Evidence map›Paper›PMID 16734720›Full record

ReviewCancer science2006

Signal transduction of inflammatory cytokines and tumor development.

Akihiko Yoshimura

Open access · bronzeAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Cancer science, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 129 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
129citing papers in PubMed, 3 pooled it
10.6field-weighted citation impact, top 1% 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

129 citing papers in PubMed, 3 syntheses or guidelines pooled it, 317 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
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  5. Review
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69 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

1 author at 1 institution in 1 country.

Akihiko YoshimuraDivision of Molecular and Cellular Immunology, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashiku, Fukuoka 812-8582, Japan. yakihiko@bioreg.kyushu-u.ac.jp
Kyushu University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It has been estimated that >20% of all malignancies are initiated or exacerbated by inflammation. Until recently, the molecular basis of this process has not been clarified. However, recent studies have uncovered the molecular mechanism of intracellular signaling pathways of inflammatory cytokines such as tumor necrosis factor (TNF)-alpha, interferon (IFN)-gamma and interleukin (IL)-6. Three major transcription factors including NF-kappaB, STAT1 and STAT3 have been shown to play major roles in transmitting inflammatory cytokine signals to the nucleus. One function of NF-kappaB and STAT3 in tumor cells is the promotion of cell growth and cell survival through the induction of target genes, whose products promote cell division and inhibit apoptosis. In addition, NF-kappaB and STAT1 are important transcription factors that induce inflammatory mediators from inflammatory cells, especially macrophages, while STAT3 often antagonizes this process. STAT1 is generally believed to be an anti-oncogene because it promotes apoptosis through p53, but it could promote inflammation-mediated tumor development by enhancing tissue injury, remodeling, fibrosis and inflammation. Hence, the inhibition of NF-kappaB and STATs offers a strategy for treatment of a variety of malignancies and can convert inflammation-induced tumor growth into inflammation-induced tumor regression.

Indexed as

AnimalsCell Transformation, NeoplasticCytokinesHumansInflammationMacrophagesSignal TransductionCytokines

Identifiers

PMID16734720
PMCPMC11159428
OpenAlexW2130156594

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.