Objective: Uveal melanoma (UM) is an aggressive malignancy with a poor prognosis and no available effective treatment. Therefore, exploring a potential prognostic marker for UM could provide new possibilities for early detection, recurrence, and treatment.
Methods: In this study, we used "ConsensusClusterPlus" to classify patients with UM into subgroups, screened for significant differences in immune prognostic factors between subgroups, selected three genes using LASSO (Least absolute shrinkage and selection operator) regression to construct a risk model, and performed tumor immune cell infiltration analysis on the risk model. infiltration analysis, and then verified the heterogeneous role of the 3 core genes in other cancers by pan-cancer analysis and validate its expression by RT-qPCR in normal and tumor cells.
Results: We consistently categorized 80 UM patients into two subgroups after the immunogenetic set, where the UM1 subgroup had a better prognosis than the UM2 subgroup, and used 3 immune-related genes AZGP1, SLCO5A1, and CTF1 to derive risk scores as independent prognostic markers and predictors of UM clinicopathological features. We found significant differences in overall survival (OS) between low- and high-risk groups, and prognostic models were negatively correlated with B cell and myeloid dendritic cell and positively correlated with CD8+ T cell AZGP1 and CTF1 were significantly upregulated in UM cells compared with normal UM cells.
Conclusion: Immunogens are significantly associated with the prognosis of UM, and further classification based on genetic characteristics may help to develop immunotherapeutic strategies and provide new approaches to develop customized treatment strategies for patients.
Keywords: UM; bioinformatics; immunity; prognosis; uveal melanoma.
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