Rapid High-Throughput Diagnostic Triage after a Mass Radiation Exposure Event Using Early Gene Expression Changes

Radiation-induced gastrointestinal and cutaneous injuries: understanding models, pathologies, assessments, and clinically accepted practices

PURPOSE

A U. S. and European joint effort fostering the development of medical countermeasures (MCMs) operable in case of radiological or nuclear emergencies.

METHODS

Based on the joint engagement between the U.S. National Institute of Allergy and Infectious Diseases (NIAID) and the French Institut de Radioprotection et de Sûreté Nucléaire (IRSN), a Statement of Intent to Collaborate was signed in 2014 and a series of working group meeting were established. In December 2022, the NIAID and IRSN hosted a five-day, U.S./European meeting titled 'Radiation-Induced Cutaneous and Gastrointestinal Injuries: Advances in Understanding Pathologies, Assessment, and Clinically Accepted Practices' in Paris, France. The goals of the meeting were to bring together U.S. and European investigators to explore new research avenues for the medical management of skin and gastrointestinal injuries, including specific diagnostics for each organ system, animal models, and promising medical countermeasures (MCMs) to mitigate radiation damage. There was also an emphasis on exploring additional areas of medicine and response to understand best practices from other emergency scenarios, which could be leveraged to improve radiation preparedness, and the importance of accurate dosimetry in preclinical work.

RESULTS

Subsequent to the workshop, seven collaborative projects, funded by both organizations, were established on topics ranging from MCMs and predictive biomarkers, and using physical methods to assess cutaneous radiation injuries, to mechanistic studies to understand radiation-induced damage in multiple organ systems. The importance of accurate dosimetry in preclinical works was highlighted and two recently published U.S./European commentaries that focus on the need for dosimetry standardization in the reported literature had their origins in this meeting. This commentary summarizes the workshop and open discussions among academic investigators, industry researchers, and U.S. and IRSN program representatives.

CONCLUSIONS

Given the substantive progress made due to these interactions, both groups plan to expand out these meetings by incorporating high-level investigators from across the globe, while endeavoring to maintain the informal setting that was conducive to in-depth scientific discussion and enhanced the state of the science in radiation research.

Validating a Four-gene Set for H-ARS Severity Prediction in Peripheral Blood Samples of Irradiated Rhesus Macaques

Increased radiological and nuclear threats require preparedness. Our earlier work identified a set of four genes (DDB2, FDXR, POU2AF1 and WNT3), which predicts severity of the hematological acute radiation syndrome (H-ARS) within the first three days postirradiation In this study of 41 Rhesus macaques (Macaca mulatta, 27 males, 14 females) irradiated with 5.8-7.2 Gy (LD29-50/60), including some treated with gamma-tocotrienol (GT3, a radiation countermeasure) we independently validated these genes as predictors in both sexes and examined them after three days. At the Armed Forces Radiobiology Research Institute/Uniformed Services University of the Health Sciences, peripheral whole blood (1 ml) of Rhesus macaques was collected into PAXgene® Blood RNA tubes pre-irradiation after 1, 2, 3, 35 and 60 days postirradiation, stored at -80°C for internal experimental analyses. Leftover tubes from these already ongoing studies were kindly provided to Bundeswehr Institute of Radiobiology. RNA was isolated (QIAsymphony), converted into cDNA, and for further gene expression (GE) studies quantitative RT-PCR was performed. Differential gene expression (DGE) was measured relative to the pre-irradiation Rhesus macaques samples. Within the first three days postirradiation, we found similar results to human data: 1. FDXR and DDB2 were up-regulated, FDXR up to 3.5-fold, and DDB2 up to 13.5-fold in the median; 2. POU2AF1 appeared down regulated around tenfold in nearly all Rhesus macaques; 3. Contrary to human data, DDB2 was more up-regulated than FDXR, and the difference of the fold change (FC) ranged between 2.4 and 10, while the median fold changes of WNT3, except days 1 and 35, were close to 1. Nevertheless, 46% of the Rhesus macaques showed down-regulated WNT3 on day one postirradiation, which decreased to 12.2% on day 3 postirradiation. Considering the extended phase, there was a trend towards decreased fold changes at day 35, with median-fold changes ranging from 0.7 for DDB2 to 0.1 for POU2AF1, and on day 60 postirradiation, DGE in surviving animals was close to pre-exposure values for all four genes. In conclusion, the diagnostic significance for radiation-induced H-ARS severity prediction of FDXR, DDB2, and POU2AF1 was confirmed in this Rhesus macaques model. However, DDB2 showed higher GE values than FDXR. As shown in previous studies, the diagnostic significance of WNT3 could not be reproduced in Rhesus macaques; this could be due to the choice of animal model and methodological challenges.

Development of a Point-of-Care Microfluidic RNA Extraction Slide for Gene Expression Diagnosis after Irradiation

In times of war, radiological/nuclear emergency scenarios have become a reemphasized threat. However, there are challenges in transferring whole-blood samples to laboratories for specialized diagnostics using RNA. This project aims to miniaturize the process of unwieldy conventional RNA extraction with its stationed technical equipment using a microfluidic-based slide (MBS) for point-of-care diagnostics. The MBS is thought to be a preliminary step toward the development of a so-called lab-on-a-chip microfluidic device. A MBS would enable early and fast field care combined with gene expression (GE) analysis for the prediction of hematologic acute radiation syndrome (HARS) severity or identification of RNA microbes. Whole blood samples from ten healthy donors were irradiated with 0, 0.5 and 4 Gy, simulating different ARS severity degrees. RNA quality and quantity of a preliminary MBS was compared with a conventional column-based (CB) RNA extraction method. GE of four HARS severity-predicting radiation-induced genes (FDXR, DDB2, POU2AF1 and WNT3) was examined employing qRT-PCR. Compared to the CB method, twice as much total RNA from whole blood could be extracted using the MBS (6.6 ± 3.2 µg vs. 12.0 ± 5.8 µg) in half of the extraction time, and all MBS RNA extracts appeared DNA-free in contrast to the CB method (30% were contaminated with DNA). Using MBS, RNA quality [RNA integrity number equivalent (RINe)] values decreased about threefold (3.3 ± 0.8 vs. 9.0 ± 0.4), indicating severe RNA degradation, while expected high-quality RINe ≥ 8 were found using column-based method. However, normalized cycle threshold (Ct) values, as well as radiation-induced GE fold-changes appeared comparable for all genes utilizing both methods, indicating that no RNA degradation took place. In summary, the preliminary MBS showed promising features such as: 1. halving the RNA extraction time without the burden of heavy technical equipment (e.g., a centrifuge); 2. absence of DNA contamination in contrast to CB RNA extraction; 3. reduction in blood required, because of twice the biological output of RNA; and 4. equal GE performance compared to CB, thus, increasing its appeal for later semi-automatic parallel field applications.

