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肝癌相关差异表达基因的生物信息学分析及蛋白互作网络构建

Bioinformatics Analysis of Hepatocellular Carcinoma Related Gene and Construction of a Protein-Protein Interaction Network

  • 摘要: 目的 建立生物信息学分析筛选肝癌基因芯片差异表达基因的方法,助力肝癌发病分子机制的研究。方法 通过R语言软件分析肝癌芯片数据GSE45436中肝癌组织和癌旁组织差异表达的基因, DAVID软件对差异表达基因进行GO功能富集及KEGG通路富集分析,String和Cytoscape软件分析关键基因和模块。结果 共筛选出375个差异表达明显的基因,其中表达上调和下调的分别有99个和296个。差异基因功能分析主要涉及细胞周期、p53信号通路、补体途径、细胞色素P450代谢通路等。蛋白质-蛋白质相互作用(protein-protein interaction, PPI)网络显示拓扑异构酶Ⅱα (TOP2A) 可能与肝癌的发生发展最为相关。结论 本研究采用基因芯片结合生物信息学方法,构建了肝癌差异表达基因编码的蛋白互作网络。TOP2A可能是肝癌相关的核心基因。

     

    Abstract: Objective To identify key genes associated with hepatocellular carcinoma (HCC) through analyzing the functions of differentially expressed genes (DEGs) and the interactions of their encoded proteins. Methods The microarray dataset GSE45436 was downloaded from the Gene Expression Omnibus (GEO) database. The DEGs in hepatocellular carcinoma and adjacent tissues were analyzed using the R software. Bioinformatics tools DAVIA, STRING, GEPIA, Cytoscape, cBioPortal were applied to analyze the biological functions of the DEGs and their encoded protein interactions. Results A total of 375 DEGs were identified, consisting of 296 downregulated genes and 99 upregulated genes. The enriched functions and pathways of the DEGs included cell cycle, p53 signaling pathway, complement activation, and metabolism of xenobiotics by cytochrome P450. The PPIanalysis showed that TOP2A might be involved in the carcinogenesis of HCC. Conclusions Differentially expressed genes in hepatocellular carcinoma and adjacent tissues and their encoded protein interactions revealed by the bioinformatics analysis provide guidance for further research on the molecular mechanism and targeted therapy of HCC. TOP2A may play a key role in HCC.

     

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