Diagnosis of partial body radiation exposure in mice using peripheral blood gene expression profiles

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

PURPOSE

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

MATERIAL AND METHODS

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

RESULTS

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

CONCLUSION

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

Metabolomics and transcriptomics based multi-omics integration reveals radiation-induced altered pathway networking and underlying mechanism

Recent advancement in integrated multi-omics has significantly contributed to many areas of the biomedical field. Radiation research has also grasped uprising omics technologies in biomarker identification to aid in triage management. Herein, we have used a combinatorial multi-omics approach based on transcriptomics together with metabolomics and lipidomics of blood from murine exposed to 1 Gy (LD) and 7.5 Gy (HD) of total-body irradiation (TBI) for a comprehensive understanding of biological processes through integrated pathways and networking. Both omics displayed demarcation of HD group from controls using multivariate analysis. Dysregulated amino acids, various PC, PE and carnitine were observed along with many dysregulated genes (Nos2, Hmgcs2, Oxct2a, etc.). Joint-Pathway Analysis and STITCH interaction showed radiation exposure resulted in changes in amino acid, carbohydrate, lipid, nucleotide, and fatty acid metabolism. Elicited immune response was also observed by Gene Ontology. BioPAN has predicted Elovl5, Elovl6 and Fads2 for fatty acid pathways, only in HD group. Collectively, the combined omics approach facilitated a better understanding of processes uncovering metabolic pathways. Presumably, this is the first in radiation metabolomics that utilized an integrated omics approach following TBI in mice. Our work showed that omics integration could be a valuable tool for better comprehending the mechanism as well as molecular interactions.

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

PURPOSE

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

MATERIALS & METHODS

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

RESULTS

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

CONCLUSION

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

The delayed effects of acute radiation exposure (DEARE): characteristics, mechanisms, animal models, and promising medical countermeasures

PURPOSE

Terrorist use of nuclear weapons and radiation accidents put the human population at risk for exposure to life-threatening levels of radiation. Victims of lethal radiation exposure face potentially lethal acute injury, while survivors of the acute phase are plagued with chronic debilitating multi-organ injuries for years after exposure. Developing effective medical countermeasures (MCM) for the treatment of radiation exposure is an urgent need that relies heavily on studies conducted in reliable and well-characterized animal models according to the FDA Animal Rule. Although relevant animal models have been developed in several species and four MCM for treatment of the acute radiation syndrome are now FDA-approved, animal models for the delayed effects of acute radiation exposure (DEARE) have only recently been developed, and there are no licensed MCM for DEARE. Herein, we provide a review of the DEARE including key characteristics of the DEARE gleaned from human data as well as animal, mechanisms common to multi-organ DEARE, small and large animal models used to study the DEARE, and promising new or repurposed MCM under development for alleviation of the DEARE.

CONCLUSIONS

Intensification of research efforts and support focused on better understanding of mechanisms and natural history of DEARE are urgently needed. Such knowledge provides the necessary first steps toward the design and development of MCM that effectively alleviate the life-debilitating consequences of the DEARE for the benefit of humankind worldwide.

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

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

Prediction of Total-Body and Partial-Body Exposures to Radiation Using Plasma Proteomic Expression Profiles

There is a need to identify new biomarkers of radiation exposure for not only systemic total-body irradiation (TBI) but also to characterize partial-body irradiation and organ specific radiation injury. In the current study, we sought to develop novel biodosimetry models of radiation exposure using TBI and organ specific partial-body irradiation to only the brain, lung or gut using a multivariate proteomics approach. Subset panels of significantly altered proteins were selected to build predictive models of radiation exposure in a variety of sample cohort configurations relevant to practical field application of biodosimetry diagnostics during future radiological or nuclear event scenarios. Female C57BL/6 mice, 8-15 weeks old, received a single total-body or partial-body dose of 2 or 8 Gy TBI or 2 or 8 Gy to only the lung or gut, or 2, 8 or 16 Gy to only the brain using a Pantak X-ray source. Plasma was collected by cardiac puncture at days 1, 3 and 7 postirradiation for total-body exposures and only the lung and brain exposures, and at days 3, 7 and 14 postirradiation for gut exposures. Plasma was then screened using the aptamer-based SOMAscan proteomic assay technology, for changes in expression of 1,310 protein analytes. A subset panel of protein biomarkers which demonstrated significant changes (P < 0.01) in expression after irradiation were used to build predictive models of radiation exposure using different sample cohorts. Model 1 compared controls vs. all pooled irradiated samples, which included TBI and all organ specific partial irradiation. Model 2 compared controls vs. TBI vs. partial irradiation (with all organ specific partial exposure pooled within the partial-irradiated group), and model 3 compared controls vs. each individual organ specific partial-body exposure separately (brain, gut and lung). Detectable values were obtained for all 1,310 proteins included in the SOMAscan assay for all samples. Each model algorithm built using a unique sample cohort was validated with a training set of samples and tested with a separate new sample series. Overall predictive accuracies of 89%, 78% and 55% resulted for models 1-3, respectively, representing novel predictive panels of radiation responsive proteomic biomarkers. Though relatively high overall predictive accuracies were achieved for models 1 and 2, all three models showed limited accuracy at differentiating between the controls and partial-irradiated body samples. In our study we were able to identify novel panels of radiation responsive proteins useful for predicting radiation exposure and to create predictive models of partial-body exposure including organ specific radiation exposures. This proof-of-concept study also illustrates the inherent physiological limitations of distinguishing between small-body exposures and the unirradiated using proteomic biomarkers of radiation exposure. As use of biodosimetry diagnostics in future mass casualty settings will be complicated by the heterogeneity of partial-body exposure received in the field, further work remains in adapting these diagnostic tools for practical use.

