Biologically-based mechanistic models of radiation-related carcinogenesis applied to epidemiological data

A comparative study on the dose-effect of low-dose radiation based on microdosimetric analysis and single-cell sequencing technology

The biological mechanisms triggered by low-dose exposure still need to be explored in depth. In this study, the potential mechanisms of low-dose radiation when irradiating the BEAS-2B cell lines with a Cs-137 gamma-ray source were investigated through simulations and experiments. Monolayer cell population models were constructed for simulating and analyzing distributions of nucleus-specific energy within cell populations combined with the Monte Carlo method and microdosimetric analysis. Furthermore, the 10 × Genomics single-cell sequencing technology was employed to capture the heterogeneity of individual cell responses to low-dose radiation in the same irradiated sample. The numerical uncertainties can be found both in the specific energy distribution in microdosimetry and in differential gene expressions in radiation cytogenetics. Subsequently, the distribution of nucleus-specific energy was compared with the distribution of differential gene expressions to guide the selection of differential genes bioinformatics analysis. Dose inhomogeneity is pronounced at low doses, where an increase in dose corresponds to a decrease in the dispersion of cellular-specific energy distribution. Multiple screening of differential genes by microdosimetric features and statistical analysis indicate a number of potential pathways induced by low-dose exposure. It also provides a novel perspective on the selection of sensitive biomarkers that respond to low-dose radiation.

Human-mouse comparison of the multistage nature of radiation carcinogenesis in a mathematical model

Mouse models are vital for assessing risk from environmental carcinogens, including ionizing radiation, yet the interspecies difference in the dose response precludes direct application of experimental evidence to humans. Herein, we take a mathematical approach to delineate the mechanism underlying the human-mouse difference in radiation-related cancer risk. We used a multistage carcinogenesis model assuming a mutational action of radiation to analyze previous data on cancer mortality in the Japanese atomic bomb survivors and in lifespan mouse experiments. Theoretically, the model predicted that exposure will chronologically shift the age-related increase in cancer risk forward by a period corresponding to the time in which the spontaneous mutational process generates the same mutational burden as that the exposure generates. This model appropriately fitted both human and mouse data and suggested a linear dose response for the time shift. The effect per dose decreased with increasing age at exposure similarly between humans and mice on a per-lifespan basis (0.72- and 0.71-fold, respectively, for every tenth lifetime). The time shift per dose was larger by two orders of magnitude in humans (7.8 and 0.046 years per Gy for humans and mice, respectively, when exposed at ~35% of their lifetime). The difference was mostly explained by the two orders of magnitude difference in spontaneous somatic mutation rates between the species plus the species-independent radiation-induced mutation rate. Thus, the findings delineate the mechanism underlying the interspecies difference in radiation-associated cancer mortality and may lead to the use of experimental evidence for risk prediction in humans.

Minimum latency effects for cancer associated with exposures to radiation or other carcinogens

BACKGROUND

In estimating radiation-associated cancer risks a fixed period for the minimum latency is often assumed. Two empirical latency functions have been used to model latency, continuously increasing from 0. A stochastic biologically-based approach yields a still more plausible way of describing latency and can be directly estimated from clinical data.

METHODS

We derived the parameters for a stochastic biologically-based model from tumour growth data for various cancers, and least-squares fitted the two types of empirical latency function to the stochastic model-predicted cumulative probability.

RESULTS

There is wide variation in growth rates among tumours, particularly slow for prostate and thyroid cancer and particularly fast for leukaemia. The slow growth rate for prostate and thyroid tumours implies that the number of tumour cells required for clinical detection cannot greatly exceed 106. For all tumours, both empirical latency functions closely approximated the predicted biological model cumulative probability.

CONCLUSIONS

Our results, illustrating use of a stochastic biologically-based model using clinical data not tied to any particular carcinogen, have implications for estimating latency associated with any mutagen. They apply to tumour growth in general, and may be useful for example, in planning screenings for cancer using imaging techniques.

Noncancer Effects of Ionizing Radiation Exposure on the Eye, the Circulatory System and beyond: Developments made since the 2011 ICRP Statement on Tissue Reactions

For radiation protection purposes, noncancer effects with a threshold-type dose-response relationship have been classified as tissue reactions (formerly called nonstochastic or deterministic effects), and equivalent dose limits aim to prevent occurrence of such tissue reactions. Accumulating evidence demonstrates increased risks for several late occurring noncancer effects at doses and dose rates much lower than previously considered. In 2011, the International Commission on Radiological Protection (ICRP) issued a statement on tissue reactions to recommend a threshold of 0.5 Gy to the lens of the eye for cataracts and to the heart and brain for diseases of the circulatory system (DCS), independent of dose rate. Literature published thereafter continues to provide updated knowledge. Increased risks for cataracts below 0.5 Gy have been reported in several cohorts (e.g., including in those receiving protracted or chronic exposures). A dose threshold for cataracts is less evident with longer follow-up, with limited evidence available for risk of cataract removal surgery. There is emerging evidence for risk of normal-tension glaucoma and diabetic retinopathy, but the long-held tenet that the lens represents among the most radiosensitive tissues in the eye and in the body seems to remain unchanged. For DCS, increased risks have been reported in various cohorts, but the existence or otherwise of a dose threshold is unclear. The level of risk is less uncertain at lower dose and lower dose rate, with the possibility that risk per unit dose is greater at lower doses and dose rates. Target organs and tissues for DCS are also unknown, but may include heart, large blood vessels and kidneys. Identification of potential factors (e.g., sex, age, lifestyle factors, coexposures, comorbidities, genetics and epigenetics) that may modify radiation risk of cataracts and DCS would be important. Other noncancer effects on the radar include neurological effects (e.g., Parkinson's disease, Alzheimer's disease and dementia) of which elevated risk has increasingly been reported. These late occurring noncancer effects tend to deviate from the definition of tissue reactions, necessitating more scientific developments to reconsider the radiation effect classification system and risk management. This paper gives an overview of historical developments made in ICRP prior to the 2011 statement and an update on relevant developments made since the 2011 ICRP statement.

The scientific basis for the use of the linear no-threshold (LNT) model at low doses and dose rates in radiological protection

The linear no-threshold (LNT) model was introduced into the radiological protection system about 60 years ago, but this model and its use in radiation protection are still debated today. This article presents an overview of results on effects of exposure to low linear-energy-transfer radiation in radiobiology and epidemiology accumulated over the last decade and discusses their impact on the use of the LNT model in the assessment of radiation-related cancer risks at low doses. The knowledge acquired over the past 10 years, both in radiobiology and epidemiology, has reinforced scientific knowledge about cancer risks at low doses. In radiobiology, although certain mechanisms do not support linearity, the early stages of carcinogenesis comprised of mutational events, which are assumed to play a key role in carcinogenesis, show linear responses to doses from as low as 10 mGy. The impact of non-mutational mechanisms on the risk of radiation-related cancer at low doses is currently difficult to assess. In epidemiology, the results show excess cancer risks at dose levels of 100 mGy or less. While some recent results indicate non-linear dose relationships for some cancers, overall, the LNT model does not substantially overestimate the risks at low doses. Recent results, in radiobiology or in epidemiology, suggest that a dose threshold, if any, could not be greater than a few tens of mGy. The scientific knowledge currently available does not contradict the use of the LNT model for the assessment of radiation-related cancer risks within the radiological protection system, and no other dose-risk relationship seems more appropriate for radiological protection purposes.

