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

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

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

FAILLA MEMORIAL LECTURE How We Got Here: One Laboratory's Odyssey in the Field of Radiation-Inducible Genes

This review focuses on early discoveries that contributed to our understanding and the scope of transcriptional responses after radiation damage. Before the development of modern approaches to assess overall global transcriptomic responses, the idea that mammalian cells could respond to DNA-damaging agents in a manner analogous to bacteria was not generally accepted. To investigate this possibility, the development of technology to identify differentially expressed low-abundance transcripts substantially facilitated our appreciation that DNA damaging agents like UV radiation and subsequently ionizing radiation did in fact produce robust transcriptional responses. Here we focus on our identification and characterization of radiation-inducible genes, and how even early studies on stress gene signaling highlighted the broad scope of transcriptional responses to radiation damage. Since then, the central role of transcriptional responses to radiation injury in maintaining genome integrity has been highlighted in many processes, including cell cycle checkpoint control, resistance to cancer by p53 and other key factors, cell senescence, and metabolism.

Advanced Technologies in Radiation Research

The U.S. Government is committed to maintaining a robust research program that supports a portfolio of scientific experts who are investigating the biological effects of radiation exposure. On August 17 and 18, 2023, the Radiation and Nuclear Countermeasures Program, within the National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH), partnered with the National Cancer Institute, NIH, the National Aeronautics and Space Administration, and the Radiation Injury Treatment Network to convene a workshop titled, Advanced Technologies in Radiation Research (ATRR), which focused on the use of advanced technologies under development or in current use to accelerate radiation research. This meeting report provides a comprehensive overview of the research presented at the workshop, which included an assembly of subject matter experts from government, industry, and academia. Topics discussed during the workshop included assessments of acute and delayed effects of radiation exposure using modalities such as clustered regularly interspaced short palindromic repeats (CRISPR) - based gene editing, tissue chips, advanced computing, artificial intelligence, and immersive imaging techniques. These approaches are being applied to develop products to diagnose and treat radiation injury to the bone marrow, skin, lung, and gastrointestinal tract, among other tissues. The overarching goal of the workshop was to provide an opportunity for the radiation research community to come together to assess the technological landscape through sharing of data, methodologies, and challenges, followed by a guided discussion with all participants. Ultimately, the organizers hope that the radiation research community will benefit from the workshop and seek solutions to scientific questions that remain unaddressed. Understanding existing research gaps and harnessing new or re-imagined tools and methods will allow for the design of studies to advance medical products along the critical path to U.S. Food and Drug Administration approval.

DDB2 and MDM2 genes are promising markers for radiation diagnosis and estimation of radiation dose independent of trauma and burns

In the field of biodosimetry, the current accepted method for evaluating radiation dose fails to meet the need of rapid, large-scale screening, and most RNA marker-related studies of biodosimetry are concentrating on a single type of ray, while some other potential factors, such as trauma and burns, have not been covered. Microarray datasets that contain the data of human peripheral blood samples exposed to X-ray, neutron, and γ-ray radiation were obtained from the GEO database. Totally, 33 multi-type ray co-induced genes were obtained at first from the differentially expressed genes (DEGs) and key genes identified by weighted gene co-expression network analysis (WGCNA), and these genes were mainly enriched in DNA damage, cellular apoptosis, and p53 signaling pathway. Following transcriptome sequencing of blood samples from 11 healthy volunteers, 13 patients with severe burns, and 37 patients with severe trauma, 6635 trauma-related DEGs and 7703 burn-related DEGs were obtained. Through the exclusion method, a total of 12 radiation-specific genes independent of trauma and burns were identified. ROC curve analysis revealed that the DDB2 gene performed the best in diagnosis of all three types of ray radiation, while correlation analysis showed that the MDM2 gene was the best in assessment of radiation dose. The results of multiple-linear regression analysis indicated that such analysis could improve the accuracy in assessment of radiation dose. Moreover, the DDB2 and MDM2 genes remained effective in radiation diagnosis and assessment of radiation dose in an external dataset. In general, the study brings new insights into radiation biodosimetry.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

The DNA damage response to radiological imaging: from ROS and γH2AX foci induction to gene expression responses in vivo

