Gene expression comparisons performed for biodosimetry purposes on in vitro peripheral blood cellular subsets and irradiated individuals

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.

High-throughput screening strategies for space-based radiation countermeasure discovery

As humanity begins to venture further into space, approaches to better protect astronauts from the hazards found in space need to be developed. One particular hazard of concern is the complex radiation that is ever present in deep space. Currently, it is unlikely enough spacecraft shielding could be launched that would provide adequate protection to astronauts during long-duration missions such as a journey to Mars and back. In an effort to identify other means of protection, prophylactic radioprotective drugs have been proposed as a potential means to reduce the biological damage caused by this radiation. Unfortunately, few radioprotectors have been approved by the FDA for usage and for those that have been developed, they protect normal cells/tissues from acute, high levels of radiation exposure such as that from oncology radiation treatments. To date, essentially no radioprotectors have been developed that specifically counteract the effects of chronic low-dose rate space radiation. This review highlights how high-throughput screening (HTS) methodologies could be implemented to identify such a radioprotective agent. Several potential target, pathway, and phenotypic assays are discussed along with potential challenges towards screening for radioprotectors. Utilizing HTS strategies such as the ones proposed here have the potential to identify new chemical scaffolds that can be developed into efficacious radioprotectors that are specifically designed to protect astronauts during deep space journeys. The overarching goal of this review is to elicit broader interest in applying drug discovery techniques, specifically HTS towards the identification of radiation countermeasures designed to be efficacious towards the biological insults likely to be encountered by astronauts on long duration voyages.

Cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose

In the search for biological markers after a large-scale exposure of the human population to radiation, gene expression is a sensitive endpoint easily translatable to in-field high throughput applications. Primarily, the ex-vivo irradiated healthy human blood model has been used to generate available gene expression datasets. This model has limitations i.e., lack of signaling from other irradiated tissues and deterioration of blood cells cultures over time. In vivo models are needed; therefore, we present our novel approach to define a gene signature in mouse blood cells that quantitatively correlates with radiation dose (at 1 Gy/min). Starting with available microarray datasets, we selected 30 radiation-responsive genes and performed cross-validation/training–testing data splits to downselect 16 radiation-responsive genes. We then tested these genes in an independent cohort of irradiated adult C57BL/6 mice (50:50 both sexes) and measured mRNA by quantitative RT-PCR in whole blood at 24 h. Dose reconstruction using net signal (difference between geometric means of top 3 positively correlated and top 4 negatively correlated genes with dose), was highly improved over the microarrays, with a root mean square error of ± 1.1 Gy in male and female mice combined. There were no significant sex-specific differences in mRNA or cell counts after irradiation.

Transcriptomes of Wet Skin Biopsies Predict Outcomes after Ionizing Radiation Exposure with Potential Dosimetric Applications in a Mouse Model

Countermeasures for radiation diagnosis, prognosis, and treatment are trailing behind the proliferation of nuclear energy and weaponry. Radiation injury mechanisms at the systems biology level are not fully understood. Here, mice skin biopsies at h2, d4, d7, d21, and d28 after exposure to 1, 3, 6, or 20 Gy whole-body ionizing radiation were evaluated for the potential application of transcriptional alterations in radiation diagnosis and prognosis. Exposure to 20 Gy was lethal by d7, while mice who received 1, 3, or 6 Gy survived the 28-day time course. A Sammon plot separated samples based on survival and time points (TPs) within lethal (20 Gy) and sublethal doses. The differences in the numbers, regulation mode, and fold change of significantly differentially transcribed genes (SDTGs, p < 0.05 and FC > 2) were identified between lethal and sublethal doses, and down and upregulation dominated transcriptomes during the first post-exposure week, respectively. The numbers of SDTGs and the percentages of upregulated ones revealed stationary downregulation post-lethal dose in contrast to responses to sublethal doses which were dynamic and largely upregulated. Longitudinal up/downregulated SDTGs ratios suggested delayed and extended responses with increasing IR doses in the sublethal range and lethal-like responses in late TPs. This was supported by the distributions of common and unique genes across TPs within each dose. Several genes with potential dosimetric marker applications were identified. Immune, fibrosis, detoxification, hematological, neurological, gastric, cell survival, migration, and proliferation radiation response pathways were identified, with the majority predicted to be activated after sublethal and inactivated after lethal exposures, particularly during the first post-exposure week.

