EV-associated miRNAs from pleural lavage as potential diagnostic biomarkers in lung cancer

Abstract

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 specifc biomarkers by investigating the use of extracellular vesicles (EVs) isolated from the pleural lavage, a proximal fuid in lung cancer patients, as a source of potential biomarkers. We isolated EVs by ultracentrifuge method from 25 control pleural fuids and 21 pleural lavages from lung cancer patients. Analysis of the expression of EVassociated 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 diferential expression analysis yielded a list of 14 miRNAs that were signifcantly 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 fnding, 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 fuids and lavages as an untapped source of biomarkers, and specifcally, identifes miRNA-1-3p, miRNA-144-5p and miRNA 150-5p as promising biomarkers of lung cancer diagnosis.

Te authors would like to acknowledge the work that has been done by all clinicians that have participated in the recruitment of clinical samples. We thank the patients for their willingness to participate in the study. Te sample collection was supported by IRBLleida BIOBANK (B.0000682) and Plataforma biobancos PT17/0015/0027.EC hold a postdoctoral fellowship from the Departament de Salut of the Generalitat de Catalunya (SLT002/16/00274). Tis study was supported by: “Discovery, validation and implementation of biomarkers for Precision Oncology” (ISCIII PIE15/00029), CIBERONC (CB16/12/00231 and CB16/12/00328), Grups consolidats de la Generalitat de Catalunya (2017SGR1368 and 2017SGR1661) and Asociación Española contra el Cancer (GCTRA1804MATI).