Landscape of MicroRNA Regulatory Network Architecture and Functional Rerouting in Cancer.
Landscape of MicroRNA Regulatory Network Architecture and Functional Rerouting in Cancer.
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癌症中 MicroRNA 调控网络架构和功能重路由的概况。
DOI：
10.1158/0008-5472.can-20-0371
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发表时间：
2023-01-04
期刊：
影响因子：
11.2
通讯作者：
中科院分区：
文献类型：
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作者：
体细胞突变是癌症发展的主要来源，并且已经在蛋白质编码区中鉴定出许多驱动突变。然而，位于microRNAs（miRNAs）中的突变的功能及其在整个人类基因组中的靶结合位点在很大程度上仍然未知。在这里，我们在30种癌症类型中建立了详细的癌症特异性miRNA调控网络，以系统地分析miRNA突变及其在3' UTR，CDS和5' UTR区域中的靶位点的影响。来自9，819个样本的总共3，518，261个突变被映射到miRNA-基因相互作用（mGI）。在几乎所有的癌症类型中，miRNAs的突变与其靶基因的突变显示出相互排斥的模式。线性回归方法确定了148个候选驱动突变，这些突变可以显著干扰miRNA调控网络。3 'UTR中的驱动突变通过改变RNA结合能和靶基因的表达发挥作用。最后，3'UTR中突变的驱动基因靶标在癌症中显著下调，并在癌症进展期间作为肿瘤抑制因子发挥作用，这表明潜在的miRNA候选物具有显著的临床意义。开发了一个方便用户的开放式门户网站（mGI地图），以便利进一步使用这一数据资源。总之，这些结果将有助于新的非编码生物标志物的鉴定和靶向miRNA调控网络的治疗药物设计。
Somatic mutations are a major source of cancer development, and many driver mutations have been identified in protein coding regions. However, the function of mutations located in microRNAs (miRNAs) and their target binding sites throughout the human genome remains largely unknown. Here, we built detailed cancer-specific miRNA regulatory networks across 30 cancer types to systematically analyze the effect of mutations in miRNAs and their target sites in 3’ UTR, CDS, and 5’ UTR regions. A total of 3,518,261 mutations from 9,819 samples were mapped to miRNA-gene interactions (mGI). Mutations in miRNAs showed a mutually exclusive pattern with mutations in their target genes in almost all cancer types. A linear regression method identified 148 candidate driver mutations that can significantly perturb miRNA regulatory networks. Driver mutations in 3’UTRs played their roles by altering RNA binding energy and the expression of target genes. Finally, mutated driver gene targets in 3’ UTRs were significantly downregulated in cancer and functioned as tumor suppressors during cancer progression, suggesting potential miRNA candidates with significant clinical implications. A user-friendly, open-access web portal (mGI-map) was developed to facilitate further use of this data resource. Together, these results will facilitate novel non-coding biomarker identification and therapeutic drug design targeting the miRNA regulatory network.