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7 January 2020 Identification of Radiation-Dose-Dependent Expressive Genes in Individuals Exposed to External Ionizing Radiation
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For victims of radiological accidents, rapid dose estimation and damage prediction are essential. Administering the gold-standard biodosimetry chromosome aberration assay requires highly skilled individuals and several days of labor; consequently, rapid turnaround is an important concern. Identification of new dose estimation markers and damage-predicting in vivo molecules to replace the chromosome aberration assay is crucial to improving the delivery time of medical treatment. Here, we investigated the applicability of mRNA levels using a mouse model. Female C57BL/6J mice were X-ray irradiated at various doses, and a DNA microarray was then performed to identify differentially expressed mRNAs in whole blood. The microarray analysis identified 14 radioresponsive mRNAs with more than fourfold differences by pattern matching in the expression at 24 h postirradiation. In particular, mRNA expression of Slfn4, Itgb5, Smim3, Tmem40, Litaf, Gp1bb and Cxx1c was significantly increased in a radiation-dose-dependent manner, as validated by reverse transcription quantitative polymerase chain reaction. We also performed an analysis using the cBioPortal for Cancer Genomics and found that the overall survival of ovarian adenocarcinoma patients with alterations in Smim3 and that of thymoma patients with alterations in Cxx1c had a worse prognosis than patients without these alterations. These findings suggest that the expression of several genes in whole blood was a sensitive and specific biomarker of radiation exposure and can be used as a rapid and reliable prospective molecular biomarker in radiological emergencies.

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Masaru Yamaguchi, Teruki Nishida, Yoshiaki Sato, Yuji Nakai, and Ikuo Kashiwakura "Identification of Radiation-Dose-Dependent Expressive Genes in Individuals Exposed to External Ionizing Radiation," Radiation Research 193(3), 274-285, (7 January 2020).
Received: 30 September 2019; Accepted: 17 December 2019; Published: 7 January 2020

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