Use of Murine Models 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 choice and use of pre-clinical models are necessary for rigorous, pre-clinical studies to rapidly move laboratory findings into the clinic to treat patients. Methods: To elucidate how tumor latency and the heterogeneity of the TME contributes to ICB resistance, we performed comprehensive characterization of the TME using quantitative flow-cytometry and RNA expression analysis (NanoString) utilizing three distinct breast cancer models, all derived from the same autochthonous model. Tumor cells were obtained from the commonly used MMTV-PyMT murine breast cancer model and 1E6, 1E5 or 1E4 cells were either immediately injected into the mammary fat pad of FVB/NJ wild type mice or frozen (i.e. the tumor inoculation derived from the MMTV-PyMT tumors were never cultured). We then correlated the immunophenotyping to the efficacy observed from ICB. Results: These studies reveal that the number of cells used to generate syngeneic tumors significantly influences tumor latency, the infiltrating leukocyte population and response to ICB. The 4 models had vastly different TMEs which correlated to responses to ICB. Compared to the autochthonous model, all three 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 tumor cell PD-L1expression and T-cell PD-1 expression did not. Conclusions: Here we have identified ICB-sensitive and resistant breast cancer models, generated from the same tumor cell inoculum. These models represent an opportunity to further interrogate the TME for breast cancer treatment and provide novel insights into therapeutic combinations and response to ICB. We believe this work serves as an important resource for the field to inform proper mouse model selection for pre-clinical studies.