Quantitative urinary proteomics using stable isotope labelling by peptide dimethylation in patients with prostate...

Prostate cancer (PCa) is the most commonly diagnosed malignancy in men. The current prevalent diagnosis method, prostate-specific antigen (PSA) screening test, has low sensitivity, specificity and is poor at predicting the grade of disease. Thus, new biomarkers are urgently needed to improve the PCa diagnosis and staging for the management of patients. The aim of this study is to investigate the first voided urinary sample after massage for biomarker discovery for PCa. In this work, untargeted metabolomic profiling of the first voided urinary sample after massage from 28 confirmed prostate cancer patients, 20 benign enlarged prostate patients and 6 healthy volunteers was performed using liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-MS/MS). Single and multiple peptide protein and cross-linking molecules were identified using PEAKS software. Analytical and diagnostic performance was tested using the Student's t test, Benjamini Hochberg correction and the receiver operating characteristic (ROC) curves. Using differential display analysis to compare peptides and cross-linking molecules of urinary samples between patients with benign, enlarged prostate and malignant cancer, we identified multiple peptides derived from osteopontin (SPP1) and prothrombin (F2) that are lower in PCa patients than in benign and enlarged prostate. The diagnosis accuracies of SPP1 and F2 peptides are 0.65-0.77 and 0.68-0.72, respectively. In addition to this, there are significant differences between PCa and benign/enlarged prostate patients in pyridinoline (PYD) and deoxypyridinoline (DPD) (p value = 0.001). Differences also, as shown in the excretion of these molecules for different stages of PCa (p value = 0.04) as the level of DPD and DPD/PYD ratio, were high in patients with locally advanced tumours. The study underscores the importance of proteomics analysis, and our results demonstrate that a urinary-based in depth proteomic approach allows the potential identification of dysregulated pathways and diagnostic biomarkers.