Molecular and cellular phenotypic differences distinguish murine syngeneic models from human tumors

The clinical success of immune checkpoint inhibitors that target cytotoxic T-lymphocyte associated protein 4 (CTLA4) and programmed cell death protein 1 (PD-1) or programmed death ligand-1 (PD-L1) demonstrates that reactivation of the human immune system delivers durable responses for some patients and represents an exciting approach for cancer treatment. The combination of multiple immunotherapies as well as the combination of immunotherapy with targeted therapy is being pursued vigorously to increase the rate and extend the duration of response. Preclinical models for immuno-oncology (IO) typically require immunocompetent mice bearing murine syngeneic tumors. To facilitate translation of preclinical studies into human, we characterized the genomic, transcriptomic, and protein expression of a panel of mouse tumor cell lines grown culture as well as tumor samples. Our studies identified many genetic and cellular phenotypic differences that distinguish murine syngeneic models from human cancers. For example, only a small fraction of the somatic single nucleotide variants (SNVs) in mouse cell lines directly match SNVs from human actionable cancer genes. At the cellular level, some epithelial tumor models have a more mesenchymal phenotype with relatively low T-lymphocyte infiltration compared to the corresponding human cancers. Furthermore, in contrast to what has been reported for human tumors, we did not observe a correlation between neoantigen load and cytolytic activity in syngeneic models. Finally, the relative immunogenicity of syngeneic tumors does not typically resemble that of human tumors of the same tissue origin. CT26, a colon tumor model, had the highest immunogenicity and was the most responsive model to CTLA4 inhibitor treatment, by contrast to the relatively low immunogenicity and response rate to checkpoint inhibitor therapies in human colon cancers. These differences highlight limitations of syngeneic models for evaluating novel immune therapies and rationalize some of the challenges associated with translating preclinical findings to clinical studies.