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Mathematical Analysis of Glioma Growth in a Murine Model

Five immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at five separate time points to characterize growth and development of t...

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Autores principales: Rutter, Erica M., Stepien, Tracy L., Anderies, Barrett J., Plasencia, Jonathan D., Woolf, Eric C., Scheck, Adrienne C., Turner, Gregory H., Liu, Qingwei, Frakes, David, Kodibagkar, Vikram, Kuang, Yang, Preul, Mark C., Kostelich, Eric J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451439/
https://www.ncbi.nlm.nih.gov/pubmed/28566701
http://dx.doi.org/10.1038/s41598-017-02462-0
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author Rutter, Erica M.
Stepien, Tracy L.
Anderies, Barrett J.
Plasencia, Jonathan D.
Woolf, Eric C.
Scheck, Adrienne C.
Turner, Gregory H.
Liu, Qingwei
Frakes, David
Kodibagkar, Vikram
Kuang, Yang
Preul, Mark C.
Kostelich, Eric J.
author_facet Rutter, Erica M.
Stepien, Tracy L.
Anderies, Barrett J.
Plasencia, Jonathan D.
Woolf, Eric C.
Scheck, Adrienne C.
Turner, Gregory H.
Liu, Qingwei
Frakes, David
Kodibagkar, Vikram
Kuang, Yang
Preul, Mark C.
Kostelich, Eric J.
author_sort Rutter, Erica M.
collection PubMed
description Five immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at five separate time points to characterize growth and development of the tumor. After 25 days, the final tumor volumes of the mice varied from 12 mm(3) to 62 mm(3), even though mice were inoculated from the same tumor cell line under carefully controlled conditions. We generated hypotheses to explore large variances in final tumor size and tested them with our simple reaction-diffusion model in both a 3-dimensional (3D) finite difference method and a 2-dimensional (2D) level set method. The parameters obtained from a best-fit procedure, designed to yield simulated tumors as close as possible to the observed ones, vary by an order of magnitude between the three mice analyzed in detail. These differences may reflect morphological and biological variability in tumor growth, as well as errors in the mathematical model, perhaps from an oversimplification of the tumor dynamics or nonidentifiability of parameters. Our results generate parameters that match other experimental in vitro and in vivo measurements. Additionally, we calculate wave speed, which matches with other rat and human measurements.
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spelling pubmed-54514392017-06-02 Mathematical Analysis of Glioma Growth in a Murine Model Rutter, Erica M. Stepien, Tracy L. Anderies, Barrett J. Plasencia, Jonathan D. Woolf, Eric C. Scheck, Adrienne C. Turner, Gregory H. Liu, Qingwei Frakes, David Kodibagkar, Vikram Kuang, Yang Preul, Mark C. Kostelich, Eric J. Sci Rep Article Five immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at five separate time points to characterize growth and development of the tumor. After 25 days, the final tumor volumes of the mice varied from 12 mm(3) to 62 mm(3), even though mice were inoculated from the same tumor cell line under carefully controlled conditions. We generated hypotheses to explore large variances in final tumor size and tested them with our simple reaction-diffusion model in both a 3-dimensional (3D) finite difference method and a 2-dimensional (2D) level set method. The parameters obtained from a best-fit procedure, designed to yield simulated tumors as close as possible to the observed ones, vary by an order of magnitude between the three mice analyzed in detail. These differences may reflect morphological and biological variability in tumor growth, as well as errors in the mathematical model, perhaps from an oversimplification of the tumor dynamics or nonidentifiability of parameters. Our results generate parameters that match other experimental in vitro and in vivo measurements. Additionally, we calculate wave speed, which matches with other rat and human measurements. Nature Publishing Group UK 2017-05-31 /pmc/articles/PMC5451439/ /pubmed/28566701 http://dx.doi.org/10.1038/s41598-017-02462-0 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Rutter, Erica M.
Stepien, Tracy L.
Anderies, Barrett J.
Plasencia, Jonathan D.
Woolf, Eric C.
Scheck, Adrienne C.
Turner, Gregory H.
Liu, Qingwei
Frakes, David
Kodibagkar, Vikram
Kuang, Yang
Preul, Mark C.
Kostelich, Eric J.
Mathematical Analysis of Glioma Growth in a Murine Model
title Mathematical Analysis of Glioma Growth in a Murine Model
title_full Mathematical Analysis of Glioma Growth in a Murine Model
title_fullStr Mathematical Analysis of Glioma Growth in a Murine Model
title_full_unstemmed Mathematical Analysis of Glioma Growth in a Murine Model
title_short Mathematical Analysis of Glioma Growth in a Murine Model
title_sort mathematical analysis of glioma growth in a murine model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451439/
https://www.ncbi.nlm.nih.gov/pubmed/28566701
http://dx.doi.org/10.1038/s41598-017-02462-0
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