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

Abstract
Data availability
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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

Bahman Afsari

Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University, Baltimore, United States

Competing interests
No competing interests declared.
Albert Kuo

Department of Biostatistics, Johns Hopkins University, Baltimore, United States

Competing interests
No competing interests declared.
YiFan Zhang

Department of Biostatistics, Johns Hopkins University, Baltimore, United States

Competing interests
No competing interests declared.
Lu Li

Department of Biostatistics, Johns Hopkins University, Baltimore, United States

Competing interests
No competing interests declared.
Kamel Lahouel

Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University, Baltimore, United States

Competing interests
No competing interests declared.

"This ORCID iD identifies the author of this article:" 0000-0002-4339-5749
Ludmila Danilova

Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins School of Medicine, Baltimore, United States

Competing interests
No competing interests declared.

"This ORCID iD identifies the author of this article:" 0000-0003-2813-3094
Alexander Favorov

Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University, Baltimore, United States

Competing interests
No competing interests declared.
Thomas A Rosenquist

Department of Pharmacological Sciences, Stony Brook University, Stony Brook, United States

Competing interests
No competing interests declared.
Arthur P Grollman

Department of Pharmacological Sciences, Department of Medicine, Stony Brook University, Stony Brook, United States

Competing interests
No competing interests declared.
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..
Leslie Cope

Division of Biostatistics and Bioinformatics, Department of Oncology, Johns Hopkins University, Baltimore, United States

Competing interests
No competing interests declared.
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..
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..

"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

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.