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Erratum to: The somatic autosomal mutation matrix in cancer genomes

Authors :
Uma Mudunuri
Brian T. Luke
Regina Z. Cer
David Neil Cooper
Joseph Ivanic
Nuri A. Temiz
Ming Yi
Jack R. Collins
Duncan E. Donohue
Robert M. Stephens
Albino Bacolla
Karen M. Vasquez
Source :
Human Genetics
Publication Year :
2015
Publisher :
Springer Science and Business Media LLC, 2015.

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, (5m)CpG 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, 10.4% of the SAMMs had an Undetermined tissue of origin, and 92.2% of the remaining SAMMs were assigned to the correct tissue of origin. [corrected]. Thus, although tumors from different tissues may have similar mutation patterns, their SAMMs often display signatures that are characteristic of specific tissues.

Details

ISSN :
14321203 and 03406717
Volume :
134
Database :
OpenAIRE
Journal :
Human Genetics
Accession number :
edsair.doi.dedup.....e7631bd4f3f37fd84a4de3dede1f87e6
Full Text :
https://doi.org/10.1007/s00439-015-1576-z