中国肿瘤生物治疗杂志2019，Vol.26Issue(4)：431-439,9.DOI:10.3872/j.issn.1007-385x.2019.04.010
基于生物信息学分析的肝细胞癌预后相关基因的筛选
Identification of prognosis-related genes in hepatocellular carcinoma based on bioinformatical analysis
摘要
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 Genome Atlas), 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.关键词
肝细胞癌/生物信息分析/预后相关基因/基因本体分析/京都基因与基因组百科全书分析/蛋白质相互作用网络Key words
hepatocellular carcinoma/bioinformatical analysis/prognostic gene/gene ontology analysis/Kyoto Encyclopedia of Genes and Genomes analysis/protein-protein interaction network分类
医药卫生引用本文复制引用
孙厚芳,颜次慧,吴磊,李百会,杨莉莉..基于生物信息学分析的肝细胞癌预后相关基因的筛选[J].中国肿瘤生物治疗杂志,2019,26(4):431-439,9.基金项目
国家自然科学基金资助项目(No.81572265) （No.81572265）
