Evidence map›Paper›PMID 40836218›Full record

ArticleBiological procedures online2025

Refining Flow Cytometry-based Sorting of Plasma-derived Extracellular Vesicles.

Daniele Reverberi, Maria Chiara Ciferri, Nicole Rosenwasser, Alessandro Catino, Giuseppina Poppa, Ilaria Giusti, Vincenza Dolo, Rodolfo Quarto, Sara Santamaria, Monica Colombo and 2 more

Abstract read
In one paragraph

Article in Biological procedures online, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

12 authors.

Daniele Reverberi *Scientific Direction, IRCCS Ospedale Policlinico San Martino, Genova, Italy.
Maria Chiara Ciferri *Department of Experimental Medicine (DIMES), University of Genova, Genova, Italy.
Nicole RosenwasserDepartment of Experimental Medicine (DIMES), University of Genova, Genova, Italy.
Alessandro CatinoCellular Oncology, IRCCS Ospedale Policlinico San Martino, Genova, Italy.
Giuseppina PoppaDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Ilaria GiustiDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Vincenza DoloDepartment of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy.
Rodolfo QuartoDepartment of Experimental Medicine (DIMES), University of Genova, Genova, Italy.
Sara SantamariaMedical Oncology Clinic, IRCCS Ospedale Policlinico San Martino, Genova, Italy.
Monica ColomboMolecular Pathology, IRCCS Ospedale Policlinico San Martino, Genova, Italy.
Simona CocoLung Cancer Unit, IRCCS Ospedale Policlinico San Martino, Genova, Italy.
Roberta TassoDepartment of Experimental Medicine (DIMES), University of Genova, Genova, Italy. roberta.tasso@unige.it.

Funding

Gilead Italy Fellowship Program 2022Worldwide Cancer Research 24-0042
6 · The paper itself

Abstract

backgroundExtracellular vesicles (EVs) are membrane-bound particles crucial for intercellular communication and serve as promising biomarkers for diseases, including cancer. Isolating and characterizing specific EV subpopulations, particularly those in plasma/serum, enhances biomarker precision and supports targeted therapies. Cancer-derived EVs often express unique surface markers, enabling distinction from other EVs. Accurate sorting of tumor-associated EVs provides insights into cancer progression, metastasis, and treatment response.

resultsThis study presents a robust method for isolating and sorting CD9 + plasma EVs as a proof-of-concept for broader EV subpopulation analyses. Plasma EVs were isolated via sucrose cushion ultracentrifugation, optimizing purity and yield. Flow cytometry with fluorescence threshold triggering was fine-tuned to detect and sort CD9 + EVs, with instrument calibration and parameter adjustments mitigating swarming and improving sorting accuracy. Size exclusion chromatography further enhanced efficiency by reducing background noise. Sorted CD9 + EVs retained size and marker expression, including Syntenin, Alix, Flotillin-1, and CD9, which were enriched post-sorting.

conclusionsThese advancements enable high-purity EV subpopulation isolation, facilitating applications such as identifying cancer biomarkers and developing EV-based targeted therapies.

Indexed as

CancerExtracellular VesiclesFlow CytometrySortingTumor Biomarkers

Identifiers

PMID40836218
PMCPMC12366389

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.