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Expression Patterns of Necroptosis-Related Genes: Predicting Prognosis and Immunotherapeutic Effects in Cutaneous Melanoma.

Journal of oncology (2022-07-26)
Dong Dong, Wei Wang, Heng Wang, Liang Chen, Tianyi Liu
RÉSUMÉ

Increasing evidence has shown a strong correlation between necroptosis and antitumor immunity. However, precise expression patterns of necroptosis-related genes in cutaneous melanoma (CM) have not been clearly elucidated nor have their effects on the immune cell infiltration in the tumor microenvironment. We investigated the expression patterns of necroptosis-related genes of individuals with cutaneous melanoma based on 67 necroptotic genes and methodically associated the expression patterns with the comprehensive characterization of tumor immune microenvironment. Using principal component analysis methods, the NRG score was developed to quantify the expression patterns of necroptotic genes in CM patients. Three different necroptotic subtypes were determined with marked survival differences, showing distinct characteristics of immune cell infiltration. The high NRG score group with comprehensive immunosuppression was characterized by the worse immunotherapeutic efficacy and the poor prognosis, while the low NRG score group indicated a robust activation of immune function and a better response to immunotherapy, which may be responsible for a better prognosis. Furthermore, the predictive ability of the NRG score on prognosis and immunotherapeutic benefits was further revalidated using the other independent datasets of cutaneous melanoma. The results indicated that patients with low NRG scores exhibited prolonged survival. Surprisingly, all patients with CM with clinical response, including complete response/partial response, belonged to the low NRG score group. Our present work revealed the close association between expression patterns of necroptosis-associated genes and tumor immune microenvironment. NRG score can serve as a potential predictor to independently assess patients' prognosis with CM and effectively estimate the response to immunological therapy, thus facilitating the identification of appropriate candidates with CM for immunotherapy and the formulation of individualized therapeutic approaches.

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