Mass Spectrometry-Based Extracellular Vesicle Proteomics for Biomarker Discovery.

Extracellular vesicle (EV) proteomics has emerged as a powerful platform for decoding intercellular communication and advancing biomarker discovery across human diseases. EVs carry proteins that reflect their cells of origin, offering a minimally invasive window into physiological and pathological processes. Mass spectrometry (MS) now enables deep, high-resolution EV proteome profiling, aided by improved isolation and rigorous characterization that ensure sample purity and integrity. Advanced computational pipelines integrating quantitative modeling, spectral-library prediction, machine learning and multi-omics analysis extract meaningful biological signals, revealing subtle disease-associated EV signatures and establishing EV proteomics as a strong platform for biomarker discovery and precision medicine. This review provides an integrated framework linking EV isolation principles, characterization strategies, mass-spectrometric workflows, and computational analysis to the biological and clinical insights they generate. We also highlight key challenges and future directions, including the need for standardized reference materials, unified pre-analytical workflows, and EV proteome reference atlases. Together, these innovations are transforming EV proteomics into a next-generation tool for precision medicine.

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Publication Details

Journal
PubMed
Published
2026-08-03
DOI
https://doi.org/10.1002/mas.70040
Primary Topic
Extracellular vesicles in disease
Type
article
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article

Mass Spectrometry-Based Extracellular Vesicle Proteomics for Biomarker Discovery.

Juan Peng, Chao Kang, Ya-Juan Liu
PubMed
Extracellular vesicles in disease
article

Mass Spectrometry-Based Extracellular Vesicle Proteomics for Biomarker Discovery.

Juan Peng, Chao Kang, Ya-Juan Liu
article en

Abstract

Extracellular vesicle (EV) proteomics has emerged as a powerful platform for decoding intercellular communication and advancing biomarker discovery across human diseases. EVs carry proteins that reflect their cells of origin, offering a minimally invasive window into physiological and pathological processes. Mass spectrometry (MS) now enables deep, high-resolution EV proteome profiling, aided by improved isolation and rigorous characterization that ensure sample purity and integrity. Advanced computational pipelines integrating quantitative modeling, spectral-library prediction, machine learning and multi-omics analysis extract meaningful biological signals, revealing subtle disease-associated EV signatures and establishing EV proteomics as a strong platform for biomarker discovery and precision medicine. This review provides an integrated framework linking EV isolation principles, characterization strategies, mass-spectrometric workflows, and computational analysis to the biological and clinical insights they generate. We also highlight key challenges and future directions, including the need for standardized reference materials, unified pre-analytical workflows, and EV proteome reference atlases. Together, these innovations are transforming EV proteomics into a next-generation tool for precision medicine.

PubMed
Guizhou University (CN), Zhuzhou Central Hospital (CN), State Key Laboratory of Respiratory Disease (CN), Guangzhou Medical University (CN)
Openalex Percentile: Top 15%
Extracellular vesicles in disease
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