Rethinking Immunotherapy Resistance in Melanoma: A Narrative Review of Clinical Patterns, Resistance Mechanisms, and...

Background/Objectives: Immune checkpoint inhibitors have revolutionized the treatment of advanced melanoma, yet primary and acquired resistance remain major barriers to durable disease control. This narrative review examines the clinical patterns, biological mechanisms, biomarker limitations, and therapeutic implications of immunotherapy failure. Methods: A structured search of PubMed, Web of Science, and ClinicalTrials.gov identified relevant studies published from January 2010 to May 2026, supplemented by landmark earlier reports. Results: Immunotherapy resistance encompasses heterogeneous patterns, including early progression, oligoprogression, dissociated response, brain-dominant progression, relapse after response, and progression after treatment discontinuation. These clinical phenotypes arise from overlapping mechanisms such as loss of antigen presentation, impaired interferon signaling, oncogenic immune exclusion, melanoma dedifferentiation, suppressive myeloid and regulatory T-cell programs, stromal and vascular barriers, metabolic restriction, and deterioration of tumor-reactive T-cell clones. Conventional response criteria and static biomarkers, including PD-L1 expression and tumor mutational burden, do not adequately capture this complexity because resistance varies across lesions and evolves under treatment pressure. Negative trials of IDO1 inhibition, cytokine intensification, vaccines, and intratumoral immune stimulation further show that biological plausibility and early activity do not guarantee clinical benefit when target engagement, patient enrichment, and endpoint selection are inadequate. Conclusions: Immunotherapy resistance in melanoma should be viewed as a variety of biologically distinct clinical states rather than a single endpoint. Future progress will require resistance-matched treatment, longitudinal tissue and circulating tumor DNA assessment, adaptive trial designs, and endpoints aligned with treatment kinetics. This framework may improve salvage selection and interpretation of post-PD-1 studies in clinical practice.