Candidate ionising radiation exposure biomarkers must be validated in humans exposed in vivo. Blood from patients undergoing positron emission tomography-computed tomography scan (PET-CT) and skeletal scintigraphy (scintigraphy) was drawn before (0 h) and after (2 h) the procedure for correlation analyses of the response of selected biomarkers with radiation dose and other available patient information. FDXR, CDKN1A, BBC3, GADD45A, XPC, and MDM2 expression was determined by qRT-PCR, DNA damage (γH2AX) by flow cytometry, and reactive oxygen species (ROS) levels by flow cytometry using the 2', 7'-dichlorofluorescein diacetate test in peripheral blood mononuclear cells (PBMC). For ROS experiments, 0- and 2-h samples were additionally exposed to UVA to determine whether diagnostic irradiation conditioned the response to further oxidative insult. With some exceptions, radiological imaging induced weak γH2AX foci, ROS and gene expression fold changes, the latter with good coherence across genes within a patient. Diagnostic imaging did not influence oxidative stress in PBMC successively exposed to UVA. Correlation analyses with patient characteristics led to low correlation coefficient values. γH2AX fold change, which correlated positively with gene expression, presented a weak positive correlation with injected activity, indicating a radiation-induced subtle increase in DNA damage and subsequent activation of the DNA damage response pathway. The exposure discrimination potential of these biomarkers in the absence of control samples as frequently demanded in radiological emergencies, was assessed using raw data. These results suggest that the variability of the response in heterogeneous populations might complicate identifying individuals exposed to low radiation doses.

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

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

SETD2 regulates gene transcription patterns and is associated with radiosensitivity in lung adenocarcinoma

Lung adenocarcinoma (LUAD) has high morbidity and mortality worldwide, and its prognosis remains unsatisfactory. Identification of epigenetic biomarkers associated with radiosensitivity is beneficial for precision medicine in LUAD patients. SETD2 is important in repairing DNA double-strand breaks and maintaining chromatin integrity. Our studies established a comprehensive analysis pipeline, which identified SETD2 as a radiosensitivity signature. Multi-omics analysis revealed enhanced chromatin accessibility and gene transcription by SETD2. In both LUAD bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq), we found that SETD2-associated positive transcription patterns were associated with DNA damage responses. SETD2 knockdown significantly upregulated tumor cell apoptosis, attenuated proliferation and migration of LUAD tumor cells, and enhanced radiosensitivity in vitro. Moreover, SETD2 was a favorably prognostic factor whose effects were antagonized by the m6A-related genes RBM15 and YTHDF3 in LUAD. In brief, SETD2 was a promising epigenetic biomarker in LUAD patients.

Transcriptomics of Wet Skin Biopsies Predict Early Radiation-Induced Hematological Damage in a Mouse Model

The lack of an easy and fast radiation-exposure testing method with a dosimetric ability complicates triage and treatment in response to a nuclear detonation, radioactive material release, or clandestine exposure. The potential of transcriptomics in radiation diagnosis and prognosis were assessed here using wet skin (blood/skin) biopsies obtained at hour 2 and days 4, 7, 21, and 28 from a mouse radiation model. Analysis of significantly differentially transcribed genes (SDTG; p ≤ 0.05 and FC ≥ 2) during the first post-exposure week identified the glycoprotein 6 (GP-VI) signaling, the dendritic cell maturation, and the intrinsic prothrombin activation pathways as the top modulated pathways with stable inactivation after lethal exposures (20 Gy) and intermittent activation after sublethal (1, 3, 6 Gy) exposure time points (TPs). Interestingly, these pathways were inactivated in the late TPs after sublethal exposure in concordance with a delayed deleterious effect. Modulated transcription of a variety of collagen types, laminin, and peptidase genes underlay the modulated functions of these hematologically important pathways. Several other SDTGs related to platelet and leukocyte development and functions were identified. These results outlined genetic determinants that were crucial to clinically documented radiation-induced hematological and skin damage with potential countermeasure applications.

NIH Policies and Regulatory Pathways to U.S. FDA licensure: Strategies to Inform Advancement of Radiation Medical Countermeasures and Biodosimetry Devices

The Radiation and Nuclear Countermeasures Program within the National Institute of Allergy and Infectious Diseases (NIAID), is tasked with the mandate of identifying biodosimetry tests to assess exposure and medical countermeasures (MCMs) to mitigate/treat injuries to individuals exposed to significant doses of ionizing radiation from a radiological/nuclear incident, hosted. To fulfill this mandate, the Radiation and Nuclear Countermeasures Program (RNCP), hosted a workshop in 2018 workshop entitled "Policies and Regulatory Pathways to U.S. FDA licensure: Radiation Countermeasures and Biodosimetry Devices." The purpose of the meeting was to facilitate the advancement of MCMs and biodosimetry devices by assessing the research devices and animal models used in preclinical studies; government policies on reproducibility, rigor and robustness; regulatory considerations for MCMs and biodosimetry devices; and lessons learned from sponsors of early stage MCM or biodosimetry devices. Meeting presentations were followed by a NIAID-led, open discussion among academic investigators, industry researchers and U.S. government representatives.

