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Ionizing radiations encountered by astronauts on deep space missions produce biological damage by two main mechanisms: (1) Targeted effects (TE) due to direct traversals of cells by ionizing tracks. (2) Non-targeted effects (NTE) caused by release of signals from directly hit cells. The combination of these mechanisms generates non-linear dose response shapes, which need to be modeled quantitatively to predict health risks from space exploration. Here we used a TE + NTE model to analyze data on APC(1638N/+) mouse tumorigenesis induced by space-relevant doses of protons, 4He, 12C, 16O, 28Si or 56Fe ions, or γ rays. A customized weighted Negative Binomial distribution was used to describe the radiation type- and dose-dependent data variability. This approach allowed detailed quantification of dose-response shapes, NTE- and TE-related model parameters, and radiation quality metrics (relative biological effectiveness, RBE, and radiation effects ratio, RER, relative to γ rays) for each radiation type. Based on the modeled responses for each radiation type, we predicted the tumor yield for a Mars-mission-relevant mixture of these radiations, using the recently-developed incremental effect additivity (IEA) synergy theory. The proposed modeling approach can enhance current knowledge about quantification of space radiation quality effects, dose response shapes, and ultimately the health risks for astronauts.

The main goal of this study is to test the utility of calyculin A induced G2-PCC assay as a biodosimetry triage tool for assessing a wide range of low and acute high radiation dose exposures of photons. Towards this initiative, chromosome aberrations induced by low and high doses of x-rays were evaluated and characterized in G2-prematurely condensed chromosomes (G2-PCCs) by fluorescence in situ hybridization (FISH) using human centromere and telomere specific PNA (peptide nucleic acid) probes. A dose dependent increase in the frequency of dicentric chromosomes was observed in the G2-PCCs up to 20 Gy of x-rays. The combined yields of dicentrics and rings in the G2-PCCs showed a clear dose dependency up to 20 Gy from 0.02/cell for 0.1 Gy to 14.98/cell for 20 Gy. Centric rings were observed more frequently than acentric ring chromosomes in the G2-PCCs at all the radiation doses from 1 Gy to 20 Gy. A head-to-head comparison was also performed by FISH on the yields of chromosome aberrations induced by different doses of x-rays (0 Gy -7.5 Gy) in colcemid arrested metaphase chromosomes and calyculin A induced G2-PCCs. In general, the frequencies of dicentrics, rings and acentric fragments were slightly higher in G2-PCCs than in colcemid arrested metaphase chromosomes at all the radiation doses, but the differences were not statistically significant. To reduce the turnaround time for absorbed radiation dose estimation, attempt was made to obtain G2-PCCs by reducing the culture time to 36 hrs. The absorbed doses estimated in x-rays irradiated (0,1,2 and 4 Gy) G2-PCCs after 36 hrs of culture were grossly like that of G2-PCCs and colcemid arrested metaphase chromosomes prepared after 48 hrs of culture. Our study indicates that the shortened version of calyculin A induced G2-PCC assay coupled with the FISH staining technique can serve as an effective triage biodosimetry tool for large-scale radiological/nuclear incidents. [ABSTRACT FROM AUTHOR]

After a large-scale radiological or nuclear event, hundreds of thousands of people may be exposed to ionizing radiation and require subsequent medical management. Acute exposure to moderate doses (2–6 Gy) of radiation can lead to the hematopoietic acute radiation syndrome, in which the bone marrow (BM) is severely compromised, and severe hemorrhage and infection are common. Previously, we have developed a panel of intracellular protein markers (FDXR, ACTN1, DDB2, BAX, p53 and TSPYL2), designed to reconstruct absorbed radiation dose from human peripheral blood (PB) leukocyte samples in humanized mice up to 3 days after exposure. The objective of this work was to continue to use the humanized mouse model to evaluate biomarker dose-/ time- kinetics in human PB leukocytes in vivo, at an earlier (day 2) and later (day 7) time point, after exposure to total-body irradiation (TBI) doses of 0 to 2 Gy of X rays. In addition, to assess hematological sensitivity and radiation-induced injury, PB leukocyte cell counts, human BM hematopoietic stem cell (HSC) and progenitor cell [multipotent progenitor (MPP), common myeloid progenitor (CMP), granulocyte myeloid progenitor (GMP), megakaryocyte/erythrocyte progenitor (MEP) and multi-lymphoid progenitor (MLP)] levels were measured, and their correlation was also examined as the BM damages are difficult to assess by routine tests. Peripheral blood B-cells were significantly lower after TBI doses of 0.5 Gy on day 2 and 2 Gy on days 2 and 7; T-cells were significantly reduced only on day 2 after 2 Gy TBI. Bone marrow HSCs and MPP cells showed a dose-dependent depletion after irradiation with 0.5 Gy and 2 Gy on day 2, and after 1 Gy and 2 Gy on day 7. Circulating B cells correlated with HSCs, MPP and MLP cells on day 2, whereas T cells correlated with MPP, and myeloid cells correlated with MLP cells. On day 7, B cells correlated with MPP, CMP, GMP and MEP, while myeloid cells correlated with CMP, GMP and MEP. The intracellular leukocyte biomarkers were able to discriminate unirradiated and irradiated samples at different time points calculated by receiver operating characteristic (ROC) curve. Using machine learning algorithm methods, combining ACTN1, p53, TSPYL2 and PBT cell and PB-B cell counts served as a strong predictor (area under the ROC >0.8) to distinguish unirradiated and irradiated samples independent of the days after TBI. The results further validated our biomarker-based triage assay and additionally evaluated the radiation sensitivity of the hematopoietic system after TBI exposures. [ABSTRACT FROM AUTHOR]

