Comparing syngeneic and autochthonous models of breast cancer to identify tumor immune components that correlate with response to immunotherapy in breast cancer

Abstract Background: The heterogeneity of the breast tumor microenvironment (TME) may contribute to the lack of durable responses to immune checkpoint blockade (ICB), however, mouse models to test this are currently lacking. Proper selection and use of preclinical models are necessary for rigorous, preclinical studies to rapidly move laboratory findings into the clinic to treat patients.Methods: We compared 3 versions of a common syngeneic and autochthonous mouse model to elucidate how tumor latency and TME heterogeneity contributes to ICB resistance. We performed comprehensive characterization of the TME using quantitative flow-cytometry and RNA expression analysis (NanoString) utilizing three distinct syngeneic breast cancer models, all derived from the MMTV-PyMT autochthonous model. A commonly used protocol was used to obtain tumor cells from MMTV-PyMT mice and 1E6, 1E5 or 1E4 cells were immediately injected into the mammary fat pad of FVB/NJ wild type mice. We then performed deep immunophenotyping and tested ICB efficacy in the 3 syngeneic models compared to the autochthonous model. Results: The 4 models had vastly different TMEs that correlated to ICB responses. We found that the number of cells used to generate syngeneic tumors significantly influences tumor latency, infiltrating leukocyte population and response to ICB. Compared to the autochthonous model, all 3 syngeneic models had significantly more tumor infiltrating lymphocytes (TILs; CD3+, CD4+, and CD8+) and higher proportions of PD-L1 positive myeloid cells, whereas the MMTV-PyMT model had the highest frequency of myeloid cells out of total leukocytes. Increased TILs correlated with response to anti-PD-L1 and anti-CTLA-4 therapy; but PD-L1expression on tumor cells or PD-1 expression of T-cells did not.Conclusions: These studies reveal that the commonly used syngeneic models have low concordance with the autochthonous model. We have identified ICB-sensitive and resistant syngeneic breast cancer models, generated from the same tumor cell inoculum, and find that only the 1E4 syngeneic model is representative of the slow growing, autochthonous model. Given the lack of benefit from ICB in breast cancer, the identification of robust murine models presented here provides the opportunity to further interrogate the TME for breast cancer treatment and provide novel insights into therapeutic combinations to overcome ICB resistance.