LAUSR

Targeted therapies have transformed the landscape for the treatment of metastatic lung cancer. Despite their success, targeted therapies are not curative and acquired resistance is a major impediment to cures for patients treated with these therapies. A paradigm for the success of targeted therapies in lung cancer comes from epidermal growth factor receptor (EGFR) mutant lung cancer where mutations in exons encoding the tyrosine kinase domain of EGFR confer sensitivity to tyrosine kinase inhibitors (TKIs), and several TKIs are currently approved for the first-line treatment of EGFR mutant lung cancer. Moreover, there is heterogeneity in the durability and depth of responses between patients and at different metastatic sites within individual patients. Therefore, there is a need to understand the biology of EGFR mutant tumors and identify factors that affect TKI sensitivity. We developed transgenic mouse models of EGFR mutant lung cancer and have used them to study tumor progression and TKI resistance. When we modeled acquired resistance to the TKI osimertinib as a first-line therapy in transgenic mouse models of EGFRL858R-induced lung adenocarcinoma, we found that it is mediated largely through secondary mutations in EGFR—either C797S or L718V/Q or Kras mutations. We also identified a therapeutic approach to prevent the emergence of secondary mutations in EGFR. To determine whether the presence of co-occurring genetic alterations contributes to a more complex spectrum of resistance mechanisms in vivo, we have developed new mouse models to specifically evaluate the consequences of co-occurring tumor suppressor gene alterations on the progression and TKI sensitivity of EGFR mutant tumors. Collectively, our findings highlight how genetically engineered mouse models of lung cancer, including those with complex genotypes, can be leveraged to study tumor progression and drug resistance in vivo. Citation Format: Katerina A. Politi. Modeling sensitivity and resistance to systemic therapies in lung cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr IA10.