改写A total of 816 DEGs among the three subgroups were involved in the univariate Cox regression analysis We defined the differentially expressed genes with P 0001 and HR 1 as risk genes while those w

In the univariate Cox regression analysis, a total of 816 DEGs among the three subgroups were analyzed. Genes with P < 0.001 and HR > 1 were classified as risk genes, while those with P < 0.001 and HR < 1 were classified as protective genes. To accurately predict the stemness subtype status, we utilized LASSO regression analysis via the "glmnet" R package to rank the importance of the risk and protective genes. A stemness-based classifier was constructed using multivariate logistic regression, with the formula as follows: riskscore = ΣCoeficient (Stemness gene i) * Expression (Stemness gene i). The classifier was then normalized to a range of 0 to 1, and patients were classified into high- and low-risk groups based on the optimal cutoff value of the normalized riskscore calculated using the "survminer" package. The time-dependent ROC curve was used to assess the capacity of the prediction based on the multivariate logistic model, with the optimal cutoff value of the classifier determined and the AUC evaluated using the "pROC" package. We also analyzed the differences in immune microenvironment and pathway activity between the high- and low-risk groups as previously mentioned.