The Potential of Omics in Biological Dosimetry

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

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.

Chromosome aberration dynamics in breast cancer patients treated with radiotherapy: Implications for radiation biodosimetry

Although radiological accidents often result in partial-body radiation exposure, most biodosimetry studies focus on estimating whole-body exposure doses. We have evaluated time-dependent changes in chromosomal aberrations before, during, and after localized fractionated radiotherapy. Twelve patients with carcinoma in situ of the breast who underwent identical adjuvant radiation therapy (50 Gy in 25 fractions) were included in the study. Lymphocytes were collected from patients before, during, and after radiotherapy, to measure chromosome aberrations, such as dicentric chromosomes and translocations. Chromosome aberrations were then used to calculate whole- and partial-body biological absorbed doses of radiation. Dicentric chromosome frequencies in all study participants increased during radiotherapy (p < 0.05 in Kruskal-Wallis test). Increases of translocation frequencies during radiotherapy were observed in seven of the twelve patients. The increased levels of dicentric chromosomes and translocations persisted throughout our 1-year follow-up, and evidence of partial-body exposure (such as Papworth's U-value > 1.96) was observed more than 1 year after radiotherapy. We found that cytogenetic biomarkers reflected partial-body fractionated radiation exposure more than 1 year post-exposure. Our findings suggest that chromosome aberrations can be used to estimate biological absorbed radiation doses and can inform medical intervention for individuals suspected of fractionated or partial-body radiation exposure.

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.

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.

Gene Expression Profiles from Heart, Lung and Liver Samples of Total-Body-Irradiated Minipigs: Implications for Predicting Radiation-Induced Tissue Toxicity

In the event of a major accidental or intentional radiation exposure incident, the affected population could suffer from total- or partial-body exposures to ionizing radiation with acute exposure to organs that would produce life-threatening injury. Therefore, it is necessary to identify markers capable of predicting organ-specific damage so that appropriate directed or encompassing therapies can be applied. In the current work, gene expression changes in response to total-body irradiation (TBI) were identified in heart, lungs and liver tissue of Göttingen minipigs. Animals received 1.7, 1.9, 2.1 or 2.3 Gy TBI and were followed for 45 days. Organ samples were collected at the end of day 45 or sooner if the animal displayed morbidity necessitating euthanasia. Our findings indicate that different organs respond to TBI in a very specific and distinct manner. We also found that the liver was the most affected organ in terms of gene expression changes, and that lipid metabolic pathways were the most deregulated in the liver samples of non-survivors (survival time <45 days). We identified organ-specific gene expression signatures that accurately differentiated non-survivors from survivors and control animals, irrespective of dose and time postirradiation. At what point did these radiation-induced injury markers manifest and how this information could be used for applying intervention therapies are under investigation.

Comparative metabolic profiles of total and partial body radiation exposure in mice using an untargeted metabolomics approach

INTRODUCTION

A large scale population exposure to ionizing radiation during intentional or unintentional nuclear accidents undoubtedly generates a complex scenario with partial-body as well as total-body irradiated victims. A high throughput technique based rapid assessment method is an urgent necessity for stratification of exposed subjects independent of whether exposure is uniform total-body or non-homogenous partial-body.

OBJECTIVE

Here, we used Nuclear Magnetic Resonance (NMR) based metabolomics approach to compare and identify candidate metabolites differentially expressed in total and partially irradiated mice model.

METHODS

C57BL/6 male mice (8-10 weeks) were irradiated total-body or locally to thoracic, hind limb or abdominal regions with 10 Gy of gamma radiation. Urine samples collected at 24 h post irradiation were examined using high resolution NMR spectroscopy and the datasets were analysed using multivariate analysis.

RESULTS

Multivariate and metabolic pathway analysis in urine samples collected at 24 h post-radiation exhibited segregation of all irradiated groups from controls. Metabolites associated with energy metabolism, gut flora metabolism and taurine were common to partial and total-body irradiation, thus making them potential candidates for radiation exposure. Nevertheless, a distinct metabolic pattern was observed in partial-body exposed groups with maximum changes observed in the hind limb region indicating differential tissue associated radiation sensitivity. The organ-specific changes may provide an early warning regarding the physiological system at risk after radiation injury.

CONCLUSION

The study affirms potentiality of metabolite markers and comparative analysis could be an important piece of information for an integrated solution to a complex research question in terms of radiation biomarkers.

Dose and Dose-Rate Effects in a Mouse Model of Internal Exposure to 137Cs. Part 1: Global Transcriptomic Responses in Blood

Internal contamination by radionuclides may constitute a major source of exposure and biological damage after radiation accidents and potentially in a dirty bomb or improvised nuclear device scenario. We injected male C57BL/6 mice with radiolabeled cesium chloride solution (137CsCl) to evaluate the biological effects of varying cumulative doses and dose rates in a two-week study. Injection activities of 137CsCl were 5.71, 6.78, 7.67 and 9.29 MBq, calculated to achieve a target dose of 4 Gy at days 14, 7, 5 and 3, respectively. We collected whole blood samples at days 2, 3, 5, 7 and 14 so that we can publish the issue in Decemberfrom all injection groups and measured gene expression using Agilent Mouse Whole Genome microarrays. We identified both dose-rate-independent and dose-rate-dependent gene expression responses in the time series. Gene Ontology analysis indicated a rapid and persistent immune response to the chronic low-dose-rate irradiation, consistent with depletion of radiosensitive B cells. Pathways impacting platelet aggregation and TP53 signaling appeared activated, but not consistently at all times in the study. Clustering of genes by pattern and identification of dose-rate-independent and -dependent genes provided insight into possible drivers of the dynamic transcriptome response in vivo, and also indicated that TP53 signaling may be upstream of very different transcript response patterns. This characterization of the biological response of blood cells to internal radiation at varying doses and dose rates is an important step in understanding the effects of internal contamination after a nuclear event.

