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dc.contributor.authorvan Dijk, Erik
dc.contributor.authorvan den Bosch, Tom
dc.contributor.authorLenos, Kristiaan J
dc.contributor.authorEl Makrini, Khalid
dc.contributor.authorNijman, Lisanne E
dc.contributor.authorvan Essen, Hendrik F B
dc.contributor.authorLansu, Nico
dc.contributor.authorBoekhout, Michiel
dc.contributor.authorHageman, Joris H
dc.contributor.authorFitzgerald, Rebecca C
dc.contributor.authorPunt, Cornelis J A
dc.contributor.authorTuynman, Jurriaan B
dc.contributor.authorSnippert, Hugo J G
dc.contributor.authorKops, Geert J P L
dc.contributor.authorMedema, Jan Paul
dc.contributor.authorYlstra, Bauke
dc.contributor.authorVermeulen, Louis
dc.contributor.authorMiedema, Daniël M
dc.date.accessioned2021-06-29T00:31:38Z
dc.date.available2021-06-29T00:31:38Z
dc.date.issued2021-05-27
dc.identifier.issn2041-1723
dc.identifier.otherPMC8160133
dc.identifier.other34045449
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/324542
dc.descriptionFunder: Medical Research Council
dc.descriptionFunder: Cancer Research UK
dc.description.abstractSurvival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing. Here, we introduce a scalable measure of chromosomal copy number heterogeneity (CNH) that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data and live cell imaging we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 37 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.
dc.languageeng
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceessn: 2041-1723
dc.sourcenlmid: 101528555
dc.subjectHumans
dc.subjectNeoplasms
dc.subjectPrognosis
dc.subjectSurvival Rate
dc.subjectRisk Assessment
dc.subjectGene Expression Profiling
dc.subjectGenomics
dc.subjectGene Expression Regulation, Neoplastic
dc.subjectGenetic Heterogeneity
dc.subjectMutation
dc.subjectModels, Genetic
dc.subjectComputer Simulation
dc.subjectAdolescent
dc.subjectAdult
dc.subjectAged
dc.subjectAged, 80 and over
dc.subjectMiddle Aged
dc.subjectChild
dc.subjectFemale
dc.subjectMale
dc.subjectYoung Adult
dc.subjectDNA Copy Number Variations
dc.subjectTumor Microenvironment
dc.subjectDatasets as Topic
dc.subjectProgression-Free Survival
dc.titleChromosomal copy number heterogeneity predicts survival rates across cancers.
dc.typeArticle
dc.date.updated2021-06-29T00:31:38Z
prism.issueIdentifier1
prism.publicationNameNature communications
prism.volume12
dc.identifier.doi10.17863/CAM.71995
rioxxterms.versionofrecord10.1038/s41467-021-23384-6
rioxxterms.versionVoR
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidvan den Bosch, Tom [0000-0002-5266-8446]
dc.contributor.orcidLenos, Kristiaan J [0000-0003-1165-8732]
dc.contributor.orcidHageman, Joris H [0000-0002-1386-054X]
dc.contributor.orcidFitzgerald, Rebecca C [0000-0002-3434-3568]
dc.contributor.orcidSnippert, Hugo J G [0000-0002-4189-5213]
dc.contributor.orcidKops, Geert J P L [0000-0003-3555-5295]
dc.contributor.orcidYlstra, Bauke [0000-0001-9479-3010]
dc.contributor.orcidVermeulen, Louis [0000-0002-6066-789X]
dc.contributor.orcidMiedema, Daniël M [0000-0002-0729-3753]


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International