Abstract
BACKGROUND AND OBJECTIVE: Lung cancer is one of the most common cancers worldwide. Thus far, good tumor markers for diagnosing this disease have not been found. Therefore, the discovery of novel biomarkers through the application of new methods has become a hotspot in lung cancer research. The aim of this study is to analyze low-molecular-weight metabolites in the serum and urine samples of lung cancer patients and patients with other lung diseases through metabolomics and to explore potential tumor markers further. METHODS: Both serum and urine samples from 19 lung cancer patients and 15 patients with other lung diseases were subjected to metabolomic analysis using gas chromatography mass spectrometry. Orthogonal to partial least squares discriminant analysis was performed for modeling. Two sample t-test was used to identify differences in metabolite concentrations. RESULTS: A total of 57 metabolites were found in the serum, and 38 metabolites were found in the urine. Multivariate statistical analysis yielded a significant distinction in the metabolic profiles between lung cancer patients and patients with other lung diseases. The t-test results indicated a total of 13 metabolites in the serum and 7 metabolites in the urine with statistically significant differences. CONCLUSIONS: Metabolomics is useful in discriminating between lung cancer and other lung diseases. As a novel approach, it has potential in the diagnosis of lung cancer at molecular level.