Mass Spectrometry-Based Extracellular Vesicle Proteomics for Biomarker Discovery.

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.