Genetically Engineered Mouse Models That Closely Resemble Human Patients Enable More Relevant Cancer Drug Studies

The use of genetically engineered mouse models (GEMMs) as recipients for xenografts of various types of human tumors enables study of tumor growth in an animal system with intact immune system and identification of genetic signatures that can be used to predict the responsiveness of these tumors to drug treatment.

Investigators at the University of North Carolina (Chapel Hill, USA) reasoned that drug studies conducted using traditional mouse models, which lack functional immune systems, could produce misleading results. To evaluate this theory they examined the efficacy of four chemotherapeutic or targeted anticancer drugs, alone and in combination, using mouse models representing three distinct breast cancer subtypes: Basal-like (GEMM), Luminal B (GEMM), and Claudin-low (non-GEMM). Drugs tested as single agents included carboplatin, paclitaxel, erlotinib, and lapatinib. The investigators used RNA expression analysis to profile tumors in order to develop signatures that corresponded to treatment and response and then tested their predictive potential using human patient data.


Results published in the June 18, 2013, online edition of the journal Clinical Cancer Research revealed that while lapatinib alone exhibited exceptional efficacy in one model system, generally single-agent activity was modest, while some combination therapies were more active and life prolonging. Through analysis of RNA expression in this large set of chemotherapy-treated mouse tumors, a pair of gene expression signatures was identified that predicted pathological complete response to neoadjuvant anthracycline/taxane (doxorubicin/paclitaxel) therapy in human patients with breast cancer.

Results presented in this study showed that mouse-derived gene signatures could predict drug response even after accounting for common clinical variables and other predictive genomic signatures, suggesting that mice could be used to identify new biomarkers for human cancer patients. Senior author Dr. Charles Perou, professor of molecular oncology research at the University of North Carolina, said, “This is a wonderful example of how well chosen mouse models can inform a human disease state. In this case we used years of research to match the models to specific human subtypes, and then treated the animals with therapies identical to what human cancer patients are receiving. We were ultimately able to develop a biomarker of treatment response from the mouse that works in humans.”

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