Introduction: Treating head and neck squamous cell carcinomas (HNSCC), especially human papillomavirus negative (HPV-) and locally advanced cases, remains difficult. Our previous analyses of radiotherapy-only HNSCC clinical trials data using mechanistically-motivated models of tumor repopulation and killing by radiotherapy predicted that hyperfractionation with twice-daily fractions, or hypofractionation involving increased doses/fraction and reduced treatment durations, both improve tumor control and reduce late normal tissue toxicity, compared with standard protocols using 35x2 Gy. Here we further investigated the validity of these conclusions by analyzing a large modern dataset on 3,346 HNSCC radiotherapy patients from the University Health Network in Toronto, Canada, where 42.5% of patients were also treated with chemotherapy. Methods: We used a two-step approach that combines mechanistic modeling concepts with state-of-the-art machine learning, beginning with Random Survival Forests (RSF) for an exploratory analysis and followed by Causal Survival Forests (CSF) for a focused causal analysis. The mechanistic concept of biologically effective dose (BED) was implemented for the standard dose-independent (DI) tumor repopulation model, our alternative dose-dependent (DD) repopulation model, and a simple model with no repopulation (BEDsimp). These BED variants were included in the RSF model, along with age, stage, HPV status and other relevant variables, to predict patient overall survival (OS) and cause-specific mortality (deaths from the index cancer, other cancers or other causes). Results: Model interpretation using Shapley Additive Explanations (SHAP) values and correlation matrices showed that high values of BEDDD or BEDDI, but not BEDsimp, were associated with decreased patient mortality. Targeted causal inference analyses were then performed using CSF to estimate the causal effect of each BED variant on OS. They revealed that high BEDDD (>61.8 Gy) or BEDDI (>57.6 Gy), but not BEDsimp, increased patient restricted mean survival time (RMST) by 0.5-1.0 years and increased survival probability (SP) by 5-15% several years after treatment. In addition to population-level averages, CSF generated individual-level causal effect estimates for each patient, facilitating personalized medicine. Discussion: These findings are generally consistent with those of our previous mechanistic modeling, implying the potential benefits of altered radiotherapy fractionation schemes (e.g. 25x2.4 Gy, 20x2.75 Gy, 18x3.0 Gy) which increase BEDDD and BEDDI and counteract tumor repopulation more effectively than standard fractionation. Such regimens may represent potentially useful hypofractionated options for treating HNSCC. [ABSTRACT FROM AUTHOR]

