Journal Article

DKFZ-2020-01051

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Pan-cancer analysis of whole genomes.

ICGC/TCGAPan-CancerAnalysisofWholeGenomesConsortium

2020
Nature Publ. Group52462 London [u.a.]

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Please use a persistent id in citations: doi:10.1038/s41586-020-1969-6

Abstract: Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

Keyword(s): Cell Proliferation: genetics (MeSH) ; Cellular Senescence: genetics (MeSH) ; Chromothripsis (MeSH) ; Cloud Computing (MeSH) ; DNA Mutational Analysis (MeSH) ; Evolution, Molecular (MeSH) ; Female (MeSH) ; Genome, Human: genetics (MeSH) ; Genomics (MeSH) ; Germ-Line Mutation: genetics (MeSH) ; High-Throughput Nucleotide Sequencing (MeSH) ; Humans (MeSH) ; Information Dissemination (MeSH) ; Male (MeSH) ; Mutagenesis: genetics (MeSH) ; Mutation (MeSH) ; Neoplasms: classification (MeSH) ; Neoplasms: genetics (MeSH) ; Neoplasms: pathology (MeSH) ; Oncogenes: genetics (MeSH) ; Promoter Regions, Genetic: genetics (MeSH) ; RNA Splicing: genetics (MeSH) ; Reproducibility of Results (MeSH) ; Telomerase: genetics (MeSH) ; Telomere: genetics (MeSH) ; TERT protein, human ; Telomerase

Note: 2020 Feb;578(7793):82-93 / siehe Correction: DKFZ Autoren affiliiert im PCAWG Consortium: https://inrepo02.dkfz.de/record/265692 / https://doi.org/10.1038/s41586-022-05598-w

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Contributing Institute(s):

1. Theoretische Bioinformatik (B080)
2. Bioinformatik und Omics Data Analytics (B240)
3. B260 Bioinformatik der Genomik und Systemgenetik (B260)
4. Translationale Medizinische Onkologie (B340)
5. Angewandte Bioinformatik (B330)
6. B062 Pädiatrische Neuroonkologie (B062)
7. B087 Neuroblastom Genomik (B087)
8. Epigenomik (B370)
9. Pädiatrische Gliomforschung (B360)
10. B060 Molekulare Genetik (B060)
11. KKE Neuropathologie (B300)
12. Hochdurchsatz-Sequenzierung (W190)
13. B063 Krebsgenomforschung (B063)
14. DKTK Koordinierungsstelle Berlin (BE01)
15. DKTK HD zentral (HD01)

Research Program(s):

1. 312 - Functional and structural genomics (POF3-312) (POF3-312)

Appears in the scientific report 2020

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