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.

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.

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.

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.

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.

MicroRNA Expression for Early Prediction of Late Occurring Hematologic Acute Radiation Syndrome in Baboons

For effective medical management of radiation-exposed persons after a radiological/nuclear event, blood-based screening measures in the first few days that could predict hematologic acute radiation syndrome (HARS) are needed. For HARS severity prediction, we used microRNA (miRNA) expression changes measured on days one and two after irradiation in a baboon model. Eighteen baboons underwent different patterns of partial or total body irradiation, corresponding to an equivalent dose of 2.5 or 5 Gy. According to changes in blood cell counts (BCC) the surviving baboons (n = 17) exhibited mild (H1-2, n = 4) or more severe (H2-3, n = 13) HARS. In a two Stage study design we screened 667 miRNAs using a quantitative real-time polymerase chain reaction (qRT-PCR) platform. In Stage II we validated candidates where miRNAs had to show a similar regulation (up- or down-regulated) and a significant 2-fold miRNA expression difference over H0. Seventy-two candidate miRNAs (42 for H1-2 and 30 for H2-3) were forwarded for validation. Forty-two of the H1-2 miRNA candidates from the screening phase entered the validation step and 20 of them showed a statistically significant 2–4 fold up-regulation relative to the unexposed reference (H0). Fifteen of the 30 H2-3 miRNAs were validated in Stage II. All miRNAs appeared 2–3 fold down-regulated over H0 and allowed an almost complete separation of HARS categories; the strongest candidate, miR-342-3p, showed a sustained and 10-fold down-regulation on both days 1 and 2. In summary, our data support the medical decision making of the HARS even within the first two days after exposure where diagnostic tools for early medical decision are required but so far missing. The miRNA species identified and in particular miR-342-3p add to the previously identified mRNAs and complete the portfolio of identified mRNA and miRNA transcripts for HARS prediction and medical management.

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.

A Molecular Profile of the Endothelial Cell Response to Ionizing Radiation

Ionizing radiation exposure can cause acute radiation sickness (ARS) by damaging the hematopoietic compartment. Radiation damages quiescent hematopoietic stem cells (HSCs) and proliferating hematopoietic cells, resulting in neutropenia, thrombocytopenia and increased risk for long-term hematopoietic dysfunction and myelodysplasia. While some aspects of the hematopoietic response to radiation injury are intrinsic to hematopoietic cells, the recovery of the HSC pool and overall hematopoiesis is also dependent on signals from bone marrow endothelial cells (BM ECs) within the HSC vascular niche. The precise mechanisms through which BM ECs regulate HSC regeneration remain unclear. Characterization of the altered EC gene expression that occurs in response to radiation could provide a roadmap to the discovery of EC-derived mechanisms that regulate hematopoietic regeneration. Here, we show that 5 Gy total-body irradiation substantially alters the expression of numerous genes in BM ECs within 24 h and this molecular response largely resolves by day 14 postirradiation. Several unique and nonannotated genes, which encode secreted proteins were upregulated and downregulated in ECs in response to radiation. These results highlight the complexity of the molecular response of BM ECs to ionizing radiation and identify several candidate mechanisms that should be prioritized for functional analysis in models of hematopoietic injury and regeneration.

First Generation Gene Expression Signature for Early Prediction of Late Occurring Hematological Acute Radiation Syndrome in Baboons

We implemented a two-stage study to predict late occurring hematologic acute radiation syndrome (HARS) in a baboon model based on gene expression changes measured in peripheral blood within the first two days after irradiation. Eighteen baboons were irradiated to simulate different patterns of partial-body and total-body exposure, which corresponded to an equivalent dose of 2.5 or 5 Gy. According to changes in blood cell counts the surviving baboons (n = 17) exhibited mild (H1-2, n = 4) or more severe (H2-3, n = 13) HARS. Blood samples taken before irradiation served as unexposed control (H0, n = 17). For stage I of this study, a whole genome screen (mRNA microarrays) was performed using a portion of the samples (H0, n = 5; H1-2, n = 4; H2-3, n = 5). For stage II, using the remaining samples and the more sensitive methodology, qRT-PCR, validation was performed on candidate genes that were differentially up- or down-regulated during the first two days after irradiation. Differential gene expression was defined as significant (P < 0.05) and greater than or equal to a twofold difference above a H0 classification. From approximately 20,000 genes, on average 46% appeared to be expressed. On day 1 postirradiation for H2-3, approximately 2-3 times more genes appeared up-regulated (1,418 vs. 550) or down-regulated (1,603 vs. 735) compared to H1-2. This pattern became more pronounced at day 2 while the number of differentially expressed genes decreased. The specific genes showed an enrichment of biological processes coding for immune system processes, natural killer cell activation and immune response (P = 1 × E-06 up to 9 × E-14). Based on the P values, magnitude and sustained differential gene expression over time, we selected 89 candidate genes for validation using qRT-PCR. Ultimately, 22 genes were confirmed for identification of H1-3 classifications and seven genes for identification of H2-3 classifications using qRT-PCR. For H1-3 classifications, most genes were constantly three to fivefold down-regulated relative to H0 over both days, but some genes appeared 10.3-fold (VSIG4) or even 30.7-fold up-regulated (CD177) over H0. For H2-3, some genes appeared four to sevenfold up-regulated relative to H0 (RNASE3, DAGLA, ARG2), but other genes showed a strong 14- to 33-fold down-regulation relative to H0 (WNT3, POU2AF1, CCR7). All of these genes allowed an almost completely identifiable separation among each of the HARS categories. In summary, clinically relevant HARS can be independently predicted with all 29 irradiated genes examined in the peripheral blood of baboons within the first two days postirradiation. While further studies are needed to confirm these findings, this model shows potential relevance in the prediction of clinical outcomes in exposed humans and as an aid in the prioritizing of medical treatment.

