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Interpreting pathways to discover cancer driver genes with Moonlight

Author

Listed:
  • Antonio Colaprico

    (Interuniversity Institute of Bioinformatics in Brussels (IB)2
    Université Libre de Bruxelles (ULB)
    University of Miami, Miller School of Medicine)

  • Catharina Olsen

    (Interuniversity Institute of Bioinformatics in Brussels (IB)2
    Université Libre de Bruxelles (ULB)
    Vrije Universiteit Brussel, UZ Brussel
    Brussels Interuniversity Genomics High Throughput core (BRIGHTcore), VUB-ULB)

  • Matthew H. Bailey

    (Washington University in St. Louis
    Washington University)

  • Gabriel J. Odom

    (University of Miami, Miller School of Medicine
    Florida International University)

  • Thilde Terkelsen

    (Computational Biology Laboratory, and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center)

  • Tiago C. Silva

    (University of Miami, Miller School of Medicine
    University of Sao Paulo)

  • André V. Olsen

    (Computational Biology Laboratory, and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center)

  • Laura Cantini

    (Institut Curie
    INSERM, U900
    Mines ParisTech
    Computational Systems Biology Team, Institut de Biologie de l’Ecole Normale Supérieure, CNRS UMR8197, INSERM U1024, Ecole Normale Supérieure, Paris Sciences et Lettres Research University)

  • Andrei Zinovyev

    (Institut Curie
    INSERM, U900
    Mines ParisTech)

  • Emmanuel Barillot

    (Institut Curie
    INSERM, U900
    Mines ParisTech)

  • Houtan Noushmehr

    (University of Sao Paulo
    Brain Tumor Center, Henry Ford Health System)

  • Gloria Bertoli

    (Institute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR))

  • Isabella Castiglioni

    (Institute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR))

  • Claudia Cava

    (Institute of Molecular Bioimaging and Physiology of the National Research Council (IBFM-CNR))

  • Gianluca Bontempi

    (Interuniversity Institute of Bioinformatics in Brussels (IB)2
    Université Libre de Bruxelles (ULB))

  • Xi Steven Chen

    (University of Miami, Miller School of Medicine
    University of Miami Miller School of Medicine)

  • Elena Papaleo

    (Computational Biology Laboratory, and Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center
    University of Copenhagen)

Abstract

Cancer driver gene alterations influence cancer development, occurring in oncogenes, tumor suppressors, and dual role genes. Discovering dual role cancer genes is difficult because of their elusive context-dependent behavior. We define oncogenic mediators as genes controlling biological processes. With them, we classify cancer driver genes, unveiling their roles in cancer mechanisms. To this end, we present Moonlight, a tool that incorporates multiple -omics data to identify critical cancer driver genes. With Moonlight, we analyze 8000+ tumor samples from 18 cancer types, discovering 3310 oncogenic mediators, 151 having dual roles. By incorporating additional data (amplification, mutation, DNA methylation, chromatin accessibility), we reveal 1000+ cancer driver genes, corroborating known molecular mechanisms. Additionally, we confirm critical cancer driver genes by analysing cell-line datasets. We discover inactivation of tumor suppressors in intron regions and that tissue type and subtype indicate dual role status. These findings help explain tumor heterogeneity and could guide therapeutic decisions.

Suggested Citation

  • Antonio Colaprico & Catharina Olsen & Matthew H. Bailey & Gabriel J. Odom & Thilde Terkelsen & Tiago C. Silva & André V. Olsen & Laura Cantini & Andrei Zinovyev & Emmanuel Barillot & Houtan Noushmehr , 2020. "Interpreting pathways to discover cancer driver genes with Moonlight," Nature Communications, Nature, vol. 11(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-019-13803-0
    DOI: 10.1038/s41467-019-13803-0
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    Cited by:

    1. Brian D. Lehmann & Antonio Colaprico & Tiago C. Silva & Jianjiao Chen & Hanbing An & Yuguang Ban & Hanchen Huang & Lily Wang & Jamaal L. James & Justin M. Balko & Paula I. Gonzalez-Ericsson & Melinda , 2021. "Multi-omics analysis identifies therapeutic vulnerabilities in triple-negative breast cancer subtypes," Nature Communications, Nature, vol. 12(1), pages 1-18, December.

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