MicroRNA-mRNA interactions underlying colorectal cancer molecular subtypes.
MicroRNA-mRNA interactions underlying colorectal cancer molecular subtypes.
复制标题
DOI：
10.1038/ncomms9878
复制
发表时间：
2015-11-17
影响因子：
16.6
通讯作者：
Medico E
中科院分区：
文献类型：
--
作者：
Cantini L;Isella C;Petti C;Picco G;Chiola S;Ficarra E;Caselle M;Medico E
大肠癌（CRC）的转录亚型最近已确定的基因表达谱。在这里，我们描述了一个分析管道，microRNA主调节分析（MMRA），开发用于搜索潜在驱动CRC亚型的microRNA。从microRNA-mRNA肿瘤表达数据集开始，MMRA通过评估其亚型特异性表达、亚型mRNA特征的靶向富集和基于网络分析的对亚型基因表达的贡献来识别候选调节microRNA。当应用于450个样本的CRC数据集时，通过3种不同的转录分类器分配给亚型，MMRA识别出24种候选microRNA，在大多数情况下在干细胞/锯齿状/间充质（SSM）预后不良亚型中下调。在CRC细胞系中的功能验证证实了通过miR-194、miR-200 b、miR-203和miR-429下调SSM亚型，它们共享介导该效应的靶基因和途径。这些结果表明，通过结合统计检验、靶标预测和网络分析，MMRA有效地鉴定了与癌症亚型功能相关的microRNA。 结直肠癌亚型可以通过其不同的生物学和分子特性来区分。在这里，作者介绍了microRNA主调节分析，这是一种识别驱动亚型特异性基因表达和癌症变异的microRNA的工具。
Colorectal cancer (CRC) transcriptional subtypes have been recently identified by gene expression profiling. Here we describe an analytical pipeline, microRNA master regulator analysis (MMRA), developed to search for microRNAs potentially driving CRC subtypes. Starting from a microRNA–mRNA tumour expression data set, MMRA identifies candidate regulator microRNAs by assessing their subtype-specific expression, target enrichment in subtype mRNA signatures and network analysis-based contribution to subtype gene expression. When applied to a CRC data set of 450 samples, assigned to subtypes by 3 different transcriptional classifiers, MMRA identifies 24 candidate microRNAs, in most cases downregulated in the stem/serrated/mesenchymal (SSM) poor prognosis subtype. Functional validation in CRC cell lines confirms downregulation of the SSM subtype by miR-194, miR-200b, miR-203 and miR-429, which share target genes and pathways mediating this effect. These results show that, by combining statistical tests, target prediction and network analysis, MMRA effectively identifies microRNAs functionally associated to cancer subtypes. Colorectal cancer subtypes can be distinguished by their different biological and molecular properties. Here the authors present microRNA Master Regulator Analysis, a tool to identify microRNAs driving subtype-specific gene expression and cancer variation.
影响因子：
3
作者：
Corà D;Herrmann C;Dieterich C;Di Cunto F;Provero P;Caselle M
通讯作者：
Caselle M