The risk of a large-scale event leading to acute radiation exposure necessitates the development of high-throughput methods for providing rapid individual dose estimates. Our work addresses three goals, which align with the directive of the European Union's Realizing the European Network of Biodosimetry project (EU-RENB): 1. To examine the suitability of different gene expression platforms for biodosimetry purposes; 2. To perform this examination using blood samples collected from prostate cancer patients (in vivo) and from healthy donors (in vitro); and 3. To compare radiation-induced gene expression changes of the in vivo with in vitro blood samples. For the in vitro part of this study, EDTA-treated whole blood was irradiated immediately after venipuncture using single X-ray doses (1 Gy/min(-1) dose rate, 100 keV). Blood samples used to generate calibration curves as well as 10 coded (blinded) samples (0-4 Gy dose range) were incubated for 24 h in vitro, lysed and shipped on wet ice. For the in vivo part of the study PAXgene tubes were used and peripheral blood (2.5 ml) was collected from prostate cancer patients before and 24 h after the first fractionated 2 Gy dose of localized radiotherapy to the pelvis [linear accelerator (LINAC), 580 MU/min, exposure 1-1.5 min]. Assays were run in each laboratory according to locally established protocols using either microarray platforms (2 laboratories) or qRT-PCR (2 laboratories). Report times on dose estimates were documented. The mean absolute difference of estimated doses relative to the true doses (Gy) were calculated. Doses were also merged into binary categories reflecting aspects of clinical/diagnostic relevance. For the in vitro part of the study, the earliest report time on dose estimates was 7 h for qRT-PCR and 35 h for microarrays. Methodological variance of gene expression measurements (CV ≤10% for technical replicates) and interindividual variance (≤twofold for all genes) were low. Dose estimates based on one gene, ferredoxin reductase (FDXR), using qRT-PCR were as precise as dose estimates based on multiple genes using microarrays, but the precision decreased at doses ≥2 Gy. Binary dose categories comprising, for example, unexposed compared with exposed samples, could be completely discriminated with most of our methods. Exposed prostate cancer blood samples (n = 4) could be completely discriminated from unexposed blood samples (n = 4, P < 0.03, two-sided Fisher's exact test) without individual controls. This could be performed by introducing an in vitro-to-in vivo correction factor of FDXR, which varied among the laboratories. After that the in vitro-constructed calibration curves could be used for dose estimation of the in vivo exposed prostate cancer blood samples within an accuracy window of ±0.5 Gy in both contributing qRT-PCR laboratories. In conclusion, early and precise dose estimates can be performed, in particular at doses ≤2 Gy in vitro. Blood samples of prostate cancer patients exposed to 0.09-0.017 Gy could be completely discriminated from pre...

Recent epidemiology studies highlighted the detrimental health effects of exposure to low dose and low dose rate ionizing radiation (IR): nuclear industry workers studies have shown increased leukaemia and solid tumour risks following cumulative doses of <100mSv and dose rates of <10mGy per year; paediatric patients studies have reported increased leukaemia and brain tumours risks after doses of 30-60mGy from computed tomography scans. Questions arise, however, about the impact of even lower doses and dose rates where classical epidemiological studies have limited power but where subsets within the large cohorts are expected to have an increased risk. Further progress requires integration of biomarkers or bioassays of individual exposure, effects and susceptibility to IR. The European DoReMi (Low Dose Research towards Multidisciplinary Integration) consortium previously reviewed biomarkers for potential use in IR epidemiological studies. Given the increased mechanistic understanding of responses to low dose radiation the current review provides an update covering technical advances and recent studies. A key issue identified is deciding which biomarkers to progress. A roadmap is provided for biomarker development from discovery to implementation and used to summarise the current status of proposed biomarkers for epidemiological studies. Most potential biomarkers remain at the discovery stage and for some there is sufficient evidence that further development is not warranted. One biomarker identified in the final stages of development and as a priority for further research is radiation specific mRNA transcript profiles.

Accurate assessment of the individual exposure dose based on easily accessible samples (e.g. blood) immediately following a radiological accident is crucial. We aimed at developing a robust transcription-based signature for biodosimetry from human peripheral blood mononuclear cells irradiated with different doses of X-rays (0.1 and 1.0 Gy) at a dose rate of 0.26 Gy/min. Genome-wide radiation-induced changes in mRNA expression were evaluated at both gene and exon level. Using exon-specific qRT-PCR, we confirmed that several biomarker genes are alternatively spliced or transcribed after irradiation and that different exons of these genes exhibit significantly different levels of induction. Moreover, a significant number of radiation-responsive genes were found to be genomic neighbors. Using three different classification models we found that gene and exon signatures performed equally well on dose prediction, as long as more than 10 features are included. Together, our results highlight the necessity of evaluating gene expression at the level of single exons for radiation biodosimetry in particular and transcriptional biomarker research in general. This approach is especially advisable for practical gene expression-based biodosimetry, for which primer- or probe-based techniques would be the method of choice.

