Characterization of Extracellular Vesicles from Bronchoalveolar Lavage Fluid and Plasma of Patients with Lung Lesions Using Fluorescence Nanoparticle Tracking Analysis

The current lack of reliable methods for quantifying extracellular vesicles (EVs) isolated from complex biofluids significantly hinders translational applications in EV research. The recently developed fluorescence nanoparticle tracking analysis (FL-NTA) allows for the detection of EV-associated proteins, enabling EV content determination. In this study, we present the first comprehensive phenotyping of bronchopulmonary lavage fluid (BALF)-derived EVs from non-small cell lung cancer (NSCLC) patients using classical EV-characterization methods as well as the FL-NTA method. We found that EV immunolabeling for the specific EV marker combined with the use of the fluorescent mode NTA analysis can provide the concentration, size, distribution, and surface phenotype of EVs in a heterogeneous solution. However, by performing FL-NTA analysis of BALF-derived EVs in comparison to plasma-derived EVs, we reveal the limitations of this method, which is suitable only for relatively pure EV isolates. For more complex fluids such as plasma, this method appears to not be sensitive enough and the measurements can be compromised. Our parallel presentation of NTA-based phenotyping of plasma and BALF EVs emphasizes the great impact of sample composition and purity on FL-NTA analysis that has to be taken into account in the further development of FL-NTA toward the detection of EV-associated cancer biomarkers.

Automated summary

The study conducted a comprehensive phenotyping of bronchopulmonary lavage fluid (BALF)-derived EVs from non-small cell lung cancer (NSCLC) patients using FL-NTA method, revealing that the method is suitable only for relatively pure EV isolates and may not be sensitive enough for more complex fluids like plasma. The research highlights the importance of sample composition and purity in FL-NTA analysis for the detection of EV-associated cancer biomarkers.