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dc.contributor.authorBergholtz, H
dc.contributor.authorCarter, JM
dc.contributor.authorCesano, A
dc.contributor.authorCheang, MCU
dc.contributor.authorChurch, SE
dc.contributor.authorDivakar, P
dc.contributor.authorFuhrman, CA
dc.contributor.authorGoel, S
dc.contributor.authorGong, J
dc.contributor.authorGuerriero, JL
dc.contributor.authorHoang, ML
dc.contributor.authorHwang, ES
dc.contributor.authorKuasne, H
dc.contributor.authorLee, J
dc.contributor.authorLiang, Y
dc.contributor.authorMittendorf, EA
dc.contributor.authorPerez, J
dc.contributor.authorPrat, A
dc.contributor.authorPusztai, L
dc.contributor.authorReeves, JW
dc.contributor.authorRiazalhosseini, Y
dc.contributor.authorRicher, JK
dc.contributor.authorSahin, Ö
dc.contributor.authorSato, H
dc.contributor.authorSchlam, I
dc.contributor.authorSørlie, T
dc.contributor.authorStover, DG
dc.contributor.authorSwain, SM
dc.contributor.authorSwarbrick, A
dc.contributor.authorThompson, EA
dc.contributor.authorTolaney, SM
dc.contributor.authorWarren, SE
dc.date.accessioned2021-09-09T14:47:28Z
dc.date.available2021-09-09T14:47:28Z
dc.identifier.citationCancers, 13 (17), pp. 4456 - 4456
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/4802
dc.identifier.eissn2072-6694
dc.identifier.doi10.3390/cancers13174456
dc.description.abstractBreast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular diversity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse samples and protein profiling of 100-plex for human samples. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.
dc.format.extent4456 - 4456
dc.languageeng
dc.language.isoeng
dc.publisherMDPI AG
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleBest Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler
dc.typeJournal Article
dcterms.dateAccepted2021-09-01
rioxxterms.versionVoR
rioxxterms.versionofrecord10.3390/cancers13174456
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2021-09-01
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfCancers
pubs.issue17
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/Clinical Studies
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Clinical Studies/Clinical Trials & Statistics Unit
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/Clinical Studies
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Clinical Studies/Clinical Trials & Statistics Unit
pubs.publication-statusPublished online
pubs.volume13
pubs.embargo.termsNot known
icr.researchteamClinical Trials & Statistics Unit
icr.researchteamClinical Trials & Statistics Uniten_US
dc.contributor.icrauthorCheang, Chonen


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