Human iPSC-derived Disease Models for Drug Discovery (Handbook of Experimental Pharmacology, 281) 3031423488, 9783031423482

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Handbook of Experimental Pharmacology  281

Markus H. Kuehn Wei Zhu   Editors

Human iPSC-derived Disease Models for Drug Discovery

Handbook of Experimental Pharmacology Volume 281 Editor-in-Chief Martin C. Michel, Dept of Pharmacology, Johannes Gutenberg Universität, Mainz, Germany Editorial Board Members James E. Barrett, Center for Substance Abuse Research, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, USA David Centurión, Dept.. of Pharmabiology, Center for Research and Advanced Studies, Col. Granjas-Coapa, Mexico Veit Flockerzi, Institute for Experimental and Clinical Pharmacology and Toxicology, Saarland University, Homburg, Germany Pierangelo Geppetti, Headache Center, University of Florence, Florence, Italy Franz B. Hofmann, Forschergruppe 923 Carvas, Technical University, München, Germany Kathryn Elaine Meier, Dept. of Pharmaceutical Sciences, Washington State University Spokane, Spokane, USA Clive P. Page, SIPP, Kings College London, London, UK KeWei Wang, School of Pharmacy, Qingdao University, Qingdao, China

The Handbook of Experimental Pharmacology is one of the most authoritative and influential book series in pharmacology. It provides critical and comprehensive discussions of the most significant areas of pharmacological research, written by leading international authorities. Each volume in the series represents the most informative and contemporary account of its subject available, making it an unrivalled reference source. HEP is indexed in PubMed and Scopus.

Markus H. Kuehn • Wei Zhu Editors

Human iPSC-derived Disease Models for Drug Discovery

Editors Markus H. Kuehn Center for Prevention and Treatment of Visual Loss; Department of Ophthalmology and Visual Sciences University of Iowa Iowa City, IA, USA

Wei Zhu School of Pharmacy Qingdao University Qingdao, Shandong, China

ISSN 0171-2004 ISSN 1865-0325 (electronic) Handbook of Experimental Pharmacology ISBN 978-3-031-42348-2 ISBN 978-3-031-42349-9 (eBook) https://doi.org/10.1007/978-3-031-42349-9 # The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 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 Paper in this product is recyclable.

Preface

This volume is a culmination of the contributions of many distinguished scientists in the field of induced pluripotent stem (iPS) cell technology. Dr. Shinya Yamanaka, who was awarded the Nobel Prize in Physiology or Medicine in 2012 for his groundbreaking discovery of reprogramming somatic skin cells into iPS cells, had a vision to develop new therapies using this technology and to bring these cells to patients as soon as possible. Since then, the technology has revolutionized the study of human disease, given rise to regenerative medicine strategies, and provided unprecedented opportunities for pharmacologic research in laboratories all over the world. iPS cells provide an essentially unlimited supply of cell types that are difficult to obtain from patients, including neurons or cardiomyocytes, or are difficult to maintain in primary cell culture. They can be obtained from patients afflicted with a particular disease but can also be modified to generate disease models by using recently developed gene editing techniques. Together with cutting-edge technologies like 3D printing, iPS cells have enabled the creation of organoids that replicate conditions of entire diseased organs and enable previously impossible investigations to reshape our understanding of diseases and possibilities for innovative treatments. This volume provides an extensive review of the use of iPSC in pharmaceutics, cell-based modeling, and materials science. It particularly highlights advancements in disease models of the nervous system. This focus is not accidental, as the stability of the nervous system is crucial for the overall health of the human body and has been particularly difficult to model in vitro. By using iPS cells, researchers have been able to explore pathomechanisms of both the central nervous system and peripheral nervous system with remarkable precision. However, the scope of iPS cell applications extends beyond neuronal systems and encompasses fields such as cardiology and diabetes. Human iPSCs also hold the potential to address conditions where the target cell population has been lost, and such regenerative approaches offer considerable promise for currently incurable diseases, including cardiac failure or photoreceptor degeneration. Consequently, this volume also delves into pivotal quality control

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measures during the manufacturing of iPS cell-derived cellular products to emphasize the need to adhere to Good Manufacturing Practices throughout the production process. Such considerations have gained critical importance as clinical trials using iPS cells as a treatment strategy for Parkinson's disease, spinal cord injuries, or heart failure are being initiated. As editors of this volume, we extend our gratitude to the authors for their invaluable contributions. Their pioneering studies reflect the tangible impact of Dr. Yamanaka’s vision for transformative treatments to improve patients’ lives. It is our hope that this compilation not only captures the current advances in iPS cell-based applications, but also serves as a catalyst to further drive advancements in the pursuit of enhanced therapies for currently intractable disease. Iowa City, IA, USA Qingdao, PR China

Markus H. Kuehn Wei Zhu

Contents

Part I

iPSC Production for Pharmaceutical Research

Human iPS Cells for Clinical Applications and Cellular Products . . . . . Moyra Lawrence 3D Bioprinting of Induced Pluripotent Stem Cells and Disease Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shaojun Liang, Yijun Su, and Rui Yao Part II

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CNS iPSC and Organoids

iPSCs-Derived Neurons and Brain Organoids from Patients . . . . . . . . . Wanying Zhu, Lei Xu, Xinrui Li, Hao Hu, Shuning Lou, and Yan Liu Retinal Ganglion Cells in a Dish: Current Strategies and Recommended Best Practices for Effective In Vitro Modeling of Development and Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kang-Chieh Huang, Cátia Gomes, and Jason S. Meyer

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Applications of Induced Pluripotent Stem Cell-Derived Glia in Brain Disease Research and Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Zhiqi Yang, Mingyue Gong, Chuanyan Yang, Chunhai Chen, and Kuan Zhang Human-Induced Pluripotent Stem Cell-Based Model of the Blood-Brain at 10 Years: A Retrospective on Past and Current Disease Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Abraham J. Al-Ahmad Human Retinal Organoids in Therapeutic Discovery: A Review of Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Lin Cheng and Markus H. Kuehn

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Part III

Contents

iPSC-Derived Nociceptive Neurons

Using Human iPSC-Derived Peripheral Nervous System Disease Models for Drug Discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191 Yuan Gao Part IV

Non-Neuronal Specialized Cell Types

Human-Induced Pluripotent Stem Cell-Based Differentiation of Cardiomyocyte Subtypes for Drug Discovery and Cell Therapy . . . . . . . 209 Ziwei Pan and Ping Liang Cardiac Disease Modeling with Engineered Heart Tissue . . . . . . . . . . . . 235 Lin Cai, Ruxiang Wang, and Donghui Zhang iPSC-Derived Corneal Endothelial Cells . . . . . . . . . . . . . . . . . . . . . . . . . 257 Qingjun Zhou, Zongyi Li, and Haoyun Duan iPSCs-Based Therapy for Trabecular Meshwork . . . . . . . . . . . . . . . . . . 277 Wei Zhu, Xiaoyan Zhang, Shen Wu, Ningli Wang, and Markus H. Kuehn Harnessing Human Pluripotent Stem Cell-Derived Pancreatic In Vitro Models for High-Throughput Toxicity Testing and Diabetes Drug Discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 Carmen Ching, Elhadi Iich, and Adrian Kee Keong Teo

Part I iPSC Production for Pharmaceutical Research

Human iPS Cells for Clinical Applications and Cellular Products Moyra Lawrence

Contents 1 Pluripotency and Stem Cell Culture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Reprogramming: Reversing Developmental Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Reprogramming Human Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Safety of iPSCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Manufacturing Safe Therapeutics from iPSCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Transferring to GMP Grade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Freedom to Operate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 iPSC Quality Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Mutations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Gene Editing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Differentiation Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Cellular Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Retinal and Corneal Cells from iPSCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Neural Cells for Parkinson’s Disease and Spinal Cord Injury . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Heart Failure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Transfusion Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 Mesenchymal Stromal Cells and Cartilage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 Targeting Cancer Using iPSC-Derived Therapies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Human induced pluripotent stem cells (iPSCs), since their discovery in 2007, have rapidly become a starting cell type of choice for the differentiation of many M. Lawrence (✉) Centre for iPS Cell Research and Application (CiRA) and Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_643

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mature cell types. Their flexibility, amenability to gene editing and functional equivalence to embryonic stem cells ensured their subsequent adoption by many manufacturing processes for cellular products. In this chapter, we will discuss the process whereby iPSCs are generated, key quality control steps which should be considered during manufacturing, the application of good manufacturing practice to production processes and iPSC-derived cellular products which are already undergoing clinical trials. iPSCs provide a new avenue for the next generation of cellular therapeutics and by combining new differentiation protocols, quality control and reproducible manufacturing, iPSC-derived cellular products could provide treatments for many currently untreatable diseases, allowing the largescale manufacture of high-quality cell therapies. Keywords

Clinical trials · Good manufacturing practice · Induced pluripotent stem cell · Patient safety · Regulatory approval

1

Pluripotency and Stem Cell Culture

Pluripotency is the ability of cells to contribute to all three germ layers, forming any cell in the adult organism. Cells of the early mouse embryo, when injected into a host tissue, form a tumour containing cells of all three germ layers while maintaining a mass of undifferentiated cells at the centre of the tumour (Stevens 1968, 1970). These tumours are known as teratomas and their proliferative capacities were soon captured in culture as embryonic carcinoma cells (ECC) (Evans 1972). ECCs were the first pluripotent cell type to be cultured in vitro, demonstrating that the ability to self-renew and form all three germ layers could be propagated if culture conditions were sufficient. Two decades later, a second type of pluripotent stem cell known as the embryonic germ cell (EGC) was derived from primordial germ cells (Resnick et al. 1992). ECCs provided a stepping stone to the discovery of the most widely used pluripotent stem cell type: the embryonic stem cell (ESC). Firstly, because ECCs could contribute to development when aggregated with a normal early mouse embryo, it was hypothesised that the early embryo contained pluripotent cells (Mintz and Illmensee 1975). Secondly, ECCs actually provided one group with the conditions necessary to culture ESCs. Using conditioned medium from ECCs, the cells of the E3.5 mouse blastocyst were dissociated and grown as pluripotent ESCs (Martin 1981). A second group also derived ESCs from blastocysts at the same time using serum-containing medium and fibroblasts (Evans and Kaufman 1981). When injected subcutaneously, these cells could form tumours containing cells of all three germ layers and when cultured in vitro, they could either self-renew or form embryoid bodies containing cells from all three germ layers (Evans and Kaufman 1981; Martin 1981), indicating that the pluripotent state could be maintained in vitro and propagated with the correct culture conditions. ESCs were later derived from

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human embryos (Thomson et al. 1998) and held great promise for regenerative medicine because of their ability to generate any cell type in the adult body.

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Reprogramming: Reversing Developmental Time

August Weismann was one of the first to suggest that during cell division somatic cells advance to more restricted states of potency over time. Furthermore, he postulated that the parts of the body which can regenerate contain “supplementary determinants”, which gradually decrease as differentiation proceeds (Weismann 1893) implying that the regenerative capacity of adult tissues declines as the organism ages. Further cementing the idea that cells cannot go back to states of increased potency, he hypothesised that germ cells are generated directly from the pluripotent cells of the early embryo and do not pass through differentiated intermediates. This idea is known as the Weismann barrier (Weismann 1893). However, we now know that primordial germ cells are in fact specified from more differentiated cells in the post-implantation epiblast (Ginsburg et al. 1990). Thus, not only is it possible to transit to a state of increased potency, but cells of the early embryos routinely do this during normal development. The first evidence that this was also possible in vitro came from the experiments of Briggs and King (1952). Nuclei from a frog blastula were transplanted into enucleated eggs, resulting in the formation of normal embryos and tadpoles (Briggs and King 1952). These experiments refuted the idea that the nucleus itself changes with differentiation and loses the ability to make all cell types (Weismann 1893). Work by John Gurdon showed that more differentiated cells could be reverted. He transplanted a tadpole intestinal epithelium cell nucleus into an enucleated egg, resulting in a developmentally normal tadpole (Gurdon 1962). Somatic cell nuclear transfer was subsequently carried out in sheep (Wilmut et al. 1997) and mouse (Wakayama et al. 1998) to generate viable individuals. The unique environment of the oocyte was not the only one capable of reprogramming somatic cells. If a pluripotent cell was fused with a somatic one, the somatic nucleus became pluripotent (Miller and Ruddle 1976). This was surprising as we would expect the somatic nucleus to cause the pluripotent one to differentiate, rather than the somatic one to revert to pluripotency. Mouse teratocarcinoma cells (Miller and Ruddle 1976), embryonic germ cells (Tada et al. 1997), and embryonic stem cells (Matveeva et al. 1998) were all capable of reprogramming somatic cell nuclei to pluripotency. This work was subsequently extended to human cells when fibroblasts were shown to revert to pluripotency when fused with human embryonic stem cells (Cowan et al. 2005). It still remained unclear, however, which components of the pluripotent cell’s or oocyte’s cytoplasmic milieu were responsible for the ability to reset differentiated cells to pluripotency. A breakthrough occurred in 2006 when a Japanese group, starting from an initial pool of 24 pluripotency-associated factors, identified four factors (Oct4, Klf4, Sox2, and c-Myc) whose overexpression could revert differentiated cells to a pluripotent state (Takahashi and Yamanaka 2006). By

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using a system whereby pluripotent cells became resistant to neomycin, the group could select for cells which had been faithfully transported back to pluripotency, or “reprogrammed”. These reprogrammed cells were known as induced pluripotent stem cells (iPSCs). iPSCs could contribute to all three germ layers and the germline of chimeras, demonstrating that full epigenetic resetting had occurred (Maherali et al. 2007; Okita et al. 2007; Wernig et al. 2007).

2.1

Reprogramming Human Cells

It was very soon shown that this reprogramming protocol could be extended to human cells (Takahashi et al. 2007). Human fibroblasts and synoviocytes could be reprogrammed into iPSCs using the human counterparts of the factors promoting reprogramming in mouse cells (Takahashi et al. 2007). These human iPSCs could form teratomas consisting of all three germ layers when injected into immunodeficient mice, showing that they had similar functional plasticity to mouse iPSCs (Takahashi et al. 2007). Because of their somatic tissue origin, iPSCs bypassed ethical concerns about human embryonic stem cells, which had previously proved a stumbling block to research in many countries, impeding the progress of these therapeutics towards the clinic (Lo and Parham 2009). The adult cells used to generate iPSCs could be taken from a skin biopsy, allaying any fears about the use of human embryos. Crucially, from the discovery of human iPSCs onwards, research demonstrated that induced pluripotent stem cells (iPSCs) showed the same functional plasticity as human embryonic stem cells, allowing differentiation protocols developed for ESCs to be adapted to iPSCs (Hirami et al. 2009; Nakamura et al. 2014; Takahashi et al. 2007; Takayama et al. 2008). Thanks to a combination of these factors, iPSCs were rapidly adopted as a starting material for many emerging cellular products (Sullivan et al. 2020).

2.2

Safety of iPSCs

Early work on mouse iPSCs focused on making iPSCs which more faithfully mirrored ESCs and which could contribute to the germline (Maherali et al. 2007; Okita et al. 2007). By changing the selectable marker and introducing the reprogramming factors using safer methods many groups succeeded in making iPSCs which had a more ESC-like epigenetic state and less risk of tumorigenesis (Meissner et al. 2007; Nakagawa et al. 2008; Okita et al. 2007, 2008; Wernig et al. 2007). However, these studies also uncovered a key issue which would slow the progress of iPSC-derived cellular products towards the clinic. Some of the chimeric offspring which had been generated by injecting iPSCs into blastocysts developed tumours as iPSC-derived cells reactivated their c-myc transgenes and began tumorigenesis (Okita et al. 2007). This showed that despite having faithfully undergone differentiation in vivo, iPSCs with incompletely silenced c-myc were capable of either retaining or reactivating tumorigenicity, posing a critical risk to

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recipients of iPSC-derived cells. As differentiation in vivo should generate cells at later stages of maturity than in vitro differentiation, there remains the possibility that iPSCs could resist differentiation and persist in cellular products differentiated in vitro in quantities sufficient to initiate cancer. Unfortunately, it is likely that Myc reactivation occurs in human iPSCs in a similar manner to that in mouse iPSCs. For example, during the adaptation of a hESC protocol for megakaryocyte differentiation to iPSCs, it was found that iPSCs which reactivated MYC expression formed megakaryocytes more efficiently (Takayama et al. 2010). MYC expression increased the proliferation of the megakaryocyte progenitors generated during the differentiation, thus producing more mature megakaryocytes. Therefore, the culture selected for cells which had not inactivated Myc. In conclusion, despite their promise for regenerative medicine and drug testing, iPSCs pose a risk of tumorigenesis which needs to be mitigated during the differentiation of cellular products. In harnessing the power of iPSCs for clinical applications, we should bear in mind that patient safety must be paramount in any clinical intervention and quality control is of the utmost importance as iPSC-derived cellular products approach the clinic.

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Manufacturing Safe Therapeutics from iPSCs

In designing therapeutics from stem cells for the treatment of human disease, it is crucial that we keep three important criteria in mind. First, cellular therapeutics must be of the highest available quality and safe for every patient. Second, therapies must be effective and efficiently treat the disease they are designed to treat. Third, therapeutics should be consistent from batch to batch and have traceability for all components and processes involved in their manufacture. To ensure that these three ideals are met, cellular products are manufactured within the framework of good manufacturing ractice (GMP). Each country or region designates its own GMP guidelines and the authority responsible for inspections and certification. In the European Union and the UK, products manufactured according to GMP must be of consistently high quality, be appropriate for their intended use, and meet the requirements of the marketing authorisation or product specification (“Commission Directive 2003/94/EC of 8 October 2003 laying down the principles and guidelines of good manufacturing practice in respect of medicinal products for human use and investigational medicinal products for human use” 2003; EMA Publication: Good Manufacturing Practice 2022). In the USA, the Food and Drug Administration is responsible for GMP inspection and certification, and in the European Union, it is the responsibility of the European Medicines Agency (“Commission Delegated Regulation (EU) No 1252/2014 of 28 May 2014 supplementing Directive 2001/ 83/EC of the European Parliament and of the Council with regard to principles and guidelines of good manufacturing practice for active substances for medicinal products for human use” 2014; Rehakova et al. 2020). Marketing authorisation which is granted in one country of the European Union should apply to other

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member states; however, states have the right to withdraw marketing authorisation to protect public health, if necessary (“Directive 2001/83/EC of the European Parliament and of the Council of 6 November 2001 on the Community code relating to medicinal products for human use (as amended)” 2001). In the UK, the Medicines and Healthcare Products Regulatory Agency is responsible for inspections to ensure compliance with GMP requirements (Cell and Gene Therapy Catapult Guidance on the development and marketing of ATMPs in the UK and EU at this position post – BREXIT 2022; Medicines and Healthcare Products Regulatory Authority Publication: Good manufacturing practice and good distribution practice 2020). Manufacturers which pass inspections by these agencies are granted marketing authorisation for their products (“Directive 2001/83/EC of the European Parliament and of the Council of 6 November 2001 on the Community code relating to medicinal products for human use (as amended)” 2001; Medicines and Healthcare Products Regulatory Authority Publication: Good manufacturing practice and good distribution practice 2020). From the very beginning of the manufacturing process, GMP applies to cellular products derived from iPSCs (“European Medicines Agency Guideline on quality, non-clinical and clinical requirements for investigational advanced therapy medicinal products in clinical trials” 2019). In Europe, the somatic cells used as a starting material for reprogramming to iPSCs must be harvested in compliance with the EU Tissues and Cells Directive (“Commission Directive 2006/17/EC of 8 February 2006 implementing Directive 2004/23/EC of the European Parliament and of the Council as regards certain technical requirements for the donation, procurement and testing of human tissues and cells” 2006; “Directive 2004/23/EC of the European Parliament and of the Council of 31 March 2004 on setting standards of quality and safety for the donation, procurement, testing, processing, preservation, storage and distribution of human tissues and cells” 2004) or the EU Blood Directive (“Directive 2002/98/EC of the European Parliament and of the Council of 27 January 2003 setting standards of quality and safety for the collection, testing, processing, storage and distribution of human blood and blood components and amending Directive 2001/83/EC” 2002), depending on the cell type used. Safety checks must be performed on the starting material and reprogrammed cells to ensure they are free of pathogens such as viral and transmissible spongiform encephalopathy (“Guidelines on Good Manufacturing Practice specific to Advanced Therapy Medicinal Products” 2017; “Note for guidance on minimising the risk of transmitting animal spongiform encephalopathy agents via human and veterinary medicinal products (EMA/410/01 rev.3)” 2011). Once clinical grade iPSCs have been generated, their physical, chemical, and biological properties should be subject to quality control. Recent work by the Global Alliance for iPSC Therapies (GAiT) adapted the International Stem Cell Banking Initiative’s guidance for human embryonic stem cells to iPSCs (Sullivan et al. 2018, 2020). GAiT suggested the following seven criteria as quality control attributes: identity, microbiological sterility, absence of endotoxins, genetic fidelity and stability, viability, characterisation of markers, and potency (Sullivan et al. 2018). These guidelines also suggest suitable assays to verify each quality attribute (Sullivan et al. 2018). iPSC lines which are genetically

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modified to reduce immunogenicity or promote differentiation may require additional quality control checks (Thon et al. 2015). International organisations such as the International Stem Cell Forum (ISCF, http://www.stem-cell-forum.net/) and the International Society for Stem Cell Research (ISSCR, https://www.isscr.org/) have also produced guidelines on quality control of iPSC-derived cellular products (https://www.isscr.org/policy/guidelines-for-stem-cell-research-and-clinical-transla tion, https://stemcellforum.org/forum_initiatives.cfm). The raw materials used for manufacturing should be of the highest available quality, preferably pharmacological or pharmaceutical standard (“Directive 2001/83/ EC of the European Parliament and of the Council of 6 November 2001 on the Community code relating to medicinal products for human use (as amended)” 2001; “Guidelines on Good Manufacturing Practice specific to Advanced Therapy Medicinal Products” 2017). For reagents which are not available at pharmacological or pharmaceutical grade, additional testing routines may be incorporated into the manufacturing process (“Directive 2001/83/EC of the European Parliament and of the Council of 6 November 2001 on the Community code relating to medicinal products for human use (as amended)” 2001; “Guidelines on Good Manufacturing Practice specific to Advanced Therapy Medicinal Products” 2017). For example, biological starting materials may undergo standardised testing for biological activity. GMP principles apply from the acquisition of the cells to the certification of the final product (“Commission Delegated Regulation (EU) No 1252/2014 of 28 May 2014 supplementing Directive 2001/83/EC of the European Parliament and of the Council with regard to principles and guidelines of good manufacturing practice for active substances for medicinal products for human use” 2014; Committee for Advanced Therapies (CAT) 2019) with the stringency of GMP criteria increasing as the manufacturing process proceeds. GMP-compliant premises must separate sterile from non-sterile workflow and clean areas must be compliant with ISO 14644-1, have controlled and tested air quality, and be frequently monitored (“Guidelines on Good Manufacturing Practice specific to Advanced Therapy Medicinal Products” 2017). Systems used for manufacturing should be closed, if possible, to minimise contamination risk, and all final products must be sterility tested (“Guidelines on Good Manufacturing Practice specific to Advanced Therapy Medicinal Products” 2017). The entire manufacturing process is carried out under a quality management system (QMS), containing the certificates of analysis and documentation of the starting materials, specifications, packaging instructions, standard operating procedures for manufacturing, checklists to ensure quality controls have been performed at each stage, technical agreements, routine checks of equipment and airflow, testing reports of intermediate products, and batch testing of the final product (“Commission Directive 2003/94/EC of 8 October 2003 laying down the principles and guidelines of good manufacturing practice in respect of medicinal products for human use and investigational medicinal products for human use” 2003; “Guidelines on Good Manufacturing Practice specific to Advanced Therapy Medicinal Products” 2017). The manufacturer is responsible for setting the appropriate level of quality management throughout the process. Qualified personnel are responsible for the implementation of this system on each manufacturing site and

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must perform analyses in separate quality control laboratories (“Directive 2001/83/ EC of the European Parliament and of the Council of 6 November 2001 on the Community code relating to medicinal products for human use (as amended)” 2001). Manufacturing must be performed in an identical fashion for each batch, and if variations are introduced, the process must be revalidated (“Commission Directive 2003/94/EC of 8 October 2003 laying down the principles and guidelines of good manufacturing practice in respect of medicinal products for human use and investigational medicinal products for human use” 2003). Any deviation from standard practice during batch production must be approved by a qualified person (“Guidelines on Good Manufacturing Practice specific to Advanced Therapy Medicinal Products” 2017). The final product must have full traceability and be labelled accordingly (“Commission Directive 2003/94/EC of 8 October 2003 laying down the principles and guidelines of good manufacturing practice in respect of medicinal products for human use and investigational medicinal products for human use” 2003; “Directive 2001/83/EC of the European Parliament and of the Council of 6 November 2001 on the Community code relating to medicinal products for human use (as amended)” 2001). Once specification criteria have been met, the product can be released. Sterility and safety testing will be included in these release criteria, along with other criteria such as potency. The batch’s raw materials and manufacturing protocols are checked to ensure they correspond with standard operating procedures. Batch release is carried out by the qualified person and the details of each batch are registered. In general, three consecutive batches must be manufactured to validate the process (“Guidelines on Good Manufacturing Practice specific to Advanced Therapy Medicinal Products” 2017). Once batch release has been carried out, traceability data must be retained for 30 years after the product expiry date, or longer if specified in the marketing authorisation (“Guidelines on Good Manufacturing Practice specific to Advanced Therapy Medicinal Products” 2017). Product specification files and batch documentation must be kept for 1 year after batch expiry or 5 years after certification by a qualified person. For investigational medicinal products, documentation must be kept for 5 years after completion or formal discontinuation of the last clinical trial (“Commission Directive 2003/94/EC of 8 October 2003 laying down the principles and guidelines of good manufacturing practice in respect of medicinal products for human use and investigational medicinal products for human use” 2003; “Guidelines on Good Manufacturing Practice specific to Advanced Therapy Medicinal Products” 2017).

4

Transferring to GMP Grade

4.1

Freedom to Operate

There are many factors which influence the success of a cellular therapeutic and these need to be carefully considered along the path from bench to bedside. Freedom to operate is the ability to commercialise a product without infringing on the intellectual

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property of others. This is a crucial factor to consider before starting a manufacturing process. The process of iPS generation itself was the subject of a patent struggle between many groups with different technologies (https://www.nature.com/articles/ nbt0610-544). Interestingly, the US and UK granted patents to different parties (https://www.nature.com/articles/news.2010.43, https://bioinformant.com/historic-pat ent-challenges-to-pluripotent-stem-cells-escs-and-ipscs/). Many patents have subsequently been filed all over the world for iPSC-related cellular products and assays, and it is important to verify that new processes do not infringe on the intellectual property of any existing patents (Morita et al. 2019). Additionally, technologies used for reprogramming or differentiation may also be subject to freedom to operate restrictions. Manufacturing processes involving iPSCs can be extremely expensive, once staff costs, facility costs and reagent costs are factored in, so making sure a product can survive in the market and cover its manufacturing costs is a crucial consideration (Lawrence et al. 2021; Ten Ham et al. 2021).

4.2

iPSC Quality Control

4.2.1 Mutations Echoing early studies on the reactivation of Myc in iPSC cultures (Okita et al. 2007; Takayama et al. 2010) the safety of starting iPSC cultures remains a key concern for manufacturers. iPSCs can contain mutations that originate either in the starting cell (Rouhani et al. 2022, Gore et al. 2011) or are acquired during extended periods of culture (Gore et al. 2011; Rouhani et al. 2022). Despite the fact that long-term culture appears to select against many of these mutations (Hussein et al. 2011) some of the acquired mutations can enable increased proliferation or differentiation, potentially allowing the mutated clones to overgrow the wild-type ones (Laurent et al. 2011; Rouhani et al. 2022; Takayama et al. 2010) and posing a risk to the recipients of iPSC-derived cellular products. Therefore, adequate quality control should be performed on iPSCs just before manufacturing begins for each batch, whether this is coarse resolution karyotyping, single nucleotide polymorphism arrays (Laurent et al. 2011), or whole exome or genome sequencing for single nucleotide resolution (Rouhani et al. 2022) This data then needs to be scanned for problematic mutations using databases such as COSMIC (https://cancer.sanger.ac.uk/cosmic) (Rouhani et al. 2022). However, the possibility that as-yet unidentified mutations could pose a risk to patient safety remains a very pertinent concern (Rouhani et al. 2022). 4.2.2 Gene Editing One of iPSCs’ greatest strength as a starting product for cellular therapeutics lies in their ease of genetic manipulation (Pawlowski et al. 2017; Zou et al. 2009). This makes it straightforward to remove potentially immunogenic surface proteins such as HLA Class I (Börger et al. 2016; Feng et al. 2014; Suzuki et al. 2020) or add transcription factors to promote differentiation to a desired cell type (Evans et al. 2021; Pawlowski et al. 2017). Recently, GMP-compliant genome editing has become widely available (Basar et al. 2020). Adding transcription factors into the genome risks the possibility of undesired expression at later stages; therefore,

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transgene expression needs to be monitored throughout culture (Takayama et al. 2010). All editing methods also have off-target risks; however, updating protocols can minimise these risks. For example using Cas9 protein instead of nucleic acids (Kim et al. 2014) and using paired Cas9 nickases instead of double-stranded Cas9 nucleases (Mali et al. 2013) can reduce the off-target cuts generated by Cas9. However, all off-target sites need to be monitored, regardless of the editing technology used. This should preferably be carried by whole genome sequencing due to its high resolution and sensitivity (Basar et al. 2020). Standardised whole-genome sequencing protocols for off-target assessment often use immortalised cell lines, which do not have the same epigenetic and genomic environment as iPSCs (Tsai et al. 2015). Therefore, much care needs to be taken to validate the results in the end cell population.

To address the risks posed by iPSCs which could remain undifferentiated in cellular products, the reactivation of transgenes which could endow iPSCs with antidifferentiation effects or off-target genome editing which could generate a growth advantage, systems have been generated to eradicate all iPSC escape clones in a given recipient. One such system integrates a Caspase-9 transgene into the genome, which can be induced with a chemical, initiating apoptosis in any cells carrying the transgene (Yagyu et al. 2015). This would allow the cellular product to be cleared from the body in the case of uncontrolled proliferation. Systems like this may form a key backup to ensure the long-term safety of iPSC-derived cellular products.

4.2.3

Differentiation Capacity

Another factor meriting consideration is the variability in differentiation efficiency between iPSC lines. Some lines differentiate very well in a given differentiation protocol, whereas others underperform (Evans et al. 2021; Takayama et al. 2010). There is debate in the field as to whether cells retain a memory of the tissue from which they were derived, differentiating preferentially into this tissue in vitro (Horton et al. 2020). However, overall it is unclear what causes this variability. Generating lines with better reporters for fully reprogrammed cells, more efficient reprogramming protocols, or culture conditions which better maintain the pluripotent state may go some way towards achieving homogeneous differentiation (Khan et al. 2021; Lawrence et al. 2019; Takashima et al. 2014; Theunissen et al. 2014). In the meantime, however, this obstacle decreases the iPSC lines suitable for a given manufacturing protocol. Additionally, depending on the regulatory landscape of the county in question, certain iPSC lines will not be considered GMP grade and will thus be unsuitable for manufacturing cellular products, further decreasing the choice of iPSC lines. The high costs associated with generating a master bank of pluripotent cells (Ten Ham et al. 2021) additionally restrict the iPSC lines available for manufacturing process development.

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Cellular Products

5.1

Introduction

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Long before the advent of GMP, cellular products had a long history as successful therapeutics. James Blundell carried out the first documented human-to-human blood transfusion in 1818 (Blundell 1819), demonstrating that cells from one person could be used to treat another. However, it was not yet known what components of the blood were essential as more and more patients were successfully transfused (Waller 1826). Later, bone marrow transplantation was carried out to counteract the falling blood cell counts in patients undergoing chemotherapy (Pegg et al. 1962) and was later extended to non-malignant diseases (Hobbs et al. 1981). As tissue culture techniques and our understanding of the cellular composition of transfusion and transplantation products advanced, it became possible to expand cellular products in the lab. One of the first solid tissue cellular products to be widely used was skin. Pioneering work made it possible to culture a burns victim’s own epithelial cells from a skin biopsy, expand them in the lab, and then use them to treat large areas of damaged epithelium (Gallico et al. 1984). Interestingly, these biopsies could be expanded over 10,000-fold in 3–4 weeks; however eventually, the cultured keratinocytes stopped replicating due to senescence (Barrandon et al. 2012). In fact, many tissue stem cells, including haematopoietic stem cells, lose replicative potential with age (Vaziri et al. 1994). The limited replicative lifetime of these tissue stem cells restricted their use as the starting material for large-scale cellular therapeutics. Finite replication limited the batch size of cellular therapeutics to lower dose therapeutics or required the repeated generation and testing of small batches of cellular therapeutics from different cell samples, making quality control and scaleup a significant limiting factor. Their infinite replicative capacity is one of the key factors which makes iPSCs an attractive source of starting material for cellular therapeutics, enabling the consistent production of large batches of differentiated cells. Building on the principles of GMP, many iPSC-derived cellular products are already advancing towards the clinic and many have already begun clinical trials. Over time, this number will increase and guidelines for iPSC-derived cellular products will adapt to manage the increasing diversity of iPSC-derived therapeutics.

5.2

Retinal and Corneal Cells from iPSCs

Retinal pigment epithelial (RPE) cells are the cells supporting the overlying layer of photoreceptors in the eye. These cells are lost during age-related macular degeneration (AMD), resulting in significant vision impairment (Mandai et al. 2017). AMD treatments have been developed, but vision often worsens after treatment stops (Mandai et al. 2017). ESC differentiation to RPE cells was very well characterised to the point where clinical trials had been registered for RPE products derived from ESCs (Mehat et al. 2018; Ramsden et al. 2013). By adapting a protocol designed for

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ESCs, RPE cells could then be efficiently differentiated from iPSCs (Hirami et al. 2009). RPE cells advanced quickly through pre-clinical trials and, as a result, were the first iPSC-derived product to be transplanted into humans, in a safety trial carried out in Japan (Mandai et al. 2017). To do this, autologous iPSCs were generated from an AMD patient, to minimise the risk of immunological rejection. These iPSCs were then differentiated into RPE cells, which were transplanted as a sheet into the patient’s eye. The trial was halted after the first patient as three genomic deletions were discovered in the second patient’s cells, therefore no general conclusions about safety or efficacy could be made. However, the first patient had no tumours by 25 months and the transplanted cells were not rejected, despite the lack of immunosuppressants (Mandai et al. 2017). Furthermore, the cells expanded slightly in the 4 years following the transplantation and visual acuity remained stable without anti-VEGF treatment (https://pubmed.ncbi.nlm.nih.gov/31248784/). This clinical trial was the first demonstration of the safety of iPSC-derived cellular products in a transplantation setting, albeit with a sample size too low to deduce general safety. Trials are now due to start in the USA, using iPSC-derived RPE cells on a synthetic scaffold (Kodati 2020), and in China, using iPSC-derived RPE cells (“Safety and Efficacy of Autologous Transplantation of iPSC-RPE in the Treatment of Macular Degeneration” 2022). RPE cell suspensions differentiated from HLA homozygous iPSCs are also undergoing clinical trials in Kobe, Japan, lead by the same team which performed the first iPSC-derived RPE transplant. This will pave the way for non-autologous transplants (Kurimoto 2017), allowing the manufacture of large batches of cells and the transplantation of several patients at once. This could potentially overcome the prohibitively high costs associated with generating a personalised iPSC-derived product for each patient. Clinical trials are taking place in Kobe, Japan, for retinal sheets differentiated from allogenic iPSCs (Hirami 2020). These will be transplanted subretinally into patients suffering from retinitis pigmentosa, a disease characterised by the loss of photoreceptors. With the transplanted retinal sheets, it is hoped that the patients’ visual acuity can be rescued. Cells of the cornea, the outer protective layer of the eye, can also be differentiated from iPSCs. Four patients were transplanted with iPSC-derived corneal sheets in a clinical trial which was completed recently in Japan (Human administration of cellular products made from the iPS cell stock 2022; Yada 2022). Two of the patients did not require immunosuppression and all four had more visual acuity after transplant, indicating that this cellular therapy may be a safe and effective one and a promising candidate for further trials (Yada 2022).

5.3

Neural Cells for Parkinson’s Disease and Spinal Cord Injury

Parkinson’s disease is a neurodegenerative disease characterised by the loss of dopaminergic neurons in the substantia nigra pars compacta of the ventral mesencephalon (Parmar et al. 2020). Patients are generally treated with levodopa to restore dopamine levels; however, keeping levels constant poses a major challenge and adverse effects include psychiatric problems and hallucinations (Parmar et al. 2020).

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As Parkinson’s disease is caused by the deficiency of just one cell type, it quickly became a candidate for cell replacement therapies with early successes in dopaminergic neuron differentiation from iPSCs building on results generated using ESCs (Hargus et al. 2010; Kim et al. 2020). In a clinical trial started in 2018, researchers in Kyoto, Japan, transplanted Parkinson’s disease patients with iPSC-derived dopaminergic progenitor cells (Human administration of cellular products made from the iPS cell stock 2022; Takahashi 2020). Two separate trials of iPSC-derived neurons to treat Parkinson’s disease are currently taking place in the USA, along with one in China and one in Australia (Allife Medical Science and Technology Co. 2019; Schweitzer et al. 2020; Stoker and Barker 2020). It is hoped that these transplants may rival or surpass the transplants of human foetal material which have been already carried out and which can improve the symptoms of Parkinson’s patients (Stoker and Barker 2020). Due to their capacity for infinite expansion, iPSCs may enable us to mass-produce transplantable neurons, helping keep product costs low while providing a safe, reproducibly-manufactured cellular therapy. Spinal cord injury can be extremely debilitating, resulting in sensory, motor, and autonomic paralyses (Ago et al. 2022). Transplanted neural stem cells can bridge the incision, relaying information across the break and contributing to functional recovery (Ago et al. 2022). Participants are currently being recruited for a clinical trial of iPSC-derived neural stem or progenitor cells (Okano 2020). Patients will be transplanted with neural progenitor cells on a defined day after spinal cord injury to assess safety and efficacy (Okano 2020).

5.4

Heart Failure

Heart failure affects more than 26 million people worldwide and is characterised by defects in the myocardium, impairing ventricular filling or ejection (Pagliaro et al. 2020). Ischaemic heart disease, where the heart muscle is deprived of oxygen due to impaired blood flow, is responsible for 50% of heart failure cases in North America and Europe (Pagliaro et al. 2020). Research on the generation of heart tissue from iPSCs has advanced rapidly. Protocols have been optimised to generate cardiomyocytes from iPSCs, and these cardiomyocytes have been shown to be suitable for transplantation, integrating into animal models of ischaemia (Yokoyama et al. 2021). Efficacy in rescuing cardiac contractility has yet to be demonstrated. Suspension culture can also enable the large-scale manufacture of these iPSC-derived cardiomyocytes (Sougawa et al. 2021), however, this process is dependent on the presence of mouse embryonic fibroblasts, which may be an issue for process conversion to GMP grade. To date, several clinical trials have been registered using iPSC-derived cardiomyocytes to treat heart conditions. Three of these trials are taking place in Japan, two using iPSC-derived cardiomyocyte spheroids and the other using iPSC-generated cardiomyocyte sheets (Heartseed 2021; Human administration of cellular products made from the iPS cell stock 2022; Sawa 2021; Shimizu 2020). Two iPSC-derived cardiomyocyte trials are also taking place in China, the first injected through a catheter into the damaged region of

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the endocardium (Tao 2021) and the second injected intravenously (Xu 2018). A sixth trial is taking place in Germany transplanting engineered heart muscle, made from iPSC-derived cardiomyocytes and stromal cells in a hydrogel (Zimmermann 2020), into advanced heart failure patients. It is hoped that by combining the heart tissue with a synthetic microenvironment, its integration and function can be improved, resulting in better outcomes for recipients and repairing some of the tissue damage caused by heart failure.

5.5

Transfusion Products

Because of the infinite replicative capacity of iPSCs, they have the ability to produce very large numbers of cells for clinical interventions. Transfusion products constitute one of these iPSC-derived product types. Platelets are the small anucleate discoid cells in the bloodstream responsible for clotting and wound healing (Menter et al. 2017). Every year, hundreds of thousands of patients receive platelet units to prevent haemorrhage, including patients after trauma or surgery, those suffering from bone marrow insufficiency, or patients who have undergone cancer treatment (Estcourt et al. 2017). Each platelet unit consists of 3 × 1011 cells (Thon et al. 2015), which is several orders of magnitude higher than the cellular products above. Megakaryocytes are the large, multinucleated cells which produce platelets, and each megakaryocyte is estimated to produce up to 4,000 platelets (Kaufman et al. 1965), meaning that very large numbers of megakaryocytes are needed to produce a single platelet unit. Additionally, multiply transfused or multiparous patients can develop antibodies against antigens on the surface of platelets, making matching more challenging (Stanworth et al. 2015). Building on results from ESCs (Gaur et al. 2006; Lu et al. 2011; Pick et al. 2013; Takayama et al. 2008), many groups successfully differentiated megakaryocytes from iPSCs (Börger et al. 2016; Feng et al. 2014; Mills et al. 2014; Moreau et al. 2016; Nakamura et al. 2014). Some of these systems have been transitioned to GMP grade (Sugimoto et al. 2022b and Lawrence et al. 2021). Recently, one of these groups advanced iPSC-derived platelets into clinical trials, successfully transfusing an aplastic anaemia patient with allogenic iPSC-derived platelets in a dose escalation study (Sugimoto et al. 2021, 2022a). No adverse effects were observed up to 1 year after the last dose, paving the way for efficacy trials in the future (Sugimoto et al. 2021).

5.6

Mesenchymal Stromal Cells and Cartilage

Early studies on mouse bone marrow-derived cells revealed their ability to provide a niche for haematopoietic stem cells and granulocytes, allowing the latter to be cultured in vitro for several months (Dexter et al. 1977). Marrow fibroblasts were soon identified as the cell responsible and adopted for models studying cell–niche

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interactions and bone developmental biology (Galipeau and Sensébé 2018). The widespread use of marrow fibroblasts, by then referred to as mesenchymal stromal cells (MSCs), as a niche provider for other cells enabled the discovery that they could modulate the innate and adaptive immunity of other cells. This immune modulatory capacity enabled their early use in clinical trials to dampen the immune response to autologous blood cell transfusion (Koç et al. 2000) and ameliorate graftversus-host disease (GvHD) (Le Blanc et al. 2008). Following positive results in allogenic MSC trials, GMP-grade MSC differentiation was optimised from iPSCs and patients were intravenously transfused with iPSC-derived MSCs (Bloor et al. 2020). This trial suggested that iPSC-derived MSCs were safe and many of the patients’ GvHD decreased in severity over the course of the trial (Bloor et al. 2020). iPSC-derived MSC trials were then started for patients suffering from respiratory failure due to COVID-19 or other causes (Cynata 2020). Trials like these will ascertain whether the immunomodulatory functions of MSCs could be useful to target diverse inflammatory conditions. Cartilage damage is common in joints subject to wear and tear, such as the knee joint. Cartilaginous organoids can be efficiently differentiated from iPSCs, and these cells have been shown to be capable of hypertrophic maturation in vitro (Tam et al. 2021). Following successful transplantation into mice, trials have started testing these organoids in patients suffering from knee joint cartilage damage (Repair of articular cartilage damage by transplantation of allogeneic iPS cell-derived cartilage 2020). Future clinical trials may determine the efficacy of iPSC-derived MSC and cartilage transplants and their comparability to current standards of care.

5.7

Targeting Cancer Using iPSC-Derived Therapies

Natural killer cells are immune cells derived from haematopoietic stem cells which patrol the blood, lymphatics, and tissue for infected or transformed cells (Lanier 2008). As well as recognising cells missing Major Histocompatibility Complex Class I antigens, termed the “missing self”, NK cells can also be activated or inhibited by a diverse repertoire of receptors (Lanier 2008). This capacity has been harnessed in the generation of NK cells targeting various cancers. NK differentiation from iPSCs was optimised (Woan et al. 2021), and these cells were capable of tumour eradication in mouse models (Woan et al. 2021). These cells have recently entered clinical trials for patients suffering from diverse cancer types, including solid tumours, myeloma, leukaemia, lymphoma (Griffis 2019; Mohamed 2020; Hong et al. 2020), and ovarian cancer (Kaneko 2021). Similarly, a subset of T cells known as natural killer T (NKT) cells recognise lipid antigens presented on CD1d, initiating both innate and adaptive immune responses against cancer cells (Kitayama et al. 2016). iPSC-derived NKT cells are currently being tested in clinical trials for solid tumours in children in Japan (Motohashi 2021).

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Thus, iPSC-derived cellular therapeutics can be used not only for tissue replacement but also to eradicate cancer cells in a highly targeted manner, initiating immune recognition and tumour clearance.

6

Conclusion

Despite iPSCs’ relatively recent discovery, their infinite capacity for expansion, flexibility for differentiation, and amenability to gene editing have made them a promising starting cell type for many cell therapies. iPSC-derived cellular products are already making huge strides towards the clinic, with many products showing safety and efficacy in clinical trials. The iPSC-derived regenerative medicine field holds much promise for many currently untreatable diseases as many more wellcharacterised differentiated cell types become available year after year. In progressing towards the clinic, however, it is crucial that iPSC safety, manufacturing consistency, and traceability be key factors which alongside therapy efficacy and patient safety must take centre stage. International guidelines on iPSC safety will also play an important role in regulating safety and reproducibility as iPSC-derived therapeutics go forward. Basic research on mutational load, gene editing techniques, and the mechanisms underlying iPSC differentiation to target cell types have a decisive role to play in the advancement of safe and effective iPSC-derived therapies towards the clinic as new results are incorporated into emerging therapeutics. Working on the promising results of the clinical trials described above, iPSCs are rapidly becoming a cell of choice for therapeutics manufacturers, building on decades of research on human pluripotent stem cells, their culture and differentiation. Going forward with clear quality standards, consistent manufacturing protocols and a deep understanding of cellular biology, iPSC-derived cellular products can provide a new generation of therapeutics, paving the way for the treatment of many currently intractable diseases and providing a flexible and consistent starting cell for many developing cellular therapies. Acknowledgements I would like to thank Emma Lawrence for proofreading, editing, and regulatory advice. Thank you also to Charlotte Flahou for clinical trial information and David Cyranoski for proofreading. I am very grateful to the Japanese Society for the Promotion of Science (JSPS) for funding my research (PE21019), Prof. Takuya Yamamoto for his supervision, support, and mentorship, and all my colleagues at the Centre for iPS Cell Research and Application (CiRA) and the Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Japan.

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3D Bioprinting of Induced Pluripotent Stem Cells and Disease Modeling Shaojun Liang, Yijun Su, and Rui Yao

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Overview of 3D Printing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Bioinks for Bioprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Bioinks for iPSC Bioprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3D Bioprinting of iPSCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Inkjet Bioprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Microextrusion-Based Bioprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Stereolithography (SLA)-Based Bioprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Laser-Assisted Bioprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 iPSC-Based Bioprinting for Disease Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Bioprinting of iPSC-Derived Cells for Cardiac Disease Models . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Bioprinted iPSC-Derived Neural Physiological and Disease Models . . . . . . . . . . . . . . . . . . . . . . 13 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

30 31 31 34 35 37 38 40 41 42 43 46 50 51

Abstract

Patient-derived induced pluripotent stem cells (iPSCs), carrying the genetic information of the disease and capable of differentiating into multilineages in vitro, are valuable for disease modeling. 3D bioprinting enables the assembly of the cell-laden hydrogel into hierarchically three-dimensional architectures that S. Liang · Y. Su Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing, Department of Mechanical Engineering,, Tsinghua University, Beijing, China R. Yao (✉) Biomanufacturing and Rapid Forming Technology Key Laboratory of Beijing, Department of Mechanical Engineering,, Tsinghua University, Beijing, China State Key Laboratory of Tribology in Advanced Equipment, Tsinghua University, Beijing, China e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_646

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recapitulate the natural tissues and organs. Investigation of iPSC-derived physiological and pathological models constructed by 3D bioprinting is a fast-growing field still in its infancy. Distinctly from cell lines and adult stem cells, iPSCs and iPSC-derived cells are more susceptible to external stimuli which can disturb the differentiation, maturation, and organization of iPSCs and their progeny. Here we discuss the fitness of iPSCs and 3D bioprinting from the perspective of bioinks and printing technologies. We provide a timely review of the progress of 3D bioprinting iPSC-derived physiological and pathological models by exemplifying the relatively prosperous cardiac and neurological fields. We also discuss scientific rigors and highlight the remaining issues to offer a guiding framework for bioprinting-assisted personalized medicine. Keywords

Bioinks · Bioprinting · Disease modeling · Induced pluripotent stem cells

1

Introduction

Preclinical animal models have been extensively established to study disease progression mechanisms and foster therapy development. However, due to species differences and uncontrollable variables, animal models are limited in investigating disease progression in human patients and quantitative analysis of disease mechanisms at the molecular level. Although planar cultured human cell models are widely used alternatives, they, however, are limited in recapitulating the complex tissue microenvironment, such as components and structures of the extracellular matrix (ECM) which play a crucial role in development and tissue homeostasis (Zagris 2001). Dysregulation of ECM geometric structure and biochemical properties leads to various pathological states in diseases, such as cancer, fibrosis, and osteoarthritis (Bonnans et al. 2014). For instance, abnormal collagen I deposition and increased ECM stiffness are observed in liver fibrosis (Long et al. 2022), and excessive ECM degradation is linked to osteoarthritis (Zhen and Cao 2014). These indispensable roles of ECM have motivated the fabrication of sophisticated three-dimensional (3D) in vitro models incorporating biomimetic ECM/cell components, mimicking the microenvironment and cell-cell/matrix interactions in disease conditions. Currently, pathogenesis-related and high-throughput 3D models with high reproducibility are urgently needed. 3D printing is a widely used material processing technology and is advanced in precisely printing hierarchical architectures based on computed tomography (CT), magnetic resonance imaging (MRI), or computer-designed virtual models. 3D printing has expanded its processing materials from plastics to various synthetic or natural extracellular matrix-derived biomaterials, such as collagen, laminin, gelatin, and alginate. 3D bioprinting can fabricate reliable in vitro human disease models by integrating multiple factors, including geometrical structures, biochemicals, mechanics, multicellular types, etc.

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Induced pluripotent stem cells (iPSCs) are capable of differentiating into multilineages, offering an unlimited cell source of otherwise inaccessible tissue cells, such as hepatocytes and neural and cardiac cells. Here, we review the recent advances in the 3D bioprinting of iPSCs and the application of engineered architectures in human disease modeling, a fast-growing field still in its infancy. We analyze the fitness of iPSCs and 3D bioprinting from the perspective of bioinks and printing technologies. As biomaterial-based bioinks are vehicles to transfer cells and provide an extracellular matrix environment, we first introduce a bioink specific for bioprinting iPSCs. Subsequently, the respective printing techniques are introduced and discussed from the perspective of fitness to iPSCs. Then, we review the progression of 3D bioprinting iPSC-derived physiological and pathological models by exemplifying the relatively prosperous cardiac and neurological fields. We further discuss scientific rigors in the integration of iPSCs and bioprinting and highlight the issues that need to be addressed in the future for broader applications.

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Overview of 3D Printing

3D printing first appeared in the 1980s and was used to manufacture product prototypes by combining computer-aided design with material processing. It has gradually evolved to fabricate functional parts more directly and more rapidly. 3D printing is based on a digital model file. It constructs solid objects layer-by-layer with materials, such as metals and polymers through extrusion, sintering, light curing, and other methods (Ngo et al. 2018). 3D printing technology is based on the “discrete-stacking” principle. “Discrete” refers to discrete the digital data of a part into a series of two-dimensional (2D) layers (or surfaces), one-dimensional filaments (or lines), or zero-dimensional dots (or micropatterns). “Stacking” means reconstructing the 3D solids through the deposition and adhesion of the discrete elements under the guidance of specific virtual files, thus forming objects with complex structures and compositions (Fig. 1). Unlike traditional subtractive manufacturing, such as removal-cutting, 3D printing is a bottom-up manufacturing method and a process of downscaling manufacturing (Ngo et al. 2018). The earliest established 3D printing method is stereolithography (SLA). The most widely used 3D printing worldwide is fused deposition modeling (FDM). Selective laser sintering (SLS) is used more frequently in metals and ceramics (Ngo et al. 2018).

3

Bioinks for Bioprinting

The development of printing materials with improved biocompatibility has advanced 3D printing in the biological field, so 3D bioprinting has emerged since the 2000s. In February 2015, “Bioprinting” entered Oxford Dictionaries, became an official word, and was defined as “The use of 3D printing technology with materials that incorporate viable living cells. For, e.g., to produce tissue for reconstructive surgery.” Based

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Fig. 1 The diagram of “discrete-stacking” principle in 3D printing

on computer-designed hierarchical structures, 3D bioprinting can assemble biomaterials, living cells, and other biological elements, including bioactive proteins and cytokines, to engineer tissue-like architectures based on the “discrete-stacking” principle (Ozbolat et al. 2016). The biomaterials used for bioprinting, termed bioink, have more profound biocompatibility and biological activities than materials used in traditional 3D printing. Bioinks are usually laden with cells and provide 3D microenvironments for cells. The 3D printing endows the cell-laden bioink with predesigned properties of geometry and mechanics, mimicking the 3D microenvironment of natural tissue. The responsive properties of bioinks to temperature, pH, or light within the range of cellular compatibility expand the spectrum of regulation in the printing procedure. The bioinks include natural and synthetic materials. Some natural materials, such as chitosan, sodium alginate, and agarose, show good printability and shape fidelity. However, they rarely include signaling factors for inducing complex behaviors in stem cells (Hospodiuk et al. 2017; Zhang et al. 2017). Vertebrate-derived natural materials, including gelatin, collagen, fibrin, hyaluronic acid, and Matrigel, have cell adhesion and inductive signaling factors but show relatively poor printability and shape fidelity. Mixing these two types of natural biomaterials is a common bioink composition strategy. Another strategy is to create synthetic materials that are both printable and biologically active by regulating properties such as degradability and degree of crosslinking through synthetic ratios. Common synthetic bioinks include polyethylene glycol (PEG), polycaprolactone (PCL), polyglycolic acid (PGA), and pluronics (Hospodiuk et al. 2017; Zhang et al. 2017). The printability of bioinks depends on the tunability of the sol-gel transitions under cell-compatible conditions. Bioinks can be classified according to their

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properties, such as shear-thinning biomaterials, temperature-sensitive biomaterials, pH-regulated biomaterials, and photosensitive biomaterials. Shear-thinning bioinks are widely used in microextrusion-based bioprinting. Shear thinning refers to the phenomenon in which the material shows lowered viscosity and flows more easily when subjected to shear force. Bioinks with shear-thinning properties exhibit low viscosity and low internal stress at the tip of the nozzle during extrusion, which can effectively protect cells from shear force (Zhang et al. 2017). Most hydrogels have shear-thinning properties, including gelatin, sodium alginate, and GelMA (gelatin methacrylate). On the other hand, fibrin cannot be used alone for microextrusionbased printing in part due to the lack of shear-thinning properties (Hospodiuk et al. 2017). Shear-thinning biomaterials can also respond to temperature, pH, and light stimulus. Temperature-sensitive bioinks can be crosslinked by temperature adjustment, thus showing vast applications in extrusion and inkjet printing. Common temperature-sensitive biomaterials include agarose, gelatin, Matrigel, and Pluronic F-127. Specifically, Pluronic F-127 shows shear-thinning properties above 20°C and reverts to a liquid state below 4°C (Zhang et al. 2017), so it needs to be kept at a higher temperature during bioprinting. PH-regulated biomaterials can be crosslinked by pH variation, such as chitosan, collagen I, and hyaluronic acids. These materials are generally precrosslinked by adding acids to the material to facilitate subsequent printing. Photosensitive biomaterials are materials that can be crosslinked by UV or visible light. They are essential for laser printing and SLA. Commonly used photosensitive bioinks include GelMA and PEG. Additionally, decellularized extracellular matrix (dECM) is a widely used bioink with biological properties similar to in vivo ECM. Recent studies are considering both inductive biological cues and higher printability. The materials mentioned above are often combined to meet the multifaceted demands in bioprinting. The microenvironment formed by bioinks regulates the differentiation and selfassembly of stem cells. Conversely, cells can remodel the microenvironment by degrading the surrounding ECM and depositing new ECM components to grow, migrate, and assemble structures (Shellard and Mayor 2020). Thus, cell degradable bioinks are especially attractive for 3D bioprinting because they can mimic the dynamic balance of the ECM in response to cell signaling, which is indispensable for in vitro tissue reconstruction. Chimene et al. established a bioink formulation based on covalently cross-linkable GelMA (Chimene et al. 2020). The encapsulated MSC cells remodeled 3D bioprinted scaffolds by depositing nascent extracellular matrix proteins, and the cells showed endochondral differentiation in the absence of an osteoinductive agent. It has been demonstrated that the degradation rate of ECM is a critical factor in successful tissue regeneration: rapid degradation will lead to a scaffold degrading faster than nascent ECM deposits, while excessively slow degradation will constrict the room for cell growth and healing (Chimene et al. 2020). Therefore, the versatility of bioinks and the modifiability of mechanical properties allow bioinks to be formulated for different cell types and tissue structures. The formulation of iPSC-specific bioinks needs to take full account of

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the factors: biocompatibility, printability, tunability, mechanical stability, and cell remodeling.

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Bioinks for iPSC Bioprinting

The biochemical composition and mechanics of the microenvironment are developed corresponding with tissues or development in vivo. iPSCs can mimic the different stages of tissue and organ development in vitro. The stem cell niches required for tissue development need to be rebuilt to provide biophysical (e.g., stiffness and geometry) and biochemical (e.g., growth factors and signaling pathway cues) information (Gu et al. 2017; Sun et al. 2019). Ideal bioinks should provide a biomimetic extracellular microenvironment and regulate the maintenance of pluripotency or lineage differentiation. Next, we introduce the fitness of bioinks and iPSC/iPSC-derived cells from the perspective of pluripotent maintenance and the promotion of lineage specification. Large-scale iPSC expansion, maintenance of pluripotency, and karyotype maintenance are the basis for iPSC applications. Matrigel is currently the most commonly used substrate component for iPSC culture, providing biochemical signaling for iPSCs. Matrigel and other biomaterials with good mechanical properties were blended to improve the printability of the bioink, making the printed structures bioactive and mechanically stable. iPSCs were sensitive to the bioinks because the bioink continually affects the maintenance of cellular properties after printing (Koch et al. 2018). Thus, even though the components are unaltered, the material ratios of bioinks significantly affect the maintenance of iPSC pluripotency. Our previous study found that Matrigel and hydroxypropyl chitin, which have temperaturesensitive properties, can promote iPSCs aggregation and proliferation. However, excessive Matrigel concentrations can affect cell aggregate homogeneity and lead to iPSC differentiation (Li et al. 2018), demonstrating that the balance between pluripotency maintenance and the initiation of differentiation should be considered holistically. For directed differentiation, different differentiation stages and different lineages have distinct requirements for biological signaling and mechanical properties. Tissue-derived dECM preserves the major components of the ECM of natural tissue but has poor printability. Yu et al. improved the printability of heart-derived or liverderived dECM with GelMA and obtained a photocrosslinkable dECM bioink, which allowed regulation of the mechanical properties of the hydrogel structures by tuning the exposure time without changing the formulation component (Yu et al. 2019). They found that the highly tissue-matched dECM bioink promoted the cellular activity and maturation of iPSC-derived cardiomyocytes and hepatocytes. Furthermore, the modified bioink enables the fabrication of microscale geometries, offering biophysical cues that guide cells to spontaneously reorganize into the predesigned transverse heart and lobular liver structures. Instead of dECM, Kupfer et al. formulated a bioink with chemically defined biochemical compositions and mechanical properties, biomimetic the embryonic heart microenvironments. They printed

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iPSCs to form 3D hydrogels and induced iPSC differentiation into cardiomyocytes in situ. The differentiation process was enhanced by the bioink components fibronectin and laminin-111, which are ECM components of the fetal heart (Kupfer et al. 2020). Therefore, bioinks need to be designed adaptably for iPSC-derived cells or tissues based on the biochemical and mechanical properties of the tissue ECM. Given that different types of cells require distinct cell niches, bioinks must be tailor-made depending on the cell type to satisfy the development and structural assembly. Based on the principle of discrete stacking, 3D bioprinting allows the fabrication of intricate hierarchal tissues with multiple types of cells encapsulated in cell-specific bioinks. Ma et al. formulated bioinks with designed chemical compositions and mechanical properties based on liver and endothelial cell characteristics. GelMA, with a stiffness similar to that of healthy liver tissue, was used to support iPSC-derived hepatocytes; methacrylate-hyaluronic acid (GMHA), which can promote endothelial cell proliferation and support vascularization, was blended with GelMA to support endothelial and mesenchymal cells. The three cells were printed into a multicellular liver model with microscopic hexagonal geometry, which showed apparent morphological organization and liver function (Ma et al. 2016). In summary, bioinks can regulate the maintenance of pluripotency and cell differentiation of iPSCs by modulating biochemical and mechanical properties. Table 1 summarizes the typical bioinks specified for undifferentiated iPSCs and iPSC-derived cells. Notably, the biological and mechanical properties of the extracellular microenvironment change dynamically during tissue development, which needs to be considered in the bioink formulation for iPSC-derived cells. To guide tissue maturation and ordered morphogenesis, the biochemical and physical signals must be added into the printed architectures in real time, following the dynamic requirement for physiological signaling in tissue development. Thus, in-depth studies are needed to reveal the changes in the extracellular matrix components and mechanical properties of tissue development. In addition, printing technologies capable of orienting biochemical and mechanical properties need to be developed.

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3D Bioprinting of iPSCs

With the development of bioinks, 3D bioprinting has rapidly developed. Ding et al. reviewed stem cell-based 3D bioprinting technologies, including inkjet bioprinting, microextrusion-based bioprinting (termed bioplotting), SLA-based bioprinting, and laser-assisted bioprinting (Fig. 2) (Ding et al. 2018). Due to the characteristics that distinguish iPSCs from adult stem cells, Li et al. reviewed engineering-derived approaches, including cell printing, that are suitable for bioprinting iPSCs (Li et al. 2017). As iPSCs or iPSC-derived cells are susceptible to external stimuli, inappropriate parameters of bioprinting may impact the phenotype and differentiation ability of iPSCs or iPSC-derived cells. Here, we focus on the fitness of the representative bioprinting technologies and iPSC cells or iPSC-differentiated cells in the context of cell viability, pluripotency maintenance, and cell fate determination.

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Table 1 The bioinks used for bioprinting iPSCs and iPSC-derived cells iPSCs

Differentiated iPSCs

Cells Undifferentiated iPSCs

Bioink Hydroxypropyl chitin/Matrigel

Undifferentiated iPSCs Undifferentiated iPSCs

Matrigel/ hyaluronic acid Polyurethane

Undifferentiated iPSCs

Alginate/ carboxymethylchitosan/ agarose Matrigel/ gelatin/fibrin/ GelMA

iPSC-derived spinal neuronal progenitor cells

iPSC-derived neural aggregates

Alginate/fibrin/ genipin

iPSC-derived astrocytes; iPSCderived motor neuron progenitors iPSC-derived cortical neurons; iPSC-derived glial cells iPSC; iPSCderived NSCs

Gelatin/laminin

iPSC-derived cardiomyocytes

iPSC; iPSCderived cardiomyocytes iPSC-derived cardiomyocyte

Matrigel/ alginate

Main findings High cell yield, high pluripotency maintenance and uniform aggregation Pluripotency maintenance High survival, reduced injury by shear stress In situ cell proliferation and successive multilineage differentiation Activity of neuronal networks, differentiating and extending axons throughout microscale scaffold channels High cell survival rate and differentiation into mature neural phenotype Cell clusters on the scaffold surface, good differentiation with extended neurites and astrocytic processes Differentiation within the construct, neuronal and astrocytic markers

Alginate/gelatin

Good cell viability

Patient-derived dECM/gelatin (sacrificial bioink) Alginate/PEGfibrinogen/ PEGDA Laminin111/ fibronectin/ GelMA/ collagen methacrylate

Certain structure and function of cardiac tissue Certain 3D structure of cardiac tissue Proliferation and subsequently differentiation into cardiomyocytes in situ

References Li et al. (2018)

Koch et al. (2018) Wong et al. (2018) Gu et al. (2017)

Joung et al. (2018)

Abelseth et al. (2019) Han et al. (2022)

Salaris et al. (2019) Fantini et al. (2019) Noor et al. (2019)

Maiullari et al. (2018) Kupfer et al. (2020)

(continued)

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Table 1 (continued) Cells iPSC-derived cardiomyocytes; iPSC-derived hepatocytes iPSC-derived hepatocyte

Bioink dECM/GelMA

Main findings High viability and maturation

References Yu et al. (2019)

RGD-coupled sodium alginate

FaulknerJones et al. (2015)

iPSC-derived MSCs

Alginate/gelatin

iPSCs & irradiated mature chondrocytes

Alginate/ nanofibrillated cellulose

Pluripotency maintenance and cell phenotype of the differentiated cells Increased survival duration of transplanted hiMSCs Cartilage production in cocultures with irradiated chondrocytes

Ji et al. (2020) Nguyen et al. (2017)

Fig. 2 Schematic diagram of common technology for 3D bioprinting of living stem cells. Adapted with permission from American Chemical Society: [ACS Biomaterials Science & Engineering], copyright (2018) (Ding et al. 2018)

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Inkjet Bioprinting

Inkjet bioprinting technology, also known as drop-on-demand bioprinting, produces predefined cell patterns or structures by depositing tiny volumes (1–100 pL) of bioink and cellular droplets through small nozzles on a series of substrate structures repeatedly in a highly controlled and precise manner (Ding et al. 2018). Inkjet bioprinting was first reported in 2003 when Boland et al. successfully constructed micropatterns using inkjet bioprinting and thermal hydrogels mixed with cells (Boland et al. 2003). Inkjet bioprinting requires a low-viscosity material to avoid

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clogging the needle. The viscosity range of the ink should be approximately 3.5–12 mPa
s (Mandrycky et al. 2016). The most common driving methods for inkjet bioprinting are thermal, piezoelectric, valve, and electrostatic fields, which show mild impacts on the viability of stem cells (Saunders and Derby 2014). Thermal-based inkjet bioprinting showed approximately 80% stem cell viability (Saunders and Derby 2014; Xu et al. 2005). The valve-based inkjet bioprinting showed approximately 84% embryonic stem cell viability (Faulkner-Jones et al. 2015). The electrostatic force-based inkjet bioprinting reached over 95% viability for human adipose-derived stem cells (Yao et al. 2012) and 92% viability for hepatic stem cells (Huo et al. 2020). Inkjet bioprinting favorable for stem cell viability has been used to construct 3D iPSC-derived models. Jones et al. used valve-based inkjet bioprinting to print iPSCs and iPSC-derived hepatocyte-like cells. They found that iPSCs maintained high viability, and iPSC-derived hepatocyte-like cells were successfully constructed into mini-liver models (Fig. 3a) (Faulkner-Jones et al. 2015). Our research found that high-voltage electrostatic-based inkjet printing could efficiently fabricate microspheres where iPSCs and iPSC-derived cells can self-organize into organoids (unpublished data). Inkjet bioprinting has high printing precision, which facilitates printing a single cell by adjusting the cell density and volume of the droplet. Additionally, the droplet generation rate can be more than 2.5 × 105 drops per second. The productive and high printing efficiency make inkjet printing a powerful platform for highthroughput screening of toxicants. However, due to the similar size of the printing nozzle and cell size, inkjet bioprinting shows limitation in high cell density in bioinks, making it challenging to print iPSC clones, clusters, or aggregates.

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Microextrusion-Based Bioprinting

Microextrusion-based bioprinting, also known as bioplotting, is the most commonly used method for fabricating large-sized 3D structures with predesigned spatial patterns containing cells/cell aggregates/organoids and bioinks. Unlike inkjet bioprinting, which breaks bioinks into droplets, bioplotting extrudes continuous filaments (usually several hundred microns) composed of viscous materials and cells through a nozzle, generally driven by pneumatic or piston pressure. The process of printing can be reprogrammed to form hierarchically multilayered 3D architectures (Ding et al. 2018). Bioplotting was first reported in 2005 when researchers used bioinks, including sodium alginate, to enable the precise spatial construction of complex structures at the centimeter scale (Khalil et al. 2005; Yan et al. 2005). To facilitate bioink flow and 3D architecture formation, bioplotting generally requires the sol-gel transition of bioinks during printing, so temperature-sensitive hydrogels such as gelatin, collagen, and Pluronic F127 are often used. Extrusion printing shows a wide compatibility with the viscoelasticity of bioinks. Hydrogels with elastic moduli between hundreds

Fig. 3 Examples of different bioprinting techniques applied to iPSCs. (a) Inkjet bioprinting of iPSCs to build mini-livers. Adapted with permission from IOP Publishing [Biofabrication], copyright (2015) (Faulkner-Jones et al. 2015). (b) Microextrusion-based bioprinting using a novel bioink to print iPSCs and obtain a 3D structure with high cell activity. Adapted with permission from IOP Publishing: [Biofabrication], copyright (2018) (Li et al. 2018). (c) SWIFT to construct vascular channels in the embryoid matrix. Adapted with permission from American Association for the Advancement of Science: [Science Advances], copyright (2019) (Skylar-Scott et al. 2019). (d) DLP technology of iPSCs to quickly build a biomimetic human hepatic model. Adapted with permission from PubMed Central (PMC): [Proc Natl Acad Sci U S A], copyright (2016) (Ma et al. 2016). (e) Laser-assisted bioprinting of Matrigel to construct iPSC arrays with high activity. Adapted with permission from IOP Publishing: [Biofabrication], copyright (2018) (Koch et al. 2018)

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and thousands of Pascal and viscosities between tens and tens of millions of mPa
s are all suitable for bioplotting (Mandrycky et al. 2016). The main factors affecting cell viability are inner needle diameter, length, and extrusion rate (Gu et al. 2017; Li et al. 2018; Nguyen et al. 2017). Generally, at the same extrusion pressure, the diameter of the needle is inversely proportional to the shear force of the bioink during extrusion, which causes mechanical damage to the cells. Therefore, the extrusion pressure and needle diameter must be tuned collaboratively during the printing process, especially for iPSCs susceptible to mechanical stimuli. Li et al. found that a high cell survival rate (>90%) could be achieved using a 260 μm inner diameter to obtain high printing efficiency (Li et al. 2018). iPSCs should maintain their proliferation capacity and the potential to differentiate into three germ layers after bioplotting. For in situ expansion and sequential differentiation, Gu et al. bioplotted human iPSCs with a clinically amenable polysaccharide-based bioink composed of alginate, carboxymethyl-chitosan, and agarose (Gu et al. 2017). Li et al. realized the bioplotting of iPSC single cells with a new type of bioink hydroxypropyl chitin. It could be crosslinked in a few seconds under physiological conditions, so the cells suffered low damage and had a high survival rate (Fig. 3b). With the help of Matrigel, iPSCs can rapidly amplify into clusters and maintain a pluripotent phenotype. iPSCs could be harvested without damage when the bioink was cooled to approximately 4°C (Li et al. 2018). In addition to undifferentiated iPSCs, bioplotting has also been used for iPSC-derived cells, such as differentiated neural cells (Hirano et al. 2021), to construct biomimetic tissue models. Tubular lumen with complex hierarchical structures can also be bioplotted, removing sacrificial material, as illustrated in SWIFT (sacrificial writing into functional tissue) technology (Fig. 3c), to fabricate vascularized cardiac tissues with iPSC-derived cardiomyocytes and supporting cells (Skylar-Scott et al. 2019). Coaxial bioplotting is used to print iPSC-derived neurons and glial cells to make human cortical neural constructs (Salaris et al. 2019). Bioplotting is a versatile printing technology, such as compatibility with a wide range of biological inks, the ability to print single dispersed cells or cell clusters, and the flexibility to upgrade technology such as SWIFT. It has the advantages of high efficiency, high cell density, and large-scale fabrication. However, the resolution of bioplotting is low, as the diameter of microfilaments is generally more than 100 μm. It is challenging to realize single-cell printing. Moreover, shear effects that may affect iPSCs cannot be avoided.

