MERIT

Systematic Analysis and Characterization of Mutational Effect on RNA Interactome Topology

Yongsheng Li, Daniel J. McGrail, Juan Xu, Junyi Li, Ning Ning Liu, Ming Sun, Richard Lin, Rita Pancsa, Jiwei Zhang, Ju Seog Lee, Hui Wang, Gordon Mills, Xia Li, Song Yi, Nidhi Sahni

    Research output: Contribution to journalArticle

    3 Citations (Scopus)

    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.

    Original languageEnglish (US)
    Pages (from-to)532-546
    Number of pages15
    JournalHepatology
    Volume70
    Issue number2
    DOIs
    StatePublished - Jan 1 2019

    Fingerprint

    RNA-Binding Proteins
    RNA
    Hepatocellular Carcinoma
    Mutation
    Neoplasms
    Genes
    Precision Medicine
    Neoplasm Genes
    Tumor Biomarkers
    Cell Proliferation
    Genome

    ASJC Scopus subject areas

    • Hepatology

    Cite this

    Li, Y., McGrail, D. J., Xu, J., Li, J., Liu, N. N., Sun, M., ... Sahni, N. (2019). MERIT: Systematic Analysis and Characterization of Mutational Effect on RNA Interactome Topology. Hepatology, 70(2), 532-546. https://doi.org/10.1002/hep.30242

    MERIT : Systematic Analysis and Characterization of Mutational Effect on RNA Interactome Topology. / Li, Yongsheng; McGrail, Daniel J.; Xu, Juan; Li, Junyi; Liu, Ning Ning; Sun, Ming; Lin, Richard; Pancsa, Rita; Zhang, Jiwei; Lee, Ju Seog; Wang, Hui; Mills, Gordon; Li, Xia; Yi, Song; Sahni, Nidhi.

    In: Hepatology, Vol. 70, No. 2, 01.01.2019, p. 532-546.

    Research output: Contribution to journalArticle

    Li, Y, McGrail, DJ, Xu, J, Li, J, Liu, NN, Sun, M, Lin, R, Pancsa, R, Zhang, J, Lee, JS, Wang, H, Mills, G, Li, X, Yi, S & Sahni, N 2019, 'MERIT: Systematic Analysis and Characterization of Mutational Effect on RNA Interactome Topology', Hepatology, vol. 70, no. 2, pp. 532-546. https://doi.org/10.1002/hep.30242
    Li, Yongsheng ; McGrail, Daniel J. ; Xu, Juan ; Li, Junyi ; Liu, Ning Ning ; Sun, Ming ; Lin, Richard ; Pancsa, Rita ; Zhang, Jiwei ; Lee, Ju Seog ; Wang, Hui ; Mills, Gordon ; Li, Xia ; Yi, Song ; Sahni, Nidhi. / MERIT : Systematic Analysis and Characterization of Mutational Effect on RNA Interactome Topology. In: Hepatology. 2019 ; Vol. 70, No. 2. pp. 532-546.
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    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.",
    author = "Yongsheng Li and McGrail, {Daniel J.} and Juan Xu and Junyi Li and Liu, {Ning Ning} and Ming Sun and Richard Lin and Rita Pancsa and Jiwei Zhang and Lee, {Ju Seog} and Hui Wang and Gordon Mills and Xia Li and Song Yi and Nidhi Sahni",
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    AU - Li, Junyi

    AU - Liu, Ning Ning

    AU - Sun, Ming

    AU - Lin, Richard

    AU - Pancsa, Rita

    AU - Zhang, Jiwei

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    AU - Wang, Hui

    AU - Mills, Gordon

    AU - Li, Xia

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