MP28-11 A 4-MIRNA SCORE PREDICTS THE INDIVIDUAL METASTATIC RISK OF RENAL CELL CARCINOMA PATIENTS

Abstract

You have accessJournal of UrologyKidney Cancer: Epidemiology & Evaluation/Staging I1 Apr 2018MP28-11 A 4-MIRNA SCORE PREDICTS THE INDIVIDUAL METASTATIC RISK OF RENAL CELL CARCINOMA PATIENTS Joana Heinzelmann, Madeleine Arndt, Ramona Pleyers, Tobias Fehlmann, Sebstian Hölters, MArtin Janssen, Alexey Pryalukhin, Rainer Bohle, Mieczyslaw Gajda, Elke Schaeffeler, Michael Stöckle, and Kerstin Junker Joana HeinzelmannJoana Heinzelmann More articles by this author , Madeleine ArndtMadeleine Arndt More articles by this author , Ramona PleyersRamona Pleyers More articles by this author , Tobias FehlmannTobias Fehlmann More articles by this author , Sebstian HöltersSebstian Hölters More articles by this author , MArtin JanssenMArtin Janssen More articles by this author , Alexey PryalukhinAlexey Pryalukhin More articles by this author , Rainer BohleRainer Bohle More articles by this author , Mieczyslaw GajdaMieczyslaw Gajda More articles by this author , Elke SchaeffelerElke Schaeffeler More articles by this author , Michael StöckleMichael Stöckle More articles by this author , and Kerstin JunkerKerstin Junker More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.911AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES The prognosis of patients with renal cell carcinoma strongly depends on the metastatic potential of the primary tumor. Recently, we have identified miRNAs which characterize primary renal cell carcinoma (ccRCC) with high metastatic risk. The aim of this study is to determine whether a combination of differently expressed miRNAs in samples of primary resected tumors can predict the individual risk for metastatic disease in ccRCC patients. METHODS FPE samples of metastatic (n=57) and non-metastatic (n=51) primary ccRCCs were collected between 2000 and 2013 in two German academic centers. We evaluated the association of altered miRNA expression with the metastatic potential of tumors using qPCR. In a test-cohort, we selected the best discriminators for metastatic and non-metastatic ccRCC. The selected miRNAs were subsequently approved in a validation- cohort. A prognostic 4-miRNA-signature was established using support vector machines. Cox regression analyses were performed using IBM SPSS Statistics for correlation of miRNA-model and clinico-pathological parameters to metastasis-free and overall survival. RESULTS Nine out of 14 candidate miRNAs showed significant expression alterations in the test cohort. Thereof, eight miRNAs were approved in the validation cohort. We established a 4-miRNA score (miR-30a-3p, miR-30c-5p, miR-139-5p, miR-144) with a sensitivity of 86%, a specificity of 70% and a accuracy of 78%. This score was the superior predictor for metastasis-free (HR=13.614, p=0.00003) and overall survival (p=0.002) compared to T-category, Grading and N-status, likewise in the subgroup of patients with low risk tumors (pT1a/b, cN0, cM0, G1-2) (HR=17.323, p=0.028). CONCLUSIONS The 4-miRNA score is applicable as an independent prognostic molecular tool superior to clinico-pathological parameters for accurate prediction of individual metastatic risk even in low risk ccRCC. Our score improves the stratification of ccRCC patients in high and low metastatic risk groups for individual follow-up and adjuvant therapy strategies. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e360 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Joana Heinzelmann More articles by this author Madeleine Arndt More articles by this author Ramona Pleyers More articles by this author Tobias Fehlmann More articles by this author Sebstian Hölters More articles by this author MArtin Janssen More articles by this author Alexey Pryalukhin More articles by this author Rainer Bohle More articles by this author Mieczyslaw Gajda More articles by this author Elke Schaeffeler More articles by this author Michael Stöckle More articles by this author Kerstin Junker More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...