The Influence of Computed Tomography Contrast Agent on Radiation-Induced Gene Expression and Double-Strand Breaks

After nuclear scenarios, combined injuries of acute radiation syndrome (ARS) with, e.g., abdominal trauma, will occur and may require contrast-enhanced computed tomography (CT) scans for diagnostic purposes. Here, we investigated the effect of iodinated contrast agents on radiation-induced gene expression (GE) changes used for biodosimetry (AEN, BAX, CDKN1A, EDA2R, APOBEC3H) and for hematologic ARS severity prediction (FDXR, DDB2, WNT3, POU2AF1), and on the induction of double-strand breaks (DSBs) used for biodosimetry. Whole blood samples from 10 healthy donors (5 males, 5 females, mean age: 28 ± 2 years) were irradiated with X rays (0, 1 and 4 Gy) with and without the addition of iodinated contrast agent (0.016 ml contrast agent/ml blood) to the blood prior to the exposure. The amount of contrast agent was set to be equivalent to the blood concentration of an average patient (80 kg) during a contrast-enhanced CT scan. After irradiation, blood samples were incubated at 37°C for 20 min (DSB) and 8 h (GE, DSB). GE was measured employing quantitative real-time polymerase chain reaction. DSB foci were revealed by γH2AX + 53BP1 immunostaining and quantified automatically in >927 cells/sample. Radiation-induced differential gene expression (DGE) and DSB foci were calculated using the respective unexposed sample without supplementation of contrast agent as the reference. Neither the GE nor the number of DSB foci was significantly (P = 0.07-0.94) altered by the contrast agent application. However, for some GE and DSB comparisons with/without contrast agent, there were weakly significant differences (P = 0.03-0.04) without an inherent logic and thus are likely due to inter-individual variation. In nuclear events, the diagnostics of combined injuries can require the use of an iodinated contrast agent, which, according to our results, does not alter or influence radiation-induced GE changes and the quantity of DSB foci. Therefore, the gene expression and γH2AX focus assay can still be applied for biodosimetry and/or hematologic ARS severity prediction in such scenarios.

Applicability of Gene Expression in Saliva as an Alternative to Blood for Biodosimetry and Prediction of Radiation-induced Health Effects

As the great majority of gene expression (GE) biodosimetry studies have been performed using blood as the preferred source of tissue, searching for simple and less-invasive sampling methods is important when considering biodosimetry approaches. Knowing that whole saliva contains an ultrafiltrate of blood and white blood cells, it is expected that the findings in blood can also be found in saliva. This human in vivo study aims to examine radiation-induced GE changes in saliva for biodosimetry purposes and to predict radiation-induced disease, which is yet poorly characterized. Furthermore, we examined whether transcriptional biomarkers in blood can also be found equivalently in saliva. Saliva and blood samples were collected in parallel from radiotherapy (RT) treated patients who suffered from head and neck cancer (n = 8) undergoing fractioned partial-body irradiations (1.8 Gy/fraction and 50-70 Gy total dose). Samples were taken 12-24 h before first irradiation and ideally 24 and 48 h, as well as 5 weeks after radiotherapy onset. Due to the low quality and quantity of isolated RNA samples from one patient, they had to be excluded from further analysis, leaving a total of 24 saliva and 24 blood samples from 7 patients eligible for analysis. Using qRT-PCR, 18S rRNA and 16S rRNA (the ratio being a surrogate for the relative human RNA/bacterial burden), four housekeeping genes and nine mRNAs previously identified as radiation responsive in blood-based studies were detected. Significant GE associations with absorbed dose were found for five genes and after the 2nd radiotherapy fraction, shown by, e.g., the increase of CDKN1A (2.0 fold, P = 0.017) and FDXR (1.9 fold increased, P = 0.002). After the 25th radiotherapy fraction, however, all four genes (FDXR, DDB2, POU2AF1, WNT3) predicting ARS (acute radiation syndrome) severity, as well as further genes (including CCNG1 [median-fold change (FC) = 0.3, P = 0.013], and GADD45A (median-FC = 0.3, P = 0.031)) appeared significantly downregulated (FC = 0.3, P = 0.01-0.03). A significant association of CCNG1, POU2AF1, HPRT1, and WNT3 (P = 0.006-0.04) with acute or late radiotoxicity could be shown before the onset of these clinical outcomes. In an established set of four genes predicting acute health effects in blood, the response in saliva samples was similar to the expected up- (FDXR, DDB2) or downregulation (POU2AF1, WNT3) in blood for up to 71% of the measurements. Comparing GE responses (PHPT1, CCNG1, CDKN1A, GADD45A, SESN1) in saliva and blood samples, there was a significant linear association between saliva and blood response of CDKN1A (R2 = 0.60, P = 0.0004). However, the GE pattern of other genes differed between saliva and blood. In summary, the current human in vivo study, (I) reveals significant radiation-induced GE associations of five transcriptional biomarkers in salivary samples, (II) suggests genes predicting diverse clinical outcomes such as acute and late radiotoxicity as well as ARS severity, and (III) supports the view that blood-based GE response can be reflected in saliva samples, indicating that saliva is a "mirror of the body" for certain but not all genes and, thus, studies for each gene of interest in blood are required for saliva.

PUM1 and PGK1 are Favorable Housekeeping Genes over Established Biodosimetry-related Housekeeping Genes such as HPRT1, ITFG1, DPM1, MRPS5, 18S rRNA and Others after Radiation Exposure

In gene expression (GE) studies, housekeeping genes (HKGs) are required for normalization purposes. In large-scale inter-laboratory comparison studies, significant differences in dose estimates are reported and divergent HKGs are employed by the teams. Among them, the 18S rRNA HKG is known for its robustness. However, the high abundance of 18S rRNA copy numbers requires dilution, which is time-consuming and a possible source of errors. This study was conducted to identify the most promising HKGs showing the least radiation-induced GE variance after radiation exposure. In the screening stage of this study, 35 HKGs were analyzed. This included selected HKGs (ITFG1, MRPS5, and DPM1) used in large-scale biodosimetry studies which were not covered on an additionally employed pre-designed 96-well platform comprising another 32 HKGs used for different exposures. Altogether 41 samples were examined, including 27 ex vivo X-ray irradiated blood samples (0, 0.5, 4 Gy), six X-irradiated samples (0, 0.5, 5 Gy) from two cell lines (U118, A549), as well as eight non-irradiated tissue samples to encompass multiple biological entities. In the independent validation stage, the most suitable candidate genes were examined from another 257 blood samples, taking advantage of already stored material originating from three studies. These comprise 100 blood samples from ex vivo X-ray irradiated (0-4 Gy) healthy donors, 68 blood samples from 5.8 Gy irradiated (cobalt-60) Rhesus macaques (RM) (LD29/60) collected 0-60 days postirradiation, and 89 blood samples from chemotherapy-(CTx) treated breast tumor patients. CTx and radiation-induced GE changes in previous studies appeared comparable. RNA was isolated, converted into cDNA, and GE was quantified employing TaqMan assays and quantitative RT-PCR. We calculated the standard deviation (SD) and the interquartile range (IQR) as measures of GE variance using raw cycle threshold (Ct) values and ranked the HKGs accordingly. Dose, time, age, and sex-dependent GE changes were examined employing the parametrical t-test and non-parametrical Kruskal Wallis test, as well as linear regression analysis. Generally, similar ranking results evolved using either SD or IQR GE measures of variance, indicating a tight distribution of GE values. PUM1 and PGK1 showed the lowest variance among the first ten most suitable genes in the screening phase. MRPL19 revealed low variance among the first ten most suitable genes in the screening phase only for blood and cells, but certain comparisons indicated a weak association of MRPL19 with dose (P = 0.02-0.09). In the validation phase, these results could be confirmed. Here, IQR Ct values from, e.g., X-irradiated blood samples were 0.6 raw Ct values for PUM1 and PGK1, which is considered to represent GE differences as expected due to methodological variance. Overall, when compared, the GE variance of both genes was either comparable or lower compared to 18S rRNA. Compared with the IQR GE values of PUM1 and PGKI, twofold-fivefold increased values were calculated for the biodosimetry HKG HPRT1, and comparable values were calculated for biodosimetry HKGs ITFG1, MRPS5, and DPM1. Significant dose-dependent associations were found for ITFG1 and MRPS5 (P = 0.001-0.07) and widely absent or weak (P = 0.02-0.07) for HPRT1 and DPM1. In summary, PUM1 and PGK1 appeared most promising for radiation exposure studies among the 35 HKGs examined, considering GE variance and adverse associations of GE with dose.

Validation of genes for H-ARS severity prediction in leukemia patients - interspecies comparison, challenges, and promises

PURPOSE

In a previous baboon-study, a total of 29 genes were identified for clinical outcome prediction of the hematologic, acute, radiation, syndrome (H-ARS) severity. Among them, four genes (FDXR, DDB2, POU2AF1, WNT3) appeared promising and were validated in five leukemia patients. Within this study, we sought further in-vivo validation in a larger number of whole-body irradiated patients.

