1. Cancer Biology

Supervised mutational signatures for obesity and other tissue-specific etiological factors in cancer

  1. Bahman Afsari
  2. Albert Kuo
  3. YiFan Zhang
  4. Lu Li
  5. Kamel Lahouel
  6. Ludmila Danilova
  7. Alexander Favorov
  8. Thomas A Rosenquist
  9. Arthur P Grollman
  10. Ken W Kinzler
  11. Leslie Cope
  12. Bert Vogelstein
  13. Cristian Tomasetti  Is a corresponding author
  1. Johns Hopkins University, United States
  2. Johns Hopkins School of Medicine, United States
  3. Stony Brook University, United States
  4. Howard Hughes Medical Institute, Ludwig Center, United States
https://doi.org/10.7554/eLife.61082
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Cite this article
  1. Bahman Afsari
  2. Albert Kuo
  3. YiFan Zhang
  4. Lu Li
  5. Kamel Lahouel
  6. Ludmila Danilova
  7. Alexander Favorov
  8. Thomas A Rosenquist
  9. Arthur P Grollman
  10. Ken W Kinzler
  11. Leslie Cope
  12. Bert Vogelstein
  13. Cristian Tomasetti
(2021)
Supervised mutational signatures for obesity and other tissue-specific etiological factors in cancer
eLife 10:e61082.
https://doi.org/10.7554/eLife.61082
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Abstract

Determining the etiologic basis of the mutations that are responsible for cancer is one of the fundamental challenges in modern cancer research. Different mutational processes induce different types of DNA mutations, providing 'mutational signatures' that have led to key insights into cancer etiology. The most widely used signatures for assessing genomic data are based on unsupervised patterns that are then retrospectively correlated with certain features of cancer. We show here that supervised machine-learning techniques can identify signatures, called SuperSigs, that are more predictive than those currently available. Surprisingly, we found that aging yields different SuperSigs in different tissues, and the same is true for environmental exposures. We were able to discover SuperSigs associated with obesity, the most important lifestyle factor contributing to cancer in Western populations.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

The following previously published data sets were used
    1. Weinstein
    (2013) TCGA
    CDG @ https://portal.gdc.cancer.gov/.
    https://portal.gdc.cancer.gov/

Article and author information

Author details

  1. Bahman Afsari

    Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University, Baltimore, United States
    Competing interests
    No competing interests declared.

  2. Albert Kuo

    Department of Biostatistics, Johns Hopkins University, Baltimore, United States
    Competing interests
    No competing interests declared.

  3. YiFan Zhang

    Department of Biostatistics, Johns Hopkins University, Baltimore, United States
    Competing interests
    No competing interests declared.

  4. Lu Li

    Department of Biostatistics, Johns Hopkins University, Baltimore, United States
    Competing interests
    No competing interests declared.

  5. Kamel Lahouel

    Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University, Baltimore, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4339-5749

  6. Ludmila Danilova

    Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins School of Medicine, Baltimore, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2813-3094

  7. Alexander Favorov

    Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University, Baltimore, United States
    Competing interests
    No competing interests declared.

  8. Thomas A Rosenquist

    Department of Pharmacological Sciences, Stony Brook University, Stony Brook, United States
    Competing interests
    No competing interests declared.

  9. Arthur P Grollman

    Department of Pharmacological Sciences, Department of Medicine, Stony Brook University, Stony Brook, United States
    Competing interests
    No competing interests declared.

  10. Ken W Kinzler

    Howard Hughes Medical Institute, Ludwig Center, Baltimore, United States
    Competing interests
    Ken W Kinzler, K.W.K. is a founder of and hold equity, and serve as consultant to Thrive Earlier Detection and Personal Genome Diagnostics. K.W.K. is on the Board of Directors of Thrive Earlier Detection. K.W.K. is a consultant to Sysmex, Eisai, and CAGE Pharma and hold equity in CAGE Pharma. K.W.K. is a consultant to and hold equity in NeoPhore. The companies named above, as well as other companies, have licensed previously described technologies from Johns Hopkins University. K.W.K is an inventor on some of these technologies. Licenses to these technologies are or will be associated with equity or royalty payments to the inventors as well as to Johns Hopkins University. Patent applications on the work described in this paper have or may be filed by Johns Hopkins University. The terms of all these arrangements are being managed by Johns Hopkins University in accordance with its conflict of interest policies..

  11. Leslie Cope

    Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University, Baltimore, United States
    Competing interests
    No competing interests declared.

  12. Bert Vogelstein

    Ludwig Center & Howard Hughes Medical Institute, Johns Hopkins University, Baltimore, United States
    Competing interests
    Bert Vogelstein, B.V. is a founder of and hold equity, and serve as consultant to Thrive Earlier Detection and Personal Genome Diagnostics. B.V. is a consultant to Sysmex, Eisai, and CAGE Pharma and hold equity in CAGE Pharma. BV is also a consultant to Nexus, and is a consultant to and hold equity in NeoPhore. The companies named above, as well as other companies, have licensed previously described technologies from Johns Hopkins University. B.V. is an inventor on some of these technologies. Licenses to these technologies are or will be associated with equity or royalty payments to the inventors as well as to Johns Hopkins University. Patent applications on the work described in this paper have or may be filed by Johns Hopkins University. The terms of all these arrangements are being managed by Johns Hopkins University in accordance with its conflict of interest policies..

  13. Cristian Tomasetti

    Oncology, Johns Hopkins School of Medicine, Baltimore, United States
    For correspondence
    ctomasetti@jhu.edu
    Competing interests
    Cristian Tomasetti, C.T. is a consultant to Bayer and Johnson & Johnson. Thrive Earlier Detection has licensed previously described technologies from Johns Hopkins University. C.T. is an inventor on some of these technologies. Licenses to these technologies are or will be associated with equity or royalty payments to the inventors as well as to Johns Hopkins University. Patent applications on the work described in this paper have or may be filed by Johns Hopkins University. The terms of all these arrangements are being managed by Johns Hopkins University in accordance with its conflict of interest policies..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3277-4804

Funding

The John Templeton Foundation (#61471)

  • Bahman Afsari
  • Albert Kuo
  • YiFan Zhang
  • Lu Li
  • Kamel Lahouel
  • Ludmila Danilova
  • Cristian Tomasetti

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2021, Afsari et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Bahman Afsari
  2. Albert Kuo
  3. YiFan Zhang
  4. Lu Li
  5. Kamel Lahouel
  6. Ludmila Danilova
  7. Alexander Favorov
  8. Thomas A Rosenquist
  9. Arthur P Grollman
  10. Ken W Kinzler
  11. Leslie Cope
  12. Bert Vogelstein
  13. Cristian Tomasetti
(2021)
Supervised mutational signatures for obesity and other tissue-specific etiological factors in cancer
eLife 10:e61082.
https://doi.org/10.7554/eLife.61082

Share this article

https://doi.org/10.7554/eLife.61082

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