4.7 Article

Benchmarking blood collection tubes and processing intervals for extracellular vesicle performance metrics

Journal

JOURNAL OF EXTRACELLULAR VESICLES
Volume 12, Issue 5, Pages -

Publisher

WILEY
DOI: 10.1002/jev2.12315

Keywords

anticoagulants; biomarkers; cancer; exosomes; extracellular vesicles; plasma; preservatives; proteomics; RNA sequencing; serum

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The analysis of extracellular vesicles (EV) in blood samples is being extensively studied, as it has the potential to provide clinically meaningful biomarkers for health and disease. This study investigated the impact of different blood collection tubes and processing intervals on EV characteristics in blood samples. The results showed that the choice of blood collection tube and processing interval significantly affected various metrics related to blood sample quality, ex-vivo generation of EV from blood cells, EV recovery, and molecular signatures associated with EV. These findings provide valuable guidance for selecting optimal conditions for EV analysis and contribute to standardizing EV studies.
The analysis of extracellular vesicles (EV) in blood samples is under intense investigation and holds the potential to deliver clinically meaningful biomarkers for health and disease. Technical variation must be minimized to confidently assess EV-associated biomarkers, but the impact of pre-analytics on EV characteristics in blood samples remains minimally explored. We present the results from the first large-scale EV Blood Benchmarking (EVBB) study in which we systematically compared 11 blood collection tubes (BCT; six preservation and five non-preservation) and three blood processing intervals (BPI; 1, 8 and 72 h) on defined performance metrics (n = 9). The EVBB study identifies a significant impact of multiple BCT and BPI on a diverse set of metrics reflecting blood sample quality, ex-vivo generation of blood-cell derived EV, EV recovery and EV-associated molecular signatures. The results assist the informed selection of the optimal BCT and BPI for EV analysis. The proposed metrics serve as a framework to guide future research on pre-analytics and further support methodological standardization of EV studies.

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