ER表达状态乳腺癌差异表达microRNAs相关信号通路的分析

Bioinformatics-based analysis of signaling pathways for differently expressed microRNAs between different ER status breast cancers

目的:利用生物信息的方法,建立一种对不同ER表达状态乳腺癌差异表达microRNAs生物学功能和信号通路系统分析的方法,探讨microRNAs在不同ER状态中可能发挥的调控作用。方法:通过文献挖掘,找出不同ER表达状态乳腺癌差异表达microRNAs,利用预测软件TargetScan、PicTar、miRanda和TarBase数据库得出microRNAs可能靶向的基因集,对靶基因集进行去除随机化的富集分析后,再利用DAVID数据库进行相关生物学功能和信号通路分析。结果:通过文献挖掘的方法找到了5个不同ER表达状态乳腺癌microRNAs差异表达数据集,分别包含了11、43、25、6及19个差异表达的microRNAs。经过靶基因预测及富集后,得到的不同microRNAs靶基因集分别包括1 553、1 750、1 905、1 250和1 826个靶基因。进一步功能及通路分析发现,这些靶基因集可能参与转录相关蛋白质定位及转移、RNA代谢、细胞周期、细胞凋亡和细胞分裂等多个生物学过程,并发现3条共同的BIOCARTA细胞信号通路可能与ER表达调节相关。结论:找到了不同ER表达状态乳腺癌差异表达的microRNAs,并利用生物信息学方法对这些mi-croRNAs进行系统分析,为进一步研究microRNAs在乳腺癌不同分子亚型分化中的调控机制奠定基础。

OBJECTIVE： To develop a bioinformatics-based approach for analysis of cellular functions and pathways affected by differently expressed microRNAs in different ER status of breast cancers and explore the regulatory roles of microRNAs. METHODS： By literature metrological methods,aberrant expressed microRNAs were collected. By target prediction algorithm TargetScan,PicTar and miRanda, TarBase database and data enrichment analysis as well as target gene sets of differently expressed microRNAs were built. Then by usijag of DAVID database, Gene Ontology categories and biological functions as well as signaling pathways that are probably regulated by differently expressed microRNAs were analysed. RESULTS： Five sets of microRNAs including 11,43,25,6 and 19 respectively were found. After microR NAs target prediction and a two-step data enrichment procedure,1 553,1 750,1 905,1 250 and 1 826 target genes of 5 mi croRNA sets were collected. Gene Ontology analysis suggested these genes might involve in transcription, protein location and transport, RNA metabolism, cell cycle and apoptosis. Also, 3 BIOCARTA signal pathways correlating with ER status were found. CONCLUSION： This bioinformatics-based approach for analysis of differently microRNAs in different ER status breast cancers provides a new method for biological interpretation of microRNAs profiling data,and may be helpful to understand the regulatory roles of mieroRNAs in different molecular subtypes of breast cancers.