Gastrointestinal Cancers: An Interdisciplinary Approach: An Interdisciplinary Approach (Interdisciplinary Cancer Research, 4) 3031483707, 9783031483707

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Interdisciplinary Cancer Research  4

Nima Rezaei  Editor

Gastrointestinal Cancers: An Interdisciplinary Approach

Interdisciplinary Cancer Research Volume 4 Series Editor Nima Rezaei Department of Clinical Immunology, Karolinska Institutet, Stockholm, Sweden Cancer Immunology Project (CIP), Universal Scientific Education and Research Network (USERN), Stockholm, Sweden Editorial Board Members Atif A. Ahmed, University of Missouri–Kansas City, Kansas City, MO, USA Rodrigo Aguiar, Universidade Federal de São Paulo, São Paulo, São Paulo, Brazil Maria R. Ambrosio, University of Siena, Siena, Italy Mehmet Artac, Department of Medical Oncology, Necmettin Erbakan University, Konya, Türkiye Tanya N. Augustine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa Rolf Bambauer, Institute for Blood Purification, Homburg, Germany Ajaz Ahmad Bhat, Division of Translational Medicine, Sidra Medical and Research Center, Doha, Qatar Luca Bertolaccini, European Institute of Oncology, Milan, Italy Chiara Bianchini, University Hospital of Ferrara, Ferrara, Italy Milena Cavic, Institute of Oncology and Radiology of Serbia, Belgrade, Serbia Sakti Chakrabarti, Medical College of Wisconsin, Milwaukee, USA William C. S. Cho, Department of Clinical Oncology, Queen Elizabeth Hospital, Kowloon, Hong Kong Anna M. Czarnecka, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland Cátia Domingues, University of Coimbra, Coimbra, Portugal A. Emre Eşkazan, Istanbul University-Cerrahpaşa, Istanbul, Türkiye Jawad Fares, Northwestern University, Chicago, IL, USA Carlos E. Fonseca Alves, São Paulo State University, São Paulo, São Paulo, Brazil Pascaline Fru, University of the Witwatersrand, Johannesburg, South Africa Jessica Da Gama Duarte, Olivia Newton-John Cancer Research Institute, Heidelberg, Australia Mónica C. García, Universidad Nacional de Córdoba, Córdoba, Argentina Melissa A. H. Gener, Children’s Mercy Hospital, Kansas City, MO, USA José Antonio Estrada Guadarrama, Universidad Autónoma del Estado de México, Toluca, Mexico

Kristian M. Hargadon, Gilmer Hall, Hargadon Laboratory, Hampden–Sydney College, Hampden Sydney, VA, USA Paul Holvoet, Catholic University of Leuven, Leuven, Belgium Vladimir Jurisic, Faculty of Medical Sciences, University of Kragujevac, Kragujevac, Serbia Yearul Kabir, University of Dhaka, Dhaka, Bangladesh Theodora Katsila, National Hellenic Research Foundation, Athens, Greece Jorg Kleeff, Martin-Luther-University Halle-Wittenberg, Halle, Germany Chao Liang, Hong Kong Baptist University, Hong Kong, Hong Kong Mei Lan Tan, Universiti Sains Malaysia, Pulau Pinang, Malaysia Weijie Li, Children’s Mercy Hospital, Kansas City, MO, USA Sonia Prado López, Institute of Solid State Electronics, Technische Universität Wien, Vienna, Austria Muzafar A. Macha, Islamic University of Science and Technology, Awantipora, India Natalia Malara, Magna Graecia University, Catanzaro, Italy Adile Orhan, University of Copenhagen, Copenhagen, Denmark Heriberto Prado-Garcia, National Institute of Respiratory Diseases “Ismael Cosío Villegas”, Mexico City, Distrito Federal, Mexico Judith Pérez-Velázquez, Helmholtz Zentrum München, Munich, Germany Wafaa M. Rashed, Children’s Cancer Hospital, Cairo, Egypt Francesca Sanguedolce, University of Foggia, Foggia, Italy Rosalinda Sorrentino, University of Salerno, Fisciano, Salerno, Italy Irina Zh. Shubina, N.N.Blokhin National Medical Research Center of Oncology, Moscow, Russia Heloisa Sobreiro Selistre de Araujo, Universidade Federal de São Carlos, Sao Carlos, Brazil Ana Isabel Torres-Suárez, Universidad Complutense de Madrid, Madrid, Spain Jakub Włodarczyk, Medical University of Lodz, Lodz, Poland Joe Poh Sheng Yeong, Singapore General Hospital, Singapore, Singapore Marta A. Toscano, Hospital de Endocrinología y Metabolismo Dr. Arturo Oñativia, Salta, Argentina Tak-Wah Wong, National Cheng Kung University Medical Center, Tainan, Taiwan Jun Yin, Central China Normal University, Wuhan, China Bin Yu, Zhengzhou University, Zhengzhou, China

The “Interdisciplinary Cancer Research” series publishes comprehensive volumes on different cancers and presents the most updated and peer-reviewed articles on human cancers. Over the past decade, increased cancer research has greatly improved our understanding of the nature of cancerous cells which has led to the development of more effective therapeutic strategies to treat cancers. This translational series is of special value to researchers and practitioners working on cell biology, immunology, hematology, biochemistry, genetics, oncology and related fields.

Nima Rezaei Editor

Gastrointestinal Cancers: An Interdisciplinary Approach

Editor Nima Rezaei Department of Clinical Immunology Karolinska Institutet Stockholm, Sweden Cancer Immunology Project (CIP) Universal Scientific Education and Research Network (USERN) Stockholm, Sweden

ISSN 2731-4561 ISSN 2731-457X (electronic) Interdisciplinary Cancer Research ISBN 978-3-031-48370-7 ISBN 978-3-031-48371-4 (eBook) https://doi.org/10.1007/978-3-031-48371-4 # 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

Gastrointestinal cancers are among the most prevalent malignancies worldwide, with about one fourth of global cancer incidence and about one third of all cancer-related death. The Interdisciplinary Cancer Research series publishes comprehensive volumes on different cancers. It plans to present the most updated and peer-reviewed interdisciplinary chapters on cancers. This interdisciplinary book series is of special value to researchers and practitioners working on cell biology, immunology, hematology, biochemistry, genetics, oncology, and related fields. This is the main concept of Cancer Immunology Project (CIP) and Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), which are two active interest groups of the Universal Scientific Education and Research Network (USERN). Gastrointestinal cancers include esophageal cancer, gastric cancer, colorectal cancer, pancreatic cancer, and liver cancer, which all, except the last one, are covered in this volume. Liver cancer will be discussed in the next volume. The fourth volume of the book, entitled Gastrointestinal Cancers: An Interdisciplinary Approach, starts with an introduction on gastrointestinal cancers, which requires interdisciplinary approach. Microenvironment and the role of microbiotaimmunity axis are discussed in Chap. 2. Epithelial-mesenchymal transition in gastrointestinal cancer, from a basic to a clinical approach, is explained in Chap. 3. Meanwhile metabolomics of gastrointestinal cancers, deregulation of immune system in gastric cancer development, and the role of H. pylori in gastric cancer are presented in Chaps. 4, 5, 6, and 7, respectively. Role of tumor microenvironment in gastric, colorectal, and esophageal cancers is the subject of Chaps. 9 and 10, while the interplay between immunity and gut microbiota in colon cancer is discussed in Chap. 11. Chapter 12 presents the importance of immunotherapy, including CAR-T cell in gastrointestinal cancers. Development of nanocarriers for the treatment of colorectal cancer is explained in Chap. 13, while challenges of oncotherapeutics in colorectal cancer are discussed in Chap. 14. After discussion on weight loss and malnutrition following esophageal cancer in Chap. 15, pancreatic cancer and its treatment is discussed in Chaps. 16 and 17.

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I hope that this interdisciplinary book will be comprehensible, cogent, and of special value for researchers, oncologists, and gastroenterologists who wish to extend their knowledge on gastrointestinal cancer and its treatment. Stockholm, Sweden

Nima Rezaei

Contents

Interdisciplinary Approach in Gastrointestinal Cancers . . . . . . . . . . . . . Khashayar Danandeh, Maryam Balibegloo, and Nima Rezaei

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Gastrointestinal Cancers: What Is the Real Board of Microenvironment and the Role of Microbiota–Immunity Axis? . . . . Edda Russo, Federico Boem, Lavinia Curini, and Amedeo Amedei

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Epithelial-Mesenchymal Transition in Gastrointestinal Cancer: From a Basic to a Clinical Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . Simona Gurzu and Ioan Jung

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Metabolomics of Gastrointestinal Cancers . . . . . . . . . . . . . . . . . . . . . . . Giulia Nannini, Gaia Meoni, Leonardo Tenori, and Amedeo Amedei

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Deregulation of Immune System in Gastric Cancer Development, How Immune Nutrition Might Restore the Functions of Immune Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Luigi Spagnoli, Federica Petrelli, Bruno Perotti, Marco Arganini, and Maria Raffaella Ambrosio Helicobacter pylori Virulence Factors, Pathogenicity, and Gastric Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Alaa M. Elgohary, Nourhan M. Gomaa, Mohamed A. Ibrahim, Hagar S. Ahmed, Shimaa M. Ibraheem, and Mustafa H. Frag Gastric Cancer and Helicobacter pylori . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Irena Mladenova Role of Neuromodulators in Regulation of the Tumor Microenvironment of Gastric and Colorectal Cancers . . . . . . . . . . . . . . 151 Debanjan Chakroborty and Chandrani Sarkar The Role of Tumor Microenvironment in Colon Cancer . . . . . . . . . . . . 187 Caterina Fattorini, Marco Arganini, Andrea Cavazzana, and Maria Raffaella Ambrosio

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Unraveling the Esophageal Cancer Tumor Microenvironment: Insights and Novel Immunotherapeutic Strategies . . . . . . . . . . . . . . . . . 215 Inamu Rashid Khan, Faizyana Ali, Sheema Hashem, Alanoud Abdulla, Sabah Nisar, Tariq Masoodi, Ammira S. Al-Shabeeb Akil, Ajaz A. Bhat, and Muzafar A. Macha The Interplay Between Immunity and Gut Microbiota in Colon Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Lara Malaspina, Federica Petrelli, Bruno Perotti, Marco Arganini, and Maria Raffaella Ambrosio Immunotherapy in Gastrointestinal Cancer Focusing on CAR-T Cell Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251 Asma Mousavi, Faeze Gharibpoor, Sepideh Razi, and Nima Rezaei Development of Biocompatible Nanocarriers for the Treatment of Colorectal Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 Bibi Noorheen Haleema Mooneerah Neeroa, Nurshafida Adzlin Shamsul Anuar, Brianna, Mostafa Yusefi, Kamyar Shameli, and Sin-Yeang Teow Challenges of Onco-therapeutics in Early-Onset Colorectal Cancer . . . . 291 Katie Doogan, Alexandra M. Zaborowski, and Des C. Winter Unintentional Weight Loss and Malnutrition After Esophageal Cancer and Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 Alexis Sudlow, Annelie Shaw, Clare Corish, and Carel W. le Roux Current Clinical Landscape of Immunotherapeutic Approaches in Pancreatic Cancer Treatment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 Pooya Farhangnia, Shamim Mollazadeh Ghomi, Shabnam Mollazadehghomi, and Ali-Akbar Delbandi The Tumor Microenvironment in Pancreatic Cancer and Challenges to Immunotherapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381 Adile Orhan Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403

About the Editor

Nima Rezaei, MD, PhD, Professor Nima Rezaei gained his medical degree (MD) from Tehran University of Medical Sciences and subsequently obtained an MSc in Molecular and Genetic Medicine and a PhD in Clinical Immunology and Human Genetics from the University of Sheffield, UK. He also spent a short-term fellowship of Pediatric Clinical Immunology and Bone Marrow Transplantation in the Newcastle General Hospital. Prof. Rezaei is now the Full Professor of Immunology and Vice Dean of Research and Technologies, School of Medicine, Tehran University of Medical Sciences, and the co-founder and Head of the Research Center for Immunodeficiencies. He is also the Founder of Universal Scientific Education and Research Network (USERN). Prof. Rezaei has already been the Director of more than 100 research projects and has designed and participated in several international collaborative projects. Prof. Rezaei is the editor, editorial assistant, or editorial board member of more than 40 international journals. He has edited more than 50 international books, has presented more than 500 lectures/posters in congresses/meetings, and has published more than 1200 scientific papers in the international journals.

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Interdisciplinary Approach in Gastrointestinal Cancers Khashayar Danandeh, Maryam Balibegloo, and Nima Rezaei

Abstract

Since the first studies around the cancers and their burden, gastrointestinal (GI) cancers have been responsible for considerable rates of mortality and morbidity through the years. They have remained incurable in many subtypes despite significant development in diagnosis and therapies since their first-ever diagnosis in the early nineteenth century. GI-related cancers constituted about 36% of all cancer-related deaths in 2020. GI system includes longitude sites from the mouth to the anus with a variety of functions and features. Colorectal, gastric,

K. Danandeh Research Center for Immunodeficiencies, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran Network of Immunity in Infection, Malignancy, and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran M. Balibegloo Research Center for Immunodeficiencies, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran Network of Immunity in Infection, Malignancy, and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran Cancer Immunology Project (CIP), Universal Scientific Education and Research Network (USERN), Chicago, IL, USA N. Rezaei (*) Research Center for Immunodeficiencies, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran Network of Immunity in Infection, Malignancy, and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2022_12 Published online: 30 August 2022

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liver, esophageal, pancreatic, and gallbladder cancers are the six major GI malignancies, in descending order regarding their incidence rates in 2020, worldwide. Recently, a better understanding of the genetic, epigenetic, and biology of GI cancers has resulted in improved survival. Nevertheless, despite specific biomarkers, biosensors, and selective para-clinic and laboratory data used in the diagnostic approach, early diagnosis is challenging. Interdisciplinary studies over immune-related cells and their interactions with gene expression and mutation in the tumor microenvironment have recently added new insights into the diagnosis and treatment. Although the combination of chemotherapy, immunotherapy, and biological drugs provided a better survival rate than in the past, annual deaths are among the most lethal cancers. Studies and experiments around GI cancers, their causes, and optimal therapies are actively continuing. Keywords

Chemotherapy · Gastrointestinal cancers · Immunoediting · Immunotherapy

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Introduction

Cancer has remained a significant issue in human society throughout the world. Considering all gastrointestinal (GI) cancers together, they have been reported to be the leading cause of cancer-related deaths with the highest incidence, worldwide in 2020. Additionally, colorectal cancer (CRC) is the third most prevalent cancer being responsible for the third most cancer-related deaths, as well in men. In women, CRC is the second most common with the third-highest cancer-related deaths. Furthermore, gastric cancer is the third cause of cancer-related death globally (Sung et al. 2021). In addition to the long longitude of the GI tract, including the mouth, oropharynx, esophagus, stomach, liver, pancreas, biliary system, small intestine, and colorectum, a large number of epithelial cells could increase the risk of cancer in this major system. Some risk factors can play a significant role in the incidence of GI cancers acting synergically such as adiposity (Murphy et al. 2018; O’Sullivan et al. 2018), frequent alcohol consumption (Scherübl 2020; Yoo et al. 2021), and tobacco use (Chen and Haber 2021). Meanwhile, dysbiosis of the gut microbiome may contribute to GI malignancy susceptibility (Weng et al. 2019). The human immune system reacts to cancerous cells in two ways: by responding to tumor-specific antigens (TSA) (molecules specific to cancer cells) or tumorassociated antigens (TAA) (molecules expressed differentially by cancer cells and normal cells) (Finn 2008). Recent studies have demonstrated that immunity can enhance cellular and molecular changes, inhibit or limit tumor expansion, and modify tumor immunogenicity (Grivennikov et al. 2010). By a process known as “cancer immunoediting”, a functional immune system may prevent, regulate, and shape/promote cancer (Mittal et al. 2014). Dendritic cells (DCs), as one of the main antigen-presenting cells (APC) initiating the cancer-immunity cycle, play an

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essential role in the modulation of innate and adaptive immune responses (Wculek et al. 2020). Esophagus and gastric cancers, being among the deadliest GI malignancies, have poor prognosis by routine chemo/radiotherapy strategies. Nevertheless, novel immunotherapies by targeting programmed cell death-ligand 1 (PD-L1) in addition to defects in mismatch repair (dMMR) genes resulting in microsatellite instability (MSI-H) phenotype make a new gate to these poor prognosis cancers (Vrána et al. 2019). Immunology provides a chance for scientifically driven treatment development. The introduction of immune checkpoint inhibitors (ICIs) such as antibodies against cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), programmed death 1 (PD-1), and PD-L1 has developed a framework for cancer immunotherapy (Andrews et al. 2019).

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Primary Tumor Sites and Types of Gastrointestinal Cancers

GI cancers are on the list of most common primary tumors and malignancies and they play a role in secondary and metastatic tumors. Different studies have classified GI cancers in different ways based on various factors such as anatomic tumor sites and upper and lower GI cancers, gene expression patterns, mutations, molecular biomarkers, and cancer staging. Based on the GI circulation, the whole GI tract is divided into two major parts: the lower and upper GI tract. The ligament of Treitz, also known as the suspensory ligament of the duodenum, is the anatomic territory that distinguishes upper and lower blood supply, so the cancer sites above the ligament of Treitz are defined as upper GI cancers, including esophagus and gastric cancers. The rest below the ligament, named lower ones, includes the duodenum, liver, gallbladder, and colorectum (DiGregorio and Alvey 2020). Specific gene alteration, expression, and distinct molecular landmarks have been recognized through the years. Esophageal, gastric, and CRC are the primary malignancies classified more in this category due to a higher proportion of morbidity and mortality. Specific genes are recognized in esophageal, gastric, and CRCs including vascular endothelial growth factor (VEGF), human epidermal growth factor receptor 2 (HER2), and epidermal growth factor receptor (EGFR) (Fakhri and Lim 2017).

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History of Gastrointestinal Cancers

Cancer always has been a severe regret of general and health care society since it was discovered. Moreover, GI cancers, as one among the highest-burden malignancies, had a long history of diagnosing and therapies until today. Initiating from the most upper part, esophageal cancer history goes back to ancient Chinese and Islamic clinicians. In the middle of the nineteenth century, diagnosis improved so fast; Vincenz Czerny (1842–1916) accomplished the first successful cervical esophageal excision for cancer in 1877. Then in 1913, the first successful esophagectomy for cancer was performed by Tohru Ohsawa (1882–1984) (Karamanou et al. 2017).

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Gastric or stomach cancer has been misdiagnosed in many cases through the earlier part of the nineteenth century due to lack of direct examination. One of the most historically contributed mortality which clarified a gastric cancer-related death was Napoleon Bonaparte’s in 1821. He had the symptoms of a vague syndrome and progressive epigastric pain. Finally, benign and malignant gastric ulcers were only characterized by J. Cruveilhier in 1835. Nevertheless, great clinicians and scientists like Avicenna have recognized gastric-related symptoms and gastritis since the seventeenth century or even much sooner. Between the late nineteenth and early twentieth centuries, clinicians and experts recognized the principal risk factors of these cancers well. Direct examination of mucosa occurred by developing and progression of autopsy and endoscopy. Besides the detection of gastric and duodenal ulcers and Helicobacter pylori (H.Pylori) infection in many cases, many studies proved the significant role of smoking, excessive alcohol consumption, and their synergistic effect (Santoro 2005; Graham 2014). The description of the pancreatic islets was named after Paul Langerhans in 1869 for the first time. Scattered evidence has been found regarding pancreatic neoplasms, but pancreatic-related diseases remained unknown and incurable for many years. Indeed, the very first insights into acute pancreatitis were obtained from Reginald H. Fitz, a pathologist who explained the clinical features of acute pancreatitis in 1889. Because of being unknown, lack of direct observations, and challenging accessibility, pancreas cancers were explored later than other GI cancers. Near the late twentieth to early twenty-first centuries, diagnosis improved by the development of para-clinic and laboratory data (Rustgi 2013; Navarro 2016). The investigations on heredity and primary CRCs began in the late nineteenth century by Dr. Aldred Warthin (Schlussel et al. 2014). Further genetic development and studies so far helped to recognize the hereditary nonpolyposis CRC (HNPCC) well and described a complete definition of CRC in the late twentieth century (Lynch et al. 1993; Matsui et al. 2000).

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Epidemiology of Gastrointestinal Cancers

GI cancers are almost always placed in the top list of global cancer incidence and prevalence, with more than one-fourth of cancer population cases. According to the GLOBOCAN 2020 study which estimated 36 kinds of cancers in 186 countries all around the world, colon, stomach, liver, rectum, and esophagus cancers are in the top ten cancers with a higher incidence. The term Human Development Index (HDI), defined by the United Nation’s 2019 Human Development Report, can demonstrate the relation between high HDI regions and major risk factors such as adiposity and smoking or alcohol consumption for GI cancers (Programme 2019). The incidence of GI cancers varies significantly by geography, with colon cancers being more common in Europe and Northern America. Norway and Hungary are the countries with the highest incidence rates of colon cancers compared to all countries in females and males, respectively. Rectal cancer is also distributed with almost the same pattern. HDI is effective in both the incidence and prevalence of CRCs. According

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to recent studies, those countries with high or very high HDI are the leading regions for CRCs. Unsuitable diet, obesity, and higher rates of smoking and alcohol users are the main problems in high HDI countries (Dizdar and Kılıçkap 2019; Sung et al. 2021). Colon cancer is the top among all other GI cancers, with nearly 20% of the whole GI-related new cases. Gastric, liver, rectal, esophageal, pancreatic, gallbladder, and anus cancers follow colon cancer in descending order (Lu et al. 2021; Sung et al. 2021). In contrast, stomach and liver cancer incidences are higher in Asia and/or Africa (Sung et al. 2021). Smoking, alcohol, infections, hereditary factors, nutrition, and obesity are major risk factors for GI malignancies. Changes in lifestyle and environmental variables and medical developments all have an impact on the epidemiology of GI malignancies (Dizdar and Kılıçkap 2019). In addition, the 5-year prevalence of all GI cancers showed that Japan had the highest rate in the whole world by 785 per 100,000 people (Fereidouni et al. 2020).

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Mortality and Morbidity of Gastrointestinal Cancers

According to World Health Organization (WHO) estimates, cancer is the primary or second major cause of death even after excluding patients with the age of 70 and over in more than 110 countries over 183 in 2019, and one of the five top causes in other nations (Bray et al. 2021). The health care system suffers a lot from the GI cancer burden. CRC accounts for about 25% of GI-related mortalities. The other top-five ones in descending order are liver (23%), gastric (21%), esophagus (15%), and pancreatic (13%) cancers (Sung et al. 2021). CRC is responsible for the world’s second cancer-related mortality with about 9% of all cancer deaths, with nearly one million deaths in 2020. Meanwhile, liver (third), stomach (fourth), esophagus (sixth), and pancreas (seventh) cancers are the next lethal ones with 8%, 8%, 5%, and 5% of all estimated mortalities in 2020, respectively. Eastern regions of Asia and Europe are responsible for the most GI-related morbidity and mortality worldwide. Mongolia had the highest age-standardized mortality rates in both sexes for all GI cancers with 130.1 deaths in every 100,000 people (Fereidouni et al. 2020; Sung et al. 2021). However, there is a strong relationship between morbidity and mortality and specific risk factors of every GI cancer. For instance, CRC associated with diet, alcohol use, and smoking increased in the modern lifestyle and justified the burden raised in high HDI regions. According to their subsites, stomach cancers are divided into two primary types: cardia (upper part) and non-cardia (lower part). The main risk factor of non-cardia stomach cancer is H.Pylori infection, accounting for nearly all occurrences. However, investigations have revealed two different causes for gastric cardia cancers; some have named H.Pylori infection as the main reason. Nevertheless, others linked it to the excess body weight and gastroesophageal reflux disease (GERD) injuries, with adenocarcinoma-like properties. A major kind of primary liver cancer is hepatocellular carcinoma (HCC), constituting almost 80% of cases. Chronic hepatitis B (HBV) or C virus (HCV)

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infection, aflatoxin-contaminated foods, high alcohol consumption, obesity, type 2 diabetes mellitus, and smoking are the key risk factors for HCC, for which China has the highest burden. The two major histologic subtypes are squamous cell carcinoma (SCC) and adenocarcinoma. High alcohol consumption, heavy smoking, and dietary components and behaviors are the main causes of SCC. For adenocarcinoma, excess body weight, Barrett’s esophagus, and GERD play key roles (Sung et al. 2021).

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6.1

Interdisciplinary Approach in the Diagnosis of Gastrointestinal Cancers

One of the most challenging issues around GI cancers is early diagnosing, which is still not feasible in many cases. Despite science and technology development and many confirmed molecular or laboratory biomarkers and other para-clinic data in different kinds of GI cancer diagnoses, the mortality and 5-year survival rates have remained concerning. Also, early-stage GI cancers have no distinct symptoms, so it gives the opportunity to cancerous cells to move up into advanced and late poor prognosis stages. Optimal diagnosis methods are unavailable, and accessible ways have low specificity and sensitivity, such as detecting occult blood in the stool or carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) as two main biomarkers for diagnosing and follow-up monitoring. Serologic tests are commonly used to diagnose a few cancers. The best example is α-fetoprotein (AFP) which is mainly used for diagnosing HCC. Imaging data like computed tomography scan (CTS), endoscopic retrograde cholangiopancreatography (ERCP), and endoscopic ultrasound are chosen methods for additional investigations. CRC is the most diagnosable GI-related cancer among all GI malignancies, with 95% of 5-year survival in early-stage diagnosis, while pancreatic cancer with nearly 5% is the worst (Nannini et al. 2020). Endosonography (EUS) and CTS are two para-clinic assessment ways that give data for the staging of malignancies according to tumor node metastasis (TNM) classification. TNM staging classification can give clear guidance for further treatment plans; however, the prominent blind spot of this kind of staging is the final report. The final reports of imaging data are strongly dependent on the radiology experts and professionals, which increases the risk of bias and incorrect diagnosis (Cho 2015). There was a long history of investigating DNA and RNA biomarkers or some inherited molecular markers of genes such as CDH1 gene (encoding epithelial cadherin, E-cadherin) or IL-1 gene. Furthermore, recognized GI cancer-related immune checkpoints and their ligands are playing a crucial role in diagnosis and targeted immunotherapy (Radhika et al. 2016). Epigenetic changes were the constant part of all cancers, including GI cancers. Improper DNA methylation is the most common alteration in GI cancers. Besides, histone and non-coding RNA modifications are both known as GI-related epigenetic changes. There are several reports of aberrant DNA methylation in blood

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and fecal DNAs in CRCs. The observation showed that in gastric cancer with the EBV (Epstein-Barr virus) and H.Pylori infections, as two common risk factors, there is a strong association between DNA promotor methylation and these risk factors. Through the progression of neoplasms in Barrett’s esophagus, hypermethylation of CDKN2A gene in addition to methylation of promotor in APC and ESR1 has been detected. In pancreatic cancer, especially ductal adenocarcinomas, as the most common subtype among all the others, NTPX2, SARP2, RPRM, and LHX1 have been detected with significant epigenetic changes. Furthermore, wrong DNA methylation has been observed in biliary tract cancers such as cholangiocarcinoma as the most prevalent subtype. The various methylation levels in TFPI2, NPTX2, and CCND2 genes have been discovered in cholangiocarcinoma. In the group of genes (CDH1, CDKN2A, GSTP1, RASSF1A, RUNX3, and WIF1), hypermethylation of DNA is happened in HCC compared to healthy tissue (Vedeld et al. 2018). The use of electrochemical nano biosensors for biomarkers miRNA 106A in the early detection of GI cancer has already been described (Richardson et al. 2001). Nextgeneration sequencing technology has had some footprints as a novel method through the years. Generation of Sanger sequencing, Maxam Gilbert sequencing, and whole-genome sequencing (WGS) data analysis provided opportunities for early diagnosis in some difficult situations and lighted hopes for improved survival. WGS analysis demonstrated that integrated data with specific DNA genes such as BRCA1, BRCA2, and PALB2 could precisely target the malignancies. MINT25, PRDM5, and GDNF are also found in gastric cancers with high sensitivity and specificity. In esophagus SCC, TFF1 methylation was reported as a potential early-diagnose biomarker compared to the intact tissue. CD1D is one of the most potential genes for diagnosing and comparing intact and cancerous tissue with acceptable sensitivity and specificity. However, the main problem of epigenetic examination is time, at least weeks to months lasts, to prepare the report of genetic data (Watanabe et al. 2009; Neelapu and Surekha 2016; Nakagawa and Fujita 2018). The primary goal for any cancer is the earliest possible diagnosis to decrease mortality and morbidity rates. Emerging biomarkers, biosensors, and computational technologies are focused as most likely methods for early diagnosis. Moreover, genetic and immune-related factor interactions are inseparable during cancer progression. These factors can play a momentous role in early diagnosis after many failures by available methods. The suppression of the p53 gene and the expression of CD44 aberrant transcripts are both frequent phenomena that can be used to diagnose cancer (Tahara 1995). Gene expression/mutation can be a two-edged sword; for instance, COX-1 is found in most tissues and is assumed to be responsible for maintaining low levels of prostanoids. Nevertheless, COX-2 is an instant reaction gene strongly inducible at sites of inflammation and is overexpressed in some malignancies (Wang and DuBois 2018). Autophagy is one of the leading processes during cancer growth; although it can be an inhibitor in the early stages, it helps the cancer progress in the late phases. Detecting microRNAs (miRNAs) as a non-coding regulatory RNA in tumor cells associated with the autophagy process in GI cancers is a novel possible diagnosing biomarker (Pourhanifeh et al. 2020). HER2 is found in the gastroesophageal junction. Mutations in the ERBB2 gene cause HER2

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overexpression, which leads to early-stage carcinogenesis. The MET, also known as hepatic growth factor (HGF), is a receptor tyrosine kinase that stimulates many signaling pathways. Activation of signaling cascades such as the HGF/c-Met signaling cascade has been identified as a prognostic and predictive marker for gastric cancer. PD-1 and cytotoxic T lymphocyte-associated protein 4 (CTLA-4) are immunological checkpoints regulating cellular brakes on T lymphocytes and acting as a predictor biomarker for GI cancers. PD-1 biomarker overexpression detection is a predictive immune checkpoint for some GI cancers (Bramhachari and Neelapu 2020). Also, advanced studies over epigenetic data in GI cancers with CRC as top priority demonstrated a group of promising genes that could predict the early stages of GI cancers. Epigenetic changes by DNA promoter methylation are detected in novel genes, including CDO1, ZNF331, and ZSCAN18, with a higher correlation with DCLK1 for CRCs (Marie Vedeld et al. 2015).

6.2

Interdisciplinary Approach in the Treatment of Gastrointestinal Cancers

6.2.1 Approved Therapies Immunotherapy has developed and altered cancer treatment plans during recent years, yet remained disappointing for GI cancers. The implication of immunotherapy in cancer treatment is based on the idea that cancer cells impair regulatory T-cellmediated immunosuppression as one of their key immune evasion mechanisms. Tumor cells can utilize various strategies to evade the immune system. Tumors can decrease cytotoxic T-cell activity by manipulating cytokines pathways that increase T regulatory cells and myeloid-derived suppressor cells. All the processes result in CD4 and CD 8 T cells being suppressed since they would not be able to identify foreign antigens anymore. MHC class expression can also be lost, causing T lymphocytes to lose their ability to identify them. Tumors can increase the expression of immune checkpoint molecules like PD-L1, causing peripheral T-cell exhaustion and malignant cell apoptosis inhibition. The discovery of immune-based therapy changed the trends in treatment and prognosis in a promising way. A vast amount of immunotherapy plans hold on the patients in different levels of cancers; interleukin (IL)-2-activated lymphocytes, tumor-specific reactive CD8+ T-lymphocyte transfer, DC vaccines, non-specific biological response modifiers (OK432,9 lentinan,10 PSK11), and TAA-derived peptides. All of these therapies have been effective in contributed cases (Hazama et al. 2018; Golshani and Zhang 2020). Immune Checkpoint Blockade ICIs have been conventional immunotherapy for GI cancers since their first successful response in melanoma in 2011. In 2013, they were used in GI cancers for the first time and showed many effective results in the patients. Immune checkpoint molecules, of which PD-1 and CTLA-4 are the most well-studied ones, interact with APCs and other cell types to prevent T cells from becoming overactive. PD-1 is a CD28 family member that modulates the immune system by being expressed on

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activated T cells, B cells, and myeloid cells. When PD-1 is activated by its ligand PD-L1, inhibitory signals are transmitted to T cells, resulting in the establishment of peripheral tolerance. Pembrolizumab, nivolumab, and camrelizumab are three popular ICI agents examined in different trials on esophagus cancers; in addition, all these drugs are approved by the Food and Drug Administration (FDA) for GI cancers. Statistics demonstrated a significant benefit in survival compared to routine chemotherapy, especially in SCC. Both pembrolizumab and nivolumab prolonged survival in advanced gastric cancer compared to chemotherapy alone. The CRC predictor biomarkers, MSI-H/dMMR, also can be targeted by these anti-PD-1 antibodies and enhance survival significantly (Lu et al. 2020). Seventeen patients with non-CRC dMMR GI malignancies were treated with pembrolizumab in a phase II study. The study showed an objective response rate of 47% with four participants reaching a complete response. However, there was not any clinical activity regarding objective response rate in those with proficient MMR (pMMR). It is explained as those with dMMR develop neo-antigens in response to genomic alterations which are being identified by the immune system (Le et al. 2015). CD73 and Adenosine Receptor Subtype After significant development in immune-related treatment strategies for GI cancers, anti-PD-1 and anti-CTLA-4 became one of the vastly used treatment plans with or without chemotherapy and adjuvant therapies. Molecular studies demonstrated that during the cancer progression and metastasis, CD73 and adenosine receptor subtype (A2AR) are actively expressed compared to the normal tissue. Advanced studies on targeting CD73 and A2AR by blocking the process significantly enhanced the efficacy of anti-PD-1 and anti-CTLA-4 therapy. Furthermore, it even stopped and slowed the progression of cancer growth and metastasis efficiently. The results around cellular immunotherapy were controversial. However, chimeric antigen receptor (CAR)-T therapy as an adoptive T-cell therapy with antigens like EGFR, HER2, CEA, and MUC1 has provided some excellent survival improvement in GI cancers, especially in CRC (Ma et al. 2019). Cancer Vaccination Cancer vaccination has been used to generate an antitumor immune response that can eradicate a tumor and offer continuous monitoring to prevent its regrowth in a variety of tumor forms. Autologous, peptide, viral vector, and DC vaccines have all been recruited in GI-related cancers in the last decade. Autologous vaccines are made from cells taken directly from a patient’s tumor and, by definition, cover all relevant TAAs. Autologous tumor cells, as opposed to single-peptide vaccinations, can prevent tumor escape by eliciting adaptive immunity against several tumor antigens. On the other hand, whole tumor cell vaccines have demonstrated minimal therapeutic benefit since the majority of antigens are found in normal cells, and the immune response elicited is not unique to cancer cells. The justification for using peptide vaccines is based on discovering and synthesizing antigenic epitopes obtained from TAA or TSA that are 8–11 amino acids long. Peptide vaccines can elicit particular T cells that fight TSA, and they can be used with adjuvants to boost

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the tumor-specific immune response. The antitumor immune response relies heavily on DCs. DCs may present numerous TAA via MHC class I and II molecules as vital APCs. They also play a crucial role in programming and regulating the antitumor response by supplying the necessary co-stimulatory signals and guiding the production of cytokines. The goal of using viral antigen vaccines is to take advantage of the virus’s pathogenicity to build a strong, tumor-specific immune response. Recombinant viral vectors benefit from producing any number of antigens while also delivering innate pro-inflammatory signals that boost the TAA-specific immune response. Therapeutic immune vaccines have been tried in some different trials so far. In situ vaccines have been tried on tumors with a lack of expressing T cells and peptide ones to enhance cytotoxic T cells’ response. Immune vaccines get ready the immunity to face cancer cells with educated responses (Kalyan et al. 2018; Bouzid et al. 2020). Adoptive Cell Therapy Adoptive cell therapy (ACT) is a cancer immunotherapy method that uses the patient’s own lymphocytes to attack cancer cells. It acts as a stimulant and tries to load autologous lymphocytes with cytokines or tumor antigens, then cultivates them ex vivo before reinfusing them back into the patient. Cytokine-induced killer (CIK) cells, tumor-infiltrating lymphocytes (TILs), natural killer (NK) cells, and CAR-T cells are all examples of adoptive immunotherapy for HCC. Many investigations have been conducted to determine the feasibility and safety of ACT in patients with HCC, providing the groundwork for its therapeutic use (Jixia et al. 2017). Conversion of Cold Tumors to Hot Tumors Based on the recent classification, tumors are divided into two primary groups: hot tumors with immunogenic microenvironments and cold tumors with non-immunogenic ones. A considerable number of T-cell involvement with increased PD-L1 expression on the tumor cells characterizes a hot tumor, whereas a mild infiltration of immune cells characterizes a cold tumor. An increasing body of research suggests that hot tumors react well to ICIs, but cool tumors do not. As a result, in the case of cold tumors, combining ICIs with cancer vaccines, molecular target therapies, or chemoradiation has the potential to cause cytotoxic T lymphocytes infiltration and overexpression of PD-L1 on tumors, resulting in the conversion of cold tumors to hot tumors; patients will then be followed by ICIs therapy (Kono 2018). Oncolytic Viruses Oncolytic viruses are selectively reproduced in tumor cells and cause lysis without damaging normal tissues. Oncolytic viruses’ anticancer efficacy is based on their ability to destroy cancer cells directly by growing inside them and cell lysis induction. Because the tumor’s defensive systems against viral infection are impaired, most viruses may spread to a large extent in cancer cells. Tumor antigens and viruses in cell lysates also trigger immune responses against cancer cells nearby. Reoviruses, varicella viruses, and Sindbis viruses are examples of wild-type viruses that exclusively infect tumors. These viruses initiate the first step to fight cancerous

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cells. Next, engineering is used to remove viral genes that are required for replication in normal cells but have no function in cancer cells. Furthermore, tumor-specific promoters, such as the promoter of human telomerase reverse transcriptase, are used before important viral genes in cancer cells to inhibit viral transcription in normal cells. Viruses can then successfully target tumor cells after being modified by TAA-specific receptors (Chiocca and Rabkin 2014).

6.2.2

Treatment Plans Based on Involved Organ

Esophagus Cancer The esophagus is one of the most prevalent upper GI cancers, which could involve other essential parts of the body due to its anatomical position. SCC is the most common subtype, so most of the trials and studies are actively around it. Surgery and resection along with radiotherapy and chemotherapy are authorized for these kinds of cancers. Immune-related target therapies have also been approved for ICI combinations recently. The combination of ipilimumab (anti-CTLA4 agent) and nivolumab and pembrolizumab (anti-PD-1) were used in the SCC cases with promising results. Recent developments in epigenetics and molecular studies have led to specific genes and biomarkers discovery and peptide and DCs vaccines were added to the immunotherapy treatment plans (Kono et al. 2018). Gastric Cancer Gastric cancer-approved treatment varies from case to case. Stomach surgery and segmental and radical tumor resection were some of the first approved plans. In advanced stages, radiotherapy and/or chemotherapy were added. In addition, radiation and target therapy by antibodies of HER2 and VEGF receptor 2 (VEGFR2) were accepted for the patients. Immunotherapy got a trend in recent years with ICIs as the center of attention. However, the results had a wide range from negative and poor to non-sense and very effective. Other immunotherapies (monotherapy or combination) that were tested through the years include immune vaccines, adoptive cell transfer, and targeting specific receptors (OX40) by antibodies, which had different prognoses. Also, CD73 expression was higher in gastric cancer versus the healthy tissues. This persuaded researchers to try combination therapy for antiPD-1 and CD73 blockade (Sitarz et al. 2018). Liver Cancer HCC is the leader of the most lethal liver cancer subtypes. Treatment strategies of liver cancer have a long history as well. First-line therapy for early stages is surgery and resection, and in chronic liver failure, cirrhosis and fibrosis, indeed, a liver transplant is the choice. Immune-related therapy is approved for liver cancer. Targeting multi-kinase inhibitors and recently ICIs as the second-line for HCC were approved. Also, immune vaccines and combination therapy had a high potential for enhancing the patients’ quality of life. As discussed, numerous types of immunotherapy have been developed for HCC, the most promising of which is ICIs targeting PD-1/PD-L1 and CTLA4. Most of the studies have investigated ICI-based

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medicines and other therapeutic techniques. Although ICI monotherapy protocols have demonstrated advantages in certain HCC patients with generally acceptable adverse events profiles, response rates (about 20%) have been unsatisfactory, owing to the liver’s immunosuppressive qualities and the HCC tumor microenvironment immunosuppressive features. Several sorts of combination strategies are now being investigated in order to improve treatment effectiveness (Llovet et al. 2008). Pancreatic Cancer Pancreatic cancer overview for the upcoming 10 years is concerning. Ductal carcinomas are the most common subtypes with more than 90% of all cases. The main reason for poor prognosis and survival among the patients is weak modalities and clues for diagnosing. The conventional approved therapies for these patients are surgery (resection), chemotherapy, radiation, and immune-related targeted therapy for EGFR inhibitors. ICIs monotherapy and combinations were a little controversial. Although, in some trials, the combination of ICIs and chemotherapy and/or radiation had effective results (McGuigan et al. 2018). Colorectal Cancer Rating among the top three cancer-related deaths, CRC’s approved strategies for treatment consist of surgery for local, total, or radical resection, chemotherapy, radiotherapy, and immune-related target therapy for antibodies against EGFR and VEGF. Novel authorized immunotherapy is ICI, used in refractory dMMR/MSI-H metastatic CRCs with effective results. MSI is described as a change in the microsatellite area inside tumor cells compared to normal cells. Microsatellites are short, simple sequence DNA repeats. MSI findings for repeated unit insertion or deletion were linked to DNA mismatch repair system problems. The MSI subgroup accounts for about 15% of all CRCs. Its prevalence varies by stage. 15% of stage II–III CRCs are dMMR, while only 4–5% of stage IV CRC cancers are dMMR. MSI-H status has also been linked to a better overall prognosis as compared to individuals with microsatellite stable CRC in recent years, MSS or pMMR (Schatoff et al. 2017). Gallbladder Cancer Intrahepatic cholangiocarcinoma, extrahepatic cholangiocarcinoma, gallbladder cancer, and ampulla of Vater cancer are all examples of biliary tract malignancies, a mixed collection of severe carcinomas. Chemo-resistance is increasingly common in gallbladder cancer, necessitating novel therapeutic intervention measures. Cholangiocarcinoma is among the rare cancers with a bleak outlook. The usual approach to treat these cancers is surgical resection and adjuvant therapy such as chemotherapy and radiation, but immunotherapy is a considerable strategy in many cases (Rizzo et al. 2021). While being promising in some solid tumors, such as renal cell carcinoma (RCC) and melanoma, the role of immunotherapy in biliary tract cancer is not well defined, yet (Ahn and Bekaii-Saab 2019). In cholangiocarcinoma, single-agent ICIs have had mixed outcomes, indicating modest but meaningful responses in a small number of patients. In order to give more effective therapy choices in advanced cholangiocarcinoma, novel combination tactics with ICIs are now being investigated in this scenario (Rizzo et al. 2021).

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6.2.3 Therapies Under Development Combination therapy development has become a heated debate in recent years. Some trials and evidence have shed light on the higher benefit of the combination of immunotherapies, or immunotherapy with other conventional treatments than monotherapy, such as immunotherapy-chemotherapy. Combination therapies can open new gates to treat more advanced cancers later than first-line treatment. For instance, the combination of anti-PD-1 antibody (nivolumab) and anti-CTLA-4 antibody (ipilimumab) is thought to be significantly more effective than monotherapy for GI cancers (Overman et al. 2018). Studies over ICIs are still progressing, and adoptive T-cell therapy and cancer vaccine are two interesting topics for further GI cancer therapy development. CAR-T cell therapy with more accurate target antigens is another active therapeutic study plan (Comoli et al. 2019). Many new forms of such therapies, including blockade of LAG3, TIGIT, IDO, CD47, or TIM3, are currently in the clinical development stage, the latter being a receptor for HMGB1. Another hot topic is retaining the DNA associated with this connection by triggering toll-like receptors (TLR) (Mazzarella et al. 2019). Studying molecular mechanisms that promote immunosuppression, such as CD73, can be in future therapeutic plans combination (Harvey et al. 2020). Novel immune vaccines are targeting A2AR and CD73 and seem to have an effective result for GI cancer patients (Harvey et al. 2020). TLRs are potential breakthroughs in immune-related therapies. TLRs are expressed by various numbers of myeloid cells. They identify the special molecular patterns of pathogen-associated molecules. The process of signaling afterward activates the expression of inflammatory cytokines. All conducted the way to activate the innate immune system. MEDI9197 is a TLR7 and TLR8 agonist that activates myeloid and lymphoid cells to produce pro-inflammatory cytokines. New trials showed a bright vision of combination therapy for MEDI9197 and ICIs, which improved the successful response (Wilkinson and Leishman 2018).

7

Conclusion

Finding an efficient solution for reducing the heavy burden of GI cancers’ morbidity and mortality is inquiring. Besides detecting occult blood in the fecal, specific biomarkers such as CEA, CA19-9, supplementary imaging data like CTS and ERCP, gene sequencing, and molecular markers like PD-1/PD-L1 are proposed diagnostic methods. According to the new studies, the diagnostic approach and treatment plans have been established, but more suffered from low sensitivity and specificity. New developments around the interdisciplinary data introduced some immune checkpoint inhibitory agents such as anti-PD-1 (nivolumab) and antiCTLA-4 (ipilimumab) antibodies in special settings. Moreover, in advanced cancers, combination therapy has been suggested for second-line therapy and later. Early diagnosis and finding a more effective and convenient therapeutic plan are demanding and require more studies in the future.

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Acknowledgments The authors would like to acknowledge the help rendered by Dr. Zeinab Najafi for providing her valuable comments. Compliance with Ethical Standards The authors declare that there is no conflict of interest.

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Gastrointestinal Cancers: What Is the Real Board of Microenvironment and the Role of Microbiota–Immunity Axis? Edda Russo, Federico Boem, Lavinia Curini, and Amedeo Amedei

Abstract

The tumor microenvironment (TME) represents a complex and dynamic entity, able to affect oncogenesis, tumor cells’ preservation, local invasion, and metastatic propagation of gastrointestinal cancers. The TME is able to change according to malignancy type, but common characteristics include immune cells, blood vessels, stromal cells, and extracellular matrix. Moreover, emerging evidence includes also the gut microbiome (GM) in the TME and, in particular, its mutual interplay with the immune response (named microbiome–immunity axis), in gastrointestinal cancers. In this scenario, the reciprocal interaction between cancer cells, immune system, and GM leads to new thinking on the TME borders’ redefinition in the field of gastrointestinal cancers. In this chapter, we retraced the most important studies on the crosstalk between microbiome (and its metabolites) and immune response, and how it affects the TME of gastrointestinal cancers. We discussed the multiple layers of the TME within the holobiont vision and examined how microbial dysbiosis could influence the mutual relationship between the host immunology and GM in several districts of the gastrointestinal tract, affecting oncogenesis, tumor progression, and response to immunotherapy treatment. A deep understanding of all the actors and dynamics of TME in the gastrointestinal tract will allow the design of more effective and tailored therapies, able to target specific TME levels and components, associated with the malignancy development and progression.

E. Russo · L. Curini · A. Amedei (*) Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy e-mail: amedeo.amedei@unifi.it F. Boem Philosophy and Technology Section (PHIL), University of Twente (NL), Enschede, Netherlands # The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2022_6 Published online: 20 August 2022

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Keywords

Gastrointestinal cancer · Immune response · Immunity · Immunotherapy · Microbiome · Microbiota · Tumor microenvironment

1

Introduction

Digestive tumors are malignant conditions of the gastrointestinal (GI) system and accessory digestion organs (esophagus, biliary system stomach, small intestine, large intestine, rectum, pancreas, and anus). The general symptoms can include obstruction, abnormal bleeding, and different associated problems. Gastrointestinal tract (GIT) cancers represent a significant portion of the global health-care burden (Arnold et al. 2020), and, according to their prevalence, colon (CRC), stomach, and liver cancers are the main concerns within this group (fourth, sixth, and seventh most prevalent, respectively). The principal causes of death are stomach cancer (second highest), liver cancer (third highest), and CRC (fifth highest) (Russo et al. 2019). Even though it is not one of the top 10 most common cancers, pancreatic ductal adenocarcinoma (PDAC) has some of the worst prognoses and is presumed to be one of the leading causes of death from cancer by 2030 (Rahib et al. 2014). Furthermore, esophageal cancer is common in some countries (Bray et al. 2018). The multistep biological mechanisms acting in the prevention and development of GI cancer are still largely unknown, which is why GI cancers are thought to be a multifactorial disease caused by complex interactions between genetic factors, epigenetic changes, immune function, environment elements (including geographic area and socioeconomic status), way of life, and nutrition. The majority of GI cancer investigations and therapeutic strategies have mainly concentrated on cell-autonomous processes in the epithelial compartment. Indeed, tumor cells trigger important molecular, cellular, and physical alteration within their host tissues. Nevertheless, there is mounting in vivo evidence that epithelial cells react to their “microenvironment.” Indeed, the emerging tumor microenvironment (TME) represents an intricate and ever-changing entity. TME patterns vary according to malignancy type, but common characteristics include immune cells, blood vessels, stromal cells, and extracellular matrix (ECM). The TME is a dynamic “influencer” of tumor development; in fact, a mutual relationship is created between cancer cells and TME elements in early oncogenesis to promote tumor cell preservation, local invasion, and metastatic propagation. Moreover, the TME coordinates a molecular system that fosters angiogenesis, to re-establish oxygen/nutrient source and remove metabolic waste, in order to overcome a hypoxic and acidic microenvironment. In addition, cancers are infiltrated by a variety of adaptive and innate immune cells that can have both pro- and antitumorigenic impact (Anderson and Simon 2020). Finally, another critical feature of this complex network in GI cancers is the luminal content, particularly the gut microbiome (GM); its implications on immunity and tumorigenesis are only just beginning to be recognized (Fig. 1) (Russo et al. 2016). Nevertheless, all the abovementioned factors could influence GI

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Fig. 1 The GI microbiota and immune system interact in a complex network with the cancer cells through a TME modulation. The GI microbiota can influence TME and thus tumor growth in both a positive or negative way and can also modulate the immune responses. Cancer growth is inhibited by the host immune system, which can be stimulated by the GI bacteria. Cancer can affect the host immunity by activating immunosuppressive pathways and can also modulate the GI flora

microbiota, changing its structure and functions during cancer development (Vivarelli et al. 2019). In healthy individuals, GI microflora acts as a symbiont, protecting against invading pathogens and avoiding cancer development (Pickard et al. 2017). When the fine equilibrium of this commensal bacterial community is destroyed, a dysbiosis state can develop, which can lead to pathological processes in the host, such as cancer (Cugini et al. 2021). Finally, increasing data on the TME physiology has suggested new targets within to improve cancer alternative therapies. In this chapter, we would like to reconsider the TME state of the art to define its boards within the holobiont (defined as the assemblage of a host and the many other species living in or around it, which together form a discrete ecological unit) vision and to assess its interaction with microbiota and their reciprocal influence in GI cancers. We will discuss how disequilibria (dysbiosis) could influence the mutual relationship between the host immunity and intestinal bacteria affecting oncogenesis, tumor progression, and response to immunotherapy treatment.

2

The Borders of GIT Microenvironment

In the past, tumors have traditionally been considered genetic disorders, which means that the main approach in the field of oncology, especially after the innovations brought by the molecular turn in biomedicine, has been to identify the

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biological (genetic) signature of the tumor. This approach has certainly paid off (both in terms of mechanistic comprehension and therapeutic intervention), but it has also clearly marked the understanding of cancer phenomena. In particular, the causes of GIT cancer have consequently been thought of as intrinsically linked to specific properties of tissues and cells in which it takes place. However, starting from the development of a pluralistic perspective on the origins of GIT cancers, and tumors in general, among all we can first remember the famous work by Hanahan and Weinberg (2000, 2011) where greater attention has also been paid to context-dependent causes (think, for instance, of the epigenetic dimension). Furthermore, greater importance has been progressively given to the idea that cancer, like any biological phenomenon, is profoundly determined and shaped (both in its genesis and development) by the environment that surrounds it and therefore in its so-called ecological dimension. Conversely, in this systemic feature, the environment enclosing the tumor is also affected by it. Therefore, in recent years, the TME concept has progressively been imposed in both research and clinical contexts. Despite its significance, a precise definition of microenvironment is still to come. This is due not only to the difficulty of experimentally characterizing the microenvironment but also for theoretical reasons. Indeed, from a purely molecular perspective, phenomena of an ecological nature (therefore interdependent with each other) present challenges both at an experimental and theoretical level. Specifically, such difficulties reverberate on the nature of the cause–effect relationship. In other words, it is particularly hard to dissect, in a purely mechanistic way, how much the microenvironment (prior to the tumor onset) guarantees the conditions for the development of the tumor itself and how much the intrinsic tumorigenic events lead to the formation of a specific microenvironment that is crucial for the disease development. Furthermore, one might wonder, spatially, how far the microenvironment extends, and whether distant but precise effects inherent to the onset of the disease (such as specific aspects of regulatory/organismal pathways) should be considered part of it or not (Laplane et al. 2018, 2019). Considering these difficulties, which see both experimental and conceptual dimensions deeply intertwined, some scholars have recently proposed a sort of microenvironment taxonomy (Laplane et al. 2018). This specification, even according to the authors, should not be thought of as exhaustive or fixed but rather as an indication of the opportunity to have a more pluralistic approach and a greater description granularity of these phenomena. According to this perspective, the authors distinguish at least six different levels (both in structural and functional terms) of the microenvironment: (1) tumor cell to tumor cell environment (TCTCE), that is, the one that develops from the specific interaction between tumor cells; (2) the tumor niche (CN) consisting of a more or less circumscribed portion of tissue that has certain characteristics (such as the relationship between tumor cells and the still healthy proximal context); (3) the confined TME (CTME) understood as that part of the microenvironment within the cancerous lesions; (4) the proximal TEM (PrTEM), i.e., the microenvironment adjacent to the tumor mass; (5) the peripheral TEM (PeTEM), i.e., those parts of the organism not strictly part of the tumor context but that are functionally connected

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Fig. 2 The multiple layers of the tumor environment. The figure depicts the different TME layers (TCTCE, tumor–cell to tumor–cell environment; TOE, tumor organismal environment). (Adapted from Laplane et al. 2018)

to it (e.g., lymph nodes); and finally, (6) the tumor organismal environment (TOE), which refers to all those macrofunctions or regulatory regions that, although very distant from the tumor, can influence its genesis and development (Fig. 2). Interestingly, whereas the purely molecular approach is used to consider biological phenomena in an isolated way, relatively to more or less circumscribed portions of biological substratum, the ecological view also allows us to make a point of a conceptual nature, remembering how something like a disease is not a fixed, static object that can be easily circumscribed in a single point but should rather be seen as a process that involves, to different degrees, diverse levels of interaction within the organism, if not the organism itself. The perspective that extends to the organism as such the privilege of being at the center of both scientific research and therapeutic investigation should not be interpreted in a vague way. Indeed, this approach does not reject the advances and discoveries made by focusing on specific anatomical sites and distinctive mechanisms, but rather inserts them into a broader framework. On the one hand, this vision well represents the research developments increasingly aimed to integrate elements and processes previously ascribed only to single systems. An explicative example is the growth of studies focusing on the interconnections between the immune, endocrine, and nervous systems (both central and enteric) (Pérez et al. 2021). On the other hand, even if only focusing on the immunological aspects, different scholars seem to suggest that it is the action field of a system such as the immune system is the organism as a whole (Poon and Farber 2020).

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This perspective change shows how the notion of the microenvironment, also by virtue of its ecological nature, can and should be inserted into a frame that is more representative of the different levels of biological organization and their close interconnection and interdependence. Thus, the disease study, especially in tumors, now presents challenges that force researchers and clinicians to consider it, in a unitary way, within its ecological scalability: from the distinctive molecular mechanisms to the global organismic response. Deprived of its context, even the microenvironment notion risks becoming too reductionist an instrument, both in terms of explanation and as a target of therapeutic activity. In other words, it is not possible to study and use the microenvironment in a profitable way if we want to consider it in a pure, purified, and isolated way rather than fully inserted in its systemic dimension. This view change is even more necessary if we consider that the concept of the organism itself is also undergoing profound revision. In particular, the so-called holobiontic dimension has become increasingly popular, according to which biological individuals macroscopically understood, such as animals and plants, are actually functional (not occasional) associations of different species (Boem et al. 2021; Bordenstein and Theis 2015). A particularly important example is the kind of holobiontic integration between the human part (often called the “host”) and its microbiota. Indeed, considering the tumors, more studies suggest that the microbiota not only contributes to specific local TME characteristics but, by virtue of its systematic nature and pervasiveness at the organismic level, it is capable of influencing numerous global functions and therefore directly and indirectly interacting with the disease development (Laplane et al. 2019; Wong-Rolle et al. 2021). Microbiota’s ability to modulate immune activities (both locally and at a general level) or to directly influence some pathways (both at the tissue and organismic level) (Chiu et al. 2017) makes it a privileged actor in the TME study both in its meaning of “context of proximity” to the tumor and also, in a broader perspective, including the entire biological individual.

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The New “Actors” of the TME: The Gut Microbiota and Its Metabolites

3.1

The Microbiota of the Gastrointestinal Tract

Previously, the human body was thought to be a self-sustaining organism, able to control all the complexity of its cellular metabolism. However, different recent studies have demonstrated that the human body is, in fact, an ecosystem that included also trillions of microorganisms, which are known as “microbiota.” The human microbiota could contain a number of microorganisms that is 10 times more than the total number of human cells in the body. The microbiota inhabits all the body surfaces exposed to the surrounding environment, such as mucosa tissues and the skin, from the GI to the respiratory and urogenital tracts.

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This human GIT ecosystem is the outcome of an evolutionary process between microflora and the mammalian body. It encompasses the greatest amount of microbes able to generate compounds used as nutrients, thus creating a favorable setting for colonization; indeed, the colon includes more than 70% of all body microbial flora. It is important to highlight that the microbiota has a crucial effect on physiological mechanisms like food digestion and immune system reactions (Belkaid and Hand 2014). Regarding its composition, it consists of microorganisms from the Archaea, Bacteria, Eukarya, and viruses. The majority of bacteria are strict anaerobes, with also facultative anaerobes and aerobes. Although commensal bacteria are symbiotic, they can cause pathology after translocation through the mucosa or in particular conditions, such as immunodeficiency (Maier et al. 2014). Overall, the composition of the commensal bacteria is personal, but the richness of the bacterial population profile among body districts is greater than it is between individuals (Berg et al. 2020). A bacterial community that is commonly present in multiple body sites can be referred to as the “core” of a healthy microbiota (Rinninella et al. 2019). Over 50 bacterial phyla have been defined but only 2 of them dominate the normal GIT flora: Bacteroidetes and Firmicutes, with Actinobacteria, Proteobacteria, Fusobacteria, Verrucomicrobia, and Cyanobacteria in marginal proportions (Jandhyala et al. 2015). The amount of microbial species living in the human intestine varies greatly between people, but, according to study on multiple subjects, the total human enteric microflora is composed of over 35,000 bacterial species (Thursby and Juge 2017). Approximately 70% of bacteria cannot be cultured using standard microbiological methods; indeed, traditional culture-based methods only detect about 30% of our microbiota (Ito et al. 2019). Nowadays, genomic nextgeneration sequencing (NGS) approach is critical for detecting the bacterial microbiota composition and metagenome, and these techniques provide more evidence about the relevance of the microbial community in host metabolic activities, cancer evolution, and inflammation. The oral cavity, stomach, small intestine, and colon are the four distinct sites of the human GIT, each with its own activity as a specific microbial community. The enteric mucosa is the body’s largest area that is persistently subjected to microbial and nutritional antigens. However, the organization of the intestinal flora is not uniform. Bacterial concentration in the human GIT increases from the mouth (less than 200 species) to the colon (bacteria reaching 1,010–1,012/g luminal content, with anaerobe bacteria predominating) (Sędzikowska and Szablewski 2021). In addition, the microbial structure shifts between these GIT locations. The comparison of biopsy samples of the small intestine with the colon from healthy controls showed that several microbial strains are increased at different sections. Bacilli of the Firmicutes and Actinobacteria are abundant in small intestine specimens. The intestinal epithelium is divided from the lumen by a dense mucus layer, resulting in significant latitudinal heterogeneity in microbiota communities. The microbiota of the gut lumen is greatly different from the microflora incorporated in the mucus layer, as well as the microbial community resident in the epithelium. Numerous

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types of bacteria found in the intestinal lumen were unable to enter the mucus layer or epithelial crypts. Streptococcus, Bacteroides, Bifidobacterium, members of the Enterobacteriaceae, Enterococcus, Clostridium, Lactobacillus, and Ruminococcus were all found in feces, but only Clostridium, Lactobacillus, and Enterococcus were found in the small intestine’s mucus layer and epithelial crypts (Dieterich et al. 2018). Bacterial pathways (enzymes, metabolic activity, adhesion capacity), host elements (bile acids, mucus pH, digestive enzymes, transit time), and nonhost factors could all make a contribution to the modifications along the GIT length (medication, nutrients, environmental factors) (Rowland et al. 2018). The GI microflora is important to host metabolism because it generates compounds that interact with the host and implements important metabolic functions. The GM members, in particular, are a first defense against pathogen invasion and break down indigestible dietary components (Rowland et al. 2018), promote angiogenesis, support fat metabolism, synthesize vitamins, aid in immune system development, and maintain homeostasis (Kho and Lal 2018) (Fig. 3). The microbial community is isolated from the internal gut milieu by a layer of epithelial cells that act as a barrier, balancing the crosstalk between the immune host system and the external environment. Moreover, epithelial layers are able to counteract microorganism invasion; indeed, adaptive and innate immune responses

Fig. 3 The main functions of GI microbiota members

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protect the mucosa and internal environment of the human body. Nearly 80% of immunological cells are involved in the mucosal-associated immune system, with the majority of these cells residing in the GIT, where the level of immunogenic food components and bacterial flora is highest in comparison to other areas of the body (Russo et al. 2016). Normally, the microbial flora does not induce a pro-inflammatory response since the immune system recognizes the commensal bacteria and maintains homeostasis; however, when these pathways are compromised (e.g., use of antibiotics, immunodeficiency, and unhealthy diets) or new pathogenic bacteria are presented into this balanced system, the immune system reacts to the microbial population, activating a pathological condition and fostering inflammation and tumor growth in the GIT (Russo et al. 2016). Several studies suggest that a disequilibrium of the intestinal flora and its metabolic activities is associated with the onset and development of GI pathologies such as colorectal cancer (CRC), functional dyspepsia, severe diarrhea, inflammatory bowel disease (IBD), celiac disease, and irritable bowel syndrome (IBS) (NagaoKitamoto et al. 2016; Yu et al. 2021). It is already comprehended that the GM imbalance (dysbiosis) can be triggered by both intrinsic (e.g., stress, genetics, and aging) and extrinsic factors (e.g., appendectomy, diet, and antibiotic use) (Padhi et al. 2022).

3.2

Alteration of Microbiota in the GI Cancers

The relationship between cancer, TME, and microbes is intricate and complex. GM may influence tumor development affecting the TME by inducing oxidative stress, genotoxicity, host immune response disturbance, and chronic inflammation. Alteration in microbiome composition, linked to oncogenesis and cancer progression, has been observed in several GIT compartments. Regarding the esophageal cancers, a general decreased species’ abundance is detected in esophageal squamous cell carcinoma and esophageal adenocarcinoma (the two distinct histological types), as well as Barrett’s esophagus (a precancerous lesion of the esophageal adenocarcinoma) compared with normal esophageal tissue. Genera that appeared enriched in Barrett’s esophagus are Streptococcus, Campylobacter, Prevotella, and Veillonella. In esophageal squamous cell carcinoma, Streptococcus species, Veillonella parvula, and Porphyromonas gingivalis are the most abundant species, whereas Lautropia, Peptococcus, Treponema, Corynebacterium, Moryella, and Cardiobacterium genera are depleted (Liu et al. 2018; Smet et al. 2022). Moreover, Fusobacteria is enriched in esophageal squamous cell carcinoma compared with controls (Shao et al. 2019). An enrichment of Lactobacillus fermentum, Enterobacteriaceae, Prevotella, Leptotrichia, and Akkermansia muciniphila, and a depletion of Streptococci have been observed in esophageal adenocarcinoma (Shao et al. 2019; Snider et al. 2019). Furthermore, epidemiological data shows an opposite relation between Helicobacter pylori eradication and the occurrence of esophageal adenocarcinoma,

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which could be caused by a change in the gastric microbial community (Peek Jr. and Blaser 2002). In addition, H. pylori infection has been indicated as one of the most frequent direct causes of gastric cancer (Yu et al. 2017). Indeed, recent evidence suggests that H. pylori may stimulate the local immune response (Amedei et al. 2003, 2014; Orsini et al. 2007) to gastric mucosa through generation of inflammatory molecules, such as chemokines and cytokines within gastric tissues, for further oncogenic changes caused by other microbes (Coker et al. 2018). However, a lot of research has demonstrated that stomach dysbiosis, involving multiple bacteria communities, is a dynamic phenomenon that correlates with cancer progression. So, for the progression and metastasis of gastric cancer, a synergistic interplay among the TME elements, such as H. pylori infection, immune cells and mediators, and different proteins, along with matrix metalloproteinases, is essential (Li and Yu 2020; Sohn et al. 2017). Moreover, CRC has been linked to microbial signature variations within the tumor differing from the bacterial assemblage of the adjacent normal tissue. These alterations include decreased diversity and perturbations in the community structure, which become more pronounced as the CRC progresses (Fang et al. 2021). Reduced amounts of favorable significant protective clades, such as butyrate-producing species from Clostridium clusters IV and XIV have been reported in CRC, whereas an increase in species such as Fusobacterium, Campylobacter, Escherichia, Bacteroides, and Porphyromonas has been attributed to an increase in pro-oncogenic capacity (Russo et al. 2017). In addition, Fusobacterium nucleatum frequently is found in CRC tissue, both at the adenoma and adenocarcinoma stages, grouped with other oral commensal species, including Leptotrichia, Peptostreptococcus, and Campylobacter species. Because of its ability to localize with tumor-enriched lectins via the outer membrane protein [fatty acid-binding protein 2 (Fap2)], F. nucleatum is commonly encountered at higher levels in the TME. Furthermore, F. nucleatum alters the TME by inhibiting the natural killer (NK) cells’ antitumor responses and promoting the myeloid cell recruiting process. Bacterial profiles related to Fusobacterium-enriched but not Fusobacterium-negative malignancies were found in distant metastases, indicating that F. nucleatum affects also microbial metastatic dissemination (Russo et al. 2017). The microbiota members that have been associated with CRC tumorigenesis are enterotoxigenic Bacteroides fragilis (ETBF), Escherichia coli, Streptococcus gallolyticus, and Enterococcus faecalis. Numerous studies have looked into the GM role in hepatocellular carcinoma (Bartolini et al. 2021). An increase in the richness of pro-inflammatory intestinal communities, such as Proteobacteria and Enterobacteriaceae, has been observed. Besides, some studies found that microbiome changes are linked to lower levels of butyrate-producing Clostridiales and anti-inflammatory species such as A. muciniphila. All these strains may affect the cancer’s overall pro-inflammatory phenotype (Komiyama et al. 2021). In recent years, evidence has shown that bacteria take part in the beginning and progression of cancer at sites previously considered sterile, such as pancreas (Nejman et al. 2020). In pancreatic cancer, bacteria belonging to the Proteobacteria phylum were the most represented (Nejman et al. 2020). Moreover, also alteration in

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species belonging to the Enterobacteriaceae and Pseudomonadaceae families was observed (Geller et al. 2017). The most prevalent bacteria phyla in the pancreas TME included Proteobacteria, Bacteroidetes, and Firmicutes (Li et al. 2021). In addition to intratumoral dysbiosis, other reports have shown a difference in the GM between pancreas of tumor patients and healthy controls, with increase in Bacteroidetes and lower Firmicutes (Ren et al. 2017). Finally, another study suggests that Fusobacterium species are linked to a worse prognosis in pancreatic cancer, meaning that they could be used as a predictive biomarker (Mitsuhashi et al. 2015).

