Chi Yuxiang, Ma Guoyuan, Liu Qiang, Xiang Yunzhi, Liu Defeng, Du Jiajun
Institute of Oncology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China.
Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Front Immunol. 2025 Jul 2;16:1608407. doi: 10.3389/fimmu.2025.1608407. eCollection 2025.
Metabolic reprogramming within the tumor microenvironment plays a pivotal role in tumor progression and therapeutic responses. Nevertheless, the relationship between aberrant glutathione (GSH) metabolism and the immune microenvironment in lung adenocarcinoma, as well as its clinical implications, remains unclear.
We leveraged genome-wide association study (GWAS) data and applied genetic causal analysis to evaluate the causal relationships among plasma 5-oxoproline levels, lung adenocarcinoma (LUAD) risk, and 731 immune phenotypes. We incorporated single-cell RNA sequencing data from LUAD to compare transcription factor activity, cell communication networks, and CD8 T cell subset distributions across distinct GSH metabolic groups, followed by pseudotime analysis. Whole-transcriptome data from the TCGA database were analyzed for functional enrichment, immune infiltration, and immune functionality. Prognostic genes were identified using WGCNA and LASSO-Cox regression, and the expression was validated via qRT-PCR. Thereafter, immunotherapeutic efficacy and drug sensitivity were predicted using the TIDE platform and the oncoPredict package. A prognostic model was constructed to forecast patient survival, which was further validated in two independent GEO datasets.
Genetic causal analysis indicated a positive correlation between plasma 5-oxoproline levels and LUAD risk. ScRNA-seq analysis revealed an increased proportion of exhausted CD8 T cells in the high GSH metabolic group, accompanied by altered transcription factor activity and distinct cell communication patterns. Furthermore, whole-transcriptome data analysis demonstrated that patients with a high metabolic phenotype exhibited significantly diminished immune functionality and overall immune infiltration. Using WGCNA and LASSO-Cox regression, we ultimately identified three key genes (LCAL1, RHOV, and MARCHF4) and generated a gene risk score. This score effectively predicts both immunotherapy response and drug sensitivity. qRT-PCR confirmed the upregulation of MARCHF4 in LUAD cells. In addition, stratification by gene risk scores revealed significant differences in immune cell infiltration, immunotherapeutic response, and drug sensitivity. The nomogram model demonstrated strong predictive accuracy in both the TCGA cohort and two independent GEO validation datasets.
GSH metabolic reprogramming may suppress antitumor immunity by modulating transcription factor activity, remodeling cell communication networks, and regulating CD8+ T cells. The prognostic risk model developed herein effectively predicts immunotherapeutic response, drug sensitivity, and overall survival in patients with LUAD.
肿瘤微环境中的代谢重编程在肿瘤进展和治疗反应中起关键作用。然而，肺腺癌中异常的谷胱甘肽（GSH）代谢与免疫微环境之间的关系及其临床意义仍不清楚。
我们利用全基因组关联研究（GWAS）数据并应用遗传因果分析来评估血浆5-氧代脯氨酸水平、肺腺癌（LUAD）风险和731种免疫表型之间的因果关系。我们纳入了来自LUAD的单细胞RNA测序数据，以比较不同GSH代谢组之间的转录因子活性、细胞通讯网络和CD8 T细胞亚群分布，随后进行拟时间分析。对来自TCGA数据库的全转录组数据进行功能富集、免疫浸润和免疫功能分析。使用WGCNA和LASSO-Cox回归鉴定预后基因，并通过qRT-PCR验证其表达。此后，使用TIDE平台和oncoPredict软件包预测免疫治疗疗效和药物敏感性。构建一个预后模型来预测患者生存情况，并在两个独立的GEO数据集中进一步验证。
遗传因果分析表明血浆5-氧代脯氨酸水平与LUAD风险呈正相关。单细胞RNA测序分析显示，高GSH代谢组中耗竭的CD8 T细胞比例增加，同时转录因子活性改变，细胞通讯模式不同。此外，全转录组数据分析表明，具有高代谢表型的患者免疫功能显著降低，整体免疫浸润减少。使用WGCNA和LASSO-Cox回归，我们最终鉴定出三个关键基因（LCAL1、RHOV和MARCHF4）并生成一个基因风险评分。该评分可有效预测免疫治疗反应和药物敏感性。qRT-PCR证实LUAD细胞中MARCHF4上调。此外，按基因风险评分分层显示免疫细胞浸润、免疫治疗反应和药物敏感性存在显著差异。列线图模型在TCGA队列和两个独立的GEO验证数据集中均显示出强大的预测准确性。
GSH代谢重编程可能通过调节转录因子活性、重塑细胞通讯网络和调节CD8+ T细胞来抑制抗肿瘤免疫。本文开发的预后风险模型可有效预测LUAD患者的免疫治疗反应、药物敏感性和总生存期。