Insights into radiation carcinogenesis based on dose-rate effects in tissue stem cells

PURPOSE

Increasing epidemiological and biological evidence suggests that radiation exposure enhances cancer risk in a dose-dependent manner. This can be attributed to the 'dose-rate effect,' where the biological effect of low dose-rate radiation is lower than that of the same dose at a high dose-rate. This effect has been reported in epidemiological studies and experimental biology, although the underlying biological mechanisms are not completely understood. In this review, we aim to propose a suitable model for radiation carcinogenesis based on the dose-rate effect in tissue stem cells.

METHODS

We surveyed and summarized the latest studies on the mechanisms of carcinogenesis. Next, we summarized the radiosensitivity of intestinal stem cells and the role of dose-rate in the modulation of stem-cell dynamics after irradiation.

RESULTS

Consistently, driver mutations can be detected in most cancers from past to present, supporting the hypothesis that cancer progression is initiated by the accumulation of driver mutations. Recent reports demonstrated that driver mutations can be observed even in normal tissues, which suggests that the accumulation of mutations is a necessary condition for cancer progression. In addition, driver mutations in tissue stem cells can cause tumors, whereas they are not sufficient when they occur in non-stem cells. For non-stem cells, tissue remodeling induced by marked inflammation after the loss of tissue cells is important in addition to the accumulation of mutations. Therefore, the mechanism of carcinogenesis differs according to the cell type and magnitude of stress. In addition, our results indicated that non-irradiated stem cells tend to be eliminated from three-dimensional cultures of intestinal stem cells (organoids) composed of irradiated and non-irradiated stem cells, supporting the stem-cell competition.

CONCLUSIONS

We propose a unique scheme in which the dose-rate dependent response of intestinal stem cells incorporates the concept of the threshold of stem-cell competition and context-dependent target shift from stem cells to whole tissue. The concept highlights four key issues that should be considered in radiation carcinogenesis: i.e. accumulation of mutations; tissue reconstitution; stem-cell competition; and environmental factors like epigenetic modifications.

Considerations of Medical Preparedness to Assess and Treat Various Populations During a Radiation Public Health Emergency

During a radiological or nuclear public health emergency, given the heterogeneity of civilian populations, it is incumbent on medical response planners to understand and prepare for a potentially high degree of interindividual variability in the biological effects of radiation exposure. A part of advanced planning should include a comprehensive approach, in which the range of possible human responses in relation to the type of radiation expected from an incident has been thoughtfully considered. Although there are several reports addressing the radiation response for special populations (as compared to the standard 18-45-year-old male), the current review surveys published literature to assess the level of consideration given to differences in acute radiation responses in certain sub-groups. The authors attempt to bring clarity to the complex nature of human biology in the context of radiation to facilitate a path forward for radiation medical countermeasure (MCM) development that may be appropriate and effective in special populations. Consequently, the focus is on the medical (as opposed to logistical) aspects of preparedness and response. Populations identified for consideration include obstetric, pediatric, geriatric, males, females, individuals of different race/ethnicity, and people with comorbidities. Relevant animal models, biomarkers of radiation injury, and MCMs are highlighted, in addition to underscoring gaps in knowledge and the need for consistent and early inclusion of these populations in research. The inclusion of special populations in preclinical and clinical studies is essential to address shortcomings and is an important consideration for radiation public health emergency response planning. Pursuing this goal will benefit the population at large by considering those at greatest risk of health consequences after a radiological or nuclear mass casualty incident.

Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms

The probability that an observed cancer was caused by radiation exposure is usually estimated using cancer rates and risk models from radioepidemiological cohorts and is called assigned share (AS). This definition implicitly assumes that an ongoing carcinogenic process is unaffected by the studied radiation exposure. However, there is strong evidence that radiation can also accelerate an existing clonal development towards cancer. In this work, we define different association measures that an observed cancer was newly induced, accelerated, or retarded. The measures were quantified exemplarily by Monte Carlo simulations that track the development of individual cells. Three biologically based two-stage clonal expansion (TSCE) models were applied. In the first model, radiation initiates cancer development, while in the other two, radiation has a promoting effect, i.e. radiation accelerates the clonal expansion of pre-cancerous cells. The parameters of the TSCE models were derived from breast cancer data from the atomic bomb survivors of Hiroshima and Nagasaki. For exposure at age 30, all three models resulted in similar estimates of AS at age 60. For the initiation model, estimates of association were nearly identical to AS. However, for the promotion models, the cancerous clonal development was frequently accelerated towards younger ages, resulting in associations substantially higher than AS. This work shows that the association between a given cancer and exposure in an affected person depends on the underlying biological mechanism and can be substantially larger than the AS derived from classic radioepidemiology.

Mathematical models of the solid cancer induced by atomic bomb and the spontaneous cancer in the daily life-Proposal of a new medical treatment for cancers

BACKGROUND

A mathematical model of the radiation-induced cancer was devised to explain the change of incidence rates pursued by Radiation Effect Research Foundation for 25 years.

AIM

The aim of this work is construction of mechanisms of radiation-induced cancer and cancers observed in the daily life.

METHODS AND RESULTS

First, we found a way to separate spontaneous cancers from radiation-induced cancers observed among atomic-bomb victims in Hiroshima and Nagasaki districts by using a constructed algorithm. The isolated incidence rates of radiation-induced cancers were reproduced by a two-stage model mechanical collision of impinging radiation with cells and succeeding mutation of the damaged cell to cancer. This model satisfactorily reproduced observed solid cancer incidence rates. We further attempted to construct a mathematical model for the age-dependence of spontaneous cancers appearing in the daily life and concluded that the cancer should be generated at cell division.

CONCLUSION

With these findings, we reached to a conclusion that cancers may be suppressed by eliminating damaged cells with mild-dose radiation.

Effects of spatial variation in dose delivery: what can we learn from radon-related lung cancer studies?

Exposure to radon progeny results in heterogeneous dose distributions in many different spatial scales. The aim of this review is to provide an overview on the state of the art in epidemiology, clinical observations, cell biology, dosimetry, and modelling related to radon exposure and its association with lung cancer, along with priorities for future research. Particular attention is paid on the effects of spatial variation in dose delivery within the organs, a factor not considered in radiation protection. It is concluded that a multidisciplinary approach is required to improve risk assessment and mechanistic understanding of carcinogenesis related to radon exposure. To achieve these goals, important steps would be to clarify whether radon can cause other diseases than lung cancer, and to investigate radon-related health risks in children or persons at young ages. Also, a better understanding of the combined effects of radon and smoking is needed, which can be achieved by integrating epidemiological, clinical, pathological, and molecular oncology data to obtain a radon-associated signature. While in vitro models derived from primary human bronchial epithelial cells can help to identify new and corroborate existing biomarkers, they also allow to study the effects of heterogeneous dose distributions including the effects of locally high doses. These novel approaches can provide valuable input and validation data for mathematical models for risk assessment. These models can be applied to quantitatively translate the knowledge obtained from radon exposure to other exposures resulting in heterogeneous dose distributions within an organ to support radiation protection in general.

Radiation dose rate effects: what is new and what is needed?

