An EBC/Plasma miRNA Signature Discriminates Lung Adenocarcinomas From Pleural Mesothelioma and Healthy Controls

Background Despite significant improvement in screening programs for cancers of the respiratory district, especially in at-risk subjects, early disease detection is still a major issue. In this scenario, new molecular and non-invasive biomarkers are needed to improve early disease diagnosis. Methods We profiled the miRNome in exhaled breath condensate (EBC) and plasma samples from fourteen patients affected by lung AdCa, nine healthy subjects. miRNA signatures were then analyzed in another neoplasia of the respiratory district, i.e. pleural mesothelioma (n = 23) and subjects previously exposed to asbestos were used as controls for this cohort (n = 19). Selected miRNAs were analyzed in purified pulmonary neoplastic or normal epithelial and stromal cell subpopulation from AdCa patients. Finally, the plasmatic miRNA signature was analyzed in a publicly available cohort of NSCLC patients for data validation and in silico analysis was performed with predicted miRNA targets using the multiMiR tool and STRING database. Results miR-597-5p and miR-1260a are significantly over-expressed in EBC from lung AdCa and are associated with AdCa. Similarly, miR-1260a is also up-regulated in the plasma of AdCa patients together with miR-518f-3p and correlates with presence of lung cancer, whereas let-7f-5p is under-expressed. Analysis of these circulating miRNAs in pleural mesothelioma cases confirmed that up-regulation of miR-518f-3p, -597-5p and -1260a, is specific for lung AdCa. Lastly, quantification of the miRNAs in laser-assisted microdissected lung tissues revealed that miR-518f-3p, 597-5p and miR-1260a are predominantly expressed in tumor epithelial cells. Validation analysis confirmed miR-518f-3p as a possible circulating biomarker of NSCLC. In silico analysis of the potentially modulated biological processes by these three miRNAs, shows that tumor bioenergetics are the most affected pathways. Conclusions Overall, our data suggest a 3-miRNAs signature as a non-invasive and accurate biomarker of lung AdCa. This approach could supplement the current screening approaches for early lung cancer diagnosis.