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المؤلفZiegler, Colleen
المؤلفSlemons, Isaiah
المؤلفDeSilva, Chris
المؤلفWitkowski, Barbara
المؤلفMir, Alain
المؤلفAnandakrishnan, Sangeetha
المؤلفFarmer, Andrew
المؤلفContreras, Elma
المؤلفRichardson, David
المؤلفVranic, Semir
المؤلفGatalica, Zoran
المؤلفDerkach, Dmitry N.
تاريخ الإتاحة2019-12-12T11:04:53Z
تاريخ النشر2019-12-01
اسم المنشورMolecular Cancer Therapeutics
المعرّفhttp://dx.doi.org/10.1158/1535-7163.TARG-19-B094
الاقتباسColleen 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
الرقم المعياري الدولي للكتاب1535-7163
معرّف المصادر الموحدhttps://www.biosyntagma.com/news/
معرّف المصادر الموحدhttps://mct.aacrjournals.org/content/18/12_Supplement/B094
معرّف المصادر الموحدhttp://hdl.handle.net/10576/12392
الملخصBreast 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.
راعي المشروعbioSyntagma, LLC, PHOENIX, AZ; Takara Bio USA, Inc., Mountain View, CA;
اللغةen
الناشرAmerican Association for Cancer Research
الموضوعbreast cancer
molecular classification
tumor microenvironment
PD-L1
spatial distribution
العنوانAbstract B094: Novel method for patient stratification in breast carcinoma based upon spatial analysis of tumor microenvironment
النوعConference Paper
رقم العدد12
رقم المجلد18
ESSN1538-8514
dc.accessType Abstract Only


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