Lung cancer is the leading cause of cancer-related deaths among men and women in the world, accounting for the 25% of cancer mortality. Early diagnosis is an unmet clinical issue. In this work, we focused to develop a novel approach to identify highly sensitive and specific biomarkers by investigating the use of extracellular vesicles (EVs) isolated from the pleural lavage, a proximal fluid in lung cancer patients, as a source of potential biomarkers. We isolated EVs by ultracentrifuge method from 25 control pleural fluids and 21 pleural lavages from lung cancer patients. Analysis of the expression of EV-associated miRNAs was performed using Taqman OpenArray technology through which we could detect 288 out of the 754 miRNAs that were contained in the OpenArray. The differential expression analysis yielded a list of 14 miRNAs that were significantly dysregulated (adj. p-value < 0.05 and logFC lower or higher than 3). Using Machine Learning approach we discovered the lung cancer diagnostic biomarkers; miRNA-1-3p, miRNA-144-5p and miRNA-150-5p were found to be the best by accuracy. Accordance with our finding, these miRNAs have been related to cancer processes in previous studies. This results opens the avenue to the use of EV-associated miRNA of pleural fluids and lavages as an untapped source of biomarkers, and specifically, identifies miRNA-1-3p, miRNA-144-5p and miRNA 150-5p as promising biomarkers of lung cancer diagnosis.

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Introduction: Our study sought to know the current implementation of video-assisted thoracoscopic surgery (VATS) for anatomical lung resections in Spain. We present our initial results and describe the auditing systems developed by the Spanish VATS Group (GEVATS). Methods: We conducted a prospective multicentre cohort study that included patients receiving anatomical lung resections between 12/20/2016 and 03/20/2018. The main quality controls consisted of determining the recruitment rate of each centre and the accuracy of the perioperative data collected based on six key variables. The implications of a low recruitment rate were analysed for "90-day mortality" and "Grade IIIb-V complications". Results: The series was composed of 3533 cases (1917 VATS; 54.3%) across 33 departments. The centres' median recruitment rate was 99% (25-75th:76-100%), with an overall recruitment rate of 83% and a data accuracy of 98%. We were unable to demonstrate a significant association between the recruitment rate and the risk of morbidity/mortality, but a trend was found in the unadjusted analysis for those centres with recruitment rates lower than 80% (centres with 95-100% rates as reference): grade IIIb-V OR = 0.61 (p = 0.081), 90-day mortality OR = 0.46 (p = 0.051). Conclusions: More than half of the anatomical lung resections in Spain are performed via VATS. According to our results, the centre's recruitment rate and its potential implications due to selection bias, should deserve further attention by the main voluntary multicentre studies of our speciality. The high representativeness as well as the reliability of the GEVATS data constitute a fundamental point of departure for this nationwide cohort.