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Proteomics Investigation of Breast Cancer Biomarkers in Urine and Blood for Diagnosis and Monitoring ______

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Proteomics Investigation of Breast Cancer Biomarkers in Urine and Blood for Diagnosis and Monitoring ______ PROTEOMICS INVESTIGATION OF BREAST CANCER BIOMARKERS IN URINE AND BLOOD FOR DIAGNOSIS AND MONITORING _______________________________________________________________________________________________ Julia Beretov BSc. Dip Med Sc., Dip Edu A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Faculty of Medicine St George and Sutherland Clinical School March 2016 ORIGINALITY STATEMENT I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged. Signed …………………………………………….............. Date ……………………………………………................. ii COPYRIGHT STATEMENT ‘I hereby grant the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstract International (this is applicable to doctoral theses only). I have either used no substantial portions of copyright material in my thesis or I have obtained permission to use copyright material; where permission has not been granted I have applied/will apply for a partial restriction of the digital copy of my thesis or dissertation.' Signed ……………………………………………........................... Date ……………………………………………........................... AUTHENTICITY STATEMENT ‘I certify that the Library deposit digital copy is a direct equivalent of the final officially approved version of my thesis. No emendation of content has occurred and if there are any minor variations in formatting, they are the result of the conversion to digital format.’ Signed ……………………………………………........................... Date ……………………………………………........................... ABSTRACT Breast cancer is a major world-wide health problem and is the most commonly diagnosed cancer amongst women in Australia and the world. Although the survival of patients has increased over the last two decades, due to improved screening programs and postoperative adjuvant systemic therapies (hormone therapy and chemotherapy), patients undergo aggressive treatment and many die from metastatic relapse. Whilst screening for early breast cancer detection using mammography and ultrasound is successful, it may provide a false negative result because of the density or architecture of breast tissue. Additionally, it cannot make a clear distinction of benign breast disease from malignancy. Furthermore, if breast cancer is detected at an early stage, when treatment is likely to be more effective, then more lives will be saved. Breast cancer is a heterogeneous disease, composed of distinct molecular subtypes associated with different clinical outcomes, and would benefit from the development of new disease-specific biomarkers. Current clinical and pathological parameters are not able to monitor breast cancer progression or accurately predict its prognosis. Presently, there are no biomarkers that can be used for early diagnosis and therefore there is an urgent need to identify novel breast cancer biomarkers to improve the early detection and monitor progression. The application of proteomics and high- throughput methods based on mass spectrometry (MS) of peptide or protein mixtures provides a large number of individual proteins. Advances in proteomics technology have allowed us to dig deeper into the human proteome, provide a new insight into cancer biology and allow for the discovery of novel biomarkers. Therefore, the main research objectives of this thesis were to conduct scientific investigation to 1) analyse biological samples including urine and blood, from breast cancer patients and control subjects using proteomics; 2) identify novel proteins or a panel of proteins which are associated with the presence of disease; 3) validate the identified potential biomarkers from urine and blood in breast cancer cell lines and primary breast cancer tissues for diagnosis. iii After successfully developing a standardised method for urine protein extraction and precipitation using liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis (detailed in Chapter 3), this method was applied to additional urine samples from breast cancer patients (Chapter 4). Proteomic analysis of urine to identify breast cancer biomarker candidates using a label-free LC-MS/MS approach, revealed 59 urinary proteins that were significantly different in breast cancer patients compared to the normal healthy control subjects (p<0.05, fold change >3). Thirty-six urinary proteins were exclusively found in specific breast cancer stages, with 24 increasing and 12 decreasing in their abundance. Preliminary validation of 3 potential markers ECM1, MAST4 and filaggrin was performed in breast cancer cell lines by Western blotting. One potential marker, MAST4, was further validated in human breast cancer tissues as well as human breast cancer urine samples with immunohistochemistry (IHC) and Western blotting (WB), respectively. The importance of the process of blood collection itself is critical to the accuracy and reproducibility of quantitative biomarker analysis (detailed in Chapter 5). Applying a label-free LC-MS/MS approach to analyse the blood protein abundances in four different blood tubes (2 serum and 2 plasma collection tubes) revealed that there was up to 70% variation between the tubes. The variation in proteins and individual protein abundances detected across the different tubes identified that the richest source was found using the serum gold BD Vacutainer® SST™ gel tube and plasma purple BD Vacutainer ® EDTA tubes. Additionally, applying fractionation it was apparent that the most informative data was obtained from the low to medium (3- 50kDa) fraction. Comparative profiling of the LC-MC/MC data (Chapter 6) identified 50 proteins modulated in the different breast cancer stages (p<0.05 and fold change ⩾3.0) and amongst these, a panel of 17 unique up-regulated stage specific breast cancer proteins were identified. Using this information, five candidates were identified: Clusterin, Insulin-like growth factor-binding protein 3 (IGFBP3), Leucine-rich alpha-2- glycoprotein (LRG-1), S100-A6 and Vitronectin. These putative markers were validated with WB and IHC in breast cancer cell lines, along with serum, plasma and iv tumour samples from patients and healthy subjects. Serum and plasma samples were mined for new biomarkers using a proteomics approach, which highlighted the proteins which are significantly associated with breast cancer. This study has demonstrated that the expression of these selected proteins could be further developed into clinically relevant diagnostic biomarkers, capable of discriminating patients with breast cancer from healthy individuals. The results from my research have identified several important proteins in urine and blood for the detection, monitoring invasive progression, prediction of progression and therapeutic management of breast cancer. This could have a major impact on the prognosis of breast cancer for the tens of thousands of women who succumb to the disease each year. v ACKNOWLEDGMENTS “Happiness is a way of life, not a destiny”. “We are the master of our destiny. We are responsible for our own happiness” William Ernest Henley. This thesis represents the culmination of seven years of part-time doctoral study yet only contains a fraction of the amount of work performed during this time and certainly reflects only a very small portion of my personal growth during this period. The time has come to officially thank all the people who have helped me through the whole PhD journey, which was only possible due to the work and support of my family, friends and colleagues that I have had the opportunity to thank here. Everybody surrounding me was constantly reminding me to see the “big picture” and tackle the real issue: let’s see what we can find in breast cancer patients to help identify the disease early. Firstly, I would like to thank all my supervisors: Associate Professor Yong Li, Dr Valerie Wasinger and Associate Professor Peter Graham. Thank you for giving me this opportunity to take on this journey, supporting me all the way and reviewing my thesis. I would like to express my utmost gratitude to my supervisor Associate Professor Yong Li, for giving me the opportunity to embark on this journey. Whose support, encouragement and help has been invaluable for the thesis and for my development as a researcher at large. By the time I came under Yong Li’s supervision, he was already recognised for his skills and patience and he never failed to show these great qualities. He reviewed all my
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