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

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.

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.

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.

Impact of GADD45A on Radiation Biodosimetry Using Mouse Peripheral Blood

High-dose-radiation exposure in a short period of time leads to radiation syndromes characterized by severe acute and delayed organ-specific injury accompanied by elevated organismal morbidity and mortality. Radiation biodosimetry based on gene expression analysis of peripheral blood is a valuable tool to detect exposure to radiation after a radiological/nuclear incident and obtain useful biological information that could predict tissue and organismal injury. However, confounding factors, including chronic inflammation, can potentially obscure the predictive power of the method. GADD45A (Growth arrest and DNA damage-inducible gene a) plays important roles in cell growth control, differentiation, DNA repair, and apoptosis. GADD45A-deficient mice develop an autoimmune disease, similar to human systemic lupus erythematosus, characterized by severe hematological disorders, kidney disease, and premature death. The goal of this study was to elucidate how pre-existing inflammation in mice, induced by GADD45A ablation, can affect radiation biodosimetry. We exposed wild-type and GADD45A knockout male C57BL/6J mice to 7 Gy of X rays and 24 h later RNA was isolated from whole blood and subjected to whole genome microarray and gene ontology analyses. Dose reconstruction analysis using a gene signature trained on gene expression data from irradiated wild-type male mice showed accurate reconstruction of either a 0 Gy or 7 Gy dose with root mean square error of ± 1.05 Gy (R^2 = 1.00) in GADD45A knockout mice. Gene ontology analysis revealed that irradiation of both wild-type and GADD45A-null mice led to a significant overrepresentation of pathways associated with morbidity and mortality, as well as organismal cell death. However, based on their z-score, these pathways were predicted to be more significantly overrepresented in GADD45A-null mice, implying that GADD45A deletion may exacerbate the deleterious effects of radiation on blood cells. Numerous immune cell functions and quantities were predicted to be underrepresented in both genotypes; however, differentially expressed genes from irradiated GADD45A knockout mice predicted an increased deterioration in the numbers of T lymphocytes, as well as myeloid cells, compared with wild-type mice. Furthermore, an overrepresentation of genes associated with radiation-induced hematological malignancies was associated with GADD45A knockout mice, whereas hematopoietic and progenitor cell functions were predicted to be downregulated in irradiated GADD45A knockout mice. In conclusion, despite the significant differences in gene expression between wild-type and GADD45A knockout mice, it is still feasible to identify a panel of genes that could accurately distinguish between irradiated and control mice, irrespective of pre-existing inflammation status.

A simplified protocol for gene expression-based biological dosimetry using peripheral whole blood

PURPOSE

Assessing alterations in the expression of radiation-responsive genes in peripheral blood cells is considered a promising approach for high-throughput radiation biodosimetry. However, optimization of conditions for storage and transport of blood samples would be critical for obtaining reliable results. Recent studies involved the incubation of isolated peripheral blood mononuclear cells (in cell culture medium) and/or use of RNA stabilizing agents for sample storage, immediately after the ex vivo irradiation of whole blood. We used a simpler protocol by incubating undiluted peripheral whole blood without any RNA stabilizing agent, and studied the impact of storage temperature and incubation time on the expression levels of 19 known radiation responsive genes.

MATERIALS & METHODS

Peripheral whole blood was γ-irradiated ex vivo at room temperature at low (0.5 Gy), moderate (1 Gy, 2 Gy) and high (4 Gy) doses and immediately incubated at two different temperatures at 4 °C or 37 °C for 2h, 4h and 24 h. Using qRT-PCR, mRNA expression levels of CDKN1A, DDB2, GADD45A, FDXR, BAX, BBC3, MYC, PCNA, XPC, ZMAT3, AEN, TRIAP1, CCNG1, RPS27L, CD70, EI24, C12orf5, TNFRSF10B, ASCC3 were analyzed at respective time-points and compared with the sham-irradiated controls.

RESULTS

Transcriptional responses of all 19 genes did not alter significantly upon incubation of whole blood samples at 4 °C, as compared to untreated controls. However, incubation at 37 °C for 24 h resulted in significant radiation-induced overexpression in 14 out of the 19 genes analyzed (except CDKN1A, BBC3, MYC, CD 70 and EI24). Detailed patterns during incubation at 37 °C revealed time-dependent up-regulation of these genes, with DDB2 and FDXR showing significant up-regulation both at 4 and 24 h with the highest fold-change observed.

