Urothelial Carcinoma: Methods and Protocols [2 ed.] 1071632906, 9781071632901

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Methods in Molecular Biology 2684

Michèle J. Hoffmann · Nadine T. Gaisa Roman Nawroth · Thorsten H. Ecke  Editors

Urothelial Carcinoma Methods and Protocols Second Edition

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-by step 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.

Urothelial Carcinoma Methods and Protocols Second Edition

Edited by

Michèle J. Hoffmann Department of Urology, Medical Faculty and University Hospital, Heinrich-Heine-University Duesseldorf, Duesseldorf, Germany; German Study Group of Bladder Cancer (DFBK e.V.), Munich, Germany

Nadine T. Gaisa Institute of Pathology, University Hospital, RWTH Aachen University, Aachen, Germany; German Study Group of Bladder Cancer (DFBK e.V.), Munich, Germany

Roman Nawroth Department of Urology, University Hospital Rechts der Isar, Technical University Munich, Munich, Germany; German Study Group of Bladder Cancer (DFBK e.V.), Munich, Germany

Thorsten H. Ecke Department of Urology, Helios Hospital, Bad Saarow, Germany; Department of Urology, Universit€atsmedizin Berlin Charité, Berlin, Germany; German Study Group of Bladder Cancer (DFBK e.V.), Munich, Germany

Editors Miche`le J. Hoffmann Department of Urology Medical Faculty and University Hospital Heinrich-Heine-University Duesseldorf Duesseldorf, Germany

Nadine T. Gaisa Institute of Pathology University Hospital RWTH Aachen University Aachen, Germany

German Study Group of Bladder Cancer (DFBK e.V.) Munich, Germany

German Study Group of Bladder Cancer (DFBK e.V.) Munich, Germany

Roman Nawroth Department of Urology University Hospital Rechts der Isar Technical University Munich Munich, Germany

Thorsten H. Ecke Department of Urology Helios Hospital Bad Saarow, Germany

German Study Group of Bladder Cancer (DFBK e.V.) Munich, Germany

Department of Urology Universit€atsmedizin Berlin Charite´ Berlin, Germany German Study Group of Bladder Cancer (DFBK e.V.) Munich, Germany

ISSN 1064-3745 ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-0716-3290-1 ISBN 978-1-0716-3291-8 (eBook) https://doi.org/10.1007/978-1-0716-3291-8 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This 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 Urothelial carcinoma has many faces and is characterized by a marked tumor heterogeneity, which makes this tumor entity fascinating to study from a scientific perspective. However, this heterogeneity poses particular challenges for medical care in routine clinical practice and research. Compared to tumor entities such as breast or lung cancer, our understanding of carcinogenesis and treatment of urothelial carcinoma has been proceeding only gradually. With the advent of novel therapies, namely immune checkpoint blockade, and highthroughput analyses, a turning point was marked, reflected already when the first edition of this book was published. Excitingly, this development has been fueled over recent years by novel methodological developments that have contributed to a better understanding of the biology and heterogeneity of urothelial carcinoma. Accordingly, this second edition includes several novel chapters on molecular characterization and urothelial carcinogenesis. This new understanding has also led to the development of new biomarkers and approaches for targeted therapy. New cellular models allow investigation of novel therapy approaches on patient samples instead of commercial cancer cell lines. Several surprising findings have been described in recent years that might revolutionize our understanding of urothelial carcinoma carcinogenesis, treatment, and prognosis but are still subject to scientific discussion and therefore have not been included in this second edition. These include, for example, therapy prediction based on molecular subtypes or the analysis and understanding of a bladder microbiome. We hope that the concepts and techniques described in this second edition will contribute to further increase of knowledge on urothelial carcinoma, and that it may also be helpful for research on other cancers. Miche`le J. Hoffmann Nadine T. Gaisa Roman Nawroth Thorsten H. Ecke

Duesseldorf, Germany Aachen, Germany Munich, Germany Bad Saarow, Germany

v

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

PART I

v ix

MOLECULAR CHARACTERIZATION

1 Scoring Systems for Immunohistochemistry in Urothelial Carcinoma . . . . . . . . . 3 Mark-Sebastian Bo¨sherz, Iryna V. Samarska, and Nadine T. Gaisa 2 A Panel-Based Method for the Reproduction of Distinct Molecular Subtype Classifications of Muscle-Invasive Urothelial Bladder Cancer . . . . . . . . . 27 Csilla Olah and Tibor Szarvas 3 Analysis of Mutational Signatures Using the mutSignatures R Library . . . . . . . . . 45 Damiano Fantini and Joshua J. Meeks 4 A Drug Repurposing Pipeline Based on Bladder Cancer Integrated Proteotranscriptomics Signatures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Marika Mokou, Shaman Narayanasamy, Rafael Stroggilos, Irina-Afrodita Balaur, Antonia Vlahou, Harald Mischak, and Maria Frantzi 5 Characterization of Native COMPASS Complex in Urothelial Carcinoma Cells by Size Exclusion Chromatography . . . . . . . . . . . . . . . . . . . . . . . . 101 Christoph Peter, Wolfgang A. Schulz, and Patcharawalai Whongsiri

PART II

UROTHELIAL CARCINOGENESIS

6 Reconstructing Phylogenetic Relationship in Bladder Cancer: A Methodological Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Lancelot Seillier and Martin Peifer 7 Using Sister Chromatid Exchange Assay to Detect Homologous Recombination Deficiency in Epigenetically Deregulated Urothelial Carcinoma Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Theodoros Rampias and Apostolos Klinakis 8 Identification of STAG2-Mutant Bladder Cancers by Immunohistochemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Youngrok Park, Alana Lelo, Brent Harris, Deborah L. Berry, Krysta Chaldekas, Jung-Sik Kim, and Todd Waldman

PART III

CELLULAR AND ANIMAL MODELS

9 Genome-Wide CRISPR Screening for the Identification of Therapy Resistance-Associated Genes in Urothelial Carcinoma . . . . . . . . . . . . . . . . . . . . . . . 155 Klaus Mantwill and Roman Nawroth

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viii

10

Contents

Tissue Slice Culture and Analysis of Tumor-Associated Hyaluronan in Urothelial Carcinoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 William Donelan, Paul L. Crispen, and Sergei Kusmartsev

PART IV

BIOMARKERS

11

NGS-Based Tumor-Informed Analysis of Circulating Tumor DNA . . . . . . . . . . . Iver Nordentoft, Karin Birkenkamp-Demtro¨der, and Lars Dyrskjøt 12 Considering the Effects of Modern Point-of-Care Urine Biomarker Assays in Follow-Up of Patients with High-Risk Non-muscle-Invasive Bladder Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Thorsten H. Ecke, Natalya Benderska-So¨der, Ekkehardt Bismarck, Bas W. G. van Rhijn, Tilman Todenho¨fer, and Bernd J. Schmitz-Dr€ ager 13 Simplex Droplet Digital PCR Assays for the Detection of TERT Promoter Mutations in Urine Samples for the Non-invasive Diagnosis of Urothelial Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Maria Zvereva, Md Ismail Hosen, Nathalie Forey, Mahdi Sheikh, Caroline Kannengiesser, Ibrahima Ba, Arnaud Manel, Emmanuel Vian, and Florence Le Calvez-Kelm 14 Predictive Biomarkers of Response to Neoadjuvant Therapy in Muscle Invasive Bladder Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jussi Nikkola and Peter Black 15 Assessment of PD-L1 Status in Urothelial Cancer. . . . . . . . . . . . . . . . . . . . . . . . . . . Veronika Bahlinger, Arndt Hartmann, and Markus Eckstein

PART V 16

17

18

19

20

179

199

213

229 249

THERAPY DEVELOPMENT

Epigenetic Priming and Development of New Combination Therapy Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sarah Meneceur, Camilla M. Grunewald, ¨ nter Niegisch, and Miche`le J. Hoffmann Gu Evaluation of FGFR Alteration Status in Urothelial Tumors. . . . . . . . . . . . . . . . . . Veronika Bahlinger, Markus Eckstein, Arndt Hartmann, and Robert Sto¨hr Antibody-Drug-Conjugates (ADC): A Novel Treatment Option in Urothelial Carcinoma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ¨ nter Niegisch Gu Intravesical Infusion of Oncolytic Virus CG0070 in the Treatment of Bladder Cancer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Paola Grandi, Andrea Darilek, Anay Moscu, Anu Pradhan, and Roger Li Analysis of ICAM-1 Expression on Bladder Carcinoma Cell Lines and Infectivity and Oncolysis by Coxsackie Virus A21 . . . . . . . . . . . . . Kate Relph, Mehreen Arif, Hardev Pandha, Nicola Annels, and Guy R. Simpson

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

259

283

293

303

319

329

Contributors NICOLA ANNELS • Targeted Cancer Therapy, Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK MEHREEN ARIF • Targeted Cancer Therapy, Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK IBRAHIMA BA • Department of Genetics, Bichat Claude Bernard Hospital, Paris, France VERONIKA BAHLINGER • Institute of Pathology, University Hospital Erlangen, FriedrichAlexander-Universit€ at Erlangen-Nu¨rnberg, Erlangen, Germany IRINA-AFRODITA BALAUR • Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg NATALYA BENDERSKA-SO¨DER • Urologie 24, Nu¨rnberg, Germany DEBORAH L. BERRY • Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University School of Medicine, Washington, DC, USA KARIN BIRKENKAMP-DEMTRO¨DER • Department of Clinical Medicine, Aarhus University, Aarhus, Denmark EKKEHARDT BISMARCK • Urologie 24, Nu¨rnberg, Germany PETER BLACK • Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada MARK-SEBASTIAN BO¨SHERZ • Institute of Pathology, RWTH Aachen University, Aachen, Germany KRYSTA CHALDEKAS • Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University School of Medicine, Washington, DC, USA PAUL L. CRISPEN • Department of Urology, University of Florida, College of Medicine, Gainesville, FL, USA ANDREA DARILEK • CG Oncology, Inc., Irvine, CA, USA WILLIAM DONELAN • Department of Urology, University of Florida, College of Medicine, Gainesville, FL, USA LARS DYRSKJØT • Department of Clinical Medicine, Aarhus University, Aarhus, Denmark THORSTEN H. ECKE • Department of Urology, Helios Hospital, Bad Saarow, Germany; Department of Urology, Universit€ a tsmedizin Berlin Charite´, Berlin, Germany; German Study Group of Bladder Cancer (DFBK e.V.), Munich, Germany MARKUS ECKSTEIN • Institute of Pathology, University Hospital Erlangen, FriedrichAlexander-Universit€ at Erlangen-Nu¨rnberg, Erlangen, Germany DAMIANO FANTINI • Department of Urology, Northwestern University, Chicago, IL, USA; Xilio Therapeutics, Waltham, MA, USA NATHALIE FOREY • Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC), Lyon, France MARIA FRANTZI • Department of Biomarker Research, Mosaiques Diagnostics, Hannover, Germany NADINE T. GAISA • Institute of Pathology, University Hospital, RWTH Aachen University, Aachen, Germany; German Study Group of Bladder Cancer (DFBK e.V.), Munich, Germany PAOLA GRANDI • CG Oncology, Inc., Irvine, CA, USA

ix

x

Contributors

CAMILLA M. GRUNEWALD • Department of Urology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University, Duesseldorf, Germany BRENT HARRIS • Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University School of Medicine, Washington, DC, USA ARNDT HARTMANN • Institute of Pathology, University Hospital Erlangen, FriedrichAlexander-Universit€ at Erlangen-Nu¨rnberg, Erlangen, Germany ` MICHELE J. HOFFMANN • Department of Urology, Medical Faculty and University Hospital, Heinrich-Heine-University Duesseldorf, Duesseldorf, Germany; German Study Group of Bladder Cancer (DFBK e.V.), Munich, Germany MD ISMAIL HOSEN • Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC), Lyon, France; Department of Biochemistry and Molecular Biology, Faculty of Biological Sciences, University of Dhaka, Dhaka, Bangladesh CAROLINE KANNENGIESSER • Department of Genetics, Bichat Claude Bernard Hospital, Paris, France JUNG-SIK KIM • Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University School of Medicine, Washington, DC, USA APOSTOLOS KLINAKIS • Biomedical Research Foundation of the Academy of Athens, Athens, Greece SERGEI KUSMARTSEV • Department of Urology, University of Florida, College of Medicine, Gainesville, FL, USA FLORENCE LE CALVEZ-KELM • Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC), Lyon, France ALANA LELO • Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University School of Medicine, Washington, DC, USA ROGER LI • Department of Genitourinary Oncology, H. Lee Moffitt Cancer Center, Tampa, FL, USA; Department of Immunology, H. Lee Moffitt Cancer Center, Tampa, FL, USA ARNAUD MANEL • Department of Urology, Le Creusot Hospital, Le Creusot, France KLAUS MANTWILL • Department of Urology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany JOSHUA J. MEEKS • Departments of Urology, Biochemistry and Molecular Genetics, Northwestern University, Chicago, IL, USA SARAH MENECEUR • Department of Urology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University, Duesseldorf, Germany HARALD MISCHAK • Department of Biomarker Research, Mosaiques Diagnostics, Hannover, Germany; Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK MARIKA MOKOU • Department of Biomarker Research, Mosaiques Diagnostics, Hannover, Germany ANAY MOSCU • Department of Pharmacy, H. Lee Moffitt Cancer Center, Tampa, FL, USA SHAMAN NARAYANASAMY • Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg ROMAN NAWROTH • Department of Urology, University Hospital Rechts der Isar, Technical University Munich, Munich, Germany; German Study Group of Bladder Cancer (DFBK e.V.), Munich, Germany GU¨NTER NIEGISCH • Department of Urology, Medical Faculty and University Hospital Duesseldorf, Heinrich-Heine-University, Duesseldorf, Germany; Center for Integrated Oncology Aachen Bonn Cologne Du¨sseldorf (CIO ABCD), CIO-D, Aachen, Germany JUSSI NIKKOLA • Department of Urology, Tampere University Hospital, Tampere, Finland

Contributors

xi

IVER NORDENTOFT • Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark CSILLA OLAH • Department of Urology, University of Duisburg-Essen, Essen, Germany HARDEV PANDHA • Targeted Cancer Therapy, Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK YOUNGROK PARK • Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University School of Medicine, Washington, DC, USA MARTIN PEIFER • Department of Translational Genomics, University of Cologne, Cologne, Germany CHRISTOPH PETER • Institute of Molecular Medicine I, Medical Faculty, Heinrich Heine University Du¨sseldorf, Du¨sseldorf, Germany ANU PRADHAN • Department of Pharmacy, H. Lee Moffitt Cancer Center, Tampa, FL, USA THEODOROS RAMPIAS • Biomedical Research Foundation of the Academy of Athens, Athens, Greece KATE RELPH • Targeted Cancer Therapy, Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK IRYNA V. SAMARSKA • Department of Pathology, GROW – School for Oncology and Reproduction, Maastricht University, Medical Centre+, Maastricht, The Netherlands BERND J. SCHMITZ-DRA€ GER • Urologie 24, Nu¨rnberg, Germany; Department of Urology, Friedrich-Alexander University, Erlangen, Germany WOLFGANG A. SCHULZ • Department of Urology, Medical Faculty and University Hospital Du¨sseldorf, Heinrich-Heine-University, Du¨sseldorf, Germany LANCELOT SEILLIER • University Hospital RWTH Aachen University, Aachen, Germany MAHDI SHEIKH • Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC), Lyon, France GUY R. SIMPSON • Targeted Cancer Therapy, Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK ROBERT STO¨HR • Institute of Pathology, University Hospital Erlangen, Friedrich-AlexanderUniversit€ at Erlangen-Nu¨rnberg, Erlangen, Germany RAFAEL STROGGILOS • Systems Biology Center, Biomedical Research Foundation, Academy of Athens, Athens, Greece TIBOR SZARVAS • Department of Urology, University of Duisburg-Essen, Essen, Germany; Department of Urology, Semmelweis University, Budapest, Hungary TILMAN TODENHO¨FER • Studienpraxis Urologie, Nu¨rtingen, Germany; Medical Faculty, University of Tu¨bingen, Tu¨bingen, Germany BAS W. G. VAN RHIJN • Department Surgical Oncology (Urology), Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands; Department of Urology, University of Regensburg, Caritas-Hospital St. Josef, Regensburg, Germany EMMANUEL VIAN • Department of Urology Infirmerie Protestante de Lyon, Caluire et Cuire, France ANTONIA VLAHOU • Systems Biology Center, Biomedical Research Foundation, Academy of Athens, Athens, Greece TODD WALDMAN • Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University School of Medicine, Washington, DC, USA PATCHARAWALAI WHONGSIRI • Department of Biochemistry and Microbiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand MARIA ZVEREVA • Department of Chemistry, Lomonosov Moscow State University, Moscow, Russia; Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC), Lyon, France

Part I Molecular Characterization

Chapter 1 Scoring Systems for Immunohistochemistry in Urothelial Carcinoma Mark-Sebastian Bo¨sherz, Iryna V. Samarska, and Nadine T. Gaisa Abstract Immunohistochemistry is widely used in diagnostic and scientific analysis of urothelial carcinoma. Objective interpretation of staining results is mandatory for accuracy and comparability in diagnostic and therapeutic patient care as well as research. Herein we summarize and explain standardized microscopic evaluation and scoring approaches for immunohistochemical stainings. We focus on commonly used and generally feasible approaches for different cellular compartments and comment on their utility in diagnostics and research practice. Key words Urothelial carcinoma, Scoring, Immunohistochemistry, Tumor markers, Therapeutic markers

1

Introduction Immunohistochemistry allows for characterizing normal and pathological processes in tissues and is consequently an integral method in biomedicine [1, 2]. In urothelial carcinoma immunohistochemical stainings are routinely used in (differential) diagnostics [3, 4], identification of precursor lesions [5, 6], and therapeutic stratification [7, 8]. Furthermore, biomarkers are widely evaluated for putative diagnostic, therapeutic, or prognostic purposes in research settings [9–11]. However, inconsistencies in staining results and interobserver variability count among the greatest methodological challenges [12, 13], and the setback in reproducibility is potentially further amplified in case of narrowing down the scope of analysis in tissue microarrays (TMA) [14]. An integral approach to improve standardization and comparability is the reporting of staining results in scores. Over time several scoring systems for a wide range of markers were established,

Miche`le J. Hoffmann et al. (eds.), Urothelial Carcinoma: Methods and Protocols, Methods in Molecular Biology, vol. 2684, https://doi.org/10.1007/978-1-0716-3291-8_1, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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Mark-Sebastian Bo¨sherz et al.

ranging from basic estimations of staining percentages, advanced considerations of staining extent and intensity, to sophisticated calculations encompassing different tissue compartments [15, 16]. Additionally, in recent years digital approaches and automated analyses based on artificial intelligence were established to overcome the inherently subjective nature of visual evaluation of stainings in the future [17–19]. Here, we describe the currently used manual scoring systems for commonly stained biomarkers in urothelial carcinoma with background information for each marker as well as detailed written and visual guidelines for standardized calculation and interpretation of different scores. We thereby hope to contribute to methodical robustness and well-founded analyses in the diagnostic and scientific field of urothelial carcinoma.

2

Methodical Prerequisites

2.1 Staining Procedure

For reproducible results, standardized staining protocols are crucial. We previously described manual and automated staining protocols for different markers [20]. Immunohistochemical staining procedures comprise many essential steps, including appropriate grossing of the specimen, proper fixation, paraffin block preparation, antigen retrieval, selection and preparation of antibody and reagents, incubation, washing, and counterstaining [21]. All steps have different critical points that might affect immunohistochemistry (IHC) results. The standardized protocols and procedures are therefore necessary to ensure reliable reproducible results. Furthermore, for methodological validity, we emphasize the importance of appropriate positive and negative controls for each staining, preferably as on-slide controls (for positive controls). This is particularly important if staining intensity has to be evaluated.

2.2 Determination of Dimensions under a Microscope

Some scoring systems demand an estimation of positive staining as a proportion of a region of interest; in such cases knowledge of the field of view in different tissue areas and different magnifications is crucial. The field diameter of the field of view under a microscope is calculated by dividing the field number of the eyepiece by the objective’s magnification [22]. For example, the field of view’s diameter of an eyepiece with a field number of 20 mm at the 20× objective equals 1 mm; the corresponding area equals (1 mm/ 2)2 × π ≈ 0.785 mm2.

Scoring Systems for Immunohistochemistry

3

5

Markers and Applicable Scoring Systems in Urothelial Carcinoma For immunohistochemical marker evaluation, only stainings that are placed in the correct cellular topography (e.g., membranous, nuclear, cytoplasmic, etc.) of the protein of interest can be considered positive. It is essential to be aware that abnormalities during the staining procedure may result in a high background signal and, therefore, low intensity of the specific signal, which might affect the scoring. In the following sections, we present scoring systems for urothelial carcinoma markers, based on their expectably stained compartments.

