Patterns of somatic structural variation in human cancer genomes View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2020-02-05

AUTHORS

Yilong Li, Nicola D. Roberts, Jeremiah A. Wala, Ofer Shapira, Steven E. Schumacher, Kiran Kumar, Ekta Khurana, Sebastian Waszak, Jan O. Korbel, James E. Haber, Marcin Imielinski, Joachim Weischenfeldt, Rameen Beroukhim, Peter J. Campbell

ABSTRACT

A key mutational process in cancer is structural variation, in which rearrangements delete, amplify or reorder genomic segments that range in size from kilobases to whole chromosomes1–7. Here we develop methods to group, classify and describe somatic structural variants, using data from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), which aggregated whole-genome sequencing data from 2,658 cancers across 38 tumour types8. Sixteen signatures of structural variation emerged. Deletions have a multimodal size distribution, assort unevenly across tumour types and patients, are enriched in late-replicating regions and correlate with inversions. Tandem duplications also have a multimodal size distribution, but are enriched in early-replicating regions—as are unbalanced translocations. Replication-based mechanisms of rearrangement generate varied chromosomal structures with low-level copy-number gains and frequent inverted rearrangements. One prominent structure consists of 2–7 templates copied from distinct regions of the genome strung together within one locus. Such cycles of templated insertions correlate with tandem duplications, and—in liver cancer—frequently activate the telomerase gene TERT. A wide variety of rearrangement processes are active in cancer, which generate complex configurations of the genome upon which selection can act. More... »

PAGES

112-121

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41586-019-1913-9

    DOI

    http://dx.doi.org/10.1038/s41586-019-1913-9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1124593374

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/32025012


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