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. Methods Three versions of a common syngeneic model derived from the MMTV-PyMT autochthonous model were generated by inoculating 1E6, 1E5, or 1E4 cells derived from the MMTV-PyMT mouse into wildtype recipient mice. To elucidate how tumor latency and TME heterogeneity contribute to ICB resistance, comprehensive characterization of the TME using quantitative flow-cytometry and RNA expression analysis (NanoString) was performed. Subsequently, response to ICB was tested. These procedures were repeated using the EMT6 breast cancer model. Results The 3 syngeneic versions of the MMTV-PyMT model had vastly different TMEs that correlated to ICB response. The number of cells used to generate syngeneic tumors significantly influenced tumor latency, infiltrating leukocyte populations, and response to ICB. These results were confirmed using the EMT6 breast cancer model. Compared to the MMTV-PyMT autochthonous model, all 3 MMTV-PyMT 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 autochthonous 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 tumor cell number correlates with tumor latency, TME, and response to ICB. ICB-sensitive and resistant syngeneic breast cancer models were identified, in which the 1E4 syngeneic model was most resistant to ICB. Given the lack of benefit from ICB in breast cancer, identifying 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.