Extracellular vesicles (EVs) mediate intercellular communication via transferring proteins and other biological molecules and have been recently investigated as biomarkers of disease. Sensitive and specific biomarkers are required for lung cancer diagnosis and prognosis. The present study screens for abnormal EV proteins in non-small cell lung cancer (NSCLC) using a quantitative proteomics strategy involving LC-MS/MS to identify ideal biomarkers for NSCLC diagnosis. EVs are enriched from the sera of early and advanced NSCLC patients and healthy controls and from cell culture supernatants of lung adenocarcinoma and bronchial epithelial cell lines. In the sera and supernatants, 279 and 632 differentially expressed proteins, respectively, are associated with signaling pathways including extracellular membrane-receptor interaction, focal adhesion, and regulation of the actin cytoskeleton. Thirty-two EV proteins are identified at the intersection of differentially expressed proteins between the NSCLC groups and cell lines. Based on bioinformatics analysis, in silico immunohistochemical, and PRM verification, fibronectin is selected for following in vitro studies and validation with an independent cohort. Fibronectin on EVs is estimated to perform well in the diagnosis of NSCLC patients based on AUC, showing great potential for clinical use and demonstrating the efficacy of this method for EV-associated biomarker screening.
Keywords: biomarkers; extracellular vesicles; label-free quantification; lung cancer; proteomics.
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