Article Abstract

Identification of potential therapeutic targets in hepatocellular carcinoma using an integrated bioinformatics approach

Authors: Qinfeng Huang, Junhong Li, Ailing Wei


Background: Hepatocellular carcinoma (HCC) frequently recurs and has poor prognosis, and thus it is essential to investigate the molecular mechanisms associated with HCC development using integrated bioinformatics approaches to identify potential therapeutic targets.
Methods: Gene expression data from three microarray datasets, namely, GSE36376, GSE45267, and GSE51401 and 318 HCC tissues and 266 adjacent non-tumorous tissues from HCC patients were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were selected with the limma package in R language, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional enrichment analysis. A protein-protein interaction (PPI) network and a sub-network were established using Search Tool for the Retrieval of Interacting Genes (STRING) and visualized with Cytoscape.
Results: A total of 2,249 DEGs were identified in the three datasets, which included 1,735 upregulated and 514 downregulated DEGs. Functional annotation of the DEGs using GO analysis identified categories that were mainly associated with mitotic nuclear division, chromosome segregation, and sister chromatid segregation. KEGG pathway analysis showed that the categories of cell cycle and the p53 signaling pathway, which contributes to the development of HCC, were mainly enriched with DEGs. PPI network and sub-network analyses identified cyclin dependent kinase 2 (CDK2), cyclin B1 (CCNB1), and cell division cycle 20 (CDC20) as hub genes. Furthermore, the categories of cell cycle and p53 signaling pathway were enriched with the hub genes CCNB1 and CDK2.
Conclusions: DEGs such as CCNB1, CDC20, and CDK2 as well as classified under the categories of the p53 signaling pathway and the cell cycle were associated with HCC and thus may be potentially utilized as therapeutic targets for the treatment of HCC.