1. Characterization of Extracellular Vesicles from Bronchoalveolar Lavage Fluid and Plasma of Patients with Lung Lesions Using Fluorescence Nanoparticle Tracking Analysis
- Author
-
Magdalena Dlugolecka, Jacek Szymanski, Lukasz Zareba, Zuzanna Homoncik, Joanna Domagala-Kulawik, Malgorzata Polubiec-Kownacka, and Malgorzata Czystowska-Kuzmicz
- Subjects
Lung Neoplasms ,bronchoalveolar lavage fluid ,QH301-705.5 ,fluorescence nanoparticle tracking analysis ,General Medicine ,Flow Cytometry ,Fluorescence ,Article ,extracellular vesicles ,plasma ,non-small-cell lung cancer ,Biomarkers, Tumor ,Humans ,Nanoparticles ,Biology (General) ,Lung - Abstract
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.
- Published
- 2021