You have accessJournal of UrologyKidney Cancer: Basic Research II1 Apr 2015MP47-19 URINE AND SERUM METABOLOMICS ANALYSES MAY DISTINGUISH BENIGN AND MALIGNANT RENAL NEOPLASMS. Oluyemia Falegan, Mark Ball, Rustem Shaykhutdinov, Michael Gorin, Phillip Pierorazio, George Netto, Mohamad Allaf, Hans Vogel, and Eric Hyndman Oluyemia FaleganOluyemia Falegan More articles by this author , Mark BallMark Ball More articles by this author , Rustem ShaykhutdinovRustem Shaykhutdinov More articles by this author , Michael GorinMichael Gorin More articles by this author , Phillip PierorazioPhillip Pierorazio More articles by this author , George NettoGeorge Netto More articles by this author , Mohamad AllafMohamad Allaf More articles by this author , Hans VogelHans Vogel More articles by this author , and Eric HyndmanEric Hyndman More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.1539AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES There are currently no serum or urine biomarkers to differentiate benign from malignant renal neoplasms. We sought to determine if 1H nuclear magnetic resonance (NMR) and gas chromatography-mass spectrometry (GCMS) based metabolomics analyses of urine and serum are able to differentiate between benign renal masses and renal cell carcinoma (RCC). METHODS Patients with clinical T1a renal lesions who underwent extirpative surgery had preoperative fasting urine and serum collected. Serum and urine samples from 53 patients were assessed with 1H NMR and GCMS based metabolomics. Using the Chenomx software package and Metabolite detector software, the groups were stratified according to pathologic stage into benign, pT1-2 and pT3a groups. Metabolomic signatures of each group were compared using orthogonal partial least square discriminate analysis (OPLS-DA). RESULTS Pathologic analysis revealed benign lesions in 13 (24.5%) patients and RCC in 40 (75.5%; pT1-2 in 29 and pT3 in 11). A total of 58 and 98 metabolites could be detected in each of the 53 serum samples that were analyzed by 1H NMR and GCMS, respectively. 72 metabolites were identified in the urine samples examined by 1H NMR. Alterations in the levels of creatinine, methanol, eicosanoic acid, amino acids and citric acid cycle intermediates among other metabolites were detected in RCCs relative to controls. 1H NMR discriminated between benign masses and pT1 RCC (serum R2 = 0.455, Q2 = 0.28; urine R2 = 0.497, Q2 = 0.367) and as well as benign and pT3 RCC (serum R2 = 0.579, Q2 = 0.369; urine R2 = 0.779, Q2 = 0.681. GCMS discriminated benign masses from pT3 RCC (R2 = 0.631, Q2 = 0.481) and pT1 from pT3 RCC (R2 = 0.704, Q2 = 0.539). CONCLUSIONS In this pilot study, urine and serum metabolomics differentiated benign from malignant renal masses as well as pT1 from pT3 RCC. While future investigation is needed, metabolomics may have a role in pre-operative risk stratification for small renal masses. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e558-e559 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Oluyemia Falegan More articles by this author Mark Ball More articles by this author Rustem Shaykhutdinov More articles by this author Michael Gorin More articles by this author Phillip Pierorazio More articles by this author George Netto More articles by this author Mohamad Allaf More articles by this author Hans Vogel More articles by this author Eric Hyndman More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...