Identification of biomarkers of metastatic disease in uveal melanoma using proteomic analyses Thesis submitted in accordance with the requirements of the University of Liverpool for the degree of Doctor in Philosophy Martina Angi June 2015 To Mario, the wind beneath my wings 2 Acknowledgments First and foremost, I would like to acknowledge my primary supervisor, Prof. Sarah Coupland, for encouraging me to undergo a PhD and for supporting me in this long journey. I am truly grateful to Dr Helen Kalirai for being the person I could always turn to, for a word of advice on cell culture as much as on parenting skills. I would also like to acknowledge Prof. Bertil Damato for being an inspiration and a mentor; and Dr Sarah Lake and Dr Joseph Slupsky for their precious advice. I would like to thank Dawn, Haleh, Fidan and Fatima for becoming my family away from home, and the other members of the LOORG for the fruitful discussions and lovely cakes. I would like to acknowledge Prof. Heinrich Heimann and the clinical team at LOOC, especially Sisters Hebbar, Johnston, Hachuela and Kaye, for their admirable dedication to UM patients and for their invaluable support to clinical research. I would also like to thank the members of staff in St Paul’s theatre and Simon Biddolph and Anna Ikin in Pathology for their precious help in sample collection. I am grateful to Dr Rosalind Jenkins who guided my first steps in the mysterious word of proteomics, and to Dr Deb Simpsons and Prof. Rob Beynon for showing me its beauty. I am truly grateful to my parents for always supporting and believing in me, and to my sister Giulia for always being there for me. I am also very grateful to my husband Mario for the sacrifice of being apart in these years, and to Lucia and Ferdinando for having given a completely different meaning to our life. Finally, I would like to gratefully acknowledge Cancer Research UK for funding the Clinical Research Training Fellowship that lead to this PhD. 3 Abstract Uveal melanoma (UM) is the most common intraocular malignancy in adults. Despite successful ocular treatment, about 50% of patients succumb to metastatic dissemination, which occurs haematogenously and mainly affects the liver. On the basis of clinical, histopathological and genetic features of the primary tumour it is possible to predict if the individual patient is at high risk (HR) or low risk (LR) of developing metastases. However, the mechanisms responsible for the development of metastatic disease in UM are still largely unknown; therefore no adjuvant treatment is currently offered to HR patients to prevent development of fatal disease. As the time to discovery of clinically detectable metastases can range from months to decades, a secreted biomarker(s) that could be routinely tested in blood is much needed. The scope of the work presented in this thesis was to use proteomics as a tool to identify potential novel, UM-specific biomarkers. Moreover, the proteomic data acquired would complement genomic and transcriptomic information already generated by the Liverpool Ocular Oncology Research Group, with the ultimate aim of increasing our understanding of UM development and dissemination. The aim of Chapter 2’s project was to compare the proteome of UM tissue samples at HR versus LR of developing metastatic disease using isobaric tags for relative and absolute quantitation (iTRAQ) labelling and mass spectrometry (MS). The quantification of proteins in our samples, proteomic analysis and further validation by immunohistochemistry has led to the identification of two novel prognostic and potentially therapeutic target, S100A6 and the tumour suppressor PDCD4. In Chapter 3 we focused on proteins released in the conditioned medium (secretome) of short-term cultures of HR and LR UM cells, as well as normal melanocytes. Using a label-free quantitative proteomic approach, almost 2000 proteins were identified and quantified, with more than 30% of these identified as secreted and/or previously described in exosomes. Using these data, an 18-protein signature able to discriminate between HR and LR UM was identified. Further validation will be necessary in secretome samples and in the peripheral blood of UM patients, but this has the potential of being translated into a clinically useful assay to detect early development of metastatic disease. As reported in Chapter 4, we also conducted a pilot clinical study on circulating tumour cells (CTC) in UM, using the CellSearch® platform with the novel melanoma kit to enumerate CTC in the peripheral blood of UM patients at LR, HR or with overt metastatic disease. CTC were detected in metastatic and HR tumours and were not present in LR UM, however, the number of CTC detected varied widely, calling into question the clinical value of using this platform in UM patients. The research detailed in Chapter 5 had a direct clinical value, as it addressed the procedures undertaken during the acquisition and processing of prognostic biopsies from UM tumours treated conservatively. The modifications introduced led to a significant improvement of the success rate of such prognostic biopsies for risk stratification, which is essential for clinical management, follow-up and research purposes. In conclusion, the work conducted throughout this PhD has provided further insight into the molecular characteristics that can differentiate between HR and LR UM, identifying novel potential biomarkers that will need validation in the clinical setting. 4 Table of contents Dedication…………...……………………………………………………………………………..................2 Acknowledgments ................................................................................................ 3 Abstract ................................................................................................................ 4 Table of contents .................................................................................................. 5 List of abbreviations ............................................................................................. 9 List of publications .............................................................................................. 12 List of poster and oral presentations ................................................................... 13 Chapter 1 General introduction ........................................................................ 15 1.1 Uveal melanoma ............................................................................................... 16 1.1.1 Incidence and risk factors ................................................................................ 16 1.1.2 Anatomical considerations and clinical features ............................................. 17 1.1.3 Diagnosis and treatment ................................................................................. 20 1.1.4 Metastatic dissemination of UM ..................................................................... 24 1.1.5 Personalised prognostication in UM ................................................................ 27 1.1.6 Detection and treatment of metastatic UM .................................................... 34 1.1.7 The need for novel biomarkers ........................................................................ 38 1.2 Proteomics ........................................................................................................ 39 1.2.1 Proteomics workflow ....................................................................................... 39 1.2.2 Previous proteomics studies in UM ................................................................. 47 1.3 Scope and outline of tHis tHesis ......................................................................... 52 5 Chapter 2 Quantitative proteomic analysis of uveal melanoma tumour tissue . 54 2.1 Introduction ...................................................................................................... 55 2.1.1 iTRAQ ............................................................................................................... 57 2.2 MetHods ........................................................................................................... 59 2.2.1 Sample preparation ......................................................................................... 59 2.2.2 iTRAQ labelling ................................................................................................. 61 2.2.3 MS analysis ...................................................................................................... 62 2.2.4 Data analysis .................................................................................................... 64 2.2.5 Immunohistochemical analysis ........................................................................ 65 2.3 Results .............................................................................................................. 69 2.3.1 Characteristics of used tumour and choroid samples ..................................... 69 2.3.2 iTRAQ results ................................................................................................... 71 2.3.3 Protein identification ....................................................................................... 71 2.3.4 Protein expression in tissue sections ............................................................... 76 2.3.5 Validation of PDCD4 and S100A6 expression in an independent cohort of primary UM tissues ...................................................................................................... 78 2.4