Assessing therapeutic responses in Kras mutant cancers using genetically engineered mouse models

Area of Science:

• Oncology
• Translational Medicine
• Preclinical Research

Background:

• Current preclinical models like xenografts and early genetically engineered mouse models (GEMMs) have limitations in predicting human clinical outcomes for novel anti-cancer agents.
• Recent advancements in GEMMs offer closer emulation of human disease, but their predictive capability for therapeutic responses requires systematic evaluation.

Purpose of the Study:

• To systematically evaluate the utility of two state-of-the-art mutant Kras-driven GEMMs in predicting clinical therapeutic responses.
• To assess the efficacy of standard-of-care chemotherapeutics and combination therapies (EGFR and VEGF inhibitors) in these GEMMs.

Main Methods:

• Utilized two Kras-driven GEMMs: one for non-small-cell lung carcinoma and one for pancreatic adenocarcinoma.
• Modeled standard clinical endpoints, including overall survival and progression-free survival, using noninvasive imaging.
• Assessed responses to standard chemotherapeutics and combination therapies involving EGFR and VEGF inhibitors.

Main Results:

• The evaluated GEMMs demonstrated a strong correlation with human responses in corresponding clinical trials.
• Noninvasive imaging modalities effectively modeled clinical endpoints like overall and progression-free survival.
• The models provide a foundation for predicting therapeutic outcomes in cancer treatment.

Conclusions:

• Validated GEMMs can accurately model human anti-cancer therapeutic responses, outperforming traditional preclinical models.
• These advanced GEMMs are valuable tools for predicting treatment outcomes and investigating mechanisms of therapeutic response and resistance.
• The findings support the use of these validated GEMMs in accelerating the development of effective cancer therapies.