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从高通量实验数据中鉴定和分析 Myc 和 microRNAs 的调控网络。

Identification and analysis of the regulatory network of Myc and microRNAs from high-throughput experimental data.

机构信息

School of Life Sciences and Bioengineering, Southwest Jiaotong University, Chengdu 610031, PR China.

出版信息

Comput Biol Med. 2013 Sep;43(9):1252-60. doi: 10.1016/j.compbiomed.2013.06.002. Epub 2013 Jun 13.

Abstract

As a transcription factor, c-Myc exerts significant influence in cancer development by regulating transcription of a large number of target genes including microRNAs. However, details of regulatory networks composed of Myc, microRNAs, and microRNA target genes are still unclear. Here, at system level, we built a comprehensive Myc-regulated miRNAs (Myc-miRNAs) regulatory network through the integration of experimentally validated high-throughput data and computational predictions. Using miRNA genomic information with ChIP-PET, we identified 30 Myc-miRNAs and found most of these Myc-miRNAs target genes were significantly enriched in cell cycle, apoptosis, cell proliferation GO terms and Myc-regulated signaling pathways, using gene sets enrichment analysis. We found most Myc-miRNAs involved in Myc-related cancer pathways expressed abnormally in Myc-associated tumors through the integration of diverse types of experimental data. Based upon Myc target genes identified by ChIP-chip assays, we identified that 1031 Myc-miRNAs feed-forward loops (FFLs) were significantly different from those obtained by chance; also, 11 high-quality FFLs were extracted from experimentally validated interactions. Finally, we built the miRNA-protein interaction network of experimentally validated Myc-miRNAs and discussed the more complex network composed of several FFLs networks. As shown in this study, we performed comprehensive analysis of the Myc-miRNAs regulatory network and provided potential Myc-miRNAs target genes which were involved in Myc pathway and cancer-related biological processes.

摘要

作为转录因子,c-Myc 通过调节大量靶基因(包括 microRNAs)的转录,对癌症的发生发展产生重要影响。然而,Myc、microRNAs 和 microRNA 靶基因组成的调控网络的细节仍然不清楚。在这里,我们在系统水平上,通过整合实验验证的高通量数据和计算预测,构建了一个全面的 Myc 调控 microRNAs(Myc-miRNAs)调控网络。利用 ChIP-PET 的 miRNA 基因组信息,我们鉴定出 30 个 Myc-miRNAs,通过基因集富集分析发现,这些 Myc-miRNAs 的靶基因大多显著富集在细胞周期、凋亡、细胞增殖等 GO 术语和 Myc 调控的信号通路中。通过整合多种类型的实验数据,我们发现大多数与 Myc 相关的癌症途径中的 Myc-miRNAs 在 Myc 相关肿瘤中表达异常。基于 ChIP-chip 实验鉴定的 Myc 靶基因,我们发现 1031 个 Myc-miRNAs 的前馈环(FFL)与随机获得的结果有显著差异;此外,还从实验验证的相互作用中提取了 11 个高质量的 FFL。最后,我们构建了实验验证的 Myc-miRNAs 的 miRNA-蛋白质相互作用网络,并讨论了由几个 FFL 网络组成的更复杂的网络。如本研究所示,我们对 Myc-miRNAs 调控网络进行了全面分析,并提供了潜在的 Myc-miRNAs 靶基因,这些靶基因参与 Myc 途径和癌症相关的生物学过程。

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