Nguyen2016 - Feedback regulation in cell signalling: Lessons for cancer therapeutics

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Short description
Feedback regulation in cell signalling: Lessons for cancer therapeutics

This model is described in the article:

Nguyen LK, Kholodenko BN.
Semin. Cell Dev. Biol. 2016 Feb; 50: 85-94

Abstract:

The notion of feedback is fundamental for understanding signal transduction networks. Feedback loops attenuate or amplify signals, change the network dynamics and modify the input-output relationships between the signal and the target. Negative feedback provides robustness to noise and adaptation to perturbations, but as a double-edged sword can prevent effective pathway inhibition by a drug. Positive feedback brings about switch-like network responses and can convert analog input signals into digital outputs, triggering cell fate decisions and phenotypic changes. We show how a multitude of protein-protein interactions creates hidden feedback loops in signal transduction cascades. Drug treatments that interfere with feedback regulation can cause unexpected adverse effects. Combinatorial molecular interactions generated by pathway crosstalk and feedback loops often bypass the block caused by targeted therapies against oncogenic mutated kinases. We discuss mechanisms of drug resistance caused by network adaptations and suggest that development of effective drug combinations requires understanding of how feedback loops modulate drug responses.

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Format
SBML (L2V4)
Related Publication
  • Feedback regulation in cell signalling: Lessons for cancer therapeutics.
  • Nguyen LK, Kholodenko BN
  • Seminars in cell & developmental biology , 2/ 2016 , Volume 50 , pages: 85-94
  • Systems Biology Ireland, University College Dublin, Belfield, Dublin 4, Ireland; Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, VIC 3800, Australia. Electronic address: lan.k.nguyen@monash.edu.
  • The notion of feedback is fundamental for understanding signal transduction networks. Feedback loops attenuate or amplify signals, change the network dynamics and modify the input-output relationships between the signal and the target. Negative feedback provides robustness to noise and adaptation to perturbations, but as a double-edged sword can prevent effective pathway inhibition by a drug. Positive feedback brings about switch-like network responses and can convert analog input signals into digital outputs, triggering cell fate decisions and phenotypic changes. We show how a multitude of protein-protein interactions creates hidden feedback loops in signal transduction cascades. Drug treatments that interfere with feedback regulation can cause unexpected adverse effects. Combinatorial molecular interactions generated by pathway crosstalk and feedback loops often bypass the block caused by targeted therapies against oncogenic mutated kinases. We discuss mechanisms of drug resistance caused by network adaptations and suggest that development of effective drug combinations requires understanding of how feedback loops modulate drug responses.
Contributors
Emma Fairbanks

Metadata information

is
BioModels Database MODEL1708250003
BioModels Database BIOMD0000000651
hasTaxon
Taxonomy Homo sapiens
isDescribedBy
Mathematical Modelling Ontology Ordinary differential equation model
PubMed 26481970
hasProperty
NCIt C16212
hasPart
Pathway Ontology PW:0000102
Pathway Ontology PW:0000180
Curation status
Curated
  • Model originally submitted by : Emma Fairbanks
  • Submitted: Aug 25, 2017 10:50:56 AM
  • Last Modified: Jan 29, 2018 9:53:00 AM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Jan 29, 2018 9:53:00 AM
    • Submitted by: Emma Fairbanks
    • With comment: Current version of Nguyen2016 - Feedback regulation in cell signalling: Lessons for cancer therapeutics
  • Version: 1 public model Download this version
    • Submitted on: Aug 25, 2017 10:50:56 AM
    • Submitted by: Emma Fairbanks
    • With comment: Original import of Feedback regulation in cell signalling: Lessons for cancer therapeutics
Curator's comment:
(added: 24 Jan 2018, 14:05:29, updated: 24 Jan 2018, 14:05:29)
?Figure 4e of the reference publication has been reproduced. The model as such reproduces the plots corresponding to the no MEK inhibition (MEKI=0) condition. To obtain simulations for MEK inhibition set MEKI=300 or 500. The simulations where performed using Copasi 4.19 (Build 140) and the plots were obtained using Matlab R2014b.