Genetically engineered mouse models of breast carcinoma: a translational resource for highlighting human breast subtype etiology and developing personalized therapeutic approaches

Approximately one in eight women will be diagnosed with breast cancer during their lifetime. While increased public awareness has led to earlier detection of this common disease, a greater understanding of tumor biology has led to the development of many promising therapeutics. A difficult frontier, however, has been identifying the appropriate target population for new drugs as not all breast cancer patients will respond to a particular therapeutic. Currently, approximately five percent of oncology drugs that enter clinical testing are ultimately approved by the US Food and Drug Administration for use. This low success rate reflects not only the difficulty of developing anticancer therapeutics, but also flaws in preclinical testing methodology for selecting the most appropriate cancer patient subset for early clinical testing. With so many patients either not responding or relapsing with the current standard of care, improved personalized therapeutic approaches are greatly needed. Breast cancer is a heterogeneous disease consisting of multiple intrinsic subtypes. Even though clear clinical and genetic distinctions between the subtypes have been described, the driving mechanisms underlying the initiation, growth and metastasis of breast tumors are under intense investigation to more fully characterize these phenotypes since targeted treatment against specific aberrations promises to be more effective with less systemic side effects. Genetically engineered mouse models are a useful resource for studying mammary cancers in vivo under genetically controlled and immune competent conditions. Identifying murine models with conserved human tumor features will not only facilitate etiology determinations for the intrinsic subtypes, but also serve as a useful preclinical resource for testing the efficacy of new therapeutic approaches. These mice promise to be better predictors of clinical trial success because they resemble tumor biology more closely than other approaches. The work presented here focuses on determining the degree to which current mouse models of breast carcinoma resemble the human disease state and identifies mouse model counterparts for each of the human intrinsic subtypes. If these credentialed mouse models are used for preclinical testing, we anticipate a higher success rate for the development of targeted therapeutics.Doctor of Philosoph