Despite decades of research to understand the biological effects of ionising radiation, there is still much uncertainty over the role of dose rate. Motivated by a virtual workshop on the "Effects of spatial and temporal variation in dose delivery" organised in November 2020 by the Multidisciplinary Low Dose Initiative (MELODI), here, we review studies to date exploring dose rate effects, highlighting significant findings, recent advances and to provide perspective and recommendations for requirements and direction of future work. A comprehensive range of studies is considered, including molecular, cellular, animal, and human studies, with a focus on low linear-energy-transfer radiation exposure. Limits and advantages of each type of study are discussed, and a focus is made on future research needs.

Application of radiation omics in the development of adverse outcome pathway networks: an example of radiation-induced cardiovascular disease

BACKGROUND

Epidemiological studies have indicated that exposure of the heart to doses of ionizing radiation as low as 0.5 Gy increases the risk of cardiac morbidity and mortality with a latency period of decades. The damaging effects of radiation to myocardial and endothelial structures and functions have been confirmed radiobiologically at high dose, but much less is known at low dose. Integration of radiation biology and epidemiology data is a recommended approach to improve the radiation risk assessment process. The adverse outcome pathway (AOP) framework offers a comprehensive tool to compile and translate mechanistic information into pathological endpoints which may be relevant for risk assessment at the different levels of a biological system. Omics technologies enable the generation of large volumes of biological data at various levels of complexity, from molecular pathways to functional organisms. Given the quality and quantity of available data across levels of biology, omics data can be attractive sources of information for use within the AOP framework. It is anticipated that radiation omics studies could improve our understanding of the molecular mechanisms behind the adverse effects of radiation on the cardiovascular system. In this review, we explored the available omics studies on radiation-induced cardiovascular disease (CVD) and their applicability to the proposed AOP for CVD.

RESULTS

The results of 80 omics studies published on radiation-induced CVD over the past 20 years have been discussed in the context of the AOP of CVD proposed by Chauhan et al. Most of the available omics data on radiation-induced CVD are from proteomics, transcriptomics, and metabolomics, whereas few datasets were available from epigenomics and multi-omics. The omics data presented here show great promise in providing information for several key events of the proposed AOP of CVD, particularly oxidative stress, alterations of energy metabolism, extracellular matrix and vascular remodeling.

CONCLUSIONS

The omics data presented here shows promise to inform the various levels of the proposed AOP of CVD. However, the data highlight the urgent need of designing omics studies to address the knowledge gap concerning different radiation scenarios, time after exposure and experimental models. This review presents the evidence to build a qualitative omics-informed AOP and provides views on the potential benefits and challenges in using omics data to assess risk-related outcomes.

Mathematical modeling for mutator phenotype and clonal selection advantage in the risk analysis of lung cancer

Cancer is one of the leading diseases for human mortality. Although substantial research works have been conducted to investigate the initiation and progression of cancer disease, it is still an active debate regarding the function of mutations conferring a clone advantage and the importance of mutator phenotypes caused by the mutation of stability genes. To address this issue further, we develop a mathematical model based on the incidence data of non-small cell lung cancer and small cell lung cancer from the Surveillance Epidemiology and End Results registry in the USA. The key biological parameters have been analyzed to investigate the potential effective measures for inhibiting the risk of lung cancer. Although the first event is the gene mutation that leads to clonal expansion of cells for lung cancer, the simulation results show that the clonal advantage of cancer cells alone is insufficient to cause tumorigenesis. Our analysis suggests that mutations in genes that keep genetic stability are critical in the development of lung cancer. This implies that mutator phenotype is an important indicator for the diagnosis of lung cancer, which can enable early detection and treatment to reduce the risk of lung cancer effectively. Furthermore, the parameter analysis indicates that it would be highly effective to control the risk of lung cancer by inhibiting the transformation rate from the normal cells to mutated cells and the clonal expansion of cells with fewer gene mutations.

Review of Knowledge of Uranium-Induced Kidney Toxicity for the Development of an Adverse Outcome Pathway to Renal Impairment

An adverse outcome pathway (AOP) is a conceptual construct of causally and sequentially linked events, which occur during exposure to stressors, with an adverse outcome relevant to risk assessment. The development of an AOP is a means of identifying knowledge gaps in order to prioritize research assessing the health risks associated with exposure to physical or chemical stressors. In this paper, a review of knowledge was proposed, examining experimental and epidemiological data, in order to identify relevant key events and potential key event relationships in an AOP for renal impairment, relevant to stressors such as uranium (U). Other stressors may promote similar pathways, and this review is a necessary step to compare and combine knowledge reported for nephrotoxicants. U metal ions are filtered through the glomerular membrane of the kidneys, then concentrate in the cortical and juxtaglomerular areas, and bind to the brush border membrane of the proximal convoluted tubules. U uptake by epithelial cells occurs through endocytosis and the sodium-dependent phosphate co-transporter (NaPi-IIa). The identified key events start with the inhibition of the mitochondria electron transfer chain and the collapse of mitochondrial membrane potential, due to cytochrome b5/cytochrome c disruption. In the nucleus, U directly interacts with negatively charged DNA phosphate, thereby inducing an adduct formation, and possibly DNA strand breaks or cross-links. U also compromises DNA repair by inhibiting zing finger proteins. Thereafter, U triggers the Nrf2, NF-κB, or endoplasmic reticulum stress pathways. The resulting cellular key events include oxidative stress, DNA strand breaks and chromosomal aberrations, apoptosis, and pro-inflammatory effects. Finally, the main adverse outcome is tubular damage of the S2 and S3 segments of the kidneys, leading to tubular cell death, and then kidney failure. The attribution of renal carcinogenesis due to U is controversial, and specific experimental or epidemiological studies must be conducted. A tentative construction of an AOP for uranium-induced kidney toxicity and failure was proposed.

From Atherosclerosis to Myocardial Infarction: A Process-Oriented Model Investigating the Role of Risk Factors

Mathematical models are able to reflect biological processes and to capture epidemiologic data. Thus, they may help elucidate roles of risk factors in disease progression. We propose to account for smoking, hypertension, and dyslipidemia in a previously published process-oriented model that describes the development of atherosclerotic lesions resulting in myocardial infarction (MI). The model is sex-specific and incorporates individual heterogeneity. It was applied to population-based individual risk factors and MI rates (Cooperative Health Research in the Region of Augsburg (KORA) study) together with subclinical atherosclerotic lesion data (Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study). Different model variants were evaluated, testing the association of risk factors with different disease processes. Best fits were obtained for smoking affecting a late-stage disease process, suggesting a thrombogenic role. Hypertension was mainly related to complicated, vulnerable lesions. Dyslipidemia was consistent with increasing the number of initial lesions. By accounting for heterogeneity, individual hazard ratios differ from the population average. The mean individual hazard ratio for smoking was twice the population-based hazard ratio for men and even more for women. Atherosclerotic lesion progression and MI incidence data can be related in a mathematical model to illuminate how risk factors affect different phases of this pathological process.