3.3

Microbial Post-biotics of the GI Tract

Because the host–microbiome relationship in GI tumors has only recently been discovered, other mechanisms, such as aberrant cell-to-cell connections and the generation, conversion, and sensing in the TME of bacterial bioactive small molecules, known as “post-biotics,” could be involved. Notably, post-biotics are “nonviable” bacterial products or metabolic by-products (metabolites) of probiotic microorganisms that promote biological activity in the host (Patel and Denning 2013). Microbiome-modulated post-biotics (MMPBs) have the potential to affect host pathways such as proliferation, differentiation, migration, and cellular death. Furthermore, MMPBs may influence mucosal maturation and activity, as well as systemic immunity (Gaudet et al. 2015). The study of bacterial post-biotics as messengers between GM and immune system could in part clarify the deficient host–microbial interconnections within the TME in GI cancer. More understanding of how GM metabolic activity can influence the host immune system (immunomodulation) may strengthen translation to clinical applications. However, GM communicates with the host through the generation of metabolites such as small chain fatty acids (SCFAs), tryptophan (Trp) catabolites, and bile acids. The MMPBs are engaged in differentiated bioactive activities for the host cells, resulting in a wide range of pathophysiological effects (Brestoff and Artis 2013). SCFAs are the most investigated MMPBs in GI cancer, and their production is influenced by diet; indeed, they are secondary compounds generated through the fermentation of nutritional substrates, such as proteins, peptides, resistant starches, and undigested fibers by the GM. They represent a class of fatty acids with fewer than six carbons (such as acetic, formic, propionic, butyric, and valeric acid) whose generation is shaped by a number of factors, including host diets and GM variability with the presence of specific commensal bacteria (Canfora et al. 2015). The Bacteroidetes phylum mainly produces acetate and propionate, whereas the Firmicutes phylum secretes butyrate (Magne et al. 2020). SCFAs are a source of energy for local colonocytes within the eukaryotic TME, but they can be also transported to blood circulation and many other tissues. Intriguingly, the amount of the primary SCFAs (butyrate, acetate, and propionate) can vary across the entire digestive tract and can have different production ratios and physiological activities. Indeed, the synthesis of the various fermentation products varies depending on the

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microbial community and environmental factors such as pH, hydrogen partial pressure, and available substrates. As for the SCFAs synthesis, acetate, which is the most represented SCFA, is generated by GM as a fermentation product, but also by acetogenic bacteria, from H2 and CO2. Propionate and acetate were found in both large and small intestines, with a larger ratio of butyrate in the cecum and colon (Vogt et al. 2015). Propionate can be generated through the lactate pathway by Firmicutes and/or succinate pathway by Bacteroidetes phylum (Louis et al. 2014), while succinate is a metabolic end product for some bacteria, and specialist succinate utilizers convert most of the succinate into propionate (Macfarlane and Macfarlane 2003). Even so, while butyrate is a favorable source of energy for gut epithelial cells and has a low level in the systemic circulation, propionate is mostly metabolized in the liver, and only acetate has elevated concentrations in peripheral blood (Sleeth et al. 2010). SCFAs have also modulatory effects on immune system cells. Indeed, their role is to ensure the gut barrier’s status quo and regulate the activation and proliferation of T-regulatory cells (Tregs), able to help the body maintain control during inflammation-induced T helper (Th) cell activity. As a result, a lack of SCFAs leads to a decrease in Tregs in the tissue, which indirectly favors the recruitment and proliferation of Th17 cells, thereby promoting inflammatory processes in the gut mucosa (Camilleri et al. 2019). The recent findings of SCFAs’ ability to bind receptors such as GPR41, GPR43, and GPR109a (G-protein-coupled receptors that are typically expressed on a wide variety of cell types) allowed for the clarification of SCFA regulatory activity in GI cancer, suppressing inflammation and oncogenesis in the colon (Singh et al. 2014). Butyrate, and to a lesser extent propionate, has been found to affect CD8+ T cell signaling pathways, increasing the expression of IFN-γ and granzyme B. Butyrate stimulates histone deacetylation via HDAC inhibition, resulting in higher expression of CD8+ T cell effector molecules (Luu et al. 2018). Furthermore, metabolomic analyses revealed an altered level of Trp and Trp metabolites in patients with GI disorders, in addition to altered SCFA levels (Wyatt and Greathouse 2021; Russo et al. 2019) Trp metabolic activity via the kynurenine (Kyn) pathway, as well as microbial modification of Trp to indolic complexes, is critical for host health and is both altered in cancer development. Changes in tryptophan metabolism begin early in CRC development as an adaptive mechanism for the tumor to evade immune surveillance and metastasize. Moreover, Trp metabolism by bacteria may involve multiple pathways as it is a substrate for both intestinal mucosa and bacterial enzymes (Nozaki and Ishimura 1972). Trp is produced from dietary substrates and is absorbed by SLC6A19/B0AT1 (a sodiumdependent neutral amino acid transporter) (Hashimoto et al. 2012). It is a precursor for many MMPBs and can perform a variety of host functions, including immune homeostasis and inflammatory response. The Trp availability is required for protein synthesis, production of indole and nicotinamide derivatives via kynurenine, and synthesis of serotonin (Richard et al. 2009). Bile acids (BAs) are primarily synthesized in the liver and secreted to the gallbladder before being released into the duodenum, following food consumption. The amount and composition of the BA pool in the digestive tract can be modified by GM via primary to secondary BA biotransformation.

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They are essential for maintaining a healthy GM, lipid and carbohydrate metabolism, insulin sensitivity, and innate immunity. The BA not only promotes emulsification and fat solubilization, but also increase the expression of a nuclear bile acid receptor (FXR) and a membrane G protein-coupled receptor (TGR5). This compound represents the mechanistic connections between BA and development of GI cancer. The reduction in secondary BA synthesis, caused by GM dysbiosis, reduces the activation of nuclear receptors FXR and TGR5 in the ileum, resulting in retained bile salts, increased gut permeability, small bowel translocation, and bacterial overgrowth, all of which make a significant contribution to hepatic diseases (Sinal et al. 2000). The FXR plays a major role in mediating intermodulation between the host and GM, specifically through regulation of enterohepatic BA circulation. FXR regulates BA levels via a tissue-specific mechanism (Goodwin et al. 2000). In addition, mouse models showed that FXR activation, stimulated by BA compounds (converted by GM), may preserve against bacterial overgrowth, gut permeability, and small bowel translocation (Inagaki et al. 2006). The degree of FXR activation may be modulated by GM dysbiosis, which causes BA variation and, as a result, liver disease caused by retained bile salts and a leaky gut. Bacteria translocated from the intestinal tract may also reduce FXR activation in hepatocytes, resulting in decreased BSEP (bile salt export pum) activity.

4

The Microbiota–Immunity Axis

4.1

The “Immune” TME

As previously reported, immune cells play a major role in the TME, in suppressing or promoting tumor growth, inducing a dynamic and ever-changing condition (Whiteside 2008). From the immunological point of view, the TME shows different composition depending on the type of tumor, but hallmark features include immune cells, such as T and B cells, macrophages, NK cells, neutrophils, dendritic cells (DCs), stromal cells, blood vessels, and extracellular matrix (Fig. 4). A persistent inflammatory state is a common feature underlying the development of malignant neoplasm in several types of GI cancer, including CRC and hepatocellular (Patel 2020). Broadly, immune cells are represented by innate and adaptive cells. In particular, innate immunity is a nonspecific defense system that kicks in the hours after a foreign antigen enters the body, represented by macrophages, neutrophils, NK, and DCs. On the other hand, adaptive immunity is triggered by antigen exposure and uses an immunological memory to counteract a threat and improve immune responses. This type of immune defense includes T, B, and NK cells (Černý and Stříž 2019). In this regard, there are various specific populations of T cells that influence carcinogenesis within the TME. In detail, cytotoxic T cells (CD8+) are the immune cells that detect abnormal tumor antigens expressed on cancer cells and are able to destroy them. However, the presence of cytotoxic T cells in the TME is frequently linked to a better prediction in cancer patients. In addition,

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Fig. 4 Immune tumor microenvironment. The TME composition differs between cancer types. TME generally includes immune cells, such as T and B cells, NK cells, macrophages, neutrophils, DCs, endothelial cells, extracellular matrix, and tumor cells

in order to kill tumor cells, cytotoxic T cells inhibit angiogenesis by secreting IFN-γ (Manjarrez-Orduño et al. 2018). Within the TME framework, the CD4+ T-cells differentiate into a number of subtypes and hence coordinate a wide range of immunological responses. Moreover, Th-1 cells are pro-inflammatory CD4+ T cells that secrete interleukin-2 (IL-2) and IFN-γ to assist CD8+ cells (van der Leun et al. 2020). Increased levels of Th-1 cells in the TME have been linked to better outcomes in a variety of cancers (Anderson and Simon 2020; Niccolai et al. 2017). In comparison to T cells, the TME owns a small number of invading B cells, known for producing antibodies’ immune cells. They are able to present antigens and secrete cytokines. B cells are most commonly found in the tumor borders and in lymph nodes near the TME. Tumor-infiltrating B cells are required for the formation of “tertiary lymphoid structures,” which are ectopic lymphoid structures within the TME. In addition, antitumorigenic activities of B cells include antigen presentation to T cells, production of antitumor antibodies, and secretion of cytokines promoting cytotoxic immune responses (Anderson and Simon 2020). On the other hand, the

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presence of B cells in the TME can predict a poor prognosis in several cancers, such as bladder cancer. Finally, the regulatory B cells promote tumor growth by secreting cytokines (such as IL-10) that inhibit macrophage, neutrophil and cytotoxic T-cell immune responses (Černý and Stříž 2019; Li et al. 2020). A recent study has revealed that NK cells are also regulatory cells that interact with DCs, macrophages, T cells, and endothelial cells in a reciprocal manner (Vivier et al. 2008). NK cells can be usually classified into two types, based on their function: those that directly participate in cell-mediated tumor cell death and those that release inflammatory cytokines. In general, NK cells are extremely effective at killing circulating tumor cells, but their cytotoxic action is less effective at killing tumor cells in TME. In most cancers, the infiltrated macrophages have been shown to have an important role in providing an immunosuppressive microenvironment for tumor growth. In fact, macrophages are a key component of the innate immune system that regulates immune responses by phagocytozing pathogens and presenting antigens. Two distinct subsets have been described: M1 and M2 macrophages (Martinez et al. 2009). Typically, M1 macrophages phagocytize and kill cells, and immune-suppressive M2 macrophages, which aid in wound healing. While both types of macrophages can be found within the tumor, the TME supports tumor growth and progression by promoting the M2 phenotype, through hypoxia and the production of some cytokines (e.g., IL-4). In several cancer types, such as gastric cancer, high macrophage infiltration is associated with a poor prognosis (Hao et al. 2012). As one of the most abundant leukocytes in the immune system, neutrophils play a pivotal role in cancer progression via different processes, including angiogenesis, immunosuppression, and cancer metastasis (Wu et al. 2019). In fact, depending on the type of tumor and the disease stage, neutrophils can either prevent or enhance tumor growth. As a tumor grows, neutrophils are drawn to the TME, where they contribute to the inflammation increase by releasing cytokines and reactive oxygen species (ROS), which promote tumor cell death (Wu et al. 2020). Furthermore, tumor cells’ aberrant metabolism produces metabolic alterations in TME (e.g., hyperglycolysis, lactate, and lipid deposition), which inhibit the activity of another antigen-presenting cell (APC) DCs (Peng et al. 2021). DCs help to initiate pathogenspecific T-cell responses by bridging the gap between adaptive and innate immunity. DCs’ fate is determined by the TME, which can provide environmental signals that either cause an immune response to tumor cells or allow them to pass. DCs are triggered to tolerate the presence of tumor cells through cytokines released by the TME, which prevent the formation of an immune response (Du et al. 2018). Finally, cancer cells attract supporting cells from the adjacent endogenous stroma to promote critical phases of tumor formation. The stromal cell composition differs widely between tumor types and includes vessel endothelial cells, fibroblasts, adipocytes, and stellate cells. Once attracted to the TME, stromal cells release a range of factors that promote angiogenesis, proliferation, invasion, and metastasis (Denton et al. 2018).

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The Role of Microbiota–Immunity Axis in Gastrointestinal Cancers

As result, for the aforementioned processes, GM and the host immune system have established a viable two-way relationship, ensuring the preservation of microbial eubiosis (Al-Rashidi 2022), described as the “microbiota–immunity axis” (Han et al. 2021; Jiao et al. 2020). In particular, the highly active microbial population has been demonstrated to interact with the immune system of the host and play a variety of positive tasks, explaining also the host organism tolerance and the microbiota–immune balance (Romagnani 2006). As previously mentioned, the dysbiosis condition could become a pivotal driver for various diseases, with distinct microbial profiles that can cause pathophysiology in several organs (Clemente et al. 2012; Lazar et al. 2018), including inflammation and cancer (Vivarelli et al. 2021). The presence of dysbiosis status induces dysregulated immune responses, so the host becomes more vulnerable to infections. Moreover, as immunotolerance is also affected, the immune system can react against the self-components with autoimmune reaction, which can vary in strength, being either overactivated (as in allergic reactions and chronic inflammation) or underactivated (as in immunodeficiency and malignancy) (Toor et al. 2019). Regarding GI cancer, the microbiota immunity–axis influences tumor genesis and progression, both directly on tumor cells or indirectly, through the immune system modulation, affecting cancer immunosurveillance (Jain et al. 2021). In fact, a sophisticated interplay between host immune response, environmental variables, and microbial factors, such as H. pylori infection, can lead to gastric cancer (Nasr et al. 2020). As previously reported, colonization of the gastric mucosa by H. pylori induces a multiple immunity response that includes a local infiltration of immune cells, including neutrophils, macrophages, T and B cells, and cytokine secretion (Das et al. 2006). While this huge immune response occurs, H. pylori makes immune cell hyporeactive, suppressing their proliferation and production of interferongamma (IFN-γ) (Das et al. 2006). In this way, a downregulation of immune surveillance mechanisms occurs and the transformed cells evade the apoptosis mechanisms. Concerning CRC, the microbiota–immunity interaction appears to play a key role in all development stages, from oncogenesis to therapy and prognosis (Bartolini et al. 2020). This mechanism is expressed in particular through F. nucleatum, which promotes cancer through cell proliferation and immune response suppression (Nosho et al. 2016). Fusobacterium species can promote tumor growth by inducing multiple immunosuppressive adaptations, inhibiting immune response, and increasing myeloid-derived suppressor cells and tumorassociated macrophages inside colorectal tumors (Park et al. 2017). In particular, F. nucleatum has been implicated in a decrease in CD3+ T lymphocytes, as well as in an increase in the production of cytokines with claimed pro-tumor effect, such as IL-6, IL-12, IL-17, and TNF-α, IL-12, and IL-17, and in a suppression of Th cell activity (Chen et al. 2017; Mima et al. 2016). Among all, IL-17 and IL-22, in particular, can be secreted even after a stimulation of Th17 cells induced by a

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pro-inflammatory state caused by a dysbiotic microbiota (Russo et al. 2016; Wu et al. 2009). Similarly, some strains of E. coli and B. fragilis can induce a DNA damage by producing genotoxins, such as B. fragilis toxin and colibactin toxin, already found in patients with adenomatous polyposis (S. Wu et al. 2009). In detail, these toxins can induce an intestinal tissue damage, trigger chronic intestinal inflammation, and play a crucial role in the CRC development (Cheng et al. 2020). In pancreatic cancer, bacteria increase myeloid-derived suppressor cell recruitment, suppressing the Th1 immune response, and promoting IL-17 release. All these immunosuppressive consequences also contribute to immunotherapy lack of success (Huber et al. 2020). In addition, a recent study has found increased incidence of oral bacteria including F. nucleatum in cystic lesions of human pancreas (Gaiser et al. 2019). Similarly, a large amount of F. nucleatum was also found on bile samples from gallbladder cancer patients (Tsuchiya et al. 2018). To protect the host from infections and illnesses, the intestinal barrier, immune response, and microbiota interact in a dynamic process. A change in GM composition can activate the mucosal immune response, leading homeostasis to be disrupted. In this scenario, bacteria and immune cells migrate to the liver, causing inflammation-mediated liver damage and possibly paving the way for chronic hepatic disease and liver cancer (Bartolini et al. 2021; Peterson and Artis 2014; Yang et al. 2020). The liver immune system is characterized by cells of the innate immune system, including Kupffer cells, NK cells, and a particular abundance of cells from the adaptive immunity, especially T cells (both αβ and γδ). The role of γδT cells in liver cancer is controversial and depends mainly on subsets and disease stage. In fact, on the one hand, their ability to infiltrate tumors causing the progression of liver cancer and, on the other hand, their cytotoxic action combined with NK cells seem to be able to prevent the recurrence of hepatocellular carcinoma (Zhou et al. 2020). Related to this, microbiota plays an important role in maintaining the homeostasis of hepatic γδT cells. In detail, the mechanism could be attributed to lipid antigens, a microbiota component, which activates hepatic γδT cells and produces IL-17A. Hence, the activated γδT17 cells act on their pro-inflammatory and anti-infection abilities, exasperating liver cancer (Xi et al. 2019). In addition, increased intestinal permeability during liver cancer allows bacterial translocation into the liver, particularly Lactobacillus gasseri. As a result, liver T cells secrete IL-17A in response to microbial stimulation, aggravating liver disease (Tedesco et al. 2018). In conclusion, a thorough knowledge of the microbiota–immune axis will provide light on the fundamental mechanisms behind GM dysbiosis and its impact on liver diseases, including cancer. Hence, microbiota–immune axis can also predict disease progression and survival, as well as influence how well cancer treatment works. The ability to manipulate the microbiota can be used to improve the efficacy of immunotherapies while lowering their toxicity (Yi et al. 2019). In particular, increasing data suggests that gut dysbiosis may have a direct impact on local and systemic antitumor immunity. In addition, recurrent antibiotic exposure, which impairs intestine eubiosis and promotes the spread of gut infections, has been linked to an increased cancer risk (Cianci et al. 2019). In general, dysbiosis may play a role in tumor formation or the failure of immune checkpoint inhibitor-based therapy (Shui et al. 2019).

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Targeting TME for Cancer Immunotherapies

Numerous studies have documented the potential for using microbiota – and its derived immune metabolism – within the TME as a new therapeutic target for cancer (Suraya et al. 2020). Because GM influences both innate and adaptive cancer immunity, it is interesting to presume that it may contribute to regulating antitumor immunity induced by chemotherapy, radiotherapy, and immunotherapy. Regarding immunotherapy, today the ability to stimulate antitumor T cell responses that block inhibitory T cell signaling pathways has transformed the treatment for cancer. Immune checkpoint inhibitors (ICIs) are monoclonal antibodies that identify specific membrane receptors on the surface of T cells, preventing tumor cells from inhibiting them. The programmed cell death protein 1 (PD-1) and its ligand are the targets of the most widely used monoclonal antibodies’ ICIs (Pardoll 2015). Immunotherapy has significantly improved the overall survival of cancer patients. Nevertheless, only a small percentage of patients benefit from ICIs (Jiang and Zhou 2015), and the explanations for this phenomenon are not entirely known (Russo et al. 2020). It is important to note that the latest study emphasizes the function of microbiota within TME in defining immune responses to ICI treatment (Sears and Pardoll 2018), characterizing tumor-infiltrating lymphocytes (TILs). In addition, TILs appear to be involved in response to checkpoint inhibition (Cesano and Warren 2018). Mouse models are used to observe the relation between ICIs and particular microbiota members (Sivan et al. 2015) (Vetizou et al. 2015; Taur et al. 2014), suggesting that the efficacy of checkpoint blockade could be improved through microbiota modulation (Fig. 5). Moreover, melanoma growth in mice was different on the basis of distinct microbiota profile. Variations in antitumor immune-mediated response, particularly in intratumoral CD8+ T cell accumulation and tumor-specific T-cell responses, were documented. Intriguingly, upon cohousing or after fecal microbial flora transplantation (FMT), it was observed that the different antitumor immune-mediated response was reset (Sivan et al. 2015). Bacteroides and Burkholderia were linked to the GM antitumor activity in another study that looked at subjects with various malignancy, including antibiotic treatment during a CTLA-4 (protein receptor that functions as an immune checkpoint) treatment. In response to these bacteria, innate immune cells produce IL-12, which can activate the adaptive immune response, stimulating T cells (Vetizou et al. 2015). Furthermore, a rise in Collinsella aerofaciens, Enterococcus faecium, and Bifidobacterium longum was found through the GM evaluation of patients who responded positively to PD-1 blockade. When fecal specimens from responders patients were transferred to germ-free mice, tumor growth was moderate and therapeutic activity was better than in mice that received samples from nonresponder patients. Additionally, an increase in CD8+ T cells and reduced Tregs were observed in the TME (Matson et al. 2018). These exploratory mouse investigations supported the crucial GM involvement in cancer ICI treatment and incentivized clinical investigation to establish the impact of the microflora on ICI therapies. Moreover, another study showed that primary resistance to ICIs can be related to abnormal

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Fig. 5 Gut microbiota impact on the efficacy of PD-1 blockade. Specific GM profiles correlate with response to PD-1 blockade in tumor patients. Fecal microbiota transplantation (FMT) from responders into mice improves responses to anti-PD-1 treatment and is correlated with increased anticancer CD8+ cells in the tumor environment. Mice receiving FMT from nonresponders’ patients did not benefit from anti-PD-1 therapy, and tumor microenvironment is enriched in immunesuppressive CD4+ Tregs

enteric microbiota profiles, demonstrating that anti-PD-1/PD-L1 treatment was effective in patients with advanced epithelial malignancy who were not treated with antibiotics, particularly in comparison to the results of those who did receive antibiotics (Routy et al. 2018). This finding suggests that antibiotic therapy can damage GM, damaging immune checkpoint blockade response. In addition, patients responding to PD-1 blockade showed a distinctive microbial structure, enriched in Akkermansia and Alistipes. Furthermore, germ-free mice were treated with FMT using fecal samples from responding patients prior to anti-PD-1 therapy. The immune response was reported to be increased in these mice while the immune response of germ-free mice treated with FMT from nonresponders was recovered by oral supplementation with A. muciniphila. By increasing the enrolment of CXCR3 + CCR9+ CD4+ T cells into mouse tumor beds, these bacteria improved the efficacy of PD-1 blockade in an IL-12-dependent process (Routy et al. 2018). Gopalakrishnan and colleagues studied the oral flora and GM of patients with metastatic melanoma receiving anti-PD-1 therapy. Regarding the systemic immune responses, gut samples enriched in Clostridiales, Ruminococcaceae, or Faecalibacterium from patients with malignancy showed more effector T cells (CD4+ and CD8+) in the peripheral blood and a protected cytokine response to anti-PD-1 treatment. On the other hand, patients whose gut samples were enriched in Bacteroidales had higher frequencies of Tregs and a reduced cytokine response to anti-PD-1 treatment (Gopalakrishnan et al. 2018). Immune profiling revealed increased antitumor and systemic immunity in melanoma patients responding to therapies showing a favorable enteric microbial flora, as well as in germ-free mice receiving FMT from responding subjects.

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However, GM can also cause toxicity to immune checkpoint blockade. This consequence was first detected in animal models and then in patients (Chaput et al. 2017), (Frankel et al. 2017), (Zitvogel et al. 2017). The microbial taxa related to this effect belong to Firmicutes phylum and Ruminococcaceae family (Gopalakrishnan et al. 2018), (Chaput et al. 2017), (Frankel et al. 2017). In contrast, microbiota taxa that do not respond to ICIs belong to Bacteroidales order; however, an abundance in these taxa generally reduces the ratio of toxicity (Gopalakrishnan et al. 2018), (Chaput et al. 2017), (Frankel et al. 2017).

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Conclusion

The multifaceted series of events that lead to the evolution and progression of GI cancer, as well as its intense interaction with the surrounding TME, should be investigated further, especially in light of the presence of the microbiota–immunity axis, which certainly contributes to enlarging the TME boundaries. Cancer treatment has undergone a revolution in the last decade (Russo et al. 2020). Previously, drugs targeted tumors more broadly (e.g., chemotherapy), but novel therapeutic approaches target particular cells within the TME. While therapeutically targeting the TME is an appealing strategy for cancer treatment, existing FDA-approved treatments are ineffective. As we learn more about how the TME contributes to tumorigenesis, new therapeutic targets and strategies will emerge. In this scenario, understanding the multiple layers of tumor microenvironment, as well as the reciprocal interactions among its members, can help to implement better therapeutic regimes for cancer management; however, a more integrated and pluralistic approach using combination of strategies appears to be more effective than single modalities because tumor heterogeneity arises from a variety of signaling pathways/crosstalks that exist in the network of communicating cancer cells. Compliance with Ethical Standards The authors declare that there is no conflict of interest.

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Epithelial-Mesenchymal Transition in Gastrointestinal Cancer: From a Basic to a Clinical Approach Simona Gurzu and Ioan Jung

Abstract

Since 1968, when Betty Hay first described the concept of epithelialmesenchymal transition (EMT), over 54,000 articles have been published on this topic in the Medline and Web of Science databases. In the last 5 years, over 5500 papers on EMT in physiological, tumor, and non-tumor lesions have been issued annually. The first guideline for EMT research was edited in 2020 by the EMT International Association (TEMTIA). Despite rapidly growing interest in this subject, the EMT process is far from being understood. It is involved in embryogenesis, organ development, and the regeneration or healing of damaged tissues with fibrosis. However, its role in cancer is equally important. The present chapter aims to provide a literature update regarding the EMT of gastrointestinal cancers, which includes carcinomas, neuroendocrine neoplasms, stromal tumors of the gastrointestinal tract from the esophagus to the anal canal, and hepatic and pancreatic malignancies. Drawing on experimental studies, in vivo observations, and microscopic examinations of gastrointestinal cancers, the authors intend to highlight the most important features of EMT, which might guide oncologists in identifying the best approach for targeted anti-EMT therapy. The role of EMT in inducing drug resistance was also explored for all types of cancer examined, in the context of both basic and clinical approaches. Keywords

Cholangiocarcinoma · Colorectal · Gastric · Hepatocellular carcinoma · Melatonin · Mesenchymal to epithelial transition · Migrastatics · Neuroendocrine · Pancreas · Wnt S. Gurzu (*) · I. Jung Department of Pathology, George Emil Palade University of Medicine, Pharmacy, Science and Technology, Targu-Mures, Romania e-mail: [email protected]; [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2022_61 Published online: 6 October 2022

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Abbreviations ACRG APC CIN CK CMS CRC CSC CTC EBV E-cadherin ECM EGFR EMT EMT-TF ENA/VASP EpCAM FAP FAT1 FDA FFPE FGFR FOLFIRINOX FU GATA GC GIST GlcCer GMS H. pylori HCC HDAC HE HER-2 HGFR HIF HMGN IBD IHC IL ISH

Asian Cancer Research Group Adenomatous polyposis coli Chromosomal instability Cytokeratin Consensus molecular subtypes Colorectal cancer Cancer stem cell Circulating tumor cell Epstein-Barr virus Epithelial cadherin Extracellular matrix Epidermal growth factor receptor Epithelial-mesenchymal transition EMT-activating transcription factor Enabled/vasodilator stimulated phosphoprotein Epithelial cellular adhesion molecule Familial adenomatous polyposis FAT Atypical Cadherin 1 Food and Drug Administration Formalin-fixed paraffin-embedded tissue Fibroblast growth factor receptor 5-fluorouracil/leucovorin/irinotecan/oxaliplatin Fluorouracil GATA binding protein Gastric cancer Gastrointestinal stromal tumor Glucosylceramide Glasgow Microenvironment Score Helicobacter pylori Hepatocellular carcinoma Histone deacetylase Hematoxylin and eosin Human epidermal growth factor receptor 2 Hepatocyte growth factor receptor Hypoxia-inducing factor High mobility group nucleosome-binding protein Inflammatory bowel diseases Immunohistochemistry Interleukin In situ hybridization

Epithelial-Mesenchymal Transition in Gastrointestinal Cancer: From a. . .

ISLR Klf4 MANEC MET miRNA MMP MSI MSS mTOR N-cadherin NCCN NEC NET OS PanIN PD-1 PDAC PDGFR PD-L1 PRRX ROCK SCC SIN3A SLUG SMA SMAD SNAIL SOX TCGA TEMTIA TF TGF TNF Twist UBE2T VEGF WHO Wnt YAP1 ZEB ZO-1

Immunoglobulin superfamily containing leucine-rich repeat Kruppel-like factor 1 Mixed adeno-neuroendocrine carcinoma Mesenchymal epithelial transition MicroRNAs Metalloproteinase Microsatellite instability Microsatellite stable status Mammalian target of rapamycin kinase Neural cadherin National Comprehensive Cancer Network Neuroendocrine carcinoma Neuroendocrine tumor Overall survival rate Pancreatic intraepithelial neoplasia Programmed cell death protein-1 Pancreatic ductal adenocarcinoma Platelet-derived growth factor receptor Programmed death ligand 1 Paired related homeobox 1 Rho kinase Squamous cell carcinoma SIN3 transcription regulator family member A Snail-related transcription factor or Snai2 Smooth muscle actin Mothers against decapentaplegic homolog Zinc finger protein SNAIL or Snai1 Sex-determining region Y-Box Cancer Genome Atlas Consortium EMT International Association Transcription factor Transforming growth factor Tumor necrosis factor Twist Basic Helix-Loop-Helix Transcription factor 1 Ubiquitin conjugating enzyme E2T Vascular endothelial growth factor World Health Organization Wingless and INT-1 Yes-associated protein 1 Zinc finger E-box binding homeobox Zonula occludens-1

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Introduction

Epithelial-mesenchymal transition (EMT) is defined as a cellular reprogramming process in which the cytoskeleton remodeling of epithelial structures induces phenotypic and genotypic conversion from an epithelial to a mesenchymal-like state. The epithelial cells are transformed from polygonal to elongated cells with spindle-shaped morphology. The loss of epithelial cadherin (E-cadherin) polarity, acquirement of fibroblastic properties, and high motility have also been observed to accompany the EMT process (Aiello et al. 2019; Dong et al. 2022; Ikenaga et al. 2012; Luu 2021; Qiu et al. 2022; Xue et al. 2022). Three subtypes of EMT are known. Type 1 drives early embryogenesis and organ development and is involved in several processes such as neural crest formation, the genesis of heart valves, and Müllerian duct regression. Type 2 is responsible for the physiologic response to tissue injury, wound healing, tissue self-renewal, fibrosis, and epithelial tissue explants in vitro. Type 3 is known to be involved in carcinogenesis, cancer progression, invasion, immune escape, and metastasis (Aiello et al. 2019; Clevers 2006; Gurzu et al. 2015; Ieda et al. 2019; Yang et al. 2020). EMT plays roles in the migration of tumor cells through actin remodeling and the loss of cell-cell adhesion. It also strongly influences the incorporation of tumor cells in metastatic organs (Gandalovicova et al. 2017; Vasarri et al. 2022). This chapter aims to characterize the EMT phenomenon of gastrointestinal cancers, which include not only malignant tumors developed in the gastrointestinal (GI) tract from the esophagus to the anal canal but also pancreatic and hepatobiliary cancers. A better understanding of EMT from both a basic and a clinical perspective might yield the necessary insight for oncologists to develop new therapeutic approaches (NCCN 2022).

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Epithelial Plasticity and EMT Subtyping in Cancer

Epithelial plasticity is a dynamic and partially reversible process characterized by the interconversion of tumor cells between EMT and mesenchymal-to-epithelial transition (MET) phenotype (Liu et al. 2021; Yang et al. 2020). Most of the studies focusing on EMT examined this phenomenon based on immunohistochemical (IHC) antibodies or in situ hybridization (ISH) methods and formalin-fixed paraffinembedded tissues (FFPE). Although EMT is a process characteristic of epithelial tumors, EMT-like changes were also described in non-epithelial neoplasms such as leukemia, sarcoma, gastrointestinal stromal tumors (GIST), and melanoma (Kovecsi et al. 2017; Yang et al. 2020). From an IHC perspective, EMT is defined as the partial loss of positivity for cytokeratin (CK) and other membrane markers of cell-cell adhesion such as E-cadherin, β-catenin, EpCAM (epithelial cellular adhesion molecule), claudins (especially claudin 7), and occludins (e.g., zonula occludens-1 [ZO-1]). EMT is also characterized by the increased activity of mesenchymal antibodies such as vimentin, neural cadherin (N-cadherin), fibronectin, metalloproteinases (MMP),

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smooth muscle actin (SMA), or vitronectin which are regulated by EMT-activating transcription factors (EMT-TF) (Aiello et al. 2019; Dardare et al. 2021; Gurzu et al. 2015; Xue et al. 2022; Zheng et al. 2015). Most of the TFs – like SNAIL (zinc finger protein SNAIL or Snai1), SLUG (snail-related transcription factor or Snai2), and ZEB1 and ZEB2 (zinc finger E-box binding homeobox 1 and 2) – are zinc finger proteins (Liu et al. 2021). Based on the EMT phenomenon, carcinomas are classified as having an “epithelial,” “mesenchymal,” or “quasi-mesenchymal” phenotype: • Epithelial phenotype/absent EMT – Carcinomas are usually defined by positivity for CKs, which are epithelial markers, and for cell-cell adhesion markers such E-cadherin (CDH1 gene) or β-catenin (CTNNB1 gene), which show membrane positivity. Diffuse expression of pan-CK (clone AE1/AE3) and membrane E-cadherin ± β-catenin, without positivity for mesenchymal markers or EMT-TFs, is an indicator of the epithelial phenotype. Carcinomas showing epithelial phenotype are less aggressive than other molecular groups (Banias et al. 2020; Gurzu et al. 2015; Liu et al. 2021; Roseweir et al. 2019). • Mesenchymal phenotype/high EMT – This phenotype is specific to carcinomas that are negative or show patchy positivity for E-cadherin and present loss or membrane-to-nuclei translocation for β-catenin, along with positivity for mesenchymal markers. Positive reaction for at least three EMT-TFs is also considered an indicator of high or “complete EMT.” The commonest examined TFs are SNAIL, SLUG, Twist, ZEB1, and ZEB2. Other EMT-TFs are HDAC1/HDAC2 (histone deacetylase), SIN3A (SIN3 transcription regulator family member A), and Ovol 1/2, among others. The mesenchymal phenotype is found more frequently in poorly or undifferentiated carcinomas and is known as a factor of aggressivity, high mobility in tumor cells, resistance to apoptosis or senescence, enhanced capacity for metastasis, the promotion of genomic instability, immune suppression, stemness, and drug resistance (Luu 2021; Okuda et al. 2022; Roseweir et al. 2019; Sadoughi et al. 2022). • Hybrid phenotype/low EMT – This phenotype is characterized by simultaneous retained epithelial and gained mesenchymal features. It is also known as “partial EMT,” “transitory status,” “transition phenotype,” “quasi-mesenchymal subtype,” or “intermediated hybrid epithelial and mesenchymal phenotype.” These carcinomas can be positive for CKs and E-cadherin but also show immunoexpression for antibodies such as vimentin, fibronectin, N-cadherin (CDH2), or EMT-TFs (Banias et al. 2020; Collisson et al. 2011; Gurzu et al. 2015; Okuda et al. 2022; Rajagopal et al. 2021; Roseweir et al. 2019).

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Molecular Pathways of EMT: General Data

Triggers of EMT are mechanical stress, inflammation, low pH, hypoxia, neo-angiogenesis, immune response, alterations of the extracellular matrix (ECM), and oncologic therapy, along with Wingless and INT-1 (Wnt), Notch, or transforming

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growth factor β (TGF-β) signaling pathways (Dardare et al. 2021; Ieda et al. 2019; Luu 2021; Vasarri et al. 2022). • Wnt signaling pathway – The canonical Wnt is the most explored signaling pathway of EMT. Activation of the Wnt signaling is defined by a trimeric complex which includes 19 Wnt genes, the Wnt receptor Frizzled, and low-density lipoprotein receptor-related protein 5/6 (LRP5/6). This complex is synthesized in the cell membrane and plays a role in preventing the phosphorylation and degradation of β-catenin. The consequence of Wnt signaling activation is membrane-to-cytoplasm and then to nucleus translocation of β-catenin with further activation of other EMT-mediated genes, such as cyclin D1 and c-myc (Clevers 2006; Gurzu et al. 2015, 2016; Qiu et al. 2022). • Transcriptional EMT – β-catenin links E-cadherin to the cytoskeleton (Roseweir et al. 2019). Some TFs, such as SNAIL and ZEB, act as epithelial repressors rather than mesenchymal promoters. Other TFs, such as Twist and PRRX (paired Related Homeobox 1), are mesenchymal inducers. SNAIL and ZEB1/2 repress transcription of E-cadherin, miR-200 family members, and other EMT-related epithelial molecules such as Mucin-1, desmoplakin, claudins, and occludins. SNAIL stimulates the activity of the mesenchymal genes fibronectin and MMP9, while ZEB is known as a “metastasis promoter” that induces the expression of vimentin and N-cadherin. Twist induces transcription of SLUG, with further activation of vimentin and N-cadherin (Dardare et al. 2021; Liu et al. 2021; Sadoughi et al. 2022). Independent of the organ or the type of malignancy, EMT-TFs act as key upstream regulators of EMT (Yang et al. 2020). • EMT and microRNAs (miRNAs) – The most common EMT-mediating miRNAs are miR-200 and miR-34 (Gurzu et al. 2015, 2016; Dardare et al. 2021). The mi-R200 family plays a role in the inhibition of the tumorigenesis and local invasion or stimulates cell mobility and capacity for metastasis. It directly targets the E-cadherin and exerts an inhibitory effect against EMT-TFs such as Twist, ZEB1/2, SNAIL, and SLUG and influences DNA methylation. Members such as miR-200, miR-203, sex-determining region Y-Box 2 (SOX2), and Kruppel-like factor 1 (Klf4) play a double role, acting as both EMT and stemness modulators (Ieda et al. 2019; Liao et al. 2021; Wang et al. 2017). Mi-R34a/b/c gene expression is induced by activation of the TP53 gene and SNAIL downregulation. The miR-34SNAIL axis influences the miR-200/ZEB axis, which plays a role in maintaining the full epithelial phenotype (miR-200high/ZEBlow), partial EMT (miR-200medium/ZEBmedium), or mesenchymal phenotype (miR-200low/ZEBhigh) (Liao et al. 2021; Lu et al. 2013). The miR-151a controls contact between tumor and endothelial cells, along with endothelial cell movement and angiogenesis, through the upregulation of SLUG. It also regulates the expression of E-cadherin, SLUG, and fibronectin (Liao et al. 2021). Other miRNAs involved in the EMT phenomenon are mi-R7, mi-R9, miR-103/107, and miR-181, among others (Luu 2021; Okabe et al. 2015). • EMT and HIPPO pathway – This pathway signaling is involved in controlling cell shape and motility during physiologic and pathologic EMT through the

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downregulation of the nuclear yes-associated protein 1 (YAP1). Inhibition of HIPPO signaling induces tumor cell motility, angiogenesis, and metastasis (Chang et al. 2022; Liao et al. 2021; Liu et al. 2021). • EMT and metastasis – leader vs. follower cells – If EMT is characteristic of primary tumors, carcinoma cells from metastatic sites can undergo the reverse process of MET (Dardare et al. 2021; Liu et al. 2021; Luu 2021). Tumor cells can migrate individually (single-cell migration; EMT phenomenon) or as a group (collective migration). During collective cell migration, two groups of cells were identified: leader (pathfinder or tip cells) and follower (trailing) cells. The leader cells are localized to the leading edge and have the role of exploring and modulating the microenvironment and ECM. They interact with ECM growth factors and chemokines. The collective leader cells are guided by catenins, Rho GTP-ases, Arp 2/2, or filopodia or lamellipodia, which are proteins from the enabled/vasodilator stimulated phosphoprotein (Ena/VASP) family and are responsible for maintaining the integrity of the cytoskeleton (Gurzu et al. 2008, 2013; Khalil and Friedl 2010). Leader cells can remain in the leading position for hours but can also be linked to the followers by adhesion molecules. To keep cell-cell junctions and collective movement, “chain-like cooperative behavior” is necessary for the follower cells. If the junctions are not maintained, they can still move as packs of cells through a “pushing elongation” mechanism, which is more common in tumors undergoing expansive growth (Khalil and Friedl 2010; Liao et al. 2021; Zoeller et al. 2019). The genetic profile of the 2 groups is not similar, and at least 14 different gene mutations were identified between the 2 groups (Liao et al. 2021; Zoeller et al. 2019).

4

Esophageal Squamous Cell Carcinoma

Esophageal cancer ranks seventh in cancer incidence and sixth for mortality globally (Dong et al. 2022; Zhai et al. 2022). Most of the carcinomas of the upper and middle esophagus are squamous cell carcinomas (SCC), whereas adenocarcinomas usually develop in the middle part and gastroesophageal junction. Little is known about the EMT of esophageal SCCs. ZEB1/2, SLUG, Twist, and SOX2 are the most obvious modified EMT-TFs, as are miRNAs and long non-coding RNAs (Liao et al. 2021; Wang et al. 2022). • Transcriptional EMT from early and late-partial EMT to mesenchymal phenotype – In SCCs of the esophagus, the expression of TFs depends on the EMT stage. In this process, ZEB1/2, Twist, and SNAIL proved to be activated from early or partial EMT to late or complete EMT and maintain positivity of tumor cells for vimentin and N-cadherin. SMAD2 seems to be upregulated in the late stages of partial EMT. While in adenocarcinomas, stemness is more characteristic for poorly differentiated, mesenchymal-type tumors, in SCCs stemness properties are exhibited in tumor cells during early and late-partial EMT and downregulated in SCCs with the mesenchymal phenotype (Liao et al. 2021; Wen

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et al. 2016). ZEB1 and ZEB2 can be modulated by TGF-β1, which downregulates the tumor suppressor gene LINC00886 located at 3q25.31, or by ELF3, which binds to the promoter region of miR-144-3p and suppresses its transcriptional role in SCCs (Dong et al. 2022). Another hypothesis refers to Twist-induced expression of ZEB1, vimentin, and podoplanin. Podoplanin (D2-40) is a marker of lymphatic vessels and cancer stem cells (CSCs). Its activity is independent of E-cadherin (Liao et al. 2021). • EMT and FAT Atypical Cadherin 1 (FAT1) – Downregulation of the adhesion molecule FAT1 stimulates EMT by conferring stemness properties to cancer cells and promoting β-catenin nuclear translocation (Zhai et al. 2022). FAT1 downregulation can also inhibit HIPPO pathway signaling through further upregulation of the nuclear expression of YAP1/TAZ protein complexes, increasing tumor cell motility and metastasis (Liao et al. 2021; Liu et al. 2021). • EMT-driven metabolomics – The metabolic alterations that frame the EMT process are targeted by TGF-β (Rajagopal et al. 2021). Its activation can be induced by acidosis, which is the result of lactate synthesized by tumor cells. TGF-β-related EMT is accompanied by the promotion of fatty acid metabolism and the phosphorylation of SMAD 2/3 (Liao et al. 2021). • EMT and chemoresistance – EMT-induced cisplatin resistance of esophageal SCCs mainly occurs through increased drug efflux. One such mechanism is FAT1 knockdown, which induces the upregulation of the drug resistance-related gene ABCC3 (Zhai et al. 2022).

5

Gastric and Gastroesophageal Cancer

Data from 2020 (GLOBOCAN) shows that gastric cancer (GC) ranks fifth for incidence and fourth for cancer global mortality (He et al. 2022), although molecular-targeted drugs have already been synthesized for the molecular groups established by the Cancer Genome Atlas (TCGA) Consortium, World Health Organization (WHO), and the Asian Cancer Research Group (ACRG). GC incidence is higher in Asia and East Europe, and geographic differences were reported in molecular profile and evolution (Kadar et al. 2015). Individualized therapy is based on the following molecular groups: Epstein-Barr (EBV)-positive, cases with genomic stability, the chromosomal instability (CIN) group, microsatellite instable (MSI) carcinomas, microsatellite stable tumors displaying EMT (MSS/EMT), MSS/TP53+, and MSS/TP53- carcinomas (Satala et al. 2020). • Transcriptional EMT – EMT of GC cells is mostly driven via the Wnt pathway. It has been primarily analyzed for intestinal-type carcinomas (adenocarcinomas). During EMT, E-cadherin/ZO-1 suppression with further N-cadherin/vimentin upregulation can also be modulated by miR-4742e5p (Bae et al. 2022). Like other carcinomas, EMT is influenced by inflammation and the immune status of tumor cells. The human immunoglobulin superfamily containing leucine-rich repeat (ISLR) is one of the newest factors proven to stimulate invasion and

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metastasis of GC cells via EMT. Physiologically, ISLR is involved in the differentiation of myofibroblasts, muscle regeneration, and muscle atrophy. In GC, ISLR expression is inversely correlated with E-cadherin and positively correlated with MMP2 and EMT-mesenchymal markers N-cadherin, vimentin, SNAIL, and Twist (Sun et al. 2022). ISLR association with the density of immune stromal components CD8+ T cells, macrophages, and dendritic cells has also been demonstrated (Li et al. 2020). • EMT and Helicobacter pylori (H. pylori) – Infection with H. pylori proved to enhance the stemness of gastric mucosa cells. In chronic gastritis, the stem properties are determined by positivity of atrophic gastric mucosa for cell-cell surface markers such as CD44. CD133 and TFs Oct4, Nanog, Sox2/Sox9, and c-myc can then be expressed in areas with intestinal metaplasia, co-localized with H. pylori. Unusual CD117 (c-KIT) positivity of gastric mucosa might also be an indicator of stemness properties. When the microenvironment of the mucosa is altered, carcinogenesis may be the next step. H. pylori-related tumorigenesis can be driven via Wnt/β-catenin (CagA/E-cadherin interaction), TGF-β (SNAIL inducer), or HIPPO (YAP1 activation) signaling pathways. The CD44+ CSCs are chemoresistant against 5-fluorouracil (5-FU) and cisplatin (He et al. 2022; Okabe et al. 2015). • EMT in adenocarcinomas of the gastroesophageal junction – Adenocarcinomas of the esophagus and those located at the junction between the esophagus and stomach share similar signaling pathways. EMT was reported to occur via the TGF-β superfamily, which includes TGF-ß1, the mothers against decapentaplegic homolog 4 (SMAD4), and bone morphogenetic protein 7. They interact with the stem cell marker CD44 and other TFs (such ZEB1 and ZEB2) and downregulate expression of EpCAM (Okabe et al. 2015).

6

Cancer of the Small Intestine

Fewer than 40 Medline-indexed papers focused on the EMT of the small intestine and its premalignant disorders. The most common premalignant lesions of the small intestine are inflammatory bowel diseases (IBD), mainly Crohn disease. A challenging therapeutic target is the synthesis of anti-fibrosis drugs. It was experimentally proven that this synthesis should be focused on inhibition of TGF-ß and AMP-activated protein kinase pathways, which are EMT inductors (Huang et al. 2022). In inflammatory processes, EMT of enterocytes occurs via the Wnt/ß-catenin signaling pathway. Like other segments of the GI tract, it includes E-cadherin/Ncadherin switch, loss of tight junction proteins ZO-1 and ZO-2 and some claudins, and upregulation of vimentin and nuclear SNAIL. In experimental studies in pigs, EMT of enterocytes was more obvious in the jejunum, along with a high expression of TGF-ß1, and not in the ileum. As the number of Peyer’s patch M cells decreased in the ileum in synchrony with EMT of enterocytes, it was supposed that immune surveillance can be significantly affected in patients with IBD-induced EMT (Chen et al. 2021).

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Adenocarcinoma and Carcinoma of Ampulla of Vater

Although transcriptional EMT occurring via the Wnt/ß-catenin pathway can be seen in both intestinal- and pancreatobiliary-type carcinomas of the ampulla of Vater, some notable features should be highlighted. In intestinal-type carcinomas, membrane-to-nuclear translocation of ß-catenin is an indicator of EMT. The non-intestinal carcinoma is characterized by membranous loss of both E-cadherin and ß-catenin, a more desmoplastic stroma, and high tumor budding degree, as in colorectal carcinomas (CRC). EMT is more intense in the invasive edges than in the tumor center (Sung et al. 2014). Adenocarcinomas are rare and mainly occur in the jejunum and ileum. Independent of location, mesenchymal phenotype/high-EMT is characterized by negative E-cadherin and diffuse positivity for vimentin and fibronectin. It is also associated with poorly differentiated histology, especially in the invasive edges, and proved an independent negative prognostic factor. SMA is not a marker of EMT of small intestine adenocarcinoma cells (Kim et al. 2013).

6.2

Gastrointestinal Stromal Tumor (GIST)

Although unusual, EMT-TFs proved to influence the behavior of such mesenchymal tumors including GISTs. E-cadherin can be seen in 30% of GISTs, as a positive prognostic parameter. Half of the cases express nuclear SLUG, which induces CSC properties in the tumor cells, along with CD44 (Kovecsi et al. 2017).

7

Colorectal Cancer

CRC has the third highest incidence rate and is the fourth most common cause of cancer-related death worldwide (Lu et al. 2022; Sadoughi et al. 2022). It is one of the carcinomas for which targeted molecular therapy has been implemented, with good results, for more than 10 years. There are still cases, however, which do not respond to this therapy. About 20% of patients with metastatic CRCs remain alive 5 years after diagnosis (Yang et al. 2022). As in other carcinomas, EMT seems to contribute to rapid evolution and chemoresistance. • EMT and hereditary polyposis cancer syndromes – The first connection between EMT and cancer was suggested when nuclear β-catenin, an important component of the Wnt signaling pathway, proved to be linked on the cytoplasmic adenomatous polyposis gene (APC). Its mutations can be responsible by occurrence of familial adenomatous polyposis (FAP) (Jung et al. 2015). In the absence of APC mutation, Axin2 mutation can also induce β-catenin membrane-to-nuclear translocation, with further predisposition for hereditary CRC (Clevers 2006). • EMT-based molecular subtyping of CRC – The four consensus molecular subtypes (CMS) include the following groups: (1) CMS1, hypermutated

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carcinomas with MSI, BRAF mutations, or significant immune reaction; (2) CMS2, carcinomas displaying CIN with/without activation of the EMT-related pathways Wnt and myc (low EMT or epithelial phenotype); (3) CMS3, metabolic-activated KRAS-mutated carcinomas; and (4) CMS4, carcinomas with highly developed angiogenesis and TGF-β-induced mesenchymal phenotype. CMS4 carcinomas also show stromal activation, immunosuppression, and large amounts of CD68-positive cytokine-secreting macrophages. They are also associated with an increased risk of lymph node and peritoneal carcinomatosis and unfavorable prognoses (Banias et al. 2020; Ieda et al. 2019). The CMS4 tumors are also known as stem-like carcinomas. In these cases, the EMT-TFs can acquire a stem-like phenotype characterized by double positivity of tumor cells for EMT-TFs and markers of CSCs, such as CD44, CD133, or CD24 (Wang et al. 2017; Zheng et al. 2015). • EMT and microsatellite status – Although the relation between EMT and microsatellites is far too complex to be characterized, it has been experimentally determined that MSI-CRCs, which are associated with mutations of TGF-β receptor type II, do not appear during TGF-induced EMT. MSI or MSS carcinomas with intact TGF-β type II receptors are more prone to EMT. The loss or reduction of junctional E-cadherin along with the acquirement of N-cadherin and vimentin is more frequently seen in MSS than in MSI carcinomas (Banias et al. 2020; Ieda et al. 2019; Pino et al. 2010). Although E-cadherin downregulation is considered “the hallmark of EMT” (Roseweir et al. 2019), it usually has a patchy expression in tumor glands, and its complete loss is extremely rare. β-catenin loss or membraneto-cytoplasm/membrane-to-nuclear translocation defines the EMT (Clevers 2006). EMT features are correlated with the morphological particularities of MSI vs. MSS carcinomas; as MSI tumors present high levels of inflammation compared with MSS, inflammation-induced EMT may be predominantly expressed in MSI carcinomas (Pino et al. 2010; Toth et al. 2011). • EMT and tumor buds – If simultaneous E-cadherin/β-catenin junctional activity is diffusely seen in the center of the tumor and invasive edge, along with cytoplasmic maspin, the case is considered as having an epithelial phenotype. This immunoprofile characterizes one third of CRCs (Banias et al. 2020; Gurzu and Jung 2021). If the EMT is observed in both the tumor core and invasive area (buds), it is classified as having a mesenchymal phenotype (CMS4). If only the buds exhibit EMT, the carcinomas are considered hybrid/quasi-mesenchymal. For these reasons, quantification of EMT and the EMT-TFs in both the tumor center and tumor buds is recommended. The budding degree is recognized by the WHO as an important prognostic parameter (Banias et al. 2020; Gurzu et al. 2018; Studer et al. 2021; Wang et al. 2017). The mesenchymal phenotype/high EMT/CMS4 is encountered in fewer than 15% of CRCs and is reflected by nuclear β-catenin or simultaneously loss of β-catenin and maspin, along with membrane positivity for ZEB1 and fascin, cytoplasmic SNAIL reactivity, increased tumor budding, and a worse prognosis (Alexander et al. 2022; Banias et al. 2020; Roseweir et al. 2019). Low EMT/hybrid phenotype/transitory status is observed in one third of CRCs and is characterized by low membrane E-cadherin,

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cytoplasm-to-nuclear translocation of maspin in tumor buds, and positivity for at least one of the EMT-TFs (ZEB1, fascin, or SNAIL) (Banias et al. 2017, 2020; Gurzu and Jung 2021; Roseweir et al. 2019). • EMT and tumor stroma – For CRC, the Glasgow Microenvironment Score (GMS) is calculated based on the inflammatory score and tumor stroma percentage at the invasive edge (Alexander et al. 2021). The Klintrup-Mäkinen inflammatory grade is estimated using hematoxylin and eosin (HE) stains and is based on the density of inflammatory cells in the invasive areas. Under this system, CRCs are categorized as score 0, no stromal inflammation; score 1, few inflammatory cells without glandular destruction; score 2, moderate amount of inflammatory cells with patchy arrangement and focal destruction of glands; and score 3, high-grade inflammatory cell reaction (mainly macrophages) forming a band in the invasive edge, with significant destruction of glands (Klintrup et al. 2005). Intra-tumor-stroma ratio is counted at low-power field (100× magnification) using pictures of the invasive area, which show tumor cells in all borders of the image and do not include inflammation, necroses, or mucus. Cases are classified as stroma-low (≤50%) and stroma-high, which is fibrotic/dense and comprises >50% of image (Huijbers et al. 2013). GMS includes three prognostic groups: good, score 0 (high inflammation in the invasive areas [scores 2/3], independent of stromal ratio); intermediate, score 1 (low inflammation, low stroma); and poor prognosis (low inflammation, high stroma), score 2 (Alexander et al. 2021; Jakubowska et al. 2017). GMS 2 reflects a mesenchymal subtype with a high risk of local relapse and distant metastases (Alexander et al. 2021). Based on desmoplastic reaction, CRCs can also be classified as mature (collagen fibers, without hyalin), intermediate (keloid-like collagen and hyalinization), and immature (myxoid stroma with an amorphous mucinous material). Immature types are CRCs with mesenchymal or quasi-mesenchymal phenotype which express the EMT-TFs called ZEB1 and Twist1 (Hashimoto et al. 2022). • EMT in colitis-induced CRC – In patients with inflammation, TGF-β1, SMA, TNF-α (tumor necrosis factor), NF-kB signaling pathway, ECM, ISLR, and interleukins (IL) (mainly IL-1, IL-6, and IL-8) are triggers of EMT and fibrosis (Clevers 2006; Ieda et al. 2019; Lu et al. 2022; Sun et al. 2022). In the acute phase, neutrophils and CD-68 macrophages expressing IL-1β favor stromal storage of TNF-α, TGF-β, and IL-1β. If the inflammatory cytokines TNF-α and IL-1β are removed, the EMT process is reversible in its early phases. In the chronic phase of colitis, fibrosis is mainly induced by growth factors such as basic fibroblast growth factor (FGF), epidermal growth factor (EGF), hepatocyte growth factor (HGF), and their receptors (Ieda et al. 2019). In these cases, EMT can be characterized by Wnt-mediated loss of E-cadherin and the upregulation of EMT-TFs but can also result from the activation of the vitamin D receptor pathway. Vitamin D receptor interacts with the TGFβ1/SMAD3 signaling pathway (Lu et al. 2022), but the Wnt/Ca2+ pathway can also be an EMT signaling mechanism (Clevers 2006). • EMT and circulating tumor cells (CTC) – Exosomes are tiny CRC cells and cancer-associated fibroblast-derived vesicles of 30–150 nm in diameter that

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contain DNA, ncRNAs, epigenetic modulation, and metabolites. They can be detected in circulating blood and other bodily fluids, such as urine or saliva (Yang et al. 2022). As circulating tumor cells (CTCs) can express both epithelial and mesenchymal markers, it has been suggested that EMT plays a crucial role in the systemic spread of carcinoma cells (Wang et al. 2017). • EMT and neuroendocrine components – Although rare, neuroendocrine tumors (NET), NECs, mixed neuroendocrine-non-neuroendocrine tumors, and mixed adenocarcinomas with neuroendocrine components (MANEC) are difficult to treat and are frequently chemoresistant. Their incidence increased 6.4 times from 1973 to 2012. The EMT phenomenon is poorly understood in these tumors. The TGF-β1/SMAD signaling pathway was hypothesized as an EMT promoter of NECs, with further E-cadherin/N-cadherin switch and upregulation of SLUG (but not SNAIL). TGF-β1 is responsible for partial EMT and collective migration of NEC cells, which usually maintain E-cadherin junctional activity. During cell migration, TGF-β1 stimulates MMP2, which promotes the adhesion of cancer cells to the extracellular matrix and stimulates metastasis (Sasaki et al. 2022).

8

Pancreatic Cancer

8.1

Pancreatic Ductal Adenocarcinoma (PDAC)

PDAC is the eighth most common cause of cancer-related death worldwide, with a 5-year overall survival rate (OS) of less than 10% and a median survival time of less than 8–10 months (Luu 2021; Safa 2020; Wang et al. 2017). It is the fourth leading cause of cancer-related death and is projected to become the second most lethal cancer by 2030 (Dardare et al. 2021; Rajagopal et al. 2021). Two of the factors which induce aggressivity in PDACs are excessive desmoplastic stroma with rich ECM and EMT plasticity, which is more intense in undifferentiated/mesenchymal-type carcinomas (Ikenaga et al. 2012). Several mechanisms of EMT have been proposed for PDAC, as follows: • Stromal-related EMT – Dense acellular stromal ECM forms bands of fibrous stroma surrounding cancer cells, creating a physical barrier around them. It can induce hypoxia and physically blocks the penetration of chemotherapics (such as gemcitabine) or immunotherapics in tumor cells. On the other hand, it is rich in collagen, laminin, fibronectin, hyaluronic acid, cytokines, chemokines, growth factors, and other components that actively participate in EMT. Collagen internalization is the first step of stromal-related EMT. Pancreatic stellate cells then play the role of CSCs and induce intracellular and stromal internalization of collagen with further ECM remodeling through simultaneous activity with MMPs, urokinase plasminogen activator, and other remodeling factors (Dardare et al. 2021; Ikenaga et al. 2012; Rajagopal et al. 2021; Safa 2020). • Transcriptional EMT in classic/epithelial phenotype/pancreatic progenitor – Although TFs such as SNAIL and ZEB act as epithelial repressors in most of

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carcinomas, their preventive role against metastasis in PDAC is controversial (Liu et al. 2021; Wang et al. 2017). In a spontaneously metastatic genetically engineered mouse model of PDAC, it was observed that deletion of SNAIL or Twist, which is regulated by the miR-200 family, does not delay carcinogenesis or metastasis and did not improve the OS. The histology of the tumor remained unaffected. However, tumor architecture, desmoplasia, number of myofibroblasts, microvascular density, intensity of CD3-positive tumor-infiltrating T cells, cancer cell apoptosis, and IHC expression of SNAIL and Twist remained restricted to the areas displaying intraepithelial neoplasia (PanIN). These carcinomas co-express MUC5AC and MUC1, but not MUC2 or MUC6 (Aiello et al. 2019; Bailey et al. 2016; Zheng et al. 2015). On the other hand, FOXA1/2 is inhibited by GATA binding protein 6 (GATA6), which is essential for a proper pancreas development during embryogenesis (Collisson et al. 2011). Classic PDAC is mostly a GATA6high tumor. GATA6 silencing induces not only dedifferentiation, basality phenotype, and EMT but also resistance to adjuvant 5-FU, specifically 5-FU/leucovorin regimen (Martinelli et al. 2017). • EMT of KRAS-mutated carcinomas – TGF-β plays role in EMT genesis and KRAS activation with further synthesis of ILs, mainly IL-6, which maintains an active stroma (Dardare et al. 2021; Sadoughi et al. 2022). KRAS-mutated carcinomas are even classic PDACs or exocrine-like/aberrantly differentiated endocrine exocrine carcinomas (Bailey et al. 2016; Collisson et al. 2011). Although KRAS-wild type carcinomas are usually treated with anti-EGFR drugs, erlotinib resistance does not depend on the KRAS status in PDACs (Collisson et al. 2011). Alterations of TGF-β can also be induced by other genes involved in pancreatogenesis, such as SMAD4 (Bailey et al. 2016; Rajagopal et al. 2021). • EMT of basal-like/quasi-mesenchymal carcinomas – PDACs with squamous component, marked by CKs 5/6/14, and positivity for vimentin are called basallike carcinomas. Their high aggressivity compared with classic PDACs seems to occur as a result of EMT activation via silencing of the GATA6 pro-epithelial/ anti-mesenchymal gene. These carcinomas are GATA6low tumors. Despite chemotherapy, the progression rate after implementation of the FOLFIRINOX (5-FU/leucovorin/irinotecan/oxaliplatin) protocol is about 60%, compared with 15% in classic PDAC (Bailey et al. 2016; Collisson et al. 2011; Dardare et al. 2021; Martinelli et al. 2017). • EMT of mesenchymal/stem-like carcinomas – The EMT-TFs can acquire stemlike features, which are defined by double positivity for CD44 or CD133 and CD24, and are associated with proliferation of pancreatic stellate cells and resistance to chemotherapy. Gemcitabine sensitivity is decreased in PDACs with the mesenchymal phenotype, which are usually poorly differentiated carcinomas rich in CSCs. Mesenchymal stem cells from desmoplastic stroma (which result from secretion of cytokine granulocyte-macrophage colonystimulating of PDAC cells and intracellular collagen internalization by cancer cells) exert pro-stemness effect upon tumor cells (Aiello et al. 2019; Ikenaga et al. 2012; Luu 2021; Rajagopal et al. 2021; Safa 2020; Zheng et al. 2015).

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• Transcriptional EMT in metastatic tissues – In metastatic organs, such as liver metastases from a PDAC, activation of metastasis-associated macrophages can induce the transformation of hepatic stellate cells into SMA-positive myofibroblasts. This results in fibrotic stromal expansion and resistance to chemotherapy. In pulmonary metastases from a PDAC, myofibroblast activation is more intense in areas with CD68-positive macrophages (Nielsen et al. 2016). This data demonstrates that in PDACs, EMT mediated by TFs is not primarily responsible for tumor invasion but rather for fibrogenesis and subsequent chemoresistance to both gemcitabine and FOLFIRINOX protocols (Bailey et al. 2016; Martinelli et al. 2017). • EMT and HIPPO pathway – Downregulation of HIPPO pathway signaling increases risk of metastasis through the formation of a complex called ZIP4miR-373-LATS2-ZEB1/YAP1-ITGA3 (Liu et al. 2021). • EMT-driven metabolomics – The TGF-β-induced metabolic alterations increase the intracellular levels of retinoic acid with further activation of fibronectin and collagen, as well as ECM proliferation. This results in high-intensity stromal desmoplasia (Rajagopal et al. 2021).

8.2

Neuroendocrine Tumors (NETs)

Gastroenteropancreatic NETs can be driven by TGF-ß, which mediates the EMT phenomenon (Xue et al. 2021). In grade 1 and 2 pancreatic NETs, E-cadherin can be lost in 50% of cases. Twenty percent of them are also marked by vimentin, which is an indicator of EMT and of increased risk of lymph node and systemic metastases. SNAIL and Twist can be upregulated (Zhou et al. 2021).

