Zhang Jingqi, Lin Liping, Li Wenyuan, Guo Jing
Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Discov Oncol. 2025 May 21;16(1):847. doi: 10.1007/s12672-025-02692-z.
Lung cancer remains one of the leading causes of cancer-related mortality, with non-small cell lung cancer (NSCLC) accounting for 85% of cases worldwide. NSCLC pathogenesis and progression are intricately linked to inflammatory stimuli, immune evasion, and metabolic reprogramming. In this study, the impact of inflammation, immunity, and metabolism on NSCLC was investigated by a Mendelian randomization analysis taking 91 inflammatory factors, 731 immune cells, and 1400 metabolites as exposures, and the FinnGen database NSCLC cohort (ncases = 5315, ncontrol = 314,193) was the outcome. A number of metabolites, inflammatory proteins, and immune cells were identified as potentially associated with NSCLC based on mendelian randomization analysis. Validation in the UK Biobank database lung cancer cohort (ncases = 2671, ncontrols = 372,016) further confirmed the inhibitory role of the metabolite N-acetyl-aspartyl-glutamate (NAAG) on lung cancer. Subsequently, single-cell and protein-protein interaction analyses identified inflammatory protein expression patterns in NSCLC, distribution ratios of immune cells in NSCLC. Subsequent multi-omics network analysis showed key interaction nodes between NAAG and inflammatory proteins. These findings enhance the understanding of the roles of inflammation, immunity, and metabolism in NSCLC occurrence and progression, offering potential targets and strategies for further research on its treatment and management.
肺癌仍然是癌症相关死亡的主要原因之一,其中非小细胞肺癌(NSCLC)占全球病例的85%。NSCLC的发病机制和进展与炎症刺激、免疫逃逸和代谢重编程密切相关。在本研究中,通过孟德尔随机化分析研究了炎症、免疫和代谢对NSCLC的影响,该分析将91种炎症因子、731种免疫细胞和1400种代谢物作为暴露因素,以芬兰基因数据库NSCLC队列(病例数=5315,对照数=314193)作为结果。基于孟德尔随机化分析,确定了一些代谢物、炎症蛋白和免疫细胞可能与NSCLC相关。在英国生物银行数据库肺癌队列(病例数=2671,对照数=372016)中进行验证,进一步证实了代谢物N-乙酰天门冬氨酰谷氨酸(NAAG)对肺癌的抑制作用。随后,单细胞和蛋白质-蛋白质相互作用分析确定了NSCLC中的炎症蛋白表达模式、NSCLC中免疫细胞的分布比例。随后的多组学网络分析显示了NAAG与炎症蛋白之间的关键相互作用节点。这些发现加深了对炎症、免疫和代谢在NSCLC发生和进展中的作用的理解,为其治疗和管理的进一步研究提供了潜在的靶点和策略。