Lung cancer metabolomics: a pooled analysis in the Cancer Prevention Studies

Tang, Ziyin; Liang, Donghai; Deubler, Emily L.; Sarnat, Jeremy A.; Chow, Sabrina S.; Diver, W. Ryan; Wang, Ying

doi:http://dx.doi.org/10.1186/s12916-024-03473-1

Lung cancer metabolomics: a pooled analysis in the Cancer Prevention Studies

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Tang Z, Liang D, Deubler EL, Sarnat JA, Chow SS, Diver WR, et al. Lung cancer metabolomics: a pooled analysis in the Cancer Prevention Studies. BMC Med. 2024 Jun 24;22(1):262. DOI: 10.1186/s12916-024-03473-1

Abstract

Background: A better understanding of lung cancer etiology and the development of screening biomarkers have important implications for lung cancer prevention. Methods: We included 623 matched case-control pairs from the Cancer Prevention Study (CPS) cohorts. Pre-diagnosis blood samples were collected between 1998 and 2001 in the CPS-II Nutrition cohort and 2006 and 2013 in the CPS-3 cohort and were sent for metabolomics profiling simultaneously. Cancer-free controls at the time of case diagnosis were 1:1 matched to cases on date of birth, blood draw date, sex, and race/ethnicity. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using conditional logistic regression, controlling for confounders. The Benjamini-Hochberg method was used to correct for multiple comparisons. Results: Sphingomyelin (d18:0/22:0) (OR: 1.32; 95% CI: 1.15, 1.53, FDR = 0.15) and taurodeoxycholic acid 3-sulfate (OR: 1.33; 95% CI: 1.14, 1.55, FDR = 0.15) were positively associated with lung cancer risk. Participants diagnosed within 3 years of blood draw had a 55% and 48% higher risk of lung cancer per standard deviation increase in natural log-transformed sphingomyelin (d18:0/22:0) and taurodeoxycholic acid 3-sulfate level, while 26% and 28% higher risk for those diagnosed beyond 3 years, compared to matched controls. Lipid and amino acid metabolism accounted for 47% to 80% of lung cancer-associated metabolites at P < 0.05 across all participants and subgroups. Notably, ever-smokers exhibited a higher proportion of lung cancer-associated metabolites (P < 0.05) in xenobiotic- and lipid-associated pathways, whereas never-smokers showed a more pronounced involvement of amino acid- and lipid-associated metabolic pathways. Conclusions: This is the largest prospective study examining untargeted metabolic profiles regarding lung cancer risk. Sphingomyelin (d18:0/22:0), a sphingolipid, and taurodeoxycholic acid 3-sulfate, a bile salt, may be risk factors and potential screening biomarkers for lung cancer. Lipid and amino acid metabolism may contribute significantly to lung cancer etiology which varied by smoking status.