Prediction of in vivo radiation dose status in radiotherapy patients using ex vivo and in vivo gene expression signatures

Ionizing radiation effects on blood-derived extracellular vesicles: insights into miR-34a-5p-mediated cellular responses and biomarker potential

Adverse effects of ionizing radiation on normal tissues limit the radiation dose in cancer treatment, thereby compromising treatment efficiency. Among the consistently affected non-cancer cells, peripheral blood mononuclear cells (PBMCs) exhibit high radiosensitivity and have the potential to induce systemic effects. PBMC-released extracellular vesicles (EVs), contribute to the communication of such systemic effects. This study aimed to investigate the effects of ionizing radiation on EVs as part of the systemic response of PBMCs in terms of microRNA cargo and biological functions.Therefore, whole blood samples from healthy donors were irradiated ex-vivo (0 Gy, 1 Gy, 2 Gy, 4 Gy) and EVs from PBMCs were isolated after 96 h by PEG precipitation or ultracentrifugation. Candidate microRNAs were examined in PBMC-derived EVs from individual donors. The uptake of membrane-stained fluorescent EVs by different recipient cells was quantified by fluorescence-activated cell sorting analysis. The biological effects of increased miR-34a-5p and of total EVs on recipient cells were assessed.Irradiation of PBMCs induced a dose-dependent upregulation of miR-34a-5p within EVs and PBMCs. However, interindividual differences between donors were noticed in the extent of upregulation, and small EVs displayed more pronounced changes in microRNA levels in comparison to large EVs. Irradiation in presence of the small molecule inhibitor KU-60019 demonstrated that this upregulation is dependent on ATM (Ataxia telangiectasia mutated) activation. Moreover, fibroblasts and keratinocytes were identified as preferred EV recipients. Increased miR-34a-5p levels led to a significant reduction in viability and induction of senescence in keratinocytes but not in fibroblasts, indicating a cell type-specific response.In conclusion, this study further elucidated the complex cellular response of normal tissue after radiation exposure. It confirmed radiation-induced modifications of microRNA expression levels in EVs from PBMCs and identified a robust upregulation of miR-34a-5p in the small EV subfraction, suggesting this microRNA as a potential novel candidate for the development of biomarkers for radiation exposure. Moreover, the different uptake efficiencies observed among specific cell types suggested that EVs induce cell type-specific responses in the intercellular communication of systemic radiation effects.

Radiation Research Society Journal-based Historical Review of the Use of Biomarkers for Radiation Dose and Injury Assessment: Acute Health Effects Predictions

A multiple-parameter based approach using radiation-induced clinical signs and symptoms, hematology changes, cytogenetic chromosomal aberrations, and molecular biomarkers changes after radiation exposure is used for biodosimetry-based dose assessment. In the current article, relevant milestones from Radiation Research are documented that forms the basis of the current consensus approach for diagnostics after radiation exposure. For example, in 1962 the use of cytogenetic chromosomal aberration using the lymphocyte metaphase spread dicentric assay for biodosimetry applications was first published in Radiation Research. This assay is now complimented using other cytogenetic chromosomal aberration assays (i.e., chromosomal translocations, cytokinesis-blocked micronuclei, premature chromosome condensation, γ-H2AX foci, etc.). Changes in blood cell counts represent an early-phase biomarker for radiation exposures. Molecular biomarker changes have evolved to include panels of organ-specific plasma proteomic and blood-based gene expression biomarkers for radiation dose assessment. Maturation of these assays are shown by efforts for automated processing and scoring, development of point-of-care diagnostics devices, service laboratories inter-comparison exercises, and applications for dose and injury assessments in radiation accidents. An alternative and complementary approach has been advocated with the focus to de-emphasize "dose" and instead focus on predicting acute or delayed health effects. The same biomarkers used for dose estimation (e.g., lymphocyte counts) can be used to directly predict the later developing severity degree of acute health effects without performing dose estimation as an additional or intermediate step. This review illustrates contributing steps toward these developments published in Radiation Research.

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.

Candidate biomarkers and persistent transcriptional responses after low and high dose ionizing radiation at high dose rate

PURPOSE

Development of an integrated time and dose model to explore the dynamics of gene expression alterations and identify biomarkers for biodosimetry following low- and high-dose irradiations at high dose rate.

MATERIAL AND METHODS

We utilized multiple transcriptome datasets (GSE8917, GSE43151, and GSE23515) from Gene Expression Omnibus (GEO) for identifying candidate biological dosimeters. A linear mixed-effects model with random intercept was used to explore the dose-time dynamics of transcriptional responses and to functionally characterize the time- and dose-dependent changes in gene expression.

RESULTS

We identified genes that are correlated with dose and time and discovered two clusters of genes that are either positively or negatively correlated with both dose and time based on the parameters of the model. Genes in these two clusters may have persistent transcriptional alterations. Twelve potential transcriptional markers for dosimetry-ARHGEF3, BAX, BBC3, CCDC109B, DCP1B, DDB2, F11R, GADD45A, GSS, PLK3, TNFRSF10B, and XPC were identified. Of these genes, BAX, GSS, and TNFRSF10B are positively associated with both dose and time course, have a persistent transcriptional response, and might be better biological dosimeters.

CONCLUSIONS

With the proposed approach, we may identify candidate biomarkers that change monotonically in relation to dose, have a persistent transcriptional response, and are reliable over a wide dose range.

Effects of cyclophosphamide and mitomycin C on radiation-induced transcriptional biomarkers in human lymphoblastoid cells

PURPOSE

Ionizing radiation (IR)-induced transcriptional changes are considered a potential biodosimetry for dose evaluation and health risk monitoring of acute or chronic radiation exposure. It is crucial to understand the impact of confounding factors on the radiation-responsive gene expressions for accurate and reproducible dose assessment. This study aims to explore the potential influence of exposures to chemotherapeutic agents such as cyclophosphamide (CP) and mitomycin C (MMC) on IR-induced transcriptional biomarkers.

