Genome-wide screening of abberant methylated drivers combined with relative risk loci in bladder cancer.

ABSTRACT:

Background

To explore important methylation-driven genes (MDGs) and risk loci to construct risk model for prognosis of bladder cancer (BCa).

Methods

We utilized TCGA-Assembler package to download 450K methylation data and corresponding transcriptome profiles. MethylMix package was used for identifying methylation-driven genes and functional analysis was mainly performed based on ConsensusPathDB database. Then, Cox regression method was utilized to find prognostic MDGs, and we selected 17 hub genes via stepwise regression and multivariate Cox models. Kruskal-Wallis test was implemented for comparisons between risk with other clinical variables. Moreover, we constructed the risk model and validated it in GSE13507. Gene set enrichment analysis was performed using the levels of

SUBMITTER: Zhang C 

PROVIDER: S-EPMC6970050 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature