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Discovery and Validation of Biomarkers in Breast Cancer by Nina Gran Egeland Thesis submitted in fulfilment of the requirements for the degree of PHILOSOPHIAE DOCTOR (PhD) Faculty of Science and Technology Department of Chemistry, Bioscience and Environmental Engineering 2020 University of Stavanger NO-4036 Stavanger NORWAY www.uis.no ©2020 Nina Gran Egeland ISBN: 978-82-7644-953-2 ISSN: 1890-1387 PhD: Thesis UiS No. 546 Scientific Environment The present PhD-project was conducted in its entirety at the Department of Pathology, Stavanger University Hospital, Stavanger, Norway. In affiliation with the Department of Chemistry, Bioscience and Environmental Engineering, Faculty of Science and Technology, University of Stavanger, Stavanger, Norway. Supported by generous grants from the Folke Hermansen Foundation, in 2013 and 2019. Acknowledgements Acknowledgements First and foremost, I would like to express my deepest gratitude to my main supervisor Professor Emiel Janssen. Ever since I knocked on your door in search for employment in 2012, you have supported and motivated me throughout this long journey. I admire your vast knowledge and insight in the complex world of breast cancer research and pathology. You are an inspiration to me, I highly respect your professional competence, and I could not have hoped for a better mentor. But most importantly, I will never forget your understanding, kindness and compassion after I fell ill, and how you kindly encouraged me to complete this thesis thereafter. I am forever grateful. The best boss in the world! To my committed co-supervisor Kristin Jonsdottir, who equally appreciate the utmost importance of accuracy in formatting, straight lines, and symmetry in powerpoints and word-documents. You have included me in your work since day one, taught me valuable skills in the laboratory and I have learned so much from you! Thank you for countless meetings of more or less academic character, for all the coffees and chocolate, your support, our walks, and for being a dear friend. You are such a generous person, and I truly value our friendship. Thank you to the Folke Hermansen Foundation for generously financing this PhD thesis, and to the Department of Pathology and the Research Department for allowing me the time and opportunity to fulfil this work. To my co-supervisor Deirdre Cronin-Fenton in Århus, thank you for our nice collaboration and for your patience with this thesis, for putting up with endless e-mails of draft revisions, and for all the valuable intellectual input. I admire your knowledge in clinical epidemiology. I would also like to thank Kristina Lauridsen for being an invaluable support whilst figuring out the TMAs and the quirks of Visiopharm, and vii Acknowledgements Cathrine Hjorth and Anders Kjærsgaard for all your help with the statistics. I am indebted to all my talented co-authors in general, both at SUS, in Oslo, Denmark, and the US. Especially Siri Lunde with whom I wrote my very first article on breast cancer, and who has been a good friend and support ever since. I am grateful to Marie Austdal and Einar Gudlaugsson for sharing their expertise and knowledge. A warm thanks to Professor Håvard Søiland for your positivity, enthusiasm and support. To all my dear past and present co-workers at the Department of Pathology and at the laboratory at Hillevåg, thank you for creating such an including and supportive work environment over the years. A special thanks to Bianca Van-Diermen Hidle, who were my witty go-to-lady whenever I was at a loss up at the department; you are truly missed. Special thanks also to Melinda Lillesand and Emma Rewcastle, who together with Bianca has cut countless of slides for me, helped me with the whimsical scanner, and offered many welcomed coffee breaks. Thank you to my wonderful long-time office-mate Aida Johannesen, to Irene Øvestad for sharing the unavoidable lab frustrations, to Kjersti Tjensvoll and Satu Oltedal for all the good advice, to Eliza Janssen for all administrative help, and to Ivar Skaland for excellent technical guidance on the DIA algorithms. Thank you also to my former colleague Hanne Hagland and fellow current and former PhD-students Dordi Lea, Martin Watson and Tone Lende for all your helpful tips, practical help and encouragements. To all the other clever people of Dept. of Path. and at Hillevåg; thank you for all your technical and practical assistance and for being such pleasant colleagues. Moreover, to all the skilful clinicians and members of the breast cancer research group FFB; your commitment to your patients are admirable; thank you for inspiring me with your impressive knowledge. My appreciation extends to all my new co-workers at the Department of Breast and Endocrine Surgery; thank you for welcoming me and v Acknowledgements including me in your enjoyable work environment. Janne Jonassen; it is a true delight to share an office with you, I especially appreciate your sense of humour and exceptional organizational skills, and I look forward to continue working with you. I would also like to take this opportunity to acknowledge all the