3.1 Membranous Markers 3.1.1

PD-L1

3.1.2 Receptor Tyrosine Kinases (RTKs)

Immune checkpoint inhibitor (ICI) therapy has revolutionized the clinical management of several tumor entities (partly) based on (immuno-)histopathological assessment [23, 24]. In urothelial carcinoma, ICI therapy is routinely eligible for adjuvant [25] and firstline treatment of locally or systemically progressed disease [26] in cases of immunohistochemically positive PD-L1 expression [7]. The complexity of PD-L1 assessment is further increased by the availability of various antibody clones and different scoring algorithms as well as cut-offs depending on the current approval of PD-L1 inhibitors [7]. In routine diagnostics the tumor proportion score (TPS), the combined positivity score (CPS), and the immune cell score (IC) are primarily used [27]. Several essential factors can affect the results of the staining. First, it is necessary to stain the most recent paraffin block with a sufficient volume of invasive neoplastic cells (>100) without cauterization artifacts or necrotic areas. The metastatic tumor might have different PD-L1 expression from the primary tumor. However, evaluating the PD-L1 staining can be challenging in metastasis to the lymph nodes. Moreover, neoadjuvant chemotherapy or immunotherapy may alter PD-L1 expression as well. Therefore, using a tissue sample obtained immediately after neoadjuvant chemotherapy or immunotherapy is not recommended [7]. Recent studies indicate major interchangeability of the different antibody clones except for SP142, which detects significantly fewer tumor cells [7, 28]. Exemplary staining patterns for TPS, CPS, and IC scoring are presented in Tables 1, 2, and 3 and Fig. 1. Receptor tyrosine kinases are common oncogenes in a wide spectrum of malignancies [29]. The availability of pharmacological inhibitors for many molecules made their expression within a given tumor a promising approach in the context of personalized medicine [30, 31].

Mark-Sebastian Bo¨sherz et al.

6

Table 1 PD-L1 scoring via tumor proportion score Tumor proportion score (TPS) [7, 27] Description Quantitative assessment of the stained proportion of tumor cells Designation PD-L1 Scope

Tumor cells

Calculation 1. Define the total amount of tumor cells (=100%) 2. Assess the proportion of tumor cells with membranous PD-L1 staining Results

Remarks

Range Cut-offs

0–5 TC0 TC1

0% C/T>G, C>A/G>T, C>G/G>C have error rates of 10-5, and A>G/T>C have error rates of 10-4. The C>A/G>T errors originate in part due to DNA damage during sample handling [19]. 9. One should be aware that whatever a tumor-informed or tumor-agnostic panel approach is chosen, clonal evolution of mutations during the disease course of sub-clonal origin, treatment-induced new cancer driver mutations, or potential actionable targets might be missed. The only solution for this is the costly deep WGS or WES of longitudinal cfDNA plasma samples during the disease course. 10. More than 25% of the somatic mutations in COSMIC are C>T alterations [20]. Spontaneous deamination of methylated cytosine is a frequent source of C>T/G>A errors [15]. The C>T errors depend strongly on the sequence context, with the highest error rates for G(C>T)G and increased error rates for G (C>T)N or N(C>T)G [18]. C>T mutations induced by deamination enzymes of the APOBEC family are frequent in, e.g., urothelial cancers, e.g. C>T in TCA and TCT trinucleotide motifs [21]. 11. For robust error correction, 9 bp unique molecular identifiers (UMIs) are incorporated by replacing the twist adapters with xGen™ UDI-UMI Adapters (Integrated DNA Technologies).

Acknowledgments We thank Mads Heilskov Rasmussen and Amanda Frydendahl Boll Johansen for collaboration on double capture protocol development. We thank Lotte Gernyx for technical assistance during of NGS library preparation and capture protocols development. References 1. Thierry AR, El Messaoudi S, Gahan PB et al (2016) Origins, structures, and functions of circulating DNA in oncology. Cancer Metastasis Rev 35:347–376 2. Kustanovich A, Schwartz R, Peretz T, Grinshpun A (2019) Life and death of circulating cellfree DNA. Cancer Biol Ther 20:1057–1067

3. Alcaide M, Cheung M, Hillman J et al (2020) Evaluating the quantity, quality and size distribution of cell-free DNA by multiplex droplet digital PCR. Sci Rep 10:12564 4. Cristiano S, Leal A, Phallen J et al (2019) Genome-wide cell-free DNA fragmentation in patients with cancer. Nature 570:385–389

NGS-Based Tumor-Informed Analysis of Circulating Tumor DNA 5. Christensen E, Birkenkamp-Demtro¨der K, Sethi H et al (2019) Early detection of metastatic relapse and monitoring of therapeutic efficacy by ultra-deep sequencing of plasma cell-free DNA in patients with urothelial bladder carcinoma. J Clin Oncol 37:1547–1557 6. Sanz-Garcia E, Zhao E, Bratman SV, Siu LL (2022) Monitoring and adapting cancer treatment using circulating tumor DNA kinetics: current research, opportunities, and challenges. Sci Adv 8:eabi8618 7. Steensma DP, Bejar R, Jaiswal S et al (2015) Clonal hematopoiesis of indeterminate potential and its distinction from myelodysplastic syndromes. Blood 126:9–16 8. Newman AM, Lovejoy AF, Klass DM et al (2016) Integrated digital error suppression for improved detection of circulating tumor DNA. Nat Biotechnol 34:547–555 9. Schmitt MW, Kennedy SR, Salk JJ et al (2012) Detection of ultra-rare mutations by nextgeneration sequencing. Proc Natl Acad Sci U S A 109:14508–14513 10. Bae JH, Liu R, Nguyen E et al (2021) CODEC enables “single duplex” sequencing. bioRxiv. 2021.06.11.448110 11. Shendure J, Balasubramanian S, Church GM et al (2017) DNA sequencing at 40: past, present and future. Nature 550:345–353 12. Gerstung M, Papaemmanuil E, Campbell PJ (2014) Subclonal variant calling with multiple samples and prior knowledge. Bioinformatics 30:1198–1204 13. Birkenkamp-Demtro¨der K, Christensen E, Nordentoft I et al (2018) Monitoring

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treatment response and metastatic relapse in advanced bladder cancer by liquid biopsy analysis. Eur Urol 73:535–540 14. Pallisgaard N, Spindler K-LG, Andersen RF et al (2015) Controls to validate plasma samples for cell free DNA quantification. Clin Chim Acta 446:141–146 15. Salk JJ, Schmitt MW, Loeb LA (2018) Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations. Nat Rev Genet 19:269–285 16. Gorini F, Scala G, Di Palo G et al (2020) The genomic landscape of 8-oxodG reveals enrichment at specific inherently fragile promoters. Nucleic Acids Res 48:4309–4324 17. Brodin J, Mild M, Hedskog C et al (2013) PCR-induced transitions are the major source of error in cleaned ultra-deep pyrosequencing data. PLoS One 8:e70388 18. Ma X, Shao Y, Tian L et al (2019) Analysis of error profiles in deep next-generation sequencing data. Genome Biol 20:50 19. Chen L, Liu P, Evans TC Jr, Ettwiller LM (2017) DNA damage is a pervasive cause of sequencing errors, directly confounding variant identification. Science 355:752–756 20. Tate JG, Bamford S, Jubb HC et al (2019) COSMIC: the catalogue of somatic mutations in cancer. Nucleic Acids Res 47:D941–D947 21. Chan K, Roberts SA, Klimczak LJ et al (2015) An APOBEC3A hypermutation signature is distinguishable from the signature of background mutagenesis by APOBEC3B in human cancers. Nat Genet 47:1067–1072

Chapter 12 Considering the Effects of Modern Point-of-Care Urine Biomarker Assays in Follow-Up of Patients with High-Risk Non-muscle-Invasive Bladder Cancer Thorsten H. Ecke, Natalya Benderska-So¨der, Ekkehardt Bismarck, Bas W. G. van Rhijn, Tilman Todenho¨fer, and Bernd J. Schmitz-Dra¨ger Abstract Background: Although a plethora of urine markers for diagnosis and follow-up of patients with bladder cancer (BC) has been developed and studied, the clinical impact of urine testing on patient management remains unclear. The goal of this manuscript is to identify scenarios for a potential use of modern point-ofcare (POC) urine marker assays in the follow-up of patients with high-risk non-muscle-invasive BC (NMIBC) and estimate potential risks and benefits. Methods: To permit comparison between different assays, the results of 5 different POC assays studied in a recent prospective multicenter study including 127 patients with suspicious cystoscopy undergoing TURB were used for this simulation. For the current standard of care (SOC), a “marker-enforced” procedure, and a combined strategy sensitivity (Se), estimated number of cystoscopies, and the numbers needed to diagnose (NND) over a 1-year follow-up period were calculated. Results: For regular cystoscopy (SOC), a Se of 91.7% and a NND of 42.2 repetitive office cystoscopies (WLCs) for 1 recurrent tumor at 1 year were calculated. For the “marker-enforced” strategy, marker sensitivities between 94.7% and 97.1% were observed. The “combined” strategy yielded for markers with a Se exceeding 50% an overall Se at 1 year similar or superior to the current SOC. Savings regarding the number of cystoscopies in the “marker-enforced” strategy vs. the SOC were small, while, depending on the marker, up to 45% of all cystoscopies may be saved using the “combined” strategy. Conclusions: Based on the results of this simulation, a marker-supported follow-up of patients with high-risk (HR) NMIBC is safe and offers options to significantly reduce the number of cystoscopies without compromising the Se. Further research focusing on prospective randomized trials is needed to finally find a way to include marker results into clinical decision-making. Key words Urinary tumor markers, Bladder cancer, Follow-up, Surveillance, Diagnosis, Disease management

Thorsten H. Ecke and Natalya Benderska-So¨der contributed equally with all other contributors. Miche`le J. Hoffmann et al. (eds.), Urothelial Carcinoma: Methods and Protocols, Methods in Molecular Biology, vol. 2684, https://doi.org/10.1007/978-1-0716-3291-8_12, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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Introduction Although a variety of diagnostic point-of-care (POC) urine marker assays had been developed over the recent decades and is used at urology centers and in private practices to follow-up patients with non-muscle-invasive bladder cancer (NMIBC), concepts on implementing these assays in routine follow-up are missing [1]. In consequence, repetitive office cystoscopy (WLC) and urine cytology remain the mainstay of surveillance in patients with NMIBC until today [2, 3] even though side effects of WLC like hematuria and urinary tract infection have been reported and obviously generate anxiety among patients [4–6]. Despite all efforts, tumor progression to MIBC, putting the patient at risk for a potentially fatal outcome, is still observed in approximately 10% of patients with primary high-risk (HR) NMIBC at 5 years [7]. For low
/intermediate-risk NMIBC, tumor recurrence is the major concern. Therefore, the use of urine markers may yield a reduction in WLC potentially delaying detection of tumor recurrence. A recent simulation study [8] suggested that this procedure may be feasible and a prospective trial exploring this risk group is ongoing [9]. As the sensitivity of POC assays in low-grade tumors apparently is limited for several tests [10], this study analyzes if and how a use of POC urine markers may be useful in the follow-up of patients with HR NMIBC. This question has gained new interest after introduction of the recent modification of the EAU risk classification [2]. Regrouping of the small group of very high-risk tumors to a separate category has tremendous impact, substantially lowering the tumor progression rates in HR NMIBC as reported for the previous classification [7, 11]. This new situation requires a reconsideration of the current follow-up procedure of these patients. The use of POC assays appears attractive as these assays are readily available, can be performed without the need of specific equipment, and are relatively cheap. In general, these markers may be used as an adjunct for routine follow-up to improve the sensitivity (Se) of office white light endoscopy (WLC) and, in consequence, may improve early detection [12, 13] (Fig. 1). A marker-guided follow-up restricting WLC to patients with a positive urine marker test represents a different strategy with the intention to decrease the diagnostic workload [9]. This procedure may be combined with routine WLC, a concept used in the CeFub trial [12, 13] (Fig. 1). The aim of this study was to analyze the potential impact of commercially available POC urine markers in the management of patients with HR NMIBC considering different surveillance strategies. This simulation is of particular interest as the underlying data were retrieved from a recent prospective multicenter study

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Fig. 1 Designs for standard of care (SOC), a “marker-enforced” procedure, and a “combined” strategy in patients with high-risk NMIBC

comprising five different POC assays and thus permitting a direct comparison between the assays. Based on these data and expected results on tumor recurrence, we simulated the outcome regarding diagnosis of tumor recurrence and frequency of WLC for different strategies over a 1-year interval. 1.1 Target Population

Recently, the EAU guideline committee initiated a comprehensive work-up of the former risk classification [2]. This procedure was triggered by the fact that data included in the old European Organisation for Research and Treatment of Cancer (EORTC) risk tables originate from control groups of six prospective randomized trials conducted in the 1980s [11] and may no longer represent the current course of disease. Furthermore, the old EORTC risk tables are based on the 1973 tumor grading system and did not consider the WHO 2004/2016 grading classification. The new EAU nomogram based on more recent data collected from institutional databases of several high-ranking academic centers should make up for these deficits [2, 7]. It includes the WHO 2004/2016 grading classification and considers potential technical improvement and changes, e.g., induced by technically improved WLC resolution and routine re-TURB. Nevertheless, concerns remain as (1) the data were not derived from prospective trials, (2) follow-up intervals may be too short, (3) data were mostly collected from academic centers and therefore may not reflect a real-world situation, and (4) data from patients after adjuvant intravesical BCG therapy were not included [14]. It should be mentioned that there are conflicting data, e.g., from a large multicenter systematic review and meta-analysis on the outcome of 3088 patients with high-risk and very high-risk NMIBC (T1G3, multifocal, highly recurrent, or carcinoma in situ) demonstrating that 21% of the patients developed progression to MIBC and 428 (14%) subsequently died of BC after a median follow-up of 48–123 months [15]. However, this analysis also

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includes a relevant number of very HR patients, and the quality of surveillance and adjuvant therapy was not uniform among different studies. As the authors consider adjuvant BCG therapy as a current standard in patients with HR NMIBC [2, 3], consideration of the CUETO risk tables [16] may be discussed as an alternative; however, recent validation studies [17, 18] and data from the randomized NIMBUS trial suggest that at least prediction of tumor recurrence by the CUETO tables may overestimate the actual risk [19]. Summarizing the references mentioned above, we applied a 1-year recurrence rate of 10% for patients with HR NMIBC to this simulation. 1.2 Performance of WLC

It is of key importance to notice that WLC, the so-called gold standard, has limitations: several studies and subsequent systematic reviews with meta-analyses demonstrate that the Se of WLC, routinely conducted as an office cystoscopy, will not exceed 75% in recurrent HR tumors if compared with blue light cystoscopy and subsequent TURB [20, 21]. In addition, also specificity (Sp) of WLC is 30% of all TURB procedures in the multicenter study underlying this analysis [23]. Although this observation may also have technical reasons (e.g., a loss of small tissue specimens or cauterization artifacts), it is obvious that misinterpretation of cystoscopic findings accounts for a relevant part of this problem. As the results of the CeFub trial suggest that the use of markers does not affect the specificity of WLC, this point was not addressed in this simulation [11, 12]. For this analysis, sensitivity of routine WLC was set to 75% based on the meta-analysis by Burger and associates [21]. However, the pioneering phase III trial by v. d. Aa and coworkers could demonstrate that performance of WLC along with the awareness of a positive marker results significantly improved Se of WLC [11, 12]. As upper tract tumors are infrequent, we considered the outcome of current follow-up in patients with HR NMIBC as the result of WLC.

1.3 Performance of Urine Markers: Urine Cytology

Urine cytology represents a standard in management of patients undergoing surveillance for high-risk NMIBC and is implemented in current clinical guidelines [2, 3]. The usefulness of this examination is supported by the fact that sensitivity in high-grade NMIBC is considerable along with an outstanding specificity. Nevertheless, it was not included in this analysis for several reasons: (1) Despite a good sensitivity in high-grade (HG) disease, it is generally accepted

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that sensitivity of molecular urine markers is higher as consistently demonstrated by prospective studies reported by respective reviews [10]. It is the authors’ bias that in high-risk disease with a potentially fatal outcome, sensitivity is decisive, specifically if the frequency of WLC is reduced. (2) Reports on performance of urine cytology greatly differ, thus generating difficulties to estimate sensitivity of cytology within the context of this consideration [10]. The reasons for these differences are subjectivity and interobserver variation due to differing expertise of cytopathologists [24]. Finally, (3) it remains unclear how recommendations on a use of urine cytology should be implemented in patient management [2, 3].

2

Materials This study is based on the results of a recent prospective multicenter study [23]. A total of 206 urine samples (second morning urine) from patients with a suspicious WLC result during follow-up for NMIBC were collected before TURB at 8 different German urology centers. The study was approved by the local Institutional Review Board of National Medical Association Brandenburg (No. AS 147(bB)/2013, updated 2020). All patients provided written informed consent. Patient characteristics are summarized in Table 1. For 127 patients (61.6%), TURB confirmed the suspicious results of the previous WLC; in 74 cases (35.9%) histopathology did not confirm the presence of tumor cells. In five cases (2.4%), histopathology was not available.

3

Methods All urine samples were analyzed at the participating centers using the (1) BTA stat®, (2) NMP22® BladderChek®, (3) UBC® rapid test quantitative using the concile Omega 100 POC reader, (4) CancerCheck® UBC® Rapid VISUAL, and (5) the Uromonitor® assay according to the manufacturer’s instructions.

3.1

BTA Stat®

The bladder tumor antigen (BTA stat®) test is a rapid, noninvasive, qualitative urine test that detects a bladder tumor-associated antigen (human complement factor H-related protein) in urine [25, 26]. An immunochromatographic reaction is performed in a cartridge to permit visual detection of the presence of the bladder tumor antigen. Based on the results of the underlying study [23], an overall sensitivity of 75.4% for the detection of HG tumors and a specificity of 53.8% were used for this analysis (Table 2).

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Table 1 Demographic characteristics of patients included in the assessment of POC assays in 206 patients with previous NMIBC and suspicious WLC [TE] Parameter (n = 206)

Result

Median age (years)

74.0

Range: 38–96

Gender (%) [m/f]

79.1/20.9

Ratio: 4/1

Smoking status (%) [active, former/never]

55.3/26.7

Missing: 18.0

TURB result n (%)

Missing: 5 (2.4%)

CIS

13 (6.3)

LG NMIBC

54 (26.2)

HG NMIBC

35 (16.9)

MIBC

16 (7.8)

Negative

79 (36.3)

Table 2 Sensitivity and specificity of POC tests in 206 patients with suspicious WLC based on the histological results of a subsequent TURB [23]

Assay

Cutoff

n

Sensitivity (%) LG

Sensitivity (%) HG

n

Specificity (%)

BTA stat®

Visual pos.

127

59.6

75.4

79

53.8

NMP22® BladderChek®

Visual pos.

127

8.8

39.7

79

92.4

CancerCheck® UBC® rapid VISUAL

Visual pos.

127

35.1

52.2

79

87.2

UBC® rapid test

10 μg/l

127

57.9

76.8

79

63.3

Visual pos.

127

60.0

59.4

79

94.1

Uromonitor

®

3.2 NMP22® BladderChek®

The NMP22® BladderChek® is based on the detection of NMP22, a nuclear mitotic apparatus protein that is released from dead cells (e.g., apoptotic cells). In urothelial carcinoma cells, NMP22 is elevated concordant with the structural and morphological changes characteristic of malignant cell nuclei [27]. Based on the results of the underlying study [23], an overall sensitivity of 39.7% for the detection of HG tumors and a specificity of 92.4% were used for this analysis (Table 2).

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The UBC® Rapid assay (concile, Freiburg, Germany) is marketed in two different versions, either as the qualitative (visual) CancerCheck® UBC® Rapid VISUAL and as the quantitative POC assay UBC® Rapid Test, using the concile Omega 100 POC reader [28]. Both assays are targeting cytokeratins 8 and 18. Based on the results of the underlying study [23], an overall sensitivity of 52.2% for the detection of HG tumors and a specificity of 87.2% were used for this analysis for the CancerCheck® UBC® Rapid VISUAL, and an overall sensitivity of 76.8% for HG tumors and a specificity of 63.3% were used for the quantitative point-ofcare assay UBC® Rapid Test (Table 2).

3.4

Uromonitor®

The Uromonitor® test is a DNA-based assay for the detection of oncogene hotspot mutations in bladder cancer tumor cells exfoliated to urine in a real-time PCR platform, targeting alterations of the TERTp c.1-124C > T, TERTpc.1-146C > T, FGFR3 p.R248C, and FGFR3 p.S249C [29]. In patients under surveillance for non-muscle-invasive bladder cancer (NMIBC), a minimum of 10 mL of urine was collected before cystoscopy. The sample is filtered through a 0.8-μm filter membrane and stored at room temperature. In a next step, DNA extraction and Uromonitor® testing are performed. Based on the results of the underlying study [23], an overall sensitivity of 59.4% for the detection of HG tumors and a specificity of 94.1% were used for this analysis (Table 2). Uromonitor was the only marker to detect low-grade (LG) and HG tumor recurrence with a comparable sensitivity.