A recent development of new therapeutic agents and novel drug targets for cancer treatment

Despite recent advances in cancer diagnosis, prevention, detection, as well as management, the disease is expected to be the top cause of death globally. The chemotherapy approach for cancer has become more advanced in its design, yet no medication can cure enough against all types of cancer and its stage. Thus, this review aimed to summarize a recent development of new therapeutic agents and novel drug targets for the treatment of cancer. Several obstacles stand in the way of effective cancer treatment and drug development, including inaccessibility of tumor site by appropriate drug concentration, debilitating untoward effects caused by non-selective tissue distribution of chemotherapeutic agents, and occurrence of drug resistance, which leads to cross-resistance to a variety of drugs. Resistance to treatment with anticancer drugs results from multiple factors and the most common reason for acquiring drug resistance is marking and expelling drugs that prevent cancer cells to be targeted by chemotherapeutic agents. Moreover, insensitivity to drug-induced apoptosis, alteration, and mutation of drug target and interference/change of DNA replication are other main causes of treatment failure.

Cancer risk from chronic exposures to chemicals and radiation: a comparison of the toxicological reference value with the radiation detriment

This article aims at comparing reference methods for the assessment of cancer risk from exposure to genotoxic carcinogen chemical substances and to ionizing radiation. For chemicals, cancer potency is expressed as a toxicological reference value (TRV) based on the most sensitive type of cancer generally observed in animal experiments of oral or inhalation exposure. A dose-response curve is established by modelling experimental data adjusted to apply to human exposure. This leads to a point of departure from which the TRV is derived as the slope of a linear extrapolation to zero dose. Human lifetime cancer risk can then be assessed as the product of dose by TRV and it is generally considered to be tolerable in a 10^-6-10^-4 range for the public in a normal situation. Radiation exposure is assessed as an effective dose corresponding to a weighted average of energy deposition in body organs. Cancer risk models were derived from the epidemiological follow-up of atomic bombing survivors. Considering a linear-no-threshold dose-risk relationship and average baseline risks, lifetime nominal risk coefficients were established for 13 types of cancers. Those are adjusted according to the severity of each cancer type and combined into an overall indicator denominated radiation detriment. Exposure to radiation is subject to dose limits proscribing unacceptable health detriment. The differences between chemical and radiological cancer risk assessments are discussed and concern data sources, extrapolation to low doses, definition of dose, considered health effects and level of conservatism. These differences should not be an insuperable impediment to the comparison of TRVs with radiation risk, thus opportunities exist to bring closer the two types of risk assessment.

Risk of lung cancer due to external environmental factor and epidemiological data analysis

Lung cancer is a cancer with the fastest growth in the incidence and mortality all over the world, which is an extremely serious threat to human's life and health. Evidences reveal that external environmental factors are the key drivers of lung cancer, such as smoking, radiation exposure and so on. Therefore, it is urgent to explain the mechanism of lung cancer risk due to external environmental factors experimentally and theoretically. However, it is still an open issue regarding how external environment factors affect lung cancer risk. In this paper, we summarize the main mathematical models involved the gene mutations for cancers, and review the application of the models to analyze the mechanism of lung cancer and the risk of lung cancer due to external environmental exposure. In addition, we apply the model described and the epidemiological data to analyze the influence of external environmental factors on lung cancer risk. The result indicates that radiation can cause significantly an increase in the mutation rate of cells, in particular the mutation in stability gene that leads to genomic instability. These studies not only can offer insights into the relationship between external environmental factors and human lung cancer risk, but also can provide theoretical guidance for the prevention and control of lung cancer.

COHERE - strengthening cooperation within the Canadian government on radiation research

PURPOSE

Canadian Organization on Health Effects from Radiation Exposure (COHERE) is a government initiative to better understand biological and human health risks from ionizing radiation exposures relevant to occupational and environmental settings (<100 mGy, <6 mGy/h). It is currently a partnership between two federal agencies, Health Canada (HC) and the Canadian Nuclear Safety Commission (CNSC). COHERE's vision is to contribute knowledge to reduce scientific uncertainties from low dose and dose-rate exposures. COHERE will advance our understanding by bridging the knowledge gap between human health risks and linkages to molecular- and cellular-level responses to radiation. Research focuses on identifying sensitive, early, and key molecular events of relevance to risk assessment.

CONCLUSIONS

The initiative will address questions of relevance to better apprize Canadians, including radiation workers and members of the public and Indigenous peoples, on health risks from low dose radiation exposure and inform radiation protection frameworks at a national and international level. Furthermore, it will support global efforts to conduct collaborative undertakings and better coordinate research. Here, we describe a historical overview of the research conducted, the strategic research agenda that outlines the scientific framework, stakeholders, opportunities to harmonize internationally, and how research outcomes will better inform communication of risk to Canadians.

Simulating the dynamics of atherosclerosis to the incidence of myocardial infarction, applied to the KORA population

Analyzing epidemiological data with simplified mathematical models of disease development provides a link between the time-course of incidence and the underlying biological processes. Here we point out that considerable modeling flexibility is gained if the model is solved by simulation only. To this aim, a model of atherosclerosis is proposed: a Markov Chain with continuous state space which represents the coronary artery intimal surface area involved with atherosclerotic lesions of increasing severity. Myocardial infarction rates are assumed to be proportional to the area of most severe lesions. The model can be fitted simultaneously to infarction incidence rates observed in the KORA registry, and to the age-dependent prevalence and extent of atherosclerotic lesions in the PDAY study. Moreover, the simulation approach allows for non-linear transition rates, and to consider at the same time randomness and inter-individual heterogeneity. Interestingly, the fit revealed significant age dependence of parameters in females around the age of menopause, qualitatively reproducing the known vascular effects of female sex hormones. For males, the incidence curve flattens for higher ages. According to the model, frailty explains this flattening only partially, and saturation of the disease process plays also an important role. This study shows the feasibility of simulating subclinical and epidemiological data with the same mathematical model. The approach is very general and may be extended to investigate the effects of risk factors or interventions. Moreover, it offers an interface to integrate quantitative individual health data as assessed, for example, by imaging.

The role of mitochondrial oxidative stress and the tumor microenvironment in radiation-related cancer

The health risks associated with low-dose radiation, which are a major concern after the Fukushima Daiichi nuclear power plant accident (the Fukushima accident), have been extensively investigated, and the cancer risks from low-dose radiation exposure (below ~ 100 mSv) are thought to be negligible. According to World Health Organization and the United Nations Scientific Committee on the Effects of Atomic Radiation reports, the level of radiation exposure from the Fukushima accident is limited, estimating no significant increased risk from the accident. Radiation-induced cell injury is mainly caused by oxidative damage to biomolecules, including DNA, lipids and proteins. Radiation stimulates metabolic activation within the mitochondria to provide energy for the DNA damage response. Mitochondrial respiratory chain complexes I and III are the most important intracellular source of reactive oxygen species (ROS) during oxidative phosphorylation in eukaryotic cells. Manganese superoxide dismutase and glutathione are key players in redox control within cells. However, perturbation of the antioxidant response leads to chronic oxidative stress in irradiated cells. Excess ROS of mitochondrial origin is reported in cancer-associated fibroblast and promotes carcinogenesis. The aim of this review paper is to discuss critical roles of mitochondria in radiation-related cancer by introducing our recent studies. In particular, elevated mitochondrial ROS in stromal fibroblasts potentiate transforming growth factor-beta (TGF-β) signaling, which triggers smooth muscle actin (α-SMA) expression to stimulate myofibroblast differentiation. Radiation-induced myofibroblasts promote tumor growth by enhancing angiogenesis. Thus, radiation affects both malignant cancer cells and neighboring stromal cells through secretion of soluble factors.