9

Hepatobiliary Cancers

9.1

Hepatocellular Carcinoma (HCC)

The incidence of HCC has significantly increased in last decades (Turdean et al. 2012). It is ranked as the sixth most frequent cancer worldwide and the fourth leading cause of cancer-related death (Negri et al. 2022). Although similarities with other carcinomas exist, some particularities of the EMT phenomenon seem to characterize HCC. • EMT signaling pathways – As in other carcinomas, transcriptional EMT is the most common pathway that occurs via Wnt/β-catenin signaling and activation of EMT-TFs (such SNAIL), which is seen in half of HCCs (Cakil et al. 2022). β-catenin membrane-to-nuclear translocation could also be the consequence of Axin2 mutation (Clevers 2006). Ubiquitin-conjugating enzyme E2T (UBE2T) is a linker of Wnt/β-catenin with MAPK/ERK and AKT/mammalian target of rapamycin (mTOR) signaling pathways. UBE2T can activate the Wnt/β-catenin signal independently of β-catenin mutational status in HCC cells (Lioulia et al. 2022). Another

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mechanism of activation of transcriptional EMT is TGF-β signaling, which induces a mesenchymal phenotype in HCC cells (Cakil et al. 2022; Chung et al. 2018). Activation of GBA1, which catalyzes the conversion of glucosylceramide (GlcCer) to ceramide, can also activate EMT (Qiu et al. 2022). As in PDACs, metastasisassociated macrophages can suppress EMT-TFs and promote myofibroblast activation and metastasis (Nielsen et al. 2016; Wang et al. 2017). • EMT and resistance to systemic inhibitors – HCC is known to have a high resistance to most available target therapies. The multi-kinase inhibitor sorafenib was approved by the Food and Drug Administration (FDA) as the first-line treatment for patients with HCCs showing mutations of the platelet-derived growth factor receptor (PDGFR) gene (NCCN 2022; Negri et al. 2022; Qiu et al. 2022). Second-line treatment is done with multi-kinase inhibitor regorafenib, with everolimus, which is a mTOR inhibitor, or using immune checkpoint inhibitors (Cakil et al. 2022; Negri et al. 2022). The platinum compound cisplatin can be used in sorafenib-resistant cases (Cakil et al. 2022). On the one hand, sorafenib is believed to be involved in inhibition on TGF-β1-induced EMT by degradation of type II TGF-β receptors. It has produced positive results in patients with epithelial-phenotype HCC (Chung et al. 2018). On the other hand, EMT, activation of hepatic stellate cells, and the mesenchymal phenotype were shown to play an incriminating role in the development of resistance to these drugs (Chung et al. 2018). CD44, a stemness inductor, can be responsible for translocation of the TGF-β receptor to lipid raft membrane domains and further blocking of sorafenib-induced TGF-β1 inhibition (Chung et al. 2018). GBA1, an EMT activator, can also induce sorafenib resistance, but the exact mechanism is unknown (Qiu et al. 2022). HCC cell- and fibroblast-derived exosomes are involved in acquired resistance to everolimus (Negri et al. 2022; Yang et al. 2022). Vitamin D has been suggested as a drug resistance reversing agent that may re-sensitize HCC cells to everolimus (Negri et al. 2022). Although cisplatin can be included in therapeutic regimens of HCC, it has been shown that low doses can induce the expression of CSCs, which are marked by CD44, CD133, and CD90. EMT-like features, such as the transformation of hepatocytes into fibroblast-like cells and increased drug resistance, were also observed in HepG2 cells in a dose- and time-dependent manner (Cakil et al. 2022).

9.2

Cholangiocarcinoma

Although the incidence of cholangiocarcinoma is not high (3% of all GI malignancies and 10–30% of all hepatobiliary cancers), the prognosis is extremely unfavorable, and few therapeutic options are available (Lefler et al. 2022; Lin et al. 2022; Turdean et al. 2012). Inflammation is the key target in the development of cholangiocarcinomas (Lin et al. 2022). Transcriptional EMT, mainly based on E-cadherin/ZO-1 suppression and enrichment of SLUG, is modulated by several factors, including high mobility of the group nucleosome-binding protein 3 (HMGN3) (Sorin et al. 2022).

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For intrahepatic and hilar cholangiocarcinomas, targeted molecular therapy is based on FGFR2 and IDH1 genes, while human epidermal growth factor receptor 2 (HER-2) is used as a target for extrahepatic/distal carcinomas (Lin et al. 2022; Medscape.org 2022). When used as a second-line treatment, regorafenib, a multitarget tyrosine kinase inhibitor, was shown to inhibit EMT in both primary tumor and pulmonary metastases. Inhibition of EMT activated through the HIPPO pathway is reflected by YAP1 nuclear activity. Regorafenib activity is enhanced by amphiregulin (Chang et al. 2022).

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Future Challenges

10.1

EMT and Migrastatic Drugs

The term “migrastatics,” which derives from Latin “migrare” and Greek “statikos,” was recently proposed for “drugs that can inhibit not only local invasion, such the cytostatics, but also extravasation and metastatic colonization.” As a natural compound, the actin-targeting drug is extracted from marine sponges (such as jasplakinolide) or from plants from the family Cucurbitaceae (Gandalovicova et al. 2017; Vasarri et al. 2022). In melanoma, glioblastomas, breast cancer, and HCC, migrastatics target Rho kinase (ROCK) and ROCK-myosin II downstream and inhibit actin depolymerization with further cytoskeleton remodeling (Gandalovicova et al. 2017; Maiques et al. 2021). Although the concept is new and poorly understood, it may be involved in EMT and could be useful in the development of a new therapeutic approach for cancers with high malignancy potential, including GI, pancreatic, and liver cancers (Dardare et al. 2021).

10.2

EMT and Targeting Immune Checkpoints

Because EMT is associated with an inflammatory tumor microenvironment in non-small cell lung cancer, especially mesenchymal-type adenocarcinomas, it was supposed that they can respond to immune checkpoints programmed cell death 1 (PD-1) and programmed death-ligand 1 (PD-L1) (Lou et al. 2016). If similar data can be obtained for GI carcinomas, CRCs with immature or inflammatory-rich stroma might be considered candidates for immune therapy (Hashimoto et al. 2022).

10.3

EMT and Melatonin

This hormone secreted by the pineal gland was recently shown to inhibit EMT and induce tumor cell apoptosis. These mechanisms supposedly involve inhibition of pro-angiogenic vascular endothelial growth factor (VEGF) in PDAC, suppression of

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the MMP9 and NF-kB signaling pathways in esophageal cancer (respectively, VEGF and NF-kB in GC), downregulation of VEGF and hypoxia-inducing factor (HIF-1α), and upregulation of TFs such as FOXA2, occluding or ZO-1 in CRC and HCC (Sadoughi et al. 2022).

10.4

EMT and Dexamethasone

Dexamethasone is frequently added in oncologic regimens as a supportive drug. However, little is known about its possible relation to EMT in tumor cells. Recent studies have shown that prolonged exposure to dexamethasone could revert exogenous Snail-dependent EMT to partial EMT through re-activation of CDH1 and Ovol2 (Okuda et al. 2022).

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Conclusion

Despite the rapidly growing interest of researchers in the EMT phenomenon and recent studies implicating it in tumor cell migration and metastasis, the complex mechanisms that underpin EMT are still an enigma. A deep understanding of EMT could precipitate far-reaching breakthroughs in targeted cancer therapies. Future research should focus on migrastatics, the development of targeted drugs, and the synergism of natural and chemically synthesized products. While narrow, this open gate could represent the only chance for many patients affected by life-threatening cancers. Acknowledgments The elaboration of this chapter was partially supported by the Romanian National Authority for Scientific Research, No. 20 PCCF/2018. The English proofreading was done by Cambridge Proofreading LLC. Conflict of Interests None declared. Compliance with Ethical Standards This is a review-type chapter based on literature data which were included in the list of references. No ethical committee approval was necessary.

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Metabolomics of Gastrointestinal Cancers Giulia Nannini, Gaia Meoni, Leonardo Tenori, and Amedeo Amedei

Abstract

Cancer is one of the leading causes of death worldwide and a serious health concern for different countries, particularly the most industrialized cities. Despite recent advancements in diagnosis and treatment, gastrointestinal (GI) malignancies continue to rank among the most aggressive tumors and have a dismal prognosis. Metabolomics is the right method to explain the metabolic processes that belong to living systems and, being the dysregulated metabolism, one of the cancer hallmarks, it could open a new path for evaluating cancerrelated aspects, such as diagnosis and treatment efficacy. The current instrumental metabolomic methods for this type of analysis are nuclear magnetic resonance (NMR) and mass spectrometry (MS). For these purposes, we will include an exhaustive update in this analysis on the status of NMR and MS metabolomic studies using biological fluids for the diagnosis and development of gastrointestinal cancers.

Giulia Nannini and Gaia Meoni have equally contributed to this chapter G. Nannini Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy G. Meoni · L. Tenori Magnetic Resonance Center (CERM) and Department of Chemistry “Ugo Schiff”, University of Florence, Florence, Italy Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Florence, Italy A. Amedei (✉) Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy SOD of Interdisciplinary Internal Medicine, Azienda Ospedaliera Universitaria Careggi (AOUC), Florence, Italy e-mail: amedeo.amedei@unifi.it # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2023_182 Published online: 20 September 2023

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Keywords

Colorectal cancer · Esophageal cancer · Gastric cancer · Liver cancer · Mass spectrometry · Metabolomics · Nuclear magnetic resonance spectroscopy · Pancreatic cancer

1

Introduction

In this century, cancer is one of the main causes of death and a serious health concern for different countries, especially the most industrialized cities. The major reason is the constant increase of population worldwide concomitant with the prolonged life expectancy (Bray et al. 2018). Being the most aggressive cancer (for both men and women) and despite many improvements in diagnosis and therapy, gastrointestinal (GI) cancers remain one of the most fatal cancers (Amedei et al. 2011), and in particular, the pancreatic cancer (PC), gastric cancer (GC), colorectal cancer (CRC), esophageal cancer (EC), and liver cancer (LC). In addition, in both men and women, the gastric and colorectal cancers are, respectively, the third and fifth for worldwide incidence and second and third for mortality (Collaboration et al. 2017). Examining separately the different gastrointestinal cancers, we can assert that GC is one of the most malignant cancers worldwide, and the Asia has a very high rate (Ferlay et al. 2015). Unfortunately, one of the major factors contributing to the poor prognosis is that more GC cases are identified only in the advanced stages (Compare et al. 2010). To date, although different approaches are used to diagnose gastric cancers, there are no standardized guidelines (Leung et al. 2008). Finally, the symptoms (both epidemiological and molecular) of gastric cancer vary according to the malignancy location and the histological type. Colorectal cancer is the third most commonly diagnosed cancers according to the worldwide epidemiological data in both men and women (Siegel et al. 2018). If the CRC is detected at an early stage and is localized, usually the 5-year survival can reach 90%; however, the survival declines considerably if the neoplasia is diagnosed late and spreads to other organs (Siegel et al. 2013). Currently, the fecal occult blood test and serum tumor markers are the clinical tests available for the diagnosis of colorectal cancer, but the lack of sensitivity and specificity of these markers restricts their use (Weitz et al. 2005; Huerta 2003). Pancreatic cancer is one of the most harmful neoplasia with a 5-year survival rate of only 5%. PC is actually ranked as the fourth leading cause of tumor-related deaths in the USA, and it is recently estimated to be the second leading cause of such fatalities in 2020 (Siegel et al. 2018). The symptoms linked to pancreatic tumor, namely abdominal pain, weariness, nausea, and, especially, weight loss, are not PC specific, and this is the major factor responsible for tardive diagnosis and high mortality (Zhang et al. 2012a; Li et al. 2015). There are different ways to detect pancreatic cancer, and the more diffuse are endoscopic retrograde, computed tomography, resonance, and cholangiopancreatography (Hanada et al. 2015). Liver cancer is the

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sixth most commonly diagnosed cancers and the second leading cause of tumor deaths worldwide (McGlynn et al. 2015). The most common histological type of primary liver cancer, which results from chronic liver cirrhosis linked to hepatitis, is hepatocellular carcinoma (HCC) (El-Serag and Rudolph 2007). Because of the lack of symptoms during the early disease stages, HCC usually has a bad prognosis (Sakamoto 2009). The popular HCC causes are liver cirrhosis and infection with hepatitis B virus (HBV) and hepatitis C virus, respectively. In particular, HBV in Asia is clearly a significant risk factor for HCC. Due to HCV infection, alcohol intake, and high rates of obesity linked to non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), and eventual development of chronic liver disease with cirrhosis, Western countries have shown rising incidence rates in the past decades (Ozakyol 2017; Younossi et al. 2018). Curative treatment approaches such as surgical resection or orthotopic liver transplantation are applicable only in a narrow subset of patients with retained liver function at early HCC stages. Therefore, the overall prognosis for HCC patients remains unsatisfactory, with a 5-year survival of 6.9%, an incidence-to-mortality ratio of 0.95, and a median overall survival of just 11 months (Greten et al. 2005). Although considerable efforts have been made over the past few decades to discover novel biomarkers for early tumor detection in clinical practice, recent approaches to HCC diagnosis, including serum α-fetoprotein and liver imaging measurements, lack adequate accuracy and sensitivity (Ressom et al. 2012). Finally, esophageal cancer (EC) is considered one of the most common cancers and ranked as the sixth leading cause of tumor mortality in 2018, causing about 572,000 new cases and 508,000 deaths worldwide (Bray et al. 2018). Esophagus squamous cell cancer accounts for nearly 90% of all esophageal cancers occurring worldwide. Proximal to the squamocolumnar junction, esophageal squamous cell carcinoma (SCC) occurs, showing a multifactorial pathogenesis. Inflammation and other mutagenic/carcinogenic factors contribute to in situ dysplasia and subsequent malignant transformation. The main risk factors are alcohol, tobacco, caustic strictures, tylosis, thoracic radiation, and achalasia (Watanabe 2015). East Asia and Central Asia are the regions with the highest global incidence of esophageal SCC, followed by areas along the Great Rift Valley in Africa and Uruguay in South America (Arnold et al. 2015). Esophageal cancer is diagnosed accidentally through routine endoscopy or by monitoring identified Barrett’s esophagus at an early stage (15% of EC). However, most esophageal cancers are detected when they are locally advanced and are due to initial symptoms that are not unique, such as heartburn or abdominal bloating (Meves et al. 2015; Rubenstein and Shaheen 2015). The gold standard for diagnosis is upper endoscopy with biopsy and histopathological (Zhang et al. 2016a, b). In addition to the fecal detection of occult blood, currently, serum tumor–associated markers such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19–9 (CA19–9) are used for the clinical monitoring of gastrointestinal neoplasia, but these tests are not advantageous as diagnostic screening, showing low specificity and low sensitivity (Burton and Ma 2019). Nevertheless, as we have previously explained, the efficacy of the different therapeutic approaches for antigastrointestinal (GI) cancers is strictly linked to early diagnosis. Several models for different malignancies have been developed to determine the causal risk based on

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clinical features, but while the findings can seem relevant considering the population level, they have a poor predictive value evaluating a single patient (Thrift and Whiteman 2013). Different studies, exploiting bacterial genome–based analysis or high-throughput metabolomics, documented that more gastrointestinal metabolites can modulate pathogen infection in various gut segments (Browne et al. 2017; Hirata and Kunisawa 2017; Kunisawa et al. 2012). For example, they can influence biofilm formation and cell adhesion, such as D-amino acids produced by Bacillus subtilis (Mühlen and Dersch 2016). Moreover, increasing data showed a key metabolite’s role in the modulation of the immune system regulating the development of some adaptive immune cells, especially the T cells (Levy et al. 2017), which have a crucial role in the development of gastrointestinal neoplasia. In fact, the Amedei group showed that deregulated adaptive immune responses, characterized by a decreased number of effective T cells, affect the development of gastric cancer and pancreatic and colorectal cancers (Amedei et al. 2009; Niccolai et al. 2016; Niccolai et al. 2017). One of the hallmarks of cancer is dysregulated metabolism and modifications in the expression of many genes encoding metabolic enzymes, transporters, or regulatory effectors that have been related with tumor development (Robey et al. 2015). First, Warburg suggested that fixed mitochondrial defects were mainly responsible for both cancer development and its associated highly glycolytic phenotype. Instead, the preservation of oxidative metabolism in cancer and its maintenance in the absence of exogenous substrates (‘The Metabolism of Tumours: Investigations from the Kaiser Wilhelm Institute for Biology, Berlin-Dahlem.’, 1931, Warburg 1956) have been shown by subsequent data (Dickens and Greville 1933a, b) indicating an increased metabolic range and an intrinsic capacity to use endogenous substrates oxidatively when exogenous substrates are not accessible (Robey et al. 2015). Metabolism changes associated with cancer can indicate alterations in either metabolic ability or control or both. Ability changes are well defined, while changing control can eventually be of greater relative significance (Newsholme and Board 1991). Since control does not reside in any metabolic pathway at a single point and controlling factors vary between intact cells and in vitro assays, changes observed in individual pathway elements do not always translate into changes in metabolic flux and vice versa. Notably, different metabolic alterations associated with cancer can be interrelated to cellular growth; in fact, tumor development requires the biosynthesis of lipids, proteins, and nucleic acids. As previously reported, frequently, the expression of oncogenes or the loss of cancer suppressors promote metabolic changes, by expression, activity, or flow of the main metabolic pathways. Various components of glucose and glutamine metabolism have been documented as key regulators of neoplasia metabolism. In view of the importance of metabolic changes in the two fundamental cancer aspects, such as development and prognosis, the metabolomics is an essential -omics study, as it can be used to estimate the modifications of the principal metabolites (Burton and Ma 2019). It is well documented that with the

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neoplasia progression, the metabolic characteristics of cancerous cells change (Aboagye and Bhujwalla 1999; Teahan et al. 2011), and typical metabolic changes include deregulated amino acid and glucose absorption, augmented demand for nitrogen, and increased use of anabolic metabolic pathways (Pavlova and Thompson 2016). This metabolic reprogramming can be can be exploited for early cancer diagnosis using biological fluids and decreasing the requirement for more invasive screening. Using nuclear magnetic resonance (NMR) analysis (Wijeyesekera et al. 2012), readily accessible urine and blood samples may be used to detect potential biomarkers associated with cancer risk, presence, and prognosis. Blood flows into every human organ, serving as a transport (in response to different stimuli) of secreted/excreted molecules, while urine contains molecules removed by renal filtration (Berger 1999a, b). In addition, increasing data suggesting that the metabolism of gut microbiota secretes numerous compounds, including fatty acids, indole, and vitamin K, many of which have toxic effects on the lumen, contributing to the carcinogenesis of gastrointestinal neoplasia, especially for colorectal and pancreatic cancer. Finally, different microbiome researchers affirm that great and exhaustive information could be gained by using a more integrative approach that also includes comprehensive fecal metabolite analysis. The stool samples contain numerous molecules that mirror different phases of nutrition such as ingestion, digestion, and, especially, absorption by gastrointestinal tract and gut microbiota. Bacterial biomass (25–54%) exfoliated colonic epithelial cells, undigested food residues (fiber, protein, DNA, mucopolysaccharides, etc.), and small molecules or metabolites such as carbohydrates, organic acids, and amino acids constitute the dry fecal matter. Fecal metabolomes are made up of these small molecules. There is a growing interest in using methods focused on metabolomics to investigate cancer metabolism. NMR and mass spectrometry (MS) are the instrumental metabolomic techniques of the two main classes. The rewards are intrinsically distinct from both of these two strategies. The MS platform provides sensitivity and selectivity to metabolomic research, while NMR provides very high reproducibility, is quantitative, and requires minimal sample preparation steps to prevent separation or derivatization (Emwas 2015). Due to the potential effect of NMR-based metabolomics on the traditional clinical management of the different cancer phases (diagnosis, prognosis, and risk assessment) using readily accessible biofluids, the aim of this chapter is to provide an exhaustive and comprehensive overview of the current literature available in this circumscribed but promising field. In comparison, the use of MS-based or metabolomic analysis methods of cells, tissues, and animal models has been documented elsewhere (Turano 2014; Xiao and Zhou 2017). Interestingly, while breast cancer, for example, has been widely studied using NMR-based systemic biofluid metabolomics (especially for the prediction of relapse risk) (McCartney et al. 2018), this field still appears in its embryo for GI cancers.

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Different Metabolic Approaches

Metabolomics belongs to the scientific domain of the -omic sciences. It deals with the characterization of the metabolome, defined as the whole set of metabolites (small molecules Ib2) disease, higher levels of unsaturated lipid compared with patients with non-lymph node metastasis and with early-stage (≤Ib2) disease. In addition, Xu et al. (2013) and Wang et al. (2016) found a higher fatty acid biosynthesis in EC blood samples. Despite the difference in the trend of fatty acids, most of the studies mentioned detected lower levels of acylcarnitines and higher levels of carnitine in EC blood compared to those of healthy controls. Indeed, carnitine and acylcarnitines are essential for the transport of long-chain fatty acids across the mitochondrial membrane for degradation and energy production. Many cancer-related abnormalities in energy metabolism and intermediate metabolic disorders are also closely related due to abnormal levels of

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acylcarnitine (Qiu et al. 2009; Chen et al. 2009; Peluso et al. 2000; Adlouni et al. 1988; Sewell and Böhles 1995). A dysregulated energy metabolism is demonstrated in EC blood samples by abnormal levels of lysophosphatidylcholines (lysoPCs). In a reaction catalyzed by lysophospholipase A1, lysoPCs can hydrolyze into fatty acids and subsequently decay in the mitochondria to generate energy through β-oxidation (Wang et al. 2012). LysoPCs in a reaction catalyzed by lysophospholipase D (lysoPLD) can also be transformed into lysophosphatidic acid (LPA). Interestingly, the serum levels of LysoPC (14:0) demonstrated to be downregulated in esophageal cancer plasma and together with LPA (18:1) showed a decreased trend with EC progression (Wang et al. 2016; Xu et al. 2013; Zhu et al. 2020) in serum samples. Cancer cells also display alteration in the nucleotide metabolism. A few nucleosides also showed significant variations in EC samples. Levels of 1-methyladenosine, N2, N2-dimethylguanosine, N2-methylguanosine, and cytidine were significantly increased while the concentration of uridine was significantly lower in cancer patients compared to control serum samples (Djukovic et al. 2010). In EC tissues, the levels of nucleoside triphosphates [adenosine triphosphate (ATP), cytidine triphosphate (CTP), guanosine-5′-triphosphate (GTP), and uridine-5′-triphosphate (UTP)] were statistically significantly lower, whereas those of nucleoside monophosphates, such as guanosine monophosphate (GMP), were much higher compared to healthy tissues (Tokunaga et al. 2018). Upregulated metabolism of hypoxanthine was observed to be higher in blood, tissues, and urine of EC patients than that of the controls. Different studies have shown that in tumor cells, enzymes associated with the purine biosynthetic pathway are enhanced because purine nucleotides are necessary for the proliferation of tumor cells. Based on detected biomarkers, several authors suggested statistical models to accurately diagnose the EC using less-invasive biological specimens such as blood and urine. Zhu et al. (2017) obtained a better performance using glucose as EC predictor with a sensitivity of 83.3%, a specificity of 100%, and an AUC of 0.952 among all the identified serum biomarkers (low level in EC: pipecolic acid, glucose, glutamic acid, oleic acid; high level in EC: lactic acid, cholesterol, myo-inositol-1-phosphate). Zhang et al. (2012b) compared the model obtained with the biomarkers identified using LC–MC versus those identified with NMR obtaining a specificity of 86%, a sensitivity of 77%, and an AUC of 0.82 with the former and a specificity of 88%, a sensitivity of 82%, and an AUC of 0.86 with the latter. Nevertheless, by combining the best biomarkers obtained with both techniques, they get a sensitivity and a specificity of 91% and an AUC of 0.95. These models were created to use the serum profile to distinguish EC patients from those considered at high risk of developing EC such as patients with Barrett’s esophagus (BE) and patients with high-grade dysplasia (HGD). Urine samples (Davis et al. 2012; Vignoli et al. 2019) have also been used to distinguish patients with EC and BE patients obtaining an AUC of 0.943 using 1H-NMR profiling approach. Wang et al. (2016) provided a serum metabolomic model based on UHPLC–QTOF/MS approach to distinguish the esophageal cancer progression (from stage I to stage III). Another attempt to provide patient stratification according to the severity of the disease was proposed by Jin

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et al. (2014) using a GC/MS serum metabolomic approach to distinguish EC patients with or without lymph node metastasis obtaining a predictive accuracy of 90%. Finally, Ouyang et al. (2023) identified significant NMR-based metabolic alterations in serum, urine, and tumor tissues in EC patients compared to those of the controls. In addition, significant alterations of many metabolites in serum and urine were linked to the metabolic profiles of EC cancer tissues. Both in serum and urine creatine, glycine was selected as the potential biofluid biomarker panel for EC detection.

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Conclusion

In this exhaustive chapter, we have reported the most recent and significate metabolomic studies in human gastrointestinal cancers. Therefore, we can conclude that the comparative 1H NMR or MS examination of urine, blood, biopsy, and/or feces in GI cancer patients suggested a large variety of biomarker candidates. As previously reported, the early stage of gastrointestinal cancers usually presents no symptoms, so they are diagnosed at advanced stages resulting in a poor prognosis. The discovery of predictive biomarkers could lead to early diagnosis improving the length and especially the life quality of GI patients. To minimize unfavorable prognosis and medical costs, it is therefore crucial to establish low-cost and noninvasive diagnostic techniques. We may conclude that biofluid NMR or MS analysis could be a high-performance, quantitative, and reproducible test that completely suits the notion of large-scale noninvasive population screening of gastrointestinal cancers. Finally, we think that in future, the biofluid NMR or MS analysis could also be used to monitor the treatment efficacy favoring a tailored and personalized therapy. Conflict of Interest All other authors have nothing to disclose.

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Deregulation of Immune System in Gastric Cancer Development, How Immune Nutrition Might Restore the Functions of Immune Cells Luigi Spagnoli, Federica Petrelli, Bruno Perotti, Marco Arganini, and Maria Raffaella Ambrosio

Abstract

Gastric carcinoma (GC) is one of the most frequent neoplasms around the world and still remains the second cause of death of all malignancies worldwide, even if a steady decline in the incidence rate has been observed in the last few decades. Studies on the genetic landscape of GC have been published, and a molecular classification has been proposed, focusing on the possibility of using a specific target therapy for each group of patients. During the past few years, immunotherapy has become one of the most widely applied therapies in the treatment of advanced neoplasm, including GC. Unfortunately, positive responses to immunotherapy are limited to a small fraction of patients with GC, and, due to tumour heterogeneity, its efficacy remains to be better understood. One of the reasons could be the ability of the tumour to escape the immune system. Therefore, more recently, many efforts have been spent to find strategies aimed at enhancing the host defence mechanisms. Among these, immune nutrition (IN) seemed to be promising. IN has the ability to reduce hospital stay and the health system costs and to improve the nutritional status, metabolism, incidence of post-operative complications, adherence to anticancer therapies, quality of life (QOL), and, ultimately, survival. In fact, by IN, the balance between the immunological system and the tumour is shifted towards giving more strength to the immunological response. Although further studies are needed to optimize IN protocols and confirm their prognostic impact, our review seems to support the rationale for

L. Spagnoli · F. Petrelli · M. R. Ambrosio (✉) Pathology Unit, U.O.C. Anatomia Patologica, Azienda Toscana Nord Ovest, Pisa, Italy e-mail: [email protected]; [email protected] B. Perotti · M. Arganini Surgery Unit, Azienda Toscana Nord Ovest, Pisa, Italy # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2023_184 Published online: 7 October 2023

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implementing IN in the routine management of patients undergoing elective surgery for GC. Keywords

Gastric cancer · Immune nutrition · Immune system · Immunity · Immunotherapy

1

Introduction

1.1

Epidemiology and Pathogenesis

Gastric carcinoma (GC) is a multifactor disease: 90% of causes are sporadic and the other 10% develop in a familial/hereditary setting (Jemal et al. 2011). According to the last statistics from the International Agency for Research on Cancer (IARC), GC is the fifth most common cancer worldwide and the fourth cause of cancer-related death with 768,793 new deaths in 2020 (Ladeiras-Lopes et al. 2008). The incidence shows wide geographical variation, ranging from 75,3% of cancers in Asia to 2,7% in North America (Sitarz et al. 2018). The higher risk areas are China and Japan, whereas the lower risk ones are North America and Oceania (Lin et al. 2014). GC affects more frequently men (M:F = 2:1) in their fifth decade of life. Although GC is often reported as a single entity, it can be generally classified into two subsites, which differ in terms of anatomic topography, epidemiology and carcinogenesis. Non-cardial GC develops in the lower stomach (antrum and pylorus) and represents the majority (80%) of GC in higher incidence countries, and almost all cases are attributable to chronic infections by Helicobacter pylori that leads to atrophic gastritis and intestinal metaplasia in a stepwise progression known as Correa’s cascade (Serizawa et al. 2015). Although only 5% of infected patients will develop GC, H. pylori is classified as class I carcinogenic by the IARC because it induces DNA mutations and epigenetic changes. The extent to which H. pylori favours neoplastic transformation likely depends on bacterial genetic [vacuolating toxin (vacA) versus cytotoxicity-associated immunodominant antigen (cagA) antibodies], host genetics [single-nucleotide polymorphism of Interleukin1B (IL1B) and Tumor Necrosis Factor (TNF) genes], age of infection acquisition and environmental factors. Established risk factors beyond H. pylori for non-cardial gastric cancer include tobacco smoking, alcohol intake and high consumption of food preserved in salt, processed meat and grilled or barbecued meat and fish (Munoz and Franceschi 1997; Nishino et al. 2006). Less common risk factors include obesity and autoimmune gastritis (Massarrat and Stolte 2014; Buckland et al. 2015). Cardial GC develops in the upper stomach (cardia), mainly affects men in the seventh decade of life and represents 50–60% of GC in North Europe and USA. Risk factors include gastro-esophageal reflux disease and obesity.

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The GC arising in a familial/hereditary setting include: (A) Hereditary diffuse GC (HDGC): it is an autosomal dominant cancer susceptibility syndrome characterized by diffuse-type GC and invasive lobular breast cancer, mainly caused by inactivating germline mutation in CDH1 gene encoding E-cadherin, a molecule involved in cell-to-cell adhesion. The prevalence of HDGC is 5 cm) and loss of body weight (> 3 kg) (Li et al. 1998). Negative correlation between NPY level and tumor stage was also evident in GC but not in CRC (Li et al. 1998). In contrary in another study performed with tumor and normal gastric tissues it was shown by cDNA microarray-based comparative genomic hybridization that NPY gene was amplified in GC (Yang 2007). These contradictory findings indicate that the role of NPY in GI cancers is still controversial. Although there are only a few reports regarding the role of NPY in GC and CRC from human sample studies, there are recently some reports from animal model studies that show the regulatory role of NPY in GI cancers (Chakroborty et al. 2022). NPY was reported to regulate tumorigenesis by promoting proliferation (PI3-K/pAkt), and by downregulating microRNA-375 (miR-375)dependent apoptosis in intestinal epithelial cells in a dextran sodium sulfate (DSS) model of inflammation-induced tumorigenesis (Jeppsson et al. 2017). In an axozymethane/dextran sodium sulfate (AOM/DSS)-induced mouse model of inflammatory CRC, upregulation of NPY was associated with increased angiogenesis. NPY and Y2 receptor upregulation was related to higher expression of TNF-α, which promotes progression of colon carcinogenesis (Sarkar and Chakroborty 2014). Significant upregulation of NPY was seen in CT26 colon cancer tissues where a dual regulatory role of NPY was reported. NPY via Y1 receptors, which are predominantly expressed by tumor cells, controls the proliferation and growth of the cancer cells (Goswami et al. 2020). NPY by acting through Y2 receptors that are mostly expressed by the endothelial cells also controls the functions of these cells present in the tumor microenvironment (Chakroborty et al. 2022). Recent findings demonstrated that NPY acts through Y2R to promote angiogenesis in colon cancer by activating the ERK/MAPK pathway in colonic endothelial cells (Chakroborty et al. 2022).

3.6.2 Substance P (SP) SP, a small undecapeptide, is a member of the large family of structurally related peptides, the tachykinins which have a conserved carboxyl-terminal domain

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(Phe-X-Gly-Leu-Met-NH2, X hydrophobic or aromatic; Harrison and Geppetti 2001) and share common pharmacological properties. SP mediates its actions by binding to its high-affinity neurokinin-1 receptor (NK-1R; Pernow 1983; Maggi et al. 1997), which is a seven transmembrane domain G-protein coupled receptor. At high concentrations, SP can also activate neurokinin-2 (NK-2R) and neurokinin-3 (NK-3R) receptors (Regoli et al. 1994). In GC and CRC, SP activates the NK-1 receptor, which is expressed on primary colon and gastric adenocarcinoma cells. SP and NK1R expressions were upregulated in CRC compared to adjacent normal tissues and were significantly associated with lymph node metastasis and poor prognosis (Mou et al. 2016). Similar high overexpression of NK-1R was reported in GC cells and tissues (Rosso et al. 2008). Presence of different isoforms of NK-1R was reported in GC cells and tissues. Activation of the NK-1 receptor resulted in promotion of a number of processes like mitogenesis, angiogenesis, cell survival, migration, and metastasis, thereby proving its involvement in regulation of the TME (Mayordomo et al. 2012). SP also promoted N-methyl-N′-nitro-N-nitrosoguanidineinduced gastric carcinogenesis (Tatsuta et al. 1995) and the number of SP-positive nerves might be related to GC progression (Feng et al. 2011).

3.6.3 Vasoactive Intestinal Peptide Vasoactive intestinal peptide (VIP), a 28-residue amino acid peptide, is a member of the secretin/glucagon hormone superfamily. It was first isolated from porcine duodenum and characterized in 1970. It is widely distributed in the CNS and PNS as well as in the respiratory, reproductive, cardiovascular, and GI systems (Iwasaki et al. 2019). In the GI tract it is mainly localized in the myenteric and submucosal neurons and nerve terminals and as its name implies, is a potent vasodilator (Larsson et al. 1976; Costa and Furness 1983). VIP mediates its actions through VPAC1 and VPAC2, which are class B of G-protein coupled receptors, also known as the secretin receptor family. VIP regulates a number of GI functions such as gastric acid secretion, intestinal anion secretion, cellular motility, vasodilation, smooth muscle relaxation, and intestinal contractility (Iwasaki et al. 2019). In addition to regulating several physiological function in the GI tract, VIP has also been implicated in the pathogenesis of both GC and CRC. Both VPAC1 and VPAC2 are overexpressed in GC and CRC. While VPAC1 primarily expresses on the epithelial cells, VPAC2 expression is mainly on smooth muscle cells of the GI tract (Iwasaki et al. 2019). VPAC1 is overexpressed colon (96%) and gastric adenocarcinomas (54%) (Reubi et al. 2000). It was reported that 35% of welldifferentiated colon cancers, 65% of moderately differentiated tumors and 87% of poorly differentiated colon cancers expressed VPAC1. VPAC1 overexpression was reported in blood vessels and tumor-associated macrophages (Liu et al. 2014). Another study however reported that VIP inhibited the progression of GC by depressing the activation of TAM, which resulted in reduced expressions of TNFα, IL-6, IL-12, and iNOS. VI-treated TAM could significantly reduce the growth of MKN45 GC (Chen et al. 2015a, b). VIP could also inhibit proliferation of colonic cancer-cells (Lelièvre et al. 1998). In the APC(Min/+) model of

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spontaneous colon cancer, defects in the expressions of the anti-inflammatory neuropeptides, VIP, and pituitary adenylate cyclase-activating peptide (PACAP), increased colonic inflammation, which resulted in increased initiation and progression of colonic cancers (Vinuesa et al. 2012). VIP stimulated proliferation of HT29 colon cancer cells by activation of Ras/Rap1-B-Raf-ERK pathway (Alleaume et al. 2003) and VIP antagonists, neurotensin(6–11)VIP(7–28) inhibited HCT-15 cancer cell growth (Levy et al. 2002). Furthermore, antagonist treatment of SpragueDawley rats bearing colon tumors after injection with azoxymethane (AOM) (15 mg/kg/week) for 2 weeks showed reduced tumor volume, lymphocyte infiltration, and the number of dysplastic crypts (Levy et al. 2002). However, in Colon 26-L5 adenocarcinoma cells, VIP was reported to reduce the invasive potential of tumor cells (Ogasawara et al. 1997). VIP and its receptor, VPAC1, can serve as potential prognostic markers and therapeutic targets for GC as higher VIP/VPAC1 expressions were observed in GC compared to normal tissues which showed positive correlations with tumor stage, metastases, and poor survival. Activation of VPAC1 by VIP significantly increased transient receptor potential vanilloid 4 (TRPV4)mediated Ca2+ entry, which led to GC progression in a Ca2+ signaling-dependent manner. In addition, as a positive feedback mechanism, VPAC1/TRPV4/Ca2+ signaling increased the expression and secretion of VIP in GC cells (Tang et al. 2019).

4

Conclusion

In recent years, our knowledge has significantly improved in understanding the role played by nerves and neurotransmitters/neuromodulators in development and progression of non-CNS solid tumors. GI cancers are of significant interest in this area as the organs in the GI tract are not only richly innervated by nerves from the CNS but also by the GI tract’s own nervous system, the ENS (Costa 2000; Lomax et al. 2009; Bharucha 2003; Phillips and Powley 2007; Uesaka et al. 2016; Burns and Thapar 2006). The ENS plays a critical role in regulating GI tract functions and maintaining homeostasis which is largely dependent upon the proper functioning of the ENS/CNS, failure of which leads to several GI diseases including GC and CRC (Costa 2000; Lomax et al. 2009; Di et al. 2019; Kulkarni et al. 2018; Duraker et al. 2003; Schledwitz et al. 2021). Neurotransmitters or neurohormones as messenger molecules have thus emerged as important players in the growth and progression of GC and CRC (Chakroborty et al. 2004, 2008; Basu and Dasgupta 1997; Basu and Dasgupta 1999). Initially, the role of the CNS in regulating the growth of GC and CRC was extensively studied as it was considered as the primary source of the neuromodulators in the GI tract. However, with the evidence of synthesis and secretion of different neurotransmitters by nonneuronal sources in the GI tract like gastric and colonic epithelial cells, entero endocrine cells, endothelial cells, immune cells, cancer cells and the presence of neurotransmitter receptors in tumor cells and

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other cells in the TME, this area of research has taken a dramatic turn in last two decades. Understanding the interactions between the neuromodulators and the cancer cells and other cells within the TME that regulate the growth of GC and CRC will therefore contribute to unraveling new therapeutic targets (Basu and Dasgupta 1997, 1999; Chakroborty et al. 2004, 2008, 2022; Cheng et al. 2008; Cianchi et al. 2003; Dowling et al. 2015; Mezey et al. 1998, 1999; Gershon and Tack 2007; Sarkar et al. 2022; Shah et al. 2021). Despite a growing interest in recent years in studying these neuromodulators and their connection to tumor development and progression, our knowledge is limited due to the lack of sufficient number of studies that involve human subjects over long durations and also due to the lack of suitable number of appropriate animal models that faithfully mimic the complex and diverse TME observed in GC and CRC which have often resulted in contradictory reports. A more comprehensive approach toward understanding the functions of these neuromodulators in individual component of the TME is therefore needed. Currently available advanced techniques such as single-cell RNA-Seq data and spatial transcriptomics can be used to develop a complete inventory of TME cells and assess the expression levels of different neurotransmitter receptors in individual TME component in GC and CRC patients (Ahmed et al. 2022; Mangiola et al. 2021; Hernandez et al. 2021; Zhu et al. 2017). In vivo gene editing strategies of candidate genes identified from high-resolution transcriptomic mapping and creation of relevant human organoids together with live-cell imaging can be used to study the progression of GC and CRC (Ahmed et al. 2022; Mangiola et al. 2021; Hernandez et al. 2021; Zhu et al. 2017). Also, in order to develop novel ENS-based therapeutic strategies for GC and CRC, it is needed that more human studies be conducted to confirm the clinical relevance of experimental findings. In addition, continued research and identification of novel targets that contribute to the modulation of the TME to promote metastatic progression will further help to improve therapeutic approaches. In this chapter, we have summarized some of the important findings regarding the role of neuromodulators in the TME of GC and CRC that were reported to date including the findings from our own laboratory. The summary of the functions of the neuromodulators in the TME of GC and CRC is provided in Table 1. With more studies in the field, the key gaps in knowledge regarding the mechanisms of GC and CRC carcinogenesis can be filled which will lead to the identification of sensitive biomarkers for diagnosis and designing of effective therapeutic interventions to improve patient outcomes. Therefore, a better understanding of neurotransmitters and neuropeptides, their receptors, and the therapeutic efficacy of their agonists and antagonists is warranted. A number of agents targeting the neurotransmitters such as the DA receptor agonists and antagonists, the beta-blockers, ACh receptor antagonists, and 5-HT receptor blockers are being widely used in the clinics for the treatment of various diseases. With their known safety profiles, these agents can easily be repurposed for any new use in therapy.

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Table 1 Summary of the functions of the neuromodulators in the tumor microenvironments of gastric and colorectal cancers Neuromodulator Acetylcholine

Catecholamines Dopamine

Epinephrine and norepinephrine

Serotonin

Role in gastric and colon cancers 1. Promotes gastric cancer cell migration and invasion via promotion of epithelial to mesenchymal transition 2. Promotes colon cancer cell migration by enhancing the secretion of MMPs 3. Regulates drug resistance in gastric cancers

References Yu et al. (2017) Yang et al. (2016) Cheng et al. (2008) Hering et al. (2021) Felton et al. (2018) Xian et al. (2013)

1. Inhibits VEGF-mediated angiogenesis in gastric and colon cancers 2. Promotes vessel normalization and endothelial cell quiescence in colon cancer 3. Promotes pericyte migration and maturation in tumor microenvironment 4. Improves perfusion, reduces hypoxia and enhances drug availability in tumor microenvironment in colon cancer 5. Inhibits gastric cancer cell proliferation 1. Promote proliferation, invasion, and survival of gastric cancer cells 2. Enhance glycolysis in gastric cancer cells 3. Promote epithelial to mesenchymal transition in gastric cancer cells 4. Promote resistance against therapeutic and targeted agents in gastric and colon cancers 5. Promote secretion of VEGF, MMPs, and AP1 in gastric cancers 6. Promote proliferation and migration of tumor endothelial cells and tumor angiogenesis both in gastric and colon cancers 1. Paradoxical in nature 2. Plays protective role in the early stages of tumor development by promoting DNA repair activity in cancer cells in colon cancer 3. Promotes colon cancer cell proliferation by activating serotonin re-uptake transporters and receptors in colon cancer

Chakroborty et al. (2011), Chakroborty et al. (2004), and Sarkar et al. (2022) Sarkar et al. (2008) and Ganguly et al. (2010)

Zhang et al. (2019) Yao et al. (2009) Wang et al. (2021) Shi et al. (2010) Shi et al. (2013) Pu et al. (2012) Liu et al. (2015)

Kannen et al. (2020) Ye et al. (2021) Gershon and Tack (2007) and Xu et al. (2006) Sakita et al. (2019) Tutton and Barkla (1978), Chan et al. (2020), Balakrishna et al. (2021), Zamani and Qu (2012), Peters et al. (2014) (continued)

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Table 1 (continued) Neuromodulator

Nitric oxide

γ-Aminobutyric acid

Neuropeptide Y

Substance P

Role in gastric and colon cancers

References

4. Creates pro-inflammatory microenvironment promoting colorectal cancer progression 5. Promotes angiogenesis in colon cancer 1. Promotes VEGF-mediated angiogenesis in colorectal cancer 2. Lack of inducible nitric oxide synthase in Apc(min/+)mice promotes tumorigenesis 3. In gastric cancer inducible nitric oxide synthase expression is related to increased VEGF expression, microvessel density, lymph node metastasis, and decreased immune responses 4. Endothelial nitric oxide promotes angiogenesis in gastric cancer 1. GABARD overexpression promotes proliferation and migration of colorectal cancer cells 2. GABARD overexpression correlates with gene set defining epithelial to mesenchymal transition, angiogenesis in colorectal cancer 3. GABA via GABAA receptors promotes proliferation of gastric cancer cells activating the ERK-1/2/ cyclin D1 pathway 4. GABA via GABAB inhibits gastric carcinogenesis and experimental colorectal carcinogénesis 1. Promotes cell proliferation of colorectal cancer cells 2. Inhibition of NPY promotes apoptosis on colon cancer cells 3. Promotes cell proliferation, migration and tubule formation capabilities of endothélial cells 4. Promotes angiogenesis in colon cancer 1. Promotes lymph node metastasis in colon cancer 2. Promotes mitogenesis, angiogenesis, cell survival, and migration metastasis of colon cancer cells 3. Promotes gastric carcinogenesis

Nocito et al. (2008) and Schneider et al. (2021)

Song et al. (2002) Karadayı et al. (2013) Yamaguchi et al. (2005) and Zhang et al. (2011) Wang et al. (2005)

Niu et al. (2020) Maemura et al. (2009) and Tatsuta et al. (1990)

Sarkar and Chakroborty (2014) Jeppsson et al. (2017) Goswami et al.(2020) Chakroborty et al. (2022)

Mou et al. (2016) and Mayordomo et al. (2012) Tatsuta et al. (1995) Feng et al. (2011)

(continued)

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Table 1 (continued) Neuromodulator Vasoactive intestinal polypeptide

Role in gastric and colon cancers 1. Inhibits gastric cancer by depressing activation of tumorassociated macrophages 2. Inhibits proliferation of colonic cancer cells 3. Stimulate proliferation of colonic cancer cells by activation of Ras/Rap1/B/Raf/ERK pathway 4. Ras antagonist treatment reduces tumor volume, lymphocyte infiltration, and number dysplastic crypts formation in colon cancer 5. Reduces invasive potential of colon 26-L5 adenocarcinoma cells 6. Promotes gastric cancer progression in Ca2+ signalingdependent manner

References Chen et al. (2015a, b) Lelièvre et al. (1998) Alleaume et al. (2003) Levy et al. (2002) Ogasawara et al. (1997) Tang et al. (2019)

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The Role of Tumor Microenvironment in Colon Cancer Caterina Fattorini, Marco Arganini, Andrea Cavazzana, and Maria Raffaella Ambrosio

Abstract

Colorectal cancer (CRC) is one of the most common causes of morbidity and mortality in both women and men. Given that CRC is an important health problem, many efforts have been spent to better stratify patients in terms of prognosis and prediction of response to therapy. In recent years, the tumor microenvironment (TME) has received increasing attention by scientific community; many research focused on its possible prognostic and predictive role. Here we aim to summarize the latest available knowledge in this field through a literature research and to highlight possible critical issues and opportunities. The most relevant studies highlighted the crucial role of TME in cancer development and progression. The immune compartment above all is an important prognostic factor. In fact, a brisk peri- and intratumoral inflammatory response is associated with better survival, while low immune infiltrates are a sign of poor outcome. Investigators comparing hematoxylin-eosin tumor-infiltrating lymphocyte evaluation and immunohistochemical lymphocytic subset studies came to stackable conclusions. To enter immune cells’ assessment in routine clinical practice, previous studies focused on possible standardized scores such as Immunoscore® and tumor-stroma ratio. Moreover, recent groups implemented manual cell count with digital image analysis software. Finally, components of TME are also promising therapeutic targets: antiangiogenetic agents and immunotherapy are now routinely available and agents directed against other TME components such as cancer-associated fibroblasts are under study. The role of

C. Fattorini · A. Cavazzana · M. R. Ambrosio (*) Pathology Unit, Azienda Sanitaria Toscana Nord-Ovest, Pisa, Italy e-mail: [email protected] M. Arganini Surgery Unit, Ospedale Unico Versilia and Nuovo Ospedale Apuane, Azienda Sanitaria Toscana Nord Ovest, Pisa, Italy # The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2022_26 Published online: 12 October 2022

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TME in CRC progression and prognosis has been widely recognized. However, there is a lack of standardization regarding immune infiltrates’ assessment that would make it incorporable in routine clinical practice. Moreover, the role of digital pathology in TME evaluation is currently under studies and the true cost-benefit ratio of new technologies is not yet fully elucidated. Finally, further research would lead to novel therapeutic strategies. Keywords

Colorectal cancer · Inflammatory response · Tumor microenvironment

1

Introduction

Colorectal cancer is one of the commonest cancers occurring in both women and men, ranking third in terms of new cases, preceded by breast and lung cancer, and second for mortality after lung cancer in 2020 (Global Cancer Observatory 2020). CRC incidence and mortality rates greatly vary from country to country according to Human Development Index (HDI). The highest incidence occurs in high HDI countries (Europe, Australia, and Northern America mainly), and this fact is strongly related to CRC risk factors: countries with higher population level of obesity, red meat consumption, alcohol consumption, sedentary lifestyle, and tobacco use are at the higher risk of developing CRC. The mean age at diagnosis is 68 years for men and 72 years for women. However, in the last years, an increased incidence has been observed in patients younger than 50 years (Sawicki et al. 2021). Considering these data, CRC is indeed an important health problem and during the last decades, a lot of efforts have been made to improve diagnosis and prognosis. Prognostic stratification of patients is mainly based on a correct staging following the TNM staging system (Amin et al. 2017); the most relevant pathological parameters taken into consideration are depth of tumor invasion (T) and presence/absence of lymph nodes (N) and distant (M) metastasis. Other important prognostic factors that guide treatment decisions are lymphovascular and perineural invasion, the state of resection margins, microsatellite instability, and KRAS/NRAS/BRAF mutation status. Scientists’ attention has recently focused on tumor microenvironment as an important host factor that seems to play a crucial role in CRC progression; these studies allow clinicians to better stratify patients’ outcome and guide therapy (Liu et al. 2020). Tumor microenvironment (TME) is the complex background where the tumor settles and grows, and it consists of all cellular and noncellular components that have close interaction with tumor cells. The cellular component of TME is composed mainly of endothelial cells and pericytes that form blood vessels, immune cells, and stromal cells such as fibroblasts, whereas noncellular component consists of extracellular matrix (ECM) and signaling molecules such as cytokines (Baghban et al. 2020).

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In this chapter, we will focus on the main components of tumor microenvironment in colorectal cancer and their role in promoting tumorigenesis and cancer progression; afterward, we will take into consideration the latest technologies used for TME analysis as well as the therapeutic implications of TME in colorectal cancer.

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TME and Colorectal Cancer

Tumor microenvironment is now widely recognized as an important host factor in determining patient treatment response and survival (Alexander et al. 2020). Both tumor-infiltrating immune cells and stroma cells contribute to determine the clinical behavior of the neoplasia. The first studies of peritumoral immune infiltrates in colorectal cancer patients date back to the 1960s, when Spratt and colleagues first took into consideration TME as a variable influencing prognosis (Spratt and Spjut 1967). Since that time, the role of TME has been extensively studied, especially the immune compartment.

3

Immune Cellular Compartment of TME

Scientists have generally reported that a brisk inflammatory cell infiltrate within and around tumor cells was associated with improved clinical outcome, and it was thought to be the host immune response to the tumor (Murray et al. 1975; Watt and House 1978; House and Watt 1979; Svennevig et al. 1984). Subsequently, studies had focused on determining the density and composition of immune infiltrate of TME, trying to find a connection between lymphocyte and macrophage subsets and outcome. Various methods of assessment of immune infiltrates on hematoxylin and eosin (H&E) sections have been developed over time: immuno-scores, Crohn’s-like reaction evaluation, tumor-infiltrating lymphocyte studies, and combined assessments. Moreover, many scientists focused on the characterization of lymphocytic subpopulations.

3.1

Jass and Klintrup-Makinen Scores

One of the first and most important work was the ones carried out by Jass and colleagues in 1986 and by Klintrup and coworkers in 2005 that both ended up becoming important semiquantitative scores. Jass and coworkers evaluated immune infiltrates at the invasive margin (IM) and developed a three-point scale: pronounced, moderate, and little. A pronounced infiltrate appeared to be an independent prognostic factor and allowed scientists to stratify patients’ survival (Jass 1986). Subsequently, in 2005, Klintrup and colleagues developed the Klintrup-Makinen (KM) score: they also evaluated infiltrates at the invasive front and in the areas of deepest invasion. Overall, inflammatory reaction and the amount of lymphoid cells

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and neutrophilic and eosinophilic granulocytes were assessed by using a four-degree scale. A score of 0 indicated an absence of reaction, 1 weak, 2 moderate, and 3 severe increase of each cell type. A similar scale was used at the invasive margin. A score of 0 was given when there was no increase of inflammatory cells, 1 denoted mild and patchy increase of inflammatory cells at the invasive margin, but no destruction of invading cancer cell islets by the inflammatory cells. A score of 2 was given when inflammatory cells formed a band-like infiltrate at the invasive margin with some destruction of cancer cell islets by inflammatory cells. A score of 3 denoted a very prominent inflammatory reaction, forming a cuplike zone at the invasive margin, and destruction of cancer cell islets was frequent and invariably present. Examples of moderate and severe immune infiltrates can be noted in Fig. 1. Macrophage reaction

Fig. 1 Hematoxylin-eosin slides representing lymphocytic immune infiltrate examples in colonic adenocarcinoma at 20× magnification. (a) and (b) Peritumoral immune infiltrate of moderate density arranged at invasive tumor margin. (c) and (d) A brisk lymphocytic infiltrate encircled neoplastic glands

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was graded as either absent (grade 0) or present (grade 1). Macrophage reaction was recorded as being present when collections of foamy macrophages encircling invading tumor islets were observed, and as being absent when such collections of macrophages were not observed (Klintrup et al. 2005). Similarly to Jass, they concluded that high-grade inflammation was an independent prognostic factor in colorectal cancer.

3.2

Crohn’s-Like Reaction

Graham and colleagues analyzed the presence of discrete lymphoid aggregates with or without germinal centers beyond the advancing tumor front of 100 colorectal cancers (Graham and Appelman 1990). This type of peritumoral immune infiltration was called “Crohn’s disease-like reaction (CLR)” because of the similarities with the reactive infiltrates of Crohn’s disease, and it was mainly located in muscularis propria or pericolic fat tissue. The intensity of this reaction was graded as absent, mild, or intense. They also evaluated the presence of invasion beyond the tonic muscularis propria, nodal metastases, and lymphoid infiltrates at tumor margins; moreover, they correlated CLR with survival. Graham and colleagues concluded that CLR happened more frequently in right-sided cancer that invaded muscularis propria and pericolic fat. They also noted that an intense CLR was associated with a high immune infiltrate at tumor margin, a lower incidence of nodal metastases, and a statistically significant increase in 10-year survival rate. They hypothesized that CLR represented a part of the favorable host response together with TILs at invasive tumor margin. In 2013, Ueno and colleagues analyzed more than 1000 colorectal cancers and proposed a new way of CLR evaluation, revising the “Graham method”: they noted the total number of lymphoid aggregates (LA) observed in all tumor slides per case, the average number of LA per slide, and the number of LAs in a ×2 microscopic objective lens field where CLR was most intense; moreover, they determined the diameter of the largest LA. Based on their results, they concluded that there was no significant correlation between the number and recurrence rate or 5-year diseasespecific survival rate. In contrast, they found that the size of LA was important: LA with a diameter larger or equal to 1 mm were associated with lower recurrence rate and higher 5-year disease-specific survival rate, and they had an independent impact on survival from T stage, N stage, or tumor budding (Ueno et al. 2013). Also Vayrynen and coworkers revised the Graham method: they not only counted the number of CLR follicles but also the length of the invasive front. Then they defined a new parameter, called “CLR density,” which is the number of CLR follicles/the length of the invasive front. Also the number of lymphoid follicles with germinal centers, the average diameter of the lymphoid follicles, and the histological layer with the highest concentration of lymphoid follicles were annotated. Finally, they include the qualitative criteria of Graham in CLR evaluation as follows: 0 (no reaction) denoting no or at most one single lymphoid aggregate in all tumor sections, 1 (mild reaction) defined as occasional lymphoid aggregates with

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rare or absent germinal centers, and 2 (intense reaction) denoting numerous lymphoid aggregates with germinal centers. Statistical analysis revealed that high CLR density was associated with low stage, mismatch repair deficiency, and high peritumoral and intratumoral T-cell infiltrates; moreover, high CLR density was a stage independent marker of better survival rate. Scientists concluded that their new parameter, the so-called CLR density, was superior to Graham method for CLR evaluation, allowing a better patient stratification.

3.3

TIL Evaluation on H&E

TILs are the main component of the immune cell infiltrate of TME. TILs comprise T-lymphocytes, B-lymphocytes, and also NK cells and have been shown to have important prognostic value in colorectal cancer (Hendry et al. 2017). Both intratumoral (IT) TILs and TILs at the invasive margin (IM) of tumors have been evaluated. Invasive margin was defined as an interface between the host stroma and the invading edge area of a tumor (Klintrup et al. 2005). Many scientists evaluated the role of B- and T-lymphocytes in TME, and most part of studies found a positive association with survival using Klintrup-Makinen score (Ogino et al. 2009; Hynes et al. 2017; Ropponen et al. 1997; Iseki et al. 2018; Rozek et al. 2016).

3.4

Combined Assessment

In 2009, Ogino and coworkers developed a combined scoring system taking into consideration Klintrup-Makinen score, Crohn’s-like reaction, and intratumoral and peritumoral TIL evaluation (Ogino et al. 2009). They analyzed more than 800 colorectal cancers and assigned a semiquantitative score to each element and then combined them in a total score called “overall lymphocytic reaction score.” Based on an arbitrary cutoff, they separated the cohort into three categories and then related the results to survival data. They founded that all elements except intratumoral TILs were statistically significant for overall survival (OS) regardless of other clinical, pathological, or molecular characteristics; in particular, a high overall lymphocytic score was associated with higher OS compared to patients with low immune infiltrates.

3.5

Immune Cell Subsets

Scientists have also focused on subset characterization of immune cells, B-lymphocytes, T-lymphocytes, and NK cells, in particular, and their relationship with survival data. CD20 is used as a B-lymphocyte marker, while CD3 is a pan-T cell marker and CD56 is the marker of NK cells. T-lymphocytes are subdivided in CD4+ helper T-cells (Th cells), CD8+ cytotoxic T-cells, FOXP3+ regulatory T-cells (Treg), CD45RO+ memory T-cells, and PD1+ CD8+ T-cells (namely, exhausted T-cells).

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One of the principal works on immune cell infiltrate characterization in colorectal cancer was that of Galon and colleagues (Galon et al. 2006). They performed a combined genomic and immunohistochemical (IHC) study of more than 400 colorectal cancer patients. They evaluated the expression level of genes related to inflammation and the composition of the adaptive immune response to tumors by using immunohistochemical markers of different lymphocyte subpopulations: CD3-, CD8-, and CD45RO-positive cells’ density at the center of tumor (CT) and the invasive margin (IM). Then Galon and coworkers related IHC and genomic results to patients’ outcome. They concluded that type, location, and density of immune adaptive response had a prognostic value: both disease-free survival (DFS) and OS rates were higher for patients with high density of CD3-, CD8-, and CD45ROpositive cells at IM and CT. Some other investigated the role of single markers: • CD3 is a pan T-cell marker. Most studies found a significant positive association between CD3+ cell number and survival (Sinicrope et al. 2009; Galon et al. 2006; Guidoboni et al. 2001; Flaherty et al. 2016; Laghi et al. 2009; Deschoolmeester et al. 2010; Berntsson et al. 2017; Nearchou et al. 2019). Some others instead didn’t find any significant association with survival (Lavotshkin et al. 2015; Hanke et al. 2015; Schweiger et al. 2016). • CD8 is a cytotoxic T-cell marker. The role of cytotoxic cells is mainly to recognize a foreign antigen, induce cell lysis, and recruit other immune cells via cytokine production (Alexander et al. 2020). Many authors found that higher CD8+ cell-rich immune infiltrates were associated with better survival (Menon et al. 2004; Prizment et al. 2017; Chiba et al. 2004; Flaherty et al. 2016; Guidoboni et al. 2001; Deschoolmeester et al. 2010; Eriksen et al. 2018; Katz et al. 2009). However, other scientists didn’t find that association (Takemoto et al. 2004; Baeten et al. 2006; Suzuki et al. 2010). • CD4 is a surface marker expressed by helper T-cells, which plays a role in anticancer immunity by having cytotoxic capabilities and also by recruiting cytotoxic T- and B-cells (Borst et al. 2018). In most cases, scientists found a positive association between density of CD4+ cells and survival data (Chen et al. 2016; Ling et al. 2014; Canna et al. 2005), while in some cases not (Menon et al. 2004; Nagtegaal et al. 2001; Lavotshkin et al. 2015; Matsutani et al. 2018). • CD45RO is a surface marker expressed especially by effector memory T-cells. These types of cells enact a swift response to a recognized foreign antigen (Mahnke et al. 2013). Also for that marker, studies tended to find a correlation between expression and survival (Kim et al. 2015; Chen et al. 2016; Richards et al. 2014; Pagès et al. 2009). • FOXP3 is expressed by regulatory T-cells, whose role is to regulate the immune system by suppressing T-cell activity and preventing overactivity and autoimmune events (Alexander et al. 2020). Some scientists theorize that regulatory T-cells may have a negative effect on survival because of their anti-immune effect and some studies seem to corroborate this theory, other works instead found a positive association with survival (Kim et al. 2015; Chen et al. 2016; Ling et al.

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2014; Miller et al. 2017; Salama et al. 2009; Nosho et al. 2010; Märkl et al. 2017) or they didn’t find it at all (Mori et al. 2015; Loddenkemper et al. 2006; Chen and Chen 2014). Surely further studies are needed to elucidate the exact role of FOXP3+ cells in colorectal cancer TME. • PD-1+ CD8+ T-cells: these types of cells are also known as “exhausted T-cells.” The concept of “T-cell exhaustion” was born a few years ago. Wherry defined T-cell exhaustion as a state of T-cell dysfunction that arises during chronic infections and cancer (Wherry 2011). Poor effector function, sustained expression of inhibitory receptors, and a transcriptional state distinct from that of functional effector or memory T cells characterize exhausted T-cells. In particular, when chronically stimulated, CD8+ effector (cytotoxic) T-cells progressively lose their functions: firstly, there is a reduced expression of pro-inflammatory cytokines that causes a loss of effector T-cell proliferation capacity; then these cells acquire PD-1 membranous expression; afterward, they lose their cytolytic function; the result of all these steps is the deletion of CD8+ PD-1+ effector T-cells, namely, a “T-cell exhaustion.” In tumor context, T-cell exhaustion can lead to premature cessation of the immune response against neoplasia. The expression of PD-1 seems to be a crucial event in T-cell exhaustion process; because of this, scientists theorized that cancer patients with active immune infiltrates can benefit from immune checkpoint inhibitors. In fact, PD-1 inhibition would be able to return CD8+ PD-1+ effector T-cells on a functional state. Several studies have been conducted on exhausted T-cells in colon cancer. For example, Prall and Hühns analyzed PD-1 expression of T-cells in CRC microenvironment by using CD8, granzyme B, FoxP3, CD68, S100, and PD-1 immunohistochemistry (Prall and Hühns 2017). The density of every immune cell subtype was calculated and then a hierarchical clusterization was made. They found three different groups representing different types of immune microenvironment: an “immunoreactive” group with numerous PD-1+ cells, an “anergic/immune-naive” group, and an “intermediate” group. Furthermore, they concluded that the immunoreactive group has not only an active host anti-tumor response but also an undercurrent T-cell exhaustion mechanism. The identification of such immune type of cells in CRC microenvironment can possibly have clinical and therapeutical implications, and further studies are certainly needed to carefully evaluate the role of checkpoint inhibitors in this category of patients. • CD20 is a pan B-cell marker; B-lymphocytes interact with T-cells, produce cytokines to recruit and activate T-cells, and then act as antigen-presenting cells (APC) and produce antibodies (Tsou et al. 2016). There are only a few studies examining the expression and role of CD20+ cells in CRC, and most of them found a positive association between CD20 expression and survival (Chen et al. 2016; Meshcheryakova et al. 2014; Berntsson et al. 2016; Edin et al. 2019). • CD56/CD57 are NK cell markers, whose role is to induce cell lysis (Vivier et al. 2008). Most part of the few available studies found a positive association with survival considering both IM and IT (Menon et al. 2004; Coca et al. 1997; Tachibana et al. 2005; Liska et al. 2012).

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Despite the results of all these studies examining the impact of single immune cell subsets on outcome, a semiquantitative H&E evaluation of immune infiltrates seems to be enough for a correct assessment of inflammatory infiltrates, given that it provides similar prognostic results (Alexander et al. 2020).

3.6

TAMs (Tumor-Associated Macrophages)

Tumor-associated macrophages are monocyte deputies to phagocytosis, antigen presentation, and T-cell recruiting. Their role in cancer progression is still not fully known. Many studies have highlighted a dual role of TAM within TME: these cells have both pro-tumor (Wang et al. 2021b) and anti-tumor properties (Pernot et al. 2014). TAMs are subdivided into two categories: M1 and M2 cells. M1 TAMs are known for their role in contrasting tumor progression, while M2 TAMs are believed to have a pro-tumor role. CD68 is a generic macrophages marker, while CD163 and CD206 are more specific for M2 macrophages. Using these antibodies, investigators analyzed the density of M1 and M2 TAMs in CRC. Most studies found that the presence of M2 cells was generally associated with a worse outcome, while high M1 count was related to better prognosis (Edin et al. 2012). When considering both M1 and M2 density together, the anti-tumor effect seems to prevail since available studies highlighted their positive association with survival. For example, two studies (Li et al. 2017; Forssell et al. 2007) found that high density of TAM at tumor front was associated with more TIL count, less epithelialmesenchymal transition (EMT) markers, fewer tumor buds, and finally longer OS.

3.7

TANs (Tumor-Associated Neutrophils)

Neutrophils are an essential component of the innate immune system. They normally induce phagocytosis, release lytic enzymes, and contribute to produce ROS. Like TAMs, TANs also polarize toward two distinct phenotypes in response to environmental signals: N1 neutrophils that have antitumorigenic properties and N2 neutrophils, with pro-tumorigenic activity. N1 cells increase cytotoxicity and produce various numbers of molecules, such as TNF-alfa, ROS, and Fas that reduce immunosuppressive abilities. N2 cells instead support tumor progression and invasion via production of many factors such as VEGF, MMP9, and CCL5 and also by capturing circulating tumor cells and promoting their migration to distant sites (Mizuno et al. 2019). It seems that the levels of TGF-beta inside the tumor determine neutrophil polarization: high TGF-beta levels promote N2 differentiation, while low levels promote N1 polarization. The role of TANs in CRC is still not yet clear, since studies highlighted conflicting results. For example, Rao and colleagues found that a high density of TANs was associated with worse survival (Rao et al. 2012), while Berry and coworkers noted a better survival (Berry et al. 2017).

