Network and pathway analysis related to hepatitis b with and without hepatocellular carcinoma using computational bioinformatics approach

Sedigheh Behrouzifar,1,* Meysam mobasheri,2

2. Islamic Azad University-Pharmaceutical Branch



Chronic infection with hepatitis b is an independent risk factor for the development of hepatocellular carcinoma (hcc) which can occur without cirrhosis. because of the long-term treatment process for hepatitis b, designing new combined therapeutic strategies to eradicate viral carcinogenesis would be very helpful. this study was conducted to identify hub genes and active key pathways in liver tissue of hbsag positive patients with hepatocellular carcinoma.


Microarray data of gse84402 deposited in geo database was downloaded. the differentially expressed genes (degs) were determined in 14 hbsag positive cancerous liver tissue samples and 14 hbsag positive non-cancerous tissue samples using limma r packages. then genes with the cut-off criteria of p < 0.05 and log fold-change (fc) above 1.5 were selected. hub genes were further screened using cytoscape software and annotated using kegg enrichment pathway analysis. afterward, the centrality and modularity class of hub genes were analyzed using gephi software. finally, the prognostic values of the hub genes with high centrality were assessed using proggenev2 database.


107 up-regulated genes were screened out. kegg pathways enriched with the degs were mainly cell cycle, p53 signaling pathway, dna replication, viral carcinogenesis and micrornas in cancer. five hub genes with the highest centrality were ccnb1, cdk1, ccna2, bub1b and ccnb2. ccna2 was suggested to be prognostic factor for liver carcinoma. the gene ontology molecular function enriched for the three modules were primarily microtubule motor activity and exodeoxyribonuclease activity. pathways enriched for the three modules in wikipathway were primarily, cell cycle, retinoblastoma in cancer and gastric cancer network.


High throughput data analysis indicated that the several genes implicated in cell cycle regulatory machinery have pivotal roles in the progression of liver carcinoma that could potentially be used as diagnostic and therapeutic targets. identification of the molecular mechanism of hepatocellular carcinoma and important pathways involved in viral carcinogenesis for designing novel therapeutic agents is important.


Hepatocellular carcinoma, network analysis, hub genes, viral carcinogenesis pathway, bioinformatics