Patterns of somatic structural variation in human cancer genomes
- PMID: 32025012
- PMCID: PMC7025897
- DOI: 10.1038/s41586-019-1913-9
Patterns of somatic structural variation in human cancer genomes
Erratum in
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Author Correction: Patterns of somatic structural variation in human cancer genomes.Nature. 2023 Feb;614(7948):E38. doi: 10.1038/s41586-022-05597-x. Nature. 2023. PMID: 36697835 Free PMC article. No abstract available.
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.
Comment in
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Global genomics project unravels cancer's complexity at unprecedented scale.Nature. 2020 Feb;578(7793):39-40. doi: 10.1038/d41586-020-00213-2. Nature. 2020. PMID: 32025004 No abstract available.
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