatory cells’ infiltration. Scavenger receptors are, however, not only present at the surface of macrophages but also on the surface of ECs. For example, the scavenger receptor class F member 1 cooperates with TLRs to trigger inflammatory innate immune responses [34] (Fig. 5.1). The activation of monocytes/macrophages in the vessel wall initiates the innate immune response. Specific adaptive responses mediated by T and B cells follow this innate response [35, 36]. The presence of auto-antibodies against ox-LDL in the lesions of atherosclerotic humans and animal models provided initial evidence of the involvement of adaptive immunity in the development of atherosclerosis [37–40]. As in other inflamed tissues, Th1 cells exceed the number of Th2 cells in atherosclerotic plaques [41, 42]. Th1-skewing, dependent on T-box transcription factor 21 (TBX21 or TBET), is accomplished by IL12 and IL18, produced by activated macrophages and interaction with dendritic cells (DCs), leading to interferon (IFN)-γ secretion by Th1 cells [43–46]. TBET deficiency reduces atherosclerosis by increasing Th2 cytokines, IL4, IL5, and IL10 [46–48]. IL4 produced by Th2 cells counteracts the production of IFN-γ. Also, Treg cells produce IL4, IL5, IL10, and IL13 [49, 50]. Natural Treg cells are unique because they do not require antigen exposure to gain their immunosuppressive activities. In contrast, inducible Treg cells derive from effector T-cell populations in the periphery only after exposure to antigen. They are also CD4+ CD25+ cells, which do not require forkhead box P3 to be functional (64). Among them, Treg1 cells secrete IL10, while Th3 cells secrete TGF-β. Natural and inducible Treg cells compete with other T cell subsets for antigen complexes and the major histocompatibility complex class II, preventing autoimmunity. They increase the inhibitory cytotoxic T-lymphocyte-associated protein 4 by down-regulating costimulatory CD80/CD86 and through direct cytotoxic and inhibitory effects on other effector cells [51]. Other inflammatory T cells are Th17 cells, which secrete IL17 and IL22. The IL17 family of cytokines consists of six members—IL17A, IL17B, IL17C, IL17D, IL17E, and IL17F. All IL17 interleukins activate NFκB, mitogen-activated protein kinase (MAPK or ERK)-1 and MAPK2, CCAAT enhancer-binding protein (c/EBP)-β, and c/EBP-δ in target macrophages resulting in secretion of inflammatory TNF-α, IL-1β, and IFN-γ [52–57] (Fig. 5.1). NKT cells are a unique subset of T cells with NK-specific (NK1.1 and Ly49) and T-cell-specific (CD4) surface markers. These cells recognize antigen in the context of CD1d, not MHC, expressed on antigen-presenting cells. Their ligands are glycolipid antigens. They are abundant in the liver and most lymphoid tissues. The invariant NKT cells secrete large amounts of anti-inflammatory cytokines IL4, IL10, and IL13 and pro-inflammatory IFN-γ [58]. They are autoregulatory cells capable of inducing tolerance by communicating with Treg cells [59]. Although they may play a tolerogenic role in some diseases like type 1 diabetes, they are likely to be proatherogenic [60–65] (Fig. 5.1).

94

5 Non-coding RNAs Related to Atherosclerosis

5.1.1 Non-coding RNAs in Endothelial Injury, Inflammation, and Apoptosis 5.1.1.1

Endothelial Cells

Zinc finger E-box-binding homeobox two antisense RNA 1 (ZEB1-AS1) mediates ox-LDL-induced EC injury. Ox-LDL sequesters p53 from binding to the ZEB-AS1 promoter, thereby up-regulating ZEB-AS1 and the nucleotide-binding oligomerization domain 2 (NOD2) through recruitment of leucine-rich pentatricopeptide repeat motif-containing protein to stabilize NOD2 mRNA [66]. The metastasis-associated lung adenocarcinoma transcript one lncRNA (MALAT1) is lower in human plaques than in normal arteries. It is also lower in symptomatic than in asymptomatic plaques. Low MALAT1 is associated with endothelial dysfunction and loss of protection against ox-LDL-induced cytokine release and apoptosis via up-regulation of miR155 that is increased by hypertension and inflammation [67–73]. Also, the decrease of MALAT1 and the up-regulation of miR-200c-3p is associated with oxygen–glucose deprivation [74.] In contrast, miR-130a activates PI3K/AKT/eNOS signaling and thereby retains EC viability and NO release, while it decreases inflammatory cytokine levels and cell apoptosis [75, 76]. The increase of circ-RNA circ_0068087 in diabetes protects against high glucose-induced endothelial dysfunction and inflammation by silencing miR-197, thereby suppressing the TLR4/NFκB/ NLR family pyrin domain containing 3 (NLRP3) inflammasome pathway [77]. Endothelial dysfunction is associated with decreased insulin sensitivity, involving miR-7 [14] (Fig. 5.1). The repair of endothelium requires the attraction of endothelial progenitor cells (EPC s) and EC proliferation. MiR-9 promotes migration and invasion of EPCs [78]. Resveratrol can reduce neointimal formation in a vascular graft model by promoting progenitor cells’ differentiation to endothelial cells through a miR-21/AKT/β-catenin dependent mechanism [79]. MiR-29 targets the teneleven translocation-1 (TET1), which converts 5-methylcytosine (5mC) to 5hydroxymethycytosine (5hmC), contributing to early differentiation of stem cells [80]. X inactive specific transcript (XIST) stimulates hypoxia-induced EC proliferation [81]. In contrast, the H19 imprinted maternally expressed transcript lncRNA (H19) decreases EC proliferation and increases apoptosis by up-regulating MAPKs and NFkB [82, 83]. Ablation of MALAT1 and maternally expressed 3 lncRNA (MEG3), particularly in type 2 diabetes, is associated with reduced EC proliferation [84, 85]. Several miRs correlate positively with angiogenesis. Among them: let-7a, high in patients with hypertension, atherosclerosis, and cardiac hypertrophy and fibrosis [86]; miR-9, high in patients with hyperglycemia [87]; miR-21 up-regulated by ANG II [88]; miR-27b induced by shear stress [89]; miR-132, high in patients with heart failure [90]; and miR-210, increased in patients with aortic stenosis [91]. Two members of the miR-17–92 cluster have opposite effects on angiogenesis. MiR-17 potentiates angiogenesis by facilitating the expression of HIF-1α and VEGF, which regulate each other. However, miR-92 blocks angiogenesis by silencing

5.1 Endothelial Injury, Inflammation, and Apoptosis

95

integrin subunit alpha 5 [92–95]. The increase of myocardial infarction associated transcript (MIAT) in diabetes partially abolished the miR-150-5p–mediated repression on VEGF [96]. Overexpression of small nucleolar RNA host gene 12 (SNHG12) improved the recovery of neurological function by targeting miR-150, increasing vascular density, and VEGF expression in the infarct border zone of mice [97]. The increase of miR-221/222 in initial atherosclerotic plaques inhibits angiogenesis [98]. However, in advanced plaques, chronic inflammation downregulates miR-221/222 in ECs and decreases the growth arrest-specific homeobox by decreased repression of zinc finger E-box binding homeobox (ZEB)-2, resulting in increased angiogenesis [75, 99–101]. The long non-coding RNA activated by TGF-β (LncRNA-ATB) induces angiogenesis by sponging miR-195, thereby de-repressing PI3K/AKT/MAPK signaling [102]. PVT1 oncogene (PVT1) binds and degrades miR-26b and promotes angiogenesis [103] (Fig. 5.1). Functionally, miR-16 and miR-424 inhibit angiogenesis via blocking VEGF [104–107]. MiR-34a inhibits angiogenesis by targeting NOTCH and VEGF [108, 109]. Metformin, or the inhibition of miR-34a with an anti-miR-34a, increases the expression of sirtuin1 and attenuates the impairment in angiogenesis in high glucose-exposed endothelial cells [110]. Recombinant HDL increased miR-223 and suppressed the initial induction of angiogenesis post-ischemia when capillary and arteriolar density allowed adequate perfusion [111]. The increase of miR-615-5p in response to vascular tissue injury inhibits VEGF/AKT/eNOS signaling [112]. The decrease of miR-126 and MANTIS (LOC107985770) inhibits angiogenic sprouting and alignment of ECs in response to shear stress and inflammation [75, 93, 113–118] (Fig. 5.1).

5.1.1.2

Monocytes and Macrophages

Endothelial injury is associated with increased infiltration of monocytes, which differentiate into macrophages. MiR-17a and miR-20a induce hypoxia-induced infiltration of monocytes and activation of macrophages [119–121]. Repression of nexilin F-actin binding protein antisense RNA 1 (NEXN)-AS1 and NEXN increase NFκB activity associated with the up-regulation of monocyte-specific adhesion molecules and inflammatory cytokines by ECs [122]. In contrast, the athero-protective pulsatile shear flow induces the spectrin-repeat containing nuclear envelope family member 3 (LINC00341), which represses VCAM1 [123] (Fig. 5.1). MiR-21 enriched exosomes produced by IL-1β-primed mesenchymal cells induced M2 macrophage polarization [124]. MiR-424 and miR-503 synergistically induce the integrins (ITG)-B2, ITG-7, and ITGAL (or Cd11a), and endoglin (ENG or Cd105), and promote differentiation of monocytes to M2 macrophages. They also induce cyclin (CCN)-E1, CCND1, CCND3, and cyclin-dependent kinase (CDK)-6 [107, 125, 126]. They act through the down-regulation of miR-9 that blocks monocyte differentiation, but the silencing of miR-9 may be overturned by cyclin-dependent kinase inhibitor 2B (CDKN2B) antisense RNA 1 (ANRIL) [127–129] (Fig. 5.1).

96

5 Non-coding RNAs Related to Atherosclerosis

Specifically, miR-155-3p, miR-155-5p, miR-147-3p and miR-9-5p, all have significantly higher expression levels in M1 cells, whereas miR-27a-5p, let-7c-13p, miR-23a-5p and miR-23b-5p, all have higher expression levels in M2 cells. Besides, two sub-clusters of M1 macrophage-specific miRs can be discerned. The first sub-cluster 1 includes early response miRs like miR-29b-1-5p, miR-222-5p, miR-1931, miR-3473b, miR-3473e, and miR-5128, all of which are tightly correlated. The late response miRs let-7e-3p, miR-9-5p/3p, miR-125a-3p, miR-147-5p/3p, miR-155-3p, and let-7e-3p belong to the second sub-cluster [130]. Ox-LDL significantly up-regulates let-7e in ECs. Let-7e promotes NFκB activation and translocation to the nucleus by inhibiting its target gene IκBβ and increasing inflammatory and adhesion molecules’ expression. The long intergenic non-protein coding RNA 1826 (LINC01826 or Lnc-MKI67IP-3) may sponge let-7e, thereby suppressing its pro-inflammatory effects [131]. MiR-9 enhances M1 macrophage polarization by inducing peroxisome proliferator-activated receptor (PPAR)-δ [132]. MiR-34a silences p53-small interfering RNA that attenuates high-glucose-induced endothelial inflammation and oxidative stress by repressing sirtuin (SIRT)-1 [133]. OxLDL induces toll-like receptor adaptor molecule one that up-regulates miR-155 in macrophages, associated with activation of the MAPK1/2 and suppressor of cytokine signaling 1 (SOCS1) / signal transducing and activator of transcription (STAT)-3 /NFκB signaling and elevation of IL6 and TNF-α levels [134]. Homeobox (HOX) transcript antisense lncRNA (HOTAIR), higher in obesity and type 2 diabetes, stimulates oxidative stress and inflammation in macrophages by silencing miR-330-5p [135]. Ox-LDL-induced taurine up-regulated 1 (TUG1) enhances inflammation and apoptosis by silencing miR-133, increasing fibroblast growth factor (FGF) [136]. The silencing of let-7d by lin-28 homolog (LIN28)-b in diabetic human plaques activates NFκB [137]. The decrease of miR-10a in patients with kidney disease and miR-132 in patients with metabolic syndrome induces inflammation, particularly by IL8 [138–149]. Repression of Krüppel-like zinc finger transcription factor (KLF)2 in macrophages leads to a decrease of miR-124a and miR-150 associated with augmented expression of inflammatory mediators C–C motif chemokine ligand 2 (CCL2 or MCP1) and C-X-C motif chemokine ligand 1 [150]. The decrease of miR-124 also induces KLF6 that restrains miR-223, thereby enhancing the secretion of IL-1β by macrophages [151, 152]. Decrease of mir-126 by TNF-α and ROS in hyperglycemia is associated with inflammation by de-repression of high-mobility group box 1 [153, 154]. Low MALAT1 is associated with high IFN-γ and TNF-α and accelerated atherosclerosis [155] (Fig. 5.1). The increase of miR-125b in patients with type 2 diabetes and stroke protects against M1 macrophage polarization [156–158]. ApoE in HDL induces miR-146a in monocytes and macrophages, thereby inhibiting pro-inflammatory responses [159]. Further, inhibition of inflammation by miR-146a suppresses ox-LDL accumulation and foam cell formation [160]. However, aging lowers miR-146a causing pronounced inflammation [161]. MiR-181a-5p and miR-181a-3p cooperatively recede inflammation by blocking the NFκB [162] (Fig. 5.1).

5.1 Endothelial Injury, Inflammation, and Apoptosis

5.1.1.3

97

Foam Cells

Ox-LDL by up-regulating LOX-1 induces miR-146a via the JNK and NF-κB pathways in macrophages, preventing inflammation [163]. The decrease of nuclear paraspeckle assembly transcript (NEAT1) increases the expression of CD36 and lipid accumulation in foam cells [164]. The increase of miR-9-5p inhibits expression of ABCA1, thereby decreasing reverse cholesterol transport [165]. MiR-378 directly targets ABCG1, and loss of miR-378 suppression resulted in increased cholesterol efflux and atheroprotection in mice [166]. ZNFX1 antisense RNA 1 (ZFAS1) induces inflammation and reduces cholesterol efflux in atherosclerotic plaques [167]. Reduction of the lincRNA HOXC cluster antisense RNA 1 (HOXC-AS1) in atherosclerotic plaques increases cholesterol accumulation by ox-LDL [168]. In contrast, let-7 g prevents foam cell formation by silencing miR-33 that otherwise would inhibit the expression of ABCA1 and ABCG1 [169–171]. LncRNA CDKN2B antisense RNA 1 (CDKN2B-AS1) increases cholesterol efflux and reduces lipid accumulation by silencing ADAM metallopeptidase domain 10 (ADAM10) [172]. Foam cells excessively accumulate lipids leading to cell burst and release of thrombogenic particles. Reduced levels of miR-181b in vascular cells increase TF associated with thrombogenicity associated with endothelial injury [173] (Fig. 5.1).

5.1.1.4

Dendritic and T Cells

Let-7c is essential for ox-LDL-mediated monocytes’ differentiation to DCs and DC maturation, cytokine production, and subsequent T-cell proliferation [174]. MiR-17, miR-20a, and miR-106a inhibit monocytic differentiation to macrophages but induce maturation of DCs [107, 175, 176]. DCs secrete exosomes that contain miR-155 that enhances and miR-146a that reduces inflammatory gene expression [177]. MALAT1 may block this action of miR-155 [178]. MiR-21, significantly up-regulated in acute myocardial infarction patients, reduces the number of circulating Treg cells through a TGF-β1 / SMAD family member (SMAD)-independent signaling pathway in mononuclear cells [179]. Let7, silencing miR-33, retains the Treg and M2 macrophage phenotype [180]. NEAT targets STAT6 for ubiquitination and elevates Th2 cytokines IL4, IL5, and IL13 by regulating the enhancer of zeste 2 polycomb repressive complex 2 (EZH2) / itchy E3 ubiquitin protein ligase (ITCH) axis [181]. MiR-146a induces Th1 differentiation by enhancing T-bet in mononuclear cells [159, 182, 183]. However, miR-146a deficiency in CD4 cells enhances IL21 and induces Th17 differentiation, further enhanced by the inflammation-related miR-155 [134, 184–186]. The down-regulation of the cancer susceptibility 11 lncRNA (CASC11) increases TGF-β, inducing IL17 secretion by inflammatory Th17 cells, and increasing IL9 [187–189]. T-cell derived extracellular vesicles enriched in miR-150-5p and miR-142-3p may block DC activation [190] (Fig. 5.1).

98

5.1.1.5

5 Non-coding RNAs Related to Atherosclerosis

Apoptosis of Endothelial Cells and Plaque Destabilization

Atherosclerotic plaque rupture and subsequent acute events such as acute myocardial infarction and stroke are due to uncontrolled apoptosis in ECs, macrophages, and VSMCs [191]. Apoptosis in ECs, induced by inflammatory cytokines and ox-LDL, leads to endothelial erosion. Apoptosis in VSMCs leads to thinning of fibrous cap and plaque instability [187, 192, 193]. MiR-34a enhances oxidative stress-associated EC apoptosis [194, 195]. MiR-124a, increased in smokers susceptible to atherosclerosis, induces EC apoptosis by blocking PI3K/AKT signaling and promoting ROS release [196]. Transfer of miR-155 from VSMCs to ECs causes endothelial cell death [197]. The growth arrest-specific five lncRNA (GAS5)-enriched microvesicles secreted by macrophages induce apoptosis of ECs and macrophages [198]. H19 increases apoptosis by silencing let-7b. Naturally, let-7b inhibits the ox-LDL-induced EC apoptosis, NO deficiency, and ROS secretion [82, 137]. The decrease of mir-125 and the increase of taurine up-regulated 1 (TUG1) promotes apoptosis [142, 199–203]. The decrease of miR-126 in response to tissue damage may also decrease chemokine CXCL-12 and its receptor CXCR-4, which counteract apoptosis and recruit endothelial progenitor cells [204]. MiR-21, mechanistically increased by shear stress, protects ECs cells against apoptosis induced by ROS and inflammation by increasing eNOS and NO production and silencing the programmed cell death 4 (PDCD4) gene [205–210]. MiR-181 enhances TNF-α-induced cell death, while MIAT decreases apoptosis by sponging of miR-181b [211, 212]. MIAT also sponges miR-150 that promotes plaque growth via increased macrophage infiltration and lipid accumulation and destabilizes plaques by increasing EC apoptotic cell death mediated by ox-LDL [213–215].(Fig. 5.1).

5.2 Fibroproliferative Remodeling and Plaque Destabilization Atherosclerotic plaque formation also results from VSMC fibroproliferative remodeling in the vascular wall. The recruitment of progenitor cells to the blood vessel wall and the proliferation of VSMCs is regulated by platelet-derived growth factor (PDGF)-B, functioning as dimer PDGF-BB secreted by ECs [216]. Insulin-like growth factor 1 (IGF1) enhances VSMC by acting synergistically with PDGF-BB [217]. TGF-β induces VSMC differentiation involving SMAD2, 3, and 4. SMADs bind directly to the regulatory elements of myocardin, one of the central transcriptional regulators of the VSMC lineage. Differentiated VSMCs express various SMCspecific contractile and contractile-associated proteins, including SM myosin heavy chain, SM22, calponin, and SM α-actin [218, 219]. The effects of TGF-β on VSMCspecific gene expression are mediated via NOX4, suggesting that ROS regulates SMC-specific gene transcription [220] (Fig. 5.2). When shear stress and vessel damage occur, mature VSMCs de-differentiate associated with decreased VSMC differentiation marker gene expression and increased

5.2 Fibroproliferative Remodeling and Plaque Destabilization

99

Fig. 5.2 Non-coding RNAs in fibroproliferative remodeling and plaque destabilization. Atherosclerotic plaque formation also results from VSMC fibroproliferative remodeling in the vascular wall. PDGF secreted by ECs attracts progenitor cells that differentiate to VSMCs. PDGF and IGF1 induce VSMC proliferation. However, miR-34a enriched in microvesicles secreted by VSMCs in atherosclerotic plaques induces senescence in progenitor cells. MiR-143–145, induced by TGF-β in early lesions, acts as communication molecules between VSMCs and ECs to modulate the angiogenic and vessel stabilization properties of ECs, which are impaired by a decrease of GAS5. The increase of miR-21, miR-92a, and miR-378a-5p, and the decrease of miR-26a, silenced by UCA1, miR-124a, silenced by circWDR77, miR-214, silenced by LINC00341, miR-370, silenced by circCHFR, and miR-544a, silenced by lncRNA LEF1-AS1, induce VSMC proliferation. In contrast, miR-638 and miR-663 inhibit proliferation. Shear stress and inflammation up-regulate miR-26a, which may be blocked by UCA1, miR-146a, miR-155, and miR-221–222. They dedifferentiate contractile to proliferative VSMCs. Cholesterol loading in VSMCs converts VSMCs to macrophage-like cells driven by the decrease of miR-143–145. TF induces macrophage-like cells to secrete MIF that inhibits VSMC migration and changes ECM composition deposited by VSMCs, characterized by decreased laminin and collagen. The decrease of miR-124 exacerbates this, while miR-143–145 prevents it. LincRNA-p21 and PVT1 cause VSMC senescence and death, but miR21, miR-25, MIAT, silencing miR-150 and miR-181b, and ANRIL, silencing miR-181a may inhibit this. VSMC-derived macrophage-like cells also have reduced phagocytic capacity compared with activated peritoneal macrophages. Reduced phagocytosis, for example, of apoptotic cells, is evident in advanced atherosclerosis and directly promotes the formation of the ‘necrotic’ core of advanced plaques, inhibited by miR-29. Apoptosis is also associated with the calcification of plaques due to the increase of miR-221–222. Increased non-coding RNAs are in red, decreased in green

100

5 Non-coding RNAs Related to Atherosclerosis

proliferation, migration, and matrix synthesis [221]. VSMC (de-)differentiation depends on the matrix composition whereby fibronectin supports SMC proliferation, while collagen (COL)- IV and laminin promote VSMC differentiation. Matrix degradation and re-expression of fibronectin and other growth-promoting matrix components such as COLI also occurs following vessel injury and likely contribute to VSMC phenotypic modulation [222, 223]. Pro-inflammatory markers contribute to this de-differentiation leading to extensive accumulation of immature VSMCs that fail to re-differentiate [224]. Especially, macrophage migration inhibitory factor (MIF) induced by tissue factor (TF) causes de-differentiation and migration of immature VSMCs [225, 226] (Fig. 5.2). Also, VSMCs switch to macrophage-like cells driven by lipid accumulation. However, in contrast to classical macrophages, VSMC-derived macrophage-like cells lack phagocytic capacity, promoting necrotic core formation that exacerbates inflammation [227, 228] (Fig. 5.2). The shoulder area of a plaque is most vulnerable to rupture because it contains fewer VSMCs and more macrophages. This co-localization suggests that preferentially macrophages induce VSMC apoptosis through death-ligand/death receptor interactions [229–231]. Apoptotic VSMCs show a thickened basal lamina surrounding the cytoplasmic remnants of the VSMC. Inefficient clearance of apoptotic VSMCs results in secondary necrosis and subsequent inflammation [232]. Metalloproteinases (MMPs), secreted by inflammatory cells, degrade the fibrous cap and increase plaque’s vulnerability [187]. Another form of cell death is autophagy. Autophagy is the lysosome-dependent degradation of cytoplasm and damaged cell organelles like mitochondria, ER, and peroxisomes [232–234]. Various stimuli and stressors, including ROS, lipid species, and inflammatory cytokines associated with metabolic stress, induce autophagy. Although autophagy is a survival mechanism, excessive autophagic activity destructs ER and mitochondria, ultimately causing cell death [235, 236] (Fig. 5.2). VSMC apoptosis also induces calcification of plaques [237]. Calcification may depend on systemic factors, including hyperlipidemia, inflammation, and type 2 diabetes. Local VSMCs and circulating hematopoietic stem cells calcify. Matrix vesicles derived from macrophages that undergo apoptosis serve as a nidus for calcification [238]. Fragmented calcification spreads into the surrounding collagen-rich extracellular matrix (ECM) in fibrocalcific plaques. The calcified sheets may break into nodules with fibrin deposition associated with thrombosis [239]. Therefore, intraplaque calcification may not be a stabilizing factor per se [240, 241]. While extensive calcifications may stabilize the plaque, small microcalcifications may cause plaque rupture. These microcalcifications are derived from matrix vesicles enriched in calcium-binding proteins [242]. Finally, the total amount of calcium does not seem related to plaque vulnerability, but there was an association between hydroxyapatite content and plaque instability [243] (Fig. 5.2).

5.2 Fibroproliferative Remodeling and Plaque Destabilization

101

5.2.1 Non-coding RNAs in Fibroproliferative Remodeling and Plaque Destabilization PDGF secreted by ECs attracts progenitor cells that differentiate to VSMCS. However, miR-34a enriched in microvesicles secreted by VSMCs induces stem cell senescence by silencing SIRT1 [244]. MiR-143–145 induced by TGF-β acts as communication molecules between VSMCs and ECs to modulate the angiogenic and vessel stabilization properties of ECs [245]. However, GAS5 knockdown aggravates hypertension-induced microvascular dysfunction by inhibiting EC and VSMC cross-talk [246]. MiR-21, higher in type 2 diabetes and related to systemic inflammation, stimulates VSMC proliferation by increasing MAPK7 and KRAS proto-oncogene GTPase (KRAS) signaling [247–253]. Up-regulation of miR-92a inhibits KLF4 expression, thereby promoting proliferation and migration of VSMCs and inhibiting differentiation of VSMCs to macrophage-like cells. PDGF-BB-induced miR-378a-5p promotes VSMC proliferation and migration by targeting the CDK1/p21 signaling pathway [254–256]. The urothelial cancer-associated 1 (UCA1) sponges miR-26a and thereby increases VSMC proliferation and migration [257]. The circular RNA derived from WD repeat domain 77 (circWDR77) induces VSMC proliferation and migration via targeting miR-124/FGF2 [258]. The lncRNA derived from spectrin repeat-containing nuclear envelope family member 3 (LINC00341) promotes VSMC proliferation and migration via a miR-214/FOXO4 feedback loop [259]. The circ-RNA derived from the checkpoint with forkhead and ring finger domains (circCHFR) facilitates the proliferation and migration of VSMCs by acting as a sponge of miR-370, thereby increasing the expression of the forkhead box O1 (FOXO1) that binds the promoter region of CCND1 mRNA [260]. LEF1-AS1 silences miR-544a, thereby stimulating the phosphatase and tensin homolog (PTEN) pathway, resulting in enhanced VSMC proliferation and migration [261]. MiR-638, induced by PDGF-BB, inhibits VSMC proliferation, and migration by targeting the orphan nuclear receptor NOR1 [262]. MiR-663, induced by a shear stress-associated inflammatory response in ECs, inhibits PDGF-induced VSMC proliferation and migration and increases VSMC differentiation [263]. MiR-424 may inhibit VSMC proliferation, but this inhibition is overwhelmed by inflammation in pathological situations such as injury-induced restenosis [264]. MiR-26a, miR-146a, and miR-155 de-differentiate contractile to synthetic VSMCs, but UCA1 may block this action of miR-26a [257, 265–268]. MiR-221–222 also de-differentiate contractile VSMCs and induce their calcification [98, 269, 270] (Fig. 5.2). The decrease of miR-124 is associated with a decrease of collagen, shifting contractile to proliferating VSMCS [271]. MiR-145 counteracts this shift [204, 272]. Cholesterol loading in VSMCs downregulates miR-143/145 and the master VSMC differentiation transcription factor myocardin, thereby converting VSMCs to dysfunctional macrophage-like cells [273].

102

5 Non-coding RNAs Related to Atherosclerosis

Asthma-induced IgE activates the tumor protein p53 pathway corepressor 1 lncRNA (lincRNA-p21) pathway to induce VSMC senescence [274]. The ANG II-induced PVT1 up-regulates matrix metalloproteinase (MMP)-2 and MMP-9 and represses TIMP metallopeptidase inhibitor 1 (TIMP1), facilitating VSMC apoptosis and ECM degradation. It promotes a switch from the contractile to synthetic VSMC phenotype [275]. In contrast, miR-21, miR-25, and MIAT silencing miR-150 and miR-181 protect VSMCs against apoptosis [276]. ANRIL in atherosclerotic plaques protects VSMC from senescence, possibly by downregulating miR-181a and upregulating SIRT1 [277, 278]. MiR-29 silences COL-1A and COL-3A, reducing lesion size, enhancing fibrous cap thickness, and reducing necrotic zones [279] (Fig. 5.2).

References 1. Eelen, G., et al. (2018). Endothelial cell metabolism. Physiological Reviews, 98, 3–58. https:// doi.org/10.1152/physrev.00001.2017. 2. Chua, C. C., Hamdy, R. C., & Chua, B. H. (1998). Upregulation of vascular endothelial growth factor by H2O2 in rat heart endothelial cells. Free Radical Biology and Medicine, 25, 891–897. https://doi.org/10.1016/s0891-5849(98)00115-4. 3. De Bock, K., et al. (2013). Role of PFKFB3-driven glycolysis in vessel sprouting. Cell, 154, 651–663. https://doi.org/10.1016/j.cell.2013.06.037. 4. Yu, P., et al. (2017). FGF-dependent metabolic control of vascular development. Nature, 545, 224–228. https://doi.org/10.1038/nature22322. 5. Choi, Y. K. (2017). A positive circuit of VEGF increases Glut-1 expression by increasing HIF1alpha gene expression in human retinal endothelial cells. Archives of Pharmacal Research, 40, 1433–1442. https://doi.org/10.1007/s12272-017-0971-5. 6. Pamukcu, B., Lip, G. Y., Devitt, A., Griffiths, H., & Shantsila, E. (2010). The role of monocytes in atherosclerotic coronary artery disease. Annals of Medicine, 42, 394–403. https://doi.org/ 10.3109/07853890.2010.497767. 7. Jaipersad, A. S., Lip, G. Y., Silverman, S., & Shantsila, E. (2014). The role of monocytes in angiogenesis and atherosclerosis. Journal of the American College of Cardiology, 63, 1–11. https://doi.org/10.1016/j.jacc.2013.09.019. 8. Haskard, D. O., Boyle, J. J., Evans, P. C., Mason, J. C., & Randi, A. M. (2013). Cytoprotective signaling and gene expression in endothelial cells and macrophages-lessons for atherosclerosis. Microcirculation, 20, 203–216. https://doi.org/10.1111/micc.12020. 9. Arderiu, G., Espinosa, S., Pena, E., Aledo, R., & Badimon, L. (2014). Monocyte-secreted Wnt5a interacts with FZD5 in microvascular endothelial cells and induces angiogenesis through tissue factor signaling. Journal of Molecular Cell Biology, 6, 380–393. https://doi. org/10.1093/jmcb/mju036. 10. Ribatti, D., Levi-Schaffer, F., & Kovanen, P. T. (2008). Inflammatory angiogenesis in atherogenesis–a double-edged sword. Annals of Medicine, 40, 606–621. https://doi.org/10.1080/ 07853890802186913. 11. Franco, C. A., et al. (2016). Non-canonical Wnt signalling modulates the endothelial shear stress flow sensor in vascular remodelling. Elife, 5, e07727. https://doi.org/10.7554/eLife. 07727. 12. Kim, S., & Woo, C. H. (2018). Laminar flow inhibits ER stress-induced endothelial apoptosis through PI3K/Akt-dependent signaling pathway. Molecules and Cells, 41, 964–970. https:// doi.org/10.14348/molcells.2018.0111. 13. Wang, X. L., et al. (2019). Atorvastatin plus therapeutic ultrasound improve postnatal neovascularization in response to hindlimb ischemia via the PI3K-Akt pathway. American Journal of Translational Research, 11, 2877–2886.

References

103

14. Cao, Y. L., Liu, D. J., & Zhang, H. G. (2018). MiR-7 regulates the PI3K/AKT/VEGF pathway of retinal capillary endothelial cell and retinal pericytes in diabetic rat model through IRS-1 and inhibits cell proliferation. European Review for Medical and Pharmacological Sciences, 22, 4427–4430. https://doi.org/10.26355/eurrev_201807_15493. 15. Resnick, N., et al. (2003). Fluid shear stress and the vascular endothelium: For better and for worse. Progress in Biophysics and Molecular Biology, 81, 177–199. 16. Cabrera-Fuentes, H. A., et al. (2015). Regulation of monocyte/macrophage polarisation by extracellular RNA. Thrombosis and Haemostasis, 113, 473–481. https://doi.org/10.1160/ TH14-06-0507. 17. Jablonski, K. A., et al. (2015). Novel Markers to Delineate Murine M1 and M2 Macrophages. PLoS ONE, 10, e0145342. https://doi.org/10.1371/journal.pone.0145342. 18. Xuan, W., Qu, Q., Zheng, B., Xiong, S., & Fan, G. H. (2015). The chemotaxis of M1 and M2 macrophages is regulated by different chemokines. Journal of Leukocyte Biology, 97, 61–69. https://doi.org/10.1189/jlb.1A0314-170R. 19. Bories, G. F. P., & Leitinger, N. (2017). Macrophage metabolism in atherosclerosis. FEBS Letters, 591, 3042–3060. https://doi.org/10.1002/1873-3468.12786. 20. Cole, J. E., Georgiou, E., & Monaco, C. (2010). The expression and functions of toll-like receptors in atherosclerosis. Mediators of Inflammation, 2010, 393946. https://doi.org/10. 1155/2010/393946. 21. Wesche, H., et al. (1999). IRAK-M is a novel member of the Pelle/interleukin-1 receptorassociated kinase (IRAK) family. Journal of Biological Chemistry, 274, 19403–19410. 22. Rosati, O., & Martin, M. U. (2002). Identification and characterization of murine IRAK-M. Biochemical and Biophysical Research Communications, 293, 1472–1477. https://doi.org/10. 1016/S0006-291X(02)00411-4. 23. Kobayashi, K., et al. (2002). IRAK-M is a negative regulator of Toll-like receptor signaling. Cell, 110, 191–202. 24. Hulsmans, M., et al. (2012). Interleukin-1 receptor-associated kinase-3 is a key inhibitor of inflammation in obesity and metabolic syndrome. PLoS ONE, 7, e30414. https://doi.org/10. 1371/journal.pone.0030414. 25. van ‘t Veer, C. et al. (2007). Induction of IRAK-M is associated with lipopolysaccharide tolerance in a human endotoxemia model. Journal of Immunology, 179, 7110–7120. 26. Forstermann, U., Xia, N., & Li, H. (2017). Roles of vascular oxidative stress and nitric oxide in the pathogenesis of atherosclerosis. Circulation Research, 120, 713–735. https://doi.org/ 10.1161/CIRCRESAHA.116.309326. 27. Hulsmans, M., & Holvoet, P. (2010). The vicious circle between oxidative stress and inflammation in atherosclerosis. Journal of Cellular and Molecular Medicine, 14, 70–78. https:// doi.org/10.1111/j.1582-4934.2009.00978.x. 28. Holvoet, P., De Keyzer, D., & Jacobs, D. R., Jr. (2008). Oxidized LDL and the metabolic syndrome. Future Lipidol, 3, 637–649. https://doi.org/10.2217/17460875.3.6.637. 29. Holvoet, P., Lee, D. H., Steffes, M., Gross, M., & Jacobs, D. R., Jr. (2008). Association between circulating oxidized low-density lipoprotein and incidence of the metabolic syndrome. JAMA, 299, 2287–2293. https://doi.org/10.1001/jama.299.19.2287. 30. Negre-Salvayre, A., et al. (2017). Dual signaling evoked by oxidized LDLs in vascular cells. Free Radical Biology and Medicine, 106, 118–133. https://doi.org/10.1016/j.freeradbiomed. 2017.02.006. 31. 31van Berkel, T. J. et al. (2005). Scavenger receptors: Friend or foe in atherosclerosis? Current Opinion Lipidology, 16, 525–535. 32. Hoekstra, M., & Sorci-Thomas, M. (2017). Rediscovering scavenger receptor type BI: Surprising new roles for the HDL receptor. Current Opinion in Lipidology, 28, 255–260. https://doi.org/10.1097/MOL.0000000000000413. 33. Dai, Y., Condorelli, G., & Mehta, J. L. (2016). Scavenger receptors and non-coding RNAs: Relevance in atherogenesis. Cardiovascular Research, 109, 24–33. https://doi.org/10.1093/ cvr/cvv236.

104

5 Non-coding RNAs Related to Atherosclerosis

34. Murshid, A., Borges, T. J., Lang, B. J., & Calderwood, S. K. (2016). The scavenger receptor SREC-I cooperates with toll-like receptors to trigger inflammatory innate immune responses. Front Immunol, 7, 226. https://doi.org/10.3389/fimmu.2016.00226. 35. Shimada, K. (2009). Immune system and atherosclerotic disease: Heterogeneity of leukocyte subsets participating in the pathogenesis of atherosclerosis. Circulation Journal, 73, 994– 1001. 36. Moore, K. J., & Tabas, I. (2011). Macrophages in the pathogenesis of atherosclerosis. Cell, 145, 341–355. https://doi.org/10.1016/j.cell.2011.04.005. 37. Gounopoulos, P., Merki, E., Hansen, L. F., Choi, S. H., & Tsimikas, S. (2007). Antibodies to oxidized low density lipoprotein: Epidemiological studies and potential clinical applications in cardiovascular disease. Minerva Cardioangiologica, 55, 821–837. 38. Hansson, G. K., & Hermansson, A. (2011). The immune system in atherosclerosis. Nature Immunology, 12, 204–212. https://doi.org/10.1038/ni.2001. 39. Libby, P., Ridker, P. M., & Hansson, G. K. (2011). Progress and challenges in translating the biology of atherosclerosis. Nature, 473, 317–325. https://doi.org/10.1038/nature10146. 40. Lahoute, C., Herbin, O., Mallat, Z., & Tedgui, A. (2011). Adaptive immunity in atherosclerosis: Mechanisms and future therapeutic targets. Nature Reviews Cardiology, 8, 348–358. https://doi.org/10.1038/nrcardio.2011.62. 41. Laurat, E., et al. (2001). In vivo downregulation of T helper cell 1 immune responses reduces atherogenesis in apolipoprotein E-knockout mice. Circulation, 104, 197–202. 42. Mallat, Z., Taleb, S., Ait-Oufella, H., & Tedgui, A. (2009). The role of adaptive T cell immunity in atherosclerosis. Journal of Lipid Research, 50(Suppl), S364-369. https://doi.org/10.1194/ jlr.R800092-JLR200. 43. Elhage, R., et al. (2003). Reduced atherosclerosis in interleukin-18 deficient apolipoprotein E-knockout mice. Cardiovascular Research, 59, 234–240. 44. Davenport, P., & Tipping, P. G. (2003). The role of interleukin-4 and interleukin-12 in the progression of atherosclerosis in apolipoprotein E-deficient mice. American Journal of Pathology, 163, 1117–1125. https://doi.org/10.1016/S0002-9440(10)63471-2. 45. Mallat, Z., et al. (2001). Expression of interleukin-18 in human atherosclerotic plaques and relation to plaque instability. Circulation, 104, 1598–1603. 46. Mallat, Z., et al. (2001). Interleukin-18/interleukin-18 binding protein signaling modulates atherosclerotic lesion development and stability. Circulation Research, 89, E41-45. 47. Buono, C., et al. (2005). T-bet deficiency reduces atherosclerosis and alters plaque antigenspecific immune responses. Proceedings of the National Academy of Sciences of the United States of America, 102, 1596–1601. https://doi.org/10.1073/pnas.0409015102. 48. Binder, C. J., et al. (2004). IL-5 links adaptive and natural immunity specific for epitopes of oxidized LDL and protects from atherosclerosis. Journal of Clinical Investigation, 114, 427–437. https://doi.org/10.1172/JCI20479. 49. Wurtz, O., Bajenoff, M., & Guerder, S. (2004). IL-4-mediated inhibition of IFN-gamma production by CD4+ T cells proceeds by several developmentally regulated mechanisms. International Immunology, 16, 501–508. 50. Engelbertsen, D., et al. (2013). T-helper 2 immunity is associated with reduced risk of myocardial infarction and stroke. Arteriosclerosis, Thrombosis, and Vascular Biology, 33, 637–644. https://doi.org/10.1161/ATVBAHA.112.300871. 51. Ray, A., Khare, A., Krishnamoorthy, N., Qi, Z., & Ray, P. (2010). Regulatory T cells in many flavors control asthma. Mucosal Immunology, 3, 216–229. https://doi.org/10.1038/mi.2010.4. 52. Butcher, M., & Galkina, E. (2011). Current views on the functions of interleukin-17Aproducing cells in atherosclerosis. Thrombosis and Haemostasis, 106, 787–795. https://doi. org/10.1160/TH11-05-0342. 53. Erbel, C., et al. (2009). Inhibition of IL-17A attenuates atherosclerotic lesion development in apoE-deficient mice. The Journal of Immunology, 183, 8167–8175. https://doi.org/10.4049/ jimmunol.0901126. 54. Jovanovic, D. V., et al. (1998). IL-17 stimulates the production and expression of proinflammatory cytokines, IL-beta and TNF-alpha, by human macrophages. The Journal of Immunology, 160, 3513–3521.

References

105

55. Madhur, M. S., et al. (2011). Role of interleukin 17 in inflammation, atherosclerosis, and vascular function in apolipoprotein e-deficient mice. Arteriosclerosis, Thrombosis, and Vascular Biology, 31, 1565–1572. https://doi.org/10.1161/ATVBAHA.111.227629. 56. Ley, K., Smith, E., & Stark, M. A. (2006). IL-17A-producing neutrophil-regulatory Tn lymphocytes. Immunologic Research, 34, 229–242. https://doi.org/10.1385/IR:34:3:229. 57. Danzaki, K., et al. (2012). Interleukin-17A deficiency accelerates unstable atherosclerotic plaque formation in apolipoprotein E-deficient mice. Arteriosclerosis, Thrombosis, and Vascular Biology, 32, 273–280. https://doi.org/10.1161/ATVBAHA.111.229997. 58. Kronenberg, M., & Gapin, L. (2002). The unconventional lifestyle of NKT cells. Nature Reviews Immunology, 2, 557–568. https://doi.org/10.1038/nri854. 59. Nowak, M., & Stein-Streilein, J. (2007). Invariant NKT cells and tolerance. International Reviews of Immunology, 26, 95–119. https://doi.org/10.1080/08830180601070195. 60. Yang, Y., Bao, M., & Yoon, J. W. (2001). Intrinsic defects in the T-cell lineage results in natural killer T-cell deficiency and the development of diabetes in the nonobese diabetic mouse. Diabetes, 50, 2691–2699. 61. Bobryshev, Y. V., & Lord, R. S. (2005). Co-accumulation of dendritic cells and natural killer T cells within rupture-prone regions in human atherosclerotic plaques. Journal of Histochemistry and Cytochemistry, 53, 781–785. https://doi.org/10.1369/jhc.4B6570.2005. 62. Bobryshev, Y. V. (2005). Natural killer T cells in atherosclerosis. Arteriosclerosis Thrombosis, and Vascular Biology, 25, e40; author reply e40, doi:https://doi.org/10.1161/01.ATV.000016 1317.01678.75. 63. Chan, A. T., Kollnberger, S. D., Wedderburn, L. R., & Bowness, P. (2005). Expansion and enhanced survival of natural killer cells expressing the killer immunoglobulin-like receptor KIR3DL2 in spondylarthritis. Arthritis and Rheumatism, 52, 3586–3595. https://doi.org/10. 1002/art.21395. 64. Tupin, E., et al. (2004). CD1d-dependent activation of NKT cells aggravates atherosclerosis. Journal of Experimental Medicine, 199, 417–422. https://doi.org/10.1084/jem.20030997. 65. Major, A. S., et al. (2004). Quantitative and qualitative differences in proatherogenic NKT cells in apolipoprotein E-deficient mice. Arteriosclerosis, Thrombosis, and Vascular Biology, 24, 2351–2357. https://doi.org/10.1161/01.ATV.0000147112.84168.87. 66. Xu, X., Ma, C., Duan, Z., Du, Y., & Liu, C. (2019). lncRNA ZEB1-AS1 Mediates Oxidative Low-Density Lipoprotein-Mediated Endothelial Cells Injury by Post-transcriptional Stabilization of NOD2. Front Pharmacol, 10, 397. https://doi.org/10.3389/fphar.2019.00397. 67. Klimczak, D. et al. (2017). Plasma microRNA-155–5p is increased among patients with chronic kidney disease and nocturnal hypertension. Journal of the American Society of Hypertension, 11, 831–841 e834. doi:https://doi.org/10.1016/j.jash.2017.10.008. 68. Wu, X. Y., Fan, W. D., Fang, R., & Wu, G. F. (2014). Regulation of microRNA-155 in endothelial inflammation by targeting nuclear factor (NF)-kappaB P65. Journal of Cellular Biochemistry, 115, 1928–1936. https://doi.org/10.1002/jcb.24864. 69. O’Connell, R. M., Taganov, K. D., Boldin, M. P., Cheng, G., & Baltimore, D. (2007). MicroRNA-155 is induced during the macrophage inflammatory response. Proceedings of the National Academy of Sciences of the United States of America, 104, 1604–1609. https:// doi.org/10.1073/pnas.0610731104. 70. Sun, H. X., et al. (2012). Essential role of microRNA-155 in regulating endothelium-dependent vasorelaxation by targeting endothelial nitric oxide synthase. Hypertension, 60, 1407–1414. https://doi.org/10.1161/HYPERTENSIONAHA.112.197301. 71. Qiu, X. K., & Ma, J. (2018). Alteration in microRNA-155 level correspond to severity of coronary heart disease. Scand J Clin Lab Invest, 1–5. doi:https://doi.org/10.1080/00365513. 2018.1435904. 72. Li, S., et al. (2018). The suppression of ox-LDL-induced inflammatory cytokine release and apoptosis of HCAECs by long non-coding RNA-MALAT1 via regulating microRNA155/SOCS1 pathway. Nutrition, Metabolism and Cardiovascular Diseases, 28, 1175–1187. https://doi.org/10.1016/j.numecd.2018.06.017.

106

5 Non-coding RNAs Related to Atherosclerosis

73. Cremer, S., et al. (2019). Hematopoietic deficiency of the long noncoding RNA MALAT1 promotes atherosclerosis and plaque inflammation. Circulation, 139, 1320–1334. https://doi. org/10.1161/CIRCULATIONAHA.117.029015. 74. Wang, S., et al. (2019). MALAT1 lncRNA induces autophagy and protects brain microvascular endothelial cells against oxygen-glucose deprivation by binding to miR-200c-3p and upregulating SIRT1 expression. Neuroscience, 397, 116–126. https://doi.org/10.1016/j.neu roscience.2018.11.024. 75. Jiang, Y., et al. (2014). Peripheral blood miRNAs as a biomarker for chronic cardiovascular diseases. Scientific Reports, 4, 5026. https://doi.org/10.1038/srep05026. 76. Song, C. L., et al. (2016). MicroRNA-130a alleviates human coronary artery endothelial cell injury and inflammatory responses by targeting PTEN via activating PI3K/Akt/eNOS signaling pathway. Oncotarget, 7, 71922–71936. https://doi.org/10.18632/oncotarget.12431. 77. Cheng, J., et al. (2019). Downregulation of hsa_circ_0068087 ameliorates TLR4/NFkappaB/NLRP3 inflammasome-mediated inflammation and endothelial cell dysfunction in high glucose conditioned by sponging miR-197. Gene, 709, 1–7. https://doi.org/10.1016/j. gene.2019.05.012. 78. Zhou, D. M., et al. (2020). MiR-9 promotes angiogenesis of endothelial progenitor cell to facilitate thrombi recanalization via targeting TRPM7 through PI3K/Akt/autophagy pathway. Journal of Cellular and Molecular Medicine, 24, 4624–4632. https://doi.org/10.1111/jcmm. 15124. 79. Campagnolo, P., et al. (2015). Resveratrol-induced vascular progenitor differentiation towards endothelial lineage via MiR-21/Akt/beta-catenin is protective in vessel graft models. PLoS ONE, 10, e0125122. https://doi.org/10.1371/journal.pone.0125122. 80. Cui, Y., Li, T., Yang, D., Li, S., & Le, W. (2016). miR-29 regulates Tet1 expression and contributes to early differentiation of mouse ESCs. Oncotarget, 7, 64932–64941. https://doi. org/10.18632/oncotarget.10751. 81. Hu, C., Bai, X., Liu, C., & Hu, Z. (2019). Long noncoding RNA XIST participates hypoxiainduced angiogenesis in human brain microvascular endothelial cells through regulating miR485/SOX7 axis. Microcirculation. https://doi.org/10.1111/micc.12601. 82. Pan, J. X. (2017). LncRNA H19 promotes atherosclerosis by regulating MAPK and NFkB signaling pathway. European Review for Medical and Pharmacological Sciences, 21, 322–328. 83. Zhang, Z., et al. (2017). Increased plasma levels of lncRNA H19 and LIPCAR are associated with increased risk of coronary artery disease in a Chinese population. Scientific Reports, 7, 7491. https://doi.org/10.1038/s41598-017-07611-z. 84. Qiu, G. Z., Tian, W., Fu, H. T., Li, C. P., & Liu, B. (2016). Long noncoding RNA-MEG3 is involved in diabetes mellitus-related microvascular dysfunction. Biochemical and Biophysical Research Communications, 471, 135–141. https://doi.org/10.1016/j.bbrc.2016.01.164. 85. Michalik, K. M., et al. (2014). Long noncoding RNA MALAT1 regulates endothelial cell function and vessel growth. Circulation Research, 114, 1389–1397. https://doi.org/10.1161/ CIRCRESAHA.114.303265. 86. Bao, M. H., et al. (2013). Let-7 in cardiovascular diseases, heart development and cardiovascular differentiation from stem cells. International Journal of Molecular Sciences, 14, 23086–23102. https://doi.org/10.3390/ijms141123086. 87. Yi, J., & Gao, Z. F. (2019). MicroRNA-9-5p promotes angiogenesis but inhibits apoptosis and inflammation of high glucose-induced injury in human umbilical vascular endothelial cells by targeting CXCR4. International Journal of Biological Macromolecules, 130, 1–9. https:// doi.org/10.1016/j.ijbiomac.2019.02.003. 88. Chen, L. Y., et al. (2019). Activation of the STAT3/microRNA-21 pathway participates in angiotensin II-induced angiogenesis. Journal of Cellular Physiology. https://doi.org/10.1002/ jcp.28564. 89. Demolli, S., et al. (2017). Shear stress-regulated miR-27b controls pericyte recruitment by repressing SEMA6A and SEMA6D. Cardiovascular Research, 113, 681–691. https://doi.org/ 10.1093/cvr/cvx032.

References

107

90. Masson, S., et al. (2018). Circulating microRNA-132 levels improve risk prediction for heart failure hospitalization in patients with chronic heart failure. European Journal of Heart Failure, 20, 78–85. https://doi.org/10.1002/ejhf.961. 91. Rosjo, H., et al. (2014). Prognostic value of circulating microRNA-210 levels in patients with moderate to severe aortic stenosis. PLoS ONE, 9, e91812. https://doi.org/10.1371/journal. pone.0091812. 92. Liu, F., Li, R., Zhang, Y., Qiu, J., & Ling, W. (2014). Association of plasma MiR-17–92 with dyslipidemia in patients with coronary artery disease. Medicine (Baltimore), 93, e98. doi:https://doi.org/10.1097/MD.0000000000000098. 93. Bonauer, A., Boon, R. A., & Dimmeler, S. (2010). Vascular microRNAs. Current Drug Targets, 11, 943–949. 94. Bonauer, A., et al. (2009). MicroRNA-92a controls angiogenesis and functional recovery of ischemic tissues in mice. Science, 324, 1710–1713. https://doi.org/10.1126/science.1174381. 95. Li, J., et al. (2019). HIF1A and VEGF regulate each other by competing endogenous RNA mechanism and involve in the pathogenesis of peritoneal fibrosis. Pathology, Research and Practice, 215, 644–652. https://doi.org/10.1016/j.prp.2018.12.022. 96. Desjarlais, M., Dussault, S., Dhahri, W., Mathieu, R., & Rivard, A. (2017). MicroRNA-150 modulates ischemia-induced neovascularization in atherosclerotic conditions. Arteriosclerosis, Thrombosis, and Vascular Biology, 37, 900–908. https://doi.org/10.1161/ATVBAHA. 117.309189. 97. Zhao, M., Wang, J., Xi, X., Tan, N., & Zhang, L. (2018). SNHG12 promotes angiogenesis following ischemic stroke via regulating miR-150/VEGF pathway. Neuroscience, 390, 231– 240. https://doi.org/10.1016/j.neuroscience.2018.08.029. 98. Chistiakov, D. A., Sobenin, I. A., Orekhov, A. N., & Bobryshev, Y. V. (2015). Human miR-221/222 in physiological and atherosclerotic vascular remodeling. BioMed Research International, 2015, 354517. https://doi.org/10.1155/2015/354517. 99. Chen, Y., et al. (2010). Regulation of the expression and activity of the antiangiogenic homeobox gene GAX/MEOX2 by ZEB2 and microRNA-221. Molecular and Cellular Biology, 30, 3902–3913. https://doi.org/10.1128/MCB.01237-09. 100. Jia, Q. W., et al. (2017). Predictive effects of circulating miR-221, miR-130a and miR-155 for coronary heart disease: A multi-ethnic study in China. Cellular Physiology and Biochemistry, 42, 808–823. https://doi.org/10.1159/000478071. 101. Dentelli, P., et al. (2010). microRNA-222 controls neovascularization by regulating signal transducer and activator of transcription 5A expression. Arteriosclerosis, Thrombosis, and Vascular Biology, 30, 1562–1568. https://doi.org/10.1161/ATVBAHA.110.206201. 102. Zhu, A. D., Sun, Y. Y., Ma, Q. J., & Xu, F. (2019). lncRNA-ATB promotes viability, migration, and angiogenesis in human microvascular endothelial cells by sponging microRNA-195. Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb.28692. 103. Zheng, J., et al. (2018). lncRNA PVT1 promotes the angiogenesis of vascular endothelial cell by targeting miR26b to activate CTGF/ANGPT2. International Journal of Molecular Medicine, 42, 489–496. https://doi.org/10.3892/ijmm.2018.3595. 104. Devaux, Y., et al. (2013). A panel of 4 microRNAs facilitates the prediction of left ventricular contractility after acute myocardial infarction. PLoS ONE, 8, e70644. https://doi.org/10.1371/ journal.pone.0070644. 105. Takahashi, K., et al. (2016). Dysregulation of ossification-related miRNAs in circulating osteogenic progenitor cells obtained from patients with aortic stenosis. Clinical Science (Lond), 130, 1115–1124. https://doi.org/10.1042/CS20160094. 106. Chamorro-Jorganes, A., et al. (2011). MicroRNA-16 and microRNA-424 regulate cellautonomous angiogenic functions in endothelial cells via targeting vascular endothelial growth factor receptor-2 and fibroblast growth factor receptor-1. Arteriosclerosis, Thrombosis, and Vascular Biology, 31, 2595–2606. https://doi.org/10.1161/ATVBAHA.111.236521. 107. Bye, A., et al. (2016). Circulating microRNAs predict future fatal myocardial infarction in healthy individuals—The HUNT study. Journal of Molecular and Cellular Cardiology, 97, 162–168. https://doi.org/10.1016/j.yjmcc.2016.05.009.

108

5 Non-coding RNAs Related to Atherosclerosis

108. Shi, S., Jin, Y., Song, H., & Chen, X. (2019). MicroRNA-34a attenuates VEGF-mediated retinal angiogenesis via targeting Notch1. Biochemistry and Cell Biology, 97, 423–430. https:// doi.org/10.1139/bcb-2018-0304. 109. Li, J., et al. (2018). MicroRNA-34a promotes CMECs apoptosis and upregulate inflammatory cytokines, thus worsening CMECs damage and inhibiting angiogenesis by negatively targeting the Notch signaling pathway. Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb. 27433. 110. Arunachalam, G., Lakshmanan, A. P., Samuel, S. M., Triggle, C. R., & Ding, H. (2016). Molecular interplay between microRNA-34a and Sirtuin1 in hyperglycemia-mediated impaired angiogenesis in endothelial cells: Effects of metformin. Journal of Pharmacology and Experimental Therapeutics, 356, 314–323. https://doi.org/10.1124/jpet.115.226894. 111. Hourigan, S. T., et al. (2018). The regulation of miRNAs by reconstituted high-density lipoproteins in diabetes-impaired angiogenesis. Scientific Reports, 8, 13596. https://doi.org/10.1038/ s41598-018-32016-x. 112. Icli, B. et al. (2019). MicroRNA-615–5p regulates angiogenesis and tissue repair by targeting AKT/eNOS (Endothelial NO Synthase) signaling in endothelial cells. Arteriosclerosis, Thrombosis, and Vascular Biology, ATVBAHA119312726. doi:https://doi.org/10.1161/ATV BAHA.119.312726. 113. Leisegang, M. S., et al. (2017). Long noncoding RNA MANTIS facilitates endothelial angiogenic function. Circulation, 136, 65–79. https://doi.org/10.1161/CIRCULATIONAHA.116. 026991. 114. Basilio, J., et al. (2013). TNFalpha-induced down-regulation of Sox18 in endothelial cells is dependent on NF-kappaB. Biochemical and Biophysical Research Communications, 442, 221–226. https://doi.org/10.1016/j.bbrc.2013.11.030. 115. Gross, C. M., et al. (2014). Sox18 preserves the pulmonary endothelial barrier under conditions of increased shear stress. Journal of Cellular Physiology, 229, 1802–1816. https://doi.org/10. 1002/jcp.24633. 116. Fontijn, R. D., et al. (2014). Adipose tissue-derived stromal cells acquire endothelial-like features upon reprogramming with SOX18. Stem Cell Research, 13, 367–378. https://doi.org/ 10.1016/j.scr.2014.09.004. 117. Kuehbacher, A., Urbich, C., Zeiher, A. M., & Dimmeler, S. (2007). Role of Dicer and Drosha for endothelial microRNA expression and angiogenesis. Circulation Research, 101, 59–68. https://doi.org/10.1161/CIRCRESAHA.107.153916. 118. Ohtani, K., & Dimmeler, S. (2011). Control of cardiovascular differentiation by microRNAs. Basic Research in Cardiology, 106, 5–11. https://doi.org/10.1007/s00395-010-0139-7. 119. Chen, J., et al. (2015). MiR-17-5p as circulating biomarkers for the severity of coronary atherosclerosis in coronary artery disease. International Journal of Cardiology, 197, 123–124. https://doi.org/10.1016/j.ijcard.2015.06.037. 120. Jia, C., et al. (2014). Notoginsenoside R1 attenuates atherosclerotic lesions in ApoE deficient mouse model. PLoS ONE, 9, e99849. https://doi.org/10.1371/journal.pone.0099849. 121. Poitz, D. M., et al. (2013). Regulation of the Hif-system by micro-RNA 17 and 20a - role during monocyte-to-macrophage differentiation. Molecular Immunology, 56, 442–451. https://doi. org/10.1016/j.molimm.2013.06.014. 122. Hu, Y. W., et al. (2019). Long noncoding RNA NEXN-AS1 mitigates atherosclerosis by regulating the actin-binding protein NEXN. Journal of Clinical Investigation, 129, 1115– 1128. https://doi.org/10.1172/JCI98230. 123. Huang, T. S., et al. (2017). LINC00341 exerts an anti-inflammatory effect on endothelial cells by repressing VCAM1. Physiological Genomics, 49, 339–345. https://doi.org/10.1152/phy siolgenomics.00132.2016. 124. Yao, M. et al. (2020). Exosomal miR-21 secreted by IL-1beta-primed-mesenchymal stem cells induces macrophage M2 polarization and ameliorates sepsis. Life Science, 118658. doi:https:// doi.org/10.1016/j.lfs.2020.118658. 125. Nguyen, M. A., et al. (2018). Extracellular vesicles secreted by atherogenic macrophages transfer MicroRNA to inhibit cell migration. Arteriosclerosis, Thrombosis, and Vascular Biology, 38, 49–63. https://doi.org/10.1161/ATVBAHA.117.309795.

References

109

126. Nazari-Jahantigh, M., et al. (2012). MicroRNA-155 promotes atherosclerosis by repressing Bcl6 in macrophages. Journal of Clinical Investigation, 122, 4190–4202. https://doi.org/10. 1172/JCI61716. 127. Wang, Y., et al. (2017). MicroRNA-9 inhibits NLRP3 inflammasome activation in human atherosclerosis inflammation cell models through the JAK1/STAT signaling pathway. Cellular Physiology and Biochemistry, 41, 1555–1571. https://doi.org/10.1159/000470822. 128. Forrest, A. R., et al. (2010). Induction of microRNAs, mir-155, mir-222, mir-424 and mir503, promotes monocytic differentiation through combinatorial regulation. Leukemia, 24, 460–466. https://doi.org/10.1038/leu.2009.246. 129. Hu, J., Wu, H., Wang, D., Yang, Z., & Dong, J. (2018). LncRNA ANRIL promotes NLRP3 inflammasome activation in uric acid nephropathy through miR-122-5p/BRCC3 axis. Biochimie, 157, 102–110. https://doi.org/10.1016/j.biochi.2018.10.011. 130. Lu, L., et al. (2016). Time Series miRNA-mRNA integrated analysis reveals critical miRNAs and targets in macrophage polarization. Scientific Reports, 6, 37446. https://doi.org/10.1038/ srep37446. 131. Lin, Z., et al. (2017). Let-7e modulates the inflammatory response in vascular endothelial cells through ceRNA crosstalk. Scientific Reports, 7, 42498. https://doi.org/10.1038/srep42498. 132. Thulin, P., et al. (2013). MicroRNA-9 regulates the expression of peroxisome proliferatoractivated receptor delta in human monocytes during the inflammatory response. International Journal of Molecular Medicine, 31, 1003–1010. https://doi.org/10.3892/ijmm.2013.1311. 133. Wu, J., et al. (2019). Inhibition of P53/miR-34a improves diabetic endothelial dysfunction via activation of SIRT1. Journal of Cellular and Molecular Medicine, 23, 3538–3548. https:// doi.org/10.1111/jcmm.14253. 134. Wu, Y., Ye, J., Guo, R., Liang, X., & Yang, L. (2018). TRIF regulates BIC/miR-155 via the ERK signaling pathway to control the ox-LDL-induced macrophage inflammatory response. Journal of Immunology Research, 2018, 6249085. https://doi.org/10.1155/2018/6249085. 135. Liu, J., Huang, G. Q., & Ke, Z. P. (2019). Silence of long intergenic noncoding RNA HOTAIR ameliorates oxidative stress and inflammation response in ox-LDL-treated human macrophages by upregulating miR-330-5p. Journal of Cellular Physiology, 234, 5134–5142. https://doi.org/10.1002/jcp.27317. 136. Zhang, L., et al. (2018). TUG1 knockdown ameliorates atherosclerosis via up-regulating the expression of miR-133a target gene FGF1. Cardiovascular Pathology, 33, 6–15. https://doi. org/10.1016/j.carpath.2017.11.004. 137. Brennan, E., et al. (2017). Protective Effect of let-7 miRNA Family in Regulating Inflammation in Diabetes-Associated Atherosclerosis. Diabetes, 66, 2266–2277. https://doi.org/10.2337/ db16-1405. 138. Ye, J., et al. (2019). miR-221 Alleviates the Ox-LDL-Induced Macrophage Inflammatory Response via the Inhibition of DNMT3b-Mediated NCoR Promoter Methylation. Mediators of Inflammation, 2019, 4530534. https://doi.org/10.1155/2019/4530534. 139. Ortega, F. J., et al. (2013). Targeting the circulating microRNA signature of obesity. Clinical Chemistry, 59, 781–792. https://doi.org/10.1373/clinchem.2012.195776. 140. Wang, N., et al. (2012). Urinary microRNA-10a and microRNA-30d serve as novel, sensitive and specific biomarkers for kidney injury. PLoS ONE, 7, e51140. https://doi.org/10.1371/jou rnal.pone.0051140. 141. Marques-Rocha, J. L., et al. (2016). Expression of inflammation-related miRNAs in white blood cells from subjects with metabolic syndrome after 8 wk of following a Mediterranean diet-based weight loss program. Nutrition, 32, 48–55. https://doi.org/10.1016/j.nut. 2015.06.008. 142. Zhu, N., et al. (2011). Endothelial enriched microRNAs regulate angiotensin II-induced endothelial inflammation and migration. Atherosclerosis, 215, 286–293. https://doi.org/10. 1016/j.atherosclerosis.2010.12.024. 143. Fang, Y., Shi, C., Manduchi, E., Civelek, M., & Davies, P. F. (2010). MicroRNA-10a regulation of proinflammatory phenotype in athero-susceptible endothelium in vivo and in vitro. Proceedings of the National Academy of Sciences of United States of America, 107, 13450–13455. https://doi.org/10.1073/pnas.1002120107.

110

5 Non-coding RNAs Related to Atherosclerosis

144. Guo, H., et al. (2010). A functional varient in microRNA-146a is associated with risk of esophageal squamous cell carcinoma in Chinese Han. Familial Cancer, 9, 599–603. https:// doi.org/10.1007/s10689-010-9370-5. 145. Harris, T. A., Yamakuchi, M., Ferlito, M., Mendell, J. T., & Lowenstein, C. J. (2008). MicroRNA-126 regulates endothelial expression of vascular cell adhesion molecule 1. Proceedings of the National Academy of Sciences of United States of America, 105, 1516–1521. https://doi.org/10.1073/pnas.0707493105. 146. Nakamachi, Y., et al. (2009). MicroRNA-124a is a key regulator of proliferation and monocyte chemoattractant protein 1 secretion in fibroblast-like synoviocytes from patients with rheumatoid arthritis. Arthritis and Rheumatism, 60, 1294–1304. https://doi.org/10.1002/art. 24475. 147. Villeneuve, L. M., et al. (2010). Enhanced levels of microRNA-125b in vascular smooth muscle cells of diabetic db/db mice lead to increased inflammatory gene expression by targeting the histone methyltransferase Suv39h1. Diabetes, 59, 2904–2915. https://doi.org/ 10.2337/db10-0208. 148. Shaked, I., et al. (2009). MicroRNA-132 potentiates cholinergic anti-inflammatory signaling by targeting acetylcholinesterase. Immunity, 31, 965–973. https://doi.org/10.1016/j.immuni. 2009.09.019. 149. Pang, J. L., Wang, J. W., Hu, P. Y., Jiang, J. S., & Yu, C. (2018). HOTAIR alleviates oxLDL-induced inflammatory response in Raw264.7 cells via inhibiting NF-kappaB pathway. European Review for Medical and Pharmacological Sciences, 22, 6991–6998. doi:https://doi. org/10.26355/eurrev_201810_16170. 150. Manoharan, P., et al. (2014). Reduced levels of microRNAs miR-124a and miR-150 are associated with increased proinflammatory mediator expression in Kruppel-like factor 2 (KLF2)deficient macrophages. Journal of Biological Chemistry, 289, 31638–31646. https://doi.org/ 10.1074/jbc.M114.579763. 151. Chen, Q., et al. (2012). Inducible microRNA-223 down-regulation promotes TLR-triggered IL-6 and IL-1beta production in macrophages by targeting STAT3. PLoS ONE, 7, e42971. https://doi.org/10.1371/journal.pone.0042971. 152. Kim, G. D., Ng, H. P., Patel, N., & Mahabeleshwar, G. H. (2019). Kruppel-like factor 6 and miR-223 signaling axis regulates macrophage-mediated inflammation. The FASEB Journal, 33, 10902–10915. https://doi.org/10.1096/fj.201900867RR. 153. Tang, S. T., Wang, F., Shao, M., Wang, Y., & Zhu, H. Q. (2017). MicroRNA-126 suppresses inflammation in endothelial cells under hyperglycemic condition by targeting HMGB1. Vascular Pharmacology, 88, 48–55. https://doi.org/10.1016/j.vph.2016.12.002. 154. Li, H. Y., et al. (2016). Plasma MicroRNA-126-5p is associated with the complexity and severity of coronary artery disease in patients with stable angina pectoris. Cellular Physiology and Biochemistry, 39, 837–846. https://doi.org/10.1159/000447794. 155. Gast, M., et al. (2019). Immune system-mediated atherosclerosis caused by deficiency of long non-coding RNA MALAT1 in ApoE-/-mice. Cardiovascular Research, 115, 302–314. https:// doi.org/10.1093/cvr/cvy202. 156. Shen, Y., et al. (2017). miR-34a and miR-125b are upregulated in peripheral blood mononuclear cells from patients with type 2 diabetes mellitus. Experimental and Therapeutic Medicine, 14, 5589–5596. https://doi.org/10.3892/etm.2017.5254. 157. Banerjee, S., et al. (2013). miR-125a-5p regulates differential activation of macrophages and inflammation. Journal of Biological Chemistry, 288, 35428–35436. https://doi.org/10.1074/ jbc.M112.426866. 158. Li, D. B., et al. (2017). Plasma exosomal miR-422a and miR-125b-2-3p serve as biomarkers for ischemic stroke. Current Neurovascular Research, 14, 330–337. https://doi.org/10.2174/ 1567202614666171005153434. 159. Li, K., Ching, D., Luk, F. S., & Raffai, R. L. (2015). Apolipoprotein E enhances microRNA146a in monocytes and macrophages to suppress nuclear factor-kappaB-driven inflammation and atherosclerosis. Circulation Research, 117, e1–e11. https://doi.org/10.1161/CIRCRE SAHA.117.305844.

References

111

160. Yang, K., et al. (2011). MiR-146a inhibits oxidized low-density lipoprotein-induced lipid accumulation and inflammatory response via targeting toll-like receptor 4. FEBS Letters, 585, 854–860. https://doi.org/10.1016/j.febslet.2011.02.009. 161. Jiang, M., et al. (2012). Dysregulated expression of miR-146a contributes to age-related dysfunction of macrophages. Aging Cell, 11, 29–40. https://doi.org/10.1111/j.1474-9726. 2011.00757.x. 162. Su, Y., et al. (2019). MicroRNA-181a-5p and microRNA-181a-3p cooperatively restrict vascular inflammation and atherosclerosis. Cell Death Disease, 10, 365. https://doi.org/10. 1038/s41419-019-1599-9. 163. Li, Z., et al. (2016). Oxidized low-density lipoprotein upregulates microRNA-146a via JNK and NF-kappaB signaling. Molecular Medicine Reports, 13, 1709–1716. https://doi.org/10. 3892/mmr.2015.4729. 164. Wang, L., Xia, J. W., Ke, Z. P., & Zhang, B. H. (2019). Blockade of NEAT1 represses inflammation response and lipid uptake via modulating miR-342-3p in human macrophages THP-1 cells. Journal of Cellular Physiology, 234, 5319–5326. https://doi.org/10.1002/jcp. 27340. 165. D’Amore, S., et al. (2018). Identification of miR-9-5p as direct regulator of ABCA1 and HDLdriven reverse cholesterol transport in circulating CD14+ cells of patients with metabolic syndrome. Cardiovascular Research, 114, 1154–1164. https://doi.org/10.1093/cvr/cvy077. 166. Wang, D., et al. (2014). Coenzyme Q10 promotes macrophage cholesterol efflux by regulation of the activator protein-1/miR-378/ATP-binding cassette transporter G1-signaling pathway. Arteriosclerosis, Thrombosis, and Vascular Biology, 34, 1860–1870. https://doi.org/10.1161/ ATVBAHA.113.302879. 167. Tang, X., et al. (2020). LncRNA ZFAS1 confers inflammatory responses and reduces cholesterol efflux in atherosclerosis through regulating miR-654-3p-ADAM10/RAB22A axis. International Journal of Cardiology. https://doi.org/10.1016/j.ijcard.2020.03.056. 168. Huang, C., et al. (2016). Long Noncoding RNA HOXC-AS1 Suppresses Ox-LDL-Induced Cholesterol Accumulation Through Promoting HOXC6 Expression in THP-1 Macrophages. DNA and Cell Biology, 35, 722–729. https://doi.org/10.1089/dna.2016.3422. 169. Martino, F., et al. (2015). Circulating miR-33a and miR-33b are up-regulated in familial hypercholesterolaemia in paediatric age. Clin Sci (Lond), 129, 963–972. https://doi.org/10. 1042/CS20150235. 170. Rayner, K. J., et al. (2010). MiR-33 contributes to the regulation of cholesterol homeostasis. Science, 328, 1570–1573. https://doi.org/10.1126/science.1189862. 171. Wang, Y. S., et al. (2017). Let-7g suppresses both canonical and non-canonical NF-kappaB pathways in macrophages leading to anti-atherosclerosis. Oncotarget, 8, 101026–101041. https://doi.org/10.18632/oncotarget.18197. 172. Li, H., et al. (2019). Long non-coding RNA CDKN2B-AS1 reduces inflammatory response and promotes cholesterol efflux in atherosclerosis by inhibiting ADAM10 expression. Aging (Albany NY), 11, 1695–1715. https://doi.org/10.18632/aging.101863. 173. Witkowski, M., et al. (2020). Vascular miR-181b controls tissue factor-dependent thrombogenicity and inflammation in type 2 diabetes. Cardiovascular Diabetology, 19, 20. https://doi. org/10.1186/s12933-020-0993-z. 174. Frostegard, J., Zhang, Y., Sun, J., Yan, K., & Liu, A. (2016). Oxidized Low-Density Lipoprotein (OxLDL)-treated dendritic cells promote activation of t cells in human atherosclerotic plaque and blood, which is repressed by statins: microRNA let-7c Is Integral to the Effect. Journal of the American Heart Association, 5. doi:https://doi.org/10.1161/JAHA.116.003976. 175. Fontana, L., et al. (2007). MicroRNAs 17–5p-20a-106a control monocytopoiesis through AML1 targeting and M-CSF receptor upregulation. Nature Cell Biology, 9, 775–787. https:// doi.org/10.1038/ncb1613. 176. Riepsaame, J., et al. (2013). MicroRNA-mediated down-regulation of M-CSF Receptor contributes to maturation of mouse monocyte-derived dendritic cells. Front Immunology, 4, 353. https://doi.org/10.3389/fimmu.2013.00353.

