Divergent immune landscapes of primary and syngeneic Kras-driven mouse tumor models

Immune cells play critical functions in cancer, and mice with intact immune systems are vital to understanding tumor immunology. Both genetically engineered mouse models (GEMMs) and syngeneic cell transplant approaches use immunocompetent mice to define immune-dependent events in tumor development and progression. Due to their rapid and reproducible nature, there is expanded interest in developing new syngeneic tools from established primary tumor models. However, few studies have examined the extent that syngeneic tumors reflect the immune profile of their originating primary models. Here, we describe comprehensive immunophenotyping of two well-established GEMMs and four new syngeneic models derived from these parental primary tumors. To our knowledge, this is the first systematic analysis comparing immune landscapes between primary and orthotopic syngeneic tumors. These models all use the same well-defined human-relevant driver mutations, arise at identical orthotopic locations, and are generated in mice of the same background strain. This allows for a direct and focused comparison of tumor immune landscapes in carefully controlled mouse models. We identify key differences between the immune infiltrate of GEMM models and their corresponding syngeneic tumors. Most notable is the divergence of T cell populations, with different proportions of CD8+ T cells and regulatory T cells across several models. We also observe immune variation across syngeneic tumors derived from the same primary model. These findings highlight the importance of immune variance across mouse modeling approaches, which has strong implications for the design of rigorous and reproducible translational studies.

Automated summary

This study systematically analyzed the immune landscapes of two established GEMMs and four new syngeneic models, revealing key differences in immune infiltrates between GEMM models and their corresponding syngeneic tumors, particularly in the distribution of T cell populations. The study also observed immune variations across syngeneic tumors derived from the same primary model, highlighting the importance of immune variance in mouse modeling approaches for translational research design.