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IntroductionProstate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results.ObjectivesIn this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH.MethodsUrine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1H nuclear magnetic resonance (1H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches.ResultsThe urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH.ConclusionPCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

BackgroundProstate cancer (PCa) is characterized by clinical and biological heterogeneity and has differential outcomes and mortality rates. Therefore, it is necessary to identify molecular alterations to define new therapeutic strategies based on the risk of progression. In this study, the prognostic relevance of the insulin-like growth factor (IGF) system was examined in molecular subtypes defined by TMPRSS2-ERG (T2E) gene fusion within a series of patients with primary localized PCa.MethodsA cohort of 270 formalin-fixed and paraffin-embedded (FFPE) primary PCa samples from patients with more than 5 years’ follow-up was collected. IGF-1R, IGF-1, IGFBP-3 and INSR expression was analyzed using quantitative RT-PCR. The T2E status and immunohistochemical ERG findings were considered in the analyses. The association with both biochemical and clinical progression-free survival (BPFS and PFS, respectively) was evaluated for the different molecular subtypes using the Kaplan-Meier proportional risk log-rank test and the Cox proportional hazards model.ResultsAn association between IGF-1R overexpression and better BPFS was found in T2E-negative patients (35.3% BPFS, p-value = 0.016). Multivariate analysis demonstrated that IGF-1R expression constitutes an independent variable in T2E-negative patients [HR: 0.41. CI 95% (0.2–0.82), p = 0.013]. These data were confirmed using immunohistochemistry of ERG as subrogate of T2E. High IGF-1 expression correlated with prolonged BPFS and PFS independent of the T2E status.Conclusions IGF-1R, a reported target of T2E, constitutes an independent factor for good prognosis in T2E-negative PCa. Quantitative evaluation of IGF-1/IGF-1R expression combined with molecular assessment of T2E status or ERG protein expression represents a useful marker for tumor progression in localized PCa.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-017-3356-8) contains supplementary material, which is available to authorized users.

Prostate cancer (PCa) is a hormone-dependent tumor characterized by an extremely heterogeneous prognosis. Despite recent advances in partially uncovering some of the biological processes involved in its progression, there is still an urgent need for identifying more accurate and specific prognostic procedures to differentiate between disease stages. In this context, targeted approaches, focused on mapping dysregulated metabolic pathways, could play a critical role in identifying the mechanisms driving tumorigenesis and metastasis. In this study, a targeted analysis of the nuclear magnetic resonance-based metabolomic profile of PCa patients with different tumor grades, guided by transcriptomics profiles associated with their stages, was performed. Serum and urine samples were collected from 73 PCa patients. Samples were classified according to their Gleason score (GS) into low-GS (GS < 7) and high-GS PCa (GS ≥ 7) groups. A total of 36 metabolic pathways were found to be dysregulated in the comparison between different PCa grades. Particularly, the levels of glucose, glycine and 1-methlynicotinamide, metabolites involved in energy metabolism and nucleotide synthesis were significantly altered between both groups of patients. These results underscore the potential of targeted metabolomic profiling to characterize relevant metabolic changes involved in the progression of this neoplastic process.