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.

Gene expression response of mice after a single dose of 137CS as an internal emitter

Cesium-137 is a radionuclide of concern in fallout from reactor accidents or nuclear detonations. When ingested or inhaled, it can expose the entire body for an extended period of time, potentially contributing to serious health consequences ranging from acute radiation syndrome to increased cancer risks. To identify changes in gene expression that may be informative for detecting such exposure, and to begin examining the molecular responses involved, we have profiled global gene expression in blood of male C57BL/6 mice injected with 137CsCl. We extracted RNA from the blood of control or 137CsCl-injected mice at 2, 3, 5, 20 or 30 days after exposure. Gene expression was measured using Agilent Whole Mouse Genome Microarrays, and the data was analyzed using BRB-ArrayTools. Between 466-6,213 genes were differentially expressed, depending on the time after 137Cs administration. At early times (2-3 days), the majority of responsive genes were expressed above control levels, while at later times (20-30 days) most responding genes were expressed below control levels. Numerous genes were overexpressed by day 2 or 3, and then underexpressed by day 20 or 30, including many Tp53-regulated genes. The same pattern was seen among significantly enriched gene ontology categories, including those related to nucleotide binding, protein localization and modification, actin and the cytoskeleton, and in the integrin signaling canonical pathway. We compared the expression of several genes three days after 137CsCl injection and three days after an acute external gamma-ray exposure, and found that the internal exposure appeared to produce a more sustained response. Many common radiation-responsive genes are altered by internally administered 137Cs, but the gene expression pattern resulting from continued irradiation at a decreasing dose rate is extremely complex, and appears to involve a late reversal of much of the initial response.

Embryonic ionizing radiation exposure results in expression alterations of genes associated with cardiovascular and neurological development, function, and disease and modified cardiovascular function in zebrafish

The relationship between ionizing radiation (IR) and carcinogenesis is long established, but recently the association between IR and other diseases is starting to be recognized. Currently, there is limited information on the genetic mechanisms governing the role of IR in non-cancer related adverse health effects and in regards to an early developmental exposure. In this study, zebrafish embryos were exposed to a range of IR doses (0, 1, 2, 5, 10 Gy) at 26 h post fertilization (hpf). No significant increase in mortality or hatching rate was observed, but a significant decrease in total larval length, head length, and eye diameter was observed in the 10 Gy dose. Transcriptomic analysis was conducted at 120 hpf to compare gene expression profiles between the control and highest IR dose at which no significant differences were observed in morphological measurements (5 Gy). 253 genes with well-established function or orthology to human genes were significantly altered. Gene ontology and molecular network analysis revealed enrichment of genes associated with cardiovascular and neurological development, function, and disease. Expression of a subset of genetic targets with an emphasis on those associated with the cardiovascular system was assessed using Quantitative PCR (qPCR) to confirm altered expression at 5 Gy and then to investigate alterations at lower doses (1 and 2 Gy). Strong correlation between microarray and qPCR expression values was observed, but zebrafish exposed to 1 or 2 Gy resulted in a significant expression alteration in only one of these genes (LIN7B). Moreover, heart rate was analyzed through 120 hpf following IR dosing at 26 hpf. A significant decrease in heart rate was observed at 10 Gy, while a significant increase in heart rate was observed at 1, 2, and 5 Gy. Overall these findings indicate IR exposure at doses below those that induce gross morphological changes alters heart rate and expression of genes associated with cardiovascular and neurological functions.

Application of multivariate modeling for radiation injury assessment: a proof of concept

Multivariate radiation injury estimation algorithms were formulated for estimating severe hematopoietic acute radiation syndrome (H-ARS) injury (i.e., response category three or RC3) in a rhesus monkey total-body irradiation (TBI) model. Classical CBC and serum chemistry blood parameters were examined prior to irradiation (d 0) and on d 7, 10, 14, 21, and 25 after irradiation involving 24 nonhuman primates (NHP) (Macaca mulatta) given 6.5-Gy ⁶⁰Co Υ-rays (0.4 Gy min⁻¹) TBI. A correlation matrix was formulated with the RC3 severity level designated as the “dependent variable” and independent variables down selected based on their radioresponsiveness and relatively low multicollinearity using stepwise-linear regression analyses. Final candidate independent variables included CBC counts (absolute number of neutrophils, lymphocytes, and platelets) in formulating the “CBC” RC3 estimation algorithm. Additionally, the formulation of a diagnostic CBC and serum chemistry “CBC-SCHEM” RC3 algorithm expanded upon the CBC algorithm model with the addition of hematocrit and the serum enzyme levels of aspartate aminotransferase, creatine kinase, and lactate dehydrogenase. Both algorithms estimated RC3 with over 90% predictive power. Only the CBC-SCHEM RC3 algorithm, however, met the critical three assumptions of linear least squares demonstrating slightly greater precision for radiation injury estimation, but with significantly decreased prediction error indicating increased statistical robustness.

