Landscape and Clinical Significance of Immune Checkpoint in Cutaneous Melanoma

BackgroundThe incidence of cutaneous melanoma (CM) is increasing, and its prognosis is not optimistic. Although immune checkpoint (ICP) inhibitors are effective in the treatment of CM patients, they are not effective for all CM patients. There is an urgent need for a marker to predict both the prognosis and the immunotherapy effect in patients with CM. ApproachesTwo groups of patients with greatly different prognosis and response to immunotherapy were identified by unwatched cluster exploration of TCGA on the basis of 34 ICPs. The prognosis and immunotherapy effect of CM were predicted by developing a precise and given signature on the basis of ICPs, and a multivariate Cox risk regression model was established from the TCGA cohort consisting of 454 CM samples. The model was validated in 210 and 231 samples in the test and verification cohorts, respectively. ResultsThe prognosis in clinical subgroups was predicted by the classification system. High-risk patients had poorer responses to chemotherapy and immunotherapy. Finally, the signature was recognized as an independent prognostic factor. Based on checkpoint-based signature (ICPBS) and clinical characteristics, we constructed a nomogram for the prognosis in patients with CM, which was superior to ICPBS in efficacy than ICPBS alone. ConclusionAs a useful prognostic tool to further improve cancer immunotherapy, the signature can accurately predict recurrence and overall survival among patients with CM.

Automated summary

The incidence of cutaneous melanoma is rising, and better markers are needed to predict prognosis and immunotherapy effectiveness. By analyzing TCGA data and developing a signature based on immune checkpoint proteins, researchers were able to accurately predict prognosis and response to therapy in melanoma patients. The signature was found to be an independent prognostic factor and a nomogram based on the signature was more effective than the signature alone.