112

5 Non-coding RNAs Related to Atherosclerosis

177. Alexander, M., et al. (2015). Exosome-delivered microRNAs modulate the inflammatory response to endotoxin. Nature Communications, 6, 7321. https://doi.org/10.1038/ncomms 8321. 178. Wu, J., et al. (2018). The long noncoding RNA MALAT1 induces tolerogenic Dendritic cells and regulatory T cells via miR155/dendritic cell-specific intercellular adhesion molecule-3 grabbing Nonintegrin/IL10 Axis. Front Immunology, 9, 1847. https://doi.org/10.3389/fimmu. 2018.01847. 179. Li, S., et al. (2015). MicroRNA-21 negatively regulates Treg cells through a TGF-beta1/Smadindependent pathway in patients with coronary heart disease. Cellular Physiology and Biochemistry, 37, 866–878. https://doi.org/10.1159/000430214. 180. Ouimet, M., et al. (2015). MicroRNA-33-dependent regulation of macrophage metabolism directs immune cell polarization in atherosclerosis. Journal of Clinical Investigation, 125, 4334–4348. https://doi.org/10.1172/JCI81676. 181. Huang, S., et al. (2019). NEAT1 regulates Th2 cell development by targeting STAT6 for degradation. Cell Cycle, 18, 312–319. https://doi.org/10.1080/15384101.2018.1562285. 182. Guo, M., et al. (2010). miR-146a in PBMCs modulates Th1 function in patients with acute coronary syndrome. Immunology and Cell Biology, 88, 555–564. https://doi.org/10.1038/icb. 2010.16. 183. Chen, Y. et al. (2016). MicroRNA-146a-5p negatively regulates pro-inflammatory cytokine secretion and cell activation in lipopolysaccharide stimulated human hepatic stellate cells through inhibition of toll-like receptor 4 signaling pathways. International Journal of Molecular Sciences, 17. doi:https://doi.org/10.3390/ijms17071076. 184. Yao, R., et al. (2011). The altered expression of inflammation-related microRNAs with microRNA-155 expression correlates with Th17 differentiation in patients with acute coronary syndrome. Cellular & Molecular Immunology, 8, 486–495. https://doi.org/10.1038/cmi. 2011.22. 185. Li, B., et al. (2017). miR-146a modulates autoreactive Th17 cell differentiation and regulates organ-specific autoimmunity. Journal of Clinical Investigation, 127, 3702–3716. https://doi. org/10.1172/JCI94012. 186. Escobar, T. M., et al. (2014). miR-155 activates cytokine gene expression in Th17 cells by regulating the DNA-binding protein Jarid2 to relieve polycomb-mediated repression. Immunity, 40, 865–879. https://doi.org/10.1016/j.immuni.2014.03.014. 187. Hansson, G. K., Libby, P., & Tabas, I. (2015). Inflammation and plaque vulnerability. Journal of Internal Medicine, 278, 483–493. https://doi.org/10.1111/joim.12406. 188. Chen, J., & Dang, J. (2020). LncRNA CASC11 was downregulated in coronary artery disease and inhibits transforming growth factor-beta1. Journal of International Medical Research, 48, 300060519889187. https://doi.org/10.1177/0300060519889187. 189. Tao, K., Hu, Z., Zhang, Y., Jiang, D., & Cheng, H. (2019). LncRNA CASC11 improves atherosclerosis by downregulating IL-9 and regulating vascular smooth muscle cell apoptosis and proliferation. Bioscience, Biotechnology, and Biochemistry, 83, 1284–1288. https://doi. org/10.1080/09168451.2019.1597621. 190. Tung, S. L., et al. (2018). Regulatory T cell-derived extracellular vesicles modify dendritic cell function. Scientific Reports, 8, 6065. https://doi.org/10.1038/s41598-018-24531-8. 191. Kerr, J. F., Wyllie, A. H., & Currie, A. R. (1972). Apoptosis: A basic biological phenomenon with wide-ranging implications in tissue kinetics. British Journal of Cancer, 26, 239–257. 192. Sato, K. et al. (2017). Potent vasoconstrictor kisspeptin-10 induces atherosclerotic plaque progression and instability: reversal by its receptor GPR54 antagonist. Journal of the American Heart Association, 6. doi:https://doi.org/10.1161/JAHA.117.005790. 193. Plutzky, J. (1999). Atherosclerotic plaque rupture: Emerging insights and opportunities. American Journal of Cardiology, 84, 15J-20J. 194. Raitoharju, E., et al. (2011). miR-21, miR-210, miR-34a, and miR-146a/b are up-regulated in human atherosclerotic plaques in the Tampere Vascular Study. Atherosclerosis, 219, 211–217. https://doi.org/10.1016/j.atherosclerosis.2011.07.020.

References

113

195. Su, G., Sun, G., Liu, H., Shu, L., & Liang, Z. (2018). Downregulation of miR-34a promotes endothelial cell growth and suppresses apoptosis in atherosclerosis by regulating Bcl-2. Heart and Vessels, 33, 1185–1194. https://doi.org/10.1007/s00380-018-1169-6. 196. de Ronde, M. W. J. et al. (2017). High miR-124–3p expression identifies smoking individuals susceptible to atherosclerosis. Atherosclerosis, 263, 377–384. doi:https://doi.org/10.1016/j. atherosclerosis.2017.03.045. 197. Zheng, B., et al. (2017). Exosome-mediated miR-155 transfer from smooth muscle cells to endothelial cells induces endothelial injury and promotes atherosclerosis. Molecular Therapy, 25, 1279–1294. https://doi.org/10.1016/j.ymthe.2017.03.031. 198. Chen, L., et al. (2017). Exosomal lncRNA GAS5 regulates the apoptosis of macrophages and vascular endothelial cells in atherosclerosis. PLoS ONE, 12, e0185406. https://doi.org/ 10.1371/journal.pone.0185406. 199. Chen, C., et al. (2016). Tanshinol suppresses endothelial cells apoptosis in mice with atherosclerosis via lncRNA TUG1 up-regulating the expression of miR-26a. American Journal of Translational Research, 8, 2981–2991. 200. Zhang, Y., et al. (2015). MicroRNA-26a prevents endothelial cell apoptosis by directly targeting TRPC6 in the setting of atherosclerosis. Scientific Reports, 5, 9401. https://doi. org/10.1038/srep09401. 201. Feldman, A., et al. (2017). Analysis of circulating miR-1, miR-23a, and miR-26a in atrial fibrillation patients undergoing coronary bypass artery grafting surgery. Annals of Human Genetics, 81, 99–105. https://doi.org/10.1111/ahg.12188. 202. Li, D., et al. (2010). MicroRNA-125a/b-5p inhibits endothelin-1 expression in vascular endothelial cells. Journal of Hypertension, 28, 1646–1654. https://doi.org/10.1097/HJH.0b0 13e32833a4922. 203. Martin, M. M., et al. (2007). The human angiotensin II type 1 receptor +1166 A/C polymorphism attenuates microRNA-155 binding. Journal of Biological Chemistry, 282, 24262–24269. https://doi.org/10.1074/jbc.M701050200. 204. Zernecke, A. et al. (2009). Delivery of microRNA-126 by apoptotic bodies induces CXCL12dependent vascular protection. Science Signaling, 2, ra81. doi:https://doi.org/10.1126/scisig nal.2000610. 205. Hijmans, J. G., et al. (2018). Association between hypertension and circulating vascularrelated microRNAs. Journal of Human Hypertension. https://doi.org/10.1038/s41371-0180061-2. 206. Cengiz, M., et al. (2015). Circulating miR-21 and eNOS in subclinical atherosclerosis in patients with hypertension. Clinical and Experimental Hypertension, 37, 643–649. https:// doi.org/10.3109/10641963.2015.1036064. 207. Weber, M., Baker, M. B., Moore, J. P., & Searles, C. D. (2010). MiR-21 is induced in endothelial cells by shear stress and modulates apoptosis and eNOS activity. Biochemical and Biophysical Research Communications, 393, 643–648. https://doi.org/10.1016/j.bbrc. 2010.02.045. 208. Sheedy, F. J., et al. (2010). Negative regulation of TLR4 via targeting of the proinflammatory tumor suppressor PDCD4 by the microRNA miR-21. Nature Immunology, 11, 141–147. https://doi.org/10.1038/ni.1828. 209. Lin, Y., et al. (2009). Involvement of MicroRNAs in hydrogen peroxide-mediated gene regulation and cellular injury response in vascular smooth muscle cells. Journal of Biological Chemistry, 284, 7903–7913. https://doi.org/10.1074/jbc.M806920200. 210. Loffler, D., et al. (2007). Interleukin-6 dependent survival of multiple myeloma cells involves the Stat3-mediated induction of microRNA-21 through a highly conserved enhancer. Blood, 110, 1330–1333. https://doi.org/10.1182/blood-2007-03-081133. 211. Zhong, X., et al. (2017). MIAT promotes proliferation and hinders apoptosis by modulating miR-181b/STAT3 axis in ox-LDL-induced atherosclerosis cell models. Biomedicine & Pharmacotherapy, 97, 1078–1085. https://doi.org/10.1016/j.biopha.2017.11.052. 212. Ghorbani, S., et al. (2017). miR-181 interacts with signaling adaptor molecule DENN/MADD and enhances TNF-induced cell death. PLoS ONE, 12, e0174368. https://doi.org/10.1371/jou rnal.pone.0174368.

114

5 Non-coding RNAs Related to Atherosclerosis

213. Gong, F. H., et al. (2018). Reduced atherosclerosis lesion size, inflammatory response in miR150 knockout mice via macrophage effects. Journal of Lipid Research, 59, 658–669. https:// doi.org/10.1194/jlr.M082651. 214. Qin, B., et al. (2017). MicroRNA-150 targets ELK1 and modulates the apoptosis induced by ox-LDL in endothelial cells. Molecular and Cellular Biochemistry, 429, 45–58. https://doi. org/10.1007/s11010-016-2935-3. 215. Yan, B., et al. (2015). lncRNA-MIAT regulates microvascular dysfunction by functioning as a competing endogenous RNA. Circulation Research, 116, 1143–1156. https://doi.org/10. 1161/CIRCRESAHA.116.305510. 216. Hellstrom, M., Kalen, M., Lindahl, P., Abramsson, A., & Betsholtz, C. (1999). Role of PDGFB and PDGFR-beta in recruitment of vascular smooth muscle cells and pericytes during embryonic blood vessel formation in the mouse. Development, 126, 3047–3055. 217. Grant, M. B. et al. (1994). Localization of insulin-like growth factor I and inhibition of coronary smooth muscle cell growth by somatostatin analogues in human coronary smooth muscle cells. A potential treatment for restenosis? Circulation, 89, 1511–1517. 218. Guo, X., & Chen, S. Y. (2012). Transforming growth factor-beta and smooth muscle differentiation. World Journal of Biological Chemistry, 3, 41–52. https://doi.org/10.4331/wjbc.v3. i3.41. 219. Xie, W. B., et al. (2013). Smad2 and myocardin-related transcription factor B cooperatively regulate vascular smooth muscle differentiation from neural crest cells. Circulation Research, 113, e76-86. https://doi.org/10.1161/CIRCRESAHA.113.301921. 220. Cucoranu, I., et al. (2005). NAD(P)H oxidase 4 mediates transforming growth factor-beta1induced differentiation of cardiac fibroblasts into myofibroblasts. Circulation Research, 97, 900–907. https://doi.org/10.1161/01.RES.0000187457.24338.3D. 221. Roostalu, U., et al. (2018). Distinct Cellular Mechanisms Underlie Smooth Muscle Turnover in Vascular Development and Repair. Circulation Research, 122, 267–281. https://doi.org/10. 1161/CIRCRESAHA.117.312111. 222. Raines, E. W. (2000). The extracellular matrix can regulate vascular cell migration, proliferation, and survival: Relationships to vascular disease. International Journal of Experimental Pathology, 81, 173–182. 223. Orr, A. W., et al. (2009). Molecular mechanisms of collagen isotype-specific modulation of smooth muscle cell phenotype. Arteriosclerosis, Thrombosis, and Vascular Biology, 29, 225–231. https://doi.org/10.1161/ATVBAHA.108.178749. 224. Lim, S., & Park, S. (2014). Role of vascular smooth muscle cell in the inflammation of atherosclerosis. BMB Reports, 47, 1–7. 225. Chen, D., et al. (2015). Expression of human tissue factor pathway inhibitor on vascular smooth muscle cells inhibits secretion of macrophage migration inhibitory factor and attenuates atherosclerosis in ApoE-/- mice. Circulation, 131, 1350–1360. https://doi.org/10.1161/ CIRCULATIONAHA.114.013423. 226. Fan, Y., et al. (2017). Macrophage migration inhibitory factor triggers vascular smooth muscle cell dedifferentiation by a p68-serum response factor axis. Cardiovascular Research, 113, 519–530. https://doi.org/10.1093/cvr/cvx025. 227. Shankman, L. S., et al. (2015). KLF4-dependent phenotypic modulation of smooth muscle cells has a key role in atherosclerotic plaque pathogenesis. Nature Medicine, 21, 628–637. https://doi.org/10.1038/nm.3866. 228. Schrijvers, D. M., De Meyer, G. R., Kockx, M. M., Herman, A. G., & Martinet, W. (2005). Phagocytosis of apoptotic cells by macrophages is impaired in atherosclerosis. Arteriosclerosis, Thrombosis, and Vascular Biology, 25, 1256–1261. https://doi.org/10.1161/01.ATV.000 0166517.18801.a7. 229. Bennett, M. R., Macdonald, K., Chan, S. W., Boyle, J. J., & Weissberg, P. L. (1998). Cooperative interactions between RB and p53 regulate cell proliferation, cell senescence, and apoptosis in human vascular smooth muscle cells from atherosclerotic plaques. Circulation Research, 82, 704–712.

References

115

230. Kockx, M. M. (1998). Apoptosis in the atherosclerotic plaque: Quantitative and qualitative aspects. Arteriosclerosis, Thrombosis, and Vascular Biology, 18, 1519–1522. 231. Clarke, M. C., et al. (2006). Apoptosis of vascular smooth muscle cells induces features of plaque vulnerability in atherosclerosis. Nature Medicine, 12, 1075–1080. https://doi.org/10. 1038/nm1459. 232. Grootaert, M. O. J., et al. (2018). Vascular smooth muscle cell death, autophagy and senescence in atherosclerosis. Cardiovascular Research, 114, 622–634. https://doi.org/10.1093/ cvr/cvy007. 233. Mei, Y., Thompson, M. D., Cohen, R. A., & Tong, X. (1852). Autophagy and oxidative stress in cardiovascular diseases. Biochimica Et Biophysica Acta, 243–251, 2015. https://doi.org/ 10.1016/j.bbadis.2014.05.005. 234. Yang, X., et al. (2017). Oxidative stress-mediated atherosclerosis: Mechanisms and therapies. Frontiers in Physiology, 8, 600. https://doi.org/10.3389/fphys.2017.00600. 235. Levine, B., & Yuan, J. (2005). Autophagy in cell death: An innocent convict? Journal of Clinical Investigation, 115, 2679–2688. https://doi.org/10.1172/JCI26390. 236. Martinet, W., & De Meyer, G. R. (2009). Autophagy in atherosclerosis: A cell survival and death phenomenon with therapeutic potential. Circulation Research, 104, 304–317. https:// doi.org/10.1161/CIRCRESAHA.108.188318. 237. Clarke, M. C., et al. (2008). Chronic apoptosis of vascular smooth muscle cells accelerates atherosclerosis and promotes calcification and medial degeneration. Circulation Research, 102, 1529–1538. https://doi.org/10.1161/CIRCRESAHA.108.175976. 238. Nakahara, T., et al. (2017). Coronary artery calcification: from mechanism to molecular imaging. JACC Cardiovasc Imaging, 10, 582–593. https://doi.org/10.1016/j.jcmg.2017. 03.005. 239. Otsuka, F., Sakakura, K., Yahagi, K., Joner, M., & Virmani, R. (2014). Has our understanding of calcification in human coronary atherosclerosis progressed? Arteriosclerosis, Thrombosis, and Vascular Biology, 34, 724–736. https://doi.org/10.1161/ATVBAHA.113.302642. 240. van den Bouwhuijsen, Q. J. et al. (2015). Coexistence of calcification, intraplaque hemorrhage and lipid core within the asymptomatic atherosclerotic carotid plaque: the rotterdam study. Cerebrovascular Diseases, 39, 319−324. doi:https://doi.org/10.1159/000381138. 241. Baek, J. H., et al. (2017). The protective effect of middle cerebral artery calcification on symptomatic middle cerebral artery infarction. Stroke, 48, 3138–3141. https://doi.org/10.1161/STR OKEAHA.117.017821. 242. Hutcheson, J. D., Maldonado, N., & Aikawa, E. (2014). Small entities with large impact: Microcalcifications and atherosclerotic plaque vulnerability. Current Opinion in Lipidology, 25, 327–332. https://doi.org/10.1097/MOL.0000000000000105. 243. Bischetti, S., et al. (2017). Carotid plaque instability is not related to quantity but to elemental composition of calcification. Nutrition, Metabolism and Cardiovascular Diseases, 27, 768– 774. https://doi.org/10.1016/j.numecd.2017.05.006. 244. Fulzele, S., et al. (2019). Muscle-derived miR-34a increases with age in circulating extracellular vesicles and induces senescence of bone marrow stem cells. Aging (Albany NY), 11, 1791–1803. https://doi.org/10.18632/aging.101874. 245. Climent, M. et al. (2015). TGFbeta Triggers miR-143/145 transfer from smooth muscle cells to endothelial cells, Thereby modulating vessel stabilization. Circulation Reseac, 116, 1753−1764. doi:https://doi.org/10.1161/CIRCRESAHA.116.305178. 246. Wang, Y. N., et al. (2016). Long Noncoding RNA-GAS5: A novel regulator of hypertensioninduced vascular remodeling. Hypertension, 68, 736–748. https://doi.org/10.1161/HYPERT ENSIONAHA.116.07259. 247. Elia, L., et al. (2009). The knockout of miR-143 and -145 alters smooth muscle cell maintenance and vascular homeostasis in mice: Correlates with human disease. Cell Death and Differentiation, 16, 1590–1598. https://doi.org/10.1038/cdd.2009.153. 248. Cordes, K. R., et al. (2009). miR-145 and miR-143 regulate smooth muscle cell fate and plasticity. Nature, 460, 705–710. https://doi.org/10.1038/nature08195.

116

5 Non-coding RNAs Related to Atherosclerosis

249. Liu, K., et al. (2017). Expression levels of atherosclerosis-associated miR-143 and miR-145 in the plasma of patients with hyperhomocysteinaemia. BMC Cardiovascular Disorders, 17, 163. https://doi.org/10.1186/s12872-017-0596-0. 250. de Gonzalo-Calvo, D., Cenarro, A., Civeira, F., & Llorente-Cortes, V. microRNA expression profile in human coronary smooth muscle cell-derived microparticles is a source of biomarkers. Clin Investig Arterioscler, 28, 167–177. doi:https://doi.org/10.1016/j.arteri.2016. 05.005. 251. Kumar, S., Kim, C. W., Simmons, R. D., & Jo, H. (2014). Role of flow-sensitive microRNAs in endothelial dysfunction and atherosclerosis: Mechanosensitive athero-miRs. Arteriosclerosis, Thrombosis, and Vascular Biology, 34, 2206–2216. https://doi.org/10.1161/ATVBAHA.114. 303425. 252. Ji, R., et al. (2007). MicroRNA expression signature and antisense-mediated depletion reveal an essential role of MicroRNA in vascular neointimal lesion formation. Circulation Research, 100, 1579–1588. https://doi.org/10.1161/CIRCRESAHA.106.141986. 253. Olivieri, F., et al. (2015). MiR-21-5p and miR-126a-3p levels in plasma and circulating angiogenic cells: Relationship with type 2 diabetes complications. Oncotarget, 6, 35372–35382. https://doi.org/10.18632/oncotarget.6164. 254. Wang, J., et al. (2019). MicroRNA-92a promotes vascular smooth muscle cell proliferation and migration through the ROCK/MLCK signalling pathway. Journal of Cellular and Molecular Medicine, 23, 3696–3710. https://doi.org/10.1111/jcmm.14274. 255. Liu, S., et al. (2019). Corrigendum: MiR-378a-5p regulates proliferation and migration in vascular smooth muscle cell by targeting CDK1. Front Genet, 10, 193. https://doi.org/10. 3389/fgene.2019.00193. 256. Liu, S., et al. (2019). MiR-378a-5p regulates proliferation and migration in vascular smooth muscle cell by targeting CDK1. Front Genet, 10, 22. https://doi.org/10.3389/fgene.2019. 00022. 257. Tian, S., et al. (2018). LncRNA UCA1 sponges miR-26a to regulate the migration and proliferation of vascular smooth muscle cells. Gene, 673, 159–166. https://doi.org/10.1016/j.gene. 2018.06.031. 258. Chen, J., Cui, L., Yuan, J., Zhang, Y., & Sang, H. (2017). Circular RNA WDR77 target FGF-2 to regulate vascular smooth muscle cells proliferation and migration by sponging miR-124. Biochemical and Biophysical Research Communications, 494, 126–132. https://doi.org/10. 1016/j.bbrc.2017.10.068. 259. Liu, X., Ma, B. D., Liu, S., Liu, J., & Ma, B. X. (2019). Long noncoding RNA LINC00341 promotes the vascular smooth muscle cells proliferation and migration via miR-214/FOXO4 feedback loop. American Journal of Translational Research, 11, 1835–1842. 260. Yang, L., Yang, F., Zhao, H., Wang, M., & Zhang, Y. (2019). Circular RNA circCHFR facilitates the proliferation and migration of vascular smooth muscle via miR-370/FOXO1/Cyclin D1 pathway. Molecular Therapy Nucleic Acids, 16, 434–441. https://doi.org/10.1016/j.omtn. 2019.02.028. 261. Zhang, L., Zhou, C., Qin, Q., Liu, Z., & Li, P. (2019). LncRNA LEF1-AS1 regulates the migration and proliferation of vascular smooth muscle cells by targeting miR-544a/PTEN axis. Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb.28728. 262. Li, P., et al. (2013). MicroRNA-638 is highly expressed in human vascular smooth muscle cells and inhibits PDGF-BB-induced cell proliferation and migration through targeting orphan nuclear receptor NOR1. Cardiovascular Research, 99, 185–193. https://doi.org/10.1093/cvr/ cvt082. 263. Li, P., et al. (2013). MicroRNA-663 regulates human vascular smooth muscle cell phenotypic switch and vascular neointimal formation. Circulation Research, 113, 1117–1127. https://doi. org/10.1161/CIRCRESAHA.113.301306. 264. Merlet, E., et al. (2013). miR-424/322 regulates vascular smooth muscle cell phenotype and neointimal formation in the rat. Cardiovascular Research, 98, 458–468. https://doi.org/10. 1093/cvr/cvt045.

References

117

265. Becker, S., et al. (2016). Identification of cardiomyopathy associated circulating miRNA biomarkers in patients with muscular dystrophy using a complementary cardiovascular magnetic resonance and plasma profiling approach. Journal of Cardiovascular Magnetic Resonance, 18, 25. https://doi.org/10.1186/s12968-016-0244-3. 266. Leeper, N. J., et al. (2011). MicroRNA-26a is a novel regulator of vascular smooth muscle cell function. Journal of Cellular Physiology, 226, 1035–1043. https://doi.org/10.1002/jcp. 22422. 267. Liu, X., et al. (2009). A necessary role of miR-221 and miR-222 in vascular smooth muscle cell proliferation and neointimal hyperplasia. Circulation Research, 104, 476–487. https:// doi.org/10.1161/CIRCRESAHA.108.185363. 268. Choi, S., et al. (2018). TNF-alpha elicits phenotypic and functional alterations of vascular smooth muscle cells by miR-155-5p-dependent down-regulation of cGMP-dependent kinase 1. Journal of Biological Chemistry, 293, 14812–14822. https://doi.org/10.1074/jbc.RA118. 004220. 269. Mackenzie, N. C., Staines, K. A., Zhu, D., Genever, P., & Macrae, V. E. (2014). miRNA-221 and miRNA-222 synergistically function to promote vascular calcification. Cell Biochemistry and Function, 32, 209–216. https://doi.org/10.1002/cbf.3005. 270. Liu, X., Cheng, Y., Yang, J., Xu, L., & Zhang, C. (2012). Cell-specific effects of miR-221/222 in vessels: Molecular mechanism and therapeutic application. Journal of Molecular and Cellular Cardiology, 52, 245–255. https://doi.org/10.1016/j.yjmcc.2011.11.008. 271. Chen, W., et al. (2018). MicroRNA-124-3p inhibits collagen synthesis in atherosclerotic plaques by targeting prolyl 4-hydroxylase subunit alpha-1 (P4HA1) in vascular smooth muscle cells. Atherosclerosis, 277, 98–107. https://doi.org/10.1016/j.atherosclerosis.2018.08.034. 272. Lovren, F., et al. (2012). MicroRNA-145 targeted therapy reduces atherosclerosis. Circulation, 126, S81-90. https://doi.org/10.1161/CIRCULATIONAHA.111.084186. 273. Vengrenyuk, Y., et al. (2015). Cholesterol loading reprograms the microRNA-143/145myocardin axis to convert aortic smooth muscle cells to a dysfunctional macrophage-like phenotype. Arteriosclerosis, Thrombosis, and Vascular Biology, 35, 535–546. https://doi.org/ 10.1161/ATVBAHA.114.304029. 274. Guo, W., et al. (2019). IgE Aggravates the senescence of smooth muscle cells in abdominal aortic aneurysm by upregulating LincRNA-p21. Aging Dis, 10, 699–710. https://doi.org/10. 14336/AD.2018.1128. 275. Zhang, Z., et al. (2019). Knockdown of lncRNA PVT1 inhibits vascular smooth muscle cell apoptosis and extracellular matrix disruption in a murine abdominal aortic aneurysm model. Molecules and Cells, 42, 218–227. https://doi.org/10.14348/molcells.2018.0162. 276. Zhang, B., et al. (2019). MicroRNA-25 Protects Smooth Muscle Cells against CorticosteroneInduced Apoptosis. Oxidative Medicine and Cellular Longevity, 2019, 2691514. https://doi. org/10.1155/2019/2691514. 277. Tan, P., et al. (2019). LncRNA-ANRIL inhibits cell senescence of vascular smooth muscle cells by regulating miR-181a/Sirt1. Biochemistry and Cell Biology, 97, 571–580. https://doi. org/10.1139/bcb-2018-0126. 278. Arslan, S., et al. (2017). Long non-coding RNAs in the atherosclerotic plaque. Atherosclerosis, 266, 176–181. https://doi.org/10.1016/j.atherosclerosis.2017.10.012. 279. Ulrich, V., et al. (2016). Chronic miR-29 antagonism promotes favorable plaque remodeling in atherosclerotic mice. EMBO Molecular Medicine, 8, 643–653. https://doi.org/10.15252/ emmm.201506031.

Chapter 6

Non-coding RNAs in Cardiomyopathy and Heart Failure

Abstract Cardiac hypertrophy is the thickening of the myocardium, particularly the left ventricle. Cardiac hypertrophy may occur physiologically because of athletic training and is usually a uniform increase in ventricular wall thickness. At the early stage of pathological hypertrophy, the increased size of cardiomyocytes is initially a compensatory mechanism. However, sustained hypertrophy may lead to maladaptive cardiac remodeling, including fibrosis, inflammation, and cell death. This remodeling increases the risk for dilated cardiomyopathy, arrhythmia, heart failure, and even sudden death. Imbalance in let-7, miR-1, miR-7, miR-9, miR-17-92, miR18, miR-21, miR-22, miR-25, miR-26a, miR-29, miR-30a, miR-31, miR-33, miR34a, miR-92, miR-98, miR-101a, miR-106a, miR-124, miR-125, miR-130, miR133, miR-143-145, miR-146a, miR-150, miR-155, miR-181, miR-199, miR-208, miR-214, miR-221-222, miR-223, miR-433, miR-455 and miR-489, and lncRNAs CHFR, HOTAIR, H19, LINC-ROR, MALAT1, MEG3, MIAT, MIRT1, NEAT1, TINCR, TUG1, UCA1, XIST and WISPER, and circ-RNAs ANRIL are associated with cardiomyopathy. The let-7 family and miR-1, miR-7, miR-9, miR-17, miR-21, miR-26a/b, miR-29, miR-30a, miR-34a, miR-124, miR-130, miR-133, miR-143145, miR-146a, miR-150, miR-155, miR-181 family, miR-221-222, miR-223, miR378 and miR-455, and lncRNAs GAS5, HOTAIR, H19, lincRNA-p21, LINC-ROR, MALAT1, MEG3, MIAT, NEAT1, TUG1 and UCA1, and circ-RNAs ANRIL and PVT1 link metabolic to cardiovascular diseases.

6.1 Mechanisms in Cardiomyopathy and Heart Failure A third of the cells in the heart are cardiomyocytes (CMs). The heart also contains stem cells, endothelial cells (ECs), immune-system-related macrophages, T cells, fibroblasts (FBs), smooth muscle cells (SMCs), and sympathetic and parasympathetic neuronal cells. A tight balance between these cell types is needed to maintain the integrity of the heart [1]. Pathological stimuli such as aging, myocardial injury, pressure overload, volume overload, neurohormonal activation, and inflammation cause cardiac remodeling [2, 3] (Fig. 6.1).

Illustrations by Pieterjan Ginckels, Faculty of Architecture, KU Leuven, Ghent, Belgium. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 P. Holvoet, Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer, https://doi.org/10.1007/978-3-030-68844-8_6

119

120

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

Fig. 6.1 Non-coding RNAs and cardiometabolic risk components in the development of cardiomyopathy. Silencing of miR-1 and miR-133 impairs the differentiation of stem cells to CMs. M1 macrophages secrete ANG II, IGF1, IL6, IFN-γ, PDGF, and VEGF, which induce CMs to undergo hypertrophy, involving Ras/STAT3 signaling. High levels of let-7, miR-9, miR-21, miR-25, repressing MALAT1, miR-29, miR-106a, miR-146a, miR-208, miR-223, and NEAT1, silencing miR-378, induce cardiac hypertrophy. Low levels of miR-1, sponged by UCA1, miR92b-3p, miR-98, miR-133, sponged by LINC-ROR and XIST, miR-150, silenced by MIAT, and miR-199 exacerbate hypertrophy. MiR-26a, miR-214-3p, increased by a decrease of TINCR, and a decrease of let-7, silenced by H19, and miR-489 silenced by lncRNA CHFR may prevent hypertrophy. Inflammatory molecules secreted by M1 macrophages also induce activation of fibroblasts and fibrosis involving TGF-β/SMAD/Wnt signaling. Increased let-7, miR-9, miR-17, miR-21, miR25, miR-29, miR-31, miR-34a, miR-125 due to decreased MEG3, miR-130, miR-146a, miR-155, miR-433, H19, silencing miR-455, TUG1, silencing miR-29c, and WISPER are associated with cardiac fibrosis. The decrease of miR-1, miR-18a, miR-24 silenced by MIAT, miR-30a silenced by MALAT1, miR-101a, and miR-133, silenced by LINC-ROR, exacerbates fibrosis. The increase of miR-221-222 and miR-378 and the decrease of miR-223 may block fibrosis. ANG II, IGF1, TGF-β, and TNF-α secreted by M1 macrophages induce ECM remodeling and wound repair associated with increased collagen, elastin, and fibrillin. High levels of miR-17, miR-146a, miR-155, and WISPER, and low levels of miR-1, miR-24, silenced by MIAT, miR-101a, and miR-133 are associated with increased ECM deposition. MiR-26a may prevent this. Wound repair is associated with monocytes’ infiltration, induced by the decrease of miR-150. Monocytes may differentiate

6.1 Mechanisms in Cardiomyopathy and Heart Failure

121

 into fibroblasts, induced by miR-21, thereby augmenting fibrosis. Monocytes also differentiate into M1 macrophages. This differentiation depends on the interaction between let-7, miR-146a, H19, and MALAT1. Increased miR-155, miR-223, and MIRT1, and decreased miR-30a and miR-133 are associated with M1 macrophage polarization and inflammation. MiR-21, miR-29, miR-181, and the decrease of miR-223 may revert inflammation. MiR-33 mediates lipid accumulation and foam cell deposition. The decrease of miR-133 is associated with an increase in inflammatory T cells. HIF-1α, VEGF, PlGF secreted by inflammatory cells cause endothelial dysfunction with impaired angiogenesis. The increase of miR-9, miR-17, miR-26a, miR-124, and miR-223 impairs angiogenesis. MiR-9 blocks the angiogenic capacity of CMs by blocking PDGF action. The increase of let7b-5p, let-7f, miR-21, miR-30b/c, miR-126, miR-130a, miR-133, miR-143, miR-221, and miR378 may restore angiogenesis. Besides, CM-derived exosomes induced by ischemia and enriched in miR-143 and miR-221 may restore angiogenesis. Inflammatory cells and injured ECs secrete ROS and DAMPS, causing cell death. MiR-181 protects against ROS and DAMPS. The increase of miR-9, miR-34a, miR-223, and ANRIL mediates cell death. The decrease of miR-1, miR-7, miR-133, and miR-873, silenced by lncRNA NRF, exacerbates cell death. However, high miR-21, NEAT1 silencing miR-34a, TUG1 silencing miR-145, miR-378, and UCA1 protect against apoptosis. Silencing of miR-17 by H19, HOTAIR, and MALAT1, silencing miR-150 and miR-181 by MIAT, and a decrease of miR-223 also prevents cell death. However, the decrease of miR-181b is associated with increased ROS. Increased non-coding RNAs are in red, decreased in green

Cardiac hypertrophy is the thickening of the myocardium, particularly the left ventricle. This thickening may occur physiologically because of athletic training and is usually a uniform increase in ventricular wall thickness. At the early stage of pathological hypertrophy, the increased size of cardiomyocytes is a compensatory mechanism. However, sustained hypertrophy may eventually lead to maladaptive cardiac remodeling, including fibrosis and inflammation. Angiotensinogen (ANG) II-induced cardiomyopathy results in part from the angiotensin II receptor type 1 (AT1R or AGTR1)-mediated Janus kinase (JAK)/signal transducing and activator of transcription (STAT)-3 signaling and STAT3-dependent activation of local Ras [4, 5]. Latent STATs reside in the cytoplasm until activated via tyrosine phosphorylation leading to their dimerization and nuclear translocation [6–8]. However, unphosphorylated STATs are also involved. Unphosphorylated STAT1 and interferon regulatory factor (IRF)-1 support transcription of proteasome subunit β9 (PSMB9 or LMP2). LMP2 is a member of the class II region of the major histocompatibility complex (MHC) induced by interferon (IFN)-γ. Unphosphorylated STAT3 is induced by and up-regulates E2F transcription factor 1 (E2F1) that controls cyclin (CCN)-D1 and CCNE expression [9–11]. Mechanical stretch locally activates myocyte AT1R signaling even through an ANG-II-independent mechanism by integrating G proteins into the cytosol [12]. In addition to the G protein GQ, AT1R stimulates several tyrosine kinases, including JAK, SRC proto-oncogene, non-receptor tyrosine kinase (SRC), and epidermal growth factor receptor (EGFR) [5, 13] (Fig. 6.1). Activated FBs called myofibroblasts are the effector cells of fibrosis. Myofibroblasts originate from quiescent tissue FBs, circulating CD34 + fibrocytes, and epithelial cells, and ECs [14, 15]. Myofibroblasts are fibroblast-like in terms of extracellular matrix (ECM) synthesis and SMC-like in terms of migration. Cross-talk between macrophages and myofibroblasts leads to their activation. ANG II activates toll-like receptor adaptor molecule 1 (TRIF or TICAM1), transforming growth

122

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

factor (TGF)-β, insulin-like growth factor 1 (IGF1), TGF-β/SMAD family member (SMAD)signaling. This increases Wnt proteins, vascular endothelial growth factor (VEGF)-α, endothelin-1 (EDN-1), and platelet-derived growth factor (PDGF). In fibrotic conditions, there are changes in the composition and arrangement of ECM proteins, including type I and type III fibrillar collagens (COL1 and COL3) regulated by several growth factors such as ANG II, TGF-β1, IGF1, and tumor necrosis factor (TNF)-α [16–23]. Besides COL, ECM components like elastin, fibrillin, fibronectin, and proteoglycans change. Myofibroblasts modify the balance of metalloproteinases (MMPs) and TIMP metallopeptidase inhibitors (TIMPs) to promote fibrosis [16, 24]. Dynamic ECM changes activate myofibroblasts and induce inflammatory leukocytes, driving wound repair [3, 25–28]. The renin-angiotensin-aldosterone system (RAAS) is activated, increasing levels of active TGF-β1. SMCs, monocytes, and FBs are recruited, and ECM proteins are deposited [29]. Besides activated myofibroblasts, a subset of monocytes/macrophages may thus contribute to the fibrotic response [22, 30] (Fig. 6.1). The initial inflammatory response consists of the infiltration of monocytes, which differentiate into macrophages. Recruited monocytes express the chemokine receptor CCR2 and infiltrate the infarcted myocardium in response to the up-regulation of C-C motif chemokine ligand 2 (CCL2 or MCP1) [31]. This inflammatory response also augments damage-associated molecular patterns (DAMPs) [32]. DAMPs are not only secreted by activated leukocytes but also by stressed cardiomyocytes and fibroblasts [33–36]. Several DAMPs can trigger the inflammatory response and, together with mitochondrial reactive oxidant species (ROS), induce CM death [33–39] (Fig. 6.1). During the later phase of the immune response, T lymphocytes infiltrate. Cardiac T cells are primed to induce cardiac injury and remodeling and retain this memory on adoptive transfer [40–42]. Thereby, Th1 and Th17 cells increase, while Th2 and Treg cells decrease. This shift to TH1 and Th17 cells results in increased inflammatory interleukin (IL)-1β, IL6, IL-17, IL-23, and decreased anti-inflammatory IL4, IL5, IL10, and IL13 [43–46]. Treg cells’ suppressive function plays a key role in controlling both innate and adaptive immune responses through secretion of IL10 and TGF-β and attenuation of interstitial fibrosis, myocardial MMP2 activity, and cardiac apoptosis [47–50] (Fig. 6.1). During the development of cardiac hypertrophy, capillary ECs undergo a phenotypic change favoring angiogenesis. The latter is needed to support the contractile function of the myocardium [51, 52]. The myocardium secretes VEGF and placental growth factor (PlGF), which coordinates vascular growth to meet demands for blood supply to sustain the increase in myocardial mass and performance. VEGF mainly interacts with the VEGF receptor 1 (VEGFR-1, also known as FMS-like tyrosine kinase 1) and VEGFR-2 (also known as FLK-1/kinase insert domain protein receptor) [53, 54]. VEGFR-1 and its soluble form VEGFR-1 are up-regulated in the heart. The soluble form of VEGFR-1 prevents capillary growth by trapping VEGF in pressureoverloaded hearts. Inhibition of the soluble form of VEGFR-1 by PlGF causes the release of VEGF to induce angiogenesis [55–57]. Endothelium-derived NO mediates angiogenesis-induced myocardial hypertrophy by promoting proteasomal

6.1 Mechanisms in Cardiomyopathy and Heart Failure

123

degradation of regulators of G-protein signaling. NO potentiates G-protein–mediated hypertrophic signaling involving the phosphatidylinositol 3-kinase (PI3K)/AKT serine/threonine kinase 1 (AKT)/mechanistic target of rapamycin kinase (mTOR) pathway [58]. However, angiogenesis is repressed at the transition from compensated hypertrophy to decompensated heart failure [59–61]. In the pressure-overloaded heart, the myocardium becomes ischemic, and the DNA-binding activity of HIF-1 increases. HIF-1α stabilizes in hypoxic conditions and transactivates genes encoding hypoxia- and angiogenesis- associated VEGF and erythropoietin. However, during prolonged pathological hypertrophy, HIF-1α and VEGF are down-regulated despite persistent myocardial hypoxia in the hypertrophied myocardium. This harmful HIF-1 down-regulation, involving the tumor suppressor p53 in hypertrophied hearts, exacerbates myocardial hypoxia and accelerated myocardial damage and dysfunction [62– 65]. Impaired angiogenesis may lead to oxidative stress-induced injury. However, the restoration of blood flow may further augment tissue damage via reperfusion injury due to abrupt re-oxygenation, ROS generation, and activation of the complement pathway [33, 37, 66] (Fig. 6.1).

6.2 Non-coding RNAs in Cardiomyopathy and Heart Failure Figure 6.1 illustrates the role of non-coding RNAs in several mechanisms contributing to cardiomyopathy and heart failure development.

6.2.1 Non-coding RNAs in Cardiac Hypertrophy MiR-1 and miR-133 induce cardiogenesis in mesenchymal cells by targeting NOTCH signaling [67, 68]. Let-7 mediates ANG II-induced cardiac hypertrophy [69]. The H19 imprinted maternally expressed transcript lncRNA (H19) inhibits cardiomyopathy by silencing let-7 [70]. High miR-9 is associated with cardiac hypertrophy and remodeling [71, 72]. MiR-21, which is increased selectively in fibroblasts of the failing heart, augments mitogen-activated protein kinase (MAPK or ERK) activity through inhibition of sprouty RTK signaling antagonist (SPRY1), thereby inducing the extent of cardiac hypertrophy and fibrosis [73]. High miR-25 is associated with pressureoverload-induced hypertrophy and cardiac fibrosis [74, 75] and causes degradation of the metastasis-associated lung adenocarcinoma transcript one lncRNA (MALAT1) [76]. Oxidative stress, TGF-β, and IGF1 induce miR-29, related to hypertrophic cardiomyopathy [77–81]. In contrast, miR-29 deficiency prevents cardiac hypertrophy and fibrosis [82]. MiR-106a promotes cardiac hypertrophy by silencing mitofusin 2 [83]. MiR-146a, up-regulated in left ventricular biopsies of patients with

124

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

aortic stenosis, provokes cardiac hypertrophy and left ventricular dysfunction [84]. The increase of miR-208a associated with cardiac injury after acute myocardial infarction induces cardiac hypertrophy through pathological myosin switching and cardiac remodeling [85–87]. MiR-223 causes cardiac hypertrophy but not fibrosis by directly interacting with 3’-UTRs of F-box and WD repeat domain containing 7 and activin A receptor type 2A, two negative regulators of the AKT signaling, and by directly silencing IGF1R and β1-integrin, two positive regulators of AKT signaling [88–90]. High levels of nuclear paraspeckle assembly transcript (NEAT1) promote hypoxia-induced CM proliferation and migration and ischemia-induced apoptosis by silencing miR-378a-3p [91, 92] (Fig. 6.19). MiR-1, a member of the muscle-specific myomiR family, is highly abundant in the heart. Its decrease is related to cardiac dysfunction, particularly in type 2 diabetes in association with oxidative stress [93, 94]. Urothelial cancer associated 1 (UCA1) promotes cardiac hypertrophy by silencing miR-1 and miR-184 [95]. Cardiac-targeted delivery of miR-1 reversed pressure overload-induced cardiac hypertrophy and reduced myocardial fibrosis [96]. ANG II decreases miR-92b-3p, associated with cardiac hypertrophy due to increased myocyte-specific enhancer factor 2D [97]. Decrease of miR-98 in infarcted and ischemic myocardium augments ANG II-induced cardiac hypertrophy by de-repressing CCND2 [69]. MiR-98 attenuates cardiac hypertrophy through down-regulation of mTOR and inhibits TGF-β1induced ECM deposition and apoptosis by regulating Fas/CASP-3 signaling [98– 100]. The long intergenic non-protein coding RNA regulator of reprogramming (LINC-ROR) induces hypertrophy by silencing miR-133 [94, 101–103]. Inhibition of X inactive specific transcript (XIST) improved myocardial injury due to the derepression of miR-133. Silencing of miR-150 is associated with cardiac hypertrophy but may ameliorate TGF-β1/SMAD-induced cardiac fibrosis [104, 105]. Downregulation of miR-199 is associated with cardiac hypertrophy, characterized by an increased heart weight and cardiomyocyte size, but with normal cardiac morphology and function, by targeting PGC1-α [106, 107]. High miR-26a inhibits cardiac hypertrophy and ECM deposition and attenuates cardiac apoptosis but impairs angiogenesis [108–112]. MiR-214-3p, active due to the down-regulation of the TINCR ubiquitin domain-containing lncRNA (TINCR), particularly in diabetes, attenuates myocardial hypertrophy by silencing calcium/calmodulin-dependent protein kinase II [113–117]. The lncRNA cardiac hypertrophy related factor (CHRF) sponges miR-489 and reduces hypertrophy [118, 119] (Fig. 6.1).

6.2.2 Non-coding RNAs in Cardiac Fibrosis and ECM Deposition Let-7, increased after myocardial infarction, induces fibrosis by decreasing the recruitment of transcription factor 21-positive epicardial cells [120]. MiR-17 is

6.2 Non-coding RNAs in Cardiomyopathy and Heart Failure

125

associated with TGF-β1-induced FB proliferation and COL secretion [121]. MiR21 promotes cardiac fibrosis by reducing the phosphatase and tensin homolog (PTEN)/AKT phosphorylation-dependent pathway leading to a decrease of the SMAD family member 7 (SMAD7) [122–124]. Further, the reduction of PTEN activates a fibrotic gene program and promotes monocyte-to-fibrocyte transition together with activation of CCL2 (MCP-1) [125]. Oxidative stress and hypoxia up-regulate miR-31, inducing cardiac troponin-T, E2F transcription factor 6, mineralocorticoid receptor, and TIMP4 [126]. Mir-31 may be competed out by lnc-31 originating from the same nuclear precursor of miR-31. Lnc-31 counteracts the differentiation of proliferating myoblasts [127]. MiR-34a, up-regulated by TGF-β1, increases fibrosis through silencing SMAD4 [128]. The down-regulation of maternally expressed 3 lncRNA (MEG3) increases miR-125b leading to cardiac fibrosis by inhibiting p53 [129, 130]. Deficiency of differentiated embryonic chondrocyte gene 1 in mice increased M1 to M2 macrophage polarization. It decreased fibrosis and apoptosis, likely by repressing miR-130 associated with ECM remodeling [131, 132] MiR-146a induces fibrosis by enhancing COL1α1 and COL4α1 [133]. High miR-155 stimulates ANG II/TGF-β1/SMAD3 signaling, increases COL1 deposition associated with decreased SOCS1 expression and inflammation, inducing fibrosis [77, 134]. MALAT1 may silence miR-155 but miR-25 down-regulates MALAT1 [135]. MiR433 elevated in fibroblasts compared to cardiomyocytes activates TGF-β1, MAPKs, p38 kinase, and SMAD3, ultimately inducing cardiac fibrosis [136]. Taurine upregulated 1 (TUG1) promotes differentiation of cardiac fibroblasts to myofibroblasts by silencing miR-29c [137]. The WNT1 inducible signaling pathway protein 2 (WISP2) super-enhancer-associated RNA (WISPER) enriched in cardiac fibroblasts collagen cross-linking, stabilization of ECM, and fibrosis [138]. Low miR-1 de-represses fibullin-2 implicated in ECM remodeling [139–144]. Lower levels of miR-18a-5p are associated with cardiac fibrosis through the upregulation of NOTCH2 signaling [145]. Lower miR-22 is associated with fibrosis because of increased TGF-β receptor expression. MiR-22 abrogates the action of MALAT1, but H19 sponges miR-22 [146–149]. Cardiac fibrosis also occurs when H19 silences miR-455, thereby inducing the connective tissue growth factor [70, 150, 151]. ANG II-induced myocardial infarction associated transcript (MIAT) downregulates miR-24 in cardiac fibroblasts and up-regulates TGF-β1, thereby promoting fibroblast proliferation and COL accumulation [152]. Sponging of miR-30a by MALAT1 in myocardial tissues induces myocardial fibrosis through the snail family transcriptional repressor 1 [153, 154]. Low levels of miR-101a are associated with cardiac fibrosis de-repression of TGF-β receptor on cardiac fibroblasts [155, 156]. MiR-101a and TGF-β are mutually inhibitory and co-direct the activation, proliferation, and COL synthesis of FBs [157]. Sponging of miR-133 by LINC-ROR increases cardiac fibrosis by inducing ERK1/2 and SMAD2 phosphorylation and increasing COL4A1 and COL1A1 deposition [158–160]. The increase of miR-221/222 levels in aortic stenosis patients correlated negatively with the extent of myocardial fibrosis and with left ventricular stiffness. Inhibition of both miRs in mice led to increased fibrosis and left ventricular dilation

126

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

and dysfunction by de-repressing TGF-β and SMAD2 signaling [161]. Cardiomyocytes exposed to mechanical stress secrete miR-378, inhibiting cardiac fibrosis [162]. Inhibition of miR-223 suppresses the NLRP3 inflammasome activation and alleviates myocardial fibrosis and apoptosis [163] (Fig. 6.1).

6.2.3 Non-coding RNAs in Cardiac Inflammation Silencing miR-150 by MIAT may result in increased infiltration of monocytes [105, 164]. Let-7 induces inflammation. H19 represses let-7, but LINC-ROR competes out this repression [165–167]. Also, miR-146a blocks H19 [168, 169]. The repression of H19 by miR-146a may, however, be reverted by MALAT1 [168, 170, 171]. MiR-146a activates Th1 cells [172]. MiR-33 increases lipid accumulation and inflammation by lowering the expression of ATP binding cassette subfamily A member 1 (ABCA1) [173, 174]. Increased expression of miR-223 due to the decrease of sponging MEG3 leads to the activation of the NLR family pyrin domain containing 3 (NLRP3) inflammasome [175]. The myocardial infarction associated with transcript 1 (MIRT1) is increased in response to MI and induces inflammation and apoptosis [176, 177]. The ANG II-induced decrease of miR-30a causes inflammation by increasing the expression of intercellular adhesion molecule (ICAM)-1 and vascular cell adhesion molecule (VCAM) by ECs [178]. MALAT1 enhances inflammation by sponging miR-133 [179–181]. MiR-21 attenuates inflammation by inhibiting p38 and NFκB signaling activation [182]. SMAD7 up-regulates miR-29, thereby decreasing pro-inflammatory cytokines IL-1β and TNF-α, and infiltration of CD3(+) T cells and F4/80(+) macrophages [183]. The increase of miR-181a in LPS-stimulated bone marrow-derived mesenchymal cells inhibited cardiomyocyte inflammation and oxidative stress [184] (Fig. 6.1).

6.2.4 Non-coding RNAs in Cardiac Angiogenesis High levels of miR-9 in cardiac tissues block PDGF, reducing the paracrine angiogenic capacity of cardiomyocytes [185, 186]. Synthetic microparticles conjugated with VEGF165 improved the survival of endothelial progenitor cells via miR-17 inhibition [187]. MiR-124 suppresses CD151-facilitated angiogenesis in the heart [188]. MiR-223 inhibits angiogenesis by targeting the ribosomal protein S6 kinase B1/HIF-1a signaling pathway [189]. Let-7b-5p, let-7f, miR-21, miR-30b, miR-30c, miR-126, miR-130a-3p, miR132, miR-133, and miR-378 protect against myocardial ischemia through inducing cardiac angiogenesis and vascular regeneration resulting in the increased blood flow

6.2 Non-coding RNAs in Cardiomyopathy and Heart Failure

127

to ischemic myocardium [190]. MiR-133-enriched EPC-derived exosomes transmitted to cardiac fibroblasts increased the angiogenesis potential of cardiac fibroblasts [191]. Exosomes enriched in miR-143 and miR-221 may restore angiogenesis [192] (Fig. 6.1).

6.2.5 Non-coding RNAs in Cardiac Apoptosis MiR-9 induces CM apoptosis by targeting the Yes1 associated transcriptional regulator (YAP1), thereby inducing caspase-3/7 activity [193]. MiR-34a aggravates hypoxia-induced apoptosis by silencing protein phosphatase one regulatory subunit 10, which reduces telomere shortening, DNA damage responses, and cardiomyocyte apoptosis, and improves functional recovery after AMI [194, 195]. Although NEAT1 may inhibit apoptosis by silencing miR-34a, hypoxia-induced NEAT1 may by itself induce apoptosis [196]. Cyclin-dependent kinase inhibitor 2B (CDKN2B) antisense RNA 1 (ANRIL) by itself induces apoptosis by degrading IL33 [197]. MiR-223 also mediates hypoxia-induced apoptosis [198] (Fig. 6.1). The decrease of miR-1 promotes the release of reactive oxygen species (ROS) by decreasing the NAD+ to NADH ratio and the NAD+ -dependent deacetylase activity of sirtuin (SIRT)-3. The decrease of miR-7 following ischemic reperfusion injury is related to CM apoptosis by activating the hypoxia-inducible factor-1/p-p38 pathway [199, 200]. P53 induces necrosis-related factor (NRF) that binds miR-873 and increases necrotic cell death in CMs [201]. β carvedilol inhibited apoptosis in the heart via up-regulating miR-133, which is, however, decreased in the failing heart [202] (Fig. 6.1). Bone marrow-derived mesenchymal and cardiac progenitor cells secrete miR-21enriched microvesicles protecting cardiomyocytes against ROS-mediated apoptosis by targeting programmed cell death 4 (PDCD4), [203–206]. High levels of TUG1 protect against apoptosis by silencing miR-145 [207]. Overexpression of miR-378 inhibits cardiac apoptosis by reducing caspase 3 protein levels [92, 208]. Also, UCA1 protects cardiomyocytes from hypoxia/reoxygenation apoptosis [209]. Sponging of miR-17 by the homeobox (HOX) transcript antisense lncRNA (HOTAIR), H19, and MALAT1 protect against ECM degradation and apoptosis in the heart [210–212]. As in other tissues, the silencing of miR-150 and miR-181 by MIAT blocks apoptosis. Reduction of the miR-181 family members harms myocardium because of increased myocardial response to oxidative stress. However, it is protective because it increases the expression of AKT3 and the phosphoinositide-3-kinase regulatory subunit 3, thereby reducing apoptosis of CMs [213–216] (Fig. 6.1).

128

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

6.3 Metabolic Syndrome: The Link Between Metabolic and Cardiovascular Diseases 6.3.1 Definition of Metabolic Syndrome Obesity often clusters with dyslipidemia, hypertension, and hyperglycemia in metabolic syndrome (MetS). Non-alcoholic fatty liver disease (NAFLD) is also a manifestation of end-organ damage of MetS. The National Cholesterol Education Program Adult Treatment Panel III defined MetS components as (1) waist circumference ≥ 102 cm in men and ≥ 88 cm in women; (2) fasting triglycerides ≥ 150 mg/dL (1.70 mmol/L); (3) HDL-cholesterol < 40 mg/dL (1.03 mmol/L) in men and < 50 mg/dL (1.29 mmol/L) in women; (4) blood pressure ≥ 130/85 mmHg; (5) fasting glucose ≥ 100 mg/dL (5.55 mmol/L). Persons with at least three of these components have MetS [217–220]. The American Heart Association (AHA) and the National Heart Lung and Blood Institute (NHLBI) slightly modified the ATP III criteria by not including abdominal obesity as an essential risk factor [221] (Fig. 6.2).

Fig. 6.2 Non-coding RNAs linking metabolic and cardiovascular diseases. Metabolic syndrome components are hypertension, hyperglycemia, dyslipidemia, and obesity. Blood pressure, glucose, lipids, ox-LDL, and inflammatory cytokines and adipokines determine the expression of the let-7 family, miR-1, miR-7, miR-9, miR-17, miR-21, miR-26, miR-29, miR-30a, miR-34a, miR-124, miR-130, miR-133, miR-143-145, miR-146a, miR-150, miR-155, miR-181 family, miR-221-222, miR-223, miR-378, miR-455, GAS5, HOTAIR, H19, lincRNA-p21, LINC-ROR, MALAT1, MEG3, MIAT, NEAT1, TUG1, UCA1, ANRIL, and PVT1. They link metabolic to cardiovascular diseases

6.3 Metabolic Syndrome: The Link Between Metabolic and Cardiovascular Diseases

129

6.3.2 Oxidative Stress and Metabolic Syndrome Elevated oxidized LDL (ox-LDL), but not elevated LDL-cholesterol, was associated with a higher risk of future MetS in the Cardiovascular Risk Development in Young Adults (CARDIA) Study [222, 223]. Elevated ox-LDL was significantly associated with the incidence of abdominal obesity, hyperglycemia, and hypertriglyceridemia. Ox-LDL may be related to obesity because it induces WAT growth. Experimental data showing that ox-LDL induces adipocyte proliferation directly or indirectly by increasing the infiltration of inflammatory monocytes/macrophages supports this hypothesis [224, 225]. As discussed above, the increase in WAT mass may also be explained by cellular hypertrophy due to the increased lipid accumulation in the pre-existing adipocytes rather than an increase in cell number or differentiation. Ox-LDL also decreases adiponectin and increases ROS production, especially when glucose is high [226]. Ox-LDL activates c-Jun N-terminal kinase (JNK) and disrupts insulin signaling in both adipocytes and macrophages in a CD36-dependent manner. Macrophages isolated from Cd36(−/−) mice elicited less JNK activation after highfat diet feeding and restored insulin signaling [227]. Not only CD36 but also LOX-1 is independently associated with insulin resistance in WAT [228].

6.3.3 Metabolic Syndrome and Cardiovascular Risk The coronary event rate was higher among subjects with diabetes and with MetS in the Health, Aging, and Body Composition Study. Subjects with both diabetes and MetS had the highest cardiovascular risk [229]. The Mayo Clinic cohort study revealed an increase in CHD and CVD risk and all-cause mortality across exercise electrocardiographic categories with an increasing number of MetS components [230]. Patients with a higher number of MetS criteria have a higher risk of developing cardiac allograft vasculopathy after heart transplantation [231]. MetS is associated with lower cardiorespiratory fitness [232]. In the Taiwan Survey of Hypertension, Hyperglycaemia, and Hyperlipidaemia cohort, the MetS-attributed risk for CVD was 39% in men and 44% in women. Of all MetS components, central obesity had the highest population attributable risk in women (57%), whereas hypertension had the highest population attributable risk in men (57%) [233]. Also, we demonstrated that participants in the Health ABC study with high ox-LDL had a 2.0-fold higher adjusted risk of myocardial infarction even after adjusting for MetS [234].

130

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

6.3.4 Non-coding RNAs and Metabolic Syndrome Components Increased levels of miR-130, miR-140-5p, miR-142-3p, miR-143, and miR-222, and decreased concentrations of miR-15a, miR-146a, miR-423-5p, and miR-520c3p are strongly linked to measures of BMI, waist circumference, leptin, insulin, HOMA-IR, TG, and HDL-cholesterol [235]. Let-7 g is inversely related to low levels of HDL-cholesterol, associated with impaired reverse cholesterol transport [236, 237]. Type 2 diabetes patients have lower levels of miR-1-3p, miR-133a-3p, and growth arrest-specific five lncRNA (GAS5) levels [238, 239]. MiR-7 levels are low in islets from obese and moderately diabetic individuals, and increases after bariatric surgery and correlate with diabetes remission [240]. MiR-9, up-regulated in CD14 + cells of MetS patients, positively correlates to BMI, the Homeostasis Model Assessment of insulin resistance, triglycerides, and negatively to ABCA1 and HDL-cholesterol levels [241]. Increased expression of miR-17-5p in omental fat tissue reflects obesity and hyperglycemia [242]. Serum levels of miR-21 and miR-34a are elevated in NAFLD patients with non-alcoholic fatty liver disease [243, 244]. TNF-α and inflammatory cytokines, leptin, and resistin down-regulate miR-26b expression in adipocytes [245]. MiR-26a regulates glucose and lipid metabolisms and insulin signaling but is low in overweight subjects’ liver. MiR-26a has a beneficial effect on insulin sensitivity, hepatic glucose production, and fatty acid synthesis, thereby preventing obesity-induced metabolic complications [246]. MiR-29a and miR-29c increased in skeletal muscle from patients with type 2 diabetes, attenuate insulin signaling and expression of insulin substrate receptor (IRS)-1 and PI3K, and decreases glucose uptake by silencing GLUT4 [247]. MiR-29 is inversely related to glucocorticoid resistance [248]. MiR-30a in subcutaneous WAT corresponds with low insulin sensitivity in obese subjects, and restoration of miR-30a in WAT of obese mice improved insulin sensitivity and increased energy expenditure, decreased fat in the liver, and prevented WAT inflammation [249]. Circulating miR-34a is higher, while miR-146a and miR-150 are lower in obese subjects [250]. MiR-34a also increases with insulin resistance, while miR-146a is lower in pre-diabetic individuals, type 2 diabetes patients with insulin treatment, and type 2 diabetes patients with nephropathy and diabetic foot [251]. Circulating miR34a relates positively, while miR-21 and miR-146a are inversely related to blood pressure [252, 253]. The increase of miR-124 determines the overall metabolic, proliferative, and inflammatory state of cells [254]. MiR-143 and miR-222 correlate positively, while miR-146a is inversely related to obesity [235]. Circulating levels of miR-143-3p correlate with levels of leptin and are associated with insulin resistance in MetS patients due to decreased expression of IGF2R [255, 256]. MiR-145a and miR223, together with miR-101 and miR-125b-5p, are members of a regulatory network in lipid and lipoprotein metabolism and insulin signaling [257]. Low miR-181a in monocytes of obese patients is associated with insulin resistance, MetS, and coronary artery disease [258]. Increased levels of miR-223 in serum microvesicles are associated with progression from prediabetes to type 2 diabetes [259]. Mir-378 induces

6.3 Metabolic Syndrome: The Link Between Metabolic and Cardiovascular Diseases

131

adiponectin expression, while ANRIL represses expression of AdipoR1, a key regulator of glucose metabolism [260, 261]. TGF-β-induced miR-455 is associated with brown and white adipogenesis, lipid accumulation in liver associated with diabetes, and with high glucose-induced oxidative stress and inflammation [262–266]. The expression of miR-26a, GAS5, HOTAIR, H19, LINC-ROR, MALAT1, MEG3, NEAT1, and TUG1 depends on ox-LDL and hypoxia [267–275]. ANRIL, H19, MALAT1, MEG3, MIAT, NEAT1, and PVT1 oncogene (PVT1) mediated the response to inflammatory cytokines [276–284]. H19 is a regulator of adiponectin expression [285]. Low levels of the tumor protein p53 pathway corepressor 1 lncRNA (lincRNA-p21) are associated with high oxidative stress and increased TNF-α, IL1β, and IL-6 [286]. TGF-β1 and the macrophage-derived CCL18 induce UCA1, and thereby glucose uptake [287, 288]. Non-coding RNAs HOTAIR and MIAT and their target miRs, such as miR-150 and miR-155, are crucial in the sepsis/MetS cross-talk [289] (Fig. 6.2).

References 1. Banerjee, I., Fuseler, J. W., Price, R. L., Borg, T. K., & Baudino, T. A. (2007). Determination of cell types and numbers during cardiac development in the neonatal and adult rat and mouse. American Journal of Physiology Heart and Circulatory Physiology, 293, H1883–H1891. https://doi.org/10.1152/ajpheart.00514.2007. 2. Schirone, L., et al. (2017). A review of the molecular mechanisms underlying the development and progression of cardiac remodeling. Oxidative Medicine and Cellular Longevity, 2017, 3920195. https://doi.org/10.1155/2017/3920195. 3. Chen, W., & Frangogiannis, N. G. (2010). The role of inflammatory and fibrogenic pathways in heart failure associated with aging. Heart Failure Reviews, 15, 415–422. https://doi.org/ 10.1007/s10741-010-9161-y. 4. El-Adawi, H., et al. (2003). The functional role of the JAK-STAT pathway in post-infarction remodeling. Cardiovascular Research, 57, 129–138. 5. Tsai, C. T., et al. (2008). Angiotensin II activates signal transducer and activators of transcription 3 via Rac1 in atrial myocytes and fibroblasts: implication for the therapeutic effect of statin in atrial structural remodeling. Circulation, 117, 344–355. https://doi.org/10.1161/CIR CULATIONAHA.107.695346. 6. Leonard, W. J., & O’Shea, J. J. (1998). Jaks and STATs: biological implications. Annual Review of Immunology, 16, 293–322. https://doi.org/10.1146/annurev.immunol.16.1.293. 7. Wen, Z., & Darnell, J. E., Jr. (1997). Mapping of Stat3 serine phosphorylation to a single residue (727) and evidence that serine phosphorylation has no influence on DNA binding of Stat1 and Stat3. Nucleic Acids Research, 25, 2062–2067. 8. Wen, Z., Zhong, Z., & Darnell, J. E., Jr. (1995). Maximal activation of transcription by Stat1 and Stat3 requires both tyrosine and serine phosphorylation. Cell, 82, 241–250. 9. Chatterjee-Kishore, M., Wright, K. L., Ting, J. P., & Stark, G. R. (2000). How Stat1 mediates constitutive gene expression: A complex of unphosphorylated Stat1 and IRF1 supports transcription of the LMP2 gene. EMBO Journal, 19, 4111–4122. https://doi.org/10.1093/emboj/ 19.15.4111. 10. Yang, J., et al. (2005). Novel roles of unphosphorylated STAT3 in oncogenesis and transcriptional regulation. Cancer Research, 65, 939–947. 11. Yue, H., Li, W., Desnoyer, R., & Karnik, S. S. (2010). Role of nuclear unphosphorylated STAT3 in angiotensin II type 1 receptor-induced cardiac hypertrophy. Cardiovascular Research, 85, 90–99. https://doi.org/10.1093/cvr/cvp285.

132

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

12. Zou, Y., et al. (2004). Mechanical stress activates angiotensin II type 1 receptor without the involvement of angiotensin II. Nature Cell Biology, 6, 499–506. https://doi.org/10.1038/ncb 1137. 13. Mehta, P. K., & Griendling, K. K. (2007). Angiotensin II cell signaling: Physiological and pathological effects in the cardiovascular system. American Journal of Physiology. Cell Physiology, 292, C82–C97. https://doi.org/10.1152/ajpcell.00287.2006. 14. Wynn, T. A. (2008). Cellular and molecular mechanisms of fibrosis. The Journal of Pathology, 214, 199–210. https://doi.org/10.1002/path.2277. 15. Giricz, Z., et al. (2014). Cardioprotection by remote ischemic preconditioning of the rat heart is mediated by extracellular vesicles. Journal of Molecular and Cellular Cardiology, 68, 75–78. https://doi.org/10.1016/j.yjmcc.2014.01.004. 16. Berk, B. C., Fujiwara, K., & Lehoux, S. (2007). ECM remodeling in hypertensive heart disease. Journal of Clinical Investigation, 117, 568–575. https://doi.org/10.1172/JCI31044. 17. Weber, K. T., Pick, R., Jalil, J. E., Janicki, J. S., & Carroll, E. P. (1989). Patterns of myocardial fibrosis. Journal of Molecular and Cellular Cardiology, 21(Suppl 5), 121–131. 18. Jalil, J. E., et al. (1989). Fibrillar collagen and myocardial stiffness in the intact hypertrophied rat left ventricle. Circulation Research, 64, 1041–1050. 19. Vannella, K. M., & Wynn, T. A. (2017). Mechanisms of Organ Injury and Repair by Macrophages. Annual Review of Physiology, 79, 593–617. https://doi.org/10.1146/annurevphysiol-022516-034356. 20. Chen, X. Q., et al. (2015). TRIF promotes angiotensin II-induced cross-talk between fibroblasts and macrophages in atrial fibrosis. Biochemical and Biophysical Research Communications, 464, 100–105. https://doi.org/10.1016/j.bbrc.2015.05.131. 21. Russo, I., & Frangogiannis, N. G. (2016). Diabetes-associated cardiac fibrosis: Cellular effectors, molecular mechanisms and therapeutic opportunities. Journal of Molecular and Cellular Cardiology, 90, 84–93. https://doi.org/10.1016/j.yjmcc.2015.12.011. 22. Kong, P., Christia, P., & Frangogiannis, N. G. (2014). The pathogenesis of cardiac fibrosis. Cellular and Molecular Life Sciences, 71, 549–574. https://doi.org/10.1007/s00018-0131349-6. 23. Weber, K. T., Swamynathan, S. K., Guntaka, R. V., & Sun, Y. (1999). Angiotensin II and extracellular matrix homeostasis. International Journal of Biochemistry & Cell Biology, 31, 395–403. 24. Rossi, M. A. (1998). Pathologic fibrosis and connective tissue matrix in left ventricular hypertrophy due to chronic arterial hypertension in humans. Journal of Hypertension, 16, 1031–1041. 25. Frangogiannis, N. G. (2017). Fibroblasts and the extracellular matrix in right ventricular disease. Cardiovascular Research, 113, 1453–1464. https://doi.org/10.1093/cvr/cvx146. 26. Frangogiannis, N. G. (2017). The extracellular matrix in myocardial injury, repair, and remodeling. Journal of Clinical Investigation, 127, 1600–1612. https://doi.org/10.1172/JCI 87491. 27. Valiente-Alandi, I., Schafer, A. E., & Blaxall, B. C. (2016). Extracellular matrix-mediated cellular communication in the heart. Journal of Molecular and Cellular Cardiology, 91, 228– 237. https://doi.org/10.1016/j.yjmcc.2016.01.011. 28. Frieler, R. A., & Mortensen, R. M. (2015). Immune cell and other noncardiomyocyte regulation of cardiac hypertrophy and remodeling. Circulation, 131, 1019–1030. https://doi.org/ 10.1161/CIRCULATIONAHA.114.008788. 29. Bujak, M., & Frangogiannis, N. G. (2007). The role of TGF-beta signaling in myocardial infarction and cardiac remodeling. Cardiovascular Research, 74, 184–195. https://doi.org/ 10.1016/j.cardiores.2006.10.002. 30. Nahrendorf, M., et al. (2007). The healing myocardium sequentially mobilizes two monocyte subsets with divergent and complementary functions. Journal of Experimental Medicine, 204, 3037–3047. https://doi.org/10.1084/jem.20070885. 31. Dewald, O., et al. (2005). CCL2/Monocyte Chemoattractant Protein-1 regulates inflammatory responses critical to healing myocardial infarcts. Circulation Research, 96, 881–889. https:// doi.org/10.1161/01.RES.0000163017.13772.3a.

References

133

32. Nian, M., Lee, P., Khaper, N., & Liu, P. (2004). Inflammatory cytokines and postmyocardial infarction remodeling. Circulation Research, 94, 1543–1553. https://doi.org/10.1161/01.RES. 0000130526.20854.fa. 33. Timmers, L., et al. (2012). The innate immune response in reperfused myocardium. Cardiovascular Research, 94, 276–283. https://doi.org/10.1093/cvr/cvs018. 34. Ghigo, A., Franco, I., Morello, F., & Hirsch, E. (2014). Myocyte signalling in leucocyte recruitment to the heart. Cardiovascular Research, 102, 270–280. https://doi.org/10.1093/ cvr/cvu030. 35. Andrassy, M., et al. (2008). High-mobility group box-1 in ischemia-reperfusion injury of the heart. Circulation, 117, 3216–3226. https://doi.org/10.1161/CIRCULATIONAHA.108. 769331. 36. Yamauchi-Takihara, K., et al. (1995). Hypoxic stress induces cardiac myocyte-derived interleukin-6. Circulation, 91, 1520–1524. 37. Eltzschig, H. K., & Eckle, T. (2011). Ischemia and reperfusion–from mechanism to translation. Nature Medicine, 17, 1391–1401. https://doi.org/10.1038/nm.2507. 38. de Haan, J. J., Smeets, M. B., Pasterkamp, G., & Arslan, F. (2013). Danger signals in the initiation of the inflammatory response after myocardial infarction. Mediators of Inflammation, 2013, 206039. https://doi.org/10.1155/2013/206039. 39. Arslan, F., de Kleijn, D. P., & Pasterkamp, G. (2011). Innate immune signaling in cardiac ischemia. Nature Reviews Cardiology, 8, 292–300. https://doi.org/10.1038/nrcardio.2011.38. 40. Kaikita, K., et al. (2004). Targeted deletion of CC chemokine receptor 2 attenuates left ventricular remodeling after experimental myocardial infarction. American Journal of Pathology, 165, 439–447. https://doi.org/10.1016/S0002-9440(10)63309-3. 41. Laroumanie, F., et al. (2014). CD4+ T cells promote the transition from hypertrophy to heart failure during chronic pressure overload. Circulation, 129, 2111–2124. https://doi.org/10. 1161/CIRCULATIONAHA.113.007101. 42. Bansal, S. S., et al. (2017). Activated T Lymphocytes are Essential Drivers of Pathological Remodeling in Ischemic Heart Failure. Circulation: Heart Failure, 10, e003688. https://doi. org/10.1161/CIRCHEARTFAILURE.116.003688. 43. Cheng, X., et al. (2005). Effects of Atorvastatin on Th polarization in patients with acute myocardial infarction. European Journal of Heart Failure, 7, 1099–1104. https://doi.org/10. 1016/j.ejheart.2005.01.020. 44. Cheng, X., et al. (2005). TH1/TH2 functional imbalance after acute myocardial infarction: coronary arterial inflammation or myocardial inflammation. Journal of Clinical Immunology, 25, 246–253. https://doi.org/10.1007/s10875-005-4088-0. 45. Zhang, J., et al. (2006). Myosin specific-T lymphocytes mediated myocardial inflammation in adoptive transferred rats. Cellular & Molecular Immunology, 3, 445–451. 46. Cheng, X., et al. (2008). The Th17/Treg imbalance in patients with acute coronary syndrome. Clinical Immunology, 127, 89–97. https://doi.org/10.1016/j.clim.2008.01.009. 47. Sakaguchi, S., et al. (2006). Foxp3+ CD25+ CD4+ natural regulatory T cells in dominant self-tolerance and autoimmune disease. Immunological Reviews, 212, 8–27. https://doi.org/ 10.1111/j.0105-2896.2006.00427.x. 48. Vignali, D. A., Collison, L. W., & Workman, C. J. (2008). How regulatory T cells work. Nature Reviews Immunology, 8, 523–532. https://doi.org/10.1038/nri2343. 49. Liang, B., et al. (2008). Regulatory T cells inhibit dendritic cells by lymphocyte activation gene-3 engagement of MHC class II. Clinical Immunology, 180, 5916–5926. 50. Tang, T. T., et al. (2012). Regulatory T cells ameliorate cardiac remodeling after myocardial infarction. Basic Research in Cardiology, 107, 232. https://doi.org/10.1007/s00395-0110232-6. 51. van Berlo, J. H., Maillet, M., & Molkentin, J. D. (2013). Signaling effectors underlying pathologic growth and remodeling of the heart. Journal of Clinical Investigation, 123, 37–45. https://doi.org/10.1172/JCI62839. 52. Souders, C. A., Bowers, S. L., & Baudino, T. A. (2009). Cardiac fibroblast: The renaissance cell. Circulation Research, 105, 1164–1176. https://doi.org/10.1161/CIRCRESAHA. 109.209809.

