ReviewBiomarker research2026
Unlocking the power of extracellular vesicles: multi-omics integration for cancer biomarker discovery.
Review in Biomarker research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Artificial intelligence and extracellular vesicles in oncology: towards tumor diagnosis, prediction, and therapy.Drug delivery · 2026Review
- Review Article: Biomarkers in Liver Transplantation for Hepatocellular Carcinoma: Towards Precision Medicine.Alimentary pharmacology & therapeutics · 2026Review
- Renal Tubular Epithelial Cells as Central Hubs of Kidney Disease.Diagnostics (Basel, Switzerland) · 2026Review
- Review
- Artificial Intelligence-Enabled Bioengineering of Extracellular Vesicle Platforms in Cardiovascular Medicine.Bioengineering (Basel, Switzerland) · 2026Review
- The Promise and Challenges of Mesenchymal Stem Cell-Derived Extracellular Vesicles in Periodontal Disease.Pathogens (Basel, Switzerland) · 2026Review
- Mechanistic interplay between extracellular vesicles and neutrophil extracellular traps: unveiling the "sterile inflammation" cascade in obesity-induced diabetes progression.Frontiers in immunology · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The search for reliable cancer biomarkers is increasingly driven by the need for non-invasive tools that can monitor tumor dynamics in real time. Extracellular vesicles (EVs) are a heterogeneous family of nanoparticles secreted by almost all cell types under physiological and pathological conditions. By carrying proteins, nucleic acids, lipids and metabolites that reflect the molecular state of their cells of origin, EVs act as dynamic messengers of tumor biology. Their stability and abundance in easily accessible body fluids make them ideal candidates for liquid biopsy, offering a unique opportunity to investigate the molecular mechanisms underlying cancer initiation, progression and therapy resistance. Advances in high-throughput omics technologies, including proteomics, metabolomics, lipidomics and transcriptomics, have enabled comprehensive profiling of EV cargo. These approaches have already identified promising biomarkers now entering clinical application, creating opportunities for earlier detection and more personalized interventions. However, relying on a single omics layer captures only a fraction of the molecular complexity underlying malignant disease. Integrative multi-omics strategies might uncover the regulatory networks and signaling pathways that drive tumor heterogeneity and evolution. Bioinformatics multi-omics integration focuses on developing tools that combine data from multiple omics experiments, revealing how their components interact and how these interactions change in disease. This review summarizes recent advances in EV-based multi-omics research for cancer diagnosis and clinical management, emphasizing how integrative approaches not only enhance biomarker discovery but also provide a systems-level understanding of disease mechanisms, paving the way toward precision and personalized 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.