Assessment of ER Stress and autophagy induced by ionizing radiation in both radiotherapy patients and ex vivo irradiated samples

Acute radiation leads to several toxic clinical states and triggers some molecular pathways. To shed light on molecular mechanisms triggered by ionizing radiation (IR), we examined the expression profiles of endoplasmic reticulum (ER) stress and autophagy-related genes in individuals who were exposed to IR. Blood samples were collected from 50 cancer patients before radiotherapy and on the 5th, 15th, and 25th days of the treatment. Peripheral blood samples from 10 healthy volunteers were also obtained for ex vivo irradiation, divided into five and irradiated at a rate of 373 kGy/h to 0, 0.1, 0.5, 1, and 3Gy γ-rays using a constant gamma source. GRP78, ATG5, LC3, ATF4, XBP1, and GADD153 genes were analyzed by quantitative real-time polymerase chain reaction (QRT-PCR) using beta 2 microglobulin (B2M) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as references. In both groups, expressions of the selected genes have increased. It can be concluded that IR induces ER stress and related authophagy pathway in the peripheral lymphocyte cells proportionally by dose.

Gene expression-based dosimetry by dose and time in mice following acute radiation exposure

Rapid and reliable methods for performing biological dosimetry are of paramount importance in the event of a large-scale nuclear event. Traditional dosimetry approaches lack the requisite rapid assessment capability, ease of use, portability and low cost, which are factors needed for triaging a large number of victims. Here we describe the results of experiments in which mice were acutely exposed to ⁶⁰Co gamma rays at doses of 0 (control) to 10 Gy. Blood was obtained from irradiated mice 0.5, 1, 2, 3, 5, and 7 days after exposure. mRNA expression levels of 106 selected genes were obtained by reverse-transcription real time PCR. Stepwise regression of dose received against individual gene transcript expression levels provided optimal dosimetry at each time point. The results indicate that only 4–7 different gene transcripts are needed to explain ≥ 0.69 of the variance (R²), and that receiver-operator characteristics, a measure of sensitivity and specificity, of ≥ 0.93 for these statistical models were achieved at each time point. These models provide an excellent description of the relationship between the actual and predicted doses up to 6 Gy. At doses of 8 and 10 Gy there appears to be saturation of the radiation-response signals with a corresponding diminution of accuracy. These results suggest that similar analyses in humans may be advantageous for use in a field-portable device designed to assess exposures in mass casualty situations.

Assessment of biodosimetry methods for a mass-casualty radiological incident: medical response and management considerations

Following a mass-casualty nuclear disaster, effective medical triage has the potential to save tens of thousands of lives. In order to best use the available scarce resources, there is an urgent need for biodosimetry tools to determine an individual's radiation dose. Initial triage for radiation exposure will include location during the incident, symptoms, and physical examination. Stepwise triage will include point of care assessment of less than or greater than 2 Gy, followed by secondary assessment, possibly with high throughput screening, to further define an individual's dose. Given the multisystem nature of radiation injury, it is unlikely that any single biodosimetry assay can be used as a standalone tool to meet the surge in capacity with the timeliness and accuracy needed. As part of the national preparedness and planning for a nuclear or radiological incident, the authors reviewed the primary literature to determine the capabilities and limitations of a number of biodosimetry assays currently available or under development for use in the initial and secondary triage of patients. Understanding the requirements from a response standpoint and the capability and logistics for the various assays will help inform future biodosimetry technology development and acquisition. Factors considered include: type of sample required, dose detection limit, time interval when the assay is feasible biologically, time for sample preparation and analysis, ease of use, logistical requirements, potential throughput, point-of-care capability, and the ability to support patient diagnosis and treatment within a therapeutically relevant time point.

Laboratory intercomparison of gene expression assays

The possibility of a large-scale acute radiation exposure necessitates the development of new methods that could provide rapid individual dose estimates with high sample throughput. The focus of the study was an intercomparison of laboratories' dose-assessment performances using gene expression assays. Lithium-heparinized whole blood from one healthy donor was irradiated (240 kVp, 1 Gy/min) immediately after venipuncture at approximately 37°C using single X-ray doses. Blood samples to establish calibration curves (0.25-4 Gy) as well as 10 blinded test samples (0.1-6.4 Gy) were incubated for 24 h at 37°C supplemented with an equal volume of medium and 10% fetal calf serum. For quantitative reverse transcription polymerase chain reaction (qRT-PCR), samples were lysed, stored at -20°C and shipped on ice. For the Chemical Ligation Dependent Probe Amplification methodology (CLPA), aliquots were incubated in 2 ml CLPA reaction buffer (DxTerity), mixed and shipped at room temperature. Assays were run in each laboratory according to locally established protocols. The mean absolute difference (MAD) of estimated doses relative to the true doses (in Gy) was calculated. We also merged doses into binary categories reflecting aspects of clinical/diagnostic relevance and examined accuracy, sensitivity and specificity. The earliest reported time on dose estimates was <8 h. The standard deviation of technical replicate measurements in 75% of all measurements was below 11%. MAD values of 0.3-0.5 Gy and 0.8-1.3 Gy divided the laboratories contributions into two groups. These fourfold differences in accuracy could be primarily explained by unexpected variances of the housekeeping gene (P = 0.0008) and performance differences in processing of calibration and blinded test samples by half of the contributing laboratories. Reported gene expression dose estimates aggregated into binary categories in general showed an accuracies and sensitivities of 93-100% and 76-100% for the groups, with low MAD and high MAD, respectively. In conclusion, gene expression-based dose estimates were reported quickly, and for laboratories with MAD between 0.3-0.5 Gy binary dose categories of clinical significance could be discriminated with an accuracy and sensitivity comparable to established cytogenetic assays.

