Evidence map›Paper›PMID 21832255›Full record

ArticleMolecular & cellular proteomics : MCP2011

Signaling network state predicts twist-mediated effects on breast cell migration across diverse growth factor contexts.

Hyung-Do Kim, Aaron S Meyer, Joel P Wagner, Shannon K Alford, Alan Wells, Frank B Gertler, Douglas A Lauffenburger

Open access · hybridAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.5field-weighted citation impact, top 16% 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

20 citing papers in PubMed, 31 citations in OpenAlex.

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  10. An atlas of human kinase regulation.Molecular systems biology · 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

7 authors at 2 institutions in 1 country.

Hyung-Do KimDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge MA 02139, USA.
Aaron S Meyer
Joel P Wagner
Shannon K Alford
Alan Wells
Frank B Gertler
Douglas A Lauffenburger
Massachusetts Institute of Technology · USUniversity of Pittsburgh Medical Center · US

Funding

Tumor Cell Networks CenterU54CA112967 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI LAUFFENBURGER, DOUGLAS A · 2004 to 2015
$26.2M
Spatial Segregation of Cell Functioning During MotilityR01GM069668 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI WELLS, ALAN · 2004 to 2019
$4.7M
Computational Modeling of Cell Migration in 3D MatricesR01GM081336 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI LAUFFENBURGER, DOUGLAS A · 2008 to 2011
$1.1M
Molecular Regulation of Cancer ProgressionI01BX001017 · VA · VETERANS HEALTH ADMINISTRATION · PI WELLS, ALAN · 2012 to 2015
–
BLRD VA I01 BX001017NCI NIH HHS U54 CA112967NCI NIH HHS U54-CA112967NIGMS NIH HHS R01 GM069668NIGMS NIH HHS R01 GM081336NIGMS NIH HHS R01-GM081336
6 · The paper itself

Abstract

Epithelial-mesenchymal transition (EMT), whether in developmental morphogenesis or malignant transformation, prominently involves modified cell motility behavior. Although major advances have transpired in understanding the molecular pathways regulating the process of EMT induction per se by certain environmental stimuli, an important outstanding question is how the activities of signaling pathways governing motility yield the diverse movement behaviors characteristic of pre-induction versus postinduction states across a broad landscape of growth factor contexts. For the particular case of EMT induction in human mammary cells by ectopic expression of the transcription factor Twist, we found the migration responses to a panel of growth factors (EGF, HRG, IGF, HGF) dramatically disparate between confluent pre-Twist epithelial cells and sparsely distributed post-Twist mesenchymal cells-but that a computational model quantitatively integrating multiple key signaling node activities could nonetheless account for this full range of behavior. Moreover, motility in both conditions was successfully predicted a priori for an additional growth factor (PDGF) treatment. Although this signaling network state model could comprehend motility behavior globally, modulation of the network interactions underlying the altered pathway activities was identified by ascertaining differences in quantitative topological influences among the nodes between the two conditions.

Indexed as

Cell MovementSignal TransductionBreastCell LineComputer SimulationEpithelial CellsEpithelial-Mesenchymal TransitionErbB ReceptorsFemaleHumansIntercellular Signaling Peptides and ProteinsIntracellular Signaling Peptides and ProteinsLeast-Squares AnalysisModels, BiologicalMultivariate AnalysisNuclear ProteinsErbB ReceptorsIntercellular Signaling Peptides and ProteinsIntracellular Signaling Peptides and ProteinsNuclear ProteinsTWIST1 protein, humanTwist-Related Protein 1

Identifiers

PMID21832255
PMCPMC3226401
OpenAlexW2121503315

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.