Evidence map›Paper›PMID 19800114›Full record

ArticleBiomaterials2010

The use of nanoparticle-mediated targeted gene silencing and drug delivery to overcome tumor drug resistance.

Yogesh B Patil, Suresh K Swaminathan, Tanmoy Sadhukha, Linan Ma, Jayanth Panyam

Abstract read
In one paragraph

Article in Biomaterials, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers.

0numbers the graph read from it
0cells of the map it votes in
92citing papers in PubMed
8.1field-weighted citation impact, top 2% 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

92 citing papers in PubMed, 301 citations in OpenAlex.

  1. Article
  2. Review
  3. The landscape of nanoparticle-based siRNA delivery and therapeutic development.Molecular therapy : the journal of the American Society of Gene Therapy · 2024
    Review
  4. Recent Advances in Targeted Therapies for Infantile Hemangiomas.International journal of nanomedicine · 2024
    Review
  5. Article
  6. Nanomedicine in cancer therapy.Signal transduction and targeted therapy · 2023
    Review
  7. Review
  8. Article
  9. Article
  10. Review
  11. Engineering poly- and micelleplexes for nucleic acid delivery - A reflection on their endosomal escape.Journal of controlled release : official journal of the Controlled Release Society · 2023
    Review
  12. Review
  13. Review
  14. Review
  15. Non-viral vectors for RNA delivery.Journal of controlled release : official journal of the Controlled Release Society · 2022
    Review
  16. Article
  17. Polymeric nanoparticles-Promising carriers for cancer therapy.Frontiers in bioengineering and biotechnology · 2022
    Review
  18. Review
  19. Review
  20. Review

32 more citing papers are in PubMed but not listed here.

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

5 authors at 3 institutions in 1 country.

Yogesh B PatilDepartment of Pharmaceutical Sciences, Eugene Applebaum College of Pharmacy and Health Sciences, Wayne State University, Detroit, MI 48201, USA.
Suresh K Swaminathan
Tanmoy Sadhukha
Linan Ma
Jayanth Panyam
University of Minnesota · USEugene Applebaum College of Pharmacy and Health Sciences · USMasonic Cancer Center

Funding

DUAL-AGENT NANOPARTICLES TO OVERCOME DRUG RESISTANCER21CA116641 · NCI · UNIVERSITY OF MINNESOTA · PI PANYAM, JAYANTH · 2007 to 2008
$299k
NCI NIH HHS 7R21CA116641-02NCI NIH HHS R21 CA116641
6 · The paper itself

Abstract

Overexpression of drug efflux transporters such as P-glycoprotein (P-gp) enables cancer cells to develop resistance to multiple anticancer drugs. Functional inhibitors of P-gp have shown promising efficacy in early clinical trials, but their long-term safety is yet to be established. A novel approach to overcome drug resistance is to use siRNA-mediated RNA interference to silence the expression of the efflux transporter. Because P-gp plays an important role in the physiological regulation of endogenous and xenobiotic compounds in the body, it is important to deliver P-gp targeted siRNA and anticancer drug specifically to tumor cells. Further, for optimal synergy, both the drug and siRNA may need to be temporally colocalized in the tumor cells. In the current study, we investigated the effectiveness of simultaneous and targeted delivery of anticancer drug, paclitaxel, along with P-gp targeted siRNA, using poly(D,L-lactide-co-glycolide) nanoparticles to overcome tumor drug resistance. Nanoparticles were surface functionalized with biotin for active tumor targeting. Dual agent nanoparticles encapsulating the combination of paclitaxel and P-gp targeted siRNA showed significantly higher cytotoxicity in vitro than nanoparticles loaded with paclitaxel alone. Enhanced therapeutic efficacy of dual agent nanoparticles could be correlated with effective silencing of the MDR1 gene that encodes for P-gp and with increased accumulation of paclitaxel in drug-resistant tumor cells. In vivo studies in a mouse model of drug-resistant tumor demonstrated significantly greater inhibition of tumor growth following treatment with biotin-functionalized nanoparticles encapsulating both paclitaxel and P-gp targeted siRNA at a paclitaxel dose that was ineffective in the absence of gene silencing. These results suggest that that the combination of P-gp gene silencing and cytotoxic drug delivery using targeted nanoparticles can overcome tumor drug resistance.

Indexed as

Drug Resistance, NeoplasmGene SilencingAnimalsATP Binding Cassette Transporter, Subfamily B, Member 1BiotinCell DeathCell Line, TumorDrug Delivery SystemsGene Expression Regulation, NeoplasticHumansMiceNanoparticlesPaclitaxelParticle SizeRNA, Small InterferingSurface PropertiesATP Binding Cassette Transporter, Subfamily B, Member 1BiotinPaclitaxelRNA, Small Interfering

Identifiers

PMID19800114
PMCPMC2783414
OpenAlexW2013270956

What OpenQuestion holds

Textmetadata
LicenceTDM
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.