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

Interlaboratory comparison of high-throughput protein biomarker assay quantifications for radiation exposure classification

In the event of a widespread radiological incident, thousands of individuals will require rapid assessment of exposure using validated biodosimetry assays to inform clinical triage. In this scenario, multiple biodosimetry laboratories may be necessary for large-volume sample processing. To meet this need, we have developed a high-throughput assay for the rapid measurement of intracellular protein biomarkers in human peripheral blood samples using an Imaging Flow Cytometry (IFC) platform. The objective of this work was to harmonize and validate the reproducibility of our blood biomarker assay for radiation exposure across three IFC instruments, two located at Columbia University (CU) and the third at Health Canada. The Center for Radiological Research (CRR) at CU served as the central laboratory and reference instrument, where samples were prepared in triplicate, labeled with two radiation responsive leukocyte biomarkers (BAX and phosphor-p53 (Ser37)), and distributed for simultaneous interrogation by each IFC. Initial tests showed that significantly different baseline biomarker measurements were generated on each instrument when using the same acquisition settings, suggesting that harmonization of signal intensities is necessary. Subsequent tests harmonized biomarker measurements after irradiation by modulating laser intensity using two reference materials: unstained samples and standardized rainbow beads. Both methods generated measurements on each instrument without significant differences between the new and references instruments, allowing for the use of one master template to quantify biomarker expression across multiple instruments. Deming regression analyses of 0-5 Gy dose-response curves showed overall good correlation of BAX and p53 values across new and reference instruments. While Bland-Altman analyses indicated low to moderate instrument biases, ROC Curve analyses ultimately show successful discrimination between exposed and unexposed samples on each instrument (AUC values > 0.85).

Parotid glands have a dysregulated immune response following radiation therapy

Head and neck cancer treatment often consists of surgical resection of the tumor followed by ionizing radiation (IR), which can damage surrounding tissues and cause adverse side effects. The underlying mechanisms of radiation-induced salivary gland dysfunction are not fully understood, and treatment options are scarce and ineffective. The wound healing process is a necessary response to tissue injury, and broadly consists of inflammatory, proliferative, and redifferentiation phases with immune cells playing key roles in all three phases. In this study, select immune cells were phenotyped and quantified, and certain cytokine and chemokine concentrations were measured in mouse parotid glands after IR. Further, we used a model where glandular function is restored to assess the immune phenotype in a regenerative response. These data suggest that irradiated parotid tissue does not progress through a typical inflammatory response observed in wounds that heal. Specifically, total immune cells (CD45+) decrease at days 2 and 5 following IR, macrophages (F4/80+CD11b+) decrease at day 2 and 5 and increase at day 30, while neutrophils (Ly6G+CD11b+) significantly increase at day 30 following IR. Additionally, radiation treatment reduces CD3- cells at all time points, significantly increases CD3+/CD4+CD8+ double positive cells, and significantly reduces CD3+/CD4-CD8- double negative cells at day 30 after IR. Previous data indicate that post-IR treatment with IGF-1 restores salivary gland function at day 30, and IGF-1 injections attenuate the increase in macrophages, neutrophils, and CD4+CD8+ T cells observed at day 30 following IR. Taken together, these data indicate that parotid salivary tissue exhibits a dysregulated immune response following radiation treatment which may contribute to chronic loss of function phenotype in head and neck cancer survivors.

Comparative Analysis of miRNA Expression after Whole-Body Irradiation Across Three Strains of Mice

