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Cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose

In the search for biological markers after a large-scale exposure of the human population to radiation, gene expression is a sensitive endpoint easily translatable to in-field high throughput applications. Primarily, the ex-vivo irradiated healthy human blood model has been used to generate availabl...

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Autores principales: Ghandhi, Shanaz A., Shuryak, Igor, Ponnaiya, Brian, Wu, Xuefeng, Garty, Guy, Morton, Shad R., Kaur, Salan P., Amundson, Sally A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9391341/
https://www.ncbi.nlm.nih.gov/pubmed/35986207
http://dx.doi.org/10.1038/s41598-022-18558-1
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author Ghandhi, Shanaz A.
Shuryak, Igor
Ponnaiya, Brian
Wu, Xuefeng
Garty, Guy
Morton, Shad R.
Kaur, Salan P.
Amundson, Sally A.
author_facet Ghandhi, Shanaz A.
Shuryak, Igor
Ponnaiya, Brian
Wu, Xuefeng
Garty, Guy
Morton, Shad R.
Kaur, Salan P.
Amundson, Sally A.
author_sort Ghandhi, Shanaz A.
collection PubMed
description In the search for biological markers after a large-scale exposure of the human population to radiation, gene expression is a sensitive endpoint easily translatable to in-field high throughput applications. Primarily, the ex-vivo irradiated healthy human blood model has been used to generate available gene expression datasets. This model has limitations i.e., lack of signaling from other irradiated tissues and deterioration of blood cells cultures over time. In vivo models are needed; therefore, we present our novel approach to define a gene signature in mouse blood cells that quantitatively correlates with radiation dose (at 1 Gy/min). Starting with available microarray datasets, we selected 30 radiation-responsive genes and performed cross-validation/training–testing data splits to downselect 16 radiation-responsive genes. We then tested these genes in an independent cohort of irradiated adult C57BL/6 mice (50:50 both sexes) and measured mRNA by quantitative RT-PCR in whole blood at 24 h. Dose reconstruction using net signal (difference between geometric means of top 3 positively correlated and top 4 negatively correlated genes with dose), was highly improved over the microarrays, with a root mean square error of ± 1.1 Gy in male and female mice combined. There were no significant sex-specific differences in mRNA or cell counts after irradiation.
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spelling pubmed-93913412022-08-21 Cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose Ghandhi, Shanaz A. Shuryak, Igor Ponnaiya, Brian Wu, Xuefeng Garty, Guy Morton, Shad R. Kaur, Salan P. Amundson, Sally A. Sci Rep Article In the search for biological markers after a large-scale exposure of the human population to radiation, gene expression is a sensitive endpoint easily translatable to in-field high throughput applications. Primarily, the ex-vivo irradiated healthy human blood model has been used to generate available gene expression datasets. This model has limitations i.e., lack of signaling from other irradiated tissues and deterioration of blood cells cultures over time. In vivo models are needed; therefore, we present our novel approach to define a gene signature in mouse blood cells that quantitatively correlates with radiation dose (at 1 Gy/min). Starting with available microarray datasets, we selected 30 radiation-responsive genes and performed cross-validation/training–testing data splits to downselect 16 radiation-responsive genes. We then tested these genes in an independent cohort of irradiated adult C57BL/6 mice (50:50 both sexes) and measured mRNA by quantitative RT-PCR in whole blood at 24 h. Dose reconstruction using net signal (difference between geometric means of top 3 positively correlated and top 4 negatively correlated genes with dose), was highly improved over the microarrays, with a root mean square error of ± 1.1 Gy in male and female mice combined. There were no significant sex-specific differences in mRNA or cell counts after irradiation. Nature Publishing Group UK 2022-08-19 /pmc/articles/PMC9391341/ /pubmed/35986207 http://dx.doi.org/10.1038/s41598-022-18558-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ghandhi, Shanaz A.
Shuryak, Igor
Ponnaiya, Brian
Wu, Xuefeng
Garty, Guy
Morton, Shad R.
Kaur, Salan P.
Amundson, Sally A.
Cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose
title Cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose
title_full Cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose
title_fullStr Cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose
title_full_unstemmed Cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose
title_short Cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose
title_sort cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9391341/
https://www.ncbi.nlm.nih.gov/pubmed/35986207
http://dx.doi.org/10.1038/s41598-022-18558-1
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