GSE183368
Characterizing the Tumor Immune Microenvironment of Syngeneic Mouse Models of Ovarian Cancer to Predict Response to PD-L1 blockade
Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer with an imperative need for new treatments. Immunotherapy has had marked success in some cancer types; however, clinical trials studying the efficacy of immune checkpoint inhibitors for the treatment of EOC provided benefit in <15% of patients. EOC is a particularly complex cancer since it develops from various tissues in the reproductive tract and metastasizes into the peritoneal cavity where it is able to colonize almost all organs, creating different tumor microenvironments (TME) containing a variety of immune profiles. In this study, we assessed the immune composition of different murine syngeneic models of EOC from different cellular origins (ovarian and fallopian tube epithelium) and harboring known mutations relevant to human disease, including TP53 mutation, PTEN suppression, and constitutive KRAS activation. We determined immunogenicity of multiple tumor models in vivo, the T and myeloid profile of orthotopic tumors and the immune composition of ascites, by flow cytometry, IHC and single cell RNA-sequencing. Our findings allowed us to predict which models might respond best to PD-L1 blockage, according to key characteristics such as tumor immunogenicity, MHC status, and T cell infiltration. Together these data highlight the heterogeneity found in murine EOC, as in human disease, identified features that might predict immune checkpoint inhibitor efficacy, and revealed crucial information about differences between murine models in the TME composition vs. ascites fluid. These data provide a solid foundation for selecting models in future testing of immunotherapies according to the immune composition and tumor characteristics. Overall design: scRNA-seq profiles of primary orthotopic STOSE and ID8 mouse tumors