Abstract ES2-2: Triple Negative Breast Cancer: Subtypes, Molecular Targets, and Therapeutic Approaches

Abstract

Listen

Translate article

Abstract The term “triple negative breast cancer” (TNBC) is used to classify 10%–20% of all breast cancers that lack estrogen receptor (ER) and progesterone receptor expression as well as amplification of the human epidermal growth factor receptor 2 (HER2)1. Disease heterogeneity and the absence of well-defined molecular targets have made treatment of TNBC challenging. To make significant clinical advances for TNBC patients, integrative and comprehensive genomic and molecular analyses of TNBC are required to understand the complexity of the disease as well as to allow identification of homogeneous subsets and ‘driver pathways’ that can then be therapeutically targeted. In response to this need, we compiled an extensive number of TNBC gene expression (GE) profiles and initiated molecular subtyping of the disease2. We identified two basal-like TNBC subtypes with cell cycle and DDR GE signatures (BL1 and BL2); two mesenchymal subtypes with high expression of genes involved in differentiation and growth factor pathways (M and MSL); an immunomodulatory (IM) type; and a luminal subtype driven by androgen signaling (LAR). Differential GE was used to designate 25 TNBC cell line models representative of these subtypes. Predicted ‘driver’ signaling pathways were pharmacologically targeted in these preclinical models as proof of concept that analysis of distinct GE signatures can inform therapy selection. Representative BL1 and BL2 subtype cell lines preferentially respond to cisplatin. Mesenchymal, basal, and luminal subtype lines with aberrations in PI3K signaling have the greatest sensitivity, in general, to phosphatidylinositol 3-kinase (PI3K) inhibitors. The LAR subtype cell lines express AR and are uniquely sensitive to bicalutamide (AR antagonist). We have also developed “TNBCtype,” a web-based subtyping tool for candidate TNBC tumor samples using our GE metadata and classification methods3. The approaches used and data generated have value for biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies. 1. Dent, R., Trudeau, M., Pritchard, K.I., Hanna, W.M., Kahn, H.K., Sawka, C.A., Lickley, L.A., Rawlinson, E., Sun, P., and Narod, S.A. (2007). Triple-negative breast cancer: clinical features and patterns of recurrence. Clin Cancer Res 13, 4429–4434. 2. Lehmann, B.D., Bauer, J.A., Chen, X., Sanders, M.E., Chakravarthy, A.B., Shyr, Y., and Pietenpol, J.A. (2011). Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest. 121: 2750–67. 3. Chen, X., Li, J., Gray, W.H., Lehmann, B.D., Bauer, J.A., Shyr, Y., and Pietenpol, J.A. (2012). TNBCtype: A Subtyping Tool for Triple-Negative Breast Cancer. Cancer informatics 11, 147–156. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr ES2-2.