Identification of prognosis-related genes in hepatocellular carcinoma based on bioinformatical analysis
10.3872/j.issn.1007-385x.2019.04.010
- VernacularTitle:基于生物信息学分析的肝细胞癌预后相关基因的筛选
- Author:
SUN Houfang
;
YAN Cihui
;
WU Lei
;
LI Baihui
;
YANG Lili
- Publication Type:Journal Article
- Keywords:
hepatocellular carcinoma;
bioinformatical analysis;
prognostic gene;
gene ontology analysis;
Kyoto Encyclopedia of Genes and Genomes analysis;
protein-protein interaction network
- From:
Chinese Journal of Cancer Biotherapy
2019;26(4):431-439
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To identify the differentially expressed genes (DEGs) between hepatocellular carcinoma (HCC) tissues and normal liver tissues by bioinformatic methods, and to explore the intrinsic mechanism of these candidate genes involving in the occurrence and development of HCC from transcriptome level as well as the clinical significance of their associations with the prognosis of HCC patients. Methods: Gene expression profiles of GSE45267, GSE64041, GSE84402 and TCGA were downloaded from GEO (Gene Expression Omnibus) and TCGA(The Cancer GenomeAtlas), respectively. R software and Bioconductor packages were used to identify the DEGs between HCC tissues and para-cancer tissues, and then Gene Ontology (GO) Enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Protein-Protein Interaction (PPI) network analysis and survival analysis were performed. Results: Forty-six up-regulated genes and 154 down-regulated genes were screened out,and GO enrichment analysis showed that these DEGs were mainly related to cell division, proliferation, cycle regulation, oxidation-reduction process and certain metabolic pathways. KEGG pathway analysis revealed that DEGs were mainly involved in tryptophan metabolism, retinol metabolism and other metabolic pathways as well as p53 pathway. Over-expression of a panel of up-regulated genes (CCNA2, CDK1, DLGAP5, KIF20A, KPNA2 and MELK) was shown to be significantly negatively correlated with the prognosis of HCC patients in the TCGA dataset (all P<0.01). Conclusion: A set of up-regulated hub genes that are negatively correlated with prognosis will provide potential guiding value for the clinical research on the diagnosis and treatment of HCC.
- Full text:20190410.pdf
