In the event of a large-scale radiation exposure, accurate and quick assessment of radiation dose received would be critical for triage and medical treatment of large numbers of potentially exposed individuals. Current methods of biodosimetry, such as the dicentric chromosome assay, are time consuming and require sophisticated equipment and highly trained personnel. Therefore, scalable biodosimetry approaches, including gene expression profiles in peripheral blood cells, are being investigated. Due to the limited availability of appropriate human samples, biodosimetry development has relied heavily on mouse models, which are not directly applicable to human response. Therefore, to explore the feasibility of using non-human primate (NHP) models to build and test a biodosimetry algorithm for use in humans, we irradiated ex vivo peripheral blood samples from both humans and rhesus macaques with doses of 0, 2, 5, 6 and 7 Gy, and compared the gene expression profiles 24 h later using Agilent human microarrays. Among the dose-responsive genes in human and using non-human primate, 52 genes showed highly correlated expression patterns between the species, and were enriched in p53/DNA damage response, apoptosis and cell cycle-related genes. When these interspecies-correlated genes were used to build biodosimetry models with using NHP data, the mean prediction accuracy on non-human primate samples was about 90% within 1 Gy of delivered dose in leave-one-out cross-validation. However, tests on human samples suggested that human gene expression values may need to be adjusted prior to application of the NHP model. A “multi-gene” approach utilizing all gene values for cross-species conversion and applying the converted values on the NHP biodosimetry models, gave a leave-one-out cross-validation prediction accuracy for human samples highly comparable (up to 94%) to that for non-human primates. Overall, this study demonstrates that a robust NHP biodosimetry model can be built using interspecies-correlated genes, and that, by using multiple regression-based cross-species conversion of expression values, absorbed dose in human samples can be accurately predicted by the NHP model.
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1 June 2017
Research Article|
March 22 2017
Developing Human Radiation Biodosimetry Models: Testing Cross-Species Conversion Approaches Using an Ex Vivo Model System
Jin G. Park;
Jin G. Park
1
a Biodesign Center for Personalized Diagnostic, Biodesign Institute, Arizona State University, Arizona
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Sunirmal Paul;
Sunirmal Paul
1,
d Center for Radiological Research, Columbia University Medical Center, New York
2 Currently at Department of Radiology, Rutgers New Jersey Medical School, New Jersey.
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Natalia Briones;
Natalia Briones
a Biodesign Center for Personalized Diagnostic, Biodesign Institute, Arizona State University, Arizona
3 Currently at Integrated Cancer Genomics Division, Translational Genomics Research Institute, AZ.
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Jia Zeng;
Jia Zeng
a Biodesign Center for Personalized Diagnostic, Biodesign Institute, Arizona State University, Arizona
b Department of Biomedical Informatics, Arizona State University, Arizona
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Kristin Gillis;
Kristin Gillis
a Biodesign Center for Personalized Diagnostic, Biodesign Institute, Arizona State University, Arizona
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Garrick Wallstrom;
Garrick Wallstrom
a Biodesign Center for Personalized Diagnostic, Biodesign Institute, Arizona State University, Arizona
b Department of Biomedical Informatics, Arizona State University, Arizona
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Joshua LaBaer;
Joshua LaBaer
4
a Biodesign Center for Personalized Diagnostic, Biodesign Institute, Arizona State University, Arizona
c School of Molecular Sciences, Arizona State University, Arizona
4 Addresses for correspondence: Biodesign Center for Personalized Diagnostic and School of Molecular Sciences, Arizona State University, Arizona; email: Joshua.Labaer@asu.edu; and Center for Radiological Research, Columbia University Medical Center, New York; email: saa2108@cumc.columbia.edu.
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Sally A. Amundson
Sally A. Amundson
4
d Center for Radiological Research, Columbia University Medical Center, New York
4 Addresses for correspondence: Biodesign Center for Personalized Diagnostic and School of Molecular Sciences, Arizona State University, Arizona; email: Joshua.Labaer@asu.edu; and Center for Radiological Research, Columbia University Medical Center, New York; email: saa2108@cumc.columbia.edu.
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Radiat Res (2017) 187 (6): 708–721.
Article history
Received:
November 13 2016
Accepted:
February 16 2017
Citation
Jin G. Park, Sunirmal Paul, Natalia Briones, Jia Zeng, Kristin Gillis, Garrick Wallstrom, Joshua LaBaer, Sally A. Amundson; Developing Human Radiation Biodosimetry Models: Testing Cross-Species Conversion Approaches Using an Ex Vivo Model System. Radiat Res 1 June 2017; 187 (6): 708–721. doi: https://doi.org/10.1667/RR14655.1
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