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

Hdl Handle:
http://hdl.handle.net/10147/294602
Title:
Hypoxia-inducible factor (HIF) network: insights from mathematical models
Authors:
Cavadas, Miguel AS; Nguyen, Lan K; Cheong, Alex
Citation:
Cell Communication and Signaling. 2013 Jun 10;11(1):42
Issue Date:
10-Jun-2013
URI:
http://dx.doi.org/10.1186/1478-811X-11-42; http://hdl.handle.net/10147/294602
Abstract:
Abstract 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.
Item Type:
Journal Article

Full metadata record

DC FieldValue Language
dc.contributor.authorCavadas, Miguel AS-
dc.contributor.authorNguyen, Lan K-
dc.contributor.authorCheong, Alex-
dc.date.accessioned2013-06-26T09:08:53Z-
dc.date.available2013-06-26T09:08:53Z-
dc.date.issued2013-06-10-
dc.identifier.citationCell Communication and Signaling. 2013 Jun 10;11(1):42-
dc.identifier.urihttp://dx.doi.org/10.1186/1478-811X-11-42-
dc.identifier.urihttp://hdl.handle.net/10147/294602-
dc.description.abstractAbstract 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.-
dc.titleHypoxia-inducible factor (HIF) network: insights from mathematical models-
dc.typeJournal Article-
dc.language.rfc3066en-
dc.rights.holderMiguel AS Cavadas et al.; licensee BioMed Central Ltd.-
dc.description.statusPeer Reviewed-
dc.date.updated2013-06-19T15:05:22Z-
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