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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Main Authors: 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
Format: Article
Language:English
Published: Elsevier 2009-01-01
Series:Neoplasia: An International Journal for Oncology Research
Online Access:http://www.sciencedirect.com/science/article/pii/S1476558609800870
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spelling 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.
url http://www.sciencedirect.com/science/article/pii/S1476558609800870
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