METHODS

The human B lymphoblastoid cells (AHH-1) were exposed to 0, 20, 50, 100, 200 and 500 μg/ml CP or 0, 0.025, 0.05, 0.1 and 1 μg/ml MMC, respectively. The appropriate concentrations of CP and MMC were added for 1 h before irradiation with 0, 2, 4 and 6 Gy of 60Co γ-rays at a dose rate of 1 Gy/min. Cell viability was evaluated by CCK-8 assay. The gene expression responses of 18 radiation-induced transcriptional biomarkers were examined at 24 h after exposures to CP and MMC, respectively. The expression levels of five crucial DNA interstrand crosslinks (ICLs) repair genes were also evaluated. The biodosimetry models were established based on the specific radiation-responsive gene combinations.

RESULTS

The baseline transcriptional levels of the 18 selected genes were slightly affected by CP treatment in the absence of IR, while the transcript responses to IR could be inhibited as the concentration of CP up to 50 μg/ml. MMC treatment up-regulated the background levels in most radiation-responsive gene expressions. Of 18 genes, only the relative mRNA expression levels of CDKN1A and BBC3 were repressed after treatment with IR and MMC in combination. The relative mRNA level of RAD51 was significantly up-regulated after exposure to CP, while the expression of FANCD2, RAD51 and BLM showed an overall increase in response to MMC treatment. After irradiation, the relative mRNA expression levels of FANCD2, BRCA2 and RAD51 exhibited dose-dependent increases in IR alone and MMC treatment groups. In addition, the biodosimetry models were established using 2-4 radiation-responsive genes based on different radiation exposure scenarios.

CONCLUSION

Our findings suggested that IR-induced gene expression changes were slightly affected after exposure to a relatively low concentration of CP and MMC. Gene expression combinations might improve the broad applicability of transcriptional biodosimetry across diverse radiation exposures.

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.

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.

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?

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.

Transcriptional Dynamics of DNA Damage Responsive Genes in Circulating Leukocytes during Radiotherapy

Simple Summary

In this study, the transcriptional response of a panel of radiation responsive genes was monitored over time in blood samples after radiation exposure in vivo. For this aim, cancer patients treated by radiotherapy were recruited after consent forms were obtained. Following the first fraction of radiotherapy, 2 mL blood samples were collected at different time points during the first 24h hours (before the second fraction was delivered) and at mid and end of treatment. Amongst the 9 genes studied, the gene FDXR stood out as the most sensitive and responsive to the low dose of radiation received from the localised radiation treatment by the circulating white blood cells. The activation of FDXR was found to depend on the volume of the body exposed with a peak of expression around 8–9 hours after irradiation was delivered. Finally results obtained ex vivo confirmed the results obtained in vivo.

Abstract

External beam radiation therapy leads to cellular activation of the DNA damage response (DDR). DNA double-strand breaks (DSBs) activate the ATM/CHEK2/p53 pathway, inducing the transcription of stress genes. The dynamic nature of this transcriptional response has not been directly observed in vivo in humans. In this study we monitored the messenger RNA transcript abundances of nine DNA damage-responsive genes (CDKN1A, GADD45, CCNG1, FDXR, DDB2, MDM2, PHPT1, SESN1, and PUMA), eight of them regulated by p53 in circulating blood leukocytes at different time points (2, 6–8, 16–18, and 24 h) in cancer patients (lung, neck, brain, and pelvis) undergoing radiotherapy. We discovered that, although the calculated mean physical dose to the blood was very low (0.038–0.169 Gy), an upregulation of Ferredoxin reductase (FDXR) gene transcription was detectable 2 h after exposure and was dose dependent from the lowest irradiated percentage of the body (3.5% whole brain) to the highest, (up to 19.4%, pelvic zone) reaching a peak at 6–8 h. The radiation response of the other genes was not strong enough after such low doses to provide meaningful information. Following multiple fractions, the expression level increased further and was still significantly up-regulated by the end of the treatment. Moreover, we compared FDXR transcriptional responses to ionizing radiation (IR) in vivo with healthy donors’ blood cells exposed ex vivo and found a good correlation in the kinetics of expression from the 8-hours time-point onward, suggesting that a molecular transcriptional regulation mechanism yet to be identified is involved. To conclude, we provided the first in vivo human report of IR-induced gene transcription temporal response of a panel of p53-dependant genes. FDXR was demonstrated to be the most responsive gene, able to reliably inform on the low doses following partial body irradiation of the patients, and providing an expression pattern corresponding to the % of body exposed. An extended study would provide individual biological dosimetry information and may reveal inter-individual variability to predict radiotherapy-associated adverse health outcomes.

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.

The transcriptomic revolution and radiation biology

PURPOSE

This article will briefly review the origins and evolution of functional genomics, first describing the experimental technology, and then some of the approaches applied to data analysis and visualization. It will emphasize application of functional genomics to radiation biology, using examples from the author's work to illustrate several key types of analysis. It concludes with a look at non-coding RNA, alternative reading of the genome, and single-cell transcriptomics, some of the innovative areas that may help to shape future research in radiation biology and oncology.

CONCLUSIONS

Transcriptomic approaches have provided insight into many areas of radiation biology and medicine, and innovations in technology and data analysis approaches promise continued contributions to radiation science in the future.

High-LET Carbon and Iron Ions Elicit a Prolonged and Amplified p53 Signaling and Inflammatory Response Compared to low-LET X-Rays in Human Peripheral Blood Mononuclear Cells

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

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.

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.

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.

The p53 Protein Family in the Response of Tumor Cells to Ionizing Radiation: Problem Development

Survival mechanisms are activated in tumor cells in response to therapeutic ionizing radiation. This reduces a treatment's effectiveness. The p53, p63, and p73 proteins belonging to the family of proteins that regulate the numerous pathways of intracellular signal transduction play a key role in the development of radioresistance. This review analyzes the p53-dependent and p53-independent mechanisms involved in overcoming the resistance of tumor cells to radiation exposure.

Transcriptomics for radiation biodosimetry: progress and challenges

PURPOSE

Transcriptomic-based approaches are being developed to meet the needs for large-scale radiation dose and injury assessment and provide population triage following a radiological or nuclear event. This review provides background and definition of the need for new biodosimetry approaches, and summarizes the major advances in this field. It discusses some of the major model systems used in gene signature development, and highlights some of the remaining challenges, including individual variation in gene expression, potential confounding factors, and accounting for the complexity of realistic exposure scenarios.

