Thesis

BIRGIT M.M. WEVER TOWARD A NEW ERA OF CANCER DETECTION PATIENT-FRIENDLY SOLUTIONS

BIRGIT M.M. WEVER TOWARD A NEW ERA OF CANCER DETECTION PATIENT-FRIENDLY SOLUTIONS

Printing of this thesis was financially supported by: Afdeling Pathologie, Amsterdam UMC, locatie VUmc Bridea Medical B.V. Cancer Center Amsterdam ChipSoft B.V. Rovers Medical Devices B.V. Self-screen B.V. Stichting Longkanker Nederland Vrije Universiteit Amsterdam DOI: 10.5463/thesis.511 ISBN: 978-94-6473-309-9 Layout and design: Marilou Maes | persoonlijkproefschrift.nl Printed by: Ipskamp Printing | proefschriften.net © Copyright 2024. Birgit M.M. Wever All rights reserved. No part of this thesis may be reproduced, stored or transmitted in any way or by means without the written permission of the author or by the publishers of the publication.

VRIJE UNIVERSITEIT Toward a new era of cancer detection: patient-friendly solutions ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad Doctor aan de Vrije Universiteit Amsterdam, op gezag van de rector magnificus prof.dr. J.J.G. Geurts, in het openbaar te verdedigen ten overstaan van de promotiecommissie van de Faculteit der Geneeskunde op donderdag 18 januari 2024 om 11.45 uur in een bijeenkomst van de universiteit, De Boelelaan 1105 door Birgit Margaretha Maria Wever geboren te Drechterland

promotoren: prof.dr. R.D.M. Steenbergen dr. M.C.G. Bleeker copromotor: dr. N.E. van Trommel promotiecommissie: dr. D. van den Broek prof.dr. J. Gribnau prof.dr. N.C.T. van Grieken prof.dr. C.J.M. van Noesel dr. J.M.A. Pijnenborg prof.dr.ir. L.I. Segerink

‘What is now proved was once, only imagined’ William Blake

TABLE OF CONTENTS Chapter 1 General introduction 9 Part 1 Endometrial and ovarian cancer detection in patient-friendly samples Chapter 2 Non-invasive detection of endometrial cancer by DNA methylation analysis in urine Clinical Epigenetics. 12, 1, p. 165. (2020) 31 Chapter 3 DNA methylation markers for endometrial cancer detection in minimally invasive samples: a systematic review Epigenomics. 12:18, 1661-1672. (2020) 49 Chapter 4 DNA methylation testing for endometrial cancer detection in urine, cervicovaginal self-samples and cervical scrapes International Journal of Cancer. 153(2): 341-351. (2023) 77 Chapter 5 Molecular analysis for ovarian cancer detection in patientfriendly samples medRxiv. 2023.09.28.23296279. (2023) 109 Part 2 Non-small cell lung cancer detection in urine Chapter 6 Detection of non-metastatic non-small cell lung cancer in urine by methylation-specific PCR analysis: a feasibility study Lung Cancer. 170:156-64. (2022) 149 Chapter 7 Dynamics of methylated cell-free DNA in the urine of nonsmall cell lung cancer patients Epigenetics. Oct 4:1-13. (2021) 175 Chapter 8 Summary and general discussion 205 Appendices Dutch summary | Nederlandse samenvatting 238 List of contributing authors 242 PhD portfolio 244 List of publications 246 About the author | Curriculum Vitae 248 Cover design description 249 Acknowledgements | Dankwoord 250

