Evidence map›Paper›PMID 40231694›Full record

ReviewNanomedicine (London, England)2025

MicroRNA-targeted nanoparticle delivery systems for cancer therapy: current status and future prospects.

Yang Lou, Yutian Wang, Juan Lu, Xi Chen

Abstract readReview
In one paragraph

Review in Nanomedicine (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. Review
  10. Review
  11. Review
  12. Review
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.

Yang LouInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.ORCID 0000-0001-9088-7984
Yutian WangInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Juan LuInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Xi ChenInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, the regulatory effects of microRNAs (miRNAs) on gene expression have been exploited for applications in the diagnosis and treatment of cancer, neurological diseases, and cardiovascular diseases. However, the susceptibility of miRNAs to degradation during somatic circulation and the challenges associated with their delivery to target tissues and cells have limited the clinical application of miRNAs. For application in tumor therapy, it is essential for miRNAs to specifically target cancer cells. Therefore, various novel miRNA delivery systems that protect miRNA against the activity of serum nuclease and deliver miRNA to target cells have been developed and optimized. This review introduces the passive and active targeting strategies of nanoparticles, summarizes the recent progress of miRNA nanocarriers with tumor-targeting ability, and discusses various nanoparticle delivery systems and their antitumor applications. Additionally, this review focuses on the translational challenges and potential strategies for advancing miRNA-based therapies into the clinic.

Indexed as

Drug Delivery SystemsMicroRNAsNanoparticle Drug Delivery SystemNanoparticlesNeoplasmsAnimalsHumansMicroRNAsNanoparticle Drug Delivery SystemcancermicroRNAmicroRNA deliverynanoparticlestherapy

Identifiers

PMID40231694
PMCPMC12068351

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.