In vitro Assessment of the DNA Damage Response in Dental Mesenchymal Stromal Cells Following Low Dose X-ray Exposure

Stem cells contained within the dental mesenchymal stromal cell (MSC) population are crucial for tissue homeostasis. Assuring their genomic stability is therefore essential. Exposure of stem cells to ionizing radiation (IR) is potentially detrimental for normal tissue homeostasis. Although it has been established that exposure to high doses of ionizing radiation (IR) has severe adverse effects on MSCs, knowledge about the impact of low doses of IR is lacking. Here we investigated the effect of low doses of X-irradiation with medical imaging beam settings (<0.1 Gray; 900 mGray per hour), in vitro, on pediatric dental mesenchymal stromal cells containing dental pulp stem cells from deciduous teeth, dental follicle progenitor cells and stem cells from the apical papilla. DNA double strand break (DSB) formation and repair kinetics were monitored by immunocytochemistry of γH2AX and 53BP1 as well as cell cycle progression by flow cytometry and cellular senescence by senescence-associated β-galactosidase assay and ELISA. Increased DNA DSB repair foci, after exposure to low doses of X-rays, were measured as early as 30 min post-irradiation. The number of DSBs returned to baseline levels 24 h after irradiation. Cell cycle analysis revealed marginal effects of IR on cell cycle progression, although a slight G₂/M phase arrest was seen in dental pulp stromal cells from deciduous teeth 72 h after irradiation. Despite this cell cycle arrest, no radiation-induced senescence was observed. In conclusion, low X-ray IR doses (< 0.1 Gray; 900 mGray per hour), were able to induce significant increases in the number of DNA DSBs repair foci, but cell cycle progression seems to be minimally affected. This highlights the need for more detailed and extensive studies on the effects of exposure to low IR doses on different mesenchymal stromal cells.

REVIEW OF QUANTITATIVE MECHANISTIC MODELS OF RADIATION-INDUCED NON-TARGETED EFFECTS (NTE)

Quantitative mechanistic modeling of the biological effects of ionizing radiation has a long rich history. Initially, it was dominated by target theory, which quantifies damage caused by traversal of cellular targets like DNA by ionizing tracks. The discovery that mutagenesis, death and/or altered behavior sometimes occur in cells that were not themselves traversed by any radiation tracks but merely interacted with traversed cells was initially seen as surprising. As more evidence of such 'non-targeted' or 'bystander' effects accumulated, the importance of their contribution to radiation-induced damage became more recognized. Understanding and modeling these processes is important for quantifying and predicting radiation-induced health risks. Here we review the variety of mechanistic mathematical models of nontargeted effects that emerged over the past 2-3 decades. This review is not intended to be exhaustive, but focuses on the main assumptions and approaches shared or distinct between models, and on identifying areas for future research.

Adverse outcome pathways, key events, and radiation risk assessment

The overall aim of this contribution to the 'Second Bill Morgan Memorial Special Issue' is to provide a high-level review of a recent report developed by a Committee for the National Council on Radiation Protection and Measurements (NCRP) titled 'Approaches for Integrating Information from Radiation Biology and Epidemiology to Enhance Low-Dose Health Risk Assessment'. It derives from previous NCRP Reports and Commentaries that provide the case for integrating data from radiation biology studies (available and proposed) with epidemiological studies (also available and proposed) to develop Biologically-Based Dose-Response (BBDR) models. In this review, it is proposed for such models to leverage the adverse outcome pathways (AOP) and key events (KE) approach for better characterizing radiation-induced cancers and circulatory disease (as the example for a noncancer outcome). The review discusses the current state of knowledge of mechanisms of carcinogenesis, with an emphasis on radiation-induced cancers, and a similar discussion for circulatory disease. The types of the various informative BBDR models are presented along with a proposed generalized BBDR model for cancer and a more speculative one for circulatory disease. The way forward is presented in a comprehensive discussion of the research needs to address the goal of enhancing health risk assessment of exposures to low doses of radiation. The use of an AOP/KE approach for developing a mechanistic framework for BBDR models of radiation-induced cancer and circulatory disease is considered to be a viable one based upon current knowledge of the mechanisms of formation of these adverse health outcomes and the available technical capabilities and computational advances. The way forward for enhancing low-dose radiation risk estimates will require there to be a tight integration of epidemiology data and radiation biology information to meet the goals of relevance and sensitivity of the adverse health outcomes required for overall health risk assessment at low doses and dose rates.

ProZES: the methodology and software tool for assessment of assigned share of radiation in probability of cancer occurrence

ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany.

Biologically-based modeling of radiation risk and biomarker prevalence for papillary thyroid cancer in Japanese a-bomb survivors 1958-2005

PURPOSE

Thyroid cancer of papillary histology (PTC) is the dominant type in radio-epidemiological cohorts established after nuclear accidents or warfare. Studies on post-Chernobyl PTC and on thyroid cancer in the life span study (LSS) of Japanese a-bomb survivors consistently revealed high radiation risk after exposure during childhood and adolescence. For post-Chernobyl risk assessment overexpression of the CLIP2 gene was proposed as molecular biomarker to separate radiogenic from sporadic PTC. Based on such binary marker a biologically-based risk model of PTC carcinogenesis has been developed for observational Chernobyl data. The model featured two independent molecular pathways of disease development, of which one was associated with radiation exposure. To gain credibility the concept for a mechanistic risk model must be based on general biological features which transcend findings in a single cohort. The purpose of the present study is therefore to demonstrate portability of the model concept by application to PTC incidence data in the LSS. By exploiting the molecular two-path concept we improve the determination of the probability of radiation causing cancer (POC).

MATERIALS AND METHODS

The current analysis uses thyroid cancer incidence data of the LSS with thyroid cancer diagnoses and papillary histology (n = 292) from the follow-up period between 1958 and 2005. Risk analysis was performed with both descriptive and biologically-based models.

RESULTS

Judged by goodness-of-fit all applied models described the data almost equally well. They yielded similar risk estimates in cohorts post-Chernobyl and LSS. The preferred mechanistic model was selected by biological plausibility. It reflected important features of an imperfect radiation marker which are not easily addressed by descriptive models. Precise model predictions of marker prevalence in strata of epidemiological covariables can be tested by molecular measurements. Application of the radiation-related molecular pathway from our preferred model in retrospective risk assessment decreases the threshold dose for 50% POC from 0.33 (95% confidence interval (CI) 0.18; 0.64) Gy to 0.04 (95% CI 0.01; 0.19) Gy for females and from 0.43 (95% CI 0.17; 1.84) Gy to 0.19 (95% CI 0.05; 1.00) Gy for males. These improvements are still not sufficient to separate radiation-induced from sporadic PTC cases at very low doses <0.015 Gy typical for the Fukushima accident.

CONCLUSIONS

Successful application of our preferred mechanistic model to LSS incidence data confirms and improves the biological two-path concept of radiation-induced PTC. Model predictions suggest further molecular validation studies to consolidate the basis of biologically-based risk estimation.

