Nomogram based on Autophagy Related Genes for Predicting the Survival in Melanoma

Abstract

Background: Autophagy, a highly conserved lysosomal degradation pathway, isassociated with the prognosis of melanoma. However, prognostic prediction modelsbased on autophagy related genes (ARGs) have never been recognized in melanoma.In the present study, we aimed to establish a novel nomogram to predict the prognosisof melanoma based on ARGs signature and clinical parameters.Methods: Data from The Cancer Genome Atlas (TCGA) and the Genotype-TissueExpression (GTEx) databases were extracted to identify the differentially expressedARGs. Univariate, least absolute shrinkage and selection operator (LASSO) andmultivariate analysis were used to select the prognostic ARGs. ARG signature, ageand stage were then enrolled to establish a nomogram to predict the survivalprobabilities of melanoma. The nomogram was evaluated by concordance index(C-index), receiver operating characteristic (ROC) curve and calibration curve.Decision curve analysis (DCA) was performed to assess the clinical benefits of thenomogram and TNM stage model. The nomogram was validated in GEO cohorts.Results: Five prognostic ARGs were selected to construct ARGs signature model andvalidated in the GEO cohort. Kaplan-Meier survival analysis suggested that patientsin high-risk group had significantly worse overall survival than those in low-riskgroup in TCGA cohort (P = 5.859 × 10-9) and GEO cohort (P = 3.075 × 10-9).We then established and validated a novel promising prognostic nomogram throughcombining ARGs signature and clinical parameters. The C-index of the nomogramwas 0.717 in TCGA training cohort and 0.738 in GEO validation cohort.TCGA/GEO-based ROC curve and decision curve analysis (DCA) demonstrated thatthe nomogram was better than traditional TNM staging system for melanomaprognosis.Conclusion: We firstly developed and validated an ARGs signature based-nomogramfor individualized prognosis prediction in melanoma patients, which could assist withdecision making for clinicians.

Development and Validation of a Combined Ferroptosis and Immune Prognostic Model for Melanoma

“…Currently, several studies have reported immune-related molecular markers as prognostic markers for melanoma [29][30][31], but these prognostic markers had limitations. First, molecular markers in previous studies contained various genes, which increased the workload and cost in clinical practice and constrained the clinical utility of these molecular markers to some extent [29,32,33].…”