MATERIAL AND METHODS

Peripheral blood was drawn from 10 leukemia patients before and up to 3 days during a fractionated (2 Gy/day) total-body irradiation (TBI) with 2-12Gy. After RNA-isolation, gene expression (GE) was evaluated on 31 genes widely used in biodosimetry and H-ARS prediction employing qRT-PCR. A customized low-density-array (LDA) allowed simultanously analyzing all genes, the 96-well format further examined the four most promising genes. Fold-changes (FC) in GE relative to pre-irradiation were calculated.

RESULTS

Five patients suffering from acute-lymphoblastic-leukemia (ALL) respectively non-Hodgkin-lymphoma (NHL) revealed sufficient RNA-amounts and corresponding lymphocyte and neutrophile counts for running qRT-PCR, while acute-myeloid-leukemia (AML) and one myelofibrosis patient could not supply enough RNA. Generally, 1-2µg total RNA was isolated, whereas up to 10-fold differences in RNA-quantities (associated suppressed GE-changes) were identified among pre-exposure and exposure samples. From 31 genes, 23 were expressed in at least one of the pre-exposure samples. Relative to pre-exposure, the number of expressed genes could halve at 48 and 72h after irradiation. Using the LDA, 13 genes were validated in human samples. The four most promising genes (vid. sup.) were either undetermined or too close to pre-exposure. However, they were measured using the more sensitive 96-well format, except WNT3, which wasn´t detectable. As in previous studies, an opposite regulation in GE for FDXR in leukemia patients (up-regulated) relative to baboons (down-regulated) was reconfirmed. Radiation-induced GE-changes of DDB2 (up-regulated) and POU2AF1 (down-regulated) behaved similarly in both species. Hence, 16 out of 23 genes of two species showed GE-changes in the same direction, and up-regulated FDXR as in human studies were revalidated.

CONCLUSION

Identified genes for H-ARS severity prediction, previously detected in baboons, were validated in ALL but not in AML patients. Limitations related to leukemia type, associated reduced RNA amounts, suppressed GE changes, and methodological challenges must be considered as factors negatively affecting the total number of validated genes. Based on that, we propose additional controls including blood cell counts and preferably fluorescence-based RNA quantity measurements for selecting promising samples and using a more sensitive 96-well format for candidate genes with low baseline copy numbers.

Development of high-throughput systems for biodosimetry

Biomarkers for ionising radiation exposure have great utility in scenarios where there has been a potential exposure and physical dosimetry is missing or in dispute, such as for occupational and accidental exposures. Biomarkers that respond as a function of dose are particularly useful as biodosemeters to determine the dose of radiation to which an individual has been exposed. These dose measurements can also be used in medical scenarios to track doses from medical exposures and even have the potential to identify an individual's response to radiation exposure that could help tailor treatments. The measurement of biomarkers of exposure in medicine and for accidents, where a larger number of samples would be required, is limited by the throughput of analysis (i.e. the number of samples that could be processed and analysed), particularly for microscope-based methods, which tend to be labour-intensive. Rapid analysis in an emergency scenario, such as a large-scale accident, would provide dose estimates to medical practitioners, allowing timely administration of the appropriate medical countermeasures to help mitigate the effects of radiation exposure. In order to improve sample throughput for biomarker analysis, much effort has been devoted to automating the process from sample preparation through automated image analysis. This paper will focus mainly on biological endpoints traditionally analysed by microscopy, specifically dicentric chromosomes, micronuclei and gamma-H2AX. These endpoints provide examples where sample throughput has been improved through automated image acquisition, analysis of images acquired by microscopy, as well as methods that have been developed for analysis using imaging flow cytometry.

Evaluating transport conditions of conventional, widely used EDTA blood tubes for gene expression analysis in comparison to expensive, specialized PAXgene tubes in preparedness for radiological and nuclear events

PURPOSE

Gene expression (GE) analysis of a radio-sensitive gene set (FDXR, DDB2, WNT3, POU2AF1) has been introduced in the last decade as an early and high-throughput prediction tool of later developing acute hematologic radiation syndrome (H-ARS) severity. The use of special tubes for RNA extraction from peripheral whole blood (PAXgene) represent an established standard in GE studies, although uncommonly used in clinics and not immediately available in the quantities needed in radiological/nuclear (R/N) incidents. On the other hand, EDTA blood tubes are widely utilized in clinical practice.

MATERIAL AND METHODS

Using blood samples from eleven healthy donors, we investigated GE changes associated with delayed processing of EDTA tubes up to 4 h at room temperature (RT) after venipuncture (simulating delays caused by daily clinical routine), followed by a subsequent transport time of 24 h at RT, 4 °C, and -20 °C. Differential gene expression (DGE) of the target genes was further examined after X-irradiation with 0 Gy and 4 Gy under optimal transport conditions.

RESULTS

No significant changes in DGE were observed when storing EDTA whole blood samples up to 4 h at RT and subsequently kept at 4 °C for 24 h which is in line with expected DGE. However, other storage conditions, such as -20 °C or RT, decreased RNA quality and/or (significantly) caused changes in DGE exceeding the known methodological variance of the qRT-PCR.

CONCLUSION

Our data indicate that the use of EDTA whole blood tubes for GE-based H-ARS severity prediction is comparable to the quality of PAXgene tubes, when processed ≤ 4 h after venipuncture and the sample is transported within 24 hours at 4 °C.

The DNA damage response to radiological imaging: from ROS and γH2AX foci induction to gene expression responses in vivo

Candidate ionising radiation exposure biomarkers must be validated in humans exposed in vivo. Blood from patients undergoing positron emission tomography-computed tomography scan (PET-CT) and skeletal scintigraphy (scintigraphy) was drawn before (0 h) and after (2 h) the procedure for correlation analyses of the response of selected biomarkers with radiation dose and other available patient information. FDXR, CDKN1A, BBC3, GADD45A, XPC, and MDM2 expression was determined by qRT-PCR, DNA damage (γH2AX) by flow cytometry, and reactive oxygen species (ROS) levels by flow cytometry using the 2', 7'-dichlorofluorescein diacetate test in peripheral blood mononuclear cells (PBMC). For ROS experiments, 0- and 2-h samples were additionally exposed to UVA to determine whether diagnostic irradiation conditioned the response to further oxidative insult. With some exceptions, radiological imaging induced weak γH2AX foci, ROS and gene expression fold changes, the latter with good coherence across genes within a patient. Diagnostic imaging did not influence oxidative stress in PBMC successively exposed to UVA. Correlation analyses with patient characteristics led to low correlation coefficient values. γH2AX fold change, which correlated positively with gene expression, presented a weak positive correlation with injected activity, indicating a radiation-induced subtle increase in DNA damage and subsequent activation of the DNA damage response pathway. The exposure discrimination potential of these biomarkers in the absence of control samples as frequently demanded in radiological emergencies, was assessed using raw data. These results suggest that the variability of the response in heterogeneous populations might complicate identifying individuals exposed to low radiation doses.

