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Identification of four subtypes of Triple Negative Breast Cancer (TNBC) by genomic profiling

GSE76339 Homo sapiens Genome variation profiling by SNP array; SNP genotyping by SNP array 142 samples Submitted 2015/12/25 Platform GPL8887Platform GPL8888
Summary
The aggressive triple negative breast cancers (TNBCs), which lack estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2), comprise a high-risk subset of human breast cancers which remain poorly characterized and lack effective treatments. While meta-analyses have recently suggested the complexity of these tumors, no robust phenotypes have been defined. We identified four distinct subtypes through gene expression analyses of 198 TNBCs (84 Discovery, 114 Validation). We then classified 221 publically available TNBCs profiled on the same mRNA expression array. All three sets supported stratification of tumors by cell cycle (Subtype 1 Luminal – FOXA1, LUM), DNA repair (Subtype 2, Mesenchymal – ADIPOQ, MES), downregulated immunological (Subtype 3, Basal-Like – SOX10/8, BL), and upregulated immunological (Subtype 4, Basal Immune – STAT1, BI) signaling pathways. Additional classified data sets demonstrate significantly lower risk of relapse and death with BI tumors, and highest risk with BL tumors, even after correction with known risk factors. DNA copy number profiling of our primary study set produced optimal differentiation of the LUM subtype from the remaining tumors, and drove expression of FGFR2 and CDK1 in BL and BI subtypes. Subtype-specific targets include MUC1 in LUM tumors, CTLA4 in BI tumors, and a potential dependence of MES tumors on NTRK2, DDR2, PDGFRA, TEK, and ADRB2, which, upon validation, could enable targeted treatment with tyrosine-kinase inhibitors and beta-blockers. These findings further define TNBCs and provide the rationale for studies targeting agents against these tumor subtypes, thereby enabling a higher potential for preventive efficacy in patients with TNBC.
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Also filed as BioProject PRJNA306943. Searching any of these in the dataset finder brings you back here.

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