134

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

53. Saharinen, P., Bry, M., & Alitalo, K. (2010). How do angiopoietins Tie in with vascular endothelial growth factors? Current Opinion in Hematology, 17, 198–205. https://doi.org/10. 1097/MOH.0b013e3283386673. 54. Zentilin, L., et al. (2010). Cardiomyocyte VEGFR-1 activation by VEGF-B induces compensatory hypertrophy and preserves cardiac function after myocardial infarction. The FASEB Journa, 24, 1467–1478. https://doi.org/10.1096/fj.09-143180. 55. Luttun, A., Tjwa, M., & Carmeliet, P. (2002). Placental growth factor (PlGF) and its receptor Flt-1 (VEGFR-1): Novel therapeutic targets for angiogenic disorders. Annals of the New York Academy of Sciences, 979, 80–93. 56. Luttun, A., et al. (2002). Revascularization of ischemic tissues by PlGF treatment, and inhibition of tumor angiogenesis, arthritis and atherosclerosis by anti-Flt1. Nature Medicine, 8, 831–840. https://doi.org/10.1038/nm731. 57. Bry, M., Kivela, R., Leppanen, V. M., & Alitalo, K. (2014). Vascular endothelial growth factor-B in physiology and disease. Physiological Reviews, 94, 779–794. https://doi.org/10. 1152/physrev.00028.2013. 58. Lambert, N. A., et al. (2010). Regulators of G-protein signaling accelerate GPCR signaling kinetics and govern sensitivity solely by accelerating GTPase activity. Proceedings of the National Academy of Sciences of the United States of America, 107, 7066–7071. https://doi. org/10.1073/pnas.0912934107. 59. Zhao, X., et al. (2015). Overexpression of cardiomyocyte alpha1A-adrenergic receptors attenuates postinfarct remodeling by inducing angiogenesis through heterocellular signaling. Arteriosclerosis, Thrombosis, and Vascular Biology, 35, 2451–2459. https://doi.org/10.1161/ATV BAHA.115.305919. 60. Zou, Y., et al. (2011). Heat shock transcription factor 1 protects heart after pressure overload through promoting myocardial angiogenesis in male mice. Journal of Molecular and Cellular Cardiology, 51, 821–829. https://doi.org/10.1016/j.yjmcc.2011.07.030. 61. Zhang, M., et al. (2010). NADPH oxidase-4 mediates protection against chronic load-induced stress in mouse hearts by enhancing angiogenesis. Proceedings of the National Academy of Sciences of the United States of America, 107, 18121–18126. https://doi.org/10.1073/pnas. 1009700107. 62. Forsythe, J. A., et al. (1996). Activation of vascular endothelial growth factor gene transcription by hypoxia-inducible factor 1. Molecular and Cellular Biology, 16, 4604–4613. 63. Grimm, C., et al. (2002). HIF-1-induced erythropoietin in the hypoxic retina protects against light-induced retinal degeneration. Nature Medicine, 8, 718–724. https://doi.org/10.1038/ nm723. 64. Semenza, G. L. (2012). Hypoxia-inducible factors in physiology and medicine. Cell, 148, 399–408. https://doi.org/10.1016/j.cell.2012.01.021. 65. Sano, M., et al. (2007). p53-induced inhibition of Hif-1 causes cardiac dysfunction during pressure overload. Nature, 446, 444–448. https://doi.org/10.1038/nature05602. 66. Feng, Y., Madungwe, N. B., da Cruz Junho, C. V. & Bopassa, J. C. (2017). Activation of G protein-coupled oestrogen receptor 1 at the onset of reperfusion protects the myocardium against ischemia/reperfusion injury by reducing mitochondrial dysfunction and mitophagy. British Journal of Pharmacology, 174, 4329–4344. https://doi.org/10.1111/bph.14033. 67. Huang, F., et al. (2013). miR-1-mediated induction of cardiogenesis in mesenchymal stem cells via downregulation of Hes-1. BioMed Research International, 2013, 216286. https://doi. org/10.1155/2013/216286. 68. Takaya, T., et al. (2009). MicroRNA-1 and MicroRNA-133 in spontaneous myocardial differentiation of mouse embryonic stem cells. Circulation Journal, 73, 1492–1497. https://doi. org/10.1253/circj.cj-08-1032. 69. Yang, Y., Ago, T., Zhai, P., Abdellatif, M., & Sadoshima, J. (2011). Thioredoxin 1 negatively regulates angiotensin II-induced cardiac hypertrophy through upregulation of miR-98/let-7. Circulation Research, 108, 305–313. https://doi.org/10.1161/CIRCRESAHA.110.228437. 70. Liu, L., et al. (2016). The H19 long noncoding RNA is a novel negative regulator of cardiomyocyte hypertrophy. Cardiovascular Research, 111, 56–65. https://doi.org/10.1093/ cvr/cvw078.

References

135

71. Xiao, Y., et al. (2019). Inhibition of MicroRNA-9-5p Protects Against Cardiac Remodeling Following Myocardial Infarction in Mice. Human Gene Therapy, 30, 286–301. https://doi. org/10.1089/hum.2018.059. 72. Wang, L., et al. (2016). MicroRNA-9 regulates cardiac fibrosis by targeting PDGFR-beta in rats. Journal of Physiology and Biochemistry, 72, 213–223. https://doi.org/10.1007/s13105016-0471-y. 73. Thum, T., et al. (2008). MicroRNA-21 contributes to myocardial disease by stimulating MAP kinase signalling in fibroblasts. Nature, 456, 980–984. https://doi.org/10.1038/nature07511. 74. Dirkx, E., et al. (2013). Nfat and miR-25 cooperate to reactivate the transcription factor Hand2 in heart failure. Nature Cell Biology, 15, 1282–1293. https://doi.org/10.1038/ncb2866. 75. Tan, K. S., et al. (2009). Expression profile of microRNAs in young stroke patients. PLoS ONE, 4, e7689. https://doi.org/10.1371/journal.pone.0007689. 76. Hua, W. F., et al. (2016). RBM24 suppresses cancer progression by upregulating miR-25 to target MALAT1 in nasopharyngeal carcinoma. Cell Death and Disease, 7, e2352. https://doi. org/10.1038/cddis.2016.252. 77. Derda, A. A., et al. (2015). Blood-based microRNA signatures differentiate various forms of cardiac hypertrophy. International Journal of Cardiology, 196, 115–122. https://doi.org/10. 1016/j.ijcard.2015.05.185. 78. Roncarati, R., et al. (2014). Circulating miR-29a, among other up-regulated microRNAs, is the only biomarker for both hypertrophy and fibrosis in patients with hypertrophic cardiomyopathy. Journal of the American College of Cardiology, 63, 920–927. https://doi.org/10.1016/ j.jacc.2013.09.041. 79. van Rooij, E., et al. (2008). Dysregulation of microRNAs after myocardial infarction reveals a role of miR-29 in cardiac fibrosis. Proceedings of the National Academy of Sciences of the United States of America, 105, 13027–13032. https://doi.org/10.1073/pnas.0805038105. 80. Zhang, Y., et al. (2014). miR-29b as a therapeutic agent for angiotensin II-induced cardiac fibrosis by targeting TGF-beta/Smad3 signaling. Molecular Therapy, 22, 974–985. https:// doi.org/10.1038/mt.2014.25. 81. Abonnenc, M., et al. (2013). Extracellular matrix secretion by cardiac fibroblasts: role of microRNA-29b and microRNA-30c. Circulation Research, 113, 1138–1147. https://doi.org/ 10.1161/CIRCRESAHA.113.302400. 82. Sassi, Y., et al. (2017). Cardiac myocyte miR-29 promotes pathological remodeling of the heart by activating Wnt signaling. Nature Communications, 8, 1614. https://doi.org/10.1038/ s41467-017-01737-4. 83. Guan, X., et al. (2016). miR-106a promotes cardiac hypertrophy by targeting mitofusin 2. Journal of Molecular and Cellular Cardiology, 99, 207–217. https://doi.org/10.1016/j.yjmcc. 2016.08.016. 84. Heggermont, W. A., et al. (2017). Inhibition of microRNA-146a and overexpression of its target dihydrolipoyl succinyltransferase protect against pressure overload-induced cardiac hypertrophy and dysfunction. Circulation, 136, 747–761. https://doi.org/10.1161/CIRCUL ATIONAHA.116.024171. 85. Callis, T. E., et al. (2009). MicroRNA-208a is a regulator of cardiac hypertrophy and conduction in mice. Journal of Clinical Investigation, 119, 2772–2786. https://doi.org/10.1172/JCI 36154. 86. Fichtlscherer, S., Zeiher, A. M., & Dimmeler, S. (2011). Circulating microRNAs: Biomarkers or mediators of cardiovascular diseases? Arteriosclerosis, Thrombosis, and Vascular Biology, 31, 2383–2390. https://doi.org/10.1161/ATVBAHA.111.226696. 87. Montgomery, R. L., et al. (2011). Therapeutic inhibition of miR-208a improves cardiac function and survival during heart failure. Circulation, 124, 1537–1547. https://doi.org/10.1161/ CIRCULATIONAHA.111.030932. 88. Dickinson, B. A., et al. (2013). Plasma microRNAs serve as biomarkers of therapeutic efficacy and disease progression in hypertension-induced heart failure. European Journal of Heart Failure, 15, 650–659. https://doi.org/10.1093/eurjhf/hft018.

136

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

89. Yang, L., et al. (2016). Overexpression of miR-223 tips the balance of pro- and antihypertrophic signaling cascades toward physiologic cardiac hypertrophy. Journal of Biological Chemistry, 291, 15700–15713. https://doi.org/10.1074/jbc.M116.715805. 90. Shi, L., et al. (2016). miR-223-IGF-IR signalling in hypoxia- and load-induced rightventricular failure: A novel therapeutic approach. Cardiovascular Research, 111, 184–193. https://doi.org/10.1093/cvr/cvw065. 91. Zhao, J., Chen, F., Ma, W., & Zhang, P. (2020). Suppression of long noncoding RNA NEAT1 attenuates hypoxia-induced cardiomyocytes injury by targeting miR-378a-3p. Gene, 731, 144324. https://doi.org/10.1016/j.gene.2019.144324. 92. Fang, J., et al. (2012). Overexpression of microRNA-378 attenuates ischemia-induced apoptosis by inhibiting caspase-3 expression in cardiac myocytes. Apoptosis, 17, 410–423. https:// doi.org/10.1007/s10495-011-0683-0. 93. Vegter, E. L., van der Meer, P., & Voors, A. A. (2017). Associations between volume status and circulating microRNAs in acute heart failure. European Journal of Heart Failure, 19, 1077–1078. https://doi.org/10.1002/ejhf.867. 94. Yildirim, S. S., Akman, D., Catalucci, D., & Turan, B. (2013). Relationship between downregulation of miRNAs and increase of oxidative stress in the development of diabetic cardiac dysfunction: Junctin as a target protein of miR-1. Cell Biochemistry and Biophysics, 67, 1397–1408. https://doi.org/10.1007/s12013-013-9672-y. 95. Zhou, G., Li, C., Feng, J., Zhang, J., & Fang, Y. (2018). lncRNA UCA1 Is a Novel Regulator in Cardiomyocyte Hypertrophy through Targeting the miR-184/HOXA9 Axis. Cardiorenal Medicine, 8, 130–139. https://doi.org/10.1159/000487204. 96. Sayed, D., Hong, C., Chen, I. Y., Lypowy, J., & Abdellatif, M. (2007). MicroRNAs play an essential role in the development of cardiac hypertrophy. Circulation Research, 100, 416–424. https://doi.org/10.1161/01.RES.0000257913.42552.23. 97. Hu, Z. Q., et al. (2017). Targeting myocyte-specific enhancer factor 2D contributes to the suppression of cardiac hypertrophic growth by miR-92b-3p in mice. Oncotarget, 8, 92079– 92089. https://doi.org/10.18632/oncotarget.20759. 98. Sun, C., et al. (2017). MicroRNA-98 negatively regulates myocardial infarction-induced apoptosis by down-regulating Fas and caspase-3. Scientific Reports, 7, 7460. https://doi.org/10. 1038/s41598-017-07578-x. 99. Cheng, R., Dang, R., Zhou, Y., Ding, M., & Hua, H. (2017). MicroRNA-98 inhibits TGF-beta1induced differentiation and collagen production of cardiac fibroblasts by targeting TGFBR1. Human Cell, 30, 192–200. https://doi.org/10.1007/s13577-017-0163-0. 100. Li, Q., et al. (2016). Overexpression of microRNA-99a attenuates cardiac hypertrophy. PLoS ONE, 11, e0148480. https://doi.org/10.1371/journal.pone.0148480. 101. Jiang, F., Zhou, X., & Huang, J. (2016). Long non-coding RNA-ROR mediates the reprogramming in cardiac hypertrophy. PLoS ONE, 11, e0152767. https://doi.org/10.1371/journal. pone.0152767. 102. Care, A., et al. (2007). MicroRNA-133 controls cardiac hypertrophy. Nature Medicine, 13, 613–618. https://doi.org/10.1038/nm1582. 103. Li, Q., Lin, X., Yang, X., & Chang, J. (2010). NFATc4 is negatively regulated in miR-133amediated cardiomyocyte hypertrophic repression. American Journal of Physiology Heart and Circulatory Physiology, 298, H1340–H1347. https://doi.org/10.1152/ajpheart.00592.2009. 104. Che, H., et al. (2019). Inhibition of microRNA-150-5p alleviates cardiac inflammation and fibrosis via targeting Smad7 in high glucose-treated cardiac fibroblasts. Journal of Cellular Physiology. https://doi.org/10.1002/jcp.29386. 105. Liu, W., et al. (2015). MicroRNA-150 protects against pressure overload-induced cardiac hypertrophy. Journal of Cellular Biochemistry, 116, 2166–2176. https://doi.org/10.1002/jcb. 25057. 106. Li, Z., et al. (2016). miR-199-sponge transgenic mice develop physiological cardiac hypertrophy. Cardiovascular Research, 110, 258–267. https://doi.org/10.1093/cvr/cvw052. 107. Baumgarten, A., et al. (2013). TWIST1 regulates the activity of ubiquitin proteasome system via the miR-199/214 cluster in human end-stage dilated cardiomyopathy. International Journal of Cardiology, 168, 1447–1452. https://doi.org/10.1016/j.ijcard.2012.12.094.

References

137

108. Liu, Y., Wang, Z., & Xiao, W. (2016). MicroRNA-26a protects against cardiac hypertrophy via inhibiting GATA4 in rat model and cultured cardiomyocytes. Molecular Medicine Reports, 14, 2860–2866. https://doi.org/10.3892/mmr.2016.5574. 109. Chai, Z. T., et al. (2013). MicroRNA-26a inhibits angiogenesis by down-regulating VEGFA through the PIK3C2alpha/Akt/HIF-1alpha pathway in hepatocellular carcinoma. PLoS ONE, 8, e77957. https://doi.org/10.1371/journal.pone.0077957. 110. Chiang, M. H., et al. (2020). miR-26a attenuates cardiac apoptosis and fibrosis by targeting ataxia-telangiectasia mutated in myocardial infarction. Journal of Cellular Physiology. https:// doi.org/10.1002/jcp.29537. 111. Icli, B., et al. (2013). MicroRNA-26a regulates pathological and physiological angiogenesis by targeting BMP/SMAD1 signaling. Circulation Research, 113, 1231–1241. https://doi.org/ 10.1161/CIRCRESAHA.113.301780. 112. Zheng, L., Lin, S., & Lv, C. (2018). MiR-26a-5p regulates cardiac fibroblasts collagen expression by targeting ULK1. Scientific Reports, 8, 2104. https://doi.org/10.1038/s41598-018-205 61-4. 113. Tang, C. M., et al. (2016). Myocyte-specific enhancer factor 2C: a novel target gene of miR214-3p in suppressing angiotensin II-induced cardiomyocyte hypertrophy. Scientific Reports, 6, 36146. https://doi.org/10.1038/srep36146. 114. Zhao, Y., et al. (1863). MiR-485-5p modulates mitochondrial fission through targeting mitochondrial anchored protein ligase in cardiac hypertrophy. Biochimica et Biophysica Acta, 2871–2881, 2017. https://doi.org/10.1016/j.bbadis.2017.07.034. 115. Shao, M., et al. (2017). LncRNA TINCR attenuates cardiac hypertrophy by epigenetically silencing CaMKII. Oncotarget, 8, 47565–47573. https://doi.org/10.18632/oncotarget.17735. 116. Zhu, W. S., et al. (2016). Targeting EZH1 and EZH2 contributes to the suppression of fibrosisassociated genes by miR-214-3p in cardiac myofibroblasts. Oncotarget, 7, 78331–78342. https://doi.org/10.18632/oncotarget.13048. 117. Chen, Y., Tan, S., Liu, M., & Li, J. (2018). LncRNA TINCR is downregulated in diabetic cardiomyopathy and relates to cardiomyocyte apoptosis. Scandinavian Cardiovascular Journal, 1–17. https://doi.org/10.1080/14017431.2018.1546896. 118. Wang, K., et al. (2014). The long noncoding RNA CHRF regulates cardiac hypertrophy by targeting miR-489. Circulation Research, 114, 1377–1388. https://doi.org/10.1161/CIRCRE SAHA.114.302476. 119. Wo, Y., Guo, J., Li, P., Yang, H., & Wo, J. (2018). Long non-coding RNA CHRF facilitates cardiac hypertrophy through regulating Akt3 via miR-93. Cardiovascular Pathology, 35, 29–36. https://doi.org/10.1016/j.carpath.2018.04.003. 120. Seeger, T., et al. (2016). Inhibition of let-7 augments the recruitment of epicardial cells and improves cardiac function after myocardial infarction. Journal of Molecular and Cellular Cardiology, 94, 145–152. https://doi.org/10.1016/j.yjmcc.2016.04.002. 121. Zhang, Y., et al. (2018). Resveratrol Inhibits the TGF-beta1-induced proliferation of cardiac fibroblasts and collagen secretion by downregulating miR-17 in rat. BioMed Research International, 2018, 8730593. https://doi.org/10.1155/2018/8730593. 122. Roy, S., et al. (2009). MicroRNA expression in response to murine myocardial infarction: miR-21 regulates fibroblast metalloprotease-2 via phosphatase and tensin homologue. Cardiovascular Research, 82, 21–29. https://doi.org/10.1093/cvr/cvp015. 123. Lorenzen, J. M., et al. (2015). Osteopontin is indispensible for AP1-mediated angiotensin IIrelated miR-21 transcription during cardiac fibrosis. European Heart Journal, 36, 2184–2196. https://doi.org/10.1093/eurheartj/ehv109. 124. Yuan, J., et al. (2017). Mir-21 promotes cardiac fibrosis after myocardial infarction via targeting Smad7. Cellular Physiology and Biochemistry, 42, 2207–2219. https://doi.org/10. 1159/000479995. 125. Gupta, S. K., et al. (2016). miR-21 promotes fibrosis in an acute cardiac allograft transplantation model. Cardiovascular Research, 110, 215–226. https://doi.org/10.1093/cvr/ cvw030.

138

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

126. Martinez, E. C., et al. (2017). MicroRNA-31 promotes adverse cardiac remodeling and dysfunction in ischemic heart disease. Journal of Molecular and Cellular Cardiology, 112, 27–39. https://doi.org/10.1016/j.yjmcc.2017.08.013. 127. Ballarino, M., et al. (2015). Novel long noncoding RNAs (lncRNAs) in myogenesis: A miR31 overlapping lncRNA transcript controls myoblast differentiation. Molecular and Cellular Biology, 35, 728–736. https://doi.org/10.1128/MCB.01394-14. 128. Huang, Y., Qi, Y., Du, J. Q., & Zhang, D. F. (2014). MicroRNA-34a regulates cardiac fibrosis after myocardial infarction by targeting Smad4. Expert Opinion on Therapeutic Targets, 18, 1355–1365. https://doi.org/10.1517/14728222.2014.961424. 129. Nagpal, V., et al. (2016). MiR-125b Is critical for fibroblast-to-myofibroblast transition and cardiac fibrosis. Circulation, 133, 291–301. https://doi.org/10.1161/CIRCULATIONAHA. 115.018174. 130. Li, J. Q., et al. (2016). Long non-coding RNA MEG3 inhibits microRNA-125a-5p expression and induces immune imbalance of Treg/Th17 in immune thrombocytopenic purpura. Biomedicine & Pharmacotherapy, 83, 905–911. https://doi.org/10.1016/j.biopha. 2016.07.057. 131. Li, X., et al. (2020). Dec1 deficiency protects the heart from fibrosis, inflammation, and myocardial cell apoptosis in a mouse model of cardiac hypertrophy. Biochemical and Biophysical Research Communications, 532, 513–519. https://doi.org/10.1016/j.bbrc.2020. 08.058. 132. Bertero, T., et al. (2015). A YAP/TAZ-miR-130/301 molecular circuit exerts systems-level control of fibrosis in a network of human diseases and physiologic conditions. Scientific Reports, 5, 18277. https://doi.org/10.1038/srep18277. 133. Feng, B., Chen, S., Gordon, A. D., & Chakrabarti, S. (2017). miR-146a mediates inflammatory changes and fibrosis in the heart in diabetes. Journal of Molecular and Cellular Cardiology, 105, 70–76. https://doi.org/10.1016/j.yjmcc.2017.03.002. 134. Wei, Y., et al. (2017). Inhibition of microRNA155 ameliorates cardiac fibrosis in the process of angiotensin II-induced cardiac remodeling. Molecular Medicine Reports, 16, 7287–7296. https://doi.org/10.3892/mmr.2017.7584. 135. Wang, Q., Lu, G., & Chen, Z. (2019). MALAT1 promoted cell proliferation and migration via MALAT1/miR-155/MEF2A pathway in hypoxia of cardiac stem cells. Journal of Cellular Biochemistry, 120, 6384–6394. https://doi.org/10.1002/jcb.27925. 136. Tao, L., et al. (2016). Crucial Role of miR-433 in regulating cardiac fibrosis. Theranostics, 6, 2068–2083. https://doi.org/10.7150/thno.15007. 137. Zhu, Y., Feng, Z., Jian, Z., & Xiao, Y. (2018). Long noncoding RNA TUG1 promotes cardiac fibroblast transformation to myofibroblasts via miR29c in chronic hypoxia. Molecular Medicine Reports, 18, 3451–3460. https://doi.org/10.3892/mmr.2018.9327. 138. Micheletti, R., et al. (2017). The long noncoding RNA Wisper controls cardiac fibrosis and remodeling. Science Translational Medicine, 9. https://doi.org/10.1126/scitranslmed.aai9118. 139. Karakikes, I., et al. (2013). Therapeutic cardiac-targeted delivery of miR-1 reverses pressure overload-induced cardiac hypertrophy and attenuates pathological remodeling. Journal of the American Heart Association, 2, e000078. https://doi.org/10.1161/JAHA.113.000078. 140. Curcio, A., et al. (2013). MicroRNA-1 downregulation increases connexin 43 displacement and induces ventricular tachyarrhythmias in rodent hypertrophic hearts. PLoS ONE, 8, e70158. https://doi.org/10.1371/journal.pone.0070158. 141. Ikeda, S., et al. (2009). MicroRNA-1 negatively regulates expression of the hypertrophyassociated calmodulin and Mef2a genes. Molecular and Cellular Biology, 29, 2193–2204. https://doi.org/10.1128/MCB.01222-08. 142. Li, Q., et al. (2010). Attenuation of microRNA-1 derepresses the cytoskeleton regulatory protein twinfilin-1 to provoke cardiac hypertrophy. Journal of Cell Science, 123, 2444–2452. https://doi.org/10.1242/jcs.067165. 143. Komamura, K., et al. (2006). Heart-type fatty acid binding protein is a novel prognostic marker in patients with non-ischaemic dilated cardiomyopathy. Heart, 92, 615–618. https://doi.org/ 10.1136/hrt.2004.043067.

References

139

144. Varrone, F., et al. (2013). The circulating level of FABP3 is an indirect biomarker of microRNA-1. Journal of the American College of Cardiology, 61, 88–95. https://doi.org/ 10.1016/j.jacc.2012.08.1003. 145. Geng, H., & Guan, J. (2017). MiR-18a-5p inhibits endothelial-mesenchymal transition and cardiac fibrosis through the Notch2 pathway. Biochemical and Biophysical Research Communications, 491, 329–336. https://doi.org/10.1016/j.bbrc.2017.07.101. 146. Gong, Y. Y., Peng, M. Y., Yin, D. Q., & Yang, Y. F. (2018). Long non-coding RNA H19 promotes the osteogenic differentiation of rat ectomesenchymal stem cells via Wnt/betacatenin signaling pathway. European Review for Medical and Pharmacological Sciences, 22, 8805–8813. https://doi.org/10.26355/eurrev_201812_16648. 147. Song, Y., et al. (2019). Long noncoding RNA MALAT1 promotes high glucose-induced human endothelial cells pyroptosis by affecting NLRP3 expression through competitively binding miR-22. Biochemical and Biophysical Research Communications, 509, 359–366. https://doi. org/10.1016/j.bbrc.2018.12.139. 148. van Boven, N., et al. (2017). Serially measured circulating miR-22-3p is a biomarker for adverse clinical outcome in patients with chronic heart failure: The Bio-SHiFT study. International Journal of Cardiology, 235, 124–132. https://doi.org/10.1016/j.ijcard.2017. 02.078. 149. Hong, Y., et al. (2016). MiR-22 may suppress fibrogenesis by targeting TGFbetaR I in cardiac fibroblasts. Cellular Physiology and Biochemistry, 40, 1345–1353. https://doi.org/10.1159/ 000453187. 150. Huang, Z. W., Tian, L. H., Yang, B., & Guo, R. M. (2017). Long noncoding RNA H19 Acts as a competing endogenous RNA to mediate CTGF expression by sponging miR-455 in cardiac fibrosis. DNA and Cell Biology, 36, 759–766. https://doi.org/10.1089/dna.2017.3799. 151. Greco, S., et al. (2016). Long noncoding RNA dysregulation in ischemic heart failure. Journal of Translational Medicine, 14, 183. https://doi.org/10.1186/s12967-016-0926-5. 152. Qu, X., et al. (2017). MIAT Is a pro-fibrotic long non-coding RNA Governing cardiac fibrosis in post-infarct myocardium. Scientific Reports, 7, 42657. https://doi.org/10.1038/srep42657. 153. Yuan, Y., et al. (2016). Overexpression of miR-30a in lung adenocarcinoma A549 cell line inhibits migration and invasion via targeting EYA2. Acta Biochimica et Biophysica Sinica (Shanghai), 48, 220–228. https://doi.org/10.1093/abbs/gmv139. 154. Pan, Y., et al. (2018). Long non-coding MALAT1 Functions as a competing endogenous RNA to regulate vimentin expression by sponging miR-30a-5p in hepatocellular carcinoma. Cellular Physiology and Biochemistry, 50, 108–120. https://doi.org/10.1159/000493962. 155. Pan, Z., et al. (2012). MicroRNA-101 inhibited postinfarct cardiac fibrosis and improved left ventricular compliance via the FBJ osteosarcoma oncogene/transforming growth factorbeta1 pathway. Circulation, 126, 840–850. https://doi.org/10.1161/CIRCULATIONAHA. 112.094524. 156. Zhao, X., et al. (2015). MicroRNA-101a inhibits cardiac fibrosis induced by hypoxia via targeting TGFbetaRI on cardiac fibroblasts. Cellular Physiology and Biochemistry, 35, 213– 226. https://doi.org/10.1159/000369689. 157. Zhou, Y., Shiok, T. C., Richards, A. M., & Wang, P. (2018). MicroRNA-101a suppresses fibrotic programming in isolated cardiac fibroblasts and in vivo fibrosis following trans-aortic constriction. Journal of Molecular and Cellular Cardiology, 121, 266–276. https://doi.org/ 10.1016/j.yjmcc.2018.07.251. 158. Matkovich, S. J., et al. (2010). MicroRNA-133a protects against myocardial fibrosis and modulates electrical repolarization without affecting hypertrophy in pressure-overloaded adult hearts. Circulation Research, 106, 166–175. https://doi.org/10.1161/CIRCRESAHA. 109.202176. 159. Chen, S., et al. (2014). Cardiac miR-133a overexpression prevents early cardiac fibrosis in diabetes. Journal of Cellular and Molecular Medicine, 18, 415–421. https://doi.org/10.1111/ jcmm.12218. 160. Castoldi, G., et al. (2012). MiR-133a regulates collagen 1A1: Potential role of miR-133a in myocardial fibrosis in angiotensin II-dependent hypertension. Journal of Cellular Physiology, 227, 850–856. https://doi.org/10.1002/jcp.22939.

140

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

161. Verjans, R., et al. (2018). MicroRNA-221/222 family counteracts myocardial fibrosis in pressure overload-induced heart failure. Hypertension, 71, 280–288. https://doi.org/10.1161/HYP ERTENSIONAHA.117.10094. 162. Yuan, J., et al. (2018). MicroRNA-378 suppresses myocardial fibrosis through a paracrine mechanism at the early stage of cardiac hypertrophy following mechanical stress. Theranostics, 8, 2565–2582. https://doi.org/10.7150/thno.22878. 163. Xu, D., Zhang, X., Chen, X., Yang, S., & Chen, H. (2020). Inhibition of miR-223 attenuates the NLRP3 inflammasome activation, fibrosis, and apoptosis in diabetic cardiomyopathy. Life Sciences, 256, 117980. https://doi.org/10.1016/j.lfs.2020.117980. 164. Liu, Z., et al. (2015). MicroRNA-150 protects the heart from injury by inhibiting monocyte accumulation in a mouse model of acute myocardial infarction. Circulation: Cardiovascular Genetics, 8, 11–20. https://doi.org/10.1161/CIRCGENETICS.114.000598. 165. Fu, Z., et al. (2017). Endogenous miRNA Sponge LincRNA-ROR promotes proliferation, invasion and stem cell-like phenotype of pancreatic cancer cells. Cell Death Discovery, 3, 17004. https://doi.org/10.1038/cddiscovery.2017.4. 166. Ghazal, S., et al. (2015). H19 lncRNA alters stromal cell growth via IGF signaling in the endometrium of women with endometriosis. EMBO Molecular Medicine, 7, 996–1003. https:// doi.org/10.15252/emmm.201505245. 167. Peng, F., et al. (2017). H19/let-7/LIN28 reciprocal negative regulatory circuit promotes breast cancer stem cell maintenance. Cell Death and Disease, 8, e2569. https://doi.org/10.1038/ cddis.2016.438. 168. Liang, R., et al. (2018). MiR-146a promotes the asymmetric division and inhibits the selfrenewal ability of breast cancer stem-like cells via indirect upregulation of Let-7. Cell Cycle, 17, 1445–1456. https://doi.org/10.1080/15384101.2018.1489176. 169. Olivieri, F., et al. (2013). MiR-146a as marker of senescence-associated pro-inflammatory status in cells involved in vascular remodelling. Age (Dordr), 35, 1157–1172. https://doi.org/ 10.1007/s11357-012-9440-8. 170. Ding, Y., et al. (2018). Mechanism of long non-coding RNA MALAT1 in lipopolysaccharideinduced acute kidney injury is mediated by the miR-146a/NF-kappaB signaling pathway. International Journal of Molecular Medicine, 41, 446–454. https://doi.org/10.3892/ijmm. 2017.3232. 171. Dai, L., et al. (2018). Knockdown of LncRNA MALAT1 contributes to the suppression of inflammatory responses by up-regulating miR-146a in LPS-induced acute lung injury. Connective Tissue Research, 59, 581–592. https://doi.org/10.1080/03008207.2018.1439480. 172. Guo, M., et al. (2010). miR-146a in PBMCs modulates Th1 function in patients with acute coronary syndrome. Immunology and Cell Biology, 88, 555–564. https://doi.org/10.1038/icb. 2010.16. 173. Deng, X., et al. (2018). B-RCA revealed circulating miR-33a/b associates with serum cholesterol in type 2 diabetes patients at high risk of ASCVD. Diabetes Research and Clinical Practice, 140, 191–199. https://doi.org/10.1016/j.diabres.2018.03.024. 174. Nishiga, M., et al. (2017). MicroRNA-33 controls adaptive fibrotic response in the remodeling heart by preserving lipid raft cholesterol. Circulation Research, 120, 835–847. https://doi.org/ 10.1161/CIRCRESAHA.116.309528. 175. Zhang, Y., et al. (2018). Melatonin prevents endothelial cell pyroptosis via regulation of long noncoding RNA MEG3/miR-223/NLRP3 axis. Journal of Pineal Research, 64. https://doi. org/10.1111/jpi.12449. 176. Zangrando, J., et al. (2014). Identification of candidate long non-coding RNAs in response to myocardial infarction. BMC Genomics, 15, 460. https://doi.org/10.1186/1471-2164-15-460. 177. Li, X., Zhou, J., & Huang, K. (2017). Inhibition of the lncRNA Mirt1 attenuates acute myocardial infarction by suppressing NF-kappaB activation. Cellular Physiology and Biochemistry, 42, 1153–1164. https://doi.org/10.1159/000478870. 178. Demolli, S., et al. (2015). MicroRNA-30 mediates anti-inflammatory effects of shear stress and KLF2 via repression of angiopoietin 2. Journal of Molecular and Cellular Cardiology, 88, 111–119. https://doi.org/10.1016/j.yjmcc.2015.10.009.

References

141

179. Gast, M., et al. (2018). Immune system-mediated atherosclerosis caused by deficiency of long noncoding RNA MALAT1 in ApoE-/- mice. Cardiovascular Research. https://doi.org/ 10.1093/cvr/cvy202. 180. Yu, S. Y., Dong, B., Tang, L., & Zhou, S. H. (2018). LncRNA MALAT1 sponges miR133 to promote NLRP3 inflammasome expression in ischemia-reperfusion injured heart. International Journal of Cardiology, 254, 50. https://doi.org/10.1016/j.ijcard.2017.10.071. 181. Yan, Y., et al. (2016). Circulating long noncoding RNA UCA1 as a novel biomarker of acute myocardial infarction. BioMed Research International, 2016, 8079372. https://doi.org/10. 1155/2016/8079372. 182. Yang, L., et al. (2018). MicroRNA-21 prevents excessive inflammation and cardiac dysfunction after myocardial infarction through targeting KBTBD7. Cell Death and Disease, 9, 769. https://doi.org/10.1038/s41419-018-0805-5. 183. Wei, L. H., et al. (2013). Smad7 inhibits angiotensin II-induced hypertensive cardiac remodelling. Cardiovascular Research, 99, 665–673. https://doi.org/10.1093/cvr/cvt151. 184. Liu, H. Y., et al. (2020). Lipopolysaccharide-stimulated bone marrow mesenchymal stem cellsderived exosomes inhibit H2O2-induced cardiomyocyte inflammation and oxidative stress via regulating miR-181a-5p/ATF2 axis. European Review for Medical and Pharmacological Sciences, 24, 10069–10077. https://doi.org/10.26355/eurrev_202010_23224. 185. Li, J., Dai, Y., Su, Z. & Wei, G. (2016). MicroRNA-9 inhibits high glucose-induced proliferation, differentiation and collagen accumulation of cardiac fibroblasts by down-regulation of TGFBR2. Bioscience Reports, 36. https://doi.org/10.1042/bsr20160346 (2016). 186. Zhang, J., et al. (2011). MicroRNA-9 is an activation-induced regulator of PDGFR-beta expression in cardiomyocytes. Journal of Molecular and Cellular Cardiology, 51, 337–346. https://doi.org/10.1016/j.yjmcc.2011.05.019. 187. Aday, S., et al. (2017). Synthetic microparticles conjugated with VEGF165 improve the survival of endothelial progenitor cells via microRNA-17 inhibition. Nature Communications, 8, 747. https://doi.org/10.1038/s41467-017-00746-7. 188. Zhao, Y., et al. (2018). MiR-124 aggravates failing hearts by suppressing CD151-facilitated angiogenesis in heart. Oncotarget, 9, 14382–14396. https://doi.org/10.18632/oncotarget. 24205. 189. Dai, G. H., et al. (2014). MicroRNA-223-3p inhibits the angiogenesis of ischemic cardiac microvascular endothelial cells via affecting RPS6KB1/hif-1a signal pathway. PLoS ONE, 9, e108468. https://doi.org/10.1371/journal.pone.0108468. 190. Moghiman, T., et al. (2020). Therapeutic angiogenesis with exosomal microRNAs: An effectual approach for the treatment of myocardial ischemia. Heart Failure Reviews. https://doi. org/10.1007/s10741-020-10001-9. 191. Lin, F., et al. (2019). YBX-1 mediated sorting of miR-133 into hypoxia/reoxygenation-induced EPC-derived exosomes to increase fibroblast angiogenesis and MEndoT. Stem Cell Research & Therapy, 10, 263. https://doi.org/10.1186/s13287-019-1377-8. 192. Ribeiro-Rodrigues, T. M., et al. (2017). Exosomes secreted by cardiomyocytes subjected to ischaemia promote cardiac angiogenesis. Cardiovascular Research, 113, 1338–1350. https:// doi.org/10.1093/cvr/cvx118. 193. Zheng, J., Peng, B., Zhang, Y., Ai, F., & Hu, X. (2019). miR-9 knockdown inhibits hypoxiainduced cardiomyocyte apoptosis by targeting Yap1. Life Sciences, 219, 129–135. https://doi. org/10.1016/j.lfs.2019.01.014. 194. Boon, R. A., et al. (2013). MicroRNA-34a regulates cardiac ageing and function. Nature, 495, 107–110. https://doi.org/10.1038/nature11919. 195. Shi, K., Sun, H., Zhang, H., Xie, D., & Yu, B. (2019). miR-34a-5p aggravates hypoxia-induced apoptosis by targeting ZEB1 in cardiomyocytes. Biological Chemistry, 400, 227–236. https:// doi.org/10.1515/hsz-2018-0195. 196. Wei, Q., Zhou, H. Y., Shi, X. D., Cao, H. Y., & Qin, L. (2019). Long noncoding RNA NEAT1 promotes myocardiocyte apoptosis and suppresses proliferation through regulation of miR129-5p. Journal of Cardiovascular Pharmacology, 74, 535–541. https://doi.org/10.1097/FJC. 0000000000000741.

142

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

197. Yang, J., et al. (2019). LncRNA ANRIL knockdown relieves myocardial cell apoptosis in acute myocardial infarction by regulating IL-33/ST2. Cell Cycle, 18, 3393–3403. https://doi. org/10.1080/15384101.2019.1678965. 198. Tang, Q., et al. (2018). Absence of miR-223-3p ameliorates hypoxia-induced injury through repressing cardiomyocyte apoptosis and oxidative stress by targeting KLF15. European Journal of Pharmacology, 841, 67–74. https://doi.org/10.1016/j.ejphar.2018.10.014. 199. Li, B., et al. (2014). MicroRNA-7a/b protects against cardiac myocyte injury in ischemia/reperfusion by targeting poly(ADP-ribose) polymerase. PLoS ONE, 9, e90096. https://doi.org/10.1371/journal.pone.0090096. 200. Sheng, Z., et al. (2019). MicroRNA-7b attenuates ischemia/reperfusion-induced H9C2 cardiomyocyte apoptosis via the hypoxia inducible factor-1/p-p38 pathway. Journal of Cellular Biochemistry, 120, 9947–9955. https://doi.org/10.1002/jcb.28277. 201. Wang, K., et al. (2016). The long noncoding RNA NRF regulates programmed necrosis and myocardial injury during ischemia and reperfusion by targeting miR-873. Cell Death and Differentiation, 23, 1394–1405. https://doi.org/10.1038/cdd.2016.28. 202. Xu, C., et al. (2014). beta-Blocker carvedilol protects cardiomyocytes against oxidative stressinduced apoptosis by up-regulating miR-133 expression. Journal of Molecular and Cellular Cardiology, 75, 111–121. https://doi.org/10.1016/j.yjmcc.2014.07.009. 203. Cheng, Y., et al. (2009). MicroRNA-21 protects against the H(2)O(2)-induced injury on cardiac myocytes via its target gene PDCD4. Journal of Molecular and Cellular Cardiology, 47, 5–14. https://doi.org/10.1016/j.yjmcc.2009.01.008. 204. Dong, S., et al. (2014). microRNA-21 promotes cardiac fibrosis and development of heart failure with preserved left ventricular ejection fraction by up-regulating Bcl-2. International Journal of Clinical and Experimental Pathology, 7, 565–574. 205. Gu, H., et al. (2018). Serum-derived extracellular vesicles protect against acute myocardial infarction by regulating miR-21/PDCD4 signaling pathway. Frontiers in Physiology, 9, 348. https://doi.org/10.3389/fphys.2018.00348. 206. Xiao, J., et al. (2016). Cardiac progenitor cell-derived exosomes prevent cardiomyocytes apoptosis through exosomal miR-21 by targeting PDCD4. Cell Death and Disease, 7, e2277. https://doi.org/10.1038/cddis.2016.181. 207. Wu, Z., Zhao, S., Li, C., & Liu, C. (2018). LncRNA TUG1 serves an important role in hypoxiainduced myocardial cell injury by regulating the miR1455pBinp3 axis. Molecular Medicine Reports, 17, 2422–2430. https://doi.org/10.3892/mmr.2017.8116. 208. Zhang, J., et al. (2017). Overexpression of exosomal cardioprotective miRNAs mitigates hypoxia-induced H9c2 cells apoptosis. International Journal of Molecular Sciences. 18. https://doi.org/10.3390/ijms18040711. 209. Wang, Q. S., Zhou, J., & Li, X. (2020). LncRNA UCA1 protects cardiomyocytes against hypoxia/reoxygenation induced apoptosis through inhibiting miR-143/MDM2/p53 axis. Genomics, 112, 574–580. https://doi.org/10.1016/j.ygeno.2019.04.009. 210. Hu, J., et al. (2018). Long non-coding RNA HOTAIR promotes osteoarthritis progression via miR-17-5p/FUT2/beta-catenin axis. Cell Death and Disease, 9, 711. https://doi.org/10.1038/ s41419-018-0746-z. 211. Huang, Z., Lei, W., Hu, H. B., Zhang, H., & Zhu, Y. (2018). H19 promotes non-small-cell lung cancer (NSCLC) development through STAT3 signaling via sponging miR-17. Journal of Cellular Physiology, 233, 6768–6776. https://doi.org/10.1002/jcp.26530. 212. Zhang, A., Shang, W., Nie, Q., Li, T., & Li, S. (2018). Long non-coding RNA H19 suppresses retinoblastoma progression via counteracting miR-17-92 cluster. Journal of Cellular Biochemistry, 119, 3497–3509. https://doi.org/10.1002/jcb.26521. 213. Seeger, T., et al. (2013). Immunosenescence-associated microRNAs in age and heart failure. European Journal of Heart Failure, 15, 385–393. https://doi.org/10.1093/eurjhf/hfs184. 214. Das, S., et al. (2017). Divergent effects of miR-181 family members on myocardial function through protective cytosolic and detrimental mitochondrial microRNA targets. Journal of the American Heart Association, 6. https://doi.org/10.1161/jaha.116.004694.

References

143

215. Yuan, L., et al. (2019). Inhibition of miR-181b-5p protects cardiomyocytes against ischemia/reperfusion injury by targeting AKT3 and PI3KR3. Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb.29271. 216. Guo, F., et al. (2018). The interplay of LncRNA ANRIL and miR-181b on the inflammationrelevant coronary artery disease through mediating NF-kappaB signalling pathway. Journal of Cellular and Molecular Medicine, 22, 5062–5075. https://doi.org/10.1111/jcmm.13790. 217. Ford, E. S. (2004). The metabolic syndrome and mortality from cardiovascular disease and all-causes: Findings from the National Health and Nutrition Examination Survey II Mortality Study. Atherosclerosis, 173, 309–314. https://doi.org/10.1016/j.atherosclerosis.2003.12.022. 218. Grundy, S. M., et al. (2004). Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation, 109, 433–438. https://doi.org/10.1161/01.CIR.0000111245. 75752.C6. 219. Kahn, R., et al. (2005). The metabolic syndrome: Time for a critical appraisal: joint statement from the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care, 28, 2289–2304. 220. Grundy, S. M., et al. (2001). Cardiovascular risk assessment based on US cohort studies: Findings from a National Heart, Lung, and Blood institute workshop. Circulation, 104, 491– 496. 221. Alberti, K. G., et al. (2009). Harmonizing the metabolic syndrome: A joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation, 120, 1640–1645. https://doi.org/10.1161/CIRCULATIONAHA.109.192644. 222. Holvoet, P., De Keyzer, D., & Jacobs, D. R., Jr. (2008). Oxidized LDL and the metabolic syndrome. Future Lipidology, 3, 637–649. https://doi.org/10.2217/17460875.3.6.637. 223. Holvoet, P., Lee, D. H., Steffes, M., Gross, M., & Jacobs, D. R., Jr. (2008). Association between circulating oxidized low-density lipoprotein and incidence of the metabolic syndrome. JAMA, 299, 2287–2293. https://doi.org/10.1001/jama.299.19.2287. 224. Masella, R., et al. (2006). Oxidised LDL modulate adipogenesis in 3T3-L1 preadipocytes by affecting the balance between cell proliferation and differentiation. FEBS Letters, 580, 2421–2429. https://doi.org/10.1016/j.febslet.2006.03.068. 225. Nishimura, S., et al. (2007). Adipogenesis in obesity requires close interplay between differentiating adipocytes, stromal cells, and blood vessels. Diabetes, 56, 1517–1526. https://doi. org/10.2337/db06-1749. 226. Ouedraogo, R., et al. (2006). Adiponectin suppression of high-glucose-induced reactive oxygen species in vascular endothelial cells: Evidence for involvement of a cAMP signaling pathway. Diabetes, 55, 1840–1846. https://doi.org/10.2337/db05-1174. 227. Kennedy, D. J., et al. (2011). A CD36-dependent pathway enhances macrophage and adipose tissue inflammation and impairs insulin signalling. Cardiovascular Research, 89, 604–613. https://doi.org/10.1093/cvr/cvq360. 228. Goodpaster, B. H., et al. (2005). Obesity, regional body fat distribution, and the metabolic syndrome in older men and women. Archives of Internal Medicine, 165, 777–783. https://doi. org/10.1001/archinte.165.7.777. 229. Butler, J., et al. (2006). Metabolic syndrome and the risk of cardiovascular disease in older adults. Journal of the American College of Cardiology, 47, 1595–1602. https://doi.org/10. 1016/j.jacc.2005.12.046. 230. Lyerly, G. W., et al. (2010). Maximal exercise electrocardiographic responses and coronary heart disease mortality among men with metabolic syndrome. Mayo Clinic Proceedings, 85, 239–246. https://doi.org/10.4065/mcp.2009.0509. 231. Sanchez-Gomez, J. M., et al. (2012). Influence of metabolic syndrome on development of cardiac allograft vasculopathy in the transplanted heart. Transplantation, 93, 106–111. https:// doi.org/10.1097/TP.0b013e3182398058.

144

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

232. Grundy, S. M., Barlow, C. E., Farrell, S. W., Vega, G. L., & Haskell, W. L. (2012). Cardiorespiratory fitness and metabolic risk. American Journal of Cardiology, 109, 988–993. https:// doi.org/10.1016/j.amjcard.2011.11.031. 233. Wang, W. S., et al. (2012). Age- and gender-specific population attributable risks of metabolic disorders on all-cause and cardiovascular mortality in Taiwan. BMC Public Health, 12, 111. https://doi.org/10.1186/1471-2458-12-111. 234. Holvoet, P., et al. (2004). The metabolic syndrome, circulating oxidized LDL, and risk of myocardial infarction in well-functioning elderly people in the health, aging, and body composition cohort. Diabetes, 53, 1068–1073. 235. Al-Rawaf, H. A. (2019). Circulating microRNAs and adipokines as markers of metabolic syndrome in adolescents with obesity. Clinical Nutrition, 38, 2231–2238. https://doi.org/10. 1016/j.clnu.2018.09.024. 236. Krause, B. J., et al. (2015). Micro-RNAs Let7e and 126 in plasma as markers of metabolic dysfunction in 10 to 12 years old children. PLoS ONE, 10, e0128140. https://doi.org/10.1371/ journal.pone.0128140. 237. Wang, Y. T., Tsai, P. C., Liao, Y. C., Hsu, C. Y., & Juo, S. H. (2013). Circulating microRNAs have a sex-specific association with metabolic syndrome. Journal of Biomedical Science, 20, 72. https://doi.org/10.1186/1423-0127-20-72. 238. Kokkinopoulou, I., et al. (2019). Decreased expression of microRNAs targeting type-2 diabetes susceptibility genes in peripheral blood of patients and predisposed individuals. Endocrine, 66, 226–239. https://doi.org/10.1007/s12020-019-02062-0. 239. Carter, G., et al. (2015). Circulating long noncoding RNA GAS5 levels are correlated to prevalence of type 2 diabetes mellitus. BBA Clinical, 4, 102–107. https://doi.org/10.1016/j. bbacli.2015.09.001. 240. Atkin, S. L., et al. (2018). Changes in blood microRNA expression and early metabolic responsiveness 21 days following bariatric surgery. Frontiers in Endocrinology (Lausanne), 9, 773. https://doi.org/10.3389/fendo.2018.00773. 241. D’Amore, S., et al. (2018). Identification of miR-9-5p as direct regulator of ABCA1 and HDLdriven reverse cholesterol transport in circulating CD14+ cells of patients with metabolic syndrome. Cardiovascular Research, 114, 1154–1164. https://doi.org/10.1093/cvr/cvy077. 242. Heneghan, H. M., Miller, N., McAnena, O. J., O’Brien, T., & Kerin, M. J. (2011). Differential miRNA expression in omental adipose tissue and in the circulation of obese patients identifies novel metabolic biomarkers. Journal of Clinical Endocrinology and Metabolism, 96, E846– E850. https://doi.org/10.1210/jc.2010-2701. 243. Yamada, H., et al. (2013). Associations between circulating microRNAs (miR-21, miR-34a, miR-122 and miR-451) and non-alcoholic fatty liver. Clinica Chimica Acta, 424, 99–103. https://doi.org/10.1016/j.cca.2013.05.021. 244. Rodrigues, P. M., et al. (2017). miR-21 ablation and obeticholic acid ameliorate nonalcoholic steatohepatitis in mice. Cell Death and Disease, 8, e2825. https://doi.org/10.1038/cddis.201 7.246. 245. Xu, G., et al. (2013). Modulation of hsa-miR-26b levels following adipokine stimulation. Molecular Biology Reports, 40, 3577–3582. https://doi.org/10.1007/s11033-012-2431-0. 246. Fu, X., et al. (2015). MicroRNA-26a regulates insulin sensitivity and metabolism of glucose and lipids. Journal of Clinical Investigation, 125, 2497–2509. https://doi.org/10.1172/JCI 75438. 247. Massart, J., et al. (2017). Altered miR-29 expression in type 2 diabetes influences glucose and lipid metabolism in skeletal muscle. Diabetes, 66, 1807–1818. https://doi.org/10.2337/db170141. 248. Glantschnig, C., et al. (2019). A miR-29a-driven negative feedback loop regulates peripheral glucocorticoid receptor signaling. The FASEB Journal, 33, 5924–5941. https://doi.org/10. 1096/fj.201801385RR. 249. Koh, E. H., et al. (2018). miR-30a remodels subcutaneous adipose tissue inflammation to improve insulin sensitivity in obesity. Diabetes, 67, 2541–2553. https://doi.org/10.2337/db171378.

References

145

250. Hijmans, J. G., et al. (2018). Influence of overweight and obesity on circulating inflammationrelated microRNA. Microrna, 7, 148–154. https://doi.org/10.2174/221153660766618040212 0806. 251. Garcia-Jacobo, R. E., et al. (2019). Circulating miR-146a, miR-34a and miR-375 in type 2 diabetes patients, pre-diabetic and normal-glycaemic individuals in relation to beta-cell function, insulin resistance and metabolic parameters. Clinical and Experimental Pharmacology and Physiology, 46, 1092–1100. https://doi.org/10.1111/1440-1681.13147. 252. Hijmans, J. G., et al. (2018). Association between hypertension and circulating vascularrelated microRNAs. Journal of Human Hypertension, 32, 440–447. https://doi.org/10.1038/ s41371-018-0061-2. 253. Watanabe, K., et al. (2020). The association between microRNA-21 and hypertensioninduced cardiac remodeling. PLoS ONE, 15, e0226053. https://doi.org/10.1371/journal.pone. 0226053. 254. Zhang, H., et al. (2017). Metabolic and proliferative state of vascular adventitial fibroblasts in pulmonary hypertension is regulated through a microRNA-124/PTBP1 (Polypyrimidine Tract Binding Protein 1)/pyruvate kinase muscle axis. Circulation, 136, 2468–2485. https:// doi.org/10.1161/CIRCULATIONAHA.117.028069. 255. Xihua, L., et al. (2019). Circulating miR-143-3p inhibition protects against insulin resistance in Metabolic Syndrome via targeting of the insulin-like growth factor 2 receptor. Translational Research, 205, 33–43. https://doi.org/10.1016/j.trsl.2018.09.006. 256. Takanabe, R., et al. (2008). Up-regulated expression of microRNA-143 in association with obesity in adipose tissue of mice fed high-fat diet. Biochemical and Biophysical Research Communications, 376, 728–732. https://doi.org/10.1016/j.bbrc.2008.09.050. 257. Sud, N., et al. (2017). Aberrant expression of microRNA induced by high-fructose diet: Implications in the pathogenesis of hyperlipidemia and hepatic insulin resistance. Journal of Nutritional Biochemistry, 43, 125–131. https://doi.org/10.1016/j.jnutbio.2017.02.003. 258. Hulsmans, M., et al. (2012). Decreased miR-181a expression in monocytes of obese patients is associated with the occurrence of metabolic syndrome and coronary artery disease. Journal of Clinical Endocrinology and Metabolism, 97, E1213–E1218. https://doi.org/10.1210/jc.20121008. 259. Parrizas, M., et al. (2019). miR-10b and miR-223-3p in serum microvesicles signal progression from prediabetes to type 2 diabetes. Journal of Endocrinological Investigation. https://doi. org/10.1007/s40618-019-01129-z. 260. Sun, L. Y., et al. (2018). LncRNA ANRIL regulates AML development through modulating the glucose metabolism pathway of AdipoR1/AMPK/SIRT1. Molecular Cancer, 17, 127. https://doi.org/10.1186/s12943-018-0879-9. 261. Ishida, M., et al. (2014). MicroRNA-378 regulates adiponectin expression in adipose tissue: A new plausible mechanism. PLoS ONE, 9, e111537. https://doi.org/10.1371/journal.pone. 0111537. 262. Ong, J., et al. (2017). Identification of transforming growth factor-beta-regulated microRNAs and the microRNA-targetomes in primary lung fibroblasts. PLoS ONE, 12, e0183815. https:// doi.org/10.1371/journal.pone.0183815. 263. Zhang, H., et al. (2015). MicroRNA-455 regulates brown adipogenesis via a novel HIF1anAMPK-PGC1alpha signaling network. EMBO Reports, 16, 1378–1393. https://doi.org/10. 15252/embr.201540837. 264. Cai, Z., Liu, J., Bian, H., Cai, J., & Guo, X. (2016). MiR-455 enhances adipogenic differentiation of 3T3-L1 cells through targeting uncoupling protein-1. Pharmazie, 71, 625–628. https://doi.org/10.1691/ph.2016.6734. 265. Fang, S., et al. (2020). MiR-455 targeting SOCS3 improve liver lipid disorders in diabetic mice. Adipocyte, 9, 179–188. https://doi.org/10.1080/21623945.2020.1749495. 266. Chen, P., et al. (2019). MiR-455-5p ameliorates HG-induced apoptosis, oxidative stress and inflammatory via targeting SOCS3 in retinal pigment epithelial cells. Journal of Cellular Physiology, 234, 21915–21924. https://doi.org/10.1002/jcp.28755.

146

6 Non-coding RNAs in Cardiomyopathy and Heart Failure

267. Tang, Y., et al. (2015). The lncRNA MALAT1 protects the endothelium against ox-LDLinduced dysfunction via upregulating the expression of the miR-22-3p target genes CXCR2 and AKT. FEBS Letters, 589, 3189–3196. https://doi.org/10.1016/j.febslet.2015.08.046. 268. Chen, L., et al. (2017). Exosomal lncRNA GAS5 regulates the apoptosis of macrophages and vascular endothelial cells in atherosclerosis. PLoS ONE, 12, e0185406. https://doi.org/ 10.1371/journal.pone.0185406. 269. Han, Y., Ma, J., Wang, J., & Wang, L. (2018). Silencing of H19 inhibits the adipogenesis and inflammation response in ox-LDL-treated Raw264.7 cells by up-regulating miR-130b. Molecular Immunology, 93, 107–114. https://doi.org/10.1016/j.molimm.2017.11.017. 270. Yan, L., Liu, Z., Yin, H., Guo, Z., & Luo, Q. (2019). Silencing of MEG3 inhibited oxLDL-induced inflammation and apoptosis in macrophages via modulation of the MEG3/miR204/CDKN2A regulatory axis. Cell Biology International, 43, 409–420. https://doi.org/10. 1002/cbin.11105. 271. Pang, J. L., Wang, J. W., Hu, P. Y., Jiang, J. S., & Yu, C. (2018). HOTAIR alleviates oxLDL-induced inflammatory response in Raw264.7 cells via inhibiting NF-kappaB pathway. European Review for Medical and Pharmacological Sciences, 22, 6991–6998. https://doi.org/ 10.26355/eurrev_201810_16170. 272. Wang, L., Xia, J. W., Ke, Z. P., & Zhang, B. H. (2019). Blockade of NEAT1 represses inflammation response and lipid uptake via modulating miR-342-3p in human macrophages THP-1 cells. Journal of Cellular Physiology, 234, 5319–5326. https://doi.org/10.1002/jcp. 27340. 273. Zhang, L., et al. (2018). TUG1 knockdown ameliorates atherosclerosis via up-regulating the expression of miR-133a target gene FGF1. Cardiovascular Pathology, 33, 6–15. https://doi. org/10.1016/j.carpath.2017.11.004. 274. Tian, S., et al. (2018). LncRNA UCA1 sponges miR-26a to regulate the migration and proliferation of vascular smooth muscle cells. Gene, 673, 159–166. https://doi.org/10.1016/j.gene. 2018.06.031. 275. Takahashi, K., Yan, I. K., Haga, H., & Patel, T. (2014). Modulation of hypoxia-signaling pathways by extracellular linc-RoR. Journal of Cell Science, 127, 1585–1594. https://doi. org/10.1242/jcs.141069. 276. Luo, R., Xiao, F., Wang, P., & Hu, Y. X. (2020). lncRNA H19 sponging miR-93 to regulate inflammation in retinal epithelial cells under hyperglycemia via XBP1s. Inflammation Research, 69, 255–265. https://doi.org/10.1007/s00011-019-01312-1. 277. Xu, Y., et al. (2019). Long non-coding RNA NEAT1 alleviates acute-on-chronic liver failure through blocking TRAF6 mediated inflammatory response. Frontiers in Physiology, 10, 1503. https://doi.org/10.3389/fphys.2019.01503. 278. Li, Y., Zhang, S., Zhang, C., & Wang, M. (2020). LncRNA MEG3 inhibits the inflammatory response of ankylosing spondylitis by targeting miR-146a. Molecular and Cellular Biochemistry, 466, 17–24. https://doi.org/10.1007/s11010-019-03681-x. 279. Li, J., & Liu, S. (2020). LncRNA GAS5 suppresses inflammatory responses and apoptosis of alveolar epithelial cells by targeting miR-429/DUSP1. Experimental and Molecular Pathology, 113, 104357. https://doi.org/10.1016/j.yexmp.2019.104357. 280. Song, B., Ye, L., Wu, S., & Jing, Z. (2020). Long non-coding RNA MEG3 regulates CSEinduced apoptosis and inflammation via regulating miR-218 in 16HBE cells. Biochemical and Biophysical Research Communications, 521, 368–374. https://doi.org/10.1016/j.bbrc. 2019.10.135. 281. Liang, W. J., et al. (2019). Long non-coding RNA MALAT1 sponges miR-149 to promote inflammatory responses of LPS-induced acute lung injury by targeting MyD88. Cell Biology International. https://doi.org/10.1002/cbin.11235. 282. Sun, G., Li, Y., & Ji, Z. (2019). Up-regulation of MIAT aggravates the atherosclerotic damage in atherosclerosis mice through the activation of PI3K/Akt signaling pathway. Drug Delivery, 26, 641–649. https://doi.org/10.1080/10717544.2019.1628116. 283. Zhao, Y., Zhao, J., Guo, X., She, J., & Liu, Y. (2018). Long non-coding RNA PVT1, a molecular sponge for miR-149, contributes aberrant metabolic dysfunction and inflammation

References

284.

285.

286.

287.

288.

289.

147

in IL-1beta-simulated osteoarthritic chondrocytes. Bioscience Reports, 38. https://doi.org/10. 1042/bsr20180576. Deng, W., Chen, K., Liu, S., & Wang, Y. (2019). Silencing circular ANRIL protects HK-2 cells from lipopolysaccharide-induced inflammatory injury through up-regulating microRNA-9. Artificial Cells, Nanomedicine, and Biotechnology, 47, 3478–3484. https://doi.org/10.1080/ 21691401.2019.1652187. Jiang, H., et al. (2018). Asymmetric expression of H19 and ADIPOQ in concave/convex paravertebral muscles is associated with severe adolescent idiopathic scoliosis. Molecular Medicine, 24, 48. https://doi.org/10.1186/s10020-018-0049-y. Ding, X. M., Zhao, L. J., Qiao, H. Y., Wu, S. L., & Wang, X. H. (2019). Long non-coding RNA-p21 regulates MPP(+)-induced neuronal injury by targeting miR-625 and derepressing TRPM2 in SH-SY5Y cells. Chemico-Biological Interactions, 307, 73–81. https://doi.org/10. 1016/j.cbi.2019.04.017. Hu, M. L., Wang, X. Y., & Chen, W. M. (2018). TGF-beta1 upregulates the expression of lncRNA UCA1 and its downstream HXK2 to promote the growth of hepatocellular carcinoma. European Review for Medical and Pharmacological Sciences, 22, 4846–4854. https://doi.org/ 10.26355/eurrev_201808_15620. Su, Y., et al. (2019). Macrophage-derived CCL18 promotes osteosarcoma proliferation and migration by upregulating the expression of UCA1. Journal of Molecular Medicine (Berlin), 97, 49–61. https://doi.org/10.1007/s00109-018-1711-0. Meydan, C., Bekenstein, U., & Soreq, H. (2018). Molecular regulatory pathways link sepsis with metabolic syndrome: Non-coding RNA elements underlying the sepsis/metabolic cross-talk. Frontiers in Molecular Neuroscience, 11, 189. https://doi.org/10.3389/fnmol.2018. 00189.

Chapter 7

Non-coding RNAs Related to Cardiometabolic Diseases and Associated to Cancer

Abstract Low miR-1, miR-7, miR-17, miR-26a, miR-29a, miR-30a, miR-34a, miR-124, miR-133, miR-143-145, miR-150, miR-378, miR-455, lincRNA-p21, and MEG3 are related to cancer. In contrast, high miR-9, miR-21, miR-130, miR-155, miR-221, HOTAIR, H19, LINC-ROR, MALAT1, MIAT, NEAT1, TUG1, UCA1, XIST, ZFAS1, ANRIL, ciRs-7, and PVT1 are related to cancer. High and low let-7, miR-146a, miR-181, miR-223, and GAS5 are associated with cancer. These noncoding RNA profiles allow a metabolic reprogramming in tumors to retain stemness and epithelial-mesenchymal transition, insulin sensitized state and angiogenesis. It also explains the shift from OXPHOS to glycolysis, the immune escape, and the prevention of apoptosis in tumors.

7.1 Mechanisms of Cancer Progression 7.1.1 Induction of Stemness Hypoxia induces transforming growth factor (TGF)-β that activates sirtuin (SIRT)-1, which induces MYC proto-oncogene, bHLH transcription factor (MYC), POU class 5 homeobox one or POU5F1 (OCT4), Nanog homeobox (NANOG), SRY-box transcription factor 2 (SOX2), and lin-28 homolog (LIN28) [1–5]. Loss of E-cadherin promotes Wnt signaling and β-catenin accumulation in the nucleus, inducing stemness. MYC, NANOG, OCT4, and SOX2 regulate stemness. Stemness is also induced by snail family transcriptional repressor 1 (SNAIL or SNAI) and twist family bHLH transcription factor (TWIST), also involved in epithelial to mesenchymal transition (EMT) [6–10]. SIRT2, however, inhibits β-catenin signaling and downregulates expression of Wnt target genes, while SIRT6 represses Wnt target genes by interacting with lymphoid enhancer-binding factor 1 and deacetylating histone 3 (Fig. 7.1.) Importantly, retaining stem cells is critical to maintaining the M2 phenotype of tumor-associated macrophages (TAMs). M2 TAMs promote the growth and motility Illustrations by Pieterjan Ginckels, Faculty of Architecture, KU Leuven, Ghent, Belgium. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 P. Holvoet, Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer, https://doi.org/10.1007/978-3-030-68844-8_7

149

150

7 Non-coding RNAs Related to Cardiometabolic Diseases …

Fig. 7.1 Role of non-coding RNAs in hypoxia-induced cancer progression. Hypoxia-mediated up-regulation of TGF-β via CASC11 induces SIRT1. SIRT1 maintains stemness by upregulating MYC, OCT4, NANOG, SOX2, and LIN28. The up-regulation of miR-9, miR-221, lncRNAs ES1, MALAT1, and MIAT promotes stemness. The inactivation of let-7 by LIN28 and the silencing of miR-1, miR-7, miR-29a, miR-30a by FEZF1-AS1, miR-34a by HOTAIR, NEAT1 and XIST, miR124, miR-133, miR-143, and miR-146a by PVT1 exacerbates stemness. NIFK-AS1 may revert the latter. In contrast, Let7-i-5p and miR-181a-2-3p repress stemness. TGF-β and SIRTs activate EMT inducers SMAD-2, -3, and 4, and transcription factors SNAIL, SLUG, TWIST, and ZEB. TGF-β also induces EMT through pathways that do not involve SMAD, like PI3K/AKT/mTOR signaling. The up-regulation of miR-21, miR-155, miR-221, H19, TUG1, UCA1, XIST, ZFAS1, and PVT1 induces EMT. Silencing of miR-1, miR-7 by SOX21-AS1, miR-17 by LINC01939, miR-26a by MALAT1, miR-30a by LINC00460, MALAT1 and XIST, miR-34a by CASC11 and HOTAIR, miR-124 by H19, MALAT1, NEAT1, UCA1, XIST and circ-HIPK3, miR-130, miR143-145 by LINC-ROR and SOX21-AS1, miR-150, miR-378, miR-455, lincRNA-p21, and MEG3 also enhances EMT. Besides, high miR-9 and low miR-29, silenced by H19, MIAT, and TUG1, promote EMT by repressing E-cadherin. In contrast, miR-181 b and lincRNA-p21 inhibit EMT. SIRT1 activates Wnt/β catenin signaling that activates stemness genes MYC, NANOG, OCT4, and SOX2, and induces EMT genes SNAIL and TWIST, closing a vicious circle. Further, Wnt/β catenin signaling leads to insulin sensitized state by activating IGF1/IGF1R and IRS signaling and downregulation of PTEN, leading to activation of PI3K/AKT signaling. Up-regulation of miR-155 and silencing of miR-7 by circ-HIPK3, miR-26a by TUG1, miR-30a by MALAT1, XIST and PVT1, miR-126 by XIST, miR-145 by circ-ZNF609, miR-455 and GAS5 activate IGF1/IGF1R and IRS signaling. MiR-9 and miR-17 block IGF1/IGF1R signaling. Up-regulation of miR-9, miR-17, miR21, miR-26a, miR-29, miR-130, miR-155, miR-221-222 by decreased circ-MTO1, and miR-223,

7.1 Mechanisms of Cancer Progression

151

 and decreased miR-145, and GAS5 inhibit PTEN, thereby activating PI3K/AKT. PTEN may be de-repressed by TUG1, silencing miR-26a, and UCA1. Increased PI3K/AKT signaling promotes glycolysis. The up-regulation of miR-155, LINC-ROR, and MACC1-AS1, both silencing miR145, MALAT1, TUG1, UCA1 silencing miR-125 and miR-143, and PVT1 silencing miR-143 facilitates glycolysis. The down-regulation of miR-1, miR-34a, and MEG3 exacerbates glycolysis. MiR-378 and lincRNA-p21 inhibit glycolysis and favor transition from glycolysis to OXPHOS. Glycolysis may be induced in a VEGF-dependent or VEGF-independent way, the latter involving DKK2. Increased PI3K/AKT signaling also induces angiogenesis. The increase of miR-9, miR-21, miR-130b, and XIST stimulates angiogenesis. The down-regulation of miR-26a, miR-29, silenced by PVT1, miR-34a, miR-124, miR-145, miR-150, silenced by ZFAS1, and miR-223 silenced by lncRNA F63 and circRNA_001587, and GAS5 exacerbates angiogenesis. An increase of miR-1792 and a decrease of miR-146a blocks angiogenesis. Insulin sensitized state is associated with decreased cell senescence and apoptosis. MiR-130a, miR-146a, HOTAIR, MALAT1, and ANRIL protect against apoptosis. The inactivation of let-7 by LIN28 and the silencing of miR-9 by MEG3, NEAT1, and TUG1, miR-17, miR-26a, miR-29 by H19, miR-30a by NORAD and PVT1, miR34a by LINC-ROR, miR-133 by MIAT, NEAT1 and XIST, miR-145 by TUG1 and BRE-AS1, and miR-150 by MIAT, ZFAS1, and PVT1 decreases cancer cell senescence and death. In contrast, the up-regulation of miR-124, miR-181a/d and miR-378, due to the down-regulation of GAS5, and the down-regulation of miR-146a induces apoptosis. The survival of cancer cells is also due to their immune escape. Anti-tumor immunity is suppressed by inducing M2 macrophages, MDSCs, and Treg cells and reducing cytotoxic T cells. The increase of let-7e, miR-9, miR-21, miR-30a, miR125, miR-146a/b, miR-181a, miR-223, and HOTAIR lower anti-tumor immunity. The silencing of let-7 by H19 and ANRIL, miR-17, miR-26a, miR-34a, miR-150 by PVT1, and miR-181b, also lowers anti-tumor immunity. MiR-33, miR-130, and miR-155 decrease immune escape by shifting M2 to M1 macrophages. Inflammatory cytokines change the composition of ECM related to EMT. EMT, insulin-sensitized state, low anti-tumor immunity, and high angiogenesis induce cancer cell proliferation. MiR-21, miR-130, miR-181a/d, miR-221-222, miR-223, by down-regulation of GAS5 or vice versa, H19, MALAT1, NEAT1, TUG1, UCA1, XIST, ZFAS1, and PVT1 increases cancer cell proliferation. Silencing of let-7a by ANRIL, miR-17 by BLACAT1, HNF1A-AS1, HOTAIR, H19, NEAT and cSMARCAS, or the up-regulation of miR-17 by NEAT1 and down-regulation of circ-RNAs circ-ITCH and circ-MTO1 may induce proliferation pending on the tumor type. Silencing of miR-26a by MALAT1, miR-29, miR-126 by PVT1, miR-145 by KCNQ1OT1, TUG1, and ZEB1-AS1, miR-146a, miR-181a by circ-ANAPC7, and miR-378 exacerbate proliferation. Increased non-coding RNAs are in red; decreased in green

of mesenchymal cells, tumor angiogenesis, immune escape. Similarly, hypoxia induces the differentiation of M2 myeloid suppressor cells (MDSCs). They facilitate immune escape by promoting Treg cell proliferation and phenotypic switch from M1 toward M2 macrophages [11]. Signal transducing and activator of transcription (STAT)-3 drives MDSC expansion, preventing differentiation of monocytic MDSC to macrophages and dendritic cells (DCs) [12, 13]. Leptin and fatty acid metabolism induce MDSCs, which promote tumor progression but prevent dysregulation of glucose uptake and insulin signaling associated with obesity [14] (Fig. 7.1).

7.1.1.1

Non-coding RNAs and Stemness

LncRNA cancer susceptibility 11 (CASC11) promotes TGF-β1, increasing cancer cell stemness [15]. Induction of miR-9 and miR-221 maintained the mesenchymal stem-cell potential in non-invasive MCF-7 breast cancer cells [16]. The polycomb

152

7 Non-coding RNAs Related to Cardiometabolic Diseases …

repressive complex 1 (PRC1) maintains the stem cell markers OCT4 and CD133 in gastric cancer tissues by up-regulating miR-21 [17]. The long intergenic non-protein coding RNA 1108 (LncRNA ES1) induces stemness and reduces cellular senescence using OCT4/SOX2. The latter down-regulate miR-302 and miR-106b [18, 19]. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) enhances the stability of SOX2 and silences miR-20b-5p, derepressing OCT4, increasing stemness. Stemness is reinforced by the up-regulation of urothelial cancer-associated 1 (UCA1) [20–22]. High levels of myocardial infarction associated transcript (MIAT) are associated with an increase of OCT4 [23]. Wnt/β-catenin up-regulates the stemness inducer lin-28 homolog (LIN28), which suppresses mature let-7 by post-transcriptional repression [24, 25]. Downregulation of miR-7 induces stemness through activation of the Krüppel-like zinc finger transcription factor (KLF)-4/phosphatidylinositol 3-kinase (PI3K)/AKT serine/threonine kinase 1 (AKT)/p21 pathway [26, 27]. The down-regulation of miR-29a in triple-negative breast cancer is associated with increased expression of stemness regulators OCT4, NANOG, and SOX2 [28]. TGF-β1-induced decrease of miR-30a, possibly silenced by the fasciculation and elongation protein zeta 1 (FEZF1) antisense RNA 1 (FEZF1-AS1), is associated with induction of NANOG, activation of Wnt/β-catenin and PI3K/AKT pathway, resulting in insulin-sensitized state and cancer cell proliferation [29–31]. Low miR-34a-5p, silenced by the nuclear paraspeckle assembly transcript 1 (NEAT1) and X inactive specific transcript (XIST), correlates with high stemness inducer LIN28B, high expression of SIRT1, and activation of Wnt/β-catenin pathway [32–35]. Let-7i-5p and miR-181a-2-3p inhibited cervical cancer stem cells by silencing SOX2 [36]. MiR-145 represses SOX2, NANOG, and OCT4, usually related to cancer cells’ pluripotency [37] (Fig. 7.1). HOX transcript antisense RNA (HOTAIR) up-regulates SOX2, which is targeted by miR-34a [38]. Low miR-124 is associated with the maintenance of stemness with the expression of CD44 and SOX9 [39]. The decrease of miR-133, like the decrease of miR-1, induces the RUNX family transcription factor 1 (RUNX1 or EVI-1), associated with the proliferation of stem cells [40, 41]. Low miR-143 is associated with stemness by inducing SOX2 [42]. Circ-RNA derived from PVT1 oncogene (PVT1) silences miR-146a and increases the expression of 5-lipoxygenase activating protein and cytochrome c oxidase subunit II (COX2), thereby increasing stemness. Restoration of miR-146a also resulted in decreased cancer cell leukotriene B4 production. Thus, miR-146a is an endogenous dual inhibitor of amino acid metabolism in lung cancer cells by regulating both prostaglandin and leukotriene production through direct targeting of the COX2 [43, 44]. The silencing of miR-146a may be reverted by the nucleolar protein interacting with the FHA domain of MKI67 (NIFK) antisense RNA 1 (NIFK-AS1), especially in tumor-associated macrophages [45]. Overexpression of miR-146b attenuates stemness by inhibiting the tumor protein p53 pathway corepressor 1 (lincRNA-p21)/β-catenin pathway [46]. MiR-221-3p and miR-221-5p act as anti-stemness miRNAs by targeting OCT4, NANOG, and SOX2 mRNAs in embryonic stem cells [47] (Fig. 7.1).

