Introduction/objectives: Incidence of esophageal adenocarcinoma (EA), an often fatal cancer, has increased sharply over recent decades. Several important risk factors (reflux, obesity, smoking) have been identified for EA and its precursor, Barrett's esophagus (BE), but a key challenge remains identifying individuals at highest risk, since most with reflux do not develop BE, and most with BE do not progress to cancer. Metabolomics represents an emerging approach for identifying novel biomarkers associated with cancer development.
Methods: We used targeted liquid chromatography-mass spectrometry (LC-MS) to profile 57 metabolites in 322 serum specimens derived from individuals with gastroesophageal reflux disease (GERD), BE, high-grade dysplasia (HGD), or EA, drawn from two well-annotated epidemiologic parent studies.
Results: Multiple metabolites differed significantly (P<0.05) between BE versus GERD (n=9), and between HGD/EA versus BE (n=4). Several top candidates (FDR q≤0.15), including urate, homocysteine, and 3-nitrotyrosine, are linked to inflammatory processes, which may contribute to BE/EA pathogenesis. Multivariate modeling achieved moderate discrimination between HGD/EA and BE (AUC=0.75), with less pronounced separation for BE versus GERD (AUC=0.64).
Conclusion: Serum metabolite differences can be detected between individuals with GERD versus BE, and between those with BE versus HGD/EA, and may help differentiate patients at different stages of progression to EA.
Keywords: Barrett’s esophagus; esophageal adenocarcinoma; gastroesophageal reflux disease; metabolomics; risk stratification; serum biomarkers.