Early molecular markers for retrospective biodosimetry and prediction of acute health effects

Radiation-induced biological changes occurring within hours and days after irradiation can be potentially used for either exposure reconstruction (retrospective dosimetry) or the prediction of consecutively occurring acute or chronic health effects. The advantage of molecular protein or gene expression (GE) (mRNA) marker lies in their capability for early (1-3 days after irradiation), high-throughput and point-of-care diagnosis, required for the prediction of the acute radiation syndrome (ARS) in radiological or nuclear scenarios. These molecular marker in most cases respond differently regarding exposure characteristics such as e.g. radiation quality, dose, dose rate and most importantly over time. Changes over time are in particular challenging and demand certain strategies to deal with. With this review, we provide an overview and will focus on already identified and used mRNA GE and protein markers of the peripheral blood related to the ARS. These molecules are examined in light of 'ideal' characteristics of a biomarkers (e.g. easy accessible, early response, signal persistency) and the validation degree. Finally, we present strategies on the use of these markers considering challenges as their variation over time and future developments regarding e.g. origin of samples, point of care and high-throughput diagnosis.

The 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.

The transcriptomic revolution and radiation biology

PURPOSE

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

CONCLUSIONS

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

Development of Biomarkers for Radiation Biodosimetry and Medical Countermeasures Research: Current Status, Utility, and Regulatory Pathways

Biomarkers are important indicators of biological processes in health or disease. For this reason, they play a critical role in advanced development of radiation biodosimetry tools and medical countermeasures (MCMs). They can aid in the assessment of radiation exposure level, extent of radiation-induced injury, and/or efficacy of an MCM. This meeting report summarizes the presentations and discussions from the 2020 workshop titled, "Biomarkers in Radiation Biodosimetry and Medical Countermeasures," sponsored by the Radiation and Nuclear Countermeasures Program (RNCP) at the National Institute of Allergy and Infectious Diseases (NIAID). The main goals of this meeting were to: 1. Provide an overview on biomarkers and to focus on the state of science with regards to biomarkers specific to radiation biodosimetry and MCMs; 2. Understand developmental challenges unique to the role of biomarkers in the fields of radiation biodosimetry and MCM development; and 3. Identify existing gaps and needs for translational application.

Improved radiation expression profiling in blood by sequential application of sensitive and specific gene signatures

PURPOSE

Combinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning (ML) based signatures (with 8-20% misclassification rates). These signatures can quantify therapeutically relevant as well as accidental radiation exposures. The prodromal symptoms of acute radiation syndrome (ARS) overlap those present in influenza and dengue fever infections. Surprisingly, these human radiation signatures misclassified gene expression profiles of virally infected samples as false positive exposures. The present study investigates these and other confounders, and then mitigates their impact on signature accuracy.

METHODS

This study investigated recall by previous and novel radiation signatures independently derived from multiple Gene Expression Omnibus datasets on common and rare non-neoplastic blood disorders and blood-borne infections (thromboembolism, S. aureus bacteremia, malaria, sickle cell disease, polycythemia vera, and aplastic anemia). Normalized expression levels of signature genes are used as input to ML-based classifiers to predict radiation exposure in other hematological conditions.

RESULTS

Except for aplastic anemia, these blood-borne disorders modify the normal baseline expression values of genes present in radiation signatures, leading to false-positive misclassification of radiation exposures in 8-54% of individuals. Shared changes, predominantly in DNA damage response and apoptosis-related gene transcripts in radiation and confounding hematological conditions, compromise the utility of these signatures for radiation assessment. These confounding conditions (sickle cell disease, thrombosis, S. aureus bacteremia, malaria) induce neutrophil extracellular traps, initiated by chromatin decondensation, DNA damage response and fragmentation followed by programmed cell death or extrusion of DNA fragments. Riboviral infections (e.g. influenza or dengue fever) have been proposed to bind and deplete host RNA binding proteins, inducing R-loops in chromatin. R-loops that collide with incoming replication forks can result in incompletely repaired DNA damage, inducing apoptosis and releasing mature virus. To mitigate the effects of confounders, we evaluated predicted radiation-positive samples with novel gene expression signatures derived from radiation-responsive transcripts encoding secreted blood plasma proteins whose expression levels are unperturbed by these conditions.

