A novel RNA sequencing-based prognostic nomogram to predict survival for patients with cutaneous melanoma: Clinical trial/experimental study

BACKGROUND: Plenty of evidence has suggested that long non-coding RNAs (lncRNAs) have played a vital part may act as prognostic biomarkers in a variety of cancers. The aim of this study was to screen survival-related lncRNAs and to construct a lncRNA-based prognostic model in patients with cutaneous melanoma (CM). METHODS: We obtained lncRNAs expression profiles and clinicopathological data from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. A lncRNA-based prognostic model was established in training set. The established prognostic model was evaluated, and validated in the validation set. Then, a prognostic nomogram combining the lncRNA-based risk score and clinicopathological characteristics was developed in training set, and assessed in the validation set. The accuracy of the model was evaluated by the discrimination and calibration plots. RESULTS: A total of 212 lncRNAs were identified to be differentially expressed in CM. After univariate analysis, LASSO penalized regression analysis, and multivariate analysis, 3 lncRNAs were used to construct risk score model. The proposed risk score model could divide patients into high-risk and low-risk groups with significantly different survival in both training set and validation set. The ROC curve showed good performance in survival prediction in both sets. Furthermore, the nomogram for predicting 3-, 5-, and 10-year OS was established based on lncRNA-based risk score and clinicopathologic factors. The prognostic accuracy of the risk model was confirmed by the discrimination and calibration plots in both training set and validation set. CONCLUSIONS: We established a novel three lncRNA-based risk score model and nomogram to predict overall survival of CM. The proposed nomogram may provide information for individualized treatment in CM patients.