Abstract 4630: Deep Immuno-profiling of syngeneic tumor mouse models for preclinical studies

Abstract Identification of major cellular players involved in progression of cancer is key to success of new immunotherapies. It is however a daunting challenge due to the complex interplay between tumor cells and the immune system. Component of innate and adaptive immunity may be directed to a pro- or anti-tumor function. In order to cope with the complexity of the tumor microenvironment (TME), it is necessary to use an experimental approach characterizing the heterogeneity of cell types, the evolution of their relative proportion and their fine-tuned functional specificity. This approach should lead to the identification of new cellular biomarkers characteristics of different stages of tumor cancer progression. To decipher the impact of immunotherapy treatments, cellular phenotyping of leukocytes infiltrating TME but also those present in peripheral organs is necessary. In order to increase our understanding in the precise mode of action of anti-PD1 treatment at the cellular level in sensitive and unsensitive syngeneic models, we investigated immunophenotypes and responses to immune checkpoint inhibitor (ICI) of several hallmark tumor models (MC38, CT26, B16F10, B16-OVA, RENCA, EMT6) in immunocompetent mouse models by flow and mass cytometry. We compared growth kinetics and profiled the immune cell composition of tumor microenvironment (TME), draining lymph node (dLN) and blood in order to establish immune-phenotypic cell signatures that correlates with treatment efficacy. Supervised, unsupervised and integrative data analysis arewere used to identify significant changes across different experimental settings. Our results indicate that each model possesses a unique tumor-immune infiltrate profile that can be modulated with immunotherapies. Overall, these studies provide an important resource of highly well-characterized syngeneic tumor model and highlight the importance of tumor immune landscape changes across models that will drive selection of the most appropriate model to test novel immunotherapeutic agents and enhance our translation of knowledge from syngeneic models to human tumors. Citation Format: Anais Joachim, Emilie Maturin, Marielle Mello, Lillia Hadjem, Magali Grange, Olivier Deas, Ana Zarubica, Bernard Malissen, Hervé Luche. Deep Immuno-profiling of syngeneic tumor mouse models for preclinical studies. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4630.