Photodynamic Therapy: Methods and Protocols (Methods in Molecular Biology, 2451) 1071620983, 9781071620984

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Methods in Molecular Biology 2451

Mans Broekgaarden · Hong Zhang Mladen Korbelik · Michael R. Hamblin Michal Heger Editors

Photodynamic Therapy Methods and Protocols

METHODS

IN

MOLECULAR BIOLOGY

Series Editor John M. Walker School of Life and Medical Sciences University of Hertfordshire Hatfield, Hertfordshire, UK

For further volumes: http://www.springer.com/series/7651

For over 35 years, biological scientists have come to rely on the research protocols and methodologies in the critically acclaimed Methods in Molecular Biology series. The series was the first to introduce the step-by-step protocols approach that has become the standard in all biomedical protocol publishing. Each protocol is provided in readily-reproducible step-bystep fashion, opening with an introductory overview, a list of the materials and reagents needed to complete the experiment, and followed by a detailed procedure that is supported with a helpful notes section offering tips and tricks of the trade as well as troubleshooting advice. These hallmark features were introduced by series editor Dr. John Walker and constitute the key ingredient in each and every volume of the Methods in Molecular Biology series. Tested and trusted, comprehensive and reliable, all protocols from the series are indexed in PubMed.

Photodynamic Therapy Methods and Protocols

Edited by

Mans Broekgaarden Institute for Advanced Biosciences, Université de Grenoble Alpes, Grenoble, France

Hong Zhang van ‘t Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands

Mladen Korbelik British Columbia Cancer Research Centre, Vancouver, BC, Canada

Michael R. Hamblin Laser Research Centre, University of Johannesburg, Doornfontein, South Africa

Michal Heger Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics, Jiaxing University College of Medicine, Jiaxing, Zhejiang, P. R. China

Editors Mans Broekgaarden Institute for Advanced Biosciences Universite´ de Grenoble Alpes Grenoble, France

Hong Zhang van ‘t Hoff Institute for Molecular Sciences University of Amsterdam Amsterdam, The Netherlands

Mladen Korbelik British Columbia Cancer Research Centre Vancouver, BC, Canada

Michael R. Hamblin Laser Research Centre University of Johannesburg Doornfontein, South Africa

Michal Heger Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics Jiaxing University College of Medicine Jiaxing, Zhejiang, P. R. China

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-2098-4 ISBN 978-1-0716-2099-1 (eBook) https://doi.org/10.1007/978-1-0716-2099-1 © Springer Science+Business Media, LLC, part of Springer Nature 2022 This work is subject to copyright. All rights are reserved 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 Humana imprint is published by the registered company Springer Science+Business Media, LLC, part of Springer Nature. The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A.

Preface It is our pleasure to present this special issue in the Methods in Molecular Biology book series, focused on state-of-the-art methods and protocols for research on photodynamic therapy. With this volume, we aspire to provide scientists and clinicians with the necessary background information and tools to perform high-quality, focused, and competitive research in this multidisciplinary field. Photodynamic therapy (PDT) is a non- to minimally invasive treatment modality that has been approved for various medical applications, including the treatment of dermal lesions, vascular disorders, microbial infections, and cancer. In addition, variants of this technology are also used for diagnostic purposes (photodynamic diagnosis and theranostics) and drug delivery (i.e., photochemical internalization). The core of PDT revolves around the excitation of photosensitizers by visible light. Excited photosensitizers react with molecular oxygen to form reactive oxygen species (ROS). The ROS are at the helm of the therapeutic effects, as these transient species oxidize lipids, proteins, and nucleic acids. Oxidation of biomolecules leads to fragmentation, aggregation, or structural modifications that culminate in functional loss and, in some instances, induces a change in biological properties or responsiveness. Examples include the creation of pro-immunogenic molecules that aid in the post-therapeutic immune signaling following oncological PDT and the liberation of microbial antigens that trigger an immune response in antimicrobial PDT. For the treatment of cancer, the PDT procedure includes the topical or systemic administration of photosensitizer molecules, their accumulation in tumor tissue, and the subsequent illumination of the tumor with resonant light. Due to the relatively selective photosensitization and subsequent illumination of tumors, PDT causes relatively little harm to surrounding, non-illuminated healthy tissue. Direct cytotoxic effects at the cellular level stem from the induction of hyperoxidative stress, which culminates in direct cell death typically by a mix of necrosis and apoptosis. In addition to the direct cytotoxic effects, tumor tissue is also affected by indirect effects. When administered systemically in free form, conventional photosensitizers also localize to the intratumoral vascular endothelium and the tumor stroma. Upon light exposure, excessive ROS production results in thrombosis and hemostasis in the tumor vasculature and consequent anoxia and hyponutrition of tumor cells. Oxidative modification of tumor stroma leads to detrimental perturbations of the tumor microenvironment. These effects cause massive tumor cell death and induce a prolonged and specific anti-tumor immune response that is required for long-term tumor control. In light of these dynamics, the book volume features protocols to measure oxidative stress and photodamage, presents advanced in vitro and in vivo models to assess photodynamic efficacy, and addresses platforms to optimally photosensitize tumor tissue. Inasmuch as some tumors exhibit relatively low oxygen tension, chapters were included that describe PDT using oxygen-independent photosensitizers. Furthermore, five chapters are included that address methods related to PDT immunobiology, ranging from epigenetic modulation to immune checkpoint blockade to vaccination. Due to light absorption and scattering, larger tumors suffer from inhomogeneous light distribution. Since ROS production is proportional to fluence, the more distal regions of the tumors are often underexposed to excitation light, leading to sublethal oxidative damage. Sublethally afflicted tumor cells activate several survival pathways that enable the cell to cope

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with the damage and survive. In the clinical setting, this phenomenon manifests as tumor regrowth. In many cases, the tumors recur with a more aggressive phenotype. Accordingly, it is imperative that tumor cells in underexposed areas are stopped from fully executing survival pathways. The book therefore features chapters that outline inhibitors of key molecular regulators in two important survival pathways, which can be co-delivered with photosensitizers or co-encapsulated into photosensitizer delivery systems aimed at pharmacologically deterring tumor regrowth. Antimicrobial PDT leverages the photochemical production of ROS to cause lethal damage to the DNA, proteins, and membranes of bacteria, fungi, and viruses. In contrast to commonly used antibiotics, antifungals, and antiviral drugs, no general mechanism of microbial resistance has currently been identified for PDT. This means that firstly, it is not necessary to identify the precise strain causing an infection before starting treatment and that, secondly, the cycle of novel drug ! resistance ! novel drug does not apply. Moreover, antimicrobial PDT acts almost instantly, while antibiotics can take days or weeks to eliminate an infection. The photosensitizers are administered directly into the infected site so that beneficial bacteria in the gut are unaffected. This makes PDT an attractive treatment to, for example, disinfect burn wounds, prevent surgical wound infections, treat abscesses, acne and periodontal disease, and possibly even perform nasal decontamination to prevent the spread of contagious respiratory pathogens. To aid scientists in selecting appropriate models for their PDT research, this volume starts with an up-to-date overview of methods and protocols to establish suitable in vitro and in vivo models (Chapters 1–15). These range from simple cell cultures to advanced 3D culturing techniques, and high-content assays for these models are also presented. Part I additionally covers in ovo models as well as rodent and rabbit models of cancer. Part II (Chapters 16 and 17) presents the development of several novel (oxygen-independent) photosensitizers accompanied by practical methods for their characterization. Part III (Chapters 18–26) introduces considerations and methods to develop and test nextgeneration photosensitization strategies. Such strategies include the development of photonanomedicines functionalized with ligands for active targeting of photosensitizers (thirdgeneration photosensitizers), and photonanomedicines co-formulated with adjuvant therapeutics (fourth-generation photosensitizers). Part IV (Chapters 27–31) provides contemporary insights into the immunomodulatory effects of PDT. In Part V (Chapters 32–36), an overview of methods and models to study the antimicrobial effects of PDT are presented. Lastly, in Part VI (Chapters 37–39), a variety of general biochemical and molecular biological techniques are outlined, which will be useful to further develop the therapeutic applications of PDT. We thank all the authors who have contributed to this comprehensive volume by giving us a glimpse into their laboratory notebooks. We express our gratitude not only for sharing these valuable methods and protocols, but also for critically reviewing the contributions of others to ensure a high-quality standard for each chapter. We hope this volume of Methods in Molecular Biology is an inspiration to both new and established PDT scientists and that it helps them in their design of innovative research programs in this continuously advancing and multidisciplinary field. Grenoble, France Amsterdam, The Netherlands Vancouver, BC, Canada Doornfontein, South Africa Jiaxing, P. R. China

Mans Broekgaarden Hong Zhang Mladen Korbelik Michael R. Hamblin Michal Heger

Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

PART I

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IN VITRO AND IN VIVO MODELS TO STUDY PHOTODYNAMIC THERAPY

1 Application of Monolayer Cell Cultures for Investigating Basic Mechanisms of Photodynamic Therapy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Mans Broekgaarden 2 The Negative Impact of Cancer Cell Nitric Oxide on Photodynamic Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Jonathan M. Fahey and Albert W. Girotti 3 Microtumor Models as a Preclinical Investigational Platform for Photodynamic Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Mans Broekgaarden and Jean-Luc Coll 4 A Perfusion Model to Evaluate Response to Photodynamic Therapy in 3D Tumors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Shubhankar Nath, Michael Pigula, Tayyaba Hasan, and Imran Rizvi 5 Analysis of Treatment Effects on Structurally Complex Microtumor Cultures Using a Comprehensive Image Analysis Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Anne-Laure Bulin, Mans Broekgaarden, and Tayyaba Hasan 6 High-Throughput Examination of Therapy-Induced Alterations in Redox Metabolism in Spheroid and Microtumor Models. . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Mans Broekgaarden, Anne-Laure Bulin, and Tayyaba Hasan 7 Spatiotemporal Tracking of Different Cell Populations in Cancer Organoid Models for Investigations on Photodynamic Therapy. . . . . . . . . . . . . . . . . . . . . . . . 81 Anne-Laure Bulin and Tayyaba Hasan 8 Generating Large Numbers of Pancreatic Microtumors on Alginate-Gelatin Hydrogels for Quantitative Imaging of Tumor Growth and Photodynamic Therapy Optimization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 Nazareth Milagros Carigga Gutierrez, Tristan Le Clainche, Jean-Luc Coll, Lucie Sancey, and Mans Broekgaarden 9 The Chicken Embryo Chorioallantoic Membrane as an In Vivo Model for Photodynamic Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Jaroslava Joniova´ and Georges Wagnie`res 10 Subcutaneous Xenograft Models for Studying PDT In Vivo. . . . . . . . . . . . . . . . . . 127 Girgis Obaid and Tayyaba Hasan

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In Vivo Models for Studying Interstitial Photodynamic Therapy of Locally Advanced Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gal Shafirstein, Emily Oakley, Sasheen Hamilton, Michael Habitzruther, Sarah Chamberlain, Sandra Sexton, Leslie Curtin, and David A. Bellnier Orthotopic Models of Pancreatic Cancer to Study PDT . . . . . . . . . . . . . . . . . . . . . Girgis Obaid, Zhiming Mai, and Tayyaba Hasan An Orthotopic Murine Model of Peritoneal Carcinomatosis of Ovarian Origin for Intraoperative PDT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Thierry Michy, Claire Bernard, Jean-Luc Coll, and Ve´ronique Josserand Photodynamic Treatments for Disseminated Cancer Metastases Using Fiber-Optic Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Eric M. Kercher and Bryan Q. Spring Stereotaxic Implantation of F98 Cells in Fischer Rats: A Syngeneic Model to Investigate Photodynamic Therapy Response in Glioma. . . . . . . . . . . . . . . . . . . Anne-Laure Bulin, Jean-Franc¸ois Adam, and He´le`ne Elleaume

PART II 16

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INORGANIC PHOTOSENSTIZERS AND LIGHT-ACTIVATABLE ANTI-CANCER PRODRUGS

New Generation of Photosensitizers Based on Inorganic Nanomaterials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Xiaomin Liu and Hong Zhang Cytotoxicity of Metal-Based Photoactivated Chemotherapy (PACT) Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Vadde Ramu, Austin B. Auyeung, and Sylvestre Bonnet

PART III 18

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THIRD- AND FOURTH-GENERATION PHOTOSENSITIZERS AND TARGETING STRATEGIES

Photosensitized Oxidation of Intracellular Targets: Understanding the Mechanisms to Improve the Efficiency of Photodynamic Therapy . . . . . . . . . Thiago Teixeira Tasso and Maurı´cio S. Baptista Inhibition of the HIF-1 Survival Pathway as a Strategy to Augment Photodynamic Therapy Efficacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mark J. de Keijzer, Daniel J. de Klerk, Lianne R. de Haan, Robert T. van Kooten, Leonardo P. Franchi, Lionel M. Dias, Tony G. Kleijn, Diederick J. van Doorn, and Michal Heger Strategies for Improving Photodynamic Therapy Through Pharmacological Modulation of the Immediate Early Stress Response . . . . . . . . . . . . . . . . . . . . . . . . Daniel J. de Klerk, Mark J. de Keijzer, Lionel M. Dias, Jordi Heemskerk, Lianne R. de Haan, Tony G. Kleijn, Leonardo P. Franchi, and Michal Heger Nanobody-Targeted Photodynamic Therapy: Nanobody Production and Purification. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vida Mashayekhi, Erik Schooten, Paul M. P. van Bergen en Henegouwen, Marta M. Kijanka, and Sabrina Oliveira

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Conjugation of IRDye Photosensitizers or Fluorophores to Nanobodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vida Mashayekhi and Sabrina Oliveira In Vitro Assessment of Binding Affinity, Selectivity, Uptake, Intracellular Degradation, and Toxicity of Nanobody-Photosensitizer Conjugates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Irati Beltra´n Herna´ndez, Timo W. M. De Groof, Raimond Heukers, and Sabrina Oliveira Investigation of the Therapeutic Potential of Nanobody-Targeted Photodynamic Therapy in an Orthotopic Head and Neck Cancer Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pieter B. A. A. van Driel, Stijn Keereweer, Clemens W. G. M. Lowik, and Sabrina Oliveira Assessment of the In Vivo Response to Nanobody-Targeted PDT Through Intravital Microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Henriette S. de Bruijn, Ann L. B. Seynhaeve, Timo L. M. ten Hagen, Sabrina Oliveira, and Dominic J. Robinson Orthotopic Breast Cancer Model to Investigate the Therapeutic Efficacy of Nanobody-Targeted Photodynamic Therapy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marion M. Deken, Shadhvi S. Bhairosingh, Alexander L. Vahrmeijer, and Sabrina Oliveira

PART IV 27

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PHOTODYNAMIC THERAPY-INDUCED IMMUNE SIGNALING

Evaluation of the Antitumor Immune Response Following Photofrin-Based PDT in Combination with the Epigenetic Agent 5-Aza-20 -Deoxycytidine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Malgorzata Wachowska, Angelika Muchowicz, and Jakub Golab Controlling Immunoregulatory Cell Activity for Effective Photodynamic Therapy of Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mladen Korbelik, Zdzislaw M. Szulc, Alicja Bielawska, and Duska Separovic Measuring the Antitumor T-Cell Response in the Context of Photodynamic Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jan Willem Kleinovink and Ferry Ossendorp Combination of Photodynamic Therapy and Immune Checkpoint Blockade. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jan Willem Kleinovink and Ferry Ossendorp Combination of Photodynamic Therapy and Therapeutic Vaccination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jan Willem Kleinovink and Ferry Ossendorp

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PART V ANTIMICROBIAL PHOTODYNAMIC THERAPY 32

In Vitro Potentiation of Antimicrobial Photodynamic Inactivation by Addition of Potassium Iodide. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 607 Nasim Kashef and Michael R. Hamblin

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Contents

In Vivo Potentiation of Antimicrobial Photodynamic Therapy in a Mouse Model of Fungal Infection by Addition of Potassium Iodide . . . . . . . . . . . . . . . . . Nasim Kashef and Michael R. Hamblin Bioluminescent Models to Evaluate the Efficiency of Light-Based Antibacterial Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Ana T. P. C. Gomes, Maria A. F. Faustino, Maria G. P. M. S. Neves, and Adelaide Almeida Photochemical Internalization as a New Strategy to Enhance Efficacy of Antimicrobial Agents Against Intracellular Infections . . . . . . . . . . . . . . . . . . . . . Xiaolin Zhang, Leonie de Boer, and Sebastian A. J. Zaat Determination of the Efficiency of Photodynamic Decontamination of Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Michael Glueck and Kristjan Plaetzer

PART VI 37

38 39

621

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MOLECULAR TECHNIQUES AND TOOLS IN PHOTODYNAMIC THERAPY RESEARCH

Super-Resolution Imaging of Intracellular Lipid Nanocarriers to Study Drug Delivery in Photodynamic Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . 703 Enzo M. Scutigliani, Jakub A. Kochan, Emilie C. B. Desclos, Art Jonker, Michal Heger, and Przemek M. Krawczyk Detection of Paraptosis After Photodynamic Therapy . . . . . . . . . . . . . . . . . . . . . . . 711 David Kessel Optimal Use of 20 ,70 -Dichlorofluorescein Diacetate in Cultured Hepatocytes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 721 Megan J. Reiniers, Lianne R. de Haan, Laurens F. Reeskamp, Mans Broekgaarden, Ruurdtje Hoekstra, Rowan F. van Golen, and Michal Heger

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

749

Contributors JEAN-FRANC¸OIS ADAM • Inserm UA07 Synchrotron Radiation for Biomedicine, University of Grenoble Alpes, Grenoble, France ADELAIDE ALMEIDA • Department of Biology & CESAM, University of Aveiro, Aveiro, Portugal AUSTIN B. AUYEUNG • Leiden Institute of Chemistry, Leiden University, Leiden, The Netherlands MAURI´CIO S. BAPTISTA • Biochemistry Department, Institute of Chemistry, Universidade de Sa˜o Paulo, Sa˜o Paulo, Brazil DAVID A. BELLNIER • Photodynamic Therapy Center at the Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center (Roswell Park), Buffalo, NY, USA IRATI BELTRA´N HERNA´NDEZ • Pharmaceutics, Department of Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, The Netherlands CLAIRE BERNARD • Institute for Advanced Biosciences, University of Grenoble Alpes, INSERM U1209, CNRS UMR5309, Grenoble, France; CHU Grenoble Alpes, University of Grenoble Alpes, Grenoble, France SHADHVI S. BHAIROSINGH • Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands ALICJA BIELAWSKA • Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA LEONIE DE BOER • Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands SYLVESTRE BONNET • Leiden Institute of Chemistry, Leiden University, Leiden, The Netherlands MANS BROEKGAARDEN • Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Institute for Advanced Biosciences INSERM U1209, CNRS UMR5309, Universite´ de Grenoble Alpes, Grenoble, France; Team Cancer Targets and Experimental Therapeutics, Department Microenvironment Cell Plasticity and Signaling, Institute for Advanced Biosciences, Universite´ de Grenoble-Alpes, Alle´e des Alpes, La Tronche, France; INSERM U 1209, CNRS UMR5309, Alle´e des Alpes, La Tronche, France ANNE-LAURE BULIN • Wellman Center for Photomedicine, Department of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Universite´ de Grenoble Alpes, INSERM UA07, Synchrotron Radiation for Biomedicine, Grenoble, France NAZARETH MILAGROS CARIGGA GUTIERREZ • Institute for Advanced Biosciences, INSERM U1209, CNRS UMR 5309, Universite´ de Grenoble Alpes, Grenoble, France SARAH CHAMBERLAIN • Photodynamic Therapy Center at the Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center (Roswell Park), Buffalo, NY, USA JEAN-LUC COLL • Institute for Advanced Biosciences, University of Grenoble Alpes, INSERM U1209, CNRS UMR 5309, Grenoble, France LESLIE CURTIN • Laboratory Animals Shared Resources, Roswell Park, Buffalo, NY, USA HENRIETTE S. DE BRUIJN • Center for Optical Diagnostics and Therapy, Department of Otolaryngology and Head and Neck Surgery, Erasmus MC, Rotterdam, The Netherlands

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Contributors

TIMO W. M. DE GROOF • Amsterdam Institute of Molecular and Life Sciences (AIMMS), Division of Medicinal Chemistry, Faculty of Sciences, VU University, Amsterdam, The Netherlands; In Vivo Cellular and Molecular Imaging Lab, Department of Medical Imaging, Vrije Universiteit Brussel, Brussels, Belgium MARION M. DEKEN • Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands EMILIE C. B. DESCLOS • Department of Medical Biology, Amsterdam University Medical Centers (location AMC), Cancer Center Amsterdam, Amsterdam, The Netherlands LIONEL M. DIAS • Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics, Jiaxing University, College of Medicine, Jiaxing, Zhejiang, People’s Republic of China; Laboratory of Experimental Oncology, Department of Pathology, Erasmus MC, Rotterdam, The Netherlands DIEDERICK J. VAN DOORN • Department of Gastroenterology and Hepatology, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, The Netherlands HE´LE`NE ELLEAUME • Inserm UA07 Synchrotron Radiation for Biomedicine, University Grenoble Alpes, Grenoble, France JONATHAN M. FAHEY • Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA MARIA A. F. FAUSTINO • LAQV-REQUIMTE, Department of Chemistry, University of Aveiro, Aveiro, Portugal LEONARDO P. FRANCHI • Department of Biochemistry and Molecular Biology, Institute of Biological Sciences (ICB 2), Federal University of Goia´s (UFG), Goiaˆnia, Goia´s, Brazil ALBERT W. GIROTTI • Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA MICHAEL GLUECK • Laboratory of Photodynamic Inactivation of Microorganisms, Department of Biosciences and Medical Biology, Paris Lodron University Salzburg, Salzburg, Austria JAKUB GOLAB • Department of Immunology, Center of Biostructure Research, Medical University of Warsaw, Warsaw, Poland; Centre for Preclinical Research and Technology, Medical University of Warsaw, Warsaw, Poland ROWAN F. VAN GOLEN • Department of Gastroenterology and Hepatology, Leiden University Medical Center, Leiden, The Netherlands ANA T. P. C. GOMES • Department of Biology & CESAM, University of Aveiro, Aveiro, Portugal LIANNE R. DE HAAN • Laboratory of Experimental Oncology, Department of Pathology, Erasmus MC, Rotterdam, The Netherlands; Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics, Jiaxing University College of Medicine, Jiaxing, Zhejiang, People’s Republic of China MICHAEL HABITZRUTHER • Photodynamic Therapy Center at the Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center (Roswell Park), Buffalo, NY, USA MICHAEL R. HAMBLIN • Laser Research Centre, Faculty of Health Science, University of Johannesburg, Doornfontein, South Africa SASHEEN HAMILTON • Photodynamic Therapy Center at the Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center (Roswell Park), Buffalo, NY, USA

Contributors

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TAYYABA HASAN • Department of Dermatology, Wellman Center for Photomedicine, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA; Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA JORDI HEEMSKERK • Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics, Jiaxing University College of Medicine, Jiaxing, Zhejiang, People’s Republic of China MICHAL HEGER • Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics, Jiaxing University College of Medicine, Jiaxing, Zhejiang, People’s Republic of China; Department of Pharmaceutics, Utrecht Institute of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Laboratory of Experimental Oncology, Department of Pathology, Erasmus MC, Rotterdam, The Netherlands RAIMOND HEUKERS • Amsterdam Institute of Molecular and Life Sciences (AIMMS), Division of Medicinal Chemistry, Faculty of Sciences, VU University, Amsterdam, The Netherlands RUURDTJE HOEKSTRA • Tytgat Institute for Liver and Intestinal Research, Amsterdam UMC, Location AMC, Amsterdam, The Netherlands JAROSLAVA JONIOVA´ • Laboratory for Functional and Metabolic Imaging, Institute of Physics, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland ART JONKER • Department of Medical Biology, Amsterdam University Medical Centers (location AMC), Cancer Center Amsterdam, Amsterdam, The Netherlands VE´RONIQUE JOSSERAND • Institute for Advanced Biosciences, University of Grenoble Alpes, INSERM U1209, CNRS UMR5309, Grenoble, France NASIM KASHEF • Department of Microbiology, School of Biology, College of Science, University of Tehran, Tehran, Iran STIJN KEEREWEER • Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus Medical Centre, Rotterdam, The Netherlands MARK J. DE KEIJZER • Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics, Jiaxing University College of Medicine, Jiaxing, Zhejiang, People’s Republic of China; Department of Pharmaceutics, Utrecht Institute of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands ERIC M. KERCHER • Translational Biophotonics Cluster, Northeastern University, Boston, MA, USA; Nanomedicine Science and Technology Center, Northeastern University, Boston, MA, USA; Department of Physics, Northeastern University, Boston, MA, USA DAVID KESSEL • Department of Pharmacology, Wayne State University School of Medicine, Detroit, MI, USA MARTA M. KIJANKA • Apo-T B.V., Oss, The Netherlands TONY G. KLEIJN • Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics, Jiaxing University College of Medicine, Jiaxing, Zhejiang, People’s Republic of China; Laboratory of Experimental Oncology, Department of Pathology, Erasmus MC, Rotterdam, The Netherlands JAN WILLEM KLEINOVINK • Department of Immunology, Tumor Immunology Group, Leiden University Medical Center, Leiden, The Netherlands DANIEL J. DE KLERK • Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics, Jiaxing University College of Medicine,

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Contributors

Jiaxing, Zhejiang, People’s Republic of China; Laboratory of Experimental Oncology, Department of Pathology, Erasmus MC, Rotterdam, The Netherlands JAKUB A. KOCHAN • Department of Medical Biology, Amsterdam University Medical Centers (location AMC), Cancer Center Amsterdam, Amsterdam, The Netherlands; Department of Cell Biochemistry, Faculty of Biochemistry, Biophysics and Biotechnology, Jagiellonian University, Krakow, Poland ROBERT T. VAN KOOTEN • Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands MLADEN KORBELIK • Department of Integrative Oncology, BC Cancer Research Centre, British Columbia Cancer Agency, Vancouver, BC, Canada PRZEMEK M. KRAWCZYK • Department of Medical Biology, Amsterdam University Medical Centers (location AMC), Cancer Center Amsterdam, Amsterdam, The Netherlands TRISTAN LE CLAINCHE • Institute for Advanced Biosciences, INSERM U1209, CNRS UMR 5309, Universite´ de Grenoble Alpes, Grenoble, France XIAOMIN LIU • State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, China; Van ’t Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands; State Key Laboratory of Luminescence and Applications, Changchun Institute of Optics, FineMechanics and Physics, Chinese Academy of Sciences, Changchun, China CLEMENS W. G. M. LOWIK • Department of Radiology & Nuclear Medicine, Optical Molecular Imaging, Erasmus Medical Center, Rotterdam, The Netherlands ZHIMING MAI • Department of Dermatology, Massachusetts General Hospital, Harvard Medical School, Wellman Center for Photomedicine, Boston, MA, USA VIDA MASHAYEKHI • Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University, Utrecht, The Netherlands THIERRY MICHY • Institute for Advanced Biosciences, University of Grenoble Alpes, INSERM U1209, CNRS UMR5309, Grenoble, France; CHU Grenoble Alpes, University of Grenoble Alpes, Grenoble, France ANGELIKA MUCHOWICZ • Department of Immunology, Center of Biostructure Research, Medical University of Warsaw, Warsaw, Poland SHUBHANKAR NATH • Wellman Center for Photomedicine, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA MARIA G. P. M. S. NEVES • LAQV-REQUIMTE, Department of Chemistry, University of Aveiro, Aveiro, Portugal EMILY OAKLEY • Photodynamic Therapy Center at the Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center (Roswell Park), Buffalo, NY, USA GIRGIS OBAID • Wellman Center for Photomedicine, Department of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA SABRINA OLIVEIRA • Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University, Utrecht, The Netherlands; Department of Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, The Netherlands FERRY OSSENDORP • Department of Immunology, Tumor Immunology Group, Leiden University Medical Center, Leiden, The Netherlands MICHAEL PIGULA • Wellman Center for Photomedicine, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA KRISTJAN PLAETZER • Laboratory of Photodynamic Inactivation of Microorganisms, Department of Biosciences and Medical Biology, Paris Lodron University Salzburg, Salzburg, Austria

Contributors

xv

VADDE RAMU • Leiden Institute of Chemistry, Leiden University, Leiden, The Netherlands LAURENS F. REESKAMP • Department of Vascular Medicine, Amsterdam UMC, Location AMC, Amsterdam, The Netherlands MEGAN J. REINIERS • Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics, Jiaxing University College of Medicine, Jiaxing, Zhejiang, P. R. China; Department of Surgery, Haaglanden Medisch Centrum, The Hague, The Netherlands IMRAN RIZVI • Joint Department of Biomedical Engineering, University of North Carolina, Chapel Hill, NC, USA DOMINIC J. ROBINSON • Center for Optical Diagnostics and Therapy, Department of Otolaryngology and Head and Neck Surgery, Erasmus MC, Rotterdam, The Netherlands LUCIE SANCEY • Institute for Advanced Biosciences, INSERM U1209, CNRS UMR5309, Universite´ de Grenoble Alpes, Grenoble, France ERIK SCHOOTEN • LinXis B.V., Amsterdam, The Netherlands ENZO M. SCUTIGLIANI • Department of Medical Biology, Amsterdam University Medical Centers (location AMC), Cancer Center Amsterdam, Amsterdam, The Netherlands DUSKA SEPAROVIC • Department of Pharmaceutical Sciences, Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI, USA SANDRA SEXTON • Laboratory Animals Shared Resources, Roswell Park, Buffalo, NY, USA ANN L. B. SEYNHAEVE • Laboratory of Experimental Oncology, Department of Pathology, Erasmus MC, Rotterdam, The Netherlands GAL SHAFIRSTEIN • Photodynamic Therapy Center at the Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center (Roswell Park), Buffalo, NY, USA BRYAN Q. SPRING • Translational Biophotonics Cluster, Northeastern University, Boston, MA, USA; Department of Physics, Northeastern University, Boston, MA, USA; Department of Bioengineering, Northeastern University, Boston, MA, USA ZDZISLAW M. SZULC • Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, SC, USA THIAGO TEIXEIRA TASSO • Chemistry Department, Institute of Exact Sciences, Universidade Federal de Minas Gerais, Minas Gerais, Brazil TIMO L. M. TEN HAGEN • Laboratory of Experimental Oncology, Department of Pathology, Erasmus MC, Rotterdam, The Netherlands ALEXANDER L. VAHRMEIJER • Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands PAUL M. P. VAN BERGEN EN HENEGOUWEN • Cell Biology, Neurobiology and Biophysics, Department of Biology, Faculty of Science, Utrecht University, Utrecht, The Netherlands PIETER B. A. A. VAN DRIEL • Department of Orthopaedic Surgery, Leiden University Medical Center, Leiden, The Netherlands MALGORZATA WACHOWSKA • Department of Laboratory Diagnostics and Clinical Immunology of Developmental Age, Medical University of Warsaw, Warsaw, Poland GEORGES WAGNIE`RES • Laboratory for Functional and Metabolic Imaging, Institute of Physics, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland SEBASTIAN A. J. ZAAT • Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands

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Contributors

HONG ZHANG • State Key Laboratory of Integrated Optoelectronics, College of Electronic Science and Engineering, Jilin University, Changchun, China; Van ’t Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands XIAOLIN ZHANG • Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Infection and Immunity Institute, Amsterdam, The Netherlands

Part I In Vitro and In Vivo Models to Study Photodynamic Therapy

Chapter 1 Application of Monolayer Cell Cultures for Investigating Basic Mechanisms of Photodynamic Therapy Mans Broekgaarden Abstract Conventional monolayer cell cultures continue to be an inexpensive and highly accessible model of human disease that can be easily harnessed to study the molecular and cellular mechanisms of photodynamic therapy (PDT). In this communication, a collection of informative assays for conventional cell cultures are provided to determine (1) the photosensitizer uptake kinetics and localization, (2) the efficacy of PDT using metabolism- or protein-based quantification methods, (3) the effects of PDT and combination treatments on the cell cycle, (4) the cell death pathways induced by PDT, and (5) the extent of mitochondrial membrane permeabilization of PDT and photochemotherapy combinations. For each type of assay, examples from the recent literature are provided in which novel photosensitizers, their nanocarriers, and various PDT-based combination therapies are investigated. Together, these assays are examples of approaches by which monolayer cell cultures can be used as a simple yet robust and versatile model to investigate PDT. Key words Phototherapy, Photochemotherapy, In vitro, Viability, Metabolism, Cytotoxicity, Flow cytometry, Fluorescence microscopy, Dosimetry

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Introduction The therapeutic mechanism of photodynamic therapy (PDT) revolves around the excitation of photosensitizers, resulting in the rapid generation of cytotoxic concentrations of reactive molecular species in photosensitized cells and tissues [1–3]. The resulting oxidative damage to cellular constituents and subsequent biological effects are often difficult to predict, as these processes are highly dependent, among others, on the photosensitizer type, target cell type or organ, and state of the treated cultures (e.g., prior exposure to therapeutics, hypoxia, nutrient starved) [4–7]. To understand the often complex molecular and cellular mechanisms of PDT, two-dimensional cell cultures are highly useful and widely applied biological models. The information obtained from these models is crucial when exploring new photosensitizers and

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_1, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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photosensitization strategies, and investigating signal transduction pathways, cell survival mechanisms, and adjuvant therapeutics (i.e., [8–12]). Moreover, in comparison to 3D culture models and in vivo models, they constitute an inexpensive and highly accessible model of human disease (cancer and non-cancer). In addition, a tremendous number of assays are available, specifically for 2D culture models, ranging from toxicological assays, immunoblotting, enzyme-linked immunosorbent assays, genomics/transcriptomics, flow cytometry, (fluorescence) microscopy, as well as many fluorescence or luminescence-based reporter assays for a variety of specific investigations. In this communication we will describe a straightforward approach to investigate the effects of PDT on the molecular and cellular level using monolayer cell cultures in combination with various informative bioassays. The methods will be supplemented with various examples of studies in which these methods are used. Although the presented overview of methods and studies to analyze the effects of PDT on monolayer cell cultures is in no means complete, it provides a glimpse into the possibilities of using conventional cell cultures in PDT research.

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Methods

2.1 Photosensitization and Photosensitizer Localization

One of the primary interests of investigators that are developing novel photosensitizers, photonanomedicines, or alternative delivery strategies is to determine the extent of cellular uptake, mechanism of uptake, intracellular localization, and/or potential excretion mechanisms. The following section will provide examples of widely used methods for qualitative and quantitative assessment of photosensitizer uptake that can be easily adjusted to answer the abovementioned queries. Given that many photosensitizers are fluorescence emitters in the visible range, photosensitizer uptake can be efficiently investigated using fluorescence spectroscopy. A typical experiment may consist of seeding cells in multiwell plates at a density that reaches near-confluence overnight. The following day, the cultures can be incubated with a photosensitizing agent, and after defined incubation periods the cultures can be washed and measured using a multiplate reader to quantify the absorption or fluorescence emission of the photosensitizer. Alternatively, the cell monolayers may be dissolved in a chemical solvent (e.g., DMSO) and transferred to quartz cuvettes for spectrophotometric or spectrofluorometric analysis. Using these methods, investigators can easily optimize photosensitizer doses to reach desired intracellular photosensitizer concentrations (dose-escalation experiment), test various photosensitization time intervals, and investigate in vitro pharmacokinetics (pulse-chase experiments). It is strongly recommended to

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combine such assays with a subsequent or parallel protein quantification assay to correct for potential dark toxicity of the photosensitizer, inaccuracies during the initial cell seeding, and differences in cell densities between various cell types. Although fluorescence spectroscopy provides semiquantitative readouts of photosensitizer uptake with relatively high throughput, it typically does not inform on the intracellular localization patterns of the photosensitizing agents. (Confocal) fluorescence microscopy represents a valuable alternative to investigate photosensitizer uptake in cell cultures, providing insightful qualitative data on the intracellular localization of photosensitizers. Such information is vital to predict the efficacy and mode of cell death induced by subsequent PDT. Cells can be seeded on glass surfaces or grown on microscopy coverslips. For proper attachment, many cell types need an extracellular matrix scaffold in order to adhere to glass surfaces, such as collagen I, fibronectin, laminin, or others. Upon their growth on glass surfaces, cells can be stained with various organelle dyes such as DAPI (nucleus), mitotracker (mitochondria), and/or lysotracker (lysosomes), to determine the intracellular localization of the photosensitizer. The organelle-specific dyes need to be carefully selected to prevent spectral overlap and other physicochemical interferences with the photosensitizer. Using these methods, we have previously compared the uptake of zinc phthalocyanine delivered through tumor-targeted liposomes (TTLs, immunotargeted to human EGFR using nanobodies) and non-targeted liposomes (NTLs), demonstrating that photosensitizer uptake by the targeted cells was significantly enhanced using immunoconjugated liposomes (Fig. 1a and b) [8]. We additionally characterized the specificity of liposomal uptake using a lipid-anchored dye (1-palmitoyl-2-{6-[(7-nitro-21,3-benzoxadiazol-4-yl)amino]hexanoyl}-sn-glycero-3-phosphocholine) to fluorescently label the liposomes. Confocal microscopy and fluorescence spectroscopy were used to quantify the extent to which the liposomes were selectively taken up by cells that overexpress the target receptor (Fig. 1c and d) [8]. 2.2 In Vitro Photodynamic Therapy

Although performing PDT in vitro on 2D cell cultures can be quite easy in practice, it is complicated by the impact of a large number of parameters. Therefore, a typical PDT treatment protocol should start with careful planning of the timeline of the experiment, taking into account, among others, (1) the desired confluence of the cultures, (2) the drug-light interval, and (3) the PDT dosimetry. First, the appropriate cell density for 2D cell culture initiation should be carefully selected, as optimal cell numbers can vary dramatically between different cell types. A pilot experiment to determine cell densities is typically performed in which increasing cell numbers are seeded and grown until the desired time point. By performing a viability assay at this time (e.g., using the viability

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Fig. 1 Methods to determine photosensitizer uptake on cell culture. (a) Intracellular delivery of zinc phthalocyanine (ZnPC) by either tumor-targeted liposomes (TTLs, immunotargeted to human EGFR using nanobodies) or non-targeted liposomes (NTLs) was qualitatively determined using confocal laser scanning microscopy (scale bar ¼ 10 μm.). (b) The observed differences in ZnPC uptake were corroborated with fluorescence spectroscopy. (c) In a parallel experiment, the specificity of TTL and NTL uptake was investigated using a liposome-anchored dye on EGFR-positive A431 cells and EGFR-negative NIH 3 T3 cells using confocal laser scanning microscopy (scale bar ¼ 25 μm). (d) The observed differences in liposome uptake levels were corroborated with fluorescence spectroscopy. (Reproduced from Ref. [8] with permission from the Royal Society of Chemistry)

assays described below), and plotting the signal intensity as a function of initial cell numbers, a plateau may be observed. This plateau may be caused by either detector saturation or reaching a maximum cell density in the cultures. The ideal cell density may lie somewhere between 50 and 75% of the absorbance intensity plateau. For PDT experiments, consider seeding cells in black-walled multiwell plates for the irradiation of the cultures. Alternatively, or in addition, a sheet of black plastic or cardboard containing an appropriately sized round perforation can be fashioned to prevent unwanted light contamination in neighboring wells during the PDT protocol (e.g., 1.9 cm2 for a single well of a 24-well plate). The use of a dark surface to avoid scattering of the incoming light is also strongly recommended. Secondly, the drug-light interval needs to be optimized for individual photosensitizers and cell types. Various photosensitizers exert different uptake kinetics upon addition of the photosensitizer, potentially leading to an underestimation of PDT treatment effects for photosensitizers with low uptake constants. In addition, the excretion kinetics of the photosensitizers upon removal of the

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photosensitizer should be investigated, as this may also lead to an underestimation of the PDT treatment effects when significant delays occur between the photosensitizer uptake and actual light irradiation. These uptake parameters can be investigated in great detail using the abovementioned methodologies for photosensitizer uptake, and the findings should inform the drug-light intervals. Thirdly, the PDT dosimetry should be carefully optimized for each photosensitizer type, using an appropriate light source capable of exciting the photosensitizer(s) of interest. Note that the irradiance [mW/cm2] has a prominent effect on the PDT outcome. High irradiances may result in the rapid generation of high levels of reactive oxygen species in a short period of time, accompanied by rapid photobleaching of the photosensitizer. Alternatively, low irradiances at the same light dose produce reactive oxygen species during a longer period of time, causing prolonged oxidative stress. The impact of these different approaches is reflected on the activation of cell signaling pathways: Whereas the immediate-early stress response and hypoxic stress response were downmodulated following PDT with liposomal zinc phthalocyanine at 671 nm, 500 mW/ cm2, and 15 J/cm2, irradiation at 50 mW/cm2 and 15 J/cm2 caused a significant upregulation of these pathways in Sk-Cha1 human cholangiocarcinoma cells [13]. It should be noted that at this irradiance, photothermal effects may be observed, although this was not further investigated. For a complete assessment of the treatment efficacy of PDT for a given photosensitizer, it is recommended to perform dose-escalation experiments for photosensitizer concentrations, light doses, and irradiances. Proper controls to evaluate the induction of hyperthermia by the irradiation regime should also be taken into account. A typical protocol for initiating PDT on 2D cultures starts with harvesting near-confluent cell cultures from culture flasks by washing the cells with PBS and incubation with a cell detachment solution (e.g., trypsin) for 5–15 min. Add 8 mL medium, perform cell counts, and dilute the cell suspension in culture medium to the desired density, preparing a sufficient volume for the entire experiment. Seed the desired cell density in the individual wells of multiwell plates of choice. Allow the cells to adhere to the plate surface, which typically takes 4–24 h. Subsequently, incubate cells with the desired photosensitizer concentrations during the predefined photosensitization time. The inclusion of a light-only control and photosensitizer-only control is strongly recommended to correct for hyperthermic effects and photosensitizer dark toxicity, respectively. Immediately prior to performing PDT, turn on the irradiation source. Adjust the spot size corresponding to the multiwell plates (e.g., 1.9 cm2 for 24-well plates, or a 2-by-2 grid on 96-well plates). Let the source warm up for 20–30 minutes to stabilize the laser beam, and then adjust the irradiance using a power meter

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(typical range 10–250 mW/cm2). Subsequently wash the cultures three times using PBS or medium. Irradiate the cultures with the desired dose(s) of laser light (e.g., between 0.1 and 100 J/cm2), and then place the cultures back in standard culture conditions. Please note that conventional culture conditions involve atmospheric oxygen levels which typically does not reflect physiological oxygen levels in vivo. From here on, the cultures can be analyzed for a variety of investigations, including assays for treatment efficacy (Subheading 2.3), effect of PDT on the cell cycle (Subheading 2.4), determining the extent and type of cell death (Subheading 2.5), or investigating the loss of mitochondrial membrane potential (Subheading 2.6). Alternatively, or in addition, cells can be harvested for protein, DNA, or RNA isolation and subsequent detailed molecular analyses such as proteomics and transcriptomics [14–18]. 2.3 Combined Assessment of Viability and Metabolic Activity

One of the primary interests of many investigators is to determine the efficacy of PDT, for which a variety of techniques are available. Tetrazolium-based toxicity assays constitute one of the most widely applied methods in PDT research. With respect to tetrazoliumbased assays, the use of water-soluble tetrazolium (WST) or 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2(4-sulfophenyl)-2H-tetrazolium (MTS) provides a substantial advantage as these reagents are nondestructive to the cell cultures, and can thus be easily combined with subsequent protein quantification assays. The conversion of tetrazolium salts to formazan is catalyzed by NAD(P)H-dependent dehydrogenases in metabolically active cells [19]. Commercially available WST or MTS can be used in accordance to the manufacturer’s instructions, prior to which cells can be seeded and treated with PDT as described above. Following a desired and predefined incubation time (e.g., between 1 and 72 h), cell culture medium is removed and replaced with fresh culture medium containing an appropriate dilution of the WST or MTS solution (MTS requires supplementation with phenazine methosulfate) [20]. As the formation of formazan is dependent on the cell type, cell density, treatment, and dilution of the tetrazolium solution, the exact dilutions and incubation times may need to be carefully optimized. As an example, we have previously used a 1:30 dilution of WST-1 in culture medium combined with a 30-min incubation time, yielding reproducible results for A431 human squamous cell carcinoma cells, SK-Cha1 human cholangiocarcinoma cells, primary human umbilical vein endothelial cells (HUVECs), EMT6 murine mammary carcinoma cells, and RAW 264.7 murine macrophages [8, 14, 15, 21, 22]. However, the major pitfall of metabolism-based viability assays is that they operate on the assumption that the treatment of interest does not influence cell metabolism, which is not true in most cases. Various studies have demonstrated that PDT impairs glycolysis,

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affects mitochondrial respiration, and promotes autophagy [23– 26]. Therefore, auxiliary assays may be necessary to provide additional toxicological information to corroborate the findings. Protein or DNA quantification may be considered as valuable alternatives, or in addition to tetrazolium-based viability assays. Such assays provide a crude readout of the total amount of tissue in a given experimental condition, but is agnostic to the viability or metabolic state of the tissue. Assays based on residual protein levels in the cell cultures following excessive washing are also widely applied, including sulforhodamine B staining and bicinchoninic acid-based protein quantification. These assays operate on the assumption that cytotoxic treatments either prevent proliferation or induce cell death, with the dead cells being washed away prior to the actual protein quantification. Using both the WST-1 assay combined with the sulforhodamine staining method for protein quantification [27], Weijer et al. previously investigated the timedependent efficacy of PDT with zinc phthalocyanine encapsulated in cationic liposomes, as evaluated on various cell lines. The results demonstrated that although the general trend in therapeutic efficacy was similar using the two assays, distinct differences could be detected, indicating that PDT may promote cellular metabolism that may be falsely detected as increased overall cell viability by the formazan-based assay alone [15]. These findings underline the necessity to investigate treatment responses using various mechanistically distinct assays, such as metabolic activity, protein/DNA quantities, and levels of apoptosis/ necrosis (described in more detail below). Lastly, by combining metabolism-based viability assays with protein quantification methods, the effects of treatment on cell metabolism can be easily investigated. For example, the absorbance of formazan can be divided by the protein concentration to obtain a relative metabolic activity per mg protein. In all cases, careful planning of the experiments in terms of timeline and starting cell densities is critical to ensure that the final readouts fall within the linear detection range; that is, the measurements should not be subject to signal saturation. 2.4 Cell Cycle Profiling

As chemotherapies and radiotherapeutic regimens remain the standard of care for many inoperable cancer patients, investigating the beneficial effects of PDT to these therapies may hold significant translational value. Radiotherapy and many chemotherapeutics exert their effects through the induction of DNA damage, triggering cell cycle arrests, mitotic perturbations, and programmed cell death. Although most photosensitizers do not induce DNA damage as their intracellular localization patterns typically do not involve the nucleus, cell cycle profiling remains a useful tool to investigate the cytostatic efficacies of PDT combined with either chemotherapeutics or radiotherapy.

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Flow cytometry represents a versatile tool for analyzing treatment effects on individual cells that can be performed in addition or as an alternative to the assays described above. The effects of treatment on the proliferation of cells can be investigated by profiling the different cell cycle phases on permeabilized cells and subsequent DNA staining with, e.g., propidium iodide (PI) [28]. By measuring the fluorescence intensity per cell, its DNA content can be quantified. A relative fluorescence intensity of 1 represents cells in the G0/G1 phase of the cell cycle. Cells emitting twice that fluorescence intensity are in the G2/M phase, and cells with a relative fluorescence intensity >1 and 220 arb. units). Cell cycle profiling has been used abundantly to investigate combination therapies of PDT and DNA-damaging chemotherapeutics. For instance, the potential of PDT to enhance the effect of cisplatin chemotherapy for the treatment of esophageal cancer cells has been explored. In this study, cisplatin alone induced a prominent cell cycle arrest in the S and G2/M phases in KYSE-510 human P53-mutated esophageal carcinoma cell cultures, whereas adjuvant Photofrin-PDT resulted in an increased population with sub-G1 DNA content (apoptosis) [32]. Another recent study demonstrated that a combination therapy of PDT and the hypoxia-activated chemotherapeutic tirapazamine induced DNA damage and intra-S and G2/M phase arrests in A431 human

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epidermoid carcinoma cells and Sk-Cha-1 human cholangiocarcinoma cells, indicating that oxygen consumption during PDT induces a brief state of hypoxia that is capable of activating hypoxia-activated cytotoxins [9]. Cell cycle profiling has similarly been used to test the efficacy of novel nanoemulsions containing chloroaluminum phthalocyanine and doxorubicin in the context of breast cancer. Evaluation of the cell cycle revealed that, in the absence of light, doxorubicin arrested 4T1 murine mammary carcinoma cells in the G2/M phase, whereas the multi-agent nanoemulsions induced massive apoptosis following light irradiation [34]. These examples clearly demonstrate the utility of cell cycle profiling in the evaluation of photochemotherapy combinations and the development of new photonanomedicines. 2.5 Determination of Cell Death Modes

The efficacy of any given therapy can stem from various factors, including inhibition of proliferation and induction of programmed or spontaneous cell death (apoptosis/necrosis). Measuring the extent to which particular cell death pathways are involved in establishing the cytotoxic effects of PDT provides valuable insights into the proposed mechanism of cell killing. The various cell death mechanisms induced by PDT have unique immunomodulatory properties [35, 36] and play a crucial role in the induction of an antitumor immune response by PDT [2, 22, 37]. Therefore, the mechanism through which PDT-treated cells perish may have dire consequences to the therapeutic efficacy of PDT in immunocompetent animal models and patients. To investigate both the extent and the mode of cell death following treatments, flow cytometry can be performed following the staining of apoptotic cells with Annexin V and necrotic cells using a DNA stain such as PI. Annexin V binds to phosphatidylserine, which is specifically presented on the outer surface of apoptotic cells [38]. Whereas both healthy cells and apoptotic cells are impermeable to PI, the DNA of necrotic cells is effectively stained due to the loss of cell membrane integrity. Detection of both fluorophores in individual cells using flow cytometry can thus identify healthy (unstained), apoptotic (Annexin V positive), and necrotic (PI positive) cell populations. Considering the rationale that PI can only stain cells with compromised cell membranes, whereas Annexin V can also stain the inner membrane of such cells, the cells that test positive for both PI and Annexin V should also be considered as necrotic. Variations of this staining protocol exist and commercial assay kits to perform such investigations are widely available. A typical experiment follows a similar cell seeding and treatment protocol as described for the abovementioned cell cycle profiling procedure and is schematically depicted in Fig. 3. At the time of cell harvesting, prepare 15 mL centrifuge tubes for all experimental conditions and keep the tubes on ice. As necrotic

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Fig. 3 Experimental overview of a typical cell death quantification experiment, with an example of a nanocarrier-based PDT experiment. Cells are seeded in multiwell plates and treated as desired, and both culture medium and washing solution (typically PBS) are harvested in centrifuge tubes for each sample. Cells are then harvested using cell detachment solution, which are collected in the centrifuge tubes already containing the harvested medium and washing solution. Immediately thereafter, cells and cell debris are washed by centrifugation, and stained for Annexin V and DNA using a cell membrane-impermeant dye. Cell death profiling is performed using flow cytometry, depicting the histograms of DNA content within the linear range

and apoptotic cells frequently detach from the culture surface, it is advised to collect the culture medium from all experimental conditions in their respective 15 mL tubes. Wash the cultures using PBS, and transfer the PBS to the appropriate 15 mL centrifuge tubes (already containing the harvested culture medium). Cultures can then be harvested using a cell detachment solution (e.g., trypsin), and the harvested cells can be added to the 15 mL centrifuge tubes. Cells can then be pelleted by centrifugation, and cell staining can be performed using a commercially available kit in accordance with the manufacturer’s instructions. With the use of the Annexin V/PI staining method, we previously demonstrated that the therapeutic efficacy of PDT with a liposomal formulation of zinc phthalocyanine predominantly induced necrotic cell death [21]. A similar method was used to investigate the light dose-dependent induction of cell death by PDT following a combinatorial photosensitization strategy, which revealed that low-dose PDT induced mainly apoptotic cell death, whereas high-dose PDT induced necrosis [39]. In a study on the

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capacity of PDT to disrupt lymphatic vessels it was demonstrated that PDT with benzoporphyrin derivative is highly effective toward human lymphatic endothelial cells, which was related to a significant increase in Annexin V-positive cells. These findings were corroborated by the detection of increased caspase 3 and caspase 9 activity, cleavage of poly (ADP-ribose) polymerase (PARP), and DNA fragmentation, suggesting that apoptosis was the main mechanism of cell death. As the efficacy of PDT and the emergence of apoptotic markers could be inhibited by the caspase inhibitor ZVAD-FMK as well as by the autophagy inhibitor 3-methyladenine, the authors concluded that autophagy constituted the triggering source of PDT-induced apoptosis in human lymphatic endothelial cells [40]. 2.6 Assessment of Mitochondrial Membrane Potential

As a preliminary marker for apoptosis, flow cytometry may also be performed on cells stained with a marker for the mitochondrial membrane potential (MMP), as mitochondrial depolarization is an early event during apoptosis. It should be noted that loss of MMP is reversible and may not necessarily culminate in cell death. Measuring loss of MMP thus constitutes an early marker of potential treatment effects. To measure mitochondrial membrane integrity following PDT, the use of the dyes 5,50 ,6,60 -tetrachloro-1,10 ,3,30 -tetraethyl-benzimidazolylcarbocyanine iodide (JC-1), 3,30 -dihexyloxacarbocyanine iodide (DiOC6), and mitotracker orange (MTO) is described. The cationic JC-1 dye accumulates in mitochondria where it forms red-emitting aggregates. In case of MMP, the JC-1 aggregates dissociate into green-emitting monomers. With respect to PDT, we and others have used JC-1 to investigate the cellular effects of PDT as an individual therapy or in combination with adjuvant therapies [9, 41–43]. A typical experiment can follow the same procedure for cell seeding and PDT treatment as described for the cell cycle profiling and mode of cell death investigations. However, prior to harvesting the cells for FACS, cell cultures are stained for 30 min with 10 μg/mL JC-1 in PBS (e.g., 500 μL/well for 24-well plates) under standard culture conditions. Cells are subsequently harvested as described for the cell cycle profiling and mode of cell death investigations. Flow cytometry can then be performed to quantify the presence of red-emitting JC-1 aggregates (λex 585 nm, λem 590 nm) and green-emitting JC-1 monomers (λex 514 nm, λem 529 nm). Separation of the cell debris from the intact cells is done by applying an appropriate gate in the forward scatter (FSC)/side scatter (SSC) plots. Plots based on the 530 nm emission and 585 nm emission can be used to gate and quantify the red fluorescent population (healthy cells) and green fluorescent cell population (loss of MMP). Obtained data can be depicted as bar graphs or given as percentages/ratios [9]. As an alternative to flow cytometry, JC-1 can also be used to study loss of MMP using confocal fluorescence microscopy [44].

Assays for Monolayer Cell Cultures to Investigate PDT

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Alternatively, mitochondrial dyes may be used to evaluate the loss of MMP following PDT, as distinct localization patterns of the dyes indicate whether the MMP is intact. With the use of MTO, it was demonstrated that 1c1c7 murine hepatoma cells underwent massive loss of MMP directly following PDT with benzoporphyrin derivative. However, the MMP was restored within 30–60 min when cells were exposed to a sublethal radiant exposure [26]. In a similar fashion DiOC6 can be used in combination with confocal microscopy or flow cytometry to investigate MMP. In a study in which a highly effective PDT regimen was designed based on the combined photosensitization of cells with zinc phthalocyanine and meso-tetrakis(4-N-methylpyridyl)porphine (TMPyP), the use of the DiOC6 staining revealed that most cells underwent significant loss of MMP in a time-dependent fashion. Moreover, the investigators corroborated these findings by detecting increased levels of apoptosis (Annexin V/PI method) and poly (ADP-ribose) polymerase (PARP) cleavage (using immunoblotting) [39]. Therefore, investigations on the loss of MMP by PDT or PDT-based combinations may help to better understand the mechanisms and kinetics of the projected treatments.

3

Data Analysis and Interpretation The presented overview of methods to analyze the effects of PDT emphasizes the strength of 2D culture models to explore the therapeutic efficacies and mechanisms of PDT, PDT-based combination treatments, newly developed nanoparticular phototherapeutics, and novel photosensitizing agents. As PDT has received interest in the treatment of various cancer and non-cancer pathologies [45], PDT investigations on the disease of interest can be achieved by the selection of appropriate cell lines, and/or patient-derived primary cells. For example, a wide range of cancer cell lines exist for studies on the applications of PDT in oncology. Retinal pigment epithelium and/or vascular endothelial cells can be selected for in vitro studies on PDT in ophthalmology (e.g., age-related macular degeneration). A variety of other cell lines exist to study the effects of PDT on, e.g., blood vessels and angiogenesis (vascular endothelial cells, vascular smooth muscle cells), wound healing (fibroblasts, endothelial cells), and immune system (macrophages, T cells, natural killer cells), to name a few. A realistic view should be kept when interpreting data obtained from conventional 2D cultures. Although monolayer cell cultures may provide valuable mechanistic information, the extent at which these mechanisms occur in these cultures may not directly translate to 3D culture models or in vivo models, let alone the clinical situation.

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A first example relates to the oxygen pressures in vitro versus in vivo. Oxygen is a crucial component of PDT, as it is a substrate in the relaxation processes of photoexcited, triplet-state photosensitizers, resulting in the formation of O2  (superoxide anion, type I photochemical reactions) and 1O2 (singlet oxygen, type II photochemical reactions). These ROS are responsible for inducing the cytotoxic effects of PDT in cells and tissues. As PDT on in vitro models is typically performed at atmospheric partial oxygen pressures (20%, 160 mmHg), the results are not fully representative of the clinical situation. In healthy peripheral tissues, oxygen levels are typically in the range of 3.4–6.8% (38 mmHg), whereas tumors often develop as hypoxic tissues, with oxygen percentages often in the range of 0.3–4.2% (2–32 mmHg) [46]. Differences in oxygen availabilities can strongly influence PDT responses, with hyperoxic conditions typically favoring PDT outcomes [47, 48]. In addition, atmospheric oxygen levels typically fail to evoke a (naturally occurring) hypoxic survival response, mediated by the hypoxia-inducible factor-1 transcription factor [4, 10, 30, 49]. More accurate investigations on PDT efficacy may be performed using hypoxic incubators, although these are not widely available. A second example relates to drug uptake and light dosimetry. These are typically homogeneous in 2D cultures, making it safe to assume that all cells in culture are exposed to similar photosensitizer concentrations and radiant exposures. As a result, 2D cultures may provide a response homogeneity and reproducibility that are not typically observed in more advanced experimental models. Instead of considering this as a weakness, these factors make 2D cell cultures a highly useful model to compare the effects of PDT and other treatments between cell types of varying origins. Differences in metabolism, gene expression profiles, surface protein expression patterns, and a plethora of other factors may contribute to variations in dose-response correlations and the mechanisms through which photosensitizers and PDT exert their therapeutic effects. To accurately assess these, it is strongly advised to explore the treatment effects on various cell lines within the same study, especially since substantial differences in chemotherapy and PDT efficacies can be observed within various cell lines derived of the same cancer type [10, 30, 50, 51]. In addition, an immunotargeted drug delivery system for PDT should be tested not only on cells that overexpress the targeted surface marker, but also on cell types devoid of this marker to determine nonspecific uptake [8]. Similarly, a combination therapy of PDT and DNA-damaging agents may be tested on p53-positive and p53-negative cell lines, as this mutation occurs frequently in cancer with significant effects on the therapeutic efficacy of DNA-damaging agents [9, 52]. As such, the use of 2D cell cultures provides a level of control that is not easily achievable with more advanced disease models, further demonstrating the convenience of these models in basic fundamental and translational research. l

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Thirdly, a major shortcoming of 2D culture models in PDT research is their inability to capture mesoscopic treatment effects. In clinical and preclinical in vivo studies on PDT for cancer, PDT is known to not only kill tumor cells, but also induce a vascular shutdown [53] and an antitumor immune response [2], as well as influence the tumor stroma [54]. It is also challenging to use conventional 2D cultures to study the effect of PDT on physical cell-cell interactions, as cell types of different origins can have highly different proliferation rates and compete for the same limited space in culture dishes. However, heterotypic cell signaling interactions (non-direct effects) can be studied using compartment-restricted cell cultures (e.g., cell culture inserts) or bystander models [55]. Lastly, another factor to consider is the nature of the assays used in 2D culture models. In the clinic, as well as in many animal experiments, the primary readout of treatment efficacy is the tumor size, measured using a variety of imaging techniques or caliper measurements. Such measurements are not feasible in conventional cell cultures, thus rendering direct comparisons of treatment efficacies between in vitro and in vivo experiments challenging. In contrast, available treatment efficacy assessments for conventional cell cultures are much more detailed in nature, yet individually do not capture the treatment effects in its entirety. For example, a protein quantification will provide information on the absolute reduction of tissue by a given treatment, but it does not provide information on the viability of the remaining tissues. Similarly, a tetrazolium-based viability assay does not provide information on whether the metabolically formed formazan resulted from small numbers of metabolically hyperactive cells or from large numbers of metabolically senescent cells. In the same way, with respect to photosensitization, confocal fluorescence microscopy may provide a qualitative readout of photosensitizer uptake and localization, whereas flow cytometry or fluorescence spectroscopy may be used to provide more “quantitative” information regardless of localization. Therefore, in the evaluation of PDT strategies, it is strongly advised to not base the assessment of treatment efficacies and/or treatment optimization on a single type of assay and cell type, but rather a combination of mechanistically distinct methods performed on multiple and phenotypically distinct cell types.

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Discussion When considering the use of 2D cancer models for investigations toward PDT, the dissimilarities between these models and the clinical presentation of cancer tissues in patients should be taken into account. Although the results obtained in 2D models provide valuable insights into the mechanisms by which therapies such as

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PDT exert their often complex effects, the simplistic nature of these models does not account for the complexity in tissue architecture, vascularization, metabolic gradients, heterogeneous drug distributions, inhomogeneous light dosimetry, and molecular and cellular diversity that are typically observed in 3D cultures, in vivo models, and clinical settings. Despite these shortcomings, 2D monolayer cell cultures are relatively inexpensive, provide a high level of control, and typically produce robust results. As such, 2D culture models are an excellent exploratory model for the development of new photosensitizing agents, PDT treatment strategies, and combination therapies, or when studying the molecular mechanisms associated to PDT. An elaborate assessment including multiple assay types and various cell lines should be considered to obtain robust information prior to proceeding to 3D or in vivo models. References 1. Plaetzer K, Krammer B, Berlanda J, Berr F, Kiesslich T (2009) Photophysics and photochemistry of photodynamic therapy: fundamental aspects. Lasers Med Sci 24:259–268 2. Castano AP, Mroz P, Hamblin MR (2006) Photodynamic therapy and anti-tumour immunity. Nat Rev Cancer 6:535–545 3. Dolmans DEJGJ, Fukumura D, Jain RK (2003) Photodynamic therapy for cancer. Nat Rev Cancer 3:380–387 4. Broekgaarden M, Weijer R, van Gulik TM, Hamblin MR, Heger M (2015) Tumor cell survival pathways activated by photodynamic therapy: a molecular basis for pharmacological inhibition strategies. Cancer Metastasis Rev 34: 643–690 5. Weijer R, Broekgaarden M, Kos M, van Vught R, Rauws EAJ, Breukink E, van Gulik TM, Storm G, Heger M (2015) Enhancing photodynamic therapy of refractory solid cancers: combining second-generation photosensitizers with multi-targeted liposomal delivery. J Photochem Photobiol C Photochem Rev 23: 103–131 6. O’Connor AE, Gallagher WM, Byrne AT (2009) Porphyrin and nonporphyrin photosensitizers in oncology: preclinical and clinical advances in photodynamic therapy. Photochem Photobiol 85:1053–1074 7. Casas A, Di Venosa G, Hasan T, Batlle A (2011) Mechanisms of resistance to photodynamic therapy. Curr Med Chem 18: 2486–2515 8. Broekgaarden M, van Vught R, Oliveira S, Roovers RC, van Bergen en Henegouwen PMP, Pieters RJ, Van Gulik TM, Breukink E, Heger M (2016) Site-specific conjugation of

single domain antibodies to liposomes enhances photosensitizer uptake and photodynamic therapy efficacy. Nanoscale 8: 6490–6494 9. Broekgaarden M, Weijer R, van Wijk AC, Cox RC, Egmond MR, Hoebe R, van Gulik TM, Heger M (2017) Photodynamic therapy with liposomal zinc Phthalocyanine and Tirapazamine increases tumor cell death via DNA damage. J Biomed Nanotechnol 13:204–220 10. Broekgaarden M, Weijer R, Krekorian M, Ijssel B, Kos M, Alles LK, Wijk AC, Bikadi Z, Hazai E, Gulik TM et al (2016) Inhibition of hypoxia-inducible factor 1 with acriflavine sensitizes hypoxic tumor cells to photodynamic therapy with zinc phthalocyanineencapsulating cationic liposomes. Nano Res 6: 1639–1662 11. Obaid G, Chambrier I, Cook MJ, Russell DA (2012) Targeting the oncofetal ThomsenFriedenreich disaccharide using jacalin-PEG phthalocyanine gold nanoparticles for photodynamic cancer therapy. Angew Chem Int Ed Engl 51:6158–6162 12. Obaid G, Chambrier I, Cook MJ, Russell DA (2015) Cancer targeting with biomolecules: a comparative study of photodynamic therapy efficacy using antibody or lectin conjugated phthalocyanine-PEG gold nanoparticles. Photochem Photobiol Sci 14:737–747 13. Van Dilla MA, Trujillo TT, Mullaney PF, Coulter JR (1969) Cell microfluorometry: a method for rapid fluorescence measurement. Science 163:1213–1214 14. Weijer R, Broekgaarden M, van Golen RF, Bulle E, Nieuwenhuis E, Jongejan A, Moerland PD, van Kampen AHC, van Gulik TM, Heger

Assays for Monolayer Cell Cultures to Investigate PDT M (2015) Low-power photodynamic therapy induces survival signaling in perihilar cholangiocarcinoma cells. BMC Cancer 15:1014 15. Weijer R, Clavier S, Zaal EA, Pijls MME, van Kooten RT, Vermaas K, Leen R, Jongejan A, Moerland PD, van Kampen AHC et al (2017) Multi-OMIC profiling of survival and metabolic signaling networks in cells subjected to photodynamic therapy. Cell Mol Life Sci 74: 1133–1151 16. Buytaert E, Matroule JY, Durinck S, Close P, Kocanova S, Vandenheede JR, de Witte PA, Piette J, Agostinis P (2008) Molecular effectors and modulators of hypericin-mediated cell death in bladder cancer cells. Oncogene 27: 1916–1929 17. Starkey JR, Rebane AK, Drobizhev MA, Meng F, Gong A, Elliott A, McInnerney K, Spangler CW (2008) New two-photon activated photodynamic therapy sensitizers induce xenograft tumor regressions after near-IR laser treatment through the body of the host mouse. Clin Cancer Res 14:6564–6573 18. Tsaytler PA, O’Flaherty MC, Sakharov DV, Krijgsveld J, Egmond MR (2008) Immediate protein targets of photodynamic treatment in carcinoma cells. J Proteome Res 7:3868–3878 19. Stockert JC, Horobin RW, Colombo LL, Bla´zquez-Castro A (2018) Tetrazolium salts and formazan products in cell biology: viability assessment, fluorescence imaging, and labeling perspectives. Acta Histochem 120:159–167 20. Dunigan DD, Waters SB, Owen TC (1995) Aqueous soluble tetrazolium/formazan MTS as an indicator of NADH- and NADPHdependent dehydrogenase activity. Biotechniques 19:640–649 21. Broekgaarden M, de Kroon AIPM, van Gulik TM, Heger M (2014) Development and in vitro proof-of-concept of interstitially targeted zinc- phthalocyanine liposomes for photodynamic therapy. Curr Med Chem 21: 377–391 22. Broekgaarden M, Kos M, Jurg FA, van Beek AA, van Gulik TM, Heger M (2015) Inhibition of NF-κB in tumor cells exacerbates immune cell activation following photodynamic therapy. Int J Mol Sci 16:19960–19977 23. Hilf R (2007) Mitochondria are targets of photodynamic therapy. J Bioenerg Biomembr 39: 85–89 24. Kessel D, Vicente MGH, Reiners JJ (2006) Initiation of apoptosis and autophagy by photodynamic therapy. Autophagy 2:289–290 25. Pogue BW, O’Hara JA, Demidenko E, Wilmot CM, Goodwin IA, Chen B, Swartz HM, Hasan T (2003) Photodynamic therapy with

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38. Koopman G, Reutelingsperger CP, Kuijten GA, Keehnen RM, Pals ST, van Oers MH (1994) Annexin V for flow cytometric detection of phosphatidylserine expression on B cells undergoing apoptosis. Blood 84:1415–1420 ˜ ete M, Villanueva A 39. Acedo P, Stockert JC, Can (2014) Two combined photosensitizers: a goal for more effective photodynamic therapy of cancer. Cell Death Dis 5:e1122 40. Wachowska M, Osiak A, Muchowicz A, Gabrysiak M, Domagała A, Kilarski WW, Golab J (2016) Investigation of cell death mechanisms in human lymphatic endothelial cells undergoing photodynamic therapy. Photodiagn Photodyn Ther 14:57–65 41. Chiu SM, Oleinick NL (2001) Dissociation of mitochondrial depolarization from cytochrome c release during apoptosis induced by photodynamic therapy. Br J Cancer 84: 1099–1106 42. Shimamura Y, Tamatani D, Kuniyasu S, Mizuki Y, Suzuki T, Katsura H, Yamada H, Endo Y, Osaki T, Ishizuka M et al (2016) 5-Aminolevulinic acid enhances ultrasoundmediated antitumor activity via mitochondrial oxidative damage in breast cancer. Anticancer Res 36:3607–3612 43. Tian S, Yong M, Zhu J, Zhang L, Pan L, Chen Q, Li K-T, Kong Y-H, Jiang Y, Yu T-H et al (2017) Enhancement of the effect of methyl pyropheophorbide-a-mediated photodynamic therapy was achieved by increasing ROS through inhibition of Nrf2-HO-1 or Nrf2-ABCG2 signaling. Anti Cancer Agents Med Chem 17:1824–1836 44. Chen C-W, Chan Y-C, Hsiao M, Liu R-S (2016) Plasmon-enhanced photodynamic cancer therapy by upconversion nanoparticles conjugated with Au nanorods. ACS Appl Mater Interfaces 8:32108–32119 45. Huang Z (2005) A review of progress in clinical photodynamic therapy. Technol Cancer Res Treat 4:283–293 46. McKeown SR (2014) Defining normoxia, physoxia and hypoxia in tumours—implications for treatment response. Br J Radiol 87:20130676 47. Blake E, Allen J, Curnow A (2013) The effects of protoporphyrin IX-induced photodynamic

therapy with and without iron chelation on human squamous carcinoma cells cultured under normoxic, hypoxic and hyperoxic conditions. Photodiagn Photodyn Ther 10:575–582 48. Bajgar R, Kolarova H, Bolek L, Binder S, Pizova K, Hanakova A (2014) High oxygen partial pressure increases photodynamic effect on HeLa cell lines in the presence of Chloraluminium Phthalocyanine. Anticancer Res 34: 4095–4099 49. Ferrario A, von Tiehl KF, Rucker N, Schwarz MA, Gill PS, Gomer CJ (2000) Antiangiogenic treatment enhances photodynamic therapy responsiveness in a mouse mammary carcinoma. Cancer Res 60:4066–4069 50. Celli JP, Solban N, Liang A, Pereira SP, Hasan T (2011) Verteporfin-based photodynamic therapy overcomes gemcitabine insensitivity in a panel of pancreatic cancer cell lines. Lasers Surg Med 43:565–574 51. Daemen A, Peterson D, Sahu N, McCord R, Du X, Liu B, Kowanetz K, Hong R, Moffat J, Gao M et al (2015) Metabolite profiling stratifies pancreatic ductal adenocarcinomas into subtypes with distinct sensitivities to metabolic inhibitors. Proc Natl Acad Sci U S A 112: E4410–E4417 52. Fan S, El-Deiry WS, Bae I, Freeman J, Jondle D, Bhatia K, Fornace AJ, Magrath I, Kohn KW, O’Connor PM (1994) p53 gene mutations are associated with decreased sensitivity of human lymphoma cells to DNA damaging agents. Cancer Res 54:5824–5830 53. Fingar VH (1996) Vascular effects of photodynamic therapy. J Clin Laser Med Surg 14: 323–328 54. Huang H-C, Rizvi I, Liu J, Anbil S, Kalra A, Lee H, Baglo Y, Paz N, Hayden D, Pereira S et al (2018) Photodynamic priming mitigates chemotherapeutic selection pressures and improves drug delivery. Cancer Res 78: 558–571 55. Bazak J, Fahey JM, Wawak K, Korytowski W, Girotti AW (2017) Enhanced aggressiveness of bystander cells in an anti-tumor photodynamic therapy model: role of nitric oxide produced by targeted cells. Free Radic Biol Med 102: 111–121

Chapter 2 The Negative Impact of Cancer Cell Nitric Oxide on Photodynamic Therapy Jonathan M. Fahey and Albert W. Girotti Abstract Numerous studies have shown that low-flux nitric oxide (NO) in tumors produced mainly by inducible nitric oxide synthase (iNOS/NOS2) can signal for angiogenesis, inhibition of apoptosis, and promotion of cell growth, migration, and invasion. Studies in the authors’ laboratory have revealed that iNOS-derived NO in various cancer cell types elicits resistance to cytotoxic photodynamic therapy (PDT) and moreover endows PDT-surviving cells with more aggressive proliferation and migration/invasion. In this chapter, we describe how cancer cell iNOS/NO in vitro can be monitored in different PDT model systems (e.g., a targeted cell-bystander cell model) and how pharmacologic interference with basal and PDT-upregulated iNOS/NO can significantly improve PDT outcomes. Key words 2D Co-cultures, Nitric oxide (NO), Inducible nitric oxide synthase (iNOS), iNOS/NO measurements, PDT resistance, Post-PDT aggressiveness, Bystander effects, Anti-iNOS/NO adjuvants

1

Introduction Classical photodynamic therapy (PDT) is a unique antitumor treatment modality involving a photosensitizing agent (PS), PS-exciting visible-to-near-infrared light, and O2 for treating a variety of solid tumors, including breast, prostate, and brain tumors, some of which are chemo/radiotherapy resistant [1, 2]. Early studies involving porfimer sodium as PS revealed that endogenous nitric oxide (NO) in mouse syngeneic tumor models markedly reduced PDT effectiveness [3, 4]. This was realized by showing that L-NAME, a nonspecific nitric oxide synthase (NOS) inhibitor, significantly enhanced tumor regression rate after PDT. The antiPDT action of NO was mainly attributed to its effects on the tumor microvasculature, i.e., NO-mediated vasodilation acting in opposition to PDT-induced vasoconstriction [4]. Studies in the authors’ laboratory have revealed that NO produced by inducible nitric oxide synthase (iNOS/NOS2) in a variety of tumor cells can elicit

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_2, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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nonvascular anti-PDT effects via (1) increased resistance signaling after a PDT challenge and (2) increased aggressiveness of cells that can withstand the challenge [5–12]. Using several human cancer cell lines (breast COH-BR1, MCF-7, MDA-MB-231; prostate PC3, DU145; glioblastoma U87, U251) sensitized in mitochondria with 5-aminolevulinic acid (ALA)-induced protoporphyrin IX (PpIX), the authors’ group has made several key findings with negative impact on PDT efficacy. For example, all of the indicated cells expressed iNOS at a low basal level, but the enzyme underwent a rapid and prolonged upregulation after ALA/light treatment. The resulting NO signaled for greater resistance because more extensive apoptosis occurred when an iNOS activity inhibitor (1400W, GW274150) or NO scavenger (cPTIO) was present [5– 7]. In addition, PC3 cells that survived the ALA/light challenge and expressed greater iNOS were found to proliferate, migrate, and invade more rapidly than non-challenged controls [8, 9]. Moreover, in more recent studies, NO from ALA/light-targeted cells caused a striking increase in growth and migration rate of non-targeted “bystander” cells, which made no physical contact with targeted counterparts [13]. A novel technique was developed for distinguishing targeted cells from bystanders and for assessing the effects of NO diffusing from the former to the latter [13, 14]. In this chapter, the authors describe some in vitro experimental approaches that can be used to (1) determine iNOS/NO status in tumor cells exposed to PDT-like conditions, (2) assess the role of NO in possible resistance to photokilling or enhanced aggressiveness of surviving cells, and (3) detect changes in iNOS status and growth/migration rate of bystander cells. Two human prostate cancer lines (PC3 and DU145) are used for illustrating the methodology.

2

Materials

2.1 Reagents and Antibodies

1. Stock solutions of the following reagents were prepared as described [5–9, 12–14]: pro-sensitizer ALA, iNOS inhibitor 1400W (N-[3-aminomethyl)benzyl]acetamidine), NO scavenger cPTIO (2-(4-carboxyphenyl)-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide), NO probe DAF-2DA (4-aminofluorescein diacetate), and MTT (3-(4,5-dimethylthiazolyl-2yl)-2,5-diphenyl tetrazolium bromide) for viable cell determinations. Rabbit-derived primary antibodies against human iNOS and β-actin, along with peroxidase-conjugated secondary antibodies and materials for cell recovery and Western blot analyses (trypsin, lysis buffers, protease inhibitors, acrylamide, bis-acrylamide), are obtained from conventional suppliers [5– 9, 12–14].

In Vitro Models for Assessing Nitric Oxide’s Anti-PDT Effects

2.2 Cell Culture Analyses

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1. Human prostate carcinoma PC3 and DU145 cells are cultured in DMEM/F12 medium supplemented with 10% fetal bovine serum (FBS) and antibiotics, using 35 or 100 mm dishes, standard culture conditions [5–9] with passage every third day, and fewer than 6 passages. 2. Instrumentation and reagents for SDS-PAGE, immunoblotting on PVDF membranes, chemiluminescence detection, and image analysis software (e.g., ImageJ). 3. Detection of NO: Confocal fluorescence microscope, capable of performing 495 nm excitation and detecting 515 nm fluorescence emission. 4. Cytotoxicity and proliferation assays: Multi-plate reader, capable of measuring absorbance at 563 nm. 5. Migration assay: Phase-contrast or bright-field microscope equipped with CCD camera, image analysis software (e.g., ImageJ). 6. Invasion assay: 96-Well trans-well plates, cell scrapers, phasecontrast or bright-field microscope equipped with CCD camera, image analysis software (e.g., ImageJ), and a multi-plate reader, capable of measuring absorbance at 563 nm.

2.3 Bystander Model Supplies

1. Impermeable silicone-rimmed flexi-Perm® conA rings (12 mm bottom diameter) are used for separating bystander cells from PDT-targeted cells [13]. 2. These rings can be used repeatedly after cleaning and sterilization according to supplier recommendations.

3

Methods

3.1 Cell Sensitization and Irradiation

1. PC3 or DU145 cells at ~40% confluency in phenol red- and serum-free medium are metabolically sensitized with PpIX by incubating with 1.0 mM ALA for 30 min in the dark at 37
C. When 1400W or cPTIO was used, it was introduced from a stock solution in PBS 30 min before ALA and maintained at the same concentration throughout, i.e., 25–50 μM for either agent. 2. After ALA treatment, switch cells to fresh medium without ALA and irradiate on a translucent plastic platform over a bank of cool white fluorescent or LED lamps [5–9, 13]. Light fluence rate at culture dish bottoms is typically 10–12 W/m2, as measured with a YSI radiometer, so 15-min irradiation corresponds to a light fluence of ~1 J/cm2. Immediately after irradiation, switch cells to 10% FBS-containing medium lacking (controls) or containing 1400W or cPTIO, and then return cells to the incubator.

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3. At various postirradiation times, beginning immediately (0 h) and extending to 24 h, cell samples are taken for various determinations (below). 4. Cells exposed to light alone (light controls) or ALA alone (dark controls) are prepared and analyzed in parallel. 3.2 Western Blot Analyses

1. Prepare cell lysates as described [5, 6], determine total protein concentration, and then analyze by Laemmli SDS-PAGE, using 15% acrylamide/bis-acrylamide (37.5:1 w/w) and a uniform total protein load per lane, e.g., 100 μg. 2. Transfer separated proteins electrophoretically to a PVDF membrane. 3. Incubate membrane with the primary antibody against iNOS (~130 kDa), followed by a peroxidase-conjugated IgG secondary antibody. Supplier-suggested dilutions of stock antibody solutions are as follows: iNOS (1:250), β-actin (1:2000), and secondary (1:5000). 4. Repeat step 3 with an antibody against β-actin, which serves as an internal loading standard. 5. Visualize bands using a chemiluminescence-based system [5–9] and quantify band intensity using the online Image-J program (Fig. 1a).

3.3 Detection of Cellular NO

1. Prepare a stock solution of 1 mM DAF-2DA in DMSO immediately before experimental use and keep in the dark. 2. At various postirradiation times, cells in 35 mm dishes are switched to serum-free medium and incubated with 20 μM DAF-2DA for 30 min in the dark. 3. After washing, analyze cells for DAF-2-triazole fluorescence by fluorescence microscopy using 495 nm excitation and 515 nm emission [6] (Fig. 2) (see Note 1).

3.4 Evaluation of Cell Photokilling and NOMediated Resistance

1. After increasing times of post-ALA/light-dark incubation out to 24 h, determine the viable cell fraction by MTT assay [8, 9]. Remove medium from each 35 mm dish and replace with fresh medium containing 0.5 mg MTT/mL. After 4–6 h of incubation at 37
C, solubilize cells in 1 mL of isopropanol and then measure formazan absorbance at 563 nm as an indicator of viable cell amount. 2. Express values relative to those of ALA-only or light-only controls. 3. For cells irradiated in the presence of 1400W or cPTIO, assess the extent of iNOS/NO-mediated cytoprotection by showing greater viability loss when either of these agents is present (Fig. 1b) (see Note 2).

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Fig. 1 Pro-survival and pro-growth effects of upregulated iNOS/NO in PC3 cells after an ALA/light challenge. Panel (a) Western blot shows iNOS levels at various postirradiation times, beginning immediately (0 h) and extending to 20 h. The dark control (DC) represents nonirradiated ALA-treated cells. Numbers at bottom represent iNOS band intensities relative to β-actin and normalized to DC. Panel (b) shows MTT-assessed survival of PC3 cells over 24 h after ALA/light treatment, followed by proliferation of surviving cells. The mitigating effects of inhibiting iNOS with 1400W (25 μM) or scavenging NO with cPTIO (25 μM) are shown in each case

Fig. 2 Imaging of iNOS-generated NO in ALA/light-challenged PC3 cells. ALA-treated PC3 cells were either not irradiated (DC) or irradiated in the absence (ALA/hν) or presence (ALA/W/hν) of 1400W (25 μM). After 22 h of dark incubation, followed by 30 min with DAF-2DA (20 μM), cells were examined by fluorescence microscopy. Numbers below images represent integrated fluorescence intensities: mean  SD of values from 3 viewing fields. Bar: 200 μm

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3.5 iNOS/NO Effects on Surviving Cell Proliferation

1. Twenty-four hours after irradiation, remove medium, wash cells once, overlay with 10% FBS-containing medium, and return to the incubator. 2. At increasing time intervals up to 72 h, remove medium from each dish and carry out MTT assay as described in Subheading 3.4, formazan absorbance at 563 nm serving as a measure of viable proliferating cells. 3. For cells irradiated in the presence of 1400W or cPTIO, determine the extent of iNOS/NO-stimulated proliferation by measuring the degree of slowdown in the presence of 1400W or cPTIO (Fig. 1b) (see Note 3).

3.6 Effects of iNOS/ NO on Migration of Surviving Cells

1. Prepare for a gap closure or “wound healing” assay, which measures migratory cell departure from the general monolayer population. 2. Seed PC3 or DU145 cells in 35 mm dishes and allow them to proliferate to at least 90% confluency. 3. Sensitize with Subheading 3.1.

ALA-induced

PpIX

as

described

in

4. Generate a linear scratch midway across the cell monolayer using a sterile 200 μL pipette tip. 5. Photograph and measure gap zones before and after irradiation in the absence vs. presence of 1400W or cPTIO, using a suitable microscope with attached camera and appropriate software [9, 12]. 6. Prepare ALA-only or light-only controls and monitor similarly over the same time frames. 7. Calculate the percent of gap closure using the following equation: 100  [time-0 gap  time-t gap]/time-0 gap. 8. Prepare at least four replicates for each experimental condition. 3.7 Effects of iNOS/ NO on Surviving Cell Invasiveness

1. A multiple well device is preferred for measuring cell invasiveness, e.g., a 96-place trans-well unit [9]. 2. Grow PC3 or DU145 cells to ~60% confluency in 10 cm dishes. 3. Prepare chambers by adding 225 μL of 10% FBS-containing medium to each lower well, the FBS subsequently serving as a chemoattractant. 4. Insert a Matrigel-infused polycarbonate filter with 8 μm pores over each lower well and place the entire unit into a 37
C incubator. 5. Incubate cells with ALA in the dark and then irradiate as described in Subheading 3.1, either excluding (controls) or

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Fig. 3 NO-mediated hyper-invasiveness of PC3 cells that survive ALA/light treatment. Immediately after ALA treatment and irradiation (1 J/cm2) in the absence vs. presence of 1400W, cells in serum-free medium were tested for invasiveness using a Neuro-Probe trans-well system. Control cells (ALA alone) were examined alongside. Cells traversing filter inserts in response to 10% FBS-containing medium in lower chambers were recovered, stained, and quantified. (a) Scheme showing assay steps. (b) Extent of invasion over 48 h: mean  SE (n ¼ 3). *P < 0.01 vs. ALA; **P < 0.05 vs. ALA/hν

including 1400W or cPTIO to test for NO involvement in any enhanced invasiveness. 6. Twenty-four hours after irradiation, wash cells, gently scrape attached ones into serum-free medium, slowly layer into upper wells of invasion chambers (225 μL per well), and return the unit to the incubator. 7. After a given incubation time up to 48 h, gently remove medium in upper wells by aspiration and using a cotton-tipped swab, gently wipe off cells remaining on top of each filter. 8. Detach cells that had traversed the filters by centrifuging into 10% FBS-containing medium (400  g for 10 min); see Fig. 3a for the schematic of the entire procedure. 9. Allow recovered cells to adhere (~6-h incubation), then photograph, and quantify by MTT assay (Fig. 3b). 3.8 Evaluation of PDT Bystander Effects and NO Involvement

1. A novel approach is used involving impermeable silicone-based rings, which allow PDT-targeted cells to be distinguished from non-targeted bystanders [13]. 2. With 2 or 3 rings attached on a 135 mm culture dish (Fig. 4a), seed ~5  106 target cells (outside rings) and ~5  103 bystanders per ring (inside), using 10% FBS-containing medium.

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Fig. 4 Stimulation of bystander cell proliferation and migration by NO diffusing from PDT-targeted PC3 cells. (a) Culture dish arrangement showing stained PC3 cells before (a) and after (b) removal of the two rings separating target and bystander cells. Width of cell-free space after ring removal is ~4 mm. (b) Accelerated bystander cell proliferation after target cell ALA/light stress: inhibition by 1400W. (c) Accelerated bystander migration after target cell ALA/light stress: prevention by 1400W. *P < 0.05; **P < 0.01

3. After 24 h or ~70% target cell confluency, switch the latter to serum-free medium, sensitize with ALA-induced PpIX (Subheading 3.1), and irradiate the entire dish in the absence vs. presence of 1400W or cPTIO in the target compartment (see Note 4). 4. After ~2 h or postirradiation incubation, carefully remove rings, aspirate the medium, and replace with 10 mL of 10% FBS medium ( 1400W or cPTIO), which now overlays all cells. 5. Return cells to the incubator and hold there for increasing periods up to 48 h. 6. At various times, recover cells from the targeted and bystander populations for determination of iNOS status by Western blotting (Subheading 3.2), cell proliferation rate by MTT assay (Subheading 3.5) (Fig. 4b), and cell migration by gap closure assay (Subheading 3.6) (Fig. 4c). 7. Special care is required in recovering cells from the relatively small bystander compartments [13, 14] (see Notes 5 and 6).

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8. Use conditioned medium from targeted cells to determine whether danger-associated molecular patterns (DAMPs) [15] that are longer-lived than NO (see Note 2), e.g., certain cytokines, might contribute to bystander effects [13]. After PDT, switch all cells to FBS-containing medium; 5–6 h later, remove bystander medium and replace with conditioned medium from targeted cells, using medium from nonirradiated cells as a control. Track bystander responses (proliferation, migration) over the next 36–48 h.

4

Notes 1. DAF-2DA enters cells and is hydrolyzed to weakly fluorescent DAF-2, which is trapped inside. NO itself does not react with DAF-2, but rather NO-derived N2O3, which nitrosates the probe to highly fluorescent DAF-2-triazole [16, 17]. 2. NO is a short-lived free radical with a lifetime of 1–2 s in H2O [18]. Consequently, it must be continually generated by iNOS to be effective in pro-survival signaling of cancer cells. 1400W (a competitive inhibitor of iNOS enzyme) and cPTIO (a NO trap) should be maintained at the suggested (noncytotoxic) concentrations before, during, and after irradiation of photosensitized cells. At these concentrations, neither agent absorbs visible light to any significant extent, so interference with PpIX excitation should be minimal. 3. If NO produced by PDT-upregulated iNOS stimulates cell proliferation, 1400W and cPTIO should suppress this response, and also migration and invasion. However, the opposite would transpire for cell photokilling, i.e., if NO enhances resistance, 1400W and cPTIO should weaken this response, leading to greater photokilling. 4. Broadband visible irradiation of the entire culture dish, including non-sensitized cells in the bystander compartments, should have no significant effect on the latter, based on demonstrated negative effects with light controls [5–9, 12, 13]. Consequently, only the sensitized target cells should be affected when the entire dish is irradiated. 5. The rings enclosing bystander cells and separating them from targeted cells need to be removed very carefully at some selected postirradiation time (e.g., 2–3 h) so as to maintain the ~4 mm gap separating the targeted and bystander cells (Fig. 4a). It is crucial that the compartments be kept distinct and that any bystander contamination with much more abundant targeted cells be kept at a bare minimum.

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6. The preferred way to recover bystander cells is to first carefully remove all the targeted counterparts by scraping toward the culture dish periphery and away from the bystander domains. Then the bystanders can be safely removed by collecting into a small volume of medium (e.g., 25 μL) for different analyses (Subheadings 3.2, 3.5–3.7). Since bystander contents per ring are relatively low, combining cells from 2–3 rings in any given experiment is advised.

Acknowledgments Studies in the authors’ laboratory were supported by NIH/NCI Grant CA70823, a grant from the Wisconsin Breast Cancer Showhouse for a Cure, and a grant from the Advancing a Healthier Wisconsin Endowment. Jerzy Bazak and Witold Korytowski at the Jagiellonian University, Krakow, Poland, are gratefully acknowledged for their groundbreaking contributions to the PDT bystander studies. References 1. Dougherty TJ, Gomer CJ, Henderson BW, Jori G, Kessel D, Korbelik M, Moan J, Peng J (1998) Photodynamic therapy. J Natl Cancer Inst 90:889–905 2. Agostinis P, Berg K, Cengel KA, Foster TH, Girotti AW, Gollnick SO et al (2011) Photodynamic therapy of cancer: an update. CA Cancer J Clin 61:250–281 3. Henderson BW, Sitnik-Busch TM, Vaughan LA (1999) Potentiation of photodynamic therapy antitumor activity in mice by nitric oxide synthase inhibition is fluence rate dependent. Photochem Photobiol 70:64–71 4. Korbelik M, Parkins CS, Shibuya H, Cecic I, Stratford MR, Chaplin DJ (2000) Nitric oxide production by tumour tissue: impact on the response to photodynamic therapy. Br J Cancer 82:1835–1843 5. Bhowmick R, Girotti AW (2010) Cytoprotective induction of nitric oxide synthase in a cellular model of 5-aminolevulinic acid-based photodynamic therapy. Free Radic Biol Med 48:1296–1301 6. Bhowmick R, Girotti AW (2011) Rapid upregulation of cytoprotective nitric oxide in breast tumor cells subjected to a photodynamic therapy-like oxidative challenge. Photochem Photobiol 87:378–386 7. Bhowmick R, Girotti AW (2013) Cytoprotective signaling associated with nitric oxide upregulation in tumor cells subjected to

photodynamic therapy-like oxidative stress. Free Radic Biol Med 57:39–48 8. Bhowmick R, Girotti AW (2014) Pro-survival and pro-growth effects of stress-induced nitric oxide in a prostate cancer photodynamic therapy model. Cancer Lett 343:115–122 9. Fahey JM, Girotti AW (2015) Accelerated migration and invasion of prostate cancer cells after a photodynamic therapy-like challenge: role of nitric oxide. Nitric Oxide 49:47–55 10. Girotti AW, Fahey JM, Korytowski W (2016) Multiple means by which nitric oxide can antagonize photodynamic therapy. Curr Med Chem 23:2754–2769 11. Girotti AW (2016) Modulation of the antitumor efficacy of photodynamic therapy by nitric oxide. Cancers (Basel) 8(10):E96 12. Fahey JM, Girotti AW (2017) Nitric oxidemediated resistance to photodynamic therapy in a human breast tumor xenograft model: improved outcome with NOS2 inhibitors. Nitric Oxide 62:52–61 13. Bazak J, Fahey JM, Wawak K, Korytowski W, Girotti AW (2017) Enhanced aggressiveness of bystander cells in an anti-tumor photodynamic therapy model: role of nitric oxide produced by targeted cells. Free Radic Biol Med 102: 111–121 14. Bazak J, Fahey JM, Wawak K, Korytowski W, Girotti AW (2017) Bystander effects of nitric

In Vitro Models for Assessing Nitric Oxide’s Anti-PDT Effects oxide in anti-tumor photodynamic therapy. Cancer Cell Microenviron 4(1):e1511. https://doi.org/10.14800/ccm.1511 15. Garg AD, Krysko DV, Vandenabeele P, Agostinis P (2011) DAMPs and PDT-mediated photo-oxidative stress: exploring the unknown. Photochem Photobiol Sci 10:670–680 16. Nagano T (2009) Bioimaging probes for reactive oxygen species and reactive nitrogen species. J Clin Biochem Nutr 45:111–124

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17. Lancaster JR Jr (2010) The use of diaminofluorescein for nitric oxide detection: conceptual and methodological distinction between NO and nitrosation. Free Radic Biol Med 49: 1145 18. Thomas DD, Liu X, Kantrow SP, Lancaster JR Jr (2001) The biological lifetime of nitric oxide: implications for the perivascular dynamics of NO and O2. Proc Natl Acad Sci U S A 98:355–360

Chapter 3 Microtumor Models as a Preclinical Investigational Platform for Photodynamic Therapy Mans Broekgaarden and Jean-Luc Coll Abstract Classic preclinical investigations on the mechanisms and effects of photodynamic therapy (PDT) are typically performed in two-dimensional cell cultures that have some, albeit limited, relevance to cancer biology. Bioengineered three-dimensional (3D) culture models of cancer are gaining traction in translational oncology as microtumors recapitulate the tumor architectures and cellular heterogeneity more faithfully than conventional 2D cultures. These 3D models bridge a gap between highly relevant but low-throughput in vivo animal models and high-throughput two-dimensional cultures with low clinical relevance, and thus hold promise as preclinical testing platforms in PDT research. Here, we discuss the potential applications of organotypic cancer models for PDT research and provide two well-established methodologies for generating 3D cultures of cancer: a liquid-suspended spheroid model and an adherent microtumor culture model grown on extracellular matrix scaffolds. Particular emphasis is given to harvesting the cultures for the purpose of immunoblotting and flow cytometry. Key words Ultra-low adhesion 3D culture models, Bioengineering, Biomaterials, Spheroid, Oncology, Experimental therapies, Translational research, Cancer therapy, Chemotherapy, Phototherapy, Flow cytometry, Immunoblotting

1

Introduction In the assessment of new cancer therapeutic and treatment strategies, preclinical models that resemble the clinical manifestation of cancer are essential to investigate the therapeutic mechanisms and predict their clinical efficacy [1]. Conventional in vitro models typically comprise cancer cell lines that are grown as monolayers. Although these two-dimensional cancer cultures permit rapid and relatively inexpensive acquisition of data with high level of detail on a cellular and molecular level, the monolayer cultures bear little resemblance to the three-dimensional, heterogeneous, and architecturally complex tumor tissues that are formed during carcinogenesis in patients [2]. In this respect, animal models of cancer are more faithful to the clinical situation, but experiments are low

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_3, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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throughput, costly, and typically met with strong ethical considerations. Moreover, the dosimetry and treatment parameters that provide favorable results in vitro typically fail to achieve similar results in vivo, indicating a significant translational gap between the classic in vitro cultures and in vivo cancer models [3]. In this context, there has been an emerging interest in 3D culturing technologies as the in vitro microtumors act as an intermediate between monolayer cultures and in vivo cancer models. A plethora of culturing methodologies have been developed, ranging from highly specific disease models [4–6] to techniques that can be applied in a more universal manner to cancer-derived cells and cell lines [7–10]. Within the field of experimental oncology, 3D cultures of commercially available cell lines are useful models as they form heterogeneous aggregates on which new therapeutics can be assessed in a reproducible manner [11]. Alternatively, cancer organoid cultures derived from patient tissues are currently being explored to predict treatment responses in the clinic and inform the design of personalized treatment strategies [9, 10, 12]. A major benefit of organotypic models is that they retain the capacity for high-throughput screening of therapeutic efficacies, thereby allowing rapid assessment of the most effective doses and treatment regimens. To facilitate this, various recent studies have developed imaging-based methodologies for multiparametric assessment of treatment effects [13–15]. These studies demonstrated that treatment effects are not fully represented by a single parameter, and illustrate the power of microtumor culture models to assess therapeutic efficacies on a mesoscopic level. With respect to photodynamic therapy (PDT), organotypic 3D cancer models are highly informative tools to study drug uptake and optimize the PDT treatment parameters [16–18]. For example, Glidden et al. used pancreatic microtumors to characterize the perfusion of the photosensitizer benzoporphyrin derivative (BPD) into individual microtumors, and investigated the extent of BPD photobleaching following PDT, providing spatial profiles of photosensitizer uptake and cell killing to optimize the treatment parameters of PDT [18]. In addition, 3D cancer cultures have generated a wealth of information on the mechanisms and mesoscopic effects of PDT and PDT-based combination therapies [19, 20]. In ovarian microtumors, various investigators demonstrated heterogeneous tumor growth patterns following cancer therapies [13], investigated the therapeutic capacity of photoimmunoconjugates [21], and explored the mechanisms underlying the synergistic enhancement of carboplatin chemotherapy efficacy by combining it with BPD-PDT [22]. Pancreatic microtumors have been applied in investigations toward phenotypic differences between chemosensitive and chemoresistant microtumors and their individual susceptibilities to BPD-PDT [23]. In addition, it was demonstrated that neoadjuvant PDT significantly enhanced the

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efficacy of oxaliplatin in an organotypic model of metastatic pancreatic cancer, and demonstrated delayed effects of BPD-PDT [24]. Similar microtumor models of pancreatic cancer were used to evaluate the impact of cancer-associated fibroblasts and cancer therapies on cancer metabolism [25–27]. Lastly, microtumors of varying origins are also valuable for the design and optimization of novel nanoscale therapeutics for PDT [28–33], also termed photonanomedicines [34]. Taken together, organotypic cancer cultures can be exploited in PDT research to facilitate high-throughput screening of treatment effects, elucidate the effects of treatments on a mesoscopic level, optimize the dosimetry and treatment parameters of PDT, and ultimately guide the design and refinement of in vivo experiments for further investigations. Moreover, microtumor culturing technologies can be harnessed for high-throughput analysis of treatment effects, can be performed at relatively low costs, and are not hampered by the ethical constraints that are associated with in vivo experimentation. To promote the exploitation of microtumors in PDT research, methodologies to generate two distinct yet widely established 3D cancer cultures are provided in this communication. The first of these protocols establishes liquid-suspended microtumors by leveraging microplates coated with low-attachment surfactants (Subheadings 3.1–3.4). The second model is based on a liquid-overlay culture that utilizes hydrogels of extracellular matrix as a base for adherent microtumor growth [7] (Subheadings 3.5– 3.8). Both models can be harnessed to yield translationally relevant information in a reproducible and accessible manner.

