An advanced discrete state-discrete event multiscale simulation model of the response of a solid tumor to chemotherapy: Mimicking a clinical study

Stamatakos, GS; Kolokotroni, EA; Dionysiou, DD; Georgiadi, E; Desmedt, C

dc.contributor.author	Stamatakos, GS	en
dc.contributor.author	Kolokotroni, EA	en
dc.contributor.author	Dionysiou, DD	en
dc.contributor.author	Georgiadi, E	en
dc.contributor.author	Desmedt, C	en
dc.date.accessioned	2014-03-01T01:32:37Z
dc.date.available	2014-03-01T01:32:37Z
dc.date.issued	2010	en
dc.identifier.issn	0022-5193	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20198
dc.subject	Breast cancer	en
dc.subject	Cancer modeling	en
dc.subject	Chemotherapy	en
dc.subject	In silico oncology	en
dc.subject	Simulation	en
dc.subject.classification	Biology	en
dc.subject.classification	Mathematical & Computational Biology	en
dc.subject.other	epirubicin	en
dc.subject.other	cancer	en
dc.subject.other	chemotherapy	en
dc.subject.other	histology	en
dc.subject.other	optimization	en
dc.subject.other	sensitivity analysis	en
dc.subject.other	simulation	en
dc.subject.other	tumor	en
dc.subject.other	article	en
dc.subject.other	breast tumor	en
dc.subject.other	cancer chemotherapy	en
dc.subject.other	cancer model	en
dc.subject.other	cell kinetics	en
dc.subject.other	cell proliferation	en
dc.subject.other	clinical study	en
dc.subject.other	computer model	en
dc.subject.other	drug response	en
dc.subject.other	pharmacodynamics	en
dc.subject.other	priority journal	en
dc.subject.other	sensitivity analysis	en
dc.subject.other	stem cell	en
dc.subject.other	tumor growth	en
dc.subject.other	tumor volume	en
dc.subject.other	Algorithms	en
dc.subject.other	Antigens, Neoplasm	en
dc.subject.other	Apoptosis	en
dc.subject.other	Breast Neoplasms	en
dc.subject.other	Cell Cycle	en
dc.subject.other	Cell Proliferation	en
dc.subject.other	Clinical Trials as Topic	en
dc.subject.other	Computer Simulation	en
dc.subject.other	DNA Topoisomerases, Type II	en
dc.subject.other	DNA-Binding Proteins	en
dc.subject.other	Epirubicin	en
dc.subject.other	Female	en
dc.subject.other	Gene Expression	en
dc.subject.other	Humans	en
dc.subject.other	Individualized Medicine	en
dc.subject.other	Models, Biological	en
dc.subject.other	Necrosis	en
dc.subject.other	Neoplasms	en
dc.subject.other	Neoplastic Stem Cells	en
dc.subject.other	Software Design	en
dc.subject.other	Treatment Outcome	en
dc.title	An advanced discrete state-discrete event multiscale simulation model of the response of a solid tumor to chemotherapy: Mimicking a clinical study	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.jtbi.2010.05.019	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.jtbi.2010.05.019	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	In this paper an advanced, clinically oriented multiscale cancer model of breast tumor response to chemotherapy is presented. The paradigm of early breast cancer treated by epirubicin according to a branch of an actual clinical trial (the Trial of Principle, TOP trial) has been addressed. The model, stemming from previous work of the In Silico Oncology Group, National Technical University of Athens, is characterized by several crucial new features, such as the explicit distinction of proliferating cells into stem cells of infinite mitotic potential and cells of limited proliferative capacity, an advanced generic cytokinetic model and an improved tumor constitution initialization technique. A sensitivity analysis regarding critical parameters of the model has revealed their effect on the behavior of the biological system. The favorable outcome of an initial step towards the clinical adaptation and validation of the simulation model, based on the use of anonymized data from the TOP clinical trial, is presented and discussed. Two real clinical cases from the TOP trial with variable molecular profile have been simulated. A realistic time course of the tumor diameter and a reduction in tumor size in agreement with the clinical data has been achieved for both cases by selection of reasonable model parameter values, thus demonstrating a possible adaptation process of the model to real clinical trial data. Available imaging, histological, molecular and treatment data are exploited by the model in order to strengthen patient individualization modeling. The expected use of the model following thorough clinical adaptation, optimization and validation is to simulate either several candidate treatment schemes for a particular patient and support the selection of the optimal one or to simulate the expected extent of tumor shrinkage for a given time instant and decide on the adequacy or not of the simulated scheme. (C) 2010 Elsevier Ltd. All rights reserved.	en
heal.publisher	ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD	en
heal.journalName	Journal of Theoretical Biology	en
dc.identifier.doi	10.1016/j.jtbi.2010.05.019	en
dc.identifier.isi	ISI:000280929800013	en
dc.identifier.volume	266	en
dc.identifier.issue	1	en
dc.identifier.spage	124	en
dc.identifier.epage	139	en