Role of the "inflammation-immunity-metabolism" network in non-small cell lung cancer: a multi-omics analysis.

IF 2.8 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM
Jingqi Zhang, Liping Lin, Wenyuan Li, Jing Guo
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引用次数: 0

Abstract

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.

“炎症-免疫-代谢”网络在非小细胞肺癌中的作用:多组学分析
肺癌仍然是癌症相关死亡的主要原因之一,非小细胞肺癌(NSCLC)占全球病例的85%。非小细胞肺癌的发病和进展与炎症刺激、免疫逃避和代谢重编程有着复杂的联系。本研究采用孟德尔随机化分析,以91种炎症因子、731个免疫细胞和1400种代谢物为暴露物,以FinnGen数据库NSCLC队列(ncases = 5315, ncontrol = 314,193)为结果,研究炎症、免疫和代谢对NSCLC的影响。基于孟德尔随机化分析,许多代谢物、炎症蛋白和免疫细胞被确定为与非小细胞肺癌潜在相关。在英国生物银行数据库肺癌队列(ncases = 2671, n对照= 372016)的验证进一步证实了代谢物n -乙酰-天冬氨酸-谷氨酸(NAAG)对肺癌的抑制作用。随后,单细胞和蛋白相互作用分析确定了非小细胞肺癌中炎症蛋白的表达模式,免疫细胞在非小细胞肺癌中的分布比例。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。这些发现增强了对炎症、免疫和代谢在非小细胞肺癌发生和进展中的作用的理解,为进一步研究其治疗和管理提供了潜在的靶点和策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Discover. Oncology
Discover. Oncology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
2.40
自引率
9.10%
发文量
122
审稿时长
5 weeks
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