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dc.contributor.authorNawaz, S
dc.contributor.authorTrahearn, NA
dc.contributor.authorHeindl, A
dc.contributor.authorBanerjee, S
dc.contributor.authorMaley, CC
dc.contributor.authorSottoriva, A
dc.contributor.authorYuan, Y
dc.date.accessioned2020-05-28T12:04:11Z
dc.date.issued2019-10-21
dc.identifier.citationEBioMedicine, 2019, 48 pp. 224 - 235
dc.identifier.issn2352-3964
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/3657
dc.identifier.eissn2352-3964
dc.identifier.doi10.1016/j.ebiom.2019.10.001
dc.description.abstractBACKGROUND: Despite treatment advances, there remains a significant risk of recurrence in ovarian cancer, at which stage it is usually incurable. Consequently, there is a clear need for improved patient stratification. However, at present clinical prognosticators remain largely unchanged due to the lack of reproducible methods to identify high-risk patients. METHODS: In high-grade serous ovarian cancer patients with advanced disease, we spatially define a tumour ecological balance of stromal resource and immune hazard using high-throughput image and spatial analysis of routine histology slides. On this basis an EcoScore is developed to classify tumours by a shift in this balance towards cancer-favouring or inhibiting conditions. FINDINGS: The EcoScore provides prognostic value stronger than, and independent of, known risk factors. Crucially, the clinical relevance of mutational burden and genomic instability differ under different stromal resource conditions, suggesting that the selective advantage of these cancer hallmarks is dependent on the context of stromal spatial structure. Under a high resource condition defined by a high level of geographical intermixing of cancer and stromal cells, selection appears to be driven by point mutations; whereas, in low resource tumours featured with high hypoxia and low cancer-immune co-localization, selection is fuelled by aneuploidy. INTERPRETATION: Our study offers empirical evidence that cancer fitness depends on tumour spatial constraints, and presents a biological basis for developing better assessments of tumour adaptive strategies in overcoming ecological constraints including immune surveillance and hypoxia.
dc.formatPrint-Electronic
dc.format.extent224 - 235
dc.languageeng
dc.language.isoeng
dc.publisherELSEVIER
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subjectHumans
dc.subjectOvarian Neoplasms
dc.subjectDisease Susceptibility
dc.subjectDiagnostic Imaging
dc.subjectNeoplasm Staging
dc.subjectPrognosis
dc.subjectProportional Hazards Models
dc.subjectMutation
dc.subjectFemale
dc.subjectKaplan-Meier Estimate
dc.titleAnalysis of tumour ecological balance reveals resource-dependent adaptive strategies of ovarian cancer.
dc.typeJournal Article
dcterms.dateAccepted2019-10-01
rioxxterms.versionofrecord10.1016/j.ebiom.2019.10.001
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2019-10-21
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfEBioMedicine
pubs.notesNot known
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/Computational Pathology & Integrated Genomics
pubs.organisational-group/ICR/Primary Group/Royal Marsden Clinical Units
pubs.publication-statusPublished
pubs.volume48
pubs.embargo.termsNot known
icr.researchteamComputational Pathology & Integrated Genomics
dc.contributor.icrauthorNawaz, Sidra
dc.contributor.icrauthorSottoriva, Andrea
dc.contributor.icrauthorYuan, Yinyin


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