RENEB Inter-Laboratory Comparison 2021: Inter-Assay Comparison of Eight Dosimetry Assays

Tools for radiation exposure reconstruction are required to support the medical management of radiation victims in radiological or nuclear incidents. Different biological and physical dosimetry assays can be used for various exposure scenarios to estimate the dose of ionizing radiation a person has absorbed. Regular validation of the techniques through inter-laboratory comparisons (ILC) is essential to guarantee high quality results. In the current RENEB inter-laboratory comparison, the performance quality of established cytogenetic assays [dicentric chromosome assay (DCA), cytokinesis-block micronucleus assay (CBMN), stable chromosomal translocation assay (FISH) and premature chromosome condensation assay (PCC)] was tested in comparison to molecular biological assays [gamma-H2AX foci (gH2AX), gene expression (GE)] and physical dosimetry-based assays [electron paramagnetic resonance (EPR), optically or thermally stimulated luminescence (LUM)]. Three blinded coded samples (e.g., blood, enamel or mobiles) were exposed to 0, 1.2 or 3.5 Gy X-ray reference doses (240 kVp, 1 Gy/min). These doses roughly correspond to clinically relevant groups of unexposed to low exposed (0-1 Gy), moderately exposed (1-2 Gy, no severe acute health effects expected) and highly exposed individuals (>2 Gy, requiring early intensive medical care). In the frame of the current RENEB inter-laboratory comparison, samples were sent to 86 specialized teams in 46 organizations from 27 nations for dose estimation and identification of three clinically relevant groups. The time for sending early crude reports and more precise reports was documented for each laboratory and assay where possible. The quality of dose estimates was analyzed with three different levels of granularity, 1. by calculating the frequency of correctly reported clinically relevant dose categories, 2. by determining the number of dose estimates within the uncertainty intervals recommended for triage dosimetry (±0.5 Gy or ±1.0 Gy for doses <2.5 Gy or >2.5 Gy), and 3. by calculating the absolute difference (AD) of estimated doses relative to the reference doses. In total, 554 dose estimates were submitted within the 6-week period given before the exercise was closed. For samples processed with the highest priority, earliest dose estimates/categories were reported within 5-10 h of receipt for GE, gH2AX, LUM, EPR, 2-3 days for DCA, CBMN and within 6-7 days for the FISH assay. For the unirradiated control sample, the categorization in the correct clinically relevant group (0-1 Gy) as well as the allocation to the triage uncertainty interval was, with the exception of a few outliers, successfully performed for all assays. For the 3.5 Gy sample the percentage of correct classifications to the clinically relevant group (≥2 Gy) was between 89-100% for all assays, with the exception of gH2AX. For the 1.2 Gy sample, an exact allocation to the clinically relevant group was more difficult and 0-50% or 0-48% of the estimates were wrongly classified into the lowest or highest dose categories, respectively. For the irradiated samples, the correct allocation to the triage uncertainty intervals varied considerably between assays for the 1.2 Gy (29-76%) and 3.5 Gy (17-100%) samples. While a systematic shift towards higher doses was observed for the cytogenetic-based assays, extreme outliers exceeding the reference doses 2-6 fold were observed for EPR, FISH and GE assays. These outliers were related to a particular material examined (tooth enamel for EPR assay, reported as kerma in enamel, but when converted into the proper quantity, i.e. to kerma in air, expected dose estimates could be recalculated in most cases), the level of experience of the teams (FISH) and methodological uncertainties (GE). This was the first RENEB ILC where everything, from blood sampling to irradiation and shipment of the samples, was organized and realized at the same institution, for several biological and physical retrospective dosimetry assays. Almost all assays appeared comparably applicable for the identification of unexposed and highly exposed individuals and the allocation of medical relevant groups, with the latter requiring medical support for the acute radiation scenario simulated in this exercise. However, extreme outliers or a systematic shift of dose estimates have been observed for some assays. Possible reasons will be discussed in the assay specific papers of this special issue. In summary, this ILC clearly demonstrates the need to conduct regular exercises to identify research needs, but also to identify technical problems and to optimize the design of future ILCs.

RENEB Inter-Laboratory Comparison 2021: The Gene Expression Assay

Early and high-throughput individual dose estimates are essential following large-scale radiation exposure events. In the context of the Running the European Network for Biodosimetry and Physical Dosimetry (RENEB) 2021 exercise, gene expression assays were conducted and their corresponding performance for dose-assessment is presented in this publication. Three blinded, coded whole blood samples from healthy donors were exposed to 0, 1.2 and 3.5 Gy X-ray doses (240 kVp, 1 Gy/min) using the X-ray source Yxlon. These exposures correspond to clinically relevant groups of unexposed, low dose (no severe acute health effects expected) and high dose exposed individuals (requiring early intensive medical health care). Samples were sent to eight teams for dose estimation and identification of clinically relevant groups. For quantitative reverse transcription polymerase chain reaction (qRT-PCR) and microarray analyses, samples were lysed, stored at 20°C and shipped on wet ice. RNA isolations and assays were run in each laboratory according to locally established protocols. The time-to-result for both rough early and more precise later reports has been documented where possible. Accuracy of dose estimates was calculated as the difference between estimated and reference doses for all doses (summed absolute difference, SAD) and by determining the number of correctly reported dose estimates that were defined as ±0.5 Gy for reference doses <2.5 Gy and ±1.0 Gy for reference doses >3 Gy, as recommended for triage dosimetry. We also examined the allocation of dose estimates to clinically/diagnostically relevant exposure groups. Altogether, 105 dose estimates were reported by the eight teams, and the earliest report times on dose categories and estimates were 5 h and 9 h, respectively. The coefficient of variation for 85% of all 436 qRT-PCR measurements did not exceed 10%. One team reported dose estimates that systematically deviated several-fold from reported dose estimates, and these outliers were excluded from further analysis. Teams employing a combination of several genes generated about two-times lower median SADs (0.8 Gy) compared to dose estimates based on single genes only (1.7 Gy). When considering the uncertainty intervals for triage dosimetry, dose estimates of all teams together were correctly reported in 100% of the 0 Gy, 50% of the 1.2 Gy and 50% of the 3.5 Gy exposed samples. The order of dose estimates (from lowest to highest) corresponding to three dose categories (unexposed, low dose and highest exposure) were correctly reported by all teams and all chosen genes or gene combinations. Furthermore, if teams reported no exposure or an exposure >3.5 Gy, it was always correctly allocated to the unexposed and the highly exposed group, while low exposed (1.2 Gy) samples sometimes could not be discriminated from highly (3.5 Gy) exposed samples. All teams used FDXR and 78.1% of correct dose estimates used FDXR as one of the predictors. Still, the accuracy of reported dose estimates based on FDXR differed considerably among teams with one team's SAD (0.5 Gy) being comparable to the dose accuracy employing a combination of genes. Using the workflow of this reference team, we performed additional experiments after the exercise on residual RNA and cDNA sent by six teams to the reference team. All samples were processed similarly with the intention to improve the accuracy of dose estimates when employing the same workflow. Re-evaluated dose estimates improved for half of the samples and worsened for the others. In conclusion, this inter-laboratory comparison exercise enabled (1) identification of technical problems and corrections in preparations for future events, (2) confirmed the early and high-throughput capabilities of gene expression, (3) emphasized different biodosimetry approaches using either only FDXR or a gene combination, (4) indicated some improvements in dose estimation with FDXR when employing a similar methodology, which requires further research for the final conclusion and (5) underlined the applicability of gene expression for identification of unexposed and highly exposed samples, supporting medical management in radiological or nuclear scenarios.

Radiation-Induced Gene Expression Changes Used for Biodosimetry and Clinical Outcome Prediction: Challenges and Promises

As the war in Ukraine progresses, the radiological and nuclear threat has never been as real as now. The formation of life-threatening acute radiation syndrome (ARS), in particular after the deployment of a nuclear weapon or an attack on a nuclear power station, must be considered realistic. ARS is caused by massive cell death, leading to functional organ deficits and, via systemic inflammatory responses, finally aggravates into multiple organ failure. As a deterministic effect, the severity of the disease dictates the clinical outcome. Hence, predicting ARS severity via biodosimetry or alternative approaches appears straightforward. Because the disease occurs delayed, therapy starting as early as possible has the most significant benefit. A clinically relevant diagnosis should be carried out within the diagnostic time window of about 3 days after exposure. Biodosimetry assays providing retrospective dose estimations within this time frame will support medical management decision-making. However, how closely can dose estimates be associated with the later developing ARS severity degrees when considering dose as one among other determinants of radiation exposure and cell death? From a clinical/triage point of view, ARS severity degrees can be further aggregated into unexposed, weakly diseased (no acute health effects expected), and strongly diseased patient groups, with the latter requiring hospitalization as well as an early and intensive treatment. Radiation-induced gene expression (GE) changes occur early after exposure and can be quickly quantified. GE can be used for biodosimetry purposes. Can GE be used to predict later developing ARS severity degrees and allocate individuals to the three clinically relevant groups as well?

