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AuthorZiegler, Colleen
AuthorSlemons, Isaiah
AuthorDeSilva, Chris
AuthorWitkowski, Barbara
AuthorMir, Alain
AuthorAnandakrishnan, Sangeetha
AuthorFarmer, Andrew
AuthorContreras, Elma
AuthorRichardson, David
AuthorVranic, Semir
AuthorGatalica, Zoran
AuthorDerkach, Dmitry N.
Available date2019-12-12T11:04:53Z
Publication Date2019-12-01
Publication NameMolecular Cancer Therapeuticsen_US
Identifierhttp://dx.doi.org/10.1158/1535-7163.TARG-19-B094
CitationColleen Ziegler, Isaiah Slemons, Chris DeSilva, Barbara Witkowski, Alain Mir, Sangeetha Anandakrishnan, Andrew Farmer, Elma Contreras, David Richardson, Semir Vranic, Zoran Gatalica, Dmitry N. Derkach. Novel method for patient stratification in breast carcinoma based upon spatial analysis of tumor microenvironment [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr B094. doi:10.1158/1535-7163.TARG-19-B094
ISSN1535-7163
URIhttps://www.biosyntagma.com/news/
URIhttps://mct.aacrjournals.org/content/18/12_Supplement/B094
URIhttp://hdl.handle.net/10576/12392
AbstractBreast cancer consists of several intrinsic molecular subtypes, providing the basis for clinical treatment decisions. Lately, it is becoming increasingly recognized that factors other than the intrinsic cancer characteristics, such as immune components’ activity in the tumor microenvironment, have important effects on treatment choices and efficacy. bioSyntagma has developed a method, the Molecular Fingerprint (mPrint®), that enables multiplexed analysis of spatially defined regions in formalin-fixed, paraffin-embedded (FFPE) tumor samples allowing for analysis of the gene signatures unique to the tumor microenvironment. This method was applied to molecularly defined sets of breast cancers and used to evaluate four different tumor regions of interest (ROIs): 1) viable carcinoma proper (>90% cancer cells), 2) fibrotic tumor center (sparse cellularity), 3) interface between viable tumor and inflammatory component (tumor and inflammatory microenvironment) and 4) tissue away from the tumor (normal breast tissue). This was compared to the whole tissue scrapes from each patient block. Each ROI and tissue scrape was analyzed by high throughput qPCR for a panel of 248 genes using SmartChip technology (Takara Bio, USA). Sequential tissue slices from each patient were also analyzed using immunohistochemistry (IHC) for three targets and investigated for correlation with qPCR results for validation of the method. Overall, reasonable concordance was observed in general expression trends between selected IHC and RNA expression. qPCR data were further analyzed using hierarchical clustering analysis and showed that morphologically defined ROI’s cluster completely differently than traditional clustering of entire tissue scrapes. Notably, patient clustering based on morphological regions was independent of the intrinsic cancer subtype, as determined by molecular profiling of whole tissue scrapes, as well as independent of trends in Tumor Mutational Burden (TMB) and Microsatellite Instability (MSI). These findings suggest that current methods of patient stratification based on whole tumor molecular subtyping may be inferior to stratification based on molecular characteristics of the tumor microenvironment.
SponsorbioSyntagma, LLC, PHOENIX, AZ; Takara Bio USA, Inc., Mountain View, CA;
Languageen
PublisherAmerican Association for Cancer Research
Subjectbreast cancer
Subjectmolecular classification
Subjecttumor microenvironment
SubjectPD-L1
Subjectspatial distribution
TitleAbstract B094: Novel method for patient stratification in breast carcinoma based upon spatial analysis of tumor microenvironment
TypeConference Paper
Issue Number12
Volume Number18
ESSN1538-8514


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