Evidence map›Paper›PMID 25862520›Full record

ArticleCellular signalling2015

Mixed-effects model of epithelial-mesenchymal transition reveals rewiring of signaling networks.

Poonam Desai, Jun Yang, Bing Tian, Hong Sun, Mridul Kalita, Hyunsu Ju, Adriana Paulucci-Holthauzen, Yingxin Zhao, Allan R Brasier, Rovshan G Sadygov

Abstract read
In one paragraph

Article in Cellular signalling, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

14 citing papers in PubMed, 27 citations in OpenAlex.

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  14. Computational modeling of cardiac fibroblasts and fibrosis.Journal of molecular and cellular cardiology · 2016
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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

10 authors at 1 institution in 1 country.

Poonam DesaiDepartment of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, TX 77555, United States.
Jun YangDepartment of Internal Medicine, University of Texas Medical Branch, Galveston, TX 77555, United States.
Bing TianDepartment of Internal Medicine, University of Texas Medical Branch, Galveston, TX 77555, United States; Sealy Center for Molecular Medicine, University of Texas Medical Branch, Galveston, TX 77555, United States.
Hong SunDepartment of Internal Medicine, University of Texas Medical Branch, Galveston, TX 77555, United States.
Mridul KalitaSealy Center for Molecular Medicine, University of Texas Medical Branch, Galveston, TX 77555, United States.
Hyunsu JuDepartment of Internal Medicine, University of Texas Medical Branch, Galveston, TX 77555, United States; Institute for Translational Sciences, University of Texas Medical Branch, Galveston, TX 77555, United States; Department of Preventive Medicine and Community Health, University of Texas Medical Branch, Galveston, TX 77555, United States.
Adriana Paulucci-HolthauzenOptical Microscopy Core, University of Texas Medical Branch, Galveston, TX 77555, United States.
Yingxin ZhaoDepartment of Internal Medicine, University of Texas Medical Branch, Galveston, TX 77555, United States; Sealy Center for Molecular Medicine, University of Texas Medical Branch, Galveston, TX 77555, United States; Institute for Translational Sciences, University of Texas Medical Branch, Galveston, TX 77555, United States.
Allan R BrasierDepartment of Internal Medicine, University of Texas Medical Branch, Galveston, TX 77555, United States; Sealy Center for Molecular Medicine, University of Texas Medical Branch, Galveston, TX 77555, United States; Institute for Translational Sciences, University of Texas Medical Branch, Galveston, TX 77555, United States.
Rovshan G SadygovDepartment of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, TX 77555, United States; Sealy Center for Molecular Medicine, University of Texas Medical Branch, Galveston, TX 77555, United States. Electronic address: rovshan.sadygov@utmb.edu.
The University of Texas Medical Branch at Galveston · US

Funding

Synthetic Organic Chemistry CoreP30ES006676 · NIEHS · UNIVERSITY OF TEXAS MEDICAL BR GALVESTON · PI ELFERINK, CORNELIS JOHAN · 1995 to 2017
$21.7M
UTMB Clinical and Translational Science AwardUL1TR000071 · NCATS · UNIVERSITY OF TEXAS MED BR GALVESTON · PI BRASIER, ALLAN R. · 2012 to 2014
$14.4M
Novel computational methods for in vivo proteome dynamics estimation using heavy water metabolic labeling and LC-MSR01GM112044 · NIGMS · UNIVERSITY OF TEXAS MED BR GALVESTON · PI SADYGOV, ROVSHAN G · 2015 to 2023
$2.7M
NCATS NIH HHS UL1 TR000071NCATS NIH HHS UL1TR000071NHLBI NIH HHS HHSN268201000037CNIAID NIH HHS HHSN272200800048CNIEHS NIH HHS P30 ES006676NIGMS NIH HHS R01 GM112044NIGMS NIH HHS R01GM112044PHS HHS HHSN268201000037CPHS HHS HHSN272200800048C
6 · The paper itself

Abstract

The type II epithelial-mesenchymal transition (EMT) produces airway fibrosis and remodeling, contributing to the severity of asthma and chronic obstructive pulmonary disease. While numerous studies have been done on the mechanisms of the transition itself, few studies have investigated the system effects of EMT on signaling networks. Here, we use mixed effects modeling to develop a computational model of phospho-protein signaling data that compares human small airway epithelial cells (hSAECs) with their EMT-transformed counterparts across a series of perturbations with 8 ligands and 5 inhibitors, revealing previously uncharacterized changes in signaling in the EMT state. Strong couplings between menadione, TNFα and TGFβ and their known phospho-substrates were revealed after mixed effects modeling. Interestingly, the overall phospho-protein response was attenuated in EMT, with loss of Mena and TNFα coupling to heat shock protein (HSP)-27. These differences persisted after correction for EMT-induced changes in phospho-protein substrate abundance. Construction of network topology maps showed significant changes between the two cellular states, including a linkage between glycogen synthase kinase (GSK)-3α and small body size/mothers against decapentaplegic (SMAD)2. The model also predicted a loss of p38 mitogen activated protein kinase (p38MAPK)-independent HSP27 signaling, which we experimentally validated. We further characterized the relationship between HSP27 and signal transducers and activators of transcription (STAT)3 signaling, and determined that loss of HSP27 following EMT is only partially responsible for the downregulation of STAT3. These rewired connections represent therapeutic targets that could potentially reverse EMT and restore a normal phenotype to the respiratory mucosa.

Indexed as

Epithelial-Mesenchymal TransitionModels, MolecularSignal TransductionCell LineEpithelial CellsHSP27 Heat-Shock ProteinsHumansMicroscopy, Immunoelectronp38 Mitogen-Activated Protein KinasesPhosphorylationSTAT3 Transcription FactorTransforming Growth Factor alphaTransforming Growth Factor betaHSP27 Heat-Shock Proteinsp38 Mitogen-Activated Protein KinasesSTAT3 Transcription FactorTransforming Growth Factor alphaTransforming Growth Factor betaCellular signalingCorrelative networksEMTMixed-effects modeling

Identifiers

PMID25862520
PMCPMC4437893
OpenAlexW2020185026

What OpenQuestion holds

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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.