Evidence map›Paper›PMID 36748374›Full record

ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2022

Role of biomimetic nanomaterials made from glioma cell- derived extracellular vesicles in targeted delivery of STAT3-siRNA.

Dun Hu, Xin Li, Shengdan Nie, Shan Wang

Abstract read
In one paragraph

Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 3D-ASC-Exos as a novel drug carrier for glioma treatment.Frontiers in cell and developmental biology · 2025
    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

4 authors.

Dun HuDepartment of Pharmaceutical Engineering, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083. huduncsu@163.com.
Xin LiDepartment of Pharmaceutical Engineering, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083.
Shengdan NieOffice of Clinical Medicine, Hunan Provincial People's Hospital; First Affiliated Hospital of Hunan Normal University, Changsha 410005, China. nieshengdan@163.com.
Shan WangDepartment of Pharmaceutical Engineering, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083. wangshancsu0717@163.com.

Funding

the National Natural Science Foundation of China 81872919 and 82070857
6 · The paper itself

Abstract

objectivesGlioma is the most common primary intracranial tumor and there is still no ideal treatment at present. Gene therapy, as one of the new methods for treating glioma, has attracted attention in recent years. But its application in treating glioma is very limited due to lack of effective delivery vectors. This study aims to investigate the feasibility of biomimetic nanomaterials made from glioma cells-derived extracellular vesicles (EV) for targeted delivery of signal transducers and activators of transcription 3 (STAT3)-small interfering RNA (siRNA) in treating glioma.

methodsFirst, U251 glioma cells-derived extracellular vessel (EVU251) was extracted by ultra-centrifugal method. Nanoparticle tracking analysis was used to characterize the particle size distribution, the transmission electron microscope was used to analyze the morphology, and Western blotting was used to verify the expression of srface characteristic protein. The homing ability was verified by cell uptake assay after labeling EVU251 with membrane dye kit PKH67; the EVU251 contents were removed by a low permeability method and then EVMU251 was prepared through a microporous membrane. Finally, the biomimetic nanomaterials EVMU251@STAT3-siRNA were prepared by loading STAT3-SiRNA with electro-dyeing method. The real-time quantitative PCR was used to quantify the successful encapsulation of siRNA, and the encapsulation and drug loading rate was calculated; then Cy5-labeled siRNA was used to evaluate the ability of biomimetic nanomaterials (EVMU251@CY5-siRNA) to target U251 cells. Lysosomal escape ability of the biomimetic nanomaterial was evaluated by lysosomal dye lyso-tracker green. At last, the ability of EVMU251@STAT3-siRNA to knock down STAT3 gene and selective killing of U251 cells was detected by cell experiments in vitro.

resultsThe size of EVU251 ranged from 50 nm to 200 nm with a natural disc shape. The expression of extracellular vesicle marker proteins could be detected on the membrane of EVU251. The cell uptake assay demonstrated that it had homing ability to target U251 cells. After EVU251 was prepared as EVMU251@STAT3-siRNA, the particle size was (177.9±5.0) nm, the siRNA loading rate was (33.5±2.2)% and the drug loading rate was (3.24±0.21)%. The biomimetic nanomaterial EVMU251@STAT3-siRNA still had the ability to target U251 cells and successfully deliver siRNA to the cytoplasm without lysosomal degradation. The EVMU251@STAT3-siRNA can effectively knock down the expression of STAT3 gene and produce selective killing ability in U251 cells.

conclusionsThe biomimetic nanomaterials EVMU251@STAT3-siRNA made from glioma U251 cells-derived extracellular vesicles can knock down STAT3 gene of U251 cells and produce selective killing effect, which can provide a new idea for the treatment of glioma.

Indexed as

GliomaNanostructuresBiomimeticsCarbocyaninesCell Line, TumorCell ProliferationHumansRNA, Small InterferingSTAT3 Transcription FactorCarbocyaninescyanine dye 5RNA, Small InterferingSTAT3 protein, humanSTAT3 Transcription Factorextracellular vesiclegene therapygliomanucleic nanocarriersignal transducers and activators of transcription 3small interfering RNAtargeted delivery

Identifiers

PMID36748374
PMCPMC10930272

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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.