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Stereolithography (SLA)-Based Bioprinting

SLA-based cell printing uses ultraviolet (UV) light or visible light to scan the surface of a photosensitive bioink point by point and the material in the scanned area (approximately tens to hundreds of microns) gels by photopolymerization reactions (Arcaute et al. 2006; Moroni et al. 2018). This process is repeated for successive stacks of layers until the 3D object is assembled. The DLP (digital light projection)

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and CLIP (continuous liquid interface production) techniques, which are SLA-based printing combined with projection and continuous liquid interfacial growth, can significantly improve the printing efficiency and scalability for the fabrication of complex 3D microstructures (Ding et al. 2018). Bioinks should contain photosensitive groups that can react under visible or UV light irradiation. Commonly used bioinks include GelMA, poly(ethylene glycol)diacrylate (PEGDA), and methacrylated hyaluronic acid (HAMA), which are mostly synthetic or natural materials with modification. To satisfy SLA-based bioprinting, the bioink should have low and medium viscosities, usually ranging from 1 to 300 mPa
s (Mandrycky et al. 2016). Until now, there have been few available photosensitive bioinks to meet the requirements of various iPSC-derived multilineages. Currently, studies that use SLA-based bioprinting to print iPSCs or iPSC-derived cells have emerged but have developed relatively slowly. The micrometer-level resolution of the DLP-based 3D bioprinting system enabled Ma et al. to construct an iPSC-derived multicellular hepatic model with a liver lobule hexagonal pattern within several seconds (Fig. 3d) (Ma et al. 2016). hiPSC-derived hepatic progenitors and endothelial and mesenchymal cells were realigned within the 3D microscale hydrogel hexagonal structure and were developed into the enhanced function of hiPSC-derived hepatocyte-like cells. Ma et al. developed and applied this technique to the scalable fabrication of iPSC-derived cardiac tissue suitably cultured in 24-well and 96-well plates, which has great potential for high-throughput in vitro drug screening applications (Ma et al. 2019). As such, SLA-based bioprinting is an efficient, highly flexible, and highresolution bioprinting system advanced in building 3D microscopic anatomic constructions. The main factors affecting cell survival in SLA-based bioprinting are light intensity and light duration. However, this technology requires the extra design of photomask plates, adding to the complexity of the process. Furthermore, since the photoinitiator is retained in the printed structure and the intensity of the light may cause gene mutations, the effect of photoinitiators on iPSC differentiation and the genotoxicity of light duration and intensity on iPSC-derived cells need to be taken into account.

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Laser-Assisted Bioprinting

Laser-assisted bioprinting can be divided into two methods: laser-guided direct writing (LGDW) and laser-induced forward transfer (LIFT). Renn et al. proposed LGDW in 1999, which uses the force of a laser beam on cells to deposit cells on the surface of the substrate. Cells can be transferred from tens of microns to a few millimeters (Odde and Renn 1999). LIFT uses the thermal impact of the laser on the material to transfer cell-laden bioinks. A laser beam passes through the transparent substrate and focuses on the interface between the bioink and the substrate. Therefore, the interaction allows the cell-laden droplets to leave the substrate and deposit on the receiving layer below (Guillotin et al. 2010).

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Laser-assisted bioprinting is a relatively new method compared to the other three bioprinting techniques mentioned above. Koch et al. used laser-assisted bioprinting to print iPSC-laden HAMA/Matrigel bioinks (Koch et al. 2018), and found that iPSC survival rate reached over 90% after bioprinting, and further differentiated into cardiomyocyte-like cells (Fig. 3e). They demonstrated that influence of the bioink material was more likely to affect cells than the printing technique itself. Laser-assisted bioprinting has a high resolution of several to dozens of microns. The laser does not interact with the cells directly, so the cell survival rate is relatively high. However, the efficiency of laser-assisted bioprinting is low. It can only print hundreds of bioink drops per second. In summary, as a special type of stem cell, more attention needs to be paid to the survival rate, proliferation, and pluripotency of iPSCs during printing. Therefore, appropriate bioinks should be considered to maximize iPSC activity and pluripotency or to fit targeted differentiating cells. It is also necessary to consider the characteristics of different printing technologies, such as the requirements for bioinks, effects on cells and complexity of the printing model, to properly construct tissue models. Bioprinting based on iPSCs requires special attention to the printing parameters to avoid damaging the cell phenotype or function of iPSCs. Currently, printing techniques other than these mentioned techniques have been developed. For example, material-free 3D cell models can be constructed by extracting cell clusters with microneedle arrays and positioning deposition (Nakamura et al. 2021; Ong et al. 2017).

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iPSC-Based Bioprinting for Disease Modeling

3D bioprinting technology provides the framework for modeling disease processes by recapitulating the pathological/physiological extracellular microenvironment. The impact of microenvironmental alterations on pathogenesis can be investigated with 3D bioprinting disease models by specifying the tuning of biochemical and mechanical properties as well as geometric structures (Memic et al. 2017). For example, to reveal the effects of microenvironmental stiffness on cancer cell migration, Soman et al. employed 3D-printed polyethylene glycol scaffolds with tuned elastic moduli (Soman et al. 2012). They found that cancer cells’ displacement, velocity, and path straightness parameters were sensitive to substrate stiffness. Additionally, with bioprinting method, Grolman et al. revealed that the geometry of microchannels influenced the migration profile of macrophages and interaction with breast cancer cells (Grolman et al. 2015). iPSCs reprogrammed from autologous cells directly from patients show significant advantages in precision medicine and disease investigations (Fiorotto et al. 2019). iPSCs can be differentiated into multilineage cells, including neurons, hepatocytes, myocytes, and pancreatic beta cells (Koike et al. 2019; Nagamoto et al. 2016; Palpant et al. 2017; Vatine et al. 2019), offering unlimited cell sources for in vitro physiological and disease modeling. iPSCs or iPSC-derived cells can be assembled into hierarchical physiological and pathological models by 3D

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bioprinting techniques. Thus, the printed iPSC-derived disease models provide insights into disease pathogenesis in genetic information and a more realistic 3D environment. Here, we discuss the strategies for constructing 3D-bioprinted iPSCderived physiological and pathological models from the perspective of the characteristics of 3D bioprinting and iPSCs. As 3D-bioprinted iPSC disease models are still in their infancy, we mainly discuss the strategies for building models on cardiac and neurological disease models that have shown initial progress in the fabrication of physiological and disease models with the integration of iPSCs and 3D bioprinting.

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Bioprinting of iPSC-Derived Cells for Cardiac Disease Models

Cardiac disease patient-specific iPSCs can be differentiated into various cardiovascular cell types, such as cardiomyocytes (iPSC-derived CMs), endothelial cells (iPSC-derived ECs), and cardiac fibroblasts (iPSC-derived CFs) (Cho et al. 2021)

Fig. 4 3D bioprinted cardiac disease models. (a) Schematics of the application of iPSCs derived from cardiac disease patients in disease modeling. (b, c) An arterial vascular network geometry was printed within a cardiac organoid matrix using patient-specific cardiac structural data. (b) The three images show the embedding, evacuation, and perfusion of branched vascular channels within a cardiac tissue matrix. (c) Left panel is the 3D CAD model of a normal human heart, including a segment of the left anterior descending (LAD) artery and a diagonal branch, downloaded from the National Institutes of Health 3D Print Exchange. The right panel is a polydimethylsiloxane mold using the 3D computed tomography data, and the LAD artery and diagonal and septal (arrowheads) branches are embedded into a septal-anterior wall wedge [yellow section] of the cardiac tissue matrix via SWIFT. (b, c) Adapted with permission from American Association for the Advancement of Science: [Science Advances], copyright (2019) (Skylar-Scott et al. 2019). (d, e) 3D bioprinting of personalized cardiac patches based on iPSC-derived CMs. (d) CT image of a human heart and left ventricle coronary arteries. (e) The left panel is the side view of the printing concept and the distinct cellular bioinks. The right panel is a printed iPSC-derived cardiac patch where the blood vessels (CD31 in green) are seen between the cardiac tissue (actin in pink). (d, e) Adapted with permission from American Association for the Advancement of Science: [Science Advances], copyright (2019) (Noor et al. 2019)

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(Fig. 4a). iPSC-derived CMs from cardiac disease patients recapitulated the phenotypes of cardiac diseases such as dilated cardiomyopathy and familial hypertrophic cardiomyopathy, which exhibits pathological phenotypes such as cellular enlargement and contractile arrhythmia (Lan et al. 2013; Sun et al. 2012). A biomimetic cardiac extracellular microenvironment needs to be constructed to facilitate the in vitro maturation and structural assembly of iPSC-derived cardiac cells. The ECM provides biochemical, mechanical, and geometric signals, which coordinately regulate the organization and physiological function of the native myocardium (Cho et al. 2021). dECM-based bioinks preserve the natural characteristics of microenvironments, but the inherently poor mechanical properties of dECM bioinks limit the construction of multilayer architectures with high fidelity. For example, fibrillar collagens, the primary component of cardiac ECM, provide critical biochemical and mechanical cues for aligning cardiomyocytes (Frangogiannis 2017). Shin et al. developed mechanically tunable dECM-based bioink with heart-derived dECM, nanoclay, and PEGDA, enabling bioplotting and photopolymerization (Shin et al. 2021). The printing process and bioink did not impact the viability of iPSC-derived CM and human cardiac fibroblasts. Additionally, the compressive modulus of the dECM bioinks was tuned from 13.4 to 89 kPa, encompassing ranges of tissue stiffness from healthy (~5–15 kPa) to fibrotic (~30–100 kPa) cardiac tissue states, highlighting the potential for applications in modeling both healthy and fibrotic cardiac tissue. Therefore, bioinks with biochemical and mechanically tunable properties enable investigation of the pathological mechanisms, particularly with an altered mechanical microenvironment. However, one drawback in Shin et al.’s study is that cardiac fibroblasts could not spread out in the photopolymerized hydrogel, likely a direct result of nonbiodegradable networks that prevented the cells from remodeling the matrix (Shin et al. 2021). Progressively, Lee et al. developed a method to bioprint natural collagen into cardiac ventricles with structural integrity using freeform reversible embedding of suspended hydrogels (FRESH) (Lee et al. 2019). In the printed ventricles, human embryonic stem cell-derived cardiomyocytes (hESC-derived CMs), cardiac fibroblasts, and endothelial cells could spread and be assembled into synchronously contracting cardiac tissues and perfusable vasculature. As iPSC differentiation is similar to hESCs, this study can be extended to constructing iPSC-derived cardiac models. In addition to bioink-based tunability, 3D bioprinting can modulate the cell alignment of iPSC-derived CMs by defining the spatial orientation of the printed structures (Maiullari et al. 2018; Zhang et al. 2016). Maiullari et al. bioplotted iPSCderived CMs that showed a preferential cell orientation along the printing direction but a random cellular orientation when embedded in bulks (Maiullari et al. 2018). Basara et al. used 3D bioprinting to develop a construct with conductive and topographical cues for iPSC-derived CMs (Basara et al. 2022). In the structure, iPSC-derived CMs showed an aligned pattern and improved synchronous beating and conduction velocity. The patient-derived iPSC-derived CMs exhibited a reduced alignment in parallel with the underlying topography (Macadangdang et al. 2015). Integration of patient-derived iPSCs and 3D bioprinting enables investigation of the

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disease mechanism from scopes of deficiencies in response to geometric and topographical cues. 3D bioprinting can spatially deposit bioinks based on computational models transformed from medical imaging scans to simulate the geometry and topology of tissues. 3D bioprinting based on computer modeling allows the simulation of the geometric characteristics of a patient’s heart tissue. Mark A Skylar-Scott et al. developed SWIFT to construct an iPSC-derived cardiac model with the characteristics of patient vascular networks (Skylar-Scott et al. 2019). In this study, hundreds of thousands of iPSC-derived cardiac organoids were embedded in the bulk structure, where a single channel can be printed with a sacrificial gelatin ink (Fig. 4b). An arterial vascular network with geometric characteristics of the patient’s heart was printed within the bulk structure using patient-specific cardiac structural data from the National Institutes of Health 3D Print Exchange (Fig. 4c). In addition to simulating the anatomical properties of the patient, Noor et al. added patient-derived dECM and iPSCs to construct personalized thick vascularized cardiac patches by 3D bioprinting (Noor et al. 2019). In this study, the geometry of the blood vessel of the patient’s left ventricle was 3D bioprinted based on computeraided design (CAD) software that used anatomical data from the CT images (Fig. 4d). The patient iPSC-derived CMs were combined with collagenous nanofibers; patient iPSC-derived ECs were mixed with gelatin. These two types of bioinks were extrusion printed simultaneously to a thick (≈2 mm) patient-specific vascularized patch (Fig. 4e). Thus, 3D bioprinting shows the potential to assemble patient-derived cells and patient anatomical features to fabricate personalized tissues. However, there are still challenges in the fabrication of disease models, including adequate numbers of iPSCs, culture methods to facilitate nutrient and oxygen delivery, and microvascularization. To solve these issues, Noor et al. proposed the strategies that the entire blood vessels of the heart were imaged and incorporated into the blueprint of the organ and called for advanced technologies to precisely print these small-diameter blood vessels within thick structures (Noor et al. 2019). In summary, 3D bioprinting allows the construction of personalized cardiac physiological and pathological models by orthogonally modulating the composition of the bioink, the geometry and topology, and the mechanical properties of the printed cardiac tissues to simulate the extracellular microenvironment. This involves computational graphics design for 3D bioprinting, sacrificeable inks, mechanical tunability, and other properties. However, there are still challenges, such as the alignment of cardiomyocytes, microvascularization, and scalable cardiac tissue construction, which need advanced engineering, biomaterial, and biological technologies.

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Bioprinted iPSC-Derived Neural Physiological and Disease Models

Neural diseases such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, multiple sclerosis, and amyotrophic lateral sclerosis affect millions of individuals annually and pose heavy burdens on public health. The fabricated in vitro neural models are more accessible, accurate, and reproducible for understanding healthy and pathological tissue development than animal models. Human primary neural cells are challenging to obtain and, therefore, inaccessible for in vitro neural model construction. iPSCs can be differentiated into astrocytes and different neuron subtypes, including glutamatergic, GABAergic, cholinergic, and dopaminergic neurons, providing a rich source of neural cells (Fig. 5a) (Chambers et al. 2009; Osaki et al. 2018). Patient-derived iPSCs carry individual genetic information and have been used to investigate neurological and neuropsychiatric disorders, including Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, amyotrophic lateral sclerosis, hypoxic injury, autism spectrum disorder, and

Fig. 5 3D bioprinting neural physiological models based on iPSCs and iPSC-derived cells. (a) Schematics of the application of iPSCs derived from neural disease patients in disease modeling. (b) Immunostaining analysis of bioprinted neural cells and mosaic reconstruction of confocal images. MAP2 (green), TBR1 (red), and DAPI (blue) signals are shown. Adapted with permission from Licensee MDPI, Basel, Switzerland: [Journal of Clinical Medicine], copyright (2019) (Salaris et al. 2019). (c) 3D scaffolds with red-fluorescent BC cells 5 weeks after bioprinting (left panel). Immunofluorescence labeling of iPSC-derived neural cells after 3 weeks of culture inside the scaffold (right panel). There was extensive neurite formation from neurons intermingled with astrocytic processes on the surface of the scaffolds. Adapted with permission from Licensee MDPI, Basel, Switzerland: [International Journal of Molecular Sciences], copyright (2022) (Han et al. 2022). (d, e) The granular structures supported longer neurite extensions compared to bulk hydrogels. (d) Microstructures of extruded hydrogel granules fabricated with nylon mesh weaves of 40 μm pore sizes. (e) 3D reconstruction of confocal images of cells in bulk (left panel) and granular (right panel) hydrogels at day 7. Neurite outgrowth and neurite network formation in the granular hydrogel constructs. (d, e) Adapted with permission from Elsevier [Bioactive Materials], copyright (2022) (Hsu et al. 2022)

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brain tumors (Costamagna et al. 2019). Therefore, patient-derived iPSCs provide important seeding cells for neurological disease model construction. Neural models constructed by integrating 3D bioprinting and iPSCs are in their infancy. iPSC-derived neural cells can self-assemble, continually developing under appropriate circumstances in vitro. 3D bioprinting can provide suitable extracellular matrix environments and spatial positioning for iPSC-derived neural cells, promising the construction of biomimetic neural tissues. In the following, we described the strategies of 3D printing-based neurophysiological models in the context of bioink, mechanical modulation, geometric modulation, and multiplefactor modulation. We also highlight the state-of-art research of neural disease model construction. The bioinks used in bioprinting neural cells include fibrin hydrogels, hyaluronic acid hydrogels grafted with laminin, PCL microfibers, PCL with gelatin, GelMA and PEGDA (Thomas and Willerth 2017). Some native biomaterials blended in boinks promoted neural development. For example, laminin stimulates axonal outgrowth when added to 3D biomaterial scaffolds, likely because it plays a role in axonal guidance and cell migration in neural development (Edgar et al. 2017). Fibrin functionalized with laminin elicits higher neurite outgrowth than unmodified fibrin scaffolds (Pittier et al. 2005). In the future, more studies are needed to reveal the roles of extracellular matrix components and mechanical signals in neural development and morphogenesis, thus laying the theoretical foundation for developing bioinks suitable for fabricating iPSC-derived neural models. The brain is exceptionally soft with the stiffness in the range of 0.5–1 kPa, which is tightly associated with tissue morphogenesis and function (Franze 2013; Warren et al. 2021). The stiffness varies in different regions and developmental stages. For example, cerebral stiffness in bovine brains is 1.33 ± 0.63 kPa in white matter and 0.68 ± 0.20 kPa in gray matter (Weickenmeier et al. 2016). Some nerve diseases change the stiffness of the brain tissues. Compared to healthy persons, there is a significant reduction in the white matter and cortical gray matter of Alzheimer’s patients but not in the subcortical gray matter (Hiscox et al. 2020). For in vitro studies, 3D bioprinting can tune the stiffness of the printed architectures, which will modulate the cellular behaviors, i.e., differentiation and morphogenesis, of the encapsulated neural cells. Additionally, softer hydrogels (~100–500 Pa) have been found to promote neuronal differentiation and maturation, while stiffer hydrogels (~1,000–10,000 Pa) enhance glial differentiation (Saha et al. 2008; Teixeira et al. 2009). Salaris et al. bioplotted soft alginate/matrix bioink and iPSC-derived neuronal and glial precursor cells. The bioprinted cells were highly viable and further differentiated into cells with neuronal morphology and expression of neurofilament proteins (Fig. 5b) (Salaris et al. 2019). In another study, Han et al. found that the maturation of in vitro neural tissues could be optimized by tuning the mechanical properties of the bioink (Han et al. 2022). With optimized mechanical conditions by tuning microtransglutaminase and gelatin concentrations, iPSC-derived motor neuron precursors and astrocytes displayed good differentiation with extended neurites and astrocytic processes in the three-layered hydrogel (Fig. 5c). These two studies

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demonstrated that 3D bioprinting can modulate neural development by controllably tuning the mechanical microenvironment. However, inside the scaffolds, iPSCderived neural cells showed limited morphological differentiation, suggesting that iPSC-derived neural cells required extra regulatory cues. 3D bioprinting can simulate the topological structure of the brain surface to study the effect of topological structure on neural development. Currently, studies based on 3D printing technology are mainly focused on scaffold strategy, meaning 3D printing of biomaterial scaffolds and then seeding cells onto the scaffolds. Hsu et al. found that geometry significantly affects cell morphogenesis. They bioplotted hyaluronic acid hydrogel to generate different geometric structures: bulk and granular scaffolds (Hsu et al. 2022). They found that granular structures supported high viability, more neurite-bearing cells, and longer neurite extensions (65.52 ± 11.59 μm) compared to bulk hydrogels (22.90 ± 4.70 μm) (Fig. 5d, e). Gasparotto et al. bioprinted scaffolds promoting the differentiation of iPSC-derived neural cells by optimizing the chemical factors and geometric structures (Gasparotto et al. 2022). They found that graphene promotes iPSC commitment to the neuroectoderm. Therefore, the 3D bioprinting technology can be used for the investigation of the effects of microtopography in the orientation of the neural neurites. Although it is still in its infancy, bioprinting iPSC-derived neural tissue has shown potential in disease modeling. At the current stage of disease models built with the integration of 3D printing and iPSCs, printing methods mainly focus on the fabrication of disease model-related devices. Shi et al. employed iPSC-derived neural progenitor cells and a 3D printing mini weight-drop impact device to build a mild traumatic brain injury model that recapitulated several hallmarks of brain impact injury (Fig. 6a) (Shi et al. 2021). With the model, iPSC-derived neurospheres subjected to a single mild impact could recover from the injury, but repetitive mild impacts led to neuron loss, reactive astrogliosis, and glial scar formation (Fig. 6b). This suggested that the integration of a 3D printing device and iPSC-derived neurospheres has potential in modeling neural disease. Furthermore, based on the integration of 3D printing microfluidic chips and patient-derived iPSCs, Osaki et al. established a neural disease model involving neural and muscle systems. Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease involving the loss of motor neurons (MNs) and muscle atrophy that still has no effective treatment (Osaki et al. 2018; Rojas et al. 2020). In the printing microfluidic chip, the patient iPSC-derived skeletal myoblasts spontaneously formed muscle fiber bundles around the pillar structures, and iPSC-derived neural stem cell axon outgrowth formed neuromuscular junctions on the muscle fiber bundles (Fig. 6c, d) (Osaki et al. 2018). ALS pathological phenotypes, such as MN degradation and apoptosis, were simulated in the chip. Therefore, the integration of 3D printing chips and patient-derived iPSCs advanced the investigation of the multicellular interaction of iPSC-derived cells in the pathogenesis process. In summary, autologous disease models constructed by bioprinting of patientderived iPSC can be a valuable tool for studying disease pathology and aid in screening personalized drugs against the disease. 3D bioprinting is used to study

Fig. 6 The 3D printing devices and iPSC-derived neural cells were integrated into neural disease models. (a, b) Formation of microglia and neurospheres in a 3D coculture repetitive model of mild traumatic brain injury. (a) Mini-impact device design. The 3D printing mini weight-drop impact device includes the guide construct, the neurosphere holder, and the neurosphere impactor. (b) Timeline and design of the 3D coculture impact study. The lower panel shows the

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neural disease mechanisms by modulating the printing structures’ mechanical properties, geometry, and cellular orientation. However, the brain is a vascularized tissue of nerve bundles and networks formed by various types of cells. The recapitulation of the neural system by 3D bioprinting offers massive potential and also faces challenges, i.e., the simulation of physiological arrangement of neural cells, including neuronal cells, glial cells, oligodendrocytes, and endothelial cells. This requires the improvement of cell-laden bioprinting that precisely deposits cells in spatial architectures. It is also necessary to develop bioinks that promote the continuous maturation of multiple cells and guide the alignment of neuronal cells.

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Outlook

Integration of 3D bioprinting and iPSCs endows the hydrogel architectures with genetic backgrounds and a biomimetic microenvironment with spatiotemporal regulatory cues, which is proven to be very powerful and instrumental in disease modeling. As a fast-growing field in its infancy, some challenges should be considered for future advancement. Firstly, the fitness of the bioprinting window with iPSC differentiation stages should be carefully evaluated. The in vitro iPSC differentiation resembles the stages of sequential progression in lineage development. Dispersibility, tolerability to mechanical disturbance, and structural self-assembly are the key factors influencing cell behaviors when iPSCs and iPSC-derived cells are used for in vitro model construction. Therefore, the appropriate stages of iPSC differentiation adaptable for printing and self-organization in vitro need to be studied in depth. Secondly, the denseness of iPSC-derived tissues constructed by 3D bioprinting technology needs to be improved. The cell density in 3D printed structures is much lower than that in human tissues and organs, which will directly affect the cell-cell/ matrix interactions and the structural assembly of cells. Thus, the mechanisms associated with the proliferation of iPSC-derived cells need to be studied in depth, and efficient technologies for the large-scale expansion of iPSC-derived cells need to be developed. iPSC-derived organoids can be printed as blocks, a recently reported Fig. 6 (continued) appearance of cocultured microglia (red) and neural progenitor cells (green); microglia were distributed around the neurospheres. The right two panels are the control and treatment with two impacts. Adapted with permission from Wiley Online library: Advanced Healthcare Materials, copyright (2021) (Shi et al. 2021). (c, d) Amyotrophic lateral sclerosis (ALS) patient-derived motor unit on a chip microfluidic device. (c) A motor neurons spheroid and a skeletal muscle fiber bundle in a microfluidic chip on day 0 (upper panel) and on day 7 (lower panel). After 7 days of coculture, many axons reached the muscle fiber bundle and end feet of neurons attached to myotubes, resulting in the formation of a motor unit with neuromuscular junctions (NMJ). (d) Comparison of the patient-derived ALS model with the ESC-derived model. Fewer thick neural fibers and less NMJ formation were seen on the patient-derived ALS motor unit model compared with the ESC-derived motor unit. Adapted with permission from American Association for the Advancement of Science: Science advances, copyright (2018) (Osaki et al. 2018)

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strategy to improve the cell density of bioprinting tissues. The fitness of bioprinting and organoids needs to be considered in the context of high cell viability, intact spheroid morphology, and biomimetic biological building blocks. Thirdly, the effects of the mechanical properties on the iPSC-derived cells within the bioinks should be further investigated. The mechanical microenvironment plays critical roles in lineage specification, self-organization and maturation of iPSCderived cells, and disease development. The subtle changes in the mechanical properties of bioinks may alter the cell fate determination and structural assembly of iPSC-derived cells as well as the tissue functions. The digital control of the mechanical properties of the bioink during printing is the bottleneck technology for fabricating tissue models with high-fidelity microenvironment niches. Therefore, there is a need for ways that provide nondestructive visualization for feedback control over the bioink mechanics concomitant with the 3D bioprinting process. Lastly, the freedom for iterative printing in different spatiotemporal windows must be extended. Along with tissue development, multiple cells from different germ layers will migrate together and interact closely in a three-dimensional space. The matrix components are also remodeled. To construct complex organs, the cells and matrix components should be assembled at specific time points in correspondence with the timeline of organ development. This requires the development of highprecision iterative printing, i.e., the spatiotemporal secondary printing in the printed architectures, enabling the addition of cellular or extracellular matrix components at specific spatial locations and times in the printed structure. Advanced bioprinting iPSC-derived tissues are valuable tools for personalized drug screening and tissue regeneration. Bioprinting of iPSCs and disease modeling studies can significantly benefit the understanding of tissue development and pathogenetic mechanisms. This paper summarizes the state-for-art development in the field and provides a timely summary and guidance framework for future development for bioprinting-assisted personalized medicine. Acknowledgments The authors are sincerely grateful for funding from the National Key Research and Development Program of China (2018YFA0109000) and the National Natural Science Foundation of China (31871015). Funding The authors declare no competing financial interest.

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Part II CNS iPSC and Organoids

iPSCs-Derived Neurons and Brain Organoids from Patients Wanying Zhu, Lei Xu, Xinrui Li, Hao Hu, Shuning Lou, and Yan Liu

Contents 1 Introduction of iPSCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 iPSCs-Derived Neurons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Application of iPSCs-Derived Neurons for Disease Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 iPSCs-Derived Brain Organoids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Application of iPSCs-Derived Brain Organoids for Disease Modeling . . . . . . . . . . . . . . . . . . . . . 6 Applications for Transplantation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Induced pluripotent stem cells (iPSCs) can be differentiated into specific neurons and brain organoids by adding induction factors and small molecules in vitro, which carry human genetic information and recapitulate the development process of human brain as well as physiological, pathological, and pharmacological characteristics. Hence, iPSC-derived neurons and organoids hold great promise for studying human brain development and related nervous system diseases in vitro, and provide a platform for drug screening. In this chapter, we summarize the development of the differentiation techniques for neurons and brain organoids from iPSCs, and their applications in studying brain disease, drug screening, and transplantation.

W. Zhu · L. Xu · X. Li · H. Hu · S. Lou · Y. Liu (✉) School of Pharmacy, Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_657

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Keywords

Induced pluripotent stem cells (iPSCs) · Neurons · Brain organoids · Disease modeling · Transplantation therapy

1

Introduction of iPSCs

In 2006, Yamanaka et al. firstly reported reprogramming mouse somatic cells into induced pluripotent stem cells (iPSCs), which exhibited similar characteristics to embryonic stem cells by introducing four transcription factors – Oct4, Sox2, Klf4, and c-Myc (Takahashi and Yamanaka 2006). In the following year, the reprogramming of human fibroblasts into human induced pluripotent stem cells was reported independently by Shinya Yamanaka and James Thomson (Takahashi et al. 2007; Yu et al. 2007). Human iPSCs retain the genetic information of patients (Avior et al. 2016) and have the potential to differentiate into three germ layers (Takahashi et al. 2007; Yu et al. 2007) while avoiding the ethical issues of embryonic stem cells. Therefore, human iPSCs have been widely used to study gene regulation (Hockemeyer and Jaenisch 2016), disease modeling (Dimos et al. 2008; Ebert et al. 2009), drug screening (Tanaka et al. 2009) and in precision medicine (Gunaseeli et al. 2010) (Fig. 1). Since species differences make it difficult to completely recapitulate human disease phenotypes in animals such as mice (Li and Li 2012; Doncheva et al. 2021), and human primary nerve cells and brain tissue are

Fig. 1 Schematic of the neurons and organoids that derived from iPSCs and their potential application. IPSCs with the patients’ genetic information can be obtained by reprogramming. Then, neurons and organoids are derived from iPSCs in 2D and 3D culture, respectively. These models are widely used in gene editing, disease modeling, drug screening, and precision medicine

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difficult to obtain (Smith et al. 2019), which has become obstacle to the research of neurological diseases and brain science. The emergence of human iPSCderived neurons (Karumbayaram et al. 2009; Hu and Zhang 2009; Liu and Zhang 2010) and brain organoids (Lancaster et al. 2013) brings hope to overcome the dilemma. Hence, we overview the differentration of neurons and brain organoids from human iPSCs, and the research progress of disease modeling and precise treatment based on cell transplantation.

2

iPSCs-Derived Neurons

The development of vertebrate central nervous system composed of multiple neuronal subtypes that should go through the following procedures: induction of neural ectoderm from the embryonic ectoderm, the regional patterning of the neural plate and eventually differentiation of functional neurons from regionalized progenitors. It is the regional patterning principle that directs neural differentiation, which is defined by a set of morphogens with different gradients along anterior–posterior (A-P) and dorsal–ventral (D-V) axes: FGFs (fibroblast growth factors), WNTs (wingless-type MMTV integration sites), and retinoic acid (RA) for A-P patterning and WNTs, BMPs (bone morphogenetic proteins), and sonic hedgehog (SHH) for D-V patterning (Rallu et al. 2002; Rash and Grove 2007) (Wernig et al. 2008). Multiple neuronal lineages have been producted from human pluripotent stem cells (hPSCs) based on this theory (Fig. 2). As early as 2005, motoneurons from human embryonic stem cells (hESCs) were generated in the presence of RA at the early stage of neuroectodermal development and then differentiated by adding SHH. These motoneurons generated in vitro were electrophysiologically active and could form functional neuronal synaptic connections and carry out neuromuscular transmission (Li et al. 2005). Subsequently, iPSCs-derived motoneurons were generated in the patterning similar to

Fig. 2 Differentiation of neurons from human pluripotent stem cells (hPSCs). To date, a variety of neuronal lineages have been generated from hPSC, including motoneurons, dopaminergic neurons, serotonergic neurons, GABAergic neurons, and cholinergic neurons, which provide promising perspectives for further research

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hPSCs (Dimos et al. 2008; Karumbayaram et al. 2009; Hu et al. 2010). Notably, on the path to differentiate motor neurons, a small molecule, purmorphamine, as a SHH pathway agonist, was discovered to replace SHH, which had the benefits of chemical stability, broad availability, and lower cost. Using purmorphamine, the differentiation rate of motoneurons increases from 20% to over 90% (Hu et al. 2010; Li et al. 2008). Dopamine neurons have always been of particular interest among the hPSCsderived neurons because of their promising potential as a cell replacement therapy for Parkinson’s disease. Since dopamine neurons have a ventral midbrain identity, SHH and FGF8 are commonly involved in the in vitro differentiation of dopamine neurons from neural precursors (Yang et al. 2008; Yan et al. 2005). At first, the generated TH+ neurons did not exhibit sufficient regional identity, although they expressed markers of dopamine neurons. The discovery that dopamine neurons are floor plate cell origin inspired researchers to differentiate dopamine neurons through floor plate cells. While WNT is exclusively expressed in the ventral midbrain, the activation of the WNT pathway allows midbrain patterning of plate floor neural precursors (Prakash et al. 2006). Since then, functional midbrain dopamine neurons have been produced and more effort has been spent on improving purity, making alternative cellular therapy possible. They applied dual SMAD inhibition to improve efficiency, added FGF8b to stimulate caudal patterning, and use the floor plate marker CORIN to make cell sorting. Eventually, researchers have generated functional dopamine neurons with high efficiency and sufficient precision which, in principle, can be transplanted into PD animal models. Serotonergic neurons are differentiated from progenitors with ventral hindbrain identity. Given that hPSC tend to differentiate into forebrain progenitors in the absence of morphogens (Li et al. 2005), the production of serotonergic neurons requires morphogens that promote caudalization. One of the procedures of the differentiation is the activation of WNT pathway to induce caudalization, and SHH pathway to induce ventralization, and application of FGF4 to enhance differentiation from ventral hindbrain progenitors to serotonergic neurons (Lu et al. 2016; Vadodaria et al. 2019a). During the procedure, CHIR99021 is a kind of WNT pathway agonist, whose discovery is a turning point for the efficient generation of midbrain dopaminergic (DA) neurons from hPSC (Kirkeby et al. 2012; Lu et al. 2013). There is another strategy that can be used to generate serotonergic neurons directly from human fibroblasts in the presence of transcription factors. Both methods can attain functional serotonergic neurons, which have the capacity of spontaneous electrical activity, release serotonin, and are able to respond to stimulation or drugs that are known to regulate serotonin release (Lu et al. 2016; Vadodaria et al. 2016). Basal forebrain cholinergic neurons (BFCN) and γ-aminobutyric acid (GABA) interneurons both originate from the medial ganglionic eminence (MGE) and are involved in a variety of neurological disorders such as Alzheimer’s disease (AD), Huntington’s disease (HD), Down syndrome (DS), and schizophrenia (SCZ). Researchers have demonstrated the generation of robust forebrain GABA interneurons from hPSCs with small molecules and/or growth factors

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(SB-431542 + LSB + XAV939 + SHH + purmorphamine or SB-431542 + BMPRIA-Fc + DKK1 + purmorphamine + Y27632) (Maroof et al. 2013; Nicholas et al. 2013). Notably, the strategy that induces MGE progenitors to cholinergic neurons or GABA interneurons can substantially cut costs as well as enhance reliability and efficiency. Zhang and his colleagues adopted the use of small molecules, like SHH or purmorphamine, to pattern neuroepithelial cells into a nearly pure population of MGE progenitor cells expressing NKX2.1 and then produced cholinergic neurons or GABA interneurons with or without nerve growth factor (NGF) respectively (Liu et al. 2013a, b). Another advantage of this method is that merely transplantation of MGE progenitors into animals can generate cholinergic neurons and GABA interneurons in vivo, which showed electrophysiological activity. Additionally, the transcription factor LIM homeobox 6 (LHX6) appears to induce the MGE progenitors toward GABA interneuron identity and promotes the generation of functional human GABA interneuron subtypes, such as somatostatin (SST) and parvalbumin (PV) neurons (Yuan et al. 2018; Flandin et al. 2011). As for GABA neurons, some scientists have also patterned lateral ganglionic eminence (LGE) progenitors to medium spiny GABA neurons (MSN), using a method similar to MGE progenitor-engaged differentiation but employing different concentration of SHH. The transplantation of MSN into animal models has exhibited the potential to ameliorate deficiencies, giving promising support for alternative treatments for HD (Ma et al. 2012). In addition to cerebral neurons, cerebellar neurons can also be differentiated from hPSCs. The cerebellum has an abundant cell type in terms of granule cells and Purkinje cells. In 2007, researchers succeeded to differentiate granule cells and Purkinje cells in vitro by adding BMP4 and FGF4, which are essential to cerebellum development (Salero and Hatten 2007). Subsequently, the differentiation efficiency was improved by Sasai with the SFEBq (serum-free culture of embryoid body-like aggregates generated by quick reaggregation procedure) method (Eiraku et al. 2008). Thus, the future of replacement therapy for cerebellar-related diseases appears to be promising. In the past decade, the relentless development of hPSCs technology yielded surprising improvements and the technology to differentiate neurons from hPSCs became increasingly mature. To date, multiple types of functional neurons have been produced from hPSCs.

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Application of iPSCs-Derived Neurons for Disease Modeling

With the development of various methods for the differentiation of iPSCs-derived neurons in 2D culture, iPSCs-derived neurons were rapidly gaining attention in neural disease modeling. As early as 2008, iPSCs derived from amyotrophic lateral sclerosis (ALS) patients were differentiated into motor neurons, although their purity was only about 20% (Dimos et al. 2008). Park et al. generated iPSCs from Parkinson’s disease (PD) patients with genetic diseases in the same year, including

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Fig. 3 Application of iPSC-derived neurons for disease modeling. Neurons derived from iPSCs are widely used in neurodegenerative disease modeling since they carry the patients’ genetic information. Since the differentiation process corresponds to development stages, researchers used neurons derived from iPSCs to simulate neurodevelopmental disorders. Neurons derived from iPSCs may also display abnormal electrical activity of characteristic of psychiatric disorders that can be revealed by calcium imaging and electrophysiology. In addition, neurons derived from healthy iPSCs are used to study genetic diseases by using gene editing techniques such as CRISPR/Cas9

Parkinson’s disease (PD), HD, DS (Park et al. 2008). These studies make it possible to reproduce normal and pathological neural phenotypes in vitro, helping to study diseases and develop drug targets (Fig. 3). Studies of iPSCs-derived neurons differentiated from patients with neurodegenerative diseases have been continually reported. ALS is a neurodegenerative disease caused by the selective death of upper and lower motor neurons (Renton et al. 2014) and iPSCs-derived motor neurons with genetic information from ALS patients provide a promising in vitro model for familial and sporadic ALS (Dimos et al. 2008; Chen et al. 2014a; Sances et al. 2016). Other motor neuron diseases are also modeled by iPSCs-derived neurons, such as spinal muscular atrophy (SMA) (Ebert et al. 2009; Wang et al. 2013) and frontotemporal dementia (FTD) (Almeida et al. 2012). HD is an autosomal dominant monogenic neurodegenerative disease with exon CAG repeats in the huntingtin (HTT) gene (Ross and Tabrizi 2011). Striatal

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medium spiny neurons (MSNs) are the cell types most susceptible to degeneration in HD, and the HD iPSCs Consortium was the first to report an increased death rate of HD iPSCs-derived MSNs (HD iPSC Consortium 2012). There are also studies utilizing HD iPSCs-derived neurons as a drug screening platform and these found that miR196a reduces mHtt aggregation by mediating the ubiquitin–proteasome pathway (Cheng et al. 2013), while P110-TAT, a peptide inhibitor of dynein-related protein (Drp1), reduces mitochondrial hyperfission and cell death in HD (Guo et al. 2013). Alzheimer’s disease (AD) is characterized by neurofibrillary tangles containing hyperphosphorylated tau (pTau) and beta-amyloid plaques (Montine et al. 2012) and iPSCs-derived neurons are widely used in vitro for modeling AD, whether familial (Yagi et al. 2011) or sporadic (Israel et al. 2012; Kondo et al. 2013; Oksanen et al. 2017). Another neurodegenerative disorder with both genetic and sporadic pathogenesis is PD, which is characterized by the loss of dopaminergic neurons in the substantia nigra (Kalia and Lang 2015). IPSCs-derived neurons derived from familial patients (Byers et al. 2011; Cooper et al. 2012) or isogenic model (Jiang et al. 2012; Ryan et al. 2013) are well suitable for PD disease modeling. In addition to neurodegenerative diseases, iPSC-derived neurons are also used to recapitulate a variety of neurodevelopmental disorders, such as autism spectrum disorder (ASD) (Iakoucheva et al. 2019) and DS. Many studies have used iPSCderived neurons to model neurodevelopmental disorders including fragile X Syndrome (Urbach et al. 2010; Sheridan et al. 2011; Doers et al. 2014; Telias et al. 2015; Kumari et al. 2015), Timothy syndrome (Paşca et al. 2011), Rett syndrome (RTT) (Ananiev et al. 2011; Marchetto et al. 2010; Djuric et al. 2015; Kim et al. 2011; Williams et al. 2014), SHANK3-associated Phelan–McDermid syndrome (Shcheglovitov et al. 2013; Bidinosti et al. 2016), and non-syndromic ASD (Griesi-Oliveira et al. 2015). DS is a neurodevelopmental disorder caused by trisomy 21. It is reported that rescue of the DSCAM-PAK1 pathway alleviates neuronal migration defects (Huo et al. 2018) and mitochondrial dysfunction (Xu et al. 2022) in DS iPSC-derived GABAergic interneurons. IPSCs-derived neurons also contribute to the simulation of other neurodevelopmental disorders such as lissencephaly (Bamba et al. 2016; Shahsavani et al. 2018) and alternating hemiplegia of childhood (Snow et al. 2020). Furthermore, in the study of psychiatric disorders iPSCs-derived neurons carrying genetic information of patients are of great significance for elucidating the etiology of these conditions. Schizophrenia (SCZ) is a common mental illness and studies found that SCZ iPSCs-derived neurons showed reduced neural connectivity (Brennand et al. 2011) and abnormal expression of genes associated with cytoskeletal remodeling or oxidative stress (Brennand et al. 2015). It has been reported that the disrupted in schizophrenia 1 (DISC1) gene causes synaptic vesicle release defects in forebrain neurons derived from SCZ iPSCs (Wen et al. 2014). Bipolar disorder (BIP) is another psychiatric disorder with similar prevalence, age of onset, symptom severity, and response to drug therapy to SCZ, but more focused on affecting mood (Hill 2012; Laursen 2011; Lichtenstein et al. 2009). BIP iPSCs-derived neurons were developed to investigate the cellular phenotypes of hippocampal dentate gyrus-like neurons and hyperactive action-potential firing in BIP iPSCs-

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derived neurons was selectively reversed by lithium treatment (Mertens et al. 2015). Subsequent studies also divided BIP iPSCs-derived neurons into two subpopulations based on their different responses to lithium (Chen et al. 2014b; Stern et al. 2018). iPSCs-derived neurons from patients of major depressive disorder (MDD), another common mental illness, presented with altered serotonergic circuits (Vadodaria et al. 2019a) and hyperactivity induced by serotonin (Vadodaria et al. 2019b). The rapid development of gene editing technology makes it possible to specifically introduce genetic edition in iPSCs. Programmable site-specific nuclei, including zinc finger nuclei (ZFN) (Hockemeyer et al. 2009; Zou et al. 2009), transfer activator-like effector nuclei (TALENs) (Christian et al. 2010; Hockemeyer et al. 2011) and particularly the CRISPR-Cas9 system (Cong et al. 2013; Perez-Pinera et al. 2013; Smith et al. 2014), are widely used in gene editing of ESCs and iPSCs. These gene editing techniques can correct the pathogenic gene mutation in iPSC from patients, and can also introduce specific gene mutations into wild-type iPSCs for disease modeling and to explore the pathogenesis. For example, genetic correction of mutations in Niemann–Pick type C patient-specific iPSCs leads to rescue of metabolic defects in cholesterol metabolism and autophagy (Maetzel et al. 2014). Correspondingly, iPSCs modeling heterozygous and homozygous dominant earlyonset AD have been generated using CRISPR-Cas9, resulting in mutations in amyloid precursor protein (APP (Swe)), presenilin-1 (PSEN1 (M146V)). Subsequently derived cortical neurons show genotype-dependent disease-related phenotype (Paquet et al. 2016). Further, RTT iPSCs-derived neurons of MeCP2 mutations at various distinct sites were constructed from the same cell line and the potential therapeutic targets were reported according to the mutant iPSCs (Xiang et al. 2020). Gene editing is a powerful tool for studying diseases caused by early-onset single gene mutations (single gene diseases) and late-onset diseases with complex pathogenicity caused by multiple genetic and environmental factors. Many neurological diseases lack appropriate animal models for drug screening, and it is difficult to use animal models to conduct high-throughput screening of small molecule libraries (Avior et al. 2016). Therefore, iPSCs-derived neurons are favored in drug discovery of neurological diseases. Two main drug screening strategies, candidate drug screening and high-throughput screening of small molecule libraries, are employed to screen drugs using iPSCs-derived neurons as a disease model. Candidate drug screening is applicable to diseases with clear pathogenic mechanisms or therapeutic effects in other models. In this way, a clear set of compounds is applied to iPSCs-derived neurons to identify the best drugs. Lee et al. first used familial dysautonomia iPSCs to verify the effectiveness of candidate drugs to improve neuronal differentiation and migration (Lee et al. 2009). Since then, several additional screens of candidate drugs for neural diseases using iPSCsderived neurons have been reported (Xu et al. 2022; Yahata et al. 2011; Egawa et al. 2012). For example, among four candidate compounds to cure the abnormal ALS motor neuron phenotype, instead of trichostatin A, spliceostatin A and garcinol, anacardic acid was found to be able to alleviate symptoms (Egawa et al. 2012). Another strategy, high-throughput screening of small molecule libraries, enables the screening of over a million compounds (Barmada et al. 2014). The best approach

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may be to combine high throughput with screening of resulting candidate drugs. For instance, Barmada et al. first performed high-throughput screening on ALS mouse neurons and then screened candidate compounds for ALS iPSCs-derived motor neurons (Barmada et al. 2014). Similarly, CHIR99021 was first shown to improve mitochondria by high-throughput screening in mouse horizontal cells (HdhQ111) and was then verified as a candidate compound in HD iPSCs-derived neurons (Hu et al. 2021). However, it is important to remember that iPSCs-derived neurons still do not completely represent all factors that affect the pathogenesis of diseases, such as the spatial structure of organs and intercellular interactions, which limits the application of iPSCs-derived neurons in disease modeling and drug screening.

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iPSCs-Derived Brain Organoids

iPSCs-derived neuronal 2D culture systems aid the research of nervous system diseases. However, 2D culture systems cannot simulate the 3D internal environment of the human brain, nor can they reflect the interaction between cells at the 3D level, therefore, a 3D culture system was developed (Fig. 4). The 3D culture system is possible since hPSCs in vitro can spontaneously form 3D cell groups – the embryoid body. Subsequently, these suspension-cultured embryoid body aggregates are gradually differentiated into several polarized neural precursor cells with rosette structures, which are then resuspended into neurospheres. After that, these neurospheres are embedded in Matrigel containing extracellular matrix proteins of neurons. The generation of this technology not only makes up for the defects of the traditional 2D cell culture system that cannot simulate the complex structure of brain tissue and microenvironment in vivo. It also breaks through the limitation that animal models lack the genetic characteristics, brain regions and functions of human beings, and consequently cannot truly and comprehensively simulate the embryology of the human brain and the development of diseases (Di Lullo and Kriegstein 2017; Chiaradia and Lancaster 2020). This technology is an important tool to study the development and evolution of the human brain, explore the interaction between different brain regions, brain and other organs, and carry out disease simulation and drug screening in vitro. In 2008, Eiraku et al. established the serum-free embryoid bodies (SFEB) method, in which layered spheres are cultured similar to structure of the cerebral cortex (Eiraku et al. 2008). Then, Eiraku et al. induced the 3D structure of the optic cup by adding matrigel to the culture system (Eiraku et al. 2011). In 2012, Mariani et al. induced human iPSCs into a 3D multilayer cortical structure and demonstrated that its gene expression profile was similar to that of human embryonic telencephalon (Mariani et al. 2012). These works have laid a foundation for the generation of brain organoid technology and, in 2013, Lancaster et al. were the first to report a culture scheme for human brain organoids (Lancaster and Knoblich 2014; Lancaster et al. 2013). The neural differentiated embryoid body was embedded in Matrigel, and neural development related regulatory factors were added to the suspension culture process. Finally, the embryoid body was transferred to a bioreactor. After

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Fig. 4 Summary of major milestones in the development of iPSCs-derived brain organoids. The advent of iPSCs technology has enabled the production of 3D brain organoids, which are considered to be a more advanced alternative than 2D culture systems due to their better representation of the structure and complexity of the human brain. Lancaster et al. produced brain organoids including retina, forebrain, midbrain, hindbrain, and choroid plexus by embedding embryoids into the extracellular matrix (ECM). Subsequently, by the addition of specific factors, the fate of progenitor cells was manipulated to create regionally specified brain organoids. The emergence of this technology has also promoted the production of assembloids, which can simulate the interaction between different brain regions through the fusion of two or more brain regions

long-term neural differentiation culture, human brain organoids with the appropriate 3D structure were obtained. This work is the first to construct brain organoids using hPSCs and to use brain organoids to study the process of brain development as a disease model, which is a significant milestone. In 2021, Giandomenico et al. improved the method and produced telencephalic organoids that can be cultured for a long time by making smaller embryoid body spheres or using fiber-micro scaffolds to increase the surface area, as well as slice culture (Giandomenico et al. 2021). After a long time of culture, mature neurons and astrocytes were generated, which is conducive to the study of events at a later stage of cortical development. Furthermore, the neuronal cells in the brain organoids can be labeled with exogenous plasmids. This work is of great significance to the modeling of neurodevelopmental diseases. Whole-brain organoids contain a variety of cell lineages, which is conducive to simulating the connection between different brain regions. However, the induction process mainly depends on the intrinsic ability of induced stem cells to differentiate, resulting in high variability and heterogeneity in different cell lines or different batches. By adding small chemical molecules to regulate SMAD, WNT, SHH, and other signaling pathways during the induction process, researchers have generated directionally induced brain organoids (Qian et al. 2018). So far, researchers have been able to cultivate regional-specific brain organoids, such as the cerebral cortex, forebrain, midbrain, hypothalamus, cerebellum, and hippocampus (Kelley and Pasca

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2022). In addition, by ectopically expressing human ETS variant 2 (ETV2) in human embryonic stem cells or fusing the brain organoids and the neural-specific vascular organoids generated by initial transient mesoderm induction, vascular-like network structures were induced in cerebral cortical organoids, creating the brain organoids with the vasculature (Cakir et al. 2019; Sun et al. 2022). The emergence of the technology to cultivate regionally specified cerebral organoids has also promoted the production of assembloids from different brain regions, which can better simulate the anatomical structure, physiological characteristics, interaction between brain regions, and the regulatory relationship between the brain and other tissues and organs, providing a platform for studying the formation of complex neural structures. For example, the fusion of dorsal forebrain organoids and ventral forebrain organoids can simulate the migration of inhibitory interneurons (Bagley et al. 2017; Birey et al. 2017). Xiang et al. established a thalamic organoid culture method and fused thalamic organoids with frontal cortex organoids to study the neural projection of thalamic to cortex (Xiang et al. 2019). Recently, a research group has constructed organoids of the cerebral cortex and hindbrain/spinal cord and fused them with human skeletal muscle organoids to form functional human 3D cortico-motor assembloids (Andersen et al. 2020). Each step of the researchers’ exploration of the 3D brain organoid model is striving to build an in vitro model closer to the real human brain, so as to further study the development and evolution of the human brain in vitro, explore the interaction between different brain regions, the brain and other organs, and provide an important tool for disease modeling and drug screening in vitro.

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Application of iPSCs-Derived Brain Organoids for Disease Modeling

Although 2D cultured cells and animal models have been widely used in the study of neurological diseases by the researchers all over the world, 3D cultured human brain organoids are gradually showing the unique advantages in this field (Di Lullo and Kriegstein 2017; Tang et al. 2022). Brain organoids can model neuro developmental diseases and degenerative diseases contributed by self-organizing characteristics and a genetic background similar to the patients (Fig. 4). Neurodevelopmental disorder is a kind of central nervous system dysfunction caused by abnormal brain development during the embryonic stage, resulting in widespread and diverse neurobehavioral disorders. Using animal models and fetal materials to study these diseases may present researchers with problems due to species differences or ethical concerns. As a new platform for disease research and drug screening, brain organoids can effectively avoid these problems. Since the cerebral organoids were first established, they were applied to research into primary microcephaly, which is a kind of neurodevelopmental disorder. Cerebral organoids were generated from the patient-derived iPSCs that carry a mutation in CDK5RAP2 (Lancaster et al. 2013). Patients-derived cerebral organoids were smaller, and their neuro progenitor cells showed pathological phenotypes including reduced

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proliferation and early differentiation. The researchers also used CRISPR/Cas9 technology to disrupt the CDK5RAP2 gene in control cerebral organoids and the results showed similar pathological phenotypes. Thereafter, brain organoids have been widely used in studies of neurodevelopment diseases. The generation of brain organoids from the DS patients-derived iPSCs contributed to significant advances in the pathophysiology of the disease. It has been found that the OLG2 plays a key role in the over-production of inhibitory neurons in DS brain organoids, and suppression of OLG2 expression can effectively improve these symptoms. This study suggests that it may be possible to reverse abnormal brain development of the embryo and improve postnatal cognitive function in DS patients (Xu et al. 2019). Brain organoids derived from DS patients-iPSCs also showed reduced abnormal neurogenesis and impaired mitochondrial function. Through interference with the DSCAM/PAK1 pathway, the cortical development defects of DS can be reversed (Xu et al. 2022; Tang et al. 2021). In addition, brain organoids are also being used for research into disorders such as autism spectrum disorder, Timothy syndrome, tuberous sclerosis complex, and Fragile X syndrome (Kang et al. 2021; Miyoshi et al. 2021; Eichmüller et al. 2022; Birey et al. 2022). Neurodegenerative diseases are a class of diseases characterized by degeneration of the central and peripheral nervous systems leading to progressive structural and functional degeneration, including AD, PD, Huntington’s disease, and amyotrophic lateral sclerosis. 3D cultured human brain organoids based on pluripotent stem cell technology open a new way to study these diseases. Beta-amyloid plaques and tau tangles are the main pathological features of AD. These pathological processes lead to neuronal degeneration, synaptic and neuronal loss, and ultimately atrophy of the nervous system. In brain organoids derived from human iPSCs, researchers found that mutations in β-amyloid precursor protein and presenilin-1 induced significant extracellular deposition of β-amyloid (Raja et al. 2016). The link among pathogenic APOE genotype, Aβ and tau pathology and neurodegeneration was recapitulated by using cerebral organoids derived from AD patient’s iPSCs, suggesting that targeting APOE ε4 may be an effective treatment (Zhao et al. 2020). Recently, sporadic AD was mimicked by exposing brain organoids to human serum as blood-brain barrier leakage is a well-known risk factor for AD. The serum-exposed brain organoids recapitulated many AD-like pathologies, including increased amyloid beta (Aβ) aggregates and phosphorylated microtubule-associated tau protein (p-Tau) level, synaptic loss, and neural network impairment (Chen et al. 2021). In addition to AD, research into PD has also benefitted from brain organoids. The selective loss of midbrain dopaminergic neurons in the substantia nigra pars compacta and the presence of intraneuronal protein inclusions, termed Lewy bodies, are the main pathological features of the PD, which are difficult to recapitulate in mouse models. Recently, midbrain organoids had been developed for simulating the main pathological characteristics of PD for the first time. Using the CRISPR/Cas9 system, researchers established the human ESC lines with GBA1 depletion, which matches the genetic trait found in PD patients. Brain organoids generated from these stem cells displayed both Lewy body production, nigra dopamine neuron loss (Jo et al. 2021). Also, midbrain orgnoids derived from PD patient iPSC showing

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the upregulation of α-synuclein were generated to study the correlation between the pathogenesis of PD and vesicular chemical storage (Zhu et al. 2022). In addition to neurodevelopmental and neurodegenerative diseases, the recent global COVID-19 pandemic has also drawn attention to the neurological harm of viral infections. Brain organoids were used to study the effects of Zika virus infection of the nervous system on the brain (Qian et al. 2016) and were also used to screen for effective drugs. Researchers employed brain organoids to perform drug screening for approximately 6,000 compounds, including FDA approved drugs, clinical trial candidates, and pharmacologically active compounds. Emricasan and Niclosamide were found to rescue Zika-induced apoptosis of cortical neural precursor cells and effectively inhibit Zika-virus replication, thus identifying lead compounds for anti-Zika-virus drug development (Xu et al. 2016). The global spread of a novel coronavirus caused a large number of infections and deaths. Infected patients experience not only respiratory symptoms but also neurological symptoms, including headaches, insomnia, and seizures. Brain organoids were used to demonstrate for the first time that the novel coronavirus can target cortical neurons and neural progenitor cells (Zhang et al. 2020). In addition to disease research, using human brain organoids to study human evolution has become a new direction of research in recent years. There are significant differences between the brains of humans, ancient humans and non-human primates, including the number of neurons. Through establishing chimpanzee, macaque, and human brain organoids, scientists revealed several human-specific gene expression patterns, which provide a basis for further exploration of the genetic regulatory mechanisms that evolutionarily distinguish humans from other primates (Pollen et al. 2019; Pinson et al. 2022; Benito-Kwiecinski et al. 2021). In summary, the neurologic disease models established by using human brain organoids are powerful tools to explore the pathogenesis of human neurodevelopmental defects, degenerative diseases, and infectious diseases, and also provide a potent technical platform for screening therapeutic drugs and discovering therapeutic strategies (Fig. 5).

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Applications for Transplantation

The brain is the most complex and sophisticated organ in animals. Therefore, the adoption of traditional therapeutic approaches to central nervous system (CNS) disorders often encounters numerous challenges. In recent years, cell transplantation has been extensively proposed and explored as an emerging therapeutic option and a new prospect for the treatment of CNS disorders including degenerative diseases, traumatic brain injury, and stroke (Fig. 6). The origin of cell transplantation can be traced back to the nineteenth century and involved subcutaneous injection of fluid from animal testicles to restore sexual potency in patients (Lefrère and Berche 2010). Although this experiment was criticized and was considered unscientific by most scientists at the time, it may be the first instance of cell transplantation therapy. In 1956, the American doctor

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Fig. 5 Applications of iPSCs-based human brain organoids. Due to their self-organizing characteristics and potential to share genetic background with affected patients, brain organoids based on the human iPSCs can model nervous system diseases, including neuro-developmental, neuro-degenerative, and neuro-infectious diseases. In addition to disease research, using human brain organoids to study human evolution has become a new direction of research in recent years

E. Donnall Thomas performed the first successful bone marrow transplantation in post-radiation leukemia patients (Park et al. 2015), thus initiating the modern era of cell transplantation therapy and opening the gate for cell transplantation to move from basic research to clinical care. However, these early-stage cell transplantation therapies were faced with the dilemma transplantable cells were a scarce resource, and further that immunocompatibility was an important limiting factor for success of transplantation therapy. Excitingly, as is mentioned above, since James Thomson and Yoshi Yamanaka pioneered hPSCs technology (Thomson et al. 1998; Yu et al. 2007; Yamanaka 2008), human pluripotent stem cells (hPSCs) transplantation is a promising treatment. This approach represents a groundbreaking strategy in this field, with fewer concerns about cell sources and quantity, or immunocompatibility. One of the most significant uses of cell transplantation lies in its capability to treat central degenerative diseases. The major pathology of PD is progressive loss of dopaminergic (DA) neurons in the midbrain, which may be treatable with transplantation therapy (Barker et al. 2015). Thus, along with the development of hPSCs, transplantation with the application of DA neurons differentiated from hPSCs has been utilized. Researchers have transplanted hESCs or iPSCs-derived DA neurons and neuronal precursor cells into rodent and primate PD models, respectively, and found that the exogenous grafts are capable of integrating with the host’s cells and improve the behavior of PD model animals (Chen et al. 2016; Cardoso et al. 2018;

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Fig. 6 Cell transplantation and replacement therapy based on neurons, progenitor cells and brain organoids have undergone a long period of fundamental investigation and have now been demonstrated to be capable of brain repairing after transplantation into human brain, as well as for the construction of a novel human-rodent chimeric brain model for further experimental studies

Wang et al. 2018; Kikuchi et al. 2017). Recent reports also demonstrated that autologous transplantation of iPSCs-derived midbrain DA neurons in a monkey model of PD resulted in extensive axon as well as the recovery of behavioral functions in the treated monkeys (Emborg et al. 2013; Tao et al. 2021). In addition to PD, cell transplantation has also been demonstrated to improve learning and memory of animals with Huntington’s disease and in learning and memory deficits models (Ma et al. 2012; Liu et al. 2013b; Martinez-Losa et al. 2018). For a long time, most cell transplantation therapies used neurons or progenitor cells obtained in 2D culture. However, the tissues of normal multicellular organisms are 3D structures. In 2013, Lancaster et al. proposed a method for constructing cerebral organoids in a 3D culture system, starting the exploration of organoids to simulate the development of different brain regions (Martinez-Losa et al. 2018). Since then, there have been many attempts to apply organoids to research on human brain development and disease. In 2018, Fred H Gage instituted a procedure for transplanting human brain organoids into the adult mouse brain. The in vivo grafted organoids revealed gradual neuronal differentiation and maturation, axonal growth into several regions of the host brain, along with integration between grafts and the host brain (Mansour et al. 2018). Furthermore, by optimizing the organoid culture protocol, small-sized cerebral organoids were efficiently generated. After transplanting them into the medial prefrontal cortex of mice, the organoids were observed to survive and functionally integrate into the original neural circuits through the formation of bidirectional synaptic junctions with the host neurons of the mice (Dong et al. 2021). These studies confirmed the potential use and benefits of organoid transplantation for cell replacement therapy. On the basis of these prior successful transplantation experiments, a concept of a human-mouse chimeric brain model is gradually being developed. By transplanting

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iPSCs-based neural progenitors or organoids into the mouse brain, which provides an in vivo microenvironment, including metabolic support through the vascular system, a well-integrated animal model for research into circuit integration mechanisms, neuronal growth, and axonogenesis can be established under physiological conditions. This concept was first employed in the investigation of DS pathophysiology. After transplantation of DS GABAergic progenitors into the mouse medial septum, survival and differentiation of DS GABAergic interneurons derived from both disease and natural iPSCs were demonstrated in the mouse brain (Huo et al. 2018). Since then, there have been an increasing number of relevant studies using the human-mouse chimeric brain. By combining this with innovative new technologies, it is possible to build completely new experimental systems for the study of many diseases affecting human brain development. Through in vivo imaging of human-derived pyramidal neurons differentiated from iPSCs in chimeric mice Vincenzo De Paola’s team has provided insights into the earliest stages of human axonal, synaptic, and network activity development and revealed the cellular phenotype of DS (Real et al. 2018). Jiang Peng’s group has also employed this approach to study DS. By manipulating ventral forebrain neural progenitors derived from DS patient iPSCs and implanting them into immunodeficient mice to establish a neuronal chimeric mice model, the investigators were able to show that DS hiPSC-derived brain organoids over-produce specific subclasses of GABAergic interneurons, leading to impaired recognition memory in these neuron-chimeric mice (Xu et al. 2019). During the further investigation of DS, with human iPSC-based brain organoids and mouse chimeras, as well as the usage of scRNA-seq after the organoids-mouse brain integration, it was revealed that DS microglia manifested enhanced synaptic pruning, which altered the synaptic function of neurons (Jin et al. 2022). Additional results have also been reported using similar protocols and approaches to establish mouse chimera models and have provided insight into neuronal differentiation and maturation, glial cell formation, microglia integration. Chimeric mouse models have also been used to demonstrate axonal growth into multiple regions of the host brain and their integration into sensory and motivation-related circuits. These findings indicate that transplantation derived neurons mature and engage host circuits that control behavior (Mansour et al. 2018; Revah et al. 2022). Cell transplantation and replacement therapy holds enormous promise for a better understanding of human physiological development and pathology of neurodegenerative diseases, which benefits both basic scientific research and the development of treatments for disease. It is hoped that these insights will provide a new outlook for many CNS neurodegenerative conditions and other currently intractable diseases. In the meantime, studies and clinical trials are already under way. Further research is still needed to overcome difficulties in cell transplantation therapy, which are the guideposts to lead us on our continuation of research and exploration.

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Conclusion

In summary, iPSCs-derived neurons and brain organoids have made great progress in the studies on human brain development and disease mechanism. However, iPSCs-derived neurons still have structural deficits, iPSCs-derived brain organoids cultivation still faces technical challenges, and the iPSCs-derived neurons and brain organoids still cannot fully simulate the complex structure and function of the brain. As a new biological culture technology, iPSCs-derived neurons and brain organoids have great research potential and application value in the research of human brain development, disease mechanism, transplantation therapy, and drug screening. The construction and application of iPSCs-derived neurons and brain organoids will continue to be a research focus in the medical sciences, and the use of iPSCsderived neuron and brain organoid transplants to cure neurological diseases remains an important direction in the development of future precision medicine treatments.

