| Autor: |
Iversen ES; Department of Statistical Science, Duke University, Durham, NC, USA., McCarthy JM; Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA., Burdett KB; Duke Cancer Institute, Duke University Medical Center, Durham, NC, USA., Lipton G; Department of Statistical Science, Duke University, Durham, NC, USA., Phillips G; Department of Hematologic Malignancies & Cell Therapy, Duke University, Durham, NC, USA., Dressman H; Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA., Ross J; Department of Hematologic Malignancies & Cell Therapy, Duke University, Durham, NC, USA., Chao N; Department of Hematologic Malignancies & Cell Therapy, Duke University, Durham, NC, USA. |
| Abstrakt: |
Purpose: Design and characterization of a radiation biodosimetry device are complicated by the fact that the requisite data are not available in the intended use population, namely humans exposed to a single, whole-body radiation dose. Instead, one must turn to model systems. We discuss our studies utilizing healthy, unexposed humans, human bone marrow transplant patients undergoing total body irradiation (TBI), non-human primates subjected to the same irradiation regimen received by the human TBI patients and NHPs given a single, whole-body dose of ionizing radiation. Materials and Methods: We use Bayesian linear mixed models to characterize the association between NHP and human expression patterns in radiation response genes when exposed to a common exposure regimen and across exposure regimens within the same species. Results: We show that population average differences in expression of our radiation response genes from one to another model system are comparable to typical differences between two randomly sampled members of a given model system and that these differences are smaller, on average, for linear combinations of the probe data and for the model-based combinations employed for dose prediction as part of a radiation biodosimetry device. Conclusions: Our analysis suggests that dose estimates based on our gene list will be accurate when applied to humans who have received a single, whole-body exposure to ionizing radiation. |