CHAPTER 1 GENERAL INTRODUCTION

10 Chapter 1 GENERAL INTRODUCTION The global cancer burden of 19 million new cases in 2020 is expected to grow to over 30 million new cases in 2040, based on population growth and aging (1). Cancer remains one of the leading causes of death worldwide, despite the development and use of innovative treatments during the last decades (2). High mortality rates are partly caused by late diagnosis, as cancer is often detected at an advanced stage when treatment options are limited. Another major cause of high mortality rates is recurrence after effective initial treatment (3). The rising cancer burden has also increased the focus on understanding the underlying causes of cancer. As a result, more cancer risk factors are known, thereby also increasing the number of individuals with a high cancer risk (4). This places increasing pressure on the healthcare system, emphasizing the need for innovative cancer detection strategies. Patient-friendly cancer detection methods could offer a potential solution to advance cancer diagnostics. This strategy would allow self-collection from home and reduce the initial need to visit a healthcare professional, which could alleviate the burden on both patients and healthcare systems. 1.1 Challenges and opportunities in cancer diagnostics and surveillance Currently, invasive tissue biopsy procedures are performed in the diagnostic workup of individuals with suspected cancer. However, conventional tissue sampling is often associated with discomfort, time-consuming procedures, high costs, and potential complications. Moreover, cancerous lesions can be missed or incompletely captured during biopsy procedures. These limitations encourage the development of alternative and less invasive methods for cancer diagnosis (5). The use of a liquid biopsy, which refers to the sampling and analysis of body fluids, holds potential as a novel tool for cancer detection (6, 7). Blood is the most extensively investigated liquid biopsy, but also alternative fluids are actively pursued, including saliva, sputum, stool, urine, and vaginal fluid (8). Their patient-friendly collection method enables the convenient and repetitive acquisition of fresh tumor material, which can easily be performed at home. Home-based sample collection has readily been implemented in cancer screening programs. The examination of home-collected cervicovaginal material (9) and stool (10) for cervical and colorectal cancer screening, respectively, helps to identify individuals with an increased cancer risk. Patient-friendly sample collection at home maximizes the reach of health monitoring efforts while minimizing logistical challenges and patient burden.

11 General introduction Reliable cancer detection requires highly sensitive and specific methods. A measurable characteristic that objectively reflects the presence of a certain biological condition is known as a biological marker, or shortly: a biomarker (11). The perfect biomarker would have 100% sensitivity and 100% specificity, meaning that individuals with disease will always get a positive test result and individuals without disease will always score negative. Combining patient-friendly sampling methods with reliable biomarker testing can serve as a powerful tool that is convenient for patients and effective in detecting cancer at a curable stage. Finding a suitable biomarker for early cancer diagnosis is challenging. No one-sizefits-all approach exists, as cancer is a complex heterogeneous disease in which each cancer type carries a unique molecular background. Even cancers that originate from the same organ or tissue type may differ extensively in their genetic profile. The complexity of cancer development and its underlying mechanisms are detailed within the conceptual hallmarks of cancer framework, as primarily described by Hanahan and Weinberg (12). The original model described six general mechanisms that drive cancer development, including self-sufficiency in growth signals, insensitivity to growthinhibitory signals, evasion of programmed cell death, limitless replicative potential, sustained angiogenesis, and tissue invasion and metastasis. During the last two decades, the original model has been updated twice (13, 14), which accentuates the continued advances in understanding the cellular and genetic mechanisms involved in carcinogenesis. The most recent update of the hallmarks of cancer includes the crucial role of non-mutational epigenetic reprogramming in malignant transformation (14). Epigenetics refers to the reprogramming of cells by altering the expression of genes, without modifying the DNA sequence itself. This adds an additional layer of complexity to the genome. One of the well-studied epigenetic mechanisms is DNA methylation (15). This epigenetic alteration is associated with gene silencing and poses an attractive biomarker to detect cancer early (16). 1.2 DNA methylation as biomarker for cancer detection The DNA methylation machinery is a crucial regulator of gene expression and essential for normal tissue development and homeostasis. The reversible nature of DNA methylation allows dynamic changes during embryonic development and the generation of tissue-specific methylation marks (17). Examples of fundamental processes in which DNA methylation is involved include the repression of repetitive elements, inactivation of one copy of the X-chromosome in females, and the silencing of gene transcription (17, 18). Exposure to chemical compounds (e.g. tobacco smoke) or normal physiological processes (e.g. aging) can also alter DNA methylation levels (19, 20). 1

