Prognostic Value of DNA Methylation-Driven Genes in Clear Cell Renal Cell Carcinoma: A Study Based on Methylation and Transcriptome Analyses

Maolin Hu 1 2, Jiangling Xie 3, Huiming Hou 2, Ming Liu 2, Jianye Wang 1 2

Affiliations

PMID: 32733620
PMCID: PMC7369658
DOI: 10.1155/2020/8817652

Free PMC article

Abstract

Background: Few previous studies have comprehensively explored the level of DNA methylation and gene expression in ccRCC. The purpose of this study was to identify the key clear cell renal cell carcinoma- (ccRCC-) related DNA methylation-driven genes (MDG) and to build a prognostic model based on the level of DNA methylation.

Methods: RNA-seq transcriptome data and DNA methylation data were obtained from The Cancer Genome Atlas. Based on the MethylMix algorithm, we obtain ccRCC-related MDG. The univariate and multivariate Cox regression analyses were employed to investigate the correlation between patient overall survival and the methylation level of each MDG. Finally, a prognosis risk score was established based on a linear combination of the regression coefficient derived from the multivariate Cox regression model (β) multiplied with the methylation level of the gene.

Results: 19 ccRCC-related MDG were identified. Three MDG (NCKAP1L, EVI2A, and BATF) were further screened and integrated into a prognostic risk score model, risk score = (3.710∗methylation level of NCKAP1L) + (-3.892∗methylation level of EVI2A) + (-3.907∗methylation level of BATF). The risk model was independent from conventional clinical characteristics as a prognostic factor for ccRCC (HR = 1.221, 95% confidence interval: 1.063-1.402, and P = 0.005). The joint survival analysis showed that the gene expression and methylation levels of the prognostic genes EVI2A and BATF were significantly related with prognosis.

Conclusion: This study provided an important bioinformatics foundation for in-depth studies of ccRCC DNA methylation.