Jan Van Deun 1,3, Glenn Vergauwen1,3, Pieter Mestdagh 2,3 , Jo Vandesompele 2,3 , Olivier De Wever1,2, An Hendrix1,2,∗
1Laboratory of Experimental Cancer Research, Department of Radiation Oncology and Experimental Cancer Research, Ghent University, Ghent, Belgium;
2Department of Medical Genetics, Ghent University, Ghent, Belgium;
3Cancer Research Institute Ghent, Ghent, Belgium;
Extracellular vesicles (EVs) transmit information (nucleic acids, proteins and lipids) between different cell types, organs and even organisms, and have been detected in multiple body fluids. The con- nection of EVs to many aspects of human disease stimulated many researchers to explore their biomarker potential. The rapid expan- sion of the EV research field resulted in a struggle to cope with het- erogeneity in the implementation and reporting of isolation pro- tocols and characterization methods, delaying the introduction of EV-specific biomarkers in clinical setting. We carried out a compar- ative study of commonly implemented EV isolation methods which revealed a method dependent outcome using omics approaches. Density gradient centrifugation minimized the co-isolation of (non)-membranous contaminants of different origin and obtained a unique proteome and transcriptome signature. In addition, pre- analytical parameters that are commonly implemented but often vary among research groups, such as centrifugal filter types, were shown to have an impact on EV analysis and should be care- fully considered and reported. To help overcome these issues in EV research, we established the EV-TRACK knowledgebase (www. evtrack.org), a crowdsourcing database that centralizes EV biology and methodology. It currently comprises experimental parameters of over 1200 EV-related publications. The EV-TRACK platform aims to stimulate authors, reviewers, editors and funders to put exper- imental guidelines into practice, which is a prerequisite to realize the clinical potential of EV-related biomarkers.
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