12 Chapter 1 Cancer cells exhibit abnormal methylation patterns, which can drive malignant transformation. Global hypomethylation along the genome contributes to genomic instability (16), while focal hypermethylation is associated with gene promoters and leads to the silencing of genes involved in tumor suppression (15). DNA methylation changes are already observed during the most early phases of carcinogenesis and are therefore attractive for early cancer detection (15, 16). It has been shown that DNA methylation markers even allow the detection of precancerous lesions of the anus (21), cervix (22), colon (23), oral cavity (24), and vulva (25). The work described in this thesis focuses on promoter hypermethylation of cancerrelated genes as biomarkers for cancer detection (Figure 1). DNA methylation involves a chemical reaction in which a methyl group (CH3) is attached to the cytosine base of the DNA. This covalent transfer is mediated by the DNA methyltransferase (DNMT) enzyme family and produces 5-methylcytosine. Methylation of the cytosine base occurs exclusively in CG-rich regions, also referred to as CpG islands. CpG islands are found in the promoter regions of many genes, including those associated with tumor suppression, referred to as tumor suppressor genes (26). Me Me Me Inactive Me Methylated CpG Unmethylated CpG Active NH2 N N O cytosine N NH2 CH3 N O 5-methylcytosine DNMT Hypermethylation at gene promoters Loss of tumor suppressor gene function Figure 1: Gene inactivation by DNA methylation. Gene expression can be silenced by hypermethylation of the promoter region, rendering tumor suppressor genes inactive. During DNA methylation, a methyl group (CH3) is added to the cytosine base by DNA methyltransferases (DNMTs) at CG-rich regions, known as CpG islands. Created with BioRender.com.

13 General introduction Methylated DNA remains stable after long-term storage of clinical samples and can be analyzed efficiently using relatively inexpensive methods (27, 28). Bisulfite modification of the DNA is a fundamental first step of many methylation detection workflows. By treating the extracted DNA with sodium bisulfite, methylated cytosine can be distinguished from unmethylated cytosine by selective deamination of unmethylated cytosine to uracil. Methylation levels of a specific target region can be measured precisely using a quantitative methylation-specific PCR reaction (qMSP). Methylationspecific primers only amplify methylated cytosine-containing regions, which provides a highly sensitive quantification of methylated DNA in an excess of unmethylated DNA (29, 30). Methylation analysis does not require the presence of intact tumor cells for interpretation and can also be performed on fragmented DNA that has been shed by tumors (27). This offers opportunities for methylation testing in different types of patient material (e.g. tissue and liquid biopsies). 1.3 Cell-free DNA biology Both normal and tumor cells release nucleic acids, including cell-free DNA (cfDNA), into the circulation. Although the exact origin of cfDNA in the circulation is still under debate, proposed release mechanisms include apoptotic or necrotic cell death and active secretion (31). The presence of extracellular DNA was first described by Mandel and Métais in 1948 (32). This finding remained largely unnoticed by scientists until it was related to lupus disease in 1966 (33). Toward the end of the century, the discovery of fetal DNA in maternal blood (34), cancer-derived genetic mutations (35, 36), and aberrant promoter hypermethylation of tumor suppressor genes (37, 38) in serum and plasma followed. In the past decades, there has been a steep increase in research on the molecular profiling of cfDNA derived from tumor cells, referred to as tumor-derived cfDNA, for diagnostic purposes. Tumor-derived cfDNA accurately reflects molecular alterations in the tumor tissue (39, 40) and has high potential for non-invasive cancer detection (41). Molecular analysis of tumor-derived cfDNA allows the identification of a variety of biomarkers, including, but not limited to, copy number changes, differences in fragment lengths, fusion genes, methylation, and mutations (42, 43). The specific biological properties of cfDNA are related to its origin. The size of small cfDNA fragments in the circulation varies from 140 to 170 base pairs and peaks around 167 base pairs. This size is characteristic of the length needed to wrap DNA around a histone protein (147 base pairs), forming a mono-nucleosome, and the presence of a linker DNA (20 base pairs) which protects DNA from degradation (44-46). In healthy individuals, the majority of cfDNA is derived from leukocytes (47). Generally, the amount of cfDNA in circulation is extremely low (0-100 ng/mL) but elevates under normal physiological conditions, such as exercise, and pathological conditions, such 1

