Evidence map›Paper›PMID 27043642›Full record

ReviewJournal of clinical medicine2016

Signal Transduction Pathways of EMT Induced by TGF-β, SHH, and WNT and Their Crosstalks.

Jingyu Zhang, Xiao-Jun Tian, Jianhua Xing

Open access · goldAbstract readReview
In one paragraph

Review in Journal of clinical medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 184 papers.

0numbers the graph read from it
0cells of the map it votes in
184citing papers in PubMed
22.1field-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

184 citing papers in PubMed, 313 citations in OpenAlex.

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  11. Super-enhancer profiling reveals ThPOK/ZBTB7B, a CD4Cellular and molecular life sciences : CMLS · 2025
    Article
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  16. Recent Advances in the Application of Cucurbitacin B as an Anticancer Agent.International journal of molecular sciences · 2025
    Review
  17. Review
  18. Article
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  20. Article

124 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

3 authors at 1 institution in 1 country.

Jingyu ZhangDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA. zhangjy7@pitt.edu.
Xiao-Jun TianDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA. xjtian@pitt.edu.
Jianhua XingDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA. xing1@pitt.edu.
University of Pittsburgh · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial-to-mesenchymal transition (EMT) is a key step in development, wound healing, and cancer development. It involves cooperation of signaling pathways, such as transformation growth factor-β (TGF-β), Sonic Hedgehog (SHH), and WNT pathways. These signaling pathways crosstalk to each other and converge to key transcription factors (e.g., SNAIL1) to initialize and maintain the process of EMT. The functional roles of multi-signaling pathway crosstalks in EMT are sophisticated and, thus, remain to be explored. In this review, we focused on three major signal transduction pathways that promote or regulate EMT in carcinoma. We discussed the network structures, and provided a brief overview of the current therapy strategies and drug development targeted to these three signal transduction pathways. Finally, we highlighted systems biology approaches that can accelerate the process of deconstructing complex networks and drug discovery.

Indexed as

EMTmodelingSHHsignaling transduction pathwaysTGF-βWNT

Identifiers

PMID27043642
PMCPMC4850464
OpenAlexW2304542741

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.