Identification of immune-related prognostic biomarkers in lung squamous cell carcinoma microenvironment.

BACKGROUND: Lung squamous cell carcinoma (LUSC) is a leading cause of cancer-related mortality. Although immunotherapy has recently demonstrated clinical benefits, the biological roles of immune-related genes (IRGs) in LUSC remain insufficiently understood. METHODS: In this study, transcriptomic and clinical data from 493 LUSC patients were obtained from The Cancer Genome Atlas (TCGA). IRGs were identified through weighted gene co-expression network analysis, followed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression to screen for prognostic genes and establish a risk prediction model. The model's predictive performance was validated, and the immune landscape associated with distinct risk subgroups was systematically characterized. Expression patterns and clinical significance of the signature genes were further investigated using bioinformatics analysis, quantitative real-time PCR, Western blotting, and immunohistochemistry. RESULTS: A total of 55 differentially expressed IRGs were identified, among which 8 genes (PSMD1, ANGPTL4, LTBP3, MIF, NFATC3, NR1D2, PLXNB3, and SP1) demonstrated significant prognostic value. A prognostic signature based on these 8 IRGs was established that stratified patients into high- and low-risk groups with distinct survival outcomes, immune landscapes, and enriched pathways. As one of the constituent genes of the risk model, NR1D2 was found to be downregulated in LUSC and associated with poor prognosis. Functional assays indicated that NR1D2 facilitated malignant progression by regulating macrophage polarization and enhancing tumor cell migration. CONCLUSION: This study establishes a novel IRGs-based prognostic signature with potential utility for risk stratification and individualized immunotherapeutic strategies in LUSC. Furthermore, it also provides valuable insights into the role of NR1D2 in clinical outcomes.