Congenic Mouse Medels of Melanoma for the Characterization of Tumor Immune Responses



 DESCRIPTION (provided by applicant): There has been longstanding interest in the relationship between the immune system and malignant melanoma, the deadliest form of skin cancer. Melanoma has been the tumor of choice for the evaluation of a wide variety of therapeutic approaches that rely on stimulation of the immune system to combat cancer. Early clinical trials of modulators of immune checkpoints, including agents that block CTLA-4 and PD-1 signaling, focused on melanoma for the evaluation of clinical responses. The striking responses to immune checkpoint inhibitors noted in some melanoma patients have now been observed in several other malignancies, including renal cell, lung, breast, bladder, and prostate cancer. These findings are very encouraging, however the specific mechanisms of response and reasons why only a subset of patients respond to therapy are not known. Based on the critical role that mouse models played in the identification of CTLA-4 and PD-1 as immune checkpoints and therapeutic targets in cancer, it is likely that human-relevant animal models will be required to understand mechanisms of response and to optimize therapy so that a larger proportion of patients respond. We have generated a series of genetically engineered mouse models that reflect the genetic diversity of human melanoma and isolated corresponding congenic melanoma cells lines that form tumors following injection into immune competent C57Bl/6J mice. The genetic models and series of congenic lines represents an ideal set of models for the study of cancer immunology and response to immune therapies. We propose to characterize and validate these melanoma models, evaluate the effects of tumor genotype and mutational burden, and compare immune responses with those seen in human melanoma. Furthermore, we propose to characterize immune responses in novel melanoma brain metastasis and systemic metastasis models. We will make all of the findings and approaches available through the Oncology Models Forum.