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Retinal Ganglion Cells in a Dish: Current Strategies and Recommended Best Practices for Effective In Vitro Modeling of Development and Disease Kang-Chieh Huang, Cátia Gomes, and Jason S. Meyer

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Established Approaches for the Directed Differentiation of Human RGCs . . . . . . . . . . . . . . . . . 3 Essential Characteristics for hPSC-RGCs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Modeling RGC Neurodegeneration with hPSCs and the Necessity for Proper Controls . . . 5 Future Directions for Advancing hPSC-RGC Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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K.-C. Huang Department of Biology, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA C. Gomes Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA J. S. Meyer (✉) Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA Department of Pharmacology and Toxicology, Indiana University School of Medicine, Indianapolis, IN, USA Department of Ophthalmology, Indiana University School of Medicine, Indianapolis, IN, USA e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_642

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Abstract

The ability to derive retinal ganglion cells (RGCs) from human pluripotent stem cells (hPSCs) provides an extraordinary opportunity to study the development of RGCs as well as cellular mechanisms underlying their degeneration in optic neuropathies. In the past several years, multiple approaches have been established that allow for the generation of RGCs from hPSCs, with these methods greatly improved in more recent studies to yield mature RGCs that more faithfully recapitulate phenotypes within the eye. Nevertheless, numerous differences still remain between hPSC-RGCs and those found within the human eye, with these differences likely explained at least in part due to the environment in which hPSC-RGCs are grown. With the ultimate goal of generating hPSC-RGCs that most closely resemble those within the retina for proper studies of retinal development, disease modeling, as well as cellular replacement, we review within this manuscript the current effective approaches for the differentiation of hPSCRGCs, as well as how they have been applied for the investigation of RGC neurodegenerative diseases such as glaucoma. Furthermore, we provide our opinions on the characteristics of RGCs necessary for their use as effective in vitro disease models and importantly, how these current systems should be improved to more accurately reflect disease states. The establishment of characteristics in differentiated hPSC-RGCs that more effectively mimic RGCs within the retina will not only enable their use as effective models of RGC development, but will also create a better disease model for the identification of mechanisms underlying the neurodegeneration of RGCs in disease states such as glaucoma, further facilitating the development of therapeutic approaches to rescue RGCs from degeneration in disease states. Keywords

Differentiation · Disease modeling · Retinal ganglion cell · Stem cell

1

Introduction

Retinal ganglion cells (RGCs) are projection neurons of the central nervous system (CNS) that play a primary role in the transmission of visual information between the retina and the brain. RGCs receive visual input from photoreceptors through bipolar cells or amacrine cells and connect with downstream targets in the brain via long axonal projections (Crair and Mason 2016; Erskine and Herrera 2014). The function of RGCs is also dependent upon their highly compartmentalized structure, in which RGC dendrites are found within the inner plexiform layer (IPL) in the retina, the RGC soma integrates signals within the ganglion cell layer (GCL), and finally RGC axons project toward the brain, initially within the nerve fiber layer along the inner retinal surface before entering the optic nerve and exiting the eye (Conforti et al. 2007; Whitmore et al. 2005; Yu et al. 2013). The proximal part of the RGC axon

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remains unmyelinated until the optic nerve head (ONH) through the lamina cribrosa and then becomes myelinated and eventually forms synaptic contacts with downstream neurons primary in the lateral geniculate nucleus (LGN), superior colliculus (SC), and pretectal areas of the brain (Parmhans et al. 2021; Syc-Mazurek and Libby 2019). Notably, glial cells including astrocytes and microglia interact with RGCs along each RGC compartment in different ways. For example, astrocytes in the nerve fiber layer (NFL) within the inner retina secrete neurotrophic factors that are responsible for RGC development, and microglia regulate synaptic pruning as well as phagocytosis of dead RGCs within the IPL, GCL, and NFL (Anderson and Vetter 2019; Au and Ma 2022; Vecino et al. 2016). As the sole projection neurons that convey visual signals from the eye to the brain, RGCs are long (~50 mm), postmitotic projection neurons that are particularly susceptible to acute injury or chronic neurodegeneration characteristic of glaucoma or other optic neuropathies, leading to irreversible progressive loss of vision (Yu et al. 2013). Historically, research in rodent models has successfully investigated many mechanisms of RGC injury in a variety of disease states (Agostinone et al. 2018; Belforte et al. 2021; Duan et al. 2015; Tran et al. 2019), and several studies have analyzed cellular mechanisms underlying RGC neurodegeneration and identified factors that can promote RGC regeneration in experimental rodent models (Agostinone et al. 2018; Belforte et al. 2021; Jacobi et al. 2022; Lindborg et al. 2021). While these studies have provided a wealth of knowledge pertaining to the mechanisms associated with RGC damage, more recent studies have revealed numerous differences between RGCs from rodent and primate sources (Peng et al. 2019), as well as significant variances in glia across rodents and primates (Galatro et al. 2017a, b; Hodge et al. 2019; Oberheim et al. 2009; Patir et al. 2019; Smith and Dragunow 2014; Zhang et al. 2016), suggesting that perhaps at least some of these mechanisms may not necessarily be conserved in patients. Thus, a critical need exists to develop a complementary model with which we can compare findings in experimental rodent models and also confirm phenotypes in a more human-relevant cellular system. Human pluripotent stem cell (hPSC)-derived retinal organoids have been developed as a tool for understanding human retinal development as well as modeling retinal diseases (Capowski et al. 2019; Fligor et al. 2018; Meyer et al. 2011; Nakano et al. 2012; Wahlin et al. 2017). hPSCs can be further subdivided as either human embryonic stem cells (hESCs) or human induced-pluripotent stem cells (hiPSCs), but collectively, hPSCs have the ability to give rise to all cell types of human tissues. As hiPSCs can be generated through the reprogramming of adult somatic cells such as fibroblasts or peripheral blood mononuclear cells (Takahashi et al. 2007; Yu et al. 2007), they can be used as a novel in vitro model of genetic contributions to disease when derived from patient samples harboring these genetic variants. Historically, it has been exceptionally difficult to obtain human RGCs for the study of neurodegenerative features and as such, hPSCs have become a valuable resource to produce retinal cells for studying human retinogenesis, drug screening, disease modeling, or transplantation. We and others have previously demonstrated the generation of three-dimensional retinal organoids from hPSCs in a stepwise

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manner, mimicking many temporal and spatial characteristics of human retinogenesis, consisting of all of the major cell types of the human retina (Capowski et al. 2019; Eldred et al. 2018; Fligor et al. 2018; Meyer et al. 2009; Nakano et al. 2012; Ohlemacher et al. 2015; Wahlin et al. 2017; Zhong et al. 2014). Alternatively, it may often be preferable to study cell autonomous features of retinal diseases, in which case it becomes more desirable to isolate specific cell types such as RGCs into two-dimensional cultures, with specific culture medium formulations that promote RGC survival, neurite outgrowth, and functional maturation (Gomes et al. 2022; Ohlemacher et al. 2016; Teotia et al. 2019; Vander Wall et al. 2019). We and others have previously demonstrated the use of hPSC-RGCs for studying RGC development and modeling glaucoma-associated neurodegeneration in this manner (Gomes et al. 2022; Teotia et al. 2017b, 2020; Vander Wall et al. 2019, 2020). Moreover, as improvements are continually made to hPSC-RGC differentiation protocols, it has become increasingly possible to use these cells for drug screening as well as for transplantation with the goal of RGC replacement (Patel et al. 2020; Zhang et al. 2021). However, as recent studies have demonstrated differential gene signatures between hPSC-RGCs compared to RGCs found within the fetal or adult retina (Sridhar et al. 2020), there are likely some challenges to further adapt hPSC-RGCs to create the most physiologically relevant model for human RGC neurodegeneration. Among the possibilities that may account for the differences between human RGCs and hPSC-RGCs is the environment in which they grow and mature. hPSC-RGCs typically lack the compartmentalized and polarized structure of RGCs in vivo, including the interactions with other cell types. More so, while RGCs interact with many types of neurosupportive cells in vivo including astrocytes, microglia, and vascular cells, these cells are not typically found within retinal organoids or other hPSC-RGC cultures. Without the support of these surrounding cells, these cultures are likely limited in their ability to provide the factors necessary to support the maturation of hPSC-RGCs in vitro. To create the most physiologically relevant hPSC-RGCs and to be able to mimic the neurodegenerative conditions that affect RGCs within the patient eye, we here discuss current RGC differentiation systems as well as current applications for modeling RGC diseases with hPSCRGCs. Further, we provide our opinions on how to reduce variability across experimental groups by characterizing the features required for the definitive identification and characterization of hPSC-RGCs, as well as the necessary approaches for the advancement of hPSC-RGCs toward more translational applications.

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Established Approaches for the Directed Differentiation of Human RGCs

Approaches have been developed by multiple groups to successfully generate hPSCRGCs appropriate for a variety of applications including in vitro studies of retinogenesis, disease modeling, and cell replacement related to glaucoma or other optic neuropathies (Risner et al. 2021; Sluch et al. 2017; Teotia et al. 2017b, 2020; Vander Wall et al. 2019, 2020). These protocols to derive hPSC-RGCs can be

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Fig. 1 Schematic summary of current methods to derive RGCs in vitro

divided into three main categories: (1) 2D differentiation, in which the entire differentiation process from hPSCs to RGCs is conducted in adherent cultures for the duration of the differentiation process; (2) 3D differentiation, in which at least part of the differentiation process (especially the latter stages) occurs as suspension cultures to better simulate the spatial features of the developing neural environment, particularly including the formation of retinal organoids; and (3) direct differentiation, in which cells are not guided in a stepwise manner to become RGCs but rather either undifferentiated hPSCs or unrelated somatic cells such as fibroblasts are genetically reprogrammed with RGC-associated transcription factors to drive their fate toward RGCs. While each of these three approaches has been used to effectively produce RGCs, they also have their own strengths and weaknesses that need to be considered when choosing an appropriate protocol for the derivation of RGCs for downstream applications (Fig. 1). The generation of hPSC-RGCs through the use of 2D differentiation protocols is often conducted by directing the differentiation of hPSCs toward an RGC fate by treatment with small molecule inhibitors and activators of key signaling pathways. Many of these protocols primarily follow dual SMAD inhibition methods to induce the initial differentiation of neural progenitors (Chambers et al. 2009), with subsequent modifications for RGC enrichment (Croteau et al. 2022; Risner et al. 2021; Sluch et al. 2017). 2D differentiation approaches provide advantages including a typically faster differentiation timeline to yield hPSC-RGCs. Further, as adherent cultures, these systems are typically less complicated to adopt, and their adherent nature lends itself to the large-scale production and screening of hPSCRGCs. However, 2D differentiation protocols do not necessarily recapitulate the 3D retinal microenvironment and because they are unable to mimic the spatial structure of the developing retina in the dish, these approaches may not always be the most physiologically relevant, especially when cellular interactions are an important

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consideration for experimental questions. More so, in 2D cultures of differentiating RGCs, it becomes challenging to definitively identify and characterize hPSC-RGCs. While within the retina, RGCs can be identified based upon their location and morphological features, these features are not reliably preserved in a culture dish. Further, the expression of characteristic molecular markers including BRN3 or ISL1 can also be used to identify RGCs, as these markers are specific to RGCs uniquely within retinal tissue (Badea and Nathans 2011; Wu et al. 2015). However, these common RGC transcription factors are often expressed elsewhere in the body, decreasing their utility when starting from a pluripotent source. For example, previous studies have shown the expression of RGC markers such as BRN3 outside of the retina in auditory and somatosensory neurons (Badea et al. 2012), while ISL1 is a well-known marker for motor neurons (Liang et al. 2011). Thus, given the ability of hPSCs to generate all cell types of the body, the mere expression of a single transcription factor is not sufficient to definitively identify a cell as an RGC, and further steps must be taken to definitively prove an RGC fate. 3D differentiation approaches, particularly the use of retinal organoids, provide a promising solution to identify hPSC-RGCs using traditional markers such as BRN3 and ISL1. As retinal organoids are often described as “mini-retinas” that spatially and temporally follow the major stages of retinogenesis in a dish, these approaches can help to eliminate the possibility of non-retinal lineages in differentiating cultures at early stages (Capowski et al. 2019; Eldred et al. 2018; Fligor et al. 2018, 2021; Vander Wall et al. 2020). While the differentiation of retinal organoids provides a more definitive source for the study of RGCs, the RGC layer within these retinal organoids is often highly disorganized and previous studies have shown the loss of RGCs in long-term cultures of retinal organoids (Capowski et al. 2019; Fligor et al. 2020; Kobayashi et al. 2018; Rabesandratana et al. 2020). Thus, many studies focused upon RGCs have obtained organoids and then manually isolated RGCs following enzymatic dissociation, allowing for the prolonged growth and maturation of hPSC-RGCs in 2D cultures for extended periods of time (Sluch et al. 2017; Vander Wall et al. 2019, 2020). hPSC-RGCs derived from 3D differentiation protocols offer significant advantages as they more closely mimic the major stages of human retinogenesis, providing a better in vitro developmental model. Furthermore, given their isolation from retinal organoids, the identification of hPSC-RGCs based upon the expression of molecular markers becomes more accurate. However, 3D culture systems typically require more technical skills to establish and maintain, and the percentage yield of hPSC-RGCs within retinal organoids is not always consistent across different differentiation experiments. To further enhance the purity of RGCs derived from either 2D or 3D differentiation methods, previous studies have applied CRISPR/Cas9 genome editing approaches to establish an RGC reporter line that can also be used for the purification of RGCs from a heterogenous population, based on either expression of a fluorescent reporter or the expression of cell surface antigens including Thy1.2 (Sluch et al. 2017). To date, these reporters have been broadly established in multiple cell lines and proven to be strongly applicable for studies related to RGC development and degeneration in diseases related to glaucoma, as well as studies focused on neuron–

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glia interactions as well as efforts for hPSC-RGC transplants for cell replacement (Croteau et al. 2022; Gomes et al. 2022; Patel et al. 2020; Risner et al. 2021; Vander Wall et al. 2019, 2020; Zhang et al. 2021). Although both 2D and 3D differentiation approaches have reliably generated large quantities of RGCs, they both require relatively longer periods of time to reach an RGC fate. As a result, some other studies have focused upon the genetic reprogramming of RGCs from other cell types, including either skin fibroblasts or undifferentiated hPSCs, through the forced expression of critical transcription factors (Liu et al. 2013; Pang et al. 2011). As hPSC-RGCs retain a relatively young, immature phenotype due to the process of iPSC reprogramming erasing epigenetic marks of aging (Huh et al. 2016; Lo Sardo et al. 2017; Mertens et al. 2018; Takahashi et al. 2007), stem cell-derived RGCs may be limited in their ability to properly serve as a tool for the study of adult onset RGC neurodegenerative diseases such as glaucoma. To further address age-related phenotypes, previous studies have directly converted fibroblasts into a variety of types of neurons through the delivery of defined neuron-associated transcription factors, bypassing the embryonic-like stage (Miskinyte et al. 2017; Pfisterer et al. 2011; Qin et al. 2020; Sepehrimanesh et al. 2021; Vierbuchen et al. 2010; Yang et al. 2020a). This method has been highly effective for modeling age-related phenotypes associated with multiple neurodegenerative diseases including Alzheimer’s diseases, tauopathies, and Huntington disease (Capano et al. 2022; Mertens et al. 2021; Victor et al. 2014), and recent studies have begun to focus on the ability to directly reprogram RGCs from fibroblasts following similar methods, albeit at relatively low efficiencies (Wang et al. 2020; Xiao et al. 2020). The direct reprogramming of RGCs provides a distinct advantage of often being much faster than traditional directed differentiation protocols and may provide better opportunities for the study of age-related phenotypes. Nevertheless, direct conversion of cells into RGCs likely yields a heterogenous population of RGC-like cells and non-RGCs, depending on the efficiency of transduction as well as the process of reprogramming itself. Previous studies focused on the direct conversion of fibroblasts into neurons have also shown the partial reprogramming of some cells that no longer possess all of the features of the starting cell type, but also lack some of the features of the desired differentiated cell type. Given the fact that RGCs, like other neurons, are postmitotic, a significant obstacle exists in the purification of fully reprogrammed RGCs apart from other cell types, as well as the sufficient generation of appropriate numbers of fully reprogrammed RGCs for desired analyses. Further, a close characterization of directly reprogrammed RGCs will also be needed when following these approaches to ensure that bona fide RGCs are produced, due to the overlapping transcriptional signatures with other neural cell types (Xiao et al. 2020).

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Essential Characteristics for hPSC-RGCs

While many approaches may exist to derive hPSC-RGCs, an important next decision involves the level of maturation necessary to achieve the goals of the planned study, and whether or not the predicted phenotypes can be effectively modeled in vitro. hPSC-RGCs are intrinsically a developmental model, owing to their derivation from a pluripotent cell source. In this context, they provide substantial opportunities for the study of human retinogenesis, as well as the specification of RGCs and perhaps their numerous subtypes, as each of these areas of study does not necessarily require advanced stages of maturation. However, for the study of neurodegenerative features associated with optic neuropathies, including glaucoma, these are conditions that are more typically associated with advanced age (Mancino et al. 2018; Mirzaei et al. 2017). Thus, it is likely that hPSC-RGC models will need to possess numerous characteristics of advanced stages of maturation to best serve as an in vitro disease model. To that end, we propose 5 essential characteristics of hPSC-RGCs that should be taken into consideration when properly designing experimental approaches. Depending on the requirements of the experimental plan, differentiated hPSCRGCs should (1) be derived from a retinal lineage, (2) express appropriate RGC-associated markers, (3) establish a complex neuronal morphology with extensive and elaborate neurite outgrowth, (4) become polarized during maturation to exhibit identifiable somatodendritic and axonal compartments, and (5) exhibit proper excitable properties by electrophysiological analyses (Fig. 2). First, and perhaps the easiest of the criteria to meet, is the definitive identification of differentiated cells as RGCs. As mentioned above, while it is easy in the retina to simply identify RGCs based upon their location and morphology, this is not always possible in a differentiating culture of hPSCs, particularly given their pluripotent

Fig. 2 Proposed criteria outlining the characteristics for hPSC-RGCs essential for proper in vitro modeling

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Fig. 3 Schematic of RGC compartmentalization and current status of immunocytochemical detection. (a) Properly mature RGCs exhibit compartmentalized structure with the expression of RGC-associated protein markers in appropriate locations. (b–i) Immunostaining characterizes the expression of RGC-associated markers. The commonly used BRN3:tdTomato:Thy1.2 reporter is highlighted. PAX6 and ISLET1 are RGC transcription factors localized within the nucleus. MAP 2 is characteristic of somatodendritic structures and labels neurites of hPSC-RGCs. Scale bar: 50 μm. IPL, inner plexiform layer; GCL, ganglion cell layer; AIS, axon initial segment

nature in which these cells can become any cell type of the body. Thus, it is often necessary to identify RGCs based upon the expression of appropriate molecular markers. While RGCs have unique transcription factors for their identification within the retina, they share the expression of similar transcription factors within the central nervous system and thus, the identification of hPSC-RGCs based upon the expression of transcription factors individually may not be sufficient to ensure the definitive identification of hPSC-RGCs. To address this, presumptive RGCs should ideally be derived along a documented retinal lineage, such as through an earlier population of retinal progenitors or by the generation of retinal organoids, to help exclude the possibility that hPSCs differentiated into non-retinal cells (Fligor et al. 2018; Ohlemacher et al. 2016; Teotia et al. 2017a; Vander Wall et al. 2020). Additionally, to further ensure that differentiated cells are indeed RGCs, a panel of molecular markers should be used to characterize the hPSC-RGCs (Fig. 3). While some of these markers may be found in other lineages, they often are not found among the same non-retinal cells. For example, BRN3 is an RGC marker that can be found in auditory or somatosensory neurons (Badea et al. 2012), ISL1 is an RGC marker that can be expressed in many other types of tissues, including motor neurons of the central nervous system (Liang et al. 2011), while RBPMS is yet another RGC marker that is found in several mesodermal cell types (Bartsch et al. 2022;

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Nakagaki-Silva et al. 2019). However, the combinatorial expression of these markers in an individual cell would help to ensure proper RGC specification. For instance, while neither the expression of the transcription factors BRN3 nor PAX6 individually are sufficient to identify an RGC from an hPSC source, co-expression of PAX6 and BRN3 has been suggested as a proposed set of combinatorial transcription factors for the identification of hPSC-RGCs (Fig. 3b–e) (Xiao et al. 2020). Additionally, in the identification of these protein markers, one should especially take into consideration the proper localization of these proteins (e.g., transcription factor expression within the nucleus, not cytosol). Among cell types of the retina, one of the most distinguishing characteristics of RGCs are their morphological features. RGCs typically have extensive dendritic arborizations extending in a stratified manner into the inner plexiform layer, while also extending long axons out of the eye to connect with the brain (Liu and Sanes 2017; Troilo et al. 1996). While these precise features are not perfectly recapitulated in a culture dish, many studies have been able to demonstrate extensive neurite outgrowth that would further aid in the identification of hPSC-RGCs, as other retinal cell types do not develop equally elaborate and lengthy morphological features. These elaborate neurite outgrowths can be used not only as an identifying feature of RGCs compared to other retinal cell types, but previous studies have also suggested that the complexity of neurite outgrowth can serve as a parameter for overall RGC health (Agostinone et al. 2018). In hPSC models, recent studies have also identified robust neurite outgrowth in healthy RGCs, while disease models of glaucomaassociated neurodegeneration have demonstrated decreased neurite complexity compared to controls (Gomes et al. 2022; Teotia et al. 2019; Vander Wall et al. 2020). Taken together, morphological features of hPSC-RGCs can not only serve as an important parameter for the identification of RGCs, but also as an essential readout of RGC health. For some applications for disease modeling, particularly for a disease like glaucoma, the compartmentalization of RGCs may also be essential (Donato et al. 2019; Syc-Mazurek and Libby 2019). It is well-established that the primary site of injury is along the initial part of the axon, and degeneration of RGC compartments occurs by different mechanisms in the axonal and somatodendritic regions (Syc-Mazurek and Libby 2019). During the growth and maturation of RGCs, multiple neurites initially extend from the cell body, and eventually one of these neurites extends to become an axon while the rest become dendrites. To determine the extent of RGC maturation, this compartmentalization can be analyzed by staining for features such as MAP 2 expression as a dendrite marker while markers including tau or neurofilament can serve as appropriate axonal markers. In immature RGCs, these proteins are not yet properly segregated and overlapping patterns of expression will exist, while more mature RGCs will exhibit more restricted and compartmentalized expression of these markers. The expression of synaptic proteins by RGCs can also serve as an indicator of RGC maturation, with more mature RGCs expressing higher levels of these proteins, although it has been suggested that hPSC-RGCs derived to date often lack the overall proper punctal localization of these synaptic proteins on either

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dendrites or axon terminals (Croteau et al. 2022; Vander Wall et al. 2019; Xiao et al. 2020). Finally, to fully recapitulate the properties of RGCs in an hPSC model, the functional properties of these cells should also be taken into consideration. As the projection neurons of the visual system that connect the eye with the brain, RGCs are excitatory neurons that convey visual information by transducing action potentials down their long axons (Chen and Chiao 2014; You et al. 2013). Previous studies have demonstrated the ability of hPSC-RGCs to exhibit at least some appropriate excitable properties, including the firing of action potentials (both spontaneously and in response to a depolarizing current) as well as the conduction of both inward and outward ionic currents (Croteau et al. 2022; Gomes et al. 2022; Sluch et al. 2017; Vander Wall et al. 2019). These excitable properties can also serve as an indicator of the overall health of the hPSC-RGCs when properly controlled, as previous studies have demonstrated that RGCs with a glaucoma-associated mutation were more easily excitable than parallel isogenic control RGCs (Gomes et al. 2022; Vander Wall et al. 2020). While whole cell patch clamp provides the greatest cellular resolution, it is also technically challenging and low throughput, making it difficult for all labs to implement. As such, other approaches may also be suitable as a parameter for hPSC-RGC activity, including both calcium imaging and multielectrode array (MEA) recordings. In particular, MEA approaches can not only provide a measure of neuronal activity, but they can also represent network connectivity and allow for the analysis of the same cellular population over time (Fujii et al. 2016). However, as MEA approaches analyze a relatively large population of cells at a time, it is essential to maintain a high purity of hPSC-RGCs to eliminate variability in mixed populations.

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Modeling RGC Neurodegeneration with hPSCs and the Necessity for Proper Controls

Glaucoma is the second most prevalent cause of blindness worldwide with a current incidence of approximately 70 million individuals, and the loss of vision associated with the disease is due to damage to RGCs. To date, the mechanisms underlying neurodegeneration in glaucoma are not completely understood, and limited options exist to protect or regenerate patient RGCs. Glaucoma itself is often considered a group of diseases with a variety of risk factors, such as increased age as well as the elevation of intraocular pressure (IOP) (Artero-Castro et al. 2020). However, as these conditions are difficult to properly mimic in an hPSC-RGC model, glaucomaassociated monogenic risk factors have become a powerful approach to study features of RGC neurodegeneration in a dish, especially with many of the genetic risk factors adequate to cause glaucoma under a normal range of IOP. Several groups have established patient-specific hPSC-RGCs with underlying genetic mutations, including Optineurin (OPTN, E50K), SIX6(H141N), and TBK1(duplication) mutations, all of which have revealed disease-related phenotypes (Ohlemacher et al. 2016; Teotia et al. 2017b; Tucker et al. 2014). In addition to glaucoma,

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hPSC-RGCs have also been used for the study of inherited optic neuropathies, including Leber’s hereditary optic neuropathy (LHON) (Danese et al. 2022; Nie et al. 2022; Wong et al. 2017; Yang et al. 2020b) and autosomal dominant optic atrophy (DOA) (Sladen et al. 2022). The use of patient-specific hPSCs with relevant gene variants provides an important tool for investigating molecular or cellular mechanisms underlying RGC neurodegeneration. Further, compared with animal models of glaucoma, hPSC-RGCs are an important complementary model that can help to simplify the cellular complexity found within numerous cell types present in retinal tissue, and can allow for the study of cell autonomous features of disease states within RGCs themselves. While hPSC-RGCs provide opportunities for the investigation of diseaseassociated phenotypes in a human cellular model, the variability present between individuals (and by extension, different lines of hPSCs) may confound analyses to identify differences between disease and control cell lines. In some cases, this variability may mask disease-related phenotypes while in other situations, phenotypes due to variability between individuals may be mistaken for diseaseassociated phenotypes. To overcome these issues, the use of gene editing strategies such as CRISPR/Cas9 is an essential part of any current hPSC disease modeling study, as these approaches can be applied to precisely insert or delete nucleotides in the genome, with the insertion of a disease-related risk allele in the genome of otherwise healthy cell lines, or the correction of the disease-related allele when cells are derived from patient-specific hPSCs. In this capacity, CRISPR/Cas9 genome editing represents a powerful approach for disease modeling that allows for the specific analysis of the role of certain gene variants in any cell type, without confounding variables due to other differences in genomic backgrounds across cell lines (Musunuru 2013). In hPSC-RGCs, CRISPR/Cas9 genome editing has been used successfully to model aspects of RGC neurodegeneration associated with glaucoma through the insertion of an OPTN(E50K) mutation in a wild-type hPSC line as well as the correction of this variant in a patient-specific hPSC line with the OPTN(E50K) mutation (Vander Wall et al. 2020). Similar approaches have also been recently adopted for the study of dominant optic atrophy (DOA) through the gene correction of a patient-specific hPSC line with the OPA1(R445H) mutation (Sladen et al. 2021). Collectively, these studies have demonstrated that genome editing can minimize the effects of variability between hPSC lines and allows for the study any gene variants of interest without misinterpretation of other genomic differences between cell lines. Taken together, future studies of hPSC-RGCs for disease modeling will need to explore similar gene editing strategies to ensure that experiments are conducted with proper isogenic controls.

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Future Directions for Advancing hPSC-RGC Technologies

In the past several years, the use of hPSC-RGCs has provided numerous opportunities for the investigation of RGC development and disease. As recent studies have demonstrated a low degree of RGC conservation between rodents and

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primates (including humans) (Peng et al. 2019), many studies have become further reliant upon hPSC-RGCs as a compensatory human cellular model. However, despite the human cellular origins of hPSC-RGCs, current culture systems often do not allow for the complete in vitro maturation of hPSC-RGCs. This failure to fully mature is likely not due to an intrinsic inability to reach full maturation, but is likely due more to the environment in which these cells are found in a dish. As media formulations have improved over the past several years, studies have demonstrated increased physiological maturation of hPSC-RGCs (Ohlemacher et al. 2016; Vander Wall et al. 2020). Additionally, the lack of other surrounding cell types, particularly neighboring supportive glia, likely also prevents the full maturation of hPSC-RGCs. Indeed, previous studies have demonstrated that the co-culture of hPSC-RGCs with astrocytes can improve and expedite the functional maturation of hPSC-RGCs (Vander Wall et al. 2019). However, while these factors may present some limitations for current systems, the recognition of these limitations also provides new opportunities for the study and advancement of hPSC-RGC cell culture models that will further support hPSC-RGC maturation. Among the existing issues for the use of hPSC-RGCs is the lack of proper compartmentalization of these cells, with defined somatodendritic and axonal compartments. During the growth of hPSC-RGCs, robust neurite outgrowth has been observed, yet the presence of clear, defined somatodendritic and axonal compartments has not yet been reported, indicating a degree of morphological immaturity. To overcome this barrier, recent studies have begun to induce proper polarization of hPSC-RGCs through the use of microfluidic platforms that can potentially promote better RGC compartmentalization (Fligor et al. 2021; Teotia et al. 2019). The use of microfluidic devices recruits axonal growth from hPSCRGCs through microgrooves and further enables hPSC-RGCs polarization, with important implications for the study of axonal regeneration (Teotia et al. 2019). However, while this is an important step toward hPSC-RGC compartmentalization, whether hPSC-RGC neurites specify into distinct axonal and somatodendritic compartments in microfluidic devices has yet to be determined. Another important consideration for hPSC-RGCs is the fact that in the dish, they do not necessarily interact with other neurons which may induce cell death due to the lack of connectivity and survival factors. In vivo, RGCs receive input from bipolar and amacrine cells and send information to downstream targets largely within the lateral geniculate nucleus and superior colliculus, where RGC axons connect and receive retrograde neurotrophic factors that can support RGC survival and maturation (Crair and Mason 2016; Erskine and Herrera 2014). Previous studies have described increased RGC death in 3D retinal organoids in long-term cultures (Capowski et al. 2019), yet this RGC loss can be largely attenuated through the formation of assembloids between retinal and brain organoids, creating a 3D environment that may help to better mimic RGC compartmentalization and communication with downstream targets (Fligor et al. 2021). Assembloid models will also provide a novel way to assess the role of the microenvironment in hPSC-RGC maturation, as well as how neighboring cells can adversely affect RGCs in disease states.

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While certain aspects of RGC neurodegeneration may occur in a cell autonomous fashion, glial cells located in the nerve fiber layer within retina as well as distal optic nerve are known to interact with RGCs and contribute to RGC maturation as well as induce certain aspects of disease states. For example, microglia regulate RGC development including through the pruning of extraneous synapses, and they phagocytose RGCs that die off (Anderson et al. 2019). Under disease states, astrocytes and microglia are known to become either neuroprotective or neurotoxic to RGCs (Bordone et al. 2017; Gomes et al. 2022; Guttenplan et al. 2020; Zhao et al. 2021), suggesting that RGC survival is also regulated by non-cell autonomous responses. Therefore, when modeling RGC diseases, it is also important to consider the contribution of glial cells. Indeed, we have previously demonstrated that diseased astrocytes can promote the degeneration of otherwise healthy RGCs, while healthy astrocytes can rescue disease RGCs, highlighting the fact that astrocytes can greatly modulate RGC neurodegenerative features (Gomes et al. 2022). To further advance the maturation of hPSC-RGCs and create more physiologically relevant disease models, the use of hPSC-derived glial cells in combination with hPSC-RGCs will be an important avenue for investigation. To further our abilities to study molecular aspects of RGC neurodegeneration, the use of CRSIPR/Cas9 gene editing will likely be instrumental. Indeed, previous studies have developed an efficient method to purify hPSC-RGCs from otherwise mixed populations, with the use of a combined tdTomato and mouse Thy1.2 antigen (Sluch et al. 2017). This hPSC reporter line has already been used in many studies for hPSC-RGCs (Croteau et al. 2022; Gomes et al. 2022; Patel et al. 2020; Risner et al. 2021; Vander Wall et al. 2019, 2020; Zhang et al. 2021). Further, related studies have also used CRISPR/Cas9 gene editing to create disease models with paired isogenic controls, which limits variability between cell lines (Vander Wall et al. 2020). In future studies, it is apparent that CRISPR/Cas9 genome editing technologies will become more commonplace, whether it is used to create new disease models or perhaps tag subcellular structures or organelles with fluorescent proteins for subsequent analyses in disease states. Of interest, it may also be possible to establish unique reporter cell lines for the identification and analysis of RGC subtypes (Langer et al. 2018), as previous studies have suggested differential susceptibility of RGC subtypes to disease states (Daniel et al. 2018).

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Concluding Remarks

Significant advances have already been made in the translational application of hPSC-RGCs for studies of retinal development, in vitro disease modeling, and cell replacement. However, in the future pursuit of RGC studies, it will be of paramount importance to carefully assess hPSC-RGC integrity, ensuring that these cells meet the highest of standards needed to ascertain unique disease-related phenotypes.

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Applications of Induced Pluripotent Stem Cell-Derived Glia in Brain Disease Research and Treatment Zhiqi Yang, Mingyue Gong, Chuanyan Yang, Chunhai Chen, and Kuan Zhang

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Astrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Oligodendrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Microglia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Glia Involvement in Brain Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Brain Diseases Involving Astrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 Alzheimer’s Disease (AD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.2 Parkinson’s Disease (PD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.3 Huntington’s Disease (HD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.4 Traumatic Brain Injury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.5 Ischemia/Stroke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Brain Diseases Involving Microglia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Alzheimer’s Disease (AD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Parkinson’s Disease (PD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.3 Ischemia/Stroke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Brain Diseases Involving Oligodendrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 Krabbe Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Multiple Sclerosis (MS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.3 Alzheimer’s Disease (AD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.4 Ischemia/Stroke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Generation of Induced Pluripotent Stem Cell (iPSC)-Derived Glia . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Generation of iPSC-Derived Astrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Generation of iPSC-Derived Microglia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Generation of iPSC-Derived Oligodendrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Z. Yang · M. Gong · C. Yang · K. Zhang (✉) Brain Research Center and State Key Laboratory of Trauma and Chemical Poisoning, Third Military Medical University, Chongqing, China e-mail: [email protected] C. Chen Department of Occupational Health, Third Military Medical University, Chongqing, China # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_697

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4 Research Models of Pluripotent Stem Cell-Derived Glia to Define the Role of Glial Pathology in Human Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Pathophysiological Neuroglial Interaction Models in 2D Cell Cultures . . . . . . . . . . . . . 4.1.1 Alzheimer’s Disease (AD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.2 Parkinson’s Disease (PD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.3 Huntington’s Disease (HD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 3D Brain Organoids from iPSC-Derived Neurons and Glia . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Alzheimer’s Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Parkinson’s Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Limitations and Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Chimeric Mice from iPSC-Derived Glia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Functional Decoding of iPSC-Derived Astrocytes Combined with Ca2+ Imaging at Multiple Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Potential Methods of Treatment Using Pluripotent Stem Cell-Derived Glia . . . . . . . . . . . . . . 5.1 Treatment by iPSC-Derived Astrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.1 Alzheimer’s Disease (AD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.2 Parkinson’s Disease (PD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.3 Huntington’s Disease (HD) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.4 Traumatic Brain Injury (TBI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.5 Ischemia/Stroke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.6 Integration of Transplanted Astrocytes and Behavioral Improvements . . . . . . 5.2 Treatment by iPSC-Derived Microglia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Treatment by iPSC-Derived Oligodendrocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Pediatric Disease Targets of GPC-Based Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.2 Adult Disease Targets of GPC-Based Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Glia are integral components of neural networks and are crucial in both physiological functions and pathological processes of the brain. Many brain diseases involve glial abnormalities, including inflammatory changes, mitochondrial damage, calcium signaling disturbance, hemichannel opening, and loss of glutamate transporters. Induced pluripotent stem cell (iPSC)-derived glia provide opportunities to study the contributions of glia in human brain diseases. These cells have been used for human disease modeling as well as generating new therapies. This chapter introduces glial involvement in brain diseases, then summarizes different methods of generating iPSC-derived glia disease models of these cells. Finally, strategies for treating disease using iPSC-derived glia are discussed. The goal of this chapter is to provide an overview and shed light on the applications of iPSC-derived glia in brain disease research and treatment. Keywords

Astrocytes · Brain diseases · Brain organoids · Chimeric mice · Glial progenitor cells · Microglia · Oligodendrocytes

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Introduction

The central nervous system (CNS) is composed of two major cell types: neurons and glia. Glial cells, including astroglia, microglia, and oligodendrocytes, are integral components of neural networks and function directly in nearly all physiological processes. Glial cells have long been considered as only supportive to neuron functions (Robertson 2018). More recent studies have demonstrated the central role they play in the brain, especially when it comes to certain complex brain diseases (Albert et al. 2021). Despite clear differences in etiology, many studies have indicated that brain diseases often converge on some underlying glial abnormalities, which include inflammatory changes, mitochondrial damage, calcium signaling disturbance, hemichannel opening, and loss of glutamate transporters (Hastings et al. 2022). With the ability to produce human-induced pluripotent stem cell (hiPSC)-derived glia in vitro, researchers have been able to study how these cells might contribute to human brain diseases and gain further insights into future therapy (Albert et al. 2021). iPSCs are a self-renewable pool of cells derived from an organism’s somatic cells. They can be programmed to develop into other cell types, including glial cells. iPSCs have been used for human disease modeling as well as generating new therapies. These cells have advantages over traditional animal models in that they more accurately represent the human genome (Albert et al. 2021). The present chapter discusses how glial cells derived from iPSCs are being used as both brain disease models and for developing potential therapeutic methods.

1.1

Astrocytes

Astrocytes are the most abundant type of glial cells in the brain. The estimated percentage of astrocytes is 20–60% of all the cells in the CNS (von Bartheld et al. 2016). These cells are very specialized and heterogeneous throughout the CNS (Kim et al. 2019b). Their main role is to provide support to neurons and maintain brain homeostasis, such as the regulation of synapse formation, neuroinflammation, and lactate and glutamate levels (Descalzi 2021; Kumar et al. 2022; Yin et al. 2021). Recent studies have demonstrated that they integrate neural circuits and modulate neuronal activity within the so-called tripartite synapse (Halassa and Haydon 2010). Thereby, they participate in cognitive processes such as learning and memory (Steinman et al. 2016). During pathological processes, astrocytes are involved in multiple brain diseases, including Parkinson’s disease, Alzheimer’s disease, Huntington’s disease, stroke, and traumatic injury to the CNS (Albert et al. 2021).

1.2

Oligodendrocytes

Oligodendrocytes are most numerous in the white matter. They provide myelin around many axons of the CNS, which improves neural conductivity (Mozafari

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and Baron-Van Evercooren 2021). However, the role of oligodendrocytes is not limited to myelin production. They are also involved in supporting, modulating, and regulating neurons. Oligodendrocytes produce factors that promote neuronal survival and increase axon length (Wilkins et al. 2003). In addition, they maintain axonal integrity and are metabolically coupled to axons shuffling lactate via monocarboxylate transporters (Micu et al. 2018). Therefore, oligodendrocytes are essential not only for maintaining neural communication, but also for the survival and function of neurons. Oligodendrocytes are reported to be vulnerable to brain diseases, such as multiple sclerosis (MS), white matter stroke, leukodystrophies, and cerebral palsy (Simons and Nave 2015).

1.3

Microglia

Microglia are resident macrophages that provide immunosurveillance to the CNS and make up approximately 5–10% of CNS cells (Colonna and Butovsky 2017). Microglia turn into an amoeboid and activated state if there are any pathological signals coming from the other surrounding CNS cells (Heindl et al. 2018). Activated microglia move quickly toward the sites of inflammation, where they can release cytotoxic substances and undergo phagocytosis together with manifesting anti- or pro-inflammatory responses (Choi et al. 2020). In their “resting state,” microglia are crucial in the processes of neuronal patterning and synaptic wiring (Harry 2013). They clear cellular debris, secrete cytokines, and express neurotransmitter receptors (Harry 2013). As such, they are involved in synaptic pruning (Schafer et al. 2012; Tremblay et al. 2010).

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Glia Involvement in Brain Diseases

Glial abnormalities are associated with, and sometimes a cause of, multiple brain diseases. Here, we take a closer look at the proposed roles of astrocytes in brain disorders and how these cells specifically become affected by various pathologies.

2.1

Brain Diseases Involving Astrocytes

Apart from their fundamental physiological functions, astrocytes are involved in pathological events. Astrocytic dysfunction can generate neurological disorders such as neurodegenerative diseases, neurodevelopmental diseases, epilepsy, and astrogliomas (Suga et al. 2019). Below, we outline brain disorders involving astrocytic pathological mechanisms.

2.1.1 Alzheimer’s Disease (AD) AD is a neurodegenerative disorder characterized by progressive and irreversible loss of cognitive functions (Scheltens et al. 2016). This disease typically manifests

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later in life, affecting around 10% of over 65-year-olds with disease prevalence strongly correlating with age (Masters et al. 2015). AD is characterized by senile plaques composed of amyloid beta protein (Aβ) and aggregates of hyperphosphorylated tau protein in the brain (Scheltens et al. 2016). Notably, multiple pathological changes have been observed within astrocytes in brains of AD and animal models of this disease (Osborn et al. 2016). Even before the appearance of amyloid plaques, reactive astrogliosis and disruption of the astrocytic domain organization in AD mice have occurred (Olabarria et al. 2010; Yeh et al. 2011). In addition, reactive astrocytes surrounding amyloid-β plaques show aberrant Ca2+ activities (Delekate et al. 2014; Kuchibhotla et al. 2009) and increase linearly with cognitive decline (Serrano-Pozo et al. 2011), likely contributing to disease progression. In contrast, astrocytes distant from plaques were found to have dystrophic branches with reduced complexity (Olabarria et al. 2010; Yeh et al. 2011). Single-cell transcriptomics has demonstrated that astrocytes from AD brains are different from “normal” healthy astrocytes, showing dysregulations in neurotransmitter recycling, including glutamate and GABA, and impaired homeostatic functions (Mirzaei et al. 2022). Astrocytes were also efficiently derived from iPSCs from AD patients (Oksanen et al. 2017). These cells showed higher Aβ production, altered mitochondrial function, increased oxidative stress, and a reduction in lactate release. Furthermore, healthy neurons co-cultured with AD astrocytes displayed lower calcium-transient amplitudes (Oksanen et al. 2017). Thus, AD astrocytes show a severe disease phenotype and deeply modulate neuronal activities, making them capable of contributing to AD pathogenesis (Bigarreau et al. 2022).

2.1.2 Parkinson’s Disease (PD) PD is a progressive neurodegenerative condition, affecting 10 million people worldwide (Greenamyre and Hastings 2004). This neurological condition is a clinically heterogenous disorder characterized by the loss of dopaminergic neurons (Lester et al. 2010) accompanied by reactive changes in astrocytes and microglia in the nigrostriatal system (Bigarreau et al. 2022). The earliest signs of PD likely start within the gastrointestinal system where astrocyte-lineage related cells (enteric glial cells [EGCs]) become affected. The dysfunction of EGCs is related to the initiation and development of PD (Clairembault et al. 2015). More importantly, studies have shown selective astrocytic expression of mutant A53T α-synuclein, associated with a familial form of the disorder, which led to dopaminergic and motor neuron degeneration (Gu et al. 2010). In addition, co-culture of healthy neurons with patient-derived astrocytes differentiated from iPSCs led to neurodegeneration and α-synuclein accumulation (di Domenico et al. 2019). This evidence indicates that astrocytes are significant in PD progression. 2.1.3 Huntington’s Disease (HD) HD is an autosomal dominant neurodegenerative disease characterized by movement disorders, psychiatric symptoms, and cognitive decline (Bigarreau et al. 2022). HD is caused by a single gene mutation – a polyglutamine (CAG repeat) expansion on the N-terminal region of huntingtin gene (HTT) (Kuan et al. 2015). The

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pathological hallmark of HD is aggregation of the mutant huntingtin protein (mtHtt), which can trigger progressive neurodegeneration (Waldvogel et al. 2015). Astrocytic pathology has been implicated in HD, with astrocytes contributing to HD pathogenesis through transcriptional activation of proinflammatory genes, functional changes in glutamate, and ion homeostasis (Palpagama et al. 2019). Astrocytes derived from HD iPSCs exhibit impaired inward rectifying K+ currents, lengthened spontaneous calcium waves, and reduced cell membrane capacitance (Garcia et al. 2019).

2.1.4 Traumatic Brain Injury Traumatic brain injury (TBI) is among the leading causes of preventable disability in younger individuals. Nearly half of the spinal cord injury (SCI) incidents occur between ages 16 and 30, and less than 1% of the affected patients make a full recovery (Singh et al. 2014; Wyndaele and Wyndaele 2006). When stimulated by TBI, astrocytes become activated and undergo a series of changes, including alterations in gene expression, hypertrophy, and loss of inherent functions. These activated astrocytes have a dual role both as regulators of neuroinflammation and in scar formation (Yu et al. 2021). This heterogeneity is determined by the background of the astrocytes. In an inflammatory background, A1 astrocytes are generated and marked by C3 expression. A2 astrocytes are induced by ischemia and hypoxia and are indicated to play a neuroprotective role (Yu et al. 2021). 2.1.5 Ischemia/Stroke Stroke is a leading cause of death and long-term disability worldwide. Due to a lack of glucose and oxygen because of the loss of blood flow, neural tissue is biochemically and metabolically compromised, resulting in cell death after ischemic stroke (He et al. 2022). Astrocytes undergo reactive astrogliosis after ischemic insult. In this process, astrocytes change from the normally bushy form to a hypertrophic stellate shape and then to a highly polarized shape with long processes pointing to the ischemic core (Ding 2014). In addition, in the initial step after ischemia, there is an acute increase in astrocytic Ca2+ signaling and subsequent glutamate and GABA release from astrocytes (Sompol and Norris 2018). The role of astrocytes in ischemia or stroke is complex: they work as a versatile player in regulatory processes depending on context, region, and time (He et al. 2022). On the one hand, reactive astrocytes provide neuroprotection through antioxidation, anti-excitatory effects, and metabolic support and contribute to neurorestoration involving neurogenesis, synaptogenesis, angiogenesis, and oligodendrogenesis. On the other hand, reactive astrocytes are also vital in neuroinflammation and brain edema and contribute to the formation of glial scars, which hinders functional recovery (He et al. 2022). In summary, there are some common pathological features typically found in diseased, native glia. These features induce astrocyte atrophy and death, damage to surrounding neurons, loss of myelin, and recruitment of neurotoxic microglia (Hastings et al. 2022). Pathological features include: (1) increased proinflammatory cytokine release and reduced protective factor release; (2) mitochondrial damage and increased ROS production; (3) aberrant calcium signaling; (4) connexin dysregulation; (5) loss of glutamate transporter leading to excitotoxicity; (6) loss

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of potassium buffering ability leading to increased excitability of surrounding neurons; (7) autophagy and proteasome deficits; and (8) apoptosis (Hastings et al. 2022).

2.2

Brain Diseases Involving Microglia

Microglia, the brain’s innate immune cells, are essential in initiating a defense response to infection or neuroinflammation in the host (Wang et al. 2022). However, during chronic inflammation, microglia may lose their homeostatic functions and secrete various proinflammatory cytokines and mediators. This process initiates neural dysfunction and neurodegeneration (Parajuli and Koizumi 2022). Next, we briefly review the role of microglia in various pathological brain conditions.

2.2.1 Alzheimer’s Disease (AD) During the progression of AD, microglia can produce proinflammatory cytokines, which are thought to accelerate disease progression and cognitive decline (Akiyama et al. 2000; Cameron and Landreth 2010). Consistent with this, Aβ has been found to induce microglial production of proinflammatory cytokines, such as IL-1β and TNF-α, which can cause neuronal cell death (Maezawa et al. 2011; Parajuli et al. 2013). In addition, mice lacking Nlrp3 or Casp1, which activate proinflammatory cytokines, are protected from spatial memory loss in an AD model (Heneka et al. 2013). Moreover, microglia express TREM2 and CD33, receptors that mediate disruption of phagocytosis, increased proinflammatory processes, and impaired clearance of Aβ (Griciuc et al. 2013). 2.2.2 Parkinson’s Disease (PD) Studies suggest that microglia can exacerbate PD or promote neuronal survival, depending on their activation profile, and are thus key players in disease progression (Parajuli and Koizumi 2022). On the one hand, microglia are activated through p38 MAPK and NF-κB signaling pathways in response to inflammation and express multiple proinflammatory cytokines when exposed to α-synuclein (Gilks et al. 2005; Moehle et al. 2012). On the other hand, microglia phagocytose and degrade α-synuclein released by neurons, thereby protecting neurons (Choi et al. 2020). In addition, α-synuclein has been demonstrated to be transferred between microglia through tunneling nanotubes, which may be the mechanism that induces the propagation of α-synuclein (Scheiblich et al. 2021). 2.2.3 Ischemia/Stroke Activated microglia are important for post-ischemic inflammation. Studies indicate that microglia have both beneficial and harmful roles in ischemia depending on the disease phase (Parajuli and Koizumi 2022). During the acute phase of stroke, proliferating resident microglial cells protect neurons by producing neurotrophic factors such as IGF1 (Lalancette-Hébert et al. 2007). Selected ablation of these proliferating microglia after stroke decreases IGF1 and increases lesion size and

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number of apoptotic neurons (Lalancette-Hébert et al. 2007). In contrast to the acute phase, during the chronic phase, activated microglia located in the peri-infarct and distal regions can induce delayed selective neuronal loss. These activated microglia release a large variety of proinflammatory mediators, including IL-1β, IL-6, and TNF-α, which can lead to acute inflammatory reactions (Chen et al. 2017; Li et al. 2020b) and exacerbate damage to neighboring neurons and result in delayed deterioration of ischemic tissue (Neher et al. 2013, 2014).

2.3

Brain Diseases Involving Oligodendrocytes

Oligodendrocytes produce myelin, an insulating sheath required for the saltatory conduction of electrical impulses along axons (Goldman and Kuypers 2015). Oligodendrocyte loss induced demyelination is one of the mechanisms involved in white matter damage (Helman et al. 2015). These myelin disorders are among the most prevalent and disabling conditions in neurology (Rosati 2001). Major brain diseases involving oligodendrocytes are briefly introduced in this section.

2.3.1 Krabbe Disease Krabbe disease (globoid cell leukodystrophy) is a lysosomal storage disease (LSD) characterized by progressive and profound demyelination. The infantile-onset form of Krabbe disease is the most common, although juvenile and adult-onset forms have been described (Bradbury et al. 2021). Children with an infantile onset generally appear normal at birth but begin to miss developmental milestones by 6 months of age and die by 2–4 years of age (Bradbury et al. 2021). This disease is caused by a deficiency of the acid hydrolase galactosylceramidase (GALC), which is responsible for the degradation of galactosylceramides and sphingolipids, which are abundant in myelin membranes (Suzuki and Suzuki 1970). The absence of GALC leads to the toxic accumulation of galactosylsphingosine in oligodendrocytes and Schwann cells. This process causes demyelination of the central and peripheral nervous systems (Bradbury et al. 2021). 2.3.2 Multiple Sclerosis (MS) MS is a chronic inflammatory disease of the CNS leading to demyelination and neurodegeneration (Correale and Ysrraelit 2022). The MS disease process may involve neural centers implicated in the control of breathing, leading to ventilatory disturbances during both wakefulness and sleep (Kimoff et al. 2022). The degeneration of oligodendrocytes (OGDs) and OGD precursors (OPCs) with age is the main reason for this disease (Correale and Ysrraelit 2022). Age-related neuronal changes such as mitochondrial alterations, increased oxidative stress, and disrupted paranodal junctions may impact myelin integrity. In addition, aging-induced decline of regenerative processes progressively hinders remyelination in MS, which further exacerbates the progress of MS (Stahon et al. 2016).

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2.3.3 Alzheimer’s Disease (AD) AD is a progressive consequence of two hallmark pathological changes in gray matter: extracellular amyloid plaques and neurofibrillary tangles (Nasrabady et al. 2018). However, recent neuroimaging studies have implicated micro- and macrostructural abnormalities in white matter in the progression of AD (Nasrabady et al. 2018). This suggests that white matter degeneration and demyelination may also be important pathophysiological features of AD. Specifically, changes in the number of oligodendrocytes or their precursor cells and/or their dysfunction can affect myelin integrity and potentially be implicated in AD pathogenesis (Bartzokis 2011). One of the main reasons for the demyelination in AD is that oligodendrocytes suffer from oxidative stress and DNA damage, which can be produced by a wide range of factors (Bartzokis 2011; Tse and Herrup 2017). In addition, other mechanisms induce demyelination in AD, such as ischemia, excitotoxicity, iron overload, Aβ toxicity, and tauopathy (Nasrabady et al. 2018). Hence, white matter abnormalities, and in particular myelin and oligodendrocytes, could be mechanistically important in AD pathology and could be potential treatment targets. 2.3.4 Ischemia/Stroke Common brain injuries such as ischemic stroke are also accompanied by the destruction of myelin structures and apoptosis of oligodendrocytes (Chen et al. 2020). Oligodendrocytes are extremely susceptible to ischemic stroke, and myelin sheath loss is the pathological hallmark of white matter stroke (WMS) (Marin and Carmichael 2019). After stroke, cholesterol synthesis and transport disorders reduce myelination, increase oligodendrocyte loss, and decrease oligodendrogenesis, which may be the main reasons for destruction of myelin structure (Li et al. 2020a). Studies also suggest that ischemic stroke induces high expression of tissue inhibitors of metalloproteinase-3 (TIMP-3) in astrocytes and promotes high expression of tumor necrosis factor-α (TNF-α) and matrix metalloproteinase-3 (MMP-3) in microglia, promoting inflammation in the ischemic brain (Yang et al. 2011). Thereby, this neuroinflammation induced by stroke also causes demyelination.

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Generation of Induced Pluripotent Stem Cell (iPSC)-Derived Glia

In order to study human diseases, human iPSCs are required, because despite some evolutionarily conserved similarities, rodent and human brains differ from each other (Hodge et al. 2019). Another important factor is that human iPSCs bypass some of the ethical issues associated with utilizing human tissue for research purposes because these cells are obtained from human somatic cells (Silva et al. 2015). Differentiated somatic cells can be reprogrammed back into pluripotency through methods using Yamanaka factors (Oct3/4, Sox2, c-Myc, and Klf4) (Takahashi and Yamanaka 2006) or the non-integrating Sendai viral vector (Ban et al. 2011). iPSCs can be differentiated into various cell types, including neurons and glia, making them a powerful tool to study human CNS cells in vitro (Albert et al. 2021) (Fig. 1a).

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Fig. 1 Overview of neuronal and glial cell production from human iPSCs (a), in vitro and in vivo research models of iPSC-derived neurons and glia (b), and applications of these models (c)

In the following part, we discuss methods of generating astrocytes, microglia, and oligodendrocytes from iPSCs. These processes can be used to study how these cells may contribute to disease in a human-specific way, both in vitro and via transplantation in vivo.

3.1

Generation of iPSC-Derived Astrocytes

According to previous studies, the general mechanism of producing iPSC-derived astrocytes has four steps: (1) formation of rosette-forming neuroepithelial cells from iPSCs; (2) generation of neural stem cells (NSCs); (3) expansion of induced NSCs in suspension culture with growth factors; and (4) astrocyte differentiation and maturation (Kumar et al. 2022). Combinations of morphogens and growth factors have been used in various studies. These combinations include retinoic acid, the winglesstype MMTV integration site protein family, fibroblast growth factor (FGF), and growth differentiation factor (Krencik et al. 2011; Lippmann et al. 2015; Osakada and Takahashi 2011; Takahashi et al. 2007). Most of the above methods are time-consuming and have low efficiency. The initial protocols took up to 180 days to isolate the iPSCs and differentiate them into

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astrocytes (Emdad et al. 2012; Krencik et al. 2011; Krencik and Zhang 2011). Therefore, scientists have attempted to develop more rapid methods to obtain iPSC-derived astrocytes. One study directly converted skin fibroblasts into astrocytes using various transcription factors (TFs) such as nuclear factor IA (NFIA), NFIB, and sex-determining region (SRY)-box transcription factor 9 (SOX9) (Caiazzo et al. 2015). Two other studies demonstrated that human iPSCs can be induced into functional astrocytes by activating NFIA and SOX9 pathways. They successfully produced astrocytes in 4–7 weeks using NFIA or NFIA and SOX9 (Li et al. 2018; Tchieu et al. 2019). Using SOX9 and NFIB as TFs, recent protocols produced functional astrocytes in 30 days (Shaltouki et al. 2013; Tcw et al. 2017) and even after only 2 weeks (Canals et al. 2018). Importantly, it should be noted that none of the available protocols are free of limitations, which are as follows: (1) lack of sufficient details to reproduce the above methods; (2) the purity and maturity of iPSC-derived astrocytes are not comparable to those derived from primary astrocytes; and (3) astrocytes generated using the above methods are often poorly characterized (Kumar et al. 2022).

3.2

Generation of iPSC-Derived Microglia

Until now, only a few studies have focused on microglia derived from iPSCs (Bigarreau et al. 2022). The first attempts to generate microglia from mouse were based on driving murine iPSCs toward the neuroectodermal lineage (Tsuchiya et al. 2005). However, based on ontogenic studies, microglia arise from mesodermal primitive yolk sac progenitors rather than from the neuroectodermal lineage (Ginhoux et al. 2010). In recent studies, microglia have been successfully generated from iPSCs (Abud et al. 2017; Muffat et al. 2016; Takata et al. 2017). The protocols of these studies shared many cytokines for driving the iPSCs toward the mesodermal/hematopoietic progenitor fate, but display multiple discrepancies in culture conditions, duration, yield, and purity (Abud et al. 2017; Muffat et al. 2016). It is also important to assess the functionality of microglia derived from iPSCs. Studies have demonstrated that microglia generated from human iPSCs acquire key functional properties of the microglia cells, such as their response to inflammatory signaling, the ability to migrate, their phagocytic capabilities, and their ADP-dependent calcium response (Abud et al. 2017; Bigarreau et al. 2022; Muffat et al. 2016; Takata et al. 2017).

3.3

Generation of iPSC-Derived Oligodendrocytes

Oligodendrocytes produce a laminated myelin sheath that wraps neuronal axons, which enables a fast and energy-efficient transmission of electrical signals (Xin and Chan 2020). Myelin is also significant for axonal integrity and survival, and even small changes affecting oligodendrocyte metabolism can lead to neurodegeneration (Lee et al. 2012). In human brains, there are many myelinated neurons (white matter)

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that mediate cognitive function and behavior (Xin and Chan 2020). Myelin disorders are among the most prevalent and disabling conditions in neurology (Goldman et al. 2012). Therefore, generating iPSC-derived oligodendrocytes is both meaningful for cell replacement therapies for demyelinating disorders and to model their pathophysiological role in cell culture (Czepiel et al. 2011; Ferraiuolo et al. 2016). Multiple protocols have been employed for generating iPSC-derived oligodendrocytes. These protocols either use chemically defined media mimicking the human embryonic environment or are based on over-expression of TFs required for human oligodendroglial specification (Mozafari and Baron-Van Evercooren 2021). Wang and colleagues acquired an efficient method that succeeded in generating iPSC-derived OPCs, which could broadly populate, myelinate the axons of host neurons, and rescue hypomyelinated mice (Wang et al. 2013). However, this protocol is still largely limited in application by the lengthy culture times, as 80 to over 200 days of differentiation is required to obtain OPCs expressing the O4 antigen (Wang et al. 2013). In another study, generation of iPSC-derived OPCs was achieved in a shorter time frame of 75 days in vitro using dual SMAD inhibition and retinoid and SHH signaling to mimic embryonic spinal cord development (Douvaras et al. 2014). One important improvement was based on the use of a cocktail of three oligodendrocyte TFs, SOX10, OLIG2, and NKX6.2 (Ehrlich et al. 2017). This method reduced the OPC generation time to 1 month and increased efficiency up to 70% (Ehrlich et al. 2017). In addition, it has been demonstrated that rodent OPCs may be generated in vitro directly from somatic cells, using specific TFs (Najm et al. 2013; Yang et al. 2013). Such method avoids generating pluripotent intermediate cell stages and reduces the risk of tumorigenesis (Najm et al. 2013; Yang et al. 2013). However, so far, the efficiency of direct reprogramming of somatic cells into oligodendroglia is much lower than indirect approaches in terms of their expansion capacity and myelinogenic potential. Direct reprogramming of human somatic cells into oligodendroglia has not been reported (Mozafari and Baron-Van Evercooren 2021). Hence, in the future, scientists should continue studying the development of more efficient and faster reprogramming techniques to achieve highly enriched myelinogenic cells.

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Research Models of Pluripotent Stem Cell-Derived Glia to Define the Role of Glial Pathology in Human Disease

Research models of iPSC-derived glia provide insights into understanding the underlying physiological and pathological roles of glia in human brains (Albert et al. 2021). Most research models of iPSC-derived glia have been based on human glial cells derived from iPSCs of patients with various neurological disorders (Wang et al. 2020). These data advance our understanding of the mechanisms of brain disorders involving glia dysfunctions. In the following section, we discuss the applications of in vitro and in vivo models of iPSC-derived glia.

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Pathophysiological Neuroglial Interaction Models in 2D Cell Cultures

Neuroglial interactions are impaired in brain disorders through pathophysiological glial mechanisms (Bigarreau et al. 2022). Therefore, modeling the role of glia in brain diseases using iPSCs, a concept known as “disease-in-a-dish,” is essential for understanding detailed pathogenesis processes (Fig. 1b and c). A few examples of studies on neuroglial interactions in these diseases are reviewed below.

4.1.1 Alzheimer’s Disease (AD) Glial cells from AD patients display pathological characteristics, such as reduced Aβ uptake or altered morphology of AD microglial cells (Lin et al. 2018). In a co-culture study of astrocytes derived from iPSCs from AD patients with healthy neurons, astrocytes showed increased Aβ production, altered mitochondrial metabolism, and reduced lactate secretion (Oksanen et al. 2017), as demonstrated in AD patients. Additionally, glutamate/glycine or GABA administration resulted in lower calciumtransient amplitudes in healthy neurons co-cultured with AD astrocytes as compared with healthy neurons co-cultured with healthy astrocytes (Oksanen et al. 2017). Therefore, AD astrocytes are involved in impaired neuronal activities and contribute to AD pathogenesis. 4.1.2 Parkinson’s Disease (PD) Previous studies have shown that astrocytes accumulate α-synuclein, which spreads between astrocytes and neurons, during the course of PD (Lee et al. 2010). Modeling PD with co-culture of astrocytes and neurons derived from iPSCs from PD patients further confirmed this point (Lee et al. 2010). In addition, control neurons were less viable when co-cultured with PD astrocytes, and conversely the PD neuron phenotype was partially rescued by control astrocytes (Bigarreau et al. 2022). Moreover, further investigation demonstrated impairment of autophagy in PD astrocytes and neuroglia interaction through alteration of extravesical biogenesis in astrocytes (di Domenico et al. 2019) (de Rus Jacquet et al. 2021). 4.1.3 Huntington’s Disease (HD) Glia contribute to HD pathogenesis through transcriptional activation of proinflammatory genes, functional changes in glutamate and ion homeostasis, and finally to neuron death (Palpagama et al. 2019). Astrocytes derived from HD iPSCs exhibit impaired inward rectifying K+ currents, lengthened spontaneous calcium waves, and reduced cell membrane capacitance, as described in HD (Garcia et al. 2019). In addition, mitochondrial membrane potential and superoxide anion production were maintained in these astrocytes (Hamilton et al. 2020).

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3D Brain Organoids from iPSC-Derived Neurons and Glia

Due to the difficulty of studying the detailed pathological mechanisms of neurodegenerative diseases in brains of living patients, developing disease models capable of more accurately representing disease biology in human brains is key to elucidating the degenerative processes underlying these diseases, and critical for exploration and evaluation of potential treatments and medications (Albert et al. 2021). Creation of iPSCs has revolutionized in vitro study of human disease by granting access to a virtually unlimited supply of human cells. However, conventional 2D cell cultures cannot recreate the intricate cell architecture and microenvironment of human brain tissue. Cerebral organoids derived from iPSCs, first described by Lancaster et al. (2013), have shown potential to overcome the inaccessibility of human brain tissue. These brain organoids contain different regional identities of the brain, display the characteristic layering of neurons, and are a promising novel platform for screening applications (Lancaster et al. 2013). In addition to neurons, brain organoids give rise to both astrocytes and oligodendrocytes (Kim et al. 2019a; Kwak et al. 2020; Paşca et al. 2015; Tieng et al. 2014). The co-occurrence of neurons and glia in brain organoids makes them an attractive model for studying the neuroglial interaction. iPSC-derived brain organoids from a healthy human subject can be used to model the brain microenvironment for studying interactions between a variety of cell types during physiological states; iPSC-derived brain organoids from patients can be used to study key pathological events in brain diseases (Fig. 1b and c).

4.2.1 Alzheimer’s Disease Cerebral organoids derived from iPSCs of a patient with familial AD (fAD) have been observed to replicate key pathological progressions of AD, such as formation of Aβ aggregates, hyperphosphorylated tau, and increased apoptosis (Gonzalez et al. 2018; Raja et al. 2016; Yin and VanDongen 2021). AD pathology was ameliorated by treatment with γ-secretase and BACE1 inhibitors (Raja et al. 2016). In addition, some researchers have studied the functional defects of AD neuronal networks using cerebral organoids. PSEN1/2 and APP fAD organoids display asynchronous calcium transients, increased neuronal activity, and hyperexcitability (Ghatak et al. 2019; Raja et al. 2016). Further studies provided evidence for the involvement of astrocytes in AD by brain organoids harboring the APOεE4 allele. Both reduced Aβ uptake and cholesterol accumulation have been found in APOεE4 astrocytes (Lin et al. 2018). 4.2.2 Parkinson’s Disease For studies of PD, midbrain organoid (MO) is an attractive model. Organoids patterned toward the midbrain are enriched in dopamine (DA) neurons and express midbrain-specific markers such as EN1, FOXA2, LMX1A, and TH (Jo et al. 2016; Smits et al. 2019; Tieng et al. 2014). More importantly, MO DA neurons display characteristics of PD brains. First, neuromelanin inclusions characteristic of the human substantia nigra pars compacta have been observed after 2 months in culture

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(Jo et al. 2016). Second, MO DA neurons are susceptible to neuronal death caused by neurotoxins 6-hydroxydopamine (6-OHDA) and 1-methyl-4-phenyl-1,2,3,6tetrahydropyridine (MPTP) (Kim et al. 2019a; Kwak et al. 2020; Monzel et al. 2020). Third, these MO DA neurons have been shown to demonstrate aberrant accumulation and deposition of α-synuclein (Kim et al. 2019a). Lastly, these neurons also replicate molecular features of the disease (Chlebanowska et al. 2020).

4.2.3 Limitations and Improvements Cerebral organoids are excellent models for neurodevelopmental disorders because they exhibit similar developmental events as the fetal human brain (Camp et al. 2015; Gordon et al. 2021; Lancaster et al. 2013; Luo et al. 2016; Renner et al. 2017). In contrast, the most common neurodegenerative diseases (e.g., AD and PD) are prevalent in the elderly population. It is a challenge to recapitulate the aging brain in an inherently immature organoid. This may limit their applications as models of neurodegenerative diseases. Some strategies have been investigated for inducing aging-like effects in iPSC-derived neurons. Nguyen et al. simulated oxidative stress by exposure of iPSC-derived neuronal cells to hydrogen peroxide, MG-132, and 6-hydroxydopamin (Nguyen et al. 2011). Miller and colleagues used progerin to stimulate late-onset age-related disease features in hiPSC-based disease models (Miller et al. 2013). They found that expression of progerin in iPSC-derived fibroblasts and neurons induces multiple aging-related markers and characteristics, such as dendrite degeneration, progressive loss of tyrosine hydroxylase (TH) expression, and enlarged mitochondria or Lewy-body-precursor inclusions (Miller et al. 2013).

4.3

Chimeric Mice from iPSC-Derived Glia

Drugs tested in animal models of human brain diseases often fail in the clinic (Ferreira et al. 2020; Kola and Landis 2004; Pound et al. 2004; Zeiss 2015). Therefore, it is important to develop reproducible and valid models to study human brain diseases. One approach is to utilize iPSCs to model disease in 2D and 3D cell culture as detailed above. The next step is using these human iPSCs to model neurodegenerative diseases in rodents in order to achieve a “humanized” model – a model that more closely resembles the human condition (Albert et al. 2021). In humanized models of brain diseases, iPSCs are derived from a patient’s somatic cells and differentiated to neuronal or glial precursors. These cells are then transplanted to the rodent brain and studied in situ (Fig. 1b). Human glial progenitor cells (hGPCs) can migrate and differentiate into functional oligodendrocytes and astrocytes when transplanted neonatally into murine hosts. These transplanted hGPCs outcompete the host glial pool to ultimately colonize and dominate the recipient brains (Mariani et al. 2019). In these studies, the donor hGPCs generate myelinogenic oligodendrocytes as well as astrocytes when they are transplanted into congenitally hypomyelinated mutants, so that the recipient mice develop a largely humanized white matter, with entirely human-

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derived myelin (Mariani et al. 2019). Moreover, when the transplanted hGPCs are derived from patient- and disease-specific pluripotent stem cells, human glial chimeric mice are an ideal model to investigate the pathological role of glia in human neurodegenerative and neuropsychiatric diseases, as well as the potential for therapeutic glial cell replacement in these disorders (Han et al. 2013; Zhang and Chen 2017). Until now, most work toward a humanized model of neurodegenerative disease using iPSC transplants has been done in AD. In these studies, transgenic mice expressing human AD mutations in amyloid precursor protein (APP) as well as presenilin 1 (PSEN1) were crossed with immunodeficient mice to facilitate the graft (Radde et al. 2006). These differentiated iPSCs transplanted to the transgenic mouse model recapitulate the features of AD in humans in contrast to using the mouse alone to model the disease (Najm et al. 2020). In one study, iPSCs were generated from APOEε3/3 and APOEε4/4 lines. These cells were then differentiated into neurons and transplanted to the hippocampi of both transgenic mouse lines with human APOEε3/3 or APOEε4/4 knocked in (7-month-old mice) (Najm et al. 2020). These APOEε4/4 neurons transplanted to APOEε4/4 mice had gene transcriptional profiles indicating synaptic dysfunction and dysregulated calcium homeostasis. In addition, these neurons produced more Aβ aggregates compared to the neurons transplanted to the APOEε4/4 mice (Najm et al. 2020). The humanized model of neurodegenerative disease using iPSC transplants may also be of great value in screening agents, both small molecules and biologics, whose effects on human neuronal cells require assessment (Mariani et al. 2019) (Fig. 1c).

4.4

Functional Decoding of iPSC-Derived Astrocytes Combined with Ca2+ Imaging at Multiple Levels

Astrocytes transduce and encode information through elevating intracellular calcium (Semyanov et al. 2020). These astrocyte Ca2+ transients are highly diverse, with complex spatiotemporal features (Volterra et al. 2014). Furthermore, astrocytic Ca2+ transients can be evoked by various physiological changes or pathological events (Volterra et al. 2014). Recent studies have indicated that astrocytic Ca2+ transients are essential for cognitive functions. Nicotinic receptor-dependent astrocytic Ca2+ responsiveness is an integral part of the cellular substrate underlying memory persistence (Wu and Gao 2022; Zhang et al. 2021) (Fig. 2). However, the study of human astrocytes and their interactions with neurons and microvasculature is difficult due to the inability to collect primary biomaterials. As such, how to combine Ca2+ indicators and Ca2+ imaging methods with research models of human iPSCderived astrocytes is necessary to define the physiological and pathological roles of astrocytes in human brains (Gorzo and Gordon 2022). Ca2+ indicators are divided into two main types: chemical indicators and genetically encoded calcium indicators (GECI). GECIs are chimeric proteins formed by fusing one or two fluorescent proteins with a calcium binding protein. One of the most popular modifications is GCaMP6 (Gorzo and Gordon 2022). One recent study

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Fig. 2 Nicotinic receptor-dependent astrocytic responsiveness is an integral part of the cellular substrate underlying memory persistence. Fear learning causes the de novo induction of Ca2+ transients in astrocytes, which is significant for persistence of fear memory. Deletion of nicotinic receptors in astrocytes inhibits Ca2+ transients and impairs fear memory

has shown a method to obtain human neurons with expression of the GCaMP6s Ca2+ indicator, based on a human iPSC line with the TetON–NGN2 transgene complex (Galiakberova et al. 2022). In addition, in order to study the functions of human stem cell-derived cortical organoids (hCO), hCOs expressing GECI GCaMP6s have been made and transplanted in the brains of mice (Revah et al. 2022). Human iPSCderived astrocytes and organoids expressing GECIs allow researchers to quickly, conveniently, and efficiently study the functions of human astrocytes using fluorescence microscopy (Fig. 3a). For decoding functions of astrocytic Ca2+ transients, in vivo Ca2+ imaging at multiple levels has been developed (Ding et al. 2022; Qin et al. 2020). In subcellular level studies, two-photon laser scanning microscopy (2PLSM) is preferred, as good resolution can be acquired at substantial tissue depths (>500 μm). During one study, GCaMP6f was combined with in vivo two-photon Ca2+ imaging to determine transient changes in Ca2+ within astrocytic soma and processes, including primary branches, higher-order branches, and terminal leaflets (Ding et al. 2022) (Fig. 3b, c). The heterogenous characteristics of Ca2+ transients were clearly shown using the above method. In addition, to study the functions of astrocytes in freely moving mice, optic fiber recording can be combined with GECIs (Qin et al. 2020). This approach enables selective and reliable measurement of astrocytic Ca2+ activity and provides a powerful approach to record astrocytic activity selectively, stably, and chronically in freely behaving mice (Qin et al. 2020) (Fig. 3b, c).

