Salivary Metabolomics for the Diagnosis of Lung Cancer Using a Rapid Thin-Film Micro-Extraction Method

Abstract

In recent years, numerous metabolomics experiments on lung cancer have not only identified novel biomarkers for early diagnosis, but also investigated the altered metabolic pathways to enhance our understanding of its pathogenesis. Thin-film microextraction (TFME) is a non-invasive, cost-effective, and selective analytical technique for the rapid identification of metabolite biomarkers in clinical samples and has significant potential to be used in this field. This study aimed to investigate the role of targeted salivary metabolomics as a diagnostic tool for non-small cell lung cancer (NSCLC) using a TFME-based method applied to the saliva. A total of 40 NSCLC patients comprised the study group, along with 38 healthy controls. TFME blades modified with SiO2 nanoparticles and produced by a custom-made coating system. Validation of the metabolite biomarker analysis were performed by these blades using liquid chromatography-tandem mass spectroscopy (LC-MS/MS). The extraction efficiencies of SiO2 nanoparticle/polyacrylonitrile (PAN) composite coated blades were compared for 18 metabolites. Response surface methodology (RSM) was used to optimize the analysis conditions. The efficacy of metabolites for diagnosis was determined by in silico methods and the results revealed that phenylalanine and purine metabolism metabolites (i.e. hypoxanthine) are of great importance, while ROC curve data revealed that proline, hypoxanthine, and phenylalanine were potential biomarkers for NSCLC diagnosis.