ReviewProteomics2026
Challenges and Opportunities in State-of-the-Art Proteomics Analysis for Biomarker Development From Plasma Extracellular Vesicles.
Review in Proteomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Assessing Extracellular Vesicle Proteins as Predictive Biomarkers for Developing Type 1 Diabetes.Proteomics · 2026Article
- Exercise and Skeletal Muscle-Derived Extracellular Vesicles: Their Cargo, Release, and Role in Metabolic Regulation.Journal of extracellular biology · 2026Review
- Engineering inertial flow patterns for signal amplification in disc-based protein assays.Theranostics · 2026Article
- Integrating mass spectrometry-based multi-omic signatures of extracellular vesicles: from discovery to clinical translation.Clinical & translational immunology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Extracellular vesicles (EVs) are membrane-bound particles secreted by cells, playing crucial roles in intercellular communication. The composition of EVs can undergo changes in response to stress and disease conditions, making them excellent biomarker candidates. However, extracting protein information from EVs can be challenging due to their low abundance in complex biofluids and copurification with contaminant proteins and particles. Techniques to enrich EVs have their strengths and limitations, without one being able to purify EVs to complete homogeneity. This can lead to compromised recovery rates and increased complexity, making data interpretation difficult. In this viewpoint article, we explore the concept that better characterization of EV composition, followed by quantification of EV proteins in complex samples, might be a more viable route for biomarker development. Mass spectrometers can provide reproducible deep coverage of the EV proteome, despite sample impurities. This paradigm shift presents opportunities to integrate advanced bioinformatics tools to refine the EV proteome landscape, identify novel biomarkers, and streamline validation processes in biomarker development. By focusing on leveraging technology rather than achieving absolute purity, this approach can transform current practices and open opportunities for robust biomarker discovery. Herein, we highlight not only such opportunities but also challenges to implement this concept. SUMMARY: Extracellular vesicles (EVs) have enormous potential as biomarkers of diseases, as they can carry signatures of the cells they are derived from and the pathogenesis process. Biofluids, such as blood plasma, are highly complex and contain many components with physicochemical properties similar to those of EVs, making it challenging to obtain pure EV fractions. Challenges in obtaining pure preparations represent a main hurdle for studying EVs, and their components are potential biomarkers. This article explores the concept of studying EV proteins within complex samples, discussing opportunities and needs to move this field forward.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.