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dc.contributor.authorLoizides, Charalambos
dc.contributor.authorIacovides, Demetris
dc.contributor.authorHadjiandreou, Marios M.
dc.contributor.authorRizki, Gizem
dc.contributor.authorAchilleos, Achilleas
dc.contributor.authorStrati, Katerina
dc.contributor.authorMitsis, Georgios D.
dc.date.accessioned2016-01-05T01:54:24Z
dc.date.available2016-01-05T01:54:24Z
dc.date.issued2015-12
dc.date.submitted2015-05
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/1721.1/100699
dc.description.abstractTumorigenesis is a complex, multistep process that depends on numerous alterations within the cell and contribution from the surrounding stroma. The ability to model macroscopic tumor evolution with high fidelity may contribute to better predictive tools for designing tumor therapy in the clinic. However, attempts to model tumor growth have mainly been developed and validated using data from xenograft mouse models, which fail to capture important aspects of tumorigenesis including tumor-initiating events and interactions with the immune system. In the present study, we investigate tumor growth and therapy dynamics in a mouse model of de novo carcinogenesis that closely recapitulates tumor initiation, progression and maintenance in vivo. We show that the rate of tumor growth and the effects of therapy are highly variable and mouse specific using a Gompertz model to describe tumor growth and a two-compartment pharmacokinetic/ pharmacodynamic model to describe the effects of therapy in mice treated with 5-FU. We show that inter-mouse growth variability is considerably larger than intra-mouse variability and that there is a correlation between tumor growth and drug kill rates. Our results show that in vivo tumor growth and regression in a double transgenic mouse model are highly variable both within and between subjects and that mathematical models can be used to capture the overall characteristics of this variability. In order for these models to become useful tools in the design of optimal therapy strategies and ultimately in clinical practice, a subject-specific modelling strategy is necessary, rather than approaches that are based on the average behavior of a given subject population which could provide erroneous results.en_US
dc.description.sponsorshipEuropean Territorial Cooperation Programmesen_US
dc.description.sponsorshipNational Funds of Greece and Cyprusen_US
dc.language.isoen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pone.0143840en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePublic Library of Scienceen_US
dc.titleModel-Based Tumor Growth Dynamics and Therapy Response in a Mouse Model of De Novo Carcinogenesisen_US
dc.typeArticleen_US
dc.identifier.citationLoizides, Charalambos, Demetris Iacovides, Marios M. Hadjiandreou, Gizem Rizki, Achilleas Achilleos, Katerina Strati, and Georgios D. Mitsis. “Model-Based Tumor Growth Dynamics and Therapy Response in a Mouse Model of De Novo Carcinogenesis.” Edited by Fabrizio Mattei. PLoS ONE 10, no. 12 (December 9, 2015): e0143840.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biologyen_US
dc.contributor.mitauthorRizki, Gizemen_US
dc.relation.journalPLOS ONEen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsLoizides, Charalambos; Iacovides, Demetris; Hadjiandreou, Marios M.; Rizki, Gizem; Achilleos, Achilleas; Strati, Katerina; Mitsis, Georgios D.en_US
dc.identifier.orcidhttps://orcid.org/0000-0003-2560-1606
mit.licenseOPEN_ACCESS_POLICYen_US


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