Evidence map›Paper›PMID 21537367›Full record

ArticleWorld journal of biological chemistry2010

Anticancer actions of PPARγ ligands: Current state and future perspectives in human lung cancer.

Shou Wei Han, Jesse Roman

Open access · hybridAbstract read
In one paragraph

Article in World journal of biological chemistry, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.1field-weighted citation impact, top 45% 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

5 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
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.

Shou Wei HanShou Wei Han, Jesse Roman, Division of Pulmonary, Critical Care and Sleep Disorders Medicine, Department of Medicine, University of Louisville School of Medicine, Louisville, KY 40202, United States.
Jesse Roman
University of Louisville · US

Funding

Lung extracellular matrix and tumor progressionR01CA116812 · NCI · UNIVERSITY OF LOUISVILLE · PI ROMAN, JESSE · 2008 to 2012
$1.6M
The role of EP4 in fibronectin-induced human lung cancer cell growthK22CA123104 · NCI · UNIVERSITY OF LOUISVILLE · PI HAN, SHOUWEI · 2008 to 2010
$397k
NCI NIH HHS K22 CA123104NCI NIH HHS R01 CA116812
6 · The paper itself

Abstract

Peroxisome proliferator-activated receptors (PPARs) are ligand-dependent nuclear transcription factors and members of the nuclear receptor superfamily. Of the three PPARs identified to date (PPARγ, PPARβ/δ, and PPARα), PPARγ has been studied the most, in part because of the availability of PPARγ agonists (also known as PPARγ ligands) and its significant effects on the management of several human diseases including type 2 diabetes, metabolic syndrome, cardiovascular disease and cancers. PPARγ is expressed in many tumors including lung cancer, and its function has been linked to the process of lung cancer development, progression and metastasis. Studies performed in gynogenic and xenograft models of lung cancer showed decreased tumor growth and metastasis in animals treated with PPARγ ligands. Furthermore, data are emerging from retrospective clinical studies that suggest a protective role for PPARγ ligands on the incidence of lung cancer. This review summarizes the research being conducted in this area and focuses on the mechanisms and potential therapeutic effects of PPARγ ligands as a novel anti-lung cancer treatment strategy.

Indexed as

Gene expression and regulationHuman lung cancerLigandsPeroxisome proliferator-activated receptor γSignaling pathwaysTherapy

Identifiers

PMID21537367
PMCPMC3083946
OpenAlexW2094066333

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.