乳腺癌基因表达谱芯片的生物信息学分析

Bioinformatics analysis of breast cancer gene expression profile chip

目的利用生物信息学方法及网页统计工具筛选与乳腺癌的发病相关的枢纽基因(hub基因),并且联合蛋白数据库等多数据库比对,进一步分析生物学功能及与预后的相关性。方法从GEO数据库中下载得到2个表达谱芯片数据集,利用在线工具GEO2R比对数据集中正常组织与乳腺癌组织的差异表达基因(DEG),使用DAVID在线数据库对差异基因进行功能富集分析和通路注释,后使用网页工具STRING和Cytoscape软件构建蛋白互作(PPI)网络并用其筛选出hub基因,最后结合Kaplan-Meier plotter数据库对筛选出的hub基因进行进一步分析和验证。结果共选取出127个DEG,其中有36个表达上调,91个表达下调。后使用Cytoscape软件中插件cytoHubba再次筛选得出AURKA、CDK1、PCNA、TOP2A、HMMR、RRM2、PRC1、MCM4、GINS2、SMC4等10个基因确定为hub基因。Kaplan-Meier plotter数据库生存分析验证显示除CDK1、SMC4外,其他基因的差异表达均与乳腺癌患者的总生存率(OS)相关。结论最后筛选出hub基因的与乳腺癌的发生及预后有密切关系,可进一步探究验证作为乳腺癌的潜在的预测指标和治疗靶点。

Objective To screen pivotal genes(hub genes)related to breast cancer incidence by bioinformatics methods and webpage statistics tools,and combine with protein database to further analyze biological function and correlation with prognosis.Methods Two microarray datasets were downloaded from Gene Expression Omnibus(GEO)database.The differentially expressed genes(DEG)between breast cancer samples and normal tissue samples were screened by GEO2R tools.The enrichment analysis and pathway annotation were performed to function differential genes by DAVID online database,and protein interaction network(PPI)web tools STRING and Cytoscape software were constructed.The hub genes were selected and combined with the Kaplan-Meier plotter database for further analysis and verification.Results A total of 127 differentially expressed genes were screened,of which 36 were up-regulated and 91 were down-regulated.The Cytoscape software plug-in cytoHubba was used to re-screen,and AURKA,CDK1,PCNA,TOP2A,HMMR,RRM2,PRC1,MCM4,GINS2,SMC4 were identified as hub genes.The survival analysis showed that except CDK1SMC4,the abnormal expressions of other hub genes were significantly associated with overall survival(OS)of breast cancer patient.Conclusion It is demonstrated that abnormal expressions of screened hub gene,may be involved in development and progression of breast cancer,which may serve as potential predictors and therapeutic targets for further research of breast cancer.