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

Radiation Adverse Outcome pathways (AOPs): examining priority questions from an international horizon-style exercise

PURPOSE

The Organisation for Economic Co-operation and Development (OECD) Adverse Outcome Pathway (AOP) Development Programme is being explored in the radiation field, as an overarching framework to identify and prioritize research needs that best support strengthening of radiation risk assessment and risk management strategies. To advance the use of AOPs, an international horizon-style exercise (HSE) was initiated through the Radiation/Chemical AOP Joint Topical Group (JTG) formed by the OECD Nuclear Energy Agency (NEA) High-Level Group on Low Dose Research (HLG-LDR) under the auspices of the Committee on Radiological Protection and Public Health (CRPPH). The intent of the HSE was to identify key research questions for consideration in AOP development that would help to reduce uncertainties in estimating the health risks following exposures to low dose and low dose-rate ionizing radiation. The HSE was conducted in several phases involving the solicitation of relevant questions, a collaborative review of open-ended candidate questions and an elimination exercise that led to the selection of 25 highest priority questions for the stated purpose. These questions were further ranked by over 100 respondents through an international survey. This final set of questions was judged to provide insights into how the OECD's AOP approach can be put into practice to meet the needs of hazard and risk assessors, regulators, and researchers. This paper examines the 25 priority questions in the context of hazard/risk assessment framework for ionizing radiation.

CONCLUSION

By addressing the 25 priority questions, it is anticipated that constructed AOPs will have a high level of specificity, making them valuable tools for simplifying and prioritizing complex biological processes for use in developing revised radiation hazard and risk assessment strategies.

Factors Influencing Effects of Low-dose Radiation Exposure

ABSTRACT

It is now well accepted that the mechanisms induced by low-dose exposures to ionizing radiation (LDR) are different from those occurring after high-dose exposures. However, the downstream effects of these mechanisms are unclear as are the quantitative relationships between exposure, effect, harm, and risk. In this paper, we will discuss the mechanisms known to be important with an overall emphasis on how so-called "non-targeted effects" (NTE) communicate and coordinate responses to LDR. Targeted deposition of ionizing radiation energy in cells causing DNA damage is still regarded as the dominant trigger leading to all downstream events whether targeted or non-targeted. We regard this as an over-simplification dating back to formal target theory. It ignores that last 100 y of biological research into stress responses and signaling mechanisms in organisms exposed to toxic substances, including ionizing radiation. We will provide evidence for situations where energy deposition in cellular targets alone cannot be plausible as a mechanism for LDR effects. An example is where the energy deposition takes place in an organism not receiving the radiation dose. We will also discuss how effects after LDR depend more on dose rate and radiation quality rather than actual dose, which appears rather irrelevant. Finally, we will use recent evidence from studies of cataract and melanoma induction to suggest that after LDR, post-translational effects, such as protein misfolding or defects in energy metabolism or mitochondrial function, may dominate the etiology and progression of the disease. A focus on such novel pathways may open the way to successful prophylaxis and development of new biomarkers for better risk assessment after low dose exposures.

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.

Mathematical modeling the gene mechanism of colorectal cancer and the effect of radiation exposure

Cancer is the result of continuous accumulation of gene mutations in normal cells. The number of mutations is different in different types of cancer and even in different patients with the same type of cancer. Therefore, studying all possible numbers of gene mutations in malignant cells is of great value for the understanding of tumorigenesis and the treatment of cancer. To this end, we applied a stochastic mathematical model considering the clonal expansion of any premalignant cells with different mutations to analyze the number of gene mutations in colorectal cancer. The age-specific colorectal cancer incidence rates from the Surveillance, Epidemiology and End Results (SEER) registry in the United States and the Life Span Study (LSS) in Nagasaki and Hiroshima, Japan are chosen to test the reasonableness of the model. Our fitting results indicate that the transformation from normal cells to malignant cells may undergo two to five driver mutations for colorectal cancer patients without radiation-exposed environment, two to four driver mutations for colorectal cancer patients with low level radiation-exposure, and two to three driver mutations for colorectal cancer patients with high level radiation-exposure. Furthermore, the net growth rate of the mutated cells with radiation-exposure was is higher than that of the mutated cells without radiation-exposure for the models with two to five driver mutations. These results suggest that radiation environment may affect the clonal expansion of cells and significantly affect the development of tumors.