Analysis of expression profile data identifies key genes and pathways in hepatocellular carcinoma

The aims of the present study were to identify key genes and pathways associated with hepatocellular carcinoma (HCC) progression and predict compounds potentially associated with this type of carcinogenesis. The gene expression profile data of the GSE49515 dataset was obtained from the Gene Expression Omnibus database. The limma software package was used to identify the differentially expressed genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Biological Networks Gene Ontology tool and the Database for Annotation, Visualization and Integrated Discovery, respectively. The Michigan Molecular Interactions database plugin within the Cytoscape software platform was used to perform protein-protein interaction (PPI) network analysis. Chemical-gene interaction data for HCC were obtained from the Comparative Toxicogenomics Database to evaluate the associations between drugs and specific genes. A total of 302 DEGs, including 231 downregulated and 71 upregulated, were identified. Cytokine-cytokine receptor interaction and chemokine signaling were the significantly enriched pathways. Additionally, PPI network analysis indicated a total of 13 highest degree hub nodes, including FBJ murine osteosarcoma viral oncogene homolog (FOS) and DNA damage-inducible transcript 3 protein (DDIT3). Chemical-gene interaction analysis revealed that FUN and FOS were targeted by >500 compounds, while >200 genes were targeted by 2,3,7,8-tetrachlorodibenzodioxin and benzo(α)pyrene. In conclusion, the present study demonstrated that FOS, DDIT3, the cytokine-cytokine receptor interaction pathway and the chemokine signaling pathway may be key genes and pathways associated with the development of HCC. Furthermore, exposure to 2,3,7,8-tetrachlorodibenzodioxin or benzo(α)pyrene may lead to hepatocarcinogenesis.