7.1 Mechanisms of Cancer Progression

153

7.1.2 Induction of EMT Hypoxia induces TGF-β that activates SIRT1, which is a positive regulator of EMT in tumors. EMT is the conversion of epithelial cells to mesenchymal cells, contributing to tissue remodeling during development, wound repair, and cancer metastasis. TGFβ signaling induces EMT through SMAD family member (SMAD). Upon ligand binding, cell surface complexes of type-II and two type-I receptors phosphorylate and activate SMAD2 and SMAD43. Activated SMADS form complexes with SMAD4 and regulate transcription of EMT-inducing transcription factors, SNAIL and snail family transcriptional repressor 2 (SLUG or SNAI2), the zinc-finger E-box-binding homeobox (ZEB), and TWIST. They promote the transcription of genes typically expressed in mesenchymal cells, such as N-cadherin, vimentin, and fibronectin. On the contrary, epithelial markers E-cadherin, claudins, occludins, and cytokeratins are suppressed. SIRT1 is recruited by ZEB1 to the E-cadherin promoter to cause transcriptional repression [48, 49]. Similarly, SIRT1 interacts with TWIST to silence the E-cadherin promoter [50]. SIRT1 may mediate the recruitment of SIRT7 to the E cadherin promoter and thereby repress E-cadherin, in addition to direct up-regulation of SLUG expression by SIRT7 [51, 52]. In contrast, SIRT1 has been identified as an EMT repressor by inhibiting TGF-β signaling by deacetylating SMAD4, thereby decreasing metalloproteinase (MMP) transcription and E-cadherin degradation [53]. SIRT2 activates AKT/glycogen synthase kinase 3β (GSK3β)/β-catenin signaling to promote EMT in hepatocellular carcinoma. Deacetylation of SLUG by SIRT2 promotes SLUG protein stability and repression of SLUG target genes, including E-cadherin [54]. SIRT4 up-regulates E-cadherin and decreases vimentin expression, inhibiting EMT [55]. Importantly, activation of EMT programs confers stem-like traits on healthy and neoplastic cells [56, 57]. TGF-β also activates other signaling pathways that do not involve SMADS, like the PI3K/AKT/mechanistic target of rapamycin kinase (mTOR) pathway and small GTPases [49] (Fig. 7.1).

7.1.2.1

Non-coding RNAs and EMT

Higher levels of miR-21, due to down-regulation of the maternally expressed 3 (MEG3), induce EMT by up-regulating SNAI1 or SNAIL, N-cadherin β-catenin, and down-regulating E-cadherin [58]. TGF-β1 elevates the expression of miR-155 in cancer cells through SMAD3 and SMAD4, associated with miR-155-mediated loss of c/EBP-β shifting TGF-β action from growth inhibition to EMT [59]. SLUG/βcatenin increases miR-221 in hypoxic cancer stem cells, thereby increasing IL8 and TNF-α, enhancing TGF-β-mediated EMT [60–63]. H19 promotes TGF-β-induced EMT by silencing miR-29, miR-194, miR-370-3p, and miR-484 and increasing expression of β-catenin, MYC, CCN (CCN)-D1, and CDK14 [64–70]. Taurine upregulated 1 (TUG1) promotes EMT and stemness through up-regulating SIRT1 and Wnt/β-catenin signaling by sponging miR-138-5p. Besides, TUG1 activates the Janus kinase 2 (JAK2)/STAT3 pathway, up-regulates ZEB1, induces SMAD2 and SMAD3

154

7 Non-coding RNAs Related to Cardiometabolic Diseases …

phosphorylation, TGF-β, TGF-β receptor, MMP-2, and MMP9, and decreases Ecadherin expression, possibly by sponging miR-29. TGF-1β, H19, and MIAT also repress miR-29 [71–74]. UCA1 promotes EMT and tumor metastasis by silencing miR-203, thereby inducing ZEB2, and by sponging miR-185-5p, thereby increasing Wnt/β-catenin signaling [75, 76]. XIST induces EMT by silencing miR-200b and miR-429, thereby increasing expression of ZEB1 and activating the notch receptor 1 (NOTCH1) signaling by silencing miR-137 [77]. High ZNFX1 antisense RNA 1 (ZFAS1) in tumors also induces ZEB1 expression and promotes EMT [78]. PVT1 promotes EMT by inducing TGF-β/SMAD signaling and increasing SNAIL, SLUG, β-catenin, N-cadherin, and vimentin while decreasing E-cadherin [79]. The silencing of miR-1 by MALAT1 is associated with increased proliferation and viability of cancer cells and EMT by activation of PI3K/AKT/mTOR signaling [80–82], an increase of Wnt/β-catenin signaling via induction of the E2F transcription factor 5 that interacts with tumor suppressor proteins p130 and p107, and by inducing cyclin-dependent kinase (CDK)-14 [83–86]. The silencing of miR-7 by SOX21 antisense divergent transcript 1 (SOX21-AS1), miR-17 by the long intergenic non-protein coding RNA 1939 (LINC01939), and miR-26a by MALAT1 increases EMT [87–89]. The hypoxia-sensitive long intergenic non-protein coding RNA 460 (LINC00460), MALAT1, and XIST silence miR-30a, inducing EMT by up-regulating ZEB2 [90–94]. Silencing of miR-34a and miR-143-145 by CASC11 promotes EMT by suppressing the degradation of SNAIL mRNA. HOTAIR also silences miR-34a, resulting in increased Wnt/TGF-β/SMAD3/4 signaling [95– 98]. The H19 imprinted maternally expressed transcript (H19), MALAT1, NEAT1, UCA1, XIST, and the homeodomain interacting protein kinase 3 circ-RNA (circHIPK3) silence miR-124, increasing TRAF6 and SNAIL, promoting EMT [99– 106]. In particular, macrophage-derived IL8 induces MALAT1 that promotes EMT and metastasis by inducing PI3K/AKT signaling through the sponging of miR-124 [107–110]. P53 promotes EMT by directly binding to the promoter of miR-130b that otherwise would silence ZEB1 [111]. Long intergenic non-protein coding RNA, a regulator of reprogramming (LINC-ROR), and SOX21-AS1 also silence miR-145 and de-repress ZEB2 [112, 113]. Decreased expression of miR-150 is associated with the up-regulation of GLI family zinc finger one and SNAIL, which promote EMT [114]. Low miR-378 expression results in de-repression of BMP2 associated with gastric cancer cell invasion and EMT [115, 116]. Low miR-455 increases TGF-β signaling and EMT by up-regulating ZEB1 [117, 118]. The decrease of lincRNA-p21 increases EMT, cell proliferation, migration and invasion, and transition of the cell cycle from G1, and inhibits apoptosis by changing the p21/p53 ratio [119–121]. Overexpression of lincRNA-p21 inhibits tumor invasion through mediating NOTCH-induced EMT [122]. TGF-β-induced repression of maternally expressed 3 (MEG3) in breast cancer tissues is associated with EMT and lymph node metastasis resulting from decreased E-cadherin and increased ZEB [123, 124]. MiR-9 downregulates E-cadherin. This repression results in the activation of Wnt/β-catenin signaling and the promotion of EMT and tumor angiogenesis by

7.1 Mechanisms of Cancer Progression

155

vascular endothelial growth factor (VEGF) [125]. However, miR-9 may inhibit EMT by targeting TWIST [126]. MiR-181b may repress EMT by silencing NFκB-targeting genes [127]. High miR-223 in tumors induces or inhibits EMT in a context-dependent manner [128] (Fig. 7.1).

7.1.3 Induction of Insulin Sensitized State, Cancer Cell Proliferation, and Protection Against Apoptosis Hypoxia-induced insulin-like growth factor 1 (IGF1R) signaling increases phosphorylation of insulin substrate receptors (IRS) and PI3K/AKT and increases glucose uptake and insulin signaling. Phosphorylated AKT enhances cell proliferation and cell survival and reduces apoptosis [4, 129]. Activation of the Wnt signaling pathway is associated with reduced phosphatase and tensin homolog (PTEN) and increased PI3K/AKT signaling, thereby favoring an insulin-sensitized state [130–132]. PTEN blocks the PI3K/AKT pathway by GSK3β-regulated degradation of β-catenin, rendering cancer cells more sensitive to apoptosis [133, 134]. PTEN inhibits Wnt signaling by blocking the AKT pathway and reducing the expression of IGF1R [135] (Fig. 7.1).

7.1.3.1

Non-coding RNAs and Insulin Sensitized State

MiR-155 promotes insulin-like growth factor 1 (IGF1) signaling, decreases GSK3β, and increases β-catenin [136]. MYB proto-oncogene, transcription factor (MYB)induced circHIPK3 silences miR-7, while TUG1 silences miR-26a, and PVT1 silences miR-30a, thereby inducing IGF1/IGF1R signaling [137–140]. The decrease of miR-455-5p up-regulates IGF1R and is associated with increased solute carrier family two member one (SLC2A1 or GLUT1) expression and glucose uptake [141]. Down-regulation of growth arrest-specific 5 (GAS5) in lung adenocarcinoma increases IGF1R proteins’ expression [142]. Silencing of miR-30a by the hypoxia-sensitive LINC00460 and by MALAT1 and XIST is associated with activation of the LIN28B/ insulin substrate receptor (IRS)-1 and up-regulating ZEB2 [90]. XIST also acts as a ceRNA of miR-126, thereby inducing IRS1/PI3K/AKT pathway in glioblastoma cells [143]. The circRNA derived from zinc finger protein 609 (circ-ZNF609) sponges miR-145-5p, thereby elevating p70S6K1 expression that plays a crucial role in activating the IRS [144]. MiR-9 and miR-155 down-regulate PTEN, leading to insulin sensitivity by activating PI3K/AKT/mTOR signaling [125]. However, glucose-induced miR-9 may block IGF1R and, thereby, insulin signaling [145]. MiR-17 inhibits PTEN, thereby activating AKT/mTOR signaling [146]. However, mir-17-5p completely abrogated

156

7 Non-coding RNAs Related to Cardiometabolic Diseases …

IGF1R-mediated, anchorage-independent growth of breast cancer cells by targeting the amplified in breast cancer 1 [147]. MiR-21, miR-26a, and miR-29 also repress PTEN [148–152]. TUG1 may, however, revert the action of miR-26a [153]. The miR-130 family directly targets PTEN, increasing pAKT [154, 155]. Higher miR-221-222 due to lower expression of circ-MTO1 inhibits PTEN [156]. However, the HIF-1α- and TGF-β1 up-regulated UCA1 reverts this inhibition [157]. Macrophage-derived exosomes enriched in miR-223 induce cancer cell proliferation through the PTEN–PI3K/AKT axis [158]. A decrease of miR-145, miR-125b, miR-136, and miR-381, leads to loss of PTEN and enhanced expression of MYC and PI3K, and β-catenin signaling [159]. Downregulation of GAS5 is associated with an increase of miR-205 that blocks PTEN, associated with increased PI3K/AKT signaling [160]. MiR-181a/d promotes growth factor-induced AKT phosphorylation [161]. H19 induces PI3K/AKT signaling by silencing miR-106b-5p [162]. LINC-ROR induces AKT signaling [163]. UCA1 facilitates phosphorylation of the cAMP-responsive element-binding protein and activates PI3K/AKT signaling [164]. The decrease of MEG3 down-regulates p53 and activates PI3K/AKT/mTOR signaling [165, 166]. Besides, down-regulation of MEG3 increases miR-27 and miR-125b, thereby decreasing the expression of the PH domain and leucine-rich repeat protein phosphatase 2 and activating AKT signaling and cancer cell proliferation (Fig. 7.1).

7.1.4 Induction of Glycolysis Cancer cells use glycolysis instead of oxidative phosphorylation (OXPHOS) to sustain their energy demand even when oxygen supply is adequate. This phenomenon is known as aerobic glycolysis or the “Warburg effect” [167, 168]. This low dependence on cancer cells’ mitochondrial activity avoids mitochondrial dysfunction in cancer cells, favoring an increased uptake of glucose through GLUT1 and conversion of pyruvate into lactate to generate energy, which correlates with a poorer prognosis and more aggressive phenotypes [169, 170]. Overall, Wnt/SNAIL/βcatenin signaling is implicated in increased glucose uptake and suppressed mitochondrial respiration through the Wnt/β-catenin target gene MYC. Herein, Wnt controls pyruvate dehydrogenase kinase (PDK)-1, an enzyme that inhibits mitochondrial OXPHOS by reducing pyruvate’s conversion into acetyl-CoA and thereby maintaining the glycolysis dependent nature of tumor cells [171, 172]. The loss of repression of glucose-6-phosphate-dehydrogenase (G6PD) activates glycolytic genes. Besides, the oncogenes p53, MYC and KRAS proto-oncogene, GTPase (KRAS); the PI3K/AKT, protein kinase AMP-activated catalytic (AMPK), and HIF-1α signaling pathways; and sirtuins participate in the regulation of glycolysis that is associated with cancer cell proliferation and metastasis and is inhibited by FOXO3a [173–175]. G6PD is also associated with activation of NOTCH signaling and proliferation and migration by affecting EMT [176].

7.1 Mechanisms of Cancer Progression

157

VEGF stimulation led to a metabolic transition from mitochondrial OXPHOS to glycolysis in pancreatic cancer. HIF1α and NRP1 protein levels were both increased after VEGF stimulation. The down-regulation of neuropilin 1 (NRP1 or VEGF165R) reduced glycolysis in pancreatic cancer cells [177, 178]. The Dickkopf associated protein 2 (DKK2) promotes tumor metastasis and angiogenesis through a VEGFindependent but glycolysis-dependent pathway [179] (Fig. 7.1).

7.1.4.1

Non-coding RNAs and Glycolysis

The increased miR-155 expression is associated with decreased GSK3β and increased β-catenin expression, thereby increasing glycolysis and inhibiting apoptosis by targeting SOCS3 [136, 180]. Hypoxia-responsive LINC-ROR sponges miR-145, thereby enhancing HIF-1α and pyruvate dehydrogenase kinase 1 (PDK1) linked to glycolysis [181, 182]. The silencing of miR-145-5p by the TGF-β1-induced lncRNA MET transcriptional regulator MACC1 antisense (MACC1-AS1) enhances glycolysis and anti-oxidation, coordinated by the AMPK/LIN28 pathway [183–186]. MALAT1 up-regulates glycolytic genes and downregulates gluconeogenic enzymes [187]. TUG1 silences miR-600 and thereby triggers the AMPK/GSK3-β/β-catenin cascade resulting in enhanced glycolysis [188, 189]. UCA1 promotes glycolysis by activating mTOR and HK2 by activating STAT3 and repression of miR-125 and miR143 [157, 190–196]. PVT1 positively regulates hexokinase 2 expression by acting as a ceRNA of miR-143, which may be reinforced by the forkhead box M1 circ-RNA (circ-FOXM1) [197, 198]. A decrease of miR-1 and miR-122 results in loss of repression of glucose-6phosphate-dehydrogenase and an increased glycolysis [199]. A decrease of miR-34a leads to the de-repression of LDHA, thereby inducing glycolysis [200]. A decrease of MEG3 is associated with enhanced aerobic glycolysis by induction of MYC [201]. MiR-378* causes a shift from glycolysis to OXPHOS by inhibiting the expression of the estrogen-related receptor (ERR)-γ [202]. LincRNA-p21 inhibits β-catenin signaling activity, thereby attenuating the viability, self-renewal, and glycolysis of colorectal cancer cells [203] (Fig. 7.1).

7.1.5 Induction of Angiogenesis Hypoxia induces angiogenesis through the HIF-1α/VEGF axis, involving Wnt ligands [204]. Low oxygen levels promote angiogenesis by inducing angiopoietin, basic fibroblast growth factor (bFGF), hepatocyte growth factor (HGF), and plateletderived growth factor (PDGF) [205, 206]. Angiogenesis is necessary for providing O2 to a growing tumor and for metastasis [206]. PDK1 not only inhibits mitochondrial respiration and induces Wnt-mediated glycolysis, but it also induces vessel growth [172] (Fig. 7.1).

158

7.1.5.1

7 Non-coding RNAs Related to Cardiometabolic Diseases …

Non-coding RNAs and Angiogenesis

MiR-9 induces VEGF and thereby promotes tumor angiogenesis [125]. MiR-21 suppresses transforming growth factor-induced mRNA, enhancing endothelial tube formation and angiogenesis [175]. MiR-130b-3p promotes angiogenesis by targeting homeobox that otherwise induces CD31 and CD34 [207]. XIST promotes angiogenesis by silencing miR-429 [208]. PVT1 promotes angiogenesis by silencing miR-29 and miR-128, thereby upregulating VEGF [209, 210]. MYC also downregulates miR-29, up-regulating the B7 family of immune checkpoint homolog 3 (B7-H3), increasing angiogenesis [211]. TGF-β1 secreted by tumor macrophages down-regulates miR-34a, thereby inducing angiogenesis and invasion of colorectal cancer cells via up-regulating VEGF [212]. Decrease of miR-124 in bladder cancer increased CDK4 associated with increased cancer cell viability and angiogenesis rate [213]. Low miR-145 is associated with increased HIF-2α and angiogenesis in neuroblastoma [214]. MiR-150-5p inactivated VEGFA/VEGFR2 and the downstream AKT/mTOR signaling pathway in CRC [215]. Down-regulation of miR-150 by ZFAS1, MYC, and miR-155 is associated with cancer cell proliferation, migration, invasion, and angiogenesis through increased VEGFA/VEGFR2 expression and downstream AKT/mTOR signaling [215–217]. Lnc-RNA F630028O10Rik (RIKEN cDNA F630028O10; abbreviated as F63) silenced miR-223, down-regulating VEGFA- mediated angiogenesis [218]. CircRNA_001587 inhibits prostate cell angiogenesis and tumorigenesis by impairing miR-223-mediated inhibition of solute carrier family 4 member 4 [219]. A decrease of GAS5 leads to the activation of the Wnt/β-catenin signaling pathway, associated with more angiogenesis, tumor growth, and metastasis [220]. MiR-17-92 targets HIF1α and VEGFA and suppresses tumor progression by inhibiting angiogenesis [221]. MiR-26a/b directly binds to the 3 -UTR of HGF mRNA, repressing the HGF-VEGF pathway and inhibiting angiogenesis [222]. The decrease of miR-26a in gastric cancer cells de-represses the HGF-VEGF pathway and restores angiogenesis [222]. Injection of a miR-146a-5p antagomir inhibited tumor growth by reducing angiogenesis and inducing apoptosis. Thus, miR-146a-5p functions as a control switch between angiogenesis and cell death [223] (Fig. 7.1).

7.1.6 Repression of Anti-tumor Immunity and Apoptosis The tumor comprises tumor cells and fibroblasts, stromal, vascular, immune cells, and extracellular matrix (ECM) [224]. The infiltration of immune cells both promote and delay tumor progression. Anti-tumor immunity is mostly dependent on CD8+ cytotoxic T lymphocytes, which produce cytokines, cytotoxic perforins, and granzymes, promoting cancer cell apoptosis [225]. Cancer cells evade immune suppression by down-regulating tumor antigenicity, suppressing cytokines, and increasing Treg cells [226, 227]. Activation of Wnt/β-catenin ablate CD8+ T-cell function and suppress anti-cancer immunity [228]. NKT cells also cause anti-tumor activity by releasing

7.1 Mechanisms of Cancer Progression

159

interferon (IFN)-γ and interleukin (IL)-4. NKT cells share properties with adaptive T cells, and their maturation again depends on Wnt ligands and β-catenin, which suppress IFN-γ production [229–231]. Further, Wnt signaling is involved in immune evasion in tumors by driving the expression of programmed death-ligand 1 (PD-L1), which is recognized by inhibitory immune checkpoint receptor PD-1 on activated T cells [232]. Further, the Wnt/β-catenin pathway is closely associated with chronic inflammation and oxidative stress in cancers by opposing the peroxisome proliferator-activated receptor (PPAR)-γ signaling [233]. IL-1β, IL2, and tumor necrosis factor (TNF)-α render the inflammatory microenvironment more tumorigenic. The pro-inflammatory mediators released during the chronic inflammation induce NFκB, MAPK, nuclear factor erythroid 2-related factor 2, PI3K, JAK/STAT, and Wnt/β-catenin [234]. Induction of Wnt is associated with Wnt ligands’ secretion that stimulates tumor-associated macrophages to produce IL-1β, thus driving systemic inflammation [235]. TAMs are mainly alternatively activated M2 macrophages with immunosuppressive and tumorpromoting capabilities. Hypoxic environment and hypoxia-treated glioma cell supernatants can polarize macrophages toward an M2 phenotype through TGF-β [236]. TNF-α derived from M2 tumor-associated macrophages promotes EMT and cancer stemness through the Wnt/β-catenin pathway. Reprogramming TAMs towards classically activated M1 macrophages may thwart tumor-associated immunosuppression and unleash anti-tumor immunity [237] (Fig. 7.1). The up-regulation of Wnt/β-catenin signaling may be due to NOTCH blockade, promoting the proliferation and pro-oncogenic cytokine production of Kupffer cell-like TAMs in the liver, facilitating cancer progression and metastasis [238]. Tumor-infiltrating MDSCs reduce NOTCH1/2 [239]. MDSCs are immature myeloid cells recruited by VEGF and IL-1β to sites of inflammation and the tumor microenvironment to prevent immune-mediated damage [240, 241] (Fig. 7.1).

7.1.6.1

Non-coding RNAs and Anti-tumor Immunity

Low levels of miR-181b are associated with EGFR-dependent vascular cell adhesion molecule (VCAM)-1 expression and monocyte infiltration [242]. The increase of let-7e, miR-125, miR-146a, miR-146b, and miR-155 induces differentiation of monocytes to MDSCs, increasing the resistance to immunotherapy in melanoma patients [243]. Besides, miR-146a is involved in the induction by STAT3 of tumor-derived factors, such as IL-6, IL-10, and VEGF, to ensure persistent STAT3 activation in the tumor microenvironment through cross-talk between tumor cells and tumor-associated immune cells. Activated STAT3 by this “positive feedback loop” further promotes the expression of growth factors and angiogenic factors, which then represses the effects of the host anti-tumor responses and accelerates tumor growth and metastasis [244]. MiR-9 also induces the differentiation of MDSCs by targeting RUNX1 [245]. Exosome-derived miR-9, miR30a, and miR-181a activate the JAK/STAT signaling pathway via targeting SOCS3, thereby promoting the expansion of MDSCs [246, 247]. By down-regulating JAK2

160

7 Non-coding RNAs Related to Cardiometabolic Diseases …

and STAT1, miR-21 inhibits the IFN-γ-induced STAT1 signaling pathway required for macrophage M1 polarization. Inhibition of STAT1 by miR-21 also results in the down-regulation of programmed cell death-1 (PD1)/PD-L1, which induces the immune system to escape [248, 249]. MiR-21-5p-enriched exosomes from hypoxiaprimed mesenchymal cells promoted lung cancer development by reducing apoptosis and promoting macrophage M2 polarization [250]. Also, miR-21 induces MDSC differentiation [251]. MiR-155 inhibits the expression of p38 in DCs, and thereby their anti-tumor response. MiR-155 also inhibits CD8+ T cells’ anti-tumor activity by targeting FOXO3A, up-regulating AKT and STAT5, and suppressing T cells’ proliferative and invasive activities. Further, the interaction between STAT5 and mTOR is crucial for maintaining FoxO3a-positive Treg cells [252–254]. MiR-223, enriched in microvesicles of IL4 activated M2 macrophages, induces the accumulation of M2 macrophages [255, 256]. HOTAIR also attracts macrophages, which induce cancer cell proliferation, and differentiates MDSCs, allowing immune escape and decreasing cancer cell death [257, 258]. Small LIN28 inhibitors increased let-7 leading to reactivation of anti-tumor immunity. Besides, they inhibited cancer cell proliferation, migration, and invasion by inhibiting downstream gene MYC [259–262]. Suppression of let-7 increased M2 macrophages and abated recruitment of activated cytotoxic T lymphocytes [263]. Reciprocally, Wnt pathway activation leads to an increase of H19, which in turn decreases Let-7c bioavailability. In contrast to H19, miR-146a increases the Let-7c level through degrading LIN28 [264, 265]. ANRIL in prostate cancer is associated with increased TGF-β1 and pSMAD2 and decreased pSMAD7 by suppressing let-7a [266]. The decrease of miR-17 results in increased reactive oxygen species (ROS) and STAT3, thereby inducing MDSCs [267]. UCA1 represses miR-26a/b, miR-193a, and miR-214, thereby inducing PD-L1 and cancer cell immune escape [268]. Further, the activation of NFκB signaling and inflammation in non-small cell lung cancer cells decreases mir-26a [269]. The actin filament associated protein 1 (AFAP1) antisense RNA (AFAP1-AS1) silenced miR-26a, retaining the M2 macrophage phenotype [270]. The inhibition of protein tyrosine phosphatase-1B induces M2 macrophage polarization via reducing miR-26a, enhancing mitogen-activated protein kinase phosphatase-1 (MKP1) expression [271]. Low miR-34a is also associated with decreased anti-tumor immunity by increasing C–C motif chemokine ligand 22 (CCL22), which recruits Treg cells to facilitate immune escape [272–274]. PVT1 silences miR-150 resulting in overexpression of hypoxia-inducible protein 2 that promotes the immune escape from NK cells through an IL13/STAT3 signaling pathway [275, 276]. Low expression of miR-150 is also associated with tumor invasion induced by CCL20 and IL22, which also lowers anti-tumor immunity and protects stemness [277, 278]. PVT1 also increases the production of inflammatory cytokines IL8, TNF-α, and IL-1β by sponging miR-149 [279]. Overexpression of miR-130 and miR-33 in exosomes decreases tumor progression by shifting macrophage polarization from M2 to M1 phenotype [280]. MiR-155 reprograms TAMs to pro-inflammatory, anti-tumor macrophages, possibly through the targeting of CCAAT enhancer-binding protein (c/EBP)-β [281] (Fig. 7.1).

7.1 Mechanisms of Cancer Progression

7.1.6.2

161

Non-coding RNAs and Cancer Cell Apoptosis

MiR-107/miR-130a impeded apoptosis through targeting PTEN. Circ-ZFR promoted apoptosis by sponging miR-130a/miR-107 [282]. MiR-146a silences the DNA damage-inducible transcript 3, a mediator of endoplasmic reticulum stress that usually promotes stress-induced apoptosis [283]. Down-regulation of miR-146a induces apoptosis by inducing TRAF6 and NF-κB protein expression, increased IL6, IL17A, IL21 levels, and enhanced p-STAT3 protein expression. The inhibition of TRAF6 attenuated anti-miR-146a effects on Th17 cell differentiation’s function to modulate apoptosis [284]. HOTAIR silences miR-218, thereby inducing cancer cell viability by upregulating VOPP1 WW domain-binding protein and preventing apoptosis through oxidative cellular injury [285, 286]. MALAT1 increases β-catenin by silencing miR142-3p, increasing proliferation and migration, and inhibiting apoptosis of non-small cell lung cancer cells [287]. ANRIL inhibits apoptosis by silencing miR-144 [288]. Stemness-inducers LIN28a and LIN28B inhibit let-7 and promote an insulinsensitized state that protects against cell senescence [289, 290]. MiR-9 induces apoptosis. However, MEG3, NEAT1, and TUG1 silence miR-9, protecting cancer cells against apoptosis. The silencing of miR-9 also promotes the invasion of cancer cells by inducing β-galactoside α-2,6-sialyltransferase 1 that increases the expression of IL8 [291–294]. Suppression of miR-17–92 and miR-106b up-regulates BCL2 like 11 (BCL2L11 or BIM), which is a significant determinant for initiating the intrinsic apoptotic pathway. Under physiological conditions, BIM is essential for shaping immune responses where its absence promotes autoimmunity. However, too early BIM induction eliminates cytotoxic T cells prematurely, resulting in chronic inflammation and tumor progression [295]. The decrease of miR-26a in hepatocellular carcinoma is associated with reduced p53-induced mitochondrial apoptosis, contributing to chronic lymphocytic leukemia development [296, 297]. H19 inhibits apoptosis by sponging miR-29b-3p, thereby enhancing the MCL1 apoptosis regulator, BCL2 family member [298]. Further, the decrease of miR-29 up-regulates FGF2, thereby inhibiting apoptosis [299]. Non-coding RNA activated by DNA damage (NORAD) and PVT1 inhibit apoptosis by silencing miR-30a and miR-16-5p and up-regulating ADAM metallopeptidase domain 19 (ADAM19) [138, 300]. MiR-34a induces apoptosis by targeting high mobility group box 1 [301]. However, LINC-ROR may prevent apoptosis by silencing miR-34a, thereby decreasing NOTCH1 and BCL2 expression [302]. MIAT, NEAT1, and XIST silence miR-133 in tumors [303–306]. Decrease of miR-133, together with that of miR-1 and miR-218, is associated with overexpression of TNF-related apoptosis-inducing ligand (TRAIL). TRAIL is a potent anti-cancer agent specifically targeting cancerous cells while sparing healthy cells. However, resistance to TRAIL occurs. Tumors become resistant to TRAIL-induced apoptosis by the effect of TRAIL on T cells [307]. Low miR-133 is also associated with increased p21, thereby increasing mRNA and protein expressions of proliferating cell nuclear antigen, antigen identified by monoclonal antibody Ki 67 (Ki67), CCNE, CDK2, and BCL2, and decreasing expression of BCL2 associated X, apoptosis regulator (BAX), resulting in increased proliferation and decreased apoptosis [308–311].

162

7 Non-coding RNAs Related to Cardiometabolic Diseases …

Further, a low miR-143-145 expression is associated with reducing caspase 3 and 7 activity and induction of BCL2, protects against apoptosis, and cellular cytotoxicity [312, 313]. TUG1 increases cancer cell viability, proliferation, and migration and decreases apoptosis through the silencing of miR-145-5p that inhibits Rho-associated coiled-coil containing protein kinase 1 [314, 315]. In contrast, overexpression of the BRISC and BRCA1 A complex member 2 (BABAM2) antisense RNA 1 (BABAM2AS1 or BRE-AS1) induces miR-145 to inhibit proliferation and promote apoptosis of prostate cancer cells [316, 317]. MIAT, ZFAS1, and PVT1 silence miR-150, associated with increased expression of the MYB proto-oncogene, transcription factor and the RAB9A member Ras oncogene family resulting in increased proliferation, migration, and invasion of cancer cells, and protection against apoptosis by de-repression of NOTCH3 [217, 318–322]. MiR-124 suppresses programmed cell death (PDCD)-6 expression, inducing apoptosis [323]. MiR-181a/b induce apoptosis by targeting BCL2 [324, 325]. The decrease of GAS5 induces apoptosis because of the up-regulation of miR-378 [326] (Fig. 7.1).

7.1.7 Cancer Cell Proliferation Above, we showed that EMT, insulin sensitivity, escape of anti-tumor immunity, and increased angiogenesis contributed to cancer cell proliferation.

7.1.7.1

Non-coding RNAs and Cancer Cell Proliferation

Up-regulation of STAT3/miR-21 signaling induces Wnt/β-catenin and represses cellcycle arrest by down-regulating MEG3 and increasing miR-141, silencing PDCD4 [327–329]. The PDCD4 antisense RNA 1 (PDCD4-AS1) de-represses PDCD4, but its expression is low in cancer cells [330, 331]. MiR-130 enhances cancer cell proliferation by targeting transforming growth factor-beta receptor 2 [332]. MiR-130 may, however, be silenced by the mitochondrial ribosomal protein L19 lncRNA (lncRNA MRPL39) and the FYVE, RhoGEF, and PH domain containing 5 (FGD5) antisense RNA 1 (FGD5-AS1) [333, 334]. MiR-181a and miR-181d promote cancer cell proliferation through E2F transcription factor 1 (E2F1) [335], but miR-181a inhibits cancer cell proliferation by targeting CDK1 [336]. The high mobility group AT-hook 1 (HMGA1, formerly HMG-I/Y) induces the expression of miR-221-222, exacerbating tumor growth through regulating the cell cycle by increasing CCND1 and CCNE1 and migration by silencing TIMP metallopeptidase inhibitor 3 (TIMP3) [337]. MiR-223 is either endogenously expressed by myeloid cells or secreted in extracellular vesicles targeting cancer cells. There, miR-223 acts either as a tumor promoter or as a tumor suppressor in a context-dependent manner. For example, the NFκB-dependent stimulation of miR-223-3p promotes the proliferation and migration of gastric cancer cells by directly targeting the AT-rich interaction domain 1A

7.1 Mechanisms of Cancer Progression

163

[338]. However, miR-223-3p-induced up-regulation of p53 expression in a feedback loop inhibits proliferation and migration of squamous cell carcinoma cells [339]. The decrease of miR-223-5p in non-small cell lung cancer tissues enhances proliferation and migration by up-regulating E2F8 [340]. The increase or decrease of miR-223 depends on GAS5 expression [341]. H19 promotes proliferation, migration, and invasion of breast cancer and colorectal cancer cells by sponging miR-93-5p, thereby enhancing the expression of STAT3, as was shown for miR-17 [342]. MALAT1 inhibits the binding of miR-497 to eukaryotic translation initiation factor 4E (EIF4E), leading to increased translation of mRNAs encoding proteins required for cell cycle progression, survival, and proliferation and increased nuclear transport of mRNA encoding CCND1 [343, 344]. NEAT1 induced by hypoxia and LIN28B induces cancer cells’ proliferation by activating TGF-β and Wnt/β-catenin signals through silencing miR-101-p, miR-139-5p, miR-339-5p, miR-495-3p, and miR-506 [345– 350]. TUG1 increases proliferation by increasing CCND1 expression and induces migration by increasing MMP-9 expression [351]. UCA1 promotes tumor growth via sponging miR-28-5p and upregulating homeobox B3 by silencing miR-204 and up-regulating C-X-C motif chemokine receptor 4 (CXCR4), by sponging miR-298 and increasing CDK6 expression, and by binding to miR-495-3p and up-regulating particular AT-rich-binding protein 1 [352–356]. Messenger RNA of the insulin-like growth factor 2 binding protein binds on the ACACCC motifs within UCA1 and prevents the association of miR-122-5p with UCA1, thereby shifting the availability of miR-122-5p from UCA1 to the target mRNAs and reducing the UCA1-mediated cell invasion [357]. XIST promotes proliferation and migration of non-small cell lung cancer cells via sponging miR-16, thereby up-regulating CDK8 expression, and by inducing TGF-β2 expression by targeting miR-141-3p [358, 359]. However, the down-regulation of XIST promotes tumor growth by increasing the expression of miR-497-5p that silences PDCD4 [360, 361]. ZFAS1 induces cancer cell proliferation via silencing miR-200b-3p and miR-484, thereby inducing the Wnt signal [362, 363]. Also, CDKN2B antisense RNA 1 (ANRIL) promotes proliferation and migration of prostate cancer cells by silencing let-7a, thereby inducing the TGF-β/SMAD pathway and by silencing miR-122-5p, thereby inducing the miR-125a-3p/fibroblast growth factor receptor 1/mitogen-activated protein kinase (MAPK) pathway [266, 364, 365]. However, in many tumors, ANRIL correlates positively with tumor suppressors cyclin-dependent kinase inhibitor 2A (p16-CDKN2A), cyclin-dependent kinase inhibitor 2B (p15-CDKN2B), and a splice variant of CDKN2A (p14-ARF). ANRIL and p14-ARF correlated the most through the activation of a bidirectional p14-ARF/ANRIL promoter [366]. The bladder cancer-associated transcript one lncRNA (BLACAT1), HNF1A antisense RNA 1 (HNF1A-AS1), HOTAIR, and H19, and the circ-RNA derived from exons 15 and 16 of the SWI/SNF related, matrix associated, actin-dependent regulator of chromatin, subfamily a, member 4 (cSMARCA4) silence the miR-17 family, increasing cancer cell proliferation [367–373]. In contrast, SOX4 up-regulates the miR-17-92 cluster by downregulating Rb1 protein expression in prostate cancer

164

7 Non-coding RNAs Related to Cardiometabolic Diseases …

cells, thereby inducing proliferation, migration, and invasion [374, 375]. High miR17, due to the increase of NEAT1 and the decrease of circ-MTO1 and the itchy E3 ubiquitin-protein ligase circ-RNA (circ-ITCH), activates NOTCH signaling [376, 377]. Low miR-26 induces cancer cell growth by up-regulating MYC and MAPK6 [378–380]. A forkhead box O1 (FOXO1)-MALAT1-miR-26a-5p feedback loop mediates the proliferation and migration of osteosarcoma cells [381]. The decrease of miR-29 in hepatocellular cancer increases the expression of CCNA and CCND1 [382]. PVT1 induces the proliferation of cervical cancer cells by silencing miR-140 and up-regulating SMAD3, by silencing miR-31 and up-regulating CDK1, and by silencing miR-126 up-regulating solute carrier family 7 member 5 (SLC7A5) [137, 383–385]. The potassium voltage-gated channel subfamily Q member 1 (KCNQ1) opposite strand/antisense transcript 1, TUG1, and zinc finger E-box-binding homeobox two antisense RNA 1 (ZEB1-AS1) induce cancer cell proliferation by sponging miR-145, thereby inducing HIF-1α, CCNE2, ER-α, and Rho-associated coiled-coil containing protein kinase 1 [314, 315, 386–388]. Down-regulation of miR-146a-5p is also induced by MYC and associated with increased proliferation, invasion, and migration of breast cancer cells by upregulating IRAK1 [389, 390]. Silencing of miR-181a by the anaphase-promoting complex subunit 7 circ-RNA (circ-ANAPC7) induces cancer cell proliferation, colony formation, and cell invasion capacities by increasing CCNB1 and CCND1 [336, 391, 392]. Metformin induces miR-378 that silences CDK1, leading to suppression of cell proliferation in hepatocellular carcinoma [393] (Fig. 7.1).

7.1.8 EGFR Signaling and Cancer Progression TGF-β transactivates the epidermal growth factor receptor (EGFR) and facilitates cancer progression through Ras. Ras is a membrane-associated guanine nucleotidebinding protein activated in response to growth factors and T-cell receptors. Ras activates several signaling pathways involving extracellular signal-regulated kinases (ERKs), which promote cell detachment from the ECM and motility. Most of the indirect ERK targets localize in the nucleus. The ERKs modulate the activity of proteins implicated in RNA transport/metabolism. They regulate MYC, Fos proto-oncogene, AP-1 transcription factor subunit (FOS), and Jun proto-oncogene, AP-1 transcription factor subunit (JUN) involved in stemness [394–397]. Other common ERK targets include proteins implicated in cell cycle regulation, apoptosis, and signaling pathways involving TGF-β, PI3K/AKT, MAPK, insulin, and FOXO, contributing to cross-talk and feedback regulation [398]. ER-α36 mediates estrogen-stimulated MAPK/ERK activation and regulates migration, invasion, proliferation in cervical cancer cells [399]. Estrogen and insulin synergistically promote endometrial cancer progression via cross-talk between PI3K/AKT, MAPK, and ERK [400] (Fig. 7.2).

7.1 Mechanisms of Cancer Progression

165

Fig. 7.2 BMI1, EZH2, and ERK in cancer. TGF-β, UCA1, ZFAS1, circ-HIPK3, and ciRs-7 all silencing miR-7, and PVT1, silencing miR-455, induce EGF/EGFR signaling. The decrease of miR133 and GAS5 enhances this. MiR-221-222 inhibits EGFR signaling. Increased EGF/EGFR leads to Ras/Raf/MAPK/ERK signaling, possibly by increasing miR-9 and LINC-ROR and decreasing miR-29a, miR-30a, and miR-34a and miR-150, both silenced by MIAT. Induction of ERK causes detachment of cancer cells from ECM, activation of PI3K/AKT signaling, and stemness via MYC, FOS, and JUN, inducing stemness. ERK signaling is further activated through insulin and estrogen but inhibited by miR-221-222. TGF-β interacts with cytokine receptors and induces PI3K/AKT signaling by activating BMI1 and EZH2, which inhibit PTEN. The increase in BMI1 is due to the increase of HOTAIR. High HOTAIR and MALAT1, and low miR-26a, miR-34a, silenced by TUG1, and miR-124 induce EZH2 and recruit EZH2 to its target genes, thereby inducing stemness. Increased non-coding RNAs are in red; decreased in green

7.1.8.1

Non-coding RNAs and EGFR Signaling

A decrease of miR-7 is associated with increased proliferation and decreased apoptosis by increasing PI3K and EGFR, the thyroid receptor interactor protein 6, and MAP3K9 that activates the MAP2K7 (or MEK)/ERK and the NFκB pathway [401– 405]. UCA1 up-regulation promotes hypoxia-resistant gastric cancer cells’ migration through the miR-7-5p/EGFR axis and increased PI3K/AKT/mTOR signaling

166

7 Non-coding RNAs Related to Cardiometabolic Diseases …

[406, 407]. ZFAS1 in colorectal cancer cells silences miR-7-5p, increasing proliferation, migration, and invasion, and inhibiting apoptosis [408]. c-MYB-induced circ-HIPK3 promotes colorectal cancer growth and metastasis by sponging miR7, thereby increasing the expression of miR-7 target EGFR [139]. Up-regulation of the circular cerebellar degeneration related protein 1 antisense RNA (ciRs7 or CDR1-AS) abrogated the tumor-suppressive roles of miR-7, including cell proliferation, migration, and invasion by de-repressing the homeobox 13-mediated NFκB/p65 pathway, inducing PTEN/PI3K/AKT pathway, and increasing expression of EGFR and CCNE1 [409–411]. Down-regulation of miR-133 induces EGFR [412, 413]. RUNX2-mediated up-regulation of PVT1 silenced miR-455, associated with increased expression of EGFR promoting proliferation and migration of cancer cells [414, 415]. Down-regulation of GAS5 in lung adenocarcinoma associated with increased expression of EGFR [142]. The increase of miR-9 activates the Ras/Raf/MAPK/ERK signaling that, together with activation of the PI3K/AKT/mTOR pathway, leads to cancer cell proliferation and chemoresistance [416]. LINC-ROR induces phosphorylated MAPK/ERK signaling by stabilizing the ERK-specific phosphatase dual-specificity phosphatase 7, also known as MKP-X, activating estrogen receptor signaling [417]. Downregulation of miR-29a is associated with activation of MAPK8 (or JNK) and p38MAPK/ERK and CDK6, thereby promoting cancer cell migration and inhibiting apoptosis [418]. A decrease of miR-30a was associated with the activation of the Ras/Raf/MEK/ERK signaling pathway in hepatocellular carcinoma [419]. MIAT silences miR-34a, increasing ERK and phosphorylated PI3K/AKT resulting in enhanced lymph node metastasis [301, 420]. MIAT also silences miR-150, associated with cancer cell proliferation by inducing AKT/ERK signaling and expression of CCND1, CDK4, and CDK6 [421, 422]. In contrast, miR-221 silences ADAMTS6, suppressing cell migration by inhibiting EGFR and ERK1/2 [423] (Fig. 7.2).

7.1.9 BMI1 and EZH2 in Cancer Progression Oncogenes such as the BMI1 proto-oncogene, polycombing ring finger 1 (BMI1), and enhancer of zeste 2 polycomb repressive complex 2 (EZH2) are upstream regulators and downstream targets of the PI3K/AKT pathway. TGF-β induces BMI1 and EZH2 [424]. BMI1 downregulates PTEN that antagonizes the PI3K/AKT signaling pathway [425]. However, in prostate cancer cells, PTEN reduces the function of BMI1 to prevent tumorigenesis, indicating that a PTEN/BMI-1 double-negative feedback loop may occur and govern EMT in certain types of cancer [426]. EZH2 induces cancer cell stemness and EMT [427, 428]. Further, inhibition of EZH2 may increase PTEN expression, thereby decreasing pAKT expression and inducing cell apoptosis [428]. However, PTEN loses its ability to inhibit PI3K/AKT signaling by phosphorylation, ubiquitination, acetylation, and oxidation [429]. PI3K/AKT, as in the pancreas, activates mTORC1 and mTORC2, inducing cancer

7.1 Mechanisms of Cancer Progression

167

cell growth, proliferation, migration, and invasion. But mTORC1 hyperactivation also leads to feedback inhibition of the PI3K/AKT signaling (Fig. 7.2).

7.1.9.1

Non-coding RNAs and BMI1 and EZH2

HOTAIR silences miR-148b, thereby increasing the expression of BMI1 that favors cancer stemness [430, 431]. Also, HOTAIR interacts with EZH2 and recruits it to the target gene promoters/loci. EZH2 introduces H3K27-trimethylation, and LSD1 demethylates H3K4 and contributes to gene silencing (Fig. 1.5). CDK1/2 favors the interaction between EZH2 and HOTAIR and not between BRCA1 DNA repair associated (BRCA1) and EZH2 [432]. MALAT1 upregulates EZH2 by sponging miR-217, miR-218, and miR-363-3p [433, 434]. The small nucleolar RNA host gene 6 (SNHG6) lncRNA promotes EMT by silencing miR-26a, thereby upregulating the EZH2 axis, which inhibits the production of Th1 type chemokines such as the chemokine C-X-C motif ligand (CXCL)-9 and CXCL10, thereby compromising the trafficking of tumor-specific T cells, which mediate cytotoxic effects on cancer cells and promote anti-tumor function [435]. TUG1 promotes EMT with cell proliferation and migration by suppressing miR-34a and miR-382 via recruiting EZH2 in adriamycin-resistant acute myeloid leukemia tissues suppressing PDCD4 expression [436–438]. Down-regulation of miR-124 enhances growth and inhibits radiation-induced apoptosis and cisplatin-resistance of lung cancer by inducing the EZH2-STAT3 signaling axis [439] (Fig. 7.2).

7.2 Non-coding RNAs Related to Metabolic and Cardiovascular Diseases Are also Involved in Cancer Progression Above, we identified let-7, miR-1, miR-7, miR-9, miR-17, miR-21, miR-26a, miR29, miR-30a, miR-34a, miR-124, miR-130, miR-143/145, miR-146a, miR-150, miR155, miR-181, miR-221/222, miR-223, miR-378 and miR-455 as pre-dominant miRs linking metabolic to cardiovascular diseases. GAS5, HOTAIR, H19, lincRNA-p21, LINC-ROR, MALAT1, MEG3, MIAT, NEAT1, TUG1, UCA1, ANRIL, and PVT1 regulate this cluster of miRs related to cancer.

7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic Diseases and Cancer Table 7.1 gives an overview of the actions of non-coding RNAs in the development of cardiometabolic diseases and cancer. Low miR-1, miR-26a, miR-133, miR-378, and miR-455, and high miR-155, HOTAIR, LINC-ROR, TUG1, and XIST are typically

Low

Cancer

• Induces cardiac hypertrophy • Induces cardiogenesis and cardiac fibrosis with ECM deposition • Increases CM death

• Increases CM cell death

miR-1

miR-7

• Increases the number of stem cells which differentiate to β cells • Reduces mature β cell mass, blocks insulin secretion and reduces insulin sensitivity

• Promotes β cell expansion • Let7-d: promotes M2 to M1 macrophage polarization • Let7-b: promotes apoptosis

• Induces stemness • Induces EMT • Induces IGF1R and EGFR signaling

• Induces stemness • Increases EMT • Promotes glycolysis

• Reduces the number of • Induces stemness, except adipocyte precursors and let7i-5p that inhibits stemness • Promotes M2 macrophage impaired white adipogenesis accumulation and represses • Let-7a: promotes angiogenesis cytotoxic T-cell-mediated • Let7-b: induces NO and anti-tumor immunity decreases ROS • Let-7c: promotes monocyte to dendritic cell differentiation • Let-7e: promotes M2 to M1 macrophage polarization • Let-7 g: protects from the miR-21-induced reduction of Treg cells and reduces foam cell generation • Let-7 family: cardiac hypertrophy and fibrosis

High

Let-7

MiRs

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 Overview of the role of non-coding RNAs in the pathogenesis of cardiometabolic diseases and cancer

(continued)

• Let-7 induces MDSCs and immune escape

High

168 7 Non-coding RNAs Related to Cardiometabolic Diseases …

miR-9

• Induces monocyte to M2 macrophage differentiation

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Represses beige adipocyte maturation • Increases EPC migration and angiogenesis • Reduces maturation and proliferation of insulin-secreting β cells • Induces M1 macrophage polarization and foam cell generation • Induces cardiac hypertrophy and remodeling

High

Low

Cancer

(continued)

• Maintains stemness and increases EMT by inhibiting E-cadherin, but may inhibit EMT by targeting TWIST • Blocks PTEN, thereby increasing PI3K/AKT signaling • Blocks IGF1R signaling • Reduces anti-tumor immunity by increasing MDSCs • Increases angiogenesis • Induces apoptosis

High

7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic … 169

miR-17

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued) Low

Cancer High

• Impairs IGF1 signaling, • Increases EMT and cancer cell • Induces cancer cell glucose transport and Induces proliferation proliferation by inhibiting • Reduces anti-tumor immunity inflammation-associated PTEN, thereby activating by inducing MDSCs insulin resistance AKT/mTOR signaling, and by • Regulates EC proliferation but • Reduces cancer cell targeting the Rb family, and by senescence and death inhibits angiogenesis mediating MYB • Increases recruitment of • Hampers IGF1-driven tumor monocytes and differentiation growth • miR-17-92: impairs of monocytes to dendritic cells and M1 macrophages. angiogenesis Reduces T reg cells • Promotes hepatic steatosis and cardiac fibrosis • Causes mitochondrial dysfunction and ROS release; induces apoptosis (continued)

High

170 7 Non-coding RNAs Related to Cardiometabolic Diseases …

miR-21

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Reduces the number of white adipocyte precursors but increases adiponectin signaling and improves insulin sensitivity • Induces differentiation of stem cells to ECs, and increases angiogenesis • Reduces the number of Treg cells and induces differentiation of monocytes to macrophages and fibroblasts, but prevents extreme inflammation by retaining M2 macrophage phenotype • Induces VSMC proliferation • Promotes cardiac hypertrophy and fibrosis and hepatic steatosis • Reduces cell death

High

Low

Cancer • • • •

(continued)

Induces EMT Inhibits PTEN Increases angiogenesis Reduces anti-tumor immunity by favoring M2 macrophage polarization and MDSC differentiation

High

7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic … 171

• Increases white adipogenesis

miR-29a

• Impairs insulin secretion and IRS signaling • Reverts reduction of anti-inflammatory Th2 and Treg cells resulting from a decrease of miR-133 • Induces fibrous cap formation but prevents necrotic core formation in atherosclerotic plaques • Induces cardiac hypertrophy and fibrosis and hepatic steatosis

• Impairs brown adipogenesis • Induces maturation of • Impairs maturation of insulin-secreting β cells and insulin-secreting β cells and insulin secretion in response to insulin secretion in response to high glucose high glucose • Impairs angiogenesis • Increases angiogenesis • Converts contractile to • Increases VSMC proliferation synthetic VSMCs • Reduces cardiac hypertrophy and ECM deposition • Suppresses FA uptake in the liver • Attenuates apoptosis

High

miR-26a

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Induces stemness • Increases EMT • Activation of ERK and PI3K signaling • Increases angiogenesis • Reduces cancer cell death

• Promotes EMT • Increases IGF1, leading to PI3K/AKT activation • Increases angiogenesis • Reduces anti-tumor immunity • Reduces apoptosis

Low

Cancer

(continued)

• Inhibits PTEN, activating PI3K

• Decreases PTEN, leading to PI3K/AKT activation

High

172 7 Non-coding RNAs Related to Cardiometabolic Diseases …

miR-30

• Induces cardiac hypertrophy and fibrosis

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• miR-30a: promotes white adipogenesis • miR-30b/c: promotes brown adipogenesis • Blocks M1 macrophage polarization and reduces inflammatory T cells and inflammation-associated insulin resistance • Prevents inflammation but induces lipid deposition in the liver

High • miR-30a: Induces stemness • Increases EMT • Induces IGF1R/IRS1 and ERK signaling • Reduced cancer cell death

Low

Cancer

(continued)

• Induces MDSCs and immune escape

High

7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic … 173

miR-34a

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Reduces the number of white adipocyte and VSMC precursors • Impairs white and brown adipogenesis but inhibits lipid deposition in WAT • Represses maturation and proliferation of insulin-secreting β cells • Impairs angiogenesis • Induces M1 macrophage polarization and impairs cholesterol efflux • Induces cardiac fibrosis and hepatic steatosis; limits FA oxidation • Increases cell senescence and death

High • Induces stemness • Promotes EMT • Increases PI3K/AKT signaling; increase of EZH2, inhibiting PTEN • Increases glycolysis • Increases angiogenesis • Increases the number of Treg cells and reduces anti-tumor immunity

Low

Cancer • Increases apoptosis

High

(continued)

174 7 Non-coding RNAs Related to Cardiometabolic Diseases …

miR-130

miR-124a

• Decreases FABP4 • Increases M1 macrophage polarization • Induces de-differentiation of contractile to synthetic VSMCs with increased proliferation

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Represses white adipocyte maturation and induces inflammation in WAT • miR-130b: protects precursor cells in the pancreas • Increases angiogenesis and NO release • miR-130: decreases inflammatory cytokines and inhibits lipid accumulation • Induces cardiac fibrosis

• Differentiates stem cells in adipose tissue • Impairs maturation of white adipocytes and β cell proliferation and AKT and insulin signaling • Impairs angiogenesis • Blocks ROS release • Increases cell senescence and death

High Induces stemness Promotes EMT Increases angiogenesis Inhibits apoptosis

• miR-130b: induces EMT

• • • •

Low

Cancer

(continued)

• miR-130b: induces angiogenesis • Induces M1 macrophage polarisation, increases immune response • Represses apoptosis

High

7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic … 175

• Brown adipogenesis requires the down-regulation of miR-133, which results in increased expression of PRDM16 • Increases M1 macrophage polarization and number of inflammatory T cells • Promotes cardiac hypertrophy and fibrosis • Increased apoptosis

• Converts VSMCs to macrophage-like cells with an impaired phagocytic capacity

miR-133

miR-143-145

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Blocks the proliferation of white adipocyte precursors • Blocks reprogramming of mature β cells to proliferating pluripotent stem cells • Impairs insulin signaling • Increases angiogenesis • Activates EC and VSMC cross-talk and maintains VSM contractility • Induces M1 macrophage polarization • Impairs cholesterol efflux and promotes hepatic steatosis

• miR-133a: increases differentiation of beige adipocytes in response to cold exposure • Induces cardiogenesis

High

• • • •

Induces stemness Promotes EMT Increases glycolysis Represses apoptosis

• Induces EMT by up-regulation of EGFR

Low

Cancer High

(continued)

176 7 Non-coding RNAs Related to Cardiometabolic Diseases …

• miR-146b: impairs adiponectin signaling and induces mitochondrial dysfunction and inflammation without insulin resistance when adiponectin is low • MiR-146a: increases lipid accumulation in liver and hepatic steatosis

• Increases monocyte infiltration in the heart and associated with cardiac hypertrophy fibrosis • Decreases cell death

miR-146

miR-150

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Impairs brown adipogenesis • Impairs angiogenesis • Blocks DC activation induced by inflammatory T cells • Promotes hepatic steatosis and insulin resistance • Increases cell death

• miR-146a: blocks white adipocyte precursor proliferation • miR-146a: blocks reprogramming of β cells to pluripotent stem cells • Impairs PI3K/AKT signaling • miR-146a: blocks M1 macrophage polarization and scavenger-receptor-mediated uptake of ox-LDL; increases the number of Th1 but decreases the number of Th17 cells • Induces de-differentiation of contractile to synthetic proliferating VSMCs • Promotes cardiac hypertrophy and cardiac fibrosis • Increases cell senescence and death

High

• Induces EMT • Induces ERK and cancer cell proliferation • Increases angiogenesis • Reduces anti-tumor immunity • Decreases cancer cell death

• miR-146a: induces stemness • miR-146b; blocks stemness • miR-146a and miR-146b: reduce anti-tumor immunity by inducing MDSCs • Inhibits angiogenesis

Low

Cancer

(continued)

• miR-146a: increases apoptosis

High

7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic … 177

• Induces lipid accumulation in WAT; impairs beige adipogenesis • Impairs reprogramming of β cells to pluripotent stem cells and reduces insulin signaling • Causes oxidative and endoplasmic reticulum stress and inflammation • Impairs VSMC contractility and NO vasorelaxation • Promotes cardiac hypertrophy and fibrosis • Induces apoptosis

• miR-181d: impairs white • miR-181a: increases withe adipocyte maturation adipocyte precursor • miR-181b: reduces IGF1R and proliferation insulin signaling • miR-181a: reverts M1 • miR-181b: increases ROS and macrophage polarization and M1 macrophage polarization reduces cardiac inflammation • miR-181b: induces and oxidative stress microthrombus formation • miR-181a/b: blocks M1 macrophage polarization but • Decreases cell death induces lipid deposition in the liver

miR-181

High

miR-155

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• miR-181b: increases monocyte infiltration in tumors

Low

Cancer Induces EMT Induces IGF1 signaling Induces glycolysis Promotes angiogenesis Induces MDSCs and immune escape

(continued)

• miR-181b: suppresses EMT • miR-181b: increases AKT signaling • miR-181a: induces MDSCs • Induces apoptosis

• • • • •

High

178 7 Non-coding RNAs Related to Cardiometabolic Diseases …

miR-221-222

• Increased angiogenesis in advanced plaques

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Induces insulin resistance and inflammation in WAT • Decreases insulin secretion • Reduces angiogenesis in new plaques • Induces shift from M1 to M2 macrophages and suppresses ox-LDL-induced inflammation • Induces de-differentiation of contractile to synthetic proliferating VSMCs • Induces atherosclerotic plaque calcification • Induces hepatic steatosis but blocks cardiac fibrosis

High

Low

Cancer

(continued)

• Maintains stemness • Promotes EMT • Represses PTEN and induces PI3K/AKT signaling but acts anti-oncogenic by repressing EGFR and ERK

High

7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic … 179

• Increases brown adipogenesis • Ices EMT and thermogenesis to counteract inflammation-induced obesity • Restores PI3K/AKT signaling • Promotes reverse cholesterol transport • Increases VSMC proliferation • Protects from cardiac and liver fibrosis • Inhibits apoptosis by maintaining insulin signaling

miR-378

Low

Cancer • De-represses maturation of β cells but represses IGF1R and insulin signaling • Impairs angiogenesis • Blocks M1 macrophage polarization • Blocks cholesterol biosynthesis and uptake of HDL-associated cholesteryl esters; promotes cholesterol efflux • Induces cardiac hypertrophy and inflammation • Increases cell death

High

miR-223

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

(continued)

• Induces shift from glycolysis to OXPHOS, reducing cancer cell proliferation and migration • Induces cancer cell death

• Induces or inhibits cancer cell proliferation in a context-dependent manner • Inhibits PTEN and induces PI3K/AKT signaling and cancer cell proliferation. However, it inhibits proliferation by up-regulating p53 • Increases the number of M2 macrophages

High

180 7 Non-coding RNAs Related to Cardiometabolic Diseases …

HOTAIR

GAS5

LncRNAs

miR-455

• Suppresses EC and VSMC cross-talk • Reduces cell death by up-regulation of miR-21

• Induces M1 macrophage polarization • Induces hepatic steatosis

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Increases EMT • Induces IGF1R and EGFR signaling

Low

Cancer

• Increases white adipocyte differentiation • Impairs β cell proliferation and induces insulin resistance • Increases M1 macrophage polarization

• Impairs white adipocyte • Induces IGF1R and EGFR precursor proliferation and signaling adipogenesis but maintains β • Induces cancer cell death through miR-378 cell maturation and insulin secretion • Suppresses VSMC proliferation by silencing miR-21 • Inhibits cardiac remodeling by silencing miR-21 • Increases cell death

• Increases brown adipogenesis and thermogenesis

High

(continued)

• Increases stemness • Promotes EMT • Increases IGF2 signaling and insulin trough BMI1 and silencing of PTEN • Recruits EZH2 • Attracts macrophages in tumors and increases the number of MDSCs • Decreases cancer cell death

• Reverses EMT • Promotes NK cell-mediated cytotoxicity • Prevents angiogenesis

High

7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic … 181

• Impairs differentiation of mesenchymal cells to white adipocytes • Increases brown adipogenesis • Restores β cell mass and insulin signaling • Prevents repair of endothelium and reduces angiogenesis • Promotes lipid deposition in the liver • Protects against cardiac hypertrophy but induces cardiac fibrosis • Increases cell death • Increases inflammation and liver fibrosis • Increases cell senescence • Blocks reprogramming of β cells to pluripotent precursor cells

LincRNA-p21

LINC-ROR

High

H19

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Increases stemness • Induces EMT • Induces glycolysis

Low

Cancer

• • • •

• • • •

(continued)

Promotes stemness and EMT Induces AKT signaling Promotes glycolysis Inhibits apoptosis

Promotes EMT Induces PI3K/AKT signaling Reduces anti-tumor immunity Reduces cancer cell death

High

182 7 Non-coding RNAs Related to Cardiometabolic Diseases …

• Promotes pathological angiogenesis • Promotes cardiac hypertrophy and fibrosis • Reduces cell death

• Induces insulin resistance • Limits lipid accumulation in the liver

• Impairs β cell maturation and insulin secretion • Induces EC proliferation and angiogenesis • Protects from cardiac fibrosis and ER stress-induced apoptosis

MEG3

MIAT

• Activates NLRP3 inflammasome in the heart by silencing miR-133 • Increases glucose and lipids in the liver; blocks insulin signaling • Cardiac hypertrophy and fibrosis

• EC dysfunction and M1 macrophage polarization is associated with a decrease of MALAT1 in atherosclerotic plaques

High

MALAT1

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Increases EMT • Induces PI3K/AKT/mTOR signaling • Induces glycolysis • Decreases cancer cell death

Low

Cancer Induces stemness Promotes EMT Increases IRS1 signaling Promotes glycolysis Is induced by M2 TAMs Inhibits apoptosis

(continued)

• Induces stemness • Promotes EMT • Induces ERK and PI3K/AKT signaling • Reduces cancer cell death

• • • • • •

High

7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic … 183

• Facilitates progenitor cell differentiation in WAT • Protects ECs from oxidative stress • Promotes Th2 cell differentiation • NEAT1-paraspeckles facilitate lipid accumulation of lipids in macrophages, activate inflammasomes, and induce apoptosis • Induces liver fibrosis • Increases M1 macrophage polarization • Induces cardiac fibrosis • Increases cell death • Increases angiogenesis • Converts contractile to synthetic proliferating VSMCs • Induces cardiac hypertrophy and fibrosis • Reduces apoptosis

TUG1

UCA1

High

NEAT1

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued) Low

Cancer

• • • • • •

• • • •

(continued)

Increases stemness Promotes EMT Reverts inhibition of PTEN Induces glycolysis Reduces anti-tumor immunity Reduces cancer cell death

Induces stemness Promotes EMT Induces glycolysis Reduces cancer cell death

• Induces stemness and EMT • Reduces cancer cell death

High

184 7 Non-coding RNAs Related to Cardiometabolic Diseases …

• Increases inflammation • Reduces cholesterol efflux • Protects from ischemia/reperfusion-related myocardial injury

ZFAS1

• Reduces cell death by silencing miR-181 but increases cell death by activating NFκB • Blocks progenitor cell proliferation but improves insulin secretion by silencing miR-7

ANRIL

CiRs-7

Circ-RNAs

• Promotes hypoxia-induced angiogenesis • Mediates ox-LDL-induced EC injury and ischemia/reperfusion related myocardial injury

High

XIST

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued) Low

Cancer Induces stemness Promotes EMT Increases IRS1 signaling Promotes angiogenesis Reduces cancer cell death

(continued)

• Induces PI3K/AKT and EGFR

• Increases immune escape • Reduces cancer cell death

• Promotes EMT • Increases angiogenesis • Reduces cancer cell death

• • • • •

High

7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic … 185

PVT1

• Decreases AKT signaling

Low

Non-coding RNA Cardiometabolic diseases

Table 7.1 (continued)

• Induces differentiation of white preadipocytes, increases the fatty acid synthesis, and blocks fatty acid oxidation • Increases angiogenesis • Promotes ANG II-induced increase of inflammatory cytokines, thickening of adventitia, loss of elastin, and apoptosis

High

Low

Cancer • Promotes EMT • Induces EGFR signaling

High

186 7 Non-coding RNAs Related to Cardiometabolic Diseases …

7.3 Comparison of the Role of Non-coding RNAs in Cardiometabolic …

187

related to the development of cardiometabolic diseases and cancer. High miR-34a and lincRNA-p21 are mostly related to cardiometabolic diseases, while low levels are related to cancer. High and low let-7, miR-146a, miR-181, miR-223, and GAS5 are associated with cardiometabolic diseases and cancer. Both high and low miR-9, miR-21, miR-130, miR-221-222, H19, MALAT1, MIAT, NEAT1, UCA1, ZFAS1, ANRIL, ciRs-7, and PVT1 are related to cardiometabolic diseases, while high levels are typically related to cancer. However, silencing of miR-9 is required to avoid cancer cell senescence. High and low miR-7, miR-17, miR-29a, miR-30a, miR-124, miR-143-145, miR-150, and MEG3 are related to cardiometabolic diseases, while low levels are typically related to cancer. However, in some tumors, high miR-17 may induce proliferation, the decrease of miR-26a and miR-29a inhibits PTEN, and the increase of miR-30a protects against immune response by expanding MDSCs. Overall, more non-coding RNAs are driven to either higher or lower levels in tumors than cardiometabolic tissues.

References 1. Lee, J. S., et al. (2015). SIRT1 is required for oncogenic transformation of neural stem cells and for the survival of “cancer cells with neural stemness” in a p53-dependent manner. NeuroOncology, 17, 95–106. https://doi.org/10.1093/neuonc/nou145. 2. Chen, X., et al. (2014). High levels of SIRT1 expression enhance tumorigenesis and associate with a poor prognosis of colorectal carcinoma patients. Scientific Reports, 4, 7481. https:// doi.org/10.1038/srep07481. 3. Brandl, L., et al. (2018). The c-MYC/NAMPT/SIRT1 feedback loop is activated in early classical and serrated route colorectal cancer and represents a therapeutic target. Medical Oncology, 36, 5. https://doi.org/10.1007/s12032-018-1225-1. 4. Mimeault, M., & Batra, S. K. (2013). Hypoxia-inducing factors as master regulators of stemness properties and altered metabolism of cancer- and metastasis-initiating cells. Journal of Cellular and Molecular Medicine, 17, 30–54. https://doi.org/10.1111/jcmm.12004. 5. Glinsky, G. V. (2008). “Stemness” genomics law governs clinical behavior of human cancer: Implications for decision making in disease management. Journal of Clinical Oncology, 26, 2846–2853. https://doi.org/10.1200/JCO.2008.17.0266. 6. Thiery, J. P., Acloque, H., Huang, R. Y., & Nieto, M. A. (2009). Epithelial-mesenchymal transitions in development and disease. Cell, 139, 871–890. https://doi.org/10.1016/j.cell. 2009.11.007. 7. Acloque, H., Adams, M. S., Fishwick, K., Bronner-Fraser, M., & Nieto, M. A. (2009). Epithelial-mesenchymal transitions: The importance of changing cell state in development and disease. Journal of Clinical Investigation, 119, 1438–1449. https://doi.org/10.1172/JCI 38019. 8. McCrea, P. D., & Gottardi, C. J. (2016). Beyond beta-catenin: Prospects for a larger catenin network in the nucleus. Nature Reviews Molecular Cell Biology, 17, 55–64. https://doi.org/ 10.1038/nrm.2015.3. 9. Colella, B., Faienza, F., & Di Bartolomeo, S. (2019). EMT regulation by autophagy: A new perspective in glioblastoma biology. Cancers (Basel), 11. https://doi.org/10.3390/cancers11 030312. 10. Lamb, R., et al. (2013). Wnt pathway activity in breast cancer sub-types and stem-like cells. PLoS ONE, 8, e67811. https://doi.org/10.1371/journal.pone.0067811. 11. Sica, A., & Massarotti, M. (2017). Myeloid suppressor cells in cancer and autoimmunity. Journal of Autoimmunity, 85, 117–125. https://doi.org/10.1016/j.jaut.2017.07.010.

188

7 Non-coding RNAs Related to Cardiometabolic Diseases …

12. Trikha, P., & Carson, W. E., 3rd. (1846). Signaling pathways involved in MDSC regulation. Biochimica et Biophysica Acta, 55–65, 2014. https://doi.org/10.1016/j.bbcan.2014.04.003. 13. Kumar, V., et al. (2016). CD45 phosphatase inhibits STAT3 transcription factor activity in myeloid cells and promotes tumor-associated macrophage differentiation. Immunity, 44, 303– 315. https://doi.org/10.1016/j.immuni.2016.01.014. 14. Ostrand-Rosenberg, S. (2018). Myeloid derived-suppressor cells: Their role in cancer and obesity. Current Opinion in Immunology, 51, 68–75. https://doi.org/10.1016/j.coi.2018. 03.007. 15. Fu, Y., et al. (2019). LncRNA CASC11 promotes TGF-beta1, increases cancer cell stemness and predicts postoperative survival in small cell lung cancer. Gene, 704, 91–96. https://doi. org/10.1016/j.gene.2019.04.019. 16. Cheng, C. W., et al. (2018). Increased cellular levels of microRNA-9 and microRNA-221 correlate with cancer stemness and predict poor outcome in human breast cancer. Cellular Physiology and Biochemistry, 48, 2205–2218. https://doi.org/10.1159/000492561. 17. Ni, S. J., et al. (2018). CBX7 regulates stem cell-like properties of gastric cancer cells via p16 and AKT-NF-kappaB-miR-21 pathways. Journal of Hematology & Oncology, 11, 17. https:// doi.org/10.1186/s13045-018-0562-z. 18. Lin, S. L. (2011). Concise review: Deciphering the mechanism behind induced pluripotent stem cell generation. Stem Cells, 29, 1645–1649. https://doi.org/10.1002/stem.744. 19. Keshavarz, M., & Asadi, M. H. (2019). Long non-coding RNA ES1 controls the proliferation of breast cancer cells by regulating the Oct4/Sox2/miR-302 axis. FEBS Journal. https://doi. org/10.1111/febs.14825. 20. Tang, D., et al. (2019). Long noncoding RNA MALAT1 mediates stem cell-like properties in human colorectal cancer cells by regulating miR-20b-5p/Oct4 axis. Journal of Cellular Physiology. https://doi.org/10.1002/jcp.28687. 21. Xiao, Y., Pan, J., Geng, Q., & Wang, G. (2019). LncRNA MALAT1 increases the stemness of gastric cancer cells via enhancing SOX2 mRNA stability. FEBS Open Bio. https://doi.org/ 10.1002/2211-5463.12649. 22. Jen, J., et al. (2017). Oct4 transcriptionally regulates the expression of long non-coding RNAs NEAT1 and MALAT1 to promote lung cancer progression. Molecular Cancer, 16, 104. https:// doi.org/10.1186/s12943-017-0674-z. 23. Almnaseer, Z. A., & Mourtada-Maarabouni, M. (2018). Long noncoding RNA MIAT regulates apoptosis and the apoptotic response to chemotherapeutic agents in breast cancer cell lines. Bioscience Reports, 38. https://doi.org/10.1042/BSR20180704. 24. Cai, W. Y., et al. (2013). The Wnt-beta-catenin pathway represses let-7 microRNA expression through transactivation of Lin28 to augment breast cancer stem cell expansion. Journal of Cell Science, 126, 2877–2889. https://doi.org/10.1242/jcs.123810. 25. Balzeau, J., Menezes, M. R., Cao, S., & Hagan, J. P. (2017). The LIN28/let-7 pathway in cancer. Frontiers in Genetics, 8, 31. https://doi.org/10.3389/fgene.2017.00031. 26. Jia, B., et al. (2019). MiR-7-5p suppresses stemness and enhances temozolomide sensitivity of drug-resistant glioblastoma cells by targeting Yin Yang 1. Experimental Cell Research, 375, 73–81. https://doi.org/10.1016/j.yexcr.2018.12.016. 27. Chang, Y. L., et al. (2015). MicroRNA-7 inhibits the stemness of prostate cancer stem-like cells and tumorigenesis by repressing KLF4/PI3K/Akt/p21 pathway. Oncotarget, 6, 24017–24031. https://doi.org/10.18632/oncotarget.4447. 28. Drago-Ferrante, R., et al. (2017). Suppressive role exerted by microRNA-29b-1-5p in triple negative breast cancer through SPIN1 regulation. Oncotarget, 8, 28939–28958. https://doi. org/10.18632/oncotarget.15960. 29. Miao, Y., et al. (2019). miR-30a inhibits breast cancer progression through the Wnt/betacatenin pathway. International Journal of Clinical and Experimental Pathology, 12, 241–250. 30. Liu, L., Chen, L., Wu, T., Qian, H., & Yang, S. (2019). MicroRNA-30a-3p functions as a tumor suppressor in renal cell carcinoma by targeting WNT2. American Journal of Translational Research, 11, 4976–4983.