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.

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.

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

PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Single-Cell RNA-Sequencing Identifies Activation of TP53 and STAT1 Pathways in Human T Lymphocyte Subpopulations in Response to Ex Vivo Radiation Exposure

Detrimental health consequences from exposure to space radiation are a major concern for long-duration human exploration missions to the Moon or Mars. Cellular responses to radiation are expected to be heterogeneous for space radiation exposure, where only high-energy protons and other particles traverse a fraction of the cells. Therefore, assessing DNA damage and DNA damage response in individual cells is crucial in understanding the mechanisms by which cells respond to different particle types and energies in space. In this project, we identified a cell-specific signature for radiation response by using single-cell transcriptomics of human lymphocyte subpopulations. We investigated gene expression in individual human T lymphocytes 3 h after ex vivo exposure to 2-Gy gamma rays while using the single-cell sequencing technique (10X Genomics). In the process, RNA was isolated from ~700 irradiated and ~700 non-irradiated control cells, and then sequenced with ~50 k reads/cell. RNA in each of the cells was distinctively barcoded prior to extraction to allow for quantification for individual cells. Principal component and clustering analysis of the unique molecular identifier (UMI) counts classified the cells into three groups or sub-types, which correspond to CD4+, naïve, and CD8+/NK cells. Gene expression changes after radiation exposure were evaluated using negative binomial regression. On average, BBC3, PCNA, and other TP53 related genes that are known to respond to radiation in human T cells showed increased activation. While most of the TP53 responsive genes were upregulated in all groups of cells, the expressions of IRF1, STAT1, and BATF were only upregulated in the CD4+ and naïve groups, but were unchanged in the CD8+/NK group, which suggests that the interferon-gamma pathway does not respond to radiation in CD8+/NK cells. Thus, single-cell RNA sequencing technique was useful for simultaneously identifying the expression of a set of genes in individual cells and T lymphocyte subpopulation after gamma radiation exposure. The degree of dependence of UMI counts between pairs of upregulated genes was also evaluated to construct a similarity matrix for cluster analysis. The cluster analysis identified a group of TP53-responsive genes and a group of genes that are involved in the interferon gamma pathway, which demonstrate the potential of this method for identifying previously unknown groups of genes with similar expression patterns.

Use of a Humanized Mouse Model System in the Validation of Human Radiation Biodosimetry Standards

After a planned or unplanned radiation exposure, determination of absorbed dose has great clinical importance, informing treatment and triage decisions in the exposed individuals. Biodosimetry approaches allow for determination of dose in the absence of physical measurement apparatus. The current state-of-the-art biodosimetry method is based on the frequency of induced dicentric chromosomes in peripheral blood T cells, which is proportional to the absorbed radiation dose. Since dose-response curves used for obtaining absorbed dose for humans are based on data sourced from in vitro studies, a concerning discrepancy may be present in the reported dose. Specifically, T-cell survival after in vitro irradiation is much higher than that measured in humans in vivo and, in addition, is not dose dependent over some dose ranges. We hypothesized that these differences may lead to inappropriately inflated dicentric frequencies after in vitro irradiation when compared with in vivo irradiation of the same samples. This may lead to underestimation of the in vivo dose. To test this hypothesis, we employed the humanized mouse model, which allowed direct comparison of cell depletion and dicentric frequencies in human T cells irradiated in vivo and in vitro. The results showed similar dicentric chromosome induction frequencies measured in vivo and in vitro when assessed 24 h postirradiation despite the differences in cell survival. These results appear to validate the use of in vitro data for the estimation of the absorbed dose in human radiation biodosimetry.

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.

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.