Whole- or partial-body exposure to ionizing radiation damages major organ systems, leading to dysfunction on both acute and chronic timescales. Radiation medical countermeasures can mitigate acute damages and may delay chronic effects when delivered within days after exposure. However, in the event of widespread radiation exposure, there will inevitably be scarce resources with limited countermeasures to distribute among the affected population. Radiation biodosimetry is necessary to separate exposed from unexposed victims and determine those who requires the most urgent care. Blood-based, microRNA signatures have great potential for biodosimetry, but the affected population in such a situation will be genetically heterogeneous and have varying miRNA responses to radiation. Thus, there is a need to understand differences in radiation-induced miRNA expression across different genetic backgrounds to develop a robust signature. We used inbred mouse strains C3H/HeJ and BALB/c mice to determine how accurate miRNA in blood would be in developing markers for radiation vs. no radiation, low dose (1 Gy, 2 Gy) vs. high dose (4 Gy, 8 Gy), and high risk (8 Gy) vs. low risk (1 Gy, 2 Gy, 4 Gy). Mice were exposed to whole-body doses of 0 Gy, 1 Gy, 2 Gy, 4 Gy, or 8 Gy of X rays. MiRNA expression changes were identified using NanoString nCounter panels on blood RNA collected 1, 2, 3 or 7 days postirradiation. Overall, C3H/HeJ mice had more differentially expressed miRNAs across all doses and timepoints than BALB/c mice. The highest amount of differential expression occurred at days 2 and 3 postirradiation for both strains. Comparison of C3H/HeJ and BALB/c expression profiles to those previously identified in C57BL/6 mice revealed 12 miRNAs that were commonly expressed across all three strains, only one of which, miR-340-5p, displayed a consistent regulation pattern in all three miRNA data. Notably multiple Let-7 family members predicted high-dose and high-risk radiation exposure (Let-7a, Let-7f, Let-7e, Let-7g, and Let-7d). KEGG pathway analysis demonstrated involvement of these predicted miRNAs in pathways related to: Fatty acid metabolism, Lysine degradation and FoxO signaling. These findings indicate differences in the miRNA response to radiation across various genetic backgrounds, and highlights key similarities, which we exploited to discover miRNAs that predict radiation exposure. Our study demonstrates the need and the utility of including multiple animal strains in developing and validating biodosimetry diagnostic signatures. From this data, we developed highly accurate miRNA signatures capable of predicting exposed and unexposed subjects within a genetically heterogeneous population as quickly as 24 h of exposure to radiation.

Development of a human peripheral blood ex vivo model for rapid protein biomarker detection and applications to radiation biodosimetry

In the event of a widespread radiological incident, thousands of people may be exposed to a wide range of ionizing radiation. In this unfortunate scenario, there will be a need to quickly screen a large number of people to assess the amount of radiation exposure and triage for medical treatment. In our earlier work, we previously identified and validated a panel of radiosensitive protein biomarkers in blood leukocytes, using the humanized-mouse and non-human primate (NHP) models. The objective of this work was to develop a high-throughput imaging flow-cytometry (IFC) based assay for the rapid measurement of protein biomarker expression in human peripheral blood samples irradiated ex vivo. In this assay design, peripheral human blood samples from healthy adult donors were exposed to 0-5 Gy X-irradiation ex vivo and cultured for up to 2 days. Samples were stained with a cocktail of surface antigens (CD66b, CD20, and CD3), fixed and permeabilized, and intracellularly stained for BAX (Bcl-2-associated X) protein, used here as a representative biomarker. Samples were interrogated by IFC, and a uniform analysis template was created to measure biomarker expression in heterogeneous and specific leukocyte subtype populations at each time point. In this human blood ex vivo model, we show that within gated populations of leukocyte subtypes, B-cells are highly radiosensitive with the smallest surviving fraction, followed by T-cells and granulocytes. Dose-dependent biomarker responses were measured in the lymphocytes, B-, and T-cell populations, but not in the granulocytes, with dose-response curves showing increasing fold changes in BAX protein expression up to Day 2 in lymphocyte populations. We present here the successful use of this ex vivo model for the development of radiation dose-response curves of a candidate protein biomarker towards future applications of dose reconstruction and biodosimetry.

Machine learning approach for quantitative biodosimetry of partial-body or total-body radiation exposures by combining radiation-responsive biomarkers

