Early Detection of Lung Cancer by Molecular Markers in Endobronchial Epithelial-Lining Fluid

Abstract

Early detection of malignancies in the lung by less-invasive methods aims at achieving efficient intervention and subsequently a reduction of the high mortality rate. We investigated whether biomarker analysis in endobronchial epithelial-lining fluid (ELF) collected by bronchoscopic microsampling (BMS) may be useful for a definitive preoperative diagnosis. ELF was collected from subsegmental bronchi close to the indeterminate pulmonary nodule, which was detected by computed tomography, and from the contralateral lung. Diagnosis was confirmed by transbronchial biopsy or surgery. The study includes 142 ELF samples from 51 non-small-cell lung cancer patients and 20 benign cases. Microarray analysis was done with a patient subset (n = 15) to narrow down genes associated with a malignant phenotype. Thirteen potential biomarkers have been further analyzed by quantitative real-time polymerases chain reaction in an independent patient cohort (n = 56). All patients underwent BMS without complications. Gene-expression analyses by microarrays and quantitative real-time polymerases chain reaction could be reliably applied to ELF samples, and resulted in potential biomarkers for malignant pulmonary nodules. Four genes (tenascin-C, [C-X-C motif] ligand 14, S100 calcium binding protein A9, and keratin 17) were found to be upregulated in ELF of non-small-cell lung cancer patients with adenocarcinoma or squamous cell carcinoma. Combined analysis of tenascin-C expression and the nodule size improved the prediction of malignancy in this patient cohort. Our study suggests that the analysis of specific biomarkers in ELF collected by BMS could be a potentially useful adjunct to other diagnostic techniques aiming at the preoperative diagnosis of malignant pulmonary nodules.