Multiomic profiling of checkpoint inhibitor-treated melanoma: Identifying predictors of response and resistance, and markers of biological discordance

We concurrently examine the whole genome, transcriptome, methylome, and immune cell infiltrates in baseline tumors from 77 patients with advanced cutaneous melanoma treated with anti-PD-1 with or without anti-CTLA-4. We show that high tumor mutation burden (TMB), neoantigen load, expression of IFNγ-related genes, programmed death ligand expression, low PSMB8 methylation (therefore high expression), and T cells in the tumor microenvironment are associated with response to immunotherapy. No specific mutation correlates with therapy response. A multivariable model combining the TMB and IFNγ-related gene expression robustly predicts response (89% sensitivity, 53% specificity, area under the curve [AUC], 0.84); tumors with high TMB and a high IFNγ signature show the best response to immunotherapy. This model validates in an independent cohort (80% sensitivity, 59% specificity, AUC, 0.79). Except for a JAK3 loss-of-function mutation, for patients who did not respond as predicted there is no obvious biological mechanism that clearly explained their outlier status, consistent with intratumor and intertumor heterogeneity in response to immunotherapy. [Display omitted] •Multiomic analysis predicts response but not resistance to immunotherapy•Nonresponders had no common mechanisms of resistance•Structural rearrangements and PSMB8 promoter methylation occurred in nonresponders•JAK3 mutation was a possible resistance mechanism in a patient predicted to respond Newell et al. used clinical features and multiomic analysis (WGS, RNAseq, immunohistochemistry, methylation) to show that IFNγ plus TMB most accurately predicted response to immunotherapy, but not resistance. No common mechanism of resistance was identified in keeping with tumor heterogeneity, and patients with clinical and molecular discordance were analyzed individually.