A Quantitative Volumetric Micro-Computed Tomography Method to Analyze Lung Tumors in Genetically Engineered Mouse Models
Two genetically engineered, conditional mouse models of lung tumor formation, K-rasLSL-G12D and K-rasLSL-G12D/p53LSL-R270H, are commonly used to model human lung cancer. Developed by Tyler Jacks and colleagues, these models have been invaluable to study in vivo lung cancer initiation and progressio...
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Series: | Neoplasia: An International Journal for Oncology Research |
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doaj-3a322bb0516e4a1b9d50a378c2275d322020-11-25T01:10:22ZengElsevierNeoplasia: An International Journal for Oncology Research1476-55861522-80022009-01-01111394710.1593/neo.81030A Quantitative Volumetric Micro-Computed Tomography Method to Analyze Lung Tumors in Genetically Engineered Mouse ModelsBrian B. Haines0Kimberly A. Bettano1Melissa Chenard2Raquel S. Sevilla3Christopher Ware4Minilik H. Angagaw5Christopher T. Winkelmann6Christopher Tong7John F. Reilly8Cyrille Sur9Weisheng Zhang10Oncology Pharmacology, Merck & Co., Inc., 33 Avenue Louis Pasteur, Boston, MA 02115, USAImaging, Merck & Co., Inc., 33 Avenue Louis Pasteur, Boston, MA 02115, USAOncology Pharmacology, Merck & Co., Inc., 33 Avenue Louis Pasteur, Boston, MA 02115, USAImaging, Merck & Co., Inc., 33 Avenue Louis Pasteur, Boston, MA 02115, USAHistology & Biomarker, Merck & Co., Inc., 33 Avenue Louis Pasteur, Boston, MA 02115, USALaboratory Animal Resources, Merck & Co., Inc., 33 Avenue Louis Pasteur, Boston, MA 02115, USAImaging Department, Merck & Co., Inc., Sumneytown Pike, P.O. Box 4, West Point, PA 19486, USABiometrics Research, Merck & Co., Inc., 126 E. Lincoln Avenue, P.O. Box 2000, Rahway, NJ 07065, USAHistology & Biomarker, Merck & Co., Inc., 33 Avenue Louis Pasteur, Boston, MA 02115, USAImaging Department, Merck & Co., Inc., Sumneytown Pike, P.O. Box 4, West Point, PA 19486, USAImaging, Merck & Co., Inc., 33 Avenue Louis Pasteur, Boston, MA 02115, USA Two genetically engineered, conditional mouse models of lung tumor formation, K-rasLSL-G12D and K-rasLSL-G12D/p53LSL-R270H, are commonly used to model human lung cancer. Developed by Tyler Jacks and colleagues, these models have been invaluable to study in vivo lung cancer initiation and progression in a genetically and physiologically relevant context. However, heterogeneity, multiplicity and complexity of tumor formation in these models make it challenging to monitor tumor growth in vivo and have limited the application of these models in oncology drug discovery. Here, we describe a novel analytical method to quantitatively measure total lung tumor burden in live animals using micro-computed tomography imaging. Applying this methodology, we studied the kinetics of tumor development and response to targeted therapy in vivo in K-ras and K-ras/p53 mice. Consistent with previous reports, lung tumors in both models developed in a time- and dose (Cre recombinase)-dependent manner. Furthermore, the compound K-rasLSL-G12D/p53LSL-R270H mice developed tumors faster and more robustly than mice harboring a single K-rasLSL-G12D oncogene, as expected. Erlotinib, a small molecule inhibitor of the epidermal growth factor receptor, significantly inhibited tumor growth in K-rasLSL-G12D/p53LSL-R270H mice. These results demonstrate that this novel imaging technique can be used to monitor both tumor progression and response to treatment and therefore supports a broader application of these genetically engineered mouse models in oncology drug discovery and development. http://www.sciencedirect.com/science/article/pii/S1476558609800870 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Brian B. Haines Kimberly A. Bettano Melissa Chenard Raquel S. Sevilla Christopher Ware Minilik H. Angagaw Christopher T. Winkelmann Christopher Tong John F. Reilly Cyrille Sur Weisheng Zhang |
spellingShingle |
Brian B. Haines Kimberly A. Bettano Melissa Chenard Raquel S. Sevilla Christopher Ware Minilik H. Angagaw Christopher T. Winkelmann Christopher Tong John F. Reilly Cyrille Sur Weisheng Zhang A Quantitative Volumetric Micro-Computed Tomography Method to Analyze Lung Tumors in Genetically Engineered Mouse Models Neoplasia: An International Journal for Oncology Research |
author_facet |
Brian B. Haines Kimberly A. Bettano Melissa Chenard Raquel S. Sevilla Christopher Ware Minilik H. Angagaw Christopher T. Winkelmann Christopher Tong John F. Reilly Cyrille Sur Weisheng Zhang |
author_sort |
Brian B. Haines |
title |
A Quantitative Volumetric Micro-Computed Tomography Method to Analyze Lung Tumors in Genetically Engineered Mouse Models |
title_short |
A Quantitative Volumetric Micro-Computed Tomography Method to Analyze Lung Tumors in Genetically Engineered Mouse Models |
title_full |
A Quantitative Volumetric Micro-Computed Tomography Method to Analyze Lung Tumors in Genetically Engineered Mouse Models |
title_fullStr |
A Quantitative Volumetric Micro-Computed Tomography Method to Analyze Lung Tumors in Genetically Engineered Mouse Models |
title_full_unstemmed |
A Quantitative Volumetric Micro-Computed Tomography Method to Analyze Lung Tumors in Genetically Engineered Mouse Models |
title_sort |
quantitative volumetric micro-computed tomography method to analyze lung tumors in genetically engineered mouse models |
publisher |
Elsevier |
series |
Neoplasia: An International Journal for Oncology Research |
issn |
1476-5586 1522-8002 |
publishDate |
2009-01-01 |
description |
Two genetically engineered, conditional mouse models of lung tumor formation, K-rasLSL-G12D and K-rasLSL-G12D/p53LSL-R270H, are commonly used to model human lung cancer. Developed by Tyler Jacks and colleagues, these models have been invaluable to study in vivo lung cancer initiation and progression in a genetically and physiologically relevant context. However, heterogeneity, multiplicity and complexity of tumor formation in these models make it challenging to monitor tumor growth in vivo and have limited the application of these models in oncology drug discovery. Here, we describe a novel analytical method to quantitatively measure total lung tumor burden in live animals using micro-computed tomography imaging. Applying this methodology, we studied the kinetics of tumor development and response to targeted therapy in vivo in K-ras and K-ras/p53 mice. Consistent with previous reports, lung tumors in both models developed in a time- and dose (Cre recombinase)-dependent manner. Furthermore, the compound K-rasLSL-G12D/p53LSL-R270H mice developed tumors faster and more robustly than mice harboring a single K-rasLSL-G12D oncogene, as expected. Erlotinib, a small molecule inhibitor of the epidermal growth factor receptor, significantly inhibited tumor growth in K-rasLSL-G12D/p53LSL-R270H mice. These results demonstrate that this novel imaging technique can be used to monitor both tumor progression and response to treatment and therefore supports a broader application of these genetically engineered mouse models in oncology drug discovery and development.
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url |
http://www.sciencedirect.com/science/article/pii/S1476558609800870 |
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