肝细胞癌发病和预后关键基因的生物信息学筛选及验证

摘要/Abstract

摘要： 目的通过生物信息学分析方法筛选肝细胞癌（hepatocellular carcinoma,HCC）发病关键基因,验证HCC发病关键基因中与预后有关的基因。
方法：从基因表达数据库（Gene Expression Omnibus,GEO 数据库）下载GSE112790和GSE101685数据集,筛选2个数据集中HCC组织和癌旁正常组织的差异表达基因（differentially expressed genes,DEGs）,利用基因本体论（gene ontology,GO）富集分析和京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes,KEGG）信号通路分析DEGs的生物学过程和相关信号通路,利用Cytoscape软件从DEGs构建的蛋白质相互作用网络中筛选出10个关键基因,验证其中与预后有关的基因。
结果：2个数据集共筛选出344个DEGs,其中104个上调,240个下调。GO富集分析显示,DEGs主要富集在细胞周期过程、有丝分裂细胞周期过程、有机酸代谢过程、羧酸代谢过程和草酸代谢过程。KEGG信号通路分析显示,DEGs富集在细胞色素P450-外源性物质代谢通路、p53信号通路、细胞色素P450-药物代谢通路、代谢通路、亚油酸代谢通路等。CDK1、CCNB1、CCNA2、CCNB2、MAD2L1、AURKA、TTK、CDC20、NDC80和BIRC5可能在HCC的发生发展中发挥作用。组织标本验证结果显示,HCC组织CDK1和MAD2L1 mRNA表达水平高于癌旁正常组织,且差异均有统计学意义（P<0.001）。生存分析结果显示,CDK1低表达组HCC患者生存期长于高表达组HCC患者,且差异有统计学意义（P=0.030）;而MAD2L1与HCC患者预后无关联（P=0.481）。
结论：CDK1、CCNB1、CCNA2、CCNB2、MAD2L1、AURKA、TTK、CDC20、NDC80和BIRC5可能在HCC的发生发展中发挥作用。其中CKD1与HCC患者预后有关联,可能成为新的HCC预后生物标志物。

关键词: 肝细胞癌, 关键基因, 发病, 预后, 生物信息学分析

Abstract: Objective: To screen the key genes of hepatocellular carcinoma (HCC) and verify the prognostic genes of the key genes by bioinformatics.
Method: GSE112790 and GSE101685 data sets were downloaded from Gene Expression Omnibus (GEO) database to screen common differentially expressed genes in HCC tissues and paracancerous tissues. The biological processes and related signaling pathways of the differentially expressed genes (DEGs) were analyzed by gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Ten key genes were screened from the protein-protein interaction network constructed by DEGs through Cytoscape software, which were screened and verified involved in prognosis.
Result: A total of 344 DEGs were screened out in the two data sets, among which 104 were up-regulated and 240 were down-regulated. GO enrichment analysis showed that differentially expressed genes were mainly concentrated in cell cycle process, mitotic cell cycle process, organic acid metabolism process, carboxylic acid metabolism process and oxalic acid metabolism process. KEGG enrichment analysis showed that the differentially expressed genes were mainly concentrated in metabolism of xenobiotics by cytochrome P450, p53 signaling pathway, drug metabolism-cytochrome P450, metabolic pathways, linoleic acid metabolic pathway, CDK1, CCNB1, CCNA2, CCNB2, MAD2L1, AURKA, TTK, CDC20, NDC80 and BIRC5 may play a role in the development and progression of HCC. After tissue specimen verification, the mRNA expression levels of CDK1 and MAD2L1 in HCC tissues were higher than those in adjacent tissues, and the differences were statistically significant (P<0.001). Results of survival analysis showed that the survival time of CDK1 low expression group was significantly longer than that of the high expression group (P=0.030), and MAD2L1 was not correlated with the prognosis of HCC patients (P=0.481).
Conclusion: CDK1, CCNB1, CCNA2, CCNB2, MAD2L1, AURKA, TTK, CDC20, NDC80 and BIRC5 may play a role in the development and progression of HCC. CKD1 is associated with the prognosis of HCC and may become a new prognostic marker.

Key words: Hepatocellular carcinoma, Key genes, Pathogenesis, Prognosis, Bioinformatics analysis

施文武, 陈智敏, 周金华. 肝细胞癌发病和预后关键基因的生物信息学筛选及验证[J]. 肝癌电子杂志, 2022, 9(3): 1-6.

Shi Wenwu, Chen Zhimin, Zhou Jinhua. Bioinformatics analysis and validation of key genes in the pathogenesis and prognosis of hepatocellular carcinoma[J]. Electronic Journal of Liver Tumor, 2022, 9(3): 1-6.

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