3.5

Data Work-Up

The simulation was restricted to a 1-year period. As data quality on the distribution of tumor recurrence over the time is poor and consideration would further complicate the analysis, we assumed an equal distribution of recurrences over the surveillance period and between HR patients at “higher and lower” risk. A negative finding at the 3-month WLC was chosen as the starting point. We based the analysis on four follow-up visits/year as recommended for HR NMIBC by major guidelines [2, 3]. Three different approaches were included in this consideration: 1. The first one represents the current standard of care (SOC) with 3-month WLC [2, 3] (Fig. 1a). 2. The second approach (“marker enforced”) consists of a marker examination and subsequent information of the urologist before WLC [12, 13] (Fig. 1b). 3. Finally, a combination of a marker-guided follow-up with regular cystoscopy at 3 and 12 months was added (“combined,” e.g., CeFub trial) [12, 13] (Fig. 1c).

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For all strategies the total number of WLC, the percentage of WLCs saved in the different procedures if opposed to the SOC, the proportion of tumors diagnosed based on a 10% recurrence rate, and the number needed to diagnose (NND) one recurrent tumor were calculated. We did not consider interval diagnoses triggered by gross hematuria as these are rare and we concluded that these events are not likely to significantly affect the results. Based upon literature cited above [20, 21], Se of WLC was set to 75%. In case of positive marker results, WLC Se was corrected by 25–94% as suggested by fluorescence TURB results and a prospective randomized trial [12, 13, 21]. Se and Sp of markers were used as outlined above and summarized in Table 2 [23]. Patients with tumor recurrence during follow-up were excluded from further consideration.

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Notes The Notes of the simulation are summarized in Table 3. The calculation of the performance of a WLC-based follow-up (SOC) with a Se of 91.7% appears to reflect observations in daily practice. A NND of 42.2 WLCs for detection of one recurrent tumor was calculated. For the “marker-enforced” strategy, marker sensitivities between 94.7% (NMP22® BladderChek®) and 97.1% (CancerCheck® UBC® Rapid VISUAL) were observed (Table 3). The “combined” strategy, based on the procedure reported for the CeFub study [13], appears of interest as markers with a Se exceeding 50% could generate an overall Se comparable or slightly superior to the current SOC. Only NMP22® BladderChek® may be related to a slightly lower Se than the SOC, while the other assays were calculated to yield high sensitivities ranging between 94.7% and 98.4% (UBC(R) rapid test, quantitative) (Table 3). Savings regarding the number of WLCs in the “markerenforced” strategy were small and ranged between 0.18% (NMP22® BladderChek®, CancerCheck® UBC® Rapid VISUAL) and 0.36% (UBC® Rapid Test), translating into NND ranging from 39.7 (UBC® Rapid Test) to 40.8 (NMP22® BladderChek®) (Table 3).

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Discussion Surveillance of patients with HR NMIBC has remained a challenge until today with a need to improve the balance between the risk of missing a tumor recurrence or progression and a potential overdiagnosis rendering patients to unnecessary invasive procedures. A

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Table 3 Sensitivity, no. of WLCs, and NND based on different follow-up regimens. Green, strategies presumably having an equal or superior sensitivity as the SOC

Strategy

WLC Total no. of saved vs. SOC WLC (%)

SOC

3.872

0

91.7

42.2

3.857

0.34

97.0

39.8

3.865

0.18

94.7

40.8

3.864

0.18

96.4

40.1

3.858

0.36

97.1

39.7

3.861

0.28

96.1

40.2

2.847

26.47

96.3

29.6

2.134

44.89

89.2

23.9

2.211

42.90

94.7

23.3

UBC® rapid test

2.668

31.10

98.4

27.1

Uromonitor®

2.097

45.84

96.0

21.8

Recurrence diagnosed Sensitivity (n ¼ 100) (%) NND

Marker enforced BTA stat® ®

NMP22 BladderChek ®

CancerCheck UBC rapid VISUAL

®

®

UBC® rapid test Uromonitor

®

Combined (CeFub) BTA stat® ®

NMP22 BladderChek ®

CancerCheck UBC rapid VISUAL

®

®

plethora of studies published over the last decades suggest that molecular urine markers might be helpful [25–29, overview in 10]; however, only the CeFub trial has provided proof within the context of a prospective, randomized trial using microsatellite analysis [12, 13]. Despite this, recommendations on how to implement a biomarker test result into clinical decision-making are missing [1– 3]. POC molecular urine markers appear attractive for a use in patient surveillance in private practice as processing and handling are easy and do not require performance by a technician. No expensive laboratory infrastructure is required, the results are rapidly available, and most assays are relatively cheap. These features along with the fact that reimbursement is directly made to the physician-in-charge may explain the acceptance of these assays by the physician community. On the other hand, the limited sensitivity of most assays in low-grade bladder cancer limits the usefulness of POC markers in patients with previous low-grade NMIBC [1, 10, 23] (Table 2).

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The recent reclassification of the former NMIBC risk groups by the EAU working group may be considered tremendously helpful for a use of urine markers in follow-up of patients with HR NMIBC [2]. Sylvester et al. [7] used data from a large contemporary database for comparison of the classification based on the old risk groups (WHO 1973 grading) versus the new classifications based on both, the WHO 1973 grading and the WHO 2004/2016 grading classification. Key innovation is the introduction of a small very HR group (2–3% from a total of 3401 patients) with an unfavorable prognosis, indicated by a 5-year progression rate of >40%. This group was extracted from the former HR group, thus lowering progression rates in the new HR group. This resulted in a lower progression rate at 1 year of less than 4% in patients with primary HR NMIBC. Based on this change, reconsideration of how to implement diagnostic markers in follow-up of patients with HR NMIBC appears timely. In general, several strategies are conceivable aiming at a reduction of WLCs or an improved diagnostic sensitivity. Furthermore, combinations are conceivable. Such a combined procedure was chosen for the only prospective randomized marker trial published so far [12, 13] (Fig. 1). van der Aa and coworkers conducted a multicenter clinical trial in 448 patients with NMIBC (pTa, pT1, G1, G2). The voided urine positive or negative test results using microsatellite analysis were communicated to the urologist in the intervention arm of 226 patients, in which cystoscopy was done in case of a positive test results at 3, 12, and 24 months. At a median 34-month followup, 218 recurrences were detected in the intervention arm compared to only 163 in the control arm (p ¼ 0.001). Inspired by the finding of the CeFub trial that the knowledge of a positive marker result significantly improves Se of WLC, we added a marker-enforced strategy, adding an upfront marker result to a subsequent WLC (Fig. 1). This simulation intended to compare different surveillance strategies regarding their Se but also to estimate patient burden reflected by the number of WLCs needed to diagnose (NND) recurrence. The strength of this consideration relates to the fact that data were used from a recent multicenter study that permit a side-by-side comparison of several commercially available POC assays [23]. Furthermore, data on specificity appear very robust, as all patients received a TURB with histopathologic assessment. There is an important observation in this study suggesting that consideration of urine markers in tumor surveillance may have additional effects: more than one out of three TURBs did not confirm the presence of tumor tissue (Table 2) [23]. Several reasons, e.g., tissue damage caused by electrocauterization, may be responsible for at least a part of this observation. Nevertheless, this observation is supported by previous findings by Schmitz-Dra¨ger

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et al. reporting a histologically negative TURB result in 24% of patients with previous low
/intermediate-risk NMIBC in a retrospective monocenter analysis [22]. The authors concluded that consideration of a negative immunocytology result could have saved a relevant number of patients from an unnecessary intervention. The fact that a high rate of histopathologically negative TURBs was also observed in the present multicenter study conducted by experienced urology centers including several academic referral centers further supports the need for changes in current surveillance of patients with NMIBC [23]. Since observations on the specificity of WLC are rare and widely differ, we did not consider this aspect in the present simulation. The authors postulate that Se of a new follow-up regimen should be equal or superior to the SOC. Based on this prerequisite, a “marker-enforced” procedure is likely to generate a higher Se, but also “combined” strategies may generate results equal or superior to the SOC (Table 3). As suggested in Table 3, all strategies and markers yield a good overall Se despite obvious limitations regarding the sensitivity of WLC and urine markers. The reason behind is repetitive testing: those tumors not detected at one visit remain in the “surveillance pool” and may be diagnosed at the upcoming visit. This is demonstrated by the fact that, despite an apparently low Se, WLC detects 92% of all tumors within 1 year, which matches with experience gained from routine practice; in addition, it should be kept in mind that surveillance will further continue. As expected, combining an upfront marker examination with a subsequent WLC (“marker-enforced” strategy) (Fig. 1) improved Se for all markers from 91.7% (SOC) to values between 94.7% and 97.1% (Table 3). Given the fact that efforts to achieve this improvement are limited, a > 5% increase as calculated for the BTA stat® and the UBC® Rapid Test appears remarkable, even though it is not statistically significant due to the small number of cases. On the other hand, it is obvious that there are no relevant savings regarding the diagnostic burden reflected by NND of 40 WLCs yielding a single tumor diagnosis. However, given an overall risk of tumor progression of 10% over a 5-year interval [7] and the fact that most progressing tumors are likely to be diagnosed during routine follow-up visits, the authors assume that an improved Se (marker-enforced strategy) will only have marginal effects on early detection and subsequent patient survival. Application of the simulation to a “combined” strategy as used in the CeFub trial did obviously not compromise Se. Only the NMP22® BladderChek® yielded an overall Se slightly below the SOC, while for the UBC® Rapid Test, an overall Se of 98.4 was calculated (Table 3). Unlike for the “marker-enforced” strategy, savings of WLCs in the “combined” strategy apparently would be

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significant with reductions ranging between 26.5% (BTA stat®) and 45.8% for the Uromonitor® due to its high Sp. The NND in this scenario dropped to nearly 50% of the SOC strategy for the Uromonitor®. As all calculations are based on the same assumptions, results may differ in a real-world situation regarding the absolute height of the effects, but relation between the strategies and markers should be maintained. The recurrence rate was found to be of key importance for this simulation as higher rates will improve performance of surveillance, while lower rates would have an opposite effect. A 10% tumor recurrence rate in patients with HR NMIBC at 1 year may slightly overestimate the actual risk; however, this figure appeared the best estimate currently available. We conclude from these data that, despite limitations regarding assay performance, commercially available POC assays harbor the potential to improve management of patients with HR NMIBC by improving Se of WLC, which may in turn improve early detection and impact tumor progression and/or reduce the amount of WLC procedures and thus improve the NND. The key to change is to consider marker results in clinical decision-making. There are several limitations that apply to this study: 1. The reported frequency of tumor recurrences greatly differs in the literature [15, 16]. However, as the new EAU risk calculator only provides an estimation of tumor progression in patients without adjuvant treatment [2, 7], we based recurrence rates for this simulation on contemporary though retrospective cohort studies and the 2-year follow-up results of a recent phase III trial [15, 17, 19]. 2. Marker performance may be overestimated, as urine testing was done in patients with a suspicious WLC before TURB [23]. On the other hand, specificity information appears extremely robust, as a negative finding was not only supported by a negative WLC but confirmed by negative histopathology. 3. The problem of “anticipatory positive” marker results could not be addressed in this simulation thus potentially underestimating marker performance. 4. Previous studies could demonstrate improved sensitivity for multi-marker testing [30]. While this option appears not to be realistic for “advanced” high performance molecular marker assays, based on logistic challenges and costs, combination of two or even more POC assays would be conceivable. As only limited data for combined testing are available and multimarker testing harbors the risk of a decreased Sp, we did not consider this aspect in this study.

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This simulation should encourage the urologic community to question current surveillance regimens of patients with HR NMIBC, which are, so far, based upon expert opinion and the anticipation of WLC as a “gold standard.” The authors hope that our consideration may assist future investigators to develop hypotheses, design relevant studies, and calculate sample sizes.

6

Conclusions This simulation suggests that implementation of diagnostic POC assays may yield a similar sensitivity if compared to regular WLC, the current standard of care, in the follow-up of patients with HR NMIBC. Furthermore, depending on the strategy chosen, the number of WLCs may be safely reduced and the NND can be significantly lowered. The authors conclude that further prospective randomized clinical trials providing experimental proof of our simulation are urgently needed.

References 1. Kamat AM, Vlahou A, Taylor JA et al (2014) Urine markers in the management of high risk non muscle-invasive bladder cancer. Urol Oncol 32:1069–1077 2. Babjuk M, Burger M, Capoun O et al (2022) European Association of Urology guidelines on non-muscle-invasive bladder cancer (ta, T1, and carcinoma in situ). Eur Urol 81(1): 75–94 3. Chang SS, Boorjian SA, Chou R (2016) Diagnosis and treatment of non-muscle invasive bladder cancer: AUA/SUO guideline. J Urol 196(4):1021–1029 4. Herr HW (2015) The risk of urinary tract infection after flexible cystoscopy in patients with bladder tumor who did not receive prophylactic antibiotics. J Urol 193:548–551 5. Cusumano JA, Hermenau M, Gaitanis M et al (2020) Evaluation of post-flexible cystoscopy urinary tract infection rates. Am J Health Syst Pharm 77(22):1852–1858 6. McClintock G, Wong E, Mancuso P et al (2021) Music during flexible cystoscopy for pain and anxiety – a patient-blinded randomised control trial. BJU Int 128(Suppl 1): 27–32 7. Sylvester RJ, Rodrı´guez O, Hernández V et al (2021) European Association of Urology (EAU) prognostic factor risk groups for nonmuscle-invasive bladder cancer (NMIBC) incorporating the WHO 2004/2016 and WHO 1973 classification Systems for Grade:

an update from the EAU NMIBC guidelines panel. Eur Urol 79:480 8. Roupret M, Gontero P, McCracken SRC et al (2022) Reducing the frequency of follow-up cystoscopy in low-grade pTa non–muscle-invasive bladder cancer using the ADXBLADDER biomarker. Eur Urol Focus 8(6):1643–1649 9. Benderska-So¨der N, Hovanec J, Pesch B et al (2020) Towards non-invasive follow-up of low risk bladder cancer – rationale and concept of the UroFollow trial. Urol Oncol 12:886–895 10. Schmitz-Dra¨ger BJ, Droller M, Lokeshwar VB et al (2015) Molecular molecular markers for bladder cancer screening, early diagnosis and surveillance. Urol Int 94:1–24 11. EORTC Risk calculator: http://www.eortc.be 12. van der Aa MN, Steyerberg EW, Bangma C et al (2010) Cystoscopy revisited as the gold standard for detecting bladder cancer recurrence: diagnostic review bias in the randomized, prospective CEFUB trial. J Urol 183(1):76–80 13. van der Aa MN, Zwarthoff EC, Steyerberg EW et al (2009) Microsatellite analysis of voidedurine samples for surveillance of low-grade non-muscle-invasive urothelial carcinoma: feasibility and clinical utility in a prospective multicenter study (cost-effectiveness of follow-up of urinary bladder cancer trial [CEFUB]). Eur Urol 55(3):659–667 14. Lobo N, Hensley PJ, Bree KK et al (2022) Updated European Association of Urology

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(EAU) prognostic factor risk groups overestimate the risk of progression in patients with non-muscle-invasive bladder cancer treated with bacillus Calmette-Gue´rin. Eur Urol Oncol 5(1):84–91 15. van den Bosch S, Witjes JA (2011) Long-term cancer-specific survival in patients with highrisk, non-muscle-invasive bladder cancer and tumour progression: a systematic review. Eur Urol 60(3):493–500 16. Fernandez-Gomez J, Madero R, Solsona E et al (2009) Predicting non muscle invasive bladder cancer recurrence and progression in patients treated with bacillus Calmette-Guerin: the CUETO scoring model. J Urol 182:2195– 2203 17. Krajewski W, Aumatell J, Subiela JD et al (2022) European Association of Urologyyoung academic urologists (EAU-YAU): urothelial carcinoma working group. Accuracy of the CUETO, EORTC 2016 and EAU 2021 scoring models and risk stratification tables to predict outcomes in high-grade non-muscleinvasive urothelial bladder cancer. Urol Oncol 40(11):491.e11–491.e19 18. Krajewski W, Rodrı´guez-Faba O, Breda A et al (2019) Validation of the CUETO scoring model for predicting recurrence and progression in T1G3 urothelial carcinoma of the bladder. Actas Urol Esp 43(8):445–451 19. Grimm MO, van der Heijden AG, Colombel M et al (2020) Treatment of high-grade nonmuscle-invasive bladder carcinoma by standard number and dose of BCG instillations versus reduced number and standard dose of BCG instillations: results of the European Association of Urology Research Foundation Randomised Phase III Clinical Trial “NIMBUS”. Eur Urol 20. S0302–2838(20)30334–1 20. Stenzl A, Penkoff H, Dajc-Sommerer E et al (2011) Detection and clinical outcome of urinary bladder cancer with 5-aminolevulinic acid-induced fluorescence cystoscopy: a multicenter randomized, double-blind, placebocontrolled trial. Cancer 117(5):938–947 21. Burger M, Grossman HB, Droller M et al (2013) Photodynamic diagnosis of nonmuscle-invasive bladder cancer with hexaminolevulinate cystoscopy: a meta-analysis of detection and recurrence based on raw data. Eur Urol 64(5):846–854

22. Schmitz-Dra¨ger C, Bonberg N, Pesch B et al (2016) Replacing cystoscopy by urine markers in the follow-up of patients with low risk non muscle-invasive bladder cancer? – an IBCN project. Urol Oncol 34:452–459 23. Ecke TH, Meisl CJ, Hofbauer S et al (2023) The value of urinary based rapid tests during follow-up in bladder cancer: BTA stat®, Alere NMP22® BladderChek®, UBC® rapid test, CancerCheck® UBC® rapid VISUAL, and uromonitor® in comparison to cytology. AM230902, 38th annual EAU congress, 2023 Milan, Italy 24. Yafi FA, Brimo F, Auger M et al (2014) Is the performance of urinary cytology as high as reported historically? A contemporary analysis in the detection and surveillance of bladder cancer. Urol Oncol 32(1):27.e1-6 25. Raitanen MP, Marttila T, Kaasinen E et al (2000) Sensitivity of human complement factor H related protein (BTA stat) test and voided urine cytology in the diagnosis of bladder cancer. J Urol 163(6):1689–1692 26. Guo A, Wang X, Gao L et al (2014) Bladder tumour antigen (BTA stat) test compared to the urine cytology in the diagnosis of bladder cancer: a meta-analysis. Can Urol Assoc J 8(5–6):E347–E352 27. Moonen PM, Kiemeney LA, Witjes JA (2005) Urinary NMP22 BladderChek test in the diagnosis of superficial bladder cancer. Eur Urol 48(6):951–956 28. Meisl CJ, Karakiewicz PI, Einarsson R et al (2022) Nomograms including the UBC® rapid test to detect primary bladder cancer based on a multicentre dataset. BJU Int 130(6):754–763 29. Batista R, Vinagre J, Prazeres H et al (2019) Validation of a novel, sensitive, and specific urine-based test for recurrence surveillance of patients with non-muscle-invasive bladder cancer in a comprehensive multicenter study. Front Genet 18(10):1237 30. Todenho¨fer T, Hennenlotter J, Esser M et al (2014) Stepwise application of urine markers to detect tumor recurrence in patients undergoing surveillance for non-muscle-invasive bladder cancer. Dis Markers 2014:973406

Chapter 13 Simplex Droplet Digital PCR Assays for the Detection of TERT Promoter Mutations in Urine Samples for the Non-invasive Diagnosis of Urothelial Cancer Maria Zvereva, Md Ismail Hosen, Nathalie Forey, Mahdi Sheikh, Caroline Kannengiesser, Ibrahima Ba, Arnaud Manel, Emmanuel Vian, and Florence Le Calvez-Kelm Abstract Somatic mutations in the telomerase reverse transcriptase (TERT) promoter region are highly frequent in urothelial cancer (UC), and their detection in urine (cell-free DNA from the urine supernatant or DNA from exfoliated cells in the urine pellet) has demonstrated promising evidence as putative non-invasive biomarkers for UC detection and monitoring. However, detecting these tumour-derived mutations in urine requires highly sensitive methods, capable of measuring low-allelic fraction mutations. We developed sensitive droplet digital PCR (ddPCR) assays for detecting urinary TERT promoter mutations (uTERTpm), targeting the two most common mutations (C228T and C250T), as well as the rare A161C, C228A, and CC242-243TT mutations. Here, we described the step-by-step protocol uTERTpm mutation screening using simplex ddPCR assays and give some recommendations for isolation of DNA from urine samples. We also provide limits of detection for the two most frequent mutations and discuss advantages of the method for clinical implementation of the assays for the detection and monitoring of UC. Key words Droplet digital PCR, Liquid biopsy, Urothelial cancer, Urine samples, TERT promoter mutations

