ReviewAdvanced healthcare materials2026
Extracellular Vesicles in Cancer: Biomarkers, Mechanisms, and Emerging Diagnostic Technologies.
Review in Advanced healthcare materials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
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.
Indexed as
Identifiers
What Socratic 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 Socratic graph.