胶质母细胞瘤差异表达基因的生物信息学分析  

Bioinformatics analysis of differentially expressed genes in glioblastoma

作　　者：彭倩 韩刚[2] 张志辰[2] 宋龙飞 满君 PENG Qian;HAN Gang;ZHANG Zhichen;SONG Longfei;MAN Jun(Beijing University of Chinese Medicine,Beijing 100029,China;Dongfang Hospital,Beijing University of Chinese Medicine,Beijing 100078,China;Affiliated Hospital of Weifang Medical University,Shandong Weifang 261031,China.)

机构地区：[1]北京中医药大学,北京100029 [2]北京中医药大学东方医院,北京100783 [3]潍坊医学院附属医院,山东潍坊261031

出　　处：《现代肿瘤医学》2020年第23期4073-4078,共6页Journal of Modern Oncology

基　　金：国家中医药管理局国家中医临床研究基地业务建设科研专项课题(编号:JDZX2015288)。

摘　　要：目的:应用生物信息学方法挖掘胶质母细胞瘤(GBM)的相关基因,进而探讨发病机制,为GBM临床诊断和靶向治疗提供理论依据。方法:从GEO(Gene Expression Omnibus)数据库下载基因芯片数据集GSE4290和GSE15824,应用GEO2R筛选GBM的差异表达基因(DEGs)。采用DAVID数据库进行GO富集和KEGG通路富集分析,分别应用STRING数据库和Cytoscape软件构建蛋白质相互作用网络和关键基因模块,筛选GBM靶基因。进一步运用ONCOMINE数据库验证临床组织样本中靶基因与GBM的关系。结果:共筛选出76个DEGs,富集分析结果显示DEGs在血管生成的正调节、抗原的呈递和处理、信号转导、调节自噬等方面存在显著富集。共挖掘出POSTN、TAGLN、CALD1、EPCAM 4个GBM靶基因,经证实均在临床GBM组织样本中存在显著上调且靶基因的上调与患者的不良预后密切相关。结论:通过生物信息学共挖掘出4个与GBM显著相关的靶基因,可能是未来GBM发病机制、临床诊断、治疗的重要研究靶点。Objective:To provide theoretical basis for the pathogenesis,clinical diagnosis and targeted therapy of GBM,we excavated the related genes of GBM by bioinformatics analysis.Methods:We downloaded gene datasets GSE4290 and GSE15824 from the Gene Expression Omnibus(GEO)database and screened the differentially expressed genes(DEGs)by GEO2 R.DAVID database was used for GO enrichment and KEGG pathway enrichment analysis.The STRING database and Cytoscape software were respectively used to construct the protein interaction network and key gene module to screen hub genes of GBM.The relationship between hub genes and GBM was further verified in clinical tissue samples from ONCOMINE database.Results:76 DEGs were identified,and the DEGs were mainly enriched in positive regulation of angiogenesis,antigen processing and presentation,signal transduction,regulation of autophagy.A total of 4 hub genes,including POSTN,TAGLN,CALD1 and EPCAM were excavated,all of which were significantly up-regulated in clinical GBM tissue samples and the up-regulated hub genes were closely related to the poor prognosis of patients.Conclusion:Four hub genes significantly related to GBM were identified through bioinformatics,which may be important research targets for pathogenesis,clinical diagnosis and treatment of GBM in the future.

关 键 词：胶质母细胞瘤 差异表达基因 蛋白相互作用网络 GO和KEGG通路富集分析 靶基因 

分 类 号：R730.264[医药卫生—肿瘤]