1

Introduction There is a tremendous need for robust and cost-effective non-invasive urothelial cancer (UC) biomarkers to complement or replace the gold-standard invasive cystoscopy for the early detection and monitoring of this highly recurrent disease. To date, due to performance inconsistencies or cost-effectiveness considerations, none of the commercially available urine biomarkers are recommended by urological societies for routine BC clinical management or for screening high-risk populations [1, 2]. Detecting molecular alterations of the urothelial tumour in the urine promises to be an

Miche`le J. Hoffmann et al. (eds.), Urothelial Carcinoma: Methods and Protocols, Methods in Molecular Biology, vol. 2684, https://doi.org/10.1007/978-1-0716-3291-8_13, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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important addition in the liquid biopsy of BC [3]. TERT promoter ‘hotspots’ mutations are detected at high frequency (60–85%) in all stages and grades of UCs and represent promising simple candidate non-invasive biomarkers [4]. These mutations have been detected in the urinary DNA collected at the time of clinical diagnosis of UC and during post-surgical follow-ups. We developed nextgeneration sequencing (NGS)- and ddPCR-based sensitive assays for the detection of low-abundance TERT promoter mutations [5] and specifically showed in case-control studies that urinary TERT promoter mutations (uTERTpm) have excellent sensitivity and specificity for the detection of BC [6] and that these mutations could also be detected in urinary DNA of asymptomatic individuals years prior to primary diagnosis of BC with high specificity [7]. While the NGS assay shows great promise for reliable detection of uTERTpm in urine samples, the complex laboratory workflow and requirement of extensive bioinformatics skills for data analysis are still considered as a bottleneck for its large-scale clinical implementation. In addition, it requires the simultaneous analysis of a large set of samples as it relies on the detection of outliers. The development of ddPCR assays for TERT mutation screening represents an attractive alternative as it combines the following advantages: (i) cost-effectiveness, (ii) capacity to detect low-abundance mutations, (iii) ability to screen individual or limited numbers of samples, (iv) short hands-on-time and easy laboratory workflows, and (v) absence of the requirement for complex bioinformatics skills or systems [8]. All of the above arguments should favour the clinical implementation of this genetic test. Moreover, the ddPCR approach enables absolute quantification, which in theory provides a more accurate assessment of the mutant allele fraction (MAF) of the observed mutation(s). Finally, ddPCR assays are more likely to provide uTERTpm screening data from retrospective long-term frozen urine samples compared to NGS-based assays, both because ddPCR assays allow amplification of very short DNA fragments, such as degraded urinary DNA from nucleases activity, and because these assays are less sensitive to PCR inhibitors [9]. In terms of future potential clinical applications, the uTERTpm biomarker could offer a simple and non-invasive biomarker for screening and early detection, because it has been shown to be detectable years before the clinical diagnosis of urothelial cancer. This idea is further supported by studies showing that screening high-risk populations using inexpensive and robust urinary biomarkers followed by cystoscopy could be cost-effective [10]. Individuals at high risk of developing urothelial cancer include those who smoke cigarettes or are exposed to bladder carcinogens, but screening could also target individuals with unknown origin of haematuria. In addition, uTERTpm could be used as a dynamic urine biomarker during surveillance for recurrence after initial diagnosis and treatment of urothelial cancer. Because of the high recurrence

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rates associated with the disease, the current clinical management guidelines recommend post-surgical monitoring with repeated cystoscopies (every 3–6 months for 5 years for intermediate-risk patients and lifelong for high-risk patients) [11]. Potential long-term public health and economic benefits of this biomarker include: • Improved detection of early-stage urothelial cancer, leading to better survival. • Reduced numbers of unnecessary cystoscopy procedures in patients with a negative urinary uTERTpm test result. • Improved surveillance for urothelial cancer recurrence with dynamic monitoring of the marker, reducing the number of unnecessary repeated – expensive and invasive – cystoscopies during long-term follow-up. • Reduction of possible complications and discomfort associated with unnecessary invasive procedures, thus increasing the proportion of patients who adhere to screening or surveillance protocols. • Reduction of costs related to the unnecessary clinical procedures.

2

Materials We list a combination of kits and platforms that need to be purchased from specific providers as well as regular molecular biology laboratory equipment.

2.1 DNA Isolation for Urine Samples

The kits used for the isolation of DNA from urine samples are the following: 1. Quick-DNA™ Urine Kit (ref D3061) from Zymo Research, Dpbs-1X and 2-Mercaptoethanol for circulating DNA from the supernatant and for DNA from exfoliated cells. 2. Quick-DNA™ Urine Kit (ref D3061) from Zymo Research, Dpbs-1X and 2-Mercaptoethanol or QIAamp Circulating Nucleic Acid Kit (ref 55114) associated with buffer ATL (ref 939011) from Qiagen for total urine samples. 3. Optional: conditioning buffer for preservation of samples (Zymo Research, ref D3061-1).

2.2 uTERTpm Mutation Screening

The reagents used for the DNA amplification mix for the ddPCR platform are the following: 1. ddPCR Supermix (No dUTP), 500 RXN (ref 1863024 – Bio-Rad).

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2. Custom ddPCR probe 10031280 – Bio-Rad).

assays

(HEX)

1000rxns

(ref

3. Custom ddPCR probe 10031277 – Bio-Rad).

assays

(FAM)

1000rxns

(ref

4. Rsal (10 U/μL) restriction enzyme (×5000). 5. 7-Deaza-2′-deoxy-guanosine-5′-triphosphate. 6. Water quality molecular biology. The reagents and plastics used in the AutoDG instrument are: 1. Automated DG Oil for Probes, 140 mL (ref 1864110 – Bio-Rad). 2. DG32 Automated DG Cartridge (ref 1864108 – Bio-Rad). 3. Pipet tips for AutoDG system (ref 1864121 – Bio-Rad). 4. Half-skirt 96-well ddPCR plates (ref 12001925 – Bio-Rad). 5. Foil seals f/PCR and QX100 ddPCR (ref 1814040 – Bio-Rad). 6. The oil used for the QX200 plate reader is the kit: droplet reader oil, 2×1L bottles (ref 1863004 – Bio-Rad). 7. Bio-Rad also recommends the use of a PCR machine that allows the ramping to be modified during temperature changes.

3

Methods Introduction of Different Types of Urinary DNA Urine is in direct contact with the urothelium and therefore represents a reservoir of potential biomarkers for specific urological diseases. In every individual, urothelial cells desquamate in the urine, the so-called exfoliated cells that contain cellular DNA (cellDNA). Urothelial cells can also actively release small DNA fragments, called cell-free DNA (cfDNA). In patients with urothelial cancer, in addition to non-malignant cells and cfDNA, urine will contain tumour cells with related tumour cell DNA alterations (tcellDNA) and cfDNA harbouring tumour-derived alterations, also called circulating tumour DNA (ctDNA). From a voided urine sample, the two types of DNA (tcellDNA and ctDNA) can be measured together if the whole urine is extracted, the DNA eluted within the same fraction or separately if the whole fresh urine is centrifuged within the few hours after collection, and the supernatant containing the small cfDNA and ctDNA fragments and the cell pellet containing the exfoliated cells with cellDNA and tcellDNA are split for independent DNA isolation. Note that the post-storage centrifugation of frozen whole urine samples will not allow for the isolation of the two DNA types because the lysis of the

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cells during freezing and thawing steps would lead to contamination of the supernatant by cellDNA of lysed cells. 3.1 Urine Cell-Free DNA Isolation from Urine Supernatants

The protocol used is the Quick-DNA™ Urine Kit from Zymo Research. 1. The urine samples (15–40 mL each) were collected and centrifuged within 2 h at 3000 g for 15 min. The supernatants and pellets were separated into two tubes for separate processing. Pellets samples are directly stored at -80C if possible. 2. In the supernatant tube, the provided conditioning buffer can be added (70 μL per mL of supernatant) if the tubes cannot be frozen at -80C or processed directly. The conditioning buffer will stabilise the urine samples and allow the samples to be stored for up to 1 month at room temperature. Preserved urine samples can also be frozen at -80 °C within the month. 3. If the supernatants have been stored at -80 °C, they are then thawed in a water bath at 20 °C for use. 4. In order to recover the cfDNA, clearing beads are added and mixed with the samples at a rate of 10 μL for samples below 14 mL and 20 μL for higher volumes The samples are then centrifuged at 3000 g for 15 min to pellet the DNA. For efficiency and standardisation, the supernatants are then all reduced to a final volume of 400 μL so that we can add the same volumes of buffer to each. 5. The proteins in the samples are digested with the digestion buffer and proteinase K for 30 min at 55 °C (see Note 1). The mixtures are then passed through columns and eluted in 25 μL with a buffer provided in the kit (see Note 2).

3.2 DNA Isolation from Cell Pellet

The protocol used is the Quick-DNA™ Urine Kit from Zymo Research. The urine samples (15–40 mL each) were collected and centrifuged within 2 h at 3000 g for 15 min. The supernatants and pellets were separated into two tubes for separate processing. All pellets are stored at -80 °C until use. 1. The pellets are thawed at 20 °C in a water bath and centrifuged again for 15 min at 3000 g to ensure that the cells are no longer in suspension. 2. For efficiency and standardisation, the pellets are brought to a volume of 400 μL (supernatant + cells or PBS-1X buffer + cells). This allows us to add the same volume of buffer to all samples. 3. The proteins in the samples are digested with digestion buffer and proteinase K for 30 min at 55 °C (see Note 1). The

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mixtures are then passed through columns and eluted in 25 μL of a buffer provided in the kit (see Note 2). 3.3 DNA Isolation from Whole Urine Samples (Cell-Free DNA and Cell DNA Within the Same Fraction)

We have tested two different kits for the DNA isolation from whole urine samples (cell-free DNA and cell DNA in the same fraction). The choice depends on the starting sample volume of urine. If the total volume is less than 4 mL, either the QIAamp Circulating Nucleic Acid Kit or the Quick-DNA™ Urine Kit can be used. However, if the total volume is between 5 mL and 40 mL, then only the Quick-DNA™ Urine Kit from Zymo Research will provide adequate solution. Total urine DNA can be isolated from fresh frozen urine samples (stored at -80 °C) or from voided urine preserved with Zymo Research conditioning buffer and kept at room temperature for up to a month. 1. The QIiAamp Circulating Nucleic Acid Kit. 1.1. The QIAamp Circulating Nucleic Acid Kit can be used with urine samples up to 4 mL. This kit uses columns placed on a vacuum manifold to extract nucleic acids. 1.2. The samples are thawed at 20 °C in a water bath. 1.3. The lysis of the sample is performed by using lysis buffer in combination with Carrier RNA and Proteinase K. For urine samples, ATL buffer must also be added at this stage to allow complete release of nucleic acids. This step is performed in a water bath at 60 °C for 30 min. 1.4. ACB buffer is then added, and the samples are left on ice for at least 5 min. Passage through the columns attached to the vacuum manifold is then carried out to allow the nucleic acids to bind to the membranes (see Note 3). 1.5. After the washing steps, the samples are eluted with 60 μL of AVE buffer and by centrifuging the columns at 20,000 g. 2. The Quick-DNA Urine Kit. 2.1. The Quick-DNA Urine Kit is used for urine samples from 2 to 40 mL. 2.2. The samples are thawed at 20 °C in a water bath. 2.3. Clearing beads are added and mixed with the samples at a rate of 10 μL for samples below 14 mL and 20 μL for higher volumes. The samples are then pelleted by centrifuging at 3000 g for 15 min. For efficiency and standardisation, the supernatants are then all reduced to a final volume of 400 μL so that the same volumes of buffer can be added to each sample. 2.4. The proteins present in the samples are digested with digestion buffer and proteinase K for 30 min at 55 °C (see Note 1). The mixtures are then passed through

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columns and eluted in 25 μL of the buffer provided in the kit (see Note 2). 3.4 TERT Probes and Primers Design

For each ddPCR assay, 5′-FAM or 5′-HEX reporter dye and 3′ Iowa Black Fluorescent quencher were designed (Bio-Rad, Hercules, California, USA). Table 1 provides the sequences of probes and primers and characteristics for the detection of TERT promoter mutations by ddPCR.

3.5 TERT-Mutated Cell Lines for Experimental Positive Controls

A DNA sample from cell lines carrying a TERT promoter mutation is used as positive control for every different TERT assays and every evaluated samples series in a 96-well plate to indicate that the interrogated mutation can be detected therefore excluding any technical problems for the FAM-mutated probes. See Table 2 for cell lines that may serve as a control. In addition, a DNA sample from wild-type cell lines is used as a negative control in each ddPCR run to check for the specificity of HEX wild-type probes therefore excluding potential false-positive calls. Finally, a No Template

Table 1 Probes and primers for detecting C228T, C250T, C228A, CC242-243TT, and A161C mutations by ddPCR assays Primer/ Mutation type probe

Sequence (5′ to 3′)

Fluorescent dye and PCR Product quencher Size (bp)

TERT C228T

fw_primer rev_primer wt_probe mut_probe

CCCTCCCGGGTCC CCGCGGAAAGGAAGG CGGAgGGGGCTGG CCCGGAaGGGGCTG

– – HEX_IowaBlack FAM_IowaBlack

64

TERT C250T

fw_primer rev_primer wt_probe mut_probe

TCCAGCTCCGCCTCCTCC GGGCCGCGGAAAGGAAGG TCCCGACCCCTcCCGGGTCC TCCCGACCCCTtCCGGGTCC

– – HEX_IowaBlack FAM_IowaBlack

109

TERT C228A

fw_primer rev_primer wt_probe mut_probe

CGCGGAAAGGAAGGG CCCCTCCCGGGTC CGGAgGGGGCTGG CCCGGAtGGGGCTG

– – HEX_IowaBlack FAM_IowaBlack

64

TERT CC242243TT

fw_primer rev_primer wt_probe mut_probe

GAGGGCCCGGAGG CTTCACCTTCCAGCTCC CTGGGCCGGggAC CCGGaaACCCGGGA

– – HEX_IowaBlack FAM_IowaBlack

88

TERT A161C

fw_primer rev_primer wt_probe mut_probe

CGGACCCCGCCCCGT CCAGGGCTTCCCACGTGC CAGCGCTGCCtGAAACTCGC CAGCGCTGCCgGAAACTCG

– – HEX_IowaBlack FAM_IowaBlack

88 154

Fw forward, rev reverse, wt wild-type, mut mutated ddPCR probes containing either a 5′-FAM or 5′-HEX reporter dye and 3′ Iowa Black® Fluorescent quencher were HPLC purified

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Table 2 A list of cancer cell lines carrying TERT promoter mutations [12] that could be used as positive control for each ddPCR run Cell line name

Lineage

TERT promoter mutations

RKN

Ovary

A161C

5637

urinary_tract

C228T

786-O

Kidney

C228T

A101D

Melanoma

C228T

A2058

Melanoma

C228T

BFTC-909

Kidney

C228T

CAL 27

upper_aerodigestive

C228T

Calu-1

lung_NSC

C228T

Daoy

Medulloblastoma

C228T

GAMG

Glioma

C228T

GB-1

Glioma

C228T

GI-1

Glioma

C228T

H4

Glioma

C228T

HSC-3

upper_aerodigestive

C228T

HT-1376

urinary_tract

C228T

HT-144

Melanoma

C228T

Hep G2

Liver

C228T

Hs 294 T

Melanoma

C228T

IGR-39

Melanoma

C228T

JHH-7

Liver

C228T

KALS-1

Glioma

C228T

KNS-81

Glioma

C228T

LN-229

Glioma

C228T

LOX IMVI

Melanoma

C228T

MDA-MB-231

Breast

C228T

NCI-H2052

Mesothelioma

C228T

ONS-76

Medulloblastoma

C228T

OS-RC-2

Kidney

C228T

RMG-I

Ovary

C228T

RT-112

urinary_tract

C228T

SCaBER

urinary_tract

C228T (continued)

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Table 2 (continued) Cell line name

Lineage

TERT promoter mutations

SF-295

Glioma

C228T

SH-10-TC

Stomach

C228T

SK-MEL-24

Melanoma

C228T

SK-MEL-30

Melanoma

C228T

SNU-387

Liver

C228T

SNU-423

Liver

C228T

SNU-475

Liver

C228T

SW579

Thyroid

C228T

SW 1783

Glioma

C228T

T24

urinary_tract

C228T

U-251 MG

Glioma

C228T

U-87 MG

Glioma

C228T

VM-CUB1

urinary_tract

C228T

HCC-44

lung_NSC

C228A

NCI-H1435

lung_NSC

C228A

ES-2

Ovary

CC242-243TT

G-361

Melanoma

CC242-243TT

Hs 944.T

Melanoma

CC242-243TT

RPMI-7951

Melanoma

CC242-243TT

SK-MEL-5

Melanoma

CC242-243TT

8305C

Thyroid

C250T

A-375

Melanoma

C250T

COLO 741

Melanoma

C250T

KYSE-410

Esophagus

C250T

RVH-421

Melanoma

C250T

SK-MEL-2

Melanoma

C250T

UACC-257

Melanoma

C250T

WM-266-4

Melanoma

C250T

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Control (NTC), i.e. a ddPCR experiment without any template DNA, is run for every TERT assays. 3.6 Generation of ddPCR Droplets Using the AutoDG Platform

The Automated Droplet Generator (Bio-Rad QX200 AutoDG ddPCR system) generates partitioned water-oil emulsion droplets (up to 20,000 droplets per 20ul reaction) in a 96-well plate format. Each partition acts as an individual PCR microreactor in which amplified target sequences are detected by fluorescence. Before launching the AutoDG platform, it is necessary to pre-cool the holder for the PCR plate. To set up droplet generation and reaction mix: 1. A 22 μL of reaction mix is prepared using 10 ng of DNA as template, 11 μL of 2× ddPCR supermix-no dUTP (Bio-Rad), 1.1 μL of 20× FAM and HEX probes for mutated and wildtype alleles, 1.1 μL of RsaI restriction enzyme (10 U/μL), and 0.2 μL of 7-deaza-dGTP, Li-salt (2 μM) (see Notes 4 and 5). The reaction mixture is made by hand and dispensed into a 96-well plate manually before being mixed with the droplets. 2. The name of the run and related notes are entered and the columns of the 96-well plate to be filled by the system selected using the AutoDG touch-screen interface. The Automated Droplet Generator will prompt for the consumables to be loaded. Correct loading of the consumables will lead the corresponding area to be coloured green. 3. The system will ask for the confirmation of information and prompt for the start of the run. A countdown timer will display the running time. When the run is launched, a time-elapsed counter begins. Every run has an exportable log file for future reference. Plates with generated droplets should be further processed for PCR amplification within 30 min or stored at 4 °C maximum of 4 h prior to amplification. 4. The 96-well PCR plate should be heat sealed using Bio-Rad’s PX1™ PCR Plate Sealer and pierceable foil heat seal. 5. After sealing, in order to avoid evaporation during the PCR amplification, it is necessary to roll the surface with a roller or wipe it with a napkin so that the boundaries of each well become clearly visible. After heat sealing, place the PCR plate in a thermal cycler for PCR using the following amplification condition guidelines.

