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Combined inhibitory effect of formestane and herceptin on a subpopulation of CD44+/CD24low breast cancer cells
Authors:Carla Cavaliere  Sara Corvigno  Mario Galgani  Gennaro Limite  Agostina Nardone  Bianca Maria Veneziani
Institution:1. Department of Cellular and Molecular Biology and Pathology “L. Califano”;2. Department of Surgery;3. Oncotech, Medical School, University of Naples “Federico II”?, Naples, Italy
Abstract:In breast cancer, stromal cells surrounding cancer epithelial cells can influence phenotype by producing paracrine factors. Among many mediators of epithelial–stromal interactions, aromatase activity is perhaps one of the best studied. Clinical data suggest that estrogen‐independent signaling leads to increased proliferation even during therapy with aromatase inhibitors (AIs). Molecular mechanism of crosstalk between the estrogen receptor (ER) and the epidermal growth factor receptor (HER) family have been implicated in resistance to endocrine therapy, but this interaction is unclear. The ability of aromatase to induce estradiol biosynthesis provides a molecular rationale to combine agents that target aromatase activity and the HER pathway. We targeted stromal–epithelial interactions using formestane, which exerts antiaromatase activity, combined with the monoclonal anti‐HER2 antibody herceptin, in a subpopulation of CD44+/CD24low cells sorted from epithelial‐mesenchymal co‐cultures of breast cancer tissues. The growth inhibition was respectively 16% (P < 0.01) in the response to herceptin, 25% to formestane (P < 0.01), and 50% (P < 0.001) with the combination of the two drugs, suggesting that herceptin cooperates with formestane‐induced inhibition of aromatase and this effect could be mediated through HER family receptors. In cells which expressed ERα, formestane/herceptin combination suppressed the mRNA expression of aromatase and HER2 and decreased cyclin D1 expression. These results show that combination therapies involving AIs and anti‐HER2 can be efficacious for the treatment of cancer in experimental models and suggest that subtyping breast tumors gives useful information about response to treatment. (Cancer Sci 2010)
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