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Modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents

PURPOSE: Radiation therapy, whether given alone or in combination with chemical agents, is one of the cornerstones of oncology. We develop a quantitative model that describes tumor growth during and after treatment with radiation and radiosensitizing agents. The model also describes long-term treatm...

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Autores principales: Cardilin, Tim, Almquist, Joachim, Jirstrand, Mats, Zimmermann, Astrid, Lignet, Floriane, El Bawab, Samer, Gabrielsson, Johan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499765/
https://www.ncbi.nlm.nih.gov/pubmed/30976845
http://dx.doi.org/10.1007/s00280-019-03829-y
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author Cardilin, Tim
Almquist, Joachim
Jirstrand, Mats
Zimmermann, Astrid
Lignet, Floriane
El Bawab, Samer
Gabrielsson, Johan
author_facet Cardilin, Tim
Almquist, Joachim
Jirstrand, Mats
Zimmermann, Astrid
Lignet, Floriane
El Bawab, Samer
Gabrielsson, Johan
author_sort Cardilin, Tim
collection PubMed
description PURPOSE: Radiation therapy, whether given alone or in combination with chemical agents, is one of the cornerstones of oncology. We develop a quantitative model that describes tumor growth during and after treatment with radiation and radiosensitizing agents. The model also describes long-term treatment effects including tumor regrowth and eradication. METHODS: We challenge the model with data from a xenograft study using a clinically relevant administration schedule and use a mixed-effects approach for model-fitting. We use the calibrated model to predict exposure combinations that result in tumor eradication using Tumor Static Exposure (TSE). RESULTS: The model is able to adequately describe data from all treatment groups, with the parameter estimates taking biologically reasonable values. Using TSE, we predict the total radiation dose necessary for tumor eradication to be 110 Gy, which is reduced to 80 or 30 Gy with co-administration of 25 or 100 mg kg(−1) of a radiosensitizer. TSE is also explored via a heat map of different growth and shrinkage rates. Finally, we discuss the translational potential of the model and TSE concept to humans. CONCLUSIONS: The new model is capable of describing different tumor dynamics including tumor eradication and tumor regrowth with different rates, and can be calibrated using data from standard xenograft experiments. TSE and related concepts can be used to predict tumor shrinkage and eradication, and have the potential to guide new experiments and support translations from animals to humans.
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spelling pubmed-64997652019-05-20 Modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents Cardilin, Tim Almquist, Joachim Jirstrand, Mats Zimmermann, Astrid Lignet, Floriane El Bawab, Samer Gabrielsson, Johan Cancer Chemother Pharmacol Original Article PURPOSE: Radiation therapy, whether given alone or in combination with chemical agents, is one of the cornerstones of oncology. We develop a quantitative model that describes tumor growth during and after treatment with radiation and radiosensitizing agents. The model also describes long-term treatment effects including tumor regrowth and eradication. METHODS: We challenge the model with data from a xenograft study using a clinically relevant administration schedule and use a mixed-effects approach for model-fitting. We use the calibrated model to predict exposure combinations that result in tumor eradication using Tumor Static Exposure (TSE). RESULTS: The model is able to adequately describe data from all treatment groups, with the parameter estimates taking biologically reasonable values. Using TSE, we predict the total radiation dose necessary for tumor eradication to be 110 Gy, which is reduced to 80 or 30 Gy with co-administration of 25 or 100 mg kg(−1) of a radiosensitizer. TSE is also explored via a heat map of different growth and shrinkage rates. Finally, we discuss the translational potential of the model and TSE concept to humans. CONCLUSIONS: The new model is capable of describing different tumor dynamics including tumor eradication and tumor regrowth with different rates, and can be calibrated using data from standard xenograft experiments. TSE and related concepts can be used to predict tumor shrinkage and eradication, and have the potential to guide new experiments and support translations from animals to humans. Springer Berlin Heidelberg 2019-04-11 2019 /pmc/articles/PMC6499765/ /pubmed/30976845 http://dx.doi.org/10.1007/s00280-019-03829-y Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Cardilin, Tim
Almquist, Joachim
Jirstrand, Mats
Zimmermann, Astrid
Lignet, Floriane
El Bawab, Samer
Gabrielsson, Johan
Modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents
title Modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents
title_full Modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents
title_fullStr Modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents
title_full_unstemmed Modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents
title_short Modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents
title_sort modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499765/
https://www.ncbi.nlm.nih.gov/pubmed/30976845
http://dx.doi.org/10.1007/s00280-019-03829-y
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