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Calibration curve for radiation dose estimation using FDXR gene expression biodosimetry - premises and pitfalls. | LitMetric

Calibration curve for radiation dose estimation using FDXR gene expression biodosimetry - premises and pitfalls.

Int J Radiat Biol

Cancer Mechanisms and Biomarkers Group, Centre for Radiation, Chemical and Environmental Hazards, UK Health Security Agency, Oxfordshire, England.

Published: August 2024

AI Article Synopsis

Article Abstract

Purpose: Radiation-induced alterations in gene expression show great promise for dose reconstruction and for severity prediction of acute health effects. Among several genes explored as potential biomarkers, FDXR is widely used due to high upregulation in white blood cells following radiation exposure. Nonetheless, the absence of a standardized protocols for gene expression-based biodosimetry is a notable gap that warrants attention to enhance the accuracy, reproducibility and reliability. The objective of this study was to evaluate the sensitivity of transcriptional biodosimetry to differences in protocols used by different laboratories and establish guidelines for the calculation of calibration curve using FDXR expression data.

Material And Methods: Two sets of irradiated blood samples generated during RENEB exercise were used. The first included samples irradiated with known doses including: 0, 0.25, 0.5, 1, 2, 3 and 4 Gy. The second set consisted of three 'blind' samples irradiated with 1.8 Gy, 0.4 Gy and a sham-irradiated sample. After irradiation, samples were incubated at 37 °C over 24 h and sent to participating laboratories, where RNA isolation and FDXR expression analysis by qPCR were performed using sets of primers/probes and reference genes specific for each laboratory. Calibration curves based on FDXR expression data were generated using non-linear and linear regression and used for dose estimation of 'blind' samples.

Results: Dose estimates for sham-irradiated sample (0.020-0.024 Gy) and sample irradiated with 0.4 Gy (0.369-0.381 Gy) showed remarkable consistency across all laboratories, closely approximating the true doses regardless variation in primers/probes and reference genes used. For sample irradiated with 1.8 Gy the dose estimates were less precise (1.198-2.011 Gy) but remained within an acceptable margin for triage within the context of high dose range.

Conclusion: Methodological differences in reference genes and primers/probes used for FDXR expression measurement do not have a significant impact on the dose estimates generated, provided that all reference genes performed as expected and the primers/probes target a similar set of transcript variants. The preferred method for constructing a calibration curve based on FDXR expression data involves employing linear regression to establish a function that describes the relationship between the logarithm of absorbed dose and FDXR ΔCt values. However, one should be careful with using non-irradiated sample data as these cannot be accurately represented on a logarithmic scale. A standard curve generated using this approach can give reliable dose estimations in a dose range from 50 mGy to 4 Gy at least.

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Source
http://dx.doi.org/10.1080/09553002.2024.2373751DOI Listing

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