CONCLUSION

Overall, the undiluted whole blood incubated at 37 °C for 24 h was found to elicit most optimal transcriptional response in the genes studied, with most profound overexpression of DDB2 and FDXR. We propose that sample storage/transport/post-transit incubation at the physiological temperature for up to 24 h may enhance the sensitivity of gene expression based biodosimetry and facilitate its usage for triage application.

Paper-Based Vertical Flow Immunoassay for the Point-of-Care Multiplex Detection of Radiation Dosimetry Genes

In a nuclear or radiological incident, first responders must quickly and accurately measure radiation exposure among civilians as medical countermeasures are radiation dose-dependent and time-sensitive. Although several approaches have been explored to measure absorbed radiation dose, there is an important need to develop point-of-care (POC) bioassay devices that can be used immediately to triage thousands of individuals potentially exposed to radiation. Here we present a proof-of-concept study showing the use of a paper-based vertical flow immunoassay (VFI) to detect radiation dosimetry genes. Using labeled primers during amplification and a multiplex membrane, our results showed that the nucleic acid VFI can simultaneously detect two biodosimetry genes, CDKN1A and DDB2, as well as one housekeeping gene MRPS5. The assay demonstrated good linearity and precision with an inter- and intra-assay coefficient of variance <20% and <10%, respectively. Moreover, the assay showed its ability to discriminate non-irradiated controls (0 Gy) from irradiated samples (1 + 2 Gy) with an overall sensitivity of 62.5% and specificity of 100% (AUC = 0.8672, 95% CI: 0.723-1.000; p = 0.004). Interestingly, the gene combination also showed a dose-dependent response for 0, 1, and 2 Gy, similar to data obtained by real-time PCR benchmark. These preliminary results suggest that a VFI platform can be used to detect simultaneously multiple genes that can be then quantified, thus offering a new approach for a POC biodosimetry assay that could be rapidly deployed on-site to test a large population and help triage and medical management after radiological event.

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.

Candidate Gene Expression in Regional Population and Its Relevance for Radiation Triage

Quantification of gene expression signatures has been substantiated as a potential and rapid marker for radiation triage and biodosimetry during nuclear emergencies. Similar to the established biodosimetry assays, the gene expression assay has drawbacks such as being highly dynamic and transient, not specific to ionizing radiation, and also influenced by confounding factors such as gender, health status, lifestyle, and inflammation. In view of that, prior knowledge of baseline expression of certain candidate genes in a population could complement the discrimination of the unexposed from the exposed individuals without the need for individual pre-exposure controls. We intended to establish a baseline expression of reported radiation-responsive genes such as CDKN1A, DDB2, FDXR, and PCNA in the blood samples of healthy human participants and then compare it with diabetic/hypertension participants (as a chronic inflammatory condition) drawn from south Indian population. Further, we have examined the appropriateness of the assay for radiation triage-like situations; i.e., the expression profiles of those genes were examined in the participants who underwent X-ray-based medical imaging. Acute inflammation induced by lipopolysaccharide exposure in the blood significantly increased the fold expression of those genes (p < 0.0001) compared to the control. Whereas the basal expression level of those genes among the participants with the inflammatory condition is marginally higher than those observed in the healthy participants; despite the excess, the fold increase in those genes between the groups did not differ significantly. Consistent with the inflammatory participants, the basal expression level of those genes in the blood sample of participants who received X-radiation during neuro-interventional and computed tomography imaging is marginally higher than those observed in the pre-exposure of respective groups. Nevertheless, the fold increase in those genes did not differ significantly as the fold change fell within the two folds. Thus, overall results suggest that the utility of CDKN1A, DDB2, FDXR, and PCNA gene expression for radiation triage specific after very low-dose radiation exposure needs to be interpreted with caution for a much more reliable triage.

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.

Biodose Tools: an R shiny application for biological dosimetry

INTRODUCTION

In the event of a radiological accident or incident, the aim of biological dosimetry is to convert the yield of a specific biomarker of exposure to ionizing radiation into an absorbed dose. Since the 1980s, various tools have been used to deal with the statistical procedures needed for biological dosimetry, and in general those who made several calculations for different biomarkers were based on closed source software. Here we present a new open source program, Biodose Tools, that has been developed under the umbrella of RENEB (Running the European Network of Biological and retrospective Physical dosimetry).

