A prevalent skin cancer with a dismal prognosis before it spreads, cutaneous melanoma is challenging to cure. We downloaded melanoma data from the TCGA database, and the patients there were split into two groups: one for training and one for validation. After that, tumor metastatic genes in melanoma were evaluated using univariate Cox regression, LASSO regression, and multivariate Cox regression. A predictive model linked to melanoma metastasis genes was then created. To categorize melanoma patients, the model might be employed. Melanoma patients in the training and validation cohorts could be divided into high-risk and low-risk groups; the high-risk group had a considerably worse prognosis (P <0.05). The theoretical groundwork for comprehending the function of metastatic genes in melanoma is established by our investigation. Several algorithms were used to evaluate the relationship between the immune cell infiltration level and the model gene CD74. In an immunotherapy cohort, CD74's capacity to forecast treatment outcome was evaluated. Prognosis was found to be improved by high CD74 expression. High CD74 expression was substantially linked to the activation of immune-related pathways, according to correlation pathway analysis. Patients who responded to immunotherapy and those with lower IC50 who received chemotherapeutic treatment tended to express CD74 at a higher level. In melanoma cell lines, RT-qPCR discovered a substantial downregulation of CD74 expression. Analysis of the single-cell transcriptome revealed that B cells express CD74 with excellent specificity. Analysis using "CellChat" demonstrated that CD74 participates in MIF and MHC-II-mediated pathways that control the immune microenvironment. In conclusion, CD74 will be helpful for immunotherapy and is a trustworthy biomarker for melanoma.
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