Development of novel biodosimetry assays and medical countermeasures is needed to obtain a level of radiation preparedness in the event of malicious or accidental mass exposures to ionizing radiation (IR). For biodosimetry, metabolic profiling with mass spectrometry (MS) platforms has identified several small molecules in easily accessible biofluids that are promising for dose reconstruction. As our microbiome has profound effects on biofluid metabolite composition, it is of interest how variation in the host microbiome may affect metabolomics based biodosimetry. Here, we 'knocked out' the microbiome of male and female C57BL/6 mice (Abx mice) using antibiotics and then irradiated (0, 3, or 8 Gy) them to determine the role of the host microbiome on biofluid radiation signatures (1 and 3 d urine, 3 d serum). Biofluid metabolite levels were compared to a sham and irradiated group of mice with a normal microbiome (Abx-con mice). To compare post-irradiation effects in urine, we calculated the Spearman's correlation coefficients of metabolite levels with radiation dose. For selected metabolites of interest, we performed more detailed analyses using linear mixed effect models to determine the effects of radiation dose, time, and microbiome depletion. Serum metabolite levels were compared using an ANOVA. Several metabolites were affected after antibiotic administration in the tryptophan and amino acid pathways, sterol hormone, xenobiotic and bile acid pathways (urine) and lipid metabolism (serum), with a post-irradiation attenuative effect observed for Abx mice. In urine, dose×time interactions were supported for a defined radiation metabolite panel (carnitine, hexosamine-valine-isoleucine [Hex-V-I], creatine, citric acid, and Nε,Nε,Nε-trimethyllysine [TML]) and dose for N1-acetylspermidine, which also provided excellent (AUROC ≥ 0.90) to good (AUROC ≥ 0.80) sensitivity and specificity according to the area under the receiver operator characteristic curve (AUROC) analysis. In serum, a panel consisting of carnitine, citric acid, lysophosphatidylcholine (LysoPC) (14:0), LysoPC (20:3), and LysoPC (22:5) also gave excellent to good sensitivity and specificity for identifying post-irradiated individuals at 3 d. Although the microbiome affected the basal levels and/or post-irradiation levels of these metabolites, their utility in dose reconstruction irrespective of microbiome status is encouraging for the use of metabolomics as a novel biodosimetry assay. [ABSTRACT FROM AUTHOR]

Blood-based gene expression profiles that can reconstruct radiation exposure are being developed as a practical approach to radiation biodosimetry. However, age and sex could potentially limit the accuracy of the approach. In this study, we determined the impact of age on the peripheral blood cell gene expression profile of female mice exposed to radiation and identified differences and similarities with a previously obtained transcriptomic signature of male mice. Young (2 months) and old (24 months) female mice were irradiated with 4 Gy X-rays, total RNA was isolated from blood 24 hours later and subjected to whole-genome microarray analysis. Dose reconstruction analyses using a gene signature trained on gene expression data from irradiated young male mice showed accurate reconstruction of 0 or 4 Gy doses with root mean square error of ±0.75 Gy (R2 = 0.90) in young female mice. Although dose reconstruction for irradiated old female mice was less accurate than young female mice, the deviation from the actual radiation dose was not statistically significant. Pathway analysis of differentially expressed genes revealed that after irradiation, apoptosis-related functions were overrepresented, whereas functions related to quantities of various immune cell subtypes were underrepresented, among differentially expressed genes from young female mice, but not older animals. Furthermore, young mice significantly upregulated genes involved in phagocytosis, a process that eliminates apoptotic cells and preserves tissue homeostasis. Both functions were also overrepresented in young, but not old, male mice following 4 Gy X-irradiation. Lastly, functions associated with neutrophil activation that is essential for killing invading pathogens and regulating the inflammatory response were predicted to be uniquely enriched in young but not old female mice. This work supports the concept that peripheral blood gene expression profiles can be identified in mice that accurately predict physical radiation dose exposure irrespective of age and sex. [ABSTRACT FROM AUTHOR]

As the number of cancer survivors grows, prediction of radiotherapy-induced second cancer risks becomes increasingly important. Because the latency period for solid tumors is long, the risks of recently introduced radiotherapy protocols are not yet directly measurable. In the accompanying article, we presented a new biologically based mathematical model, which, in principle, can estimate second cancer risks for any protocol. The novelty of the model is that it integrates, into a single formalism, mechanistic analyses of pre-malignant cell dynamics on two different time scales: short-term during radiotherapy and recovery; long-term during the entire life span. Here, we apply the model to nine solid cancer types (stomach, lung, colon, rectal, pancreatic, bladder, breast, central nervous system, and thyroid) using data on radiotherapy-induced second malignancies, on Japanese atomic bomb survivors, and on background US cancer incidence. Potentially, the model can be incorporated into radiotherapy treatment planning algorithms, adding second cancer risk as an optimization criterion.

Mathematical models of radiation carcinogenesis are important for understanding mechanisms and for interpreting or extrapolating risk. There are two classes of such models: (1) long-term formalisms that track pre-malignant cell numbers throughout an entire lifetime but treat initial radiation dose–response simplistically and (2) short-term formalisms that provide a detailed initial dose–response even for complicated radiation protocols, but address its modulation during the subsequent cancer latency period only indirectly. We argue that integrating short- and long-term models is needed. As an example of this novel approach, we integrate a stochastic short-term initiation/inactivation/repopulation model with a deterministic two-stage long-term model. Within this new formalism, the following assumptions are implemented: radiation initiates, promotes, or kills pre-malignant cells; a pre-malignant cell generates a clone, which, if it survives, quickly reaches a size limitation; the clone subsequently grows more slowly and can eventually generate a malignant cell; the carcinogenic potential of pre-malignant cells decreases with age.