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Fig. 3 Overview of decoding functions of astrocytes using in vivo models by iPSC-derived glia with GECI expression, combined with Ca2+ imaging methods at multiple levels. a. Schematic steps for differentiation of iPSC to NPCs/GPCs with GECI expression. b. 3D brain organoids or chimeric mice can be acquired from iPSC-NPCs/GPCs with GECI expression. c. Decoding astrocytic functions at multiple levels can be achieved by in vivo two-photon imaging (single cellular or subcellular level) and optic fiber recordings in freely behaving mice (population level). GECIs: Genetically encoded calcium indicators; NSCs: Neural stem cells; GPCs: Glial progenitor cells

By combining Ca2+ imaging at multiple levels(optic fiber recordings or two-photon calcium imaging) and hCOs expressing GECIs, Revah and colleagues showed that hCOs transplanted into the somatosensory cortex of newborn athymic rats develop mature cell types that integrate into sensory and motivation-related circuits (Revah et al. 2022). They found that transplanted hCO cells exhibited synchronous and rhythmic activity and could be activated by sensory stimuli (Revah et al. 2022). These data suggest that transplanted hCO receive appropriate functional inputs and can be activated by environmental stimuli (Revah et al. 2022), providing a useful method for detecting circuit-level phenotypes in patient-derived cells. In summary, the combination of models of hiPSC-derived glia with GECI expression and Ca2+ imaging at multiple levels will promote studies on the physiological and pathological processes of astrocytes in human brain diseases (Fig. 3).

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Potential Methods of Treatment Using Pluripotent Stem Cell-Derived Glia

Glia pathologies are found in many brain diseases, as discussed above, and thus transplantation of healthy glia can have therapeutic benefits. Many studies have indicated that cell transplantation is an attractive treatment strategy for a variety of brain disorders, as it promises to replenish lost functions and rejuvenate the brain

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(Hastings et al. 2022). Therefore, in the next section we focus on glia transplantation and discuss potential methods of treatment using iPSC-derived glia.

5.1

Treatment by iPSC-Derived Astrocytes

Astrocytes, the most-abundant non-neuronal cell population in the brain, are vital in physiological and pathological processes. In a healthy brain, astrocytes form complex networks capable of crosstalk with neuronal nets (Kuga et al. 2011; Szabó et al. 2017; Winship et al. 2007), and regulate key aspects of functions of neurons (Dallérac et al. 2013; Henneberger et al. 2010), oligodendrocytes (Dutta et al. 2018; Lutz et al. 2009), microglia (Bohlen et al. 2017), and the neurovascular unit (Bozoyan et al. 2012; Winship et al. 2007). Astrocytic abnormalities are involved in, and sometimes cause, various brain disorders ranging from neurodegenerative diseases (e.g., AD, PD) (Bigarreau et al. 2022; Mirzaei et al. 2022) to brain injuries (e.g., TBI, stroke) (He et al. 2022; Yu et al. 2021). These findings should prompt scientists to study whether astrocyte transplantation is an effective clinical strategy for treatment of related brain diseases.

5.1.1 Alzheimer’s Disease (AD) Recent data indicates that astrocytes mediate neuroprotective effects in AD mouse models. In one study, ablation of astrocytes resulted in increased amyloid pathology, worsening of the inflammatory profile, and reduced synaptic density (Mirzaei et al. 2022). In addition, Han and colleagues demonstrated that transplantation of hGPCs into neonatal immunodeficient mice resulted in enhanced long-term potentiation and improved cognition in human glial chimeric mice (Han et al. 2013). Therefore, more research groups have started to evaluate the therapeutic effects of astrocyte transplantation in AD. In 3xTg-AD mice, human CNS stem cells (HuCNS-SC cells) migrate and differentiate into immature neurons and glia and significantly increase synaptic and growth-associated markers (Ager et al. 2015). In addition, transplantation of HuCNS-SC cells improves cognitive behavior. These improvements in aged 3xTgAD mice were not associated with altered Aβ or tau pathology. Rather, the findings suggest that human NSC transplantation improves cognition by enhancing endogenous synaptogenesis (Ager et al. 2015). In another study, researchers directly transplanted astrocytes isolated from adult and neonatal mice into the hippocampi of transgenic APPSwe1PS1dE9 (APPdE9) mice. They found that most of the transplanted astrocytes were near Aβ deposits in the hippocampus of APdE9 mice. Further data revealed that both adult and neonatal transplanted astrocytes internalized human Aβ deposits in vivo, suggesting the role of astrocytes as active Aβ clearing cells in the CNS (Pihlaja et al. 2008). In addition, studies in a mouse model of human tauopathy supported the neuroprotective role of astrocytes – transplanting neural precursor cell-derived astrocytes showed a reduction in neuronal death in cortical areas (Hampton et al. 2010). Alternatively, one group autologously transplanted enteric glial cells (EGCs)

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isolated from the gastrointestinal nervous system into the brain of a rat model of AD generated by infusion of a toxic form of amyloid-β (1–42 peptide). These transplanted EGCs displayed functional similarities between the resident astrocytes in response to increasing plaque burden (Esposito et al. 2016). The EGCs also migrated to amyloid deposition sites and reduced fibrillar Aβ load and neurofibrillary tangle burden. Apart from that, these cells reduced inflammation in the brain. Furthermore, EGC engraftment improved both learning and spatial memory skills in these animals (Esposito et al. 2016). The underlying mechanisms may be related to decreased proinflammatory factors (TNF-α, PGE2, and IL6) and increased neurotrophic factors (NGF, BDNF, and GDNF) by these transplanted EGCs (Hastings et al. 2022). Together, these lines of evidence indicate that transplantation of iPSC-derived astrocytes may be a safe and effective therapeutic approach for treating AD in the future.

5.1.2 Parkinson’s Disease (PD) Despite α-synuclein being a predominantly neuronal protein, it has also been reported to aggregate in astrocytes (Braak et al. 2007). Specific upregulation of α-synuclein was also seen in astrocytes derived from patient iPSCs carrying LRRK2 mutation (kinase involved in autophagy and associated with an autosomal dominant form of PD) (di Domenico et al. 2019). Importantly, astrocytes have been shown to selectively express PD-related mutant A53T α-synuclein, which led to rapidly progressing paralysis in mice, accompanied by profound dopaminergic and motor neuron degeneration (Gu et al. 2010). Moreover, it has been demonstrated that PD-linked mutation in astrocytes alone is enough to cause neurodegeneration and α-synuclein accumulation (di Domenico et al. 2019). These findings highlight the important role of astrocytes in PD progression and indicate that astrocyte replacement may be an effective treatment for PD. Indeed, studies demonstrated that transplantation of astrocytes, which are differentiated from glial-restricted precursor cells (GRPs) (Proschel et al. 2014) or adult bone marrow mesenchymal stromal cells (Bahat-Stroomza et al. 2009), improved motor behavior and increased striatal dopamine production and neuronal survival. Further data showed that bioengineering approaches within astrocytes during transplantation maintained the beneficial phenotype of astrocytes (Song et al. 2018), enhanced local dopamine synthesis, and improved motor coordination in a rat model (Tornatore et al. 1996). In these bioengineering approaches, astrocytes were modified to artificially express TFs (Nurr1 and Foxa2) (Song et al. 2018) or tyrosine hydroxylase (TH) (Gu et al. 2010). Finally, co-grafting of astrocytes and neural progenitor cells into the striatum also led to enhanced behavioral recovery in PD mice that surpassed the therapeutic benefit of grafting these neural progenitors alone (Song et al. 2018). Together, transplanted astrocytes can provide different benefits in PD by secreting neuroprotective factors, degrading α-synuclein, reducing oxidative stress, restoring potassium buffering, and replenishing the resident astrocytic pool (Song et al. 2018).

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5.1.3 Huntington’s Disease (HD) A growing body of studies have implicated astrocytes in the pathological progression of HD. Specific expression of mtHtt in astrocytes was sufficient to induce certain kinds of pathology, including motor abnormalities, body weight loss, and lower life expectancy (Bradford et al. 2009). In addition, HD patient iPSC-derived astrocytes showed cytoplasmic vacuolation under basal cell culture conditions, suggesting that astrocytes are highly sensitive to mtHtt accumulation, and their dysfunctions occur in a cell-autonomous manner (Juopperi et al. 2012). Moreover, HD mice have also demonstrated altered spontaneous Ca2+ signaling in striatal astrocytes that had diminished frequency, amplitude, and duration compared to wild-type animals (Jiang et al. 2016). Scientists have already attempted to assess the potential therapeutic effects of transplantation of astrocytes in HD. Striatal transplantation of astrocytes derived from hGPCs improved electrophysiological properties, restored interstitial potassium homeostasis, and reduced striatal volume loss in HD mice (Benraiss et al. 2016). In addition, transplanted astrocytes significantly delayed motor and cognitive deterioration and extended survival in HD mice (Benraiss et al. 2016). These results suggest that astrocyte transplantation can be a cell-based strategy for ameliorating disease in this disorder. 5.1.4 Traumatic Brain Injury (TBI) TBI is among the leading causes of preventable disability in younger individuals (Hastings et al. 2022). Unlike neurodegenerative diseases where cellular dysfunctions occur in multiple brain regions, TBI represents a localized area of damage and inflammation. The local injury conditions make cell transplantation therapies more applicable for TBI treatment (Hastings et al. 2022). Astrocytes are activated in TBI and function directly in the brain injury (Yu et al. 2021). Therefore, transplantations of astrocytes have been used as potential strategies for TBI treatment. Astrocyte graft can fill up cavities and replenish lost cells in the damaged area and then alleviate the symptoms associated with trauma (Hastings et al. 2022). Furthermore, healthy transplanted astrocytes suppress astrogliosis of the resident cell population and re-organize the injured tissue to make axonal growth easier (Davies et al. 2006; Wu et al. 2013). Astrocytes also promote neuronal survival and encourage new neurite outgrowth by providing neurotrophic cues (Chu et al. 2014; Fan et al. 2013). Additionally, studies have demonstrated that transplanted human iPSCderived astrocytes can form close interactions with blood vessels (Krencik et al. 2011) and increase vascularization of lesioned areas (Kliot et al. 1990; Olby and Blakemore 1996). These findings show that astrocyte transplantation is an effective way to alleviate TBI and could help patients regain lost neurological functions and increase their capacity for independent living (Hastings et al. 2022).

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5.1.5 Ischemia/Stroke Cerebral ischemia, often caused by stroke, is one of the leading reasons for disability and death worldwide (Flynn et al. 2008). Ischemia can trigger excitotoxity in astrocytes, leading to a reduced ability of astrocytes to buffer extracellular glutamate as well as increased ATP release (Ashpole et al. 2013). Damage to astrocytic mitochondria was also observed in other studies, which further contributes to blood-brain barrier (BBB) breakdown (Nahirney et al. 2016) and glutamate transporter 1 (GLT1) downregulation (Ouyang et al. 2014). Astrocytes in the hippocampus are vulnerable to ischemia-induced mitochondrial damage and oxidative stress (Ouyang et al. 2007), which may be the underlying reason of frequently observed memory deficits following stroke. In order to rescue memory disorders after ischemic stroke, researchers co-transplanted NSCs alongside astrocytes, brain microvascular endothelial cells (BMECs), or both (Cai et al. 2015). Interestingly, while NSC graft alone did not affect the cognition of stroke animals, double (astrocytes + NSCs or BMECs + NSCs) or triple transplantation led to significant improvements (Cai et al. 2015). In addition, cyclin-dependent kinase 5 (CDK5) hyperactivation has been observed in several brain disorders and shown to induce pathologically activated states of astrocytes (Meyer et al. 2014; Su and Tsai 2011). It was therefore hypothesized that preventing CDK5 hyperactivation would promote transplanted astrocytes to maintain their non-pathologically activated states (Becerra-Calixto and CardonaGómez 2017; Becerra-Calixto et al. 2018). Indeed, knocking down astrocytic CDK5 prior to engraftment increased the ability of transplanted astrocytes to prevent local cell loss, enhance BBB recovery, and ultimately improve neurological and motor performance (Becerra-Calixto and Cardona-Gómez 2017; Becerra-Calixto et al. 2018). After stroke, transplanted astrocytes can replenish the resident neural network, protect the BBB, and improve blood flow to the brain by supplying neuro- and astro-protective factors such as erythropoietin (Gunnarson et al. 2009; Swanson et al. 2004). In summary, transplantation of astrocytes can replace apoptotic astrocytes, reduce inflammation, and improve functional outcome in models of AD, PD, HD, TBI, and stroke in brains. These results provide evidence that astrocyte transplantation may be an effective strategy for the treatment of multiple brain diseases. 5.1.6

Integration of Transplanted Astrocytes and Behavioral Improvements Transplantation of GPCs provides a potential therapeutic approach for some brain diseases. Before clinical application, it is necessary to demonstrate the incorporation of transplanted astrocytes into existing circuits. Zhang and colleagues provided the first in vivo evidence of the morphological and functional integration of transplanted astrocytes in a host brain (Zhang et al. 2016; Zhang and Chen 2017). They utilized in vivo two-photon Ca2+ imaging along with immunohistochemistry, fluorescent indicator labeling-based axon tracing, and correlated light/electron microscopy to analyze the profiles and functional status of transplanted astrocytes (Zhang et al. 2016). Morphological results indicated that, after transplantation into the

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Fig. 4 Morphological and functional integrations of transplanted astrocytes. a. Glial progenitor cells (green) are transplanted into the brains of adult mice. b. Transplanted astrocytes (green) can form morphological connections with neurons (tripartite synapse), astrocytes (gap junctions), and blood vessels (endfeet) in the brains of host mice. c. Transplanted astrocytes (green) can form newly established synaptic contacts with the host cholinergic afferents. The sensory-evoked Ca2+ responses in transplanted astrocytes were dependent on the functional expression of nicotinic receptors and the formation of synapse-like contacts with host cholinergic afferents from the basal forebrain. ER: endoplasmic reticulum

somatosensory cortex (Fig. 4a), transplanted astrocytes could, respectively, form gap junctions, tripartite synapses, and endfeet with host astrocytes, neurons, and microvasculature (Fig. 4b). Moreover, the transplanted astrocytes could respond with Ca2+ transients to sensory stimulation. These sensory-evoked responses are mediated by functionally-expressed nicotinic receptors and newly-established synaptic contacts with the host cholinergic afferents (Fig. 4c) (Zhang et al. 2016). In addition to the morphological and functional integration of transplanted astrocytes, a recent study demonstrated that transplanted astrocytes could improve the behavior of aging mice (Yang et al. 2022). In this study, GPCs derived from embryonic cortical NSCs were transplanted into the brains of aged mice (Fig. 5a). Their integration and intervention effects in the aged brain were examined 12 months after transplantation. Results indicated that transplanted astrocytes could migrate, differentiate, achieve long-term integration, and maintain much younger

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Fig. 5 The brain can be rejuvenated by transplantation of astrocytes. a. Glial progenitor cells can be generated from embryonic cortical neural stem cells in vitro and then transplanted into the brains of aged mice. Their integration and intervention effects in the aged brain were examined 12 months after transplantation. b. After transplantation they can migrate, differentiate, achieve long-term integration, and maintain much younger morphology in the aged brain. c. Age-dependent sensory response degeneration was reversed by GPC transplantation

morphology in the aged brain (Fig. 5b). More interestingly, age-dependent sensory response degeneration was reversed by GPC transplantation (Fig. 5c). This work demonstrated that morphological, functional, and even behavioral impairment can be alleviated by transplantation of astrocytes (Yang et al. 2022). These studies provide strong support for the use of GPC transplantation in future clinical treatment.

5.2

Treatment by iPSC-Derived Microglia

Microglia are specialized macrophages of the CNS that respond quickly to any pathological event in the brain (Parajuli and Koizumi 2022). However, when there is chronic inflammation, microglia may secrete various proinflammatory cytokines and mediators that initiate neural dysfunction and neurodegeneration (Parajuli and Koizumi 2022). In addition, in some diseases (e.g., LSDs), there are disorders caused by gene mutations in microglia (Platt et al. 2018). Therefore, microglial replacement could be an effective intervention for these pathological conditions.

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Hematopoietic stem cell transplantation (HSCT) is currently applied to treat LSDs (Biffi et al. 2013; Krivit 2002; McGraw et al. 2005). In these diseases, there is a group of inherited metabolic disorders caused by mutations in genes encoding lysosomal hydrolases, integral membrane proteins, and transporters (Neufeld 1991). By transplantation of HSCT, microglia are replaced with bone marrow-derived cells (Biffi et al. 2013; Krivit 2002; McGraw et al. 2005). However, busulfan-mediated myeloablation prior to HSCT caused rapid, complete, and permanent loss of adult neurogenesis, which may lead to patients’ cognitive deficits (Buchbinder et al. 2018; Sailor et al. 2022). Hence, it is desirable to develop an alternative method for replacing microglia without the need for myeloablation. A recent study successfully achieved transplantation of microglia through depletion and replacement of these cells without myeloablation in adult mice (Villa et al. 2018).

5.3

Treatment by iPSC-Derived Oligodendrocytes

Dysfunctions of oligodendrocytes contribute to demyelinating and dysmyelinating diseases of the CNS, and accidental, neurodegenerative, and psychiatric disorders (Mozafari and Baron-Van Evercooren 2021). Remyelination of axons promotes axon integrity, improves the deficient function, and protects neurons from subsequent axonal degeneration (Edgar and Garbern 2004; Popko 2010). Activation of the endogenous oligodendroglial pool seems to be feasible for MS, and cell transplantation has become one of the most promising strategies to achieve replacement of dysfunctional oligodendrocytes. Hence, the potential of different human cell types to produce myelin after transplantation has been explored in rodent models of dysmyelination or demyelination (Chanoumidou et al. 2020). Compared to rodent oligodendroglia, human oligodendroglia show a slow tempo of differentiation and extended period of migration (Chanoumidou et al. 2020). In the following portion, we will focus on the developments achieved in experimental cell therapy based on GPC engraftment for myelin disorders.

5.3.1 Pediatric Disease Targets of GPC-Based Therapy Many children suffer from diseases of myelin loss caused by metabolic demyelinations (e.g., Krabbe disease), LSDs (e.g., metachromatic leukodystrophy), astroglial pathology (e.g., Alexander’s disease), and so on. Because glial progenitors are both widespread and associated with oligodendrocytic production, GPCs seem to be a promising vehicle for dispersing oligodendrocytes throughout diseased brains, which highlights cell replacement as an attractive potential therapeutic strategy (Goldman et al. 2012). For LSDs, wild-type (WT) lysosomal enzymes may be released by donor cells and taken up by deficient host cells through the mannose-6-phosphate receptor pathway (Jeyakumar et al. 2005). Therefore, a small number of donor glia may provide sufficient enzymatic activity to correct the catalytic deficit and storage disorder of a much larger number of host cells (Jeyakumar et al. 2005). In a mouse model of mucopolysaccharidosis type VII, the cell-based rescue of enzymatically

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deficient host cells by WT donor NSCs was first reported. In this study, NSCs were neonatally implanted to the forebrain of mice with mucopolysaccharidosis type VII. These transplanted cells restored lost enzymatic functions of host mice (Snyder et al. 1995). Similarly, another study reported that human NSCs also achieved substantial enzyme replacement in β-hexosaminidase-deficient mouse with Sandhoff disease (Lee et al. 2007). Apart from that, for diseases that require both enzyme replacement and structural remyelination, intracerebral delivery of GPCs would seem an especially promising treatment approach. For example, metachromatic leukodystrophy (MLD) and Krabbe disease are both characterized by enzyme-deficiencies associated with early demyelination (Goldman et al. 2012). GPC grafts achieved broad parenchymal dispersal and integration, as well as enzymatic rescue and structural remyelination (Goldman et al. 2012) in both diseases. For diseases of congenital hypomyelination, experimental assessments of GPCs as vectors for remyelination have also occurred. Human GPCs were transplanted into newborn shiverer mice, a hypomyelinated mutant deficient in myelin basic protein, then spread widely throughout the brain, developed as oligodendrocytes, and yielded context-dependent myelination (Yandava et al. 1999). In addition, researchers established the integration of transplanted GPCs throughout the entire neuraxis, including the spinal cord and roots, as well as the entire brain, brainstem, cerebellum, and cranial nerve roots (Windrem et al. 2008). These data suggested that neonatal GPC implantation is an effective strategy to treat childhood disorders of myelin formation and maintenance.

5.3.2 Adult Disease Targets of GPC-Based Treatment In adults, some diseases induce oligodendrocytic loss, including diabetic white matter loss, TBI, and MS (Goldman et al. 2012). All of these are potential targets of GPC replacement therapy. However, the adult disease environment may limit the applications of GPC engraftment. For instance, researchers must overcome the chronically ischemic environment of diabetics and the inflammatory disease environments of MS before cell-based remyelination treatment (Franklin and Ffrench-Constant 2008; Ip et al. 2006). In MS, cell-based remyelination has always been an attractive method for treatment. But the inflammatory environment has made MS a difficult target for cell therapy (Goldman et al. 2012). Nonetheless, a new generation of immune modulators (e.g., natalizumab, alemtuzumab, rituximab) has substantially diminished disease recurrence, making cell replacement a tenable repair strategy (Weinstock-Guttman and Ramanathan 2012). This has demonstrated that transplanted human GPCs could mature as oligodendrocytes and myelinated residual host axons in lysolecithin-induced demyelinated lesions in the adult rat brain (Windrem et al. 2002). Hence, GPCs seem to be effective cellular vectors for adult remyelination, although the disease environment is more complex and makes adult targets less approachable than their pediatric counterparts.

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Conclusion

In the physiological and pathological functions of brains, neurons are quite literally only half of the story – the other half is glial cells. Glial cells sustain the homeostasis of the nervous system and are involved in various functions in the brain, such as the regulation of synapse formation, neuroinflammation, and lactate and glutamate levels (Kumar et al. 2022). Dysfunctions of glia are accompanied by the impairment of neuronal functions. The development of iPSC-derived neuroglial cellular models improved our understanding of neuroglial interactions under physiological and pathological conditions (Bigarreau et al. 2022). The use of pre-clinical chimeric models should also help to establish disease models for studying pathological mechanisms, drug screening, and so on (Mozafari and Baron-Van Evercooren 2021). Furthermore, considering the emerging role of glia in many brain disorders, glia transplantation is likely to become an effective approach, alone or in combination with transplantation of other cell types such as neurons or NSCs (Hastings et al. 2022). In autologous cell transplantation, fibroblasts or mesenchymal stem cells are harvested from patients and reprogrammed into iPSCs, which then differentiate into the glia-lineage cells ready for transplantation (Hastings et al. 2022). While autologous cell transplantation using iPSC-derived glia transplantation minimizes potential rejection and the extent of immunosuppression needed, there are some considerable limitations. These include the ability to generate the cell of interest rapidly and successfully, the safety and stability of the generated cells, and the heterogeneity among clones when considering the stability of their epigenetic traits (Chanoumidou et al. 2020). Predictably, with solutions of these above technical difficulties, iPSCderived glia will become more widespread during clinical treatment in brain diseases. Acknowledgments We thank Jia Lou for technical assistance. Funding This work was supported by the National Key R&D Program of China (no. 2018YFA0109600) and the National Natural Science Foundation of China (no. 81771175).

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Human-Induced Pluripotent Stem Cell-Based Model of the Blood-Brain at 10 Years: A Retrospective on Past and Current Disease Models Abraham J. Al-Ahmad

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Modeling Diseases at the BBB Using Induced Pluripotent Stem Cells . . . . . . . . . . . . . . . . . . . . 2.1 Adrenoleukodystrophy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Allan–Herndon–Dudley Syndrome (AHDS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Alzheimer’s Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Amyotrophic Lateral Sclerosis (ALS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Cerebral Hypoxia/Ischemia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 COVID-19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 GLUT1 Deficiency Syndrome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 Huntington’s Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.9 Neural Ceroid Lipofuscinosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.10 Pathogen–Host Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Limitations and Challenges of iPSC-Based Models of the BBB in Disease Modeling . . . 4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The initial discovery and derivation of induced pluripotent stem cells (iPSCs) by Yamanaka and colleagues in 2006 revolutionized the field of personalized medicine, as it opened the possibility to model diseases using patient-derived stem cells. A decade of adoption of iPSCs within the community of the blood-brain barrier (BBB) significantly opened the door for modeling diseases at the BBB, a task until then considered challenging, if not impossible. A. J. Al-Ahmad (✉) Department of Pharmaceutical Sciences, Jerry H. Hodge School of Pharmacy, Texas Tech University Health Sciences Center, Amarillo, TX, USA e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_645

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In this book chapter, we provided an extensive review of the literature on the use of iPSC-based models of the human BBB to model neurological diseases including infectious diseases (COVID-19, Streptococcus, Neisseria) neurodevelopmental diseases (adrenoleukodystrophy, Allan–Herndon–Dudley Syndrome, Batten’s disease, GLUT1 deficiency syndrome), and neurodegenerative diseases (Alzheimer’s disease, the current findings and observations, but also the challenges and limitations inherent to the use of iPSC-based models in reproducing the human BBB during health and diseases in a Petri dish. Keywords

Blood-brain barrier · In vitro · Stem cells

1

Introduction

The blood-brain barrier (BBB) is a component of the neurovascular unit (Fig. 1) formed by specialized brain microvascular endothelial cells (BMECs) surrounded by a basement membrane shared with pericytes, astrocytes, and neurons (Page et al. 2020; Sifat et al. 2019; Mager et al. 2017; Suzuki et al. 2016; Shah and Abbruscato 2014; Obermeier et al. 2013; Yang and Rosenberg 2011). The BBB plays an essential role in brain homeostasis, as it tightly regulates the diffusion of solutes and nutrients inside the brain parenchyma (by the presence of tight junction complexes), contributes to the brain glucose metabolism via the presence of a metabolic coupling, and limits the entrance of noxious substances (via the presence of efflux pumps in BMECs). Despite its potent ability to protect the central nervous system from disruption and invasion by exogenous organisms, the BBB can and will be part of the pathophysiology of many neurological diseases. Yet, assessing the cellular and molecular mechanisms of the BBB during such neurological diseases

Pericytes

Neurons

Tight junctions

Astrocyte end-feet

Basement membrane

Blood vessel lumen Brain microvascular Endothelial cells

Fig. 1 Schematic representation of the blood-brain barrier as a neurovascular unit

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remains challenging and limited, due to the nature of the BBB (located in microvessels) and its accessibility (extraction of microvessels from post-mortem brains). On the other hand, the use of in vitro models of the BBB (based on primary cultures and immortalized cell lines) to model diseases has in the past shown several limitations. Firstly, a common issue with primary cells is the rapid loss of their phenotype upon isolation often displayed as decreased barrier tightness and expression pattern compared to their in vivo counterparts (Lyck et al. 2009), but also by differences in the expression profile of certain signaling pathways. For instance, the hCMEC/D3 cell line (Weksler et al. 2005), an immortalized human BMEC line, expression profile highlighted the upregulation of several genes associated with endothelial cell activation following an inflammatory state. Some primary cultures of BMECs (originated from bovine and porcine sources) alleviate some of the issues encountered with common sources (e.g., humans, and rodents) as these models are known to form tight monolayers. However, their intrinsic nature makes the accessibility to molecular biology tools challenging, and therefore limits their wide-scale utilization behind drug permeability screening. Finally, another noticeable but important limitation of these models is the limited extent associated with them. Most of the studies remain first and foremost studies based on BMECs monocultures. Monocultures are essential to understand BMEC response and behavior during disease states at the cellular and molecular level but fail to integrate the cellular response, as they often omit the inclusion of astrocytes and pericytes in the culture system. Since the initial publication by Yu and colleagues (2007) on the derivation process of human somatic cells into induced pluripotent stem cells (iPSCs) 15 years ago, the adoption and implementation of iPSCs as a source for patientspecific cells to model diseases in a Petri dish. The adoption of iPSCs in disease modeling has been tremendous in the field of neurosciences during the past decade, becoming an innovative and highly sought (Vitrac and Cloez-Tayarani 2018; Li et al. 2018; Kim 2015; Zeng et al. 2014; Broccoli et al. 2014; Jung et al. 2012). Surprisingly, a decade after the seminal publication by Lippmann and colleagues of the initial differentiation protocol, the same level of attraction and adoption of an iPSC-based model of the BBB for disease modeling appears lower in the field. However, there are several publications by our group and others that have been diligent and productive to create momentum within the field. For instance, the seminal publication by Vatine and colleagues that described and characterized iPSC-derived brain microvessels endothelial cells (iBMECs) from patients suffering from Allan–Herndon–Dudley Syndrome (AHDS) trailblazed the use of patientderived iPSCs to model diseases at the BBB (Vatine et al. 2017). We further documented and published (Patel, R., Page, S., and Al-Ahmad, A. J. (2017) Isogenic blood-brain barrier models based on patient-derived stem cells display interindividual differences in cell maturation and functionality. J Neurochem 142:74–88.) a differentiation protocol allowing to obtain isogenic iBMECs, astrocytes and neurons from different control iPSC lines (Fig. 2). In this chapter,

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EC++ EC-Immature BMECs

Mature BMECs

Somatic cells from healthy patients Somatic cells from diseased patients

Astrocytes

Undifferentiated iPSCs

NIM 5 days NDM

Neural Stem Cells

Neural Prog. Cells

NDM 21 days NMM Neurons

Fig. 2 Schematic representation of the isogeneic model of the in vitro model of the human bloodbrain barrier from induced pluripotent stem cells as described by our group. Undifferentiated iPSCs can be directed towards iBMECs by following the differentiation protocol described by Lippmann and colleagues (Lippmann ES et al., Sci Reports 2014), or induced (by incubation in neural induction medium (NIM) and differentiated into neural progenitor lineage (by incubation in neural differentiation medium (NDM)) as described in our protocol (Patel R et al., J Neurochem 2017), with neural progenitor cells being further differentiated in astrocytes (using astrocytes differentiation medium, AMM) or neurons (using neuron maturation medium). Such approach provides a modular system allowing both monocultures and co-culture based models, with iBMECs grown on Transwell(R) inserts. while astrocytes and/or neurons grown as co-culture with indirect contacts, and assess the effect of a disease on the barrier function by measuring changes in tranendothelial electrical resistance (TEER) and permeability to various tracers and other small molecules

we will non-exhaustively cover the current literature and advances in modeling diseases at the BBB using iPSCs as a platform.

2

Modeling Diseases at the BBB Using Induced Pluripotent Stem Cells

2.1

Adrenoleukodystrophy

Adrenoleukodystrophy (ALD) is a rare genetic disease characterized by impaired metabolism of very long chain fatty acids (VLCFAs), resulting in their accumulation within the central nervous system white matter, resulting in demyelination, and eventually neuronal cell death. In patients suffering from the childhood cerebral form (ccALD, an X-linked form), the prognosis is bleak with patients surviving rarely more than a few years after the onset of the disease. The disruption of the BBB in ccALD patients is a known phenomenon, with experimental therapies showing signs of its recovery and repair in the literature (Orchard et al. 2019; Zierfuss et al. 2020; Lund et al. 2020). As of today, there is only one report of the iPSC model of ccALD at the BBB by Lee and colleagues (2018), in which the authors reported a significant decrease in the barrier function (as noted by decreased TEER, increased number of frayed junctions), and abnormal lipid inclusion in cells.

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Allan–Herndon–Dudley Syndrome (AHDS)

Allan–Herndon–Dudley Syndrome (AHDS) is a neurodevelopmental disorder classified as X-linked mental retardation (XLMR) characterized by a severe psychomotor and intellectual disability within the first year of life. The etiology of the disease is associated with a mutation in the SLC16A2 gene encoding for the monocarboxylate transporter 8 (MCT8), a solute carrier involved in the transport of the thyroid hormone T3, at the blood-brain barrier. The development of an animal model of AHDS was hampered by the presence of a rodent-specific organic anion transporter (Oatp1c1) which allows the transport of thyroxine (T4, precursor of T3 hormone), failing to completely recapitulate the phenotype. The characterization of an in vitro model of the human BBB based on iPSCs derived from AHDS patients by Vatine and colleagues may constitute the first documented case of modeling a disease at the BBB using iPSCs (Vatine et al. 2017). Interestingly, AHDS-iBMECs were unremarkable in terms of barrier function (TEER and permeability). However, these defective iPSC lines showed a significant decrease in T3 and T4 uptake (and diffusion across the monolayers) compared to parental controls. More importantly, Vatine and colleagues confirmed their observations by genetically modifying control iPSC lines by introducing a deletion into the gene using CRISPR/Cas9 technology. Conversely, correction of the defective gene in one of the ADHS-iBMECs with a functional copy of SLC16A2 was capable to rescue the phenotype. Taken together, this study set the stage for the proof of principle in modeling diseases at the BBB using iPSCs, but also initiated the possibility to investigate the presence of a barrier phenotype for neurological diseases in which the contribution of the BBB in neurological disease.

2.3

Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common type of dementia and constitutes the sixth cause of death in industrialized countries (Alzheimer’s 2015). It is characterized by neuronal cell death in the hippocampal region, progressing into the surrounding cortical regions. Until now, the etiology of the disease remains unclear; however, two concurrent hypotheses have been brought forward: the Aβ hypothesis (in which aberrant accumulation of Aβ peptides in the brain parenchyma are considered responsible for the disease) and the Tau hypothesis (in which Tau hyperphosphorylation within neurons is the key element of the disease). Until very recently, the pathophysiology was mostly centered around neurons. However, the work of Zlokovic and colleagues brought evidence of a BBB component involved in AD pathophysiology (Nation et al. 2019; Sweeney et al. 2019; Montagne et al. 2017; Ramanathan et al. 2015; Zhao et al. 2015; Winkler et al. 2015; Tarasoff-Conway et al. 2015). There is evidence of an “Aβ clearance hypothesis,” in which the BBB contributes to a “brain-to-blood” clearance via a pericyte and endothelial cellmediated clearance. AD occurrence is commonly divided into two forms: the sporadic form (representing about 80% of the total occurrence of the disease) and

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a genetic form (20%) commonly referred to as “familial forms of Alzheimer’s disease” (FAD). In these familial forms, several genes have been identified including APP, PSEN1, and PSEN2. Several studies, using iPSC-derived BMECs, investigated the effect of an Aβ40 and Aβ42-rich environment on barrier integrity (Williams et al. 2022; Raut et al. 2022; Blanchard et al. 2020; Rieker et al. 2019). Such Aβ-rich environment can represent the rich perivascular Aβ deposition observed around cerebral blood vessels as observed in patients suffering from cerebral amyloid angiopathy (CAA) (Ghiso et al. 2014; Yamada 2015; Viswanathan and Greenberg 2011). These studies showed the presence of a vasculotoxic effect of Aβ peptides on the BBB, as noted by the decreased cell viability, impaired barrier function, and altered energetic metabolism. Our group also demonstrated that iBMECs are capable of the uptake of Aβ40 and subsequently its diffusion across the BBB, in agreement with observations done by Zlokovic and colleagues (Sweeney et al. 2019; Nation et al. 2019; Montagne et al. 2017). In addition to assessing the intrinsic effects of Aβ peptides, three studies have investigated the contribution of genetic factors as observed in FAD patients on the BBB using iPSCs, highlighting the contribution of PSEN1 (and to a much lesser extent PSEN2) on an impaired barrier phenotype at the BBB (Raut et al. 2021; Oikari et al. 2020; Katt et al. 2019). In these studies, the authors have differentiated iBMECs from iPSCs obtained from FAD patients presenting mutations in either presenilin-1 (PSEN1) or presenilin-2 (PSEN2) genes. Presenilins are transmembrane proteins involved in the processing and cleavage of amyloid precursor protein (APP). Although their function appears well documented in neurons, their primary function at the BBB remains elusive. These three studies reported very similar outcomes in PSEN1-iBMECs compared to control iBMECs: PSEN1-iBMECs showed reduced barrier function (as noted by reduced TEER and increased permeability to paracellular tracers), impaired efflux pumps activity, and reduced tight junction (TJ) proteins. Moreover, our group showed that both PSEN1- and PSEN2-iBMECs have altered glucose metabolism (glucose uptake and glycolysis) and also aberrant Aβ40 secretion compared to the control (Raut et al. 2021). These results suggest that mutations associated with FAD, which were primarily centered on neurons, may affect the BBB as well and therefore could contribute to the pathophysiology of the disease. In conclusion, iPSC-derived BMECs have provided evidence of their possibility to provide information on the contribution of the BBB to Alzheimer’s disease.

2.4

Amyotrophic Lateral Sclerosis (ALS)

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by a selective and progressive fatal disease characterized by the loss of motoneurons in patients, which ultimately leads to their death. It is estimated that about 5–10% of ALS cases are classified as “familial forms” with identified genetic mutations.

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Various genes have been associated with ALS including mutations in C9ORF72, FUS, SOD1, or TDP43 (Brenner and Freischmidt 2022). A study published by Mohamed and colleagues using iPSCs derived from patients harboring mutations in SOD1 or in C9ORF72 reported an increased expression and activity of P-glycoprotein (ABCB1, an efflux transporter) in iBMECs co-cultured with ALS-astrocytes derived from ALS patients (Mohamed et al. 2019). Interestingly, their report documented an increase in iPSC-derived astrocytes from patients with a sporadic form or mutated SOD1, but not in patients with mutated C9ORF72. Unfortunately, this study did not further investigate how iBMECs generated from these patients yielded in terms of phenotype. Another study, performed by Katt and colleagues on two iPSC lines obtained from ALS patients (one harboring a SOD1 mutation, the other a mutation on C9ORF72) reported a deficient iBMEC phenotype marked by lower transendothelial electrical resistance (TEER), but also an altered glucose uptake and P-gp activity (Katt et al. 2019). Notably, differences in phenotypes were observed between these two iPSC lines, with the one harboring mutations in the C9ORF72 gene showing the worst phenotype outcome.

2.5

Cerebral Hypoxia/Ischemia

Hypoxia is environmental stress characterized by an impaired oxygen supply in regard of oxygen needs. Often, such oxygen impairment is elicited by a hypoperfusion state resulting in both a hypoxic and ischemic (lack of glucose and nutrients) status. Such condition is encountered in various stages of life including in premature neonates (hypoxic-ischemic encephalopathy) (Landucci et al. 2022), and healthy adults (acute mountain sickness, high altitude cerebral edema) (Dunn and Isaacs 2021), but also encountered in patients suffering from stroke injury or cardiac arrest (Sandroni et al. 2021). The effect of hypoxia/ischemia on the BBB is well-documented (Herrera and Gonzalez-Candia 2021; Dunn and Isaacs 2021) and is often accompanied by the onset of vasogenic edema (brain swelling) driven by the disruption of TJ complexes (claudin-5, occludin) via proteolysis mediated by various proteases such as matrix metalloproteinases (MMPs) (Baumann et al. 2022; Zhang et al. 2018; Turner and Sharp 2016; Suzuki et al. 2016; Engelhardt et al. 2015; Jin et al. 2015). Such disruption is commonly accepted to be driven via a VEGF-dependent mechanism. As previously mentioned, a major caveat of existing models is their poor barrier properties making difficult their representation and the complexity occurring in vivo. We contributed to assessing the ability of iPSC-derived BMECs to respond to cerebral hypoxia/ischemia in vitro with two different studies (Page et al. 2016, 2019). Compared to hCMEC/D3 cells, we were able to demonstrate that iBMECs were more responsive to chemical-induced hypoxia (CoCl2 treatment) than hCMEC/D3 cells but showed comparable outcomes than hCMEC/D3 when exposed to normobaric hypoxia. Furthermore, we also demonstrated that both oxygen and glucose deprivation (OGD) stress was necessary to maximally decrease the barrier

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function in our model. We have demonstrated that overall iBMECs monolayers showed higher HIF-1alpha levels (a major oxygen-sensing protein in mammalian cells) compared to hCMEC/D3 cells under normoxic conditions but showed a lower induction rate during OGD stress. Notably, treatment with HIF1 inhibitors reported in the literature only had marginal effects on maintaining the barrier function, while treatment with VEGF inhibitors used in the clinic (sorafenib and sunitinib) had deleterious effects on the barrier recovery during reoxygenation. Taken together, we had demonstrated that iBMECs can respond to hypoxia/ischemia similarly to existing models, but also highlighted issues encountered with small molecules inhibitors touted as beneficial against hypoxia-induced vasogenic edema in pre-clinical models (but failed to translate into efficacious therapies in clinical settings), suggesting that iPSC-based models of the BBB can serve as a surrogate to validate targets.

2.6

COVID-19

COVID-19 has been the first major pandemic of the twenty-first century, with over 600 million cases and 6 million deaths. The causing agent of COVID-19 is SARSCoV-2, a beta-coronavirus considered to have originated from bats and adapted to humans via mutations in its spike protein, resulting in its higher affinity to human ACE2 (angiotensin-converting enzyme 2). Although its primary tropism toward pulmonary tissues, the presence of neurological symptoms observed in COVID-19 patients raised the hypothesis of a possible neuroinvasion by the virus across the BBB. Two studies used iBMECs to assess such a hypothesis. The first study published was by Buzhdygan and colleagues (2020) who demonstrated the vasculotoxic effect of the S1 domain (cleaved domain following interaction between spike and ACE2) in iBMECs monocultures. In addition to its vasculotoxic, Rhea and colleagues reported the ability of S1 to diffuse across the BBB in both mice and humans (using iPSCs) (Rhea et al. 2020), albeit such diffusion was tributary to an amount of S1 significantly higher than reported in patients serum (including vaccinated patients) (Ogata et al. 2021), with a diffusion rate similar to albumin, hence suggesting that such diffusion may occur by passive absorption rather than a receptor-mediated transcytosis. Finally, a more recent but also more exhaustive study by Krasemann and colleagues (2022) shed light by directly investigating interactions between SARSCoV-2 and the BBB. The authors reported evidence of endothelial cell activation and inflammation in the brain vasculature of COVID-19 patients that died from the disease, but also evidence of the ability of SARS-CoV-2 to infect and replicate within iBMECs, suggesting that iBMECs may be infected and impaired as somatic endothelial cells.

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GLUT1 Deficiency Syndrome

GLUT1 Deficiency Syndrome (GLUT1DS) is a rare autosomal dominant neurological disease characterized by mutations in the SLC2A1 gene (Tang and Monani 2021; Bourque et al. 2021; Klepper et al. 2020; Koepsell 2020; Gras et al. 2014; Klepper 2012; Verrotti et al. 2012; Pascual et al. 2004; Seidner et al. 1998), resulting in a broad-spectrum impairment of glucose and lactate uptake at the BBB, commonly reported by a reduction of their CSF/blood level ratio lesser than 0.5. GLUT1DS patients suffer from a spectrum of clinical symptoms including epileptic seizures, movement disorders (including impaired gait and ataxia), as well as intellectual disability. Until now, there is no cure for the disease, with only interventions to address the symptoms by implementing a restrictive ketogenic diet as an adjuvant to the use of antiepileptic drugs (AEDs). One of the major challenges encountered in modeling GLUT1DS with iPSCs is the scarcity of iPSC lines available in the repository with only one iPSC publicly available (Meyer et al. 2018). Another challenge is determining which mutations of the disease are considered representative of the disease, as over 20 mutations have been until now reported in the literature. Finally, another issue encountered is the lack of proper parental controls, which would allow a direct comparison in the phenotype outcome observed between iPSCs. Recently our group developed an in vitro model of GLUT1DS using a wellknown iPSC line (iPS(IMR90)-c4 iPS line (Yu et al. 2007)), and CRISPR/Cas9 gene editing technology (Iqra et al. 2022). We intentionally introduced a frameshift mutation targeting the fourth transmembrane domain, resulting in a truncated form of GLUT1 (containing only the first three transmembrane domains with a non-sense fourth transmembrane domain). We demonstrated that undifferentiated iPSC clones were not affected by GLUT1 truncation in terms of viability or in terms of differentiation into iBMECs. However, we noted that such truncation significantly decreased glucose uptake and diffusion across iBMECs monolayers, ATP production deficit, and change in the metabolic profile. These GLUT1DS-iBMECs also showed a deficit in angiogenesis, nicely correlating with in vivo models of the disease.

2.8

Huntington’s Disease

Huntington’s disease (HD) is a rare neurodegenerative autosomal dominant disease characterized by a progressive onset of involuntary movements (chorea), mood, and cognitive impairments, with a fatal prognosis commonly associated with the disease (15–20 years after the onset of the disease). The pathophysiology of the disease can be resumed to an aberrational number of CAG repeats in the HTT gene, resulting in the aggregation of Huntingtin’s protein inside neurons, eventually leading them to their deaths. Notably, several studies reported an early disruption of the BBB (Di Pardo et al. 2017; Drouin-Ouellet et al. 2015). Two studies using iPSC from HD patients have been published so far: one from Lim and colleagues based on the adult form of the disease (Lim et al. 2017), and one

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model based on the juvenile form of the disease published by Linville and colleagues (2022). In both studies, iPSCs were capable of differentiation into BMECs, albeit resulting in impaired phenotype as marked by poor barrier properties, and inconsistent expression of TJ proteins. Interestingly, the study by Lim and colleagues reported an aberrant activity of WNT signaling in HD-iBMECs, while the study by Linville and colleagues reported an aberrant activity of VEGF signaling, suggesting a possible difference between the juvenile and adult form of HD impairment at the BBB.

2.9

Neural Ceroid Lipofuscinosis

Neural Ceroid Lipofuscinosis (NCLs) is a group of neurological diseases belonging to the umbrella of lysosomal storage disorders (LSDs). NCLs are considered autosomal recessive disorders except for adult NCLs (Kufs disease, Parry disease). NCLs are commonly characterized by the abnormal build of lipofuscin granules in cells. Under physiological conditions, such lipofuscin granules are degraded, while in NCL patients, such degradation is impaired leading to their building within the central nervous system and subsequently leading to neurotoxicity and neuronal cell death. Clinical manifestations of NCLs include neurological features (blindness, seizures, movement disorders) which are progressing as the disease stage advances over time. There are no cures and no treatments for NCLs, with patients rarely surviving to reach puberty or adolescence, even with lifelong assistance. As of today, there is only one study that assessed the effect of NCLs on the BBB using iPSCs. Kinarivala and colleagues (2020) assessed the phenotype of iBMECs differentiated from an iPSC line derived from a patient suffering from Batten’s disease (mutation in the CLN3 gene). Such CLN3-iBMECs displayed a poor barrier phenotype compared to a control iPSC line (iPS(IMR90)-c4), impaired vesicular trafficking, abnormal angiogenesis, and impaired autophagy. Notably, co-culture of healthy iBMECs monolayers with CLN3-neurons resulted in impaired barrier function suggesting that the mutation in other cells of the neurovascular unit may further aggravate the phenotype.

2.10

Pathogen–Host Interactions

The blood-brain barrier is naturally set to provide a formidable barrier to pathogens capable of infection of the central nervous system. However, a small but significant number of pathogens (ranging from viruses to fungi) are known to cross the bloodbrain barrier, perform their neuroinvasion and lead to severe infection of the CNS. This is particularly challenging, as most chemotherapeutic agents capable to fight off such infections also display a poor BBB penetration. The use of iBMECs to better understand the cellular and molecular mechanisms between Gram-positive streptococcus (Group B Streptococcus) or Gram-negative diplococcus (Neisseria meningitides) has been extensively promoted by Brandon Kim and Kelly Doran in

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several studies and reviews (Kim et al. 2017; Kim and Schubert-Unkmeir 2019; Martins Gomes et al. 2019; Espinal et al. 2022). For instance, these models have shown the ability of GBS to adhere to and invade iBMECs similarly to somatic counterparts. In addition, such infection results in the activation of iBMECs, increasing several pro-inflammatory cytokines (CXCL1, CXCL2, CXCL8), and decreased barrier function via a Snail1-dependent mechanism.

3

Limitations and Challenges of iPSC-Based Models of the BBB in Disease Modeling

In this book chapter, we have provided several examples of disease models at the BBB using iPSCs. We have highlighted the positive sides of such models and demonstrated the relevance of such models to better understand the cellular and molecular mechanisms of such diseases at the BBB, the contribution of the BBB in the pathophysiology of such disorders, and even possibly use such models for screening drug candidates capable to reverse or attenuate the disease. Although we have presented the use of iPSC-derived models of the BBB for disease modeling, it is also important to highlight the limitations and caveats inherent to such models. The first issue encountered with iPSC-based models of the human BBB is the phenotypic nature of the iBMECs obtained by differentiation. Since the original differentiation protocol was established by Lippmann and colleagues (2012), its subsequent improvements and iterations did not affect the overall differentiation protocol. This raised concern by Lis and colleagues who stated that iBMECs obtained using the Shusta protocol are not definitive iBMECs and rather differentiate into neuroepithelial cells (Lu et al. 2021a, b). Such studies remain to be replicated and corroborated by others, while Shusta and colleagues addressed the issue in a commentary shortly after such publication (Lippmann et al. 2020). Until now, iPSCderived BMECs have been behaving and living to most of the expectations of the community; however, taking a precautionary approach (and referring to iBMECs as BMEC-like cells) is recommended until the resolution of this controversy. The second issue encountered with the use of iPSCs for disease modeling at the BBB is the need for appropriate controls. During this chapter, we have seen on several occasions that iPSC lines of patients were available, but often lack the inclusion of matching parental controls. The inclusion of matching parental controls is essential to exclude variations in the phenotype observed. Therefore, it is important to consider when establishing iPSC lines from patients to include iPSC from somatic cells obtained from parental controls (e.g., siblings, parents). The third issue with iPSCs is the inherent risk of genetic drifting due to derivation. The derivation process of somatic cells into iPSCs heavily relies on epigenetic reprogramming, erasing the somatic epigenetic signature to reverse such cells into pluripotency (Rouhani et al. 2022). Hence, it is important to include several clones (minimum two clones) obtained from the same patient’s somatic cells, to remove the risk of wrongly associating a phenotype with a disease, when it may be a reflection of genetic variability.

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The fourth issue is the need for isogeneic models of patient-specific models of the BBB. In most of the studies cited in this chapter, we have seen that most of these studies rely on iBMECs monocultures. Such models are advantageous for understanding the phenotype at a molecular level; however, the reliance on a monoculture limits the representation of the model in terms of reflection of the in vivo counterparts. We have also seen at several instances how other elements of the neurovascular unit (e.g., astrocytes, neurons) influence iBMECs phenotype. Hence, it is important to promote studies that are more integrative of co-cultures and inclusive of the different elements of the neurovascular unit. Finally, one aspect of the iPSCs in disease modeling related to the genetic disease is the choice of mutations as representative of the disease.

4

Concluding Remarks

In this chapter, we have navigated through a decade of using iPSCs-derived BBB models, and their subsequent use for disease modeling. We have appreciated the diversity of applications of the type of diseases modeled, but we also have seen the absence of models published in the literature addressing important neurological diseases with a known BBB component such as epilepsies (drug resistance) or multiple sclerosis (in regards of leukocytes-endothelial cell interactions). We have seen that iBMECs as disease models share behavior similar to their primary and immortalized cells counterpart, but also raised the controversy of the very intrinsic endothelial cell identity of these iBMECs. Looking forward and trying to predict how the field will look like in 10 years is a subtle exercise of reading tea leaves. We can however expect to have revisions in the protocol to ensure a directed evolution of the differentiation protocol to ensure a cellular identity closer to the in vivo BBB, the integration of the different components of the neurovascular unit (e.g., astrocytes, pericytes, neurons) in an isogeneic manner and using next-generation engineering techniques (microfluidics, 3-D printing) to reconstitutes a cytoarchitecture closest of the in vivo as we can, to ensure that such models closely match the in vivo situation. In conclusion, this decade of the iPSC-based model of the BBB and their use to model diseases at the BBB have shown promising results and we can expect that within the next decade such models will increase the diversity of diseases modeled, but also improve in quality.

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Human Retinal Organoids in Therapeutic Discovery: A Review of Applications Lin Cheng and Markus H. Kuehn

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Research that Paved the Way for RO Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Methods of Induction of Human ROs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 The SFEBq (3D) Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 The 3D-2D-3D Culture Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Human ROs Are Used Extensively to Study Disease Mechanisms . . . . . . . . . . . . . . . . . . . . . . 5 Human RO-Derived Cells Are a Valuable Resource for Biobanking for Regenerative Medicine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Dissociated Photoreceptor Transplantation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Dissociated RGC Transplantation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 RPE Transplantation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Retinal Sheet Transplantation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Challenges of Cell Replacement Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Human RO-Derived Cells Are Widely Used for Disease Modeling . . . . . . . . . . . . . . . . . . . . . 7 Use of Human ROs for Therapeutic Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Drug Toxicity and Efficacy Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Gene Therapy and Genetic Editing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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L. Cheng (✉) Department of Ophthalmology and Visual Sciences, University of Iowa Carver College of Medicine, Iowa City, IA, USA Center for the Prevention and Treatment of Visual Loss, Veterans Affairs Medical Center, Iowa City, IA, USA e-mail: [email protected] M. H. Kuehn Department of Ophthalmology and Visual Sciences, University of Iowa Carver College of Medicine, Iowa City, IA, USA Center for the Prevention and Treatment of Visual Loss, Veterans Affairs Medical Center, Iowa City, IA, USA Institute for Vision Research, University of Iowa Carver College of Medicine, Iowa City, IA, USA # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_691

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8 ROs Can Be Integrated with Other Technologies to Broaden the Range of Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Challenges of Current RO Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 Variation Limits Reliability and Producibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Cryopreservation Compromises the Morphology and Cellularity of ROs . . . . . . . . . 9.3 Degeneration of Retinal Cells with Prolonged Culture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4 The Absence of Vascular and Glial Cells Limits the Use of ROs . . . . . . . . . . . . . . . . . . 10 Outlook and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Human embryonic stem cells (hESCs)- and induced pluripotent stem cells (hiPSCs)-derived retinal organoids (ROs) are three-dimensional laminar structures that recapitulate the developmental trajectory of the human retina. The ROs provide a fascinating tool for basic science research, eye disease modeling, treatment development, and biobanking for tissue/cell replacement. Here we review the previous studies that paved the way for RO technology, the two most widely accepted, standardized protocols to generate ROs, and the utilization of ROs in medical discovery. This review is conducted from the perspective of basic science research, transplantation for regenerative medicine, disease modeling, and therapeutic development for drug screening and gene therapy. ROs have opened avenues for new technologies such as assembloids, coculture with other organoids, vasculature or immune cells, microfluidic devices (organ-on-chip), extracellular vesicles for drug delivery, biomaterial engineering, advanced imaging techniques, and artificial intelligence (AI). Nevertheless, some shortcomings of ROs currently limit their translation for medical applications and pose a challenge for future research. Despite these limitations, ROs are a powerful tool for functional studies and therapeutic strategies for retinal diseases. Keywords

Drug discovery · Drug screening · Eye diseases · Gene therapy · Genetic editing · Human ESCs · Human iPSCs · Regenerative medicine · Retinal degenerative diseases · Retinal organoids (ROs) · Transplantation

1

Introduction

Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) are two types of pluripotent stem cells. They have the capacity to self-renew, divide continuously in an undifferentiated state, and differentiate into any cell type present in the adult body. Retinal organoids (ROs) are three-dimensional aggregates of cells that are self-organized into retina-like tissues. ROs contain seven different cell types found in the human retina, including the neural retina and the retinal pigment epithelium (RPE). The neural retina portion of the RO contains all major retina-

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specific cell types: amacrine, bipolar, horizontal, retinal ganglion cells (RGCs), Müller glia, and rod and cone photoreceptors. Human ESCs- or iPSCs-derived ROs mimic the human retina in the expression profiles of cell differentiation markers, retinal disease genes, and mRNA alternative splicing, and exhibit electrophysiological functions (Kim et al. 2019). ROs also recapitulate the developmental trajectory of the retina in vivo. Thus, ROs open new avenues for research into human organ development, eye disease modeling, and gene therapy. Growing primary cultures of retinal cells can be challenging due to the difficulty of obtaining human eye samples. Additionally, the various types of retinal cells require different microenvironments to provide the proper trophic support, cellular organization, and synaptic connections to confer visual function (Eldred and Reh 2021). The integrity of primary cells is usually compromised due to axotomy, lack of blood flow, or the absence of biomechanical support. These factors lead to limited viability and metabolic artifacts in cultured cells (Akerstrom et al. 2017). These issues are significantly less of a concern with ROs. ROs are ex vivo miniature organs that are similar to human retinas at the cellular, molecular, and functional levels (Cowan et al. 2020; Sridhar et al. 2020). The advantages of ROs are as follows: (1) Unlimited supply. Since human ESCs or iPSCs are self-renewable, it is, in theory, possible to produce an unlimited number of ROs. (2) Faster than animal models. Human organoid cultures can be established with a high success rate within a few weeks or months, thus saving considerable time and resources when compared to the establishment of rodent models. (3) Can be cultured for several months to 2 years in vitro. (4) Allow investigation of the effects of a single parameter in a multicellular environment. (5) Can generate patient-specific iPSCs with this patient’s genome and differentiate into ROs. Patient-derived organoids are invaluable in personalized medicine, providing robust personalized data, including the effect of specific mutations on drugs (Kim et al. 2020). (6) ROs allow more clinical relevance than animal models; patient-specific ROs maintain the individual’s genomic and epigenetic memory (Wang et al. 2018). Overall, ROs are a valuable tool for the study of human retinogenesis and retinal diseases. They are also an ideal resource for cell replacement, a robust platform for evaluating the toxicology, pharmacokinetics, and pharmacodynamics of candidate drugs, as well as the development of engineered viral vectors (Kondo and Inoue 2019). However, RO technologies would benefit from improvements in reproducibility and long-term cell survival, two factors that currently hinder their utility for preclinical application in drug discovery. This chapter reviews the applications of ROs for retinal drug discovery and the challenges of RO technology.

2

Research that Paved the Way for RO Technology

The serum-free culture of embryoid body-like aggregates with quick aggregation (SFEBq culture) method was introduced in 2011. Yet, prior to this landmark study, substantial progress had been made in developing methods to differentiate human stem cells into retinal cells. Earlier studies generated retinal cells by combining

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retinal progenitor cells (RPCs) with retinal explants or other retinal cells (Yue et al. 2010; Tomita et al. 2006). These RPCs and retinal cells were obtained from ESCs, iPSCs, or harvested directly from animals (Tucker et al. 2011a; Lamba et al. 2010; Meyer et al. 2011; Lamba et al. 2006; Van Hoffelen et al. 2003). The extrinsic environment of retinal cells/explants helps RPCs to differentiate into retinal cells, both in vivo and in vitro (Lamba et al. 2006). This spontaneous differentiation method was able to generate photoreceptors (Banin et al. 2006), RGCs, amacrines, cone-like cells, astrocytes (Banin et al. 2006), RPE (Vaajasaari et al. 2011), and other cell types. Yet, limitations of this method include low efficiency, poor cell purity (5–30%), lack of cell maturation, and low cell integration and functionality upon transplantation. Eventually, investigators developed other methods to generate large numbers of retinal cells by utilizing forced expression of transcription factors (TFs) or controlled signaling of RPCs. First, Amirpour et al. reported that RPCs can be generated from hESCs using a combination of several growth factors including noggin, DKK-1, IGF-1, and bFGF (Lamba et al. 2010; Amirpour et al. 2012). WNT and bone morphogenetic protein (BMP) signaling inhibition is important for eye field generation following embryonic body (EB) formation (Reh et al. 2010). Then, RPCs were directed to further differentiate into retinal cells by TFs or by manipulation of RPC signaling. For instance, forced expression of CRX (cone-rod homeobox) directs mouse and human RPCs to differentiate into photoreceptors (Jomary and Jones 2008; Jomary et al. 2010). Exposure of mouse neural progenitors to bFGF and sonic hedgehog (SHH) drives their differentiation into RGC-like cells (Jagatha et al. 2009). Directed expression of PAX6 (Paired Box 6) in human RPCs led to differentiation into RGC-like cells (Kayama et al. 2010; Suzuki et al. 2012). RGC-like cells can also be generated from RPCs through forced expression of Math5 or Brn3, which is a downstream effector of Pax6 (Chen et al. 2010; Liu et al. 2000; Brown et al. 1998). WNT, BMP, IGF, and FGF2 (Jagatha et al. 2009) have been reported to force ESCs/iPSCs to generate RPCs. On the other hand, photoreceptors and RGCs were successfully developed from RPCs with a forced signaling control. RX (retinal homeobox protein), MITF (melanocyte inducing transcription factor), PAX6, and VSX2 (visual system homeobox 2) help RPC specification into photoreceptors. Retinoic acid (RA) and taurine are important for photoreceptor differentiation and maturation. Photoreceptors were also induced from RPCs by SHH and/or the coculture of rabbit RPE cells (Amirpour et al. 2012). Stem cells treated with DKK-1, noggin, and DAPT are pushed to differentiate into RGC-like cells and to exhibit RGC markers and function. Retinal cells generated by these methods are abundant and their purity is improved (~90% vs. 5–30% in the coculture method). Still, their function remains compromised, and their long-term survival, integration into the host retina, and ability to form neural circuits is unsatisfactory. These deficiencies were largely remedied by the introduction of the two culture methods described below.

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Methods of Induction of Human ROs

An organoid is a three-dimensional (3D) structure grown from stem cells and consisting of organ-specific cell types that self-organize through cell sorting and spatially restricted lineage commitment. ROs are organoids that mimic the human retina. Individual reports have described different methods to generate ROs, but most are based on the following two methods. These two protocols are widely accepted, standardized approaches to generate ROs.

3.1

The SFEBq (3D) Method

The SFEBq method is a seminal achievement described by Yoshiki Sasai’s group. This method was first reported to generate ROs using the mouse ESCs in 2011 (Eiraku et al. 2011) and using human ESCs in 2012 (Nakano et al. 2012) (Fig. 1a). The cells are cultured in 3D suspension for the entire process. The procedure for inducing hESCs- or hiPSCs-derived ROs is detailed in Nakano et al. (2012). This method utilizes a WNT inhibitor (IWR1e) to induce retinal epithelia (a single-lumen vesicle) with anterior neuroectodermal/ectodermal fate in the extracellular matrix Matrigel. Hedgehog smoothened agonist (SAG) is added between 12 and 18 days to enhance the transition from the anterior neural lineage to a full retinal lineage. A Notch signaling inhibitor (DAPT) is added to increase photoreceptor yield. Inhibiting GSK3 (using CHIR99021) and FGFR (by SU5402) induces the transition from neural retina (NR) tissue to RPE, while removing this inhibition facilitates the reversion of this RPE-like tissue back to the NR fate (Kuwahara et al. 2015). In brief, the first step is to generate RPCs (from day 0 to day 18). On day 0, subconfluent human iPSCs are dissociated into single cells using TrypLE Express enzyme. They are plated at 12,000 cells/well in low-cell adhesion V-bottomed 96-well plates; the medium consists of 100 μL of retinal differentiation medium (RDM), 2 μM ROCK inhibitor thiazovivin, and 3 μM IWR1e. RDM is GMEM supplemented with 20% KSR (KnockOut™ Serum Replacement), 1× minimum essential media-non-essential amino acids (MEM-NEAA), 1 mM pyruvate, 0.1 mM β-mercaptoethanol, and 1× penicillin/streptomycin. On day 2, 20 μL RDM supplemented with 3 μM IWR1e and 6% Matrigel is added to each well (3 μM IWR1e and 1% Matrigel at final concentration). During days 6–12, RDM containing 3 μM IWR1e and 1% Matrigel is exchanged every 3–4 days. On days 12–18, RDM containing 10% fetal bovine serum (FBS), 100 nM SAG, and 1% Matrigel is changed every 3–4 days. On day 18, RDM is replaced with RO maintenance medium, DMEM/F12-GlutaMAX supplemented with 1% N2, 10% FBS, 0.5 μM all-trans retinoic acid (RA), 0.1 mM taurine, and 1× penicillin/ streptomycin. Optionally, ROs can be excised from the main body on day 18–24 and cultured in suspension. It was later found that transient early treatment with bone morphogenic protein 4 (BMP4, starting at 1.5 nM or 55 ng/mL on day 6 and subject to half-dilution every third day to day 18) could replace Matrigel to induce hiPSCs to ROs very efficiently. In this method, RDM is replaced with gfCDM + KSR medium,

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Fig. 1 A comparison of the SFEBq (3D) method and the 3D-2D-3D culture method for culturing hESCs or hiPSCs-derived retinal organoids (ROs). (a) The first method pioneered by the Sasai group by introducing the Matrigel to induce ROs. This method has been further developed into another method to replace Matrigel with BMP4 to induce neuroepithelium differentiation. At day 300, the outer segment of the photoreceptor (indicated by the arrow) is presented at the exposed

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which is half IMEM, half Ham’s F12, 10% KSR, 1× GlutaMAX, 1% chemically defined lipid concentration, monothioglycerol, and 1× penicillin/streptomycin. IWR1e is no longer needed in the BMP method (Fig. 2a). Subsequently, retinal cells are generated with different selective cultures. On day 18, the floating aggregates are transferred to 96-well flat bottom ultra-low attachment microplates and cultured in NR-selective culture, RPE-selective culture, or induction-reversal culture (Kuwahara et al. 2017) (Fig. 2a). The medium is changed every 3–4 days. 1. NR-selective culture. From day 18 to the observation date, replace RDM with NR maintenance medium, which is DMEM/F12-GlutaMAX medium supplemented with 10% FBS, 1× N2 supplement, 0.5 μM RA, 100 μM taurine, and 1× penicillin/streptomycin. NR tissues grow continuously under these conditions for several weeks. 2. RPE-selective culture. From day 18 to day 23, change with RPE induction medium, which is DMEM/F12-GlutaMAX medium supplemented with 1× N2 supplement, 1× penicillin/streptomycin, 3 μM CHIR99021, and 5 μM SU5402. On day 24, change with RPE maintenance medium, which is DMEM/F12GlutaMAX medium supplemented with 1× N2 supplement, 1% FBS, 3 μM CHIR99021, and 1× penicillin/streptomycin. RPE tissues grow slowly compared with NR tissues. 3. Induction-reversal culture. In this method, culturing retinal epithelium in RPE induction medium from day 18 to 23 induces a transition from NR to RPE fate. Then, a switch back to NR maintenance medium on day 24–35 facilitates the reversion of RPE-biased epithelium back to NR fate (Kuwahara et al. 2017). This method will result in turnip-shaped ROs with both RPE and NR. The NR-RPE tissue boundary self-forms a ciliary margin-like tissue on culture day 63. These ciliary margin-like tissues are stem cell niches that can form neurospheres (Kuwahara et al. 2015). In brief, on days 18–23, change to RPE induction medium, and switch to NR maintenance medium from day 24 to day 150 or later. NR is formed near the ciliary margin-like tissue.

 ⁄ Fig. 1 (continued) surface of ROs. The retinal differentiation medium (RDM) contains GMEM and 20% KSR (vol/vol). Scissors represent dissecting the neural retina-like tissue from the stem cell aggregates under a stereo microscope at day 18. After day 18, the ROs are cultured in RO maintenance medium containing DMEM/F12, 1% N2, 10% FBS, and taurine. The development of ROs is listed in the timeline. (b) The second method is 3D-2D-3D method. In this method, the embryonic bodies (EBs) are formed and are further attached to the plate. The EBs will spontaneously develop into the ROs or brain organoids. The brain organoids are discarded, and the ROs are collected and cultured. Scissors represent dissecting the neural retina-like tissue from the stem cell aggregates under a stereo microscope. The development of ROs is listed in the timeline. hESCs, Human embryonic stem cells; hiPSCs, human induced pluripotent stem cells; RA, all-trans retinoic acid

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Fig. 2 The bone morphogenic protein (BMP)-modified SFEBq (3D) method and 3D-2D-3D culture method for culturing hESCs or hiPSCs-derived retinal organoids. (a) BMP4 is added from day 6, and gradually reduced to half every 3 days to induce the RO differentiation. At day 18, ROs are cultured with the neural retina (NR)-selective culture, RPE-selective culture, or induction-reversal culture. The basal medium for these three differentiation paths is DMEM/F12 and 1% N2. NR-selective culture adds 10% FBS, 5 μM RA, and 100 μM taurine from day 18 to the observation date. RPE-selective culture is adding 3 μM CHIR99021 and 5 μM SU5402 from day 18–23 and then changing to 3 μM CHIR99021 and 10% FBS afterward. Induction-reversal culture is adding 3 μM CHIR99021 and 5 μM SU5402 from day 18 to 23 and then switching to NR maintenance medium, which contains 10% FBS, 5 μM RA, and 100 μM taurine. Scissors represent dissecting the neural retina-like tissue from the stem cell aggregates under a stereo microscope. (b) BMP4 is added from day 6 and gradually reduced by half to day 18 to improve the efficiency of generating ROs over BOs. The method is like the original protocol but adding BMP4 treatment in the early developmental time and after the ROs have been generated; they are subjected to different fate cultures of NR-selective, RPE-selective, or induction-reversal selective. Scissors represent dissecting the neural retina-like tissue from the stem cell aggregates under a stereo microscope

3.2

The 3D-2D-3D Culture Method

In the 3D-2D-3D method, 3D embryoid body (EB) aggregates formed in suspension by hiPSCs or hESCs are temporarily maintained adherent (2-dimensional, 2D) during retinal domain (mainly RPCs) formation. They are then excised and lifted for 3D suspension culture (Zhong et al. 2014; Meyer et al. 2009). The cells follow

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intrinsic mechanisms to develop into ROs or brain organoids (BOs) with minimal extrinsic stimulation for RO differentiation. In brief, in this method, first EBs are formed (3D aggregates) from hiPSCs or hESCs. Then, EBs are allowed to attach to the culture plate surface and form patches of retinal epithelia consisting of RPCs (2D culture). The retinal epithelial patches are lifted from the tissue culture plate with a 30G sterile needle attached to a 1 mL syringe and cultured in suspension (3D culture). The retinal progenitor cells in the retinal domains self-assemble and form ROs with stratified retinal layers (Fig. 1b). One disadvantage of this method is that it requires extensive labor to manually lift the retinal epithelia and is not well suited to generate large quantities of ROs. Frequently, BOs are generated alongside the ROs and need to be removed manually. Akin to the SFEBq method, a transient BMP4 treatment from day 6 to day 18 significantly favors ROs over BOs in the 3D-2D-3D method as well (Fig. 2b). BMP4 treatment during the early differentiation stage prevents hESCs-derived forebrain neuroepithelium from adopting the telencephalic fate and redirects it into the retinal progenitors (Kuwahara et al. 2015). In this method, the hiPSCs or hESCs are detached by dispase and dissociated into small clumps in mTeSR+ medium plus 10 μM (-)-blebbistatin (ROCK inhibitor). Over the following days, the aggregates are gradually switched from mTeSR+ medium to neural induction medium (NIM) containing DMEM/F12 (1:1), 1% N2 supplement, 1× MEM-NEAA, and 2 μg/mL heparin. On differentiation day 7, the aggregates are seeded onto growth-factor-reduced Matrigel (Corning)-coated dishes with NIW. At day 16, the medium is switched to “day 16” medium [MEM/F12 (3:1) supplemented with 2% B27 (without vitamin A), 1× NEAA, and 1% penicillin/ streptomycin]. Between days 21 and 28, the horseshoe-shaped neural retina domains are dissected using a sharp needle under the microscope and cultured in suspension in low-adhesive 96-well plates to form 3D ROs. In this long-term suspension culture, the medium is changed to “day 42” medium, which is a day 16 medium supplemented with 10% FBS, 100 μM taurine, and 1× GlutaMAX (Fig. 1b). To promote photoreceptor maturation, suspension cultures of organoids can be supplemented with 1 μM RA every 48 h between days 63 and 98. Like in the SFEBq method, it is suggested that ROs are cultured in an agitated culture system to reduce the degeneration of neurons (Fig. 1b).

