Evidence map›Paper›PMID 25995995›Full record

ArticleRNA & disease (Houston, Tex.)

The regulation of the p53/MDM2 feedback loop by microRNAs.

Cen Zhang, Juan Liu, Xiaolong Wang, Zhaohui Feng

Open access · diamondAbstract read
In one paragraph

Article in RNA & disease (Houston, Tex.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 23% 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

9 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. 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 at 2 institutions in 1 country.

Cen ZhangDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers, State University of New Jersey, New Brunswick, NJ 08903, USA.
Juan LiuDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers, State University of New Jersey, New Brunswick, NJ 08903, USA.
Xiaolong WangDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers, State University of New Jersey, New Brunswick, NJ 08903, USA.
Zhaohui FengDepartment of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers, State University of New Jersey, New Brunswick, NJ 08903, USA.
Rutgers Cancer Institute of New JerseyRutgers, The State University of New Jersey · US

Funding

The role of glutaminase 2, a novel p53 target gene in metabolism, in liver cancerR01CA143204 · NCI · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI FENG, ZHAOHUI · 2010 to 2014
$1.6M
NCI NIH HHS R01 CA143204
6 · The paper itself

Abstract

Tumor suppressor p53 and its signaling pathway play a central role in tumor prevention. The E3 ubiquitin ligase MDM2, which is a direct p53 transcriptional target and also the most critical negative regulator of p53, forms an autoregulatory negative feedback loop with p53 in the cell to tightly regulate the levels and activity of p53. MicroRNAs (miRNAs) are endogenously expressed small non-coding RNAs that play a critical role in the post-translational regulation of gene expression. Recent studies have revealed that miRNAs directly regulate the levels of p53 or MDM2 to modulate the p53 function in tumor suppression. Recently, we identified miR-339-5p as a new miRNA that directly represses MDM2 to activate p53 and enhance p53 function in tumor suppression. Thus, miRNAs have become a new but important component of the p53 signaling pathway through regulating the p53/MDM2 feedback loop.

Indexed as

MDM2microRNAp53tumor

Identifiers

PMID25995995
PMCPMC4435570
OpenAlexW1481278115

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.