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Purpose: This collaboration of five established European gene expression labs investigated the potential impact of culture conditions on the transcriptional response of peripheral blood to radiation exposure. Materials and methods: Blood from one healthy donor was exposed ex vivo to a Cobalt 60 source to produce a calibration curve in addition to four unknown doses. After exposure, the blood samples were either diluted with RPMI medium or left untouched. After 24-h incubation at 37 C the diluted blood samples were lysed, while the undiluted samples were mixed with the preservative RNALater and all samples were shipped frozen to the participating labs. Samples were processed by each lab using microarray (one lab) and QRT-PCR (four labs). Results: We show that although culture conditions affect the total amount of RNA recovered (p < .0001) and its integrity (p < .0001), it does not significantly affect dose estimates (except for the true dose at 1.1 Gy). Most importantly, the different analysis approaches provide comparable mean absolute difference of estimated doses relative to the true doses (p ¼ .9) and number of out of range (>0.5 Gy) measurements (p ¼ .6). Conclusion: This study confirms the robustness of gene expression as a method for biological dosimetry. ARTICLE HISTORY

Purpose: RENEB, 'Realising the European Network of Biodosimetry and Physical Retrospective Dosimetry,' is a network for research and emergency response mutual assistance in biodosimetry within the EU. Within this extremely active network, a number of new dosimetry methods have recently been proposed or developed. There is a requirement to test and/or validate these candidate techniques and inter-comparison exercises are a well-established method for such validation. Materials and methods: The authors present details of inter-comparisons of four such new methods: dicentric chromosome analysis including telomere and centromere staining; the gene expression assay carried out in whole blood; Raman spectroscopy on blood lymphocytes, and detection of radiationinduced thermoluminescent signals in glass screens taken from mobile phones. Results: In general the results show good agreement between the laboratories and methods within the expected levels of uncertainty, and thus demonstrate that there is a lot of potential for each of the candidate techniques. INTERNATIONAL JOURNAL OF RADIATION BIOLOGY, 2017 VOL. 93, NO. 1, 99-109 http://dx.doi.org/10.1080/09553002.2016 Conclusions: Further work is required before the new methods can be included within the suite of reliable dosimetry methods for use by RENEB partners and others in routine and emergency response scenarios.

Purpose: In order to ensure efficient use of medical resources following a radiological incident, there is an urgent need for high-throughput time-efficient biodosimetry tools. In the present study, we tested the applicability of a gene expression signature for the prediction of exposure dose as well as the time elapsed since irradiation. Materials and methods: We used whole blood samples from seven healthy volunteers as reference samples (X-ray doses: 0, 25, 50, 100, 500, 1000, and 2000 mGy; time points: 8, 12, 24, 36 and 48 h) and samples from seven other individuals as 'blind samples' (20 samples in total). Results: Gene expression values normalized to the reference gene without normalization to the unexposed controls were sufficient to predict doses with a correlation coefficient between the true and the predicted doses of 0.86. Importantly, we could also classify the samples according to the time since exposure with a correlation coefficient between the true and the predicted time point of 0.96. Because of the dynamic nature of radiation-induced gene expression, this feature will be of critical importance for adequate gene expression-based dose prediction in a real emergency situation. In addition, in this study we also compared different methodologies for RNA extraction available on the market and suggested the one most suitable for emergency situation which does not require on-spot availability of any specific reagents or equipment. Conclusions: Our results represent an important advancement in the application of gene expression for biodosimetry purposes.

Understanding the differences in biological response to photon and particle radiation is important for optimal exploitation of particle therapy for cancer patients, as well as for the adequate application of radiation protection measures for astronauts. To address this need, we compared the transcriptional profiles of isolated peripheral blood mononuclear cells 8 h after exposure to 1 Gy of X-rays, carbon ions or iron ions with those of non-irradiated cells using microarray technology. All genes that were found differentially expressed in response to either radiation type were up-regulated and predominantly controlled by p53. Quantitative PCR of selected genes revealed a significantly higher up-regulation 24 h after exposure to heavy ions as compared to X-rays, indicating their prolonged activation. This coincided with increased residual DNA damage as evidenced by quantitative γH2AX foci analysis. Furthermore, despite the converging p53 signature between radiation types, specific gene sets related to the immune response were significantly enriched in up-regulated genes following irradiation with heavy ions. In addition, irradiation, and in particular exposure to carbon ions, promoted transcript variation. Differences in basal and iron ion exposure-induced expression of DNA repair genes allowed the identification of a donor with distinct DNA repair profile. This suggests that gene signatures may serve as a sensitive indicator of individual DNA damage repair capacity. In conclusion, we have shown that photon and particle irradiation induce similar transcriptional pathways, albeit with variable amplitude and timing, but also elicit radiation type-specific responses that may have implications for cancer progression and treatment