EV-ADD, a database for EV-associated DNA in human liquid biopsy samples

Abstract

Extracellular vesicles (EVs) play a key role in cellular communication both in physiological conditions and in pathologies such as cancer. Emerging evidence has shown that EVs are active carriers of molecular cargo (e.g. protein and nucleic acids) and a powerful source of biomarkers and targets. While recent studies on EV-associated DNA (EV-DNA) in human biofluids have generated a large amount of data, there is currently no database that catalogues information on EV-DNA. To fill this gap, we have manually curated a database of EV-DNA data derived from human biofluids (liquid biopsy) and in-vitro studies, called the Extracellular Vesicle-Associated DNA Database (EV-ADD). This database contains validated experimental details and data extracted from peer-reviewed published literature. It can be easily queried to search for EV isolation methods and characterization, EV-DNA isolation techniques, quality validation, DNA fragment size, volume of starting material, gene names and disease context. Currently, our database contains samples representing 23 diseases, with 13 different types of EV isolation techniques applied on eight different human biofluids (e.g. blood, saliva). In addition, EV-ADD encompasses EV-DNA data both representing the whole genome and specifically including oncogenes, such as KRAS, EGFR, BRAF, MYC, and mitochondrial DNA (mtDNA). An EV-ADD data metric system was also integrated to assign a compliancy score to the MISEV guidelines based on experimental parameters reported in each study. While currently available databases document the presence of proteins, lipids, RNA and metabolites in EVs (e.g. Vesiclepedia, ExoCarta, ExoBCD, EVpedia, and EV-TRACK), to the best of our knowledge, EV-ADD is the first of its kind to compile all available EV-DNA datasets derived from human biofluid samples. We believe that this database provides an important reference resource on EV-DNA-based liquid biopsy research, serving as a learning tool and to showcase the latest developments in the EV-DNA field. EV-ADD will be updated yearly as newly published EV-DNA data becomes available and it is freely available at www.evdnadatabase.com.

Keywords: EV-ADD; EV-DNA; cfDNA; database; extracellular vesicles; liquid biopsy.

FIGURE 1

Simplified schematic workflow of EV‐ADD. Workflow is presented in three steps: (1) identification of studies on EV‐DNA isolated from in‐vitro and human biofluids samples; (2) screening of data for eligibility in EV‐ADD; and finally (3) inclusion and upload of EV‐DNA data to EV‐ADD. As the EV‐ADD relies on publications from the EV community, clear communication and feedback between researchers and database curators is essential to maintain the EV‐DNA lifecycle.

FIGURE 2

Search results on EV‐ADD. (A) An example of a query for “KRAS gene” as a search criterion in EV‐ADD. (B) The database retrieves data on type of diseases, number of patients, EV‐ADD data score system (% score), type of EV‐DNA detected, source of biofluids, EV‐DNA fragment size, methods of EV isolation, EV purification and characterization, subtypes of EVs, EV‐DNA isolation techniques, EV‐DNA quantification methods, volume of biofluids, enzymatic treatments, reference (Möhrmann et al., 2018), method of DNA detections, results, application, PubMed ID, EV‐TRACK ID and score (if any). NTA = nanoparticle tracking analysis, SEM = scanning electron microscopy, WB = western blot

FIGURE 3

(A) An overview of the main functions in the EV‐ADD. Published data on EV‐DNA isolated from human biofluids is manually curated and annotated in a web‐based application in the EV‐ADD which can be searched and sorted based on various categories. (B) EVs can be isolated from human biofluids using (C) various EV purification techniques and (D) EV‐DNA can then be isolated using commercial kits or in‐house protocols. (E) Lastly, EV‐DNA mutations, SNPs and CNVs can be detected using various PCR and sequencing techniques. UC = ultracentrifugation, ddPCR = Droplet Digital PCR, qPCR = Quantitative PCR, RT‐PCR = Reverse Transcription PCR