Ex-vivo dose response characterization of the recently identified EDA2R gene after low level radiation exposures and comparison with FDXR gene expression and the γH2AX focus assay

OBJECTIVE

Recently, promising radiation-induced EDA2R gene expression (GE) changes after low level radiation could be shown. Stimulated by that, in this study, we intended to independently validate these findings and to further characterize dose-response relationships in comparison to FDXR and the γH2AX-DNA double-strand break (DSB) focus assay, since both assays are already widely used for biodosimetry purposes.

MATERIALS AND METHODS

Peripheral blood samples from six healthy human donors were irradiated ex vivo (dose: ranging from 2.6 to 49.7 mGy). Subsequently, the fold-differences relative to the sham irradiated reference group were calculated. Radiation-induced changes in GE of FDXR and EDA2R were examined using the quantitative real-time polymerase-chain-reaction (qRT-PCR). DSB foci were quantified in 100 γH2AX + 53BP1 immunostained cells employing fluorescence microscopy. Examinations were performed at single time points enabling sufficient detection of both endpoints.

RESULTS

A significant increase in EDA2R GE relative to the unexposed control was observed in the range of 2.6 mGy (1.6-fold, p = .045) to 5.4 mGy (2.2-fold, p = .0002), whereas the copy numbers increased linearly up to 13.1-fold at 49.7 mGy. On the contrary, FDXR upregulation (2.2-fold) became significant after a 22.6 mGy exposure (p ≤ .02) and increased linearly up to 4-fold at 49.7 mGy. A significant increase in radiation-induced foci (relative to unexposed, RIF-fd) was observed after 11.3 mGy (RIF-fd: 1.5 ± 0.5, p ≤ .03), while the foci increased linearly up to 3-fold at 49.7 mGy. From this, the FDXR and RIF-fd slopes have shown comparability, while the EDA2R slope was five times higher. Nevertheless, the coefficient of variation (CV) of EDA2R was about 30% higher than for RIF-fd.

CONCLUSION

Higher radiation-induced EDA2R GE changes and a lower radiation detection level compared to RIF-fd and FDXR GE changes examined under optimal conditions ex vivo on human samples appear promising. Yet, our results represent just the beginning of further studies to be conducted in animal models for further time- and dose-dependent evaluation and additional examinations on radiologically examined patients to evaluate the impact of confounder, such as age, sex, social behavior, or diseases.

Four Genes Predictive for the Severity of Hematological Damage Reveal a Similar Response after X Irradiation and Chemotherapy

Radiological and especially nuclear accidents and incidents pose a threat to populations. In such events, gene expression (GE) analysis of a set of 4 genes (FDXR, DDB2, POU2AF1, WNT3) is an emerging approach for early and high-throughput prediction of the later manifesting severity degrees of the hematological acute radiation syndrome (H-ARS). Validation of this gene set on radiation victims is difficult since these events are rare. However, chemotherapy (CTX) is widely used e.g., breast cancer patient treatment and pathomechanisms, as well as blood cell count changes are comparable among both exposure types. We wondered whether GE changes are similarly deregulated after CTX, which would be interpreted as a confirmation of our already identified gene set for H-ARS prediction after irradiation. We examined radiation-induced differential GE (DGE) of our gene set as a positive control using in vitro whole blood samples from ten healthy donors (6 females, 4 males, aged: 24-40 years). Blood was incubated in vitro for 8 h after X irradiation with 0 and 4 Gy (1 Gy/min). These data were compared with DGE measured in vivo in blood samples of 10 breast tumor CTX patients (10 females, aged: 39-71 years) before and 4 days after administration of cyclophosphamide and epirubicin. RNA was isolated, reverse transcribed and quantitative real-time polymerase-chain-reaction (qRT-PCR) was performed to assess DGE of FDXR, DDB2, POU2AF1 and WNT3 relative to the unexposed samples using TaqMan assays. After X irradiation, we found a significant upregulation (irrespective of sex) with mean fold changes of 21 (P < 0.001) and 7 (P < 0.001) for FDXR and DDB2 and a significant down-regulation with mean fold changes of 2.5 (P < 0.001) and 2 (P = 0.005) for POU2AF1 and WNT3, respectively. After CTX, a similar pattern was observed, although mean fold changes of up-regulated FDXR (6-fold, P < 0.001) and DDB2 (3-fold, P < 0.001) as well as down-regulated POU2AF1 (1.2-fold, P = 0.270) and WNT3 (1.3-fold, P = 0.069) appeared lower corresponding to less altered blood cell count changes observed after CTX compared to historic radiation exposure data. However, a subpopulation of CTX patients (n = 6) showed on average a significant downregulation of POU2AF1 (1.8-fold, P = 0.04) and WNT3 (2.1-fold, P = 0.008). In summary, the pattern of up-regulated GE changes observed in all CTX patients and down-regulated GE changes observed in a subgroup of CTX patients appeared comparable with an already identified gene set predictive for the radiation-induced H-ARS. This underlines the significance of in vivo GE measurements in CTX patients, employed as a surrogate model to further validate already identified radiation-induced GE changes predictive for the H-ARS.

A Review of Radiation-Induced Alterations of Multi-Omic Profiles, Radiation Injury Biomarkers, and Countermeasures

Increasing utilization of nuclear power enhances the risks associated with industrial accidents, occupational hazards, and the threat of nuclear terrorism. Exposure to ionizing radiation interferes with genomic stability and gene expression resulting in the disruption of normal metabolic processes in cells and organs by inducing complex biological responses. Exposure to high-dose radiation causes acute radiation syndrome, which leads to hematopoietic, gastrointestinal, cerebrovascular, and many other organ-specific injuries. Altered genomic variations, gene expression, metabolite concentrations, and microbiota profiles in blood plasma or tissue samples reflect the whole-body radiation injuries. Hence, multi-omic profiles obtained from high-resolution omics platforms offer a holistic approach for identifying reliable biomarkers to predict the radiation injury of organs and tissues resulting from radiation exposures. In this review, we performed a literature search to systematically catalog the radiation-induced alterations from multi-omic studies and radiation countermeasures. We covered radiation-induced changes in the genomic, transcriptomic, proteomic, metabolomic, lipidomic, and microbiome profiles. Furthermore, we have covered promising multi-omic biomarkers, FDA-approved countermeasure drugs, and other radiation countermeasures that include radioprotectors and radiomitigators. This review presents an overview of radiation-induced alterations of multi-omics profiles and biomarkers, and associated radiation countermeasures.