Deoxyribonucleic acid damage-associated biomarkers of ionising radiation: current status and future relevance for radiology and radiotherapy

Diagnostic and therapeutic radiation technology has developed dramatically in recent years, and its use has increased significantly, bringing clinical benefit. The use of diagnostic radiology has become widespread in modern society, particularly in paediatrics where the clinical benefit needs to be balanced with the risk of leukaemia and brain cancer increasing after exposure to low doses of radiation. With improving long-term survival rates of radiotherapy patients and the ever-increasing use of diagnostic and interventional radiology procedures, concern has risen over the long-term risks and side effects from such treatments. Biomarker development in radiology and radiotherapy has progressed significantly in recent years to investigate the effects of such use and optimise treatment. Recent biomarker development has focused on improving the limitations of established techniques by the use of automation, increasing sensitivity and developing novel biomarkers capable of quicker results. The effect of low-dose exposure (0-100 mGy) used in radiology, which is increasingly linked to cancer incidences, is being investigated, as some recent research challenges the linear-no-threshold model. Radiotherapy biomarkers are focused on identifying radiosensitive patients, determining the treatment-associated risk and allowing for a tailored and more successful treatment of cancer patients. For biomarkers in any of these areas to be successfully developed, stringent criteria must be applied in techniques and analysis of data to reduce variation among reports and allow data sets to be accurately compared. Newly developed biomarkers can then be used in combination with the established techniques to better understand and quantify the individual biological response to exposures associated with radiology tests and to personalise treatment plans for patients.

High and low dose responses of transcriptional biomarkers in ex vivo X-irradiated human blood

PURPOSE

Modifications of gene expression following ionizing radiation (IR) exposure of cells in vitro and in vivo are well documented. However, little is known about the dose-responses of transcriptionally responsive genes, especially at low doses. In this study, we investigated these dose-responses and assessed inter-individual variability.

MATERIALS AND METHODS

High dose (0.5-4 Gy) and low dose (5-100 mGy) gene expression responses at 2 h and 24 h using 13 biomarkers transcriptionally regulated through the DNA damage response by the tumor suppressor p53 were investigated. Inter-individual variation was also examined.

RESULTS

High dose-response curves were best constructed using a polynomial fit while the low dose-response curves used a linear fit with linear R(2) values of 0.841-0.985. Individual variation was evident in the high and low dose ranges. The FDXR, DDB2 high dose gene combination produced a mean dose estimate of 0.7 Gy for 1 Gy irradiated 'unknown' samples (95% CIs of 0.3-1.1 Gy) and 1.4 Gy for 2 Gy exposure (95% CIs of 0.6-2.1 Gy). The FDXR, DDB2, CCNG1 low dose gene combination estimated 98 mGy (95% CIs of 27-169 mGy) for 100 mGy exposure.

CONCLUSIONS

These findings identify genes that fulfill some of the requirements of a good exposure biomarker even at low doses, such as sensitivity, reproducibility and simple proportionality with dose.

Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans

Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host’s inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A S. aureus classifier derived from a cohort of 94 human subjects distinguished S. aureus blood stream infection (BSI) from healthy subjects (AUC 0.99) and E. coli BSI (AUC 0.84). Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84). Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.92, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues.

Assessment of total- and partial-body irradiation in a baboon model: preliminary results of a kinetic study including clinical, physical, and biological parameters

This biodosimetry study used irradiated baboons to investigate the efficacy of a kinetic multiparameter (clinical, physical, and biological) approach for discriminating partial-body irradiation (PBI) and total-body irradiation (TBI). Animals were unilaterally (front) exposed to 60Co gamma rays (8 to 32 cGy min) using either TBI or vertical left hemi-body irradiation (HBI), as follows: 2.5 Gy TBI (n = 2), 5 Gy TBI (n = 2), 5 Gy HBI (n = 2), and 10 Gy HBI (n = 2). Midline tissue doses were measured at the anterior iliac crest level with an ionization chamber, and body dosimetry was performed using thermoluminescent dosimeters. Blood samples were collected before exposure and from 1 h until 200 d after irradiation. Clinical status, complete blood cell count, biochemical parameters, and cytogenetic analysis were evaluated. The partial least square discriminant analysis chosen for statistical analysis showed that the four groups of irradiated baboons were clearly separated. However, the dicentric chromosome assay may not distinguish HBI from TBI in confounding situations where equivalent whole-body doses are similar and the time of exposure is sufficient for peripheral blood lymphocyte homogenization. Interestingly, as bone marrow shielding in HBI animals prevented aplasia from happening, hematologic parameters such as the platelet count and Flt-3 ligand level helped to distinguish HBI and TBI. Moreover, the ratio of neutrophil to lymphocyte counts, creatine kinase, and citrulline levels may be discriminating biomarkers of dose or injury. Both early and delayed clinical signs and bioindicators appear to be useful for assessment of heterogeneous irradiation.

Proton radiation-induced miRNA signatures in mouse blood: characterization and comparison with 56Fe-ion and gamma radiation

PURPOSE

Previously, we showed that microRNA (miRNA) signatures derived from the peripheral blood of mice are highly specific for both radiation energy (γ-rays or high linear energy transfer [LET] (56)Fe ions) and radiation dose. Here, we investigate to what extent miRNA expression signatures derived from mouse blood can be used as biomarkers for exposure to 600 MeV proton radiation.

MATERIALS AND METHODS

We exposed mice to 600 MeV protons, using doses of 0.5 or 1.0 Gy, isolated total RNA at 6 h or 24 h after irradiation, and used quantitative real-time polymerase chain reaction (PCR) to determine the changes in miRNA expression.

