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dc.contributor.authorWilliams, MJen_US
dc.contributor.authorWerner, Ben_US
dc.contributor.authorHeide, Ten_US
dc.contributor.authorCurtis, Cen_US
dc.contributor.authorBarnes, CPen_US
dc.contributor.authorSottoriva, Aen_US
dc.contributor.authorGraham, TAen_US
dc.date.accessioned2018-03-27T08:24:20Z
dc.date.issued2018-06en_US
dc.identifier.citationNature genetics, 2018, 50 (6), pp. 895 - 903en_US
dc.identifier.issn1061-4036en_US
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/1606
dc.identifier.eissn1546-1718en_US
dc.identifier.doi10.1038/s41588-018-0128-6en_US
dc.description.abstractSubclonal architectures are prevalent across cancer types. However, the temporal evolutionary dynamics that produce tumor subclones remain unknown. Here we measure clone dynamics in human cancers by using computational modeling of subclonal selection and theoretical population genetics applied to high-throughput sequencing data. Our method determined the detectable subclonal architecture of tumor samples and simultaneously measured the selective advantage and time of appearance of each subclone. We demonstrate the accuracy of our approach and the extent to which evolutionary dynamics are recorded in the genome. Application of our method to high-depth sequencing data from breast, gastric, blood, colon and lung cancer samples, as well as metastatic deposits, showed that detectable subclones under selection, when present, consistently emerged early during tumor growth and had a large fitness advantage (>20%). Our quantitative framework provides new insight into the evolutionary trajectories of human cancers and facilitates predictive measurements in individual tumors from widely available sequencing data.en_US
dc.formatPrint-Electronicen_US
dc.format.extent895 - 903en_US
dc.languageengen_US
dc.language.isoengen_US
dc.rights.urihttp://www.rioxx.net/licenses/under-embargo-all-rights-reserveden_US
dc.subjectHumansen_US
dc.subjectNeoplasmsen_US
dc.subjectCell Proliferationen_US
dc.subjectHigh-Throughput Screening Assaysen_US
dc.subjectHigh-Throughput Nucleotide Sequencingen_US
dc.titleQuantification of subclonal selection in cancer from bulk sequencing data.en_US
dc.typeJournal Article
dcterms.dateAccepted2018-03-23en_US
rioxxterms.versionofrecord10.1038/s41588-018-0128-6en_US
rioxxterms.licenseref.urien_US
rioxxterms.licenseref.startdate2018-06en_US
rioxxterms.typeJournal Article/Reviewen_US
dc.relation.isPartOfNature geneticsen_US
pubs.issue6en_US
pubs.notes6 monthsen_US
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Evolutionary Genomics & Modelling
pubs.organisational-group/ICR/Students
pubs.organisational-group/ICR/Students/PhD and MPhil
pubs.organisational-group/ICR/Students/PhD and MPhil/16/17 Starting Cohort
pubs.publication-statusPublisheden_US
pubs.volume50en_US
pubs.embargo.terms6 monthsen_US
icr.researchteamEvolutionary Genomics & Modellingen_US
dc.contributor.icrauthorSottoriva, Andreaen_US
dc.contributor.icrauthorWerner, Benjaminen_US
dc.contributor.icrauthorHeide, Timonen_US


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