PURPOSE: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancers in adults, and microRNAs (miRNAs) differentially expressed in ccRCC tumors have been identified and proposed to predict prognosis. In the present study, we comprehensively analyzed the genome-wide miRNA expression profiles in ccRCC, with the aim to generate a tumor-specific miRNA signature of prognostic values. METHODS: The miRNA profiles in tumor and the adjacent normal tissue were analyzed, and the association of the differentially expressed miRNAs with patient survival was examined with univariate Cox regression analysis. Finally, a tumor-specific miRNA signature was generated and examined with Kaplan-Meier survival, univariate, and multivariate Cox regression analyses. RESULTS: A total of 147 miRNAs were found differentially expressed between tumor and matched non-tumor tissues from 58 ccRCC patients. The prognostic values of these differentially expressed miRNAs were subsequently analyzed in the 411 ccRCC patients, and 22 miRNAs were found significantly correlated with patient survival. Finally, a tumor-specific miRNA signature of 22 miRNAs was generated and validated as an independent prognostic parameter. CONCLUSIONS: A tumor-specific miRNA signature consisting of 22 miRNAs was identified and validated as an independent prognostic factor, which could serve as a novel biomarker for ccRCC prognostication and help in predicting treatment outcome.
PURPOSE:Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancers in adults, and microRNAs (miRNAs) differentially expressed in ccRCC tumors have been identified and proposed to predict prognosis. In the present study, we comprehensively analyzed the genome-wide miRNA expression profiles in ccRCC, with the aim to generate a tumor-specific miRNA signature of prognostic values. METHODS: The miRNA profiles in tumor and the adjacent normal tissue were analyzed, and the association of the differentially expressed miRNAs with patient survival was examined with univariate Cox regression analysis. Finally, a tumor-specific miRNA signature was generated and examined with Kaplan-Meier survival, univariate, and multivariate Cox regression analyses. RESULTS: A total of 147 miRNAs were found differentially expressed between tumor and matched non-tumor tissues from 58 ccRCC patients. The prognostic values of these differentially expressed miRNAs were subsequently analyzed in the 411 ccRCC patients, and 22 miRNAs were found significantly correlated with patient survival. Finally, a tumor-specific miRNA signature of 22 miRNAs was generated and validated as an independent prognostic parameter. CONCLUSIONS: A tumor-specific miRNA signature consisting of 22 miRNAs was identified and validated as an independent prognostic factor, which could serve as a novel biomarker for ccRCC prognostication and help in predicting treatment outcome.
Authors: Na Liu; Nian-Yong Chen; Rui-Xue Cui; Wen-Fei Li; Yan Li; Rong-Rong Wei; Mei-Yin Zhang; Ying Sun; Bi-Jun Huang; Mo Chen; Qing-Mei He; Ning Jiang; Lei Chen; William C S Cho; Jing-Ping Yun; Jing Zeng; Li-Zhi Liu; Li Li; Ying Guo; Hui-Yun Wang; Jun Ma Journal: Lancet Oncol Date: 2012-05-03 Impact factor: 41.316
Authors: J Ferlay; E Steliarova-Foucher; J Lortet-Tieulent; S Rosso; J W W Coebergh; H Comber; D Forman; F Bray Journal: Eur J Cancer Date: 2013-02-26 Impact factor: 9.162
Authors: Sakshi Gulati; Pierre Martinez; Tejal Joshi; Nicolai Juul Birkbak; Claudio R Santos; Andrew J Rowan; Lisa Pickering; Martin Gore; James Larkin; Zoltan Szallasi; Paul A Bates; Charles Swanton; Marco Gerlinger Journal: Eur Urol Date: 2014-07-19 Impact factor: 20.096
Authors: Jesús García-Donas; Benoit Beuselinck; Lucía Inglada-Pérez; Osvaldo Graña; Patrick Schöffski; Agnieszka Wozniak; Oliver Bechter; Maria Apellániz-Ruiz; Luis Javier Leandro-García; Emilio Esteban; Daniel E Castellano; Aranzazu González Del Alba; Miguel Angel Climent; Susana Hernando; José Angel Arranz; Manuel Morente; David G Pisano; Mercedes Robledo; Cristina Rodriguez-Antona Journal: JCI Insight Date: 2016-07-07
Authors: Vincenzo Petrozza; Antonio Carbone; Teresa Bellissimo; Natale Porta; Giovanni Palleschi; Antonio Luigi Pastore; Angelina Di Carlo; Carlo Della Rocca; Francesco Fazi Journal: Int J Mol Sci Date: 2015-12-08 Impact factor: 5.923