2

Materials

2.1 Cell Lines and Culture Medium

1. For both medium-suspended spheroid microtumors and matrix-adherent microtumors, a variety of commercial cancer cell lines or primary cancer tissues can be used to initiate the cultures. Similar culture medium as used for monolayer cultures can be used for the culturing of the microtumors, and these will therefore not be specified further below. Careful optimization of culture media for primary cancer tissues may be required [1, 8–10].

2.2 Generating Suspended Spheroids

1. Ultralow attachment surface U-bottom plates, 96-well (Corning). See Note 1. 2. Sterile phosphate-buffered saline without Ca2+ and Mg2+ (PBS / ). 3. Gentle cell dissociation solution (e.g., dispase).

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2.3 Generating Adherent Microtumor Cultures

1. Black-walled 24-well plates. See Note 1. 2. Growth factor-reduced Matrigel (Corning). See Note 2. 3. An ice pack with a flat surface for cooling the 24-well plates. 4. Sterile PBS without calcium and magnesium (PBS

/

).

5. Gentle cell dissociation solution. 6. 50 mL Centrifuge tubes. 2.4 Materials for Performing PDT

1. A photosensitizer of choice. 2. An excitation light source that corresponds to the photosensitizer’s absorption peak. 3. A power meter to adjust the light source output irradiance.

2.5 Sample Preparation for Immunoblotting

1. Wide-orifice 200 μL pipette tips. For suspended spheroids only. 2. Cell recovery solution microtumors only. 3. Sterile PBS

/

(Corning).

For

adherent

.

4. Sterile PBS with Ca2+ and Mg2+ (PBS+/+). 5. RIPA lysis buffer, supplemented with protease and phosphatase inhibitors. 6. Protein quantification assay kit. 2.6 Flow Cytometry Sample Preparation

1. Gentle cell dissociation solution (e.g., dispase; it is not recommended to use trypsin, as many cell surface markers are cleaved by this protease). 2. PBS+/+. 3. Centrifuge tubes, 15 mL. 4. Flow cytometry test tubes with cell strainer caps. 5. Ethanol 96%,

20  C.

6. Optional: Antibody diluent.

3

Methods

3.1 Generating Suspended Spheroids

1. From a near-confluent 75 cm2 culture flask, harvest cancer cells by washing with 5 mL PBS / and incubating for 5–10 min with 2 mL cell dissociation solution at 37  C. Dilute the cell suspension to a concentration of 5  104 cells/mL. Prepare the appropriate volume of cell suspension in accordance to the number of wells or plates required for the experiments, using 100 μL/well. See Note 3. 2. Transfer 100 μL cell suspension, i.e., 5  103 cells, in each well, and incubate at standard culture conditions (5% CO2, 37  C) for at least 24 h to facilitate spheroid formation. See also Note 4.

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3. Cultures may be kept for up to 2 weeks when medium is refreshed every 3 days. To do so, 100 μL of culture medium is carefully added to the cultures, after which 100 μL (a mix of old and fresh medium) is immediately removed and discarded. During medium addition, the pipette tip should be placed on the walls of the individual wells and slowly added to the spheroids. Do not mix the culture media by pipetting up and down in the well as this may disrupt the spheroids. Upon removing, take care not to place the pipette too deep in the wells to prevent disturbing the spheroids. Also take care not to aspirate the spheroids while removing and discarding the medium from the wells. 3.2 Treatment of Suspended Spheroid Cultures with PDT

1. On the day of treatment, dim the lights in the culture room(s)/ cell culture hood to the minimum amount necessary to handle the cultures. High levels of ambient light may cause unwanted phototoxicity in the cultures or bleach the photosensitizers prior to PDT. 2. Prepare a 2X solution of the desired photosensitizer concentration(s) in complete culture medium. For example, if the final concentration of your photosensitizer in the wells should be 1 μM, prepare a 2 μM solution. Bring the volume of each well to 100 μL. Add 100 μL of photosensitizer solution to the cell culture medium already in the wells. 3. Incubate the spheroids for the desired photosensitizer-light interval to facilitate cellular uptake and drug diffusion into the spheroids. Optional: Excess photosensitizers may be removed by repetitive addition and removal of 100 μL culture medium for at least three times. However, note that it is challenging to completely remove the photosensitizer from the culture medium and that the spheroids can be easily disrupted. 4. Irradiate the spheroids with laser light that corresponds to the photosensitizer’s absorption peak. For 96-well plates, 4 wells may be irradiated at the same time, and the spot size should be adjusted appropriately. See also Note 5. 5. Following PDT, place the cultures back in standard culture conditions. 6. When desired, the treatment effects on these cultures can be assessed with various methods as described in Note 6 and the references therein. Otherwise, the cultures may be processed for protein isolation or flow cytometry as described in Subheadings 3.3 and 3.4.

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3.3 Harvesting Suspended Spheroids for Immunoblotting

1. To obtain a sufficient amount of protein from the cultures, plan on pooling 8–16 spheroids as a single lysate. Please note that protein yields for control groups may be higher compared to protein yields for the treatment groups. Consider performing a pilot experiment to accurately determine the protein yields and the amount of wells that need to be pooled to achieve the desired amount of protein. See also Note 7. 2. Use a 20–200 μL pipette in combination with the wide-orifice pipette tips to transfer the full contents of the wells to a 15 mL centrifuge tube. Perform visual checks during the pipetting procedure to determine whether the aspirated spheroids are indeed in the pipette tip. 3. Centrifuge the tubes containing the pooled spheroids for 5 min at 500  g and 4  C. Aspirate culture medium and wash the spheroid pellet once with 5 mL PBS+/+. Repeat the centrifugation. 4. Aspirate the PBS from the spheroid pellet and lyse the spheroids in 200 μL of ice-cold, fully supplemented RIPA buffer. 5. Incubate on ice and vortex rigorously every 30 min for a duration of 1-4 h, or until the pellet is fully dissolved. Lyse the spheroid samples on ice. Store the lysates at 80  C until further use. 6. Perform a protein quantification assay to determine the protein yields. Proceed with the appropriate immunoblotting protocol for the proteins of interest.

3.4 Harvesting Suspended Spheroids for Flow Cytometry

1. To obtain a sufficient number of cells from the cultures, plan on pooling 8–16 spheroids as a single sample. Cell numbers for control groups may be higher compared to cell numbers for the treatment groups. See also Note 8. 2. Use a 20–200 μL pipette in combination with the wide-orifice pipette tips to transfer the full contents of the wells to a 15 mL centrifuge tube. Perform a visual check during the pipetting procedure to determine whether the spheroids are indeed in the pipette tip. 3. Centrifuge the tubes containing the pooled spheroids for 5 min at 500  g and 4  C. Aspirate culture medium and wash the spheroid pellet once with 5 mL PBS / . Repeat the centrifugation. 4. Aspirate the PBS and gently resuspend the spheroid pellet in 1 mL gentle cell dissociation solution for 10 min at room temperature. 5. Add 5 mL fresh culture medium and centrifuge the tubes for 5 min at 500  g and 4  C. Aspirate the cell dissociation solution and culture medium and resuspend the cell pellet in 300 μL PBS+/+. Keep cells on ice.

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6. Optional: Cells can be fixed at this point, by slowly adding 700 μL ethanol ( 20  C) to the cells while very gently swerving the cell suspensions on a vortex. Note that this step permeabilizes the cell membranes, but that cells can be stored at 20  C for up to 4 weeks. Otherwise this step can be skipped and the suspensions can be processed immediately for staining and flow cytometry on the same day. 7. Prior to analysis with flow cytometry, add 9 mL of PBS+/+ to each tube and centrifuge the tubes for 5 min at 500  g and 4  C. Remove the supernatant and gently resuspend the cell pellets in minimum 100 μL of PBS+/+, or antibody diluent. See also Note 9. 8. Add the desired concentration of dyes or antibodies to the cell suspensions and incubate for the appropriate amount of time in accordance to the manufacturer’s recommendations. Supplement the cell suspensions with additional PBS+/+ or antibody diluent to achieve a total volume of at least 300 μL. 9. To remove large cell clusters that may not have been dissociated completely, carefully transfer the contents of the centrifuge tubes to the cell strainer caps of the flow cytometry tubes. If necessary, gently tap the bottom of the tubes on a hard surface to facilitate the passage of the sample through the strainer. Large cell clusters may block the capillary of the flow cytometer. 10. Perform flow cytometry as desired. 3.5 Generating Adherent Microtumor Cultures

1. On the day prior to microtumor culture initiation, start the thawing procedure for the Matrigel. Determine how much Matrigel is required for the desired experiment. For a single 24-well plate, a volume of 6 mL Matrigel is required, but additional Matrigel is needed to supplement the culture medium. As a rule of thumb, count 1 vial for a single plate, 2 vials for 2–3 plates, 3 vials for 4–5 plates, etc. Place the vial (s) of Matrigel on ice in a Styrofoam box, and let the gel thaw overnight at 4  C by placing the Styrofoam box in a refrigerator or cold room. 2. On the day of microtumor culture initiation, prepare the culture hood by collecting the plates, ice packs, pipettes, and pipette tips. Prepare 4 additional 50 mL tubes to store the remainder of Matrigel. 3. Take the Styrofoam box with Matrigel from the refrigerator/ cold room. Keep the Matrigel on ice at all times; if not, the gel will irreversibly solidify. Sterilize the box with 70% ethanol and place in the culture hood.

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4. Take the flat-surface ice pack from the freezer ( 20  C), disinfect, and transfer to culture hood. Place the 24-well plate on the ice pack and let it cool down for several seconds. 5. Keep the plate on the ice pack at all times. Carefully transfer 250 μL of ice-cold Matrigel in every well of the 24-well plate. Place the lid back on top of the plate, and inspect the plate carefully to ensure that the Matrigel is dispersed evenly over the surface of the wells. Rock the plates very gently to distribute the Matrigel over uncovered patches of surface. It is critical to avoid air bubbles in the Matrigel. 6. Place the 24-well plates containing the Matrigel at 37  C (e.g., culture incubator) for 20 min. This delay will be enough to achieve solidification of the hydrogels without letting them dry out. 7. During the incubation time, prepare a 50 mL centrifuge tube with 2 mL unused Matrigel. Add 48 mL of fully supplemented culture medium and mix well. Label the tube as “culture medium with 4% Matrigel.” 8. The remainder of the unused Matrigel can be stored as aliquots of 1 mL in sterile ice-cold 50 mL tubes. These aliquots can be used as supplements to the culture medium, which needs to be refreshed every 3–4 days (see step 13 below). Keep these on ice at all times and store at 20  C. 9. Following the 20-min incubation, take the 24-well plates with the solidified Matrigel out of the incubator, and gently add 0.5 mL of culture medium with 4% Matrigel. The plates can now be kept at room temperature for cell seeding. 10. From a near-confluent 75 cm2 culture flask, harvest cancer cells by washing with 5 mL PBS / and incubating for 5–10 min with 2 mL cell dissociation solution at 37  C. Add culture medium and harvest the cells, count them, and dilute the cell suspension to a concentration of 1.5  104 cells/mL (please note that other cell densities may be used, and it is likely dependent on the cell type and length of the experiment). Prepare the appropriate volume of cell suspension in accordance to the number of wells or plates required for the experiments, using 0.5 mL cell suspension/well. 11. Gently add 0.5 mL cell suspension in every well. Note that the cell suspension will be diluted 1:1 in the culture medium with 4% Matrigel. The final dilutions in the wells will thus be 7.5  103 cells/well in the medium containing 2% Matrigel. 12. Incubate the plates at standard culture conditions for at least 7 days to establish mature microtumor cultures. 13. Culture medium should be refreshed every 3–4 days, and every 2–3 days from day 10 onwards to prevent substantial medium

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acidification and nutrient depletion. To do so, take out a frozen aliquot of 1 mL Matrigel (step 9 of this protocol). Then add 49 mL of fully supplemented warm culture medium and rigorously dissolve the frozen Matrigel. Label the tube as “culture medium with 2% Matrigel.” Carefully aspirate the old medium from the microtumor cultures, making sure not to disturb the microtumors or the solidified Matrigel scaffolds with the pipette tip. Then, gently add the freshly prepared culture medium with 2% Matrigel. Unused culture medium containing Matrigel can be stored for up to 2 weeks in the fridge or cold room. 3.6 Treatment of Adherent Microtumor Cultures with PDT

1. On the day of treatment, dim the lights in the culture room(s)/ cell culture hood to the minimum amount of light necessary to handle the cultures. High levels of ambient light may cause unwanted phototoxicity in the cultures or bleach the photosensitizers prior to PDT. 2. Prepare a solution with the desired photosensitizer concentration(s) in complete culture medium. See also Note 5. Prepare a sufficient volume that corresponds to 1 mL per well. Remove culture medium and replace with photosensitizersupplemented medium. In the control wells, replace the culture medium with fresh medium devoid of photosensitizer. 3. Incubate the microtumors for the desired photosensitizer-light interval to facilitate cellular uptake and drug diffusion into the microtumors. Subsequently, the photosensitizer-containing medium can be removed from the cultures and replaced by fresh culture medium supplemented with 2% Matrigel. Also refresh medium in the control wells with 2% Matrigelsupplemented medium. See also Note 10. 4. Irradiate the microtumor cultures with laser light that corresponds to the photosensitizer’s absorption peak. For 24-well plates, irradiate each well individually. See Note 3. 5. Following PDT, place the cultures back in the standard culture conditions. 6. When desired, the treatment effects on these cultures can be assessed with various methods as described in Note 6 and the references therein. Otherwise, the cultures may be processed for protein isolation or flow cytometry as described in Subheadings 3.7 and 3.8.

3.7 Harvesting Adherent Microtumors for Immunoblotting

1. For adherent cultures in 24-well plates, a single well is typically sufficient to run multiple immunoblots. Plan the experiment accordingly.

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2. Prepare 1000 μL pipette tips and use scissors to cut 2/3 mm off the tip, creating a large-orifice (non-sterile) pipette tip. Create a tip for each individual sample. 3. Place the microtumor culture plates on ice or perform the procedure in a cold room (4  C). Aspirate the culture medium. Using a normal pipette tip, add 1 mL of cell recovery solution to each well to digest the Matrigel. 4. Using the large-orifice 1000 μL pipette tips, briefly mix the Matrigel and cell recovery solution with the pipette tip to detach the gel from the plate. Transfer the contents of each well to a 15 mL centrifuge tube. 5. Place the tubes on ice in the cold room or refrigerator. Mix by inverting the tube every 10–15 min for a duration of 2 h or longer, until the Matrigel is completely dissolved and the microtumors are settling on the bottom of the tubes. See also Note 11. 6. Centrifuge the tubes containing the microtumors for 5 min at 500  g and 4  C, remove the supernatant, wash twice with 5 mL ice-cold PBS+/+, and repeat the centrifugation. 7. Remove the supernatant, and lyse the microtumors in 200 μL fully supplemented RIPA buffer. Place directly on ice. 8. Incubate on ice and vortex rigorously every 30 min for a duration of 1–4 h, or until the pellet is fully dissolved. Lyse the microtumor samples on ice. Store the lysates at 80  C until further use. 9. Perform a protein quantification assay to determine the protein yields. Proceed with the appropriate immunoblotting protocol for the proteins of interest. 3.8 Harvesting Adherent Microtumors for Flow Cytometry

1. For adherent cultures in 24-well plates, a single well will yield sufficient cells for flow cytometry. 2. Repeat steps 2–6 from Subheading 3.7, thus obtaining 15 mL centrifuge tubes with washed and pelleted microtumors. 3. Aspirate the supernatant and gently resuspend the microtumor pellet in 1 mL gentle cell dissociation solution for 10 min at room temperature. 4. Add 5 mL fresh culture medium and centrifuge the tubes for 5 min at 500  g and 4  C. Aspirate the cell dissociation solution and culture medium and resuspend the cell pellet in 300 μL PBS+/+. Keep cells on ice. 5. Optional: Cells can be fixed at this point, by slowly adding 700 μL ethanol ( 20  C) to the cells while very gently swerving the cell suspensions on a vortex. Note that this step will permeabilize the cell membranes, but that cells can then be

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stored at 20  C for up to 4 weeks. Otherwise this step can be skipped and the suspensions can be processed immediately for staining and flow cytometry on the same day. 6. Prior to analysis with flow cytometry, add 9 mL of PBS+/+ to each tube and centrifuge the tubes for 5 min at 500  g and 4  C. Remove the supernatant and gently resuspend the cell pellets in minimum 100 μL of PBS+/+, or antibody diluent. See also Note 9. 7. Add the desired concentration of dyes or antibodies to the cell suspensions and incubate for the appropriate amount of time in accordance to the manufacturer’s recommendations. Supplement the cell suspensions with additional PBS+/+ or antibody diluent to achieve a total volume of at least 300 μL. 8. To remove large cell clusters that may not have been dissociated completely, carefully transfer the contents of the centrifuge tubes to the cell strainer caps of the flow cytometry tubes. If necessary, gently tap the bottom of the tubes on a hard surface to facilitate the passage of the sample through the strainer. Large cell clusters may block the capillary of the flow cytometer. 9. Perform flow cytometry as desired.

4

Notes 1. Preferentially, for PDT research, the multi-well plates should be black-walled to prevent unwanted scattering of photons between wells. Alternatively, the plates may be placed on a black surface to reduce the extent of light scattering. A sheet of black plastic or cardboard containing a perforation the size of 4 wells of a 96-well plate or a 1.9 cm2 round perforation for a single well of a 24-well plate may be used to prevent unwanted light contamination in neighboring wells during the PDT protocol. 2. The exact contents of Matrigel may vary from batch to batch. Specifically, variations in protein and endotoxin levels may cause deviations in experimental outcomes. It is recommended to keep track of the protein and endotoxin levels in the Matrigel batches, and communicate with the vendor when ordering new stocks of Matrigel to guide the selection of the new batches. It is also advised to specify the protein and endotoxin levels in scientific publications to promote the reproducibility of the findings by other investigators. 3. For suspended microtumors, a starting volume of 100 μL is also feasible, but larger volumes are not recommended to maintain sufficient space in the wells to allow refreshing of the

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culture medium and addition of investigational compounds. Although this protocol mentions the use of one cancer cell type per culture, various co-cultures can be initiated at this point by mixing different cell types at defined ratios. Alternatively, other cell types can be added at earlier or later time points during the culturing of the microtumors, as described in [15, 35]. 4. Microtumors typically form within 24 h. Note that microtumor cultures can differ quite dramatically in morphology and growth behavior in both suspended and adherent microtumor cultures, depending on the cell lines and cell types used to initiate these [11, 15, 18, 22, 23, 36]. It is recommended that a characterization of the cultures is performed when starting with any type of microtumor culture system. 5. The concentration of photosensitizer for PDT may differ dramatically. For benzoporphyrin derivative (a.k.a. verteporfin), a concentration of 0.25–1 μM may be used to achieve sufficient photosensitization. Typical irradiation parameters use a total radiant exposure of 5–100 J/cm2 with a power density of 50–500 mW/cm2. A power meter should always be used to confirm the light dosimetry. An automated shutter system or a manual timer may be used to time the exposure intervals. The plates can be shifted manually upon completion of the time intervals. More details on the PDT dosimetry and other treatment parameters can be appreciated in various previous publications [14–17, 36]. 6. Assessment of treatment effects in both suspended and adherent microtumor cultures can be performed using various noncommercial but accessible methodologies, including qVista [14], AnaSP [38], or CALYPSO [15]. Alternatively, commercial viability assessment kits may be used in some occasions, such as the CellTiter-Glo 3D (Promega) or Alamar Blue assay (Thermo Fisher Scientific) [39]. Caution should be applied to ensure that the assay components do not bind the components of the hydrogel matrices to cause erroneous results. 7. To obtain protein samples that have a sufficient concentration for two immunoblots, the suspended microtumors of 8–12 wells should be pooled as a single protein lysate. 8. Please note that in comparison to 2D cultures, cells obtained from 3D cultures may undergo substantial differentiation. For example, cells with a predominant epithelial phenotype in monolayers will lose certain epithelial expression markers when cultured in 3D. Cells may be subject to unsuccessful mitosis, resulting in unforeseen aberrations in cell cycle profiles [37]. Lastly, the dissociated cell suspensions typically contain many necrotic cells. However necrosis may be caused to some extent by the presence of necrotic cores in certain types of

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microtumors. Finally, it is likely that the dissociation protocol causes substantial cell death. 9. The lower the resuspension volume, the lower the required volume of antibody for sufficient staining. Doing this efficiently can significantly lower the cost of the experiments, as antibodies and dyes can be quite expensive. However, it is advised to keep the resuspension volumes 100 μL, as small residual volumes of PBS may not be effectively removed during aspiration of the supernatant, which may cause the antibody dilutions to be rather inaccurate and lead to large deviations in the results. 10. Try to keep the time interval between removing the excess photosensitizer and the light irradiation to a minimum. Prolonged incubation in the absence of photosensitizer may result in significant photosensitizer efflux from the cells, leading to inaccurate evaluation of treatment efficacies. 11. This is an important step in the preparation of functional lysates and cell suspensions. In case the Matrigel is incompletely dissolved, the microtumors cannot be completely pelleted during centrifugation, leading to a substantial loss of sample. If the Matrigel cannot be dissolved within an acceptable timeframe (e.g., 1–2 h), consider adding more cell recovery solution to the tubes. References 1. Sachs N, Clevers H (2014) Organoid cultures for the analysis of cancer phenotypes. Curr Opin Genet Dev 24:68–73 2. Tanner K, Gottesman MM (2015) Beyond 3D culture models of cancer. Sci Transl Med 7: 283ps9 3. Pampaloni F, Reynaud EG, Stelzer EHK (2007) The third dimension bridges the gap between cell culture and live tissue. Nat Rev Mol Cell Biol 8:839–845 4. Clevers H (2016) Modeling development and disease with organoids. Cell 165:1586–1597 5. Rizvi I, Gurkan UA, Tasoglu S, Alagic N, Celli JP, Mensah LB, Mai Z, Demirci U, Hasan T (2013) Flow induces epithelial-mesenchymal transition, cellular heterogeneity and biomarker modulation in 3D ovarian cancer nodules. Proc Natl Acad Sci U S A 110: E1974–E1983 6. Li X, Nadauld L, Ootani A, Corney DC, Pai RK, Gevaert O, Cantrell MA, Rack PG, Neal JT, Chan CW-M et al (2014) Oncogenic transformation of diverse gastrointestinal tissues in primary organoid culture. Nat Med 20: 769–777

7. Lee GY, Kenny PA, Lee EH, Bissell MJ (2007) Three-dimensional culture models of normal and malignant breast epithelial cells. Nat Methods 4:359–365 8. Boj SF, Hwang C-I, Baker LA, Chio IIC, Engle DD, Corbo V, Jager M, Ponz-Sarvise M, Tiriac H, Spector MS et al (2015) Organoid models of human and mouse ductal pancreatic cancer. Cell 160:324–338 9. Sachs N, de Ligt J, Kopper O, Gogola E, Bounova G, Weeber F, Balgobind AV, Wind K, Gracanin A, Begthel H et al (2018) A living biobank of breast cancer organoids captures disease heterogeneity. Cell 172(1–2): 373–386.e10 10. van de Wetering M, Francies HE, Francis JM, Bounova G, Iorio F, Pronk A, van Houdt W, van Gorp J, Taylor-Weiner A, Kester L et al (2015) Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell 161:933–945 11. Vinci M, Gowan S, Boxall F, Patterson L, Zimmermann M, Court W, Lomas C, Mendiola M, Hardisson D, Eccles SA (2012) Advances in establishment and analysis of

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three-dimensional tumor spheroid-based functional assays for target validation and drug evaluation. BMC Biol 10:29 12. Weeber F, Ooft SN, Dijkstra KK, Voest EE (2017) Tumor organoids as a pre-clinical cancer model for drug discovery. Cell Chem Biol 24:1092–1100 13. Celli JP, Rizvi I, Evans CL, Abu-Yousif AO, Hasan T (2010) Quantitative imaging reveals heterogeneous growth dynamics and treatment-dependent residual tumor distributions in a three-dimensional ovarian cancer model. J Biomed Opt 15:051603 14. Celli JP, Rizvi I, Blanden AR, Massodi I, Glidden MD, Pogue BW, Hasan T (2014) An imaging-based platform for high-content, quantitative evaluation of therapeutic response in 3D tumour models. Sci Rep 4:3751 15. Bulin A-L, Broekgaarden M, Hasan T (2017) Comprehensive high-throughput image analysis for therapeutic efficacy of architecturally complex heterotypic organoids. Sci Rep 7: 16445 16. Rizvi I, Anbil S, Alagic N, Celli JP, Zheng LZ, Palanisami A, Glidden MD, Pogue BW, Hasan T (2013) PDT dose parameters impact tumoricidal durability and cell death pathways in a 3D ovarian cancer model. Photochem Photobiol 89:942–952 17. Anbil S, Rizvi I, Celli JP, Alagic N, Pogue BW, Hasan T (2013) Impact of treatment response metrics on photodynamic therapy planning and outcomes in a three-dimensional model of ovarian cancer. J Biomed Opt 18:098004 18. Glidden MD, Celli JP, Massodi I, Rizvi I, Pogue BW, Hasan T (2012) Image-based quantification of benzoporphyrin derivative uptake, localization, and Photobleaching in 3D tumor models, for optimization of PDT parameters. Theranostics 2:827–839 19. Kucinska M, Murias M, Nowak-Sliwinska P (2017) Beyond mouse cancer models: threedimensional human-relevant in vitro and non-mammalian in vivo models for photodynamic therapy. Mutat Res 773:242–262 20. Chudy M, Tokarska K, Jastrze˛bska E, Bułka M, Drozdek S, Lamch Ł, Wilk KA, Brzo´zka Z (2018) Lab-on-a-chip systems for photodynamic therapy investigations. Biosens Bioelectron 101:37–51 21. Rahmanzadeh R, Rai P, Celli JP, Rizvi I, BaronLu¨hr B, Gerdes J, Hasan T (2010) Ki-67 as a molecular target for therapy in an in vitro three-dimensional model for ovarian cancer. Cancer Res 70:9234–9242 22. Rizvi I, Celli JP, Evans CL, Abu-Yousif AO, Muzikansky A, Pogue BW, Finkelstein D,

Hasan T (2010) Synergistic enhancement of carboplatin efficacy with photodynamic therapy in a three-dimensional model for micrometastatic ovarian cancer. Cancer Res 70: 9319–9328 23. Cramer GM, Jones DP, El-Hamidi H, Celli JP (2017) ECM composition and rheology regulate growth, motility, and response to photodynamic therapy in 3D models of pancreatic ductal adenocarcinoma. Mol Cancer Res 15: 15–25 24. Broekgaarden M, Rizvi I, Bulin A-L, Petrovic L, Goldschmidt R, Celli JP, Hasan T (2018) Neoadjuvant photodynamic therapy augments immediate and prolonged oxaliplatin efficacy in metastatic pancreatic cancer organoids. Oncotarget 9:13009–13022 25. Broekgaarden M, Anbil S, Bulin A-L, Obaid G, Mai Z, Baglo Y, Rizvi I, Hasan T (2019) Modulation of redox metabolism negates cancerassociated fibroblasts-induced treatment resistance in a heterotypic 3D culture platform of pancreatic cancer. Biomaterials 222:119421 26. Broekgaarden M, Bulin A-L, Frederick J, Mai Z, Hasan T (2019) Tracking photodynamic- and chemotherapy-induced redox state perturbations in 3D culture models of pancreatic cancer: a tool for identifying therapyinduced metabolic changes. J Clin Med 8:1399 27. Bulin A-L, Broekgaarden M, Simeone D, Hasan T (2019) Low dose photodynamic therapy harmonizes with radiation therapy to induce beneficial effects on pancreatic heterocellular spheroids. Oncotarget 10:2625–2643 28. Mohammad-Hadi L, MacRobert AJ, Loizidou M, Yaghini E (2018) Photodynamic therapy in 3D cancer models and the utilisation of nanodelivery systems. Nanoscale 10: 1570–1581 29. Klein OJ, Yuan H, Nowell NH, Kaittanis C, Josephson L, Evans CL (2017) An integrintargeted, highly diffusive construct for photodynamic therapy. Sci Rep 7:13375 30. Kumari P, Jain S, Ghosh B, Zorin V, Biswas S (2017) Polylactide-based block copolymeric micelles loaded with chlorin e6 for photodynamic therapy: in vitro evaluation in monolayer and 3D spheroid models. Mol Pharm 14: 3789–3800 31. Flak D, Yate L, Nowaczyk G, Jurga S (2017) Hybrid ZnPc@TiO2 nanostructures for targeted photodynamic therapy, bioimaging and doxorubicin delivery. Mater Sci Eng C Mater Biol Appl 78:1072–1085 32. Chiarante N, Garcı´a Vior MC, Awruch J, Marino J, Roguin LP (2017) Phototoxic action of a zinc(II) phthalocyanine encapsulated into

Microtumor Models for PDT Research poloxamine polymeric micelles in 2D and 3D colon carcinoma cell cultures. J Photochem Photobiol B 170:140–151 33. Obaid G, Bano S, Mallidi S, Broekgaarden M, Kuriakose J, Silber Z, Bulin A-L, Wang Y, Mai Z, Jin W et al (2019) Impacting pancreatic cancer therapy in heterotypic in vitro organoids and in vivo tumors with specificity-tuned, NIR-activable photoimmunonanoconjugates: towards conquering desmoplasia? Nano Lett 19:7375–7387 34. Obaid G, Broekgaarden M, Bulin A-L, Huang H-C, Kuriakose J, Liu J, Hasan T (2016) Photonanomedicine: a convergence of photodynamic therapy and nanotechnology. Nanoscale 8:12471–12503 35. Celli JP (2012) Stromal interactions as regulators of tumor growth and therapeutic response: a potential target for photodynamic therapy? Isr J Chem 52:757–766 36. Broekgaarden M, Rizvi I, Bulin A-L, Petrovic L, Goldschmidt R, Celli JP, Hasan T,

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Broekgaarden M, Rizvi I, Bulin A-L et al (2018) Neoadjuvant photodynamic therapy augments immediate and prolonged oxaliplatin efficacy in metastatic pancreatic cancer organoids. Oncotarget 9(16):13009–13022 37. Molla A, Couvet M, Coll J-L (2017) Unsuccessful mitosis in multicellular tumour spheroids. Oncotarget 8:28769–28784 38. Zanoni M, Piccinini F, Arienti C, Zamagni A, Santi S, Polico R, Bevilacqua A, Tesei A (2016) 3D tumor spheroid models for in vitro therapeutic screening: a systematic approach to enhance the biological relevance of data obtained. Sci Rep 6:19103 39. Bonnier F, Keating ME, Wro´bel TP, Majzner K, Baranska M, Garcia-Munoz A, Blanco A, Byrne HJ (2015) Cell viability assessment using the Alamar blue assay: a comparison of 2D and 3D cell culture models. Toxicol In Vitro 29:124–131

Chapter 4 A Perfusion Model to Evaluate Response to Photodynamic Therapy in 3D Tumors Shubhankar Nath, Michael Pigula, Tayyaba Hasan, and Imran Rizvi Abstract Numerous cancer models have been developed to investigate the effects of mechanical stress on the biology of cells. Here we describe a protocol to fabricate a perfusion model to culture 3-dimensional (3D) ovarian cancer nodules under constant flow. The modular design of this model allows for a wide range of treatment regimens and combinations, including PDT and chemotherapy. Finally, methods for a number of readouts are detailed, allowing researchers to investigate a variety of biological and cytotoxic parameters related to mechanical stress and therapeutic modalities. Key words Perfusion model, Photodynamic therapy, Ovarian cancer, Shear stress, Fluid stress, Mechanotransduction, 3D tumor

1

Introduction In recent decades, three-dimensional (3D) cell culture systems have gained attention to evaluate the effects of therapeutic agents in vitro. Physiologically-relevant tumor models can mimic aspects of complex microenvironments that are seen in vivo [1–5]. Recent studies suggest that mechanical stressors (such as hydrodynamic forces) play a critical role in the biology of tumor cells, including motility, proliferation, metastases, and even resistance to therapy [6, 7]. Many types of cancers experience these mechanical forces at some point in their progression. Our lab and others have developed perfusion models to examine genetic, molecular, and morphological changes in 3D tumor nodules grown under constant flow [8– 11]. Cells are typically grown in overlay or embedded cultures in a scaffold that mimics the extracellular matrix (ECM) to simulate microenvironmental factors and cellular-stromal interactions that are not replicated in traditional 2D models on tissue culture-treated plastic [1]. Studies by many laboratories, including Demirci and colleagues ), have used flow-based devices to evaluate the effects of hydrodynamic

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_4, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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forces on cellular and molecular biology and also as diagnostic tools [8, 12]. Fluidic systems have shown physiological relevance to in vivo systems to study molecular changes in cancer cells that experience shear stress, such as in esophageal cancer [9] and ovarian cancer [8]. Based on these platforms, we investigated the effects of fluid forces encountered by 3D tumor nodules under constant flow [13]. Simulating the intraperitoneal movements of ascitic fluid observed in advanced-stage ovarian cancer, our model revealed flow-induced changes in molecular markers associated with epithelial-mesenchymal transition (EMT) [8]. The tumor microenvironment involves a complex interplay between tumor cells, ECM, stromal cells, immune cells, and vasculature. These microenvironmental factors can contribute to poor treatment outcomes for a range of therapies, including the restricted interactions of immune cells and cancer cells. Studies by Swartz and colleagues and Kamm and colleagues have used microfluidic models to investigate the role of flow in tumor cell migration and extravasation, and to understand the interaction between immune cells and cancer cells [14–16]. Numerous efforts are also underway to use flow-based platforms to study multiple integrated biological systems on a single device. This “labon-a-chip” approach helps to study the interaction between multiple “organs” in vitro and to facilitate the process of drug screening and disease diagnosis [17, 18]. Many factors influence the biology of cells in the tumor microenvironment that may adversely impact the outcomes of different anticancer treatments such as chemotherapy, radiotherapy, and targeted inhibitors. Photodynamic therapy (PDT), an FDA-approved light-based treatment modality, has been shown to overcome chemoresistance in many cancer types and to synergize with conventional treatment approaches [19, 20]. PDT utilizes a photosensitizer (PS) and an appropriate wavelength of light to generate reactive molecular species that kill target cells. In this context, microfluidic models could be used as a tool to examine the efficacy of PDT to sensitize tumor cells to other treatments. Microfluidic devices have been used to screen various PS and nanoconstructs for anticancer therapy [21]. Flow-based models, designed with readily available, inexpensive, components, may be applicable to a broad range of tumors that experience stress from fluid movement in order to investigate the molecular and phenotypic changes that may contribute to poor treatment response.

2 2.1

Materials Cell Culture

1. Human ovarian cancer cell line (NIH:OVCAR5). Other rationally-selected tumor cells can also be used.

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2. Growth medium: RPMI 1640, 10% fetal bovine serum (FBS), 100 U/mL penicillin, 100 μg/mL streptomycin. 3. Sterile phosphate-buffered saline (PBS), pH 7.4. 4. 0.25% Trypsin-EDTA. 5. Centrifuge machine. 6. Hemocytometer. 7. Humidified cell culture incubator (37  C with 5% CO2). 8. Viability stain: 4 μM Calcein AM, 10 μg/mL propidium iodide in PBS. The viability stain must be prepared fresh each time. 2.2

Chip Fabrication

1. Glass coverslips with a dimension of 24  40 mm and thickness of 0.13–0.17 mm. 2. Cut medical grade double-sided adhesive (DSA) film of 254 μm thickness (Adhesives Research, Inc.) into 24  40 mm rectangular pieces with three channels of 4 mm width and a 3 mm space in between. Fabricate the channel outlet region with a 127 angle to facilitate fluid entrance to and exit from the channels as shown in Fig. 1 (see Note 1). 3. Growth factor-reduced Matrigel (Corning). 4. Cut polymethyl methacrylate (PMMA) sheet of 3.175 mm thickness into 24  40 mm rectangular pieces using a laser cutter. Include inlet and outlet ports of microchannels of 2.2 mm in diameter and position 5 mm from the edge of the chip as shown in Fig. 1.

Fig. 1 Dimensions of the perfusion model components. Perfusion channels are composed of three components: a polymethylmethacrylate (PMMA) layer (top), a micromachined double-sided adhesive (DSA) layer with embedded channels (middle), and a glass coverslip (bottom). The dimensions of each component and individual channel are shown

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5. Sterile cotton swab. 6. Carbon dioxide (CO2)-permeable silicon tubing with outer and inner diameters of 2.4 mm and 0.8 mm, respectively. 7. Epoxy glue. 2.3

Cell Infusion

1. Sterile 1 mL and 20 mL Luer-Lok syringes and 18-gauge blunt-end needles. 2. Programmable multichannel syringe pump with space for at least three syringes for one chip.

3

Methods Perform all the procedures at room temperature and inside cell culture laminar hood unless otherwise mentioned. The protocol described below is for making one chip and it can be scaled up accordingly. Follow institutional regulation for disposal of biological and chemical waste and sharps.

3.1 Preparation of Materials

1. Thaw Matrigel overnight on ice (~100 μL Matrigel is sufficient for one microfluidic chip). 2. Sterilize PMMA and DSA by UV irradiation for 45 min inside a cell culture hood. Flip the PMMA and DSA using sterile forceps and sterilize the other side for additional 45 min. Keep the sterile DSA and PMMA in a sterile petri dish until used. 3. Cut the CO2-permeable tubing into three 100 cm and three 40 cm pieces. Autoclave (121  C, 15 psi, 30 min) the tubing in an autoclave pouch and it can be stored until needed. 4. Dip glass coverslip in 100% ethanol and air-dry to sterilize.

3.2

Chip Assembly

1. The microfluidic chip assembly process is illustrated in Fig. 2. 2. Use sterile forceps and other equipment to handle sterile materials for chip assembly. 3. Remove the wax protector from one side of DSA film and place it on a clean, sterile coverslip with all the corners appropriately aligned. Use the pointed end of the forceps to press the DSA against the coverslip. 4. Remove the wax protector from the other side of DSA film. 5. Place the “coverslip-DSA film” on an ice pack (to prevent Matrigel polymerization) with the coverslip touching the ice pack surface. Wait for 2 min to cool it down. 6. Add 20 μL Matrigel on the open coverslip area of each channel and spread evenly using a P20 pipette tip. Remove the “coverslip-DNA film” from the ice pack and incubate at room temperature for 4 min for Matrigel to polymerize.

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Fig. 2 Chip assembly. (1) A glass coverslip was attached to DSA film and (2) was placed on an ice pack to prevent Matrigel polymerization. Matrigel was spread evenly on the channel surface. The chips were incubated at room temperature, allowing gelation of Matrigel within the channels. (3) A PMMA layer was used to cover the Matrigel-coated glass coverslip and DSA films, (4) forming channels. (5) Next, gas-permeable silicon tubing was placed to the inlet and outlet ports of the chips. Epoxy glue was added to seal the external tubing edges at the inlet and outlet

7. Place top PMMA on the adhesive side of DSA to cover the Matrigel-coated glass coverslip and DSA film, forming microfluidic channels. Press the coverslip against the PMMA using a sterile cotton swab until the PMMA completely adheres to the DSA film. 8. Place three 100 cm tubing to the inlet and three 40 cm tubing to the outlet ports of microfluidic chips. 9. Add Epoxy glue to seal the external tubing edges and fix them at the inlet and outlet. 3.3 Cell Preparation and Infusion

1. Maintain NIH:OVCAR5 cells in monolayer in a T75 flask in the growth medium. Split the cells at a ratio of 1:10 every 3–4 days to maintain their exponential growth. 2. Wash the cell layer once with 10 mL PBS and trypsinize the cells by adding 1–2 mL of trypsin-EDTA at 37  C. Add 10 mL growth medium to quench the enzymatic reaction. 3. Centrifuge the cell suspension at 450  g for 5 min. Discard the supernatant.

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4. Resuspend the cells in 10 mL growth medium and count the cell concentration using a hemocytometer. 5. Prepare three 1 mL syringes with 600 μL of the cell suspension at a concentration of 106 cells/mL. 6. Load the syringes on a syringe pump inside the cell culture laminar flow and connect the blunt-end needles with the corresponding inlet tubes. Connect the outlet tubes with three 50 mL waste tubes as shown in Fig. 3a (see Note 2). 7. Run the pump to flow cells at a rate of 100 μL/min for 5 min (see Note 3). 8. Put clamps on the inlet tubes near to the needle (to prevent accidental plunging during syringe change) and switch to three 20 mL syringes with 20 mL 2% Matrigel in the growth medium (see Note 4). 9. Unclamp the tubes and place the whole system (the pump, microfluidic chip, and waste tubes) into a cell culture incubator. 10. Start the pump at a rate of 2 μL/min for the next 7 days (see Note 5). 11. To evaluate cell viability or molecular changes, move to either Subheadings 3.4, 3.5, or 3.6 below (see Note 6). 3.4 In Situ Imaging for Viability Assay

1. Load freshly prepared viability stain into 1 mL syringe (see Note 7). 2. Clamp and switch tubing to staining mix syringes and flow at 10 μL/min for 90 min through each channel at 37  C. 3. Clamp inlet and outlet tubes near the chip and cut off any excess tubing. Securely mount the chip on a fluorescence microscope and acquire images using appropriate imaging parameters. Mosaic images may be acquired in order to image the entire channel (see Note 8).

3.5 Protein Extraction for WB

1. To collect the cell from each channel, replace the waste container with a fresh 15 mL centrifuge tube (for cell collection). 2. Transfer the whole system (pump, microfluidic chip, and collection tube) into a cold room or work on ice. 3. Load 6 mL of prechilled cell recovery solution (Corning) in a 10 mL syringe. 4. Clamp and switch tubing to cell recovery solution syringe and flow at 100 μL/min for 60 min through each channel. 5. Spin down the cells in the collection tube in a prechilled centrifuge machine at a speed of 450  g for 10 min. 6. Discard the supernatant and wash the cell pellet once with 5 mL prechilled PBS.

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Fig. 3 3D tumor culture in a perfusion model and evaluation of growth and response. (a) Syringes with medium/cells were loaded on a syringe pump. Inlet tubing was connected to the syringe and outlet tubing was connected to a waste container. Cells were pumped initially and allowed to adhere to the Matrigel bed. (b) Growth medium was pumped for 7 days under appropriate growth conditions. Tumor nodules were formed under constant flow. Scale bar: 10 μm. (c) After day 7, live-dead staining was performed using Calcein and propidium iodide. Mosaic images were acquired using a confocal microscope and stitched together to get the whole image of the channel. Scale bar: 500 μm

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7. Lyse the cell pellet in 1  RIPA buffer in the presence of phosphatase and protease inhibitors, if desired. Proceed to SDS-PAGE and Western blot or store the lysates in a 80  C freezer after snap freezing (see Note 9). 3.6 Nucleic Acid Extraction for Transcriptomics/RTqPCR

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1. Collect the cell pellet using cell recovery solution as described above. 2. Wash the cell pellet once with 5 mL prechilled PBS. 3. Lyse the cell pellet in appropriate lysis buffer for downstream application, such as DNA or RNA purification following the optimized protocol provided by the DNA or RNA isolation kits’ manufacturer.

Notes 1. PMMA and DSA models can be designed using AutoCAD or other 3D drawing software. 2. Outlet tubing can be connected to 50 mL waste tubes by drilling a hole in the cap of the tube and inserting the tubing into the hole. 3. Cells are initially loaded only into the inlet tubing, NOT into the channels themselves. Cells adhere to the Matrigel-coated channels while under flow. 100 cm of the tubing used in this design will hold precisely 500 μL of liquid. The flow rate and number of cells inoculated were previously characterized [8]. The same study also showed that OVCAR5 cells first roll on the Matrigel beds before they colonize to grow. 4. Care should be taken not to introduce bubbles into the system during needle transfer between syringes or during the process of flowing medium. Bubbles should be removed from syringes prior to loading onto the pump. When attaching tubing to needles or switching needles between syringes, put all syringes on the pump and run the pump until drops formed on all syringes are visible. Before attaching a needle to a new syringe, fill the needle bore completely with the medium so that no empty space will be left in the needle itself when attaching it to a new syringe. To remove bubbles from the flow medium, it can be prepared a day in advance and placed in a filter-stoppered flask in the incubator. 5. 24 h of flow requires 3 mL medium at 2 μL/min flow rate. 6. After day 7, the tumor nodules grown in the microfluidic channels can be subjected to PDT or other treatments. The biological readouts can be measured by in situ viability staining, WB, RT-qPCR, or fluorescence-assisted cell sorting (FACS). The nodules are very small (~100 μm) and generally they do

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not require to be individualized for WB or nucleic acid extraction. However, single-cell suspension may be required for some downstream applications, such as FACS. 7. Protect the viability staining solution from light and perform the staining process in the dark. The staining solution should be prepared fresh each time and used directly. The viability staining is generally a terminal assay. Flow rate (10 μL/min) of the stain was optimized and shown to have no adverse effect on cell viability [8]. 8. Representative images of immunofluorescent and live-dead staining are shown in Fig. 3b and c. Live spheroid area can be determined using previously described image analysis algorithms [22, 23]. 9. Inhibitors are critical to maintain the phosphorylation status of the proteins. The cell lysates should be mixed with 4X SDS-loading buffer (reducing or nonreducing) and boiled at 95  C for 5 min before using lysates on SDS-PAGE or storage.

Acknowledgments This work was supported by the National Institute of Health grants R00CA175292 (to IR) and R01CA158415 (to TH). References 1. Rizvi I, Bulin A-L, Briars E et al (2016) Mind the gap: 3D models in photodynamic therapy. In: Herwig Kostron TH (ed) Photodynamic medicine: from bench to clinic. The Royal Society of Chemistry, London, pp 197–221 2. Bissell MJ, Radisky D (2001) Putting tumours in context. Nat Rev Cancer 1(1):46–54 3. Bissell MJ, Hall HG, Parry G (1982) How does the extracellular matrix direct gene expression? J Theor Biol 99(1):31–68 4. Stock K, Estrada MF, Vidic S et al (2016) Capturing tumor complexity in vitro: comparative analysis of 2D and 3D tumor models for drug discovery. Sci Rep 6:28951 5. Griffith LG, Swartz MA (2006) Capturing complex 3D tissue physiology in vitro. Nat Rev Mol Cell Biol 7(3):211–224 6. Polacheck WJ, German AE, Mammoto A et al (2014) Mechanotransduction of fluid stresses governs 3D cell migration. Proc Natl Acad Sci U S A 111(7):2447–2452 7. Mpekris F, Angeli S, Pirentis AP et al (2015) Stress-mediated progression of solid tumors: effect of mechanical stress on tissue

oxygenation, cancer cell proliferation, and drug delivery. Biomech Model Mechanobiol 14(6):1391–1402 8. Rizvi I, Gurkan UA, Tasoglu S et al (2013) Flow induces epithelial-mesenchymal transition, cellular heterogeneity and biomarker modulation in 3D ovarian cancer nodules. Proc Natl Acad Sci U S A 110(22): E1974–E1983 9. Calibasi Kocal G, Guven S, Foygel K et al (2016) Dynamic microenvironment induces phenotypic plasticity of esophageal cancer cells under flow. Sci Rep 6:38221 10. van Duinen V, Trietsch SJ, Joore J et al (2015) Microfluidic 3D cell culture: from tools to tissue models. Curr Opin Biotechnol 35: 118–126 11. Zervantonakis IK, Hughes-Alford SK, Charest JL et al (2012) Three-dimensional microfluidic model for tumor cell intravasation and endothelial barrier function. Proc Natl Acad Sci U S A 109(34):13515–13520 12. Lee WG, Kim Y-G, Chung BG et al (2010) Nano/microfluidics for diagnosis of infectious

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diseases in developing countries. Adv Drug Deliv Rev 62(4):449–457 13. Afshar S, Nath S, Demirci U et al (2018) Identification of hydrodynamic forces around 3D surrogates using particle image velocimetry in a microfluidic channel. In: SPIE BiOS. SPIE, p8 14. Pisano M, Triacca V, Barbee KA et al (2015) An in vitro model of the tumor-lymphatic microenvironment with simultaneous transendothelial and luminal flows reveals mechanisms of flow enhanced invasion. Integr Biol 7(5): 525–533 15. Swartz MA, Lund AW (2012) Lymphatic and interstitial flow in the tumour microenvironment: linking mechanobiology with immunity. Nat Rev Cancer 12(3):210–219 16. Adriani G, Pavesi A, Tan AT et al (2016) Microfluidic models for adoptive cell-mediated cancer immunotherapies. Drug Discov Today 21(9):1472–1478 17. Haeberle S, Zengerle R (2007) Microfluidic platforms for lab-on-a-chip applications. Lab Chip 7(9):1094–1110

18. Srinivasan V, Pamula VK, Fair RB (2004) An integrated digital microfluidic lab-on-a-chip for clinical diagnostics on human physiological fluids. Lab Chip 4(4):310–315 19. Obaid G, Broekgaarden M, Bulin A-L et al (2016) Photonanomedicine: a convergence of photodynamic therapy and nanotechnology. Nanoscale 8(25):12471–12503 20. Celli JP, Spring BQ, Rizvi I et al (2010) Imaging and photodynamic therapy: mechanisms, monitoring, and optimization. Chem Rev 110(5):2795–2838 21. Chudy M, Tokarska K, Jastrze˛bska E et al (2017) Lab-on-a-chip systems for photodynamic therapy investigations. Biosensors Bioelectron 101:37–51 22. Bulin A-L, Broekgaarden M, Hasan T (2017) Comprehensive high-throughput image analysis for therapeutic efficacy of architecturally complex heterotypic organoids. Sci Rep 7(1): 16645 23. Celli JP, Rizvi I, Blanden AR et al (2014) An imaging-based platform for high-content, quantitative evaluation of therapeutic response in 3D tumour models. Sci Rep 4:3751

Chapter 5 Analysis of Treatment Effects on Structurally Complex Microtumor Cultures Using a Comprehensive Image Analysis Procedure Anne-Laure Bulin, Mans Broekgaarden, and Tayyaba Hasan Abstract As three-dimensional (3D) culture models are attractive platforms to assess treatment response and expedite the development of new therapeutic regimens, appropriate methodologies to extract quantitative data from these models are required. Here, we present a live/dead staining protocol together with a recently developed analysis methodology for the multiparametric assessment of treatment effects on 3D culture models (CALYPSO: Comprehensive image AnaLYsis Procedure for Structurally complex Organoids). This methodology can process up to thousands of individual organoids within a single experiment and provides multiple informative readouts for each individual microtumor. Moreover, this protocol utilizes conventional fluorescence microscopy and commercially available dyes, allowing it to be easily implemented in most laboratories. Taken together, the methodology presented here encourages the use of microtumor models by enabling the high-throughput assessment of treatment effects, regardless of 3D culture type or microtumor architectures. Key words Organoids, Spheroids, Ultralow adhesion, Treatment outcomes, Liquid-overlay cultures, Confocal microscopy, Cytotoxicity, Therapy screening, Necrosis, Cancer

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Introduction Microtumor models, i.e., three-dimensional (3D) culture models of cancer, are becoming increasingly popular as they bridge the gap between traditional two-dimensional (2D) cell culture models and in vivo models. A major benefit of 3D cultures in comparison to in vivo models is that microtumor cultures retain their potential for high-throughput assessment of biological phenomena and treatment effects. Recent investigations on photodynamic therapy (PDT) have demonstrated the capacity of 3D culture models to optimize PDT dosimetry [1–4], determine drug penetration [5], and explore the role of tumor architecture in the treatment response [6–8]. However, one of the major challenges is that many methods and protocols to quantitatively assess treatment

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effects are optimized for 2D cultures, and have limited applicability to 3D culture models. Thus, the exploitation of microtumor/organoid models in the exploration of treatment effects requires the adaptation of existing methodologies designed for 2D cultures, in order for them to be accurate in 3D cultures. In 3D models, the evaluation of treatment cytotoxicity predominantly relies on microscopic techniques rather than colorimetric assays based on cell metabolism. To assess treatment effects, fluorescent dyes that specifically stain live and dead cells have been frequently used to qualitatively report the health of 3D cultures [9– 11]. However, extracting quantitative data (e.g., viability index, live area/volume) from those assays is less common. Recently, image analysis methodologies have been developed to facilitate highthroughput and multi-parametric screening of treatment effects. For example, Celli et al. developed an image analysis method to calculate microtumor volumes from 2D images and demonstrated its capacity to assess treatment responses on various matrixadherent microtumor cultures [12]. Such volumetric analyses were also used by Zanoni et al., who demonstrated that the size and shape of the spheroids (suspended microtumors) are a source of treatment response variability [13]. Inspired by these assays, but challenged by encountering highly heterogeneous nonsymmetrical microtumors that render volumetric calculations highly inaccurate, we recently developed an image analysis methodology (CALYPSO), written in MATLAB, that relies on calculating microtumor areas rather than volumes and correlating the area of a spheroid plane with a viability parameter [14]. By leveraging widely established live/dead cell stains in combination with confocal fluorescence microscopy, this assay was capable of quantifying treatment responses on both matrix-adherent microtumor cultures and suspended spheroids, and yielded multiple parameters of treatment outcomes for every individual microtumor [8, 14–19]. In this communication, we will outline the procedure to achieve live/ dead staining of the 3D cultures, perform quantitative imaging, and use the CALYPSO image analysis code to obtain a wealth of representative results that reflect the mesoscopic effects of various cancer treatments. Practically, the assay relies on the staining of live cells using calcein AM, and dead cells using propidium iodine (PI). Staining of live cells by calcein AM occurs when calcein passes the cell membranes, after which it is digested by intracellular esterases into a strong fluorophore that is retained intracellularly. For dead cells, PI is a DNA-binding fluorophore that cannot pass intact cell membranes, and thus specifically stains cells with compromised membrane integrity (i.e., necrotic cells). Through confocal fluorescence imaging at low magnifications, whole spheroids (suspension cultures) or a multitude of microtumors (hydrogel-adherent cultures) can be imaged simultaneously. Subsequent image analysis using the

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CALYPSO methodology can then be performed to determine the fluorescence intensities of the live and dead stains for every individual organoid within the field of view. However, to ensure correct image processing, specific control groups need to be included in every experiment. These controls comprise a “no treatment” control group and a “total killing” control group. These controls are used to set up the microscope parameters but are also necessary for the image analysis procedure to calculate the background fluorescence intensities and to determine the threshold of both fluorescence channels. This protocol will provide the preparation of the control groups, as well as the optimization of the imaging parameters. We will subsequently detail the steps that are necessary to run the CALYPSO image analysis, which can be applied to 3D cultures regardless of the type or microtumor shape. Please note that the CALYPSO analysis code can be made accessible by the authors of this chapter. Lastly, although this methodology has been developed and optimized for live/dead analysis using calcein AM and PI staining, it may be used for quantitative image analysis for different purposes, such as measuring the expression of fluorescent reporter dyes or proteins.

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Materials 1. 200 μL Sterile pipette tips (for the protocol performed on suspension cultures). 2. 1 mL Pipette tips (for the protocol performed on adherent cultures). 3. 4% Formalin in deionized water. 4. 0.1% Triton X-100. 5. Sterile phosphate-buffered saline with Ca2+ and Mg2+ (PBS++). 6. 0.1 M Glycine in deionized water, prepare fresh. 7. Calcein acetoxymethyl ester (calcein AM). 8. 1 mg/mL Propidium iodine (PI). 9. MATLAB 2016b or later versions, supplemented with the Image Processing and Bioformats toolbox (Mathworks, Cambridge MA). Alternatively, ImageJ/FIJI may be used; see Note 1. 10. Software for statistical analysis.

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Methods

3.1 Preparing the Total Killing Controls on Adherent Microtumor Cultures

1. See Note 2 for the relevance of the total killing controls. 2. Aspirate the medium in the well using a 1 mL pipette tip. 3. Add 500 μL of 4% formalin and incubate for 2 min. 4. Remove the formalin and replace by 500 μL of 0.1% Triton X-100. Incubate between 30 min and 2 h to permeabilize the cell membranes, to facilitate complete membrane permeabilization without disrupting the microtumors. The incubation time depends on the compactness of the nodules. 5. Remove the Triton X-100 from the cultures and gently wash three times with 500 μL of 0.1 M glycine. 6. After washing with 0.1 M glycine, leave the culture in 500 μL sterile PBS++.

3.2 Live/Dead Staining on Adherent Microtumor Cultures

1. Prepare the live/dead staining mixture, containing 2 μM calcein AM and 3 μM PI in PBS++, and prepare sufficient volume to enable the addition of 500 μL live/dead mix to each well of the plate. 2. Aspirate the medium (or PBS for the total killing controls) from each well. 3. Replace with 500 μL of the live/dead mix solution. 4. Incubate for 30–45 min before imaging at 37
C.

3.3 Preparing the Total Killing Controls on Suspended Organoid Cultures

1. See Note 2 for the relevance of the total killing controls. 2. Aim to remove all but 50 μL of culture medium from the spheroid-containing wells (see Note 3). Gently aspirate the culture medium using a 200 μL pipette tip. Visually check the pipette tips to ensure that the spheroids are not aspirated. 3. Slowly add 50 μL of 4% formalin to the wells and incubate for 2 min. 4. Aspirate 50 μL from the well and replace by 50 μL of 0.1% Triton X-100. Incubate between 30 min and 2 h to permeabilize the cell membranes. 5. Remove 50 μL from the well containing the Triton X-100 and replace by 50 μL 0.1 M glycine. Repeat this step twice. 6. Aspirate 50 μL and replace by sterile PBS++.

3.4 Live/Dead Staining on Suspended Organoid Cultures

1. In the meantime, prepare the live/dead staining mixture, containing 4 μM calcein and 6 μM PI in PBS++, and prepare sufficient volume to enable the addition of 50 μL live/dead mix to each well of the plate.

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2. Bring the volume of each well to 100 μL by aspirating extra medium using a 200 μL pipette tip, while being careful not to remove the spheroid. 3. Add to each well 100 μL of live/dead mix in a concentration twice as high as the final desired concentration (i.e., 4 μM of calcein and 6 μM of PI in PBS++, to reach a final concentration of 2 μM of calcein and 3 μM of PI in each well). 4. Incubate for 1 h before imaging. While signal can be detected earlier than 1 h after addition of the live/dead mix in the well, we observed that 1 h was an optimal time to avoid having signal variation in one well between the beginning and the end of the imaging process. 3.5 Quantitative Live/Dead Imaging

1. Image the organoids using a 4X (0.16 NA, air) objective (adherent cultures) or a 10 (0.4 NA, air) objective (for the suspension cultures) to acquire 512512 pixel images. In order to maximize the signal collection, the pinhole of the confocal setup should be opened at its maximum (see Note 4). 2. Detect the emission of calcein at 520 nm  20 nm upon laser excitation at 488 nm. 3. Detect the emission of PI at 630  20 nm upon laser excitation at 559 nm. 4. For each field of view, acquire a bright-field image upon the 559 nm excitation. 5. In the case of the spheroid cultures, a single image is acquired per well. However, for the adherent microtumor cultures, a mosaic of four nonoverlapping/adjacent images can be recorded, covering over 20% of the total well surface. Those images should be recorded in the center of the well where the hydrogel surface is almost flat. All images should be carefully named so that it can be easily deduced to which control or treatment group the images belong. It is advised to keep a template sheet in the folder where the images are stored.

3.6 CALYPSO Image Analysis: Data Organization

1. Obtain the CALYPSO image analysis codes (available upon request from the authors). 2. In the data files, prepare separate folders for each treatment group, as well as for the no treatment and the total killing control groups. 3. Sort the image files into their corresponding groups. See Note 5.

3.7 CALYPSO Image Analysis: Background Subtraction

1. Open “CALYPSO_ExtractBkgd.” For a technical explanation of this procedure, see Note 6.

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2. Set the code parameters. Select “No” for the clear border option, and select “Yes” for the dilate mask option. Use “Mask-Adapt” for the ImType query. Set the adaptive threshold at a value of 0.55 and adjust based on how accurate the masking procedure has been performed by inspecting the masked images. Do not use the “Remask” function. For AreaMinObject, define the minimal size of interest. This depends on the image resolution, and can be calculated for a single cell ~400 μm2, or a group of 5 cells to arbitrarily define a microtumor at 2000 μm2. 3. Run the code on the folder containing the images pertaining to the no treatment controls. 4. The code generates a new folder that contains the masked images and the background values. Visually check the mask that defines the individual organoids. The background is calculated on the inverse masks. If the images are inappropriately masked (i.e., if the organoids are not properly highlighted), rerun the code after adapting the adaptive threshold value to, e.g., 0.58 or 0.52. Repeat these steps if necessary until an acceptable masked image is obtained in which the individual organoids are properly outlined and thus effectively removed from the inverse mask that is used to determine the background fluorescence intensities. Use the same adaptive threshold value for all subsequent steps within the experiment. 5. Take note of the median background intensities for both channels, which are used for all further steps. 3.8 CALYPSO Image Analysis: Thresholding the Fluorescence Intensities

1. Open “CALYPSO_Extract_Threshold.” See Note 7 for a technical explanation on the thresholding procedure. 2. Set the code parameters. Select “No” for the clear border option, and select “Yes” for the dilate mask option. Use “Mask-Adapt” for the “ImType” query. Set the adaptive threshold at a value of 0.55 (or as optimized during the extract background procedure). 3. Define the background values for the green (FLUO2Bkdg) and red channels (FLUO1Bkdg). 4. Run the code on the no treatment control group and the total killing control group, creating two output files that contain the threshold of the live and dead channels. 5. Take note of the mean threshold values, which are required for the final steps of the image analysis procedure.

3.9 CALYPSO Image Analysis: Data Extraction

1. Open the “CALYPSO” code. 2. Specify the background values (derived in Subheading 3.7). 3. Specify the threshold values (derived in Subheading 3.8).

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4. Run the code on every folder containing the images of the treatment groups. Also run the code on the control groups. This will generate masked image files, and data sheets that contain a multitude of parameters for every individual microtumors/spheroids per image. The parameters include the microtumor/spheroid surface area, live fluorescence intensity, dead fluorescence intensity, viability (live intensity/(live intensity + dead intensity)), live area, dead area, and various others. In addition, the code generates heatmaps that provide information on the spatial distribution of the viability in the microtumors/spheroids. See Note 8 for further information on the output metrics. 3.10 Data Analysis and Interpretation

1. Plot the viability of the individual microtumors/spheroids or the median viability per image, and create boxplots containing the data of all the treatment groups. Run a Pearson-Omnibus test for normality. Select an appropriate statistical test (typically for non-Gaussian distributions) to determine whether there are significant differences in data distributions between the treatment groups of interest. 2. Plot the total area of the individual microtumors/spheroids or the median organoid area per image, and create boxplots containing the data of all the treatment groups. Run a PearsonOmnibus test for normality. Select an appropriate statistical test (typically for non-Gaussian distributions) to determine whether there are significant differences in data distributions between the treatment groups of interest. 3. Plot the live area of the individual microtumors/spheroids or the median live area per image, and create boxplots containing the data of all the treatment groups. Run a Pearson-Omnibus test for normality. Select an appropriate statistical test (typically for non-Gaussian distributions) to determine whether there are significant differences in data distributions between the treatment groups of interest. 4. Sum the live microtumor/spheroid areas per image. If multiple images per well were consistently taken, sum the cumulative live areas for every image to obtain a residual viable disease per well. Plot these values as boxplots and run an appropriate test for normality. Select the appropriate statistical test to determine whether there are significant differences in data distributions between the treatment groups of interest. 5. Display the individual plots side by side and create an overview of the viability heatmaps. It is likely that every treatment affects these parameters in a different manner, and only by inspecting all these parameters can one appreciate the full scope of possible treatment effects (Figs. 1 and 2) [8, 20].

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Fig. 1 Illustration of output obtained using the CALYPSO analysis protocol on a suspension culture of AsPC-1 pancreatic cells grown as 3D spheroids and subjected to an escalation dose of PDT. 0.25 μM of benzoporphyrin derivative was incubated for 90 min before the irradiation was delivered by a 690 nm laser with a fluence rate of 150 mW.cm2 and increasing radiant exposures (1 J.cm2 to 80 J.cm2). Bright-field images along with viability heatmaps of representative spheroids are displayed in (a), where scale bar represents 200 μm. (b–d) represent the dose correlation between the total area, the fractional live area, and the normalized viability, respectively, as a function of the total irradiance delivered to the sample. For each parameter, mean  SEM are depicted and data is derived from a single experiment (N ¼ 4). Published first in Scientific Reports [20]

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Notes 1. Although this protocol focuses on the use of the CALYPSO image analysis procedure described previously [20], the image analysis may also be performed in a similar manner using ImageJ/FIJI. Please see the original publication for more specific details on the individual steps of the image analysis procedure. 2. To fix the dynamic range of the fluorescence intensities on the confocal microscope and correctly set up the imaging parameters that will give a viability value ranging from zero to one, the “no treatment” and “total killing” groups are essential. It is strongly advised to keep these controls included as part of the experiments without compromise; otherwise no quantitative and representative data can be obtained from the experiments.

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Fig. 2 Illustration of output obtained using the CALYPSO analysis protocol on an adherent culture of OVCAR-5 ovarian carcinoma cells grown on a bed of Matrigel and subjected to an escalation dose of PDT. 0.25 μM of benzoporphyrin derivative was incubated for 60 min before the irradiation was delivered by a 690 nm laser with a fluence rate of 150 mW.cm2 and increasing radiant exposures (5 J.cm2 to 40 J.cm2). Live/dead images (green represents live cells whereas red depicts dead cells) along with viability heatmaps of representative spheroids are displayed in A), where scale bar represents 400 μm. B), C), and D) represent the dose correlation between the normalized organoid size, the fractional live area, and the normalized viability, respectively, as a function of the total irradiance delivered to the sample. For each parameter, mean  SEM are depicted and data is derived from three replicate experiments in which (N ¼ 24–36). Published first in Scientific Reports [20]

3. For suspended spheroid cultures, it is impossible to aspirate the entire volume of medium present within the well without aspirating the spheroid. Thus, for every step, we advise to leave a 50 μL volume in the wells at all times to ensure the spheroid not to be aspirated. Place the pipette tip at the top of the well and slowly proceed down into the culture medium when aspirating the medium. 4. In 3D cultures where multiple microtumors are grown simultaneously, not all microtumors may be on the same focal plane. To minimize this and maximize the signal intensity, the image acquisition is currently done with a completely opened pinhole. The CALYPSO methodology however is independent of the acquisition parameter and could be used to analyze data acquired with a more closed pinhole. As an extension, CALYPSO may be customized to handle z-stacks.

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5. This step is only essential for the no treatment and the total killing control groups. However, a systematic sorting will aid in keeping track of each treatment groups in often large datasets. 6. The background correction is necessary to run the CALYPSO code. Its purpose is to quantify the intensity of the background on the inter-organoid space for each fluorescent channel. The median intensities of the inter-microtumor space will then be subtracted to all pixels within the images prior to further analysis. It is recommended to calculate the background using the no treatment groups as the microtumors are typically most intact under these conditions. If debris of cells are present, their small size will exclude them to be considered as microtumors, and their emissions will be considered in the estimation of the background, leading to overestimation. Briefly, it consists of isolating the inter-microtumor space by designing a mask that highlights every microtumor using the bright-field image and by then inverting this image. This binary image is then multiplied to each fluorescent channel and the median of the pixel intensity is calculated in this inter-microtumor space and this gives the background. More details can be found in the original paper [20]. 7. Thresholding of the fluorescence intensities of both channels is used for the extraction of the relative live and dead area from the live/dead images. It is not required for the extraction of the viability values. Thresholding binarizes the fluorescence intensities, and the threshold intensity determines whether the signal in each pixel is “on” or “off.” This program isolates every organoid in the field of view of the bright-field images and extracts the threshold values using Otsu’s thresholding method. The threshold values are calculated using the no treatment and total killing controls. If done correctly, the live microtumor area in the no treatment controls should approximate the total microtumor area, and the dead microtumor area in the total killing controls should equal the total organoid area. The live microtumor area in the total killing controls should be 0. The binarized masks that are created during the threshold extraction should be inspected to ensure correct image processing. 8. After inputting the background and threshold values obtained as described above, the CALYPSO data extraction code can be run on subfolders containing all the images taken for a singletreatment condition. For each individual microtumor isolated from the bright-field image, the following parameters will be extracted: (1) total area, (2) mean intensity of the live channel, (3) mean intensity of the dead channel, (4) viability, (5) live area, (6) dead area, (7) fractional live area (live area/total area), and (8) fractional dead area (dead area/total area). For

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adherent cultures where numerous microtumors are present on a single image, mean and median values of all the abovementioned parameters can be extracted, as well as the total live area in each well and the total dead area in each well. As all these parameters are extracted on a nodule-by-nodule fashion, possible correlations can be extracted, such as size-response correlations [8], 3D plots of total area, viability, fractional live area [20], and other comparisons [21]. References 1. Foster TH, Hartley DF, Nichols MG, Hilf R (1993) Fluence rate effects in photodynamic therapy of multicell tumor spheroids. Cancer Res 53:1249–1254 2. Madsen SJ, Sun C-H, Tromberg BJ, Cristini V, De Magalha˜es N, Hirschberg H (2006) Multicell tumor spheroids in photodynamic therapy. Lasers Surg Med 38:555–564 3. Rizvi I, Anbil S, Alagic N, Celli JP, Zheng LZ, Palanisami A, Glidden MD, Pogue BW, Hasan T (2013) PDT dose parameters impact tumoricidal durability and cell death pathways in a 3D ovarian cancer model. Photochem Photobiol 89:942–952 4. Rizvi I, Bulin A-L, Briars E, Anbil S, Hasan T (2016) Chapter 11. Mind the gap: 3D models in photodynamic therapy. In: Photodynamic medicine, pp 197–221 5. Georgakoudi I, Foster TH (1998) Effects of the subcellular redistribution of two nile blue derivatives on photodynamic oxygen consumption. Photochem Photobiol 68:115–122 6. Celli JP, Rizvi I, Evans CL, Abu-Yousif AO, Hasan T (2010) Quantitative imaging reveals heterogeneous growth dynamics and treatment-dependent residual tumor distributions in a three-dimensional ovarian cancer model. J Biomed Opt 15:051603 7. Rizvi I, Celli JP, Evans CL, Abu-Yousif AO, Muzikansky A, Pogue BW, Finkelstein D, Hasan T (2010) Synergistic enhancement of carboplatin efficacy with photodynamic therapy in a three-dimensional model for micrometastatic ovarian cancer. Cancer Res 70: 9319–9328 8. Broekgaarden M, Rizvi I, Bulin A-L, Petrovic L, Goldschmidt R, Celli JP, Hasan T, Broekgaarden M, Rizvi I, Bulin A-L et al (2018) Neoadjuvant photodynamic therapy augments immediate and prolonged oxaliplatin efficacy in metastatic pancreatic cancer organoids. Oncotarget 9:13009–13022 9. Smalley KSM, Haass NK, Brafford PA, Lioni M, Flaherty KT, Herlyn M (2006)

Multiple signaling pathways must be targeted to overcome drug resistance in cell lines derived from melanoma metastases. Mol Cancer Ther 5:1136–1144 10. Stehn JR, Haass NK, Bonello T, Desouza M, Kottyan G, Treutlein H, Zeng J, Nascimento PRBB, Sequeira VB, Butler TL et al (2013) A novel class of anticancer compounds targets the actin cytoskeleton in tumor cells. Cancer Res 73:5169–5182 11. Kienzle A, Kurch S, Schlo¨der J, Berges C, Ose R, Schupp J, Tuettenberg A, Weiss H, Schultze J, Winzen S, et al. (2017) Dendritic mesoporous silica nanoparticles for pHstimuli-responsive drug delivery of TNF-alpha. Adv Healthc Mater 6 12. Celli JP, Rizvi I, Blanden AR, Massodi I, Glidden MD, Pogue BW, Hasan T (2014) An imaging-based platform for high-content, quantitative evaluation of therapeutic response in 3D tumour models. Sci Rep 4:3751 13. Zanoni M, Piccinini F, Arienti C, Zamagni A, Santi S, Polico R, Bevilacqua A, Tesei A (2016) 3D tumor spheroid models for in vitro therapeutic screening: a systematic approach to enhance the biological relevance of data obtained. Sci Rep 6:19103 14. Bulin A-L, Broekgaarden M, Hasan T (2017) Comprehensive high-throughput image analysis for therapeutic efficacy of architecturally complex heterotypic organoids. Sci Rep 7: 16445 15. Bulin A-L, Broekgaarden M, Simeone D, Hasan T (2019) Low dose photodynamic therapy harmonizes with radiation therapy to induce beneficial effects on pancreatic heterocellular spheroids. Oncotarget 10:2625–2643 16. Broekgaarden M, Bulin A-L, Frederick J, Mai Z, Hasan T (2019) Tracking photodynamic- and chemotherapy-induced redox state perturbations in 3D culture models of pancreatic cancer: a tool for identifying therapyinduced metabolic changes. J Clin Med 8:1399

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17. Broekgaarden M, Anbil S, Bulin A-L, Obaid G, Mai Z, Baglo Y, Rizvi I, Hasan T (2019) Modulation of redox metabolism negates cancerassociated fibroblasts-induced treatment resistance in a heterotypic 3D culture platform of pancreatic cancer. Biomaterials 222:119421 18. Obaid G, Bano S, Mallidi S, Broekgaarden M, Kuriakose J, Silber Z, Bulin A-L, Wang Y, Mai Z, Jin W et al (2019) Impacting pancreatic cancer therapy in heterotypic in vitro organoids and in vivo tumors with specificity-tuned, NIR-activable photoimmuno-nanoconjugates: towards conquering desmoplasia? Nano Lett 19:7573–7587 19. Broekgaarden M, Bulin A-L, Porret E, Musnier B, Chovelon B, Ravelet C, Sancey L,

Elleaume H, Hainaut P, Coll J-L et al (2020) Surface functionalization of gold nanoclusters with arginine: a trade-off between microtumor uptake and radiotherapy enhancement. Nanoscale 12(13):6959–6963, Epub ahead of print 20. Bulin A-L, Broekgaarden M, Hasan T (2017) Comprehensive high-throughput image analysis for therapeutic efficacy of architecturally complex heterotypic organoids. Sci Rep 7: 16645 21. Anbil S, Rizvi I, Celli JP, Alagic N, Pogue BW, Hasan T (2013) Impact of treatment response metrics on photodynamic therapy planning and outcomes in a three-dimensional model of ovarian cancer. J Biomed Opt 18:098004

Chapter 6 High-Throughput Examination of Therapy-Induced Alterations in Redox Metabolism in Spheroid and Microtumor Models Mans Broekgaarden, Anne-Laure Bulin, and Tayyaba Hasan Abstract The capacity of cancer cells to adjust their metabolism to thrive in new environments and in response to treatments has been implicated in the acquisition of treatment resistance. To optimize therapeutic strategies such as photodynamic therapy (PDT)-based combination treatments, methods to characterize the plasticity of cancer metabolism in response to treatments are required. This protocol provides a method for highthroughput and label-free tracking of metabolic redox states in cancer tissues, leveraging the autofluorescent properties of nicotinamide dinucleotide (NAD(P)H) and oxidized flavoprotein adenine dinucleotide (FAD). The methodology is optimized to be applied to 3D spheroid/microtumor/organoid cultures, regardless of the culture type (e.g., adherent or suspension cultures) and morphology. The exploitation of these methods may elucidate mechanisms of metabolic adaptation and perturbations in redox homeostasis, and chart the overall tumor health in both 3D culture models and ex vivo tissues following cancer therapies, such as PDT. Key words Optical redox ratio, Spheroids, Metabolic plasticity, High-throughput screening, Oxidative stress, Oxidative phosphorylation

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Introduction Cancer is hallmarked by aberrant metabolism that is remarkably distinct to the metabolism of healthy tissues. The capacity of cancer cells to adjust their metabolism to new biological ecosystems and environmental conditions has been implicated in cancer progression, dissemination, and treatment resistance [1–3]. Thus, elucidating how cancer tissues respond to therapies may inspire the development of new treatment strategies to overcome metabolisminduced resistance. In this context, photodynamic therapy (PDT) is a light-activated cancer therapy that eradicates cancer tissues through excessive oxidative damage [4, 5], which has profound effects on various metabolic pathways such as mitochondrial respiration [6–8] and autophagy [9, 10]. In addition, the destruction of the

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tumor vasculature by PDT induces tumor hypoxia, activating the hypoxia-inducible factor 1 (HIF-1) [11–13]. As HIF-1 is a master regulator of glycolysis and survival [14], its inhibition during PDT was demonstrated to reduce the metabolic adaptation of hypoxic cancer cells and enhance the treatment efficacy [15–17]. These findings underscore that metabolic adaptation mechanisms may play a role in cancer cell survival following PDT, and that a better understanding of adaptive cancer metabolism can guide the development of effective combination therapies. To assess the metabolic/redox state of cancer tissues, quantification of the optical redox state represents a practical approach that can be achieved in a label-free and noninvasive manner using fluorescence microscopy. Redox imaging hinges on the detection of nicotinamide dinucleotide (NAD(P)H) and oxidized flavoprotein adenine dinucleotide (FAD) fluorescence emission, two critical metabolites in the tricarboxylic acid cycle, oxidative phosphorylation, and various other metabolic pathways [18, 19]. Metabolic redox imaging informs on the redox state of tissues, typically represented by the normalized optical redox ratio that is derived by dividing the NAD(P)H emission intensity by the sum of the NAD (P)H and FAD intensities. The redox state is an indication of the oxidative phosphorylation activity in tissues, but is also influenced by oxidative stress. Treatment-induced aberrations in redox state have been well documented in the literature for cells in monolayer. For example, PDT was shown to decrease NAD(P)H fluorescence [20, 21] and cause severe oxidative stress [11]. Although previous studies typically correlate the NAD(P)H and FAD emission intensities and/or lifetimes with the health of the cells, it should be noted that the redox state can be perturbed without cell death being an immediate or prolonged consequence. By charting metabolic adaptation processes following treatments using redox imaging, and with the inclusion of substantially more detailed auxiliary assays of treatment effects, the survival strategies of tumor tissues following therapy may be better understood [22, 23]. To assess the effects of cancer therapies in vitro, 3D culture models such as spheroids and microtumors are an attractive platform as tumor architectures and nutrient gradients are more accurately recapitulated in those models in comparison to monolayer cultures [24, 25]. However, the application of redox imaging on 3D cultures is challenging and methods to do this accurately remain scarce and typically require customized optical setups [22, 26, 27]. To investigate cancer metabolism in various microtumor models of cancer, we recently developed a label-free imaging-based methodology for high-throughput tracking of redox metabolism, leveraging conventional fluorescence microscopy (MAMBO: Methodology for the Assessment of redox MetaBolism in Organotypic cultures) [28]. This methodology allows the assessment of redox metabolism in various 3D cultures [28, 29]; it can also

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Fig. 1 Schematic outline of the redox imaging methodology. Imaging involved two-photon microscopy to detect the autofluorescence of NAD(P)H and FAD in cultures and tissues. To improve signal-to-noise ratios while preventing photothermal effects, a small z-stack is taken and summed. Quantitative image analysis is then performed using a custom-built image processing workflow from which spatial information can be additionally derived in the form of redox ratio heatmaps

distinguish between oxidative stress and oxidative phosphorylation if appropriate experimental control groups are included. For instance, we recently demonstrated that benzoporphyrin-derivative (BPD) PDT caused increased redox states in pancreatic cancer microtumors that could be partially attributed to increased oxidative phosphorylation activity [30]. In this chapter, we provide a protocol to investigate the redox state of cancer organoids using fluorescence intensity-based imaging of endogenous NAD(P)H and FAD. The protocol includes critical steps that are necessary to optimize the imaging settings and image analysis procedures (Fig. 1), as well as a control experiment to ensure correct image acquisition, analysis, and data interpretation. The methodology can be applied to both suspended organoids and extracellular matrix-adherent organoids, as demonstrated previously [28–30], and to identify alterations in native redox state and treatment-induced metabolic perturbations. This may contribute to the intelligent design of combination treatments that provide enhanced therapy outcomes and more efficient disease control. Moreover, with multiphoton imaging becoming more widely available and increasingly utilized, noninvasive redox imaging will allow real-time and in-depth spatiotemporal tracking of the redox metabolism of tissues in vivo [31].

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Materials

2.1 Determination of Spectral Overlap

1. 100 mM NADH in ultrapure water. 2. 100 mM FAD in ultrapure water. 3. Glass-bottom, black-walled 96-well plate.

2.2 Suspended Spheroid Cultures

1. U-bottom, 96-well ultralow attachment plates (Corning).

2.3 Liquid-Overlay Adherent Microtumor Cultures

1. 24-well black-walled culture plates.

2.4 For the Redox State Controls and Treatment Groups

1. Rotenone 50 μM in dimethyl sulfoxide (DMSO).

2. Matrigel extracellular matrix (Corning), kept on ice at all times.

2. 2,4-Dinitrophenol (DNP), 50 mM in DMSO. 3. Hydrogen peroxide (H2O2), 20 mM in ultrapure water, filter sterilized. Prepared on the day of experiment. 4. Sodium azide (NaN3), 2.5 mM in DMSO. 5. Photosensitizer solution, prepared at a 10 concentration in DMSO.

2.5 Imaging of NAD(P)H and FAD Autofluorescence Intensities and Image Analysis

1. A (confocal) fluorescence microscope, equipped with either a 405 nm excitation source or a two-photon excitation source set at 750 nm. The emission is collected at 440 nm (NAD(P)H) and 520 nm (FAD). 2. MATLAB 2016b or later versions, supplemented with the Image Processing and Bioformats toolboxes (Mathworks, Cambridge MA). Alternatively, ImageJ/FIJI may be used; see Note 1. 3. The custom-built image processing and analysis code for the examination of redox metabolism in organoid cultures (MAMBO), described by Broekgaarden et al. [28] (available upon request).

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Methods

3.1 Determination of Spectral Overlap

1. Prepare dilutions of NADH and FAD in culture medium. Prepare dilutions in the range of 0.01–1 mM. Transfer 100 μL of volume into 96-well plates. 2. Image the solutions using a 750 nm (two-photon) or 405 nm (single photon) excitation source. Through a 10x objective (0.4 NA, air), acquire the fluorescence intensity emitted at 440  20 nm and 520  20 nm, using a scanning speed of

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12.5 μs/pixel. Obtain a z-stack of 30 images spaced 0.1 μm apart (a setting that will later prevent photothermal effects in the organoid cultures). 3. Process the images in ImageJ and plot the NADH and FAD concentration-dependent emission curves. To do so, sum the emission intensities over the z-stack, thus generating a single image for each fluorescent channel. Extract both the NADH and FAD intensities for each solution. Plot the 440  20 nm and 520  20 nm emission intensities as a function of NADH and FAD concentrations. If done correctly, the NADH solution should have considerable emission at both 440  20 nm and 520  20 nm, whereas FAD emission is only detected through the 520  20 nm emission filter. Calculate the percentage of the NADH emission intensity that is detected at 520  20 nm relative to the 440  20 nm emission intensity. Within the image analysis and data extraction code, this percentage named “overlap factor” will be used to correct the FAD emission intensities. See Note 1. 3.2 Control Experiment to Ensure Correct Image Acquisition and Processing

1. Plan the control experiment by designating at least six control groups. These include control groups (1) no treatment and (2) total killing, as well as four other groups: (3) a group where mitochondrial complex I is inhibited with rotenone, (4) a group where cytochrome c oxidase is inhibited with NaN3, (5) a group where oxidative phosphorylation is uncoupled by DNP, and (6) a group where oxidative stress is induced by H2O2. 2. Prepare the 3D cultures using established methodologies [32– 36]. See Notes 2 and 3 for further details on establishing the organoid cultures. 3. Plan an incubation period of at least 24 h with rotenone, NaN3, DNP, and H2O2. Dilute the solutions 10 in the culture medium. Final concentrations are 5 μM rotenone, 250 μM NaN3, 5 mM DNP, and 2 mM H2O2. See Note 4. 4. Following incubation, image the microtumors using a 750 nm excitation (two photon) or a 405 nm excitation (single photon). Through the 10 objective, acquire bright-field images, as well as emission intensity images recorded at 440  20 nm and 520  20 nm with a scanning speed of 12.5 μs/pixel. Obtain a z-stack of 30 images spaced 0.1 μm apart. 5. Run the MAMBO image analysis and data extraction code in MATLAB. See Note 5, and an example of expected results in Fig. 2.

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Fig. 2 Control experiment for redox imaging on AsPC-1 spheroids to ensure correct image acquisition and processing. AsPC-1 spheroid cultures were initiated by seeding 5000 cells/well in U-bottom ultralow attachment plates, and 48 h of culturing in RPMI growth medium. Spheroids were treated as indicated for 48 h, after which redox imaging was performed. Images clearly depict reduced redox states in spheroid treated with mitochondrial complex I inhibitors, and increased redox states upon exposure to mitochondrial uncouplers and oxidizing agents 3.3 Treatment of the Organoid Cultures

1. Carefully plan the timeline of the experiment and the layout of the plates in terms of designating the treatment groups. For each experiment, include 3 control groups: (1) a no treatment control, (2) a negative control (low redox ratio) through incubation with rotenone or NaN3, and (3) a positive control (high redox ratio) through incubation with DNP or H2O2. The incubation times for the positive and negative control should be between 24 and 48 h. 2. Prepare the microtumor cultures using established methodologies [32–36]. See Notes 1 and 2 for further details on establishing the organoid cultures. 3. Perform the treatments as desired. Perform the exposures to the controlled conditions. 4. Following incubation, image the microtumors using a 750 nm excitation (two photon) or a 405 nm excitation (single photon). Through the 10 objective, acquire bright-field images, as well as emission intensity images recorded at 440  20 nm and 520  20 nm with a scanning speed of 12.5 μs/pixel. Obtain a z-stack of 30 images spaced 0.1 μm apart. See Note 6. 5. Run the MAMBO image analysis and data extraction code in MATLAB. See Note 5.

3.4 Data Analysis and Representation

1. The MAMBO image analysis workflow was written in MATLAB and can be obtained by contacting the corresponding authors. The MAMBO image analysis and data extraction procedure will provide the following parameters: (1) organoid size(s), (2) mean and median NAD(P)H

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Fig. 3 PDT induces perturbations in the redox state of MIA-PaCa-2 organoids grown as adherent cultures on Matrigel scaffolds. (a) Redox imaging on adherent MIA PaCa-2 organoids that were photosensitized for 1 hour with 0.25 μM BPD, and treated with 690 nm laser light at radiant exposures of either 10 or 25 J/cm2. Redox imaging was performed 96 h post-treatment. (b) Box-whisker plots displaying the range of redox states in the PDT-treated cultures, a Kruskal-Wallis test and Dunn’s post hoc test for multiple comparisons were performed to indicate statistically significant differences

intensities per microtumor, (3) mean and median FAD intensities per microtumor, and most importantly (4) normalized redox ratio per microtumor. The code will additionally generate redox ratio heatmaps and masks of the bright-field and fluorescence images (see Note 7 and Fig. 3). 2. Generate box-whisker plots to investigate the distribution of redox ratios. Perform appropriate statistical tests to evaluate significant differences between the treatment and control groups (Fig. 3). 3. Optionally, microtumor sizes can be correlated to the normalized redox ratio by generating scatterplots.

4

Notes 1. We previously determined the emission of NADH collected in the 540  20 nm channel (referred to as “the FAD channel”) to be 39% of the emission collected in the 440  40 nm channel (referred to as “the NAD(P)H channel”). The overlap factor was thus set at 0.39: A value of 0.39 times the NADH emission measured at 440  20 nm was subsequently subtracted from the fluorescence intensity measured through the 540  20 nm filter of every pixel during the image analysis procedure, prior to the background determinations. The overlap factor is highly dependent on the gain of the detector and the laser settings, and thus needs to be determined to ensure proper data correction. Image acquisition parameters should be optimized during

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the determination of the spectral overlap of NADH in the FAD detection channel and should not be changed at any time during subsequent investigations. 2. To establish suspended spheroid cultures in 96-well ultralow attachment plates (e.g., as described in [34, 36, 37]), harvest cancer cells from culture flasks and dilute to a concentration of 5  104 cells/mL in culture medium; seed 50 μL of this cell suspension in each well. Cell numbers may be adjusted to achieve the desired cell densities. 3. Adherent microtumors on extracellular matrix can be established using the liquid-overlay technique [32, 33, 35, 38, 39]. Extracellular matrix hydrogels are prepared in 24-well plates, by adding 250 μL of ice-cold Matrigel to each well. The hydrogels are then solidified for 20 min at 37  C. Cells are harvested from culture flasks and seeded onto the hydrogels in a volume of 1 mL at a density of 7.5  103 cells/mL. Culture medium should be supplemented with 2% Matrigel. Cell numbers may be adjusted to achieve the desired cell densities. 4. Although these conditions worked well on suspended/nonadherent organoids, it is likely that the concentrations need to be optimized depending on the cell and culture types. 5. For running the MAMBO image analysis and data extraction code in MATLAB, set the correct magnification (e.g., 10 or 4 and adapt the conversion factor to extract the spheroid/ organoid/microtumor areas in μm2), and define the overlap factor for NADH in the FAD channel that was determined in Subheading 3.1 (e.g., 0.40). The “Clear border” and “Remask” options should be disabled, and the “Dilate mask” option should be enabled at a factor 2. Define a minimum object size of 1000 px for suspended organoid cultures, which ensures selecting only the organoid, and 325 px for adherent organoid cultures that corresponds to a group of 5 cells. For the adaptive thresholding to properly generate the masks, which is an essential step to accurately calculate the background intensities within the code, select a threshold value of 0.55. However, perform visual checks on the masked images generated by the code to ensure that correct masking is achieved. Increase or decrease the adaptive thresholding value if necessary. 6. The acquisition of the 3 μm z-stack is not intended to provide spatial information on the redox state. Instead, it is used for summing the fluorescence intensities over all the images, thereby increasing the signal-to-noise ratio. Although this is typically done during conventional laser scanning microscopy by scanning the samples at the exact same place for a multitude of times, the use of near-infrared or infrared light delivered

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through a pulsed laser during two-photon excitation may result in significant photothermal effects and/or photobleaching of the fluorophores. To ameliorate this, the enhanced signal-tonoise ratios may be acquired at 0.1-μm-spaced intervals along the z-axis. 7. The redox ratio heatmaps will provide spatial distribution of redox states throughout the microtumors. The masked images created by the code are intended for assessing whether correct image processing was achieved. For the first few images analyzed in each experiment, it is not uncommon to go back and forth between the thresholding values in the code and assess the generated output images to optimize the image analysis procedure. References 1. Lehue´de´ C, Dupuy F, Rabinovitch R, Jones RG, Siegel PM (2016) Metabolic plasticity as a determinant of tumor growth and metastasis. Cancer Res 76:5201–5208 2. Vander Heiden MG, DeBerardinis RJ (2017) Understanding the intersections between metabolism and cancer biology. Cell 168: 657–669 3. Vander Heiden MG (2011) Targeting cancer metabolism: a therapeutic window opens. Nat Rev Drug Discov 10:671–684 4. Castano AP, Mroz P, Hamblin MR (2006) Photodynamic therapy and anti-tumour immunity. Nat Rev Cancer 6:535–545 5. Dolmans DEJGJ, Fukumura D, Jain RK (2003) Photodynamic therapy for cancer. Nat Rev Cancer 3:380–387 6. Hilf R (2007) Mitochondria are targets of photodynamic therapy. J Bioenerg Biomembr 39: 85–89 7. Kessel D (2014) Reversible effects of photodamage directed toward mitochondria. Photochem Photobiol 90:1211–1213 8. Pogue BW, O’Hara JA, Demidenko E, Wilmot CM, Goodwin IA, Chen B, Swartz HM, Hasan T (2003) Photodynamic therapy with verteporfin in the radiation-induced fibrosarcoma1 tumor causes enhanced radiation sensitivity. Cancer Res 63:1025–1033 9. Kessel D, Oleinick NL (2009) Initiation of autophagy by photodynamic therapy. Methods Enzymol 453:1–16 10. Kessel D, Vicente MGH, Reiners JJ (2006) Initiation of apoptosis and autophagy by photodynamic therapy. Autophagy 2:289–290 11. Broekgaarden M, Weijer R, van Gulik TM, Hamblin MR, Heger M (2015) Tumor cell

survival pathways activated by photodynamic therapy: a molecular basis for pharmacological inhibition strategies. Cancer Metastasis Rev 34: 643–690 12. Fingar VH (1996) Vascular effects of photodynamic therapy. J Clin Laser Med Surg 14: 323–328 13. Ferrario A, von Tiehl KF, Rucker N, Schwarz MA, Gill PS, Gomer CJ (2000) Antiangiogenic treatment enhances photodynamic therapy responsiveness in a mouse mammary carcinoma. Cancer Res 60:4066–4069 14. Semenza GL (2012) Hypoxia-inducible factors in physiology and medicine. Cell 148:399–408 15. Broekgaarden M, Weijer R, Krekorian M, Ijssel B, Kos M, Alles LK, Wijk AC, Bikadi Z, Hazai E, Gulik TM et al (2016) Inhibition of hypoxia-inducible factor 1 with acriflavine sensitizes hypoxic tumor cells to photodynamic therapy with zinc phthalocyanineencapsulating cationic liposomes. Nano Res 6: 1639–1662 16. Weijer R, Broekgaarden M, Krekorian M, Alles LK, van Wijk AC, Mackaaij C, Verheij J, van der Wal AC, van Gulik TM, Storm G et al (2016) Inhibition of hypoxia inducible factor 1 and topoisomerase with acriflavine sensitizes perihilar cholangiocarcinomas to photodynamic therapy. Oncotarget 7:3341–3356 17. Lamberti MJ, Pansa MF, Vera RE, Ferna´ndezZapico ME, Rumie Vittar NB, Rivarola VA (2017) Transcriptional activation of HIF-1 by a ROS-ERK axis underlies the resistance to photodynamic therapy. PLoS One 12: e0177801 18. Georgakoudi I, Quinn KP (2012) Optical imaging using endogenous contrast to assess

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metabolic state. Annu Rev Biomed Eng 14: 351–367 19. Heikal AA (2010) Intracellular coenzymes as natural biomarkers for metabolic activities and mitochondrial anomalies. Biomark Med 4: 241–263 20. Pogue BW, Pitts JD, Mycek MA, Sloboda RD, Wilmot CM, Brandsema JF, O’Hara JA (2001) In vivo NADH fluorescence monitoring as an assay for cellular damage in photodynamic therapy. Photochem Photobiol 74:817–824 21. Zhang Z, Blessington D, Li H, Busch TM, Glickson J, Luo Q, Chance B, Zheng G (2004) Redox ratio of mitochondria as an indicator for the response of photodynamic therapy. J Biomed Opt 9:772–778 22. Walsh AJ, Castellanos JA, Nagathihalli NS, Merchant NB, Skala MC (2016) Optical imaging of drug-induced metabolism changes in murine and human pancreatic cancer organoids reveals heterogeneous drug response. Pancreas 45:863–869 23. Daemen A, Peterson D, Sahu N, McCord R, Du X, Liu B, Kowanetz K, Hong R, Moffat J, Gao M et al (2015) Metabolite profiling stratifies pancreatic ductal adenocarcinomas into subtypes with distinct sensitivities to metabolic inhibitors. Proc Natl Acad Sci U S A 112: E4410–E4417 24. Pampaloni F, Reynaud EG, Stelzer EHK (2007) The third dimension bridges the gap between cell culture and live tissue. Nat Rev Mol Cell Biol 8:839–845 25. Tanner K, Gottesman MM (2015) Beyond 3D culture models of cancer. Sci Transl Med 7: 283ps9 26. Cannon TM, Shah AT, Skala MC (2017) Autofluorescence imaging captures heterogeneous drug response differences between 2D and 3D breast cancer cultures. Biomed Opt Express 8:1911–1925 27. Shah AT, Heaster TM, Skala MC (2017) Metabolic imaging of head and neck cancer organoids. PLoS One 12:e0170415 28. Broekgaarden M, Bulin A-L, Frederick J, Mai Z, Hasan T (2019) Tracking photodynamic- and chemotherapy-induced redox state perturbations in 3D culture models of pancreatic cancer: a tool for identifying therapyinduced metabolic changes. J Clin Med 8:1399 29. Bulin A-L, Broekgaarden M, Simeone D, Hasan T (2019) Low dose photodynamic therapy harmonizes with radiation therapy to induce beneficial effects on pancreatic heterocellular spheroids. Oncotarget 10:2625–2643

30. Broekgaarden M, Anbil S, Bulin A-L, Obaid G, Mai Z, Baglo Y, Rizvi I, Hasan T (2019) Modulation of redox metabolism negates cancerassociated fibroblasts-induced treatment resistance in a heterotypic 3D culture platform of pancreatic cancer. Biomaterials 222:119421 31. Skala MC, Riching KM, Gendron-FitzpatrickA, Eickhoff J, Eliceiri KW, White JG, Ramanujam N (2007) In vivo multiphoton microscopy of NADH and FAD redox states, fluorescence lifetimes, and cellular morphology in precancerous epithelia. Proc Natl Acad Sci U S A 104: 19494–19499 32. Celli JP, Rizvi I, Evans CL, Abu-Yousif AO, Hasan T (2010) Quantitative imaging reveals heterogeneous growth dynamics and treatment-dependent residual tumor distributions in a three-dimensional ovarian cancer model. J Biomed Opt 15:051603 33. Rizvi I, Celli JP, Evans CL, Abu-Yousif AO, Muzikansky A, Pogue BW, Finkelstein D, Hasan T (2010) Synergistic enhancement of carboplatin efficacy with photodynamic therapy in a three-dimensional model for micrometastatic ovarian cancer. Cancer Res 70: 9319–9328 34. Bulin A-L, Broekgaarden M, Hasan T (2017) Comprehensive high-throughput image analysis for therapeutic efficacy of architecturally complex heterotypic organoids. Sci Rep 7: 16445 35. Broekgaarden M, Rizvi I, Bulin A-L, Petrovic L, Goldschmidt R, Celli JP, Hasan T (2018) Neoadjuvant photodynamic therapy augments immediate and prolonged oxaliplatin efficacy in metastatic pancreatic cancer organoids. Oncotarget 9:13009–13022 36. Zanoni M, Piccinini F, Arienti C, Zamagni A, Santi S, Polico R, Bevilacqua A, Tesei A (2016) 3D tumor spheroid models for in vitro therapeutic screening: a systematic approach to enhance the biological relevance of data obtained. Sci Rep 6:19103 37. Molla A, Couvet M, Coll J-L (2017) Unsuccessful mitosis in multicellular tumour spheroids. Oncotarget 8:28769–28784 38. Lee GY, Kenny PA, Lee EH, Bissell MJ (2007) Three-dimensional culture models of normal and malignant breast epithelial cells. Nat Methods 4:359–365 39. Glidden MD, Celli JP, Massodi I, Rizvi I, Pogue BW, Hasan T (2012) Image-based quantification of benzoporphyrin derivative uptake, localization, and Photobleaching in 3D tumor models, for optimization of PDT parameters. Theranostics 2:827–839

Chapter 7 Spatiotemporal Tracking of Different Cell Populations in Cancer Organoid Models for Investigations on Photodynamic Therapy Anne-Laure Bulin and Tayyaba Hasan Abstract Three-dimensional (3D) in vitro models of tumors are gaining interest as versatile platforms for treatment screening. In this context, heterocellular cultures in which various cell types are co-cultured are being explored to investigate whether partner cells can influence the treatment efficacies. However, when the cells are co-cultured, it is challenging to distinguish them and it becomes impossible to identify whether the treatment affects each cell line in a similar way or if there is a certain selectivity. Here, we propose a protocol in which different cell types are pre-labeled with fluorescent reporters prior to 3D culture initiation. Subsequently, the internal architecture of the 3D cancer models can be longitudinally monitored for model characterization, and to potentially detect architectural and treatment selectivity in response to therapy. This protocol employs quantum dots as non-photobleaching dyes and two-photon excited microscopy as a widely accessible imaging modality. In combination with an appropriate image analysis workflow, this protocol will help to investigate the architectural development of heterotypic microtumor/ spheroid/organoid models and possibly identify treatment efficacies on individual cell populations represented within the models. Key words Heterocellular culture, Longitudinal tracking, Spheroid architecture, Quantum dots, Pancreatic cancer organoids, Fibroblasts, Cancer stroma

1

Introduction Cancer is a heterogeneous disease in which multiple types of cancer cells and stromal cells such as fibroblasts, endothelial cells, and immune cells coexist in competitive and architecturally complex environments [1]. Pancreatic cancer (PanCa) is a prime example of a cancer type with a prominent tumor stroma that is mainly composed of cancer-associated fibroblasts and fibroblast-like pancreatic stellate cells [2, 3]. These stromal cells engage in excessive cross talk, promoting growth and providing metabolic support to the cancer cells [4, 5]. The dense tumor stroma and the intercellular

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cross talk have been implicated in the highly resistant nature of PanCa to cancer therapies [6]. The treatment resistance of PanCa directly translates to the dismal prognosis in patients. Indeed, PanCa remains a highly lethal malignancy characterized by a 5-year survival rate that does not exceed 6% [6] despite the current standard of care that consists of a complete surgical resection if the patient is eligible and/or to a combination of chemotherapy and radiation therapy either as adjuvant or palliative modalities. Stringent chemotherapeutic regimens such as FOLFIRINOX , liposomal irinotecan, and nab-paclitaxel have achieved promising clinical results, but the toxicity of these treatments restricts their application to patients with high viability scores. In this context, photodynamic therapy (PDT) is being explored as a potential treatment for PanCa. PDT is a lightactivated cancer therapy in which cytotoxicity is induced by the tumor-specific generation of reactive oxygen species generated by nontoxic photosensitizers [7–9]. In a recent phase I/II clinical trial, it has been shown that PDT is feasible and safe for inoperable PanCa patients. The promise of PDT for those PanCa patients is also demonstrated by rendering one of them eligible to a curative surgery [10]. A recent trend is the combination of PDT with chemotherapies and radiotherapy, to investigate whether enhanced treatment outcomes can be achieved, preferentially with lower levels of toxicity [11–14]. In the context of therapy development, 3D cancer models are particularly interesting as they can provide highly useful information on the architectural effects of PDT and chemotherapeutics on such microtumors [12, 13, 15–17], and can be used to optimize PDT dosimetry [18–20]. In addition, they recapitulate the nutrient and oxygen gradients observed in vivo, which is critical when investigating a therapy of which the efficiency is often connected to the amount of oxygen available [17, 21–24]. Classic 3D models of cancer for therapy assessment comprise single cancer cell lines that are grown as microtumors or spheroids. However, as it is becoming evident that the tumor stroma has profound biological functions that may dictate treatment efficacies, the inclusion of stromal cell types such as fibroblasts is becoming more frequently explored [4, 14, 25–32]. Such models thus capture the multicellular nature of tumors in vitro and mimic the heterocellular interactions between these cell types, which may have strong influences on tumor biology and treatment susceptibility [12, 31]. One outstanding question of critical importance relates to the architectural composition of the heterotypic microtumors: that is, how are the different cell types developing within the microtumors and what is their spatial localization? The protocol provided in this chapter can be used to longitudinally monitor individual cell types within heterotypic 3D cancer cultures in a nondisruptive method (Fig. 1). Through pre-labeling

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Fig. 1 Illustration of the labeling and imaging protocol used to obtain heterocellular spheroids composed of MIA PaCa-2 pancreatic cancer cells and MRC5 fibroblasts labeled with QTracker 655 and QTracker 525, respectively. A representative image acquired using the two-photon excitation (790 nm) is shown for each cancer-to-stroma ratio spheroid grown in the well; cancer cells (MIA PaCa-2) are shown in red and fibroblasts (MRC5) in green. Scale bar corresponds to 200 μm

cells with nontoxic and photostable quantum dots (QD), this method can be used to monitor the microtumor cultures for at least 5 days, and thus constitutes a feasible approach to track and quantify the different cell populations during organoid development. As such, the biological relevance of the 3D models can be assessed, and may also have the capacity to determine the potential selectivity of a treatment toward specific cell lines, although this needs to be further investigated. The protocol outlined here, and as illustrated in Fig. 1, specifically addresses heterotypic PanCa microtumors comprised of commercially available cell lines that are grown in suspension, thus forming spheroids (U-bottom ultralow-attachment 96-well plates). However, the protocol may be similarly applied to different cancer models and cell types, as well as varying 3D culture techniques. The PanCa model described here is composed of pancreatic cancer cells and human embryonic lung fibroblasts, seeded at different ratios. Both neoplastic cells and fibroblasts were pre-labeled using different quantum dots that are characterized by distinct emission spectra upon a unique excitation wavelength. In order to inform the internal architecture of the spheroid, either a single plane or a collection of planes (z-stacks) may be acquired throughout the entire spheroid using two-photon imaging microscopy. Quantum dots have an extremely high two-photon absorption cross section compared to

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common labeling dyes and are particularly insensitive to photobleaching, which offers an evident advantage for longitudinal tracking [33] over the conventionally used organic dyes. Please note that more cell lines can be co-cultured and labeled with different quantum dots, with the limiting factor being the imaging setup.

