Abstract LB136: Global metabolomics identified promising biomarkers for lung cancer risk among former smokers
Authors: Thuraya Al-Sayegh, Wanqing Wen, Jie Wu, Wei Zheng, Xiao-Ou Shu, Qiuyin Cai
Journal: Cancer Research (2024)

Abstract Purpose: We comprehensively searched the plasma metabolome to identify biomarkers related to lung cancer risk among former smokers using pre-diagnostic blood samples collected in two prospective cohort studies: the Shanghai Men’s Health Study and the Southern Community Cohort Study. Methods: This nested case-control study includes 237 lung cancer cases and 237 controls individually matched on age, sex, race, smoking pack-year, years since quitting smoking, and blood collection time. The plasma metabolites were measured using Metabolon’s Global Discovery Panel. Values of metabolites were log-transformed and compared between cases and controls using the two-tailed paired T-test. Associations of metabolites with lung cancer risk at a False Discovery Rate adjusted p-value (P-FDR) of &amp;lt;0.10 were considered statistically significant. Conditional logistic regression was used to evaluate the association between metabolites and lung cancer risk with adjustment for diabetes, BMI, alcohol use, physical activity, educational level, pack years, time since last meal, and time since quitting smoking. The odds ratios were reported per standard deviation increment. A subsequent backward selection of conditional logistic regression was conducted. The analysis was then stratified by race (Asian, Black, and White), years since quitting (≤8 years and &amp;gt;8 years), and interval from blood draw to diagnosis (≤6 years and &amp;gt;6 years). Results: We found that 45 plasma metabolites were significantly associated with lung cancer risk (p-FDR&amp;lt;0.10), including 11 in amino acids, 3 in nucleotides, 2 in peptides, 1 in carbohydrates, 7 in lipids, 2 in energy, 2 in xenobiotics, 2 in the partially characterized pathway, and 15 unknown metabolites. Nine metabolites remained statistically significant in the backward selection model. Among them, metabolites significantly associated with increased odds of lung cancer were S-carboxyethylcysteine (OR=1.40; 95% CI: 1.06-1.84), alpha-ketoglutarate (OR=1.60; 95% CI: 1.19-2.16), myristoleoylcarnitine (OR=1.67; 95% CI: 1.27-2.21), 2-hydroxyhippurate (salicylurate) (OR=1.58; 95% CI: 1.16-2.15), gamma-glutamylglutamine (OR=1.68; 95%CI: 1.09-2.61), and an unknown metabolite X-23780 (OR=1.29; 95% CI: 1.00-1.67). Conversely, ceramide (OR=0.60; 95% CI; 0.43-0.82), homoarginine (OR=0.66; 95% CI: 0.49-0.89), and an unknown metabolite X-16935 (OR=0.53; 95% CI= 0.37-0.77) were significantly associated with lower odds of lung cancer. The associations did not vary significantly by race, years since quitting, or interval from blood draw to diagnosis. Conclusion: Several plasma metabolites were associated with lung cancer risk among former smokers. These associations were consistent across race, interval from blood draw to diagnosis, and years since quitting smoking, representing promising biomarkers for identification of high-risk former smokers for lung cancer screening. Citation Format: Thuraya Al-Sayegh, Wanqing Wen, Jie Wu, Wei Zheng, Xiao-Ou Shu, Qiuyin Cai. Global metabolomics identified promising biomarkers for lung cancer risk among former smokers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB136.