Show simple item record

dc.contributor.authorKhan, AM
dc.contributor.authorYuan, Y
dc.date.accessioned2017-03-01T12:34:11Z
dc.date.issued2016-11-04
dc.identifier.citationScientific reports, 2016, 6 pp. 36231 - ?
dc.identifier.issn2045-2322
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/447
dc.identifier.eissn2045-2322
dc.identifier.doi10.1038/srep36231
dc.description.abstractThe number of tumour biopsies required for a good representation of tumours has been controversial. An important factor to consider is intra-tumour heterogeneity, which can vary among cancer types and subtypes. Immune cells in particular often display complex infiltrative patterns, however, there is a lack of quantitative understanding of the spatial heterogeneity of immune cells and how this fundamental biological nature of human tumours influences biopsy variability and treatment resistance. We systematically investigate biopsy variability for the lymphocytic infiltrate in 998 breast tumours using a novel virtual biopsy method. Across all breast cancers, we observe a nonlinear increase in concordance between the biopsy and whole-tumour score of lymphocytic infiltrate with increasing number of biopsies, yet little improvement is gained with more than four biopsies. Interestingly, biopsy variability of lymphocytic infiltrate differs considerably among breast cancer subtypes, with the human epidermal growth factor receptor 2-positive (HER2+) subtype having the highest variability. We subsequently identify a quantitative measure of spatial variability that predicts disease-specific survival in HER2+ subtype independent of standard clinical variables (node status, tumour size and grade). Our study demonstrates how systematic methods provide new insights that can influence future study design based on a quantitative knowledge of tumour heterogeneity.
dc.formatElectronic
dc.format.extent36231 - ?
dc.languageeng
dc.language.isoeng
dc.publisherNATURE PORTFOLIO
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subjectLymphocytes, Tumor-Infiltrating
dc.subjectHumans
dc.subjectBreast Neoplasms
dc.subjectReceptor, erbB-2
dc.subjectDiagnosis, Computer-Assisted
dc.subjectBiopsy
dc.subjectPrognosis
dc.subjectTissue Array Analysis
dc.subjectUser-Computer Interface
dc.subjectFemale
dc.subjectBiomarkers, Tumor
dc.titleBiopsy variability of lymphocytic infiltration in breast cancer subtypes and the ImmunoSkew score.
dc.typeJournal Article
dcterms.dateAccepted2016-10-12
rioxxterms.versionofrecord10.1038/srep36231
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2016-11-04
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfScientific reports
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
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.publication-statusPublished
pubs.volume6
pubs.embargo.termsNot known
icr.researchteamComputational Pathology & Integrated Genomics
dc.contributor.icrauthorYuan, Yinyin


Files in this item

Thumbnail

This item appears in the following collection(s)

Show simple item record

https://creativecommons.org/licenses/by/4.0
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0