Exploiting clinical trial data drastically narrows the window of possible solutions to the problem of clinical adaptation of a multiscale cancer model

Stamatakos, GS; Georgiadi, EC; Graf, N; Kolokotroni, EA; Dionysiou, DD

dc.contributor.author	Stamatakos, GS	en
dc.contributor.author	Georgiadi, EC	en
dc.contributor.author	Graf, N	en
dc.contributor.author	Kolokotroni, EA	en
dc.contributor.author	Dionysiou, DD	en
dc.date.accessioned	2014-03-01T01:35:40Z
dc.date.available	2014-03-01T01:35:40Z
dc.date.issued	2011	en
dc.identifier.issn	1932-6203	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/21162
dc.subject.other	apoptosis	en
dc.subject.other	article	en
dc.subject.other	cancer chemotherapy	en
dc.subject.other	cancer model	en
dc.subject.other	cancer stem cell	en
dc.subject.other	cell division	en
dc.subject.other	clinical study	en
dc.subject.other	clinical trial (topic)	en
dc.subject.other	data analysis	en
dc.subject.other	histology	en
dc.subject.other	mathematical model	en
dc.subject.other	nephroblastoma	en
dc.subject.other	nutrient availability	en
dc.subject.other	preoperative treatment	en
dc.subject.other	sensitivity analysis	en
dc.subject.other	solid tumor	en
dc.subject.other	tissue oxygenation	en
dc.subject.other	treatment response	en
dc.subject.other	tumor growth	en
dc.subject.other	tumor volume	en
dc.subject.other	validation process	en
dc.title	Exploiting clinical trial data drastically narrows the window of possible solutions to the problem of clinical adaptation of a multiscale cancer model	en
heal.type	journalArticle	en
heal.identifier.primary	10.1371/journal.pone.0017594	en
heal.identifier.secondary	http://dx.doi.org/10.1371/journal.pone.0017594	en
heal.identifier.secondary	e17594	en
heal.language	English	en
heal.publicationDate	2011	en
heal.abstract	The development of computational models for simulating tumor growth and response to treatment has gained significant momentum during the last few decades. At the dawn of the era of personalized medicine, providing insight into complex mechanisms involved in cancer and contributing to patient-specific therapy optimization constitute particularly inspiring pursuits. The in silico oncology community is facing the great challenge of effectively translating simulation models into clinical practice, which presupposes a thorough sensitivity analysis, adaptation and validation process based on real clinical data. In this paper, the behavior of a clinically-oriented, multiscale model of solid tumor response to chemotherapy is investigated, using the paradigm of nephroblastoma response to preoperative chemotherapy in the context of the SIOP/GPOH clinical trial. A sorting of the model's parameters according to the magnitude of their effect on the output has unveiled the relative importance of the corresponding biological mechanisms; major impact on the result of therapy is credited to the oxygenation and nutrient availability status of the tumor and the balance between the symmetric and asymmetric modes of stem cell division. The effect of a number of parameter combinations on the extent of chemotherapy-induced tumor shrinkage and on the tumor's growth rate are discussed. A real clinical case of nephroblastoma has served as a proof of principle study case, demonstrating the basics of an ongoing clinical adaptation and validation process. By using clinical data in conjunction with plausible values of model parameters, an excellent fit of the model to the available medical data of the selected nephroblastoma case has been achieved, in terms of both volume reduction and histological constitution of the tumor. In this context, the exploitation of multiscale clinical data drastically narrows the window of possible solutions to the clinical adaptation problem. © 2011 Stamatakos et al.	en
heal.publisher	PUBLIC LIBRARY SCIENCE	en
heal.journalName	PLoS ONE	en
dc.identifier.doi	10.1371/journal.pone.0017594	en
dc.identifier.isi	ISI:000287965200030	en
dc.identifier.volume	6	en
dc.identifier.issue	3	en