ReviewInternational journal of molecular sciences2026
Extracellular Vesicles in Cancer Diagnosis and Therapy: Advances, Challenges, and Prospects for Clinical Translation.
Review in International journal of molecular sciences, 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.
- Extracellular Matrix-Based and Extracellular Matrix-Bioinspired Scaffolds for Extracellular Vesicle Delivery in Dental Pulp Regeneration: A Narrative Review.Biotech (Basel (Switzerland)) · 2026Review
- Mesenchymal Stem Cells and Extracellular Vesicles: Bridging the Translational Gap in Regenerative Medicine.International journal of molecular sciences · 2026Article
- Exosome-Based Liquid Biopsy in Biliary Tract Cancer: Nanotechnology-Enabled Strategies and Future Perspectives.International journal of nanomedicine · 2026Review
- Precision Engineering of Extracellular Vesicles as Programmable Carriers for mRNA Therapeutics.International journal of nanomedicine · 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
4 authors.
Funding
Abstract
Extracellular vesicles (EVs) have emerged as promising tools for cancer diagnosis and therapy owing to their excellent biocompatibility, low immunogenicity, and ability to transport diverse bioactive molecules. This review summarizes recent advances in EVs research, focusing on isolation and detection technologies, their diagnostic and therapeutic applications in oncology, and the key challenges limiting clinical translation. Conventional EVs isolation methods, including ultracentrifugation, density-gradient centrifugation, and polymer-based precipitation, are discussed alongside emerging strategies such as immunoaffinity enrichment, microfluidic separation, lipid-mediated isolation, and thermophoretic enrichment, with comparative evaluation of their yield, purity, cost, and scalability. In cancer diagnosis, EV-associated biomolecules, such as miRNAs, mRNAs, proteins, and lncRNAs, show strong potential as liquid biopsy biomarkers for noninvasive early detection and dynamic disease monitoring. In therapeutic contexts, EVs serve as versatile carriers for gene molecules, chemotherapeutic agents, and small-molecule drugs, and can enhance immunotherapy and RNA-based treatments. Importantly, EVs released from metabolically active tissues, particularly skeletal muscle, contribute to systemic immune regulation and metabolic homeostasis, and their biogenesis and molecular cargo can be influenced by physical activity and exercise-related nutritional status. These insights highlight the need to integrate microengineering technologies, biomolecular profiling, standardized manufacturing systems, and lifestyle-related factors such as exercise and nutrition to accelerate the clinical translation of EV-based strategies in precision oncology and regenerative medicine.
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.