BMC Genomics (Jan 2020)

Comparison of the molecular and cellular phenotypes of common mouse syngeneic models with human tumors

  • Wenyan Zhong,
  • Jeremy S. Myers,
  • Fang Wang,
  • Kai Wang,
  • Justin Lucas,
  • Edward Rosfjord,
  • Judy Lucas,
  • Andrea T. Hooper,
  • Sharon Yang,
  • Lu Anna Lemon,
  • Magali Guffroy,
  • Chad May,
  • Jadwiga R. Bienkowska,
  • Paul A. Rejto

DOI
https://doi.org/10.1186/s12864-019-6344-3
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 17

Abstract

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Abstract Background The clinical success of immune checkpoint inhibitors demonstrates that reactivation of the human immune system delivers durable responses for some patients and represents an exciting approach for cancer treatment. An important class of preclinical in vivo models for immuno-oncology is immunocompetent mice bearing mouse syngeneic tumors. To facilitate translation of preclinical studies into human, we characterized the genomic, transcriptomic, and protein expression of a panel of ten commonly used mouse tumor cell lines grown in vitro culture as well as in vivo tumors. Results Our studies identified a number of genetic and cellular phenotypic differences that distinguish commonly used mouse syngeneic models in our study from human cancers. Only a fraction of the somatic single nucleotide variants (SNVs) in these common mouse cell lines directly match SNVs in human actionable cancer genes. Some models derived from epithelial tumors have a more mesenchymal phenotype with relatively low T-lymphocyte infiltration compared to the corresponding human cancers. CT26, a colon tumor model, had the highest immunogenicity and was the model most responsive to CTLA4 inhibitor treatment, by contrast to the relatively low immunogenicity and response rate to checkpoint inhibitor therapies in human colon cancers. Conclusions The relative immunogenicity of these ten syngeneic tumors does not resemble typical human tumors derived from the same tissue of origin. By characterizing the mouse syngeneic models and comparing with their human tumor counterparts, this study contributes to a framework that may help investigators select the model most relevant to study a particular immune-oncology mechanism, and may rationalize some of the challenges associated with translating preclinical findings to clinical studies.

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