The somatic autosomal mutation matrix in cancer genomes

Temiz, Nuri A., Donohue, Duncan E., Bacolla, Albino, Vasquez, Karen M., Cooper, David Neil ORCID: https://orcid.org/0000-0002-8943-8484, Mudunuri, Uma, Ivanic, Joseph, Cer, Regina Z., Yi, Ming, Stephens, Robert M., Collins, Jack R. and Luke, Brian T. 2015. The somatic autosomal mutation matrix in cancer genomes. Human Genetics 134 (8) , pp. 851-864. 10.1007/s00439-015-1566-1

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Abstract

DNA damage in somatic cells originates from both environmental and endogenous sources, giving rise to mutations through multiple mechanisms. When these mutations affect the function of critical genes, cancer may ensue. Although identifying genomic subsets of mutated genes may inform therapeutic options, a systematic survey of tumor mutational spectra is required to improve our understanding of the underlying mechanisms of mutagenesis involved in cancer etiology. Recent studies have presented genome-wide sets of somatic mutations as a 96-element vector, a procedure that only captures the immediate neighbors of the mutated nucleotide. Herein, we present a 32 × 12 mutation matrix that captures the nucleotide pattern two nucleotides upstream and downstream of the mutation. A somatic autosomal mutation matrix (SAMM) was constructed from tumor-specific mutations derived from each of 909 individual cancer genomes harboring a total of 10,681,843 single-base substitutions. In addition, mechanistic template mutation matrices (MTMMs) representing oxidative DNA damage, ultraviolet-induced DNA damage, 5mCpG deamination, and APOBEC-mediated cytosine mutation, are presented. MTMMs were mapped to the individual tumor SAMMs to determine the maximum contribution of each mutational mechanism to the overall mutation pattern. A Manhattan distance across all SAMM elements between any two tumor genomes was used to determine their relative distance. Employing this metric, 89.5 % of all tumor genomes were found to have a nearest neighbor from the same tissue of origin. When a distance-dependent 6-nearest neighbor classifier was used, 86.9 % of all SAMMs were assigned to the correct tissue of origin. Thus, although tumors from different tissues may have similar mutation patterns, their SAMMs often display signatures that are characteristic of specific tissues.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Medicine
Subjects:	Q Science > QH Natural history > QH426 Genetics R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Publisher:	Springer
ISSN:	0340-6717
Date of First Compliant Deposit:	30 March 2016
Date of Acceptance:	12 May 2015
Last Modified:	01 Jul 2023 18:44
URI:	https://orca.cardiff.ac.uk/id/eprint/84071

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