Murine syngeneic tumor models are critical to novel immuno-based therapy development, but the molecular and immunologic features of these models are still not clearly defined. The translational relevance of differences between the models is not fully understood, impeding appropriate preclinical model selection for target validation, and ultimately hindering drug development. Across a panel of commonly used murine syngeneic tumor models, we showed variable responsiveness to immunotherapies. We used array comparative genomic hybridization, whole-exome sequencing, exon microarray analysis, and flow cytometry to extensively characterize these models, which revealed striking differences that may underlie these contrasting response profiles. We identified strong differential gene expression in immune-related pathways and changes in immune cell–specific genes that suggested differences in tumor immune infiltrates between models. Further investigation using flow cytometry showed differences in both the composition and magnitude of the tumor immune infiltrates, identifying models that harbor “inflamed” and “non-inflamed” tumor immune infiltrate phenotypes. We also found that immunosuppressive cell types predominated in syngeneic mouse tumor models that did not respond to immune-checkpoint blockade, whereas cytotoxic effector immune cells were enriched in responsive models. A cytotoxic cell–rich tumor immune infiltrate has been correlated with increased efficacy of immunotherapies in the clinic, and these differences could underlie the varying response profiles to immunotherapy between the syngeneic models. This characterization highlighted the importance of extensive profiling and will enable investigators to select appropriate models to interrogate the activity of immunotherapies as well as combinations with targeted therapies in vivo. Cancer Immunol Res; 5(1); 1–13. ©2016 AACR.
Note: Supplementary data for this article are available at Cancer Immunology Research Online (http://cancerimmunolres.aacrjournals.org/).
- Received May 20, 2016.
- Revision received October 24, 2016.
- Accepted November 11, 2016.
- ©2016 American Association for Cancer Research.