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A comprehensive catalogue of somatic mutations from a human cancer genome
Open accessAbstract
All cancers carry somatic mutations. A subset of these somatic alterations, termed driver mutations, confer selective growth advantage and are implicated in cancer development, whereas the remainder are passengers. Here we have sequenced the genomes of a malignant melanoma and a lymphoblastoid cell line from the same person, providing the first comprehensive catalogue of somatic mutations from an individual cancer. The catalogue provides remarkable insights into the forces that have shaped this cancer genome. The dominant mutational signature reflects DNA damage due to ultraviolet light exposure, a known risk factor for malignant melanoma, whereas the uneven distribution of mutations across the genome, with a lower prevalence in gene footprints, indicates that DNA repair has been preferentially deployed towards transcribed regions. The results illustrate the power of a cancer genome sequence to reveal traces of the DNA damage, repair, mutation and selection processes that were operative years before the cancer became symptomatic. The two cancer genome sequences presented in this issue demonstrate how next-generation sequencing technologies can inform us about mutational processes, repair pathways and gene networks associated with cancer development. First, the genome of a cell line derived from a bone marrow metastasis in a patient who had small-cell lung cancer. This cancer is typical of the type induced by smoking, and the sequence contains mutation signatures characteristic of some of the more than 60 carcinogens present in tobacco smoke. The second paper compares the whole genome sequence of a melanoma cell line to a lymphoblastoid cell line from the same individual. This, the first complete mutational analysis of a solid tumour, reveals a dominant mutational signature reflecting DNA damage due to exposure to ultraviolet light. Here, the genomes of a malignant melanoma and a lymphoblastoid cell line from the same person are sequenced, providing the first comprehensive catalogue of somatic mutations from an individual cancer. The data provide insight into the causes of tumour formation and the development of the cancer genome, with the dominant mutational signature reflecting DNA damage due to ultraviolet light exposure.
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“Melanoma somatic mutations consist almost entirely of C → T transitions, 28% of which are TCC → T mutations (19,31).”
From Evidence for recent, population-specific evolution of the human mutation rate (2015) · cites this paper as [31]
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Metadata
- Authors
- Pleasance, E. D., Cheetham, R. K., Stephens, P. J., McBride, D. J., Humphray, S. J., Greenman, C. D., Varela, I., Lin, M.-L., Ordóñez, G. R., Bignell, G. R., Ye, K., Alipaz, J., Bauer, M. J., Beare, D., Butler, A., Carter, R. J., Chen, L., Cox, A. J., Edkins, S., Kokko-Gonzales, P. I., Gormley, N. A., Grocock, R. J., Haudenschild, C. D., Hims, M. M., James, T., Jia, M., Kingsbury, Z., Leroy, C., Marshall, J., Menzies, A., Mudie, L. J., Ning, Z., Royce, T., Schulz-Trieglaff, O. B., Spiridou, A., Stebbings, L. A., Szajkowski, L., Teague, J., Williamson, D., Chin, L., Ross, M. T., Campbell, P. J., Bentley, D. R., Futreal, P. A., & Stratton, M. R.
- Affiliations
- Wellcome Sanger Institute (GB)
- Illumina (United Kingdom) (GB)
- Leiden University Medical Center (NL)
- Illumina (United States) (US)
- Dana-Farber Cancer Institute (US)
- Institute of Cancer Research (GB)
- Corresponding author
- Futreal, P. Andrew
- Stratton, Michael R.
- ORCID
- Pleasance, Erin D.
- McBride, David J.
- Humphray, Sean J.
- Greenman, Chris D.
- Varela, Ignacio
- Lin, Meng-Lay
- Ye, Kai
- Bauer, Markus J.
- Chen, Lina
- Edkins, Sarah
- James, Terena
- Jia, Mingming
- Marshall, John
- Menzies, Andrew
- Ning, Zemin
- Spiridou, Anastassia
- Teague, Jon
- Ross, Mark T.
- Campbell, Peter J.
- Futreal, P. Andrew
- Stratton, Michael R.
- Venue
- Nature
- Published
- 2009-12-16
- Volume
- 463
- Issue
- 7278
- Pages
- 191-196
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3145108
- OpenAlex
- W2150677022
- Cited by
- 1,696
- References
- 43
- Citations by year
- 2026: 23 · 2025: 47 · 2024: 43 · 2023: 49 · 2022: 50 · 2021: 83 · 2020: 76 · 2019: 87 · 2018: 69 · 2017: 94 · 2016: 121 · 2015: 116 · 2014: 144 · 2013: 166 · 2012: 189
- FWCI
- 58.62
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- UEA Digital Repository (University of East Anglia) (submittedVersion)
- Funders
- Wellcome Trust (077012/Z/05/Z, 077012, 088340, 093867)
- Kay Kendall Leukaemia Fund
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › DNA Repair Mechanisms
- Keywords
- somatic mutations, mutational signatures, melanoma, lymphoblastoid cell lines, DNA repair, small cell lung cancer, tobacco smoke carcinogens, driver mutations, passenger mutations, cancer genome evolution
- MeSH terms
- Adult, DNA Damage, DNA Mutational Analysis, DNA Repair, Humans, Male, Melanoma, Mutation, Neoplasms, Ultraviolet Rays, Genome, Human, Mutagenesis, Insertional, Sequence Deletion, Gene Dosage, Loss of Heterozygosity, Polymorphism, Single Nucleotide, MicroRNAs, Cell Line, Tumor, Genes, Neoplasm, Precision Medicine
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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