PMID- 21943356
OWN - NLM
STAT- MEDLINE
DCOM- 20120216
LR  - 20211020
IS  - 1470-8728 (Electronic)
IS  - 0264-6021 (Print)
IS  - 0264-6021 (Linking)
VI  - 441
IP  - 1
DP  - 2012 Jan 1
TI  - Data-driven modelling of receptor tyrosine kinase signalling networks quantifies 
      receptor-specific potencies of PI3K- and Ras-dependent ERK activation.
PG  - 77-85
LID - 10.1042/BJ20110833 [doi]
AB  - 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.
FAU - Cirit, Murat
AU  - Cirit M
AD  - Department of Chemical and Biomolecular Engineering, North Carolina State 
      University, Raleigh, NC 27695-7905, USA.
FAU - Haugh, Jason M
AU  - Haugh JM
LA  - eng
GR  - R01 GM088987/GM/NIGMS NIH HHS/United States
GR  - R01 GM088987-02/GM/NIGMS NIH HHS/United States
PT  - Journal Article
PL  - England
TA  - Biochem J
JT  - The Biochemical journal
JID - 2984726R
RN  - 0 (Proto-Oncogene Proteins c-sis)
RN  - 0 (Receptors, Fibroblast Growth Factor)
RN  - 103107-01-3 (Fibroblast Growth Factor 2)
RN  - 1B56C968OA (Becaplermin)
RN  - EC 2.7.1.- (Phosphatidylinositol 3-Kinases)
RN  - EC 2.7.10.1 (Receptor Protein-Tyrosine Kinases)
RN  - EC 2.7.11.24 (Extracellular Signal-Regulated MAP Kinases)
SB  - IM
MH  - Animals
MH  - Becaplermin
MH  - Computer Simulation
MH  - Extracellular Signal-Regulated MAP Kinases/genetics/*metabolism
MH  - Fibroblast Growth Factor 2/genetics/metabolism
MH  - Fibroblasts/metabolism
MH  - Gene Expression Regulation, Enzymologic
MH  - Humans
MH  - Kinetics
MH  - Mice
MH  - Models, Biological
MH  - NIH 3T3 Cells
MH  - Phosphatidylinositol 3-Kinases/genetics/*metabolism
MH  - Proto-Oncogene Proteins c-sis/genetics/metabolism
MH  - Receptor Protein-Tyrosine Kinases/genetics/*metabolism
MH  - Receptors, Fibroblast Growth Factor/genetics/*metabolism
MH  - Signal Transduction
PMC - PMC3687362
MID - NIHMS346075
EDAT- 2011/09/29 06:00
MHDA- 2012/02/18 06:00
PMCR- 2013/06/20
CRDT- 2011/09/28 06:00
PHST- 2011/09/28 06:00 [entrez]
PHST- 2011/09/29 06:00 [pubmed]
PHST- 2012/02/18 06:00 [medline]
PHST- 2013/06/20 00:00 [pmc-release]
AID - BJ20110833 [pii]
AID - 10.1042/BJ20110833 [doi]
PST - ppublish
SO  - Biochem J. 2012 Jan 1;441(1):77-85. doi: 10.1042/BJ20110833.