References

189

31. Chen, Q., et al. (2020). miR-30a-3p inhibits the proliferation of liver cancer cells by targeting DNMT3a through the PI3K/AKT signaling pathway. Oncology Letters, 19, 606–614. https:// doi.org/10.3892/ol.2019.11179. 32. Zhou, J., et al. (2017). Inhibition of LIN28B impairs leukemia cell growth and metabolism in acute myeloid leukemia. Journal of Hematology & Oncology, 10, 138. https://doi.org/10. 1186/s13045-017-0507-y. 33. Luo, Y., et al. (2019). Long non-coding RNA NEAT1 promotes colorectal cancer progression by competitively binding miR-34a with SIRT1 and enhancing the Wnt/beta-catenin signaling pathway. Cancer Letters, 440–441, 11–22. https://doi.org/10.1016/j.canlet.2018.10.002. 34. Ma, W., et al. (2015). Dysregulation of the miR-34a-SIRT1 axis inhibits breast cancer stemness. Oncotarget, 6, 10432–10444. https://doi.org/10.18632/oncotarget.3394. 35. Liu, H., Deng, H., Zhao, Y., Li, C., & Liang, Y. (2018). LncRNA XIST/miR-34a axis modulates the cell proliferation and tumor growth of thyroid cancer through MET-PI3K-AKT signaling. Journal of Experimental & Clinical Cancer Research, 37, 279. https://doi.org/10.1186/s13 046-018-0950-9. 36. Chhabra, R. (2018). let-7i-5p, miR-181a-2-3p and EGF/PI3K/SOX2 axis coordinate to maintain cancer stem cell population in cervical cancer. Scientific Reports, 8, 7840. https://doi.org/ 10.1038/s41598-018-26292-w. 37. Zhou, X., Yue, Y., Wang, R., Gong, B., & Duan, Z. (2017). MicroRNA-145 inhibits tumorigenesis and invasion of cervical cancer stem cells. International Journal of Oncology, 50, 853–862. https://doi.org/10.3892/ijo.2017.3857. 38. Deng, J., et al. (2017). Long non-coding RNA HOTAIR regulates the proliferation, selfrenewal capacity, tumor formation and migration of the cancer stem-like cell (CSC) subpopulation enriched from breast cancer cells. PLoS ONE, 12, e0170860. https://doi.org/10.1371/ journal.pone.0170860. 39. Sabelstrom, H., et al. (2019). Driving neuronal differentiation through reversal of an ERK1/2miR-124-SOX9 axis abrogates glioblastoma aggressiveness. Cell Reports, 28, 2064–2079 e2011. https://doi.org/10.1016/j.celrep.2019.07.071. 40. Yamamoto, H., et al. (2016). miR-133 regulates Evi1 expression in AML cells as a potential therapeutic target. Scientific Reports, 6, 19204. https://doi.org/10.1038/srep19204. 41. Hinai, A. A., & Valk, P. J. (2016). Review: Aberrant EVI1 expression in acute myeloid leukaemia. British Journal of Haematology, 172, 870–878. https://doi.org/10.1111/bjh.13898. 42. Tianhua, Y., Dianqiu, L., Xuanhe, Z., Zhe, Z., & Dongmei, G. (2020). Long non-coding RNA Sox2 overlapping transcript (SOX2OT) promotes multiple myeloma progression via microRNA-143-3p/c-MET axis. Journal of Cellular and Molecular Medicine, 24, 5185–5194. https://doi.org/10.1111/jcmm.15171. 43. Iacona, J. R., Monteleone, N. J., & Lutz, C. S. (2018). miR-146a suppresses 5-lipoxygenase activating protein (FLAP) expression and Leukotriene B4 production in lung cancer cells. Oncotarget, 9, 26751–26769. https://doi.org/10.18632/oncotarget.25482. 44. Zhang, W., et al. (2019). PVT1 (rs13281615) and miR-146a (rs2910164) polymorphisms affect the prognosis of colon cancer by regulating COX2 expression and cell apoptosis. Journal of Cellular Physiology, 234, 17538–17548. https://doi.org/10.1002/jcp.28377. 45. Zhou, Y. X., et al. (2018). Long non-coding RNA NIFK-AS1 inhibits M2 polarization of macrophages in endometrial cancer through targeting miR-146a. International Journal of Biochemistry & Cell Biology, 104, 25–33. https://doi.org/10.1016/j.biocel.2018.08.017. 46. Yang, W., et al. (2016). MiR-146b-5p overexpression attenuates stemness and radioresistance of glioma stem cells by targeting HuR/lincRNA-p21/beta-catenin pathway. Oncotarget, 7, 41505–41526. https://doi.org/10.18632/oncotarget.9214. 47. Chen, T. Y., Lee, S. H., Dhar, S. S., & Lee, M. G. (2018). Protein arginine methyltransferase 7-mediated microRNA-221 repression maintains Oct4, Nanog, and Sox2 levels in mouse embryonic stem cells. Journal of Biological Chemistry, 293, 3925–3936. https://doi.org/10. 1074/jbc.RA117.000425. 48. Byles, V., et al. (2012). SIRT1 induces EMT by cooperating with EMT transcription factors and enhances prostate cancer cell migration and metastasis. Oncogene, 31, 4619–4629. https:// doi.org/10.1038/onc.2011.612.

190

7 Non-coding RNAs Related to Cardiometabolic Diseases …

49. Katsuno, Y., Lamouille, S., & Derynck, R. (2013). TGF-beta signaling and epithelialmesenchymal transition in cancer progression. Current Opinion in Oncology, 25, 76–84. https://doi.org/10.1097/CCO.0b013e32835b6371. 50. Feng, H., et al. (2017). The expression of SIRT1 regulates the metastaticplasticity of chondrosarcoma cells by inducing epithelial-mesenchymal transition. Scientific Reports, 7, 41203. https://doi.org/10.1038/srep41203. 51. Malik, S., et al. (2015). SIRT7 inactivation reverses metastatic phenotypes in epithelial and mesenchymal tumors. Scientific Reports, 5, 9841. https://doi.org/10.1038/srep09841. 52. O’Callaghan, C., & Vassilopoulos, A. (2017). Sirtuins at the crossroads of stemness, aging, and cancer. Aging Cell, 16, 1208–1218. https://doi.org/10.1111/acel.12685. 53. Simic, P., et al. (2013). SIRT1 suppresses the epithelial-to-mesenchymal transition in cancer metastasis and organ fibrosis. Cell Reports, 3, 1175–1186. https://doi.org/10.1016/j.celrep. 2013.03.019. 54. Chen, J., et al. (2013). SIRT2 overexpression in hepatocellular carcinoma mediates epithelial to mesenchymal transition by protein kinase B/glycogen synthase kinase-3beta/beta-catenin signaling. Hepatology, 57, 2287–2298. https://doi.org/10.1002/hep.26278. 55. Miyo, M., et al. (2015). Tumour-suppressive function of SIRT4 in human colorectal cancer. British Journal of Cancer, 113, 492–499. https://doi.org/10.1038/bjc.2015.226. 56. Mani, S. A., et al. (2008). The epithelial-mesenchymal transition generates cells with properties of stem cells. Cell, 133, 704–715. https://doi.org/10.1016/j.cell.2008.03.027. 57. Nieto, M. A., Huang, R. Y., Jackson, R. A., & Thiery, J. P. (2016). Emt: 2016. Cell, 166, 21–45. https://doi.org/10.1016/j.cell.2016.06.028. 58. Xu, G., et al. (2018). MEG3/miR21 axis affects cell mobility by suppressing epithelialmesenchymal transition in gastric cancer. Oncology Reports, 40, 39–48. https://doi.org/10.3892/ or.2018.6424. 59. Johansson, J., et al. (2013). MiR-155-mediated loss of C/EBPbeta shifts the TGF-beta response from growth inhibition to epithelial-mesenchymal transition, invasion and metastasis in breast cancer. Oncogene, 32, 5614–5624. https://doi.org/10.1038/onc.2013.322. 60. Storci, G., et al. (2013). Slug/beta-catenin-dependent proinflammatory phenotype in hypoxic breast cancer stem cells. American Journal of Pathology, 183, 1688–1697. https://doi.org/10. 1016/j.ajpath.2013.07.020. 61. Li, T., et al. (2017). MiR-221 mediates the epithelial-mesenchymal transition of hepatocellular carcinoma by targeting AdipoR1. International Journal of Biological Macromolecules, 103, 1054–1061. https://doi.org/10.1016/j.ijbiomac.2017.05.108. 62. Li, B., et al. (2017). miR-221/222 promote cancer stem-like cell properties and tumor growth of breast cancer via targeting PTEN and sustained Akt/NF-kappaB/COX-2 activation. ChemicoBiological Interactions, 277, 33–42. https://doi.org/10.1016/j.cbi.2017.08.014. 63. Zhu, G., et al. (2019). TRAF6 promotes the progression and growth of colorectal cancer through nuclear shuttle regulation NF-kB/c-jun signaling pathway. Life Sciences, 235, 116831. https://doi.org/10.1016/j.lfs.2019.116831. 64. Sun, Y., et al. (2019). LncRNA H19/miR-194/PFTK1 axis modulates the cell proliferation and migration of pancreatic cancer. Journal of Cellular Biochemistry, 120, 3874–3886. https:// doi.org/10.1002/jcb.27669. 65. Zheng, L., Zhou, Z., & He, Z. (2015). Knockdown of PFTK1 inhibits tumor cell proliferation, invasion and epithelial-to-mesenchymal transition in pancreatic cancer. International Journal of Clinical and Experimental Pathology, 8, 14005–14012. 66. Liu, M. H., Shi, S. M., Li, K., & Chen, E. Q. (2016). Knockdown of PFTK1 expression by RNAi inhibits the proliferation and invasion of human non-small lung adenocarcinoma cells. Oncology Research, 24, 181–187. https://doi.org/10.3727/096504016X14635761799038. 67. Li, C. F., Li, Y. C., Wang, Y., & Sun, L. B. (2018). The effect of LncRNA H19/miR-194-5p axis on the epithelial-mesenchymal transition of colorectal adenocarcinoma. Cellular Physiology and Biochemistry, 50, 196–213. https://doi.org/10.1159/000493968. 68. Li, J., et al. (2018). Long noncoding RNA H19 promotes transforming growth factor-betainduced epithelial-mesenchymal transition by acting as a competing endogenous RNA of

References

69.

70.

71.

72.

73.

74.

75.

76.

77.

78.

79.

80.

81.

82.

83.

84.

191

miR-370-3p in ovarian cancer cells. OncoTargets and Therapy, 11, 427–440. https://doi.org/ 10.2147/OTT.S149908. Zhang, Q., Li, X., Li, X., Li, X., & Chen, Z. (2018). LncRNA H19 promotes epithelialmesenchymal transition (EMT) by targeting miR-484 in human lung cancer cells. Journal of Cellular Biochemistry, 119, 4447–4457. https://doi.org/10.1002/jcb.26537. Lv, M., et al. (1864). lncRNA H19 regulates epithelial-mesenchymal transition and metastasis of bladder cancer by miR-29b-3p as competing endogenous RNA. Biochimica et Biophysica Acta - Molecular Cell Research, 1887–1899, 2017. https://doi.org/10.1016/j.bbamcr.2017. 08.001. Zhu, J., Shi, H., Liu, H., Wang, X., & Li, F. (2017). Long non-coding RNA TUG1 promotes cervical cancer progression by regulating the miR-138-5p-SIRT1 axis. Oncotarget, 8, 65253– 65264. https://doi.org/10.18632/oncotarget.18224. Xiao, C. H., et al. (2018). Long non-coding RNA TUG1 promotes the proliferation of colorectal cancer cells through regulating Wnt/beta-catenin pathway. Oncology Letters, 16, 5317–5324. https://doi.org/10.3892/ol.2018.9259. He, C., et al. (2018). lncRNA TUG1-mediated Mir-142-3p downregulation contributes to metastasis and the epithelial-to-mesenchymal transition of hepatocellular carcinoma by targeting ZEB1. Cellular Physiology and Biochemistry, 48, 1928–1941. https://doi.org/10. 1159/000492517. Lu, Y., et al. (2018). Long noncoding RNA TUG1/miR-29c axis affects cell proliferation, invasion, and migration in human pancreatic cancer. Disease Markers, 2018, 6857042. https:// doi.org/10.1155/2018/6857042. Gong, P., et al. (2018). LncRNA UCA1 promotes tumor metastasis by inducing miR203/ZEB2 axis in gastric cancer. Cell Death and Disease, 9, 1158. https://doi.org/10.1038/ s41419-018-1170-0. Chen, X., Gao, J., Yu, Y., Zhao, Z., & Pan, Y. (2018). Long non-coding RNA UCA1 targets miR-185-5p and regulates cell mobility by affecting epithelial-mesenchymal transition in melanoma via Wnt/beta-catenin signaling pathway. Gene, 676, 298–305. https://doi.org/10. 1016/j.gene.2018.08.065. Wang, X., et al. (2018). Knockdown of LncRNA-XIST suppresses proliferation and TGFbeta1-induced EMT in NSCLC through the notch-1 pathway by regulation of miR-137. Genetic Testing and Molecular Biomarkers, 22, 333–342. https://doi.org/10.1089/gtmb.2018. 0026. Fang, C., et al. (2017). Long non-coding ribonucleic acid zinc finger antisense 1 promotes the progression of colonic cancer by modulating ZEB1 expression. Journal of Gastroenterology and Hepatology, 32, 1204–1211. https://doi.org/10.1111/jgh.13646. Zhang, X., et al. (2018). Long noncoding RNA PVT1 promotes epithelialmesenchymal transition via the TGFbeta/Smad pathway in pancreatic cancer cells. Oncology Reports, 40, 1093–1102. https://doi.org/10.3892/or.2018.6462. Gao, S., et al. (2019). MiR-1 inhibits prostate cancer PC3 cells proliferation through the Akt/mTOR signaling pathway by binding to c-Met. Biomedicine & Pharmacotherapy, 109, 1406–1410. https://doi.org/10.1016/j.biopha.2018.10.098. Xu, L., et al. (2014). Tumor suppressor miR-1 restrains epithelial-mesenchymal transition and metastasis of colorectal carcinoma via the MAPK and PI3K/AKT pathway. Journal of Translational Medicine, 12, 244. https://doi.org/10.1186/s12967-014-0244-8. Dong, P., et al. (2014). The impact of microRNA-mediated PI3K/AKT signaling on epithelialmesenchymal transition and cancer stemness in endometrial cancer. Journal of Translational Medicine, 12, 231. https://doi.org/10.1186/s12967-014-0231-0. Li, S. M., et al. (2018). The putative tumour suppressor miR-1-3p modulates prostate cancer cell aggressiveness by repressing E2F5 and PFTK1. Journal of Experimental & Clinical Cancer Research, 37, 219. https://doi.org/10.1186/s13046-018-0895-z. Ou-Yang, J., Huang, L. H., & Sun, X. X. (2017). Cyclin-dependent kinase 14 promotes cell proliferation, migration and invasion in ovarian cancer by inhibiting Wnt signaling pathway. Gynecologic and Obstetric Investigation, 82, 230–239. https://doi.org/10.1159/000447632.

192

7 Non-coding RNAs Related to Cardiometabolic Diseases …

85. Mao, Y., et al. (2017). High expression of PFTK1 in cancer cells predicts poor prognosis in colorectal cancer. Molecular Medicine Reports, 16, 224–230. https://doi.org/10.3892/mmr. 2017.6560. 86. Chang, J., Xu, W., Du, X., & Hou, J. (2018). MALAT1 silencing suppresses prostate cancer progression by upregulating miR-1 and downregulating KRAS. OncoTargets and Therapy, 11, 3461–3473. https://doi.org/10.2147/OTT.S164131. 87. Zhang, X., Zhao, X., Li, Y., Zhou, Y., & Zhang, Z. (2019). Long noncoding RNA SOX21-AS1 promotes cervical cancer progression by competitively sponging miR-7/VDAC1. Journal of Cellular Physiology, 234, 17494–17504. https://doi.org/10.1002/jcp.28371. 88. Chen, M., et al. (2019). LINC01939 inhibits the metastasis of gastric cancer by acting as a molecular sponge of miR-17-5p to regulate EGR2 expression. Cell Death and Disease, 10, 70. https://doi.org/10.1038/s41419-019-1344-4. 89. Cai, Z. G., Wu, H. B., Xu, X. P., & Li, W. (2018). Down-regulation of miR-26 plays essential roles in TGFbeta-induced EMT. Cell Biology International. https://doi.org/10.1002/cbin. 11029. 90. Tang, M., Zhou, J., You, L., Cui, Z., & Zhang, H. (2019). LIN28B/IRS1 axis is targeted by miR30a-5p and promotes tumor growth in colorectal cancer. Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb.29529. 91. Quan, X., Li, X., Yin, Z., Ren, Y., & Zhou, B. (2019). p53/miR-30a-5p/ SOX4 feedback loop mediates cellular proliferation, apoptosis, and migration of non-small-cell lung cancer. Journal of Cellular Physiology, 234, 22884–22895. https://doi.org/10.1002/jcp.28851. 92. di Gennaro, A., et al. (2018). A p53/miR-30a/ZEB2 axis controls triple negative breast cancer aggressiveness. Cell Death & Differentiation, 25, 2165–2180. https://doi.org/10.1038/s41418018-0103-x. 93. Hu, X., et al. (2019). Long noncoding RNA LINC00460 aggravates invasion and metastasis by targeting miR-30a-3p/Rap1A in nasopharyngeal carcinoma. Human Cell, 32, 465–476. https://doi.org/10.1007/s13577-019-00262-4. 94. Pan, Y., et al. (2018). Long non-coding MALAT1 functions as a competing endogenous RNA to regulate vimentin expression by sponging miR-30a-5p in hepatocellular carcinoma. Cellular Physiology and Biochemistry, 50, 108–120. https://doi.org/10.1159/000493962. 95. Nie, D., Fu, J., Chen, H., Cheng, J., & Fu, J. (2019). Roles of microRNA-34a in epithelial to mesenchymal transition, competing endogenous RNA sponging and its therapeutic potential. International Journal of Molecular Sciences, 20. https://doi.org/10.3390/ijms20040861. 96. Rokavec, M., et al. (2014). IL-6R/STAT3/miR-34a feedback loop promotes EMT-mediated colorectal cancer invasion and metastasis. Journal of Clinical Investigation, 124, 1853–1867. https://doi.org/10.1172/JCI73531. 97. Si, W., et al. (2016). MiR-34a inhibits breast cancer proliferation and progression by targeting Wnt1 in Wnt/beta-catenin signaling pathway. American Journal of the Medical Sciences, 352, 191–199. https://doi.org/10.1016/j.amjms.2016.05.002. 98. Zheng, F., et al. (2020). Novel regulation of miR-34a-5p and HOTAIR by the combination of berberine and gefitinib leading to inhibition of EMT in human lung cancer. Journal of Cellular and Molecular Medicine, 24, 5578–5592. https://doi.org/10.1111/jcmm.15214. 99. Zhang, T. H., et al. (2019). LncRNA UCA1/miR-124 axis modulates TGFbeta1-induced epithelial-mesenchymal transition and invasion of tongue cancer cells through JAG1/Notch signaling. Journal of Cellular Biochemistry, 120, 10495–10504. https://doi.org/10.1002/jcb. 28334. 100. Zhu, J., et al. (2018). Knockdown of long non-coding RNA XIST inhibited doxorubicin resistance in colorectal cancer by upregulation of miR-124 and downregulation of SGK1. Cellular Physiology and Biochemistry, 51, 113–128. https://doi.org/10.1159/000495168. 101. Hu, D., & Zhang, Y. (2019). Circular RNA HIPK3 promotes glioma progression by binding to miR-124-3p. Gene, 690, 81–89. https://doi.org/10.1016/j.gene.2018.11.073. 102. Cui, R. J., et al. (2019). miR-124-3p availability is antagonized by LncRNA-MALAT1 for slug-induced tumor metastasis in hepatocellular carcinoma. Cancer Medicine. https://doi.org/ 10.1002/cam4.2482.

References

193

103. Pang, Y., et al. (2019). NEAT1/miR124/STAT3 feedback loop promotes breast cancer progression. International Journal of Oncology, 55, 745–754. https://doi.org/10.3892/ijo. 2019.4841. 104. Liu, S., et al. (2019). LncRNA-H19 regulates cell proliferation and invasion of ectopic endometrium by targeting ITGB3 via modulating miR-124-3p. Experimental Cell Research, 381, 215–222. https://doi.org/10.1016/j.yexcr.2019.05.010. 105. Wei, C., Lei, L., Hui, H., & Tao, Z. (2019). MicroRNA-124 regulates TRAF6 expression and functions as an independent prognostic factor in colorectal cancer. Oncology Letters, 18, 856–863. https://doi.org/10.3892/ol.2019.10358. 106. Li, S. L., et al. (2017). MicroRNA-124 inhibits cell invasion and epithelial-mesenchymal transition by directly repressing Snail2 in gastric cancer. European Review for Medical and Pharmacological Sciences, 21, 3389–3396. 107. Jin, Y., Feng, S. J., Qiu, S., Shao, N., & Zheng, J. H. (2017). LncRNA MALAT1 promotes proliferation and metastasis in epithelial ovarian cancer via the PI3K-AKT pathway. European Review for Medical and Pharmacologic, 21, 3176–3184. 108. He, B., Peng, F., Li, W., & Jiang, Y. (2019). Interaction of lncRNA-MALAT1 and miR-124 regulates HBx-induced cancer stem cell properties in HepG2 through PI3K/Akt signaling. Journal of Cellular Biochemistry, 120, 2908–2918. https://doi.org/10.1002/jcb.26823. 109. Chen, Y., et al. (2018). LncRNA MALAT1 promotes cancer metastasis in osteosarcoma via activation of the PI3K-Akt signaling pathway. Cellular Physiology and Biochemistry, 51, 1313–1326. https://doi.org/10.1159/000495550. 110. Tee, A. E., et al. (2016). The long noncoding RNA MALAT1 promotes tumor-driven angiogenesis by up-regulating pro-angiogenic gene expression. Oncotarget, 7, 8663–8675. https:// doi.org/10.18632/oncotarget.6675. 111. Dong, P., et al. (2013). Mutant p53 gain-of-function induces epithelial-mesenchymal transition through modulation of the miR-130b-ZEB1 axis. Oncogene, 32, 3286–3295. https://doi.org/ 10.1038/onc.2012.334. 112. Li, C., et al. (2017). The lincRNA-ROR/miR-145 axis promotes invasion and metastasis in hepatocellular carcinoma via induction of epithelial-mesenchymal transition by targeting ZEB2. Scientific Reports, 7, 4637. https://doi.org/10.1038/s41598-017-04113-w. 113. Wei, A. W., & Li, L. F. (2017). Long non-coding RNA SOX21-AS1 sponges miR-145 to promote the tumorigenesis of colorectal cancer by targeting MYO6. Biomedicine & Pharmacotherapy, 96, 953–959. https://doi.org/10.1016/j.biopha.2017.11.145. 114. Fan, H., Liu, X., Zheng, W. W., Zhuang, Z. H., & Wang, C. D. (2017). MiR-150 alleviates EMT and cell invasion of colorectal cancer through targeting Gli1. European Review for Medical and Pharmacologic, 21, 4853–4859. 115. Yang, Y. J., Luo, S., & Wang, L. S. (2019). Effects of microRNA-378 on epithelialmesenchymal transition, migration, invasion and prognosis in gastric carcinoma by targeting BMP2. European Review for Medical and Pharmacologic, 23, 5176–5186. https://doi.org/ 10.26355/eurrev_201906_18182. 116. Zeng, M., Zhu, L., Li, L., & Kang, C. (2017). miR-378 suppresses the proliferation, migration and invasion of colon cancer cells by inhibiting SDAD1. Cellular & Molecular Biology Letters, 22, 12. https://doi.org/10.1186/s11658-017-0041-5. 117. Zeng, Y., et al. (2019). MicroRNA-455-3p mediates GATA3 tumor suppression in mammary epithelial cells by inhibiting TGF-beta signaling. Journal of Biological Chemistry, 294, 15808–15825. https://doi.org/10.1074/jbc.RA119.010800. 118. Xue, J., et al. (2018). CircLRP6 regulation of ZEB1 via miR-455 is involved in the epithelial-mesenchymal transition during arsenite-induced malignant transformation of human keratinocytes. Toxicological Sciences, 162, 450–461. https://doi.org/10.1093/toxsci/ kfx269. 119. Zhang, Y., et al. (2019). LincRNA-p21 leads to G1 arrest by p53 pathway in esophageal squamous cell carcinoma. Cancer Management and Research, 11, 6201–6214. https://doi. org/10.2147/CMAR.S197557.

194

7 Non-coding RNAs Related to Cardiometabolic Diseases …

120. Chen, Y., et al. (2017). Down regulation of lincRNA-p21 contributes to gastric cancer development through Hippo-independent activation of YAP. Oncotarget, 8, 63813–63824. https:// doi.org/10.18632/oncotarget.19130. 121. Wang, X., et al. (2017). Long intragenic non-coding RNA lincRNA-p21 suppresses development of human prostate cancer. Cell Proliferation, 50. https://doi.org/10.1111/cpr.12318. 122. Jia, M., et al. (2016). lincRNA-p21 inhibits invasion and metastasis of hepatocellular carcinoma through Notch signaling-induced epithelial-mesenchymal transition. Hepatology Research, 46, 1137–1144. https://doi.org/10.1111/hepr.12659. 123. Zhang, W., et al. (2017). LncRNA MEG3 inhibits cell epithelial-mesenchymal transition by sponging miR-421 targeting E-cadherin in breast cancer. Biomedicine & Pharmacotherapy, 91, 312–319. https://doi.org/10.1016/j.biopha.2017.04.085. 124. Terashima, M., Tange, S., Ishimura, A., & Suzuki, T. (2017). MEG3 long noncoding RNA contributes to the epigenetic regulation of epithelial-mesenchymal transition in lung cancer cell lines. Journal of Biological Chemistry, 292, 82–99. https://doi.org/10.1074/jbc.M116. 750950. 125. Bertrand, F. E., McCubrey, J. A., Angus, C. W., Nutter, J. M., & Sigounas, G. (2014). NOTCH and PTEN in prostate cancer. Advances in Biological Regulation, 56, 51–65. https://doi.org/ 10.1016/j.jbior.2014.05.002. 126. Babion, I., et al. (2019). miR-9-5p exerts a dual role in cervical cancer and targets transcription factor TWIST1. Cells, 9. https://doi.org/10.3390/cells9010065. 127. Wang, H., et al. (2015). Upregulation of miR-181s reverses mesenchymal transition by targeting KPNA4 in glioblastoma. Scientific Reports, 5, 13072. https://doi.org/10.1038/sre p13072. 128. Ma, J., et al. (2015). Down-regulation of miR-223 reverses epithelial-mesenchymal transition in gemcitabine-resistant pancreatic cancer cells. Oncotarget, 6, 1740–1749. https://doi.org/ 10.18632/oncotarget.2714. 129. Haisa, M. (2013). The type 1 insulin-like growth factor receptor signalling system and targeted tyrosine kinase inhibition in cancer. Journal of International Medical Research, 41, 253–264. https://doi.org/10.1177/0300060513476585. 130. Li, Y., et al. (2001). Deficiency of Pten accelerates mammary oncogenesis in MMTV-Wnt-1 transgenic mice. BMC Molecular Biology, 2, 2. https://doi.org/10.1186/1471-2199-2-2. 131. Stiles, B., et al. (2004). Liver-specific deletion of negative regulator Pten results in fatty liver and insulin hypersensitivity [corrected]. Proceedings of the National academy of Sciences of the United States of America, 101, 2082–2087. https://doi.org/10.1073/pnas.0308617100. 132. Ohigashi, T., Mizuno, R., Nakashima, J., Marumo, K., & Murai, M. (2005). Inhibition of Wnt signaling downregulates Akt activity and induces chemosensitivity in PTEN-mutated prostate cancer cells. Prostate, 62, 61–68. https://doi.org/10.1002/pros.20117. 133. Huang, M., et al. (2006). Identification of genes regulated by Wnt/beta-catenin pathway and involved in apoptosis via microarray analysis. BMC Cancer, 6, 221. https://doi.org/10.1186/ 1471-2407-6-221. 134. Sharma, M., Chuang, W. W., & Sun, Z. (2002). Phosphatidylinositol 3-kinase/Akt stimulates androgen pathway through GSK3beta inhibition and nuclear beta-catenin accumulation. Journal of Biological Chemistry, 277, 30935–30941. https://doi.org/10.1074/jbc.M20 1919200. 135. Zhao, H., et al. (2005). Overexpression of the tumor suppressor gene phosphatase and tensin homologue partially inhibits wnt-1-induced mammary tumorigenesis. Cancer Research, 65, 6864–6873. https://doi.org/10.1158/0008-5472.CAN-05-0181. 136. Wang, J., Guo, J., & Fan, H. (2019). MiR-155 regulates the proliferation and apoptosis of pancreatic cancer cells through targeting SOCS3. European Review for Medical and Pharmacologic, 23, 5168–5175. https://doi.org/10.26355/eurrev_201906_18181. 137. Shao, Y., et al. (2020). Long non-coding RNA PVT1 regulates glioma proliferation, invasion, and aerobic glycolysis via miR-140-5p. European Review for Medical and Pharmacologic, 24, 274–283. https://doi.org/10.26355/eurrev_202001_19922.

References

195

138. Feng, K., et al. (2018). Long noncoding RNA PVT1 enhances the viability and invasion of papillary thyroid carcinoma cells by functioning as ceRNA of microRNA-30a through mediating expression of insulin like growth factor 1 receptor. Biomedicine & Pharmacotherapy, 104, 686–698. https://doi.org/10.1016/j.biopha.2018.05.078. 139. Zeng, K., et al. (2018). CircHIPK3 promotes colorectal cancer growth and metastasis by sponging miR-7. Cell Death and Disease, 9, 417. https://doi.org/10.1038/s41419-018-0454-8. 140. Tan, X., Fan, S., Wu, W., & Zhang, Y. (2015). MicroRNA-26a inhibits osteosarcoma cell proliferation by targeting IGF-1. Bone Research, 3, 15033. https://doi.org/10.1038/boneres. 2015.33. 141. Hu, Y., Yang, Z., Bao, D., Ni, J. S., & Lou, J. (2019). miR-455-5p suppresses hepatocellular carcinoma cell growth and invasion via IGF-1R/AKT/GLUT1 pathway by targeting IGF-1R. Pathology, Research and Practice, 215, 152674. https://doi.org/10.1016/j.prp.2019.152674. 142. Dong, S., et al. (2015). The long non-coding RNA, GAS5, enhances gefitinib-induced cell death in innate EGFR tyrosine kinase inhibitor-resistant lung adenocarcinoma cells with wide-type EGFR via downregulation of the IGF-1R expression. Journal of Hematology & Oncology, 8, 43. https://doi.org/10.1186/s13045-015-0140-6. 143. Cheng, Z., Luo, C., & Guo, Z. (2020). LncRNA-XIST/microRNA-126 sponge mediates cell proliferation and glucose metabolism through the IRS1/PI3K/Akt pathway in glioma. Journal of Cellular Biochemistry, 121, 2170–2183. https://doi.org/10.1002/jcb.29440. 144. Wang, S., et al. (2018). CircZNF609 promotes breast cancer cell growth, migration, and invasion by elevating p70S6K1 via sponging miR-145-5p. Cancer Management and Research, 10, 3881–3890. https://doi.org/10.2147/CMAR.S174778. 145. Chen, Y. C., Ou, M. C., Fang, C. W., Lee, T. H., & Tzeng, S. L. (2019). High glucose concentrations negatively regulate the IGF1R/Src/ERK Axis through the MicroRNA-9 in colorectal cancer. Cells, 8. https://doi.org/10.3390/cells8040326. 146. Shi, Y. P., Liu, G. L., Li, S., & Liu, X. L. (2020). miR-17-5p knockdown inhibits proliferation, autophagy and promotes apoptosis in thyroid cancer via targeting PTEN. Neoplasma, 67, 249–258. https://doi.org/10.4149/neo_2019_190110N29. 147. Hossain, A., Kuo, M. T., & Saunders, G. F. (2006). Mir-17-5p regulates breast cancer cell proliferation by inhibiting translation of AIB1 mRNA. Molecular and Cellular Biology, 26, 8191–8201. https://doi.org/10.1128/MCB.00242-06. 148. Wu, Y., et al. (2017). MicroRNA-21 (Mir-21) Promotes Cell Growth and Invasion by Repressing Tumor Suppressor PTEN in Colorectal Cancer. Cellular Physiology and Biochemistry, 43, 945–958. https://doi.org/10.1159/000481648. 149. Zhao, B. W., Dai, H. Y., Hao, L. N., & Liu, Y. W. (2019). MiR-29 regulates retinopathy in diabetic mice via the AMPK signaling pathway. European Review for Medical and Pharmacologic, 23, 3569–3574. https://doi.org/10.26355/eurrev_201905_17778. 150. Li, W., Jiang, Y., Wu, X., & Yang, F. (2019). Targeted regulation of miR-26a on PTEN to affect proliferation and apoptosis of prostate cancer cells. Cancer Biotherapy and Radiopharmaceuticals. https://doi.org/10.1089/cbr.2018.2664. 151. Coronel-Hernandez, J., et al. (2019). Cell migration and proliferation are regulated by miR26a in colorectal cancer via the PTEN-AKT axis. Cancer Cell International, 19, 80. https:// doi.org/10.1186/s12935-019-0802-5. 152. Tumaneng, K., et al. (2012). YAP mediates crosstalk between the Hippo and PI(3)K-TOR pathways by suppressing PTEN via miR-29. Nature Cell Biology, 14, 1322–1329. https://doi. org/10.1038/ncb2615. 153. Yang, B., et al. (2018). TUG1 promotes prostate cancer progression by acting as a ceRNA of miR-26a. Bioscience Reports, 38. https://doi.org/10.1042/BSR20180677. 154. Egawa, H., et al. (2016). The miR-130 family promotes cell migration and invasion in bladder cancer through FAK and Akt phosphorylation by regulating PTEN. Scientific Reports, 6, 20574. https://doi.org/10.1038/srep20574. 155. Wei, H., et al. (2017). miR-130a deregulates PTEN and stimulates tumor growth. Cancer Research, 77, 6168–6178. https://doi.org/10.1158/0008-5472.CAN-17-0530.

196

7 Non-coding RNAs Related to Cardiometabolic Diseases …

156. Li, Y., Wan, B., Liu, L., Zhou, L., & Zeng, Q. (2019). Circular RNA circMTO1 suppresses bladder cancer metastasis by sponging miR-221 and inhibiting epithelial-to-mesenchymal transition. Biochemical and Biophysical Research Communications, 508, 991–996. https:// doi.org/10.1016/j.bbrc.2018.12.046. 157. Fan, L., et al. (2018). Long noncoding RNA urothelial cancer associated 1 regulates radioresistance via the hexokinase 2/glycolytic pathway in cervical cancer. International Journal of Molecular Medicine, 42, 2247–2259. https://doi.org/10.3892/ijmm.2018.3778. 158. Zhu, X., et al. (2019). Macrophages derived exosomes deliver miR-223 to epithelial ovarian cancer cells to elicit a chemoresistant phenotype. Journal of Experimental & Clinical Cancer Researc, 38, 81. https://doi.org/10.1186/s13046-019-1095-1. 159. Wang, D. Y., Gendoo, D. M. A., Ben-David, Y., Woodgett, J. R., & Zacksenhaus, E. (2019). A subgroup of microRNAs defines PTEN-deficient, triple-negative breast cancer patients with poorest prognosis and alterations in RB1, MYC, and Wnt signaling. Breast Cancer Research, 21, 18. https://doi.org/10.1186/s13058-019-1098-z. 160. Dong, L., Li, G., Li, Y., & Zhu, Z. (2019). Upregulation of long noncoding RNA GAS5 inhibits lung cancer cell proliferation and metastasis via miR-205/PTEN Axis. Medical Science Monitor, 25, 2311–2319. https://doi.org/10.12659/MSM.912581. 161. Strotbek, M., et al. (2017). miR-181 elevates Akt signaling by co-targeting PHLPP2 and INPP4B phosphatases in luminal breast cancer. International Journal of Cancer, 140, 2310– 2320. https://doi.org/10.1002/ijc.30661. 162. Wei, J., et al. (2018). Long non-coding RNA H19 promotes TDRG1 expression and cisplatin resistance by sequestering miRNA-106b-5p in seminoma. Cancer Medicine, 7, 6247–6257. https://doi.org/10.1002/cam4.1871. 163. Zhai, X. Q., Meng, F. M., Hu, S. F., Sun, P., & Xu, W. (2019). Mechanism of LncRNA ROR promoting prostate cancer by regulating Akt. European Review for Medical and Pharmacologic, 23, 1969–1977. https://doi.org/10.26355/eurrev_201903_17235. 164. Li, Z., Yu, D., Li, H., Lv, Y., & Li, S. (2019). Long noncoding RNA UCA1 confers tamoxifen resistance in breast cancer endocrinotherapy through regulation of the EZH2/p21 axis and the PI3K/AKT signaling pathway. International Journal of Oncology, 54, 1033–1042. https://doi. org/10.3892/ijo.2019.4679. 165. Zhang, C. Y., et al. (2017). Overexpression of long non-coding RNA MEG3 suppresses breast cancer cell proliferation, invasion, and angiogenesis through AKT pathway. Tumour Biology, 39, 1010428317701311. https://doi.org/10.1177/1010428317701311. 166. Deng, R., et al. (2018). MEG3 affects the progression and chemoresistance of Tcell lymphoblastic lymphoma by suppressing epithelial-mesenchymal transition via the PI3K/mTOR pathway. Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb.28093. 167. Warburg, O. (1956). On respiratory impairment in cancer cells. Science, 124, 269–270. 168. Warburg, O. (1956). On the origin of cancer cells. Science, 123, 309–314. https://doi.org/10. 1126/science.123.3191.309. 169. Gottlieb, E., & Tomlinson, I. P. (2005). Mitochondrial tumour suppressors: A genetic and biochemical update. Nature Reviews Cancer, 5, 857–866. https://doi.org/10.1038/nrc1737. 170. Kunkel, M., et al. (2003). Overexpression of Glut-1 and increased glucose metabolism in tumors are associated with a poor prognosis in patients with oral squamous cell carcinoma. Cancer, 97, 1015–1024. https://doi.org/10.1002/cncr.11159. 171. Lee, S. Y., et al. (2012). Wnt/Snail signaling regulates cytochrome C oxidase and glucose metabolism. Cancer Research, 72, 3607–3617. https://doi.org/10.1158/0008-5472.CAN-120006. 172. Pate, K. T., et al. (2014). Wnt signaling directs a metabolic program of glycolysis and angiogenesis in colon cancer. EMBO Journal, 33, 1454–1473. https://doi.org/10.15252/embj.201 488598. 173. Hu, Z. Y., Xiao, L., Bode, A. M., Dong, Z., & Cao, Y. (2014). Glycolytic genes in cancer cells are more than glucose metabolic regulators. Journal of Molecular Medicine (Berl), 92, 837–845. https://doi.org/10.1007/s00109-014-1174-x.

References

197

174. Vander Heiden, M. G., Cantley, L. C., & Thompson, C. B. (2009). Understanding the Warburg effect: The metabolic requirements of cell proliferation. Science, 324, 1029–1033. https://doi. org/10.1126/science.116080. 175. Wu, F., et al. (2019). Exosomes increased angiogenesis in papillary thyroid cancer microenvironment. Endocrine-Related Cancer. https://doi.org/10.1530/ERC-19-0008. 176. Singh, A., et al. (2013). Transcription factor NRF2 regulates miR-1 and miR-206 to drive tumorigenesis. Journal of Clinical Investigation, 123, 2921–2934. https://doi.org/10.1172/ JCI66353. 177. Shi, S., et al. (2016). VEGF promotes glycolysis in pancreatic cancer via HIF1alpha upregulation. Current Molecular Medicine, 16, 394–403. https://doi.org/10.2174/156652401 6666160316153623. 178. Mehta, V., et al. (2018). VEGF (vascular endothelial growth factor) induces NRP1 (neuropilin1) cleavage via ADAMs (a disintegrin and metalloproteinase) 9 and 10 to generate novel carboxy-terminal NRP1 fragments that regulate angiogenic signaling. Arteriosclerosis, Thrombosis, and Vascular Biology, 38, 1845–1858. https://doi.org/10.1161/ATVBAHA.118. 311118. 179. Deng, F., et al. (2019). Tumor-secreted dickkopf2 accelerates aerobic glycolysis and promotes angiogenesis in colorectal cancer. Theranostics, 9, 1001–1014. https://doi.org/10.7150/thno. 30056. 180. Dong, Z. C., et al. (2019). MiR-155 affects proliferation and apoptosis of bladder cancer cells by regulating GSK-3beta/beta-catenin pathway. European Review for Medical and Pharmacologic, 23, 5682–5690. https://doi.org/10.26355/eurrev_201907_18305. 181. Takahashi, K., Yan, I. K., Kogure, T., Haga, H., & Patel, T. (2014). Extracellular vesiclemediated transfer of long non-coding RNA ROR modulates chemosensitivity in human hepatocellular cancer. FEBS Open Bio, 4, 458–467. https://doi.org/10.1016/j.fob.2014. 04.007. 182. Takahashi, K., Yan, I. K., Haga, H., & Patel, T. (2014). Modulation of hypoxia-signaling pathways by extracellular linc-RoR. Journal of Cell Science, 127, 1585–1594. https://doi. org/10.1242/jcs.141069. 183. Zhao, Y., et al. (2018). The lncRNA MACC1-AS1 promotes gastric cancer cell metabolic plasticity via AMPK/Lin28 mediated mRNA stability of MACC1. Molecular Cancer, 17, 69. https://doi.org/10.1186/s12943-018-0820-2. 184. Guo, T., et al. (2018). Elevated MACC1 expression predicts poor prognosis in small invasive lung adenocarcinoma. Cancer Biomark, 22, 301–310. https://doi.org/10.3233/CBM-171017. 185. Zhu, B., et al. (2018). Evaluation of the correlation of MACC1, CD44, Twist1, and KiSS-1 in the metastasis and prognosis for colon carcinoma. Diagnostic Pathology, 13, 45. https://doi. org/10.1186/s13000-018-0722-z. 186. Jeong, H., et al. (2018). Prognostic characteristics of MACC1 expression in epithelial ovarian cancer. BioMed Research International, 2018, 9207153. https://doi.org/10.1155/2018/920 7153. 187. Malakar, P., et al. (2019). Long noncoding RNA MALAT1 regulates cancer glucose metabolism by enhancing mTOR-mediated translation of TCF7L2. Cancer Research, 79, 2480–2493. https://doi.org/10.1158/0008-5472.CAN-18-1432. 188. Zhang, P., et al. (2018). AMPK/GSK3beta/beta-catenin cascade-triggered overexpression of CEMIP promotes migration and invasion in anoikis-resistant prostate cancer cells by enhancing metabolic reprogramming. The FASEB Journal, 32, 3924–3935. https://doi.org/ 10.1096/fj.201701078R. 189. Weng, Y., et al. (2018). The miR-15b-5p/PDK4 axis regulates osteosarcoma proliferation through modulation of the Warburg effect. Biochemical and Biophysical Research Communications, 503, 2749–2757. https://doi.org/10.1016/j.bbrc.2018.08.035. 190. Zhang, Y., Liu, Y., & Xu, X. (2018). Knockdown of LncRNA-UCA1 suppresses chemoresistance of pediatric AML by inhibiting glycolysis through the microRNA-125a/hexokinase 2 pathway. Journal of Cellular Biochemistry, 119, 6296–6308. https://doi.org/10.1002/jcb. 26899.

198

7 Non-coding RNAs Related to Cardiometabolic Diseases …

191. Li, Z., Li, X., Wu, S., Xue, M., & Chen, W. (2014). Long non-coding RNA UCA1 promotes glycolysis by upregulating hexokinase 2 through the mTOR-STAT3/microRNA143 pathway. Cancer Science, 105, 951–955. https://doi.org/10.1111/cas.12461. 192. Hu, M. L., Wang, X. Y., & Chen, W. M. (2018). TGF-beta1 upregulates the expression of lncRNA UCA1 and its downstream HXK2 to promote the growth of hepatocellular carcinoma. European Review for Medical and Pharmacologic, 22, 4846–4854. https://doi.org/10.26355/ eurrev_201808_15620. 193. Mota, M. S. V., et al. (2018). Deficiency of tumor suppressor Merlin facilitates metabolic adaptation by co-operative engagement of SMAD-Hippo signaling in breast cancer. Carcinogenesis, 39, 1165–1175. https://doi.org/10.1093/carcin/bgy078. 194. Feng, Y., et al. (2018). The epigenetically downregulated factor CYGB suppresses breast cancer through inhibition of glucose metabolism. Journal of Experimental & Clinical Cancer Researc, 37, 313. https://doi.org/10.1186/s13046-018-0979-9. 195. Li, T., Xiao, Y., & Huang, T. (2018). HIF1alphainduced upregulation of lncRNA UCA1 promotes cell growth in osteosarcoma by inactivating the PTEN/AKT signaling pathway. Oncology Reports, 39, 1072–1080. https://doi.org/10.3892/or.2018.6182. 196. Zhang, B., Fang, S., Cheng, Y., Zhou, C., & Deng, F. (2019). The long non-coding RNA, urothelial carcinoma associated 1, promotes cell growth, invasion, migration, and chemoresistance in glioma through Wnt/beta-catenin signaling pathway. Aging (Albany NY), 11, 8239–8253. https://doi.org/10.18632/aging.102317. 197. Tian, S., Han, G., Lu, L., & Meng, X. (2020). Circ-FOXM1 contributes to cell proliferation, invasion, and glycolysis and represses apoptosis in melanoma by regulating miR-1433p/FLOT2 axis. World Journal of Surgical Oncology, 18, 56. https://doi.org/10.1186/s12957020-01832-9. 198. Chen, J., et al. (2019). Long non-coding RNA PVT1 promotes tumor progression by regulating the miR-143/HK2 axis in gallbladder cancer. Molecular Cancer, 18, 33. https://doi.org/10. 1186/s12943-019-0947-9. 199. Barajas, J. M., et al. (2018). The role of miR-122 in the dysregulation of glucose-6-phosphate dehydrogenase (G6PD) expression in hepatocellular cancer. Scientific Reports, 8, 9105. https://doi.org/10.1038/s41598-018-27358-5. 200. Xiao, X., et al. (2016). The miR-34a-LDHA axis regulates glucose metabolism and tumor growth in breast cancer. Scientific Reports, 6, 21735. https://doi.org/10.1038/srep21735. 201. Zuo, S., Wu, L., Wang, Y., & Yuan, X. (2020). Long non-coding RNA MEG3 activated by Vitamin D suppresses glycolysis in colorectal cancer via promoting c-Myc degradation. Frontiers in Oncology, 10, 274. https://doi.org/10.3389/fonc.2020.00274. 202. Eichner, L. J., et al. (2010). miR-378( *) mediates metabolic shift in breast cancer cells via the PGC-1beta/ERRgamma transcriptional pathway. Cell Metabolism, 12, 352–361. https:// doi.org/10.1016/j.cmet.2010.09.002. 203. Wang, J., et al. (2015). miRNA-regulated delivery of lincRNA-p21 suppresses beta-catenin signaling and tumorigenicity of colorectal cancer stem cells. Oncotarget, 6, 37852–37870. https://doi.org/10.18632/oncotarget.5635. 204. Zhang, Z., et al. (2016). Wnt/beta-catenin signaling determines the vasculogenic fate of postnatal mesenchymal stem cells. Stem Cells, 34, 1576–1587. https://doi.org/10.1002/stem. 2334. 205. Tirpe, A. A., Gulei, D., Ciortea, S. M., Crivii, C., & Berindan-Neagoe, I. (2019). Hypoxia: Overview on hypoxia-mediated mechanisms with a focus on the role of HIF genes. International Journal of Molecular Sciences, 20. https://doi.org/10.3390/ijms20246140. 206. Olsen, J. J., et al. (2017). The role of Wnt signalling in angiogenesis. Clinical Biochemist Reviews, 38, 131–142. 207. Liao, Y., et al. (2020). Dysregulated Sp1/miR-130b-3p/HOXA5 axis contributes to tumor angiogenesis and progression of hepatocellular carcinoma. Theranostics, 10, 5209–5224. https://doi.org/10.7150/thno.43640. 208. Cheng, Z., et al. (2017). Long non-coding RNA XIST promotes glioma tumorigenicity and angiogenesis by acting as a molecular sponge of miR-429. Journal of Cancer, 8, 4106–4116. https://doi.org/10.7150/jca.21024.

References

199

209. Mao, Z., Xu, B., He, L., & Zhang, G. (2019). PVT1 promotes angiogenesis by regulating miR-29c/vascular endothelial growth factor (VEGF) signaling pathway in non-small-cell lung cancer (NSCLC). Medical Science Monitor, 25, 5418–5425. https://doi.org/10.12659/MSM. 917601. 210. Yu, C., et al. (2019). LncRNA PVT1 regulates VEGFC through inhibiting miR-128 in bladder cancer cells. Journal of Cellular Physiology, 234, 1346–1353. https://doi.org/10.1002/jcp. 26929. 211. Purvis, I. J., et al. (2019). Role of MYC-miR-29-B7-H3 in medulloblastoma growth and angiogenesis. Journal of Clinical Medicine, 8. https://doi.org/10.3390/jcm8081158. 212. Zhang, D., et al. (2018). TGF-beta secreted by tumor-associated macrophages promotes proliferation and invasion of colorectal cancer via miR-34a-VEGF axis. Cell Cycle. https://doi.org/ 10.1080/15384101.2018.1556064. 213. Cao, Z., Xu, L., Zhao, S., & Zhu, X. (2019). The functions of microRNA-124 on bladder cancer. OncoTargets and Therapy, 12, 3429–3439. https://doi.org/10.2147/OTT.S193661. 214. Zhang, H., et al. (2014). MicroRNA-145 inhibits the growth, invasion, metastasis and angiogenesis of neuroblastoma cells through targeting hypoxia-inducible factor 2 alpha. Oncogene, 33, 387–397. https://doi.org/10.1038/onc.2012.574. 215. Chen, X., et al. (2018). miR-150-5p suppresses tumor progression by targeting VEGFA in colorectal cancer. Aging (Albany NY), 10, 3421–3437. https://doi.org/10.18632/aging.101656. 216. Srutova, K., et al. (2018). BCR-ABL1 mediated miR-150 downregulation through MYC contributed to myeloid differentiation block and drug resistance in chronic myeloid leukemia. Haematologica, 103, 2016–2025. https://doi.org/10.3324/haematol.2018.193086. 217. Chen, X., et al. (2018). SP1-induced lncRNA-ZFAS1 contributes to colorectal cancer progression via the miR-150-5p/VEGFA axis. Cell Death and Disease, 9, 982. https://doi.org/10. 1038/s41419-018-0962-6. 218. Qin, L., et al. (2020). A novel tumour suppressor lncRNA F630028O10Rik inhibits lung cancer angiogenesis by regulating miR-223-3p. Journal of Cellular and Molecular Medicine, 24, 3549–3559. https://doi.org/10.1111/jcmm.15044. 219. Zhang, X., Tan, P., Zhuang, Y., & Du, L. (2020). Hsa_circRNA_001587 upregulates SLC4A4 expression to inhibit migration, invasion and angiogenesis of pancreatic cancer cells via binding to microRNA-223. American Journal of Physiology. Gastrointestinal and Liver Physiology. https://doi.org/10.1152/ajpgi.00118.2020. 220. Song, J., Shu, H., Zhang, L., & Xiong, J. (2019). Long noncoding RNA GAS5 inhibits angiogenesis and metastasis of colorectal cancer through the Wnt/beta-catenin signaling pathway. Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb.27743. 221. Ma, H., et al. (2016). MicroRNA-17~92 inhibits colorectal cancer progression by targeting angiogenesis. Cancer Letters, 376, 293–302. https://doi.org/10.1016/j.canlet.2016.04.011. 222. Si, Y., et al. (2017). miR-26a/b inhibit tumor growth and angiogenesis by targeting the HGFVEGF axis in gastric carcinoma. Cellular Physiology and Biochemistry, 42, 1670–1683. https://doi.org/10.1159/000479412. 223. Simanovich, E., Brod, V., Rahat, M. M., & Rahat, M. A. (2017). Function of miR-146a-5p in tumor cells as a regulatory switch between cell death and angiogenesis: Macrophage therapy revisited. Frontiers in Immunology, 8, 1931. https://doi.org/10.3389/fimmu.2017.01931. 224. Klemm, F., & Joyce, J. A. (2015). Microenvironmental regulation of therapeutic response in cancer. Trends in Cell Biology, 25, 198–213. https://doi.org/10.1016/j.tcb.2014.11.006. 225. Salgado, R., et al. (2015). The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: Recommendations by an International TILs Working Group 2014. Annals of Oncology, 26, 259–271. https://doi.org/10.1093/annonc/mdu450. 226. den Haan, J. M., Lehar, S. M., & Bevan, M. J. (2000). CD8(+) but not CD8(-) dendritic cells cross-prime cytotoxic T cells in vivo. Journal of Experimental Medicine, 192, 1685–1696. https://doi.org/10.1084/jem.192.12.1685. 227. Kushwah, R., & Hu, J. (2011). Role of dendritic cells in the induction of regulatory T cells. Cell and Bioscience, 1, 20. https://doi.org/10.1186/2045-3701-1-20.

200

7 Non-coding RNAs Related to Cardiometabolic Diseases …

228. Manicassamy, S., et al. (2010). Activation of beta-catenin in dendritic cells regulates immunity versus tolerance in the intestine. Science, 329, 849–853. https://doi.org/10.1126/science.118 8510. 229. Nair, S., & Dhodapkar, M. V. (2017). Natural killer T cells in cancer immunotherapy. Frontiers in Immunology, 8, 1178. https://doi.org/10.3389/fimmu.2017.01178. 230. Kling, J. C., et al. (2018). Temporal regulation of natural killer T cell interferon gamma responses by beta-catenin-dependent and -independent Wnt signaling. Frontiers in Immunology, 9, 483. https://doi.org/10.3389/fimmu.2018.00483. 231. Chen, Q. Y., et al. (2010). Human CD1D gene expression is regulated by LEF-1 through distal promoter regulatory elements. The Journal of Immunology, 184, 5047–5054. https://doi.org/ 10.4049/jimmunol.0901912. 232. Castagnoli, L., et al. (2019). WNT signaling modulates PD-L1 expression in the stem cell compartment of triple-negative breast cancer. Oncogene, 38, 4047–4060. https://doi.org/10. 1038/s41388-019-0700-2. 233. Vallee, A., Lecarpentier, Y., & Vallee, J. N. (2019). Targeting the canonical WNT/beta-catenin pathway in cancer treatment using non-steroidal anti-inflammatory drugs. Cells, 8. https://doi. org/10.3390/cells8070726. 234. Qu, X., Tang, Y., & Hua, S. (2018). Immunological approaches towards cancer and inflammation: A cross talk. Frontiers in Immunology, 9, 563. https://doi.org/10.3389/fimmu.2018. 00563. 235. Wellenstein, M. D., et al. (2019). Loss of p53 triggers WNT-dependent systemic inflammation to drive breast cancer metastasis. Nature. https://doi.org/10.1038/s41586-019-1450-6. 236. Guo, X., et al. (2016). Hypoxia promotes glioma-associated macrophage infiltration via periostin and subsequent M2 polarization by upregulating TGF-beta and M-CSFR. Oncotarget, 7, 80521–80542. https://doi.org/10.18632/oncotarget.11825. 237. Chen, Y., et al. (2019). TNF-alpha derived from M2 tumor-associated macrophages promotes epithelial-mesenchymal transition and cancer stemness through the Wnt/beta-catenin pathway in SMMC-7721 hepatocellular carcinoma cells. Experimental Cell Research, 378, 41–50. https://doi.org/10.1016/j.yexcr.2019.03.005. 238. Ye, Y. C., et al. (2019). NOTCH signaling via WNT regulates the proliferation of alternative, CCR2-independent tumor-associated macrophages in hepatocellular carcinoma. Cancer Research, 79, 4160–4172. https://doi.org/10.1158/0008-5472.CAN-18-1691. 239. Sierra, R. A., et al. (2014). Rescue of notch-1 signaling in antigen-specific CD8+ T cells overcomes tumor-induced T-cell suppression and enhances immunotherapy in cancer. Cancer Immunology Research, 2, 800–811. https://doi.org/10.1158/2326-6066.CIR-14-0021. 240. Gabrilovich, D. I., & Nagaraj, S. (2009). Myeloid-derived suppressor cells as regulators of the immune system. Nature Reviews Immunology, 9, 162–174. https://doi.org/10.1038/nri2506. 241. Ostrand-Rosenberg, S., & Sinha, P. (2009). Myeloid-derived suppressor cells: Linking inflammation and cancer. The Journal of Immunology, 182, 4499–4506. https://doi.org/10.4049/jim munol.0802740. 242. Liu, Y. S., et al. (2017). MiR-181b modulates EGFR-dependent VCAM-1 expression and monocyte adhesion in glioblastoma. Oncogene, 36, 5006–5022. https://doi.org/10.1038/onc. 2017.129. 243. Huber, V., et al. (2018). Tumor-derived microRNAs induce myeloid suppressor cells and predict immunotherapy resistance in melanoma. Journal of Clinical Investigation, 128, 5505– 5516. https://doi.org/10.1172/JCI98060. 244. Sun, X., et al. (2015). miR-146a is directly regulated by STAT3 in human hepatocellular carcinoma cells and involved in anti-tumor immune suppression. Cell Cycle, 14, 243–252. https://doi.org/10.4161/15384101.2014.977112. 245. Tian, J., et al. (2015). MicroRNA-9 regulates the differentiation and function of myeloidderived suppressor cells via targeting Runx1. The Journal of Immunology, 195, 1301–1311. https://doi.org/10.4049/jimmunol.1500209. 246. Jiang, M., et al. (2020). Cancer exosome-derived miR-9 and miR-181a promote the development of early-stage MDSCs via interfering with SOCS3 and PIAS3 respectively in breast cancer. Oncogene, 39, 4681–4694. https://doi.org/10.1038/s41388-020-1322-4.

References

201

247. Xu, Z., et al. (2017). MiR-30a increases MDSC differentiation and immunosuppressive function by targeting SOCS3 in mice with B-cell lymphoma. FEBS Journal, 284, 2410–2424. https://doi.org/10.1111/febs.14133. 248. Tominaga, T., et al. (2019). Clinical significance of soluble programmed cell death-1 and soluble programmed cell death-ligand 1 in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy. PLoS ONE, 14, e0212978. https://doi.org/10.1371/jou rnal.pone.0212978. 249. Yang, Z., Liao, B., Xiang, X., & Ke, S. (2020). MiR-21-5p promotes cell proliferation and G1/S transition in melanoma by targeting CDKN2C. FEBS Open Bio. https://doi.org/10.1002/ 2211-5463.12819. 250. Ren, W., et al. (2019). Extracellular vesicles secreted by hypoxia pre-challenged mesenchymal stem cells promote non-small cell lung cancer cell growth and mobility as well as macrophage M2 polarization via miR-21-5p delivery. Journal of Experimental & Clinical Cancer Researc, 38, 62. https://doi.org/10.1186/s13046-019-1027-0. 251. Guo, X., et al. (2018). Immunosuppressive effects of hypoxia-induced glioma exosomes through myeloid-derived suppressor cells via the miR-10a/Rora and miR-21/Pten Pathways. Oncogene, 37, 4239–4259. https://doi.org/10.1038/s41388-018-0261-9. 252. Qiu, C., Ma, J., Wang, M. L., Zhang, Q., & Li, Y. B. (2019). MicroRNA-155 deficiency in CD8+ T cells inhibits its anti-glioma immunity by regulating FoxO3a. European Review for Medical and Pharmacologic, 23, 2486–2496. https://doi.org/10.26355/eurrev_201903_ 17396. 253. Ling, N., et al. (2013). microRNA-155 regulates cell proliferation and invasion by targeting FOXO3a in glioma. Oncology Reports, 30, 2111–2118. https://doi.org/10.3892/or.2013.2685. 254. Jia, J., Li, X., Guo, S., & Xie, X. (2020). MicroRNA-155 suppresses the translation of p38 and impairs the functioning of dendritic cells in endometrial cancer mice. Cancer Management and Research, 12, 2993–3002. https://doi.org/10.2147/CMAR.S240926. 255. Xue, Y., et al. (2019). Tumorinfiltrating M2 macrophages driven by specific genomic alterations are associated with prognosis in bladder cancer. Oncology Reports, 42, 581–594. https:// doi.org/10.3892/or.2019.7196. 256. Yang, M., et al. (2011). Microvesicles secreted by macrophages shuttle invasion-potentiating microRNAs into breast cancer cells. Molecular Cancer, 10, 117. https://doi.org/10.1186/14764598-10-117. 257. Lu, M. Y., et al. (2017). Targeting LncRNA HOTAIR suppresses cancer stemness and metastasis in oral carcinomas stem cells through modulation of EMT. Oncotarget, 8, 98542–98552. https://doi.org/10.18632/oncotarget.21614. 258. Cai, H., et al. (2016). Epigenetic inhibition of miR-663b by long non-coding RNA HOTAIR promotes pancreatic cancer cell proliferation via up-regulation of insulin-like growth factor 2. Oncotarget, 7, 86857–86870. https://doi.org/10.18632/oncotarget.13490. 259. Chen, Y., et al. (2019). LIN28/let-7/PD-L1 pathway as a target for cancer immunotherapy. Cancer Immunology Research. https://doi.org/10.1158/2326-6066.CIR-18-0331. 260. Wang, L., et al. (2018). Small-molecule inhibitors disrupt let-7 oligouridylation and release the selective blockade of let-7 processing by LIN28. Cell Reports, 23, 3091–3101. https:// doi.org/10.1016/j.celrep.2018.04.116. 261. Huang, J., et al. (2018). Role of Lin28A/let-7a/c-Myc pathway in growth and malignant behavior of papillary thyroid carcinoma. Medical Science Monitor, 24, 8899–8909. https:// doi.org/10.12659/MSM.908628. 262. Li, J. P., et al. (2018). Hyperoside and let-7a-5p synergistically inhibits lung cancer cell proliferation via inducing G1/S phase arrest. Gene, 679, 232–240. https://doi.org/10.1016/j. gene.2018.09.011. 263. Baer, C., et al. (2016). Suppression of microRNA activity amplifies IFN-gamma-induced macrophage activation and promotes anti-tumour immunity. Nature Cell Biology, 18, 790– 802. https://doi.org/10.1038/ncb3371. 264. Liang, R., et al. (2018). MiR-146a promotes the asymmetric division and inhibits the selfrenewal ability of breast cancer stem-like cells via indirect upregulation of Let-7. Cell Cycle, 17, 1445–1456. https://doi.org/10.1080/15384101.2018.1489176.

202

7 Non-coding RNAs Related to Cardiometabolic Diseases …

265. Wang, M., et al. (2019). H19 regulation of oestrogen induction of symmetric division is achieved by antagonizing Let-7c in breast cancer stem-like cells. Cell Proliferation, 52, e12534. https://doi.org/10.1111/cpr.12534. 266. Zhao, B., et al. (2018). Overexpression of lncRNA ANRIL promoted the proliferation and migration of prostate cancer cells via regulating let-7a/TGF-beta1/ Smad signaling pathway. Cancer Biomark, 21, 613–620. https://doi.org/10.3233/CBM-170683. 267. Zhang, M., et al. (2011). Both miR-17-5p and miR-20a alleviate suppressive potential of myeloid-derived suppressor cells by modulating STAT3 expression. The Journal of Immunology, 186, 4716–4724. https://doi.org/10.4049/jimmunol.1002989. 268. Wang, C. J., et al. (2019). The lncRNA UCA1 promotes proliferation, migration, immune escape and inhibits apoptosis in gastric cancer by sponging anti-tumor miRNAs. Molecular Cancer, 18, 115. https://doi.org/10.1186/s12943-019-1032-0. 269. Guan, X., Fang, Y., Long, J., & Zhang, Y. (2019). Annexin 1-nuclear factor-kappaBmicroRNA-26a regulatory pathway in the metastasis of non-small cell lung cancer. Thoracic Cancer, 10, 665–675. https://doi.org/10.1111/1759-7714.12982. 270. Mi, X., et al. (2020). M2 macrophage-derived exosomal lncRNA AFAP1-AS1 and MicroRNA-26a affect cell migration and metastasis in esophageal cancer. Molecular Therapy - Nucleic Acids, 22, 779–790. https://doi.org/10.1016/j.omtn.2020.09.035. 271. Xu, X., et al. (2019). Inhibition of PTP1B promotes M2 polarization via MicroRNA26a/MKP1 signaling pathway in murine macrophages. Frontiers in Immunology, 10, 1930. https://doi.org/10.3389/fimmu.2019.01930. 272. Yang, P., et al. (2012). TGF-beta-miR-34a-CCL22 signaling-induced Treg cell recruitment promotes venous metastases of HBV-positive hepatocellular carcinoma. Cancer Cell, 22, 291–303. https://doi.org/10.1016/j.ccr.2012.07.023. 273. Ayoub, M., et al. (2019). The immune mediated role of extracellular HMGB1 in a heterotopic model of bladder cancer radioresistance. Scientific Reports, 9, 6348. https://doi.org/10.1038/ s41598-019-42864-w. 274. Zhou, Y., Li, Y., Lu, J., Hong, X., & Xu, L. (2019). MicroRNA30a controls the instability of inducible CD4+ Tregs through SOCS1. Molecular Medicine Reports, 20, 4303–4314. https:// doi.org/10.3892/mmr.2019.10666. 275. Xu, Y., et al. (2018). Long non-coding RNA PVT1/miR-150/HIG2 axis regulates the proliferation, invasion and the balance of iron metabolism of hepatocellular carcinoma. Cellular Physiology and Biochemistry, 49, 1403–1419. https://doi.org/10.1159/000493445. 276. Cui, C., et al. (2019). Hypoxia-inducible gene 2 promotes the immune escape of hepatocellular carcinoma from nature killer cells through the interleukin-10-STAT3 signaling pathway. Journal of Experimental & Clinical Cancer Researc, 38, 229. https://doi.org/10.1186/s13046019-1233-9. 277. Ito, M., et al. (2014). MicroRNA-150 inhibits tumor invasion and metastasis by targeting the chemokine receptor CCR6, in advanced cutaneous T-cell lymphoma. Blood, 123, 1499–1511. https://doi.org/10.1182/blood-2013-09-527739. 278. Khosravi, N., et al. (2018). IL22 Promotes Kras-Mutant lung cancer by induction of a protumor immune response and protection of stemness properties. Cancer Immunology Research, 6, 788–797. https://doi.org/10.1158/2326-6066.CIR-17-0655. 279. Zhao, Y., Zhao, J., Guo, X., She, J., & Liu, Y. (2018). Long non-coding RNA PVT1, a molecular sponge for miR-149, contributes aberrant metabolic dysfunction and inflammation in IL-1beta-simulated osteoarthritic chondrocytes. Bioscience Reports, 38. https://doi.org/10. 1042/BSR20180576. 280. Moradi-Chaleshtori, M., Bandehpour, M., Soudi, S., Mohammadi-Yeganeh, S., & Hashemi, S. M. (2020). In vitro and in vivo evaluation of anti-tumoral effect of M1 phenotype induction in macrophages by miR-130 and miR-33 containing exosomes. Cancer Immunology, Immunotherapy. https://doi.org/10.1007/s00262-020-02762-x. 281. Cai, X., et al. (2012). Re-polarization of tumor-associated macrophages to pro-inflammatory M1 macrophages by microRNA-155. Journal of Molecular Cell Biology, 4, 341–343. https:// doi.org/10.1093/jmcb/mjs044.

References

203

282. Liu, T., et al. (2018). Circular RNA-ZFR inhibited cell proliferation and promoted apoptosis in gastric cancer by sponging miR-130a/miR-107 and modulating PTEN. Cancer Research and Treatment, 50, 1396–1417. https://doi.org/10.4143/crt.2017.537. 283. Tan, W., et al. (2018). miRNA 146a promotes chemotherapy resistance in lung cancer cells by targeting DNA damage inducible transcript 3 (CHOP). Cancer Letters, 428, 55–68. https:// doi.org/10.1016/j.canlet.2018.04.028. 284. Li, T., et al. (2019). miR146a regulates the function of Th17 cell differentiation to modulate cervical cancer cell growth and apoptosis through NFkappaB signaling by targeting TRAF6. Oncology Reports, 41, 2897–2908. https://doi.org/10.3892/or.2019.7046. 285. Li, P., et al. (2017). lncRNA HOTAIR contributes to 5FU resistance through suppressing miR-218 and activating NF-kappaB/TS signaling in colorectal cancer. Molecular Therapy Nucleic Acids, 8, 356–369. https://doi.org/10.1016/j.omtn.2017.07.007. 286. Baras, A. S., Solomon, A., Davidson, R., & Moskaluk, C. A. (2011). Loss of VOPP1 overexpression in squamous carcinoma cells induces apoptosis through oxidative cellular injury. Laboratory Investigation, 91, 1170–1180. https://doi.org/10.1038/labinvest.2011.70. 287. Liu, J., et al. (2019). MicroRNA-142-3p/MALAT1 inhibits lung cancer progression through repressing beta-catenin expression. Biomedicine & Pharmacotherapy, 114, 108847. https:// doi.org/10.1016/j.biopha.2019.108847. 288. Ma, Y., et al. (2019). LncRNA ANRIL promotes cell growth, migration and invasion of hepatocellular carcinoma cells via sponging miR-144. Anti-Cancer Drugs, 30, 1013–1021. https://doi.org/10.1097/CAD.0000000000000807. 289. Zhu, H., et al. (2011). The Lin28/let-7 axis regulates glucose metabolism. Cell, 147, 81–94. https://doi.org/10.1016/j.cell.2011.08.033. 290. Benhamed, M., Herbig, U., Ye, T., Dejean, A., & Bischof, O. (2012). Senescence is an endogenous trigger for microRNA-directed transcriptional gene silencing in human cells. Nature Cell Biology, 14, 266–275. https://doi.org/10.1038/ncb2443. 291. Han, Y., et al. (2018). miR-9 inhibits the metastatic ability of hepatocellular carcinoma via targeting beta galactoside alpha-2,6-sialyltransferase 1. Journal of Physiology and Biochemistry, 74, 491–501. https://doi.org/10.1007/s13105-018-0642-0. 292. Wu, M., et al. (2019). LncRNA MEG3 inhibits the progression of prostate cancer by modulating miR-9-5p/QKI-5 axis. Journal of Cellular and Molecular Medicine, 23, 29–38. https:// doi.org/10.1111/jcmm.13658. 293. Xie, Q., Lin, S., Zheng, M., Cai, Q., & Tu, Y. (2019). Long noncoding RNA NEAT1 promotes the growth of cervical cancer cells via sponging miR-9-5p. Biochemistry and Cell Biology, 97, 100–108. https://doi.org/10.1139/bcb-2018-0111. 294. Xie, C. H., et al. (2016). Long non-coding RNA TUG1 contributes to tumorigenesis of human osteosarcoma by sponging miR-9-5p and regulating POU2F1 expression. Tumour Biology, 37, 15031–15041. https://doi.org/10.1007/s13277-016-5391-5. 295. Sionov, R. V., Vlahopoulos, S. A., & Granot, Z. (2015). Regulation of bim in health and disease. Oncotarget, 6, 23058–23134. https://doi.org/10.18632/oncotarget.5492. 296. Gao, X. M., et al. (2018). microRNA-26a induces a mitochondrial apoptosis mediated by p53 through targeting to inhibit Mcl1 in human hepatocellular carcinoma. OncoTargets and Therapy, 11, 2227–2239. https://doi.org/10.2147/OTT.S160895. 297. D’Abundo, L., et al. (2017). Anti-leukemic activity of microRNA-26a in a chronic lymphocytic leukemia mouse model. Oncogene, 36, 6617–6626. https://doi.org/10.1038/onc.201 7.269. 298. Pan, Y., et al. (2019). LncRNA H19 overexpression induces bortezomib resistance in multiple myeloma by targeting MCL-1 via miR-29b-3p. Cell Death and Disease, 10, 106. https://doi. org/10.1038/s41419-018-1219-0. 299. Xu, M., et al. (2019). MicroRNA-29 targets FGF2 and inhibits the proliferation, migration and invasion of nasopharyngeal carcinoma cells via PI3K/AKT signaling pathway. European Review for Medical and Pharmacologic, 23, 5215–5222. https://doi.org/10.26355/eurrev_201 906_18186.

204

7 Non-coding RNAs Related to Cardiometabolic Diseases …

300. Li, J., Xu, X., Wei, C., Liu, L., & Wang, T. (2020). Long noncoding RNA NORAD regulates lung cancer cell proliferation, apoptosis, migration, and invasion by the miR-30a-5p/ADAM19 axis. International Journal of Clinical and Experimental Pathology, 13, 1–13. 301. Liu, L., Ren, W., & Chen, K. (2017). MiR-34a promotes apoptosis and inhibits autophagy by targeting HMGB1 in acute myeloid leukemia cells. Cellular Physiology and Biochemistry, 41, 1981–1992. https://doi.org/10.1159/000475277. 302. Chen, Y. M., Liu, Y., Wei, H. Y., Lv, K. Z., & Fu, P. F. (2016). Large intergenic non-coding RNA-ROR reverses gemcitabine-induced autophagy and apoptosis in breast cancer cells. Oncotarget, 7, 59604–59617. https://doi.org/10.18632/oncotarget.10730. 303. Li, T. F., Liu, J., & Fu, S. J. (2018). The interaction of long non-coding RNA MIAT and miR-133 play a role in the proliferation and metastasis of pancreatic carcinoma. Biomedicine & Pharmacotherapy, 104, 145–150. https://doi.org/10.1016/j.biopha.2018.05.043. 304. Li, X., et al. (2019). LncRNA NEAT1 silenced miR-133b promotes migration and invasion of breast cancer cells. International Journal of Molecular Sciences, 20. https://doi.org/10.3390/ ijms20153616. 305. Zhou, K., Yang, J., Li, X., & Chen, W. (2019). Long non-coding RNA XIST promotes cell proliferation and migration through targeting miR-133a in bladder cancer. Experimental and Therapeutic Medicine, 18, 3475–3483. https://doi.org/10.3892/etm.2019.7960. 306. Yu, X., et al. (2019). CXCL12/CXCR4 promotes inflammation-driven colorectal cancer progression through activation of RhoA signaling by sponging miR-133a-3p. Journal of Experimental & Clinical Cancer Researc, 38, 32. https://doi.org/10.1186/s13046-018-1014-x. 307. Beyer, K., et al. (2019). Interactions of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) with the immune system: Implications for inflammation and cancer. Cancers (Basel), 11. https://doi.org/10.3390/cancers11081161. 308. Xiao, X. H., et al. (2018). Regulating Cdc42 and its signaling pathways in cancer: Small molecules and MicroRNA as new treatment candidates. Molecules, 23. https://doi.org/10. 3390/molecules23040787. 309. Cheng, Z., et al. (2014). miR-133 is a key negative regulator of CDC42-PAK pathway in gastric cancer. Cellular Signalling, 26, 2667–2673. https://doi.org/10.1016/j.cellsig.2014.08.012. 310. Perez-Yepez, E. A., Saldivar-Ceron, H. I., Villamar-Cruz, O., Perez-Plasencia, C., & AriasRomero, L. E. (2018). p21 Activated kinase 1: Nuclear activity and its role during DNA damage repair. DNA Repair (Amst), 65, 42–46. https://doi.org/10.1016/j.dnarep.2018.03.004. 311. Zhang, Z. L., et al. (2018). Effect of PAK1 gene silencing on proliferation and apoptosis in hepatocellular carcinoma cell lines MHCC97-H and HepG2 and cells in xenograft tumor. Gene Therapy, 25, 284–296. https://doi.org/10.1038/s41434-018-0016-9. 312. Li, C., et al. (2019). Prognostic roles of microRNA 143 and microRNA 145 in colorectal cancer: A meta-analysis. The International Journal of Biological Markers. https://doi.org/10. 1177/1724600818807492. 313. Gomes, S. E., et al. (2016). miR-143 or miR-145 overexpression increases cetuximabmediated antibody-dependent cellular cytotoxicity in human colon cancer cells. Oncotarget, 7, 9368–9387. https://doi.org/10.18632/oncotarget.7010. 314. Zhuang, S., Liu, F., & Wu, P. (2019). Upregulation of long noncoding RNA TUG1 contributes to the development of laryngocarcinoma by targeting miR-145-5p/ROCK1 axis. Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb.28614. 315. Zheng, M., Sun, X., Li, Y., & Zuo, W. (2016). MicroRNA-145 inhibits growth and migration of breast cancer cells through targeting oncoprotein ROCK1. Tumour Biology, 37, 8189–8196. https://doi.org/10.1007/s13277-015-4722-2. 316. Jiao, L., et al. (2018). Regulation of glycolytic metabolism by autophagy in liver cancer involves selective autophagic degradation of HK2 (hexokinase 2). Autophagy, 14, 671–684. https://doi.org/10.1080/15548627.2017.1381804. 317. Chen, Z., Zhen, M., & Zhou, J. (2019). LncRNA BRE-AS1 interacts with miR-145-5p to regulate cancer cell proliferation and apoptosis in prostate carcinoma and has early diagnostic values. Bioscience Reports, 39. https://doi.org/10.1042/BSR20182097.

