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Prostate cancer (PCa) is the second leading cause of cancer death among men and associated with profound metabolic changes. It is important to discover new biomarkers for the diagnosis of PCa and metabolomics technology has made progress toward identifying metabolic alterations in diseases that may provide clinically useful biomarkers. The purpose of this work was to determine the distinctive metabolic signatures from PCa. Plasma samples from PCa patients and age-matched healthy controls were investigated using high resolution ultrahigh performance liquid chromatography-mass spectrometry (UPLC/MS) and the datasets were analyzed using pattern recognition methods. Metabolic differences among PCa and control subjects were identified based on multivariate statistical analyses. As a result, 19 distinguishable metabolites were detected and 11 metabolic pathways were established. The altered metabolic pathways were associated with synthesis and degradation of ketone bodies, and phenylalanine metabolism, etc. To demonstrate the utility of plasma biomarkers for the diagnosis of PCa, three metabolites comprising sarcosine, acetylglycine and coreximine that contributed to the combined model were selected as candidate biomarkers. Distinctive signature with these metabolites could significantly increase the diagnostic performance of PCa. In this study, metabolomics technology has proved to be a powerful tool for the discovery of new biomarkers for disease and suggest that panels of metabolites may be valuable to translate our findings to clinically useful diagnostic tests.

Plasma metabolic profiling and novel metabolite biomarkers for diagnosing prostate cancer