Developing Human Radiation Biodosimetry Models: Testing Cross-Species Conversion Approaches Using an Ex Vivo Model System

In the event of a large-scale radiation exposure, accurate and quick assessment of radiation dose received would be critical for triage and medical treatment of large numbers of potentially exposed individuals. Current methods of biodosimetry, such as the dicentric chromosome assay, are time consuming and require sophisticated equipment and highly trained personnel. Therefore, scalable biodosimetry approaches, including gene expression profiles in peripheral blood cells, are being investigated. Due to the limited availability of appropriate human samples, biodosimetry development has relied heavily on mouse models, which are not directly applicable to human response. Therefore, to explore the feasibility of using non-human primate (NHP) models to build and test a biodosimetry algorithm for use in humans, we irradiated ex vivo peripheral blood samples from both humans and rhesus macaques with doses of 0, 2, 5, 6 and 7 Gy, and compared the gene expression profiles 24 h later using Agilent human microarrays. Among the dose-responsive genes in human and using non-human primate, 52 genes showed highly correlated expression patterns between the species, and were enriched in p53/DNA damage response, apoptosis and cell cycle-related genes. When these interspecies-correlated genes were used to build biodosimetry models with using NHP data, the mean prediction accuracy on non-human primate samples was about 90% within 1 Gy of delivered dose in leave-one-out cross-validation. However, tests on human samples suggested that human gene expression values may need to be adjusted prior to application of the NHP model. A "multi-gene" approach utilizing all gene values for cross-species conversion and applying the converted values on the NHP biodosimetry models, gave a leave-one-out cross-validation prediction accuracy for human samples highly comparable (up to 94%) to that for non-human primates. Overall, this study demonstrates that a robust NHP biodosimetry model can be built using interspecies-correlated genes, and that, by using multiple regression-based cross-species conversion of expression values, absorbed dose in human samples can be accurately predicted by the NHP model.

Ionizing radiation biomarkers in epidemiological studies - An update

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

Evaluating biomarkers to model cancer risk post cosmic ray exposure

Robust predictive models are essential to manage the risk of radiation-induced carcinogenesis. Chronic exposure to cosmic rays in the context of the complex deep space environment may place astronauts at high cancer risk. To estimate this risk, it is critical to understand how radiation-induced cellular stress impacts cell fate decisions and how this in turn alters the risk of carcinogenesis. Exposure to the heavy ion component of cosmic rays triggers a multitude of cellular changes, depending on the rate of exposure, the type of damage incurred and individual susceptibility. Heterogeneity in dose, dose rate, radiation quality, energy and particle flux contribute to the complexity of risk assessment. To unravel the impact of each of these factors, it is critical to identify sensitive biomarkers that can serve as inputs for robust modeling of individual risk of cancer or other long-term health consequences of exposure. Limitations in sensitivity of biomarkers to dose and dose rate, and the complexity of longitudinal monitoring, are some of the factors that increase uncertainties in the output from risk prediction models. Here, we critically evaluate candidate early and late biomarkers of radiation exposure and discuss their usefulness in predicting cell fate decisions. Some of the biomarkers we have reviewed include complex clustered DNA damage, persistent DNA repair foci, reactive oxygen species, chromosome aberrations and inflammation. Other biomarkers discussed, often assayed for at longer points post exposure, include mutations, chromosome aberrations, reactive oxygen species and telomere length changes. We discuss the relationship of biomarkers to different potential cell fates, including proliferation, apoptosis, senescence, and loss of stemness, which can propagate genomic instability and alter tissue composition and the underlying mRNA signatures that contribute to cell fate decisions. Our goal is to highlight factors that are important in choosing biomarkers and to evaluate the potential for biomarkers to inform models of post exposure cancer risk. Because cellular stress response pathways to space radiation and environmental carcinogens share common nodes, biomarker-driven risk models may be broadly applicable for estimating risks for other carcinogens.