2

Materials 1. Confluent flasks of MIA PaCa-2 (PanCa cell line) and MRC5 (fibroblast cell line) (see Note 1). 2. Qtracker 525 labeling kit (Thermo Fisher). 3. Qtracker 655 labeling kit (Thermo Fisher). 4. Sterile 2 mL microcentrifuge tubes. 5. Hemocytometer and trypan blue. 6. Culture medium. 7. Trypsin and Ca2+- and Mg2+-free phosphate-buffered saline (PBS) for cell harvesting. 8. U-bottom ultralow-attachment plates, 96-wells (Corning). 9. A special disposable container for quantum dot waste (cadmium). 10. Image analysis software such as ImageJ/FIJI (open access) or MATLAB (Mathworks).

3

Methods

3.1 Plate the Unlabeled Control (MIA PaCa-2 and MRC5) (see Note 2)

1. Harvest the cells (MIA PaCa-2 and MRC5) from their culture flask and for each cell line prepare 5
104 cells per mL suspension.

3.2 Label First Cell line (MIA PaCa-2 Cells) Using QTracker 655

1. In a 2 mL microcentrifuge tube, mix 5 μL of component A with 5 μL of component B of the QTracker kit and incubate for 5 min (see Note 4).

2. Seed 50 μL of each cell suspension in the unlabeled control wells (see Note 3).

2. Harvest the cells from their culture flask and prepare a 1
106 cells/mL suspension. 3. Place 500 μL of the cell suspension in the microcentrifuge tube containing the quantum dots (see Note 5). 4. Homogenize the solution by pipetting up and down a few times and place in the incubator (37  C, 5% CO2) for 20 min (see Note 6).

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5. After incubation, centrifuge the tube (5 min, 1000 rpm) to obtain a pellet. 6. Gently aspirate the supernatant and discard appropriately (i.e., in a quantum dot waste container). 7. Resuspend in 500 μL of fresh medium. 8. Repeat steps 5–7 twice to remove the non-absorbed quantum dots. 9. Count the cells with a hemocytometer. We advise to a use a trypan blue exclusion assay in order to check the viability of the labeled cells (see Note 7). 10. Prepare a suspension containing 5
104 of labeled cell per mL and seed 50 μL of the cell suspension in each well. 3.3 Label Second Cell line (MRC5 Cells) with QTracker 525

1. In a 2 mL microcentrifuge tube, mix 5 μL of component A with 5 μL of component B of the QTracker kit and leave for 5 min. 2. Harvest the cells from their culture flask and prepare a 1
106 cells/mL suspension. 3. Add 500 μL of this 1
106 cells/mL suspension to the microcentrifuge tube containing the quantum dots. 4. Homogenize the solution by pipetting up and down a few times and place in the incubator (37  C, 5% CO2) for 15 min (see Note 6). 5. After incubation, centrifuge the tube (5 min, 1000 rpm) to obtain a pellet. 6. Gently aspirate the supernatant and discard appropriately (i.e., in a quantum dot waste container). 7. Resuspend in 500 μL of fresh medium. 8. Repeat steps 5–7 twice to remove the non-absorbed quantum dots. 9. Count the cells with a hemocytometer. We advise to a use a trypan blue exclusion assay in order to check the viability of the labeled cells (see Note 7). 10. To grow spheroids containing different MIA PaCa-2:MRC5 ratios, add 50 μL of the following cell suspensions of labeled cells (second cell line) to the 50 μL of cell suspension already in the wells (first cell line): l

l

l

25,000 labeled cells/mL and seed 50 μL/well to obtain 2:1 (MIA PaCa-2:MRC5) ratio 50,000 labeled cells/mL and seed 50 μL/well to obtain 1:1 (MIA PaCa-2:MRC5) ratio 100,000 labeled cells/mL and seed 50 μL/well to obtain 1: 2 (MIA PaCa-2:MRC5) ratio

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200,000 labeled cells/mL and seed 50 μL/well to obtain 1: 4 (MIA PaCa-2:MRC5) ratio.

11. Optionally, treatments such as PDT, chemotherapy, radiotherapy, or combinations thereof may be initiated following the establishment of the heterocellular spheroids (24–48 h post-seeding). See Note 8. 3.4 Imaging the Spheroids Using Two-Photon Microscopy

1. Set the excitation at 790 nm (optimal wavelength to excite the quantum dots). 2. Select the proper filters to optimally collect the light emitted with a maximum at 655 nm and 525 nm for the quantum dots internalized in MIA PaCa-2 and MRC5, respectively. 3. Set the dynamic range of each detector by using the unlabeled spheroid control group: when excited, those spheroids should not emit any light. The detection threshold can be adjusted accordingly. 4. Images could be acquired through a 10
objective over 512
512 pixel or with a better resolution if desired. 5. Z-stacks can also be acquired as the two-photon excitation will selectively excite a single plane of the spheroid and 3D reconstruction can be performed using the open-source ImageJ/ FIJI software.

3.5 Extract Quantitative Data from the Images

1. Using a data-analyzing software such as ImageJ/FIJI (open source) or MATLAB, create a mask that will highlight the spheroid boundary and extract the overall area of the spheroid. 2. For each fluorescence channel, define a threshold intensity: every pixel for which the intensity is either higher or lower than the threshold value will be considered as “on” or “off,” respectively (see Note 9). 3. Using the threshold extracted for each fluorescence channel, binarize the fluorescence images. 4. Quantify the “on” area for each channel and calculate the ratio of each cell line by dividing those areas by the sum of the area of each channel. For instance, the percentage of cells labeled with the QD emitting in channel 1 is defined as Area of on pixels in channel 1 Area of on pixels in channel 1 þ Area of on pixels in channel 2 In case a z-stack has been recorded, repeat this calculation for each slice. Figure 2 represents an example where the ratio of each cell line has been recorded throughout the spheroid (see Note 9).

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Fig. 2 Illustration of the quantitative analysis that can be performed after imaging. Images were taken 1 day post-plating to ensure a comparable cancer cells:fibroblasts ratio compared to the known plating ratio. MIA PaCa-2 (labeled with the 655 nm QTracker kit) is co-cultured with MRC5 (labeled with the 525 QTracker kit) in different ratios, namely (a) 1:0, (b) 1:1, (c) 1:4, and (d) 0:1. The results obtained using the analysis code are in agreement with the ratio of cells plated

4

Notes 1. The protocol is described for a co-culture composed of MIA PaCa-2 PanCa cells and MRC5 (fibroblasts). However, it has also been applied to AsPC-1 and Capan2 PanCa cancer cell lines, OVCAR-5 ovarian cancer cells, as well as a line of pCAF (pancreatic cancer-associated fibroblasts) without any toxicity issues. 2. Unlabeled spheroids are a necessary control group to set up the microscope parameters. 3. For the unlabeled control, a single MIA PaCa-2/MRC5 ratio is used. The purpose of those control wells is only to ensure that there is no fluorescence signal detected when the cells do not contain any quantum dots. Although a different ratio can be used, it is important to use controls that do contain each cell line. 4. The labeling and seeding protocol is described here to obtain spheroids with various ratios of MIA PaCa-2 PanCa cells and MRC5 fibroblasts labeled with the QTracker 655 and the QTracker 525 labeling kits, respectively. For each labeling kit, a sub-toxic concentration of 20 nM of quantum dots was used as it induces a sufficiently intense staining to enable monitoring the culture over at least five consecutive days while remaining a sub-toxic concentration for the cells. The volumes used in the protocol are given to label 500,000 cells of each cell line and can be adapted based on the required number of cells (see Notes 2–4).

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5. As some cells could be lost during the various steps of the protocol, plan on labeling slightly more cells than needed. 6. The incubation time has to be optimized for each cell line and may vary between 15 and 30 min. 7. The concentration of living cells should not differ too much from the initial concentration. 8. Steps 3.4 and 3.5 can be reproduced after a treatment such as PDT, chemotherapy, or radiation therapy. One just has to make sure that the photosensitizer used for PDT does not absorb the excitation wavelength (790 nm) in order to prevent a potential perturbation of the fluorescence signal or to induce PDT during the imaging procedure. 9. The thresholds will have to be adapted for every imaging day, as the emission intensity of the quantum dots will decrease as the cells divide. In order to estimate those thresholds, we recommend to use for every experiment, control groups made of spheroids containing a single cell line. While common thresholding methods, including Otsu’s method [34], are widely used for image processing, the thresholding method should be optimized for every experiment and imaging system.

Acknowledgments A-L B was supported by a Bullock-Wellman Fellowship and awards from the Bettencourt-Schueller and Philippe foundations. References 1. Joyce JA, Pollard JW (2008) Microenvironmental regulation of metastasis. Nat Rev Cancer 9:239–252 2. Bardeesy N, DePinho RA (2002) Pancreatic cancer biology and genetics. Nat Rev Cancer 2:897–909 3. Ryan DP, Hong TS, Bardeesy N (2014) Pancreatic adenocarcinoma. N Engl J Med 371: 1039–1049 4. Broekgaarden M, Anbil S, Bulin A-L, Obaid G, Mai Z, Baglo Y, Rizvi I, Hasan T (2019) Modulation of redox metabolism negates cancerassociated fibroblasts-induced treatment resistance in a heterotypic 3D culture platform of pancreatic cancer. Biomaterials 222:119421 5. Sousa CM, Biancur DE, Wang X, Halbrook CJ, Sherman MH, Zhang L, Kremer D, Hwang RF, Witkiewicz AK, Ying H et al (2016) Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion. Nature 536:479–483

6. Perera RM, Bardeesy N (2015) Pancreatic cancer metabolism: breaking it down to build it back up. Cancer Discov 5:1247–1261 7. Dougherty TJ, Gomer CJ, Henderson BW, Jori G, Kessel D, Korbelik M, Moan J, Peng Q (1998) Photodynamic therapy. J Natl Cancer Inst 90:889–905 8. Castano AP, Mroz P, Hamblin MR (2006) Photodynamic therapy and anti-tumour immunity. Nat Rev Cancer 6:535–545 9. Agostinis P, Berg K, Cengel KA, Foster TH, Girotti AW, Gollnick SO, Hahn SM, Hamblin MR, Juzeniene A, Kessel D et al (2011) Photodynamic therapy of cancer: an update. CA Cancer J Clin 61:250–281 10. Huggett MT, Jermyn M, Gillams A, Illing R, Mosse S, Novelli M, Kent E, Bown SG, Hasan T, Pogue BW et al (2014) Phase I/II study of verteporfin photodynamic therapy in locally advanced pancreatic cancer. Br J Cancer 110:1698–1704

Longitudinal Imaging of Cell Populations in Heterotypic Cultures 11. Huang H-C, Mallidi S, Liu J, Chiang C-T, Mai Z, Goldschmidt R, Ebrahim-Zadeh N, Rizvi I, Hasan T (2016) Photodynamic therapy synergizes with irinotecan to overcome compensatory mechanisms and improve treatment outcomes in pancreatic cancer. Cancer Res 76: 1066–1077 12. Broekgaarden M, Rizvi I, Bulin A-L, Petrovic L, Goldschmidt R, Celli JP, Hasan T, Broekgaarden M, Rizvi I, Bulin A-L et al (2018) Neoadjuvant photodynamic therapy augments immediate and prolonged oxaliplatin efficacy in metastatic pancreatic cancer organoids. Oncotarget 9:13009–13022 13. Rizvi I, Celli JP, Evans CL, Abu-Yousif AO, Muzikansky A, Pogue BW, Finkelstein D, Hasan T (2010) Synergistic enhancement of carboplatin efficacy with photodynamic therapy in a three-dimensional model for micrometastatic ovarian cancer. Cancer Res 70: 9319–9328 14. Bulin A-L, Broekgaarden M, Simeone D, Hasan T (2019) Low dose photodynamic therapy harmonizes with radiation therapy to induce beneficial effects on pancreatic heterocellular spheroids. Oncotarget 10:2625–2643 15. Madsen SJ, Sun C-H, Tromberg BJ, Cristini V, De Magalha˜es N, Hirschberg H (2006) Multicell tumor spheroids in photodynamic therapy. Lasers Surg Med 38:555–564 16. Celli JP, Rizvi I, Evans CL, Abu-Yousif AO, Hasan T (2010) Quantitative imaging reveals heterogeneous growth dynamics and treatment-dependent residual tumor distributions in a three-dimensional ovarian cancer model. J Biomed Opt 15:051603 17. Rizvi I, Bulin A-L, Briars E, Anbil S, Hasan T (2016) Chapter 11. Mind the gap: 3D models in photodynamic therapy. In: Photodynamic medicine, pp 197–221 18. Foster TH, Hartley DF, Nichols MG, Hilf R (1993) Fluence rate effects in photodynamic therapy of multicell tumor spheroids. Cancer Res 53:1249–1254 19. Bigelow CE, Mitra S, Knuechel R, Foster TH (2001) ALA- and ALA-hexylester-induced protoporphyrin IX fluorescence and distribution in multicell tumour spheroids. Br J Cancer 85:727–734 20. Finlay JC, Mitra S, Patterson MS, Foster TH (2004) Photobleaching kinetics of Photofrin in vivo and in multicell tumour spheroids indicate two simultaneous bleaching mechanisms. Phys Med Biol 49:4837–4860 21. Georgakoudi I, Foster TH (1998) Effects of the subcellular redistribution of two nile blue

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derivatives on photodynamic oxygen consumption. Photochem Photobiol 68:115–122 22. Glidden MD, Celli JP, Massodi I, Rizvi I, Pogue BW, Hasan T (2012) Image-based quantification of benzoporphyrin derivative uptake, localization, and Photobleaching in 3D tumor models, for optimization of PDT parameters. Theranostics 2:827–839 23. Alemany-Ribes M, Garcı´a-Dı´az M, Busom M, Nonell S, Semino CE (2013) Toward a 3D cellular model for studying in vitro the outcome of photodynamic treatments: accounting for the effects of tissue complexity. Tissue Eng Part A 19:1665–1674 24. Broekgaarden M, Bulin A-L, Frederick J, Mai Z, Hasan T (2019) Tracking photodynamic- and chemotherapy-induced redox state perturbations in 3D culture models of pancreatic cancer: a tool for identifying therapyinduced metabolic changes. J Clin Med 8:1399 25. Jaganathan H, Gage J, Leonard F, Srinivasan S, Souza GR, Dave B, Godin B (2014) Threedimensional in vitro co-culture model of breast tumor using magnetic levitation. Sci Rep 4: 6468 26. Åkerfelt M, Bayramoglu N, Robinson S, Toriseva M, Schukov H-P, H€arm€a V, Virtanen J, Sormunen R, Kaakinen M, Kannala J et al (2015) Automated tracking of tumorstroma morphology in microtissues identifies functional targets within the tumor microenvironment for therapeutic intervention. Oncotarget 6:30035–30056 27. Robinson S, Guyon L, Nevalainen J, Toriseva M, Åkerfelt M, Nees M (2015) Segmentation of image data from complex organotypic 3D models of cancer tissues with Markov random fields. PLoS One 10: e0143798 28. Pankova D, Chen Y, Terajima M, Schliekelman MJ, Baird BN, Fahrenholtz M, Sun L, Gill BJ, Vadakkan TJ, Kim MP et al (2016) Cancerassociated fibroblasts induce a collagen crosslink switch in tumor stroma. Mol Cancer Res 14:287–295 29. Roberts GC, Morris PG, Moss MA, Maltby SL, Palmer CA, Nash CE, Smart E, Holliday DL, Speirs V (2016) An evaluation of matrixcontaining and humanised matrix-free 3-dimensional cell culture systems for studying breast cancer. PLoS One 11:e0157004 30. Zhu L, Fan X, Wang B, Liu L, Yan X, Zhou L, Zeng Y, Poznansky MC, Wang L, Chen H et al (2017) Biomechanically primed liver microtumor array as a high-throughput mechanopharmacological screening platform for stromareprogrammed combinatorial therapy. Biomaterials 124:12–24

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31. Bulin A-L, Broekgaarden M, Hasan T (2017) Comprehensive high-throughput image analysis for therapeutic efficacy of architecturally complex heterotypic organoids. Sci Rep 7: 16645 32. Obaid G, Bano S, Mallidi S, Broekgaarden M, Kuriakose J, Silber Z, Bulin A-L, Wang Y, Mai Z, Jin W et al (2019) Impacting pancreatic cancer therapy in heterotypic in vitro organoids and in vivo tumors with specificity-tuned, NIR-activable photoimmuno-nanoconjugates:

towards conquering desmoplasia? Nano Lett 19:7573–7587 33. Wu X, Liu H, Liu J, Haley KN, Treadway JA, Larson JP, Ge N, Peale F, Bruchez MP (2003) Immunofluorescent labeling of cancer marker Her2 and other cellular targets with semiconductor quantum dots. Nat Biotechnol 21: 41–46 34. Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Systems Man Cybernetics 9:62–66

Chapter 8 Generating Large Numbers of Pancreatic Microtumors on Alginate-Gelatin Hydrogels for Quantitative Imaging of Tumor Growth and Photodynamic Therapy Optimization Nazareth Milagros Carigga Gutierrez, Tristan Le Clainche, Jean-Luc Coll, Lucie Sancey, and Mans Broekgaarden Abstract The emerging use of 3D culture models of cancer has provided novel insights into the therapeutic mechanisms of photodynamic therapy on a mesoscopic scale. Especially microscale tumors grown on scaffolds of extracellular matrix can provide statistically robust data on the effects of photosensitizers and photodynamic therapy by leveraging high-throughput imaging-based assays. Although highly informative, the use of such 3D cultures can be impractical due to the high costs and inter-batch variability of the extracellular matrix scaffolds that are necessary to establish such cultures. In this study, we therefore provide a protocol to generate inexpensive and defined hydrogels composed of sodium alginate and gelatin that can be used for culturing 3D microtumors in a manner that is compatible with state-of-the-art imaging assays. Our results reveal that the alginate-gelatin hydrogels can perform similarly to a commercially available ECM scaffold in terms of facilitating microtumor growth. We then applied these microtumor models to quantify the uptake and dark toxicity of benzoporphyrin derivative encapsulated in liposomes with either an anionic or a cationic surface charge. The results indicate that cationic liposomes achieve the highest level of uptake in the microtumors, yet also exert minor toxicity. Moreover, we reveal that there is typically a significant positive correlation between microtumor size and liposome uptake. In conclusion, alginate-based hydrogels are inexpensive and effective scaffolds for 3D culture models of cancer, with versatile applications in research toward photodynamic therapy. Key words Liposomal drug delivery, 3D cultures, Organoids, Spheroids, Extracellular matrix, Benzoporphyrin derivative, Toxicology, Drug uptake, Lipid nanoparticles, Fluorescence microscopy, Image analysis

1

Introduction As the pathway from the discovery of new therapeutic agents to clinical trials is a very expensive and high-risk process, robust experimental models are essential at the preclinical phase to obtain the most accurate data for further translational research. As extensively reviewed by others, three-dimensional cultures are appropriate

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_8, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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experimental models as they bridge the gap between conventional 2D cell cultures and in vivo experiments, as they recapitulate the 3D architecture, biochemical and biomechanical cues, as well as cellcell interactions more faithfully than 2D cultures [1]. In terms of nomenclature, it was proposed that 3D cultures of cancer can be classified as either cancer organoids (when derived directly from patients) or spheroids (when derived from cell lines) [2]. However, we propose to uniformly use the term “microtumors” for these 3D cultures, as this term neither implies the organ-like structures of the objects, nor implies that the objects form spherical structures as this is often not the case [3]. Due to this unique combination of biological relevance and capacity for high-throughput analysis, 3D cultures of cancer are emerging as highly informative models within the field of photodynamic therapy (PDT). In 3D cultures of ovarian cancer grown on commercially available extracellular matrix (ECM) hydrogels, Celli et al. used quantitative image analysis to characterize how PDT and chemotherapies affect the size distributions and viabilities of large numbers of microtumors [4]. Rizvi et al. used similar ovarian microtumors to demonstrate a synergy between neoadjuvant PDT followed by carboplatin chemotherapy: PDT was shown to disrupt the microtumor integrity, allowing subsequent carboplatin to penetrate deeper into the masses [5]. ECM hydrogel-adherent ovarian microtumors were also used by Rahmanzadeh et al. to investigate the efficacy of novel liposomes carrying photoimmunoconjugates [6]. Combining 3D culture models with high-throughput assays has provided new insights into possible correlations between microtumor size and treatment susceptibility [7, 8]. Using ECM hydrogel-adherent cultures of pancreatic cancer cells grown in the presence of cancer-associated fibroblasts, we recently discovered that these stromal cells influence the redox state of pancreatic microtumors and promote resistance to both PDT and oxaliplatin [9]. More simple 3D culture models, in which cells are grown in non-adherent U-bottom well-plates, have also generated useful insights in the efficacy of radiotherapy-PDT combinations [10], photoimmunoliposomes [11], cyclodextrin-based photosensitizer nanocarriers [12], and the effect of stroma-cancer cell interactions on the efficacy of PDT [13]. Using more complex models of micrometastatic ovarian cancer in which peritoneal flow of ascites was mimicked, Rizvi et al. elucidated that flow promotes an epithelial-to-mesenchymal transition in the ovarian microtumors [14]. A subsequent study by Nath et al. demonstrated that the effects of flow-induced shear stress on ovarian microtumors caused resistance to carboplatin, but not to PDT [15]. Although this list is far from complete, it provides a glimpse into the possibilities of 3D culture models in PDT research, providing scientific discoveries that could not be made with 2D cultures.

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Throughout the studies listed above, the most informative models were the hydrogel-based adherent microtumor cultures that were established using methods similar to the liquid-overlay technique. Such cultures generated hundreds to thousands of individual microtumors per experiment, which could be individually analyzed with low-magnification fluorescence-based assays and automated high-throughput quantitative image analysis [3, 4, 16, 17]. In almost all cases, the investigators used a commercially available, growth factor-reduced ECM hydrogels as the culture scaffold, composed mostly of laminin and collagen IV [18]. Such hydrogels are highly practical as they solidify at 37
C without requiring catalysts, yet its use for 3D culture is not without challenges. First of all, most of these products have substantial batchto-batch variety that, although not always visible based on the morphology of the microtumors, can exert a dramatic influence on the microtumor treatment response. For example, during routine lot comparisons of commercially available ECM hydrogels, we have previously determined the median viability of MIA PaCa-2microtumors following a 72-h exposure to 1 mM oxaliplatin at 66%, 32%, 50%, and 45% in four different hydrogel lots (not published). Secondly these ECM solutions are generally fairly expensive; using the protocols listed in the abovementioned references, in which 250 μL of ECM solution is used for each well of a 24-well plate, a 10 mL vial yields less than two 24-well plates. Thus, for culturing microtumors, there is a need for hydrogels that are less expensive, easy to prepare, and based on more defined mixtures that are less susceptible to batch-to-batch heterogeneity. In this context, we explored the use of sodium alginate-based hydrogels for culturing microtumors in accordance with the liquidoverlay method. Alginates are polysaccharides typically extracted from brown seaweeds, and are widely used in the food industry and as biomaterials. They readily form hydrogels by ionic gelation with high concentrations of Ca2+, Sr2+, or Ba2+ [19]. Previous studies reported that human intestinal organoids derived from pluripotent stem cells could be cultured in vitro and undergo epithelial differentiation in a minimally supportive hydrogel containing only alginate, where best spheroid survival was observed with 1% and 2% alginate gels. Rheology measurements of the alginate gels (0.5–4%) demonstrated that the storage and loss moduli of 0.5% alginate were most similar to commercial ECM hydrogels [20]. As alginate hydrogels can be easily supplemented with extracellular matrix components to improve cellular adhesion and microtumor growth, a hybrid alginate hydrogel with a low percentage of gelatin (i.e., denatured collagen) was prepared. In comparison to commercial ECM mixtures, the alginate-gelatin hydrogels are inexpensive, with an estimated cost that is 100-fold lower. Moreover, the hydrogels are compatible with the aforementioned high-content imaging assays to rapidly quantify the dark toxicity, uptake, and treatment

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effects on hundreds to thousands of individual microtumors per experimental condition. In this protocol, we provide the necessary steps to prepare alginate-gelatin hydrogels to culture PANC-1 pancreatic cancer microtumors. In addition, we demonstrate their compatibility with high-content imaging assays by exploring the uptake and toxicity of various lipid nanocarriers for the delivery of the photosensitizer benzoporphyrin derivative.

2 2.1

Materials Plate Coating

1. Poly-D-lysine hydrobromide (30–70 kDa) 0.5 mg/mL in ultrapure water. 2. Plastic, tissue culture-treated 24-well culture plates.

2.2 Hydrogel Preparation

1. Phosphate-buffered saline (pH 7.4). 2. Low-viscosity sodium alginate (C6H9NaO7) from brown algae, 4% solution in phosphate-buffered saline. 3. Gelatin 2% solution in phosphate-buffered saline or ultrapure water. 4. Calcium chloride (CaCl2), 100 mM in ultrapure water. 5. Sterile cellulose filters 0.22 μm. 6. 50 mL Syringe. 7. 50 mL Sterile tubes for each solution. 8. 25 mL Sterile tubes for each batch. 9. Magnetic stirrer. 10. Autoclave, 121
C, 15 psi of pressure.

2.3 Microtumor Culture

1. PANC-1 human pancreatic cancer cell line. 2. Dulbecco’s modified Eagle’s medium (DMEM), supplemented with 10% fetal bovine serum (FBS), penicillin (100 U/mL), and streptomycin (100 mg/mL). 3. Cell culture incubator, 37
C, 5% CO2.

2.4 Liposome Preparation

Liposomes were prepared as described previously [21]. It is not the focus of this protocol and will therefore not be discussed in detail here. In this exploratory study, we evaluated several liposome formulations in order to demonstrate the feasibility of our alginategelatin hydrogel-based pancreatic microtumor model. Three types of liposomes were prepared at a 5 mM lipid concentration, composed of cholesterol, 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC) and 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), and stabilized by either cationic 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), anionic 1,2-dioleoyl-sn-glycero-3-

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Table 1 Characteristics of the BPD-containing liposomes used throughout this protocol

Liposome batch Composition (mol%)

Size (mean  st. dev.)

PE-BPD

DSPC:Chol:DOPC:DOPE (25:30:25:20)

132.7  2.2

1.57 * 1012  6.95 * +6.38  0.48 1010

PG-BPD

DSPC:Chol:DOPC:DOPG (25:30:25:20)

158.9  1.6

1.66 *1012  1.69 * 1011

PEG-BPD DSPC:Chol:DOPC:DSPEPEG (43:30:25:2)

111.2  1.7

1.65 * 1012  1.12 * +2.91  0.74 1011

Concentration (mean  st. dev.)

Zeta potential (mV  st. dev.)

5.53  1.05

phospho-(10 -rac-glycerol) (DOPG), or PEG2000 conjugated 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy (polyethylene glycol)-2000] (DSPE-PEG) phospholipids. The photosensitizer benzoporphyrin derivative (BPD/verteporfin) was added to the lipid film during the preparation process at a lipid: BPD ratio of 0.008. The three batches are described in Table 1, and characterized using nanoparticle tracking analysis and electrophoretic light scattering spectroscopy. 2.5 Quantification of Liposome Uptake

1. Fully supplemented cell culture medium (DMEM). 2. Phosphate-buffered saline (pH 7.4). 3. A fluorescence microscope, equipped with a 5 or 10 objective and a 405 nm excitation source. 4. Image analysis software: In this protocol we used MATLAB 2016b (Mathworks, Natick, MA) and the custom-built CALYPSO image analysis code that was previously described [3].

2.6 Quantification of Liposome Toxicity

1. Calcein AM, 4 mM, in DMSO. 2. Propidium iodide, 1 mg/mL (1.41 mM). 3. Fully supplemented cell culture medium (DMEM). 4. Formalin 4% in sterile phosphate-buffered saline (pH 7.4). 5. Triton X-100, 0.5% (v/v), in sterile phosphate-buffered saline (pH 7.4). 6. A fluorescence microscope, equipped with a 5 or 10 objective and a 488 nm and 560 nm excitation source. 7. Image analysis software: In this protocol we used MATLAB 2016b and the custom-built CALYPSO image analysis code that was previously described [3].

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Methods

3.1 Preparation of Stock Solutions

1. Prepare the 100 mM CaCl2 solution by dissolving 735 mg CaCl2 dihydrate in 50 mL ultrapure water. 2. Preparing the 4% (w/v) alginate solution: Prepare 50 mL of PBS in a heat-resistant flask and place it on a magnetic stirrer at a speed at which a vortex can be seen. Then slowly add 2 g of sodium alginate to obtain a 4% (w/v) alginate solution. Leave the solution to fully dissolve at room temperature for about 1–2 h. 3. Preparing the 2% (w/v) gelatin solution: Prepare 50 mL of ultrapure water in a heat-resistant flask and place it on a magnetic stirrer at a speed at which a vortex can be seen. Then slowly add 1 g of gelatin to obtain a 2% (w/v) gelatin solution. Leave the solution to fully dissolve at 50
C for about 1–2 h. 4. Prepare the 0.5 mg/mL poly-D-lysine solution (powder suitable for cell culture) by dissolving the powder in ultrapure water that was previously filtered as explained below. 5. Sterilize the CaCl2 and ultrapure water using the 0.22 μm filter and a syringe (without needle). Pass the solutions through the filter to sterilize them. Remove the plunger of the syringe, put the filter on the tip of the syringe, and put the syringe with the filter above a new tube to collect the sterile solution. 6. Sterilize the alginate and gelatin solution by autoclaving. 7. Store the solutions at 4
C. The solutions are stable for at least 3 months.

3.2

Plate Coating

1. To prevent the alginate gels from detaching from the cell culture plastics during 3D culture experiments, a coating with poly-D-lysine is necessary. Add 250 μL of poly-D-lysine 0.5 mg/mL to each well of a 24-well plate, and incubate for 1 h. 2. Recollect the poly-D-lysine in a sterile storage tube. The solution can be reused at least three times.

3.3 Hydrogel Fabrication

1. Prepare a working solution of hydrogel mix that contains 2% alginate and 0.5% gelatin. The total volume to prepare has to be calculated based on a required volume of 125 μL/well (62.5 μL of 4% (w/v) alginate +31.5 μL of 2% (w/v) gelatin). See Notes 1 and 2 for more details on why these conditions were selected. 2. Add 125 μL of the alginate-gelatin working solution to each well, and verify the whole bottom surface of the plate is covered by the solution. Gel mix should cover very easily the whole surface after incubation with poly-D-lysine (Fig. 1).

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Fig. 1 Schematic overview of the alginate-gelatin hydrogel 3D culture method as described in this protocol

3. Polymerize the alginate by carefully adding 100 μL of CaCl2 100 mM on the top of the hydrogel mix (Fig. 1). See Note 3. 4. Remove any unbound CaCl2 by very gently washing the hydrogels with PBS. 5. Let the solution sit in a horizontal position without moving for 10 min at room temperature until the gels are polymerized. See Notes 4 and 5. 3.4 Microtumor Culture

1. Maintain the PANC-1 cells in monolayer in a T75 flask in the DMEM-enriched medium. Subculture the cells at a ratio of 1: 10 every 3–4 days when they have reached the confluence to maintain their growth. 2. Prepare a solution containing 15,000 PANC-1 cells/mL on the day of the experiment. Consider a final volume of 500 μL for each well. 3. Seed 500 μL of the PANC-1 suspension to each well (7500 cells/well). Add the cell suspension slowly, against the wall of the well to not disturb the hydrogels. 4. Incubate the plate(s) at 37
C, 5% CO2, for 7 days. Typical growth curves can be observed in Fig. 2. Refreshing the culture medium can be done after 10 days of culture, or as desired. This should be done very gently to not disturb the hydrogels. 5. At different time points in this growth curve, the microtumor cultures can be used to study the uptake and toxicity of photosensitizers (Subheadings 3.5 and 3.6, respectively), or to study the efficacy of PDT (Subheading 3.7).

3.5 Liposome Uptake Assay

1. Prepare appropriate dilutions of the liposome suspensions in fully supplemented culture medium. In this protocol we prepared a range of 0–250 μM, referring to the final lipid

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Fig. 2 The performance of alginate-gelatin hydrogels at different concentrations of alginate (1%, 2%, and 3%) and 0.5% of gelatin in comparison to Matrigel. Logistic growth curves of PANC-1 microtumors grown on (a) 1% w/v alginate and 0.5% w/v gelatin, (b) 2% w/v alginate and 0.5% w/v gelatin, and (c) 3% w/v alginate and 0.5% w/v gelatin. Depicted are the mean and standard error of the mean of 30–200 microtumors, obtained from three technical repeats

concentration. With a BPD:lipid ratio of 0.008, the final BPD concentrations were thus in the range of 0–2 μM. Prepare a sufficient amount corresponding to 500 μL per well for each experimental condition. 2. Recuperate the plate with the 7-day-old PANC-1 microtumors from the incubator. Transfer 500 μL of each liposome dilution into a different well containing the microtumors. One should note that this causes a twofold dilution in the final liposome concentration. 3. Incubate the plate for 24 h. 4. Recuperate the plate after incubation and collect all the medium with a micropipette: carefully tilt the plate at a ~45
angle to create a pool of medium that can be easily removed from the plate without disturbing or aspirating the microtumors. 5. Wash the microtumors with 0.5 mL of PBS, and then add 0.5 mL of fresh PBS. 6. Image the microtumors using a 5 or 10 objective on a (confocal) fluorescence microscope. Here, the zoom was modified to acquire 1024  1024 images with a pixel size of 1.38 μm. In order to maximize the signal collection, the pinhole of a confocal setup should be opened at its maximum. 7. Detect the emission of BPD using λex: 405 nm and λem: 600–740 nm. 8. Set the channel saturation adjusting the gain with the highest concentration of the treatments. 9. For each field of view acquire at least two bright-field images per well. Images should preferably be taken in the center of the well.

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Toxicity Analysis

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1. Prepare the total killing control. Remove cell culture medium from a designated well, and fix the microtumors for 5 min in 500 μL of 4% (w/v) buffered formalin at room temperature. Remove the formalin and permeabilize the microtumors for 30 min at 37
C in 500 μL of 0.5% (v/v) Triton X-100. Subsequently remove the Triton X-100 and store the microtumors under PBS until the plate is ready to be stained. 2. Prepare the live/dead staining mixture, containing 2 μM of calcein and 3 μM propidium iodide in culture medium, and prepare a sufficient volume to add 0.5 mL to each well of the plate (e.g., for a 24-well plate, prepare a 13 mL staining mixture). 3. Remove the PBS from the wells of the culture plate (which was added in step 5 of Subheading 3.5) and replace it with 0.5 mL of the live/dead staining mix. 4. Incubate for 1 h at standard culture conditions before imaging. 5. Image the microtumors using a 5 or 10 objective on a (confocal) fluorescence microscope. Here, we acquired 512  512 px images with a pixel size of 2.76 μm. In order to maximize the signal collection, the pinhole of a confocal setup should be opened at its maximum. 6. Detect the emission of calcein using λex: 488 nm and λem: 500–540 nm. 7. Detect the emission of propidium iodide λex: 560 nm and λem: 600–650 nm. 8. For each field of view, also acquire a bright-field image using the 560 nm excitation. 9. Adjust the gain of the fluorescence detection using the no treatment and total killing controls. Set the detector gain for propidium iodide using the total killing control, whereby a maximum signal is acquired without saturating the detector. Repeat this step for the calcein emission using the no treatment controls. The parameters should be kept identical throughout the entire imaging session. Note that there should be no detectable calcein emission in the total killing controls. 10. Record at least two images for each treatment, preferably taken at the center of the well where the hydrogel is best aligned with the microscope’s focal plane.

3.7 Photodynamic Therapy

1. For the treatment of the microtumor cultures with photodynamic therapy, the following steps can be performed upon completing Subheading 3.4 of this protocol. 2. Recuperate the plate with the 7-day-old PANC-1 microtumors from the incubator. Transfer 500 μL of the desired photosensitizer solution into the wells containing the microtumors. One

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should note that this causes a twofold dilution in the final photosensitizer concentration. 3. Incubate the plate at standard culture conditions for 1–24 h as desired, and then wash the plate once with 1 mL PBS. 4. Irradiate the plate with an appropriate light source that excites the photosensitizer, at an appropriate light dose (typically in the range of 0–100 J/cm2), and an appropriate light fluence (typically in the range of 10–250 mW/cm2). This can be done at room temperature. Return the plate to the standard culture conditions. 5. The efficacy of the treatment can be determined using the protocol in Subheading 3.6, at the desired time intervals posttreatment, such as 24 h, 48 h, 72 h, or even 7 days posttreatment [8]. 3.8 Data Analysis and Visualization

1. Data should be organized in such a way that each set of images corresponding to different treatments are in different folders. 2. Here, the image analysis was performed using a custom-built MATLAB code for automated image analysis that was adapted from Bulin et al. (2017) [3], which is available upon request. The code is further detailed in the abovementioned publication and will not be further detailed here. The bright-field images and the masked fluorescence images are depicted in Fig. 3a. 3. For the liposome uptake analysis, calculate the mean fluorescence emission of the microtumors per experimental conditions. Plot the mean fluorescence intensity as a function of lipid concentration to obtain dose-response curves (Fig. 3b). Additional plots can be generated to uncover potential correlations between microtumor size and (liposomal) photosensitizer uptake (Fig. 3c), or to uncover correlations between liposome surface charge and uptake (Fig. 3d). 4. For the liposome toxicity analysis, extract the mean viability, microtumor size, and mean dead signal (necrosis) per organoid. To quantify the percentage of viability, data can be normalized to the no treatment controls. To quantify the percentage of necrosis, the propidium iodide emission can be normalized to the total killing controls. The data can be plotted as dose-response curves as shown previously [8, 9]. Here, the toxicities of only the highest concentration of the liposomes were compared, provided in box-whisker plots (Fig. 4). See Note 6. For follow-up biomolecular investigations, see Note 7.

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Fig. 3 Quantification of the uptake of liposome-encapsulated BPD in PANC-1 microtumors. (a) Bright-field images of 7-day-old PANC-1 microtumors and masked BPD fluorescence images during the image analysis procedure. Scale bar: 200 μm. (b) The BPD emission from microtumors incubated with varying concentrations of PE-BPD (red), PG-BPD (green), and PEG-BPD (blue). Each data point depicts the mean and its 95% CI, obtained from 30 to 80 microtumors (two experimental repeats). The data was fitted using one-phase association equations. (c) The uptake of the BPD-containing liposomes (250 μM lipid concentration) plotted as a function of the microtumor size. A Pearson correlation analysis was performed to determine whether the positive correlation between microtumor size and liposome uptake was statistically significant. (d) The uptake of the BPD-containing liposomes by microtumors plotted as a function of the liposome surface charge, which was statistically analyzed using a Pearson correlation analysis

4

Notes 1. Regarding the supplementation of the alginate hydrogels with 0.5% (w/v) gelatin: studies on 3D bioprinting showed that hydrogels prepared with 3.25% (w/v) sodium alginate and 4% (w/v) gelatin showed higher printability and cell viability for non-small cell lung cancer microtumors from patient-derived xenograft cells co-cultured with cancer-associated fibroblasts [22]. As alginate is largely inert, the addition of gelatin provides cells/microtumors a substrate to adhere to, such as the RGD motif. In order to optimize the concentration of alginate and gelatin, we tested several hydrogel compositions to culture PANC-1 microtumors (Fig. 5). Regarding the gelatin concentration, we noticed that on gels containing no gelatin, the microtumors did not adhere and drifted on the alginate hydrogels. With concentrations of gelatin ranging from 0.1 to 0.5%

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Fig. 4 Quantification of the toxicity of the BPD-containing liposomes in PANC-1 microtumors based on (a) microtumor viability, (b) normalized microtumor size based on the bright-field images, and (c) microtumor necrosis in which the total killing (TK) control was used to quantify the percentage. Depicted are box-whisker plots with the median, 25th and 75th percentile, and 90% confidence interval of 20–30 microtumors from two experimental repeats. The microtumor viability and size were statistically analyzed using a one-way ANOVA and Dunnett’s multiple comparisons test, and significant differences compared to the no treatment (NT) control group are indicated with asterisks ( p < 0.01). The microtumor necrosis was statistically analyzed using Kruskal-Wallis test and a Dunn’s multiple comparisons test. Significant differences are indicated with asterisks ( p < 0.001)

Fig. 5 PANC-1 microtumor development after 3 days of growth on the alginate-gelatin hydrogels at either 1% or 2% (w/v) alginate, supplemented with either 0%, 0.1%, 0.2%, 0.5%, or 1% (w/v) of gelatin. Depicted are representative images from 2 experimental repeats. The images were taken using a confocal laser scanning microscope in bright-field mode, using a 10 magnification. Scale bar: 200 μm

(w/v), the PANC-1 cells were able to adhere and form microtumors, with the largest nodules observed at a concentration of 0.5% (w/v). At a concentration of 1% gelatin, the PANC-1 microtumors aggregated and formed extremely large masses that prevented accurate image analysis. 2. With respect to the alginate concentration, we tested concentration in the 1–3% (w/v) range due to the comparable stiffness of such hydrogels compared to Matrigel [20]. Hydrogels of

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1–3 (w/v) alginate and 0.5% (w/v) gelatin were all suitable to generate PANC-1 microtumors. Upon comparing the PANC1 microtumor growth curves, we determined that hydrogels of 2% (w/v) alginate and 0.5% (w/v) gelatin best mimicked the growth of PANC-1 microtumors on Matrigel. 3. Regarding the cross-linking with CaCl2: The ionic crosslinking parameters differed substantially among the reviewed alginate gel formation protocols. For a low-viscosity alginate powder diluted in water or PBS, where spheroids were suspended in the alginate solution, ionic cross-linking was performed using droplets of 2% (w/v) CaCl2 deposited at the bottom of the wells before the alginate solution containing spheroids was added [20]. Bioprinted scaffolds containing 3.25% (w/v) sodium alginate and 4% (w/v) gelatin were cross-linked after printing with 100 mM CaCl2 for 3 min [22]. The latter protocol appeared most suited for our application, which is why we also chose 100 mM CaCl2 for crosslinking the alginate-gelatin hydrogels. In addition, 100 mM CaCl2 was shown to be well tolerated by intestinal stem cells, lung cancer cells, and cancer-associated fibroblast [20, 22]. We tested the addition of 50 μL of 100 mM CaCl2 on the bottom or on the top the gel mix, observing that the volume was not enough to polymerize the whole volume of the mix. We then tested the addition of 100 μL of 100 mM CaCl2 below the gel mix, on top of the gel mix, or 50 μL on the bottom combined with 50 μL on the top of the gel. In all cases, the gel appeared to be cross-linked correctly. Finally, we decided to use 100 μL of CaCl2 on top of the gel mix as was the most practical solution. 4. Alginate-gelatin mix and CaCl2 solutions should be maintained at 4
C right after its preparation and during the well seeding to improve the cationic polymerization with CaCl2. It has been postulated that the cold reduces the reactivity of the ionic cross-linkers (i.e., Ca2+), making the cross-linking slower, which overall improves the uniformity of the hydrogel [23]. 5. Although it was initially expected that the CaCl2 solution could be washed away after the cross-linking, we noticed that the solution is completely incorporated into the hydrogel. This brings the total hydrogel volume to 225 μL, and dilutes the actual alginate and gelatin concentrations. The actual percentages are 1.11% alginate and 0.27% gelatin. 6. In the results presented here, the cationic BPD-PE liposomes exerted some mild toxicity, as reflected in a minute yet significant decrease in overall microtumor viability (98.5% for the NT, versus 96.6 for BPD-PE). Please note that a 100% viability is not typically seen due to the presence of necrotic microtumor

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cores. The toxicity of BPD-PE was also reflected in the extent of necrosis, which was 2.2% in the NT versus 4.8% for the BPDPE-treated microtumors. This toxicity can be attributed to the non-PEGylated nature of these cationic liposomes, which are known to perturb mitochondrial membrane function [24]. 7. Harvesting microtumors is possible for biomolecular investigations such as immunofluorescence microscopy, immunoblotting, and qPCR. The alginate hydrogels should dissolve in solutions containing high concentrations of calcium chelators, such as 100 mM EDTA or 100 mM sodium citrate.

Acknowledgments This study was funded by the Phospholipid Research Center (Heidelberg, Germany), project number MAB-2020-080/1-1. References 1. Pampaloni F, Reynaud EG, Stelzer EHK (2007) The third dimension bridges the gap between cell culture and live tissue. Nat Rev Mol Cell Biol 8:839–845 2. Baker LA, Tiriac H, Clevers H et al (2016) Modeling pancreatic cancer with organoids. Trends Cancer 2:176–190 3. Bulin A-L, Broekgaarden M, Hasan T (2017) Comprehensive high-throughput image analysis for therapeutic efficacy of architecturally complex heterotypic organoids. Sci Rep 7: 16645 4. Celli JP, Rizvi I, Evans CL et al (2010) Quantitative imaging reveals heterogeneous growth dynamics and treatment-dependent residual tumor distributions in a three-dimensional ovarian cancer model. J Biomed Opt 15: 051603 5. Rizvi I, Celli JP, Evans CL et al (2010) Synergistic enhancement of carboplatin efficacy with photodynamic therapy in a three-dimensional model for micrometastatic ovarian cancer. Cancer Res 70:9319–9328 6. Rahmanzadeh R, Rai P, Celli JP et al (2010) Ki-67 as a molecular target for therapy in an in vitro three-dimensional model for ovarian cancer. Cancer Res 70:9234–9242 7. Anbil S, Rizvi I, Celli JP et al (2013) Impact of treatment response metrics on photodynamic therapy planning and outcomes in a threedimensional model of ovarian cancer. J Biomed Opt 18:098004 8. Broekgaarden M, Rizvi I, Bulin A-L et al (2018) Neoadjuvant photodynamic therapy augments immediate and prolonged oxaliplatin

efficacy in metastatic pancreatic cancer organoids. Oncotarget 9:13009–13022 9. Broekgaarden M, Anbil S, Bulin A-L et al (2019) Modulation of redox metabolism negates cancer-associated fibroblasts-induced treatment resistance in a heterotypic 3D culture platform of pancreatic cancer. Biomaterials 222:119421 10. Bulin A-L, Broekgaarden M, Simeone D et al (2019) Low dose photodynamic therapy harmonizes with radiation therapy to induce beneficial effects on pancreatic heterocellular spheroids. Oncotarget 10:2625–2643 11. Obaid G, Bano S, Mallidi S et al (2019) Impacting pancreatic cancer therapy in heterotypic in vitro organoids and in vivo tumors with specificity-tuned, NIR-activable photoimmunonanoconjugates: towards conquering desmoplasia? Nano Lett 19:7573–7587 12. Yakavets I, Guereschi C, Lamy L et al (2020) Cyclodextrin nanosponge as a temoporfin nanocarrier: balancing between accumulation and penetration in 3D tumor spheroids. Eur J Pharm Biopharm 154:33–42 13. Broekgaarden M, Alkhateeb A, Bano S et al (2020) Cabozantinib inhibits photodynamic therapy-induced auto- and paracrine MET signaling in heterotypic pancreatic microtumors. Cancers 12:1401 14. Rizvi I, Gurkan UA, Tasoglu S et al (2013) Flow induces epithelial-mesenchymal transition, cellular heterogeneity and biomarker modulation in 3D ovarian cancer nodules. Proc Natl Acad Sci U S A 110:E1974–E1983

3D Culture Models on Alginate-Gelatin Hydrogels 15. Nath S, Pigula M, Khan AP et al (2020) Flowinduced shear stress confers resistance to carboplatin in an adherent three-dimensional model for ovarian cancer: a role for EGFRtargeted Photoimmunotherapy informed by physical stress. J Clin Med 9:924 16. Celli JP, Rizvi I, Blanden AR et al (2014) An imaging-based platform for high-content, quantitative evaluation of therapeutic response in 3D tumour models. Sci Rep 4:3751 17. Broekgaarden M, Bulin A-L, Frederick J et al (2019) Tracking photodynamicand chemotherapy-induced redox-state perturbations in 3D culture models of pancreatic cancer: a tool for identifying therapy-induced metabolic changes. J Clin Med 8:1399 18. Caliari SR, Burdick JA (2016) A practical guide to hydrogels for cell culture. Nat Methods 13: 405–414 19. Andersen T, Auk-Emblem P, Dornish M (2015) 3D cell culture in alginate hydrogels. Microarrays 4:133–161

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20. Capeling MM, Czerwinski M, Huang S et al (2019) Nonadhesive alginate hydrogels support growth of pluripotent stem cell-derived intestinal organoids. Stem Cell Rep 12: 381–394 21. Broekgaarden M, de Kroon AIPM, Van Gulik TM et al (2013) Development and in vitro proof-of-concept of interstitially targeted zinc- phthalocyanine liposomes for photodynamic therapy. Curr Med Chem 21:377–391 22. Mondal A, Gebeyehu A, Miranda M et al (2019) Characterization and printability of sodium alginate -gelatin hydrogel for bioprinting NSCLC co-culture. Sci Rep 9:19914 23. Lee KY, Mooney DJ (2012) Alginate: properties and biomedical applications. Prog Polym Sci 37:106–126 24. Roursgaard M, Knudsen KB, Northeved H et al (2016) In vitro toxicity of cationic micelles and liposomes in cultured human hepatocyte (HepG2) and lung epithelial (A549) cell lines. Toxicol In Vitro 36:164–171

Chapter 9 The Chicken Embryo Chorioallantoic Membrane as an In Vivo Model for Photodynamic Therapy Jaroslava Joniova´ and Georges Wagnie`res Abstract For many decades the chicken embryo chorioallantoic membrane (CAM) has been used for research as an in vivo model in a large number of different fields, including toxicology, bioengineering, and cancer research. More specifically, the CAM is also a suitable and convenient model system in the field of photodynamic therapy (PDT), mainly due to the easy access of its membrane and the possibility of grafting or growing tumors on the membrane and, interestingly, to study the PDT effects on its dense vascular network. In addition, the CAM is simple to handle and cheap. Since the CAM is not innervated until later stages of the embryo development, its use in research is simplified compared to other in vivo models as far as ethical and regulatory issues are concerned. In this review different incubation and drug administration protocols of relevance for PDT are presented. Moreover, data regarding the propagation of light at different wavelengths and CAM development stages are provided. Finally, the effects induced by photobiomodulation on the CAM angiogenesis and its impact on PDT treatment outcome are discussed. Key words Chicken embryo chorioallantoic membrane, CAM, Photodynamic therapy, PDT, Model system, Vascular network, Angiogenesis, Xenograft

1

Introduction In the field of photodynamic therapy (PDT), relevant in vivo model organisms enabling to study the vascular effects of this treatment are of high interest. In many cases, rodents embody in vivo cancer models used for research in this field. However, the use of such models rises ethical, regulatory questions and concerns since these animals are frequently subject to tumor cell injections or tumor grafting. Importantly, such studies are frequently inducing pain caused by growing tumors and following PDT treatment. Also, living in a limited space and artificial environment generates stress for the animals [1, 2]. For decades, the chicken embryo chorioallantoic membrane (CAM) has been representing an attractive, relevant, inexpensive, and easy-to-handle in vivo model to study various concepts in the

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_9, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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fields of cosmetology and biomedical sciences. The first report describing the CAM as in vivo model in biomedical research dates more than 100 years ago [3, 4]. Since the CAM is not innervated until later stages of its development, it enables to perform experiments without causing pain to the embryo [5]. It has been established [6, 7] that if eggs are sacrificed before their embryo development day (EDD) 14, i.e., before the development of pain receptors, chicken embryos do not experience any pain and, hence, no authorizations are necessary for most Western countries, which simplifies the research process. Thus, it offers to circumvent the ethical issues concerning the experiments performed on mammals. Moreover, it has been demonstrated that the CAM represents a relevant model for determining the ideal LD50 values for anticancer drugs [8]. A significant correlation of the LD50 values between the CAM and rodent models has been shown, suggesting that preliminary rodent toxicological studies could take advantage of using the CAM as a predictive model, not only to reduce the time, number of animals, and drug administration conditions, but, what is more important, to apply the 3Rs (replacement, reduction, and refinement) principle. The exciting potential of the CAM is exploited in various fields of research, including angiogenesis [9, 10], tumor biology [11], especially investigation of the tumor angiogenesis, tissue engineering [12, 13], toxicological studies for anticancer drugs [8, 14], pharmacology [15, 16], allergology [17], teratology [18], material-tissue biocompatibility [19–21], immune cell cultivation of viruses and bacteria [22, 23], bone regeneration [24], physiology [25, 26], metabolomics [27], and many more. The CAM presents, in particular, a suitable model to study the vascular effects of PDT due to the accessibility of the superficial tissue layers, allowing to use a broad range of wavelengths to induce PDT effects and/or for the visualization of blood vessels during or at different times after PDT.

2

Methods

2.1 CAM Incubation and Development

CAMs can be incubated either in ovo or ex ovo (Fig. 1). Fertilized eggs can be purchased from certified hatcheries. Standardly used protocol for in ovo (cultivation in the shell) [28, 29] includes placing fertilized eggs in a 37
C humidified and automatically rotating incubator during 3 days blunt end up. At EDD 3, a small (diameter: 3 mm) hole is made at the pointed end of the eggshell and covered with tape. Eggs are then placed back in the incubator in a stationary position until further use. Another method consists of incubating and cultivating the CAM outside its eggshell—ex ovo [30]. As in the in ovo incubation, eggs are placed for 3 days blunt

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Fig. 1 Chicken embryo at EDD 14. (a) In ovo and (b) ex ovo CAM

end up in a rotating incubator. At EDD 3, eggs are cracked into a sterile petri dish or plastic disposable weighing tray. Eventually, eggshell fragments can be placed around the CAM to serve as a calcium source for the embryo. This approach significantly widens the surface and accessibility of the CAM vascular network. According to our knowledge, there is no clear evidence in the literature indicating that data obtained with one or the other of these two methods significantly differ. However, a much higher risk of contamination exists when using the ex ovo method. It should be noted, however, that novel methods based on the use of artificial eggshells are being developed to overcome this obstacle. Such artificial eggshells are made from polydimethylsiloxane or polycarbonate and allow observation of the CAM vascular network from multiple directions [31]. During the chicken development in its amniotic egg, three extraembryonic membranes, i.e., allantois, chorion, and amnion, envelop the embryo. The allantoic membrane fuses with the chorion and forms the CAM, an extraembryonic tissue, which serves as the respiratory organ of the avian embryos. Throughout the CAM development, an extremely dense vessel system connected to the embryonic circulation is formed with blood vessel diameters ranging from several microns (capillaries) to about half a millimeter (Fig. 1). The embryonic development, as well as the development of its vessel system, has been studied and described in detail in many references [32, 33]. Development stages are usually described as EDD or Hamburger and Hamilton stages. In the latter, the development of the chicken embryo is classified and divided into a series of 46 stages, also known as HH stages, that are based on the external features of the embryo [32, 34]. The CAM plays a key role in the chicken development, in particular since it is responsible for calcium transport from the eggshell to the embryo, and it stabilizes the acid-base equilibrium

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of the embryo [35–37]. It should also be noted that the CAM’s lymphatic system is very similar to the mammalian one, both from a functional and molecular point of view [38]. Although many studies are performed directly on the normal CAM, many groups are exploiting the advantages of this membrane as a substrate to conduct experiments on cell lines, spheroids, or tumors grown at its surface. 2.2 Tumors Grown on CAM

Since the lymphoid system of the CAM develops at its late stages, this membrane is an excellent natural substrate for a wide range of different types of cancer cells, thus allowing to grow threedimensional (3D) tumors. Such a tumor formation on the CAM better resembles the tumor microenvironment when compared to cell-derived models like 3D cell culture tumors or tumor organoids [39–41]. Highly vascularized CAM network enables to form the tumors a few days after grafting. Hence, because of this unique advantage of the CAM, complex and multistep studies can be carried out, including comprehensive cancer cell dissemination, morphological studies of tumor-blood vessel interactions, intravascular tumor cell invasion, or metastasis formation. In addition, this advantage enables to study, in particular, the intravasation steps of the metastatic cascade in vivo [42]. Finally, histological analysis of tumors after their treatments can be performed, allowing to widen the treatment analysis and enhance the functionality of this model. In recent years, the successful transplantations of many different human tumor cell lines on the CAM have been reported, including glioma cancer [43, 44], prostate cancer [45, 46], ovarian cancer [47–50], osteosarcoma [51], bowel cancer [52], leukemia [53], pancreatic cancer [54, 55], as well as transplantation of resected patient’s tissue from adenocarcinoma of the breast, squamous carcinoma of the lung, thyroid carcinoma [56], or musculoskeletal tumor [57]. The methods used for grafting the tumors depend on the cell line. A detailed list of cancer cell types that were successfully implanted on the CAM, including an inoculation technique, is presented in the review published by Nowak-Sliwinska et al. [58].

2.3 The CAM as a Model to Study and Optimize PDT

The CAM model has been used for many decades as an in vivo model to study PDT. As described in more details in other chapters of this book, PDT is a multistep process in which a non- or poorly toxic photosensitizer (PS), or its precursor, is administered either systemically (intravenously, orally) or topically. After a period, ranging typically between an hour and several days depending on the PS, following its adequate level and/or selective accumulation in the lesion, the PS is excited with wavelengths corresponding to the PS absorption peak(s), typically with red or NIR light. This excited PS can interact with molecular oxygen contained in tissues, an energy transfer that can produce different forms of reactive oxygen

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species (ROS), singlet oxygen in most cases [59, 60]. ROS can then interact with their environment, a mechanism which frequently leads, among other effects, to transient or permanent occlusion of the vasculature [61]. As mentioned above, the accessibility of the CAM vascular network makes it a convenient model to study such PDT effects. More details about the CAM’s vascular response to PDT are given below in Subheading 3.1. 2.3.1 Photosensitizer Administration Protocols to the CAM

The PDT effects strongly depend, among others, on the PS administration route. In the CAM model, PSs can be administered topically [29], intraperitoneally (IP) [62, 63], or intravascularly (IV) [64–69]. Each administration route has its own advantages and disadvantages. A topical administration is fast and simple, but it is useful and of interest only for a few PSs. It is mostly used for studies focused on surface-accessible lesions [62]. When administered topically, PSs diffuse through the CAM’s intact external membrane before to be filtered by the mesoderm, and, finally, partially taken up by endothelial cells of blood vessels [63]. Like topical administrations, IP injections are also fast and simple. In this case, the circulatory system of the embryo enables the PS to reach the CAM vessels. However, here again, IP administrations work well for certain PSs only. A more detailed description of the different PS administration approaches and their uptakes by the CAM was published by Hammer-Wilson et al. [63]. This group has shown, along with Hornung et al., that the PS uptake by the CAM is comparable for both IP and IV administration routes [62, 63]. IV administrations are the most time consuming and require experience and skills to insert the needle into a CAM vessel. Yet, perforation of blood vessels due to the IV injection disrupts the blood circulation only minimally and, therefore, the PS can circulate in the bloodstream and reach the organs of the embryo [70]. The volume that can be injected intravenously depends on the EDD of the embryo. Typically, it ranges between 1 and 100 μL, since the blood volume increases proportionally with the CAM development [71]. For studies of the vascular response to PDT, the IV PS administration is usually performed from EDD 11 and later. PSs used in PDT are frequently hydrophobic. Thus, different delivery systems, including liposomes and nanoparticles, are often used to facilitate their administration and uptake by the CAM and/or the lesion it contains [72, 73]. A 0.9% sodium chloride solution is often used as a solvent to facilitate the distribution of the PS for all three types of administration (topical, IP, and IV). An overview of different drug delivery systems that have been studied on the CAM model is presented by Vargas et al. and NowakSliwinska et al. and thus will not be discussed here in more details [15, 58].

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2.4 Light Dosimetry in the CAM Model

In addition to the two crucial parameters (PS and oxygen) mentioned above that are playing a key role in PDT, the knowledge and mastering of the light dosimetry in the treated tissues are of great importance. Since most assays are performed on the CAM, light dosimetry in this membrane is very important. The light propagation and, consequently, its dosimetry in biological tissues are governed by their optical properties. Thus, the knowledge of the optical properties of biological tissues is essential to model the propagation of light and, consequently, for proper therapeutic design and planning. Among the parameters describing the optical properties of biological tissues, which are all wavelength dependent, the most important are the scattering (μs) and absorption (μa) coefficients, the scattering phase function (p), the refractive index of the tissue (n), and the anisotropy factor (g). More extensive descriptions and introduction to these optical parameters are presented elsewhere [74, 75]. Surprisingly, the optical parameters of the CAM have virtually not been reported according to the best of our knowledge. This is probably due to the heterogeneous aspects of this membrane which is also relatively thin as compared to the penetration depth of light in the CAM. This situation explains our decision to bypass these difficulties by measuring directly the fluence rate (FR) above, in, and underneath the CAM at different wavelengths of interest (405, 514, and 635 nm) and for well-controlled and homogeneous illumination conditions of the air-CAM interface. The fluence rate was measured with the experimental setup depicted in Fig. 2. Diode lasers (with typical bandwidths of 5 nm) were used as light sources to deliver light at 405 and 635, whereas an argon ion laser, operated in the single-line mode, was used to deliver light at 514 nm. A frontal light distributor with an outer diameter of 2 mm was coupled to these light sources generating a homogeneous circular spot with sharp edges (the whole surface of the CAM was illuminated). The powers of the light at the output of the light distributor were typically in the order of 10 mW (typical irradiance at the air-tissue interface of the CAM: 2 mW/cm2), depending on the dynamic ranges and spectral sensitivity of the detector. The FR was directly measured with a calibrated optical fiber-based spherical isotropic probe presenting an outer diameter of 850 μm that was attached to a vertical translation stage. The light collected by this isotropic probe was guided to a photosensitive diode by an integrated optical fiber. Measurements at 405 nm were carried out with a MV405/20 violet vision filter placed between this fiber and the photosensitive diode to reject the tissue autofluorescence induced by the violet light. Preliminary studies indicated that this autofluorescence was not problematic for illuminations at 514 and 635 nm.

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Fig. 2 Experimental setup for measurements of the fluence rate in the CAM

Fertilized eggs were cultured in ovo using the standard protocol described in Subheading 2. Measurements of the FR were conducted on the CAMs (5 eggs per condition) at EDDs 9 and 11, and its respective average values and standard deviations were calculated. Before each measurement, the isotropic probe was first placed in the light spot in the absence of egg to determine the primary incidence, also expressed in mW/cm2. Thereafter, the FR was measured 1 mm above, as well as inside the CAM, at a depth of 1 mm, above the yolk, the embryo, and what is called the “free space” (i.e., the volume between the yolk and the embryo which contains albumin only). The normalized (FR above or in free space, yolk, and embryo of the CAM/divided by FR in the air in the absence of egg) results of these measurements are presented in Fig. 3. No measurable differences were observed between EDDs 9 and 11. Therefore, the data obtained at these two EDDs have been pooled together. Since violet light is known to be strongly absorbed by hemoglobin, the normalized FR at 405 nm in the CAM is much lower (about 35% of the primary incidence) than for the other wavelengths. It is interesting to note that the FR in the CAM is about the same as the primary incidence in the green, whereas a marked increase (about 1.4 times the primary incidence) of the FR in the CAM is observed in the red. The FR above the CAM is also much

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Fig. 3 Normalized fluence rates in (free space, yolk, and embryo) and above the CAM at different wavelengths. Black squares, red circles, and blue triangles represent measurements conducted at 405, 514, and 635 nm, respectively

larger than the primary incidence in the red and in the green, whereas this is not the case in the violet. This difference reflects the reduced reflectance of the CAM at this last wavelength that is strongly absorbed by hemoglobin. Although not statistically relevant, it seems that the presence of the yolk underneath the CAM results in an increase (in the order of 10–20%) of the FR in this membrane for green and red lights only. This is expected considering the yellowish aspect of the yolk. Finally, it should be noted that the relatively large standard deviations observed at 514 nm are due to the presence of speckles resulting from the long coherence length of the light produced by the argon ion laser. To the best of our knowledge, this is the first report describing the FR in the CAM, in particular when this membrane is illuminated with a “broad” (25 mm in diameter) homogenous spot. Our results illustrate the importance of a precise assessment of the light distribution in biological samples such as the CAM, in particular, if different wavelengths are considered. If treatments are performed at one of the three wavelengths investigated in this report, measuring of the FR in air (i.e., the primary incidence) enables to determine the value of the FR in the CAM. This is mandatory to master the light dosimetry, in particular, to study the action spectra of PSs or to compare photodamage induced on the CAM with different models (in vitro or in vivo).

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Data Analysis and Interpretation

3.1 CAM’s Vascular response to PDT

As mentioned above, PDT induces the generation of ROS which then leads to the activation of a cascade of physiological and tissular effects that can be temporary or permanent. One well-known PDT effect is the induction of a permanent vascular occlusion [61]. Debefve et al. have recorded the dynamics of such angioocclusions after PDT in the CAM using a microscope equipped with a real-time and highly sensitive camera to image the PS (verteporfin) fluorescence [66]. These works followed the first optimization study of the vascular occlusion induced by benzoporphyrin derivative monoacid ring A (BPD-MA) administered intravenously to the CAM. This study was performed to optimize and better understand the mechanisms involved in the treatment of certain forms of age-related macular degeneration (AMD) by BPD-MAbased PDT [64]. It is also known that PDT induces an angiogenic response [76]. Indeed, after application of PDT, the resulting vessel closure frequently leads to hypoxia and/or secondary inflammations. Consequently, these effects of PDT result in the promotion of angiogenesis, an evolution which plays a role in tumor or AMD reoccurrences [61, 67]. Thus, various antiangiogenic compounds able to suppress vascular growth have been studied on the CAM in combination with PDT to inhibit the revascularization of such lesions [61, 76–80]. Additionally, it was observed, in particular in the CAM, that the blood vessel permeability can be enhanced following a low-dose PDT [81]. Since PDT affects the endothelial cell membranes, as evidenced by the depletion of their tight junctions, the vascular permeability is enhanced. Ultimately, low-dose PDT can be used to improve the selective delivery of drugs, including chemotherapeutic agents, in the targeted lesion [82]. This method was investigated and improved by combining PDT with cyclo-oxygenase inhibitor (acetylsalicylic acid) in the CAM. It was shown that the administration of acetylsalicylic acid induced a significant enhancement of the vessel leakage, thus enabling to reduce the total dose of chemotherapeutic drugs [81]. Another important study illustrating the potential and interest of the CAM model was focused on the demonstration of the direct correlation existing between the decrease of the tissular partial pressure of oxygen (pO2) observed during PDT and the resulting tissue damages. The pO2 was derived from the measurement of the protoporphyrin IX (PpIX) triplet-state lifetime that is quenched by molecular oxygen, with PpIX being used not only as a pO2 probe but also as PS [29]. It was shown on the CAM that such measurements of the pO2 change during the illumination enable to predict the tissue response to PDT in real time. Consequently, this

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approach looks very promising to better master and individualize the light dosimetry in PDT. It should be noted that the ability to measure the local tissular partial pressure of oxygen is important not only for PDT but also for other treatments, including radiotherapy. 3.2 Quantification Methods of the PDT Effects on the CAM Vascular Network 3.2.1 Image ProcessingBased Techniques

There are several different approaches to assess PDT effects on the CAM vascularization. These approaches can be classified into two categories, namely the qualitative or quantitative ones. Vascular morphology and density represent the basic foundation of these methods. Historically, the first approach proposed by Gottfried et al. to assess the PDT damages was based on a postirradiation inspection of the blood vessels. These damages were classified according to a scale ranging across “0” (corresponding to no damage), “1” (slight damages), “2” (moderate damages), and finally “3” (severe damages with widespread hemorrhage and occlusion of the irradiated area) [83]. In the same year, a method based on the assessment of the growth of new vessels into a collagen gel matrix that contains fibroblast growth factors was developed [84]. In addition, several other methods based on the visual counting of vessels, combined or not with automated image processing have been reported [85, 86]. A robust and semiquantitative approach has been reported by Lange et al. [64]. This group established a scale based on fluorescence angiographies conducted typically 1 day after PDT. The fluorescing contrast agents injected intravenously were mostly fluorescein isothiocyanate (FITC) conjugated with dextran or PSs, such as BPD-MA. Lange et al. established an arbitrary damage scale (Table 1) where scores, ranging between 0 and 5, are assigned according to the diameter of the largest vessels closed by PDT. Moreover, an IV injection of a fluorescent agent not only enables to quantify the PDT effect on angio-occlusion but also, simultaneously, allows a semiquantitative estimation of the PDT

Table 1 Arbitrary damage scale assessing the PDT efficacy in CAM vascular network [64] Scale

Criterion/indicator

0

No vascular damage

1

Partial closure of capillaries with a diameter smaller than 10 μm

2

Closure of the capillary system with partial closure of blood vessels with a diameter smaller than 30 μm, and size reduction of larger blood vessels

3

Closure of vessels with a diameter smaller than 30 μm, and partial closure of higher order vessels

4

Total closure of vessels with a diameter smaller than 70 μm, and partial closure of larger vessels

5

Total occlusion of the irradiated area

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efficiency by observing and monitoring the blood flow in the irradiated vessel network. Thereby, the blood circulation can be compared in the illuminated area and zone where PDT was not applied while using a standard image processing [64]. The most common parameters used to assess quantitatively the status of a vascular network after PDT are the vessel lengths [87], the vascular density [88], the vessel diameters, and the vessel branching points/mm2 [89]. Unfortunately, these quantification techniques are carried out ex vivo to obtain a satisfactory contrast. In addition, in virtually all cases, information is given about the larger vessels only, but no information is provided regarding the capillary plexus [90]. This situation explains why a noninvasive automated quantification method based on macros of the ImageJ open-source software [91] has been developed to provide information about the microvasculature (including capillaries) network of the CAM in ovo [92]. After an IV injection of FITC-dextran, a series of descriptors (number of branching points/mm2; closed area surrounded by vessels and/or capillaries, defined as the mean area of the vessel network meshes with units [μm2]; and the mean of the third quartile of the mesh area histogram also with units of [μm2]) are provided. This automated quantification method was compared and validated with other nonautomated, more empirical, and somewhat arbitrary grading methods [92]. Excepting fluorescence imaging and histology (which will be discussed later) as cornerstones for the quantification of the vascular damage induced by PDT, many of other imaging methods have been developed to evaluate the CAM network. These methods include photoacoustic microscopy to image the 3D morphological vascular network of the CAM after PDT in real time [93–95]. In addition, few studies have been reported recently where magnetic resonance imaging or positron-emission tomography was used for the nondestructive and noninvasive assessment of developing vessels [96–99]. However, the resolution of these new methods is not sufficient to visualize all parts of the vascular network. Finally, electron microscopy is used and provides supplementary information for this application [100]. Unfortunately, the constraints, complexity, and time-consuming aspects of this approach do not speak in favor of its extensive use, in particular for applications aiming at screening a large number of different drugs or PDT protocols. 3.2.2 Biochemical and Histopathological Based Techniques

As described in Subheading 3, the advantage of the CAM immunodeficiency enables to graft tumors on the membrane. Thereafter, various PDT treatments can be performed and the effects can be assessed at different time points after the illumination. Afterward, these tumors and eventually dissociated tumor cells can be dissected and subject to immunohistochemical, biochemical, and/or histological assays. In addition, numerous methods and assays can be

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examined after embedding of the CAM in paraffin. Furthermore, tissue staining assays can be applied. Protocols strongly depend on the desired molecule or antigen of interest. For biochemical studies, harvested samples are placed into the proper buffer (i.e.: SDS for Western blot or extraction buffers for ELISA RIPA analysis) as reviewed by Deryugina et al. [101]. Altogether, the image processing techniques described above that are dedicated to the characterization of the vascular network along with immunohistochemical and biochemical assays provide valuable complementary information to study the effects of PDT. 3.3 Effects Induced by Sub-thermal Irradiances of Visible or NIR Light on the CAM angiogenesis and Metabolic Activity

Although the CAM is a relevant model for numerous PDT-related studies, it should be noted that several unexpected factors can significantly influence or distort the results. One of these factors is in relation to the exposure of the CAM to light, even if sub-thermal irradiances are applied for several minutes. Therefore, it is mandatory to master and document the exposure of the CAM to all light sources, including room light, daylight, and, importantly, light emitted by microscopes during routine controls of the eggs’ status. The effects induced by such low levels of light are not so surprising considering the extensive prior art reported in the fields of photobiomodulation (PBM), which is sometimes also referred to as low-level light/laser therapy (LLLT) [102]. PBM is based on the application of low irradiances (less than 50 mW/cm2) of red or near-infrared light, usually at wavelengths ranging between 600 and 900 nm. Although the precise mechanism of PBM remains unknown, its influence on the mitochondria respiration, ATP production, and oxygen consumption has been reported, including an increase of the membrane polarization [103]. Moreover, PBM has been shown to promote wound healing and angiogenesis [102]. To illustrate the importance of these effects induced by PBM, we have conducted a preliminary study of its impact on the CAM angiogenesis (Fig. 4). Eggs were incubated in ovo according to the standard protocol described above in Subheading 2.1. Briefly, a small hole was made at the pointed end of the egg and covered with a tape at EDD 3. Three days later (EDD 6) this hole was enlarged to 2.5 cm in diameter to enable the application of light. A similar setup as depicted in Fig. 2 was used (excluding the isotropic probe and photosensitive diode). PBM irradiation conditions were as follows: a frontal light distributor was coupled to a 670 nm diode producing a homogeneous circular spot with sharp edges and covering the whole surface of the CAM. The light was applied during 180 s with an irradiance of 15 mW/cm2. Control eggs were taken out of the incubator for the same amount of time (180 s) without application of the light. In addition, in another set of eggs light at 730 nm was applied during 180 s with the same irradiance. At this wavelength no difference was observed when compared to the control group (data not shown). This observation

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Fig. 4 PBM effects on the CAM angiogenesis. Fluorescent angiograms were acquired with an epi-fluorescent microscope using a 10 objective (NA: 0.3, WD 16.0). 20 μL of a fluorescent agent (FITC-dextran, 25 kD, 25 mg/mL) was IV injected along with an IP administration of India ink to increase the image contrast. Image analysis was performed using a macro written in ImageJ (NIH, Bethesda, USA) (PNS 2010). N ¼ 9 per condition

is in agreement with other studies where 730 nm was observed as wavelength with minimal induction of PBM effects [103]. The assessment of the PBM effects on angiogenesis was performed using the approach described above [92], which is based on fluorescence angiographies performed on the CAM 6 days after PBM (EDD 12). Figure 4 presents a typical CAM fluorescence angiogram (left image) characterized quantitatively with the results obtained from the image processing and analysis software. From the processed angiograms, three descriptors were extracted: the number of branching points/mm2, the mean area of the vessel network meshes, and the mean of the third quartile of the mesh area histogram. Three images of three eggs per condition were analyzed. As presented in Fig. 4, our results demonstrate that PBM significantly stimulates the CAM angiogenesis. Moreover, strong wavelength-dependent stimulation of the CAM angiogenesis was observed (unpublished data), an observation which is in a good agreement with other reports [103]. It should be noted that similar irradiations performed on CAMs subject to hypoxia during 1 h demonstrated that PBM can modulate their oxygen consumptions and, consequently, their metabolism (data not shown). Altogether, these studies strongly suggest that PBM has an impact on a very broad spectrum of biological mechanisms, including those involved in angiogenesis, metabolomics (oxygen level and consumption), and consequently PDT. Therefore, it must be kept in mind that exposure of the CAM to visible or NIR light may strongly affect the final results and, consequently, researchers must limit and document the exposure of eggs to such light while preparing and conducting experiments with CAMs.

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Discussion and Conclusion In conclusion, the CAM model is very interesting to study various aspects of PDT, in particular, those that are in relation to the vascular effects of this treatment. The CAM is simple to handle and cheap and its easily accessible vascular network enables to conduct numerous studies providing statistically robust information about different aspects of PDT which can be obtained during or after the illumination. Furthermore, since the CAM is only innervated at its late development stages, no ethical approvals are necessary to conduct experiments, unlike most other in vivo models/assays. Finally, this chapter illustrates how important it is to minimize and/or document the exposure of the CAM to light, in particular when the membrane of this model is observed under a microscope. If not, the resulting PBM effects are likely to bias the results obtained with most assays.

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The CAM Model for PDT model for giant cell tumor of bone. BMC Cancer 11:241 58. Nowak-Sliwinska P, Segura T, Iruela-Arispe ML (2014) The chicken chorioallantoic membrane model in biology, medicine and bioengineering. Angiogenesis 17:779–804 59. Dolmans DEJGJ, Fukumura D, Jain RK (2003) Photodynamic therapy for cancer. Nat Rev Cancer 3:380–387 60. Dougherty TJ, Gomer CJ, Henderson BW, Jori G, Kessel D, Korbelik M, Moan J, Peng Q (1998) Photodynamic therapy. J Natl Cancer Inst 90:889–905 61. Weiss A, van den Bergh H, Griffioen AW, Nowak-Sliwinska P (2012) Angiogenesis inhibition for the improvement of photodynamic therapy: the revival of a promising idea. Biochim Biophys Acta 1826:53–70 62. Hornung R, Hammer-Wilson MJ, Kimel S, Liaw LH, Tadir Y, Berns MW (1999) Systemic application of photosensitizers in the chick chorioallantoic membrane (CAM) model: photodynamic response of CAM vessels and 5-aminolevulinic acid uptake kinetics by transplantable tumors. J Photochem Photobiol B Biol 49:41–49 63. Hammer-Wilson MJ, Cao D, Kimel S, Berns MW (2002) Photodynamic parameters in the chick chorioallantoic membrane (CAM) bioassay for photosensitizers administered intraperitoneally (IP) into the chick embryo. Photochem Photobiol Sci 1:721–728 64. Lange N, Ballini JP, Wagnieres G, van den Bergh H (2001) A new drug-screening procedure for photosensitizing agents used in photodynamic therapy for CNV. Invest Ophthalmol Vis Sci 42:38–46 65. Pegaz B, Debefve E, Ballini J-P, Wagnie`res G, Spaniol S, Albrecht V, Scheglmann DV, Nifantiev NE, van den Bergh H, KonanKouakou YN (2006) Photothrombic activity of m-THPC-loaded liposomal formulations: pre-clinical assessment on chick chorioallantoic membrane model. Eur J Pharm Sci 28: 134–140 66. Debefve E, Pegaz B, van den Bergh H, Wagnie`res G, Lange N, Ballini J-P (2008) Video monitoring of neovessel occlusion induced by photodynamic therapy with verteporfin (Visudyne®), in the CAM model. Angiogenesis 11:235–243 67. Nowak-Sliwinska P, van Beijnum JR, van Berkel M, van den Bergh H, Griffioen AW (2010) Vascular regrowth following photodynamic therapy in the chicken embryo chorioallantoic membrane. Angiogenesis 13: 281–292

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68. Lim SH, Nowak-Sliwinska P, Kamarulzaman FA, van den Bergh H, Wagnie`res G, Lee HB (2010) The neovessel occlusion efficacy of 15-hydroxypurpurin-7-lactone dimethyl ester induced with photodynamic therapy. Photochem Photobiol 86:397–402 69. Nowak-Sliwinska P, van Beijnum JR, Casini A, Nazarov AA, Wagnieres G, van den Bergh H, Dyson PJ, Griffioen AW (2011) Organometallic ruthenium(II) arene compounds with antiangiogenic activity. J Med Chem 54: 3895–3902 70. Leng T, Miller JM, Bilbao KV, Palanker DV, Huie P, Blumenkranz MS (2004) The chick chorioallantoic membrane as a model tissue for surgical retinal research and simulation. Retina (Philadelphia, Pa) 24:427–434 71. Barnes AE, Jensen WN (1959) Blood volume and red cell concentration in the normal chick embryo. Am J Phys 197:403–405 72. Vargas A, Pegaz B, Debefve E, KonanKouakou Y, Lange N, Ballini J-P, van den Bergh H, Gurny R, Delie F (2004) Improved photodynamic activity of porphyrin loaded into nanoparticles: an in vivo evaluation using chick embryos. Int J Pharm 286: 131–145 73. Vargas A, Eid M, Fanchaouy M, Gurny R, Delie F (2008) In vivo photodynamic activity of photosensitizer-loaded nanoparticles: formulation properties, administration parameters and biological issues involved in PDT outcome. Eur J Pharm Biopharm 69:43–53 74. Jacques SL, Pogue BW (2008) Tutorial on diffuse light transport. J Biomed Opt 13: 041302 75. Jacques SL (2013) Optical properties of biological tissues: a review. Phys Med Biol 58:R37–R61 76. Weiss A, van Beijnum JR, Bonvin D, Jichlinski P, Dyson PJ, Griffioen AW, Nowak-Sliwinska P (2014) Low-dose angiostatic tyrosine kinase inhibitors improve photodynamic therapy for cancer: lack of vascular normalization. J Cell Mol Med 18:480–491 77. Madsen SJ, Sun CH, Tromberg BJ, Wallace VP, Hirschberg H (2000) Photodynamic therapy of human glioma spheroids using 5-aminolevulinic acid. Photochem Photobiol 72:128–134 78. Zuluaga M-F, Mailhos C, Robinson G, Shima DT, Gurny R, Lange N (2007) Synergies of VEGF inhibition and photodynamic therapy in the treatment of age-related macular degeneration. Invest Ophthalmol Vis Sci 48: 1767–1772

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79. Debefve E, Pegaz B, Ballini J-P, van den Bergh H (2009) Combination therapy using verteporfin and ranibizumab; optimizing the timing in the CAM model. Photochem Photobiol 85:1400–1408 80. Nowak-Sliwinska P, Weiss A, van Beijnum JR, Wong TJ, Ballini J-P, Lovisa B, van den Bergh H, Griffioen AW (2012) Angiostatic kinase inhibitors to sustain photodynamic angio-occlusion. J Cell Mol Med 16: 1553–1562 81. Debefve E, Pegaz B, Ballini J-P, Konan YN, van den Bergh H (2007) Combination therapy using aspirin-enhanced photodynamic selective drug delivery. Vasc Pharmacol 46: 171–180 82. Debefve E, Cheng C, Schaefer SC, Yan H, Ballini J-P, van den Bergh H, Lehr H-A, Ruffieux C, Ris H-B, Krueger T (2010) Photodynamic therapy induces selective extravasation of macromolecules: insights using intravital microscopy. J Photochem Photobiol B Biol 98:69–76 83. Gottfried V, Davidi R, Averguj C, Kimel S (1995) In vivo damage to chorioallantoic membrane blood vessels by porphyceneinduced photodynamic therapy. J Photochem Photobiol B Biol 30:115–121 84. Nguyen M, Shing Y, Folkman J (1994) Quantitation of angiogenesis and antiangiogenesis in the chick embryo chorioallantoic membrane. Microvasc Res 47:31–40 85. Larger E, Marre M, Corvol P, Gasc J-M (2004) Hyperglycemia-induced defects in angiogenesis in the chicken chorioallantoic membrane model. Diabetes 53:752–761 86. Wei D, Gao Y, Cao X, Zhu N, Liang J, Xie W, Zhen M, Zhu M (2006) Soluble multimer of recombinant endostatin expressed in E. coli has anti-angiogenesis activity. Biochem Biophys Res Commun 345:1398–1404 87. Pyriochou A, Tsigkos S, Vassilakopoulos T, Cottin T, Zhou Z, Gourzoulidou E, Roussos C, Waldmann H, Giannis A, Papapetropoulos A (2007) Anti-angiogenic properties of a sulindac analogue. Br J Pharmacol 152:1207–1214 88. Blacher S, Devy L, Hlushchuk R, Larger E, Lamande´ N, Burri P, Corvol P, Djonov V, Foidart J-M, Noe¨l A (2011) Quantification of angiogenesis in the chicken chorioallantoic membrane (CAM). Image Analysis Stereol 24:169–180 89. Strick DM, Waycaster RL, Montani JP, Gay WJ, Adair TH (1991) Morphometric measurements of chorioallantoic membrane

vascularity: effects of hypoxia and hyperoxia. Am J Phys 260:H1385–H1389 90. Vickerman MB, Keith PA, McKay TL, Gedeon DJ, Watanabe M, Montano M, Karunamuni G, Kaiser PK, Sears JE, Ebrahem Q et al (2009) VESGEN 2D: automated, user-interactive software for quantification and mapping of angiogenic and lymphangiogenic trees and networks. Anat Rec (Hoboken) 292:320–332 91. Schneider CA, Rasband WS, Eliceiri KW (2012) NIH image to ImageJ: 25 years of image analysis. Nat Methods 9:671–675 92. Nowak-Sliwinska P, Ballini J-P, Wagnie`res G, van den Bergh H (2010) Processing of fluorescence angiograms for the quantification of vascular effects induced by anti-angiogenic agents in the CAM model. Microvasc Res 79:21–28 93. Hajireza P, Krause K, Brett M, Zemp R (2013) Glancing angle deposited nanostructured film Fabry-Perot etalons for optical detection of ultrasound. Opt Express 21: 6391–6400 94. Chen S-L, Burnett J, Sun D, Wei X, Xie Z, Wang X (2013) Photoacoustic microscopy: a potential new tool for evaluation of angiogenesis inhibitor. Biomed Opt Express 4: 2657–2666 95. Xiang L, Xing D, Gu H, Yang D, Yang S, Zeng L, Chen WR (2007) Real-time optoacoustic monitoring of vascular damage during photodynamic therapy treatment of tumor. J Biomed Opt 12:014001 96. Giannopoulou E, Katsoris P, Hatziapostolou M, Kardamakis D, Kotsaki E, Polytarchou C, Parthymou A, Papaioannou S, Papadimitriou E (2001) X-rays modulate extracellular matrix in vivo. Int J Cancer 94:690–698 97. Chesnick IE, Fowler CB, Mason JT, Potter K (2011) Novel mineral contrast agent for magnetic resonance studies of bone implants grown on a chick chorioallantoic membrane. Magn Reson Imaging 29:1244–1254 98. Warnock G, Turtoi A, Blomme A, Bretin F, Bahri MA, Lemaire C, Libert LC, Seret AEJJ, Luxen A, Castronovo V et al (2013) In vivo PET/CT in a human glioblastoma chicken chorioallantoic membrane model: a new tool for oncology and radiotracer development. J Nucl Med 54:1782–1788 99. Kivrak Pfiffner F, Waschkies C, Tian Y, Woloszyk A, Calcagni M, Giovanoli P, Rudin M, Buschmann J (2014) A new in vivo magnetic resonance imaging method to noninvasively monitor and quantify the

The CAM Model for PDT perfusion capacity of three-dimensional biomaterials grown on the chorioallantoic membrane of chick embryos. Tissue Eng Part C Methods 21:339–346 100. Easterling A, Burton GJ, Skepper JN, NasrEsfahani MH (1993) A scanning electron microscopic study of the chick chorioallantoic membrane: cell death and the involvement of oxygen free radicals. Scanning Microsc 7: 87–95; discussion 95–96 101. Deryugina EI, Quigley JP (2008) Chapter 2. Chick embryo chorioallantoic membrane models to quantify angiogenesis induced by

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Chapter 10 Subcutaneous Xenograft Models for Studying PDT In Vivo Girgis Obaid and Tayyaba Hasan Abstract The most facile, reproducible, and robust in vivo models for evaluating the anticancer efficacy of photodynamic therapy (PDT) are subcutaneous xenograft models of human tumors. The accessibility and practicality of light irradiation protocols for treating subcutaneous xenograft models also increase their value as relatively rapid tools to expedite the testing of novel photosensitizers, respective formulations, and treatment regimens for PDT. This chapter summarizes the methods used in the literature to prepare various types of subcutaneous xenograft models of human cancers and syngeneic models to explore the role of PDT in immuno-oncology. This chapter also summarizes the PDT treatment protocols tested on the subcutaneous models, and the procedures used to evaluate the efficacy at the molecular, macromolecular, and host organism levels. Key words Cell lines, Syngeneic models, Immunocompetent models, Patient-derived xenografts, Photodynamic therapy

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Introduction For decades, research into photodynamic therapy (PDT) has used mostly subcutaneous xenograft models of human cancer in rodents, such as mice and rats, and has helped the approval of a dozen photosensitizers (PSs) globally with more than 500 active PDT clinical trials [1–4]. Subcutaneous xenograft models residing in an anatomical site allow for both facile photoirradiation and longitudinal monitoring of tumor volume, perfusion, and oxygenation. Thus, these models have understandably been the first option when translocating from in vitro testing to in vivo evaluation of antitumor PDT efficacy [5, 6]. In this chapter, methods of generating and utilizing subcutaneous xenograft models of cancer as tools for evaluating PDT efficacy are detailed and discussed. These models include human cell line xenografts, syngeneic xenografts, immunocompetent xenografts, and patient-derived xenografts. Each type of model has been leveraged for a specific purpose and can often be matched to the implications of the resultant findings. Challenges

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that subcutaneous xenograft models face are also discussed, along with emerging strategies described in the literature used to address them.

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Methods In this section, the methods used for a number of subcutaneous tumor models that have been reported as testing platforms for PDT are discussed. These include implantation of human cell line xenografts (Subheading 2.1), implantation of syngeneic cell line xenografts (Subheading 2.2), and implantation of patient-derived xenografts (PDX) (Subheading 2.3). Subsequently, we briefly discuss various PDT treatment strategies (Subheading 2.4). The main advantages of using human cell line xenografts include the flexibility to rapidly evaluate treatment regimens in a broad variety of disease indications from human origin; however, the main disadvantage is the inability to assess the immunological components of therapies. Conversely, the strength of using syngeneic cell line xenografts is their ability to recapitulate secondary responses to PDT regimens mediated by the innate and adaptive immune system. The limited number of established syngeneic cancer cell lines available for testing is a major limitation, in addition to the absence of human molecular targets and cellular sensitivities that are not directly comparable with human disease. PDX tumor models recapitulate the molecular, cellular, and structural heterogeneity of patient tumors; however, they suffer from rapid partner cell turnover with the host species and, like human cell line xenografts, can only be tested in immunocompromised host rodent species. The details of how these models are used to evaluate PDT-based regimens will be discussed as follows.