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4

Stromal Cellular Compartment of TME

4.1

Cancer-Associated Fibroblasts (CAFs)

Cancer-associated fibroblasts are the main component of the stromal compartment of TME (Pietras and Ostman 2010). Physiologically, fibroblasts are cells of connective tissue with elongated morphology and negativity for epithelial, endothelial, or leukocyte markers and the main producers of extracellular matrix (ECM); they also have an important role in tissue repair processes. Fibroblasts normally produce various numbers of substances including TGF-beta, which favors the acquisition of a myofibroblast phenotype; VEGF-alfa, which promotes angiogenesis; and numerous chemokines and cytokines. Fibroblasts also play a role in immune system regulation, by promoting immuno-tolerance processes. CAFs are a distinct population of fibroblasts with unique characteristics that actively interact with neighboring cancer cells and originate from local stromal fibroblasts. According to some studies, the contact between fibroblasts and tumor cells would stimulate the production of TGF-beta and other mediators that promote the expression of alfa-SMA, the activity of the contractile cytoskeleton, and the activation of JAK-STAT signaling pathway, finally driving the acquisition of a CAF phenotype. Also genomic alterations like double-strand breaks are able to promote the transformation of fibroblasts into CAFs (Sahai et al. 2020). CAFs perform multiple functions: they are in charge of ECM remodeling, enzyme production, and tumor stiffness promotion. Mechanical alteration of peritumoral stromal compartment could lead to blood vessel collapsing, to hypoxia, and subsequently to increased invasion capabilities. They also promote angiogenesis via VEGF production and are able to influence the immune compartment: various chemokines and cytokines produced by CAFs have important immunosuppressive or immunopromoting effects on CD8+ T-cells, regulatory T-cells, and macrophages (Sahai et al. 2020). Moreover, through CXCL5 secretion, CAFs promote PD-L1 expression in cancer cells (Deng et al. 2021). The role of CAF in CRC has been widely investigated but nowadays study results are conflicting. Tsujino and coworkers studied the role of myofibroblasts in CRC, considering alfa-SMA as a marker, and found that tumors with abundant myofibroblasts were associated with shorter DFS (Tsujino et al. 2007). In 2013, Choi and colleagues analyzed various CAF subpopulations using various immunohistochemical markers and their prognostic significance in CRC. They noted that podoplanin+ CAFs were associated with less aggressive tumors and more favorable prognosis; on the contrary, alfa-smooth muscle actin (SMA)+/podoplanin- and S100+/podoplanin- fibroblasts were associated with tumor progression (Choi et al. 2013). Another study analyzed the combined role of CAF and M2 TAMs (Herrera et al. 2013): the expression of CAF and M2 macrophages was related to patients’ survival; in particular, FAP marker was associated with poorer survival. Son and coworkers instead found that immature CAFs located at the invasive tumor front were a favorable prognostic factor (Son et al. 2019).

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Finally, recent studies found that an almost total depletion of CAFs within TME results in more aggressive tumors (McAndrews et al. 2021); in particular, a selective depletion of alfa-SMA+ CAFs in genetic mouse models resulted in increased tumor invasiveness capabilities and reduced OS. It is therefore clear that further studies are needed to clarify CAFs’ role in CRC.

5

TME and Mismatch Repair System

The genetic pathways through which CRC develops are mainly three: subsequent mutations in APC/TP53/KRAS that lead to the classic adenoma-carcinoma sequence; chromosomal instability, in which tumor suppressor genes are silenced by promoter methylation; and finally the microsatellite instability (MSI) pathway, characterized by alteration of mismatch repair system. The latter type of CRC is defined as deficient mismatch repair (dMMR) or MSI cancers, and they represent 10% of all CRC and occur due to mutations in MMR genes and subsequently the loss of repair functions of one or several MMR proteins, in particular MLH1, MSH2, MSH6, and PMS2. MSI tumors are usually characterized by a distinct morphology: right sided, an abundant immune infiltrate (high TIL count and brisk Crohn’s-like lymphocytic reaction), medullary morphology, or mucinous/signet-ring cell differentiation. Mismatch repair-deficient tumors can be sporadic or associated with Lynch syndrome, an inherited syndrome that predisposes to develop numerous tumors, including colorectal cancer. For this reason, it is very important to identify Lynch syndrome patients and subsequently test their family members. In most cases, sporadic dMMR tumors are caused by acquired methylation of MLH1 promoter leading to MLH1 and PMS2 production loss. Moreover, 50% of sporadic MSI tumors carry the BRAF V600E mutation. Instead, inherited cases are mainly due to germline mutations of MSH2, PMS2, or MSH2 genes, leading to MSH2/MSH6 combined loss or MSH6 or PMS2 isolated loss, and are not characterized by BRAF mutations (Samowitz 2015). Morphologic characteristics are able to suggest microsatellite status; in particular, TIL count on H&E can predict MSI status with a specificity between 62% and 97% and a sensitivity between 21% and 93%. For this reason, in the past years, scientists used TILs as a screening test for MSI; in fact, a few years ago, MSI genetic testing was expensive, so clinician needed to selectively test patients. However, now, with the advent of immunohistochemical testing for DNA mismatch repair proteins, according to the latest National Comprehensive Cancer Guidelines, screening for MSS/MSI status is recommended for all CRC cases (Hendry et al. 2017). If there is a loss of one or more proteins detected with ICH testing, then a BRAF gene mutation status test is recommended to identify BRAF V600E-negative tumors as a screening for possible Lynch syndrome-associated tumors. In Fig. 2 is represented a case of MSI CRC tumor with loss of MSH6 protein immunohistochemical expression (see below). The main reason behind high TIL infiltration in MSI colorectal cancers is that dMMR are known to be immunogenic and neoantigen bearing (Phillips et al. 2004).

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Fig. 2 Colonic adenocarcinoma dMMR. (a) and (b) A representative area for MMR protein evaluation in a colic adenocarcinoma (H&E slides, 5× magnification in (a) and 10× in (b)). (c) Complete loss of MSH6 protein expression in adenocarcinoma glands is a clue of microsatellite instability (MSH6 stain, 10× magnification). (d)–(f) Respectively, MSH2- (d), PMS2- (e), and MLH1- (f) positive immunostain in cancer glands (original magnification 10×)

Accordingly, MSI tumors are characterized by a high tumor mutational burden (TMB): hypermethylation, BRAF mutations, and mismatch repair protein gene encoding DNA are responsible for the presence of neo-antigens and subsequently for an abundant immune infiltrate. In fact, a high TMB causes an increased expression of MHC-I molecules and the subsequent differentiation of T-cells in CD8+ cytotoxic T-lymphocytes. Moreover, it increases the efficiency of antigen-presenting cells (APCs) and upregulates MHC-II molecules causing CD4+ helper T-cells to activate other immune cells (Bai et al. 2021). Furthermore, the high TIL recruitment of MSI tumors, which comprises CD8+ lymphocytes, CD4+ lymphocytes, NK cells, and macrophages, is responsible for the increased secretion of various cytokines such as TNF, granzyme, and perforin (Mlecnik et al. 2016). Finally, Korehisa and colleagues investigated the role of programmed deathligand 1 (PD-L1) expression in MSI tumors; they assessed more than 400 CRC for MSI status and then analyzed the expression of PD-L1 in cancer and stromal compartment and tried to relate their data with survival and other histopathological characteristics. They concluded that, compared to MSS tumors, MSI cases have a higher expression of PD-L1 in both tumor and stromal cells; moreover, MSI tumors with high PD-L1 expression had poorer differentiation and lymphatic and vascular invasion compared to MSS cancers. For these reasons, MSI tumors may have a potential benefit from PD-L1/PD1 inhibitors (Korehisa et al. 2018).

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However, if it’s true that MSI tumors have high TIL infiltrate, it’s not true that TME characteristics depend solely on MMR status; in fact, the prognostic value of immune infiltrate in CRC is statistically independent from MS status (Al-Badran et al. 2021).

6

The Relationship Between TME and Chemotherapy in CRC

The relationship between TILs and neoadjuvant chemo-/radiotherapies in colorectal cancer has been widely investigated. Many research groups have focused on immunohistochemical analysis of lymphocytic subsets. For example, Teng and coworkers analyzed pre- and posttreatment CD3+ and CD8+ lymphocytic infiltrates of 136 rectal cancer patients that underwent neoadjuvant radio- and/or chemotherapy and concluded that high pre-treatment levels of both CD3+ and CD8+ lymphocytes were associated with high tumor regression grade (TRG ≥ 3) and favorable DFS and OS (Teng et al. 2015). Yasuda and colleagues examined advanced rectal cancer specimen that underwent neoadjuvant radiotherapy and analyzed the density of CD4+ and CD8+ lymphocytes in preoperative samples. They noted that the number of CD4+ and CD8+ cells correlated with TRG and histological grade; moreover, CD8+ lymphocytes were an independent prognostic factor of complete response and neoadjuvant therapy (Yasuda et al. 2011). Another study (Zhang et al. 2019) compared the efficacy of neoadjuvant chemotherapy (NAC) and neoadjuvant chemoradiotherapy (NACR) in relation to CD8+, CD4+, FOXP3+, and PD-L1+ TILs in more than 100 rectal cancer specimens. They noted that in NAC cases, high levels of CD4+, CD8+, CTLA-4+, and PD-L1+ lymphocytes were associated with favorable response to therapy, while FOXP3+ cells were associated with poor response to NAC. In NACR specimens, there was a higher infiltration of CTLA-4+ TILs compared to NAC cases. Moreover, the levels of CD8 + TILs and FOXP3 + TILs following NAC or NACR were independent prognostic factors. Finally, Wang and colleagues (Wang et al. 2021a) evaluated the efficacy of chemotherapy alone or in combination with bevacizumab in metastatic colorectal cancers in relation to CD3+ and CD8+ TILs in tumor core and invasive margin. Their results highlighted the prognostic role of CD8+/CD3+ T-cell ratio for OS. In the chemotherapy+bevacizumab group, patients with CD8+ cell infiltrates at invasive margin had longer OS and PFS, while in the chemotherapy group, patients with high CD8+/ CD3+ T-cell ratio had high response rate and those with high CD3+ cell count in tumor core had longer OS. In conclusion, TIL density and composition have an important role in predicting treatment efficacy and survival rates.

7

TME and Metastatic CRC

The most common cause of mortality in CRC patients is metastasis, being the liver the main site of secondary lesions; 50–60% of patients will develop liver metastasis (Galindo-Pumariño et al. 2021), while the lung/thorax is the second most common

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site (Kamal et al. 2020). It is now clear that TME plays an important role in tumor progression; according to the “seed and soil” hypothesis, tumor cells reach distant sites where TME provides favorable conditions (Paget 1989). Regarding the liver, for example, first of all the primary tumor prepares the distant niche by releasing pro-inflammatory and pro-angiogenic factors, interleukins, and TGF-beta. All these factors recruit various hepatic cells: Kupffer cells, hepatic stellate cells, and myeloidderived cells that produce growth factors. Subsequently, cancer cells migrate to vessels through epithelial-mesenchymal transition promoted by CAFs. Circulating tumor cells also activate cytotoxic liver cells and promote immune surveillance evasion through CTLA-4 and PD-1 production (Galindo-Pumariño et al. 2021). Kamal and coworkers reviewed the role of TME in CRC metastases (Kamal et al. 2020). They found that the lowest risk of progression was observed in tumor subclones with low mutational burden, neoantigen depletion, and high CD3+ T-cell infiltration. The highest risk of progression instead was observed in tumor subclones having immunogenic mutations. Moreover, immune-privileged metastases that have low TIL level and lack immunoediting have greater risk to recur. Van den Eynde and colleagues (Van den Eynde et al. 2018) analyzed immune infiltrate density of more than 200 patients with metastatic CRC. They performed the Immunoscore® (see below) of primary lesions and metastases. Scientists found that small metastases had low Immunoscore; moreover, high Immunoscore was associated with a lower number of metastases. Finally, they concluded that the degree of immune infiltration of CRC metastases was the most significant prognostic indicator of tumor relapse, OS, and DFS.

8

TME Validated Scores

8.1

Tumor-Stroma Ratio

As stated above, H&E evaluation of immune cell infiltrates provides similar prognostic information compared to immunohistochemical studies, so investigators have developed a reproducible score able to evaluate the abundance of immune cells in TME: the tumor-stroma ratio. Tumor-stroma ratio (TSR) is defined as a histological feature that expresses the value of the stromal component that surrounds cancer cells based on morphological evaluation of tissue sections on H&E slides (Souza da Silva et al. 2021). In their work, van Pelt and coworkers (van Pelt et al. 2018) illustrated the evaluation procedure for TSR: • The first step is to choose the H/E slide with the most invasive part of the tumor. • Then select the area with the highest amount of stroma with 2.5× or 5× lens. • Finally choose the area where both tumor cells and stromal cells are present at 10×. • Estimate the amount of stroma tissue per 10% increment per image field.

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• Assign the calculated value to one of this two categories: stroma-high, in which more than 50% of the area is occupied by stroma, or stroma-low, in which equal or less than 50% of the area is occupied by stroma in the histological section. TSR is considered an important clinical-pathological parameter and many studies confirmed its prognostic value in CRC (Mesker et al. 2009; Huijbers et al. 2013; van Pelt et al. 2016). In fact, Huijbers and coworkers found that stroma-high patients had lower OS and DFS. Also Mesker and colleagues obtained similar results: they concluded that stroma-high patients had poorer survival compared to stroma-low cases. In conclusion, TSR is a simple, reliable, and cost-effective prognostic parameter, thus routinely usable by pathologists.

8.2

Immunoscore®

One of the first research groups working on TME scoring system was that of Galon and coworkers. In the study published in 2006, they performed a combined genomic and immunohistochemical study of lymphocyte infiltrates at both the center of the tumor and invasive margin in more than 400 CRC cases; they used different IHC markers to differentiate lymphocyte subpopulations (CD3, CD8, CD45RO) and studied the expression level of genes related to inflammation and finally related the results with prognostic data (Galon et al. 2006). After that, they demonstrated the prognostic value of CD3+ cells in immune infiltrates of CRC and developed the so-called Immunoscore®. This score was at first developed using CD45RO IHC to mark memory T-cells and CD8 to mark cytotoxic T-lymphocytes in tumor center and invasive margin. The score demonstrated a high prognostic value being predictive of OS DFS and DSS (Pagès et al. 2009). Subsequent studies of the same research group (Mlecnik et al. 2011) further validated its prognostic value. In 2014, the group modified the score (Galon et al. 2014): CD45RO has been replaced by CD3. They also developed a digital image analysis of immune cells using a not publicly available software (Hermitte 2016). Also the Immunoscore demonstrated a high prognostic value and seemed to be superior to TNM parameters and MSI status (Galon et al. 2016). Afterward, other research groups have conducted similar studies trying to validated the score and generally found a positive association with survival (Pagès et al. 2018).

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TME Analysis and Digital Pathology

In recent years, scientists have started comparing manual semiquantitative H&E or IHC assessment of immune infiltrates to digital pathology technologies (Hendry et al. 2017). For example, Vayrynen and colleagues (Väyrynen et al. 2012) assessed immune cell density in CRC specimens via computer-assisted image analysis. They

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found that computer-based counting method provided more reproducible, rapid, and accurate results than visual semiquantitative assessment. So they concluded that the use of image analysis software is a valuable time-efficient alternative to manual cell count. In 2020, Nearchou and coworkers analyzed CD3+/CD8+ T-cells, CD68+/ CD163+ macrophages, and tumor budding in CRC specimens using automated image analysis and machine learning approaches. They created a prognostic model using CD68+/CD163+ cell ratio, lymphocytes within 50 μm to tumor buds, and lymphocytic infiltration and identified a subpopulation of patients with better survival (Nearchou et al. 2020). In 2021, the same research group proposed two spatial statistical methodologies for CD3+ and CD8+ lymphocytes and tumor budding and applied these digital image analysis methods to 232 stage II CRC specimens. Thanks to these new methods, they were able to develop new prognostic tools for CRC patients (Nearchou et al. 2021). Another research group (Lin et al. 2021) used artificial intelligence to provide an accurate profiling of spatial organization characteristics of public H&E slides’ archive. They analyzed infiltrating lymphocyte ratio (ILR) and infiltrating stroma ratio (ISR) and found that they had prognostic value; in particular, they were associated with relapse-free survival (RFS). All the aforementioned studies concluded that digital pathology is a valuable tools aiding in patients’ prognostic stratification. However, digital image analysis requires additional time and economic resources that need to be carefully considered. Therefore, additional studies are needed to evaluate cost-benefit of these new technologies.

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TME as a Therapeutic Target

Nowadays, different types of therapies are directly acting on TME components. For example, angiogenesis inhibition is considered a standard treatment for CRC patients for some years now. Bevacizumab was the first VEGF inhibitor approved by FDA, used alone or in combination with other agents, as a first or second line of treatment. Subsequently, other agents were released: aflibercept, another VEGF inhibitor, and ramucirumab, a monoclonal antibody against VEGFR2. All these agents are used with a great clinical benefit from CRC patients (Fridman et al. 2020). In the last few years, scientists also focused on CAFs as a possible therapeutic target. Studies focused on various aspects: CAF reprogramming toward a normal fibroblast phenotype or an antitumorigenic CAF phenotype acting on TGF-beta signaling, blocking CAF signals such as chemokine CXCL12, and targeting other ECM components in order to interfere with cancer cells communication (Sahai et al. 2020). For example, among others, Yuan et al. studied the role of MyD88 signal expressed by myofibroblasts in colitis-associated cancer (CAC) in mouse models and found that MyD88 promoted M2 polarization of TAMs via osteopontin secretion and STAT3/PPAR-gamma pathway activation (Yuan et al. 2021). M2 TAMs are known for their role in tumorigenesis. A few years earlier, Xie and coworkers

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studied MyD88 signaling pathway as a potential therapeutic target (Xie et al. 2015): they developed a MyD88 inhibitor designed to interfere with its homodimerization and tested it in a mouse model of CAC, obtaining encouraging results. Ma and colleagues studied the role of periostin in a CRC mouse model and found that fibroblast periostin secretion, a protein involved in various inflammatory diseases, contributes to tumor progression (Ma et al. 2020). For some years, periostin has been studied by scientists as a possible target for inhibition or activation (Kudo 2019). Also STAT3 pathway has been investigated: Heichler and coworkers noted that STAT3 activation and overexpression in CAFs tend to accelerate CRC tumorigenesis in mice models (Heichler et al. 2020) and also cause chemoresistance. For all these reasons, also STAT3 was taken into consideration as a possible druggable target (Chalikonda et al. 2021). Regarding immunotherapy, the possible role of PD-L1 inhibitors in CRC has been widely studied. Studies conducted on MSS tumors with high infiltration by T-lymphocytes demonstrated that this category of patients does not respond to immune checkpoint inhibitors (Fridman et al. 2020). As stated above, MSI tumors are characterized by a high tumor mutational burden (TMB) and a high neoantigen load; therefore, they also have abundant intra- and peritumoral immune infiltrates; moreover, the expression of PD-L1 is higher in these types of CRC, so patients may potentially benefit from PD-L1 inhibitors, also considering that dMMR patients benefit less from conventional chemotherapy. Immune checkpoint inhibitors block checkpoint molecules such as PD-1 and CTLA-4 and activate T-cell anti-tumor response. For example, Le and colleagues evaluated the efficacy of PD-1 blockade with anti-PD-1 antibody pembrolizumab in patients with dMMR advanced CRC and observed that the immune-related objective response rate and immune-related progression-free survival rate were higher for mismatch repair-deficient colorectal cancers compared to mismatch repair-proficient colorectal cancers (Le et al. 2015). Another trial studied the clinical benefit of using nivolumab, an anti-PD-1 molecule, and ipilimumab, an anti-CTLA4 monoclonal antibody, in combination in dMMR CRC patients. Scientists concluded that the aforementioned combination provided durable responses and clinical benefit for this category of patients (Overman et al. 2018). Moreover, in our institution, a study is ongoing for evaluating the impact of TME, PD-1/PD-L pathway activation, and MSI on CRC prognosis. Finally, in 2020, the US Food and Drug Administration (FDA) approved pembrolizumab as first-line treatment of patients with unresectable or metastatic MSI colorectal cancer. Therapeutic molecules studied in MSI tumor cohorts in combination with checkpoint inhibitors are agents blocking colony-stimulating factor 1 receptor CCR2 and CCR5 expressed by macrophages and myeloid-derived suppressor cells (MDSCs). These molecules are able to induce macrophage repolarization and anti-tumor immune response in M2 macrophages. Another strategy is to use alone or in combination complement component 5a receptor (C5aR) blocking agents that regulate inflammatory responses and cancer development.

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Concerning MSS tumors, beta-catenin or PAX4 inhibitors are under studies; this category of therapy could increase the immune infiltrate within the tumor and consequently the anti-tumor immune response (Fridman et al. 2020). Scientists are also exploring other possibilities like delivering T-cells directly to the tumor core using chemokines such as CXCL9 and CXCL10 and antibodies or infuse effector T-cells (Ganesh et al. 2019). The most recent studies are focusing on the development of innovative strategies such as oncolytic virus-based therapies, immunogenic chemo- and radiotherapies, or cell-based therapies, like T-lymphocytes with chimeric antigen receptors or autologous TILs (Fridman et al. 2020).

11

Conclusion

The complex role of tumor microenvironment in colorectal neoplasm has long been investigated. Most scientists agree that a brisk intra- and peritumoral immune cell response is a positive prognostic factor; on the contrary, a low inflammatory response is related to poor prognosis. Many studies investigated not only density but also composition of CRC immune infiltrates and related these data to prognostic indicators. Authors came to the conclusion that the influence of tumor microenvironment on patients’ prognosis is similar regardless of tumor cell types, except for FOXP3+ lymphocytes and M2 macrophages. Other works focused on the best method for immune cell assessment and compared semiquantitative methods based on H&E slides’ evaluation and immunohistochemical assessment. Also in this case, investigators obtained similar results regardless of the evaluation method used. In the past few years, research groups focused on comparing manual H&E or immunohistochemical assessment methods with digital pathology. The implementation of routine practice with digital image analysis software led to more precise immune infiltrate counts and also to spatial organization evaluation of every single part of TME. However, digital pathology has an economic cost, is time consuming, and requires a specific training, so more studies are needed to carefully evaluate the benefit-cost ratio of using new technologies in routine practice. Also the possible role of TME component in CRC therapy has been widely studied. Scientists focused mostly on immunotherapy, evaluating the benefit of immune checkpoint inhibitors, and antiangiogenetic factors. In conclusion, the literature available so far highlights how a dense and coordinated immune response is responsible for an effective anti-tumor activity of TME on neoplastic progression. It is not a single cell type determining this but the choral of the immune compartment. Nevertheless, there is a need for a standardized assessment method to incorporate in clinical practice to be place side by side with TNM staging in order to better stratify patients’ prognosis and implementing therapeutic strategies. Acknowledgments None. Compliance with Ethical Standards The authors declare that there is no conflict of interest.

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Unraveling the Esophageal Cancer Tumor Microenvironment: Insights and Novel Immunotherapeutic Strategies Inamu Rashid Khan, Faizyana Ali, Sheema Hashem, Alanoud Abdulla, Sabah Nisar, Tariq Masoodi, Ammira S. Al-Shabeeb Akil, Ajaz A. Bhat, and Muzafar A. Macha

Abstract

Esophageal cancer remains one of the most challenging cancers to treat, with a poor prognosis due to factors such as late detection, high mortality rate, and aggressive nature. This makes it a significant global health concern. The development of esophageal squamous cell carcinoma has been linked to genes like p53 and Rb, which regulate the cell cycle. Harmful mutations in these genes lead to uncontrolled cell division and cancer progression. The tumor microenvironment

Authors Inamu Rashid Khan and Faizyana Ali have contributed equally to this work. I. R. Khan Department of Zoology, School of Life Sciences, Central University of Kashmir, Ganderbal, Jammu & Kashmir, India F. Ali Department of Clinical Biochemistry, University of Kashmir, Hazratbal Srinagar, Jammu and Kashmir, India S. Hashem Department of Human Genetics, Sidra Medicine, Doha, Qatar A. Abdulla · A. S. Al-Shabeeb Akil · A. A. Bhat (✉) Department of Human Genetics-Precision Medicine in Diabetes, Obesity and Cancer Program, Sidra Medicine, Doha, Qatar e-mail: [email protected] S. Nisar St. Jude Children’s Research Hospital, Memphis, TN, USA T. Masoodi Human Immunology Department, Research Branch, Sidra Medicine, Doha, Qatar M. A. Macha (✉) Watson-Crick Centre for Molecular Medicine, Islamic University of Science and Technology, Kashmir, India e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2023_172 Published online: 2 August 2023

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of esophageal cancer contains various innate immune cells, including natural killer cells, tumor-associated macrophages, dendritic cells, myeloid-derived suppressor cells, neutrophils, and mast cells. These cells, along with other diverse cell populations within the tumor microenvironment, inhibit cell death, and promote blood vessel formation, invasion, and metastasis. Immunological checkpoints, secreted chemicals, and immune cells with negative effects all contribute to the ability of esophageal cancer cells to resist the immune system and suppress antitumor immunity. Understanding how the tumor microenvironment evolves in different esophageal cancer subtypes and recognizing the similarities and differences among tumor microenvironments in various cancer types are critical for developing targeted therapies in the future. Cancer immunotherapy represents a potentially new treatment approach for esophageal cancer. Recently, checkpoint inhibitors such as programmed cell death protein 1, programmed death-ligand 1, and cytotoxic T-lymphocyte-associated protein 4 have been proposed as strategies to enhance tumor cell destruction and restore T-cell activity in esophageal cancer specifically. To improve the effectiveness of immunotherapy and develop innovative methods for prognostic prediction or treatment, comprehensive knowledge of the immunological landscapes within esophageal cancer is essential. Keywords

Angiogenesis · Checkpoint inhibitors · Esophageal cancer · Immunotherapy · Innate immune cells · Prognostic prediction · Tumor microenvironment

Abbreviations APC BE CAFs CRT CTLA-4 DCs EAC EC ESCC GERD HGF MCs MDSCs NK cells ORR PD-1 PD-L1

Antigen-presenting cells Barret’s esophagus Cancer-associated fibroblasts Radiation therapy Cytotoxic T-lymphocyte-associated protein 4 Dendritic cells Esophageal adenocarcinoma Esophageal cancer Esophageal squamous cell carcinoma Gastroesophageal reflux disease Hepatocyte growth factor Mast cells Myeloid-derived suppressor cells Natural killer cells Objective response rates As programmed cell death protein 1 Programmed death-ligand 1

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TAMs TAPs Th17 cells TIM-3 TLRs TME

1

217

Tumor-associated macrophages Tumor-associated platelets T helper 17 cells T-cell immunoglobulin and mucin domain-3 Toll-like receptors Tumor microenvironment

Introduction

Esophageal cancer (EC) is the most lethal and aggressive among all gastrointestinal (GI) malignancies. With an annual incidence of 572,000 and 47,000 and 509,000 and 42,000 deaths, EC is the sixth and fourth most common cause of cancer-related deaths worldwide and in India, respectively (Bray et al. 2018; Siegel et al. 2018). Among many states of India, Kashmir has the third highest incidence of EC in the world (Khuroo et al. 1992; Mir and Dar 2009; Wani et al. 2014). Despite significant advances in surgery and chemotherapy (CT) (Carboplatin, Paclitaxel, 5FU, Cisplatin) or targeted therapy (TT) (anti-EGFR) based chemo-radiation therapy (CRT), EC is still characterized by poor prognosis and low survival rates (5-year survival is 15–20%) (Pennathur et al. 2013), primarily due to an advanced stage of cancer at the time of detection, loco-regional/distant metastasis and failure to the currently available CRT’s. This poor response includes inherited and acquired resistance to the CRT/TT treatment and associated severe toxicities resulting in significant co-morbidities (Rivelli et al. 2015). Differential response levels to chemotherapeutic drugs and other treatment regimens further exacerbate the problem. A complete understanding of the underlying pathology of EC might help us overcome the inadequate therapeutic response and help identify novel therapeutic strategies with minimal inherent or acquired resistance. Moreover, identifying prognostic and diagnostic biomarkers is necessary, including a panel of serum, surface, and genetic markers which can help both to identify the type and stage of cancer and provide a way to generate immune detection in immunotherapeutic systems (Huang and Fu 2019). Esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) are the two primary forms of EC, which vary in their origin and clinical characteristics. While the ESCC develops from the stratified squamous epithelial lining of the organ, EAC develops from the columnar glandular cells of the epithelium. ESCC is one of the most aggressive types of cancer, frequently showing lymph node metastasis and tumor invasion into adjacent organs, even in the early stages. With respect to location, the incidence rate of EC varies greatly. The incidence of EAC is increasing in Western countries. However, ESCC remains the significant type of cancer in many Asian countries, including India (80%) (Zhang et al. 2012). The major risk factors for the development of both ESCC and EAC includes the consumption of smoking, tobacco chewing (Brooks et al. 2009), alcohol

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consumption, diet low in zinc (Choi et al. 2018), achalasia for ESCC (Lambert and Hainaut 2007) or obesity, chronic gastroesophageal reflux disease (GERD) (Zhang et al. 2012; Mansour et al. 2017). In addition, epigenetic factors, inherent genetic predisposition, unique dietary habits, and obesity are the potential causes of EC. Barret’s esophagus (BE), a premalignant condition in which columnar intestinal cells take the place of the lower esophagus’s usual squamous epithelial lining (Spechler 2013; Sharma 2022), is regarded as a severe chronic GERD with longterm consequences (Jankowski et al. 1999). According to estimates, 2% of the general population is at risk for BE [14], whereas 10% of GERD patients are at risk of developing EC (Spechler 2013). While the incidence of BE is increasing among many countries, including the USA, approximately 0.12–0.5% of people with BE are estimated to develop EAC annually. Genes that oversee and regulate cell cycle proteins like p53 and Rb play a significant role in the emergence of EC (Niyaz et al. 2020; Zhu et al. 2020). Deleterious mutations render these genes ineffective and allow uncontrolled cell division and cancer development (Engeland 2022). Additionally, 76% of ESCC patients have elevated levels of the epidermal growth factor receptor (EGFR), which is usually accompanied by a dismal prognosis. In addition, 78.6% of ESCC patients have alterations or amplifications in pathways for a receptor tyrosine kinase (RAS) and protein kinase B (AKT) that are downstream of the EGFR (Huang and Yu 2018) (Fig. 1).

2

Immune System

The immune system comprises two primary parts, including the innate and adaptive immune systems. The innate immune system, which already exists in the body, serves as the initial line of protection and is activated when an antigen enters the body. The adaptive immune system is typically silent but combats microorganisms that escape or outperform innate immunity (Cianci et al. 2019). The innate immune system is made up of immune cells, including pathogen-clearing cells such as T cells, B cells, natural killer cells (NK cells), Langerhans cells, dendritic cells (DC), macrophages, platelets, mast cells (MCs), complement systems and cytokines that are quickly committed to an infection site during the inflammation. Antigenpresenting cells (APC) stimulate the adaptive immune system, including B and T cells with a large complex of antigen receptors, including toll-like receptors (TLRs) and major class II histocompatibility complex (MHC II) molecules involved in identifying pathogens and presenting antigens respectively. Antigens mounted on the APC cells bind specifically with the receptors on the B and T lymphocyte and promote their proliferation, maturation, and activation (Gaudino and Kumar 2019). Immunotherapies are the treatment of choice for both early and advanced cancers, including EC. While some tumor cells express immunological checkpoint proteins such as programmed death ligand-1 (PD-L1), lymphocytes express their ligands like programmed cell death protein 1 (PD-1) that prevent the destruction of the tumor cells by lymphocytes (Kelly 2019). Similarly, a transmembrane receptor cytotoxic

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Fig. 1 Schematic diagram of the EGFR signaling pathway. EGFR activation occurs when a ligand such as EGF binds to EGFR and causes receptor dimerization. The receptor dimerization leads to the auto-phosphorylation of growth factor proteins such as GRB2 and PLCγ, tyrosine kinase JAK, and proto-oncogene Src and adaptor protein SHC, which results in the activation of downstream cell survival pathways such as RAS-RAF-MEK-ERK, JAK/STAT, PI3K/mTOR and NF-kB pathways Abbreviations: EGFR: epidermal growth factor receptor; PLCγ: phospholipase C gamma; JAK: Janus kinase; Src: Src homology 2 domain-containing

T lymphocyte-associated protein 4 (CTLA-4) on T cells suppress their activation by its ligands (CD80 or CD86) present on the tumor cells (Bhat et al. 2021a, b). Checkpoint inhibitor therapy, a kind of cancer immunotherapy, targets important immune system regulators that cancer cells employ to defend themselves from immune attack. Recently, intriguing alternatives for the targeted treatment have been proposed, including checkpoint inhibitors that target PD-1, PD-L1, or CTLA4 (Fig. 2) (Wang et al. 2022).

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Fig. 2 Immune checkpoint therapy in EC. T-cells recognize tumor-specific antigens present on the surface of antigen-presenting cells or tumor cells through the TCR. The binding of PD-1 checkpoint protein present on the T cells with the ligand PD-L1 on the tumor cells inactivates the T-cell function resulting in the inhibition of tumor cell killing. CTLA-4 is a receptor on T cells that binds to CD80/86 on antigen-presenting cells and downregulates the immune system. Monoclonal antibodies such as -anti-PD-L1 drugs (Pembrolizumab and Nivolumab) and anti-CTLA4 drugs (Tremelimumab and Ipilimumab) that function as immune checkpoint inhibitors can be used to restore the immune response against EC Abbreviations: EC esophageal cancer, TCR T-cell receptor, PD-1 programmed-cell death protein 1, PD-L1 programmed-death ligand 1, CTLA4 cytotoxic T lymphocyte-associated protein 4, MHC major histocompatibility complex

3

Immune System-Mediated Esophageal Cancer Initiation Progression

For decades, identifying and characterizing epigenetic alterations in tumor cells was the main focus of cancer initiation and development. However, these research findings did not translate well from bench to bedside. Recent studies have conclusively established the importance of tumor microenvironment (TME), particularly the presence of immune cells in the initiation and progression of cancers, including EC (Diao 2020). Immune cells, including NK cells, tumor-associated macrophages (TAMs), regulatory T cells (T-regs), DCs, MCs, myeloid-derived suppressor cells (MDSCs), neutrophils, tumor associated-platelets (TAPs) and associated cytokines and chemokines are present in the EC TME (Cui et al. 2021). Along with these

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immune cells, a variety of other stromal cells including cancer-associated fibroblasts (CAFs), neuroendocrine cells, endothelial cells, adipocytes, blood lymphatic vascular cells, and pericytes contribute to immune escape, increasing angiogenesis, invasion & metastasis, therapeutic resistance and therefore promote aggressive tumor behavior (Bhat et al. 2021a, b; Cui et al. 2021). During the early stages of tumor formation, the presence of neo-antigens and tumor-associated antigens trigger DC-mediated activation of cytotoxic T lymphocytes, immunological checkpoints, and tumor cell-released substances negatively regulate immune cells and decrease antitumor immunity. The following are distinct cell types and risk factors linked to the development of EC.

3.1

Myeloid-Derived Suppressor Cells

MDSCs are immune cells in the TME that negatively modulate immunological reactions during inflammation and cancer. Monocytic MDSCs (M-MDSCs) and polymorphonuclear MDSCs (PMN-MDSCs) are the two primary subpopulations of MDSCs. The growth of MDSCs in the TME is induced by tumor-derived substances such as granulocyte-macrophage colony-stimulating factor (GM-CSF) and granulocyte colony-stimulating factor (G-CSF) (reviewed in Bhat et al. 2021a, b). Inflammation, specifically pro-inflammatory chemicals like IL-1, IL-6, and prostaglandin E2, as well as other tumor-secreted substances, including vascular endothelial growth factor (VEGF) stimulate and increase MDSCs. Many studies have shown that cancer patients with higher MDSCs have a worse prognosis than those with low numbers. Furthermore, elevated MDSC levels have been found in EC patients and are linked to advanced disease. These MDSCs suppress antitumor immunity by several mechanisms, including direct inhibition of NK cell cytotoxicity, inhibition of T-cell activation, promoting tumor cell growth, invasion & metastasis, and therapeutic resistance (reviewed in Bhat et al. 2021a, b). In addition, by activating T-regs, MDSCs promote immunological suppression and impair T cellmediated tumor clearance (reviewed in Bhat et al. 2021a, b). The majority of the enzymatic activity necessary for MDSCs to inhibit T-cell proliferation and activation is provided by arginase-1 and inducible nitric oxide synthase-2 (iNOS). While arginine is converted into urea and L-ornithine, arginase-1 depletes arginine from T cells, lowering the expression of the CD3ζ chain and impairing T cells’ ability to respond to activating signals (Rodriguez et al. 2003). Recent research has demonstrated that M-MDSCs produced by extracellular vesicles generated from melanoma might predict immunotherapy resistance (Zhao et al. 2021). Similarly, M-MDSCs and PMN-MDSCs also showcase various strategies for controlling the development of tumors. Even though PMN-MDSCs are more common in tumors, M-MDSCs exhibit more potent suppressive properties (Marvel and Gabrilovich 2015).

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Regulatory T Cells

Regulatory T cells (Tregs) are a very small subpopulation of T cells that suppress the exaggerated immunological response to maintain homeostasis and self-tolerance (Kondĕlková et al. 2010). In healthy physiology, Tregs are also known to regulate CD4+ and CD8+ T cells, macrophages, B cells, NK cells, and DCs. However, they also suppress antitumor immune response as well. Tregs play a major role during tumorigenesis by suppressing inflammation and attenuating antitumor immunity by releasing immunosuppressive cytokines, interfering with the presentation of tumorassociated antigens, cytotoxic cell activity, and granule release inhibition (Vignali et al. 2008; Labani-Motlagh et al. 2020). However, the depletion of Tregs promotes tumor antigen-specific immunity and rejection of endogenous immune-mediated malignancies, highlighting the importance of Treg cells for antitumor immunity (Fietta et al. 2009). Therefore, modulation of Tregs represents a novel cancer therapeutic opportunity. CCL17 and CCL22 produced by tumor cells & macrophages activate C-C chemokine receptor 4 (CCR4) and attract Tregs recruitment to the EC microenvironment. While the Treg infiltration is associated with deeper tumor invasion, metastasis, overall disease severity, and shorter postchemotherapy survival, immunotherapy and CTLA4 inhibition were more effective in Treg-depleted patients than non-depleted patients (Fietta et al. 2009). Among the many suppression functions of Tregs, those essential for preserving self-tolerance (i.e., the systems whose deficiency results in autoimmune illness) greatly affect tumor immunity. Surprisingly, the Foxp3 transcription factor regulates a few downstream molecules, including IL-2 receptor subunits (CD122, CD25) and CTLA-4, and their absence abolishes Treg-suppressive action but promotes autoimmune disorders (Sakaguchi et al. 2008). In addition, Foxp3 interacts with transcription factors (NFAT and AML1) and inhibits IL-2 synthesis (Ono et al. 2007), thereby making Tregs dependent on activated conventional T cells (Tconv) for IL-2 (Fig. 3).

3.3

T Helper 17 Cells

T helper 17 (Th17) cells, a small subpopulation of pro-inflammatory T-helper cells, are known to regulate immunomodulation with both anti-cancer and pro-tumorigenic properties. Upon stimulation by transforming growth factor-β (TGF-β) and IL-6, Th17 cells limit the proliferation of CD8+ T cells by expressing ectonucleotidases CD39 and CD73 (Zhang 2018). Through the secretion of cytokines, including IL-17 and IL-22 via STAT3 pathway activation, these Th17 cells promote angiogenesis and accelerate cancer growth (Tesmer et al. 2008). Based on the composition of TNF-, IL-1, IL-6, IL-21, TGF, and IL-23 in the TME (Nam et al. 2008), Th17 cells have been shown to transform into either Tregs or Th1 cells performing a range of contrasting tasks. While both the Tregs and Th17 (CD4+ T cell subtypes) actively contribute to the growth and spread of lung cancers (Marshall et al. 2016), Th17 cells, in part, function as an independent predictor for EC lymph node metastasis and poor patient prognosis (Chen et al. 2012). In addition

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Fig. 3 Cancer evasion of immune surveillance via TME-mediated cytokines/chemokines. Several chemokines and cytokines secreted by cancer cells block the actions of NK cells, DCs and T cells and attract TAMs. Additionally, MDSCs and Treg T cells are produced by tumour cells, which can further limit T cell activity. PD-L1/2 is expressed by TAMs and tumour cells to prevent T-cell activation by the PD-1 receptor. Collectively, these cells promote tumour development and proliferation while suppressing antitumor immunity by various mechanisms

to TME, increased Th17 cells have been reported in the peripheral blood of both EAC and ESCC patients and are associated with the tumor stage (Huang and Fu 2019).

3.4

Tumor-Associated Macrophages

Macrophages involved in innate and adaptive immune responses are crucial cells for tissue homeostasis and protect the body against invading pathogens. Based on the presence of interferons in the microenvironment, macrophages are polarized to either pro-inflammatory M1 or anti-inflammatory M2 phenotype. M1 macrophages by secreting chemokines/cytokines (IL-12, IL-23, TNF-/CCL-5, CXCL9, CXCL10, and CXCL5) activate Th1 cells and suppress cancer cell proliferation and inhibit survival (Atri et al. 2018). M2 macrophages, on the other hand, release cytokines including IL-1 receptor antagonist (IL-1ra), IL-10 & TGF-β and are crucial for tissue remodeling, wound healing, angiogenesis, and the development of tumors (Krzyszczyk et al. 2018). In addition, M2 macrophages closely resemble TAMs, are extremely flexible, and adopt a variety of activation states between M1 and M2. They are necessary for the breakdown of the extracellular matrix (ECM), remodeling of the TME and motility of tumor cells, and the induction of angiogenesis. They exhibit markers that are unique to both M1 (IFN-γ, TNFα, MMP-9, CCL2, CCL5,

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CXCL9, CXCL10, CXCL16, IL-12, & IL-23) and M2 (IL-10, TGF-β, arginase-1, PPARγ) (Lin et al. 2019). Specifically to ECs, increased expression of tumor-derived macrophage chemo-attractant protein-1 (MCP1) has been associated with generating angiogenic enzymes such as thymidine phosphorylase, dismal prognosis, and ineffective treatment in ESCC patients (Shimada et al. 2002).

3.5

Cancer-Associated Fibroblasts

CAFs, characterized by the overexpression of fibroblast activation protein-α (FAPα) and α-smooth muscle actin (αSMA), is a subpopulation of fibroblasts that is prevalent in the TME of many solid tumors, including ECs. These CAFs are a diverse population of cells that are believed to be originated either from cancer cells, reprogrammed tissue-resident fibroblast, fibrocytes, mesenchymal stem cells from the bone marrow, epithelial & endothelial cells via epithelial to mesenchymal transition (EMT) (Xing et al. 2010). This phenotype is hypothesized to be produced by cancer-cell-secreted factors such as TGF. In addition, microRNAs secreted by the cancer cells have been shown to transform fibroblasts into CAFs (Savardashtaki et al. 2019). Many malignancies, including EC, are caused by chronic inflammation and injury called non-healing wounds. Fibroblasts and other cells that typically respond to injury are crucial to the development, progression, and eventual dissemination of malignancies via interaction with tumor and other stromal cells through secreted factors that activate pro-inflammatory pathways, impairing immune surveillance and altering the ECM (Lin et al. 2016). Using a 3D organotypic cell culture model, it has been shown that the hepatocyte growth factor (HGF) produced by activated fibroblasts facilitates invasion by EC cells and promotes resistance to cisplatin and 5-fluorouracil (Sakaguchi et al. 2008). Using in vivo mouse models, it has been demonstrated that the development of EC was associated with the invasion of MDSCs and activated fibroblasts resulting in a strong desmoplastic response in the tumor stroma (Bhat et al. 2021a, b). A similar increase in tumor cell proliferation, angiogenesis, and motility of cancer cells was observed by CAFs using in vitro models. Furthermore, irradiation induced p120-catenin and HGF upregulated by fibroblasts co-cultured with ESCC cells, reflecting a phenotype that is more intrusive (Baba et al. 2020).

4

Targeted Immunotherapy in EC

Immunotherapy is a biological therapy that enhances the body’s defense mechanisms using substances made by the body or in the lab to enhance, target, or restore immune system function. Immunotherapy is a therapeutic procedure that improves or restores the ability of the immune system to detect and eradicate tumor cells by altering or preventing co-stimulatory cues. Co-stimulatory signals such as PD-1, cytotoxic T lymphocyte-associated antigen 4 (CTLA4), lymphocyte activation gene 3 (LAG-3) & T-cell immunoglobulin, and mucin domain-3 (TIM-3) fine-tunes the

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immune cell function to identify and target only external antigens while recognizing self-produced antigens as non-threats (Shi et al. 2018). However, cancer cells expressing immune checkpoints inhibitors like PD-1 and CTLA4 alter co-stimulatory signals and elude or impede immune monitoring, resulting in tumor growth and development. Therefore, efforts are focused on developing immunotherapeutic interventions to enhance antitumor immune response safely and effectively (Blattman and Greenberg 2004). PD-1 functions as an inhibitory signaling receptor on the surface of T lymphocytes. Programmed cell death-ligand1 (PD-L1) is one of the ligands which cancer cells commonly overexpress to inhibit function and stimulation of lymphocytes, inhibiting T-cell-mediated eradication (Sharpe and Pauken 2018). Recent research has revealed that checkpoint inhibition, which targets PD-1 or PDL-1, is a successful therapy for several tumors, including melanoma, lymphoma, lung cancer, head and neck cancer, and others that express high levels of PD-L-1 or PD-1 overexpression in T cells (Chen et al. 2020). PD-L1 inhibitors are therefore recognized as efficient, targeted therapies for preventing T-cell cancer evasion. An anti-PD-1 antibody “pembrolizumab (Nivolumab)” binds with the PD-L1 on tumor cells to stop it from interacting to the PD-1 on T cells and stopping T cell inhibition, allowing T cells to kill cancer cells (Han et al. 2020). In a phase II KEYNOTE-180 clinical trial, EC patients who received pembrolizumab experienced overall remission rates of only 10%, with median overall survival times (mOS) of 5.8 months and objective response rates (ORR) of 14.3% (Vivaldi et al. 2020). A similar study using pembrolizumab observed ORR of 13.8% and 6.3% in EC patients with PD-L1 expression compared to PD-L1 negative patients, respectively (Shah et al. 2019). Though the side effects of pembrolizumab including nausea, vomiting, and hypertension have not been thoroughly studied; however, these clinical studies result in the FDA approval of pembrolizumab as a second-line therapy option for PD-L1 positive EC patients. Another anti-PD-L1 antibody Nivolumab has been approved by the FDA as a secondary treatment for EC patients with advanced disease (Barsouk et al. 2019). A homolog of the CD28 protein, CTLA4 is a transmembrane protein that is only expressed on activated T cells. It is a suppressor of IL-2 expression and an antagonistic regulator of T cells (preventing the entry into the G1 phase of the cell cycle) and thus allowing the cancer cells to escape the immune attack. CTLA4 has been shown in certain studies to be an immune-based target for cancer treatment (Leach et al. 1996). While many CTLA4-targeting antibodies, such as Ipilimumab and Tremelimumab, are currently being used against various tumors, no clinical evidence of their effectiveness for EC patients is currently available (Zhao et al. 2018). More recently, a fully humanized monoclonal antibody “Tremelimumab” has also been investigated as a secondary therapy for metastatic melanoma (Comin-Anduix et al. 2016). Another immunological checkpoint is the TIM-3 which significantly inhibits CD4+ T helper cells and CD8+ cytotoxic T lymphocytes (Balajam et al. 2020). Recently Zhao et al. analyzed the expression of TIM-3 and PD-1 on CD8+ TILs in EC patient samples and observed that patients with high expression of PD-1 and high density of CD8+ TILs have worse relapse-free survival (RFS) and OS

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(Zhao et al. 2020). Despite this, no drug is currently in use targeting TIM-3 in EC patients (Alsina et al. 2018). Another crucial immune checkpoint protein, LAG-3, is expressed by TILs, NK, and B cells. Similar to TIM3, no therapies targeting LAG-3 are currently ongoing in EC patients. While many vaccines effectively activate cytotoxic T cells and target cancer-specific antigens, however such studies on EC patients have shown mixed results attributed to the distinct molecular features of EAC and ESCC subtypes (To et al. 2022). Therefore, future clinical studies should be designed considering the potential variability among different tumors and their subtypes. In addition, personalized cancer immunotherapy called adoptive T-cell transfer uses the patient’s own autologous immune cells that have been altered and amplified ex vivo. The use of adoptive T-cell therapy has increased survival in EC (Gu et al. 2021). Despite these improvements, immunotherapy is associated with immune-related adverse events (irAEs) such as cutaneous, gastrointestinal, endocrine, and liver toxicity. While many biomarkers can predict immunotherapy prognosis, the low efficacy of these biomarkers warrants new biomarkers predicting immunotherapy response. An overview of therapeutic targets, clinical trials, and key parameters in EC immunotherapy is shown in Table 1.

5

Conclusion and Future Directions

In the Western world, including the United States, EAC stands as the predominant subtype of esophageal cancer EC. Despite remarkable advancements in multimodal treatment modalities, the prognosis for EC patients remains disheartening, with the average survival time falling short of a year. Consequently, there is an imperative demand for innovative therapeutic approaches for advanced EAC and ESCC, emphasizing targeted therapies that deliver exceptional efficacy and minimal adverse effects. The genesis of ESCC has been associated with genes such as p53 and retinoblastoma (Rb), wherein deleterious mutations render these tumor suppressor genes ineffective, thereby fostering cancer development. The esophageal cancer TME encompasses various immune cells, including NK cells, TAMs, T-regs, DCs, MCs, MDSCs, neutrophils, TAPs, and a myriad of cytokines and chemokines that play a vital role in cancer progression. A multitude of clinical trials are currently underway to scrutinize the potential benefits of conjoining cytotoxic and targeted therapies for EC patients. Concurrently, researchers are delving into next-generation treatment strategies, encompassing peptide vaccines, adoptive T-cell therapy, oncolytic viruses, and the amalgamation of immune-chemotherapy with radiation therapy. Nonetheless, given the low response rates and the significant clinical and financial risks associated with immunotherapy, a meticulous patient selection process is imperative to optimize treatment outcomes and reduce unnecessary burden on patients. In light of the pivotal role played by the TME in cancer development and progression, it is of paramount importance to gain a comprehensive understanding of the similarities and disparities among the TMEs in the various EC subtypes. This

PD-L1 CTLA4 IDO1 OX40

VISTA

TGF-β

CD40

LAG-3 TIGIT

2 3

6

7

8

9 10

4 5

Target PD-1

No. 1

ABBV-428 (anti-CD40 antibody) Relatlimab Tiragolumab

Indoximod MEDI0562 (anti-OX40 antibody) CA-170 (VISTA antagonist) Galunisertib

Therapeutic strategy Nivolumab (pembrolizumab) Durvalumab Ipilimumab

NCT01968109 NCT03417037

NCT02955251

NCT02581787

NCT02812875

NCT03301597 NCT02221960

NCT03040986 NCT01938612

Clinical trial identifier NCT02743494

I/II I

I

I

I/II

II I

II I/II

Phase II

Completed Completed

Completed

Completed

Completed

Completed

Completed Completed

Status Completed

ESCC, EAC ESCC, EAC

ESCC, EAC

ESCC

ESCC, EAC

EAC ESCC, EAC

ESCC, EAC ESCC, EAC

Patient population ESCC

Safety and tolerability Safety and tolerability ORR Safety and tolerability

PFS Safety and tolerability PFS Safety and tolerability ORR

Primary outcome measures OS

Table 1 Overview of therapeutic targets, clinical trials, and key parameters in esophageal cancer immunotherapy

Vonderheide et al. (2010) Ascierto et al. (2017) Rodriguez-Abreu et al. (2020)

Papadopoulos et al. (2017) Melisi et al. (2016)

Soliman et al. (2014) Curti et al. (2013)

Kelly et al. (2020) Reck et al. (2013)

References Kudo et al. (2017)

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invaluable insight will shed light on the heterogeneous signaling outcomes, patient diversity, and differential responses to treatment, thereby paving the way for tailored therapeutic strategies that cater to individual patient needs and enhance survival rates in this devastating malignancy. Ethics Approval and Consent to Participate Not applicable. Consent for Publication All authors consent to publication. Availability of Data Not applicable. Competing Interests The authors declare no competing interests. Funding This study was supported by the Ramalingaswami Fellowship (Grant number: DO NO. BT/HRD/35/02/2006) from the Department of Biotechnology, & Core Research Grant (CRG/2021/003805) from the Science and Engineering Research Board (SERB), Govt. of India, New Delhi, Promotion of University Research and Scientific Excellence (PURSE) grant from the Department of Biotechnology, Govt. of India, New Delhi, to the Islamic University of Science and Technology (IUST), Awantipora to Dr. Macha, and Sidra Medicine Precision Program funding to Ajaz A. Bhat (SDR400105).

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The Interplay Between Immunity and Gut Microbiota in Colon Cancer Lara Malaspina, Federica Petrelli, Bruno Perotti, Marco Arganini, and Maria Raffaella Ambrosio

Abstract

Despite the introduction of valid screening programs and advances in therapies, colorectal cancer (CRC) still remains one of the leading causes of death with an increasing incidence in younger patients. The association of this tumor with external modifiable factors such as life habits and diet is well known. In recent years, growing attention has been focused on the intestinal microbiota, the complex ecosystem made up of bacteria, viruses, and fungi, which plays a crucial role in CRC tumorigenesis as well as in response to therapy. There are a lot of mechanisms underlying the interplay between CRC and microbiota and their identification is crucial to exploit the microbiota in every phase, from prevention to early identification of disease, as a new therapeutic target and finally as a biomarker of response to conventional therapy. In the following paragraphs, we will elucidate the role of intestinal microbiota and immune system in CRC carcinogenesis as well as their interplay. Moreover, we will address the potential role of gut microbiota in CRC screening, diagnosis, and therapy. Keywords

Carcinogenesis · Colon cancer · Dysbiosis · Gut microbiota

1

Introduction

CRC is one of the most common cancers ranking third in terms of incidence, much higher in developed countries rather than in developing ones and accounting for 1.9 million new cases in 2020 (Morgan et al. 2023). With its continued L. Malaspina · F. Petrelli · B. Perotti · M. Arganini · M. R. Ambrosio (✉) Azienda Sanitaria Toscana Nord Ovest, Pisa, Italy e-mail: [email protected]; [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2023_179 Published online: 30 August 2023

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progression in Western countries, the incidence of CRC is predicted to increase to 2.2 million new cases and 1.1 million deaths in the next decade (Arnold et al. 2017). The introduction of effective colonoscopy screening resulted in a shift to earlier stage diagnosis (Siegel et al. 2022) and a subsequent decrease in mortality. If this is true for people over 65 years, in the last decades, incidence increased in young adults for whom the screening is not recommended. This trend, along with the continued burden in the overall population, is alarming. Therefore, new screening strategies for early detection and proper treatment are urgently needed (Song et al. 2020) along with the implementation of known preventive measures. Most CRCs are sporadic or non-inherited and well-known and modifiable environmental factors, such as diet and lifestyle (smoking, metabolic syndrome, consumption of red and processed meat; low consumption of fruits/vegetables, physical inactivity, and heavy alcohol consumption) account for over 50% of sporadic CRC (Song et al. 2020). Among them, the intestinal microbiota was recognized as an important contributor and despite the long-standing association between CRC, diet, and microbiome, which dates back to the 60 s (Aries et al. 1969), its role in CRC initiation, progression, and metastasis was only recently investigated (Cheng et al. 2020; Drewes et al. 2016).

2

Gut Microbiota

Gut microbiota is a complex ecosystem derived from a process of host- microbes coevolution that lasts for thousands of years and depends both on the host and on their physiological environment (Sung et al. 2017). Human gut microbiota is composed of an outstanding number (1013 to 1014) of archaea, bacteria, eukaryotes, viruses, and microbes dominated by four main phyla: Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria (Gaines et al. 2018). Their gene pool forms the so-called “microbiome”, exceeding the human genome by 150 times (Cheng et al. 2020). It is usually divided into two main groups: the “core human microbiome” and the “variable human microbiome” the former comprises a large proportion (38%) shared interindividually, the latter indicates microbial genes belonging to a specific cohort of people. They are due to specific host characteristics depending also on environmental changes and socio-cultural influences (Turnbaugh et al. 2007) occurring after birth. Early, microorganisms colonize all the surfaces of the human body exposed to external agents, reaching a stabilization within the first year of life (Sung et al. 2017). The lower tract of the gastrointestinal system harbors the greatest density and diversity of microorganisms (Lee et al. 2021) and recent evidence revealed that these communities and their collective genomes are not just passive bystanders but actively maintain the physiology and health of the host by influencing basic functions, such as metabolism, nutrition, tissue development, inflammation and immunomodulation, and pathogen resistance regardless of health or disease status (Ge et al. 2021), Mammals and their commensal microbes are normally symbiotic, and the immune system has established various tolerance mechanisms. Specifically,

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in the intestine, the gut microbiota is able to maintain epithelial homeostasis to support gut-associated lymphoid tissue (GALT) and it enhances epithelial cytokine production which regulates the action of T and B lymphocytes, macrophages, and eosinophils. Although the majority of host-microbiota interactions are symbiotic and beneficial, in specific conditions, the equilibrium of the microbiota-immunity axis breaks being responsible for several pathologies. (Lee and Mazmanian 2010; Cheng et al. 2020). Dysbiosis is defined as an alteration of the considered normal proportion of different specimens composing the microbiota (Bartolini et al. 2020). It can be caused by a variety of factors such as particular diseases (autoimmune and chronic diseases) but also by metabolic conditions (overweight, obesity), drugs, activation of inflammatory signaling, dietary intake changes, infection, and lack of nucleotidebinding oligomerization domain 2 (NOD2) (Ge et al. 2021; Song et al. 2020). Alterations in the microbiome structure and function have been recently and largely associated with host disease pathogenesis since they affect metabolic and immune pathways, mediating CRC carcinogenesis (Song et al. 2020). The growing body of evidence showing the association between dysbiosis, immune system, and CRC development in a tripartite relationship (Sears and Pardoll 2011) brought to the formulation of three different dysbiosis-related oncogenic models. According to the “alfa-bugs” model, some specifical species (e.g., enterotoxigenic Bacteroides fragilis-ETBF, S. bovis, E. coli, superoxide-producing E. faecalis) are able to grow out of protective microbial species remodeling the composition of the microbiota and, at the same time, to act against the immune system with both a direct and indirect pro-oncogenic effect. Notably, true oncomicrobes in the intestine account for a very small proportion of all microbial population but still, alterations of the balance between good and bad microbes seem to promote tumor development (Sears and Pardoll 2011). The “bacterial driver-passenger” model suggests that some “driver bacteria“ have the ability to promote cancer development through genetic instability, producing DNA-damaging compounds and inflammatory cytokines. In a second phase, they would be outcompeted by “passenger bacteria”, such as Fusobacterium spp., bacteria which are usually poor colonizers of healthy intestines but have a competitive advantage in tumoral microenvironment and exert cancer-promoting activities. All these result in different compositions of the microbiota during CRC initiation and development, so that pathogens responsible for tumor initiation may be absent in the following stages (Tjalsma et al. 2012). In the “keystone pathogen” model, some poorly represented pathogens have the ability to remodel the microbiota either through direct or indirect effects on it, respectively altering the transcriptional profile of the microbiome and affecting host modulation (e.g., impaired immunosurveillance) or both, causing disruption of host homeostasis. Great effort was put into identifying a universal CRC-associated microbiota that is yet to be determined. Fusobacterium nucleatum, Escherichia coli, and Bacteroides fragilis

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seem to be involved in CRC while the role of depleted strains is less well understood; however, they are thought to play a key role in tumor-associated bacterial overgrowth and subsequent CRC development (Cheng et al. 2020).

2.1

Microbiota-Associated Mechanisms of Carcinogenesis

It has been extensively shown that gut microbiota has a major role in cancer initiation but also in its regulation, progression, and susceptibility to host immune response and therapy (Ge et al. 2021). Thus, gut microbiota and microbiome become targets in the search for biomarkers for diagnosis and treatment purposes, opening new horizons in terms of screening and therapeutic approaches. An intact microbiota is necessary for optimal treatment response (Ge et al. 2021) and the exact composition of the altered cancer-associated microbiota is hard to encode, mainly because of major individual variation representing a challenge in medical practice. In this setting, understanding mechanisms underlying microbiota-mediated carcinogenesis is fundamental to identify novel approaches to the disease. Microbiota-associated mechanisms in CRC carcinogenesis include: • Inflammation; Chronic inflammation is a well-established risk factor for CRC. It seems that inflammation-associated mediators such as interleukin-6 (IL-6), tumor necrosis factor-α (TNF- α), IL-23, and reactive oxygen species form a microenvironment favoring carcinogenesis through DNA damage, thus altering the physiology of the host, a mechanism that could explain colitis-associated CRC (Arthur et al. 2012). In this setting, microbiota is both a target and a cause of inflammatory processes promoting cancer and impacting on its progression. Normally, the intestinal mucosal barrier segregates the intestinal microbiota from immune cells but continuous bacterial stimulation can cause a perpetual state of low inflammation (Cheng et al. 2020) with a double effect. Microbiota is targeted by inflammatory cells and their mediators with the result of fostering the expansion of bacteria with genotoxic potential and creating the opportunity for this microorganism to adhere to the colonic mucosa by decreasing protective mucins and antimicrobial peptide production (Arthur et al. 2012). Conversely, inflammation cannot induce CRC without the microbiota or bacteriaderived compounds and toxins which allow barrier disruption and enable commensal bacteria and their degradation products to invade the tumor stroma. Some examples of these bacterial toxins strongly associated with carcinogenesis and tumor progression are those produced by Escherichia coli or Bacteroides fragilis (Cheng et al. 2020).

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Gut microbiome dysbiosis promotes inflammation via induction of the cytokine CCL5 (C-C chemokine ligand 5) (Elinav et al. 2011), recruiting lymphocytes in the intestine up to non-physiological levels (Ge et al. 2021). CCL-5-driven inflammation, in turn, promotes epithelial cell proliferation through local activation of the IL-6 pathway, leading to cancer formation (Hu et al. 2013). F. nucleatum, enriched in samples collected from colonic human adenomas and carcinoma, was studied in ApcMin/+ mice models and it was found able to ingenerate a pro-inflammatory environment suitable for neoplastic progression by activating the NF-kB pathway and recruiting tumor-infiltrating immune cells (Kostic et al. 2013). Moreover, F. nucleatum-associated inflammatory cytokines in colorectal cancer specimens were assessed using immunoassays: expression of the cytokines IL17A and TNFα was markedly increased (Ye et al. 2017). A similar mechanism is exploited by P. anaerobius inducing a pro-inflammatory immune microenvironment by recruiting a series of tumor-infiltrating immune cells, especially immunosuppressive myeloid-derived suppressor cells, tumor-associated macrophages, and granulocytic tumor-associated neutrophils, to promote tumor progression (Cheng et al. 2020; Long et al. 2019). • Immune dysregulation: The gut microbiome can inhibit infection by intestinal pathogens by adjusting the environment in the niche they occupied, competing for nutrients, and releasing bacteriocins, in a highly dynamic dialogue with the host, THUS contributing to protection against pathogens in and outside the gut (Schnupf et al. 2018). This process starts during the constitution of the microbiome at birth, affecting the maturation of the immune system, the development of tolerance, and the containment of the microbiome (Honda and Littman 2016; Ge et al. 2021). In the intestinal mucosa, the microflora affects the phenotype and function of T and B cells, playing a key role in maintaining immune homeostasis by inhibiting the response to harmless antigens and preserving the integrity of the intestinal mucosal barrier function (Honda and Littman 2016). Indeed, the host intestinal mucosal surface barrier allows microbial symbiosis, and resident bacteria profoundly shape mammalian immunity (Hooper et al. 2012). Microbiota is subject to continuous modification to repair environmental damage with the aim of maintaining homeostasis. Disruption of such a fragile balance results in a confrontation between the microorganisms and the immune system, which may result in proinflammatory or tumorigenic conditions (Ge et al. 2021). Host recognition pathways of the microbiota exploit various pattern recognition receptors (PRRs) such as Toll-like receptors (TLRs), modulating inflammatory response to microorganism molecular patterns. TLRs engagement on tumorinfiltrating myeloid cells caused by invading bacterial components is mediated by myeloid differentiation factor 88 (MyD88)-mediated production of inflammatory cytokines, most notably interleukin (IL)-23. It subsequently determines a cytokine activation cascade comprising IL-17A, IL-6, and IL-22, eventually promoting tumor

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cell proliferation by activating nuclear factor-kB (NF-kB) and STAT3 signaling pathways. Moreover, the collateral upregulation of IL-17C can transform IEC through TLR/MyD88-dependent signaling, and promote tumor cell survival and tumorigenesis (Cheng et al. 2020). • Pathogenic bacteria and their virulence factors F. nucleatum, an oral commensal bacterium, acts at the early step of colorectal carcinogenesis affecting the b-catenin signaling pathway thus inducing oncogenic and inflammatory responses. To do so, F. nucleatum uses its unique FadA adhesin A (FadA), which selectively binds to E-cadherin thus inducing oncogenic and inflammatory responses via activated b-catenin signal. FadA gene levels in patients with adenomas and adenocarcinomas are >10–100 times higher compared to healthy individuals (Rubinstein et al. 2013). Additionally, F. nucleatum inhibits T-cell activation and natural killer cell cytotoxicity through another surface adhesin, Fap2, which binds to the human immune inhibitory receptor T-cell immunoglobulin and ITIM domain (Gur et al. 2015). Fap2-dependent invasion-induced secretion of the proinflammatory cytokines, IL-8, and CXCL1, associated with CRC progression, increased metastatic potential and cell seeding, poor prognosis, and enhanced recruitment of tumor-associated macrophages and fibroblasts (Casasanta et al. 2020). F. nucleatum also modulates autophagy in IECs by activating regulatory microRNAs (Yu et al. 2017). P. anaerobius which normally resides in the oral cavity and gut, selectively enriched in the fecal and mucosal microbiota from patients with CRC, promotes cancer development via its surface protein, putative cell wall binding repeats 2 (PCWBR2). PCWBR2 directly interacts with intestinal epithelial cell receptor integrin α2/β1, frequently overexpressed in human CRC tumors and cell lines to initiate an oncogenic PI3K-Akt signaling pathway, promoting tumor cell proliferation (Long et al. 2019). S. bovis, occasionally presents in the human gastrointestinal tract flora, was remarkably associated with CRC development through inflammation-driven carcinogenesis via, but not limited to, IL-1, cyclooxygenase-2 (COX-2), and IL-8 (Abdulamir et al. 2010). Finally, chronic Salmonella infection increases the risk of cancer since it promotes colonic tumorigenesis by its protein AvrA, which can activate both the Wnt/b-catenin and STAT3 signaling pathways in colonic tumor cells (Wang et al. 2018; Lu et al. 2014). • Genotoxins Genotoxins are toxins capable of causing damage to the DNA leading to mutations and eventually to cancer. Thus, bacteria producing this kind of substance participate in colonic carcinogenesis. Some strains of E. coli, usually commensal inhabitants of the mammalian colon, harbor the genomic island, polyketide synthase (pks), coding for production of the

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polyketide-peptide genotoxin, colibactin. In different laboratory models, this toxin was related to DNA damage and promotion of cell senescence and enhanced tumor cell proliferation (Cuevas-Ramos et al. 2010; Cougnoux et al. 2014). Campylobacter jejuni produces a cytolethal distending toxin, which causes double-stranded DNA breaks and promotes colorectal tumorigenesis (Lasry et al. 2016). Salmonella exploits the PI3K pathway in colonic epithelial cells to damage the DNA using a typhoid toxin (Martin et al. 2019). • Oxidative stress Oxidative stress originates from the breakdown of the balance between pro-oxidative molecules [(e.g., reactive oxygen species (ROS) and reactive nitrogen species (RNS)] and anti-oxidative defenses. Chronic inflammation induced by microbial persistent stimulation induces inflammatory cells to increase the production of ROS and RNS, promoting DNA damage and CRC development through oncogenes activation or tumor-suppressor gene inactivation (Cheng et al. 2020). The gut microbiota can also directly produce ROS. E. faecalis infection contributes to chromosomal instability and CRC risk because of superoxide production, which damages DNA in epithelial cells via a bystander effect and hydroxyl radicals, observed in laboratory models, powerful mutagens that cause DNA breaks, point mutations, and protein-DNA crosslinking (Cheng et al. 2020; Wang et al. 2014; de Almeida et al. 2018). Similarly, the bacterium enterotoxigenic Bacteroides fragilis (ETBF) is a significant source of chronic inflammation and ROS production and has been implicated as a risk factor for colorectal cancer (Goodwin et al. 2011). • Diet and bacteria metabolites Diet is an important risk factor for cancer that is amenable to intervention. More than a third of CRC cases are related to potentially modifiable factors such as unbalanced diets low in whole grains and dairy products, and high in red and processed meat (Zhang et al. 2019). At the same time, obesity is well known for increasing CRC risk, directly proportionate to the increase of body mass index (BMI) (Song et al. 2019). Tilg et al. investigated microbiota as the “missing link” in the close interaction between dietary factors and CRC. Diet can in fact rapidly alter the intestinal microbiota potentially contributing to disease susceptibility (Tilg et al. 2018) by modulating the intestinal microbiome composition and diversity (Cheng et al. 2020). Unbalanced dietary patterns determine the production of pro-carcinogenic chemicals such as N-nitroso compounds (NOCs), hydrogen sulfide (H2S), and secondary bile acids. Gut microbiota was found involved in the production of NOCs, highly mutagenic carcinogens via DNA alkylation. In healthy individuals, NOC-producing bacteria are a minority but excessive intake of nitrate and nitrite can make them the prevalent population with resulting dysbiosis, inflammatory response, and enrichment in

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E. coli. Microbiota production represents the source of endogenous NOCs while the major source of exogenous NOCS is highly processed meat whose intake has been correlated with a higher risk of CRC. In addition, CRC risk was significantly associated with exposure to heterocyclic amines (HCA) and polycyclic aromatic hydrocarbon (PHA), derived from red meat cooked at high temperatures. They are able to alter microbial metabolism and disrupt homeostasis and at the same time, microbiota can induce their bioactivation and transformation into toxic secondary metabolites. Furthermore, red meat contains heme iron, which can cause dysbiosis in mice models with a reduction of Firmicutes and Deferribacteres and an increase in Proteobacteria and Bacteroides altering the digestive health with a mechanism involving colonic levels of short-chain fatty acids (SCFAs) like butyrate (Tilg et al. 2018). It has health-promoting effects, along with acetate and propionate, and they are the predominant fermentation product in healthy adults consuming balanced diets. Butyrate, produced by Firmicutes via fermentation of dietary fiber and resistant starches, regulates epithelial proliferation, downregulates proinflammatory cytokines, and induces apoptosis in CRC cells. SCFAs reduce bacterial proliferation and DNA damage lowering fecal pH and interacting with GALT T-cells differentiation. Enhanced apoptosis and prevented cancer cell proliferation result in a global antitumoral effect and reduced SCFA levels were linked to a higher risk of carcinogenesis. Sulfate-reducing bacteria are abundant in the stools of CRC patients compared with those of healthy individuals. They use methionine and cysteine as substrates to generate H2S that inhibits butyrate oxidation and generates DNA-damaging ROS, altering the gut barrier and stimulating CRC progression. Bile acids derive from a different type of microbial metabolism since intestinal bacteria metabolize primary bile acids produced in the liver to secondary forms. High-fat diets lead to impaired bile metabolism, demonstrated in animal models, where populations fed in a western-style diet, high in fat components, developed significantly more colonic tumors than those on a control diet, correlating with higher cell proliferation in colonic crypts, impaired bile acid transport, and inactivation of the farnesoid X receptor (FXR), a nuclear bile acid receptor. Furthermore, secondary bile acids have been shown to be genotoxic via oxidative stress from ROS generation causing oxidative DNA damage (Cheng et al. 2020). • Biofilm Biofilm is an emerging concept about microbiota-related CRC carcinogenesis. Biofilms are communities of different microorganisms (bacteria but also fungi, Eukarya, and viruses) aggregated and encased in a polymeric matrix which makes them extremely resilient. They colonize different surfaces of the human body (Flemming and Wuertz 2019) and when mucosal barrier disruption occurs they come into direct contact with mucosal epithelial cells usually protected by mucus. Invasive polymicrobial biofilms were detected in most right-sided tumors (89%) but in only 12% of left-sided tumors and were accompanied by diminished E-cadherin, increased epithelial permeability,

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and enhanced IL-6 and STAT3 activation, subsequently increasing epithelial proliferation, diminishing apoptosis and promoting pro-carcinogenic tissue inflammation mediated by bacterial antigen translocation (Dejea et al. 2014).

