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目的:采用生物信息学方法筛选和分析原发性肝细胞癌组织和癌旁组织差异表达基因（DEGs），探索原发性肝细胞癌发生和预后的分子机制。方法:通过GEO数据库收集了GSE76427数据集，采用GEO2R在线分析鉴定了DEGs。利用GO和KEGG数据库对DEGs进行富集和功能注释。基于STRING数据库和Cytoscape软件构建蛋白质互相作用网络分析肝细胞癌发病关键基因。通过GEPIA数据库对这些关键基因进行生存曲线的分析。结果:共筛选出74个肝细胞癌DEGs，包括3个上调基因和71个下调基因。GO富集分析结果显示，下调的DEGs主要参与细胞对镉离子和锌离子的反应、生长负调节、异源代谢过程和激素介导的信号通路。KEGG通路富集分析结果显示，下调的DEGs通路主要涉及视黄醇代谢、化学致癌作用、药物代谢-细胞色素P450、细胞色素P450对异生物素的代谢、色氨酸代谢及咖啡因代谢等。蛋白质互相作用网络筛选出10个下调的核心基因：MT1G、MT1F、MT1X、MT1E、MT1H、胰岛素样生长因子1、FOS、CXCL12、EGR1、BGN，其中胰岛素样生长因子1与原发性肝细胞癌的预后有关。结论:通过对肝细胞癌芯片数据的生物信息学分析结果显示10个关键基因可能对原发性肝细胞癌的发生和发展起关键作用。胰岛素样生长因子1与原发性肝细胞癌的预后有关。“,”Objective:To screen and analyze the differentially-expressed genes (DEGs) in primary hepatocellular carcinoma tissues and adjacent tissues using bioinformatics methods to explore the molecular mechanism of the occurrence and prognosis of primary hepatocellular carcinoma.Methods:GSE76427 data set was collected through GEO database, and DEGs were identified using GEO2R online analysis. Go and KEGG databases were used for enrichment and functional annotation of DEGs. Protein interaction network was built based on the STRING database and Cytoscape software to analyze the key genes of hepatocellular carcinoma, and the survival curve of these key genes were analyzed using the GEPIA database.Results:A total of 74 hepatocellular carcinoma DEGs were screened, of which 3 and 71 were up-and-down-regulated genes. The results of GO enrichment analysis showed that the down-regulated DEGs were mainly involved in cell response to cadmium and zinc ions, negative growth regulation, heterologous metabolic processes and hormone-mediated signaling pathways. KEGG pathway enrichment analysis results showed that the down-regulated DEGs pathway were mainly involved in retinol metabolism, chemical carcinogenesis, drug metabolism-cytochrome P450, cytochrome P450 metabolizing xenobiotics, tryptophan metabolism and caffeine metabolism. Protein interaction network had screened out 10 down-regulated core genes: MT1G, MT1F, MT1X, MT1E, MT1H, insulin-like growth factor 1, FOS, CXCL12, EGR1, and BGN. Among them, the insulin-like growth factor 1 was related to the prognosis of primary hepatocellular carcinoma.Conclusion:Bioinformatics analysis results of HCC chip data showed that 10 key genes may play a key role in the occurrence and development of HCC and the insulin like growth factor 1 is associated with the prognosis of primary hepatocellular carcinoma.