Cited by 1,523Cancer Genomics and DiagnosticsEvolution and Genetic DynamicsChromatin Remodeling and Cancer

Universal Patterns of Selection in Cancer and Somatic Tissues

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Martincorena, Iñigo, Raine, Keiran M., Gerstung, Moritz, Dawson, Kevin J., Haase, Kerstin, Van Loo, Peter, Davies, Helen, Stratton, Michael R. +1 more·2017·Cell

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Abstract

Cancer develops as a result of somatic mutation and clonal selection, but quantitative measures of selection in cancer evolution are lacking. We adapted methods from molecular evolution and applied them to 7,664 tumors across 29 cancer types. Unlike species evolution, positive selection outweighs negative selection during cancer development. On average, <1 coding base substitution/tumor is lost through negative selection, with purifying selection almost absent outside homozygous loss of essential genes. This allows exome-wide enumeration of all driver coding mutations, including outside known cancer genes. On average, tumors carry ∼4 coding substitutions under positive selection, ranging from <1/tumor in thyroid and testicular cancers to >10/tumor in endometrial and colorectal cancers. Half of driver substitutions occur in yet-to-be-discovered cancer genes. With increasing mutation burden, numbers of driver mutations increase, but not linearly. We systematically catalog cancer genes and show that genes vary extensively in what proportion of mutations are drivers versus passengers.

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  • The dN/dS ratio test confirmed that somatic variants in Alzheimer's disease brains experienced stronger positive selection than somatic variants in control brains, with greater than a 350% increase in positively selected cells.

    “Direct examination of the signal of positive selection on these variants using the dN/dS ratio test36 confirmed that somatic variants in AD brains experienced stronger positive selection than somatic variants in control brains (Figure 2H-I), with greater than a 350% increase in positively selected cells (Figure 2J).”
  • The 285 developmental-disorder-associated genes significantly overlap 369 previously described cancer driver genes, with 70 genes overlapping (p = 1.7 × 10-49).

    “We observed a significant overlap between the 285 DNM-enriched DD-associated genes and a set of 369 previously described cancer driver genes19 (overlap of 70 genes; p = 1.7 × 10-49, logistic regression correcting for shet), as observed previously20,21, as well as a significant enrichment of nonsynonymous DNMs in both overlapping and non-overlapping cancer genes (Supplementary Table 9).”

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Authors
Martincorena, I., Raine, K. M., Gerstung, M., Dawson, K. J., Haase, K., Van Loo, P., Davies, H., Stratton, M. R., & Campbell, P. J.
Affiliations
  • Wellcome Sanger Institute (GB)
  • European Bioinformatics Institute (GB)
  • The Francis Crick Institute (GB)
  • University of Cambridge (GB)
Corresponding author
  • Martincorena, Iñigo
  • Campbell, Peter J.
Venue
Cell
Publisher
Elsevier BV
Published
2017-11
Volume
171
Issue
5
Pages
1029-1041.e21
ISSN
0092-8674 (ISSN-L)
OpenAlex
W2611387862
Cited by
1,523
References
75
Citations by year
2026: 109 · 2025: 171 · 2024: 192 · 2023: 215 · 2022: 206 · 2021: 183 · 2020: 183 · 2019: 147 · 2018: 105 · 2017: 11
FWCI
41.02
Type
journal article
Language
en
Update notices
erratum (2018-06-14)
Open access
Locations
  • Cell (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Figshare (submittedVersion, cc-by)
Funders
  • EMBO (766-2015)
  • Cancer Research UK (C57387/A21777, FC001202)
  • Wellcome Trust (FC001202)
  • Francis Crick Institute
  • UK Medical Research Council (FC001202)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
Keywords
tumor evolution, clonal selection, positive selection, negative selection, purifying selection, driver mutations, passenger mutations, somatic mutations, mutational burden, cancer genes
MeSH terms
Humans, Models, Genetic, Neoplasms, Selection, Genetic, Point Mutation, Polymorphism, Single Nucleotide, Microsatellite Instability, INDEL Mutation, Mutation Rate

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