RESULTS

A total of 26 miRNA were differentially expressed after proton irradiation, in either one (77%) or multiple conditions (23%). Statistical classifiers based on proton, γ, and (56)Fe-ion miRNA expression signatures predicted radiation type and proton dose with accuracies of 81% and 88%, respectively. Importantly, gene ontology analysis for proton-irradiated cells shows that genes targeted by radiation-induced miRNA are involved in biological processes and molecular functions similar to those controlled by miRNA in γ ray- and (56)Fe-irradiated cells.

CONCLUSIONS

Mouse blood miRNA signatures induced by proton, γ, or (56)Fe irradiation are radiation type- and dose-specific. These findings underline the complexity of the miRNA-mediated radiation response.

Radiation dose effect of DNA repair-related gene expression in mouse white blood cells

Background

The aim of this study was to screen molecular biomarkers for biodosimetry from DNA repair-related gene expression profiles.

Material/Methods

Mice were subjected to whole-body exposure with ⁶⁰Co γ rays with a dose range of 0–8 Gy at a dose rate of 0.80 Gy/min. RNA was extracted from the peripheral blood of irradiated mice at 4, 8, 12, 24 and 48hrs post-irradiation. The mRNA transcriptional changes of 11 genes related to DNA damage and repair were detected using real-time quantitative polymerase chain reaction (RT-PCR).

Results

Of the 11 genes examined, CDKN1A (cyclin-dependent kinase inhibitor 1A or p21, Cip1) and ATM (ataxia telangiectasia mutated) expression levels were found to be heavily up- and down-regulated, respectively, with exposure dose increasing at different post-irradiation times. RAD50 (RAD50 homolog), PLK3 (polo-like kinase 3), GADD45A (growth arrest and DNA damage-inducible, alpha), DDB2 (damage-specific DNA-binding protein 2), BBC3 (BCL2-binding component 3) and IER5 (immediate early response 5) gene expression levels were found to undergo significant oscillating changes over a broad dose range of 2–8 Gy at post-exposure time points observed. Three of the genes were found not to change within the observed exposure dose and post-radiation time ranges.

Conclusions

The results of this study add to the biodosimetry with biomarker data pool and will be helpful for constructing appropriate gene expression biomarker systems to evaluate radiation exposure doses.

Gene expression-based detection of radiation exposure in mice after treatment with granulocyte colony-stimulating factor and lipopolysaccharide

In a large-scale nuclear incident, many thousands of people may be exposed to a wide range of radiation doses. Rapid biological dosimetry will be required on an individualized basis to estimate the exposures and to make treatment decisions. To ameliorate the adverse effects of exposure, victims may be treated with one or more cytokine growth factors, including granulocyte colony-stimulating factor (G-CSF), which has therapeutic efficacy for treating radiation-induced bone marrow ablation by stimulating granulopoiesis. The existence of infections and the administration of G-CSF each may confound the ability to achieve reliable dosimetry by gene expression analysis. In this study, C57BL/6 mice were used to determine the extent to which G-CSF and lipopolysaccharide (LPS, which simulates infection by gram-negative bacteria) alter the expression of genes that are either radiation-responsive or non-responsive, i.e., show potential for use as endogenous controls. Mice were acutely exposed to (60)Co γ rays at either 0 Gy or 6 Gy. Two hours later the animals were injected with either 0.1 mg/kg of G-CSF or 0.3 mg/kg of LPS. Expression levels of 96 different gene targets were evaluated in peripheral blood after an additional 4 or 24 h using real-time quantitative PCR. The results indicate that the expression levels of some genes are altered by LPS, but altered expression after G-CSF treatment was generally not observed. The expression levels of many genes therefore retain utility for biological dosimetry or as endogenous controls. These data suggest that PCR-based quantitative gene expression analyses may have utility in radiation biodosimetry in humans even in the presence of an infection or after treatment with G-CSF.

Plasma miRNA as biomarkers for assessment of total-body radiation exposure dosimetry

The risk of radiation exposure, due to accidental or malicious release of ionizing radiation, is a major public health concern. Biomarkers that can rapidly identify severely-irradiated individuals requiring prompt medical treatment in mass-casualty incidents are urgently needed. Stable blood or plasma-based biomarkers are attractive because of the ease for sample collection. We tested the hypothesis that plasma miRNA expression profiles can accurately reflect prior radiation exposure. We demonstrated using a murine model that plasma miRNA expression signatures could distinguish mice that received total body irradiation doses of 0.5 Gy, 2 Gy, and 10 Gy (at 6 h or 24 h post radiation) with accuracy, sensitivity, and specificity of above 90%. Taken together, these data demonstrate that plasma miRNA profiles can be highly predictive of different levels of radiation exposure. Thus, plasma-based biomarkers can be used to assess radiation exposure after mass-casualty incidents, and it may provide a valuable tool in developing and implementing effective countermeasures.

Peripheral blood signatures of lead exposure

BACKGROUND

Current evidence indicates that even low-level lead (Pb) exposure can have detrimental effects, especially in children. We tested the hypothesis that Pb exposure alters gene expression patterns in peripheral blood cells and that these changes reflect dose-specific alterations in the activity of particular pathways.

METHODOLOGY/PRINCIPAL FINDING

Using Affymetrix Mouse Genome 430 2.0 arrays, we examined gene expression changes in the peripheral blood of female Balb/c mice following exposure to per os lead acetate trihydrate or plain drinking water for two weeks and after a two-week recovery period. Data sets were RMA-normalized and dose-specific signatures were generated using established methods of supervised classification and binary regression. Pathway activity was analyzed using the ScoreSignatures module from GenePattern.

