A Two-DNA Methylation Signature to Improve Prognosis Prediction of Clear Cell Renal Cell Carcinoma
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Purpose: Effective biomarkers and models are needed to improve the prognostic prospects of clear cell renal cell carcinoma(ccRCC). The purpose of this work was to identify DNA methylation biomarkers and to evaluate the utility of DNA methylationanalysis for ccRCC prognosis. Materials and Methods: An overview of genome-wide methylation of ccRCC tissues derived from The Cancer Genome Atlas(TCGA) database was download for analysis. DNA methylation signatures were identified using Cox regression methods. The potentialclinical significance of methylation biomarkers acting as a novel prognostic markers was analyzed using the Kaplan–Meiermethod and receiver operating characteristic (ROC) curves. Results: This study analyzed data for 215 patients with information on 23171 DNA methylation sites and identified a two-DNAmethylation signature (cg18034859, cg24199834) with the help of a step-wise multivariable Cox regression model. The area underthe curve of ROCs for the two-DNA methylation signature was 0.819. The study samples were stratified into low- and high-risk classificationsbased on an optimal threshold, and the two groups showed markedly different survival rates. Moreover, the two-DNAmethylation marker was suitable for patients of varying ages, sex, stages (I and IV), and histologic grade (G2). Conclusion: The two-DNA methylation signature was deemed to be a potential novel prognostic biomarker of use in increasingthe accuracy of predicting overall survival of ccRCC patients.
Abstract
Purpose: Effective biomarkers and models are needed to improve the prognostic prospects of clear cell renal cell carcinoma(ccRCC). The purpose of this work was to identify DNA methylation biomarkers and to evaluate the utility of DNA methylationanalysis for ccRCC prognosis. Materials and Methods: An overview of genome-wide methylation of ccRCC tissues derived from The Cancer Genome Atlas(TCGA) database was download for analysis. DNA methylation signatures were identified using Cox regression methods. The potentialclinical significance of methylation biomarkers acting as a novel prognostic markers was analyzed using the Kaplan–Meiermethod and receiver operating characteristic (ROC) curves. Results: This study analyzed data for 215 patients with information on 23171 DNA methylation sites and identified a two-DNAmethylation signature (cg18034859, cg24199834) with the help of a step-wise multivariable Cox regression model. The area underthe curve of ROCs for the two-DNA methylation signature was 0.819. The study samples were stratified into low- and high-risk classificationsbased on an optimal threshold, and the two groups showed markedly different survival rates. Moreover, the two-DNAmethylation marker was suitable for patients of varying ages, sex, stages (I and IV), and histologic grade (G2). Conclusion: The two-DNA methylation signature was deemed to be a potential novel prognostic biomarker of use in increasingthe accuracy of predicting overall survival of ccRCC patients.
참고문헌 (38)
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