Evidence map›Paper›PMID 27966906›Full record

ArticleACS nano2017

Overcoming Tamoxifen Resistance of Human Breast Cancer by Targeted Gene Silencing Using Multifunctional pRNA Nanoparticles.

Yijuan Zhang, Marissa Leonard, Yi Shu, Yongguang Yang, Dan Shu, Peixuan Guo, Xiaoting Zhang

Abstract read
In one paragraph

Article in ACS nano, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed
7.8field-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

69 citing papers in PubMed, 138 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Nanotechnology-based biomedical devices in the cancer diagnostics and therapy.Medical oncology (Northwood, London, England) · 2025
    Review
  6. Review
  7. Article
  8. In VivoPharmaceuticals (Basel, Switzerland) · 2024
    Article
  9. Review
  10. Article
  11. Molecular pharmaceutics · 2024
    Article
  12. Review
  13. Review
  14. Article
  15. Advances of medical nanorobots for future cancer treatments.Journal of hematology & oncology · 2023
    Review
  16. Review
  17. Review
  18. Article
  19. Article
  20. Article

9 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

7 authors at 1 institution in 1 country.

Yijuan Zhang
Marissa Leonard
Yi ShuCollege of Pharmacy, Department of Physiology & Cell Biology, College of Medicine, and Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University , Columbus, Ohio 43210, United States.
Yongguang Yang
Dan ShuCollege of Pharmacy, Department of Physiology & Cell Biology, College of Medicine, and Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University , Columbus, Ohio 43210, United States.
Peixuan GuoCollege of Pharmacy, Department of Physiology & Cell Biology, College of Medicine, and Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University , Columbus, Ohio 43210, United States.ORCID 0000-0001-5706-2833
The Ohio State University · US

Funding

Translational Therapeutics Research Program (TT)P30CA016058 · NCI · OHIO STATE UNIVERSITY · PI WANCAI YANG · 1985 to 2026
$132.3M
Role of MED1 in HER2-mediated tumorigenesisR01CA197865 · NCI · UNIVERSITY OF CINCINNATI · PI Xiaoting Zhang · 2015 to 2026
$3.7M
Cancer specific and organ-avoiding RNA architectures for quantitative imagingR01EB019036 · NIBIB · UNIVERSITY OF KENTUCKY · PI EVERS, BERNARD MARK, GUO, PEIXUAN · 2014 to 2017
$1.3M
NCI NIH HHS P30 CA016058NCI NIH HHS R01 CA197865NIBIB NIH HHS R01 EB019036
6 · The paper itself

Abstract

Most breast cancers express estrogen receptor (ER) α, and the antiestrogen drug tamoxifen has been widely used for their treatment. Unfortunately, up to half of all ERα-positive tumors have intrinsic or acquired endocrine therapy resistance. Our recent studies revealed that the ER coactivator Mediator Subunit 1 (MED1) plays a critical role in tamoxifen resistance through cross-talk with HER2. Herein, we assembled a three-way junction (3-WJ) pRNA-HER2apt-siMED1 nanoparticle to target HER2-overexpressing human breast cancer via an HER2 RNA aptamer to silence MED1 expression. We found that these ultracompact RNA nanoparticles are very stable under RNase A, serum, and 8 M urea conditions. These nanoparticles specifically bound to HER2-overexpressing breast cancer cells, efficiently depleted MED1 expression, and significantly decreased ERα-mediated gene transcription, whereas point mutations of the HER2 RNA aptamer on these nanoparticles abolished such functions. The RNA nanoparticles not only reduced the growth, metastasis, and mammosphere formation of the HER2-overexpressing breast cancer cells but also sensitized them to tamoxifen treatment. These biosafe nanoparticles efficiently targeted and penetrated into HER2-overexpressing tumors after systemic administration in orthotopic xenograft mouse models. In addition to their ability to greatly inhibit tumor growth and metastasis, these nanoparticles also led to a dramatic reduction in the stem cell content of breast tumors when combined with tamoxifen treatment in vivo. Overall, we have generated multifunctional RNA nanoparticles that specifically targeted HER2-overexpressing human breast cancer, silenced MED1, and overcame tamoxifen resistance.

Indexed as

Antineoplastic Agents, HormonalBacteriophage lambdaDrug Resistance, NeoplasmGene SilencingHumansNanoparticlesParticle SizeRNA, ViralSurface PropertiesTamoxifenTumor Cells, CulturedAntineoplastic Agents, HormonalRNA, ViralTamoxifenbreast cancerHER2 RNA aptamerMED1pRNA of phi29 DNA packaging motortamoxifen resistance

Identifiers

PMID27966906
PMCPMC5488869
OpenAlexW2566579262

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.