Background: Metastatic melanoma (MM) represents a common malignancy with poor prognosis. Immune checkpoint inhibition (ICI), including PD-1 blockade, has been emerging as the popular therapeutic in MM for its durable treatment effect, but its response rate is still limiting. Methods: We comprehensively analyzed the associations between KMT2C somatic mutation and the tumor microenvironment as well as the ICI response of MM patients based on three published cohorts. Gene differential expression analysis between tumor samples with mutated and wild-type KMT2C was performed by DESeq2 package. Functional enrichment analysis was conducted by using clusterProfiler package. Kaplan-Meier was used to perform overall survival probability estimate through survival package and rms package was applied for the construction of nomogram model. Results: We report here that KMT2C is a potential biomarker for anti-PD-1 treatment in MM. This biomarker can be used for comprehensively analyzing its association with patients’ prognosis, tumor microenvironment and genomic features. Mutations of KMT2C profoundly altered expression of immune- and DNA replication-related genes in MM tumors. MM patients harboring KMT2C mutations showed significantly better overall survival (OS) after treatment with PD-1 monoclonal antibody as compared to wild-type KMT2C. Although KMT2C mutation has no significant influence on immune cell infiltration into MM tumors, the tumor mutation load and neoantigen load are indeed elevated in KMT2C mutated MM samples. This might represent a possible pathway through which KMT2C regulates the response of MM patients to anti-PD-1 treatment. Finally, we constructed a nomogram model by combing the independent prognostic factors, including KMT2C mutation, which could effectively predict the 1-year survival probability of MM patients after anti-PD-1 treatment. Conclusions: In conclusion, we report the role of KMT2C in anti-PD-1 treatment response regulation in MM for the first time. This may consequently be helpful for KMT2C personalized application.