2.1 Implantation of Human Cell Line-Based Xenografts

Owing to the relative simplicity of generating subcutaneous primary cell line tumor models of human cancers, they are the most common type of tumor model to be leveraged for assessing PDT efficacy, in addition to non-PDT treatments also described historically in the literature. This simplicity is also the reason why human cell line xenografts have also been used to measure the PDT efficacy of a broad variety of cancer indications including tumors of the pancreas [7–9], brain [5] [10, 11], and ovaries [12, 13], among others. In general, the methods for generating tumors from human cell lines are relatively uniform throughout the literature. Human cell lines are cultured to near confluence in 2D monolayer, mostly in fetal bovine serum-containing media. In order to implant them to develop into tumors, they are detached from culture, typically using trypsin, and concentrated to the required density for subcutaneous injections. As trypsin can rapidly cleave cell surface proteins that are used by the implanted cells to attach to

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the host species tissue, trypsin-free gentle cell detachment reagents, such as Dispase®, can be recommended as less perturbative alternatives [14]. The concentrated cell suspensions are then prepared for implantation in PBS, culture media, or combinations of PBS or culture media with Matrigel to enable the stable embedding of the cells under the skin and to prevent leakage. Matrigel has been shown to have no impact on tumor development or on tumor cell metabolism and can be recommended for any tumor implantation protocols to prevent tumor cell loss and to provide consistent tumor morphologies. However, being naturally derived, it can vary in composition which might make it susceptible to batch-tobatch variability [15]. A simpler matrix consisting of type I collagen has been shown to be a suitable alternative to Matrigel that allows for effective and reproducible tumor implantation [16]. An example of Matrigel used for implantation is reported in a study by Spring et al. who reported the development of both subcutaneous and orthotopic pancreatic ductal adenocarcinoma (PDAC) model using the metastatic AsPC1 cell line to assess the efficacy of a combinatorial PDT-based nanoconstruct. The subcutaneous PDAC model was generated using 6-week-old Swiss nude mice implanted with 1
106 AsPC-1 cells per mouse on the hind leg. To aid in the formation of the subcutaneous tumors, cells were implanted in a 50/50 mixture of Matrigel and serum-containing DMEM media, injected in a total volume of 50 ⎧L. Similarly, Mallidi et al. used female Swiss nude mice (6–8 weeks old) and subcutaneously implanted on 3
106 U87 human glioblastoma cells suspended in 300 ⎧L in 100% growth factor-reduced Matrigel on the mice backs [5]. Such processes for preparing human cell line xenografts using Matrigel to study PDT are thoroughly reported in the literature for various cancer models including lung cancer [17] [18] and cervical cancer [19], among others. Thus, for preliminary screening of in vivo PDT efficacy, human cell line-based xenograft tumors can be recommended as the model of choice for simplified and rapid testing. The relatively large number of publications of PDT using human cell line-based xenograft tumors may also serve as a point of reference to help evaluate findings in the context of those already published using the same tumors. 2.2 Implantation of Syngeneic Cell Line-Based Tumors

Syngeneic tumor models are generated using cancer cell lines implanted into the same species as the host recipients, which are most often mice or rats in studies involving PDT [20]. The major advantage of using syngeneic models is to recapitulate and preserve immunological responses to anticancer therapies, as a result of the immune compatibility of tumor cells of the same species and the resulting capability to use immunocompetent strains of host animals [20]. However, the degree of relevance of nonhuman tumors that are designed to model PDT treatment response in human

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diseases can be questionable. This concern becomes particularly significant when evaluating PDT-based targeted therapies where molecular targets and epitopes require sequence homologies closely matching those of humans to accurately assess outcomes. The majority of PDT studies in the following methods descriptions for syngeneic tumor implantations are designed to monitor intrinsic host tissue responses to therapy, the most important being antitumor immune responses. Tong et al. used Balb/c mice implanted subcutaneously with the metastatic 4 T1 murine breast adenocarcinoma cells to evaluate the efficacy of benzoporphyrin derivative monoacid ring A (BPD-MA) in combination with Adriamycin [21]. Cell suspensions (200 ⎧L in what is assumed to be culture media) containing 8
106 4 T1 cells were implanted subcutaneously into the right flank of Balb/c mice until tumors reached 100–150 mm3 in volume, as determined by caliper measurements of tumor dimensions. In this study, no specific motivation to use a syngeneic model was mentioned, although the methods described here can be used in future studies involving the analysis of host responses, molecular or immunological, that are otherwise unaccounted for when using human cell line or tissue model xenografts. In another study using a syngeneic model of squamous cell carcinoma, the efficacy of PDT using Foscan was evaluated in combination with a ceramide analog [22]. In this study, the authors required an intact immune system that is provided by a syngeneic model to evaluate the multifaceted in vivo response to antitumor PDT. Given that ceramide signaling is known to modulate the immune system, a syngeneic model was particularly important for evaluating this specific combination regimen [23]. Female syngeneic C3H/HeN mice were implanted with 1
106 SCCVII squamous carcinoma cells subcutaneously in the lower back and were allowed to grow for 7–10 days in order to reach 6–8 mm in diameter. The study found that combining PDT with the ceramide analog improved survival in the syngeneic model and that intrinsic ceramides served as predictive biomarkers for tumor responses to PDT. In addition to mice, rats have also been used to generate syngeneic tumors for the investigation of PDT-based treatment regimens. Owing to the larger size of rats, more complex and thorough PDT procedures are possible, such as interstitial illumination and real-time dosimetry. An example of such a study was published by the group of Ronald Moore, who generated subcutaneous R3327-H prostate tumors and AY-27 bladder tumors in syngeneic Fischer CDF344 male rats [24]. R3327-H tumors and AY-27 tumors were initially passaged subcutaneously in donor rats that are a cross between Fischer and Copenhagen breeds. Before the tumors grew to a maximum of 5000 mm3 in the donor rats, they were excised and cut into 3 mm chunks in sterile Hanks’

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balanced salt solution. The R3327-H tumors and AY-27 tumors were then implanted subcutaneously into the flanks of the recipient Fischer CDF344 male rats and were allowed to grow for 16–20 weeks or 10–14 days, respectively. Following ALA-PDT, tumor dimensions were monitored using calipers and the volumes were calculated using the ellipsoid formula. Syngeneic models have also been used to explore the immunological role of PDT. A seminal report by Korbelik and Dougherty demonstrated that splenocytes from PDT-sensitized or X-ray-sensitized immunocompetent mice bearing syngeneic subcutaneous tumor models were able to enhance the antitumor efficacy of PDT when injected into immunodeficient mice with syngeneic subcutaneous tumor models of the same tumor type [20]. Syngeneic EMT-6 mammary sarcoma cells and Meth-A fibrosarcoma cells (1
106 cells) were implanted subcutaneously in the lower dorsum of 7–9-week-old Balb/cJ mice (immunocompetent) and Balb/cJscid.TO (severe combined immunodeficient) female mice were also implanted in the same manner. Splenocytes were isolated from spleens by mild mechanical separation of the tissue, selective lysis of erythrocytes using ammonium chloride, and filtration through 50 mm polyester membranes. Two days prior to subcutaneous tumor implantation of the recipient Balb/cJ-scid.TO immunodeficient mice, the freshly prepared splenocytes were injected into the tail veins of the recipient mice at a density of 1–2
107 cells/ mouse. The donor mice were then subject to Photofrin-PDT as described before. The authors found that adoptive transfer of splenocytes from X-ray-sensitized tumor-bearing donor mice had a significant protective effect on the regrowth of the subcutaneous tumors following PDT. Even more so, the adoptive transfer of splenocytes from PDT-sensitized EMT-6 tumor-bearing donor mice resulted in a complete cure of EMT-6 tumor-bearing recipient mice. This effect was supported by the finding that adoptive transfer of splenocytes from PDT-sensitized Meth-A tumor-bearing donor mice had no inhibitory effect on the growth rate of the EMT-6 tumor-bearing recipient mice. The strength of this protocol lies in its ability to accurately probe which leukocytes are responsible or play a major contributing role in the immunological destruction of residual tumor cells following PDT. Syngeneic murine xenograft models bearing two contralateral subcutaneous tumors have proven to be a powerful tool to explore the impact of PDT on a phenomenon known more widely in oncology as the abscopal effect. The abscopal effect occurs when distant tumors that represent metastatic disease are eradicated by the adaptive immune system following the localized focal treatment of the primary neoplasm [25]. Examples of such focal treatments include radiotherapy [26], thermal ablation [27], and PDT [28]. By confining light irradiation to one of the two contralateral tumors, the immunological effects of PDT can be monitored

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relatively simply with a degree of control that is not observed with protocols requiring the adoptive transfer of immune cells. An important study by Mroz et al. demonstrated that the contralateral subcutaneous rechallenge of mice with colon adenocarcinomas that had been initially treated with PDT 90 days prior was rejected in more than 95% of mice tested [29]. Importantly, contralateral tumor rechallenge was only rejected following PDT of mice implanted with CT26.CL25 tumors expressing the immunogenic tumor antigen β-galactosidase. Wild-type CT26 (CT26WT) colon adenocarcinoma cells or CT26.CL25 cells transfected with the lacZ gene encoding the model tumor-associated antigen β-galactosidase were implanted into immunocompetent Balb/c mice subcutaneously on the right thigh at a density of 3.5
105 cells per mouse. Vernier calipers were used to monitor the tumor dimensions until the diameters reached 5–7 mm, approximately 9 days following implantation. 90 days following PDT with BPD, surviving mice were rechallenged with 3.5
105 CT26TW or CT26.CL25 cells subcutaneously implanted in the contralateral left thigh and the tumor volumes were monitored for another 60 days. A recent study by Lu et al. leveraged contralateral subcutaneous syngeneic xenograft models to investigate the immunomodulatory effects of PDT using a nanoconstruct containing a chlorin-based PS, in synergy with an immune checkpoint inhibitor of indoleamine 2,3-dioxygenase (IDO) [30]. PDT of the primary tumor in combination with IDO inhibition leads to tumor antigen presentation and T-cell proliferation that leads to the destruction of the contralateral tumor. Contralateral tumor models of MC38 and CT26 colon adenocarcinomas were generated in C57BL/6 mice and Balb/c mice, respectively, by implanting 2
105 cells into the left flank and 1
106 cells into the right flank of each mouse. Due to the simplicity of generating syngeneic tumor xenografts that can develop in the presence of a functional immune system, syngeneic models are recommended as the model of choice for assessing the immunological aspects of PDT treatment response. Weaknesses associated with the subcutaneous physiological location of these syngeneic tumor xenografts are outweighed by the unique ability to monitor contralateral untreated tumors that helps predict the capacity of PDT treatment to control metastatic and recurrent disease in patients. 2.3 Implanting Patient-Derived Xenografts (PDX)

The complex and heterogeneous patient-derived xenograft (PDX) models of cancer are a powerful testing platform due to their increased physiological relevance and stronger predictive power for human tumor response to anticancer treatment regimens [31]. In addition, the fact that they are passaged through multiple generations of immunodeficient mice avoids the nonphysiological selective pressures that tumor tissues experience under ex vivo and in vitro tissue culture. PDX tumor models have also been leveraged

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to test the efficacy of PDT regimens when implanted subcutaneously in mice. The strain of mice used for PDX implantation are most commonly immunocompromised, such as the athymic Swiss nude strain, to prevent immunogenicity and rejection of the xenograft [31]. However, the innate immune system present in the Swiss nude mice can prove to be problematic and an immunodeficient SCID strain is preferred, which lacks T cells and B cells [32]. SCID mice can oftentimes produce T cells and B cells as they age; therefore nonobese diabetic (NOD)-SCID mice are sometimes preferred due to their absence of T cells and B cells and dysfunctional natural killer cells [33, 34]. The absence of fully functional immune systems in Swiss nude mice, SCID mice, and NOD-SCID mice can limit the evaluation of PDT to only direct anti-PDX tumor effects, without any impact of the innate and adaptive immune systems. Nwogu et al. investigated the efficacy of a newly reported photosensitizer, termed PS1, in a murine PDX model of non-small cell lung cancer (NSCLC) and compared it to PDT using the approved PS Photofrin [35]. The subcutaneous PDX model was developed using tumor tissue that was surgically resected from 85 NSCLC patients from 2000 to 2010 that was histologically verified as primary tumor disease. To add to the heterogeneity of the model, tumor tissues of differing cellular origin and staging were used. The resected patient tumor tissue was cut to 2
2 mm dimension and was immediately passaged in SCID mice. For the PDT experiments, second-passage PDX tumor tissue from the first-generation SCID mice was cut to the same 2
2 mm dimensions and implanted subcutaneously onto the abdominal wall of four groups of SCID mice. When the tumor diameters reached 4–6 mm, PDT using Photofrin was performed. A recent study by Lin et al. explored the “trimodal” therapeutic effects of a nanoconstruct integrating PDT using a pyropheophorbide A derivative, photothermal therapy, and doxorubicin chemotherapy in PDX models for bladder cancer obtained from Jackson Laboratories, namely BL269, BL440, BL645, and BL293 [36]. The PDX models were passaged subcutaneously on the flank in NOD-SCID gamma (NSG) mice and implanted orthotopically on the wall of the bladder, or subcutaneously on the flank. The nanoconstruct, termed nanoporphyrin, was administered intravesically into the bladder 2 days following orthotopic implantation for subsequent PDT. Although PDX models boast of a genomic, cellular, and structural fidelity to the patient tumor, the inconsistency and dynamism of cell type proportions can result in inconsistencies in treatment response between in vivo passages. It has been shown that PDX tumor stromal cells, such as fibroblasts, are rapidly replaced by host species fibroblast, and thus the advantage of true tumor heterogeneity is dampened by dynamic heterogeneity in tumor development as a function of time when transplanted into mice [37].

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2.4 PDT Treatment Regimens 2.4.1 Photosensitizer Administration Routes

2.4.2 Selection of PS-Light Interval

For the majority of PDT studies using subcutaneous xenograft tumor models, the treatment protocol follows a similar pattern, whereby the intravenous administration of a PS or a sensitizer formulated into a solubilizing vehicle is ensued by discrete PS-light intervals. PSs and their respective formulations have been administered intravenously through tail-vein injections [5, 7, 20, 21, 24], intraperitoneally [22] and intratumorally [30]. Intravenous tail-vein administration is the most common route used in preclinical in vivo studies using subcutaneous xenograft models for PDT, whereby the pharmacokinetics of common PSs is well studied and well understood. Implications on the effects of certain PS-light intervals are also the most well understood for intravenous administration, although this will be discussed in greater detail in the following section. Intraperitoneal administration is less common, and the pharmacokinetics of tumor delivery are not as well understood. Thus, future studies using intraperitoneal administration of photosensitizing agents would likely require a separate set of biodistribution experiments, either longitudinally using fluorescence imaging of the PS molecules or terminally using tissue extraction protocols and subsequent analysis. Intratumoral administration bears little relevance to the clinical application of the PDT regimens being tested. However, it serves a very specific purpose when the goal is to confine the sensitizer and its concomitant combination agents to one point of focus to evaluate secondary biological effects in distant sites such as contralateral tumors. PDT, in addition to other activatable therapies with a narrow radius of damage, provides a unique level of precision for differentially targeting the tumor endothelium or parenchyma. The duration of PS-light intervals is dictated by the option of inducing vascular PDT (short PS-light interval, ca. 15 min), direct tumor cell phototoxicity (long PS-light interval, ca. 3 h or more), or a combination of both (intermediate PS-light interval, ca. 90 min) [38]. These intervals of 15 min, 90 min, and 3 h or more are somewhat limited to amphiphilic PS molecules administered as free molecules or weakly associated with inert vehicles. PS-light intervals are different for photosensitizing entities with differing pharmacokinetics and pharmacodynamics, such as strongly hydrophilic sensitizers with ambiguous intracellular uptake rates and stable nanocarriers with longer circulation half-lives. For such photosensitizing entities, separate experiments are required to individually determine the time-dependent tumor compartment localization. Such studies are time consuming and technically challenging; hence more commonly with new photosensitizing entities, investigators either establish the time of maximal tumor uptake as the time for irradiation or select arbitrary time points, such as 24 h.

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To exemplify the impact of drug-light interval on therapeutic efficacy, PDT has been performed in subcutaneous U87 glioblastoma xenografts using 0.5 mg/kg of BPD formulated in a liposome that mimics the clinical formulation, Visudyne [5]. The BPD formulation was injected intravenously via a tail-vein injection, with a comparison of either a 1-h or 3-h PS-light interval. The subcutaneous U87 tumors were irradiated with an Intense 690 nm diode laser light at an irradiance of 100 mW/cm2 delivering a total fluence of 100 J/cm2. The authors found that the 3-h PS-light interval was less tumoricidal than the 1-h PS-light interval for vascular PDT, and they found that tumoricidal efficacy correlated with tumor oxygenation. This unique spatiotemporal selectivity of tumor phototoxicity by tuning the PS-light interval is also only specific to parenterally administered exogenous photosensitizing entities, and thus alternative PDT treatments, such as ALA-based therapies, are further complicated by a rate-limiting endogenous metabolic conversion into the active PS protoporphyrin IX. 2.4.3 Light Application

The second determinant of PDT dosimetry is the light application to activate the sensitizers and control the localization and extent of RMS generation. PDT light dosimetry is most often described in the literature with two parameters: power density, also known as irradiance, expressed as W/cm2, and fluence expressed as J/cm2. The relationship between energy, power, and time is described in Eq. 1. Equation 1 is used to determine the irradiation time and irradiance needed to achieve certain fluences of light and the light application protocols described in the literature for PDT regimens in subcutaneous xenograft models will be discussed in this section. Although fluence is the principal metric of PDT dosimetry, it is becoming increasingly evident that irradiance must be regulated to optimize outcomes, with numerous reports claiming that the same fluence administered to tumors is more efficacious when delivered using lower irradiances [39, 40]. Energy ðJ Þ ¼ Power ðW Þ
Time ðs Þ

ð1Þ

In the remainder of this section, examples of established PDT protocols for a variety of photosensitizers and photosensitization strategies are provided. In a previous study by our group, a liposomal nanoconstruct was prepared containing the photosensitizer BPD in the membrane and a polymeric PEG-PLGA nanoparticle encapsulated in the core, which entrapped the anti-metastatic and antiangiogenic smallmolecule inhibitor, XL184 [7]. The combination nanoconstruct was referred to as photoactivable multi-inhibitor nanoliposome (PMIL). Treatment in this subcutaneous AsPC-1 model was initiated following intravenous administration of 0.25 mg/kg

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BPD equivalent and 0.1 mg/kg XL184 equivalent contained in the PMIL construct. The subcutaneous tumors were irradiated 60 min following intravenous administration using a 690 nm diode laser delivering a light fluence of 75 J/cm2 at an irradiance of 100 mW/ cm2. The study concluded that only with the combinatorial nanoconstruct, PDT treatment reduced tumor volumes down to 10% of those in untreated control mice and less than 40% in those mice treated with the monotherapies. Similarly, in a subcutaneous 4 T1 breast tumor model, 5 mg/ kg Adriamycin was administered intravenously through tail-vein injections 4 days after the tumors reached their required volume of 100–150 mm3. The following day, 1 mg/kg of BPD was administered intravenously, and the tumors were irradiated with 120 J/ cm2 of 690 nm laser light 24 h later [21]. It was found that the PDT-Adriamycin combination therapy was just under twofold more potent at controlling tumor growth in vivo, as compared to PDT alone, and prolonged mice survival to the same degree. In a separate study using SCCVII subcutaneous xenograft model for squamous cell carcinoma, intraperitoneal injection of Foscan formulations was also explored [22]. Foscan was formulated in a 2/3/5 v/v combination of ethanol/polyethylene glycol 400/water and was administered intraperitoneally at a dose of 0.1 mg/kg. Following a 24-h duration, the subcutaneous SCCVII tumors were irradiated with 650 nm light at a fluence of 50 J/cm2 and an irradiance of 80–90 mW/cm2. The light was generated using a Sciencetech FBQTH high-throughput illuminator. For the mice receiving the combination treatment with a ceramide analog, C6-pyridinium ceramide dissolved in water was injected intraperitoneally at a dose of 80 mg/kg either 24 h prior to PDT or immediately after. Up to 90 days following PDT, mouse survival was only ca. 35%, whereas in combination with the ceramide analog, survival was ca. 80%. Subcutaneous R3327-H prostate tumors and AY-27 bladder tumors in Fischer CDF344 rats have also been treated with PDT after the tumors reached 1000 mm3 in volume [24]. Intravenous administration of 500 mg/kg of ALA dissolved in PBS by tail-vein injection in the rats was performed 4 h prior to interstitial photoirradiation of the subcutaneous tumors. The tumors were irradiated with 630 nm light delivered by a tunable Coherent CR-599 argonpumped dye laser through a beam equally split into 8 quartz fibers with terminal diffusing tips that were placed interstitially into the tumors, equally spaced 7 mm apart in a hexagonal, icosahedral pattern. The wavelength and power output of light set to 80 mW for each individual fiber were measured using a Laser Therapeutics power meter and the eighth fiber was kept attached to the power meter for real-time monitoring of light dosimetry during the irradiation protocol. Four hours after injection of ALA, the tumors

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were irradiated with light doses ranging from 1000 to 3000 J. The authors showed that with a 3000 J treatment of PDT, all subcutaneous R3327-H prostate tumors and AY-27 bladder tumors were cured and only mild reductions in tumor perfusion were recorded, as is consistent with tumor cell-targeted PDT regimens like ALA-PDT. In an immune-competent mouse model, PDT was performed on the Balb/cJ mice 6 days following implantation of EMT-6 and Meth-A tumors in groups of 8–10 mice per arm [20]. Briefly, 10 mg/kg of Photofrin was administered intravenously and the tumors were irradiated 24 h later using 630 nm light (A5000 unit with a 1 kW xenon bulb, Photon Technology International, Inc.) at an irradiance of 120–130 mW/cm2 and a fluence of either 110 J/ cm2 (EMT-6) or 150 J/cm2 (Meth-A tumors). A 5 mm core diameter liquid light guide (2000A, Luminex) was also used to apply the light. The primary observation was tumor regrowth, as evaluated by visual inspection thrice weekly, and mice with no evidence of tumor regrowth for 90 days were considered complete cures. In another experiment within the same study, PDT was compared with 35 Gy of X-ray radiotherapy at 3.33 Gy/min using a Philips RT250 radiotherapy system (250 kVp, 0.5 mm Cu). The study concluded that PDT of the subcutaneous tumors was able to generate tumor-specific sensitized immune cells that provided a prolonged antitumor immunity. In another immune-competent model of colon cancer, vascular PDT was performed on subcutaneous CT26WT tumors or CT26. CL25 tumors expressing the immunogenic tumor antigen β-galactosidase by intravenous injection of 1 mg/kg of BPD dissolved in 5% dextrose [29]. The tumors were irradiated using a 1 W 690 nm diode laser (B&W Tek Inc., Newark) at 120 J/cm2 fluence and an irradiance of 100 mW/cm2, with a PS-light interval of 15 min. Interestingly, 70% of PDT-treated CT26.CL25 tumor-bearing mice rechallenged with contralateral subcutaneous CT26.CL25 cells rejected tumor growth and the remaining 30% of the mice were found to escape immune destruction because of a loss of expression of the immunogenic β-galactosidase. PS constructs have also been directly injected intratumorally for PDT-based combination regimens. Mice bearing primary right flank tumors at a volume of 100 mm3 were treated with a PDT-indoleamine 2,3-dioxygenase (IDO) inhibitor immunotherapy combination regimen at a chlorin-based photosensitizing ligand dose of 20 μmol/kg injected intratumorally [30]. Following a PS-light interval of 12 h, the primary right flank tumor was irradiated with 650 nm light at a fluence of 90 J/cm2 and an irradiance of 100 mW/cm2 and a secondary untreated tumor was monitored for immune-based control. Irradiation of the nanoconstruct containing both the chlorin-based ligand and the IDO

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inhibitor in the primary tumor was the most effective at controlling the growth of a contralateral secondary tumor that was not exposed to either the construct or the light. In a subcutaneous PDX model of non-small cell lung cancer, mice were intravenously injected with a novel PS1 PDT agent or with Photofrin at doses of 1.5 μmol/kg or 6 mg/kg, respectively [35]. Following a PS-light interval of 24 h, the subcutaneous PDX tumors were irradiated with 665 nm light for the mice injected with PS1, or with 630 nm light for the mice injected with Photofrin. Photoirradiation was performed using tunable dye lasers pumped by an argon ion laser (Spectra-Physics) and Plexiglas holders that construct light exposure to only 4–5 mm. In comparison with the approved photosensitizer Photofrin, PDT using PS1 was more effective at inducing tumor necrosis and apoptosis and prolonged the time duration before PDX tumor regrowth. As mentioned earlier, subcutaneous xenografts are particularly advantageous for studying activatable therapies such as PDT due to their accessibility and relatively feasible photoirradiation. Although the skin (~500 μm) in such models is not a significant barrier for near-infrared light penetration, skin phototoxicity can be a concern for non-targeted PDT regimens and can impair the accuracy of tumor volume measurements. From the experience in our lab, we found that skin phototoxicity and scarring following non-targeted PDT often resolve within a week [5]. It must also be noted that PDT of subcutaneous tumors often does not represent the toxicity profile of the regimen if performed in vivo, and thus PDT doses that may provide complete control of a subcutaneous tumor may not be tolerated orthotopically at sensitive anatomical sites, such as the liver, pancreas, and brain [13, 41]. This adds a layer of complexity for selecting PDT dosimetry parameters either in orthotopic models or in patients, which cannot reliably be guided by PDT doses that are effective in subcutaneous models.

3

Data Analysis and Interpretation The assessment of treatment efficacy for PDT is not necessarily a trivial task, as it is subject to the study design and hypothesis. Therefore, this section will discuss several methods for longitudinal monitoring of treatment efficacy (Subheading 3.1), and intermediary response monitoring using sophisticated functional imaging modalities (Subheading 3.2).

3.1 Longitudinal Monitoring of Treatment Efficacy

A key advantage of using subcutaneous tumor xenograft models is the ability to longitudinally monitor tumors in response to treatment using simple measurements. The three most common modalities used to longitudinally monitor tumor progression include caliper measurements, ultrasound imaging, and bioluminescence

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imaging. Of these three, caliper imaging is the most frequently used due to its technical simplicity and non-perturbative approach, although it can be subject to experimenter bias and is recommended only under blinded conditions. Caliper measurements are not recommended for tumors below 2 mm in diameter and also cannot account for variations in the thickness of the skin, which can be problematic for proinflammatory treatments like PDT. Ultrasound imaging is more sensitive than caliper measurements and is therefore recommended for monitoring smaller tumors. The unavailability and expense of sophisticated ultrasound imaging instruments may be a concern. Manual selection of tumor tissue during image analysis can also be subject to experimenter bias and requires experience to accurately determine tumor margins. Wholemouse imaging systems used to detect bioluminescence signals from tumors may also not be available to all research facilities. Although noninvasive and highly sensitive, the less common bioluminescence imaging has multiple drawbacks. These weaknesses include the need for stable transfection of bioluminescence enzymes (e.g., luciferase), the nonlinear bioluminescence transmission through the tissue, the need for an exogenous probe (e.g., luminol), and the dependence on ATP, which varies with the types of treatments administered. In the study by Spring et al., tumor volumes were calculated using the hemi-ellipsoid equation and the three dimensions of the tumors were measured longitudinally using calipers [7]. The tumor volumes reached 50 mm3 within 18 days after implantation, after which the PDT-based combination treatment using a photoactivable multi-inhibitor nanoliposome (PMIL) was initiated. The PMIL contained both the PS BPD and anti-metastatic and antiangiogenic small-molecule inhibitor, XL184 [7]. Following PDT-based combination therapy, subcutaneous tumor volume was monitored for up to 47 days (Fig. 1a). The biggest difference between the test treatment arm using PMIL and the control arms was observed at 37 days, where the fractional residual tumor volume was significantly lower than all the control arms with no treatment, free XL184, nanoparticle formulation (NP[XL148]), PDT using liposomal BPD (L[BPD]), or a mixture of L[BPD]and NP[XL184] (Fig. 1b). Importantly, treatment using the PMIL significantly reduced liver and lymph node metastases more than any other treatment arm, demonstrating the power of co-encapsulated therapies. Metastases were quantified in the liver and lymph nodes using a quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay that measures human and mouse glyceraldehyde 3-phosphate dehydrogenase (GAPDH) housekeeping genes. In the study by Lu et al. looking into the combined effects of a nanoconstruct containing a PS and the IDO inhibitor (IDOi@TBC-Hf), a subcutaneous contralateral model was used to monitor the immune-based control of untreated tumors [30]. PDT

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b Fraction residual tumour

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XL 18 4] PD ]+ ]( N hn P[ XL ) 18 4] (h n) PM IL (h n)

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Fig. 1 Growth rates of subcutaneous AsPC-1 tumors (a) and fractional residual tumors at 19 days following treatment (b) with the c-MET/VEGFR-2 inhibitor (XL184), free or in a nanoparticle (NP); with PDT using liposomal BPD (L[BPD]); with combinations of BPD and XL184; and with co-encapsulated XL184 nanoparticles within BPD liposomes (PMIL) (figure adapted from Spring B.Q. et al. (2016) Nat. Nanotechnol. 11:378–387 https://doi.org/10.1038/nnano.2015.311)

of the primary tumor in combination with IDO inhibition leads to tumor antigen presentation and T-cell proliferation that leads to the destruction of the contralateral tumor (Fig. 2a). The volumes of the primary right flank and secondary left flank untreated tumors were monitored longitudinally using calipers, and tumor sections were analyzed for infiltrating leukocytes using immunohistochemistry. It was found that the untreated secondary tumors did not grow when the primary tumors were treated with the nanoconstruct containing the PS and the IDO inhibitor with photoirradiation (IDOi@TBCHf; Fig. 2b). In a clinically relevant subcutaneous PDX model of NSCLC, PDT was explored using Photofrin and a novel photosensitizer PS1 [35]. Following PDT, mice were monitored for 60 days and the tumor volumes were longitudinally measured. Biomolecular analysis of PDX tissue death was performed on the tumors using H&E staining and caspase 3 immunohistochemistry, confirming that PDT induced apoptotic tissue damage. Figure 3 demonstrates that PDT using PS1 was more efficacious than with Photofrin in its capacity to control tumor regrowth, as enabled by an easily accessible tumor. Longitudinal tumor monitoring is facilitated by the accessibility of subcutaneous tumors and provides critical insights into dynamic responses to PDT, such as rates of tumor regrowth and its negative impact on prognosis. Longitudinal tumor monitoring, however, informs only of the terminal effects of treatment on tumor volume, giving no information of the mode of death or intermediate events that occur in response to PDT. By monitoring

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Fig. 2 (a) Irradiation of the nanoconstruct containing the chlorin-based PS and the IDO immune checkpoint inhibitor (IDOi@TBC-Hf) results in simultaneous tumor antigen release and sustained T-cell proliferation, (b) ultimately controlling untreated contralateral tumor (figure adapted with permission from Lu, K. et al., 2016. Journal of the American Chemical Society, 138(38), pp. 12502–12,510. Copyright 2018 American Chemical Society)

Fig. 3 Photographs of NSCLC PDX subcutaneous tumors in SCID mice (blue circle), before and 28 days after PDT using the novel PS PS1 or Photofrin (figure adapted from Nwogu C, et al. (2016) J. Surg. Res. 200:8–12 https://doi.org/10. 1016/j.jss.2015.07.024)

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intermediary responses, interventions can be incorporated into the treatment regimens to potentiate the efficacy of the PDT-based regimen used. These will be discussed in the following section. 3.2 Intermediary Response Monitoring Using In Vivo Functional Imaging

The accessibility of subcutaneous tumors has also been leveraged to combine sophisticated in vivo functional imaging techniques with therapy to guide the prediction of treatment success, which can ultimately be used to design interventions that help minimize treatment failures. Photoacoustic imaging (PAI) involves the pulsed laser excitation of intrinsic or exogenous chromophores with distinct absorption profiles to generate localized acoustic signals that propagate through the tissue and can be detected using an ultrasound probe [42]. The main advantage for PAI is the deep tissue imaging of a broad variety of chromophores that are otherwise undetectable, such as hemoglobin, using tunable lasers as the excitation source. A major strength for PAI is the capacity to selectively and quantitatively measure the relative proportions of oxyhemoglobin and deoxyhemoglobin to establish in vivo tissue oxygenation, which has proven to be powerful for oxygendependent regimens, such as PDT. Another powerful modality that provides valuable information for intermediary PDT responses is blood oxygenation level-dependent-magnetic resonance imaging (BOLD-MRI) [43]. Conventional MRI imaging leverages deflections in the magnetic field in water and fat-containing tissue to provide structural and morphological information. BOLD-MRI is a type of functional MRI (fMRI) that integrates information on the differential magnetic properties of oxygenated and deoxygenated hemoglobin and thus can be used to determine relative changes in tissue oxygenation. High-resolution micro-positron emission tomography (PET) imaging has also been used to report on tumor metabolic functionality for numerous treatment modalities and has implications in PDT response monitoring [44]. Micro-PET leverages radiolabeled probes with certain biological activities, such as a glucose conjugate of a radiolabeled probe, which informs of in vivo glucose consumption. Being endogenously radioactive, sensitivity of imaging is much greater than modalities requiring exogenous activation, such as fluorescence imaging. However, common PET probes used have a short half-life and the radioactivity of the PET probes used could also intrinsically induce tumor damage, confounding the results further. These modalities are used to monitor intermediary responses to PDT; although powerful in their own right and provide functional information that is otherwise not attainable, they require expensive instruments, can take significant amounts of time to acquire, and oftentimes need dedicated facilities. However, the immediate clinical relevance of these modalities makes them highly valuable and worth investing in at the preclinical level, in order to serve as early indicators of the extent of PDT antitumor response.

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Fig. 4 Representative images of structure using ultrasound imaging (a, e, i), oxygen saturation using PAI (b, f, j), necrotic regions using H&E staining (c, g, k), and hypoxic regions using immunofluorescence of pimonidazole (d, h, l). Scale bars are 5 mm for ultrasound and PAI images, and 1 mm for H&E and immunofluorescence images (figure reproduced from Mallidi, S. et al. (2015) Theranostics 5:289–301 doi:https://doi.org/10. 7150/thno.10155)

Mallidi et al. monitored the oxygenation of subcutaneous glioblastoma tumors using PAI of oxyhemoglobin and deoxyhemoglobin as a measure of the degree of response to PDT [5]. By correlating the degree of post-PDT oxygenation with tumor reduction, the authors developed an algorithm that enabled the prediction to PDT response as a means of customizing therapy for maximal outcomes. Tumor growth was monitored using calipers and the ellipsoid equation was used to estimate tumor volume. Following PDT using liposomal BPD, PAI imaging of oxygenated and deoxygenated hemoglobin was performed using 750 nm and 850 nm wavelength illumination, respectively, to derive estimates of oxygen saturation before, immediately after, 6 h after, and 24 h after PDT. Figure 4 shows a representation of the subcutaneous U87 tumors imaged using ultrasound imaging, oxygen saturation using PAI, H&E staining of necrotic tissue, and immunofluorescence of hypoxic regions bound to pimonidazole. Ultrasound imaging was also used to longitudinally monitor subcutaneous and orthotopic PDX models of bladder cancer following a combined nanoparticle incorporating photodynamic, photothermal, and chemotherapeutic treatment regimens [36]. The mice behavior was longitudinally monitored and 30 days after PDT, the PDX tumors were imaged using ultrasound imaging with and without microbubbles (5
107 per mouse) to enhance the contrast of blood perfusing the tumors. Microbubbles used as ultrasound imaging contrast are mostly organic gases trapped in a lipid or protein-based shell [45]. Tumor volumes were monitored longitudinally every 2–3 days for up to 5 weeks. The study found that in the subcutaneous PDX model, the

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trimodal combination therapy using the nanoconstruct was more efficacious at controlling tumor growth over 30 days, than the monotherapies alone. In the orthotopic PDX model, trimodal combination therapy using the nanoconstruct resulted in a significantly thinner bladder wall containing the tumor, than with the free doxorubicin comparison, and a significant higher ratio of functional bladder area. In another study, treatment response of subcutaneous prostate tumors to PDT with TOOKAD was monitored using blood oxygenation level-dependent contrast magnetic resonance imaging (BOLD-MRI) [6]. BOLD-MRI was particularly relevant for monitoring the efficacy of this treatment modality, as PDT with TOOKAD is predominantly a vascular therapy leveraging peroxynitrite radicals. PDT induced a 25–40% localized reduction of BOLDMRI signal, which suggested that treatment significantly reduced blood flow to the irradiated regions (Fig. 5b, c). Fei et al. used MRI imaging combined with micro-PET to generate functional images, respectively, to evaluate PDT responses in C3H mice implanted with RIF-1 tumors that were subject to PDT using a silicon phthalocyanine [46]. The authors generated 3D reconstructions of the whole mouse by overlaying structural information from MRI and functional information from microPET imaging [47]. Prior to imaging, the PS was administered. The mice were then injected with the PET probe 18F-fluorodeoxyglucose (FDG) and 6 min later, the tumors were irradiated with 670 nm light. Micro-PET images were acquired for a total of 90 min and it confirmed that the uptake of FDG was significantly reduced after irradiation, as compared to an untreated control, which informed of an immediate reduction in metabolic demand directly in response to PDT. Using such sophisticated image modalities to probe the physiological and functional consequences of PDT not only helps identify the antitumor mechanisms induced (e.g., thrombosis, oxygen depletion, cellular insult, attenuation of metabolism), but also helps provide an intermediary means for predicting efficacy and intervening to augment outcomes. The most common modalities used for intermediary response monitoring for PDT focus on oxygenation of the tumor and perfusion. Other emerging imaging modalities that could be informative for monitoring responsiveness to PDT include metabolic imaging [47]. As these modalities become better suited for deep-tissue imaging, their uses could extend to monitoring orthotopic tumors, which will be discussed in other chapters, and ultimately be extended to the clinic to better predict PDT treatment response in situ.

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Fig. 5 (a) TOOKAD-PDT of a subcutaneous prostate cancer xenograft mode with representative BOLD-MRI images demonstrating the time-dependent reduction (minutes) in signal, indicating a reduced blood flow to the tumor (b, c). With TOOKAD administration, photoirradiation alone had no impact on the BOLD-MRI signal (d, e) (reprinted by permission from Springer Nature: Nature Medicine, Monitoring photodynamic therapy of solid tumors online by BOLD-contrast MRI, Gross S, Gilead A, Scherz A, Neeman M, Salomon Y. (2003) [6])

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Discussion The body of literature within PDT and the wider family of oncology fields demonstrate the power of subcutaneous xenograft models to rapidly evaluate the treatment outcomes, new therapeutics, and novel treatment regimens, both with regard to dosing strategies and combinatorial therapy. With specific consideration of PDT, the accessibility of subcutaneous tumors for photoirradiation and subsequent monitoring of physiological parameters, such as blood flow and oxygenation, prove to be invaluable tools in the expedition of clinical translation of PDT [6]. Although extremely powerful in their own right, it cannot go unmentioned that subcutaneous models lack a critical component of recapitulating the PDT treatment response of the parent human disease, namely the anatomical site. Multiple studies have outlined the discrepancy between PDT treatment response of subcutaneous xenograft models and that of their orthotopic equivalent, mostly a decreased susceptibility to tumor destruction when moving into an orthotopic model [7, 10]. Multiple hypotheses account for this discrepancy, the most widely accepted being the more complex, pathophysiologically relevant interactions of the tumor xenograft with the appropriate respective anatomical environment, leading to variable responses to the treatment and varying patterns of metastases. This can also be accompanied by the recruitment of organ-specific partner cells when xenograft tumors are orthotopically generated, leading to a therapeutic response that is more representative of one in the clinical manifestation of the disease. Specifically, in the context of PDT, the discrepancy between subcutaneous and orthotopic tumor treatment responses is further complicated by the need for different light illumination strategies. Although fiber-optic light delivery technologies have been advanced and optimized to serve the utility of lasers in bioimaging and phototherapy, accurate guidance of internal irradiation protocols of orthotopic tumors can be more technically involved [48–50]. Conversely, illumination of orthotopic tumors directly can be more effective for PDT when no light penetration barrier of intermediary tissue is present, as in the case for irradiating subcutaneous models. Regardless of the challenges and complexities they present, the utility of orthotopic xenograft models for evaluating PDT efficacy will be discussed in separate chapters of this book.

Acknowledgments We would like to acknowledge NIH grants K99CA215301 and R00CA215301 to Girgis Obaid, and P01CA084203 and S10 ODO1232601 to Tayyaba Hasan.

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33. Shultz LD, Schweitzer PA, Christianson SW, Gott B, Schweitzer IB, Tennent B, McKenna S, Mobraaten L, Rajan T, Greiner DL (1995) Multiple defects in innate and adaptive immunologic function in NOD/LtSz-scid mice. J Immunol 154:180–191 34. Bosma M (1992) B and T cell leakiness in the scid mouse mutant. Immunodefic Rev 3: 261–276 35. Nwogu C, Pera P, Bshara W, Attwood K, Pandey R (2016) Photodynamic therapy of human lung cancer xenografts in mice. J Surg Res 200: 8–12 36. Lin TY, Li Y, Liu Q, Chen JL, Zhang H, Lac D, Zhang H, Ferrara KW, Wachsmann-Hogiu S, Li T et al (2016) Novel theranostic nanoporphyrins for photodynamic diagnosis and trimodal therapy for bladder cancer. Biomaterials 104:339–351 37. Cassidy JW, Caldas C, Bruna A (2015) Maintaining tumor heterogeneity in patient-derived tumor xenografts. Cancer Res 75:2963–2968 38. Chen B, Pogue BW, Hoopes PJ, Hasan T (2005) Combining vascular and cellular targeting regimens enhances the efficacy of photodynamic therapy. Int J Radiat Oncol Biol Phys 61: 1216–1226 39. Rizvi I, Anbil S, Alagic N, Celli J, Zheng LZ, Palanisami A, Glidden MD, Pogue BW, Hasan T (2013) PDT dose parameters impact tumoricidal durability and cell death pathways in a 3D ovarian cancer model. Photochem Photobiol 89:942–952 40. Rogers GS (2012) Continuous low-irradiance photodynamic therapy: a new therapeutic paradigm. J Natl Compr Cancer Netw 10(Suppl 2):S14–S17 41. Ji Y, Powers SK, Brown JT, Walstad D, Maliner L (1994) Toxicity of photodynamic therapy with Photofrin in the normal rat brain. Lasers Surg Med 14:219–228 42. Xu M, Wang LV (2006) Photoacoustic imaging in biomedicine. Rev Sci Instrum 77: 041101 43. Glover GH (2011) Overview of functional magnetic resonance imaging. Neurosurg Clin 22:133–139 44. Wang J, Maurer L (2005) Positron emission tomography: applications in drug discovery and drug development. Curr Trends Med Chem 5:1053–1075 45. Sirsi S, Borden M (2009) Microbubble compositions, properties and biomedical applications. Bubble Sci Eng Technol 1:3–17 46. Fei B, Wang H, Muzic RF Jr, Flask C, Wilson DL, Duerk JL, Feyes DK, Oleinick NL (2006) Deformable and rigid registration of MRI and

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Chapter 11 In Vivo Models for Studying Interstitial Photodynamic Therapy of Locally Advanced Cancer Gal Shafirstein, Emily Oakley, Sasheen Hamilton, Michael Habitzruther, Sarah Chamberlain, Sandra Sexton, Leslie Curtin, and David A. Bellnier Abstract Interstitial photodynamic therapy (I-PDT) is a promising therapy considered for patients with locally advanced cancer. In I-PDT, laser fibers are inserted into the tumor for effective illumination and activation of the photosensitizer in a large tumor. The intratumoral light irradiance and fluence are critical parameters that affect the response to I-PDT. In vivo animal models are required to conduct light dose studies, to define optimal irradiance and fluence for I-PDT. Here we describe two animal models with locally advanced tumors that can be used to evaluate the response to I-PDT. One model is the C3H mouse bearing large subcutaneous SCCVII carcinoma (400–600 mm3). Using this murine model, multiple light regimens with one or two optical fibers with cylindrical diffuser ends (cylindrical diffuser fiber, CDF) can be used to study tumor response to I-PDT. However, tissue heating may occur when 630 nm therapeutic light is delivered through CDF at an intensity
60 mW/cm and energy
100 J/cm. These thermal effects can impact tumor response while treating locally advanced mice tumors. Magnetic resonance imaging and thermometry can be used to study these thermal effects. A larger animal model, New Zealand White rabbit with VX2 carcinoma (~5000 mm3) implanted in either the sternomastoid (neck implantation model) or the biceps femoris muscle (thigh implantation model), can be used to study I-PDT with image-based pretreatment planning using computed tomography. In the VX2 model, the light delivery can include the use of multiple laser fibers to test light dosimetry and delivery that are relevant for clinical use of I-PDT. Key words Interstitial photodynamic therapy, Locally advanced cancer, SCCVII, VX2 carcinoma

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Introduction Cancer patients who failed to respond to surgery and chemoradiation therapy have high risk of developing large, locally advanced cancers (LAC). These patients have limited treatment options [1], and second- and third-line therapies, like the newest immunotherapies [2–4], result in relatively low response rates. In many cases, the LAC is adjacent to sensitive anatomy, so salvage surgery is not possible or too complex, and is associated with significant morbidity and low success rates [5, 6].

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Interstitial photodynamic therapy (I-PDT) has shown promising results in achieving control of LAC [7–9]. In I-PDT, one or more optical fibers are inserted into the targeted LAC to provide intramural illumination. The goal of I-PDT is to provide complete ablation of the target tumor while sparing normal tissue and critical organs. I-PDT can be repeated, with no cumulative toxicity or development of therapy resistance, in order to extend patient disease-free interval. The light irradiance and fluence (dosimetry) are key parameters that impact the response to I-PDT [7, 10–12]. Image-guided computer models are used to compute the light dosimetry in I-PDT. These models should be tested in animal models before translation into clinical studies [13, 14]. Here we describe a mouse model with subcutaneous and relatively large murine carcinoma, and a rabbit model with intramuscular cancerous tumor that can match the size of many LACs in patients. These animal models are suitable to test treatment planning methods, image-guided techniques, and light dosimetry to optimize I-PDT with clinically approved PS (porfimer sodium, Photofrin®), as recently described [15]. The first model is a murine syngeneic SCCVII squamous cell carcinoma, which is a widely accepted murine model for studying head and neck cancer [15, 16]. The locally advanced SCCVII is nonmetastatic and poorly immunogenic [16, 17]. We have reported little spontaneous necrosis or extensive hypoxia, and we have never observed spontaneous regression in the many 100 s of SCCVII tumors used in our studies [15]. For I-PDT light delivery, we use one or two cylindrical diffusing fiber optics (cylindrical diffuser fibers, CDFs), as shown in the sketches in Fig. 1.

Fig. 1 Drawings illustrate the administration of I-PDT in locally advanced SCCVII in mice. (a) A single catheter (18 G shielded IV catheter; Becton, Dickinson and Company, Franklin Lakes, NJ) is inserted through the center of the tumor, along its long axis, and parallel to the skin. (b) Two catheters are inserted at 6–7 mm apart, along the tumor long axis. The light is delivered through cylindrical diffuser fibers (CDFs): optical fibers with 0.98 mm diameter, 2 cm long cylindrical diffuser ends (e.g., RD 20, Medlight SA, Ecublens, Switzerland). During I-PDT, the tumor is slightly elevated (5–10 mm) above from the mouse body using a custom-made fixture

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Noteworthy, in this mouse tumor and location, the red light (i.e., 630 nm) can induce significant tumor tissue heating that will result in complete response and cure when
60 mW/cm and 540 J/cm were administered through CDFs (porfimer sodium, Photofrin®) [15]. However, the addition of the photosensitizer (i.e., Photofrin®) resulted in significantly ( p < 0.05) higher cure rate in comparison to light alone (no photosensitizer); for more details please see Shafirstein et al. (2018) [15]. The SCCVII tumor margins are readily defined in magnetic resonance imaging (MRI), and MR thermometry can be used to study tumor response and tissue heating during I-PDT. The second model discussed here is the locally advanced VX2 carcinoma established in New Zealand White rabbits. The rabbit VX2 tumor has been used extensively in studies of interstitial ablative therapies, including I-PDT [15, 18]. The New Zealand White (NZW) rabbit host allows support of tumors larger than those allowed in mice (2 cm at the longest axis) by most institutional Animal Care and Use Committees (IACUC). Tumors are initiated by implantation of a single piece of tumor previously harvested from a large VX2 tumor growing in a “donor” NZW rabbit. These 1 mm3 pieces are obtained only from tumors that show expected tumor growth patterns [19]. The VX2 tumor has a high frequency of spontaneous metastases. We recently reported on the use of the NZW rabbit with VX2 to study light dosimetry in I-PDT in the treatment of LAHNC; see Shafirstein et al. (2018) [15]. Because of our interest in I-PDT of locally advanced head and neck cancer (LAHNC), we implanted the VX2 tumor in the sternomastoid muscle. This location allows us to determine tumor response as well as evaluate the risk of multiple catheter insertion-related complications and photodynamic damage to the surrounding tissues, vessels, and nerves in the head and neck region. In these tumors, multiple fibers can be implanted to study the effect of adjacent fibers on the response to I-PDT. The VX2 is likely to metastasize once it reaches about 2–3 cm in its longest diameter (~5000 mm3). If implanted in the sternomastoid muscle, a
2 cm VX2 tumor shows a strong tendency to metastasize to the lungs [15]. Caliper measurements of VX2 tumors implanted intramuscularly often underestimate this tumor size. As such, it is recommended to image the VX2 tumor every week with non-contrast computed tomography (CT). These scans can also be used for pretreatment planning, as we recently described [15]. If implanted in the thigh muscle, the tumor could reach 2–2.5 cm before it is likely to metastasize.

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Materials

2.1 Syngeneic SCCVII Squamous Cell Carcinoma Model

1. The SCCVII cell line may be available through material transfer agreement with Roswell Park or other institutes. See also Note 1. 2. RPMI-1640 medium. 3. Fetal bovine serum (FBS). 4. L-Glutamine, penicillin, and streptomycin. 5. 0.25% Trypsin-EDTA. 6. Phosphate-buffered saline (PBS). 7. Hemocytometer. 8. 1 mL Syringes with a 26-gauge needle. 9. Isoflurane. 10. Heating plate. 11. Cylindrical diffuser fiber. 12. IV catheter.

2.2 Rabbit VX2 Carcinoma

1. The VX2 cell line (or frozen tumors) may be available through material transfer agreement with Roswell Park or other institutes. See also Note 1. 2. Acepromazine. 3. Cryoprotectant freezing media. 4. Chlorhexidine. 5. Isopropyl alcohol. 6. Betadine. 7. Vicryl suture. 8. Sterile drapes. 9. Isotropic detection fibers. 10. CT-compatible surface fiducial markers. 11. Buprenorphine. 12. Meloxicam. 13. Transparent closed-end sharp catheters. 14. Enrofloxacin. 15. Hypochlorous acid.

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Methods

3.1 I-PDT in Murine Syngeneic SCCVII Squamous Cell Carcinoma

1. SCCVII cells are grown in culture medium RPMI-1640 supplemented with 10% fetal bovine serum (FBS), 1 L-glutamine, and 100 units/mL penicillin and streptomycin in an atmosphere of 5% CO2 at 37  C. 2. Once confluent, the cells are trypsinized with 0.25% trypsinEDTA and washed with 1 phosphate-buffered saline (PBS). 3. Cell count is performed using a hemocytometer; cells are resuspended in 1 PBS to create a volume of one million (106) cells per 100 μL total volume for each inoculation. 4. Using 1 mL syringes with a 26-gauge needle, the suspension of SCCVII cells is injected subcutaneously into the right upper shoulder region of each mouse. See Note 2 for additional information. 5. Mice are followed few times a week, tumor size is measured with calipers, and tumor volumes are calculated as π/ 6  L  W2 (L ¼ length at longest axis, W ¼ width orthogonal to L). See Note 3 for recommendations on animal feed for I-PDT experiments on these models. 6. The mice were treated when the SCCVII tumors reach 400–600 mm3, which occurs at about 7–8 days postinoculation. Untreated tumors double their size within another 10–11 days. 7. The I-PDT treatment is conducted while the mice are under gas anesthesia with isoflurane (2–3%) on a heating plate set at 38  C. It is important to note that during I-PDT treatment we utilize a fixture to guide our insertion of laser fibers. The tumors are pulled away (5–10 mm) from the mouse body to reduce phototoxicity.

3.2 Post-procedure Follow-up and Treatment Assessment in the SCCVII/C3H Mice

1. Generally, clinical signs of morbidity (as defined by the local IACUC) rarely occur following I-PDT. When any sign is present, institute veterinary staff should be contacted. Vigilance should then be increased for the remainder of the cohort. 2. Tumors should be measured every 1–3 days after I-PDT. 3. Significant edema may be observed at the tumor site within 1–2 days after I-PDT, and may last for several more days. Edema may complicate tumor measurement. 4. A scab or eschar may form within 1–2 days, and may remain for 1–2 weeks. This may complicate tumor measurement. 5. Mice should be humanely euthanized when tumors in control groups or tumors that failed therapy reach the maximum volume defined by the local IACUC.

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6. Treatment-related tumor regression occurs within 7–10 days. Cures may be defined as no manually palpable tumor at 60 or more days following I-PDT. 3.3 Acquisition and Maintenance of the Rabbit VX2 Carcinoma Model

Hereinafter are the specific steps for doing intramuscular implantation of a VX2 carcinoma in the neck or thigh in NZW rabbits of about 2–2.5 kg body weight. The veterinary staff at the Laboratory Animal Shared Resources (LASR) at Roswell Park provided the preparation of the VX2 tumor piece maintained in their cryopreserved tissue bank and the surgical procedures to implant the tumor in either the sternomastoid or the biceps femoris muscles of specific pathogen-free NZW rabbits. 1. The VX2 carcinoma cannot be grown in cell culture and must be maintained via passage in live rabbits. The VX2 carcinoma is implanted in the biceps femoris thigh muscle of a donor rabbit for passage. Once the tumor grows to approximately 3 cm in its longest diameter, the donor rabbit is humanely euthanized, and the tumor is harvested aseptically, prepared into 2 mm x 2 mm pieces, frozen in cryoprotectant freezing media, and then stored in liquid nitrogen. 2. To prepare the frozen VX2 carcinoma for implantation in an experimental rabbit, individual vials of frozen VX2 carcinoma are thawed in a 37  C water bath, then placed in complete media, and centrifuged at 800 RPM for 5 min. The VX2 tumor pieces are then removed from the complete media and placed in phosphate-buffered saline, trimmed to the desired implantation size, and stored on wet ice until implantation occurs.

3.4 Implantation of the VX2 Model in Rabbits

1. Rabbits are sedated with 0.3 mg/kg acepromazine intravenously (IV) and then anesthetized via facemask with 2% isoflurane in oxygen. 2. The rabbit’s corneas are lubricated and the lateral neck or lateral thigh area is aseptically prepared by removing the hair with electric clippers, followed by a chemical depilatory, and then the skin is disinfected with chlorhexidine and isopropyl alcohol followed by betadine. 3. The animal is then moved to the operating room, placed on warm water recirculating heating pad, and monitored during the surgical procedure via pulse oximetry, electrocardiogram (EKG), and core body temperature. The rabbit is draped with sterile drapes and sterile surgical instruments are used. 4. A 2 cm incision in the skin is made over either the sternomastoid (neck implantation model) or the biceps femoris muscle (thigh implantation model), and with delicate blunt dissection the subcutaneous tissue is separated from the muscle fibers.

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5. Using small curved forceps, the delicate muscle fibers are separated to create a pocket in the muscle and the sterile 2 mm  2 mm piece of VX2 carcinoma is then implanted in the pocket. One 6–0 Vicryl suture is used to close the pocket and then the skin is closed with 5–0 Vicryl suture or tissue glue. 6. The animal is given fluids and analgesics subcutaneously and allowed to recover. The animals are monitored daily for tumor growth and signs of lung metastasis, and imaged weekly, with non-contrast CT, following the implantation of the tumor to determine the initiation of the I-PDT treatment. See Note 3 for recommendations on animal feed for I-PDT experiments on these models. 3.5 Pretreatment Planning

1. Pretreatment non-contrast CT imaging is performed weekly to assess the growth of VX2 tumors. Once tumors are approximately 2 cm at the longest axis, CT scans of the NZW rabbits with CT-compatible surface fiducial markers are obtained. See Note 4 for additional information. 2. Image visualization and segmentation: The CT scans are exported to image visualization and processing software, which is used to segment the tumor geometry along with any surrounding critical structures such as major blood vessels and surrounding tissues. The segmentations are individually smoothed using a Gaussian filter. Three-dimensional (3-D) computer-aided design (CAD) models are created from the smoothed segmentations. 3. Treatment planning: The 3-D models are then exported to a finite element method (FEM) software, in which cylinders are virtually inserted within the tumor geometry to represent the sterilized plastic catheters through which the light diffusing optical fibers are placed during treatment. A tetrahedral mesh of approximately 600,000 elements is generated for the tumor geometry along with the surrounding critical structures and cylindrical catheters. We then apply a FEM solution to the light diffusion approximation of the equation for radiative transfer to simulate the light distribution within the tumor geometry during I-PDT. Our FEM has been previously described by Oakley et al. (2015) [20] and is used to determine the number, location, and light parameters of the source CDFs needed to deliver a prescribed light irradiance and fluence to 100% of the tumor volume.

3.6 Preparing the Rabbit and VX2 Tumor for I-PDT Treatment

1. Twenty-four hours prior to the I-PDT treatment, the rabbit is sedated with 0.3 mg/kg acepromazine IV and then anesthetized via face mask with 2% isoflurane in oxygen. An IV catheter is placed in the auricular vein and the photosensitizer is injected slowly through the catheter. The catheter is then flushed with

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0.9% saline and removed. The fiducial markers that were placed during the treatment planning CT scan are removed and tattoos are applied to permanently mark their location. This step is performed because the fiducial markers frequently fall off and can be lost prior to the I-PDT treatment. 2. On the day of I-PDT, the rabbits are sedated with 0.3 mg/kg acepromazine IV and then anesthetized via face mask with 2% isoflurane in oxygen. It is important that the rabbit is in a surgical plane of anesthesia prior to implantation of the I-PDT fibers. An IV catheter is placed in the auricular vein for IV access. 3. The rabbit’s corneas are lubricated and the skin overlying the tumor is aseptically prepared by removing the hair with electric clippers, followed by a chemical depilatory, and then the skin is disinfected with chlorhexidine and isopropyl alcohol followed by Betadine. Meticulous aseptic preparation of the I-PDT treatment area is critical to avoid posttreatment infection. 4. The rabbit is placed on a warm water recirculating heating pad and draped with sterile paper drapes. Monitoring during the fiber insertion procedure includes assessment of respiratory rate, heart rate, pulse oximetry, and core body temperature. Aseptic technique is used while inserting the sterile I-PDT fibers. 5. The rabbit is transported under isoflurane anesthesia to the CT scanner for imaging, which is used to verify correct placement of the fibers. 6. The rabbit is then transported, under isoflurane anesthesia, to the PDT treatment room. During the I-PDT treatment the rabbit is placed on warm water recirculating heating pad for thermal support, and its vital signs (heart rate, EKG, pulse oximetry, respiratory rate, and core body temperature) are monitored every 10 min. 7. I-PDT treatment: Sterilized transparent closed-end sharp catheters are inserted according to the treatment plan (see Subheading 3.5) using the surface fiducial markers as references. The use of these surface fiducial markers has been previously described by Oakley et al. (2017) [21]. The catheters may be inserted perpendicular and/or transverse to the body of the rabbit according to the treatment plan (see Fig. 2). 8. Additional catheters are inserted at the margins of the tumor. Isotropic detection fibers are fed through these catheters and are used to monitor the light irradiance and fluence at the tumor margins to ensure that the prescribed light dose is delivered during treatment. Source CDFs are fed through the catheters based on the treatment plan (see Subheading 3.5). The I-PDT treatment can be performed in one session or

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Fig. 2 CT scans obtained post-catheter insertion. The above figures show two different CT slices of a NZW rabbit with plastic cylindrical catheters inserted throughout the tumor volume. In this particular rabbit, cylindrical catheters were inserted both perpendicular and transverse to the body of the animal

multiple sessions of consecutive light administration depending on the maximum laser power output available. During I-PDT, intravenous fluids (0.9% normal saline) are given at a volume of 5 mL/kg/h. At the conclusion of treatment, opioid (0.05 mg/ kg buprenorphine, subcutaneous) and NSAID (0.5 mg/kg meloxicam, orally) analgesics are given subcutaneously for pain relief, and the rabbit is recovered from anesthesia. 3.7 Posttreatment Follow-up and Treatment Assessment in the Rabbit VX2 Model

1. Post-procedural monitoring and care are critical for a successful outcome with this model. Rabbits must be monitored daily for post-procedure infection, tissue necrosis, and lung metastasis. Non-contrast CT imaging is performed once weekly to monitor for lung metastasis and local response to treatment. Rabbits receive meloxicam (0.5 mg/kg orally SID) and enrofloxacin (5 mg/kg orally SID) daily for analgesia and to prevent local infection at the PDT site. Tissue necrosis and sloughing at the treatment site are expected. The treatment area is examined daily and cleaned with 0.015% hypochlorous acid and treated topically with triple-antibiotic ointment. Necrotic tissue is debrided as needed. Secondary surgical debridement and closure of skin defects may be needed if skin and tissue sloughing are extensive. 2. Posttreatment CT scans are performed weekly for 3 weeks to assess tumor response to treatment. If no tumor growth occurs within the first three weeks, tumor response is evaluated up to 12 weeks posttreatment. If at 12 weeks no tumor is observed on the CT scans, that rabbit will be considered a cure. In some cases, metastasis to the lungs occurs. If this happens, local control can be assessed through CT imaging.

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Notes 1. The Roswell Park mouse SCCVII and the NZW rabbit VX2 cell lines were confirmed to be of mouse origin, and tested for evidence of cross-species contamination (human, rat, Chinese hamster, and African green monkey). No contamination was found. Short tandem repeat (STR) testing was performed and the genetic profile obtained. The VX2 sample was confirmed to be of rabbit origin and no mammalian interspecies contamination was detected. 2. Subcutaneous injection of as little as 100 SCCVII cells in 100 μl sterile PBS into the shoulder region of 8–12-week-old C3H mice will result in a tumor growth within 30 days postinjection. 3. The diet used in the Roswell Park Laboratory Animal Shared Resource does not contain alfalfa, thus lowering the occurrence of natural phytoestrogens. Typical isoflavone concentrations (daidzein + genistein aglycone equivalents) range from 150 to 250 mg/kg. Exclusion of alfalfa reduces chlorophyll, improving optical imaging clarity. 4. Image-based FEM pretreatment planning for mice with SCCVII can be performed using small animals’ MRI as described by Shafirstein et al. (2018) [15].

Acknowledgments The authors would like to thank Diane Filippini for her assistance in obtaining the CT scans and Dr. Craig Hendler MD for conducting the diagnosis of CT scans, at the Department of Radiology at Roswell Park. This work was supported in part by National Cancer Institute of the National Institutes of Health under Award Number R01CA193610 to Gal Shafirstein, and by Roswell Park Comprehensive Cancer Center Support Grant P30CA16056. We thank Concordia Laboratories Inc. for providing the porfimer sodium (Photofrin) at no cost. The authors would like to thank the staff of the shared resources at Roswell Park Comprehensive Cancer Center for their technical assistance in performing these studies: Laboratory Animal Shared Resource and Translational Imaging Shared Resource. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or Roswell Park Comprehensive Cancer Center.

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Conflict of Interest Gal Shafirstein, David Bellnier, and Emily Oakley are co-inventors in patent applications (owned by Roswell Park Comprehensive Cancer Center) of a light dosimetry system for interstitial and thermal photodynamic therapy. Gal Shafirstein acknowledges research grant support from Concordia Laboratories Inc. Gal Shafirstein acknowledges a service on the advisory board for Concordia International Corp. and Pinnacle Biologics, Inc. All other co-authors declare no potential conflicts of interest. References 1. McDonald MW, Lawson J, Garg MK, Quon H, Ridge JA, Saba N, Salama JK, Smith RV, Yeung AR, Yom SS et al (2011) ACR appropriateness criteria retreatment of recurrent head and neck cancer after prior definitive radiation expert panel on radiation oncologyhead and neck cancer. Int J Radiat Oncol Biol Phys 80:1292–1298 2. Bauml J, Seiwert TY, Pfister DG, Worden F, Liu SV, Gilbert J, Saba NF, Weiss J, Wirth L, Sukari A et al (2017) Pembrolizumab for platinum- and cetuximab-refractory head and neck cancer: results from a single-arm, phase II study. J Clin Oncol 35:1542–1549 3. Ferris RL, Blumenschein G Jr, Fayette J, Guigay J, Colevas AD, Licitra L, Harrington K, Kasper S, Vokes EE, Even C et al (2016) Nivolumab for recurrent squamous-cell carcinoma of the head and neck. N Engl J Med 375:1856–1867 4. Vermorken JB, Mesia R, Rivera F, Remenar E, Kawecki A, Rottey S, Erfan J, Zabolotnyy D, Kienzer HR, Cupissol D et al (2008) Platinumbased chemotherapy plus cetuximab in head and neck cancer. N Engl J Med 359: 1116–1127 5. Licitra L, Vermorken JB (2004) Is there still a role for neoadjuvant chemotherapy in head and neck cancer? Ann Oncol 15:7–11 6. Khuri FR, Shin DM, Glisson BS, Lippman SM, Hong WK (2000) Treatment of patients with recurrent or metastatic squamous cell carcinoma of the head and neck: current status and future directions. Semin Oncol 27:25–33 7. Shafirstein G, Bellnier D, Oakley E, Hamilton S, Potasek M, Beeson K, Parilov E (2017) Interstitial photodynamic therapy-a focused review. Cancers (Basel) 9(2):12 8. Karakullukcu B, Nyst HJ, van Veen RL, Hoebers FJ, Hamming-Vrieze O, Witjes MJ, de Visscher SA, Burlage FR, Levendag PC, Sterenborg HJ et al (2012) mTHPC mediated

interstitial photodynamic therapy of recurrent nonmetastatic base of tongue cancers: development of a new method. Head Neck 34: 1597–1606 9. Lou PJ, Jager HR, Jones L, Theodossy T, Bown SG, Hopper C (2004) Interstitial photodynamic therapy as salvage treatment for recurrent head and neck cancer. Br J Cancer 91:441–446 10. Davidson SR, Weersink RA, Haider MA, Gertner MR, Bogaards A, Giewercer D, Scherz A, Sherar MD, Elhilali M, Chin JL et al (2009) Treatment planning and dose analysis for interstitial photodynamic therapy of prostate cancer. Phys Med Biol 54:2293–2313 11. Finlay JC, Zhu TC, Dimofte A, Stripp D, Malkowicz SB, Busch TM, Hahn SM (2006) Interstitial fluorescence spectroscopy in the human prostate during motexafin lutetium-mediated photodynamic therapy. Photochem Photobiol 82:1270–1278 12. Johansson A, Axelsson J, Andersson-Engels S, Swartling J (2007) Realtime light dosimetry software tools for interstitial photodynamic therapy of the human prostate. Med Phys 34: 4309–4321 13. Du KL, Mick R, Busch TM, Zhu TC, Finlay JC, Yu G, Yodh AG, Malkowicz SB, Smith D, Whittington R et al (2006) Preliminary results of interstitial motexafin lutetium-mediated PDT for prostate cancer. Lasers Surg Med 38: 427–434 14. Swartling J, Hoglund OV, Hansson K, Sodersten F, Axelsson J, Lagerstedt AS (2016) Online dosimetry for temoporfinmediated interstitial photodynamic therapy using the canine prostate as model. J Biomed Opt 21:28002 15. Shafirstein G, Bellnier DA, Oakley E, Hamilton S, Habitzruther M, Tworek L, Hutson A, Spernyak JA, Sexton S, Curtin L et al (2018) Irradiance controls photodynamic

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efficacy and tissue heating in experimental tumours: implication for interstitial PDT of locally advanced cancer. Br J Cancer 119: 1191–1199 16. Khurana D, Martin EA, Kasperbauer JL, O’Malley BW Jr, Salomao DR, Chen L, Strome SE (2001) Characterization of a spontaneously arising murine squamous cell carcinoma (SCC VII) as a prerequisite for head and neck cancer immunotherapy. Head Neck 23:899–906 17. Suit HD, Sedlacek RS, Silver G, Dosoretz D (1985) Pentobarbital anesthesia and the response of tumor and normal tissue in the C3Hf/sed mouse to radiation. Radiat Res 104:47–65 18. Elliott JT, Samkoe KS, Gunn JR, Stewart EE, Gardner TB, Tichauer KM, Lee TY, Hoopes PJ, Pereira SP, Hasan T et al (2015) Perfusion CT estimates photosensitizer uptake and biodistribution in a rabbit orthotopic pancreatic

cancer model: a pilot study. Acad Radiol 22: 572–579 19. Shafirstein G, Kaufmann Y, Hennings L, Siegel E, Griffin RJ, Novak P, Ferguson S, Moros EG (2009) Conductive interstitial thermal therapy (CITT) inhibits recurrence and metastasis in rabbit VX2 carcinoma model. Int J Hyperth 25:446–454 20. Oakley E, Wrazen B, Bellnier DA, Syed Y, Arshad H, Shafirstein G (2015) A new finite element approach for near real-time simulation of light propagation in locally advanced head and neck tumors. Lasers Surg Med 47:60–67 21. Oakley E, Bellnier DA, Hutson A, Wrazen B, Arshad H, Quon H, Shafirstein G (2017) Surface markers for guiding cylindrical diffuser fiber insertion in interstitial photodynamic therapy of head and neck cancer. Lasers Surg Med 49:599–608

Chapter 12 Orthotopic Models of Pancreatic Cancer to Study PDT Girgis Obaid, Zhiming Mai, and Tayyaba Hasan Abstract A hallmark of pancreatic ductal adenocarcinoma (PDAC) is its poor prognosis that stems from a marked resistance to therapy, an invasive nature, and a high metastatic potential. Photodynamic therapy (PDT) is a promising modality for effectively managing PDAC both preclinically and clinically. While clinical trials of PDT for PDAC are still in their early stages, a plethora of elegant preclinical studies are supporting the translation and clinical adoption of PDT-based treatment regimens, many of which leverage orthotopic preclinical models of PDAC. Given the aggressiveness of the disease that is largely dependent on the localization of PDAC tumors, it is imperative that preclinical models used to evaluate PDT-based treatment regimens recapitulate elements of the natural pathogenesis in order to design treatment regimens tailored to PDAC with the highest potential for clinical success. In light of the importance of clinically relevant models of PDAC, this chapter details and discusses the methodologies developed over the last three decades to leverage orthotopic PDAC models in order to evaluate PDT-based treatment regimens. The shortcomings of these are also discussed, in addition to the future directions that the field is headed to establish the most relevant orthotopic models of PDAC. Key words Pancreatic ductal adenocarcinoma, Orthotopic models, Photodynamic therapy

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Introduction The response of pancreatic ductal adenocarcinoma (PDAC) to therapeutic regimens, such as photodynamic therapy (PDT)based treatments, has been extensively studied in vitro using tumor cell lines. Although tumor cell lines present a useful model for studying the biochemical and molecular features of PDAC and its response to therapy, they lack the complexity of an in vivo environment, which is crucial for investigating the tumorigenesis, invasiveness, metastasis, and multiparametric responses to treatments. For that reason, in vivo tumor models are more desirable to study PDAC and in order to advance treatments that can improve its clinical management. The various in vivo models used

Girgis Obaid and Zhiming Mai contributed equally with all other contributors. Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_12, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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to study PDAC can be broadly divided into two subcategories: subcutaneous and orthotopic models. Although subcutaneous tumor models offer a facile and robust platform for the preclinical in vivo testing of PDT treatment regimens, they fail to recapitulate the tumor pathophysiology that is characteristic of PDAC. On the contrary, orthotopic models are able to offer a more physiologically relevant representation of the disease. This is exemplified by their capacity to recruit and activate pancreatic stellate cells from the host bone marrow, which induces desmoplasia in the orthotopic PDAC tumors that plays a central role in the resistance of PDAC to treatments [1, 2]. Furthermore, orthotopic implantation of PDAC cells has been shown to precede the invasion of healthy pancreatic tissue, thereby impairing its physiological functions, in addition to metastasizing to the liver, lung, lymph nodes, and peritoneum, as is characteristic of clinical PDAC [3–5]. Specifically, in the context of evaluating PDT efficacy, clinical studies have found that the perfusion of PDAC tumors strongly correlates with positive outcomes to PDT, suggesting that the vascular delivery of photosensitizers (PS) and oxygenation that are affected by the host environment play critical roles [6]. Given that PDACs are characteristically hypovascular with respect to pancreatic tissue, and that orthotopic PDAC models are also hypovascular [7], the orthotopic presence of a xenograft tumor is critical in being able to mimic in vivo treatment responses to PDT, as this has also been found to directly contribute to poor drug delivery and chemoresistance [2, 8]. Orthotopic models used for the preclinical evaluation of PS-based treatments for PDT include cell line-derived models and genetically engineered mouse (GEM) models. This chapter outlines the procedural details of using orthotopic PDAC models to evaluate PDT efficacy and discusses their utility and relevance to human PDAC. In addition, the potential for using established orthotopic syngeneic models and non-murine models in future studies evaluating PDT is also discussed.

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2.1 Cell Line-Based Orthotopic PDAC Models

Orthotopic xenograft mouse models of human PDAC have been used in preclinical studies of PDT treatment efficacy due to their capacity to mimic the tumor microenvironment, which is a critical determinant of tumorigenesis, metastasis, response to treatments, and survival of the host animal. Orthotopic models thus provide a more accurate prediction of the capacity of PDT to control the primary tumor, subsequent distal metastases, and rates and modes of mortality in a manner that is more characteristic of clinically presented PDAC. In the orthotopic xenograft models of PDAC that have been reported for PDT studies in the literature to date,

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pancreatic cancer cells either are implanted directly into the pancreas to form tumors or can spontaneously develop in the pancreas of GEM models that either incorporate oncogenes or lack tumorsuppressing genes. Of these two types of orthotopic models, cell line-derived orthotopic PDAC models are most common type of models used for PDT studies due to their simplicity, predictability, and, most importantly, use of cancer cells from human origin. In this section, we briefly describe the formation of orthotopic PDAC mouse models by the implantation of human pancreatic cancer cell lines, discuss common PDT treatment designs, and introduce some quantitative methods for assessing treatment efficacies. A common approach for preparing orthotopic PDAC tumors involves the implantation of cells in Matrigel to prevent their leakage. A suspension of cancer cells (e.g., 1
106 cells) in 50 μL of 50% ice-cold Matrigel mixed with PBS or cell culture media is typically injected into the tail of the pancreas of an immunocompromised mouse following externalization by laparotomy, as reported previously [4, 9, 10]. During the preparation of orthotopic PDAC models, the need to prevent cell leakage after implantation becomes paramount, as any cells that escape from the implantation site can generate metastases that have no relevance to the natural progression of the disease [3]. Thus, the use of Matrigel is of particular importance in the case of orthotopic PDAC implantation [3, 4, 9, 11]. The cell lines used in this model typically include AsPC-1 cells and MIA PaCa-2 cells, as they represent patients with either highly aggressive and metastatic disease (AsPC-1 derived from metastatic lesion) or less aggressive and less metastatic disease (MIA PaCa-2 derived from primary tumor) [4, 9, 11, 12]. Although experiments have shown that AsPC-1 and MIA PaCa-2 cells can be implanted into severe combined immunodeficient mice (SCID, lacking both T and B lymphocytes) and Swiss nude mice (absent thymus) with a similar capacity to allow for orthotopic tumor formation, the latter is more preferable because of the absence of fur in the nude mice that facilitates experimental procedures such as the laparotomies during implantation and PDT, in addition to longitudinal monitoring of tumors using modalities, such as ultrasound imaging. Both dimensional measurements of excised tumors and noninvasive ultrasound imaging of mice bearing orthotopic PDACs [9] have determined that orthotopic AsPC-1 or MIA PaCa-2 tumors reach a volume of approximately 25–50 mm3 9 days after implantation. Thus, that time point has been deemed as appropriate for the initiation of PDT treatments, as described in more detail below, considering that there are issues with light penetration within tumors when using simple surface illumination protocols. Of the studies reported in the literature, the following is a representative description of a typical PDT procedure performed in an orthotopic PDAC model [4, 9, 12]. Nine days following

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implantation of 1x106 cancer cells into the pancreas as described above, mice are injected intravenously with a photosensitizer such as benzoporphyrin derivative (BPD) formulated into liposomes, at a dose of 0.25 mg/kg equivalent. The pancreas is then externalized in a laparotomy procedure 60–90 min following administration of the PS formulation. Tumors are then irradiated with a 690 nm diode laser operating at an irradiance of 100 mW/cm2 delivering a total fluence of 75 J/cm2 per mouse. The pancreas is then returned to the peritoneum and the abdominal wall and skin are sutured and allowed to heal. Given the complexity of the irradiation process and the time needed for the mice to heal following the laparotomy procedure, the frequency of treatment regimens using repeated PDT procedures is thus limited to the time delay of wound healing. The mice typically heal within 5 days after laparotomy; however, this time delay can be a major limitation for PDT treatment in orthotopic models. The description of the PDT protocol mentioned above is of course only representative, and treatment protocols and regimens can be amended to achieve different responses. For example, in order to augment the intratumoral accumulation of a liposomal formulation of the anticancer drug irinotecan by up to ten-fold, the chemotherapy formulation was administered prior to the administration of the PS [9]. Like before, 60 min following intravenous PS injection, the pancreas was externalized and irradiated with 75 J/cm2 of 690 nm light at an irradiance of 100 mW/cm2. 2.2 Genetically Engineered Mouse (GEM) Models

To date, only one study has used a GEM model to evaluate the efficacy of PDT on orthotopic PDAC tumors [13]. GEM models use mice that have been genetically engineered to cause a loss of tumor-suppressor genes or a gain of oncogenes known to be associated with PDAC, which causes the spontaneous development of mouse PDACs within the pancreas. The major advantage that GEM models offer over orthotopic human cell line xenograft models is the natural disease development and progression that is analogous of the spontaneous development and progression of human PDAC. However, limitations include poor control of tumor size, tumor morphology, and timing of tumor development, in addition to the extended times often needed for tumors to develop [14]. The major limitation of using GEM models for PDT, which is true for other treatment modalities also, is the increased sensitivity of the mouse tumor cells to therapy and the absence of human molecular treatment targets. This limitaction of molecular targets being exclusively of mouse origin becomes increasingly problematic with photoimmunotherapy (PIT, antibody-targeted PDT) and PDT-based combination regimens that utilize targeted smallmolecule inhibitors [14]. Abd-Elgaliel et al. crossed LSL-K-RasG12D mice with floxed p53 mice and pancreatic specific Cre (Pdx-1-Cre) mice to produce

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transgenic mice with conditional p53 deletion (tumor suppressor) and endogenous mutant K-RasG12D [13]. These mice spontaneously developed orthotopic PDAC 6–8 weeks following birth. These mice were then used to explore a targeted PDT approach, whereby a novel derivative of the photosensitizer prodrug, 5-aminolevulinic acid (5-ALA), was used, which is susceptible to cleavage by Cathepsin E that is expressed within tumors. Following spontaneous developments of the tumors, mice were injected intravenously with 50 μL solutions of 5-ALA or the 5-ALA prodrug at a dose of 1 mg/kg. 60 min following administration, the pancreas was externalized by a laparotomy and the pancreas was irradiated with a 652 nm diode laser at an irradiance of 50 mW/cm2 and a fluence of 10 J/cm2. Following irradiation, the pancreas was returned, and the abdominal wall and skin were sutured. The study found that the Cathepsin E-cleavable 5-ALA prodrug induced a greater degree of apoptosis in the GEM tumor than native 5-ALA, as identified by TUNEL staining, with a greater degree of selectivity toward PDAC tumor tissue. There is a wide variety of GEM models of pancreatic cancer that have been described in the literature, which have yet to be investigated in the context of PDT. These GEM models vary in the location of spontaneous tumor formation, the patterns of metastases, and the degrees of aggressiveness [15]. An example of a metastatic GEM PDAC model that experiences a rapid transformation from murine pancreatic intraepithelial neoplasia (mPanIN) to PDAC is the Pdx1-Cre;K-rasG12D;Ink4a/Arf/; p53lox/lox model [15–17]. A particular GEM model such as this one can enable PDT studies that establish dose parameters and combination regimens can inhibit posttreatment metastases, while optimizing the antitumor immune response [18]. Conversely, when wanting to evaluate the longitudinal immunological responses to PDT without confounding results by rapid tumor progression, a nonmetastatic and long-surviving GEM model (18 months), such as the Elastase-tTA TRE-Cre;K-rasG12V model, could prove to be very valuable [15]. 2.3 Prospective Orthotopic Models

In recent years, there have also been significant advances in generating additional sophisticated orthotopic models of PDAC that have not yet been adopted for the evaluation of PDT. These include syngeneic models whereby a host species pancreas is implanted with cells or chunks derived from PDAC that has developed in another rodent of the same species [2, 19]. The most pronounced advantage of syngeneic models is their compatibility with immunocompetent rodents that can provide insights into the immunological consequences of PDT-based treatment regimens [2, 19]. Furthermore, it has been shown that orthotopic implantation of syngeneic tumor chunks derived from genetically engineered models can more faithfully recapitulate the desmoplastic phenotype of PDAC in vivo [20].

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However, there are a number of drawbacks of using syngeneic models, the most noteworthy being the rodent origins of the disease which invariably respond differently to treatment than human tumors. Furthermore, variations in disease target sequence homology between rodent PDAC tumors and human PDAC tumors can yield ambiguous results when evaluating PDT in combination with targeted therapies like small-molecule tyrosine kinase inhibitors and receptor-targeted biologics [21]. Additional orthotopic PDAC models that have not been discussed in the literature for PDT include non-murine models, such as rat models [22] and hamster models of PDAC [23]. In a study by Hogz et al. orthotopic implantation of rat DSL-6A/C1 PDAC cells in 50% Matrigel mixed with saline was compared to the orthotopic implantation of rat DSL-6A/C1 PDAC tumor chunks derived from preformed subcutaneous tumors [22]. The authors found that implantation of the chunks was more frequently successful (>75%) than implantation of the cell suspension (50%), which resulted in peritoneal dissemination, which is indicative of cell leakage. The tumors formed following chunk implantation also presented a dense stroma indicating that the model recapitulated the PDAC desmoplastic reaction. However, a disadvantage of using rats for evaluating treatment regimens, such as PDT, is the quantity of activate ingredients required, such as PSs, which is ca. tenfold greater than that needed for mice considering that their mass is approximately tenfold greater than that of mice. Hamster models have also been used to generate orthotopic PDAC tumors as the pancreas in a hamster has been reported to closely match the histological, topographical, and phylogenetic characteristics of the human pancreas [23]. In a study by Abraham et al. nitrosamine-derived HaP-T1 tumor cell implantation was compared with nitrosamine-derived HaP-T1 tumor chunk implantation into the pancreas [23]. The authors found that tumor cell implantation produced tumors that were more invasive and more metastatic to the lymph nodes, liver, and peritoneum than tumors generated by chunk implantation. Thus, although unexplored in the context of PDT, both rat and hamster orthotopic models of PDAC hold strong potential to evaluate PDT-based regimens that can model a response that closely resembles that of the human disease.

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Data Analysis and Interpretation In a broad sense, treatment efficacy can be evaluated using two metrics: tumor-based outcomes as a function of inhibition of growth and metastases, and host-based outcomes as a function of long-term mice survival. Inhibition of tumor growth can be quantified by a simple weight measurement of excised tumors upon

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Fig. 1 Ultrasound image showing a cross section of an orthotopic MIA PaCa2 tumor in an anesthetized Swiss nude mouse. Width and height measurements of the tumor shown in blue were obtained using the VevoLAZR, VisualSonics software (figure courtesy of Dr. Srivalleesha Mallidi and is associated with a previously published study [9])

termination of the study. However, terminal measurements do not account for dynamic longitudinal changes in tumor volume or for rates of tumor growth in response to PDT. Thus more sophisticated methods for monitoring tumors following therapy are needed [12]. Although not as readily accessible for longitudinal monitoring as subcutaneous tumors, the introduction of sophisticated imaging modalities, such as ultrasound imaging, has facilitated the monitoring of orthotopic PDAC tumors deeply seated within live mice [9]. An example of the utility of ultrasound imaging for determining orthotopic PDAC tumor volume is shown in Fig. 1, where a 3D reconstruction of the tumor is acquired, and length, width, and height dimensions are measured post-imaging. Using the hemiellipsoid equation, Volume ¼

π
length
width
height , 6

the tumor volumes can be calculated and monitored in response to PDT-based treatments and throughout the duration of disease progression. In addition to monitoring primary orthotopic PDAC tumor volumes, metastases, which play a critical role in the disease progression of clinical PDAC, can be detected using classical H&E staining of the draining lymph nodes, and secondary organs. The

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Fig. 2 (a) Liver and lymph node metastasis from orthotopic ASPC-1 tumors following PDT-based combination therapies following treatment with the c-MET/VEGFR-2 inhibitor (XL184), free or in a nanoparticle (NP); with PDT using liposomal BPD (L[BPD]); with combinations of BPD and XL184; and with co-encapsulated XL184 nanoparticles within BPD liposomes (PMIL). (b) Immunohistochemical cross section of an orthotopic ASPC-1 tumor in the pancreas with human cancer cells stained with anti-human cytokeratin 8 antibodies, intratumoral microvessels colored red and peritumoral microvessels colored white (figure adapted from Spring B.Q. et al. (2016) Nat. Nanotechnol. 11:378–387 doi:https://doi.org/10.1038/nnano.2015.311)

hallmark of a xenograft model is the coexistence of cells from two different species—human tumor cells and mouse host cells. This advantage enables a real-time polymerase chain reaction (RT-PCR)-based method to differentially amplify the human and mouse housekeeping gene cDNA fragments to quantitatively estimate the number of human cancer cells in excised mouse organs, which we have described previously as a routine approach to quantify metastatic burden in these orthotopic models [4]. Figure 2a shows a summary of RT-PCR quantitation of liver and lymph node metastases from an orthotopic AsPC-1 tumor following treatment with the anti-metastatic and antivascular c-MET/VEGFR-2 inhibitor (XL184), free or in a nanoparticle (NP); with PDT using liposomal benzoporphyrin derivative (L[BPD]); with combinations of BPD and XL184; and with co-encapsulated XL184 nanoparticles within BPD liposomes (photoactivable multi-inhibitor nanoliposome, PMIL). PDT-based combination therapy was induced nine days following implantation of AsPC-1 cells into the pancreas as described above. As a result of the vascular targets of this nanoparticle-based combination regimen, cross sections of the orthotopic tumors were also stained for human cancer cells (cytokeratin 8, green) and endothelial cells within (red) and outside (white) the tumor (Fig. 2b). Using these methods, Spring et al. demonstrated that the combination PMIL nanoconstruct treatment resulted in a selective reduction in the intratumoral microvessel density feeding the tumor, as compared to the peritumoral space.

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Fig. 3 H&E staining of sections of pancreatic tissue in the absence (a, b, c) or presence of a transgenic PDAC tumor (d, e, f). Apoptotic tissue stained for TUNEL is shown in brown (arrows) and was visualized by using ApopTag Peroxidase Kit. Scale bars are 200 μm. Reprinted from Abd-Elgaliel WR, Cruz-Monserrate Z, Wang H, Logsdon CD and Tung CH, Pancreatic cancer-associated Cathepsin E as a drug activator, 221–227, Copyright (2013), with permission from Elsevier

In the study by Abd-Elgaliel et al. [13], analysis of the PDT treatment response in the GEM model mice bearing orthotopic PDACs was performed terminally on tissue sections. The GEM mice were sacrificed 24 h after 5-ALA-based PDT and the pancreases were sectioned and stained with conventional H&E to visualize areas of necrosis in addition to TUNEL staining to visualize areas of apoptotic tissue (Fig. 3). By evaluating the degree of apoptosis from the tumor section images derived, the authors were able to conclude that the treatment was more selective than conventional 5-ALA-based PDT.

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Discussion As tumor models of PDAC grow in sophistication, they increasingly represent human presentations of pancreatic cancer more faithfully. Importantly, the cellular, molecular, and macrophysiological responses to PDT become more pertinent and outcomes of treatment protocols tested in orthotopic models become more predictive of PDT patient responses. With this growing sophistication comes challenges with accessibility to implantation and photoirradiation, in addition to limitations in species-dependent sequence homology of molecular targets, as is the case for GEM models and syngeneic models. However, the power of evaluating a PDT-based treatment protocol designed for PDAC in an orthotopic setting, complete with stromal cell recruitment, desmoplasia, and hypovascularity, makes these models some of the most

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appealing and predictive of how patients might respond to such treatments in the clinic, further expediting the translation of PDT for managing PDAC in the clinic [24]. Given that orthotopic PDAC models have not been reported so extensively to date for testing PDT regimens, existing models developed in the literature, such as syngeneic mouse, rat, and hamster PDAC models, hold strong potential for increasing the relevance of orthotopic testing, especially in the context of a functional immune system.

Acknowledgments We would like to acknowledge NIH grants K99CA215301 and R00CA215301 to Girgis Obaid, and P01CA084203 and S10 ODO1232601 to Tayyaba Hasan. Girgis Obaid and Zhiming Mai contributed equally to this work. References 1. Scarlett CJ, Colvin EK, Pinese M, Chang DK, Morey AL, Musgrove EA, Pajic M, Apte M, Henshall SM, Sutherland RL et al (2011) Recruitment and activation of pancreatic stellate cells from the bone marrow in pancreatic cancer: a model of tumor-host interaction. PLoS One 6:e26088 2. Erstad DJ, Sojoodi M, Taylor MS, Ghoshal S, Razavi AA, Graham-O’Regan KA, Bardeesy N, Ferrone CR, Lanuti M, Caravan P et al (2018) Orthotopic and heterotopic murine models of pancreatic cancer and their different responses to FOLFIRINOX chemotherapy. Dis Model Mech:11 3. Chai MG, Kim-Fuchs C, Angst E, Sloan EK (2013) Bioluminescent orthotopic model of pancreatic cancer progression. J Vis Exp 76: 50395 4. Spring BQ, Bryan Sears R, Zheng LZ, Mai Z, Watanabe R, Sherwood ME, Schoenfeld DA, Pogue BW, Pereira SP, Villa E et al (2016) A photoactivable multi-inhibitor nanoliposome for tumour control and simultaneous inhibition of treatment escape pathways. Nat Nanotechnol 11:378–387 5. Higuchi T, Yokobori T, Naito T, Kakinuma C, Hagiwara S, Nishiyama M, Asao T (2018) Investigation into metastatic processes and the therapeutic effects of gemcitabine on human pancreatic cancer using an orthotopic SUIT2 pancreatic cancer mouse model. Oncol Lett 15:3091–3099 6. Jermyn M, Davis SC, Dehghani H, Huggett MT, Hasan T, Pereira SP, Bown SG, Pogue BW (2014) CT contrast predicts pancreatic cancer

treatment response to verteporfin-based photodynamic therapy. Phys Med Biol 59: 1911–1921 7. Craven KE, Gore J, Korc M (2016) Overview of pre-clinical and clinical studies targeting angiogenesis in pancreatic ductal adenocarcinoma. Cancer Lett 381:201–210 8. Feig C, Gopinathan A, Neesse A, Chan DS, Cook N, Tuveson DA (2012) The pancreas cancer microenvironment. Clin Cancer Res 18:4266–4276 9. Huang HC, Mallidi S, Liu J, Chiang CT, Mai Z, Goldschmidt R, Ebrahim-Zadeh N, Rizvi I, Hasan T (2016) Photodynamic therapy synergizes with irinotecan to overcome compensatory mechanisms and improve treatment outcomes in pancreatic cancer. Cancer Res 76: 1066–1077 10. Obaid G, Spring BQ, Bano S, Hasan T (2017) Activatable clinical fluorophore-quencher antibody pairs as dual molecular probes for the enhanced specificity of image-guided surgery. J Biomed Opt 22:1–6 11. Dai L, Lu C, Yu XI, Dai LJ, Zhou JX (2015) Construction of orthotopic xenograft mouse models for human pancreatic cancer. Exp Ther Med 10:1033–1038 12. Huang H-C, Rizvi I, Liu J, Anbil S, Kalra A, Lee H, Baglo Y, Paz N, Hayden D, Pereira S (2018) Photodynamic priming mitigates chemotherapeutic selection pressures and improves drug delivery. Cancer Res 78: 558–571

Orthotopic Models of Pancreatic Cancer 13. Abd-Elgaliel WR, Cruz-Monserrate Z, Wang H, Logsdon CD, Tung CH (2013) Pancreatic cancer-associated Cathepsin E as a drug activator. J Control Release 167:221–227 14. Richmond A, Su Y (2008) Mouse xenograft models vs GEM models for human cancer therapeutics. Dis Model Mech 1:78–82 15. Westphalen CB, Olive KP (2012) Genetically engineered mouse models of pancreatic cancer. Cancer J 18:502–510 16. Lee JW, Komar CA, Bengsch F, Graham K, Beatty GL (2016) Genetically engineered mouse models of pancreatic cancer: the KPC model (LSL-Kras(G12D/+) ;LSL-Trp53 (R172H/+) ;Pdx-1-Cre), its variants, and their application in immuno-oncology drug discovery. Curr Protoc Pharmacol 73:14 39 1–14 39 20 17. Bardeesy N, Aguirre AJ, Chu GC, Cheng K-h, Lopez LV, Hezel AF, Feng B, Brennan C, Weissleder R, Mahmood U (2006) Both p16Ink4a and the p19Arf-p53 pathway constrain progression of pancreatic adenocarcinoma in the mouse. Proc Natl Acad Sci U S A 103:5947–5952 18. Kosharskyy B, Solban N, Chang SK, Rizvi I, Chang Y, Hasan T (2006) A mechanism-based combination therapy reduces local tumor growth and metastasis in an orthotopic model of prostate cancer. Cancer Res 66: 10953–10958

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19. Nikfarjam M, Yeo D, He H, Baldwin G, Fifis T, Costa P, Tan B, Yang E, Wen S, Christophi C (2013) Comparison of two syngeneic orthotopic murine models of pancreatic adenocarcinoma. J Invest Surg 26:352–359 20. Majumder K, Arora N, Modi S, Chugh R, Nomura A, Giri B, Dawra R, Ramakrishnan S, Banerjee S, Saluja A et al (2016) A novel immunocompetent mouse model of pancreatic cancer with robust stroma: a valuable tool for preclinical evaluation of new therapies. J Gastrointest Surg 20:53–65. discussion 65 21. Behrens D, Walther W, Fichtner I (2017) Pancreatic cancer models for translational research. Pharmacol Ther 173:146–158 22. Hotz HG, Reber HA, Hotz B, Foitzik T, Buhr HJ, Cortina G, Hines OJ (2001) An improved clinical model of orthotopic pancreatic cancer in immunocompetent Lewis rats. Pancreas 22: 113–121 23. Abraham AT, Shah SR, Davidson BR (2004) The HaP-T1 Syrian golden hamster pancreatic cancer model: cell implantation is better than tissue implantation. Pancreas 29:320–323 24. Huggett MT, Jermyn M, Gillams A, Illing R, Mosse S, Novelli M, Kent E, Bown SG, Hasan T, Pogue BW et al (2014) Phase I/II study of verteporfin photodynamic therapy in locally advanced pancreatic cancer. Br J Cancer 110:1698–1704

Chapter 13 An Orthotopic Murine Model of Peritoneal Carcinomatosis of Ovarian Origin for Intraoperative PDT Thierry Michy, Claire Bernard, Jean-Luc Coll, and Ve´ronique Josserand Abstract Advanced ovarian cancer is the most serious among gynecological malignancies and is associated with 35% five-year overall survival. Surgery is the first therapeutic indication, and the absence of remaining macroscopic lesions is the most important prognostic factor. However, tumor dissemination over the whole abdominal cavity largely contributes to the difficulty of complete surgical resection. Consequently, any therapeutic approach that may complete surgical resection should improve patient survival. Considering that some sites are not suitable for surgery because of their close location to vital organs, intraoperative photodynamic therapy (ioPDT) appears to be a complementary therapeutic approach to surgery to obtain the lowest residual disease. Relevant in vivo cancer models that closely resemble human ovarian cancer are essential for preclinical research of alternative antitumor therapeutic strategies. Thus, we propose a comprehensive protocol to set up an orthotopic ovarian xenograft in mice leading to peritoneal carcinomatosis that could be harnessed for antitumor therapeutic application and evaluation. Key words Intraoperative Photodynamic Therapy, Ovarian peritoneal carcinomatosis, Bioluminescence imaging, Orthotopic implantation, Murine model

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Introduction Worldwide, epithelial ovarian carcinoma is the leading cause of mortality among gynecological malignancies [1] and is associated with a 35% five-year overall survival [2]. At the time of diagnosis, approximately 75% of women with ovarian cancer present with an advanced stage of the disease. Currently, treatment is based on cytoreductive surgery completed by chemotherapy (intravenous cisplatin and paclitaxel repeated every 3 weeks for a total of 6 treatment courses). The therapeutic management consists of selecting patients who should benefit from primary cytoreductive surgery followed by six courses of chemotherapy and those that would be better served by neoadjuvant chemotherapy with consideration of interval debulking pending chemotherapy response

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_13, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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[3]. Decision-making depends on the extent of the disease that needs to be evaluated before surgery and will partly determine the ability to perform a complete cytoreduction. However, preoperative assessment by noninvasive imaging for evaluation of the peritoneal spread in intraperitoneal and pelvic malignant tumors is not informative enough with false-positive and false-negative rates reaching more than 20%, which is not acceptable [4]. Currently, the gold standard for precisely quantifying the intra-abdominal extent of peritoneal carcinomatosis is laparoscopic exploration. Scores are attributed based on a combination of the distribution and quantification of the tumor load throughout all abdominopelvic regions [5, 6]. The PCI (Peritoneal Cancer Index) and Fagottimodified scores (see Note 1) are the most relevant for predicting the ability to perform a complete resection [7]. However, some areas may not be explored and provide incomplete assessment of tumor extent due to adhesions or pelvic area that are not accessible before larger tumor masses are removed. When surgery is performed, several studies have demonstrated that the amount of residual disease is the most important impact factor of survival [8–11]. Since 1986, the Gynecologic Oncology Group (GOG) has defined the optimal residual disease as measuring 1 cm in diameter [12]. Unfortunately, conventional cytoreductive surgery often remains suboptimal for a number of patients. Indeed, some tumor situations such as implants in the small or large bowel mesentery, hepatic pedicle involvement, and carcinomatosis including bulky nodes on the diaphragm surface and on the mesentery may cause postoperative surgical complications. As a consequence, adjuvant therapy such as intraoperative photodynamic therapy (ioPDT) that could be applied immediately following surgical tumor debulking and could treat residual peritoneal tumors in areas where surgical procedures are at high risk of perioperative complications would be of great value [13, 14]. The use of PDT for the treatment of peritoneal carcinomatosis was first investigated in mice by Tochner et al. in 1986 [15] and they reported a high cure rate of 85% that encouraged further research over the next 30 years. Three human trials (Phases I and II) have been conducted so far and have shown that applying PDT after surgical debulking of peritoneal carcinomatosis is feasible with some clinical benefits [16, 17]. Overall survival was slightly prolonged but the low tumor-to-normal tissue selectivity ratio of the photosensitizer (Photofrin) as well as its prolonged retention time in tissues led to significant toxicities, mainly capillary leak syndrome, bowel perforation, and skin damage. Since then, secondgeneration photosensitizers with better tumor selectivity and shorter in vivo retention time have been developed and have shown promising results in animal models with 15–300% increase in survival, extended tumor necrosis, and tumor size reduced by up

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to 90% [18]. Presently, new opportunities are offered by tumortargeted PDT in which photosensitizers are conjugated to tumorspecific moieties (antibodies, peptides, or ligands such as folic acid) and this recent strategy warrants further investigation in animal models. To assess the efficacy of new therapeutic strategies for advanced ovarian cancer, it is necessary to set up a murine model of peritoneal carcinomatosis similar to the human clinical situation by taking into account the pathophysiological mechanisms of ovarian cancer dissemination. Ninety percent of ovarian cancers develop from the coelomic epithelium, and the most frequent histological type is the serous one. Historically, the pathogenesis of ovarian serous tumors has focused on origins within the ovary, and tumor transformation of the ovarian surface epithelium was found to be caused by different risk factors [19]. However, more recent literature has suggested that the fallopian tubes may also be a source of serous epithelioma ovarian cancer and primary peritoneal tumor nodules [20, 21]. First, the epithelia of both the fallopian tube and ovarian surface share a common mesodermal embryological origin and a close anatomic proximity derived from an invagination of the coelom known as the Mullerian or paramesonephric ducts [22]. In 1999, Dubeau et al. proposed that they may form identical histological entities that degenerate in the same way. Second, recent studies have suggested that excision of the fimbriae from tubal sterilization in the general female population may confer the greatest risk reduction of serous epithelioma ovarian cancer and primary peritoneal tumor nodules [23, 24]. This hypothesis was confirmed by the implementation of prophylactic salpingo-oophorectomy for familial risk, which has shown a high prevalence of tubal carcinoma or precursor serous tubal intraepithelial carcinoma in resected tissue [25]. Additionally, it was shown in Dicer-p10 double-knockout mice models that the tube was the source of epithelioma ovarian cancer [26]. Consequently, when considering the development of an animal model of peritoneal carcinomatosis of ovarian origin, orthotopic implantation of human ovarian adenocarcinoma cells in mice appears to be the most representative in terms of anatomical and pathophysiological properties of human ovarian cancer. Contrary to direct intraperitoneal injection of human tumor cells in mice that leads to random peritoneal dissemination, orthotopic implantation in the fallopian tube perfectly reproduces the pathogenesis of ovarian cancer in which peritoneal metastases disseminate from the primary tumor site alike in human peritoneal carcinomatosis from advanced ovarian cancer where the peritoneal liquid circulation washes the ovarian surface and thus disseminates tumor cells in the abdominal cavity [10].

