Establishment and Validation of the Prognostic Model

Univariate Cox regression analysis was applied to assess the prognostic value of m⁷G-related DEGs by estimating the correlation between each DEG and survival status in TCGA cohort. A consensus cluster analysis was performed to identify prognostically relevant m⁷G-related DEGs. Using the minor absolute construction and selection operator (LASSO) Cox regression model (based on the optimal λ value) to select the strongest performing candidate genes, we identified nine m⁷G-related DEGs for use in a prognostic model. A risk score was calculated by correcting TCGA expression data using the following formula: risk score = ∑7_iX_i × Y_i (where X is a coefficient and Y is the gene expression level). Patients with LUSC in TCGA were divided into low- and high-risk groups according to the median risk score for further analysis. Kaplan–Meier analysis was used to compare survival rates between the two groups, followed by receiver operating characteristic (ROC) validation and principal component analysis (PCA).