Evidence mapPaperPMID 41527006Full record

ReviewBiomarker research2026

Unlocking the power of extracellular vesicles: multi-omics integration for cancer biomarker discovery.

Chiara Ansermino, Radmila Pavlovic, Clarissa Braccia, Denise Drago, Chiara Anelli, Annapaola Andolfo

Abstract readReview
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Chiara AnserminoProteomics and Metabolomics Facility (ProMeFa), Center for OMICS Sciences (COSR), IRCCS Ospedale San Raffaele, 20132, Milan, Italy.
Radmila PavlovicProteomics and Metabolomics Facility (ProMeFa), Center for OMICS Sciences (COSR), IRCCS Ospedale San Raffaele, 20132, Milan, Italy.
Clarissa BracciaProteomics and Metabolomics Facility (ProMeFa), Center for OMICS Sciences (COSR), IRCCS Ospedale San Raffaele, 20132, Milan, Italy. braccia.clarissa@hsr.it.
Denise DragoProteomics and Metabolomics Facility (ProMeFa), Center for OMICS Sciences (COSR), IRCCS Ospedale San Raffaele, 20132, Milan, Italy. drago.denise@hsr.it.
Chiara AnelliDepartment of Molecular Medicine, University of Pavia, 27100, Pavia, Italy.
Annapaola AndolfoProteomics and Metabolomics Facility (ProMeFa), Center for OMICS Sciences (COSR), IRCCS Ospedale San Raffaele, 20132, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

BiomarkersCancerExtracellular vesiclesMulti-omics

Identifiers

PMID41527006
PMCPMC12809910

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.