Evidence map›Paper›PMID 23443091›Full record

ArticleInternational journal of molecular sciences2012

RORα, a potential tumor suppressor and therapeutic target of breast cancer.

Jun Du, Ren Xu

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 29% 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 100 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. The Circadian Modulators as Molecular Targets in Cancer-A Review.International journal of molecular sciences · 2025
    Review
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  7. Melatonin Receptor Expression in Primary Uveal Melanoma.International journal of molecular sciences · 2024
    Article
  8. Article
  9. Article
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  19. Review
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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

2 authors at 1 institution in 1 country.

Jun DuMarkey Cancer Center, University of Kentucky, Lexington, KY 40536, USA. ren.xu2010@uky.edu.
Ren Xu
University of Kentucky · US

Funding

Supporting New Faculty Recruitment Through Biomedical Research Core CenterP30CA147886 · NCI · UNIVERSITY OF KENTUCKY · PI EVERS, BERNARD MARK · 2009 to 2010
$1.4M
NCI NIH HHS P30 CA147886
6 · The paper itself

Abstract

The function of the nuclear receptor (NR) in breast cancer progression has been investigated for decades. The majority of the nuclear receptors have well characterized natural ligands, but a few of them are orphan receptors for which no ligand has been identified. RORα, one member of the retinoid orphan nuclear receptor (ROR) subfamily of orphan receptors, regulates various cellular and pathological activities. RORα is commonly down-regulated and/or hypoactivated in breast cancer compared to normal mammary tissue. Expression of RORα suppresses malignant phenotypes in breast cancer cells, in vitro and in vivo. Activity of RORα can be categorized into the canonical and non-canonical nuclear receptor pathways, which in turn regulate various breast cancer cellular function, including cell proliferation, apoptosis and invasion. This information suggests that RORα is a potent tumor suppressor and a potential therapeutic target for breast cancer.

Indexed as

ApoptosisCell ProliferationBreast NeoplasmsFemaleHumansNeoplasm InvasivenessNuclear Receptor Subfamily 1, Group F, Member 1Tumor Suppressor ProteinsNuclear Receptor Subfamily 1, Group F, Member 1RORA protein, humanTumor Suppressor Proteins

Identifiers

PMID23443091
PMCPMC3546659
OpenAlexW2041004059

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.