3.3

Summary

The most frequently used methods to differentiate hESCs or hiPSCs into ROs are the SFEBq (3D) culture method and the 3D-2D-3D culture method. The first method uses the quick reaggregation approach in 96-well U- or V-bottomed plates to form the self-organized stratified NR and RPE. The second method forms the EBs suspension (3D) and lets the EBs attach (2D) and randomly develop into the retinal or brain organoids following the intrinsic mechanism. Then, ROs are selected and cultured in suspension (3D). The difference between these two methods is the quantity and quality of ROs generated. Without the addition of BMP4, the first method generated 12.3 ± 11.2

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retinal domains, and the second method generated 6.3 ± 6.7 retinal domains, per differentiation (Berber et al. 2021). Therefore, the efficacy of the first 3D method is higher than that of the 3D-2D-3D method. Both methods produce ROs of similar quality, although neither the 3D method nor the 3D-2D-3D method results in ROs that always show satisfactory lamination of NR. Consequently, we cannot conclude that one method is inherently superior to the other. One method may work well for one lab but not work for another, perhaps due to differences between cell lines used or other factors that lead to variability in RO culture systems. Fortunately, modifications and improvements of these two methods are continuously ongoing. One example is the introduction of transient early BMP4 treatment, which strikingly improves the lamination of ROs (Kuwahara et al. 2015).

4

Human ROs Are Used Extensively to Study Disease Mechanisms

The advantage of human ROs is that they maintain the genetics of the individuals from which the stem cells are derived. As a result, they can be used to find diseaserelated variants. In addition, ROs allows detailed observation of stem cell morphogenesis, maintenance, and differentiation that resembles primary tissues. This enhances the potential to study both human physiology and development. Numerous studies have employed ROs to uncover cellular mechanisms of disease. For example, Daniszewski and his colleagues carried out a large-scale single-cell RNA-seq study of hiPSCs-derived ROs from primary open-angle glaucoma (POAG) and healthy individuals and found 97 statistically significant RGC-specific expression quantitative trait loci (Daniszewski et al. 2022). Likewise, progressive photoreceptor degeneration was observed in ROs derived from a retinitis pigmentosa (RP) model due to mutations in the pre-mRNA processing factor (PRPF31) gene (Rodrigues et al. 2022). Moreover, ROs can be used to study their own interactions with vessels, immune cells, stromal cells, other organoids, environmental factors, and pathogens such as viruses, parasites, and bacteria. One example is a recent study using ROs to study the effects of retinal infection by SARS-CoV-2. The study found that SARSCoV-2 can infect and replicate in human ROs, infecting various retinal lineages including RGCs and photoreceptors (Menuchin-Lasowski et al. 2022). Another study analyzed the influence of fine inhalable particles (particulate matter less than 2.5 μm in diameter, PM2.5) on the developing retina. The authors found that PM2.5 suppresses cell proliferation and promotes cell apoptosis, thereby potentially contributing to abnormal human retinal development (Zeng et al. 2021). ROs have also been used for transcription and multi-omic analysis. Examples include studies that revealed cell-specific cis-regulatory elements and non-coding genetic disease risk mechanisms in the developing ROs (Thomas et al. 2022) or the presence of disease-causing mutations in previously unrecognized exons exclusively expressed in the retina (Tucker et al. 2011b). Overall, human ROs provide a valuable tool for mechanistic studies by allowing researchers to observe the retina in a controlled environment that closely mimics

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Fig. 3 Application of human retinal organoids in basic research, biobanking, disease modeling, and therapeutic discovery. In basic research, ROs can be used for studying the pathophysiologic mechanism, RO development, and interaction with vessels, immune cells, stroma cells, etc. In biobanking, the patient-specific ROs can be used for cell transplantation for regenerative medicine in the manner of dissociated cells or retinal sheets. Or it could be used for organ development. The third application is that ROs can be used for eye disease modeling, to study the genomic or epigenetic variants, or to study developmental eye diseases. The fourth application is therapeutic development. The ROs can be used to develop gene therapy and genetic editing for precision medicine and be used for high-throughput drug screening and cell therapy

in vivo conditions. Such studies are invaluable to understanding how diseaseassociated mutations contribute to the pathogenesis of retinal disease and will be helpful in eventually discovering treatments (Fig. 3(1)).

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Human RO-Derived Cells Are a Valuable Resource for Biobanking for Regenerative Medicine

Replacing cells lost due to retinal degeneration with new cells that functionally connect to the remaining host retina could regenerate impaired vision and restore eyesight. RO-derived cells have exceptional promise for regenerative medicine; they have emerged as a valuable and unlimited resource for cell replacement therapy (Fig. 3(2)). Transplanting retinal cells or RPCs from ROs following selection by flow cytometry or transplantation of retinal sheets has been extensively investigated in preclinical studies (Wang et al. 2019; Zou et al. 2019). To increase the benefit of the grafted cells, many studies have combined cells or retinal sheets with biodegradable scaffolds to help with cell survival, migration, and integration (Luo et al. 2021). Two points must be considered before transplantation. First, it is crucial to determine whether dissociated cells, a mixed cell population, highly enriched cells, cells within a scaffold, or bioengineered sheets are to be transplanted. An equally important decision is the selection of a suitable disease model. A suitable disease model allows the determination of a treatment window in the natural progression of the disease that permits successful therapy. In many cases, secondary disease mechanisms, including gliosis, vascular attenuation, or pronounced neuroinflammation, may become significant barriers to the survival, integration, or function of transplanted cells.

5.1

Dissociated Photoreceptor Transplantation

Numerous studies have reported that transplantation of human RO-derived photoreceptors can partially restore vision in animals with retinal degenerative diseases, including Leber congenital amaurosis (LCA) (Kruczek et al. 2017), age-related macular degeneration (AMD) (Ribeiro et al. 2021), rod-cone dystrophies (Gagliardi et al. 2018; Santos-Ferreira et al. 2016), and other degenerative photoreceptor diseases (Lin et al. 2020). The photoreceptors in ROs have a well-formed outer nuclear-like layer containing photoreceptors with inner segments (IS), connecting cilium, and outer segments. One group transplanted human photoreceptors into a mouse model of human achromatopsia prior to photoreceptor degeneration (Gasparini et al. 2022). They isolated cone cells from ROs, transplanted them into the subretinal space, and saw extensive incorporation of photoreceptors into the host retina. The transplanted photoreceptors polarized with the formation of inner and outer segments as well as cilia. These grafted cells also formed synaptic ribbons and putative synapses. They also interacted with the host Müller glia and bipolar cells. The investigators also carried out muti-electrode array recordings which showed a graft-mediated light response. Another group has shown that human RO-derived cone photoreceptors elaborate nascent outer segments (OS) and form putative synapses with recipient murine bipolar cells (Ribeiro et al. 2021). Their transplanted RO-derived cone photoreceptors survived in the outer retina for up to 4 months post-transplantation in rd1 mice.

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One of the most significant factors limiting transplantation success is immune rejection of the grafted material, and host immune suppression is generally necessary for prolonged xenograft survival. For example, immunosuppression through genetic ablation of the IL2 receptor enhances the long-term integration of hESCs-derived photoreceptors in the retina of Crx knockout mice (Zhu et al. 2017). Similarly, an immunosuppressive regimen enabled long-term survival (up to 5 months) of xenotransplanted hESCs-derived photoreceptors into a canine model of inherited retinal degeneration (Ripolles-Garcia et al. 2022). Immunomodulation may be particularly important in the retina of older individuals since aging is associated with immune dysregulation that results in enhanced para-inflammatory responses. This could render the retina less receptive to transplanted photoreceptors (Chen et al. 2019). The most common approach for photoreceptor transplantation is subretinal injection. The outer limiting membrane (OLM) is a natural barrier between the subretinal space and the outer nuclear layer (ONL). It can be surgically disrupted which leads to a significant increase in the number of photoreceptors integrated within the ONL (West et al. 2008; Pearson et al. 2010; Barber et al. 2013). However, whether this is a viable surgical approach in patients remains to be determined.

5.2

Dissociated RGC Transplantation

RO-derived RGCs have been widely used for RGC replacement (Luo et al. 2021; Rabesandratana et al. 2020; Oswald et al. 2021). In human ROs, RGCs are born around day 25 and maintained to around day 80. This two-month time window is ideal to harvest RGCs from ROs for transplantation into the host retina. At later stages of RO development, RGCs will degenerate and disappear. As is the case for photoreceptor transplantation, the primary challenges of RGC transplantation are survival and integration of RGCs into the host retina. An additional significant obstacle to RGC function is the need to extend the axon along the optic nerve to the visual centers of the brain. RGC axons and dendrites in the RO are typically intact and exhibit good connectivity within the structure. However, after dissociation from the RO, the integrity of the axons becomes compromised. The detrimental effects of dissociation can be counteracted by transplantation in the presence of growth factors, such as BDNF, CNTF, and GDNF, which can help RGC survive (Di Polo et al. 1998; Leaver et al. 2006; Ren et al. 2012; Hu et al. 2017). Second, the cells are sometimes transplanted through subretinal injections, which are far from the location where RGCs are situated near the internal limiting membrane (ILM). This is done to minimize immune reactions and to achieve a high local concentration of transplanted cells. The donor cells must then migrate and form axonal projections into the host optic nerve. The integration efficiency is typically about 1% when primary RGC are translated, but appears to be as high as 5% when the graft is derived from ROs (Oswald et al. 2021). Despite these challenges, a recent study successfully transplanted mouse RO-derived RGC grafted cells that polarized within the host retina and formed axonal processes that followed host axons along

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the retinal surface and entered the optic nerve head (Oswald et al. 2021). These are encouraging findings that suggest that restoration of vision in conditions that lead to RGC loss may be possible. Among these, glaucoma is by far the most common. Glaucoma involves additional formidable obstacles including retinal neuroinflammation and structural and compositional changes to the optic nerve head. Future studies will need to determine solutions to these challenges for survival, migration, and integration of donor RGCs.

5.3

RPE Transplantation

Owing in part to early successes in the generation of RPE from stem cells, studies of transplanting RPE for vision-threatening diseases, including AMD and RP, have advanced furthest along the translational pathway. In a recent study, transplantation of a stem cell-derived RPE monolayer under the macula of non-human primates demonstrated that the graft cells maintained polarity and rescued vision (Liu et al. 2021a). Such findings in preclinical models have encouraged several ongoing clinical trials to investigate RPE transplantation as a treatment for AMD (Kashani et al. 2021). Studies have also indicated that dissociated RPE cells do not survive well after transplantation since Bruch’s membrane in the eyes of older patients does not support RPE attachment. This can also lead to transplanted cells escaping into the vitreous cavity and causing retinal detachments (Zarbin et al. 2019). Therefore, most transplantation studies now employ RPE sheet scaffolds instead of dissociated cells (Hynes and Lavik 2010). The development of biomaterial that closely mimics the properties of Bruch’s membrane would be helpful. The developmental stage of the transplanted RPE is vital for vision rescue. It is not suitable if it is too proliferative (causes proliferative vitreoretinopathy or scar formation) or has become non-proliferative (non-reparative) (Stern and Temple 2015).

5.4

Retinal Sheet Transplantation

Instead of transplanting specific cell types, some scientists are interested in transplanting both photoreceptors and RPE obtained from ROs as retinal sheets. The retinal sheets are dissected as a whole or part of the well-organized structure of the fetal retina or RO. Consequently, the graft consists of retinal cells, RPCs, and— in some cases—RPE. One advantage of this approach appears to be that photoreceptor outer segments are better maintained when portions of RPE are transplanted along with the intact photoreceptor sheet, whereas isolated photoreceptor sheets do not maintain outer segments. For example, following transplantation of hESCsderived retinal sheets into primate models of retinal degeneration, maturation of the graft results in the formation of an ONL as well as inner and outer photoreceptor segments. The potential formation of synaptic contacts between the graft and host cells has also been reported (Shirai et al. 2016). Other researchers transplanted a “total retinal patch” consisting of RO sheets and healthy RPE cells on an artificial

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Bruch’s membrane to end-stage retinal degenerative rats. They found long-term survival of the co-graft in the rat subretinal space and improvement in visual function (Thomas et al. 2021). The co-grafts grew, generated new photoreceptors, and developed neuronal processes that integrated into the host retina. Studies indicate that cells in transplanted RO sheets differentiate, integrate, and improve visual function in rats with retinal degeneration (Lin et al. 2020; McLelland et al. 2018). Compared to dissociated cell transplantation, retinal sheet transplantation shows remarkably improved survival, integration, synaptic connectivity, and connectivity to the visual centers of the brain (Lin et al. 2020; McLelland et al. 2018). Taken together, there is hope that retinal sheet transplantation will become a feasible approach for the restoration of vision in people suffering from severe photoreceptor degeneration.

5.5

Challenges of Cell Replacement Therapy

The two most critical challenges facing cell replacement therapy to regenerate damaged retinas are the correct integration of transplanted material into the host retina and subsequent graft rejection due to inflammation or gliosis. To achieve vision, structural and functional integration of new neurons into a pre-existing neuronal network is necessary. The transplanted neuron’s integration is guided by signals from the environment of the recipient retina, e.g., GABA (Tyson and Anderson 2014), neurotrophins (West et al. 2012; Nakao et al. 2000; Suzuki et al. 2003), and expression of some genes such as Disrupted in Schizophrenia 1 (DISC1) (Duan et al. 2007). To date, these intrinsic signaling pathways are typically the only stimuli for grafted cells to guide their migration into the tissue, integrate with other neurons, and form neuritic/synaptic connections and circuits to improve vision. However, it is conceivable that targeted provision of additional neurotrophins could lead to improved integration and visual recovery. A second challenge to successful transplantation is immunogenicity. Although the neural retina is partly protected due to the central nervous system’s immune privilege, mechanisms of the innate and adaptive immune system will eventually remove transplanted cells. One obvious solution to avoid immune rejection is to conduct autologous transplantation. In this case, RO generated from hiPSCs derived from the intended recipient would be used. While this is likely a viable approach, it is costly and labor-intensive to generate specific hiPSC lines for each patient. Furthermore, autologous transplantation may not be ideal for patients with retinal degeneration due to the presence of disease-causing mutations. The creation of universal donor hiPSCs that can be used for many patients provides additional benefits with respect to reproducibility and safety, as discussed elsewhere (Lawrence 2023). Most studies established immune suppression around the tissue for months to help preserve the cells. Yet, others report that immune modulation is required during tissue repair and regeneration in the retina (Neves et al. 2016). In a damaged retina of flies and mice, innate immune cells release the mesencephalic astrocyte-derived neurotrophic factor (MANF). MANF promotes alternative activation of innate

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immune cells, enhances neuroprotection and tissue repair, and improves the success of photoreceptor replacement therapies. Additionally, scientists suppress human genes associated with CD8, CD4, and NK cells (e.g., monoclonal antibody CD38) to neutralize the NK cells and T cells, anti-IL-2 receptor antibodies to suppress the immune recognition, or knockout HLA I/II genes. HLA I/II knockout hiPSCsderived neurons are the universal donor of biobanking for tissue/cell replacement (Mattapally et al. 2018; Petrus-Reurer et al. 2020). A group in Japan found that the HLA-C-retained but HLA-A and -B-disrupted hiPSCs could evade T cells and NK cells in vitro and in vivo. They estimated that these HLA-A/B-disrupted hiPSCs, combined with HLA-class II knockout, were immunologically compatible with >90% of the world’s population, greatly facilitating hiPSCs-based regenerative medicine applications (Xu et al. 2019). These hiPSC lines were HLA matched for 40% of the Japanese population and complied with the good manufacturing practice (GMP) process for the clinical application (Yoshida et al. 2022). Glucocorticoids had been included in RPE transplant trials and are known to reduce the production of inflammatory cytokines. At the same time, it is important to recognize hypoimmunity as a potential side effect (Nicholson et al. 2022).

6

Human RO-Derived Cells Are Widely Used for Disease Modeling

ROs recapitulate the in vivo development of the human retina (Kim et al. 2019; Kuwahara et al. 2015). Cowan et al. reported that cell types in ROs mature to a stable developed state at a rate similar to that of human retinal development in vivo (Cowan et al. 2020; Sridhar et al. 2020). Therefore, ROs are an ideal model to recapitulate retinal development and study the retinal developmental disorders (Cheng et al. 2022) (Fig. 3(3)). Importantly, ROs may also reveal the influence of genetic variations encoded in the genome of the individual from whom the iPSCs were derived. This provides a clear advantage over animal models in cases where a disease-causing mutation has not been conclusively identified or where a phenotype results from the activity of multiple genes. Inherited retinal diseases could cause retinal cell loss, leading to permanent vision loss or blindness. More than 250 genetic mutations have been identified to contribute to inherited retinal diseases, but causative variants are only identified in 24%–53% of tested inherited retinal disease patients, indicating that current methods relying largely on the identification of non-silent genetic abnormalities are insufficient (Mullin et al. 2021). Patient-derived iPSC-based modeling using ROs has the potential to expand the catalog of disease-causing variants and increase the number of patients that may benefit from retinal gene therapy. The presence of multiple cell types within the RO allows the investigation of cell type-specific disease mechanisms (Cowan et al. 2020). For example, autosomal dominant RP may be the result of copy number variants of the RHO (rhodopsin) gene. ROs generated from a donor with four copies of the RHO gene display elevated rhodopsin expression in nascent photoreceptor cells, which subsequently

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failed to form photoreceptor outer segments (Kandoi et al. 2023). Importantly, this study also demonstrated that overexpression of RHO in ROs can be rescued by a small molecule inhibitor (photoregulin3). Similar studies have been carried out to model other retinal degenerative diseases including additional forms of RP (Gao et al. 2020; Cuevas et al. 2021; Su et al. 2022), AMD (Volkner et al. 2022), glaucoma (VanderWall et al. 2020), LCA (Kruczek et al. 2021; Li et al. 2019; Leung et al. 2022), enhanced S-cone syndrome (Cuevas et al. 2021; Bohrer et al. 2019), retinoblastoma (Liu et al. 2021b; Norrie et al. 2021; Rozanska et al. 2022; Kanber et al. 2022), X-linked juvenile retinoschisis (Huang et al. 2019), and Usher disease (Leong et al. 2022). Finally, ROs can be used to model the pathophysiology of ocular tumors. Norrie et al. have developed patient-specific ROs carrying the RB1 mutation (Norrie et al. 2021). Injection of dissociated cells from these ROs into the vitreous cavity of immunocompromised mice invariably leads to the formation of retinoblastomas with molecular, cellular, and genomic features indistinguishable from those of human retinoblastomas. Similar findings were also presented by Liu et al. (Liu et al. 2021b). Therefore, ROs are a valuable model in human ocular cancer research to investigate the effects of germline cancer-predisposing mutations and to develop novel therapies.

7

Use of Human ROs for Therapeutic Development

7.1

Drug Toxicity and Efficacy Screening

ROs derived from carefully selected, differentiation-efficient iPSC lines can be generated on a large scale and used for drug toxicity and efficacy screening, making them a valuable resource as in vitro platforms for high-throughput drug screening (Fig. 3(4)). Their human origins make them more clinically relevant than murine or macaque animal models, which may differ from human cells in biochemical responses. Such differences may be poorly understood and result in vastly different responses to the same stimuli. The thalidomide disaster of 1957–1961 highlighted, for the first time, that differences do exist between species in the reaction to drugs (Vargesson 2015). The immunomodulatory imide drug (IMiD) thalidomide was a widely used sedative drug in the late 1950s and early 1960s for treating morning sickness in pregnant women. It became apparent in the 1960s that thalidomide treatment resulted in severe birth defects, especially of the limbs, in thousands of children. The reason underlying thalidomide-induced teratogenesis is that thalidomide binds to the protein cereblon (CRBN) and inhibits its associated E3 ubiquitin ligase function. In mice, CRBN is resistant to thalidomide-induced inhibition of CRBN autoubiquitination (Hirose et al. 2020) and does not cause birth defects (Fratta et al. 1965). Another example is the metabolization of acetaminophen which, in humans, is primarily metabolized by the enzyme CYP2E1 and results in production of the toxic

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intermediate N-acetyl-p-benzoquinone imine (NAPQI). Rodents, on the other hand, metabolize acetaminophen primarily by glucuronidation and sulfation and have much lower levels of CYP2E1 activity than humans, making them relatively resistant to acetaminophen toxicity (McGill et al. 2012; Mohar et al. 2014). These examples stress the importance of using human-based models in drug development and toxicity testing.

7.2

Gene Therapy and Genetic Editing

Many of the retinal diseases leading to severe vision loss have a genetic basis. Of these, an increasing number appear to be treatable with gene therapy. Initial testing of gene therapy strategies is more efficiently carried out in vitro and, as discussed above, benefits from using human cells and organoids representing multiple retinal cell types. It is also important to note that most gene therapy approaches rely upon viral vectors for the delivery of genetic material and that the ability of the vectors to infect specific cell types often differs among species. Thus, ROs provide a tool to quickly, easily, and reproducibly create a scalable experimental system to develop gene therapy or genetic editing strategies and optimize the therapeutic delivery system (Fig. 3(4)). For the development of gene therapy strategies, it is ideal to establish patientspecific hiPSC lines with the mutation (if known) and test adeno-associated virus (AAV) vectors in the ROs carrying this predisposing mutation. For example, patientspecific ROs have been used to model dominant LCA caused by mutations in the photoreceptor transcription factor CRX gene. ROs carrying the LCA-CRX mutation show defective photoreceptor maturation with diminished expression of visual opsins. Allele-specific gene editing rescued this dominant CRX-associated LCA phenotype in a RO model (Chirco et al. 2021). AAV-mediated CRX gene augmentation therapy partially restored photoreceptor phenotype and expression of phototransduction-related genes in ROs derived from iPSCs of LCA (Kruczek et al. 2021). Likewise, CRB1 gene variations can cause RP, LCA, or in some cases, macular degeneration. Buck et al. tested rAAV-CRB gene supplementation in patient iPSCs-derived ROs and demonstrated protection of ROs from vision loss (Kuwahara et al. 2022). Genetic editing involves making precise changes to an individual’s DNA to correct or eliminate the genetic mutations that cause inherited retinal diseases. This can be done using techniques such as CRISPR/Cas9, which allows scientists to cut and modify specific sections of DNA. An advantage of in vivo gene editing is that it is a permanent correction to the genome under physiological conditions and may be able to correct gain-of-function mutations. ROs are the ideal tool to screen genetic editing events, including gene repair rate and off-target activity. Using lentivirus expressing adenine base editors (ABE) to the subretinal space and to correct the pathogenic Rpe65 nonsense mutation exemplifies this use (Suh et al. 2021). The treatment restored the mutation with up to 29% efficiency and rescued photoreceptor survival and visual function in rd21 mice. A second example is the delivery of

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AAV5 viruses into the subretinal space in the para-fovea region to correct the CEP290 gene mutation (rod degeneration) in LCA (Maeder et al. 2019). Here, expression of the gene editing construct was driven by the photoreceptor-specific GRK1 promoter to restrict genetic editing to photoreceptor cells. Although gene-based therapies have shown remarkable progress in the past decade, several challenges must be overcome to realize their full potential. First is delivery; the genes must be delivered safely and effectively to the specific cells. No matter how dedicated the subretinal injection is, the injection itself will tremendously affect the photoreceptors. In animal models, subretinal injection will cause retinal detachment and may damage photoreceptor cells. An alternative delivery approach would be trans-scleral subretinal peripheral injection, which does not penetrate the retina. The injected cells will not disseminate into the bloodstream, minimizing the local and systemic immune responses with higher safety and efficacy (Reichel et al. 2021). Other non-viral delivery methods, such as nanoparticles and nanoblades (loaded with donor sgRNA for “all-in-one” homology-directed repair), are currently being developed. The second challenge to gene-based therapies is off-target effects. Off-target effects lead to toxicity, immune reactions, or other adverse effects. Researchers are working to develop better methods for controlling the expression of therapeutic genes to minimize off-target effects. Third is the immune response. Scientists are exploring ways to mitigate the immune response caused by therapeutic foreign gene introduction, such as using modified genes or co-administering immunosuppressive drugs. Fourth is the longterm safety and efficacy of a permanent gene repair. It is possible that unintended consequences, such as the development of new mutations or changes in gene expression patterns, may happen over time. Fifth is the cost and accessibility. Gene-based therapies can be expensive and difficult to access, limiting their availability to patients who need them. One reason why gene-based therapies are expensive is that the design is specific to a single mutation. Patients may have multiple mutations in one gene or multiple genes in the clinical setting. The mutations are highly heterogeneous. Phenotypic manifestations of a single mutation can also vary: from severe to mild, high penetration to low penetration, and dominant to recessive. Therefore, targeting a single point mutation or single gene may not be useful for patients with complex mutation profiles. Developing therapies targeting a larger population can reduce costs and improve access to these therapies. The first directly administered gene replacement therapy was approved by the Food and Drug Administration in 2017 and was designed to treat patients with mutations in RPE65. Since then, a number of clinical trials to treat retinal degenerative diseases have been initiated including those using genetic editing (e.g., NCT03872479). ROs will play an important role in the development of therapies by providing an experimental system that allows the generation of large numbers of “targets” that reflect both the genetic and biochemical characteristics of the human retina. Their value is further enhanced by the co-existence of multiple retinal cell types. This not only allows for the development of cell type-specific promoters but also provides opportunities to evaluate both direct and indirect effects on cell populations that are not the intended target.

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ROs Can Be Integrated with Other Technologies to Broaden the Range of Investigation

Current RO contains several neuronal cell types but lacks other important components of the natural retina, including vasculature and microglia. One approach to address this potential shortcoming is through coculture of ROs with brain organoids (BOs) (Fig. 4a), vascular cell types (pericytes, endothelium cells), or immune cells (microglia/macrophages, lymphocytes, T cells, or B cells) (Fig. 4c). Data have also demonstrated that ROs can be fused with BOs to form assembloids, in which RGCs extend axons deep into assembloids, modeling the projections of RGC to the thalamus (Fligor et al. 2021; Fernando et al. 2022). Future, recent studies demonstrated the development of optic cups in BOs. Two bilaterally symmetrical optic cups developed when growing hiPSCs-derived BOs, mirroring the development of eye structures in human embryos (culture day 30–50). These optic cups are small spherical structures with primitive corneal epithelial and lens-like cells, RPE, retinal progenitor cells, axon-like projections, and electrically active neuronal networks (Arthur et al. 2022; Gabriel et al. 2021). These organoids can help to study brain–eye interactions during embryonic development, model congenital retinal disorders, and be used for drug screening and transplantation (Fig. 4b). Finally, coculture of ROs with glial cells, including microglia and astrocytes, has been reported (Chichagova et al. 2023; VanderWall et al. 2019). Such studies facilitated the dissection of developmental and pathobiological interactions between RO RGCs and astrocytes (VanderWall et al. 2019). In addition to assembloids of ROs and other cell types, ROs have been integrated with a microfluid chip system. The organ-on-chip is a microfluidic-based assembly in which organoids are grown on one side of a membrane, and stromal cells (or other cell types) on the other surface (Fig. 4d). Liquids and gases are circulated through the system to mimic air and blood flow in precisely fabricated and controlled microfluidic channels. The organ-on-chip method permits time-lapse monitoring of cell–cell interactions, recapitulates the in vivo microenvironment, and shows excellent promise for therapeutic discovery (Jahagirdar et al. 2022). It is an excellent choice when a well-controlled dynamic microenvironment is desired; for example, it can be used to study the effects of hypoxic microenvironments or high/low glucose conditions. A second advantage of the organ-on-chip system is the tissue–tissue interface which allows maintenance of cell types in separate compartments. This makes possible studies investigating cell–cell interactions and migration. This advantage also makes the organ-on-chip system compatible with a wide variety of cell sources, including immune, cancer, stromal, or microbial cells. Studies have shown improved gene expression and greater predictive power in the organoid-onchip system than in the organoids alone (Jahagirdar et al. 2022), such as improved epithelial polarity and transcriptional profiles that are very similar to those of human tissue in vivo (Cao et al. 2023). ROs can also be the source of extracellular vehicles (EVs). EVs are a functional unit of stem cells and may be useful for cell-free delivery of biological therapeutics. In vivo EVs can act as essential mediators of cell-to-cell communication; for

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Fig. 4 Emerging technologies integrated with ROs. (a) The assembloids of ROs and brain organoids (BOs) connected by nerve-like axonal projections of optic origin. ROs and BOs are connected with each other, and cells are migrating from one side to another with axon-like structure. (b) Development of optic cups in BOs. The hiPSCs-derived BOs have developed retinal cups with RPE and retinal ganglion cell marker BRN3A. Scale bar: 200 μm. (c) The organ-on-chip system

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example, the EVs in the retina may facilitate interactions between photoreceptors and Müller glia (Kalargyrou et al. 2022). EVs isolated from hiPSCs-derived ROs display a characteristic spheroid and cup-shaped morphology, with diameters ranging from approximately 50 to 200 nm (Zhou et al. 2021). Characterization of these EVs demonstrated that they contain a cocktail of microRNAs, lipids, and proteins (Kim et al. 2013) that function both in retinal development and to delay retinal degeneration (Chen et al. 2021). EVs derived from RO cells may provide an efficient, stable, and safe approach for the delivery of biologics because this cellfree approach minimizes immune rejection and tumor formation. Translationally, EVs offer the advantage that they can be conveniently stored in a freezer and may thus be used as an off-the-shelf therapeutic agent. Integration of ROs with other technology is still a novel field of study but offers tantalizing prospects for future advancements. For example, ROs could be intergraded with biomaterial engineering for tissue regeneration (such as 3D bio-ink printing) or with advanced imaging techniques (such as multiphoton microscopy or optogenetics) to better visualize and manipulate the function of neurons. Such studies have the potential to revolutionize our understanding of pathophysiology affecting the human eye and to accelerate the development of new treatments for ocular disorders.

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Challenges of Current RO Technology

ROs provide a great platform to seek therapeutic discovery, but their utilization is not without limitations. The challenges include high variability across hiPSC lines, difficulty to cryopreserve ROs for later use, degeneration of retinal cells with prolonged culture, and absence of vascular, glial, and immune cells (Fig. 5).

9.1

Variation Limits Reliability and Producibility

Organoids have the advantage of improved functionality and complexity over 2D culture. However, high variation between and within the culture is the most pressing issue in current RO technology. First, different labs use various protocols and methods to generate ROs, yielding ROs with a distinct cellular composition that makes the comparison of data among multiple investigators challenging

Fig. 4 (continued) integrated with ROs broadened the investigation of ROs. Left: The ROs on a chip. The microfluidic devices are lined with human cells and organoids for pharmaceutical and chemical development, disease modeling, and study of human physiology/pathology. Right: The organ-on-chip system replicates the critical functions of living organs by connecting the organoids or cells. It simulates complex cell–cell and cell–matrix interaction and represents a new in vitro disease model. (d) Extracellular vehicles (EVs) as an approach to delivering the cell-free cargo of ROs materials to the eye

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Fig. 5 The pros and cons of retinal organoids. The ROs are good in saving time in establishing the model system to study eye disease when compared with murine models. The ROs also performed well in terms of the robustness of the assay, accessibility of the research material, and representation of human physiology. The quantity of biomaterial of ROs is plenty, genetic manipulation is relatively easy, and personalized modeling of ocular diseases is possible. The cons of ROs are relatively high costs compared with culturing other cells, labor-intensive, and the variability of the ROs generated. The standardization of the ROs is challenging, and interorgan communication is poor since no choroidal lineage cells are generated. It is also difficult to cryopreserve the ROs without compromising the RO morphology. It also has a graduate degeneration of cells in the ROs

(Chichagova et al. 2020). Second, using a specific iPSC line pronounced batch-tobatch differences are commonly observed, even within laboratories. This may result in batches of ROs reaching specific maturation stages at different culture times. Third, individual stem cell lines differ from one another with respect to the origin of the somatic cells, donor age, genetic background, and epigenetic modifications. Some cell lines consistently yield few or poor-quality ROs (Regent et al. 2022). This limits their utility in research and burdens the reproducibility of findings. Variability can in part be addressed by carefully selecting good hiPSC lines and culturing ROs in a chemical-defined approach, e.g., using BMP4 rather than Matrigel. Yet, to improve productiveness and accuracy, it is imperative that more robust experimental protocols are developed that minimize artificial variation among RO batches.

9.2

Cryopreservation Compromises the Morphology and Cellularity of ROs

The ability to cryopreserve ROs in liquid nitrogen will be needed for eventual “offthe-shelf” regenerative treatment approaches as well as for preclinical/clinical studies. Cryopreservation also allows large-scale RO production, reducing costs and decreasing variability across larger experiments like drug screening campaigns. Unfortunately, reported methods to cryopreserve ROs long-term without comprising

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the cell integrity or laminar layers have yet to gain universal acceptance in other laboratories. Early cryopreservation protocol employed a two-step en bloc cryopreservation approach to store NR epithelia at differentiation day 30 (Nakano et al. 2012). First, the ROs with 1 mL NR medium are kept on ice for 10 min; then the supernatant is replaced with 1 mL of pretreatment solution (10% DMSO, 5% ethylene glycol, 10% sucrose, and 75% NR medium) for 15–20 min. Then, ROs are suspended in an ice-cold freezing medium (RO maintenance medium, 2 M DMSO, 1 M acetamide, and 3 M propylene glycol). ROs are then quickly frozen by direct immersion in liquid nitrogen. However, in our hands, laminar layers of the ROs are frequently disrupted upon thawing. A second approach is to use Cryostem medium (Clinisciences, Nanterre, France) for cryopreservation of whole ROs (Rabesandratana et al. 2020; Reichman et al. 2017). Reichman et al. froze d84 ROs and reported that 16 days after thawing, ROs featured intact rosettes containing CRX+ and RCVRN+ photoreceptor precursors similar to nonfrozen ROs at the same stage (Reichman et al. 2017). However, the authors reported that the laminar structure of the preserved ROs was compromised. More encouraging results have been reported for methods to preserve ROs for a shorter duration to facilitate shipping. One such approach is to place them in 96-well cell culture plates in 100 μL of fresh RO medium and to seal these with parafilm (Georgiou et al. 2020). The investigators reported that ROs retain their morphological and functional characteristics upon storage at room temperature (RT) for 5 days. A second approach to shipping relied on conditioning the RO medium with oxygen and CO2 (as is used for organoid culture) as well as adding extra bFGF and BDNF before sealing the plates. Organoid viability was not impacted upon overnight shipping (Singh et al. 2020).

9.3

Degeneration of Retinal Cells with Prolonged Culture

Upon maturation, neuronal cells cease to divide and thus ROs are stable in vitro for several months to a year (Gao et al. 2020), with some groups claiming a culture of up to 2 years. The length of time that ROs can be maintained depends on several factors, including the culture conditions and the quality of the starting stem cells. As the culture time increases, the ROs may undergo changes in their structure, gene expression, and functionality, which may limit their utility for certain experiments or applications. It is worth noting that maintaining the viability and function of ROs for extended periods can be challenging and requires careful attention to the culture conditions, including the nutrient supply, oxygen levels, and growth factors. The use of spinner flasks or a bioreactor may help promote the exchange of nutrition and gas in the medium and may help maintain good morphology of the ROs for such extended periods. Such approaches have been shown to improve the laminar stratification and increase the yield of photoreceptor cells bearing cilia and nascent OS-like structures (Ovando-Roche et al. 2018; DiStefano et al. 2021).

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A biologic reason that cells within the ROs will degenerate is that the various cell types within the structure develop sequentially, mimicking the embryologic development of the retina. Early-born cells, particularly RGCs, tend to gradually degenerate as the culture matures. This may be due to the absence of synaptic projection to the superior colliculus that is required for RGC survival in ocular development in vivo (Isenmann et al. 2003). Thus, it is conceivable that recreating the niche through the inclusion of growth factors such as CNTF and BDNF may support the long-term survival of RGC. Alternatively, ROs cocultured with BOs or other cell types might enable long-term culture without loss of specific cell types.

9.4

The Absence of Vascular and Glial Cells Limits the Use of ROs

Many retinal diseases not only impact retinal neurons but also involve retinal vasculature and/or glial cells. Microglia, in particular, invariably become activated when neuronal cells are stressed or begin to degenerate; the resulting neuroinflammation appears to contribute to the pathogenesis of many chronic retinal diseases. Similarly, astrocytes alter their behavior during retinal degeneration and play a significant role in the health of surrounding neurons. The absence of immune cells may limit the ability to study immune-mediated retinal diseases, while the absence of glial cells may limit the ability to study interactions between neurons and glial cells in the retina. Likewise, the lack of vasculature in ROs limits their usefulness in the study of retinal diseases that involve changes to the vasculature (most notably, diabetic retinopathy). This deficiency may in some cases be addressed by coculture with defined cell types, such as microglia. For example, studies have shown that it is possible to integrate iPSCs-derived microglia-like cells (iMG) into developing ROs (Chichagova et al. 2023). The iMG were incorporated into monocultures at 13 weeks and did not interfere with the normal development and function of ROs at 15 and 22 weeks of differentiation. The retinal vasculature and the choriocapillaris are themselves composed of multiple cell types. Their incorporation into an in vitro model of the eye may require the use of assembloids, as discussed above.

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Outlook and Future Directions

ROs provide an unlimited source of human-derived cells for modeling eye diseases and cell replacement therapies. They also provide an excellent platform to test for drugs and vectors for gene therapy or cell genetic editing (McClements et al. 2022). While more labor-intensive than traditional culture-based assays, stem cell-derived ROs open a new avenue for disease modeling, high-throughput drug screening, and therapeutic development. The main challenge in retinal drug discovery is producing ROs of uniform quality to yield reproducible findings. However, it is expected that quality control improvements, both in the stem cells and the reagents used, will gradually increase reproducibility. Many research teams are also engaged in

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improving cryopreservation strategies and the coculture of ROs with other organoids; it is also expected that continuous improvements will eventually yield the desired results. RO technology is rapidly evolving, and astonishing developments could revolutionize their use for pharmaceutical development. ROs are integrated with emerging technologies, such as RO-derived EVs for drug delivery, whole organoid electrophysiological analysis, transplantable biomaterials/scaffold development, 3D bioprinting, and advanced imaging technologies (3D tomography, multiphoton microscopy, optogenetics, AI, or machine learning). Combined with these technologies, ROs may provide unprecedented opportunities to study retinal function and open novel avenues in therapeutic discovery.

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Part III iPSC-Derived Nociceptive Neurons

Using Human iPSC-Derived Peripheral Nervous System Disease Models for Drug Discovery Yuan Gao

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 What Is Human iPSC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Overview of Human IPSC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Application Prospects of Human IPSC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 What Is Peripheral Neuropathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Overview of Peripheral Nerve Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Traditional Treatment of Peripheral Nerve Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Feasibility of IPSC-Derived Models for Peripheral Nerve Diseases Treatment . . . . . 4 Application of Disease Models in Peripheral Neuropathy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Limitations of Traditional Disease Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Advantages of Human iPSC-Derived Peripheral Disease Models . . . . . . . . . . . . . . . . . . . 4.3 Basic Steps in IPSC-Derived Disease Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Classification of IPSC-Derived Disease Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Application of Different Human IPSC-Derived Models for Peripheral Nerve Diseases in Drug Discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Neuromuscular Junction Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Neural Crest Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Various IPSC-Derived Neuronal Cell Subtypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Neural Mesodermal Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Induced pluripotent stem cells (IPSCs), with their remarkable ability to differentiate into various cell types, including peripheral nervous system cells such as neurons and glial cells, offer an excellent platform for in vitro disease modeling. These iPSC-derived disease models have proven valuable in drug discovery, as Y. Gao (✉) Translational Medicine Research Center, Shanxi Medical University, Taiyuan, China # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_690

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they provide more precise simulations of a patient’s disease state and allow for the assessment of potential therapeutic effectiveness and safety. Keywords

Drug discovery, Induced pluripotent stem cell, Peripheral nervous system

1

Introduction

Recent advancements in human-induced pluripotent stem cell (iPSC) technology have enabled the reprogramming of somatic cells from patients into stem cells. IPSCs, with their remarkable ability to differentiate into various cell types, including peripheral nervous system cells such as neurons and glial cells, offer an excellent platform for in vitro disease modeling. These iPSC-derived disease models have proven valuable in drug discovery, as they provide more precise simulations of a patient’s disease state and allow for the assessment of potential therapeutic effectiveness and safety. This chapter explores the recent progress in the development of peripheral nervous system disease models using patient-derived iPSCs and their implications in drug discovery. Additionally, we delve into the utilization of 3D organ models that more accurately mimic tissue structures for disease simulation. We also analyze the potential benefits and obstacles associated with employing 3D organoids to model peripheral nervous system development and neurodegeneration. Given the limited regenerative capacity and minimal opportunities for repair, peripheral nerve damage poses a significant clinical challenge. In this chapter, we highlighted the potential effect of the iPSC-based therapy for the treatment of distant communication peripheral nerve deficits. Although traditional cell-based treatments have shown promise in nerve regeneration, iPSC-based therapy offers an innovative alternative by connecting the therapeutic potential of IPSC-derived products without the need for cell transplantation. This approach has significant potential for the upcoming clinical application due to its ability to overcome limitation associated with cell transplantation, such as immune rejection and limited cell availability. Furthermore, we delve into a preclinical and clinical study that supports the efficacy and safety of IPSC-based therapy in stimulating nerve regeneration and functional recovery. Finally, the study explores the future perspective and potential advancement in this field, including the deployment of optimized iPSC-derived products and the integration of innovative delivery systems for enhanced therapeutic outcomes. Overall, this chapter shed light on the exciting prospect of iPSC-based therapy as the cell-free approach for addressing distant communication peripheral nerve deficits. In this chapter we focus on the cure of distant communication peripheral nerve deficits, however, iPSC-based therapy shows significant potential; as a result, it represents a cell-free approach for upcoming drug discovery.

Using Human iPSC-Derived Peripheral Nervous System Disease Models for. . .

2

What Is Human iPSC

2.1

Overview of Human IPSC

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Pluripotent stem cells form the foundation for diverse cell types in early mammalian development. The term “embryonic stem cells” (ESC) refers to these specialized cells that can be grown in vitro, have the capacity to generate all types of embryonic lineages in vivo, and can differentiate in vitro to produce all types of somatic cells (Evans and Kaufman 1981). Currently, embryonic stem cells have created a lot of attention as a potential source of cells for the treatment of numerous degenerative disorders and have been successfully applied in clinical settings to treat a variety of associated diseases. However, the ethical issues associated with the use of embryonic stem cells are far from simple. The mainly aspects are described as follows: 1. Failing in vitro fertilization embryos could result in abnormal development. 2. The allogenic origin of ESCs might result in immune rejection following transplantation which will severely hamper human ESC-based clinical trials (Aach et al. 2017). Human pluripotent stem cells (hPSCs) have received a lot of interest lately (Doss and Sachinidis 2019). Due to their exceptional capacities to develop into several cell types, particularly a wide range of neural crest derivatives, human embryonic stem cells (hESCs) and human-induced pluripotent stem cells (hiPSCs) are included. Epithelial or blood cells that have undergone differentiation to a pluripotent stage akin to that of an embryo are the source of induced pluripotent stem cells (iPSC), which can be used to produce any kind of human cell that is currently needed. For instance, in vitro differentiation can produce any type of somatic cell, including hepatocytes, smooth muscle cells, endothelial cells, and cardiomyocytes. The previous research has a great significance that iPSC generation is achieved through transcription factor-mediated cell reprogramming. Initially, a team of Japanese scientists successfully generated iPSCs by transfecting four transcription factors (Oct4, Sox2, Klf4, and c-Myc) into fibroblasts (Takahashi et al. 2007). This groundbreaking study revealed the potential of cell reprogramming and provided important guidance for subsequent research. The differentiation process of iPSCs is achieved by mimicking the mechanisms of embryonic development. In the differentiation process of peripheral nervous system cells, researchers promote the differentiation of iPSCs into Schwann cells, sensory neurons, motor neurons, and other peripheral nervous system-related cell types through directed induction and regulation of specific signaling pathways (Chambers et al. 2009).

2.2

Application Prospects of Human IPSC

Studies have shown that these cells exhibit high consistency, between in vitro pluripotent stem cells and in vivo peripheral nervous system cells in terms of morphology, function, and gene expression. For example, iPSC-derived sensory neurons can form synaptic connections and produce electrophysiological activities (Hester et al. 2011) similar to in vivo neurons. Furthermore, the study supported that

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these cells express cell-specific markers and exhibit molecular characteristics similar to in vivo cells (Wichterle et al. 2002). These features make iPSC-derived peripheral nervous system cells an ideal model for studying peripheral nervous system development, function, and disease mechanisms. iPSCs have been used as a novel autologous cell source for cell replacement therapy for several degenerative diseases, including ischemic heart failure, Parkinson’s disease, Alzheimer’s disease, diabetes mellitus, and age-related macular degeneration because iPSCs can be generated from any individual and that millions or even billions of clinically relevant phenotypic cells such as cardiac or neuronal cells can be derived from iPSCs without the ethical and immune rejection concerns surrounding human ESCs.

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What Is Peripheral Neuropathy

3.1

Overview of Peripheral Nerve Diseases

Peripheral nervous system disease includes various disorders that affect the peripheral nervous system, including peripheral neuropathy (Barrell and Smith 2019) and neuralgia (Finnerup et al. 2021). According to the anatomical site of the lesion, peripheral nerve diseases are classified as neuropathies, radiculopathies, plexopathies (Ropper et al. 2014), acute, subacute, chronic, recurrent, and progressive neuropathies according to the course of the disease; primary and interstitial neuropathies according to the pathological changes of the injury; mononeuropathies, multiple mononeuropathies, and polyneuropathies according to the cumulative nerve distribution. Sensory disorders (sensory deficits, pain, etc.), motor disorders (abnormal activation of motor neurons, paralytic states), and stimulation symptoms (tremors of muscle bundles, painful spasms) are just a few of the distinctive signs and symptoms of peripheral neuropathies. Neuropathic pain, a frequent sign of peripheral neuropathies, is difficult to treat and frequently necessitates a multidisciplinary strategy (Cavalli et al. 2019).

3.2

Traditional Treatment of Peripheral Nerve Diseases

For the treatment of acute peripheral nerve diseases, it is recommended (Attal 2019) to use tricyclic antidepressants, gabapentin or pregabalin, and the SNRI’s venlafaxine or duloxetine as the first-line treatment. The second-line treatments recommended include tramadol, topical lidocaine, or high-concentration capsaicin. As the third-line therapies for peripheral neuropathic pain, powerful opioids (such as oxycodone and morphine) and botulinum toxin-A (BTX-A) were also included. Cannabinoids and valproate had weak recommendations against their use in neuropathic pain. Other interventional therapies (Murphy et al. 2020) include injectable pain blockers, electrical stimulation, and implantable drug delivery systems (IDDS). The study showed that the third-line treatments are frequently advised in the

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advanced stages of the disease but they only temporarily relieve the patient’s pain and have no beneficial effects on acute peripheral neuropathy.

3.3

Feasibility of IPSC-Derived Models for Peripheral Nerve Diseases Treatment

As mentioned earlier, iPSC has the capability to differentiate into both neurons and glia, allowing them to faithfully represent both the central and peripheral nervous system. Typically, neural crest cells (NCCs), which can differentiate into peripheral neurons, glia, and non-neural cell types, are produced by the iPSCs. The study documented that more than 60% of the NCCs produced from iPSCs have been found to differentiate into enteric neurons, sensory neurons, and Schwann cells toward the end, which are helpful for disease modeling. Mehler et al. (2020) have shown the importance of treating the iPSC-NCCs, which were hypoimmunogenic and displayed in vitro immunosuppressive features. HLA class II and costimulatory molecules were not expressed on the iPSC-NCCs, and HLA class I molecule expression was lower than that observed on iPSCs. iPSC-NCCs significantly reduced T-cell activation in terms of immunosuppressive features. It increases stem cell therapy effectiveness and significantly reduces graft rejection. Therefore, using iPSC to generate adequate NCCs to compensate or make up for the small number of NCCs found in embryonic transient tissues provides a new therapeutic strategy for treating disorders affecting the downstream peripheral nerve. The study demonstrated the importance that the implanted iPSC-derived neural crest stem cells (iPSC-NCSCs) regulate axonal myelination, develop into Schwann cells, and incorporate into the myelin sheath surrounding axons. The present understanding supports that iPSC-NCCs may positively contribute to the development of a new therapeutic approach for nerve-hopping pain (Labau et al. 2022). The treatment of Schwann cells plays a central role in prosperous nerve repair and regeneration by supporting both axonal growth and myelination. However, this is a limited approachable point for the advancement of Schwann cell biology, and the creation of treatments for disorders linked to Schwann cells because there are few sources of human Schwann cells for study.. Schwann cells have been shown a great ability to recover peripheral neuropathy symptoms by causing Schwann cell apoptosis (Pang et al. 2023; Wang et al. 2023). Consequently, the study strongly suggested that Schwann cells be a major target for the therapy of peripheral nervous system complications. Pan et al. (2021) have added exosomes produced from iPSCs to acellular nerve grafts (ANGs) to fill in long-distance peripheral nerve deficits. The scientists discovered that Oct3/4, Sox2, Klf4, and c-Myc were non-integrating transduced into human fibroblasts to reprogram them into iPSCs. The obtained iPSCs had highly active alkaline phosphatase expression and expressed Oct4, SSEA4, Nanog, and Sox2, which also differentiated into all three germ layers in vivo and differentiated into mature peripheral neurons and Schwann cells (SCs) in vitro. After isolation and biological characteristics of iPSCs-derived exosomes, exosomes were internalized inside SCs through the endocytic pathway and exhibited

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a proliferative effect on SCs that were involved in the process of axonal regeneration and remyelination. The study concludes that utilizing iPSC-derived peripheral nervous system models provides the researcher with a valuable platform for designing disease models, gaining deeper insight into disease mechanism, and evaluating the efficacy of potential treatment for the peripheral disorder.

4

Application of Disease Models in Peripheral Neuropathy

4.1

Limitations of Traditional Disease Models

Peripheral nerve disease models serve as indispensable tools for comprehensively studying disease and assessing drug effectiveness whether in vitro, in vivo, or a combination of both, by faithfully recapitulating the corresponding pathophysiology and clinical manifestation. Both basic research and pharmaceutical research and development (R&D) have depended heavily on animal modeling, most typically using mice, as a non-clinical efficacy model. However, it is common for the results of animal model experiments to fail to translate when transitioning to the clinic. To be honest, traditional animal and cell models have limitations and cannot fully replicate human physiological and pathological processes. In contrast, it is more interesting to use an appropriate human model of diseases in vitro that recapitulates the pathophysiological mechanisms. It would be beneficial to model human primary cell-based diseases, but this will be limited by the lack of expandable cellular sources from patients, particularly difficult-to-access cells like cardiomyocytes, neuronal cells, pancreatic beta cells, and other clinically relevant cells from organs other than skin and peripheral blood.

4.2

Advantages of Human iPSC-Derived Peripheral Disease Models

Since any clinically relevant phenotypic cells can be derived from iPSCs in unlimited quantities for high-throughput assays and iPSCs can be derived from any individual patient and healthy subjects, iPSCs have been a good solution to the clinical bottleneck problem, iPSC-derived disease models possess high physiological and genetic similarities, allowing for more accurate simulations of a patient’s disease condition at the same time so that iPSC-derived cell therapy is becoming more and more popular.

4.3

Basic Steps in IPSC-Derived Disease Modeling

The establishment and use of iPSCs-based disease models usually involve the following steps (Lorenzo et al. 2013), (1) reprograming somatic cells into iPSC

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(2) inducing iPSC differentiation into disease-relevant cell types, (3) generating disease-specific iPSC intervention line, (4) characterizing the disease phenotype and molecular profile, and (5) conducting functional assay and drug screening to study disease mechanism and assess therapeutic interventions, and creation of isogenic controls using gene editing techniques such as CRISPR/Cas9 (usually by editing known disease-associated genes to obtain repaired healthy iPSCs); differentiation of the cells into various disease-related specific cells and define diseasespecific phenotypes by comparing diseased and healthy specific cells or organoids; studying these phenotypes at the molecular level can identify new pathological mechanisms and provide new opportunities for drug discovery and personalized therapy. In the production of IPSC-derived peripheral nerve disease models, by reprogramming patients’ somatic cells into iPSCs and then differentiating them into neural cells, a relatively realistic model of peripheral nervous system disease can be established, providing an effective tool for studying the pathogenesis of the disease as well as developing new drug treatments. One of the key steps is to obtain and culture iPSCs (Peter et al. 2019). Currently, common methods include transforming patients’ somatic cells into iPSCs by cell reprogramming techniques and then maintaining their stemness in a culture medium. To improve the efficiency of obtaining and culturing iPSCs, researchers are also exploring and optimizing culture conditions, such as adding specific factors and optimizing culture medium formulations. In addition, standardized validation and testing are required to ensure the genetic stability and purity of iPSCs.

4.4

Classification of IPSC-Derived Disease Modeling

IPSC-based disease modeling tools are currently categorized into two main types: 2D and 3D models. 2D iPSC-based disease models are extensively employed to investigate monogenic diseases, which are characterized by diseases caused by mutations in a single gene (Ebert et al. 2009a). This approach is well suited for peripheral diseases because iPSCs can be easily obtained from patients with these diseases and differentiated into disease-related cells such as neurons. Ebert et al. (2009b) generated iPSCs from fibroblasts obtained from ALS patients. These cells were expanded in culture, maintained their disease genotype, and generated motor neurons that displayed selective defects. This was the first study to demonstrate the use of human iPSCs in modeling specific pathological features of genetic diseases, representing a significant advancement in studying disease mechanisms, screening new drug compounds, and developing new therapies. Kiskinis and his team (Álvarez et al. 2023) overcame the technical limitations of iPSC models, including abnormal aggregation and inefficient maturation of differentiated neurons, by applying an artificial extracellular matrix (ECM). They obtained patient-specific iPSCs from an ALS patient and differentiated these stem cells into motor neurons with ALS features. The study highlighted the importance of artificial ECM in studying the development, function, and dysfunction of human neurons. And with the development of iPSCs-derived organoids, iPSCs have made important advances in 3D

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disease modeling (McCauley and Wells 2017). Organoids are three-dimensional multicellular aggregates derived from stem cell differentiation that are capable of self-organization and can exhibit structural features and cellular interactions of mature tissues (Dutta et al. 2017). The parallel differentiation of patient-derived and genetically corrected iPSCs into organoids allows for the designation of organoid organ-level disease phenotypes that can be qualified for specific molecular lesions. Once a clear platform for organoid-level studies is established, diseased organoids can be used for drug screening and validation studies. Van Lent (2023) reported the use of human iPSC-derived 3D organoid models, including neurons, muscle cells, Schwann cells, endothelial cells, and glial cells, for modeling CMT1A. By suppressing PMP22 expression and improving the ultrastructure myelin defect of CMT1A organoids, they recreated the key features of CMT. This demonstrated the utility of iPSCs in modeling peripheral nervous system diseases using organoid models and emphasized their therapeutic potential. Xia et al. (2023) developed cochlear organoids with functional peripheral auditory circuitry in a staging threedimensional (3D) co-culture system by initially reprogramming cochlear progenitor cells (CPCs) with increased proliferative potency that could be long-term expanded, then stepwise inducing the differentiation of cochlear HCs, as well as the outgrowth of neurites from SGNs. However, it is important to note that cochlear organoids are still a relatively new and developing technology. Further research is needed to optimize their structure and function, improve their maturity, and enhance their predictive power for drug screening and clinical applications. Nonetheless, the establishment of cochlear organoids with functional synapses represents a significant step forward in advancing our understanding of sensorineural hearing loss and developing potential treatments for this condition.

5

Application of Different Human IPSC-Derived Models for Peripheral Nerve Diseases in Drug Discovery

5.1

Neuromuscular Junction Model

The neuromuscular junction (NMJ) acts as a specialized cellular synapse connecting motor neuron with skeletal muscle fiber and facilitating the conversion of electrical and chemical signal into coordinated physical activity is a cellular synapse between motor neurons and skeletal muscle fibers that translates electrical and chemical signals into physical activity. The neuromuscular junction degeneration is a specific pathological feature of many neuromuscular diseases, including amyotrophic lateral sclerosis (ALS) and muscular dystrophy, which are closely associated with peripheral nerve diseases. Neuromuscular junction (NMJ) degeneration is the early cytopathy of ALS that directly influences motor neuron function. Cytopathic cells, motor neurons, and skeletal muscles in the NMJ influenced each other to promote the progression of ALS (Pradat et al. 2007). Meanwhile, NMJ models in vitro address the limitations of animal models in NMJ development and disease processes (Vilmont et al. 2016). This model is easy to operate and allows for preclinical

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efficacy and side effect testing of medicines in a patient-specific mode. Santhanam N et al. (2018) developed an NMJ model in vitro by using a labeled co-culture system and image subtraction video to monitor muscle contractions. At the same time, the addition of incremental doses of different synapse-blocking drugs Botox, Curare, and α-BTX established dose-response curves for the three NMJ-blocking drugs. This system now enables functional monitoring of NMJ in a human model system with applications for ALS, SMA, and other neurodegenerative diseases utilizing iPSCderived cells. Osaki T et al. (2018) combined IPSC from ALS patients with a microfluidic device to construct an NMJ model at the 3D level to study the ability of the combination of rapamycin and bosutinib to restore muscle contraction. Yoshioka K et al. (2020) developed an NMJ model and successfully developed a 3D NMJ model consisting of motor neurons and myotubes, which optimized the level of contractile force production, making the model more sensitive in assessing the effects of drugs on muscle contraction and shortening the time required to construct the model, making it easier to apply in drug screening. Human disease modeling of the NMJ in vitro may help construct mechanistic hypotheses for early pathogenesis in neuromuscular diseases as well as facilitate the identification and validation of targets and personalized preclinical therapeutic candidates (Pereira et al. 2021a). It is important to note that while NMJ models offer significant advantages, they also have their limitations. These models may not fully capture the complexity of the in vivo NMJ environment and additional validation and refinement are necessary to improve their accuracy and predictive power. Nevertheless, they provide valuable tools for preclinical drug screening, reducing reliance on animal studies, and improving the efficiency of drug development processes.

5.2

Neural Crest Model

During early vertebrate development, a distinct group of cells called neural crest stem cells (NCSCs) emerges, exhibiting stem cell-like properties, NCSCs to their multipotency and ability to generate a diverse array of cell types, serve as a valuable cellular resource for tissue regeneration disease modeling and drug discovery (Soto et al. 2021). Numerous studies have shown (Liu and Cheung 2016) that adult tissuederived NCLSC can be used for peripheral nerve regeneration and that human ESC/ iPSC-derived NCLSC can differentiate into peripheral neurons and Schwann cells. Thus, this technology has served as a platform to identify potential drug candidates that can restore impaired function and potentially be used as therapeutic agents. Liu Q et al. (2012) provided a pathway to generate large numbers of neural crestspectrum cells from hESC and patient-specific iPSC for potential cell therapy and drug screening. These in vitro disease models have become a powerful assay system for evaluating NCC dysfunction in not only neurocristopathies but also infants with toxic exposure to factors such as vitamin A and alcohol, which affect neural crest development. Lee G et al. (2009) established a model in vitro by patient-specific targeted differentiation of iPSCs into the neural crest spectrum (the main tissue affected in ancestral autonomic dysfunction FD) as well as exposed three

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quantifiable parameters of disease state: defects in IKBKAP splicing, neurogenesis, and migration of FD-iPSC derived neural crest precursors. The researchers then investigated the effects of epigallocatechin gallate (ECGC) and tocotrienols on FD and explored the feasibility of the drug candidates’ effects on the disease. Lee G’s group (2009) then used the same model to further investigate the effect of SKF (α2adrenergic receptor (α2AR) antagonist) on the defective migration of neural crest precursors. The utilization of iPSC-derived neural crest models in the drug target screening process offers several advantages. Firstly, it provides a human-specific model that more accurately reflects the biology of peripheral neurological diseases compared to traditional animal models or cell lines. Secondly, these models can be personalized by using iPSCs derived from patients with specific genetic backgrounds, allowing for the identification of individualized drug targets or treatment approaches.

5.3

Various IPSC-Derived Neuronal Cell Subtypes

The human nervous system is a highly intricate network composed of multiple neuronal cell subtypes, and its functionality relies on their intricate interaction. Although the most neurological disorder can be attributed to an abnormality in specific cell subtypes, the underlying mechanism behind this condition remains largely elusive (Lee et al. 2012). Additionally, mixed-type cultures and co-cultures enable additional analysis of diverse phenotypes within neuronal populations without sacrificing potential cellular non-autonomous disease etiology processes (Imaizumi et al. 2015). To accurately represent diseases, differentiated cells with localized characteristics must be used. Certainly, scientists from all over the world have employed hiPSCs from patients to examine several diseases of the peripheral nervous system, including amyotrophic lateral sclerosis (ALS) (Pereira et al. 2021b; Davis-Dusenbery et al. 2014), chemotherapy-induced peripheral neuropathy (CIPN) (Sances et al. 2016), and neuropathic pain (Mortensen et al. 2022; Ryu et al. 2022). Davis-Dusenbery et al. (2014) induced differentiation of pluripotent stem cells into spinal motor neurons (MNs) through the use of small molecules and recombinant signaling molecules in three main stages: neuralization via GSK-3β and dual SMAD inhibition, tailing with retinoic acid (SHH agonist), and ventralization via SHH activation. Then, MN progenitors depend on neurotrophic factors (GDNF, BDNF, CNTF) for axonal projection and differentiate into MN and become electrophysiologically active within 2–4 weeks. Peripheral neurotoxicity is a major task in drug development and environmental medicine. Current methods used to test neurotoxicity in addition to costly experimental animals (Xiong et al. 2021), new strategies for ipSCD-based high-throughput screening (Hartung and Leist 2008) hold great promise for drug discovery, toxicology research, and regenerative medicine. Hoelting et al. (2016) developed a toxicological test model for peripheral neurotoxicity by tracing iPSC differentiation into dorsal root ganglion (DRG) neurons. The assay leverages the potential of human pluripotent stem cells to generate cells or tissues to assess cell death and neurite damage, enabling the testing of more than 30 chemical

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agents. The study demonstrated the potential of hiPSCs for clinically relevant safety testing of drugs in use and emerging drug candidates. This dorsal root ganglion (DRG)-like neuron-based neurotoxicity testing model allows for different exposure parameters, such as the time window of exposure. Holzer et al. (2022) demonstrated the viability of creating a human cell-based target-cell specific assay by showing that modest dosages of bortezomib might cause mild noncytotoxic stress. Additionally, ipSC-derived sensory neurons are a useful model for assessing CIPN in investigations including chemotherapy (Sances et al. 2016). Previous research has demonstrated the significance of iPSC-derived sensory neurons (iPSC-SNs), which have been shown to represent the clinical characteristics of CIPN, including individual CIPN sensitivity and the degradation of distal nerve ends. By contrasting the neurotoxicity of various kinds of chemotherapeutic drugs, iPSC-derived pharmacokinetic parameters were obtained from models associated with the development of CIPN (Holzer et al. 2022; Schinke et al. 2021). Cai S et al. (2017) developed an efficient chemical protocol to differentiate human-induced pluripotent stem cells into PSC-derived sensory neurons. The derived sensory neurons express membranebound signaling along with the sensory neuron-associated transcription factors BRN3A, trypanosomes, and NeuN. After in vitro induction of somatic cells from patients with neuropathic pain, Namer et al. demonstrated the lack of effectiveness of lacosamide, an antiepileptic drug for neuropathic pain, in the treatment of neuropathic pain (Namer et al. 2019). However, it is important to note that the translation of iPSC-based research findings into clinical applications still faces challenges. Additional studies, rigorous validation, and regulatory considerations are necessary to ensure the safety, efficacy, and reproducibility of iPSC-based personalized medicine approaches. Nonetheless, the confirmation that patient-derived iPSCs can inform efficient treatment planning represents a significant step forward in realizing the potential of individualized medicine.

5.3.1 Neural Mesodermal Model The central and peripheral nervous systems jointly regulate and control the interconnected network of nervous system disorders within the body. A particularly fascinating cell population known as neural crest cells (NCCs) serves as the primary source of development for the peripheral nervous system (PNS) (Tchevers et al. 2019). A small portion of the NCC population goes through a natural reprogramming procedure involving OCT4 activation throughout this process to increase its capacity for differentiation (Zalc et al. 2021). The current study suggests an alternative and easy-to-handle model of neural-mesodermal assemblies, which are generated by co-culturing mesoderm and neurospheres (Rockel et al. 2023). Moreover, iPSC-based peripheral nervous system models have the potential to be utilized for toxicity screening and drug testing. These models enable researchers to assess the effects of various chemical compounds, drugs, or environmental factors on peripheral nervous system cells derived from iPSCs. By exposing these cells to different substances, researchers can evaluate their impact on cellular viability, functionality, and other relevant endpoints. This information can aid in identifying

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potential toxicities or therapeutic effects, contributing to the development of safer and more effective drugs.

6

Conclusion

Further scientific study is needed to enhance the precision and significance of iPSCderived peripheral nervous system cell models, further scientific investigation is necessary. The integration of advanced technologies, such as genome editing and organ-on-a-chip system, holds the potential to achieve a more comprehensive representation of disease complexity (Hockemeyer et al. 2011; Park et al. 2012). In conclusion, peripheral nervous system modeling using iPSCs represents a promising approach with vast potential for drug discovery and customized therapy. Through disease-specific iPSC-derived models, researchers can conduct efficient screenings and identify potential therapeutic compounds. Furthermore, by using patient-specific iPSC-derived peripheral nervous system cell models, personalized medicine can be advanced, allowing for tailored treatment options based on individual patient characteristics. Continued advancements in technology and collaborative efforts will further enhance the precision and applicability of these models, ultimately leading to significant progress in clinical and neurological medicines.

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Part IV Non-Neuronal Specialized Cell Types

Human-Induced Pluripotent Stem Cell-Based Differentiation of Cardiomyocyte Subtypes for Drug Discovery and Cell Therapy Ziwei Pan and Ping Liang

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Different Drug Screening Platforms and the Emergence of Human iPSCs . . . . . . . . . . . . . . . . 2.1 Animal Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 In Vitro Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Adult Human Cardiomyocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Human iPSC-CMs and Their Subtypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Generation of Ventricular-Like Cardiomyocytes from iPSCs for Cell Therapy and Drug Discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Generation of Atrial-Like Cardiomyocytes from iPSCs for Cell Therapy and Drug Discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Generation of Nodal-Like Cardiomyocytes from iPSCs and Use in Cell Therapy . . . 4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Drug attrition rates have increased over the past few years, accompanied with growing costs for the pharmaceutical industry and consumers. Lack of in vitro models connecting the results of toxicity screening assays with clinical outcomes accounts for this high attrition rate. The emergence of cardiomyocytes derived from human pluripotent stem cells provides an amenable source of cells for disease modeling, drug discovery, and cardiotoxicity screening. Functionally similar to to embryonic stem cells, but with fewer ethical concerns, induced pluripotent stem cells (iPSCs) can recapitulate patient-specific genetic Z. Pan · P. Liang (✉) Key Laboratory of Combined Multi-organ Transplantation, Ministry of Public Health, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China Institute of Translational Medicine, Zhejiang University, Hangzhou, China e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_663

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backgrounds, which would be a huge revolution for personalized medicine. The generated iPSC-derived cardiomyocytes (iPSC-CMs) represent different subtypes including ventricular-, atrial-, and nodal-like cardiomyocytes. Purifying these subtypes for chamber-specific drug screening presents opportunities and challenges. In this chapter, we discuss the strategies for the purification of iPSCCMs, the use of iPSC-CMs for drug discovery and cardiotoxicity test, and the current limitations of iPSC-CMs that should be overcome for wider and more precise cardiovascular applications. Keywords

Cardiotoxicity · Drug screening · iPSC · Subtype

1

Introduction

Cardiovascular disease (CVD) is the most significant cause of morbidity and mortality in the modern world. However, despite advances in clinical research, much about pharmacological and cellular treatments for CVD remains to be learned. New drug discovery, development, and safety testing take up a long, arduous, and expensive period while facing a high rate of attritions due to the lack of economical and reliable methods that can accurately mimic human physiological responses. Drug development usually takes 10–15 years and costs approximately $1,000 million for every new drug (DiMasi et al. 2016), presenting a huge amount of time, effort, and money. The cost and risk grow exponentially as drugs advance toward the clinic (DiMasi et al. 2016), especially when a new drug is ultimately abandoned. Adverse drug reactions (ADRs) are major causes of drug attrition and include cardiac adverse drug reactions, also called cardiotoxicity. Cardiac adverse drug reactions alone account for approximately one-third of drugs withdrawn due to safety concerns, including disturbances in ventricular depolarization/repolarization and QT interval, arrhythmias, bradycardia, tachycardia, decreases in left ventricular ejection fraction, and congestive heart failure (Guo et al. 2011; Mathur et al. 2013; Weaver and Valentin 2019). Besides, a substantial number of drugs can also affect cardiac function beyond electrophysiology, such as contractility, mitochondrial function, and cellular signaling. Over the past few decades, strict assessment of cardiac safety issues has caused a consistent rise in the attrition rate during all phases of drug development. To decrease the potential for toxicity and late-stage drug attrition, pharmaceutical and biotechnology industries seek systems that can identify drug-induced toxicity with phenotypic screening at early stages of development to reduce cost and risk (Moffat et al. 2014). Model systems that can better predict human toxic effects are therefore highly needed.

