Immune Microenvironment Related Competitive Endogenous RNA Network as Powerful Predictors for Melanoma Prognosis Based on WGCNA Analysis

Cutaneous melanoma is the most life-threatening skin malignant tumor due to its increasing metastasis and mortality rate. The abnormal competitive endogenous RNA network promotes the development of tumors and becomes biomarkers for the prognosis of various tumors. At the same time, the tumor immune microenvironment (TIME) is of great significance for tumor outcome and prognosis. From the perspective of TIME and ceRNA network, this study aims to explain the prognostic factors of cutaneous melanoma systematically and find novel and powerful biomarkers for target therapies. We obtained the transcriptome data of cutaneous melanoma from The Cancer Genome Atlas (TCGA) database, 3 survival-related mRNAs co-expression modules and 2 survival-related lncRNAs co-expression modules were identified through weighted gene co-expression network analysis (WCGNA), and 144 prognostic miRNAs were screened out by univariate Cox proportional hazard regression. Cox regression model and Kaplan-Meier survival analysis were employed to identify 4 hub prognostic mRNAs, and the prognostic ceRNA network consisting of 7 lncRNAs, 1 miRNA and 4 mRNAs was established. After analyzing the composition and proportion of total immune cells in cutaneous melanoma microenvironment through CIBERSORT algorithm, it is found through correlation analysis that lncRNA-TUG1 in the ceRNA network was closely related to the TIME. In this study, we first established cutaneous melanoma's TIME-related ceRNA network by WGCNA. Cutaneous melanoma prognostic markers have been identified from multiple levels, which has important guiding significance for clinical diagnosis, treatment, and further scientific research on cutaneous melanoma.