肝癌相关差异基因的生物信息学分析

摘要

Objective To identify differentially expressed genes in liver cancer by bioinformatics analysis method,and provide potential basis for drug targets and molecular biomarkers that were involved in the development of liver cancer.Methods The gene expression profile datasets GSE60502,which included 18 pairs of liver cancer and adjacent tissues,respectively,were downloaded from Gene Expression Omnibus (GEO).Differentially expressed genes between liver cancer and adjacent tissues were identified.The gene functions,genome pathways,and protein-protein interactions were analyzed by DAVID and STRING database.Results A total of 1 108 differentially expressed genes were identified,including 605 up-regulated genes and 503 down-regulated genes.The differentially expressed genes mainly involved in cell cycle,DNA replication,cancer pathway,p53 signaling,focal adhesion,complement and coagulation cascades,nutrient metabolism,and hormone metabolism.Twenty genes were located in the hubs of protein-protein interaction network by STRING database.Conclusion Through the bioinformatics method,the present study may improve understanding the molecular mechanism,biological process,and molecular function of liver cancer.Furthermore,the present study may aid in the development of novel means of prevention,diagnosis and treatment of liver cancer.%目的 采用生物信息学方法对肝癌差异表达基因进行基因功能和信号通路分析,为临床筛选肝癌发生、发展的相关分子标志物及药物靶点提供理论基础.方法 从公共数据库(GEO)中获取18例肝癌组织和18例癌旁组织的基因表达阵列数据进行生物信息学分析,筛选差异表达基因.利用DAVID和STRING数据库对差异表达基因进行基因功能、信号通路和蛋白相互作用分析.结果 通过对两组数据的差异表达基因筛选,共获得1 108个差异表达基因,其中上调基因605个、下调基因503个.差异表达基因主要涉及细胞周期、DNA复制、癌通路、p53信号通路、黏附、补体途径、三大营养物质代谢及性激素代谢等.通过STRING数据库分析列出位于前20位蛋白互作网络的中心节点蛋白.结论 本研究采用生物信息学方法对肝癌基因芯片数据进行挖掘,从基因水平探讨肝癌发生发展的物质基础、分子功能和生物学过程,为肝癌发生的机制研究、肿瘤标志物的筛选及药物靶点选择提供参考.