CONCLUSIONS

This approach identifies and eliminates misclassified samples with underlying hematological or infectious conditions, leaving only samples with true radiation exposures. Diagnostic accuracy is significantly improved by selecting genes that maximize both sensitivity and specificity in the appropriate tissue using combinations of the best signatures for each of these classes of signatures.

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.

Whole blood gene expression within days after total-body irradiation predicts long term survival in Gottingen minipigs

Gottingen minipigs mirror the physiological radiation response observed in humans and hence make an ideal candidate model for studying radiation biodosimetry for both limited-sized and mass casualty incidents. We examined the whole blood gene expression profiles starting one day after total-body irradiation with increasing doses of gamma-rays. The minipigs were monitored for up to 45 days or time to euthanasia necessitated by radiation effects. We successfully identified dose- and time-agnostic (over a 1-7 day period after radiation), survival-predictive gene expression signatures derived using machine-learning algorithms with high sensitivity and specificity. These survival-predictive signatures fare better than an optimally performing dose-differentiating signature or blood cellular profiles. These findings suggest that prediction of survival is a much more useful parameter for making triage, resource-utilization and treatment decisions in a resource-constrained environment compared to predictions of total dose received. It should hopefully be possible to build such classifiers for humans in the future.

Intercomparison of conventional and QuickScan dicentric scoring for the validation of individual biodosimetry analysis in Taiwan

PURPOSE

The dicentric chromosome assay (DCA), the gold standard for radiation biodosimetry, evaluates an individual absorbed radiation dose by the analysis of DNA damage in human lymphocytes. The conventional (C-DCA) and QuickScan (QS-DCA) scoring methods are sensitive for estimating radiation dose. The Biodosimetry Laboratory at Institute of Nuclear Energy Research (INER), Taiwan, participated in intercomparison exercises conducted by Health Canada (HC) in 2014, 2015 and 2018 to validate the laboratory's accuracy and performance.

MATERIAL AND METHODS

Blood samples for the conventional dose response curve for Taiwan were irradiated with 0, 0.25, 0.5, 1, 2, 3, 4 and 5 Gy. Ten blind blood samples were provided by HC. Either or both of two methods of conventional (C) or QuickScan (QS) scoring could be chosen for the HC's intercomparison. For C-DCA triage scoring, only cells with 46 centromeres were counted and each scorer recorded the number of dicentrics in the first 50 metaphases or stopped scoring when 30 dicentrics were reached. Scorers also recorded how much time it took to analyze 10, 20, and 50 cells. Subsequently, the data were entered into the Dose Estimate software (DoseEstimate_v5.1) and dose estimates were calculated. With QS-DCA scoring, a minimum of 50 metaphase cells (or 30 dicentrics) were scored in apparently complete metaphases without verification of exactly 46 centromeres.

RESULTS

For the blinded blood samples irradiated at HC and shipped to INER, the mean absolute deviation (MAD) derived after scoring 50 cells for C-DCA and QS-DCA was <0.5 Gy for all three intercomparisons, meeting the criteria for acceptance.

CONCLUSION

The results indicated that the Biodosimetry Laboratory at INER can provide reliable dose estimates in the case of a large-scale radiation accident.

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.

The RABiT-II DCA in the Rhesus Macaque Model

An automated platform for cytogenetic biodosimetry, the "Rapid Automated Biodosimetry Tool II (RABiT-II)," adapts the dicentric chromosome assay (DCA) for high-throughput mass-screening of the population after a large-scale radiological event. To validate this test, the U.S. Federal Drug Administration (FDA) recommends demonstrating that the high-throughput biodosimetric assay in question correctly reports the dose in an in vivo model. Here we describe the use of rhesus macaques (Macaca mulatta) to augment human studies and validate the accuracy of the high-throughput version of the DCA. To perform analysis, we developed the 17/22-mer peptide nucleic acid (PNA) probes that bind to the rhesus macaque's centromeres. To our knowledge, these are the first custom PNA probes with high specificity that can be used for chromosome analysis in M. mulatta. The accuracy of fully-automated chromosome analysis was improved by optimizing a low-temperature telomere PNA FISH staining in multiwell plates and adding the telomere detection feature to our custom chromosome detection software, FluorQuantDic V4. The dicentric frequencies estimated from in vitro irradiated rhesus macaque samples were compared to human blood samples of individuals subjected to the same ex vivo irradiation conditions. The results of the RABiT-II DCA analysis suggest that, in the lymphocyte system, the dose responses to gamma radiation in the rhesus macaques were similar to those in humans, with small but statistically significant differences between these two model systems.

