High-resolution metabolomics-based biomarker discovery using exhaled breath condensate from patients with lung cancer

Abstract

Early diagnosis and treatment are critical for improving the survival of patients with lung cancer, which is the leading cause of cancer-related deaths worldwide. In this study, we investigated whether the metabolomics analysis of exhaled breath condensate (EBC) from patients with lung cancer can provide biomarkers that can be used for noninvasive screening for lung cancer diagnosis. EBC samples obtained from patients with lung cancer (n = 20) and healthy individuals (n = 5) were subjected to high-resolution metabolomics (HRM) using liquid chromatography-mass spectrometry (LC-MS). Univariate analysis, with a false discovery rate (FDR), q = 0.05, and hierarchical clustering analysis were performed to discover significantly different metabolites between the healthy controls and patients with lung cancer. This was followed by the identification of the metabolites using the METLIN database. Pathway analysis based on the identified metabolites revealed that arachidonic acid (AA) metabolism was the most significantly affected pathway. Finally, 5-hydroxyicosatetraenoic acid (HETE) (m/z 343.2233, [M + Na](+)), a metabolite involved in AA metabolism, was found to be significantly higher in patients with lung cancer than in healthy counterparts. Our finding suggested that the HRM of EBC samples is a useful approach for identifying biomarkers for noninvasive screening for lung cancer diagnosis.