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

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.

肺鳞状细胞癌（LUSC）作为非小细胞肺癌的常见亚型，具有显著的肿瘤异质性且预后难以预测。本研究基于STING通路（STING pathway）相关基因构建了预后模型，用于LUSC患者的风险分层并指导免疫治疗。本研究通过对TCGA-LUSC数据集进行加权基因共表达网络分析，筛选出包含13个STING相关关键基因（含CD47与CLDN5）的MEbrown模块，以此构建了STING通路死亡相关基因特征（SPDRS）。经最小绝对收缩和选择算子回归（LASSO回归）优化后的模型，可有效将患者划分为高风险组与低风险组，两组间存在显著的生存差异。高风险组患者的免疫浸润水平更高，尤其是静止性CD4记忆性T细胞与M2型巨噬细胞浸润，同时免疫检查点表达与基质评分均显著上调。功能富集分析显示，该模型显著富集于免疫相关通路与肿瘤微环境调控通路中。药物敏感性预测筛选出了可靶向SPDRS相关分子的潜在治疗药物。整合SPDRS与临床特征的列线图展现出优异的预后预测效能。本研究构建了一种基于STING通路的新型患者分层系统，可阐明肿瘤微环境异质性并为个体化治疗策略提供参考依据。本研究结果证实SPDRS可同时作为预后生物标志物与治疗反应预测因子，推动肺鳞状细胞癌的精准免疫治疗实践。