MATERIALS AND METHODS

The application has been developed using the R programming language and the shiny package as a framework to create a user-friendly online solution. Since no unique method exists for the different mathematical processes, several meetings and periodic correspondence were held in order to reach a consensus on the solutions to be implemented.

RESULTS

The current version 3.6.1 supports dose-effect fitting for dicentric and translocation assay. For dose estimation Biodose Tools implements those methods indicated in international guidelines and a specific method to assess heterogeneous exposures. The app can include information on the irradiation conditions to generate the calibration curve. Also, in the dose estimate, information about the accident can be included as well as the explanation of the results obtained. Because the app allows generating a report in various formats, it allows traceability of each biological dosimetry study carried out. The app has been used globally in different exercises and training, which has made it possible to find errors and improve the app itself. There are some features that still need consensus, such as curve fitting and dose estimation using micronucleus analysis. It is also planned to include a package dedicated to interlaboratory comparisons and the incorporation of Bayesian methods for dose estimation.

CONCLUSION

Biodose Tools provides an open-source solution for biological dosimetry laboratories. The consensus reached helps to harmonize the way in which uncertainties are calculated. In addition, because each laboratory can download and customize the app's source code, it offers a platform to integrate new features.

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.

Gene Expression Changes in a Prefinal Health Stage of Lethally Irradiated Male and Female Rhesus Macaques

Radiation-induced gene expression (GE) changes can be used for early and high-throughput biodosimetry within the first three days postirradiation. However, is the method applicable in situations such as the Alexander Litvinenko case or the Goiania accident, where diagnosis occurred in a prefinal health stage? We aimed to characterize gene expression changes in a prefinal health stage of lethally irradiated male and female rhesus macaques. Peripheral blood was drawn pre-exposure and at the prefinal stage of male and female animals, which did not survive whole-body exposure with 700 cGy (LD66/60). RNA samples originated from a blinded randomized Good Laboratory Practice study comprising altogether 142 irradiated rhesus macaques of whom 60 animals and blood samples (15 samples for both time points and sexes) were used for this analysis. We evaluated GE on 34 genes widely used in biodosimetry and prediction of the hematological acute radiation syndrome severity (H-ARS) employing quantitative real-time polymerase chain reaction (qRT-PCR). These genes were run in duplicate and triplicate and altogether 96 measurements per time point and sex could be performed. In addition, 18S ribosomal RNA (rRNA) was measured to depict the ribosome/transcriptome status as well as for normalization purposes and 16S rRNA was evaluated as a surrogate for bacteremia. Mean differential gene expression (DGE) was calculated for each gene and sex including all replicate measurements and using pre-exposure samples as the reference. From 34 genes, altogether 27 genes appeared expressed. Pre-exposure samples revealed no signs of bacteremia and 18S rRNA GE was in the normal range in all 30 samples. Regarding prefinal samples, 46.7% and 40% of animals appeared infected in females and males, respectively, and for almost all males this was associated with out of normal range 18S rRNA values. The total number of detectable GE measurements was sixfold (females) and 15-fold (males) reduced in prefinal relative to pre-exposure samples and about tenfold lower in 80% of prefinal compared to pre-exposure samples (P < 0.0001). An overall 11-fold (median) downregulation in prefinal compared to pre-exposure samples was identified for most of the 27 genes and even FDXR appeared 4-14-fold downregulated in contrast to a pronounced up-regulation according to cited work. This pattern of overall downregulation of almost all genes and the rapid reduction of detectable genes at a prefinal stage was found in uninfected animals with normal range 18S rRNA as well. In conclusion, in a prefinal stage after lethal radiation exposure, the ribosome/transcriptome status remains present (based on normal range 18S rRNA values) in 60-67% of animals, but the whole transcriptome activity in general appears silenced and cannot be used for biodosimetry purposes, but probably as an indicator for an emerging prefinal health stage.

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).

