Extracellular Vesicles in Cancer: Biomarkers, Mechanisms, and Emerging Diagnostic Technologies

Extracellular vesicles (EVs) are nanoscale, membrane-bound particles that transport diverse biomolecules-including proteins, nucleic acids, lipids, and metabolites-between cells, thereby orchestrating key processes in cancer progression. Tumor-derived EVs modulate angiogenesis, epithelial-to-mesenchymal transition, extracellular matrix remodeling, fibroblast activation, and immune evasion, shaping the tumor microenvironment, and driving metastasis as well as therapy resistance. With their stability in biofluids and cargo reflective of cellular origin, EVs have emerged as powerful non-invasive biomarkers for early detection, disease monitoring, and prognosis across multiple cancer types. Recent advances in enrichment, characterization, and molecular profiling technologies-ranging from ultracentrifugation and microfluidics to proteomics, RNA sequencing, and surface-enhanced Raman spectroscopy, have greatly expanded the diagnostic potential of EVs. Integration with machine learning further enhances sensitivity, specificity, and tumor classification, while multiomic and multiplex platforms enable high-throughput and clinically relevant applications. This review highlights the multifaceted roles of EVs in cancer biology, catalogs emerging biomarkers, and compares state-of-the-art detection technologies, offering a comprehensive reference for advancing EV-based diagnostics and precision oncology.

Authors

Institutions

Publication Details

Journal
Advanced Healthcare Materials
Published
2026-07-26
DOI
https://doi.org/10.1002/adhm.71462
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Extracellular Vesicles in Cancer: Biomarkers, Mechanisms, and Emerging Diagnostic Technologies

Juan Peng, Sichong Xie, Chao Kang, Cheng Wang et al.
Advanced Healthcare Materials
Extracellular vesicles in disease
article

Extracellular Vesicles in Cancer: Biomarkers, Mechanisms, and Emerging Diagnostic Technologies

Juan Peng, Sichong Xie, Chao Kang, Cheng Wang, Yajuan Liu
article en

Abstract

Extracellular vesicles (EVs) are nanoscale, membrane-bound particles that transport diverse biomolecules-including proteins, nucleic acids, lipids, and metabolites-between cells, thereby orchestrating key processes in cancer progression. Tumor-derived EVs modulate angiogenesis, epithelial-to-mesenchymal transition, extracellular matrix remodeling, fibroblast activation, and immune evasion, shaping the tumor microenvironment, and driving metastasis as well as therapy resistance. With their stability in biofluids and cargo reflective of cellular origin, EVs have emerged as powerful non-invasive biomarkers for early detection, disease monitoring, and prognosis across multiple cancer types. Recent advances in enrichment, characterization, and molecular profiling technologies-ranging from ultracentrifugation and microfluidics to proteomics, RNA sequencing, and surface-enhanced Raman spectroscopy, have greatly expanded the diagnostic potential of EVs. Integration with machine learning further enhances sensitivity, specificity, and tumor classification, while multiomic and multiplex platforms enable high-throughput and clinically relevant applications. This review highlights the multifaceted roles of EVs in cancer biology, catalogs emerging biomarkers, and compares state-of-the-art detection technologies, offering a comprehensive reference for advancing EV-based diagnostics and precision oncology.

Advanced Healthcare Materials
Central South University (CN), Guizhou University (CN), Guangzhou University (CN), Zhuzhou Central Hospital (CN), State Key Laboratory of Respiratory Disease (CN), Guangzhou Medical University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 15%
Extracellular vesicles in disease
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.