A predictive model for assessing prognostic risks in gastric cancer patients using gene expression and methylation data.

ABSTRACT:

Background

The role(s) of epigenetic reprogramming in gastric cancer (GC) remain obscure. This study was designed to identify methylated gene markers with prognostic potential for GC.

Methods

Five datasets containing gene expression and methylation profiles from GC samples were collected from the GEO database, and subjected to meta-analysis. All five datasets were subjected to quality control and then differentially expressed genes (DEGs) and differentially expressed methylation genes (DEMGs) were selected using MetaDE. Correlations between gene expression and methylation status were analysed using Pearson coefficient correlation. Then, enrichment analyses were conducted to identify signature genes that were significantly different at both the gene expression and methylation

SUBMITTER: Luo D 

PROVIDER: S-EPMC7789242 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature