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bioRxiv · 10.1101/570846

Identification of differentially expressed genes in hepatocellular carcinoma by integrated bioinformatic analysis

Yan, G.·Liu, Z.
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Abstract

Hepatocellular carcinoma is one of the most common tumors in the world and has a high mortality rate. This study elucidates the mechanism of hepatocellular carcinoma- (HCC) related development. The HCC gene expression profile (GSE54238, GSE84004) was downloaded from Gene Expression Omnibus for comprehensive analysis. A total of 359 genes were identified, of which 195 were upregulated and 164 were downregulated. Analysis of the condensed results showed that \"extracellular allotrope\" is a substantially enriched term. \"Cell cycle\", \"metabolic pathway\" and \"DNA replication\" are three significantly enriched Kyoto Encyclopedia of Genes and Genomespathways. Subsequently, a protein-protein interaction network was constructed. The most important module in the protein-protein interaction network was selected for path enrichment analysis. The results showed that CCNA2, PLK1, CDC20, UBE2C and AURKA were identified as central genes, and the expression of these five hub genes in liver cancer was significantly increased in The Cancer Genome Atlas. Univariate regression analysis was also performed to show that the overall survival and disease-free survival of patients in the high expression group were longer than in the expression group. In addition, genes in important modules are mainly involved in \"cell cycle\", \"DNA replication\" and \"oocyte meiosis\" signaling pathways. Finally, through upstream miRNA analysis, mir-300 and mir-381-3p were found to coregulate CCNA2, AURKA and UBE2C. These results provide a set of targets that can help researchers to further elucidate the underlying mechanism of liver cancer.

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Yan, G., Liu, Z.. 2019-03-07. Identification of differentially expressed genes in hepatocellular carcinoma by integrated bioinformatic analysis. https://doi.org/10.1101/570846

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