Construction and Validation of a Ferroptosis-Related Prognostic Signature for Melanoma Based on Single-Cell RNA Sequencing - Liu, Yating; Shou, Yanhong; Zhu, Ronghui; Qiu, Zhuoqiong; Zhang, Qi; Xu, Jinhua (Frontiers in Cell and Developmental Biology, 2022)
Melanoma, the deadliest type of skin cancer, is on the rise globally. The generally poor prognosis makes melanoma still an enormous public health problem. Ferroptosis is a newly emerging form of iron-dependent regulated cell death, which has been implicated in the development and treatment of several tumors. However, whether there is a connection between ferroptosis-related genes and the prognosis of melanoma patients remains an enigma. In the present study, we identified a ferroptosis-related genes signature to predict the prognosis of melanoma patients by analyzing single-cell RNA-sequencing data from the Gene Expression Omnibus (GEO). Single-cell trajectory analysis was performed to explore malignant differentiation. CellChat was used to investigate intercellular communications in melanoma. Collectively, a novel four-gene signature (CP, MAP1LC3A, TF, and TP53) was constructed for prognosis prediction. COX proportional hazards regression analysis showed that the established ferroptosis-associated risk model was an independent prognostic predictor for melanoma patients (HR=2.3293; 95%CI 1.1528-4.706) (P<0.018). Patients with low-risk scores had significantly better overall survival(OS) than those with high-risk scores in TCGA, GSE59455, and GSE22153 dataset (P=0.0015, P=0.031, P=0.077). Furthermore, the gene expression level of the four genes were verified in multistrain melanoma cell lines and normal human epidermal melanocytes(NHEM).The protein expression level of the four genes in clinical samples were further verified in the Human Protein Atlas(HPA) databases. Taken together, our study identified the prognostic significance of the ferroptosis-related genes in melanoma and developed a novel four-gene prognostic signature, which may shed light on the prognostic assessment and clinical decision making for melanoma patients.