Radiation-induced alternative transcription and splicing events and their applicability to practical biodosimetry

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

Quantification of damage due to low-dose radiation exposure in mice: construction and application of a biodosimetric model using mRNA indicators in circulating white blood cells

Biodosimetry, the measurement of radiation damage in a biologic sample, is a reliable tool for increasing the accuracy of dose estimation. Although established chromosome analyses are suitable for estimating the absorbed dose after high-dose irradiation, biodosimetric methodology to measure damage following low-dose exposure is underdeveloped. RNA analysis of circulating blood containing radiation-sensitive cells is a candidate biodosimetry method. Here we quantified RNA from a small amount of blood isolated from mice following low-dose body irradiation (<0.5 Gy) aimed at developing biodosimetric tools for situations that are difficult to study in humans. By focusing on radiation-sensitive undifferentiated cells in the blood based on Myc RNA expression, we quantified the relative levels of RNA for DNA damage-induced (DDI) genes, such as Bax, Bbc3 and Cdkn1a. The RNA ratios of DDI genes/Myc in the blood increased in a dose-dependent manner 4 h after whole-body irradiation at doses ranging from 0.1 to 0.5 Gy (air-kerma) of X-rays, regardless of whether the mice were in an active or resting state. The RNA ratios were significantly increased after 0.014 Gy (air-kerma) of single X-ray irradiation. The RNA ratios were directly proportional to the absorbed doses in water ranging from 0.1 to 0.5 Gy, based on gamma-irradiation from (137)Cs. Four hours after continuous irradiation with gamma-rays or by internal contamination with a beta-emitter, the increased RNA ratios resembled those following single irradiation. These findings indicate that the RNA status can be utilized as a biodosimetric tool to estimate low-dose radiation when focusing on undifferentiated cells in blood.

Global Gene Expression Alterations as a Crucial Constituent of Human Cell Response to Low Doses of Ionizing Radiation Exposure

Exposure to ionizing radiation (IR) is inevitable to humans in real-life scenarios; the hazards of IR primarily stem from its mutagenic, carcinogenic, and cell killing ability. For many decades, extensive research has been conducted on the human cell responses to IR delivered at a low dose/low dose (LD) rate. These studies have shown that the molecular-, cellular-, and tissue-level responses are different after low doses of IR (LDIR) compared to those observed after a short-term high-dose IR exposure (HDIR). With the advent of high-throughput technologies in the late 1990s, such as DNA microarrays, changes in gene expression have also been found to be ubiquitous after LDIR. Very limited subset of genes has been shown to be consistently up-regulated by LDIR, including CDKN1A. Further research on the biological effects and mechanisms induced by IR in human cells demonstrated that the molecular and cellular processes, including transcriptional alterations, activated by LDIR are often related to protective responses and, sometimes, hormesis. Following LDIR, some distinct responses were observed, these included bystander effects, and adaptive responses. Changes in gene expression, not only at the level of mRNA, but also miRNA, have been found to crucially underlie these effects having implications for radiation protection purposes.

Microfluidic module for blood cell separation for gene expression radiobiological assays

Advances in molecular techniques have improved discovery of biomarkers associated with radiation exposure. Gene expression techniques have been demonstrated as effective tools for biodosimetry, and different assay platforms with different chemistries are now available. One of the main challenges is to integrate the sample preparation processing of these assays into microfluidic platforms to be fully automated for point-of-care medical countermeasures in the case of a radiological event. Most of these assays follow the same workflow processing that comprises first the collection of blood samples followed by cellular and molecular sample preparation. The sample preparation is based on the specific reagents of the assay system and depends also on the different subsets of cells population and the type of biomarkers of interest. In this article, the authors present a module for isolation of white blood cells from peripheral blood as a prerequisite for automation of gene expression assays on a microfluidic cartridge. For each sample condition, the gene expression platform can be adapted to suit the requirements of the selected assay chemistry.

Toward the development of transcriptional biodosimetry for the identification of irradiated individuals and assessment of absorbed radiation dose

The most frequently used and the best established method of biological dosimetry at present is the dicentric chromosome assay, which is poorly suitable for a mass casualties scenario. This gives rise to the need for the development of new, high-throughput assays for rapid identification of the subjects exposed to ionizing radiation. In the present study, we tested the usefulness of gene expression analysis in blood cells for biological dosimetry. Human peripheral blood from three healthy donors was X-irradiated with doses of 0 (control), 0.6, and 2 Gy. The mRNA level of 16 genes (ATF3, BAX, BBC3, BCL2, CDKN1A, DDB2, FDXR, GADD45A, GDF15, MDM2, PLK3, SERPINE1, SESN2, TNFRSF10B, TNFSF4, and VWCE) was assessed by reverse transcription quantitative PCR 6, 12, 24, and 48 h after exposure with ITFG1 and DPM1 used as a reference genes. The panel of radiation-responsive genes was selected comprising GADD45A, CDKN1A, BAX, BBC3, DDB2, TNFSF4, GDF15, and FDXR. Cluster analysis showed that ΔC t values of the selected genes contained sufficient information to allow discrimination between irradiated and non-irradiated blood samples. The samples were clearly grouped according to the absorbed doses of radiation and not to the time interval after irradiation or to the blood donor.

