基于GEO数据库筛选慢性乙型病毒性肝炎患者对干扰素α治疗无应答相关的关键免疫基因和通路

Screening of key immune genes and pathways related to the ineffectiveness of interferon alpha treatment in patients with chronic hepatitis B based on GEO database

目的基于GEO数据库筛选接受干扰素α(IFN-α)治疗的慢性乙型病毒性肝炎(CHB)患者中应答者(Rs)和无应答者(NRs)之间差异表达的免疫基因,以探索IFN-α治疗CHB失败的分子基础。方法从GEO数据库中下载基因芯片数据集GSE27555,包含6例Rs和7例NRs。使用R软件筛选Rs和NRs肝脏组织的差异表达基因,再从免疫相关基因数据库ImmPort下载包含1793个基因在内的标志性免疫基因集,提取差异表达基因中的免疫基因,获取差异免疫基因。再对差异免疫基因进行基因本体论(gene ontology,GO)和京都基因与基因组百科全书(kyoto encyclopedia of genes and genomes,KEGG)分析。通过STRING在线分析工具构建差异免疫基因的蛋白-蛋白相互作用(PPI)网络,进一步利用Cytoscape软件中的Cytohubba插件对差异免疫基因按Degree、MCC、MNC、Closeness算法计算评分位于前10的基因,再取交集,得到枢纽基因(Hub基因)。结果从Rs与NRs间共筛选出差异免疫基因88个,其中上调基因13个,下调基因75个。GO分析发现,这些差异免疫基因主要涉及的生物过程包括T细胞活化、细胞趋化性、细胞-细胞粘附的调节、抗原加工和提呈等方面。KEGG分析显示,这些差异免疫基因主要富集于细胞因子-细胞因子受体相互作用、Th细胞分化、抗原加工和提呈、病毒蛋白与细胞因子和细胞因子受体的相互作用、趋化因子信号通路、T细胞受体信号通路、IL-17信号通路、自然杀伤细胞介导的细胞毒性、Toll样受体信号通路等免疫应答信号通路中。在PPI网络中通过不同算法筛选出的7个共同的Hub基因分别为CD8A、I FNG、CCL2、CCL5、CXCL10、CCL4、FCGR3A。结论利用生物信息学方法分析了Rs与NRs之间的差异免疫基因及信号通路,并确定了7个与IFN-α治疗CHB无应答相关的Hub基因。这些Hub基因可能成为预测IFN-α治疗CHB应答情况的潜在生物标志物。

Objective To screen the differentially expressed immune genes between responders(Rs)and non-responders(NRs)in chronic hepatitis B patients receiving interferon alpha(IFN-α)treatment and to explore the molecular basis of IFN-αtreatment failure.Methods The gene expression profile GSE27555 which contained 6 Rs and 7 NRs was obtained from the Gene Expression Omnibus(GEO)database;then differentially expressed genes between liver tissues of Rs and NRs were selected by the R software.The iconic immune gene set consisting of 1793 genes was downloaded from the immunology database and analysis portal(ImmPort).The immune genes were extracted from the differentially expressed genes to obtain the differentially expressed immune genes.Subsequently,Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses of the differentially expressed immune genes were performed by the R software.Protein-protein interaction(PPI)network of the differentially expressed immune genes was constructed using the STRING online tool.The plugin CytoHubba of the Cytoscape software was applied to identify the top 10 genes by using Degree,MCC,MNC,and Closeness algorithms;then the intersection was taken to obtain the hub genes.Results A total of 88 differentially expressed immune genes,consisting of 13 upregulated and 75 downregulated genes,were identified between Rs and NRs.GO analysis showed that the differentially expressed immune genes were significantly enriched in T cell activation,cell chemotaxis,regulation of cell-cell adhesion,antigen processing and presentation.KEGG pathway analysis suggested that the differentially expressed immune genes were significantly enriched in cytokine-cytokine receptor interactions,Th cell differentiation,antigen processing and presentation,interactions between viral proteins and cytokines and cytokine receptors,chemokine signaling pathways,T cell receptor signaling pathway,IL-17 signaling pathway,natural killer cell-mediated cytotoxicity,Toll-like receptor signaling pathway,and other immune response signaling pathways.The top 7 hub genes,identified by the plugin cytoHubba of the Cytoscape software by using Degree,MCC,MNC and Closeness algorithms,were CD8A,IFNG,CCL2,CCL5,CXCL10,CCL4,and FCGR3A.Conclusion This study made a comprehensive analysis of the differentially expressed immune genes and signal pathways between Rs and NRs by bioinformatics,and identified 7 Hub genes related to the ineffectiveness of IFN-αtreatment in CHB patients.These hub genes may serve as potential biomarkers for predicting the response of IFN-αtreatment in CHB patients.