During a large-scale radiological event such as an improvised nuclear device detonation, many survivors will be shielded from radiation by environmental objects, and experience only partial-body irradiation (PBI), which has different consequences, compared with total-body irradiation (TBI). In this study, we tested the hypothesis that applying machine learning to a combination of radiation-responsive biomarkers (ACTN1, DDB2, FDXR) and B and T cell counts will quantify and distinguish between PBI and TBI exposures. Adult C57BL/6 mice of both sexes were exposed to 0, 2.0-2.5 or 5.0 Gy of half-body PBI or TBI. The random forest (RF) algorithm trained on ½ of the data reconstructed the radiation dose on the remaining testing portion of the data with mean absolute error of 0.749 Gy and reconstructed the product of dose and exposure status (defined as 1.0 × Dose for TBI and 0.5 × Dose for PBI) with MAE of 0.472 Gy. Among irradiated samples, PBI could be distinguished from TBI: ROC curve AUC = 0.944 (95% CI: 0.844-1.0). Mouse sex did not significantly affect dose reconstruction. These results support the hypothesis that combinations of protein biomarkers and blood cell counts can complement existing methods for biodosimetry of PBI and TBI exposures.

Revision of cytogenetic dosimetry in the IAEA manual 2011 based on data about radio-sensitivity and dose-rate findings contributing

In order to achieve the goal of rapid response, effective controland protection of life inlarge-scale radiation events, the IAEA Manual 2011 has been revised based on the data of radio-sensitivity, dose-rate findings. Analyze individual differences in radiation sensitivity using ⁶⁰ Co radiation (0.27 Gy/min). Chromosomal aberrations with different irradiation dose rates were used to establish the biological dose curve and analyze the excess of the "dicentric + ring" caused by the dose rate at each dose point; DAPI-images and Metafer 4 were used to capture metaphase images and make further analysis. The data were collected in 2020, Dicentric + ring/100 Cells was 17.5-43.8, the average value was28.32 ± 6.98. The mean value of Dicentric + ring/100 Cells was 31.37 in males while 25.27 in females, there are significant differences (p < .01). The irradiation dose is dominant, At each dose point, the value of"(dicentric chromosome + centric rings)/cell" is proportional to "dose rate", that is, Y = kx + b, within the dose range of 1-5 Gy, "(dicentric chromosome + centric rings)/Cell" holds a quadratic linear relationship with dose rate, that is, y = ax²  + bx + c; The DAPI-images might give you more hints than those of conventional Giemsa-stain. The authors recommend that the IAEA Manual 2011 could be revised based on data of radio-sensitivity and dose-rate, which may contribute to the establishment of a unified dose-response calibration curve and stimulation of potential for automation in cytogenetic biodosimetry. (1) Individual differences of radiosensitivity are very large. (2) At each dose point, "(dicentric chromosome + centric rings)/cell" is proportional to "dose rate", that is, Y = kx + b. (3) "(dicentric chromosome + centric rings)/Cell" is a quadratic linear relationship with dose rate, that is, y = ax²  + bx + c. (4) We created a "Unity Standard Curve of Biological Dose Estimation". Creating a Unity Standard Curve of Biological Dose, under these circumstances, we can form a joint and rapid response to a nuclear and radiological accident.

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.

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.

Cytogenetic Damage of Human Lymphocytes in Humanized Mice Exposed to Neutrons and X Rays 24 h After Exposure

Detonation of an improvised nuclear device highlights the need to understand the risk of mixed radiation exposure as prompt radiation exposure could produce significant neutron and gamma exposures. Although the neutron component may be a relatively small percentage of the total absorbed dose, the large relative biological effectiveness (RBE) can induce larger biological DNA damage and cell killing. The objective of this study was to use a hematopoietically humanized mouse model to measure chromosomal DNA damage in human lymphocytes 24 h after in vivo exposure to neutrons (0.3 Gy) and X rays (1 Gy). The human dicentric and cytokinesis-block micronucleus assays were performed to measure chromosomal aberrations in human lymphocytes in vivo from the blood and spleen, respectively. The mBAND assay based on fluorescent in situ hybridization labeling was used to detect neutron-induced chromosome 1 inversions in the blood lymphocytes of the neutron-irradiated mice. Cytogenetics endpoints, dicentrics and micronuclei showed that there was no significant difference in yields between the 2 irradiation types at the doses tested, indicating that neutron-induced chromosomal DNA damage in vivo was more biologically effective (RBE ∼3.3) compared to X rays. The mBAND assay, which is considered a specific biomarker of high-LET neutron exposure, confirmed the presence of clustered DNA damage in the neutron-irradiated mice but not in the X-irradiated mice, 24 h after exposure.