3.7 Amplification Conditions

The PCR amplifications of the droplets for the uTERTpm assays were carried using the following PCR conditions: 95 °C for 10 min, 40 cycles of 94 °C for 30 s, ramp 2.5/s, 54 °C for C228T, 55 °C for the C228A and CC242-243TT, and 64 °C for C250T and for A161C assays using the following PCR conditions: 95 °C for 10 min, 50 cycles of 96 °C for 30 s, ramp 2.5/s, 60 °C for 1 min, ramp 2.5/s, and for all followed by 98 °C for 10 min. After PCR, the plate can be left in the thermal cycler overnight at 10 °C or

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stored at 4 °C no more than 3 days before running it in a QX200 Droplet Reader. 3.8 Scan of the 96Well Plate by the QX200 Droplet Reader

The fluorescent intensity (FAM- and HEX-probes in our assays) of each droplet is measured with the droplet reader QX200 Droplet (Bio-Rad). 1. The QX Manager software associated to the droplet reader computer allows the user to create, in set-up mode, the new plate with unique name corresponding to mutation type, i.e. the C228T, C228A, CC242-243TT, C250T, or A161C assays. 2. Once every sample’s name has been entered, the user can select for all samples the absolute quantification (ABS) experiments type and enter probe name and channels FAM (channel 1) and HEX (channel 2) (see Note 6). For control without any template DNA, the non-template type of experiment (NTC) should be selected to the specific well(s) before launching the ddPCR run. 3. The plate loading protocol is then complete and the run can be launched using the start button. This will initiate the reading process during which where PCR-positive (FAM and HEX droplets) and PCR-negative droplets are counted to provide absolute quantification of target DNA in digital form

3.9 Count of Numbers of ddPCR Droplets and Calculations of Mutant Allelic Fraction (MAF)

After the ddPCR data is read on the droplet reader, the analysis of the raw data is performed using the QX Manager Software Standard Edition v1.2 (Bio-Rad). 1. The 2D amplitude plots generated by the QX Manager Software Standard Edition v1.2 is opened to set the threshold levels of amplitudes in the two channels (for the wild-type and mutated probe). 2. The thresholds for the channel 1 (mutated probe) for the A161C, C228A, C228T, CC242-243TT, and C250T probes were 1760, 700, 1500, 500, and 3500, respectively. For the channel 2 (wild-type probe), the thresholds for A161C, C228A, C228T, CC242-243TT, and C250T probes were 1623, 1250, 1750, 1440, and 2000, respectively (see Note 7). 3. After the threshold amplitude is set, the raw data containing the number of droplets in each channel are exported in Excel. The subsequent calculation of the Mutant Allelic Fraction (MAF) is performed in Excel. 4. The number of droplets in Channel 1 (Ch1+Ch2-) represents the number of droplets having fluorescent intensity of the probe specific for the mutations. Similarly, the number of droplets showing fluorescent intensity for both the probes is

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found in the Ch1+Ch2+ region. The number of droplets detected by the probe with the wild-type allele are reported as Ch1-Ch2+. 5. The MAF is calculated by dividing the total number of droplets found in the two regions (Ch1+Ch2 and Ch1+Ch2+) with the total number found in all three regions (Ch1+Ch2, Ch1+Ch2+ and Ch1-Ch2+). The representative figures for wild-type and mutated samples are shown in Fig. 1. 3.10 Determination of the Threshold Number of Minimum Mutated Droplets to Call a Mutation

The ddPCR assays often generate some background fluorescence, and hence this noise should be normalised to call a mutation in a given sample. This is done by determining the minimum number of droplets recorded at the channels respective for calling the mutation (Ch1+Ch2 and Ch1+Ch2+). This threshold number of droplets is determined by the following ways: 1. DNA is extracted from a series of cell lines (n = 20) wild type for the A161C, C228T, C228A, CC242-243TT and C250T mutations. 2. The respective ddPCR assays are performed on these cell lines. 3. The 2D amplitude plots from the QX Manager Software Standard Edition v1.2 are analyzed by setting the threshold amplitudes for both the mutated and wild type channels (as mentioned in Subheading 3.9). 4. Poisson regression of the number of droplets above the threshold is generated from the count of channel 1 (for mutated probe) and of channel 2 (for wildtype probe). 5. The Poisson regression line is used to set the minimum numbers of droplets recorded at the two regions (Ch1+Ch2 and Ch1+Ch2+) to call for a mutation.

3.11 Determination of the Limit of Detection (LOD) of the ddPCR Assays

The limit of detection (LOD) of the TERT-ddPCR assays can be determined using the following protocol: 1. Genomic DNA extracted from the cell lines with C228T and C250T TERT promoter mutations (HepG2 and A375, respectively) are serially diluted into TERT-wild-type DNA obtained from white blood cells of healthy controls to achieve from 100% cell lines DNA to 0% mutant allele fractions (Table 3). Quantities of 5 ng, 10 ng, and 20 ng template DNA can be used for this experiment. 2. The ddPCR assays are performed on each of the abovementioned samples, using the respective ddPCR assays.

Simplex Droplet Digital PCR Assays for the Detection of TERT Promoter. . .

225

Fig. 1 Examples of 2D scatterplots obtained from TERT promoter mutation ddPCR assays in representative samples. Assays testing for C228T, C250T, C228A, CC242-243TT, and A161C mutations are displayed in four examples of mutated samples (left panels) and in four examples of wild-type samples (right panels). In the left panel, fluorescent probes (FAM) detect respective mutations as exemplified by the count of droplets with mutated alleles, while in the right panel, wild-type samples do not show any positive droplets (FAM) above the threshold line but show droplets with HEX fluorescence associated with wild-type probes. The pink lines are the thresholds for channel 1 (mutated probe) and channel 2 (wild-type probe) for the ddPCR mutation assays

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Table 3 Dilution of TERT-mutated cell line DNA against the wild-type DNA for determining the LOD Amount of template DNA for ddPCR Dilution factor from mutated cell line Mutant allele fraction (ng) DNA (%) 5/10/20

None (100% mutated cell line DNA)

100%

5/10/20

2

50

5/10/20

2.5

40

5/10/20

5

20

5/10/20

10

10

5/10/20

20

5

5/10/20

50

2

5/10/20

100

1

5/10/20

200

0.5

5/10/20

500

0.2

5/10/20

1000

0.1

5/10/20

2000

0.05

5/10/20

5000

0.02

5/10/20

None-100% wild-type DNA

0.01

3. The threshold amplitude is set and the MAF calculated for each dilution using the method described in the above section. 4. From this data, the LOD can be set for each of the assays.

4

Notes 1. If an important viscosity appears after adding the lysis buffer (thick urine in case of gross haematuria, for instance) is observed, you could double the volume of the buffer and proteinase K in order to reduce the risk of clogging the columns. 2. To increase the amount of DNA recovered and not dilute our samples further, a double elution of initial eluates could be performed. This means that, after the first elution, the eluate is passed through on the column again. 3. This step can be quite time consuming as the efficiency of the passage of lysates through the vacuum can vary according to

Simplex Droplet Digital PCR Assays for the Detection of TERT Promoter. . .

227

the quantity of debris, which if too high may lead to the clogging of the membranes. In such a case, the samples must be centrifuged at the risk of losing some of the nucleic acids and lowering the DNA yield. 4. The two most common somatic mutations of the TERT promoter (C228T and C250T) occur within the terminal G-tracts of the second putative quadruplex sequence. These secondary structures at the TERT promoter mutation sites pose a significant problem for the ddPCR assays to show distinct droplet clusters. To resolve this issue, we used 7-deaza-dGTP, Li-salt at a 2 μM concentration. 5. Alternatively, a reduced volume of probes (1 μL each) and RsaI restriction enzyme (1 μL) have been successfully validated. The rest of the mix is unchanged. 6. Usually, the channel 1 is for the mutated probe and channel 2 for the wild-type probe. 7. The thresholds of amplitude could vary from run to run (according to the stability of the fluorescent probes), and thus the threshold may sometimes need to be slightly adjusted dynamically.

5

Conclusion The ddPCR-based simplex assays established for the detection of urinary TERT promoter mutations demonstrated good analytical and clinical performance for the non-invasive detection of urothelial cancer. The simplex screening of the five TERT promoter mutations is now performed in five independent ddPCR reactions. One could consider establishing multiplex uTERTpm assays, which will consist in performing the screening of the set of mutations in one or two ddPCR reactions, leading to reduced cost and simplified laboratory and analytical workflows. This would be valuable for high-throughput screening of large sample size such as required in screening programs. The validation of uTERTpm as a urinary biomarker of urothelial cancer should be performed in large international studies including in screening studies and cancer control studies that will assess its clinical utility and overall benefit over current clinical practice and potential other urine markers. Such studies would provide research-based evidence that could favour the integration of uTERTpm into routine clinical management of urothelial cancer, possibly including the development of screening strategies in high-risk groups, who would benefit from close surveillance with a simple, non-invasive test.

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Acknowledgements The work was supported by the French Cancer League, the Russian Foundation for Basic Research and the International Agency for Research on Cancer. Disclaimer Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization, the authors alone are responsible for the views expressed in this chapter, and they do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer/World Health Organization.

References 1. Larre´ S, Catto JWF, Cookson MS et al (2013) Screening for bladder cancer: rationale, limitations, whom to target, and perspectives. Eur Urol 63:1049–1058. https://doi.org/10. 1016/J.EURURO.2012.12.062 2. Schmitz-Dr€ager BJ, Droller M, Lokeshwar VB et al (2015) Molecular markers for bladder cancer screening, early diagnosis, and surveillance: the WHO/ICUD consensus. Urol Int 94(1):1–24 3. Xylinas E, Kluth LA, Rieken M et al (2014) Urine markers for detection and surveillance of bladder cancer. Urol Oncol 32:222 4. Zvereva M, Pisarev E, Hosen I et al (2020) Activating telomerase TERT promoter mutations and their application for the detection of bladder cancer. Int J Mol Sci 21:1–19. https:// doi.org/10.3390/IJMS21176034 5. Hosen MI, Forey N, Durand G et al (2020) Development of sensitive droplet digital PCR assays for detecting urinary TERT promoter mutations as non-invasive biomarkers for detection of urothelial cancer. Cancers (Basel) 1 2 : 1 – 1 8 . h t t p s : // d o i . o r g / 1 0 . 3 3 9 0 / CANCERS12123541 6. Avogbe PH, Manel A, Vian E et al (2019) Urinary TERT promoter mutations as non-invasive biomarkers for the comprehensive detection of urothelial cancer. EBioMedicine 44:431–438. https://doi.org/10.1016/j. ebiom.2019.05.004 7. Hosen MI, Sheikh M, Zvereva M et al (2020) Urinary TERT promoter mutations are

detectable up to 10 years prior to clinical diagnosis of bladder cancer: evidence from the Golestan cohort study. EBioMedicine 53. https://doi.org/10.1016/J.EBIOM.2020. 102643 8. Olmedillas-Lo´pez S, Olivera-Salazar R, Garcı´aArranz M et al (2022) Current and emerging applications of droplet digital PCR in oncology: an updated review. Mol Diagn Ther 26: 61–87. https://doi.org/10.1007/S40291021-00562-2 9. Hindson CM, Chevillet JR, Briggs HA et al (2013) Absolute quantification by droplet digital PCR versus analog real-time PCR. Nat Methods 10:1003. https://doi.org/10. 1038/NMETH.2633 10. Lotan Y, Svatek RS, Sagalowsky AI (2006) Should we screen for bladder cancer in a highrisk population? A cost per life-year saved analysis. Cancer 107:982–990. https://doi.org/ 10.1002/cncr.22084 11. Powles T, Bellmunt J, Comperat E et al (2022) Bladder cancer: ESMO clinical practice guideline for diagnosis, treatment and follow-up ☆. Ann Oncol 33:244–258. https://doi.org/10. 1016/J.ANNONC.2021.11.012/ATTACH MENT/1FF2D52A-82D0-4BEE-96C044A05F81B2A0/MMC2.PDF 12. Huang FW, Bielski CM, Rinne ML et al (2015) TERT promoter mutations and monoallelic activation of TERT in cancer. Oncogenesis 4: e176. https://doi.org/10.1038/ONCSIS. 2015.39

Chapter 14 Predictive Biomarkers of Response to Neoadjuvant Therapy in Muscle Invasive Bladder Cancer Jussi Nikkola and Peter Black Abstract Neoadjuvant cisplatin-based chemotherapy is recommended prior to surgical removal of the bladder for patients with non-metastatic muscle invasive bladder cancer. Despite a survival benefit, approximately half of patients do not respond to chemotherapy and are exposed potentially unnecessarily to substantial toxicity and delay in surgery. Therefore, biomarkers to identify likely responders before initiating chemotherapy would be a helpful clinical tool. Furthermore, biomarkers may be able to identify patients who do not need subsequent surgery after clinical complete response to chemotherapy. To date, there are no clinically approved predictive biomarkers of response to neoadjuvant therapy. Recent advances in the molecular characterization of bladder cancer have shown the potential role for DNA damage repair (DDR) gene alterations and molecular subtypes to guide therapy, but these need validation from prospective clinical trials. This chapter reviews candidate predictive biomarkers of response to neoadjuvant therapy in muscle invasive bladder cancer. Key words Muscle invasive bladder cancer, Urothelial carcinoma, Neoadjuvant therapy, Chemotherapy, Targeted therapy, Predictive biomarkers, Immune checkpoint inhibition

1

Introduction Up to 50% of patients with nonmetastatic muscle invasive bladder cancer (MIBC, pT2-4aN0M0) treated with radical cystectomy (RC) alone will progress to metastatic disease [1–3]. Cisplatinbased neoadjuvant therapy (NAC) before RC confers an overall survival benefit of 5–10% for these patients [4–6]. However, only 40–50% of patients experience a major response, defined as absence of MIBC and lymph node metastasis (≤ypT1N0) in the RC specimen [7]. Patients with residual MIBC with or without nodal metastasis in the RC specimen have a poor prognosis [8]. Response to NAC is only inadequately determined by clinical evaluation, and approximately one in three patients with a clinical complete response will have residual MIBC at RC [9]. Therefore, in the absence of clinical progression to unresectable disease, all patients

Miche`le J. Hoffmann et al. (eds.), Urothelial Carcinoma: Methods and Protocols, Methods in Molecular Biology, vol. 2684, https://doi.org/10.1007/978-1-0716-3291-8_14, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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proceed to RC regardless of clinical response. This represents overtreatment of patients with a pathologic complete response to NAC (ypT0N0) who would not need local consolidation therapy if we had biomarkers to identify them more accurately. The most commonly used NAC regimens are methotrexate, vinblastine, doxorubicin, and cisplatin (MVAC) and gemcitabine and cisplatin (GC). Both regimens can be given in a dose dense manner (ddMVAC and ddGC), and both have traditionally been thought to have similar rates of pathologic downstaging to ypT0/ ypT1, progression-free survival, and overall survival [10– 15]. Recently, the GETUG-AFU V05 VESPER Trial has provided the first evidence that ddMVAC provides better 3-year progressionfree survival over GC in the neoadjuvant setting [16]. There are several arguments to prefer neoadjuvant over adjuvant cisplatin-based chemotherapy for patients with MIBC. Systemic chemotherapy is often better tolerated before surgery, rather than after surgery when patients may experience a delay in chemotherapy administration because of complications or debilitation. Patients are more likely to receive both modalities if they have chemotherapy before surgery [17]. NAC is administered with the intent of ablating micrometastatic disease and the burden of this disease will be lowest in the neoadjuvant compared to the adjuvant setting. Furthermore, NAC has the potential to downstage bulky and locally advanced tumors, allowing for a higher likelihood of achieving a negative surgical margin which is an established prognostic factor after RC. On the other hand, if NAC is ineffective, it can delay definitive local therapy and allow disease progression. This is likely a key factor in the poor uptake of NAC in the routine practice of many urologists. In rare cases, complications of NAC make patients unfit for RC. The identification of biomarkers to reliably predict response to NAC is a critical unmet need in the care of patients with MIBC. There are currently no validated predictive biomarkers to determine which MIBC patients should receive NAC. An accurate biomarker could allow likely nonresponders to avoid NAC and proceed to an alternative neoadjuvant therapy or directly to RC. A biomarker predicting pathologic complete response in patients with clinical complete response after NAC could guide the decision to preserve the bladder. In this chapter, we review the most promising predictive biomarkers under clinical development. We will focus on NAC before RC, but the same considerations can also apply to NAC before radiation-based therapy. We will also focus on chemotherapy over other neoadjuvant therapies since no other therapies, including immune checkpoint inhibitors, are currently used in the neoadjuvant setting. Putative predictive biomarkers include: DNA repair gene alterations, RNA-based molecular subtypes and gene expression signatures, and receptor tyrosine kinases (Table 1).

Ref

Choueri [22]

Van Allen [23]

Gil-Jimenez [30]

Plimack [31]

Font [37]

Groenendjik [29]

Choi [39]

Biomarker

ERCC1

ERCC2

ERCC2

ATM, RB1 and FANCC

BRCA1

ERBB2

Molecular subtypes: Basal-like, luminal-like, and p53-like

Cisplatin-based

GC or ddMVAC

ddMVAC

NAC-therapy

165

50

31

Patients (n)

MVAC or GC

CMV or GC

Whole Platinum-based transcriptome microarray

NGS (178 cancer associated genes)

RT-PCR

18

71

57

ERCC2 was the only gene significantly enriched in the responder cohor t (p < 0.01)

PR in 43% of ERCC1 positive and 60% in ERCC1 negative

PR in 0% of p53-like, 40% in basal-like, and 67% in luminallike

ypT < 1

(continued)

9/38 of complete responders vs 0/33 of nonresponders had ERBB missense mutations (p = 0.003)

PR in 60% with low/intermediate BRCA1 levels vs. 22% in those with high levels (p = 0.01) ypT0N0

ypT0–1

ATM, RB1, and FANCC were associated with PR in the discover y (p < 0.001) and validation (p = 0.033) cohor ts

ypT0/tis/ Somatic deleterious mutations in ta/T1N0 ERCC2 were found in 13% responders and in 2/95 2% nonresponders ( p = 0.009)

ypT0 or ypTis

1, the effect is antagonistic; and if CI < 1, the effect is synergistic; see Fig. 1 (see Note 9).

3.3.2 Colony Forming Assay

1. Seed cells in a 6-well plate 1 day before treatment (Table 3). 2. Treat cells with the compound/combination of interest and incubate the cells for 3 days, include a solvent control. 3. After 3 days, observe the cells under the microscope to verify the effect of the treatment. 4. Detach the cells; stop enzyme activity. 5. Count the cells treated with solvent as a control, and seed in triplicate 2000 cells per 6-well. Likewise, seed the same volume of cell suspension from compound-treated cells. Mix thoroughly to spread cell evenly (see Note 10). 6. Incubate for 10–14 days at 37 °C. 7. When clearly visible colonies have formed, remove the medium and wash the cells with PBS buffer, aspirate, and wash with 50% methanol in PBS buffer. 8. Fix the cells for 10 min in 100% methanol.

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Chou-Talalay analysis

120

Compound 1

100

Compound 2

80

2 .0

1 .5

Combination

60

CI

Cell viability (%)

Cell viability

CI>1 Antagonistic CI=1 Additive

1 .0

40

CI10 μM in resistant basal cells. Treatment was performed for 7–12 days but frequency of EV addition was not outlined. The second preclinical and translational study published by the same group as a short communication focused on the evaluation of Trop-2 targeted by SG [19]. In an approach comparable to their previous work, gene expression data from clinical cohorts of MIBC patients as well as 35 UC cell lines were analyzed regarding mRNA and protein expression of Trop-2. Expression levels were compared to those of Nectin-4. While protein and mRNA expression of both targets were positively correlated, Trop-2 mRNA levels were higher in patient samples and cell lines. Further Trop-2 expression was stable in both patient samples and cell lines as compared to Nectin4 and not restricted to either luminal or basal urothelial cancers. Only in neuro-endocrine-like bladder cancers, Trop-2 was not detected. For dose response evaluation, WST-1 assay was used. IC50 toward SG was cell-line dependent in the range of 0.01–5 μM. To our knowledge, in vivo experiments regarding efficacy of EV or SG treatment in urothelial cancer have not yet been published in an original report. However, data is available from the manufacturer’s assessment report for EV as published by the EMA (assessment Report EMA/249357/2022). An overview on the animal models applied is given in Table 2. In summary, when planning preclinical and translational studies, ADCs should always be considered as treatment controls. These substances are characterized by high efficacy and have the potential

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Table 2 Urothelial cancer xenograft models for the evaluation of the antineoplastic efficacy of enfortumabvedotin (assessment Report EMA/249357/2022) Cell line

Animal

Dosage

Schedule

AG-B1

SCID mouse

0.4–0.8 mg/kg

Every 4 days

AG-B8

CB17/SCID mouse

0.5 mg/kg, 1.0 mg/kg,1.5 mg/kg i.v.