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Here, we propose a comprehensive protocol to set up an orthotopic murine model of carcinomatosis of ovarian origin. Animal preparation (anesthesia, analgesia, and laparotomy) and tumor cell intratubal implantation will be described, and primary tumor growth and metastasis will be depicted by noninvasive bioluminescence imaging. Intra-abdominal development of the primary tumor in this model appears to be anatomically close to human peritoneal carcinomatosis from ovarian origin. Because of peritoneal liquid circulation, ovarian tumor cell dissemination leads to invasion of whole parietal and visceral peritoneum layers as well as intra- and retroperitoneal organs.

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Materials

2.1 Cell line and Culture Conditions

1. Human ovarian adenocarcinoma cell line SKOV3 (ATCC HTB-77). 2. RPMI 1640 medium supplemented with 1% glutamine and 10% fetal bovine serum. 3. SKOV3pGL3 cell line is derived from luciferase stable transfection of SKOV3 cells (see Note 2). 4. Dulbecco’s phosphate-buffered saline (1X). 5. Trypsin-EDTA 0.5%.

2.2 Animal Preparation

1. Six-week-old female NMRI nude mice, kept under pathogenfree conditions, fed and watered ad libitum in cages of 4–5 animals in a dedicated room at 23  3  C with a 12-h light/ dark cycle (see Note 3). 2. Isoflurane. 3. Carbomer 980 hydrogel (2 mg/g). 4. Antiseptic dermal solution of povidone-iodine 10%. 5. Buprenorphine (0.3 mg/mL). 6. Surgical tools: scalpel, surgical nippers, 29 G needle, 2 clamps. 7. Optime 4/0 and Monocryl 4/0 resorbable suture wires.

2.3

Animal Imaging

1. D-Luciferin (100 mg/mL) to be 10 diluted in PBS. 2. One milliliter syringe with 25G needle. 3. IVIS Bioluminescence imaging system and Living Image image analysis software.

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3.1 Preparation of Cells for Injection

On the day of orthotopic injection, SKOV3-Luc cells at ~60% confluency are washed twice with 1x phosphate-buffered saline (PBS), harvested by trypsinization (10 min at 37  C), and, after centrifugation at 250  g for 5 min, resuspended in cold 1 PBS at a concentration of 6  107 cells/mL. Cell suspension is homogenized by gently upturning the tube several times before taking a 50 μL sample (3  106 cells) in a 1 mL syringe immediately before injection to avoid redeposit or cell agglomerates.

3.2 Anesthesia and Analgesia

1. Weigh and identify the mouse before anesthesia (isoflurane/air 4% for induction and 2% thereafter) and place it on a heating mat (37  C) on the right flank. 2. Apply a drop of carbomer 980 hydrogel (2 mg/g) on both eyes to prevent dryness during anesthesia. 3. Disinfect the right flank using yellow betadine on a cotton bud (Fig. 1a). 4. For analgesia purposes, inject buprenorphine (0.1 mg/kg of body weight) subcutaneously using a 29 G needle (Fig. 1b). 5. Control the level of anesthesia by pinching the footpad before starting the surgery.

Fig. 1 Intratubal injection of ovarian cancer cells. (a) Disinfection of the flank, (b) subcutaneous injection of buprenorphine, (c) incision of the skin, (d) isolation of the right adnexa, (e) distal and proximal clamping of the fallopian tube, (f) injection of cells in the fallopian tube, (g) replacement of the fallopian tube in the abdominal cavity, and (h) suture of the peritoneum and the skin

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3.3 Intratubal Injection Procedure

1. Using sterile surgical scissors and forceps, perform a 2 cm skin incision on the right lower abdominal area (Fig. 1c) (see Note 4). 2. Lift the muscle and perform an incision to reach the peritoneum. 3. Identify and isolate the right adnexa (Fig. 1d). 4. Using a sterile surgical nipper, clamp both the proximal and distal fallopian tube (Fig. 1e). 5. Insert a 29 G needle into the tube at a 45 angle and slowly inject 50 μL of cell suspension into the lumen of the fallopian tube in a retrograde manner (Fig. 1f). 6. Slowly remove the needle and wait for 15 s before releasing the proximal clamp. Then, replace the fallopian tube in the abdominal cavity while keeping the distal clamp (Fig. 1g). When the adnexa are replaced, then release the distal clamp (see Note 5). 7. Close the peritoneum and the skin by simple interrupted stitches with a synthetic absorbable suture (Optime 4/0 for the peritoneum and Monocryl 4/0 for the skin) (Fig. 1h). 8. Replace the mouse on the right flank in the cage. Make sure that all animals are awake and active before leaving unattended and look after the mice daily to control their scars and any possible signs of pain or infection.

3.4 Tumor Growth and Metastasis Monitoring by Noninvasive Bioluminescence Imaging

1. By using a human ovarian adenocarcinoma cell line that stably expresses the luciferase reporter gene (SKOV3-Luc), noninvasive bioluminescence can first be used to monitor primary tumor growth and peritoneal carcinomatosis dissemination and second to evaluate therapeutic efficacy. Primary tumor growth and metastasis are monitored weekly by in vivo bioluminescence imaging. 2. Five minutes before imaging, vigil mice receive a 300 μL intraperitoneal injection of D-luciferin (150 mg/kg) and are anesthetized (isoflurane/air 4% for induction and 2% thereafter) 3 min before being placed in the optical imaging system (IVIS Kinetic, Perkin Elmer) for 2 successive acquisitions (supine (Fig. 2) and right position). 3. Bioluminescence images are presented in false colors using a rainbow scale and superimposed on a photographic image of the mouse. 4. Semiquantitative data of luciferase-positive tumor cell signals are obtained by drawing regions of interest on the abdomen using the manufacturer’s software (e.g., Living Image; Perkin Elmer). Over time, these noninvasive measurements provide a rough localization of tumor nodules and a relative quantitation of luciferase-positive cells that reflects the evolution of the global tumor burden.

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Fig. 2 Clinical presentation of ovarian cancer development in mice (supine position) using noninvasive bioluminescence imaging 21 days after tumor cell implantation. Black arrow: primary tumor

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Notes 1. Peritoneal Cancer Index (PCI) is clinically used to describe the peritoneal spread of intraperitoneal and pelvic malignant tumors. The PCI quantitatively combines the distribution of the tumor throughout 13 abdominopelvic regions with a lesion size score. Every lesion size is scored from 1 to 3. A numeric score from 0 to 39 indicates the extent of the disease within all regions. This index has been adapted for evaluation in rodents in which the abdominal cavity is divided into 4 quadrants, to which are assigned a score of 0–5 based on the tumor size inside (0: no detectable tumor, 1: 0–0.5 cm tumor, 2: 0.5–1 cm tumor, 3: 1–2 cm tumor, 4: 2–3 cm tumor, 5: >3 cm tumor). The results of all four quadrants are summated giving a 0–20 experimental PCI score. Fagotti-modified scoring is a laparoscopy-based clinical score for predicting surgical resectability, taking into account diaphragmatic carcinomatosis, mesenteric retraction, stomach infiltration, and liver metastases. In this score, each item is assigned an index value of 2. In the final model 78% of patients were optimally resected when the predictive index score was 85% inhibition for a 20 mg/kg dose. The sedation of a pro-inflammatory phenotype of immune cells was echoed in monocyte-derived macrophages from healthy subjects and rheumatoid arthritis patients, where RWJ 67657 (0–10 μM) reduced protein levels of TNF-α (IC50 ¼ 0.03 μM in patients), IL-6, IL-8 (IC50 ¼ 1.2 μM in patients), and matrix metalloproteinase-9 (MMP-9) and transcript levels of TNF-α, IL-1β, IL-6, IL-8, and COX-2 [272]. RWJ 67657 inhibited the activity of p38 but not its phosphorylation in lipopolysaccharide-stimulated monocyte-derived macrophages. A study in IL-1β- and TNF-α-stimulated human umbilical vein endothelial cells showed similar inhibitory behavior of RWJ 67657 toward IL-6, IL-8, and E-selectin but had no effect on intercellular adhesion molecule 1 (ICAM-1) and vascular cell adhesion protein 1 (VCAM-1). Combination treatment with RWJ 67657 and the NF-κB inhibitor MOL-294 strongly augments the antiinflammatory effects [268]. Given the importance of inflammatory signaling in tumor biology as well as cellular and molecular responses to PDT (see Subheading 2), pharmacological immunomodulation at the level of p38 after PDT is expected to confer beneficial effects on therapeutic outcome. Unfortunately, only a few studies examined the effects of RWJ 67657 on cancer cells and none have been conducted in the framework of PDT. In human breast cancer (MCF-7 and MCF-7TN-R) cells, RWJ 67657 dose-dependently inhibited p38 and decreased ATF and NF-κB signaling, resulting in impaired clonogenic survival as well as stalled tumor growth in immunocompromised female ovariectomized mice bearing MCF-7TN-R xenografts (dosing: 60 mg/kg for 9 d) [265]. Additionally, RWJ 67657 (0–10 μM) blocked critical proteins that mediate EMT (Twist, Snail, Slug, and zinc finger E-box binding homeobox 2 (ZEB2) [343]) and favorably modulated expression levels of miRNAs that are involved in resistance to chemotherapy and endocrine therapy (miR-199, miR-200, miR-302, miR-303, and miR-328 [344–347]). An earlier study by the same group also looked into the effect of RWJ 67657mediated p38 inhibition on estrogen receptor activity in breast cancer (MCF-7) cells, nonmalignant breast epithelial (MCF10A) cells, and human embryonic kidney (HEK 293) cells [266]. RWJ 67657 was able to reduce cell growth via p38 inhibition, which in turn induced downregulation of the estrogen receptor and its co-activators steroid receptor coactivator-1 (SRC-1), SRC-2, and SRC-3.

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SB202190 or FHPI (4-(4-fluorophenyl)-2-(4-hydroxyphenyl)-5(4-pyridyl)1H-imidazole) is a pyridinyl imidazole derivative that selectively inhibits p38α and p38β isoforms via competitive binding in the catalytic ATP-binding site [240]. The compound has been tested for antiviral and anti-inflammatory properties in neurodegenerative diseases [240, 282–284]. SB202190 has been investigated in PDT alongside other p38 inhibitors. Luna et al. [275] reported that Photofrin-PDT of mouse fibrosarcoma (RIF-1) cells resulted in transcriptional engagement of the NF-κB-, CRE-2-, C/EBP-, and AP-1 response elements (see Fig. 2). Photofrin-PDT further induced phosphorylation of p38, c-JUN, ERK1/2, and SAPK/JNK and promoted nuclear protein binding to the NF-κB, CRE-2 (activated by p38 and ERK1/2), c-FOS, and c-JUN response elements. COX-2 expression was subdued by inhibitors of p38 (SB202190 and SB203580), slightly reduced following MEK1 inhibition by U0126 (directly upstream of ERK1/2), and not influenced after NF-κB inhibition with SN50. Given that COX-2 promotes tumor cell proliferation, metastasis, and therapeutic recalcitrance [278] and given the steering role of the p38 pathway herein, the results reflect adjuvant potency of SB202190 in PDT. Another study on Pc4-PDT in mouse leukemic lymphoblasts (LY-R) and Chinese hamster ovary (CHO) cells showed that SB202190 blocked PDT-induced apoptosis in mainly LY-R cells and to a lesser extent in CHO cells. While PDT strongly activated p38/HOG in CHO cells, no such activation occurred in LY-R cells despite the p38-mediated cell death. The authors contended that the high level of constitutively active p38/HOG in LY-R cells may have predisposed the cells to rapid activation of apoptosis following PDT. Constitutive p38 overexpression in itself could serve as a barometer to gauge whether cancer cells are more amenable to PDT [277], especially in light of the fact that prolonged activation of AP-1 transcription factors (that are activated by p38 upstream) poises cells for apoptosis (see Fig. 3). In contrast, a study by Chan et al. [276] on hypericin-PDT demonstrated that p38 inhibition by SB202190 and SB203580 enhanced apoptosis in nasopharyngeal carcinoma (HK-1) cells, which was mediated by caspase-9 and caspase-3. P38 and JNK were rapidly activated by PDT, an effect that in turn was inhibited by 1O2 scavengers. Blockade of p38 but not JNK (by SP600125) accelerated the proteolytic cleavage of caspase-9 and execution of the apoptotic program. Besides effects on PDT-induced apoptosis, studies have shown that SB202190 inhibition of p38 has additional downstream effects that could benefit cancer therapy. SB202190 downregulates leukocyte-adhesion molecules such as ICAM-1 and various pro-inflammatory cytokines that collectively could hamper tumor sustenance [285–287, 348]. SB202190 was able to inhibit spheroid invasion in ovarian cancer (SKOV3) cells [279], although this

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was contrary to another study showing that SB202190 increased cell migration through inhibition of p38 in human corneal epithelial cells as a result of the involvement of p38 in the EMT process [288]. In a combined treatment regimen with SB203580 and SB590885, SB202190 exerted an antiproliferative effect on melanoma cells carrying a BRAF V600E mutation and induced endolysosomal perturbations possibly as a result of interference in the endocytic transport machinery [280]. Furthermore, SB202190 was able to induce transcription factor EB (TFEB)/transcription factor binding to IGHM enhancer 3 (TFE3)-dependent autophagy and lysosomal biogenesis independently of p38 inhibition [281], which might be related to its aforementioned effect on lysosomal processing [280]. Autophagy can have cytoprotective functions, which should be ruled out before combining PDT with SB202190. 4.2.6 SB203580

As PD 169316, SB203580 is a synthetic 2,4,5-triarylimidazole that selectively inhibits p38 catalytic activity by binding to the ATP-binding pocket without inhibiting phosphorylation of p38 by upstream kinases [298]. Inhibition of p38 by SB203580 has generally been associated with an increase in apoptosis in human cancer cells, as was shown in melanoma (Colo 853 and FO-1) cells following p38 induction with, respectively, farnesylthiosalicylic acid [294] and adenoviral melanoma differentiation-associated gene-7/ IL-24 [290]; in breast cancer (MDA-MB-453 and MDA-MB-231) cells where p38 was activated with, respectively, α-tocopheryloxybutyric acid [297] and aplidin [291]; in neuroblastoma (SH-SY5Y) cells where p38 was induced by the prion protein mimetic peptide PrP106–126 [292]; and in colon cancer (HT-29) cells where p38 was stimulated with indomethacin [293]. The activated p38-mediated apoptosis proceeded via caspase-3 in those studies that had assayed caspase-3. Ye et al. [299] further demonstrated that SB203580 can reverse p38 activation and consequent apoptosis by the phytochemical 3,30 -diindolylmethane even when the upstream ASK-1 activator TRAF2 (see Fig. 3) is repressed. Also, p38 has been associated with moderating P-glycoprotein (P-gp) levels in murine leukemia (L1210/VCR) cells, which imparted MDR against vincristine. SB203580 treatment considerably reversed the MDR and resensitized the cells to vincristine [295]. Finally, SB203580 inhibited human renal cancer (Caki-1) cell migration and invasion induced by butaprost by inactivating p38 and consequently downregulating MMP-9 protein levels and activity [296]. SB203580 has been investigated in the context of PDT and p38 as exemplified in Subheading 3 with the data from Song et al. [187], who demonstrated the deleterious effects of SB203580 on pro-inflammatory (survival) signaling. Wang et al. [178] reported that PDT with the PS berberine sensitized cisplatin-resistant human melanoma (A375/DDP, SKMel-19/DDP, and

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M8/DDP) cells to cisplatin, an effect that coincided with an increase in protein levels of p-p38, p-JNK, p-ERK1/2, BAX, cleaved caspase-9, and cleaved caspase-3 and a reduction in Bcl-2. Neutralization of ROS with NAC and blocking of p38 with SB203580 reduced the extent of PDT-induced cell death by roughly 100% and 50%, respectively, whereby NAC treatment also downregulated p38 protein levels. Lastly, Ge et al. [179] demonstrated that ALA-PDT of human squamous carcinoma (SCL-1) increased levels of p-MEK, p-ERK1/2, p-p38, p-Elk-1, p-JNK, and p-c-Jun and that inhibition of ERK1/2 with PD98059, p38 with SB203580, and JNK with SP60125 reversed these changes and amplified apoptotic cell death. 4.2.7 SB239063

SB239063 (trans-1-(4-hydroxycyclohexyl)-4-(4-fluorophenyl)-5[(2-methoxy)pyrimidin-4-yl] imidazole) is a potent and selective p38 inhibitor (IC50 ¼ 44 nM [309]) that has chiefly been investigated for protection against inflammatory and neurological disorders [311–315, 349]. SB239063 has not been tested in combination with PDT. Nevertheless, the p38 inhibitor harnesses several interesting modulatory properties that make it an eligible adjuvant drug candidate for cancer chemotherapy or PDT. First, inhibition of the p38 signaling pathway by SB239063 decreased cell proliferation, migration, VEGF protein levels, and angiogenic ability in human endothelial (ECV304) cells that had been primed with human hepatocellular carcinoma (HepG2) cell-derived bone morphogenic protein (BMP2) [306]. BMP2 moderates liver cancer development [350] and activates p38 under hypoxic conditions in human articular chondrocytes [351]. These effects could be pertinent in select PDT applications since BMP2 is a driver of the abovementioned processes in cancers of non-hepatic origin as well [352–354]. Also, PDT induces hypoxia by damaging and occluding vasculature [355] that consequently may undergo remodeling, where endothelial cells and VEGF occupy a central role [356]. Second, SB239063 blocks p38-dependent release of TNF-α [302, 303], attenuates IL-6 [300], and inhibits NF-κB activation and translocation [304, 305], which could deter inflammation-driven tumor cell survival (see Fig. 2), including the propagation of the immediate early stress response via the TNF-α/TNFR signaling axis (see Fig. 3). Finally, the anticancer attributes of SB239063 emanate from its ability to (1) inhibit transforming growth factor β (TGF-β)- and bFGF-induced cell migration (in human corneal epithelial cells) [301]; (2) suppress invasion and MMP-3 production in pancreatic cancer cells [243] and invasion of nicotineprimed human colorectal cancer cells [316]; and (3) reduce tumor volume, intratumoral vascularization, and migration proneness in BMP2-overexpressing HepG2 xenografts in mice [306].

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As with other p38 inhibitors, SB239063 may confer cytoprotection. Kim et al. [308] reported that SB239063 inhibited apoptosis and restored anti-apoptotic BCL-2 protein levels in human diploid fibroblasts that had been treated with hydrogen peroxide and staurosporine. Accordingly, SB239063 can protect cells from oxidative stress and apoptotic fallout. Another study demonstrated that SB239063 can attenuate radiation-induced vascular inflammation and recruitment of immune cells [307], which may have negative implications for immune control of PDT-treated tumors (see Subheading 1). 4.2.8 Thymoquinone

Thymoquinone is a monoterpene phytochemical extracted from the seeds of Nigella sativa that has been extensively researched for its antioxidant, anti-inflammatory, and anticancer properties [323, 357]. The phytochemical is toxic to cancer cells, including colon cancer cells [323, 326, 327], pancreatic cancer cells [319, 328], prostate cancer cells [329], laryngeal carcinoma cells [330], and leukemia cells [331], where it generally induces apoptosis that can proceed in a p53-dependent [332] and p53-independent manner [332, 333]. As numerous other anticancer compounds, thymoquinone generates ROS in cancer cells [320, 333], serving as a trigger for apoptotic signaling [358–363]. A study by El-Najjar et al. [317] convincingly demonstrated that thymoquinone incites oxidative stress in human colon cancer (Caco-2, HCT-116, LoVo, DLD-1, and HT-29) cells by triggering ROS generation, which was abrogated by NAC. However, ROS activated the ASK-1 downstream target JNK as well as ERK, but not p38. The null effect on p38 may be related to the p38-inhibiting properties of thymoquinone that may have countered stimulation by ROS, possibly via ASK-1 given that JNK was activated. Direct ASK-1 activation by thymoquinone has never been reported. Only one investigation [203] could be retrieved on rheumatoid arthritis synovial fibroblasts where the body of proof regarding thymoquinone activation of ASK-1 was somewhat compelling. Thymoquinone inhibited TNF-α-induced p-p38 and p-JNK expression. The p-p38 and p-JNK downregulation was mediated by ASK-1, as evidenced by the finding that TNF-α selectively induced phosphorylation of ASK-1 at the Thr845 residue that in turn was inhibited by thymoquinone in a dose-dependent manner. Several studies have confirmed that thymoquinone blocks p38, although the data are not consistent. For example, Park et al. [296] demonstrated that thymoquinone inhibits p38 in cultured human renal carcinoma (Caki-1) cells, where it co-downregulated protein levels of p-AKT, prostaglandin E2 receptor 2 (EP2), and MMP-9 and with it hampered cell migration and invasion. The p38-inhibiting properties of thymoquinone have been reproduced in oral cancer cells [318], but not in other studies. In human

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bladder cancer (T24 and HTB-9) cells, for instance, thymoquinone induced pathways related to EMT and attenuated mTOR activity and downstream signaling, but had no effect on ERK 1/2 or p38 MAPK activity. Conversely, it was shown that thymoquinone induced apoptosis in human pancreatic cancer (FG/COLO357 and CD18/HPAF) cells by the activation rather than inhibition of JNK and p38 [319]. Similar observations were made by Woo et al. [320] in human breast cancer (MCF-7 and MDA-MB-231) cells, where thymoquinone activated p38, JNK, and ERK that culminated in apoptosis. The p38 activation and cell death were attenuated by the selective p38 inhibitor SB203580 (see Subheading 4.2.6) and NAC. Thymoquinone-induced p38 activation, reduction of X-linked inhibitor of apoptosis protein (XIAP), BCL-2, BCL-xL, and survivin as well as increased apoptosis and reduced proliferation were further confirmed in human breast cancer (MDA-MB-231) xenografts in mice. Finally, thymoquinone reportedly induces autophagic cell death and reduces metastatic propensity of irinotecan-resistant (CPT-11-R) LoVo colon cancer cells, both of which involve p38 activation [321, 322]. Taken altogether, the effect direction of thymoquinone on p38 activity is variable in cancer cells and difficult to predict. Inasmuch as thymoquinone has never been assayed in cells treated by PDT, studies are needed to investigate a potential synergistic or additive effect of such a combinatorial modality and rule out therapeutic antagonism. 4.2.9 VX-702

VX-702 is an orally dosed selective p38α inhibitor [364]. P38α mediates the biosynthesis of TNF-α and IL-1β at the transcriptional and translational level and with it occupies a central role in pro-inflammatory signaling (see Subheading 2.1). Accordingly, p38α is pharmacologically targeted for the modulation of cytokine production [365] and researched for the treatment of rheumatoid arthritis and other inflammatory diseases [334, 340, 366– 368]. Although the drug does not cause serious clinical side effects, VX-702 lacked efficacy in human trials and was therefore discontinued in the framework of the aforementioned conditions [367]. In terms of anticancer properties, VX-702 is efficacious although there is paucity in the number of supporting studies. A recent investigation elucidated that VX-702 is an inhibitor of p38 as well as Nemo-like kinase (NLK), which is responsible for survival signaling in endocrine-resistant breast cancer [335]. Combined treatment of VX-702 with the mTOR inhibitor everolimus produced a significant anticancer effect in therapy-resistant cell linederived and patient-derived xenograft models [336]. VX-702 further inhibited apoptosis induced with the histone deacetylase (HDAC) inhibitor Trichostatin A in cultured colonic epithelial (HCoEpiC) cells. Apoptotic signaling concurred with increased BAX and reduced BCL-2 levels. Trichostatin A also promoted

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p38 expression and activation, all of which were reversed by VX-702 [338]. VX-702 has never been tested in the context of PDT. It is notable that VX-702 attenuates fibrosis in chronic graft-versushost disease and suppresses infiltration of immune cells [339], which might negatively impact PDT given its reliance on antitumor immunity for long-term tumor control (see Subheading 1). 4.3 Other Inhibitors of the ASK-1 Pathway

In this section inhibitors are described that do not directly target ASK-1 or p38 but are considered potentially relevant inhibitors of the ASK-1 pathway (see Fig. 6) because they affect regulators located upstream or downstream of ASK-1 and p38 or impact nodes in other pathways that intersect with ASK-1 signaling. A summary of their mechanism of action, pharmacological and biological effects, test systems, and application in PDT is provided in Table 3. BAY 11–7082 and BAY 11–7085 (synonym: BAY 11–7083) are inhibitors of nuclear factor of kappa light polypeptide gene enhancer in B-cell inhibitor alpha (IκBα) that itself inhibits NF-κB. The compounds act by blocking TNF-α-induced phosphorylation of IκBα (IC50 ¼ 10 μM for BAY 11–7085), which leads to decreased levels of NF-κB and subsequently reduced expression of the adhesion molecules ICAM-1, VCAM-1, and E-selectin in HUVECs. Both compounds also induce JNK-1 and p38 and reduce ERK-1 in TNF-α-stimulated endothelial cells [370]. BAY 11–7082 also inhibits ubiquitin-specific protease (USP)7 and USP21 (IC50 ¼ 0.19 and 0.96 μM, respectively) [371] that constitute druggable targets in cancer therapy [426]. However, BAY 11–7082 could stabilize HIF-1α by blocking its proteasomal degradation [372] and possibly interfere in therapeutic modalities targeting the HIF-1 survival pathway (see Subheading 1, Fig. 2) or aid in tumor survival signaling. With respect to PDT, IκBα is downregulated and NF-κB is upregulated, at least after hypericin PDT [186]. These molecular targets should therefore be susceptible to BAY 11–7082 and BAY 11–7085. BAY 11–7082 completely abolished ALA-PDT-induced JNK activation, which almost completely abrogated PDT-induced apoptosis in human oral cancer (Ca9–22) cells [373]. BAY 117085 was employed to mechanistically elucidate hypericin-PDT-mediated changes in COX-2 expression in human cervix carcinoma (HeLa) wild-type cells in comparison to genetically modified HeLa cells that stably overexpress IκBα and that are devoid of NF-κB DNA-binding activity. The study revealed that PDT did not result in altered COX-2 expression levels when NF-κB was inhibited pharmacologically or genetically compared to non-illuminated controls, indicating that NF-κB was not involved in the upregulation of COX-2 by hypericin-PDT [186].

Fig. 6 Overview of inhibitors that affect the immediate early stress response upstream or downstream of ASK-1 and p38 that are eligible candidates for use as adjuvants in PDT. LogP (octanol:water partition coefficient) values were retrieved from PubChem and were predicted with XLogP2 or XlogP3 software. The half maximum inhibitory concentration (IC50, enzymes), half maximum lethal concentration (LC50, in vitro), half maximum lethal dose (LD50, in vivo), t1/2 (circulation halflife), and spectral properties were obtained from the material safety data sheets (retrieved from the Cayman Chemicals and Spectrum Chemical website), PubChem, LC Laboratories, Merck-Millipore, Pfizer, Selleckchem, and TargetMol. The half maximum inhibitory concentration (IC50, used for proliferation and enzymes) and half maximum growth inhibitory concentrations (GI50) were obtained from available literature. This also applies to LC50, LD50, and t1/2 data that were missing from or inconsistent in the abovementioned databases. Abbreviations: Em emission, Ex excitation, ip intraperitoneal, iv intravenous, MW molecular weight, NA information not available, sc subcutaneous, TDLO the lowest dose causing a toxic effect, λmax the wavelength at which there is an absorption maximum (may be multiple absorption bands)

[186, 370, 374]

Yes

Yes

In vitro: HUVECs, HeLa, T24, Nalm6, Farage, Pfeiffer, Ramos, Raji, ARH-77, TRF, NAD, HDMAR, U937, K562, HF1, 1063, SaSO2 cells

In vitro: PC-3, MCF-7, AZACB, CF33, CF41. MG cells

Cell death; loss of Inhibition of p65 NF-κB mitochondrial potential binding to κB; inhibition of AP1 binding to DNA-binding motif; inhibition of surface expression of ICAM-1, VCAM-1, and E-selectin; induction of JNK-1 and p38 and reduction of ERK-1 (in endothelial cells) AKT dephosphorylation; Cell death; antiinhibition of P70-S6 inflammatory; analgesic; kinase activity; antipyretic downregulation of PGE2,

Inhibition of IκBα phosphorylation

Inhibition of COX-2 (noncompetitive) and PDK-1,

BAY 11–7085 (BAY 11–7083)

Celecoxib

[187, 375–382]

[369–373]

Yes In vitro: HBL-1, RAW 264.7, IL-1R, Ca9–22, HGC-27, HUVECs, MGC80–3, AGS, NCI-N87, L-02 cells In vivo: HGC-27 xenografts in male BALB/c nude mice

Tested in PDT References

Tumor growth inhibition; Inhibition of NF-κB; increased apoptosis; cell induction of JNK-1 and cycle arrest (S-phase) p38; reduction of ERK-1 (in TNF-α-stimulated endothelial cells); abrogation of JNK activation (by PDT); downregulation of BCL-2 and upregulation of BAX protein levels; inhibition of TNF-α-induced surface expression of ICAM-1, VCAM-1, and E-selectin; stabilization of HIF-1α

Tested in

Inhibition of TNF-α-induced IκBα phosphorylation; inhibition of USP7 and USP21

Biological effect

BAY 11–7082

Pharmacological effect

Mechanism

Name

Table 3 Overview of up- and downstream inhibitors of ASK-1 and their pharmacological and biological characteristics

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Inhibition of COX-2

NS-398

Reduction of PGE2, Antiproliferative; inhibition In vitro: Colo320, BA, RIF, Yes LLC, AA/C1, RG/C2, of tumor growth; COX-2, and VEGF (after RR/C1, KS, JW2, HT29, induction of apoptosis PDT) HeLa, THRC cells In vivo: RIF cell xenografts

Yes

(continued)

[186, 189, 399–401]

[187, 189, 397, 398]

Reduction of COX-2 Anti-inflammatory; protein levels and inhibition of autophagy inhibition of PGE2 (after PDT) release; inhibition of JNK phosphorylation; reduction of p300HAT expression (all after PDT)

In vitro: MCF-7, A375, MG-63 cells

Antioxidant

NAC

[387–396]

In vitro: HepG2, 3-T3-L1, Yes J774.2, U87MG, LN18, GL261, Caco-2, human osteoarthritic chondrocytes, PC-3, DU145, Eca-109 cells, human primary neutrophils, rabbit primary smooth muscle cells

Downregulation of HIF-1α Anti-angiogenic; antiproliferative; protein levels (no effect synergistic reduction of on mRNA); inhibition of growth and migration mTOR at higher doses; (after PDT) downregulation of EGFR, PI3K, and AKT

Inhibition of PI3K and PIM1

LY294002

[383–386]

In vitro: HT-29, LS-174 T, Yes LS-180, Caco2, COH-BR6, MDA-MB468, BT474, A2058, SK-MEL5, MCF-7, DU145, MCF12A cells In vivo: HT-29 and LS-174 T xenografts in male athymic nude mice

Downregulation of Nox1, HDAC4, FEN1; upregulation of p21, DUSP4 protein levels and PDK4, PPAR-α, PPAR-γ transcript levels; downregulation of cyclin A, D1, and E protein expression

Inhibition of NOX

Diphenylene iodonium (DPI)

In vivo: EMT6 xenografts in female BALB/c mice Antiproliferative; growth inhibition; cell cycle arrest (G1/S)

VEGF, COX-2, TNF-α, IL-1β, and p53 protein levels (after PDT)

cadherin-11 binding

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Inhibition of MEK and AhR

PD98059

Binding to inactive form of Antiproliferative; accelerated cell death of MEK, the upstream glucose-deprived cells activator of ERK and AP-1; inhibition of ERK1/ 2 phosphorylation

Inhibition of NF-κB In vitro: Anti-inflammatory; through direct thiol MCF-7, antiproliferative; modification at cys-179 TNF-α-stimulated HeLa acceleration of cell death of IKKβ and at cys-38 of cells of glucose-deprived cells p65/RelA; decay of subunit IκB; inhibition of α-chymotrypsin, protein kinase C, some cysteine proteases such as bromelain, ficin, and papain; downregulation of COX-2 protein and decrease in secreted PGE2

[187, 402–404]

[186, 405–411]

Yes In vitro: Hep3B, HepG2, PLC, SKHep, glucosedeprived HepG2, HeLa, T24, 3T3, KNRK, NRK-47F, NRK-52E, KB, PC12, MCF10A, MCF10A-Neo, MCF10A-NeoT, 143B, 143Bp0 cells, rat primary sympathetic neurons, 129/Ola mice-derived astrocytes In vivo: male CD mice, Sprague-Dawley rats

Tested in PDT References

Yes

in female C3H/HeJ mice, C26 xenografts in male BALB/cByJ mice

Inhibition of NF-κB

Tested in

N-tosyl-Lphenyla lanine chloro methyl ketone (TPCK)

Biological effect

Pharmacological effect

Mechanism

Name

Table 3 (continued)

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SP600125

Pyrrolidine dithiocarba mate (PDTC)

Downregulation of COX-2 Anti-inflammatory; cell protein; decrease in cycle arrest (G1); secreted PGE2 reversion of deoxynivalenol-induced mitochondrial dysfunction and apoptosis

In vitro: Sprague-Dawley rat-derived vascular smooth muscle cells, MCF-7, MG-63, GH3 cells In vivo: Balb/c mice, MRL/lpr mice, NMRI mice, Sprague-Dawley rats Yes

Selective inhibition of Competition with ATP to Inhibition of cell activation In vitro: HeLa, T24, HK-1, Yes MG-63, U2OS, human and differentiation; antiJNK inhibit c-Jun CD4+, HCE-T, RAW inflammatory; inhibition phosphorylation; 264.7, MIN6, HCT116 of autophagy (after PDT) downregulation of cells inflammatory genes In vivo: CL57BL/6 and (coding for COX-2, IL-2, JNK-KO CL57BL/6 IL-10, INF-γ, and mice, neonatal BALB/c TNF-α) mice

Inhibition of IκB

[186, 192, 276, 397, 419–425]

[187, 412–418]

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Celecoxib is a noncompetitive inhibitor of COX-2 that is classified as a nonsteroidal anti-inflammatory drug with analgesic, antiinflammatory, and antipyretic properties [378, 427]. Celecoxib further inhibits 3-phosphoinositide-dependent kinase-1 (PDK-1)mediated apoptosis (IC50 ¼ 48 uM), causes AKT dephosphorylation [375], and binds to cadherin-11 (CDH11) [376] that is overexpressed in several types of cancer [428], together accounting for the compound’s anticancer properties. Photofrin-PDT (i.v. injection of 5 mg/kg, light-dose interval of 16 h, cumulative radiant exposure of 135 J/cm2) substantially increased protein levels of PGE2, COX-2, VEGF, IL-1β, and TNF-α in syngeneic mammary carcinomas (EMT6) implanted into the dorsal scapula region of female BALB/c mice. Celecoxib (10 mg/kg, i.p. injections directly after and at 4 h and 24 h post-PDT) reduced the levels of all listed proteins to pre-PDT baseline values, suggesting a role of NF-κB signaling. In human breast cancer (MCF-7) cells, PDT upregulated p53 protein levels that were downmodulated to pre-PDT control levels by celecoxib [187]. Diphenylene iodonium (DPI) is an iodonium-class flavoprotein dehydrogenase inhibitor that blocks the activity of NADPH oxidases (NOX). The compound has been explored as an oncotherapeutic for a subset of human cancers that overexpress NOX, including colorectal cancer [383] and breast cancer [385], which require NOX for their survival and growth [429]. Doroshow et al. [383] demonstrated that DPI retarded the growth of cultured cancer cells that overexpressed NOX1 (human colon cancer cell lines Caco2, HT-29, LS-174T) at 0.01–0.25 μM concentration by decreasing steady-state ROS production (coinciding with decreased mRNA expression of NOX1 and antioxidant enzymes) and causing G1/S cell cycle arrest, reduced proliferative signaling at the level of the transcriptome, and apoptosis in some of the cell lines. DPI decreased the expression of cyclin A, D1, and E in vitro. In vivo, DPI reduced tumor volume by ~40% compared to vehicle control in HT-29 and LS-174T xenografts in athymic nude mice. In light of the above, DPI could be used in conjunction with PDT of cancer types that rely on NOX signaling for sustenance, especially given that NOX isoforms may be activated by PDT [430, 431] and hence aid in survival. It is imperative that DPI is administered after PDT inasmuch as it acts as an antioxidant [430, 432] that could otherwise enfeeble the efficacy of PDT. LY294002 is a morpholine-based compound that is a strong inhibitor of PI3K [391] with an IC50 of 0.5 μM/0.57 μM/ 0.97 μM for the PI3Kα/δ/β isoforms [393], but also inhibits other proteins such as the proto-oncogene serine/threonine-protein kinase (PIM1) [392] that is overexpressed in some forms of cancer [394, 395, 433–435]. The PI3K pathway regulates key biological processes such as cell growth, survival, proliferation, and angiogenesis [436]. Every key node in the PI3K pathway is

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frequently mutated or amplified in many cancers [437] that not only fortifies the tumor, but also causes loss of sensitivity to some chemotherapeutics [438], which is why this pathway is widely targeted by singular or hybrid chemotherapeutic modalities [439, 440]. LY294002 is further interesting for application in PDT in that the drug can downregulate HIF-1α [389], which is a key survival regulator in PDT-subjected, sublethally afflicted cancer cells (see Subheading 1, Fig. 2). In a study on ALA-PDT and LY294002, Zhang et al. [390] showed that the combinatorial modality exerted a synergistic inhibitory effect on the migration of human esophageal cancer (Eca-109) cells and reduced gene and protein expression levels of epidermal growth factor receptor (EGFR), PI3K, and AKT. NAC is commonly used as a nutritional supplement with strong antioxidant properties, acting directly as a scavenger of ROS and other types of oxidants and radicals [441]. Pretreatment of human breast cancer (MCF-7) cells with NAC (2.5 mM) before PhotofrinPDT reduced COX-2 protein levels to baseline values and strongly inhibited PGE2 release, indicating that PDT-induced ROS generation is responsible for pro-inflammatory signaling via COX-2 and PGE2 [187]. Equally important was the finding that pretreatment of cells with a potent antioxidant did not abrogate the photooxidative destruction of cells by PDT but inferentially improved therapeutic efficacy, as was the case for COX-2 inhibition using small interfering RNA (siRNA). Moreover, NAC pretreatment of human osteosarcoma (MG-63) cells was found to inhibit MPPa-PDTinduced autophagy and JNK phosphorylation [397]. Finally, Tsai et al. [189] showed that ALA-PDT of human melanoma (A375) cells strongly induced p300 HAT mRNA that led to elevated HAT activity and PS concentration-dependent cell death. Oxidative stress can activate p300HAT and result in increased histone acetylation and subsequent regulation of gene expression [442, 443] that could favor cell survival. In that respect, the ALA-PDT also augmented survivin protein levels in A375 and mouse colon carcinoma (C26) cells. NAC abolished the p300HAT transcriptional response induced by ALA-PDT. NS-398 [N-(2-cyclohexyloxy-4-nitrophenyl)methanesulfonamide] is a nonsteroidal anti-inflammatory drug and a selective inhibitor of COX-2 with antiproliferative and pro-apoptotic attributes [399, 400]. Hypericin-PDT of cultured human cervix carcinoma (HeLa) cells pretreated with 50 μM of NS-398 completely blocked the release of PGE2 induced by PDT and slightly increased the extent of apoptosis, although to a lesser degree than the p38 inhibitor PD 169316 (see Subheading 4.2.2) [186]. In PH-PDTtreated cultured radiation-induced fibrosarcoma cells, the addition of NS-398 directly after illumination entirely eliminated detectable protein levels of PGE2 and COX, which were both strongly upregulated by PDT. PH-PDT of radiation-induced fibrosarcomas in

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C3H/HeJ mice resulted in protein overexpression of COX-2, PGE2, and VEGF. NS-398 treatment (10 mg/kg i.p.) reduced PGE2 and VEGF protein levels by ~50% and ~75%, respectively, and ensured that ~55% and ~75% of animals remained tumor free during 90 d post-PDT follow-up when PDT was performed at a cumulative radiant exposure of 200 and 300 J/cm2, respectively, compared to 0% and ~25% in the PDT-only treatment group [401]. Finally, Tsai et al. [189] demonstrated that the inclusion of NS-398 in liposomal chlorin e6-PDT of mouse colon carcinomas (C26) improved PDT efficacy by about 45%. N-tosyl-L-phenylalanine chloromethyl ketone (TPCK) is an inhibitor of serine/cysteine endopeptidases that also inhibits the expression of inflammatory mediators by blocking NF-κB through direct thiol modification at Cys-179 of inhibitor of nuclear factor kappa-B kinase subunit beta (IKKβ) and at Cys-38 of p65/RelA [404]. Pretreatment of human breast cancer (MCF-7) cells with TPCK (10 μM) in Photofrin-PDT substantially attenuated PDT-induced COX-2 and PGE2 protein levels [187]. PD98059 is a non-ATP competitive MEK inhibitor (IC50 ¼ 2 μM) that specifically inhibits MEK-1-mediated activation of MAPK without directly inhibiting p38, JNK, and ERK1/ 2 [409, 410], although causing phosphorylation of ERK1/ 2 [405]. PD98059 is also a ligand for the aryl hydrocarbon receptor (AhR) and functions as an AhR antagonist [411]. AhR ligands are produced by the tumor microenvironment and via intracrine routes [444]. Sustained transcriptional activation of AhR promotes tumor growth and impairs antitumor immunity [445]. AhR further mediates proteasomal processing of estrogen receptor α and affects ERK kinase activity and signaling by direct cross talk [446] while stimulating cell proliferation through interactions with EGF [447]. Blockade of AhR induced cell cycle arrest in the G1 phase in rat hepatoma (5 L) cells and G2/M phase in murine hepatoma (1c1c7) cells [448]. AhR is targeted pharmacologically to inhibit its pro-tumorigenic properties and to re-sensitize tumor cells to therapies [445, 449]. Despite these anticancer properties of PD98059, hypericin-PDT-treated human cervix carcinoma (HeLa) cells and bladder cancer (T24) cells that had been pretreated with 20 μM PD98059 elicited no effect on COX-2 protein levels that were increased by PDT itself. PDT-induced downmodulation of COX-2 as well as other regulators of that inflammatory pathway such as PGE2 were effectuated by other inhibitors, including PD 169316 (see Subheading 4.2.2) and NS-398 (this section) [186]. Similar non-responsiveness in the COX-2/PGE2 signaling axis was observed in human breast cancer (MCF-7) cells [187]. Actual anticancer effects of PDT + PD98059 were not studied. Pyrrolidine dithiocarbamate (PDTC) is a metal chelating compound that can induce G1-phase cell cycle arrest in vascular smooth muscle cells [412] and inhibits NF-κB [416–418]. Accordingly,

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PDTC reverted deoxynivalenol-induced mitochondrial dysfunction and apoptosis via the NF-κB/iNOS pathway [413, 450]. Deoxynivalenol is an inducer of stress responses in the ER and ribosomes and triggers mitochondrial dysfunction and intrinsic apoptosis through oxidative stress [451, 452]. In PDT an opposite (i.e., non-protective) effect is induced by PDTC. Pretreatment of human breast cancer (MCF-7) cells with PDTC (10 μM) in Photofrin-PDT substantially attenuated PDT-induced COX-2 and PGE2 protein levels [187]. SP600125 is an anthrapyrazolone that acts as a potent, cellpermeable, selective inhibitor of JNK and dose-dependently competes with ATP to inhibit the phosphorylation of c-Jun. Through JNK inhibition, SP600125 prevents the activation of inflammatory genes such as COX-2, IL-2, interferon (IFN)-γ, and TNF-α [419]; regulates TLR-mediated inflammatory signaling [423, 424]; and downregulates Beclin-1 and reduces autophagy while increasing apoptosis [425]. Treatment of squamous nasopharynx carcinoma (HK-1) cells with Zn-BC-AM-PDT was shown to upregulate p-p38, p-JNK, and p-ATF, where SP600125 slightly reduced p-JNK and considerably attenuated p-ATF that mediates the proteotoxic stress response (see Subheading 1, Fig. 2) [192]. However, pretreatment of cells with SP600125 did not induce apoptotic cell death regardless of drug concentration (0–20 μM) and light dose (0–2 J/cm2). On the other hand, SP600125 was able to reduce pyropheophorbide-α methyl ester (MPPa)-PDT-induced autophagic signaling in human osteosarcoma (MG-63) cells, which involved p-JNK and microtubule-associated protein 1A/1B-light chain 3, phosphatidylethanolamine conjugate (LC-3 II) downregulation by SP600125 following their induction by PDT [397]. Both JNK and LC-3 II are involved in autophagy [453, 454]. The effect of SP600125 on PDT-induced cell death was not studied.

5

Conclusions When activated, the immediate early stress response protects the cell from oxidative stress and can activate other PDT-induced downstream survival pathways. However, long-term activation can induce apoptosis. Since the immediate effect of ASK-1 activation is protection against oxidative stress and since its downstream effects can have pro-inflammatory (i.e., survival) consequences, ASK-1 inhibition in combination with PDT is expected to improve treatment efficacy. However, the combination of ASK-1 inhibitors and PDT has currently not been tested in any experimental setting. In contrast, downstream targets of the ASK-1 pathway, such as p38, have been used in combination with PDT. Nevertheless, the results show that inhibition can both sensitize cancer cells to PDT and

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Chapter 21 Nanobody-Targeted Photodynamic Therapy: Nanobody Production and Purification Vida Mashayekhi, Erik Schooten, Paul M. P. van Bergen en Henegouwen, Marta M. Kijanka, and Sabrina Oliveira Abstract Nanobodies have recently been introduced to the field of photodynamic therapy (PDT) as a very promising strategy to target photosensitizers selectively to cancer cells. Nanobodies are known for their characteristic small size (15 kDa), high specificity, and high binding affinities. These features allow rapid accumulation of nanobody-photosensitizer conjugates at the tumor site and rapid clearance of unbound fractions, and thus illumination for activation is possible 1 or 2 h postinjection. Preclinical studies have shown extensive tumor damage after nanobody-targeted PDT. This chapter addresses the first steps toward preparing nanobodyphotosensitizer conjugates, which are the nanobody production and purification. The protocol for nanobody production addresses either medium- or large-scale bacterial expression, while the nanobody purification is described for two main strategies: affinity chromatography and ion-exchange chromatography. For the first strategy, protocols are described for different affinity tags and purification from either medium-scale or large-scale productions. For the second strategy, the protocol given is for purification from a large-scale production. Key words Nanobody production, Nanobody purification, Affinity chromatography, Ion-exchange chromatography

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Introduction Nanobodies have recently been introduced to the field of photodynamic therapy (PDT) as a very promising strategy to target photosensitizers selectively to cancer cells [1–4]. Nanobodies are the variable domain of heavy-chain antibodies that exist in animals of the Camelidae family [5] and can also be referred to as VHH (variable domain of the heavy chain of the heavy-chain antibody) or single-domain antibodies. Nanobodies are the smallest naturally occurring antibody fragments, well known for their high specificity and high binding affinities, with potential for distinct applications,

Vida Mashayekhi and Erik Schooten contributed equally to this work. Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_21, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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such as biotechnology, molecular imaging, or cancer therapy [6– 8]. In targeted PDT, nanobodies have been shown to efficiently and selectively kill cancer cells overexpressing their target, namely EGFR [1], C-Met [3], and US28 [4]. In preclinical studies, nanobodies have been shown to accumulate rapidly into tumors, to enable rapid clearance of unbound nanobody-photosensitizer conjugates, allowing illumination for activation 1 or 2 h postinjection. Importantly, this strategy has led to extensive tumor damage, with minimal damage to normal surrounding tissues [2]. This chapter addresses the first steps toward preparing nanobody-photosensitizer conjugates, which are the nanobody production and purification. For protocols on earlier steps, such as the preparation of a library for phage display or the selection of nanobodies for a certain target of interest, the reader is referred to other protocols, such as [9–14]. Several nanobody production systems have been described [15] and most of them are based on secretion of the protein into the culture medium, as this simplifies purification substantially. In such cases, nanobodies are provided with a signal sequence that induces transport through the ER-Golgi pathway for eukaryotic production system. The eukaryotic production systems include the yeasts Saccharomyces cerevisiae and Pichia pastoris, filamentous fungi like Aspergilli, or mammalian CHO cells [16–18]. However, these production systems are usually costly and bacterial expression is in most cases sufficient for cheap and rapid production of nanobodies that do not need posttranslational modification for their functionality. Expression of nanobodies in E. coli can be in the cytoplasm or by secretion into the periplasmic space by providing the nanobody with an appropriate N-terminal leader sequence, usually a 22-amino acid sequence from PelB. The nanobody production described here concerns medium, i.e., 800 mL, or large, i.e., 5 L, scale production, starting from an already prepared stock of E. coli BL21-DE3 transformed with a suitable IPTG-inducible vector for recombinant production in bacteria, containing the sequence of the nanobody of interest, with a pelB sequence for periplasmic localization. Thereafter, two main strategies are described for purification: affinity chromatography and ion-exchange chromatography. The affinity chromatography is described for nanobodies containing different affinity tags, namely histidine-tag (or his-tag) and EPEA-tag (or C-tag), as well as for nanobodies that bind protein A. This strategy is described for purification from either medium-scale or large-scale productions. For the second strategy, i.e., ion-exchange chromatography, the protocol given is for purification from a large-scale production using cation and anion exchange.

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Materials General

1. Luria Bertani (LB): Dissolve 10 g tryptone, 5 g yeast extract, 10 g NaCl in 800 ml Milli-Q and adjust pH to 7.4 with 2 M NaOH. Adjust volume to 1 l with Milli-Q. Sterilize with autoclaving. 2. YT-2x medium: Dissolve 16 g tryptone, 10 g yeast extract, and 5 g NaCl in 800 mL Milli-Q and adjust pH to 7.4 with 2 M NaOH. Adjust volume to 1 L with Milli-Q. Sterilize with autoclaving. 3. Sterile 20% glucose. 4. LB-agar plate, supplemented with appropriate antibiotic and 2% glucose. 5. 1 M Isopropyl β-D-thiogalactopyranoside (IPTG). 6. Appropriate antibiotics and chloramphenicol (30 mg/mL). 7. 1x PBS: 138 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 1.8 mM KH2PO4 in Milli-Q; adjust to pH 7.4 with 1 M HCl. 8. SDS-PAGE loading buffer (4x): 200 mM Tris/HCl, pH 6.8, 40% glycerol, 400 mM DTT, 8% w/v SDS, 0.4% bromophenol blue. 9. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) buffers and equipment. 10. NanoDrop Spectrophotometer (Thermo Fisher Scientific). 11. Spectrophotometer (e.g., Eppendorf Biophotometer plus).

2.2 Production with Fermentor (or Bioreactor)

1. Terrific broth (TB), supplemented with 0.089 M potassium phosphate buffer and 0.1% glucose: 60 g tryptone, 120 g yeast extract, 4.5 g glucose, 20 mL glycerol in 4.5 L Milli-Q. Potassium phosphate buffer pH 7.4 contains 0.17 M KH2PO4 and 0.72 M K2HPO4 in 500 mL Milli-Q and is added to TB with a 1:9 ratio. Sterilize both components by autoclaving and add together when cooled down. 2. Antifoam solution. 3. 1 M H2SO4. 4. 2 M NaOH. 5. Benchtop fermentor system (or bioreactor) containing a 7.5 L vessel (e.g., Eppendorf BioFlo 115 benchtop fermentor).

2.3 Purification with Beads (Medium Scale)

1. Beads: Nickel-NTA agarose (QIAGEN).

2.3.1 Purification of Nanobodies Containing Histidine-Tag

3. Econo-Pac® Chromatography Column (gravity-flow column, Bio-Rad).

2. Elution buffer: 300 mM Imidazole; dissolve imidazole in 1x PBS, adjust pH to 7.4 with 1 M HCl.

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2.3.2 Purification of Nanobodies Containing EPEA-Tag (C-Tag)

1. CaptureSelect™ C-tag Affinity Matrix (Thermo Fisher Scientific).

2.4 Purification with A¨KTAxpress (Large Scale)

¨ KTAxpress chromatography system with Unicorn software 1. A (GE Healthcare), or similar system which has the possibility for multistep protein purification.

2. Elution buffer: Tris (20 mM) containing MgCl2 (2 M). First dissolve Tris in demi-water and adjust pH to 7.4. Add MgCl2 and check pH again.

2. 2  5 mL HiTrap desalting columns, stacked (GE Healthcare). 3. 20% Ethanol. 4. 2 M NaCl. 5. 0.1 M HCl. 6. 0.1 M NaOH. 7. 0.45 μm Bottle-top 500 mL PES filters. 2.4.1 Purification of Nanobodies Containing Histidine-Tag

1. Columns: 1 mL or 5 mL HisTrap FF crude column (GE Healthcare). 2. Binding buffer: 20 mM Sodium phosphate buffer, 0.5 M NaCl, 10 mM imidazole, pH 7.4. 3. Elution buffer: 20 mM Sodium phosphate buffer, 0.5 M NaCl, 300 mM imidazole, pH 7.4.

2.4.2 Purification of Nanobodies Containing EPEA-Tag (C-Tag)

1. Columns: 1 mL or 5 mL CaptureSelect™ C-tag column (Thermo Fisher Scientific). 2. Binding buffer: 20 mM Sodium phosphate buffer, 150 mM NaCl, pH 7.4, or PBS. 3. Elution buffer: 20 mM Tris, 2 M MgCl2, pH 7.

2.4.3 Purification of Nanobodies with Affinity for Protein A (see Note 1)

1. Columns: 1 mL or 5 mL HiTrap Protein A HP column (GE Healthcare). 2. Binding buffer: 20 mM Sodium phosphate buffer, 150 mM NaCl, pH 7.4, or PBS. 3. Elution buffer: 0.1 M Citrate buffer, pH 3.

2.4.4 Purification of Nanobodies with Cation-Exchange Column

1. Columns: 1 mL or 5 mL HiTrap SP HP column (GE Healthcare). 2. Binding buffer (A): 25 mM Sodium acetate buffer, pH dependent on pI of purified nanobody. 3. Elution buffer (B): 25 mM Sodium acetate, 1 M NaCl, pH dependent on pI of purified nanobody (the same as pH of buffer A).

Nanobody Production and Purification 2.4.5 Purification of Nanobodies with Anion-Exchange Column

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1. Column: HiPrep™ Q XL 16/10 column (GE Healthcare) Buffer: 1x PBS 2. Elution buffer is not needed as the purified nanobody is in the flow through, whereas impurities bind to the column.

Methods

3.1 Medium-Scale Production of Nanobody (800 mL of Culture Media)

1. Streak BL21-DE3 bacteria from the appropriate glycerol stock onto an LB-agar plate using a sterile loop, toothpick, or pipette tip. Incubate the plate O/N at 37  C. 2. Start an O/N pre-culture by inoculating a single colony from a bacterial plate in LB medium, supplemented with 2% glucose, appropriate antibiotic, and 30 μg/mL chloramphenicol (see Note 2). Incubate O/N at 37  C on a shaker. 3. Prepare 800 mL of growth solution for the production of nanobody by mixing YT-2x medium containing 0.1% glucose, appropriate antibiotic, and O/N culture of bacteria (1 mL of O/N culture should be added to 100 mL of growth solution, see Note 3). Incubate the flask for 3–4 h to reach optical density (OD600 nm) between 0.5 and 0.7. Add IPTG (final concentration of 1 mM) and shake the flask for 16 h at 22–25  C. 4. Measure the OD600 nm before harvesting the cells (see Note 4). Centrifuge the bacterial culture at 6000  g for 20 min at 4  C. Discard the supernatant and resuspend the pellet in 20 mL of PBS. Freeze/thaw the cells twice to disrupt the outer cell membrane and release the periplasmic content, which contains the nanobody. 5. Centrifuge the cells at 12,000  g for 20 min at 4  C. Transfer the supernatant to a clean falcon tube. Keep the pellet in freezer for analysis on SDS-PAGE gel. Purification of the nanobody is explained in Subheading 3.3.

3.2 Large-Scale Production of Nanobody (5 L of Culture Media)

The procedure described below is intended for using the Eppendorf BioFlo 115 benchtop fermentor (or bioreactor). At some points in the procedure there is a referral to the manufacturer’s manual for more detailed descriptions.

3.2.1 Preparation of Bacteria

1. Follow Subheading 3.1, step 1.

3.2.2 Vessel Sterilization and O/N Bacterial Pre-culture

1. Follow Subheading 3.1, step 2, to prepare O/N culture. 2. Prepare the 5 L fermentor vessel for sterilization; check whether all necessary parts are in the vessel and install the DO2 (dissolved oxygen) probe and pH probe according to the manufacturer’s manual.

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3. Add 2 L demi-water to the vessel and sterilize by autoclaving for 25 min at 121  C. 3.2.3 Production in Fermentor

1. After sterilization, position the vessel next to the BioFlo 115 control cabinet, and tighten the screws on the head plate. 2. Put the sample kit back in place and tighten the glass bottle (make sure that the metal clip is tight on the silicon tube). Secure all connections. 3. Connect the cooling lines to the cooling loop and the exhaust/ condenser and start the watercooler (switch ON and then press the enter button for a few seconds). 4. Turn on the control cabinet. 5. It takes around 2 h for the DO2 probe to get polarized before it can be calibrated. Calibrate its zero value to “0” and then connect the cable. When the DO2 probe is polarized set its span value. Set the DO2 to 70% and Auto. 6. Carefully place the agitation motor on top of the vessel and put the heating blanket around the vessel (approximately 1 cm below media level). 7. Add a small amount of demi-water to the temperature probe holder and put it in until it reaches the bottom. 8. Connect the air supply from the fermentor to the sparger. 9. Connect the pH sensor to its corresponding data cable. 10. Remove the H2O using the harvest tube and replace with the short silicon tube (close the clip). 11. Add 5 L TB medium (supplemented with potassium phosphate buffer, 0.1% glucose, appropriate antibiotic, and 500 μl antifoam) using a sterile funnel. Put 1 mL sample aside which can be used as “blank” when measuring ODs at 600 nm on a spectrophotometer. 12. Calibrate the pH sensor according to the manufacturer’s manual. 13. Insert the tubing of the base and/or acid into the pumps and “prime” them. Use syringe needles to bring acid and base in the vessel via the two septum ports. 14. Set pH to Auto (choose for pH 7.0  0.1) and set the fermentor to the Agit cascade and Agit to Auto (max agit 1000 rpm and min 200) (see Note 5). 15. Heat up the media to 37  C. Set Temp to Auto. 16. Connect the foam trap to the exhaust/condenser. 17. Allow gas to flow in the vessel (adjust left gas controller up to 1) until the DO2 probe gives a stable signal. 18. Start up the BioCommand® supervisory software to monitor all parameters during the fermentor production.

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19. As soon as all parameters have reached the optimal value (DO2 will be higher than 70%), start the inoculation by adding 50 mL (1:100 dilution) of the overnight culture using the big port on the top. 20. Allow the bacteria to grow at 37  C until the desired OD is reached. Use the sample kit to take samples to monitor the OD at 600 nm. 21. Once the OD600 nm is in log phase (usually between 2 and 4; see Note 6), add IPTG to a final concentration of 1 mM. 22. Lower the temperature for O/N production to 25  C. 3.2.4 Harvesting Bacterial Culture

1. Take two samples with a 20-min interval to monitor whether the OD is stable. If the OD is stable and not increasing anymore, choose “End batch” in BioCommand (look in Batch Control). 2. Set everything to OFF (including gas) apart from agitation and remove the blanket. 3. Connect the harvest tube and collect the culture. 4. Turn off Agit, prime the pumps out, and switch them off. Switch off the console and the cooler. 5. Clean the fermentor vessel and tubing according to the manufacturer’s manual. 6. Centrifuge the culture at 6000  g for 20 min at 4  C. Resuspend the pellet in PBS (180 mL for 5 L culture) and freeze/ thaw two times. The purification is described in Subheadings 3.4 and 3.5.

3.3 Purification of Nanobodies with Affinity Chromatography Approach Using Gravity-Flow Column

This protocol refers to the purification of nanobodies using Nickel (for nanobodies with histidine-tag, his-tag) and CaptureSelect™ C-tag Affinity Matrix (for nanobodies with EPEA-tag or C-tag) with gravity-flow column, and thus from medium-scale nanobody production. 1. Add appropriate amount of beads to a small column and wash with PBS to remove storage buffer (see Note 7). 2. Load the periplasmic fraction on the column and incubate for 1 h at 4  C on a shaker. 3. Collect the flow-through and wash the beads with cold PBS. Repeat this step until the absorbance of flow-through at 280 nm approaches baseline. 4. Elute nanobody containing his-tag with two resin-bed volume of 300 mM imidazole solution. Repeat this step to collect all bound nanobody. To elute a nanobody containing EPEA-tag from C-tag Affinity Matrix, use Tris-MgCl2 elution buffer. Monitor the absorbance of fractions at 280 nm.

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5. To remove imidazole or MgCl2 use gel filtration or dialysis. 6. Analyze purified proteins by SDS-PAGE. 3.4 Purification of Nanobodies Through Affinity chromatography with A¨KTAxpress System

3.4.1 Sample Preparation and Column Attachment

The method stated below can be used for nanobodies containing either the histidine-tag or the EPEA-tag or for nanobodies which can be purified using protein A (see Note 8). The purification steps are similar and differ only in buffer usage. The buffers and columns for each type of affinity purification are indicated under materials. The method includes a second chromatography step using desalting columns to exchange the buffer used in the first chromatography step against PBS. 1. Filter all buffers through a 0.2 μm PES filter and degas until all dissolved air bubbles have disappeared (use a vacuum pump, see Note 9). 2. Filter the bacterial periplasm using a 0.45 μm vacuum filter and check the pH. Adjust if necessary (see Note 10). 3. Attach the appropriate affinity column on column position 1 (depending on the nanobody, either HisTrap, CaptureSelect™ C-tag, or protein A HP) and two stacked HiTrap desalt¨ KTAxpress system ing columns on column position 5 of the A (see Note 11).

3.4.2 Nanobody Purification and Buffer Exchange

The following steps can be included in a single purification program, but will be addressed separately. A purification program can be made beforehand using the “method wizard” function available in the Unicorn software. During purification all parameters (flow rate, pressure, absorbance) should be monitored and intervention is possible at each step. 1. Remove 20% ethanol from the system (including sample loading tubing) and the columns using Milli-Q water (see Note 12). 2. Equilibrate the system and columns (including the sample loading tubing) with at least five column volumes (CV) of binding buffer for the affinity columns (position 1). Equilibrate the desalting columns with 5 CV of PBS (position 5). 3. Load the sample (bacterial periplasm) onto the column with a flow rate of 1 mL/min or 5 mL/min, for the 1 mL or 5 mL columns, respectively (see Note 13). 4. Wash out the sample with 10–15 CV of binding buffer, until the absorbance reaches a steady baseline. 5. Elute the sample with 5 CV 100% elution buffer (one-step block elution). Make sure that the eluted peak fractions will be stored in one of the five sample loops (10 mL) within the system.

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6. Wash out any remaining protein with an additional 5–10 CV of elution buffer. 7. Wash the pumps and system with PBS. 8. Load sample from sample loop onto the stacked HiTrap desalting columns with a flow rate of 5 mL/min and collect peak fractions (see Note 14). 9. Elute the sample with 1.1 CV PBS (11 mL). Make sure that the peak fractions are collected using the fraction collector. 10. Wash system and columns with 5–10 CV of Milli-Q water, followed by 5–10 CV of 20% ethanol. 11. Analyze obtained fractions by SDS-PAGE (see Note 15). 3.5 Purification of Nanobodies Using Ion-Exchange Chromatography

3.5.1 Sample Preparation and Column Attachment

The method stated below can be used for purification of nanobodies devoid of purification tags, such as the histidine-tag or the EPEA-tag. The ion-exchange chromatography protocol is based on the separation of molecules due to their charge. Depending on the pH of the buffer, nanobodies may carry a net positive charge, a net negative charge, or no charge. The isoelectric point (i.e., pI) is a pH at which a molecule has no net charge. The pI value can be determined experimentally or in silico based on the primary sequence of the molecule, using, e.g., ProtParam Tool. As the choice of buffer pH affects the net charge of the nanobody, when purifying the nanobody using a negatively charged cation-exchange resin the nanobody should carry a positive net charge. In order for the nanobodies to carry a positive net charge a buffer with a pH lower than the pI of the nanobody should be used. The buffers and columns used in this procedure are indicated under materials. The method includes two consecutive chromatography steps, indicated as STEP 1 and STEP 2. 1. Filter all buffers as described in Subheading 3.4, step 1. 2. Filter the bacterial periplasm as described in Subheading 3.4, step 2. The first purification step involves a negatively charged cation-exchange resin; therefore adjust the pH of the periplasm to 0.5–1.5 pH units less than the pI of the nanobody (see Note 10). 3. Attach the HiTrap SP HP cation-exchange chromatography column on column position 1.

3.5.2 Nanobody Purification Using the HiTrap SP HP Cation-Exchange Chromatography Column (STEP 1)

A purification program can be made beforehand using the “method wizard” function available in the Unicorn software. During purification all parameters (flow rate, pressure, absorbance) can be monitored and intervention is possible at each step. 1. Remove 20% ethanol from the system as described in Subheading 3.4, step 4.

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2. Equilibrate the system and columns (including the sample loading tubing) with at least five column volumes (CV) of binding buffer A for cation-exchange column (see Note 16). 3. Load the sample (bacterial periplasm) onto the column with a flow rate of 1 mL/min or 5 mL/min, for the 1 mL or 5 mL columns, respectively. 4. Wash out the sample with 10–15 CV of binding buffer A, until the absorbance reaches a steady baseline. 5. Elute the sample with increasing gradient set to 100% target buffer B. Make sure that the eluted peak fractions are collected. 6. Wash out any remaining protein with an additional 5–10 CV of elution buffer (100% buffer B). 7. Pull together fractions collected in steps 8 and 9. 8. Wash system and columns with 5–10 CV of Milli-Q water, followed by 5–10 CV of 20% ethanol. 9. Analyze obtained fractions by SDS-PAGE. 3.5.3 Nanobody Purification Using the HiPrep™ Q XL 16/10 Column Anion-Exchange Chromatography Column (STEP 2)

1. Attach the HiPrep™ Q XL 16/10 column anion-exchange chromatography column on column position 1. 2. Wash the column in Milli-Q water to remove ethanol. 3. Wash the column in 0.1 M NaOH at a flow rate of 5 mL/min for 4 min. 4. Wash the system in Milli-Q water at a flow rate of 5 mL/min for 10 min. 5. Wash the system in PBS at a flow rate of 5 mL/min for 10 min. 6. Load sample obtained in step 10. 7. Collect the flow-through as this fraction contains purified nanobody. 8. Wash the system with 5–10 CV of 2 M NaCl. 9. Wash the system with 5–10 CV of Milli-Q water. 10. Wash the system with 3–5 CV of 0.1 M HCl. 11. Wash the system with 5–10 CV of Milli-Q water. 12. Wash the system with 3–5 CV of 0.1 M NaOH. 13. Wash system and columns with 5–10 CV of Milli-Q water, followed by 5–10 CV of 20% ethanol. 14. Analyze obtained fractions by SDS-PAGE.

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Notes 1. Some nanobodies have affinity for protein A or G and therefore protein A or G beads can be used for purification. This enables tag-less protein purification. 2. Take along a mock O/N culture as a negative control. 3. To ensure sufficient aeration, about 2/3 of the flask should be empty. As an example, for production of 800 mL cells, 2 L flask should be used. Terrific broth (TB) can be used alternatively for the production of nanobodies. The difference between YT-2x and TB medium is that the latter is more nutritious and may result in higher yields of produced nanobodies. 4. To evaluate the induction of nanobody, samples can be collected before and after addition of IPTG and analyzed on SDS-PAGE gel. To this end, 1 mL samples should be centrifuged at 4000  g for 5 min and the pellets resuspended in sample buffer. To adjust the ODs, 40 μL of sample buffer should be used per 0.5 of OD. Boil 30 μL of samples at 100  C for 10 min and load on 15% SDS-PAGE gel. The protein bands are visualized using Coomassie blue staining. 5. Agitation controls dissolved oxygen through automatically controlled agitation speed. When the actual DO2 value drops below the set point, the system will increase the agitation speed up to as much as the high limit to meet the culture demands. Once the DO2 set point is reached or exceeded, the agitation will fall back down to the low limit. 6. Fermentor productions can reach very high ODs (up to 20) as a result of better controlled medium for bacterial growth. Due to a longer log phase, IPTG is usually added at an OD between 2 and 4. 7. The beads for affinity chromatography should be chosen based on the tag on the nanobody. Nickel beads are used for purification of nanobodies with histidine-tag (his-tag) and C-tag Affinity Matrix is suitable for the nanobodies with EPEA tag (or C-tag). The right amount of beads required to obtain pure nanobody fractions should be determined experimentally. 8. Depending on the expected nanobody yield, one may choose a 5 mL affinity column with a five times higher binding capacity, instead of a 1 mL column. 9. Air bubbles introduced into a column may clog the buffer flow, resulting in an increased column pressure, and a decreased binding capacity. Therefore, it is important to degas all buffers which are passed over the column. Avoid vigorous shaking of the buffers after degassing.

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10. Always check the pH of the periplasm and adjust if necessary (pH should be around 7). Alternatively, the sample may be diluted (e.g., 1:1) in the binding buffer. When purifying a nanobody containing a histidine-tag using a HisTrap column, make sure that the bacterial periplasm does not contain any chelating reagents (e.g., EDTA), as this may remove the nickel ions from the column. This drastically impacts the nanobody yield. 11. The columns can be attached to the system manually, or using a ¨ KTAx“column attachment program” which is preset for the A press system. When attaching columns manually, take into account the maximum flow rate and pressure limit for each particular column. 12. When removing ethanol from the system, make sure that sample loops and fractionation tubing are rinsed as well. Additionally, the tubing which will be used for sample loading should be rinsed. 13. Be sure to collect the flow-through during sample loading. When elution fractions are analyzed by SDS-PAGE, the flowthrough should be loaded as well. If the flow-through still contains nanobody (if for instance maximum column capacity was reached), an additional purification round can be performed using the flow-through. 14. The maximum recommended sample volume of a 5 mL HiTrap desalting column is 1.5 mL. When two columns are stacked, the maximum sample volume is 3 mL. If the sample volume exceeds 3 mL (high protein yield, or broad elution peak), make sure that any excess sample is collected. 15. When eluted fractions are not clean (multiple bands observed on SDS-PAGE), a shallow linear gradient elution (over 20 CV) may be applied to separate proteins with similar binding strengths. Additionally, mild detergents (e.g., 0.2% Triton X-100) can be added to the elution buffer to reduce possible nonspecific hydrophobic interactions. 16. When purifying the nanobody using a cation-exchange column use the buffer of 0.5–1.5 pH units less than the pI of the nanobody. When purifying the nanobody using an anionexchange column use the buffer 0.5–1.5 pH units greater than the pI of the nanobody.

Acknowledgments The authors received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 677582).

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References 1. Heukers R, van Bergen en Henegouwen PMP, Oliveira S (2014) Nanobody–photosensitizer conjugates for targeted photodynamic therapy. Nanomed Nanotechnol 10:1441–1451 2. van Driel PBAA, Boonstra MC, Slooter MD et al (2016) EGFR targeted nanobody–photosensitizer conjugates for photodynamic therapy in a pre-clinical model of head and neck cancer. J Control Release 229:93–105 3. Heukers R, Mashayekhi V, Ramirez-Escudero M et al (2019) VHH-photosensitizer conjugates for targeted photodynamic therapy of met-overexpressing tumor cells. Antibodies 8: 1–13 4. de Groof TWM, Mashayekhi V, Fan TS et al (2019) Nanobody-targeted photodynamic therapy selectively kills viral GPCR-expressing glioblastoma cells. Mol Pharm 16:3145–3156 5. Hamers-Casterman C, Atarhouch T, Muyldermans S et al (1993) Naturally occurring antibodies devoid of light chains. Nature 363: 446–448 6. Oliveira S, Heukers R, Sornkom J et al (2013) Targeting tumors with nanobodies for cancer imaging and therapy. J Control Release 172: 607–617 7. de Meyer T, Muyldermans S, Depicker A (2014) Nanobody-based products as research and diagnostic tools. Trends Biotechnol 32: 263–270 8. Helma J, Cardoso MC, Muyldermans S et al (2015) Nanobodies and recombinant binders in cell biology. J Cell Biol 209:633–644 9. Ignatovich O, Jespers L, Tomlinson IM et al (2012) Creation of the large and highly functional synthetic repertoire of human VH and Vκ domain antibodies. In: Saerens D, Muyldermans S (eds) Single domain antibodies: methods and protocols. Humana Press, Totowa, pp 39–63 10. Olichon A, de Marco A (2012) Preparation of a Naı¨ve library of camelid single domain antibodies. In: Saerens D, Muyldermans S

(eds) Single domain antibodies: methods and protocols. Humana Press, Totowa, pp 65–78 11. Dolk E, Verrips T, de Haard H (2012) Selection of VHHs under application conditions. In: Saerens D, Muyldermans S (eds) Single domain antibodies: methods and protocols. Humana Press, Totowa, pp 199–209 12. Kumaran J, MacKenzie CR, Arbabi-Ghahroudi M (2012) Semiautomated panning of naive Camelidae libraries and selection of singledomain antibodies against peptide antigens. In: Saerens D, Muyldermans S (eds) Single domain antibodies: methods and protocols. Humana Press, Totowa, pp 105–124 13. Pellis M, Muyldermans S, Vincke C (2012) Bacterial two hybrid: a versatile one-step intracellular selection method. In: Saerens D, Muyldermans S (eds) Single domain antibodies: methods and protocols. Humana Press, Totowa, pp 135–150 14. Verheesen P, Laeremans T (2012) Selection by phage display of single domain antibodies specific to antigens in their native conformation. In: Saerens D, Muyldermans S (eds) Single domain antibodies: methods and protocols. Humana Press, Totowa, pp 81–104 15. Liu Y, Huang H (2018) Expression of singledomain antibody in different systems. Appl Microbiol Biotechnol 102:539–551 16. Gorlani A, Lutje Hulsik D, Adams H et al (2012) Antibody engineering reveals the important role of J segments in the production efficiency of llama single-domain antibodies in Saccharomyces cerevisiae. PEDS 25:39–46 17. Ezzine A, M’Hirsi el Adab S, BouhaoualaZahar B et al (2012) Efficient expression of the anti-AahI’ scorpion toxin nanobody under a new functional form in a Pichia pastoris system. Biotechnol Appl Biochem 59:15–21 18. Bazl MR, Rasaee MJ, Foruzandeh M et al (2007) Production of chimeric recombinant single domain antibody—green fluorescent fusion protein in Chinese hamster ovary cells. Hybridoma 26:1–9

Chapter 22 Conjugation of IRDye Photosensitizers or Fluorophores to Nanobodies Vida Mashayekhi and Sabrina Oliveira Abstract Fluorophores have been conjugated to nanobodies for approximately a decade, for several applications in molecular biology. More recently, photosensitizers have been conjugated to nanobodies for targeted photodynamic therapy (PDT). The most common chemistry is the random conjugation in which commercial fluorophores or photosensitizers contain a N-hydroxysuccinimide ester (NHS ester) group that reacts specifically and efficiently with lysines in the amino acid sequence of the nanobody and with the N-terminal amino groups to form a stable amide bond. Alternatively, maleimide-containing fluorophores or photosensitizers can be used for conjugation to thiols, in a site-directed manner through a cysteine incorporated at the C-terminal of the nanobody. This chapter addresses both conjugation strategies, providing details on the reaction conditions, purification, and characterization of the conjugates obtained. Key words Nanobody, conjugation

1

Photosensitizer,

Fluorophore,

Random

conjugation,

Site-directed

Introduction Fluorophores have been conjugated to nanobodies for approximately a decade, for several applications in molecular biology, such as to investigate the internalization of the epidermal growth factor receptor, EGFR [1, 2]. Near-infrared fluorophores have been conjugated to nanobodies and particularly employed for preclinical optical molecular imaging of tumors. Our laboratory has developed nanobodies for optical imaging of EGFR [3, 4], HER2 [5, 6], and CAIX [6, 7] in human tumor xenografts grown in mice. More recently, our group has conjugated photosensitizers to nanobodies for targeted photodynamic therapy (PDT) [8–11]. In general, two main strategies can be used for such conjugations: (a) a random conjugation employing a fluorophore or photosensitizes with a N-hydroxysuccinimide (NHS) ester that reacts with lysine amino acids in the nanobody sequence and the N-terminal amino group and (b) a site-directed conjugation in which the fluorophore or

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_22, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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photosensitizer contains a maleimide (Mal) group that can react with thiols, as present in cysteines, preferably added at the C-terminal of the amino acid sequence. In the random conjugation, lysine residues in the amino acid sequence are acylated with fluorophore or photosensitizer molecules, forming a new amide bond. Since this reaction occurs at random, the degree of conjugation (DOC) depends on the number and accessibility of the lysines, and thus may vary for each different nanobody sequence. Importantly, forcing the reaction for maximizing the DOC should be done with caution, as this could compromise the binding properties of the conjugate to the target of interest. The second strategy is a Michael addition of a thiol, present on a cysteine amino acid, to a maleimide linked to the fluorophore of photosensitizer, forming a thioether bond. Theoretically, it is possible to force the reaction for maximizing the DOC without compromising the binding properties of the conjugate to the target of interest. Such optimization can be done through variations in pH, incubation time, temperature, and nanobody-to-photosensitizer or -fluorophore molar ratio. Nevertheless, these variations should always be followed by determination of binding affinities to confirm that the nanobody remains functional post-conjugation. This chapter addresses both conjugation strategies (Fig. 1), providing details on the reaction conditions, purification, and characterization of the conjugates obtained. This protocol focuses on the fluorophores and photosensitizers commercially available, IRDye 700DX NHS or IRDye 700DX Mal and IRDye 800CW NHS or IRDye 800CW Mal, but can serve as a reference even when other photosensitizers or fluorophores are to be conjugated to nanobodies or other targeting moieties.

2 2.1

Materials General

1. 1x PBS: 138 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 1.8 mM KH2PO4 in Milli-Q; adjust to pH 7.4 with HCl. 2. SDS-PAGE loading buffer without bromophenol blue: 200 mM Tris/HCl, pH 6.8, 40% glycerol, 400 mM DTT, 8% w/v SDS. 3. Nanobody dissolved in 1x PBS. 4. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) buffers and equipment. 5. IRDye 700DX NHS or IRDye 700DX Mal and IRDye 800CW NHS or IRDye 800CW Mal (LI-COR Biosciences) dissolved in anhydrous DMSO. 6. Zeba spin desalting columns (2 mL and 5 mL).

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Fig. 1 Schematic representation of the random conjugation (top) and the site-directed conjugation (bottom)

7. Amicon ultracentrifugal filter (0.5 mL and 4 mL). 8. NanoDrop Spectrophotometer (Thermo Fisher Scientific). 9. Odyssey infrared scanner (LI-COR). 2.2 Site-Directed Conjugation

1. Tris buffer: 50 mM Tris; adjust to pH 8.5. 2. Tris(2-carboxyethyl)phosphine hydrochloride (TCEP). 3. PBS-EDTA: PBS pH 7.4 supplemented with 0.4 mM EDTA. 4. Sodium phosphate buffer (50 mM) with 500 mM NaCl and 1 mM EDTA, adjust to pH 6.9.

3

Methods All experiments are performed at room temperature unless otherwise indicated.

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3.1 Random Conjugation

1. In a 1.5 mL or 2 mL microtube mix 1 mL of nanobody (1 mg/ mL) with 4 molar equivalents of photosensitizer or fluorophore (pre-dissolved in DMSO) and incubate for 2 h at room temperature on an overhead shaker (see Notes 1 and 2). Protect the tube from light. 2. Separate nanobody-photosensitizer or nanobody-fluorophore conjugate from free photosensitizer or fluorophore by gel filtration chromatography using Zeba desalting columns in two sequential steps or dialysis (see Notes 3 and 4). To use 5 mL Zeba column (7 kDa cutoff), first remove the column’s bottom closure and loosen the cap. Place the column in a 15 mL falcon tube and centrifuge at 1000
g for 2 min at 4  C to remove the storage buffer. Discard the buffer and add 2.5 mL of washing buffer (PBS 1x) on top of the resin. Using the centrifugation conditions indicated by the provider (i.e., 1000
g for 2 min), rinse the resin three consecutive times, and then transfer the column into a clean 15 mL tube. Apply the sample on top of the column and collect the flow-through after centrifugation (1000
g, 2 min, 4  C). 3. Take 0.2–0.5 μL (corresponding approximately to 0.2–0.5 μg) of nanobody-photosensitizer or nanobody-fluorophore conjugate into a microtube and prepare the samples for gel electrophoresis with the sample buffer without bromophenol blue. 4. After boiling the samples for 5 min, load the samples on a 15% SDS-PAGE gel. Run the gel until a clear distance of 1–2 cm is left between the front of the gel and the end of the glass. Then, disassemble the gel cassette and place the gel immediately on the Odyssey infrared scanner (see Note 5). 5. Image the gel using the appropriate channel (700 or 800 nm) to detect the fluorescence and estimate the percentage of free photosensitizer fluorophore (fluorescence intensity of the band of free/total fluorescence intensity). The gel can be stained by Coomassie blue afterwards to visualize the protein bands (see Note 6) (Fig. 2). 6. If the percentage of free dye is higher than 10%, repeat the purification using Zeba columns and determine the purity of the conjugate on gel again (see Note 7). 7. Determine the DOC by using the formulas provided by the manufacturer of the photosensitizer or fluorophore. Determine the absorption of the sample at 280 nm and at the wavelength of the maximum absorption of the photosensitizer or fluorophore (i.e., 689 nm for IRDye 700DX, or 774 nm for IRDye 800CW). Use the function Uv-Vis of a NanoDrop spectrophotometer. Dilute the sample 1:3 and 1:6 in PBS and measure the absorbance of each sample twice. The

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Fig. 2 Nanobodies and the respective nanobody-photosensitizer conjugates are separated by SDS-PAGE, with the following order (numbered 1–6): R2, R2–PS, 7D12, 7D12–PS, 7D12-9G8, and 7D12-9G8–PS. Prior to the Coomassie stain, the fluorescence of the photosensitizer is detected (depicted in red, top gel); after the Coomassie stain, the proteins are visualized (depicted in black, bottom gel). (Figure from [9])

concentration of protein and DOC can be calculated with the following formulas: Protein concentration

mg A280  ðR
A Þ
Mw
DF ¼ Ext ml

where R ¼ correction factor (absorbance of photosensitizer/fluorophore at 280 nm), A ¼ maximum absorbance of dye (λmax), Ext ¼ extension coefficient of protein (M1 cm1), Mw ¼ molecular weight of protein, DF (dilution factor) ¼ the factor by which the conjugate was diluted before measuring with Nanodrop A280  ðR
A Þ Dye A ratio ¼  Extprot Protein Extdye where Extdye ¼ extension coefficient of photosensitizer/fluorophore (M1 cm1), R ¼ correction factor (absorbance of dye at 280 nm), Extprot ¼ extension coefficient of protein (M1 cm1)

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8. Depending on the subsequent experiments planned, it may be necessary to have a solution of nanobody-photosensitizer or nanobody-fluorophore conjugate with higher concentration. In that case, use Amicon centrifugal filters to concentrate the sample. Depending on the sample volume, 0.5 ml or 4 ml tubes (10 kDa cutoff) can be used. The following is a general procedure for using 0.5 mL tube: In order to remove the trace of glycerine and also pre-wet the tube, add PBS to the Amicon tube and centrifuge at 14,000
g, 10 min, 4  C. Add the conjugate solution to the tube and centrifuge at 14,000
g, 10 min, 4  C. Place the filter upside down in a clean tube and centrifuge at 1000
g, 2 min, 4  C, to collect the concentrated sample. The following is a general procedure for using 4 mL tube (10 kDa): In order to remove the trace of glycerine and also pre-wet the tube, add PBS to the Amicon tube and centrifuge at 5000
g, 10 min, 4  C. Add the conjugate solution to the tube and centrifuge at 5000
g, 4  C, for a maximum 15–60 min. Use a Pasteur pipette to collect the concentrated sample from the bottom of the filter. 3.2 Site-Directed Conjugation 3.2.1 Protocol 1

Two different protocols for site-directed conjugation are presented here. The optimal method leading to the highest DOC should be determined experimentally for each nanobody. 1. Replace the buffer in which the nanobody is dissolved (i.e., PBS) with Tris buffer, using Zeba desalting column (see Subheading 3.1, step 2, for the procedure). 2. Add 0.5 M of TCEP to the nanobody solution to a final concentration of 20 mM and incubate for 15 min at room temperature, to reduce possible disulfide bonds between the C-terminal cysteines. No shaking is needed (see Notes 8–10). 3. To stop this reduction step, exchange the buffer to PBS-EDTA using Zeba column (see Subheading 3.1, step 2, for the procedure; see Note 11). 4. Use the NanoDrop spectrophotometer to determine the absorption at 280 nm and thus the protein concentration (by correcting with the known extinction coefficient of the protein), and adjust the concentration of the protein to 1 mg/mL (see Note 2). 5. Immediately mix the nanobody with 3 molar equivalents of photosensitizer or fluorophore and incubate overnight at 4  C on an overhead shaker (see Note 11). Protect the reaction tube from light.

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6. If the overnight conjugation mixture looks cloudy, first spin down at 1000
g for 1 min and proceed with the supernatant. Remove the free dye using two consecutive Zeba desalting columns (see Subheading 3.1, step 2, for the procedure). Proceed with the protocol as in Subheading 3.1 from step 3. 3.2.2 Protocol 2

1. Add 0.5 M of TCEP to the nanobody solution to a final concentration of 20 mM and incubate for 15 min at room temperature, to reduce possible disulfide bonds between the C-terminal cysteines. No shaking is needed (see Notes 8–10). 2. To stop this reduction step, exchange the buffer to sodium phosphate containing NaCl and EDTA, using Zeba desalting column (see Subheading 3.1, step 2, for the procedure, Note 11). Proceed with the protocol as in Subheading 3.2 from step 4.

4

Notes 1. The nanobody-photosensitizer or fluorophore molar ratio needs to be optimized for each specific nanobody. 2. The recommended starting concentration of nanobody for random and site-directed conjugation is 1 mg/mL. However, higher concentration can be used in order to obtain higher DOC. Extra caution should be taken into account as this could compromise the binding properties of the conjugate to the target of interest. 3. The number of Zeba columns used for purification of the conjugate can vary, with the photosensitizer or fluorophore employed, as well as the nanobody sequence; thus, this should be explored experimentally. 4. Performing dialysis for removing the free photosensitizer or fluorophore only works for the most hydrophilic molecules. 5. A pre-stained ruler will indicate the position of the front of the gel. When disassembling the cassette to image the gel, do not place the gel in any buffer. Instead, place the gel from the cassette immediately on the scanner. Placing the gel in buffer could lead to the diffusion of unconjugated photosensitizer or fluorophore from the front of the gel, which would lead to an inaccurate determination of the percentage of free photosensitizer or fluorophore in the sample. 6. In general, 1–2 μg of protein can be stained with Coomassie blue for a well-visible protein band. Lower amounts of protein are usually loaded for conjugates, which may not be well visible with Coomassie staining, but it is possible to load side-by-side samples of purified protein and conjugate.

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7. If the reaction is performed in large scale (>1 mL), initially 5 mL Zeba columns can be used for purification. Based on our experience, if the amount of free dye is still more than 10% after 2
5 mL Zeba columns, a good purification is obtained with subsequent concentration of the sample using Amicon centrifugal filters, followed by 2 mL Zeba columns. 8. TCEP can be purchased as aqueous solution in ampule (0.5 M) or powder. In general, TCEP is very soluble in aqueous buffers at almost any pH. However, it is significantly less soluble in organic solvents such as methanol and ethanol. 9. For most applications, 5–50 mM TCEP effectively reduces disulfide bonds in peptides or proteins within a few minutes at room temperature. 10. There are studies suggesting that the reaction can be performed in the presence of TCEP since it does not contain thiol groups. However, some groups have reported that TCEP can react with the maleimide group during labeling reaction [12]. Therefore, it is recommended to remove TCEP before the reaction with the photosensitizer or fluorophore. 11. Site-directed conjugation in PBS works well, but other buffers with pH from 6.5 to 7.5 can also be used. Since unprotonated amines can also react with maleimides, reaction above pH 8.0 should be avoided. The reaction can be carried out at room temperature for 2 h or at 4  C for 16–18 h. For heat-resistant nanobodies, the reaction can be performed at 37  C for 2 h.

Acknowledgments The authors received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 677582). References 1. Hofman EG, Ruonala MO, Bader AN et al (2008) EGF induces coalescence of different lipid rafts. J Cell Sci 121:2519–2528 2. Heukers R, Vermeulen JF, Fereidouni F et al (2013) Endocytosis of EGFR requires its kinase activity and N-terminal transmembrane dimerization motif. J Cell Sci 126:4900–4912 3. Oliveira S, van Dongen GAMS, Walsum MS et al (2012) Rapid visualization of human tumor xenografts through optical imaging with a near-infrared fluorescent anti–epidermal

growth factor receptor nanobody. Mol Imaging 11:33–46 4. van Driel PBAA, van der Vorst JR, Verbeek FPR et al (2014) Intraoperative fluorescence delineation of head and neck cancer with a fluorescent anti-epidermal growth factor receptor nanobody. Int J Cancer 134:2663–2673 5. Kijanka M, Warnders F-J, el Khattabi M et al (2013) Rapid optical imaging of human breast tumour xenografts using anti-HER2 VHHs site-directly conjugated to IRDye 800CW for

Nanobody-Photosensitizer Conjugates image-guided surgery. Eur J Nucl Med Mol I 40:1718–1729 6. Kijanka MM, van Brussel ASA, van der Wall E et al (2016) Optical imaging of pre-invasive breast cancer with a combination of VHHs targeting CAIX and HER2 increases contrast and facilitates tumour characterization. EJNMMI Res 6:1–13 7. van Brussel ASA, Adams A, Oliveira S et al (2016) Hypoxia-targeting fluorescent Nanobodies for optical molecular imaging of pre-invasive breast cancer. Mol Imaging Biol 18:535–544 8. Heukers R, van Bergen en Henegouwen PMP, Oliveira S (2014) Nanobody–photosensitizer conjugates for targeted photodynamic therapy. Nanomed Nanotechnol 10:1441–1451

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9. van Driel PBAA, Boonstra MC, Slooter MD et al (2016) EGFR targeted nanobody–photosensitizer conjugates for photodynamic therapy in a pre-clinical model of head and neck cancer. J Control Release 229:93–105 10. Heukers R, Mashayekhi V, Ramirez-Escudero M et al (2019) VHH-photosensitizer conjugates for targeted photodynamic therapy of Met-overexpressing tumor cells. Antibodies 8: 1–13 11. de Groof TWM, Mashayekhi V, Fan TS et al (2019) Nanobody-targeted photodynamic therapy selectively kills viral GPCR-expressing glioblastoma cells. Mol Pharm 16:3145–3156 12. Kim Y, Ho SO, Gassman NR et al (2008) Efficient site-specific labeling of proteins via cysteines. Bioconjug Chem 19:786–791

Chapter 23 In Vitro Assessment of Binding Affinity, Selectivity, Uptake, Intracellular Degradation, and Toxicity of Nanobody-Photosensitizer Conjugates Irati Beltra´n Herna´ndez, Timo W. M. De Groof, Raimond Heukers, and Sabrina Oliveira Abstract Photosensitizers have recently been conjugated to nanobodies for targeted photodynamic therapy (PDT) to selectively kill cancer cells. The success of this approach relies on nanobody-photosensitizer conjugates that bind specifically to their targets with very high affinities (kD in low nM range). Subsequently, upon illumination, these conjugates are very toxic and selective to cells overexpressing the target of interest (EC50 in low nM range). In this chapter, protocols are described to determine the binding affinity of the nanobody-photosensitizer conjugates and assess the toxicity and selectivity of the conjugates when performing in vitro PDT studies. In addition, and because the efficacy of PDT also depends on the (subcellular) localization of the conjugates at the time of illumination, assays are described to investigate the uptake and the intracellular degradation of the nanobody-photosensitizer conjugates. Key words Nanobody-photosensitizer conjugate, Binding affinity, Selective toxicity, Co-cultures, Uptake, Intracellular degradation

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Introduction Photosensitizers have recently been conjugated to nanobodies for targeted photodynamic therapy (PDT) to selectively kill cancer cells [1–8]. Nanobodies are the smallest naturally occurring antigenbinding domain, derived from heavy-chain antibodies found in Camelids [9], and have been employed in many different applications [10–14]. One of the strongest points of nanobody-targeted PDT is the selectivity and specificity for killing tumor cells. The photosensitizer is selectively delivered to the cells which overexpress the target of interest on the cell membrane, such as the epidermal growth factor receptor (EGFR).

Irati Beltra´n Herna´ndez and Timo W. M. De Groof contributed equally to this work Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_23, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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Nanobody-photosensitizer conjugates bind differently to cells which have different expression levels of the target and, most importantly, nanobody-targeted PDT can selectively kill those cells with the highest target expression, while negative or low-expressing cells remain unaffected [1, 2]. The success of the nanobody-targeted PDT approach relies on nanobody-photosensitizer conjugates that bind specifically to their targets with very high affinities (kD in low nM range). Although nanobodies are known to bind with very high affinities to their targets, a nanobody-photosensitizer conjugate may have its binding properties affected by the conjugation of the photosensitizer. It is therefore essential to determine the binding affinity of the conjugate, as low affinity will likely result in poor accumulation at the tumor site in vivo [15, 16]. Here, we describe a stepwise protocol to determine the binding affinity of nanobody-photosensitizer conjugates, performing binding assays on cells. After this, we describe an assay to determine the toxicity of the nanobody-photosensitizer conjugates on cells, when the photosensitizer is activated by the appropriate light. Here, a method in a 96-well plate format is described, allowing for testing a wide range of concentrations to obtain EC50 values (usually in the low nM range). Furthermore, this approach relies on conjugates that are very toxic to cells overexpressing the target of interest while leaving cells with low target expression unaffected. It is very important to assess this selectivity, as some tumor markers are also present in normal tissues surrounding tumors, though at a lower degree. For this, a method is here described involving co-cultures of cells with different expression levels. In general, the efficacy of PDT is also partly determined by the (subcellular) localization of the photosensitizers upon illumination [17–22]. Because the reactive oxygen species generated by the photosensitizer travel only short distances, PDT will only generate cell damage near the site where they are generated [18, 23]. The localization of photosensitizer generally depends on its chemical properties, such as molecular weight, hydrophobicity, and charge [24, 25]. Some photosensitizers show preferred intracellular localization in the plasma membrane, while others end up in intracellular organelles like mitochondria, endoplasmic reticulum, Golgi, and lysosomes [22]. However, in this approach of nanobody-targeted PDT, the nanobody is the main driver for the distribution of the photosensitizer. For example, nanobody-photosensitizer conjugates could be taken up by the target cells via endocytosis [1, 26]. The different intracellular routes that the receptors can take could potentially be tuned and exploited to maximize the efficacy of the PDT. Processes like receptor activation, clustering, or passive uptake cause internalization of the receptors into early endosomes [26, 27]. Internalized receptors subsequently recycle back to the membrane via different types of recycling vesicles or

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traffic toward protein degradation, which involves late endosomes, multiple vesicular bodies, and lysosomes. Alternatively, proteins can be degraded via the ubiquitin-proteasome system (UPS) [27]. The different localization and chemical nature (pH, reducing environment) affect the extent of the damage caused by light activation and hence the efficacy of PDT [28–30]. Because of this, determining the intracellular fate of nanobody-photosensitizer conjugates is a relevant part of their in vitro characterization. This chapter describes examples for determining the extracellular and intracellular fraction of nanobody-photosensitizer conjugates. Next, a method for determining the ratio of internalized/total nanobodyphotosensitizer conjugate and an approach to study the degradation of the conjugates are described. Altogether, this chapter describes essential protocols to characterize and investigate nanobody-photosensitizer conjugates in the in vitro setting.

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Materials

2.1 General Materials

1. Cells with and without expression of the target of interest. 2. Cell culture medium, such as Dulbecco’s modified Eagle medium (DMEM) + 10% fetal bovine serum (see Note 1). 3. Milli-Q (18 M^-cm). 4. 1x PBS: 138 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 1.8 mM KH2PO4 in Milli-Q; adjusted to pH 7.4 with HCl. 5. Nanobody-photosensitizer conjugates in PBS. 6. Odyssey Infrared Scanner (LI-COR) or a similar device for detection of near-infrared wavelengths.

2.2 Binding Assay on Cells for Affinity Determination

1. Binding medium: 1% BSA and 25 mM HEPES in Dulbecco’s modified Eagle medium (DMEM) without phenol red. Adjusted to pH 7.2. Stored at 4  C. 2. GraphPad Prism or similar standard analysis software.

2.3 In Vitro Nanobody-Targeted PDT and Toxicity Assessment

1. PDT medium: Dulbecco’s modified Eagle medium (DMEM) without phenol red, supplemented with 10% FCS, 100 U/mL penicillin, and 100 μg/mL streptomycin. 2. Light source applicable to a 96-well plate format, for instance a device consisting of 96 LED lamps (670  10 nM, 1 LED per well) [31, 32]. 3. Laser measurement sensor (Ophir Optronics LTD), or similar optometer able to measure light intensity at 690 nm. 4. Alamar Blue reagent (BIO-RAD).

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5. FluoStar Optima fluorescent plate reader (BMG Labtech GmbH) or similar plate reader capable of exciting at 550 nm and detecting emission at 590 nm. 6. GraphPad Prism or similar standard analysis software. 2.4 Live/Dead Cell Assay with Mono- and Co-Cultures

1. Propidium iodide (Invitrogen).

2.5 Internalization Assay

1. Acid wash buffer. Either:

2. Calcein AM (Invitrogen). 3. EVOS Microscope (Advanced Microscopy Group, AMG, Thermo Fischer Scientific) equipped with 10 objective, and GFP and RFP (or Texas Red) LED-based fluorescence light cubes, or other similar microscopes.

(a) 0.2 M Glycine buffer, 0.15 M NaCl pH 3.0 [33] (b) 0.05 M Glycine buffer, 0.15 M NaCl pH 3.0 [34] (c) 0.2 M Acetic acid, 0.5 M NaCl pH 2.5 [35, 36] (d) Acid stripping buffer: DMEM supplemented with 0.2% bovine serum albumin (BSA) and with the pH adjusted to 3.5 using HCl [37] (e) DMEM, 10 mM HEPES, 0.2% BSA pH 2.5 [38] 2. A detector for quantification of the label. This can either be a fluorescence scanner or a radioactive counter. 125I-labeled nanobodies can be quantified using a PerkinElmer Precisely 1470 automatic gamma counter [26]. In case of the PS IRDye700DX, the PS can be quantified using an Odyssey scanner (Li-COR) [1]. 3. ELISA materials: Antibodies directed against the nanobodies or tags (e.g., anti-VHH, anti-Myc or anti-His). Peroxidaseconjugated secondary antibodies and detectable colorimetric (o-phenylenediamine (OPD), tetramethylbenzidine TMB), fluorescent, or chemiluminescent substrate, combined with the appropriate detector. 4. TCA precipitation: 20% (w/v) Trichloroacetic acid (TCA) in Milli-Q.

