Suppr超能文献

两个患肺癌风险不同的种族群体吸烟者的代谢组学特征

Metabolomics Profiles of Smokers from Two Ethnic Groups with Differing Lung Cancer Risk.

作者信息

Dator Romel, Villalta Peter W, Thomson Nicole, Jensen Joni, Hatsukami Dorothy K, Stepanov Irina, Warth Benedikt, Balbo Silvia

机构信息

Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota 55455, United States.

Department of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, Währingerstraβe 38, 1090 Vienna, Austria.

出版信息

Chem Res Toxicol. 2020 Aug 17;33(8):2087-2098. doi: 10.1021/acs.chemrestox.0c00064. Epub 2020 May 11.

Abstract

African American (AA) smokers are at a higher risk of developing lung cancer compared to whites. The variations in the metabolism of nicotine and tobacco-derived carcinogens in these groups were reported previously with the levels of nicotine metabolites and carcinogen-derived metabolites measured using targeted approaches. While useful, these targeted strategies are not able to detect global metabolic changes for use in predicting the detrimental effects of tobacco use and ultimately lung cancer susceptibility among smokers. To address this limitation, we have performed global untargeted metabolomics profiling in urine of AA and white smokers to characterize the pattern of metabolites, identify differentially regulated pathways, and correlate these profiles with the observed variations in lung cancer risk between these two populations. Urine samples from AA ( = 30) and white ( = 30) smokers were used for metabolomics analysis acquired in both positive and negative electrospray ionization modes. LC-MS data were uploaded onto the cloud-based XCMS online (http://xcmsonline.scripps.edu) platform for retention time correction, alignment, feature detection, annotation, statistical analysis, data visualization, and automated systems biology pathway analysis. The latter identified global differences in the metabolic pathways in the two groups including the metabolism of carbohydrates, amino acids, nucleotides, fatty acids, and nicotine. Significant differences in the nicotine degradation pathway (cotinine glucuronidation) in the two groups were observed and confirmed using a targeted LC-MS/MS approach. These results are consistent with previous studies demonstrating AA smokers with lower glucuronidation capacity compared to whites. Furthermore, the d-glucuronate degradation pathway was found to be significantly different between the two populations, with lower amounts of the putative metabolites detected in AA compared to whites. We hypothesize that the differential regulation of the d-glucuronate degradation pathway is a consequence of the variations in the glucuronidation capacity observed in the two groups. Other pathways including the metabolism of amino acids, nucleic acids, and fatty acids were also identified, however, the biological relevance and implications of these differences across ethnic groups need further investigation. Overall, the applied metabolomics approach revealed global differences in the metabolic networks and endogenous metabolites in AA and whites, which could be used and validated as a new potential panel of biomarkers that could be used to predict lung cancer susceptibility among smokers in population-based studies.

摘要

与白人相比,非裔美国(AA)吸烟者患肺癌的风险更高。此前曾报道过这些群体中尼古丁和烟草衍生致癌物代谢的差异,使用靶向方法测量了尼古丁代谢物和致癌物衍生代谢物的水平。虽然这些靶向策略很有用,但它们无法检测出用于预测吸烟的有害影响以及最终吸烟者患肺癌易感性的整体代谢变化。为了解决这一局限性,我们对AA和白人吸烟者的尿液进行了整体非靶向代谢组学分析,以表征代谢物模式、识别差异调节的途径,并将这些图谱与这两个人群中观察到的肺癌风险差异相关联。来自AA(n = 30)和白人(n = 30)吸烟者的尿液样本用于在正离子和负离子电喷雾电离模式下进行的代谢组学分析。液相色谱 - 质谱数据上传到基于云的XCMS在线(http://xcmsonline.scripps.edu)平台,用于保留时间校正、对齐、特征检测、注释、统计分析、数据可视化和自动化系统生物学途径分析。后者确定了两组代谢途径的整体差异,包括碳水化合物、氨基酸、核苷酸、脂肪酸和尼古丁的代谢。使用靶向液相色谱 - 串联质谱方法观察并证实了两组中尼古丁降解途径(可替宁葡萄糖醛酸化)的显著差异。这些结果与先前的研究一致,表明与白人相比,AA吸烟者的葡萄糖醛酸化能力较低。此外,发现d - 葡萄糖醛酸降解途径在两个人群之间存在显著差异,与白人相比,在AA中检测到的推定代谢物数量较少。我们假设d - 葡萄糖醛酸降解途径的差异调节是两组中观察到的葡萄糖醛酸化能力差异的结果。还确定了其他途径,包括氨基酸、核酸和脂肪酸的代谢,然而,这些种族间差异的生物学相关性和影响需要进一步研究。总体而言,所应用的代谢组学方法揭示了AA和白人在代谢网络和内源性代谢物方面的整体差异,这可以作为一个新的潜在生物标志物面板进行使用和验证,可用于在基于人群的研究中预测吸烟者患肺癌的易感性。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验