Identification of key genes in breast cancer of prognostic value
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摘要：
目的:筛选与乳腺癌发病相关的关键基因,为研究乳腺癌的诊疗提供新的潜在分子靶标.方法:使用GEO2R在线工具比较乳腺癌与正常乳腺组织基因表达情况,进行差异显著性分析,利用基因功能注释工具DAVID对差异基因进行GO和KEGG富集分析.通过STRING数据库构建差异基因的蛋白互作网络,基于最大团中心性(maximal clique centrality,MCC)算法鉴别关键基因,利用Kaplan Meier生存分析验证关键基因对患者生存时间的影响.结果:乳腺癌基因表达差异分析共产生491个差异基因,其中有254个上调,237个下调.GO富集分析表明差异基因显著富集于肿瘤相关的生物学过程、细胞组分和分子功能,KEGG通路富集分析主要集中于PI3K-Akt信号通路、黏附斑和癌症通路.基于MCC算法共选取10个关键基因,其中的4个基因(ISG15,IFIT1,GBP1和IFI27)过表达与患者生存时间显著降低密切相关(P<0.05).结论:共鉴别了4个与乳腺癌发病密切相关的关键基因,相关研究结果可为研究乳腺癌的诊疗提供新的潜在分子靶标.
Objective:To identify key genes and pathways involved in the pathogenesis of breast cancer using bioinformatics methods.Methods:The GEO2R online tool was used to analyze the gene expression profiles of breast cancer.The differentially expressed genes(DEGs)was annotated by GO and KEGG enrichment analysis.The STRING database was used to construct a protein-protein interaction(PPI)network with the differentially expressed genes.The PPI network data was visualized using Cytoscape software.The key genes of the PPI network were identified based on MCC algorithm.The selected key genes were then subject to Kaplan Meier survival analysis to test the role of hub genes on survival time of breast cancer patients.Results:Differentially expressed analysis resulted in a total of 491 DEGs,of which 254 were up-regulated and 237 were down-regulated.GO enrichment analysis showed that these DEGs were significantly enriched in tumor-related biological processes,cellular components and molecular functions,and KEGG pathway enrichment analysis focused on PI3 K-Akt signaling pathway,adhesion plaques and cancer pathways.Based on the MCC algorithm,a total of 10 key genes were selected and only four of them has been shown to be associated with significantly decreased survival time of the breast cancer patients(P<0.05).The four key genes were ISG15,IFIT1,GBP1 and IFI27 respectively.Conclusion:This study resutts in identification four key genes contributing to the development of breast cancer.The discovery of these key genes provides new clues for studying the pathogenesis of breast cancer as well as potential molecular targets for treatment of the disease.
作者：
徐久成 李成长
Xu Jiucheng;Li Chengzhang(State Key Laboratory Cultivation Base for Cell Differentiation Regulation,College of Life Science,Henan Normal University,Xinxiang 453007,China;Engineering Lab of Intelligence Business&Internet of Things,Henan Province,Henan Normal University,Xinxiang 453007,China;Department of Physiology and Neurobiology,School of Basic Medicine,Xinxiang Medical University,Xinxiang 453003,China)
机构地区：
betway官方app 生命科学学院细胞分化调控省部共建国家重点实验室培育基地 betway官方app 计算机与信息工程学院河南省智慧商务与物联网工程实验室 新乡医学院基础医学院生理学与神经生物学教研室
出处：
《betway官方app 学报：自然科学版》 CAS 北大核心 2020年第2期27-33,F0002,共8页
基金：
国家自然科学基金(61976082,61370169,61772176,61402153)。
关键词：
乳腺癌 关键基因 PI3K
breast cancer hub genes PI3K
分类号：
TP391 [自动化与计算机技术—计算机应用技术]