Identifying radiation responsive exon-regions of genes often used for biodosimetry and acute radiation syndrome prediction

Gene expression (GE) analysis of FDXR, DDB2, WNT3 and POU2AF1 is a promising approach for identification of clinically relevant groups (unexposed, low- and high exposed) after radiological/nuclear events. However, results from international biodosimetry exercises have shown differences in dose estimates based on radiation-induced GE of the four genes. Also, differences in GE using next-generation-sequening (NGS) and validation with quantitative real-time polymerase chain reaction (qRT-PCR) was reported. These discrepancies could be caused by radiation-responsive differences among exons of the same gene. We performed GE analysis with qRT-PCR using TaqMan-assays covering all exon-regions of FDXR, DDB2, WNT3 and POU2AF1. Peripheral whole blood from three healthy donors was X-irradiated with 0, 0.5 and 4 Gy. After 24 and 48 h a dose-dependent up-regulation across almost all exon-regions for FDXR and DDB2 (4–42-fold) was found. A down-regulation for POU2AF1 (two- to threefold) and WNT3 (< sevenfold) at the 3’-end was found at 4 Gy irradiation only. Hence, this confirms our hypothesis for radiation-responsive exon-regions for WNT3 and POU2AF1, but not for FDXR and DDB2. Finally, we identified the most promising TaqMan-assays for FDXR (e.g. AR7DTG3, Hs00244586_m1), DDB2 (AR47X6H, Hs03044951_m1), WNT3 (Hs00902258_m1, Hs00902257_m1) and POU2AF1 (Hs01573370_g1, Hs01573371_m1) for biodosimetry purposes and acute radiation syndrome prediction, considering several criteria (detection limit, dose dependency, time persistency, inter-individual variability).

Early molecular markers for retrospective biodosimetry and prediction of acute health effects

Radiation-induced biological changes occurring within hours and days after irradiation can be potentially used for either exposure reconstruction (retrospective dosimetry) or the prediction of consecutively occurring acute or chronic health effects. The advantage of molecular protein or gene expression (GE) (mRNA) marker lies in their capability for early (1-3 days after irradiation), high-throughput and point-of-care diagnosis, required for the prediction of the acute radiation syndrome (ARS) in radiological or nuclear scenarios. These molecular marker in most cases respond differently regarding exposure characteristics such as e.g. radiation quality, dose, dose rate and most importantly over time. Changes over time are in particular challenging and demand certain strategies to deal with. With this review, we provide an overview and will focus on already identified and used mRNA GE and protein markers of the peripheral blood related to the ARS. These molecules are examined in light of 'ideal' characteristics of a biomarkers (e.g. easy accessible, early response, signal persistency) and the validation degree. Finally, we present strategies on the use of these markers considering challenges as their variation over time and future developments regarding e.g. origin of samples, point of care and high-throughput diagnosis.

mRNA and small RNA gene expression changes in peripheral blood to detect internal Ra-223 exposure

PURPOSE

Excretion analysis is the established method for detection of incorporated alpha-emitting radionuclides, but it is laborious and time consuming. We sought a simplified method in which changes in gene expression might be measured in human peripheral blood to detect incorporated radionuclides. Such an approach could be used to quickly determine internal exposure in instances of a radiological dispersal device or a radiation accident.

MATERIALS AND METHODS

We evaluated whole blood samples from five patients with castration-resistant prostate cancer and multiple bone metastases (without visceral or nodal involvement), who underwent treatment with the alpha emitting isotope Radium-223 dichloride (Ra-223, Xofigo^®). Patients received about 4 MBq per cycle and, depending on survival and treatment tolerance, were followed for six months. We collected 24 blood samples approximately monthly corresponding to treatment cycle.

RESULTS

Firstly, we conducted whole genome screening of mRNAs (mRNA seq) and small RNAs (small RNA seq) using next generation sequencing in one patient at eight different time points during all six cycles of Ra-223-therapy. We identified 1900 mRNAs and 972 small RNAs (222 miRNAs) that were differentially up- or down-regulated during follow-up after the first treatment with Ra-223. Overall candidate RNA species inclusion criteria were a general (≥|2|-fold) change or with peaking profiles (≥|5|-fold) at specific points in time. Next we chose 72 candidate mRNAs and 101 small RNAs (comprising 29 miRNAs) for methodologic (n = 8 samples, one patient) and independent (n = 16 samples, four patients) validation by qRT-PCR. In total, 15 mRNAs (but no small RNAs) were validated by methodologic and independent testing. However, the deregulation occurred at different time points, showing a large inter-individual variability in response among patients.

CONCLUSIONS

This proof of concept provides support for the applicability of gene expression measurements to detect internalized alpha-emitting radionuclides, but further work is needed with a larger sample size. While our approach has merit for internal deposition monitoring, it was complicated by the severe clinical condition of the patients we studied.

Development of Biomarkers for Radiation Biodosimetry and Medical Countermeasures Research: Current Status, Utility, and Regulatory Pathways

Biomarkers are important indicators of biological processes in health or disease. For this reason, they play a critical role in advanced development of radiation biodosimetry tools and medical countermeasures (MCMs). They can aid in the assessment of radiation exposure level, extent of radiation-induced injury, and/or efficacy of an MCM. This meeting report summarizes the presentations and discussions from the 2020 workshop titled, "Biomarkers in Radiation Biodosimetry and Medical Countermeasures," sponsored by the Radiation and Nuclear Countermeasures Program (RNCP) at the National Institute of Allergy and Infectious Diseases (NIAID). The main goals of this meeting were to: 1. Provide an overview on biomarkers and to focus on the state of science with regards to biomarkers specific to radiation biodosimetry and MCMs; 2. Understand developmental challenges unique to the role of biomarkers in the fields of radiation biodosimetry and MCM development; and 3. Identify existing gaps and needs for translational application.

Early-response multiple-parameter biodosimetry and dosimetry: risk predictions

The accepted generic multiple-parameter and early-response biodosimetry and dosimetry assessment approach for suspected high-dose radiation (i.e. life-threatening) exposure includes measuring radioactivity associated with the exposed individual (if appropriate); observing and recording prodromal signs/symptoms; obtaining serial complete blood counts with white-blood-cell differential; sampling blood for the chromosome-aberration cytogenetic bioassay using the 'gold standard' dicentric assay (premature chromosome condensation assay for exposures >5 Gy photon acute doses equivalent), measurement of proteomic biomarkers and gene expression assays for dose assessment; bioassay sampling, if appropriate, to determine radioactive internal contamination; physical dose reconstruction, and using other available opportunistic dosimetry approaches. Biodosimetry and dosimetry resources are identified and should be setup in advance along with agreements to access additional national, regional, and international resources. This multifaceted capability needs to be integrated into a biodosimetry/dosimetry 'concept of operations' for use in a radiological emergency. The combined use of traditional biological-, clinical-, and physical-dosimetry should be use in an integrated approach to provide: (a) early-phase diagnostics to guide the development of initial medical-management strategy, and (b) intermediate and definitive assessment of radiation dose and injury. Use of early-phase (a) clinical signs and symptoms, (b) blood chemistry biomarkers, and (c) triage cytogenetics shows diagnostic utility to predict acute radiation injury severity.

Training of clinical triage of acute radiation casualties: a performance comparison ofon-siteversusonlinetraining due to the covid-19 pandemic

A collection of powerful diagnostic tools have been developed under the umbrellas of NATO for ionising radiation dose assessment (BAT, WinFRAT) and estimate of acute health effects in humans (WinFRAT, H-Module). We assembled a database of 191 ARS cases using the medical treatment protocols for radiation accident victims (n= 167) and the system for evaluation and archiving of radiation accidents based on case histories (n= 24) for training purposes of medical personnel. From 2016 to 2019, we trained 39 participants comprising MSc level radiobiology students in an on-site teaching class. Enforced by the covid-19 pandemic in 2020 for the first time, an online teaching of nine MSc radiobiology students replaced the on-site teaching. We found that: (a) limitations of correct diagnostic decision-making based on clinical signs and symptoms were experienced unrelated to the teaching format. (b) A significant performance decrease concerning online (first number in parenthesis) versus on-site teaching (reference and second number in parenthesis) was seen regarding the estimate time (31 vs 61 cases per hour, two-fold decrease,p= 0.005). Also, the accurate assessment of response categories (89.9% vs 96.9%,p= 0.001), ARS (92.4% vs 96.7%,p= 0.002) and hospitalisation (93.5% vs 97.0%,p= 0.002) decreased by around 3%-7%. The performances of the online attendees were mainly distributed within the lower quartile performance of on-site participants and the 25%-75% interquartile range increased 3-7-fold. (c) Comparison of dose estimates performed by training participants with hematologic acute radiation syndrome (HARS) severity mirrored the known limitations of dose alone as a surrogate parameter for HARS severity at doses less than 1.5 Gy, but demonstrated correct determination of HARS 2-4 and support for clinical decision making at dose estimates >1.5 Gy, regardless of teaching format. (d) Overall, one-third of the online participants showed substantial misapprehension and insecurities of elementary course content that did not occur after the on-site teaching.

