Ferroptosis-related gene signature

The "limma" R package was used to identify the differentially expressed genes (DEGs) between tumor tissues and adjacent nontumorous tissues with a false discovery rate (FDR) < 0.05 in the TCGA cohort. Univariate Cox analysis of overall survival (OS) was performed to screen ferroptosis-related genes with prognostic values. P values were adjusted by Benjamini & Hochberg (BH) correction. An interaction network for the overlapping prognostic DEGs was generated by the STRING database (version 11.0) 19 (link). To minimize the risk of overfitting, the LASSO-penalized Cox regression analysis was applied to construct a prognostic model 20 , 21 (link). The LASSO algorithm was used for variable selection and shrinkage with the "glmnet" R package. The independent variable in the regression was the normalized expression matrix of candidate prognostic DEGs, and the response variables were overall survival and status of patients in the TCGA cohort. Penalty parameter (λ) for the model was determined by tenfold cross-validation following the minimum criteria (i.e. the value of λ corresponding to the lowest partial likelihood deviance). The risk scores of the patients were calculated according to the normalized expression level of each gene and its corresponding regression coefficients. The formula was established as follows: score= e^{sum (each gene's expression × corresponding coefficient)}. The patients were stratified into high-risk and low-risk groups based on the median value of the risk score. Based on the expression of genes in the signature, PCA was carried out with the "prcomp" function of the "stats" R package. Besides, t-SNE were performed to explore the distribution of different groups using the "Rtsne" R package. For the survival analysis of each gene, the optimal cut-off expression value was determined by the "surv_cutpoint" function of the "survminer" R package. The "survivalROC" R package was used to conduct time‐dependent ROC curve analyses to evaluate the predictive power of the gene signature.