Bioinformatics Analysis of Hepatocellular Carcinoma Related Gene and Construction of a Protein-Protein Interaction Network

Objective To identify key genes associated with hepatocellular carcinoma (HCC) through analyzing the functions of differentially expressed genes (DEGs) and the interactions of their encoded proteins. Methods The microarray dataset GSE45436 was downloaded from the Gene Expression Omnibus (GEO) database. The DEGs in hepatocellular carcinoma and adjacent tissues were analyzed using the R software. Bioinformatics tools DAVIA, STRING, GEPIA, Cytoscape, cBioPortal were applied to analyze the biological functions of the DEGs and their encoded protein interactions. Results A total of 375 DEGs were identified, consisting of 296 downregulated genes and 99 upregulated genes. The enriched functions and pathways of the DEGs included cell cycle, p53 signaling pathway, complement activation, and metabolism of xenobiotics by cytochrome P450. The PPIanalysis showed that TOP2A might be involved in the carcinogenesis of HCC. Conclusions Differentially expressed genes in hepatocellular carcinoma and adjacent tissues and their encoded protein interactions revealed by the bioinformatics analysis provide guidance for further research on the molecular mechanism and targeted therapy of HCC. TOP2A may play a key role in HCC.