Quantifying murine bone marrow and blood radiation dose response following (18)F-FDG PET with DNA damage biomarkers

The purpose of this study was to quantify the poorly understood radiation doses to murine bone marrow and blood from whole-body fluorine 18 ((18)F)-fluorodeoxyglucose (FDG) positron emission tomography (PET), by using specific biomarkers and comparing with whole body external low dose exposures. Groups of 3-5 mice were randomly assigned to 10 groups, each receiving either a different activity of (18)F-FDG: 0-37MBq or whole body irradiated with corresponding doses of 0-300mGy X-rays. Blood samples were collected at 24h and at 43h for reticulocyte micronucleus assays and QPCR analysis of gene expression in peripheral blood leukocytes. Blood and bone marrow dose estimates were calculated from injected activities of (18)F-FDG and were based on a recommended ICRP model. Doses to the bone marrow corresponding to 33.43mGy and above for internal (18)F-FDG exposure and to 25mGy and above for external X-ray exposure, showed significant increases in radiation-induced MN-RET formation relative to controls (P<0.05). Regression analysis showed that both types of exposure produced a linear response with linear regression analysis giving R(2) of 0.992 and 0.999 for respectively internal and external exposure. No significant difference between the two data sets was found with a P-value of 0.493. In vivo gene expression dose-responses at 24h for Bbc3 and Cdkn1 were similar for (18)F-FDG and X-ray exposures, with significant modifications occurring for doses over 300mGy for Bbc3 and at the lower dose of 150mGy for Cdkn1a. Both leucocyte gene expression and quantification of MN-RET are highly sensitive biomarkers for reliable estimation of the low doses delivered in vivo to, respectively, blood and bone marrow, following (18)F-FDG PET.

A translatable predictor of human radiation exposure

Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major threat to both public health and national security. In the event of a radiological or nuclear disaster, rapid and accurate biodosimetry of thousands of potentially affected individuals will be essential for effective medical management to occur. Currently, health care providers lack an accurate, high-throughput biodosimetric assay which is suitable for the triage of large numbers of radiation injury victims. Here, we describe the development of a biodosimetric assay based on the analysis of irradiated mice, ex vivo-irradiated human peripheral blood (PB) and humans treated with total body irradiation (TBI). Interestingly, a gene expression profile developed via analysis of murine PB radiation response alone was inaccurate in predicting human radiation injury. In contrast, generation of a gene expression profile which incorporated data from ex vivo irradiated human PB and human TBI patients yielded an 18-gene radiation classifier which was highly accurate at predicting human radiation status and discriminating medically relevant radiation dose levels in human samples. Although the patient population was relatively small, the accuracy of this classifier in discriminating radiation dose levels in human TBI patients was not substantially confounded by gender, diagnosis or prior exposure to chemotherapy. We have further incorporated genes from this human radiation signature into a rapid and high-throughput chemical ligation-dependent probe amplification assay (CLPA) which was able to discriminate radiation dose levels in a pilot study of ex vivo irradiated human blood and samples from human TBI patients. Our results illustrate the potential for translation of a human genetic signature for the diagnosis of human radiation exposure and suggest the basis for further testing of CLPA as a candidate biodosimetric assay.

2013 Dade W. Moeller lecture: medical countermeasures against radiological terrorism

Soon after the 9-11 attacks, politicians and scientists began to question our ability to cope with a large-scale radiological terrorism incident. The outline of what was needed was fairly obvious: the ability to prevent such an attack, methods to cope with the medical consequences, the ability to clean up afterward, and the tools to figure out who perpetrated the attack and bring them to justice. The medical response needed three components: the technology to determine rapidly the radiation doses received by a large number of people, methods for alleviating acute hematological radiation injuries, and therapies for mitigation and treatment of chronic radiation injuries. Research done to date has shown that a realistic medical response plan is scientifically possible, but the regulatory and financial barriers to achieving this may currently be insurmountable.

