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Cell-of-origin chromatin organization shapes the mutational landscape of cancer

Author

Listed:
  • Paz Polak

    (Brigham & Women’s Hospital and Harvard Medical School
    The Broad Institute of MIT and Harvard)

  • Rosa Karlić

    (Bioinformatics Group, Faculty of Science, University of Zagreb, Horvatovac 102a, 10000 Zagreb, Croatia)

  • Amnon Koren

    (The Broad Institute of MIT and Harvard
    Harvard Medical School)

  • Robert Thurman

    (University of Washington)

  • Richard Sandstrom

    (University of Washington)

  • Michael S. Lawrence

    (The Broad Institute of MIT and Harvard)

  • Alex Reynolds

    (University of Washington)

  • Eric Rynes

    (University of Washington)

  • Kristian Vlahoviček

    (Bioinformatics Group, Faculty of Science, University of Zagreb, Horvatovac 102a, 10000 Zagreb, Croatia
    University of Oslo, P.O. Box 1080, Blindern, NO-0316 Oslo, Norway)

  • John A. Stamatoyannopoulos

    (University of Washington
    University of Washington)

  • Shamil R. Sunyaev

    (Brigham & Women’s Hospital and Harvard Medical School
    The Broad Institute of MIT and Harvard)

Abstract

An analysis of cell-type-specific epigenomic features reveals a relationship between epigenomic and mutational profiles; chromatin characteristics can explain a large proportion of mutational variance in cancer genomes and the mutational distribution can identify the probable cell type from which a given cancer originated from.

Suggested Citation

  • Paz Polak & Rosa Karlić & Amnon Koren & Robert Thurman & Richard Sandstrom & Michael S. Lawrence & Alex Reynolds & Eric Rynes & Kristian Vlahoviček & John A. Stamatoyannopoulos & Shamil R. Sunyaev, 2015. "Cell-of-origin chromatin organization shapes the mutational landscape of cancer," Nature, Nature, vol. 518(7539), pages 360-364, February.
    • Handle: RePEc:nat:nature:v:518:y:2015:i:7539:d:10.1038_nature14221
    DOI: 10.1038/nature14221
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    Cited by:

    1. Sheng Wang & Sebastian O. Klein & Sylvia Urban & Maximilian Staudt & Nicolas P. F. Barthes & Dominica Willmann & Johannes Bacher & Manuela Sum & Helena Bauer & Ling Peng & Georg A. Rennar & Christian , 2024. "Structure-guided design of a selective inhibitor of the methyltransferase KMT9 with cellular activity," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    2. Koon-Kiu Yan & Shaoke Lou & Mark Gerstein, 2017. "MrTADFinder: A network modularity based approach to identify topologically associating domains in multiple resolutions," PLOS Computational Biology, Public Library of Science, vol. 13(7), pages 1-22, July.
    3. Luan Nguyen & Arne Hoeck & Edwin Cuppen, 2022. "Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation features," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Kseniia Cheloshkina & Maria Poptsova, 2021. "Comprehensive analysis of cancer breakpoints reveals signatures of genetic and epigenetic contribution to cancer genome rearrangements," PLOS Computational Biology, Public Library of Science, vol. 17(3), pages 1-23, March.
    5. Miguel M. Álvarez & Josep Biayna & Fran Supek, 2022. "TP53-dependent toxicity of CRISPR/Cas9 cuts is differential across genomic loci and can confound genetic screening," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    6. Alexander Martinez-Fundichely & Austin Dixon & Ekta Khurana, 2022. "Modeling tissue-specific breakpoint proximity of structural variations from whole-genomes to identify cancer drivers," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    7. Michael Habig & Cecile Lorrain & Alice Feurtey & Jovan Komluski & Eva H. Stukenbrock, 2021. "Epigenetic modifications affect the rate of spontaneous mutations in a pathogenic fungus," Nature Communications, Nature, vol. 12(1), pages 1-13, December.

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