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- W2315773670 abstract "Abstract Background: Currently, there are targeted therapies for estrogen receptor (ER) positive and HER2-amplified breast cancers. However, treatment options for patients with triple negative breast cancers (TNBCs), tumors that are hormone receptor negative (ER and progesterone, PR) and lack HER2 amplification, has been limited by the heterogeneity and lack of moleclular understanding of the subtypes of this disease. Use of genomic information (gene expression, copy number analysis, methylation arrays, and next-generation sequencing) will unravel the complexity of the disease and identify novel targeted therapies. Methods and Findings: In order to identify biologically distinct TNBC subgroups and associated molecular drivers, we compiled an extensive TNBC transcriptome dataset from 21 independent breast cancer studies. We performed reiterative k-means clustering analysis on a 386 TNBC gene expression profile training set and identified six stable clusters that display unique gene expression patterns and gene ontologies. An independent set of 201 TNBC gene expression profiles was used to validate the six TNBC subgroups. We identified two basal-like subgroups (BL1 and BL2) characterized by cell cycle and DNA damage response genes, two mesenchymal-like subgroups (M and MSL) enriched in cell differentiation, epithelial-mesenchymal transition and growth factor pathways, an immunomodulatory subgroup (IM) defined by immune cell surface antigens, receptors and signal transduction genes, and a luminal subgroup (LAR) driven by androgen receptor signaling. Using tumor gene expression signatures, we identified representative cell lines to model each of the TNBC subgroups and also pharmacologically targeted prominent signaling pathways. Conclusions: Through transciptome analysis we subclassified TNBC into six biological subgroups and identified potential therapeutic targets for future exploration. The data generated in this study have significant value for target selection in drug discovery, clinical trial design and selection of biomarkers that will enable the alignment of TNBC patients to the appropriate targeted therapy. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr PD01-07." @default.
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- W2315773670 date "2010-12-01" @default.
- W2315773670 modified "2023-10-18" @default.
- W2315773670 title "Abstract PD01-07: Transcriptome Analysis of Triple Negative Breast Cancers Identifies Six Distinct Biological Subgroups and Reveals Therapeutic Strategies" @default.
- W2315773670 doi "https://doi.org/10.1158/0008-5472.sabcs10-pd01-07" @default.
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