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Different Drug Screening Platforms and the Emergence of Human iPSCs

Given these limitations and recognizing the fact that drugs regularly have to be withdrawn from the market because of cardiotoxicity, there is an urgent need for more comprehensive models for drug testing. To date, several models have been used for drug screening, yet each model has its limitations.

2.1

Animal Models

Rodents are the most commonly used models for animal testing, including rats, mice, and guinea pigs. Larger animals (pigs, dogs, sheep, and primates) are physiologically closer to humans than rodents, and parameters such as heart rate, action potential duration (APD), repolarization mechanisms, contractile filament protein isoforms, ion channels, and ion pumps may be similar to humans (Tsang et al. 2016). However, despite a substantial match between large animal models and humans, animal models still cannot replace human clinical trials. Their use for highthroughput drug screening is also limited, as costs, time, and manpower required are significant. Thus, the ethical and economical concerns associated with the use of animals are usually substantial, thus explaining why the use of animals is generally minimized.

2.2

In Vitro Models

Human embryonic kidney 293 (HEK 293) and Chinese hamster ovary (CHO) cell lines can overexpress specific genes of interest, such as KCNH2, a gene encoding for the alpha subunit of a potassium ion channel (human ether-a-go-go related gene, hERG). Cell lines overexpressing hERG channel can be used as heterologous expression models to evaluate the effect of drugs for functional assessment (Thomas et al. 2006). Due to the high-throughput and low cost of this platform, the hERG inhibition cellular screening assay has been used widely at the early stage of drug development, since drug-induced blocking of hERG may induce ventricular tachyarrhythmia (Clancy and Rudy 2001; Sauer and Newton-Cheh 2012). A main drawback of these cellular models is the lack of macromolecular cardiac ion channel complexes, which prevents simulation of the exact molecular and electrophysiological cardiomyocyte-specific phenotype (Hoekstra et al. 2012). Therefore, druginduced hERG blockage is not sensitive enough for predicting all kinds of drug toxicity. Consequently, due to preclinical findings of adverse effects on hERG or QTc, many candidates are discarded during the initial phase of drug discovery despite their otherwise favorable characteristics. It has been estimated that the discontinuation rate of preclinical drug testing studies due to these issues is approximately 60% (Ponti 2008).

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Adult Human Cardiomyocytes

Primary cardiomyocytes obtained from biopsies or explanted hearts are extremely difficult to culture (Prior et al. 2018) and thus cannot be used for high-throughput experiments. Furthermore, it is known that the adult heart lacks a stem/progenitor cell population and cannot be regenerated (Li et al. 2018). Consequently, the only source for large amounts of human cardiomyocytes are pluripotent stem cells including both embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs). For the last few decades, pluripotent stem cells could only be obtained from the inner cell mass of the blastocyst-stage embryo which created ethical problems. The discovery of iPSCs by Shinya Yamanaka and Kazutoshi Takahashi in 2006 revolutionized the field of stem cell biology and regenerative medicine (Takahashi and Yamanaka 2006). Reprogramming somatic adult tissue by forced expression of Oct4, Klf4, Sox2, and c-Myc (OKSM) can generate patient-specific iPSCs. Since ESCs often face ethical concerns and regulatory restrictions, iPSCs have become a superior option. Importantly, iPSC-CMs acquire many characteristics of normal in vivo cardiomyocytes, including molecular, structural, and functional properties such as ion channel, transporter, and receptor expression, as well as electrophysiological properties and biochemical reactions (Ma et al. 2011).

3

Human iPSC-CMs and Their Subtypes

Several cardiomyocyte differentiation protocols have been developed ranging from embryoid body (EB)-based 3D differentiation to small molecule-induced monolayer differentiation (Burridge et al. 2012; Mummery et al. 2012). Nowadays, the generation of iPSC-CMs can be achieved in chemically defined conditions by modulation of WNT signaling (Burridge et al. 2014; Lian et al. 2012). Although successful, most of these studies have resulted in mixed cardiovascular populations, containing predominantly ventricular-like cells together with around 15–20% atrial-like and 5% nodal-like cells (Burridge et al. 2014). A mixed population can be problematic for research, as contaminating cell types can easily influence disease or drug outcomes in vitro and alter the behavior of cardiovascular grafts in vivo. The isolation of each subtype is important for both engraftment to the host and drug screening. Ideally, the use of iPSC-CMs for drug efficacy and toxicity screening should involve relatively pure populations of the cardiomyocyte subtype of interest, as electrical heterogeneity in in vitro preparations could confuse results, particularly when atrial or ventricular arrhythmias are concerned. Thus, one of the main challenges is to achieve a more defined iPSC-CM subtype with high purity during the differentiation. To treat diseases that affect specific regions of the heart, it is essential to develop differentiation strategies that promote the generation of each of the cardiomyocyte subtypes. Currently, purified iPSC-CMs can be achieved by selectively isolating the desired subtypes. One approach has been to include reporter gene constructs to select

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specific cell types, such as myosin light chain 2 (MYL2)-GFP for ventricular cardiomyocytes (Bizy et al. 2013) or sarcolipin (SLN)-tdTomato for atrial cardiomyocytes (Josowitz et al. 2014). Besides, during the early stage of progenitor development, progenitors that express NKX2.5+/TBX5+ can predominantly give rise to ventricular cardiomyocytes (Thomas et al. 2022). During WNT inhibition, separate precursor populations arise from the mesoderm that selectively express CYP26A1 which gives rise to CD235a+ ventricular progenitors, or RALDH2 that promotes atrial myocyte genesis (Lee et al. 2017). Subtype-specific cardiomyocyte differentiation protocols employing a cocktail of chemicals and growth factors have also been established (Devalla et al. 2015; Lee et al. 2017; Protze et al. 2017). These methods mimic in vivo heart development by controlling several signaling pathways, including WNT, retinoic acid (RA), BMP, and Activin/Nodal signaling. Inhibition of the WNT pathway at the mesoderm stage is essential for cardiac development (Marvin et al. 2001; Protze et al. 2019; Schneider and Mercola 2001), and RA signaling promotes the formation of atrialspecific ion channels and enables the in vitro testing of drugs that specifically target these channels (Devalla et al. 2015; Hochgreb et al. 2003; Niederreither et al. 2001; Protze et al. 2019). In addition, ErbB antagonist AG1478, fibroblast growth factor (FGF) inhibitor PD173074, and activation of TGFβ pathway boost the nodal population by inhibiting neuregulin/ErbB signaling pathway (Brown et al. 2017; Protze et al. 2017; Zhu et al. 2010); retinoic acid inhibition with BMS-189453 increases the ventricular population (Zhang et al. 2011). Furthermore, Lee et al. (2017) demonstrated that iPSC-derived ventricular-like and atrial-like cardiomyocytes (iPSC-vCMs and iPSC-aCMs) are enriched by controlling the levels of BMP4 and Activin/Nodal signaling, in addition to RA signaling (Lee et al. 2017; Protze et al. 2019). The cardiac cell subtypes can be identified by their specific gene expression profiles (myosin light chain proteins MLC2a and MLC2v) and different electrophysiological properties (action potential shape). For example, APD at a certain percentage of repolarization (e.g., APD90 duration (Cyganek et al. 2018; Pei et al. 2017)) is operationalized and used alone or as a ratio (e.g., repolarization fraction [APD90APD50]/APD90 (Pei et al. 2017) or APD20/APD80 (He et al. 2003)) to classify atrial cardiomyocytes, based upon their shorter plateau duration. No highly reliable cell surface marker is currently available to allow for fluorescence-activated cell sorting of these iPSC-CM subpopulations. These advances have laid a strong foundation to obtain “on-demand” chamberspecific cell types from infinite source of iPSCs (Fig. 1).

3.1

Generation of Ventricular-Like Cardiomyocytes from iPSCs for Cell Therapy and Drug Discovery

Current cardiomyocyte differentiation protocols result in a heterogeneous population of cardiomyocytes in which more than half, but sometimes as many as 90%, are ventricular-like. However, a small population of atrial- and nodal-like

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Fig. 1 Generation of iPSC-CMs and their subtypes. The iPSC-CMs containing a mixture of different subtypes are generated using a 2D small molecule-based monolayer differentiation protocol. For the upcoming experiments, particular types of cardiomyocytes need to be generated in order to get precise results. Atrial-like cardiomyocytes can be used for modeling atrial fibrillation and testing atrial-specific drugs. Ventricular-like cardiomyocytes have the potential for the restoration of cardiac function after myocardial infarction and abrogate possible ventricular arrhythmias. Biological SAN pacemaker cells are a promising alternative to artificial pacemakers with serious drawbacks

cardiomyocytes is almost always present. Multiple strategies have been used to purify ventricular-like cardiomyocytes for cell therapy and regeneration as well as other purposes. Firstly, ventricular-like cardiomyocytes can be selected by specific gene reporters, such as MLC2v promoter-derived fluorescent proteins (Chen et al. 2017; Li et al. 2017), EGFP+/mCherry- cells that represent ventricular subtype, and TBX5+ NKX2-5+ FHF-like cells that give rise to ventricular-like cardiomyocytes (Zhang et al. 2019). Furthermore, cell-specific surface markers (such as CD77+/ CD200- cell surface signature) can be used for the purification of ventricular-like cardiomyocytes (Veevers et al. 2018). CD235a+ CYP26A1+ mesoderm progenitors can develop into ventricular-like cardiomyocytes (Lee et al. 2017). Small molecules and growth factors are without a doubt the most practical technique to produce particular cardiomyocyte subtypes. Sequential administration of BMP4, Rho kinase

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inhibitor, Activin A, and IWR-1 in cardiogenic embryoid bodies can generate over 92% of ventricular-like cardiomyocytes (Karakikes et al. 2014; Weng et al. 2014), and inhibition of RA signaling indirectly promotes ventricular subtype formation (Zhang et al. 2011). According to this, a pan-retinoic acid receptor antagonist BMS-189453 together with Noggin significantly directs the cardiac progenitors toward a ventricular-like subtype. So far, drug screening campaigns using purified ventricular-like cardiomyocytes have not been reported. The purified iPSC-derived ventricular-like cardiomyocytes (iPSC-vCMs) often serve as controls when atrial-specific drugs are tested. However, most drug screening experiments are based on the regular differentiation protocol, which results in predominated ventricular-like cardiomyocytes. And many drug test results are based on the ventricular ion channels, such as the Comprehensive In Vitro Proarrhythmia Assay (CiPA) initiative established in 2013. According to the FDA guidelines, to bring a new drug to the market, appropriate toxicity tests have to be performed. These tests include, but are not limited to, “the studies of the absorption, distribution, metabolism, and excretion of the drug in animals.” The current in vitro standard for preclinical assessment is the analysis of hERG channel response in heterologous cell types. Although this method is reliable in terms of isolating compounds with potential arrhythmogenic properties, the high safety margins associated with hERG assay reduce confidence in predicting arrhythmogenic potential accurately (Gintant 2011). As such, issues with false positives are a significant problem and may have led to several harmless compounds being abandoned despite their therapeutic potential (Kramer et al. 2013). The need for more predictive preclinical cardiac toxicity test assays is critical, and iPSC-CMs represent an excellent model for screening new compounds for potentially toxic effects. The objective of the CiPA initiative is to establish a new paradigm for assessment of the clinical potential of torsades de pointes (TdP) that is not measured exclusively by the potency of hERG block and QT prolongation. These are the basic aims of CiPA: (1) In vitro drug effects on multiple cardiac ventricular channels including IKr, IKs, ICa, L, INa, L, INa, Ito, and IK1. (2) In silico reconstruction of cardiac action potential. (3) Confirmation using human stem cell-derived cardiomyocytes. (4) Careful clinical assessment of electrophysiologic effects in phase 1 ECG safety studies (Fig. 2). To assess electrophysiological effects in vitro, CiPA focuses on experimental approaches using multi-electrode array (MEA) or voltage-sensing optical (VSO) techniques, which provide high-throughput tests and reduced variability. In MEA studies, changes in the duration of extracellular field potentials are used to detect delayed repolarization and the incidence of proarrhythmic early after depolarizations (EADs). VSO studies rely on optical measures of transmembrane voltage to detect changes in the APD and repolarization morphology as well as EAD incidence (Gintant et al. 2017). However, the difference between cardiomyocytes from different iPSC lines may influence the electrophysiological data. There are currently five to six companies on the US market, and the two main ones are Cellular Dynamics International (CDI) and Axiogenesis (Table 1).

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Fig. 2 The workstream of CiPA (from https://cipaproject.org/about-cipa/)

A computational iPSC-CM model has been used as part of a genetic algorithm to identify blockage of cardiac ion channels during in vitro drug studies. The voltage clamp data based on this in silico model uncovered a previously unidentified If block by quinidine, which was confirmed with experiments using the HEK293 expression system and automated patch clamp (Clark et al. 2022). In addition, patient-specific iPSC-CMs models can be used for drug screening to search for potential therapies. Numerous disease models have been developed and potential drugs have been tested that achieved great effects (Table 2).

3.2

Generation of Atrial-Like Cardiomyocytes from iPSCs for Cell Therapy and Drug Discovery

It is reported that the incidence of atrial arrhythmias has been increasing over the past few years. Though aging and pharmaceutical treatments might relate to atrial arrhythmias, appropriate experimental methods to detect drug-induced atrial arrhythmias also need to be established. Atrial fibrillation (AF) is one of the most usual arrhythmic disorders characterized by rhythm disturbances caused by ectopic activity, leading to remodeling and deterioration of atrial function, embolic stroke, and heart failure (Morin et al. 2016; Wolf et al. 1991). The major treatments of AF are electrical cardioversion and invasive catheter ablation (Calkins et al. 2018) as well as pharmacological

High TdP risk

Multiple ion channel block

Multiple ion channel block

Multiple ion channel block

Multiple ion channel block (NaV1.5, CaV1.2, hERG)

Kinase inhibitor

Dofetilide

Ibutilide

Quinidine

Vandetanib

Action site Blocks both IKr and IKs

Bepridil

Drugs listed by CIPA Azimilide

0.1 μM

300 nM

Prolongation of APDc and FPDc; reduced spike amplitude; repolarization delays; arrhythmias Repolarization prolongation; arrhythmias

1 nM

2 nM

0.1 μM

Effective concentration 0.3 μM

Arrhythmias; EAD

Prolongation of APDc and FPDc; arrhythmias

Effect FPDc prolongation; beating frequency decreasing; early after depolarization Repolarization delays; arrhythmias

Table 1 List of compounds defined by CiPA initiative and their toxicity tested on iPSC-CMs

iCell™/ iCell2™/ Cor4U®/ Cellartis®

iCell™/ iCell2 ™/ Cor4U® iCell™/ iCell2™/ Cor4U®/ Cellartis®

iCell™/ iCell2 ™/ Cor4U®

iCell™/ iCell2 ™/ Cor4U®

Cell type iCell™

Manual patch clamp/MEA/ VSO/ CardioExcyte 96

Manual patch clamp/MEA/ VSO/ CardioExcyte 96

MEA/VSO

Manual patch clamp/MEA/ VSO

MEA/VSO

Test platform MEA

(continued)

(Blinova et al. 2017, 2018; Bot et al. 2018; Kitaguchi et al. 2017; Nozaki et al. 2017; Pfeiffer-Kaushik et al. 2019) (Blinova et al. 2018; Bot et al. 2018)

(Blinova et al. 2017, 2018; Kitaguchi et al. 2017; Nozaki et al. 2017) (Blinova et al. 2017, 2018; Mulder et al. 2018; Nozaki et al. 2017) (Blinova et al. 2018; Nozaki et al. 2017)

References (Nozaki et al. 2017)

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Intermediate TdP risk

Multiple ion channel block

Multiple ion channel block

Antibiotic drug

Multiple ion channel block

Cisapride

Clarithromycin

Clozapine

Blocks both β-adrenoreceptor and hERG channel H1 receptor antagonist; multichannel block

Action site Blocks the fast sodium channel

Chlorpromazine

Astemizole

D,l Sotalol

Drugs listed by CIPA Disopyramide

Table 1 (continued)

Prolongation of FPD and APDc; EADs; repolarization delays; arrhythmias Prolongation of repolarization; arrhythmias Shortening of FPDc; increased beat frequency

Prolongation of repolarization prolongation; arrhythmias Early afterdepolarization; beating arrest

Effect Decreased FPDmax; increased EADs; prolongation of APD90 Prolongation of repolarization; arrhythmias

iCell2™/ Cor4U®/ Cellartis® iCell™ 10 μM 0.3 μM

iCell™/ Cor4U®

iCell™/ iCell2™/ Cor4U®/ Cellartis® iCell™/ iCell2™/ Cor4U®/ Cellartis®

Cell type iCell™/ iCell2™/ Cor4U®/ Cellartis® iCell2™/ Cor4U®/ Cellartis®

2.5 nM

10 μM

3 nM

15 μM

Effective concentration 10 μM

MEA/VSO/ CardioExcyte 96 MEA

(Nozaki et al. 2017)

(Blinova et al. 2017, 2018; Kitaguchi et al. 2017; Nozaki et al. 2017) (Blinova et al. 2018; Bot et al. 2018)

(Blinova et al. 2018; Bot et al. 2018; Kitaguchi et al. 2017; Nozaki et al. 2017) (Blinova et al. 2017; Bot et al. 2018; Nozaki et al. 2017)

MEA/ CardioExcyte 96 Manual patch clamp/MEA/ VSO/ CardioExcyte 96 Manual patch clamp/MEA/ VSO

(Bot et al. 2018)

References (Bot et al. 2018)

MEA/VSO/ CardioExcyte 96

Test platform VSO/ CardioExcyte 96

218 Z. Pan and P. Liang

No or very low TdP risk

Dopamine d2 receptor

Blocks serotonin receptor

Risperidone

Ondansetron

H1 receptor block; multiple ion channel block

Multiple ion channel block

Pimozide

Loratadine

H1 receptor block

Terfenadine

Blocks calcium channel

Potent dopamine receptor antagonist

Droperidol

Diltiazem

Blocks hERG channel

Domperidone

Increased beating frequency

Prolongation of repolarization; arrhythmias Shortening of APDc and FPDc

–

Prolongation of repolarization; beat rate decrease; arrhythmias Prolongation of FPDc and repolarization; decrease in spike amplitude Prolongation of FDP; arrhythmias

Prolongation of repolarization; arrhythmias

iCell™/ iCell2™/ Cor4U®/ Cellartis® iCell™/ Cor4U®/ Cellartis®

0.1 μM

iCell™/ iCell2™/ Cor4U®/ Cellartis® iCell2™/ Cor4U®/ Cellartis® iCell2™/ Cor4U®

iCell™/ iCell2™/ Cor4U®

iCell™/ iCell2™/ Cor4U®/ Cellartis® iCell2™/ Cor4U®/ Cellartis®

90 nM

30 nM

0.1 μM

3 nM

100 nM

0.1 μM

10 nM

(Blinova et al. 2017; Bot et al. 2018)

Manual patch clamp/MEA/ VSO/ CardioExcyte 96 MEA/ CardioExcyte 96

(continued)

(Bot et al. 2018; Nozaki et al. 2017)

(Blinova et al. 2018)

MEA/VSO

(Blinova et al. 2018; Bot et al. 2018; Kitaguchi et al. 2017)

MEA/ CardioExcyte 96

(Bot et al. 2018)

(Blinova et al. 2017; 2018; Harris et al. 2013)

MEA/VSO

CardioExcyte 96

(Blinova et al. 2018; Bot et al. 2018)

(Blinova et al. 2018; Bot et al. 2018; Nozaki et al. 2017)

MEA/VSO/ CardioExcyte 96

MEA/VSO/ CardioExcyte 96

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Blocks ICaL

Calcium channel antagonist Blocks multiple ion channel (Na+ and hERG)

Anticancer drug

Blocks hERG potassium channel and potent L-type calcium channel

Nifedipine

Nitrendipine

Tamoxifen

Verapamil

Ranolazine

Inhibiting both Nav1.5 and hERG

Action site Blocks β1adreno-receptor

Mexiletine

Drugs listed by CIPA Metoprolol

Table 1 (continued)

3 μM

–

0.1 μM

0.3 μM

Prolongation of FPDc

Shortening of FPDc; increased spontaneous beat rate; shortening in APD20 and APD90

iCell™/ iCell2™/ Cor4U®

10 nM

Decrease in FPDmax

iCell™/ Cor4U®/ Cellartis® iCell™/ Cor4U®

iCell™/ Cor4U®/ Cellartis® Cellartis®

10 nM

Shortened both cycle length and APD90

iCell™/ iCell2™/ Cor4U®/ Cellartis®

Cell type iCell™/ Cor4U®/ Cellartis®

1 μM

Effective concentration 100 μM

Reduced spike amplitude

Effect Induced arrhythmias

Manual patch clamp/MEA/ VSO

CardioExcyte 96

VSO/ CardioExcyte 96 CardioExcyte 96 MEA

Test platform Patch clamp/ MEA/VSO/ CardioExcyte 96 Patch clamp/ MEA/VSO/ CardioExcyte 96

(Blinova et al. 2017; Harris et al. 2013; Mulder et al. 2018)

(Blinova et al. 2017, 2018; Kitaguchi et al. 2017; Nozaki et al. 2017; Pfeiffer-Kaushik et al. 2019) (Bot et al. 2018)

(Blinova et al. 2017, 2018; Bot et al. 2018; Harris et al. 2013; Nozaki et al. 2017; Pfeiffer-Kaushik et al. 2019) (Bot et al. 2018; Pfeiffer-Kaushik et al. 2019) (Bot et al. 2018)

References (Acimovic et al. 2018; Blinova et al. 2018; Bot et al. 2018)

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Idiopathic cardiomyopathy

Class Ion channelopathies

DCM

HCM

TNNT2 (p.R173W)

KCNH2 (p.T618I) MYH7 (p.A663H)

SQT

SQT

LQT3

SCN5A (p.F1473C) SCN5A (p.V1763M) KCNH2 (p.N588K)

Genetic variants KCNQ1 (p.R190Q) KCNQ1 (c.1893del) KCNH2 (p.A614V) KCNH2 (p.R176W)

LQT3

LQT2

LQT2

LQT1

Syndrome LQT1

Altered regulation of calcium ion (Ca2+); decreased contractility; abnormal distribution of sarcomeric α-actinin

Increased IKr density; shortened APD; carbachol can prolong the action potential duration and abolished arrhythmic activity Increased beat-beat interval variability; increased IKr density Cellular enlargement and contractile arrhythmia; dysregulation of Ca2+ cycling and elevation in intracellular Ca2+ ([Ca2+]i)

E4031; chromanol 293B; propranolol; isoproterenol Pinacidil

Reduced IKr; prolonged APD; reduced wild-type KCNQ1 mRNA and protein Prolonged APD; reduction of IKr; EADs; arrhythmias Prolonged APD; reduced IKr; demonstrated arrhythmogenic electrical activity Delayed repolarization; prolonged QT interval; increased risk of fatal arrhythmia Prolonged APD; elevated late Na+ current

Verapamil; propranolol; quinidine; procainamide; lidocaine; mexiletine; ranolazine; flecainide; propafenone; metoprolol; amiodarone; sotalol; dofetilide; verapamil; diltiazem; nifedipine Metoprolol; norepinephrine

Quinidine; BmKKx2

Carbachol; quinidine; sotalol; metoprolol

Mexiletine

Mexiletine

E-4031; sotalol

Drug test Chromanol 293B; E4031

Cellular phenotype Prolonged APD; reduced IKs

Table 2 List of publications using patient-specific iPSC-CMs for drug screen

(continued)

(Sun et al. 2012)

(Guo et al. 2019) (Lan et al. 2013)

(Terrenoire et al. 2013) (Ma et al. 2013b) (El-Battrawy et al. 2018a)

References (Moretti et al. 2010) (Egashira et al. 2012) (Itzhaki et al. 2011) (Lahti et al. 2012)

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Others

Class

Fabry

ARVC

ARVC

Syndrome DCM

Table 2 (continued)

desmoglein2 (DSG2) (c.638G > A) Patient#1: GLA (c.485G > A) Patient #2: GLA (c.658C > T)

Genetic variants LMNA (p.R225X) PKP2 (c.1841 T > C) Cellular phenotype Increased nuclear senescence and cellular apoptosis Lower expression of desmosomal proteins (PKP2 and plakoglobin); larger size; darker lipid droplets; greater amount of lipid Smaller amplitude and maximal upstroke velocity (Vmax) of action potential; arrhythmogenic events GL-3 accumulates in the lysosomes

(Itier et al. 2014)

(El-Battrawy et al. 2018b)

Epinephrine; isoprenaline

SAR402671; agalsidase beta

References (Siu et al. 2012) (Ma et al. 2013a)

Drug test U0126; selumetinib; AZD6244; rapamycin Nifedipine; isoproterenol

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therapy (Prystowsky et al. 2015), while electrical cardioversion and invasive catheter ablation have a strict requirement for equipment and place. Therefore, the initial treatment of most patients with AF is anti-arrhythmic drugs (i.e., pharmacological rhythm control). However, attention must be paid to some serious adverse drug effects caused by anti-arrhythmic drugs, such as ventricular tachyarrhythmias (Hindricks et al. 2021). Thus, atrial-like cardiomyocytes are needed for the atrialspecific drug screening. During the heart development, RA plays a crucial role in the chamber formation to coax human PSCs to atrial-like cardiomyocytes in vitro. At first, animal experiments found that inhibition of the retinoic acid pathway in mouse (XavierNeto et al. 1999) and chicken (Hochgreb et al. 2003) embryos led to the development of larger ventricles, while atrial volumes would be smaller or even disappear. And in human ESC differentiation, administration of retinoic acid at an early stage can present more cells with atrial-like phenotype (Gassanov et al. 2008; Zhang et al. 2011). Zhang et al. further investigated the potential mechanisms of retinoic acid signaling and its effects on atrial and ventricular differentiation in human hESCs and found that during ESC differentiation retinoic acid treatment was able to cause 94% of differentiated cardiomyocytes to have atrial-like action potentials (Zhang et al. 2011). On this basis, the use of retinoic acid treatment for the directed differentiation of iPSC to atrial cells has become increasingly sophisticated (Kleinsorge and Cyganek 2020), and the established models of atrial fibrillation have emerged and have been applied in screening experiments for atrial-specific drugs. The atrial subtypes can be distinguished by their specific cell surface marker. Analysis of early developmental stages revealed that ventricular and atrial cardiomyocytes derive from different mesoderm populations that can be distinguished based on CD235a and RALDH2 expression, and it has been demonstrated that the mesoderm that responds to retinol to produce atrial cardiomyocytes is the RALDH2+, not the CD235a+. Using different concentrations of BMP4 and Activin A, human PSCs can be induced into distinct mesoderm populations: CD235a+CYP26A1+mesoderm gives rise to ventricular cardiomyocytes, whereas RALDH2+ALDH+ mesoderm tends to generate atrial subtype (Lee et al. 2017). Another emerging pathway to promote atrial-specific cell fate is NOTCH signaling. NOTCH signaling is required for ventricular chamber specification during heart development; however, COUP-TFII suppresses NOTCH activity and may indirectly promote atrial cardiomyocyte specification (Churko et al. 2018; Chen et al. 2012; You et al. 2005). Loss of function of HEY2, a NOTCH pathway downstream transcription factor, dramatically boosts atrial specification by increasing the percentage of atrial-like cardiomyocytes without exogenous RA exposure (Churko et al. 2018). This pathway stays immature since NOTCH signaling also regulates ion channel activity and electrophysiological properties (Khandekar et al. 2016; Qiao et al. 2017). The accurate role of NOTCH signaling in atrial and ventricular cardiomyocytes needs to be further investigated. Clinically, AF was treated by Vaughan-Williams anti-arrhythmic drug classes I and III, but it may lead to adverse effects, which limit drugs for AF treatment (Steinberg et al. 2004). Since pharmacological treatment of atrial fibrillation was

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commonly used, it is necessary to search for atrial-specific drugs and pay attention to their adverse effect. Ultrafast delayed rectifier potassium currents (IKur) and acetylcholine-regulated potassium channel currents (IKACh) are specific in atrial cardiomyocytes and can be a potential target for the modulation of electrophysiological activity in atrial cardiomyocytes. In 2017, Devalla et al. (2015) derived atrial-like cardiomyocytes from human ESCs by modulating retinoic acid signaling. They found the expression of atrialspecific ion channel genes, KCNA5 (encoding KV1.5) and KCNJ3 (encoding Kir3.1) in human ESC-derived atrial-like cardiomyocytes (hESC-aCMs). Moreover, in response to multiple ion channel blocker (such as vernakalant) and KV1.5 blocker (such as XEN-D0101), hESC-aCMs but not human ESC-derived ventricular-like cardiomyocytes (hESC-vCMs) showed APD prolongation due to a reduction in early repolarization. In hESC-aCMs, XEN-R0703, a novel Kir3.1/3.4 blocker, restored the APD shortening caused by carbachol, while neither carbachol nor XEN-R0703 had an effect on hESC-vCMs. These observations demonstrated that hESC-aCMs are a robust model for preclinical testing to assess the atrial selectivity of novel antiarrhythmic drugs. In 2018, Lukas Cyganek et al. (2018) established the 3D model of ventricularand atrial-like cardiomyocytes. By combining the transcriptome and proteome profiling of the iPSC-CM subtypes with functional characterizations via optical action potential and calcium imaging, and with contractile analyses in engineer heart tissues (EHTs), the authors demonstrated that atrial- and ventricular-like iPSC-CMs and iPSC-EHTs highly correspond to the atrial and ventricular heart muscle, respectively. When treated with isoproterenol (ISO) and carbachol, In the presence of ISO, carbachol induced a negative inotropic effect, which was slightly more pronounced in iPSC-derived atrial-like EHTs (iPSC-aEHTs) than in iPSCderived ventricular-like EHTs (iPSC-vEHTs), and when carbachol was applied without pre-stimulation with ISO, a positive inotropic response in iPSC-vEHTs but a negative inotropic response in iPSC-aEHTs was observed. And the EHTs were also generated by another group from standard protocol (Ctrl-EHTs) and retinoic acid-based protocols (RA-EHTs). Compared with Ctrl and intact human muscle strips, RA-EHTs exhibited higher mRNA and protein concentrations of atrial-selective markers, faster contraction kinetics, lower force generation, shorter APD, and higher repolarization fraction. In addition, RA-EHTs but not Ctrl-EHTs responded to pharmacological manipulation of atrial-selective potassium currents, such as 4-AP and carbachol (Lemme et al. 2018). However, the atrial-3D model stays in an immature station compared with clinical data. In 2021, Idit Goldfracht et al. (2020) generated ring-shaped atrial and ventricular EHTs and found them to differentially express several chamber-specific markers (including unique transcription factors, sarcomeric proteins, ion channels, and gap junction protein subtypes) at both the mRNA and protein levels and display distinct ventricular or atrial molecular, electrophysiological, and contractile properties. For drug testing, carbachol, the atrial IKACh channel opener, had a dose-related effect to significantly shorten the APD in the atrial-EHTs, whereas such an effect on the ventricular EHTs was negligible. Another agent known to block the atrial-specific

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currents IKur and IKACh is vernakalant, which significantly prolonged APD in atrialEHTs, whereas it had no significant effect on the ventricular tissues. Flecainide, a well-established class Ic anti-arrhythmic drug, terminated atrial arrhythmias in an atrial tissue model. On the contrary, the use of lidocaine, a class Ib anti-arrhythmic drug for ventricular arrhythmias, significantly slowed conduction rates in ventricular tissues and had no significant effect on atrial tissues. The authors also observed re-entrant arrhythmias developed spontaneously in most atrial-EHTs, whereas the ventricular EHTs seldom developed arrhythmia spontaneously or following electrical stimulation protocols. However, this research was doubted by Christ et al. (2021), since the vernakalant cannot prolong APD90 in human atrial tissues. Later, Shitiet et al. (2021) clarified their result and proved the prolongation in atrial 2D level caused by vernakalant. Based on this, it has been agreed that the immature characteristics should be considered when drawing conclusions related to the pharmacological, molecular, electrophysiological, and contractile properties of hPSCCMs. With the refinement of assay technologies, several high-throughput screening platforms are established, which further advance the development of drug screening using the iPSC-aCM model. Based on these high-throughput platforms, a series of drugs, including 4-AP, AVE0118, UCL1684, and vernakalant, were all proved to have atrial-selective effects (Gunawan et al. 2021). And a series of drug tests (such as IKr blockers, IKs channel blockers, IKur channel blockers, selective calcium channel activators, IKAch activators, and calcium channel blockers) identified that IKur inhibitors cause prolongation of pulse width duration (PWD) 30cF only in atriallike cardiomyocytes (Honda et al. 2021). In addition, ventricular-like cardiomyocytes exhibit early depolarization after treatment with IKr inhibitors, which is consistent with the clinical phenotype of induced ventricular arrhythmias. Except for regular drug screening, patient-specific models have been built using atrial-like cardiomyocytes. Laksman et al. (2017) generated atrial-like cardiomyocytes from hESCs and atrial-like myocyte sheets showing uniform action potential propagation and rapid re-entrant rotor patterns, as seen in AF. Based on this model, anti-arrhythmic drugs were tested. Flecainide profoundly slowed upstroke velocity without affecting APD, leading to reduced conduction velocities (CVs), curvatures, and cycle lengths of rotors, consistent with increased rotor organization and expansion. On the opposite, consistent with the block of rapid delayed rectifier K+ currents (Ikr) and action potential prolongation in isolated atrial-like cardiomyocytes, dofetilide prolonged APD and reduced cycle lengths of rotors in cell sheets without affecting CV. In a later study, Hong et al. (Hong et al. 2021) generated patient-specific iPSCatrial cardiomyocytes (aCMs) from two kindred carrying SCN5A mutations (E428K and N470K) and isogenic controls using CRISPR-Cas9 gene editing. The established iPSC-aCM model exhibited AF phenotype, including spontaneous arrhythmogenic activity with beat-to-beat irregularity, prolonged APD, and triggered-like beats. The single-cell recording revealed enhanced late sodium currents (INa, L) in AF iPSC-aCMs, and inhibition of INaL using ranolazine, reduced the probability of arrhythmias and irregular beats in iPSC-aCMs. And a more recent

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study showed that azoramide, a novel anti-diabetic agent, can protect human iPSCaCMs from injury induced by high-frequency electrical stimulation by regulating endoplasmic reticulum (ER) stress, which may inhibit cell apoptosis and Ca2+ dyshomeostasis via the PERK/CHOP/CaMKII pathway (Miao et al. 2022). Besides, using enrichment analysis of drug-gene signatures and functional testing in human iPSC-aCMs, Jessica C. Lal et al. identified metformin as a top repurposed drug candidate for AF (Lal et al. 2022).

3.3

Generation of Nodal-Like Cardiomyocytes from iPSCs and Use in Cell Therapy

The sinoatrial node (SAN) pacemaker cells possess pivotal roles in the cardiac conduction system and control heart rate during the lifetime. Abnormality of SAN pacemaker cells may lead to the reduction of heart rate and insufficient blood circulation, which currently can be managed by the implantation of an artificial (electronic) pacemaker (Zhao et al. 2020). Although it is now possible to derive SAN-like cardiomyocytes from iPSCs, the current induction efficiency for nodallike cells in cardiac-specific differentiation protocol is very low, usually at a ratio of less than 7–8% (Blazeski et al. 2012). Generation of nodal-like pacemaker cells from iPSCs has been achieved by using transgene-dependent and -independent methods in the past few decades. The combination of RA and BMP signaling promotes the differentiation of sinoatrial nodelike pacemaker cells from human PSCs (Protze et al. 2017). The SAN lineage can be distinguished from the NKX2.5+ atrial/ventricular cardiomyocytes and the atrioventricular node (AVN) pacemakers since it originates from TBX18+ NKX2.5- mesoderm progenitors, and the SIRPA+ CD90- nodal-like cells can be derived from NKX2.5- mesoderm progenitors by blocking FGF signaling. Recent studies have demonstrated that canonical WNT signaling promotes the differentiation of cardiac mesoderm toward pacemaker cardiomyocytes in human and mouse PSCs (Liang et al. 2020; Ren et al. 2019). A few SAN-specific markers have been identified to purify and enrich SAN cardiomyocytes from mouse and human PSCs (Barbuti and Robinson 2015), such as CD166+ (Scavone et al.2013). Overexpression of pacemaker-specific transcription factors such as SHOX2 (Ionta et al. 2015), nodal cell inducer TBX3 (Jung et al. 2014), and TGFβ activated kinase (TAK1/MAP3K7) (Brown et al. 2017) can facilitate the generation of nodallike cardiomyocytes. A recent study also found that the knockout of the transcription factor E2A substantially increased the proportion of nodal-like cells in hESC-CMs (Li et al. 2021). And five different protocols to generate nodal-like pacemaker cells have been tested in a recent study and the most efficient protocol was selected (Darche et al. 2022). It is undeniable that the identification of nodal-like cells from mixed subtype cardiomyocytes is still a big challenge since the SAN consists of a heterogeneous population of cardiomyocytes, let alone an in vitro differentiation system. But it is still meaningful to purify the nodal-like cardiomyocytes since the biological SAN

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pacemaker cells represent a promising alternative to artificial pacemakers that have serious drawbacks, especially for newborns and children with heart block. Hopefully, the iPSC-derived nodal-like cardiomyocytes would be a great option for those who need pacemaker transplantation.

4

Conclusions

Drug-induced cardiotoxicity has been troubled for a long time by unreliable models and immature techniques, as well as some ethical concerns. The pharmaceutical industry needs a better solution to assess cardiotoxicity before a new drug is put into the market. The iPSC-CMs offer excellent opportunities for disease modeling and drug screening. Since their patient-specific nature, the iPSC-CMs can be used not only in regular toxicity evaluation but also in patient-specific drug tests, given that different genetic backgrounds may result in different adverse drug reactions. While the use of iPSC-CMs in regenerative medicine is a long-term goal, a growing number of studies have already represented promising results in the ability to use these cells in the field of drug discovery, development, and toxicity screening. However, the aim should not be to replace current methods of using animal-derived primary cells or immortalized cell lines but to supply a combination of new platforms. Except for the immaturity of iPSC-CMs, another limitation of these cells is that cardiomyocyte differentiation always results in a mixture of different subtypes, which could be problematic for specific drug screening, given the differential ion channel expression profile in each cardiomyocyte subtype. Precise generation of subtype-specific (atrial-, ventricular-, and nodal-like) cardiomyocytes will take great advantage to improve the applications of patient-specific iPSCs for disease modeling, cell therapy, and drug discovery. Atrial-like cardiomyocytes can be used for modeling atrial fibrillation. Purified ventricular-like cardiomyocytes have the potential to facilitate the restoration of cardiac function after myocardial infarction and abrogate possible ventricular arrhythmias in the graft after transplantation. Biological SAN pacemaker cells represent a promising alternative to artificial pacemakers with serious drawbacks, especially for newborns and children with heart block (Zhao et al. 2020). In conclusion, the iPSC-CM model will change and improve the way druginduced cardiotoxicity screening is performed. Although animal models will remain indispensable for years, iPSC-CM model-based strategies offer the opportunity to ultimately dispose of ethical concerns and species differences, thus increasing throughput and predictive value. There is no doubt that this iPSC-CM model faces great challenge and opportunity and needs to be improved in concerted effort.

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Cardiac Disease Modeling with Engineered Heart Tissue Lin Cai, Ruxiang Wang, and Donghui Zhang

Contents 1 Functional and Structural Basis of Beating Heart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Function of Heart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Cellular and Structural Composition of Heart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 History and Different Strategies for Building the Engineered Heart Tissue . . . . . . . . . . . . . . . 2.1 Key Questions in Engineered Heart Tissue Building . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Strategies for Constructing EHT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Cardiac Disease Modeling Using EHT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Cardiac Organoid Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Cardiac Thin-Film Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Microbundle Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The rhythmically beating heart is the foundation of life-sustaining blood flow. There are four chambers and many different types of cell in the heart, but the twisted myofibrillar structures formed by cardiomyocytes are particularly important for cardiac contraction and electrical impulse transmission properties. The ability to generate cardiomyocytes using human-induced pluripotent stem cells has essentially solved the cell supply shortage for in vitro simulation of cardiac tissue function; however, modeling heart at the tissue level needs mature myocardial structure, electrophysiology, and contractile characteristics. Here, the current research on human functionalized cardiac microtissue in modeling cardiac diseases is reviewed and the design criteria and practical applications of L. Cai · R. Wang · D. Zhang (✉) State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Science, Hubei University, Wuhan, Hubei, China e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_681

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different human engineered heart tissues, including cardiac organoids, cardiac thin films, and cardiac microbundles are analyzed. Graphical Abstract

Table summarizing the ability of several in vitro myocardial models to assess heart structure and function for cardiac disease modeling. Keywords

Engineered heart tissue · Cardiomyocytes · Disease modeling

1

Functional and Structural Basis of Beating Heart

1.1

Function of Heart

Day and night, the human heart circulates blood throughout the body. This invariably calls for highly specialized, effective, and consistent functional output. Such functional properties will inevitably bring difficulties to the construction of physiological and pathological models of the heart in vitro. The outstanding self-assembly and spontaneous augmentation of heart function, however, the heart is one of the earliest organs to emerge during embryonic development (Bulatovic et al. 2016; Keller et al. 2007), offers new hope for rebuilding this powerful artificial pump in a Petri dish. The four chambers of the heart contract sequentially throughout each contraction cycle, working together to produce the optimal stroke volume. Surprisingly, the heart’s chamber structure is formed by the muscle bundles twisting in a certain way

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rather than by stacking growth. As a result, the size of the heart increases 30-fold throughout growth from birth to adult size, but the number of cardiomyocytes does not increase as much (Guo and Pu 2020). Therefore, the increased heart volume, in this case, is caused by both an increase in the volume of individual cardiomyocytes (Li et al. 1996; Mollova et al. 2013), and an improvement in the way in which the heart muscle bundles are twisted at the tissue level. Since the core function of the heart is to pump the blood for the entire body, the motive force of the pumping, namely myocardial tissue contractility, is the key action of the heart organ. The characteristics of myocardial contractility are directly related to various diseases. For instance, reduced myocardial contractility, which can occur for many reasons, is the main phenotype of heart failure (Blair et al. 2020; Martin et al. 2021; Papp et al. 2014; Solaro and Tardiff 2013). Echocardiography and cardiac computed tomography are standard clinical examinations for identifying systolic heart function. However, contractility alone is insufficient to keep the heart organ functioning properly. The contractile force must be rhythm-controlled, guided by electrical conduction. Numerous clinical tests, such as standard electrocardiograms and treadmill exercise tests, are connected to this functional index. Therefore, from the perspective of the developmental process and cardiac function, the cardiac muscle bundle of the myocardial tissue is the heart’s most basic structural and functional unit.

1.2

Cellular and Structural Composition of Heart

In the cardiac bundle, a mixed population of cells, such as cardiomyocytes, endothelial cells, fibroblasts, and smooth muscle cells, elongate in the same direction and are bound with polarity-maintaining cell connections. In the cardiac tissue, myofibrilrich cardiomyocytes, composed of myofilaments arranged in sarcomeres, constitute only 30–40% of the cell population but account for 75% of the volume (Vliegen et al. 1991). Fibroblasts are essential populations of non-cardiomyocytes and are found throughout the heart tissue, surrounding cardiomyocytes, and connecting the interstitium of cardiomyocytes. Endothelial and smooth muscle cells form a rich network of heart vasculars that regulate blood exchange with surrounding tissues. Collagen, fibronectin, and other extracellular matrix (ECM) components provide a microenvironment for cardiac tissue cells and play an essential role in maintaining tissue structure, function, and electrochemical signal transduction. Various groups of cells in the cardiac tissue are distributed in an appropriate matrix environment to form a living heart. Of all cell types, well-aligned cardiomyocytes contribute the most to maintaining muscular contractility in the heart. At the same time, intercalated disk connections between cardiomyocytes provide the structural foundation of a heartbeat. Branched cardiomyocytes are connected by intercalated disks with the adjacent branches in the cardiac bundle. At the Z-line level, where the disk’s transverse portion is located, intermediate junctions and desmosomes strengthen the link between the myocardial fibers. In the vertical part of the disk, gap junctions let cells communicate chemical

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information and transmit electrical impulses (Severs 1985). When a single cardiomyocyte is stimulated, excitement is initially produced at the cell membrane, and transverse tubules (T-tubules) convey impulses from the membrane to the interior of the cell. The myofilaments then move toward each other through excitation–contraction coupling, causing the entire cell to contract. Intercalated disks enable the connection of separate cardiomyocytes into a single unit that quickly transmits bioelectrical and chemical impulses. The beating of a single cell, therefore, soon spreads throughout the tissue, forming a heartbeat.

2

History and Different Strategies for Building the Engineered Heart Tissue

2.1

Key Questions in Engineered Heart Tissue Building

The previous chapter described how using human-induced pluripotent stem cells (hiPSCs), it is possible to generate physiologically functional human cardiomyocytes with the genotype of the stem cell donor. Also, using gene editing, cardiomyocytes with designed genotypes can be created in vitro. Although hiPSCderived cardiomyocytes may be utilized to represent a diseased phenotype at the cellular level, and can be used to study the heart’s electrophysiology, and metabolic defense mechanism, disease modeling using cardiomyocytes alone is not sufficient to provide a global view of cardiomyopathy. How to develop more mature myocardial tissue in vitro has been the main focus of research into the utilization of cardiac cell lineages to create engineered heart tissue (EHT). Maturity is defined by: tissue structure, physiological function, and response to load or stimulus. In terms of tissue structure, researchers’ expectations grew from “cardiomyocytes may survive” to “full cell junction development” and finally to “adult cardiomyocytes with T-tube structure.” Various strategies have been developed to obtain mature human cardiomyocytes, including (1) biochemical activation of maturation-promoting signals with small molecules and growth factors, (2) physical maturation stimulation through electrical impulse stimuli and contractile exercise training, and (3) construction of EHT using a natural cell matrix. As a result, it is now possible to obtain engineered myocardial tissue in vitro that closely resembles the cardiac bundle in vivo.

2.2

Strategies for Constructing EHT

Contractility and electrical conductivity are two core functions of the myocardium. The former determines the heart’s pumping capability, whereas the latter is directly tied to the heart’s electrical conduction. As a result, when creating artificial cardiac tissue in vitro, a principal objective is to develop myocardial tissue with contractile force and electrical conduction velocity comparable to adult myocardium. The attempt to generate cardiac tissue began in 2001, when cardiomyocytes derived

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from pluripotent stem cells (PSCs) were first produced in vitro (Kehat et al. 2001). However, progress in this direction was relatively slow in the following years. The development of human cardiac tissue in vitro has become a “study that lacks research data,” owing to the instability of the differentiation system’s effectiveness and the complexity of the differentiation process. At that time, some research groups pursuing microtissue function turned to using neonatal rat myocardium or myocardium derived from mouse PSCs to explore the methodology of tissue construction. The supply of cardiomyocytes was, for the most part, resolved in 2013 after research into cardiomyocyte differentiation using high-efficiency human PSCs (hPSCs) (Lian et al. 2013). Since then, several original works have been published, demonstrating considerable advances and reaching an unparalleled level in the development of in vitro functionalized cardiac tissue. In Table 1, functional indicators for a number of studies of hPSC-derived cardiomyocytes and cardiac microtissue construction methods published between 2009 and 2022 are compiled and evaluated. Surprisingly, the methods of cardiomyocyte differentiation and microtissue construction reported in the different publications are similar. When constructing heart tissue systems constructed in vitro, the general agreement is for cardiomyocyte alignment in the same orientation and an adequate supply of nutrients and oxygen, despite the varying accessibility of two gel systems, using collagen and fibrinogen gels. It is reassuring to see, concerning the functional tests, that some groups obtained contractility and conductivity values similar to those of adult myocardium. In addition to the absolute electrical conductivity and contractility values, cardiac rhythm is a crucial component in preserving normal heart function. Atrial or ventricular arrhythmias, as well as sudden death, are all linked to abnormal rhythms.

3

Cardiac Disease Modeling Using EHT

The EHT structure and the selection of detection parameters are critical in effectively modeling a specific cardiovascular disease. Here, three typical tissue engineering forms used in heart disease modeling are discussed, namely the cardiac organoid, thin film, and microbundle.

3.1

Cardiac Organoid Model

An organoid is a small cluster of cells, grown in a three-dimensional (3D) environment in vitro, that can self-organize and differentiate into functional cell types to recapitulate the structure and function of an organ in vivo. Since the first gut organoid model was constructed in 2009 (Sato et al. 2009), research of organoids of several different organs, such as the brain and kidney, has advanced significantly. Although research of cardiac organoids, useful in the study of cardiovascular diseases, lags behind that of other organs, it has increased dramatically in the last 2 years. Cardiac organoids may be created from primary cells, hPSCs, and functional

Rocking culture, early-stage ramped field stimulation from 2 to 6 Hz, isotonic contraction

–

Protocol

Structure 1,500

6 × 2 mm fibrinogen gel

–

2,565 Ref. (Tracy and Sander 2011)

28

–

Cell morphology Size, μm2

12

–

Differentiation prior to tissue seeding (days) Time in 3D culture (days) Materials

Cardiac tissue

iPSC-CMs + human dermal fibroblasts, 3:1

Native human LV

Type

Cells

hEHT RonaldsonBouchard et al. (2018)

Adult LV

Model Study

–

Rocking culture

7 × 7 mm fibrinogen/ matrigel

7–21

16

hiPSC-CMs or hESC-CM (~80% purity)

Cardiopatch Shadrin et al. (2017), Zhang et al. (2013)

–

2 × 2 mm lightpatterned gelatin methacrylate Rocking culture

7

hiPSC-CM, iPSC-SMC, iPSC-EC (2:1:1) 19

Cardiopatch Gao et al. (2017)

3,000, male 2,000, female

T3 + DEX

Single cells on matrigel mattress

5

16–30

hiPSCCM

Matrigel mattress Parikh et al. (2017)

4–8× lower membrane capacitance than adult CMs

EB differentiation

100 μL volume fibrinogen/ matrigel gel

29-Oct

10–14

Organoid Lemoine et al. (2017), Mannhardt et al. (2016) hiPSC-CM (87% TNT+)

Table 1 Characteristics of selected human engineered heart tissue models. Enhanced from Nature review cardiology (Zhang and Pu 2018)

795

2 weeks static stretch + electrical stimulation

Collagen type I gel, 20 × 3 mm

14

14–21

hiPSC-CM (70% TNT+)

Cardiac bundle Ruan et al. (2016)

240 L. Cai et al.

Other

Mitochondria

Sarcomeres

Sarcomere length (μm) Ultrastructure

Intercalated disks

Transverse tubules

Shape

Intercalated disks, desmosomes, Ttubules

Aligned to sarcomeres; 30% cell area

Aligned to sarcomeres; ~40% cell area Ref. (Vega et al. 2015) Intercalated disks, desmosomes, Ttubules

2.2

2.2 Ref. (Lundy et al. 2013)

Orderly register of sarcomeres; A, I bands and M, Z lines present.

Membrane, Bin1, Cav1.2, RYR2 staining aligned perpendicular to CM long axis CX43 localized at CM poles

Membrane, Bin1, Cav1.2, Cav3, and Ryr2 staining aligned perpendicular to CM long axis Cx43, Nav1.5, Ncadherin localized at CM poles

Orderly register of sarcomeres; A, I bands and M, Z lines present.

Rod-like

Rod

Intercalated disks, desmosomes

Orderly register of sarcomeres; A, I bands and Z lines. No Mlines –

N-cadherin localized at CM poles. Cx43 less anisotropic 2.09

No

Rod-like

–

–

–

–

–

–

–

NA

–

–

Present but sparse and poorly organized

Rod-like

No

Rod-like

Primitive intercalated disks; desmosomes

–

Regular Z lines, and inconsistent Iand A-band. No M-lines

Nav1.5 localized at CM poles. Cx43 not anisotropic 1.6 ± 0.1

Perinuclear, irregular Caveolin-3 staining

Rod-like

(continued)

Junctions, desmosomes, myofibrils

–

Adherens junctions

Elongated spindle No

Cardiac Disease Modeling with Engineered Heart Tissue 241

Model Physiology

Contractility – maximum specific stress (mN/mm2)

Maximum INa upstroke velocity (V/s) Action potential duration (APD; ms) Conduction Vel (cm/s) Physiological responses Force frequency relationship Post pause potentiation Ca2+ release from intracellular Ca stores

Membrane potential (mV)

Table 1 (continued)

–

–

60% reduced Ca2+ amplitude by SR inhibition

~3

~70%

25–44 (Hasenfuss et al. 1991; Mulieri et al. 1992)

–

–

–

Present

Present

22.4

–

–

Flat to sl. negative

Positive

Positive

50% reduced Ca2+ amplitude by SR inhibition –

–

–

18.8

1.3

–

–

–

–

Flat

2.76 ± 0.61

–

–

Cardiac bundle –

Present

Flat

–

–

–

28.5 ± 1.0; max 40.1

219

–

–

Organoid -73.5

Matrigel mattress –

Cardiopatch –

46 Ref. (Durrer et al. 1970)

38.1

Cardiopatch -70.9

APD80, 270

APD90, 500

~23

hEHT -70.0

APD80, 450

APD80: subepi. 383; subendo. 494; Ref. (Glukhov et al. 2010)

Adult LV Subepi. -79.5; subendo. -78.8; Ref. (Nabauer et al. 1996) 278 Ref. (Koncz et al. 2011)

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Structure

Cardiac tissue

Shape

Cell morphology Size, μm2

Protocol

~50% rod-like cells

917

EB differentiation; seed 7d, then ramped field stimulation from 1 to 6 Hz

Collagen type I gel on inelastic silk core. About 600 μm wide.

Rod-like

–

Perfusion (0.2 mL/ min) and electrical stimulation (400 V/ m)

Porous collagenand elastin-based scaffolds of 1-mm thickness 5 million cells

21

14

Differentiation prior to tissue seeding (days) Time in 3D culture (days) Materials

hESC-CM or hiPSC-CM (48%) plus non-myocytes including 34% fibroblasts 20

Cells

Type

Organoid Valls-Margarit et al. (2019) iPSC-CMs 71.6% ± 5.3% cTnI / MHC + human dermal fibroblasts, 7:1 20

Biowire Nunes et al. (2013)

Model Study

Rod-like

–

–

5,000 cells 1,100 rpm 10 min

21

Organoid Giacomelli et al. (2020) hiPSC-CMs (>80% pure) + hiPSCECs + hiPSC-CFs, 14:3:3 14–21

Early (disk): 5.03 × 107 later (ring-shaped) Rod-like

Collagen I+ basement membrane matrix+other essential components 5 × 106 hiPSCCM/EHT Stretch once a day 0.32 mm/ day

25

13

hiPSC-CM (69 ± 1%)

Cardiac bundle Lu et al. (2021)

Rod-like

–

(continued)

Rod-like

7,500–~150 μm in width

Maturation medium (glucosefree, fatty-acidenriched)

3 μL per device, corresponding to 2 × 104 cells 18 × 18 mm collagen (2 mg/ mL) + 20% matrigel, 35 × 106 cells/mL, 3 μL per device)

Microfluidic platform

14

15

Thin film Huebsch et al. (2022) hiPSCCM + isogenic hiPSC-SC, 4:1

14

17

Cardiopatch Veldhuizen et al. (2020) hiPSC-CMs or hESC-CM (85.5 ± 5.3% pure) + hCF, 4:1

Cardiac Disease Modeling with Engineered Heart Tissue 243

Physiology

Model

Membrane potential (mV) Maximum INa upstroke velocity (V/s) Action potential duration (APD; ms) Conduction Vel (cm/s) Physiological responses

Other

Mitochondria

Transverse tubules Intercalated disks Sarcomere length (μm) Ultrastructure Sarcomeres

Table 1 (continued)

Orderly register of sarcomeres; Hzone, I bands and M, Z lines present. Closer to sarcomeres Intercalated disks, desmosomes, Ttubules ~-78 ~140

APD90~230

–

0.83 ± 0.38

Orderly register of sarcomeres; A, I bands and M, Z lines present. –

– – – –

–

Regular Z lines. I bands and H zones present. No Mlines. Closer to sarcomeres Desmosomes, nascent intercalated disks ~-80

~125

APD90~120

~15

Intercalated disks

Cx43 localized at CM poles 1.9

Cell junctions

–

Organoid No

Organoid No

Biowire No

– –

– –

–

–

13.47 ± 3.2

–

–

–

–

–

–

-72.4 ± 3.4

Cx43 localized at CM poles –

Cardiopatch No

Cx43 localized at CM poles 2.19 ± 0.1

Cardiac bundle No

–

APD80 300

–

–

–

–

–

–

–

Thin film No

244 L. Cai et al.

Force frequency relationship Post pause potentiation Ca2+ release from intracellular Ca stores Contractility – maximum specific stress (mN/mm2)

– – – –

–

–

–

–

–

–

Present

Positive

11.28

–

–

Positive

–

–

–

–

~2.2

–

–

–

Cardiac Disease Modeling with Engineered Heart Tissue 245

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hPSC-derived cells, as irregular spheres with compartments. There are now two main approaches to building a cardiac organoid. One method is to generate embryoid bodies from human or mouse stem cells using low-speed centrifugation, hanging drops, or the inclusion of Matrigel (Corning, Glendale, Arizona, USA), and then induce cardiomyocyte differentiation through two-phase Wnt signaling regulation. Lewis-Israeli et al. (2021) created an organoid model of pregestational diabetes using hPSCs with an environment containing high levels of both glucose and insulin, revealing structural and developmental organization and lipid metabolic damage. Drakhlis et al. (2021) and Feng et al. (2022) created cardiac organoids by employing NKX2.5 knockdown human embryonic stem cell and hiPSC cell lines, respectively, to mimic phenotypes of congenital heart abnormality. In the latter method, differentiated cardiomyocytes were combined with hydrogels or other extracellular matrix components in appropriate ratios to construct cardiac organoids with specified architectures. Filippo Buono et al. (2020) generated cardiomyocytes using a patient-derived MYH7-mutant induced PSC, merging human cardiac microvascular endothelial cells and human cardiac fibroblasts to create cardiac organoids mimicking hypertrophic cardiomyopathy, and revealing arrhythmia and defective Ca2+ handling capability. Richards et al. (2020) developed a norepinephrinestimulated cardiac organoid model (50% hiPSC cardiomyocytes, 50% non-myocytes) to investigate transcriptome, morphological, and functional alterations following an acute myocardial infarction. Daly et al. (2021) generated fibrotic cardiac organoids with cardiomyocytes and fibroblasts in the ratio of 1:4, demonstrating a decline in sarcomere organization, contraction, and calcium activity. In addition to standard physical indicators, including cell composition, distribution, structural, and electrophysiological factors, the metabolic performance of heart organoids is progressively becoming a subject of study. Furthermore, cardiac organoids may be rapidly homogenized and mass-produced using 3D printing technology.

3.2

Cardiac Thin-Film Model

Another type of myocardial tissue created in a laboratory is formed as a thin film of cardiomyocytes seeded over elastic grooves to resemble the aligned lamellar structure of myocardial tissue found in vivo. First constructed in 1991, the cardiac thin film allowed researchers to examine the association between impulse and cardiomyocyte cytoarchitecture by exposing ventricular myocytes to light-engraved patterns (Rohr et al. 1991). In addition, numerous modifications have been made to patterned cardiomyocytes to evaluate their electrical and contractile characteristics (Alford et al. 2010). When producing flexible polymer film substrates, polydimethylsiloxane (PDMS) is frequently employed, and the spin coating technique can be utilized to produce substrate materials with regularly spaced ridges. With the aid of sensors, adding other materials (such as titanium) to PDMS films enables real-time monitoring of shrinkage forces (Lind et al. 2017). It is possible to generate cardiac films with micro-physiological visualization by combining colored

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hydrogels with biohybrid living structures and microfluidics, allowing for a more intuitive perception of changes in contractile properties, owing to synchronous structural color changes during cardiac film contraction (Fu et al. 2018; Wang et al. 2022). When modeling thin films for cardiac diseases, PDMS sheets with conductive elements are increasingly frequently used as substrate materials. By applying cyclic stretching to engineered anisotropic cardiac tissues cultured from primary neonatal rat ventricular myocytes, McCain et al. (2013) created a model of failing myocardium on a chip in 2013. This model accurately replicated the structure, gene expression, calcium handling capacity, and contractile properties of failing myocardium in vivo. Thin films of hiPSCs and cardiomyocytes produced by patients with Barth syndrome (BTHS) were used to imitate BTHS. This model duplicated aberrant sarcomere alignment and reduced contractile force, whereas mutation-corrected thin film created from hiPSCs and cardiomyocytes demonstrated functional recovery (Wang et al. 2014). Using hiPSCs and cardiomyocytes generated from a patient with a RYR2-mutation, Park and Zhang created a cardiac thin-film model of catecholaminergic polymorphic ventricular tachycardia (CPVT). The reentrant rhythm in CPVT tissues is readily apparent in this model when induced by fast pacing and catecholamines, thus highlighting the disease’s defining features (Park et al. 2019). Additionally, managing oxygen and nutritional conditions on a cardiac thin film can imitate ischemia–reperfusion injury (Yadid et al. 2020).

3.3

Microbundle Model

To accurately quantify tissue contractility and mechanical extension, cardiac microbundles – which can be formed as either cables or rings – are used. The most popular technique for creating cardiac micelles is the hydrogel technique, which involves mixing collagen I and Matrigel or fibrinogen with cardiac cells. Since impaired cardiac function is a common symptom of most cardiomyopathies, several microbundles can be constructed to test contractility. For example, the reduced contractile force of a cylindrical microbundle formed from gene-altered hiPSCs and cardiomyocytes can be determined by video recording the column displacement when the microbundle is connected to two flexible columns (Hansen et al. 2010; Hinson et al. 2015). When attached to a flexible PDMS column with one end free, the contractile force of a DSP-mutated microbundle formed from hiPSCs and cardiomyocytes was measured by the contraction-driven movement of PDMS (Bliley et al. 2021). Moreover, wire bending might be used to assess contractile force by suspending the microbundle between two parallel wires. This structure has been used to detect Ca2+ transients and active forces, constantly and noninvasively, in a disease setting (Zhao et al. 2019). In addition, force sensors have been used to directly measure the contraction force of cardiac microbundles attached to the fabric framework (Gu et al. 2022; Li et al. 2020, 2022; Xu et al. 2022). Another construction method is based on with 3D scaffolds constructed from electrospun nanofiber. Synthetic polymers used in fiber scaffolds can structurally

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mimic the orientation of the ECM in the myocardium, compared with the hydrogel method. However, electrospinning techniques result in nanoscale and uncontrollable porosity; this prevents cell penetration and is unfavorable for forming 3D tissue structures (Orlova et al. 2011). Another fiber scaffold has been cured by utilizing two-photon initiated polymerization, a laser writing process based on two-photon absorption, to produce a filamentous matrix with a spatial precision of nearly 100 nm. The differentiated cardiomyocytes were immediately seeded into this 3D fiber structure on dissociation, and beating fibers were created a few days later (Ma et al. 2014, 2018). This method allows precise spacing between fibers and controls the mechanical environment in which the cells live. Currently, cardiac microbundles are the structures most widely used to establish models of cardiac diseases for the study of hypertrophic cardiomyopathy, right ventricular arrhythmias, dilated heart disease, ischemic heart disease, and so on. A detailed summary is given in Table 2.

4

Concluding Remarks

The heart, a highly auto-assembling organ, is crucial for preserving blood flow throughout the body. However, research on cardiac diseases has been hampered by the lack of mature in vitro human cardiac bundle models with morphological, electrophysiological, and contractile features. Different forms of human EHT, including cardiac organoids, thin films, and microbundles, are rapidly becoming feasible, with the establishment of hiPSC-derived cardiomyocyte differentiation protocols and the development of engineered heart microtissue construction methods. In recent years, the development of human EHT has been effective in mimicking various cardiovascular disorders when evaluating electrophysiological and contractile parameters. Future advances in the generation of high-purity mature human cardiomyocytes, as well as in the structural and functional assessment of human EHT that more closely mimics human heart function, may create new opportunities for disease modeling, drug discovery, and, ultimately, the treatment of cardiovascular diseases.

