The etiology of lung cancer in never‐smokers remains elusive, despite 15% of lung cancer cases in men and 53% in women worldwide being unrelated to smoking. Here, we aimed to enhance our understanding of lung cancer pathogenesis among never‐smokers using untargeted metabolomics. This nested case‐control study included 395 never‐smoking women who developed lung cancer and 395 matched never‐smoking cancer‐free women from the prospective Shanghai Women's Health Study with 15,353 metabolic features quantified in pre‐diagnostic plasma using liquid chromatography high‐resolution mass spectrometry. Recognizing that metabolites often correlate and seldom act independently in biological processes, we utilized a weighted correlation network analysis to agnostically construct 28 network modules of correlated metabolites. Using conditional logistic regression models, we assessed the associations for both metabolic network modules and individual metabolic features with lung cancer, accounting for multiple testing using a false discovery rate (FDR) < 0.20. We identified a network module of 121 features inversely associated with all lung cancer (p = .001, FDR = 0.028) and lung adenocarcinoma (p = .002, FDR = 0.056), where lyso‐glycerophospholipids played a key role driving these associations. Another module of 440 features was inversely associated with lung adenocarcinoma (p = .014, FDR = 0.196). Individual metabolites within these network modules were enriched in biological pathways linked to oxidative stress, and energy metabolism. These pathways have been implicated in previous metabolomics studies involving populations exposed to known lung cancer risk factors such as traffic‐related air pollution and polycyclic aromatic hydrocarbons. Our results suggest that untargeted plasma metabolomics could provide novel insights into the etiology and risk factors of lung cancer among never‐smokers.

中文翻译：

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上海前瞻性女性健康研究中从不吸烟女性中进行的非靶向血浆代谢组学与肺癌的巢式病例对照研究

尽管全世界 15% 的男性肺癌病例和 53% 的女性肺癌病例与吸烟无关，但从不吸烟者的肺癌病因仍然难以捉摸。在这里，我们的目的是利用非靶向代谢组学来增强对从不吸烟者肺癌发病机制的了解。这项巢式病例对照研究包括 395 名患肺癌的从不吸烟女性和来自前瞻性上海女性健康研究的 395 名匹配的从不吸烟的无癌症女性，使用液相色谱高分辨率质量在诊断前血浆中量化了 15,353 项代谢特征光谱测定法。认识到代谢物在生物过程中经常相关且很少独立作用，我们利用加权相关网络分析来不可知地构建 28 个相关代谢物的网络模块。使用条件逻辑回归模型，我们评估了代谢网络模块和个体代谢特征与肺癌的关联，并使用错误发现率 (FDR) < 0.20 进行了多次测试。我们确定了一个由 121 个特征组成的网络模块，这些特征与所有肺癌呈负相关（p= .001，FDR = 0.028）和肺腺癌（p= .002，FDR = 0.056），其中溶血甘油磷脂在驱动这些关联中发挥了关键作用。另一个包含 440 个特征的模块与肺腺癌呈负相关（p= .014，FDR = 0.196）。这些网络模块内的各个代谢物富含与氧化应激和能量代谢相关的生物途径。这些途径已在之前涉及暴露于已知肺癌危险因素（如交通相关空气污染和多环芳烃）的人群的代谢组学研究中得到涉及。我们的结果表明，非靶向血浆代谢组学可以为从不吸烟者中肺癌的病因学和危险因素提供新的见解。