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dc.contributor.authorPCAWG Drivers and Functional Interpretation Working Group
dc.contributor.authorPCAWG Structural Variation Working Group
dc.contributor.authorPCAWG Consortium
dc.date.accessioned2020-03-02T10:30:02Z
dc.date.available2020-03-02T10:30:02Z
dc.date.issued2020-02-06
dc.identifier266499411
dc.identifier1ee80b96-cf60-43b1-9680-426ab681752a
dc.identifier85079047263
dc.identifier32025015
dc.identifier000529097800009
dc.identifier.citationPCAWG Drivers and Functional Interpretation Working Group , PCAWG Structural Variation Working Group & PCAWG Consortium 2020 , ' Analyses of non-coding somatic drivers in 2,658 cancer whole genomes ' , Nature , vol. 578 , no. 7793 , pp. 102-111 . https://doi.org/10.1038/s41586-020-1965-xen
dc.identifier.issn0028-0836
dc.identifier.otherORCID: /0000-0002-7876-7338/work/69463476
dc.identifier.otherRIS: urn:5C688B1BF1125DED5379B5F74D114FAE
dc.identifier.otherRIS: Rheinbay2020
dc.identifier.urihttps://hdl.handle.net/10023/19565
dc.description.abstractThe discovery of drivers of cancer has traditionally focused on protein-coding genes1,2,3,4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5′ region of TP53, in the 3′ untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.
dc.format.extent10
dc.format.extent14979351
dc.language.isoeng
dc.relation.ispartofNatureen
dc.subjectRC0254 Neoplasms. Tumors. Oncology (including Cancer)en
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subject3rd-DASen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subject.lccRC0254en
dc.subject.lccQA75en
dc.titleAnalyses of non-coding somatic drivers in 2,658 cancer whole genomesen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Medicineen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.contributor.institutionUniversity of St Andrews. Sir James Mackenzie Institute for Early Diagnosisen
dc.contributor.institutionUniversity of St Andrews. Cellular Medicine Divisionen
dc.identifier.doi10.1038/s41586-020-1965-x
dc.description.statusPeer revieweden


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