Using Integrated Bioinformatics Analysis to Identify Abnormally Methylated Differentially Expressed Genes in Hepatocellular Carcinoma.

ABSTRACT:

Objective

For the identification of abnormally methylated differentially expressed genes (MDEGs) in hepatocellular carcinoma (HCC), this study integrated four microarray datasets to investigate the fundamental mechanisms of tumorigenesis.

Methods

We obtained the expression (GSE76427, GSE57957) and methylation (GSE89852, GSE54503) profiles from Gene Expression Omnibus (GEO). The abnormally MDEGs were identified by using R software. We used the clusterProfiler package for the functional and pathway enrichment analysis. The String database was used to build the protein-protein interaction (PPI) network and visualize it in Cytoscape. MCODE was employed in the module analysis. Additionally, Gene Expression Profiling Interactive Analysis (GEPIA) and The Cancer Genome Atlas (TCGA)

SUBMITTER: Chen QL 

PROVIDER: S-EPMC7956867 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature