Abstract 4974: Prospective study of untargeted urinary metabolomics and risk of lung cancer among female never-smokers in Shanghai, China
Authors: Wei Jie Seow, Xiao-Ou Shu, Jeremy Nicholson, Elaine Holmes, Wei Hu, Qiuyin Cai, Yu-Tang Gao, Yong-Bing Xiang, Steve Moore, Bryan A. Bassig, Jason Yy Wong, Jinming Zhang, Bu-Tian Ji, Claire Boulange, Manuja Kaluarachchi, Kyrillos F. Adesina-Georgiadis, Anisha Wijeyesekera, Wei Zheng, Paul Elliot, Nathaniel Rothman, Qing Lan
Journal: Cancer Research (2018)

Abstract The lung cancer rate among never-smokers is the highest among Asian women, however its etiology and any relevant non-smoking related biomarkers are still unclear. Pre-diagnostic lung cancer-related metabolic biomarkers may provide novel insights into lung cancer mechanisms, and may contribute to the discovery of etiologic factors for the high lung cancer prevalence among Asian women. We evaluated the role of the urinary metabolome in lung cancer development among female never-smokers in China by conducting a nested case-control study of 275 lung cancer cases and 289 healthy controls from the Shanghai Women's Health Study, a prospective cohort comprised of 73,363 Chinese female never-smokers. Metabolic profiling of urinary chemical features was conducted using ultrahigh-performance liquid chromatography - tandem mass spectrometry (UPLC-MS) (39,409 spectral features) and 600 MHz 1H nuclear magnetic resonance (NMR) spectroscopy (386 features). Unconditional logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for the association between each log-transformed metabolite level and lung cancer risk, adjusting for potential confounders such as age, body mass index, history of respiratory disease and passive smoking. Spearman correlation and linear regression were used to estimate associations between the most significant metabolites and pre-diagnosis dietary factors. Three detected UPLC-MS urinary metabolites were negatively associated with lung cancer risk with a false discovery rate of less than 10%: pos_2.61_127.0382m/z (OR = 0.57, 95% CI = 0.46-0.72, P = 1.98 x 10-6), neg_2.60_369.0408m/z (OR = 0.97, 95% CI = 0.96-0.98, P = 1.36 x 10-6), and pos_2.61_184.0325n (OR = 0.55, 95% CI = 0.43-0.71, P = 4.91 x 10-6). These were strongly correlated with each other (rho &amp;gt; 0.65, p &amp;lt; 0.0001). The significant metabolite (pos_2.61_127.0382m/z) was identified as 5-methyl-2-furoic acid and was moderately correlated with self-reported dietary intake of soy (rho = 0.21, p &amp;lt; 0.001). In conclusion, we identified a metabolite in urine (5-methyl-2-furoic acid) that provides support for the protective association of soy-based foods on lung cancer risk that was previously observed in this population of never-smoking women. Further studies are warranted to replicate these findings. Citation Format: Wei Jie Seow, Xiao-Ou Shu, Jeremy Nicholson, Elaine Holmes, Wei Hu, Qiuyin Cai, Yu-Tang Gao, Yong-Bing Xiang, Steve Moore, Bryan A. Bassig, Jason Yy Wong, Jinming Zhang, Bu-Tian Ji, Claire Boulange, Manuja Kaluarachchi, Kyrillos F. Adesina-Georgiadis, Anisha Wijeyesekera, Wei Zheng, Paul Elliot, Nathaniel Rothman, Qing Lan. Prospective study of untargeted urinary metabolomics and risk of lung cancer among female never-smokers in Shanghai, China [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4974.