Gene expression for biodosimetry and effect prediction purposes: promises, pitfalls and future directions - key session ConRad 2021

PURPOSE

In a nuclear or radiological event, an early diagnostic or prognostic tool is needed to distinguish unexposed from low- and highly exposed individuals with the latter requiring early and intensive medical care. Radiation-induced gene expression (GE) changes observed within hours and days after irradiation have shown potential to serve as biomarkers for either dose reconstruction (retrospective dosimetry) or the prediction of consecutively occurring acute or chronic health effects. The advantage of GE markers lies in their capability for early (1-3 days after irradiation), high-throughput, and point-of-care (POC) diagnosis required for the prediction of the acute radiation syndrome (ARS).

CONCLUSIONS

As a key session of the ConRad conference in 2021, experts from different institutions were invited to provide state-of-the-art information on a range of topics including: (1) Biodosimetry: What are the current efforts to enhance the applicability of this method to perform retrospective biodosimetry? (2) Effect prediction: Can we apply radiation-induced GE changes for prediction of acute health effects as an approach, complementary to and integrating retrospective dose estimation? (3) High-throughput and point-of-care diagnostics: What are the current developments to make the GE approach applicable as a high-throughput as well as a POC diagnostic platform? (4) Low level radiation: What is the lowest dose range where GE can be used for biodosimetry purposes? (5) Methodological considerations: Different aspects of radiation-induced GE related to more detailed analysis of exons, transcripts and next-generation sequencing (NGS) were reported.

A 4-Gene Signature of CDKN1, FDXR, SESN1 and PCNA Radiation Biomarkers for Prediction of Patient Radiosensitivity

The quest for the discovery and validation of radiosensitivity biomarkers is ongoing and while conventional bioassays are well established as biomarkers, molecular advances have unveiled new emerging biomarkers. Herein, we present the validation of a new 4-gene signature panel of CDKN1, FDXR, SESN1 and PCNA previously reported to be radiation-responsive genes, using the conventional G2 chromosomal radiosensitivity assay. Radiation-induced G2 chromosomal radiosensitivity at 0.05 Gy and 0.5 Gy IR is presented for a healthy control (n = 45) and a prostate cancer (n = 14) donor cohort. For the prostate cancer cohort, data from two sampling time points (baseline and Androgen Deprivation Therapy (ADT)) is provided, and a significant difference (p > 0.001) between 0.05 Gy and 0.5 Gy was evident for all donor cohorts. Selected donor samples from each cohort also exposed to 0.05 Gy and 0.5 Gy IR were analysed for relative gene expression of the 4-gene signature. In the healthy donor cohort, there was a significant difference in gene expression between IR dose for CDKN1, FXDR and SESN1 but not PCNA and no significant difference found between all prostate cancer donors, unless they were classified as radiation-induced G2 chromosomal radiosensitive. Interestingly, ADT had an effect on radiation response for some donors highlighting intra-individual heterogeneity of prostate cancer donors.

Inter-laboratory comparison of gene expression biodosimetry for protracted radiation exposures as part of the RENEB and EURADOS WG10 2019 exercise

Large-scale radiation emergency scenarios involving protracted low dose rate radiation exposure (e.g. a hidden radioactive source in a train) necessitate the development of high throughput methods for providing rapid individual dose estimates. During the RENEB (Running the European Network of Biodosimetry) 2019 exercise, four EDTA-blood samples were exposed to an Iridium-192 source (1.36 TBq, Tech-Ops 880 Sentinal) at varying distances and geometries. This resulted in protracted doses ranging between 0.2 and 2.4 Gy using dose rates of 1.5-40 mGy/min and exposure times of 1 or 2.5 h. Blood samples were exposed in thermo bottles that maintained temperatures between 39 and 27.7 °C. After exposure, EDTA-blood samples were transferred into PAXGene tubes to preserve RNA. RNA was isolated in one laboratory and aliquots of four blinded RNA were sent to another five teams for dose estimation based on gene expression changes. Using an X-ray machine, samples for two calibration curves (first: constant dose rate of 8.3 mGy/min and 0.5-8 h varying exposure times; second: varying dose rates of 0.5-8.3 mGy/min and 4 h exposure time) were generated for distribution. Assays were run in each laboratory according to locally established protocols using either a microarray platform (one team) or quantitative real-time PCR (qRT-PCR, five teams). The qRT-PCR measurements were highly reproducible with coefficient of variation below 15% in ≥ 75% of measurements resulting in reported dose estimates ranging between 0 and 0.5 Gy in all samples and in all laboratories. Up to twofold reductions in RNA copy numbers per degree Celsius relative to 37 °C were observed. However, when irradiating independent samples equivalent to the blinded samples but increasing the combined exposure and incubation time to 4 h at 37 °C, expected gene expression changes corresponding to the absorbed doses were observed. Clearly, time and an optimal temperature of 37 °C must be allowed for the biological response to manifest as gene expression changes prior to running the gene expression assay. In conclusion, dose reconstructions based on gene expression measurements are highly reproducible across different techniques, protocols and laboratories. Even a radiation dose of 0.25 Gy protracted over 4 h (1 mGy/min) can be identified. These results demonstrate the importance of the incubation conditions and time span between radiation exposure and measurements of gene expression changes when using this method in a field exercise or real emergency situation.

Identifying a Diagnostic Window for the Use of Gene Expression Profiling to Predict Acute Radiation Syndrome

In the event of a mass casualty radiological or nuclear scenario, it is important to distinguish between the unexposed (worried well), low-dose exposed individuals and those developing the hematological acute radiation syndrome (HARS) within the first three days postirradiation. In previous baboon studies, we identified altered gene expression changes after irradiation, which were predictive for the later developing HARS severity. Similar changes in the expression of four of these genes were observed using an in vitro human whole blood model. However, these studies have provided only limited information on the time frame of the changes after exposure in relationship to the development of HARS. In this study we analyzed the time-dependent changes in mRNA expression after in vitro irradiation of whole blood. Changes in the expression of informative mRNAs (FDXR, DBB2, POU2AF1 and WNT3) were determined in the blood of eight healthy donors (6 males, 2 females) after irradiation at 0 (control), 0.5, 2 and 4 Gy using qRT-PCR. FDXR expression was significantly upregulated (P < 0.001) 4 h after ≥0.5 Gy irradiation, with an 18-40-fold peak attained 4-12 h postirradiation which remained elevated (4-9-fold) at 72 h. DDB2 expression was upregulated after 4 h (fold change, 5-8, P < 0.001 at ≥ 0.5 Gy) and remained upregulated (3-4-fold) until 72 h (P < 0.001). The earliest time points showing a significant downregulation of POU2AF1 and WNT3 were 4 h (fold change = 0.4, P = 0.001, at 4 Gy) and 8 h (fold change = 0.3-0.5, P < 0.001, 2-4 Gy), respectively. These results indicate that the diagnostic window for detecting HARS-predictive changes in gene expression may be opened as early as 2 h for most (75%) and at 4 h postirradiation for all individuals examined. Depending on the RNA species studied this may continue for at least three days postirradiation.

Acute radiation syndrome-related gene expression in irradiated peripheral blood cell populations

PURPOSE

In a nuclear or radiological event, an early diagnostic tool is needed to distinguish the worried well from those individuals who may later develop life-threatenFing hematologic acute radiation syndrome. We examined the contribution of the peripheral blood's cell populations on radiation-induced gene expression (GE) changes.