past, present and future breast cancer patients, without whom there would be no reason or material to research; you are the true motivation for continuing this work. Thank you to all my good friends and my lovely big family for all your love and support, and for taking my mind off work and brightening my life. I look forward to spending more time with you all. Last but not least, to my best friend and dearest husband Ole, without whom this thesis would never have been completed. Thank you for believing in me and supporting me when I myself was close to giving up and tempted to toss this entire thesis out of the window. You and our two little girls have brought me so much happiness and joy, and the three of you are my healthy reminder that there is so much more to life than work. I dedicate this thesis to my beloved daughters, Eirill and Åsta. Nina Gran Egeland _________________________________________________________ In honour of my aunt Reidun vi Abbreviations Abbreviations AI aromatase inhibitor APP analysis protocol package BCT breast-conserving treatment BRCA1/2 breast cancer type 1/2 susceptibility protein CD cluster of differentiation CIBERSORT Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts CIS cancer in situ CISH chromogenic in situ hybridization DBCG Danish Breast Cancer Group DIA digital image analysis DIG digoxigenin DNA deoxyribonucleic acid EBCTCG Early Breast Cancer Trialists’ Collaborative Group ECM extracellular matrix EMT epithelial-mesenchymal transition ERBB2 erb-B2 receptor tyrosine kinase ER oestrogen receptor FFPE formalin-fixed paraffin-embedded HER2 human epidermal growth factor-like receptor 2 IHC immunohistochemistry LN lymph node vii Abbreviations LNA™ locked nucleic acid™ MAI mitotic activity index MARCKLS1 myristoylated alanine-rich C kinase substrate like-1 miRNA microRNA mRNA messenger RNA NBCG Norwegian Breast Cancer Group NGS next-generation sequencing NST no special type PPH3 phosphohistone H3 PR progesterone receptor RNA ribonucleic acid ROI region of interest RT-qPCR reverse transcription quantitative polymerase chain reaction TDLU terminal ductal lobular unit TIL tumour-infiltrating lymphocyte TMA tissue microarray TME tumour microenvironment TNBC triple-negative breast cancer TNM tumour – node – metastasis VEGF vascular endothelial growth factor WS whole-slide viii Summary Summary Worldwide, breast cancer is the most common malignancy among women, and although treatment and prognosis have improved substantially over the last decades, for some patients the risk of recurrence remains for several years following diagnosis. Meanwhile, many breast cancer patients receive systemic adjuvant treatment unnecessarily, since their tumours will never recur. Implicitly, these patients are being overtreated while others are being undertreated. The challenge is to identify patients with a higher risk of developing recurrences and metastasis, from those who do not need additional treatment. These women may be spared potential treatment-induced side effects. Breast cancer is a highly complex and very heterogeneous disease, displaying both inter- and intratumoural biological variation. To ensure correct diagnosis and treatment, we need more precise and improved biomarkers. Equally important as discovering new and better biomarkers is the validation of existing ones. The work described in this thesis focuses on the discovery of novel candidate biomarkers for breast cancer, but also emphasize the equally important value of validating existing ones. The first study examined the expression of the protein MARCKSL1 by immunohistochemistry. Increased expression of MARCKSL1 was previously associated with risk for metastasis and worse prognosis in breast cancer patients, especially in those with highly proliferating tumours. In this study, we set out to validate these findings. However, in ix Summary contrast to previous findings, MARCKSL1 protein expression was not prognostic in this independent patient cohort. In the search for novel prognostic and predictive biomarkers in breast cancer, microRNAs are now emerging as potential candidates. In previous studies, gene expression of miR-18a and miR-18b correlated with high proliferation and basal-like features of breast cancer. In the second study, we applied chromogenic in situ hybridization to investigate the in situ expression of these microRNAs in both ER+ and ER- tumours. Our findings revealed that miR-18a and miR-18b are specifically expressed in the stroma surrounding the tumour, especially in ER- breast tumours that present with a high degree of tumour infiltrating lymphocytes. Additional investigations suggested that the expression of these miRNAs might be associated with macrophages. Cell proliferation is a fundamental feature of cancer cells, and high proliferation correlates with a higher risk of recurrence and reduced survival in breast cancer. Ki-67 is a well-known marker for proliferation, but its use is controversial because of the lack of consensus regarding pre-analytical processing, optimal clinical cut-off value and a high degree of variability across laboratories.

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