Novel risk prediction models for prognosis and immunotherapies of NSCLC based on coagulation and fibrinolysis-related genes

Abstract This study aimed to identify clotting and fibrinolysis related genes (CFRGs) influencing prognosis of non-small cell lung cancer (NSCLC) patients and explore their role in tumor immune microenvironment, with a focus on the F9 gene in lung adenocarcinoma (LUAD). Using TCGA and GEO databases, we screened differentially expressed CFRGs and constructed a risk model. Kaplan-Meier survival analysis and ROC curves evaluated the model's predictive efficiency. Cox regression models were applied to establish nomograms for 1, 2, and 3 years. We performed gene expression, somatic mutation, GSEA, immune microenvironment studies, and gene-drug interaction network analyses. The CFRGs-related risk model, including CSN1S1, F2RL1, F5, F9, FGA, HABP2, MMP9, and TFPI2, revealed that high-risk patients had worse survival outcomes. The expression levels of these genes and immune cell infiltration differed significantly across NSCLC, LUAD, and LUSC datasets. Tissue microarray analysis revealed higher F9 expression in LUAD tumor tissues, associated with poor prognosis. Differences in immune cell expression and immune checkpoints were observed between F9 high- and low-expression groups in LUAD. Our findings highlight CFRGs' role in NSCLC prognosis and immunity, identifying F9 as a LUAD prognostic indicator.