Evidence map›Paper›PMID 40896292›Full record

ArticleJournal of translational internal medicine2025

Harnessing the potential of small extracellular vesicle biomarkers for cancer diagnosis and prognosis with advanced analytical technologies.

Claudia Wing Lam Tam, Judy Wai Ping Yam

Abstract read
In one paragraph

Article in Journal of translational internal medicine, 2025. 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.

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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

2 authors.

Claudia Wing Lam TamDepartment of Pathology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Judy Wai Ping YamDepartment of Pathology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.ORCID https://orcid.org/0000-0002-5637-121X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small extracellular vesicles (sEVs), also referred as exosomes, have emerged as valuable indicators of cancer progression and response to treatment. They offer prospective targets for therapeutic interventions as well as insightful information about the fundamental mechanisms underlying the development of cancer. sEVs have garnered significant attention as a useful tool for liquid biopsies used in non-invasive cancer diagnosis. We discussed their potential in predicting treatment outcomes, monitoring disease progression, and classifying cancer stages and subtypes. sEVs can also shed light on how resistance to several cancer treatments, such as drug resistance, radiation resistance, chemotherapy resistance, and immunotherapy resistance develops. sEV-based cancer diagnostics have initiated clinical trials, underscoring their potential clinical value. Additionally, significant progress has been made in the development of techniques for isolating and enriching sEVs, enabling the sensitive and efficient detection of sEV proteins and nucleic acids. These advancements have resulted in enhanced sensitivity and specificity, facilitating the identification of biomarkers with low expression levels. In conclusion, sEV biomarkers offer significant potential for the diagnosis and monitoring of cancer. The utilization of sEVs in liquid biopsies presents a non-invasive method for acquiring tumour-specific information. Ongoing research and advancements in sEV-based diagnostics and therapeutics are crucial for unlocking the complete potential of sEV biomarkers in clinical settings.

Indexed as

liquid biopsiessmall extracellular vesicle-based diagnosissmall extracellular vesicle biomarkerssmall extracellular vesicle isolation

Identifiers

PMID40896292
PMCPMC12392082

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.