American Association for Cancer Research
can-20-0371_supplementary_data_suppst2.txt (19.4 MB)

Supplementary Data from Landscape of MicroRNA Regulatory Network Architecture and Functional Rerouting in Cancer

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posted on 2023-03-31, 04:47 authored by Xu Hua, Yongsheng Li, Sairahul R. Pentaparthi, Daniel J. McGrail, Raymond Zou, Li Guo, Aditya Shrawat, Kara M. Cirillo, Qing Li, Akshay Bhat, Min Xu, Dan Qi, Ashok Singh, Francis McGrath, Steven Andrews, Kyaw Lwin Aung, Jishnu Das, Yunyun Zhou, Alessia Lodi, Gordon B. Mills, S. Gail Eckhardt, Marc L. Mendillo, Stefano Tiziani, Erxi Wu, Jason H. Huang, Nidhi Sahni, S. Stephen Yi

Supplementary Table S2


National Institute of General Medical Sciences (NIGMS)

United States Department of Health and Human Services

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Susan G. Komen (SGK)

Ovarian Cancer Research Alliance (OCRA)

U.S. Department of Defense (DOD)

Cancer Prevention and Research Institute of Texas (CPRIT)

National Cancer Institute (NCI)

United States Department of Health and Human Services

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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.

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