Biweekly for 3 weeks

to become another standard option in the treatment of urothelial carcinoma. Apart from the use of ADCs from clinical routine with a well-established mode of action, these substances also offer the potential to investigate new treatment options due to their principally targeted approach and diverse pharmacochemical possibilities with regard to their metabolism and the choice of antineoplastic agent. References 1. Powles T, Rosenberg JE, Sonpavde GP (2021) Enfortumab vedotin in previously treated advanced urothelial carcinoma. N Engl J Med 384(12):1125–1135. https://doi.org/10. 1056/NEJMoa2035807 2. Tagawa ST, Balar AV, Petrylak DP (2021) TROPHY-U-01: a phase II open-label study of sacituzumab govitecan in patients with metastatic urothelial carcinoma progressing after platinum-based chemotherapy and checkpoint inhibitors. J Clin Oncol Off J Am Soc Clin Oncol 39(22):2474–2485. https://doi.org/ 10.1200/JCO.20.03489 3. Padua TC, Moschini M, Martini A (2022) Efficacy and toxicity of antibody-drug conjugates in the treatment of metastatic urothelial cancer: a scoping review. Urol Oncol 40(10):413–423. https://doi.org/10.1016/j.urolonc.2022. 07.006 4. D’Angelo A, Chapman R, Sirico M (2022) An update on antibody-drug conjugates in urothelial carcinoma: state of the art strategies and what comes next. Cancer Chemother Pharmacol 90(3):191–205. https://doi.org/10. 1007/s00280-022-04459-7 5. McCombs JR, Owen SC (2015) Antibody drug conjugates: design and selection of linker, payload and conjugation chemistry. AAPS J 17(2):339–351. https://doi.org/10.1208/ s12248-014-9710-8 6. Damelin M, Zhong W, Myers J (2015) Evolving strategies for target selection for antibodydrug conjugates. Pharm Res 32(11):

3494–3507. https://doi.org/10.1007/ s11095-015-1624-3 7. Diamantis N, Banerji U (2016) Antibody-drug conjugates—an emerging class of cancer treatment. Br J Cancer 114(4):362–367. https:// doi.org/10.1038/bjc.2015.435 8. Donaghy H (2016) Effects of antibody, drug and linker on the preclinical and clinical toxicities of antibody-drug conjugates. mAbs 8(4): 6 5 9 – 6 7 1 . h t t p s : // d o i . o r g / 1 0 . 1 0 8 0 / 19420862.2016.1156829 9. Fu Z, Li S, Han S (2022) Antibody drug conjugate: the “biological missile” for targeted cancer therapy. Signal Transduct Target Ther 7(1):93. https://doi.org/10.1038/s41392022-00947-7 10. Ritchie M, Tchistiakova L, Scott N (2013) Implications of receptor-mediated endocytosis and intracellular trafficking dynamics in the development of antibody drug conjugates. mAbs 5(1):13–21. https://doi.org/10.4161/ mabs.22854 11. Heath EI, Rosenberg JE (2021) The biology and rationale of targeting nectin-4 in urothelial carcinoma. Nat Rev Urol 18(2):93–103. https://doi.org/10.1038/s41585-02000394-5 12. Challita-Eid PM, Satpayev D, Yang P (2016) Enfortumab vedotin antibody-drug conjugate targeting Nectin-4 is a highly potent therapeutic agent in multiple preclinical cancer models. Cancer Res 76(10):3003–3013. https://doi. org/10.1158/0008-5472.CAN-15-1313

ADC in Urothelial Carcinoma 13. Tomiyama E, Fujita K, Rodriguez Pena MDC (2020) Expression of Nectin-4 and PD-L1 in upper tract urothelial carcinoma. Int J Mol Sci 2 1 ( 1 5 ) . h t t p s : // d o i . o r g / 1 0 . 3 3 9 0 / ijms21155390 14. Hoffman-Censits JH, Lombardo KA, Parimi V (2021) Expression of Nectin-4 in bladder urothelial carcinoma, in morphologic variants, and nonurothelial histotypes. Appl Immunohistochem Mol Morphol 29(8):619–625. h t t p s : // d o i . o r g / 1 0 . 1 0 9 7 / P A I . 0000000000000938 15. Pavone G, Motta L, Martorana F (2021) A new kid on the block: sacituzumab govitecan for the treatment of breast cancer and other solid tumors. Molecules 26(23). https://doi.org/ 10.3390/molecules26237294 16. Zeng P, Chen MB, Zhou LN (2016) Impact of TROP2 expression on prognosis in solid tumors: a systematic review and meta-analysis. Sci Rep 6:33658. https://doi.org/10.1038/ srep33658 17. Dum D, Taherpour N, Menz A (2022) Trophoblast cell surface antigen 2 expression in human tumors: a tissue microarray study on 18,563 tumors. Pathobiology 89(4): 2 4 5 – 2 5 8 . h t t p s : // d o i . o r g / 1 0 . 1 1 5 9 / 000522206 18. Tomiyama E, Fujita K, Nakano K (2022) Trop2 in upper tract urothelial carcinoma. Curr Oncol 29(6):3911–3921. https://doi.org/ 10.3390/curroncol29060312 19. Chou J, Trepka K, Sjostrom M (2022) TROP2 expression across molecular subtypes of urothelial carcinoma and enfortumab vedotinresistant cells. Eur Urol Oncol. https://doi. org/10.1016/j.euo.2021.11.005 20. Su D, Zhang D (2021) Linker design impacts antibody-drug conjugate pharmacokinetics and efficacy via modulating the stability and payload release efficiency. Front Pharmacol 12:687926. https://doi.org/10.3389/fphar. 2021.687926 21. Su Z, Xiao D, Xie F (2021) Antibody-drug conjugates: recent advances in linker chemistry. Acta Pharm Sin B 11(12):3889–3907. https:// doi.org/10.1016/j.apsb.2021.03.042 22. Cardillo TM, Govindan SV, Sharkey RM (2015) Sacituzumab govitecan (IMMU-132), an anti-trop-2/SN-38 antibody-drug conjugate: characterization and efficacy in pancreatic, gastric, and other cancers. Bioconjug Chem 26(5):919–931. https://doi.org/10. 1021/acs.bioconjchem.5b00223

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23. Wayne AS, Fitzgerald DJ, Kreitman RJ (2014) Immunotoxins for leukemia. Blood 123(16): 2470–2477. https://doi.org/10.1182/ blood-2014-01-492256 24. Rosenberg JE, O’Donnell PH, Balar AV (2019) Pivotal trial of enfortumab vedotin in urothelial carcinoma after platinum and antiprogrammed death 1/programmed death ligand 1 therapy. J Clin Oncol Off J Am Soc Clin Oncol 37(29):2592–2600. https://doi. org/10.1200/JCO.19.01140 25. Rosenberg JE, Milowsky M, Ramamurthy C (2022) LBA73 – study EV-103 cohort K: antitumor activity of enfortumab vedotin (EV) monotherapy or in combination with pembrolizumab (P) in previously untreated cisplatin-ineligible patients (pts) with locally advanced or metastatic urothelial cancer (la/mUC). Ann Oncol 33:S808–S869. h t t p s : // d o i . o r g / 1 0 . 1 0 1 6 / a n n o n c / annonc1089 26. Petrylak DP, Flaig TW, Mar N (2022) Study EV-103 cohort H: antitumor activity of neoadjuvant treatment with enfortumab vedotin monotherapy in patients (pts) with muscle invasive bladder cancer (MIBC) who are cisplatin-ineligible. J Clin Oncol 40(6_suppl):435–435. https://doi.org/10. 1200/JCO.2022.40.6_suppl.435 27. Necchi A, Raggi D, Bandini M (2021) SURE: an open label, sequential-arm, phase II study of neoadjuvant sacituzumab govitecan (SG), and SG plus pembrolizumab (pembro) before radical cystectomy, for patients with muscleinvasive bladder cancer (MIBC) who cannot receive or refuse cisplatin-based chemotherapy. J Clin Oncol 39(6_suppl):TPS506–TPS506. https://doi.org/10.1200/JCO.2021.39.6_ suppl.TPS506 28. Tagawa ST, Grivas P, Petrylak DP (2022) TROPHY-U-01 cohort 4: sacituzumab govitecan (SG) in combination with cisplatin (cis) in platinum (PLT)-naı¨ve patients (pts) with metastatic urothelial cancer (mUC). J Clin Oncol 40(6_suppl):TPS581–TPS581. https://doi.org/10.1200/JCO.2022.40.6_ suppl.TPS581 29. Chu CE, Sjostrom M, Egusa EA (2021) Heterogeneity in NECTIN4 expression across molecular subtypes of urothelial cancer mediates sensitivity to enfortumab vedotin. Clin Cancer Res 27(18):5123–5130. https://doi. org/10.1158/1078-0432.CCR-20-4175

Chapter 19 Intravesical Infusion of Oncolytic Virus CG0070 in the Treatment of Bladder Cancer Paola Grandi, Andrea Darilek, Anay Moscu, Anu Pradhan, and Roger Li Abstract CG0070 is a conditionally replicating oncolytic adenovirus that preferentially replicates within and kills Rb-defective cancer cells. It has been used successfully in an intravesical formulation to treat Bacillus Calmette-Guerin (BCG) unresponsive carcinoma in situ (CIS) containing non-muscle-invasive bladder cancer. As a self-replicating biologic, it shares many characteristics with intravesical BCG but has other unique features. Herein, we detail recommended standardized protocols for bladder infusion of CG0070 for the treatment of bladder cancer and provide many useful tips for trouble shooting. Key words Bladder cancer, Intravesical infusion, CG0070, Oncolytic virus, Immunotherapy

1 1.1

Introduction CG0070

CG0070 is a conditionally replicating oncolytic serotype 5 adenovirus designed to preferentially replicate in and kill cancer cells. The primary receptor for CG0070 is the coxsackievirus and adenovirus receptor (CAR), which binds to the globular knob domain on the virus. Through this high affinity interaction, the virus docks onto the cell, thus allowing secondary interactions to occur. CAR is a 46-kDa protein that is present in specialized intracellular junctions and the tight junction of polarized epithelial cells. It is highly expressed in a variety of solid tumors. Ad5 is known to infect the cells also through a3B1 [1]. In CG0070, the human E2F-l promoter drives expression of the essential El viral genes and restricts viral replication to retinoblastoma (Rb) pathway defective tumor cells, selectively killing these cells with minimal damage to normal tissues [2]. In addition, CG0070 encodes the cDNA for human GM-CSF, a potent cytokine inducer of specific, long-lasting anti-tumor immunity in animal tumor models. Expression of the GM-CSF is controlled by the endogenous viral E3 promoter. Since the E3 promoter is in turn

Miche`le J. Hoffmann et al. (eds.), Urothelial Carcinoma: Methods and Protocols, Methods in Molecular Biology, vol. 2684, https://doi.org/10.1007/978-1-0716-3291-8_19, © The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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activated by E1A, both viral replication and GM-CSF expression are ultimately under the control of the tumor-selective E2F-1 promoter. 1.2 Retinoblastoma (Rb) Pathway

Rb-pathway defects are found in the majority of urothelial carcinoma of the bladder and have been correlated with poor outcomes in patients with non-muscle-invasive bladder cancer (NMIBC) [3]. Deletion of CDKN2A (p16INK) has been described in 30–70% of urothelial carcinoma [4] and is prevalent across all tumor grades and stages. The p16INK gene is frequently the only genetic abnormality detected in many early-stage NMIBC and is, therefore, thought to be involved in the early tumorigenesis of urothelial carcinoma of the bladder [5]. It has also been linked to a poor prognosis, marked by a high rate of recurrence in NMIBC patients [6]. Since tumor cells do not usually develop both Rb and p16INK mutations together, the additive prevalence of Rb and p16 gene mutations results in nearly uniform inactivation of the Rb-pathway in urothelial carcinoma [7].

1.3

The rationale for arming CG0070 with the GM-CSF transgene is based on its proven role in stimulating anti-tumor immune response. GM-CSF is primarily produced by activated type-1 T helper cells (Th1), type 1 cytotoxic T cells, and activated macrophages and was identified as the most potent cytokine inducer of specific, long-lasting anti-tumor immunity in a murine tumor model [8]. The local expression of GM-CSF by CG0070-infected cells is hypothesized to induce local inflammatory responses, thereby enhancing the local anti-tumor activity of the vector. Additionally, GM-CSF secreted by CG0070-infected tumor cells can attract antigen presenting cells to the tumor site and lead to the priming of naive effector T-cells. Thus, in addition to its direct oncolytic effect, CG0070 may also induce systemic anti-tumor immunity such that distant tumor metastases may be eradicated. In this way, systemic therapy may be achieved with local delivery.

GM-CSF

1.4 Xenograft Models

The anti-tumor effects of adenovirus-based oncolytic vectors has been evaluated in mice using human tumor xenografts. Due to the lack of CAR expression in murine tissues, assessment of any off-target effect from the treatment is prohibited. The therapeutic efficacy of CG0070 was evaluated in a subcutaneous bladder TCC (transitional cell carcinoma) 253 J B-V tumor model in nude mice [2]. CG0070 (3 × 108, 3 × 109, or 3 × 1010 vp/dose) or saline was injected directly into subcutaneously implanted 253 J B-V bladder tumor xenografts. Anti-tumor activity was observed in a dosedependent manner compared to saline-treated tumors ( p < 0.00 l). Because CG0070 expresses human GM-CSF, which is inactive in mice, this study effectively measured only the cytotoxic anti-tumor effects of the virus. The anti-tumor activity of CG0070

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Fig. 1 Preclinical models to demonstrate anti-tumor activity of CG00070. Following establishment of orthotopic bladder tumors, 70 μL of a 0.1% solution of dodecyl h-D-maltoside were then instilled into the bladder via IVE and retained for 5 min; after which, the bladder was washed with PBS. CG0070 (3 × 1010 vp in 50 μL) was administered intravesically and retained in the bladder for 15 min. Treatment was terminated by withdrawing the virus and flushing the bladders with PBS. Mice were imaged every week following intraperitoneal injection of Luciferin. The images shown were taken on day 1 (a–b) and day 32 (c) or day 42 (a, b) for all animals except as indicated in the fig. (d) Serial sections of the paraffin-embedded bladder tissue were used for staining. Human bladder SW780 cells were stained with anti-human cytokeratin 20AE1 antibody (a and b), and virus replication was monitored by staining for hexon protein (c and d). Final color development in both the immunohistochemical protocols involved the use of 3,3V-diaminobenzidine that results in a positive staining pattern as indicated by the arrow showing the regions of specific antibody interaction (magnification, ×10)

was further evaluated in an orthotopic bladder TCC model that more closely resembles the actual treatment setting in patients. Female NCR nude mice bearing orthotopic SW780-Luc bladder tumors received six intravesical doses of CG0070 (3 × 1010 viral particles per dose in a 50 μL dosing volume) either once weekly for six consecutive weeks or twice weekly for three consecutive weeks [2]. Intravesical CG0070 achieved equal efficacy as seen in the subcutaneous model (Fig. 1).

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Fig. 2 Enhancement of urothelial transduction by DDM pretreatment in the bladders of female mice (a–c). Bladders were pretreated with PBS (a) or 0.1% DDM (b and c) and infected with a replication-defective adenovirus expressing β-galactosidase (Ad-LacZ). Depicted are representative whole bladders from a single animal tested in each group (n = 6 per group). Bladders were harvested, fixed, and stained with X-gal. Histological examination of the bladder showed that β-galactosidase expression was confined to the umbrella cells of urothelium with no expression observed in lamina propria (magnification: 20×)

To maximize viral penetration, several agents have been evaluated using a replication-defective adenovirus expressing β-galactosidase (Ad β-gal) as a marker of transduction. n-Dodecyl-β-D-maltoside (DDM) is a nonionic surfactant comprised of a maltose derivatized with a single 12 carbon chain and acts as a mild detergent and solubilizing agent. DDM has been used as a food additive as well as administered IV into humans as a formulation component for a peptide drug investigated in a Phase 1 trial as therapy for multiple sclerosis [9]. DDM is known to enhance mucosal surface permeation in rodents and humans, most likely due to its effect on membrane-associated glycosaminoglycan and tight junctions (Fig. 2) [10, 11]. Subsequent studies showed that adenovirus is compatible for co-formulation with DDM and that DDM was well-tolerated by the bladder. As a result of its increased transducibility and favorable toxicity profile, DDM was selected for use as a transduction enhancer for clinical trials involving CG0070. 1.5 Clinical Trials Using CG0070

In a phase I dose-finding clinical trial consisting of 35 patients with NMIBC recurring after intravesical BCG, patients were treated sequentially with intravesical 0.1% DDM followed by CG0070. Similar to other intravesical OV trials, grade 1–2 bladder toxicities were the most common adverse effects (AE). A total of six grade 3 or greater AEs were seen—pollakiuria in two, lymphopenia, dysuria, urgency, and nocturia in one each. Using urinary GM-CSF as a surrogate marker for pharmacokinetics, viral replication peaked at day 2 following primary infusion in the majority of the patients. Sustained viral genome shedding in the urine

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suggested ongoing viral replication between day 2 and 5 following intravesical infusion. Complete response (CR) rate and median duration of CR were 48.6% and 10.4 months (mo), with enhanced response found in patients harboring carcinoma in situ (CIS) [12]. In an exploratory analysis, 81.8% of the patients with borderline or high Rb phosphorylation responded to therapy. Interim analysis from a follow-up Phase II study in a more heavily pretreated patient population using a fixed dose of 1 × 1012 vp demonstrated 6mo CR of 45% (95% CI 32–62%), again with enhanced efficacy seen in patients with pure CIS [13]. Based on the promising preliminary results, a phase 3 trial was launched to test CG0070’s efficacy in the BCG unresponsive setting (NCT04452591). In addition, based on hypothesized mechanistic synergism with immune checkpoint blockade, two trials using the combination have been launched in the BCG unresponsive NMIBC (NCT04387461) as well as the neoadjuvant MIBC (NCT04610671) spaces, with promising preliminary findings [14, 15]. With the increasing level of evidence for its use and the widening indication, we describe the methodology of intravesical viral infusion to better inform prospective clinical trialists as well as clinicians who are interested in applying this agent. The infusion of CG0070 requires a step-wise protocol for bladder washes using saline, DDM, and CG0070. Herein, we provide step-by-step guidelines using a 2-way and 3-way catheter, depending on the availability at the infusion facility. We also provide general guidance on safety precautions and troubleshooting tips to facilitate safe drug administration.

2

Materials

2.1 General Supplies for Storage and Preparation

1. Ultra-low freezer required for storage, CG0070 vials require storage below -60 °C and DDM 5% vials from -25 °C to 15 °C. 2. CG0070 and DDM 5% vials require thawing to room temperature prior to preparation. 3. Prepared and administered according to Biosafety Level2 (BSL-2) handling guidelines. 4. 0.9% NaCl normal saline bags which are (poly-vinyl chloride) PVC-free and [di-(2-ethylhexyl) phthalate] DEHP-free required for preparation. 5. DDM 5% will need to be further diluted with 0.9% NaCl normal saline to a DDM 0.1% dilution.

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2.2 General Supplies for Administration

1. Personal protective equipment (PPE): gloves, gown, surgical mask, face shield. 2. Absorbent pads with plastic backing to place under patient, disposable preferred. 3. Sterile 2-way or 3-way Foley catheter with balloon. 4. Urine catheterization set. 5. Syringe to use to blow up Foley balloon. 6. Lidocaine jelly 2% (optional). 7. Catheter drainage bag (500 mL minimum volume). 8. Two tube clamps or hemostats to clamp catheter. 9. Catheter adapter to connect Foley port to Luer lock syringe. 10. Syringe cap to occlude the catheter adapter and/or syringe. 11. Gauze. 12. New biohazard bag for all drug and equipment disposal. 13. Cleansing wipes or cloth with soap and water to cleanse perineum at conclusion. 14. Timer (optional).

2.3 Syringes for Administration

1. 100 mL syringe with normal saline flush (or two 50 or 60 mL syringes) for total volume of 100 mL. 2. Two 50 or 60 mL syringes with DDM: One is filled to 50 mL, and the second is filled to 25 mL to constitute a total volume of 75 mL. 3. Two 50 or 60 mL syringes with DDM, both filled to 50 mL, to constitute a total volume of 100 mL. 4. One 100 mL syringe with normal saline flush (or two 50 or 60 mL syringes) for a total volume of 100 mL. 5. One 50 or 60 mL CG0070 syringe, filled to volume of approximately 40–50 mL. 6. One 50 or 60 mL syringe with normal saline, filled to a volume of 50 mL.

3

Methods

3.1 Using a 2-Way Catheter

1. Please refer to Subheading 4 regarding general precautionary measures (see Notes 1–4). 2. Using sterile techniques, perform urethral catheterization to place Foley catheter using usual institutional protocol. 3. Inflate the balloon using sterile water once catheter position is confirmed within the bladder.

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4. Ensure proper drainage of bladder. 5. Insert catheter adapter into the main port. Alternatively, a syringe with catheter tip can be used. Task 1: Initial Bladder Wash with Normal Saline (Fig. 3) 1. Refer to Subheading 4 regarding timing (see Notes 5 and 6). 2. Attach the 100 mL syringe of normal saline flush to the port. 3. Instill 100 mL of normal saline flush into the bladder via slow push to prevent backpressure that could cause splash, spill, or adapter displacement (see Note 9). 4. Clamp the Foley port. 5. Remove the catheter adapter and syringe from the Foley port. 6. Attach the drainage tube and collection bag. 7. Unclamp the Foley port. 8. Allow the bladder to drain the normal saline. 9. Re-clamp the Foley port. 10. Clamp the drainage bag tubing. 11. Remove the drainage bag from the Foley port. 12. Wipe the catheter adapter with an alcohol swab; allow it to dry completely and replace it in the Foley port. Alternatively, it can be placed onto the next syringe and then inserted into the catheter. Task 2: Second Bladder Wash with DDM 1. Attach and instill the first of the two 50 mL syringes of DDM totaling 75 mL into the bladder via slow push. 2. After the first syringe contents are instilled, clamp the infusion port. Keep the clamp behind the junction of all the ports of the catheter. 3. Change to the second syringe, unclamp the port, and slowly instill the second syringe of DDM. 4. Clamp the Foley port. 5. Remove the catheter adapter and syringe. 6. Reattach the drainage bag. 7. Unclamp the drainage tube and Foley and allow the bladder to drain the DDM. 8. Re-clamp the drainage tube and the Foley port. 9. Remove the drainage bag. 10. Clean the Foley port and adapter with an alcohol swab; allow it to dry completely.

