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Cited by 586

The DOI matches its Crossref record; 84 of the 84 references it cites were found in a registry or an index.

Exosomes in bodily fluids are a highly stable resource of disease biomarkers

Open access
Boukouris, Stephanie, Mathivanan, Suresh·2015·PROTEOMICS – Clinical Applications

Abstract

Biomarkers are measurable indicators of a biological state. As our understanding of diseases meliorates, it is generally accepted that early diagnosis renders the best chance to cure a disease. In the context of proteomics, the discovery phase of identifying bonafide biomarkers and the ensuing validation phase involving large cohort of patient samples are impeded by the complexity of bodily fluid samples. High abundant proteins found in blood plasma make it difficult for the detection of low abundant proteins that may be potential biomarkers. Extracellular vesicles (EVs) have reignited interest in the field of biomarker discovery. EVs contain a tissue‐type signature wherein a rich cargo of proteins and RNA are selectively packaged. In addition, as EVs are membranous structures, the luminal contents are protected from degradation by extracellular proteases and are highly stable in storage conditions. Interestingly, an appealing feature of EV‐based biomarker analysis is the significant reduction in the sample complexity compared to whole bodily fluids. With these prescribed attributes, which are the rate‐limiting factors of traditional biomarker analysis, there is immense potential for the use of EVs for biomarker detection in clinical settings. This review will discuss the current issues with biomarker analysis and the potential use of EVs as reservoirs of disease biomarkers.

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Crossref · 10.1002/prca.201400114

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Metadata

Authors
Boukouris, S., & Mathivanan, S.
Venue
PROTEOMICS – Clinical Applications
Publisher
Wiley
Published
2015-03-19
Volume
9
Issue
3-4
Pages
358-367
ISSN
  • 1862-8346 (ISSN-L)
  • 1862-8354
OpenAlex
W2171000684
Cited by
586
References
84
FWCI
12.09
Type
journal article
Language
en
Open access
green

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.