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Differential Expression of Autophagy-Related Long Non-Coding RNA in Melanoma
Abstract:
To explore the role of autophagy-related differential long non-coding RNA (lncRNA) in the pathogenesis of melanoma, we established a prognostic prediction model for patients with melanoma based on the expression profiles of autophagy-related gene. Based on The Cancer Genome Atlas and GeneCard database, we used single-sample gene set enrichment analysis (ssGSEA), weighted gene co-expression network analysis (WGCNA), uniCOX in R software for COX proportional hazard regression analysis, and enrichment analysis to get an idea of biological processes with autophagy-related genes, which evaluates the relationship between autophagy-related genes and immune cell infiltration in patients with melanoma. The roles of identified lncRNA were evaluated by the risk score based on the results of single factor regression analysis for each lncRNA and on the prognosis for patients obtained from the database. Then, the whole sample was divided into high- and low-risk groups. Survival curve analysis showed that low-risk group had a better prognosis. Enrichment analysis revealed multiple key pathways enriched with lncRNA-associated genes. Analysis of immune cell infiltration revealed differences between high- and low-risk groups. Finally, 3 datasets verified the effect of our model on prognosis. There are important autophagy-related lncRNA in patients with melanoma. Top 6 lncRNA are significantly related to the overall survival rate of patients with melanoma and provide the basis for predicting the prognostic survival of patients.
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