References

205

318. Sun, X., Zhang, C., Cao, Y., & Liu, E. (2019). miR-150 suppresses tumor growth in melanoma through downregulation of MYB. Oncology Research, 27, 317–323. https://doi.org/10.3727/ 096504018X15228863026239. 319. Kim, T. H., et al. (2017). miR-150 enhances apoptotic and anti-tumor effects of paclitaxel in paclitaxel-resistant ovarian cancer cells by targeting Notch3. Oncotarget, 8, 72788–72800. https://doi.org/10.18632/oncotarget.20348. 320. Somnay, Y. R., et al. (2017). Notch3 expression correlates with thyroid cancer differentiation, induces apoptosis, and predicts disease prognosis. Cancer, 123, 769–782. https://doi.org/10. 1002/cncr.30403. 321. Alipoor, F. J., Asadi, M. H., & Torkzadeh-Mahani, M. (2018). MIAT lncRNA is overexpressed in breast cancer and its inhibition triggers senescence and G1 arrest in MCF7 cell line. Journal of Cellular Biochemistry, 119, 6470–6481. https://doi.org/10.1002/jcb.26678. 322. Liang, L., et al. (2019). Long noncoding RNA ZFAS1 promotes tumorigenesis through regulation of miR-150-5p/RAB9A in melanoma. Melanoma Research. https://doi.org/10.1097/ CMR.0000000000000595. 323. Yuan, L., et al. (2017). MiR-124 inhibits invasion and induces apoptosis of ovarian cancer cells by targeting programmed cell death 6. Oncology Letters, 14, 7311–7317. https://doi.org/ 10.3892/ol.2017.7157. 324. Shi, L., et al. (2008). hsa-mir-181a and hsa-mir-181b function as tumor suppressors in human glioma cells. Brain Research, 1236, 185–193. https://doi.org/10.1016/j.brainres.2008.07.085. 325. Huang, P., Ye, B., Yang, Y., Shi, J., & Zhao, H. (2015). MicroRNA-181 functions as a tumor suppressor in non-small cell lung cancer (NSCLC) by targeting Bcl-2. Tumour Biology, 36, 3381–3387. https://doi.org/10.1007/s13277-014-2972-z. 326. Zheng, S., Li, M., Miao, K., & Xu, H. (2019). lncRNA GAS5-promoted apoptosis in triple-negative breast cancer by targeting miR-378a-5p/SUFU signaling. Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb.29445. 327. Gong, X., & Huang, M. (2017). Long non-coding RNA MEG3 promotes the proliferation of glioma cells through targeting Wnt/beta-catenin signal pathway. Cancer Gene Therapy, 24, 381–385. https://doi.org/10.1038/cgt.2017.32. 328. Liu, Z., Wu, C., Xie, N., & Wang, P. (2017). Long non-coding RNA MEG3 inhibits the proliferation and metastasis of oral squamous cell carcinoma by regulating the WNT/betacatenin signaling pathway. Oncology Letters, 14, 4053–4058. https://doi.org/10.3892/ol.2017. 6682. 329. Xu, Y. T., et al. (2018). Defining the regulatory role of programmed cell death 4 in laryngeal squamous cell carcinoma. Biochemistry and Cell Biology, 96, 522–538. https://doi.org/10. 1139/bcb-2017-0293. 330. Wang, H., Li, H., Zhang, L., & Yang, D. (2018). Overexpression of MEG3 sensitizes colorectal cancer cells to oxaliplatin through regulation of miR-141/PDCD4 axis. Biomedicine & Pharmacotherapy, 106, 1607–1615. https://doi.org/10.1016/j.biopha.2018.07.131. 331. Jadaliha, M., et al. (2018). A natural antisense lncRNA controls breast cancer progression by promoting tumor suppressor gene mRNA stability. PLoS Genetics, 14, e1007802. https://doi. org/10.1371/journal.pgen.1007802. 332. Duan, J., et al. (2016). Onco-miR-130 promotes cell proliferation and migration by targeting TGFbetaR2 in gastric cancer. Oncotarget, 7, 44522–44533. https://doi.org/10.18632/oncota rget.9936. 333. Yu, M. J., Zhao, N., Shen, H., & Wang, H. (2018). Long noncoding RNA MRPL39 inhibits gastric cancer proliferation and progression by directly targeting miR-130. Genetic Testing and Molecular Biomarkers, 22, 656–663. https://doi.org/10.1089/gtmb.2018.0151. 334. Su, D., et al. (2020). Long-noncoding RNA FGD5-AS1 enhances the viability, migration, and invasion of glioblastoma cells by regulating the miR-103a-3p/TPD52 axis. Cancer Management and Research, 12, 6317–6329. https://doi.org/10.2147/CMAR.S253467. 335. Zhang, L., et al. (2018). The miR-181 family promotes cell cycle by targeting CTDSPL, a phosphatase-like tumor suppressor in uveal melanoma. Journal of Experimental & Clinical Cancer Researc, 37, 15. https://doi.org/10.1186/s13046-018-0679-5.

206

7 Non-coding RNAs Related to Cardiometabolic Diseases …

336. Shi, Q., et al. (2017). MiR-181a inhibits non-small cell lung cancer cell proliferation by targeting CDK1. Cancer Biomark, 20, 539–546. https://doi.org/10.3233/CBM-170350. 337. Fu, F., et al. (2018). HMGA1 exacerbates tumor growth through regulating the cell cycle and accelerates migration/invasion via targeting miR-221/222 in cervical cancer. Cell Death and Disease, 9, 594. https://doi.org/10.1038/s41419-018-0683-x. 338. Yang, F., et al. (2018). NF-kappaB/miR-223-3p/ARID1A axis is involved in Helicobacter pylori CagA-induced gastric carcinogenesis and progression. Cell Death and Disease, 9, 12. https://doi.org/10.1038/s41419-017-0020-9. 339. Luo, P., et al. (2019). MiR-223-3p functions as a tumor suppressor in lung squamous cell carcinoma by miR-223-3p-mutant p53 regulatory feedback loop. Journal of Experimental & Clinical Cancer Researc, 38, 74. https://doi.org/10.1186/s13046-019-1079-1. 340. Dou, L., Han, K., Xiao, M., & Lv, F. (2019). miR-223-5p suppresses tumor growth and metastasis in non-small cell lung cancer by targeting E2F8. Oncology Research, 27, 261–268. https://doi.org/10.3727/096504018X15219188894056. 341. Dong, X., et al. (2018). GAS5 functions as a ceRNA to regulate hZIP1 expression by sponging miR-223 in clear cell renal cell carcinoma. American Journal of Cancer Research, 8, 1414– 1426. 342. Li, J. P., et al. (2019). Long noncoding RNA H19 competitively binds miR-93-5p to regulate STAT3 expression in breast cancer. Journal of Cellular Biochemistry, 120, 3137–3148. https:// doi.org/10.1002/jcb.27578. 343. Hassan, N., Zhao, J., Glover, A. R., Robinson, B. G., & Sidhu, S. B. (2019). Reciprocal interplay of miR-497 and MALAT1 promotes tumourigenesis of adrenocortical cancer. Endocrine-Related Cancer. https://doi.org/10.1530/ERC-19-0036. 344. Pisera, A., Campo, A., & Campo, S. (2018). Structure and functions of the translation initiation factor eIF4E and its role in cancer development and treatment. Journal of Genetics and Genomics, 45, 13–24. https://doi.org/10.1016/j.jgg.2018.01.003. 345. Zhang, L., et al. (2019). NEAT1 induces osteosarcoma development by modulating the miR339-5p/TGF-beta1 pathway. Journal of Cellular Physiology, 234, 5097–5105. https://doi.org/ 10.1002/jcp.27313. 346. Tu, J., et al. (2018). NEAT1 upregulates TGF-beta1 to induce hepatocellular carcinoma progression by sponging hsa-mir-139-5p. Journal of Cellular Physiology, 233, 8578–8587. https://doi.org/10.1002/jcp.26524. 347. Kong, X., et al. (2019). Overexpression of HIF-2alpha-dependent NEAT1 promotes the progression of non-small cell lung cancer through miR-101-3p/SOX9/Wnt/beta-catenin signal pathway. Cellular Physiology and Biochemistry, 52, 368–381. https://doi.org/10.33594/000 000026. 348. Yong, W., et al. (2018). Long noncoding RNA NEAT1, regulated by LIN28B, promotes cell proliferation and migration through sponging miR-506 in high-grade serous ovarian cancer. Cell Death and Disease, 9, 861. https://doi.org/10.1038/s41419-018-0908-z. 349. Xia, Y., et al. (2019). lncRNA NEAT1 facilitates melanoma cell proliferation, migration, and invasion via regulating miR-495-3p and E2F3. Journal of Cellular Physiology, 234, 19592–19601. https://doi.org/10.1002/jcp.28559. 350. Yan, Q., Tian, Y., & Hao, F. (2018). Downregulation of lncRNA UCA1 inhibits proliferation and invasion of cervical cancer cells through miR-206 expression. Oncology Research. https:// doi.org/10.3727/096504018X15185714083446. 351. Long, J., Menggen, Q., Wuren, Q., Shi, Q., & Pi, X. (2018). Long noncoding RNA taurineupregulated gene1 (TUG1) promotes tumor growth and metastasis through TUG1/Mir-1295p/astrocyte-elevated gene-1 (AEG-1) axis in malignant melanoma. Medical Science Monitor, 24, 1547–1559. 352. Cui, M., et al. (2019). LncRNA-UCA1 modulates progression of colon cancer through regulating the miR-28-5p/HOXB3 axis. Journal of Cellular Biochemistry. https://doi.org/10.1002/ jcb.27630. 353. He, C., et al. (2019). LncRNA UCA1 acts as a sponge of miR-204 to up-regulate CXCR4 expression and promote prostate cancer progression. Bioscience Reports, 39. https://doi.org/ 10.1042/BSR20181465.

References

207

354. Guo, N., Sun, Q., Fu, D., & Zhang, Y. (2019). Long non-coding RNA UCA1 promoted the growth of adrenocortical cancer cells via modulating the miR-298-CDK6 axis. Gene, 703, 26–34. https://doi.org/10.1016/j.gene.2019.03.066. 355. Sun, L., Liu, L., Yang, J., Li, H., & Zhang, C. (2019). SATB1 3’-UTR and lncRNA-UCA1 competitively bind to miR-495-3p and together regulate the proliferation and invasion of gastric cancer. Journal of Cellular Biochemistry, 120, 6671–6682. https://doi.org/10.1002/ jcb.27963. 356. Bian, Z., et al. (2016). LncRNA-UCA1 enhances cell proliferation and 5-fluorouracil resistance in colorectal cancer by inhibiting miR-204-5p. Scientific Reports, 6, 23892. https://doi. org/10.1038/srep23892. 357. Zhou, Y., et al. (2018). IMP1 regulates UCA1-mediated cell invasion through facilitating UCA1 decay and decreasing the sponge effect of UCA1 for miR-122-5p. Breast Cancer Research, 20, 32. https://doi.org/10.1186/s13058-018-0959-1. 358. Sun, J., & Zhang, Y. (2019). LncRNA XIST enhanced TGF-beta2 expression by targeting miR-141-3p to promote pancreatic cancer cells invasion. Bioscience Reports, 39. https://doi. org/10.1042/BSR20190332. 359. Zhou, X., Xu, X., Gao, C., & Cui, Y. (2019). XIST promote the proliferation and migration of non-small cell lung cancer cells via sponging miR-16 and regulating CDK8 expression. American Journal of Translational Research, 11, 6196–6206. 360. Zhang, Y., et al. (2019). lncRNA XIST regulates proliferation and migration of hepatocellular carcinoma cells by acting as miR-497-5p molecular sponge and targeting PDCD4. Cancer Cell International, 19, 198. https://doi.org/10.1186/s12935-019-0909-8. 361. Hwang, S. K., Jeong, Y. J., & Chang, Y. C. (2020). PDCD4 inhibits lung tumorigenesis by the suppressing p62-Nrf2 signaling pathway and upregulating Keap1 expression. American Journal of Cancer Research, 10, 424–439. 362. Zhang, F., et al. (2019). Long non-coding RNA ZFAS1 regulates the malignant progression of gastric cancer via the microRNA-200b-3p/Wnt1 axis. Bioscience, Biotechnology, and Biochemistry, 83, 1289–1299. https://doi.org/10.1080/09168451.2019.1606697. 363. Xie, S., Ge, Q., Wang, X., Sun, X., & Kang, Y. (2018). Long non-coding RNA ZFAS1 sponges miR-484 to promote cell proliferation and invasion in colorectal cancer. Cell Cycle, 17, 154–161. https://doi.org/10.1080/15384101.2017.1407895. 364. Zhang, L. M., et al. (2018). Long non-coding RNA ANRIL promotes tumorgenesis through regulation of FGFR1 expression by sponging miR-125a-3p in head and neck squamous cell carcinoma. American Journal of Cancer Research, 8, 2296–2310. 365. Ma, J., Li, T., Han, X., & Yuan, H. (2018). Knockdown of LncRNA ANRIL suppresses cell proliferation, metastasis, and invasion via regulating miR-122-5p expression in hepatocellular carcinoma. Journal of Cancer Research and Clinical Oncology, 144, 205–214. https://doi.org/ 10.1007/s00432-017-2543-y. 366. Drak Alsibai, K., et al. (2019). High positive correlations between ANRIL and p16CDKN2A/p15-CDKN2B/p14-ARF gene cluster overexpression in multi-tumor types suggest deregulated activation of an ANRIL-ARF bidirectional promoter. Noncoding RNA, 5. https:// doi.org/10.3390/ncrna5030044. 367. Dankert, J. T., et al. (2018). The deregulation of miR-17/CCND1 axis during neuroendocrine transdifferentiation of LNCaP prostate cancer cells. PLoS ONE, 13, e0200472. https://doi. org/10.1371/journal.pone.0200472. 368. Sun, G., et al. (2018). Decreased MiR-17 in glioma cells increased cell viability and migration by increasing the expression of Cyclin D1, p-Akt and Akt. PLoS ONE, 13, e0190515. https:// doi.org/10.1371/journal.pone.0190515. 369. Huang, F. X., et al. (2019). LncRNA BLACAT1 is involved in chemoresistance of nonsmall cell lung cancer cells by regulating autophagy. International Journal of Oncology, 54, 339– 347. https://doi.org/10.3892/ijo.2018.4614. 370. Zhang, G., An, X., Zhao, H., Zhang, Q., & Zhao, H. (2018). Long non-coding RNA HNF1AAS1 promotes cell proliferation and invasion via regulating miR-17-5p in non-small cell lung cancer. Biomedicine & Pharmacotherapy, 98, 594–599. https://doi.org/10.1016/j.bio pha.2017.12.080.

208

7 Non-coding RNAs Related to Cardiometabolic Diseases …

371. Huang, Z., Lei, W., Hu, H. B., Zhang, H., & Zhu, Y. (2018). H19 promotes non-small-cell lung cancer (NSCLC) development through STAT3 signaling via sponging miR-17. Journal of Cellular Physiology, 233, 6768–6776. https://doi.org/10.1002/jcp.26530. 372. Jia, J., et al. (2019). The contrary functions of lncRNA HOTAIR/miR-17-5p/PTEN axis and Shenqifuzheng injection on chemosensitivity of gastric cancer cells. Journal of Cellular and Molecular Medicine, 23, 656–669. https://doi.org/10.1111/jcmm.13970. 373. Yu, J., et al. (2018). Circular RNA cSMARCA5 inhibits growth and metastasis in hepatocellular carcinoma. Journal of Hepatology, 68, 1214–1227. https://doi.org/10.1016/j.jhep.2018. 01.012. 374. Liu, H., et al. (2019). The SOX4/miR-17-92/RB1 Axis Promotes Prostate Cancer Progression. Neoplasia, 21, 765–776. https://doi.org/10.1016/j.neo.2019.05.007. 375. Spagnuolo, M., et al. (2019). Transcriptional activation of the miR-17-92 cluster is involved in the growth-promoting effects of MYB in human Ph-positive leukemia cells. Haematologica, 104, 82–92. https://doi.org/10.3324/haematol.2018.191213. 376. Zhang, B., Chen, M., Jiang, N., Shi, K., & Qian, R. (2019). A regulatory circuit of circMTO1/miR-17/QKI-5 inhibits the proliferation of lung adenocarcinoma. Cancer Biology & Therapy, 1–9. https://doi.org/10.1080/15384047.2019.1598762. 377. Yang, C., et al. (2018). Circular RNA circ-ITCH inhibits bladder cancer progression by sponging miR-17/miR-224 and regulating p21, PTEN expression. Molecular Cancer, 17, 19. https://doi.org/10.1186/s12943-018-0771-7. 378. Li, J., et al. (2017). miR-26a and miR-26b inhibit esophageal squamous cancer cell proliferation through suppression of c-MYC pathway. Gene, 625, 1–9. https://doi.org/10.1016/j.gene. 2017.05.001. 379. Gong, Y., et al. (2018). MiR-26a inhibits thyroid cancer cell proliferation by targeting ARPP19. American Journal of Cancer Research, 8, 1030–1039. 380. Lv, P., et al. (2019). Long non-coding RNA SNHG6 enhances cell proliferation, migration and invasion by regulating miR-26a-5p/MAPK6 in breast cancer. Biomedicine & Pharmacotherapy, 110, 294–301. https://doi.org/10.1016/j.biopha.2018.11.016. 381. Wang, J., & Sun, G. (2017). FOXO1-MALAT1-miR-26a-5p feedback loop mediates proliferation and migration in osteosarcoma cells. Oncology Research, 25, 1517–1527. https://doi. org/10.3727/096504017X14859934460780. 382. Zhang, N. S., Dai, G. L., & Liu, S. J. (2017). MicroRNA-29 family functions as a tumor suppressor by targeting RPS15A and regulating cell cycle in hepatocellular carcinoma. International Journal of Clinical and Experimental Pathology, 10, 8031–8042. 383. Chang, Q. Q., Chen, C. Y., Chen, Z., & Chang, S. (2019). LncRNA PVT1 promotes proliferation and invasion through enhancing Smad3 expression by sponging miR-140-5p in cervical cancer. Radiology and Oncology, 53, 443–452. https://doi.org/10.2478/raon-2019-0048. 384. Tian, Z., et al. (2019). LncRNA PVT1 regulates growth, migration, and invasion of bladder cancer by miR-31/ CDK1. Journal of Cellular Physiology, 234, 4799–4811. https://doi.org/ 10.1002/jcp.27279. 385. Li, H., et al. (2018). Long non-coding RNA PVT1-5 promotes cell proliferation by regulating miR-126/SLC7A5 axis in lung cancer. Biochemical and Biophysical Research Communications, 495, 2350–2355. https://doi.org/10.1016/j.bbrc.2017.12.114. 386. Feng, W., et al. (2018). The dysregulated expression of KCNQ1OT1 and its interaction with downstream factors miR-145/CCNE2 in breast cancer cells. Cellular Physiology and Biochemistry, 49, 432–446. https://doi.org/10.1159/000492978. 387. Hu, H. B., Chen, Q., & Ding, S. Q. (2018). LncRNA LINC01116 competes with miR-145 for the regulation of ESR1 expression in breast cancer. European Review for Medical and Pharmacologic, 22, 1987–1993. https://doi.org/10.26355/eurrev_201804_14726. 388. Wu, F., et al. (2019). The lncRNA ZEB2-AS1 is upregulated in gastric cancer and affects cell proliferation and invasion via miR-143-5p/HIF-1alpha axis. OncoTargets and Therapy, 12, 657–667. https://doi.org/10.2147/OTT.S175521. 389. Long, J. P., Dong, L. F., Chen, F. F., & Fan, Y. F. (2019). miR-146a-5p targets interleukin-1 receptor-associated kinase 1 to inhibit the growth, migration, and invasion of breast cancer cells. Oncology Letters, 17, 1573–1580. https://doi.org/10.3892/ol.2018.9769.

References

209

390. Khawaled, S., et al. (2019). WWOX inhibits metastasis of triple-negative breast cancer cells via modulation of miRNAs. Cancer Research, 79, 1784–1798. https://doi.org/10.1158/00085472.CAN-18-0614. 391. Chen, S., et al. (2019). Widespread and functional RNA circularization in localized prostate cancer. Cell, 176, 831–843 e822. https://doi.org/10.1016/j.cell.2019.01.025. 392. Chen, H., et al. (2018). Circ-ANAPC7 is upregulated in acute myeloid leukemia and appears to target the MiR-181 family. Cellular Physiology and Biochemistry, 47, 1998–2007. https:// doi.org/10.1159/000491468. 393. Zhou, J., et al. (2018). Metformin induces miR-378 to downregulate the CDK1, leading to suppression of cell proliferation in hepatocellular carcinoma. OncoTargets and Therapy, 11, 4451–4459. https://doi.org/10.2147/OTT.S167614. 394. Asati, V., Mahapatra, D. K., & Bharti, S. K. (2016). PI3K/Akt/mTOR and Ras/Raf/MEK/ERK signaling pathways inhibitors as anticancer agents: Structural and pharmacological perspectives. European Journal of Medicinal Chemistry, 109, 314–341. https://doi.org/10.1016/j.ejm ech.2016.01.012. 395. Cheng, C. C., et al. (2018). Stat3/Oct-4/c-Myc signal circuit for regulating stemness-mediated doxorubicin resistance of triple-negative breast cancer cells and inhibitory effects of WP1066. International Journal of Oncology, 53, 339–348. https://doi.org/10.3892/ijo.2018.4399. 396. Muhammad, N., Bhattacharya, S., Steele, R., Phillips, N., & Ray, R. B. (2017). Involvement of c-Fos in the promotion of cancer stem-like cell properties in head and neck squamous cell carcinoma. Clinical Cancer Research, 23, 3120–3128. https://doi.org/10.1158/1078-0432. CCR-16-2811. 397. Tam, S. Y., Wu, V. W. C., & Law, H. K. W. (2020). JNK pathway mediates low oxygen level induced epithelial-mesenchymal transition and stemness maintenance in colorectal cancer cells. Cancers (Basel), 12. https://doi.org/10.3390/cancers12010224. 398. Unal, E. B., Uhlitz, F., & Bluthgen, N. (2017). A compendium of ERK targets. FEBS Letters, 591, 2607–2615. https://doi.org/10.1002/1873-3468.12740. 399. Sun, Q., Liang, Y., Zhang, T., Wang, K., & Yang, X. (2017). ER-alpha36 mediates estrogenstimulated MAPK/ERK activation and regulates migration, invasion, proliferation in cervical cancer cells. Biochemical and Biophysical Research Communications, 487, 625–632. https:// doi.org/10.1016/j.bbrc.2017.04.105. 400. Tian, W., et al. (2019). Estrogen and insulin synergistically promote endometrial cancer progression via crosstalk between their receptor signaling pathways. Cancer Biology & Medicine, 16, 55–70. https://doi.org/10.20892/j.issn.2095-3941.2018.0157. 401. Li, Q., Wu, X., Guo, L., Shi, J., & Li, J. (2019). MicroRNA-7-5p induces cell growth inhibition, cell cycle arrest and apoptosis by targeting PAK2 in non-small cell lung cancer. FEBS Open Bio, 9, 1983–1993. https://doi.org/10.1002/2211-5463.12738. 402. Huang, Q., Wu, Y. Y., Xing, S. J., & Yu, Z. W. (2019). Effect of miR-7 on resistance of breast cancer cells to adriamycin via regulating EGFR/PI3K signaling pathway. European Review for Medical and Pharmacologic, 23, 5285–5292. https://doi.org/10.26355/eurrev_201906_ 18195. 403. Ling, Y., et al. (2019). TRIP6, as a target of miR-7, regulates the proliferation and metastasis of colorectal cancer cells. Biochemical and Biophysical Research Communications, 514, 231– 238. https://doi.org/10.1016/j.bbrc.2019.04.092. 404. Xia, J., et al. (2018). miR-7 suppresses tumor progression by directly targeting MAP3K9 in pancreatic cancer. Molecular Therapy - Nucleic Acids, 13, 121–132. https://doi.org/10.1016/ j.omtn.2018.08.012. 405. Ye, T., et al. (2019). MicroRNA-7 as a potential therapeutic target for aberrant NF-kappaBdriven distant metastasis of gastric cancer. Journal of Experimental & Clinical Cancer Researc, 38, 55. https://doi.org/10.1186/s13046-019-1074-6. 406. Yang, Z., et al. (2018). Long non-coding RNA UCA1 upregulation promotes the migration of hypoxia-resistant gastric cancer cells through the miR-7-5p/EGFR axis. Experimental Cell Research, 368, 194–201. https://doi.org/10.1016/j.yexcr.2018.04.030.

210

7 Non-coding RNAs Related to Cardiometabolic Diseases …

407. Li, C., et al. (2017). Dysregulated lncRNA-UCA1 contributes to the progression of gastric cancer through regulation of the PI3K-Akt-mTOR signaling pathway. Oncotarget, 8, 93476– 93491. https://doi.org/10.18632/oncotarget.19281. 408. Mo, D., Liu, W., Li, Y., & Cui, W. (2019). Long non-coding RNA Zinc finger antisense 1 (ZFAS1) regulates proliferation, migration, invasion, and apoptosis by targeting MiR-7-5p in colorectal cancer. Medical Science Monitor, 25, 5150–5158. https://doi.org/10.12659/MSM. 916619. 409. Li, R. C., et al. (2018). CiRS-7 promotes growth and metastasis of esophageal squamous cell carcinoma via regulation of miR-7/HOXB13. Cell Death and Disease, 9, 838. https://doi.org/ 10.1038/s41419-018-0852-y. 410. Zhang, X., Yang, D., & Wei, Y. (2018). Overexpressed CDR1as functions as an oncogene to promote the tumor progression via miR-7 in non-small-cell lung cancer. OncoTargets and Therapy, 11, 3979–3987. https://doi.org/10.2147/OTT.S158316. 411. Pan, H., et al. (2018). Overexpression of circular RNA ciRS-7 abrogates the tumor suppressive effect of miR-7 on gastric cancer via PTEN/PI3K/AKT signaling pathway. Journal of Cellular Biochemistry, 119, 440–446. https://doi.org/10.1002/jcb.26201. 412. Tao, J., et al. (2012). microRNA-133 inhibits cell proliferation, migration and invasion in prostate cancer cells by targeting the epidermal growth factor receptor. Oncology Reports, 27, 1967–1975. https://doi.org/10.3892/or.2012.1711. 413. Xu, F., Li, F., Zhang, W., & Jia, P. (2015). Growth of glioblastoma is inhibited by miR-133mediated EGFR suppression. Tumour Biology, 36, 9553–9558. https://doi.org/10.1007/s13 277-015-3724-4. 414. Ning, T., et al. (2017). miR-455 inhibits cell proliferation and migration via negative regulation of EGFR in human gastric cancer. Oncology Reports, 38, 175–182. https://doi.org/10.3892/ or.2017.5657. 415. Chai, J., et al. (2018). A feedback loop consisting of RUNX2/LncRNA-PVT1/miR-455 is involved in the progression of colorectal cancer. American Journal of Cancer Research, 8, 538–550. 416. Kia, V., Paryan, M., Mortazavi, Y., Biglari, A., & Mohammadi-Yeganeh, S. (2019). Evaluation of exosomal miR-9 and miR-155 targeting PTEN and DUSP14 in highly metastatic breast cancer and their effect on low metastatic cells. Journal of Cellular Biochemistry, 120, 5666– 5676. https://doi.org/10.1002/jcb.27850. 417. Peng, W. X., Huang, J. G., Yang, L., Gong, A. H., & Mo, Y. Y. (2017). Linc-RoR promotes MAPK/ERK signaling and confers estrogen-independent growth of breast cancer. Molecular Cancer, 16, 161. https://doi.org/10.1186/s12943-017-0727-3. 418. Ma, J., et al. (2018). MicroRNA-29a inhibits proliferation and motility of schwannoma cells by targeting CDK6. Journal of Cellular Biochemistry, 119, 2617–2626. https://doi.org/10. 1002/jcb.26426. 419. Zhou, K., Luo, X., Wang, Y., Cao, D., & Sun, G. (2017). MicroRNA-30a suppresses tumor progression by blocking Ras/Raf/MEK/ERK signaling pathway in hepatocellular carcinoma. Biomedicine & Pharmacotherapy, 93, 1025–1032. https://doi.org/10.1016/j.biopha. 2017.07.029. 420. Zhang, W., et al. (2019). Increased HMGB1 expression correlates with higher expression of c-IAP2 and pERK in colorectal cancer. Medicine (Baltimore), 98, e14069. https://doi.org/10. 1097/MD.0000000000014069. 421. Xia, B., et al. (2017). Long non-coding RNA ZFAS1 interacts with miR-150-5p to regulate Sp1 expression and ovarian cancer cell malignancy. Oncotarget, 8, 19534–19546. https://doi. org/10.18632/oncotarget.14663. 422. Li, X., et al. (2019). Knockdown of SP1/Syncytin1 axis inhibits the proliferation and metastasis through the AKT and ERK1/2 signaling pathways in non-small cell lung cancer. Cancer Medicine. https://doi.org/10.1002/cam4.2448. 423. Xie, Y., et al. (2016). ADAMTS6 suppresses tumor progression via the ERK signaling pathway and serves as a prognostic marker in human breast cancer. Oncotarget, 7, 61273–61283. https:// doi.org/10.18632/oncotarget.11341.

References

211

424. Li, L., et al. (2019). A TGF-beta-MTA1-SOX4-EZH2 signaling axis drives epithelialmesenchymal transition in tumor metastasis. Oncogene. https://doi.org/10.1038/s41388-0191132-8. 425. Song, L. B., et al. (2009). The polycomb group protein Bmi-1 represses the tumor suppressor PTEN and induces epithelial-mesenchymal transition in human nasopharyngeal epithelial cells. Journal of Clinical Investigation, 119, 3626–3636. https://doi.org/10.1172/JCI39374. 426. Fan, C., et al. (2009). PTEN inhibits BMI1 function independently of its phosphatase activity. Molecular Cancer, 8, 98. https://doi.org/10.1186/1476-4598-8-98. 427. van Vlerken, L. E., et al. (2013). EZH2 is required for breast and pancreatic cancer stem cell maintenance and can be used as a functional cancer stem cell reporter. STEM CELLS Translational Medicine, 2, 43–52. https://doi.org/10.5966/sctm.2012-0036. 428. Crea, F., et al. (2012). EZH2 inhibition: Targeting the crossroad of tumor invasion and angiogenesis. Cancer and Metastasis Reviews, 31, 753–761. https://doi.org/10.1007/s10555-0129387-3. 429. Song, M. S., Salmena, L., & Pandolfi, P. P. (2012). The functions and regulation of the PTEN tumour suppressor. Nature Reviews Molecular Cell Biology, 13, 283–296. https://doi.org/10. 1038/nrm3330. 430. Zhao, X., & Tian, X. (2019). Knockdown of long noncoding RNA HOTAIR inhibits cell growth of human lymphoma cells by upregulation of miR-148b. Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb.28500. 431. Kim, M., et al. (2018). Silencing Bmi1 expression suppresses cancer stemness and enhances chemosensitivity in endometrial cancer cells. Biomedicine & Pharmacotherapy, 108, 584– 589. https://doi.org/10.1016/j.biopha.2018.09.041. 432. Bhan, A., & Mandal, S. S. (1856). LncRNA HOTAIR: A master regulator of chromatin dynamics and cancer. Biochimica et Biophysica Acta, 151–164, 2015. https://doi.org/10.1016/ j.bbcan.2015.07.001. 433. Xie, J. J., Li, W. H., Li, X., Ye, W., & Shao, C. F. (2019). LncRNA MALAT1 promotes colorectal cancer development by sponging miR-363-3p to regulate EZH2 expression. Journal of Biological Regulators and Homeostatic Agents, 33, 331–343. 434. Huo, Y., et al. (2017). MALAT1 predicts poor survival in osteosarcoma patients and promotes cell metastasis through associating with EZH2. Oncotarget, 8, 46993–47006. https://doi.org/ 10.18632/oncotarget.16551. 435. Lu, L., et al. (2015). Posttranscriptional silencing of the lncRNA MALAT1 by miR-217 inhibits the epithelial-mesenchymal transition via enhancer of zeste homolog 2 in the malignant transformation of HBE cells induced by cigarette smoke extract. Toxicology and Applied Pharmacology, 289, 276–285. https://doi.org/10.1016/j.taap.2015.09.016. 436. Zhao, L., et al. (2017). The Lncrna-TUG1/EZH2 axis promotes pancreatic cancer cell proliferation, migration and EMT phenotype formation through sponging Mir-382. Cellular Physiology and Biochemistry, 42, 2145–2158. https://doi.org/10.1159/000479990. 437. Li, Q., Song, W., & Wang, J. (2019). TUG1 confers Adriamycin resistance in acute myeloid leukemia by epigenetically suppressing miR-34a expression via EZH2. Biomedicine & Pharmacotherapy, 109, 1793–1801. https://doi.org/10.1016/j.biopha.2018.11.003. 438. Xu, C., et al. (2018). TUG1 confers cisplatin resistance in esophageal squamous cell carcinoma by epigenetically suppressing PDCD4 expression via EZH2. Cell and Bioscience, 8, 61. https://doi.org/10.1186/s13578-018-0260-0. 439. Ma, J., et al. (2018). MiR-124 induces autophagy-related cell death in cholangiocarcinoma cells through direct targeting of the EZH2-STAT3 signaling axis. Experimental Cell Research, 366, 103–113. https://doi.org/10.1016/j.yexcr.2018.02.037.

Chapter 8

Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

Abstract MiR-1, miR-26a, miR-133, miR-378, and miR-455 tend to be downregulated, while miR-155, HOTAIR, LINC-ROR, TUG1, and XIST tend to be up-regulated in cardiometabolic tissues and tumors. Compared to cardiometabolic tissues, miR-7, miR-17, miR-29a, miR-30a, miR-34a, miR-124, miR-143–145, miR150, lincRNA-p21, and MEG3 tend to be down-regulated in tumors. In contrast, miR-9, miR-21, miR-130, miR-221, H19, MALAT1, MIAT, NEAT1, UCA1, ZFAS1, ANRIL, ciRs-7, and PVT1 tend to be up-regulated. The interaction between hypoxia, glucose, oxidative stress, inflammation, TGF-β, and MYC largely determine their expression profiles. Additional decrease of miRs in tumors may be due to silencing by specific lncRNA and circ-RNAs. BLACAT1 silences miR-17 and miR-150; CASC11 silences miR-150 and up-regulates TGF-β; FEZ1-AS1silences miR-30a, upregulating stemness genes; HNF1A-AS1 silences miR-34a, but up-regulating miR124; MACC1-AS1 silences miR-34a and miR-145; NIFK-AS1 silences miR-146a; NORAD silences miR-30a and up-regulates TGF-β; lncRNA-SNHG6 silences let7c, and miR-26a, and up-regulates MYC; SOX21-AS1 silences miR-7 and miR-145; ZEB1-AS1 silences miR-133, miR-181, and miR-455; circ-ANAPC7 silences miR181; circ-HIPK3 silences miR-7; circ-ITCH up-regulates and circ-MTO1 silences miR-17; circ-ZNF609 silences miR-145. Non-coding RNAs operate in complex networks. Significantly, hypoxia induces NORAD that induces TGF-β. The latter silences miR-181, resulting in increased ZEB-AS1 and ZEB1. TGF-β also induces MACC1-AS1 that induces MYC. MYC directly sponges miR-34a and silences miR34a indirectly by inducing lncRNA-SNHG7. Differences in gene expression may also be due to tumor-specific piRs.

8.1 Regulation of miRs Table 8.1 shows the regulation of miRs by hypoxia, glucose, oxidative stress, inflammation, TGF-β, and MYC.

Illustrations by Pieterjan Ginckels, Faculty of Architecture, KU Leuven, Ghent, Belgium. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 P. Holvoet, Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer, https://doi.org/10.1007/978-3-030-68844-8_8

213

214

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

Table 8.1 Regulation of non-coding RNAs Hypoxia

Glucose

Let-7 miR-1

X

miR-7

X

miR-9

X

X

miR-17

X

X

miR-21

X

miR-26a

X

miR-29a

Oxidative stress

Inflammation

X

X

X

X

X

X

X

X

X

X

X

miR-34a

X

X

miR-124

X

X

miR-130

X

X

X

X

X X X

X

X

X

X

X

X

X

X

X

X

X

miR-133

X

miR-143–145

X

X

X

miR-146a/b

X

X

X

miR-150

X

miR-155

X

miR-181

X

miR-221–222

X

X

X X

X

X

X

X

X

X

miR-223

X X

X

X X

X

miR-455

X X

X

HOTAIR

X

X

X

X

H19

X

LincRNA-p21

X

LINC-ROR

X

MALAT1

X

X

MEG3

X

X

MIAT NEAT1

X

X X

X

GAS5

MYC

X X

miR-30a

miR-378

TGF-β

X

X X X

X

X

X X

X

X

TUG1

X

X X

X

X

X

UCA1

X

XIST

X

ANRIL

X

X

X X (continued)

8.1 Regulation of miRs

215

Table 8.1 (continued) Hypoxia PVT1

X

Glucose

Oxidative stress

Inflammation

TGF-β

MYC X

Bold crosses indicate up-regulated non-coding RNAs; italic crosses indicate down-regulated noncoding RNAs. There is no robust data yet about the regulation of ZFAS1 and ciRs-7

8.1.1 Hypoxia Cardiometabolic tissues Hypoxia induces miR-9 in VSMCs, thereby causing a phenotypic switch from contractile to proliferative cells [1]. Hypoxia induces miR-17, and hypoxia-inducible factor 1 (HIF-1α) and VEGF regulate each other through miR-17 [2, 3]. Hypoxia and transforming growth factor, beta (TGF-β) induce miR-21, preventing ischemia reperfusion-induced apoptosis, down-regulating PTEN, and increasing AKT phosphorylation. However, PPAR-γ ligands mediate proliferative response to hypoxia by increasing miR-21 [4–9]. Hypoxia induces a protective response to mitochondria via HIF-1α-mediated up-regulation of miR-26a [10]. Hypoxia-induced miR-130 silences DEAD-box helicase 6. This RNA helicase is found in P-bodies and stress granules, inhibiting translation, and degrading mRNA. The silencing of the DEAD-box helicase 6 by the miR-130 family enhanced the translation of HIF-1α [11]. Hypoxia increases miR-143 and miR-145, but this may be alleviated by hypoxia-induced LINC-ROR [12–15]. Hypoxia, very small-sized particles (PM2.5 ), high glucose, IL-1β and TNF-α, and apolipoprotein E induce miR-146a [16–24]. Hypoxia also increases miR-150 [25]. Hypoxia-induced miR-378 promotes mesenchymal stem cell survival [26]. Hypoxia-induced H19 antagonizes Y-box-binding protein (YB)-1, thereby derepressing collagen 1A1 expression and inducing cardiac fibrosis [27]. Hypoxiainduces NEAT1 and, together with ox-LDL, increases MALAT1 [28–33]. LINCROR silences miR-145 and induces HIF-1α signaling [15]. Hypoxia-induced XIST promotes angiogenesis via miR-485-3p/SOX7 axis [34]. Hypoxia-induced ANRIL protects endothelial cells by modulating the miR-7-5p/SIRT1 axis [35]. Hypoxia down-regulates miR-1 and miR-7, thereby losing the miR-7-mediated inhibition of ischemia–reperfusion-induced apoptosis by targeting the HIF-1α/p-p38 pathway [36–38]. Tumors Hypoxia-induced miR-130 silences tumor suppressor p21 (CDKN1A) [11, 39]. Hypoxia induces miR-146a by stimulating its promoter, thereby sponging CADM2 and inducing proliferation, migration, and invasion of cancer cells [19]. Hypoxia-induced miR-155-5p forms a double-negative regulatory loop with ETS transcription factor ELK3 (ELK3); ELK3 depletion induces miR-155-5p that silences ELK3 whereby miR-155 is further enhanced [40]. Snail family transcriptional

216

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

repressor 2 (SNAI2 or SLUG) / β-catenin induced by hypoxia enhances miR-221 expression [41]. Hypoxia promotes EMT by downregulating miR-34a [42] and mesenchymal transition of glioma cells by down-regulating miR-124-3p [43, 44]. Hypoxia-induces GAS5 that silences miR-221–222 related to apoptosis [45]. H19 sequesters let-7, thereby releasing HIF-1α, leading to an increased expression of pyruvate dehydrogenase kinase 1 (PDK1), glycolysis, and stemness [46]. Hypoxia induces H19 that sponges miR-181d, relieving inhibition of β-catenin expression in glioblastoma cells [47]. Hypoxia-sensitive long intergenic non-protein coding RNA 1436 (LINC01436) sponges miR-30a-3p, promoting lung cancer cell growth, migration, and invasion [48]. Chromatin-chromatin interactions are formed at the MALAT1 locus under hypoxia, resulting in the up-regulation of MALAT1 [49]. Hypoxiainduced MEG3 regulates p53 pathway members such as HIF-1α [50]. NEAT1 is a direct transcriptional target of HIF-2, and the hypoxic induction of NEAT1 induces paraspeckle formation [51]. Hypoxia induces ANRIL, thereby suppressing hypoxia-induced apoptosis [52, 53], and lincRNA-p21, increasing glycolysis [54]. Hypoxia-induced PVT1 silences miR-150 [55] (Table 8.2).

8.1.2 Glucose Cardiometabolic tissues High glucose up-regulates miR-17 that decreases VEGFA and angiogenesis [56]. Hyperglycemia increases NFκB, p38 mitogen-activated protein kinase (MAPK) activation, the release of inflammatory IL-1β, TNF-α, and C–C motif chemokine ligand 2 (CCL2 or MCP1), and miR-21. High glucose up-regulates miR-34a and downregulates miR-126, elevating superoxide dismutase 2 [57]. High glucose-induced miR-155 induces cardiac fibrosis via the TGF-β signaling pathway [58]. Glucose up-regulates miR-221–222, which silences IGF1 [59, 60]. High glucose-induced miR-455-5p represses the secretion of inflammatory cytokines IL-1β and TNF-α [61]. High glucose and inflammatory cytokines induce HOTAIR in a p65-dependent manner, and MALAT1, protecting ECs against ox-LDL-induced cytokine release [62–68]. Glucose-induced TUG1 protects the pancreas against apoptosis [69]. High glucose lowers miR-1 [70], while insulin ameliorates miR-1 expression in cells under oxidative stress [71]. High glucose promotes oxidative stress and apoptosis by downregulating miR-26a [72]. High glucose decreases miR-29a/b and increases α-smooth muscle actin and fibronectin [73]. Glucose-induced circular RNA derived from WD repeat domain 77 (circ-WDR77) sponges miR-124 that targets FGF-2 to regulate VSMC proliferation and migration [74]. Glucose silences miR145, thereby activating the PI3K/AKT/mTOR pathway [75, 76]. High glucose and LPS down-regulate GAS5 and MEG3 [77–81] while increasing MALAT1 [82–84]. High glucose promotes the binding of NFκB to MIAT [85–87].

X

X

X

X

X

X

miR-181

X

miR-155

X

miR-150

miR-146a

X

X

X

X

X

X

miR-143–145

X

miR-130

X

miR-133

X

miR-124

X

X

X

miR-34a

X

X

X

X

X

X

X

X

miR-30a

X

X

miR-29a

X

miR-26a/b

miR-21

X

X

miR-9

miR-17

X

X

miR-7

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X X

(continued)

X

X

X

X

X

LincRNA-p21 MEG3 H19 HOTAIR LINC-ROR MALAT1 MIAT NEAT1 TUG1 UCA1 ZFAS1 XIST ANRIL CiRs-7 PVT1

miR-1

Let-7

Table 8.2 Expected changes of miR expression profiles due to changed expression of lncRNAs and circ-RNAs

8.1 Regulation of miRs 217

X X

Bold crosses indicate up-regulated non-coding RNAs; italic crosses indicate down-regulated non-coding RNAs

miR-455

miR-378

X X

miR-223

X

miR-221–222 X

X

LincRNA-p21 MEG3 H19 HOTAIR LINC-ROR MALAT1 MIAT NEAT1 TUG1 UCA1 ZFAS1 XIST ANRIL CiRs-7 PVT1

Table 8.2 (continued)

218 8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

8.1 Regulation of miRs

219

Tumors High glucose downregulates miR-9 in colorectal cancer cells, thereby increasing IGF1R signaling [88]. Insulin increases pyruvate kinase M2 and glycolysis in hepatocellular carcinoma cells by suppressing miR-145 [89] (Table 8.2).

8.1.3 Oxidative Stress Cardiometabolic tissues Oxidative stress induces miR-9 through NFkB [90]. Ox-LDL increases miR-21 and PI3K/ AKT/MAPK signaling [91] and increases miR-29a, thereby inducing STAT1/ Janus kinase (JAK) signaling [92]. Oxidative stress increases miR-34a, associated with premature aging [93–95]. Ox-LDL increases miR-155 in DCs and ECs [96, 97]. Ox-LDL-induced MALAT1 promotes autophagy in human ECs by silencing miR216a-5p and induces EMT through the Wnt/β-catenin pathway [28, 98]. Ox-LDL induces MIAT that silences miR-181b [99] and increases TUG1 [100]. Tumors Oxidative stress increases peroxidase peroxiredoxin 1, which binds to forkhead box O3 (FOXO3), decreasing pro-apoptotic let-7b [101] (Table 8.2).

8.1.4 Inflammation Cardiometabolic tissues Activation of toll-like receptor (TLR)-2 and release of pro-inflammatory cytokines TNF-α and IL-1β, but not IFN-γ induce miR-9 in inflammatory cells [102]. IL-1β, palmitate, and stearic acid up-regulate miR-34a [103–105]. TNF-α induces miR-130, miR-145, miR-150, and miR-155 [106–112]. IL-12, IL-18, and CD16 also increase miR-155 [113, 114]. TNF-α, IL-6, and leptin increase miR-378 in adipocytes, thereby silencing IL4R/PI3K/AKT and limiting macrophage proliferation [115, 116]. ANG II up-regulates miR-21 by targeting the SMAD family member 7 (SMAD7) and sprouty RTK signaling antagonist 1 (SPROUTY1 or SPRY1) in primary hepatic stellate cells, associated with NLRP3 inflammasome activation [117, 118]. ANG II also up-regulates MIAT, up-regulating TGF-β [119]. Leukotriene B4, an inflammation mediator, derived from arachidonic acid by 5-lipoxygenase and 5-lipoxygenase–activating protein, activates macrophages by inducing miR-155, miR-146b, and miR-125b [120, 121]. MiR-26a and miR-30a levels inversely correlate to IL1-β [122]. Further, IL22 inhibits miR-26a in T cells [123]. IFN-γ suppresses miR-181 in activated human

220

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

CD4 lymphocytes [124] and miR-221 in DCs [125]. IFN-α also decreases miR378 and miR-30e, suppressors of human NK cell cytotoxicity [126]. IL10 decreases the expression of miR-223, together with miR-19a, miR-21, miR-31, miR-101, and miR-155 [127–129]. Tumors IL6 increases miR-17, but IFN-γ suppresses miR-17, thereby reverting antiinflammatory and anti-oxidative action in breast tumors [130–132]. Inflammation and prostaglandin E2 inhibits programmed cell death 4 (PDCD4) in prostate cancer cells through up-regulating miR-21 [133, 134]. Inflammatory C-X-C motif chemokine ligand 12 (CXCL12) / C-X-C motif chemokine receptor 4 (CXCR4) up-regulate XIST that silences miR-133a-3p, thereby de-repressing RhoA in colorectal cancer cells [135]. Mitochondrially encoded cytochrome c oxidase II (COX2) induces methylation of the promoter of let-7, down-regulating let-7 and up-regulating SOX2 [136]. MiR-7 in human gastric cancer is inversely related to IL-1β and TNF-α [137]. TNF-α also silences miR-1-3p, miR-26a, miR-133a-3p, and miR-133b [138–140]. Activation of NFκB down-regulates miR-124 in non-small-cell lung cancer cells [141] (Table 8.2).

8.1.5 TGF-β Cardiometabolic tissues TGF-β-induced lincRNA-p21 promotes liver inflammation and fibrosis by inhibiting miR-30a [142]. TGF-β suppresses miR-223 by up-regulating circular RNA derived from PWWP domain containing 2A, promoting hepatic fibrosis [143]. TGF-β also induces EGF, suppressing miR-124 through the transcription factor ETS proto-oncogene 2 to maintain proper β cell function and insulin secretion through PI3K cascades [144]. Tumors TGF-β1 up-regulates miR-9 and down-regulates E-cadherin, thereby inducing EMT, but IL10 represses this action by down-regulating miR-9 [145, 146]. TGF- β reduces miR-29a, but miR-29 blocks TGF-β function [147]. TGF-β elevates the MIR155 host gene (MIR155HG) lncRNA and miR-155, attenuating miR-143. TGF-β induces miR221 and miR-455-5p, inhibiting RUNX2 [8, 148]. TGF-β-induced EMT is associated with increased expression of MEG3 [149]. TGF-β up-regulates TUG1, which may act as a miRNA “sponge” to protect the HIF-1α mRNA 3 UTR from miR-143-5p [150]. TGF-β secreted by tumor-associated macrophages promotes proliferation and invasion of colorectal cancer by silencing miR-34a, thereby up-regulating VEGF [151]. However, the up-regulation of miR-34a reverses TGF-β-induced EMT through suppression of SMAD4 [152]. TGF-β enhances DNA methyltransferase

8.1 Regulation of miRs

221

3 alpha, repressing miR-124 promoter by hypermethylation. This loss of miR-124 enhances SMAD4, inducing SNAIL, SLUG, and ZEB2 [153]. TGF-β1 secreted by mesenchymal cells shifts macrophages to the M2 phenotype [154, 155] by downregulating miR-34a [156] or miR-124 [157]. TGF-β1 decreases miR-133a/b, while miR-133 mimics attenuate the action of TGF-β and down-regulates p-SMAD3 [158] (Table 8.2).

8.1.6 MYC MYC and POU class 5 homeobox 1 (OCT4) bind to the promoter region of miR-9 to trigger its transcription, associated with tumor metastasis [159, 160]. MYC induces miR-17-19b [161, 162], and miR-150, inducing autophagy in cancer cells [163]. MXI1, an MYC antagonist, inhibits miR-155 [164]. MYC promotes non-small-cell lung cancer by up-regulating ANRIL [165]. MYC induces H19, [166–168], and PVT1, enhancing cancer cells’ proliferation. However, PVT1 may induce or inhibit the expression of MYC [169–172]. MYC down-regulates let-7a, let-7d, and let-7 g by binding to their promoters [173]. MYC represses miR-29 through a co-repressor complex with EZH2 stimulated by repressing miR-26a by MYC [174–178]. Overexpression of miR-26a suppresses hepatocellular cancer metastasis by downregulating MYC [179]. MYC sponges miR-34a and silences miR-34a indirectly by the small nucleolar RNA host gene 7 lncRNA (lncRNA-SNHG7) [180, 181]. Besides, MYC silences miR-124, causing a shift towards the M2 macrophage phenotype [157, 182–186]. Further, the decrease of miR-124 improves insulin signaling by de-repressing AKT [187–189]. MYC up-regulates ANRIL, GAS5, MEG3, HOTAIR, H19, PVT1, and down-regulates MALAT1, NEAT1, and UCA1 [190].

8.1.7 Overview Low miR-1, miR-26a, miR-133, miR-378, and miR-455, and high miR-155, HOTAIR, LINC-ROR, TUG1, and XIST are typically related to the development of cardiometabolic diseases and cancer (Fig. 8.1). The interaction between hypoxia, glucose, oxidative stress, inflammation, TGFβ, and MYC explains the down-regulation of miR-1, miR-26a, and miR-133. They all are inversely associated with cardiometabolic diseases and cancer (Table 8.1). While inflammation down-regulates miR-378, hypoxia induces it. Glucose and TGF-β induce miR-455. Induction of miR-378 and miR-455 may protect against cardiometabolic diseases and cancer. The interaction between hypoxia, glucose, oxidative stress, inflammation, TGF-β, and MYC also explains the up-regulation of miR-155, HOTAIR, LINC-ROR, TUG1, and XIST. They all are positively related to cardiometabolic diseases and cancer. Table 8.2 shows that the increase in HOTAIR,

222

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

Fig. 8.1 Differences in the expression of non-coding RNAs with cardiometabolic diseases and cancer. Low miR-1, miR-26a, miR-133, miR-378, and miR-455, and high miR-155, HOTAIR, LINC-ROR, TUG1, and XIST are typically related to the development of cardiometabolic diseases and cancer. High miR-34a and lincRNA-p21 are mostly related to cardiometabolic diseases, while low levels are related to cancer. High and low let-7, miR-146a, miR-181, miR-223, and GAS5 are associated with cardiometabolic diseases and cancer. Both high and low miR-9, miR-21, miR130, miR-221–222, H19, MALAT1, MIAT, NEAT1, UCA1, ZFAS1, ANRIL, ciRs-7, and PVT1 are related to cardiometabolic diseases, while high levels are typically related to cancer. However, silencing of miR-9 is required to avoid cancer cell senescence. High and low miR-7, miR-17, miR-29a, miR-30a, miR-124, miR-143–145, miR-150, and MEG3 are related to cardiometabolic diseases, while low levels are typically related to cancer. However, in some tumors, high miR-17 may induce proliferation, the decrease of miR-26a and miR-29a inhibits PTEN, and the increase of miR-30a protects against immune response by expanding MDSCs. Overall, more non-coding RNAs are driven to either higher or lower levels in tumors than cardiometabolic tissues. Thus tumors are characterized by more extreme expressions of non-coding RNAs. Additional decrease of miRs in tumors may be due to silencing by specific lncRNA and circ-RNAs. BLACAT1 silences miR-17 and miR-150; CASC11 silences miR-150 and up-regulates TGF-β; FEZ1-AS1silences miR30a; HNF1A-AS1 silences miR-34a, but up-regulating miR-124; MACC1-AS1 silences miR-34a and miR-145; NIFK-AS1 silences miR-146a; NORAD silences miR-30a and up-regulates TGF-β; lncRNA-SNHG6 silences let-7c, and miR-26a, and up-regulates MYC; SOX21-AS1 silences miR-7 and miR-145; ZEB1-AS1 silences miR-133, miR-181, and miR-455; circ-ANAPC7 silences miR181; circ-HIPK3 silences miR-7; circ-ITCH up-regulates and circ-MTO1 silences miR-17; circZNF609 silences miR-145. Differences in expression of these non-coding RNAs underly differences in metabolic reprogramming of cells in cardiometabolic tissues and tumors in response to stress factors

LINC-ROR, TUG1, and XIST may further down-regulate miR-1 and miR-133. Also, they silence miR-7, miR-9, miR-17, miR-21, miR-30a, miR-34a, miR-124, miR143–145, miR-221, miR-223, and miR-455. Importantly, the decrease of miR-7, miR-17, miR-30a, miR-34a, miR-124, and miR-143–145 is more representative for expression profiles in tumors than in cardiometabolic tissues. Indeed, while high miR-34a is related to cardiometabolic diseases, low levels are related to cancer.

8.1 Regulation of miRs

223

While high and low miR-7, miR-17, miR-30a, miR-124, and miR143-145 are related to cardiometabolic diseases, low levels are typically related to cancer. Both high and low miR-9, miR-21, miR-130, miR-221–222, H19, MALAT1, MIAT, NEAT1, UCA1, ZFAS1, ANRIL, and PVT1 are related to cardiometabolic diseases, while high levels are typically related to cancer. However, silencing of miR-9 is required to avoid cancer cell senescence. In some tumors, high miR-17 may induce proliferation, the decrease of miR-26a and miR-29a inhibits PTEN, and the increase of miR-30a protects against immune response by expanding MDSCs. Table 1 shows the up-regulation of miR-9 (except for glucose), miR-21, miR-130, miR-221–222 (except for inflammation), H19, MALAT1, MIAT, ANRIL, and PVT1, mainly representative for tumors. The up-regulation of lncRNAs and circ-RNAs may explain the silencing of miR-1, miR-9, miR-17, miR-26a, miR-29a, miR-30a, miR34a, miR-124, miR-130, miR-133, miR-143–145, miR-146a, miR-150, miR-155, miR-181, and miR-455. Silencing of miR-9, miR-21, and miR-130 may protect against tumor growth. In contrast, silencing of miR-1, miR-17, miR-26a, miR-29a, miR-30a, miR-34a, miR-124, miR-133, miR-143–145, miR-150, miR-155, and miR455 may enhance tumor growth. High and low let-7, miR-146a, miR-181, miR-223, and GAS5 are related to cardiometabolic diseases and cancer. Table 1 supports a decrease of let-7, miR-181, and miR-223, and an increase of miR-146a. H19, MALAT1, and ANRIL silence let7. H19, MALAT1, and PVT1 silence miR-146a. H19 and MIAT silence miR-181. TUG1 silences miR-223. So far, we do not explain the decrease of lincRNA-p21 and MEG3, mainly in tumors. However, this decrease may explain the up-regulation of miR-9, miR-21, and miR-221–222 as in tumors. However, silencing these two lncRNAs would also increase miR-7, miR-26a, miR-29a, miR-34a, miR-143–145, miR-181, and miR223.

8.2 Differences in miR-Profiles in Cardiometabolic Tissues and Tumors May be Due to the Typical Action of lncRNAs and circ-RNAs in Tumors Differences may be due to the tumor-specific action of lnc-RNAs and circ-RNAs. In tumors, the bladder cancer-associated transcript 1 (BLACAT1) activates Wnt signaling and induces autophagy and chemoresistance by silencing miR-17 [191, 192]. BLACAT1 also silences miR-150, thereby inducing CCR2 [193]. Cancer susceptibility 11 lncRNA (CASC11) silences miR-150 in cancer cells, while miR150 overexpression does not significantly alter CASC11 expression [194]. CASC11, associated with HIF1α, up-regulates of TGF-β and induces stemness [195, 196]. The fasciculation and elongation protein zeta one lncRNA (FEZ1-AS1) increases stemness by silencing miR-30a, up-regulating Nanog homeobox (NANOG), OCT4, and SOX2 [197]. HNF1A antisense RNA 1 (HNF1A-AS1) silences miR-34a in tumors,

224

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

thereby up-regulating sirtuin (SIRT)-1 and down-regulating p53, leading to a higher Wnt signaling [95, 198–202]. HNF1A-AS1 binds to the promoter of miR-124 to promote its expression [203]. Overall, the HNF1 homeobox A (HNF1A) antisense RNA 1 (HNF1A-AS1) activates the Wnt/β-catenin signaling pathway activity by up-regulating the expression of β catenin, cyclinD1, and c-MYC [204]. TGF-β1 secreted by mesenchymal cells activates SMAD family member (SMAD)-2 and SMAD3 through TGF-β receptors and induces lncRNA MET transcriptional regulator MACC1 antisense (MACC1-AS1) that stabilizes the MET transcriptional regulator MACC1 and induces CDK6, thereby promoting cancer cell proliferation by sponging miR-34a. It also silences miR-145, thereby inducing c-MYC [205–208]. The nucleolar protein interacting with the FHA domain of MKI67 (NIFK) antisense RNA 1 (NIFK-AS1) inhibits M2 macrophage polarization by targeting miR-146a [209]. The non-coding RNA activated by DNA damage (NORAD) silences miR30a, inhibiting tumor cells’ apoptosis [210]. Hypoxia-activated NORAD induces cancer cell proliferation and migration by inducing TGF-β/RUNX2 signaling [211– 214]. The small nucleolar RNA host gene six lncRNA (SNHG6) up-regulates MYC by sponging let-7c [215] and promotes EMT through the miR-26a / EZH2 axis [216, 217]. SRY-box transcription factor (SOX)-21 antisense divergent transcript 1 (SOX21-AS1) inhibits the expression of miR-7 and miR-145 in tumors [218, 219]. Zinc finger E-box-binding homeobox two antisense RNA 1 (ZEB1-AS1) induces stemness and EMT and activates PI3K/AKT signaling by silencing miR-133 in tumors [220, 221]. ZEB1-AS1 also promotes colon adenocarcinoma malignant progression in tumors by silencing miR-455 [222]. TGF-β and ox-LDL decrease miR-181 in tumors, thereby inducing ZEB1-AS1 that silences miR-181, thereby inducing Wnt/ β-catenin signaling [223–225]. SNHG6 and ZEB1-AS1 mediate TGF-β/Smad signaling and induce EMT via regulating ZEB1 [224, 226, 227]. The anaphase-promoting complex subunit 7 circ-RNA (circ-ANAPC7) silences miR-181 in tumors [228]. High levels of the homeodomain interacting protein kinase three circ-RNA (circ-HIPK3) in tumors induce EMT [229]. Circ-HIPK3 sponges miR-7, thereby increasing the expression of miR-7 target EGFR [230]. The circRNA generated from itchy E3 ubiquitin-protein ligase (circ-ITCH) silences miR-17 [231]. The mitochondrial tRNA translation optimization one circ-RNA (circ-MTO1) may regulate cancer cell proliferation by silencing miR-17 [232]. Circ-ZNF609 sponges miR-145-5p, thereby elevating p70S6K1 [233]. Thus these additional lncRNAs and circ-RNAS may explain further decreases in let-7, miR-7, miR-17, miR-26a, miR-30a, miR-34a, miR-133, miR-145, miR-146a, miR-150, miR-181, and miR-455.

8.3 Action of piRs Particularly in Tumors Pi-sno75, derived from GAS5, potently up-regulates the transcription of tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL), a pro-apoptotic protein. The piR-sno75/ piwi like RNA-mediated gene silencing 1 (PIWIL1) or

8.3 Action of piRs Particularly in Tumors

225

piR/PIWIL4 complex interacted explicitly with the TRAIL promoter [234]. PiR651 inhibited proliferation, migration, invasion, induced apoptosis in cancer cells, and arrested cell cycle at the G(2)/M phase [235, 236]. PiR-598 also affected the expression of genes related to cell death and survival and cell-cycle progression [237]. PiR-823 increased the transcriptional activity of heat shock transcription factor 1 (HSF1) by binding to HSF1 and promoting its phosphorylation at Ser326, thereby promoting binding by heat shock protein 90 [238]. Transfection with piR-823 mimic or treatment with myeloma-derived-EVs enriched in piR823 promoted the proliferation, tube formation, and invasion of tumor endothelial cells by enhancing the expression of VEGF, IL-6, and intercellular adhesion molecule 1 (ICAM1) and attenuating apoptosis [239, 240]. PiR-004800, increased in multiple myeloma cells, protected against autophagic cell death. Its expression depends on the sphingosine-1-phosphate receptor 1 signaling pathway, which regulates the PI3K/Akt/mTOR pathway through control of piRNA-004800 expressions [241]. PiR-DQ722010 downregulation promoted activation of PI3K/AKT signaling pathway inducing prostate hyperplasia [242]. PiR-8041 reduced glioma cell line proliferation and induced apoptosis [243]. PiR-39980 repressed the ribonucleotide reductase regulatory subunit M2, promoting apoptosis and inhibiting fibrosarcoma cells’ proliferation [244]. Inhibition of piR-39980 induced senescence of neuroblastoma cells without affecting the classical apoptosis pathway by binding to Janus kinase 3 (JAK3) [245]. PiR-1245 is inversely related to tumor suppressor genes in colorectal cancer [246]. PiR-36,712 interacted with RNAs produced by selenoprotein W pseudogene 1 (SELENOW or SEPW1), and subsequently inhibited SEPW1 expression through competition of SEPW1 mRNA with SEPW1P RNA for miR-7 and miR-324. Higher SEPW1 due to down-regulation of piRNA-36,712 in breast cancer may suppress P53, inducing SLUG and decreasing P21 and E-cadherin levels, thus promoting cancer cell proliferation, invasion, and migration [247]. The heat shock protein DNAJA1 retains the stability of proteins in the S. mediterranea genome SMEDWI-1 and SMEDWI-2. Besides, DNAJA1 binds to PIWIL1, required for PIWIL1 stability in human gastric cancer cells [248]. The PIWIL1/piR-DQ593109 complex, increased in glioma endothelial cells, decreased the blood–brain barrier permeability. PIWIL1 and piR-DQ593109 form a piR-induced silencing complex, which degrades MEG3 that normally sponges miR-330-5p that silences RUNX3 [249]. PiR-54265 binds to PIWIL2, forming a PIWIL2/STAT3/phosphorylated SRC proto-oncogene, nonreceptor tyrosine kinase SRC complex. This complex activates STAT3 and promotes proliferation [250]. Higher piR-932 is associated with EMT of breast cancer cells. It may form an immune complex with piwi like RNA-mediated gene silencing 2 (PIWIL2) that suppresses glycogen synthase kinase 3 beta (GSK3β)–induced phosphorylation and ubiquitination of β-catenin, thereby stabilizing β-catenin and inducing the β-catenin/CCND1 pathway [251]. CCN1 induces miR-21 and miR-93, which bind Toll-Like Receptor 8 to trigger VEGF and Bcl-2 [252]. Besides, CCND1 induces the PIWI-interacting RNAs, piR-016658 piR-016975, related to stem cell expansion and increased the abundance of PIWIL2 in Erα- positive breast cancer cells [253]. PIWIL2 stabilizes histone deacetylase 3 and enhances the interaction

226

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

between histone deacetylase 3 and casein kinase 2, regulating cell cycle, apoptosis, and circadian rhythms [254]. The oncogene Opa interacting protein 5 (OIP5) antisense RNA 1 (OIP5-AS1) lncRNA promotes cancer cell proliferation by inducing CCAAT/enhancer-binding protein alpha (c/EBP-α), PI3K/AKT, and Wnt/β-catenin signaling through high mobility group AT-hook 2 (HMGA2) [255, 256]. PiR-30188 may guide PIWIL3 to OIP5-AS1, degrading it and reducing the sponging of miR367-3p that silences c/EBP-α, which otherwise would induce proliferation, migration, and invasion, and protect against apoptosis by inducing TRAF4. The inhibition of c/EBP-α leads to over-expression of PIWIL3, forming a positive feedback loop in the growth regulation of glioma cells [256].

References 1. Shan, F., Li, J., & Huang, Q. Y. (2014). HIF-1 alpha-induced up-regulation of miR-9 contributes to phenotypic modulation in pulmonary artery smooth muscle cells during hypoxia. Journal of Cellular Physiology, 229, 1511–1520. https://doi.org/10.1002/jcp.24593. 2. Li, J., et al. (2019). HIF1A and VEGF regulate each other by competing endogenous RNA mechanism and involve in the pathogenesis of peritoneal fibrosis. Pathology, Research and Practice, 215, 644–652. https://doi.org/10.1016/j.prp.2018.12.022. 3. Blissenbach, B., et al. (2018). Hypoxia-induced changes in plasma micro-RNAs correlate with pulmonary artery pressure at high altitude. American Journal of Physiology. Lung Cellular and Molecular Physiology, 314, L157–L164. https://doi.org/10.1152/ajplung.00146.2017. 4. Jia, Z., et al. (2017). Ischemic postconditioning protects against intestinal ischemia/reperfusion injury via the HIF-1alpha/miR-21 Axis. Scientific Reports, 7, 16190. https://doi.org/10.1038/s41598-017-16366-6. 5. Liu, L., et al. (2018). Activation of peroxisome proliferation-activated receptor-gamma inhibits transforming growth factor-beta1-induced airway smooth muscle cell proliferation by suppressing Smad-miR-21 signaling. Journal of Cellular Physiology, 234, 669–681. https:// doi.org/10.1002/jcp.26839. 6. Li, X., Li, C., Zhu, G., Yuan, W., & Xiao, Z. A. (2019). TGF-beta1 induces epithelialmesenchymal transition of chronic sinusitis with nasal polyps through MicroRNA-21. International Archives of Allergy and Immunology, 179, 304–319. https://doi.org/10.1159/000 497829. 7. Guo, X., et al. (2018). Immunosuppressive effects of hypoxia-induced glioma exosomes through myeloid-derived suppressor cells via the miR-10a/Rora and miR-21/Pten Pathways. Oncogene, 37, 4239–4259. https://doi.org/10.1038/s41388-018-0261-9. 8. Ong, J., et al. (2017). Identification of transforming growth factor-beta-regulated microRNAs and the microRNA-targetomes in primary lung fibroblasts. PLoS ONE, 12, e0183815. https:// doi.org/10.1371/journal.pone.0183815. 9. Green, D. E., Murphy, T. C., Kang, B. Y., Searles, C. D., & Hart, C. M. (2015). PPARgamma ligands attenuate hypoxia-induced proliferation in human pulmonary artery smooth muscle cells through modulation of MicroRNA-21. PLoS ONE, 10, e0133391. https://doi.org/10. 1371/journal.pone.0133391. 10. Ge, X., et al. (2018). Hypoxia-mediated mitochondria apoptosis inhibition induces temozolomide treatment resistance through miR-26a/Bad/Bax axis. Cell Death Disease, 9, 1128. https://doi.org/10.1038/s41419-018-1176-7. 11. Saito, K., Kondo, E., & Matsushita, M. (2011). MicroRNA 130 family regulates the hypoxia response signal through the P-body protein DDX6. Nucleic Acids Research, 39, 6086–6099. https://doi.org/10.1093/nar/gkr194.

References

227

12. Yue, Y., et al. (2018). miR-143 and miR-145 promote hypoxia-induced proliferation and migration of pulmonary arterial smooth muscle cells through regulating ABCA1 expression. Cardiovascular Pathology, 37, 15–25. https://doi.org/10.1016/j.carpath.2018.08.003. 13. Sun, N., et al. (2018). Inducible miR-145 expression by HIF-1a protects cardiomyocytes against apoptosis via regulating SGK1 in simulated myocardial infarction hypoxic microenvironment. Cardiology Journal, 25, 268–278. https://doi.org/10.5603/CJ.a2017.0105. 14. Ge, H., Liu, J., Liu, F., Sun, Y., & Yang, R. (2019). Long non-coding RNA ROR mitigates cobalt chloride-induced hypoxia injury through regulation of miR-145. Artificial Cells, Nanomedicine, and Biotechnology, 47, 2221–2229. https://doi.org/10.1080/21691401.2019. 1620759. 15. Takahashi, K., Yan, I. K., Haga, H., & Patel, T. (2014). Modulation of hypoxia-signaling pathways by extracellular linc-RoR. Journal of Cell Science, 127, 1585–1594. https://doi. org/10.1242/jcs.141069. 16. Liang, Y. C., et al. (2019). TNF-alpha-induced exosomal miR-146a mediates mesenchymal stem cell-dependent suppression of urethral stricture. Journal of Cellular Physiology, 234, 23243–23255. https://doi.org/10.1002/jcp.28891. 17. Lin, G., et al. (2019). miR-146a-5p mediates intermittent hypoxia-induced injury in H9c2 cells by targeting XIAP. Oxidative Medicine and Cellular Longevity, 2019, 6581217. https:// doi.org/10.1155/2019/6581217. 18. Zhong, Y. et al. (2019). PM2.5 Upregulates MicroRNA-146a-3p and Induces M1 Polarization in RAW264.7 Cells by Targeting Sirtuin1. International Journal of Medical Sciences, 16, 384–393. doi:https://doi.org/10.7150/ijms.30084. 19. Yang, L., Zhao, G., Wang, F., Li, C., & Wang, X. (2018). Hypoxia-regulated miR-146a targets cell adhesion molecule 2 to promote proliferation, migration, and invasion of clear cell renal cell carcinoma. Cellular Physiology and Biochemistry, 49, 920–931. https://doi.org/10.1159/ 000493224. 20. Lo, W. Y., Peng, C. T., & Wang, H. J. (2017). MicroRNA-146a-5p mediates high glucoseinduced endothelial inflammation via targeting interleukin-1 receptor-associated kinase 1 expression. Front Physiology, 8, 551. https://doi.org/10.3389/fphys.2017.00551. 21. Chen, S., Feng, B., Thomas, A. A., & Chakrabarti, S. (2017). miR-146a regulates glucose induced upregulation of inflammatory cytokines extracellular matrix proteins in the retina and kidney in diabetes. PLoS ONE, 12, e0173918. https://doi.org/10.1371/journal.pone.0173918. 22. Prattichizzo, F., et al. (2016). Anti-TNF-alpha treatment modulates SASP and SASP-related microRNAs in endothelial cells and in circulating angiogenic cells. Oncotarget, 7, 11945– 11958. https://doi.org/10.18632/oncotarget.7858. 23. Nahid, M. A., Satoh, M., & Chan, E. K. (2015). Interleukin 1beta-responsive MicroRNA-146a is critical for the cytokine-induced tolerance and cross-tolerance to toll-like receptor ligands. Journal of Innate Immunity, 7, 428–440. https://doi.org/10.1159/000371517. 24. Li, J., et al. (2012). miR-146a, an IL-1beta responsive miRNA, induces vascular endothelial growth factor and chondrocyte apoptosis by targeting Smad4. Arthritis Research and Therapy, 14, R75. https://doi.org/10.1186/ar3798. 25. Ikeda, K. T., et al. (2019). Hypoxia-induced pulmonary hypertension in different mouse strains: Relation to transcriptome. American Journal of Respiratory Cell and Molecular Biology, 60, 106–116. https://doi.org/10.1165/rcmb.2017-0435OC. 26. Xing, Y., et al. (2014). microRNA-378 promotes mesenchymal stem cell survival and vascularization under hypoxic-ischemic conditions in vitro. Stem Cell Research Therapy, 5, 130. https://doi.org/10.1186/scrt520. 27. Choong, O. K., et al. (2019). Hypoxia-induced H19/YB-1 cascade modulates cardiac remodeling after infarction. Theranostics, 9, 6550–6567. https://doi.org/10.7150/thno.35218. 28. Wang, K., Yang, C., Shi, J., & Gao, T. (2019). Ox-LDL-induced lncRNA MALAT1 promotes autophagy in human umbilical vein endothelial cells by sponging miR-216a-5p and regulating Beclin-1 expression. European Journal of Pharmacology, 858, 172338. https://doi.org/10. 1016/j.ejphar.2019.04.019.