14 Chapter 1 as inflammation, tissue trauma, and cancer (48). The abundance of tumor-derived DNA in the blood of cancer patients is described to be highly variable (0.01-90% of total cfDNA) and differs per tumor type and stage, depending on tumor localization and vascularization (49, 50). The presence of cfDNA is also largely determined by degradation and clearance rates (51). The described half-life of cfDNA ranges from 16 minutes to 2.5 hours (52). During the last decades, several routes of cfDNA clearance have been proposed. Yet, the exact underlying mechanisms remain elusive as this complex process involves multiple filtering organs. It is thought that the majority (71-85%) of nucleosomes are removed from circulation by the liver (53), followed by transrenal glomerular excretion and absorption in the spleen (54, 55). Enzymes that degrade DNA, known as deoxyribonucleases, play a role in generating cfDNA during cell death and clearing cfDNA in the bloodstream (56). The cfDNA release and clearance mechanisms are summarized in Figure 2. Apoptosis Necrosis Active secretion Cell-free DNA release Cell-free DNA clearance Liver Kidneys Extracellular vesicle White blood cell Red blood cell Platelet Tumor cell Normal cell-free DNA Tumor cell-free DNA Nucleosome Deoxyribonucleases Spleen Figure 2: Cell-free DNA release and clearance mechanisms. Normal and tumor-derived cell-free DNA is released into the bloodstream by cell death (apoptosis or necrosis) and active secretion. Cell-free DNA is cleared from the circulation by absorption in the liver and spleen, transrenal excretion through the kidneys, and nuclease digestion by deoxyribonucleases. Created with BioRender.com. Transrenal excretion of cfDNA was first described by Botezatu and colleagues in 2000 (57). In this pioneer study, human DNA and radioactively labeled DNA were injected in mice and both were detected in the urine. They also described the presence of Y-chromosomal DNA in the urine of women carrying a male fetus and women who were transfused with blood from a male donor. Furthermore, KRAS gene mutations were detected in the urine of patients diagnosed with colorectal cancer whose tissue

15 General introduction biopsies showed the same mutations (57). The presence of tumor-derived DNA in the urine offers opportunities for urine-based cancer detection (58). 1.4 Urine as a liquid biopsy Urine is a relatively new liquid biopsy as compared to blood. Even though blood-based cancer detection methods have shown high clinical potential, particularly for their use in diagnostics and treatment response monitoring (59, 60), this method comes with several drawbacks. The collection of blood mostly requires in-person visits and is usually performed by a specialist. Moreover, only limited amounts of blood can be collected per time point. Urine, on the other hand, is truly non-invasive and can be collected easily, repeatedly, and in large volumes without pain or discomfort. The noninvasive nature of urine sampling allows for self-collection at home with high patient acceptance (61). Urine is a dynamic fluid that consists of a variety of components (Figure 3). Nucleic acids found in the urine can be broadly classified into a high and low molecular weight group. The high molecular weight DNA (≥1 kb in size) is derived from cellular debris, such as immune cells and exfoliated cells from the genital tract or distal urethra (62). The low molecular weight DNA (10-250 bp in size) comprises small transrenally excreted fragments (63). Full void urine contains both high and low molecular weight DNA, which can be divided by separating the urine into two fractions: the urine sediment and the urine supernatant. The urine supernatant is enriched for cfDNA (low molecular weight DNA), while the urine sediment mostly contains cellular debris (high molecular weight DNA). The most optimal urine fraction may depend on the location of the tumor. For example, the urine sediment was shown to be most optimal for detecting bladder and cervical cancer, as this fraction most likely contains the highest yield of exfoliated cancer cells (64, 65). Urine has been primarily explored as a liquid biopsy for urogenital cancer types that directly release DNA fragments into the urine, including bladder and cervical cancer (22, 65-70). In recent years, there has been growing interest in the detection of nonurogenital cancers in urine in which direct shedding is unlikely (62, 71). The transrenal excretion of tumor-derived cfDNA offers opportunities for the detection of virtually any cancer type that releases cfDNA into the bloodstream (57). Even for cancer types close to the bladder and urethra (i.e. bladder and cervical cancer), both locally and transrenally released tumor-derived (cf)DNA add to the total bulk of DNA in the urine (72). Hence, urine holds the potential to become a universal tool to diagnose and monitor various cancer types (71). 1

