Ionizing radiation is a potent carcinogen, inducing cancer through DNA damage. The signatures of mutations arising in human tissues following in vivo exposure to ionizing radiation have not been documented. Here, we searched for signatures of ionizing radiation in 12 radiation-associated second malignancies of different tumour types. Two signatures of somatic mutation characterize ionizing radiation exposure irrespective of tumour type. Compared with 319 radiation-naive tumours, radiation-associated tumours carry a median extra 201 deletions genome-wide, sized 1–100 base pairs often with microhomology at the junction. Unlike deletions of radiation-naive tumours, these show no variation in density across the genome or correlation with sequence context, replication timing or chromatin structure. Furthermore, we observe a significant increase in balanced inversions in radiation-associated tumours. Both small deletions and inversions generate driver mutations. Thus, ionizing radiation generates distinctive mutational signatures that explain its carcinogenic potential.

To establish a panel of highly radiation responsive genes suitable for biological dosimetry and to explore inter-individual variation in response to ionising radiation exposure. Analysis of gene expression in response to radiation was carried out using three independent techniques (Microarray, Multiplex Quantitative Real-Time Polymerase Chain Reaction (MQRT- PCR) and nCounter® Analysis System) in human dividing lymphocytes in culture and peripheral blood leukocytes exposed ex vivo from the same donors. Variations in transcriptional response to exposure to ionising radiation analysed by microarray allowed the identification of genes which can be measured accurately using MQRT PCR and another technique allowing direct count of mRNA copies. We have identified genes which are consistently up-regulated following exposure to 2 or 4 Gy of X-rays at different time points, for all individuals in blood and cultured lymphocytes. Down-regulated genes including cyclins, centromeric and mitotic checkpoint genes, particularly those associated with chromosome instability and cancer could be detected in dividing lymphocytes only. The data provide evidence that there are a number of genes which seem suitable for biological dosimetry using peripheral blood, including sestrin 1 (SESN1), growth arrest and DNA damage inducible 45 alpha (GADD45A), cyclin-dependent kinase inhibitor 1A (CDKN1A), cyclin G1 (CCNG1), ferredoxin reductase (FDXR), p53 up-regulated mediator of apoptosis (BBC3) and Mdm2 p53 binding protein homolog (MDM2). These biomarkers could potentially be used for triage after large-scale radiological incidents and for monitoring radiation exposure during radiotherapy.

Rapid biodosimetry tools are required to assist with triage in the case of a large-scale radiation incident. Here, we aimed to determine the dose-assessment accuracy of the well-established dicentric chromosome assay (DCA) and cytokinesis-block micronucleus assay (CBMN) in comparison to the emerging γ-H2AX foci and gene expression assays for triage mode biodosimetry and radiation injury assessment. Coded blood samples exposed to 10 X-ray doses (240 kVp, 1 Gy/min) of up to 6.4 Gy were sent to participants for dose estimation. Report times were documented for each laboratory and assay. The mean absolute difference (MAD) of estimated doses relative to the true doses was calculated. We also merged doses into binary dose categories of clinical relevance and examined accuracy, sensitivity and specificity of the assays. Dose estimates were reported by the first laboratories within 0.3–0.4 days of receipt of samples for the γ-H2AX and gene expression assays compared to 2.4 and 4 days for the DCA and CBMN assays, respectively. Irrespective of the assay we found a 2.5–4-fold variation of interlaboratory accuracy per assay and lowest MAD values for the DCA assay (0.16 Gy) followed by CBMN (0.34 Gy), gene expression (0.34 Gy) and γ-H2AX (0.45 Gy) foci assay. Binary categories of dose estimates could be discriminated with equal efficiency for all assays, but at doses ≥1.5 Gy a 10% decrease in efficiency was observed for the foci assay, which was still comparable to the CBMN assay. In conclusion, the DCA has been confirmed as the gold standard biodosimetry method, but in situations where speed and throughput are more important than ultimate accuracy, the emerging rapid molecular assays have the potential to become useful triage tools.

Previous investigations in gene expression changes in blood after radiation exposure have highlighted its potential to provide biomarkers of exposure. Here, FDXR transcriptional changes in blood were investigated in humans undergoing a range of external radiation exposure procedures covering several orders of magnitude (cardiac fluoroscopy, diagnostic computed tomography (CT)) and treatments (total body and local radiotherapy). Moreover, a method was developed to assess the dose to the blood using physical exposure parameters. FDXR expression was significantly up-regulated 24 hr after radiotherapy in most patients and continuously during the fractionated treatment. Significance was reached even after diagnostic CT 2 hours post-exposure. We further showed that no significant differences in expression were found between ex vivo and in vivo samples from the same patients. Moreover, potential confounding factors such as gender, infection status and anti-oxidants only affect moderately FDXR transcription. Finally, we provided a first in vivo dose-response showing dose-dependency even for very low doses or partial body exposure showing good correlation between physically and biologically assessed doses. In conclusion, we report the remarkable responsiveness of FDXR to ionising radiation at the transcriptional level which, when measured in the right time window, provides accurate in vivo dose estimates.

Purpose: Modifications of gene expression following ionizing radiation (IR) exposure of cells in vitro and in vivo are well documented. However, little is known about the dose-responses of transcriptionally responsive genes, especially at low doses. In this study, we investigated these dose-responses and assessed inter-individual variability. Materials and methods: High dose (0.5–4 Gy) and low dose (5–100 mGy) gene expression responses at 2 h and 24 h using 13 biomarkers transcriptionally regulated through the DNA damage response by the tumor suppressor p53 were investigated. Inter-individual variation was also examined. Results: High dose-response curves were best constructed using a polynomial fit while the low dose-response curves used a linear fit with linear R² values of 0.841–0.985. Individual variation was evident in the high and low dose ranges. The FDXR, DDB2 high dose gene combination produced a mean dose estimate of 0.7 Gy for 1 Gy irradiated ‘unknown’ samples (95% CIs of 0.3–1.1 Gy) and 1.4 Gy for 2 Gy exposure (95% CIs of 0.6–2.1 Gy). The FDXR, DDB2, CCNG1 low dose gene combination estimated 98 mGy (95% CIs of 27–169 mGy) for 100 mGy exposure. Conclusions: These findings identify genes that fulfill some of the requirements of a good exposure biomarker even at low doses, such as sensitivity, reproducibility and simple proportionality with dose.