CONCLUSIONS

Transcriptomic approaches show great promise for both dose reconstruction and for prediction of individual radiological injury. However, further work will be needed to ensure that gene expression signatures will be robust and appropriate for their intended use in radiological or nuclear emergencies.

Impact of aging on gene expression response to x-ray irradiation using mouse blood

As a radiation biodosimetry tool, gene expression profiling is being developed using mouse and human peripheral blood models. The impact of dose, dose-rate, and radiation quality has been studied with the goal of predicting radiological tissue injury. In this study, we determined the impact of aging on the gene expression profile of blood from mice exposed to radiation. Young (2 mo) and old (21 mo) male mice were irradiated with 4 Gy x-rays, total RNA was isolated from whole blood 24 h later, and subjected to whole genome microarray analysis. Pathway analysis of differentially expressed genes revealed young mice responded to x-ray exposure by significantly upregulating pathways involved in apoptosis and phagocytosis, a process that eliminates apoptotic cells and preserves tissue homeostasis. In contrast, the functional annotation of senescence was overrepresented among differentially expressed genes from irradiated old mice without enrichment of phagocytosis pathways. Pathways associated with hematologic malignancies were enriched in irradiated old mice compared with irradiated young mice. The fibroblast growth factor signaling pathway was underrepresented in older mice under basal conditions. Similarly, brain-related functions were underrepresented in unirradiated old mice. Thus, age-dependent gene expression differences should be considered when developing gene signatures for use in radiation biodosimetry.

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.

Role of blood derived cell fractions, temperature and sample transport on gene expression-based biological dosimetry

PURPOSE

For triage purposes following a nuclear accident or a terrorist event, gene expression biomarkers in blood have been demonstrated to be good bioindicators of ionizing radiation (IR) exposure and can be used to assess the dose received by exposed individuals. Many IR-sensitive genes are regulated by the DNA damage response pathway, and modulators of this pathway could potentially affect their expression level and therefore alter accurate dose estimations. In the present study, we addressed the potential influence of temperature, sample transport conditions and the blood cell fraction analyzed on the transcriptional response of the following radiation-responsive genes: FDXR, CCNG1, MDM2, PHPT1, APOBEC3H, DDB2, SESN1, P21, PUMA, and GADD45.

MATERIALS AND METHODS

Whole blood from healthy donors was exposed to a 2 Gy X-ray dose with a dose rate of 0.5 Gy/min (output 13 mA, 250 kV peak, 0.2 mA) and incubated for 24 h at either 37, 22, or 4 °C. For mimicking the effect of transport conditions at different temperatures, samples incubated at 37 °C for 24 h were kept at 37, 22 or 4 °C for another 24 h. Comparisons of biomarker responses to IR between white blood cells (WBCs), peripheral blood mononuclear cells (PBMCs) and whole blood were carried out after a 2 Gy X-ray exposure and incubation at 37 °C for 24 hours.

RESULTS

Hypothermic conditions (22 or 4 °C) following irradiation drastically inhibited transcriptional responses to IR exposure. However, sample shipment at different temperatures did not affect gene expression level except for SESN1. The transcriptional response to IR of specific genes depended on the cell fraction used, apart from FDXR, CCNG1, and SESN1.

CONCLUSION

In conclusion, temperature during the incubation period and cell fraction but not the storing conditions during transport can influence the transcriptional response of specific genes. However, FDXR and CCNG1 showed a consistent response under all the different conditions tested demonstrating their reliability as individual biological dosimetry biomarkers.

Telomere Length Dynamics and Chromosomal Instability for Predicting Individual Radiosensitivity and Risk via Machine Learning

The ability to predict a cancer patient's response to radiotherapy and risk of developing adverse late health effects would greatly improve personalized treatment regimens and individual outcomes. Telomeres represent a compelling biomarker of individual radiosensitivity and risk, as exposure can result in dysfunctional telomere pathologies that coincidentally overlap with many radiation-induced late effects, ranging from degenerative conditions like fibrosis and cardiovascular disease to proliferative pathologies like cancer. Here, telomere length was longitudinally assessed in a cohort of fifteen prostate cancer patients undergoing Intensity Modulated Radiation Therapy (IMRT) utilizing Telomere Fluorescence in situ Hybridization (Telo-FISH). To evaluate genome instability and enhance predictions for individual patient risk of secondary malignancy, chromosome aberrations were assessed utilizing directional Genomic Hybridization (dGH) for high-resolution inversion detection. We present the first implementation of individual telomere length data in a machine learning model, XGBoost, trained on pre-radiotherapy (baseline) and in vitro exposed (4 Gy γ-rays) telomere length measurements, to predict post radiotherapy telomeric outcomes, which together with chromosomal instability provide insight into individual radiosensitivity and risk for radiation-induced late 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.

High-throughput meta-analysis and validation of differentially expressed genes as potential biomarkers of ionizing radiation-response

BACKGROUND AND PURPOSE

The high-throughput analysis of gene expression in ionizing radiation (IR)-exposed human peripheral white blood cells (WBC) has emerged as a novel method for biodosimetry markers detection. We aimed to detect IR-exposure differential expressed genes (DEGs) as potential predictive biomarkers for biodosimetry and radioinduced-response.

MATERIALS AND METHODS

We performed a meta-analysis of raw data from public microarrays of ex vivo low linear energy transfer-irradiated human peripheral WBC. Functional enrichment and transcription factors (TF) detection from resulting DEGs were assessed. Six selected DEGs among studies were validated by qRT-PCR on mRNA from human peripheral blood samples from nine healthy human donors 24 h after ex vivo X-rays-irradiation.

RESULTS

We identified 275 DEGs after IR-exposure (parameters: |lfc| ≥ 0.7, q value <0.05), enriched in processes such as regulation after IR-exposure, DNA damage checkpoint, signal transduction by p53 and mitotic cell cycle checkpoint. Among these DEGs, DRAM1, NUDT15, PCNA, PLK2 and TIGAR were selected for qRT-PCR validation. Their expression levels significantly increased at 1-4 Gy respect to non-irradiated controls. Particularly, PCNA increased dose dependently. Curiously, TCF4 (Entrez Gene: 6925), detected as overrepresented TF in the radioinduced DEGs set, significantly decreased post-irradiation.