Gene expression analysis in Mayak workers with prolonged occupational radiation exposure

The authors evaluated gene expression in the peripheral blood in relation to occupational exposure in Mayak workers to find out about the existence of a permanent post exposure signature. Workers were exposed to combined incorporated ²³⁹Pu and external gamma rays (n = 82) or to external gamma rays only (n = 18), and 50 unexposed individuals served as controls. Peripheral blood was taken from workers older than 70 y. RNA was isolated, converted into cDNA, and stored at -20°C. A two-stage study design was performed focusing on examinations on the transcriptional (mRNA) and post-transcriptional level (microRNA). In the first stage, 40 samples were identified for screening purposes and selection of candidate genes. For examinations on the transcriptional level, whole genome microarrays and qRT-PCR were employed on the post-transcriptional level (667 microRNAs). Candidate genes were assessed by (1) introducing a twofold difference in gene expression over the reference group and (2) showing a significant p-value using the Kruskal-Wallis test. From 42,545 transcripts of the whole genome microarray, 376 candidate genes (80 up-regulated and 296 down-regulated relative to the reference group) were selected. Expression of almost all of these genes (70-98%) appeared significantly associated with internal ²³⁹Pu and to a lesser extent were associated with external gamma-ray exposure (2-30%). Associations in the same direction were found for 45 microRNAs. Although both exposures led to modulations of different gene sets in different directions, the authors could detect no differences in gene set enrichment analysis.

Method for validating radiobiological samples using a linear accelerator

There is an immediate need for rapid triage of the population in case of a large scale exposure to ionizing radiation. Knowing the dose absorbed by the body will allow clinicians to administer medical treatment for the best chance of recovery for the victim. In addition, today's radiotherapy treatment could benefit from additional information regarding the patient's sensitivity to radiation before starting the treatment. As of today, there is no system in place to respond to this demand. This paper will describe specific procedures to mimic the effects of human exposure to ionizing radiation creating the tools for optimization of administered radiation dosimetry for radiotherapy and/or to estimate the doses of radiation received accidentally during a radiation event that could pose a danger to the public. In order to obtain irradiated biological samples to study ionizing radiation absorbed by the body, we performed ex-vivo irradiation of human blood samples using the linear accelerator (LINAC). The LINAC was implemented and calibrated for irradiating human whole blood samples. To test the calibration, a 2 Gy test run was successfully performed on a tube filled with water with an accuracy of 3% in dose distribution. To validate our technique the blood samples were ex-vivo irradiated and the results were analyzed using a gene expression assay to follow the effect of the ionizing irradiation by characterizing dose responsive biomarkers from radiobiological assays. The response of 5 genes was monitored resulting in expression increase with the dose of radiation received. The blood samples treated with the LINAC can provide effective irradiated blood samples suitable for molecular profiling to validate radiobiological measurements via the gene-expression based biodosimetry tools.

Iodine-131 dose-dependent gene expression: alterations in both normal and tumour thyroid tissues of post-Chernobyl thyroid cancers

BACKGROUND

A strong, consistent association between childhood irradiation and subsequent thyroid cancer provides an excellent model for studying radiation carcinogenesis.

METHODS

We evaluated gene expression in 63 paired RNA specimens from frozen normal and tumour thyroid tissues with individual iodine-131 (I-131) doses (0.008-8.6 Gy, no unirradiated controls) received from Chernobyl fallout during childhood (Ukrainian-American cohort). Approximately half of these randomly selected samples (32 tumour/normal tissue RNA specimens) were hybridised on 64 whole-genome microarrays (Agilent, 4 × 44 K). Associations between I-131 dose and gene expression were assessed separately in normal and tumour tissues using Kruskal-Wallis and linear trend tests. Of 155 genes significantly associated with I-131 after Bonferroni correction and with ≥2-fold increase per dose category, we selected 95 genes. On the remaining 31 RNA samples these genes were used for validation purposes using qRT-PCR.

