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Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
Published on: June 16, 2011
MERIT: Systematic Analysis and Characterization of Mutational Effect on RNA Interactome Topology
Yongsheng Li1,2, Daniel J McGrail2, Juan Xu1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Abstract:
The interaction between RNA-binding proteins (RBPs) and RNA plays an important role in regulating cellular function. However, decoding genome-wide protein-RNA regulatory networks as well as how cancer-related mutations impair RNA regulatory activities in hepatocellular carcinoma (HCC) remains mostly undetermined. We explored the genetic alteration patterns of RBPs and found that deleterious mutations are likely to occur on the surface of RBPs. We then constructed protein-RNA interactome networks by integration of target binding screens and expression profiles. Network analysis highlights regulatory principles among interacting RBPs. In addition, somatic mutations selectively target functionally important genes (cancer genes, core fitness genes, or conserved genes) and perturb the RBP-gene regulatory networks in cancer. These regulatory patterns were further validated using independent data. A computational method (Mutational Effect on RNA Interactome Topology) and a web-based, user-friendly resource were further proposed to analyze the RBP-gene regulatory networks across cancer types. Pan-cancer analysis also suggests that cancer cells selectively target "vulnerability" genes to perturb protein-RNA interactome that is involved in cancer hallmark-related functions. Specifically, we experimentally validated four pairs of RBP-gene interactions perturbed by mutations in HCC, which play critical roles in cell proliferation. Based on the expression of perturbed RBP and target genes, we identified three subtypes of HCC with different survival rates. Conclusion: Our results provide a valuable resource for characterizing somatic mutation-perturbed protein-RNA regulatory networks in HCC, yielding valuable insights into the genotype-phenotype relationships underlying human cancer, and potential biomarkers for precision medicine.
Insights
Cancer mutations disrupt protein-RNA interactions in hepatocellular carcinoma (HCC). This study decodes these networks, revealing how mutations impact gene regulation and identifying HCC subtypes with distinct survival rates for precision medicine.
Area of Science:
- Genomics
- Cancer Biology
- Molecular Networks
Background:
- Protein-RNA interactions are crucial for cellular function.
- Understanding these networks in hepatocellular carcinoma (HCC) and the impact of cancer mutations is limited.
Purpose of the Study:
- To decode genome-wide protein-RNA regulatory networks in HCC.
- To investigate how cancer-related mutations affect RNA regulatory activities.
- To identify potential biomarkers for precision medicine in HCC.
Main Methods:
- Analysis of RBP genetic alteration patterns.
- Construction of protein-RNA interactome networks using binding screens and expression data.
- Network analysis and validation using independent datasets.
- Development of a computational method (Mutational Effect on RNA Interactome Topology) and web resource.
Main Results:
- Deleterious mutations often occur on RBP surfaces.
- Somatic mutations selectively target important genes, perturbing RBP-gene regulatory networks.
- Cancer cells exploit 'vulnerability' genes to disrupt protein-RNA interactomes involved in cancer hallmarks.
- Experimentally validated RBP-gene interactions perturbed by mutations in HCC, impacting cell proliferation.
- Identified three HCC subtypes based on perturbed RBP and target gene expression, correlating with survival rates.
Conclusions:
- Provides a resource for analyzing somatic mutation-perturbed protein-RNA networks in HCC.
- Offers insights into genotype-phenotype relationships in cancer.
- Highlights potential biomarkers for precision medicine in HCC.
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