Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study.

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 >1000 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-κB 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.