Identification of Hepatocellular Carcinoma-Related Potential Genes and Pathways Through Bioinformatic-Based Analyses

Hepatocellular carcinoma (HCC) is one of the most prevalent tumors worldwide. However, the key roles of most molecules associated with tumor proliferation, invasion, and metastasis in HCC remain unclear. It is therefore important to explore potential mechanisms underlying tumorigenesis and to screen genes and pathways identified from such research for their role in pathogenesis. We selected microarray data GSE62043 consisting of paired tissue samples from 100 HCC patients, then these data were analyzed to identify differentially expressed genes (DEGs). Next, gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out to elucidate the biological processes, molecular function, cellular component (CC), and KEGG signaling pathways for the DEGs. We then constructed protein-protein interaction (PPI) networks, followed by a functional enrichment analysis, from which we obtained two significant gene modules. Finally, the gene expression data obtained from this test set were subjected to validation studies using an independent set of hepatocellular patient data archived in The Cancer Genome Atlas and Genotype-Tissue Expression (TCGA/GTEx) database. A total of 425 DEGs were identified that met both of our criteria for significance: (1) a |log2-fold change (FC)| ≥ 1.2 and (2) an adjusted p value <0.01. From these data, two significant gene modules, containing 28 pathway-related hub genes, were identified. Through application of a test/validation algorithm using HCC datasets from two independent databases, we identified a number of genes that could serve as potential biomarkers for the molecular diagnosis and therapeutic intervention of HCC, including the known genes, IGF1, IGF2, NDC80, CDK1, CENPF, CDCA8, CCNB1, BIRC5, NCAPG, and CDCA5, and the novel genes, CENPU and SPC25, which are associated with cell cycle, mitotic cell cycle, and organelle organization.