3

Clinical Value of the Microbiota

Recent insight into gut microbiota may help clinicians in selecting useful biomarkers and developing effective strategies for CRC prevention and treatment with major translational applications especially in age groups not covered by endoscopy screening, lowering CRC morbidity and mortality (Cheng et al. 2020).

3.1

Biomarkers for CRC Screening and Prognosis

Microbiota-related biomarkers may be used both for screening and as prognostic tools for CRC treatment. It seems that alterations in the composition of the fecal microbiome of patients with CRC overlap with those found in patients with colorectal adenoma. Screening the fecal metabolome and microbiome may serve to select individuals at higher risk of developing CRC (Cheng et al. 2020). As previously mentioned, a precise cancer-related ecosystem is yet to be defined but many observations have been made. For example, on healthy individuals’ stool samples, the prevalence of the phylum Firmicutes, the genera Clostridium and the family Lachnospiraceae was observed and proposed as a marker. On the contrary, the presence of Fusobacterium nucleatum in CRC patients was prominent when compared with healthy volunteers, suggesting its potential as a novel diagnostic biomarker (Bartolini et al. 2020). A study conducted on the potential role of fecal-modified microbiota as a screening tool confirmed that identifying enrichment and depletion panels of pathogenic bacterial populations is much more useful compared to the identification of a single microbe, suggesting the polymicrobial pathogenesis of the disease. However, further large-scale cross-sectional studies with diverse populations are still required to confirm these findings and to obtain more information about bacterial species at strain level. Nevertheless, the linkage between microbiota and other modifiable and not modifiable characteristics of the patient (sex or age) have to be evaluated to obtain a stronger correlation (Bartolini et al. 2020; Zackular et al. 2014).

3.2

Microbiota Modulation for CRC Prevention and Treatment

Considering the major role in CRC played by the microbiota via several mechanisms, intestinal microbiota modulation may represent a way to reverse established microbial dysbiosis, for CRC prevention and treatment. These strategies

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include dietary intervention, probiotics, prebiotics, and fecal microbiota transplantation (FMT) (Cheng et al. 2020). Dietary composition has been associated with marked intestinal microbial diversity and is therefore critical in CRC evolution. Dietary intervention, considered the most reasonable and economical approach to CRC prevention, could encourage the growth of specific bacterial strains that may convert indigestible dietary components into beneficial metabolites for the host (Cotillard et al. 2013). As shown in Yusof et al. systematic review, the Western dietary pattern, mainly consisting of red and processed meat and refined grains is associated with an elevated risk of development of CRC. In contrast, a decreased risk is linked to the adoption of a healthy dietary pattern (high intake of fruits and vegetables, whole grain cereals, fish, poultry, and soy derivatives) (Yusof et al. 2012). However, diet-induced remodeling is temporary-dependent since, once the longstanding dietary regime is resumed, the intestinal microbiome returns to its previous composition too (Cheng et al. 2020). Another ideal method for modulating the microbiota may be the direct consumption of probiotics and/or prebiotics or by recourse to fecal microbiota transplantation (FMT). Probiotics are defined by the Food and Agriculture Organization of the United Nations and the WHO (FAO/WHO) as “live microorganisms that, when administered in adequate amounts, confer a health benefit on the host” (Hill et al. 2014). They may function in multiple ways: by inactivating carcinogens or mutagens, modulating host immunity, inhibiting cell proliferation, and improving gut barrier function (Fong et al. 2020). Liu et al. observed that treatment with a mixture of probiotics (Lactobacillus plantarum, L. acidophilus, and Bifidobacterium longum) can improve the integrity of the gut mucosal barrier, increasing the amount of cell junction proteins (Liu et al. 2011). Additionally, probiotic administration can ameliorate the adverse effects of chemotherapy, immunotherapy, and radiation therapy suggesting that investigations aimed at deciphering the microbiome-host interactions before and after intervention may allow prediction of disease course (Packey and Ciorba 2010; Cheng et al. 2020). Prebiotics are nondigestible food ingredients that feed beneficial intestinal bacteria and improve host health; clinical trials have reported the positive effects of perioperative administration of symbiotic probiotics and prebiotics on patients with CRC, including fewer postoperative infections and shorter hospital stay (Flesch et al. 2017; Cheng et al. 2020). Third, growing interest and deeper understanding of intestinal microbiota’s effect on both inflammatory and neoplastic processes made FMT an emerging biotherapeutic resource (Wang et al. 2014). It consists in transferring stool transplants from healthy donors to patients believed to harbor a disease-inducing dysbiosis to restore intestinal microbial homeostasis (Cheng et al. 2020).

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Gut Microbiota Interplay in Patients Undergoing Chemotherapy After CRC Surgery

CRC can be treated with different chemotherapy (CT) regimens tailored to tumor stage, patient’s general conditions, and mutational status, including 5-fluorouracil, capecitabine, and/or platinum-based agents. Unequivocally, CT alters the composition of intestinal microbiota and consequently, the so-called “pharmacomicrobiomics” is increasingly attracting attention (Bartolini et al. 2020). Dysbiosis caused by chemotherapy administration is mainly due to colitis and diarrhea and it may interfere with therapy through different ways: dysbiosis itself, immunomodulation, and xenometabolism. Anaerobic strains are usually depleted and there is reduced production of butyrate, a short-chain fatty acid (SCFA) responsible for the trophism of the intestinal mucosa and mucosal barrier efficacy through mucus secretion. It has antitumoral action blocking cellular replication, promoting apoptosis, stimulating IL-10 production, and inhibiting the NF-κB activation (Pouncey et al. 2018). Moreover, microbiota appears also to have a direct causal role in chemotoxicity. For example, irinotecan metabolism, in first-line chemotherapeutic treatment for metastatic colorectal cancer, is linked to the composition of an individual’s gut microbiota. Irinotecan-induced mucositis is the consequence of the reactivation of its liver metabolite from intestinal bacterial β-glucuronidases and brings adverse drug responses, including severe diarrhea (Guthrie et al. 2017). On the contrary, an intact commensal microbiota is able to modulate the tumoral micro-environment and is pivotal in an optimal response to chemotherapy, also reducing side effects (Iida et al. 2013). For example, in animal models, the response to cisplatin, oxaliplatin, or cyclophosphamide drug treatment was lower or inexistent if preceded by antibiotics. However, combining cisplatin with probiotics, especially Lactobacilli, improved response to therapy and, accordingly, the oral administration of Lactobacillus johonsonii and Enterococcus hirae improve the efficacy of cyclophosphamide treatment in tumor-bearing mice, inducing a pro-inflammatory T helper differentiation (Barbosa et al. 2021). F. nucleatum is known to have a causal role in chemoresistance via the formation and activation of autophagosome in the CRC cells with the production of their related proteins. Detection of high levels of this species may represent a prognostic biomarker leading to the need of modified schemes of administered chemotherapy. Chemoresistance was also associated with high levels of IL-22 as well as a lower efficacy of anti-blastic therapy was linked to high levels of regulatory T cells creating an immunosuppressive environment (Yu et al. 2017). Unraveling at least a part of the mechanisms of chemoresistance, may provide new strategies for chemotherapy optimization allowing reduction in side effects and better results in CRC management (Bartolini et al. 2020). Similarly, the discovery of favorable or unfavorable microbiota for chemoresistance and side effects may help in tailoring chemotherapy. In perioperative settings, modulation of microbiota is involved in reduced recovery timing after surgery.

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Ambrosio et al. have recently demonstrated that immunonutrition modulates tumor microenvironment by improving immune function and prolonging survival in patients undergoing elective surgery for CRC (Ambrosio et al. 2023). In this setting many precautions should be taken into consideration: supplementary food containing microbes able to ferment acid lactic may allow enhanced healing of the surgical wound; in animal models, oral supplementation with non-absorbable phosphate, usually lacking after surgery, reduced bacterial-related anastomotic leak; antibiotic therapy should be carefully administered and, when required, for the shortest needed period; analgesics should be preferred over opioids; bowel preparation should be modified in order to try to eliminate only, or mostly reduce, virulent strains while maintaining helpful biodiversity in the microbiota (Bartolini et al. 2020).

3.4

Effects of Gut Microbiota on Immunotherapy

The immune system is not a simple bystander in cancerogenesis and its interplay with cancer has been extensively studied in the last decade displaying its unquestionable key role during tumorigenesis. It is crucial in controlling tumor growth; nonetheless, in some cases, the activity of immune cells can also favor cancer progression. The improved understanding of the interaction between the immune system and cancer, in the last years, brought a revolution in cancer treatment that can either boost or damper immune pathways to promote antitumor status. Recent data demonstrated the role of the gut microbiota in the regulation of antitumoral immune response and the efficacy of the recently developed immunotherapies such as checkpoint blockade, making gut microbiota modulation a novel adjunct approach to current therapies (Barbosa et al. 2021). Microbiota’s influence on the efficacy of immunotherapy was demonstrated in preclinical studies reporting a linkage between alterations in microbiota composition and the efficiency of CTLA-4 and PD-1 blockade. Vétizou et al. highlighted the role of microbiota since they reported that anti-CTLA-4 therapy did not inhibit tumor growth in germ-free or antibiotic-treated mice; further experiments showed how Bacteroidales and Burkholderiales were crucial for the therapeutic efficiency. As counterevidence, oral or fecal transplantation of B. fragilis in combination with B. thetaiotaomicron or B. cepacia restored the efficiency of anti-CTLA-4. The underlying mechanism was found in the generation of antitumor antigen-specific Th1 responses, promoted by the microbiota, which controlled tumor growth both in animal models and humans, likely by producing cross-reactive antigens and enhancing antitumor T-cell responses (Vétizou et al. 2015). Similarly, Sivan et al. investigated discrepancies in tumor growth and anti-PD-1 therapy when comparing genetically similar mice harboring distinct microbiota. Interestingly, fecal transplants from responsive to unresponsive mice restored the efficacy of PD-1 blockade, showing that microbiota composition plays a critical role in anti-PD-1 therapy. By analyzing microbial composition in mice prone to response

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to treatment, it has been detected an enrichment in Bifidobacterium strains. The supplementation of these species restored the antitumoral efficacy of PD-1 blockade in non-respondent mice lacking these bacteria (Sivan et al. 2015). Moreover, augmented dendritic cell function and enhanced CD8-positive T-cell priming and accumulation in the tumor microenvironment (TME) were shown to be associated with the efficacy of PD-1 blockade as well as of anti-CL4.

4

Conclusion

The gut microbiota exists in a dynamic balance between symbiosis and pathogenesis and can influence almost any aspect of host physiology. Even if a universal CRC-associated microbiota is yet to be determined, great effort was put into revealing the complexity of the mechanisms that unequivocally exist between microbiota and tumors, and more should be done in this direction in the attempt to deepen current knowledge and exploit the microbiota in all its potential, from its role in the process of carcinogenesis to all possible preventive and therapeutic applications.

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Immunotherapy in Gastrointestinal Cancer Focusing on CAR-T Cell Therapy Asma Mousavi, Faeze Gharibpoor, Sepideh Razi, and Nima Rezaei

Abstract

Cancer is a leading cause of death worldwide, accounting for nearly ten million deaths in 2020. In this regard, gastrointestinal (GI) cancers are among the cancers with the highest mortality rate. In the past, surgery, chemotherapy, radiotherapy, and their combination were the only solutions for cancer treatment; however, the emergence of immunotherapy has recently opened a new horizon in cancer A. Mousavi School of Medicine, Tehran University of Medical Sciences, Tehran, Iran Cancer Immunology Project (CIP), Universal Scientific Education and Research Network (USERN), Tehran, Iran F. Gharibpoor Cancer Immunology Project (CIP), Universal Scientific Education and Research Network (USERN), Tehran, Iran Student Research Committee, Faculty of Medicine, Guilan University of Medical Sciences, Rasht, Iran S. Razi Cancer Immunology Project (CIP), Universal Scientific Education and Research Network (USERN), Tehran, Iran Research Center for Immunodeficiencies, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran N. Rezaei (✉) Research Center for Immunodeficiencies, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran Cancer Immunology Project (CIP), Universal Scientific Education and Research Network (USERN), Stockholm, Sweden e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2023_152 Published online: 7 March 2023

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treatment, especially hematological malignancies. Although there are various methods of immunotherapy, the central concept behind all of them is using the potential of host immune cells. To date, three types of tumor immunotherapies have been used to treat GI cancers: immune checkpoint inhibitors (ICIs), vaccine therapies, and adoptive cell therapy (ACT), which includes chimeric antigen receptor (CAR)-T cells. CAR-T cell therapy is one of the most innovative and attractive cellular immunotherapies rapidly evolving in the last decades. In this method, the patient’s T cells are manipulated to express desired CARs to recognize the tumor-associated antigens (TAAs). Some of the principal TAAs in GI cancers are epithelial cell adhesion molecule (EpCAM), mucin 1 (MUC1), human epidermal growth factor receptor 2 (HER2), and carcinoembryonic antigen (CEA), which are covered in this review. Despite the remarkable progress in the CAR-T cell method, several factors limit its clinical administration. The current study aims to reveal the role of CAR-T cell therapy in GI cancers, its limitations (cytokine release syndrome, neurotoxicity, disease relapse, and on-target, off-tumor toxicities), as well as some practical strategies to improve the safety of this method. Keywords

CAR-T cell therapy · CTLA-4 · Gastrointestinal cancer · Immunotherapy · PD-1

1

Introduction

Worldwide, the prevalence of various types of cancer is rising, making them one of the major causes of disability, morbidity, and mortality (Dahiya et al. 2021). Gastrointestinal (GI) (including esophageal, stomach, liver and biliary system, pancreas, and colorectal) cancers are among the most common type of malignancies in terms of prevalence. In this way, colorectal cancers have the third-grade mortality rate among all cancers (Siegel et al. 2021). The 5-year survival rate of GI cancers is also low, especially in advanced stages (Yang et al. 2019). Early diagnosis by expanding the treatment options can increase the survival rate (Maharaj et al. 2019); however, it is limited by nonspecific symptoms of the disease, including weight loss, vomiting, nausea, heartburn, and fatigue, commonly seen in other illnesses (Mansfield 2011). Currently, the gold standard of clinical diagnosis is achieved by the pathological analysis of the tumor tissue. Upper GI endoscopy, along with colonoscopy and computed tomography, also helps make the diagnosis (Li et al. 2021a, b). The treatment option relies on the stage and type of GI cancer. The traditional treatments consist of surgical resection of the tumor, chemotherapy, radiotherapy, and their combination. These methods have limited effects, and the prognosis has remained low (Lu et al. 2020). For example, surgery is the first choice for colorectal, esophageal, and gastric cancers. Radiotherapy as neoadjuvant therapy can be used before surgery to diminish the tumor size or kill the remaining cancer cells after surgery.

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However, using these methods, only 10–30% of esophageal and rectal cancer patients show complete pathological response (Buckley et al. 2020). Immunotherapy has become a revolutionary choice for treating cancers in the last few decades. It consists of various methods to fight malignant tumors by inducing, enhancing, or suppressing the immune responses (Mellman et al. 2011). There are two types of immunotherapy: active and passive; active immunotherapy denotes a patient’s immune system response (e.g., chimeric antigen receptor (CAR)-T cell therapy and cancer vaccines), while passive immunotherapy refers to components that are made out of the patient’s body (e.g., monoclonal antibodies) (Jeremy et al. 2016). Immunotherapy has shown fewer side effects and more efficacious results in some GI cancers than conventional treatments. Immune checkpoint inhibitors (ICIs), vaccine therapies, cytokine, and adoptive cell transfer (ACT) therapy are the main types of immunotherapy for treating GI cancers (Dahiya et al. 2021). CAR-T cell therapy is a type of ACT therapy that has advanced furthermost in clinical studies. In this tactic, T cells are extracted from the patient’s bloodstream, genetically engineered to express CARs, specified to recognize the tumor-associated antigens (TAAs). The resultant T cells are then infused back into the patient (Bębnowska et al. 2020). Numerous studies confirm the success of this method in hematologic tumors; however, their performance in destroying solid tumors is under intense investigation (Kang et al. 2021). In this review, after a brief introduction to different types of immunotherapies, we focus on the CAR-T cell method, its implication in GI cancers, its limitations, and different strategies to overcome the obstacles.

2

Immune System

A healthy immune system can detect and kill tumor cells. However, numerous regulatory factors, including immune cells, cytokines, and growth factors, intervene in this process, which is disturbed in patients with cancer. The following sections investigate the immune system’s response to the tumor.

2.1

Tumor Microenvironment (TME) Role in Immunotherapy

The tumor microenvironment (TME) is a complex tissue composed of tumor cells, stromal cells, immune cells, as well as vasculature and extracellular matrices (ECM). TME components have contrary effects on tumorigenesis, tumor progression, and therapeutic resistance against immunotherapy (Zeng et al. 2021). B lymphocytes have less described function in different types of GI cancers. They can produce tumor-infiltrating plasma cells, which, by secreting antibodies, activate cytotoxic cells, CD8+ T cells, and natural killer (NK) cells. B cells are also necessary for activating T cells by acting as antigen-presenting cells (APCs) and contributing to co-stimulatory signals. In this way, studies have shown that a higher infiltration of CD138+ plasma cells is correlated with a better prognosis in colorectal and

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esophageal cancers (de Visser et al. 2005; DiLillo et al. 2010; Fristedt et al. 2016). NK cells are a member of innate immune cells and present as the first-line defense against malignant transformation. Downregulation of some NK receptors, including NKG2D, NKp30, and NKp46, has been reported in pancreatic, colorectal, and gastric cancer and is associated with disease progression and metastasis (Peng et al. 2013). Macrophages play a significant and contrary role in tumor growth regulation. For example, monocyte chemoattractant protein 1 (MCP-1), the most crucial chemokine in summoning macrophages to TME, is associated with tumor growth and is a negative immune regulator in colon cancer (McClellan et al. 2012). Furthermore, tumor-associated macrophages consist of two groups: M1-macrophages, which protect against tumor growth by secreting interleukin (IL)-6 and IL-12, and M2-macrophages that are associated with tumor proliferation, invasion, and metastasis. A higher M1/M2 ratio in TME of gastric cancer is associated with a better prognosis (Pantano et al. 2013; Duque and Descoteaux 2014). T regulatory (T-reg) cells inhibit effector T cells, monocytes, and macrophages by chemokine signaling. FOXP3 + T-regs have been reportedly associated with progression and adverse stages of gastric cancer (Liu et al. 2019). CD8+ T cells are the most powerful anti-tumor effectors and are the basis of current immunotherapy techniques (Zhang et al. 2019a; b). Dendritic cells present antigenic peptides to CD4+ T cells and activate effector T cells to respond against tumor cells. Dendritic cell-based therapy with a high expression level of lymphocyte antigen-6E (LY6E), a common protein in gastric and colorectal cancers, has shown promising results in arousing cytotoxic lymphocyte responses (Ishigami et al. 2000; Tokhanbigli et al. 2020). Cancer-associated fibroblasts secrete transforming growth factor-beta (TGF-beta) and other growth factors, which cause the proliferation of tumor cells and treatment resistance in GI cancers (Zhang et al. 2019a, b). Table 1 summarizes the role of some of the most important immune cells and cytokines in TME in the progression or restraining of the tumor.

2.2

Cancer-Immunity Cycle

Our immune system, to some extent, can detect and remove tumor cells in a stepwise manner described as the cancer-immunity cycle (Chen and Mellman 2013). This cycle is expressed in seven steps: In the first step, APCs uptake dead tumor cells and process them as antigens. The TAAs are then expressed on major histocompatibility complex (MHC) classes I and II on APCs’ surfaces and are presented to T cells (step 2). Step 3 includes priming and activating T cells, enabling them to move to the tumor’s location via the bloodstream (step 4) and invade the tumor bed (step 5). T cell receptors (TCRs) recognize TAAs presented on MHCs and interact with them (step 6), leading to the death of tumor cells (step 7). The release of TAAs from dead cancer cells aids the restart of the cycle and summons more immune cells to the tumor site. Each step is regulated by various factors (Chen and Mellman 2013; Aoki et al. 2019; Wu et al. 2020). These regulatory factors may be disturbed in cancer patients, allowing tumor cells to escape from immune cells. Immunotherapy, by

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Table 1 Role of TME components on tumor growth Cells B cells

Effects on tumor cells Inhibit

NK cells

Inhibit

Cytokines and other factors associated with these cells Producing antibodies, co-stimulatory signals Granzyme, perforin

M1-macrophages

Inhibit

TNF-alpha, IL-6, IL-12

M2-macrophages

Activate

T-reg cells

Activate

IL-10, TGF-beta, growth factors IL-10, IL-35, TGB-beta

CD8 T cells

Inhibit

Granzyme, perforin

Dendritic cells

Inhibit

Antigenic peptides, IDO

CAFs

Activate

TGF-beta, growth factors

References de Visser et al. (2005) Zhang et al. (2019a, b) Duque and Descoteaux (2014) Duque and Descoteaux (2014) van Herk and Te Velde (2016) Zhang et al. (2019a, b) Ishigami et al. (2000) Zhang et al. (2019a, b)

NK cells natural killer cells, T-reg, T-regulatory, CAF cancer-associated fibroblast, TNF-alpha tumor necrosis factor-alpha, IL interleukin, TGF-beta transforming growth factor-beta, IDO indoleamine-2,3-dioxygenase

regulating this cycle, optimizes the patient’s response to tumor removal (Chen and Mellman 2013). For example, an immune checkpoint inhibitor, the programmed death (PD) 1, is one of the most crucial proteins expressed on activated lymphocytes. This protein can interact with its ligand (PD-L1) on cancer cells, blocking the activation of T cells (Shah et al. 2019). Some advanced GI cancers, refractory to standard treatment, have shown promising results following PD/PD-L1 inhibitors (Xu et al. 2018; Antoniotti et al. 2020).

3

Types of Immunotherapies in GI Cancers

ICIs, vaccines therapy, and ACT are the most studied immunotherapies in GI cancers (Dahiya et al. 2021).

3.1

Immune Checkpoint Inhibitors (ICIs)

In recent years, ICIs have shown much potential in treating different cancers. Immune checkpoints are a group of cell surface receptors expressed by immune cells to regulate T cell activation. In this way, cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) and its ligand (B7), as well as PD-1 and its ligand (PD-L1), are two critical checkpoints that negatively regulate T cell activation (Shah et al. 2019). The application of ICIs in advanced GI cancers has shown promising results. One

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major factor that predicts the efficacy of ICIs is the presence of tumor-infiltrating lymphocytes (TILs). Studies have shown that tumors with more TILs in their TME have a more favorable outcome. In gastric and esophageal cancers, it’s been suggested that the density of TILs is higher in the early stages compared to advanced stages. This discrepancy may stem from the selection of less immunogenic cancer cell clones through tumor progression (Jindal 2018). Nevertheless, nivolumab and pembrolizumab have been approved in the United States and Europe for treating advanced esophageal, gastric, and colorectal cancer with mismatch-repair-deficient and microsatellite instability-high (dMMR/MSI-H) disease (De Mello et al. 2019; Boukouris et al. 2022).

3.2

Tumor Antigen Vaccine Therapies

In this method, TAAs are transported to the patient’s body in different ways; in one way, TAAs are introduced to APCs and expressed on their surface. The treated APCs and co-stimulatory adjuvants are then transported to the patient’s body. Another way is by inserting TAAs’ genes in the genetic material of viral agents and injecting these vectors into the patient’s body. Patients can also receive TAAs in the form of peptides accompanied by immunomodulatory agents to induce an immune response (Chudasama et al. 2021). Promising results have been demonstrated by combining vaccines with chemotherapy in GI cancers; however, there are still many challenges related to vaccine therapy such as immune tolerance of TME and low specificity of TAAs in solid tumors (Rahma and Khleif 2011; Chudasama et al. 2021).

3.3

Adoptive Cell Therapy (ACT)

This method is one of the primary passive immunization therapies. In this method, T cells are collected from patients’ blood or tumor tissue, proliferated in large numbers, and infused back into the patient’s body. TILs and CAR-T cells are the two types of ACT (Dahiya et al. 2021).

4

CAR-T Cell Therapy

4.1

Anti-tumor Mechanism of CAR-T Cell Therapy

CAR-T cell therapy is one of the most innovative and promising cellular immunotherapies rapidly evolving in the last decades (Dahiya et al. 2021). In this method, T cells are first collected from the patient’s blood, then introduced to vectors (viral or non-viral methods) carrying desired CARs genes, designed against the patient’s tumor antigens. Subsequently, vectors transfer CAR genes to T cells to express CARs on their surface. CAR-T cells are then proliferated to reach a

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therapeutic dose and are transfused to the patient (Zhang et al. 2016). In this way, CARs are synthetic immunoreceptors consisting of an intracellular signaling domain, a transmembrane domain, a hinge, and an extracellular domain called single-chain variable fragments (scFvs) (Lee et al. 2022). scFvs are the antigensensing components composed of two chains (heavy and light) of a high-affinity monoclonal antibody (mAb) (Wang et al. 2013). Although numerous studies have demonstrated the success rate of CAR-T cell therapy in hematologic malignancies, the application of this method in solid tumors, including GI cancers, is limited by several factors such as challenging infiltration of T cells to the tumor, their proliferation and steadiness in TME, and presence of diverse TAAs on solid tumor’s surface (Bębnowska et al. 2020; Murad et al. 2021). Further, we discuss some of the most studied TAAs in GI cancers targeted by CAR-T cells.

4.2

Targeted Antigens Expressed on GI Tumors

Mucin 1 (MUC1) is the first member of a high molecular weight glycoprotein presenting on the apical surface of epithelial cells. MUC1 has three domains: an extracellular domain protecting cells from the invasion of pathogens, a transmembrane domain, and an intracellular domain playing a role in signaling pathways (Bose and Mukherjee 2020). Hyperglycosylated MUC1 presents abundantly on GI cancer cells and correlates with metastasis and poor prognosis (Wang et al. 2016). The hyperglycosylated state of MUC1 in GI cancers distinguishes them from MUC1 in normal cells, making them a suitable target for CAR-T cell therapy. For example, tumor-associated MUC1 (tMUC) is overexpressed on roughly 85% of pancreatic ductal adenocarcinoma (PDA). In this way, Yazdanifar et al. have achieved promising results by designing CAR-T cells against tMUC1 (called TAB004derived CAR-T cells) in animal models of pancreatic ductal adenocarcinoma (Yazdanifar et al. 2019). Epithelial cell adhesion molecule (EpCAM) is a transmembrane glycoprotein with intracellular and extracellular domains belonging to the adhesion molecule family. Studies have revealed that EpCAM overexpression on epithelial tumors’ surfaces plays a crucial role in tumor proliferation and metastasis (Bębnowska et al. 2020). EpCAM overexpression in GI cancer cells makes them a favorable target for CAR-T cell therapy; in fact, there are some promising in vivo and in vitro studies using CAR-T cell therapies against EpCAM in GI cancers such as gastric and colorectal cancers (Zhang et al. 2019a; b; Li et al. 2021a; b). Human epidermal growth factor receptor 2 (HER2) is a cell surface tyrosine kinase and a member of the epidermal growth factor receptor (EGFR) family. Binding of ligands to the extracellular domain of HER2 initiates pathways leading to carcinogenesis, tumor proliferation, and metastasis. In this way, its overexpression correlates with poor prognosis of various cancers, including GI cancers (Budi et al. 2022). In fact, in HER2-positive gastric and colorectal cancers, HER2-specific CAR-T cells have completely eradicated the tumoral cells (Budi et al. 2022). In addition, clinical trials have reported more than 50% survival rate by using

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HER2-specific CAR-T cells as an adjuvant in treating biliary tract and pancreatic carcinoma (Siddiqui and Sardar 2021). Carcinoembryonic antigen (CEA) is a glycoprotein involved in cell adhesion. It is expressed by the luminal epithelium of the GI tract and lung. It is widely used as a marker for cancer diagnosis, prognosis, and recurrence. CEA in CAR-T cell therapy has attracted attention due to its different status in cancer cells compared to normal cells. Unlike normal cells, which express CEA only on apical surfaces, cancer cells express CEA all over their surface (Klein et al. 2017). The safety and efficacy of antiCEA-specific CAR-T cells in GI cancers, including gastric, pancreatic, and colorectal cancers, are being studied in clinical trials; however, the overall improvement in the survival has been low compared to hematologic malignancies (Umut et al. 2021). B7 family is a group of co-stimulatory or co-inhibitory proteins regulating T cell response to tumor cells. Studies have shown various and controversial expression levels of B7 family members in the cancer cell, and their role in the prognosis of GI cancers is not established yet (Sadelain et al. 2013). For instance, overexpression of B7H6, a B7 family member, has been reported in gastrointestinal stromal tumors (GISTs), playing as a ligand for the natural killer cell-activating receptor, NKp30. B7H6 has also shown an antiapoptotic role, leading to tumor proliferation of hepatocellular carcinoma. Subsequently, B7H6-specific CAR-T cells have resulted in increased cytotoxicity and less tumor burden in some B7H6-positive cells (Brandt et al. 2009; Chen et al. 2018). Also, in gastric cancer, higher expression of B7H6 correlates with a better prognosis (Li et al. 2020) (Table 2).

5

Side Effects and Limitations of CAR-T Cell Therapy

Despite the promising results of CAR-T cell therapy, this method is not the first-line cancer treatment. This is partly due to some acute and chronic related toxicities, which are life-threatening if not managed properly (Adkins 2019). Here we discuss the most critical side effects and limitations that we face in this method.

5.1

Side Effects

Cytokine Release Syndrome (CRS) CRS, one of the most common CAR-T cellrelated adverse event, is a systemic inflammatory response to the high concentration of cytokines. This syndrome occurs between the first day and the third week after CAR-T cell infusion, manifesting as high-grade fevers, hypotension, hypoxia, and even organ failure (Adkins 2019). The exact mechanism of CRS following CAR-T cell therapy underlies the process by which CAR-T cells kill tumor cells. As we mentioned earlier, the scFv of CAR-T cells is the site of detection and junction with TAAs. Following this connection, CAR-T cells become activated and secrete cytokines such as perforins, granzymes, interferon-γ (IFN-γ), and tumor necrosis factor (TNF). Modified versions of CAR-T cells can also produce more cytokines because of their co-stimulatory domain (Hay et al. 2017; an et al. 2021). Following

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Table 2 Antigens targeted by CAR-T cell therapy in gastrointestinal cancers Phase of studies Preclinical, clinical

Antigen MUC1

Other names episialin, PEM, MSA, CA15-3, KL6, DF3, MAM-6, PUM, CD227, PAS-0, and CAM 123-6

Cancers Cholangiocarcinoma, pancreatic cancer, gastric cancer, esophageal cancer, hepatocellular carcinoma, Gastric cancer, breast cancer

EpCAM

CD326

Preclinical, clinical

Gastric cancer, colorectal cancer, pancreatic cancer

HER2

ErbB2

Preclinical, clinical

CEA

--

Preclinical, clinical

Pancreatic cancer, biliary tract cancer, gastric cancer, colorectal, esophageal cancer Liver cancer, colorectal cancer, pancreatic carcinoma, gastric cancer

References Posey Jr. et al. (2016), DeSelm et al. (2017), Yazdanifar et al. (2019), Zhang et al. (2020), Supimon et al. (2021), Zhai et al. (2021) Zhang et al. (2018a), b), Ma et al. (2019), Zhang et al. (2019a), b), Zhou et al. (2019), Li et al. (2021a), b), Yang et al. (2021), Staudt et al. (2022) DeSelm et al. (2017), Feng et al. (2018), Song et al. (2018), Yu et al. (2021) Chmielewski et al. (2012), Katz et al. (2015), Thistlethwaite et al. (2017a), b), Zhang et al. (2017), Zhang et al. (2018a), b), Chi et al. (2019), Hombach et al. (2019), Cha et al. (2021), Fan et al. (2021), Kumar et al. (2021), Raj et al. (2021)

MUC1 mucin 1, EpCAM epithelial cell adhesion molecule; HER2 human epidermal growth factor receptor 2, CEA carcinoembryonic antigen

the cytokine release, immune and nonimmune cells such as epithelial cells get activated and secrete more cytokines. A key cytokine in CAR-T cell-associated CRS is IL-6 because its secretion depends on the connection between CAR-T cells and tumor-specific macrophages (Hunter and Jones 2015). Targeting these cytokines in the proper time and setting may improve the disease outcome. Clinical manifestation of CRS depends on its stage. Mild CRS presents with fever, fatigue, headache, rash, and myalgia, while severe CRS symptoms are tachycardia,

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hypotension, circulatory collapse, respiratory failure, and multi-organ failure (Chen et al. 2019). Mild to moderate symptoms can be managed by supportive care, while more severe cases may need immunomodulatory agents (Le et al. 2018). Neurotoxicity Neurologic adverse effects may present 1–3 weeks after CAR-T cell infusion (Gust et al. 2017). The pathogenesis of neurologic toxicity is not established yet; however, it is believed that endothelial cell damage caused by inflammatory cytokines may be one mechanism. In this way, it is shown that a high concentration of cytokines such as TNF-alpha, IL-6, and IFN-γ could activate endothelial cells, causing the production of a great amount of angiopoietin (Ang)-2 and von Willebrand factor (VWF) (Kometani et al. 2014; Hu et al. 2016). Subsequently, these two factors increase the permeability of the blood-brain barrier (BBB) and the development of cerebral edema (Adkins 2019). Additionally, damaged BBB results in leakage of inflammatory cytokines and CAR-T cells to brain tissue, supported by the observation of these cells in cerebrospinal fluid (Mackall and Miklos 2017; Johansson et al. 2021). Following the leakage of cytotoxic cells to the central nervous system, these cells’ direct toxic effect on neural cells manifests as neurotoxicity. The clinical manifestation of neurologic effects varies, influenced by several factors, including target antigen selection and infused cell dose (Gust et al. 2017). Symptoms range from confusion, diminished attention, and disturbance in language and writing to paralysis, seizure, or even death (Santomasso et al. 2018; Gajra et al. 2019). Furthermore, due to the inability of many immunomodulatory agents to cross the blood-brain barrier, managing severe cases is more challenging and may be limited to corticosteroids (Santomasso et al. 2018; Adkins 2019).

5.2

Limitations

Disease Relapse Besides the promising results of CAR-T cell therapy, reports of the disease relapse in patients treated with this method have opened a new window towards the immune system and CAR-T cell mechanism. One mechanism proposed for the disease relapse is antigen downregulation or antigen loss escape in the later phase of treatment. In this way, studies have shown that relapsed tumor cells express previously CAR-T cell-targeted antigens at lower or zero levels (Li et al. 2018). The mechanism proposed for antigen loss is either by producing tumor cells phenotypically similar to the previous tumor type, only lacking the CAR-T targeted antigen, or by the emergence of phenotypically different tumor cells genetically related to the previous tumor cells (Majzner and Mackall 2018). Additionally, antigen loss escape may be achieved by trogocytosis, defined as a phenomenon by which CAR-T cells capture targeted TAAs and shift target antigens into their own cell, reducing the number of expressed TAAs on targeted tumor cells (Hamieh et al. 2019). In contrast to natural immune systems’ T cells, which recognize even low-expressed antigens, CAR-T cells require a minimum expression level to detect antigens (Majzner and Mackall 2018).

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Furthermore, antigen-positive relapse is an early phase cause of disease relapse, stemming from inadequate removal of tumor cells. The most common factors responsible for this type of relapse are poor quality and quantity of T cell collection, inefficacious production of CAR-T cells, higher tumor burden, conditioning regimen for T cell persistence, and the recipient’s immune system response (Nie et al. 2020). One proposed strategy to overcome incomplete removal of tumors is to target multiple antigens instead of one. This technique is more productive in solid tumors expressing heterogeneous antigens (Bielamowicz et al. 2018). On-Target, Off-Tumor Toxicities CAR-T cells target antigens overexpressed on the tumor cells, but most of these antigens are not tumor-specific and are expressed on normal tissues, as well. On-target, off-tumor toxicity occurs when normal cells, along with tumor cells, are targeted by CAR-T cells. This complication is more prevalent in solid tumors because, unlike hematologic tumors, which express only specific TAAs, solid tumors overexpress heterogenous antigens that have lower expression levels on healthy cells (Zhang et al. 2016). For example, a clinical trial about the efficacy of CEACAM5-specific CAR-T cells in GI tumors by Thistlethwaite et al. was prematurely terminated due to the progression of transient and acute respiratory complications. The expression of CEACAM5 on lung epithelium was accused of this toxicity (Thistlethwaite et al. 2017a; b). Interestingly, using low-affinity CAR-T cells has shown anti-tumor activity against overexpressed antigens on tumor cells compared to their inactivity against normal cells, which express the same antigen at a normal level (Yang et al. 2020).

6

How to Improve the Safety of CAR-T Cell Therapy?

As we mentioned earlier, although CAR-T cell therapy is a highly potential technique in cancer treatment, several obstacles limit its administration in clinical studies. In this way, scientists seek ways to reduce this method’s toxicity while improving its specificity. Suicide gene switch, multi-target-antigen therapy, synthetic notch receptors, inhibitory chimeric antigen receptors, bispecific T cell engager, and on-switch CAR are some examples (Yu et al. 2019). Here, we mention two developing methods.

6.1

Immune Inhibitory Receptors

As we mentioned earlier, PD-1 and CTLA-4 play an important role as inhibitory receptors in reducing and eliminating T cell responses (Curran et al. 2010). Inhibitory chimeric antigen receptors (iCAR) are CARs containing PD-1 and CTLA-4 inhibitory signaling domains, along with scFv designed to detect antigens specific to normal tissue, not tumor cells. Designing T cells possessing both TAA-specific CARs and iCAR has shown reduced off-tumor toxicity due to the initiation of inhibitory signaling in CAR-T cells targeting normal cells (Fedorov et al. 2013).

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On-Switch CAR

An extracellular scFv, co-stimulatory domain, and a key downstream signaling element together form the on-switch CAR. The CAR-T cells’ therapeutic activity depends on the antigen’s recognition and the junction of a small priming molecule. Small priming molecules control the time, region, and dosage of T cell activity to relieve the toxicity. Furthermore, on- and off-switch CAR-T cell has been developed by Jan et al., in which degradable tags are incorporated into CAR to initiate lenalidomide or other thalidomide analog-induced CAR degradation (Jan et al. 2021).

7

Conclusion

Along with the remarkable success of different types of immunotherapies, scientists are investigating tactics to increase these methods’ effectiveness. The most important immunotherapies in GI cancers are ICIs, vaccine-based therapies, and ACT, including CAR-T cell therapy. CAR-T therapy has demonstrated significant efficacy compared to conventional treatments; however, the success of this method in GI cancers and other solid tumors compared to hematologic tumors is in its infancy. Using the specific features of solid tumors, for example, designing multi-targeted CAR-T cells against the more heterogeneous TAAs in solid tumors, has shown promising results. More research is still needed to reveal solid tumors’ specific features and design a more efficacious CAR-T cell with less toxicity. Acknowledgment None. Ethical Statement The manuscript does not contain clinical studies or patient data. Conflict of Interest The authors declare that they have no conflict of interest.

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Development of Biocompatible Nanocarriers for the Treatment of Colorectal Cancer

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Bibi Noorheen Haleema Mooneerah Neeroa, Nurshafida Adzlin Shamsul Anuar, Brianna, Mostafa Yusefi, Kamyar Shameli, and Sin-Yeang Teow

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Abstract

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Colorectal cancer is one of the top three cancers with highest incidence in the world. Therapies using medication remain one of the common treatment methods, but the treatment efficacy is often hindered by inefficient tumour penetration and drug delivery. Hence, the development of drug nanocarrier is becoming more important in order to maximise the drug delivery to the target cells and the cancerkilling capacity. In recent years, the use of nanoparticles for cancer therapy has gained traction due to their diverse characteristics and high flexibility for modifications. While exerting anticancer action when used individually, nanoparticles are also suitable to be used as a delivery system to transport the anticancer drug to the targets. In order to develop a non-toxic nanoparticles-based drug carrier, various biomaterials such as chitosan, xanthan gum, cellulose and alginate are also used to enhance the biocompatibility of the nanocarrier. This chapter discusses the recent development of biomaterial-derived nanocarriers and their use towards colorectal cancer therapy. Some challenges and limitations are

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B. N. H. M. Neeroa · N. A. S. Anuar · Brianna Department of Medical Sciences, School of Medical and Life Sciences, Sunway University, Selangor, Malaysia M. Yusefi Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia K. Shameli School of Medicine, Institute of Virology, Technical University of Munich, Munich, Germany S.-Y. Teow (✉) Department of Biology, College of Science, Mathematics and Technology, Wenzhou-Kean University, Wenzhou, China e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2023_158 Published online: 6 April 2023

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also discussed here to provide insights for future development of biocompatible drug nanocarriers.

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Keywords

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Biomaterial · Colorectal cancer · Nanocarrier · Nanomedicine · Treatment

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Introduction

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1.1

Colorectal Cancer and Its Management

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Colorectal cancer is the third most diagnosed cancer and the third leading cause of cancer death both in men and women worldwide. An estimated number of 1.8 million people were newly diagnosed with CRC, and 0.9 million people died from the disease in 2020 (Xi and Xu 2021). Generally, the colon epithelial tissues are genetically altered to form cancerous polyps which accumulate and develop into cancer (Bray et al. 2018). Patients with CRC can be treated by surgery, radiation therapy, chemotherapy, targeted therapy, immunotherapy or in combination according to their medical conditions. However, each treatment option may come with possible side effects (Biller and Schrag 2021). As this chapter focuses on the development of drug nanocarrier, we will focus on the therapies using medication which include chemotherapy, targeted therapy and immunotherapy. Chemotherapy is the use of anticancer drugs to destroy fast-growing cells, inhibiting the growth or division of cancer cells. According to cancer.org, patients often receive several cycles of treatment either consisting of one type of drug or more over a period of time. Some of the commonly used drugs include 5-fluorouracil (5-FU), capecitabine (Xeloda), irinotecan (Camptosar) and oxaliplatin (Eloxatin). They can also be used in combination such as FOLFOX (5-FU with leucovorin and oxaliplatin), FOLFIRI (5-FU with leucovorin and irinotecan), XELIRI/ CAPIRI (capecitabine with irinotecan) and XELOX/CAPEOX (capecitabine with oxaliplatin) (Biller and Schrag 2021). The two common method of administering the drug is either via systemic chemotherapy, where the drug is administered intravenously or orally and travels to almost all areas of the body, or regional chemotherapy, where the drug is administered into the artery which directs to a specific part of the body with cancer. Targeted therapy is a treatment that targets specific gene or protein or even the tumour ‘microenvironment’ that contributes to cancer growth, to prevent the cancer cells from spreading to surrounding healthy cells. Some of these drugs such as bevacizumab, regorafenib, ramucirumab and ziv-aflibercept are designed to inhibit angiogenesis while others such as cetuximab and panitumumab are designed to block cell receptors such as epidermal growth factor receptor (EGFR). Often, these drugs are also used in combination with drugs in chemotherapy to maximise the treatment efficacy. As these drugs act specifically on the target, cells cannot respond to the drugs if the tumour cells have specific mutations on the target such as EGFR,

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RAS and BRAF mutations, hence rendering the therapy ineffective (Awi et al. 2021; Pang et al. 2019). Immunotherapy, on the other hand, is designed to boost the body’s immune response to kill the cancer cells. Examples of drugs include pembrolizumab, nivolumab, dostarlimab and ipilimumab. Similarly, these drugs can also be used along with chemotherapeutic drugs such as capecitabine, 5-FU, oxaliplatin and irinotecan to maximise the treatment outcome (Xie et al. 2020).

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Limitations of Medication-Based Therapies Against CRC

In addition to the toxicity of chemotherapeutic drugs that limit the dosage and frequency of treatment, tumour-penetrating capacity, tissue distribution, stability and bioavailability of the drugs also play important roles in determining the success of the cancer therapy. While acting as the main component of tumour microenvironment, tumour is also surrounded by non-cancer or stromal cells such as fibroblasts, immune cells, mesenchymal stem cells as well as various types of extracellular matrix (ECM) (Gallo et al. 2021). These components also play important roles in supporting the growth and progression of the tumours and have also been identified as one of the major obstacles that complicate and resist cancer treatment. Some of the mechanisms include serving as a multilayer physical barrier enriched with the ECM to block drug penetration and the drug targets as well as directing the soluble mediators such as cytokines and chemokines to block the treatment (Gallo et al. 2021). This poses a huge challenge especially for those large-sized drugs with weak tissue-penetrating capacity. Next, the conventional chemotherapeutic drugs such as 5-FU which is a nontarget-specific drug can be further affected by the stromal cells. Due to the tissue architecture within the tumour, the drug may not be successfully delivered to the tumour sites and only retain at certain nonspecific sites, this may then give rise to another issue which is off-target toxicity. In another scenario, drugs that reach the tumour sites have to translocate through the interstitial space to reach their target cells, but this may be blocked by the endothelial cell layer which lines the blood vessels, rendering the failure of drug delivery. However, it has been known that the endothelial cell layers are rather poorly aligned in the tumour sites, hence resulting in the ‘leaky’ capillaries to allow the transendothelial transport of drugs. Under intratumoural pressure, the condition surrounding the tumour is often hypoxic and highly acidic due to the low availability of oxygen and accumulation of lactic acids (Gallo et al. 2021). This may affect the cellular uptake and the tissue distribution of the drug. The low pH condition may also affect the stability of the drug at the tumour site, and hence resulting in the reduced tumour-killing action. Aside from the ones stated above, the drugs commonly used for cancer therapy are inefficient in eradicating cancer cells as they often exhibit poor water solubility, inefficient biodistribution, and are hydrophobic (Choukaife et al. 2022). This, in turn, will prompt the need to increase the frequency of therapy and dosage requirement, which subsequently will lead to devastating adverse side effects. To summarise, conventional anticancer drugs have so far demonstrated certain limitations which impede the success rate of the therapy.

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Development of Nanocarriers Against Cancer

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Properties of Nanocarriers

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As highlighted in the previous section, several issues with the conventional drug delivery method can be improved using various types of nanomedicine. Nanomedicine is the application of nanomaterials or nanoparticles which are about 1–100 nm to medicine. According to de SL Oliveira et al. (2021), nanoparticles (NPs) are classified as complex molecules which can be functionalised with different types of cores (chemical materials), elements (surfactants or ions) and/or nuclei (central portion). This rich surface chemistry allows for various surface modifications including to make them pH-, temperature-, stimuli-responsive, enable drug and cargo loading as well as the flexibility which enables size and shape modifications. These flexibilities could partly tackle the challenges of conventional drug therapy, either via enhancing absorption and tumour penetration or stabilising drug formulation. For example, the smaller NPs are known to effectively permeate the tumour and hence kill the cancer cells more potently. The possible modifications of nanoparticles could also be conjugated with anticancer drugs, serving as a drug nanocarrier to make the drug more stable and effective under the stringent tumour microenvironment. They are highly attractive for drugs that have poor water solubility and pharmacokinetics and cause severe side effects. These properties make NP a strong candidate as nanocarriers in the drug delivery system (DDS) for treating cancer (Pushpamalar et al. 2021; Neerooa et al. 2021).

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To date, there are various types of nanocarriers that can be used for cancer treatment and they each have various ways to formulate them. Generally, however, the nanostructure of the NPs is associated with the active drugs. The type of materials to synthesise these nanocarriers can be categorised into two: organic (e.g., lipid-based, polymer-based) and inorganic (e.g., metal, quantum, nanotube, silica) (Fig. 1). Hybrid nanocarriers, on the other hand, contain a mixture of organic and/or inorganic to receive the benefits of both materials (de SL Oliveira et al. 2021).

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Types of Nanocarriers

2.2.1 Organic Nanoparticles Lipid-based nanoparticles (LNPs) constitute a diverse group of nanoparticles that are created from the lipid bilayers, and they often consist of the addition of amphiphilic lipids to water or other hydrophilic liquids. This allows for the encapsulation of both hydrophilic and hydrophobic drug molecules to be either dissolved in the liquid or lipid solution to form NPs (García-Pinel et al. 2019). They demonstrate low rate of toxicity, can control the release of drugs and increase the drug half-life. To date, liposomes, solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs) are the few LNPs that garnered the most attention in the drug discovery of cancer treatment.

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Fig. 1 Illustration of the two big categories of NPs, organic or inorganic. They are classified in accordance with the type of material used in their formation. They offer excellent potential to act as DDS for colorectal cancer

Liposome is one of the most extensively studied lipid-based nanoparticles as DDS due to its biodegradability and biocompatibility behaviour. They are also capable of decreasing the toxicity of anticancer agents while also improving the efficacy of their anti-tumour properties (Yingchoncharoen et al. 2016). Various methods can be used to generate liposomal NPs which include sonication, extrusion, reverse-phase evaporation and solvent injection. Micelles (which can be made up of either lipids or polymer) are composed of an amphiphilic lipid head and a hydrophobic single-tail region, forming a micellar nanostructure via supramolecular selfassembly. The hydrophilic shell plays an important role in supporting and stabilising the hydrophobic core, which carries and protects the drug in an aqueous solution (Galetti et al. 2019; Mkam Tsengam et al. 2022; Yadav et al. 2019). SLN is a relatively new formulated colloidal nanocarrier which mainly constitutes physiological lipids, ranging between 50 and 1,000 nm, and exists as a solid at both room and body temperature (García-Pinel et al. 2019). These lipids, namely fatty acids, and simple and complex glyceride mixtures are used to form the matrix of drug encapsulation, which is stabilised by polymers or surfactants. Development of SLNs as a DDS, however, poses some challenges due to their modest drug expulsion and loading capacity as crystallisation occurs during storage (Rajabi and Mousa 2016). Therefore, nanostructured-lipid carrier (NLC) was formulated to tackle the limitations of SLNs, making it a second-generation LNP (Chauhan et al. 2020). Constituting both solid and liquid lipids, it is typically composed of glyceryl

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dioleate, ethyl oleate, isopropyl myristate or glyceryl tricaprylate (Naseri et al. 2015). Besides having a higher drug loading capacity, the liquid lipids in the NLC improve the formulation stability by preventing lipids from crystallising which stops the drug from expulsing during storage (Scioli Montoto et al. 2020). Polymeric nanoparticles (PNPs) have attracted significant attention when studies have exhibited improved drug efficacy by minimising the side effects of anticancer drugs and making these drugs more site-specific (Haider et al. 2022). PNPs are formed when monomers or polymers are polymerised into solid colloidal systems that encapsulate the drug. Their shape and size are highly dependent on the preparation method. Being stable, biocompatible and cheap with low toxicity trait, they are one of the most used systems for drug delivery. PNPs are further divided in accordance with their structural features and formulation process. Ones commonly studied for DDS are nanogels, polymersomes, dendrimers, polymeric micelles and nanocapsules (Haider et al. 2022). Nanogels, also known as hydrogels, are NPs made up of cross-linked network of different water-soluble polymers that can retain large amount of water. Due to its high degree of fluid retention, which resembles biological tissues, nanogel is well known for its high biocompatibility for cancer treatment (Haider et al. 2022). Polymersomes, made of amphiphilic polymer, mimic the physical properties of liposomes, in which they both are composed of a hydrophilic head with a hydrophobic bilayer core, and can self-assemble into vesicles (Rideau et al. 2018). Their main role as a nanocarrier is to encapsulate and protect the anticancer drug. Dendrimers are three-dimensional (3D) PNPs that are made up of branched monomers with symmetrical layers surrounding their central core (Brar et al. 2021). Its central core is a spherical structure made of repeating carbon elements with repeating units branching from the central core. The free space within its 3D structure was thought to mediate the encapsulation of drugs of its most studied clinical applications is increasing the solubility of poorly soluble drugs (Sherje et al. 2018). PNPs can also self-assemble into biphasic spherical structures, such as nanocapsules, which are generally formed with a core (inner material) and a shell (outer layer) (Ghosh Chaudhuri and Paria 2012). It is important to note that most of these nanocarriers despite being synthesised from different materials can be modified to carry drugs or other cargoes that could target and kill cancer cells. These PNPs are typically made up of synthetic polymers via synthetic methods such as nanoprecipitation, electrospray, emulsification and particle replication in nonwetting templates (PRINT).

2.2.2 Inorganic Nanoparticles Among the metal NPs, the well-characterised and most studied NPs are gold and silver NPs. One of the attractive properties of gold NPs is their photothermal properties which are suitable for cancer treatment. When used together with a laser, the gold nanoparticles or the loaded drugs can be released in a controlled manner to specifically target and kill tumour cells without inducing nonspecific

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toxicity (Mitchell et al. 2020). On the other hand, silver NPs are mainly found to kill cancer cells by forming reactive oxygen species (ROS) or inducing apoptosis. However, silver NPs are known for their toxicity, hence limiting their use in treating cancer clinically. This can be overcome by generating more biocompatible silver nanoparticles either by constructing core-shell layers or by using it as a drug nanocarrier (Sun et al. 2021). Meanwhile, silica NPs remain one of the most used inorganic NPs for DDS due to their physiochemical properties which are versatile. Mesoporous silica NPs (MSNPs) have great biodegradability, high drug-loading capacity and low cytotoxicity. Being rich with silanol groups on their surface, MSNPs can interact with different functional groups and molecules such as metals, polymers or ligands to adjust the properties and functions of the MSNPs (de SL Oliveira et al. 2021). Nanotubes, in particular carbon nanotubes (CNTs), have amassed interest due to their multifunctional structure and properties. CNTs are carbon atoms organised in a honeycomb nanostructure to form a tubular shape. They are typically categorised into two based on carbon atom numbers: multi-wall and single-wall CNTs, both having different properties which impact their function as DDS. As their unique architecture allows for high surface area for conjugation and/or drug loading, and tumour penetration, they are an ideal nanocarrier for targeted cancer therapy. Quantum dots NPs (QDNPs) are semiconductor nanocrystals made up of heavy metal core and outer shell from periodic groups of ii-vi, such as cadmium selenide (cdSe) (Devi et al. 2022). They have unique photographic qualities: size-tunable light emission, wide absorption coefficient and high excitation of fluorescence colours. Though this makes them particularly useful in biomedical applications such as bioimaging for drug research and diagnostics, their role as cargo for drug delivery remains a challenge due to their poor water solubility and biocompatibility. The surface composition of QDNPs, however, can be chemically modified with organic biomaterials or inorganic metals to change their physiochemical properties and allow them to fit in the biological environment better, commonly known as hybrid NPs (Devi et al. 2022).

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2.2.3 Hybrid Nanoparticles Polymer-lipid hybrid NPs are an excellent example of hybrid nanocarriers. The drug is encapsulated in a hydrophilic/hydrophobic polymeric core and surrounded by a lipid layer (Rao and Prestidge 2016). They were developed to overcome the shortcomings of both materials, thus enhancing the biodistribution of the drug in the system. They inherit polymeric nanocarrier characteristics such as being rich in surface chemical modification and profound drug release profile and lipid-based nanocarriers’ efficient drug loading capacity and biocompatibility. The improved stability and biocompatibility make them an efficient nanocarrier in cancer therapy (Rao and Prestidge 2016). Table 1 summarises various types of NPs which show promising anticancer action against colorectal cancer.

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Polymerbased NPs

Type of nanosystem Lipidbased NPs

β-Cyclodextrin-alginate (β-CD, AL) nanogels

AS1411 aptamer conjugated, PEG-peptide-PLA polymersomes

Tf-binding peptidefunctionalised polymersomes

Dextran-folic acid SLNs

Resveratrol-stearate SLNs

Folic acid liposomes

Description Magnetic cellulose nanocrystals (MCNC)-PE Thermo-sensitive liposomes

5-Fluorouracil

7-ethyl-10-hydroxy camptothecin (SN38)

Doxorubicin

Doxorubicin

Doxorubicin

5-Fluorouracil

Doxorubicin

Anticancer agent Curcumin

In vitro CT26 colon cancer cell line In vivo CT26 tumourbearing BALB/c mice In vitro HCT116 human colon cancer cells In vivo BALB/c female mice In vitro C26 mouse colon cancer cells In vivo C26 subcutaneous tumour model BALB/c mice In vitro HT29 colon cancer cells

Model In vitro HCT116 colon cancer cell line In vivo BALB/c female mice In vitro CT26 colon cancer cell line In vivo BALB/c male mice In vitro HT29 CRC line

Enhanced target-specific drug release via polymer degradation, improved cellular uptake and promote apoptosis

Improved tumour growth inhibition by nucleolin-targeting and drug-controlled release by MMP-2 protein

Improved cellular uptake in TfR overexpressing cells and increased tumour accumulation and inhibition

Enhanced antineoplastic activity of doxorubicin Prevented systemic absorption and improved drug accumulation at the target site

Therapeutic effect Increased apoptotic-mediated cell death Enhanced tumour-associated M1 phenotype macrophage activities Enhanced cytotoxicity activity of 5-FU

Table 1 Effect of different types of NPs with their associated therapeutic response on colorectal cancer

Hosseinifar et al. (2018)

Ramezani et al. (2020)

Wei et al. (2020)

Serini et al. (2018) Shen et al. (2019)

References Low et al. (2019) Ektate et al. (2018) Moghimipour et al. (2018)

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Inorganic NPs

Superparamagnetic iron oxide/ calcium carbonate/polyethylene glycol (SPION-CaCO3-PEG) mesoporous silica

Alkyl-PEG-cholesteryl chloroforate-modified PAMAM dendrimers

Poly(amidoamine) (PAMAM) dendrimers

Protamine nanocapsules

Hyaluronic acid coated-folic acid functionalised (HA-FA) alginate nanogels Anisamide-eudragit S100 polymeric nanocapsule

Doxorubicin

Doxorubicin and TRAIL plasmid

Gallic acid

In vitro C26 mouse colon cancer cells In vivo C26 BALB/c male mice In vitro CT26 cancer cell line In vivo CT26 subcutaneous tumourbearing BALB/c nude mice

In vitro HCT116 CRC carcinoma and HT29 CRC adenocarcinoma

SW480 human CRC cells

In vitro HT29, HCT116 and Caco-2 cells

Thymoquinone

Curcumin and miR-145

In vitro HT29 colon cancer cells

Oxaliplatin

Comparable cytotoxicity activity with free drugs but exhibited reduced side effects

Enhanced target-specific drug release, increased drug half-life and promote apoptosis Improved drug solubility from encapsulation, increased cytotoxicity on sigma receptor overexpressing in HT29 cells Reduced cell migration and proliferation with increased cancer-killing activity in curcumin and improved cellular uptake of miR-145 Improved controlled release of drugs, promoted inhibition of cell proliferation and migration, cellular uptakes, apoptotic signalling and release of pro-inflammatory cytokines in HCT116 cells Increased cytotoxicity of drug and inhibit tumour growth rate

(continued)

Näkki et al. (2019)

Pishavar et al. (2019)

Priyadarshi et al. (2021)

ReimondezTroitiño et al. (2019)

Ramzy et al. (2020)

Shad et al. (2020)

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Hyaluronic acid-PEG (HA-PEG) conjugated multi-walled carbon nanotubes

PEG-survivin shRNA expressing plasmid (iSur-pDNA) tagged with AS1411 DNA aptamer Mesoporous silica

177Lu-labelled Au NPs

PEI-folic acid (PIF) graphene quantum dot NPs

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Description Polydopamine-coated goldsilver (PD/Au-Ag) metal NPs

Eudragit RS 100 modified quantum dot NPs

Type of nanosystem

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Table 1 (continued)

Gemcitabine

Camptothecin

Cetuximab

Doxorubicin and EFGR (epidermal growth factor receptor)

Curcumin

Anticancer agent Photothermal therapy

In vitro C26 mouse colon cancer cells In vivo C26 subcutaneously tumour-bearing female BALB/c mice In vitro HT29 colon cell line In vivo SpragueDawley rat

In vitro HCT116 cancer cell lines In vivo HCT116 subcutaneous tumourbearing BALB/c nude mice In vitro HCT116, HCT68 and SW620 colon cancer cell lines

Model In vitro HCT116 cancer cell lines In vivo HCT116 subcutaneous tumourbearing BALB/c nude mice In vitro HCT116 cancer cell lines

Improved drug’s controlled release, enhanced inhibition of cell proliferation due to internalisation by receptor-mediated endocytosis, increased cytotoxicity

Increased HCT116 cell sensitivity towards drug’s growth inhibitory effect, preventing tumour formation Improved drug’s controlled release, apoptosis initiation and in vivo anti-tumour effect. Increased cellular uptake via calltargeting AS1411 DNA aptamer

Enhanced inhibition of cell proliferation and promoted apoptosis Increased NP cellular uptake, enhanced tumour growth suppression

Therapeutic effect Promoted caspase-dependent cell death and apoptosis from mitochondrial damage and autophagy

Prajapati et al. (2019)

Babaei et al. (2020)

Shabbir et al. (2021)

Lo et al. (2020)

Khan et al. (2020)

References Hao et al. (2019)

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Various biomaterials can be used in the generation of drug nanocarriers. This review will focus on the most promising ones in the subfield of colorectal cancer treatment, namely chitosan, xanthan gum, cellulose and alginate. Chitosan is a natural polysaccharide derived from chitin and is made by deacetylation to form d-glucosamine and N-acetyl-d-glucosamine linked by 1-4-β-glycosidic bonds (Ways et al. 2018). Chitosan has mucoadhesive properties which makes it suitable for drug release in various epithelial systems including intestinal, nasal, eye and pulmonary. Referring to the structure, chitosan can form covalent and hydrogen bonds due to the presence of –NH2 and –OH functional groups, resulting in various possibilities of chitosan derivatives. These functional groups are also essential in determining the solubility of chitosan. Under low pH, the chitosan becomes positively charged as its amine groups are protonated. The positively charged amino groups from the polymer can then form hydrogen bonds and strong ionic interactions with the negatively charged epithelial surface of the mucus (Ways et al. 2018). For example, a chitosan lactate gel was successfully developed and patented for the controlled release of lactic acid onto the vaginal mucosa for vaginal maintenance therapy (Sandri et al. 2012). In another study conducted by Cerchiara’s group (2015), they found chitosan synthesised using spray-drying method was an effective nanocarrier for vancomycin in treating serious colorectal inflammation. Thus, chitosan is a promising candidate to act as a nanocarrier for the treatment of colorectal cancer. Xanthan gum is a high molecular weight heteropolysaccharide produced by Xanthomonas campestris. This material is a polyanionic polysaccharide, with pentasaccharide subunits, and glucuronic acid and pyruvic acid side chains (Malik et al. 2020). It has been extensively used for synthesising nanocarriers due to its outstanding biochemical properties, exhibiting excellent biocompatibility, water solubility and maintaining high functionality under astringent environments such as high salt or acid (Kang et al. 2019). Xanthan gum has been developed to act as a drug-controlled released matrix polymer for oral administered products. In a study, they developed aceclofenac tablets coated with xanthan gum for colon-targeted therapy. They found that the tablets were able to resist drug release in the gastrointestinal tract but could dissolve very well in the colon. It was also noted that the drug release was more efficient under a weak acidic/neutral pH rather than a highly acidic environment, which makes it a suitable colon-targeting agent (Singhvi et al. 2019). Cellulose is the most abundant natural polymer found in nature; it is made up of β-1-4 linked glucopyranose unit, forming a high-molecular-weight linear homopolymer. They are highly polymorphic, and their properties may differ due to the variety of sources and different production/extraction methods to synthesise cellulose (Lugoloobi et al. 2021). They are widely used in drug delivery systems mainly due to their abundance and low cost in manufacturing alongside their high degree of

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flexibility which allows for modification in their solubility and gelation (Lugoloobi et al. 2021). Cellulose is often functionalised to form cellulose ethers or cellulose esters as they have poor solubility due to their intermolecular hydrogen bonding. Cellulose ether derivatives are commonly favoured as nanocarriers for oral dosages due to their swelling capacity, which allows the hydrogel layers to control the drug diffusion and delivery (Amalin Kavitha et al., 2020). Recently, Li et al. (2019) successfully synthesised cellulose nanofiber as a nanocarrier for quercetin, an antioxidant, which showed a higher delivery profile than control. Cellulose nanocrystals are also synthesised which offer additional advantages compared to the original nanocarriers (Yusefi and Shameli 2021). In another study, cellulose nanocrystals were able to encapsulate curcumin for antimicrobial application and improve the stability of the formula at different pHs (Asabuwa Ngwabebhoh et al. 2018). Another biopolymeric material that has been widely used in drug delivery is alginate. Alginates are negatively charged salts that came from alginic acid, composed of 1,4-linked β-D-mannuronic acid (M) with α-L-glucuronic acid (G) that are formed in an irregular block-wise pattern (He et al. 2020; Osorio et al. 2020). Similar to chitosan, alginate has excellent mucoadhesive properties which allow its use as nanocarriers in various epithelial cancers. Sookkasem et al. (2015) formulated alginate beads, on a macro scale, which could encapsulate curcumin and allow colon therapy to be more target specific. The alginate beads prevented the rapid physiological clearance of curcumin in the upper gastrointestinal tract and were only released in the colon. In another study in 2018, Freitas and team designed mucoadhesive sericin-alginate particles which were thought to improve sustained drug release possibly via a dissolution mechanism (Freitas et al. 2018).