MATERIALS AND METHODS

EDTA-whole-blood from six healthy donors was X-irradiated with 0 and 4Gy and T-lymphocytes, B-lymphocytes, NK-cells and granulocytes were separated using immunomagnetic methods. GE were examined in cell populations and whole blood.

RESULTS

The cell populations contributed to the total RNA amount with a ratio of 11.6 for T-lymphocytes, 1.2 for B-cells, 1.2 for NK-cells, 1.0 for granulocytes. To estimate the contribution of GE per cell population, the baseline (0Gy) and the radiation-induced fold-change in GE relative to unexposed was considered for each gene. The T-lymphocytes (74.8%/80.5%) contributed predominantly to the radiation-induced up-regulation observed for FDXR/DDB2 and the B-lymphocytes (97.1%/83.8%) for down-regulated POU2AF1/WNT3 with a similar effect on whole blood gene expression measurements reflecting a corresponding order of magnitude.

CONCLUSIONS

T- and B-lymphocytes contributed predominantly to the radiation-induced up-regulation of FDXR/DDB2 and down-regulation of POU2AF1/WNT3. This study underlines the use of FDXR/DDB2 for biodosimetry purposes and POU2AF1/WNT3 for effect prediction of acute health effects.

Dose and Dose-Rate Effects in a Mouse Model of Internal Exposure from 137Cs. Part 2: Integration of Gamma-H2AX and Gene Expression Biomarkers for Retrospective Radiation Biodosimetry

Inhalation and ingestion of 137Cs and other long-lived radionuclides can occur after large-scale accidental or malicious radioactive contamination incidents, resulting in a complex temporal pattern of radiation dose/dose rate, influenced by radionuclide pharmacokinetics and chemical properties. High-throughput radiation biodosimetry techniques for such internal exposure are needed to assess potential risks of short-term toxicity and delayed effects (e.g., carcinogenesis) for exposed individuals. Previously, we used γ-H2AX to reconstruct injected 137Cs activity in experimentally-exposed mice, and converted activity values into radiation doses based on time since injection and 137Cs-elimination kinetics. In the current study, we sought to assess the feasibility and possible advantages of combining γ-H2AX with transcriptomics to improve 137Cs activity reconstructions. We selected five genes (Atf5, Hist2h2aa2, Olfr358, Psrc1, Hist2h2ac) with strong statistically-significant Spearman's correlations with injected activity and stable expression over time after 137Cs injection. The geometric mean of log-transformed signals of these five genes, combined with γ-H2AX fluorescence, were used as predictors in a nonlinear model for reconstructing injected 137Cs activity. The coefficient of determination (R2) comparing actual and reconstructed activities was 0.91 and root mean squared error (RMSE) was 0.95 MBq. These metrics remained stable when the model was fitted to a randomly-selected half of the data and tested on the other half, repeated 100 times. Model performance was significantly better when compared to our previous analysis using γ-H2AX alone, and when compared to an analysis where genes are used without γ-H2AX, suggesting that integrating γ-H2AX with gene expression provides an important advantage. Our findings show a proof of principle that integration of radiation-responsive biomarkers from different fields is promising for radiation biodosimetry of internal emitters.

In Vivo Validation of Alternative FDXR Transcripts in Human Blood in Response to Ionizing Radiation

Following cell stress such as ionising radiation (IR) exposure, multiple cellular pathways are activated. We recently demonstrated that ferredoxin reductase (FDXR) has a remarkable IR-induced transcriptional responsiveness in blood. Here, we provided a first comprehensive FDXR variant profile following DNA damage. First, specific quantitative real-time polymerase chain reaction (qPCR) primers were designed to establish dose-responses for eight curated FDXR variants, all up-regulated after IR in a dose-dependent manner. The potential role of gender on the expression of these variants was tested, and neither the variants response to IR nor the background level of expression was profoundly affected; moreover, in vitro induction of inflammation temporarily counteracted IR response early after exposure. Importantly, transcriptional up-regulation of these variants was further confirmed in vivo in blood of radiotherapy patients. Full-length nanopore sequencing was performed to identify other FDXR variants and revealed the high responsiveness of FDXR-201 and FDXR-208. Moreover, FDXR-218 and FDXR-219 showed no detectable endogenous expression, but a clear detection after IR. Overall, we characterised 14 FDXR transcript variants and identified for the first time their response to DNA damage in vivo. Future studies are required to unravel the function of these splicing variants, but they already represent a new class of radiation exposure biomarkers.

The hunt for radiation biomarkers: current situation

Purpose: The possibility of a large-scale acute radiation exposure necessitates the development of new methods that could provide a rapid assessment of the doses received by individuals using high-throughput technologies. There is also a great interest in developing new biomarkers of dose exposure, which could be used in large molecular epidemiological studies in order to correlate estimated doses received and health effects. The goal of this review was to summarize current literature focused on biological dosimetry, namely radiation-responsive biomarkers.Methods: The studies involved in this review were thoroughly selected according to the determined criteria and PRISMA guidelines.Results: We described briefly recent advances in radiation genomics and metabolomics, giving particular emphasis to proteomic analysis. The majority of studies were performed on animal models (rats, mice, and non-human primates). They have provided much beneficial information, but the most relevant tests have been done on human (oncological) patients. By inspecting the radiaiton biodosimetry literate of the last 10 years, we identified a panel of candidate markers for each -omic approach involved.Conslusions: We reviewed different methodological approaches and various biological materials, which can be exploited for dose-effect prediction. The protein biomarkers from human plasma are ideal for this specific purpose. From a plethora of candidate markers, FDXR is a very promising transcriptomic candidate, and importantly this biomarker was also confirmed by some studies at protein level in humans.

Generation of a Transcriptional Radiation Exposure Signature in Human Blood Using Long-Read Nanopore Sequencing

In the event of a large-scale event leading to acute ionizing radiation exposure, high-throughput methods would be required to assess individual dose estimates for triage purposes. Blood-based gene expression is a broad source of biomarkers of radiation exposure which have great potential for providing rapid dose estimates for a large population. Time is a crucial component in radiological emergencies and the shipment of blood samples to relevant laboratories presents a concern. In this study, we performed nanopore sequencing analysis to determine if the technology can be used to detect radiation-inducible genes in human peripheral blood mononuclear cells (PBMCs). The technology offers not only long-read sequencing but also a portable device which can overcome issues involving sample shipment, and provide faster results. For this goal, blood from nine healthy volunteers was 2 Gy ex vivo X irradiated. After PBMC isolation, irradiated samples were incubated along with the controls for 24 h at 37°C. RNA was extracted, poly(A)+ enriched and reverse-transcribed before sequencing. The data generated was analyzed using a Snakemake pipeline modified to handle paired samples. The sequencing analysis identified a radiation signature consisting of 46 differentially expressed genes (DEGs) which included 41 protein-coding genes, a long non-coding RNA and four pseudogenes, five of which have been identified as radiation-responsive transcripts for the first time. The genes in which transcriptional expression is most significantly modified after radiation exposure were APOBEC3H and FDXR, presenting a 25- and 28-fold change on average, respectively. These levels of transcriptional response were comparable to results we obtained by quantitative polymerase chain reaction (qPCR) analysis. In vivo exposure analyses showed a transcriptional radioresponse at 24 h postirradiation for both genes together with a strong dose-dependent response in blood irradiated ex vivo. Finally, extrapolating from the data we obtained, the minimum sequencing time required to detect an irradiated sample using APOBEC3H transcripts would be less than 3 min for a total of 50,000 reads. Future improvements, in sample processing and bioinformatic pipeline for specific radiation-responsive transcript identification, will allow the provision of a portable, rapid, real-time biodosimetry platform based on this new sequencing technology. In summary, our data show that nanopore sequencing can identify radiation-responsive genes and can also be used for identification of new transcripts.