Identification of abnormally expressed genes and their roles in invasion and migration of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death in the world, mainly attributable to its high migration tendency. Most patients with HCC miss the benefit of radical resection or liver transplantation because of distant metastasis of the tumor. Therefore, identification of diagnostic and therapeutic targets by analyzing abnormally expressed genes associated with tumor invasion and migration in HCC could be useful. In this study, we carried out a meta-analysis of three gene expression profile data sets (GSE45050, GSE84598 and GSE89377), including 112 liver cancer and 77 normal tissue samples, to identify candidate genes and pathways. The three gene expression omnibus (GEO) data sets had 155 differentially expressed genes (DEGs) in common, including 25 up-regulated and 129 down-regulated genes. Protein-protein interaction (PPI) networks were generated in the STRING database and explored further in Cytoscape to identify network hubs. Moreover, the statistically significant (p < 0.05) functions and signaling pathways enriched by the shared DEGs were identified. The Kaplan-Meier curve was applied to analyze univariate survival outcomes of the hub genes, which suggested and as independent prognostic factors in HCC. Additionally, we found that and were markedly upregulated in HCC cell lines. Quantitative PCR, western blot, and Immunohistochemistry (IHC) was performed to determine mRNA and protein expression of and in 20 normal liver tissues and 66 HCC tissues from patients with HCC who underwent complete surgical resection in stage 1 to 4. Results showed that expression of and were significantly higher in HCC tissues than normal tissues and were increased from HCC stage 1 to 4. Importantly, through loss of function, we showed that and both significantly promote HCC migration and invasion. In summary, we identified the key candidate DEGs and dysregulated pathways in HCC through bioinformatic analysis and experimental validation. These candidate DEGs and pathways enhance our understanding of the potential pathogenesis of HCC and may hold promise as markers for the diagnosis, treatment, and prognosis of HCC.