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Table 2 EHTs for cardiac diseases modeling Types Micro bundle

Disease models DCM

Pathological factors TTNtv mutation (Hinson et al. 2015)

MYBPC3 mutation (Ma et al. 2018) HCM (Cashman et al. 2016)

BRAF mutation

Heart failure

1–10 nmol/ LNE (Tiburcy et al. 2017) Ang II (Wang et al. 2021)

HCM (Mosqueira et al. 2018)

MYH7 mutation

Cardiac fibrosis (Wang et al. 2019)

–

Left ventricular hypertrophy (LVH) (Zhao et al. 2019)

–

Arrhythmia (Goldfracht et al. 2020) ACM (Bliley et al. 2021)

–

DSP mutation

Building methods iPSC-CM (patient/ gene editing), mixed with 7% hMSCs, 1.1 × 106 cells; collagenI, human fibrinogen hiPSC-CM (MYBPC3-KO); filamentous matrices (TPP) iPSC-CM (patient/ gene editing), 1: 8:1 = cells:collagen: Matrigel; 10 million cells/ml PSC-CM, 1.5 million cells suspended in 500 μl collagenI/ Matrigel iPSC-CM:cFB = 3:1, 5.5 × 107 cells/ml; fibrin/Matrigel PSC-CM (gene editing), 1 × 106 cells; 5 mg/ml fibrinogen and 3 U thrombin Normal (hiPSC-CM: CF = 3:1), fibrotic (hiPSC-CM:CF = 1: 3), 0.1 × 106 cells; fibrinogen: Matrigel = 3:1, thrombin iPSC-CM, ventricular cardiac cells: fibroblasts = 10:1.5; rat tail collagen + 15% Matrigel, final collagen = 3.0 mg/ mL. hESC-CM, 2 million cells+ bovine collagen +2× DMEM iPSC-CM (patient), 90% cardiomyocytes +10% cardiac fibroblasts; collagen I (1 mg/ml), Matrigel (1.7 mg/ml)

Parameters assessed in tissue Sarcomere alignment, contractile force, transcriptome

Contractile force, beating rate, sarcomere alignment, Ca2+ signaling Contractile force, electrical properties

Contractile force, size, cell number

Contractile force, Ca2+ transient Contractile force, transcriptome

Collagen area/ structure, contractile force, electrophysiology, Ca2+ transient

Contractile force, transcriptome, cell viability/ cardiomyocyte content

Optical mapping

Contractile force, length, desmoplakin staining/TEM

(continued)

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Table 2 (continued) Types

Thin film

Organoid

Disease models LQT3 (Ma et al. 2014)

Pathological factors –

Heart failure (McCain et al. 2013)

–

Barth syndrome (Wang et al. 2014) CPVT (Park et al. 2019)

Tafazzin (TAZ) mutation

iPSC-CM (patient) 1 × 105 cells/cm2; spaced 2.5 mm apart

RYR2 mutation

IRI (Yadid et al. 2020)

–

HCM (Filippo Buono et al. 2020) CHD

MYH7 mutation

iPSC-CM (patient); 1 mg/ml collagen, 0.1 mg/mg fibronectin hCM; 5 μm-tall and 4 μm-wide, spaced by 30 μm grooves hiPSC-CM:HCMEC: HCF = 3:5:2; hanging drop

Building methods iPSC-CM (patient); 3D filamentous matrices (TPIP), 50 μg/mL fibronectin, 1 mg/mL collagenase II NRVM; “brick wall” pattern, fibronectin

NKX2.5 knock down iPSC (Drakhlis et al. 2021)

hESC NKX2.5-eGFP (NKX2.5-KO), 5,000 cells; Matrigel

NKX2.5 KO iPSC (Feng et al. 2022)

iPSC (NKX2.5 -KO), 1.5 × 106 cells

Cardiac fibrosis (Daly et al. 2021)

–

PGD (LewisIsraeli et al. 2021) Myocardial infarction (Richards et al. 2020)

11.1 mM glucose, 1.14 nM insulin

Normal:hiPSC-CM: CF = 4:1, fibrotic: hiPSC-CM:CF = 1:4, 5,000 cells; 3D bioprinting, hydrogel 10,000 hPSC cells

10% O2 + 1 μM norepinephrine (NE)

50% hiPSCCMs + 50% non-myocyte (FBs: HUVECs: hADSCs = 4:2:1), ~150,000 cells

Parameters assessed in tissue Fiber diameter and spacing, contractile force

Sarcomere alignment, contractile force, Ca2+ transient, transcriptome Sarcomere alignment, contractile force

Ca2+ signaling, contractile force Contractile force, protein content, cell death Cell distributions, structures, beating frequency/time, Ca2+ signaling Total area, cardiomyocyte area/ content, compactness of myocardial layer, sarcomeres Beating percentage/ rate, Ca2+ transient, sarcomere alignment, transcriptome Spheroid contraction, Ca2+ signaling

Morphology, area, structure, seahorse, TEM Transcriptome, seahorse, L-lactate levels, elastic modulus, Ca2+ transient, contraction amplitude

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iPSC-Derived Corneal Endothelial Cells Qingjun Zhou, Zongyi Li, and Haoyun Duan

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Corneal Endothelium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Development of Corneal Endothelium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Corneal Endothelial Physiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Treatment of Corneal Endothelial Decompensation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Generation of iPSC-Derived Corneal Endothelial Cells (CECs) . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Strategies of iPSC-Derived CECs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Molecular Profiling and Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 iPSC-Based Models of Corneal Endothelial Dysfunction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Applications of iPSC-Derived CECs for Corneal Endothelial Dysfunction . . . . . . . . . . . . . . . 5.1 Tissue Engineering Corneal Endothelium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Therapeutic Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Therapeutic Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Applications and Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The corneal endothelium is the innermost monolayer of the cornea that maintains corneal transparency and thickness. However, adult human corneal endothelial cells (CECs) possess limited proliferative capacity, and injuries can only be repaired by migration and enlargement of resident cells. When corneal endothelial cell density is lower than the critical level (400–500 cells/mm2) due to disease or trauma, corneal endothelial dysfunction will occur and lead to corneal edema. Corneal transplantation remains the most effective clinical treatment therapy but Q. Zhou (✉) · Z. Li · H. Duan State Key Laboratory Cultivation Base, Shandong Provincial Key Laboratory of Ophthalmology, Eye Institute of Shandong First Medical University, Qingdao, China # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_644

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is limited by the global shortage of healthy corneal donors. Recently, researchers have developed several alternative strategies for the treatment of corneal endothelial disease, including the transplantation of cultured human CECs and artificial corneal endothelial replacement. Early-stage results show that these strategies can effectively resolve corneal edema and restore corneal clarity and thickness, but the long-term efficacy and safety remain to be further validated. Induced pluripotent stem cells (iPSCs) represent an ideal cell source for the treatment and drug discovery of corneal endothelial diseases, which can avoid the ethicalrelated and immune-related problems of human embryonic stem cells (hESCs). At present, many approaches have been developed to induce the differentiation of corneal endothelial-like cells from human induced pluripotent stem cells (hiPSCs). Their safety and efficacy for the treatment of corneal endothelial dysfunction have been confirmed in rabbit and nonhuman primate animal models. Therefore, the iPSC-derived corneal endothelial cell model may provide a novel effective platform for basic and clinical research of disease modeling, drug screening, mechanistic investigation, and toxicology testing. Keywords

Cell therapy · Corneal endothelium · Differentiation · Efficiency · iPSCs · Safety

1

Introduction

The cornea is the outermost fibrous membrane of the eyeball. It is an important refractive element and is the only pathway for external light to enter the inner retina of the eye. The cornea can be divided into five layers: the epithelial layer, Bowman’s membrane, the stromal layer, Descemet membrane, and the endothelial layer (Bi 1965; Ni et al. 1982). Corneal endothelial cells (CECs) are the monolayer hexagonal cells present on the posterior surface of the cornea, which mainly rely on barrier and pump functions to maintain normal corneal thickness and transparency (Bonanno 2012). The regenerative capacity of adult CECs is very limited. When the corneal endothelial density falls below 400–500 cells/mm2 due to disease or trauma, the decompensation of corneal endothelial function begins to occur, which results in corneal edema and opacity, and, eventually, blindness (Waring et al. 1982; Joyce 2003; Tan et al. 2012). In fact, according to the 2016 Eye Banking Statistical Report, corneal endothelial transplants accounted for 38.8% of the total corneal transplants performed in the USA in 2016 (Eye Bank Association of America 2017). Penetrating keratoplasty (PK) and the two variants of endothelial keratoplasty (EK), namely Descemet’s stripping automated endothelial keratoplasty (DSAEK) and Descemet’s membrane endothelial keratoplasty (DMEK), are the main clinical treatments for corneal endothelial decompensation. Compared to conventional PK, DSAEK and DMEK enable a less invasive and more efficient treatment of corneal endothelial diseases (White and Sabater 2019). However, all these keratoplasty

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technologies require high-quality corneal donors. Due to the lack of corneal donors worldwide, regenerative treatment of corneal endothelium-related ocular diseases has attracted considerable attention, and, in this context, determining an adequate and functional source of corneal endothelial seed cells represents the biggest problem. With the development of in vitro expansion technology for human CECs and stem cell differentiation technology, some breakthroughs have been made with regard to finding an appropriate source for corneal endothelial seed cells. Professor Kinoshita and his team from Kyoto Prefectura University of Medicine found that Rho kinase inhibitor Y-27632 could promote the rapid adhesion of transplanted CECs (Okumura et al. 2012, 2013). Using in vitro cell expansion technology, they performed a first-in-human clinical trial that involved the injection of cultured human CECs combined with Y-27632 as a therapy for the treatment of corneal endothelial decompensation in 2013, which also required corneal donors (Kinoshita et al. 2018). Therefore, numerous research groups have been eager to develop methods for producing CECs from diverse stem cell sources, such as human embryonic stem cells (hESCs), human induced pluripotent stem cells (hiPSCs), and adult stem cells (McCabe et al. 2016; Alio del Barrio et al. 2015; Ali et al. 2018a, b, 2021; Wagoner et al. 2018; Li et al. 2022). Both hESCs and hiPSCs with potential of unlimited expansion and pluripotent differentiation have been used to establish the clinical-grade cell lines. In contrast to hESCs, hiPSCs can be constructed using autologous cells to avoid the ethical and immune rejection. Further, iPSCs derived from the patients’ autologous cells could simulate the pathogenesis and screen intervention drugs (Tsujimoto and Osafune 2021; Ohnuki and Takahashi 2015). Therefore, hiPSCs have great potential for the treatment of corneal endothelial decompensation.

2

Corneal Endothelium

2.1

Development of Corneal Endothelium

The cornea develops from different embryonic origins, involving complex regulation mechanisms. The development of the cornea begins with the surface ectoderm that overlies the lens vesicle (Kidson et al. 1999; Beebe and Coats 2000). The corneal epithelium develops from the surface epidermal ectoderm, while the corneal endothelium and stroma develop from the periocular neural crest cells. Further, the formation of the corneal endothelium occurs alongside that of the stroma. During the 5–6 weeks of human gestation, the surface ectoderm is completely separated from the lens (Fig. 1). Inductive interactions between the lens vesicle and the ectoderm drive the migration of neural-crest-derived mesenchymal cells into the space between them. These mesenchymal cells then form the corneal endothelium and stroma, and the innermost layer becomes the corneal endothelium. Next, the endothelial cells secrete collagen to form the basement membrane, also known as

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Fig. 1 Development of vertebrate corneal endothelium. The lens pit and optic cup are formed when the lens placode and optic vesicle invaginate at E10.5. The periocular mesenchyme cells, derived from the cranial neural crest cells, migrate at E11.5 into the space between the newly formed presumptive corneal epithelium and lens vesicle. Between E13.5 and 14.5, while lens fibers close off the lumen of the lens vesicle, the migrated mesenchymal cells flatten, rising to the flattened endothelial layer (the presumptive corneal endothelium) by E14.5–15.5. The intermediate mesenchymal cells constitute the presumptive corneal stroma (Created with BioRender.com)

Descemet membrane, which separates the endothelium from the stroma (Murphy et al. 1984). The periocular neural crest cell migration begins with the epithelial–mesenchymal transition (EMT) (Saika et al. 2001; Zacharias and Gage 2010); however, corneal endothelial maturation indicates the formation of typical endothelial hexagonal morphology, which suggests mesenchymal–endothelial transition (MET). Previous studies have reported the diverse transcription factors involved in these processes, such as Pax6, Sox2, Sox1, Sox3, Foxc1, Foxc2, TGF-β2, Pitx2, Pitx3, Klf4, and AP2α, which mostly regulate the endothelial and stromal development (Bennett et al. 1999; Gage and Zacharias 2009; Ito and Walter 2014). Mutations in Foxc1 or TGF-β2 are associated with a lack of corneal endothelium and disruption of stromal development in mice models (Silla et al. 2014).

2.2

Corneal Endothelial Physiology

The corneal endothelium is the innermost layer of the human cornea and serves the important function of maintaining corneal transparency by keeping the cornea in a relatively dehydrated state. There are several theories regarding the homeostasis of corneal hydration and transparency, but the pump-leak hypothesis has stood the test of time. The cornea stroma generates a suction pressure due to the inherent hydration of the mucin glycans of collagen fibers. The endothelial cells present an incomplete tight junction zone between adjacent cells, which allows passive diffuser fluid from the anterior chamber into the stroma and provides nutrients to the corneal stroma.

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The driving force behind the uptake of fluid into the stroma is balanced by the transport of solute into the aqueous humor, thereby creating an osmotic deficit within the stroma. This causes the passive driving force of water to maintain a state of equilibrium and corneal clarity (Watsky et al. 1989; Van den Bogerd et al. 2018). In adult humans, CECs are arrested in the G1 phase and have limited regenerative capacity; in addition, adult endothelial cells are lost at a rate of 0.6% per year (Bourne et al. 1997). The cells can enlarge and migrate to compensate for the continued cell loss. When corneal endothelial density falls below a certain level (approximately 400–500 cells/mm2) through trauma, infection, or inherited diseases, the endothelial pumping capacity can no longer compensate for the passive leakage. If this continues, excessive fluid begins to pass through the barrier, and the stroma swells, reducing the corneal transparency (Joyce 2003; Tan et al. 2012).

2.3

Treatment of Corneal Endothelial Decompensation

The definitive treatment for corneal endothelial dysfunction is corneal transplant. Several surgical methods have been developed for the replacement of the corneal endothelium, and a high clinical standard has been set for safety and efficacy (Price et al. 2021). Full-thickness corneal transplantation, known as PK, was the classic surgical method for the treatment of corneal endothelial dysfunction and was first performed successfully by Edward Zirm in 1905 (Crawford et al. 2013). During the PK procedure, the central 7–9 mm of the dysfunctional host cornea is removed, and a comparably sized donor corneal tissue is sutured in its place. Thereafter, the transplant recipients mostly use corticosteroid drugs from a few months to a few years to prevent immunologic graft rejection. Eventually, a more selective surgical approach to dysfunctional corneal endothelium, known as EK, was developed, which improved recovery times and reduced risks. Gerritt Melles developed the first successful approach to selective endothelial replacement which is involved in a 9 mm incision and the replacement of some segments of the posterior stroma as well as of the dysfunctional endothelium and the Descemet membrane (Melles et al. 1998, 1999). With advancements in surgical techniques, other treatments evolved from the EK technique, namely deep lamellar endothelial keratoplasty (DLEK), Descemet stripping endothelial keratoplasty (DSEK), and DMEK (Fig. 2) (Melles et al. 1998, 1999; Terry and Ousley 2001; Melles et al. 2004; Price Jr and Price 2005; Melles et al. 2006). At present, approximately 40% of corneal transplants are performed for treating corneal endothelial dysfunction (Eye Bank Association of America 2015). However, a worldwide shortage of healthy human donor corneas has limited the application of corneal transplants. In an effort to address this issue, researchers have begun investigating alternative treatment options and four such alternatives are discussed here. The first is Descemet stripping without EK, which is known as “Descemet stripping only” (DSO) (Arbelaez et al. 2014). In this surgical process, the central

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Fig. 2 Schematic of the selective corneal endothelial transplantation surgery, including DLEK, DSEK, and DMEK

Descemet membrane and endothelium are carefully stripped, and the peripheral endothelial cells migrate to cover the denuded area. Different from DMEK or DSEK, DSO can only successfully improve corneal transparency when the stripped area is no more than 4–5 mm in diameter (Borkar et al. 2016). The second involves the use of Rho-associated coiled-coil-containing protein kinase (ROCK) inhibitor Y-27632, which was initially used to enhance cell adhesion, inhibit cell apoptosis, and increase the proliferation of the transplanted CECs (Okumura et al. 2009, 2014, 2016a, b; Pipparelli et al. 2013). In Japan, the Rho kinase (ROCK1 and ROCK2) inhibitor ripasudil hydrochloride hydrate was approved for treating glaucoma and ocular hypertension and for use in DSO (Moloney et al. 2017; Huang et al. 2018). Currently, the clinical trial is ongoing to verify the efficacy and safety of ripasudil for corneal endothelial decompensation by DSO (ClinicalTrials.gov Identifier: NCT03575130). The third alternative is the CEC transplantation method, in which cultured CECs are directly injected into the anterior chamber through single-cell suspension. Professor Amano’s team from Japan was the first to report that cultured human CECs could adhere to cultured human corneal tissues in vitro and form monolayer cells (Amano 2003). Professor Kinoshita’s team performed clinical trials for CEC transplantation starting from 2013 (Kinoshita et al. 2018). According to the report, the 5-year clinical follow-up for 11 patients has been completed, which includes seven cases of Fuchs corneal endothelial dystrophy and four cases of laser iridectomy, exfoliation syndrome, and bullae keratopathy associated with intraocular surgery. After 5 years of operations, corneal transparency, thickness, and visual acuity had recovered well in ten cases, and no systemic or intraocular abnormalities were found (Fig. 3). According to the optimized in vitro expansion technology, the CECs from one corneal donor can be used to theoretically realize the treatment of nearly 100 patients. Currently, several alternative seed sources, such as hESCs/hiPSCs

Fig. 3 Schematic of the cell-injection therapy for corneal endothelial decompensation. The cultured corneal endothelial cells (CECs) were isolated from the cornea of the healthy donors, and cultured in vitro free of any contamination. When confluent, CECs are digested and suspended to obtain the appropriate number and density, and supplemented with the ROCK inhibitor. After mechanical removal of the abnormal CECs and extracellular matrix of the patients with corneal endothelial decompensation, the cultured human CECs with the ROCK inhibitor were injected into the anterior chamber. Then, the patients were placed in a prone position for 3 h (Created with BioRender.com)

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and adult stem cell-derived CECs, have also been successfully used in animal models (Hatou et al. 2013; Alio del Barrio et al. 2015; Shao et al. 2015; Song et al. 2016; Zhao and Afshari 2016; Shen et al. 2017; Chen et al. 2018; Li et al. 2022). The fourth method involves the use of an artificial corneal endothelium, which is a corneal endothelium graft substitute made from synthetic material. The artificial endothelial sheet is not loaded with CECs and is attached to the central posterior corneal stroma, covering approximately 40% of the posterior corneal surface. The remaining uncovered areas provide adequate water filtration to maintain the tissue’s nutrients. Finally, corneal hydration homeostasis is reestablished through evaporation from the surface of CECs and the reduction of stromal influx in the central zone. The results of an ongoing multicenter clinical trial of the EndoArt artificial endothelium for corneal edema (Registration No. NCT03069521) showed that corneal edema was alleviated and restored in seven out of a total of eight patients after EndoArt implantation; however, artificial endothelial shedding occurred in all seven patients, which required gas injection into the anterior chamber to reposition the artificial endothelial sheet.

3

Generation of iPSC-Derived Corneal Endothelial Cells (CECs)

3.1

Strategies of iPSC-Derived CECs

At present the methods for producing CECs from hiPSCs or hESCs are mostly used to simulate the process of corneal embryonic development. First, hiPSCs/hESCs were induced into neural crest cells by inhibiting TGFβ-Smad and activating the Wnt signaling pathway using small-molecule compounds (Hatou et al. 2013; Chen et al. 2021). Second, different cytokines, small-molecule compounds, and conditioned corneal endothelial mediums were used to induce CECs from the neural crest cells. Morphological and immunofluorescence staining were used to identify the differentiated cells in vitro, and the rabbit corneal endothelial decompensation model was used to verify their function in vivo (Table 1). Three methods for producing CECs from iPSCs are reviewed in the following sections. Chen et al. derived corneal endothelial-like cells from mouse ES cells and iPSCs using all-trans retinoic acid (RA) and lens epithelial cell-conditioned medium (LECCM). First, a 1 μM RA treatment during the embryoid body culture was used to promote neural crest cell differentiation. Since corneal endothelium is located between the corneal stroma and lens, its development may be influenced by the lens epithelial cells and the corneal stroma cells. Thus, LECCM was used to derive corneal endothelial-like cells from the neural crest cells during the second stage of differentiation. These corneal endothelial-like cells expressed AQP1, zonula occludens-1 (ZO1), Na+/K+-ATPase, N-cadherin, VE-cadherin, and Vimentin (Chen et al. 2018).

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Table 1 Summary of details of methods producing CECs from hiPSCs/hESCs In vivo transplant model N.A.

In vivo function evaluation N.A.

ZO-1, N-cadherin, AQP1, Na+/K+ATPase, COL8A1, COL8A2. . .

Rabbit, monkey

Na+/K+-ATPase, AQP1, ZO-1, vimentin, Col8A1

N.A.

Corneal transparency, thickness, morphology, and density N.A.

ZO-1, Na+/K+ATPase, N-cadherin, VE-cadherin, vimentin N.A.

N.A.

N.A.

Rabbit

N2, bFGF, IGF1, IL6, IL11, TNF-α

Na+/K+-ATPase, ZO-1, N-cadherin, PITX2

Monkey

hESCs hiPSCs

RA, bFGF, ROCK inhibitor, SB431542

AQP1, ZO-1, Na+/K +-ATPase, N-cadherin, P75...

Rabbit, monkey

Shen et al. (2017)

SKPs

Co-culture with B4G12

Na+/K+-ATPase, ZO-1, N-cadherin, Col8A2. . .

Rabbit, monkey

Song et al. (2016)

hESCs

Noggin, SB431542, bovine CECs condition medium

Na+/K+-ATPase, AQP1, ZO-1

N.A.

Corneal transparency, thickness, IOP Corneal transparency and thickness, IOP Corneal transparency, thickness, morphology, and density Corneal transparency, thickness, morphology, and density, IOP N.A.

Reported studies Ali et al. (2018a, b)

Cell source hiPSCs

Induction method Noggin, SB431542, B27, PDGFBB, Dkk-2 Noggin, SB431542; B27, PDGFBB, Dkk-2

Character of induced endothelial cells ZO-1, AQP1, Na+/K +-ATPase, COL8A1, COL8A2. . .

Ali et al. (2021)

hESCs

Chen et al. (2021)

hiPSCs

hESCs

SB431542, DMH1, AMPK activator, Akt/ROCK/ PKA inhibitor, CHIR99021 RA, LECCM

Chen et al. (2018) Hatou et al. (2013)

PKH26positive COPs

RA, BIO (GSK3β inhibitor)

Hatou et al. (2021)

hiPSCs

Li et al. (2022)

(continued)

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Table 1 (continued) Reported studies Zhao and Afshari (2016)

Cell source hESCs, hiPSCs

Induction method N2, B27, bFGF, CHIR99021, SB431542, H-1125 (ROCK inhibitor)

Character of induced endothelial cells Na+/K+-ATPase, N-cadherin

In vivo transplant model N.A.

In vivo function evaluation N.A.

COP corneal-derived precursor, LECCM lens epithelial cell-conditioned medium, IOP intraocular pressure, CEC corneal endothelial cell, SKP skin-derived precursor, N.A. not analyzed

The derivation method for corneal endothelial-like cells, proposed by Ali et al., was a chemically defined two-step method (Ali et al. 2018a, b; Ali et al. 2021). Neural crest cells were induced from hESCs and hiPSCs in the first step with dual Smad-inhibitor media containing the BMP signaling-pathway inhibitor Noggin and the TGFβ signaling-pathway inhibitor SB 431542. Next, the dual Smad-inhibitor media was replaced with a corneal endothelial differentiation medium containing B27, PDGF-BB, and Dkk-2 on Day 6. After 20 days of differentiation, the hESC and hiPSC corneal endothelial-like cells exhibited a hexagonal/polygonal shape and expressed ZO1 and N-cadherin. Li et al. also derived corneal-like cells from hESCs and hiPSCs under a specific chemically defined condition (Li et al. 2022). Their method consisted of two steps; RA and basic fibroblast growth factor (bFGF) promotes the development of neural crest cells from hESCs and hiPSCs, which expressed P75, HNK-1, AP-2α, and AP-2β. Next, Rho kinase inhibitor Y-27632 and TGFβ signaling-pathway inhibitor SB431542 were used to derive corneal endothelial-like cells from neural crest cells, and these cells expressed AQP1, ZO1, Na+/K+-ATPase, and N-cadherin. Moreover, the authors identified a class of intermediate cell types, corneal endothelial precursors, which simultaneously expressed P75, AP-2β, ZO1, and Na+/K+ATPase. In vivo transplantation showed that a corneal endothelial precursor combined with nicotinamide could rapidly restore and maintain corneal transparency and thickness in the rabbit and cynomolgus monkey models for a long time, while the transplanted precursor differentiated into mature corneal endothelial-like cells in vivo.

3.2

Molecular Profiling and Characteristics

To characterize the hiPSC-derived corneal endothelial-like cells, it is necessary to identify the expressions of unique corneal endothelial markers. Na+/K+-ATPase and ZO1 are frequently used markers for corneal endothelium identification, which are responsible for the pumping and barrier functions of the corneal endothelium.

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However, these markers are ubiquitously expressed in different epithelial cells, which are not unique to the corneal endothelium. The reported high-frequency genes used to identify cultured human CECs include Na+/K+-ATPase, ZO1, COL8, SLC4A11, Vimentin, N-cadherin, AQP1, Ki67, CD166, and so on (Van den Bogerd et al. 2019). Professor Kinoshita’s team performed a series of experiments to promote the clinical translation of homogeneously cultured CECs. Through the analysis of different subpopulations, they found that functional endothelial cells displayed CD44-, CD166+, CD133-, CD105-, CD24-, and CD26-, which favor cell therapy (Hamuro et al. 2016; Ueno et al. 2016; Toda et al. 2017). At present, morphology, immunofluorescence staining, and flow analysis are used to identify hESC- and hiPSC-derived corneal endothelial-like cells in vitro, and animal transplantation experiments are used to verify their function in vivo. The markers expressed in hiPSC-derived corneal endothelial-like cells include ZO1, Na +/K+-ATPase, PITX2, AQP1, N-cadherin, COL8A1, Vimentin, and SLC4A11. The whole transcriptome analysis results showed that hESC-derived corneal endotheliallike cells are much more similar to corneal endothelium than to other human tissues and resemble adult corneal endothelium more closely than fetal ones (Song et al. 2016). Next-generation RNA-seq analysis confirmed that both the hESC- and hiPSC-derived corneal endothelial-like cells have largely equivalent transcriptomes (Ali et al. 2018a, b).

4

iPSC-Based Models of Corneal Endothelial Dysfunction

One major cause of corneal endothelial decompensation is genomic abnormalities in patients. There are four types of corneal endothelial dystrophies, namely Fuchs endothelial dystrophy (FECD), posterior polymorphous corneal dystrophy (PPCD), congenital hereditary endothelial dystrophy (CHED), and X-linked endothelial dystrophy (XCED) (Aldave et al. 2013). Some genomic mutations have been reported, such as SLC4A11, ZEB1, COL8A2, or TCF4 (Biswas et al. 2001; Wieben et al. 2012; Fautsch et al. 2021; Ong Tone et al. 2021; Lechner et al. 2013). These abnormal genes or proteins seriously affect corneal endothelial function. For studying these genetic endothelial diseases, in vivo and in vitro models have been established. The in vitro models include ex vivo specimens, primary cultures, and immortalized cell lines from patients suffering from corneal endothelial dysfunction. Further, the in vivo animal models include various genetically engineered mice and the UVA-induced mouse model (Jun et al. 2012; Liu et al. 2020). Compared with the ex vivo cell model, the in vivo animal model can be used to study the early pathophysiology and progression of the corneal endothelial diseases, as well as for drug screening. Autologous induced pluripotent stem cells can be induced into CECs, representing an attractive option for simulating corneal endothelial disease progression. To date, there has been only one study involving an iPSC-derived corneal endothelial disease model. Brejchova et al. reported clinical findings in six probands with CHED and developed an iPSC-derived corneal endothelial-like model system

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using a heterozygous carrier of the c.2240+5G>A SLC4A11 variant to investigate its potential pathogenicity (Brejchova et al. 2019). Through the hiPSC CE-like cells model, these authors assessed the expressions of the marker genes and the effects of the SLC4A11 variants on pre-mRNA splicing within its native genomic and cellular contexts, which can also be used to verify the cellular functional outcomes.

5

Applications of iPSC-Derived CECs for Corneal Endothelial Dysfunction

5.1

Tissue Engineering Corneal Endothelium

Tissue engineering cornea is a potential alternative approach for corneal transplant. Previous studies have attempted to construct tissue-engineered full-thickness cornea but mostly only managed in vitro construction or preliminary animal validation (Zhang et al. 2015, 2017). With the development of corneal transplant technology, the researchers shifted their focus to tissue-engineered corneal endothelium, which is a classic approach for regenerative treatment of corneal endothelial diseases. Tissue-engineered corneal endothelium involves inoculating the in vitro expanded or differentiated endothelial seed cells on carriers to construct tissueengineered corneal endothelial patches. The different sources of seed cells include human corneal donor, hESC/hiPSC, and adult stem cells (Chen et al. 2018; Hatou et al. 2013; Song et al. 2016; Zhao and Afshari 2016; Alio del Barrio et al. 2015; Shao et al. 2015; Shen et al. 2017; Li et al. 2022). The reported carrier materials can be classified as biotype, synthetic, and temperature-sensitive carriers (Ishino et al. 2004; Ide et al. 2006; Mimura et al. 2004). The safety and efficacy of these membranes with regard to treating corneal endothelial diseases were initially validated through both conventional and large-animal models. Compared to tissue engineering full-thickness cornea, tissue-engineered corneal endothelium needs fewer donor cells, involves an easier surgery, and offers higher safety. In recent years, the technique of direct anterior chamber injection of cultured CECs has been gradually introduced into research and clinical trials; this has become a new research direction with regard to tissue engineering corneal endothelium (Okumura et al. 2016a, b; Kinoshita et al. 2018; Peh et al. 2019; Zhao et al. 2020; Li et al. 2022). CEC transplantation is a method in which the in vitro expanded or differentiated seed cells are directly injected into the anterior chamber through single-cell suspension. Professor Amano was the first to report that cultured human CECs can adhere to human cornea tissues in vitro and form an endothelial monolayer (Amano 2003). Subsequent animal experiments have proved that this method could effectively restore the thickness and transparency of rabbit corneas. In 2013, Professor Kinoshita and his colleagues started official clinical trials for CEC transplantation for corneal endothelial dystrophy (Kinoshita et al. 2018). The basic surgical procedures were as follows: First, a 1.6 mm incision was made at the limbus using a special needle to remove diseased cells and abnormal extracellular matrix within 8 mm of the central cornea. Next, 300 μl Opti-MEM I medium containing 5–10 × 106 cells and 100 μM Y-27632 was directly injected into the

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anterior chamber using a 26G needle. Then, the patients were kept in a prone position for 3 h, and the adhesion of the transplanted cells was promoted using gravity and Y-27632. Systemic and local glucocorticoids and anti-infective drugs were used for conventional corneal transplantation. According to the report, the 5-year clinical follow-up for 11 patients has been completed, which includes seven cases of Fuchs corneal endothelial dystrophy and four cases of laser iridectomy, exfoliation syndrome, and bullae keratopathy associated with intraocular surgery. The results showed that, at 24 weeks after operation, the corneas of all patients were clear, the central corneal thickness in ten cases was less than 630 μm, and the best corrected visual acuity for nine cases was improved by more than two lines. Five years after the operation, corneal transparency, thickness, and visual acuity recovered well in ten cases, and no systemic or intraocular abnormalities were found. It is worth noting that for the seven patients with Fuchs endothelial dystrophy, the “Guttae” feature appeared in the central endothelium once again, suggesting that Fuchs endothelial dystrophy may be accompanied by an abnormal Descemet membrane.

5.2

Therapeutic Function

Although many studies have reported that corneal endothelial-like cells could be derived from hiPSCs, there have been few reports of functional studies of hiPSCderived CECs in vivo. Recently, Hatou et al. derived corneal endothelial-like cells from both research- and clinical-grade hiPSCs, and these cells formed a hexagonal monolayer with the expressions of Na+/K+-ATPase, ZO1, N-cadherin, and PITX2 (Hatou et al. 2021). To establish the monkey corneal edema model, these authors completely scraped the CECs using a soft tapered needle through nasal and temporal paracentesis of the corneal limbus. Next, 8 × 105 cells/160 μl cell suspension was injected into the anterior chamber. According to the report, the transplanted cells decreased corneal thickness and improved transparency compared to the control group, but the authors only followed up for 28 days. In a recent related study from labs of Shi and Zhou, a delivery of corneal endothelial precursors from hESCs and hiPSCs, an intermediate cellular state between neural crest cells and mature CECs, was made to validate their safety and efficacy in the rabbit and cynomolgus monkey animal models (Li et al. 2022). According to the report, the corneal-endothelial-precursors-derived from hiPSCs stained positive for the neural crest maker P75 and the corneal endothelial markers ZO1, Na+/K+-ATPase, and AQP1. Next, 8 × 105 cells/250 μl cell suspension with Y-27632 and nicotinamide was directly delivered into the anterior chamber for the rabbit corneal edema model. For the rabbits injected with precursor CECs, the corneal edema resolved gradually, and normal corneal clarity and thickness were restored within 14 days. In contrast, rabbits receiving a sham operation continued to present edema. The immunostaining results indicated that the transplanted precursor cells formed a hexagonal monolayer with the expressions of Na+/K+-ATPase, ZO1, and SLC4A11. The nicotinamide treatment effectively inhibited premature

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senescence and the EMT and facilitated proper in vivo maturation of the transplanted precursor cells. In addition, the authors also injected 6 × 105 hESC-derived corneal endothelial precursors in the monkey model. Compared with the persistent corneal edema seen in the control group, the corneal edema in the monkeys that underwent cell injection was cured with corneal transparency and thickness having recovered within 2–8 weeks. Three years after the operation, corneal transparency and thickness appeared to have recovered well, and there were no systemic or intraocular abnormalities.

5.3

Therapeutic Mechanism

The traditional mechanism in cell transplant therapy for corneal endothelial diseases is through cell replacement therapy. Studies from laboratories of Shi and Zhou were the first to elucidate the therapeutic mechanism behind the long-term efficacy of the transplantation of seed cells derived from human pluripotent stem cells (hPSCs) (Li et al. 2022). Rabbit and nonhuman primate models have been used in preclinical studies of CEC therapy. To date, hPSC-derived cell transplantation has been found to lead to the maintenance of corneal transparency up to 9 months after surgery in rabbit models and up to 3 years after surgery in nonhuman primate models. Different from human corneal endothelium, rabbit corneal endothelium has regenerative capabilities in vivo and can recover through cell proliferation after injury. In nonhuman primates, the proliferation of adult CECs is very limited and can only undergo repair through the enlargement and migration of the resident cells after injury, which is similar to humans. Therefore, the functional mechanism of transplanted cells with respect to treating corneal endothelial decompensation differs across different animal models, and the nonhuman primate model can better reflect the human situation. In this study, the authors compared the short- and long-term fates of transplanted cells in rabbit and nonhuman primate models (Fig. 4). In the rabbit model, the corneal endothelial precursor combined with nicotinamide could maintain corneal transparency for 8 weeks after surgery, but the transplanted cells completely disappeared by 8 weeks, and there were dividing cells in the autologous corneal endothelium. These observations suggest that the short-term recovery of rabbit corneas is achieved by cell replacement, while long-term recovery depends on the activation of the regenerative ability of the autologous endothelial cells. In the nonhuman primate model, corneal transparency was maintained for 3 years after the surgery. It was found that the peripheral endothelial scraping area was covered with only autologous endothelial cells, while the intermediate transition area presented a mixture of autologous and transplanted cells. Further, the central area was covered with only transplanted cells. These findings suggest that transplanted cells can stimulate the limited regenerative capacity of autologous CECs in monkeys. Nowadays, Descemet’s stripping without endothelial keratoplasty (DWEK) is utilized to reduce corneal edema (Arbelaez et al. 2014). Although the efficacy of this procedure is dependent on the size of the Descemet membrane

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Fig. 4 Schematic of the long-term functional mechanism of the transplanted cells for corneal endothelial decompensation in rabbit and nonhuman primate models. CEP corneal endothelial precursors, NAM nicotinamide, EnMT endothelial–mesenchymal transition

dissection, genetic factors, and systemic diseases, its effectiveness suggests the possibility of regenerating and repairing adult CECs in a specific environment (Borkar et al. 2016).

6

Future Applications and Challenges

Corneal endothelial regeneration has always been a difficult problem in the treatment of corneal diseases. iPSC technologies offer a remarkable potential solution for this issue due to their ability to expand indefinitely and differentiate into any cell type. Many approaches have been developed to derive corneal endothelial-like cells from hiPSCs. However, considering the application of genome-integrating viruses, there is the risk of tumorigenesis with iPSC-derived cell transplantation. To avoid integration into locations near cancer-related genes, researchers focus on the development of less risky transfection vectors, including RNA, protein, and small-molecule (Ohnuki and Takahashi 2015). According to the literature, episomal plasmid vectors that encode the reprogramming factors have been proved to be safe and efficient for iPSC generation (Mohammad Al-Shehri et al. 2021). Although iPSC technologies have the potential benefits of autologous therapy, the preparation of autologous iPSCs and the related differentiated cells carries a high medical cost and requires a long time. To save time and cost, the iPS Cell Stock Project is being established for regenerative medicine, the stock of which matches three major HLA loci, namely A, B, and DR. Matching the HLA loci between recipient and donor is expected to reduce the risk of immune rejection (Nakajima et al. 2007; Nakatsuji et al. 2008). Moreover, compared with the hESC lines, the iPSCs exhibit greater diversity due to

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the associated epigenetic memory, donor genetic background, and reprogramming features (Kim et al. 2010; Rouhani et al. 2014). As for the standardized iPSC-derived cells therapy for corneal endothelial decompensation, further studies are required to evaluate the iPSC quality and the classic molecular marker. A classic medical application of iPSC technologies is cell replacement therapy. In fact, iPSCs can be used for disease modeling, drug discovery, and toxicology screening (Yamanaka 2010). Although animal models make significant contributions to the understanding of disease mechanisms, there are only a few animal models for corneal endothelial dysfunction. Moreover, the diversity and complexity of pathogenic causes also limit the development of our understanding of the mechanism of corneal endothelial diseases. iPSC technologies offer huge potential with respect to elucidating this mechanism and screening novel drugs.

7

Summary

Although there are many limitations in corneal endothelial research, great progress has been made in the examination of corneal endothelial regeneration through the unremitting efforts of scientists. For example, the approach involving the injection of cultured human primary CECs in a clinical trial improves the visual function of 11 patients with corneal endothelium decompensation. Further, the innovative artificial corneal endothelium is found to restore corneal transparency without relying on cells and is undergoing multicenter clinical trials; it has already improved visual function for seven of the eight patients suffering from corneal endothelial diseases. iPSCs, as a promising alternative seed cell source, have been successfully differentiated into corneal endothelial-like cells. Preclinical findings show that iPSCderived cells can lead to a complete recovery of long-term corneal visual acuity and thickness. However, clinical trials are urgently needed to confirm the efficacy and safety of hiPSC-derived corneal endothelial-like cells for the treatment of corneal endothelial decompensation. Furthermore, there is also an urgent need to apply iPSC technologies to study the pathogenesis and intervention strategies of corneal endothelial decompensation. Tremendous advances in the field of iPSC-derived corneal endothelium have been seen in the past decade and the potential of iPSC technologies is still being discovered, which await for corneal endothelial applications.

References Aldave AJ, Han J, Frausto RF (2013) Genetics of the corneal endothelial dystrophies: an evidencebased review. Clin Genet 84(2):109–119. https://doi.org/10.1111/cge.2013.84.issue-2. https:// doi.org/10.1111/cge.12191 Ali M, Khan SY, Kabir F, Gottsch JD, Amer Riazuddin S (2018a) Comparative transcriptome analysis of hESC- and iPSC-derived corneal endothelial cells. Exp Eye Res 176:252–257 Ali M, Khan SY, Vasanth S et al (2018b) Generation and proteome profiling of PBMC-originated, iPSC-derived corneal endothelial cells. Invest Ophthalmol Vis Sci 59:2437–2444

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iPSCs-Based Therapy for Trabecular Meshwork Wei Zhu, Xiaoyan Zhang, Shen Wu, Ningli Wang, and Markus H. Kuehn

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Trabecular Meshwork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Trabecular Meshwork Physiology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Trabecular Meshwork Pathology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Novel Treatments for the Damaged TM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 In Vitro Models for TM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Conventional Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1 Primary TM Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.2 Immortalized Lines of TM Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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W. Zhu (✉) Department of Pharmacology, School of Pharmacy, Qingdao University, Qingdao, China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing, China e-mail: [email protected] X. Zhang Department of Pharmacology, School of Pharmacy, Qingdao University, Qingdao, China S. Wu Beijing Institute of Ophthalmology, Beijing Tongren Hospital Eye Center, Capital Medical University, Beijing, China N. Wang Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing, China Beijing Institute of Ophthalmology, Beijing Tongren Hospital Eye Center, Capital Medical University, Beijing, China M. H. Kuehn Department of Ophthalmology and Visual Sciences, University of Iowa, Iowa City, IA, USA Center for the Prevention and Treatment of Visual Loss, Iowa City Veterans Affairs Medical Center, Iowa City, IA, USA # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_671

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4.2 Induced Pluripotent Stem Cell (iPSC)-Based Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 3D Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Bioreactor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Glaucoma Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 iPSC-Based Therapy for the Damaged TM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 TM Regeneration in Mouse and Human . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.1 Tg-MYOCY437H Mice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.2 sGCα1-Deficient Mice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.3 TM Regeneration in Human Eyes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Mechanism of TM Regeneration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Challenges for Clinical Translation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The trabecular meshwork (TM) of the eye serves as an essential tissue in controlling aqueous humor (AH) outflow and intraocular pressure (IOP) homeostasis. However, dysfunctional TM cells and/or decreased TM cellularity is become a critical pathogenic cause for primary open-angle glaucoma (POAG). Consequently, it is particularly valuable to investigate TM characteristics, which, in turn, facilitates the development of new treatments for POAG. Since 2006, the advancement in induced pluripotent stem cells (iPSCs) provides a new tool to (1) model the TM in vitro and (2) regenerate degenerative TM in POAG. In this context, we first summarize the current approaches to induce the differentiation of TM-like cells from iPSCs and compare iPSC-derived TM models to the conventional in vitro TM models. The efficacy of iPSC-derived TM cells for TM regeneration in POAG models is also discussed. Through these approaches, iPSCs are becoming essential tools in glaucoma modeling and for developing personalized treatments for TM regeneration. Keywords

Glaucoma · Induced pluripotent stem cells · Intraocular pressure · Regeneration · Trabecular meshwork

1

Introduction

Glaucoma is a multifactorial degenerative optic neuropathy closely associated with elevated intraocular pressure (IOP), aging, race, and genetic factors (Fea et al. 2022). It is the second leading cause of blindness after cataracts. As a severe public health issue, it affects more than 70 million people worldwide. With the population aging, the number of glaucoma patients is estimated to increase to over 112 million by 2040 (Kang and Tanna 2021). Without proper treatment, approximately 10% of glaucoma patients will eventually become blind (Jonas et al. 2017).

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There are two classes of primary glaucoma: open-angle glaucoma (OAG) and angle closure glaucoma (ACG). OAG is the more common form and is primarily caused by elevated IOP due to an imbalance of aqueous humor (AH) secretion and outflow (McDougal and Gamlin 2015). AH is produced by the ciliary body and secreted into the posterior chamber. It passes through the pupil, flows into the anterior chamber, and, after transiting the TM, drains out of the eye into the vasculature (Alward 2003). In most primary OAG (POAG) cases, AH production is normal, yet increased resistance to AH outflow and increased IOP is the typical pathological phenotype. The most recognized outflow pathways include the conventional pathway, composed of the trabecular meshwork (TM) and Schlemm’s canal (SC), and the unconventional pathway, also known as the uveoscleral pathway (Braunger et al. 2015). The conventional pathway is responsible for approximately 80% of AH efflux. TM and SC have become attractive targets for regulating IOP in POAG (Thomson et al. 2021; Zhang et al. 2016). However, limitations in the availability of in vitro models to mirror TM and SC impede our understanding of the biological roles of TM and SC in controlling AH outflow. Significant advances in induced pluripotent stem cell (iPSC) technology have facilitated the intensive study of pathogenic mechanisms, drug discovery, and regenerative medicine for many human diseases, including glaucoma. Here, we discuss and focus on (1) the current treatments targeting TM, (2) conventional TM modeling, (3) iPSC-based TM modeling, and (4) iPSC-based therapy for damaged TM.

2

Trabecular Meshwork

2.1

Trabecular Meshwork Physiology

Since the TM serves as a significant site of AH drainage, its anatomical features have been extensively studied. The TM is a spongy tissue circumferentially located posterior to the cornea in the eye. It is 70 μm thick in the anterior region and 100–130 μm thick on average in the posterior region (Dietlein et al. 2000). It can be divided into three layers (uveal meshwork, corneoscleral meshwork, and juxtacanalicular meshwork), each with different structures and functions in regulating AH outflow from the eye (Castro and Du 2019). The inner uveal and corneoscleral meshworks contain 1–3 and 8–15 trabecular beams with approximately 25–27 μm and 2–15 μm open space, respectively (Chhunchha et al. 2017). The resistance of these two layers to AH outflow is negligible. The outer juxtacanalicular meshwork, also known as the cribriform region, is the thinnest region in the TM (2–20 μm) located adjacent to the inner wall of SC. Due to its compact fibrillar extracellular matrix (ECM) and fewer open extracellular structures, the juxtacanalicular meshwork mediates most of the resistance to AH outflow (Stamer and Clark 2017). Besides its elaborate anatomical structure, the TM also possesses a complex mixture of cell types. Single-cell RNA-sequencing techniques based on the 10×

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Genomics platform have identified 12 types of cells in human conventional outflow tissue, including fibroblasts, myofibroblasts, smooth muscle cells, Schwann cells, myelinating Schwann cells, melanocytes, macrophages, pericytes, vascular endothelial cells, T cells/natural killer cells, lymphatic endothelial cells, and epithelial cells (Patel et al. 2020; van Zyl et al. 2022). Among these, fibroblasts, myofibroblasts, and macrophages are considered the primary components of the TM. Functionally similar to fibroblasts and smooth muscle cells, cells in the juxtacanalicular meshwork possess the ability to mediate ECM turnover and contractile tone, two critical steps for controlling the resistance to AH outflow (Stamer and Clark 2017; Vranka and Acott 2017). In contrast, cells in the uveal and corneoscleral meshworks possess the ability to clear cellular debris from AH, similar to phagocytosis for macrophages. In addition, macrophages are located throughout the entire TM, leading to efficient clearance of debris that might be carried into the tissue by AH flow (Stamer and Clark 2017).

2.2

Trabecular Meshwork Pathology

Loss of TM cellularity, aberrant ECM remodeling and turnover, and changes in the biomechanical properties of the TM can disrupt AH outflow and elevate IOP, leading to glaucoma (Mallick et al. 2021; Fan et al. 2021). As reported in the 1980s, TM cellularity in humans decreases by 58% from newborns to 80-year-old individuals. TM cellularity is much lower in POAG patients than in healthy populations and also further declines with aging (Sundaresan et al. 2021; Alvarado et al. 1981). The decrease of TM cellularity in POAG eyes is apparent along the entire circumference of the eye, suggesting that it is due to intrinsic mechanisms rather than catastrophic events affecting only some segments of the tissue (Kuehn et al. 2021). The first pathogenic mutation for POAG was identified in the myocilin (MYOC) gene in 1997 (Stone et al. 1997). Overexpression of the mutant protein in the anterior segment, including TM, leads to a decline in TM cellularity presumably by causing myocilin aggregation in the endoplasmic reticulum (ER), leading to ER stress and triggering unfolded protein reactions (UPR) (Wang et al. 2019; Tanji et al. 2021). Transgenic mice MYOCY437H (Tg-MYOCY437H) display various glaucomatous phenotypes and further reveal the importance of TM cellularity in IOP homeostasis (Yan et al. 2022). Together, these data indicate that decreased TM cellularity is a critical pathogenic cause for glaucoma. In addition, abnormalities in ECM remodeling and TM mechano-biology are also considered important contributors to IOP elevation in POAG. For example, increased contractile tone, accumulated ECM deposition, disrupted actin cytoskeleton, enhanced tissue stiffness, and abnormal mechanosensory in TM all significantly increase the resistance to AH outflow (Agarwal and Agarwal 2018; Kaufman 2020).

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Novel Treatments for the Damaged TM

As discussed earlier, IOP is typically regulated by balancing AH production and drainage (Coulon et al. 2022). The primary option to lower elevated IOP in glaucoma patients is pharmacologic treatment. Conventional treatment includes use of β-adrenergic antagonists, α-adrenergic agonists, and carbonic anhydrase inhibitors to reduce AH production, and cholinergic agonists and prostaglandin analogs are to increase AH outflow through unconventional pathways (Sheybani et al. 2020). It is important to mention that medical therapy faces significant obstacles due to side effects of the drugs used, limitations of monotherapy, poor patient compliance, especially when multiple drugs are administered, and low efficiency in mediating conventional AH outflow (Lu et al. 2017). Recently, Rho kinase inhibitors have been identified as a new class of IOP lowering drugs. These drugs function primarily by modulating cytoskeleton, cell contractile tone, volume, and ECM deposition of TM (Storgaard et al. 2021). While disease-causing mutations are rare, the development of glaucoma is clearly influenced by multiple genetic factors (Wiggs 2015; Aung and Khor 2016). Therefore, gene therapy holds great promise to rescue TM dysfunction. Given the TM’s physiological and anatomical characteristics in the eye, gene therapy may be feasible because (1) eyes are immune privileged and transparent (Borrás 2017), and (2) the TM is beneath the cornea (Vranka et al. 2015), which facilitates access to the tissue. Experimentation in mouse models suggests that gene therapy may be useful for TM tissue remodeling, including modulation of ECM (O’Callaghan et al. 2017), cytoskeleton (Tan et al. 2018), and cell population (Jain et al. 2017), and subsequent reduction of elevated IOP. However, gene therapy not been shown to be effective in human eyes with POAG and has yet to be adopted in clinical practice, in part due to limited data from clinical trials (https://www.clinicaltrials.gov/) (Liu et al. 2009).

4

In Vitro Models for TM

4.1

Conventional Models

Although more and more pharmacological options and technologies are being developed to meet the current clinical requirements most, like agonists/antagonists for mechanosensitive ion channels, are still at a very early stage for clinical usage (Yarishkin et al. 2021, 2022). Clinical translation of these new drugs and technologies is a demanding challenge. As such, appropriate in vitro models to mirror TM function are extremely valuable to understand TM physiology. In the past 30 years, both primary TM cells and immortalized TM cell lines have been intensively investigated (Fig. 1).

4.1.1 Primary TM Cells Most investigators prefer to use primary cultures of isolated TM cells (pTM) from healthy and glaucomatous human donor eyes as an in vitro TM model to examine

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Fig. 1 In vitro models for trabecular meshwork using pTM and immortalized TM cells. Representative images of pTM, HTM5, and GTM3 are shown (Created with BioRender.com)

TM physiology. As described in the published “Consensus recommendations for trabecular meshwork cell isolation, characterization and culture” (Keller et al. 2018), extreme care should be taken to ensure that the resulting in vitro cultures remain representative of in vivo physiology. The function of pTM is influenced by multiple factors, including donor origin, genetic factors, post-mortem interval, storage methods of the eye before dissection, dissection techniques, and cell culture methods. For example, cultures generated from human donors under 60 years of age typically exhibit good yields and growth rates, especially if the donor is very young (Caballero et al. 2004). In contrast, establishing cultures from donors over 60 years old is often encumbered by many complications, including inadequate cell yield after isolation, low growth rates, and dedifferentiation of the TM cells at very early passages (Caballero et al. 2004). Moreover, fundamental epigenetic changes remain an issue of long-term in vitro cell culture and eventually lead to the loss of TM phenotypes along with passaging (Keller et al. 2018). These factors limit the number of experiments that can be conducted using a particular culture. As a consequence, investigators wishing to use pTM need to ensure a continuous supply of human donor eyes that can be procured within a reasonable post-mortem interval. Even with careful manipulation, contamination with cells originating from neighboring tissues, such as fibroblasts and smooth muscle cells, is unavoidable. This has been demonstrated by two recent single-cell RNA-sequencing studies using isolated human TM tissue. Tavé van Zyla et al. (2020, 2022) and Patel et al. (2020) identified 12 distinct cell types in the isolated conventional tissue. Apart from TM cells and Schlemm’s canal endothelial cells, they found contaminants derived from neighboring tissues, such as smooth muscle cells, T/NK cells, melanocytes, and pericytes. If such cells are present in the culture, it is difficult to remove them and they may proliferate along with the desired TM cells. If contaminating cell types exhibit higher viability than TM cells, they outcompete and eventually replace them. To this end,

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the culture of the mixed cells may only mirror in vivo TM physiology for a short time. In addition to human eyes, those from other non-human primates, mice, canines, felines, porcines, and bovines have also been used for pTM cell isolation and TM modeling (Keller et al. 2018). Use of animal pTM circumvents many of the challenges of using human donors, expands the supply of TM cells, and permits control over post-mortem intervals and pre-dissection procedures. However, differences between humans and other species in TM structure and other features are becoming increasingly apparent (Keller et al. 2018; Begley et al. 1991; Chen et al. 2008). Moreover, TM isolation from small eyes such as mouse eyes is a highly skilled manipulation, contamination with other cell types from neighboring tissues is unavoidable, and the very low number of cells obtained requires substantial proliferation of the culture before it can be used. This significantly limits the number of passages that remain for experimentation.

4.1.2 Immortalized Lines of TM Cells Alternatively, SV40-immortalized lines of human TM cells have been developed (Pang et al. 1994). At least one of these (hTM5) has been used extensively and may be suitable for certain studies. However, immortalization induced notable differences between hTM5 and pTM including: (1) phenotypic changes in cell shape and size, (2) cell growth curve and loss of cell contact inhibition, (3) reduced formation of cytoskeleton and ECM deposition (Stamer and Clark 2017), and (4) impaired steroid induction of MYOC secretion (Jacobson et al. 2001). As such, investigators must carefully evaluate whether immortalized TM cells truly mirror the pTM phenotypes under investigation. Unlike the SV40-immortalized TM cell lines, bovine BTM-28 T is a spontaneously immortalized TM cell line, which has many phenotypes similar to primary bovine TM cells (Mao et al. 2012). Specifically, contact inhibition is a typical feature of BTM-28 T. From this point of view, BTW-28 T is more like the TM in vivo.

4.2

Induced Pluripotent Stem Cell (iPSC)-Based Models

The difficulties inherent in the use of conventional in vitro models in the development of glaucoma medications are similar to those slowing the development of novel treatment approaches in other fields. Fortunately, the development of iPSC technology in 2006 made it possible to overcome many of these challenges (Fig. 2). iPSCs possess the same pluripotency as embryonic stem cells (ESCs) and can be differentiated into various cell types (Lupo et al. 2021; Zhang et al. 2017; Castel et al. 2020). However, because of the autologous origin of iPSCs ethical barriers to creating a “patient-in-a-dish model” are substantially reduced (Papapetrou 2016; Cherry and Daley 2013). In 2014 Ding et al. were first to report protocols differentiating iPSCs into cells resembling TM. They generated mouse iPSCs from fibroblasts of dsRed transgenic B6.Cg-Tg (ACTB-DsRed*MST)1Nagy/J mice via lentiviral transduction of Oct4,

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Fig. 2 Development of iPSC-based TM models. iPSCs can be successfully differentiated into TM-resembling cells by four options. Representative images of iPSC-TM cells generated by Options 1 and 2 are shown. CM conditioned medium, EB embryoid body, NCC neural crest cell, TM-ECM TM-derived extracellular matrix (Created with BioRender.com)

Sox2, Klf4, and c-Myc and successfully differentiated these into TM-like cells, designated iPSC-TM. In this protocol, changes in iPSCs fate are caused by factors secreted by hTM5 into the cell culture medium. iPSC-TM cells exhibit many typical characteristics of TM cells, such as elongated and spindle-like cell shape, robust expression of TM biomarkers (Caveolin 1, Collagen type IV alpha 5, matrix Gla protein, MYOC, and vascular cell adhesion molecule 1), reduced expression of stem cell biomarkers, robust phagocytic activity, increase of MYOC expression following glucocorticoid exposure, and inducible expression of Tissue Inhibitor of Metalloproteinase 3 (TIMP3). In this study, differentiation was carried out using cell culture media conditioned by immortalized hTM5 cells which, as described earlier, may not fully resemble human pTM cells. In a subsequent study, the authors used media conditioned by human pTM to achieve differentiation of mouse iPSCs into TM-like cells with similar characteristics, including the formation of glucocorticoid-induced cross-linked actin networks (Zhu et al. 2016). Mouse iPSCs reprogrammed from fibroblasts of another mouse strain, 129/SvEv, have also been investigated. Following the pTM-based differentiation protocol, iPSCs can also be efficiently transformed into TM-like cells, which are immunopositive for TM biomarkers including α-smooth muscle actin, β-tubulin, collagen 1A2, fibronectin, fibulin-5, vimentin, matrix Gla protein, and MYOC. Therefore, the genetic background is not a critical factor influencing iPSCs

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differentiation toward TM cells (Trabecular meshwork restoration in primary open angle glaucoma using stem cells.pdf n.d.; Cheng et al. 2020; 8_Kuehn_v3.pdf n.d.). The generation of human iPSC-TM from iPSCs derived by reprogramming fibroblasts or keratinocytes using Sendai virus has also been investigated (Abu-Hassan et al. 2015; Zhu et al. 2020). The creation of iPSC-TM from mouse iPSCs is a rapid process and usually TM-like morphology is observed after 7 days of differentiation. These early cells are smaller in size than mouse pTM but will continue to grow until reaching a similar size. In contrast, iPSC-TM cells generated from human iPSCs may need up to 90 days to achieve a size similar to human pTM cells (Zhu et al. 2020). This discrepancy might be due to the different speed of embryonic development in these species. While mice commonly have a gestation period of 19–21 days (Murray et al. 2010), gestation in humans on average lasts around 40 weeks. The differentiation method described above is a one-step approach directly inducing iPSCs to differentiate into TM-like cells. Two-step approaches have been developed to generate human iPSC-TM by first inducing embryoid bodies (EBs) or neural crest cells (NCCs) from iPSCs. EBs derived from iPSCs efficiently attach to ECM-coated plates and differentiate into iPSC-TM in the human pTM-conditioned medium (Abu-Hassan et al. 2015). For some cell types formation of EBs is an important initial step, which can influence the cell differentiation process (Brickman and Serup 2017). However, differentiation of iPSCs towards TM-resembling cells might not rely on this initial EB formation. Generating iPSC-TM from iPSCs via an NCCs stage, which can be cryopreserved and thawed, provides a stable and high output cell resource from iPSCs for continuous differentiation towards TM-resembling cells (Kumar et al. 2020). Despite these improvements in culture conditions, iPSC-TM generation remains problematic for clinical applications due to inconsistent differentiation efficiency and long-term in vitro culture. Additional concerns include the use of non-human material, such as fetal bovine serum (FBS), and the use of primary human cells that could contain unrecognized infectious agents. To circumvent these problems, Wang et al. proposed a two-step differentiation method for human iPSCs using a xeno- and feeder-free culture system relying on recombinant cytokines. They characterized two stages of iPSCs differentiation in pTM-conditioned medium and identified receptors that are both highly expressed and associated with the differentiation at each stage. Subsequently, they used recombinant cytokines that bind to these receptors, including transforming growth factor-β1 (TGF-β1), nerve growth factor-β (NGF-β), erythropoietin, prostaglandin F2 alpha (PGF2α), and epidermal growth factor (EGF) to induce differentiation (Wang et al. 2021). By doing so, they eliminated sources of potential contamination, enhanced the differentiation efficiency, and shortened the duration of in vitro culture. While the success of this approach is highly dependent on iPSC viability and quality, it represents an important step toward production of iPSC-TM for clinical use.

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3D Models

TM cell behavior is significantly influenced by the properties of the substrate, topography, and mechanical environment (Gasiorowski and Russell 2009; Li et al. 2022; Lamont et al. 2021). For example, substrate compliance causes changes in the TM cytoskeleton and elastic modulus, and the pore size in collagen scaffolds influences cell proliferation (Osmond et al. 2020). Topographical cues, such as the culture on a planar surface or groove-patterned nano-surface, lead to profound alternations in MYOC expression and TM cytoskeleton orientation. In vivo the TM has a 3D porous structure with three layers that fulfill different responsibilities in AH outflow (Castro and Du 2019). Consequently, appropriate 3D-engineered biomimetic tissue models may be required for mimicking in vivo TM architecture and to fully reflect TM biology. To date, a variety of FDA-approved scaffolding materials, including naturally-derived and synthetic hydrogels and biocompatible synthetic polymers, and electrospun nanofibers, have been used to create 3D-engineered TM models (Schlunck et al. 2008; Torrejon et al. 2013; Waduthanthri et al. 2019; Xue et al. 2019; Lu et al. 2020; Li et al. 2021). An example of an iPSC-based 3D model has been provided by Tian et al. (2020). iPSC-TM cells cultured on porous SU-8 scaffolds form a multilayer structure in an elongated and aligned pattern. These iPSC-derived TM cells in this 3D model not only exhibit TM morphology but also possess numerous TM-like characteristics, such as the capacity to deposit ECM, expression of TM biomarkers, glucocorticoidinducible morphological changes, and expression of MYOC. Importantly, iPSC-TM grown within the pores of this 3D structure influence fluid outflow and thereby mimic the functional role of the TM in the eye. Thus, 3D models combine the enormous potential of iPSC to generate large amounts of TM-like cells with the ability to screen for drugs designed to increase AH outflow and lower IOP within a very controlled environment. Another exciting possibility of this technology could be to examine the influence of genetic factors associated with elevated IOP in patients and the development of personalized therapy. Given the complex interplay between the TM and the underlying AH outflow structures, the next goal of 3D TM modeling has been to separately engineer TM layers and the inner wall of SC. These structures may then be assembled to create a functional biomimetic TM.

4.4

Bioreactor

TM cells are sensitive to mechanical signals and express many mechanosensing receptors or pathways responders, including responses to integrin deformation (Filla et al. 2017), NO signaling (Reina-Torres et al. 2021), caveolin signaling (De Ieso et al. 2020), and expression of mechanosensitive ion channels (Chen et al. 2022). It has been demonstrated that mechanical stretch of TM cells can induce expression changes in genes associated with steroid biosynthesis, glycerolipid metabolism, ECM–receptor interaction, ECM modification, cytoskeletal regulation, and stress responses (Chen et al. 2022; Youngblood et al. 2020). However, the current static

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culture systems are not ideal for modeling the highly dynamic events characteristic of TM mechano-biology in vivo. Therefore, to better understand the outflow physiology and facilitate mechano-drug discovery targeting TM, scientists have developed in vitro bioreactors or lab-on-a-chip systems incorporating mechanical cues into organ perfusion models. Among them, an intriguing dynamic model has been created using millifluidic technology to apply constant shear stress to 3D-cultured TM cells (Yarishkin et al. 2021). Tirendi et al. compared these models to static culture systems and concluded that bioreactor-based cell culture models mirror the in vivo microenvironment more accurately and are more appropriate for investigating the long-term responses of the TM to stimuli (Tirendi et al. 2020). For example, in an advanced 3D model with a constant medium flow (70 μl/min), TM cells can be maintained in a healthy status due to good nutrient supply and waste expulsion, which, in turn, facilitates the discovery of long-term molecular changes of TM cells in response to oxidative stress. This model can not only accurately mirror chronic stress in vivo but also provides continuous shear stress to TM cells (Zhao et al. 2016). However, given that stretch is the most recognized mechanical cue in TM (Liton and Gonzalez 2008), in vitro bioreactors with long-term treatment of stretch should be developed in the future.

4.5

Glaucoma Models

While models using healthy TM cells are helpful in elucidating the biological functions of the tissue and those mechanisms required to maintain normal IOP, models representing glaucomatous TM are essential in understanding the pathogenesis of TM changes that lead to the development of elevated IOP open-angle glaucoma (Fig. 1). Currently, the most recognized glaucoma TM models in vitro are generated by exposing pTM cells grown in the culture plates or 3D-engineered models to glucocorticoids, TGF-β, chronic oxidative stress, mechanical stretch, or by expressing mutant genes relevant to glaucoma (Vranka and Acott 2017; Raghunathan et al. 2015; Torrejon et al. 2016; Chen et al. 2021; Xiong et al. 2021). Arguably pTM cells isolated from glaucoma donor eyes are most appropriate to examine pathological changes associated with the disease, but scientists wishing to use glaucoma pTM as a model are confronted by many difficulties. These include: (1) significantly decreased TM cellularity in glaucoma eyes (Kuehn et al. 2021; Alvarado et al. 1984); (2) low viability of TM cells from eyes with glaucoma (Castro and Du 2019); (3) limited supply of glaucoma donors; (4) physiological changes introduced by long-term exposure to glaucoma medications or resulting from surgeries; and (5) difficulties to provide cell culture conditions that reflect the glaucoma associated changes in the TM microenvironment (Schnichels et al. 2021). Nevertheless, many laboratories have successfully used glaucomatous pTM resulting, for example, in the discovery of mTOR signaling and autophagic pathway in TM pathophysiology (Porter et al. 2014).

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These concerns were partially addressed by the creation of an immortalized stable cell line, designated GTM3. This line was generated in 1992 through transformation of pTM cells from a POAG patient with SV-40, similar to the HTM5 line described above. Initial findings demonstrated that GTM3 cells are stiffer than controls which is a typical phenotype of glaucomatous TM cells (Pang et al. 1994). GTM3 have since been used extensively and their use not only revealed that glucocorticoidinduced ocular hypertension is linked to glucocorticoid receptor GRβ, serinearginine rich proteins (SRps), and canonical Wnt signaling, but has also aided investigation into the role of TFG-β in ECM remodeling (Jain et al. 2012; Sugali et al. 2021). In addition, this line has been used to test the therapeutic efficiencies of investigative glaucoma medications, such as anoctamin-6, nipradilol, timolol, latanoprost, mitochondrial-targeted antioxidants XHB-5-131, and ROCK inhibitor Y27632 (Banerjee et al. 2017; Chen et al. 2020). Finally, glaucoma pathophysiology in the TM may also be investigated using patient-specific iPSC-TM. Elevated IOP can be caused by mutations in the myocilin gene, but it is also associated with multiple genetic loci and it is reasonable to assume that at least some of these variants affect the function of TM cells (Choquet et al. 2017; Gao et al. 2018; Hysi et al. 2014; Huang et al. 2019). iPSCs from patientspecific somatic cells have been successfully generated and differentiated into retinal ganglion cells (Teotia et al. 2017; Tucker et al. 2014), but iPSCs used for TM research have not yet been reported. Studies using iPSCs of POAG patients may point out previously unknown aspects of TM pathophysiology related to abnormal conventional outflow. These, in turn, will provide novel targets for pharmaceutical intervention.

5

iPSC-Based Therapy for the Damaged TM

Multiple studies have indicated that loss of TM cells is a common phenomenon in aging and that TM cell loss is particularly severe in glaucoma (Mallick et al. 2021; Alvarado et al. 1981, 1984; Babizhayev and Yegorov 2011). Studies indicate that AH outflow is accompanied by the loss of TM cells (Saccà et al. 2015) and conversely that the restorative effects of laser trabeculoplasty are related to an increase in TM cellularity (Bylsma et al. 1988). However, effective treatments to restore TM cellularity in glaucoma and rebuild the damaged tissue do not currently exist. Toward that goal, a number of research groups have utilized various types of stem cells in an effort to regenerate damaged TM in POAG and subsequently lower IOP (Yun et al. 2016). These include mesenchymal stem cells (MSC) (ManuguerraGagné et al. 2013), endogenous TM stem cells (TMSC) (Xiong et al. 2021; Raviola 1982), and iPSC (Zhu et al. 2016; Abu-Hassan et al. 2015). Here, we will focus on the use of iPSCs in TM regeneration, the therapeutic effects in multiple glaucoma models, and the mechanism underlying regeneration. In addition, we will also discuss the intrinsic challenges of iPSCs for clinical use (Fig. 3).

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Fig. 3 iPSC-based therapy for trabecular meshwork. In iPSC-based therapy transplanted iPSCderived TM cells restore TM function of Tg-MYOCY437H mice, GC1-/- mice, and in human eyes maintained in a Perfusion Organ Culture (POC) system (Created with BioRender.com)

5.1

TM Regeneration in Mouse and Human

iPSCs were first generated in 2006 by introducing four transcription factors, Oct4, Sox2, Klf4, and c-Myc into somatic cells (Takahashi and Yamanaka 2006). Since then, multiple strategies have been developed to improve this methodology, including reducing the potential for tumorigenesis by omitting c-Myc (Li et al. 2011), increasing reprogramming efficiency through regulation of somatic cell cycle gene Lin28 (Yu et al. 2007), and decreasing mutation rates by using delivery approaches that do not require chromosomal integration (Borgohain et al. 2019). These improvements have resulted in the generation of stem cells that can be derived from the intended patient and are ideally suited to treat degenerative diseases, while their autologous source minimizes ethical issues. Multiple research groups, including ours, have been working for several years to adopt this type of stem cell to treat TM degeneration in glaucoma. Transplantation of iPSC-derived TM-like cells generated by pTM-conditioned medium has been used to rescue the glaucomatous phenotype in multiple glaucoma models and models relevant to dysfunctional TM, including (1) Tg-MYOCY437H

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mice with elevated IOP at either early or advanced pathological stages (Zhu et al. 2016, 2017), (2) sGCα1-deficient mice (Thomson et al. 2021; Zhang et al. 2016; Dietlein et al. 2000; Cheng et al. 2020), and (3) ex vivo human perfused eyes where dysfunctional TM was observed due to aging (Abu-Hassan et al. 2015).

5.1.1 Tg-MYOCY437H Mice Mutations in MYOC have been identified as the most common genetic cause of juvenile open-angle glaucoma (JOAG) and POAG (Stone et al. 1997; Alward et al. 1998). The age of onset and severity of disease of this type of glaucoma are related to the location of MYOC mutations. Genetic studies and the clinical data have demonstrated that MYOC harboring the Tyr437His mutation causes a particularly severe form of ocular hypertension (Senatorov et al. 2006). Since 2001, scientists have been working to develop MYOC mutant POAG mouse models. However, MYOC knockout, overexpression, and expression of mouse Tyr437His Myoc in C57BL/6 J mice failed to produce glaucomatous phenotypes (Gould et al. 2004; Kim et al. 2001). In 2011, Zode et al. successfully developed a transgenic glaucoma mouse model (Tg-MYOCY437H) by introducing human Tyr437His MYOC under the control of a constitutive promoter. In these mice, MYOC is incompletely secreted from the cell and aggregates continuously in the endoplasmic reticulum (ER), leading to ER stress, an unfolded protein response (UPR), TM cell loss, increased IOP, and subsequent vision loss (Zode et al. 2011). However, the overall structure of the TM remains relatively undisturbed. This glaucoma mouse model is ideal for the study of glaucoma pathophysiology, particularly those related to TM dysfunction. In newborn Tg-MYOCY437H mice, TM structure and function in controlling AH outflow are relatively normal compared to age-matched littermates. However, aggregation of human Tyr437His MYOC significantly increases IOP and decreases outflow facility, an inverse numerical index of hydrodynamic AH flow resistance of TM (Kasetti et al. 2016). Both parameters indicate that the aggregation of Tyr437His MYOC induces abnormal AH outflow in TM in 4-month-old Tg-MYOCY437H mice. This finding is accompanied by other observations related to an increase of IOP, including changes in TM structure, loss of TM cells, progressive loss of RGCs, and optic nerve axonal damage (Kasetti et al. 2016; Chou et al. 2014). Of note, the genetic background of Tg-MYOCY437H mice significantly influences the severity of glaucoma (McDowell et al. 2012). For example, a mixed background of C57BL/6 J and Swiss James Lambert (SJL) results in higher IOP in Tg-MYOCY437H than on a pure C57BL/6 J background. As such, 4-month-old Tg-MYOCY437H mice on a mixed background of 50% C57BL/6 J and 50% SJL can be considered at an early pathological stage of glaucoma and used to examine the role of iPSC-TM in tissue regeneration. As reported, transplantation of purified mouse iPSC-TM cells significantly lowers IOP and enhances AH drainage from the eyes (Zhu et al. 2016). Six weeks after transplantation, the IOP of Tg-MYOCY437H mice having received iPSC-TM significantly decreased and AH outflow increased. These therapeutic effects of iPSC-TM were sustained until the last measurements 9 weeks after transplantation. Here, not only were AH dynamics

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and IOP homeostasis restored, but the decrease in IOP resulted in significant protection of RGC as well. iPSC-TM therapy has also been applied in 6-month-old Tg-MYOCY437H mice, which exhibit more severe damage in TM cellularity and function than younger animals (Zhu et al. 2017). Six weeks after the transplantation of purified iPSC-TM cells these older mice only displayed a modest decrease in IOP and increase in AH outflow. However, after 12 weeks IOP significantly decreased and AH outflow increased (Zhu et al. 2017). It remains unexplained why the TM of older mice requires a longer period of time to regenerate after iPSC-TM transplantation, but one possibility is that the severity of TM damage accumulates in an age-dependent and requires an increasingly long time to reverse. These studies demonstrated for the first time that transplantation of iPSC-TM cells can effectively regulate AH outflow capacity in glaucoma eyes and suggest a feasible strategy for using autologous iPSCs to regenerate TM damage in POAG patients.