CONCLUSION

These six DEGs show potential to be proposed as candidates for IR-exposure biomarkers, considering their observed molecular radioinduced-response. Among them, TCF4, bioinformatically detected, was validated herein as an IR-responsive gene.

Development of the FAST-DOSE assay system for high-throughput biodosimetry and radiation triage

Following a large-scale radiological incident, there is a need for FDA-approved biodosimetry devices and biomarkers with the ability to rapidly determine past radiation exposure with sufficient accuracy for early population triage and medical management. Towards this goal, we have developed FAST-DOSE (Fluorescent Automated Screening Tool for Dosimetry), an immunofluorescent, biomarker-based system designed to reconstruct absorbed radiation dose in peripheral blood samples collected from potentially exposed individuals. The objective of this study was to examine the performance of the FAST-DOSE assay system to quantify intracellular protein changes in blood leukocytes for early biodosimetry triage from humanized NOD-scid-gamma (Hu-NSG) mice and non-human primates (NHPs) exposed to ionizing radiation up to 8 days after radiation exposure. In the Hu-NSG mice studies, the FAST-DOSE biomarker panel was able to generate delivered dose estimates at days 1, 2 and 3 post exposure, whereas in the NHP studies, the biomarker panel was able to successfully classify samples by dose categories below or above 2 Gy up to 8 days after total body exposure. These results suggest that the FAST-DOSE bioassay has large potential as a useful diagnostic tool for rapid and reliable screening of potentially exposed individuals to aid early triage decisions within the first week post-exposure.

CT Irradiation-induced Changes of Gene Expression within Peripheral Blood Cells

Computed tomography (CT) is a crucial element of medical imaging diagnostics. The widespread application of this technology has made CT one of the major contributors to medical radiation burden, despite the fact that doses per individual CT scan steadily decrease due to the advancement of technology. Epidemiological risk assessment of CT exposure is hampered by the fact that moderate adverse effects triggered by low doses of CT exposure are likely masked by statistical fluctuations. In light of these limitations, there is need of further insights into the biological processes induced by CT scans to complement the existing knowledge base of risk assessment. This prompted us to investigate the early transcriptomic response of ex vivo irradiated peripheral blood of three healthy individuals. Samples were irradiated employing a modern dual-source-CT-scanner with a tube voltage of 150 kV, resulting in an estimated effective dose of 9.6 mSv. RNA was isolated 1 h and 6 h after exposure, respectively, and subsequently analyzed by RNA deep sequencing. Differential gene expression analysis revealed shared upregulation of AEN, FDXR, and DDB2 6 h after exposure in all three probands. All three genes have previously been discussed as radiation responsive genes and have already been implicated in DNA damage response and cell cycle control after DNA damage. In summary, we substantiated the usefulness of AEN, FDXR, and DDB2 as RNA markers of low dose irradiation. Moreover, the upregulation of genes associated with DNA damage reminds one of the genotoxic nature of CT diagnostics even with the low doses currently applied.

Systemic modulation of stress and immune parameters in patients treated for prostate adenocarcinoma by intensity-modulated radiation therapy or stereotactic ablative body radiotherapy

Background

In this exploratory study, the impact of local irradiation on systemic changes in stress and immune parameters was investigated in eight patients treated with intensity-modulated radiation therapy (IMRT) or stereotactic ablative body radiotherapy (SABR) for prostate adenocarcinoma to gain deeper insights into how radiotherapy (RT) modulates the immune system.

Patients and methods

RT-qPCR, flow cytometry, metabolomics, and antibody arrays were used to monitor a panel of stress- and immune-related parameters before RT, after the first fraction (SABR) or the first week of treatment (IMRT), after the last fraction, and 3 weeks later in the blood of IMRT (N = 4) or SABR (N = 4) patients. Effect size analysis was used for comparison of results at different timepoints.

Results

Several parameters were found to be differentially modulated in IMRT and SABR patients: the expression of TGFB1, IL1B, and CCL3 genes; the expression of HLA-DR on circulating monocytes; the abundance and ratio of phosphatidylcholine and lysophosphatidylcholine metabolites in plasma. More immune modulators in plasma were modulated during IMRT than SABR, with only two common proteins, namely GDF-15 and Tim‑3.

Conclusion

Locally delivered RT induces systemic modulation of the immune system in prostate adenocarcinoma patients. IMRT and SABR appear to specifically affect distinct immune components.

Electronic supplementary material

The online version of this article (10.1007/s00066-020-01637-5) contains supplementary material, which is available to authorized users.

Radiation Exposure of Peripheral Mononuclear Blood Cells Alters the Composition and Function of Secreted Extracellular Vesicles

Normal tissue toxicity is a dose-limiting factor in radiation therapy. Therefore, a detailed understanding of the normal tissue response to radiation is necessary to predict the risk of normal tissue toxicity and to development strategies for tissue protection. One component of normal tissue that is continuously exposed during therapeutic irradiation is the circulating population of peripheral blood mononuclear cells (PBMC). PBMCs are highly sensitive to ionizing radiation (IR); however, little is known about how IR affects the PBMC response on a systemic level. It was the aim of this study to investigate whether IR was capable to induce changes in the composition and function of extracellular vesicles (EVs) secreted from PBMCs after radiation exposure to different doses. Therefore, whole blood samples from healthy donors were exposed to X-ray radiation in the clinically relevant doses of 0, 0.1, 2 or 6 Gy and PBMC-secreted EVs were isolated 72 h later. Proteome and miRNome analysis of EVs as well as functional studies were performed. Secreted EVs showed a dose-dependent increase in the number of significantly deregulated proteins and microRNAs. For both, proteome and microRNA data, principal component analysis showed a dose-dependent separation of control and exposed groups. Integrated pathway analysis of the radiation-regulated EV proteins and microRNAs consistently predicted an association of deregulated molecules with apoptosis, cell death and survival. Functional studies identified endothelial cells as an efficient EV recipient system, in which irradiation of recipient cells further increased the uptake. Furthermore an apoptosis suppressive effect of EVs from irradiated PBMCs in endothelial recipient cells was detected. In summary, this study demonstrates that IR modifies the communication between PBMCs and endothelial cells. EVs from irradiated PBMC donors were identified as transmitters of protective signals to irradiated endothelial cells. Thus, these data may lead to the discovery of biomarker candidates for radiation dosimetry and even more importantly, they suggest EVs as a novel systemic communication pathway between irradiated normal, non-cancer tissues.

