【摘要】 目的利用生物信息学方法分析胶质母细胞瘤基因表达谱芯片,从转录水平探讨胶质母细胞瘤与正常组织的差异表达基因的功能及相互作用。方法从公共数据平台GEO中下载了81例胶质母细胞瘤组织和23例来源于癫痫患者的非肿瘤组织基因表达数据,利用R语言包筛选差异表达基因,进一步利用DAVID、STRING数据库对差异表达基因进行GO、KEGG富集分析、蛋白相互作用分析。结果在胶质母细胞瘤中共筛选出相对于正常组织差异表达基因823个,上调基因214个、下调基因609个。GO分析显示差异表达基因主要涉及细胞连接、突触化学信号传导、轴突及突触等生物学过程,KEGG分析提示其在包括尼古丁成瘾、吗啡成瘾、γ氨基丁酸能突触、突触囊泡循环以及ECM-受体相互作用、ErbB信号通路、HIF-1信号通路、RAS信号通路等32个通路中富集。利用STRING数据库进一步分析差异基因的蛋白-蛋白相互作用网络。结论利用生物信息学方法能有效对胶质母细胞瘤基因芯片数据进行挖掘,为进一步研究胶质母细胞瘤发生发展机制及寻找潜在的药物治疗靶点提供参考。更多还原

【Abstract】 Objective To find differentially expressed genes between glioblastoma and normal tissues by bioinformatics analysis,and to investigate their molecular function and interactions from the transcriptional level.Methods The gene expression profile datasets GSE4290,including 81 samples of glioblastoma and 23 samples of normal tissue from epileptic patients,were downloaded from Gene Expression Omnibus(GEO).Differentially expressed genes between the two kinds of tissue were identified by R package.The GO analysis,KEGG pathways,and protein-protein interactions were analyzed by DAVID,STRING database.Results A total of 823 differentially expressed genes were identified,including 214 up-regulated and 609 down-regulated genes.GO analysis showed that differentially expressed genes were mainly involved in cell attachment,synaptic chemical signal transduction,axon and synapse etc.KEGG pathways showed that it was enriched in 32 KEGG pathways,including nicotine addiction,morphine addiction,GABAergic synapses,synaptic vesicle cycle,ECM-receptor interaction,ErbB signaling pathway,HIF-1 signaling pathway,and RAS signaling pathway.The protein-protein interaction networks were analyzed by STRING database.Conclusion Bioinformatics can be effectively used to analyze glioblastoma microarray data to provide theoretical reference for further exploration of tumorigenesis mechanism and help search for potential drug therapeutic targets.更多还原