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This section focuses on the current update of nanocarriers that show potent killing against colorectal cancer. Over the years, studies have shown that colon cancer cells overexpress several proteins and cancer-specific molecules which make them as ideal therapeutic targets. These include CD98 (Xiao et al. 2018), CD44 (Jiang et al. 2018), galectins (Liu et al. 2018), biotin receptors (Lin et al. 2018) and microRNAs (miRNAs) (Zheng et al. 2018). Recent development of nanocarriers was also designed to target these molecules. On top of that, FDA-approved anticancer drugs such as 5-FU, irinotecan, oxaliplatin, doxorubicin, bevacizumab and capecitabine as well as other cancer-killing compounds such as curcumin, silymarin and colchicine were also either encapsulated or conjugated with the nanocarriers to improve the treatment efficacy. CD98 receptors overexpressed on the apical membranes of colon cancer cells, Xiao et al. (2018) synthesised a CD98-siRNA and camptothecin-loaded PEGylated Fab-NPs embedded in a hydrogel for colon targeting using mouse models. The efficacy of combination drug was higher than the nanoparticles containing a single drug due to higher drug internalisation into the tumour cells. In another study, Jiang

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et al. (2018) prepared hyaluronidase (HA)-conjugated mesoporous silica NPs loaded with 5FU and demonstrated their cytotoxicity to colon cancer cells. HA on the surface of NPs targeted the CD44 receptors overexpressed in the cancer cells. Similarly, galectins are overexpressed and found to play crucial modulatory roles in colon cancer. Liu et al. (2018) developed 5FU-loaded mesoporous silica NP-based galactosylated chitosans for colon cancer-specific drug delivery and showed potent killing against the cancer cells compared to the free 5FU in vitro. On the other hand, Lin et al. (2018) developed poly (ethylene glycol) and biotinmodified Dox-loaded silica NPs which target biotin receptors. The tumour cells were effectively killed in both HCT116 colorectal cancer cell line and tumour-bearing mice. In addition to cell receptors, some miRNAs are also found to regulate cancer events. Zheng et al. (2018) synthesised poly (D,L-lactide-co-glycolide)/poly (L-lactide)-block-poly(ethylene glycol)-folate polymer NPs that were loaded with miR-204-5p and demonstrated their anticancer effects on colon cancer cells and xenograft colon tumour models in vivo. Curcumin, a substance in turmeric plants, has exhibited various pharmacological properties such as antimicrobial (Teow et al. 2016) and anticancer actions (Tomeh et al. 2019). To further enhance the anticancer activity against colon cancer cells, curcumin has been encapsulated into various types of nanocarriers. For instance, Alkhader et al. (2018) synthesised a chitosan-pectinate NP system (CUR-CS-PECNPs) which could enhance the oral bioavailability of curcumin by protecting it from gastric degradation. A pH-responsive xylan-curcumin prodrug NPs could release the loaded curcumin at acidic pH and improve the anticancer killing against colon cancer cells compared to curcumin alone (Sauraj Kumar et al. 2018). Interestingly, codelivery of curcumin and 5-FU from a xylan-SS-curcumin redox-sensitive prodrug NPs could effectively inhibit colon cancer cells (Kumar et al. 2020). The same research group also constructed xylan-5-FU-1-acetic acid conjugates (Kumar et al. 2017) and amphiphilic xylan-stearic acid-based NPs (Kumar et al. 2019) which improved the anticancer activity of 5-FU against colon cancer cells upon delivery. AbouAitah et al. (2020) generated a mesoporous silica NPs functionalised with phosphonate groups and folic acid chitosan-glycine complex to deliver colchicine against colon cancer cells. Colchicine targeted and inhibited the cancer cells by inducing apoptosis. In another study, an epidermal growth factor- (EGF-) functionalised poly(lactic-co-glycolic acid) (PLGA) NPs successfully deliver 5-FU and perfluorocarbon for effective treatment of colon cancer. The functionalised NPs were able to selectively recognise specific receptors present on colon cancer cells and inhibit tumour growth (Wu et al. 2020). Marcelo et al. (2020) used mesoporous NPs encapsulating fluorescent silica quantum dots (SiQDs) to act as cargo for doxorubicin in killing colon cancer cell line, HCT116 and HT29 cells. They found that MSNP-doxorubicin showed the most significant cytotoxic effect in both cell lines, with a higher uptake against HCT116, while free drug doxorubicin exhibited the lowest uptake. This confirms that doxorubicin-loaded MSNPs can elicit significant cancer-killing properties. On the other hand, the nanocarrier with the luminescent SiQDs (SiQD-MSNP-doxorubicin) was postulated to undergo cellular

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internalisation but resisted immediate drug release of doxorubicin, showing possibilities of controlled drug release of doxorubicin (t > 72 h). Using an oxaliplatin-loaded PLGA microsphere, Lagarce et al. (2002) showed high entrapment efficiency (up to 90%) and diverse release profiles, which collectively improved the efficiency of local tumour treatment. Liu et al. (2015) loaded 5-FU onto a hyaluronic acid (HA)-conjugated silica nanocarriers for colon cancer treatment. The nanocarrier could attach and accumulate in colon cancer cells due to their HA surface alterations, this resulted in enhanced antitumour action and decreased side effects as compared to non-modified nanocarriers. Lee et al. (2006) generated docetaxel-loaded biodegradable dendrimers with multiple attachment sites capable of releasing drug in a controlled manner. These drug-loaded dendrimers were ten times less toxic than free docetaxel in the colon cancer treatment.

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Over the last few decades, nanomedicine has emerged and amassed tremendous growth in its potential to revolutionise cancer therapy. Massive investments, in terms of finance and labour, have been exhausted to design, research and develop NPs in hopes of implementing nanomedicine into the healthcare system. However, very few made it to the clinical trial phase and even fewer were approved for clinical use (Desai 2012). In this section, the current challenges and limitations of NPs development are discussed. To succeed in the clinical translation of nanoparticle-based therapeutics, an understanding of the biodistribution, pharmacokinetics, safety mechanisms, and mechanism of action of NPs must be fully established. However, the long-term inflammation, toxicity and carcinogenesis of these NPs are not fully understood yet (Desai 2012). This uncertainty possesses one of the biggest hurdles for nanoparticlebased drug carriers to progress onto clinical trials. Without having a clear understanding on the route of NP delivery and outcomes, patients undergoing this therapy would have increased the risk of developing unforeseen adverse reactions. Hence, it is necessary to develop in vitro and animal models tailored to investigate the main goal of NP-based drug-delivery systems which is to maximise the potency and efficacy of the therapy while reducing systemic side effects (Park 2013). In order to achieve this objective, it is crucial to use these models to (i) study about the interaction between NPs and cells, (ii) optimise the transcytosis and uptake rate of NP into the tumour microenvironment, (iii) design NPs that are able to overcome the biological barriers present in the body such as the reticuloendothelial system and renal system and (iv) determine the clearance rate and degradation of nanocarriers (Park 2013; de SL Oliveira et al. 2021). Essentially, in-depth studies on these grey areas will ensure that future nanoparticle-based drug carriers would have a smooth transition from preclinical studies to clinical settings and subsequently be validated for clinical use. Another limitation of existing nanoparticle-based drug carriers is their delivery efficacy and bioavailability which severely limits their therapeutic potency. To

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increase the delivery efficiency of nanoparticle-based therapeutics to the tumour site, the properties of NPs must be exploited or modified to extend circulation in blood (bioavailability) and minimise non-specific clearance rate by phagocytosis and the liver (Sabit et al. 2022). For instance, it was found that non-spherical NPs have higher bioavailability and are less vulnerable to mononuclear phagocyte system (MPS) sequestration in blood vessels compared to their counterpart (Ye et al. 2018). At the same time, functionalisation of NPs with active ligands specific to tumours will ensure maximum accumulation in tumour microenvironment compared to other sites which further limits free drug toxicity (Manzoor et al. 2012). Moreover, functionalisation NPs are shown to have decreased serum protein absorption and are resistant to macrophages which also enhances their bioavailability (Ye et al. 2018). Hence, further research and modifications should be done on existing nanoparticlebased drug carrier to develop drug carriers that protect the cargo (i.e., drugs) from degradation, phagocytic activities and non-specific clearance. By having long bioavailability, lower drug dosage is required. This will reduce the incidence and severity of side effects, and lower cost of treatment, contributing to better treatment outcome and high quality of life post-treatment.

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The use of biocompatible drug nanocarrier is a promising treatment method for colorectal cancer due to its ability to effectively penetrate the targeted tumour area and delivery anticancer drugs without compromising normal cells. NPs have rich surface chemistry and flexibility in size and shape modifications which makes them ideal drug carriers to overcome the limitations of conventional drug delivery methods. Despite having many challenges in understanding the mechanism of actions and the delivery methods of NPs, it is crucial to push forward with the development of drug nanocarriers which maximises the potency of anticancer drugs in selectively killing colorectal cancer cells. Future studies should be done to elucidate the mechanisms of NPs and the long-term effects of NP usage in in vivo models and clinical trials to ascertain the safety and efficacy of nanoparticle-based therapeutics for clinical use. Nevertheless, as nanomedicine is a relatively new field, caution must be observed in conducting clinical studies while taking into account patients’ safety and ethics. With continuous development in nanomedicine, it is with great hope that advances in drug nanocarriers will improve the life expectancy and quality of life of colorectal patients, and cancer patients as a whole.

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Challenges of Onco-therapeutics in Early-Onset Colorectal Cancer Katie Doogan, Alexandra M. Zaborowski, and Des C. Winter

Abstract

The incidence of colorectal cancer among adults aged less than 50 is rising. Patients with early-onset colorectal cancer are more likely to present with advanced disease stage with requirements for multimodal treatment. Younger patients appear to have higher rates of treatment-related toxicities, giving rise to unique challenges for these patients. The impact of treatment-related morbidity on quality of life can be overlooked. Survivorship issues are increasingly relevant owing to the potential for long-term survival following treatment. Striking a balance between treating early-onset colorectal cancer while preserving bowel, bladder, sexual function, and fertility is challenging yet imperative. Keywords

Chemotherapy · Early-onset colorectal cancer · Immunotherapy · Radiotherapy

1

Introduction

The incidence of early-onset colorectal cancer (age younger than 50) has increased globally. Distinct clinical and pathological patterns have emerged. Patients with early-onset colorectal cancer (EOCRC) frequently display unfavourable histopathological features and have advanced disease stage at presentation (Zaborowski et al. 2021a). Despite this, they have better or equivalent short-term and long-term survival than patients with late-onset disease (Kneuertz et al. 2015; Saraste et al. 2020; Zaborowski et al. 2021a; AlZaabi et al. 2022). Young patients are also more

K. Doogan (✉) · A. M. Zaborowski · D. C. Winter Centre for Colorectal Disease, St Vincent’s University Hospital, Dublin, Ireland e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2023_148 Published online: 15 February 2023

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likely to receive neoadjuvant chemoradiotherapy and adjuvant chemotherapy than their older counterparts and are also more likely to receive neoadjuvant and adjuvant therapies outside of current treatment guidelines with minimal adjusted survival gain (Kneuertz et al. 2015; Zaborowski et al. 2021a). The administration of intense treatment may be related to better overall performance status and more advanced disease stage at presentation (Bahadoer et al. 2022). Receiving a cancer diagnosis at a younger age comes with unique challenges compared to those in older age groups. Obstacles facing young patients with CRC arise not only from the diagnosis and disease process but also from the prescribed treatment. Patients with EOCRC are more likely to develop both disease- and treatment-related long-term side effects (AlZaabi et al. 2022). These distressing consequences are often under-recognised, with limited commentary in the literature. Issues particularly pertinent to the young patients include fertility and family planning concerns, responsibilities to young children, disruption to academic, working life and career ambitions, financial instability, and psychological impacts including a premature confrontation with mortality and a sense of lack of life completion or attainment of life goals/milestones (Perl et al. 2016; AlZaabi et al. 2022; Eng et al. 2022). Younger age is a significant predictor for increased financial burden (Simard et al. 2019). Young patients also report more psychological symptoms compared to their older counterparts, including higher anxiety levels and negative body image (Bailey et al. 2015). With the focus on achieving disease control, the impact of treatment-related morbidity on quality of life may be overlooked. Patient expectations that complications may be only mild or temporary can make it more difficult to cope with severe symptoms (Lim et al. 2021). Furthermore, survivors can attribute symptoms with potential disease progression or recurrence triggering distress (Lim et al. 2021). As survivorship improves, it is pertinent to consider quality of life when deciding on treatment strategies. Clinicians should understand the challenges of onco-therapeutics in managing early-onset colorectal cancers.

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Total Neoadjuvant Therapy and the Potential for Nonoperative Treatment

Trimodal treatment for rectal cancer (surgery, radiotherapy, and chemotherapy) achieves good local control rates and long-term survival; however, multimodal treatment is also associated with significant morbidity. Many long-term sequelae are attributable to surgical resection. Patients achieving a pathological complete response (pCR) following neoadjuvant therapy have lower local recurrence and improved survival rates compared with those with a non-pCR (Park et al. 2012). This therefore questions the added benefit of surgery in those who achieve a pCR. Nonoperative management for patients with rectal cancer who achieve complete clinical response following neoadjuvant chemotherapy is feasible, and surgical resection may not lead to improved outcomes in select cases (Habr-Gama et al. 2004). Total neoadjuvant therapy (TNT) where patients receive full-dose

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chemotherapy upfront in addition to radiotherapy has emerged as a potential option to facilitate organ preservation. This approach may be particularly attractive among young patients (Eng et al. 2022). A substantial proportion of patients who undergo surgery for EOCRC report a reduction in quality of life, and functional impairment is unfortunately common. Patients with EOCRC are more likely to undergo more complex operations for early-stage and metastatic disease (Siegel et al. 2020). Dysfunction related to operative intervention can involve bowel-, urogenital-, and fertility-related function (Bailey et al. 2015; Eng et al. 2022). Surgery can also trigger lifestyle changes and inhibit participation in hobbies and socialising (Lim et al. 2021). Therefore, the potential for nonoperative management is an attractive option, enabling younger patients to evade potentially long-lasting bowel, urinary, and sexual dysfunction associated with surgical resection. It is also of significant consideration to EOCRC cancer patients who may want to avoid a stoma, temporary, or permanent and the negative implications it can pose on quality of life, including lower body image and poorer social activity, higher levels of depression and anxiety, more pronounced sexual difficulties, sleep disturbance, and delayed return to work (Baldwin et al. 2009; Lim et al. 2021; Cotrim and Pereira 2008; Traa et al. 2012; Reese et al. 2014; den Bakker et al. 2020). Advances in multimodality therapy have led to significantly improved local control in rectal cancer. TNT should be considered in patients with high-risk locally advanced rectal cancer owing to improved chemotherapy compliance in addition to improved disease control (Zaborowski et al. 2019; Kong et al. 2021). Chemotherapy is poorly tolerated after surgery for rectal cancer, and up to 50% of patients may not complete planned cycles, and 25% may not receive any adjuvant chemotherapy (Bosset et al. 2014). Additionally, TNT appears to have reduced toxicity compared with adjuvant chemotherapy (REACCT Collaborative 2022a, b, c). Radiotherapy has been shown to be more effective in the neoadjuvant setting, with greater compliance rates than in the adjuvant setting (Beets 2021). TNT has ability to overcome suboptimal complicate rates consistently observed with adjuvant therapy (Zaborowski et al. 2019). Consistently poor adherence has been demonstrated. Similar long-term oncological outcomes have been shown for patients with clinical complete response and pathological complete response, adding to the attractiveness of this option in suitable young candidates (Smith et al. 2012; Bahadoer et al. 2022). One of the most promising potential advantages of TNT is the earlier delivery of high-dose systemic chemotherapy aimed at eradicating occult micrometastases and thereby reducing distant failure and improving long-term survival. Distant failure rates remain high in rectal cancer, ranging between 20% and 30%, and remain the most common form of treatment failure in patients with locally advanced rectal cancer. A further potential advantage of TNT is that early optimisation of systemic therapy may increase disease regression and improve pathological response rates. Disease progression during high-dose chemotherapy is suggestive of unfavourable treatment-resistant biology, in which case resection may be futile. In contrast, in patients with marked tumour regression, organ preservation may be an appropriate option, thereby facilitating a more selective practice of surgery (Zaborowski et al. 2019).

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An important advantage of TNT is the potential to avoid radical surgical intervention. Both the safety and feasibility of offering a strict surveillance strategy has been established in patients with a clinical complete response (cCR) after neoadjuvant therapy (van der Valk et al. 2018; Garcia-Aguilar et al. 2020, 2022). However, there remains hesitancy to offer organ preservation treatment to those aged under 50 owing to a potentially higher oncological risk. Recent data comparing young patients to their older counterparts following a watch-and-wait strategy after a cCR demonstrated no additional oncological risk, with comparable disease-specific survival, risk of local recurrence, and distant metastases (Bahadoer et al. 2022). While undergoing surgical resection provides greater oncological certainty owing to histological confirmation of tumour response, a watch-and-wait approach still should be discussed with patients when a cCR is demonstrated after treatment based on current evidence. Limitations associated with a TNT strategy exist. Delay to definitive surgery is a particular concern in patients who have poor response to CRT. In those with little or no response to neoadjuvant CRT, a longer interval to surgery is associated with worse overall and disease-free survival (Deidda et al. 2021). The aim should be to identify poor responder early and proceed with surgery without delay. Adding to this, neoadjuvant therapy can have a negative impact on performance status. Administration of full-dose systemic therapy may significantly affect fitness for surgery, potentially resulting in a prolonged interval to resection and/or higher postoperative morbidity rates (Ludmir et al. 2017). In addition, delaying surgery may allow local disease progression, resulting in more technically challenging dissection, increased perioperative complications, and poorer overall survival (Zaborowski et al. 2019).

3

Challenges and Consequences of Pelvic Radiotherapy

Pelvic radiotherapy can cause bowel, urinary tract, and sexual organ dysfunction. The term pelvic radiation disease (PRD) has been used to describe this, which can be defined as ‘transient or longer-term problems, ranging from mild to very severe, arising in non-cancerous tissues resulting from radiotherapy treatment to a tumour located in the pelvis’ (Andreyev et al. 2011). Symptoms can range in severity, from mild self-limiting conditions to debilitating symptoms with high morbidity. Acute toxicity, occurring in the first 3 months following treatment, encompasses an inflammatory response to radiation exposure, whereas small vessel disease, ischemia, and fibrosis underpin later toxicities (Dalsania et al. 2021). Despite newer, more precise techniques in radiation delivery to the pelvis and rectum, almost all patients still develop acute adverse effects (Tonneau et al. 2021). Gastrointestinal toxicity is a common consequence of pelvic irradiation and can be highly problematic for patients. Symptoms can include rectal bleeding, faecal incontinence, and faecal urgency. Gastrointestinal symptoms have the most significant impact on quality of life after pelvic radiation (Andreyev et al. 2010). Almost all patients receiving radical pelvic radiotherapy have a permanent change in bowel function, with a reduction in quality of life in 50% of patients and severe effects in up

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to one-third of patients (Andreyev 2015). Radiation-induced gastrointestinal symptoms affect as many patients each year as develop inflammatory bowel disease, and as cancer therapy continues to improve with increased survivorship, gastrointestinal radiation toxicity will become a more prevalent health issue (Andreyev 2015; Dalsania et al. 2021). Improvement techniques in radiation therapy in attempts to reduce the amount of exposure to adjacent normal tissue have led to reduction in acute toxicity; however, reduction of later toxicity is yet to be demonstrated (Klopp et al. 2018). Concurrent chemotherapy and prior abdominal surgery contribute to the development of longer-term complications (Dalsania et al. 2021). Toxic effects can be progressive, with the need for operative intervention to manage these complications increasing over time (Andreyev et al. 2011). Bowel dysfunction and unpredictability, due to radiotherapy in addition to surgical intervention, cause heightened anxiety and fear, exacerbating functional limitations and restrictions survivors place on themselves, for example, alternating diet to accommodate bowel function, staying at home, or near a toilet at all times (Lim et al. 2021). Urological complications too occur following pelvic radiotherapy. Due to their location, there is unavoidable radiation exposure of the bladder, urethra, and distal ureters. This can lead to a broad range of debilitating outcomes for patients including radiation cystitis; lower urinary tract dysfunction including frequency, urgency, and nocturia; fistula formation; and stricture formation (Lobo et al. 2018). There does not appear to be any difference in risk of developing urinary dysfunction between short course and long course protocols (Guckenberger et al. 2013; Bregendahl et al. 2015). Radiation-induced damage appears to cause higher rates of dysfunction than that caused by operative intervention (Pollack et al. 2006; Beraldo et al. 2015). Management of these symptoms places a tremendous burden on the healthcare system, disproportionally using more resources. Patients who require admission to hospital under urology services to manage these complications have longer lengths of hospital stays, have more operations, require more emergency surgeries, and have higher readmission rates than other urology patients (Handmer et al. 2020). Reproductive health and fertility are important considerations in young cancer patients, and it is pertinent to address sexual health concerns early to limit wider psychosocial effects (Reese et al. 2018). With the potential for prolonged survivorship in young patients and with sexual health playing a pivotal role in quality of life, it is increasingly important to recognise these challenges. Rectal cancer patients tend to report greater levels of sexual impairment; however, this may be due to combination effects of multimodal treatments including the effects of preoperative radiotherapy (Reese et al. 2018). Sexual dysfunction can act as an obstacle to reproduction. Following radiotherapy, almost 50% of men and 25% of women have difficulty maintaining sexual relations (Brown et al. 2016). Future fertility is exceptionally important to young cancer survivors (Teh et al. 2014). Multimodal treatment with a combination of radiotherapy and chemotherapy will induce higher rates of gonadotoxicity than either modality alone (Vakalopoulos et al. 2015). Pelvic radiotherapy can have detrimental effects on fertility in women, including premature ovarian failure and permanent infertility (Spanos et al. 2008; Eng et al. 2022). Pelvic radiation utilised in the treatment of rectal cancer exposed the ovaries to reasonable

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doses of radiation, with a dose-dependent relationship between radiation and premature menopause (Maltaris et al. 2007; Wo and Viswanathan 2009). In addition, the uterus is also the victim of radiation-included damage. If conception is achieved, pregnancy maintenance is impacted by the development of fibrosis and a reduction in uterine blood flow, uterine volume, and elasticity as a consequence of radiation exposure (Maltaris et al. 2007; Teh et al. 2014). Miscarriage, placental abnormalities, and premature labour are consequences (Spanos et al. 2008; Wo and Viswanathan 2009). In addition, radiation therapy can also lead to sterility in the male patient, due to effects on spermatogenesis (Vakalopoulos et al. 2015; Eng et al. 2022). The impact of treatment on fertility must be explored with patients, and options for fertility preservation discussed, particularly in the era of increased access to assisted reproductive technology. Data on how to best manage these toxicities is lacking, with a limited evidence base for proposed treatments. This is true in the management of rectal tumours and also applies to other pelvic malignancies where radiotherapy forms part of the treatment plan (Dalsania et al. 2021). However, with the emerging increased understanding of the underlying aetiology and molecular mechanisms of radiation-induced toxicity, and ongoing efforts to focus the field of radiation delivery, one can hope this can shed a light on effective treatment mechanisms and reduce the burden of radiation-induced morbidity (Andreyev 2015).

4

Implications of Chemotherapeutics in Early-Onset Colorectal Cancer

Younger patients are more likely to receive more intensive adjuvant chemotherapy with minimal survival gains (Kneuertz et al. 2015; Eng et al. 2022). Currently there is no difference in treatment recommendations between early- and later-onset patients. Multiple acute toxicities can be problematic in young patients including nausea, vomiting, acne, and alopecia (Eng et al. 2022). A consequence of this is the impairment of typical day-to-day functioning. Loss of appetite and changes in taste are also distressing side effects of chemotherapy agents (Ho et al. 2016). Alternations in cognition are also of concern, impacting on occupational, familial, and social life (Schagen et al. 2022). Psychological unmet needs are of greater prevalence than physical unmet needs in advanced colorectal cancer patients receiving chemotherapy (Sakamoto et al. 2017). Lower self-esteem, reduced social functioning, and negative body image all negatively affect quality of life in patients receiving chemotherapy (Eng et al. 2022). Long-term sequelae and chronic side effects of chemotherapy can have a substantial and ongoing impact on quality of life (Eng et al. 2022). Peripheral neuropathy is a leading cause of long-term morbidity, with chemotherapy-induced peripheral neuropathy having a negative association with quality of life in cancer survivors, with the potential for symptoms to persist for years following cessation of treatment

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(Mols et al. 2014; Seretny et al. 2014). Oxaliplatin can cause acute and chronic peripheral neuropathies, with acute neuropathic syndrome occurring in 90% of patients (Simard et al. 2019). There has been a focus on reducing the duration of treatment to reduce the risk of peripheral neuropathy, with cumulative dose the most important risk factor in platinum-based drugs (André et al. 2013; Buccafusca et al. 2019). Neuropathy can impact occupational performance and can delay return to work, with added financial impacts (Lim et al. 2021). Chemotherapy-induced ovarian failure is an essential consideration for women of childbearing age, yet to complete their family unit. Distress from failure to fulfil reproductive goals can persist for several years (Kort et al. 2014). Discussion, even brief, on the impact of treatment on ovarian function and fertility improves patients’ perception of their care (Partridge et al. 2004). Discussion of fertility preservation is imperative with all patients. Unfortunately, there is low use of fertility preservation in early-onset cancer, and this can be even less in patients with EOCRC than other cancer types (Selter et al. 2019).

5

The Growing Use of Cancer Immunotherapy

Increasing understanding of the immunobiology of colorectal cancer has enabled the development of molecularly directed and individualised treatment (Kanani et al. 2021). Immune microenvironment is of crucial importance in disease progression, therapy response, and overall survival in colorectal cancer (Ganesh et al. 2019). Immunotherapy has emerged as an alternative in cancer treatment, with promising results observed in clinical trials (Zaborowski et al. 2021b; Eng et al. 2022). Most early trials focused on metastatic CRC; however, recent data from the phase I/II (NICHE-1) study suggest an upfront role for immunotherapy in operable stages I–III disease. Microsatellite status has important therapeutic implication in CRC as it appears to predict response to immunotherapy with checkpoint blockade (Zaborowski et al. 2021b). Clinical efficacy is predominantly limited to tumours with microsatellite instability, while microsatellite stable tumours are largely refractory (Le et al. 2017). The molecular profile and immune microenvironment of EOCRC remains largely undefined; however, it has been shown that younger patients more frequently have tumours displaying microsatellite instability (Zaborowski et al. 2020). Two recent studies have reported rates of MSI in 26% of early-onset colonic tumours and 12.5% of rectal tumours (REACCT Collaborative 2022a, b, c). Based on this evidence, there is a restricted number of young patients who would achieve a durable response from current immunotherapeutic strategies. Therefore, the critical challenges with immunotherapy in colorectal cancer are whether MSS tumours can be triggered to respond to immune modulation and establish mechanisms to overcome immunotherapy resistance in these subtypes. Radiation and chemotherapy have non-specific effects on tissue and exert cytotoxic effects on normal cells, with immunotherapy overcoming the issue of

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specificity (Johdi and Sukor 2020). However, with the increasing implementation of immune-based therapies into clinical practice, the potential damaging collateral effects on the immune system have come to greater attention (Ramos-Casals et al. 2020; Nappi et al. 2018). Immune-related toxicities are of concern to those who would be eligible to receive immunotherapy agents and are known as immunerelated adverse events (irAEs). Two-thirds of cancer immunotherapy-related complications are related to immune checkpoint inhibitors, with ipilimumab, pembrolizumab, and nivolumab responsible for approximately 60% of cases (Ramos-Casals et al. 2020). Combination therapy with anti-CTLA-4 and anti-PD-1 carries the highest rates of adverse events (Kanani et al. 2021). Dermatological, gastrointestinal, hepatic, and endocrine effects occur most commonly, but irAEs can involve virtually any organ system, with pulmonary, pancreatic, renal, cardiac, neurological, haematological, and rheumatological adverse effects also documented (Ganesh et al. 2019). Typically these adverse events have delayed onset and can have prolonged duration (Ramos-Casals et al. 2020). They are frequently low grade and reversible and, however, can lead to more permanent morbidity, with overall irAE-associated mortality estimated to be in the region of 0.6% (Ramos-Casals et al. 2020). Initial concerns regarding immunotherapy-induced colitis leading to delay in subsequent surgery appear unwarranted (Kanani et al. 2021). Although generally considered less toxic than chemotherapy, due consideration must still be given to the significant unanticipated side effects (Jannin et al. 2019). While the main challenge is to elucidate the mechanisms to provide the benefits of immunotherapy to metastatic colorectal cancer patients that are mismatch repair proficient or microsatellite stable or have low microsatellite instability, other questions remain to be answered. Other key challenges that remain to be addressed include optimal duration of therapy, the benefits of a combination of ICIs and chemotherapy and/or radiotherapy, and how to best monitor response to immunotherapy. Additional challenges of accessibility to these treatments, treatment cost, and reimbursement must be considered.

6

Conclusion

As patients with EOCRC are more likely to present with advanced disease with requirements for multimodal treatment, it appears that they face higher risks for long-term treatment toxicity. Furthermore, following cessation of therapy, patients may not actively seek help for symptoms, as they can believe they no longer have access to healthcare services and support. Striking a balance between treating cancer while preserving bowel, bladder, sexual function, and fertility is imperative. As treatment options expand, quality of life in survivorship is of increasing importance. The impact of an early-age colorectal cancer diagnosis and treatment on the personal life of individuals affected must be acknowledged. Multidisciplinary collaboration is needed to overcome the challenges of treatment in EOCRC.

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Unintentional Weight Loss and Malnutrition After Esophageal Cancer and Treatment Alexis Sudlow, Annelie Shaw, Clare Corish, and Carel W. le Roux

Abstract

Patients with esophageal cancer present a management challenge from a nutritional standpoint. Among patients with esophageal cancer, weight loss and nutritional deficiencies are common with nearly 80% experiencing clinically significant (>10%) weight loss at the time of diagnosis. Nutritional complications arise not only as a result of the underlying disease process itself but also due to subsequent medical and surgical treatment. The implications of malnutrition in this patient population should not be underestimated as it has been identified as an independent risk factor in predicting survival and, in some, may either delay or entirely preclude undertaking surgery with curative intent. In patients who do undergo esophagectomy, nutritional compromise is common with approximately a quarter of patients being unable to meet caloric intake targets 1 year postoperatively and nearly one-third losing 15% of their baseline weight by 3 years. The primary causes of weight loss are often attributed to early satiety, dumping, reflux, and dysphagia; however, the underlying pathophysiology is incompletely characterized. Mechanistic studies looking at other operations which induce profound and sustained weight loss including bariatric surgery have provided critical insights into some of the potential mediators involved in weight loss including changes in gut hormones which modulate satiety and appetite via the hypothalamic gut-brain axis. In addition to physiological changes, there are important considerations with regard to alterations in eating behaviors and

Alexis Sudlow and Annelie Shaw are joint first authors. A. Sudlow · A. Shaw · C. Corish · C. W. le Roux (✉) Diabetes Complications Research Centre, Conway Institute, University College Dublin, Dublin, Ireland e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2023_142 Published online: 2 March 2023

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anatomy. A more complete understanding of the complex interaction between the physiological, psychological, and anatomical changes related to esophageal cancer and treatment may contribute to the development of a patient-centered approach in the management of weight loss and nutritional compromise in both the pre- and postoperative period, including the development of novel pharmaceutical agents to mitigate these changes. Keywords

Esophageal cancer · Esophagectomy · Weight loss

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Introduction

The management of patients with esophageal cancer (EC) is challenging from a nutritional standpoint. The disease process itself, as well as subsequent treatment, has a substantial impact on nutritional status and may have important implications for outcomes. In patients with severe nutritional compromise, this may limit further treatment options, including chemotherapy. There are more than 20 defined histological subtypes of esophageal cancer recognized according to the World Health Organization (WHO) classification system. These are broadly classified according to their origin (epithelial or non-epithelial) and whether they are benign or malignant. Adenocarcinoma (AC) is predominant in North America and Europe (Table 1), attributed in part to specific risk factors contributing to its development, namely, the increasing prevalence of obesity, gastroesophageal reflux disease (GERD), and Barrett’s esophagus (Malhotra et al. 2017), while squamous cell carcinoma (SCC) remains the most common histological subtype within most of Asia. Table 1 Risk factors for adenocarcinoma and squamous cell carcinoma (Domper Arnal et al. 2015; Wheeler and Reed 2012) Risk factor Geographical area Race/ethnicity Gender Alcohol consumption Tobacco Obesity GERD Poor intake of fruit and vegetables Socioeconomic factors Genetic characteristics

AC Australian, North America (United States), Western Europe White > black Males > females ++ +++ ++++ +

SCC Asia Iran, Southeastern Africa, South America Black > white Males > females ++++ ++++ ++

+

++ ++

GERD gastroesophageal reflux disease +: Associated risk -: No associated risk

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Diagnosis and Staging

Patients presenting with symptoms suggestive of EC, highlighted in Table 2, should undergo urgent upper gastrointestinal (GI) endoscopy. Those who have visible changes on direct endoscopic observation (i.e., macroscopic findings), alongside common presenting symptoms, should have an urgent referral to a tertiary specialist center that has experience in managing EC (Allum et al. 2018). Both direct observation at endoscopy and histological confirmation are used to diagnose the primary tumor. Following endoscopy demonstrating the presence of a suspicious lesion, urgent investigations, including computerized tomography (CT), should be arranged to facilitate prompt staging and allow for multidisciplinary team (MDT) discussion. The TNM staging system is a universal system to classify the anatomical extent and spread of cancers. In the absence of metastatic disease, the MDT may then request further investigations such as PET +/- endoscopic ultrasound (EUS) to determine resectability. Staging is paramount in developing a treatment pathway for an individual diagnosed with EC. Due to the risk associated with esophageal resection, in addition to the compromised quality of life postoperatively, it is vital to select candidates suitable for surgical intervention to avoid and minimize futile surgery in those with incurable diseases (Shemmeri and Fabian 2021). Consideration of the significant impact undergoing esophagectomy has on quality of life is an important factor that should be discussed with each patient. Although a multifactorial process, changes in appetite and body weight are important components (Wainwright et al. 2007). The centralization of care has been recognized as a critical factor influencing postoperative outcomes, with better outcomes observed in high-volume centers, where surgical experience is significant and a strong MDT is established (Wouters et al. 2009).

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Treatment and Management of Esophageal Cancer

Immediate, essential MDT planning is vital to the clinical and disease stage-specific management of EC, taking consideration of comorbidities, and is recommended in the European guidelines for the management of EC (Rice et al. 2017). Generally speaking, the management approach for AC and SCC is comparable, with subtle differences in the choice of chemotherapy and/or surgery (Lordick et al. 2016).

Table 2 Presenting symptoms of esophageal cancer (EC) (2020) Common presenting symptoms of esophageal cancer Progressive dysphagia Weight loss Heartburn (unresponsive to medical treatment) Signs of blood loss/anemia

Uncommon presenting symptoms of esophageal cancer Hoarseness Cough Pneumonia

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The management strategy should consider various patient characteristics, including the patient’s fitness for treatment and TNM staging. In patients with early-stage cancer T1/2 with no disseminated disease or involvement of other structures, esophageal resection with curative intent remains the primary treatment strategy. Early tumors may be amenable to endoscopic removal, whereas advanced or progressive diseases are likely to require additional interventions alongside surgery. Advanced EC is often treated with chemotherapy, chemoradiotherapy, surgical resection, and/or an amalgamation of these. Inoperable EC is treated with systemic palliative chemo- and/or radiotherapy (Lordick et al. 2016). Treatment intent should be considered and determined as an MDT whether the patient is suitable for curative treatment is vital. Curative treatment is typically provided to patients who are fit to undergo significant surgical resection and in addition to limited disease burden.

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Survival

Curative treatment (surgical intervention +/- neoadjuvant chemotherapy) for EC is feasible. Although, in the past, postoperative survivorship was poor, advances in surgical techniques and neoadjuvant chemotherapy have extended the survival rate of patients suitable for esophagectomy. In addition, the advancement of healthcare systems and technologies has resulted in improved operative and oncological outcomes. The 5-year survival rate for localized EC has increased to 47% in recent years, due to earlier diagnosis and improved intervention as outlined above (2019).

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Weight Loss and Nutritional Compromise in All Stages of Esophageal Cancer (EC)

Weight loss and nutritional compromise are common in the majority of patients with EC throughout the course of the disease process. At the time of diagnosis, over 80% of patients with EC have experienced unintentional, clinically significant weight loss (>10%) resulting in compromised nutritional status (Steenhagen 2019). This phenomenon begins with the onset of cancer-related symptoms and may persist throughout all stages of disease management whether it be for curative or palliative intent. The effects of nutritional compromise are of particular importance given that malnutrition has been identified as an independent risk factor in predicting survival in patients with cancer and can negatively impact treatment plans, including delaying or even precluding surgery or other treatment modalities in some cases (Steenhagen 2019). Dysphagia, defined as difficulty in swallowing, is generally progressive and is rarely an isolated symptom. Its effects on weight loss are exacerbated by additional symptoms, including anorexia, early satiety, regurgitation, and odynophagia, which are often observed in patients with EC. By the time patients present with clinical symptoms suggestive of EC, many have already lost a significant amount of weight. The mechanical symptoms secondary to EC are often further

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exacerbated by the effect of systemic carcinomatosis and cancer cachexia, resulting in additional weight and lean body loss. Furthermore, these problems may be accelerated by the side effects of treatments such as perioperative chemo-/ radiotherapy, which are delivered as a standard of care for most patients. Within this context, although treatment regimens are highly variable, the emetogenic effects of oxaliplatin-based chemotherapy are profound. Radiotherapy is also associated with a high incidence of side effects, including nausea, vomiting, reflux esophagitis, as well as diarrhea.

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The Impact of Esophagectomy on Nutritional Status

Nutritional compromise following esophagectomy is common. In patients following esophagectomy, between 65% and 70% have inadequate intakes of energy and protein at the time of discharge (Ryan et al. 2006). Furthermore, 25% of patients fail to meet their caloric intake targets at 6 and 12 months after surgery (Haverkort et al. 2012). Changes in nutritional status are most prominent in the first 6 months following surgery, with weight loss ranging from 5% to 12% at this time point (Baker et al. 2016). There is often a plateau in the nutritional deterioration trajectory observed at 6–12 months post-esophagectomy, with weight stabilizing at a new, lower baseline (Baker et al. 2017). By 3 years, in those with no recurrence, nearly one-third of patients have lost more than 15% of their preoperative total body weight (Martin and Lagergren 2009). Body mass index (BMI) at the time of diagnosis has been identified as an important predictor of postoperative unintentional weight loss (Schandl et al. 2019). Although no upper BMI has been identified, patients with a higher BMI lose more weight preoperatively but comparatively less postoperatively (Martin and Lagergren 2009; Ouattara et al. 2012). Furthermore, the use of neoadjuvant chemotherapy and female sex have also been associated with greater weight loss (Martin and Lagergren 2009). Given how prevalent and persistent this issue is, an understanding of the mechanisms of weight loss following esophagectomy is important to the MDT in managing these patients within both the hospital and community settings. Despite the potential implications for patients, there is a relative paucity of studies on the topic, with one systematic review of the nutritional implications of esophagectomy finding that no studies considered the relationship between the inadequacy of nutritional intake and change in nutritional status postoperatively (Baker et al. 2016). Importantly, the implications of these gaps in knowledge can negatively affect clinical practice. The failure to address the problem of weight loss may have a negative impact on both recovery and long-term survival. Several high-quality randomized controlled trials (RCTs) have demonstrated a greater survival benefit in patients who were able to complete perioperative chemo-/chemoradiotherapy in conjunction with esophagectomy (Cunningham et al. 2006; Ychou et al. 2011; Al-Batran et al. 2019; Shapiro et al. 2015). A better understanding of the physiological mechanisms contributing to unintentional weight loss in this context may help us

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adequately address and manage this phenomenon, ultimately supporting patients to ensure the availability of therapeutic interventions is not limited by compromised nutritional status.

7

What Are the Consequences of Weight Loss and Malnutrition Associated with Esophagectomy?

7.1

Negative Impact on Quality of Life

As a consequence of improved perioperative care, surgical techniques, perioperative chemotherapy, and nutritional support, the 5-year survival rate for the treatment of EC has improved substantially over the past 20 years (2019). Population-based cohort studies have demonstrated that patients who have undergone surgical resection for EC have the poor health-related quality of life in the short and longer term (Lagergren et al. 2007). This is, in part, reflective of the invasiveness and associated morbidity of surgical interventions, particularly if major postoperative complications arise, as well as due to persistent nutritional challenges. A systematic review identified six studies reporting on changes in nutritional status, which also reported on the effects of nutrition-related symptoms on quality of life (Baker et al. 2016). While the evidence is limited for nutrition-related quality of life, there is a general consensus that the common and long-term (>12 months) GI symptoms following esophagectomy include early satiety, nausea, dumping syndrome, reflux, dysphagia, and diarrhea, all of which have implications for weight, lean body mass, and overall nutritional status.

7.2

Reduced Long-Term Survival due to Inability to Tolerate Adjuvant Treatments

Perioperative chemotherapy is increasingly becoming the standard of care for patients undergoing esophagectomy. In patients following esophagectomy, adjuvant chemotherapy is generally delivered at 75% of the preoperative dose. However, in patients who are malnourished, there is a greater risk of life-threatening complications. Failure to complete adjuvant treatments due to systemic side effects, such as diarrhea, may have implications for long-term survival.

8

Pathophysiological Mechanisms of Weight Loss Following Esophagectomy

Valuable insights into the mechanisms which govern weight loss following esophagectomy have arisen from mechanistic studies. These studies have challenged the traditional view that postoperative weight loss is largely attributable to a simple restrictive phenomenon, primarily due to decreased gastric volume. Using a model

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of bariatric surgery has shaped our understanding of GI physiology and, in turn, informed our current appreciation of the changes following esophagectomy, which mediate unintentional weight loss (Pournaras et al. 2017). This understanding of gut hormone changes and their effect on the gut-brain axis may play an important role in developing novel treatment strategies to preserve or increase weight in patients following esophagectomy.

8.1

Changes in Gut Hormones, Bile Acids, and Gut Microbiota After Esophagectomy Gut Hormone Changes After Esophagectomy

Short-term regulation of feeding is mainly under the control of the hypothalamic gut-brain axis and the enteroendocrine system which modulates appetite, satiety, and glucose metabolism through a balance of orexigenic and anorectic gut hormones. Hunger is primarily driven by the secretion of the main orexigenic hormone, ghrelin, which is produced by Gr-cells in the gastric fundus. Food intake results in an attenuation of this response with decreased ghrelin production. There is a concurrent secretion of satiety-promoting or anorectic hormones from the enteroendocrine L-cells of the large and small intestine in response to the arrival of ingested nutrients, primarily through interactions with fatty acid bile receptors on their luminal surfaces (Spreckley and Murphy 2015). In addition to producing a sensation of fullness, these hormones, particularly glucagon-like peptide 1 (GLP-1), are essential regulators of nutrient utilization, particularly in their role in promoting insulin secretion and increasing hepatic and peripheral insulin sensitivity (Carmody et al. 2016). As previously demonstrated by mechanistic studies looking into the role of gut hormones in bariatric surgery, the anatomical changes produced by esophagectomy are thought to result in important changes in enteroendocrine signaling. These alterations are critical in mediating reduced long-term postoperative food intake. Key satiety hormones involved in appetite regulation include: • • • • • •

Glucagon-like peptide 1 (GLP-1). Peptide YY (PYY). Gastric inhibitory polypeptide (GIP). Oxyntomodulin (OXM). Pancreatic polypeptide (PP). Cholecystokinin (CCK).

The features of these gut peptide hormones in the context of OC surgery are outlined in Table 3. Models derived from bariatric surgery have largely shaped our understanding of the effects of GI surgery on modifying neurohormonal control regulating the gut-brain axis. In particular, studies characterizing the effects of satiety hormones, namely, GLP-1 and PYY, have demonstrated their importance in the long-term regulation of satiety, weight loss, and weight loss maintenance. Both GLP-1 and

Pancreas

The small and large intestine

The small and large intestine

Pancreatic polypeptide

GLP-1

OXM

Post-prandial satiety, ileal brake Decreased pancreatic exocrine function Raised energy expenditure

Post-prandial satiety, ileal brake Decreased biliary and pancreatic exocrine secretion Post-prandial satiety, ileal brake Incretin effect Cardiac, renal, vascular, immune effects

Post-prandial satiety, ileal brake

Post-prandial satiety, ileal brake Pancreatic exocrine and biliary secretion

Signals fasting, helps initiation of feeding " GH, PRL, ACTH, and cortisol

Function

Inflated post-prandial reaction

Inflated post-prandial reaction

Decreased post-prandial reaction

Inflated post-prandial reaction

Inflated post-prandial reaction

Brief decrease in fasting levels (Elliott et al. 2019a; Yamamoto et al. 2013; Miyazaki et al. 2012; Doki et al. 2006)

Response to upper GI surgery

ACTH adrenocorticotropic hormone, CCK cholecystokinin, GH growth hormone, GLP glucagon-like peptide, OXM oxyntomodulin, PRL prolactin, PYY peptide YY

L-cells

L-cells

PP-cells

L-cells

The small and large intestine

PYY

Vagal afferent neurons Brainstem Hypothalamus Gallbladder Vagal afferent neurons Hypothalamus Brainstem Vagal afferent neurons Brainstem Hypothalamus Vagal afferent neurons Hypothalamus Brainstem Mesolimbic system Pancreatic islet Hepatocytes Vagal afferent neurons Hypothalamus Pancreatic islet Hepatocytes

Vagal afferent neurons Hypothalamus Mesolimbic system

Gr-cells

L-cells

Site of action

Cell

Anorexigenic gut hormones CCK Proximal small intestine

Hormone Primary source Orexigenic gut hormones Ghrelin Stomach

Table 3 Anatomical and physiological features of the main gut peptide hormones (Murphy 2020)

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PYY are secreted by enteroendocrine L-cells throughout the GI tract, particularly in the terminal ileum and large intestine in response to both nutrients and bile (De Silva and Bloom 2012). Crossing the blood-brain barrier, they act on the arcuate nucleus of the hypothalamus, inhibiting further food intake by stimulating the anorectic pro-opiomelanocortin neurons while simultaneously inhibiting the orexigenic agouti-related peptide and neuropeptide Y neurons (Turton et al. 1996). Following esophagectomy, there is an exaggerated GLP-1 response, which, unlike the ghrelin response, remains altered long term. Although the mechanisms underlying this change have yet to be elucidated, it has been suggested that alterations in nutrient delivery and bile flow due to anatomical changes may lead to enteroendocrine cell hyperstimulation resulting in raised GLP-1 levels (Elliott et al. 2017). Postoperative weight loss and fat loss following esophagectomy can be predicted by the magnitude of the GLP-1 response (Elliott et al. 2019c). Evidence supporting the key role of satiety hormones in mediating weight loss following esophagectomy has prompted a further study to investigate the possible therapeutic role of somatostatin analogs and specific GLP-1 receptor antagonists in regulating the exaggerated gut hormone response (Elliott et al. 2019b; Murphy et al. 2021). Ghrelin is the primary orexigenic hormone secreted by the Gr-cells of the gastric fundus in response to hunger. Total circulating ghrelin levels have an inverse relationship with body weight, with patients who have experienced diet-induced weight loss demonstrating increased levels of ghrelin (Elliott et al. 2016). The orexigenic effects of ghrelin are mediated centrally as the hormone is able to cross the blood-brain barrier. In the brain, it stimulates the arcuate nucleus neuropeptide Y (NPY) and agouti-related peptide expression, enhancing appetitive behavior while simultaneously modifying dietary preferences toward carbohydrate intake. Given the anatomical changes involving the gastric fundus with gastric conduit formation during esophagectomy, it has been postulated that decreases in ghrelin may play a role in weight loss post-esophagectomy. Studies have consistently demonstrated a significant reduction in ghrelin levels in the early postoperative period. However, these changes have been shown to be transient with a return to baseline by as early as 3 months (Koizumi et al. 2011). A return to normal hunger scores with persistent weight loss, in conjunction with normalization of ghrelin levels, suggests that this is not the primary mediator of long-term weight loss following esophagectomy but that it may play a role in decreased hunger in the early postoperative period (Elliott et al. 2019a).

8.2

Alterations in Bile Acid Signaling Following Esophagectomy

Extensive changes in bile acid signaling, which are important mediators of weight loss, occur following bariatric surgery, suggesting there may be similar mechanisms involved following esophagectomy (Pournaras et al. 2012). Both of the most commonly performed bariatric procedures, sleeve gastrectomy (SG) and Roux-enY gastric bypass (RYGB), produce a substantial increase in circulating bile acids (Myronovych et al. 2014; Patti et al. 2009). Although bile acids are primarily thought to mediate their effects in the digestion of lipids, they may also play an important role

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in directly regulating metabolism, primarily through their interaction with the nuclear receptor FXR. Studies looking at FXR knock-out mice showed a substantially reduced response following SG for both weight loss and glucose tolerance compared to wild-type mice, supporting the role of bile acid signaling in postoperative weight loss (Ryan et al. 2014). Further supporting this hypothesis, in rodent models simulating the effect of RYGB, studies have demonstrated that alterations in bile flow to the terminal ileum resulted in increased plasma bile acids, gut satiety hormone response, reduced food intake, and weight loss (Pournaras et al. 2012). Although this has yet to be specifically examined in patients following esophagectomy, investigating the possible role of bile acids in postoperative weight loss merits further investigation.

8.3

Alterations to Gut Microbiota Following Esophagectomy

Similar to bile acids, studies looking at changes following bariatric surgery demonstrate that there are changes in gut microbiota in the postoperative period, which may also hold true following esophagectomy; however, the evidence for this remains limited. Following bariatric surgery, significant changes can be seen in the gut microbiota of both humans and rodents (Tremaroli et al. 2015). A decrease in bacterial families (Archaea, Firmicutes, and Prevotellaceae) is observed, while there is an increase in the ratio of Bacteroidetes to Prevotella. Esophagectomy may lead to similar microbial changes (Li et al. 2011; Zhang et al. 2009; Furet et al. 2010). At present, the exact mechanisms resulting in these changes and their clinical significance, particularly in the context of weight loss, remain unclear. Fecal transplant studies have provided evidence that altered gut microbiota may play an instrumental role in weight loss after upper GI surgery. However, there remain many confounders to this hypothesis, including perioperative antibiotic use and other mechanisms of weight loss as previously discussed throughout this chapter, and the extent to which microbial change contributes overall is unclear (Guo et al. 2018).

9

Parallel Contributory Factors to Weight Loss Post-esophagectomy

In addition to the pathophysiological changes discussed above, a number of additional factors may act in a synergistic manner to contribute toward post-surgical weight loss and nutritional compromise.

9.1

Surgical Technique

Traditional surgical approaches to esophagectomy involved large open incisions, such as a laparotomy often combined with a thoracotomy, which is highly invasive and associated with significant postoperative morbidity. More recently, there have

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been advances in techniques with the adoption of minimally invasive approaches, which are generally associated with a decreased systemic inflammatory response syndrome (SIRS) and faster recovery. Robotic surgery represents the latest advance in the minimally invasive approaches, and although this may limit the magnitude of surgical insult, the benefits may be offset by an increased risk of significant perioperative complications.

9.2

Appetitive Behavior

Appetitive behavior can be defined as the amount of effort a patient is prepared to use to obtain food. Alterations in appetitive behavior are common and profound following esophagectomy. Early satiety in the postoperative period also contributes to this effect, which ultimately reduces caloric consumption, resulting in weight loss and nutritional decline. Appetitive symptoms may be predictive of long-term weight loss after esophagectomy, e.g., appetite loss and altered desire to eat. In some individuals, cognitive behavior therapy has been shown to have a positive effect on counteracting these changes. In many patients, there is a well-described rebound increase in appetitive behavior following an initial period of decreased intake in the early postoperative period. Interestingly, this compensatory change is typically not seen in patients following esophagectomy even when the inflammatory response has subsided, suggesting there are additional postoperative changes contributing to sustained weight loss in this context, including prolonged changes in gut hormones (Elliott et al. 2019b).

9.3

Systemic Inflammatory Response

Esophagectomy is classified as a major plus intervention according to WHO definitions. The catabolic effects resulting from the SIRS following surgical intervention are a well-characterized phenomenon. The SIRS response is believed to be particularly profound in esophagectomy for several reasons, specifically the invasiveness of the two-compartment nature of the surgery as well as profound physiological stress induced by single lung ventilation. Similar to other major surgery, following esophagectomy, there is an increase in basal metabolic rate due to the surgery-related immune-driven inflammatory response (Anandavadivelan and Lagergren 2016; Heneghan et al. 2015).

9.4

Cancer Cachexia

Cancer cachexia is a disease-specific inflammatory process resulting in malnutrition in patients with underlying malignancy that is frequently seen in patients with EC (Anandavadivelan and Lagergren 2016). It is characterized by sarcopenia occurring

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with or without the loss of adipose tissue, ultimately culminating in unintentional weight loss and resultant physical and functional decline. Although this is part of a disease spectrum, at more advanced stages, it is not typically reversed by optimization of nutritional status through the provision of additional nutritional support. The causes underlying the development of cancer cachexia are multifactorial and remain to be fully elucidated. However, it appears to be the product of a negative protein and energy balance, thought to result from a combination of decreased nutrient ingestion and altered metabolism. Cancer cachexia can be described as a spectrum ranging from precachexia classified as 5% or BMI 2% and finally refractory cachexia whereby the degree of cachexia is variable but cancer not responsive to treatment with 10% weight over a 6-month follow-up period (Donohoe et al. 2017). Although the routine use of prolonged enteral feeding is not supported, it may be employed on a case-by-case basis to mitigate or manage postoperative complications such as anastomotic leak where oral intake is prohibited for an extended period or in those who are failing to meet their caloric needs via the oral route.

11

Conclusion

The method of managing unintentional weight loss in patients following esophagectomy is highly dependent on a number of factors, including baseline function, comorbidities, surgical techniques, and the presence of postoperative complications. Although this helps inform the approach to managing patients in this context, it is important to be mindful that unintentional weight loss is in itself the result of the combination of the physiological processes driven by the condition and its treatment as well as psychological factors, requiring a patient-centered approach to long-term management. Further insight into the mechanical changes resulting from the anatomical resection of the esophagus and reconstruction, as well as those mediated by gut hormones, is required. The development of pharmacological interventions which may help counteract some of the physiological changes mediated by esophagectomy, particularly those related to gut hormones, may play a key role in developing strategies to help treat or mitigate some of the weight loss which often negatively impacts patients’ long-term recovery and quality of life.

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Current Clinical Landscape of Immunotherapeutic Approaches in Pancreatic Cancer Treatment Pooya Farhangnia , Shamim Mollazadeh Ghomi , Shabnam Mollazadehghomi, and Ali-Akbar Delbandi

Abstract

As a significant contributor to cancer-related death, pancreatic cancer, as a recalcitrant tumor, generally has an appalling prognosis that has not altered over many years. At the moment, prevention or early identification at a stage where treatment is still possible is exceptionally challenging because patients seldom show symptoms, and tumors exhibit no sensitive and specific indicators to help with detection. Most patients have advanced or metastatic, intricate malignancy, and standard of care treatments, such as chemotherapy and radiotherapy, may extend life by several months in these cases. The approach to treating pancreatic cancer has been fundamentally revolutionized due to immunotherapy. However, the immunosuppressive, inaccessible tumor microenvironment (TME) may be the reason for its low immunotherapeutic effectiveness in pancreatic cancer. In this chapter, we address pancreatic cancer immunosuppressive TME

P. Farhangnia Department of Immunology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran Immunology Board for Transplantation and Cell-Based Therapeutics (ImmunoTACT), Universal Scientific Education and Research Network (USERN), Chicago, IL, USA e-mail: [email protected] S. Mollazadeh Ghomi · S. Mollazadehghomi Immunology Board for Transplantation and Cell-Based Therapeutics (ImmunoTACT), Universal Scientific Education and Research Network (USERN), Chicago, IL, USA A.-A. Delbandi (✉) Reproductive Sciences and Technology Research Center, Department of Immunology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran Department of Immunology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran Immunology Board for Transplantation and Cell-Based Therapeutics (ImmunoTACT), Universal Scientific Education and Research Network (USERN), Chicago, IL, USA e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2023_163 Published online: 29 June 2023

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and underscore an extensive spectrum of immunotherapies, including oncolytic virus therapy, adoptive cell transfer therapy (i.e., T-cell receptor [TCR]engineered T cells therapy, chimeric antigen receptor [CAR] T-cell therapy, CAR natural killer [NK] cell therapy, and cytokine-induced killer cells), immune checkpoints blockade and immunomodulators, cancer vaccines, and immunotherapeutic strategies based on targeting myeloid cells. Keywords

Cancer immunotherapy · CAR NK cell therapy · CAR T-cell therapy · Immune checkpoint blockade · Immunotherapy · Oncolytic virus therapy · Pancreatic cancer

Abbreviations APC ATRA BM CAF CAR cDC1 CEA CIK CSF1R CTL CTLA-4 DC ECM EGFR ENO1 EpCAM FAPα FDA GATA-3 G-CSF GM-CSF HER2 HIF HMGB1 HSV ICB IDO IFN-γ IL

Antigen-presenting cell All-trans retinoic acid Bone marrow Cancer-associated fibroblast Chimeric antigen receptor Type 1 conventional dendritic cell Carcinoembryonic antigen Cytokine-induced killer Colony-stimulating factor 1 receptor Cytotoxic T lymphocyte Cytotoxic T lymphocyte antigen-4 Dendritic cell Extracellular matrix Epidermal growth factor receptor α-Enolase Epithelial cell adhesion molecule Fibroblast activation protein alpha US Food and Drug Administration GATA binding protein 3 Granulocyte colony-stimulating factor Granulocyte-macrophage colony-stimulating factor Human epidermal growth factor receptor 2 Hypoxia-inducible factor High mobility group box 1 protein Herpes simplex virus Immune checkpoint blockade Indoleamine 2, 3-dioxygenase Interferon-gamma Interleukin

Current Clinical Landscape of Immunotherapeutic Approaches in. . .

LAG-3 mAb M-CSF MDSC MHC MMP mOS MSLN MUC-1 NET NK NKG2D OS OVT PD-1 PDAC PD-L1 PFS PlGF PMN PSCA rhIL-12 ROS STAT3 TAA TAM TAN T-BET TCR TGF-β TH1 TH2 TIGIT TIL TIM-3 TLR TME TNF-α TSA TSLP VEGF VISTA

Lymphocyte-activation gene 3 Monoclonal antibody Macrophage colony-stimulating factor Myeloid-derived suppressor cell Major histocompatibility complex Matrix metalloproteinase Median overall survival Mesothelin Mucin-1 Neutrophil extracellular trap Natural killer cell Natural killer group 2D Overall survival Oncolytic virus therapy Programmed cell death protein 1 Pancreatic ductal adenocarcinoma Programmed death-ligand 1 Progression-free survival Placental growth factor Polymorphonuclear Prostate stem cell antigen Recombinant human IL-12 Reactive oxygen species Signal transducer and activator of transcription 3 Tumor-associated antigen Tumor-associated macrophage Tumor-associated neutrophil T-box expressed in T cells T-cell receptor Transforming growth factor-beta T helper 1 T helper 2 T-cell immunoglobulin and ITIM domain Tumor-infiltrating lymphocyte T-cell immunoglobulin and mucin domain 3 Toll-like receptor Tumor microenvironment Tumor necrosis factor-alpha Tumor-specific antigen Thymic stromal lymphopoietin Vascular endothelial growth factor V-domain Ig-containing suppressor of T-cell activation

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Introduction

With 50,550 estimated deaths in the USA in 2023 (Siegel et al. 2023), pancreatic cancer primarily consists of pancreatic ductal adenocarcinoma (PDAC), a recalcitrant disease (Hidalgo 2010). Because symptoms are frequently nonspecific, individuals frequently present at late stages. The present standard of care for PDAC is standard cytotoxic chemotherapy, which provides just months of overall survival (OS) benefit (Conroy et al. 2011; Von Hoff et al. 2013). PDAC carcinogenesis is characterized by the steady accumulation of driver mutations, which include the oncogene KRAS (Moskaluk et al. 1997) and the tumor suppressor gene TP53 (DiGiuseppe et al. 1995). These molecular alterations are accompanied by histological changes corresponding to the various PDAC development phases (Ho et al. 2020). Morphological development begins with the establishment of precursor lesions recognized as pancreatic intraepithelial neoplasia (PanIN) (Hruban et al. 2001), which proceed to invasive adenocarcinoma (Ho et al. 2020). Modifications in the surrounding tissue stroma occur as cancer progresses. With its immunological, vascular, and connective tissue components, non-transformed tissue stroma is essential in providing a homeostatic response to damage. On the other hand, cancer hijacks such physiological reactions to generate a favorable tumor microenvironment (TME) for its effective development (Foster et al. 2018; Ho et al. 2020). Indeed, cancer acts like “wounds that never heal,” and stromal change is the outcome of “abnormal wound repair” (Dvorak 2015). Immunotherapeutic approaches have the decent ability to elicit robust anti-tumor immune responses. Immunomodulators, immune checkpoint blockade (ICB), and adoptive cell transfer therapy, such as chimeric antigen receptor (CAR) T-cell therapy, can all help with this. Clinical research employing diverse immunotherapeutic approaches to treat patients with various cancers has yielded outstanding results from 2010 to the present. Cancer cell-specific immune responses elicited by immunotherapy differ from those stimulated by therapies acting on the tumor. They can persist long after the treatment has ceased (Khalil et al. 2016; Farhangnia et al. 2022, 2023). Tumor immunotherapy has established a novel cornerstone in treating a subset of diverse solid tumors. However, currently, existing immunotherapies in PDAC have only shown minimal benefit in terms of survival (Pihlak et al. 2018; Riquelme et al. 2018). The low mutational load of PDAC and the densely packed, inaccessible TME with fibrotic, hypoxic, and immunosuppressive properties can be linked to the tumor immunological insensitivity to immunotherapies (Huber et al. 2020; Timmer et al. 2021). However, a meta-analysis revealed that targeted immunotherapy in patients with pancreatic cancer was superior in terms of increasing survival time and improving immune responses (Chen et al. 2017). Furthermore, chemotherapy and surgery in conjunction with other immunotherapies may function synergistically. Several cytotoxic drugs and adjuvant treatments have been shown to sensitize the TME to immunotherapeutic agents by triggering immunogenic cell death, altering evasive immunological processes, and decreasing immune suppression (Geboers et al. 2019; Galluzzi et al. 2020).

