Multi-model preclinical platform predicts clinical response of melanoma to immunotherapy
Perez-Guijarro, E.; Yang, H. H.; Araya, R. E.; El Meskini, R.; Michael, H. T.; Vodnala, S. K.; Marie, K. L.; Graff-Cherry, C.; Chin, S.; Iacovelli, A. J.; Kulaga, A.; Fon, A.; Michalowski, A. M.; Hugo, W.; Lo, R. S.; Restifo, N. P.; Van Dyke, T.; Sharan, S. K.; Goldszmid, R. S.; Weaver Ohler, Z.; Lee, M. P.; Day, C.-P.; Merlino, G.
Show abstract
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 the main molecular and phenotypic subtypes of human melanomas and exhibiting their 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 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.
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