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In Frontiers in immunology ; h5-index 100.0

Background : Melanoma, as one of the most aggressive and malignant cancers, ranks first in the lethality rate of skin cancers. Cuproptosis has been shown to paly a role in tumorigenesis, However, the role of cuproptosis in melanoma metastasis are not clear. Studying the correlation beteen the molecular subtypes of cuproptosis-related genes (CRGs) and metastasis of melanoma may provide some guidance for the prognosis of melanoma.

Methods : We collected 1085 melanoma samples in The Cancer Genome Atlas(TCGA) and Gene Expression Omnibus(GEO) databases, constructed CRGs molecular subtypes and gene subtypes according to clinical characteristics, and investigated the role of CRGs in melanoma metastasis. We randomly divide the samples into train set and validation set according to the ratio of 1:1. A prognostic model was constructed using data from the train set and then validated on the validation set. We performed tumor microenvironment analysis and drug sensitivity analyses for high and low risk groups based on the outcome of the prognostic model risk score. Finally, we established a metastatic model of melanoma.

Results : According to the expression levels of 12 cuproptosis-related genes, we obtained three subtypes of A1, B1, and C1. Among them, C1 subtype had the best survival outcome. Based on the differentially expressed genes shared by A1, B1, and C1 genotypes, we obtained the results of three gene subtypes of A2, B2, and C2. Among them, the B2 group had the best survival outcome. Then, we constructed a prognostic model consisting of 6 key variable genes, which could more accurately predict the 1-, 3-, and 5-year overall survival rates of melanoma patients. Besides, 98 drugs were screened out. Finally, we explored the role of cuproptosis-related genes in melanoma metastasis and established a metastasis model using seven key genes.

Conclusions : In conclusion, CRGs play a role in the metastasis and prognosis of melanoma, and also provide new insights into the underlying pathogenesis of melanoma.

Liu Jin-Ya, Liu Le-Ping, Li Ze, Luo Yan-Wei, Liang Fang

2022

cuproptosis, machine learning, melanoma, metastasis model, prognostic model, subtype