CORE 2 PROJECT SUMMARY PRECLINICAL MODELS AND PATHOLOGY CORE The Preclinical Core (Core #2) leverages the knowledge and expertise from several Moffitt investigators and core facilities and will pursue three aims that systematically support the Program Projects at three critical stages; 1) model development, 2) measurement and analysis of outcome, and 3) validation in human cohorts and organoid models. In the Aim 1, Core #2 is tasked with mouse model generation and characterization. The Core will use the embryonic stem cell-genetically engineered mouse model (ESC-GEMM) approach to enable the rapid generation of lung cancer mouse models. To this end, ESCs will be established from existing lung cancer GEMMs that also harbor regulatory alleles for efficient targeting of ESCs and control of gene expression. ESCs will be targeted with inducible expression cassettes, followed by injection into blastocysts to generate chimeric animals. ESC-derived lung cells in such chimeras carry the alleles necessary to induce lung tumorigenesis, and chimeras will be used as experimental animals without further breeding. This approach allows for the very rapid generation of lung cancer models having modulated expression or activity of metabolic enzymes of interest. In Aim 2, Core #2 will streamline the quantification of tumor burden in these mouse models by providing digital pathological (DP) analysis of murine lung cancer models. As input, histology slides are imaged at multiple magnifications using automated slide scanners. The resulting high-resolution images are processed and analyzed using innovative machine learning algorithms we have developed. The platform allows for the identification, characterization, and quantification of lung tumors and individual cells within whole lung sections. Deep learning methods will be applied to provide a comprehensive characterization of lung tumors, including tumor grading and the assessment of immune cell infiltration. Histology samples and datasets created by the program projects will be used to create training libraries for new algorithm development. The DP platform allows for highly accurate and rapid image analysis, accelerating the characterization of lung tumor models. In Aim 3, Core #2 will provide resources and expertise to validate outcomes from the mouse studies of the first two Aims. The Core will provide large, well-annotated human cohorts represented by tissue microarrays and a centralized workflow for the generation of organoid models. The Core will assist with project planning and method development, diagnostic consultation, biomarker scoring, result interpretation, and manuscript writing. Additional pathology resources will include microscopic evaluation of animal and human tissues for adequacy and diagnosis, antibody selection guidance, optimization for immunohistochemistry (IHC), and multiplexed immunofluorescence imaging.