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Immunotherapy is currently one of the arising areas of focus in pancreatic cancer therapy. This recalcitrant tumor mainly evades immune surveillance through various ways, including the secretion of immunosuppressive factors such as transforming growth factor-beta (TGF-β), establishing an immunosuppressive microenvironment depleted of T lymphocytes, and the expression of the immune checkpoints programmed death-ligand 1 (PD-L1) and PD-L2 (Kleeff et al. 2007, 2016). Moreover, in pancreatic cancer, ICB to stimulate T-cell activity is being studied (Feig et al. 2013; Soares et al. 2015). The pancreatic cancer microenvironment is notable for its extensive desmoplasia, lack of effector T lymphocytes, and T helper 2 (TH2) cell immunophenotype, all of which support cancer cells to escape immune surveillance. Therefore, monoclonal antibodies (mAbs) directed against programmed cell death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1) have limited success (Kleeff et al. 2016). Immunotherapies such as PD-1 suppression may benefit a limited percentage of cancer patients (3%) with hypermutation and microsatellite instability (Le et al. 2015). Inhibiting the tyrosine-protein kinase BTK is one approach for modulating the TME to induce a T helper 1 (TH1) cell immunophenotype. Vaccination is being studied to elicit or enhance pre-existing immune responses using agents such as GVAX (autologous pancreatic cell lines transfected with granulocyte-macrophage colony-stimulating factor [GM-CSF]) or CRS207 (live attenuated Listeria monocytogenes-expressing mesothelin [MSLN]) alone or in combination with a mAb directed against CD40 molecule to stimulate antigen-presenting cells (APCs) (Le et al. 2015). CD47 and CXC chemokine receptors are two immune-based targets being investigated. T cells expressing CARs plus oncolytic virus therapy (OVT) are being studied to stimulate inflammation, immunomodulation, and tumor cell lysis (Khaled et al. 2015). In this chapter, we elaborate on pancreatic cancer immunosuppressive microenvironment and highlight an extensive spectrum of immunotherapies, including OVT, adoptive cell transfer therapy (i.e., T-cell receptor [TCR]-engineered T cells therapy, chimeric antigen receptor [CAR] T-cell therapy, CAR natural killer [NK] cell therapy, and cytokine-induced killer cells), immune checkpoints blockade and immunomodulators, cancer vaccines, and immunotherapeutic strategies based on targeting myeloid cells (Fig. 1).

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Tumor Microenvironment in Pancreatic Cancer

The interplay of tumor cells with their neighboring microenvironment substantially influences the pathogenesis of solid tumors. PDAC is a classic illustration of the wide range of potential tumor-stroma dialogues. PDAC is highly resistant to emerging immunotherapies, which is by an exclusive assembly of diverse immune cells that creates a highly immunosuppressive environment, accounting for tumor progression (Huber et al. 2020). In this section, we delineate the role of immune cells in the TME of pancreatic cancer.

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Fig. 1 Immunotherapeutic approaches in pancreatic cancer treatment. These approaches include oncolytic virus therapy, adoptive cell transfer therapy, immune checkpoint blockade, cancer vaccines, and targeting myeloid cell within the tumor microenvironment of pancreatic cancer. CTLA-4 Cytotoxic T lymphocyte antigen-4. (This figure was created by Biorender.com)

2.1

Macrophages and Myeloid-Derived Suppressor Cells (MDSCs)

Granulocytes, dendritic cells (DCs), monocytes, and macrophages are innate immune cells of the myeloid lineage that are crucial in identifying cancer cells, induction of inflammation, and anti-tumor activities. Chronic inflammation is a facilitator of tumor growth in many insidious diseases, including pancreatic cancer (Hamada et al. 2014). Tumor cells also frequently deploy ways to elude immune monitoring. Furthermore, myeloid cells perform a double function in cancer. On the one hand, they trigger anti-tumor immune responses but also encourage local inflammation that leads to long-term and chronic inflammation linked to cancer (Huber et al. 2020).

2.1.1 Role of Macrophages in TME There are tissue-resident macrophages that are not descended from blood monocytes, such as Kupffer cells in the liver, microglia in the brain, and alveolar macrophages in the lungs. However, the majority of macrophages in healthy and inflamed tissues differentiate from bone marrow (BM)-derived monocytes in the peripheral blood circulation (Mantovani et al. 2022). Circulating monocytic cells are attracted to the TME and develop into tumor-associated macrophages (TAMs) in the presence of cytokines and chemokines, as well as other stimuli, like hypoxia and lactic acid at high levels of concentration (Gordon and Taylor 2005; Huber et al. 2020). However, a study demonstrated that a sizeable part of the macrophages in the pancreas was generated during embryonic development and increased through in situ proliferation as the tumor developed (Zhu et al. 2017). TAMs exhibit several functional states known as polarization states. A vast and expanding spectrum of TAM subpopulations has been identified. They are often categorized as “M1” and “M2” macrophages. According to a typical description, M1 macrophages produce pro-inflammatory cytokines that primarily have anti-neoplastic effects, whereas M2

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macrophages release anti-inflammatory signals that might hasten the formation of tumors (Mosser and Edwards 2008; Biswas and Mantovani 2010; Bolli et al. 2017). In numerous tumor types, including pancreatic cancer, studies have shown an inverse relationship between TAM invasion and patient prognosis (Hu et al. 2016; Di Caro et al. 2016; Mantovani et al. 2017; Zhang et al. 2020a). Diverse research teams have shown that TAMs drive immunosuppression, angiogenesis, and tumor development by releasing growth factors such as vascular endothelial growth factor (VEGF), cytokines, and proteases in mice models of PDAC (Liou et al. 2015; Griesmann et al. 2017; Nywening et al. 2018; Filippini et al. 2019). TAMs can reduce the effectiveness of treatment in PDAC significantly. TAMs affect the cytidine deaminase activity, a crucial enzyme in gemcitabine metabolism, leading to resistance to treatments based on gemcitabine in PDAC animal models (Weizman et al. 2014). By preventing monocyte migration to the TME in mice models of PDAC, CCR2 suppression promotes T-cell infiltration, increased the effectiveness of radiotherapy and chemotherapy, and reduced metastasis (Mitchem et al. 2013; Sanford et al. 2013; Liou et al. 2015; Kalbasi et al. 2017).

2.1.2 Role of MDSCs in TME A diverse population of immature myeloid cells known as MDSCs is often split into two cell types: monocytic (M-MDSC), which are phenotypically and physically comparable to monocytes, and granulocytic (polymorphonuclear [PMN]-MDSC), which are equal to neutrophils. The circulation and the microenvironment of human malignancies include much more MDSCs, and generally, PMN-MDSCs account for more than 80% of all MDSCs associated with tumors (Gabrilovich 2017; Veglia et al. 2021). Here, we highlight evidence related to MDSCs in the PDAC microenvironment. MDSC levels in human PDAC are correlated with the cancer stage (Diaz-Montero et al. 2009; Gabitass et al. 2011; Markowitz et al. 2015). A crucial element promoting MDSC recruitment and differentiation, according to findings from genetically modified mice models, is GM-CSF, which is generated by tumor cells starting in the early stages of cancer (Bayne et al. 2012; Pylayeva-Gupta et al. 2012). Additionally, the accumulation of MDSCs and pancreatic carcinogenesis are facilitated by the receptor for advanced glycation end products (RAGE) (Vernon et al. 2013). Indeed, during Ras-mediated pancreatic carcinogenesis, RAGE ablation is linked with decreased splenic MDSC accumulation (Vernon et al. 2013). Upregulation of Yes-associated protein (YAP) or genes associated with MDSC implies poor survival in PDAC patients. YAP expression levels are substantially associated with an MDSC gene signature in primary human PDAC (Murakami et al. 2017). In the PDAC milieu, CD200, a regulator of myeloid cellular function, is upregulated. Furthermore, MDSCs from patients with PDAC exhibited increased CD200 receptor expression. MDSC development may be regulated by CD200 expression in the PDAC microenvironment (Choueiry et al. 2020). MDSCs govern the inhibition of CD4+ and CD8+ T lymphocyte activity in the tumor. Also, MDSCs upregulate PD-L1, which in turn, represses T-cell activation due to the PD-L1/PD-1 interaction (Pinton et al. 2016). Additionally, MDSCs can

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restrict the T-cell activity by encouraging the growth of immune-suppressive regulatory T cells (Tregs) through the release of TGF-β and interferon-gamma (IFN-γ) in an interleukin-10 (IL-10)-reliant manner (Huang et al. 2006; Siret et al. 2020). In PDAC, targeted reduction of MDSCs maximizes intratumoral accumulation of stimulated CD8+ T lymphocytes, tumor epithelial cell death, and tumor stromal remodeling (Stromnes et al. 2014). MDSCs can potentially downregulate innate anti-tumor immunity through various strategies. In experimental breast and lung tumor models, MDSCs have been demonstrated to suppress cytotoxicity in NK cells through cell contact-reliant pathways and accelerate the transformation of macrophages toward an M2 phenotype (Liu et al. 2007; Sinha et al. 2007; Ostrand-Rosenberg et al. 2012; Huber et al. 2020).

2.2

Natural Killer (NK) Cells

NK cells are a discrete subpopulation of innate lymphoid cells with the inherent capacity to recognize and eradicate cancerous cells. NK cells play a paramount role in anti-cancer immunity due to their innumerable cytotoxicity strategies and potential to alter the immune response through cytokine production (Laskowski et al. 2022). Cytotoxic NK cells provide a robust immune response through the production of cytolytic granules and cytotoxic cytokines when they establish immunological synapses with target cells (Prager and Watzl 2019; Laskowski et al. 2022). Additionally, NK cells can identify Fc of IgG antibodies on target cells via their Fcγ receptor IIIA (FcγRIIIA; also known as CD16), causing the production of cytokines and antibody-dependent cellular cytotoxicity (ADCC). Furthermore, owing to their potential to generate various cytokines and chemokines, which affect the activity of myeloid and lymphoid cell lineages, NK cells have been raised to as “immuneregulatory” cells (Laskowski et al. 2022). NK cells, a unique immune effector cell found in the innate immune system, are thought to contribute to tumor immunosurveillance (Malmberg et al. 2017). Both preclinical and clinical investigations have shown an association between reduced NK cell activity with augmented cancer vulnerability and the likelihood of metastasis (Imai et al. 2000; Guerra et al. 2008; López-Soto et al. 2017). Indoleamine 2, 3-dioxygenase (IDO), matrix metalloproteinases (MMPs), TGF-β, and IL-10 have been revealed to be mediators of immune suppression by PDAC. These mediators minimize tumor cell recognition and killing by NK cells (Huber et al. 2020). In patients with PDAC, the relative frequency of NK cells in the blood was favorably linked with survival. However, compared to healthy participants, PDACassociated NK cells have reduced cytotoxicity (Davis et al. 2012). Peripheral NK cells from patients with PDAC showed decreased expression of NKG2D, NKp46, and NKp30, which was linked to the stage and histological grade of the patients (Husain et al. 2013; Peng et al. 2014). Additionally, the reduced expression of CD96 and CD226 (regulators of NK cell function) on NK cells was associated with cancer

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development in PDAC patients (Peng et al. 2016). Moreover, immune evasion of NK cells in human pancreatic cancer is associated with Igγ-1 chain C region (IGHG1) expression. Mechanistically, IGHG1 dampened the cytotoxic activity of NK cells by inhibiting ADCC (Li et al. 2011). Furthermore, NK cell immune escape in patients with pancreatic cancer is associated with impaired localization arising from lacking CXCR2 and impaired tumor cytotoxicity (Lim et al. 2019).

2.3

Neutrophils

Neutrophils serve as the body’s initial line of defense against infection and react to a wide variety of pro-inflammatory signals, one of which is cancer. Neutrophils have flexibility or plasticity, enabling them to modify their function in response to various inflammatory stimuli (Giese et al. 2019). Due to the inflammatory condition of the TME in PDAC, tumor cells release pro-inflammatory mediators such as tumor necrosis factor-alpha (TNF-α) and IL-12 that induce PMNs recruitment to the tumor site. To drive monocytes and DCs to the TME, PMNs release various chemokines, including CCL2, CCL3, CCL19, and CCL20 (Xiang et al. 2020). Furthermore, neutrophils are attracted to factors secreted by tumor cells. IL-1, CD200, the CXC family (CXCL1, CXCL2, CXCL5, and CXCL8), growth factors (GM-CSF, granulocyte colony-stimulating factor [G-CSF], and macrophage colonystimulating factor [M-CSF]), and others may be released by tumor cells to attract neutrophils (Jin et al. 2021). Neutrophils in the TME have a variety of roles and have been categorized in myriad ways, such as N1/N2 neutrophils, tumor-associated neutrophils (TANs), and PMN-MDSCs (Giese et al. 2019). Depending on their polarization states, neutrophils may either contribute to the progression of cancers or suppress this growth. By producing reactive oxygen species (ROS) and reactive nitrogen species, anti-tumor neutrophils can directly destroy tumor cells. They can also stimulate the activation of T cells and attract macrophages with an M1 inflammatory profile. Protumor neutrophils, conversely, can secrete MMP-9, an enzyme that encourages the development of new blood vessels and the spread of tumor cells. They can also inhibit the function of NK cells. Besides, they can recruit anti-inflammatory macrophages (M2) and Tregs. Furthermore, the activity of CD8+ T cells may be inhibited by suppressor neutrophils, also known as PMN-MDSCs, along with other types of pro-tumor neutrophils (Giese et al. 2019). It is assumed that the neutrophil polarization affects their function in the TME. A high neutrophil-to-lymphocyte ratio in solid tumors has been found to be linked to a poor prognosis in patients (Shen et al. 2014). However, these findings do not clarify whether neutrophils are directly involved in cancer development or are associated only with advanced disease. There is a broad range of how neutrophil infiltration affects cancer growth in mouse cancer models (Giese et al. 2019). The distinction between pro-tumorigenic and anti-tumorigenic neutrophils, designated N1 and N2, was initially proposed by Fridlender and colleagues. They demonstrated that the immunosuppressive cytokine TGF-β polarized neutrophils to a pro-tumorigenic

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phenotype (N2) and neutrophil depletion brought about a modest reduction in tumor development in mice models. SM16 (a TGF-β receptor inhibitor) caused TGF-β blockage, which increased neutrophils with an anti-tumorigenic phenotype (N1) (Fridlender et al. 2009). Neutrophil extracellular traps (NETs) that neutrophils produce are another way in which they distinguish apart from other immune cells. These include DNA fibers and proteolytic enzymes secreted by neutrophils to combat invading infections. However, new research indicated that NETs may play a role in the spread of cancer. DNase I, a NET inhibitor, was investigated in a mouse model of spontaneous PDAC and shown to reduce liver metastasis (Zhang et al. 2017). In the PDAC environment, IL-17 is responsible for recruiting neutrophils and triggers NETosis (Zhang et al. 2020b). Neutrophils play a part in metastasis because of their ability to move via the circulatory system and into the tissue. Neutrophils can accompany tumor cells as they migrate through the circulation. These tumor cells are often circulating tumor cells that have spread from the central tumor location (Huber et al. 2020; Zhang et al. 2020b). During the process of extravasation and following infiltration into metastatic locations, neutrophils experience apoptosis and NETosis. This causes their cargo molecules to be released, which in turn makes a milieu more favorable to tumor growth. This includes the release of ARG-1 to make an environment that suppresses the immune system; MMP-9 to stimulate the infiltration of cancerous cells and angiogenesis; and other potent serine proteases, such as neutrophil elastase, Cathepsin G, and human proteinase 3. Lipocalin-2, heparanase, CD11 and CD18, and S100/A9 are other proteins released by neutrophils. For illustration, neutrophils may stimulate tumor cells by phosphorylating PI3K/Akt after the release of lipocalin-2. This results in the downstream production of VEGF and hypoxiainducible factor-1 (HIF-1), which are proteins that are essential for the growth of tumors, vasculature, and chemoresistance (Tao et al. 2016; Huber et al. 2020).

2.4

T Lymphocytes

Tumors from patients with PDAC show a wide range of immunological diversity, with infiltrating T-cell densities and T-cell subpopulation composition (Leung et al. 2012; Bailey et al. 2016a, b; Carstens et al. 2017; Balli et al. 2017; Stromnes et al. 2017; Li et al. 2018). Recent research suggests that desmoplastic components may not impact T-cell accumulation, demonstrating a distinct spatial distribution of T cells in PDAC (Balli et al. 2017), challenging the notion that the immunosuppressive milieu of fibroblasts and desmoplastic stroma inhibits T-cell infiltration (Ene-Obong et al. 2013; Balachandran et al. 2017). An improvement in patients’ survival is linked to an increment in the number of CD8+ cytotoxic T lymphocytes (CTL) that surround cancer cells (Balli et al. 2017). Tumor samples from patients with long-term survival showed a higher percentage of CD8+ T cells, CTLs, and Tregs and a lower percentage of CD4+ T cells compared to tumor samples from patients with short-term survival (Carstens et al. 2017). Longer patients’ survival

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was substantially linked with a higher ratio of M1 to M2 macrophages and a higher number of tumor-infiltrating CD4+ and CD8+ T cells, and lesser tumor-infiltrating Tregs (Feig et al. 2013).

2.4.1 T Helper (TH) Cells: TH1, TH2, and TH17 TH1 cells, which express the T-box expressed in T cells (T-BET; or T-Box transcription factor 21 [TBX21]) transcription factor and produce IFN-γ, are a subset of CD4+ T cells. By the synthesis of cytotoxic molecules and the secretion of the cytokine IFN-γ, TH1 cells enhance cellular type I immunity, which includes the priming, stimulation, and recruitment of CTLs, M1 macrophages, and NK cells, and facilitates protection against intracellular infections and malignancies. Differentiated TH2 cells, which are effective against helminths and contribute to allergies and asthma, are defined by GATA binding protein 3 (GATA3) transcription factor, and they secrete interleukin IL-4, IL-5, and IL-13. TH1 differentiation is inhibited by TH2, and vice versa (Huber et al. 2020). In pancreatic cancer, GATA3+ TH2 cell infiltration is more prevalent than T-BET+ TH1 cell infiltration, and a higher ratio of GATA3+/T-BET+ tumorinfiltrating lymphocytes (TILs) is related with disease development (Tassi et al. 2008; De Monte et al. 2011; Dobrzanski 2013). Patients with PDAC who have a greater TH2 cytokine profile in their blood have a worse OS rate (Piro et al. 2017; Galon and Bruni 2020). Human pancreatic cancer cell proliferation was boosted by the TH2 marker cytokine IL-4, which also increased the signal transducer and activator of transcription 3 (STAT3), AKT, and mitogen-activated protein kinase (MAPK) pathway activity (Piro et al. 2017). DCs expressing the receptor for thymic stromal lymphopoietin (TSLP) were responsible for the activation and enrichment of TH2 cells in the TME. IL-1 α/β cytokines released by cancer cells and TAMs trigger the secretion of TSLP by cancer-associated fibroblasts (CAFs) (Huber et al. 2020). The presence of IL-4expressing basophils corresponds with an elevated TH2/TH1 ratio in tumors and poor patients’ survival, suggesting that these cells likely contribute to the stability of the TH2 phenotype in PDAC patients (Brunetto et al. 2019). Furthermore, in patients with pancreatic cancer, TH2-induced inflammation is associated with worse survival when basophils are recruited into lymph nodes that drain the tumor (De Monte et al. 2016). In light of the fact that toll-like receptor 4 (TLR4) ligation may increase pancreatic inflammation, thus, TLR4 activation might underlie the development of pancreatic cancer. A study revealed that DCs elicit pancreatic antigen-specific CD4+ TH2 cells and enhance the progression from pancreatitis to cancer, and MyD88 inhibition is responsible for these effects (Ochi et al. 2012). Additionally, PDACrelated immunosuppression is mediated by Bruton tyrosine kinase (BTK) signaling. An empirical study demonstrated that macrophages were reprogrammed toward a TH1 phenotype, which boosted CTLs-induced cytotoxicity, and PDAC development was inhibited in mice treated with the BTK inhibitor ibrutinib or by PI3K inhibition. Also, TH2-type macrophage programming through BTK activation in a PI3K-dependent manner is essential for PDAC formation via cross-talk between B lymphocytes and FcγR+ TAMs (Gunderson et al. 2016).

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TH17 cells contribute to PDAC control. Protecting against extracellular bacterial and fungal infections is a primary role of TH17 cells, which rely on the transcription factor retineic-acid-receptor-related orphan nuclear receptor gamma (RORγt) to synthesize IL-17, IL-21, and IL-22 (Gnerlich et al. 2010; He et al. 2011; Mucciolo et al. 2021). A study indicated that pancreatic tumors had greater TH17 frequencies than the surrounding normal tissues, and more TH17 cells were present in advanced (stage III-IV) tumors than in early (stage I–II) tumors. A correlation was also reported between the number of IL-17+ T cells present in tumor tissue and the likelihood of both OS and metastasis. Lastly, the severity of pancreatic cancer was linked to an increment of systemic IL-17 levels in PDAC patients compared to control (He et al. 2011). IL-17 promotes the development of pancreatic cancer by acting via the inflammatory pathway of REG3-JAK2-STAT3 (Loncle et al. 2015). In response to KRAS and inflammation, the pancreas undergoes a drastic change in terms of an influx of IL-17+ T lymphocytes. In addition, overexpression of IL-17A hastens the onset and development of pancreatic intraepithelial neoplasia (McAllister et al. 2014). Moreover, pancreatic cancer cells developed tuft cells and stem cell characteristics in response to IL-17, which was accompanied by upregulated expression of DCLK1, POU2F3, ALDH1A1, and IL-17RC, genes involved in cell proliferation and differentiation (Zhang et al. 2018). High numbers of CD4+ TILs generating TNF-α and IL-17 were related to the aggressive disease in human PDAC (Alam et al. 2015).

2.4.2 Regulatory T Cells (Tregs) CD4+ Tregs express a key transcription factor, the forkhead box P3 (FOXP3). The peripheral tolerance, the prevention of autoimmune disorders, and the limitation of chronic inflammatory diseases are all dependent on Tregs (Vignali et al. 2008). Patients with pancreatic cancer have a higher frequency of Tregs in their peripheral blood and TME (Liyanage et al. 2002; Lytle et al. 2019). As pancreatic ductal carcinoma has progressed from the premalignant to the cancerous stage, Tregs have a role in regulating the immune response to it. High levels of Tregs are associated with a worse prognosis in PDAC (Hiraoka et al. 2006). Tregs can limit DC proliferation and immunogenicity in pancreatic cancer. Also, reducing Tregs stimulates anti-tumor immunity in pancreatic cancer in a CD8+-activated T-cell-dependent manner (Jang et al. 2017). Contrary to these findings, pancreatic carcinogenesis is hastened by the depletion of Tregs (Zhang et al. 2020c). Furthermore, pro-inflammatory and immunosuppressive RORγt+FOXP3+ Tregs proliferate in human pancreatic cancer. Indeed, the pathogenesis of PDAC may be a result of FOXP3+RORγt+Tregs function, which acts as a double-edged sword characterized by pro-inflammatory and immunosuppressive activities (Chellappa et al. 2016). 2.4.3 Cytotoxic T Lymphocytes (CTLs) CTLs generating IFN-γ, TNF, perforin, and granzymes are the main players in fighting against cancerous cells. They generate long-lasting memory cells, which provide immunity against cancer cells in the future (Barry and Bleackley 2002; Raskov et al. 2021). Better survival in pancreatic cancer is linked to an increment in

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the number of CD8+ T lymphocytes inside the tumor tissue and in close proximity to tumor cells (Feig et al. 2013; Carstens et al. 2017; Balli et al. 2017). Dysfunctionality and exhaustion of intratumoral CD8+ CTLs include loss of effector function, expression of coinhibitory receptors such as PD-1, T-cell immunoglobulin, and mucin domain 3 (TIM-3), and lymphocyte-activation gene 3 (LAG-3), and alterations to the transcriptional profile. In a pancreatic cancer model, IL-18 receptor signaling controls tumor-reactive CD8+ T lymphocyte exhaustion by activating the IL-2/STAT5/mTOR pathway (Lutz et al. 2023).

3

Immunotherapeutic Approaches to Pancreatic Cancer

3.1

Oncolytic Virus Therapy (OVT)

OVT is a novel kind of immunotherapy in which a virus, after infecting and lysing a cancer cell, stimulates or triggers an immune response in the patient by releasing tumor antigens into the bloodstream (Nisar et al. 2022). The effectiveness and specificity of oncolytic viruses make it a desirable treatment strategy. Different oncolytic DNA and RNA viruses are now being researched and used to treat various cancer types. These viruses’ genetic makeup allows them to infect cancer cells (Lou 2003; Cerullo et al. 2012). T-VEC, a Herpes simplex virus (HSV), is the first oncolytic virus that the US Food and Drug Administration (FDA) has authorized for treating metastatic melanoma (Kaufman et al. 2015; Pol et al. 2016). The T-VEC virus has the gene encoding GM-CSF genetically integrated (Fig. 2) (Kaufman et al. 2015). T-VEC showed significant lytic effects in vitro against many tumor cell lines, including melanoma and pancreatic cancer cells (Toda et al. 2000; Kaufman et al. 2015). Additionally, in vitro and in vivo, NV1020 (r7020) and G207 (two types of

Fig. 2 Principles and mechanism of action of T-VEC oncolytic virus therapy in pancreatic cancer. GM-CSF Granulocyte-macrophage colony-stimulating factor, DC Dendritic cell, HSV-1 Herpes simplex 1, T-VEC Talimogene Laherparepvec. (This figure was created by Biorender.com)

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herpes simplex oncolytic viruses) efficiently infect and destroy human pancreatic cancer cells. NV1020 was first designated as a vaccine against HSV-1 and HSV-2 infection for humans (McAuliffe et al. 2000). Upregulated KRAS levels, a hallmark of PDAC, improve the oncolytic ability of the Bovine Herpesvirus-1 against lung cancer (Cuddington and Mossman 2014). An effective oncolytic virus against KRAS-mutant lung adenocarcinoma is Coxsackievirus Type B3 (Deng et al. 2019). HSVs demonstrated enhanced proliferation compared to adenoviruses, whereas other oncolytic viruses revealed unchanged behavior under hypoxia in malignant cells. Oncolytic viruses have varying adaptabilities under hypoxia in cancerous cells (Hay 2005). Pancreatic cancers are characterized by hypoxia, a key component of the PDAC environment (Yuen and Díaz 2014). Combining a HIF-1α inhibitor with the H-1 oncolytic parvovirus in pancreatic cancer boosted anti-tumor response and accelerated apoptosis (Cho et al. 2015). An E1B gene deletion adenovirus called ONYX-015 (dl1520) is specifically used in head and neck cancer and pancreatic cancer clinical studies. Indeed, the gene that codes for the protein E1B, which may bind to and deactivate the pro-apoptotic protein p53, has been deleted in ONYX-015 (Heise et al. 1997; Mulvihill et al. 2001; Hecht et al. 2003). Hence, these viruses may cause p53-mediated apoptosis in healthy cells, but they can persist in cancer cells that typically inactivate p53 (Kaufman et al. 2015). VCN-01 is an oncolytic adenovirus. It was engineered to replicate in cancer cells that have a defective RB1 pathway, produce hyaluronidase to accelerate viral intratumoral dissemination, and enable the extravasation of chemotherapy and immune cells into the tumor. VCN-01 demonstrated anticancer effects that were enhanced after being combined with chemotherapy in PDAC animals. The production of hyaluronidase by VCN-01 destroyed tumor stroma and enhanced the delivery of several therapeutic drugs, including chemotherapy and therapeutic antibodies (Bazan-Peregrino et al. 2021). The findings of a clinical trial demonstrated that intravenous administration of VCN-01 for treating patients with PDAC is possible and is linked with predictable and controllable adverse events. The tolerability profile of intravenous VCN-01 has been shown to be favorable (Garcia-Carbonero et al. 2022). HF10 is an HSV-1-derived oncolytic virus that has undergone spontaneous mutation and can exert a substantial anti-tumor impact on cancers without harming normal tissue. Locally advanced pancreatic cancer was treated safely with HF10 direct injection in combination with erlotinib and gemcitabine (Hirooka et al. 2018).

3.2

Adoptive Cell Transfer Therapy

Cancer patients may benefit from adoptive cellular therapy, a kind of immunotherapy that employs their own T cells and other immune system cells to combat the disease. Patients’ immune cells are often collected, expanded, and even genetically modified to better combat cancer. With the FDA’s approval of CAR T-cell therapy

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for certain patients with blood malignancies, this field has expanded greatly in recent years. Manipulated T lymphocytes can detect tumor cells based on their unique molecular signatures (Rosenberg et al. 2008; Morotti et al. 2021; Bear et al. 2021). In the following, we will delineate these immunotherapeutic approaches.

3.2.1 Tumor-Infiltrating Lymphocyte (TIL) Therapy The effectiveness of immunotherapy in treating metastatic melanoma has led to its use against other cancers. A promising treatment paradigm is TIL therapy, which employs the patient’s own TILs after surgical removal of the malignancy and subsequent expansion of these cells in vitro before reinfusion. Twenty percent of individuals with metastatic melanoma experienced a favorable response that lasted more than 3 years after receiving this treatment (Rosenberg et al. 2011). Infiltration of CD3+ T lymphocytes is linked to improved progression-free survival (PFS) in patients with gastrointestinal malignancies (Rusakiewicz et al. 2013). Patients with PDAC that had CD4+ and CD8+ T lymphocytes had a considerably better prognosis and a higher 5-year survival (Fukunaga et al. 2004; Ino et al. 2013; Sideras et al. 2014). A study indicated that expanded TILs from pancreatic tumors are functional and have the ability to recognize pancreatic cancer-related antigens (tumorassociated antigens [TAAs] and tumor-specific antigens [TSAs]). Additionally, blockade of the PD-1 receptor, activation of the 4-1BB (CD137) receptor, and enrichment of CD8+ T cells are all successful techniques for increasing TIL production and tumor reactivity (Hall et al. 2016). According to a meta-analysis, PDAC patients’ long-term oncological prognoses are substantially correlated with certain subsets of TILs, particularly CD3+, CD8+, and FOXP3+ T cells (Orhan et al. 2020). Two clinical trials are now in recruiting state, which are going to deploy TIL therapy in patients with metastatic PDAC (NCT01174121 and NCT03935893). 3.2.2

Genetically Modified T Cells

TCR-Engineered T-Cell Therapy TCR-engineered T cells are the result of the ex vivo engineering of T cells to express TCRs specific for TSAs or TAAs. TCRs are able to identify peptides presented by major histocompatibility complex (MHC) class I and II (Shafer et al. 2022; Baulu et al. 2023). In hopes of developing TCR T-cell therapy that is both safe and effective, the selection and screening of appropriate antigens are a crucial step. The ideal antigen would include epitopes that were displayed on MHC class I molecules on the surface of cancerous cells and would also be expressed homogenously and selectively (Baulu et al. 2023). Two suitable targets for TCR T-cell therapy of pancreatic cancer are MSLN and G12D. A phase I clinical trial investigates the effectiveness and safety of autologous MSLN-specific TCR T cells in patients with stage IV pancreatic cancer (NCT04809766). A patient with metastatic PDAC was treated with autologous TCR-engineered T cells. These manipulated T cells clonally express two allogeneic HLA-C*08:02– restricted KRAS G12D. Significantly, the patient’s visceral metastasis regressed (72% overall partial response). Also, the therapeutic response continued for 6 months.

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Additionally, six months following the T-cell transfer, the modified T cells composed more than 2% of all T cells that were circulated in the peripheral circulation (Leidner et al. 2022). KRAS mutations are common in cancers. The most prevalent mutation of KRAS is a single amino acid change called G12D, which is reported in various malignancies, including PDAC (Zhang et al. 2022b; Melief 2022). CAR T-Cell Therapy CAR T-cell therapy, which employs genetically modified T lymphocytes to target cancer antigens, represents an exciting new frontier in tumor treatment (Fig. 3). While CAR T-cell therapy has shown impressive clinical outcomes for treating particular subgroups of B-cell leukemia or lymphoma, various obstacles prevent it from being widely used to treat solid tumors and hematological malignancies. Life-threatening toxicities, poor anti-tumor effectiveness, antigen escape, restricted trafficking, and limited tumor penetration are all obstacles to successful CAR T-cell treatment. Moreover, CAR T-cell functionality is significantly modified by interactions with the host and TME (Sterner and Sterner 2021). The absence of appropriate TSAs is a

Fig. 3 A clinical overview of chimeric antigen receptor (CAR) T cells production, manipulation, and how these cells attack cancerous cells. (This figure was created by Biorender.com)

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key barrier to the successful cellular immunotherapy of PDAC, particularly CAR T-cell therapy. Schäfer et al. identified CD318, TSPAN8, and CD66c among 371 antigens as target candidates for CAR T-cell-based immunotherapy of PDAC (Schäfer et al. 2021). Tables 1 and 2 summarize information on CAR T-cell therapy in preclinical and clinical trial settings. In the following, suitable therapeutic targets for CAR T-cell therapy of pancreatic cancer are highlighted. B7H3 (CD276) B7H3 is a cell surface-expressed immune checkpoint molecule with an immuno-inhibitory effect by dampening T-cell activation and NK cell cytotoxicity. The fact that B7H3 is expressed at unusually high levels in many cancers but at low levels in healthy tissues makes it a promising new target for CAR T-cell therapy (Seaman et al. 2017; Liu et al. 2021; Yan et al. 2023). Mice treated with B7H3 CAR T cells demonstrated completed survival and no adverse effects (Du et al. 2019), whereas in vitro studies indicated that these cells strongly suppressed pancreatic ductal cancer cells (Du et al. 2019; Hu et al. 2022). The administration of B7H3 CAR T cells (TAA06) in patients with neuroblastoma, malignant melanoma, lung cancer, and colorectal tumor has been authorized in clinical studies (NCT05190185 and NCT05562024). Human Epidermal Growth Factor Receptor 2 (HER2) Simply put, HER2 is a transmembrane glycoprotein that plays a pivotal role in cell proliferation and differentiation at both the embryonic and adult stages of development. Inhibiting apoptosis, inducing neovascularization, and enhancing cell motility are all ways in which HER2 facilitates tumor development, proliferation, and metastasis (Yan et al. 2023). The remission of metastatic PDAC is mediated by CAR T-cell therapy with potential safety (Raj et al. 2019). In a phase I trial, the safety and durability of HER2 CAR T cells for treating pancreatic tumors were proven (Feng et al. 2018). Epidermal Growth Factor Receptor (EGFR) The transmembrane protein known as the EGFR binds to members of the extracellular EGF family of proteins. Up to 90% of patients with PDAC have a detectable level of EGFR (Yeo et al. 2022). The median overall survival (mOS) of all 14 patients treated with anti-EGFR CAR T cells was 4.9 months, indicating the safety and efficacy of this therapy for patients with metastatic pancreatic cancer (Liu et al. 2020). Carcinoembryonic Antigen (CEA) Tumor antigen CEA, a tumor-associated glycoprotein, is continually generated by aggressive gastrointestinal cancers. The effectiveness of CEA-specific CAR T cells in conjunction with recombinant human IL-12 (rhIL-12) in treating various solid tumors was assessed. In vivo data demonstrated that when anti-CEA CAR T cells are combined with rhIL-12, they greatly increase their anti-cancer efficacy, as measured by growth inhibition of the pancreatic tumor cell line AsPC-1, compared to CEA CAR T-cell treatment alone (Chi et al. 2019). Furthermore, as a possible target for PDAC, CEACAM7 (also known as CGM2) is a member of the CEA family of proteins expressed only in the colon and the pancreas.

Cyclophosphamide

Nab-paclitaxel +Cyclophosphamide Nab-paclitaxel +Cyclophosphamide –

Combination therapy Nab-paclitaxel +Cyclophosphamide

6

5

–

2

16

Participants with pancreatic cancer 7

SD=2, PD=1

PR=0, SD=0, PD=2

PR=4, SD=8, PD=2

Clinical outcomes (=number of patients) PR=2, SD=3, PD=2

I

I

I

I

Phase I

NCT02159716

NCT01897415

NCT01935843

NCT01869166

NCT identifier NCT02541370

Reference Wang et al. (2018) Liu et al. (2020) Feng et al. (2018) Beatty et al. (2018) Haas et al. (2019)

EGFR Epidermal growth factor receptor, HER2 Human epidermal growth factor receptor 2, MSLN Mesothelin, ScFv Single-chain variable fragment, PR Partial response, SD Stable disease, PD Progressive disease

MSLN

MSLN

Anti-MSLN ScFv+41BB+CD3z

Anti-EGFR ScFv +CD8a+CD137+CD3z Anti-HER2 ScFv+CD8a +CD137+CD3z Anti-MSLN ScFv+41BB+CD3z

EGFR

HER2

CAR’s structure and stimulatory domains Anti-CD133 ScFv +Human CD137+CD3z

Molecular target CD133

Table 1 Clinical evidence of CAR T-cell therapy in pancreatic cancer

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Table 2 Ongoing clinical trials of CAR T-cell therapy in pancreatic cancer Molecular target CCT301-59 CCT303-406 CD22

CD70 CEA

Claudin18.2

Claudin18.2/ CD19/BCMA/ GPC3 EGFR EpCAM EpCAM/ TM4SF1 GD2 HER2

MSLN

MUC-1 PSCA

Combination therapy – – Autologous aPD-L1 armored anti-CD22 CAR T cells Cyclophosphamide +Fludarabine+Aldesleukin – – – – PD-1 monoclonal antibody +Chemotherapy Fludarabine +Cyclophosphamide – – – – – Pembrolizumab – – – – – Rimiducid

Participants with pancreatic cancer 18 15 30

Phase I I I

NCT identifier NCT03960060 NCT04511871 NCT04556669

124

I, II

NCT02830724

75 40 5 110 123

I I, II I I, II I

NCT02349724 NCT04348643 NCT02850536 NCT04404595 NCT03874897

18

N/A

NCT03302403

40 60 72

I, II I, II N/A

NCT03182816 NCT03013712 NCT04151186

100 220 48 45 18 30 40 9 151

I, II I I I I I I, II I, II I, II

NCT02992210 NCT04650451 NCT04660929 NCT03740256 NCT03323944 NCT02706782 NCT03030001 NCT03633773 NCT02744287

CEA Carcinoembryonic antigen, EGFR Epidermal growth factor receptor, EpCAM Epithelial cell adhesion molecule, GD2 Disialoganglioside, TM4SF1 Transmembrane 4 L Six Family Member 1, HER2 Human epidermal growth factor receptor 2, MSLN Mesothelin, MUC-1 Mucin-1, PSCA Prostate stem cell antigen, BCMA B-cell maturation antigen, PD-1 Programmed cell death protein 1, PD-L1 Programmed death-ligand 1, CAR Chimeric antigen receptor, GP3 Glypican 3

Remission in xenograft tumors is mediated by CEACAM7-specific CAR T cells, which can selectively kill antigen-expressing cancerous cells (Raj et al. 2021). Mesothelin (MSLN) CAR T cells can be manipulated to recognize MSLN, a cell surface antigen involved in tumor invasion that is expressed at low levels in mesothelial tissues, but at high levels in mesothelioma, PDAC, ovarian cancer, lung cancer, and breast cancer (Yan et al. 2023). Tomar et al. have developed highly effective anti-MSLN hYP218 CAR T lymphocytes with augmented tumor

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infiltration and persistence for treating solid tumors. In pancreatic cancer (KLM-1)bearing mice, rechallenging treated animals with KLM-1 tumor cells elicited antitumor immunity due to the survival of hYP218 CAR T cells (Tomar et al. 2022). The treatment of patients with metastatic PDAC by concomitant targeting MSLN and CD19 with CAR T cells was safe and well-tolerated (Ko et al. 2020). The effectiveness of MSLN-specific CAR T cells was proven in orthotopic human pancreatic cancer animal models (Lee et al. 2022). A combination of MSLN-redirected CAR T cells and TNF-α/IL-2-armed oncolytic adenoviruses leads to tumor shrinkage in mice engrafted with highly aggressive PDAC (Watanabe et al. 2018). Disialoganglioside (GD2) GD2 is localized on the outer cell membrane and forms part of the immunological identity of mammalian cells; nevertheless, it does not often trigger an immune response. Targeting the GD2 molecules with CAR T cells directed against this molecule is possible since GD2 is expressed by many embryonal malignancies, including brain tumors, but is seldom expressed in normal cells (Yan et al. 2023). A clinical trial investigated the effectiveness and safety of GD2-specific CAR T cells in patients with solid tumors, probably including pancreatic cancer (NCT02992210). Natural Killer Group 2D (NKG2D) The activating receptor NKG2D, present in numerous immune effector cells, plays a crucial function in tumor immunosurveillance. MHC I chain-related molecules A and B (MICA and MICB) are two of the eight NKG2D ligands (NKG2DLs). Six cytomegalovirus UL16binding proteins (ULBP1-6) are also other ligands. In contrast to their high expression levels in cancer cells, NKG2DLs are either missing or expressed at low levels in healthy tissues (El-Gazzar et al. 2013; Fernández et al. 2015). The NKG2D receptor is a promising target for malignant neoplasm immunotherapy. Thus far, NKG2Dspecific CAR T cells have been used to treat hematologic and solid tumor patients. Researchers assessed the viability and safety of NKG2D-specific CAR T cells, finding that their ability to proliferate and persist in vivo was limited. Gao and colleagues have knocked down the 4.1R gene in NKG2D-specific CAR T cells, enhancing the function of CAR T cells against pancreatic carcinoma (Gao et al. 2021). Epithelial Cell Adhesion Molecule (EpCAM) The type I transmembrane glycoprotein EpCAM is overexpressed in carcinomas such as colon, stomach, PDAC, and endometrial malignancies. It has been linked to the Wnt/β-catenin signaling pathway, whose activation is thought to lead to poor T-cell infiltration in various human malignancies (Yan et al. 2023). Several clinical trials are registered to use EpCAMspecific CAR T cells in patients with pancreatic cancer (NCT04151186 and NCT03013712). Mucin-1 (MUC-1; CD227) The transmembrane mucin glycoprotein MUC-1 is highly expressed at the apical surface of epithelial cells. The differentially glycosylated form of MUC-1 is overexpressed in more than 80% of human pancreatic

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adenocarcinomas. Overexpression of MUC-1 is linked to bleak prognosis and augmented metastasis. Besides, MUC-1 promotes chemoresistance in pancreatic cancer cells by upregulation of multidrug resistance genes (Nath et al. 2013). Anti-MUC-1 CAR T cells demonstrated target-specific cytotoxicity and effectively controlled tumor growth in xenograft models of pancreatic cancer (Posey Jr. et al. 2016). Three clinical trials were registered to use MUC-1-specific CAR T cells in patients with pancreatic cancer (NCT02587689, NCT05239143, and NCT04025216). CD133 Hematopoietic and epithelial cells both express the transmembrane glycoprotein CD133. In addition to being strongly expressed in PDAC cancer stem cells (CSCs), CD133 has been discovered in various malignancies, including hepatocellular and gastric carcinomas (Yeo et al. 2022). In a phase I clinical trial, 7 patients with PDAC received CD133-specific CAR T cells. Patients received cyclophosphamide and nab-paclitaxel before receiving CAR T-cell infusion. Overall, there were 3 cases of disease stabilization, 2 cases of partial remission, and 2 cases of disease development (Wang et al. 2018). Prostate Stem Cell Antigen (PSCA) PSCA was first reported as a 123-amino-acid glycophosphatidylinositol-anchored surface glycoprotein with an unidentified function that was substantially expressed in prostate cancers but had minimal basal expression in the prostate epithelium, urinary bladder, kidney, esophagus, stomach, and placenta. Subsequent research proved its increased expression in many human cancers, including pancreatic cancer, but its absence in healthy pancreas. In a humanized mouse model of pancreatic cancer, PSCA-specific CAR T cells induce tumor elimination (Abate-Daga et al. 2014). CAR-NK Cell Therapy NK cells, which constitute 5–10% of peripheral blood lymphocytes, are a crucial element of the innate immune system and play a pivotal role in our first-line defense against infections and tumor cells. NK cells eliminate aberrant cells, such as those damaged by viruses or cancer. NK cells are distinguished from T lymphocytes by the expression of CD56 and CD16 on their surfaces rather than TCR and CD3. NK cells are further split into two primary subsets based on the level of CD56 and CD16 expression: CD16+CD56dim, which represents a more developed and cytotoxic fraction predominantly present in the peripheral blood, and CD16-CD56bright, a less mature and more immunoregulatory subset located in tissues (Basar et al. 2020; Myers and Miller 2021; Daher and Rezvani 2021; Laskowski et al. 2022). There is a lack of decent information on CAR NK cell therapy against pancreatic cancer. However, in an orthotopic mouse model of human PDAC, radiation therapy was more effective when combined with CAR NK immunotherapy targeting ROBO1 (Xia et al. 2019). Moreover, in a mouse model of pancreatic cancer, a combination of CAR NK cells targeting MSLN and cyclic guanosine monophosphate–adenosine monophosphate ([cGAMP]; a STING agonist) inhibited tumor development and increased survival (Da et al. 2022). Furthermore, two clinical trials are registered to use ROBO1 and MUC-1-specific CAR NK cells in

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patients with pancreatic cancer (NCT03941457 and NCT02839954). PSCA has recently been heralded as a target candidate for CAR NK cell immunotherapy of pancreatic cancer. Results indicate the therapeutic effectiveness of PSCA-specific CAR NK cells in human metastatic PDAC models without evidence of systemic toxicity, giving reliable justification for clinical advancement in the future (Teng et al. 2022). Cytokine-Induced Killer (CIK) Cell Therapy As a recent development in the area of cancer immunotherapy, CIK cell therapy is a combination of therapeutic approaches centered on controlling and co-opting a patient’s cells to cure diseases. In vitro-grown T lymphocytes known as CIK cells have two significant subgroups that make them distinct from other T lymphocytes. A broad range of MHC-unrestricted anti-tumor activity may be elicited by the first subset, which has a CD3+CD56+ phenotype, against both solid and hematologic cancers. The second group, which has the phenotype CD3+CD56-, more closely resembles typical T cells (Meng et al. 2017). Adoptive transfer of CIK cells has shown significant efficacy and safety for treating cancer, as evidenced by the longer life of patients with various tumor types (Schmidt-Wolf et al. 1991; Takayama et al. 2000; Gammaitoni et al. 2013; Wang et al. 2014, 2015; Schmeel et al. 2015). CIK cell therapy is more effective in preventing cancer recurrence and improving patients’ prognosis when used in combination with chemotherapy (Wu et al. 2008; Li et al. 2012; Pan et al. 2014). Furthermore, CIK cell therapy, according to research, is effective in killing CSCs in both animal models and human patients (Gammaitoni et al. 2013; Sangiolo et al. 2014). The use of CIK cells as a second-line therapy for advanced pancreatic cancer has recently been explored, and the results achieved have been promising, both when used alone and in combination with other therapies. Patients receiving CIK cells with gemcitabine-refractory advanced pancreatic cancer had a mOS of 6.2 months in a phase II clinical study (Chung et al. 2014). Patients with gemcitabine-resistant advanced pancreatic cancer who received CIK cell therapy plus S-1, an oral fluoropyrimidine derivative, had a mOS of 6.6 months, which was longer than the mOS of patients receiving S-1 alone (6.1 months) (Wang et al. 2013). OS is improved in patients with advanced pancreatic cancer after CIK cell therapy (Wang et al. 2016).

3.3

Immune Checkpoint Blockade (ICB)

A successful ICB approach, the foremost of which, is ipilimumab, which was licensed in 2011, has led to emerging immunotherapy as a new mainstay of cancer treatment. ICB prevents or reverses acquired peripheral tolerance to cancer antigens by blocking receptors and ligands implicated in pathways that attenuate T-cell activation, such as CTLA-4, PD-1, and PD-L1 (Fig. 4) (Korman et al. 2022). Table 3 provides clinical trials of immune checkpoint inhibitors and immunomodulatory agents for treating pancreatic cancer.

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Fig. 4 CTLA-4 and PD-1 functions as two well-known inhibitory immune checkpoints. During priming phase of T-cell activation occurring in lymph nodes, MHC/TCR (signal 1) and B7/CD28 (signal 2) interactions lead to transduce stimulatory signals to the T cell. In contrast, B7/CTLA-4 interaction induces an inhibitory signal in T cells. Monoclonal antibodies directed against CTLA-4 can reinvigorate T cells via disruption of CTLA-4/B7 connection. During effector phase occurring in peripheral tissues, pancreatic cancer cells upregulate PD-L1 expression. PD-1/PD-L1 interaction suppresses tumor-specific T cells, inducing an exhaustion phenotype in these cells. Monoclonal antibodies directed against PD-1 and PD-L1 can revive T cells. TCR T-cell receptor, PD-1 Programmed cell death protein 1, PD-L1 Programmed death-ligand 1, CTLA-4 Cytotoxic T lymphocyte antigen-4, MHC Major histocompatibility complex, DC: Dendritic cell. (This figure was created by Biorender.com)

PD-1/PD-L1 Axis The PD-1/PD-L1 axis was studied in PC with other immune checkpoint molecules after the successful clinical deployment of anti-PD-1/PD-L1 treatment in melanoma. The PD-1 molecule is a member of the B7-CD28 protein family (Greenwald et al. 2005; Li et al. 2022). The exhaustion of T cells is linked to the expression of PD-1, which is mostly found on effector CD4+ and CD8+ T cells (Keir et al. 2008; Ahmadzadeh et al. 2009; Sfanos et al. 2009). Tumor cells, MDSCs, TAMs, and tumor-infiltrating DCs express the PD-1 ligands PD-L1 and PD-L2. In addition to T cells and APCs, B and neoplastic cells express PD-1. Despite the low level of PD-1 expression in naive T cells, prolonged antigen exposure activates the PD-1/PD-L1 signaling pathway, ultimately leading to T-cell exhaustion. Since PD-L1 is overexpressed by tumor cells, an engagement between PD-1 and PD-L1 recruits the tyrosine phosphatase SHP2, which dephosphorylates CD28 and blocks T-cell activation (Li et al. 2022). PDAC has been shown to benefit with combination immunotherapy with antibodies against PD-L1 and CCL5 (Wang et al. 2020). By decreasing Treg and TAM infiltration and inducing CD8+ T-cell activation in the PDAC microenvironment, the combination of anti-tumor necrosis factor receptor 2 (TNFR2) and PD-L1 mAbs led to tumor regression, improved OS, and induced strong anti-tumor memory cells (Zhang et al. 2022a).

117 48 77 21 114 65 80 21 76

– Pexidartinib (PLX3397) Acalabrutinib (ACP-196) Gemcitabine hydrochloride Nab-Paclitaxel+Gemcitabine+Carboplatin Radiotherapy Radiotherapy Radiotherapy Cyclophosphamide+GVAX cancer vaccine

CSF1R, PD-1 PD-L1 PD-1 CTLA-4 PD-1 PD-L1, CTLA-4 PD-1, CTLA-4 PD-1 PD-1, CD137 (4-1BB), IL-8 PD-1

PD-1, CTLA-4

Nivolumab+ Ipilimumab

61

93

313

–

CSF1R, PD-1

CRS-207 vaccine+GVAX +Cyclophosphamide CRS-207 vaccine+GVAX +Cyclophosphamide

80 18 20 59 24 140

PD-1 PD-1 PD-1 PD-1 PD-1 PD-L1, CD40

Pembrolizumab Pembrolizumab Pembrolizumab Pembrolizumab Pembrolizumab Atezolizumab (MPDL3280A) +Selicrelumab (RO7009789) Cabiralizumab (FPA008)+Nivolumab (BMS-936558) AMG820+Pembrolizumab Durvalumab (MEDI4736) Pembrolizumab Ipilimumab Nivolumab Durvalumab+Tremelimumab Nivolumab+ Ipilimumab Anti-PD-1 antibody Nivolumab+ Urelumab (BMS-663513) +BMS-986253 Nivolumab

Number of participants 340

Combination therapy Nab-Paclitaxel+Gemcitabine+Oxaliplatin +Leucovorin+Cobimetinib+Fluorouracil +PEGPH20+BL-8040 (CXCR4 antagonist) +RO6874281+AB928+LSTA1 Onivyde+BL-8040 CXCR4 antagonist BL-8040 Olaptesed pegol Defactinib Paricalcitol Dual immune checkpoints blockade

Molecular target PD-L1, CD40, VEGF, TIGIT, IL-6 receptor

Immune checkpoint inhibitor and immunomodulator Atezolizumab+Selicrelumab (CD40 agonist)+Bevacizumab+Tiragolumab +Tocilizumab

Table 3 Clinical trials of immune checkpoint inhibitors and immunomodulatory agents in pancreatic cancer

II

II

I, II I II I I I, II II II II

I

II II I, II I, II II I

Phase I, II

NCT03190265

NCT02243371

NCT02713529 NCT02777710 NCT02362048 NCT01473940 NCT02309177 NCT02311361 NCT03104439 NCT03374293 NCT02451982

NCT02526017

NCT02826486 NCT02907099 NCT03168139 NCT02758587 NCT03331562 NCT02304393

NCT identifier NCT03193190

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PD-1 PD-1

CSF1R+PD-1

PD-1

PD-1

PD-1+CSF1R PD-1

CTLA-4, PD-1

TIM-3 TIM-3, PD-1, LAG-3 TIM-3, PD-L1 TIM-3, PD-1

Pembrolizumab Nivolumab

Cabiralizumab+Nivolumab+

Nivolumab

Pembrolizumab

Pembrolizumab+ IMC-CS4 Pembrolizumab

Ipilimumab+Nivolumab

Sym023 BGB-A425+Tislelizumab (BGB-A317) +LBL-007 LY3321367+LY3300054 BMS-986258+Nivolumab

24 358 275 92

– Human hyaluronidase PH20

25

12 40

58

30

202

43 129

8 9

CV301 vaccine+Capecitabine Gemcitabine hydrochloride+Nab-paclitaxel +Paricalcitol Defactinib+Gemcitabine Nab-Paclitaxel+Gemcitabine+APX005M (CD40 agonistic monoclonal antibody) Nab-paclitaxel+Onivyde+Fluorouracil +Gemcitabine+Oxaliplatin+Leucovorin +Irinotecan hydrochloride Cyclophosphamide+ GVAX cancer vaccine +Radiotherapy Cyclophosphamide+ GVAX cancer vaccine +Radiotherapy Cyclophosphamide+ GVAX cancer vaccine Epacadostat (INCB24360)+CRS207+GVAX cancer vaccine +Cylophosphamide Proleukin+Cyclophosphamide+Fludara+TIL therapy – – I I, II

I I, II

I, II

I II

II

II

II

I I, II

I, II I

NCT03099109 NCT03446040

NCT03489343 NCT03744468

NCT03296137

NCT03153410 NCT03006302

NCT02648282

NCT03161379

NCT03336216

NCT02546531 NCT03214250

NCT03376659 NCT02930902

PD-1 Programmed cell death protein 1, PD-L1 Programmed death-ligand 1, LAG-3 Lymphocyte activation gene-3, TIM-3 T-cell immunoglobulin and mucin domain-containing protein 3, TIGIT T-cell immunoreceptor with Ig and ITIM domains, CTLA-4 Cytotoxic T lymphocyte antigen-4, CSF1R Colony stimulating factor 1 receptor, VEGF Vascular endothelial growth factor, TIL Tumor-infiltrating lymphocyte

PD-L1+VEGF PD-1

Durvalumab+Bevacizumab Pembrolizumab

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CTLA-4 (CD152) The expression of CTLA-4 is largely found in Treg cells, and a rise in the expression of CTLA-4 is shown as a consequence of T-cell activation. The CD25-expressing helper T cells were shown to express CTLA-4. CTLA-4 functions in a way that is intrinsic to the cell by suppressing the co-stimulatory signal, which in turn hinders T-cell activation. Extrinsically, CTLA-4 acts by eliminating CD80 and CD86 from APCs, which in turn reduces the response of CD8+ T cells and regulates the infiltration of CD4+ T cells (Li et al. 2022). The infiltration of T cells into the pancreatic cancer microenvironment is controlled by the CTLA-4/CD80 pathway. CD4+ T-cell infiltration into the PDAC microenvironment was induced by disrupting the interaction between CD80 and CTLA-4 (Bengsch et al. 2017). A study demonstrated for the first time that IL-6 and CTLA-4 blockade regressed pancreatic tumors in a T-cell and CXCR3-dependent manner (Ware et al. 2023). Lymphocyte-Activation Gene 3 (LAG-3) The LAG-3 signaling pathway is used by cancer cells as a means of evading immune monitoring. Galectin-3 can decrease the function of activated T cells by binding to LAG-3 on their surface. Concurrently, LAG-3 reduces the activity of plasmacytoid DCs, which are cells that deliver antigen and trigger the development of naive T cells. T-cell proliferation can be modulated by LAG-3, which also reduces memory and effector T-cell responses and increases immunosuppression through Treg cell-mediated suppression (Li et al. 2022). TILs that express LAG-3 have been linked to decreased OS in patients with pancreatic cancer (Seifert et al. 2021). Anti-tumor immunity and a long-lasting response are achieved in pancreatic cancer by blocking the immune checkpoints on T cells, including LAG-3 and CD137 (4-1BB), and myeloid cell CXCR1/CXCR2 (Gulhati et al. 2023). T-Cell Immunoglobulin and Mucin Domain 3 (TIM-3) TIM-3 is responsible for inhibiting the T-cell response by interacting with TAAs such as CEACAM-1 and galectin-9 (Anderson et al. 2016). The formation of heterodimers between CEACAM-1 and TIM-3, which limits the T-cell response by reducing the IL-2 and TNF-α expression, is correlated with T-cell exhaustion (Huang et al. 2015; Anderson et al. 2016). Blocking TIM-3 and CEACAM-1 with antibodies increased CD8+ T-cell infiltration and IFN-γ production, which in turn reduced the development of the tumor (Zhu et al. 2005). Galectin-9, which is produced by tumor cells, binds to TIM-3, which then activates downstream signaling. This causes Ca2+ influx in helper T cells, which ultimately results in the death of these cells. Additionally, tumor-infiltrating DCs that expressed TIM-3 had an interaction with nuclear high mobility group box 1 protein (HMGB1), which decreased the effectiveness of chemotherapy by lowering the immunogenicity of nucleic acids generated from the tumor cells (Chiba et al. 2012; Li et al. 2022). TIM-3 is responsible for limiting anti-tumor immunity by mediating T-cell trogocytosis. The tumor burden was reduced and survival was increased in two mice models of melanoma by blocking TIM-3 and PD-1 simultaneously, which disrupted the trogocytosis of CD8+ TILs (Pagliano et al. 2022). Additionally, Bat3, a protein that binds to TIM-3 regulates tolerogenic dendritic cell activity in an endogenous manner (Tang et al. 2023).

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A study confirmed that TIM-3 was upregulated in pancreatic cancer cells and tissues. Also, elevated levels of TIM-3 expression in pancreatic cancer tissues may be linked to tumor cell invasion, metastasis, and recurrence (Peng et al. 2017). Furthermore, there was no correlation between the TIM-3/Galectin-9 and patients’ prognosis (NAKAYAMA et al. 2022). T-Cell Immunoglobulin and ITIM Domain (TIGIT) TIGIT is expressed on the cell surface and inhibits T-cell stimulation by triggering the development of immunomodulatory dendritic cells (Yu et al. 2008). TIGIT binds to its ligands, CD155 and CD112, to provide signals that suppress T-cell activation. TIGIT may also suppress the active signal to T cells by binding competitively to CD266 or CD96 with CD155 and CD112 (Stanietsky et al. 2009; Dougall et al. 2017; Farhangnia et al. 2022). TIGIT interaction with CD155 also causes CD155 phosphorylation and release of IL-10, which suppresses T-cell activation (Farhangnia et al. 2022). In pancreatic cancer, the CD155/TIGIT axis fosters and sustains immune evasion (Freed-Pastor et al. 2021). The effectiveness of vaccinations in a pancreatic cancer model is improved by combination of TIGIT and PD-1 blockade (Peng et al. 2022). The combination of TIGIT/PD-1 co-blockade and CD40 agonism reinvigorated pancreatic tumor cells-specific T lymphocytes (Freed-Pastor et al. 2021). The V-Domain Ig-Containing Suppressor of T-Cell Activation (VISTA) The B7 family member VISTA is homologous with the PD-L1 protein (Wang et al. 2011; Gao et al. 2017; Ni and Dong 2017). VISTA is expressed in T lymphocytes and endothelial cells (Hou et al. 2021). Pancreatic cancer is characterized by an upregulation of the immunological checkpoint VISTA. CD68+ macrophages are the primary cell type expressing VISTA. It has been demonstrated that VISTA activation suppresses cytokine generation by T cells isolated from metastatic pancreatic cancers (Blando et al. 2019). In light of this, anti-VISTA mAbs may serve as a useful immunotherapeutic approach for patients with pancreatic cancer (Blando et al. 2019; Hou et al. 2021). Furthermore, in pancreatic cancer, a better prognosis is linked to VISTA expression (Hou et al. 2021).

3.4

Cancer Vaccines

Therapeutic cancer vaccines cause tumor regression, eliminate any remaining malignancy, generate long-lasting anti-tumor memory, and prevent any undesirable, non-specific effects (Fig. 5). Vaccines against cancer often entail the exogenous delivery of tumor antigens together with adjuvants or even DCs themselves that stimulate the immune system (Saxena et al. 2021). Table 4 presents the classification of cancer vaccines in the context of pancreatic cancer studies. Furthermore, Table 5 provides clinical trials of cancer vaccines. Whole Tumor Cell Vaccines The use of a complete tumor cell vaccination is a straightforward and uncomplicated method of tumor immunotherapy. Both CD4+

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Fig. 5 Principles and mechanisms of action of cancer vaccines. Following injection of tumor antigens, these molecules are taken up and presented by APCs, particularly dendritic cells. As a result, naïve or memory CD4+ and CD8+ T cells activated by APCs. These activated lymphocytes migrate to tumor microenvironment, where they recognize and eradicate antigen-expressing tumor cells. TCR T-cell receptor, IL-2 Interleukin 2, TNF Tumor necrosis factor, IFNγ Interferon-gamma, APC Antigen-presenting cell, IL-12 Interleukin-12, MHC Major histocompatibility complex. (This figure was created by Biorender.com)

helper T-cell and CTL epitopes are present in the tumor cell vaccination. One of these vaccines is Algenpantucel-L (NLG0205). Allogeneic cancer cell lines transduced with α-1,3-galactosyltransferase are used to produce the vaccine Algenpantucel-L. α-1,3-galactosyltransferase synthesizes α-galactosylated epitopes on cell surface proteins with potential anti-tumor activity (Bot et al. 2018; Tekkesin and Tetik 2019). A phase II trial showed that when Algenpantucel-L was combined with the adjuvants gemcitabine and 5-fluoruracil, 1-year survival rates of 86%, 2-year survival rates of 51%, and 3-year survival rates of 42% were achieved (Hardacre et al. 2013). However, a study revealed that patients with locally advanced or borderline resectable PDAC who received standard of care, neoadjuvant chemotherapy, and chemoradiation did not benefit from Algenpantucel-L immunotherapy (Hewitt et al. 2022). Dendritic Cell Vaccines TAAs or TAA-coding or tumor-derived mRNA were loaded into DCs separated from the patient’s peripheral blood and then re-infused. The modified DCs then move on to the lymph nodes, where they deliver antigens to T lymphocytes while simultaneously providing co-stimulatory signals (McCormick et al. 2016). Autologous monocyte-derived DCs loaded with mRNA encoding for CEA resulted in all patients in a trial of 3 patients with stages I/II pancreatic cancer staying alive and disease-free more than 2.5 years after diagnosis (Morse et al. 2002). Apheresis was used to collect DCs from 7 patients with stage III/IV pancreatic cancer, and these DCs were then pulsed with MUC-1 peptide. In these patients,

Table 4 Classification of cancer vaccines in pancreatic cancer treatment Type of vaccine Whole tumor cell vaccine Peptide vaccine

Mechanism Irradiated tumor cells expressing TAAs

Epitope, peptide, or protein expressed by pancreatic tumor cells

Candidate vaccine Algenpantucel-L (NLG0205) GVAX RAS oncogenebased vaccine: GI-4000

Gastrin-based vaccine: G17DT Telomerase-based vaccine: GV1001 VEGFR-based vaccine: VXM01

DC vaccine

DNA vaccine

mRNA vaccine Viral/ bacterial vectorbased vaccine

DCs are pulsed with TAAs or TSAs.

Administration of genetically engineered DNA cells to produce an antigen, resulting in a protective immunological response. mRNA encoding TSAs and TAAs Immunogenic viral or bacterial vectors expressing TSAs and TAAs

Survivin-based vaccine: AYACNTSTL HSP-peptide complex-based vaccines: HSPPC-96 MUC-1-pulsed DCs DC vaccine plus LAK cells DCs loaded with mRNA encoding CEA ENO1 DNA vaccine MUC-1-VNTRn Chimeric DNA encoding FAPα and survivin RO7198457 Live-attenuated Listeria Monocytogenes encoding MSLN: CRS-207 Heat-killed whole cell vaccine of Mycobacterium obuense: IMM101

Reference Hardacre et al. (2013) Lutz et al. 2011; Le et al. (2015) Gjertsen et al. (1995, 2001), Wedén et al. (2011), AbouAlfa et al. (2011), Cohn et al. (2018), Muscarella et al. (2021) Brett et al. (2002), Gilliam et al. (2012) Bernhardt et al. (2006), Middleton et al. (2014) Miyazawa et al. (2010), Niethammer et al. (2012), Schmitz-Winnenthal et al. (2015) Kameshima et al. (2013)

Maki et al. (2007)

Rong et al. (2012) Kimura et al. (2012) Morse et al. (2002)

Cappello et al. (2013), Mandili et al. (2020) Gong et al. (2017) Geng et al. (2022)

NCT04161755 Le et al. (2015)

Dalgleish (2015), Dalgleish et al. (2016)

DC Dendritic cell, TSA Tumor-specific antigen, TAA Tumor-associated antigen, MSLN Mesothelin, HSP Heat-shock protein, FAPα Fibroblast activation protein alpha, MUC-1 Mucin-1, ENO1 α-Enolase, VNTRn Variable number tandem repeat, LAK Lymphokine-activated killer, VEGFR Vascular endothelial growth factor receptor, CEA Carcinoembryonic antigen

Stimulating tumor-specific T-cell immune responses

KRASG12D, KRASG12R

KRAS

TAAs

ELI-002

KRAS peptide vaccine+PolyICLC adjuvant

Imiquimod (TLR7 agonist)+ Pembrolizumab+ Sotigalimab (APX005M; CD40 agonist antibody)

150

I

I

12

I

I

25

–

I

I

Phase I

30

18

–

Nivolumab (anti-PD-1 mAb) +Ipilimumab (anti-CTLA-4 mAb) –

29

Participants 70

Atezolizumab (anti-PD-L1 mAb) +FOLFIRINOX

Combination therapy Pembrolizumab (anti-PD-1 mAb)

NCT02600949

NCT03956056

NCT04117087

NCT05013216

NCT04853017

NCT04161755

NCT identifier NCT03948763

ICB Immune checkpoint blockade, TAA Tumor-associated antigen, APC Antigen-presenting cell, TLR7 Toll-like receptor 7, mAb Monoclonal antibody, PD-1 Programmed cell death protein 1, PD-L1 Programmed death-ligand 1, CTLA-4 Cytotoxic T lymphocyte antigen-4

Neo-antigen peptide vaccine +Poly-ICLC adjuvant Personalized synthetic peptide vaccine

TAAs

RO7198457

KRASG12C, KRASG12V, KRASG12D, KRASG12A, KRASG13D, KRASG12R Prioritized neo-antigens and personalized mesothelin epitopes

Mechanism A tetravalent mRNA cancer vaccine targeting mutations in the KRAS gene A personalized mRNA cancer vaccine, in which mRNA encoding certain TAAs is taken up by APCs, and prompts immunological responses from both cytotoxic and memory T cells. A peptide-based cancer vaccine containing amphiphile KRAS peptides plus CpG adjuvant A peptide-based cancer vaccine eliciting immune response against mutant KRAS Inducing immune response against mutant KRAS and enhancing immune responses through ICB Stimulating tumor-specific CD4+ and CD8+ T-cell immune responses

Molecular target KRASG12D, KRASG12V, KRASG13D, KRASG12C

Vaccine mRNA-5671/ V941

Table 5 Active clinical trials of cancer vaccines in pancreatic cancer

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injection of MUC-1-pulsed DCs was safe and effective at eliciting an immune response to the MUC-1 (Rong et al. 2012). Peptide Vaccines It has been revealed that the anti-cancer vaccine candidate GV1001 (created from a peptide derived from a reverse-transcriptase portion of telomerase, or hTERT), possesses surprising cell-penetrating peptide characteristics (Günes and Rudolph 2013; Mocellin et al. 2013; Kim et al. 2016). A significant immune response was observed in 24 (63%) of 38 patients in a phase II study of GV1001 for advanced pancreatic cancer; immune responders had a better median survival (216 days) than non-responders did (88 days) (Bernhardt et al. 2006). However, in a phase III clinical trial, no significant improvement in OS was observed when chemotherapy was combined with the GV1001 vaccine (Middleton et al. 2014). Another peptide cancer vaccine was KIF20A-66. This peptide is an HLA-A24 restricted epitope generated from KIF20A, a protein that is highly transactivated in pancreatic cancer and is a member of the kinesin superfamily, protein 20A. The results of a phase I/II trial showed that the immunization with the KIF20A-66 peptide was well-tolerated. mOS was 142 days, while the median PFS was 56 days (Asahara et al. 2013). DNA Vaccines DNA vaccination targeting α-Enolase (ENO1), a TAA that is overexpressed in PDAC, effectively prolongs survival in mice that spontaneously develop PDAC (Cappello et al. 2013). Additionally, chemotherapy with gemcitabine for pancreatic cancer improves the efficacy of ENO1 DNA vaccine against TAAs, including ENO1, glyceraldheyde-3-phosphate dehydrogenase (G3P), keratin, type II cytoskeletal 8 (K2C8), and far upstream binding protein 1 (FUBP1) (Mandili et al. 2020). Another DNA vaccine named mucin 1-variable number tandem repeat (MUC1-VNTRn) showed robust cytotoxic effects in both in vivo and in vitro investigations (Gong et al. 2017). A chimeric DNA vaccine against human fibroblast activation protein alpha (FAPα) and survivin was developed by Geng and colleagues. DNA vaccination in mice with pancreatic tumors not only decreased the number of immunosuppressive cells, but also increased the number of TILs, reshaping the TME to better accommodate anti-tumor immune responses (Geng et al. 2022). mRNA Vaccines Personalized mRNA cancer vaccines contain mRNA encoding certain TAAs. Afterwards, the mRNA is internalized and the corresponding peptide antigens are displayed by APCs, leading to the triggering of immune responses from both cytotoxic and memory T cells (Fig. 6). RO7198457 (BNT122) is an mRNA cancer vaccine designed to stimulate T-cell-mediated immune responses against neo-antigens. Several clinical trials are planned in patients with different cancers, including pancreatic cancer (NCT04161755), solid tumors (NCT03289962), melanoma (NCT03815058), and colon cancer (NCT04486378).

