乳腺癌差异表达miRNA在预后中的意义
投稿时间:2017-02-10  修订日期:2017-04-03  点此下载全文
引用本文:马跃,高英静,何浪.乳腺癌差异表达miRNA在预后中的意义[J].医学研究杂志,2018,47(1):39-44
DOI: 10.11969/j.issn.1673-548X.2018.01.011
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作者单位E-mail
马跃 610500 成都医学院基础医学院  
高英静 610500 成都医学院基础医学院  
何浪 610500 成都医学院生物医学系 helang79@sohu.com 
基金项目:国家自然科学基金资助项目(81201702);国家级创新性实验项目(201313705009)
中文摘要:目的 运用生物信息学方法研究复发转移乳腺癌组织中的差异表达MicroRNAs,预测其在乳腺癌预后中的分子调控网络。方法 从GEO数据库中获取乳腺癌组织MiRNA表达谱,包括131例10年内无远处转移复发者,79例10年内有复发者。GEO2R在线分析工具筛选差异表达MiRNA,靶基因预测验证数据库预测miRNA靶基因,使用DAVID工具的基因功能注释和通路富集方法对靶基因进行分析。TF-miRNA调控数据库寻找其上游转录因子,Cytoscape软件构建互作网络。结果 复发转移组乳腺癌组织共筛选到差异表达的miRNA 5个,其中表达上调3个,表达下调2个。得到4个相关上游转录因子HIF1A、EGR1、FOXM1、ESR2,与差异miRNA共调控154个的靶基因。靶基因功能集中在BMP信号通路,TGF-β信号通路,细胞骨架组装功能和Rho GTPases信号通路。结论 差异性表达的miRNA包括hsa-miR-210、hsa-miR-33a、hsa-miR-32、hsa-miR-135a、hsa-miR-30a-3p,利用生物信息学方法,能够有效获取信息,为乳腺癌的治疗及预后监测的新策略研究开辟新思路。
中文关键词:乳腺癌  预后  microRNAs  调控网络  生物信息学
 
Differential Expression of miRNA in Breast Cancer and the Significance in Prognosis
Abstract:Objective To explore changes in the expression of MicroRNAs related to prognosis in breast cancer tissue. Methods Microarray data of breast cancer tissue were downloaded from the GEO database, including MicroRNAs profilings of 10 year distant-relapse free survival and the controls. The differentially-expressed MicroRNAs were identified use GEO2R tool. The upstream transcription factor(TF) and downstream target genes of differentially-expressed MicroRNAs were investigated with prediction websites. Function and pathway of target genes were annotated by DAVID. Regulating network of TF-miRNA-target gene were constructed by cytoscape. Results A total of 5 miRNAs were differentially expressed (3 up-and 2 down-regulated). 5 upstream TFs and 154 downstream target genes were found respectively. Functional enrichment analysis indicated that negative regulation of BMP signaling pathway, cytoskeleton organization, signaling by TGF beta, signaling by Rho GTPases were involved. Conclusion hsa-miR-210,hsa-miR-33a,hsa-miR-32,hsa-miR-135a,hsa-miR-30a-3p were the differentially-expressed miRNAs relevant to prognosis of breast cancer. Our study systemically characterize miRNAs expression changes using bioinformatics methods to the benefit of the diagnosis and treatment for breast caner prognosis.
keywords:Breast cancer  Prognosis  MicroRNAs  Regulating network  Bioinformatics
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