Animal Modeling and Preclinical Therapeutics Core in this P01 will use genetically engineered mouse (GEM) models of lung cancer, standard lung cancer cell line xenografts, and patient-derived lung cancer xenografts (PDXs) to facilitate the identification of the most effective tool compounds and combination(s) of compounds in the treatment of the genotype-specific stratified lung cancers studied in each of the projects. This core will provide technical and scientific expertise for in vivo experiments for each project in the program and allow the collective efforts of each of the three projects to focus more on the mechanistic studies to identify the best combination of compounds to maximize therapeutic efficacy. GEM models of lung cancers based on specific oncogenic genetic alterations have been instrumental in advancing the understanding of the molecular mechanisms of lung cancer pathogenesis and in the development of targeted therapeutics that are effective specific types of oncogene-driven lung cancer. Our laboratory has generated and characterized well over 30 conditional transgenic mice alleles that have inducible expression of each of the characterized lung cancer relevant oncogenic drivers. We have also created a repository of over 50 genomically annotated NSCLC lines, which can be used for conventional xenograft studies. More importantly, these GEM and standard xenograft lung cancer models have been employed successfully in multiple efficacy and pharmacodynamics studies with novel therapeutics that target genetically defined oncogenic drivers or their downstream effector pathways. In addition, our laboratory are in the process of generating and characterizing lung cancer PDX models derived from patient resected/biopsy samples at DFCI. The appropriate EGFR, KRAS, and other-genotype specific GEM, PDX and xenograft models will be used for each of the projects described in this P01 proposal. Overall the Animal Modeling and Preclinical Therapeutics Core will facilitate the preclinical discoveries that enable clinical translation with the ultimate goal of improving lung cancer outcomes.