Genetically engineered mouse models: closing the gap between preclinical data and trial outcomes

Abstract

The high failure rate of late-stage human clinical trials, particularly in oncology, predicates the need for improved translation of preclinical data from mouse tumor models into clinical predictions. Genetically engineered mouse models (GEMM) may fulfill this need, because they mimic spontaneous and autochthonous disease progression. Using oncogenic Kras-driven GEMMs of lung and pancreatic adenocarcinoma, we recently showed that these models can closely phenocopy human therapeutic responses to standard-of-care treatment regimens. Here we review the successful preclinical application of such GEMMs, as well as the potential for discovering predictive biomarkers and gaining mechanistic insights into clinical outcomes and drug resistance in human cancers.