Evidence map›Paper›PMID 36579638›Full record

ArticleDrug delivery2023

The cell type dependent sorting of CD9- and CD81 to extracellular vesicles can be exploited to convey tumor sensitive cargo to target cells.

Stefania Zuppone, Natasa Zarovni, Riccardo Vago

Open access · goldAbstract read
In one paragraph

Article in Drug delivery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.0field-weighted citation impact, top 5% of its field
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

13 citing papers in PubMed, 45 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Stefania ZupponeUrological Research Institute, Division of Experimental Oncology, IRCCS San Raffaele Scientific Institute, Milano, Italy.
Natasa ZarovniExosomics S.p.A, Siena, Italy.
Riccardo VagoUrological Research Institute, Division of Experimental Oncology, IRCCS San Raffaele Scientific Institute, Milano, Italy.
Istituto di Ricovero e Cura a Carattere Scientifico San RaffaeleVita-Salute San Raffaele University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extracellular vesicles (EVs) are lipid membrane-bound particles involved in cell-to-cell communication through a delivery of regulatory molecules essential for physiological processes. Since EVs efficiently vectorize specific cargo molecules, they have been proposed as suitable vehicles for therapeutic agents. Drug loading into EVs can be achieved by active, exogenous strategies or by genetic modifications of vesicle-producing cells. With the aim to produce EVs conveying therapeutic proteins, we genetically engineered and compared HEK293 to tumor cells. Tetraspanin-based RFP fusions were found to be more stable and preferentially sorted into EVs in HEK293. EVs isolated from genetically modified HEK293 cells media were captured by cancer cells, efficiently delivering their cargo. Cathepsin B cleavage site introduced between CD9/CD81 and RFP was recognized by tumor specific proteases allowing the release of the reporter protein. Our results indicate HEK293 cells as a preferential system for the production of EVs and pave the way to the development of nano-platforms for the efficient delivery of therapeutic proteins and prodrugs to tumor cells.

Indexed as

Extracellular VesiclesNeoplasmsCell CommunicationHEK293 CellsHumansProteinsProtein TransportTetraspanin 28Tetraspanin 29CD81 protein, humanCD9 protein, humanProteinsTetraspanin 28Tetraspanin 29cargo sortingcathepsin B-controlled releaseEVsExtracellular vesiclestetraspanin-based fusion proteins

Identifiers

PMID36579638
PMCPMC9809379
OpenAlexW4313332758

What OpenQuestion holds

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LicenceCC BY
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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.