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.

Discordant gene responses to radiation in humans and mice and the role of hematopoietically humanized mice in the search for radiation biomarkers

The mouse (Mus musculus) is an extensively used model of human disease and responses to stresses such as ionizing radiation. As part of our work developing gene expression biomarkers of radiation exposure, dose, and injury, we have found many genes are either up-regulated (e.g. CDKN1A, MDM2, BBC3, and CCNG1) or down-regulated (e.g. TCF4 and MYC) in both species after irradiation at ~4 and 8 Gy. However, we have also found genes that are consistently up-regulated in humans and down-regulated in mice (e.g. DDB2, PCNA, GADD45A, SESN1, RRM2B, KCNN4, IFI30, and PTPRO). Here we test a hematopoietically humanized mouse as a potential in vivo model for biodosimetry studies, measuring the response of these 14 genes one day after irradiation at 2 and 4 Gy, and comparing it with that of human blood irradiated ex vivo, and blood from whole body irradiated mice. We found that human blood cells in the hematopoietically humanized mouse in vivo environment recapitulated the gene expression pattern expected from human cells, not the pattern seen from in vivo irradiated normal mice. The results of this study support the use of hematopoietically humanized mice as an in vivo model for screening of radiation response genes relevant to 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.

New Approaches for Quantitative Reconstruction of Radiation Dose in Human Blood Cells

In the event of a nuclear attack or large-scale radiation event, there would be an urgent need for assessing the dose to which hundreds or thousands of individuals were exposed. Biodosimetry approaches are being developed to address this need, including transcriptomics. Studies have identified many genes with potential for biodosimetry, but, to date most have focused on classification of samples by exposure levels, rather than dose reconstruction. We report here a proof-of-principle study applying new methods to select radiation-responsive genes to generate quantitative, rather than categorical, radiation dose reconstructions based on a blood sample. We used a new normalization method to reduce effects of variability of signal intensity in unirradiated samples across studies; developed a quantitative dose-reconstruction method that is generally under-utilized compared to categorical methods; and combined these to determine a gene set as a reconstructor. Our dose-reconstruction biomarker was trained using two data sets and tested on two independent ones. It was able to reconstruct dose up to 4.5 Gy with root mean squared error (RMSE) of ± 0.35 Gy on a test dataset using the same platform, and up to 6.0 Gy with RMSE of ± 1.74 Gy on a test set using a different platform.

Transcriptomic responses in mouse blood during the first week after in vivo gamma irradiation

Due to limitations of available human models for development of gene expression based radiation biodosimetry, many such studies have made use of mouse models. To provide a broad view of the gene expression response to irradiation in the mouse, we have exposed male C57BL/6 mice to 0, 1.5, 3, 6 or 10 Gy of gamma rays, sacrificing groups of the mice at 1, 2, 3, 5, or 7 days after exposure. We then profiled global gene expression in blood from individual mice using Agilent microarrays. In general, we found increasing numbers of genes differentially expressed with increasing dose, with more prolonged responses after the higher doses. Gene ontology analysis showed a similar pattern, with more biological processes enriched among the genes responding to higher doses, and at later times after exposure. Clustering the timecourse expression data using maSigPro identified four broad patterns of response, representing different gene ontology functions. The largest of these clusters included genes with initially decreased expression followed by increased expression at later times, a pattern of expression previously reported for several genes following neutron exposure. Another gene cluster showing consistent down regulation suggests genes useful for biodosimetry throughout the first week after exposure can be identified.

Human Transcriptomic Response to Mixed Neutron-Photon Exposures Relevant to an Improvised Nuclear Device

In the possible event of a detonation of an improvised nuclear device (IND), the immediate radiation would consist of both photons (gamma rays) and neutrons. Since neutrons generally have a high relative biological effectiveness (RBE) for most physiological end points, it is important to understand the effect that neutrons would have on the biodosimetry methods that are being developed for medical triage purposes. We previously compared the transcriptomic response in human blood after neutron and photon irradiation. In this study, we analyzed the effect of mixed-field-neutron-photon radiation on gene expression responses in human peripheral blood, to elucidate the neutron contribution in the setting of a radiation exposure from an IND detonation. We used four combinations of mixed neutron-photon exposures, with increasing percentages of neutrons, to a cumulative dose of 3 Gy. The mixed-field exposures consisted of 0%, 5%, 15% and 25% of neutrons, where 0% corresponds to 3 Gy of pure X rays. A maximum neutron exposure, corresponding to 83% neutrons (0.75 Gy) was also used in the study. Increases were observed in both the number and expression level of genes, with increasing percentages of neutrons from 0% to 25% in the mixed-field exposures. Gene ontology analysis showed an overall predominance of TP53 signaling among upregulated genes across all exposures. Some TP53 regulated genes, such as EDA2R, GDF15 and VWCE, demonstrated increased expression with increasing neutron percentages in mixed-field exposures. Immune response, specifically natural-killer-cell mediated signaling, was the most significant biological process associated with downregulated genes. We observed significant suppression of T-cell-mediated signaling in mixed-field exposures, which was absent in the response to pure photons. In this first study investigating gene expression in human blood cells exposed to mixed neutron-photon fields similar to an actual IND explosion, we have identified a number of genes responding to the 3 Gy dose that showed increasing expression as the neutron percentage increased. Such genes may serve as better indicators of the expected biological damage than a report of total physical dose, and thus provide more relevant information for treating physicians.

