Abstract 2762: Spatial proteomics of lung adenocarcinoma mouse models with divergent propensities for metastasis

Abstract Introduction: Lung cancer is the leading cause of cancer deaths worldwide with most deaths attributed to metastasis. Metastases in existing mouse models of lung adenocarcinoma (LUAD) is sporadic and often requires several months of aging. These factors limit these models for basic and pre-clinical research aimed at identifying mechanisms of metastatic disease. We have recently developed two novel mouse models of LUAD that feature constitutively active Kras, loss of Trp53 function and truncated Dicer1 in different cell types. The observed survival and metastatic phenotypes of the models are dependent on the cell type in which the genetic alterations are made. We applied spatial proteomics and metabolomics to investigate molecular drivers underlying the phenotypic differences in our models. Methods and Results: Mouse models were generated by adding mutations in Dicer1, an RNAse III enzyme within the microRNA (miRNA) biosynthesis pathway, to a mouse model of Kras-driven LUAD. For both models, tumorigenesis was induced by conditional expression of an oncogenic allele of Kras, deletion of both alleles of Trp53 and deletion of one allele of Dicer1 in one cell type and the expression of a truncated Dicer1 allele in a different cell type. Mice expressing KrasG12D and deleted Trp53 in club cells without Dicer1 truncation have a reported median survival of 28. 6 weeks after tumor induction. We observed accelerated development of LUAD and lymph node metastasis (12. 1 weeks) only when we induced tumorigenesis in club cells and truncate Dicer1 in alveolar type II (ATII) cells. Induction of tumorigenesis in ATII cells and truncation of Dicer1 in club cells did not accelerate tumorigenesis or lead to detectable metastasis. Prelminary spatial proteomic analysis revealed significant upregulation of proteins associated with mitochondrial respiratory chain complex I in the tumors of both models which is consistent with processes of bioenergetic adaptation of tumor cells to hypoxic conditions. Gene Ontology annotation term enrichment revealed that the tumors of the two models have distinctive molecular function profiles. Both models show significant disruption of amino acid metabolism but only the model with increased metastatic potential showed apparent disruption in metabolites associated with steroidogenesis. Conclusions: Through cell type specific truncation/deletion of Dicer1 we have generated a mouse model that rapidly develops Kras/Trp53 driven LUAD and metastatic disease. Our findings suggest that tumorigenesis and metastasis are influenced by miRNA-mediated communication between different cell types. Additional studies are underway to link miRNA expression in these models to the results reported here for spatial proteomics and metabolomics. We will continue to develop this model to investigate the molecular mechanisms underlying metastasis. Citation Format: Paige Ramkissoon, Naomi Mitchell-Hutchinson, Julie Wells, Rick Maser, Tim Stodola, Brian Hoffmann, Anne Marchini, Elaine Bechtel, Rosalinda Doty, Carol J. Bult. Spatial proteomics of lung adenocarcinoma mouse models with divergent propensities for metastasis abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 2762.