In breast cancer, the type and distribution of infiltrating immune cells are associated with clinical outcome. Moreover, cancers with abundant tumor-infiltrating lymphocytes (TIL) are more likely to respond to immunotherapy, whereas those in which CD8+T cells are completely absent (deserts) or excluded are less likely to respond. Detailed understanding of this biology is limited by a lack of preclinical breast cancer models that recapitulate TIL distributions and their associated biology. Here we established mammary tumor-derived transplants (mTDT) from 12 Trp53-null mammary tumors in syngeneic BALB/cJ mice and examined the stability of their growth rate, TIL distribution, and transcriptomic profiles. All mTDTs were estrogen receptor negative. Half of the parental tumors were classified as infiltrated, and the rest were divided between excluded and desert phenotypes. After two orthotopic passages, most (70%) mTDT from infiltrated parents recapitulated this pattern, whereas the desert or excluded parental patterns were maintained in about half of daughter mTDT. Approximately 30% of mTDT gave rise to lung or liver metastases, although metastasis was not associated with a TIL phenotype. Unsupervised transcriptomic analysis clustered mTDT according to their TIL spatial patterns. Infiltrated mTDT transplanted subcutaneously or orthotopically were resistant to anti-PD-L1. Profiling implicated prolonged antigen stimulation and loss of effector function of lymphocytes rather than T-cell exhaustion in the lack of response of infiltrated mTDT to checkpoint blockade. In summary, the molecular diversity and immune complexity of mTDT should facilitate the dissection of mechanisms of breast cancer response to immunotherapies. Significance: A set of diverse preclinical models of breast cancer is characterized to enable mechanistic dissection of tumor-immune interactions and to improve the efficacy of immunotherapies.
CITATION STYLE
Moore, J., Ma, L., Lazar, A. A., & Barcellos-Hoff, M. H. (2022). Mammary Tumor-Derived Transplants as Breast Cancer Models to Evaluate Tumor-Immune Interactions and Therapeutic Responses. Cancer Research, 82(3), 365–376. https://doi.org/10.1158/0008-5472.CAN-21-0253
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