Dose limits for occupational exposure to ionising radiation and genotoxic carcinogens: a German perspective

This paper summarises the view of the German Commission on Radiological Protection ("Strahlenschutzkommission", SSK) on the rationale behind the currently valid dose limits and dose constraints for workers recommended by the International Commission on Radiological Protection (ICRP). The paper includes a discussion of the reasoning behind current dose limits followed by a discussion of the detriment used by ICRP as a measure for stochastic health effects. Studies on radiation-induced cancer are reviewed because this endpoint represents the most important contribution to detriment. Recent findings on radiation-induced circulatory disease that are currently not included in detriment calculation are also reviewed. It appeared that for detriment calculations the contribution of circulatory diseases plays only a secondary role, although the uncertainties involved in their risk estimates are considerable. These discussions are complemented by a review of the procedures currently in use in Germany, or in discussion elsewhere, to define limits for genotoxic carcinogens. To put these concepts in perspective, actual occupational radiation exposures are exemplified with data from Germany, for the year 2012, and regulations in Germany are compared to the recommendations issued by ICRP. Conclusions include, among others, considerations on radiation protection concepts currently in use and recommendations of the SSK on the limitation of annual effective dose and effective dose cumulated over a whole working life.

Quantification of DNA Double Strand Breaks and Oxidation Response in Children and Adults Undergoing Dental CBCT Scan

Assessing the possible biological effects of exposure to low doses of ionizing radiation (IR) is one of the prime challenges in radiation protection, especially in medical imaging. Today, radiobiological data on cone beam CT (CBCT) related biological effects are scarce. In children and adults, the induction of DNA double strand breaks (DSBs) in buccal mucosa cells and 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxo-dG) and antioxidant capacity in saliva samples after CBCT examination were examined. No DNA DSBs induction was observed in children nor adults. In children only, an increase in 8-oxo-dG levels was observed 30 minutes after CBCT. At the same time an increase in antioxidant capacity was observed in children, whereas a decrease was observed in adults. Our data indicate that children and adults react differently to IR doses associated with CBCT. Fully understanding these differences could lead to an optimal use of CBCT in different age categories as well as improved radiation protection guidelines.

Sensitivity analysis of parameters and methodological choices used in calculation of radiation detriment for solid cancer

Purpose: Radiation detriment is a concept used by the International Commission on Radiological Protection (ICRP) to quantify the harmful health effects of radiation exposure in humans. The current approach of radiation detriment calculation has been defined in ICRP Publication 103 in 2007. It is determined from lifetime risk of cancer and heritable effects for a composite reference population, taking into account the severity of the disease in terms of lethality, quality of life and years of life lost. Many parameters are used in the calculations and the variation of these parameters can have effects on the cancer detriment, which needs to be investigated.Materials and methods: In this paper, we conducted a sensitivity analysis for examining the impact of 12 different parameters or methodological choices on the calculation of solid cancer detriment, such as the lifetime risk calculation method, survival curve, dose and dose-rate effectiveness factor (DDREF), age-at-exposure, sex, reference population, risk transfer model, latency, attained age, lethality, minimum quality of life factor and relative cancer-free life lost. Sensitivity calculations have been performed systematically for each of 10 solid cancer sites, by changing each one of the parameters in turn.Results: This sensitivity analysis demonstrated a large impact on estimated detriment from DDREF, age-at-exposure, sex and lethality, a noticeable impact of risk transfer model associated to variation of baseline rates, and a limited impact of risk calculation method, survival curve, latency, attained age, quality of life and relative years of life lost.Conclusion: These results could have implications for radiation protection standards, and they should help define priorities for future research in the field of low radiation dose and dose rate research. The present sensitivity analysis is part of a global effort of ICRP to review the bases of radiation detriment calculation and assess potential evolutions to improve the radiation protection system.

Radiation Biology and Its Role in the Canadian Radiation Protection Framework

The linear no-threshold (linear-non-threshold) model is a dose-response model that has long served as the foundation of the international radiation protection framework, which includes the Canadian regulatory framework. Its purpose is to inform the choice of appropriate dose limits and subsequent as low as reasonably achievable requirements, social and economic factors taken into account. The linear no-threshold model assumes that the risk of developing cancer increases proportionately with increasing radiation dose. The linear no-threshold model has historically been applied by extrapolating the risk of cancer at high doses (>1,000 mSv) down to low doses in a linear manner. As the health effects of radiation exposure at low doses remain ambiguous, reducing uncertainties found in cancer risk dose-response models can be achieved through in vitro and animal-based studies. The purpose of this critical review is to analyze whether the linear no-threshold model is still applicable for use by modern nuclear regulators for radiation protection purposes, or if there is sufficient scientific evidence supporting an alternate model from which to derive regulatory dose limits.

History of radiation detriment and its calculation methodology used in ICRP Publication 103

Over the past decades, the International Commission on Radiological Protection (ICRP) has used radiation detriment, which is a multidimensional concept to quantify the overall harm to health from stochastic effects of low-level radiation exposure of different parts of the body. Each tissue-specific detriment is determined from the nominal tissue-specific risk coefficient, weighted by the severity of the disease in terms of lethality, impact on quality of life and years of life lost. Total detriment is the sum of the detriments for separate tissues and organs. Tissue weighting factors for the calculation of effective dose are based on relative contributions of each tissue to the total detriment. Calculating radiation detriment is a complex process that requires information from various sources and judgements on how to achieve calculations. As such, it is important to document its calculation methodology. To improve the traceability of calculations and form a solid basis for future recommendations, the ICRP Task Group 102 on detriment calculation methodology was established in 2016. As part of its mission, the history of radiation detriment was reviewed, and the process of detriment calculation was detailed. This article summarises that work, aiming to clarify the methodology of detriment calculation currently used by ICRP.

A biologically based mathematical model for spontaneous and ionizing radiation cataractogenesis

Cataracts have long been known, but a biomathematical model is still unavailable for cataratogenesis. There has been a renewed interest in ionizing radiation cataracts because the recent international recommendation of the reduced lens dose limit stimulated the discussion toward its regulatory implementation in various countries. Nevertheless, a relationship between radiation (dose and dose rate) and response (e.g., incidence, onset and progression) remains incompletely understood, raising the need for a risk-predictive mathematical model. We here report for the first time an in silico model for cataractogenesis. First, a simplified cell proliferation model was developed for human lens growth based on stem and progenitor cell proliferation as well as epithelial-fiber cell differentiation. Then, a model for spontaneous cataractogenesis was developed to reproduce the human data on a relationship between age and cataract incidence. Finally, a model for radiation cataractogenesis was developed that can reproduce the human data on a relationship between dose and cataract onset at various ages, which was further applied to estimate cataract incidence following chronic lifetime exposure. The model can serve as the foundation for further development of the risk-predictive model for cataractogenesis along with additional considerations of various biological mechanisms and epidemiological datasets.

Exposure-lag-response associations between lung cancer mortality and radon exposure in German uranium miners

Exposure-lag-response associations shed light on the duration of pathogenesis for radiation-induced diseases. To investigate such relations for lung cancer mortality in the German uranium miners of the Wismut company, we apply distributed lag non-linear models (DLNMs) which offer a flexible description of the lagged risk response to protracted radon exposure. Exposure-lag functions are implemented with B-Splines in Cox models of proportional hazards. The DLNM approach yielded good agreement of exposure-lag-response surfaces for the German cohort and for the previously studied cohort of American Colorado miners. For both cohorts, a minimum lag of about 2 year for the onset of risk after first exposure explained the data well, but possibly with large uncertainty. Risk estimates from DLNMs were directly compared with estimates from both standard radio-epidemiological models and biologically based mechanistic models. For age > 45 year, all models predict decreasing estimates of the Excess Relative Risk (ERR). However, at younger age, marked differences appear as DLNMs exhibit ERR peaks, which are not detected by the other models. After comparing exposure-responses for biological processes in mechanistic risk models with exposure-responses for hazard ratios in DLNMs, we propose a typical period of 15 year for radon-related lung carcinogenesis. The period covers the onset of radiation-induced inflammation of lung tissue until cancer death. The DLNM framework provides a view on age-risk patterns supplemental to the standard radio-epidemiological approach and to biologically based modeling.

