Identification of lung squamous cell carcinoma subtypes based on STING pathway expression and validation of prognostic features.

Abstract

Lung squamous cell carcinoma (LUSC), a prevalent non-small cell lung cancer subtype, demonstrates marked heterogeneity and unpredictable prognosis. This study established a prognostic model using STING pathway-related genes to stratify LUSC patients and guide immunotherapy. Through weighted gene co-expression network analysis of TCGA-LUSC data, we identified the MEbrown module containing 13 STING-associated key genes (including CD47 and CLDN5) to develop the STING Pathway Death-Related Signature (SPDRS). LASSO regression refined the model, which effectively stratified patients into distinct high- and low-risk groups with significant survival differences. High-risk patients exhibited enhanced immune infiltration, particularly T cells CD4 memory resting and M2 macrophages, along with elevated immune checkpoint expression and stromal scores. Functional analyses revealed enrichment in immune-related pathways and tumor microenvironment regulation. Drug sensitivity predictions identified potential therapeutic agents targeting SPDRS components. A nomogram integrating SPDRS with clinical factors demonstrated strong prognostic accuracy. This work provides a novel STING pathway-based stratification system that elucidates tumor microenvironment heterogeneity and informs personalized treatment strategies. The findings highlight SPDRS as both a prognostic biomarker and therapeutic response predictor, advancing precision immunotherapy in LUSC management.