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Updated: Aug 24, 2025

CRISPR Gene Editing Tool for MicroRNA Cluster Network Analysis
Published on: April 25, 2022
Landscape of MicroRNA Regulatory Network Architecture and Functional Rerouting in Cancer
Xu Hua1, Yongsheng Li2, Sairahul R Pentaparthi2
1Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Abstract:
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.
Significance:
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.
Insights
Somatic mutations in microRNAs (miRNAs) and their targets significantly alter cancer gene networks. This study identifies driver mutations in miRNA regulatory networks, aiding noncoding biomarker discovery and therapeutic drug design.
Area of Science:
- Genomics
- Cancer Biology
- Bioinformatics
Background:
- Somatic mutations drive cancer, but the role of mutations in microRNAs (miRNAs) and their binding sites is largely unknown.
- MicroRNAs regulate gene expression, and their dysregulation is implicated in various cancers.
Purpose of the Study:
- To systematically analyze the impact of mutations in miRNAs and their target sites across 30 cancer types.
- To build cancer-specific miRNA regulatory networks and identify driver mutations affecting these networks.
Main Methods:
- Construction of detailed cancer-specific miRNA regulatory networks.
- Mapping over 3.5 million mutations to miRNA-gene interactions (mGI) across 9,819 cancer samples.
- Utilizing linear regression to identify driver mutations perturbing miRNA networks.
Main Results:
- Identified 148 candidate driver mutations significantly affecting miRNA regulatory networks.
- Observed a mutually exclusive pattern between mutations in miRNAs and their target genes.
- Found that mutated driver gene targets in 3' UTRs act as tumor suppressors and are downregulated in cancer.
Conclusions:
- Mutations in noncoding regions, particularly miRNAs and their 3' UTR targets, play a significant role in cancer progression.
- The developed miRNA-gene interaction map (mGI-map) provides a valuable resource for identifying noncoding biomarkers.
- Findings support novel therapeutic strategies targeting miRNA regulatory networks for cancer treatment.
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