Enhancing low-dose risk assessment using mechanistic mathematical models of radiation effects

Mechanistic mathematical modeling of ionizing radiation (IR) effects has a long history spanning several decades. Models that mathematically represent current knowledge and hypotheses about how radiation damages cells and organs, leading to deleterious outcomes such as carcinogenesis, are particularly useful for estimating radiation risks at doses that are relevant for radiation protection, but are too low to provide a strong 'signal-to-noise ratio' in epidemiological or experimental studies with realistic sample sizes. Here, I discuss examples of models in several relevant areas, including radionuclide biokinetics, non-targeted IR effects, DNA double-strand break (DSB) rejoining and radiation carcinogenesis. I do not provide a detailed review of the vast modeling literature in these fields, but focus on concepts that we have implemented, such as using continuous probability distributions of exponential rates to model radionuclide biokinetics and DSB rejoining, and combining short and long time scales in carcinogenesis models. Improvements in models, including the ability to generate new hypotheses based on model predictions, may come from the introduction of additional novel concepts and from integrating multiple data types.

Radiation epidemiology and health effects following low-level radiation exposure

Radiation epidemiology is the study of human disease following radiation exposure to populations. Epidemiologic studies of radiation-exposed populations have been conducted for nearly 100 years, starting with the radium dial painters in the 1920s and most recently with large-scale studies of radiation workers. As radiation epidemiology has become increasingly sophisticated it is used for setting radiation protection standards as well as to guide the compensation programmes in place for nuclear weapons workers, nuclear weapons test participants, and other occupationally exposed workers in the United States and elsewhere. It is known with high assurance that radiation effects at levels above 100-150 mGy can be detected as evidenced in multiple population studies conducted around the world. The challenge for radiation epidemiology is evaluating the effects at low doses, below about 100 mGy of low-linear energy transfer radiation, and assessing the risks following low dose-rate exposures over years. The weakness of radiation epidemiology in directly studying low dose and low dose-rate exposures is that the signal, i.e. the excess numbers of cancers associated with low-level radiation exposure, is so very small that it cannot be seen against the very high background occurrence of cancer in the population, i.e. a lifetime risk of incidence reaching up to about 38% (i.e. 1 in 3 persons will develop a cancer in their lifetime). Thus, extrapolation models are used for the management of risk at low doses and low dose rates, but having adequate information from low dose and low dose-rate studies would be highly desirable. An overview of recently conducted radiation epidemiologic studies which evaluate risk following low-level radiation exposures is presented. Future improvements in risk assessment for radiation protection may come from increasingly informative epidemiologic studies, combined with mechanistic radiobiologic understanding of adverse outcome pathways, with both incorporated into biologically based models.

Formation of γH2AX and pATM Foci in Human Mesenchymal Stem Cells Exposed to Low Dose-Rate Gamma-Radiation

DNA double-strand breaks (DSB) are among the most harmful DNA lesions induced by ionizing radiation (IR). Although the induction and repair of radiation-induced DSB is well studied for acute irradiation, responses to DSB produced by chronic IR exposures are poorly understood, especially in human stem cells. The aim of this study was to examine the formation of DSB markers (γH2AX and phosphorylated kinase ATM, pATM, foci) in human mesenchymal stem cells (MSCs) exposed to chronic gamma-radiation (0.1 mGy/min) in comparison with acute irradiation (30 mGy/min) at cumulative doses of 30, 100, 160, 240 and 300 mGy. A linear dose-dependent increase in the number of both γH2AX and pATM foci, as well as co-localized γH2AX/pATM foci ("true" DSB), were observed after an acute radiation exposure. In contrast, the response of MSCs to a chronic low dose-rate IR exposure deviated from linearity towards a threshold model, for γH2AX, pATM foci and γH2AX/pATM foci, with an indication of a "plateau". The state of equilibrium between newly formed DSB at a low rate during the protracted exposure time and the elimination of a fraction of DSB is proposed as a mechanistic explanation of the non-linear DSB responses following a low dose-rate irradiation. This notion is supported by the observation of the elimination of a substantial fraction of DSB 6 h after the cessation of the exposures. Our results demonstrate non-linear dose responses for γH2AX and pATM foci in human MSCs exposed to low dose-rate IR and showed the existence of a threshold, which may have implications for radiation protection in humans.

MECHANISTIC MODELING PREDICTS ANTI-CARCINOGENIC RADIATION EFFECTS ON INTERCELLULAR SIGNALING IN VITRO TURN PRO-CARCINOGENIC IN VIVO

Oncogenic transformed cells represent an in vitro system mimicking early-stage carcinogenesis. These precancerous cells are subject to a selective removal via apoptosis induced by neighbor cells. By modulating the underpinning intercellular signaling mediated by cytokines and reactive oxygen/nitrogen species, ionizing radiation enhances this removal of precancerous cells in vitro, at doses from a few mGy to a few Gy. However, epidemiological data demonstrate that radiation exposure induces cancer, at least above 100 mGy. Mechanistic modeling of the given anti-carcinogenic process explains this discrepancy: The model reproduces in vitro data on apoptosis and its enhancement by radiation. For in vivo-like conditions with signal lifetimes shorter and cell densities higher than in vitro, radiation is predicted to reduce this anti-carcinogenic mechanism. Early-stage lesions that would be turned dormant or completely removed may grow large and escape this control mechanism upon irradiation.

Mechanistic Modelling of Radiation Responses

Radiobiological modelling has been a key part of radiation biology and therapy for many decades, and many aspects of clinical practice are guided by tools such as the linear-quadratic model. However, most of the models in regular clinical use are abstract and empirical, and do not provide significant scope for mechanistic interpretation or making predictions in novel cell lines or therapies. In this review, we will discuss the key areas of ongoing mechanistic research in radiation biology, including physical, chemical, and biological steps, and review a range of mechanistic modelling approaches which are being applied in each area, highlighting the possible opportunities and challenges presented by these techniques.

Is there a role for the adverse outcome pathway framework to support radiation protection?

PURPOSE

In 2012, the Organization for Economic Cooperation and Development (OECD) formally launched the Adverse Outcome Pathway (AOP) Programme. The AOP framework has the potential for predictive utility in identifying early biological endpoints linked to adverse effects. It uses the weight of correlative evidence to identify a minimal set of measurable key events that link molecular initiating events to an adverse outcome. AOPs have the capability to identify knowledge gaps and priority areas for future research based on relevance to an adverse outcome. In addition, AOPs can identify pathways that are common among multiple stressors, thereby allowing for the possibility of refined risk assessments based on co-exposure considerations. The AOP framework is increasingly being used in chemical and ecological risk assessment; however, its use in the development of radiation-specific pathways has yet to be fully explored. To bring awareness of the AOP framework to the Canadian radiation community, a workshop was held in Canada in June 2018 that brought together radiation experts from Health Canada, the Canadian Nuclear Laboratories, and the Canadian Nuclear Safety Commission.