A High Throughput Approach to Reconstruct Partial-Body and Neutron Radiation Exposures on an Individual Basis

Biodosimetry-based individualized reconstruction of complex irradiation scenarios (partial-body shielding and/or neutron + photon mixtures) can improve treatment decisions after mass-casualty radiation-related incidents. We used a high-throughput micronucleus assay with automated scanning and imaging software on ex-vivo irradiated human lymphocytes to: a) reconstruct partial-body and/or neutron exposure, and b) estimate separately the photon and neutron doses in a mixed exposure. The mechanistic background is that, compared with total-body photon irradiations, neutrons produce more heavily-damaged lymphocytes with multiple micronuclei/binucleated cell, whereas partial-body exposures produce fewer such lymphocytes. To utilize these differences for biodosimetry, we developed metrics that describe micronuclei distributions in binucleated cells and serve as predictors in machine learning or parametric analyses of the following scenarios: (A) Homogeneous gamma-irradiation, mimicking total-body exposures, vs. mixtures of irradiated blood with unirradiated blood, mimicking partial-body exposures. (B) X rays vs. various neutron + photon mixtures. The results showed high accuracies of scenario and dose reconstructions. Specifically, receiver operating characteristic curve areas (AUC) for sample classification by exposure type reached 0.931 and 0.916 in scenarios A and B, respectively. R² for actual vs. reconstructed doses in these scenarios reached 0.87 and 0.77, respectively. These encouraging findings demonstrate a proof-of-principle for the proposed approach of high-throughput reconstruction of clinically-relevant complex radiation exposure scenarios.

The hunt for radiation biomarkers: current situation

Purpose: The possibility of a large-scale acute radiation exposure necessitates the development of new methods that could provide a rapid assessment of the doses received by individuals using high-throughput technologies. There is also a great interest in developing new biomarkers of dose exposure, which could be used in large molecular epidemiological studies in order to correlate estimated doses received and health effects. The goal of this review was to summarize current literature focused on biological dosimetry, namely radiation-responsive biomarkers.Methods: The studies involved in this review were thoroughly selected according to the determined criteria and PRISMA guidelines.Results: We described briefly recent advances in radiation genomics and metabolomics, giving particular emphasis to proteomic analysis. The majority of studies were performed on animal models (rats, mice, and non-human primates). They have provided much beneficial information, but the most relevant tests have been done on human (oncological) patients. By inspecting the radiaiton biodosimetry literate of the last 10 years, we identified a panel of candidate markers for each -omic approach involved.Conslusions: We reviewed different methodological approaches and various biological materials, which can be exploited for dose-effect prediction. The protein biomarkers from human plasma are ideal for this specific purpose. From a plethora of candidate markers, FDXR is a very promising transcriptomic candidate, and importantly this biomarker was also confirmed by some studies at protein level in humans.

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

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

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

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

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

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

Medical countermeasures for radiation induced health effects: report of an Interagency Panel Session held at the NASA Human Research Program Investigator's Workshop, 26 January 2017

An Interagency Panel Session organized by the NASA Human Research Program (HRP) Space Radiation Program Element (SRPE) was held during the NASA HRP Investigator’s Workshop (IWS) in Galveston, Texas on 26 January 2017 to identify complementary research areas that will advance the testing and development of medical countermeasures (MCMs) in support of radioprotection and radiation mitigation on the ground and in space. There were several areas of common interest identified among the various participating agencies. This report provides a summary of the topics discussed by each agency along with potential areas of intersection for mutual collaboration opportunities. Common goals induded repurposing of pharmaceuticals, nutraceuticals for use as radioprotectors and/or mitigators, low-dose/chronic exposure paradigms, late effects post-radiation exposure, mixed-field exposures of gamma-neutron, performance decrements, and methods to determine individual exposure levels.

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

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

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.

