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一个 miRNA 调控网络解释了失调的 miRNA 如何扰乱多种癌症中的致癌过程。

A miRNA-regulatory network explains how dysregulated miRNAs perturb oncogenic processes across diverse cancers.

机构信息

Institute for Systems Biology, Seattle, WA 98109-5234, USA.

出版信息

Genome Res. 2012 Nov;22(11):2302-14. doi: 10.1101/gr.133991.111. Epub 2012 Jun 28.

DOI:10.1101/gr.133991.111
PMID:22745231
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3483559/
Abstract

Genes regulated by the same miRNA can be discovered by virtue of their coexpression at the transcriptional level and the presence of a conserved miRNA-binding site in their 3' UTRs. Using this principle we have integrated the three best performing and complementary algorithms into a framework for inference of regulation by miRNAs (FIRM) from sets of coexpressed genes. We demonstrate the utility of FIRM by inferring a cancer-miRNA regulatory network through the analysis of 2240 gene coexpression signatures from 46 cancers. By analyzing this network for functional enrichment of known hallmarks of cancer we have discovered a subset of 13 miRNAs that regulate oncogenic processes across diverse cancers. We have performed experiments to test predictions from this miRNA-regulatory network to demonstrate that miRNAs of the miR-29 family (miR-29a, miR-29b, and miR-29c) regulate specific genes associated with tissue invasion and metastasis in lung adenocarcinoma. Further, we highlight the specificity of using FIRM inferences to identify miRNA-regulated genes by experimentally validating that miR-767-5p, which partially shares the miR-29 seed sequence, regulates only a subset of miR-29 targets. By providing mechanistic linkage between miRNA dysregulation in cancer, their binding sites in the 3'UTRs of specific sets of coexpressed genes, and their associations with known hallmarks of cancer, FIRM, and the inferred cancer miRNA-regulatory network will serve as a powerful public resource for discovery of potential cancer biomarkers.

摘要

通过共表达在转录水平上的基因和 3'UTR 中存在保守的 miRNA 结合位点,可以发现受同一 miRNA 调控的基因。利用这一原理,我们将三种表现最佳和互补的算法整合到一个 miRNA 调控推断(FIRM)框架中,用于从共表达基因集中推断调控。我们通过分析来自 46 种癌症的 2240 个基因共表达特征来推断癌症 miRNA 调控网络,从而证明了 FIRM 的实用性。通过分析该网络对癌症已知标志的功能富集,我们发现了一组 13 个 miRNA,它们在多种癌症中调节致癌过程。我们已经进行了实验来测试来自这个 miRNA 调控网络的预测,以证明 miR-29 家族(miR-29a、miR-29b 和 miR-29c)的 miRNA 调节与肺腺癌组织侵袭和转移相关的特定基因。此外,我们通过实验验证 miR-767-5p 只调节 miR-29 靶基因的一部分,突出了使用 FIRM 推断来识别 miRNA 调控基因的特异性,miR-767-5p 部分共享 miR-29 种子序列。通过提供癌症中 miRNA 失调、其在特定共表达基因集 3'UTR 中的结合位点以及它们与已知癌症标志的关联之间的机制联系,FIRM 和推断的癌症 miRNA 调控网络将成为发现潜在癌症生物标志物的强大公共资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/876ba6baf624/2302fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/1f70fcb8c106/2302fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/e517684d5169/2302fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/954d7c1c8a19/2302fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/1e1f464f8da7/2302fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/e8bb8b73eb46/2302fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/876ba6baf624/2302fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/1f70fcb8c106/2302fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/e517684d5169/2302fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/954d7c1c8a19/2302fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/1e1f464f8da7/2302fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/e8bb8b73eb46/2302fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4d/3483559/876ba6baf624/2302fig6.jpg

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