Evidence map›Paper›PMID 21943356›Full record

ArticleThe Biochemical journal2012

Data-driven modelling of receptor tyrosine kinase signalling networks quantifies receptor-specific potencies of PI3K- and Ras-dependent ERK activation.

Murat Cirit, Jason M Haugh

Open access · greenAbstract read
In one paragraph

Article in The Biochemical journal, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

15 citing papers in PubMed, 24 citations in OpenAlex.

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  9. Development of a tandem affinity phosphoproteomic method with motif selectivity and its application in analysis of signal transduction networks.Journal of chromatography. B, Analytical technologies in the biomedical and life sciences · 2015
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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

2 authors at 1 institution in 1 country.

Murat CiritDepartment of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695-7905, USA.
Jason M Haugh
North Carolina State University · US

Funding

Dynamic Regulation of Growth Factor Signaling NetworksR01GM088987 · NIGMS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI HAUGH, JASON M. · 2010 to 2013
$1.1M
NIGMS NIH HHS R01 GM088987
6 · The paper itself

Abstract

Signal transduction networks in mammalian cells, comprising a limited set of interacting biochemical pathways, are accessed by various growth factor and cytokine receptors to elicit distinct cell responses. This raises the question as to how specificity of the stimulus-response relationship is encoded at the molecular level. It has been proposed that specificity arises not only from the activation of unique signalling pathways, but also from quantitative differences in the activation and regulation of shared receptor-proximal signalling proteins. To address such hypotheses, data sets with greater precision and coverage of experimental conditions will need to be acquired, and rigorous frameworks that codify and parameterize the inherently non-linear relationships among signalling activities will need to be developed. In the present study we apply a systematic approach combining quantitative measurements and mathematical modelling to compare the signalling networks accessed by FGF (fibroblast growth factor) and PDGF (platelet-derived growth factor) receptors in mouse fibroblasts, in which the ERK (extracellular-signal-regulated kinase) cascade is activated by Ras- and PI3K (phosphoinositide 3-kinase)-dependent pathways. We show that, whereas the FGF stimulation of PI3K signalling is relatively weak, this deficiency is compensated for by a more potent Ras-dependent activation of ERK. Thus, as the modelling would predict, the ERK pathway is activated to a greater extent in cells co-stimulated with FGF and PDGF, relative to the saturated levels achieved with either ligand alone. It is envisaged that similar approaches will prove valuable in the elucidation of quantitative differences among other closely related receptor signalling networks.

Indexed as

AnimalsBecaplerminComputer SimulationExtracellular Signal-Regulated MAP KinasesFibroblast Growth Factor 2FibroblastsGene Expression Regulation, EnzymologicHumansKineticsMiceModels, BiologicalNIH 3T3 CellsPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-sisReceptor Protein-Tyrosine KinasesReceptors, Fibroblast Growth FactorBecaplerminExtracellular Signal-Regulated MAP KinasesFibroblast Growth Factor 2Phosphatidylinositol 3-KinasesProto-Oncogene Proteins c-sisReceptor Protein-Tyrosine KinasesReceptors, Fibroblast Growth Factor

Identifiers

PMID21943356
PMCPMC3687362
OpenAlexW2108970605

What OpenQuestion holds

Textmetadata
LicenceTDM
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.