Laboratory intercomparison of gene expression assays

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.

Intercomparison in Cytogenetic Dosimetry among 22 Laboratories in China

As part of a regional International Atomic Energy Agency-coordinated research project with the support from the National Health and Family Planning Commission of China, 22 laboratories participated in the intercomparison in cytogenetic dosimetry in China. Slides for chromosomal aberrations were prepared by the Department of Radiation Epidemiology, National Institute for Radiological Protection, which organized the exercise. Slides were sent to the other participating laboratories through Express Mail Service. For estimates of dose, each laboratory scored the frequency of dicentrics plus centric rings chromosomes. The whole blood samples were irradiated with ⁶⁰Co γ-rays (1.3 Gy, 2.4 Gy and 1.5 Gy, 2.6 Gy). Each laboratory got one group of the slides. Ten of the 44 estimates of dose fell within ±5% of the true physical dose, 12 fell within ±5-10%, 9 fell within ±10-15%, 12 fell within ±15-20%, while only one sample fell ± >20%. The evaluation of the respective dose was achieved by 21 laboratories.

ROC Analysis for Evaluation of Radiation Biodosimetry Technologies

Receiver operating characteristic (ROC) analysis is a fundamental tool used for the evaluation and comparison of diagnostic systems that provides estimates of the combinations of sensitivity and specificity that can be achieved with a given technique. Along with critical considerations of practical limitations, such as throughput and time to availability of results, ROC analyses can be applied to provide meaningful assessments and comparisons of available biodosimetry methods. Accordingly, guidance from the Food and Drug Administration to evaluate biodosimetry devices recommends using ROC analysis. However, the existing literature for the numerous biodosimetry methods that have been developed to address the needs for triage either do not contain ROC analyses or present ROC analyses where the dose distributions of the study samples are not representative of the populations to be screened. The use of non-representative sample populations can result in a significant spectrum bias, where estimated performance metrics do not accurately characterize the true performance under real-world conditions. Particularly, in scenarios where a large group of people is screened because they were potentially exposed in a large-scale radiation event, directly measured population data do not exist. However, a number of complex simulations have been performed and reported in the literature that provide estimates of the required dose distributions. Based on these simulations and reported data about the output and uncertainties of biodosimetry assays, we illustrate how ROC curves can be generated that incorporate a realistic representative sample. A technique to generate ROC curves for biodosimetry data is presented along with representative ROC curves, summary statistics and discussion based on published data for triage-ready electron paramagnetic resonance in vivo tooth dosimetry, the dicentric chromosome assay and quantitative polymerase chain reaction assay. We argue that this methodology should be adopted generally to evaluate the performance of radiation biodosimetry screening assays so that they can be compared in the context of their intended use.

An update of the WHO Biodosenet: Developments since its Inception

In 2007 the World Health Organization established an international network of biodosimetry laboratories, the BioDoseNet. The goal of this network was to support international cooperation and capacity building in the area of biodosimetry around the world, including harmonisation of protocols and techniques to enable them to provide mutual assistance during a mass casualty event. In order to assess the progress and success of this network, the results of the second survey conducted in 2015 that assessed the capabilities and capacities of the members of the network, were compared to the similar first survey conducted in 2009. The results of the survey offer a unique cross-section of the global status of biodosimetry capacity and demonstrate how the BioDoseNet has brought together laboratories from around the world and strengthened the international capacity for biodosimetry.

Human serum miR-34a as an indicator of exposure to ionizing radiation

Radiation exposure in industrial accidents or nuclear device attacks is a major public health concern. There is an urgent need for markers that rapidly identify people exposed to ionizing radiation (IR). Finding a blood-based marker is advantageous because of the ease of sample collection. This study was designed to test the hypothesis that serum miR-34a could serve as an indicator of exposure to IR. Therefore, 44 women with breast cancer, where radiotherapy was part of their therapeutic protocol, were investigated in this study. After demonstrating the appropriateness of our microRNA (miRNA) extraction efficiency and miRNA assay in human serum, we analyzed the miR-34a level in paired serum samples before and after radiotherapy. Fifty Gy X-ray irradiation in daily dose fractions of 2 Gy, 5 days per week, was used in this study. We demonstrated that IR significantly increased serum level of miR-34a. By measuring miR-34a in serum, we could distinguish irradiated patients with sensitivity of 65 % and specificity of 75 %. According to this study, serum miR-34a has the potential to be used as an indicator of radiation exposure.

