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

Abstract

Background: 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. Materials and Methods: 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. Results: A total of 425 DEGs were identified that met both of our criteria for significance: (1) a jlog2-fold change (FC)j ‡ 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. Conclusion: 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.

Highly deregulated lncRNA LOC is associated with overall worse prognosis in Hepatocellular Carcinoma patients

“…However, its role in HCC remains unknown. Similarly, consistent with our finding, FAM65C was also reported to be downregulated in HCC although very little is known about this protein [74,75]. It is thus worthwhile to further characterize how lncRNA LOC deregulate the expression of HSD17B13 and FAM65C to modulate patient outcome.…”

Identification and Analysis of Genes Associated with Epithelial Ovarian Cancer by Integrated Bioinformatics Methods

“…In researches of hepatocellular carcinoma (HCC), CDCA5 was also found to be up-regulated in HCC cells, and related to poor prognosis [15]. CDCA5 participated the promotion of HCC cells proliferation, migration, and invasion, palying a tumor-promotive role and being a potential therapeutic target for patients with HCC [16,17]. Besides, CDCA5 was found to be transcribed by E2F1, and could promote oncogenesis by enhancing cell proliferation and inhibiting apoptosis via the AKT pathway in HCC [18].…”

Screening hypoxia-related genes as prognostic biomarkers and modeling the individualized prognostic predictor in hepatocellular carcinoma

“…According to the current study, some features of HCC prognosis based on expression profile have been found by large public databases. However, the purpose of these studies was often limited to mining new molecular markers but neglecting routine clinical parameters [32,33]. Thus, we integrated patient clinical information to establish a PP model for assessing prognosis.…”