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Hypoxia-inducible factor (HIF) network: insights from mathematical models

Oxygen is a crucial molecule for cellular function. When oxygen demand exceeds supply, the oxygen sensing pathway centred on the hypoxia inducible factor (HIF) is switched on and promotes adaptation to hypoxia by up-regulating genes involved in angiogenesis, erythropoiesis and glycolysis. The regula...

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Autores principales: Cavadas, Miguel AS, Nguyen, Lan K, Cheong, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3686674/
https://www.ncbi.nlm.nih.gov/pubmed/23758895
http://dx.doi.org/10.1186/1478-811X-11-42
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author Cavadas, Miguel AS
Nguyen, Lan K
Cheong, Alex
author_facet Cavadas, Miguel AS
Nguyen, Lan K
Cheong, Alex
author_sort Cavadas, Miguel AS
collection PubMed
description Oxygen is a crucial molecule for cellular function. When oxygen demand exceeds supply, the oxygen sensing pathway centred on the hypoxia inducible factor (HIF) is switched on and promotes adaptation to hypoxia by up-regulating genes involved in angiogenesis, erythropoiesis and glycolysis. The regulation of HIF is tightly modulated through intricate regulatory mechanisms. Notably, its protein stability is controlled by the oxygen sensing prolyl hydroxylase domain (PHD) enzymes and its transcriptional activity is controlled by the asparaginyl hydroxylase FIH (factor inhibiting HIF-1). To probe the complexity of hypoxia-induced HIF signalling, efforts in mathematical modelling of the pathway have been underway for around a decade. In this paper, we review the existing mathematical models developed to describe and explain specific behaviours of the HIF pathway and how they have contributed new insights into our understanding of the network. Topics for modelling included the switch-like response to decreased oxygen gradient, the role of micro environmental factors, the regulation by FIH and the temporal dynamics of the HIF response. We will also discuss the technical aspects, extent and limitations of these models. Recently, HIF pathway has been implicated in other disease contexts such as hypoxic inflammation and cancer through crosstalking with pathways like NFκB and mTOR. We will examine how future mathematical modelling and simulation of interlinked networks can aid in understanding HIF behaviour in complex pathophysiological situations. Ultimately this would allow the identification of new pharmacological targets in different disease settings.
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spelling pubmed-36866742013-06-20 Hypoxia-inducible factor (HIF) network: insights from mathematical models Cavadas, Miguel AS Nguyen, Lan K Cheong, Alex Cell Commun Signal Review Oxygen is a crucial molecule for cellular function. When oxygen demand exceeds supply, the oxygen sensing pathway centred on the hypoxia inducible factor (HIF) is switched on and promotes adaptation to hypoxia by up-regulating genes involved in angiogenesis, erythropoiesis and glycolysis. The regulation of HIF is tightly modulated through intricate regulatory mechanisms. Notably, its protein stability is controlled by the oxygen sensing prolyl hydroxylase domain (PHD) enzymes and its transcriptional activity is controlled by the asparaginyl hydroxylase FIH (factor inhibiting HIF-1). To probe the complexity of hypoxia-induced HIF signalling, efforts in mathematical modelling of the pathway have been underway for around a decade. In this paper, we review the existing mathematical models developed to describe and explain specific behaviours of the HIF pathway and how they have contributed new insights into our understanding of the network. Topics for modelling included the switch-like response to decreased oxygen gradient, the role of micro environmental factors, the regulation by FIH and the temporal dynamics of the HIF response. We will also discuss the technical aspects, extent and limitations of these models. Recently, HIF pathway has been implicated in other disease contexts such as hypoxic inflammation and cancer through crosstalking with pathways like NFκB and mTOR. We will examine how future mathematical modelling and simulation of interlinked networks can aid in understanding HIF behaviour in complex pathophysiological situations. Ultimately this would allow the identification of new pharmacological targets in different disease settings. BioMed Central 2013-06-10 /pmc/articles/PMC3686674/ /pubmed/23758895 http://dx.doi.org/10.1186/1478-811X-11-42 Text en Copyright © 2013 Cavadas et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Cavadas, Miguel AS
Nguyen, Lan K
Cheong, Alex
Hypoxia-inducible factor (HIF) network: insights from mathematical models
title Hypoxia-inducible factor (HIF) network: insights from mathematical models
title_full Hypoxia-inducible factor (HIF) network: insights from mathematical models
title_fullStr Hypoxia-inducible factor (HIF) network: insights from mathematical models
title_full_unstemmed Hypoxia-inducible factor (HIF) network: insights from mathematical models
title_short Hypoxia-inducible factor (HIF) network: insights from mathematical models
title_sort hypoxia-inducible factor (hif) network: insights from mathematical models
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3686674/
https://www.ncbi.nlm.nih.gov/pubmed/23758895
http://dx.doi.org/10.1186/1478-811X-11-42
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