2.6 Intracellular Degradation Assay

1. Size separation: Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) buffers and equipment. 2. SDS-PAGE loading buffer without bromophenol blue. 200 mM Tris–HCl, pH 6.8, 40% glycerol, 400 mM DTT, 8% w/v SDS.

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Methods Keep the nanobody-photosensitizer conjugates at 4  C or 20  C and protected from light.

3.1 Binding Assay on Cells for Affinity Determination

1. Seed cells in a 96-well plate using 100 μL per well, in such a way that cells reach around 85–90% confluency on the day of the assay (see Note 2). Perform the assay in triplicates, meaning cells should be seeded in ten by three wells per each conjugate to be tested, leaving the outer rim without cells, to avoid artifacts due to the faster evaporation of the medium in those wells. 2. On the day of the assay, let the cells adjust to room temperature for 5 min. Subsequently, bring the cells to 4  C and let settle for another 5 min (see Note 3). 3. Prepare a dilution of nanobody-photosensitizer conjugate in binding medium in a final concentration of 100 nM (see Note 4). 4. Remove culture medium from the wells and wash cells once with cold binding medium. 5. Add a concentration range of conjugate starting with the highest concentration and diluting 1:2 with binding medium in each consecutive column of wells. The final volume in each well should be 100 μL. 6. Incubate the cells with the conjugate for 2 h at 4  C, with gentle agitation. Keep the well plate protected from light. 7. Wash cells twice with cold binding medium and remove any remaining bubbles. 8. Scan the well plate to detect the bound nanobody-photosensitizer conjugate via the fluorescence of the photosensitizer. Scan at 700 nm when using the photosensitizer IRDye-700DX. 9. Plot the nanobody-photosensitizer concentration on the x-axis and the fluorescence intensity values on the y-axis (Fig. 1a), after subtracting background fluorescence corresponding to wells with cells and medium only. From the resulting saturation curve, calculate the concentration at which half of the maximum fluorescence is observed, which is known as the apparent affinity of the nanobody-photosensitizer conjugate (see Note 5).

3.2 In Vitro Nanobody-Targeted PDT and Toxicity Assessment

When setting up and performing the illumination step for PDT, wear laser safety glasses and ensure that others take precautions as well.

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Fig. 1 Specific binding and selective toxicity of nanobody-photosensitizer conjugates. (a) Nanobodyphotosensitizer conjugates were incubated with cells in a concentration range and bound conjugate was detected. Conjugates bind to cell lines with different levels of EGFR (A431 > 14C > Hela), but not to negative cells (3 T3 2.2). (b) Cell viability of 14C cells after nanobody-targeted PDT expressed as a percentage relative to untreated cells. The photosensitizer (PS) alone or light alone does not have an effect on cell viability; only the combination of conjugate (7D12-PS or 7D12-9G8-PS) with light results in cell toxicity. (c) Fluorescent microscopy of a co-culture of Hela and 14C cells when no light is applied and after nanobody-targeted PDT. Propidium iodide staining (depicted in blue) can only be detected on 14C cells after treatment, while Hela cells remain alive as depicted by the calcein staining (in green). The 7D12-PS conjugate (shown in red) can be imaged as well [1]

1. Seed cells in a 96-well plate using 100 μL per well, in such a way that cells reach around 70–75% confluency on the day of the assay (see Note 2). Perform the assay in triplicates, meaning cells should be seeded in ten by three wells per each conjugate to be tested. Do not seed cells in the outer wells in order to avoid artifacts due to the faster evaporation of the medium in those wells. 2. On the day of the assay, prepare three dilutions of the nanobody-photosensitizer conjugate in PDT medium (e.g., 50 nM, 5 nM, and 0.5 nM). 3. Remove the cell culture medium from the wells and wash once with warm PDT medium using 100 μL per well. 4. Add the nanobody-photosensitizer conjugate, starting at 50 nM and diluting 1:2 with PDT medium in the two consecutive columns of wells (for 25 and 12.5 nM). Do the same starting with 5 nM and 0.5 nM (see Note 6). The final volume in each well should be 100 μL. Use the last column of wells with cells as control wells, which will only contain 100 μL of PDT medium, and thus no conjugate (see Note 7). 5. Incubate the well plate at 37  C (5% CO2) for 30 min; this step is also referred to as pulse (see Note 8). 6. During the incubation time, set up the light-emitting device. Using the optometer and covering the device with black paper, or a black plastic box, measure the intensity of the emitted light at the height of the well plate. Adjust this intensity to the desired value (e.g., 4 mW/cm2).

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7. After the pulse, wash cells twice with PDT medium and add 100 μL of PDT medium to all the wells (including outer wells). 8. Immediately after the washes and just before illumination, use the Odyssey infrared scanner to detect the fluorescence corresponding to the nanobody-photosensitizer conjugate associated with cells (bound and/or internalized) (see Note 9). 9. Always cover the bottom of the control wells with black paper, where no nanobody-photosensitizer conjugate was added, so that these wells do not receive light. Illuminate with the desired fluence and fluence rate (e.g., a fluence rate of 4 mW/cm2 for 42 min, for a total dose of 10 J/cm2). Cover the plate with black paper during the illumination time, for safety reasons. 10. Place the well plate back in the 37 illumination.



C incubator after

11. After overnight or 24 h, bring Alamar Blue reagent to room temperature and add 10 μL to each well. Mix this with the 100 μL of medium already present in the wells (see Note 10). Make sure to add Alamar Blue reagent to some outer wells (without cells) to set the background fluorescence signal. 12. Return well plate to 37  C and incubate for 1.5 h, or until a purple to pink color develops in the control wells (see Note 11). 13. Measure the fluorescence intensity with a well plate reader. Take as background the values from wells only containing PDT medium and Alamar Blue. Set the 100% viability from the wells that did not receive light and were not treated with nanobody-photosensitizer conjugate (control wells). Express cell viability as a percentage relative to these control wells (Fig. 1b). The concentration at which 50% of the cells are killed is the EC50 and can be determined using GraphPad. 3.3 Live/Dead Cell Assays with Monoand Co-Cultures

1. Seed cells in a 96-well plate using 100 μL per well, in such a way that cells reach around 70–75% confluency on the day of the assay. When using co-cultures, seed a mixture of cells consisting of 50% of each cell line (see Note 12). 2. Perform nanobody-targeted PDT on the 96-well plate (as described above) using the nanobody-photosensitizer conjugate concentrations of interest. For instance, 25 nM nanobody-photosensitizer is enough to result in 100% toxicity to the cells. 3. Incubate the well plate at 37  C for the desired time. Live/dead assessment can be performed as early as right after PDT or after overnight incubation. Necrotic cells are already detectable early after nanobody-targeted PDT.

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4. Dilute propidium iodide and calcein AM in PBS to a concentration of 1 μg/mL and 0.5 μg/mL, respectively (see Note 13). Remove the culture medium from the wells and add 100 μL of solution per well. Incubate the well plate at 37  C for 5 min. 5. Image the cells with the EVOS Microscope using the GFP channel for calcein AM and the RFP channel for propidium iodide. Dead cells will appear red, while live cells will be stained with green (Fig. 1c). Phase-contrast images can also be taken with the EVOS Microscope and overlays are generated. 3.4 Internalization Assay

This assay is employed to investigate the uptake of nanobodyphotosensitizer conjugates, but is also applicable to conjugates of nanobody with radioisotopes or fluorophores. For determining the ratio of internal vs. total/external nanobody-photosensitizer conjugates, it is important to be able to accurately remove or isolate the extracellular nanobodyphotosensitizer fraction. Because binding of the nanobody is often mediated by charge interactions, extracellular binding nanobody can be removed using an acid wash. However, to validate whether the acid wash is successful, the binding of the nanobodyphotosensitizer to the target after acid wash at 4  C (see Note 14) needs to be assessed. This is of importance because some nanobodies are still able to bind their targets at acidic pH.

3.4.1 Determination of the Binding Equilibrium of the Nanobody Over Time

To determine the effectivity of the acid wash, the binding equilibrium of the nanobody needs to be determined first by testing the binding of a saturating concentration over time (see Note 15). 1. Seed cells in a 96-well plate to obtain confluency the next day. 2. Take the plate on ice (or 4  C) the next day and aspirate the growth medium of the latest time point. Add 100 μL of the saturating concentration of nanobody-photosensitizer, diluted in cold blocking buffer, to the well (see Note 16). 3. Do the same for the next time points. After incubation of the conjugates at different time points, aspirate all wells and carefully wash all wells 2–3 times with 150 μL of cold PBS on all wells. 4. The fluorescence intensity of the cell-bound nanobody-photosensitizer conjugates can be quantified using a preferred method (see Note 17).

3.4.2 Optimization of the Acid Wash

A critical part of this protocol is the acid wash, used to remove bound nanobody-photosensitizer conjugates from the surface of the cells, to accurately investigate the intracellular fraction. Therefore, it is important to optimize this wash, so that it is compatible with the conjugate being investigated.

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Careful consideration is needed when choosing the appropriate acid wash buffer. Different types of acid wash can be used and are summed up in the material section. To assess the effectivity of the acid wash buffer, a saturating concentration of nanobodyphotosensitizer is added to cells and incubated until binding equilibrium is reached. 1. Seed cells in a 48-well plate to obtain confluency the next day. In case of cells that detach easily, cells can be seeded 2 days before the assay. 2. Take the plate on ice (or 4  C) the next day and aspirate the growth medium. Add 100 μL of a saturating concentration of nanobody-photosensitizer, diluted in cold blocking buffer, and incubate long enough to reach binding equilibrium (as described in Subheading 3.5.1, see Note 18). 3. Remove the cold medium and add 150 μL of acid wash buffer (see Note 19) for 10 min on ice. Aspirate or collect the acid wash buffer and wash again with 150 μL of acid wash buffer (see Note 20). 4. Aspirate or collect the acid wash buffer from all wells. 5. Wash the wells 3 with 200 μL ice-cold washing buffer while keeping the plate on ice. 6. Scan the plate using a fluorescence scanner to determine the amount of residual nanobody-photosensitizer conjugates after acid wash. Alternatively, in case the acid wash is tested using radiolabeled nanobodies, lyse the cells in 150 μL RIPA buffer for 10 min at room temperature and quantify the residual nanobodies using a radioactivity counter. 3.4.3 Determining Internalized Nanobody-Photosensitizer Fraction Using Fluorescence

Using an optimized acid wash protocol allows a careful distinction between total, surface-bound, and internalized nanobodyphotosensitizer conjugates. This can be assessed by different methods. For example, the traceability of the nanobody-photosensitizer conjugates can be exploited by detecting them by their fluorescent properties. However, uptake of conjugates can also be quantified by using radiolabeled nanobodies or via ELISA. 1. Seed cells, with (and without) the receptor of interest, in two 48- or 96-well plates to obtain confluency on the day of the assay (see Note 21). One plate will be tested at 37  C (warm plate where uptake takes place) and one at 4  C (cold plate with only surface binding). 2. Next day, take the cold plate on ice and dilute the nanobodies at saturation concentration in prewarmed (37  C) or cold (4  C) binding medium. Alternatively, the cells can be preincubated with the nanobody-photosensitizer solution at 4  C,

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until binding equilibrium is reached, after which the plates are transferred to 37  C for the desired time periods. 3. Aspirate the medium from the wells of the last time point of both the warm and cold plates and add 100 or 150 μL (for 96or 48-well plate, respectively) of the nanobody in the binding medium. Put the plate back in the incubator or on ice. 4. Do the same for the next time points. After incubation of nanobodies at different time points, quickly aspirate all wells and put 150–200 μL of ice-cold PBS on all wells. 5. Wash wells again with cold PBS and apply the acid wash as optimized under Subheading 3.4.2. The amount of label in this acid wash can be regarded as bound, but not internalized nanobody-photosensitizer. The acid wash should have removed all nanobody-photosensitizer from the cells that have been kept at 4  C (see Note 22). 6. Scan the plate after this acid wash in order to quantify the internalized fraction of photosensitizer. Alternatively, lyse the cells in SDS-PAGE loading buffer and quantify the amount of label on a fluorescence scanner after size separation by SDS-PAGE. 3.4.4 Determining Internalized Nanobody-Photosensitizer Fraction Using ELISA

In case the internalization on nanobodies cannot be measured directly via their label (photosensitizer, fluorophore, radioactivity, etc.), one might consider to determine the nanobody uptake by ELISA. Nanobodies can be detected with anti-VHH antibodies or via the use of specific peptide tags (Myc, FLAG, His). 1. The first steps in this protocol are similar to the first five steps described under Subheading 3.4.3. 2. Fix the cells for 10 min with 100 μL (96-well plate) 4% paraformaldehyde in PBS. 3. Wash the cells with PBS and block the wells with 150 μL (96-well plate) blocking buffer for 30 min at room temperature. 4. Remove the blocking buffer and add the appropriate dilution of the nanobody in the blocking buffer to detect the tag. Incubate the primary antibody solution long enough to allow binding equilibrium at room temperature. 5. After reaching binding equilibrium, wash the wells 2–3x with PBS and add a secondary antibody-HRP dilution to the wells. If extra incubation steps are needed to detect the receptor of interest, repeat this step. 6. Wash the cells 3x with PBS and add OPD/TMB to the wells. 7. Stop the reaction with 1 M H2SO4 in time to allow maximum window.

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8. Quantify the fraction of internalized nanobodies (see Note 23) by spectrometry at a wavelength of 450 nm or 490 nm depending on the used substrate. 3.5 Assessment of Intracellular Degradation of NanobodyPhotosensitizer Conjugates

Upon uptake by the targeted cells, nanobody-photosensitizer conjugates can be recycled back to the membrane and secreted back into the medium or the conjugates can be degraded intracellularly by the proteasome system or the lysosomes. The free photosensitizer that is formed as a consequence of nanobody-photosensitizer degradation can either accumulate inside the cells or diffuse out of the cells into the medium. Free photosensitizer (or other label/ fluorophore) and protein-bound photosensitizer (or label/fluorophore) can be quantified upon protein precipitation by means of TCA precipitation or by size separation by SDS-PAGE. The following protocol describes how to determine the fraction of degraded nanobody-photosensitizer conjugates by using SDS-PAGE and fluorescence imager. 1. Seed cells in a 48-well plate to obtain confluency the next day. 2. The next day, if desired, cells could be preincubated with inhibitors (see Note 24). Subsequently, take the plate on ice (or 4  C) the next day and aspirate the growth medium. Add 100 μL of a saturating concentration of nanobodyphotosensitizer, diluted in cold blocking buffer, and incubate long enough to reach the binding equilibrium. 3. Transfer the cells to 37  C for the desired time periods. 4. For photosensitizer molecules that diffuse out of cell upon degradation of the conjugates, collect the medium and determine the fraction of degraded nanobody-photosensitizer conjugates by TCA precipitation of all proteins. For photosensitizer molecules that cannot diffuse out of cells (e.g., IRDye700DX), make cell lysates in sample buffer without bromophenol blue (see Note 25). 5. Determine the fraction of nanobody-photosensitizer conjugates and free photosensitizer upon size separation of the cell lysates by SDS-PAGE and quantification on a fluorescence scanner. An example of such a quantification is shown in Fig. 2.

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Notes 1. Alternatives to DMEM medium as growth medium can be used. 2. To determine the affinity of the nanobody-photosensitizer conjugates, the use of a cell line with medium to high expression levels of the target is advised. This assay should also be performed with a negative cell line to demonstrate the

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Fig. 2 Quantification of nanobody-photosensitizer and free photosensitizer upon a pulse-chase experiment in cells. (a) Cells treated with either IRDye680-labeled monovalent nanobody (7D12) or bivalent nanobody (7D12-9G8) or IRDye800-EGF were lysed and size-separated by SDS-PAGE. Ligand-bound fluorophore is visible at their height, while free fluorophore is present at the running front of the gel. (b) Ligand-bound and free fluorophore was visualized and quantified using an Odyssey imager (Li-COR) [1]

specificity of the conjugate. Cell lines with different target expression levels are also of use to further characterize the conjugate. 3. Ideally, the assay should be performed in a refrigerated room at 4  C. Alternatively, perform the assay while keeping the plate on ice. 4. In general, we expect an apparent affinity in the nanomolar range; thus starting the assay with 100 nM will give a good saturation curve. However, if the outcome is uncertain, higher starting concentrations can be used, e.g., 1 μM. 5. The apparent affinity (KD) can be determined using a one-sitespecific binding, nonlinear regression protocol with GraphPad Prism, or similar standard analysis program. The apparent affinity should remain in the same range as the apparent affinity of the unconjugated nanobody in order to conclude that the conjugation of the photosensitizer to the nanobody does not affect its binding capacity. When a drop in affinity is detected (greater than one order of magnitude), it might be due to the presence of lysine in the complementary-determining regions or CDRs of the nanobody. Moreover, too much conjugated photosensitizer may also negatively affect the binding of the nanobody. The regression protocol will also determine the Bmax, which refers to the maximum density of receptors on the cells and gives an idea of the epitope availability. Thus, cell lines with different expression levels will result in graphs with different Bmax, where a direct correlation is observed.

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6. By adding a concentration range starting from three stock dilutions, a wider range of concentrations can be covered (0.125–50 nM), than if only with 1:2 dilutions steps. 7. When assessing a nanobody-photosensitizer conjugate for the first time, a control consisting of conjugate but no light should be included. The light alone (10 J/cm2) has already been shown to have no effect on the viability of several cell lines. However, it is recommended to include this control when performing the assay the first time. 8. This short incubation period, referred to as “pulse,” is intended to simulate the short time that nanobody-photosensitizer conjugates have in vivo to accumulate at the tumor site due to their short half-life. 9. Since this incubation takes place at 37  C, internalization of the nanobody can occur. If using a monovalent nanobody, the majority will likely not be internalized in the short incubation of 30 min. However, bivalent or biparatopic nanobodies can induce dimerization of the receptor and consequent internalization of the nanobody together with the receptor. The Odyssey scanner does not allow to differentiate fluorescence corresponding to bound nanobody from the internalized nanobody; thus the obtained fluorescence intensity values correspond to both nanobody fractions. 10. The active ingredient of Alamar Blue reagent is a cellpermeable blue compound which is nonfluorescent. When entering live cells, this compound is reduced and becomes red in color and highly fluorescent. Therefore, the fluorescence and color of the media surrounding viable cells will increase. 11. The incubation time with Alamar Blue will ultimately depend on the cell line and treatment. For some cases, 1 h at 37  C is enough for the purple to pink color to develop in the control wells, while it might take up to 4 h in other cases. 12. Co-cultures of two cell lines can be used to assess the selectivity of nanobody-targeted PDT. For instance, use one cell line with low target expression and another one with medium to high expression. The cell lines can be differentiated based on the morphology and the amount of bound PS (Cy5 channel with EVOS microscope), or with a control assay with a fluorescent ligand (e.g., EGF-Alexa555 [1]). 13. Propidium iodide is membrane impermeant and will only gain access to the inside of the cell when the membrane is not intact. The fluorescence of propidium iodide increases when it intercalates with nucleic acids. On the other hand, calcein AM is cell permeant and becomes fluorescent in live cells because of their intracellular esterase activity. Therefore, propidium iodide is

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used to identify necrotic cells with membrane damage, while calcein stains live cells. 14. The acid wash needs to be tested below 16  C and preferably at 4  C to prevent trafficking of the receptor of interest. 15. The time to reach binding equilibrium differs among nanobodies. If the binding equilibrium is not known, it is recommended to use 1 h at least as the latest time point. 16. When plating the cells, use saturating concentration of nanobody-photosensitizer (10x KD). For determining the binding affinity, see the above Subheading 3.1. If possible, an irrelevant nanobody is also taken along as extra control. 17. If the nanobodies are conjugated to the photosensitizer or to a radioligand, binding can be quantified using a scanner. Other methods to detect nanobodies can include ELISA (see below). 18. One time point can be enough to check the acid wash but it is recommended to check different time points of incubation of the nanobody with the cells when assessing the effectivity of the acid wash buffer. 19. Different acid wash buffers have been used in literature and have been summarized in the material section. If a certain buffer does not work or has a toxic effect on the cells used in the assay, it is recommended to try a different acid wash buffer. 20. Preferably, wells containing cells with and without the receptor of interest are also incubated with the nanobodyphotosensitizer but no acid wash is performed to assess the total fraction. 21. For both plates, cells expressing the receptor of interest need to be plated that will be incubated with saturating concentrations of nanobodies for different time points. 22. Also keep some wells where the nanobody has been incubated for the longest time period that are not incubated with the acid wash buffer. This ensures to determine the total fraction both on the cold and warm plates. 23. In case cells were preincubated with nanobodies at 4  C, the ELISA signal in the cold plate can be regarded as the total signal in your assay. The internalized fraction is determined by the ratio of the signal in warm plate (internalized) and cold plate (total, no internalization). 24. If desired, inhibit lysosomal degradation by treatment with chloroquine (50 μM) or increasing the pH with NH4Cl (20 mM) or inhibit proteasomal degradation with MG132. 25. Some photosensitizers of fluorophore molecules might show a spectral overlap with bromophenol blue in Laemmli sample buffer (such as IRDye700DX). In SDS-PAGE, free PS will be

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run together with the bromophenol blue at the front of the gel. In case the free PS needs to be quantified, it is advisable to omit the bromophenol blue from these samples.

Acknowledgments The authors received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 677582) and the Netherlands Organization for Scientific Research (NWO: Vici grant 016.140.657). References 1. Heukers R, van Bergen en Henegouwen PM, Oliveira S (2014) Nanobody-photosensitizer conjugates for targeted photodynamic therapy. Nanomedicine 10:1441–1451 2. van Driel P, Boonstra MC, Slooter MD et al (2016) EGFR targeted nanobodyphotosensitizer conjugates for photodynamic therapy in a pre-clinical model of head and neck cancer. J Control Release 229:93–105 3. De Groof TWM, Mashayekhi V, Fan TS et al (2019) Nanobody-targeted photodynamic therapy selectively kills viral GPCR-expressing glioblastoma cells. Mol Pharm 16:3145–3156 4. Heukers R, Mashayekhi V, Ramirez-Escudero M et al (2019) VHH-photosensitizer conjugates for targeted photodynamic therapy of met-overexpressing tumor cells. Antibodies 8: 26 5. Driehuis E, Spelier S, Beltran Hernandez I et al (2019) Patient-derived head and neck cancer organoids recapitulate EGFR expression levels of respective tissues and are responsive to EGFR-targeted photodynamic therapy. J Clin Med 8:1880 6. Beltran Hernandez I, Angelier ML, Del Buono D’Ondes T et al (2020) The potential of nanobody-targeted photodynamic therapy to trigger immune responses. Cancers 12:978 7. de Bruijn HS, Mashayekhi V, Schreurs TJL et al (2020) Acute cellular and vascular responses to photodynamic therapy using EGFR-targeted nanobody-photosensitizer conjugates studied with intravital optical imaging and magnetic resonance imaging. Theranostics 10: 2436–2452 8. Deken MM, Kijanka MM, Beltran Hernandez I et al (2020) Nanobody-targeted photodynamic therapy induces significant tumor regression of trastuzumab-resistant HER2-

positive breast cancer, after a single treatment session. J Control Release 323:269–281 9. Hamers-Casterman C, Atarhouch T, Muyldermans S et al (1993) Naturally occurring antibodies devoid of light chains. Nature 363: 446–448 10. Oliveira S, Heukers R, Sornkom J et al (2013) Targeting tumors with nanobodies for cancer imaging and therapy. J Control Release 172: 607–617 11. De Meyer T, Muyldermans S, Depicker A (2014) Nanobody-based products as research and diagnostic tools. Trends Biotechnol 32: 263–270 12. Helma J, Cardoso MC, Muyldermans S et al (2015) Nanobodies and recombinant binders in cell biology. J Cell Biol 209:633–644 13. Debie P, Devoogdt N, Hernot S (2019) Targeted nanobody-based molecular tracers for nuclear imaging and image-guided surgery. Antibodies 8:12 14. De Groof TWM, Bobkov V, Heukers R et al (2019) Nanobodies: new avenues for imaging, stabilizing and modulating GPCRs. Mol Cell Endocrinol 484:15–24 15. Schmidt MM, Wittrup KD (2009) A modeling analysis of the effects of molecular size and binding affinity on tumor targeting. Mol Cancer Ther 8:2861–2871 16. Xenaki KT, Oliveira S, van Bergen en Henegouwen PMP (2017) Antibody or antibody fragments: implications for molecular imaging and targeted therapy of solid tumors. Front Immunol 8:1287 17. Shramova EI, Proshkina GM, Deyev SM et al (2017) Flavoprotein miniSOG BRET-induced cytotoxicity depends on its intracellular localization. Dokl Biochem Biophys 474:228–230

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18. Bacellar IO, Tsubone TM, Pavani C et al (2015) Photodynamic efficiency: from molecular photochemistry to cell death. Int J Mol Sci 16:20523–20559 19. Lin CW, Shulok JR, Kirley SD et al (1991) Lysosomal localization and mechanism of uptake of Nile blue photosensitizers in tumor cells. Cancer Res 51:2710–2719 20. Miller GG, Brown K, Moore RB et al (1995) Uptake kinetics and intracellular localization of hypocrellin photosensitizers for photodynamic therapy: a confocal microscopy study. Photochem Photobiol 61:632–638 21. Kessel D, Luo Y, Deng Y et al (1997) The role of subcellular localization in initiation of apoptosis by photodynamic therapy. Photochem Photobiol 65:422–426 22. Castano AP, Demidova TN, Hamblin MR (2004) Mechanisms in photodynamic therapy: part one-photosensitizers, photochemistry and cellular localization. Photodiagn Photodyn Ther 1:279–293 23. Moan J, Berg K (1991) The photodegradation of porphyrins in cells can be used to estimate the lifetime of singlet oxygen. Photochem Photobiol 53:549–553 24. Woodburn K, Kessel D (1995) Effect of density-gradients on the binding of photosensitizing agents to plasma proteins. Int J Biochem Cell Biol 27:499–506 25. Mojzisova H, Bonneau S, Brault D (2007) Structural and physico-chemical determinants of the interactions of macrocyclic photosensitizers with cells. Eur Biophys J 36:943–953 26. Heukers R, Vermeulen JF, Fereidouni F et al (2013) Endocytosis of EGFR requires its kinase activity and N-terminal transmembrane dimerization motif. J Cell Sci 126:4900–4912 27. Huotari J, Helenius A (2011) Endosome maturation. EMBO J 30:3481–3500 28. Friberg EG, Cunderlikova B, Pettersen EO et al (2003) pH effects on the cellular uptake of four photosensitizing drugs evaluated for use in photodynamic therapy of cancer. Cancer Lett 195:73–80

29. Wang C, Liu L, Cao H et al (2017) Intracellular GSH-activated galactoside photosensitizers for targeted photodynamic therapy and chemotherapy. Biomater Sci 5:274–284 30. Helander L, Sharma A, Krokan HE et al (2016) Photodynamic treatment with hexylaminolevulinate mediates reversible thiol oxidation in core oxidative stress signaling proteins. Mol Biosyst 12:796–805 31. Rijcken CJF, Hofman J-W, van Zeeland F et al (2007) Photosensitiser-loaded biodegradable polymeric micelles: preparation, characterisation and in vitro PDT efficacy. J Control Release 124:144–153 32. Hofman J-W, Carstens MG, van Zeeland F et al (2008) Photocytotoxicity of mTHPC (Temoporfin) loaded polymeric micelles mediated by lipase catalyzed degradation. Pharm Res 25: 2065–2073 33. Kameyama S, Horie M, Kikuchi T et al (2007) Acid wash in determining cellular uptake of fab/cell-permeating peptide conjugates. Biopolymers 88:98–107 34. Fabry M, Langer M, Rothen-Rutishauser B et al (2000) Monitoring of the internalization of neuropeptide Y on neuroblastoma cell line SK-N-MC. Eur J Biochem 267:5631–5637 35. Sorkin A, Krolenko S, Kudrjavtceva N et al (1991) Recycling of epidermal growth factorreceptor complexes in A431 cells: identification of dual pathways. J Cell Biol 112:55–63 36. Liu G, Dou S, Yin D et al (2007) A novel pretargeting method for measuring antibody internalization in tumor cells. Cancer Biother Radiopharm 22:33–39 37. Li N, Hill KS, Elferink LA (2008) Analysis of receptor tyrosine kinase internalization using flow cytometry. Methods Mol Biol 457: 305–317 38. Fraile-Ramos A, Kledal TN, Pelchen-Matthews A et al (2001) The human cytomegalovirus US28 protein is located in endocytic vesicles and undergoes constitutive endocytosis and recycling. Mol Biol Cell 12:1737–1749

Chapter 24 Investigation of the Therapeutic Potential of Nanobody-Targeted Photodynamic Therapy in an Orthotopic Head and Neck Cancer Model Pieter B. A. A. van Driel, Stijn Keereweer, Clemens W. G. M. Lowik, and Sabrina Oliveira Abstract Photodynamic therapy (PDT) has a great therapeutic potential because it induces local cellular cytotoxicity upon application of a laser light that excites a photosensitizer, leading to toxic reactive oxygen species. Nevertheless, PDT still is underutilized in the clinic, mostly because of damage induced to normal surrounding tissues. Efforts have been made to improve the specificity. Nanobody-targeted PDT is one of such approaches, in which the variable domain of heavy-chain antibodies, i.e., nanobodies, are used to target photosensitizers selectively to cancer cells. In vitro studies are certainly very valuable to evaluate the therapeutic potential of PDT approaches, but many aspects such as bio-distribution of the photosensitizers, penetration through tissues, and clearance are not taken into account. In vivo studies are therefore essential to assess the influence of such factors, in order to gain more insights into the therapeutic potential of a treatment under development. This chapter describes the development of an orthotopic model of head and neck cancer, to which nanobody-targeted PDT is applied, and the therapeutic potential is assessed by immunohistochemistry one day after PDT. Key words Nanobody, Targeted photodynamic therapy, Preclinical model, Therapeutic potential, Head and neck cancer

1

Introduction Photodynamic therapy (PDT) is generally based on the administration of a photosensitizer, which is then illuminated with a suitable wavelength for activation, to produce local toxicity, via the production of reactive oxygen species. This toxicity is created on the cell membrane or intracellularly, depending on the location of the photosensitizer. Although in vitro PDT studies provide valuable insights into the potency of the photosensitizer and the mechanism of cell death induced, these are far from reflecting the outcome in a living animal. For instance, common in vitro studies do not consider the vascularization of the tumors and, thus, do not assess the

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_24, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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effects of distribution of the photosensitizer through tissues. Therefore, when developing new photosensitizers or new approaches for photodynamic therapy, it is essential to assess the therapeutic potential in living animals. For this, xenografts of human tumors are very often developed subcutaneously in immunocompromised mice (such as in [1]). This approach is certainly valuable and often preferred because the tumor lies subcutaneously and, therefore, light can be easily applied and tumor volume easily measured. Alternatively, researchers have sought to use tumor models that develop at the organ or tissue of origin, also enabling the evaluation of the effect of PDT on the surrounding healthy tissues. Hence, orthotopic xenografted tumor models have been developed, for instance of head and neck cancers. An example of such an orthotopic xenografted model is a tongue tumor model where human head and neck cancer cells are inoculated into the tip of the tongue of an immunocompromised mouse [2–4]. By labeling these tumor cells with a luciferase vector, we have demonstrated that tumor growth could be followed using bioluminescence. Using this model, the growth of both primary tumor and regional cervical lymph node metastases was observed. We have employed this model in a preclinical optical imaging study in which nanobodies were investigated as optical tracers. Nanobodies are the variable domain of heavy-chain antibodies present in the blood of camelids [5]. Although nanobodies are about a tenth of the molecular weight of conventional antibodies, they have shown to be able to bind specifically and very tightly to their targets (such as the epidermal growth factor receptor, EGFR). That study showed that nanobodies could be used to delineate orthotopic tongue tumors and cervical lymph node metastases in the intraoperative setting [4]. Recently we have introduced nanobody-targeted PDT, in which photosensitizers are conjugated to nanobodies for selective killing of cancer cells [6–13]. We have shown that nanobodyphotosensitizer conjugates are very potent and their toxicity is selective to cells with high EGFR levels [6]. The first preclinical study in a mouse model was designed to assess the potential for killing tumor cells in vivo. The conjugates were administered intravenously and light application was performed 1 h postinjection [7]. In this chapter, we describe the development of this orthotopic model of head and neck cancer that was used to assess the therapeutic potential of nanobody-targeted PDT through histological analyses, one day post-PDT. In this particular case, the photosensitizer employed is the IRDye700DX, which is a water-soluble silicaphthalocyanine derivative that we have been employing throughout our nanobody-targeted PDT studies [6–13], and the settings employed for illumination (i.e., fluence and fluence rate) are the

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same as previously described [7]. Nevertheless, this model can be employed for other studies, employing other photosensitizers or conjugates of these.

2

Materials

2.1

Cell Lines

Different tongue tumor cell lines can be employed; here we report on the human oropharyngeal squamous cell carcinoma (OSCC) cell line OSC-19-luc2, which overexpresses EGFR (see Note 1).

2.2

Mice

Nude Balb/c female mice aged 4–6 weeks (e.g., at Charles River Laboratories, L’Arbresle, France) are used. Mice should be housed for 1–2 weeks to acclimatize before experiments commence. Hold the mice in individually ventilated cages (e.g., Green Line IVC, Tecniplast, USA) with environmental enrichment like nesting material and provide them with autoclaved pellet food (e.g., RM3 diet, pelleted, Special Diets Services, UK, see Note 2) and sterilized water ad libitum.

2.3 Equipment and Solutions for the Inoculation of Tumor Cells and for Monitoring Tumor Growth

1. Tumor cell suspension or material (which should be collected before starting the operation and maintained on ice). 2. Chamber with calibrated isoflurane vaporizer. 3. Isoflurane gas (see Subheading 2.6). 4. Buprenorphine (see Subheading 2.6). 5. Electric heating pad. 6. Isoflurane face mask. 7. 0.5 mL Sterile insulin syringe (30G). 8. Sterile cotton swabs. 9. Alcohol. 10. Sterile surgical instruments including scissor, small anatomical forceps, and a clamping needle holder. 11. Aqueous solution of luciferin (Caliper Life Sciences, Hopkinton, Massachusetts, USA) at 150 mg/kg in a volume of 50 μL. 12. Imaging system to measure bioluminescence. Here we used the IVIS 100 imaging system.

2.4 Equipment and Solutions for Photodynamic Therapy

1. Heat lamp. 2. Warm water bath. 3. Mouse restrainer. 4. 1 cc Syringe and 27-gauge needle or 0.5 mL insulin syringe (30G). 5. Dark room.

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6. Chamber with calibrated isoflurane vaporizer. 7. Isoflurane gas (see Subheading 2.6). 8. Buprenorphine (see Subheading 2.6). 9. Electric heating pad. 10. Eye ointment. 11. Nanobody-photosensitizer conjugates (see Subheading 2.5). 12. Electric heating pad. 13. Isoflurane face mask. 14. Anatomical forceps with curved tip. 15. Black paper. 16. Laser, optic fiber, and power meter (see Subheading 2.7). 2.5 NanobodyPhotosensitizer Conjugates

2.6

Medication

Here, the EGFR-targeted nanobodies 7D12 and 7D12-9G8 were employed. The photosensitizer used is IRDye700DX, purchased from LI-COR (LI-COR Biosciences, Lincoln, Nebraska) as an N-hydroxysuccinimide (NHS) ester. Conjugation of the photosensitizer to the nanobodies was performed as described in [7]. 1. Isoflurane, for general anesthesia (see Note 3). 2. Ophthalmic ointment, to apply during long periods of anesthesia (e.g., Lacri-Lube). 3. Painkiller: Before illumination administer the painkiller buprenorphine (0.05–0.1 mg/kg per 12 h) by subcutaneous injection.

2.7

3

Laser

For illumination of the tumors in the tip of the tongue, we used a 690 nm laser (e.g., Modulight, Tampere, Finland) with the setting as in [7]. The power at the end of the optic fiber was calibrated with a power meter (e.g., Gigahertz Optik, Turkenfeld, Germany).

Methods

3.1 Culturing Cell Line 3.1.1 Thawing Cryopreserved OSC-19-luc2-cGFP Cells

1. If the OSC-19-luc2-cGFP cells are stored in liquid nitrogen, transport the vial from liquid nitrogen to the laboratory on dry ice. 2. Prior to thawing, open and close the screw cap slightly to release the pressure and allow the nitrogen to escape during thawing. 3. Thaw the vial with OSC-19-luc2-cGFP cells in a 37  C water bath until a small amount of ice remains. Use 70% ethanol solution to clean the outside of the vial to prevent contamination and transfer the suspension with a sterile Pasteur pipette into a 15 mL tube (e.g., Falcon 15 mL conical tubes, Fisher Scientific). Quick thawing is essential to preserve cell viability.

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4. Dilute the OSC-19-luc2-cGFP cell suspension in the cold culture medium described in Note 1. Cold medium is used because DMSO is toxic to cells when the temperature is over 8  C. To avoid cell toxicity of DMSO the suspension must be diluted at least 30-fold. 5. Transfer the 15 mL tube with OSC-19-luc2-cGFP cell suspension to a centrifuge and spin the cell suspension gently at 300  g for 4 min. 6. Carefully remove the supernatant without disturbing the pellet of cells. Resuspend the pellet in 10 mL of culture medium with a sterile pipette and place in a small T25 flask. 7. Place the flask in a 37  C, 5% CO2, incubator with the cap loosened to allow gaseous exchange to occur (or fully closed if the caps have a filter top). 8. Refresh medium the next day to remove traces of DMSO. 3.1.2 Culture OSC-19-luc2-cGFP Cells

1. From a T75 flask with OSC-19-luc2-cGFP cells that have been growing in the 37  C, 5% CO2, incubator, remove culture medium with a sterile pipette. 2. Wash/rinse the adherent monolayer of OSC-19-luc2-cGFP cells with PBS twice to remove serum because trypsin is deactivated by serum. 3. Dispense 2 mL of trypsin-EDTA (0.05% trypsin) in the flask and spread evenly over the bottom. Incubate for 2–5 min at 37  C until cells visibly detach and check the detachment of cells under the microscope. 4. Resuspend cells in 8 mL of culture medium (contains FCS and therefore neutralizes trypsin) and add 0.5 mL to a new T75 flask. Cells are diluted 1:20 (see Note 4). 5. Add 19.5 mL of medium to the 0.5 mL cell suspension and put the flask in the 37  C, 5% CO2, incubator.

3.1.3 Dilution of 40,000 OSC-19-luc2-cGFP cells in 20 μL PBS

1. Take a T75 flask that is 70-80% confluent with OSC-19-luc2cGFP cells from the 37  C, 5% CO2, incubator and replace the medium 4 hours before harvesting to remove dead and detached cells. 2. To start harvesting cells, the medium is first removed by using a sterile pipette. 3. Wash/rinse the adherent monolayer of OSC-19-luc2-cGFP cells with PBS twice and add 2 mL of trypsin-EDTA (0.05% trypsin) as described in Subheading 3.1.2. 4. Resuspend cells in 8 mL culture medium and add the cell suspension to a 15 mL tube.

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5. Count cells using a hemocytometer and microscope. Calculate the total amount of cells in the 10 mL suspension. Trypan blue staining can be used to exclude dead cells during counting. 6. Depending on the amount of mice that will be used in your experiment take the correct volume of OSC-19-luc2-cGFP cell suspension and pipette into a 2 mL vial. Put the vial in a centrifuge and spin cells down (300  g for 4 min). Add the correct amount of PBS to the vial so that 40.000 OSC-19luc2-cGFP cells are diluted in 20 μL PBS. 3.2 Inoculation of Tumor Cells in the Tongue

1. During inoculation, mice need to be under general anesthesia. Bring the mice to a chamber that is connected to the calibrated isoflurane vaporizer (see Note 3). 2. When the mouse is under general anesthesia, perform a subcutaneous injection of buprenorphine (0.05–0.1 mg/kg per 12 h). 3. Because of the risk for hypothermia, all experiments should be performed by using an electric heating pad or other supplemental heat during anesthesia. Place the mouse on an electric heating pad with isoflurane face mask. Adjust the anesthesia as suggested (see Note 3). 4. Monitor mice under anesthesia by looking at the respiratory rate and pattern, mucous membrane color, and toe pinch. 5. Use a small anatomic forceps with curved tip and gently pull out the tongue of the mouse. 6. The 40,000 OSC-19-luc2-cGFP cells, diluted in 20 μL PBS, are aspirated from the vial that is prepared in Subheading 3.1.3 by using a 1 cc syringe and 30-gauge needle. Make sure that cells are evenly distributed in the 20 μL PBS. This can be done by gentle back-and-forth aspiration of the solution. 7. Inject the OSC-19-luc2-cGFP cells submucosally into the distal end of the tongue. Initially the tongue will be swollen, but this will resolve in less than one day. 8. After the procedure, watch mice until they gain consciousness. After the mice are fully recovered, they are brought back to their cages.

3.3 Monitoring Mice and Tumor Growth

1. After the inoculation, inspect the animals once a day, as a routine inspection for emergencies (see Note 5). 2. Assess tumor growth and animal welfare individually twice a week. For tumor growth, assess through visual inspection of the tongue and bioluminescence (BLI) measurements. For animal welfare, inspect their behavior and perform weight measurements.

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3. For both visual inspection of the tongue and bioluminescence imaging, mice are put under general anesthesia. Bring the mice to the chamber that is connected to the calibrated isoflurane vaporizer. Adjust the anesthesia as suggested (see Note 3). Inject an aqueous solution of luciferin (Caliper Life Sciences, Hopkinton, Massachusetts, USA) at 150 mg/kg in a volume of 50 μL intraperitoneally. Use small anatomic forceps with curved tip and gently pull out the tongue of the mouse. 4. Transport the mice to the heated bed of the IVIS 100 imaging system (Caliper Life Sciences) with incorporated nose mask and maintain general anesthesia as suggested (see Note 3). 5. Five minutes after peritoneal injection of luciferin, start imaging using the IVIS 100 imaging system. Quantify the bioluminescence signal through standardized regions of interest using the living image software (Caliper Life Sciences). 3.4 Photodynamic Therapy 3.4.1 Intravenous Injection of Nanobody-PS Conjugates

1. If tumors are visible by the human eye and the BLI signal ranges between 5  109 and 1  1010 relative light units, photodynamic therapy can be applied. 2. Place the cage with mice under a heat lamp to increase blood flow to the tail vein. 3. Prepare a warm water bath but do not exceed 45  C to prevent overheating. Test the temperature of the water by finger dipping before transporting the mouse. 4. Place the mouse into the barrel of the holding device that restrains the mouse while intravenous access is gained through the tail vein. 5. Put the tail of the mouse into the warm water bath for 2–3 min until the vein expands. 6. Use a 1 cc syringe and 27-gauge needle and hold the needle parallel to the tail vein with the bevel side up. Start the injection as distal as possible. When a second injection site is needed you can perform an injection more proximal than the first attempt. 7. Insert the needle into the vein. If the needle is correctly placed into the vein you can see the tip into the vein and injection of 100 μL will be very easy without any resistance. Press the injection site for some time until bleeding has stopped.

3.4.2 Illumination

1. Illumination of the tumor must take place in a dark room. 2. The time point for illumination should be determined based on the quantitative fluorescence spectroscopy measurements, which in this study is 1 h postinjection of 7D12-PS and 7D12-9G8-PS, as described in [7].

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3. During illumination of the tumor, mice need to be under general anesthesia. Bring the mice to a chamber that is connected to the calibrated isoflurane vaporizer (see Note 3). Perform steps 2–5 as described under Subheading 3.2. 4. Apply ophthalmic ointment during anesthesia (Lacri-Lube) to prevent corneal drying and damage. 5. Pull out the tongue of the mouse using small anatomic forceps with curved tip. When closing the mouth the tumor will stay outside because of swelling of the tumor. 6. Cover the rest of the body, except the tongue, with black paper to protect the animal from any scattering of the laser light. 7. Illuminate the tumor with the appropriate and calibrated laser (indicated under Subheading 2.5 for this study) for the necessary fluence rate and in order to have the necessary light dose (e.g., a fluence rate of 50 mW/cm2 and a fluence of 100 J/ cm2, as employed in [7]). 8. At the end of the illumination, watch mice until they gain consciousness. After the mice are fully recovered, they are brought back to their cages. 9. Inspect the mice the next day, as a routine inspection for emergencies (see Note 5). 3.5 Histological Assessment Post-PDT

1. To assess the therapeutic potential by histology (see Note 6), sacrifice mice 24 h post-PDT (see Note 7). 2. Resect the tongues and freeze for cryosections or process for paraffin sections, for subsequent hematoxylin and eosin (H&E) staining and histological analysis of the phototoxic effect (see Note 8). 3. With the guidance from an experienced pathologist, distinguish necrosis from viable tissue through visual inspection of the sections obtained. Quantify the percentage of necrosis with a software for image analysis, by drawing regions over the entire tumor and over the necrotic areas (see Note 9). In addition, the degree of damage to the surrounding tissue or to the blood vessels can be scored (e.g., using /+/++/+++ for no, mild, moderate, or extreme damage, respectively).

4

Notes 1. This chapter describes the development of a high EGFRexpressing orthotopic tumor model with the cell line OSC-19-Luc2-copGFP. Other cell lines can be used that overexpress the epidermal growth factor receptor. The OSC cell line is established in Japan with cells of a patient with a

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squamous cell carcinoma of the tongue that metastasized to the cervical lymph nodes [14]. Luc2 luciferase from pGL4.10 plasmid (Promega, Madison, WI, USA) was cloned into the multiple cloning sites of the lentiviral vector pCDH-EF1MCS-T2A-copGFP (BioCat, Heidelberg, Germany) using specific primers with the corresponding restriction sites [4]. Then, OSC-19 cells were transduced by self-inactivating lentiviral vectors and positive cell clones selected by limited dilution to create a stable expression of luciferase 2 (luc2) and green fluorescent protein (GFP): the OSC-19-Luc2-copGFP cell line [4]. The recommended medium for this cell line is Dulbecco’s modified Eagle’s medium (DMEM). Take a flask of 500 mL DMEM (Invitrogen, Carlsbad, CA, USA) that contains 4.5 g D-glucose/L, 110 mg sodium pyruvate/L, and 580 mg L-glutamine/L. Supplement it with 10% fetal bovine serum (FCS, Lonza, Basel, Swiss), 100 IU/mL penicillin, 100 μg/mL streptomycin (Invitrogen), 1 minimal essential medium nonessential amino acid solution, and 1 MEM vitamin solution (Invitrogen) [4]. 2. If it is intended to perform fluorescence imaging to detect the photosensitizer, mice should be fed with a complete but chlorophyll-free diet or alfalfa diet, as a breakdown product of chlorophyll is fluorescent and can interfere with the fluorescence detection. 3. For general anesthesia during the experiments, place the mice in a chamber that is connected to a properly calibrated isoflurane vaporizer. Perform induction of isoflurane gas anesthesia by 4% isoflurane in oxygen with a flow of 0.8 L/min. During experiments, maintain anesthesia by 2% of isoflurane in oxygen with a flow of 0.8 L/min. 4. Each cell line has a different growth rate; thus the dilution made to keep the cell line in culture should be appropriate for each cell type. 5. Inspect the animals at least once a day as a routine inspection for emergencies as described in the “Code of Practice, Animal Experiments in Cancer Research.” Check the animals individually at least once a week. An animal should be euthanized when it loses 15% of body weight in a period of 1–2 days, when the tumor mass has become too large (i.e., it hampers normal behavior), when it causes clinical symptoms, when serious clinical symptoms are present, when the animal is no longer eating or drinking, when the behavior becomes seriously abnormal, or when the endpoint of the experiment has been reached.

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6. Because of the localization of the tumor, it is not recommended to follow these mice and their tumor growth for several days after the treatment. The enlargement of the tongue due to swelling or increase of tumor volume prevents normal eating and drinking; therefore we have decided to collect tissues for histological analyses. 7. Sacrifice mice by induction of 4% isoflurane gas anesthesia in oxygen with a flow of 0.8 L/min followed by cervical dislocation. Cervical dislocation requires technical skills, and alternatives like carbon dioxide or sodium pentobarbital are available. 8. Common protocols can be followed for H&E staining of either cryosections or paraffin-embedded sections. 9. It is advised to have two independent observers to analyze and quantify the necrosis.

Acknowledgments The work described here received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 677582). References 1. Moore LS, de Boer E, Warram JM et al (2016) Photoimmunotherapy of residual disease after incomplete surgical resection in head and neck cancer models. Cancer Med 5:1526–1534 2. Keereweer S, Mieog JS, Mol IM et al (2011) Detection of oral squamous cell carcinoma and cervical lymph node metastasis using activatable near-infrared fluorescence agents. Arch Otolaryngol Head Neck Surg 137:609–615 3. Keereweer S, Kerrebijn JD, Mol IM et al (2012) Optical imaging of oral squamous cell carcinoma and cervical lymph node metastasis. Head Neck 34:1002–1008 4. van Driel PB, van der Vorst JR, Verbeek FP et al (2014) Intraoperative fluorescence delineation of head and neck cancer with a fluorescent antiepidermal growth factor receptor nanobody. Int J Cancer 134:2663–2673 5. Hamers-Casterman C, Atarhouch T, Muyldermans S et al (1993) Naturally occurring antibodies devoid of light chains. Nature 363: 446–448 6. Heukers R, van Bergen en Henegouwen PM, Oliveira S (2014) Nanobody-photosensitizer conjugates for targeted photodynamic therapy. Nanomedicine 10:1441–1451

7. van Driel P, Boonstra MC, Slooter MD et al (2016) EGFR targeted nanobodyphotosensitizer conjugates for photodynamic therapy in a pre-clinical model of head and neck cancer. J Control Release 229:93–105 8. De Groof TWM, Mashayekhi V, Fan TS et al (2019) Nanobody-targeted photodynamic therapy selectively kills viral GPCR-expressing glioblastoma cells. Mol Pharm 16:3145–3156 9. Heukers R, Mashayekhi V, Ramirez-Escudero M et al (2019) VHH-photosensitizer conjugates for targeted photodynamic therapy of met-overexpressing tumor cells. Antibodies 8: 26 10. Driehuis E, Spelier S, Beltran Hernandez I et al (2019) Patient-derived head and neck cancer organoids recapitulate EGFR expression levels of respective tissues and are responsive to EGFR-targeted photodynamic therapy. J Clin Med 8:1880 11. Beltran Hernandez I, Angelier ML, Del Buono D’OT et al (2020) The potential of nanobodytargeted photodynamic therapy to trigger immune responses. Cancers (Basel) 12:978 12. de Bruijn HS, Mashayekhi V, Schreurs TJL et al (2020) Acute cellular and vascular responses to

Therapeutic Potential in an Orthotopic Head and Neck Cancer Model photodynamic therapy using EGFR-targeted nanobody-photosensitizer conjugates studied with intravital optical imaging and magnetic resonance imaging. Theranostics 10: 2436–2452 13. Deken MM, Kijanka MM, Beltran Hernandez I et al (2020) Nanobody-targeted photodynamic therapy induces significant tumor

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regression of trastuzumab-resistant HER2positive breast cancer, after a single treatment session. J Control Release 323:269–281 14. Yokoi T, Yamaguchi A, Odajima T et al (1988) Establishment and characterization of a human cell line derived from a squamous cell carcinoma of the tongue. Tumor Research 23: 43–58

Chapter 25 Assessment of the In Vivo Response to Nanobody-Targeted PDT Through Intravital Microscopy Henriette S. de Bruijn, Ann L. B. Seynhaeve, Timo L. M. ten Hagen, Sabrina Oliveira, and Dominic J. Robinson Abstract Methods that allow real-time, longitudinal, intravital detection of the fluorescence distribution and the cellular and vascular responses within tumor and normal tissue are important tools to obtain valuable information when investigating new photosensitizers and photodynamic therapy (PDT) responses. Intravital confocal microscopy using the dorsal skinfold chamber model gives the opportunity to visualize and determine the distribution of photosensitizers within tumor and normal tissue. Next to that, it also allows the visualization of the effect of treatment with respect to changes in vascular diameter and blood flow, vascular leakage, and tissue necrosis, in the first days post-illumination. Here, we describe the preparation of the skinfold chamber model and the intravital microscopy techniques involved, for a strategy we recently introduced, that is, the nanobody-targeted PDT. In this particular approach, photosensitizers are conjugated to nanobodies to target these specifically to cancer cells. Key words Intravital microscopy, Colocalization, Targeted photodynamic therapy, Vascular response

1

Introduction The response to photodynamic therapy (PDT) is the result of the formation of highly reactive singlet oxygen that has a short lifetime and therefore a limited diffusion range. Because of this, the tissue and cellular localization of a photosensitizer is an important parameter, as it determines the primary target of PDT. For example, PDT using a photosensitizer that localizes at the mitochondrial membrane will initially lead to mitochondrial damage, whereas a drug that localizes on the cellular membrane will initially lead to membrane damage. After the initial damage is inflicted, a cascade of secondary responses lead to cellular (e.g., apoptosis and/or necrosis), vascular (e.g., constriction, leakage, and/or stasis), and even immunological responses that eventually determine the PDT efficacy.

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_25, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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For any new (targeted) photosensitizer that shows potential in in vitro studies, it is crucial to investigate the drug distribution in tumor and normal tissue, in combination with the cellular and vascular responses to the treatment in vivo. Over the years this has been done in several ways using different techniques and various animal models [1–5]. Intravital microscopy (IVM) using a chamber model transplanted with a tumor provides real-time, longitudinal images to determine both the spatial distribution of the (targeted) photosensitizer in time after administration and the vascular and cellular responses to treatment. The advantage of IVM is that the dynamic processes of both drug distribution and treatment responses can be studied longitudinally in real time in the same animal. There are different approaches possible to aid colocalization image analysis, such as (a) labeling tumor cells with GFP, which enables the identification of single tumor cells; (b) employing transgenic mice with tissue-specific fluorescent cells, for example endothelial cells; or (c) administration of fluorescent blood marker to highlight the lumen of the blood vessels [6]. A range of observation chamber models, dorsal skin, brain, breast, and abdominal, are available in a variety of species, most often mice and rats, that can be used for this type of research. The choice of species, model, and tumor line will be determined by the characteristics of the photosensitizer under investigation. Although the animal model (mouse/rat, transgenic/ normal, type of observation chamber) and tumor line (GFP expressing or not) may be different, the intravital microscopy procedure will be similar. In this chapter, we describe IVM using a mouse dorsal skinfold chamber model transplanted with an oral squamous cell carcinoma overexpressing the epidermal growth factor receptor (EGFR) [7]. This setting was used to investigate an EGFR-targeted nanobody-photosensitizer conjugate, in a recently introduced approach [8]. This approach makes use of small antibody fragments derived from heavy-chain antibodies present in Camelids [9], and has shown encouraging results in an orthotopic model of oral squamous cell carcinoma, as it induced extensive tumor damage (80–90%), with minimal damage to surrounding normal tissues [10]. Interestingly, the small size of the nanobody leads to rapid distribution and clearance of the unbound fraction, allowing light activation 1 h postinjection of the conjugate. With IVM, the distribution of the nanobody-photosensitizer conjugate is investigated within tumor and normal tissue by recording fluorescence images using different magnifications at various time points after administration. Image analysis will result in a fluorescence kinetics curve for different tissue types. Colocalization analysis results in a correlation value for the photosensitizer fluorescence and the GFP signal of the tumor. PDT responses are investigated in the same model using IVM. For determination of changes in vascular architecture,

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transmission images are recorded up to a maximum of 2 days posttreatment using a low magnification. Vascular shutdown or leakage can be investigated at a specific time point post-PDT by administering a fluorescent blood marker that is large enough not to extravagate the tumor blood vessels, and performing fluorescence imaging and image analysis. Vascular shutdown is then shown by lack of fluorescence, and leakage is visualized by fluorescence outside the vasculature. Normal histology can be used at 2 days posttreatment, on harvested tissue, to evaluate tumor and normal tissue viability or necrosis.

2

Materials

2.1

Mice

SPF-free nude mice of 6 weeks or older and preferably above 18 g are used, as younger and/or lighter mice tend to have less skin. Mice should be fed a complete but chlorophyll-free diet as pheophorbide a, a breakdown product of chlorophyll, is fluorescent and will interfere with the detection of the fluorescence of the administered photosensitizer.

2.2

Tumor Cell Line

Tumor can be transplanted in the chamber either by injecting a cell suspension or by implanting a small piece of tissue, e.g., 1 mm3 tumor fragment (see Note 1). Choose a cell line that: 1. Expresses the target of interest. 2. Grows well in skin within 1–2 weeks. 3. Can be located in the chamber (e.g., fluorescent labeled). Here we use an EGFR-overexpressing human oral squamous cell carcinoma labeled with GFP.

2.3 Analgesia and Anesthesia Procedure

2.4 Equipment and Solutions for the Skinfold Chamber Operation

A NSAID’s painkiller is administered subcutaneously pre- and 24 h post-operation preventively (1 mg/kg rimadyl cattle). General anesthesia using isoflurane/O2 inhalation is used during operation and IVM imaging. Monitor breathing of the animal throughout the procedure and adjust isoflurane flow when needed. 1. Tumor cell suspension or material (which should be collected before starting the operation and maintained on ice). 2. Heating mattress set at 37
C. 3. Chlorhexidine (2%) in alcohol. 4. Eye ointment. 5. Saline (0.9% sterile NaCl solution). 6. Operation microscope (optional). 7. Marker.

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Fig. 1 Doral skinfold window chamber parts. Visible are the two frames (white), cover glasses, and filler glass. The retaining rings are thin and do not obscure the view area

8. Skinfold chamber parts as depicted in Fig. 1. Per assembly two window frames (made from PEEK), two pairs of bolds and nuts (aluminum, M1), two retaining rings, two circular cover glasses (nr 1, 0.016 mm thick and 12 mm in diameter), and a 10 mm diameter filler glass. All materials are autoclaved at 105
C for 90 min. 9. Surgical instruments including silk suture 4/0, 0.5 mL sterile insulin syringe, two 23G needles, scalpel holder + scalpel blade size 15, surgical forceps, surgical microscissors, clamping needle holder (or hemostatic forceps), micro screwdriver, and ear puncher (Fig. 2). All materials are purchased sterile or sterilized by autoclaving for 90 min at 121
C. 2.5 Equipment and Solutions for Intravital Microscopy

1. Confocal microscope equipped with a heating stage and isoflurane-anesthesia supply unit. The anesthetized animal is placed on the heated stage and, to prevent breathing artifacts while imaging, the chamber of the animal is bolted to a second frame that is then bolted to the heated stage. With this construction the animal can breathe freely while the chamber is fixed. An inverted as well as an upright microscope can be used. Here, we use a Zeiss LSM 510 META confocal microscope. 2. Nanobody-photosensitizer conjugate, in our case a conjugate as in [8, 10]. 3. Reference standards. 4. Saline (0.9% sterile NaCl solution). 5. Eye ointment.

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Fig. 2 Instrumentation used for the establishment of the dorsal skinfold window chamber. Parts are mentioned in the text

6. Sterile cotton swipes. 7. 0.5 mL Sterile insulin syringe. 8. Infrared heating lamp.

3 3.1

Methods Tumor Collection

3.2 Operation Procedure

A tumor is transplanted by injection of a cell suspension (see Note 1 for implanting a tumor fragment of 1 mm3). Tumor cell suspension is collected by harvesting cells grown in vitro. After incubation with trypsin and its inhibition, a single-cell suspension is resuspended in medium without serum at a concentration of 50,000 cells in 10 μL. Store on ice as short as possible. Perform the procedure under aseptic or sterile conditions (see Note 2). 1. Mice receive analgesia 1 h before the procedure (1 mg/kg rimadyl cattle, sc). 2. Mice are put under general inhalation anesthesia, placed on the heating mattress, and eyes receive eye ointment to prevent dehydration. 3. Clean the hairless skin with chlorhexidine in alcohol (see Note 3 for hair removal procedure in case a hairy mouse is used). 4. Mark the spinal cord, with a marker, as a folding line to ensure symmetrical placement of the chamber.

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5. Fold the dorsal skin, along the folding line, and find the area with clearly visible blood vessels roughly in the middle of the animal. Mark on one side the window part of the frame on the skin above those larger vessels and 2 mm below the folding line and mark the position of the bolds. 6. Use the ear punch to create the holes for the bolds. 7. Excise the dorsal skin within the marked area on one side of the fold, up to the fascia of the opposed skin using the scalpel, surgical microscissors, and forceps. 8. Place the frames with the bolds over the fold and place the screws on the bolds lightly. Pull the skin up 2 mm above the top of the frame and manipulate the tissue, so that the excised fascia area matches the window in the frame. Secure the skin at the top of the frame by putting the 23G needles through the little holes and tighten the screws on the bolds. Replace the 23G needles by sutures and repeat this for the other four sets of little holes in the frame. 9. Place the 10 mm filler glass at the back of the fold in the frame, put a 12 mm cover glass on top, and secure with a retaining ring. 10. Inject 10 μL tumor cell suspension superficially in the fascia/ subcutaneous musculature using a 0.5 mL insulin syringe. Bend the needle to allow easy approach of the tissue. Place the needle between the larger vessels preferably above the middle as superficial as possible. Avoid leaks and repositioning of the needle as spread of cells through the chamber easily occurs. See Note 1 on how to implant a tumor fragment. 11. Close the window using a 12 mm cover glass and secure it with a retaining ring. 12. Mice are housed solitaire in a climate cabinet set to 32
C and 70% humidity to avoid hypothermia and dehydration of the skin flap. Use cages and enrichment that allow unobstructed movement and access to food and water. 13. Regularly check the condition of the mice, tissue, and development of the tumor. 14. When the tumor shows signs of growth, IVM experiments can be started. 3.3

IVM

3.3.1 Imaging Photosensitizer Distribution

Using the fluorescence of the nanobody-photosensitizer, the intratumoral distribution of the compound can be monitored over time. Depending on the expected pharmacokinetics of the nanobodyphotosensitizer, the time points of interest are chosen (see Note 4). 1. Before the animal experiment starts, make sure that you record the reference standard and the dark current on a daily basis (see Note 5).

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2. Imaging is performed under general inhalation anesthesia, the mouse is fixed onto the heating stage, and eyes receive eye ointment to prevent dehydration. 3. Autofluorescence is recorded before administration of the drug under investigation. Choose the excitation and detection settings fitting with the fluorophores to be imaged. In this case, we used 488 nm excitation and 505–530 nm band-pass detection for the GFP signal of the tumor and 633 nm excitation and long-pass 650 nm detection for the nanobody-photosensitizer conjugate. 4. Image the entire chamber using a low magnification (25) to identify the tumor and normal tissue and choose the regions to image at a higher magnification (100 and 200). 5. Determine the time points at which the fluorescence should be recorded depending on the physical and chemical characteristics of the nanobody-photosensitizer (see Note 4). 6. Depending on how early is the first measurement time point after administration, the animal is either allowed to wake up after administration or injected on the microscopical stage while under anesthesia. 7. Administer the photosensitizer intravenously using a 0.5 insulin syringe. 8. Record fluorescence images at the specific time points of interest after administration of the drug and, depending on the time slots between these measurements, allow the animal to wake up every time. 9. Record corresponding transmission images to create overlays with the fluorescent images as represented in Fig. 3 to visualize blood vessels (transmitted image), tumor cells (in green), and intra-tumoral distribution of the photosensitizer (in red). 3.3.2 Imaging PDT-Induced Vascular Damage

To image the PDT-induced changes to the vascular architecture of the whole chamber, a similar approach is used. See above for steps 1–7. 1. Record fluorescence and transmission before illumination of the photosensitizer. 2. Perform illumination (using the proper laser, wavelength, fluence, and fluence rate), preferably on the microscopic table to minimize loss of time and regions of interest. 3. Record fluorescence and transmission after illumination at various time points after PDT using a low (25) magnification (see Note 6). To also detect tumor vascular leakage and/or flow, an extra step is introduced.

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Fig. 3 Examples of fluorescence and transmission images of a skinfold chamber transplanted with a GFP-expressing tumor recorded using different magnifications. (a) Transmission and GFP fluorescence image using 25x magnification and composed of 4 stitched images with clearly visible artery (a), venule (v), and tumor (t) tissue. Bar is 1000 μm. (b) Transmission and GFP fluorescence image using 100 magnification and composed of 4 stitched images. Bar is 200 μm. (c and d) Images collected 1 h after administration of a targeted nanobody-photosensitizer (7D12-9G8-PS [7]) using 200 magnification showing the transmission and GFP fluorescence (c) or GFP and targeted nanobody-photosensitizer fluorescence (d). Bar is 50 μm

4. A fluorescent blood marker is administered intravenously 2 h after illumination (see Note 7). 2 MDa tetramethylrhodamine dextran (1 mg/mL, 0.1 mg mouse) remains in the bloodstream for approximately 1 h and will extravagate into the tumor tissue at damaged sites. 5. Rhodamine is detected within 30 min after administration using 543 nm excitation and 560–615 nm band-pass detection. 3.4

Image Analysis

3.4.1 Determining the Fluorescence Kinetics Over Time in Regions of Interest

1. Use ImageJ to analyze the images and Excel to perform all the calculations. 2. Determine the dark current for every imaging setting. 3. Determine the fluorescence intensity of the reference standard for every imaging day.

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4. Subtract the reference fluorescence intensity with the corresponding dark current and normalize that to a constant value, preferably close to the mean. Calculate a reference correction factor (¼RF) for every imaging day to be used to correct every recorded skinfold chamber image. 5. Draw regions of interest (ROI) around anatomic sites of interest (tumor, normal adipose tissue, blood vessels) in the skinfold chamber images. Save the ROIs accordingly. Determine the fluorescence intensity and save this as raw data. 6. Subtract the raw fluorescence intensity of the ROIs with the corresponding dark current (recorded under the same imaging conditions). 7. Correct for the reference, dividing the fluorescence intensity by the RF. 8. The corrected fluorescence intensity of the individual ROIs can now be used to create the fluorescence kinetic curves. 3.4.2 Colocalization Analysis

As the tumor cells employed express GFP and the photosensitizer conjugated to the nanobodies emits red fluorescence, colocalization analysis can be performed to measure tumor cell-specific accumulation and/or compare different photosensitizers on their performance. The coloc2 plug-in in ImageJ implements and performs the pixel intensity correlation over space methods of Pearson, Manders, Costes, Li, and more. There are many nuances and pitfalls to colocalization analysis which are described extensively in literature [11–15]. It is highly dependent on the quality of the images taken, which is greatly determined by the quality of the chamber. Avoid fluorescence bleed-through, photobleaching, overexposure, saturation, and difference in intensities between images, as all these determine image quality and result in inferior colocalization analysis. 1. Subtract the dark current from the green and the red images to be analyzed on colocalization. 2. Use the colog2 plug-in. 3. Save both the PDF and the txt file containing the data. The file contains the results of all the mentioned colocalization methods. 4. Use the data applicable in your case to report or create figures.

3.4.3 Changes Vascular Architecture in the Chamber

Transmission images recorded with 488 nm light clearly show the vascular architecture while the green light is absorbed by the red blood. Changes in vascular diameter, as a result of constriction, can therefore be visualized and measured/scored. As under transmitted light using 488 nm red blood cells can be seen in the blood flow, vasoconstriction and/or dilatation can be recorded. Until now, it

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Table 1 Qualitative score for changes to the vascular architecture in the skinfold chamber treated with PDT Score

Description



No change in vascular architecture

+

Small changes in vascular lumen size, still flow visible by eye

++

Severe changes in vascular lumen of both the artery and venule, flow visible

+++

Severe changes in vascular lumen of both the artery and venule, no flow visible

Fig. 4 Example of changes in vascular diameter observed after PDT in the skinfold chamber transplanted with a GFP-expressing tumor (t). (a) Image recorded before PDT showing normal arterial (a) and venule (v) flow. (b) Image showing severe constriction of both venule and artery 2 h after PDT treatment using a targeted nanobody-photosensitizer conjugate [7]. Microscopy observation by eye should be used to determine if this is combined with stasis

has not been possible to use a plug-in that automatically determines the reduced absorption in case of severe constriction. Therefore, we score the severity of the vascular response qualitatively using a scoring table (Table 1, Fig. 4). 3.4.4 Vascular Flow and Leakage in Tumor

Images recorded within 30 min after administration of a blood marker that is large enough not to extravagate from the tumor bloodstream can be used to score for vascular flow and detect leakage. In Fig. 5, vasoconstriction, vascular leakage, and blood flow in the tumor and in the normal vasculature are shown. With respect to flow, it is likely that parts of tumor have different responses; that is, one area in the tumor can show lack of flow, whereas another part shows normal flow. Tumor vascular flow is determined by using the rhodamine fluorescence, GFP fluorescence, and 488 nm transmission image (see Fig. 5).

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Fig. 5 Example of vascular leakage or stasis observed after PDT in the skinfold chamber transplanted with a GFP-expressing tumor. Rhodamine-dextran 2000 kDa is administered 2 h after PDT and images were recorded within 30 min after administration [7]. (a) Transmission and GFP fluorescence of tumor area before PDT. (b) Transmission and GFP fluorescence of tumor area showing vasoconstriction of artery and irregular venule diameter and disturbed flow in tumor 2 h after PDT. C. GFP and blood marker fluorescence with vascular leakage (l) and areas that show reduced flow (r) or even no flow (no)

1. Train your eye by checking the control animals first: How many vessels are visible in the tumor? Keep this in mind as 100% flow. How much tumor tissue surrounds the vessel? What is the density of the vessels in the tumor? 2. In PDT-treated animals, draw a ROI over the tumor area using the GFP signal. 3. Qualitatively determine if all vessels visible in the transmission image also show rhodamine fluorescence. If so, there is 100% flow. 4. If there are areas that show lack of flow or partial flow, draw a region of interest around this tumor area and determine its proportional size. 5. This data can now be presented in a 100% stacked column graph. 6. With respect to leakage, leakage in tumor or in normal tissue is qualitatively judged and separately scored.

4

Notes 1. To induce the growth of a tumor in a chamber, as an alternative to cell suspension, a tumor fragment can be employed. For that, tumor tissue is harvested from a donor mouse. Procedure: Kill the donor animal and dissect the tumor. Cut pieces of 1 mm3 from the viable part of the tumor and place these in a petri dish with sterile saline on ice. The tumor of the donor mouse should be large enough for sufficient material while

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avoiding too large necrotic tumors. To transplant a tumor fragment, create a small pocket in the fascia by using a bent needle and insert the fragment with a microneedle holder. Importantly, tumor material to be transplanted should be collected and stored on ice as short as possible before the operation is started. 2. The skinfold chamber operation should be performed in an operation theatre with an operation microscope. Sterility, experience, proper tools, and instruments are important factors for success. All instruments, materials, and surfaces should be sterilized or cleaned thoroughly with alcohol. 3. When hairy mice are used, shave the back of the animals, apply hair removal gel to remove all hair from the follicles as these are highly autofluorescent, and remove the gel thoroughly. 4. Although it is tempting to keep the mouse on the microscope stage for hours and image the distribution of drugs continuously, prolonged exposure to anesthesia should be avoided as it may influence the distribution of drugs throughout the body. It is better to choose a number of time points at which the fluorescence should be recorded, to be able to create a good pharmacokinetic curve. In this respect, for fast clearing drugs, short intervals, within hours after administration, should be chosen, whereas for longer retaining drugs, intervals up to days after administration can be used. 5. To be able to compare the results of different animals and different experimental days, it is important to image a reference standard and the dark current on a daily basis. The dark current is the background level (offset) of the detector without any light. The dark current of each imaging setting is collected by repeating the image recording while the laser is off. As a reference standard we image a piece of colored glass that shows fluorescence for a specific imaging setting. 6. Vascular responses to PDT can occur very quickly after PDT. Record the change in vascular architecture immediately after treatment using transmission imaging with 488 nm light. Changes in vascular architecture can be monitored up to 2 days post-PDT. After that, the condition of the tissue in the chamber might not be acceptable and overestimation of the vascular effect is a concern. 7. Treatment-induced vascular leakage is a result of damage and/or death of endothelial cells which will take some time to occur. In our case we chose 2 h post-PDT to image vascular leakage.

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Acknowledgments The authors received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 677582). References 1. de Bruijn HS, Kruijt B, van der Ploeg-van den Heuvel A et al (2007) Increase in protoporphyrin IX after 5-aminolevulinic acid based photodynamic therapy is due to local re-synthesis. Photochem Photobiol Sci 6:857–864 2. Middelburg TA, de Bruijn HS, Tettero L et al (2013) Topical hexyl aminolevulinate and aminolevulinic acid photodynamic therapy: complete arteriole vasoconstriction occurs frequently and depends on protoporphyrin IX concentration in vessel wall. J Photochem Photobiol B 126:26–32 3. van Leeuwen-van Zaane F, van Driel PB, Gamm UA, et al (2014) Microscopic analysis of the localization of two chlorin-based photosensitizers in OSC19 tumors in the mouse oral cavity. Laser Surg Med 46:224–234 4. van der Veen N, van Leengoed HL, Star WM (1994) In vivo fluorescence kinetics and photodynamic therapy using 5-aminolaevulinic acid-induced porphyrin: increased damage after multiple irradiations. Br J Cancer 70: 867–872 5. van Leengoed E, Versteeg J, van der Veen N et al (1990) Tissue-localizing properties of some photosensitizers studied by in vivo fluorescence imaging. J Photochem Photobiol B 6: 111–119 6. Seynhaeve AL, Ten Hagen TL (2016) Highresolution Intravital microscopy of tumor angiogenesis. In: Ribatti D (ed) Tumor angiogenesis assays. Methods and protocols, 1464th edn. Humana Press, New York, pp 115–127 7. De Bruijn H, Mashayekhi V, Schreurs T et al (2020) Acute cellular and vascular responses to photodynamic therapy using EGFR-targeted nanobody-photosensitizer conjugates studied with intravital optical imaging and magnetic

resonance imaging. Theranostics 10: 2436–2452 8. Heukers R, van Bergen en Henegouwen PM, Oliveira S (2014) Nanobody-photosensitizer conjugates for targeted photodynamic therapy. Nanomedicine 10:1441–1451 9. Arbabi Ghahroudi M, Desmyter A, Wyns L et al (1997) Selection and identification of single domain antibody fragments from camel heavy-chain antibodies. FEBS Lett 414: 521–526 10. van Driel PBAA, Boonstra MC, Slooter M et al (2016) EGFR targeted nanobodyphotosensitizer conjugates for photodynamic therapy in a pre-clinical model of head and neck cancer. J Control Release 229:93–105 11. Dunn KW, Kamocka MM, McDonald JH (2011) A practical guide to evaluating colocalization in biological microscopy. Am J Physiol Cell Physiol 300:C723–C742 12. Bolte S, Cordelieres FP (2006) A guided tour into subcellular colocalization analysis in light microscopy. J Microsc 224:213–232 13. Li Q, Lau A, Morris TJ et al (2004) A syntaxin 1, Galpha(o), and N-type calcium channel complex at a presynaptic nerve terminal: analysis by quantitative immunocolocalization. J Neurosci 24:4070–4081 14. Costes SV, Daelemans D, Cho EH et al (2004) Automatic and quantitative measurement of protein-protein colocalization in live cells. Biophys J 86:3993–4003 15. Manders EMM, Verbeek FJ, Aten JA (1993) Measurement of co-localization of objects in dual-colour confocal images. J Microsc 169: 375–382

Chapter 26 Orthotopic Breast Cancer Model to Investigate the Therapeutic Efficacy of Nanobody-Targeted Photodynamic Therapy Marion M. Deken, Shadhvi S. Bhairosingh, Alexander L. Vahrmeijer, and Sabrina Oliveira Abstract Photodynamic therapy (PDT) is characterized by the local application of laser light, which activates a photosensitizer to lead to the formation of singlet oxygen and other toxic reactive oxygen species, to finally kill cells. Recently, photosensitizers have been conjugated to nanobodies to render PDT more selective to cancer cells. Nanobodies are the smallest naturally derived antibody fragments from heavy-chain antibodies that exist in animals of the Camelidae family. Indeed, we have shown that nanobody-targeted PDT can lead to extensive and selective tumor damage, and thus the subsequent step is to assess whether this damage can delay or even inhibit tumor growth in vivo. To evaluate the therapeutic efficacy of PDT, mouse models are mostly employed in which human tumors are grown subcutaneously in the flank of the animals. Although very useful, it has been suggested that these tumors are further away from their natural environment and that tumors developed in the organ or tissue of origin would be closer to the natural situation. Thus, this chapter describes the development of an orthotopic model of breast cancer and the application of nanobody-targeted PDT, for the assessment of the therapeutic efficacy. Key words Nanobody-photosensitizer, Targeted photodynamic therapy, Orthotopic breast cancer model

1

Introduction Photodynamic therapy (PDT) induces cell death through local light activation of a photosensitizer, which in the presence of oxygen leads to toxic reactive oxygen species [1]. Despite the local application of light, conventional photosensitizers are nonselective molecules, which leads to collateral damage to normal tissues. Recently, photosensitizers have been conjugated to nanobodies for targeted photodynamic therapy. Nanobodies are the smallest naturally derived antibody fragments from heavy-chain antibodies that exist in animals of the Camelidae family [2]. In vitro, these conjugates have shown to be very potent and selective [3–6]. In

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vivo, such conjugates accumulate rapidly at the tumor site enabling illumination within 1–2 h after intravenous injection [7–9]. In an orthotopic model of oral squamous cell carcinoma, nanobodyphotosensitizer conjugates targeting the epidermal growth factor receptor (EGFR) led to extensive tumor damage with minimal toxicity to the surrounding tissues [7]. Thus, subsequent research is focused on assessing whether the extensive damage observed 24 h post-nanobody-targeted PDT is sufficient to delay cancer growth or even able to inhibit tumor growth in vivo. One of these studies showed selective and significant regression of breast cancer tumors after a single treatment session [9]. To evaluate the therapeutic efficacy of PDT, mouse models are mostly employed in which human tumors are grown subcutaneously in the flank of the animals. This is because it facilitates both the application of PDT and the assessment of the response (through caliper measurements of tumor volume). For instance, a number of studies have been published in which photosensitizers have been targeted to the human epidermal growth factor receptor 2 (HER2) with antibodies, such as trastuzumab [10–12]. These studies investigated the growth inhibition in subcutaneous tumors at the flank of mice, as models of breast [10], gastric [11], or non-small cell lung cancer [12]. Although very useful, it has been suggested that the subcutaneous localization of such models is far away from their natural microenvironment. Thus, in the particular case of breast cancer, it has been advised to use orthotopic implantation of cancer cells directly into the mammary fat pad, under direct vision, to allow cancer cells to benefit from the microenvironment of the organ of origin [13, 14]. In this chapter, we describe an orthotopic model of breast cancer, used to investigate the therapeutic potential of PDT, with nanobody-photosensitizer conjugates, in the preclinical setting [9]. In this particular case, we refer to a model that overexpresses HER2, and thus the nanobody employed is specifically binding to HER2. In parallel, we described the similar procedure with a low HER2-expressing breast cancer cell line, to validate the specificity of the therapy. The photosensitizer employed is the IRDye700DX, which is a water-soluble silica-phthalocyanine derivative, that has been employed throughout our nanobody-targeted PDT studies [3–9, 15], and thus the settings employed for illumination (i.e., fluence and fluence rate) are the same [7–9]. The model described here is suitable for the development and evaluation of treatment of different breast cancers. Although this chapter is focused on nanobody-targeted PDT, the basic components of the PDT and illumination can be adapted to other photosensitizers or other types of conjugates.

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2.1

Mice

NU/NU nude female mice aged 4–6 weeks are used (e.g., from Charles River Laboratories, L’Arbresle, France). Mice should be housed for 1–2 weeks to acclimatize before experiments commence. Hold the mice in individually ventilated cages (e.g., Green Line IVC, Tecniplast, USA) with environmental enrichment like nesting material and provide them with autoclaved pallet food (e.g., RM3 diet, pelleted, Special Diets Services, UK, see Note 1) and sterilized water ad libitum.

2.2

Cell Lines

Different cell lines can be employed; here we report on the usage of HCC1954 and MCF7 cell lines, which were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA) (see Note 2).

2.3 Equipment and Solutions for the Inoculation of Cells Under Direct Vision and for Monitoring Tumor Growth

1. Tumor cell suspension or material (which should be collected before starting the operation and maintained on ice). 2. Chamber with calibrated isoflurane vaporizer. 3. Isoflurane gas (see Subheading 2.6). 4. Buprenorphine (see Subheading 2.6). 5. Electric heating pad. 6. Isoflurane face mask. 7. 0.5 mL Sterile insulin syringe (30G). 8. Sterile cotton swabs. 9. Alcohol. 10. Sterile surgical instruments including scissors, small anatomical forceps, and a clamping needle holder. 11. PDS resorbable suture (5-0, 17 mm). 12. Digital caliper.

2.4 Equipment for Photodynamic Therapy

1. Heat lamp. 2. Warm water bath. 3. Mouse restrainer. 4. 1 cc Syringe and 27-gauge needle or 0.5 mL insulin syringe (30G). 5. Dark room. 6. Chamber with calibrated isoflurane vaporizer. 7. Isoflurane gas (see Subheading 2.6). 8. Buprenorphine (see Subheading 2.6). 9. Electric heating pad.

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10. Eye ointment. 11. Nanobody-photosensitizer conjugates (see Subheading 2.5). 12. Electric heating pad. 13. Isoflurane face mask. 14. Anatomical forceps with curved tip. 15. Black paper. 16. Laser, optic fiber, and power meter (see Subheading 2.7). 2.5 NanobodyPhotosensitizer Conjugates 2.6

Medication

Here, HER2-targeted nanobodies conjugated to the photosensitizer IRDye700DX were prepared, as described in [9].

1. Isoflurane, for general anesthesia (see Note 3). 2. Ophthalmic ointment, to apply during anesthesia (e.g., LacriLube). 3. Painkiller: Before illumination administer the painkiller buprenorphine (0.05–0.1 mg/kg per 12 h) by subcutaneous injection.

2.7

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Laser

For illumination of the tumors in the mammary glands, we used a 690 nm laser (e.g., Modulight, Tampere, Finland) with the setting as in [9]. The power at the end of the optic fiber should be calibrated with a power meter (e.g., Gigahertz Optik, Tu¨rkenfeld, Germany).

Methods

3.1 Culturing Cell Line 3.1.1 Thawing Cryopreserved HCC1954 and MCF7 cells

1. If the HCC1954 or MCF7 cells are stored in liquid nitrogen, transport the vial from liquid nitrogen to the laboratory on dry ice. 2. Prior to thawing, open and close the screw cap slightly to release the pressure and allow the nitrogen to escape during thawing. 3. Thaw the vial with HCC1954 or MCF7 cells in a 37  C water bath until a small amount of ice remains. Use 70% ethanol to clean the outside of the vial to prevent contamination and transfer the suspension with a sterile Pasteur pipette into a 15 mL tube. Quick thawing is essential to preserve cell viability. 4. Dilute the HCC1954 or MCF7 cell suspension in cold culture medium described in Subheading 2.2; the first few mL should be added drop by drop.

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5. Transfer the 15 mL tube with HCC1954 or MCF7 cell suspension to a centrifuge and spin the cell suspension gently at 300  g for 5 min. 6. Carefully remove the supernatant without disturbing the pellet of cells. Resuspend the pellet in 6 mL of culture medium with a sterile pipette and place in a small T25 flask. 7. Place the flask in a 37  C, 5% CO2 incubator with the cap loosened to allow gaseous exchange to occur (or fully closed if the caps have a filter top). 8. Refresh medium the next day. 3.1.2 Culture HCC1954 or MCF7 cells

1. Take a T75 flask with HCC1954 or MCF7 cells from the 37  C, 5% CO2 incubator and remove culture medium with a sterile pipette. 2. Wash/rinse the adherent monolayer of HCC1954 or MCF7 cells with PBS twice to remove serum because trypsin is deactivated by serum. 3. Dispense 1 mL of trypsin-EDTA (0.05% trypsin/0.02% EDTA) in the flask and spread evenly over the bottom. Incubate for 2–5 min at 37  C until cells visibly detach and check detachment of cells under the microscope. 4. Resuspend cells in 10 mL of culture medium (contains FCS and therefore neutralizes trypsin) and add 0.5 mL to a new T75 flask. It is recommended to dilute cells 1:20 (see Note 4). 5. Add 14.5 mL of medium to the 0.5 mL cell suspension and put the flask in the 37  C, 5% CO2 incubator.

3.1.3 Preparing HCC1954 or MCF7 Cells for Inoculations in 30 μL PBS

1. Take a T75 flask that is 70–80% confluent with HCC1954 or MCF7 cells from the 37  C, 5% CO2 incubator. 2. To start harvesting cells, follow steps 2 and 3 from Subheading 3.1.2. 3. Resuspend cells in 10 mL culture medium and add the cell suspension to a 15 mL tube. 4. Count cells using a hemocytometer and microscope. Calculate the total amount of cells in the 10 mL suspension. Trypan blue staining can be used to exclude dead cells during counting. 5. Depending on the amount of mice that will be used in the experiment, take the correct volume of the MCF7 or HCC1954 cell suspension and pipette into a 15 mL tube. Place the tube in a centrifuge and spin cells down (300  g for 5 min). Remove the medium and resuspend the pellet of cells with the correct amount of PBS, so that 500,000 MCF7 cells or 3,000,000 HCC1954 cells are diluted in 30 μL PBS.

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3.2 Inoculation of Tumor Cells in the Mammary Fat Pad

1. During inoculation, mice need to be under general anesthesia. Bring the mice to a chamber that is connected to the calibrated isoflurane vaporizer (see Note 3). 2. When the mouse is under general anesthesia, perform a subcutaneous injection of buprenorphine (0.05–0.1 mg/kg per 12 h). 3. Because of the risk for hypothermia all experiments should be performed by using an electric heating pad or other supplemental heat during anesthesia. Place the mouse on an electric heating pad with isoflurane face mask. Adjust the anesthesia as suggested (see Note 3). 4. Monitor mice under anesthesia by looking at the respiratory rate and pattern, mucous membrane color, and toe pinch (to confirm the success of anesthesia). 5. Apply ophthalmic ointment on the eyes of the mice. 6. Clean the inguinal area using a cotton swab dipped into alcohol (or an alternative disinfectant). 7. Use the tip of a surgical scissor to make a small incision (preferably max 5 mm) between the fourth and fifth nipple (of the inguinal group), lateral of the midline. Make a small pocket by inserting closed forceps. 8. Use small anatomical forceps to expose the mammary fat pad (white color). Pull the mammary gland out to expose the fat pad (see Note 5). 9. The MCF7 or HCC1954 cells, diluted in 30 μL PBS, are aspirated from the vial that is prepared in Subheading 3.1.3 by using a 0.5 mL insulin syringe (30G). Make sure that cells are evenly distributed in the 30 μL PBS. 10. Inject the MCF7 or HCC1954 cells into the mammary gland. Initially the mammary tissue gets swollen, and then release the fat pad to its position. 11. Suture the incision by using a clamping needle holder and a PDS resorbable suture (5-0, 17 mm), with two tight knots (to prevent opening of the sutures). 12. After surgery watch the mice until they gain consciousness. After the mice are fully recovered, they are brought back to their cages. 13. Check the mice the following day, to see if the sutures are still present. If not, bring the mice under general anesthesia for new sutures (described as above).

3.3 Monitoring Mice and Tumor Growth

1. After the operation, inspect the animals once a day, as a routine inspection for emergencies (see Note 6).

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2. Assess tumor growth and animal welfare individually three times a week by inspection of behavior, weight measurement, visual inspection, and measurement of the tumor. Four to six weeks after inoculation, tumors grow to ~5–6 mm in diameter. 3. Visual inspection and measurement of the tumor have to be done under general anesthesia. Tumor diameter can be measured with digital calipers. Tumor volume (mm3) is measured with the formula length  width2 x 0.52 (see Note 7). 3.4 Photodynamic Therapy 3.4.1 Intravenous Injection of Nanobody-PS Conjugates

1. If tumors are visible by the human eye and the tumor measures around 100–130 mm3, photodynamic therapy can be applied. The tumor should not be larger than 130 mm3. 2. Place the cage with mice under a heat lamp to increase blood flow to the tail vein. 3. Prepare a warm water bath but do not exceed 45  C to prevent overheating. Test the temperature of the water by finger dipping before transporting the mouse. 4. Place the mouse into the restrainer. Put the tail of the mouse into the warm water bath for 1–2 min until the vein is expanding. 5. Use a 1 cc syringe and 27-gauge needle (or 0.5 mL insulin syringe, 30G) and hold the needle parallel to the tail vein with the bevel side up. Start the injection as distal as possible. When a second injection site is needed you can perform an injection more proximal than the first attempt. 6. Insert the needle into the vein. If the needle is correctly placed into the vein you can see the tip into the vein and injection of 100 μL will be easy without any resistance. Press the injection site for some time until bleeding has stopped.

3.4.2 Illumination

1. Illumination of the tumor must take place in a dark room. 2. Based on the quantitative fluorescence spectroscopy measurements, as performed in [7, 9], the time point for illumination should be determined, which in this study is 2 h postinjection of the conjugates. 3. During illumination of the tumor, mice need to be under general anesthesia. Bring the mice to a chamber that is connected to the calibrated isoflurane vaporizer (see Note 3). 4. Perform steps 2–5 as described under Subheading 3.2. 5. Pull the breast tumor using a small anatomical forceps with curved tip.

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6. Cover the rest of the body, except the breast tumor, with black paper to protect the animal from any scattering laser light (see Note 8). 7. Illuminate the tumor with the laser, at the appropriate fluence rate and for the desired fluence, here as described in [9]. 3.5 Follow-Up and Tumor Measurements

1. Visual inspection and measurement of the tumor have to be done under general anesthesia. Tumor diameter can be measured with digital calipers. Tumor volume (mm3) is measured with the formula length  width2  0.52 (see Note 7). 2. The follow-up is desirable for at least 30 days after PDT, or until the tumor reached the maximum size, mostly a maximum of 500 mm3 (see Note 9). Plots of tumor volume over time will then indicate the effect of the therapy on the tumor growth (i.e., slower growth or partial/complete regression), compared to the control group(s).

3.6 Histological Assessment Post-PDT

4

If of interest, sacrifice mice (see Note 10), collect the breast tumors and possible surrounding tissue, and freeze for cryosections or process for paraffin sections, for subsequent processing for histological analysis of the phototoxic effect.

Notes 1. If it is intended to perform fluorescence imaging to detect the photosensitizer, mice should be fed with a complete but chlorophyll-free diet or alfalfa diet, as a breakdown product of chlorophyll is fluorescent and can interfere with the fluorescence detection. 2. This chapter describes the development of a high HER2expressing model with the cell line HCC1954, though it is in fact advised to perform these studies with two models that vary in expression level of the target (e.g., high and low, where MCF7 can be used as low), in order to validate the selectivity of the therapy. The HCC1954 cell line is established with cells of a female patient with a ductal carcinoma (TNM stage IIA, grade 3) of the mammary gland. The low HER2-expressing cell line MCF7 is established in Detroit with cells of a Caucasian woman from metastases of adenocarcinoma of the breast. The recommended culture medium for the HCC1954 and MCF7 cell lines is Roswell Park Memorial Institute medium, RPMI 1640 (Thermo Fischer Scientific), supplemented with 10% FBS (fetal bovine serum, Gibco® by Life Technologies) and 1% penicillin-streptomycin (Gibco® by Life Technologies).

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3. For general anesthesia during the experiments, place the mice in a chamber that is connected to a properly calibrated isoflurane vaporizer. Perform induction of isoflurane gas anesthesia by 4% isoflurane in oxygen with a flow of 0.8 L/min. During experiments, maintain anesthesia by 2% of isoflurane in oxygen with a flow of 0.8 L/min. 4. Each cell line has a different growth rate; thus the dilution made to keep the cell line in culture should be appropriate for each cell type. 5. For more details on the inoculation of cells into the mammary fat pad, see [16, 17]. 6. Inspect the animals at least once a day, as a routine inspection for emergencies, as described in the “code of practice, animal experiments in cancer research.” Check the animals individually at least once a week. An animal should be euthanized when it loses 15% of body weight in a period of 1–2 days, when the tumor mass has become too large (i.e., it hampers normal behavior) or causes clinical symptoms, when serious clinical symptoms are present, when the animal is no longer eating or drinking, when the behavior becomes seriously abnormal, or when the endpoint of the experiment has been reached. 7. Other formulas can be used, if used for all tumor measurements. An example is (length  width  width)/2 or (length  width  height)/2. 8. Preferably cover the body with black paper, instead of aluminum foil. 9. Depending on the effect of PDT, the tumors can be assessed longer, up to 90 days, which is the period that is generally accepted to determine whether the mice are cured. 10. Sacrifice mice by induction of 4% isoflurane gas anesthesia in oxygen with a flow of 0.8 L/min followed by cervical dislocation. Cervical dislocation requires technical skills and alternatives like carbon dioxide or sodium pentobarbital are available.

Acknowledgment The authors received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 677582 and No. 323150).

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References 1. van Straten D, Mashayekhi V, de Bruijn HS et al (2017) Oncologic photodynamic therapy: basic principles, current clinical status and future directions. Cancers 9:19 2. Hamers-Casterman C, Atarhouch T, Muyldermans S et al (1993) Naturally occurring antibodies devoid of light chains. Nature 363: 446–448 3. Heukers R, van Bergen en Henegouwen PM, Oliveira S (2014) Nanobody-photosensitizer conjugates for targeted photodynamic therapy. Nanomedicine 10:1441–1451 4. De Groof TWM, Mashayekhi V, Fan TS et al (2019) Nanobody-targeted photodynamic therapy selectively kills viral GPCR-expressing glioblastoma cells. Mol Pharm 16:3145–3156 5. Driehuis E, Spelier S, Beltran Hernandez I et al (2019) Patient-derived head and neck cancer organoids recapitulate EGFR expression levels of respective tissues and are responsive to egfrtargeted photodynamic therapy. J Clin Med 8: 1880 6. Heukers R, Mashayekhi V, Ramirez-Escudero M et al (2019) VHH-photosensitizer conjugates for targeted photodynamic therapy of met-overexpressing tumor cells. Antibodies 8: 26 7. van Driel P, Boonstra MC, Slooter MD et al (2016) EGFR targeted nanobodyphotosensitizer conjugates for photodynamic therapy in a pre-clinical model of head and neck cancer. J Control Release 229:93–105 8. de Bruijn HS, Mashayekhi V, Schreurs TJL et al (2020) Acute cellular and vascular responses to photodynamic therapy using EGFR-targeted nanobody-photosensitizer conjugates studied with intravital optical imaging and magnetic resonance imaging. Theranostics 10: 2436–2452

9. Deken MM, Kijanka MM, Beltran Hernandez I et al (2020) Nanobody-targeted photodynamic therapy induces significant tumor regression of trastuzumab-resistant HER2positive breast cancer, after a single treatment session. J Control Release 323:269–281 10. Ito K, Mitsunaga M, Nishimura T et al (2017) Near-infrared photochemoimmunotherapy by photoactivatable bifunctional antibody-drug conjugates targeting human epidermal growth factor receptor 2 positive cancer. Bioconjug Chem 28:1458–1469 11. Korsak B, Almeida GM, Rocha S et al (2017) Porphyrin modified trastuzumab improves efficacy of HER2 targeted photodynamic therapy of gastric cancer. Int J Cancer 141:1478–1489 12. Sato K, Nagaya T, Choyke PL et al (2015) Near infrared photoimmunotherapy in the treatment of pleural disseminated NSCLC: preclinical experience. Theranostics 5:698–709 13. Talmadge JE, Singh RK, Fidler IJ et al (2007) Murine models to evaluate novel and conventional therapeutic strategies for cancer. Am J Pathol 170:793–804 14. Rashid OM, Takabe K (2015) Animal models for exploring the pharmacokinetics of breast cancer therapies. Expert Opin Drug Metab Toxicol 11:221–230 15. Beltran Hernandez I, Angelier ML, Del Buono D’OT et al (2020) The potential of nanobodytargeted photodynamic therapy to trigger immune responses. Cancers (Basel) 12:978 16. Kocaturk B, Versteeg HH (2015) Orthotopic injection of breast cancer cells into the mammary fat pad of mice to study tumor growth. J Vis Exp (96):51967 17. Tavera-Mendoza LE, Brown M (2017) A less invasive method for orthotopic injection of breast cancer cells into the mouse mammary gland. Lab Anim 51:85–88

Part IV Photodynamic Therapy-Induced Immune Signaling

Chapter 27 Evaluation of the Antitumor Immune Response Following Photofrin-Based PDT in Combination with the Epigenetic Agent 5-Aza-20 -Deoxycytidine Malgorzata Wachowska, Angelika Muchowicz, and Jakub Golab Abstract Photofrin-based photodynamic therapy (PDT) is approved for clinical use by the US Food and Drug Administration and the European Medicines Agency and is among the most widely used photosensitizer for the treatment of cancer. It was broadly reported that both the innate and the adaptive arms of immune response can be activated by PDT and play a critical role in the anticancer outcome of this treatment. PDT leads to the induction of acute local inflammation that includes leukocyte infiltration as well as increased activation and production of pro-inflammatory factors and cytokines. These events can lead to the development of systemic and specific antitumor immune response. Combining Photofrin-PDT with the epigenetic agent 5-aza-20 -deoxycytidine results in potentiated antitumor effects in vivo. Understanding the molecular mechanisms underlying this phenomenon would be invaluable for clinical development of this therapeutic approach. This chapter describes a detailed protocol allowing evaluation of specific antitumor immune response induced by PDT. Key words 5-Aza-20 -deoxycytidine, Antitumor immune response, Cancer, Flow cytometry, Photodynamic therapy (PDT), T-cell activation

1

Introduction A wide variety of studies underline the crucial role of the immune response in the therapeutic outcome of photodynamic therapy (PDT) [1–3]. PDT triggers the release from tumor cells of oxidatively modified antigens and damage- and death-associated molecules that play a role in the induction of inflammation [4, 5]. Subsequently, tumor antigens can be effectively presented to T cells by antigen-presenting cells leading to the activation of the adaptive arm of antitumor immune response. Importantly, in preclinical as well as in clinical studies the presence of lymphocytes in PDT-treated tumors was shown to be crucial for the therapeutic effects [1, 6, 7].

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The majority of tumors express antigens that can be presented by dendritic cells and recognized by T cells. The priming and activation of T cells lead to the development of CD8+ and CD4+ clones, specifically recognizing tumor cells, leading to tumor cell death either directly via perforin and granzyme attack or indirectly by the production of cytokines. Nevertheless, in most cases the antitumor immune response, also when induced with PDT, is insufficient to completely eliminate the tumor. The constant, long-lasting immune response may lead to immunoediting of tumor cells changing the expression of tumor-associated antigens (TAAs) or antigen-presenting machinery or is associated with the development of other tumor-escape mechanisms that interfere with the activity and function of T cells [8]. Epigenetic modulation and aberrant silencing of numerous genes encoding TAAs are among the most commonly observed molecular changes that occur in tumor cells [9]. Thus, modifying DNA methylation with 5-aza-20 -deoxycytidine (5-aza-dC), that restores the expression of silenced or downregulated TAAs [10], has been shown to enhance the efficacy of antitumor treatments, including immunotherapy with PDT [11]. The treatment combining suboptimal Photofrin-based PDT with 5-aza-dC results in complete tumor eradication and long-lasting survival of over 80% of mice (Fig. 1). One of the features of activated T cells is their ability to secrete interferon γ (IFN-γ). At the same time the cytotoxic activity of CD8+ T cells can be enhanced by the production of IL-17 by CD4+ T cells. Here we describe how to monitor the activation of adaptive immune response by examination of IFN-γ and IL-17 secretion from T cells with flow cytometry. To address the crucial role of T cells in the therapeutic outcome we describe the protocol for the elimination of T cells via anti-CD8- or anti-CD4-depleting antibodies and describe how to evaluate the antitumor activity of lymphocytes through the adoptive transfer of T cells isolated from tumor-free mice.

