Construction of autophagy prognostic signature and analysis of prospective molecular mechanisms in skin cutaneous melanoma patients

Abstract

Background: Autophagy is closely related to skin cutaneous melanoma (SKCM), but the mechanism involved is unclear. Therefore, exploration of the role of autophagy-related genes (ARGs) in SKCM is necessary. Materials and methods: Differential expression autophagy-related genes (DEARGs) were first analysed. Univariate and multivariate Cox regression analyses were used to evaluate the expression of DEARGs and prognosis of SKCM. Further, the expression levels of prognosis-related DEARGs were verified by immunohistochemical (IHC) staining. Finally, gene set enrichment analysis (GSEA) was used to explore the underlying molecular mechanisms of SKCM. Results: Five ARGs ( APOL1 , BIRC5, EGFR, TP63, and SPNS1 ) were positively correlated with the prognosis of SKCM. IHC verified the results of the differential expression of these 5 ARGs in the bioinformatics analysis. According to the receiver operating characteristic curve, the signature had a good performance at predicting overall survival in SKCM. The signature could classify SKCM patients into high-risk or low-risk groups according to distinct overall survival. The nomogram confirmed that the risk score has a particularly large impact on the prognosis of SKCM. Calibration plot displayed excellent agreement between nomogram predictions and actual observations. Principal component analysis indicated that patients in the high-risk group could be distinguished from those in low-risk group. Results of GSEA indicated that the low-risk group is enriched with aggressiveness-related pathways such as phosphatidylinositol-3-kinase/protein kinase B and mitogen-activated protein kinase signalling pathways. Conclusion: Our study identified a 5-gene signature. It revealed the mechanisms of autophagy that lead to the progression of SKCM and established a prognostic nomogram that can predict overall survival of patients with SKCM. The findings of this study provide novel insights into the relationship between ARGs and prognosis of SKCM.

A Ferroptosis Molecular Subtype‐Related Signature for Predicting Prognosis and Response to Chemotherapy in Patients with Chronic Lymphocytic Leukemia

“…TP63 contributes to maintaining redox homeostasis through glutathione biogenesis, utilization, and regeneration. TP63 is a prognostic gene in breast cancer patients [ 26 ], lung squamous cell carcinoma [ 27 ], pancreatic cancer [ 28 ], skin cutaneous melanoma [ 29 ], anaplastic lymphoma kinase-negative anaplastic large cell lymphoma [ 30 ], etc. STEAP3 is a metal reductase, encoding a transmembrane protein that functions as an iron transporter and coordinates the regulation of iron homeostasis [ 31 ].…”

A Risk-Scoring Model Based on Evaluation of Ferroptosis-Related Genes in Osteosarcoma

“…The median risk score of each patient is considered the reference standard for classifying the high and low groups, followed by the analysis of the survival of the two groups and drawing the survival curves using the Kaplan-Meier method (K-M method) [ 16 ]. In virtue of the critical parameters and model scores and in combination with various clinical factors, we drew a clinically relevant nomogram to predict the 1-, 3-, and 5-year survival, and the scales on nomograms represented the numerical ranges of each variable [ 17 ].…”

Risk score model of autophagy-related genes in osteosarcoma

“…The scales on the nomogram represented the numerical ranges of each variable. The total scores calculated for each variable could be used to predict the survival rate (27).…”