Abstract
BackgroundHepatocellular carcinoma (HCC) is one of the most common human malignant tumors. The prognosis of HCC patients is still unsatisfying. In this study, we performed the integrated bioinformatics analysis to identify potential biomarkers and biological pathways in HCC.MethodsGene expression profiles were obtained from the Gene Expression Omnibus database (GSE55048, GSE55758, and GSE56545) for the screening of the common differentially expressed genes (DEGs) between HCC tissues and matched non-tumor tissues. DEGs were subjected to Gene Ontology, KEGG pathway, and Reactome pathway analysis. The hub genes were identified by using protein–protein interaction (PPI) network analysis. The hub genes in HCC were further subjected to overall survival analysis of HCC patients. The hub genes were further validated by in vitro functional assays.ResultsA total of 544 common differentially expressed genes were screened from three datasets. Gene Ontology, KEGG and Reactome analysis results showed that DEGs are significantly associated with the biological process of cell cycle, cell division, and DNA replication. PPI network analysis identified 20 hub genes from the DEGs. These hub genes except CENPE were all significantly up-regulated in the HCC tissues when compared to non-tumor tissues. The Kaplan–Meier survival analysis results showed that the high expression of the 20 hub genes was associated with shorter survival of the HCC patients. Further validation studies showed that knockdown of KIF14 and KIF23 both suppressed the proliferative potential, increased the caspase-3/-7 activity, up-regulated Bax expression, and promoted the invasive and migratory abilities in the HCC cells. In addition, knockdown of KIF14 and KIF23 enhanced chemosensitivity to cisplatin and sorafenib in the HCC cells. Finally, the high expression of KIF14 and KIF23 was associated with shorter progression-free survival, recurrence-free survival, and disease-specific survival of patients with HCC.ConclusionIn conclusion, the present study performed the integrated bioinformatics analysis and showed that KIF14 and KIF23 silence attenuated cell proliferation, invasion, and migration, and promoted chemosensitivity of HCC cells. KIF14 and KIF23 may serve as potential biomarkers for predicting the worse prognosis of patients with HCC.
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