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

Cancer Res. 2012 Jun 1;72(11):2695-700. doi: 10.1158/0008-5472.CAN-11-2786. Epub 2012 May 16.

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.

Publication types

  • Review

MeSH terms

  • Animals
  • Disease Models, Animal
  • Drug Evaluation, Preclinical
  • Drug Resistance, Neoplasm
  • ErbB Receptors / antagonists & inhibitors
  • Genetic Engineering*
  • Humans
  • Lung Neoplasms / drug therapy*
  • Lung Neoplasms / genetics
  • Mice
  • Pancreatic Neoplasms / drug therapy*
  • Pancreatic Neoplasms / genetics
  • Proto-Oncogene Proteins
  • Proto-Oncogene Proteins p21(ras)
  • Vascular Endothelial Growth Factor A / antagonists & inhibitors
  • ras Proteins

Substances

  • KRAS protein, human
  • Proto-Oncogene Proteins
  • Vascular Endothelial Growth Factor A
  • ErbB Receptors
  • Proto-Oncogene Proteins p21(ras)
  • ras Proteins