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Comprehensive Analysis of Hypermutation in Human Cancer.

Brittany B Campbell | Nicholas Light | David Fabrizio | Matthew Zatzman | Fabio Fuligni | Richard de Borja | Scott Davidson | Melissa Edwards | Julia A Elvin | Karl P Hodel | Walter J Zahurancik | Zucai Suo | Tatiana Lipman | Katharina Wimmer | Christian P Kratz | Daniel C Bowers | Theodore W Laetsch | Gavin P Dunn | Tanner M Johanns | Matthew R Grimmer | Ivan V Smirnov | Valérie Larouche | David Samuel | Annika Bronsema | Michael Osborn | Duncan Stearns | Pichai Raman | Kristina A Cole | Phillip B Storm | Michal Yalon | Enrico Opocher | Gary Mason | Gregory A Thomas | Magnus Sabel | Ben George | David S Ziegler | Scott Lindhorst | Vanan Magimairajan Issai | Shlomi Constantini | Helen Toledano | Ronit Elhasid | Roula Farah | Rina Dvir | Peter Dirks | Annie Huang | Melissa A Galati | Jiil Chung | Vijay Ramaswamy | Meredith S Irwin | Melyssa Aronson | Carol Durno | Michael D Taylor | Gideon Rechavi | John M Maris | Eric Bouffet | Cynthia Hawkins | Joseph F Costello | M Stephen Meyn | Zachary F Pursell | David Malkin | Uri Tabori | Adam Shlien
Cell | 2017

We present an extensive assessment of mutation burden through sequencing analysis of >81,000 tumors from pediatric and adult patients, including tumors with hypermutation caused by chemotherapy, carcinogens, or germline alterations. Hypermutation was detected in tumor types not previously associated with high mutation burden. Replication repair deficiency was a major contributing factor. We uncovered new driver mutations in the replication-repair-associated DNA polymerases and a distinct impact of microsatellite instability and replication repair deficiency on the scale of mutation load. Unbiased clustering, based on mutational context, revealed clinically relevant subgroups regardless of the tumors' tissue of origin, highlighting similarities in evolutionary dynamics leading to hypermutation. Mutagens, such as UV light, were implicated in unexpected cancers, including sarcomas and lung tumors. The order of mutational signatures identified previous treatment and germline replication repair deficiency, which improved management of patients and families. These data will inform tumor classification, genetic testing, and clinical trial design.

Pubmed ID: 29056344 RIS Download

Research resources used in this publication

None found

Antibodies used in this publication

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Associated grants

  • Agency: NIEHS NIH HHS, United States
    Id: R00 ES016780
  • Agency: NCI NIH HHS, United States
    Id: P01 CA118816
  • Agency: NIEHS NIH HHS, United States
    Id: R56 ES026821
  • Agency: NCI NIH HHS, United States
    Id: P50 CA097257
  • Agency: NIEHS NIH HHS, United States
    Id: R01 ES028271

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ExAc (tool)

RRID:SCR_004068

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. An aggregated data platform for genome sequencing data created by a coalition of investigators seeking to aggregate and harmonize exome sequencing data from a variety of large-scale sequencing projects, and to make summary data available for the wider scientific community. The data set provided on this website spans 61,486 unrelated individuals sequenced as part of various disease-specific and population genetic studies. They have removed individuals affected by severe pediatric disease, so this data set should serve as a useful reference set of allele frequencies for severe disease studies. All of the raw data from these projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects. They ask that you not publish global (genome-wide) analyses of these data until after the ExAC flagship paper has been published, estimated to be in early 2015. If you''re uncertain which category your analyses fall into, please email them. The aggregation and release of summary data from the exomes collected by the Exome Aggregation Consortium has been approved by the Partners IRB (protocol 2013P001477, Genomic approaches to gene discovery in rare neuromuscular diseases).

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1000 Genomes: A Deep Catalog of Human Genetic Variation (tool)

RRID:SCR_006828

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

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