Multi-model preclinical platform predicts clinical response of melanoma to immunotherapy

Although immunotherapy has revolutionized cancer treatment, only a subset of patients demonstrates durable clinical benefit. Definitive predictive biomarkers and targets to overcome resistance remain unidentified, underscoring the urgency to develop reliable immunocompetent models for mechanistic assessment. Here we characterize a panel of syngeneic mouse models representing a variety of molecular and phenotypic subtypes of human melanomas and exhibiting their diverse range of responses to Immune Checkpoint Blockade (ICB). Comparative analysis of genomic, transcriptomic and tumor-infiltrating immune cell profiles demonstrated alignment with clinical observations and validated the correlation of T-cell dysfunction and exclusion programs with resistance. Notably, genome-wide expression analysis uncovered a Melanocytic Plasticity Signature (MPS) predictive of patient outcome in response to ICB, suggesting that the multipotency and differentiation status of melanoma can determine ICB benefit. Our comparative preclinical platform recapitulates melanoma clinical behavior and can be employed to identify new mechanisms and treatment strategies to improve patient care. The cell lines and GEM-derived allografts from the four models were harvested and DNA was extracted for whole exome sequencing. 1.0x106 melanoma cells (Cell line-derived allografts) from each model were implanted subcutaneously (s.c.) into C57BL/6N mice. When the tumors reached in average 75mm3, mice were randomized and treated with mouse aCTLA-4 (BioXCell, BP0164, clone 9D9) or mouse IgG2b as isotype control (BioXcell, BP0086). Antibodies were administered intravenously (i.v.) at a final dose of 10mg/Kg twice per week for a total of 4 doses. Tumors were harvested at endpoint and RNA extracted for sequencing.