2 2.1

Materials Cell Culture

1. Epithelial mammary carcinoma (EMT6) cell line (American Type Culture Collection). 2. Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% heat-inactivated fetal bovine serum (FBS) and antibiotic/antimycotic solution. 3. Phosphate-buffered saline (PBS). 4. 0.25% Trypsin solution prepared from 2.5% trypsin (10). 5. Trypan blue solution.

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Fig. 1 5-Aza-20 -deoxycytidine (5-aza-dC) potentiates antitumor effect of photodynamic therapy in a murine tumor model. Mice were inoculated with 2  105 EMT6 cells. On days 1–3 mice were treated with 5-aza-dC (at a dose of 0.8 mg/kg). Photofrin was administered i.p. at a dose of 10 mg/kg on day 5, and 24 h later, the tumor site was illuminated with laser light at a fluence of 65 J/cm2. Left panels represent mean tumor volumes (SE) and right panels represent Kaplan–Meyer plots of the survival of mice bearing EMT6. *p < 0.05, compared with all other groups (Student’s t-test). #p < 0.05, compared with all other groups (log-rank test) 2.2 Tumor Implantation and Treatment

1. 8–12-Week-old BALB/c female mice with an average weight of 19 g. 2. 0.5 mL Tuberculin syringe with permanently attached 27 G needle (Becton Dickinson). 3. Micrometer steel caliper. 4. Photofrin (Axcan Pharma, Houdan, France) reconstituted in 5% glucose. 5. 5-Aza-dC (Sigma–Aldrich) dissolved in 0.9% NaCl. 6. Depleting antibodies: Anti-CD4 (GK1.5) and anti-CD8 (YTS169) and the isotype controls. 7. Light source: 630 nm He-Ne ion laser (Laser Instruments, Warsaw, Poland). 8. 0.22 μm Syringe filters.

2.3

Ex Vivo Studies

1. 70 μm BD Falcon cell strainers. 2. 2 mL Braun syringes. 3. Roswell Park Memorial Institute (RPMI 1640) medium with FBS. 4. Red blood cell lysis buffer: 150 mM NH4Cl, 1 mM NaHCO3, pH ¼ 7.4. 5. Phorbol 12-myristate 13-acetate (PMA) (Sigma–Aldrich). 6. Ionomycin (Sigma-Aldrich). 7. GolgiPlug (BD Biosciences). 8. CD8+ T cells Technologies).

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2.4 Staining and Flow Cytometry

1. Antibodies: α-CD4-PerCp-Cy5, α-CD8-FITC, α-IFN-γ-PE, α-IL-17-APC (BD Biosciences). 2. Cytofix/Cytoperm, perm/wash buffers (BD Biosciences). 3. BD FACSAria, Diva software (Becton Dickinson).

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Methods

3.1 Antitumor Photodynamic Therapy in Combination with 5-Aza-dC in EMT6 Tumor Model 3.1.1 Inoculation of Tumor Cells

1. Culture EMT6 cells in DMEM medium supplemented with 10% FBS and antibiotic/antimycotic solution in 75 cm2 culture flasks at 37  C in a humidified atmosphere composed of 95% air and 5% CO2 and passage every 2–3 days. 2. Check the cells for potential mycoplasma contamination (see Note 1). 3. On day 0 of the experiment wash the cells with PBS w/o Mg+2 and Ca+2 and harvest by 5-min trypsinization with 3 mL of 0.25% trypsin at 37  C. Inactivate trypsin with 3 mL of fully supplemented culture medium, pellet cells, and wash twice with PBS by centrifugation (300  g, 4 min, 4  C). 4. Suspend the cells in fresh PBS, verify the number and viability of tumor cells by trypan blue staining, and count the cells using a Bu¨rker chamber under a light microscope. Prepare cell suspension in PBS at a concentration of 1  107 cells/mL. Keep the cells on ice until inoculation into mice. 5. Anesthetize mice (8–9 mice per group) by intramuscular injection with ketamine (87 mg/kg) and xylazine (13 mg/kg). Place depilating cream on the right thigh of experimental mice. After 3–5 min remove the cream with damp cotton pad to remove hair. Be sure that the place of injection is properly dried out. 6. Inoculate 2  105 tumor cells in 30 μL of PBS subcutaneously into the shaved right thigh of BALB/c mouse using tuberculin syringe with permanently attached 27 G needle (Fig. 2) (see Note 2).

3.1.2 Tumor Treatment and Monitoring

1. Before 5-aza-dC administration, prepare a fresh working solution of the drug by diluting 8 mg/mL stock 100 in 0.9% NaCl (see Note 3). Filter-sterilize the solution. 2. On days 1–3 of experiment, inject mice intraperitoneally (i.p.) with 10 μL of 5-aza-dC per gram body weight and a dosage of 0.8 mg/kg. Inoculate control mice with the vehicle 0.9% NaCl. 3. On day 5 administer Photofrin (1 mg/mL in 5% glucose) i.p. at a dose of 10 mg/kg (10 μL per gram body weight). Inoculate control mice with a sterile 5% glucose solution (see Note 4).

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Fig. 2 EMT6 thigh tumor model. 2  105 of EMT6 tumor cells were inoculated into the right thigh of BALB/c mouse. Picture shows the tumor of control mouse 10 days after inoculation

4. Twenty-four hours later, anesthetize mice and restrain during the time of PDT procedure. Illuminate tumors with 630 nm light delivered by laser through the optical fiber. The power of the laser should be set to 40–50 mW/cm2, the spot diameter should be 1.6 cm, and the total fluence should be 65 J/cm2 (see Note 5). 5. Start to monitor tumor growth on day 4 when all mice develop tumors with a minimum size of 3  4 mm in diameter and continue to measure three times per week with a caliper. Determine tumor growth by the formula tumor volume (mm3) ¼ (longer diameter)  (shorter diameter)2. Sacrifice mice when the tumor diameter reaches 1500 mm3. 3.2 Analysis of Activation of Antitumor Immune Response 3.2.1 Isolation of Murine Cells

3.2.2 Ex Vivo Cell Stimulation

1. Two weeks after PDT (see Note 5), sacrifice tumor-bearing mice, immobilize, cut the skin without disruption of the peritoneum, gently isolate tumor-draining lymph nodes (popliteal, inguinal, axillary, brachial), and then cut the peritoneum to collect spleen (see Note 6). Place harvested organs in tubes filled with ice-cold PBS and keep them on ice. 2. To obtain single-cell suspension, force the spleens and lymph nodes through a 70 μm cell strainer using a syringe plunger (see Note 7). Pellet the cells by centrifugation (300  g, 4 min, 4  C), suspend in red blood cell lysis buffer, and incubate for 5 min on ice in order to lyse erythrocytes. Next, wash the cells and suspend in RPMI 1640 medium supplemented with 10% FBS. 1. Count cells in a Bu¨rker chamber and seed equal number (2  106) of cells into a 96-well plate in RPMI supplemented with 10% FBS and antibiotic/antimycotic solution. 2. Incubate the plate for 6 h at 37  C in a humidified atmosphere of 95% air and 5% CO2 with 10 ng/mL phorbol 12-myristate 13-acetate (PMA) and ionomycin at a concentration of 2 mg/ mL.

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3. Add GolgiPlug for the last 4 h of culture. 4. After the time of incubation transfer the plate to 4  C. 5. Next day, wash the cells with PBS by centrifugation of the plate (300  g, 5 min, 4  C) and stain cells for surface markers using anti-CD4 conjugated with PerCp-Cy5 and anti-CD8 coupled with FITC-conjugated monoclonal antibodies for 20 min at room temperature in the dark (see Note 8). 6. Fix and permeabilize the cells using Cytofix/Cytoperm perm/ wash buffers according to the manufacturer’s instructions. 7. For intracellular staining use anti-interferon-γ (IFN-γ) conjugated with PE and anti-interleukin 17 (IL-17) coupled to APC antibodies, and incubate for 20 min at room temperature in the dark (see Note 9). 8. Wash cells with perm/wash buffer and suspend in FACS Flow. 9. Analyze on cytometer (BD FACSAria using Diva software) (Fig. 3).

Fig. 3 Gating strategy and representative results of intracellular levels of interferon-γ (IFN-γ) in CD8+ T cells and IL-17 levels in CD4+ T cells isolated from LNs of all experimental groups assessed by flow cytometry

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Fig. 4 Scheme illustrating the course of the PDT experiment with lymphocyte depletion 3.2.3 Lymphocyte Depletion

1. On day 0, inoculate 2  105 tumor cells subcutaneously into the right thigh of experimental mice (Fig. 4). 2. On days 1-3 subject mice to treatment with 0.8 mg/kg 5-aza-dC. 3. On day 5 administer 10 mg/kg of Photofrin i.p. and 100 μg of anti-CD4 (GK1.5) and anti-CD8 (YTS169) antibodies. Inoculate control mice with 100 μg of isotype control antibodies. 4. On day 6 perform PDT as described in Subheading 3.1.2. 5. On day 7, after 48 h evaluate the efficiency of lymphocyte depletion. Collect ~50 μL of blood from cheek vein, by punching with thick needle, to heparinized tubes. Stain 20–50 μL of blood with anti-CD4 and anti-CD8 antibodies for 20 min at RT in the dark. Lyse red blood cells with lysis buffer as described in Subheading 3.2.1. Analyze cells by flow cytometry. Efficiency of depletion should be around 99%. 6. Next administration of depleting antibodies is performed on the 11th and 18th days. Always evaluate depletion efficiency after 48 h.

3.2.4 Adoptive Transfer

1. Three days before adoptive transfer, inoculate mice subcutaneously with 1  105 EMT6 cells into the right thigh, and treat with 5-aza-dC for 3 days (Fig. 5). 2. For adoptive transfer experiment use naı¨ve and cured mice (PDT and 5-aza-dC treated) that survived without tumors for over 90 days. Harvest lymph nodes and spleen of naı¨ve or longterm surviving mice and isolate cells as described in Subheading 3.2.1 3. Subsequently, combine all cells from the non-treated and treated groups, respectively, and magnetically purify CD8+ T cells by negative selection. Determine the efficiency of selection by staining 1  105 cells with anti-CD3-PerCp and anti-CD8FITC antibodies and analyze by flow cytometry. Effectiveness should reach ~98%.

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Fig. 5 The evaluation of the antitumor activity of CD8+ lymphocytes, isolated from naı¨ve or cured mice treated with PDT and 5-aza-dC. After spleen and lymph node harvest the CD8+ T cells were magnetically purified and injected into tumor-bearing mice. Next, antitumor activity of transferred lymphocytes was estimated by tumor growth monitoring

4. Then, immediately transfer 5–10  106 of CD8+ T cells into BALB/c tumor-bearing mice by intravenous (i.v.) injection. Monitor tumor growth three times a week as described in Subheading 3.1.2.

4

Notes 1. Use only mycoplasma-free cells. Contamination with mycoplasma can impede tumor growth and increase its immunogenicity leading to tumor rejection or lack of reproducibility. To check the cells for mycoplasma contamination, a sensitive PCR-based test can be used. 2. The viability of the cells must be above 95%. As the diameter of the needle attached to the syringe is very small, mix the cell suspension with automatic pipette in order to avoid mortality of the cells that can affect the tumor growth. Keep tumor cells on ice and inject them as fast as possible. 3. Always store aliquoted stock solution of 5-aza-dC at 80  C and use it only once; do not freeze-thaw as this drug is very unstable. 4. Avoid long-term storage or freeze-thaw cycles of photosensitizer; it may affect its efficacy. The photosensitizer should be protected from light at all times. 5. During the PDT procedure it is crucial to place the tumor in the center of the illumination area and perpendicularly to the light source. Be sure that mice will be anesthetized and stay stable during the whole procedure.

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6. To investigate T-cell activation post-PDT, the day of harvest and flow cytometric analysis must be chosen carefully. The optimizing experiments are needed for each experimental model. According to our experience the T-cell activity can be successfully measured between 10th and 14th days after PDT. 7. It is important to be careful during searching and collection of lymph nodes without any damage to the surrounding blood vessels. Blood leakage renders the procedure much more difficult. 8. As the spleen is a very fragile organ, do not press very hard to the syringe plunger. Rather, cut it into a few pieces and very gently force it through the strainer in order to avoid increased mortality of the splenocytes. 9. For flow cytometry analysis, in order to avoid nonspecific binding of antibodies to the cell’s FcR receptors, dilute antibodies in a staining buffer containing anti-CD16 antibodies or 5% rat serum. It is also recommended to use the viability dye that allows to reject the nonspecifically stained dead cells.

Acknowledgment The work of the authors was supported by a grant from the PolishSwiss Research Program (PSPB-057/2010) and Regional Initiative for Excellence (013/RID/2018/19) from the Polish Ministry of Education and Science, project budget 12,000,000 PLN. References 1. Korbelik M, Krosl G, Krosl J et al (1996) The role of host lymphoid populations in the response of mouse EMT6 tumor to photodynamic therapy. Cancer Res 56:5647–5652 2. Korbelik M (2006) PDT-associated host response and its role in the therapy outcome. Lasers Surg Med 38:500–508 3. Nowis D, Stoklosa T, Legat M et al (2005) The influence of photodynamic therapy on the immune response. Photodiagnosis Photodyn Ther 2:283–298 4. Garg AD, Nowis D, Golab J et al (2010) Immunogenic cell death, DAMPs and anticancer therapeutics: an emerging amalgamation. Biochim Biophys Acta 1805:53–71 5. Firczuk M, Nowis D, Golab J (2011) PDT-induced inflammatory and host responses. Photochem Photobiol Sci 10: 653–663 6. Agostinis P, Berg K, Cengel KA et al (2011) Photodynamic therapy of cancer: an update. CA Cancer J Clin 61:250–281 7. Thong PS, Ong KW, Goh NS et al (2007) Photodynamic-therapy-activated immune

response against distant untreated tumours in recurrent angiosarcoma. Lancet Oncol 8: 950–952 8. Schreiber RD, Old LJ, Smyth MJ (2011) Cancer immunoediting: integrating immunity’s roles in cancer suppression and promotion. Science 331:1565–1570 9. Campoli M, Ferrone S (2008) HLA antigen changes in malignant cells: epigenetic mechanisms and biologic significance. Oncogene 27: 5869–5885 10. Serrano A, Tanzarella S, Lionello I et al (2001) Re-expression of HLA class I antigens and restoration of antigen-specific CTL response in melanoma cells following 5-aza-20 -deoxycytidine treatment. Int J Cancer 94: 243–251 11. Wachowska M, Gabrysiak M, Muchowicz A et al (2014) 5-Aza-20 -deoxycytidine potentiates antitumour immune response induced by photodynamic therapy. Eur J Cancer 50: 1370–1381

Chapter 28 Controlling Immunoregulatory Cell Activity for Effective Photodynamic Therapy of Cancer Mladen Korbelik, Zdzislaw M. Szulc, Alicja Bielawska, and Duska Separovic Abstract Recently, it has become clear that a prerequisite requirement for most cancer therapies is controlling the negative impact of the activity of immunosuppressory cell populations. It is therefore of a considerable interest to develop treatments for containing the operation of major myeloid and lymphoid immunoregulatory cell populations. We have reported that acid ceramidase inhibitor LCL521 effectively overrides the activity of immunoregulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs) engaged in the context of tumor response to photodynamic therapy (PDT). The present communication dissects and describes in detail the procedure for the use of LCL521 as an adjuvant to PDT for improved cure rates of treated tumors based on restricting the activity of immunoregulatory cell populations. Key words Photodynamic therapy, Immunoregulatory cell populations, LCL521, Ceramidase, Tumor response

1

Introduction Controlling the tumor-promoting activity of immunosuppressory elements, dominated by immunoregulatory cell populations and negative checkpoint regulators, emerges as an imperative requirement for the clinical success of not only various cancer immunotherapies but also most of the other cancer therapies [1– 4]. The greatest potential for a successful realization of such control is to target the activity of immunoregulatory cells as they also exert influence over immune checkpoint resistance [5]. A number of agents have been shown to be effective in restricting the activity of either regulatory T cells (Tregs) or myeloid-derived suppressor cells (Mregs), which are two major immunoregulatory cell populations [6, 7]. However, there is a dearth of candidates targeting both these cell types [8, 9]. Recently, we reported that lysosomotropic acid ceramidase inhibitor LCL521 has the capacity to restrict the activity of both Tregs and Mregs [10, 11]. The induction of MDSC

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_28, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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cell death by LCL521 has also been reported [12]. Acid ceramidase is one of the key enzymes in sphingolipid metabolism [13]. By hydrolyzing ceramide into sphingosine and free fatty acids, it controls the levels of principal bioactive species of the sphingolipid superfamily. Ceramide is one of the chief intracellular promoters of apoptosis, whereas the immediate metabolite of sphingosine, sphingosine-1-phosphate (S1P), delivers cell pro-survival signals, stimulates inflammation, controls angiogenesis, and promotes activity of immunoregulatory cells [14, 15]. A sharp decline in acid ceramidase activity induced by LCL521 causes almost complete elimination of cellular sphingosine and a decrease in S1P paralleled with an increase in ceramide levels [16, 17]. Crucial participation of ceramide and S1P in many biological functions is facilitated by their roles as signal transduction molecules [18, 19]. Importantly, they were shown to have opposing impacts on PI3K/Akt/mTOR pathway; while ceramide effects are inhibitory, S1P was found to activate this pathway through its receptors [20]. The Akt/mTOR signaling is now established as crucial for the function of both Tregs (depending on the ceramide-promoting activity of protein phosphatases 2A (PP2A)) [21, 22] and Mregs (through mTOR-dependent transcription factor C/EBPß activation) [5, 23]. Thus LCL521-mediated attenuation of Treg and Mreg activity appears to be mediated through interfering with the induction of ER stress by elevated levels of ceramide and dampening Akt/mTOR signaling pathway [24]. Photodynamic therapy (PDT) is an oxidative stress-inflicting treatment mediated by light-activated photosensitizing drugs that is clinically established for the destruction of various solid tumors [25]. Survival of PDT-treated tumor cells as well as the expression of PDT-induced antitumor immune response is governed by the activity of the engaged stress-signaling networks [26]. This includes the stress response-mediated control of the activity of MDSCs and Tregs [2]. These populations were found to be at least transiently elevated following treatment of various tumors by PDT or PDT-generated vaccines [10, 27–30]. Importantly, the same studies also showed that procedures for selective depletion of these immunosuppressory populations improve the therapeutic efficacy of PDT and PDT vaccines for controlling treated tumors. This chapter provides the experimental details showing how LCL521 can be used in conjunction to temoporfin-based PDT for the treatment of mouse SCCVII tumors. Compared to PDT-alone group, a single LCL521 administration after PDT light treatment significantly reduced tumor recurrences and resulted in a marked increase in the cure rates of these tumors [10]. It will also be shown how to monitor the levels of MDSC and Treg populations in mice undergoing tumor therapy based on PDT with adjuvant LCL521.

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Materials

2.1 Treatment of SCCVII Tumors by Temoporfin-PDT Plus Adjuvant LCL521

1. C3H/HeN female mice, 7–9 weeks old (Simonsen Laboratories Inc., Gilroy, CA). 2. Surgical scalpel blade size 22 (Feather Safety Razor Co., Osaka, Japan) plus stainless scalpel handle #4L (Lipshaw, Stainless Pakistan, Karachi, Pakistan). ˝mbrecht, 3. Tissue culture dishes 60 Cell+ (Sarstedt, Nu Germany). 4. Freshly aseptically excised tissue of squamous cell carcinoma SCCVII tumors syngeneic to C3H/HeN mice [31], which is an established model for head and neck cancer [32]. 5. Enzyme solutions for tumor tissue disaggregation: 4 mg/mL collagenase type IV (Sigma-Aldrich Co, St. Louis, MO), 3 mg/ mL dispase (Boehringer, Mannheim, Germany), 10 mg/mL DNase type I (Sigma). 6. Phosphate-buffered saline (PBS): 8 g NaCl, 0.2 g KCl, 1.44 g Na2HPO4
12H2O, and 0.24 g KH2PO4 in 1 L of doubledistilled water (pH adjusted to 7.4). 7. Cell strainer, 100 μm nylon (Falcon, Corning Inc., Durham, NC). 8. In-house-constructed plexiglass holder for immobilizing mice during tumor inoculation. 9. Precision Glide Needles (20G1) and 1 mL Tuberculin Slip Tip Syringes, both form Becton Dickinson. 10. Temoporfin (Foscan) provided by Biolitec Research GmbH (Jena, Germany). 11. PDT light source: FB-QTH-3 high-throughput illuminator (Sciencetech Inc., London, Ontario, Canada) equipped with a 150 W QTH lamp and 650  10 nm interference filter; the light is delivered through an 8 mm core diameter liquid light guide (model 77638, Oriel Instruments, Stratford, CT). 12. LCL521 solution, 15 mg/mL in PBS: This compound, (1R,2R)-1-(40 -nitrophenyl)-2-N-(tetradecanoylamino)propyl-1,3-O-di(N,N-dimethylamino)acetate dihydrochloride, was synthesized by Lipidomics Shared Resource, Synthetic Unit, Medical University of South Carolina: http:// www.hollingscancercenter.org/research/shared-resources/ lipidomics/index.html[16].

2.2 Monitoring the Levels of MDSCs and Tregs

1. Fresh aseptically extracted spleens and inguinal lymph nodes, typically collected at 72 h after therapy from mice bearing SCCVII tumors. 2. Erythrocyte lysis buffer: 8.3 mg/mL Ammonium chloride, 1 mg/mL sodium bicarbonate, and 0.1 mM ethylenediaminetetraacetic acid (EDTA).

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3. Antibody staining buffer: Hanks’ balanced salt solution (Gibco, Thermo Fisher Scientific, Ottawa, Ontario, Canada) supplemented with 0.1% bovine serum albumin and containing sodium azide (0.02%). 4. Cytofix/Cytoperm fixation/permeabilization (BD Biosciences, San Jose, CA).

kit

5. Fc block: Supernatants of HB-197 hybridoma (clone 2.4G2) containing 1 mg/mL of rat anti-mouse IgG2b binding specifically mouse Fcγ receptors (FcγIII and FcγII), which prevents binding of other antibodies to these receptors (reducing background staining). 6. Fluorophore-conjugated antibodies for flow cytometry: Phycoerythrin-cyanine 5-conjugated rat anti-mouse Ly-6G (GR1, clone RB6-8C5) and Alexa Fluor 488-conjugated rat anti-mouse Ly-6C (clone HK1.4), both from eBioscience (San Diego, CA); phycoerythrin-conjugated mouse anti-mouse CD11b (Mac-1α, clone 2LPM19c) from Santa Cruz Biotechnology (Dallas, TX); fluorescein isothiocyanate-conjugated rat anti-mouse CD4 (clone RM4-5, eBioscience); phycoerythrincyanine 5-conjugated rat anti-mouse CD25 (clone PC61.5, eBioscience); and phycoerythrin-conjugated rat anti-mouse Foxp3 (clone FJK-16s, eBioscience). 7. Flow cytometer: Coulter Epics Elite ESP (Coulter Electronics, Hialeah, FL).

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Methods

3.1 Tumor Implantation, PDT  LCL521 Treatment and Tumor Response Assessment

1. Cohorts of 6–8-week-old C3H/HeN mice (at least 6 for each of the planned treatment groups) are implanted tumors by subcutaneous injection of 2
106 SCCVII cells (50 μL, suspended in PBS) into depilated sacral dorsal region (lower backs). For obtaining the tumor cell suspension, the SCCVII tumor tissue placed in a 6 cm diameter Petri dish is minced until it becomes a fine paste by chopping using surgical scalpels. Next, PBS is added at 5
volume ratio (e.g., 1 mL PBS per 0.2 g tissue). The tumor tissue is then digested into single-cell suspension by adding 0.3 mL of enzyme cocktail for every 5 mL of tumor-PBS suspension followed by shaking and incubating at 37  C for 30 min. After filtering through a 100 μm nylon cell strainer, the tumor cell suspension is (after counting on hemocytometer) adjusted for injection to 4
107 cells/mL (see Note 1). 2. The mice are not anesthetized during tumor inoculation but immobilized using in-house-constructed plexiglass holder.

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3. The mice are randomized into three treatment groups (PDT alone, LCL521 alone, and PDT plus LCL521) approximately one week after implantation when their tumors reach 6–8 mm in largest diameter. The mice from PDT groups are first administered temoporfin 0.1 mg/kg by intraperitoneal injection. The injection solution is prepared by dissolving the photosensitizer in a solvent mixture (ethanol:polyethelene glycol400: water 2:3:5) for a primary stock solution of 2 mg/mL. This is diluted 100 times in PBS for injecting 0.1 mL volume per 20 g body weight. The mice are afterwards kept away from a direct strong light for one week to prevent photosensitizer photosensitivity reactions in normal tissues. 4. For photodynamic light treatment of tumors, the mice are, 24 h after the photosensitizer administration, restrained unanesthetized in lead holders leaving their lower backs with tumors exposed. The tumors are exposed to superficial illumination by a monodirectional perpendicular beam from the tip of the light guide with the distance adjusted to obtain the spot size encompassing the tumor and 1–1.5 mm of the surrounding skin. The illumination fluence rate is kept in the 80–90 mW/cm2 range. 5. Light exposure time of tumors is calculated by multiplying the ratio between light-spot surface area (cm2) and power output (J/s) with the desired light dose of 80 J/cm2. 6. The treatment with LCL521 (75 mg/kg i.p.) is performed immediately after photodynamic light treatment. A control group of tumor-bearing mice receives the same LCL521 treatment without PDT. 7. After PDT  LCL521 light treatment, the tumors typically become impalpable within 1–2 days. For posttreatment observation, the mice are inspected three times per week for signs of tumor regrowth. In case of recurrence, the mice are euthanized typically when their tumors reach 10 mm in largest diameter. No sign of tumor recurrence at 90 days post-PDT qualifies as a tumor cure (see Note 2). 8. Statistical analysis of the results is performed using log-rank test with the significance threshold for the difference in tumor response between treatment groups set at 5%. 3.2 Determination of MDSC and Treg Levels in Mice Following Tumor PDT Treatment with or Without Adjuvant LCL521

1. The spleen cell suspension is obtained by tearing apart the spleen tissue with a forceps and flat-held scalpel blade in a Petri dish [33]. After adding 2 mL PBS, the suspension is collected and filtered through a 100 μm nylon cell strainer. The erythrocytes present in the suspension are removed by 15-min incubation in an ice-cold lysis buffer. A similar procedure is used with the lymph nodes, except that the erythrocyte lysis is not needed.

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2. Antibody staining of splenocytes or lymph node cells for flow cytometry analysis is performed using standard protocols [33]. The procedure calls for a 3-min Fc-block exposure followed by incubating the cell suspensions for 30 min on ice in antibody staining buffer with antibodies at dilutions specified by the manufacturers. During all staining steps the cell samples were kept in subdued light. 3. For monitoring MDSC levels in mice, these cells are broadly identified in spleen samples by positive staining with CD11b and GR1 antibodies. Additionally, using anti-mouse Ly6C antibody they can be further subdivided into monocytic (CD11b+GR1+Ly6Chigh) and granulocytic (CD11b+GR1+ + Ly6Clow) subsets [34]. 4. For monitoring Treg levels in mice, these cells are identified in cell suspensions from tumor-draining lymph nodes by positive staining with antibodies raised against mouse antigens CD4, CD25, and Foxp3. Unlike the first two antigens that are exposed on the surface of cells, the transcription factor Foxp3 is localized inside the cells and its detection requires intracellular staining. For this purpose the cells are, after the surface staining for CD4 and CD25, fixed and permeabilized using Cytofix/Cytoperm solution. After incubating them for 20 min at 4  C in the fixation/permeabilization solution, the cells are resuspended in perm/wash buffer (from Cytofix/Cytoperm kit) containing phycoerythrin-conjugated anti-mouse Foxp3 antibody and incubated for 30 min at 4  C. 5. For flow cytometry analysis, at least 10,000 cells are analyzed for each sample employing standard controls and routines for eliminating nonspecific staining, dead cells, and debris (see Notes 3 and 4).

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Notes 1. The experimental procedures with mice are performed with the approval of the Animal Care Committee of the University of British Columbia. 2. The published results of the experiment described in Subheading 3.1 show that, compared to PDT alone, combining LCL521 with PDT results in a significant improvement in tumor cures [10]. The LCL521 treatment alone produces no tumor cures. 3. An alternate method for monitoring Treg activity is based on determining the expression of Foxp3 and Bach2 genes as they encode signature transcription factors identifying these cells [10, 35, 36].

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Fig. 1 LCL521 alters PDT vaccine-induced immunoregulatory cell activity. Mice with SCCVII tumors were treated by PDT vaccine and/or LCL521 (75 mg/kg i.p.) as described in detail elsewhere [10], and were sacrificed 72 h later. Spleens and tumor-draining lymph nodes were disaggregated into single-cell suspensions that were stained with fluorophore-conjugated antibodies for flow cytometry-based identification of Tregs and MDSCs (CD4+CD25+Foxp3+ and CD11b+GR1+, respectively). The columns depict absolute numbers of MDSCs per spleen or Tregs per lymph node obtained with treatment groups consisting each of 4 mice. Statistically significant difference ( p < 0.05): ωuntreated tumors vs. tumor-free group, *vaccine alone vs. untreated tumor group, **vaccine plus LCL521 vs. vaccine-alone group. LCL521-alone treatment produced no significant effects. Reuse from [10] with permission from John Wiley & Sons based on authors’ copyright

4. Evidence of documented changes in MDSCs and Treg levels induced by tumor growth, LCL521, and PDT vaccine treatments found at 72 h after therapy is shown in Fig. 1. A significant rise in both immunoregulatory cell populations is shown to be caused by the presence of growing tumor and a further significant increase is instigated by PDT vaccine treatment. The data further reveal that LCL521 administered immediately after PDT vaccine prevented the rise of both MDSCs and Tregs numbers in the host mice, while no significant effects were produced by LCL521 treatment alone [10].

Acknowledgments Financial sponsorship was received from the Canadian Cancer Society (grant 701132) and from the US National Cancer Institute, National Institutes of Health (grant R01 CA77475).

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References 1. Stewart TJ, Smyth MJ (2011) Improving cancer immunotherapy by targeting tumorinduced immune suppression. Cancer Metastasis Rev 30:125–140 2. Cubillos-Ruiz JR, Mohamed E, Rodriguez PC (2017) Unfolding anti-tumor immunity: ER stress responses sculpt tolerogenic myeloid cells in cancer. J Immunother Cancer 5:5. https://doi.org/10.1186/s40425-0160203-4 3. Baniyash M (2016) Myeloid-derived suppressor cells as intruders and targets: clinical implications in cancer therapy. Cancer Immunol Immunother 65:857–867 4. Korbelik M (2018) Immunoregulatory cell populations obligatory targets with most cancer therapies. Austin J Clin Med 5(1):1032 5. De Henau O, Rausch M, Winkler D, Campesato LF, Liu C, Hirschhorn-Cymerman D, Budhu S, Ghosh A, Pink M, Tchaicha J, Douglas M, Tibbitts T, Sharma S, Proctor J, Kosmider N, White K, Stern H, Soglia J, Adams J, Palombella VJ, McGovern K, Kutok JL, Wolchok JD, Merghoub T (2016) Overcoming resistance to checkpoint blockade therapy by targeting PI3Kγ in myeloid cells. Nature 539:443–447 6. Nishikawa H, Sakaguchi S (2010) Regulatory T cells in tumor immunity. Int J Cancer 127: 759–767 7. Khaled YS, Ammori BJ, Elkord E (2013) Myeloid-derived suppressor cells in cancer: recent progress and prospects. Immunol Cell Biol 91(8):493–502 8. Mikysˇkova´ R, Indrova´ M, Polla´kova´ V, Bieblova´ J, Sˇimova´ J, Reinisˇ M (2012) Cyclophosphamide-induced myeloid-derived suppressor cell population is immunosuppressive but not identical to myeloid-derived suppressor cells induced by growing TC-1 tumors. J Immunother 35:374–384 9. Xiao S, Jin H, Korn T, Liu SM, Oukka M, Lim B, Kuchroo VK (2008) Retinoic acid increases Foxp3+ regulatory T cells and inhibits development of Th17 cells by enhancing TGF-®-driven Smad3 signaling and inhibiting IL-6 and IL-23 receptor expression. J Immunol 181:2277–2284 10. Korbelik M, Bana´th J, Zhang W, Saw KM, Szulc ZM, Bielawska A, Separovic D (2016) Interaction of acid ceramidase inhibitor LCL521 with tumor response to photodynamic therapy and photodynamic therapygenerated vaccine. Int J Cancer 139: 1372–1378

11. Korbelik M (2016) Sphingolipid activity in oxidative stress response and tumor immunity. Austin J Vaccines Immunother 3(1):1008 12. Liu F, Lu C, Bai A, Bielawski J, Bielawska A, Marshall B, Schoenlein PV, Lebedyeva IO, Liu K (2016) Ceramide activates lysosomal cathepsin B and cathepsin D to attenuate autophagy and induce ER stress to suppress myeloidderived suppressor cells. Oncotarget 7(51): 83,907–83,925 13. Park J-H, Schuchman EH (2006) Acid ceramidase and human disease. Biochim Biophys Acta 1758:2133–2138 14. Taha TA, Mullen TD, Obeid LM (2006) A house divided: ceramide, sphingosine, and sphingosine-1-phosphate in programmed cell death. Biochim Biophys Acta 1758: 2027–2036 15. Spiegel S, Milstien S (2011) The outs and the ins of sphingosine-1-phosphate in immunity. Nat Rev Immunol 11:403–415 16. Bai A, Szulc ZM, Bielawski J, Pierce JS, Rembiesa B, Terzieva S, Mao C, Xu R, Wu B, Clarke CJ, Newcomb B, Liu X, Norris J, Hannun YA, Bielawska A (2014) Targeting (cellular) lysosomal acid ceramidase by B13: design, synthesis and evaluation of novel DMG-B13 ester prodrugs. Bioorg Med Chem 22: 6933–6944 17. Cheng JC, Bai A, Beckham TH, Marrison ST, Yount CL, Young K, Lu P, Bartlett AM, Wu BX, Keane BJ, Armeson KE, Marshall DT, Keane TE, Smith MT, Jones EE, Drake RR Jr, Bielawska A, Norris JS, Liu X (2013) Radiation-induced acid ceramidase confers prostate cancer resistance and tumor relapse. J Clin Invest 123:4344–4358 18. Ruvolo PP (2003) Intracellular signal transduction pathways activated by ceramide and its metabolites. Pharmacol Res 47:383–392 19. Spiegel S, Milstein S (2002) Sphingosine-1phosphate, a key cell signaling molecule. J Biol Chem 277:25851–25854 20. Oskouian B, Saba JD (2010) Cancer treatment strategies targeting sphingolipid metabolism. Adv Exp Med Biol 688:185–205 21. Zeng H, Yang K, Cloer C, Neale G, Vogel P, Chi H (2013) mTORC1 couples immune signals and metabolic programming to establish Treg-cell function. Nature 499:485490 22. Apostolidis SA, Rodriguez-Redriguez N, Suarez-Fueyo A, Dioufa N, Ozcan E, Crispin JC, Tsokos MG, Tsokos GC (2016) Phosphatase PP2A is requisite for the function of regulatory T cells. Nat Immunol 17:556–564

Blocking Immunosuppressory Cells for PDT 23. Kaneda MM, Messer KS, Ralainirina N, Li H, Leem CJ, Gorjestani S, Woo G, Nguyen AV, Figueiredo CC, Foubert P, Schmid MC, Pink M, Winkler DG, Rausch M, Palombella VJ, Kutok J, McGovern K, Frazer KA, Wu X, Karin M, Sasik R, Cohen EE, Varner JA (2016) PI3Kγ is a molecular switch that controls immune suppression. Nature 539:437–442 24. Herr I, Debatin K-M (2001) Cellular stress response and apoptosis in cancer therapy. Blood 98:2603–2614 25. Agostinis P, Berg K, Cengel KA, Foster TH, Girotti AW, Gollnick SO, Hahn SM, Hamblin MR, Juzeniene A, Kessel D, Korbelik M, Moan J, Mroz P, Nowis D, Piette J, Wilson BC, Golab J (2011) Photodynamic therapy of cancer: an update. CA Cancer J Clin 61: 250–281 26. Korbelik M (2018) Role of stress signaling networks in cancer cell death and antitumor immune response following proteotoxic injury inflicted by photodynamic therapy. Lasers Surg Med:50. https://doi.org/10.1002/lsm. 22810 27. Castano AP, Mroz P, Wu MX, Hamblin MR (2008) Photodynamic therapy plus low-dose cyclophosphamide generates antitumor immunity in a mouse model. Proc Natl Acad Sci USA 105:5495–5500 28. Reginato E, Mroz P, Chung H, Kawakubo M, Wolf P, Hamblin MR (2013) Photodynamic therapy plus regulatory T-cell depletion produces immunity against a mouse tumor that expresses a self-antigen. Br J Cancer 109: 2167–2174 29. Korbelik M, Banath J, Saw KM (2015) Immunoregulatory cell depletion improves the efficacy of photodynamic therapy-generated cancer vaccines. Int J Mol Sci 16:

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Chapter 29 Measuring the Antitumor T-Cell Response in the Context of Photodynamic Therapy Jan Willem Kleinovink and Ferry Ossendorp Abstract The field of photodynamic therapy (PDT) of cancer, like oncology research in general, is showing increasing interest in tumor immunology and immune effects of tumor treatment. Tumor ablation by PDT can lead to strong shifts in the composition of the immune cell infiltrate of tumors, and systemic effects of local therapy have been described. T lymphocytes, also known as T cells, are a type of adaptive immune cells that are of particular interest as they are very efficient in target cell recognition and killing, both at the treatment site and systemically. Moreover, T cells can constitute immunological memory to provide long-term protection. Several studies have described in detail how T-cell immune responses are induced by PDT and can play an important role in the therapeutic effect. This chapter describes several approaches of the analysis of T-cell responses during or after PDT in a mouse tumor model. Key words Photodynamic therapy, PDT, Cancer, Immune system, T cells, Depletion, T-cell response

1

Introduction It is well established that photodynamic therapy (PDT) can induce and enhance immune responses against the tumor, which may contribute to the therapeutic effect of PDT [1, 2]. Abscopal effects of local PDT on distant untreated tumors are a sign of involvement of the immune system and have been described in preclinical cancer models and in clinical cases [3, 4]. T cells, especially a subclass called CD8 T cells or cytotoxic T lymphocytes, are crucial effector cells in immune responses against tumors, specialized in recognizing and killing target cells that display signs of nonself, such as virusinfected cells and mutated tumor cells. PDT can induce T-cell responses against the tumor, which contribute to the therapeutic effect [2, 5]. This motivates the measurement of T-cell responses in PDT research. In this chapter, we describe examples of basic analysis of T-cell responses to be applied in preclinical PDT protocols. First, we describe an easy and straightforward method to assess direct involvement of T cells during or following PDT by

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_29, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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antibody-mediated depletion of all T cells and monitoring whether the therapeutic effect is maintained in the absence of T cells. Next, we discuss the ex vivo analysis of T-cell responses in lymphoid organs (spleen, lymph nodes), in circulating blood, and at the target site (tumor). As the emphasis of this chapter is on immunological analysis, we will not discuss protocols for PDT itself or any preceding steps such as tumor cell culture and tumor inoculation. Moreover, we will only describe the preparation of samples for flow cytometry and assume comprehension of flow cytometry panel design, measurement, and data analysis. Together, these protocols describe commonly used methods for the analysis of therapyinduced T-cell responses in preclinical cancer research.

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Materials Different methods to assess or analyze T-cell responses are described here without any interdependence nor chronological or preferential order. Although not literally correct, “FACS” will be used as a synonym for flow cytometry throughout the chapter.

2.1

T-Cell Depletion

1. Depleting antibodies: Sterile (0.2 μM filtered), low endotoxin (2 log10). The infections treated at 24 h postinoculation were more resistant to aBL than they were at 6 h postinoculation. This was explained by the formation of biofilms at 24 h of inoculation, rendering bacterial cells less susceptible to aBL. As a result, recurrence of the infection was observed in the mice treated with aBL at 24 h postinfection. The authors also referred that aBL toxicity to the retina is largely dependent on the aBL transmission of the cornea in which the corneal opacity of infected corneas promotes the blocking of the light [113]. The effectiveness of aBL was also recently described in a mouse model of burn injuries. A mouse model of burn infections was developed using a bioluminescent strain of A. baumannii [8]. The bacterial strain was made bioluminescent by the transfection of luxCDABE operon to noninvasively monitor the infection in vivo. Prior to aBL therapy, clusters of bacteria were observed in the established infections, which is a feature of biofilms. The results demonstrated that aBL at 415 nm successfully inactivated bacteria in established infections: A 3 log10 inactivation of A. baumannii in mouse burns was achieved with 360 J/cm2 blue light). The results also showed that 415 nm aBL is a promising approach to penetrate and destroy biofilms [8].

5

Conclusions and Perspectives The special attention given by the scientific community to aPDT and aBL is providing a high number of successful studies that are expected to motivate more practical applications in the future. It is important to highlight that these light-activated approaches are not limited to clinical applications, but can help to improve the microbiological quality of water and food, to control insect pests, and to disinfect and sterilize materials and surfaces in different settings (e.g., hospital, household, industrial). The high number of innovative works described here show that the bioluminescence approach is an important and efficient screening tool that enables us to monitor localized infections in real time, as demonstrated in numerous models in vitro, in vivo, and ex vivo. Additionally, the bioluminescence approach is an important tool in the synthesis of

Bioluminescent Models for Antibacterial PDT

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new photosensitizers, since it can give first insights in their efficacy before undertaking more extensive research and expanding their potential applications. Thus, bacterial bioluminescent models will continue to be an important tool for established and new researchers in this fascinating field.

Acknowledgments The authors are grateful to the University of Aveiro and the FCT/MCT for the financial support for the CESAM (UID/50017/2020) and LAQV-REQUIMTE (UIDB/50006/ 2020), and the FCT project PREVINE (FCT-PTDC/ASP-PES/ 29576/2017), through national funds and, where applicable, co-financed by the FEDER. References 1. Alves E, Faustino MAF, Neves MGPMS, ˆ , Nadais H, Almeida A (2015) Cunha A Potential applications of porphyrins in photodynamic inactivation beyond the medical scope. J Photochem Photobiol C Photochem Rev 22:34–57. https://doi.org/10.1016/j. jphotochemrev.2014.09.003 ˆ , Faustino MAF, 2. Alves E, Costa L, Cunha A Neves MGPMS, Almeida A (2011) Bioluminescence and its application in the monitoring of antimicrobial photodynamic therapy. Appl Microbiol Biotechnol 92:1115–1128. https://doi.org/10.1007/s00253-0113639-y 3. Hu XQ, Huang YY, Wang YG, Wang XY, Hamblin MR (2018) Antimicrobial photodynamic therapy to control clinically relevant biofilm infections. Front Microbiol 9. https://doi.org/10.3389/fmicb.2018. 01299 4. Mesquita MQ, Dias CJ, Neves MGPMS, Almeida A, Faustino MAF (2018) Revisiting current photoactive materials for antimicrobial photodynamic therapy. Molecules 23: 2424 5. Hamblin MR (2016) Antimicrobial photodynamic inactivation: a bright new technique to kill resistant microbes. Curr Opin Microbiol 33:67–73. https://doi.org/10.1016/j.mib. 2016.06.008 6. Huang Y-Y, Wintner A, Seed PC, Brauns T, Gelfand JA, Hamblin MR (2018) Antimicrobial photodynamic therapy mediated by methylene blue and potassium iodide to treat urinary tract infection in a female rat model.

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Chapter 35 Photochemical Internalization as a New Strategy to Enhance Efficacy of Antimicrobial Agents Against Intracellular Infections Xiaolin Zhang, Leonie de Boer, and Sebastian A. J. Zaat Abstract Pathogens such as Staphylococcus aureus are able to survive in many types of host cells including phagocytes such as neutrophils and macrophages, thereby resulting in intracellular infections. Treatment of intracellular infections by conventional antimicrobials (e.g., antibiotics) is often ineffective due to low intracellular efficacy of the drugs. Thus, novel techniques which can enhance the activity of antimicrobials within cells are highly demanded. Our recent studies have shown that photochemical internalization (PCI) is a promising approach for improving the efficacy of antibiotics such as gentamicin against intracellular staphylococcal infection. In this chapter, we describe the protocols aiming to study the potential of PCI-antibiotic treatment for intracellular infections in vitro and in vivo using a RAW 264.7 cell infection model and a zebrafish embryo infection model. Proof of concept of this approach is demonstrated. The protocols are expected to prompt further development of PCI-antimicrobial based novel therapies for clinically challenging infectious diseases associated with intracellular survival of pathogens. Key words Photochemical internalization (PCI), Cytosolic release, Antibiotics, Intracellular infections, Staphylococci, Zebrafish embryo, Mouse macrophage

1

Introduction Many opportunistic or obligatory bacterial pathogens such as Mycobacterium tuberculosis, Listeria monocytogenes, Salmonella typhi, and staphylococci can evade surveillance and clearance by hosts via intracellular survival within host cells including professional phagocytes (e.g., neutrophils and macrophages), causing potentially lifethreatening infectious diseases such as tuberculosis, meningitis, typhoid fever, sepsis, endocarditis, and biomaterial-associated infection [1, 2]. Intracellular infections are difficult to treat with antimicrobial agents (e.g., antibiotics and antimicrobial peptides) because most of these drugs have limited therapeutic efficacy within cells [2, 3]. The low intracellular activity of antimicrobials may be caused by one or multiple reasons as follows: (1) low penetration/

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_35, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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cellular internalization of eukaryotic cells [3]; (2) short intracellular retention time [3]; (3) high frequencies of resistance development [4]; and (4) different subcellular localization of antimicrobials (e.g., in endosomes) and intracellular bacteria (e.g., in phagosomes) [5]. In addition, several bacterial pathogens such as S. aureus may undergo phenotypical changes within host cells (e.g., small colony variants [6]) and become dormant with much lower metabolic activity. As a result, intracellularly surviving bacteria may be tolerant or at least less susceptible to antibiotics, even though the antibiotics are effective to kill the planktonic counterparts. Moreover, the low intracellular concentration of antimicrobials might allow selection of resistant bacteria within host cells [7]. Several approaches, such as the use of delivery systems based on liposomes, micro/nanoparticle and (nano-) biomimetic carriers [2, 8], conjugation of antibiotics to specific antibodies [9], or conjugation to cell-penetrating peptides [10], have been developed to improve the efficacy of antibiotic treatment of intracellular infections. These approaches have been shown to increase cellular internalization of antibiotics by targeted cells, but often these approaches target single types of antibiotics and hardly mediate the efficient release of cargos from endocytic vesicles into the cytosol [11]. Therefore, the majority of internalized drugs may remain entrapped in endosomes after cellular uptake, and will not be able to reach intracellular bacteria. Eventually, the entrapped drugs will be degraded when endosomes fuse with lysosomes [11]. In addition, structural modification of antibiotics may result in loss or reduction of their antimicrobial activity [12]. To address the problem, we utilize photochemical internalization (PCI), a technique developed to enhance intracellular efficacy of predominantly cancer therapeutics [13, 14] and to improve cytosolic release of antibiotics (e.g., gentamicin) from endosomes and as a result enhance their efficacy against intracellular bacteria. To this end, amphiphilic photosensitizers namely tetraphenyl porphyrin disulfonate (TPPS2a) and tetraphenyl chlorin disulfonate (TPCS2a) are used. TPPS2a and TPCS2a can reversibly bind to the membrane of eukaryotic cells and during endocytosis they are internalized and inserted in the membrane of endocytic vesicles in which drugs may be sequestered into cells [13, 14]. Upon illumination, these photosensitizer-bound membranes are disrupted. Furthermore, the liberated photosensitizers may re-localize to the membrane of other intact vesicles such as phagosomes containing bacteria, and also rupture these vesicles during the illumination period. Thus, PCI may cause cytosolic release of both entrapped drugs and hidden bacteria from the vesicles, allowing antimicrobialbacteria contact in the cytosol and subsequent killing. The concept of PCI-antibiotic treatment of intracellular infections is schematically illustrated in Fig. 1.

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Fig. 1 Proposed mechanism of photochemical internalization (PCI) of antibiotics combatting intracellular bacteria. (a) Cellular uptake of antibiotics and bacteria; amphiphilic photosensitizers (PS) are administered together with antibiotics and dock into the plasma membrane prior to the formation of endosomes (insertion of TPCS2a in magnification); (b) entrapment of antibiotics and bacteria in endosomes/phagosomes; (c) PCI-induced cytosolic release of antibiotics by disrupting the membrane of endosomes upon illumination and concomitant dissociation of PS; dashed arrow indicates relocation of liberated PS to the membrane of phagosomes containing bacteria during illumination, causing PCI-induced cytosolic release of bacteria; (d) contact of antibiotics with bacteria within the cytosol allowing antimicrobial action. Reproduced from Zhang et al. 2018 [15] with permission from Elsevier

We assessed the potential of PCI-antibiotic therapy in vitro using a RAW 264.7 cell staphylococcal infection model and in vivo using a zebrafish embryo staphylococcal infection model. Our studies showed that the zebrafish embryo model is a promising in vivo system to test the efficacy of photoactivated treatments of infectious diseases since zebrafish embryos are highly accessible to light penetration owing to the transparency of the embryos during the early development stage [15]. Moreover, the immune system of zebrafish (embryos) is highly comparable to that of mammals, evidenced by the presence of all major types of immune cells such as the macrophage and the neutrophil which have conserved

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functions including phagocytosing of bacteria as the mammalian orthologs do [16]. Therefore, complementary to mouse models, the zebrafish embryo model is suitable to study the therapeutic effects of photosensitizer-based treatments on intracellular infections (and possibly also for tumors since zebrafish embryo models for tumorous diseases have been developed) in vivo. In this chapter, we describe in detail the protocols of the in vitro and in vivo assays and show the proof of concept of PCI-antibiotic therapy for intracellular infections. We hope that these protocols will help further investigations on novel therapies based on the combination of PCI and antimicrobial agents to treat a broad spectrum of clinically challenging infectious diseases associated with intracellular survival of bacteria.

2

Materials

2.1 Bacterial Strains and Inoculum Preparation

1. S. epidermidis strain O-47 [17] and S. aureus strain ATCC 49230 for antimicrobial activity testing; transgenic bacterial strains such as S. aureus strain RN4220 expressing mCherry fluorescent protein [18] for in vivo visualization of cellpathogen interaction. 2. Sterile tryptic soy broth (TSB) bacterial culture medium. 3. Blood agarose plates (Colombia agar base, with 5% sheep blood). 4. Cuvettes (1 cm path length) and spectrometer for optical density measurement. 5. Centrifuges and vials for centrifugation.

2.2 Quantitative Culture of Bacteria

1. Sterile phosphate-buffered saline (PBS). 2. 96-Well plates. 3. Blood agarose plates.

2.3 Cell Maintenance and Culture

1. RAW 264.7 cell line (commercially available). 2. Sterile cell culture well plates. 3. RPMI 1640 medium with L-glutamine, supplemented with 5% fetal bovine serum (FBS) (designated as RPMI medium in this chapter unless specified elsewhere). 4. Penicillin and streptomycin (10,000 units/mL penicillin streptomycin). 5. 2-Mercaptoethanol (2-ME). 6. Dulbecco PBS (D-PBS). 7. Cell count chambers.

100
stock and 10,000

solution μg/mL

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8. Trypan blue solution 0.2% (stock is 0.4% 1:1 added to cell suspension). 9. Light microscope with objectives of 5
and 20
. 10. Cell scrapers. 11. Cell culture flask 75 cm2 with vented cap. 2.4 Antibiotics, Photosensitizers, and Light Source

1. Antibiotics: Gentamicin is used as model drug in this chapter. 2. Tetraphenyl porphyrin disulfonate (TPPS2a) and tetraphenyl chlorin disulfonate (TPCS2a) (PCI Biotech AS, Norway). 3. LumiSource device (wavelength: 420 nm, 13.5 mW/cm2, PCI Biotech AS, Norway).

irradiance:

4. Dimethyl sulfoxide (DMSO). 5. Sterile PBS and demineralized (demi) water. 2.5

Cytotoxicity Test

1. Water-soluble tetrazolium salts (WST)-1 assay kit (SigmaAldrich). 2. MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay kit (Sigma-Aldrich). 3. Trypan blue solution (see above). 4. Light microscope with objectives of 5
and 20
. 5. Microplate reader.

2.6 Phagocytosis Assay

1. Human serum. 2. RPMI medium. 3. Sodium chloride (NaCl). 4. Triton X-100 (0.0025%). 5. Cell culture plates (flat bottom). 6. Table centrifuge and vials for centrifugation.

2.7 Experimentation with Zebrafish Embryos

1. Wild-type zebrafish such as Tail Long (TL) line for experiments to assess the efficacy of antimicrobials and the transgenic line such as mpeg1: Gal4/UAS: Kaede, expressing Kaede green fluorescent proteins in macrophages [19] for experiments to visualize cell-bacteria interactions in vivo. 2. 3-Aminobenzoic acid (Tricaine). 3. E3 medium, the recipe can be found at the website www.ZFIN. org and elsewhere [20]. 4. Agarose powder (multipurpose). 5. Petri dishes. 6. Custom-made plastic mold plates. 7. Sterile demi water.

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8. Jeweler’s forceps. 9. Glass capillaries (Harvard apparatus, 1 mm O.D.
0.78 mm). 10. Micropipette puller instrument (Flaming P-97, Sutter Instrument Inc). 11. Microloader pipette tips. 12. FemtoJet microinjector (Eppendorf) and a stand with micromanipulator (World Precision Instruments). 13. 48-Well plates. 14. Light microscope with a scale bar in ocular. 15. Zirconia beads, 2 mm (Bio-connect). 16. MagNA lyser (Roche). 17. Selective culture plates (e.g., mannitol salt 2 agar plates (BioMe´rieux) for staphylococci). 2.8

Imaging

1. Stereo fluorescence microscope. 2. Methyl cellulose solution in PBS, 2%. 3. Confocal fluorescence microscope. 4. Fluorescence antifade reagent. 5. Glass-bottom petri dishes. 6. Fluorescent compounds (e.g., photosensitizers) or fluorescently labeled compounds (e.g., antibiotics). 7. Transgenic zebrafish lines and transgenic bacteria expressing fluorescent proteins (see information described before).

3

Methods

3.1 Preparation of Bacterial Inoculum

1. Take 4–5 colonies of S. aureus ATCC49230 or S. epidermidis O-47 bacteria from blood agar culture plates and culture the bacteria in 5 mL of TSB medium for 4–6 h at 37  C with agitation at 120 rpm, allowing the bacteria to grow to the mid-logarithmic growth phase (see Note 1). 2. After culture, transfer 1 mL of bacterial inoculum in a 1 cm path length cuvette for optical density (OD) measurement. If necessary dilute 100 μL of the bacterial inoculum with 900 μL of sterile PBS for measurement. Measure the OD of the bacterial inoculum at 620 nm (OD620) using a spectrophotometer. An OD620 of 0.4–0.8 implies that the bacteria (e.g., staphylococci) have reached the mid-logarithmic growth phase. 3. Centrifuge bacteria under an appropriate condition, subsequently wash the pelleted bacteria with PBS twice, and resuspend in 1.1 mL of PBS. Measure the OD620 of bacterial suspension as described in step 2 above.

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4. Adjust bacterial suspensions to concentration(s) required for different experiments. An OD620 of 0.3 generally corresponds to 1.0
108 colony-forming units (CFU)/mL of staphylococcal bacteria. 3.2 Cell Culture and Maintenance

1. To prevent contamination during maintenance of cells, add 5 mL of 100
stock solution of penicillin and streptomycin to 500 mL of RPMI medium. Add 500 μL of 50 mM 2-mercaptoethanol (2-ME) (in demi-water) to the medium to remove toxic oxygen radicals produced by cells. Culture RAW 264.7 cells in 50 mL of the medium in a cell culture flask at 37  C in a humidified atmosphere containing 5% CO2. 2. For maintenance of RAW 264.7 cells, refresh medium once every 3–4 days. Briefly discard the medium, and wash cells with 15 mL of D-PBS. Remove D-PBS and replace with 15 mL of fresh RPMI medium. Scrape the cells attaching to the bottom of the culture flask using a cell scraper and suspend the cells uniformly in the fresh medium. Transfer 50 μL of the cell suspension to a new culture flask containing 50 mL of fresh RPMI medium containing penicillin and streptomycin. 3. For experiments, culture cells in RPMI medium without antibiotics added. After washing and scraping cells as described above, suspend cells in 10 mL of refresh medium. To quantify the number of cells, transfer 10 μL of the cell suspension to a tube and mix with 10 μL of 0.4% trypan blue. Transfer 10 μL of the mixture to a cell count chamber. Count the number of cells stained by trypan blue. Calculate the concentration of cells in the suspension following the manufacturer’s instruction. Adjust the suspension to the desired concentrations for different experiments (usually 1 to 5
105 cells/mL). Seed RAW 264.7 cells in cell culture plates and incubate the cells overnight in fresh RPMI medium as described above.

3.3 Cytotoxicity of Agents to RAW 264.7 Cells

1. To test the effects of antibiotics such as gentamicin on the metabolic activity of RAW 264.7 cells, incubate the cells overnight in 200 μL of RPMI medium containing antibiotics in a series of concentrations (15.6–1000 μg/mL for gentamicin tested in our studies). Use cells incubated in RPMI medium (no gentamicin added) as controls. 2. To test the effects of photosensitizers on the metabolic activity of RAW 264.7 cells, incubate cells for 2 h in 200 μL of RPMI medium containing photosensitizer (TPPS2a or TPCS2a) at different concentrations (0.1–0.4 μg/mL tested in our studies). Subsequently incubate the cells for another 2 h in fresh RPMI medium in order to remove excess photosensitizer from the cell membrane. Incubate cells in RPMI medium (no photosensitizer added) as controls. Illuminate cells for

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relevant time periods (e.g., 5, 10, and 15 min) using the LumiSource device. Use photosensitizer-treated cells without illumination as controls. Always protect cells from light except during illumination. After illumination, incubate cells in fresh RPMI medium for 24 h. Potential effects of photosensitizer combined with antimicrobial agents can be studied following the procedure described above, if required, with modification/ adjustments for specific experimental setups. 3. To test the cytotoxicity of photosensitizer to RAW 264.7 cells, incubate cells in RPMI medium containing photosensitizer as described above. To test the cytotoxicity of photosensitizer combined with bacteria, incubate cells first with bacterial inoculum for 45 min, allowing phagocytosis of bacteria (assay described in the Subheading 3.4 below). After phagocytosis, incubate cells in RPMI medium containing photosensitizer as described above. Cytotoxicity of antimicrobial agents can be studied following the procedure described here, if required, with modification/adjustments for specific experimental setups. 4. Follow the WST-1 assay or MTT assay to study the effect of the agents on the metabolic activity of RAW 264.7 cells at different time points (e.g., 0 and 24 h) according to the manufacturer’s instruction. To test cytotoxicity, replace the medium containing the agents with PBS and wash cells one time. After washing, incubate cells with trypan blue for approximately 5 min. Quantify the loss of cell viability by counting the number of cells stained by trypan blue under a light microscope shortly after treatment (time point 0 h) and at designated time points (e.g., 1 and 24 h). 3.4 Phagocytosis Assay (Cell Infection Model)

1. Prepare bacterial inoculum as described above. After washing, centrifuge bacteria (e.g., S. epidermidis O-47) under appropriate conditions. Resuspend the pelleted bacteria in 1.5 mL of NaCl mixed with 0.5 mL of human serum, and incubate for 20 min for opsonization. Subsequently centrifuge the suspension and wash the pelleted bacteria with RPMI medium. Adjust the bacterial inoculum to the desired concentrations (1
108 CFU/mL in our studies) with RPMI medium. 2. Seed RAW 264.7 cells in a cell culture plate as described above. Replace the culture medium with 40 μL of the bacterial inoculum. The ratio between bacteria (S. epidermidis O-47) and RAW 264.7 cells is then 40:1, meaning the multiplicity of infection (MOI) is 40. Incubate the cells with bacteria for 45 min, allowing phagocytosis of bacteria (see Note 2). 3. After phagocytosis, wash the cells gently 4 times with 60 μL of PBS, and with a final wash with 200 μL of PBS to prevent

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Fig. 2 Schematic representation of the procedure for in vitro testing of PCI-antibiotic therapy of intracellular infection using the RAW 264.7 cell infection model. Reproduced from Zhang et al. 2018 [15] with permission from Elsevier

carryover of planktonic bacteria (non-phagocytosed bacteria). According to our experience, after the washing steps, numbers of planktonic bacteria are always less than 0.5% of numbers of intracellular bacteria based on the quantitative culture. 4. Shortly after phagocytosis and at designated time points (e.g., 24 h after phagocytosis), remove the medium and lyse the cells with 100 μl of PBS containing 0.0025% Triton X-100. Transfer the PBS containing lysed cells and released intracellular bacteria into a vial and centrifuge under appropriate conditions. 5. Tenfold serially dilute the suspension of the retrieved bacteria with PBS and spot 10 μL of each dilution on agarose blood plates. Incubate the plates overnight. On the next day count the number of bacteria in countable dilutions and calculate the total number of intracellular bacteria per well. The procedure of phagocytosis assay is schematically depicted in Fig. 2. 3.5 Intracellular Antimicrobial Activity Assay

1. Follow the steps in “phagocytosis assay” to set up the RAW 264.7 cell staphylococcal infection model. 2. Incubate infected cells for 2 h in RPMI medium containing gentamicin with desired concentrations or in RPMI medium containing both gentamicin and photosensitizers with desired concentrations (10 or 30 μg/mL gentamicin only or combined with 0.25 μg/mL TPPS2a was used in our studies). Use infected cells without treatment (only incubated in RPMI medium) as controls. Always protect the photosensitizertreated cells from light except for the illumination period (mentioned below).

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Fig. 3 Representative results of reduction of intracellular S. epidermidis in RAW 264.7 cells by PCI-antibiotic treatment. CFU: colony-forming units. Cells were treated with gentamicin only (GEN, 1, 10, or 30 μg/mL, “–”) or combined with the photosensitizer TPPS2a (0.25 μg/mL, “+”) and subsequently illuminated for 15 min. Cells treated with TPPS2a alone (no GEN, “+”) or without treatment (no GEN, “–”) were used as controls. PCI significantly improves the efficacy of 10 and 30 μg/mL gentamicin against intracellular S. epidermidis, evidenced by statistically significantly lower CFU numbers of bacteria in groups treated with gentamicin-TPPS2a than that in groups treated with gentamicin only. Reproduced from Zhang et al. 2018 [15] with permission from Elsevier

3. Replace the medium with fresh RPMI medium only containing gentamicin with concentrations identical to those used for treatment (no photosensitizers added), and incubate the cells for 2 h to allow excess cell membrane-bound photosensitizers to dissociate from the membranes. 4. To remove the photosensitizers, replace the medium with fresh RPMI medium containing 1 μg/mL gentamicin, which is added in order to prevent possible growth of extracellular bacteria in the subsequent steps. 5. Illuminate the cells for certain time periods (e.g., 10 or 15 min). Use non-illuminated infected cells as controls. 6. Incubate the cells overnight. Lyse the cells and quantitatively culture intracellular surviving bacteria as described above. Representative results of reduction of intracellular S. epidermidis by treatment with gentamicin-TPPS2a are shown in Fig. 3. The procedure of the intracellular antimicrobial activity assay is schematically depicted in Fig. 2. 3.6 Visualization of Intracellular Distribution of Agents In Vitro

1. Apply confocal fluorescence microscopy to visualize intracellular distribution of antibiotics and photosensitizer in RAW 264.7 cells with or without illumination. Seed RAW 264.7 cells in a glass-bottom culture dish at the desired concentration (3
105 cell/dish in our studies) and incubate the cells in

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Fig. 4 Representative images showing intracellular distribution of gentamicin (labeled with a blue fluorescent dye) and the photosensitizer TPCS2a (red

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1 mL of RPMI medium containing fluorescently labeled gentamicin and photosensitizers at desired concentrations (10 μg/ mL gentamicin and 1 μg/mL TPCS2a were used in our study). Fluorescently labeled antibiotics can be either purchased from manufacturers or prepared according to methods/protocols reported elsewhere [21]. Always protect the cells from light except for the following illumination step. 2. Incubate the cells in fresh RPMI medium for 4 h to remove excess cell membrane-bound photosensitizers, and then illuminate the cells for 2 min. 3. Cover the cells with Prolong® Gold antifade reagent prior to imaging. The max absorption wavelength of TPPS2a and TPCS2a in aqueous media is between 410 and 420 nm [22]. Of note, TPCS2a has a second absorption peak at 650 nm, which is highly favorable for deeper tissue penetration [22]. The emission wavelengths of TPPS2a are approximately 650 and 720 nm and that of TPCS2a is approximately 650 nm [22]. Optimize the settings of the confocal microscopy for imaging according to local instructions. Representative confocal images of intracellular distribution of gentamicin and TPCS2a within RAW 264.7 cells with or without illumination are shown in Fig. 4. 1. Prepare agarose solution (1–1.5% in demi-water) by heating using a microwave oven and pour the solution in a petri dish. Place a plastic mold template (Fig. 5a) on top of the agarose solution in the petri dish to create grooves in agarose for placing embryos in proper position, facilitating injection. Incubate the petri dish at room temperature and remove the mold template when the agarose solution has solidified.

3.7 Zebrafish Embryo Infection Model

2. At 1–2 h prior to injection, dechorionize the zebrafish embryos using a forceps, releasing embryos from chorion. At 28–30 h postfertilization, place and anesthetize embryos in a petri dish filled with E3 medium containing 3-aminobenzoic acid (Tricaine, 0.02% w/v) for 5 min. Transfer the anesthetized embryos to the agarose plate overlaid with fresh E3 medium

ä Fig. 4 (continued) fluorescent) in RAW 264.7 cells without illumination (left panel) and with illumination for 2 min (right panel). Without illumination, gentamicin and TPCS2a localize in the periphery of the cells, likely in endocytic vesicles. With illumination, gentamicin and TPCS2a distribute through the entire cells, indicating PCI-induced cytosolic release of the agents. Gentamicin seems to associate with the cell nucleus, as has been reported before [25]. Scale bars ¼ 10 μm. Reproduced from Zhang et al. 2018 [15] with permission from Elsevier

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Fig. 5 Instrument used for and illustration of injections to zebrafish embryos. (a). A petri dish with a solidified agarose layer, the jeweler’s forceps used to dechorionize embryos, and the plastic mold template used to create grooves in the agarose layer; (b) a light microscope with FemtoJet injector and micromanipulator used for injections to zebrafish embryos; (c) embryos aligned in grooves in the agarose layer in an orientation suitable for injections under a light microscope (with a scale)

containing Tricaine. Align the embryos in one orientation for injections under a light microscope (Fig. 5b, c). 3. Prepare needles for injections by pulling glass microcapillaries using a micropipette puller instrument. The settings used for pulling needles depend on the instrument applied and local instructions. As a reference, the settings of the puller instrument (Sutter P-97) used in our studies were as follows: heat: 772, pull: 100, vel: 200, time: 40, and gas: 75. According to our experiences, the pulled needles are suitable for injections after breaking of the tip as described below. 4. To allow injections to embryos but minimize associated tissue damage, break the needle tip with a forceps at an appropriate outer diameter of the needle (approximately 15 μm in our studies) under a light microscope (with a scale) (see Note 3). Load approximately 10 μL of bacterial suspension (S. aureus inoculum in our studies) into the needle using a microloader pipette tip. Mount the needle onto a micromanipulator connected to the FemtoJet microinjector (Fig. 5b). Adjust the parameters such as pressure and injection time of the FemtoJet microinjector to allow injections of liquid droplets with a diameter of 125 μm, which corresponds to a calculated droplet volume of 1 nL. Check the size of droplets from time to time throughout the experiment. If the droplet sizes seem different or the needle is broken or clogged, always change for a new needle for further injections. 5. Insert the needle and inject 1 nL of bacterial inoculum (with different doses) into the blood circulation of zebrafish embryos via the blood island [23] using a foot pedal connected to the microinjector. After injections, maintain the embryos individually in E3 medium in a well plate (see Note 4). 6. To verify the number of bacteria injected, randomly select 5–6 live infected embryos to be crushed shortly after injection. Transfer the selected embryos individually to separate vials using sterile pipette tips. Remove the medium, wash the

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Table 1 Representative results of the median of CFU numbers of S. aureus retrieved from embryos injected with different aimed doses Aimed CFU per embryo

Injected CFU per embryoa

6000

7500

3000

2740

500

480

100

140

a

Median of CFU numbers of bacteria retrieved from five individual embryos crushed shortly after injection

Table 2 Over-time percent survival of embryos injected with different doses of S. aureus. PBS injections served as controls. Group sizes were between 26 and 38 embryos per group 6000 CFU per embryo

3000 CFU per embryo

500 CFU per embryo

100 CFU per embryo

PBS injection

1 dpi

65%

100%

100%

97%

97%

2 dpi

35%

77%

97%

97%

97%

3 dpi

31%

53%

82%

89%

97%

4 dpi

27%

50%

76%

82%

97%

dpi ¼ days postinjection

embryos gently with sterile PBS once, and add 100 μL of fresh PBS. To facilitate crushing of embryo, add 2–3 sterile zirconia beads to each vial. Crush embryos using a homogenizer (MagNA lyser, Roche). The setting of homogenizer used is as follows: speed: 3500 rpm and time: 30s. Other homogenizers may require different settings. 7. Quantitatively culture the retrieved bacteria by plating tenfold serial PBS dilutions as described above. To avoid overgrowth by fish microflora, it is suggested to use selective plates (e.g., mannitol salt 2 agar plates for staphylococci) for quantitative culture. Following the injection procedure described above, the actual doses of bacteria injected to embryos are verified to be close to the aim doses with minor variations (Table 1). 8. Inject different doses of bacterial inoculum into embryos and verify the actual doses injected as described above to determine the challenge doses that kill 70–90% of embryos. According to our experience, doses between 3000 and 6000 CFU/embryo of S. aureus ATCC 49230 cause these levels of death of 1-day-old embryos (Table 2), which therefore are suitable challenge doses to assess the efficacy of antibiotic alone or combined with PCI to rescue embryos (see Note 5).

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3.8 In Vivo Visualization of CellPathogen Interactions in Zebrafish Embryos

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1. Fluorescent transgenic bacteria (e.g., S. aureus RN4420 expressing mCherry red fluorescent proteins) and embryos of transgenic zebrafish lines (e.g., the mpeg1: Kaede line expressing Kaede green fluorescent proteins in zebrafish macrophages) are required for in vivo visualization of cell-pathogen interactions. Use available strains or construct transgenic bacteria expressing fluorescent proteins following protocols such as described elsewhere [24]. Prepare an inoculum of fluorescent bacteria as described before. Transgenic zebrafish lines may be requested from research groups listed on the website, www.ZFIN.org, or through the scientific literature. 2. At 28–30 h postfertilization, inject bacteria into embryos via the blood island as described in step 4 in the Subheading 3.7. Score the embryos for successful injection of fluorescent bacteria under a stereo fluorescence microscope. Discard the embryos without visible fluorescent bacteria. Of note, low doses of fluorescent bacteria (e.g., 500 CFU/embryo) may not be visible within embryos. The minimal dose of fluorescent bacteria required for in vivo visualization is dependent on the intensity of the fluorescent proteins expressed by the bacteria and may need to be determined individually for different transgenic bacteria strains/species. After injection of bacteria, maintain the embryos in E3 medium individually in a well plate. 3. Anesthetize the embryos in E3 medium containing Tricaine for approximately 5 min. Pipette approximately 500 μL of 4% methyl cellulose solution (highly viscous) into a petri dish filled with E3 medium containing Tricaine. Place the anesthetized embryos in the spot of methyl cellulose solution to temporarily immobilize them in best orientation for subsequent imaging. 4. A stereo fluorescent microscope (e.g., Leica LM 80) is used for visualization of cell-pathogen interaction in the zebrafish embryos. Depending on the fluorescence color of different elements, the corresponding filters are required. At designated time points (e.g., 2 h postinjection), image individual embryos under optimal settings according to local instructions. Representative images showing cell-pathogen in zebrafish embryos are shown in Fig. 6. In addition, confocal fluorescent microscope can be used for visualization of interactions between pathogen and single zebrafish cells in more detail.

3.9 In Vivo Antimicrobial Activity Test

1. Determine the toxicity of agents to zebrafish embryos. In our studies, we injected 1 nL of agents in a series of doses into the blood circulation of 1-day-old embryos via the blood island as described above. Monitor survival of embryos based on the movement and heartbeat using a light microscope until a certain time point (e.g., 5 days postinfection), according to the experimental design (see Note 6).

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Fig. 6 Representative images of 1-day-old zebrafish embryo at 2 h postinjection of S. aureus via the blood island (approximately 32 h postfertilization). (a) Bright-field image of a 1-day-old embryo. The blue box indicates the area showing interactions between S. aureus-mCherry (red) and zebrafish macrophages (green) at high magnification as shown in (b). Scale bars ¼ 100 μm

2. Set up the zebrafish embryo infection model as described above. Randomly divide infected embryos for different treatments. It is practically possible to have 30 embryos per group or more, depending on the experimental design. 3. At a certain time point after injection of bacteria (e.g., at 2 h postinfection, so usually 30–32 h postfertilization), inject 1 nL of antibiotic solution, photosensitizer solution, or a mixture into the blood circulation of embryos via blood island as described above. Embryos injected with 1 nL of PBS and non-treated embryos serve as controls. 4. After injections of agents, incubate embryos in E3 medium for 2 h. Then illuminate embryos for 10 min using the LumiSource. Protect embryos from light except for the illumination period (see Note 7). 5. Maintain embryos individually in E3 medium. Monitor the survival of embryos as described above. More information and video demonstrations on technical details on in vivo visualization of cell-pathogen interaction in zebrafish embryos and injections to embryos can be found in the study of Zhang et al. [18] (https://www.jove.com/video/58523) and Benard et al. [23] (http://www.jove.com/video/3781).

4

Notes 1. Other bacterial strains or species than S. epidermidis O-47 and S. aureus ATCC 49230 may be used to set up in vitro and/or in vivo infection model. Several aspects in bacterial inoculum preparation such as culture media/plates and culture condition may need to be changed/adjusted for other bacterial pathogens. Moreover, optimal wavelength for OD measurement and correlation between OD values and concentrations of bacterial

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inoculum may need to be determined for other bacterial pathogens. 2. For the RAW 264.7 cell infection model with phagocytosis of other bacterial pathogens, the ratio of bacteria to RAW 264.7 cells needs to be determined for the corresponding bacterial strains or species. In addition, other (phagocytic) cell lines may be used to establish cell infection models following the present protocol. Modification/adjustments on the protocol may be needed for other cell lines. For instance, addition of 2-ME may not be necessary for maintenance of other cell lines. 3. According to the study of Benard et al. [23], needles will have a sharper tip if they are beveled using a microgrinder. This will facilitate reproducible injections to embryos with less damage; therefore this may be considered to be included for needle preparation. The tip of the needles may need to be adjusted to different sizes for different experimental setups (e.g., injections of larger volumes of liquid, injections to older embryos, or injections at other sites than blood island). 4. To be able to visually inspect whether injections to zebrafish embryos are successful in real time, a marker dye (e.g., phenol red, 0.25%) is suggested to be added to solutions for injections. Zebrafish embryo infection models can be set up with older embryos (e.g., 2- or 3-day-old embryos). Alternative injection sites are suitable for older embryos (e.g., duct of Cuvier and tail muscle tissue), for which detailed information can be found elsewhere [18, 23]. 5. Zebrafish embryo (intracellular) infection models for other bacterial strains or species such as Salmonella enterica, serovar Typhimurium (S. typhimurium), and Mycobacterium marinum have been established following a similar protocol [23]. Thus, embryo models for other pathogens possibly can be established following the present protocol with necessary modification/ adjustments. 6. In addition to monitoring the survival of zebrafish embryos as the readout for the efficacy of treatments, quantitative culture of bacteria retrieved from embryos is suggested to be included as a direct assessment of antimicrobial efficacy at the end time point of experiments. 7. Other illumination devices with suitable excitation wavelengths may be potentially applicable to activate the photosensitizers TPPS2a and TPCS2a in vitro in cells and in vivo in zebrafish (embryos). If applicable, parameters such as intensity of light and illumination time need to be adjusted for experiments with cells or embryos using other illumination devices. In addition, according to the experimental design other aspects such as light-drug administration interval, administration routes of

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photosensitizer, and/or antimicrobial agent may need to be adjusted for in vitro studies with cells and/or in vivo studies using zebrafish embryos. References 1. Busscher HJ, van der Mei HC, Subbiahdoss G, Jutte PC, van den Dungen JJAM, Zaat SAJ, Schultz MJ, Grainger DW (2012) Biomaterial-associated infection: locating the finish line in the race for the surface. Sci Transl Med 4:153. https://doi.org/10.1126/ scitranslmed.3004528 2. Abed N, Couvreur P (2014) Nanocarriers for antibiotics: a promising solution to treat intracellular bacterial infections. Int J Antimicrob Agents 43(6):485–496. https://doi.org/10. 1016/j.ijantimicag.2014.02.009 3. Carryn S, Chanteux H, Seral C, MingeotLeclercq MP, Van Bambeke F, Tulkens PM (2003) Intracellular pharmacodynamics of antibiotics. Infect Dis Clin North Am 17(3):615–634 4. Goldstein BP (2014) Resistance to rifampicin: a review. J Antibiot (Tokyo) 67(9):625–630. https://doi.org/10.1038/ja.2014.107 5. Tulkens PM (1991) Intracellular-distribution and activity of antibiotics. Eur J Clin Microbiol Infect Dis 10(2):100–106 6. Proctor RA, von Eiff C, Kahl BC, Becker K, McNamara P, Herrmann M, Peters G (2006) Small colony variants: a pathogenic form of bacteria that facilitates persistent and recurrent infections. Nat Rev Microbiol 4(4):295–305. https://doi.org/10.1038/nrmicro1384 7. Baharoglu Z, Krin E, Mazel D (2013) RpoS plays a central role in the SOS induction by sub-lethal aminoglycoside concentrations in Vibrio cholerae. PLoS Genet 9(4):e1003421. https://doi.org/10.1371/journal.pgen. 1003421 8. Alipour M, Hosseinkhani S, Sheikhnejad R, Cheraghi R (2017) Nano-biomimetic carriers are implicated in mechanistic evaluation of intracellular gene delivery. Sci Rep 7:41,507. https://doi.org/10.1038/srep41507 9. Lehar SM, Pillow T, Xu M, Staben L, Kajihara KK, Vandlen R, DePalatis L, Raab H, Hazenbos WL, Morisaki JH, Kim J, Park S, Darwish M, Lee BC, Hernandez H, Loyet KM, Lupardus P, Fong R, Yan D, Chalouni C, Luis E, Khalfin Y, Plise E, Cheong J, Lyssikatos JP, Strandh M, Koefoed K, Andersen PS, Flygare JA, Wah Tan M, Brown EJ, Mariathasan S (2015) Novel antibody-antibiotic conjugate eliminates

intracellular S. aureus. Nature 527(7578):323–328. https://doi.org/10. 1038/nature16057 10. Brezden A, Mohamed MF, Nepal M, Harwood JS, Kuriakose J, Seleem MN, Chmielewski J (2016) Dual targeting of intracellular pathogenic bacteria with a cleavable conjugate of kanamycin and an antibacterial cell-penetrating peptide. J Am Chem Soc 138(34):10,945–10,949. https://doi.org/10. 1021/jacs.6b04831 11. Varkouhi AK, Scholte M, Storm G, Haisma HJ (2011) Endosomal escape pathways for delivery of biologicals. J Control Release 151(3):220–228. https://doi.org/10.1016/j. jconrel.2010.11.004 12. Lysenkova LN, Turchin KF, Danilenko VN, Korolev AM, Preobrazhenskaya MN (2010) The first examples of chemical modification of oligomycin A. J Antibiot (Tokyo) 63(1):17–22. https://doi.org/10.1038/ja. 2009.112 13. Hogset A, Prasmickaite L, Selbo PK, Hellum M, Engesaeter BO, Bonsted A, Berg K (2004) Photochemical internalisation in drug and gene delivery. Adv Drug Deliv Rev 56(1):95–115. https://doi.org/10.1016/j. addr.2003.08.016 14. Selbo PK, Weyergang A, Hogset A, Norum OJ, Berstad MB, Vikdal M, Berg K (2010) Photochemical internalization provides time- and space-controlled endolysosomal escape of therapeutic molecules. J Control Release 148(1):2–12 15. Zhang X, de Boer L, Heiliegers L, Man-Bovenkerk S, Selbo PK, Drijfhout JW, Hogset A, Zaat SAJ (2018) Photochemical internalization enhances cytosolic release of antibiotic and increases its efficacy against staphylococcal infection. J Control Release 283:214–222. https://doi.org/10.1016/j. jconrel.2018.06.004 16. Renshaw SA, Trede NS (2012) A model 450 million years in the making: zebrafish and vertebrate immunity. Dis Model Mech 5(1):38–47. https://doi.org/10.1242/Dmm. 007138 17. Heilmann C, Gerke C, PerdreauRemington F, Gotz F (1996) Characterization of Tn917 insertion mutants of Staphylococcus

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Chapter 36 Determination of the Efficiency of Photodynamic Decontamination of Food Michael Glueck and Kristjan Plaetzer Abstract Unsafe food causes more than 200 diseases and therefore poses a threat to the health of millions of people worldwide. Children under 5 years of age carry about 40% of the foodborne disease burden. With a rapidly growing world population, the supply of nutritious, safe, and healthy food represents a high challenge for the coming centuries. Photodynamic decontamination of food (PDc) is based on the photosensitizer (PS)mediated and light-induced overproduction of reactive oxygen species, which kill microorganisms irrespective of their resistance to conventional treatment. Several natural substances approved as food additives such as curcumin or chlorophyllin are photoactive. Thus, PDc based on these compounds is a promising approach to improve food safety. In this chapter, two experimental protocols to investigate the antimicrobial efficacy of PDc on flat objects like lettuce or slices of cucumber or round objects like mung beans in situ are described in detail, which allow for quantitative analysis of the decontamination effect. Both methods are also applicable for other radiation-based decontamination, such as UV- or γ-treatment of food. Key words Food safety, Photodynamic therapy, Photoantimicrobials, Natural substances, Decontamination efficiency

Abbreviations DPBS E. coli PDc PDI PS THB

1

Dulbecco’s phosphate-buffered saline Escherichia coli Photodynamic decontamination Photodynamic inactivation Photosensitizer Todd-Hewitt-Bouillon

Introduction According to the latest reports the UN predicts the world population to increase up to 11 billion until 2100 [1]. The supply of this

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_36, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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ever-growing number of people with healthy, clean, and affordable food represents a major issue for the upcoming centuries. Outbreaks of foodborne diseases are globally widespread and threaten the health of people worldwide. People being killed by foodborne and waterborne diarrheal diseases are estimated to reach 2.2 million annually, most of them children below 5 years: even though they account for only 9% of the world population, they carry 40% of the foodborne disease burden [2]. As a result of the use of antibiotics in animal husbandry, development of resistant pathogens rises rapidly. The most important transmission route for resistant microorganisms from animals to humans is through food [3]. This was clearly observable when, in 1983 shortly after the introduction of streptomycin as a growth promoter, a streptomycin resistance gene was detected in E. coli isolated from pigs. The resistance gene was rapidly spread to E. coli of farmers and finally to isolates of Salmonella and Shigella of urban citizens [4]. Since access to safe and healthy food represents a fundamental human right, strategies to prevent outbreaks of foodborne diseases, especially if caused by resistant pathogens, are needed badly. Photodynamic inactivation (PDI) is a very effective approach to kill microorganisms. It has been proven that photodynamic decontamination (PDc) based on photosensitizers (PS) derived from natural sources, such as curcumin (approved as E100) or chlorophyllin (approved as E140, E141), is applicable for combating foodborne diseases [5–8]. The phototoxic effect of PDI is triggered by a two-step procedure: in the first step the nontoxic photosensitizer is applied to the target cells and in the second step photoactivation of the compound with visible light produces reactive oxygen species, which in turn kill microorganisms by oxidative processes. In this chapter, two in situ procedures to investigate the potential of photodynamic decontamination on different food substrates with two geometries are described: one protocol is applicable to flat surfaces like slices of cucumbers, tomatoes, or lettuce and for round and more complex objects like mung beans and germinated mung beans an alternative experimental strategy is described. Foodstuffs with complex geometry are very difficult to decontaminate by PDc: to overcome this “3D problem” three approaches to illuminate these objects all round are suggested.

2 2.1

Materials Cell Culture

Escherichia coli (ATCC 25922). 1. DPBS (Dulbecco’s phosphate-buffered saline, Sigma Aldrich Chemie GmbH, Steinheim, Germany); use filtration to sterilize the DPBS or autoclave.

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2. THB medium: 30 g/L Todd-Hewitt-Bouillon (Carl Roth GmbH + Co. KG, Karlsruhe, Germany) and 3 g/L yeast extract (AppliChem, Darmstadt, Deutschland); autoclave at 120
C for 25 min. 3. THB plates: 30 g/L Todd-Hewitt-Bouillon (Roth), 3 g/L yeast extract (AppliChem), 15 g/L agar-agar (Kobe I, Roth); autoclave at 120
C for 25 min. 2.2 Sample Preparation 2.2.1 Vegetables

This chapter describes the preparation of the food samples, removal of preexisting contamination, and preparation of the PS stock solution. All critical steps are performed in a laminar flow bench. 1. Obtain fresh vegetables from a local food store and wash them carefully with mains water. 2. Cut them in plane slices of approximately 1.5  1.5 cm2 in size and transfer them into Petri dishes (Fig. 1a). 3. If the food has an epidermis, make sure that it is unbroken and facing up. 4. Embed the pieces all round in 15% agar-agar (Kobe I, Roth) to fixate them in the Petri dishes. 5. Remove preexisting microorganisms by covering the sample with 70% ethanol for three minutes (Fig. 1b). 6. Remove the ethanol carefully and let the sample dry.

2.2.2 Salads

1. Obtain salad from a local food store. Cut pieces of 6  6 cm2 in size and wash them carefully with water containing 1% dishwashing solution (Aro Citrus, Goldhand, Duesseldorf, Germany). Rinse thoroughly with water (see Note 1). 2. Let the lettuce dry at room temperature.

2.2.3 Beans and Sprouts

– Mung beans and fenugreek seeds were not decontaminated prior to PDc. – To germinate mung beans, place them in mains water overnight.

2.3

PDc

1. As light source, a two-dimensional, homogeneous LED array consisting of 432 LEDs as described in [9] is used (see Note 2). 2. Prepare a PS stock solution by dissolving PS in ultrapure water at 5 mM concentration. Store it in the dark at 20
C until usage. 3. Sterile cotton sticks: Autoclave cotton sticks at 120
C for 25 min and let them dry in a laminar flow workstation overnight.

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G

1.5 cm 1.5 cm

250 µl bacterial suspension

H B

70% EtOH, 3 min

250 µl photosensitizer

24 well microplate mounted to shaker

15% Agar 6 cm ~ 10 - 100 J cm-2

I

C

Photosensitizer Bacteria

250 µL

250 µl DPBS

vortex vigorously

serial dilutions (1:10) 24 h

D

~ 10 - 100 J cm-2

J

CFU

E

serial dilutions (1:10) 24 h

F

CFU

Fig. 1 Scheme of the described methods for the PDc of flat objects (a–f) and round objects (g–j) (modified from [5]): (a) Cut the vegetable, e.g., cucumber,

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Methods In the following, two experimental strategies for an in situ photodynamic decontamination of objects with different geometries are described (see Notes 3 and 4). 1. Grow E. coli in 20 mL THB at 37
C under constant agitation at 200 rpm in a shaking incubator overnight.

3.1 Photodynamic Decontamination on Flat Surfaces

2. Dilute the bacterial suspension to an optical attenuation of 0.05 at 600 nm (measured with an Infinite M200 microplate reader, Tecan, Switzerland, in 96-well microplates, Greiner Bio-One, Kremsmuenster, Austria). 3. Grow the diluted suspension for 2 h at 37
C under constant agitation at 200 rpm to the early logarithmic growth phase. 4. Prepare the vegetable (Fig. 1a, b) as described in Subheading 2.2 (sample preparation). 5. Carefully transfer 250 μL of the bacterial suspension on the vegetable surface (Fig. 1c) using a pipette. 6. Apply 250 μL of the PS at concentrations of interest (e.g., 10 μM, 50 μM, 100 μM) to the bacterial suspension (Fig. 1c). 7. Illuminate the plate from above (Fig. 1d) using a LED array (time range of illumination period 10–60 min, depending on the irradiance of the light source and the intended radiant exposure) (see Notes 5 and 6). The illumination period is calculated from the following equation:

ä Fig. 1 (continued) into 1.5  1.5 cm2 pieces. (b) Place the vegetable in a Petri dish with the unbroken epidermis facing up and embed it with 15% agar-agar. Decontaminate any preexisting microorganisms by applying 70% ethanol for 3 min. (c) Pipet 250 μL of the bacterial suspension onto the surface. Add 250 μl PS solution to the surface of the object. (d) Illuminate the Petri dish without lid. (e) Remove bacteria from the surface by rubbing a sterile cotton stick on the surface and transferring it into a 1.5 mL micro-tube containing 450 μL DPBS. Repeat this step three times. (f) Dilute the sample serially and plate it on a THB plate. Evaluate by counting of the colony-forming units after 24-h incubation at 37
C. (g) Place beans or seeds into a 2 mL micro-tube and add 250 μL of bacterial suspension. Vortex to spread the suspension on the surface. (h) Transfer the beans into a 24-well plate, add 250 μL of PS solution, and illuminate under constant agitation. (i) Transfer the treated beans or seeds into 2 mL micro-tubes containing 250 μL of DPBS and vortex vigorously. (j) Dilute the sample serially and plate it on a THB plate. Evaluate by counting the colonyforming units after 24-h incubation at 37
C

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  desired radiant exposure mJ=cm2 illumination period ½ sec  ¼ irradiance of light source ½mW=cm2  ð1Þ 8. For the serial dilutions, prepare 8  1.5 mL micro-tubes filled with 450 μL DPBS for each sample. 9. Transfer bacteria from the sample by rubbing the sterile cotton stick on the treated surface and dipping the sticks into the DPBS of the first micro-tube (Fig. 1e). Repeat this step three times to get as many bacteria as possible from the surface into the tube. The cotton stick may be pressed against the wall of the micro-tube to squeeze out the liquid. 10. To get back as much sample from the cotton stick as possible the tip of the cotton stick can be cut off and placed in the 1.5 mL micro-tube after rubbing it thrice on the treated surface. At the bottom of the tube a hole can be molten with a hot needle. The closed 1.5 mL micro-tube with the tip of the cotton stick can be placed in an open 2 mL microtube and centrifuged at 833 rcf for 3 min. 11. Prepare a serial dilution (1:10) in seven steps by transferring 50 μL from one micro-tube into the next one containing 450 μL DPBS. Make sure that the suspension is mixed well by pipetting up and down before proceeding. 12. Mark six segments on the bottom of the THB plate. For each dilution step pipet five droplets of 10 μl into each segment (Fig. 1f). 13. Incubate the plates overnight at 37
C. 14. Analyze the plates by counting colony-forming units in each segment (Fig. 1f). 3.2 PDc on Round Objects

1. Grow E. coli in 20 mL THB at 37
C under constant agitation at 200 rpm in a shaking incubator overnight. 2. Dilute the bacterial suspension to an optical attenuation of 0.05 at 600 nm (measured with an Infinite M200 microplate reader, Tecan, Switzerland, in 96-well microplates). 3. Grow the diluted suspension for two hours at 37
C under constant agitation at 200 rpm to the early logarithmic growth phase. 4. Centrifuge the 2-h culture at 833 rcf for 3 min, carefully remove the supernatant, and resuspend the pellet in DPBS. 5. Put the fenugreek seeds, mung beans, or germinated mung beans into 2 mL micro-tubes and cover them with 250 μL of

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bacterial suspension. Vortex to spread the bacteria on the surface (Fig. 1g) (see Note 7). 6. Transfer five beans or seeds into the wells of a 12- or 24-well plate using forceps (Fig. 1h). 7. Apply 250 μL of the PS at concentrations of interest (10 μM, 50 μM, 100 μM) to wells. 8. Illuminate the plate from below using a LED array (time range of illumination period 10–60 min, depending on the irradiance of the light source and the intended radiant exposure) (see Note 8). The illumination period is calculated with Eq. 1. 9. For the serial dilutions, prepare 8  1.5 mL micro-tubes filled with 450 μL DPBS for each sample. 10. Add the beans or seeds to the first micro-tube and vortex vigorously, to get the bacteria from the surface into the DPBS suspension (Fig. 1i). 11. Prepare a serial dilution (1:10) in seven steps by transferring 50 μL from one micro-tube into the next one containing 450 μL DPBS. Make sure that the suspension is mixed well by pipetting up and down before proceeding. 12. Mark six segments on the bottom of the THB plate. For each dilution step pipet five droplets of 10 μL into each segment (Fig. 1j). 13. Incubate the plates overnight at 37
C. 14. Analyze the plates by counting colony-forming units in each segment (Fig. 1j).

4

Notes 1. The salad used in the experiments showed damage when pre-decontaminated with 70% ethanol. Use dishwashing solution as described above. The dishwashing solution is named, but in principle any product could be used. 2. The ideal distance between light source and sample depends on the light source. For the array used in the experiments the irradiance was most homogeneous at a distance of approximately 15 cm. The light intensity may be measured using a pyranometer, for example LI-189 light meter equipped with a PY pyranometer detector (LI-COR, Lincoln, Nebraska, USA). Make sure that the detector can measure the wavelength of the LEDs used in the array. 3. Each experiment must consist of at least three replications. 4. Include an experiment to test the recovery efficiency of bacteria from the surface. Therefore take 250 μL of the bacterial

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A

B

C

Fig. 2 Suggestion for a 3D illumination of food: (a) Use a 2D light source (LED array) and rotate the object. (b) Use a 2D light source and rotate the light source around the object. (c) Use a 3D light source

suspension and directly dilute it in series. Take another 250 μL, place them on the sample, and use the sterile cotton swab to get the sample as described in Subheading 3.1. Compare both CFUs. 5. The radiant exposure in J/cm2 is calculated by multiplying the irradiance by the time of illumination (see Eq. 1). 6. During illumination from above remove the lid from the Petri dish to prevent a loss of irradiance. 7. As an alternative approach to the method described above one may also dip the sample (fruits or vegetables) into the bacterial suspension, apply the PS, and illuminate. A further alternative is homogenization of the treated sample, dilution, and plating on agar plates. Determine the weight of sample. Count the CFU and CFU/g that are obtained, as described in [10]. 8. For an all-round and homogeneous illumination of 3D objects three different approaches shown in Fig. 2 are suggested: (a) 2D light source (LED array) and rotation of the object. (b) 2D light source (LED array) and rotation of the light source. (c) 3D light source.

Acknowledgments The authors are grateful to Martina Hasenleitner, Christoph Hamminger, and Markus Hoerl for proofreading and their input.

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References 1. United Nations—Department of Economic and Social Affairs—Population Division. World population prospects: the 2017 revision, key findings and advance tables. 2017 [cited 2018 21.03.]; Working Paper No. ESA/P/ WP/248]. Available from https://www.com passion.com/multimedia/world-populationprospects.pdf. 2. World Health Organisation. Advancing food safety initiatives: strategic plan for food safety including foodborne zoonoses 2013–2022. 2014: p. 31. 3. Laxminarayan R et al (2013) Antibiotic resistance—the need for global solutions. Lancet Infect Dis 13(12):1057–1098 4. Witte W (2000) Selective pressure by antibiotic use in livestock. Int J Antimicrob Agents 16 (Suppl 1):19–24 5. Tortik N, Spaeth A, Plaetzer K (2014) Photodynamic decontamination of foodstuff from Staphylococcus aureus based on novel formulations of curcumin. Photochem Photobiol Sci 13(10):1402–1409

6. Luksiene Z, Brovko L (2013) Antibacterial photosensitization-based treatment for food safety. Food Eng Rev 5(4):185–199 7. Luksiene Z, Paskeviciute E (2011) Microbial control of food-related surfaces: NaChlorophyllin-based photosensitization. J Photochem Photobiol B 105(1):69–74 8. Glueck M et al (2017) New horizons in microbiological food safety: photodynamic decontamination based on a curcumin derivative. Photochem Photobiol Sci 16(12):1784–1791 9. Pieslinger A et al (2006) Characterization of a simple and homogeneous irradiation device based on light-emitting diodes: a possible low-cost supplement to conventional light sources for photodynamic treatment. Med Laser Appl 21(4):277–283 10. Buchovec I et al (2016) Effective photosensitization-based inactivation of Gram (-) food pathogens and molds using the chlorophyllin-chitosan complex: towards photoactive edible coatings to preserve strawberries. Photochem Photobiol Sci 15(4): 506–516

Part VI Molecular Techniques and Tools in Photodynamic Therapy Research

Chapter 37 Super-Resolution Imaging of Intracellular Lipid Nanocarriers to Study Drug Delivery in Photodynamic Therapy Enzo M. Scutigliani, Jakub A. Kochan, Emilie C. B. Desclos, Art Jonker, Michal Heger, and Przemek M. Krawczyk Abstract Liposomal nanocarriers are intensively investigated as delivery vehicles for photoactivatable agents used in photodynamic therapy (PDT). The uptake, intracellular distribution, and processing of the nanocarriers are of paramount importance for the effectiveness of the therapy; visualization and analysis of these processes can, therefore, stimulate the development of improved PDT modalities. Here we describe a simple protocol, based on super-resolution imaging, that can be used for detailed quantification of concentration, distribution, and size of individual lipid nanocarriers in adherent mammalian cells. Key words Photodynamic therapy, Photosensitizers, Super-resolution microscopy

1

Introduction During the last decade, photodynamic therapy (PDT) has received considerable amount of interest as a selective anticancer approach. However, several drawbacks prevent PDT from being routinely applied. Most of these drawbacks relate to the poor intra-tumoral delivery of photosensitizer molecules [1]. To overcome this problem, intensive efforts are directed towards the development of photosensitizer nanocarriers serving as drug delivery agents [1, 2]. The incorporation of photosensitizers into liposomes has been shown to be a promising approach, but a deeper understanding of how these carriers perform their role is required for optimal utilization in PDT. All liposomes share the common trait that their cellular uptake depends on their interaction with membranes of target cells. Therefore, the ability to visualize and study the behavior of nanocarrieroriginating lipids in tumor cells can provide a deeper understanding of nanocarrier performance. By incorporation of a compatible

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fluorophore in the liposome of interest, the behavior of the nanocarrier with respect to lipid dynamics can be observed with the use of various microscopic imaging techniques, including superresolution by ground-state depletion followed by individual molecule return (GSDIM) microscopy [3, 4]. Earlier studies have indeed demonstrated the benefits of visualizing lipid nanocarriers [5, 6], including fluorescence microscopy and super-resolution microscopy techniques [7–10]. Here, we provide a simple protocol for visualizing and analyzing the subcellular localization and morphology of nanocarrieroriginating lipids at nanometer resolution with the use of GSDIM super-resolution microscopy. GSDIM is mostly realized on cells attached to glass coverslips. Other setups are possible, such as imaging tissue samples, but require adapted protocols. For these reasons, only the protocols for cells plated on coverslips are described here. This method, based on a previously reported technique and protocol [11], can yield information on membranenanocarrier interactions, supporting the development of lipid nanocarriers for PDT.