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Fig. 3 Instillation via 2 way catheters. (a) Configuration of syringe + catheter adapter (blue) + Foley catheter. (b) Consider holding the catheter port and adapter during instillation. Inject fluid slowly to prevent backpressure that could cause splash, spill, or adapter displacement. (c) Clamp the main port only when changing syringes, adapters, and drain bag. (d) Remove catheter adapter (blue) attached to syringe. (e) Attach drain bag tubing to catheter, then remove clamp so bladder can drain. (f) Clamp Foley port and drainage bag tubing before disconnecting the bag and inserting the catheter adapter with next syringe

11. Replace the catheter adapter into the Foley port, or place onto the next syringe. Task 3: Instillation of DDM for 15-min Dwell 1. Attach the first DDM containing syringe. 2. Unclamp the Foley port. 3. Instill the DDM into the bladder via slow push, clamping the Foley port while the syringes are changed. 4. Instill the second syringe of DDM via slow push. 5. Clamp the Foley port.

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6. Unscrew the syringe and place a cap on the adapter in the Foley port. 7. Unclamp the Foley port. 8. Allow the DDM to dwell for 15 min, starting once all DDM is completely instilled. 9. During the 15-min dwell time, have the patient spend a few minutes laying on his/her right and left sides to distribute the DDM in the bladder. 10. Clamp the Foley port after 15 min have elapsed. 11. Remove the catheter adapter and cap from the Foley port. 12. Reattach the drainage bag. 13. Unclamp the Foley port and the drainage bag and allow the bladder to drain. 14. Re-clamp the drainage tube. 15. Remove the drainage bag from the Foley. 16. Clean the Foley port and adapter with an alcohol swab; allow it to dry completely. 17. Replace the catheter adapter into the Foley port or place on the next syringe. Task 4: Third Bladder Wash with Normal Saline 1. Attach the 100 mL normal saline syringe to the Foley port. 2. Unclamp the Foley port. 3. Instill 100 mL of normal saline flush into the bladder via slow push. 4. Clamp the Foley port. 5. Remove the catheter adapter and syringe from the Foley port. 6. Reattach the drainage bag to the Foley port. 7. Unclamp the Foley port and the drainage bag. 8. Allow the bladder to drain. 9. Re-clamp the drainage tube and the Foley port. 10. Remove the drainage bag from the Foley port. 11. Clean the Foley port and the catheter adapter with an alcohol swab and allow it to dry completely. 12. Replace the catheter adapter in the Foley port or place on the next syringe. Task 5: Instillation of CG0070 1. Attach the syringe of CG0070. 2. Unclamp the Foley port. 3. Instill the entire content of the 50 or 60 mL syringe of diluted CG0070 into the bladder via slow push. Tilt external catheter

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tip upward, so no diluted virus is accidentally lost when the syringes are switched. 4. Clamp the Foley port to change syringes to the saline flush. 5. Unclamp the infusion port. 6. Instill the 50 mL of normal saline from the second 50 or 60 mL syringe via slow push. 7. Refer to Subheading 4 regarding volume of infusion and changes in volume allowed for patients with reduced bladder capacity (see Notes 7 and 8). 8. Clamp the infusion port and remove the syringe. 9. Place a red syringe cap on the catheter adapter. 10. During the 60-min dwell time, have the patient spend a few minutes laying on his/her right and left sides to distribute the CG0070 in the bladder. Patients may move about in the treatment room as they are able. 3.2 Using a 3-Way Catheter

Following Foley insertion, ensure the drainage bag onto the main Foley port for complete bladder drainage. Then, clamp the central port on the catheter or the Foley drainage tubing using a tube clamp or hemostat. The clamp should be placed past the junction of all the ports so only the central port is clamped. If the Foley tubing is clamped, clamp as close to the junction with the Foley as possible. Insert the catheter adapter into the side infusion port. Task 1: Initial Bladder Wash with Normal Saline (Fig. 4) 1. Attach the 100 mL syringe of normal saline flush to the infusion port. 2. Instill 100 mL of normal saline flush into the bladder via slow push to prevent backpressure that could cause splash, spill, or adapter displacement. 3. Clamp the side infusion port. The syringe may remain attached, or a cap may be placed. 4. Unclamp the drainage tube and allow the bladder to drain the normal saline. 5. Re-clamp the drainage tube. 6. Remove the empty syringe or cap from the catheter side infusion port. 7. Clean the Foley port and adapter with an alcohol swab; allow it to dry completely. Task 2: Second Bladder Wash with DDM 1. Attach and instill the first of the two 50 mL syringes of DDM totaling 75 mL into the bladder via slow push.

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Fig. 4 Instillation via 3-way catheters. (a) Bladder wash with normal saline. Syringe and catheter adapter (blue) placed to infusion port. Drainage bag and tubing attached to central port and clamped. (b) Saline instilled, drainage bag clamp removed so saline can drain. Alternately, the syringe can be removed, and a cap placed during the drainage. (c) DDM syringe and catheter adapter placed to infusion port, drainage tubing clamped. (d) DDM instilled and then clamp instillation port to prepare for dwell time by removing syringe and placing a syringe cap. (e) Dwell configuration with cap (red) on catheter adapter (blue) to infusion port and drainage tubing clamped

2. After the first syringe contents are instilled, clamp the infusion port. Keep the clamp behind the junction of all the ports of the catheter. 3. Change to the second syringe, unclamp the port, and slowly instill the second syringe of DDM. 4. Clamp the infusion port and leave the second empty syringe attached or place a cap. 5. Unclamp the drainage tube and allow the bladder to drain the DDM. 6. Re-clamp the drainage tube. 7. Remove the empty syringe or cap from the infusion port. 8. Clean the Foley port and adapter with an alcohol swab; allow it to dry completely. Task 3: Instillation of DDM for 15-min Dwell 1. Verify that the drainage port is clamped. 2. Attach DDM syringe and instill the two 50 mL syringes of DDM totaling 100 mL into the bladder via slow push, clamping the infusion port while the syringes are changed. 3. Once both syringes are instilled, clamp the infusion port, remove the syringe, and place a cap to the catheter adapter.

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4. Allow the DDM to dwell for 15 min. Time starts once all DDM is completely instilled. 5. During the 15-min dwell time, have the patient spend a few minutes laying on his/her right and left sides to distribute the DDM in the bladder. 6. Unclamp the drainage tube after the 15 min have elapsed, and allow the bladder to drain completely. 7. Re-clamp the drainage tube. 8. Remove the cap from the infusion port. 9. Clean the Foley port and adapter with an alcohol swab; allow it to dry completely. Task 4: Third Bladder Wash with Normal Saline 1. Instill 100 mL of normal saline flush into the bladder via slow push. 2. Clamp the infusion port and leave the empty syringe attached. 3. Unclamp the drainage tube and allow the bladder to drain the normal saline completely. 4. Re-clamp the drainage tube and remove the empty syringe from the infusion port. 5. Clean the adapter with an alcohol swab, and allow it to dry completely. Task 5: Instillation of CG0070 1. Confirm that the drainage port is clamped. 2. Attach and instill the entire content of the 50 or 60 mL syringe of diluted CG0070 into the bladder via slow push. Tilt external catheter tip upward, so no diluted virus is accidentally lost when the syringes are switched. 3. Clamp the infusion port to change syringes. 4. Unclamp the infusion port. 5. Instill the 50 mL of normal saline from the second 50 or 60 mL syringe via slow push. 6. Refer to Subheading 4 regarding volume of infusion and changes in volume allowed for patients with reduced bladder capacity (see Notes 7 and 8). 7. Clamp the infusion port, remove the empty syringe, and attach a cap. 8. During the 60-min dwell time, have the patient spend a few minutes laying on his/her right and left sides to distribute the CG0070 in the bladder. Patients may move about in the treatment room as they are able.

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Finishing Steps 1. At the end of the 60-min dwell time for CG0070, unclamp the Foley and allow the bladder to drain completely. 2. Deflate the Foley balloon completely and remove the catheter, keeping a gauze pad over the catheter to catch any drips as the catheter is removed. 3. Immediately discard the Foley catheter and collection bag into biohazard waste. 4. Cleanse the patient perineum with an appropriate premoistened cleansing cloth or with soap, water, and a cloth. 5. The patient must be observed for 1 h following completion of the instillation process.

4

Notes 1. Universal precautions should be observed at all times during CG0070 instillation. A private room is preferred for the instillation process. If a semi-private area is used, clear signs should be provided to indicate contact isolation precautions are in effect during the instillation. 2. Providers who are pregnant, breastfeeding, or immunosuppressed, as a conservative measure, should NOT participate in study drug administration for CG0070. 3. A spill kit and eyewash station should be in close proximity to the infusion unit. 4. Providers administering CG0070 should wash their hands with soap and water and utilize local protocols as they apply to personal protective equipment (PPE) such as gown, gloves, surgical mask, and face shield. 5. Time from onset of the first bladder wash to instillation of the CG0070 should not exceed 30 min. 6. Total estimated patient care time for this process is 90–120 min (preparation, Foley catheterization, bladder wash, dwell time for DDM of 15 min, bladder wash, dwell time for CG0070 of 60 min, clean up), along with a 60-min observation period following completion. 7. The optimal total intravesical instillation volume of the CG0070 diluted in normal saline, and normal saline flush will be between 85 and 100 mL. For the first instillation, the complete volume of the diluted CG0070 must be administered followed with up to 50 mL of normal saline flush. 8. For subsequent instillations, for patients with documented reduction in bladder capacity who cannot tolerate holding

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85–100 mL in the bladder, the total intravesical instillation volume can be reduced at the discretion of the provider to a minimum of 55 mL (+/-10%), as per the instructions below: – 100% of the total volume of the diluted CG0070 must be instilled. – A minimum of 10 mL of the saline flush must be instilled following the instillation of diluted CG0070. 9. Bladder wash start time (initial wash only), DDM and CG0070 instillation start and stop times, and total volume of DDM and CG0070 administered should be documented. Any reductions in saline volumes administered must be documented including a note from the treating investigator on the reason for the reduction in volume.

5

Conclusions The protocol as outlined is simple and straightforward and easily replicated even in the hands of most healthcare providers experienced with intravesical therapy. The infusion of CG0070 has proven to be safe, with no iatrogenic transmissions recorded to date in over 200 patients treated. Due to its limited transmissibility, CG0070 is considered a Biosafety Level 2 agent. CG0070 should not be given with other intravesical therapies or with concomitant systemic immunosuppressive agent. In addition, antiviral agents used for viral infections (ganciclovir, cidofovir, brincidofovir, ribavirin, vidarabine, and interferon) should not be used in patients undergoing CG0070 treatment. In clinical trial results reported to date, the most common side effects were bladder-related symptoms, including pollakiuria, bladder spasms, and dysuria [15]. In rare cases, bladder spasms make it difficult for patients with small bladder capacities to tolerate dwell time of 60 min. One useful tactic is to pretreat patients using oxybutynin 5 mg PO × 1 1–2 h prior to infusion appointment. At the time of catheterization, it is also helpful to use generous amounts of topical lidocaine to minimize urothelial irritation. To reduce fluid overload within the bladder during treatment, patients are counselled to minimize fluid intake prior to infusion appointments. For patients who are undergoing combination immunotherapy with immune checkpoint inhibitor infusions, it is useful for them to undergo intravesical treatment prior to infusion of IV agents so as to minimize urine efflux. In the event of accidental spillage, it is imperative for the healthcare workers to take necessary precautions to minimize contamination. However, in the few instances where drug spillage has been encountered during treatment, minimal adverse events have been observed.

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In conclusion, CG0070 intravesical administration is straightforward and requires only basic familiarity with Foley catheter manipulation. Especially in patients with small bladder capacity, it is important to take all possible steps in minimizing bladder spasms during the course of treatment. Additionally, necessary precautions are required in the case of bladder spasms to prevent iatrogenic transmission. References 1. Salone B, Martina Y, Piersanti S et al (2003) Integrin alpha3beta1 is an alternative cellular receptor for adenovirus serotype 5. J Virol 77(24):13448–13454. https://doi.org/10. 1128/jvi.77.24.13448-13454.2003 2. Ramesh N, Ge Y, Ennist DL et al (2006) CG0070, a conditionally replicating granulocyte macrophage colony-stimulating factor— armed oncolytic adenovirus for the treatment of bladder cancer. Clin Cancer Res 12(1): 3 0 5 – 3 1 3 . h t t p s : // d o i . o r g / 1 0 . 1 1 5 8 / 1078-0432.CCR-05-1059 3. Cordon-Cardo C (2001) Applications of molecular diagnostics: solid tumor genetics can determine clinical treatment protocols. Mod Pathol 14(3):254–257. https://doi.org/ 10.1038/modpathol.3880294 4. Czerniak B, Chaturvedi V, Li L et al (1999) Superimposed histologic and genetic mapping of chromosome 9 in progression of human urinary bladder neoplasia: implications for a genetic model of multistep urothelial carcinogenesis and early detection of urinary bladder cancer. Oncogene 18(5):1185–1196. https:// doi.org/10.1038/sj.onc.1202385 5. Brandau S, Bo¨hle A (2001) Bladder cancer. I. Molecular and genetic basis of carcinogenesis. Eur Urol 39(5):491–497. https:// doi.org/10.1159/000052494 6. Wu Q, Possati L, Montesi M et al (1996) Growth arrest and suppression of tumorigenicity of bladder-carcinoma cell lines induced by the P16/CDKN2 (p16INK4A, MTS1) gene and other loci on human chromosome 9. Int J Cancer 65(6):840–846. https://doi.org/10. 1002/(sici)1097-0215(19960315)65: 63.0.Co;2-6 7. Yeager T, Stadler W, Belair C et al (1995) Increased p16 levels correlate with pRb alterations in human urothelial cells. Cancer Res 55(3):493–497 8. Paul WE (1993) Fundamental immunology, 3rd edn. Raven Press, New York

9. Rifkin RA, Maggio ET, Dike S et al (2011) N-dodecyl-β-D-maltoside inhibits aggregation of human interferon-β-1b and reduces its immunogenicity. J Neuroimmune Pharmacol 6(1):158–162. https://doi.org/10.1007/ s11481-010-9226-7 10. Goodkin DE, Shulman M, Winkelhake J et al (2000) A phase I trial of solubilized DR2: MBP84-102 (AG284) in multiple sclerosis. Neurology 54(7):1414–1420. https://doi. org/10.1212/wnl.54.7.1414 11. Gupta RK, Singh M, O’Hagan DT (1998) Poly (lactide-co-glycolide) microparticles for the development of single-dose controlled-release vaccines. Adv Drug Deliv Rev 32(3):225–246 12. Burke JM, Lamm DL, Meng MV et al (2012) A first in human phase 1 study of CG0070, a GM-CSF expressing oncolytic adenovirus, for the treatment of nonmuscle invasive bladder cancer. J Urol 188(6):2391–2397. https:// doi.org/10.1016/j.juro.2012.07.097 13. Packiam VT, Lamm DL, Barocas DA et al (2018) An open label, single-arm, phase II multicenter study of the safety and efficacy of CG0070 oncolytic vector regimen in patients with BCG-unresponsive non-muscle-invasive bladder cancer: interim results. Urol Oncol 36(10):440–447. https://doi.org/10.1016/j. urolonc.2017.07.005 14. Li R, Spiess PE, Sexton WJ et al (2022) Preliminary results from phase Ib/II neoadjuvant CG0070 and nivolumab (N) for cisplatin (C)ineligible muscle invasive bladder cancer (MIBC). J Clin Oncol 40(16_suppl):4574. https://doi.org/10.1200/JCO.2022.40.16_ suppl.4574 15. Li R, Steinberg GD, Uchio EM et al (2022) CORE1: phase 2, single-arm study of CG0070 combined with pembrolizumab in patients with nonmuscle-invasive bladder cancer (NMIBC) unresponsive to bacillus CalmetteGuerin (BCG). J Clin Oncol 40(16_suppl):4597. https://doi.org/10. 1200/JCO.2022.40.16_suppl.4597

Chapter 20 Analysis of ICAM-1 Expression on Bladder Carcinoma Cell Lines and Infectivity and Oncolysis by Coxsackie Virus A21 Kate Relph, Mehreen Arif, Hardev Pandha, Nicola Annels, and Guy R. Simpson Abstract Oncolytic viruses are biological agents which can easily be delivered at high doses directly to the bladder through a catheter (intravesical), with low risk of systemic uptake and toxicity. To date, a number of viruses have been delivered intravesically in patients and in murine models with bladder cancer and antitumour effects demonstrated. Here, we describe in vitro methods to evaluate Coxsackie virus, CVA21, as an oncolytic virus for the treatment of human bladder cancer by determining the susceptibility of bladder cancer cell lines expressing differing levels of ICAM-1 surface receptor to CVA21. Key words Oncolytic, Virus, Coxsackie, Bladder, Cancer

1

Introduction

1.1 Current Treatment for Bladder Cancer

Bacillus Calmette–Gue´rin (BCG) immunotherapy is standard of care for intermediate and high-risk non-muscle-invasive (NMIBC) bladder cancer and is effective in early stage disease. Whilst the initial response to BCG in NMIBC and carcinoma in situ (CIS) is high, there is still a large subgroup of nonresponders, and one-third of NMIBC patients eventually experience serious side effects of local and systemic BCG infection, with many unable to complete treatment programs.

1.2 Novel Treatments for Bladder Cancer

Bladder cancer has the highest lifetime cost per patient amongst all cancers due to the high rate of recurrence, longer overall patient survival, and requirement for lifelong cystoscopic surveillance [1, 2]. New treatments with better efficacy, low toxicity, and low cancer progression rates are required so that they can provide better quality of life. The anatomy of the bladder is ideally suited for drug therapy for anatomically superficial disease and exploits simple long-established clinical protocols using catheterisation. Catheters

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allow controlled infusion volumes and infusion rates and allow sequential or concomitant treatments, variable retention times, as well as direct visualisation and photography of tumours pre- and post-treatment. Similarly, assessment of biological response by collection of urine (e.g. cytokines, shed tumour cells) as well as biopsy acquisition via the cystoscope all allow the mechanisms of action of drugs to be examined [3, 4]. 1.3 Oncolytic Viruses as Novel Treatments for Bladder Cancer

Oncolytic viruses are biological agents which have a number of attractive properties as cancer agents. One Herpes simplex virus (HSV), T-VEC, is established as a routine treatment by intratumoural injection, and numerous others are being evaluated as single agents or in combination across a range of malignancies [5]. Various oncolytic viruses such as HSV, adenovirus, reovirus, and vaccinia virus have already shown therapeutic benefit in preclinical orthotopic models and clinically in patients with NMIBC [4, 6]. Oncolytic viruses act by two main mechanisms, firstly by direct cytolytic effect after infection and secondly by induction of a systemic anticancer immune response [7]. Various hallmarks of cancers described by Weinberg [8, 9] such as defective apoptosis signalling pathways, uncontrolled proliferation, and inactive growth suppression are utilised by oncolytic viruses for selective replication in cancer cells [7]. Some oncolytic viruses can be genetically modified to insert promoters to limit their infection and replication specifically to cancer cells, whilst other naturally occurring viruses such as measles virus target cancer cells due to an overexpressed viral entry receptor [10].

1.4 The Oncolytic Virus Coxsackie A (CVA21) Requires ICAM-1 Receptors on the Cell Surface for Entry into Bladder Cancer Cells

CVA21 is a wild-type (non-modified) Coxsackie A virus that has intrinsic oncolytic ability. CVA21 is a picornavirus, 28 nm in size, non-enveloped and consisting of a single-stranded positive RNA genome enclosed in an icosahedral capsid [11, 12]. CVA21 is a highly selective anticancer therapy as it targets ICAM-1 and DAF membrane receptors for cell entry, and both membrane receptors are frequently overexpressed in cancer cells as compared to normal cells [11]. After binding to the receptor, CVA21 is internalised into the cancer cell. Viral capsid conformational change is essential which only occurs when CVA21 attaches to the ICAM-1 receptor; however, DAF cannot induce capsid structural changes [13]. Therefore, the recognition and binding to ICAM-1 receptor leads to CVA21 lytic infection, whereas DAF acts as co-facilitator by accumulating CVA21 on the cell surface [13]. ICAM-1 is overexpressed in breast cancer, prostate cancer, melanoma, multiple myeloma, and lung cancer, and CVA21 oncolytic immunotherapy has already shown tumour-suppressive benefits in these malignancies [11]. Bladder cancer is an ideal model for CVA21 oncolytic immunotherapy as bladder cancer cells display high to intermediate ICAM-1 cytoplasmic and membrane expression which can be exploited by CVA21 for entry. CVA21 is a naturally occurring

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virus and normally induces only mild side effects such as flu-like symptoms, whilst its small size enables it to spread in the tumour microenvironment. We conducted a phase 1 trial of an ICAM-1 targeted CVA21 in non-muscle-invasive bladder cancer [14]. Clinical activity was demonstrated by induction of tumour inflammation and haemorrhage following either single or multiple administrations of CAVATAK in multiple patients and a complete resolution of tumour in one patient. However, our initial work on CVA21 involved analysis of viral activity on bladder cancer cell lines in vitro. This chapter is an introduction to working with CVA21. It describes methods to study CVA21 on bladder cancer cell lines. This includes working with the virus and calculating concentration and multiplicity of infection, determining ICAM receptor surface level expression on bladder cancer cell lines, administering virus to cell lines and calculating percentage cell survival.

