Yonsei Med J.  2019 Nov;60(11):1013-1020. 10.3349/ymj.2019.60.11.1013.

A Two-DNA Methylation Signature to Improve Prognosis Prediction of Clear Cell Renal Cell Carcinoma

Affiliations
  • 1Diabetes Center, Zhejiang Provincial Key Laboratory of Pathophysiology, Institute of Biochemistry and Molecular Biology, Medical School of Ningbo University, Ningbo, Zhejiang, China. xiyang@nbu.edu.cn
  • 2Department of Preventative Medicine, Medical School of Ningbo University, Ningbo, Zhejiang, China.

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 methylation analysis 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 potential clinical significance of methylation biomarkers acting as a novel prognostic markers was analyzed using the Kaplan-Meier method 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-DNA methylation signature (cg18034859, cg24199834) with the help of a step-wise multivariable Cox regression model. The area under the curve of ROCs for the two-DNA methylation signature was 0.819. The study samples were stratified into low- and high-risk classifications based on an optimal threshold, and the two groups showed markedly different survival rates. Moreover, the two-DNA methylation 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 increasing the accuracy of predicting overall survival of ccRCC patients.

Keyword

Carcinoma; renal cell; biomarkers; DNA methylation; prognosis

MeSH Terms

Biomarkers
Carcinoma, Renal Cell*
Classification
DNA Methylation
Genome
Humans
Methods
Methylation*
Prognosis*
ROC Curve
Survival Rate
Biomarkers
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