Identification of radiation-sensitive genes as biomarkers for biodosimetry: an ex vivo analysis of TNFRSF10B, ZMAT3, POLH, and PLK2 in human blood samples.
BACKGROUND: Humans are exposed to ionizing radiation (IR), which causes direct and indirect DNA damage. Biodosimetry is a critical component of clinical care following radiation exposure, enabling accurate assessment and mitigation of health effects. The present study was conducted to investigate the ex vivo expression of the genes TNFRSF10B, ZMAT3, PLK2, and POLH in human peripheral blood samples exposed to X-radiation at doses of 0, 0.5, 2, and 4 Gy at 0, 4, 24, and 48 hours post-exposure. Investigating gene expression dynamics through biodosimetry is a novel approach that may provide insights into gene-specific responses, potentially enhancing the accuracy and sensitivity of radiation dose assessment. MATERIALS AND METHODS: Peripheral blood samples were collected from five healthy volunteers and exposed to 0, 0.5, 2, or 4 Gy radiation with a 6 MV linear accelerator. Following the extraction of RNA and cDNA synthesis, gene expression analysis via qRT‒PCR was performed. These genes were normalized against the housekeeping gene β-actin, and the ΔΔCt method was used for statistical analysis of gene expression. The data were subjected to statistical analysis, and the level of significance (p < 0.05) was determined to test the effects of dose and time on gene expression. RESULTS: The expression of the TNFRSF10B, ZMAT3, POLH, and PLK2 genes was markedly dose- and time-dependent in response to X-ray radiation in vitro. Whole-blood samples irradiated at doses of 0, 0.5, 2, and 4 Gy and analyzed at four time points, 0, 4, 24, and 48 hours, respectively, revealed marked changes in the expression levels of the genes studied, revealing the mechanisms of the response at the cellular level to ionizing radiation. Although minor inter-individual variation in gene expression was observed, it did not significantly affect the overall trends, and the results remained statistically robust. CONCLUSION: These findings highlight a robust biodosimetry framework: TNFRSF10B demonstrated the highest diagnostic performance (AUC = 0.94; sensitivity = 98%; specificity = 75%; cut-off = 1.11), making it a highly reliable biomarker for radiation exposure. PLK2 also exhibited strong discriminative capacity (AUC = 0.84; sensitivity = 90%; specificity = 80%; cut-off =2.5), particularly for minimizing false positives. ZMAT3 (AUC = 0.78; sensitivity/specificity = 75%; cut-off = 3.21) showed balanced early-phase performance, whilePOLH (AUC = 0.73; sensitivity = 80%; specificity = 60%; cut-off = 1.10) may serve as a complementary marker. Collectively, these findings support a multi-gene expression approach for accurate biodosimetric assessment and improved triage following radiation exposure.