METHODS

The purpose of the workshop was to share knowledge on the AOP framework, specifically (1) to introduce the concept of the AOP framework and its possible utility to Canadian radiation experts; (2) to provide examples on how it has advanced risk assessment; (3) to discuss an illustrative example specific to ionizing radiation; and lastly (4) to identify the broad benefits and challenges of the AOP framework to the radiation community.

RESULTS

The participants showed interest in the framework, case examples were described and areas of challenge were identified. Herein, we summarize the outcomes of the workshop.

CONCLUSIONS

Overall, participants agreed that by building AOPs in the radiation field, a network of data-sharing initiatives will enhance our interpretation of existing knowledge where current scientific evidence is minimal. They would provide new avenues to understand effects at low-dose and dose-rates and help to quantify the combined effect of multiple stressors on shared mechanistic pathways.

Implications of recent epidemiologic studies for the linear nonthreshold model and radiation protection

The recently published NCRP Commentary No. 27 evaluated the new information from epidemiologic studies as to their degree of support for applying the linear nonthreshold (LNT) model of carcinogenic effects for radiation protection purposes (NCRP 2018 Implications of Recent Epidemiologic Studies for the Linear Nonthreshold Model and Radiation Protection, Commentary No. 27 (Bethesda, MD: National Council on Radiation Protection and Measurements)). The aim was to determine whether recent epidemiologic studies of low-LET radiation, particularly those at low doses and/or low dose rates (LD/LDR), broadly support the LNT model of carcinogenic risk or, on the contrary, demonstrate sufficient evidence that the LNT model is inappropriate for the purposes of radiation protection. An updated review was needed because a considerable number of reports of radiation epidemiologic studies based on new or updated data have been published since other major reviews were conducted by national and international scientific committees. The Commentary provides a critical review of the LD/LDR studies that are most directly applicable to current occupational, environmental and medical radiation exposure circumstances. This Memorandum summarises several of the more important LD/LDR studies that incorporate radiation dose responses for solid cancer and leukemia that were reviewed in Commentary No. 27. In addition, an overview is provided of radiation studies of breast and thyroid cancers, and cancer after childhood exposures. Non-cancers are briefly touched upon such as ischemic heart disease, cataracts, and heritable genetic effects. To assess the applicability and utility of the LNT model for radiation protection, the Commentary evaluated 29 epidemiologic studies or groups of studies, primarily of total solid cancer, in terms of strengths and weaknesses in their epidemiologic methods, dosimetry approaches, and statistical modelling, and the degree to which they supported a LNT model for continued use in radiation protection. Recommendations for how to make epidemiologic radiation studies more informative are outlined. The NCRP Committee recognises that the risks from LD/LDR exposures are small and uncertain. The Committee judged that the available epidemiologic data were broadly supportive of the LNT model and that at this time no alternative dose-response relationship appears more pragmatic or prudent for radiation protection purposes.

The Past Informs the Future: An Overview of the Million Worker Study and the Mallinckrodt Chemical Works Cohort

The purpose of this paper is to present an overview of ongoing work on the Million Worker Study (MWS), highlighting some of the key methods and progress so far as exemplified by the study of workers at the Mallinckrodt Chemical Works (MCW). The MWS began nearly 25 y ago and continues in a stepwise fashion, evaluating one study cohort at a time. It includes workers from U.S. Department of Energy (DOE) Manhattan Project facilities, U.S. Nuclear Regulatory Commission (NRC) regulated nuclear power plants, industrial radiographers, U.S. Department of Defense (DoD) nuclear weapons test participants, and physicians and technologists working with medical radiation. The purpose is to fill the major gap in radiation protection and science: What is the risk when exposure is received gradually over time rather than briefly as for the atomic bomb survivors? Studies published or planned in 2018 include leukemia (and dosimetry) among atomic veterans, leukemia among nuclear power plant workers, mortality among workers at the MCW, and a comprehensive National Council on Radiation Protection and Measurements (NCRP) Report on dosimetry for the MWS. MCW has a singular place in history: the 40 tons (T) of uranium oxide produced at MCW were used by Enrico Fermi on 2 December 1942 to produce the first manmade sustained and controlled nuclear reaction, and the atomic age was born. Seventy-six years later, the authors followed the over 2,500 MCW workers for mortality and reconstructed dose from six sources of exposure: external gamma rays from the radioactive elements in pitchblende; medical x rays from occupationally required chest examinations; intakes of pitchblende (uranium, radium, and silica) measured by urine samples; radon breath analyses and dust surveys overseen by Robley Evans and Merril Eisenbud; occupational exposures received before and after employment at MCW; and cumulative radon concentrations and lung dose from the decay of radium in the work environment. The unique exposure reconstructions allow for multiple evaluations, including estimates of silica dust. The study results are relevant today. For example, NASA is interested that radium, deposited in the brain, releases high-LET alpha particles - the only human analogue, though limited, for high energy, high-Z particles (galactic cosmic rays) traveling through space that might affect astronauts on Mars missions. Don't discount the past; it's the prologue to the future!

Typical doses and dose rates in studies pertinent to radiation risk inference at low doses and low dose rates

In order to quantify radiation risks at exposure scenarios relevant for radiation protection, often extrapolation of data obtained at high doses and high dose rates down to low doses and low dose rates is needed. Task Group TG91 on 'Radiation Risk Inference at Low-dose and Low-dose Rate Exposure for Radiological Protection Purposes' of the International Commission on Radiological Protection is currently reviewing the relevant cellular, animal and human studies that could be used for that purpose. This paper provides an overview of dose rates and doses typically used or present in those studies, and compares them with doses and dose rates typical of those received by the A-bomb survivors in Japan.

NCRP Vision for the Future and Program Area Committee Activities in 2017

The National Council on Radiation Protection and Measurements' (NCRP) vision for the future is to improve radiation protection for the general public and workers. This vision is embodied within NCRP's ongoing initiatives: preparedness for nuclear terrorism, increasing the number of radiation professionals critically needed for the nation, providing new guidance for radiation protection in the United States, addressing the protection issues surrounding the ever-increasing use of ionizing radiation in medicine, assessing the radiation doses to aircrew due to higher altitude and longer flights, providing guidance on emerging radiation issues such as the radioactive waste from hydraulic fracturing, focusing on difficult issues such as high-level waste management, and providing better estimates of radiation risks at low doses within the framework of the Million Person Study of Low Dose Radiation Health Effects. Cutting-edge initiatives include a re-evaluation of the science behind recommendations for lens of the eye dose, recommendations for emergency responders on dosimetry after a major radiological incident, guidance to the National Aeronautics and Space Administration with regard to possible central nervous system effects from galactic cosmic rays (the high-energy, high-mass particles bounding through space), re-evaluating the population exposure to medical radiation, and addressing whether the linear non-threshold model is still the best available for purposes of radiation protection (not for risk assessment). To address these initiatives and goals, NCRP has seven Program Area Committees on biology and epidemiology, operational concerns, emergency response and preparedness, medicine, environmental issues and waste management, dosimetry, and communications. The NCRP vision for the future received a quantum boost in 2016 when Dr. Kathryn D. Held (Massachusetts General Hospital and Harvard Medical School) accepted the position of NCRP Executive Director and Chief Science Officer. The NCRP quest to improve radiation protection for the public is hindered only by limited resources, both human capital and financial.