Affiliation:
1. The University of Queensland Thoracic Research Centre The Prince Charles Hospital Chermside Queensland Australia
2. Tumour Microenvironment Laboratory QIMR Berghofer Medical Research Institute Herston Queensland Australia
3. Department of Otorhinolaryngology Chinese University of Hong Kong Shatin Hong Kong
4. Li Ka Shing Institute of Health Sciences Chinese University of Hong Kong Hong Kong China
Abstract
AbstractPleural effusion occurs in both benign and malignant pleural disease. In malignant pleural effusions, the diagnostic accuracy and sensitivity of pleural fluid cytology is less than perfect, particularly for the diagnosis of malignant pleural mesothelioma, but also in some cases for the diagnosis of metastatic pleural malignancy with primary cancer in the lung, breast or other sites. Extracellular vesicles (EVs) carry an enriched cargo of microRNAs (miRNAs) which are selectively packaged and differentially expressed in pleural disease states. To investigate the diagnostic potential of miRNA cargo in pleural fluid extracellular vesicles (PFEVs), we evaluated methods for isolating the extracellular vesicle (EV) fraction including combinations of ultracentrifugation, size‐exclusion chromatography (SEC) and ultrafiltration (10 kDa filter unit). PFEVs were characterized by total and EV–associated protein, nanoparticle tracking analysis and visualisation by transmission electron microscopy. miRNA expression was analyzed by Nanostring nCounter® in separate EV fractions isolated from pleural fluid with or without additional RNA purification by ultrafiltration (3 kDa filter unit). Optimal PFEV yield, purity and miRNA expression were observed when PFEV were isolated from a larger volume of pleural fluid processed through combined ultracentrifugation and SEC techniques. Purification of total RNA by ultrafiltration further enhanced the detectability of PFEV miRNAs. This study demonstrates the feasibility of isolating PFEVs, and the potential to examine PFEV miRNA cargo using Nanostring technology to discover disease biomarkers.