2

Materials

2.1 Bladder Cancer Cell Lines 2.2

Reagents

See Table 1 for detailed info on source, culturing, and treatment of bladder cancer cell lines. 1. Media used for each cell line was supplemented with 100 U/ mL Penicillin, 100 μg/mL Streptomycin, 2 mM L-Glutamine, and 10% foetal bovine serum. 2. Phosphate-buffered saline. 3. Hank’s Solution. 4. Accutase Cell Dissociation Reagent (see Note 1). 5. Trypsin-EDTA solution. 6. Trypan blue vital stain. 7. Haemocytometer. 8. QuantiBRITE Assay—BD QuantiBRITE™ Beads PE Fluorescence Quantitation Kit (BD Biosciences, # 340495). 9. FACS stain buffer: 0.5% BSA, 2 mM EDTA in PBS. 10. Suitable desinfectant against respective virus (e.g. Virkon, Sigma Aldrich). 11. MTS colorimetric cell-viability solution. 12. Bovine serum albumin. 13. Antibodies: PE Mouse Anti-Human CD54 antibody (ICAM1, BD Biosciences Cat No: 347977) Rabbit IgG Isotype control (Abcam ab1099093) (1:3000). Goat Anti-Mouse IgG1 Alexa Fluor® 488 (Life Technologies A-21121) (1:200), and Goat Anti-Rabbit IgG Alexa Fluor® 488 (Life Technologies A11034) (1:200).

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Table 1 Bladder cancer cell lines

Transitional cell urinary bladder carcinoma cell line Media

Supplier

CVA21 MOI used for subsequent experiments

T24

McCoy’s 5a medium modified

American type culture 11.44 collection (ATCC)

TCCSUP

Dulbecco’s modified Eagle’s

ATCC

1.00

5637

RPMI-1640

ATCC

1.83

KU19-19

RPMI-1640

DSMZ

25.0

RT-112

RPMI-1640

DSMZ

25.0

VM-CUB 1

Dulbecco’s modified Eagle’s

DSMZ

25.0

J82

Eagle’s minimum essential

ATCC

25.0

253 J

RPMI1640 + Dulbecco’s modified Eagle’s

Donation. University of Leeds

2.28 × 10-3

VM-CUB-2

Dulbecco’s modified Eagle’s

Donation, University of Leeds

0.293

HCV29

RPMI-1640

Donation, University of Leeds

4.57 × 10-3

2.3

3

Virus

The Kuykendall strain of CVA21 oncolytic virus is owned and manufactured by Viralytics Limited (Sydney, Australia) and is branded as CAVATAK™. Stock virus was kindly provided by Viralytics at a concentration of 7.5 × 107 TCID50/mL in 2.15 mL vials which were stored once received at -80 °C.

Methods

3.1 QuantiBRITE™: Expression of ICAM-1 Receptors on Cancer Cell Lines

1. Seed bladder cancer cells (Table 1) in a T75 flask to reach 80–90% confluency and incubate overnight. 2. The next day, assess the confluency of cells under the microscope. Remove the media and add 10 mL of PBS to wash the cells and then discard the PBS. Add 5 mL of Accutase to the flask to detach the cells and place the flask in the incubator for 5 min (see Note 1). 3. Using a pipette, transfer the cell suspension to a 10 mL universal tube, and centrifuge at 2550 g for 3 min. Discard the supernatant, and resuspend the cell pellet carefully in approximately 5 mL of PBS.

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4. Count the cells to ensure enough cells are present in the solution to allow an accurate measurement using a flow cytometer. This needs to be between 1 × 105 and 1 × 106 cells in total. Resuspend the cells in Trypan blue in 1:10 ratio (10 μL cells and 90 μL Trypan blue) and count using a haemocytometer. Centrifuge the cells at 2550 g for 3 min. Discard the supernatant and resuspend the pellet in 0.5 mL of FACS Buffer. 5. Pipette 100 μL of cells (1 × 105 to 1 × 106 cells in total) into the appropriate number of wells of a 96-well plate and centrifuge at 2550 g for 3 min and then flick off the excess liquid. 6. Add 20 μL PBS + 20 μL PE Mouse Anti-Human CD54 (ICAM-1, BD Biosciences) antibody (dilution above) to each well. Leave the plate to incubate at RT for 20 min. Use PBS 0.1% bovine serum albumin (BSA) as a negative control (see Note 2). 7. Add 150 μL of PBS to each well and centrifuge at 2550 g for 2 min and then flick off the excess liquid. Add 200 μL of FACS Buffer. 8. Determine the mean density of ICAM-1 bound per cancer cell using QuantiBRITE™ PE beads (Fig. 1). 9. QuantiBRITE™ PE beads are conjugated with four levels of PE which are used with PE-labelled monoclonal antibodies to determine the antibody bound per cell using a flow cytometer and associated software. 3.2 Dilution of Working Virus Concentration

Definitions Multiplicity of infection (MOI) is a frequently used term in virology which refers to the number of virions that are added per cell during infection. If one million virions are added to one million cells, the MOI is one. If ten million virions are added, the MOI is ten. Add 100,000 virions, and the MOI is 0.1. Plaque forming units (pfu) is the measure of infectious virus particles capable of infecting permissive cells, causing plaque formation that allows for virus to be titrated. It is a proxy measurement rather than a measurement of the absolute quantity of particles: viral particles that are defective or which fail to infect their target cell will not produce a plaque and thus will not be counted. For example, a solution of virus A with a concentration of 1000 PFU/μL indicates that 1 μL of the solution contains enough virus particles to produce 1000 infectious plaques in a cell monolayer, but no inference can be made about the relationship of PFU to number of virus particles. TCID50 is sometimes used in place of PFU. It is the tissue culture infectious dose which will infect 50% of the cell monolayer challenged with the defined inoculum.

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Fig. 1 Linear Regression of QuantiBRITE™ PE molecules per beads with their means. In order to determine PE/ICAM-1 molecules per cell, the geometric means of 4 bead populations were obtained using flow cytometry. The log10 of the fluorescence mean (Log FL2) was plotted against the log10 of PE molecules per bead (Log PE/bead), value provided in the kit. Linear regression was calculated using the equation y = mx + .c where y = log10 fluorescence mean, x = log10 PE molecules per bead. The ICAM-1 antibody bound on unknown sample was calculated by substituting log fluorescence mean for sample mean value

If we assume the conditions used for plaque assay and TCID assay do not alter the expression of infectious virus, TCID50/mL and pfu/mL are related by: pfu=mL = 0:7 × TCID50

1. Stock 7.5 × 107 TCIID50 unit/mL of CVA21, which was previously titrated by the manufacturer, is diluted to a working concentration per well of cells using the established equation [15]: Pfu per well = Number of cells per well × Multiplicity of infection ðMOIÞ Volume of CVA21 stock needed per well =

pfu per well 7:5 × 10 pfu per mL CVA21 7

2. Virus is titrated onto bladder cancer cell lines to give a range of MOI including 0–50 MOI per cell (Fig. 2). Cell death is assessed using MTS assay (see Subheading 3.3).

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Fig. 2 Bladder cancer cell-lines display differing levels of ICAM-1 membrane receptor expression which dictate sensitivity to CVA21. (a) PE-labelled anti-ICAM-1 antibodies were used with QuantiBRITE™ PE beads to quantify the ICAM-1 molecules bound per cell on all bladder cancer cell lines. VM-CUB-1, 253J and HCV29 cell lines displayed the highest ICAM-1 expression, followed by intermediate ICAM-1 expression on T24, J82, TCCSUP, and low ICAM-1 expression on KU19-19, VM-CUB 1, and RT-112. Graph represents pooled data from two independent experiments. (b) Correlation between ICAM-1 expression level and percentage cell viability was compared for CVA21 MOI 0.75 (low), 6.25 (medium), and 50 (high). Cell lines with the highest ICAM-1 expression were most sensitive to CVA21-induced death

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Fig. 3 Conversion of MTS compound into coloured formazan product in the presence of metabolically active cells. The MTS compound ([3-(4, 5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium], inner salt) combines with an electron coupling reagent which in the presence of NADPH/NADH from metabolically active cells reduces to a coloured formazan compound. The amount of formazan compound produced is directly proportional to the number of viable cells

3.3 Incubation of Cells with Oncolytic Virus and Assessment of Cell Viability Using MTS Assay

1. Use MTS colorimetric cell-viability assay to assess reduction in cell survival induced by CVA21. 2. MTS measures the cellular respiration and metabolic activity of cells which indicates the number of viable cells (Fig. 3). 3. Count the cells using a Neubauer haemocytometer and calculate cells/volume or total number of cells (see Note 3). 4. Seed 100 μL cells/well into a 96-well plate at the required seeding density and incubate overnight at 37 °C to ensure an 80% confluency. 5. The next day, treat cells with a range of CVA21 MOIs from 0 to 50 and incubate for 72 h. 6. As an additional control, use heat-inactivated CVA21 to demonstrate that cell death induced was due to live virus (see Note 4). 7. After 72 h, dilute 100 μL of MTS reagent 1:10 in RPMI-1640 media and add to each well and incubate for an h (see Note 5). 8. Measure the absorbance/optical density (OD) at 490 nm using a microplate reader. 9. Percentage cell survival is calculated using the following equation:

%Cell survival ¼ ðAverage OD cells with treatment - Average OD MTS blankÞ =ðAverage OD cells without treatment - Average OD MTS blankÞ × 100

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Notes 1. Due to the negative effect of the proteolytic and collagenolytic activity of Accutase on cell viability, the incubation time should be kept short. 2. Always use unstained controls for antibodies in order to assess the amount of background fluorescence. Also include untreated cells as another control. 3. Quickly washing cells with PBS and adding Accutase as leaving the cell monolayer without any media can dry the layer and result in cell death. 4. CVA21 was heat inactivated at 60 °C for 2 h in a water bath. 5. Assay plate for MTS covered in aluminium foil. The MTS solution should be aliquoted and stored in 5 mL bijoux and covered with foil as MTS solutions are light sensitive.

References 1. Barocas DA, Globe DR, Colayco DC et al (2012) Surveillance and treatment of nonmuscle-invasive bladder cancer in the USA. Adv Urol 8:421709 2. Svatek RS, Hollenbeck BK, Holm€ang S et al (2014) The economics of bladder cancer: costs and considerations of caring for this disease. Eur Urol 66(2):253–262 3. Fuge O, Vasdev N, Allchorne P et al (2015) Immunotherapy for bladder cancer. Res Rep Urol 7:65–79 4. Potts KG, Hitt MM, Moore RB (2012) Oncolytic viruses in the treatment of bladder cancer. Adv Urol 2012:404581 5. Goldufsky J, Sivendran S, Harcharik S et al (2013) Oncolytic virus therapy for cancer. Oncolytic Virother 2:31–46 6. Delwar Z, Zhang K, Rennie PS et al (2016) Oncolytic virotherapy for urological cancers. Nat Rev Urol 13(6):334–352 7. Farkona S, Diamandis EP, Blasutig IM (2016) Cancer immunotherapy: the beginning of the end of cancer? BMC Med 14:73 8. Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100(1):57–70 9. Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144(5): 646–674

10. Choi A, O’Leary M, Fong Y et al (2016) From benchtop to bedside: a review of oncolytic virotherapy. Biomedicine 4(3):18 11. Bradley S, Jakes AD, Harrington K et al (2014) Applications of coxsackievirus A21 in oncology. Oncolytic Virother 3:47–55 12. Xiao C, Bator-Kelly CM, Rieder E et al (2005) The crystal structure of coxsackievirus A21 and its interaction with ICAM-1. Structure (Lond Engl 1993) 13(7):1019–1033 13. Shafren DR, Dorahy DJ, Ingham RA et al (1997) Coxsackievirus A21 binds to decayaccelerating factor but requires intercellular adhesion molecule 1 for cell entry. J Virol 71(6):4736–4743 14. Annels NE, Mansfield D, Arif M et al (2019) Phase I trial of an ICAM-1-targeted immunotherapeutic-coxsackievirus A21 (CVA21) as an oncolytic agent against non muscle-invasive bladder cancer. Clin Cancer Res 25(19):5818–5831 15. Pourianfar HR, Javadi A, Grollo L (2012) A colorimetric-based accurate method for the determination of enterovirus 71 titer. Indian J Virol 23(3):303–310

INDEX A

D

Antibody-drug conjugate (ADC) .................11, 293–300

Data processing ........................................... 64, 66, 71, 72 Deconvolution .......................55, 56, 116, 117, 123–129 Diagnosis ...................................11, 14, 17, 59, 201, 206, 209, 213–227, 249, 254 Disease management..................................................... 291 Disitamab vedotin ......................................................... 297 Distinct algorithms ....................................................... 253 DNA damage..................................... 134, 135, 141, 164, 182, 196, 233–237, 262, 267–268, 274–275 Droplet digital PCR .....................................183, 213–227 Drugs ..............................................11, 46, 60–62, 67–70, 82, 83, 85–94, 134, 138, 238, 242, 250–252, 254, 263, 276, 277, 284, 295, 297–299, 306–308, 315, 316, 319, 320

B BET inhibitor ................................................................ 265 Biomarker .............................................3, 4, 76, 146, 147, 200–211, 213–216, 227, 229–244 Bladder........................................... 16, 27, 46, 59, 69, 74, 76, 90, 113, 115, 118, 146, 147, 149, 150, 157, 167, 169, 172, 173, 203, 206, 214, 230, 234, 236, 237, 253, 284, 296, 304–317, 319–327 Bladder cancer ........................................7, 18, 32, 46, 47, 52, 53, 59, 69, 74, 76, 77, 90, 91, 113–114, 124, 135–138, 141, 145–150, 168, 173, 179, 195, 200–211, 233–235, 237–240, 242, 244, 249, 283, 284, 289, 296, 298, 299, 303–317, 319–322, 324, 325

C Cancer..........................................7, 32, 45, 59, 102, 114, 133, 146, 164, 167, 179, 200, 213, 229, 249, 260, 283, 296, 303, 319 Cancer cell fraction (CCF) ........................ 114, 117, 121, 123–126, 128, 129 Cancer genomics ........................................................... 137 CDK4/6 inhibitor .......................................157, 162–163 CG0070................................................................ 303–317 Chemotherapy........................................5, 7, 60, 64, 115, 145, 230, 232–242, 249, 283, 293, 297, 298 Circulating tumor DNA (ctDNA) ..................... 179–196, 216, 243, 244 Cisplatin.....................................136, 138, 139, 141, 230, 232–234, 237, 262, 264, 265, 276 Clonal evolution................................................... 121, 196 Cohesin.......................................................................... 146 COMPASS complex............................................. 101–108 Consensus classification .............................. 28, 29, 36, 40 Copy number analysis ................................................... 120 Coxsackie .............................................................. 319–327 CRISPR/Cas9...................................................... 156, 157 Custom panels design .........................180, 182, 185–187

E Electrophoresis .................................................... 103, 106, 168–172, 186, 193 Enfortumab vedotin (EV) ..................293, 294, 296–299 Epigenetic deregulation................................................ 135 Epigenetic priming............................................... 260–278 Epigenetics ................................. 101, 135, 137, 260–264

F FGFR testing ........................................................ 288, 290 Follow-up ................................................... 200–211, 215, 237, 243, 263, 307

G Gene expression analysis ....................... 28, 31–39, 41, 42 Genetic instability ........................................................... 45 Genome-wide screening ............................................... 157 Genomics ................................... 63, 70, 90, 91, 114–115, 118, 124, 135, 137, 155, 157, 180, 195, 224, 232–234, 236, 239, 260, 262, 285 Gradient SDS–PAGE .................................................... 103

H Histone deacetylase inhibitors (HDACi) ...................261, 262, 265, 276

Miche`le J. Hoffmann et al. (eds.), Urothelial Carcinoma: Methods and Protocols, Methods in Molecular Biology, vol. 2684, https://doi.org/10.1007/978-1-0716-3291-8, © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2023

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330 Index

Hyaluronan (HA)................................................. 167–174 Hyaluronan degradation............................................... 167

I Imaging..................... 105, 106, 141, 168, 171, 173, 237 Immune checkpoint inhibition ...................242–243, 263 Immunohistochemistry (IHC).................3–19, 145–150, 231, 232, 250, 254, 296 Immunotherapy ....................................... 5, 59, 145, 237, 241, 242, 244, 316, 319, 320 Inhibitor ....................................5, 28, 32, 34, 41, 60, 61, 104, 159, 214, 230, 239, 241, 242, 250, 253, 260–265, 270, 284, 291, 293, 294, 297, 298, 316 Intravesical infusion ...................................................... 307

K KMT2 ............................................................................ 101

L Lentivirus.............................................137, 159, 162, 163 Liquid biopsy............................................... 180, 182, 214 LundTax classification..................................................... 40

M Metaphase chromosomes ............................136, 139–140 Molecular subtype classification ..................................... 27 Muscle invasive bladder cancer (MIBC)................ 27, 28, 60, 73, 75, 79, 82–86, 114, 118, 145–147, 150, 200, 201, 204, 229–231, 234–240, 242, 243, 260, 284, 299, 307 Mutational signatures ...................................... 46–57, 115

N Neoadjuvant therapy....................................118, 229–244 Next-generation sequencing (NGS) .................. 114, 119, 155, 157, 160, 163, 180–185, 187–192, 194–196, 214, 231, 232, 284, 291 Non-negative matrix factorization (NMF)................... 46, 49, 54, 56 Nuclear protein fractionation ....................................... 102

O Omics............................... 60, 61, 69, 77, 79–83, 93, 114 Oncolytic ..................................................... 303, 304, 320 Oncolytic virus ........................... 303–317, 320, 322, 326

P PARP inhibitor (PARPi) ...................................... 135, 262 PCR bias ........................................................................ 182 PD-L1 assessment ............................................5, 250, 251 Phylogenetics................................................................. 114

Predictive biomarkers.................................. 157, 230, 231 Proteomics......................................61, 62, 64–66, 74–76, 78, 81, 82, 93, 102

Q QIAGEN therascreen® FGFR RGQ RT-PCR Kit..................................................... 284, 288, 289

R Replication stress......................................... 133, 135, 137 Repurposing ................................... 60–62, 68, 83, 90, 93 Rule set .................................................. 29, 35, 36, 39–40

S Sacituzumab govitecan (SG) .......................293, 295–299 Scoring.................. 3–19, 81, 82, 84, 137, 141, 250–254 SgRNA.................................................................. 162–164 Signature..................................34, 35, 38, 39, 46, 49–56, 61, 62, 68, 83, 86–90, 94, 116, 230, 238, 242 Signature scores.....................................29, 35, 38, 39, 42 Size exclusion chromatography (SEC) ............... 101–108 SNaPshot analysis................................................. 286–289 Software ......................................... 39, 46, 64, 66, 67, 83, 86, 93, 119–122, 126, 127, 130, 194, 223, 224, 265, 266, 268, 270, 277, 287, 288, 323 Somatic mutations ..................................... 45–47, 49, 52, 68, 119, 121, 146, 196, 227 STAG2 .................................................................. 146–150 Surveillance........................................ 145, 146, 200, 202, 205–211, 214, 215, 227, 236, 237, 319

T Targeted therapy .......................... 7, 8, 12, 260, 284, 291 TERT promoter mutations.................................. 213–227 The Cancer Genome Atlas (TCGA) .......................28–30, 35, 36, 39, 63, 102, 233, 236, 239, 240, 260 Therapeutic markers ......................................................... 3 Therapy resistance ................................................ 155–164 Tissue slice cultures.............................................. 167–174 Transcriptomics .......................................... 61–64, 69, 72, 73, 76, 78, 79, 81, 82, 92, 93, 234, 239 Trastuzumab deruxtecan ..................................... 295, 297 Tumor markers.............................................................. 243

U UMI and error suppression ................................. 117, 181 Urinary tumor markers................................................. 199 Urine samples ......................................194, 203, 213–227 Urothelial cancer .......................................... 41, 102, 196, 213–227, 234, 237, 249–254, 264–265, 288, 290, 297–300

UROTHELIAL CARCINOMA: METHODS Urothelial carcinoma .......................................... 3–19, 90, 101–108, 133–142, 155–164, 167–174, 204, 242, 249–251, 254, 283–286, 290, 291, 293–300, 304 UTX ..............................................................101–103, 107

AND

PROTOCOLS Index 331

V Variant allele frequency (VAF) ........................... 114–117, 121, 124, 180, 187, 195 Virus.................. 161–163, 303–305, 312, 314, 319–327