Combined logical and data-driven models for linking signalling pathways to cellular response

Melas, IN; Mitsos, A; Messinis, DE; Weiss, TS; Alexopoulos, LG

dc.contributor.author	Melas, IN	en
dc.contributor.author	Mitsos, A	en
dc.contributor.author	Messinis, DE	en
dc.contributor.author	Weiss, TS	en
dc.contributor.author	Alexopoulos, LG	en
dc.date.accessioned	2014-03-01T01:35:25Z
dc.date.available	2014-03-01T01:35:25Z
dc.date.issued	2011	en
dc.identifier.issn	1752-0509	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/21039
dc.subject	a priori knowledge	en
dc.subject	Cell Growth	en
dc.subject	Differential Gene Expression	en
dc.subject	Hybrid Logic	en
dc.subject	Integer Linear Program	en
dc.subject	Signalling Pathway	en
dc.subject	High Throughput	en
dc.subject	Proof of Principle	en
dc.subject.classification	Mathematical & Computational Biology	en
dc.subject.other	GROWTH-FACTOR RECEPTOR	en
dc.subject.other	TYROSINE KINASE INHIBITOR	en
dc.subject.other	HEPATOCELLULAR-CARCINOMA	en
dc.subject.other	TUMOR-CELLS	en
dc.subject.other	NETWORKS	en
dc.subject.other	TRANSDUCTION	en
dc.subject.other	INFLAMMATION	en
dc.subject.other	CANCER	en
dc.subject.other	HEPATOCYTES	en
dc.subject.other	ACTIVATION	en
dc.title	Combined logical and data-driven models for linking signalling pathways to cellular response	en
heal.type	journalArticle	en
heal.identifier.primary	10.1186/1752-0509-5-107	en
heal.identifier.secondary	http://dx.doi.org/10.1186/1752-0509-5-107	en
heal.identifier.secondary	107	en
heal.language	English	en
heal.publicationDate	2011	en
heal.abstract	Background: Signalling pathways are the cornerstone on understanding cell function and predicting cell behavior. Recently, logical models of canonical pathways have been optimised with high-throughput phosphoproteomic data to construct cell-type specific pathways. However, less is known on how signalling pathways can be linked to a cellular response such as cell growth, death, cytokine secretion, or transcriptional activity.Results: In this work, we measure the signalling activity (phosphorylation levels) and phenotypic behavior (cytokine secretion) of normal and cancer hepatocytes treated with a combination of cytokines and inhibitors. Using the two datasets, we construct ""extended"" pathways that integrate intracellular activity with cellular responses using a hybrid logical/data-driven computational approach. Boolean logic is used whenever a priori knowledge is accessible (i.e., construction of canonical pathways), whereas a data-driven approach is used for linking cellular behavior to signalling activity via non-canonical edges. The extended pathway is subsequently optimised to fit signalling and behavioural data using an Integer Linear Programming formulation. As a result, we are able to construct maps of primary and transformed hepatocytes downstream of 7 receptors that are capable of explaining the secretion of 22 cytokines.Conclusions: We developed a method for constructing extended pathways that start at the receptor level and via a complex intracellular signalling pathway identify those mechanisms that drive cellular behaviour. Our results constitute a proof-of-principle for construction of ""extended pathways"" that are capable of linking pathway activity to diverse responses such as growth, death, differentiation, gene expression, or cytokine secretion. © 2011 Melas et al; licensee BioMed Central Ltd.	en
heal.publisher	BIOMED CENTRAL LTD	en
heal.journalName	BMC Systems Biology	en
dc.identifier.doi	10.1186/1752-0509-5-107	en
dc.identifier.isi	ISI:000293234500001	en
dc.identifier.volume	5	en