| Literature DB >> 30953370 |
Zeyu Yang1, Anwei Liu1, Qiao Xiong1, Yongping Xue1, Fei Liu1, Shuxiong Zeng1, Zhensheng Zhang1, Yunfei Li2, Yinghao Sun1, Chuanliang Xu1.
Abstract
DNA methylation can regulate gene expression and is pivotal in the occurrence and development of bladder cancer. In this study, we analyzed whole-genome DNA methylation on the basis of data from The Cancer Genome Atlas to select epigenetic biomarkers predictive of survival and further understand the molecular mechanisms underlying methylation patterns in bladder cancer. We identified 540 differentially methylated genes between tumor and normal tissues, including a number of independent prognostic factors based on univariate analysis. Genes (MIR6732, SOWAHC, SERPINI1, OR10W1, OR7G3, AIM1, and ZFAND5) were integrated to establish a risk model for prognostic assessment based on multivariate Cox analysis. The methylation of SOWAHC was negatively correlated with its messenger RNA expression, and together these were significantly correlated with prognosis. This study took advantage of high-throughput data mining to provide new bioinformatics evidence and ideas for further study into the pathogenesis and prognosis of bladder cancer.Entities:
Keywords: Cox proportional hazards regression; biomarkers; bladder cancer; methylation; survival analysis
Mesh:
Year: 2019 PMID: 30953370 DOI: 10.1002/jcp.28515
Source DB: PubMed Journal: J Cell Physiol ISSN: 0021-9541 Impact factor: 6.384