摘要
ObjectiveThe aim of the study is to explore the molecular mechanism of Yadanzi(Brucea javanica)in the treatment of glioblastoma(GBM)by using the methods of bioinformatics and network pharmacology.Methods The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)and literature retrieval method were applied to obtain the active ingredients of Yadanzi(Brucea javanica),and to predict the relevant targets of the active ingredients.The GBM-related targets were retrieved and screened through the Gene Expression Profling Interactive Analysis(GEPIA)database,and mapped to each other with the targets of the components of Yadanzi(Brucea javanica)to obtain the intersection targets.The GBM differentially expressed gene targets were imported into the String database to obtain the protein interaction relationship,the Cytoscape software was used to draw the protein interaction network,the Cytobba and MCODE plug-ins were used to screen the core genes and important protein interaction modules,and the GEPIA database was applied to make survival analysis of the core genes.The network map of“active ingredients-targets”was constructed through the Cytoscape 3.6.1 software.Gene Ontology(GO)biological function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analysis for GBM differentially expressed genes were performed through the DAVID database.ResultsThrough TCMSP and literature retrieval,23 potential active ingredients and 129 related targets were obtained from Yadanzi(Brucea javanica).In the GEPIA database,247 GBM differentially expressed genes were screened,including 113 upregulated genes and 134 downregulated genes.After mapping with the targets related to the active ingredients of Yadanzi(Brucea javanica),six intersection targets were obtained,that is,the potential action targets of Yadanzi(Brucea javanica)in treating GBM,including MMP2,HMOX1,BIRC5,EGFR,CCNB2,and TOP2A.Cytoscape software was applied to build an“active ingredient-action target”network.Two active ingredients and five action targets of β-sitosterol(BS)and luteolin were found,and the targets were mainly concentrated in BS.It was found by KEGG pathway enrichment analysis that GBM differentially expressed genes were mainly involved in signaling pathways related to Staphylococcus aureus infection,phagosome formation,tuberculosis and systemic lupus erythematosus and other infectious and autoimmune diseases.It was found by GO enrichment analysis that the GBM differentially expressed genes mainly involved such biological processes(BP)as the processing and presentation of exogenous antigenic peptides and polysaccharide antigens through MHC Il molecules,y-interferon-mediated signaling pathways,extracellular matrix composition,and chemical synapses transmission;it involved cellular components such as cell junctions,axon terminal buttons,extracellular space,vesicle membranes for endocytosis,and MHC Il protein complexes;molecular functions such as calcium-mediated ionic protein binding,MHC Il molecular receptor activity,immunoglobulin binding,and phospholipase inhibitor activity were also involved.Survival analysis was conducted by GEPIA on the top 37 core targets in degree value,and a total of five genes related to GBM prognosis were obtained.Among them,FN1 and MMP2 were highly expressed while GABRD(v-aminobutyric acid A receptor delta subunit),RBFOX1,and SLC6A7 were expressed at a low level in cancer patients.Conclusion The pathogenesis of GBM is closely related to the human immune system,and BS and luteolin may be the main material basis of Yadanzi(Brucea javanica)for the treatment of GBM and the improvement of prognosis.The molecular mechanism may be related to the physical barrier formed by destroying the tumor cell stromal 68 Treatment of Glioblastoma Based on Bioinformatics and Network Pharmacology Zhao,Si.molecules and its involvement in tumor immune response.
目的:运用生物信息学和网络药理学的方法探究鸦胆子治疗脑胶质瘤(glioblastoma,GBM)的分子机制。方法:采用中药系统药理学数据库和分析平台(traditional Chinese medicine systems pharmacology database and analysis platform,TCMSP)及文献检索获取鸦胆子的活性成分,并预测活性成分的相关作用靶点。通过基因表达谱交互分析(gene expression profiling interactive analysis,GEPIA)数据库检索并筛选GBM相关靶点,与鸦胆子成分靶点互相映射,获得交集靶点。将GBM差异表达基因靶点导入String数据库获得蛋白互作关系,并采用Cytoscape软件绘制蛋白互作网络,采用Cytobba和MCODE插件筛选核心基因和蛋白互作关系重要模块,通过GEPIA数据库对核心基因进行生存分析。采用Cytoscape3.6.1软件构建“活性成分-作用靶点”网络图。采用DAVID数据库对GBM差异表达基因进行基因本体(gene ontology,GO)生物功能富集分析与京都基因和基因组百科全书(kyoto encyclopedia of genes and genomes,KEGG)信号通路富集分析。结果:通过TCMSP及文献检索得到鸦胆子的潜在活性成分23个,相关靶点129个。在GEPIA数据库中筛选到GBM差异表达基因247个,其中上调基因113个,下调基因134个,与鸦胆子活性成分相关靶点进行映射后获得6个交集靶点,即为鸦胆子治疗脑胶质瘤的潜在作用靶点,分别是MMP2、HMOX1、BIRC5、EGFR、CCNB2和TOP2A。运用Cytoscape软件构建“活性成分-作用靶点”网络发现β-谷甾醇(beta-sitosterol)和木犀草素(luteolin)2个活性成分和5个作用靶点,且作用靶点主要集中在β-谷甾醇上。KEGG通路富集分析发现GBM差异表达基因主要涉及金葡菌感染、吞噬小体形成、结核病和系统性红斑狼疮等感染性和自身免疫性疾病相关信号通路等信号通路。GO富集分析发现GBM差异表达基因主要涉及经MHC II类分子参与的外源性抗原肽和多糖抗原的加工和提呈、γ干扰素介导的信号通路、细胞外基质的组成和化学突触传递等生物学过程;涉及细胞连接、轴突终末扣、细胞外隙、内吞作用的囊泡膜和MHC II类蛋白复合物等细胞组分;涉及钙离子介导的离子蛋白结合、MHC II类分子受体活性、免疫球蛋白结合和磷脂酶抑制剂活性等分子功能。运用GEPIA对degree值排名靠前的37个核心靶点进行生存分析,共得到5个与GBM预后相关的基因,其中FN1、MMP2在癌症患者中高表达,GABRD、RBFOX1、SLC6A7在癌症患者中低表达。结论:GBM的发病与人体免疫系统密切相关,β-谷甾醇和木犀草素可能是鸦胆子治疗GBM和改善预后的主要物质基础,其分子作用机制可能与破坏肿瘤细胞基质分子形成的物理屏障和参与肿瘤的免疫应答。
