Base changes in tumour DNA have the power to reveal the causes and evolution of cancer

Hollstein, M.; Alexandrov, L. B.; Wild, C. P.; Ardin, M.; Zavadil, J.

doi:10.1038/onc.2016.192

Title: Base changes in tumour DNA have the power to reveal the causes and evolution of cancer

Journal Article · Mon Jun 06 00:00:00 EDT 2016 · Oncogene

DOI:https://doi.org/10.1038/onc.2016.192· OSTI ID:1258471

Hollstein, M. ^[1]; Alexandrov, L. B. ^[2]; Wild, C. P. ^[3]; Ardin, M. ^[3];

^[3]

World Health Organization, Lyon (France); Univ. of Leeds, Leeds (United Kingdom)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
World Health Organization, Lyon (France)

Next-generation sequencing (NGS) technology has demonstrated that the cancer genomes are peppered with mutations. Although most somatic tumour mutations are unlikely to have any role in the cancer process per se, the spectra of DNA sequence changes in tumour mutation catalogues have the potential to identify the mutagens, and to reveal the mutagenic processes responsible for human cancer. Very recently, a novel approach for data mining of the vast compilations of tumour NGS data succeeded in separating and precisely defining at least 30 distinct patterns of sequence change hidden in mutation databases. At least half of these mutational signatures can be readily assigned to known human carcinogenic exposures or endogenous mechanisms of mutagenesis. A quantum leap in our knowledge of mutagenesis in human cancers has resulted, stimulating a flurry of research activity. We trace here the major findings leading first to the hypothesis that carcinogenic insults leave characteristic imprints on the DNA sequence of tumours, and culminating in empirical evidence from NGS data that well-defined carcinogen mutational signatures are indeed present in tumour genomic DNA from a variety of cancer types. The notion that tumour DNAs can divulge environmental sources of mutation is now a well-accepted fact. This approach to cancer aetiology has also incriminated various endogenous, enzyme-driven processes that increase the somatic mutation load in sporadic cancers. The tasks now confronting the field of molecular epidemiology are to assign mutagenic processes to orphan and newly discovered tumour mutation patterns, and to determine whether avoidable cancer risk factors influence signatures produced by endogenous enzymatic mechanisms. As a result, innovative research with experimental models and exploitation of the geographical heterogeneity in cancer incidence can address these challenges.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1258471

Report Number(s):: LA-UR-16-20127; onc2016192

Journal Information:: Oncogene, Journal Name: Oncogene; ISSN 0950-9232

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 40 works

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Exploring background mutational processes to decipher cancer genetic heterogeneity Goncearenco, Alexander; Rager, Stephanie L.; Li, Minghui Nucleic Acids Research, Vol. 45, Issue W1 https://doi.org/10.1093/nar/gkx367	journal	May 2017
Sequencing Chemically Induced Mutations in the Mutamouse Lacz Reporter Gene Identifies Human Cancer Mutational Signatures Beal, Marc A.; Meier, Matt J.; LeBlanc, Danielle https://doi.org/10.1101/858159	posted_content	November 2019
Worldwide research trends on aristolochic acids (1957–2017): Suggestions for researchers Zhou, Qiang; Pei, Jin; Poon, Josiah PLOS ONE, Vol. 14, Issue 5 https://doi.org/10.1371/journal.pone.0216135	journal	May 2019
DNA Rereplication Is Susceptible to Nucleotide-Level Mutagenesis Bui, Duyen T.; Li, Joachim J. Genetics, Vol. 212, Issue 2 https://doi.org/10.1534/genetics.119.302194	journal	April 2019
Computational approaches for discovery of mutational signatures in cancer Baez-Ortega, Adrian; Gori, Kevin https://doi.org/10.1101/154716	posted_content	June 2017
Computational approaches for discovery of mutational signatures in cancer. Baez-Ortega, Adrian; Gori, Kevin Apollo - University of Cambridge Repository https://doi.org/10.17863/cam.11113	text	January 2019
Modeling cancer driver events in vitro using barrier bypass-clonal expansion assays and massively parallel sequencing Huskova, H.; Ardin, M.; Weninger, A. Oncogene, Vol. 36, Issue 43 https://doi.org/10.1038/onc.2017.215	journal	July 2017

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