Abstract：
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.
摘要：
从不吸烟者肺癌的病因仍然难以捉摸，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。这里,我们的目的是使用非靶向代谢组学方法,提高我们对从未吸烟者肺癌发病机制的认识.这项巢式病例对照研究包括395名患有肺癌的从不吸烟妇女和395名来自前瞻性上海妇女健康研究的从不吸烟的无癌妇女，使用液相色谱高分辨率质谱在诊断前血浆中量化了15,353个代谢特征。认识到代谢物在生物过程中经常相关且很少独立起作用，我们利用加权相关网络分析对28个相关代谢物网络模块进行了未知构建.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，考虑使用错误发现率(FDR)<0.20的多重测试。我们确定了与所有肺癌（p=.001，FDR=0.028）和肺腺癌（p=.002，FDR=0.056）成反比的121个特征的网络模块，其中，溶血甘油磷脂在推动这些关联方面发挥了关键作用。440个特征的另一个模块与肺腺癌呈负相关（p=0.014，FDR=0.196）。这些网络模块中的个体代谢物富集在与氧化应激相关的生物途径中，和能量代谢。这些途径已经涉及到以前的代谢组学研究，涉及暴露于已知肺癌危险因素的人群，如交通相关的空气污染和多环芳烃。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和危险因素提供新的见解。