State-of-the-Art Advances in Radiation Biodosimetry for Mass Casualty Events Involving Radiation Exposure

With the possibility of large-scale terrorist attacks around the world, the need for modeling and development of new medical countermeasures for potential future chemical, biological, radiological and nuclear (CBRN) has been well established. Project Bioshield, initiated in 2004, provided a framework to develop and expedite research in the field of CBRN exposures. To respond to large-scale population exposures from a nuclear event or radiation dispersal device (RDD), new methods for determining received dose using biological modeling became necessary. The field of biodosimetry has advanced significantly beyond this original initiative, with expansion into the fields of genomics, proteomics, metabolomics and transcriptomics. Studies are ongoing to evaluate the use of lymphocyte kinetics for dose assessment, as well as the development of field-deployable EPR technology. In addition, expansion of traditional cytogenetic assessment methods through the use of automated platforms and the development of laboratory surge capacity networks have helped to advance our biodefense preparedness. In this review of the latest advances in the field of biodosimetry we evaluate our progress and identify areas that still need to be addressed to achieve true field-deployment readiness.

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.

Radiation Dose-Rate Effects on Gene Expression in a Mouse Biodosimetry Model

In the event of a nuclear accident or radiological terrorist attack, there will be a pressing need for biodosimetry to triage a large, potentially exposed population and to assign individuals to appropriate treatment. Exposures from fallout are likely, resulting in protracted dose delivery that would, in turn, impact the extent of injury. Biodosimetry approaches that can distinguish such low-dose-rate (LDR) exposures from acute exposures have not yet been developed. In this study, we used the C57BL/6 mouse model in an initial investigation of the impact of low-dose-rate delivery on the transcriptomic response in blood. While a large number of the same genes responded to LDR and acute radiation exposures, for many genes the magnitude of response was lower after LDR exposures. Some genes, however, were differentially expressed (P < 0.001, false discovery rate <5%) in mice exposed to LDR compared with mice exposed to acute radiation. We identified a set of 164 genes that correctly classified 97% of the samples in this experiment as exposed to acute or LDR radiation using a support vector machine algorithm. Gene expression is a promising approach to radiation biodosimetry, enhanced greatly by this first demonstration of its potential for distinguishing between acute and LDR exposures. Further development of this aspect of radiation biodosimetry, either as part of a complete gene expression biodosimetry test or as an adjunct to other methods, could provide vital triage information in a mass radiological casualty event.

Radiation dose-rate effects on gene expression for human biodosimetry

Background

The effects of dose-rate and its implications on radiation biodosimetry methods are not well studied in the context of large-scale radiological scenarios. There are significant health risks to individuals exposed to an acute dose, but a realistic scenario would include exposure to both high and low dose-rates, from both external and internal radioactivity. It is important therefore, to understand the biological response to prolonged exposure; and further, discover biomarkers that can be used to estimate damage from low-dose rate exposures and propose appropriate clinical treatment.

Methods

We irradiated human whole blood ex vivo to three doses, 0.56 Gy, 2.23 Gy and 4.45 Gy, using two dose rates: acute, 1.03 Gy/min and a low dose-rate, 3.1 mGy/min. After 24 h, we isolated RNA from blood cells and these were hybridized to Agilent Whole Human genome microarrays. We validated the microarray results using qRT-PCR.

Results

Microarray results showed that there were 454 significantly differentially expressed genes after prolonged exposure to all doses. After acute exposure, 598 genes were differentially expressed in response to all doses. Gene ontology terms enriched in both sets of genes were related to immune processes and B-cell mediated immunity. Genes responding to acute exposure were also enriched in functions related to natural killer cell activation and cell-to-cell signaling. As expected, the p53 pathway was found to be significantly enriched at all doses and by both dose-rates of radiation. A support vectors machine classifier was able to distinguish between dose-rates with 100 % accuracy using leave-one-out cross-validation.

Conclusions

In this study we found that low dose-rate exposure can result in distinctive gene expression patterns compared with acute exposures. We were able to successfully distinguish low dose-rate exposed samples from acute dose exposed samples at 24 h, using a gene expression-based classifier. These genes are candidates for further testing as markers to classify exposure based on dose-rate.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-015-0097-x) contains supplementary material, which is available to authorized users.

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.

Advances in a framework to compare bio-dosimetry methods for triage in large-scale radiation events

Planning and preparation for a large-scale nuclear event would be advanced by assessing the applicability of potentially available bio-dosimetry methods. Using an updated comparative framework the performance of six bio-dosimetry methods was compared for five different population sizes (100-1,000,000) and two rates for initiating processing of the marker (15 or 15,000 people per hour) with four additional time windows. These updated factors are extrinsic to the bio-dosimetry methods themselves but have direct effects on each method's ability to begin processing individuals and the size of the population that can be accommodated. The results indicate that increased population size, along with severely compromised infrastructure, increases the time needed to triage, which decreases the usefulness of many time intensive dosimetry methods. This framework and model for evaluating bio-dosimetry provides important information for policy-makers and response planners to facilitate evaluation of each method and should advance coordination of these methods into effective triage plans.