16 Chapter 1 Transrenal excretion of cfDNA Local shedding of cell fragments Tumor cell Normal cell-free DNA Tumor cell-free DNA Normal cell Full void urine Urine sediment Urine supernatant Low molecular weight DNA High molecular weight DNA Figure 3: Urine as a liquid biopsy for cancer detection. Urine consists of different components, including normal and tumor-derived cell-free DNA and cellular debris from both normal and tumor cells. Cell-free DNA is transported into the urine by transrenal excretion. The anatomical position of the cervix and bladder allows the local shedding of cells and DNA into the urine. Created with BioRender.com. 1.5 Urine-based biomarker testing to address clinical challenges of different cancer types Given the advantages of urine collection, urine-based tests could address a wide range of clinical challenges in cancer management. Patient-friendly testing has been developed and evaluated for the accurate detection of cervical (pre)cancer in urine and cervicovaginal self-samples (22, 70). Yet, the application of urine and cervicovaginal self-samples for the detection of other gynecological cancers, including endometrial and ovarian cancer, has remained underexplored. Furthermore, although detecting non-urogenital tract cancer types in urine is appealing, this has only been examined by a limited number of studies (8). The use of urine for lung cancer detection has been described previously but focused on late-stage disease (73, 74). The feasibility of detecting early-stage lung cancer in urine, which is clinically most relevant, is largely unknown. The cancer types examined in this thesis originate from different sites of the human body and have distinct clinical challenges, which are described in the subsections below (Figure 4).

17 General introduction Ovarian cancer Late-stage presentation and difficulty in distinguishing between benign and malignant ovarian masses Lung cancer Late-stage presentation and high false positive rates during lowdose CT screening of high-risk individuals Endometrial cancer Rising incidence and many unnecessary invasive procedures for women presenting with abnormal bleeding symptoms Figure 4: Clinical challenges of cancer types for which patient-friendly biomarker testing was evaluated in this thesis. Schematic illustration of the anatomical location and short description of clinical challenges of endometrial, ovarian, and lung cancer. Created with BioRender.com. 1.5.1 Endometrial cancer Endometrial cancer or uterine cancer is the most frequently diagnosed gynecological cancer in developed countries with a rising incidence worldwide, accounting for 417,000 new diagnoses and over 97,000 deaths in 2020 (75). This gynecological malignancy arises from the inner lining of the uterus, known as the endometrium, and typically occurs in postmenopausal women (76). Women with Lynch syndrome, also known as hereditary nonpolyposis colorectal cancer syndrome, have an increased lifetime risk of endometrial cancer (77). Endometrial cancer comprises a heterogeneous range of subtypes with diverse histological and molecular features. The majority of endometrial cancers (~80%) are low-grade endometrioid with a generally good prognosis. The remaining high-grade tumors, including grade 3 endometrioid and non-endometrioid tumors (serous, clear cell, and mixed adenocarcinomas, and carcinosarcomas), have a poor prognosis due to their aggressive growth pattern and higher risk of metastasis (76). Endometrial cancer is diagnosed by invasive procedures, in which a pipelle biopsy is performed by a specialist when a thickened endometrium is observed (78). In some inconclusive cases, a hysteroscopy (i.e. visual examination of the inside of the uterus with a hysteroscope to obtain a tissue specimen) is required for a final diagnosis. Fortunately, endometrial cancer is often detected at an early-stage due to the presence of abnormal postmenopausal bleeding symptoms. Nevertheless, only a minority (~9%) of women experience these symptoms due to malignancy (79). The low specificity (~52%) of ultrasound measurements for endometrial thickness results in a substantial number of women without cancer undergoing unnecessary invasive clinical examinations to rule out malignancy (80). Moreover, women at increased risk for endometrial cancer, including women with Lynch syndrome, repeatedly undergo clinical examinations to rule 1