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

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

Validating Baboon Ex Vivo and In Vivo Radiation-Related Gene Expression with Corresponding Human Data

The research for high-throughput diagnostic tests for victims of radio/nuclear incidents remains ongoing. In this context, we have previously identified candidate genes that predict risk of late-occurring hematologic acute radiation syndrome (HARS) in a baboon model. The goal of the current study was to validate these genes after radiation exposure in humans. We also examined ex vivo relative to in vivo measurements in both species and describe dose-response relationships. Eighteen baboons were irradiated in vivo to simulate different patterns of partial- or total-body irradiation (TBI), corresponding to an equivalent dose of 2.5 or 5 Sv. Human in vivo blood samples were obtained from patients exposed to different dose ranges: diagnostic computerized tomography (CT; 0.004-0.018 Sv); radiotherapy for prostate cancer (0.25-0.3 Sv); and TBI of leukemia patients (2 × 1.5 or 2 × 2 Sv, five patients each). Peripheral whole blood of another five baboons and human samples from five healthy donors were cultivated ex vivo and irradiated with 0-4 Sv. RNA was isolated pairwise before and 24 h after irradiation and converted into cDNA. Gene expression of six promising candidate genes found previously by us in a baboon model ( WNT3, POU2AF1, CCR7, ARG2, CD177, WLS), as well as three genes commonly used in ex vivo whole blood experiments ( FDXR, PCNA, DDB2) was measured using qRT-PCR. We confirmed the six baboon candidate genes in leukemia patients. However, expression for the candidate gene FDXR showed an inverse relationship, as it was downregulated in baboons and upregulated in human samples. Comparisons among the in vivo and ex vivo experiments revealed the same pattern in both species and indicated peripheral blood cells to represent the radiation-responsive targets causing WNT3 and POU2AF1 gene expression changes. CCR7, ARG2, CD177 and WLS appeared to be altered due to radiation-responsive targets other than the whole blood cells. Linear dose-response relationships of FDXR, WNT3 and POU2AF1 using human ex vivo samples corresponded with human in vivo samples, suggesting that ex vivo models for in vivo dose estimates can be used over a wide dose range (0.001-5 Sv for POU2AF1). In summary, we validated six baboon candidate genes in humans, but the FDXR measurements underscored the importance of independent assessments even when candidates from animal models have striking gene sequence homology to humans. Since whole blood cells represented the same radiation-responsive targets for FDXR, WNT3 and POU2AF1 gene expression changes, ex vivo cell culture models can be utilized for in vivo dose estimates over a dose range covering up to 3.5 log scales. These findings might be a step forward in the development of a gene expression-based high-throughput diagnostic test for populations involved in large-scale radio/nuclear incidents.

Whole thorax irradiation of non-human primates induces persistent nuclear damage and gene expression changes in peripheral blood cells

We investigated the cytogenetic and gene expression responses of peripheral blood cells of non-human primates (NHP, Macaca mulatta) that were whole-thorax irradiated with a single dose of 10 Gy. In this model, partial irradiation of NHPs in the thoracic region (Whole Thorax Lung Irradiation, WTLI) allows the study of late radiation-induced lung injury, while avoiding acute radiation syndromes related to hematopoietic and gastrointestinal injury. A transient drop in circulating lymphocytes and platelets was seen by 9 days, followed by elevations in respiratory rate, circulating neutrophils, lymphocytes, and monocytes at 60-100 days, corresponding to computed tomography (CT) and histologic evidence of pneumonitis, and elective euthanasia of four animals. To evaluate long-term DNA damage in NHP peripheral blood lymphocytes after 10 Gy WTLI, we used the cytokinesis-block micronucleus (CBMN) assay to measure chromosomal aberrations as post-mitotic micronuclei in blood samples collected up to 8 months after irradiation. Regression analysis showed significant induction of micronuclei in NHP blood cells that persisted with a gradual decline over the 8-month study period, suggesting long-term DNA damage in blood lymphocytes after WTLI. We also report transcriptomic changes in blood up to 30 days after WTLI. We isolated total RNA from peripheral blood at 3 days before and then at 2, 5 and 30 days after irradiation. We identified 1187 transcripts that were significantly changed across the 30-day time course. From changes in gene expression, we identified biological processes related to immune responses, which persisted across the 30-day study. Response to oxygen-containing compounds and bacteria were implicated by gene-expression changes at the earliest day 2 and latest, day 30 time-points. Gene expression changes suggest a persistent altered state of the immune system, specifically response to infection, for at least a month after WTLI.