Journal
BRITISH JOURNAL OF CANCER
Volume 115, Issue 9, Pages 1078-1086Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/bjc.2016.291
Keywords
prostate cancer; serum; proteomics; biomarkers; PSA; LCMS; iTRAQ
Categories
Funding
- University of Manchester Project Diamond
- Prostate Project Charity
- Guildford
- MRC Confidence in Concept funding
- Wessex Cancer Trust
- Wessex Medical Research
- University of Southampton 'Annual Adventures in Research' Grant
- International Highly Cited Research Group (IHCRG 14-203) of the Deanship of Scientific Research
- Visiting Professor Program of King Saud University, Riyadh, Saudi Arabia
- European Regional Development Fund
- Republic of Cyprus through the Research Promotion Foundation [NEKYP/0311/17, YGEIA/BIOS/0311(BIE/07)]
- MRC
- Vice-Dean of Scientific Research Chairs of King Saud University, Riyadh, Saudi Arabia
- MRC [MR/M008959/1, MC_PC_14112] Funding Source: UKRI
- Medical Research Council [MC_PC_14112] Funding Source: researchfish
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Background: Prostate cancer (PCa) is the most common male cancer in the United Kingdom and we aimed to identify clinically relevant biomarkers corresponding to stage progression of the disease. Methods: We used enhanced proteomic profiling of PCa progression using iTRAQ 3D LC mass spectrometry on high-quality serum samples to identify biomarkers of PCa. Results: We identified 41000 proteins. Following specific inclusion/exclusion criteria we targeted seven proteins of which two were validated by ELISA and six potentially interacted forming an 'interactome' with only a single protein linking each marker. This network also includes accepted cancer markers, such as TNF, STAT3, NF-kappa B and IL6. Conclusions: Our linked and interrelated biomarker network highlights the potential utility of six of our seven markers as a panel for diagnosing PCa and, critically, in determining the stage of the disease. Our validation analysis of the MS-identified proteins found that SAA alongside KLK3 may improve categorisation of PCa than by KLK3 alone, and that TSR1, although not significant in this model, might also be a clinically relevant biomarker.
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