CONCLUSIONS/SIGNIFICANCE

The low-level Pb signature was 93% sensitive and 100% specific in classifying samples a leave-one-out crossvalidation. The high-level Pb signature demonstrated 100% sensitivity and specificity in the leave-one-out crossvalidation. These two signatures exhibited dose-specificity in their ability to predict Pb exposure and had little overlap in terms of constituent genes. The signatures also seemed to reflect current levels of Pb exposure rather than past exposure. Finally, the two doses showed differential activation of cellular pathways. Low-level Pb exposure increased activity of the interferon-gamma pathway, whereas high-level Pb exposure increased activity of the E2F1 pathway.

Radiation-induced micro-RNA expression changes in peripheral blood cells of radiotherapy patients

PURPOSE

MicroRNAs (miRNAs), a class of noncoding small RNAs that regulate gene expression, are involved in numerous physiologic processes in normal and malignant cells. Our in vivo study measured miRNA and gene expression changes in human blood cells in response to ionizing radiation, to develop miRNA signatures that can be used as biomarkers for radiation exposure.

METHODS AND MATERIALS

Blood from 8 radiotherapy patients in complete remission 1 or 2 was collected immediately before and 4 hours after total body irradiation with 1.25 Gy x-rays. Both miRNA and gene expression changes were measured by means of quantitative polymerase chain reaction and microarray hybridization, respectively. Hierarchic clustering, multidimensional scaling, class prediction, and gene ontology analysis were performed to investigate the potential of miRNAs to serve as radiation biomarkers and to elucidate their likely physiologic roles in the radiation response.

RESULTS

The expression levels of 45 miRNAs were statistically significantly upregulated 4 hours after irradiation with 1.25 Gy x-rays, 27 of them in every patient. Nonirradiated and irradiated samples form separate clusters in hierarchic clustering and multidimensional scaling. Out of 223 differentially expressed genes, 37 were both downregulated and predicted targets of the upregulated miRNAs. Paired and unpaired miRNA-based classifiers that we developed can predict the class membership of a sample with unknown irradiation status, with accuracies of 100% when all 45 upregulated miRNAs are included. Both miRNA control of and gene involvement in biologic processes such as hemopoiesis and the immune response are increased after irradiation, whereas metabolic processes are underrepresented among all differentially expressed genes and the genes controlled by miRNAs.

CONCLUSIONS

Exposure to ionizing radiation leads to the upregulation of the expression of a considerable proportion of the human miRNAome of peripheral blood cells. These miRNA expression signatures can be used as biomarkers of radiation exposure.

Gene expression analysis in radiotherapy patients and C57BL/6 mice as a measure of exposure to ionizing radiation

Dose assessment after radiological disasters is imperative to decrease mortality through rationally directed medical intervention. Our goal was to identify biomarkers capable of qualitative (nonirradiated/irradiated) and/or quantitative (dose) assessment of radiation exposure. Using real-time quantitative PCR, biodosimetry genes were identified in blood samples from cancer patients undergoing total-body irradiation. Time- (5, 12, 23, 48 h) and dose- (0-8 Gy) dependent changes in gene expression were examined in C57BL/6 mice. A training set was used to derive weighted voting classification algorithms (nonirradiated/irradiated) and continuous regression (dose assessment) models that were tested in a separate validation set of mice. Of eight biodosimetry genes identified in cancer patients ( ACTA2 , BBC3 , CCNG1 , CDKN1A , GADD45A , MDK , SERPINE1 , Tnfrsf10b ), expression of BBC3 , CCNG1 , CDKN1A , SERPINE1 and Tnfrsf10b was significantly (P < 0.05) increased in irradiated mice. CCNG1 and CDKN1A expression segregated irradiated mice from controls with an accuracy, specificity and sensitivity of 96.3, 100.0 and 94.4%, respectively, at 48 h. Multiple linear regression analysis predicted doses for the 0-, 1-, 2-, 4-, 6- and 8-Gy treatment groups as 0.0 ± 0.2, 1.6 ± 1.0, 2.9 ± 1.4, 5.1 ± 2.0, 5.3 ± 0.7 and 10.5 ± 5.6 Gy, respectively. These results suggest that gene expression analysis could be incorporated into biodosimetry protocols for qualitative and quantitative assessment of radiation exposure.

Whole mouse blood microRNA as biomarkers for exposure to γ-rays and (56)Fe ion

PURPOSE

Biomarkers of ionising radiation exposure are useful in a variety of scenarios, such as medical diagnostic imaging, occupational exposures, and spaceflight. This study investigates to what extent microRNA (miRNA) expression signatures in mouse peripheral blood can be used as biomarkers for exposures to radiation with low and high linear energy transfers.

MATERIALS AND METHODS

Mice were irradiated with doses of 0.5, 1.5, or 5.0 Gy γ-rays (dose rate of 0.0136 Gy/s) or with doses of 0.1 or 0.5 Gy (56)Fe ions (dose rate of 0.00208 Gy/s). Total RNA was isolated from whole blood at 6 h or 24 h after irradiation. Three animals per irradiation condition were used. Differentially expressed miRNA were determined by means of quantitative real-time polymerase chain reaction.

RESULTS

miRNA expression signatures were radiation type-specific and dose- and time-dependent. The differentially expressed miRNA were expressed in either one condition (71%) or multiple conditions (29%). Classifiers based on the differentially expressed miRNA predicted radiation type or dose with accuracies between 75% and 100%. Gene-ontology analyses show that miRNA induced by irradiation are involved in the control of several biological processes, such as mRNA transcription regulation, nucleic-acid metabolism, and development.

CONCLUSION

miRNA signatures induced by ionising radiation in mouse blood are radiation type- and radiation dose-specific. These findings underline the complexity of the radiation response and the importance of miRNA in it.