Murine breast cancer mastectomy model that predicts patient outcomes for drug development.

BACKGROUND: Despite massive expenditures in preclinical studies, many breast cancer agents show efficacy in murine models but fail in human trials. In humans, metastatic disease determines survival, but preclinical murine models only evaluate drug efficacy against the primary tumor. We hypothesized that evaluating efficacy against metastatic breast cancer would more efficiently predict efficacy in a murine model than evaluating the primary tumor alone. This study (1) critically evaluated a murine tumor removal model with metastatic tumor burden quantification for breast cancer preclinical trials and (2) validated the model with an agent that previously passed preclinical trials but failed human trials.
MATERIALS AND METHODS: Tumorectomy and Halsted (radical) mastectomy procedures after inoculation of 4T1-luc2 cells were compared. The effect of AZD0530, an oral Src inhibitor that passed preclinical trials but failed human trials, was evaluated using an inoculation model with/without Halsted mastectomy.
RESULTS: Significant amounts of residual disease were confirmed by bioluminescence (P = 0.003) and 100% developed local recurrence after tumorectomy versus 14% (P = 0.005) after Halsted mastectomy. Bioluminescence value at 15 min after luciferin injection highly correlated with peak except for 24 h after injection. AZD0530 significantly suppressed primary tumor burden compared with no treatment (P = 0.002); but not in lung metastases. In a Halsted mastectomy model, AZD0530 had no efficacy against lung metastases or difference in survival.
CONCLUSIONS: We critically evaluated and established a murine mastectomy model to evaluate metastatic tumors. It provides a new model for preclinical drug development that mimics the human adjuvant setting.