18 Chapter 1 out cancer. Biomarker testing in patient-friendly material could aid the triage of women presenting with postmenopausal blood loss, guide screening for primary endometrial cancer in high-risk women, and help monitor for recurrent endometrial cancer. 1.5.2 Ovarian cancer Ovarian cancer is the most deadly gynecological cancer worldwide, with 314,000 new diagnoses and over 207,000 deaths in 2020 (75). This cancer is known as a ‘silent killer’ as it often remains unnoticed until the disease has reached an advanced and incurable stage. Women with germline mutations like Lynch syndrome and BRCA1/2 have an increased lifetime risk of ovarian cancer (81). While endometrial cancers are mostly low-grade, the majority of ovarian cancers are high-grade. The most common histological subtype of ovarian cancer (~70-80%) is epithelial high-grade serous ovarian cancer, which is believed to originate from the fallopian tube (82). Women typically present with late-stage ovarian cancer when prognosis is poor and there are currently no effective screening or early detection methods (83). Pre-operative risk assessment to determine whether an ovarian mass is benign or (pre)malignant consists of radiographic imaging of the ovarian mass and a serum CA-125 measurement. The preoperative differentiation between benign and malignant ovarian masses is challenging using current diagnostic methods. More accurate methods are warranted to detect ovarian cancer early and to preoperatively differentiate between benign and malignant ovarian masses to streamline specialist referral. 1.5.3 Lung cancer Lung cancer accounts for the highest mortality rate globally, with an estimated number of 1,8 million deaths in 2020 (75). The majority of lung cancer cases are associated with tobacco use. Lung cancer originates from the cells of the respiratory epithelium and is divided into two main subtypes, small cell lung cancer (~15% of cases) and non-small cell lung cancer (NSCLC; ~85% of cases) (84). Despite advancements in the therapeutic landscape of NSCLC, mortality rates remain high. The majority of advanced NSCLC patients lack oncogenic alterations suitable for targeted treatment and only a minority of patients (~20%) respond to immunotherapy (85). With stage at diagnosis as most important prognostic factor, early detection is critical for treatment with curative intent. Therefore, large screening trials were initiated to address the value of low-dose computed tomography (LDCT) for lung cancer detection in high-risk groups (86-89). Although effective in detecting lung cancer at an earlier stage, a high number of false positives (96%) was observed resulting in unnecessary diagnostic work-up and loss of cost-effectiveness (89). Novel diagnostic tools are needed to manage positive LDCT screening outcomes and decrease false positive rates.

19 General introduction Lung cancer is currently diagnosed by conventional imaging and biopsy procedures. When a suspected nodule is observed during imaging, a biopsy is performed for further characterization by bronchoscopy, radiologically guided transthoracic needle biopsy, or a linear endobronchial ultrasound with transbronchial needle aspiration (EBUS-TBNA) (90). Procedures used for lung cancer diagnostics are expensive and susceptible to complications (91). Localization and size of the nodule are important determinants for the collection of sufficient lung tissue for diagnosis. In some cases, repeated sampling is required which may lead to delays in treatment initiation (92). Liquid biopsy has already entered lung cancer diagnostics to overcome tissue sampling issues. This FDA-approved plasma-based test for EGFR mutations showed high concordance with tissue (93) and highlights the promising potential of molecular testing in liquid biopsies when tissue availability is limited (94). 1.6 Thesis rationale and outline The overall objective of this thesis is to develop patient-friendly cancer detection methods to advance cancer diagnostics by focusing on DNA methylation analysis in urine for the detection of endometrial, ovarian, and lung cancer. For endometrial and ovarian cancer, also alternative patient-friendly sampling methods are assessed, including self-collected cervicovaginal samples and clinician-taken cervical scrapes (Figure 5). Cervicovaginal self-sample Clinician-taken cervical scrape Urine Label Figure 5: Patient-friendly sample types investigated in this thesis: urine, cervicovaginal selfsamples, and clinician-taken cervical scrapes. Created with BioRender.com. 1

20 Chapter 1 In Part 1 of this thesis, the potential of detecting endometrial and ovarian cancer in patient-friendly samples is described. In Chapter 2, the feasibility of endometrial cancer detection in urine is evaluated by testing three methylation markers in different urine fractions. In Chapter 3, a systematic review of the literature is performed to select which methylation markers for endometrial cancer detection in patient-friendly sample types deserve further development. In Chapter 4, nine methylation markers, retrieved from Chapters 2 and 3, are tested for endometrial cancer detection in paired urine, cervicovaginal self-samples, and clinician-taken cervical scrapes to comprehensively determine and compare their performance in different patient-friendly sample types. In Chapter 5, the use of patient-friendly samples for ovarian cancer detection is explored using different molecular analyses. Nine methylation markers are analyzed in urine, cervicovaginal self-samples, and clinician-taken cervical scrapes. Additionally, copy number aberrations and cfDNA fragmentation patterns are analyzed in the urine of ovarian cancer patients. In Part 2 of this thesis, the applicability of urine for the detection of non-small cell lung cancer (NSCLC) is evaluated. In Chapter 6, three methylation markers are tested to explore the use of urine for the detection of non-metastatic primary and recurrent NSCLC. For successful clinical implementation, it is essential to explore the day-today and within-days variation in urine cfDNA measurements to fully comprehend its potential as a diagnostic tool. Therefore, in Chapter 7, the dynamics of methylated cfDNA in patients with advanced stage NSCLC are investigated to determine whether a preferred collection time and frequency exists. The outcomes of this thesis contribute to a new era of patient-friendly solutions for cancer detection that can be widely implemented in future clinical practice.