Overexpression of the immediate early response 5 gene increases the radiosensitivity of HeLa cells

The effects of the immediate early response 5 (IER5) gene on the sensitivity of HeLa cells to radiation remain unclear. In the present study, stably transfected HeLa cells resulting in the knockdown or overexpression of IER5 were investigated. In addition, xenografts of normal, IER5-silenced and -overexpressed HeLa cells were injected into nude mice and examined. The results demonstrated that the radiosensitivity of the IER5-overexpressed HeLa cells was significantly increased compared with that of the normal and IER5-silenced cells. The upregulation of IER5 effectively decreased cell proliferation and IER5 silencing promoted cell proliferation compared with that in the normal HeLa cells. Following irradiation of the cells with IER5 knockdown, cell cycle was arrested at the G₂/M phase and an increase in the proportion of S phase cells was observed. By contrast, the overexpression of IER5 led to an increase in the proportion of G₁ phase cells. Furthermore, the upregulation of IER5 inhibited tumor growth in vivo. The present findings demonstrate that the IER5 gene affects the radiosensitivity of HeLa cells and serves an important role in cell proliferation, suggesting that this gene may be a potential radiotherapeutic target in cervical cancer.

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

Radiological exposure scenarios involving large numbers of people require a rapid and high-throughput method to identify the unexposed, and those exposed to low- and high-dose radiation. Those with high-dose exposure, e.g., >2 Gy and depending on host characteristics, may develop severe hematological acute radiation syndrome (HARS), requiring hospitalization and treatment. Previously, we identified a set of genes that discriminated these clinically relevant groups. In the current work, we examined the utility of gene expression changes to classify 1,000 split blood samples into HARS severity scores of H0, H1 and H2-4, with the latter indicating likely hospitalization. In several previous radiation dose experiments, we determined that these HARS categories corresponded, respectively, to doses of 0 Gy (unexposed), 0.5 Gy and 5 Gy. The main purpose of this work was to assess the rapidity of blood sample processing using targeted next-generation sequencing (NGS). Peripheral blood samples from two healthy donors were X-ray irradiated in vitro and incubated at 37°C for 24 h. A total of 1,000 samples were evaluated by laboratory personnel blinded to the radiation dose. Changes in gene expression of FDXR, DDB2, POU2AF1 and WNT3 were examined with qRT-PCR as positive controls. Targeted NGS (TREX) was used on all samples for the same four genes. Agreement using both methods was almost 78%. Using NGS, all 1,000 samples were processed within 30 h. Classification of the HARS severity categories corresponding to radiation dose had an overall agreement ranging between 90-97%. Depending on the end point, either a combination of all genes or FDXR alone (H0 HARS or unexposed) provided the best classification. Using this optimized automated methodology, we assessed 100× more samples approximately three times faster compared to standard cytogenetic studies. We showed that a small set of genes, rather than a complex constellation of genes, provided robust positive (97%) and negative (97%) predictive values for HARS categories and radiation doses of 0, 0.5 and 5 Gy. The findings of this study support the potential utility of early radiation-induced gene expression changes for high-throughput biodosimetry and rapid identification of irradiated persons in need of hospitalization.

Impact of inflammatory signaling on radiation biodosimetry: mouse model of inflammatory bowel disease

Background

Ionizing Radiation (IR) is a known pro-inflammatory agent and in the process of development of biomarkers for radiation biodosimetry, a chronic inflammatory disease condition could act as a confounding factor. Hence, it is important to develop radiation signatures that can distinguish between IR-induced inflammatory responses and pre-existing disease. In this study, we compared the gene expression response of a genetically modified mouse model of inflammatory bowel disease (Il10^−/−) with that of a normal wild-type mouse to potentially develop transcriptomics-based biodosimetry markers that can predict radiation exposure in individuals regardless of pre-existing inflammatory condition.

Results

Wild-type (WT) and Il10^−/− mice were exposed to whole body irradiation of 7 Gy X-rays. Gene expression responses were studied using high throughput whole genome microarrays in peripheral blood 24 h post-irradiation. Analysis resulted in identification of 1962 and 1844 genes differentially expressed (p < 0.001, FDR < 10%) after radiation exposure in Il10^−/− and WT mice respectively. A set of 155 genes was also identified as differentially expressed between WT and Il10^−/− mice at the baseline pre-irradiation level. Gene ontology analysis revealed that the 155 baseline differentially expressed genes were mainly involved in inflammatory response, glutathione metabolism and collagen deposition. Analysis of radiation responsive genes revealed that innate immune response and p53 signaling processes were strongly associated with up-regulated genes, whereas B-cell development process was found to be significant amongst downregulated genes in the two genotypes. However, specific immune response pathways like MHC based antigen presentation, interferon signaling and hepatic fibrosis were associated with radiation responsive genes in Il10^−/− mice but not WT mice. Further analysis using the IPA prediction tool revealed significant differences in the predicted activation status of T-cell mediated signaling as well as regulators of inflammation between WT and Il10^−/− after irradiation.

Conclusions

Using a mouse model we established that an inflammatory disease condition could affect the expression of many radiation responsive genes. Nevertheless, we identified a panel of genes that, regardless of disease condition, could predict radiation exposure. Our results highlight the need for consideration of pre-existing conditions in the population in the process of development of reliable biodosimetry markers.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5689-y) contains supplementary material, which is available to authorized users.

Gene expression-based biodosimetry for radiological incidents: assessment of dose and time after radiation exposure

PURPOSE

In order to ensure efficient use of medical resources following a radiological incident, there is an urgent need for high-throughput time-efficient biodosimetry tools. In the present study, we tested the applicability of a gene expression signature for the prediction of exposure dose as well as the time elapsed since irradiation.

MATERIALS AND METHODS

We used whole blood samples from seven healthy volunteers as reference samples (X-ray doses: 0, 25, 50, 100, 500, 1000, and 2000 mGy; time points: 8, 12, 24, 36 and 48 h) and samples from seven other individuals as 'blind samples' (20 samples in total).

RESULTS

Gene expression values normalized to the reference gene without normalization to the unexposed controls were sufficient to predict doses with a correlation coefficient between the true and the predicted doses of 0.86. Importantly, we could also classify the samples according to the time since exposure with a correlation coefficient between the true and the predicted time point of 0.96. Because of the dynamic nature of radiation-induced gene expression, this feature will be of critical importance for adequate gene expression-based dose prediction in a real emergency situation. In addition, in this study we also compared different methodologies for RNA extraction available on the market and suggested the one most suitable for emergency situation which does not require on-spot availability of any specific reagents or equipment.

CONCLUSIONS

Our results represent an important advancement in the application of gene expression for biodosimetry purposes.