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Fig. 6 Principles and mechanism of action of mRNA cancer vaccines. Following injection of mRNA cancer vaccine, mRNA encoding tumor-specific antigen (TSA) or tumor-associated antigen (TAA) are taken up by dendritic cells (DCs) via endocytosis. Afterward, DCs translate mRNA to tumoral proteins. Thereafter, naïve CD4+ and CD8+ T cells are primed and activated by tumor antigens-presenting DCs in a MHC-II and MHC-I-reliant manner, respectively. Thus, effector T cells can affect tumor growth and induce apoptosis in cancerous cells. TNFα Tumor necrosis factor alpha, IFNγ Interferon gamma, IL-2 Interleukin-2, MHC Major histocompatibility complex, TCR T-cell receptor. (This figure was created by Biorender.com)

3.5

Immunotherapeutic Strategies Based on Targeting Myeloid Cells and CAFs

In this section, we strive to highlight the therapeutic aspects of targeting myeloid cells in pancreatic cancer. Also, Table 6 provides clinical trials of immunotherapies based on targeting myeloid cells and CAFs.

3.5.1 Targeting Macrophages Macrophages are more prevalent in PDAC and play a role in tissue healing, promoting the proliferation of epithelial cells and even promoting tumor development (Mitchem et al. 2013). However, macrophage depletion approaches in solid tumors are ineffective because other myeloid cell populations tend to rise to compensate (Twyman-Saint Victor et al. 2015). A novel treatment paradigm might come from therapies that retrain macrophages to engulf and destroy living tumor cells. Antibodies that stimulate the phagocytic program in macrophages were initially discovered in PDAC treated with agonistic anti-CD40 (Beatty et al. 2011; Hosein et al. 2022). Original research suggested that anti-CD40 antibody only affected macrophages, but further studies have revealed that it also stimulated DCs and improved T-cell priming (Long et al. 2016; Byrne and Vonderheide 2016; Morrison

CAFs

Gemcitabine+Nabpaclitaxel Nivolumab+Albuminbound paclitaxel +Cisplatin+Gemcitabine FOLFIRINOX +Nivolumab +Radiotherapy+Surgery Spartalizumab (PDR001) +Gemcitabine+Nabpaclitaxel Spartalizumab+Nabpaclitaxel+Gemcitabine

Pembrolizumab +Chemotherapy

-

Combination therapy Nivolumab+ Gemcitabine+Nabpaclitaxel Nivolumab

10

165

I

II

II

II

10

168

I,II

I

II

I

Phase I,II

112

132

24

20

Participants 40

NCT04581343

NCT04390763

NCT03563248

NCT02754726

NCT03520790

NCT03329950

NCT04536077

NCT04477343

NCT identifier NCT03496662

Huang et al. (2019), Grauel et al. (2020) Biffi et al. (2019), Steele et al. (2021)

Murphy et al. (2019)

Preclinical/ clinical reference Mitchem et al. (2013), Sanford et al. (2013) Steele et al. (2016) Hegde et al. (2020), Lin et al. (2020) Hegde et al. (2020), Lin et al. (2020) Sherman et al. (2014) Sherman et al. (2014)

CCR2 C-C Motif chemokine receptor type 2, CXCR2 C-X-C Motif Chemokine Receptor 2, CAF Cancer-associated fibroblast, M-MDSC Monocytic myeloidderived suppressor cell, PMN-MDSC Polymorphonuclear myeloid-derived suppressor cell, ATR2 Angiotensin II receptor, DC Dendritic cell, VDR Vitamin D receptor, FLT3L Fms-related receptor tyrosine kinase 3 ligand, TGF-β Transforming growth factor beta, IL-1β Interleukin-1 beta

IL-1β/Canakinumab (ACZ885)

CAFs

TGF-β/NIS793

Inhibiting IL-1β signaling

CAFs

ATR2/Losartan

Inhibiting TGF-β activity

CAFs

VDR/Paricalcitol

Targeting CAFs

PMNMDSCs Conventional DCs

Cellular target M-MDSCs

FLT3L and CD40 agonists/ CDX-301 and CDX-1140

CXCR2/SX-682

Molecular target/ drug CCR2/BMS-813160

Reprogramming DCs

Therapeutic approach Targeting immunosuppressive myeloid cells

Table 6 Active clinical trials of immunotherapies based on targeting myeloid cells and cancer-associated fibroblasts in pancreatic cancer

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et al. 2020). However, anti-CD40 mAb APX005M (sotigalimab) did not improve clinical outcomes in a phase II trial, indicating that T-cell-priming function related to anti-CD40 mAb in human PDAC might not represent its fundamental mechanism of action (O’Hara et al. 2021). In mice treated with the nuclear factor kappa-light-chainenhancer of activated B cells (NF-κB) modulator LCL-161, macrophages that phagocytize and kill pancreatic tumor cells were described. This was accomplished by reprogramming macrophages to produce lymphotoxin from T cells (Roehle et al. 2021; Hosein et al. 2022). CD47, often known as the “don’t eat me” ligand, is expressed on cancer cells and can impede phagocytosis by engaging signal regulatory protein-α (SIRP-α) on macrophages. However, blocking CD47 by itself has minimal impact on most solid tumors because it does not provide a prophagocytic response (Chao et al. 2010; Weiskopf et al. 2013; Sockolosky et al. 2016; Feng et al. 2019). Alterations in the pivotal carbon metabolism of macrophages are evoked by stimulation with a CpG oligodeoxynucleotide, an agonist for the TLR9. These changes make it conceivable for macrophages to engage in anti-cancer activities, including engulfing CD47+ cancer cells (Liu et al. 2019). Signal transduction by colony-stimulating factor 1 receptor (CSF1R) in macrophages may be a worthwhile therapeutic target for reprogramming the immunosuppressive milieu in human PDAC tumors and improving the therapeutic effectiveness of immunotherapy. TAMs are eliminated from pancreatic tumors when the CSF1/CSF1R signaling pathway is blocked, and the remaining macrophages are reprogrammed to enhance anti-tumor immunity. The CSF1/CSF1R blockage improves anti-tumor interferon responses, boosts CTL infiltration, and prevents tumor growth (Zhu et al. 2014).

3.5.2 Targeting CAFs Most chemokines that attract myeloid cells come from activated fibroblasts. A renewed interest in broadly targeting subgroups of fibroblasts or their secreted products has emerged despite failing to target PDAC CAFs (Hosein et al. 2022). mAbs directed against TGF-β have a wide range of effects on immune responses, including a reduction of intratumoral fibroblasts, a lowering of CD8+ T-cell repression, and a lessening of myeloid cell infiltration (Mariathasan et al. 2018; Huang et al. 2019; Grauel et al. 2020). A phase II clinical trial is now assessing the effectiveness of combining gemcitabine, nab-paclitaxel, and PD-1 inhibitor (spartalizumab) with an anti-TGF-β mAB (NIS793) in patients with PDAC (NCT04390763). Furthermore, nivolumab (anti-PD-1 mAb) and chemoradiotherapy (FOLFIRINOX [fluorouracil, leucovorin, oxaliplatin, and irinotecan] plus stereotactic body radiotherapy [SBRT]) are now being investigated in advanced PDAC, and the angiotensin II receptor antagonist (losartan) is thought to have a role in reducing TGF-β expression (Murphy et al. 2019). Vitamin D may also promote quiescence in fibroblasts (Hosein et al. 2022). In this regard, for patients with advanced PDAC, two phase II trials are now recruiting participants: one combining paricalcitol with gemcitabine and nab-paclitaxel (NCT03520790) and the other combining nivolumab with gemcitabine, paclitaxel, and cisplatin (NCT02754726).

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The macrophages and granulocytes in PDAC vigorously produce IL-1β, which has pleiotropic effects on the TME, including promoting the development of inflammatory CAFs, which in turn generate IL-6 and have been shown to promote an immunoregulatory microenvironment and tumor cell longevity (Biffi et al. 2019; Steele et al. 2021). PDAC tumor cells may also generate IL-1β, and blocking IL-1β has synergistically favorable effects with blocking PD-1 in preclinical studies (Das et al. 2020). A phase I trial is now evaluating the effectiveness of gemcitabine and nab-paclitaxel in combination with the IL-1β-blocking mAb (canakinumab) and the PD-1-blocking mAb (spartalizumab; NCT04581343). Cancer cells and CAFs both have high levels of expression of the prolyl isomerase PIN1 (Koikawa et al. 2021). Several oncogenic pathways are promoted by PIN1, which controls the conformational change in the phosphorylated Serine/ThreonineProline motif (Yeh and Means 2007; Zhou and Lu 2016). Therefore, blocking PIN1 with drugs has been considered to be an effective approach to combating cancer (Koikawa et al. 2021; Liu et al. 2022). Several small molecule drugs, including all-trans retinoic acid (ATRA), arsenic trioxide, juglone, AG17724, KPT-6566, and sulfopin, have been found as PIN1 inhibitors and have been applied or repurposed to study PIN1 functions in oncogenesis (Liu et al. 2022). Promising results are shown in the phase I clinical trial of chemotherapy with ATRA for patients with metastatic PDAC (Kocher et al. 2020). In PDAC models, the addition of ATRA to arsenic trioxide or sulfopin treatment induces a quiescent CAF state and reduces the forming of adhesions or fibrous connective tissue within the tumor. Furthermore, PIN1 inhibition results in decreased degradation of the gemcitabine plasma membrane transporter (ENT1), increasing chemosensitivity, and it may synergize with immunotherapy (Dubiella et al. 2021; Koikawa et al. 2021). Subcutaneous and orthotopic pancreatic cancer models showed decreased tumor development when treated with DNA-barcoded micellular system encapsulating the PIN1 inhibitor AG17724, antiFAPα mAb, and T CD8+ lymphocytes-recruiting DNA aptamer (Liu et al. 2022). Placental growth factor (PlGF) is a member of the VEGF family and is mainly expressed in the placenta (Chau et al. 2017). Improvements in survival were observed in animal models of intrahepatic cholangiocarcinoma after blocking PlGF, which enriched quiescent CAFs and decreased desmoplasia (Aoki et al. 2022). PlGF enhances murine liver fibrosis and promotes tumor angiogenesis, improving cancer cell metastasis and invasion (Kim et al. 2022). PlGF is upregulated by chemotherapy, which directly triggers CAFs to generate the extracellular matrix (ECM) in PDAC. Using a combinatorial therapeutic strategy and the VEGF decoy receptor, targeting CD141+ CAFs with atezolizumab (an anti-PD-L1 mAb)-directed PlGF/VEGF inhibition enhances the efficacy of chemotherapy in pancreatic cancer (Kim et al. 2022).

3.5.3 Reprogramming Dendritic Cells While efforts to revitalize exhausted T cells have shown some success in pancreatic cancer, it is still unclear whether endogenous T-cell depletion or a lack of T-cell priming is the primary problem in patients with PDAC (Vonderheide 2018; Hosein et al. 2022). Cross-presenting type 1 conventional dendritic cells (cDC1s) are

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essential for priming tumor-specific CD8+ T lymphocyte responses, as shown by studies in mice, but they are in insufficient abundance in pancreatic cancer (Hegde et al. 2020; Lin et al. 2020). PDAC mouse models had significantly fewer CD103+ cDC1s than lung adenocarcinoma mouse models. Mouse models of PDAC have been sensitized again to CD40 agonist antibody and radiation therapy after receiving FMS-like tyrosine kinase 3 ligand (FLT3L) treatment, which increases the number of intratumoral cDC1s (Hegde et al. 2020). Early-stage clinical studies with the CD40 agonist antibody CDX-1140 in conjunction with FLT3L (CDX-301) in PDAC and other solid tumors are now underway. Results will soon reveal whether or not the treatment is safe and effective (NCT04536077 and NCT03329950). DC function may also be altered by tumor cells and TME intrinsic factors. By inhibiting cross-priming of T cells, DCs invaded by tumor cells may, for instance, promote β-catenin signaling. Tumor-infiltrating DCs synthesize retinoic acid through vitamin A metabolism (Guo et al. 2019). Accumulation of lactic acid occurs during active glycolysis in cancer and stromal cells. Additionally, activated DCs have a greater need for glucose and generate more lactate (Peng et al. 2021). An increase in lactate levels in the TME has been shown to impede the activation and antigen presentation of DCs. The DC phenotype may be influenced by the lactic acid produced by the cancer cells, which can contribute to tumor evasion (Gottfried et al. 2006). Tumor-derived molecules, including triglycerides, cholesterol esters, and fatty acids, inhibit DC cross-presentation of tumor antigens by downregulating the production of peptide-MHC class I complexes (Cao et al. 2014; Xiang et al. 2023). Compared to DCs from tumor-free mice and healthy humans, a significant percentage of DCs in tumor-bearing mice and people with cancer have high levels of triglycerides (Herber et al. 2010). Upregulation of scavenger receptor A led to enhanced absorption of extracellular lipids, which led to lipid buildup in DCs. High-lipid DCs were unable to deliver TAAs or trigger allogeneic T lymphocytes. The functional activity of DCs was restored by pharmacologically normalizing lipid abundance using an inhibitor of acetyl-CoA carboxylase, which significantly increased the efficacy of cancer vaccines (Herber et al. 2010). DCs ingest pieces of tumor cells and display antigenic peptides on MHC class I and II. DCs stimulate naïve CD8+ and CD4+ T lymphocytes by expressing co-stimulatory ligands and upregulating CCR7 after activation (Dougan et al. 2019). Damage-associated proteins, such as adenosine triphosphate (ATP) or HMGB1, produced by dying tumor cells, are essential for this process. However, DCs may be activated by the demise of tumor cells; the subsequent phagocytosis of tumor cell fragments also initiates regulatory processes in DCs that impede their interaction with T cells. Exposing DCs to microbial products that stimulate TLR signaling, such as the viral nucleic acid mimicking pIpC or CpG DNA, may circumvent this regulatory function, which is why innate immune adjuvants are being included in vaccination approaches. Targeted agents that influence DNA replication and repair pathways may also activate the STING pathway, which then triggers the generation of type I interferon and, in turn, boosts DC activation (Hosein et al. 2022; Chamma et al. 2022). For instance, in animal models of pancreatic

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cancer, STING agonist treatment increases inflammation in the immune milieu and lowers tumor burden (Jing et al. 2019).

3.5.4 Targeting Immunosuppressive Myeloid Cells Regulation of neutrophil and monocyte cell migration to the PDAC microenvironment is known to be critically dependent on the chemokine receptors CXCR2 and CCR2 and their ligands (Nywening et al. 2018). Depletion or specific interruption with neutrophil trafficking may reduce the PDAC burden in mice. However, such approaches cannot be perpetuated over the long term (Stromnes et al. 2014; Steele et al. 2016; Chao et al. 2016). In PDAC mice models, the CD11b agonist reduces accumulation of most myeloid cell types and has a substantial synergy with PD-1 blockade (Twyman-Saint Victor et al. 2015). PDAC tumor burden was decreased in mice treated with CCR2 inhibitors that selectively targeted circulating monocytes (Mitchem et al. 2013). A study determined the optimal oral dosage of the CCR2 inhibitor PF-04136309 for use in a phase II trial in combination with the chemotherapy regimen FOLFIRINOX. This combination therapy was safe and well-tolerated in patients with PDAC. Findings revealed that monocytes are retained in the BM of CCR2 inhibitor-receiving patients, which correlated with a significant decrease in circulating monocytes and M-MDSCs in the TME. This was followed by remarkable decreases in the primary tumor burden, which allowed 39% of the group to undergo surgery (Nywening et al. 2016). However, PF-04136309 in combination with nab-paclitaxel/gemcitabine induced significant pulmonary toxicity and did not show a favorable signal (Noel et al. 2020). Combining BMS-813160 (a selective CCR2/5 dual antagonist), nivolumab plus chemotherapy is being tested in an earlystage clinical trial in patients with PDAC (NCT03496662).

4

Conclusion

All in all, the paradigm shift prompted by immunotherapy is altering how we perceive cancer treatment. Immunotherapy is now being used in clinical settings for various solid cancers. Several standard treatments have failed to benefit patients with PDAC; however, immunotherapy has shown promising outcomes. This chapter highlighted an extensive spectrum of immunotherapies, including OVT, adoptive cell transfer therapy including TCR-engineered T cells therapy, CAR T-cell therapy, CAR NK cell therapy, and CIK cells, ICB and immunomodulators, cancer vaccines, and immunotherapeutic strategies based on targeting myeloid cells. As immunotherapeutic strategies for treating and managing PDAC hopefully develop, logical efforts to enhance patients’ quality of life must also be prioritized. Several trials using immunotherapy strategies have had dismal results in PDAC. Although the low success rate has several causes, immunosuppressive TME is a major contributor. Current immunotherapies should be enhanced and refined to address this significant challenge. There should also be further research into the efficacy of new immunotherapy targets found in preclinical studies, which should be validated through human clinical trials.

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Xiang H, Yang R, Tu J et al (2023) Metabolic reprogramming of immune cells in pancreatic cancer progression. Biomed Pharmacother 157:113992. https://doi.org/10.1016/j.biopha.2022.113992 Xiang Z, Hu T, Wang Y et al (2020) Neutrophil–lymphocyte ratio (NLR) was associated with prognosis and immunomodulatory in patients with pancreatic ductal adenocarcinoma (PDAC). Biosci Rep 40:BSR20201190. https://doi.org/10.1042/BSR20201190 Yan T, Zhu L, Chen J (2023) Current advances and challenges in CAR T-cell therapy for solid tumors: tumor-associated antigens and the tumor microenvironment. Exp Hematol Oncol 12:14. https://doi.org/10.1186/s40164-023-00373-7 Yeh ES, Means AR (2007) PIN1, the cell cycle and cancer. Nat Rev Cancer 7:381–388. https://doi. org/10.1038/nrc2107 Yeo D, Giardina C, Saxena P, Rasko JEJ (2022) The next wave of cellular immunotherapies in pancreatic cancer. Mol Ther Oncolytics 24:561–576. https://doi.org/10.1016/j.omto.2022. 01.010 Yu X, Harden K, Gonzalez C et al (2008) The surface protein TIGIT suppresses T cell activation by promoting the generation of mature immunoregulatory dendritic cells. Nat Immunol 10:48–57. https://doi.org/10.1038/ni.1674 Yuen A, Díaz B (2014) The impact of hypoxia in pancreatic cancer invasion and metastasis. Hypoxia (Auckland, NZ) 2:91–106. https://doi.org/10.2147/HP.S52636 Zhang J, Xu X, Shi M et al (2017) CD13(hi) Neutrophil-like myeloid-derived suppressor cells exert immune suppression through Arginase 1 expression in pancreatic ductal adenocarcinoma. Oncoimmunology 6:e1258504. https://doi.org/10.1080/2162402X.2016.1258504 Zhang R, Liu Q, Peng J et al (2020a) CXCL5 overexpression predicts a poor prognosis in pancreatic ductal adenocarcinoma and is correlated with immune cell infiltration. J Cancer 11:2371–2381. https://doi.org/10.7150/jca.40517 Zhang X, Lao M, Xu J et al (2022a) Combination cancer immunotherapy targeting TNFR2 and PD-1/PD-L1 signaling reduces immunosuppressive effects in the microenvironment of pancreatic tumors. J Immunother Cancer 10:e003982. https://doi.org/10.1136/jitc-2021-003982 Zhang Y, Chandra V, Riquelme Sanchez E et al (2020b) Interleukin-17-induced neutrophil extracellular traps mediate resistance to checkpoint blockade in pancreatic cancer. J Exp Med 217. https://doi.org/10.1084/jem.20190354 Zhang Y, Lazarus J, Steele NG et al (2020c) Regulatory T-cell depletion alters the tumor microenvironment and accelerates pancreatic carcinogenesis. Cancer Discov 10:422–439. https://doi. org/10.1158/2159-8290.CD-19-0958 Zhang Y, Liu Z, Wei W, Li Y (2022b) TCR engineered T cells for solid tumor immunotherapy. Exp Hematol Oncol 11:38. https://doi.org/10.1186/s40164-022-00291-0 Zhang Y, Zoltan M, Riquelme E et al (2018) Immune cell production of interleukin 17 induces stem cell features of pancreatic intraepithelial neoplasia cells. Gastroenterology 155:210–223. e3. https://doi.org/10.1053/j.gastro.2018.03.041 Zhou XZ, Lu KP (2016) The isomerase PIN1 controls numerous cancer-driving pathways and is a unique drug target. Nat Rev Cancer 16:463–478. https://doi.org/10.1038/nrc.2016.49 Zhu C, Anderson AC, Schubart A et al (2005) The Tim-3 ligand galectin-9 negatively regulates T helper type 1 immunity. Nat Immunol 6:1245–1252. https://doi.org/10.1038/ni1271 Zhu Y, Herndon JM, Sojka DK et al (2017) Tissue-resident macrophages in pancreatic ductal adenocarcinoma originate from embryonic hematopoiesis and promote tumor progression. Immunity 47:323–338.e6. https://doi.org/10.1016/j.immuni.2017.07.014 Zhu Y, Knolhoff BL, Meyer MA et al (2014) CSF1/CSF1R blockade reprograms tumor-infiltrating macrophages and improves response to T-cell checkpoint immunotherapy in pancreatic cancer models. Cancer Res 74:5057–5069. https://doi.org/10.1158/0008-5472.CAN-13-3723

The Tumor Microenvironment in Pancreatic Cancer and Challenges to Immunotherapy Adile Orhan

Abstract

Pancreatic ductal adenocarcinomas (PDACs) contribute to around 7% of all cancer-related deaths worldwide with a 5-year survival rate less than 10%. The incidence of the disease is rising, while the treatment modalities are few for especially the late stages of PDAC. Despite advances in the field of immunooncology, the treatment of PDAC with immunotherapy has not yet shown promising results. The composition of the tumor microenvironment (TME) contributes to the aggressive disease phenotype and treatment resistance. In this chapter, the different components of the TME in PDAC will be described and discussed to further elucidate some of the major challenges of the TME in relation to immunotherapy. Keywords

Immunohistochemistry · Immuno-oncology · Immunotherapy · Neo-angiogenesis · Pancreatic ductal adenocarcinoma · Tumor microenvironment · Tumor-infiltrating lymphocytes

A. Orhan (✉) Center for Surgical Science (CSS), Department of Surgery, Zealand University Hospital, Koege, Denmark Department of Clinical Oncology, Zealand University Hospital, Roskilde, Denmark e-mail: [email protected] # The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 Interdisciplinary Cancer Research, https://doi.org/10.1007/16833_2022_65 Published online: 19 November 2022

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1

Introduction

1.1

Immunotherapy

Treatments that enhance the immune system against cancer cells are named immunotherapy. Immune checkpoint inhibitors (ICIs), which inhibit the natural survival signals between immune cells and normal cells, are the best-known type of immunotherapy. Examples of immune checkpoint inhibitors are pembrolizumab and nivolumab that targets the programmed cell death protein 1 (PD-1) on lymphocytes or ipilimumab that targets cytotoxic T-lymphocyte-associated protein 4 (CTLA-4). During the past decade, ICIs in the treatment of malignant melanoma, NSCLC, and renal cell carcinomas have significantly improved patient survival (Motzer et al. 2015, 2018, 2019; Ott et al. 2019a, b; Rini et al. 2019; Hamid et al. 2019; Tykodi 2014). However, the potential role of immunotherapy as an effective treatment for other types of solid cancers, such as pancreatic cancer, is still uncertain, and the clinical studies are still ongoing. The effectiveness of immunotherapy is influenced by many factors, including the characteristics of both the cancer cells and the surrounding TME (Wang et al. 2017; Giuliano et al. 2018; Karamitopoulou 2019; Galon and Bruni 2020). For instance, the expression of programmed death-ligand 1 (PD-L1) on cancer cells and the tumor mutational burden (TMB) are found to influence the likeliness of response to immunotherapy, specifically ICIs (Lee and Ruppin 2019; Davis and Patel 2019b). On the other hand, the tumor fibrotic tissue (stroma) surrounding the cancer cells as well as the density of tumor-infiltrating lymphocytes (TILs) and neo-angiogenesis in the TME have been found to impact both prognosis and treatment response to immunotherapy (Galon and Bruni 2019).

1.2

Pancreatic Cancer

Pancreatic cancer is recognized as one of the most lethal cancers with a relative 5-year survival less than 10% (Jemal et al. 2017; Saad et al. 2018). The disease contributes to around 7% of all cancer-related deaths worldwide, and the incidence of the disease has been rising since 1990. A newly published research letter in JAMA based on data from the Surveillance Epidemiology and End Results (SEER) database found the sex-specific trends for pancreatic cancer in the United States (USA) among different age groups to be significantly increasing in both women and men (Gaddam et al. 2021). Interestingly, the incidence in younger individuals is estimated to be mostly increasing. With the trends described in the paper, the number of patients with pancreatic cancer is expected to be dominated by women younger than 55 years in following years. Another study found that pancreatic cancer is expected to become the second leading cause of cancer-related death in the USA in 2030 (Rahib et al. 2014). The existing data and statistics on pancreatic cancer are thus alarming, emphasizing the need for research on the matter to establish better diagnosis and improved treatment of the disease.

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The composition of the tumor microenvironment (TME) is recognized to be one of the main therapeutic difficulties in pancreatic ductal adenocarcinomas (PDACs). The TME in PDAC is often dominated by immunosuppressive cells and a dense network of desmoplastic tissue (Karamitopoulou 2019). Furthermore, neo-angiogenesis, leaky blood vessels, and early formation of micrometastases contribute to the rapid progression of the disease (Khan et al. 2015; Shi et al. 2016). Escaping anticancer immunity, inducing angiogenesis, promoting inflammation, and dissemination are all important factors among the well-establish hallmarks of cancer (Hanahan and Weinberg 2011; Hanahan 2022). Identifying pathways that promote progression in PDAC may assist in identifying novel targets and development of treatment approaches. Characterizing the immunosuppressive signature of PDAC may specifically contribute with novel insight to how the immune system can be recruited against cancer cells. Also, examining the characteristics of the TME including the interaction between immune cells, stromal components, and neo-angiogenesis may help ease the understanding of the complex nature of the disease and how it can be targeted in a multidimensional manner. In this chapter, the constitution of the TME in PDAC as well as the major difficulties in applying immune-enhancing treatment modalities for PDAC will be discussed.

2

Immune Signatures of Tumors

2.1

Hot, Cold, Immunosuppressed and Excluded Tumors

Some solid cancer types, such as malignant melanoma and lung cancer, are characterized as more likely to respond to immunotherapy. In general, such tumors have been found to have a high degree of T cell infiltration, especially that of cytotoxic CD8+ T cells in the TME. Likewise, tumors that respond efficiently to immunotherapy exhibit a high expression of PD-L1 on immune cells and a greater number of neoantigen and greater tumor mutational burden (TMB) (Galon and Bruni 2019, 2020). On the other hand, some cancers, including pancreatic cancer, are less likely to show significant clinical benefit from immunotherapy. Generally, such tumors have sparse infiltration of T cells, small number of neoantigens, and low mutational burden. The variations in the density of T cell infiltration, checkpoint activation, and degree of mutational burden assist in the categorization of solid cancers in different groups according to their immune signature (Galon and Bruni 2019). This categorization may help predict the possible clinical benefit of immuneenhancing treatments. Galon and Bruni have previously addressed some of the main challenges to immunotherapy. In their paper from 2019, the authors describe that tumors with a microenvironment dominated by CD8+ lymphocytes especially intratumorally are recognized as immunogenically warm tumors, which distinctively responds better to immunotherapy (van der Woude et al. 2017; Galon and Bruni 2019). On the other hand, tumors with low CD8+ cytotoxic T cells that are excluded from the tumor region respond less to immune-enhancing treatments and are thus classified as

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immunogenically cold tumors. However, the authors also discuss two more subtypes of immune signatures in tumors according to the level and localization of CD8+ T cell in the TME. The two additional subtypes are (1) the alteredimmunosuppressed tumors and (2) the altered-excluded tumors. These subtypes include tumors with immune signatures that cannot be classified under the traditional hot or cold groups and further emphasize the complexity of the relation between the TME and the immune system. The altered-excluded tumors are characterized by a small number of infiltrating CD8+ T cells, generally localized to the tumor border, whereas the TME is often dominated by abnormal vasculature, hypoxia, and a dense stroma. The alteredimmunosuppressed tumors also exhibit a minimal amount of CD8+ T cell infiltration in the TME. However, the infiltrative T cells in the altered-immunosuppressed tumors are mainly localized to periphery of the tumor, whereas the intratumoral region is primarily dominated by the presence of Tregs and myeloid-derived suppressor cells (MDSCs). Figure 1 illustrates the different immune signatures of tumors, and Table 1 summarizes the main characteristics of the immune signatures of tumors. Tumors classified as altered-immunosuppressed or the altered-excluded tumors both may respond to immunotherapy to a certain degree. However, the efficacy of immune-enhancing treatments may be increased when simultaneously targeting components of the TME that impact the density and localization of infiltrating cytotoxic T cells. PDAC is often classified as an immunogenically cold tumor due to the low mutational burden, low infiltration of lymphocytes, and a TME dominated by immunosuppressive cells and desmoplastic tissue (Galon and Bruni 2019, 2020;

Hot tumor

Cold tumor

Recruitment

Absence of T cells

Infiltrating T cells

Altered-excluded tumor

Altered-immunosuppressed tumor

Regulatory T cells

Hypoxia

Myeloid derived cells

T cells in tumor periphery

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T cells at tumor border

Fig. 1 An overview of some of the main characteristics of the four different immune signature types exhibited by tumors according to Galon and Bruni

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Table 1 Summarizes the different immune signatures of tumors according to T cells and TME characteristics Tumor immune signature Hot

Cold

T cells High abundance of T cells that are primarily localized intratumorally Absence of infiltrating T cells

Alteredimmunosuppressed

T cells are sparse and mainly localized to the tumor periphery

Altered-excluded

Number of T cells are small and primarily localized to the tumor border

TME Signals recruiting further T cell infiltration, sparse stromal components, less to minimal hypoxia High number of tumor-associated macrophages and cancer-associated fibroblasts (CAFs) High number of Tregs and MDSCs localized more centrally in the tumor. The TME is dominated by suppressive signals from immune suppressive cells Dominated by hypoxia, a dense stroma, and CAFs. Unsuitable environment for the survival and efficacy of T cells

Karamitopoulou 2019). Immunogenically cold tumors are less responsive to immunotherapy. Clinical studies have also described the majority of PDACs to be nonresponsive or less responsive to immunotherapy.

3

The Characteristics of the TME in PDAC

The unique composition of the TME in PDAC is hypothesized to be one of the major reasons that immunotherapy is less efficient in the treatment of the disease. The TME in PDAC consists of many different cell types and a complex interplay of signaling molecules. The main and well-described characteristics of the TME in PDAC will be discussed in the next sections of this chapter. The following components of the TME in PDAC will be described and discussed: • • • • •

Immune cells and immune checkpoints Stroma and fibrotic tissue Upregulated signaling pathways Driver mutations Neoantigens and hypermutability

3.1

Immune Cells

Immune evasion is a well-known hallmark of cancer (Hanahan and Weinberg 2011; Hanahan 2022). Normally, the immune system can detect cancerous cells and eradicate them. However, when cancer is clinically developed, the immunosurveillance against malignant cells is insufficient. There are various causes to why the immune system may not be able to destroy cancerous cells. It can be

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caused by a continuous suppression of immune cells involved in the detection and killing of malignant cells, as well as it can be caused by an inability of immune cells to infiltrate the tumor site, activate killing mechanisms, or survive and proliferate at the tumor site. The role of immune cells in cancer development and progression is apparent, but the interplay between immune cells and cancer cells in the TME is complex. Some of the main immune cells involved in immunosurveillance in PDAC will be discussed in the next section.

3.1.1 Tumor-Infiltrating Lymphocytes Immune cells can identify malignant cells and combat cancer growth (Galon and Bruni 2020). Immune cells that are especially of importance in cancer are the lymphocytes. As components of the adaptive immune system, lymphocytes that be activated through antigen-presenting receptors present on their cell surface by antigen-presenting cells (APCs) of the innate immune system. Activated lymphocytes can subsequently recruit additional lymphocytes and other immune cells to eliminate damaged cells. Thus, an important interaction between the innate and adaptive immune system exists for proper activation and function of each. Mature lymphocytes are normally found in the bloodstream and can exit the blood circulation to enter sites of damage or danger. Lymphocytes which are found in and/or around tumor cells are called tumor-infiltrating lymphocytes (TILs). TILs are involved in the recognition and elimination of cancer cells (Paijens et al. 2020). The immune cells that are mainly involved in recognizing and killing cancer cells are the CD3+ CD8+ T cells (cytotoxic T cells) and the natural killer cells (NK cells) (Farhood et al. 2019). Along these cells, the CD4+ lymphocytes and CD20+ lymphocytes (B cells) are important mediators of the adaptive immune responses (Galon and Bruni 2020). The FoxP3+ T regulatory cells (Tregs) are also recognized as important mediators of the immune response to tumors, as they suppress the immune system (Takeuchi and Nishikawa 2016). During the past decade, research have found that the density of TILs in a tumor predicts patient prognosis as well as likelihood of treatment response to immunotherapy in different cancers. Pancreatic tumors are generally poorly infiltrated with T cells and are therefore often characterized as immunogenically cold tumors that are less responsive to immune checkpoint inhibitors (ICIs) (Galon and Bruni 2019, 2020). Compared to other cancer types, the infiltration of T cells in PDAC is sparse. However, a significant association between the levels of TILs and survival outcomes has been described in PDAC (Orhan et al. 2020). Especially, high levels of cytotoxic CD8+ T cells in the TME have been correlated with significantly improved overall survival, progression-free survival, disease-free survival, and cancer-specific survival among patients with PDAC (Orhan et al. 2020). In contrast, high infiltration of FoxP3+ T cells was associated with worse prognosis. These findings are consistent with studies on TILs in other cancer types (Zheng et al. 2018; Lee et al. 2018; Ding et al. 2018; Idos et al. 2020). The localization of TILs is also of importance. As described previously, the immune signature of a tumor relies not only on the presence of cytotoxic T cells but also their localization. In PDAC, the localization of immune

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cell infiltration is also found to influence survival. High density of specifically cytotoxic T cells in the tumor center has been associated with improved prognosis both in retrospective cohorts and in a large meta-analysis (Zhang et al. 2017; Lohneis et al. 2017; Orhan et al. 2020). Analyzing the presence, density, and location of TILs in the TME of PDAC is therefore relevant when estimating patient prognosis.

3.1.2 Natural Killer Cells Natural killer (NK) cells are a part of the innate immune system and mediate antiviral as well as antitumor functions. They are cytotoxic and can induce lysis of infected or damaged cells. Together with CD8+ T cells, they are highly involved in the destruction of cancerous cells. Thus, NK cells are an important part of the first-line defense of the immune system and play a central role in tumorigenesis. Normally, NK cells are activated within just a few hours through the recognition of damage-associated molecular patterns (DAMPs) and pathogen-associated patterns (PAMPs). NK cells can kill target cells fast with the release of lytic toxins and do not need prior antigen sensitization. In comparison, the activation and differentiation of naïve T cells can take over 1–2 weeks. In the bloodstream, NK cells can detect and eliminate circulating tumor cells (Santos et al. 2014). Normally, circulating tumor cells are destroyed by NK cells within a short timeframe from first entering the circulation. However, studies have found that the activity of circulating NK cells decreases as cancer progresses (Leone et al. 2018). The NK cells are therefore involved in suppressing tumor growth and progression. In the TME, the function of NK cells is often suppressed by signals and molecules, as well as by the extracellular components of the TME such as fibrotic tissue. Tumor-infiltrating NK cells are of special interest from a therapeutic point of view, as the density of NK cell infiltration in the TME impacts prognosis (Nersesian et al. 2021). Increasing the migration, activation, and efficacy of NK cells in the TME is thus of importance. In PDAC, the expression of NK cells in the TME has been associated with survival outcomes (Orhan et al. 2020; Wang et al. 2020a). The TME of PDAC is characterized by a high number of stromal cells (e.g., cancer-associated fibroblasts (CAFs), stellate cells, etc.) and fibrotic tissue, as well as high TGF-β levels (Karamitopoulou 2019). Studies suggest that NK cells are excluded from the TME of PDAC by interactions between different stromal cells and NK cells (Ene-Obong et al. 2013). Likewise, high levels of TGF-β are found to impact NK cell activation and function through IL-6 secretion from CAFs (Huang et al. 2019). Other cytokines involved in the inhibition of NK cell activity and proliferation are IL-10 and IL-23 which may also be high in the TME of PDAC. The levels of IL-10 induce infiltration of Tregs that consequently increase further secretion of IL-10. Thus, many of the dominant components of the TME in PDAC stimulate and maintain an immunosuppressive phenotype. The impairment of the cytotoxic NK cell function in the TME increases cancer growth, and interventions that can stimulate the migration and activation of NK cells in the TME of PDAC are therefore highly relevant.

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3.1.3 Myeloid-Derived Suppressor Cells (MDSCs) Myeloid-derived suppressor cells (MDSCs) originate from stem cells from the bone marrow and constitute of cells from the myeloid lineage. Under normal circumstances, these cells are held in check, but during chronic infections or cancer, the number of MDSCs may expand rapidly. MDSCs are recruited to the bloodstream and further into the TME with the help of chemokines. Once in the TME, MDSCs can expand and suppress cytotoxic responses. A subgroup of MDSCs, the monocytic MDSCs, may additionally differentiate into tumor-associated macrophages (TAMs) that contribute to the maintenance of an immunosuppressive TME. In PDAC, the number of circulating MDSCs in the peripheral blood is correlated with higher cancer stage, suggesting that MDSCs are recruited as disease progresses. The differentiation of myeloid progenitor cells in the bone marrow to MDSCs is found to be influenced by the growth factor and granulocyte-macrophage colonystimulating factor (GM-CSF). Malignant pancreatic epithelial cells are found to produce GM-CSF (Bayne et al. 2012). The recruitment of MDSCs from the circulation to the tumor site is found to be regulated by chemokines and hypoxia. Hypoxia-inducible factors (HIFs) influence both the recruitment and differentiation of MDSCs in the TME of PDAC. HIFs are also responsible for the recruitment of Tregs to the TME. Studies indicate that the differentiation of MDSCs to TAMs of the M2 phenotype is rapidly increased in hypoxic environments (Kumar et al. 2016). Together with TAMs, MDSCs have also been found to promote cancer stem cells through the secretion of pro-inflammatory molecules (Porembka et al. 2012). Thus, MDSCs have been found to play a central role in cancer progression. Currently ongoing clinical and preclinical studies are investigating how targeting MDSCs may impact the course of cancer progression. 3.1.4 Tumor-Associated Macrophages (TAMs) Tumor-associated macrophages are macrophages found in the TME of solid cancers. TAMs are alternative activated macrophages, thus also called M2 macrophages. M2 macrophages are important for Th2 immune responses including tissue remodeling. TAMs produce anti-inflammatory cytokines such as IL-10. High infiltration of TAMs is associated with cancer progression and poor oncological outcomes in different cancer (Chittezhath et al. 2014). In the TME, TAMs are primarily localized in the hypoxic areas and are important mediator of angiogenesis (Nasrollahzadeh et al. 2020). TAMs can stimulate the motility, invasion, and intravasation of cancer cells through epidermal and vascular growth factors and their ligands as well as by immunosuppressive cytokines. Through the initiation of prostaglandin synthesis and production of platelet-derived growth factors, TAMs are found to initiate angiogenesis in the TME as well as suppressing cytotoxic T cells and NK cells (Sahraei et al. 2019). TAMs are highly involved in constituting and maintaining an immunosuppressive TME. High levels of IL-10 and TGF-β produced by TAMs inhibit T cell proliferation as well as T cell responses involved in cancer cell elimination. Furthermore, IL-10 produced by TAMs increases the tumor infiltration of Tregs and drives a more aggressive disease phenotype in cancer.

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Macrophages are primarily recruited to the tumor site and differentiated into TAMs through various signaling molecules and tumor-secreted factors such as GM-CSF and IL-6. Also, hypoxia in the TME, together with an acidic and inflamed environment at the tumor site, recruits monocytes from the bloodstream to the tumor site and stimulates the differentiation of macrophages to TAMs. In PDAC, TAMs are one of the dominating immune cell subtypes in the TME. High infiltration of TAMs in the TME is associated with worse prognosis and more aggressive disease. The TAMs in the TME of PDAC secrete immunosuppressive cytokines such as IL-10 and TGF-β, stimulating the infiltration of Tregs while inhibiting the activity of cytotoxic immune cells. TAMs also modulate the tumor stroma through the secretion of matrix proteins and proteases such as MMPs, including MMP9 which promote invasion of the basement membrane (Yang et al. 2021). Furthermore, TAMs have been found to induce resistance to gemcitabine in PDAC (Liu et al. 2020). However, the role of TAMs in relation to chemotherapy resistance is not fully understood. The various mechanisms by which TAMs influence cancer progression in PDAC are of great research interest, and the development of future treatment modalities targeting the differentiation of macrophages to TAMs is especially relevant. Figure 2 summarizes the main immune cells in the TME of PDAC discussed in this section.

3.2

Immune Checkpoints

Immune cells may be able to recognize cancer cells but unavailable to eliminate them due to various factors in the TME. Likewise, activation and proliferation of immune cells may be affected by different signaling mechanisms. Cancer cells can

Immune cells of the TME CD8+ TILs

Elimination of cancer cells. Immune stimulatory signals and recruitment of other TILs.

MDSCs

Promotion of cancer stem cells and suppression of cytotoxic responses.

TAMs

Tregs

NK cells

Stimulate the motility, invasion and intravasation of cancer cells. Promote angiogenesis and suppress immune responses

Highly involved in immune evasion. Secretes TGF-β and influences the composition of the TME

Involved in the elimination of cancer cells and activated rapidly. Often suppressed in the TME

Fig. 2 An overview and short summary of the main immune cells found in the tumor microenvironment of pancreatic ductal adenocarcinomas as described in this section. TILs tumor-infiltrating lymphocytes, MDSCs myeloid-derived suppressor cells, TAMs tumor-associated macrophages, Tregs regulatory T cells, NK cells natural killer cells

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take advantage of natural checkpoints in the immune system by increasing the expression of PD-L1 on their cell surface, thereby avoiding immune recognition and destruction (Akinleye and Rasool 2019).

3.2.1 PD-1 and PD-L1 Antibodies targeting either PD-1 (pembrolizumab and nivolumab) or PD-L1 (atezolizumab and durvalumab) have been developed to inhibit the natural binding between PD-1 and PD-L1, consequently activating the body’s immune responses against cancer cells that highly express PD-L1 on their cell surface. The effectiveness of ICIs is found to be dependent on the expression of PD-L1 of cancer cells and T cells (Davis and Patel 2019). Thus, the level of PD-L1, together with TMB, has become an important predictor of response to immunotherapy, specifically ICI therapy. In PDAC, the cancer cells are found to express PD-L1 on their cell surface. However, the expression of PD-L1 is minimal in comparison with the membranous PD-L1 expression in other cancer types (Zheng 2017; Lee and Ruppin 2019; Wang et al. 2020b). High expression of PD-L1 in PDAC has been associated with poor prognosis (Nomi et al. 2007). The efficacy of ICIs in the treatment of PDAC is limited to primarily mismatch repair-deficient (dMMR) pancreatic tumors, which accounts for approximately 1–3% of all pancreatic cancers (Hu et al. 2018). In PDAC with proficient mismatch repair (pMMR), the efficacy of immunotherapy is low (Pu et al. 2019). It is hypothesized that the minimal expression of PD-L, together with other factors related to the TME, causes the previously observed and described ineffectiveness of ICIs in PDAC (Pu et al. 2019; Eso and Seno 2020). Also, the infiltration of TILs also influences the tumor response to immune-enhancing therapies (Lee and Ruppin 2019). The correlation between the abundance of cytotoxic CD8+ T cells and responsiveness to ICIs has previously been described, and PDACs have been classified as tumors of low CD8+ TILs density and thus with a considerably lower objective response rate to PD-1/PD-L1 inhibitors (Lee and Ruppin 2019). The expression of PD-L1 on malignant cells can be activated by inflammatory cytokines, especially through interferon gamma (IFNγ). T cells, including CD4+ T helper cells and CD8+ cytotoxic T cells, as well as macrophages and NK cells, can secrete IFNγ. IFNγ can stimulate the differentiation of Th1 cells to CD4+ T helper cells which in turn secrete IFNγ, thereby creating a positive feedback loop (Castro et al. 2018). As previously described, the secretion of IFNγ can enhance the expression of membranous PD-L1 in cancer cells. This interaction between T cells, IFNγ, and PD-L1 emphasizes that the presence and degree of PD-L1 expression on malignant cells are influenced by TILs, which generally are sparsely presented in PDAC (Mucileanu et al. 2021). Thus, the inflammatory signals triggering high PD-L1 expression on cancer cells may be lacking in PDAC due to a low infiltration of T cells.

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Stroma and Fibrotic Tissue

3.3.1 Cancer-Associated Fibroblasts (CAFs) CAFs are mesenchymal cells of the TME involved in remodeling the extracellular matrix and promoting tumorigenesis. CAFs can stimulate angiogenesis, suppress immune cells involved in the elimination of malignant cells, and enhance the motility, invasion, and metastasis of cancer cells. In the tumor stroma, CAFs are the most predominant cell type and play a crucial role in the epithelial-mesenchymal transition (EMT) of cancer cells. However, some findings suggest that CAFs have a dual role in cancer and that CAFs initially function as tumor-suppressive cells but later gain tumor-promoting features (Bhowmick et al. 2004). CAFs can secrete IL-6 and TGF-β promoting immunosuppression. In return, CAFs are activated by TGF-β, and IL-1 produced by malignant cells and other stromal cells such as macrophages. Thus, the stimulation and activation of CAFs initiates a positive feedback loop, making CAFs self-sustaining. A subset of CAFs are called the myofibroblast CAFs (mCAFs). mCAFs are involved in the development of fibrotic tissue in the tumor stroma and suppression of antitumor immunity (Costa et al. 2018). Moreover, heterogeneity of CAFs has been described in PDAC. The heterogeneity in CAFs is based on the difference in cell surface markers as well as cytokine production and cell signaling (Ligorio et al. 2019). In PDAC, the CAFs are responsible for the high density of fibrosis and desmoplasia surrounding the tumor. The high density of desmoplasia is a major challenge in the treatment of PDAC, as it affects both the ability to resect tumor surgically and the delivery of antineoplastic drugs medically. CAFs are often localized in a closed or open ring, surrounding the tumor almost as a capsule. The stiffness of CAFs as well as CAFs’ ability to invade the tumor stroma is found to influenced by TGF-β levels in the TME (Stylianou et al. 2018). The dense fibrotic stroma due to the high number of CAFs in the TME of PDAC challenges both the infiltration and efficacy of cytotoxic immune cells but also the penetration of antineoplastic drugs. Thus, these features of the TME constitute a major obstacle in the applicability of immune-enhancing treatments for pancreatic cancer and should be further examined. Targeting CAFs in the TME parallel to standard oncological treatment could be a promising lead in future treatment strategies for PDAC. Figure 3 illustrates the typical composition of the TME in PDAC.

3.4

Upregulated Signaling Pathways

3.4.1 SMAD4 and TGF-b Mothers against decapentaplegic homolog 4 or SMAD4 is a protein involved in the transforming growth factor beta (TGF-β) signaling pathway (Ahmed et al. 2017). The SMAD4 protein can form complexes with other SMAD proteins and accumulate in the cell nucleus. In complexes with other SMAD proteins, the SMAD4 protein can bind to the DNA in the cell nucleus through a specific Smad-binding element (Hahn et al. 1996; Ahmed et al. 2017).

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Tumor

Neo-angiogenesis

Growth factors

Collagen

CAFs

mCAFs TGF-β

TAMs

Fig. 3 Visual presentation of the main stromal components of the tumor microenvironment (TME) contributing to a dense fibrous stroma characterizing pancreatic ductal adenocarcinomas. Growth factors and signaling molecules such as TGF-β maintain an immunosuppressive TME, while CAFs initiate tissue remodeling. TAMs can promote angiogenesis and suppress cancer immunity. CAFs cancer-associated fibroblasts, TAMs tumor-associated macrophages, mCAFs myeloid cancerassociated fibroblasts

Normally, the protein serves both as a transcription factor and as a tumor suppressor through its ability to inhibit cell proliferation and cell growth as well as reducing the formation of new blood vessels (neo-angiogenesis). The TGF-β/ SMAD4 signaling pathway normally facilitates cell cycle arrest and apoptosis. However, mutations of the TGF-β transduction result in the loss of SMAD4 signaling, thereby causing a depletion of the tumor-suppressive properties of the TGF-β/ SMAD4 signaling pathway (Ahmed et al. 2017). Paradoxically, this transformation of the TGF-β/SMAD4 signaling pathway provides the TGF-β protein tumorpromoting features. Overexpression of TGF-β is associated with increased activation of the PI3K/AKT and Ras/ERK pathways highly involved in carcinogenesis. Mutation in the SMAD4 gene is found in more than half of the PDAC cases, explaining why the SMAD4 protein is also called “deleted in pancreatic carcinoma locus 4” protein (Hahn et al. 1996). Together with mutations in the KRAS, TP53, p16, and CDKN2A genes, mutations in the SMAD4 gene are considered the main drivers of the development and progression of PDAC (Hahn et al. 1996; Tascilar et al. 2001). Studies suggest that SMAD4 mutations alone do not facilitate the initial formation of cancer, including PDAC, but rather stimulate the progression of cancer. Thus, the SMAD4 gene is considered an important driver gene in PDAC (Ottenhof et al. 2012; Oshima et al. 2013). Loss of SMAD4 expression in patients with PDAC was correlated with worse prognosis (Xing et al. 2016). Likewise, slightly improved

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survival was observed in patients with PDAC and intact expression of SMAD4 (Oshima et al. 2013; Xing et al. 2016). The TGF-β signaling pathway plays a central role in tumorigenesis. Overexpression of TGF-β, and overactivation of the signaling pathway, is associated with immunosuppression through recruitment of FoxP3+ regulatory T cells (Tregs) as well as suppression of CD8+ cytotoxic T cells and natural killer (NK) cells (Batlle and Massagué 2019). Likewise, the signaling pathway is involved in the facilitation of neo-angiogenesis through inducement of vascular endothelial growth factor (VEGF) and connective tissue growth factor (CTGF) (Padua and Massagué 2008). TGF-β also facilitates epithelial-mesenchymal transition (EMT) of cancer cells, allowing invasiveness and increasing their metastatic potential (Derynck and Akhurst 2007). In addition, TGF-β stimulates the formation of fibrosis by increasing the release of collagen, fibronectin, and elastin. Fibrosis in relation to a tumor, or desmoplasia, is one of the major challenges in PDAC (Whatcott et al. 2012; Karamitopoulou 2019). In patients with PDAC, the TGF-β levels in blood plasma or serum have been correlated with survival outcomes (Javle et al. 2014; Gough et al. 2021). Higher levels of TGF-β in serum are associated with worse prognosis. It is hypothesized that high TGF-β levels in patients with PDAC may cause an increase in the metastatic potential of the malignant cells, thereby negatively affecting survival measures. In continuation, evidence suggest that higher levels of TGF-β increase cellular invasion and metastasis in the TME of PDAC. It has been described that TGF-β expression is associated with advanced disease in PDAC (Zhao et al. 2016).

3.5

Driver Mutations

3.5.1 KRAS The rat sarcoma virus (RAS) proteins belong to the group of small GTPases and are involved in cellular signal transduction. The RAS proteins are normally able to activate genes related to cellular growth and anti-apoptosis. RAS proteins can activate the mitogen-activated protein kinase (MAP-K) and the PI3K/AKT/mTOR pathways, which are pathways both involved in cell growth and cell survival (Malumbres and Barbacid 2003). Mutations in the RAS genes can lead to overactive signaling of the RAS proteins, causing uncontrollable cell differentiation, growth, and inhibition of apoptosis (Malumbres and Barbacid 2003). Approximately 90–95% of all PDACs have mutations in the KRAS gene (Waters and Der 2018; Buscail et al. 2020). In mouse models, KRAS mutation coupled with mutations in the TP53 or SMAD4 or CDKN2A genes accelerates the development of PanINs to progressive metastatic PDAC (Waters and Der 2018). The higher occurrence of mutations in the KRAS gene in PDAC compared to other cancer types is not fully understood but may be related to environmental factors and exposure to carcinogens that may particularly trigger KRAS mutations.

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The presence of KRAS mutations in patients with PDAC is a negative prognostic factor. Patients with KRAS-mutated PDAC have poorer prognosis independent of previous surgical treatment (Bournet et al. 2016). Some subtypes of KRAS mutations are also found to have a more aggressive phenotype in terms of reduced overall survival. For instance, KRAS G12D and/or G12R mutations have been correlated with worse survival outcomes in patients with PDAC (Bournet et al. 2016). The high frequency of KRAS mutations in PDAC has led to the speculation that targeting cancer-associated KRAS or KRAS downstream signaling pathways may be novel treatment strategies for PDAC. However, no promising results have been reported or led to the approval of KRAS inhibitors for the treatment of PDAC yet. The therapeutic potential of new treatments inhibiting KRAS signaling must be further investigated.

3.6

Neoantigens and Hypermutability

3.6.1 Tumor Mutational Burden Tumor mutational burden (TMB) is a term used to quantify the number of mutations per megabase in malignant cells of a tumor. High TMB has previously been associated with potential response to immunotherapy. Some cancer types are found to have higher values of TMB, whereas other cancer types have less. There is both a variation in the mean TMB value in different cancers and between patients with the same cancer type. This heterogeneity can be useful when selecting which patients may benefit most from immune-enhancing treatment modalities. Also, treatments that may provoke higher TMB in malignant cells prior to immunotherapy could be a strategy in a personalized approach to cancer therapy in the future. Assessment of TMB is thus relevant and a research subject of interest that still need further examination. In general, the TMB is low while the expression of neoantigens is sparse in PDAC. A meta-analysis found that high TMB was present in approximately 1.1% of all included subjects (Lawlor et al. 2021). The PDAC samples that harbored high TMB values were also found to contain mutations of the MMR proteins, suggesting a correlation between MMR deficiency and high TMB. In continuation, the best responses to immunotherapy in PDAC have been described in the high TMB and/or MMR-deficient subtypes. The rareness of both high TMB values and MMR deficiency in PDAC composes a major challenge in the use of immunotherapy as a treatment for disease. 3.6.2 Mismatch Repair Proteins The MMR proteins are enzymes involved in genome stability that detect and repair errors during the DNA replication and recombination. The MMR proteins repair single-base pair mismatches as well as smaller insertions and deletions. Also, the

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proteins are responsible for repairing some types of minor DNA damage, thereby defending the cells from harmful changes in the genome (Li et al. 2020). Cells with deficient MMR proteins (dMMR) or microsatellite instability (MSI) have considerably higher occurrences of DNA mutations. Deficiency of the MMR proteins can be due to germline mono- or biallelic mutations in the MMR encoding genes, often seen in syndromes such as Lynch syndrome. However, dMMR is also seen in sporadic tumors in somatic cells, typically due to promoter hypermethylation of the MLH1 gene. Deficiency in the MMR proteins is associated with elevated presence of mutationassociated neoantigens in solid cancers (Wu et al. 2021). Mutation-associated neoantigens can be recognized by immune cells, leading to higher infiltration of lymphocytes. A higher number of infiltrating immune cells at the tumor site, especially CD8+ T cells, may ultimately improve prognosis and enhance a patient’s likelihood of response to PD-1/PD-L1 inhibitors (Wu et al. 2021). In CRC, dMMR was associated with improved disease-free survival (DFS) and overall survival (OS), presumably due to the increase of immune infiltration in dMMR tumors as a result of elevated mutation-associated neoantigens. It is hypothesized that the observed positive effect on prognosis is related to the immune system’s increased awareness and reaction to malignant cells (Wu et al. 2021). In sporadic PDAC, deficiency in the MMR proteins is rare, accounting for approximately 1–3% of all cases (Laghi et al. 2012; Abrha et al. 2020; Ghidini et al. 2020). The MMR status of PDACs can assist in the prognostication and choice of therapy. Some studies have reported better prognosis in patients with dMMR PDAC compared to patients with proficient MMR proteins (pMMR) (Brahmer et al. 2012; Patnaik et al. 2015; Ghidini et al. 2020). However, the relation between MMR status and survival outcomes in patients with PDAC is still uncertain and should be further investigated. The number of patients with dMMR in sporadic PDAC should also be evaluated in greater cohorts to determine a more precise occurrence of dMMR status in sporadic PDAC.

4

Conclusion

PDAC is a fatal disease with a low 5-year survival rate and increasing incidence worldwide. Despite the recent advances in the treatment of cancer, the potential treatments of PDAC are few. The composition of TME represents a major challenge in the treatment of PDAC. The TME of PDAC is dominated by immunosuppressive signals and a dense fibrous stroma, challenging the standard surgical and medical treatment approaches to cancer. Thus, a more multidimensional approach, targeting the different components of the TME that contribute to disease progression, may be needed to optimize responses to standard treatment modalities and to improve survival measures.

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Index

A Angiogenesis, 18, 24, 30, 31, 50, 51, 55, 126, 153, 156, 159, 160, 162, 164, 166, 167, 170–172, 196, 216, 221–224, 270, 333, 336, 361, 383, 388, 391, 392 B Biomaterial, 275, 279–280 C Cancer immunotherapy, 3, 10, 219, 226, 297– 298, 348 CAR NK cell therapy, 347–348, 363 Carcinogenesis, 8, 29, 53, 58, 73, 102, 119, 126, 133, 137, 138, 140, 141, 154, 165– 167, 169, 235–241, 245, 257, 282, 330, 333, 338, 392 Checkpoint inhibitors, 3, 34, 60, 105, 109, 194, 203, 204, 219, 220, 252, 253, 255–256, 298, 348, 350, 382, 386 Chemotherapy (CT), 9, 11, 12, 34, 36, 58, 81, 109, 112, 143, 199, 203, 217, 222, 242– 244, 252, 256, 270, 292, 293, 295–298, 307–310, 330, 333, 340, 348, 352, 357, 361, 363, 389 Chimeric antigen receptor (CAR) T-cell therapy, 9, 10, 13, 251–262, 330, 331, 340, 342–347, 363 Cholangiocarcinoma, 7, 12, 60–61, 361 Colon cancer, 4, 5, 88, 115, 156, 158, 164, 167, 168, 170–172, 187–204, 233–245, 264, 280–282, 357 Colorectal cancer (CRC), 2, 12, 25, 54–57, 70, 83–85, 88, 89, 111, 151–172, 188, 189, 191, 192, 194, 197, 199, 203, 239, 243, 254, 256, 257, 269–283, 291–298

Cytotoxic T lymphocyte-associated protein 4 (CTLA-4), 3, 4, 8, 9, 13, 34, 107, 199, 200, 203, 219, 220, 222, 244, 255, 261, 348–352 Cytotoxin-associated gene A (CagA), 53, 102, 119, 121, 122, 124–126, 140, 141 D Dysbiosis, 2, 17, 19, 25–27, 29, 32, 33, 138, 143, 235, 237, 239–243 E Early-onset colorectal cancer, 291–298 Epidemiology, 4–5, 102–104, 319, 382 Esophageal cancer (EC), 3, 18, 25, 51, 52, 62, 70, 71, 84, 89–91, 135, 215–228, 254, 256, 259, 305–320 Esophagectomy, 3, 307–320 G Gastric cancer (GC), 2–4, 7, 9, 11, 26, 32, 52, 70, 72, 86–89, 101–112, 117–126, 133–144, 151–172, 252, 254, 258 Gastric carcinoma, 102, 118, 134, 135, 138, 347 Gastrointestinal cancer, 1–13, 17–36, 45–62, 69–91, 251–262, 343 Gut microbiota, 22–29, 35, 73, 142, 233–245, 311–314 H Helicobacter pylori (H. pylori), 4, 5, 7, 14, 25, 26, 32, 53, 102, 103, 117–144, 164 Helicobacter pylori infection, 4, 5, 7, 26, 32, 118, 126, 134–137, 139–144

# The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 Interdisciplinary Cancer Research 4, https://doi.org/10.1007/978-3-031-48371-4

403

404 Hepatocellular carcinoma (HCC), 5, 26, 33, 59–60, 71, 86, 258 I Immune checkpoint blockade (ICB), 8, 35, 36, 330, 332, 348–353, 356 Immune nutrition (IN), 101–112 Immune response, 3, 9, 10, 19, 24–26, 29–35, 49, 72, 106, 107, 109–111, 120, 121, 164, 189, 193, 194, 203, 204, 220, 222, 223, 225, 244, 253, 256, 271, 330–332, 334, 338, 339, 346, 357, 360, 386, 388–390 Immune system, 2, 8, 9, 13, 19, 23–25, 27, 28, 31–33, 72, 87, 101–112, 196, 218–224, 234, 235, 237, 244, 253–255, 260, 261, 298, 334, 336, 340, 347, 353, 382–387, 390 Immunity, 2, 9, 10, 17–36, 107, 111, 193, 218, 221–223, 233–245, 254, 337, 338, 346, 352, 360, 383, 391 Immunoediting, 2, 200 Immunohistochemistry (IHC), 111, 194 Immunotherapy, 3, 6, 8–13, 33, 106, 109, 204, 216, 219, 221, 222, 224–226, 244–245, 251–262, 271, 297–298, 330, 339, 341, 348, 353, 354, 360, 363, 381–395 Inflammatory response, 28, 126, 140, 203, 238, 239, 258, 294, 315 Innate immune cells, 34, 254 L Liver cancer (LC), 5, 11, 18, 33, 61, 70, 71, 85–86, 259 M MALT lymphoma, 134, 143 Mass spectrometry (MS), 73, 75–77, 85 Melatonin, 61–62 Mesenchymal to epithelial transition, 45–62, 171, 195, 200, 393 Metabolomics, 52, 59, 69–91 Microbiome, 18, 25, 26, 138, 234–237, 239, 241 Microbiota, 17–36, 142, 173, 233–245, 311, 314 Migrastatics, 61, 62

Index N Nanocarrier, 269–283 Nanomedicine, 272, 282, 283 Neo-angiogenesis, 49, 382, 383, 392, 393 Neuroendocrine, 57, 59, 159, 221 Neuropeptides, 153, 165–168 Neurotransmitters, 153–154, 156, 168, 169 Nuclear magnetic resonance spectroscopy (NMR), 73, 75, 77–79 O Oncolytic virus therapy (OVT), 331, 332, 339–340 P Pancreas, 2, 4, 5, 18, 26, 27, 33, 58, 82, 164, 252, 332, 338, 343, 347 Pancreatic cancer (PC), 7, 12, 26, 27, 33, 57–59, 70, 73, 80, 81, 259, 327–363, 381–395 Pancreatic ductal adenocarcinoma (PDAC), 57–59, 257, 330, 383, 389, 392 Pogrammed death 1 (PD-1), 3, 8, 9, 11, 13, 34, 35, 61, 105, 109, 112, 194, 203, 218–220, 224, 225, 244, 255, 261, 298, 331, 333, 339, 341, 348–353, 360, 361, 363, 390 Prognostic prediction, 217 R Radiotherapy, 3, 11, 12, 34, 105, 199, 252, 292–298, 308, 309, 333, 360 T Treatment, 3, 19, 60, 71, 105, 135, 153, 188, 216, 234, 252, 270, 292, 306, 330, 382 Tumor-infiltrating lymphocytes (TIL), 10, 337, 382, 386 V Vacuolating toxin (VacA), 102, 119, 122–126, 140, 141 Virulence factors, 117–144, 238 W Weight loss, 70, 87, 110, 143, 252, 305–320 Wingless and INT-1 (Wnt), 49, 50, 52–56, 59, 125, 164, 238, 346