Modeling therapy resistance in genetically engineered mouse cancer models.

Abstract

Resistance to anti-cancer drugs is a major obstacle in successful treatment of cancer. Multidrug resistance is not only observed with clinically established chemotherapeutics, but also with novel targeted therapies. Although a range of drug resistance mechanisms have been identified up till now, for most drugs it is still controversial which mechanisms are responsible for resistance and therapy failure in patients. Hence, the development of strategies to circumvent drug resistance is often unfocused. Since several years genetically engineered mouse models have been generated which develop tumors that closely resemble cancer in humans. We argue that such models can be used to investigate relevant in vivo mechanisms of resistance. This includes the analysis of intrinsic and acquired resistance, and the characterization of residual cells which survive the treatment. In such model systems different drugs and therapy combinations can be optimized prior to clinical trials.