Candidate protein markers for radiation biodosimetry in the hematopoietically humanized mouse model

After a radiological incident, there is an urgent need for fast and reliable bioassays to identify radiation-exposed individuals within the first week post exposure. This study aimed to identify candidate radiation-responsive protein biomarkers in human lymphocytes in vivo using humanized NOD scid gamma (Hu-NSG) mouse model. Three days after X-irradiation (0–2 Gy, 88 cGy/min), human CD45+ lymphocytes were collected from the Hu-NSG mouse spleen and quantitative changes in the proteome of the human lymphocytes were analysed by mass spectrometry. Forty-six proteins were differentially expressed in response to radiation exposure. FDXR, BAX, DDB2 and ACTN1 proteins were shown to have dose-dependent response with a fold change greater than 2. When these proteins were used to estimate radiation dose by linear regression, the combination of FDXR, ACTN1 and DDB2 showed the lowest mean absolute errors (≤0.13 Gy) and highest coefficients of determination (R² = 0.96). Biomarker validation studies were performed in human lymphocytes 3 days after irradiation in vivo and in vitro. In conclusion, this is the first study to identify radiation-induced human protein signatures in vivo using the humanized mouse model and develop a protein panel which could be used for the rapid assessment of absorbed dose 3 days after radiation exposure.

Biodosimetric transcriptional and proteomic changes are conserved in irradiated human tissue

Transcriptional dosimetry is an emergent field of radiobiology aimed at developing robust methods for detecting and quantifying absorbed doses using radiation-induced fluctuations in gene expression. A combination of RNA sequencing, array-based and quantitative PCR transcriptomics in cellular, murine and various ex vivo human models has led to a comprehensive description of a fundamental set of genes with demonstrable dosimetric qualities. However, these are yet to be validated in human tissue due to the scarcity of in situ-irradiated source material. This represents a major hurdle to the continued development of transcriptional dosimetry. In this study, we present a novel evaluation of a previously reported set of dosimetric genes in human tissue exposed to a large therapeutic dose of radiation. To do this, we evaluated the quantitative changes of a set of dosimetric transcripts consisting of FDXR, BAX, BCL2, CDKN1A, DDB2, BBC3, GADD45A, GDF15, MDM2, SERPINE1, TNFRSF10B, PLK3, SESN2 and VWCE in guided pre- and post-radiation (2 weeks) prostate cancer biopsies from seven patients. We confirmed the prolonged dose-responsivity of most of these transcripts in in situ-irradiated tissue. BCL2, GDF15, and to some extent TNFRSF10B, were markedly unreliable single markers of radiation exposure. Nevertheless, as a full set, these genes reliably segregated non-irradiated and irradiated tissues and predicted radiation absorption on a patient-specific basis. We also confirmed changes in the translated protein product for a small subset of these dosimeters. This study provides the first confirmatory evidence of an existing dosimetric gene set in less-accessible tissues-ensuring peripheral responses reflect tissue-specific effects. Further work will be required to determine if these changes are conserved in different tissue types, post-radiation times and doses.

Influence of Confounding Factors on Radiation Dose Estimation Using In Vivo Validated Transcriptional Biomarkers

For triage purposes following a nuclear accident, blood-based gene expression biomarkers can provide rapid dose estimates for a large number of individuals. Ionizing-radiation-responsive genes are regulated through the DNA damage-response pathway, which includes activation of multiple transcription factors. Modulators of this pathway could potentially affect the response of these biomarkers and consequently compromise accurate dose estimation calculations. In the present study, four potential confounding factors were selected: cancer condition, sex, simulated bacterial infection (lipopolysaccharide), and curcumin, an anti-inflammatory/antioxidant agent. Their potential influence on the transcriptional response to radiation of the genes CCNG1 and PHPT1, two biomarkers of radiation exposure ex vivo, was assessed. First, both CCNG1 and PHPT1 were detected in vivo in blood samples from radiotherapy patients and as such were validated as biomarkers of exposure. Importantly, their basal expression level was slightly but significantly affected in vivo by patients' cancer condition. Moreover, lipopolysaccharide stimulation of blood irradiated ex vivo led to a significant modification of CCNG1 and PHPT1 transcriptional response in a dose- and time-dependent manner with opposite regulatory effects. Curcumin also affected CCNG1 and PHPT1 transcriptional response counteracting some of the radiation induction. No differences were observed based on sex. Dose estimations calculated using linear regression were affected by lipopolysaccharide and curcumin. In conclusion, several confounding factors tested in this study can indeed modulate the transcriptional response of CCNG1 and PHPT1 and consequently can affect radiation exposure dose estimations but not to a level which should prevent the biomarkers' use for triage purposes.

Candidate gene biodosimetry markers of exposure to external ionizing radiation in human blood: A systematic review

Purpose

To compile a list of genes that have been reported to be affected by external ionizing radiation (IR) and to assess their performance as candidate biomarkers for individual human radiation dosimetry.

Methods

Eligible studies were identified through extensive searches of the online databases from 1978 to 2017. Original English-language publications of microarray studies assessing radiation-induced changes in gene expression levels in human blood after external IR were included. Genes identified in at least half of the selected studies were retained for bio-statistical analysis in order to evaluate their diagnostic ability.

Results

24 studies met the criteria and were included in this study. Radiation-induced expression of 10,170 unique genes was identified and the 31 genes that have been identified in at least 50% of studies (12/24 studies) were selected for diagnostic power analysis. Twenty-seven genes showed a significant Spearman’s correlation with radiation dose. Individually, TNFSF4, FDXR, MYC, ZMAT3 and GADD45A provided the best discrimination of radiation dose < 2 Gy and dose ≥ 2 Gy according to according to their maximized Youden’s index (0.67, 0.55, 0.55, 0.55 and 0.53 respectively). Moreover, 12 combinations of three genes display an area under the Receiver Operating Curve (ROC) curve (AUC) = 1 reinforcing the concept of biomarker combinations instead of looking for an ideal and unique biomarker.

Conclusion

Gene expression is a promising approach for radiation dosimetry assessment. A list of robust candidate biomarkers has been identified from analysis of the studies published to date, confirming for example the potential of well-known genes such as FDXR and TNFSF4 or highlighting other promising gene such as ZMAT3. However, heterogeneity in protocols and analysis methods will require additional studies to confirm these results.