2

Materials Store all materials at room temperature unless stated otherwise.

2.1 UltraClean Coverslips

1. Coverslips, 24-mm diameter, thickness #1.5 (0.16–0.19 mm). 2. 2 M HCl. 3. 0.1 M Na2B4O7, pH = 8.5. 4. 2 M NaOH. 5. 20% H3PO4; Warning: This reagent is highly toxic, so use appropriate protection. 6. 70% High-grade ethanol.

2.2 Fluorescently Labeled Liposomes

2.3 Paraformaldehyde Fixation

The versatility of this protocol was validated by using different formulations of endothelium-targeting liposomes (ETLs), in which phosphatidylcholine (PC) conjugated to the fluorophore nitrobenzoxadiazole (NBD) was added at the expense of dipalmitoylphosphatidylcholine (DPPC) as described elsewhere [12, 13]. 1. Phosphate-buffered saline (PBS), pH = 7.4, CaCl2/MgCl2free. 2. 4% Paraformaldehyde (PFA), methanol-free. 3. 0.5% Triton X-100 in PBS. 4. 5% Bovine serum albumin (BSA) in PBS.

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2.4

Immunolabeling

705

1. 5% BSA. 2. Primary and secondary antibodies, prepared as specified by the manufacturer. 3. 0.1% Tween-20. 4. Parafilm.

2.5 OxeA Imaging Buffer

1. Sodium DL-lactate, 60% solution: Store 100 μL aliquots at 4  C. 2. 0.5 M Monoethanolamine (MEA), pH = 8: Store 110 μL aliquots at 20  C. 3. 5 M NaOH. 4. OxyFluor (Sigma-Aldrich): Store 40 μL aliquots at

20  C.

5. PBS. 2.6 Sample Mounting

1. Chamlide CM-B25-1 magnetic chamber (Live Cell Instrument, Seoul, Korea). 2. Heavy mineral oil.

3

Methods Carry out all procedures at room temperature unless specified otherwise. Prepare and store all reagents at room temperature unless indicated otherwise. Prepare all solutions using ultrapure water. The fixation, labeling, and imaging solutions should always be freshly prepared from stock solutions.

3.1 Preparation of Ultraclean Coverslips

1. See Note 1 for the rationale of preparing ultraclean coverslips. 2. Place coverslips in a clean glass petri dish. 3. Immerse in 2 M HCl overnight. 4. Wash with ddH2O. 5. Immerse in 0.1 M Na2B4O7 (pH = 8.5) for at least 2 h. 6. Wash with ddH2O. 7. Immerse in 2 M NaOH for at least 2 h. 8. Wash with ddH2O. 9. Immerse in 20% H3PO4. 10. Wash with ddH2O. 11. Store in 70% ethanol (high grade). 12. Each of the reagents can be reused for up to 10 procedures.

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3.2 Plating Cells and Incubation with Liposomes

1. Place ultraclean coverslips in the wells. 2. Wash with 2 mL PBS per well to remove residual ethanol. 3. Seed a number of cells that are required to reach about 60% confluence on the day of the experiment. 4. Incubate cells for 24 h. 5. Expose cells to liposomes by replacing culture medium with a pre-dilution of liposomes in culture medium.

3.3 Paraformaldehyde Fixation

1. Wash the cells with 2 mL PBS. 2. Fix with 2 mL 4% PFA for 10 min. 3. Wash twice with 2 mL PBS for 5 min. 4. Incubate with 2 mL 0.5% Triton X-100 in PBS for 10 min. 5. Wash twice with 2 mL PBS for 5 min. 6. Incubate for at least 1 hour in 2 mL 5% BSA in PBS. 7. Proceed to the labeling steps.

3.4 Immunostaining (Optional)

1. See Note 2 for general consideration regarding immunostaining in super-resolution light microscopy. 2. Incubate with primary antibody in 5% BSA in PBS. 3. Wash twice with 2 mL 0.1% Tween-20 in PBS for 5 min. 4. Incubate with secondary antibody in 5% BSA in PBS as stated in step 1. 5. Wash twice with 2 mL 0.1% Tween-20 in PBS for 5 min. 6. Store the sample in 2 mL PBS. Protect from light.

3.5 Preparation of OxeA Imaging Buffers

1. See Note 3 for the rationale and practical considerations regarding the imaging buffers. 2. Add 50 μL of MEA to a 1.5 mL tube containing 100 μL of sodium DL-lactate. 3. Add 3 μL of NaOH. 4. Add 15 μL of OxeA. 5. Add 350 μL of PBS. 6. Mix well.

3.6

Imaging Setup

1. Mount a coverslip on the magnetic ring holder. 2. Wash the sample with 500 μL of imaging buffer and subsequently cover the sample with 500 μL of imaging buffer to prevent dilution of the buffer. 3. Cover the imaging buffer with 500 μL of heavy mineral oil (see Note 4). 4. Place the ring on the stage of the microscope.

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5. Allow the sample to settle for about 15 min to minimize drift during image acquisition. 6. Proceed to image acquisition as recommended by the microscope manufacturer. 7. See Note 5 for an example image and its interpretation.

4

Notes 1. Coverslips are coated during the manufacturing process to prevent sticking during storage. Removing this layer by washing the coverslips with several reagents reduces background noise and improves image quality. 2. Aspecific labeling appears more pronounced in superresolution light microscopy compared to other light microscopy methods. We therefore advise to optimize antibody concentration and incubation time for optimal results. In general, we obtained satisfying results by limiting incubation times for the first and secondary antibodies to 45 and 30 min, respectively. To perform the antibody staining, place a 60 μL droplet of antibody solution on a Parafilm layer. Use a bent injection needle to wedge the coverslip off the bottom of the 6-well plate and use forceps to gently place it on the droplet. The cells should be in contact with the labeling solution. Do not press on the coverslip. Cover the coverslip with an opaque lid. After incubation, use the forceps and needle to place the coverslip back into the 6-well plate. 3. GSDIM requires the use of imaging buffers that reduce photobleaching of fluorophores by oxygen scavenging [11]. The OxeA buffer is effective for 2–4 h and can be used for multicolor imaging. However, other imaging buffers can be taken into consideration depending on the sample [11]. 4. To extend the oxygen-scavenging capacity of the imaging buffer, the sample is sealed with gas-impermeable oil to prevent the entrance of environmental oxygen in the sample. 5. An example is provided in Fig. 1. Super-resolution imaging allowed us to accurately determine the localization of NBD-conjugated PC originating from ETLs. Incubation of bone osteosarcoma (U2-OS) cells with NBD-ETLs resulted in the accumulation of vesicle-like structures on the cell (Fig. 1a). We visualized and quantified the diameter of these structures to demonstrate the gain in resolution (Fig. 1b, c).

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Fig. 1 Super-resolution imaging of photosensitizer-carrying liposomes. Bone osteosarcoma (U2OS) cells were seeded on ultraclean coverslips, exposed to 50 μM of NBD-tagged ETLs for 30 min, and processed for GSDIM microscopy as described in this protocol. NBD was visualized using a Leica SR GSD equipped with a Leica PL APO 160/1.40 oil immersion objective and mounted with a sCMOS pco.edge42 camera. 20,000–50,000 frames were acquired per image and processed using the ImageJ plug-in ThunderStorm [14]. (a) Comparison of super-resolution and widefield image. Scale bar represents 1 μm. (b) Histogram of vesicle diameter. (c) Histogram of square region of interest depicted in a References 1. Kruger CA, Abrahamse H (2018) Utilisation of targeted nanoparticle photosensitiser drug delivery systems for the enhancement of photodynamic therapy. Mol Basel Switz 23. h t t p s : // d o i . o r g / 1 0 . 3 3 9 0 / molecules23102628 2. Hong EJ, Choi DG, Shim MS (2016) Targeted and effective photodynamic therapy for cancer using functionalized nanomaterials. Acta Pharm Sin B [Internet] 6:297–307. [cited 2020 Dec 8]. https://doi.org/10.1016/j. apsb.2016.01.007 3. Hell SW, Kroug M (1995) Ground-statedepletion fluorescence microscopy: a concept for breaking the diffraction resolution limit. Appl Phys B [Internet] 60:495–497. [cited 2020 Dec 8]. https://doi.org/10.1007/ BF01081333

4. Fo¨lling J, Bossi M, Bock H, Medda R, Wurm CA, Hein B, Jakobs S, Eggeling C, Hell SW (2008) Fluorescence nanoscopy by groundstate depletion and single-molecule return. Nat Methods 5:943–945. https://doi.org/ 10.1038/nmeth.1257 5. Bardhan R, Lal S, Joshi A, Halas NJ (2011) Theranostic nanoshells: from probe design to imaging and treatment of cancer. Acc Chem Res 44:936–946. https://doi.org/10.1021/ ar200023x 6. Silva AKA, Kolosnjaj-Tabi J, Bonneau S, Marangon I, Boggetto N, Aubertin K, Cle´ment O, Bureau MF, Luciani N, Gazeau F, Wilhelm C (2013) Magnetic and photoresponsive theranosomes: translating cell-released vesicles into smart nanovectors for cancer therapy. ACS Nano 7:4954–4966. https://doi.org/10.1021/nn400269x

Super-Resolution Imaging of Intracellular Lipid Nanocarriers 7. Sharonov A, Hochstrasser RM (2006) Widefield subdiffraction imaging by accumulated binding of diffusing probes. Proc Natl Acad Sci U S A 103:18911–18916. https://doi. org/10.1073/pnas.0609643104 8. Kuo C, Hochstrasser RM (2011) Superresolution microscopy of lipid bilayer phases. J Am Chem Soc 133:4664–4667. https://doi. org/10.1021/ja1099193 9. Liu J-X, Xin B, Li C, Xie N-H, Gong W-L, Huang Z-L, Zhu M-Q (2017) PEGylated perylenemonoimide-dithienylethene for super-resolution imaging of liposomes. ACS Appl Mater Interfaces 9:10,338–10,343. https://doi.org/10.1021/acsami.6b15076 10. Xu H, Chen B, Gong W, Yang Z, Qu J (2020) Nanoliposomes Co-encapsulating photoswitchable probe and photosensitizer for super-resolution optical imaging and photodynamic therapy. Cytom Part J Int Soc Anal Cytol 97:54–60. https://doi.org/10.1002/cyto.a. 23864 11. Nahidiazar L, Agronskaia AV, Broertjes J, van den Broek B, Jalink K (2016) Optimizing imaging conditions for demanding multi-

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color super resolution localization microscopy. PloS One 11:e0158884. https://doi.org/10. 1371/journal.pone.0158884 12. Broekgaarden M, de Kroon AIPM, van Gulik TM, Heger M (2014) Development and in vitro proof-of-concept of interstitially targeted zinc- phthalocyanine liposomes for photodynamic therapy. Curr Med Chem 21: 377–391 13. Broekgaarden M, Weijer R, Krekorian M, IJssel B, Kos M, Alles LK, Wijk AC, Bikadi Z, Hazai E, Gulik TM, Heger M (2016) Inhibition of hypoxia-inducible factor 1 with acriflavine sensitizes hypoxic tumor cells to photodynamic therapy with zinc phthalocyanine-encapsulating cationic liposomes. Nano Res 6:1639–1662. https://doi. org/10.1007/s12274-016-1059-0 14. Ovesny´ M, Krˇ´ızˇek P, Borkovec J, Svindrych Z, Hagen GM (2014) ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging. Bioinforma Oxf Engl 30: 2389–2390. https://doi.org/10.1093/bioin formatics/btu202

Chapter 38 Detection of Paraptosis After Photodynamic Therapy David Kessel Abstract Photodynamic therapy (PDT) is a procedure for the selective photosensitization of neoplastic tissues. Subsequent irradiation with visible light can lead to cell death along with vascular shutdown and other responses that lead to selective eradication of malignant cells. Among the cellular responses to PDT are necrosis, apoptosis, and autophagy. These pathways have generally been associated with cell death, although autophagy can also be cytoprotective. A fourth effect that has hitherto been somewhat neglected is termed “paraptosis,” a lethal response that can be identified by detecting an extensive collection of cytoplasmic vacuoles. Unlike autophagy, these vacuoles are bound by single membranes. Paraptosis has been characterized as a response to misfolded endoplasmic reticulum proteins that must be “cleared” if the affected cell is to survive. At present, there is no simple biochemical test for paraptosis. This chapter describes the procedure for detection of paraptosis using phase-contrast microscopy, along with some confirmatory approaches. Key words Apoptosis, Autophagy, Endoplasmic reticulum stress, Vacuolization, Photodamage, Cell death signaling

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Introduction There have been numerous reports on death and survival pathways evoked by photodamage. A supralethal photodynamic therapy (PDT) dose can lead to necrosis, an effect characterized by loss of plasma membrane integrity, often accompanied by the loss of enzyme functions needed for the functioning of other metabolic pathways [1]. Apoptosis is a programmed phenomenon leading to fragmentation of DNA, nuclei, and cells into particles that can be engulfed and digested by macrophages [2, 3]. Autophagy is a recycling process normally evoked under starvation conditions to promote cell survival. While this effect is usually considered to be cytoprotective, under some circumstances it can be associated with cell death [4]. More recently, paraptosis has been identified as another death pathway. This involves formation of cytoplasmic vacuole formation that leads to loss viability [5, 6]. While there are reliable assays for

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_38, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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apoptosis, autophagy, and necrosis, paraptosis is not so easily measured. This phenomenon was first described in 2004 [7] and can be evoked by a variety of processes, including exposure to natural products that are being proposed as potential antitumor agents [8]. In the context of PDT, paraptosis appears to be mainly associated with photodamage to the endoplasmic reticulum (ER) [5, 6], although one report indicated a paraptotic effect after targeting of nuclei [9]. To assess paraptosis, investigators currently rely on microscopy to identify the extensive pattern of cytoplasmic vacuole formation that can be detected, often within a few hours after photodamage [4]. The importance of paraptosis being evoked by PDT is that it represents a death mode accessible where apoptosis is impaired [8, 10, 11]. Figure 1 illustrates the morphology of paraptosis compared to apoptosis. The phase-contrast image shows the cellular and nuclear fragmentation that occurs during apoptosis while the fluorescent nuclear labeling (Hoechst 33342) indicates the corresponding chromatin condensation and fragmentation that occur. In contrast, paraptosis results in no demonstrable nuclear alterations but an extensive pattern of vacuole formation. Paraptosis can be distinguished from autophagy by electron microscopy; the vacuoles are bound only by a single membrane while autophagosomes are comprised of phospholipid bilayers [3]. Paraptosis can be delayed by inhibition of protein synthesis, e.g., by cycloheximide, actinomycin D, or salubrinal [6, 12]. The latter agent was initially proposed to be a means for protecting cells from the effects of ER stress [13] but may in this context be functioning as an inhibitor of protein synthesis. It has been proposed that paraptosis is a response to the appearance of misfolded proteins in the ER, and is associated with alterations in the expression of proteins involved in MAPK/JNK pathways [14]. A test we have used to characterize paraptosis involves the labeling of cells with markers for the ER. These vacuoles can be labeled with a fluorescent probe [13]. The pattern of vacuole labeling 4 h after ER photodamage in the presence vs. absence of 5 μM cycloheximide with ERTracker Green, a fluorescent probe for the ER, is shown in Fig. 2. The labeling pattern was impaired, but viability was not preserved [13]. We have found that brief inhibition of protein synthesis does not protect from death from paraptosis, but the extent of inhibition of vacuole formation depends on the PDT dose. The chronology of vacuole formation is illustrated in Fig. 3. Vacuoles initially circle the nucleus, with more extensive vacuolization proceeding with time. After 48 h, many cells have detached from the dish and show extensive loss of cytoplasm. Figure 4 demonstrates the ability of a kit provided by ENZO to label vacuoles formed from autophagosomes induced by rapamycin in the presence of chloroquine. Chloroquine prevents autophagosomes from fusing with

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Fig. 1 Morphology of apoptosis (left panels) and paraptosis. Upper images are phase contrast, lower images represent fluorescence of the nuclear probe Hoechst 33342. The figure was reproduced from ref. 6 with permission from Wiley

Fig. 2 Labeling of the periphery of cytoplasmic vacuoles associated with paraptosis using ERTracker Green. The effect of 5 μM cycloheximide on vacuole formation after photodamage is also shown

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Fig. 3 The chronology of paraptosis: images acquired at specified intervals following PDT with benzoporphyrin derivative at an LD90 photosensitizer dose. Both floating and adhering cells are shown at the 48-h interval. The figure was reproduced from Ref. [5] with permission from Wiley

Fig. 4 Use of the ENZO Cyto-ID kit for distinguishing paraptosis from autophagy. Upper images were acquired 24 h after PDT with an LD90 dose of benzoporphyrin derivative. Lower images represent the effect of a mixture of rapamycin and chloroquine, as indicated. The green probe labels autophagic vacuoles but not those created by paraptosis. Bars ¼ 5 μm. The figure was reproduced from Ref. [5] with permission from Wiley

lysosomes [3]. There is no labeling of the vacuoles associated with paraptosis. For a more definitive assessment, electron microscopy can be employed. Figure 5 shows the difference between the double membrane that represents the boundary of autophagosomes in

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Fig. 5 Delineation of vacuoles created by autophagy (left panel) vs. paraptosis (right panel) using electron microscopy. The figure was reproduced from Ref [5] with permission from Wiley

contrast to the single membrane at the periphery of paraptotic vacuoles. In the context of chemotherapy, it was reported that paraptosis can result in relocation of the nuclear protein HMGB1 to the cell periphery [15]. We did not observe notable HMGB1 relocalization after ER photodamage, suggesting that this assay will not be useful in the context of PDT [16]. MAPK antagonists (UO126 and SP600125) can offer partial protection from paraptosis and cell death after low (~LD50) PDT doses, but not when the effect approaches LD90 values (Fig. 6). Studies involving the effects of PDT seldomly involve microscopy. Results of clinical studies or work related to tumor-bearing animals are usually assessed in terms of survival, tumor volume, or other parameters, but scarcely involve microscopy at a level of magnification required for cytoplasmic vacuole detection. Moreover, as shown in this report, paraptosis and apoptosis can occur simultaneously. The appearance of vacuoles might be ascribed to autophagy or senescence if the observer does not attempt to rule out these possibilities. Paraptosis can be detected after photodamage from many common photosensitizing agents: Photofrin, mTHPC, pyropheophorbide HPPH, hypericin, and BPD [5]. The only exception appears to be agents that initiate only lysosomal photodamage.

2

Materials

2.1 Cell Culture Procedures

1. OVCAR-5 (ovarian cancer), A549 (non-small cell lung cancer), and 1c1c7 (murine hepatoma) cells have been examined but any neoplastic cell line in culture can be used.

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Fig. 6 Effects of two MAPK antagonists on the efficacy of photodynamic therapy as a function of the PDT dose using BPD as the photosensitizing agent

2. RPMI 1640 medium, heat-inactivated fetal bovine serum, 2.5% trypsin, and antibiotics (typically penicillin and streptomycin). 3. Phosphate-buffered saline (Gibco). 4. Hoechst 33342 (stock solution 2 mM in water; use at a 1:1000 dilution). 5. Rapamycin (stock solution 0.5 mM in water; use at a 1:1000 dilution). 6. Chloroquine (stock solution 25 mM in water; use at a 1:1000 dilution). 7. U0126 (stock solution 10 mM prepared in DMSO and stored under nitrogen at 4  C): Use at a 1:1000 dilution. 8. Cycloheximide (stock solution 5 mM in water; use at a 1:1000 dilution). 9. Sterile glass coverslips (22  22 mm) placed in sterile 35 mm plastic tissue culture dishes. 2.2 Photosensitizing Agents and Irradiation

1. Benzoporphyrin derivative (BPD; VWR) is dissolved in DMSO at a 1 mM concentration. Incubate cells with a 0.5 μM concentration for 1 h. Replace medium and irradiate at 690 nm. 2. For most cell monolayers, a light dose of 90–120 mJ/cm2 at 690  10 nm is sufficient. 3. Hypericin (Beantown, Hudson, NH) is dissolved in DMSO at a 1 mM concentration. Incubate cells overnight with a 1 μM concentration. For irradiation, 120 μJ/cm2 at 600 nm is a good starting dose.

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4. Light is delivered to 35 mm dishes in a 50 mm diameter circle at 2 mW/cm2 (see Note 1). 5. Power meter, e.g., model H410 laser power, and energy meter (Scientech) (see Note 2). 2.3

Microscopy

1. Nikon Eclipse E600 or equivalent with objectives for phase contrast and fluorescence (see Note 3). 2. Image acquisition system, e.g., Metamorph (Molecular Devices, San Jose, CA). 3. Cooled microscope stage (see Note 4). 4. Chiller for maintaining dishes at 15  C (optional). 5. ENZO autophagy detection kit CYTO-IR ENZ-51031.

3 3.1

Methods Cell Culture

1. The cell lines we have examined are grown in 75 cm2 tissue culture flasks at 37  C in a humidified atmosphere containing 5% CO2 and 95% air (standard culture conditions) using RPMI 1640 medium supplemented with 5-10% heat-inactivated fetal bovine serum and antibiotics. 2. Cells are passaged when at near confluency. Wash once with sterile PBS (lacking Ca2+/Mg2+). 3. Dissociate cells for the minimal time needed to remove from dishes (normally 3–5 min) with 2 mL of 0.05% trypsin/EDTA prepared from 2.5% trypsin (Gibco). 4. Add 10 mL of complete culture medium, collect cells by centrifugation, and resuspend pellet in fresh medium for plating and further studies.

3.2 Photosensitization and Irradiation

1. Trypsinize the culture as described above and add to each tissue culture dish 1 mL of the dispersed cells. This number should be adjusted so that there will be 70–80% confluency when microscopic examination occurs. 2. Place coverslips in plastic dishes and allow the cells to attach overnight under standard culture conditions. 3. Replace medium and add photosensitizer according to individual protocols. Typical experimental conditions are listed below. Concentrations of photosensitizer are adjusted so that no more than 5 μL (0.5% v/v) of the stock solution is added to any dish and the solvent volume is consistent across all culture dishes. 4. Irradiation is usually carried out so as to result in a 75–90% loss of viability, although this can be adjusted to investigate the effects from lower PDT doses (see Note 5).

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5. Replace the medium before irradiation to eliminate photodamage to cells by light-activated photosensitizer molecules in the medium. 3.3

Microscopy

1. At intervals after photodamage, coverslips are removed from dishes, labeled with Hoechst 33342 and ENZO Cyto-ID green detection reagent or Hoechst 33342 and ERTracker Green, and examined by phase-contrast and fluorescence microscopy. 2. Coverslips are placed on microscope slides and images are acquired at 400 or 1000 magnification. The lower magnification permits having more cells in an image; more detail is revealed at 1000 magnification, although this is rarely necessary. 3. The chronology of paraptosis can be assessed by examining cells at timed intervals, e.g., 0, 1, 4, 8, 16, 24, and 48 h. 4. Since dying cells will detach from the plastic, an examination of floaters collected by centrifugation (1000  g for 10 min) is also useful for assessing modes of cell death. This can reveal whether there is also ongoing apoptosis.

3.4 Fluorescent Probes

1. A 10-min incubation with 1 μM of Hoechst 33342 (in tissue culture medium) before imaging will reveal the presence of apoptotic cells, indicated by condensed and/or fragmented chromatin. 2. ER tracker is provided with several different fluorescence characteristics. The “blue-white” form has a broad fluorescence emission band and conflicts with Hoechst 33342. ERTracker Green can be used with Hoechst 33342. Either is used at a 2 μM concentration for 10–30 min. 3. When the ENZO kit for the detection of autophagy is used, cells are treated with rapamycin (0.5 μM for 16–18 h) + chloroquine (increases lysosomal pH) at 25 μM in medium under standard culture conditions for a positive control. 4. After the incubation period, gently remove and replace the media.

3.5 Inhibition of Paraptosis

1. During incubation with photosensitizers, add cycloheximide (5 μM) or U0126 (20 μM) for the final hour. Add back after irradiation. 2. Incubate cells for 4–20 h under standard culture conditions. 3. Examine cells by phase-contrast microscopy (see Notes 6–8).

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Notes 1. Depending on the light source, the intensity can fall off at the outer edges of the field (Gaussian intensity profile). Using a relatively small coverslip and a 50 mm diameter circle of illumination results in a relatively uniform field. Studies reported here were carried out with a QH light source that produces a 3 cm diameter beam. Interference filters were used to limit the wavelength to a bandwidth of 20 nm. A 10 cm layer of water was also placed in the light beam to remove IR wavelengths from the beam to minimize heating effects. 2. Any reliable power meter can be used. The uniformity of irradiation over the light field can be monitored using a mask with a 2–3 mm diameter and assessing the light dose as a function of distance from the center. 3. While a microscope with an inverted stage can be used, use of coverslips permits the use of configuration that may be more widely available. With an inverted stage, it is feasible to more closely monitor the progression of paraptosis as a function of time, which possibly is an advantage. 4. A chilled stage will minimize metabolic changes during observation. This is usually not necessary, but changes associated with any metabolic processes can be circumvented by cooling cells to 15  C. 5. Avoid use of light doses that result in loss of viability that exceeds ~99%. This can produce off-target effects causing photodamage to enzymes that are involved in paraptosis. 6. Cycloheximide can delay the appearance of paraptosis but will not protect cells from subsequent cell death. After exposure to 10 μM cycloheximide, paraptosis may not appear for 4 h after ER photodamage but is observed 24 h later. MAPK antagonists (U0126 and SP600125) are effective only when the PDT dose is comparatively low (Fig. 6). U0126 is a MAPK antagonist that can delay vacuole formation and partially protect cells from photoinduced death at low (LD50) but not higher PDT doses. 7. Current studies are consistent with the proposal that photodamage to the ER is necessary for the appearance of paraptosis following irradiation of photosensitized cells. As new photosensitizers are examined, it would be helpful to also characterize sites of subcellular photodamage. It may be sufficient to determine that the localization of a photosensitizer fluorescence is coincident with that of a fluorescent probe for the ER. Several probes for ER, mitochondria, Golgi, plasma

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membrane, and lysosomes differing in excitation and emission spectra are now available. 8. Western blots have shown cross-linking of the ER protein BiP at very high PDT doses (LD99). Under these conditions, there is no appearance of paraptosis. This result suggests that crosslinking of ER proteins may impair structural alterations involved in vacuole formation. References 1. Luo Y, Kessel D (1997) Initiation of apoptosis versus necrosis by photodynamic therapy with chloroaluminum phthalocyanine. Photochem Photobiol 66:479–483 2. Agarwal ML, Clay ME, Harvey EJ, Evans HH, Antunez AR, Oleinick NL (1991) Photodynamic therapy induces rapid cell death by apoptosis in L5178Y mouse lymphoma cells. Cancer Res 51:5993–5996 3. Feng Y, He D, Yao Z, Klionsky DJ (2014) The machinery of macroautophagy. Cell Res 24: 24–41 4. Reiners JJ Jr, Agostinis P, Berg K, Oleinick NL, Kessel D (2010) Assessing autophagy in the context of photodynamic therapy. Autophagy 6:7–18 5. Kessel D (2019) Apoptosis, paraptosis and autophagy: death and survival pathways a associated with photodynamic therapy. Photochem Photobiol 95:119–125 6. Kessel D, Oleinick NL (2018) Cell death pathways associated with photodynamic therapy: an update. Photochem Photobiol 94:213–218 7. Sperandio S, Poksay K, de Belle I, Lafuente MJ, Liu B, Nasir J, Bredesen DE (2004) Paraptosis: mediation by MAP kinases and inhibition by AIP-1/Alix. Cell Death Differ 11:1066–1075 8. Lee D, Kim IY, Saha S, Choi KS (2016) Paraptosis in the anti-cancer arsenal of natural products. Pharmacol Ther 162:120–133 9. Pierroz V, Rubbiani R, Gentili C, Patra M, Mari C, Gasser G, Ferrari S (2016) Dual mode of cell death upon the photo-irradiation of a RuII polypyridyl complex in interphase or mitosis. Chem Sci 7:6115–6124

10. Ghosh K, De S, Das S, Mukherjee S, Sengupta Bandyopadhyay S (2016) Withaferin A induces ROS-mediated paraptosis in human breast cancer cell-Lines MCF-7 and MDA-MB-231. PLoS One 11:e0168488 11. Han H, Chou CC, Li R, Liu J, Zhang L, Zhu W, Hu J, Yang B, Tian J (2018) Chalcomoracin is a potent anticancer agent acting through triggering Oxidative stress via a mitophagy- and paraptosis-dependent mechanism. Sci Rep 22:9566 12. Boyce M, Bryant KF, Jousse C, Long K, Harding HP, Scheuner D, Kaufman RJ, Ma D, Coen DM, Ron D, Yuan J (2005) A selective inhibitor of eIF2alpha dephosphorylation protects cells from ER stress. Science 307:935–939 13. Kessel D, Reiners JJ Jr (2017) Effects of combined lysosomal and mitochondrial photodamage in a non-small-cell lung cancer cell line: the role of paraptosis. Photochem Photobiol 93: 1502–1508 14. Ram BM, Ramakrishna G (2014) Endoplasmic reticulum vacuolation and unfolded protein response leading to paraptosis like cell death in cyclosporine A treated cancer cervix cells is mediated by cyclophilin B inhibition. Biochim Biophys Acta 1843:2497–2512 15. Hoa N, Myers MP, Douglas TG, Zhang JG, Delgado C, Driggers L, Callahan LL, Van Deusen G, Pham JT, Bhakta N, Ge L, Jadus MR (2009) Molecular mechanisms of paraptosis induction: implications for a non-genetically modified tumor vaccine. PLoS One 4:e4631 16. Kessel D (2019) Pathways to paraptosis after ER photodamage in OVCAR-5 cells. Photochem Photobiol 95:1239–1242

Chapter 39 Optimal Use of 20 ,70 -Dichlorofluorescein Diacetate in Cultured Hepatocytes Megan J. Reiniers, Lianne R. de Haan, Laurens F. Reeskamp, Mans Broekgaarden, Ruurdtje Hoekstra, Rowan F. van Golen, and Michal Heger Abstract Oxidative stress is a state that arises when the production of reactive transients overwhelms the cell’s capacity to neutralize the oxidants and radicals. This state often coincides with the pathogenesis and perpetuation of numerous chronic diseases. On the other hand, medical interventions such as radiation therapy and photodynamic therapy generate radicals to selectively damage and kill diseased tissue. As a result, the qualification and quantification of oxidative stress are of great interest to those studying disease mechanisms as well as therapeutic interventions. 20 ,70 -Dichlorodihydrofluorescein-diacetate (DCFH2-DA) is one of the most widely used fluorogenic probes for the detection of reactive transients. The nonfluorescent DCFH2-DA crosses the plasma membrane and is deacetylated by cytosolic esterases to 20 ,70 -dichlorodihydrofluorescein (DCFH2). The nonfluorescent DCFH2 is subsequently oxidized by reactive transients to form the fluorescent 20 ,70 -dichlorofluorescein (DCF). The use of DCFH2-DA in hepatocyte-derived cell lines is more challenging because of membrane transport proteins that interfere with probe uptake and retention, among several other reasons. Cancer cells share some of the physiological and biochemical features with hepatocytes, so probe-related technical issues are applicable to cultured malignant cells as well. This study therefore analyzed the in vitro properties of DCFH2-DA in cultured human hepatocytes (HepG2 cells and differentiated and undifferentiated HepaRG cells) to identify methodological and technical features that could impair proper data analysis and interpretation. The main issues that were found and should therefore be accounted for in experimental design include the following: (1) both DCFH2-DA and DCF are taken up rapidly, (2) DCF is poorly retained in the cytosol and exits the cell, (3) the rate of DCFH2 oxidation is cell type-specific, (4) DCF fluorescence intensity is pH-dependent at pH < 7, and (5) the stability of DCFH2-DA in cell culture medium relies on medium composition. Based on the findings, the conditions for the use of DCFH2-DA in hepatocyte cell lines were optimized. Finally, the optimized protocol was reduced to practice and DCFH2-DA was applied to visualize and quantify oxidative stress in real time in HepG2 cells subjected to anoxia/reoxygenation as a source of reactive transients. Key words 20 ,70 -Dichlorodihydrofluorescein-diacetate, 20 ,70 -Dichlorofluorescein, Fluorogenic redox probe, Oxidative and nitrosative stress, Hepatocytes, Cellular uptake and efflux

Supplementary Information The online version of this chapter (https://doi.org/10.1007/978-1-0716-20991_39) contains supplementary material, which is available to authorized users. Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1_39, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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Introduction Oxidants in the form of reactive oxygen and nitrogen species (ROS and RNS, respectively), redox-active transition metals such as Fe2+ and Cu+, as well as activated peroxidases (e.g., cytochrome c peroxidase) are chemically reactive compounds that are able to (ir)reversibly alter the structure of (bio)molecules [1]. ROS/RNS are generated intracellularly by enzymatic sources (e.g., cytochrome P450 enzymes [2]) as well as nonenzymatic sources (e.g., oxidative phosphorylation in mitochondria [3]) and are essentially involved in cell signaling pathways when formed under controlled conditions. Transition metals are generally kept in a protein-bound state to control their reactivity, although a labile pool of free Fe2+ and Cu+ exists intracellularly and is maintained within tight concentration limits under non-pathological circumstances [4]. Under pathological circumstances, however, oxidant levels can rise due to the increased formation of ROS/RNS, augmentation of the labile Fe2+/Cu+ pool, and/or a reduction in the (extra)cellular antioxidative capacity. A state of oxidative stress consequently ensues [1] that has been causally related to cardiovascular-, neurodegenerative-, malignant-, and liver diseases [5]. Hepatocytes are particularly prone to developing oxidative stress because of their large number of mitochondria and ROS/RNS-producing enzymes as well as their principal role in copper and iron metabolism [1]. Accordingly, oxidative stress contributes to many forms of liver disease [1, 6] and therefore constitutes a major research topic within the field of hepatology. On the other end of the spectrum, radicals and oxidants are produced in a contrived clinical setting to destroy and eliminate cancerous tissue with photoproduced reactive transients. One prime example is photodynamic therapy [7], where tumors are photosensitized with a light-sensitive molecule referred to as a photosensitizer. Photosensitizers are mostly injected intravenously, after which they accumulate in the tumor tissue as a result of the enhanced permeability and retention effect [8]. The photosensitized tumor is subsequently illuminated with laser light, whereby the radiant energy enables the production of mainly singlet oxygen and superoxide anion in the presence of oxygen [7]. The extent of ROS production is proportional to the extent of cell death [9, 10], which occurs mainly by necrosis and apoptosis [11, 12]. In photodynamic therapy, ROS production is critical to therapeutic efficacy, and the degree of oxidative stress is therefore often studied in in vitro [13, 14] and in vivo models [15]. Photodynamic therapy is being investigated for liver cancer [16] using hepatocyte cell lines as representative test systems [17, 18].

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Fig. 1 The chemical structure, pH-dependent isoforms, and (estimated) acid dissociation constants (pKa) [26, 27] of DCFH2-DA, DCFH2, and DCF. Details are provided in the text

Because of their high reactivity and short half-lives oxidants are difficult to measure directly, particularly under in vitro conditions. Consequently, fluorogenic and luminogenic redox probes have emerged over the past decades as the preferred tool to measure oxidative stress in vitro due to their easy use, low cost, and nontoxicity [19, 20]. The fluorogenic 20 ,70 -dichlorodihydrofluorescein-diacetate (DCFH2-DA) is among the most frequently used redox probes. The hydrophobic acetate groups on DCFH2-DA allow for diffusion across the plasma membrane, after which they are cleaved by intracellular esterases to form the more hydrophilic DCFH2 that is believed to be retained within the cytosol (Fig. 1). DCFH2 is reactive toward many types of oxidants, including nitrogen dioxide ( NO2) [21], the carbonate radical anion (CO3 ) [21], the hydroxyl radical ( OH) [21], Fe2+ [22], Cu+ [22], thiyl radicals (e.g., the glutathione radical; GS ) [23], peroxidases (e.g., cytochrome c peroxidase) [24], and photoproduced singlet oxygen [13, 7]. Following two-electron oxidation, in which superoxide anion (O2 ) is generated as by-product [25], fluorescent DCF is formed that can be visualized or quantified as a nonspecific measure of oxidative stress (Fig. 1). Despite its widespread application, only limited research has focused on the practical aspects of the in vitro use of DCFH2-DA [28–36]. More specifically, studies on DCFH2-DA uptake, DCFH2 oxidation, and DCF retention in liver cell lines or hepatocytes are lacking. The probe kinetics in vitro are of particular concern given that hepatocytes express a multitude of membrane transporters that have important practical implications for the use of DCFH2-DA [37]. Inasmuch as primary hepatocytes swiftly dedifferentiate in l

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monolayer culture, hepatoma cell lines are commonly employed to study hepatic (patho)physiology in vitro. HepG2 is a human hepatocellular carcinoma-derived cell line that is one of the most widely used cell types for these purposes. The relatively new HepaRG cell line is an increasingly used human hepatocellular carcinomaderived cell line that has the ability to differentiate over a 4-week period into a heterogeneous monolayer culture consisting of islets of hepatocyte-like cells that are surrounded by cholangiocyte-like cells [38]. In light of the abovementioned knowledge gaps, this study aimed to optimize the practical applicability of DCFH2-DA in HepG2 cells and undifferentiated (2 weeks old) as well as differentiated (4 weeks old) HepaRG cells. The most important observations were that extracellular DCF enters HepG2 and HepaRG cells, that intracellular DCF is poorly retained, and that DCFH2 oxidation in resting cells is cell type-specific. DCF fluorescence intensity was moreover pH-dependent at pH < 7 and the stability of DCFH2-DA in cell culture medium relied on medium composition. A detailed experimental protocol that corrects for these limitations was developed with the intent to aid researchers in optimal experimental design and proper analysis of data generated using DCFH2-DA. To further demonstrate the probe’s utility under the optimized experimental conditions, DCFH2-DA was used to visualize and quantify oxidative stress in real time in HepG2 cells subjected to anoxia/reoxygenation.

2

Experimental Procedures References to supplemental material are indicated with the prefix “S.” The supplemental material is available in the Appendix published online. References [64–80] pertain to references used in the Appendix.

2.1 Reagents and Buffers

DCFH2-DA was purchased from Life Technologies/Molecular Probes (Eugene, OR) and dissolved in methanol (MeOH) at a 25-mM stock concentration or in dimethyl sulfoxide (DMSO) at a 50-mM stock concentration. DCF was acquired from SigmaAldrich (St. Louis, MO) and dissolved in DMSO at a 20-mM stock concentration. All other reagents are listed in the supplementary material, Table S1. The concentrations listed throughout this manuscript refer to final concentrations unless indicated otherwise.

2.2 Preparation of DCFH2

High-purity DCFH2 was prepared from DCFH2-DA in accordance with an optimized and validated protocol [22]. Briefly, 5 μmol of DCFH2-DA in MeOH was dissolved in 2.5 mL of 100 mM NaOH and incubated for 15 min at room temperature (RT) in the dark to ensure complete deacetylation to DCFH2. The solution was subsequently adjusted to pH ¼ 1 by the addition of 2.5 mL of 200 mM HCl to precipitate DCFH2. Next, liquid-phase extraction of

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DCFH2 was performed by the addition of 4 mL of chloroform (CHCl3) to the suspension. After vortexing the organic phase was aspirated and evaporated under a steam of N2 gas at RT in the dark. Subsequently, the crystallized DCFH2 was dissolved in MeOH to yield a 92-mM stock solution and stored under N2 gas at 20  C. 2.3 Determination of Molar Extinction Coefficients

The molar extinction coefficient (ε) of DCFH2-DA was determined in water, HEPES buffer (10 mM HEPES, 0.88% NaCl, pH ¼ 7.4, 0.292 osmol/kg), and MeOH. DCFH2-DA in DMSO was diluted in the solvent of interest (0–20 μM) and sample absorbance was determined at 258, 259, or 260 nm for water, HEPES buffer, or MeOH, respectively, by UV/VIS absorption spectroscopy (Lambda 18, Perkin Elmer, Waltham, MA) in a 1-cm path length quartz cuvette (Hellma Analytics, Mu¨llheim, Germany). The molar extinction coefficient was subsequently calculated over the complete concentration range in all solvents according to the BeerLambert eq. [39]. The molar extinction coefficient of DCFH2 in MeOH was recently reported [22]. In addition, the molar extinction coefficient of DCFH2 was determined in water, PBS (pH ¼ 12), and HEPES buffer (adjusted to pH ¼ 6 or pH ¼ 12 with HCl or NaOH, respectively). DCFH2 in MeOH was prepared in the solvent of interest (0–90 μM) and the molar extinction coefficient was determined at 287 nm for water, 286 nm for HEPES buffer (pH ¼ 6) and MeOH, 305 nm for PBS (pH = 12), and 304 nm for HEPES buffer (pH ¼ 12). Similarly, DCF in DMSO was diluted in water, PBS (pH ¼ 12), HEPES buffer, MeOH, and DMSO (0–20 μM) and its molar extinction coefficient was calculated at 503 nm, 284 nm, and 535 nm for aqueous solvent (water and HEPES buffer), MeOH, and DMSO, respectively, and at 305 nm in PBS (pH ¼ 12).

2.4 Spectral Properties of DCFH2DA, DCFH2, and DCF

Concentration-dependent (0–20 μM) ground-state absorption spectra were recorded for DCFH2-DA, DCFH2, and DCF in aqueous (Milli-Q, HEPES buffer) and organic solvents (MeOH, DMSO). In addition, pH-dependent absorption spectra of 20 μM DCF and DCFH2 as well as pH-dependent fluorescence excitation and emission spectra (Cary Eclipse, Varian, Palo Alto, CA) of 20 μM DCF were acquired in unbuffered water adjusted to pH ¼ 1–12 with 37% HCl.

2.5 Stability of DCFH2-DA and DCFH2 in Solvent

The stability of DCFH2-DA and DCFH2 was determined in organic and aqueous solvents. The stability of DCFH2 and DCFH2-DA in MeOH is reported elsewhere [22]. A 20-μM solution of each compound was prepared in DMSO, HEPES buffer, and water. Samples were stored at 20  C or 4  C in the dark and the extent of auto-oxidation (i.e., the formation of DCF) was determined spectrofluorometrically (λex ¼ 503  5 nm,

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λem ¼ 513  650 nm or λex ¼ 535  5 nm, λem ¼ 545 – 650 nm for water/HEPES or DMSO, respectively) at different time points over a period of 28 days. The fluorescence emission spectra were integrated and plotted as a percentage of the integrated spectra of a freshly prepared 20 μM DCF sample (reference standard). The short-term stability of DCFH2-DA was analyzed spectrofluorometrically in PBS and serum-free cell culture media in the form of WE, DMEM, and RPMI-1640 with or without HEPES (25 mM, pH ¼ 7.4) at ambient CO2 tension. The spectrofluorometer was employed in kinetics mode (λex ¼ 500  5 nm, λem ¼ 523  5 nm) using continuous magnetic stirring and Peltier-controlled temperature regulation. Solvents/reagents were added to the cuvette in the following order: t ¼ 0 min, 1494 μL of solvent (equilibrated at 37  C), and t ¼ 1 min, 6 μL of 5 mM DCFH2-DA in DMSO (20 μM). Fluorescence was recorded over a period of 2 h with continuous acquisition. The fluorescence emission intensity at each time point was plotted as a percentage of the fluorescence emission intensity of a 20 μM DCF reference sample, measured at the end of the kinetics read. 2.6

Cell Culture

2.7 Cellular DCFH2DA Uptake

HepaRG cells were kindly provided by Biopredic International (Saint-Gre´goire, France). HepG2 cells were purchased from ATCC (Manassas, VA). Both cell lines were cultured in WE medium supplemented with 10% (vol/vol) fetal bovine serum, 100 U/mL penicillin, 100 μg/mL streptomycin, 2 mM L-glutamine, 5 μg/mL insulin, and 50 mM hydrocortisone under standard culture conditions (humidified atmosphere of 95% air and 5% CO2 at 37  C). Cells were subcultured at a 1:5 ratio (HepG2) or 1:7 ratio (HepaRG) following detachment by trypsinization (15 min at 37  C) in a 2:1:1 accutase:accumax:PBS mixture. HepG2 cells, undifferentiated HepaRG cells, and differentiated HepaRG cells were used for experiments after 4–5, 12–16, and 26–30 days of culture, respectively. Cells were seeded in 24-well plates and used at 100% confluence for each experiment. Time- and concentration-dependent DCFH2-DA uptake was analyzed by incubating cells with 50 μM DCFH2-DA in PBS for 0–20 min or with 0–100 μM DCFH2-DA in PBS for 15 min, respectively. Following incubation, the DCFH2-DA-containing PBS was aspirated, snap frozen in liquid N2, and stored at 20  C. At a later time point, samples were thawed and centrifuged for 15 min at 15,000  g (4  C) to pellet any cellular debris. Next, 400 μL of supernatant was incubated with 600 μL of 190 mM NaOH for 15 min at RT in the dark so as to convert all DCFH2-DA into DCFH2 [22]. The concentration of DCFH2 and DCF (from concurrent auto-oxidation) was determined in each sample by means of absorbance (ε305nm ¼ 7906/M/cm in PBS, pH ¼ 12) and fluorescence spectroscopy (λex ¼ 503  5 nm,

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λem ¼ 513  700 nm against a 0–40 nM DCF standard curve), respectively. The cellular uptake of DCFH2-DA was calculated by subtracting the combined nanomolar amount of DCFH2 and DCF in the supernatant (as a measure of residual DCFH2-DA following incubation) from that of the DCFH2-DA in PBS stock solution (n ¼ 4). Data were subsequently normalized to total protein content per well that was determined in duplicates using a colorimetric commercial kit (bicinchoninic acid [BCA] protein assay, Thermo Scientific, Rockford, IL), as well as incubation time for the concentration-dependent experiments. The cell lysis solution (0.1 M NaOH and 1% Triton X-100 in water) was chosen because of the different mechanisms of cell lysis by NaOH and Triton X-100 and because these components do not interfere in the BCA derivatization reaction and subsequent spectrophotometric determination (described in section S2.7). 2.8 Cellular DCF Uptake

To investigate time-dependent uptake of DCF, cells were incubated with 50 μM DCF in serum-free WE medium for 0–20 min under standard culture conditions. At each time point, cells were washed twice with PBS and lysed with lysis solution (250 μL/well) for 1 h at 37  C. Following homogenization of cell lysates, DCF fluorescence was measured using a microplate reader (λex ¼ 460  40 nm and λem ¼ 520  20 nm; BioTek Instruments, Winooski, VT). Data were corrected for total protein content per well as described above and normalized to controls (i.e., 0-min incubation). Concentration-dependent DCF uptake was determined by incubating cells with 0–100 μM DCF in serum-free WE medium for 20 min under standard culture conditions. Subsequently, cells were washed twice in PBS and 300 μL of PBS was added to each well. DCF fluorescence was measured at abovementioned settings, corrected for total protein content per well as well as incubation time, and normalized to control (i.e., 0 μM DCF).

2.9 Intracellular DCF Retention and Transmembrane Diffusion

The extent of intracellular DCF retention was determined by incubating cells in serum-free WE medium with 100 μM DCF or solvent control for 2 h at standard culture conditions. Cells were washed twice in PBS and 500 μL of serum-free WE medium was added to each well, which was aspirated at various time points over a 20-min period. Next, cells were lysed and DCF fluorescence in the lysate was determined as described above. Intracellular DCF retention was also visualized by laser scanning confocal microscopy (Leica SP8, Leica Microsystems, Wetzlar, Germany). HepG2 cells were grown to confluency in 6-well plates pre-coated with rat tail-derived collagen I in 0.1 M acetic acid in water for 6 h (8 μg/cm2). Prior to imaging, cells were incubated with 100 μM DCF in serum-free WE medium for 2 h at standard culture conditions. Thereafter, cells were washed twice in PBS and fixed in 1.5 mL fixative (4% paraformaldehyde and 2% sucrose in

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PBS, 5 min, RT) following 5- or 30-min incubation with serumfree WE medium. Cells were stained with 1 μM Nile Red in PBS (from 5 mM Nile Red in DMSO stock solution) for 60 s and washed thrice with 1 mL PBS [11, 12]. The coverslips were then mounted on microscope slides using DAPI-containing Vectashield mounting medium (Laboratories, Burlingame, CA). Fluorescence intensities were measured per fluorophore at λex ¼ 405 nm, λem ¼ 415–480 nm for DAPI; λex ¼ 540 nm, λem ¼ 550–650 nm for Nile Red; and λex ¼ 495 nm, λem ¼ 520–580 nm for DCF. An overlay image was composed of the individually acquired images. Laser and detector settings were kept similar throughout the experiment. The transmembrane diffusibility of DCF was assessed using liposomes encapsulating DCF or 6-carboxyfluorescein (CF) at a self-quenching concentration. CF (49 mM) and DCF (18 mM) were prepared in an aqueous solution containing 98.4 and 37.3 mM NaOH, respectively, and incubated overnight at 37  C under continuous shaking. Both solutions were titrated to pH ¼ 7.4, after which solvent osmolarity was determined as described in [40] against a 0–154 mM NaCl in water (pH ¼ 7.4) standard curve and adjusted to 0.292 osmol/kg with NaCl. Liposomes were prepared by the lipid film hydration technique as described in [22]. Briefly, a lipid film was prepared by mixing stock solutions of DMPC, cholesterol, lactosyl-PE, and GM1 at a 50:40:5:5 molar ratio (10 mM final lipid concentration). The solvent was evaporated under a stream of N2 gas followed by 30 min of vacuum desiccation. The resulting lipid film was hydrated with 500 μL of self-quenching DCF or CF solution and sonicated using a tip sonicator (Branson Ultrasonics, Danbury, CT) for 5 min. Unencapsulated probe was subsequently removed by size-exclusion chromatography according to [41]. The release of encapsulated DCF or CF was determined over a period of 10 min by fluorescence spectroscopy (λex ¼ 491  5 nm, λem ¼ 523  5 nm). A cuvette containing 1500 μL of HEPES buffer was placed into the spectrometer (maintained at 22  C) and time-based acquisition was started. At t ¼ 1 min, 40 μL of iso-osmotic liposome solution was added. At t ¼ 9 min, 15 μL of 15% TX-100 in water was added to lyse the liposomes, resulting in the release of all encapsulated probe and hence maximum fluorescence intensity. 2.10 Basal Oxidant Formation and Cellular Metabolic Rate

To analyze the intracellular basal oxidant formation, cells were incubated with 0–100 μM DCFH2-DA in serum-free HEPESbuffered WE medium (25 mM, pH ¼ 7.4) at 37  C in a microplate reader in which DCF fluorescence was measured over a period of 2 h at 10-min intervals (λex ¼ 460  40 nm, λem ¼ 520  20 mn). A cell-free plate was analyzed directly thereafter to determine the rate of DCFH2-DA auto-oxidation in the incubation medium. Cellular

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DCF fluorescence was adjusted for DCFH2-DA auto-oxidation over time and normalized to total protein content per well. Cellular O2 consumption and extracellular acidification rate (as ΔpH) were determined as a measure of the overall metabolic rate in cells seeded onto 96-well plates (Seahorse Bioscience, North Billerica, MA). Cells were analyzed in 200 μL serum- and bicarbonate-free DMEM using a Seahorse XF96 analyzer (Seahorse Bioscience; n ¼ 24 per cell type, 3 measurements per sample). All data were normalized to total protein content per well. 2.11 Real-Time Analysis of Oxidant Formation During In Vitro Anoxia/ Reoxygenation in HepG2 Cells

DCFH2-DA was used to visualize acute oxidative stress in HepG2 cells under experimental conditions emulating hepatic ischemiareperfusion [42]. For this purpose, a custom-built fluorescence microscopy-based experimental setup was used (see Fig. S3 in the supplementary material). HepG2 cells were cultured as described above on collagen-coated 0.8-mm channel slides (Ibidi, Planegg, Germany). During the experiment, cells were perfused (80 μL/min) with serum-, glucose-, and pyruvate-free WE medium for 4 h at 37  C. The medium was continuously purged with a mixture of 95% N2 and 5% CO2 or 95% air and 5% CO2 (Linde Gas Benelux, Schiedam, the Netherlands) for the anoxia-reoxygenation (A/R) or control group, respectively. The slide was subsequently perfused with 100 μM DCFH2-DA in the respective incubation medium for 15 min (80 μL/min). In an additional A/R intervention group, 1 mM dimethyl malonate (DMM), which prevents the buildup of succinate during anoxia and hence reduces oxidant formation upon reoxygenation [43], was added to the perfusion medium and the DCFH2-DA-containing incubation medium. Following incubation with DCFH2-DA, perfusion was resumed with medium purged with 95% O2 and 5% CO2 in the A/R and A/R intervention groups. Cells in the control group were perfused with medium saturated with 95% air and 5% CO2. Immediately after washout of the DCFH2-DA incubation medium (~10 s), cells were visualized with a stereo fluorescence microscope (λex ¼ 470  20 nm, λem ¼ 515 nm long pass; model M165C, Leica Microsystems, Wetzlar, Germany) for a period of 30 min at 2.5-min intervals with dark intermittence periods. Cellular DCF fluorescence was subsequently quantified based on the total pixel intensity of the images following conversion to 8-bit grayscale (ImageJ software; National Institutes of Health, Bethesda, MD) and normalized to t ¼ 0 min.

2.12 Statistical Analysis

Statistical analysis was performed using GraphPad Prism (GraphPad Software, La Jolla, CA). All data were analyzed using one-way ANOVA, in which repeated-measures data were analyzed based on the area under the curve (AUC) values per sample. Intragroup multiple comparisons were made using the Dunnett’s post hoc

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test, where means were compared to a single control. For intergroup multiple comparisons, all possible pairs of means were compared using Tukey’s range test. A p-value of < 0.05 was considered statistically significant.

3

Results

3.1 The Spectral Properties of DCFH2DA and Derivatives Are pH-Dependent

The spectral properties of DCFH2-DA, DCFH2, and DCF were analyzed using absorbance and fluorescence spectroscopy, the results and discussion of which are provided in section S3.1 and Figs. S4-6. The most important and relevant finding was that changes in pH (up to pH ¼ 8.0) affect the absorption spectrum and fluorescence emission and excitation spectra of DCF, which is likely to affect experimental data interpretation and outcomes, particularly under conditions of (shifting) acidosis.

3.2 The Stability of DCFH2-DA and DCFH2 in Aqueous Solvent and Medium Is Dependent on the Composition of the Solution

The long- and short-term stability of DCFH2-DA and DCFH2 was analyzed in aqueous solvents (discussed in the Appendix) and cell culture media (the latter only for DCFH2-DA). Decay of DCFH2DA in aqueous solution, resulting in the formation of DCF, most likely occurs through base-catalyzed hydrolysis of the acetate groups and subsequent DCFH2 (auto-)oxidation. DCF generation as a measure for DCFH2-DA decay was analyzed spectrofluorometrically in solutions containing 20 μM DCFH2-DA and plotted as a percentage of a 20-μM DCF reference sample (Fig. 2). Temperature- and solute-related effects were observed when the short-term stability of DCFH2-DA was determined in different types of cell culture media (WE, DMEM, and RPMI-1640) and PBS, conditions that are relevant for in vitro use of the probe. DCF formation in PBS was undetectable at RT and negligible at 37  C following 2 h of incubation (Fig. 2a), which is in line with the data on long-term stability of DCFH2-DA in aqueous solvent (see Fig. S7 in the supplementary material). DCFH2-DA stability in cell culture medium (37  C) was analyzed at ambient CO2 tension in serum- and phenol red-free DMEM, RPMI, and WE with or without HEPES (25 mM, pH ¼ 7.4). The reason for this was that microplate-based experiments involving DCFH2-DA (as described below) generally need to be performed under these conditions. Considerable variation in the extent of DCF formation was noted for the different types of culture medium and depending on the presence of HEPES. Considering that HEPES prevents medium alkalization at ambient CO2 tension, its presence was expected to improve DCFH2-DA stability due to a reduction in [OH]-mediated deacetylation. Addition of HEPES to the different medium formulations however resulted in opposing effects on DCF formation. Specifically, the presence of HEPES slightly increased DCF formation in WE (Fig. 2b), favored it in DMEM

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Fig. 2 Short-term stability of DCFH2-DA in PBS and medium. (a) Stability of 20 μM DCFH2-DA in PBS measured at room temperature (RT; blue line) or 37  C (red line) over a period of 2 h. DCFH2-(DA) stability was measured through DCF formation and plotted as a percentage of a 20-μM DCF reference sample. (b–d) Stability of 20 μM DCFH2-DA in unbuffered (red line) and HEPES-buffered (25 mM, pH ¼ 7.4; blue line) (b) William’s E (WE), (c) Dulbecco’s modified Eagle medium (DMEM), and (d) Roswell Park Memorial Institute (RPMI) medium measured at 37  C over a period of 2 h. DCFH2-(DA) stability was measured through DCF formation and plotted as a percentage of a 20-μM DCF reference sample. All data (n ¼ 3/group) are plotted as mean  SD

(Fig. 2c), and had no notable effect in RPMI (Fig. 2d). Considering that the influence of HEPES on DCF formation appears to be independent of its presumed inhibitory effect on DCFH2-DA deacetylation, the observed differences most likely result from complex interactions between DCFH2, HEPES, and redox-active medium components (Table 1). In that regard, the extent of DCF formation in DMEM corresponds well to it being the most nutrient-rich medium with a high concentration of O2 -producing riboflavin, granted that (room) light is present to facilitate this reaction [44]. DMEM is moreover the only medium containing Fe3+ that, together with O2 , will result in the formation of Fe2+ through Haber-Weiss cycling [45]. Although all types of media contain varying amounts of antioxidants (e.g., GSH and ascorbic acid), these radical-scavenging compounds become radicals themselves upon oxidation l

l

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Table 1 Redox-active compounds in common cell culture media. All compounds are listed in μM concentrations, calculated from the manufacturer’s data sheets (see Table S1 in the supplementary material)

3+

DMEM

RPMI

WE

Salts

Fe

(nitrate)

0.25

0.00

0.00

Vitamins

Ascorbic acid

0.00

0.00

11.36

Riboflavin

1.06

0.53

0.27

Cysteine

0.00

0.00

330.17

Histidine

270.69

96.67

96.67

Methionine

201.06

100.53

100.53

Phenylalanine

399.54

90.80

151.34

Tryptophan

78.34

24.48

48.96

Tyrosine

397.37

110.38

193.17

GSH

0.00

3.25

0.16

Amino acids

Other compounds

[19]. Hence, “antioxidants” can also function as prooxidants under the appropriate conditions. Accordingly, the free radical scavengers GSH [46], cysteine [46], and ascorbic acid [47] were all shown to generate H2O2 in DMEM and/or RPMI. Addition of another compound with similar properties, in this case HEPES [48, 49], could therefore shift the redox equilibrium of the sample in opposing ways. As a result, the extent to which DCFH2 oxidation takes place will strongly depend on medium composition. The addition of HEPES to WE, for instance, could result in HEPES reacting with ascorbic acid radicals (formed as a result of, e.g., O2  generation by riboflavin [50, 51]) that would otherwise be converted into redox-unreactive dehydroascorbic acid. Consequently, HEPES would function as a catalyst for O2  formation [48] and thereby enhance DCFH2 oxidation (Fig. 2b). In DMEM, which contains a large portion of oxidant-generating compounds together with low levels of antioxidants, HEPES will likely act as a free radical sink, consequently reducing the formation of DCF (Fig. 2c). In conclusion, although DCFH2-DA is relatively stable in aqueous solution when kept at 4  C for up to 24 h, long-term storage in water or physiological buffers is not recommended. It is moreover advisable to take the effects of cell culture media components into consideration when performing in vitro assays using DCFH2-DA, thereby preferably not using DMEM. l

l

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3.3 DCFH2-DA Rapidly Accumulates in HepG2 and HepaRG Cells

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Uptake of DCFH2-DA as a function of time and concentration was analyzed in HepG2 and undifferentiated as well as differentiated HepaRG cells (Fig. 3). Uptake of DCFH2-DA was rapid, as evinced by the presence of detectable amounts of DCFH2-DA at t ¼ 0 min (i.e., very brief contact between the monolayer and the incubation medium), and plateaued at t ¼ 5 min in all groups (Fig. 3a). These data indicate that a DCFH2-DA incubation time of 5–10 min suffices for single-read experiments. The findings are moreover consistent with reports on the uptake of DCFH2-DA by Chinese hamster ovary cells [28] and on the hepatocellular uptake of 5(6)carboxy-20 70 -dichlorofluorescein diacetate (carboxy-DCF-DA) [52]. Passive diffusion is generally assumed to be the main uptake mechanism for DCFH2-DA [53], as was demonstrated by the linear uptake of carboxy-DCF-DA (measured intracellularly through its deacetylation product carboxy-DCF) over a 0–500 μM range [52]. In contrast, the DCFH2-DA uptake rate in HepG2 and HepaRG cells deviated from linearity at 100 μM (Fig. 3b–d), which might indicate a greater role for uptake through

Fig. 3 Time- and concentration-dependent uptake and cellular uptake rates of DCFH2-DA and DCF by HepG2 and HepaRG cells. (a) Time-dependent uptake of 50 μM DCFH2-DA (pmol/μg protein) by HepG2 (red bars), undifferentiated (green bars), and differentiated HepaRG cells (blue bars). DCFH2-DA uptake rates (pmol/min/μ g protein) for (b) HepG2, (c) undifferentiated, and (d) differentiated HepaRG cells, determined for 40–100 μM DCFH2-DA. (e) Time-dependent uptake of 50 μM DCF (a.u./μg protein) by HepG2 (red bars), undifferentiated (green bars), and differentiated HepaRG cells (blue bars). DCF uptake rates (a.u./min/μg protein) for (f) HepG2, (g) undifferentiated, and (h) differentiated HepaRG cells, determined for 20–100 μM DCF. All data (n ¼ 8/ group) are plotted as mean  SD. Statistical significance (p < 0.05) is designatedm with “}” for intragroup analyses

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plasma membrane transporters such as organic anion-transporting proteins 1B1 and 1B3 (OATP1B1 and OATP1B3, respectively) [54]. However, saturation of hepatocellular carboxy-DCF uptake, which strongly depended on OATP activity, did not occur until concentrations exceeded 100 μM [52]. The intracellular accumulation of carboxy-DCF was moreover significantly decreased at 4  C compared to 37  C incubation (at 4  C endocytosis and enzymatic/ transporter activity are inhibited), whereas uptake of its acetylated derivative was temperature-independent [52]. Hence, transportermediated DCFH2-DA uptake is likely not a major contributor to probe accumulation. Saturation of cytosolic esterase activity could constitute an alternative explanation for the observed plateau in the DCFH2DA uptake rate. Assuming that cellular DCFH2-DA uptake mainly proceeds through passive diffusion, intracellular [DCFH2-DA] will not exceed extracellular [DCFH2-DA], i.e., DCFH2-DA in the incubation medium. The concomitant esterase-dependent intracellular formation of DCFH2 however establishes a DCFH2-DA sink that allows for ongoing probe influx. Thus, when this enzymatic process becomes saturated, the concentration gap between intraand extracellular [DCFH2-DA] will stabilize, as a result of which probe uptake will concomitantly not increase at higher probe concentrations. This principle has been shown for acetylsalicylate uptake by hepatocytes co-incubated with the acetylesterase inhibitor paraoxon [55]. The presumed acetylesterase dependency of DCFH2-DA uptake could moreover explain the differences in uptake rate between, e.g., HepG2 and differentiated HepaRG cells (Fig. 6b, d), and underscores the notion that DCFH2-DA accumulation is likely cell type-specific. 3.4 DCF Accumulates in HepG2 and HepaRG Cells and Is Poorly Retained

The cellular uptake and excretion of DCF were analyzed because such effects are expected to skew experimental data in an upward or downward direction, respectively, when using DCFH2-DA to analyze intracellular oxidative stress. DCF uptake was determined in a time- and concentration-dependent manner. The fluorophore accumulated swiftly in all cell types, yet more rapidly in differentiated HepaRG cells compared to HepG2 and undifferentiated HepaRG cells (Fig. 3e), as evidenced by significant accumulation at t ¼ 0 min in differentiated HepaRG cells compared to t ¼ 5 min in HepG2 and undifferentiated HepaRG cells. Accordingly, overall DCF uptake was higher in differentiated HepaRG cells (p < 0.0001 and 0.001 compared to HepG2 and undifferentiated HepaRG cells, respectively, at t ¼ 20 min) as well as in undifferentiated HepaRG compared to HepG2 cells (p < 0.01 at t ¼ 20 min). This trend roughly corresponds to RNA expression levels of OATP1B1 and OATP1B3 that followed differentiated HepaRG > undifferentiated HepaRG  HepG2 cells [54]. However, because culture conditions for differentiated HepaRG cells

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did differ between the cited study and the one described here, these results might not be fully superimposable. Considering that OATP1B1 and OATP1B3 are involved in the hepatocellular uptake of carboxy-DCF [52] as well as fluorescein [56, 37], both are likely to transport DCF as well. Although DCF is assumed to be membrane impermeable, uptake through passive diffusion could also take place (as discussed below). These findings are of particular relevance for experiments in which prolonged incubation with DCFH2-DA is desired because considerable DCF formation from DCFH2-DA decay occurs under such conditions (as discussed above). The DCF uptake rate was linear over the complete concentration range in all cell types (Fig. 3f–h), in accordance with data on carboxy-DCF showing that saturation occurs at [DCF] > 100 μM [52]. In contrast to time-dependent DCF uptake (Fig. 3e), the DCF uptake rate was lower in differentiated HepaRG cells compared to HepG2 and undifferentiated HepaRG cells. Timedependent DCF uptake was measured in cell lysates, while the DCF uptake rate was analyzed in intact monolayer culture. The difference in experimental setup dictates that the overall probe distribution over the complete sample (i.e., cells and incubation medium) differs, which might affect DCF fluorescence emission properties. Nevertheless, these data collectively show that DCF formation in the incubation medium could interfere with intracellular measurements and that the extent of this effect is cell typespecific. Intracellular DCF retention was quantified spectrofluorometrically and visualized using confocal microscopy. A rapid reduction in DCF fluorescence, i.e., probe efflux, was observed for all cell types. DCF efflux stabilized at t ¼ 20 min, at which point ~50% of initial probe fluorescence was detected (Fig. 4a). DCF expulsion moreover occurred more rapidly in differentiated HepaRG cells compared to HepG2 cells (p < 0.001 at t ¼ 5 min) and undifferentiated HepaRG cells (p < 0.001 at t ¼ 10 min). As for DCF uptake and OATP1B1/3, this trend fits well with RNA expression levels of the basolateral exporter multidrug resistance protein 3 (MRP3) that followed differentiated HepaRG > undifferentiated HepaRG  HepG2 cells [54], although differences in culture medium composition for the differentiated HepaRG cells need to be taken into consideration. Both MRP3 and the apically located MRP2 expel carboxy-DCF from hepatocytes in vivo [52], and MRP2 likely does not contribute to DCF efflux in monolayer culture because of its cytosolic localization under these conditions [57]. Accordingly, MRP2 mRNA expression levels were comparable between all cell types [54]. Efflux of DCF into the extracellular space was confirmed using confocal microscopy of HepG2 cells that were loaded with 100 μM DCF prior to imaging at t ¼ 5 and 30 min following replacement of

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Fig. 4 DCF retention in cells and liposomes. (a) DCF retention (a.u./μg protein) was measured in HepG2 (red bars), undifferentiated HepaRG cells (green bars), and differentiated HepaRG cells (blue bars) loaded with 100 μM DCF for 2 h. Data (n ¼ 8/group) are plotted as mean  SD. Intragroup statistical differences (p < 0.05) are designated with “}.” (b, c) Intracellular and extracellular localization of DCF in HepG2 cells loaded with 100 μM DCF for 2 h following (b) t ¼ 5 min and (c) t ¼ 30 min of incubation in probe-free medium. Cells were counterstained with DAPI (nucleus) and Nile Red (NR; membranes). OL: overlay. The arrowheads in (b) point to the extracellular presence of DCF. (d) Efflux of DCF (blue line) and CF (red line) from liposomes encapsulating both probes at self-quenching concentration was analyzed spectrofluorometrically (λex ¼ 491  5 nm and λem ¼ 523  5 nm) in time-based acquisition mode (t ¼ 600 s) at 37  C. At t ¼ 550 s, 0.15% Triton X-100 (TX-100) was added to solubilize the liposomes and release all encapsulated probe. Data (n ¼ 3) are plotted as mean  SD

the incubation solution with probe-free WE medium (Fig. 4b, c, respectively). At t ¼ 5 min, DCF was already localized both intracellularly and in the extracellular spaces (indicated by white arrows in Fig. 4b). The co-localization between DCF and Nile Red indicates that DCF accumulates within cellular organelles. Considering that the hepatic metabolism of fluorescein proceeds through glucuronidation [58], it is plausible that DCF is processed similarly and therefore localizes within the endoplasmic reticulum. Significant loss of intra- as well as extracellular DCF fluorescence was

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737

Fig. 5 Chemical structure of (a) CF and (b) DCF

observed at t ¼ 30 compared to t ¼ 5 min, supporting the notion that DCF is actively excreted by HepG2 cells. Glucuronidation of DCF might additionally contribute to the observed loss in fluorescence since the fluorescence intensity of glucuronidated fluorescein constitutes only 4.5% of that of unconjugated fluorescein [58]. Further work is needed to substantiate this. In conclusion, DCF uptake and efflux both occur in HepG2 and HepaRG cells, presumably through transporter-mediated mechanisms. Movement of DCF across the plasma membrane needs to be taken into account when performing assays involving DCFH2-DA on these cell types, as it is expected to affect experimental outcomes. 3.5 DCF Crosses Membranes

The membrane-crossing ability of DCF was investigated by means of liposomes encapsulating DCF and the more hydrophilic 6-carboxyfluorescein (CF) at self-quenching concentration, a system that generates fluorescence upon probe leakage [41]. An increase in fluorescence (i.e., probe efflux) was observed directly after the addition of DCF-encapsulating liposomes to the iso-osmotic buffer solution, something that was not observed for CF-encapsulating liposomes (Fig. 4c). CF differs from DCF in that it lacks the two chlorine moieties but has an additional carboxylic acid group, giving it an overall charge of 3 at physiological pH [59] compared to 2 for DCF (see Figs. 5 and 1) [26]. It is likely that this difference in charge explains the passage of DCF, but not CF, across the negatively charged phospholipid bilayer that should deter the diffusion of negatively charged small molecules [60]. Despite providing information on the ability of DCF to cross phospholipid membranes, the experimental setup employed here greatly differs from in vitro conditions. Most relevantly, the high intraliposomal DCF concentration (i.e., 18 mM) creates a nonphysiological but significant concentration gradient that potentially favors DCF efflux even at iso-osmotic conditions.

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Fig. 6 Basal oxidant formation and cellular metabolic rate in HepG2 and HepaRG cells. DCF fluorescence (a.u./ μg protein) over time at increasing DCFH2-DA concentration (0–100 μM) as a measure of basal oxidant formation in (a) resting undifferentiated HepaRG, (b) differentiated HepaRG cells, and (c) HepG2 cells. Data (n ¼ 6/group) are presented as mean  SD. (d) Cellular O2 consumption (pmol/min/μg protein) and (e) extracellular acidification rates (mpH/min/μg protein) of HepG2 (red bars), undifferentiated HepaRG cells (Und. H.; green bars), and differentiated HepaRG cells (Diff. H.; blue bars). Data (n ¼ 8/group) are presented as mean  SD 3.6 Basal Oxidant Formation and Cellular Metabolic Rate Differ Between HepG2 and HepaRG Cells

The rate of basal oxidant production over time was analyzed at increasing concentration of DCFH2-DA in HepG2 and undifferentiated as well as differentiated HepaRG cells to ascertain the optimal probe concentration for assays involving these cell types. DCF formation (as a measure for intracellular oxidant formation) correlated to DCFH2-DA concentrations up to 60 μM in all cell types (Fig. 6a–c), indicating that intracellular probe levels likely reach saturating conditions at 60 μM in resting cells. Overall DCF formation was significantly higher in HepG2 cells compared to undifferentiated and differentiated HepaRG cells (p < 0.001 following 2-h incubation with 80 μM DCFH2-DA for both groups), likely due to a more oxidized redox state in the former. This notion is supported by the data on cellular O2 consumption and extracellular acidification rate, which suggest a higher metabolic rate, more glycolytic state, and/or differences in uncoupling processes in HepG2 compared to both forms of HepaRG cells (Fig. 6d and e; p < 0.001 for both groups). Accordingly, glucose

DCFH2-DA Assay Conditions in Hepatocytes

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consumption and lactate production are higher in HepG2 compared to (differentiated) HepaRG cells [61]. Nevertheless, the difference in DCF formation between HepG2 and HepaRG cells could also, in part, derive from variations in DCF metabolism that can affect DCF fluorescence intensity (as described above). Antioxidant properties could moreover differ between the cell lines and in this way lead to a difference in DCF formation. Gene expression for common antioxidant proteins however did not greatly differ between the cell lines, with the exception of peroxiredoxin-6 and catalase, which followed differentiated and undifferentiated HepaRG > HepG2 cells [54]. Overall, the extent of basal oxidant formation in resting HepG2 and HepaRG cells roughly correlates to lactate formation and O2 consumption and is best measured at a DCFH2-DA concentration of 60 μM. 3.7 Oxidative Stress During In Vitro Anoxia/ Reoxygenation Can Be Visualized in Real Time Using DCFH2-DA

DCFH2-DA was used to visualize and quantify acute oxidative stress in HepG2 cells subjected to 4 h of anoxia followed by reoxygenation (A/R) in a perfusion setup equilibrated to 37  C and positioned under a fluorescence microscope (Fig. 7a and Fig. S3 in the supplementary material). Control cells were subjected to standard culture conditions, i.e., medium saturated with 95% air and 5% CO2, throughout the experiment. A rapid and significant increase in DCF fluorescence was observed in the cells subjected to A/R (Fig. 7b, c). DCF fluorescence intensity reached a maximum at 10–12 min of reoxygenation and subsequently declined, presumably due to a reduced rate of DCF formation at constant DCF efflux and possibly due to metabolism. Considering that hepatocytes exposed to anoxia become acidic [62], the observed increase in DCF formation in this early phase of reoxygenation could well be underestimated as a result of reduced DCF fluorescence emission at pH < 7 (see Fig. S6D in the supplementary material). In comparison, a decrease in DCF fluorescence was observed in control cells following incubation with DCFH2-DA despite higher fluorescence at baseline (Fig. 7c, e). This phenomenon is explained by the difference in incubation conditions between the control and A/R group, i.e., oxygenated vs. deoxygenated medium, which enabled DCFH2 oxidation to take place in control cells but not in A/R cells during the incubation period. Addition of 1 mM DMM to the perfusion and incubation medium resulted in a profound decrease in DCF formation during reoxygenation (Fig. 7c, d). Considering that the effect of DMM stems from a reduction in succinate accumulation during anoxia that hampers mitochondrial oxidant formation upon reoxygenation [43], the increase in DCF fluorescence during A/R most likely results from mitochondrial oxidative stress that manifests in the cytosol where mitochondria-derived oxidants react with DCFH2. In that respect, the maximum signal intensity observed at t ~ 10 min indicates that mitochondrial oxidant formation during

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Fig. 7 Real-time visualization of oxidative stress during in vitro anoxia-reoxygenation. (a) Schematic overview of the perfusion setup under conditions of anoxia/reoxygenation; details are provided in the text. (b) Formation of DCF (relative pixel intensity) from DCFH2-DA (100 μM) in HepG2 cells during 30 min of reoxygenation following 4 h of anoxia and incubation with DCFH2-DA under anoxic conditions (A/R, blue line) or similar procedures in the presence of the antioxidant dimethyl malonate during the anoxia period (A/R + DMM, red line). Control cells were perfused and incubated with DCFH2-DA under normoxic conditions (4-h perfusion followed by 30-min imaging; control, green line). Data (n ¼ 3/group) are presented as mean  SEM. Representative fluorescence microscopy images of the data presented in (b) are shown for reperfused cells following (c) anoxia, (d) reperfusion following anoxia + DMM, and (e) control conditions

A/R is a rapid yet short-lived effect, as has previously been postulated in the context of hepatic ischemia-reperfusion [42].

4

Discussion The main limitations for the use of DCFH2-DA on HepG2 and HepaRG cells are the uptake of extracellular DCF, poor DCF retention, and cell type specificity of DCFH2 oxidation under resting conditions. DCFH2-DA stability is also affected by the type and pH of incubation medium in which it is dissolved. Nevertheless, DCFH2-DA can be a useful means to analyze oxidative stress in HepG2 and HepaRG cells granted that the experimental

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Fig. 8 Schematic overview of optimized assay conditions for the use of DCFH2-DA in cultured hepatocytes. Details are provided in the text

setup accounts for these limitations. A schematic overview of an experimental setup that aims to optimize conditions for the use of DCFH2-DA on cells of hepatocellular origin is therefore presented in Fig. 8. The incubation medium should preferably contain 60 μM DCFH2-DA in either PBS or serum-free WE or RPMI medium, which needs to be HEPES-buffered when performing experiments at ambient CO2 tension to maintain pH. The assay is ideally performed in a fluorescence microplate reader (equilibrated to 37  C) in time-based acquisition and equipped with the appropriate filters for DCF fluorescence detection (e.g., λex ¼ 460  40, λem ¼ 520  20 nm). Directly following analysis of the assay plate, a second plate containing only incubation medium (exactly corresponding to that used for the assay plate) should be read to correct for extracellular DCF formation. The raw data from the cell-free plate (2) need to be subtracted from the corresponding wells of the assay plate (1) at each individual time point to calculate cellular DCF fluorescence (Fig. 8, equation). Sample a.u. values should be close to 0 for the baseline measurement following this step, as was the case with the data presented in Fig. 6. However, if considerable differences in baseline values are observed, for instance because of a significant time lag in pipetting the incubation medium, data can be additionally normalized by subtracting the raw data at baseline (first read) from every subsequent time point per sample (Fig. 8, normalize). Irrespective of whether baseline correction is performed, each data point should be normalized to the total protein (or DNA) content per well to correct for differences in cell seeding density (Fig. 8, protein correction). By incubating the cells throughout the assay period, intracellular DCFH2-DA levels are maintained constantly. Moreover, intracellularly generated DCF that is expelled into the extracellular space will be detected, while outcomes are corrected for DCF formation

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in the incubation medium. In doing so, DCFH2-DA can be used to generate data on intracellular oxidative stress with minimal interference. This approach could moreover be useful when DCFH2DA, as well as other fluorogenic probes with similar properties (e.g., dihydrorhodamine 123 and hydroethidine) [63], is used on cell lines that express membrane transport proteins, e.g., MRP1expressing RAW 264.7 macrophages [63]. There are however limitations to DCFH2-DA that are more cumbersome to correct for. Specifically, DCFH2 oxidation involves the formation of an intermittent radial species, the DCF semiquinone radical (DCF /DCF ) [25, 26], which could affect DCF formation via both direct, i.e., DCFH2 oxidation, and indirect, i.e., O2  formation, mechanisms [25, 19]. In addition, overoxidation of DCF into nonfluorescent degradation products could lead to an underestimation of DCF formation [19]. Although these phenomena are not specific to DCFH2-DA [19], it will be difficult to quantify the full extent to which these processes contribute to DCF formation under assay conditions as well as to correct for them experimentally. A second, more relative limitation of DCFH2(-DA) is its non-specificity toward various radical and non-radical oxidants [21–24]. It is therefore suggested to regard data generated using DCFH2-DA as a measure for overall “oxidative” or “redox stress” and to avert to more specific probes (e.g., hydroethidine or Amplex Red) or techniques (e.g., electron paramagnetic resonance) when detection of particular radical species is warranted. In addition to the experimental setup presented in Fig. 8, the probe can also be used to visualize and quantify cytosolic oxidative stress during A/R in real time. This technique can additionally be employed to analyze the direct effect of pharmacological interventions that target intracellular oxidative stress or to analyze other phenomena using different dyes (e.g., JC-1 for mitochondrial membrane potential analysis), further expanding the possible applications of DCFH2-DA. l

l

l

5

Conclusions Despite its limitations DCFH2-DA can function as a useful fluorogenic probe to investigate the intracellular redox state in the context of liver disease. An experimental setup is proposed that aims to circumvent most interfering factors. However, caution should always be taken when interpreting data generated using fluorogenic redox probes as it is not possible to correct for all limitations.

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INDEX A Acute stress response .................................................... 411 Adaptive immune system ....................128, 131, 133, 409 Affinity chromatography.....................482, 487–489, 491 Alginate hydrogels .........................................93, 101, 104 Angiogenesis................................................. 15, 108, 115, 118–119, 267, 290, 296, 307, 308, 369, 377, 440, 454, 570 Antibiotics ............................................................. 23, 355, 368–370, 372, 483, 485, 486, 560, 562, 563, 607, 621, 631, 632, 639, 657, 671–673, 675–677, 680, 682, 684, 686, 692, 716, 717 Antigens............................................................... 118, 132, 137, 140, 141, 289, 305, 409, 414, 559, 560, 574, 585, 588, 589, 597, 598, 602 Anti-iNOS/NO adjuvants.............................................. 21 Antimicrobial photodynamic inactivation .......... 607, 621 Antitumor immune response.................................. 10, 17, 130, 167, 289, 409, 559–567, 570, 590 Apoptosis .......................................................9, 10, 13–15, 22, 138, 167, 171, 213, 215, 216, 219, 236, 266, 267, 269, 290, 294, 301, 303, 305, 307, 310, 312, 315, 316, 318, 321–323, 325–327, 329–332, 334, 335, 338, 339, 341–343, 345–347, 349–351, 353, 369, 371, 372, 377, 378, 414, 416, 418–424, 429, 431, 439–441, 443, 444, 446–448, 454, 455, 457, 522, 570, 711–713, 715, 718, 722 Apoptosis signal-regulating kinase 1 (ASK1) .............410, 448–457 Autophagy ......................................... 9, 14, 71, 266, 303, 353, 378, 414, 420, 421, 444, 455, 457, 711, 712, 714, 715, 717, 718

B Binding affinity of nanobodies ....................481, 505–519 Bioengineering ................................................................ 33 Bioluminescence applications .............................. 636, 637 Bioluminescence gene transfection (bacteria) .... 635–636 Bioluminescence imaging ................................... 136, 139, 178, 180, 181, 554, 626, 639, 641, 642, 645 Bioluminescence systems in bacteria................... 633, 634 Bioluminescence to monitor antimicrobial blue light therapy ...................................................... 657–662

Bioluminescent models for antimicrobial photodynamic therapy (clinical) ................................................ 632 Bioluminescent models for antimicrobial photodynamic therapy (environment) ...................................... 632 Biomaterials ..................................................................... 93 Biomodulation .............................................................. 118 Black phosphorus nanosheets....................................... 218 Bystander effects .......................................................27, 29

C Cancer.....................................................4, 22, 33, 49, 59, 71, 81, 92, 107, 127, 151, 165, 175, 185, 204, 213, 245, 263, 408, 481, 505, 533, 548, 569, 579, 589, 597, 610, 672, 722 Cancer metastases ................................................ 185–199 Cancer stroma ...........................................................81, 82 Cancer therapy ............................................. 9, 34, 35, 71, 72, 82, 196, 213, 219, 289, 408, 443, 448, 482, 569 Carbon nanomaterials................................................... 218 Cell death signaling..................................... 307, 420, 440 Cell lines .................................................9, 15, 16, 18, 22, 33–35, 44, 50, 82–88, 92, 94, 109, 110, 127–132, 154, 160, 163, 165, 178, 180, 188, 204, 246, 247, 256, 268, 310, 320, 327, 330, 332, 338, 351, 369–371, 375–378, 418, 420, 421, 439, 454, 510, 515–517, 525, 534–536, 538–540, 548–551, 553–555, 560, 674, 687, 715, 717, 722–724, 726, 739, 742 Cellular uptake and export ........................................... 734 Cell viabilities .................................... 9, 54, 57, 101, 219, 246, 253–256, 267, 321–323, 325, 327, 330, 333, 335, 339–342, 344–348, 351, 352, 367, 370, 372–374, 412, 420, 421, 510, 511, 535, 550, 678 Ceramidase ........................................................... 569, 570 Chemotherapy........................................9, 16, 34, 50, 82, 86, 88, 92, 133, 166, 175, 185, 187, 194, 203, 204, 213, 245, 289, 408, 415, 442, 445, 715 Chicken embryo chorioallantoic membrane (CAM).................... 107–120, 313, 329, 347, 375 Colocalization of drugs and organelles ........................... 5 Confocal microscopy ...................... 5, 15, 223, 227, 366, 682, 727, 735 Cytosolic release .......................................... 672, 673, 682

Mans Broekgaarden et al. (eds.), Photodynamic Therapy: Methods and Protocols, Methods in Molecular Biology, vol. 2451, https://doi.org/10.1007/978-1-0716-2099-1, © Springer Science+Business Media, LLC, part of Springer Nature 2022

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750 Index

Cytotoxicity in 3D cultures ............................................ 60 Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4).................................................. 589, 595

D Decontamination efficiency by photodynamic therapy ...................................................... 691–698 Dichloro-dihydrofluorescein diacetate (DCFH2-DA).......................... 723–735, 737–742 Drug uptake .....................................................16, 34, 187

E Endoplasmic reticulum stress ....................................... 711 Experimental therapies ................................................... 33

F Fibroblasts .................................................. 15, 35, 81–84, 87, 92, 101, 103, 116, 133, 295, 297, 309, 338, 341, 421, 439, 440, 446 First-generation photosensitizers ................................. 186 5-Aza-20 -deoxycytidine (5-aza-dC) ................... 560–562, 565, 566 Flow cytometry ...............................................4, 9, 10, 13, 15, 17, 36–40, 42, 43, 560, 562, 564, 565, 567, 572, 574, 580, 586 Fluidic stress .................................................................... 49 Fluorescence microendoscopy............................ 188, 189, 193–195, 197 Fluorescence microscopy ...........................................5, 13, 17, 24, 25, 60, 72, 234, 274, 654, 680, 704, 718, 740 Fluorogenic redox probes............................................. 742 Fluorophore ............................................................ 10, 60, 79, 495–502, 512, 514–516, 518, 528, 704, 707, 728, 734 Food safety .................................................................... 691 Fourth-generation photosensitizers.......................vi, 262, 290, 312 F98 syngeneic orthotopic rat model of glioblastoma.............................................. 203–209 Fullerenes.................................................... 216, 217, 227, 263, 622, 639, 646, 653

G Glioblastoma ...............................22, 129, 135, 143, 203, 309, 367, 375, 439 Gram-negative bacteria ....................................... 337, 608, 610, 611, 615, 617, 622, 635, 636, 639, 641, 651, 653–655, 657 Gram-positive bacteria ........................................ 608, 610, 635, 636, 639, 642, 648, 657

H Hepatocytes ..................................................228, 721–742 Heterocellular 3D cultures .......................................82, 83 High-throughput screening ............................34, 35, 430 Hydrogels ..........................................................35, 40, 63, 78, 91–104, 647, 649, 650 Hypoxia ........................................................................3, 9, 72, 115, 119, 152, 253, 255, 257, 289, 292, 294–297, 299, 301, 303, 305, 308, 310, 409, 410, 429, 445 Hypoxia-induced stress response ................................. 290 Hypoxia-inducible factor 1 (HIF-1)............................. 72, 289–378, 410, 411, 415, 423, 448, 455

I Immediate-early stress response ............................. 7, 290, 291, 405–458 Immune checkpoint blockade ............................. 589–596 Immunoblotting ........................................................4, 15, 23, 36, 38, 40, 42, 104 Immunocompetent Models.......................................... 187 Immunoregulatory cell populations ................... 569, 575 Immunotherapy ................................ 137, 151, 560, 569, 589, 590, 597, 598, 603 Inducible nitric oxide synthase (iNOS) ........................ 21, 22, 24, 25, 28, 430, 457 Inorganic photosensitizers................................... 219, 236 iNOS/NO measurements ................................. 21, 24–26 Interstitial photodynamic therapy ................................ 152 Intracellular degradation of drug conjugates .............. 515 Intracellular infections ........................................ 671, 672, 674, 679 Intraoperative photodynamic therapy (ioPDT) .......... 176 Intravital microscopy (IVM) ............................... 521–530 In vitro cytotoxicity ........................................................ 16 In vitro dosimetry ........................................................... 16 Ion exchange chromatography....................482, 489–490

L LCL521 ................................................................ 569–575 Liposomal drug delivery ............................................... 100 Liposomal nanocarriers................................................. 703 Liposomes.............................................5, 6, 9, 92, 94, 95, 97, 98, 100–104, 111, 135, 140, 166, 170, 263, 270, 310, 420, 672, 703, 704, 706, 708, 728, 735, 736 Liquid-overlay cultures ................................................... 35 Localized infections ............................622, 639, 640, 662 Locally advanced cancer (LAC)........................... 151, 152 Longitudinal tracking of cell population in 3D cultures...........................................................81–88

PHOTODYNAMIC THERAPY: METHODS M Magnetic nanomaterials (MNPs) ........................ 233, 236 Mechanotransduction ..................................................... 49 Metabolic plasticity ......................................................... 71 Metabolism......................................................6, 9, 16, 35, 60, 71–79, 119, 129, 144, 290, 291, 297–301, 311, 312, 373, 570, 722, 736, 739 Metal-based photosensitizer complexes ............. 235, 246 Metal complexes............................................................ 262 Metallic nanomaterials .................................................. 232 Microfluidic platforms .................................................... 50 Model system ................................................................ 235 Molecular imaging ..............................187, 188, 482, 495 Mouse macrophage ....................................................... 671 Mouse models ..................................................... 137, 152, 164, 165, 186–190, 192, 196, 198, 217, 227, 429–431, 440, 441, 534, 548, 622, 625–629, 639, 640, 645, 653, 657, 661, 662, 674 Murine models of metastatic ovarian cancer ...... 175–182

N Nanobody........................................................5, 481, 495, 505, 522, 533, 548 Nanobody-photosensitizer conjugate................ 506, 507, 509–511, 517, 522, 523, 527–528 Nanobody production ......................................... 481–492 Nanobody purification......................................... 488–490 Nanotechnology................................................... 214, 239 Natural substances ........................................................ 691 Necrosis .......................................9, 10, 13, 44, 100, 102, 104, 138, 152, 158, 171, 176, 213, 229, 266, 297, 303, 310, 341, 372, 412, 413, 522, 524, 554, 555, 711, 712, 722 Nitric oxide (NO) .......................... 21–30, 216, 269, 294 Normoxia........................................... 250, 253, 255, 257, 294, 298 Nuclear factor (erythroid-derived 2)-like 2 (NRF2) ........................................... 290, 291, 410, 411, 415, 418, 421

O Oncology .......................15, 34, 131, 146, 176, 589, 597 Optical redox ratio .......................................................... 72 Oral candidiasis ........................................... 623, 628, 629 Organelle targeting .............................................. 262, 267 Organic photosensitizers ..................................... 235, 236 Organoids ................................ 34, 60–65, 67, 68, 73–78, 81–88, 92, 93, 100, 109 Orthotopic breast cancer model ......................... 547–555 Orthotopic implantation of ovarian cancer cells in mice .................................................................... 177 Orthotopic models.............................................. 138, 146, 163–172, 523, 533, 534, 548

AND

PROTOCOLS Index 751

Orthotopic murine OSC-19-Luc head and neck cancer model ................................................................. 529 Ovarian cancer...................................................50, 87, 92, 109, 175, 177, 179, 181, 185–189, 195, 371, 417, 420, 431, 440, 443, 715 Ovarian peritoneal carcinomatosis ..............175–182, 185 Oxidants ..................................................... 265, 455, 637, 722, 723, 728, 729, 738, 739, 742 Oxidative and nitrosative stress .................................... 429 Oxidative phosphorylation ...............................72, 73, 75, 297–299, 722 Oxidative stress............................................. 7, 72, 73, 75, 266, 269, 307, 409, 412, 413, 416, 418, 419, 422, 446, 454, 455, 457, 722–724, 729, 734, 739, 740, 742

P Pancreatic cancer organoids ........................................... 81 Paraptosis .............................................................. 711–720 Patient-derived xenograft (PDX) .............. 101, 127, 128, 130–133, 187, 447 Peritoneal carcinomatosis ................... 175–182, 185–187 Photoactivated chemotherapy (PACT)............... 245–257 Photoantimicrobials ...................................................... 691 Photobleaching ....................................7, 34, 79, 84, 194, 223, 271–276, 530, 641, 707 Photochemical internalization (PCI)................. 176, 181, 672–675, 680, 684 Photochemotherapy.......................................................... 9 Photodamage ............................................. 114, 186, 192, 267–269, 711–713, 715, 718, 719 Photodynamic therapy (PDT)...................... 3–18, 21–30, 33–45, 49–57, 59, 66, 67, 71–73, 77, 81–88, 91–104, 107–120, 127–146, 158, 161, 163–172, 175–182, 185–187, 189, 192, 193, 203–209, 213–227, 232–239, 245, 261–276, 285–378, 408–413, 418–425, 429–432, 439, 441–445, 447–449, 454–457, 481–492, 505–507, 509–511, 517, 521–523, 529, 533–545, 547–555, 559–567, 569–575, 579–595, 597–604, 609, 610, 621, 622, 625–629, 632, 641, 652, 654, 657, 703–707, 711–720, 722 Photodynamic therapy-induced cancer cell aggressiveness ...................................................... 22 Photodynamic therapy-induced survival pathways................. 290, 409, 411, 418, 457, 711 Photoimmunotherapy (PT)................................. 165, 186 Photosensitizers (PSs)..............................................3–7, 9, 16, 17, 34, 36, 37, 40, 44, 45, 50, 74, 82, 88, 92, 94, 95, 97, 99, 100, 109, 111, 127, 133–135, 138, 140, 153, 157, 164, 166, 167, 176, 177, 186–189, 191–194, 204, 213–239, 245, 261, 289, 408, 481, 495–502, 505, 506, 509, 510, 514–516, 518, 521–523, 525, 528, 529,

PHOTODYNAMIC THERAPY: METHODS AND PROTOCOLS

752 Index

533–544, 547–550, 566, 573, 590, 591, 593, 594, 599, 602, 607, 621, 624, 632, 636, 639, 649, 653, 654, 658, 663, 672, 673, 675–682, 686–688, 692, 703, 714, 717–719, 722 Phototherapy .......................................146, 187, 189, 191 Potentiation of antimicrobial photodynamic therapy by potassium iodide....................................... 621–629 Preclinical cancer models .............................................. 579 Programmed cell death protein 1 (PD-1) ..................584, 586, 589 Prolyl hydroxylase domain (PHD) proteins ................ 292

Q Quantum dots (QD) ...............................................83–88, 218, 221–223, 229, 231, 263

R Radiation therapy ........................... 82, 88, 203–205, 238 Random conjugation ........................................... 495–500 Reactive molecular species ..........................................3, 50 Reactive nitrogen species (RNS) ......................... 222, 722 Reactive oxygen species (ROS) .......................... 7, 16, 82, 109, 111, 115, 213–219, 222, 235, 238, 245, 289–292, 294, 296, 310, 311, 324, 369, 409–413, 418, 420, 422, 425, 429, 445, 446, 454, 455, 506, 533, 547, 607, 608, 621, 622, 632, 637, 657, 692, 722 Redox homeostasis.......................................................... 71 Rodent models of cancer .............................................. 108

S SCCVII head and neck cancer model.......................... 152 Second-generation photosensitizers ............................ 176 Selective toxicity ............................................................ 510 Self-illuminating nanoparticles ............................ 236, 238 Shear stress ................................................................50, 92 Signalosome.......................................................... 412, 413 Silicon nanomaterials ........................................... 232–225 Single domain antibodies ............................................. 481 Site-directed conjugation of nanobodies....................495, 497, 499, 501, 502 Sodium azide ........................................74, 235, 572, 609, 622, 637, 656 Sodium bromide ........................................................... 607 Spectroscopy........................................... 4–6, 17, 95, 191, 250, 535, 554, 658, 661, 725, 726, 728, 730 Spheroid architecture...................................................... 81 Spheroids ....................................... 35–38, 57, 60, 62, 63, 65–67, 71–79, 82, 83, 85–88, 92, 93, 103, 110, 273, 311, 443 Staphylococci............................................... 671, 676, 684 Stereotaxic implantation ............................................... 204

Subcutaneous pancreatic ductal adenocarcinoma models ................................................................ 129 Super-resolution microscopy ........................................ 704 Syngeneic models ....................................... 129–132, 164, 167, 168, 171, 203–209

T T-cell activation ..........................567, 584, 586, 587, 602 T-cell depletion .................................................... 580, 582 T-cell response............................ 579–589, 597, 598, 603 T-cells............................................................ 15, 133, 140, 305, 559–561, 564–566, 569, 579, 582, 584–590, 597, 598, 602, 603 Targeted photodynamic therapy (PDT) .... 495, 505, 533 Targeted therapies....................................... 130, 168, 196 Theranostic nanoplatforms........................................... 213 Therapeutic potential of novel photosensitizers ......... 536 Therapy screening ........................................................... 59 3D Cancer cultures ............................................ 34, 35, 82 Third-generation photosensitizers .......................... vi, 262 Titanium dioxide.................................................. 215, 655 Transcription factors ............................................. 16, 290, 294, 295, 298, 300, 301, 308, 312, 320, 410, 414–419, 443, 570, 574 Translational research ...............................................16, 91 Treatment outcomes ........................ 50, 60, 82, 146, 262 2D Co-cultures ............................................................... 44

U Ultra-low adhesion 3D culture models ......................... 34 Unfolded protein response (UPR) .............................291, 341, 410, 418, 419 Upconversion nanomaterials (UCNPs) ......222, 225–227

V Vaccination ........................................................... 597–604 Vacuolization ................................................................. 712 Vascular network ........................ 109, 111, 116–118, 120 Vascular response ................................................. 111, 522 Vascular shutdown .............. 17, 289, 290, 310, 409, 524 VX2 hepatocellular carcinoma model ........ 153, 156, 159

X Xenografts................................................... 127–146, 164, 165, 170, 187, 294, 311, 313–332, 334, 335, 337, 338, 340–349, 351–353, 355, 366–369, 372, 374, 375, 420, 422, 431, 440–442, 445, 447, 454, 495, 548

Z Zebrafish embryos...................... 231, 673–676, 682–688 Zinc oxide (ZnO) ......................................................... 216