Sobotta2017 - IL-6-induced JAK1-STAT3-signaling
Ontology highlight
ABSTRACT:
SUBMITTER: 
Marcel Schilling
PROVIDER: MODEL2307050001 | BioModels | 2023-07-05
REPOSITORIES: BioModels
Publications
Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib.
Sobotta Svantje S Raue Andreas A Huang Xiaoyun X Vanlier Joep J Jünger Anja A Bohl Sebastian S Albrecht Ute U Hahnel Maximilian J MJ Wolf Stephanie S Mueller Nikola S NS D'Alessandro Lorenza A LA Mueller-Bohl Stephanie S Boehm Martin E ME Lucarelli Philippe P Bonefas Sandra S Damm Georg G Seehofer Daniel D Lehmann Wolf D WD Rose-John Stefan S van der Hoeven Frank F Gretz Norbert N Theis Fabian J FJ Ehlting Christian C Bode Johannes G JG Timmer Jens J Schilling Marcel M Klingmüller Ursula U
Frontiers in physiology 20171009
IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple pathological conditions. In hepatocytes, IL-6 activates JAK1-STAT3 signaling that induces the negative feedback regulator SOCS3 and expression of APPs. While different inhibitors of IL-6-induced JAK1-STAT3-signaling have been developed, understanding their precise impact on signaling dynamics requ ...[more]
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This model
[BIOMD0000000544]
describes the crosstalk between IFN-gamma and IL-6 induced
signalling; it aims to outline mechanisms and factors that may
control the interaction between both signalling pathways,
discussing a role of heterodimer formation in signalling
dysfunction.
To account for the possibility of different IFNR and gp130
binding sites for STAT1 and STAT3, model 1
[BIOMD0000000543]
assumes that there is no competition between STAT1 and STAT3 for
the receptor complexes (includes two extra reactions).
The reverse of this is true in model 2
[BIOMD0000000544]
where it generally is assumed that there is competition between
STAT1 and STAT3 for the receptor complexes.
This model is described in the article:
Elucidating the crosstalk
mechanism between IFN-gamma and IL-6 via mathematical
modelling.
Qi YF, Huang YX, Wang HY, Zhang Y,
Bao YL, Sun LG, Wu Y, Yu CL, Song ZB, Zheng LH, Sun Y, Wang GN,
Li YX.
BMC Bioinformatics 2013; 14: 41
Abstract:
BACKGROUND: Interferon-gamma (IFN-gamma) and interleukin-6
(IL-6) are multifunctional cytokines that regulate immune
responses, cell proliferation, and tumour development and
progression, which frequently have functionally opposing roles.
The cellular responses to both cytokines are activated via the
Janus kinase/signal transducer and activator of transcription
(JAK/STAT) pathway. During the past 10 years, the crosstalk
mechanism between the IFN-gamma and IL-6 pathways has been
studied widely and several biological hypotheses have been
proposed, but the kinetics and detailed crosstalk mechanism
remain unclear. RESULTS: Using established mathematical models
and new experimental observations of the crosstalk between the
IFN-gamma and IL-6 pathways, we constructed a new crosstalk
model that considers three possible crosstalk levels: (1) the
competition between STAT1 and STAT3 for common receptor docking
sites; (2) the mutual negative regulation between SOCS1 and
SOCS3; and (3) the negative regulatory effects of the formation
of STAT1/3 heterodimers. A number of simulations were tested to
explore the consequences of cross-regulation between the two
pathways. The simulation results agreed well with the
experimental data, thereby demonstrating the effectiveness and
correctness of the model. CONCLUSION: In this study, we
developed a crosstalk model of the IFN-gamma and IL-6 pathways
to theoretically investigate their cross-regulation mechanism.
The simulation experiments showed the importance of the three
crosstalk levels between the two pathways. In particular, the
unbalanced competition between STAT1 and STAT3 for IFNR and
gp130 led to preferential activation of IFN-gamma and IL-6,
while at the same time the formation of STAT1/3 heterodimers
enhanced preferential signal transduction by sequestering a
fraction of the activated STATs. The model provided a good
explanation of the experimental observations and provided
insights that may inform further research to facilitate a
better understanding of the cross-regulation mechanism between
the two pathways.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000544.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
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Project description:Qi2013 - IL-6 and IFN crosstalk model
(non-competitive)
This model
[BIOMD0000000543]
describes the crosstalk between IFN-gamma and IL-6 induced
signalling; it aims to outline mechanisms and factors that may
control the interaction between both signalling pathways,
discussing a role of heterodimer formation in signalling
dysfunction.
To account for the possibility of different IFNR and gp130
binding sites for STAT1 and STAT3, model 1
[BIOMD0000000543]
assumes that there is no competition between STAT1 and STAT3 for
the receptor complexes (includes two extra reactions).
The reverse of this is true in model 2
[BIOMD0000000544]
where it generally is assumed that there is competition between
STAT1 and STAT3 for the receptor complexes.
This model is described in the article:
Elucidating the crosstalk
mechanism between IFN-gamma and IL-6 via mathematical
modelling.
Qi YF, Huang YX, Wang HY, Zhang Y,
Bao YL, Sun LG, Wu Y, Yu CL, Song ZB, Zheng LH, Sun Y, Wang GN,
Li YX.
BMC Bioinformatics 2013; 14: 41
Abstract:
BACKGROUND: Interferon-gamma (IFN-gamma) and interleukin-6
(IL-6) are multifunctional cytokines that regulate immune
responses, cell proliferation, and tumour development and
progression, which frequently have functionally opposing roles.
The cellular responses to both cytokines are activated via the
Janus kinase/signal transducer and activator of transcription
(JAK/STAT) pathway. During the past 10 years, the crosstalk
mechanism between the IFN-gamma and IL-6 pathways has been
studied widely and several biological hypotheses have been
proposed, but the kinetics and detailed crosstalk mechanism
remain unclear. RESULTS: Using established mathematical models
and new experimental observations of the crosstalk between the
IFN-gamma and IL-6 pathways, we constructed a new crosstalk
model that considers three possible crosstalk levels: (1) the
competition between STAT1 and STAT3 for common receptor docking
sites; (2) the mutual negative regulation between SOCS1 and
SOCS3; and (3) the negative regulatory effects of the formation
of STAT1/3 heterodimers. A number of simulations were tested to
explore the consequences of cross-regulation between the two
pathways. The simulation results agreed well with the
experimental data, thereby demonstrating the effectiveness and
correctness of the model. CONCLUSION: In this study, we
developed a crosstalk model of the IFN-gamma and IL-6 pathways
to theoretically investigate their cross-regulation mechanism.
The simulation experiments showed the importance of the three
crosstalk levels between the two pathways. In particular, the
unbalanced competition between STAT1 and STAT3 for IFNR and
gp130 led to preferential activation of IFN-gamma and IL-6,
while at the same time the formation of STAT1/3 heterodimers
enhanced preferential signal transduction by sequestering a
fraction of the activated STATs. The model provided a good
explanation of the experimental observations and provided
insights that may inform further research to facilitate a
better understanding of the cross-regulation mechanism between
the two pathways.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000543.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2014-08-19 | BIOMD0000000543 | BioModels
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