Ionizing radiation exposure: hazards, prevention, and biomarker screening

Radiation is a form of energy derived from a source that is propagated through material in space. It consists of ionizing radiation or nonionizing radiation. Ionizing radiation is a feature of the environment and an important tool in medical treatment, but it can cause serious damage to organisms. A number of protective measures and standards of protection have been proposed to protect against radiation. There is also a need for biomarkers to rapidly assess individual doses of radiation, which can not only estimate the dose of radiation but also determine its effects on health. Proteomics, genomics, metabolomics, and lipidomics have been widely used in the search for such biomarkers. These topics are discussed in depth in this review.

Gene Expression in Parp1 Deficient Mice Exposed to a Median Lethal Dose of Gamma Rays

There is a current interest in the development of biodosimetric methods for rapidly assessing radiation exposure in the wake of a large-scale radiological event. This work was initially focused on determining the exposure dose to an individual using biological indicators. Gene expression signatures show promise for biodosimetric application, but little is known about how these signatures might translate for the assessment of radiological injury in radiosensitive individuals, who comprise a significant proportion of the general population, and who would likely require treatment after exposure to lower doses. Using Parp1^-/- mice as a model radiation-sensitive genotype, we have investigated the effect of this DNA repair deficiency on the gene expression response to radiation. Although Parp1 is known to play general roles in regulating transcription, the pattern of gene expression changes observed in Parp1^-/- mice 24 h postirradiation to a LD_50/30 was remarkably similar to that in wild-type mice after exposure to LD_50/30. Similar levels of activation of both the p53 and NFκB radiation response pathways were indicated in both strains. In contrast, exposure of wild-type mice to a sublethal dose that was equal to the Parp1^-/- LD_50/30 resulted in a lower magnitude gene expression response. Thus, Parp1^-/- mice displayed a heightened gene expression response to radiation, which was more similar to the wild-type response to an equitoxic dose than to an equal absorbed dose. Gene expression classifiers trained on the wild-type data correctly identified all wild-type samples as unexposed, exposed to a sublethal dose or exposed to an LD_50/30. All unexposed samples from Parp1^-/- mice were also correctly classified with the same gene set, and 80% of irradiated Parp1^-/- samples were identified as exposed to an LD_50/30. The results of this study suggest that, at least for some pathways that may influence radiosensitivity in humans, specific gene expression signatures have the potential to accurately detect the extent of radiological injury, rather than serving only as a surrogate of physical radiation dose.

The first in vivo multiparametric comparison of different radiation exposure biomarkers in human blood

The increasing risk of acute large-scale radiological/nuclear exposures of population underlines the necessity of developing new, rapid and high throughput biodosimetric tools for estimation of received dose and initial triage. We aimed to compare the induction and persistence of different radiation exposure biomarkers in human peripheral blood in vivo. Blood samples of patients with indicated radiotherapy (RT) undergoing partial body irradiation (PBI) were obtained soon before the first treatment and then after 24 h, 48 h, and 5 weeks; i.e. after 1, 2, and 25 fractionated RT procedures. We collected circulating peripheral blood from ten patients with tumor of endometrium (1.8 Gy per fraction) and eight patients with tumor of head and neck (2.0–2.121 Gy per fraction). Incidence of dicentrics and micronuclei was monitored as well as determination of apoptosis and the transcription level of selected radiation-responsive genes. Since mitochondrial DNA (mtDNA) has been reported to be a potential indicator of radiation damage in vitro, we also assessed mtDNA content and deletions by novel multiplex quantitative PCR. Cytogenetic data confirmed linear dose-dependent increase in dicentrics (p < 0.01) and micronuclei (p < 0.001) in peripheral blood mononuclear cells after PBI. Significant up-regulations of five previously identified transcriptional biomarkers of radiation exposure (PHPT1, CCNG1, CDKN1A, GADD45, and SESN1) were also found (p < 0.01). No statistical change in mtDNA deletion levels was detected; however, our data indicate that the total mtDNA content decreased with increasing number of RT fractions. Interestingly, the number of micronuclei appears to correlate with late radiation toxicity (r² = 0.9025) in endometrial patients suggesting the possibility of predicting the severity of RT-related toxicity by monitoring this parameter. Overall, these data represent, to our best knowledge, the first study providing a multiparametric comparison of radiation biomarkers in human blood in vivo, which have potential for improving biological dosimetry.

Global Gene Expression Response in Mouse Models of DNA Repair Deficiency after Gamma Irradiation

In the event of an improvised nuclear device or "dirty bomb" in a highly populated area, potentially hundreds of thousands of people will require screening to ensure that exposed individuals receive appropriate treatment. For this reason, there is a need to develop tools for high-throughput radiation biodosimetry. Gene expression represents an emerging approach to biodosimetry and could potentially provide an estimate of both absorbed dose and individual radiation-induced injury. Since approximately 2-4% of humans are thought to be radiosensitive, and would suffer greater radiological injury at a given dose than members of the general population, it is of interest to explore the potential impact of such sensitivity on the biodosimetric gene expression signatures being developed. In this study, we used wild-type mice and genetically engineered mouse models deficient in two DNA repair pathways that can contribute to radiation sensitivity to estimate the maximum effect of differences in radiosensitivity. We compared gene expression in response to a roughly equitoxic (LD_50/30) dose of gamma rays in wild-type C57BL/6 (8 Gy) and DNA double-strand break repair-deficient Atm^-/- (4 Gy) and Prkdc^scid (3 Gy) mutants of C57BL/6. Overall, 780 genes were significantly differentially expressed in wild-type mice one day postirradiation, 232 in Atm^-/- and 269 in Prkdc^scid. Upstream regulators including TP53 and NFκB were predicted to be activated by radiation exposure in the wild-type mice, but not in either of the DNA repair-deficient mutant strains. There was also a significant muting of the apparent inflammatory response triggered by radiation in both mutant strains. These differences impacted the ability of gene expression signatures developed in wild-type mice to detect potentially fatal radiation exposure in the DNA repair-deficient mice, with the greatest impact on Atm^-/- mice. However, the inclusion of mutant mice in gene selection vastly improved performance of the classifiers.