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Chunxia Cheng,1 Xingxing Wu,2 Yu Shen,1 Quanxi Li1 1Department of Hepatobiliary Surgery, The Second People’s Hospital of Lianyungang, Liangyungang City 222023, People’s Republic of China; 2Deparment of Pediatric Surgery, The Second People’s Hospital of Lianyungang, Liangyungang City 222023, People’s Republic of ChinaCorrespondence: Quanxi Li Tel +86-13382950660Email lqx0513@163.comBackground: Hepatocellular 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.Methods: Gene 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.Results: A 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.Conclusion: In 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.Keywords: hepatocellular carcinoma, differentially expressed genes, hub genes, KIF14, KIF23, survival analysis

Wei Wan, Yu Shen, Quanxi Li Department of Hepatobiliary Surgery, The Second People’s Hospital of Lianyungang, Liangyungang City 222023, People’s Republic of ChinaCorrespondence: Quanxi LiDepartment of Hepatobiliary Surgery, The Second People’s Hospital of Lianyungang, Liangyungang City 222023, People’s Republic of ChinaTel +86-13382950660Email 540666069@qq.comBackground: Hepatocellular carcinoma (HCC) is one of the most common human malignant tumors. The prognosis of HCC patients is still unsatisfying. Thus, it is of great importance to identify novel molecules and functional pathways associated with the pathophysiology of HCC. In this study, we performed the integrated bioinformatics analysis and experiment validation to identify novel biomarkers in the prognosis and progression of HCC.Materials and Methods: Gene expression profiles were obtained from Gene Expression Omnibus database (GSE33294) for the screening of the differentially expressed genes (DEGs) between HCC tissues and matched non-tumor tissues. The DEGs were subjected to Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Set Enrichment Analysis (GSEA). The key genes in HCC were further subjected to overall survival analysis of HCC patients. The in vitro functional studies were performed to validate the biological functions of the key gene in HCC cell progression.Results: A total of 2,334 DEGs were screened from GSE33294 dataset, including 1,120 up-regulated and 1,214 down-regulated genes. GO, KEGG and GSEA results showed that DEGs are significantly associated with the biological process of cell cycle, cell division and DNA replication. The Kaplan–Meier survival analysis results showed that the key genes from the minichromosome maintenance protein complex (MCM) family including MCM8, MCM10, MCM2, MCM3, MCM4, MCM6 and MCM7 were significantly correlated with the overall survival of the HCC patients. Further validation studies showed that MCM10 was significantly up-regulated in the HCC cell lines, and knockdown of MCM10 significantly suppressed cell proliferation as determined by the cell counting kit-8 and BrdU incorporation assays and increased the caspase-3 activity of HCC cells.Conclusion: The comprehensive bioinformatics analysis identified several key genes that were associated with the prognosis of HCC patients. The validation study results indicated that MCM10 may be an important predictor for poorer prognosis of HCC patients and may act as an oncogene to promote HCC cell progression.Keywords: hepatocellular carcinoma, GSE33294, bioinformatics, hub genes, MCM10, prognosis

The progesterone receptor (PR) plays a critical role during ovulation. Mice lacking the PR gene are anovulatory due to a failure in the rupture of the preovulatory follicles. The pathways that operate downstream of PR to control ovulation are poorly understood. Using gene expression profiling, we identified peroxisome proliferator-activated receptor gamma (PPARgamma) as a target of regulation by PR in the granulosa cells of the preovulatory follicles during the ovulatory process. To investigate the function of PPARgamma during ovulation, we created a conditional knockout mouse in which this gene was deleted via Cre-Lox-mediated excision in granulosa cells. When these mutant mice were subjected to gonadotropin-induced superovulation, the preovulatory follicles failed to rupture and the number of eggs released from the mutant ovaries declined drastically. Gene expression analysis identified endothelin-2, interleukin-6, and cyclic GMP-dependent protein kinase II as novel targets of regulation by PPARgamma in the ovary. Our studies also suggested that cycloxygenase 2-derived metabolites of long-chain fatty acids function as endogenous activating ligands of PPARgamma in the preovulatory follicles. Collectively, these studies revealed that PPARgamma is a key mediator of the biological actions of PR in the granulosa cells and activation of its downstream pathways critically controls ovulation.