Metabolomic profile of patients with suspicion for prostate cancer

125 Metabolomic profile of patients with suspicion for prostate cancer Andras I1, Crisan N.2, Socaciu C.3, Romanciuc F.3, Maxim R.3, Coman I.2 1 Clinical Municipal Hospital, Dept. of Urology, Cluj, Romania, 2University of Medicine and Pharmacy "Iuliu Hatieganu", Dept. of Urology, Cluj, Romania, 3BIOdiaTECH - Research Center for Diagnostic Applied Biotechnologies and Molecular Therapies, Metabolomics, Cluj, Romania INTRODUCTION & OBJECTIVES: The screening for prostate cancer (PC) based on digital rectal examination (DRE) and PSA has been shown to ensure only a moderate reduction in the mortality rate from this disease. The issue that rises, therefore, is to find the balance between the early diagnosis of aggressive PC and the rate of overdiagnosis and overtreatment of clinically indolent tumors. In this context, it is mandatory to identify new methods for the non-invasive evaluation of PC, that allow the improvement of the detection rate of this malignancy, but also the characterization of PC aggressiveness, the prediction of the risk of progression and the response to treatment. Metabolomics is the newest “omic” technology and can be used to determine the pattern and concentration of key metabolites involved in the alterations of intracellular metabolic pathways, which can become biomarkers of the neoplastic transformation. The objective of our study was to determine the metabolomic profile of patients with suspicion for prostate cancer in comparison with a control group. MATERIAL & METHODS: Our study included a number of 85 patients with clinical (DRE) or biochemical (PSA>4 ng/ml) suspicion for PC. Before performing prostate biopsy, we collected serum samples from all patients, which were analyzed using high performance liquid cromatography coupled with mass spectrometry. The control group included 12 healthy men under 30 years. RESULTS: We identified 200 compounds in the serum samples of the patients included in the study (aminoacids, peptides, mono- and di-glycerols, phospholipids), whose variability was analyzed statistically by PCA (Principal Component Analysis). Of these molecules, we selected different metabolites for the targeted quantitative analysis. The results were then correlated with the histopathological examination: inflammation, hyperplasia, adenocarcinoma. So far, we identified 4 compunds that have the potential of becoming biomarkers for the diagnosis of PC: lysine, phenylalanine, alanine and glycine. CONCLUSIONS: The determination of the metabolomic profile for the patients that undergo screening for PC allows the identification of new biomarkers that can improve the early diagnosis of this malignancy. Eur Urol Suppl 2015; 14(6): e1286