You have accessJournal of UrologyProstate Cancer: Basic Research (I)1 Apr 2013209 METABOLITE PROFILING AS TOOL FOR THE IDENTIFICATION OF DIFFERENTIATING AND PROGNOSTIC MARKERS OF PROSTATE CARCINOMA Carsten Stephan, Regina Reszka, Beate Kamlage, Bianca Bethan, Michael Lein, Glen Kristiansen, and Klaus Jung Carsten StephanCarsten Stephan Berlin, Germany More articles by this author , Regina ReszkaRegina Reszka Berlin, Germany More articles by this author , Beate KamlageBeate Kamlage Berlin, Germany More articles by this author , Bianca BethanBianca Bethan Berlin, Germany More articles by this author , Michael LeinMichael Lein Offenbach, Germany More articles by this author , Glen KristiansenGlen Kristiansen Bonn, Germany More articles by this author , and Klaus JungKlaus Jung Berlin, Germany More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2013.02.1589AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Metabolomic research offers a deeper insight into biochemical changes in cancer metabolism and is a promising tool for identifying novel biomarkers. We aimed to evaluate the diagnostic and prognostic potential of metabolites in prostate cancer (PCa) tissue after radical prostatectomy. METHODS 107 matched-paired tissue samples collected after radical prostatectomy were subjected to the MxPTM Broad Profiling by gas chromatographymass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (Patent WO 2010/139711 A1: “Means and methods for diagnosing prostate carcinomas”). Aminoadipic acid, cerebronic acid, gluconic acid, glycerophosphoethanolamine, 2-hydroxybehenic acid, isopentenyl pyrophosphate, maltotriose, 7-methylguanine, and tricosanoic acid were related to clinicopathological variables like prostate volume, tumor stage, Gleason score, preoperative prostate-specific antigen (PSA), and disease recurrence in the follow-up. Non-parametric statistical tests, receiver-operating characteristics (ROC) and univariate and multivariate analyses (Kaplan-Meier curve; Cox regression) were performed. RESULTS All metabolites showed higher concentrations in malignant than in nonmalignant samples except for gluconic acid and maltotriose, which had lower levels in tumors. ROC analyses showed a clear differentiation for all metabolites with a maximal area under the curve of 0.86 for tricosanoic acid. However, the metabolites were not related to tumor stage and Gleason grade. Aminoadipic acid, gluconic acid, and maltotriose levels were associated with tumor recurrence (Kaplan-Meier analysis) and were, together with tumor stage and Gleason score, a successful metabolite combination in the multivariate Cox regression model for the prediction of tumor recurrence. CONCLUSIONS This exemplary study performed with selected metabolites from a global metabolic profiling investigation proves that metabolites in prostate carcinoma tissue can be used, in combination with traditional pathological and histomorphological parameters, as promising diagnostic and prognostic tools. © 2013 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 189Issue 4SApril 2013Page: e86 Advertisement Copyright & Permissions© 2013 by American Urological Association Education and Research, Inc.MetricsAuthor Information Carsten Stephan Berlin, Germany More articles by this author Regina Reszka Berlin, Germany More articles by this author Beate Kamlage Berlin, Germany More articles by this author Bianca Bethan Berlin, Germany More articles by this author Michael Lein Offenbach, Germany More articles by this author Glen Kristiansen Bonn, Germany More articles by this author Klaus Jung Berlin, Germany More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...