Dose Variations Using an X-Ray Cabinet to Establish in vitro Dose-Response Curves for Biological Dosimetry Assays

In biological dosimetry, dose-response curves are essential for reliable retrospective dose estimation of individual exposure in case of a radiation accident. Therefore, blood samples are irradiated in vitro and evaluated based on the applied assay. Accurate physical dosimetry of the irradiation performance is a critical part of the experimental procedure and is influenced by the experimental setup, especially when X-ray cabinets are used. The aim of this study was to investigate variations and pitfalls associated with the experimental setups used to establish calibration curves in biological dosimetry with X-ray cabinets. In this study, irradiation was performed with an X-ray source (195 kV, 10 mA, 0.5 mm Cu filter, dose rate 0.52 Gy/min, 1st and 2nd half-value layer = 1.01 and 1.76 mm Cu, respectively, average energy 86.9 keV). Blood collection tubes were irradiated with a dose of 1 Gy in vertical or horizontal orientation in the center of the beam area with or without usage of an additional fan heater. To evaluate the influence of the setups, physical dose measurements using thermoluminescence dosimeters, electron paramagnetic resonance dosimetry and ionization chamber as well as biological effects, quantified by dicentric chromosomes and micronuclei, were compared. This study revealed that the orientation of the sample tubes (vertical vs. horizontal) had a significant effect on the radiation dose with a variation of -41% up to +49% and contributed to a dose gradient of up to 870 mGy inside the vertical tubes due to the size of the sample tubes and the associated differences in the distance to the focal point of the tube. The number of dicentric chromosomes and micronuclei differed by ~30% between both orientations. An additional fan heater had no consistent impact. Therefore, dosimetric monitoring of experimental irradiation setups is mandatory prior to the establishment of calibration curves in biological dosimetry. Careful consideration of the experimental setup in collaboration with physicists is required to ensure traceability and reproducibility of irradiation conditions, to correlate the radiation dose and the number of aberrations correctly and to avoid systematical bias influencing the dose estimation in the frame of biological dosimetry.

The Potential of Omics in Biological Dosimetry

Biological dosimetry is an internationally recognized method for quantifying and estimating radiation dose following suspected or verified excessive exposure to ionising radiation. In severe radiation accidents where a large number of people are potentially affected, it is possible to distinguish irradiated from non-irradiated people in order to initiate appropriate medical care if necessary. In addition to severe incidents caused by technical failure, environmental disasters, military actions, or criminal abuse, there are also radiation accidents in which only one or a few individuals are affected in the frame of occupational or medical exposure. The requirements for biological dosimetry are fundamentally different for these two scenarios. In particular, for large-scale radiation accidents, pre-screening methods are necessary to increase the throughput of samples for a rough first-dose categorization. The rapid development and increasing use of omics methods in research as well as in individual applications provides new opportunities for biological dosimetry. In addition to the discovery and search for new biomarkers, dosimetry assays based on omics technologies are becoming increasingly interesting and hold great potential, especially for large-scale dosimetry. In the following review, the different areas of biological dosimetry, the problems in finding suitable biomarkers, the current status of biomarker research based on omics, the potential applications of assays using omics technologies, and also the limitations for the different areas of biological dosimetry are discussed.

Clinical Applications of Biological Dosimetry in Patients Exposed to Low Dose Radiation Due to Radiological, Imaging or Nuclear Medicine Procedures

Radiation dosimetric biomarkers have found applications beyond radiation protection area and now are actively introduced into clinical practice. Cytogenetic assays appeared to be a valuable tool for individualized quantifying radiation effects in patients, with high capability for assessing genotoxicity of various medical exposure modalities and providing meaningful radiation dose estimates for prognoses of radiation-related cancer risk. This review summarized current data on the use of biological dosimetry methods in patients undergoing various medical irradiations to low doses. The highlighted topics include basic aspects of biological dosimetry and its limitations in the range of low radiation doses, and main patterns of in vivo induction of radiation biomarkers in clinical exposure scenarios, occurring in X-ray diagnostics, computed tomography, interventional radiology, low dose radiotherapy, and nuclear medicine (internally administered ¹³¹I and other radiopharmaceuticals). Additionally, several specific issues, examined by biodosimetry techniques, are analysed, such as contrast media effect, radiation response in pediatric patients, impact of magnetic resonance imaging, evaluation of radioprotectors, detection of patients' abnormal intrinsic radiosensitivity and dose estimation in persons involved in medical radiation incidents. A prognosis of possible directions for further improvements in this area includes the automation of cytogenetic analysis, introduction of molecular biodosimeters and development of multiparametric biodosimetry platforms. A potential approach to the advanced biodosimetry of internal exposure and/or low dose external irradiation is suggested; this can be a multiparametric platform based on the combination of the γ-H2AX foci, dicentric, and translocation assays, each applied in the optimum postexposure time range, with the amalgamation of the dose estimates. The study revealed the necessity of further research, which might clarify medical radiation safety concerns for patients via using stringent biodosimetry methodology.