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

Research output: Contribution to journalArticlepeer-review

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 (n = 30) and white (n = 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.

Original languageEnglish (US)
Pages (from-to)2087-2098
Number of pages12
JournalChemical Research in Toxicology
Volume33
Issue number8
Early online date2020
DOIs
StatePublished - Aug 17 2020

Bibliographical note

Funding Information:
The authors would like to thank the American Society for Mass Spectrometry Postdoctoral Career Development Award to R.D., Prof. Gary Siuzdak and group members (Aries Aisporna, Tao Han, Erica Forsberg, H. Paul Benton, Xavi Domingo, Rafael Montenegro, Carlos Guijas, Brian Hilmers, Bill Web, Linh Hoang, Winnie Heim Duane Rinehart, and Bill Webb) at the Scripps Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, CA for hosting R.D. to conduct this work, Prof. Sharon E. Murphy and group members, and Laura A. Maertens and Anshu Jain for the sample inventory. B.W. acknowledges the Austrian Science Fund (FWF) for funding (Erwin-Schrödinger Fellowship J-3808). P.V. acknowledges funding from grant NCI R50 CA-211256. Targeted mass spectrometry was carried out in the Analytical Biochemistry Shared Resource of the Masonic Cancer Center, University of Minnesota, funded in part by Cancer Center Support grant P30 CA-077598. This work was supported by grant CA-138338 from the National Cancer Institute.

Publisher Copyright:
Copyright © 2020 American Chemical Society.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • LC-MS
  • global metabolomics
  • XCMS Online
  • systems biology pathway analysis
  • ethnic differences
  • lung cancer susceptibility
  • tobacco smoking

PubMed: MeSH publication types

  • Journal Article

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