RESULTS

Expression of eight genes (ABCC3, C1orf9, C6orf62, FGFR1OP2, HEY2, NDOR1, STAT3, and UCP3) in normal tissue and six genes (ANKRD46, CD47, HNRNPH1, NDOR1, SCEL, and SERPINA1) in tumour tissue was significantly associated with I-131. PANTHER/DAVID pathway analyses demonstrated significant over-representation of genes coding for nucleic acid binding in normal and tumour tissues, and for p53, EGF, and FGF signalling pathways in tumour tissue.

CONCLUSION

The multistep process of radiation carcinogenesis begins in histologically normal thyroid tissue and may involve dose-dependent gene expression changes.

Comparison of established and emerging biodosimetry assays

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

Gene set enrichment analysis highlights different gene expression profiles in whole blood samples X-irradiated with low and high doses

PURPOSE

Health risks from exposure to low doses of ionizing radiation (IR) are becoming a concern due to the rapidly growing medical applications of X-rays. Using microarray techniques, this study aims for a better understanding of whole blood response to low and high doses of IR.

MATERIALS AND METHODS

Aliquots of peripheral blood samples were irradiated with 0, 0.05, and 1 Gy X-rays. RNA was isolated and prepared for microarray gene expression experiments. Bioinformatic approaches, i.e., univariate statistics and Gene Set Enrichment Analysis (GSEA) were used for analyzing the data generated. Seven differentially expressed genes were selected for further confirmation using quantitative real-time PCR (RT-PCR).

RESULTS

Functional analysis of genes differentially expressed at 0.05 Gy showed the enrichment of chemokine and cytokine signaling. However, responsive genes to 1 Gy were mainly involved in tumor suppressor protein 53 (p53) pathways. In a second approach, GSEA showed a higher statistical ranking of inflammatory and immune-related gene sets that are involved in both responding and/or secretion of growth factors, chemokines, and cytokines. This indicates the activation of the immune response. Whereas, gene sets enriched at 1 Gy were 'classical' radiation pathways like p53 signaling, apoptosis, DNA damage and repair. Comparative RT-PCR studies showed the significant induction of chemokine-related genes (PF4, GNG11 and CCR4) at 0.05 Gy and DNA damage and repair genes at 1 Gy (DDB2, AEN and CDKN1A).

CONCLUSIONS

This study moves a step forward in understanding the different cellular responses to low and high doses of X-rays. In addition to that, and in a broader context, it addresses the need for more attention to the risk assessment of health effects resulting from the exposure to low doses of IR.

DNA repair and cell cycle biomarkers of radiation exposure and inflammation stress in human blood

DNA damage and repair are hallmarks of cellular responses to ionizing radiation. We hypothesized that monitoring the expression of DNA repair-associated genes would enhance the detection of individuals exposed to radiation versus other forms of physiological stress. We employed the human blood ex vivo radiation model to investigate the expression responses of DNA repair genes in repeated blood samples from healthy, non-smoking men and women exposed to 2 Gy of X-rays in the context of inflammation stress mimicked by the bacterial endotoxin lipopolysaccharide (LPS). Radiation exposure significantly modulated the transcript expression of 12 genes of 40 tested (2.2E-06<p<0.03), of which 8 showed no overlap between unirradiated and irradiated samples (CDKN1A, FDXR, BBC3, PCNA, GADD45a, XPC, POLH and DDB2). This panel demonstrated excellent dose response discrimination (0.5 to 8 Gy) in an independent human blood ex vivo dataset, and 100% accuracy for discriminating patients who received total body radiation. Three genes of this panel (CDKN1A, FDXR and BBC3) were also highly sensitive to LPS treatment in the absence of radiation exposure, and LPS co-treatment significantly affected their radiation responses. At the protein level, BAX and pCHK2-thr68 were elevated after radiation exposure, but the pCHK2-thr68 response was significantly decreased in the presence of LPS. Our combined panel yields an estimated 4-group accuracy of ∼90% to discriminate between radiation alone, inflammation alone, or combined exposures. Our findings suggest that DNA repair gene expression may be helpful to identify biodosimeters of exposure to radiation, especially within high-complexity exposure scenarios.