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 |