Ferroptosis-Related Gene Signature Predicts the Prognosis of Skin Cutaneous Melanoma and Response to Immunotherapy - Xu, Ziqian; Xie, Yihui; Mao, Yaqi; Huang, Juntao; Mei, Xingyu; Song, Jun; Sun, Yue; Yao, Zhixian; Shi, Weimin (Frontiers in Genetics, 2021)
Ferroptosis is a new type of regulated cell death. Many pieces of evidence indicate that ferroptosis can induce the non-apoptotic death of tumor cells. The ferroptosis-related genes are expected to become a biological target for regulating cancer. Here, the regulation of ferroptosis-related genes on skin cutaneous melanoma (SKCM) we studied. In the present study, we conducted a systematic analysis based on RNA sequencing data and clinical data obtained from The Cancer Genome Atlas (TCGA) database and FerrD database. SKCM patients from the GSE78220 and MSKCC cohorts were used for validation. Applying consensus clustering on RNA sequencing data in TCGA, the obtained ferroptosis subclasses of SKCM were analyzed based on the differential expressed gene set of ferroptosis-related genes. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to construct an eight gene survival-related linear risk signature. The median cut-off risk score was used to divide patients into high- and low-risk groups. The time-dependent receiver operating characteristic (ROC) curve confirmed the predictive power of the model. The areas under the curve (AUC) of the signature at 1-,3-, and 5-year were 0.673, 0.716, and 0.746; Kaplan-Meier survival analysis showed that the prognosis of high-risk patients was worse than that of low-risk patients. Univariate and multivariate Cox regression analyses prove the risk signature was a good independent prognostic indicator. By cooperating risk scores with tumor staging, a nomogram was constructed to predict prognostic outcomes of SKCM. In addition, the immunological analysis showed different immune cell infiltration patterns and responses for immunetherapy between high- and low-risk groups. In summary, ferroptosis-related genes can predict the prognosis of SKCM and have a potential guiding role in targeted therapy of SKCM.