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Endocrine-Related Cancer 16 (2) 333 -350     DOI: 10.1677/ERC-08-0244
Copyright © 2009 by the Society for Endocrinology
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The MPA mouse breast cancer model: evidence for a role of progesterone receptors in breast cancer

Claudia Lanari, Caroline A Lamb, Victoria T Fabris, Luisa A Helguero, Rocío Soldati, María Cecilia Bottino, Sebastián Giulianelli, Juan Pablo Cerliani, Victoria Wargon and Alfredo Molinolo

Laboratory of Hormonal Carcinogenesis, Instituto de Biología y Medicina Experimental (IBYME)-Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Vuelta de Obligado 2490 C1428ADN, Buenos Aires, CF, Argentina

(Correspondence should be addressed to A Molinolo who is now at Oral and Pharyngeal Cancer Branch, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland 20892-4340, USA; Email: amolinol{at}mail.nih.gov)

(L A Helguero is now at Department of Biosciences and Nutrition, Karolinska Institutet, Novum, SE-141 57 Huddinge, Sweden)

More than 60% of all breast neoplasias are ductal carcinomas expressing estrogen (ER) and progesterone receptors (PR). By contrast, most of the spontaneous, chemically or mouse mammary tumor virus induced tumors, as well as tumors arising in genetically modified mice do not express hormone receptors. We developed a model of breast cancer in which the administration of medroxyprogesterone acetate to BALB/c female mice induces mammary ductal carcinomas with a mean latency of 52 weeks and an incidence of about 80%. These tumors are hormone-dependent (HD), metastatic, express both ER and PR, and are maintained by syngeneic transplants. The model has been further refined to include mammary carcinomas that evolve through different stages of hormone dependence, as well as several hormone-responsive cell lines. In this review, we describe the main features of this tumor model, highlighting the role of PR as a trigger of key signaling pathways mediating tumor growth. In addition, we discuss the relevance of this model in comparison with other presently used breast cancer models pointing out its advantages and limitations and how, this model may be suitable to unravel key questions in breast cancer.







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