228

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

29. Moreau, P. R., et al. (2018). Transcriptional profiling of hypoxia-regulated non-coding RNAs in human primary endothelial cells. Front Cardiovascular Medicine, 5, 159. https://doi.org/ 10.3389/fcvm.2018.00159. 30. Zhuang, Y. T., et al. (2017). IL-6 induced lncRNA MALAT1 enhances TNF-alpha expression in LPS-induced septic cardiomyocytes via activation of SAA3. European Review for Medical and Pharmacology Sciences, 21, 302–309. 31. Brock, M., et al. (2017). Analysis of hypoxia-induced noncoding RNAs reveals metastasisassociated lung adenocarcinoma transcript 1 as an important regulator of vascular smooth muscle cell proliferation. Experimental Biology and Medicine (Maywood), 242, 487–496. https://doi.org/10.1177/1535370216685434. 32. Voellenkle, C., et al. (2016). Implication of Long noncoding RNAs in the endothelial cell response to hypoxia revealed by RNA-sequencing. Scientific Reports, 6, 24141. https://doi. org/10.1038/srep24141. 33. Kong, X., et al. (2019). Overexpression of HIF-2alpha-dependent NEAT1 promotes the progression of non-small cell lung cancer through miR-101-3p/SOX9/Wnt/beta-catenin signal pathway. Cellular Physiology and Biochemistry, 52, 368–381. https://doi.org/10.33594/000 000026. 34. Hu, C., Bai, X., Liu, C., & Hu, Z. (2019). Long noncoding RNA XIST participates hypoxiainduced angiogenesis in human brain microvascular endothelial cells through regulating miR485/SOX7 axis. Microcirculation. https://doi.org/10.1111/micc.12601. 35. Shu, L., et al. (2020). lncRNA ANRIL protects H9c2 cells against hypoxia-induced injury through targeting the miR-7-5p/SIRT1 axis. Journal of Cellular Physiology, 235, 1175–1183. https://doi.org/10.1002/jcp.29031. 36. Sysol, J. R., et al. (2018). Micro-RNA-1 is decreased by hypoxia and contributes to the development of pulmonary vascular remodeling via regulation of sphingosine kinase 1. American Journal of Physiology. Lung Cellular and Molecular Physiology, 314, L461–L472. https:// doi.org/10.1152/ajplung.00057.2017. 37. Seong, M., Lee, J., & Kang, H. (2019). Hypoxia-induced regulation of mTOR signaling by miR-7 targeting REDD1. Journal of Cellular Biochemistry, 120, 4523–4532. https://doi.org/ 10.1002/jcb.27740. 38. Sheng, Z., et al. (2019). MicroRNA-7b attenuates ischemia/reperfusion-induced H9C2 cardiomyocyte apoptosis via the hypoxia inducible factor-1/p-p38 pathway. Journal of Cellular Biochemistry, 120, 9947–9955. https://doi.org/10.1002/jcb.28277. 39. Brock, M., et al. (2015). The hypoxia-induced microRNA-130a controls pulmonary smooth muscle cell proliferation by directly targeting CDKN1A. International Journal of Biochemistry & Cell Biology, 61, 129–137. https://doi.org/10.1016/j.biocel.2015.02.002. 40. Robertson, E. D., Wasylyk, C., Ye, T., Jung, A. C., & Wasylyk, B. (2014). The oncogenic MicroRNA Hsa-miR-155-5p targets the transcription factor ELK3 and links it to the hypoxia response. PLoS ONE, 9, e113050. https://doi.org/10.1371/journal.pone.0113050. 41. Storci, G., et al. (2013). Slug/beta-catenin-dependent proinflammatory phenotype in hypoxic breast cancer stem cells. American Journal of Pathology, 183, 1688–1697. https://doi.org/10. 1016/j.ajpath.2013.07.020. 42. Du, R., et al. (2012). Hypoxia-induced down-regulation of microRNA-34a promotes EMT by targeting the Notch signaling pathway in tubular epithelial cells. PLoS ONE, 7, e30771. https://doi.org/10.1371/journal.pone.0030771. 43. Wang, S., et al. (2020). Hypoxia-induced lncRNA PDIA3P1 promotes mesenchymal transition via sponging of miR-124-3p in glioma. Cell Death Disease, 11, 168. https://doi.org/10.1038/ s41419-020-2345-z. 44. Gu, H., et al. (2016). Hypoxia-responsive miR-124 and miR-144 reduce hypoxia-induced autophagy and enhance radiosensitivity of prostate cancer cells via suppressing PIM1. Cancer Medicine, 5, 1174–1182. https://doi.org/10.1002/cam4.664. 45. He, J., Dai, H., Zhao, Q., Guo, J., & Chen, C. (2020). LNCRNA Gas5 suppression protected Hl-1 cells against hypoxia injury by sponging Mir-222-3p. Experimental and Molecular Pathology, 115, 104436. https://doi.org/10.1016/j.yexmp.2020.104436.

References

229

46. Peng, F., et al. (2018). Glycolysis gatekeeper PDK1 reprograms breast cancer stem cells under hypoxia. Oncogene, 37, 1062–1074. https://doi.org/10.1038/onc.2017.368. 47. Wu, W., et al. (2017). Hypoxia induces H19 expression through direct and indirect Hif-1alpha activity, promoting oncogenic effects in glioblastoma. Scientific Reports, 7, 45029. https:// doi.org/10.1038/srep45029. 48. Yuan, S., et al. (2019). Hypoxia-sensitive LINC01436 is regulated by E2F6 and acts as an oncogene by targeting miR-30a-3p in non-small cell lung cancer. Molecular Oncology, 13, 840–856. https://doi.org/10.1002/1878-0261.12437. 49. Stone, J. K., et al. (2019). Hypoxia induces cancer cell-specific chromatin interactions and increases MALAT1 expression in breast cancer cells. Journal of Biological Chemistry, 294, 11213–11224. https://doi.org/10.1074/jbc.RA118.006889. 50. Tang, W., Dong, K., Li, K., Dong, R., & Zheng, S. (2016). MEG3, HCN3 and linc01105 influence the proliferation and apoptosis of neuroblastoma cells via the HIF-1alpha and p53 pathways. Scientific Reports, 6, 36268. https://doi.org/10.1038/srep36268. 51. Choudhry, H., et al. (2015). Tumor hypoxia induces nuclear paraspeckle formation through HIF-2alpha dependent transcriptional activation of NEAT1 leading to cancer cell survival. Oncogene, 34, 4546. https://doi.org/10.1038/onc.2014.431. 52. Yin, X., et al. (2020). Hypoxia-induced lncRNA ANRIL promotes cisplatin resistance in retinoblastoma cells through regulating ABCG2 expression. Clinical and Experimental Pharmacology and Physiology. https://doi.org/10.1111/1440-1681.13279. 53. Wei, X., et al. (2016). Long noncoding RNA ANRIL is activated by hypoxia-inducible factor1alpha and promotes osteosarcoma cell invasion and suppresses cell apoptosis upon hypoxia. Cancer Cell International, 16, 73. https://doi.org/10.1186/s12935-016-0349-7. 54. Yang, F., Zhang, H., Mei, Y., & Wu, M. (2014). Reciprocal regulation of HIF-1alpha and lincRNA-p21 modulates the Warburg effect. Molecular Cell, 53, 88–100. https://doi.org/10. 1016/j.molcel.2013.11.004. 55. Xu, Y., et al. (2018). Long Non-Coding RNA PVT1/miR-150/ HIG2 Axis Regulates the Proliferation, Invasion and the Balance of Iron Metabolism of Hepatocellular Carcinoma. Cellular Physiology and Biochemistry, 49, 1403–1419. https://doi.org/10.1159/000493445. 56. Yan, M., et al. (2019). Glucose impairs angiogenesis and promotes ventricular remodelling following myocardial infarction via upregulation of microRNA-17. Experimental Cell Research, 381, 191–200. https://doi.org/10.1016/j.yexcr.2019.04.039. 57. Banerjee, J., Roy, S., Dhas, Y., & Mishra, N. (2020). Senescence-associated miR-34a and miR-126 in middle-aged Indians with type 2 diabetes. Clinical and Experimental Medicine, 20, 149–158. https://doi.org/10.1007/s10238-019-00593-4. 58. Zhang, D., et al. (2016). miR-155 regulates high glucose-induced cardiac fibrosis via the TGF-beta signaling pathway. Molecular BioSystems, 13, 215–224. https://doi.org/10.1039/ c6mb00649c. 59. Gan, K., Dong, G. H., Wang, N., & Zhu, J. F. (2020). miR-221–3p and miR-222–3p downregulation promoted osteogenic differentiation of bone marrow mesenchyme stem cells through IGF-1/ERK pathway under high glucose condition. Diabetes Research and Clinical Practice, 108121. doi:https://doi.org/10.1016/j.diabres.2020.108121. 60. Li, Y., et al. (2009). MicroRNA-221 regulates high glucose-induced endothelial dysfunction. Biochemical and Biophysical Research Communications, 381, 81–83. https://doi.org/10.1016/ j.bbrc.2009.02.013. 61. Chen, P., et al. (2019). MiR-455-5p ameliorates HG-induced apoptosis, oxidative stress and inflammatory via targeting SOCS3 in retinal pigment epithelial cells. Journal of Cellular Physiology, 234, 21915–21924. https://doi.org/10.1002/jcp.28755. 62. 62Klimczak, D. et al. (2017). Plasma microRNA-155–5p is increased among patients with chronic kidney disease and nocturnal hypertension. Journal of the American Society of Hypertension, 11, 831–841 e834. doi:https://doi.org/10.1016/j.jash.2017.10.008. 63. Wu, X. Y., Fan, W. D., Fang, R., & Wu, G. F. (2014). Regulation of microRNA-155 in endothelial inflammation by targeting nuclear factor (NF)-kappaB P65. Journal of Cellular Biochemistry, 115, 1928–1936. https://doi.org/10.1002/jcb.24864.

230

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

64. O’Connell, R. M., Taganov, K. D., Boldin, M. P., Cheng, G., & Baltimore, D. (2007). MicroRNA-155 is induced during the macrophage inflammatory response. Proceedings of the National Academy of Sciences United States of America, 104, 1604–1609. https://doi.org/ 10.1073/pnas.0610731104. 65. Sun, H. X., et al. (2012). Essential role of microRNA-155 in regulating endothelium-dependent vasorelaxation by targeting endothelial nitric oxide synthase. Hypertension, 60, 1407–1414. https://doi.org/10.1161/HYPERTENSIONAHA.112.197301. 66. Qiu, X. K., & Ma, J. (2018). Alteration in microRNA-155 level correspond to severity of coronary heart disease. Scandinavian Journal of Clinical and Laboratory Investigation, 1–5. doi:https://doi.org/10.1080/00365513.2018.1435904. 67. Li, S., et al. (2018). The suppression of ox-LDL-induced inflammatory cytokine release and apoptosis of HCAECs by long non-coding RNA-MALAT1 via regulating microRNA155/SOCS1 pathway. Nutrition Metabolism Cardiovascular Disease, 28, 1175–1187. https:// doi.org/10.1016/j.numecd.2018.06.017. 68. Majumder, S., et al. (2019). Dysregulated expression but redundant function of the long noncoding RNA HOTAIR in diabetic kidney disease. Diabetologia, 62, 2129–2142. https://doi. org/10.1007/s00125-019-4967-1. 69. Yin, D. D., et al. (2015). Downregulation of lncRNA TUG1 affects apoptosis and insulin secretion in mouse pancreatic beta cells. Cellular Physiology and Biochemistry, 35, 1892– 1904. https://doi.org/10.1159/000373999. 70. Frias Fde, T. et al. (2016). MyomiRs as markers of insulin resistance and decreased myogenesis in skeletal muscle of diet-induced obese mice. Front Endocrinology (Lausanne), 7, 76. doi:https://doi.org/10.3389/fendo.2016.00076. 71. Chen, T., Ding, G., Jin, Z., Wagner, M. B., & Yuan, Z. (2012). Insulin ameliorates miR-1induced injury in H9c2 cells under oxidative stress via Akt activation. Molecular and Cellular Biochemistry, 369, 167–174. https://doi.org/10.1007/s11010-012-1379-7. 72. Shi, Y., et al. (2020). Ginsenoside Rg3 suppresses the NLRP3 inflammasome activation through inhibition of its assembly. The FASEB Journal, 34, 208–221. https://doi.org/10.1096/ fj.201901537R. 73. Zhang, J., et al. (2019). miR-29a/b cluster suppresses high glucose-induced endothelialmesenchymal transition in human retinal microvascular endothelial cells by targeting Notch2. Experimental and Therapeutic Medicine, 17, 3108–3116. https://doi.org/10.3892/etm.2019. 7323. 74. Chen, J., Cui, L., Yuan, J., Zhang, Y., & Sang, H. (2017). Circular RNA WDR77 target FGF-2 to regulate vascular smooth muscle cells proliferation and migration by sponging miR-124. Biochemical and Biophysical Research Communications, 494, 126–132. https://doi.org/10. 1016/j.bbrc.2017.10.068. 75. Liu, Y., Chen, X., Yao, J., & Kang, J. (2019). Circular RNA ACR relieves high glucosearoused RSC96 cell apoptosis and autophagy via declining microRNA-145-3p. Journal of Cellular Biochemistry. https://doi.org/10.1002/jcb.29568. 76. Law, P. T., et al. (2012). MiR-145 modulates multiple components of the insulin-like growth factor pathway in hepatocellular carcinoma. Carcinogenesis, 33, 1134–1141. https://doi.org/ 10.1093/carcin/bgs130. 77. Xie, C., Wu, W., Tang, A., Luo, N., & Tan, Y. (2019). lncRNA GAS5/miR-452-5p reduces oxidative stress and pyroptosis of high-glucose-stimulated renal tubular cells. Diabetes, Metabolic Syndrome and Obesity, 12, 2609–2617. https://doi.org/10.2147/DMSO.S228654. 78. Li, F., Sun, J., Huang, S., Su, G., & Pi, G. (2018). LncRNA GAS5 overexpression reverses LPS-induced inflammatory injury and apoptosis through up-regulating KLF2 expression in ATDC5 chondrocytes. Cellular Physiology and Biochemistry, 45, 1241–1251. https://doi.org/ 10.1159/000487455. 79. Chin, P. Y., Macpherson, A. M., Thompson, J. G., Lane, M., & Robertson, S. A. (2009). Stress response genes are suppressed in mouse preimplantation embryos by granulocyte-macrophage colony-stimulating factor (GM-CSF). Human Reproduction, 24, 2997–3009. https://doi.org/ 10.1093/humrep/dep307.

References

231

80. Li, X., et al. (2019). High glucose regulates ERp29 in hepatocellular carcinoma by LncRNA MEG3-miRNA 483–3p pathway. Life Sciences, 232, 116602. https://doi.org/10.1016/j.lfs. 2019.116602. 81. Li, X., Zhang, Q., & Yang, Z. (2019). Silence of MEG3 intensifies lipopolysaccharidestimulated damage of human lung cells through modulating miR-4262. Artificial Cells, Nanomedicine, and Biotechnology, 47, 2369–2378. https://doi.org/10.1080/21691401.2019. 1623233. 82. Zhang, S. H., et al. (2019). LncRNA MALAT1 affects high glucose-induced endothelial cell proliferation, apoptosis, migration and angiogenesis by regulating the PI3K/Akt signaling pathway. Europena Review for Medical and Pharmacological Sciences, 23, 8551–8559. https://doi.org/10.26355/eurrev_201910_19170. 83. Wei, S., et al. (2019). Knockdown of the lncRNA MALAT1 alleviates lipopolysaccharideinduced A549 cell injury by targeting the miR175p/FOXA1 axis. Molecular Medicine Reports, 20, 2021–2029. https://doi.org/10.3892/mmr.2019.10392. 84. Zhao, G., Su, Z., Song, D., Mao, Y., & Mao, X. (2016). The long noncoding RNA MALAT1 regulates the lipopolysaccharide-induced inflammatory response through its interaction with NF-kappaB. FEBS Letters, 590, 2884–2895. https://doi.org/10.1002/1873-3468.12315. 85. Zhang, J. et al. (2017). Long non-coding RNA MIAT acts as a biomarker in diabetic retinopathy by absorbing miR-29b and regulating cell apoptosis. Bioscience Reports, 37. doi:https://doi. org/10.1042/BSR20170036. 86. Li, Q., et al. (2018). Long non-coding RNA of myocardial infarction associated transcript (LncRNA-MIAT) Promotes diabetic retinopathy by upregulating transforming growth factorbeta1 (TGF-beta1) signaling. Medical Science Monitor, 24, 9497–9503. https://doi.org/10. 12659/MSM.911787. 87. Zhang, J., et al. (2019). C-myc contributes to the release of Muller cells-derived proinflammatory cytokines by regulating lncRNA MIAT/XNIP pathway. International Journal of Biochemistry & Cell Biology, 114, 105574. https://doi.org/10.1016/j.biocel.2019.105574. 88. Chen, Y. C., Ou, M. C., Fang, C. W., Lee, T. H., & Tzeng, S. L.(2019). High glucose concentrations negatively regulate the IGF1R/Src/ERK Axis through the MicroRNA-9 in colorectal cancer. Cells, 8. doi:https://doi.org/10.3390/cells8040326. 89. Li, Q., et al. (2014). Insulin regulates glucose consumption and lactate production through reactive oxygen species and pyruvate kinase M2. Oxidative Medicine and Cellular Longevity, 2014, 504953. https://doi.org/10.1155/2014/504953. 90. Meseguer, S., Martinez-Zamora, A., Garcia-Arumi, E., Andreu, A. L., & Armengod, M. E. (2015). The ROS-sensitive microRNA-9/9* controls the expression of mitochondrial tRNAmodifying enzymes and is involved in the molecular mechanism of MELAS syndrome. Human Molecular Genetics, 24, 167–184. https://doi.org/10.1093/hmg/ddu427. 91. Khaidakov, M., & Mehta, J. L. (2012). Oxidized LDL triggers pro-oncogenic signaling in human breast mammary epithelial cells partly via stimulation of MiR-21. PLoS ONE, 7, e46973. https://doi.org/10.1371/journal.pone.0046973. 92. Jian, D., et al. (2017). ox-LDL increases microRNA-29a transcription through upregulating YY1 and STAT1 in macrophages. Cell Biology International, 41, 1001–1011. https://doi.org/ 10.1002/cbin.10803. 93. Wu, J., et al. (2019). Inhibition of P53/miR-34a improves diabetic endothelial dysfunction via activation of SIRT1. Journal of Cellular and Molecular Medicine, 23, 3538–3548. https:// doi.org/10.1111/jcmm.14253. 94. von Muhlinen, N. et al. (2018). p53 isoforms regulate premature aging in human cells. Oncogene, 37, 2379–2393. doi:https://doi.org/10.1038/s41388-017-0101-3. 95. Wan, Y., et al. (2017). Identification of four oxidative stress-responsive MicroRNAs, miR34a-5p, miR-1915-3p, miR-638, and miR-150-3p, in hepatocellular carcinoma. Oxidative Medicine and Cellular Longevity, 2017, 5189138. https://doi.org/10.1155/2017/5189138. 96. Yan, H., et al. (2016). Upregulation of miRNA-155 expression by OxLDL in dendritic cells involves JAK1/2 kinase and transcription factors YY1 and MYB. International Journal of Molecular Medicine, 37, 1371–1378. https://doi.org/10.3892/ijmm.2016.2526.

232

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

97. Yin, S., et al. (2018). MicroRNA155 promotes oxLDLinduced autophagy in human umbilical vein endothelial cells by targeting the PI3K/Akt/mTOR pathway. Molecular Medicine Reports, 18, 2798–2806. https://doi.org/10.3892/mmr.2018.9236. 98. Li, H., et al. (2019). LncRNA MALAT1 modulates ox-LDL induced EndMT through the Wnt/beta-catenin signaling pathway. Lipids Health Disease, 18, 62. https://doi.org/10.1186/ s12944-019-1006-7. 99. Zhong, X., et al. (2018). MIAT promotes proliferation and hinders apoptosis by modulating miR-181b/STAT3 axis in ox-LDL-induced atherosclerosis cell models. Biomedicine & Pharmacotherapy, 97, 1078–1085. https://doi.org/10.1016/j.biopha.2017.11.052. 100. Wu, X., Zheng, X., Cheng, J., Zhang, K., & Ma, C. (2020). LncRNA TUG1 regulates proliferation and apoptosis by regulating miR-148b/IGF2 axis in ox-LDL-stimulated VSMC and HUVEC. Life Sciences, 243, 117287. https://doi.org/10.1016/j.lfs.2020.117287. 101. Hopkins, B. L., et al. (2018). A peroxidase Peroxiredoxin 1-specific redox regulation of the novel FOXO3 microRNA target let-7. Antioxidants & Redox Signaling, 28, 62–77. https:// doi.org/10.1089/ars.2016.6871. 102. Bazzoni, F., et al. (2009). Induction and regulatory function of miR-9 in human monocytes and neutrophils exposed to proinflammatory signals. Proceedings of the National Academy of Sciences of the United States of America, 106, 5282–5287. https://doi.org/10.1073/pnas. 0810909106. 103. Yang, B., et al. (2018). IL-1beta-induced miR-34a up-regulation inhibits Cyr61 to modulate osteoarthritis chondrocyte proliferation through ADAMTS-4. Journal of Cellular Biochemistry, 119, 7959–7970. https://doi.org/10.1002/jcb.26600. 104. Lu, H., et al. (2016). Elevated circulating stearic acid leads to a major lipotoxic effect on mouse pancreatic beta cells in hyperlipidaemia via a miR-34a-5p-mediated PERK/p53-dependent pathway. Diabetologia, 59, 1247–1257. https://doi.org/10.1007/s00125-016-3900-0. 105. Lin, X., et al. (2014). Downregulation of Bcl-2 expression by miR-34a mediates palmitateinduced Min6 cells apoptosis. Journal of Diabetes Research, 2014, 258695. https://doi.org/ 10.1155/2014/258695. 106. Wen, Z., Chen, Y., Long, Y., Yu, J., & Li, M. (2018). Tumor necrosis factor-alpha suppresses the invasion of HTR-8/SVneo trophoblast cells through microRNA-145-5pmediated downregulation of Cyr61. Life Sciences, 209, 132–139. https://doi.org/10.1016/ j.lfs.2018.08.005. 107. Lorente-Cebrian, S., et al. (2014). MicroRNAs regulate human adipocyte lipolysis: Effects of miR-145 are linked to TNF-alpha. PLoS ONE, 9, e86800. https://doi.org/10.1371/journal. pone.0086800. 108. Wang, N. et al. (2016). TNF-alpha-induced NF-kappaB activation upregulates microRNA150–3p and inhibits osteogenesis of mesenchymal stem cells by targeting beta-catenin. Open Biology, 6. doi:https://doi.org/10.1098/rsob.150258. 109. Park, M., et al. (2019). NF-kappaB-responsive miR-155 induces functional impairment of vascular smooth muscle cells by downregulating soluble guanylyl cyclase. Experimental & Molecular Medicine, 51, 1–12. https://doi.org/10.1038/s12276-019-0212-8. 110. Choi, S., et al. (2018). TNF-alpha elicits phenotypic and functional alterations of vascular smooth muscle cells by miR-155-5p-dependent down-regulation of cGMP-dependent kinase 1. Journal of Biological Chemistry, 293, 14812–14822. https://doi.org/10.1074/jbc.RA118. 004220. 111. Tili, E., et al. (2007). Modulation of miR-155 and miR-125b levels following lipopolysaccharide/TNF-alpha stimulation and their possible roles in regulating the response to endotoxin shock. The Journal of Immunology, 179, 5082–5089. https://doi.org/10.4049/ jimmunol.179.8.5082. 112. Kim, C., et al. (2013). TNFalpha-induced miR-130 resulted in adipocyte dysfunction during obesity-related inflammation. FEBS Letters. https://doi.org/10.1016/j.febslet.2013.10.018. 113. Trotta, R., et al. (2012). miR-155 regulates IFN-gamma production in natural killer cells. Blood, 119, 3478–3485. https://doi.org/10.1182/blood-2011-12-398099.

References

233

114. Cheng, Y. Q., et al. (2015). MicroRNA-155 regulates interferon-gamma production in natural killer cells via Tim-3 signalling in chronic hepatitis C virus infection. Immunology, 145, 485–497. https://doi.org/10.1111/imm.12463. 115. Xu, L. L., et al. (2014). TNF-alpha, IL-6, and leptin increase the expression of miR-378, an adipogenesis-related microRNA in human adipocytes. Cell Biochemistry and Biophysics, 70, 771–776. https://doi.org/10.1007/s12013-014-9980-x. 116. Ruckerl, D., et al. (2012). Induction of IL-4Ralpha-dependent microRNAs identifies PI3K/Akt signaling as essential for IL-4-driven murine macrophage proliferation in vivo. Blood, 120, 2307–2316. https://doi.org/10.1182/blood-2012-02-408252. 117. Ning, Z. W., et al. (2017). MicroRNA-21 mediates angiotensin II-induced liver fibrosis by activating NLRP3 Inflammasome/IL-1beta Axis via Targeting Smad7 and Spry1. Antioxidants & Redox Signaling, 27, 1–20. https://doi.org/10.1089/ars.2016.6669. 118. Chen, L. Y., et al. (2019). Activation of the STAT3/microRNA-21 pathway participates in angiotensin II-induced angiogenesis. Journal of Cellular Physiology. https://doi.org/10.1002/ jcp.28564. 119. Qu, X., et al. (2017). MIAT Is a Pro-fibrotic Long Non-coding RNA governing cardiac fibrosis in post-infarct myocardium. Scientific Reports, 7, 42657. https://doi.org/10.1038/srep42657. 120. Wang, Z., et al. (2014). Leukotriene B4 enhances the generation of proinflammatory microRNAs to promote MyD88-dependent macrophage activation. The Journal of Immunology, 192, 2349–2356. https://doi.org/10.4049/jimmunol.1302982. 121. Yokomizo, T., Nakamura, M., & Shimizu, T. (2018). Leukotriene receptors as potential therapeutic targets. Journal of Clinical Investigation, 128, 2691–2701. https://doi.org/10.1172/ JCI97946. 122. Caserta, S., et al. (2016). Circulating plasma microRNAs can differentiate human sepsis and systemic inflammatory response syndrome (SIRS). Scientific Reports, 6, 28006. https://doi. org/10.1038/srep28006. 123. Karner, J., et al. (2017). Increased microRNA-323-3p in IL-22/IL-17-producing T cells and asthma: A role in the regulation of the TGF-beta pathway and IL-22 production. Allergy, 72, 55–65. https://doi.org/10.1111/all.12907. 124. Fayyad-Kazan, H., et al. (2014). Downregulation of microRNA-24 and -181 parallels the upregulation of IFN-gamma secreted by activated human CD4 lymphocytes. Human Immunology, 75, 677–685. https://doi.org/10.1016/j.humimm.2014.01.007. 125. Sehgal, M., et al. (2015). IFN-alpha-induced downregulation of miR-221 in dendritic cells: Implications for HCV pathogenesis and treatment. Journal of Interferon and Cytokine Research, 35, 698–709. https://doi.org/10.1089/jir.2014.0211. 126. Wang, P., et al. (2012). Identification of resting and type I IFN-activated human NK cell miRNomes reveals microRNA-378 and microRNA-30e as negative regulators of NK cell cytotoxicity. The Journal of Immunology, 189, 211–221. https://doi.org/10.4049/jimmunol. 1200609. 127. Schaefer, J. S., Montufar-Solis, D., Vigneswaran, N., & Klein, J. R. (2011). Selective upregulation of microRNA expression in peripheral blood leukocytes in IL-10-/- mice precedes expression in the colon. The Journal of Immunology, 187, 5834–5841. https://doi.org/10. 4049/jimmunol.1100922. 128. Cheung, S. T., So, E. Y., Chang, D., Ming-Lum, A., & Mui, A. L. (2013). Interleukin-10 inhibits lipopolysaccharide induced miR-155 precursor stability and maturation. PLoS ONE, 8, e71336. https://doi.org/10.1371/journal.pone.0071336. 129. McCoy, C. E., et al. (2010). IL-10 inhibits miR-155 induction by toll-like receptors. Journal of Biological Chemistry, 285, 20492–20498. https://doi.org/10.1074/jbc.M110.102111. 130. Hong, K., Xu, G., Grayson, T. B., & Shalev, A. (2016). Cytokines regulate beta-cell thioredoxin-interacting protein (TXNIP) via distinct mechanisms and pathways. Journal of Biological Chemistry, 291, 8428–8439. https://doi.org/10.1074/jbc.M115.698365. 131. Li, Y., et al. (2015). Microenvironmental interleukin-6 suppresses toll-like receptor signaling in human leukemia cells through miR-17/19A. Blood, 126, 766–778. https://doi.org/10.1182/ blood-2014-12-618678.

234

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

132. Pena-Cano, M. I., et al. (2019). Deregulated microRNAs and adiponectin in postmenopausal women with breast cancer. Gynecologic and Obstetric Investigation, 84, 369–377. https://doi. org/10.1159/000496340. 133. Dong, B., et al. (2015). IL-6 inhibits the targeted modulation of PDCD4 by miR-21 in prostate cancer. PLoS ONE, 10, e0134366. https://doi.org/10.1371/journal.pone.0134366. 134. He, Q., et al. (2016). MicroRNA-21 regulates prostaglandin E2 signaling pathway by targeting 15-hydroxyprostaglandin dehydrogenase in tongue squamous cell carcinoma. BMC Cancer, 16, 685. https://doi.org/10.1186/s12885-016-2716-0. 135. Yu, X., et al. (2019). CXCL12/CXCR4 promotes inflammation-driven colorectal cancer progression through activation of RhoA signaling by sponging miR-133a-3p. Journal of Experimental and Clinical Cancer Research, 38, 32. https://doi.org/10.1186/s13046-0181014-x. 136. Ooki, A., et al. (2018). YAP1 and COX2 coordinately regulate urothelial cancer stem-like cells. Cancer Research, 78, 168–181. https://doi.org/10.1158/0008-5472.CAN-17-0836. 137. Kong, D., et al. (2012). Inflammation-induced repression of tumor suppressor miR-7 in gastric tumor cells. Oncogene, 31, 3949–3960. https://doi.org/10.1038/onc.2011.558. 138. Margolis, L. M., et al. (2017). Upregulation of circulating myomiR following short-term energy restriction is inversely associated with whole body protein synthesis. American Journal of Physiology: Regulatory, Integrative and Comparative Physiology, 313, R298–R304. https:// doi.org/10.1152/ajpregu.00054.2017. 139. Georgantas, R. W., et al. (2014). Inhibition of myogenic microRNAs 1, 133, and 206 by inflammatory cytokines links inflammation and muscle degeneration in adult inflammatory myopathies. Arthritis Rheumatology, 66, 1022–1033. https://doi.org/10.1002/art.38292. 140. Liu, Z., et al. (2019). TNFalpha-induced up-regulation of Ascl2 affects the differentiation and proliferation of neural stem cells. Aging and Disease, 10, 1207–1220. https://doi.org/10. 14336/AD.2018.1028. 141. Sun, Y., Ai, X., Shen, S., & Lu, S. (2015). NF-kappaB-mediated miR-124 suppresses metastasis of non-small-cell lung cancer by targeting MYO10. Oncotarget, 6, 8244–8254. https:// doi.org/10.18632/oncotarget.3135. 142. Tu, X., et al. (2017). TGF-beta-induced hepatocyte lincRNA-p21 contributes to liver fibrosis in mice. Scientific Reports, 7, 2957. https://doi.org/10.1038/s41598-017-03175-0. 143. Liu, W., Feng, R., Li, X., Li, D., & Zhai, W. (2019). TGF-beta- and lipopolysaccharide-induced upregulation of circular RNA PWWP2A promotes hepatic fibrosis via sponging miR-203 and miR-223. Aging (Albany NY), 11, 9569–9580. https://doi.org/10.18632/aging.102405. 144. Yang, L., et al. (2019). EGF suppresses the expression of miR-124a in pancreatic beta cell lines via ETS2 activation through the MEK and PI3K signaling pathways. International Journal of Biological Sciences, 15, 2561–2575. https://doi.org/10.7150/ijbs.34985. 145. Wang, H. et al. (2017). TGF-beta1-induced epithelial-mesenchymal transition in lung cancer cells involves upregulation of miR-9 and downregulation of its target, E-cadherin. Cellular and Molecular Biology Letters, 22, 22. doi:https://doi.org/10.1186/s11658-017-0053-1. 146. Nishioka, C., Ikezoe, T., Pan, B., Xu, K., & Yokoyama, A. (2017). MicroRNA-9 plays a role in interleukin-10-mediated expression of E-cadherin in acute myelogenous leukemia cells. Cancer Science, 108, 685–695. https://doi.org/10.1111/cas.13170. 147. Wang, H., Li, C., Jian, Z., Ou, Y., & Ou, J. (2015). TGF-beta1 reduces miR-29a expression to promote tumorigenicity and metastasis of cholangiocarcinoma by targeting HDAC4. PLoS ONE, 10, e0136703. https://doi.org/10.1371/journal.pone.0136703. 148. Xiao, L., et al. (2018). TGF-beta/SMAD signaling inhibits intermittent cyclic mechanical tension-induced degeneration of endplate chondrocytes by regulating the miR-4555p/RUNX2 axis. Journal of Cellular Biochemistry, 119, 10415–10425. https://doi.org/10. 1002/jcb.27391. 149. Terashima, M., Tange, S., Ishimura, A., & Suzuki, T. (2017). MEG3 Long Noncoding RNA Contributes to the Epigenetic Regulation of Epithelial-Mesenchymal Transition in Lung Cancer Cell Lines. Journal of Biological Chemistry, 292, 82–99. https://doi.org/10.1074/ jbc.M116.750950.

References

235

150. Yu, X., et al. (2019). Long non-coding RNA Taurine upregulated gene 1 promotes osteosarcoma cell metastasis by mediating HIF-1alpha via miR-143-5p. Cell Death Disease, 10, 280. https://doi.org/10.1038/s41419-019-1509-1. 151. Zhang, D., et al. (2018). TGF-beta secreted by tumor-associated macrophages promotes proliferation and invasion of colorectal cancer via miR-34a-VEGF axis. Cell Cycle, 17, 2766–2778. https://doi.org/10.1080/15384101.2018.1556064. 152. Huang, G., et al. (2018). MiRNA-34a reversed TGF-beta-induced epithelial-mesenchymal transition via suppression of SMAD4 in NPC cells. Biomedicine & Pharmacotherapy, 106, 217–224. https://doi.org/10.1016/j.biopha.2018.06.115. 153. Zu, L., et al. (2016). The feedback loop between miR-124 and TGF-beta pathway plays a significant role in non-small cell lung cancer metastasis. Carcinogenesis, 37, 333–343. https://doi.org/10.1093/carcin/bgw011. 154. Wu, R., et al. (2020). Enhanced alleviation of aGVHD by TGF-beta1-modified mesenchymal stem cells in mice through shifting MPhi into M2 phenotype and promoting the differentiation of Treg cells. Journal of Cellular and Molecular Medicine, 24, 1684–1699. https://doi.org/ 10.1111/jcmm.14862. 155. Liu, F., et al. (2019). MSC-secreted TGF-beta regulates lipopolysaccharide-stimulated macrophage M2-like polarization via the Akt/FoxO1 pathway. Stem Cell Research and Therapy, 10, 345. https://doi.org/10.1186/s13287-019-1447-y. 156. Pan, Y., et al. (2019). Adipocyte-secreted exosomal microRNA-34a inhibits M2 macrophage polarization to promote obesity-induced adipose inflammation. Journal of Clinical Investigation, 129, 834–849. https://doi.org/10.1172/JCI123069. 157. Veremeyko, T., Siddiqui, S., Sotnikov, I., Yung, A., & Ponomarev, E. D. (2013). IL-4/IL-13dependent and independent expression of miR-124 and its contribution to M2 phenotype of monocytic cells in normal conditions and during allergic inflammation. PLoS ONE, 8, e81774. https://doi.org/10.1371/journal.pone.0081774. 158. Duan, L. J., et al. (2015). MiR-133 modulates TGF-beta1-induced bladder smooth muscle cell hypertrophic and fibrotic response: Implication for a role of microRNA in bladder wall remodeling caused by bladder outlet obstruction. Cellular Signalling, 27, 215–227. https:// doi.org/10.1016/j.cellsig.2014.11.001. 159. Chen, X., et al. (2019). MiR-9 promotes tumorigenesis and angiogenesis and is activated by MYC and OCT4 in human glioma. Journal of Experimental & Clinical Cancer Research, 38, 99. https://doi.org/10.1186/s13046-019-1078-2. 160. Ma, L., et al. (2010). miR-9, a MYC/MYCN-activated microRNA, regulates E-cadherin and cancer metastasis. Nature Cell Biology, 12, 247–256. https://doi.org/10.1038/ncb2024. 161. Li, S. G., et al. (2018). C-Myc-dependent repression of two oncogenic miRNA clusters contributes to triptolide-induced cell death in hepatocellular carcinoma cells. Journal of Experimental & Clinical Cancer Research, 37, 51. https://doi.org/10.1186/s13046-0180698-2. 162. Mihailovich, M., et al. (2015). miR-17-92 fine-tunes MYC expression and function to ensure optimal B cell lymphoma growth. Nature Communications, 6, 8725. https://doi.org/10.1038/ ncomms9725. 163. Li, H., et al. (2019). C-myc/miR-150/EPG5 axis mediated dysfunction of autophagy promotes development of non-small cell lung cancer. Theranostics, 9, 5134–5148. https://doi.org/10. 7150/thno.34887. 164. Zhou, J., et al. (2013). MicroRNA-155 promotes glioma cell proliferation via the regulation of MXI1. PLoS ONE, 8, e83055. https://doi.org/10.1371/journal.pone.0083055. 165. Lu, Y., et al. (2016). Long noncoding RNA ANRIL could be transactivated by c-Myc and promote tumor progression of non-small-cell lung cancer. Onco Targets Therapy, 9, 3077– 3084. https://doi.org/10.2147/OTT.S102658. 166. Cui, J., et al. (2015). c-Myc-activated long non-coding RNA H19 downregulates miR-107 and promotes cell cycle progression of non-small cell lung cancer. International Journal of Clinical and Experimental Pathology, 8, 12400–12409.

236

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

167. Zhang, E. B., et al. (2014). c-Myc-induced, long, noncoding H19 affects cell proliferation and predicts a poor prognosis in patients with gastric cancer. Medical Oncology, 31, 914. https:// doi.org/10.1007/s12032-014-0914-7. 168. Barsyte-Lovejoy, D., et al. (2006). The c-Myc oncogene directly induces the H19 noncoding RNA by allele-specific binding to potentiate tumorigenesis. Cancer Research, 66, 5330–5337. https://doi.org/10.1158/0008-5472.CAN-06-0037. 169. Cho, S. W. et al. (2018). Promoter of lncRNA Gene PVT1 Is a tumor-suppressor dna boundary element. Cell, 173, 1398–1412 e1322. doi:https://doi.org/10.1016/j.cell.2018.03.068. 170. Wang, C., et al. (2020). C-Myc-activated long non-coding RNA PVT1 enhances the proliferation of cervical cancer cells by sponging miR-486-3p. Journal of Biochemistry. https://doi. org/10.1093/jb/mvaa005. 171. Tseng, Y. Y., et al. (2014). PVT1 dependence in cancer with MYC copy-number increase. Nature, 512, 82–86. https://doi.org/10.1038/nature13311. 172. Carramusa, L., et al. (2007). The PVT-1 oncogene is a Myc protein target that is overexpressed in transformed cells. Journal of Cellular Physiology, 213, 511–518. https://doi.org/10.1002/ jcp.21133. 173. Wang, Z., et al. (2011). MYC protein inhibits transcription of the microRNA cluster MC-let7a-1~let-7d via noncanonical E-box. Journal of Biological Chemistry, 286, 39703–39714. https://doi.org/10.1074/jbc.M111.293126. 174. Sander, S., et al. (2008). MYC stimulates EZH2 expression by repression of its negative regulator miR-26a. Blood, 112, 4202–4212. https://doi.org/10.1182/blood-2008-03-147645. 175. Zhang, X., et al. (2012). Coordinated silencing of MYC-mediated miR-29 by HDAC3 and EZH2 as a therapeutic target of histone modification in aggressive B-Cell lymphomas. Cancer Cell, 22, 506–523. https://doi.org/10.1016/j.ccr.2012.09.003. 176. Salvatori, B., et al. (2011). Critical role of c-Myc in acute myeloid leukemia involving direct regulation of miR-26a and histone methyltransferase EZH2. Genes Cancer, 2, 585–592. https://doi.org/10.1177/1947601911416357. 177. Dey, S., et al. (2020). miR-29a is repressed by MYC in pancreatic cancer and its restoration drives tumor-suppressive effects via downregulation of LOXL2. Molecular Cancer Research, 18, 311–323. https://doi.org/10.1158/1541-7786.MCR-19-0594. 178. Peta, E., et al. (2018). HPV16 E6 and E7 upregulate the histone lysine demethylase KDM2B through the c-MYC/miR-146a-5p axys. Oncogene, 37, 1654–1668. https://doi.org/10.1038/ s41388-017-0083-1. 179. Zhang, X., et al. (2018). MicroRNA-26a is a key regulon that inhibits progression and metastasis of c-Myc/EZH2 double high advanced hepatocellular carcinoma. Cancer Letters, 426, 98–108. https://doi.org/10.1016/j.canlet.2018.04.005. 180. Chen, P. C. et al. (2019). c-Myc Acts as a Competing Endogenous RNA to Sponge miR-34a, in the Upregulation of CD44, in Urothelial Carcinoma. Cancers (Basel), 11. doi:https://doi. org/10.3390/cancers11101457. 181. Zhang, L., Fu, Y., & Guo, H. (2019). c-Myc-induced long non-coding RNA small nucleolar RNA host gene 7 regulates glycolysis in breast cancer. Journal of Breast Cancer, 22, 533–547. https://doi.org/10.4048/jbc.2019.22.e54. 182. Jeong, D., et al. (2015). MicroRNA-124 links p53 to the NF-kappaB pathway in B-cell lymphomas. Leukemia, 29, 1868–1874. https://doi.org/10.1038/leu.2015.101. 183. Seviour, E. G., et al. (2016). Functional proteomics identifies miRNAs to target a p27/Myc/phospho-Rb signature in breast and ovarian cancer. Oncogene, 35, 801. https:// doi.org/10.1038/onc.2015.177. 184. Pello, O. M., et al. (2012). Role of c-MYC in alternative activation of human macrophages and tumor-associated macrophage biology. Blood, 119, 411–421. https://doi.org/10.1182/blood2011-02-339911. 185. Martinez, F. O., et al. (2013). Genetic programs expressed in resting and IL-4 alternatively activated mouse and human macrophages: Similarities and differences. Blood, 121, e57-69. https://doi.org/10.1182/blood-2012-06-436212.

References

237

186. Pello, O. M. (2016). Macrophages and c-Myc cross paths. Oncoimmunology, 5, e1151991. doi:https://doi.org/10.1080/2162402X.2016.1151991. 187. Sebastiani, G., et al. (2015). MicroRNA-124a is hyperexpressed in type 2 diabetic human pancreatic islets and negatively regulates insulin secretion. Acta Diabetologica, 52, 523–530. https://doi.org/10.1007/s00592-014-0675-y. 188. Baroukh, N., et al. (2007). MicroRNA-124a regulates Foxa2 expression and intracellular signaling in pancreatic beta-cell lines. Journal of Biological Chemistry, 282, 19575–19588. https://doi.org/10.1074/jbc.M611841200. 189. Xin, Y., et al. (2018). Resveratrol improves uric acid-induced pancreatic beta-cells injury and dysfunction through regulation of miR-126. Biomedicine & Pharmacotherapy, 102, 1120– 1126. https://doi.org/10.1016/j.biopha.2018.03.172. 190. Tokgun, O., Tokgun, P. E., Inci, K., & Akca, H. (2020). llncRNAs as Potential Targets in Small Cell Lung Cancer: Myc Dependent Regulation. Anti-Cancer Agents in Medicinal Chemistry. https://doi.org/10.2174/1871520620666200721130700. 191. Huang, F. X., et al. (2019). LncRNA BLACAT1 is involved in chemoresistance of nonsmall cell lung cancer cells by regulating autophagy. International Journal of Oncology, 54, 339– 347. https://doi.org/10.3892/ijo.2018.4614. 192. Wang, C. H., Li, Y. H., Tian, H. L., Bao, X. X., & Wang, Z. M. (2018). Long noncoding RNA BLACAT1 promotes cell proliferation, migration and invasion in cervical cancer through activation of Wnt/beta-catenin signaling pathway. European Review for Medical and Pharmacological Sciences, 22, 3002–3009. https://doi.org/10.26355/eurrev_201805_15057. 193. Hu, X., Liu, Y., Du, Y., Cheng, T., & Xia, W. (2019). Long non-coding RNA BLACAT1 promotes breast cancer cell proliferation and metastasis by miR-150-5p/CCR2. Cell Bioscience, 9, 14. https://doi.org/10.1186/s13578-019-0274-2. 194. Luo, H., Xu, C., Le, W., Ge, B., & Wang, T. (2019). lncRNA CASC11 promotes cancer cell proliferation in bladder cancer through miRNA-150. Journal of Cellular Biochemistry, 120, 13487–13493. https://doi.org/10.1002/jcb.28622. 195. Fu, Y., et al. (2019). LncRNA CASC11 promotes TGF-beta1, increases cancer cell stemness and predicts postoperative survival in small cell lung cancer. Gene, 704, 91–96. https://doi. org/10.1016/j.gene.2019.04.019. 196. Du, F., Guo, T., & Cao, C. (2020). Silencing of Long Noncoding RNA SNHG6 Inhibits Esophageal Squamous Cell Carcinoma Progression via miR-186-5p/HIF1alpha Axis. Digestive Diseases and Sciences, 65, 2844–2852. https://doi.org/10.1007/s10620-019-06012-8. 197. Zhang, Z., et al. (2018). Long non-coding RNA FEZF1-AS1 promotes breast cancer stemness and tumorigenesis via targeting miR-30a/Nanog axis. Journal of Cellular Physiology, 233, 8630–8638. https://doi.org/10.1002/jcp.26611. 198. Fang, C., et al. (2017). Long non-coding RNA HNF1A-AS1 mediated repression of miR34a/SIRT1/p53 feedback loop promotes the metastatic progression of colon cancer by functioning as a competing endogenous RNA. Cancer Letters, 410, 50–62. https://doi.org/10. 1016/j.canlet.2017.09.012. 199. Navarro, F., & Lieberman, J. (2015). miR-34 and p53: New insights into a complex functional relationship. PLoS ONE, 10, e0132767. https://doi.org/10.1371/journal.pone.0132767. 200. Novello, C., et al. (2014). p53-dependent activation of microRNA-34a in response to etoposide-induced DNA damage in osteosarcoma cell lines not impaired by dominant negative p53 expression. PLoS ONE, 9, e114757. https://doi.org/10.1371/journal.pone.0114757. 201. Rokavec, M., et al. (2014). IL-6R/STAT3/miR-34a feedback loop promotes EMT-mediated colorectal cancer invasion and metastasis. Journal of Clinical Investigation, 124, 1853–1867. https://doi.org/10.1172/JCI73531. 202. Ng, W. L., et al. (2014). OCT4 as a target of miR-34a stimulates p63 but inhibits p53 to promote human cell transformation. Cell Death Disease, 5, e1024. https://doi.org/10.1038/ cddis.2013.563. 203. Liu, K., et al. (2017). Wild-type and mutant p53 differentially modulate miR-124/iASPP feedback following pohotodynamic therapy in human colon cancer cell line. Cell Death Disease, 8, e3096. https://doi.org/10.1038/cddis.2017.477.

238

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

204. Zhang, X., et al. (2017). Long noncoding RNA HNF1A-AS1 indicates a poor prognosis of colorectal cancer and promotes carcinogenesis via activation of the Wnt/beta-catenin signaling pathway. Biomedicine & Pharmacotherapy, 96, 877–883. https://doi.org/10.1016/j.biopha. 2017.10.033. 205. He, W., et al. (2019). MSC-regulated lncRNA MACC1-AS1 promotes stemness and chemoresistance through fatty acid oxidation in gastric cancer. Oncogene, 38, 4637–4654. https://doi. org/10.1038/s41388-019-0747-0. 206. Zhao, Y., et al. (2018). The lncRNA MACC1-AS1 promotes gastric cancer cell metabolic plasticity via AMPK/Lin28 mediated mRNA stability of MACC1. Molecular Cancer, 17, 69. https://doi.org/10.1186/s12943-018-0820-2. 207. Zhang, X., et al. (2019). LncRNA MACC1-AS1 sponges multiple miRNAs and RNA-binding protein PTBP1. Oncogenesis, 8, 73. https://doi.org/10.1038/s41389-019-0182-7. 208. Jin, J., Chen, X., Chen, J., & Geng, X. (2020). Long noncoding RNA MACC1-AS1 is a potential sponge of microRNA-34a in cervical squamous cell carcinoma and upregulates cyclin-dependent kinase 6. Oncology Letters, 19, 2339–2345. https://doi.org/10.3892/ol.2020. 11346. 209. Zhou, Y. X., et al. (2018). Long non-coding RNA NIFK-AS1 inhibits M2 polarization of macrophages in endometrial cancer through targeting miR-146a. International Journal of Biochemistry & Cell Biology, 104, 25–33. https://doi.org/10.1016/j.biocel.2018.08.017. 210. Li, J., Xu, X., Wei, C., Liu, L., & Wang, T. (2020). Long noncoding RNA NORAD regulates lung cancer cell proliferation, apoptosis, migration, and invasion by the miR-30a-5p/ADAM19 axis. International Journal of Clinical and Experimental Pathology, 13, 1–13. 211. Zhou, K., et al. (2019). High long non-coding RNA NORAD expression predicts poor prognosis and promotes breast cancer progression by regulating TGF-beta pathway. Cancer Cell International, 19, 63. https://doi.org/10.1186/s12935-019-0781-6. 212. Kawasaki, N., et al. (2018). Long noncoding RNA NORAD regulates transforming growth factor-beta signaling and epithelial-to-mesenchymal transition-like phenotype. Cancer Science, 109, 2211–2220. https://doi.org/10.1111/cas.13626. 213. Yang, X., et al. (2019). The long noncoding RNA NORAD enhances the TGF-beta pathway to promote hepatocellular carcinoma progression by targeting miR-202-5p. Journal of Cellular Physiology, 234, 12051–12060. https://doi.org/10.1002/jcp.27869. 214. Li, H., et al. (2017). Long noncoding RNA NORAD, a novel competing endogenous RNA, enhances the hypoxia-induced epithelial-mesenchymal transition to promote metastasis in pancreatic cancer. Molecular Cancer, 16, 169. https://doi.org/10.1186/s12943-017-0738-0. 215. Chen, S., Xie, C., & Hu, X. (2019). lncRNA SNHG6 functions as a ceRNA to up-regulate c-Myc expression via sponging let-7c-5p in hepatocellular carcinoma. Biochemical and Biophysical Research Communications, 519, 901–908. https://doi.org/10.1016/j.bbrc.2019. 09.091. 216. Zhang, M., Duan, W., & Sun, W. (2019). LncRNA SNHG6 promotes the migration, invasion, and epithelial-mesenchymal transition of colorectal cancer cells by miR-26a/EZH2 axis. Onco Targets Therapy, 12, 3349–3360. https://doi.org/10.2147/OTT.S197433. 217. Liang, R., et al. (2018). SNHG6 functions as a competing endogenous RNA to regulate E2F7 expression by sponging miR-26a-5p in lung adenocarcinoma. Biomedicine & Pharmacotherapy, 107, 1434–1446. https://doi.org/10.1016/j.biopha.2018.08.099. 218. Zhang, X., Zhao, X., Li, Y., Zhou, Y., & Zhang, Z. (2019). Long noncoding RNA SOX21-AS1 promotes cervical cancer progression by competitively sponging miR-7/VDAC1. Journal of Cellular Physiology, 234, 17494–17504. https://doi.org/10.1002/jcp.28371. 219. Wei, A. W., & Li, L. F. (2017). Long non-coding RNA SOX21-AS1 sponges miR-145 to promote the tumorigenesis of colorectal cancer by targeting MYO6. Biomedicine & Pharmacotherapy, 96, 953–959. https://doi.org/10.1016/j.biopha.2017.11.145. 220. Jiang, X., et al. (2020). AR-induced ZEB1-AS1 represents poor prognosis in cholangiocarcinoma and facilitates tumor stemness, proliferation and invasion through mediating miR-133b/HOXB8. Aging (Albany NY), 12, 1237–1255. https://doi.org/10.18632/aging. 102680.

References

239

221. Xia, W., & Jie, W. (2020). ZEB1-AS1/miR-133a-3p/LPAR3/EGFR axis promotes the progression of thyroid cancer by regulating PI3K/AKT/mTOR pathway. Cancer Cell International, 20, 94. https://doi.org/10.1186/s12935-020-1098-1. 222. Ni, X., et al. (2020). Long non-coding RNA ZEB1-AS1 promotes colon adenocarcinoma malignant progression via miR-455-3p/PAK2 axis. Cell Proliferation, 53, e12723. https:// doi.org/10.1111/cpr.12723. 223. Xu, X., Ma, C., Duan, Z., Du, Y., & Liu, C. (2019). lncRNA ZEB1-AS1 mediates oxidative low-density lipoprotein-Mediated endothelial cells injury by post-transcriptional stabilization of NOD2. Front Pharmacology, 10, 397. https://doi.org/10.3389/fphar.2019.00397. 224. Gao, R., et al. (2019). Long non-coding RNA ZEB1-AS1 regulates miR-200b/FSCN1 signaling and enhances migration and invasion induced by TGF-beta1 in bladder cancer cells. Journal of Experimental & Clinical Cancer Research, 38, 111. https://doi.org/10.1186/ s13046-019-1102-6. 225. Lv, S. Y., et al. (2018). The lncRNA ZEB1-AS1 sponges miR-181a-5p to promote colorectal cancer cell proliferation by regulating Wnt/beta-catenin signaling. Cell Cycle, 17, 1245–1254. https://doi.org/10.1080/15384101.2018.1471317. 226. Wang, X., et al. (2019). LncRNA SNHG6 promotes proliferation, invasion and migration in colorectal cancer cells by activating TGF-beta/Smad signaling pathway via targeting UPF1 and inducing EMT via regulation of ZEB1. International Journal of Medical Sciences, 16, 51–59. https://doi.org/10.7150/ijms.27359. 227. Qian, W., et al. (2019). lncRNA ZEB1-AS1 promotes pulmonary fibrosis through ZEB1mediated epithelial-mesenchymal transition by competitively binding miR-141-3p. Cell Death Disease, 10, 129. https://doi.org/10.1038/s41419-019-1339-1. 228. Chen, H., et al. (2018). Circ-ANAPC7 is upregulated in acute myeloid leukemia and appears to target the MiR-181 family. Cellular Physiology and Biochemistry, 47, 1998–2007. https:// doi.org/10.1159/000491468. 229. Qian, W., Huang, T., & Feng, W. (2020). Circular RNA HIPK3 promotes EMT of cervical cancer through sponging miR-338-3p to up-regulate HIF-1alpha. Cancer Management and Research, 12, 177–187. https://doi.org/10.2147/CMAR.S232235. 230. Zeng, K., et al. (2018). CircHIPK3 promotes colorectal cancer growth and metastasis by sponging miR-7. Cell Death Disease, 9, 417. https://doi.org/10.1038/s41419-018-0454-8. 231. Yang, C. et al. (2018). Circular RNA circ-ITCH inhibits bladder cancer progression by sponging miR-17/miR-224 and regulating p. 21, PTEN expression. Molecular Cancer, 17, 19. doi:https://doi.org/10.1186/s12943-018-0771-7. 232. Hu, Y., & Guo, B. (2020). Circ-MTO1 correlates with favorable prognosis and inhibits cell proliferation, invasion as well as miR-17-5p expression in prostate cancer. Journal of Clinical Laboratory Analysis, 34, e23086. https://doi.org/10.1002/jcla.23086. 233. Wang, S., et al. (2018). CircZNF609 promotes breast cancer cell growth, migration, and invasion by elevating p70S6K1 via sponging miR-145-5p. Cancer Management Research, 10, 3881–3890. https://doi.org/10.2147/CMAR.S174778. 234. He, X., et al. (2015). An Lnc RNA (GAS5)/SnoRNA-derived piRNA induces activation of TRAIL gene by site-specifically recruiting MLL/COMPASS-like complexes. Nucleic Acids Research, 43, 3712–3725. https://doi.org/10.1093/nar/gkv214. 235. Zhang, S. J., et al. (2018). Role of piwi-interacting RNA-651 in the carcinogenesis of non-small cell lung cancer. Oncology Letters, 15, 940–946. https://doi.org/10.3892/ol.2017.7406. 236. Cheng, J., et al. (2011). piRNA, the new non-coding RNA, is aberrantly expressed in human cancer cells. Clinica Chimica Acta, 412, 1621–1625. https://doi.org/10.1016/j.cca. 2011.05.015. 237. Jacobs, D. I., et al. (2016). PIWI-interacting RNAs in gliomagenesis: Evidence from postGWAS and functional analyses. Cancer Epidemiology, Biomarkers & Prevention, 25, 1073– 1080. https://doi.org/10.1158/1055-9965.EPI-16-0047. 238. Yin, J., et al. (2017). piR-823 contributes to colorectal tumorigenesis by enhancing the transcriptional activity of HSF1. Cancer Science, 108, 1746–1756. https://doi.org/10.1111/cas. 13300.

240

8 Regulation of Non-coding RNAs in Cardiometabolic Tissues and Tumors

239. Li, B., et al. (2019). piRNA-823 delivered by multiple myeloma-derived extracellular vesicles promoted tumorigenesis through re-educating endothelial cells in the tumor environment. Oncogene, 38, 5227–5238. https://doi.org/10.1038/s41388-019-0788-4. 240. Yan, H., et al. (2015). piRNA-823 contributes to tumorigenesis by regulating de novo DNA methylation and angiogenesis in multiple myeloma. Leukemia, 29, 196–206. https://doi.org/ 10.1038/leu.2014.135. 241. Ma, H., et al. (2020). PIWI-interacting RNA-004800 Is regulated by S1P receptor signaling pathway to keep myeloma cell survival. Frontiers in Oncology, 10, 438. https://doi.org/10. 3389/fonc.2020.00438. 242. Han, R., et al. (2019). piRNA-DQ722010 contributes to prostate hyperplasia of the male offspring mice after the maternal exposed to microcystin-leucine arginine. Prostate, 79, 798– 812. https://doi.org/10.1002/pros.23786. 243. Jacobs, D. I., et al. (2018). piRNA-8041 is downregulated in human glioblastoma and suppresses tumor growth in vitro and in vivo. Oncotarget, 9, 37616–37626. https://doi.org/ 10.18632/oncotarget.26331. 244. Das, B., Roy, J., Jain, N., & Mallick, B. (2019). Tumor suppressive activity of PIWIinteracting RNA in human fibrosarcoma mediated through repression of RRM2. Molecular Carcinogenesis, 58, 344–357. https://doi.org/10.1002/mc.22932. 245. Roy, J., Das, B., Jain, N., & Mallick, B. (2020). PIWI-interacting RNA 39980 promotes tumor progression and reduces drug sensitivity in neuroblastoma cells. Journal of Cellular Physiology, 235, 2286–2299. https://doi.org/10.1002/jcp.29136. 246. Weng, W., et al. (2018). Novel evidence for a PIWI-interacting RNA (piRNA) as an oncogenic mediator of disease progression, and a potential prognostic biomarker in colorectal cancer. Molecular Cancer, 17, 16. https://doi.org/10.1186/s12943-018-0767-3. 247. Tan, L., et al. (2019). PIWI-interacting RNA-36712 restrains breast cancer progression and chemoresistance by interaction with SEPW1 pseudogene SEPW1P RNA. Molecular Cancer, 18, 9. https://doi.org/10.1186/s12943-019-0940-3. 248. Wang, C., et al. (2019). Heat shock protein DNAJA1 stabilizes PIWI proteins to support regeneration and homeostasis of planarian Schmidtea mediterranea. Journal of Biological Chemistry, 294, 9873–9887. https://doi.org/10.1074/jbc.RA118.004445. 249. Shen, S., et al. (2018). PIWIL1/piRNA-DQ593109 regulates the permeability of the bloodtumor barrier via the MEG3/miR-330-5p/RUNX3 Axis. Molecular Therapy Nucleic Acids, 10, 412–425. https://doi.org/10.1016/j.omtn.2017.12.020. 250. Mai, D., et al. (2018). PIWI-interacting RNA-54265 is oncogenic and a potential therapeutic target in colorectal adenocarcinoma. Theranostics, 8, 5213–5230. https://doi.org/10.7150/ thno.28001. 251. Wu, D., et al. (2015). Effects of novel ncRNA molecules, p15-piRNAs, on the methylation of DNA and Histone H3 of the CDKN2B promoter region in U937 Cells. Journal of Cellular Biochemistry, 116, 2744–2754. https://doi.org/10.1002/jcb.25199. 252. Zhang, Y., et al. (2014). The expression of Toll-like receptor 8 and its relationship with VEGF and Bcl-2 in cervical cancer. International Journal of Medical Sciences, 11, 608–613. https:// doi.org/10.7150/ijms.8428. 253. Lu, J., et al. (2020). Cyclin D1 promotes secretion of pro-oncogenic immuno-miRNAs and piRNAs. Clinical Science (Lond), 134, 791–805. https://doi.org/10.1042/CS20191318. 254. Zhang, Y., et al. (2018). PIWIL2 suppresses Siah2-mediated degradation of HDAC3 and facilitates CK2alpha-mediated HDAC3 phosphorylation. Cell Death Disease, 9, 423. https:// doi.org/10.1038/s41419-018-0462-8. 255. Tao, Y., et al. (2020). Long non-coding RNA OIP5-AS1 promotes the growth of gastric cancer through the miR-367-3p/HMGA2 axis. Digestive and Liver Disease, 52, 773–779. https://doi. org/10.1016/j.dld.2019.11.017. 256. Liu, X., et al. (2018). PIWIL3/OIP5-AS1/miR-367-3p/CEBPA feedback loop regulates the biological behavior of glioma cells. Theranostics, 8, 1084–1105. https://doi.org/10.7150/thno. 21740.

Chapter 9

Communication Between Tumor-Adjacent Tissues and Tumors with Emphasis on Role of Inflammatory Cells

Abstract The exchange of microvesicles between cells in tumor-adjacent tissues, particularly inflammatory cells, changes non-coding RNA profiles and, thereby, tumor phenotype. Typically, microvesicles enriched in let-7, miR-9, miR-17, miR-21, miR-29, miR-150, miR-155, miR-221-222, and miR-223 contribute to tumorigenesis. In particular, miR-155 enriched in microvesicles secreted by M1 macrophages in inflamed tumor-adjacent tissue change the action of TGF-β from growth inhibition to EMT induction. MiR-155 and TGF-β also change the expression of noncoding RNAs, thereby inducing stemness, EMT, insulin-sensitized state, angiogenesis, immune escape, and escape from death. Notably, the induction of HOTAIR will attract macrophages from inflamed tumor-adjacent tissue, thereby closing a vicious circle.

9.1 Exchange of miR-Enriched Microvesicles Microvesicles facilitate the communication between several tissues and cell types within these tissues. They are involved in the development of cardiometabolic diseases [1–13]. Typically, the let-7 and miR-17/92 families, together with miR21, miR-126, miR-146, miR-155, and miR-223, are enriched in M1 macrophagederived inflammatory microvesicles [1, 14]. Besides, microvesicles secreted by immature dendritic cells (DCs) contain more miR-21, miR-34a, miR-221, and miR222. Microvesicles secreted by mature DCs contain more miR-146a and miR-155 [15]. Microvesicles secreted by M1 macrophages in tumor-adjacent tissue and enriched in miR-17 and miR-221 may convert M2 tumor-associated macrophages (TAMs) into M1 macrophages and increase anti-tumor immunity. In contrast, tumor cells may inhibit M1 polarization and promote cancer growth by selective shuttling of miR21 enriched microvesicles [16, 17]. Tumor-adjacent tissue secretes microvesicles

Illustrations by Pieterjan Ginckels, Faculty of Architecture, KU Leuven, Ghent, Belgium. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 P. Holvoet, Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer, https://doi.org/10.1007/978-3-030-68844-8_9

241

242

9 Communication Between Tumor-Adjacent Tissues and Tumors with Emphasis …

enriched in miR-29a/c that suppresses angiogenesis and metastasis [18]. Microvesicles from TAMs selectively transfer miR-221-222 and miR-223 to tumors, promoting proliferation and invasion of cancer cells [19–22]. They also deliver miR-150, upregulating VEGF, and promoting angiogenesis [23]. MiR-223 in exosomes released by macrophages decreases phosphatase and tensin homolog (PTEN) and increases phosphatidylinositol 3-kinase (PI3K)/AKT serine/threonine kinase 1 (AKT) [22, 24] (Fig. 9.1). MiR-9 secreted in exosomes from triple-negative breast cancer cells induces differentiation of fibroblasts to cancer-associated fibroblasts, increasing cell motility [25]. Cancer-associated fibroblasts may then secrete miR-21-enriched exosomes to facilitate epithelial to mesenchymal transition (EMT) and cancer cell migration and invasion of breast cancer cells [26, 27]. Exosomes secreted by melanoma and pancreatic cancer cells enriched in miR-155 convert normal fibroblasts to cancer-associated fibroblasts. MiR-155-enriched exosomes induce vascular endothelial growth factor A (VEGFA), fibroblast growth factor 2 (FGF2), metalloproteinase (MMP9), suppressor of cytokine signaling 1 (SOCS1), and the Janus kinase (JAK)-2/signal transducing and activator of transcription (STAT)-3 signaling pathway [28, 29]. Enrichment of miR-155 contributes to the metabolic reprogramming of cancer cells by inducing the reverse Warburg effect. Thereby, tumor cells onset not only aerobic glycolysis in themselves but also corrupt stroma cells to produce energy-rich metabolites, allowing cancer cells to generate ATP, increase proliferation, and reduce cell death [30–32] (Fig. 9.1). Finally, tumors may enhance oncogenesis by releasing microvesicles enriched in anti-oncogenic miRs. The release of the tumor-suppressive let-7, selectively enriched in exosomes from metastatic gastric cancer cells, protects them from apoptosis [33] (Fig. 9.1). In conclusion, cancer cells’ behavior may be determined by changes in their intracellular non-coding RNA content and non-coding RNAs selectively packed in microvesicles released by tumor-adjacent tissue and inflammatory cells.

9.2 MiR-155 as a Link Between M1 Macrophage-Mediated Inflammation in Tumor-Adjacent Tissue and Tumor Growth and Metastasis M1 macrophages mediate inflammation in cardiometabolic tissue. M1 macrophages secrete inflammatory cytokines. In particular, tumor necrosis factor (TNF)-α, interleukin (IL)-8, and interferon (IFN)-γ, together with inflammation-associated ROS and high glucose, induce the secretion of miR-155 enriched microvesicles. These microvesicles transport miR-155 to the primary tumor. There, miR-155 acts on transforming growth factor (TGF)-β, thereby shifting growth inhibition to EMT with cancer cell proliferation and metastasis. TGF-β silences miR-1, miR-26a, miR-34a,

9.2 MiR-155 as a Link Between M1 Macrophage-Mediated Inflammation …

243

Fig. 9.1 Selective packing of miRs in microvesicles. M1 macrophages in inflamed tumor-adjacent tissue secrete microvesicles enriched in the miR-17/92, miR-21, miR-34a, miR-143-145, miR146a, miR-150, miR-155, miR-221-222, and miR-223. Typically, microvesicles enriched in miR-17 and miR-221 induce the migration of M2 TAMs into the tumor and convert M2 TAMs into M1 macrophages, increasing anti-tumor immunity. However, tumor cells secrete microvesicles enriched in miR-21, which inhibit M1 macrophage polarization. Primary tumor cells secrete microvesicles enriched in miR-9 and miR-155, which convert stromal fibroblasts to cancer-associated fibroblasts. The latter secrete microvesicles enriched in miR-21, preventing M2 to M1 macrophage polarization, and inducing EMT. Cancer-associated fibroblasts release microvesicles enriched in miR-155, which cause the Warburg effect in cancer cells and reverse the Warburg effect in neighboring stromal cells. TAMs secrete microvesicles enriched in miR-150, miR-221-222, and miR-223, inducing angiogenesis, invasion, and metastasis. In contrast, miR-29-enriched microvesicles block tumor growth. MiR-223 in exosomes released by TAMs inhibits PTEN, thereby increasing PI3K/AKT signaling and insulin-sensitized state. Tumors protect themselves from apoptosis by secreting let-7enriched microvesicles. However, when the let-7-enriched microvesicles reach the tumor-adjacent tissue, they reinforce M1-macrophage mediated inflammation in the latter, closing a vicious circle

miR-133 and miR-143-145. Besides, TGF-β induces the homeobox (HOX) transcript antisense lncRNA (HOTAIR), the tumor protein p53 pathway corepressor one lncRNA (lincRNA-p21), the metastasis-associated lung adenocarcinoma transcript one lncRNA (MALAT1), and urothelial cancer-associated 1 (UCA1). By upregulating these lncRNAs, TGF-β silences additional miRs: miR-7, miR-9, miR-21, miR-30a, miR-124, miR-150, miR-181, miR-221-222, and miR-223. The expression of miR-155 may also be inhibited but restored by transfer from microvesicles. The expression profile changes of non-coding RNAs induce stemness, EMT, insulin sensitized state, angiogenesis, and reduce anti-tumor immunity and apoptosis. In particular, the increase in HOTAIR attracts macrophages to the tumor, closing a vicious circle (Fig. 9.2).

244

9 Communication Between Tumor-Adjacent Tissues and Tumors with Emphasis …

Fig. 9.2 MiR-155 links M1 macrophage-mediated inflammation in adjacent tissue and tumor growth and metastasis. High glucose, TNF-α, IL8, IFN-γ, and ROS induce the secretion of miR155 enriched microvesicles by M1 macrophages in tumor-adjacent tissue. These microvesicles transport miR-155 to the tumor. MiR-155 acts on TGF-β, thereby shifting growth inhibition to EMT with cancer cell proliferation and metastasis. TGF-β induces changes in non-coding RNA expression, which induce stemness, EMT, insulin sensitized state, angiogenesis, and reduce antitumor immunity and apoptosis. In particular, the increase in HOTAIR attracts macrophages to the tumor, closing a vicious circle

References 1. Hulsmans, M., & Holvoet, P. (2013). MicroRNA-containing microvesicles regulating inflammation in association with atherosclerotic disease. Cardiovascular Research, 100, 7–18. https:// doi.org/10.1093/cvr/cvt161. 2. Classen, L., et al. (2017). Extracellular vesicles mediate intercellular communication: Transfer of functionally active microRNAs by microvesicles into phagocytes. European Journal of Immunology, 47, 1535–1549. https://doi.org/10.1002/eji.201646595. 3. de Gonzalo-Calvo, D., Cenarro, A., Civeira, F., & Llorente-Cortes, V. (2016). microRNA expression profile in human coronary smooth muscle cell-derived microparticles is a source of biomarkers. Clin Investig Arterioscler, 28, 167–177. https://doi.org/10.1016/j.arteri.2016. 05.005. 4. Alicka, M., Major, P., Wysocki, M., & Marycz, K. (2019). Adipose-derived mesenchymal stem cells isolated from patients with type 2 diabetes show reduced “Stemness” through

References

5. 6.

7.

8.

9.

10.

11. 12.

13.

14. 15.

16.

17. 18.

19.

20. 21.

22.

