Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Livestrong Cancer Institutes, Department of Oncology, Dell Medical School, The University of Texas at Austin, Austin, Texas.
Cancer Res. 2023 Jan 4;83(1):59-73. doi: 10.1158/0008-5472.CAN-20-0371.
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 miRNA 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' untranslated region (3' UTR), coding sequence (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 noncoding biomarker identification and therapeutic drug design targeting the miRNA regulatory networks.
A detailed miRNA-gene interaction map reveals extensive miRNA-mediated gene regulatory networks with mutation-induced perturbations across multiple cancers, serving as a resource for noncoding biomarker discovery and drug development.
体细胞突变是癌症发展的主要来源，许多驱动突变已在蛋白质编码区域被发现。然而，位于 miRNA 中的突变及其在人类基因组中靶结合位点的功能在很大程度上仍然未知。在这里，我们构建了详细的癌症特异性 miRNA 调控网络，涵盖 30 种癌症类型，以系统分析 miRNA 及其靶位点突变在 3'非翻译区（3'UTR）、编码序列（CDS）和 5'UTR 区域中的作用。共将 9819 个样本中的 3518261 个突变映射到 miRNA-基因相互作用（mGI）。在几乎所有癌症类型中，miRNA 中的突变与靶基因中的突变呈现相互排斥的模式。线性回归方法鉴定了 148 个候选驱动突变，这些突变可以显著扰乱 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来发挥作用。最后，在癌症中，3'UTR 中突变的驱动基因靶标显著下调，并在癌症进展中作为肿瘤抑制因子发挥作用，提示具有重要临床意义的潜在 miRNA 候选物。开发了一个用户友好的、开放获取的网络门户（mGI-map），以方便进一步使用此数据资源。总之，这些结果将促进针对 miRNA 调控网络的新型非编码生物标志物识别和治疗药物设计。
详细的 miRNA-基因相互作用图谱揭示了广泛的 miRNA 介导的基因调控网络，这些网络在多种癌症中受到突变诱导的干扰，可作为非编码生物标志物发现和药物开发的资源。
