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.

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.

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, Rahuman Sheriff, administrator

Metadata information

is
BioModels Database MODEL1708250003
BioModels Database BIOMD0000000651
isDescribedBy
PubMed 26481970
hasTaxon
Taxonomy Homo sapiens
hasProperty
Mathematical Modelling Ontology Ordinary differential equation model
NCIt C16212
Curation status
Curated
Name Description Size Actions

Model files

BIOMD0000000651_url.xml SBML L2V4 representation of Nguyen2016 - Feedback regulation in cell signalling: Lessons for cancer therapeutics 127.54 KB Preview | Download

Additional files

BIOMD0000000651.cps COPASI file with annotations 142.19 KB Preview | Download
BIOMD0000000651-biopax3.owl Auto-generated BioPAX (Level 3) 45.30 KB Preview | Download
BIOMD0000000651.svg Auto-generated Reaction graph (SVG) 52.55 KB Preview | Download
BIOMD0000000651.png Auto-generated Reaction graph (PNG) 121.60 KB Preview | Download
BIOMD0000000651_urn.xml Auto-generated SBML file with URNs 97.14 KB Preview | Download
BIOMD0000000651.sci Auto-generated Scilab file 154.00 bytes Preview | Download
BIOMD0000000651.sedml ?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). 5.22 KB Preview | Download
BIOMD0000000651.xpp Auto-generated XPP file 10.78 KB Preview | Download
BIOMD0000000651.vcml Auto-generated VCML file 133.51 KB Preview | Download
BIOMD0000000651.m Auto-generated Octave file 13.96 KB Preview | Download
BIOMD0000000651-biopax2.owl Auto-generated BioPAX (Level 2) 28.09 KB Preview | Download

  • Model originally submitted by : Emma Fairbanks
  • Submitted: 25-Aug-2017 10:50:56
  • Last Modified: 21-Mar-2019 12:52:15
Revisions
  • Version: 4 public model Download this version
    • Submitted on: 21-Mar-2019 12:52:15
    • Submitted by: Rahuman Sheriff
    • With comment: MAMO term qualifier updated from isDescribedBy to hasProperty
  • Version: 3 public model Download this version
    • Submitted on: 21-Dec-2018 18:26:38
    • Submitted by: administrator
    • With comment: Include the additional files provided by the submitter in the original submission: BIOMD0000000651.sedml, BIOMD0000000651.cps
  • Version: 2 public model Download this version
    • Submitted on: 29-Jan-2018 09:53:00
    • 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: 25-Aug-2017 10:50:56
    • 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.