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25 General introduction 69. Hentschel AE, Beijert IJ, Bosschieter J, Kauer PC, Vis AN, Lissenberg-Witte BI, et al. Bladder cancer detection in urine using DNA methylation markers: a technical and prospective preclinical validation. Clinical Epigenetics. 2022;14(1):19. 70. Van Keer S, van Splunter AP, Pattyn J, De Smet A, Herzog SA, Van Ostade X, et al. Triage of human papillomavirus infected women by methylation analysis in first-void urine. Scientific Reports. 2021;11(1):7862. 71. Jordaens S, Zwaenepoel K, Tjalma W, Deben C, Beyers K, Vankerckhoven V, et al. Urine biomarkers in cancer detection: A systematic review of preanalytical parameters and applied methods. International Journal of Cancer. 2023;n/a(n/a). 72. Hentschel AE, van den Helder R, van Trommel NE, van Splunter AP, van Boerdonk RAA, van Gent M, et al. The Origin of Tumor DNA in Urine of Urogenital Cancer Patients: Local Shedding and Transrenal Excretion. Cancers (Basel). 2021;13(3). 73. Reckamp KL, Melnikova VO, Karlovich C, Sequist LV, Camidge DR, Wakelee H, et al. A Highly Sensitive and Quantitative Test Platform for Detection of NSCLC EGFR Mutations in Urine and Plasma. J Thorac Oncol. 2016;11(10):1690-700. 74. Wang X, Meng Q, Wang C, Li F, Zhu Z, Liu S, et al. Investigation of transrenal KRAS mutation in late stage NSCLC patients correlates to disease progression. Biomarkers. 2017;22(7):654-60. 75. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209-49. 76. Morice P, Leary A, Creutzberg C, Abu-Rustum N, Darai E. Endometrial cancer. The Lancet. 2016;387(10023):1094-108. 77. Stoffel E, Mukherjee B, Raymond VM, Tayob N, Kastrinos F, Sparr J, et al. Calculation of risk of colorectal and endometrial cancer among patients with Lynch syndrome. Gastroenterology. 2009;137(5):1621-7. 78. Burke WM, Orr J, Leitao M, Salom E, Gehrig P, Olawaiye AB, et al. Endometrial cancer: a review and current management strategies: part II. Gynecologic oncology. 2014;134(2):393402. 79. Clarke MA, Long BJ, Del Mar Morillo A, Arbyn M, Bakkum-Gamez JN, Wentzensen N. Association of Endometrial Cancer Risk With Postmenopausal Bleeding in Women: A Systematic Review and Meta-analysis. JAMA Intern Med. 2018;178(9):1210-22. 80. Crosbie EJ, Kitson SJ, McAlpine JN, Mukhopadhyay A, Powell ME, Singh N. Endometrial cancer. The Lancet. 2022;399(10333):1412-28. 81. Whelan E, Kalliala I, Semertzidou A, Raglan O, Bowden S, Kechagias K, et al. Risk Factors for Ovarian Cancer: An Umbrella Review of the Literature. Cancers. 2022;14(11):2708. 82. Kyo S, Ishikawa N, Nakamura K, Nakayama K. The fallopian tube as origin of ovarian cancer: Change of diagnostic and preventive strategies. Cancer Medicine. 2020;9(2):421-31. 83. Liberto JM, Chen SY, Shih IM, Wang TH, Wang TL, Pisanic TR, 2nd. Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review. Cancers (Basel). 2022;14(12). 84. Schabath MB, Cote ML. Cancer Progress and Priorities: Lung Cancer. Cancer Epidemiology, Biomarkers & Prevention. 2019;28(10):1563-79. 1

