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The therapeutic significance of mutational signatures from DNA repair deficiency in cancer

Author

Listed:
  • Jennifer Ma

    (Memorial Sloan Kettering Cancer Center)

  • Jeremy Setton

    (Memorial Sloan Kettering Cancer Center)

  • Nancy Y. Lee

    (Memorial Sloan Kettering Cancer Center)

  • Nadeem Riaz

    (Memorial Sloan Kettering Cancer Center)

  • Simon N. Powell

    (Memorial Sloan Kettering Cancer Center)

Abstract

Cancer is fundamentally a disease of the genome and inherited deficiencies in DNA repair pathways are well established to increase lifetime cancer risk. Computational analysis of pan-cancer data has identified signatures of mutational processes thought to be responsible for the pattern of mutations in any given cancer. These analyses identified altered DNA repair pathways in a much broader spectrum of cancers than previously appreciated with significant therapeutic implications. The development of DNA repair deficiency biomarkers is critical to the implementation of therapeutic targeting of repair-deficient tumors, using either DNA damaging agents or immunotherapy for the personalization of cancer therapy.

Suggested Citation

  • Jennifer Ma & Jeremy Setton & Nancy Y. Lee & Nadeem Riaz & Simon N. Powell, 2018. "The therapeutic significance of mutational signatures from DNA repair deficiency in cancer," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-05228-y
    DOI: 10.1038/s41467-018-05228-y
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    Cited by:

    1. Gal Gilad & Mark D M Leiserson & Roded Sharan, 2021. "A data-driven approach for constructing mutation categories for mutational signature analysis," PLOS Computational Biology, Public Library of Science, vol. 17(10), pages 1-15, October.
    2. Qingli Guo & Eszter Lakatos & Ibrahim Al Bakir & Kit Curtius & Trevor A. Graham & Ville Mustonen, 2022. "The mutational signatures of formalin fixation on the human genome," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    3. Rotem Katzir & Noam Rudberg & Keren Yizhak, 2022. "Estimating tumor mutational burden from RNA-sequencing without a matched-normal sample," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

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