A coagulation-related long non-coding RNA signature to predict prognosis and immune features of breast cancer

Breast cancer (BC) remains one of the most common malignancies among women worldwide, with persistently poor prognosis despite advancements in diagnostics and therapies. Long non-coding RNAs (lncRNAs) and coagulation-related genes (CRGs) are increasingly recognized for their roles in prognosis and immune modulation. Using transcriptomic data from 1,045 BC patients in TCGA, we identified CRG-associated lncRNAs via coexpression analysis (Pearson |R|> 0.4, p < 0.001) and constructed a prognostic model through univariate Cox analysis, LASSO regression with tenfold cross-validation (λ = 0.05), and multivariate Cox analysis. The model stratified patients into high- and low-risk groups with distinct overall survival (HR = 3.21, p < 0.001) and demonstrated robust predictive accuracy (AUC = 0.795 at 1 year). Functional enrichment revealed immune-related pathways (e.g., cytokine signaling, PD-L1 regulation), and high-risk patients exhibited elevated tumor mutational burden (TMB) and PD-L1 expression, suggesting enhanced immunotherapy responsiveness. Drug sensitivity analysis identified 5 targeted agents (e.g., BIBW2992) with differential efficacy between risk groups. This CRG-lncRNA signature provides a novel tool for prognosis prediction and personalized immunotherapy in BC, illuminating crosstalk between coagulation and immune pathways.