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27 General introduction 1

PART 1 ENDOMETRIAL AND OVARIAN CANCER DETECTION IN PATIENT-FRIENDLY SAMPLES

CHAPTER 2 NON-INVASIVE DETECTION OF ENDOMETRIAL CANCER BY DNA METHYLATION ANALYSIS IN URINE Published as: van den Helder, R., Wever, B.M.M., van Trommel, N.E., van Splunter, A.P., Bleeker, M.C.G., Steenbergen, R.D.M. (2020). Non-Invasive Detection of Endometrial Cancer by Methylation Analysis in Urine. Clinical Epigenetics. 12, 1, p. 165.

32 Chapter 2 ABSTRACT Background The incidence of endometrial cancer is rising, and current diagnostics often require invasive biopsy procedures. Urine may offer an alternative sample type, which is easily accessible and allows repetitive self-sampling at home. Here, we set out to investigate the feasibility of endometrial cancer detection in urine using DNA methylation analysis. Results Urine samples of endometrial cancer patients (n = 42) and healthy controls (n = 46) were separated into three fractions (full void urine, urine sediment, and urine supernatant) and tested for three DNA methylation markers (GHSR, SST, ZIC1). Strong to very strong correlations (r = 0.77 – 0.92) were found amongst the different urine fractions. All DNA methylation markers showed increased methylation levels in patients as compared to controls, in all urine fractions. The highest diagnostic potential for endometrial cancer detection in urine was found in full void urine, with area under the receiver operating characteristic curve values ranging from 0.86 to 0.95. Conclusions This feasibility study demonstrates, for the first time, that DNA methylation analysis in urine could provide a non-invasive alternative for the detection of endometrial cancer. Further investigation is warranted to validate its clinical usefulness. Potential applications of this diagnostic approach include the screening of asymptomatic women, triaging women with postmenopausal bleeding symptoms, and monitoring women with increased endometrial cancer risk.

33 Non-invasive detection of endometrial cancer by DNA methylation analysis in urine BACKGROUND Endometrial cancer (EC) is the most common gynecological cancer in developed countries and the sixth most common cancer worldwide (1). Its incidence is rising globally (2) with over 380,000 new cases and 89,929 deaths reported in 2018 (3). The increasing incidence of EC is partly attributable to the rise in the prevalence of risk factors associated with EC development, like obesity (4, 5). Despite the rising incidence of EC and proven value of early diagnosis, no screening program for EC exists (6, 7). In addition, if EC is suspected, invasive biopsy procedures remain necessary in routine clinical practice to detect EC in symptomatic women. Besides, the opportunity to detect EC in asymptomatic women by cytological evaluation of cervical scrapes during cervical cancer screening programs will be missed by the transition toward a primary high-risk human papillomavirus screening approach in many countries. Hence, there is a need to detect EC using less invasive sampling methods, combined with the analysis of cancer-specific markers (6). One of the emerging biomarkers for early cancer detection is DNA methylation, which involves the addition of a methyl group to a cytosine-guanine dinucleotide (CpG). Altered DNA methylation is a common epigenetic event that occurs during the early stages of carcinogenesis of many cancer types, including EC, and has been linked to gene silencing of tumor suppressor genes. Testing for elevated DNA methylation levels of specific genes is promising in early cancer detection (8). Previous studies have shown that aberrant EC-specific DNA methylation signatures can be measured in various minimally-invasive sample types, including cervical scrapes (912), endometrial brushes (13), vaginal swabs (14, 15) and vaginal tampons (16, 17). The ability to detect EC in cervicovaginal samples implicates shedding of endometrial cells and cell fragments into the lower genital tract, and, potentially, also into the urine. Apart from cellular tumor DNA, tumor-derived DNA can be released into the bloodstream as cell free DNA (cfDNA) and pass to the urine by filtration through transrenal excretion (18, 19). The suitability of EC detection in urine has been supported by the presence of EC-specific micro-RNAs in urine (20, 21). The measurement of DNA methylation markers in urine, has been proven useful for the detection of cervical cancer (22, 23), as well as other cancers, including bladder (24-27), lung (28), and prostate cancer (29-32). However, to the best of our knowledge, no such approach has been investigated for the detection of EC. 2

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