Abstract
Aberrant methylation of DNA is a key driver of hepatocellular carcinoma (HCC). In this study, we sought to integrate four cohorts profile datasets to identify such abnormally methylated genes and pathways associated with HCC. To this end, we downloaded microarray datasets examining gene expression (GSE84402, GSE46408) and gene methylation (GSE73003, GSE57956) from the GEO database. Abnormally methylated differentially expressed genes (DEGs) were sorted and pathways were analyzed. The String database was then used to perform enrichment and functional analysis of identified pathways and genes. Cytoscape software was used to create a protein-protein interaction network, and MCODE was used for module analysis. Finally, overall survival analysis of hub genes was performed by the OncoLnc online tool. In total, we identified 19 hypomethylated highly expressed genes and 14 hypermethylated lowly expressed genes at the screening step, and finally found six mostly changed hub genes including MAD2L1, CDC20, CCNB1, CCND1, AR and ESR1. Pathway analysis showed that aberrantly methylated-DEGs mainly associated with the cell cycle process, p53 signaling, and MAPK signaling in HCC. After validation in TCGA database, the methylation and expressio...Continue Reading
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