245

an altered secretome profile, impaired anti-oxidative protection, and mitochondrial dynamics deterioration. Journal of Clinical Medicine, 8. https://doi.org/10.3390/jcm8060765. Tung, S. L., et al. (2018). Regulatory T cell-derived extracellular vesicles modify dendritic cell function. Scientific Reports, 8, 6065. https://doi.org/10.1038/s41598-018-24531-8. Mazzeo, A., et al. (2018). Molecular and functional characterization of circulating extracellular vesicles from diabetic patients with and without retinopathy and healthy subjects. Experimental Eye Research, 176, 69–77. https://doi.org/10.1016/j.exer.2018.07.003. De Luca, L., et al. (2016). MiRNAs and piRNAs from bone marrow mesenchymal stem cell extracellular vesicles induce cell survival and inhibit cell differentiation of cord blood hematopoietic stem cells: A new insight in transplantation. Oncotarget, 7, 6676–6692. https:// doi.org/10.18632/oncotarget.6791. Ragni, E., et al. (2019). Insights into inflammatory priming of adipose-derived mesenchymal stem cells: Validation of extracellular vesicles-embedded miRNA reference genes as a crucial step for donor selection. Cells, 8. https://doi.org/10.3390/cells8040369. Jin, Y., et al. (2018). Extracellular vesicles secreted by human adipose-derived stem cells (hASCs) improve survival rate of rats with acute liver failure by releasing lncRNA H19. EBioMedicine, 34, 231–242. https://doi.org/10.1016/j.ebiom.2018.07.015. Ma, X., et al. (2017). Long non-coding RNA HOTAIR enhances angiogenesis by induction of VEGFA expression in glioma cells and transmission to endothelial cells via glioma cell derived-extracellular vesicles. American Journal of Translational Research, 9, 5012–5021. Vienberg, S., Geiger, J., Madsen, S., & Dalgaard, L. T. (2017). MicroRNAs in metabolism. Acta Physiologica (Oxford), 219, 346–361. https://doi.org/10.1111/apha.12681. Teixeira, A. L., Dias, F., Gomes, M., Fernandes, M., & Medeiros, R. (2014). Circulating biomarkers in renal cell carcinoma: The link between microRNAs and extracellular vesicles, where are we now? Journal of Kidney Cancer and VHL, 1, 84–98. https://doi.org/10.15586/ jkcvhl.2014.19. Honegger, A., et al. (2015). Dependence of intracellular and exosomal microRNAs on viral E6/E7 oncogene expression in HPV-positive tumor cells. PLoS Pathogens, 11, e1004712. https://doi.org/10.1371/journal.ppat.1004712. Ismail, N., et al. (2013). Macrophage microvesicles induce macrophage differentiation and miR-223 transfer. Blood, 121, 984–995. https://doi.org/10.1182/blood-2011-08-374793. Montecalvo, A., et al. (2012). Mechanism of transfer of functional microRNAs between mouse dendritic cells via exosomes. Blood, 119, 756–766. https://doi.org/10.1182/blood-2011-02338004. Ren, W., et al. (2019). Extracellular vesicles secreted by hypoxia pre-challenged mesenchymal stem cells promote non-small cell lung cancer cell growth and mobility as well as macrophage M2 polarization via miR-21-5p delivery. Journal of Experimental & Clinical Cancer Research, 38, 62. https://doi.org/10.1186/s13046-019-1027-0. Fabbri, M. (2013). MicroRNAs and cancer: Towards a personalized medicine. Current Molecular Medicine, 13, 751–756. https://doi.org/10.2174/1566524011313050006. Zhang, H., et al. (2016). Cell-derived microvesicles mediate the delivery of miR-29a/c to suppress angiogenesis in gastric carcinoma. Cancer Letters, 375, 331–339. https://doi.org/10. 1016/j.canlet.2016.03.026. Solinas, G., Germano, G., Mantovani, A., & Allavena, P. (2009). Tumor-associated macrophages (TAM) as major players of the cancer-related inflammation. Journal of Leukocyte Biology, 86, 1065–1073. https://doi.org/10.1189/jlb.0609385. Jaiswal, R., et al. (2012). Microparticle-associated nucleic acids mediate trait dominance in cancer. The FASEB Journal, 26, 420–429. https://doi.org/10.1096/fj.11-186817. Zhu, Z., et al. (2017). Macrophage-derived apoptotic bodies promote the proliferation of the recipient cells via shuttling microRNA-221/222. Journal of Leukocyte Biology, 101, 1349– 1359. https://doi.org/10.1189/jlb.3A1116-483R. Yang, M., et al. (2011). Microvesicles secreted by macrophages shuttle invasion-potentiating microRNAs into breast cancer cells. Molecular Cancer, 10, 117. https://doi.org/10.1186/14764598-10-117.

246

9 Communication Between Tumor-Adjacent Tissues and Tumors with Emphasis …

23. Liu, Y., et al. (2013). Microvesicle-delivery miR-150 promotes tumorigenesis by up-regulating VEGF, and the neutralization of miR-150 attenuate tumor development. Protein & Cell, 4, 932–941. https://doi.org/10.1007/s13238-013-3092-z. 24. Zhu, X., et al. (2019). Macrophages derived exosomes deliver miR-223 to epithelial ovarian cancer cells to elicit a chemoresistant phenotype. Journal of Experimental & Clinical Cancer Research, 38, 81. https://doi.org/10.1186/s13046-019-1095-1. 25. Baroni, S., et al. (2016). Exosome-mediated delivery of miR-9 induces cancer-associated fibroblast-like properties in human breast fibroblasts. Cell Death & Disease, 7, e2312. https:// doi.org/10.1038/cddis.2016.224. 26. Nouraee, N., et al. (2013). Expression, tissue distribution and function of miR-21 in esophageal squamous cell carcinoma. PLoS ONE, 8, e73009. https://doi.org/10.1371/journal.pone.007 3009. 27. Donnarumma, E., et al. (2017). Cancer-associated fibroblasts release exosomal microRNAs that dictate an aggressive phenotype in breast cancer. Oncotarget, 8, 19592–19608. https://doi. org/10.18632/oncotarget.14752. 28. Zhou, X., et al. (2018). Melanoma cell-secreted exosomal miR-155-5p induce proangiogenic switch of cancer-associated fibroblasts via SOCS1/JAK2/STAT3 signaling pathway. Journal of Experimental & Clinical Cancer Research, 37, 242. https://doi.org/10.1186/s13046-0180911-3. 29. Pang, W., et al. (2015). Pancreatic cancer-secreted miR-155 implicates in the conversion from normal fibroblasts to cancer-associated fibroblasts. Cancer Science, 106, 1362–1369. https:// doi.org/10.1111/cas.12747. 30. Wilde, L., et al. (2017). Metabolic coupling and the Reverse Warburg effect in cancer: Implications for novel biomarker and anticancer agent development. Seminars in Oncology, 44, 198–203. https://doi.org/10.1053/j.seminoncol.2017.10.004. 31. Jiang, E., et al. (2019). Tumoral microvesicle-activated glycometabolic reprogramming in fibroblasts promotes the progression of oral squamous cell carcinoma. The FASEB Journal, 33, 5690–5703. https://doi.org/10.1096/fj.201802226R. 32. Shu, S., et al. (2018). Metabolic reprogramming of stromal fibroblasts by melanoma exosome microRNA favours a pre-metastatic microenvironment. Scientific Reports, 8, 12905. https:// doi.org/10.1038/s41598-018-31323-7. 33. Ohshima, K., et al. (2010). Let-7 microRNA family is selectively secreted into the extracellular environment via exosomes in a metastatic gastric cancer cell line. PLoS ONE, 5, e13247. https:// doi.org/10.1371/journal.pone.0013247.

Chapter 10

The Impact of Non-coding RNA Networks on Disease Comorbidity: Cardiometabolic Diseases, Inflammatory Diseases, and Cancer

Abstract Notably, a cluster of non-coding RNAs is at the cross-road between metabolic and cardiovascular diseases and the cross-road of metabolic diseases and cancer. This cluster consists of the let-7 family, miR-1, miR-7, miR-9, miR-17, miR-21, miR-26, miR-29, miR-30a, miR-34a, miR-124, miR-130, miR-133, miR143–145, miR-146a, miR-150, miR-155, miR-181 family, miR-221–222, miR-223, miR-378, miR-455, GAS5, HOTAIR, H19, lincRNA-p21, LINC-ROR, MALAT1, MEG3, MIAT, NEAT1, TUG1, UCA1, XIST, ZFAS1, ANRIL, PVT1. This cluster of non-coding RNAs are candidates for inclusion in machine learning approaches. However, their expression profiles may be affected by other inflammatory diseases like Alzheimer’s disease, asthma, arthritis, and renal failure. These comorbidities should be included in risk predicting algorithms. Changes in their expression profiles according to disease stage and behavioral and therapeutic changes should also be considered. Although the same non-coding RNAs are involved in cancer’s pathogenesis, opposite changes in their expression occur in tumors than in cardiometabolic tissues. The opposite changes in expression of miRs may be especially due to the specific action of lncRNAs and circ-RNAs in tumors. They include BLACAT1, CASC11, HNF1A-AS1, MACC1-AS1, NIFK-AS1, NORAD, SOX21-AS1, ZEB1AS1, circ-ANAPC7, circ-ITCH, and circ-MTO1. Besides, piRs with PIWI proteins may silence single-stranded RNAs, like lncRNAs, particularly in cancer cells. With many shared modifiable risk factors, cancer and cardiometabolic diseases often coexist in the same individuals. Therefore, combined risk assessments for cancer and cardiometabolic diseases should account for opposite non-coding RNA expression changes. Combined cardiovascular and hemato-oncological risk prediction may have synergistic, preventive public health benefits.

10.1 Identification of Non-coding RNAs at Cross-Road of Metabolic and Cardiovascular Diseases We did not find any single non-coding RNA with a unique role in developing metabolic and cardiovascular diseases or cancer. Every discussed non-coding RNA has several functions, and several non-coding RNAs share the same function. Illustrations by Pieterjan Ginckels, Faculty of Architecture, KU Leuven, Ghent, Belgium. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 P. Holvoet, Non-coding RNAs at the Cross-Road of Cardiometabolic Diseases and Cancer, https://doi.org/10.1007/978-3-030-68844-8_10

247

248

10 The Impact of Non-coding RNA Networks …

Notably, a cluster of non-coding RNAs is at the cross-road between metabolic and cardiovascular diseases. This cluster consists of the let-7 family, miR-1, miR-7, miR-9, miR-17, miR-21, miR-26, miR-29, miR-30a, miR-34a, miR-124, miR-130, miR-133, miR-143–145, miR-146a, miR-150, miR-155, miR-181 family, miR-221– 222, miR-223, miR-378 and miR-455, growth arrest-specific five lncRNA (GAS5), the homeobox (HOX) transcript antisense lncRNA (HOTAIR), the H19 imprinted maternally expressed transcript lncRNA (H19), the tumor protein p53 pathway corepressor 1 lncRNA (lincRNA-p21), long intergenic non-protein coding RNA, regulator of reprogramming (LINC-ROR), the metastasis-associated lung adenocarcinoma transcript one lncRNA (MALAT1), maternally expressed 3 lncRNA (MEG3), myocardial infarction associated transcript (MIAT), nuclear paraspeckle assembly transcript (NEAT1), taurine up-regulated 1 (TUG1) and urothelial cancer associated 1 (UCA1), X inactive specific transcript (XIST), ZNFX1 antisense RNA 1 (ZFAS1), and circ-RNAs cyclin dependent kinase inhibitor 2B antisense RNA 1 (ANRIL) and PVT1 oncogene (PVT1) link metabolic to cardiovascular diseases. Changes in their expression profiles decrease the number of stem/precursor cells, hamper differentiation to full active cells. These changes impair insulin signaling, glucose uptake, glucose, and fatty acid metabolism. They cause a shift from oxidative phosphorylation (OXPHOS) to glycolysis. They stimulate lipid deposition and increase inflammation, mainly mediated by M1 macrophages, Th1 and Th17 cells, and oxidative stress, ultimately leading to cell death. They may induce angiogenesis restoring O2 supply, but also causing infiltration of the inflammatory cells discussed above.

10.2 Many Non-coding RNAs at Cross-Road of Metabolic and Cardiovascular Diseases are also Related to Inflammatory Diseases Because the pathogenesis of cardiometabolic diseases largely depends on inflammation is not a surprise that the same non-coding RNAs participate in their development. Alzheimer’s disease Let7-a facilitates the amyloid-β-induced autophagy and neurotoxicity [1]. High levels of let-7b are associated with neurodegeneration by activating the toll-like receptor (TLR)-7 in Alzheimer’s disease (AD) [2]. MiR-7 overexpressed in the brains of dietinduced obese mice and AD patients impairs insulin signaling, increases the levels of extracellular amyloid-β (Aβ) [3]. Overexpression of ciRs-7, silencing miR-7, reduces Aβ and beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) levels in a nuclear factor-κB (NFκB)-dependent manner [4]. High miR-9-5p reduced Aβ plaque formation in mice. MiR-9 inhibited NOTCH and glycogen synthase kinase-3 beta (GSK-3β) and increased the nuclear factor, erythroid 2 like 2 (Nrf2 or NFE2L2),

10.2 Many Non-coding RNAs at Cross-Road …

249

and superoxide dismutase 1 (SOD1) [5, 6]. MiR-9 also reduced Aβ42-triggered activation of calcium/calmodulin-dependent protein kinase kinase 2 and adenosine monophosphate-activated protein kinase [7]. MiR-29 overexpression down-regulated BACE1 and BCL-2 interacting mediator of cell death (BCL2-like 11 or BIM) [8]. Overexpression of MALAT1 reduced IL-6 and TNF-α levels, increased IL-10, and inhibited neuron apoptosis, possibly by sponging miR-30b and miR-125 [9–11]. Decreased miR-124 is associated with increased expression of BACE1 and caveolin 1. Besides, low miR-124 is associated with increased phosphoinositide 3-kinase (PI3K), AKT, and GSK-3β hyperphosphorylation. Also, low miR-124 is associated with impaired angiogenesis in mice [12–16]. Silencing of NEAT and XIST upregulates miR-124 and down-regulates BACE1 in mice [17, 18]. MiR-146a and miR181a were inversely related to the risk of Alzheimer’s disease in subjects with mild cognitive impairment [19]. Inhibition of the miR-143-3p reduced Aβ1-42-induced cell apoptosis by decreasing cleaved caspase-3 and cleaved caspase-9 levels [20]. Increased expression of miR-155 in the hippocampus of AD rats induces IL-1β, IL6, TNF-α, and apoptotic caspase-3 and causes a shift to inflammatory T cells [21, 22]. Increased HIF-1α and hypoxia-induced apoptosis in an AD cell model are associated with the down-regulation of miR-223, resulting in increased phosphatase and tensin homolog (PTEN), inhibiting the PI3K/Akt pathway [23]. Restoring MEG3 expression inhibited hippocampal neurons’ apoptosis, decreased Aβ expression, inhibited oxidative stress, and inflammatory injury [24]. TUG1 silencing, elevating miR-15a, increased viability, and limited apoptosis of amyloid β-25–35-treated hippocampal neurons [25]. The knockdown of UCA1 suppressed the neural stem cell differentiation to astrocytes and promoted the neural stem cell differentiation to neurons by increasing the expression of miR-1 [26]. Asthma Increased let 7a, 7b, and 7c is associated with infants’ asthma [27]. MiR-1 levels are inversely related to sputum eosinophilia, airway obstruction, and the number of hospitalizations in asthmatic patients, possibly by inhibiting IL-13-induced eosinophil binding to endothelial cells [28]. Non-immune IgE activates the signal transducer and activator of transcription 3 (STAT3), leading to the up-regulation of miR21-5p, down-regulating PTEN. Reduced PTEN results in the activation of PI3K, the mammalian target of rapamycin (mTOR), ribosomal protein S6 kinase beta1 (p70s6k), peroxisome proliferator-activated receptor- γ coactivator 1-α (PGC1α), peroxisome proliferator-activated receptor-γ (PPAR-γ) and cyclooxygenase-2 (COX2). The outcome is increased mitochondrial activity and extracellular matrix deposition [29]. MiR-21 promotes airway remodeling through the tumor growth factor (TGF)-β / SMAD signaling pathway[ [30]. MiR-29b alleviated total inflammatory cell infiltration, reversed the imbalance of T helper 1 cell (Th1)/Th2 responses, and decreased eosinophils recruitment in the airway [31]. MiR-145-5p induces the release of chemokines and inflammatory factors, the Th1/Th2 ratio, the epithelial barrier dysfunction, and suppresses epithelial repair [32, 33]. In contrast, miR-1433p may inhibit asthma airway remodeling [34]. The activation of group 2 innate lymphoid (ILC2) cells and increased inflammation is associated with an increase of

250

10 The Impact of Non-coding RNA Networks …

miR-146a that directly blocks the proliferation of ILC2 cells and reduces the number of neutrophils in bronchoalveolar lavage. Modulation of ILC2 function by miR-146a may depend on IL-33/interleukin 1 receptor-like 1 (IL1RL1 or ST2) signaling through inhibiting interleukin 1 receptor-associated kinase 1 (IRAK1) and TNF receptorassociated factor 6 (TRAF6) [35–37]. MiR-146b reinforces the inhibitory action of miR-146a on cyclo-oxygenase (COX)-2 and IL-1β [38]. MiR-155, increased by environmental tobacco smoke and small PM2.5 particles, is associated with allergeninduced airway epithelial damage and heightened oxidant stress in asthma [39, 40]. Low levels of miR-181b in patients with eosinophilic asthma are associated with inflammation. Dexamethasone reverts this by preventing IL13-induced miR-181b-5p down-regulation and suppressing IL13-induced expression of IL-1β and chemokine eotaxin-1 [41, 42]. In contrast, TGF-β1 may induce airway smooth muscle cell proliferation and airway remodeling of asthma by up-regulating miR-181a [43]. Airway overexpression of miR-221-3p exacerbates eosinophilic inflammation [44, 45]. MiR-223 suppresses insulin-like growth factor 1 receptor (IGF1R) expression and decreases the downstream phosphorylation of AKT, reducing extracellular matrix deposition in airway smooth muscle cells [46]. GAS5 promotes airway smooth muscle cell proliferation by sponging miR10a [47]. MALAT1, sponging miR-150, derepresses EIF4E expression, activates AKT signaling, and PDGF-BB-induced airway smooth muscle cell proliferation and migration [48]. NEAT1 is associated with increased exacerbation and inflammation and decreased lung function by sponging miR-124, maintaining the M2 macrophage phenotype [49, 50]. TUG1 increased in asthma patients, promotes the airway smooth muscle cell proliferation and migration, and reduces apoptosis by sponging miR-5905p [51]. PVT1 is associated with corticosteroid-insensitive asthma by increasing inflammation and airway smooth muscle cell proliferation [52]. In contrast, MEG3 protects by restoring the Treg/Th17 imbalance in asthma by sponging miR-17 [53]. LncRNA-CASC7 increases steroid response in asthma by sponging miR-21 and inhibiting PI3K signaling [54]. Arthritis MiR-9-5p suppressed chondrocytes apoptosis and promoted cartilage remodeling in mice with osteoarthritis (OA) [55]. Up-regulation of miR-34a-5p inhibited proliferation and promoted apoptosis and autophagy in OA cells [56]. GAS5 overexpression could counteract apoptosis by sponging miR-34a that may also be inhibited by miR-145–5 [57, 58]. Up-regulation of H19 in OA samples may protect chondrocytes from IL-1β-induced apoptosis by sponging miR-106a-5p but aggravate LPSinduced injury by sponging miR-130a and increase inflammation and collagen by sponging miR-124a [59–61]. High levels of MALAT1 in OA chondrocytes inhibited their viability and promoted cartilage ECM degradation in response to IL-1β by sponging miR-145 and induced inflammation and apoptosis by sponging miR-146a. Overexpression of miR-145 blocked this MALAT1 action, possibly by preventing MALAT1 from interacting with the disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS)-5 [62, 63]. MiR-145-5p repressed TNF-α-mediated

10.2 Many Non-coding RNAs at Cross-Road …

251

signaling activation and consequently cartilage degradation by silencing mitogenactivated protein kinase kinase 4 [64]. XIST promoted OA chondrocytes’ proliferation by sponging miR-211, up-regulating the C-X-C motif chemokine receptor (CXCR)-4 [65], and increased osteopontin, a cytokine, and a matrix protein involved in arthritis and chondrocyte apoptosis by sponging miR-376c-5p [66]. Low levels of NEAT1 in OA tissues were associated with increased miR-181a expression, apoptotic rate, and inflammatory cytokines [67, 68]. High levels of PVT1 in OA patients’ cartilage and IL-1β-stimulated chondrocytes contributed to their metabolic dysfunction by elevating matrix metalloproteinase (MMP)-3, MMP-9, and MMP-13, and inflammatory prostaglandin E2, IL6, IL8, and TNF-α [69], and induced apoptosis by sponging miR-488-3p [70]. Maresin 1, a macrophage-derived mediator of inflammation that prevents mitochondrial dysfunction, increased Treg cells’ number while decreasing Th17 cells by up-regulating miR-21 [71, 72]. Myostatin inhibited miR-21-5p expression, and miR21-5p mimic prevented the myostatin-induced enhancement of IL-1β and collageninduced arthritis [73]. High levels of miR-34a were associated with an increased number of Th 1 and Th17 cells, inflammatory cytokines, and bone loss in rheumatoid arthritis (RA) model [74]. The decrease of miR-21 resulted in the activation of the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway in systematic juvenile idiopathic arthritis [75]. TGFβ1-induced decrease of miR-29a, b, and c in primary chondrocytes was related to increased SMAD, NFκB, and canonical WNT signaling [76]. High levels of miR-143 and miR-145 rendered RA fibroblast-like synoviocytes susceptible to TNFα and VEGF165 stimuli by downregulating insulin-like growth factor binding protein 5 and protected against LPSinduced apoptosis and inflammation [77, 78]. Mice deficient in miR-146a developed gouty arthritis via up-regulation of IRAK1 and the NACHT, LRR, and PYD domains containing protein (NALP3) inflammasome [79]. Injection of exosomes enriched in miR-150 reduced the clinical arthritic scores in collagen-induced arthritis mice and joint destruction by inhibiting synoviocyte hyperplasia and angiogenesis [80]. High levels of miR-155 were associated with fewer M2-like-macrophages, more Th17 cells, and increased tumor necrosis factor α (TNF) in RA models [81–83]. The transcription factor PU.1 lowered TNF-α-induced proliferation and cytokine release of rheumatoid arthritis fibroblast-like synoviocytes by suppressing miR-155, thereby reducing the production of antibodies [84, 85]. Overexpression of miR-181 silenced PTEN and inhibited proliferation, and induced apoptosis of chondrocytes in OA [86]. High miR-221-3p was associated with cartilage degeneration, while miR-223-3p protected against IL-1β-induced ECM degradation in chondrocytes via the stromal cell-derived factor 1/ C-X-C motif chemokine receptor 4 signaling and prevented the accumulation of NLR family pyrin domain containing 3 (NLRP3) protein, and inhibited IL-1β [87, 88]. NOTCH signaling down-regulated miR-223 associated with increased secretion of inflammatory cytokine by RA macrophages [89]. However, NOTCH may be blocked by overexpressing miR-9 [90]. Overexpression of miR455-3p promoted TGF-β/SMAD signaling in chondrocytes and inhibited cartilage degeneration in mice by directly suppressing p21 activated kinase 2 [91].

252

10 The Impact of Non-coding RNA Networks …

Down-regulation of ciRs-7 and up-regulation of miR-7 in IL-1β-induced chondrocytes enhanced the IL-1β-induced inflammation [92]. The decrease of HOTAIR, associated with an increase in miR-17, induced the osteogenic differentiation markers RUNX family transcription factor (RUNX)-2 and collagen (COL)-1A1 [93]. Downregulation of the HOTAIRM1-1 variant in OA cartilages inhibits mesenchymal cell viability, induces apoptosis, and suppresses differentiation by up-regulating miR125b [94]. De-repressing MEG3 in fibroblast-like synoviocytes of RA patients inhibited inflammation and apoptosis by sponging miR-141, activating AKT/mTOR signaling, and sponging miR-361-5p, up-regulating forkhead box O1 (FOXO1) [95, 96]. The increase of ZFAS1 in RA patients ZFAS1 expression was associated with increased fibroblast-like synoviocyte migration, possibly by sponging miR-27a [97]. Renal failure Let-7, miR-21, miR-29, and miR-126 are implicated in renal fibrosis [98]. Hypertension- and TGF-β1-induced increase of miR-21 is associated with renal inflammation, fibrosis, and failure [99, 100]. GAS5 may retard renal fibrosis by sponging miR-21 [101]. However, exosomal miR-21 protects against apoptosis by targeting programmed cell death 4 (PDCD4)/NFκB [102]. The silencing of MEG3 is required for optimal miR-21 action [103]. The TGF-β/Smad3-interacting lncRNA lnc-TSI may revert this [104]. A miR-30c-5p agomir decreased renal ischemia/reperfusion injury by transforming M1 macrophages to M2 macrophages and decreasing inflammatory cytokines [105]. TGF- β -induced miR-145 sponges fibroblast growth factor 10 (FGF10), intensifying renal epithelial-mesenchymal transition (EMT) [106]. Overexpression of miR-146 protected against caspase3-mediated apoptosis and increased PI3K / AKT signaling [107]. High levels of pro-pyroptotic activity of miR-155 up-regulated apoptotic caspase-1 and the inflammatory cytokines IL-1β and IL18 [108, 109]. In contrast, MALAT1 inhibited hyperglycemia-induced renal cell pyroptosis by sponging miR-23c [110, 111]. However, MALAT1 may cause NFκB-mediated renal injury by sponging miR146a [112]. High levels of NEAT1 were associated with low miR-27a-3p and hypoxia-induced renal tubular epithelial apoptosis [113]. Overexpression of ANRIL increased apoptosis and promoted TLR4, NFκB phosphorylation, and downstream inflammatory factors [114]. GAS5 overexpression decreased the NLRP3-mediated inflammation, decreasing TNF-α, IL-1β and IL6, MCP-1, and ROS [115]. HOTAIR-mediated sponging of miR34a level in kidney tissues decreased TNF-α and IL-1β and reduced the apoptotic rate [116].

10.3 Differences Between Non-coding RNAs …

253

10.3 Differences Between Non-coding RNAs in Cardiometabolic Tissues and Tumors All non-coding RNAs which relate to metabolic syndrome components are involved in cancer. Although the same non-coding RNAs are involved in the pathogenesis of cancer and cardiometabolic diseases, often opposite changes in expression profile occur in tumors than in cardiometabolic tissues. These changes allow cancer cells to retain stemness and epithelial-mesenchymal transition (EMT), inducing cancer cell proliferation and migration. These changes retain insulin signaling and angiogenesis, stimulating tumor growth. Increased angiogenesis in tumors is less harmful than in cardiometabolic tissues. Indeed, tumor-specific changes in non-coding RNA profiles are associated with M2 macrophage and Treg polarization and induction of M2 myeloid suppressor cells (MDSCs), allowing the immune system to escape. All these changes decrease cell senescence and cell death. Additional decrease of miRs in tumors may be due to silencing by specific lncRNA and circ-RNAs. Typically lncRNAs bladder cancer-associated transcript one lncRNA (BLACAT1; silencing miR-17 and miR-150), cancer susceptibility 11 lncRNA (CASC11; silencing miR-150), HNF1A antisense RNA 1 (HNF1A-AS1; silencing miR-34a, but up-regulating miR-124), lncRNA MET transcriptional regulator MACC1 antisense MACC1 antisense RNA 1 (MACC1-AS1; silencing miR34a and miR-145), NIFK antisense RNA 1 (NIFK-AS1; silencing miR-146a), noncoding RNA activated by DNA damage (NORAD; silencing miR-30a), SRY-box transcription factor 21 antisense 1 (SOX21-AS1; silencing miR-7 and miR-145), zinc finger E-box-binding homeobox two antisense RNA 1 (ZEB1-AS1; silencing miR-133, miR-181, and miR-455), and anaphase-promoting complex subunit 7 circRNA (circ-ANAPC7; silencing miR-181), itchy E3 ubiquitin-protein ligase circRNA (circ-ITCH; up-regulating miR-17), mitochondrial tRNA translation optimization one circ-RNA (circ-MTO1; silencing miR-17) may be responsible for differences in miR expression level in tumors compared to cardiometabolic tissues. Besides, piRs with PIWI proteins may silence single-stranded RNAs, like lncRNAs, particularly in cancer cells. Besides, a cell’s behavior depends not only on non-coding RNAs expressed by this cell but also on non-coding RNAs enriched in microvesicles secreted by other cell types, even in other tissues their communication. The packing of mainly miRs in microvesicles may prevent degradation but also facilitate cell-specific delivery. Tumors secrete microvesicles containing non-coding RNAs, which induce healthy cells to convert to glycolysis. Inflammatory cells secrete microvesicles containing non-coding RNAs, which induce proliferation and migration of cancer cells. Finally, cancer cells may selectively shuttle anti-oncogenic non-coding RNAs to microvesicles and remove them to preserve proliferation and metastasis. Finally, we present a model proposing the link between miR-155-enriched microvesicles secreted by M1 macrophages in the tumor-adjacent tissues and tumor cells in a vicious circle, preventing silencing miR-155 in the tumor despite potentially inhibiting lncRNAs.

254

10 The Impact of Non-coding RNA Networks …

10.4 Expected Technical Developments Underlying the Use of Non-coding RNAs as Biomarkers Overall, we present a list of non-coding RNAs, which are candidates for inclusion in machine learning approaches, considering changes in their expression profiles according to disease stage and behavioral and therapeutic changes. This list of well-characterized non-coding RNAs is timely because of two recent technical developments facilitating the evaluation of vast amounts of various omics data. First, the number of applications utilizing real-time PCR is expanding rapidly. The improved accuracy of results relative to end-point PCR, multiplexing capability, and reduced time are factors contributing to qPCR’s growth. Microchips’ use will lead to even more rapid and sensitive detection of multiple targets, possibly within 20 min [117, 118]. Portable microfluidic platforms may accelerate the production of point-of-care diagnostics [119]. Second, several artificial intelligence (AI) or machine-learning methods may be applied to classify patients for several known outcomes, like obesity, type 2 diabetes, type of cardiovascular disease, or cancer type. The goal of artificial intelligence (AI) in biomedicine is to fit vast amounts of omics data and phenotypic, therapeutic, behavioral, and social data in a predicting model. Data may be derived from traditional health records and small wearable monitoring devices for electronic medical recording, such as cell phones and fitness trackers. Tasks of AI involve computer vision, time series analysis, speech recognition, and natural language processing [120]. Computer vision is used not only for image analysis in radiology and pathology [121–124] but also in genomics for identifying alternative splicing and predicting non-coding RNA – RNA and non-coding RNA—protein interactions [125, 126]. Time series analysis is useful for continuously monitoring health data, such as blood pressure and electrocardiograms measured continuously using small wearable monitoring systems [127]. Speech-recognition techniques are used to detect neurological disorders [128]. An AI-based natural language processing is used for extracting information from electronic health record data [4]. Machine learning methods may be supervised or unsupervised. A supervised learning model predicts an item’s property, called its label, target, response variable, or output, using various features known about the item, called input features, explanatory variables, or input [129]. In short, supervised learning is applied when one already knows which outcome one wants to predict. Supervised learning requires first a set of training inputs for which the desired predictions, or training labels, are known. Once training is complete, the model can be applied to new input conditions. Examples of supervised machine learning methods are the decision tree, the support vector machine (SVM), and the neural network [130]. SVM is the most widely used supervised machine learning method in the cardiovascular [131–138] and the cancer domain [139–141] because it is relatively straightforward, yet it can capture complex nonlinear relationships. However, from the start, the precision of predictive models

10.4 Expected Technical Developments Underlying …

255

obtained by supervised learning may be reduced because of improper dichotomization of the output. Further, although SVMs select the variables necessary for the model, the relation between the variables and the regression (or class separation) is not visualized [142, 143]. In contrast, unsupervised learning algorithms infer patterns from data without a dependent variable or known labels. So the system organizes the data, searching for common characteristics among them and clustering according to internal knowledge. In short, its forte lies in discovering new patterns in data. Cluster and principal component analysis are two unsupervised learning methods. Deep learning may be supervised or unsupervised [144–147]. It originates from artificial neural networks (ANN) as in the brain, is very flexible in how it allows the labels to relate to the input features: labels are functions of intermediate variables (also known as hidden variables, intermediate features, nodes, or neurons), which are in turn functions of other intermediate variables, and so on until some intermediate variables are functions of the input features. In medicine, unsupervised deep learning has been applied mainly in the imaging field [148, 149]. Whereas unsupervised learning methods allow classification, they do not map a new sample, and extensive variation in proposed models may result from outliers’ inclusion. That is why supervised learning mostly follows unsupervised learning. Further, multicollinearity, as in logistic regression [150] and overfitting, is challenging to avoid when handling omics datasets, although increasing the sample size prevents these problems [151]. Moreover, to increase data sets, it may be necessary to combine data from multiple sources, but differences in experimental methodologies can confound analyses. Previously, we already highlighted the potential bias inherent in the case–control design, patient recruitment with differences in inclusion and exclusion criteria, and the use of different reference standards in analyzing noncoding RNAs [152, 153]. However, its primary disadvantage is that the biological interpretation of models derived from machine learning approaches such as deep learning is difficult without additional functional information. Therefore, even in the era of AI, a comprehensive review of the biological functions of non-coding RNAs, which likely may be introduced in machine learning algorithms, is relevant. It may also decrease the number of confounding factors leading to overfitting in the model.

10.5 The Need for Measuring Fluctuation of Non-coding RNAs According to the disease stage, the dynamics of expression fluctuating risk factor profile, and changes in therapies will have to be considered [152]. For example, fluctuation in non-coding RNAs with variation in body mass index may be substantial because this fluctuation rather than baseline body mass index is related to coronary

256

10 The Impact of Non-coding RNA Networks …

atherosclerosis [154]. Therefore, we will have to take care to include information about disease stage-specific expression of non-coding RNAs. This information is, however, very scarce.

References 1. Gu, H., Li, L., Cui, C., Zhao, Z., & Song, G. (2017). Overexpression of let-7a increases neurotoxicity in a PC12 cell model of Alzheimer’s disease via regulating autophagy. Experimental and Therapeutic Medicine, 14, 3688–3698. https://doi.org/10.3892/etm.2017.4977. 2. Lehmann, S. M., et al. (2012). An unconventional role for miRNA: Let-7 activates Toll-like receptor 7 and causes neurodegeneration. Nature Neuroscience, 15, 827–835. https://doi.org/ 10.1038/nn.3113. 3. Fernandez-de Frutos, M. et al. (2019). MicroRNA 7 Impairs Insulin Signaling and Regulates Abeta levels through posttranscriptional regulation of the insulin receptor substrate 2, Insulin Receptor, Insulin-Degrading Enzyme, and Liver X Receptor Pathway. Molecular Cell Biology, 39. doi:https://doi.org/10.1128/MCB.00170-19. 4. Shi, Z., et al. (2017). The circular RNA ciRs-7 promotes APP and BACE1 degradation in an NF-kappaB-dependent manner. FEBS Journal, 284, 1096–1109. https://doi.org/10.1111/ febs.14045. 5. Liu, J., et al. (2020). MiR-9-5p inhibits mitochondrial damage and oxidative stress in AD cell models by targeting GSK-3beta. Bioscience, Biotechnology, and Biochemistry, 84, 2273– 2280. https://doi.org/10.1080/09168451.2020.1797469. 6. Li, S. H., et al. (2017). Osthole stimulated neural stem cells differentiation into neurons in an alzheimer’s disease cell model via upregulation of MicroRNA-9 and rescued the functional impairment of hippocampal neurons in APP/PS1 transgenic mice. Front Neurosciences, 11, 340. https://doi.org/10.3389/fnins.2017.00340. 7. Chang, F., Zhang, L. H., Xu, W. P., Jing, P., & Zhan, P. Y. (2014). microRNA-9 attenuates amyloidbeta-induced synaptotoxicity by targeting calcium/calmodulin-dependent protein kinase kinase 2. Molecular Medicine Reports, 9, 1917–1922. https://doi.org/10.3892/mmr. 2014.2013. 8. Jahangard, Y., et al. (2020). Therapeutic effects of transplanted exosomes containing miR-29b to a rat model of alzheimer’s disease. Front Neurosciences, 14, 564. https://doi.org/10.3389/ fnins.2020.00564. 9. Ma, P., et al. (2019). Long non-coding RNA MALAT1 inhibits neuron apoptosis and neuroinflammation while stimulates neurite outgrowth and its correlation with MiR-125b mediates PTGS2, CDK5 and FOXQ1 in Alzheimer’s disease. Current Alzheimer Research, 16, 596–612. https://doi.org/10.2174/1567205016666190725130134. 10. Li, L., Xu, Y., Zhao, M., & Gao, Z. (2020). Neuro-protective roles of long non-coding RNA MALAT1 in Alzheimer’s disease with the involvement of the microRNA-30b/CNR1 network and the following PI3K/AKT activation. Experimental and Molecular Pathology, 117, 104545. https://doi.org/10.1016/j.yexmp.2020.104545. 11. Zhuang, J., et al. (2020). Long non-coding RNA MALAT1 and its target microRNA-125b are potential biomarkers for Alzheimer’s disease management via interactions with FOXQ1, PTGS2 and CDK5. American Journal of Translational Research, 12, 5940–5954. 12. Kang, Q., et al. (2017). MiR-124-3p attenuates hyperphosphorylation of Tau protein-induced apoptosis via caveolin-1-PI3K/Akt/GSK3beta pathway in N2a/APP695swe cells. Oncotarget, 8, 24314–24326. https://doi.org/10.18632/oncotarget.15149. 13. Li, A. D., et al. (2019). miR-124 regulates cerebromicrovascular function in APP/PS1 transgenic mice via C1ql3. Brain Research Bulletin, 153, 214–222. https://doi.org/10.1016/j.bra inresbull.2019.09.002.

References

257

14. An, F., et al. (2017). MiR-124 acts as a target for Alzheimer’s disease by regulating BACE1. Oncotarget, 8, 114065–114071. https://doi.org/10.18632/oncotarget.23119. 15. Wang, X., et al. (2018). A novel MicroRNA-124/PTPN1 Signal pathway mediates synaptic and memory deficits in alzheimer’s disease. Biological Psychiatry, 83, 395–405. https://doi. org/10.1016/j.biopsych.2017.07.023. 16. Fang, M., et al. (2012). The miR-124 regulates the expression of BACE1/beta-secretase correlated with cell death in Alzheimer’s disease. Toxicology Letters, 209, 94–105. https://doi.org/ 10.1016/j.toxlet.2011.11.032. 17. Yue, D., et al. (2020). Silencing of long non-coding RNA XIST attenuated Alzheimer’s disease-related BACE1 alteration through miR-124. Cell Biology International, 44, 630–636. https://doi.org/10.1002/cbin.11263. 18. Zhao, M. Y., et al. (2019). The long-non-coding RNA NEAT1 is a novel target for Alzheimer’s disease progression via miR-124/BACE1 axis. Neurological Research, 41, 489–497. https:// doi.org/10.1080/01616412.2018.1548747. 19. Ansari, A., et al. (2019). miR-146a and miR-181a are involved in the progression of mild cognitive impairment to Alzheimer’s disease. Neurobiology of Aging, 82, 102–109. https:// doi.org/10.1016/j.neurobiolaging.2019.06.005. 20. Sun, C., et al. (2020). miR-143-3p inhibition promotes neuronal survival in an Alzheimer’s disease cell model by targeting neuregulin-1. Folia Neuropathologica, 58, 10–21. https://doi. org/10.5114/fn.2020.94002. 21. Liu, D., et al. (2019). Inhibition of microRNA-155 alleviates cognitive impairment in alzheimer’s disease and involvement of neuroinflammation. Current Alzheimer Research, 16, 473–482. https://doi.org/10.2174/1567205016666190503145207. 22. Song, J., & Lee, J. E. (2015). miR-155 is involved in Alzheimer’s disease by regulating T lymphocyte function. Front Aging Neuroscienes, 7, 61. https://doi.org/10.3389/fnagi.2015. 00061. 23. Wei, H., et al. (2020). Mesenchymal stem cell-derived exosomal miR-223 regulates neuronal cell apoptosis. Cell Death Disease, 11, 290. https://doi.org/10.1038/s41419-020-2490-4. 24. Yi, J., et al. (2019). Upregulation of the lncRNA MEG3 improves cognitive impairment, alleviates neuronal damage, and inhibits activation of astrocytes in hippocampus tissues in Alzheimer’s disease through inactivating the PI3K/Akt signaling pathway. Journal of Cellular Biochemistry, 120, 18053–18065. https://doi.org/10.1002/jcb.29108. 25. Li, X., Wang, S. W., Li, X. L., Yu, F. Y., & Cong, H. M. (2020). Knockdown of long non-coding RNA TUG1 depresses apoptosis of hippocampal neurons in Alzheimer’s disease by elevating microRNA-15a and repressing ROCK1 expression. Inflammation Research, 69, 897–910. https://doi.org/10.1007/s00011-020-01364-8. 26. Zheng, J., et al. (2017). Long nonding RNA UCA1 regulates neural stem cell differentiation by controlling miR-1/Hes1 expression. American Journal of Translational Research, 9, 3696– 3704. 27. Zhang, H. H., Li, C. X., & Tang, L. F. (2019). The differential expression profiles of miRNAlet 7a, 7b, and 7c in bronchoalveolar lavage fluid from infants with asthma and airway foreign bodies. Journal of Evidence-Based Integrative Medicine, 24, 2515690X18821906. doi:https:// doi.org/10.1177/2515690X18821906. 28. Korde, A., et al. (2020). An endothelial microRNA-1-regulated network controls eosinophil trafficking in asthma and chronic rhinosinusitis. The Journal of Allergy and Clinical Immunology, 145, 550–562. https://doi.org/10.1016/j.jaci.2019.10.031. 29. Fang, L. et al. (2019). IgE Downregulates PTEN through MicroRNA-21–5p and stimulates airway smooth muscle cell remodeling. Internation Journal of Molecular Sciences, 20. doi:https://doi.org/10.3390/ijms20040875. 30. Yu, Z. W., et al. (2019). Mutual regulation between miR-21 and the TGFbeta/Smad signaling pathway in human bronchial fibroblasts promotes airway remodeling. Journal of Asthma, 56, 341–349. https://doi.org/10.1080/02770903.2018.1455859. 31. Yan, J., et al. (2019). miR-29b Reverses T helper 1 cells/T helper 2 cells imbalance and alleviates airway eosinophils recruitment in OVA-induced murine asthma by targeting inducible

258

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

42.

43.

44.

45.

46.

10 The Impact of Non-coding RNA Networks … co-stimulator. International Archives of Allergy and Immunology, 180, 182–194. https://doi. org/10.1159/000501686. Xiong, T., Du, Y., Fu, Z., & Geng, G. (2019). MicroRNA-145-5p promotes asthma pathogenesis by inhibiting kinesin family member 3A expression in mouse airway epithelial cells. Journal of International Medical Research, 47, 3307–3319. https://doi.org/10.1177/030006 0518789819. Fan, L., et al. (2016). MicroRNA-145 influences the balance of Th1/Th2 via regulating RUNX3 in asthma patients. Experimental Lung Research, 42, 417–424. https://doi.org/10. 1080/01902148.2016.1256452. Cheng, W., et al. (2016). MiR-143-3p controls TGF-beta1-induced cell proliferation and extracellular matrix production in airway smooth muscle via negative regulation of the nuclear factor of activated T cells 1. Molecular Immunology, 78, 133–139. https://doi.org/10.1016/j. molimm.2016.09.004. Lyu, B., et al. (2020). MicroRNA-146a negatively regulates IL-33 in activated group 2 innate lymphoid cells by inhibiting IRAK1 and TRAF6. Genes and Immunity, 21, 37–44. https:// doi.org/10.1038/s41435-019-0084-x. Lambert, K. A., Roff, A. N., Panganiban, R. P., Douglas, S., & Ishmael, F. T. (2018). MicroRNA-146a is induced by inflammatory stimuli in airway epithelial cells and augments the anti-inflammatory effects of glucocorticoids. PLoS ONE, 13, e0205434. https://doi.org/ 10.1371/journal.pone.0205434. Han, S., Ma, C., Bao, L., Lv, L., & Huang, M. (2018). miR-146a mimics attenuate allergic airway inflammation by impacted group 2 innate lymphoid cells in an ovalbumin-induced asthma mouse model. International Archives of Allergy and Immunology, 177, 302–310. https://doi.org/10.1159/000491438. Comer, B. S., et al. (2014). MicroRNA-146a and microRNA-146b expression and antiinflammatory function in human airway smooth muscle. American Journal of Physiology. Lung Cellular and Molecular Physiology, 307, L727-734. https://doi.org/10.1152/ajplung. 00174.2014. Qiu, L., et al. (2018). miR-155 modulates cockroach allergen- and oxidative stress-induced cyclooxygenase-2 in asthma. The Journal of Immunology, 201, 916–929. https://doi.org/10. 4049/jimmunol.1701167. Liu, Q., Wang, W., & Jing, W. (2019). Indoor air pollution aggravates asthma in Chinese children and induces the changes in serum level of miR-155. International Journal of Environmental Health Reseach, 29, 22–30. https://doi.org/10.1080/09603123.2018.1506569. Huo, X., et al. (2016). Decreased epithelial and plasma miR-181b-5p expression associates with airway eosinophilic inflammation in asthma. Clinical and Experimental Allergy, 46, 1281–1290. https://doi.org/10.1111/cea.12754. Kivihall, A., et al. (2019). Reduced expression of miR-146a in human bronchial epithelial cells alters neutrophil migration. Clinical Translational Allergy, 9, 62. https://doi.org/10.1186/ s13601-019-0301-8. Lv, X., Li, Y., Gong, Q., & Jiang, Z. (2019). TGF-beta1 induces airway smooth muscle cell proliferation and remodeling in asthmatic mice by up-regulating miR-181a and suppressing PTEN. International Journal of Clinical and Experimental Pathology, 12, 173–181. Zhang, K., et al. (2018). Decreased epithelial and sputum miR-221-3p associates with airway eosinophilic inflammation and CXCL17 expression in asthma. American Journal of Physiology. Lung Cellular and Molecular Physiology, 315, L253–L264. https://doi.org/10.1152/ ajplung.00567.2017. Zhou, Y., et al. (2016). miRNA-221-3p enhances the secretion of interleukin-4 in Mast cells through the phosphatase and tensin homolog/p38/nuclear factor-kappab pathway. PLoS ONE, 11, e0148821. https://doi.org/10.1371/journal.pone.0148821. Liu, D., Pan, J., Zhao, D., & Liu, F. (2018). MicroRNA-223 inhibits deposition of the extracellular matrix by airway smooth muscle cells through targeting IGF-1R in the PI3K/Akt pathway. American Journal of Translational Research, 10, 744–752.

References

259

47. Zhang, X. Y., et al. (2018). GAS5 promotes airway smooth muscle cell proliferation in asthma via controlling miR-10a/BDNF signaling pathway. Life Sciences, 212, 93–101. https://doi.org/ 10.1016/j.lfs.2018.09.002. 48. Lin, L., et al. (2019). Upregulation of LncRNA Malat1 induced proliferation and migration of airway smooth muscle cells via miR-150-eIF4E/Akt signaling. Front Physiology, 10, 1337. https://doi.org/10.3389/fphys.2019.01337. 49. Li, X., Ye, S., & Lu, Y. (2020). Long non-coding RNA NEAT1 overexpression associates with increased exacerbation risk, severity, and inflammation, as well as decreased lung function through the interaction with microRNA-124 in asthma. Journal of Clinical Laboratory Analysis, 34, e23023. https://doi.org/10.1002/jcla.23023. 50. Veremeyko, T., Siddiqui, S., Sotnikov, I., Yung, A., & Ponomarev, E. D. (2013). IL-4/IL-13dependent and independent expression of miR-124 and its contribution to M2 phenotype of monocytic cells in normal conditions and during allergic inflammation. PLoS ONE, 8, e81774. https://doi.org/10.1371/journal.pone.0081774. 51. Lin, J., Feng, X., Zhang, J., & Tong, Z. (2019). Long non-coding RNA TUG1 promotes airway smooth muscle cells proliferation and migration via sponging miR-590-5p/FGF1 in asthma. American Journal of Translational Research, 11, 3159–3166. 52. Austin, P. J., et al. (2017). Transcriptional profiling identifies the long non-coding RNA plasmacytoma variant translocation (PVT1) as a novel regulator of the asthmatic phenotype in human airway smooth muscle. The Journal of Allergy and Clinical Immunology, 139, 780–789. https://doi.org/10.1016/j.jaci.2016.06.014. 53. Qiu, Y. Y., et al. (2019). LncRNA-MEG3 functions as a competing endogenous RNA to regulate Treg/Th17 balance in patients with asthma by targeting microRNA-17/ RORgammat. Biomedicine & Pharmacotherapy, 111, 386–394. https://doi.org/10.1016/j.biopha.2018. 12.080. 54. Liu, J. H., Li, C., Zhang, C. H., & Zhang, Z. H. (2020). LncRNA-CASC7 enhances corticosteroid sensitivity via inhibiting the PI3K/AKT signaling pathway by targeting miR-21 in severe asthma. Pulmonology, 26, 18–26. https://doi.org/10.1016/j.pulmoe.2019.07.001. 55. Chen, H., Yang, J., & Tan, Z. (2019). Upregulation of microRNA-9-5p inhibits apoptosis of chondrocytes through downregulating Tnc in mice with osteoarthritis following tibial plateau fracture. Journal of Cellular Physiology, 234, 23326–23336. https://doi.org/10.1002/ jcp.28900. 56. Tian, F., Wang, J., Zhang, Z., & Yang, J. (2020). LncRNA SNHG7/miR-34a-5p/SYVN1 axis plays a vital role in proliferation, apoptosis and autophagy in osteoarthritis. Biological Research, 53, 9. https://doi.org/10.1186/s40659-020-00275-6. 57. Ji, Q., Qiao, X., Liu, Y., Wang, D., & Yan, J. (2020). Silencing of longchain non-coding RNA GAS5 in osteoarthritic chondrocytes is mediated by targeting the miR34a/Bcl2 axis. Molecular Medicine Reports, 21, 1310–1319. https://doi.org/10.3892/mmr.2019.10900. 58. Rezaeepoor, M., et al. (2018). Semaphorin-3A as an immune modulator is suppressed by MicroRNA-145-5p. Cell Journal, 20, 113–119. https://doi.org/10.22074/cellj.2018.4842. 59. Hu, Y., Li, S., & Zou, Y. (2019). Knockdown of LncRNA H19 relieves LPS-induced damage by modulating miR-130a in osteoarthritis. Yonsei Medical Journal, 60, 381–388. https://doi. org/10.3349/ymj.2019.60.4.381. 60. Zhang, X., Liu, X., Ni, X., Feng, P., & Wang, Y. U. (2019). Long non-coding RNA H19 modulates proliferation and apoptosis in osteoarthritis via regulating miR-106a-5p. Journal of Biosciences, 44. 61. Fu, X., et al. (2020). LncRNA-H19 silencing suppresses synoviocytes proliferation and attenuates collagen-induced arthritis progression by modulating miR-124a. Rheumatology (Oxford). https://doi.org/10.1093/rheumatology/keaa395. 62. Liu, C., Ren, S., Zhao, S., & Wang, Y. (2019). LncRNA MALAT1/MiR-145 Adjusts IL-1betainduced chondrocytes viability and cartilage matrix degradation by regulating ADAMTS5 in human osteoarthritis. Yonsei Medical Journal, 60, 1081–1092. https://doi.org/10.3349/ymj. 2019.60.11.1081.

260

10 The Impact of Non-coding RNA Networks …

63. Li, H., Xie, S., Li, H., Zhang, R., & Zhang, H. (2020). LncRNA MALAT1 mediates proliferation of LPS treated-articular chondrocytes by targeting the miR-146a-PI3K/Akt/mTOR axis. Life Sciences, 254, 116801. https://doi.org/10.1016/j.lfs.2019.116801. 64. Hu, G., et al. (2017). MicroRNA-145 attenuates TNF-alpha-driven cartilage matrix degradation in osteoarthritis via direct suppression of MKK4. Cell Death Disease, 8, e3140. https:// doi.org/10.1038/cddis.2017.522. 65. Li, L., Lv, G., Wang, B., & Kuang, L. (2018). The role of lncRNA XIST/miR-211 axis in modulating the proliferation and apoptosis of osteoarthritis chondrocytes through CXCR4 and MAPK signaling. Biochemical and Biophysical Research Communications, 503, 2555–2562. https://doi.org/10.1016/j.bbrc.2018.07.015. 66. Li, L., Lv, G., Wang, B., & Kuang, L. (2020). XIST/miR-376c-5p/OPN axis modulates the influence of proinflammatory M1 macrophages on osteoarthritis chondrocyte apoptosis. Journal of Cellular Physiology, 235, 281–293. https://doi.org/10.1002/jcp.28968. 67. Wang, Z., Hao, J., & Chen, D. (2019). Long non-coding RNA nuclear enriched abundant transcript 1 (NEAT1) regulates proliferation, apoptosis, and inflammation of chondrocytes via the miR-181a/Glycerol-3-phosphate dehydrogenase 1-Like (GPD1L) axis. Medical Science Monitor, 25, 8084–8094. https://doi.org/10.12659/MSM.918416. 68. Zhu, L. M., & Yang, M. (2019). The suppression of miR-181 inhibits inflammatory responses of osteoarthritis through NF-kappaB signaling pathway. European Review for Medical and Pharmacological Sciences, 23, 5567–5574. https://doi.org/10.26355/eurrev_201907_18290. 69. Zhao, Y., Zhao, J., Guo, X., She, J., & Liu, Y. (2018). Long non-coding RNA PVT1, a molecular sponge for miR-149, contributes aberrant metabolic dysfunction and inflammation in IL-1beta-simulated osteoarthritic chondrocytes. Bioscience Reports, 38. doi:https://doi.org/ 10.1042/BSR20180576. 70. Li, Y., Li, S., Luo, Y., Liu, Y., & Yu, N. (2017). LncRNA PVT1 regulates chondrocyte apoptosis in osteoarthritis by acting as a sponge for miR-488-3p. DNA and Cell Biology, 36, 571–580. https://doi.org/10.1089/dna.2017.3678. 71. Jin, S., et al. (2018). Maresin 1 improves the Treg/Th17 imbalance in rheumatoid arthritis through miR-21. Annals of the Rheumatic Diseases, 77, 1644–1652. https://doi.org/10.1136/ annrheumdis-2018-213511. 72. Gu, J., et al. (2018). Maresin 1 attenuates mitochondrial dysfunction through the ALX/cAMP/ROS pathway in the cecal ligation and puncture mouse model and sepsis patients. Laboratory Investigation, 98, 715–733. https://doi.org/10.1038/s41374-018-0031-x. 73. Hu, S. L., et al. (2017). Myostatin promotes interleukin-1beta expression in rheumatoid arthritis synovial fibroblasts through inhibition of miR-21-5p. Front Immunology, 8, 1747. https://doi.org/10.3389/fimmu.2017.01747. 74. Dang, Q., et al. (2017). Inhibition of microRNA-34a ameliorates murine collagen-induced arthritis. Experimental and Therapeutic Medicine, 14, 1633–1639. https://doi.org/10.3892/ etm.2017.4708. 75. Li, H. W., et al. (2016). Effect of miR-19a and miR-21 on the JAK/STAT signaling pathway in the peripheral blood mononuclear cells of patients with systemic juvenile idiopathic arthritis. Experimental and Therapeutic Medicine, 11, 2531–2536. https://doi.org/10.3892/etm.2016. 3188. 76. Le, L. T., et al. (2016). The microRNA-29 family in cartilage homeostasis and osteoarthritis. Journal of Molecular Medicine (Berl), 94, 583–596. https://doi.org/10.1007/s00109-0151374-z. 77. Hong, B. K., et al. (2017). MicroRNA-143 and -145 modulate the phenotype of synovial fibroblasts in rheumatoid arthritis. Experimental & Molecular Medicine, 49, e363. https:// doi.org/10.1038/emm.2017.108. 78. Zhong, F., et al. (2018). miR-145 eliminates lipopolysaccharides-induced inflammatory injury in human fibroblast-like synoviocyte MH7A cells. Journal of Cellular Biochemistry, 119, 10059–10066. https://doi.org/10.1002/jcb.27341. 79. Zhang, Q. B., et al. (2018). Mice with miR-146a deficiency develop severe gouty arthritis via dysregulation of TRAF 6, IRAK 1 and NALP3 inflammasome. Arthritis Research and Therapy, 20, 45. https://doi.org/10.1186/s13075-018-1546-7.

References

261

80. Chen, Z., Wang, H., Xia, Y., Yan, F., & Lu, Y. (2018). Therapeutic potential of mesenchymal cell-derived miRNA-150-5p-expressing exosomes in rheumatoid arthritis mediated by the modulation of MMP14 and VEGF. The Journal of Immunology, 201, 2472–2482. https://doi. org/10.4049/jimmunol.1800304. 81. Paoletti, A., et al. (2019). Monocyte/macrophage abnormalities specific to rheumatoid arthritis are linked to miR-155 and are differentially modulated by different TNF inhibitors. The Journal of Immunology, 203, 1766–1775. https://doi.org/10.4049/jimmunol.1900386. 82. Kurowska-Stolarska, M., et al. (2011). MicroRNA-155 as a proinflammatory regulator in clinical and experimental arthritis. Proceedings of the National Academy Sciences of the United States of America, 108, 11193–11198. https://doi.org/10.1073/pnas.1019536108. 83. Wang, Y., et al. (2020). miR-155 promotes fibroblast-like synoviocyte proliferation and inflammatory cytokine secretion in rheumatoid arthritis by targeting FOXO3a. Experimental and Therapeutic Medicine, 19, 1288–1296. https://doi.org/10.3892/etm.2019.8330. 84. Xie, Z. et al. PU.1 attenuates TNFalphainduced proliferation and cytokine release of rheumatoid arthritis fibroblastlike synoviocytes by regulating miR155 activity. Molecular Medicine Reports, 17, 8349–8356. doi:https://doi.org/10.3892/mmr.2018.8920. 85. Alivernini, S. et al. (2016). MicroRNA-155 influences B-cell function through PU.1 in rheumatoid arthritis. Nature Communications, 7, 12970. doi:https://doi.org/10.1038/ncomms 12970. 86. Wu, X. F., Zhou, Z. H., & Zou, J. (2017). MicroRNA-181 inhibits proliferation and promotes apoptosis of chondrocytes in osteoarthritis by targeting PTEN. Biochemistry and Cell Biology, 95, 437–444. https://doi.org/10.1139/bcb-2016-0078. 87. Zheng, X., et al. (2017). Downregulation of miR-221-3p contributes to IL-1beta-induced cartilage degradation by directly targeting the SDF1/CXCR4 signaling pathway. Journal of Molecular Medicine (Berl), 95, 615–627. https://doi.org/10.1007/s00109-017-1516-6. 88. Haneklaus, M., et al. (2012). Cutting edge: MiR-223 and EBV miR-BART15 regulate the NLRP3 inflammasome and IL-1beta production. The Journal of Immunology, 189, 3795– 3799. https://doi.org/10.4049/jimmunol.1200312. 89. Ogando, J., et al. (2016). Notch-regulated miR-223 targets the aryl hydrocarbon receptor pathway and increases cytokine production in macrophages from rheumatoid arthritis patients. Scientific Reports, 6, 20223. https://doi.org/10.1038/srep20223. 90. Yu, H. T., Gu, C. Z., & Chen, J. Q. (2019). MiR-9 facilitates cartilage regeneration of osteoarthritis in rabbits through regulating Notch signaling pathway. European Review for Medical and Pharmacological Sciences, 23, 5051–5058. https://doi.org/10.26355/eurrev_201 906_18168. 91. Hu, S., et al. (2019). MicroRNA-455-3p promotes TGF-beta signaling and inhibits osteoarthritis development by directly targeting PAK2. Experimental & Molecular Medicine, 51, 1–13. https://doi.org/10.1038/s12276-019-0322-3. 92. Zhou, X., et al. (2019). Role of the ciRs-7/miR-7 axis in the regulation of proliferation, apoptosis and inflammation of chondrocytes induced by IL-1beta. International Immunopharmacology, 71, 233–240. https://doi.org/10.1016/j.intimp.2019.03.037. 93. Wei, B., Wei, W., Zhao, B., Guo, X., & Liu, S. (2017). Long non-coding RNA HOTAIR inhibits miR-17-5p to regulate osteogenic differentiation and proliferation in non-traumatic osteonecrosis of femoral head. PLoS ONE, 12, e0169097. https://doi.org/10.1371/journal. pone.0169097. 94. Xiao, Y., Yan, X., Yang, Y., & Ma, X. (2019). Downregulation of long non-coding RNA HOTAIRM1 variant 1 contributes to osteoarthritis via regulating miR-125b/BMPR2 axis and activating JNK/MAPK/ERK pathway. Biomedicine & Pharmacotherapy, 109, 1569–1577. https://doi.org/10.1016/j.biopha.2018.10.181. 95. Wang, A., et al. (2019). MEG3 promotes proliferation and inhibits apoptosis in osteoarthritis chondrocytes by miR-361-5p/FOXO1 axis. BMC Medical Genomics, 12, 201. https://doi.org/ 10.1186/s12920-019-0649-6. 96. Li, G., et al. (2019). LncRNA MEG3 inhibits rheumatoid arthritis through miR-141 and inactivation of AKT/mTOR signalling pathway. Journal of Cellular and Molecular Medicine, 23, 7116–7120. https://doi.org/10.1111/jcmm.14591.

262

10 The Impact of Non-coding RNA Networks …

97. Ye, Y., Gao, X., & Yang, N. (2018). LncRNA ZFAS1 promotes cell migration and invasion of fibroblast-like synoviocytes by suppression of miR-27a in rheumatoid arthritis. Human Cell, 31, 14–21. https://doi.org/10.1007/s13577-017-0179-5. 98. Lv, W., et al. (2018). Therapeutic potential of microRNAs for the treatment of renal fibrosis and CKD. Physiological Genomics, 50, 20–34. https://doi.org/10.1152/physiolgenomics.00039. 2017. 99. Loboda, A., Sobczak, M., Jozkowicz, A., & Dulak, J. (2016). TGF-beta1/Smads and miR-21 in renal fibrosis and inflammation. Mediators of Inflammation, 2016, 8319283. https://doi. org/10.1155/2016/8319283. 100. Li, X., Wei, Y., & Wang, Z. (2018). microRNA-21 and hypertension. Hypertension Research, 41, 649–661. https://doi.org/10.1038/s41440-018-0071-z. 101. Yu, Y., et al. (2020). Long non-coding RNA-GAS5 retards renal fibrosis through repressing miR-21 activity. Experimental and Molecular Pathology, 116, 104518. https://doi.org/10. 1016/j.yexmp.2020.104518. 102. Pan, T., et al. (2019). Delayed remote ischemic preconditioning confersrenoprotection against septic acute kidney injury via exosomal miR-21. Theranostics, 9, 405–423. https://doi.org/ 10.7150/thno.29832. 103. Yang, R., et al. (2018). Inhibition of maternally expressed gene 3 attenuated lipopolysaccharide-induced apoptosis through sponging miR-21 in renal tubular epithelial cells. Journal of Cellular Biochemistry, 119, 7800–7806. https://doi.org/10.1002/jcb.27163. 104. Wang, P. et al. (2018). Long non-coding RNA lnc-TSI inhibits renal fibrogenesis by negatively regulating the TGF-beta/Smad3 pathway. Science Translational Medicine, 10. doi:https://doi. org/10.1126/scitranslmed.aat2039. 105. Zhang, C., et al. (2019). miR-30c-5p reduces renal ischemia-reperfusion involving macrophage. Medical Science Monitor, 25, 4362–4369. https://doi.org/10.12659/MSM. 914579. 106. Wu, J., et al. (2019). MicroRNA-145 promotes the epithelial-mesenchymal transition in peritoneal dialysis-associated fibrosis by suppressing fibroblast growth factor 10. Journal of Biological Chemistry, 294, 15052–15067. https://doi.org/10.1074/jbc.RA119.007404. 107. Huang, Y., et al. (2018). Regulation and mechanism of miR-146 on renal ischemia reperfusion injury. Die Pharmazie, 73, 29–34. https://doi.org/10.1691/ph.2018.7776. 108. Wu, H., et al. (2016). MiR-155 is involved in renal ischemia-reperfusion injury via direct targeting of FoxO3a and regulating renal tubular cell Pyroptosis. Cellular Physiology and Biochemistry, 40, 1692–1705. https://doi.org/10.1159/000453218. 109. Zhang, X. B., et al. (2019). Inhibition of miR-155 ameliorates acute kidney injury by apoptosis involving the regulation on TCF4/Wnt/beta-catenin pathway. Nephron, 143, 135–147. https:// doi.org/10.1159/000501038. 110. Li, X., et al. (2017). Long non-coding RNA MALAT1 regulates renal tubular epithelial pyroptosis by modulated miR-23c targeting of ELAVL1 in diabetic nephropathy. Experimental Cell Research, 350, 327–335. https://doi.org/10.1016/j.yexcr.2016.12.006. 111. Tian, H., et al. (2018). The long non-coding RNA MALAT1 is increased in renal ischemiareperfusion injury and inhibits hypoxia-induced inflammation. Renal Failure, 40, 527–533. https://doi.org/10.1080/0886022X.2018.1487863. 112. Ding, Y., et al. (2018). Mechanism of long non-coding RNA MALAT1 in lipopolysaccharideinduced acute kidney injury is mediated by the miR-146a/NF-kappaB signaling pathway. International Journal of Molecular Medicine, 41, 446–454. https://doi.org/10.3892/ijmm. 2017.3232. 113. Jiang, X., Li, D., Shen, W., Shen, X., & Liu, Y. (2019). LncRNA NEAT1 promotes hypoxiainduced renal tubular epithelial apoptosis through downregulating miR-27a-3p. Journal of Cellular Biochemistry, 120, 16273–16282. https://doi.org/10.1002/jcb.28909. 114. Zhu, Y., et al. (2020). The long non-coding RNA ANRIL promotes cell apoptosis in lipopolysaccharide-induced acute kidney injury mediated by the TLR4/Nuclear factor-kappa B pathway. Kidney Blood Pressure Research, 45, 209–221. https://doi.org/10.1159/000 505154.

References

263

115. Xie, C., Wu, W., Tang, A., Luo, N., & Tan, Y. (2019). lncRNA GAS5/miR-452-5p reduces oxidative stress and pyroptosis of high-glucose-stimulated renal tubular cells. Diabetes, Metabolic Syndrome and Obesity, 12, 2609–2617. https://doi.org/10.2147/DMSO.S228654. 116. Jiang, Z. J., Zhang, M. Y., Fan, Z. W., Sun, W. L., & Tang, Y. (2019). Influence of lncRNA HOTAIR on acute kidney injury in sepsis rats through regulating miR-34a/Bcl-2 pathway. European Review for Medical and Pharmacological Sciences, 23, 3512–3519. https://doi. org/10.26355/eurrev_201904_17717. 117. Powell, L., et al. (2018). Rapid and sensitive detection of viral nucleic acids using silicon microchips. Analyst, 143, 2596–2603. https://doi.org/10.1039/c8an00552d. 118. Cornelis, S., et al. (2018). Multiplex STR amplification sensitivity in a silicon microchip. Scientific Reports, 8, 9853. https://doi.org/10.1038/s41598-018-28229-9. 119. Wang, H., et al. (2017). A portable microfluidic platform for rapid molecular diagnostic testing of patients with myeloproliferative neoplasms. Scientific Reports, 7, 8596. https://doi.org/10. 1038/s41598-017-08674-8. 120. Magrabi, F., et al. (2019). Artificial intelligence in clinical decision support: Challenges for evaluating AI and practical implications. Yearbook of Medical Informatics, 28, 128–134. https://doi.org/10.1055/s-0039-1677903. 121. Yu, K. H., & Kohane, I. S. (2019). Framing the challenges of artificial intelligence in medicine. BMJ Quality and Safety, 28, 238–241. https://doi.org/10.1136/bmjqs-2018-008551. 122. Kanagasingam, Y., et al. (2018). Evaluation of artificial intelligence-based grading of diabetic retinopathy in primary care. JAMA Network Open, 1, e182665. https://doi.org/10.1001/jam anetworkopen.2018.2665. 123. Bera, K., Schalper, K. A., Rimm, D. L., Velcheti, V., & Madabhushi, A. (2019). Artificial intelligence in digital pathology—New tools for diagnosis and precision oncology. Nature Reviews Clinical Oncology, 16, 703–715. https://doi.org/10.1038/s41571-019-0252-y. 124. Willemink, M. J., et al. (2020). Preparing medical imaging data for machine learning. Radiology, 295, 4–15. https://doi.org/10.1148/radiol.2020192224. 125. Zou, X., Gao, X., & Chen, W. (2019). Deep learning deepens the analysis of alternative splicing. Genomics Proteomics Bioinformatics, 17, 219–221. https://doi.org/10.1016/j.gpb. 2019.05.001. 126. Han, S., et al. (2019). LncFinder: An integrated platform for long non-coding RNA identification utilizing sequence intrinsic composition, structural information and physicochemical property. Briefings in Bioinformatics, 20, 2009–2027. https://doi.org/10.1093/bib/bby065. 127. Kario, K. (2020). Management of hypertension in the digital Era: Small wearable monitoring devices for remote blood pressure monitoring. Hypertension, 76, 640–650. https://doi.org/10. 1161/HYPERTENSIONAHA.120.14742. 128. Fraser, K. C., Meltzer, J. A., & Rudzicz, F. (2016). Linguistic features identify Alzheimer’s disease in narrative speech. Journal of Alzheimer’s Disease, 49, 407–422. https://doi.org/10. 3233/JAD-150520. 129. Wainberg, M., Merico, D., Delong, A., & Frey, B. J. (2018). Deep learning in biomedicine. Nature Biotechnology, 36, 829–838. https://doi.org/10.1038/nbt.4233. 130. Xu, C., & Jackson, S. A. (2019). Machine learning and complex biological data. Genome Biology, 20, 76. https://doi.org/10.1186/s13059-019-1689-0. 131. Uddin, S., Khan, A., Hossain, M. E., & Moni, M. A. (2019). Comparing different supervised machine learning algorithms for disease prediction. BMC Medical Informatics and Decision Making, 19, 281. https://doi.org/10.1186/s12911-019-1004-8. 132. Hermans, B. J. M. et al. (2018). Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis. Europace, 20, iii113–iii119. doi:https:// doi.org/10.1093/europace/euy243. 133. Kakadiaris, I. A., et al. (2018). Machine learning outperforms ACC / AHA CVD risk calculator in MESA. Journal of the American Heart Association, 7, e009476. https://doi.org/10.1161/ JAHA.118.009476.

264

10 The Impact of Non-coding RNA Networks …

134. Nanayakkara, S., et al. (2018). Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study. PLoS Medicine, 15, e1002709. https://doi.org/10.1371/journal.pmed.1002709. 135. Hae, H., et al. (2018). Machine learning assessment of myocardial ischemia using angiography: Development and retrospective validation. PLoS Medicine, 15, e1002693. https://doi. org/10.1371/journal.pmed.1002693. 136. Angraal, S., et al. (2020). Machine learning prediction of mortality and hospitalization in heart failure with preserved ejection fraction. JACC Heart Fail, 8, 12–21. https://doi.org/10. 1016/j.jchf.2019.06.013. 137. Samad, M. D., et al. (2018). Predicting deterioration of ventricular function in patients with repaired tetralogy of fallot using machine learning. European Heart Journal Cardiovascular Imaging, 19, 730–738. https://doi.org/10.1093/ehjci/jey003. 138. Wang, X. B., Cui, N. H., Liu, X., & Ming, L. (2019). Identification of a blood-based 12-gene signature that predicts the severity of coronary artery stenosis: An integrative approach based on gene network construction, Support Vector Machine algorithm, and multicohort validation. Atherosclerosis, 291, 34–43. https://doi.org/10.1016/j.atherosclerosis.2019. 10.001. 139. Zhao, D., et al. (2019). A reliable method for colorectal cancer prediction based on feature selection and support vector machine. Medical and Biological Engineering and Computing, 57, 901–912. https://doi.org/10.1007/s11517-018-1930-0. 140. Wang, S., & Cai, Y. (1864). Identification of the functional alteration signatures across different cancer types with support vector machine and feature analysis. Biochimica et Biophysica Acta Molecular Basis Disease, 2218–2227, 2018. https://doi.org/10.1016/j.bbadis.2017.12.026. 141. Huang, S., et al. (2018). Applications of support vector machine (SVM) learning in cancer genomics. Cancer Genomics & Proteomics, 15, 41–51. https://doi.org/10.21873/cgp.20063. 142. Frizzell, J. D., et al. (2017). Prediction of 30-day all-cause readmissions in patients hospitalized for heart failure: Comparison of machine learning and other statistical approaches. JAMA Cardiology, 2, 204–209. https://doi.org/10.1001/jamacardio.2016.3956. 143. Postma, G. J., Krooshof, P. W., & Buydens, L. M. (2011). Opening the kernel of kernel partial least squares and support vector machines. Analytica Chimica Acta, 705, 123–134. https:// doi.org/10.1016/j.aca.2011.04.025. 144. Esteva, A., et al. (2019). A guide to deep learning in healthcare. Nature Medicine, 25, 24–29. https://doi.org/10.1038/s41591-018-0316-z. 145. Zhang, S., Bamakan, S. M. H., Qu, Q., & Li, S. (2019). Learning for personalized medicine: A comprehensive review from a deep learning perspective. IEEE Reviews in Biomedical Engineering, 12, 194–208. https://doi.org/10.1109/RBME.2018.2864254. 146. Kalinin, A. A., et al. (2018). Deep learning in pharmacogenomics: From gene regulation to patient stratification. Pharmacogenomics, 19, 629–650. https://doi.org/10.2217/pgs-20180008. 147. Serre, T. (2019). Deep learning: The good, the bad, and the ugly. Annual Review of Vision Science, 5, 399–426. https://doi.org/10.1146/annurev-vision-091718-014951. 148. Dalca, A. V., et al. (2019). Unsupervised deep learning for bayesian brain MRI segmentation. Medical Image Computing and Computer Assisted Intervention, 11766, 356–365. https://doi. org/10.1007/978-3-030-32248-9_40. 149. Sari, C. T., & Gunduz-Demir, C. (2019). Unsupervised feature extraction via deep learning for histopathological classification of colon tissue images. IEEE Transactions on Medical Imaging, 38, 1139–1149. https://doi.org/10.1109/TMI.2018.2879369. 150. Johnson, K. W., et al. (2018). Artificial intelligence in cardiology. Journal of the American College of Cardiology, 71, 2668–2679. https://doi.org/10.1016/j.jacc.2018.03.521. 151. Altman, N., & Krzywinski, M. (2018). The curse(s) of dimensionality. Nature Methods, 15, 399–400. https://doi.org/10.1038/s41592-018-0019-x. 152. Navickas, R., et al. (2016). Identifying circulating microRNAs as biomarkers of cardiovascular disease: A systematic review. Cardiovascular Research, 111, 322–337. https://doi.org/10. 1093/cvr/cvw174.

References

265

153. Whiting, P. F., et al. (2011). QUADAS-2: A revised tool for the quality assessment of diagnostic accuracy studies. Annals of Internal Medicine, 155, 529–536. https://doi.org/10.7326/00034819-155-8-201110180-00009. 154. Lee, D. H., et al. (2010). Differential associations of weight dynamics with coronary artery calcium versus common carotid artery intima-media thickness: The CARDIA Study. American Journal of Epidemiology, 172, 180–189. https://doi.org/10.1093/aje/kwq093.