Bioinformatics analysis of genes related to poor prognosis of human  hepatocellular carcinoma and its clinical significance

doi:10.12047/j.cjap.5764.2019.021

Abstract

Abstract: Objective:To screen genes associated with poor prognosis of hepatocellular carcinoma (HCC) and to explore the clinical significance of these genes. Methods: The proper expression profile data of HCC was obtained from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) were identified by differential expression analysis. The DAVID and String database were used for function enrichment analysis and to construct the protein-protein interaction (PPI) network respectively. The Cancer Genome Atlas (TCGA) database and the Cox Proportional Hazard Model were used for prognosis analysis of the DEGs. Results: A eligible human HCC data set (GSE84402) met the requirements. A total of 1141 differentially expressed genes were identified, including 720 up-regulated and 421 down-regulated genes. The results of function enrichment analysis and PPI network performed that CDK1、CDC6、CCNA2、CHEK1、CENPE 、PIK3R1、RACGAP1、BIRC5、KIF11 and CYP2B6 were prognosis key genes. And the prognosis analysis showed that the expressions of CDC6、PIK3R1、KIF11 and RACGAP1 were increased, and the expression of CENPE was decreased, which was closely related to prognosis of HCC. Conclusion: CDC6、CENPE、PIK3R1、KIF11 and RACGAP1 may be closely related to poor prognosis of HCC, and can be used as molecular biomarkers for future research of HCC prognosis.

Key words: hepatocellular carcinoma, poor prognosis genes, bioinformatics, Cox Proportional Hazard Model

XI Yi-bo, ZHANG Hao-min, YANG Bo, CHEN Xi-meng, HE Pei-feng, LU Xue-chun. Bioinformatics analysis of genes related to poor prognosis of human hepatocellular carcinoma and its clinical significance[J]. CJAP, 2019, 35(1): 90-96.

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Bioinformatics analysis of genes related to poor prognosis of human hepatocellular carcinoma and its clinical significance

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