5.1.2 sGCa1-Deficient Mice The ability of iPSC-TM to repair AH outflow was also demonstrated in the guanylyl cyclase (GC)-1α subunit knockout (GC1-/-) mouse (Buys et al. 2013). In aged GC1-/- mice TM cellularity is significantly decreased when compared to age-matched wild-type mice (Buys et al. 2013). Although the mechanism by which GC knockout leads to decreased TM cellularity is poorly understood, it is a second, independent, model to test the therapeutic effect of iPSC-TM. GC1-/- mice are maintained on the 129/SvEv genetic background and thus iPSCs derived from fibroblasts of the same strain have been used. Analogous to the observations in Tg-MYOCY437H mice, the elevated IOP in 11-month-old GC1-/- mice was significantly 7 weeks after transplantation (Cheng et al. 2020). These findings imply that iPSC-TM are able to restore TM function in individuals with a variety of genetic backgrounds. The data further demonstrate iPSC-TM may be able to reverse TM pathology due to several distinct damage mechanisms. This is encouraging and suggests that personalized iPSC-TM may not only benefit individuals with POAG due to MYOC mutations but also those with other forms of POAG. 5.1.3 TM Regeneration in Human Eyes Anterior segments of the eye maintained in a Perfusion Organ Culture (POC) system enable scientists to test iPSC-TM in human tissue regeneration. Such eyes may either display an age-related decline in TM cellularity, experimentally damaged TM, or may be obtained from glaucomatous donors. Human anterior segments maintained in this POC system exhibit AH outflow in the normal range of 0.2–0.4 μl/min/ mmHg, yet a continuous culture of 2 additional weeks often leads to either an abnormal increase or decrease in AH outflow facility. In contrast, iPSC-TM treated eyes retain AH outflow in the normal range, indicating that iPSC-TM have the capacity to preserve post-mortem TM (Zhu et al. 2020). Eyes receiving iPSC-TM also displayed a significantly higher TM cell density when compared to the untreated contralateral eyes. Likewise, anterior segments with experimentally damaged TM lose the capacity to adjust the outflow resistance when subjected to a two-fold

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pressure challenge. This functional ability of the TM can be restored in iPSC-TM transplanted eyes (Abu-Hassan et al. 2015). These data suggest that dysfunctional human TM can also be restored by the transplantation of human iPSC-derived TM-like cells. While experimental proof that TM function can be restored in donor eyes with naturally occurring POAG is still lacking, these findings represent important steps toward translation of stem cell-based therapy.

5.2

Mechanism of TM Regeneration

One of the most consistent findings in the TM of eyes that have received iPSC-TM transplantation is a marked increase in the density of cells in the tissue. Transplantation of iPSC-TM in 4-month-old Tg-MYOCY437H mice led to a 2.1-fold increase in cellular density (Zhu et al. 2016). Similarly, 6-month-old Tg-MYOCY437H mice receiving iPSC-TM displayed a 1.7-fold higher cell population in the TM than animals receiving PBS injections (Zhu et al. 2017). However, in both studies the number of iPSC-TM embedded in the tissue was very limited. This phenomenon was also observed in transplantation studies using GC-/- mice and human ex vivo models (Cheng et al. 2020; Zhu et al. 2020). One explanation of this finding is that functional restoration of the TM by iPSC-TM is due to repopulation of the tissue by proliferation of endogenous TM cells rather than implantation of iPSC-TM. This hypothesis is supported by the fact that significantly more TM cells of human eyes treated with iPSC-TM are positive for markers associated with cell division than in control eyes (Zhu et al. 2020). To explore this mechanism further, an in vitro co-culture system has been developed. Co-culture of primary TM (pTM) and iPSC-TM noticeably increases pTM proliferation rates when compared to pTM cultured alone. Interestingly, this effect can only be observed when direct cell–cell contact between the pTM and the iPSC-TM is allowed, excluding a role for secreted cytokines in the stimulation of cell proliferation (Zhu et al. 2016, 2017, 2020; Sui et al. 2021). Furthermore, this iPSC-TM mediated increase of pTM cell division can be blocked by treatment with the gap junction inhibitors carbenoxolone or flufenamic acid, suggesting a crucial role for gap junctions in iPSC-TM mediated TM regeneration (Sui et al. 2021). Together, these studies suggest the increased proliferation of endogenous TM cells as a result of their interaction with iPSC-TM is an important mechanism in the functional restoration of the tissue (Fig. 4).

5.3

Challenges for Clinical Translation

Despite the progress made in pre-clinical models, significant hurdles remain before iPSCs mediated regeneration of TM can be attempted clinically. These include: (1) instability of the genome after reprogramming (Jain et al. 2017); (2) epigenetic changes caused by reprogramming. These changes are usually associated with pathological disorders, especially cancer, which is always a concern for iPSCbased therapy (Du and Che 2017); (3) immune rejection of the transplanted tissue

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Fig. 4 Mechanism of TM regeneration by iPSC-based therapy. Transplanted iPSC-derived TM cells (green) can restore TM function by stimulating endogenous TM cell division (brown) (Created with BioRender.com)

(Xu et al. 2019). Cell therapy for TM regeneration may benefit from anterior chamber-associated immune deviation (ACAID), an ocular response to inhibit immune defense against ocular antigens and infections (Biros 2008). This may be the reason that immune responses in the TM after cell transplantation have not observed (Zhu et al. 2017). However, it is unclear if ACAID will provide sufficient protection in all patients; (4) uneven efficiency of current differentiation protocols (Zhu et al. 2016), as discussed earlier; (5) need to remove iPSC-TM retaining pluripotency prior to transplantation. We previously demonstrated that transplantation of iPSC-TM containing SSEA-1-positive cells, indicating pluripotency of cells, frequently leads to the formation of teratomas in the transplanted eyes (Zhu et al. 2016). Multiple successive rounds of purification can lower the SSEA-1-positive ratio in iPSC-TM cells, but may also influence cell viability which is particularly critical for the efficacy of cell therapy; (6) lack of healthy iPSC-TM cells derived from patients with inherited glaucoma (Giacalone et al. 2016). In mouse studies, healthy iPSC-TM derived from normal mice was used to treat the degenerative TM of glaucoma mice. Here, immune rejection of the grafted cells was avoided since the recipient mice were syngeneic (Deuse et al. 2019). Likewise, immune rejection can be mitigated in humans when either autologous iPSCs are used or the recipient has the same human leucocyte antigen (HLA) type (Morizane et al. 2017). However, autologous iPSCs from patients with a genetic cause for glaucoma carry the same mutations. As such any implanted iPSC-TM, or new endogenous pTM, will likely exhibit a similar defect and TM regeneration may either not be possible or may be of short duration; (7) non-specific implantation of the transplanted cells in other ocular tissues (Snider et al. 2018) may lead to unexpected side effects. For example, the attachment of iPSC-TM to the cornea might influence corneal transparency. Studies are currently underway to address some of these issues. These include the development of differentiation protocols using a defined set of cytokines to both reduce the need for xenomaterials and to improve the reliability differentiation (Wang et al. 2021). Efforts have also been made to use genome editing techniques to remove deleterious mutations from stem cells derived from donors with inherited eye disease (Burnight et al. 2018; Stone et al. 2021). The “universal” iPSC concept

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has been developed through banking major histocompatibility complex (MHC)matching iPSCs or reducing the expressions of two MHC class molecules in iPSCs, which solves the immune rejection of allotransplantation of iPSCs (Deuse et al. 2019; Morizane et al. 2017). Finally, progress has been made to enhance the efficiency of transplantation and reduce off-target implantation by targeting transplanted cells to the TM using magnetic particles (Snider et al. 2018; Wang et al. 2022).

6

Conclusion

Dysfunction of the TM is the main reason for ocular hypertension and POAG. Among the current treatment options, none can fundamentally restore TM function. Thus, new pharmacological options and technologies, including iPSC mediated TM regeneration, are developed to meet the current clinical requirements. To facilitate clinical translation of new treatments, in vitro modeling to mimic the pathophysiological TM is particularly important. Through this context, it is evident that iPSCs are becoming essential tools in glaucoma modeling and the development of personalized treatments for tissue regeneration. While significant challenges remain recent advances in iPSCs research have made great strides to create treatment plans for glaucoma that are more accurate, personalized, and efficient than current therapies. Acknowledgement This was supported in part by the National Key R&D Program of China (no. 2022YEF0132500) and the Taishan Scholar Youth Expert Program (no. tsqn202103055).

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Harnessing Human Pluripotent Stem Cell-Derived Pancreatic In Vitro Models for High-Throughput Toxicity Testing and Diabetes Drug Discovery Carmen Ching, Elhadi Iich, and Adrian Kee Keong Teo

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Current Available Pancreatic Cell Models for Studying Diabetes . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Human and Animal Cadaveric Islets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Rodent Insulinoma Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Carmen Ching and Elhadi Iich are co-first authors. C. Ching Stem Cells and Diabetes Laboratory, Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Precision Medicine Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore E. Iich Stem Cells and Diabetes Laboratory, Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore A. K. K. Teo (✉) Stem Cells and Diabetes Laboratory, Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Precision Medicine Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. H. Kuehn, W. Zhu (eds.), Human iPSC-derived Disease Models for Drug Discovery, Handbook of Experimental Pharmacology 281, https://doi.org/10.1007/164_2023_655

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2.3 Human Insulinoma Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 hiPSC-Derived Pancreatic β-Like Cell Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 High-Throughput Screening (HTS) Platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 β-Cell Survival . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 β-Cell Proliferation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Insulin Expression/Release . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The long-standing goals in diabetes research are to improve β-cell survival, functionality and increase β-cell mass. Current strategies to manage diabetes progression are still not ideal for sustained maintenance of normoglycemia, thereby increasing demand for the development of novel drugs. Available pancreatic cell lines, cadaveric islets, and their culture methods and formats, either 2D or 3D, allow for multiple avenues of experimental design to address diverse aims in the research setting. More specifically, these pancreatic cells have been employed in toxicity testing, diabetes drug screens, and with careful curation, can be optimized for use in efficient high-throughput screenings (HTS). This has since spearheaded the understanding of disease progression and related mechanisms, as well as the discovery of potential drug candidates which could be the cornerstone for diabetes treatment. This book chapter will touch on the pros and cons of the most widely used pancreatic cells, including the more recent human pluripotent stem cell-derived pancreatic cells, and HTS strategies (cell models, design, readouts) that can be used for the purpose of toxicity testing and diabetes drug discovery. Keywords

Diabetes · Drug screening · High throughput · Human · iPS · Islet · Pancreas · Stem cells · Toxicity · β-cell

1

Introduction

Diabetes is a debilitating disease that negatively impacts a patient’s quality of life. Over the years, the number of individuals diagnosed with diabetes has increased steadily (Saeedi et al. 2019). Type I and II diabetes (T1D; T2D) represent the major types of diabetes, broadly characterized by hyperglycemia and insulin deficiency due to pancreatic β-cell loss or dysfunction (Eizirik et al. 2020). Patients are heavily reliant on consistent blood glucose monitoring and lifelong treatment to manage this disease (Chatterjee et al. 2017). While there are numerous diabetes medications that can help control blood glucose levels (Lau et al. 2021; Chaudhury et al. 2017), the

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continuous increase in diabetes cases and thereby incidence of its comorbidities remains unchanged (Harding et al. 2019). Therefore, there is continued interest to develop new medications to tackle T1D and T2D (Lau et al. 2021). One of the long-standing goals in the diabetes research field is to understand and improve the survival, functionality, proliferative capacity, and maturation of human β-cells, to devise better strategies for effective insulin secretion and to combat diabetes progression. In achieving this, the gold standard of research models has always been the use of bona fide human islets, representing the human system itself (Hart and Powers 2019). However, there is a general lack of human islets for research due to the limited supply of cadaveric samples. Hence, this bottleneck has been overcome by the generation of β-cell lines derived from several species, namely rat, mouse, and human (Skelin et al. 2010; Green et al. 2018). These pancreatic cell models have provided the biomedical industry with access to an unlimited supply of “healthy” β-cells, undoubtedly increasing our knowledge on β-cell biology. However, our understanding of alterations in β-cells under diabetes conditions, especially that in humans, remains limited and incomplete. More recently, the availability of donor-derived human-induced pluripotent stem cells (hiPSCs) that can be expanded and differentiated into any cell type of interest has come under the spotlight for diabetes disease modeling, toxicity testing, and drug discovery (Teo et al. 2013a; Maxwell and Millman 2021; Amirruddin et al. 2020). Importantly, diabetes patient-derived somatic cells can be reprogrammed into hiPSCs, which in turn can be differentiated into pancreatic β-like cells. Unlike the healthy β-cell lines, hiPSCs derived from diabetes patients’ somatic cells carry the patient’s genetic alterations (Teo et al. 2013b), thereby providing patient-specific β-like cells to study the underlying disease mechanisms and to develop therapeutics for targeted treatments. Numerous extensive protocols have been devised thus far to differentiate hiPSCs into β-like cells for studying diabetes disease biology. These protocols mimic the in vivo development and leverage on the use of cocktails of growth factors and small molecules for directing cell fate. Such methods have been largely successful at generating human β-like cells that are insulin-positive and glucose-responsive for research. However, these β-like cells still do not fully recapitulate human cadaveric islets in terms of insulin content and glucose-responsiveness (Maxwell and Millman 2021). Therefore, aside from efforts taken to discover compounds to improve existing differentiation protocols, considerable work has also been performed to improve β-cell maturation, increase insulin content, and glucose-responsiveness of hiPSC-derived β-like cells (Chen 2018). Recent studies have reported the use of high-throughput screening (HTS) methods, which enables the rapid and reproducible testing of a large library of compounds and conditions, as a discovery technique to screen through compounds to achieve the above-mentioned goals (Fig. 1) (Chen 2018; Vandana et al. 2021). Generally, HTS involves the use of automated robotics, liquid handlers, and multiplexing detection systems. The large scale of variables tested can be achieved through miniaturization such as the use of microtiter plates in 96-, 384-, or

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Fig. 1 General pipeline for HTS platforms

1,536-well formats and automation, allowing for the screening of novel or repurposed compounds and drugs at a fast and cost-effective rate (Blay et al. 2020). Leveraging on the different available pancreatic cell models for research, healthy β-cells can be used in the HTS setting for toxicity testing and to tease out drugs that are able to increase β-cell proliferation in hopes of restoring β-cell mass. On the other hand, diseased β-cells derived from diabetes patients or from β-cell lines treated with diabetes stressors (Vogel et al. 2020; Small et al. 2022) are valuable for testing compounds which can restore proper insulin secretion and promote maturation due to diabetes-induced dedifferentiation. This chapter, therefore, aims to review the most commonly used β-cell lines available for research and how their application in HTS allowed for the identification of compounds and targets with a potential role in the treatment of diabetes.

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305

Current Available Pancreatic Cell Models for Studying Diabetes

While there exists human and animal cadaveric islet material for research purposes, they are ultimately limited by quantity and ease of access. As such, there is a need to establish a variety of human and rodent pancreatic cell lines that can be maintained and expanded in vitro. These cell lines can be adopted for toxicity testing and to screen for drugs to induce proliferation with the goal to increase β-cell mass in instances of β-cell loss, a hallmark of diabetes. These cell lines can be subjected to a diabetic milieu to more closely mimic the environment of “diseased” β-cells. They can then be used to screen for novel compounds and drugs, to improve β-cell survival, restore β-cell insulin secretion function, or reinstate β-cell maturity. In the case of HTS with a phenotypic readout, the cell line’s suitability to generate stable reporter through genetic manipulation needs to be taken into account when choosing or designing a cell model. Additionally, since a large amount of cell material is required for the screening process, the rate of proliferation of cell lines also needs to be considered. Thus, it is crucial to evaluate the current available cell models commonly used in β-cell studies, in order to evaluate their suitability for use in screening processes.

2.1

Human and Animal Cadaveric Islets

Cadaveric islets represent the gold standard of research models as they are directly derived from patients or animals and are therefore the most accurate representation of bona fide β-cells. While they are highly relevant for compound screening, they are not readily available in large enough quantities for HTS. Furthermore, islets are heterogenous in cell composition comprised mainly of insulin-secreting β-cells and glucagon-secreting α-cells, among others, which act in an antagonistic manner. When addressing insulin secretion dysfunction from β-cells to combat glucose control in diabetes, the use of islets in HTS may hence confound overall readouts. Moreover, due to the limited lifespan following harvesting, islet cells cannot be easily manipulated to generate stable reporter lines for sustained and continued use. Therefore, despite being closely representative of bona fide β-cells, islet samples are rarely used in HTS. Still, islets are certainly of great value in drug screens at later stages when lesser quantity is required to validate shortlisted compounds. Compound validation in islets will provide greater confidence in screened compounds before moving on to pre-clinical in vivo models and subsequently human clinical trials.

2.2

Rodent Insulinoma Lines

Since cadaveric islets are limited in quantity, there is a need to develop immortalized pancreatic β-cell lines for experimental use. In the past decades, various β-cell lines

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have been isolated or generated, with varied proliferation capacity and glucosestimulated insulin secretion (GSIS) function. These cell lines have been extensively discussed in notable reviews (Skelin et al. 2010; Green and Olson 2011) and will not be covered in the scope of this chapter. Here, we focus our attention on the most highly utilized mouse MIN6 and rat INS-1 pancreatic β-cell lines. MIN6 cell line was originally developed by Miyazaki et al. in 1990 using a simian-vacuolating virus 40 (SV40) antigen in β-cells of IT6 transgenic mouse (Table 1) (Miyazaki et al. 1990). Since then, it has been commonly used for in vitro studies of β-cell function, with sensitivity to glucose concentration and adequate insulin secretion response despite being cultured in high (25 mM) glucose media. However, after long-term culture approaching 60 passages (Cheng et al. 2012), MIN6 cells tend to lose functionality including GSIS response (Cheng et al. 2012; Dowling et al. 2006; O’Driscoll et al. 2006). Nonetheless, due to its high proliferative capacity, ease of culture, and robust insulin secretion function, MIN6 cells continue to be widely used in numerous diabetes studies. Following the generation of MIN6 cells, a rat insulinoma cell line, INS-1, was established in 1992 (Asfari et al. 1992) (Table 1). This cell line is reported to be stable across 80 passages, while retaining its differentiated β-cell phenotype. Although responsive to glucose stimulation, INS-1 cells are not clonal (Merglen et al. 2004) and do not respond with the same magnitude observed in rat islets (Hohmeier et al. 2000), prompting the creation of subclones. INS-1 832/13 cell line (Table 1) was therefore generated via human proinsulin transfection into INS-1 cells, which led to potent response to glucose (Hohmeier et al. 2000), thereby resulting in improved response to stimulus. Similar to INS-1, INS-1 832/13 cells are found to be stable across ~70 passages. However, as insulin is overexpressed through the cytomegalovirus promoter in this cell line, insulin expression cannot be used as a marker of β-cell maturity. As a consequence, this precludes the cell line from being used for the identification of targets that stimulate or repress insulin expression in HTS (Merglen et al. 2004). Still, INS-1 832/13 can be applied for other screens, such as stimulators or repressors of insulin release. In addition to INS-1 832/13, other subclones such as INS-1E have also been derived (Table 1). INS-1E clonal cell line was established without the need for genetic manipulation, but through clonal selection using insulin content and glucose-responsiveness as an indicator (Merglen et al. 2004). This subclone performs similarly to primary rat islets in terms of GSIS, thereby has better electrophysiological properties, and can be kept in culture longer than the parental INS-1 line (Merglen et al. 2004). Usually cultured as monolayer, both MIN6 (Hauge-Evans et al. 2002; Takahashi et al. 2018; Akolpoglu et al. 2021; Kelly et al. 2010), INS-1 (Hunckler and García 2020) and its subclones (Amin et al. 2016) can also be aggregated into 3D spheroids (pseudo-islets), which may be more representative of primary islets (Wassmer et al. 2020; Jiang et al. 2022). These pseudo-islets were shown to respond to certain stimuli in a more physiologically-relevant manner compared to monolayer cultures in HTS (Amin et al. 2016), which will be further discussed in the later part of this chapter. Although not of human origin, rodent β-cell lines are still widely used due to their proliferative capacity, sensitivity to glucose stimulation, ease of manipulation,

Species Mouse

Rat

Rat

Rat

Human

Human

Cell line MIN6

INS-1

INS1 832/ 13

INS-1E

EndoCβH1

EndoCβH2

Insulinoma

Insulinoma

Insulinoma

Insulinoma

Insulinoma

Origin Insulinoma

SV40 T-antigen and hTERT

SV40 T-antigen and hTERT

Clonal selection of INS-1

Human proinsulin transfection into INS-1 cells

Irradiation of pancreatic islets

Method of establishment SV40 T-antigen

Insulin is overexpressed through the cytomegalovirus promoter, hence, cannot be used in HTS for identification of targets that stimulate or repress insulin expression. Can still be applied for screens to identify modulators of insulin release Established without need for genetic manipulation. Performs similarly to primary rat islets in terms of GSIS. Improved electrophysiological properties and can be kept in culture longer than the parental INS-1 line First human β-beta cell line. Mimics characteristics of mature human β-cells and is responsive to glucose stimulation. Closer related alternative to cadaveric human islets Insertion of immortalizing transgenes that can be removed through Cre-mediated excision. Exhibits enhanced functionality

Comments High proliferative capacity, sensitive to media glucose concentration and exhibits adequate insulin secretion response. Loss of functionality develops after long-term culture approaching 60 passages Cell line is not clonal and does not respond to stimulation with the same magnitude as seen in primary rat islets

Table 1 Rodent- and human-derived insulin-secreting cell lines

(continued)

Ravassard, P. et al. A genetically engineered human pancreatic β cell line exhibiting glucose-inducible insulin secretion. J Clin invest 121, 3,589–3,597 (2011) Scharfmann, R. et al. development of a conditionally immortalized human pancreatic

Merglen, A. et al. glucose sensitivity and metabolism-secretion coupling studied during two-year continuous culture in INS-1E insulinoma cells. Endocrinology 145, 667–678 (2004)

References Miyazaki, J. et al. establishment of a pancreatic beta cell line that retains glucoseinducible insulin secretion: special reference to expression of glucose transporter isoforms. Endocrinology 127, 126–132 (1990) Asfari, M. et al. establishment of 2-mercaptoethanol-dependent differentiated insulin-secreting cell lines. Endocrinology 130, 167–178 (1992) Hohmeier, H. E. et al. isolation of INS-1derived cell lines with robust ATP-sensitive K+ channel-dependent and -independent glucose-stimulated insulin secretion. Diabetes 49, 424–430 (2000)

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Human

Human

EndoCβH5

Species

EndoCβH3

Cell line

Table 1 (continued)

Insulinoma

Insulinoma

Origin

SV40 T-antigen and hTERT

SV40 T-antigen and hTERT

Method of establishment

β cell line. J Clin Invest 124, 2087–2098 (2014) Benazra, M. et al. A human beta cell line with drug inducible excision of immortalizing transgenes. Mol Metab 4, 916–925 (2015)

Olleik, H. and Blanchi, B. 254-LB: EndoCßH5 Human Beta Cells – A Unique “Thaw and Go” Model for Accelerating Diabetes Research with Highly Functional and Readyto-Use Human Beta Cells. Diabetes 71, 254-LB (2022)

References

Comments after cell cycle arrest when compared to EndoC-βH1 Inactive form of Cre introduced into the system that can be induced by treatment with tamoxifen (Cre-ERT2). Exhibit enhanced functionality after cell cycle arrest when compared to EndoC-βH1 A pure population of insulin-expressing cells, with insulin content that is similar to primary human islets. GSIS closely follows that of bona fide β-cells

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and low cost for maintenance. These characteristics make these cell lines suitable candidates to be considered for HTS.

2.3

Human Insulinoma Lines

After multiple efforts to generate a human β-cell line, a cell line that recapitulates the characteristics of primary human islets, EndoC-βH1, was finally established in 2011 (Table 1) (Weir and Bonner-Weir 2011). Human fetal pancreatic cells were transduced with SV40 large T-antigen before being transplanted into immunodeficient mice for the formation of insulinomas. These cells were then transduced with the human Telomerase Reverse Transcriptase (hTERT) to generate the first human β-cell line (Ravassard et al. 2011). While this cell line is not suitable for clinical transplantation, its availability provides a much-needed resource for studying and understanding human β-cell biology. These cells mimic the characteristics of mature human β-cells and are also responsive to glucose stimulation, representing a closer related alternative to cadaveric human islets. As mature human β-cells are not expected to be proliferative, there was a need to modify EndoC-βH1 further. Ravassard and colleagues continued to generate EndoCβH2 and EndoC-βH3 cell lines (Table 1), with the intended outcome of being able to conditionally stop proliferation (via excision of immortalizing transgenes) and be more representative of mature human β-cells (Scharfmann et al. 2014; Benazra et al. 2015). EndoC-βH2 employs a Cre-mediated excision of immortalizing transgenes to allow for conditional halting of proliferation which better models human β-cells (Jiang et al. 2022; Weir and Bonner-Weir 2011). EndoC-βH3 is an improved model of EndoC-βH2, whereby tamoxifen-inducible Cre (Cre-ERT2) can be used to excise the immortalizing transgenes (Jiang et al. 2022; Weir and Bonner-Weir 2011). Interestingly, EndoC-βH2 and EndoC-βH3 cell lines exhibit enhanced functionality after cell cycle arrest, as compared to EndoC-βH1 (Scharfmann et al. 2014). To further improve on existing EndoC-βH lines, a fourth line, termed EndoC-β H5, was established (Table 1). This cell line encompasses a pure population of insulin-expressing cells, with insulin content that is similar to primary human islets (Olleik and Blanchi 2022). Moreover, GSIS closely follows that of bona fide β-cells. In the context of HTS, EndoC-βH5 can be employed for use in 384-well plates with highly reproducible data (Olleik and Blanchi 2022). Aggregation into spheroids also allows for detection of robust functionality, representing a closer step toward mimicking native islets in an in vivo setting (Olleik and Blanchi 2022). A possible drawback is the lack of proliferative capacity as the slow proliferation of these cells makes it difficult to generate a stable line, which may limit downstream screening methods.

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hiPSC-Derived Pancreatic b-Like Cell Models

Owing to the exciting discovery of reprogramming, patient-derived hiPSCs can now be generated and then differentiated into an unlimited supply of β-like cells for further studies. In the field of diabetes research, hiPSC-based cell models have been increasingly used to elucidate mechanisms underlying various forms of diabetes such as monogenic, T1D, and T2D (Teo et al. 2013a, b; Amirruddin et al. 2020; Zhu et al. 2016; Shi et al. 2017). Diverse pancreatic differentiation protocols have been established to generate pancreatic β-like cells (Table 2). While this human donorspecific cell-based model has a significant advantage of generating an unlimited supply of β-like cells that are close alternatives to human islets, the model does currently suffer from batch-to-batch heterogeneity and “insufficient maturity” compared to bona fide human islets. Nonetheless, it will complement human β-cell lines and human donor islets in providing a continuous supply of cell material for HTS platforms. hiPSCs can also be manipulated via gene editing to insert reporters or antibiotics followed by clonal selection, allowing for a stable and homogenous platform fit for HTS. Seminal work from the lab of Shuibing Chen has shown the great potential of using hPSC-derived β-like cells for the study of genes and environmental factors in the etiology of diabetes (Zeng et al. 2016; Guo et al. 2017; Amin et al. 2018; Zhou et al. 2018).

3

High-Throughput Screening (HTS) Platforms

A good HTS requires exquisite control of all parameters affecting the final output of the screen. A starting point would be the choice or development of the appropriate cells for the screen. The appropriate cells should be expandable to a sufficient scale for testing in replicates. The cell number, volume per well, and confluence should be optimized for the duration of the screen, taking into account the growth rate of the cells and incubation conditions the cells will be placed in. The cells also need to be amenable to genetic modification in order to add a reporter, for example, or inhibit the expression of a gene in the case of knockdowns or knockouts. In the case of transfections, optimization of transfection components will be necessary to avoid off-target effects or insufficient targeting. For drug screens, the solubility of the compounds tested and the diluent used should not affect the stability or activity of the tested drugs. A difficulty in HTS is the determination of the appropriate concentration of compound to be used when testing multiple drugs to avoid toxicity in non-lethal screens. Generally, one concentration is tested for all drugs to determine if there is an effect in the primary screen, after which a titration of selected hits is performed to determine the minimum dosage necessary for drug activity. This could mean that for certain drugs, the concentration used in the primary screen could be either too high and induce toxicity or too low and be excluded from further downstream studies. The assay readout will also need to be optimized to distinguish between a real signal versus background noise. As such, using the appropriate plate type, format,

Pagliuca et al. (2014)

Day 2

8 mM glucose

3

Day 1

8 mM glucose

Duration (days)

Growth factors

0.1 μM GSK3bi (MCX928)

1 μM GSK3bi (MCX928)

MCDB131

100 ng/ml GDF8

100 ng/ml GDF8

Media

0.5% FAF-BSA

0.5% FAF-BSA 100 ng/ml GDF8

0.5% FAF-BSA

1.5 g/l NaHCO3

1.5 g/l NaHCO3

1.5 g/l NaHCO3

Day 3 10 mM glucose

Day 2

10 mM glucose

Growth factors

10 mM glucose

3

Duration (days)

Day 1

MCDB131

Media

Rezania et al. (2014)

Definitive endoderm

Stages

Papers

8 mM glucose

3

MCDB131

0.25 mM VitC

50 ng/ml FGF7

0.5% FAF-BSA

1.5 g/l NaHCO3

10 mM glucose

2

MCDB131

Primitive gut tube

Table 2 List of hiPSC differentiation protocols, 2014–current

8 mM glucose

Day 7

2

8 mM glucose

20 mM glucose

Day 9–13

7

20 mM glucose

1:200 ITS-X

1:200 ITS-X

Day 8

200 nM LDN

100 nM LDN

MCDB131

100 nM TPB

200 nM TPB

MCDB131

10 μM ALK5iII

0.25 μM SANT

0.25 μM SANT

20 mM glucose

3

MCDB131

100 nM LDN

0.1 μM RA

0.25 μM SANT

50 nM RA

2% FAF-BSA

1.5 g/l NaHCO3

20 mM glucose

1 μM RA

Day 14–16

BLAR 3

0.25 mM VitC

2 ng/ml FGF7

2% FAF-BSA

2.5 g/l NaHCO3

10 mM glucose

3

BLAR

Pancreatic endoderm

0.25 mM VitC

50 ng/ml FGF7

2% FAF-BSA

2.5 g/l NaHCO3

10 mM glucose

2

MCDB131/BLAR

Posterior foregut

Pancreatic endocrine precursors

10 μg/ml heparin 1:200 ITS-X

10 μg/ml heparin 10 μM ZnSO4

10% FBS

21–35

(continued)

10 μM ZnSO4

10 μM Trolox

1 μM T3

CMRL1066

2 μM R428

1 mM N-Cys

1 μM T3

10 μM ALK5iII

2% FAF-BSA

1.5 g/l NaHCO3

20 mM glucose

7–15

BLAR

Maturing β-cells

100 nM GSiXX

1 μM T3

10 μM ALK5iII

100 nM LDN

2% FAF-BSA

1.5 g/l NaHCO3

20 mM glucose

7–15

BLAR

Immature β-cells

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50 ng/ml FGF7

2% FAF-BSA

0.25 mM VitC

100 ng/ml Activin A

1:50000 ITS-X

2%FAFBSA

3 μM GSK3Bi

0.25 mM VitC

100 ng/ml Activin A

2.44 mM glucose 1.23 g/l NaHCO3

Day 2–3

2.44 mM glucose

2.46 g/l NaHCO3

Day 1

2.46 g/l NaHCO3

Growth factors

3

MCDB131

1:50000 ITS-X

2.44 mM glucose

MCDB131

3

Duration (days)

Millman et al. (2016)

0.25 mM VitC

2.46 g/l NaHCO3

2.46 g/l NaHCO3

1:50000 ITS-X

1.23 g/l NaHCO3

Definitive endoderm

2% FAF-BSA

Primitive gut tube

Media

Stages

Papers

Table 2 (continued)

0.25 μM SANT1 500 nM PdbU

0.25 μM SANT1 500 nM PdbU (PKC inducer)

MCDB131

1.23 g/l NaHCO3

2.44 mM glucose

Day 7

2

1.23 g/l NaHCO3

2.44 mM glucose

Day 8

100 nM RA

2 μM RA

200 nM LDN

1:200 ITS-X

50 ng/ml FGF7

0.25 mM VitC

2% FAF-BSA

1.23 g/l NaHCO3

1:200 ITS-X

50 ng/ml FGF7

0.25 mM VitC

2% FAF-BSA

1.23 g/l NaHCO3

Posterior foregut

1.23 g/l NaHCO3

2.44 mM glucose

5

MCDB131

0.25 μM SANT1

100 nM RA

1:200 ITS-X

50 ng/ml FGF7

0.25 mM VitC

2% FAF-BSA

1.75 g/l NaHCO3

20 ng/ml Betacellulin 10 μg/ml heparin

1 μM T3 20 ng/ml Betacellulin

MCDB131

1.75 g/l NaHCO3

20 mM glucose

Day 14–17

7

1.75 g/l NaHCO3

20 mM glucose

Day 18–20

1 μM T3

10 μM ALK5iII

10 μg/ml heparin

10 μM Alk5iII

1 μM GSiXX

1 μM GSiXX

25 nM RA

0.25 μM SANT1 100 nM RA

1:200 ITS-X

0.25 mM VitC

2% FAF-BSA

1.75 g/l NaHCO3

1:200 ITS-X

0.25 mM VitC

2% FAF-BSA

1.75 g/l NaHCO3

Pancreatic endoderm

Pancreatic endocrine precursors

1 μM T3

10% FBS

CMRL1066

10 μM ALK5ill

1 μM T3

Immature β-cells

Maturing β-cells

312 C. Ching et al.

VelazcoCruz et al. (2019)

0.25 mM VitC

100 ng/ml Activin A

1:50000 ITS-X

30 μM GSK3bi

0.25 mM VitC

100 ng/ml Activin A

1.23 g/l NaHCO3

2.46 g/l NaHCO3

2% FAF-BSA

1:50000 ITS-X

0.25 mM VitC

100 ng/ml Activin A

2.46 g/l NaHCO3

2% FAF-BSA

1:50000 ITS-X

0.25 mM VitC

100 ng/ml Activin A

50 ng/ml FGF7

0.25 mM VitC

1:50000 ITS-X

2% FAF-BSA

2.44 mM glucose

Day 2–3

2.44 mM glucose

Growth factors

MCDB131 3

Day 1

Duration (days)

1:50000 ITS-X

50 ng/ml FGF7

0.25 mM VitC

2% FAF-BSA

2.44 mM glucose

MCDB131

3

Media

1:50000 ITS-X

2% FAF-BSA

2% FAF-BSA

2 μM RA 0.25 μM SANT1 10 μM Y27632 500 nM PdbU

2 μM RA 0.25 μM SANT1 10 μM Y27632 200 nM LDN

50 ng/ml FGF7

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.23 g/l NaHCO3

2.44 mM glucose

1

MCDB131

500 nM PdbU

50 ng/ml KGF

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

50 ng/ml KGF

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

50 ng/ml FGF7

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.23 g/l NaHCO3

2.44 mM glucose

5

MCDB131

5 ng/ml Activin A

10 μM Y27632

0.25 μM SANT1

0.1 μM RA

50 ng/ml KGF

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

10 μM Alk5i 10 μg/ml heparin 20 ng/ml Betacellulin

1 μM XXI 10 μM Alk5i 10 μg/ml heparin

1 μM ZnSO4 1 ml/L trace elements A

0.1 μM RA

NEAA

10 μg/ml heparin

2% FAF-BSA

2.55 mM glucose

7–35

MCDB131

10 μM ALK5ill

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.75 g/l NaHCO3

20 mM glucose

7

MCDB131

20 ng/ml Betacellulin

1 μM XXI

1 μM T3

1 μM T3

25 nM RA

0.1 μM RA 0.25 μM SANT1

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

(continued)

Harnessing Human Pluripotent Stem Cell-Derived Pancreatic In Vitro. . . 313

MCDB131

3

Media

Duration (days)

Growth factors

2% FAF-BSA

1:50000 ITS-X

0.25 mM VitC

100 ng/ml Activin A

2% FAF-BSA

1:50000 ITS-X

0.25 mM VitC

100 ng/ml Activin A

3 μM GSK3bi

1.23 g/l NaHCO3

2.46 g/l NaHCO3

2.46 g/l NaHCO3

50 ng/ml FGF7

0.25 mM VitC

1:50000 ITS-X

2% FAF-BSA

2.44 mM glucose

Day 2–3

2.44 mM glucose

Day 1

3

MCDB131

Primitive gut tube

2.44 mM glucose

3 μM GSK3bi

Veres et al. (2019)

Definitive endoderm

Stages

Papers

Table 2 (continued)

5 ng/ml Activin A

200 nM LDN

2 μM RA 0.25 μM SANT1

0.25 μM SANT1

50 ng/ml FGF7

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.23 g/l NaHCO3

2.44 mM glucose

2 μM RA

50 ng/ml FGF7

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.23 g/l NaHCO3

2.44 mM glucose

Day 7

2

MCDB131

Day 8

10 μM Y27632

10 μM Y27632

0.25 μM SANT1

0.1 μM RA

50 ng/ml FGF7

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.23 g/l NaHCO3

2.44 mM glucose

5

MCDB131

0.25 μM SANT1

0.25 μM SANT1

500 nM PdbU

0.1 μM RA

1 μM T3

1 μM XXI

1 μM T3

25 nM RA

0.1 μM RA 0.25 μM SANT1

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.75 g/l NaHCO3

20 mM glucose

Day 18–20

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.75 g/l NaHCO3

20 mM glucose

Day 14–17

7

MCDB131

20 ng/ml Betacellulin

10 μg/ml heparin

10 μM Alk5ill

1 μM XXI

1 μM T3

0.25 μM SANT1

Pancreatic endoderm

2 μM RA

Posterior foregut

Pancreatic endocrine precursors

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.23 g/l NaHCO3

2.44 mM glucose

MCDB131

1 ml/L trace elements B

Immature β-cells

Maturing β-cells

314 C. Ching et al.

Maxwell et al. (2022)

0.1% FAF-BSA

100 ng/ml Activin A

0.1% FAF-BSA

100 ng/ml Activin A

3 μM GSK3bi

1.2 g/l NaHCO3

1.2 g/l NaHCO3

1.2 g/l NaHCO3

50 ng/ml FGF7

0.25 mM VitC

0.1% FAF-BSA

4.4 mM glucose

Day 2–4

8.9 mM glucose

Growth factors

MCDB131 2

Day 1

Duration (days)

8.9 mM glucose

MCDB131

4

Media

500 nM PdbU

200 nM LDN

50 ng/ml FGF7 0.1 μM RA 0.25 μM SANT1 200 nM LDN 500 nM TPPB

50 ng/ml FGF7 2 μM RA 0.25 μM SANT1 10 μM Y27632 200 nM LDN 500 nM TPPB

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.75 g/l NaHCO3

2.44 mM glucose

4

MCDB131

5 ng/ml Activin A

10 μM Y27632

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.75 g/l NaHCO3

2.44 mM glucose

2

MCDB131

500 nM PdbU

10 μM Y27632

10 μM Y27632

20 ng/ml Betacellulin

10 μg/ml heparin

MCDB131

1 μM XXI 0.25 μM SANT1 0.1 μM RA

0.25 μM SANT1 0.1 μM RA

1 μM T3 1 μM XXI

1 μM T3

10 μM ALK5ill

10 μg/ml heparin

10 μg/ml heparin 10 μM ALK5ill

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.75 g/l NaHCO3

20 mM glucose

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

1.75 g/l NaHCO3

20 mM glucose

Day 13

7 Day 14–19

10 μg/ml heparin

10 μM Alk5ill

20 ng/ml Betacellulin

10 μM Alk5ill

1 μM XXI

1 ml/L trace elements B

1 ml/L trace elements A

1 μM ZnSO4

NEAA

10 μg/ml heparin

2.1% FAF-BSA

2.55 mM glucose

MCDB131

(continued)

Harnessing Human Pluripotent Stem Cell-Derived Pancreatic In Vitro. . . 315

0.1% FAF-BSA

1% Glutamax

100 ng/ml Activin A

0.1% FAF-BSA

1% Glutamax

100 ng/ml Activin A

3 μM GSK3bi

1.2 g/l NaHCO3

1.2 g/l NaHCO3

1.2 g/l NaHCO3

50 ng/ml FGF7

0.25 mM VitC

1% Glutamax

0.1% FAF-BSA

4.4 mM glucose

Day 2–4

8.9 mM glucose

Day 1

Growth factors

2

MCDB131

Primitive gut tube

8.9 mM glucose

MCDB131

4

Duration (days)

Hogrebe et al. (2021)

Media

Definitive endoderm

Stages

Papers

Table 2 (continued)

MCDB131

MCDB131

1 μM T3 1 μM XXI

0.1 μM RA 0.25 μM SANT1 200 nM LDN 0.2 μM TPPB

2 μM RA 0.25 μM SANT1 10 μM Y27632 200 nM LDN

10 μM ALK5ill

10 μg/ml heparin

1% pen/strep

50 ng/ml FGF7

50 ng/ml FGF7

0.25 mM VitC

1:200 ITS-X

1% Glutamax

2% FAF-BSA

1.75 g/l NaHCO3

20 mM glucose

Day 13

7

1:200 ITS-X

0.25 mM VitC

1% Glutamax

2% FAF-BSA

1.75 g/l NaHCO3

2.2 mM glucose

4

1 μM Latrunculin A

20 ng/ml Betacellulin

Pancreatic endoderm

0.25 mM VitC

1:200 ITS-X

1% Glutamax

2% FAF-BSA

1.75 g/l NaHCO3

2.2 mM glucose

2

MCDB131

Posterior foregut

1 μM XXI

1 μM T3

10 μM ALK5ill

10 μg/ml heparin

1% pen/strep

0.25 mM VitC

1:200 ITS-X

1% Glutamax

2% FAF-BSA

1.75 g/l NaHCO3

20 mM glucose

Day 14–19

20 ng/ml Betacellulin

Pancreatic endocrine precursors

1 ml/L trace elements B

1 ml/L trace elements A

1 μM ZnSO4

NEAA

10 μg/ml heparin

2.1% FAF-BSA

2.55 mM glucose

MCDB131

Immature β-cells

Maturing β-cells

316 C. Ching et al.

Balboa et al. (2022)

0.5% FAF-BSA

100 ng/ml Activin A

0.3 μM GSK3bi

0.5% FAF-BSA

100 ng/ml Activin A

3 μM GSK3bi

100 ng/ml Activin A

0.5% FAF-BSA

1.5 g/l NaHCO3

1.5 g/l NaHCO3

1.5 g/l NaHCO3

Day 3 10.44 mM glucose

Day 2

10.44 mM glucose

Growth factors

10.44 mM glucose

Duration (days)

Day 1

MCDB131

3

Media

MCDB131

0.25 mM VitC

50 ng/ml FGF7

0.5% FAF-BSA

1.5 g/l NaHCO3

10.44 mM glucose

3

MCDB131

MCDB131

MCDB131

CMRL1066

0.25 μM SANT1 0.05 μM RA 100 nM LDN

10 μM ALK5iII 1 μM GC1 20 ng/ml Betacellulin

2 ng/ml FGF7 0.25 μM SANT1 0.1 μM RA

200 nM LDN 100 nM TPB 10 ng/ml Activin A

1 μM RA 100 nM LDN 200 nM TPB

0.25 mM VitC

10 μM Y27632

0.25 μM SANT1

100 nM GSiXX

1 μM GC1

10 μM ALK5iII

100 nM LDN

(continued)

0.5 μM ZM447439

1 mM Nacetyl cysteine

10 nM T3

1:2000 lipid concentrate

1:2000 trace elements B

1:2000 trace elements A

10 μM ZnSO4 10 μM ZnSO4

100 ng/ml EGF

0.25 mM VitC

0.5 mM pyruvate

10 μM ZnSO4

10 μg/ml heparin

1:200 ITS-X

2% FAF-BSA

0–42

10 μg/ml heparin

1:200 ITS-X

2% FAF-BSA

1.5 g/l NaHCO3

20 mM glucose

7–8

10 μg/ml heparin

1:200 ITS-X

2% FAF-BSA

1.5 g/l NaHCO3

20 mM glucose

4

0.1 μM RA

0.25 μM SANT1

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

2.5 g/l NaHCO3

10.42 mM glucose

4

1 μM Latrunculin A

0.1 μM RA

0.25 μM SANT1

50 ng/ml FGF7

1:200 ITS-X

2% FAF-BSA

2.5 g/l NaHCO3

10.42 mM glucose

2

MCDB131

0.2 μM TPPB

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Fantuzzi et al. (2022)

0.25 mM VitC

MCDB131

4

Media

Duration (days)

10 μM Y27632

2

MCDB131

100 nM Wnt-C59

50 ng/ml Activin A

100 ng/ml Activin A

0.5% FAF-BSA

50 nM PI103

0.25 mM VitC

0.25 mM VitC

50 ng/ml FGF7

5 μM TGFbi (SB4)

1% B27

1% B27

4.5 mM glucose

2

MCDB131

Primitive gut tube

6 μM GSK3bi

Day 2–4

4.5 mM glucose

Growth factors

Day 1

4

Duration (days)

4.5 mM glucose

MCDB131

Media

Du et al. (2022)

Definitive endoderm

Stages

Papers

Table 2 (continued)

0.2 μM TPB 10 mM nicotinamide

0.1 μM LDN 0.25 μM SANT1

3

MCDB131

4

MCDB131

0.25 mM VitC

0.25 μM SANT1

100 ng/ml EGF

2 μM RA

100 nM Wnt-C59

1% B27

5–6

DMEMbasic

10 mM nicotinamide

0.25 mM VitC

10 μM Y27632

MCDB131 6–7

7–8

MCDB131

2 mM Nacetyl cysteine

100 nM Wnt-C59

0.25 mM VitC

10 μM ZnSO4

10 μg/ml heparin

10 μg/ml heparin 0.1 μM GSiXX

10 μM Forskolin

1 μM T3

0.5 μM R428

10 μM ALK5iII

1% B27

2–4

DMEMbasic

Immature β-cells

10 μM ISX9 (NEUROD1 inducer, 3–6 days)

1 μM T3

0.3 μM LDN

10 μM ALK5iII

1% B27

6

DMEM-basic

100 nM GSiXX

Pancreatic endoderm

1% B27

4

DMEM-basic

Posterior foregut

Pancreatic endocrine precursors

MCDB131

Maturing β-cells

318 C. Ching et al.

Growth factors

0.5% FAF-BSA

100 ng/ml GDF8

0.1 μM GSK3bi (MCX928)

1.5 g/l NaHCO3

0.5% FAF-BSA

100 ng/ml GDF8

1 μM GSK3bi (MCX928)

100 ng/ml GDF8

0.5% FAF-BSA

1.5 g/l NaHCO3

1.5 g/l NaHCO3

10 mM glucose

Day 3 10 mM glucose

Day 2

10 mM glucose

Day 1

50 ng/ml KGF

0.25 mM VitC

0.5% FAF-BSA

1.5 g/l NaHCO3

10 mM glucose

75 μM resveratrol 2 μM R428 1 mM Nacetylcysteine

1 μM GC-1 100 nM GSiXX

0.25 μM SANT-1 100 nM LDN 1 μM GC-1 100 nM GSiXX 10 μM ALK5iII 20 ng/ml Betacellulin

0.1 μM RA 100 nM LDN 200 nM TPPB 10 mM nicotinamide

10 μM ALK5iII

20 μM SP600125

10 μM Trolox

1 μM GC-1

10 μM ALK5iII

0.25 μM SANT1

100 nM LDN

1 μM RA

50 nM RA

50 ng/ml FGF7

0.25 μM SANT1

10 μM ZnSO4

10 μM ZnSO4

10 μM ZnSO4

100 ng/ml EGF

0.25 mM VitC

10 μg/ml heparin

1:200 ITS-X

2% FAF-BSA

1.5 g/l NaHCO3

20 mM glucose

10 μg/ml heparin

1:200 ITS-X

2% FAF-BSA

1.5 g/l NaHCO3

20 mM glucose

10 μg/ml heparin

1:200 ITS-X

2% FAF-BSA

1.5 g/l NaHCO3

20 mM glucose

0.25 mM VitC

1:200 ITS-X

2% FAF-BSA

2.5 g/l NaHCO3

10 mM glucose

50 ng/ml FGF7

1:200 ITS-X

2% FAF-BSA

2.5 g/l NaHCO3

10 mM glucose

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and controls is paramount to identify successful hits for secondary screens and validation experiments. The application of fluorescence might require the use of specific cell culture media as it could affect the fluorescence readouts. As miniaturization is critical for HTS, the effect of the plate format and size on media evaporation should be assessed for the duration of the screen to minimize well-to-well variability. Thus far, the focus for the application of HTS using pancreatic cells has been mainly on identifying targets or drugs capable of increasing β-cell survival, proliferation, or insulin expression and/or secretion. To this end, several studies have relied on the above-described cell models using elaborate culture systems and experimental designs to identify compounds or targets for further downstream studies.

3.1

b-Cell Survival

Autoimmune reactions by infiltrating lymphocytes result in the destruction of β-cells, thereby leading to insufficient insulin production and hyperglycemia in T1D (Grieco et al. 2012). To date, islet transplantation is the only treatment with the potential to provide long-term solution for T1D. Islet transplantation is a limited option due to donor scarcity and complications from transplantation procedures such as increased cell death of transplanted islets, loss of insulin secretion, and side effects from immuno-suppression (Bruni et al. 2014; Ryan et al. 2001, 2005). However, it is estimated that over 70% of transplanted islets are destroyed post transplantation (Hogan 2008). NF-kB is thought to play an integral role in islet cell death as a stressresponsive gene after transplantation and immune infiltration (Kim and Lee 2009; Zhao et al. 2011). To identify targets playing a role in cytokine-induced cell death, Beck et al. performed a 730 non-redundant small interfering RNA (siRNA) pool screen from Dharmacon on human islets from nine donors (Beck et al. 2013). These 730 siRNAs were selected from a previous HTS of 3,850 siRNAs on MIN6 cells. The 730 siRNA screen was performed on dispersed islet cells in 384-well plates and cell viability was assessed using caspase 3/7 activity as measured through fluorescence intensity. In their screen, Beck et al. identified that the knockdown of OTUB2 greatly increased islet cell death. These results were further validated in MIN6 cells treated with inflammatory cytokines, observing a 60% increase in caspase 3/7 activity. The silencing of OTUB2 also impaired insulin secretion in both MIN6 and human islets. Further downstream validation demonstrated OTUB2 to act through the inhibition of NF-kB, thereby playing a role in β-cell survival and having therapeutic potential in T1D treatment. β-cells exposed to fatty acids exhibit defects in glucose-responsiveness and insulin secretion, eventually leading to apoptosis. A number of compounds able to protect β-cells from the deleterious effects of fatty acids have been identified (Green and Olson 2011; Wang et al. 2010; Ahowesso et al. 2015). However, these compounds were selected based on a priori knowledge. As this approach is highly time consuming, a more unbiased approach using HTS could uncover more compounds with the ability to protect β-cells from fatty acid-induced lipotoxicity.

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Lee et al. (2017) developed a HTS assay for fatty acid-induced cell death to screen a library of drugs capable of rescuing β-cell death. To this end, Lee et al. used INS-1 cells which are susceptible to apoptosis by palmitate treatment. For their assay, Lee et al. seeded INS-1 cells into 384-well plates and tested 2,025 compounds derived from multiple libraries (kinase inhibitors, StemSelect, Bioactive Lipid Collection, and Prestwick Chemical Library). Adenosine triphosphate (ATP) levels were used as a measure of viability and were measured using ATPLite luciferase activity assay. From the primary screen, 40 hits were picked for further validation where 35 targets reproduced the primary screen. However, as ATP is not an accurate measure of viability, Lee et al. opted to use propidium iodide as a viability marker. From the secondary screen validation, MAP4K4 was identified as a mediator of palmitateinduced apoptosis. These results were further validated using shRNA and siRNA for MAP4K4. Similar approaches were used by Vogel et al. (2020) and Small et al. (2022) to identify targets capable of protecting β-cells from glucolipotoxicity (GLT). Both groups used INS-1E rat insulinoma cells as a cell model for β-cells cultured with glucose and palmitate. Vogel et al. designed a screen of 312,000 compounds in 1,536-well plate format. In their assay, ATP levels were used as a viability measure using CellTiter-Glo. In order to exclude compounds which reduced caspase activity not resulting from GLT, hits were further profiled in an apoptosis assay using Jurkat cells. From their hits, Vogel et al. identified a compound with the capacity to reduce GLT-induced apoptosis. This compound also protected rat and human islets from increased apoptosis under GLT stress and prevented reduction in GSIS. Mechanism of action studies indicated that the protective effect of this compound is through reduction of calcium influx. Interestingly, unlike canonical calcium channel blockers, the identified target still allows for insulin secretion under calcium channel over-stimulation, which makes it an interesting target for diabetes treatment. Small et al. tested 20,876 compounds from four chemical libraries (Broad institute DOS library, Diversity oriented synthesis-A library, Broad Repurposing Collection, and Bioactive Libraries) in INS-1E cells where they identified 312 hits capable of protecting against GLT (Small et al. 2022). Several of the hits were kinase inhibitors which were screened in 384-well plate format using ATP levels as viability readout. In their downstream validation, Small et al. demonstrated that one of the mechanisms through which some hits conferred protective effects is mediated through reduced calcium flux in β-cells, similar to that reported by Vogel et al. Genome Wide Association Studies (GWAS) have identified approximately 150 loci to confer susceptibility to developing diabetes. One of the identified genes, GLIS3, has been associated with T1D (Winkler et al. 2014), T2D (Cho et al. 2011), and neonatal diabetes (Senée et al. 2006). Glis3-deficient mice show reduced endocrine cell development and lowered compensatory β-cell proliferation (Kang et al. 2009, 2016). Furthermore, the reduction or loss of Glis3 predisposes mice to T1D and T2D development (Dooley et al. 2016). However, the role of GLIS3 in human pancreatic development was unclear. To address this issue, Zhu et al. (2016) generated GLIS3 KO hPSCs and attempted to determine if the human GLIS3 KO β-like cells showed similar dysfunction as mouse KO cells. However,

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their differentiation protocol did not induce GLIS3 expression. This was remedied by Amin et al. (2018) who adjusted the composition of the differentiation cocktail at the stage of pancreatic progenitors to generate β-like cells expressing GLIS3. This resulted in mono-hormonal insulin+ β-like cells expressing high levels of bona fide β-cell markers (NEUROD1, PDX1, NKX6.1, MAFA, UCN3). Using this novel differentiation protocol, Amin et al. showed that GLIS3 KO hESCs have impaired capacity to differentiate to the β-cell lineage due to higher levels of apoptosis without affecting the proportion of glucagon+ cells. There was also increased proportions of ghrelin+ and somatostatin+ cells. To identify compounds capable of rescuing the increased apoptosis in GLIS3 KO β-like cells, Amin et al. designed a high-content chemical screen of approximately 5,000 compounds from multiple libraries (an in-house library of approximately 300 signaling pathway modulators, an epigenetics library (Cayman Chemical), the Prestwick library of FDA/EMA approved drugs, LOPAC (Sigma Aldrich) and the MicroSource library). For their assays, the differentiated cells were dissociated into single cells using accutase and plated onto 804G-coated 384-well plates for 8 h before being treated with either 1 μM or 10 μM of the selected library drugs. After 4 days of culture, the cells were stained with propidium iodide, insulin, and cleaved caspase-3 before imaging. From their primary screen, 23 hits were identified of which one, Galunisertib, showed reproducible and efficacious results. As Galunisertib is known to be TGFβR1 kinase inhibitor, this led the authors to test other known TGFβ inhibitors showing consistent rescue of apoptosis in GLIS3 KO β-like cells. Using a similar approach Zhou et al. (2018) demonstrated the effects of a commonly used pesticide in increasing β-like cell death potentially resulting in diabetes. In their work, Zhou et al. differentiated H1 hESCs into insulin+ β-like cells and plated the dissociated cells on laminin-coated 384-well plates for a chemical screen. Approximately 2,000 compounds from the Phase I Toxicity Forecaster library provided by the US Environmental Protection Agency (EPA) at multiple concentrations were tested. The cells were incubated for 4 days with the selected drugs before being fixed and stained for insulin and DAPI followed by high-content imaging. Compounds which resulted in more than 60% reduction in insulin+ cells and less than 20% insulin- cells were considered positive hits and were selected for follow-up studies. From their screen, two hits were identified, one of which (Vacor) is known to have toxic effects on human β-cells (Karam et al. 1980). The second compound (propargite) is a commonly used pesticide. In their downstream analyses, Zhou et al. showed that propargite did not affect proliferation using their hESCderived β-like cells and MIN6, but induced DNA damage. Interestingly, their work also demonstrated that the cells did not undergo apoptotic but necrotic cell death as caspase-3 activity was not increased, whereas the propargite treated cells released higher levels of high mobility group B1 (HMGB1) protein. They further demonstrated that this effect could be rescued by supplementation with glutathione (GSH). Interestingly, GWAS data suggest that GSTT1 and GSTM1-null genotypes, which are genes involved in GSH conjugation to diverse substrates, are associated with higher risk of developing diabetes (Zhang et al. 2013; Saadat 2013; Pinheiro

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et al. 2013). Zhou et al. proceeded to generate KO lines for these two genes in their hESC β-like cell model and demonstrated that GSTT1-KO β-like cells are more susceptible to cell death after propargite treatment. Altogether, these studies have demonstrated the potential of using HTS to identify promising therapeutics to improve β-cell survival. Downstream experiments have validated the targets streamlined from an initially large library of compounds, showing efficacy and specificity of the screening processes to adequately select for novel compounds.

3.2

b-Cell Proliferation

Small molecules capable of inducing β-cell proliferation in humans are valuable for therapeutic treatment of T1D. T1D patients with long-standing disease still possess residual β-cell mass as shown by Meier et al. who examined samples from T1D donors (Meier et al. 2005). From their findings, the authors concluded that some β-cells were continually regenerating. However, β-cell proliferation is readily observed in rodents but not humans (Dor et al. 2004). Data regarding β-cell proliferation in humans seem contradictory as β-cell proliferation is observed right after birth but drops greatly by late adolescence (Meier et al. 2008). This data was further confirmed by comparing proliferating β-cells in young (30 years) using BrdU incorporation (Perl et al. 2010). Ex vivo culture of human β-cells showed proliferative capacity. However, the proliferating cells showed a dedifferentiation phenotype with lower insulin expression (Russ et al. 2008). These data support a need for the use of compounds to promote β-cell proliferation while also maintaining β-cell identity and function. To address these issues, Walpita et al. developed a culture system for screening dissociated human islets in a HTS manner (Walpita et al. 2012). Islet attachment to culture plates has proven to be challenging as they require extracellular matrix (ECM) for attachment. Walpita et al. used human HTB-9 bladder carcinoma cell line, which produces ECM, to support β-cell function and GSIS (Beattie et al. 1997). HTB-9 cells were cultured to confluence in 96- or 384-well plates before being used to screen a collection of 1,280 G-protein-coupled receptor compounds on co-cultured dissociated islets. Cellular proliferation was assessed using fluorescent staining for Ki-67 and insulin production was assessed by staining for C-peptide. No clear targets were identified from their screen as their focus was to demonstrate feasibility of using primary human β-cells for HTS using their approach. Culture systems using patient material tend to suffer from high levels of donor variability. This was observed by Walpita et al. even for patients with high levels of islet purity and similar BMI, although the number of donors used in this study was very low (n = 3). Another approach to increase β-cell mass in diabetes is through the induction of the oncoprotein c-MYC, a known driver of cellular proliferation (Bretones et al. 2015; Laybutt et al. 2002; Karslioglu et al. 2011). C-MYC was shown to drive proliferation in INS-1 and RINm5F cell lines (Karslioglu et al. 2011). To identify

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compounds capable of inducing c-MYC expression in β-cells, Wang et al. developed an MYC promoter-driven luciferase reporter HTS strategy (Wang et al. 2015). They generated multiple cell lines with the luciferase reporter (INS-1, BTC3, HCT116, and HepG2) but only found HepG2 to yield the most robust and consistent response for their HTS screen. For their screen, they tested 102,300 compounds from two libraries (FDA library n = 2,300 and L1 library chembridge n = 100,000) in 384-well plates. The group identified 4,500 compounds showing the greatest deviation for luciferase activation. Of the 4,500 compounds, 86 were selected for the secondary screen and IC50 determination in primary rat β-cells. From the 86 compounds, only one compound, harmine, was able to induce both an increased c-MYC protein expression in HepG2 and BrdU incorporation in rat β-cells. Harmine also induced BrdU incorporation and Ki-67 labeling when tested in human β-cells. The effects of harmine were independent of glucose concentration and also not specific to β-cells as proliferation was also observed in alpha and ductal cells, albeit not in delta or pancreatic polypeptide cells. Interestingly, harmine seems to also increase INS mRNA expression in human islets, likely due to the induction of PDX1, NKX6.1, and MAFA protein levels. However, insulin content and GSIS were similar to control condition. Since the Wang et al. screen was performed on HepG2 cells and shortlisted targets were based on a non-relevant cell line, it is conceivable that within the excluded targets, some could have achieved the same effects in β-cells. Nonetheless, their team was still able to achieve their initial purpose: to screen for drugs capable of inducing cellular proliferation. Aside from the relevance of type of cells used, inter-species differences will also affect the number and types of hits detected through HTS. For β-cell proliferation, targets which can modulate cell cycle transition genes would be important hits to identify in a HTS. Importantly, a study has identified differences between human and rodent β-cells in terms of the Cyclins and Cyclin Dependent Kinases (CDKs) in promoting β-cell proliferation (Fiaschi-Taesch et al. 2010). Consequently, performing HTS on rodent β-cells might not yield appropriate targets for stimulating human β-cell proliferation. To address these issues, Robitaille et al. developed a HTS assay using primary human islets for an RNAi functional screen (Robitaille et al. 2016). To support attachment of dissociated islets, Robitaille et al. tested six different matrices and surfaces including Matrigel, collagen type 1, poly-D-lysine (PDL), and HTB9 ECM (similar to Walpita et al.) in 384-well plates and found that PDL provided the best attachment as fewer cells were lost after processing for imaging. The authors also noted that the transfection of siRNA libraries using lipofectamine was both inefficient and interferes with β-cell function. Therefore, Robitaille et al. opted for lentiviral transduction of an shRNA library composed of three independent dsDNA sequences for 16 genes involved in cell cycle regulation. Additionally, the islets were transduced with the SV40 large T-antigen as dissociated islet cells alone were not proliferative. In their screen, they allowed the islet cells to incorporate EdU, stained for insulin and imaged using an automated confocal multiwell plate microscope. Interestingly, only a small percentage (up to 3%) of insulin+ cells incorporated EdU after 2 weeks of culture compared to 18% of non-β-cells when

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transduced with SV40 large T-antigen. This percentage increased further by two-tosix folds when p18 or p21 was knocked down with shRNA. Silencing both genes in β-cells also showed synergy and did not affect insulin secretion but showed lower insulin content indicating dedifferentiation, thereby limiting their potential therapeutic use. Current efforts to improve β-cell proliferation have not had the same progress as the efforts of potentiating β-cell survival. This could be largely due to the need for human-specific cell lines for experimentation due to species differences between rodent and human β-cells. Additionally, as human cadaveric islets are limited in supply, coupled with islet heterogeneity and difficulties in culture, HTS relying on the use of patient-derived islets face even greater hurdles before the screening platforms can even be fine-tuned. In the face of these challenges, current strategies have made improvements to islet culturing protocols, which will greatly benefit future endeavors for use of cadaveric islets. Alternatively, hiPSC-derived β-like cells could be a viable alternative for cadaveric islets as these can address many of the mentioned limitations.

3.3

Insulin Expression/Release

Identifying drugs which could enhance insulin secretion or reverse dedifferentiation for T2D patients would be a great step toward reducing the projected increase in diabetes cases. Several groups have attempted to identify compounds or factors crucial for insulin production or release. In 2010, Kiselyuk et al. generated a novel GFP insulin reporter cell line (T6PNE) from TRM6 cells, a cell line derived from human fetal islets expressing PDX1, NEUROD1, and E47, with weak insulin promoter activity (Kiselyuk et al. 2010). The authors chose to use these cells as their low level expression of β-cell genes allows for easy detection of changes in expression levels compared to more mature cells (e.g., INS-1, primary β-cells). For the HTS, a drug library containing 1,040 compounds from the NIH/JDRF custom collection (NJCC) was tested in 384-well plate format. From the primary screen, three compounds of the phenothiazine neuroleptics category were identified to increase GFP expression in reporter cells and were validated at different concentrations to determine dose-responsiveness. Long exposure to these drugs, however, resulted in repression of the insulin gene expression and chronic exposure was toxic to the cells. Although insulin expression is generally used as an indication of β-cell “function,” insulin release is actually a more accurate gauge of β-cell fitness. This is usually measured via insulin/C-peptide ELISA, which is not amenable for HTS and is high in costs. Several groups have attempted to use surrogate markers of insulin secretion through fusion of GFP or luciferase to the insulin propeptide (Liu et al. 2007; Suzuki et al. 2011). However, some of these constructs have hampered proinsulin processing or shuttling. To circumvent these issues, Burns et al. generated a Gaussia luciferase-based insulin reporter where they inserted the luciferase within the C-peptide portion of the prohormone and flanked it by additional prohormone

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convertase cleavage sites (Burns et al. 2015). This allows for comparable expression of luciferase to insulin at a much lower cost and less handling. Burns et al. validated the utility of this construct in INS-1E and MIN6 cells, using a HTS screen with the Pharmakon 1,600 bioactive compounds in 384-well format plates in both low and high glucose conditions. While this screen was not designed to test and identify novel modulators of insulin expression or secretion, it did however identify interesting classes of drugs able to increase luciferase secretion in low glucose. This finding could potentially be used to identify drugs which could result in unwarranted deaththreatening hypoglycemia in relevant patient groups. Other drugs that had additive effects on increasing insulin secretion under high glucose conditions include COX-2 inhibitors (non-steroidal anti-inflammatory drugs) and angiotensin receptor blockers (high blood pressure medication). Interestingly, a number of these drugs have never been associated with modulating insulin secretion. This is potentially due to the higher concentrations used in the screens compared to patient blood levels and a lack of in vivo drug metabolism altering compound activity. A disadvantage of the current assay is that it can detect any perturbation affecting insulin secretion but not expression. Also, this work was performed on rodent cells as they are known to secrete insulin in vitro while the human alternatives were not. However, the authors showed their construct to also be functional in primary human β-cells, indicating its potential application in more relevant cells. Another consideration is the effect of culturing β-cells in 2D format on cell function and its response to compounds. Glibenclamide is an anti-diabetic drug able to stimulate insulin secretion in intact mouse islets (Garcia-Barrado et al. 1996). However, in 2D INS-1E cell cultures, no statistical increase in insulin secretion could be detected. This suggests that the cell culture format is an important factor in identifying compounds or targets which could modulate insulin expression or secretion. To this end, Ramachandran et al. leveraged on the ability of cells to self-aggregate into spheroids without the use of scaffolds, gels, or 3D printers (Ramachandran et al. 2013). Using this method, Amin et al. performed a HTS comparing 2D cultured INS-1E to 3D INS-1E spheroids and re-aggregated human islets in 384-well format (Amin et al. 2016). Insulin secretion was tested using the Alpha-LISA test system. Overall, the 3D spheroids showed better percentages in response to the tested drugs compared to 2D cultures and re-aggregated human islets. Nonetheless, one drawback of the current spheroids is the difficulty of achieving and accounting for differences in sizes as this affects the response to stimuli. This was shown when comparing 3D spheroids’ response to glucose which was lower compared to the other tested conditions (Ramachandran et al. 2013).

4

Conclusion

There is an increasing urgent need for the identification of novel targets or therapeutics for the treatment and management of diabetes. With the current tools available, various strategies to aid β-cell survival, regeneration, and functionality can be identified, as discussed in the examples above (Table 3). The application of HTS

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Table 3 List of HTS publications related to β-cell survival, proliferation, and insulin expression Year 2010 2010 2011 2013 2013 2015 2015 2015 2016 2016 2016 2016 2016 2017 2018 2018 2020 2022

Author Kiselyuk et al. (2010) Hill et al. (2010) Walpita et al. (2012) Beck et al. (2013) Shen et al. (2013) Wang et al. (2015) Burns et al. (2015) Szabat et al. (2015) Amin et al. (2016) Zeng et al. (2016) Kalwat et al. (2016) Robitaille et al. (2016) Zeng et al. (2016) Lee et al. (2017) Amin et al. (2018) Zhou et al. (2018) Vogel et al. (2020) Small et al. (2022)

Outcome Insulin expression Insulin expression Proliferation

Cell source T6PNE

Readout Fluorescence

MIN6/primary human islets Human islet cells

Fluorescence Fluorescence

Survival

Human islet cells

Fluorescence

Proliferation

Human and rat islets

Fluorescence

Proliferation

INS-1/βTC3/HepG2/ HCT116 INS-1/MIN6

Luminescence Luminescence

MIN6

Fluorescence

INS-1

ELISA Fluorescence

Insulin expression Insulin expression Insulin expression Insulin expression Insulin expression Proliferation

INS GFP/WT HES3 cells MIN6

Luminescence

Human islet cells

Fluorescence

Survival

HES3 (hESCs)

Fluorescence

Survival

INS-1

Luminescence

Survival

Fluorescence

Survival

HES3, HUES8, H1 (hESCs) H1 (hESCs)

Fluorescence

Survival

INS-1

Luminescence

Survival

INS-1

Luminescence

Format 384well 96-well 384well 384well 384well 384well 1,536well 96-well 384well 38-well 384well 384well 384well 384well 384well 384well 1,536well 384well

has shown efficacy in screening large amounts of drugs to identify novel non- or low-toxicity compounds for the treatment of diabetes. Coupled with advances in global profiling approaches such as GWAS, next generation sequencing, and genome editing techniques such as CRISPR, HTS allow for reproducible, costeffective, and manageable validation of genes or/and factors playing a role in the susceptibility to developing diabetes. Continuous adaptations and improvements made to cell models, screening techniques, and platforms will allow for improved analytical pipelines and greater certainty of hit identification. Consequently, novel

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avenues for diabetes treatment using either newly identified or repurposed drugs identified in HTS could become available, paving the way for better management of disease progression and patients’ quality of life. Acknowledgments C.C. is supported by the NUS Research Scholarship. A.K.K.T. is supported by IMCB, A*STAR, FY2019 SingHealth Duke-NUS Surgery Academic Clinical Programme Research Support Programme Grant, Precision Medicine and Personalised Therapeutics Joint Research Grant 2019, the 2nd A*STAR-AMED Joint Grant Call 192B9002, NUHSRO/2021/ 035/NUSMed/04/NUS-IMCB Joint Lab/LOA, Paris-NUS 2021-06-R/UP-NUS (ANR-18-IDEX0001), OFIRG21jun-0097, CSASI21jun-0006, MTCIRG21-0071, SDDC/FY2021/EX/93-A147, FY 2022 Interstellar Initiative Beyond grant and H22G0a0005.

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