Developing a novel DNA methylation risk score for survival and identification of prognostic gene mutations in endometrial cancer: a study based on TCGA data.

Abstract

Few studies have focused on DNA methylation in endometrial cancer. The aim of our study is identify its role in endometrial cancer prognosis. A publicly available dataset was retrieved from The Cancer Genome Atlas. For validation of expression alteration due to methylation, RNA sequencing data were obtained from other independent cohorts. MethSurv was used to search for candidate CpG probes, which were then filtered by least absolute shrinkage and selection operator Cox regression and multivariate Cox regression analyses to identify final set of CpG probes for overall survival. A methylation-based risk model was developed and receiver operating characteristic analysis with area under curve was used for evaluation. Patients were divided into high- and low-risk groups using an optimal cut-off point. Comprehensive bioinformatic analyses were conducted to identify hub genes, key transcription factors, and enriched cancer-related pathways. Kaplan-Meier curve was used for survival analysis. A 5-CpG signature score was established. Its predictive value for 5-year overall survival was high, with area under curve of 0.828, 0.835 and 0.816 for the training, testing and entire cohorts. cg27487839 and cg12885678 had strong correlation with their gene expression, XKR6 and PTPRN2, and lower PTPRN2 expression was associated with poorer survival in both The Cancer Genome Atlas and the validation datasets. Low-risk group was associated with significantly better survival. Low-risk group harboured more mutations in hub genes and key transcription factors, and mutations in SP1 and MECP2 represented favourable outcome. We developed a methylation-based prognostic stratification system for endometrial cancer. Low-risk group was associated with better survival and harboured more mutations in the key regulatory genes.