Identification of Methylation Markers and Differentially Expressed Genes with Prognostic Value in Breast Cancer.

Abstract

Breast cancer is one of the most common cancers causing a high mortality worldwide. This study aimed to identify differential methylation and expression genes with prognostic value in breast cancer. DNA methylation and gene expression profiles (GSE60185, GSE42568, GSE21653, GSE58812, and GSE52865) were downloaded from TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) databases. The differentially expressed genes (DEGs) and differential methylation genes were identified between breast cancer samples and normal samples. Functional analysis was performed using DAVID (Database for Annotation, Visualization, and Integrated Discovery) tool. Furthermore, functional epigenetic modules (FEM) were analyzed to identify critical genes with prognostic values. A large amount of DEGs and aberrant methylation genes were identified between breast cancer samples and normal samples. These genes were mainly associated with several GO (Gene Ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, such as neuroactive ligand-receptor interaction, alcoholism, gamma-aminobutyric acid signaling pathway, and G-protein-coupled receptor signaling pathway. Additionally, 10 DEGs with differential methylation levels were significantly correlated with survival outcomes in breast cancer patients. FEM analysis revealed that several DEGs (e.g., GABRA4, GABRG1, and GABRA1) in module GABRA4 were identified as potential biomarkers in breast cancer patients. Several DEGs identified were associated with breast cancer prognosis. These DEGs might act as prognostic and diagnostic markers in breast cancer.