The effect of dose rate on the frequency of specific-locus mutations induced in mouse spermatogonia is restricted to larger lesions; a retrospective analysis of historical data

How self-interest and deception led to the adoption of the linear non-threshold dose response (LNT) model for cancer risk assessment

This paper clarifies scientific contributions and deceptive/self-serving decisions of William L. Russell and Liane Russell that led to the adoption of the linear non-threshold (LNT) model for cancer risk assessment by the US EPA. By deliberately failing to report an extremely large cluster of mutations in the control group of their first experiment, and thereby greatly suppressing its mutation rate, the Russells incorrectly claimed that the male mouse was 15-fold more susceptible to ionizing-radiation-induced gene mutations as compared with fruit flies. This self-serving error not only propelled their research program into one of great prominence, but it also promoted the LNT-based doubling dose (DD) concept in radiation genetics/cancer risk assessment, by the US National Academy of Sciences (NAS) Biological Effects of Atomic Radiation (BEAR) I Genetics Panel (1956). The DD concept became a central element in their recommendation that regulatory agencies switch from a threshold to an LNT model. This error occurred because of a decision by W. Russell not to report that a large cluster of control group mutations found in an experiment for which preliminary results were reported in 1951. This failure to report that cluster and similar clusters continued throughout the careers of the Russells, resulting in massive overestimation of low dose radiation risks supporting the LNT. The Russell database and the repeated claim that those data show that there is no threshold dose rate for mutation in irradiated mouse stem-cell spermatogonia, have provided mechanistic validation supporting the epidemiological LNT hypothesis for radiation-induced leukemias and cancers. This reanalysis supports the threshold model for both males and females, thereby rebutting epidemiological extrapolations from the NAS and EPA claiming support for the LNT hypothesis for cancer risk assessment. The implications of the Russell errors/deceptions, how/why they occurred, and their impact upon society are enormous and need to be addressed by scientific/regulatory agencies, affecting regulatory and litigation activities.

Increased Frequency of Copy Number Variations Revealed by Array Comparative Genomic Hybridization in the Offspring of Male Mice Exposed to Low Dose-Rate Ionizing Radiation

There is very little information on the transgenerational or genetic effects of low dose-rate ionizing radiation. We report the detection of the transgenerational effects of chronic low dose-rate irradiation in mice, at the molecular level in the whole genome, using array comparative genomic hybridization technology. We observed that the number of the mice with de novo copy number variations (specifically, deletions) was significantly increased in the offspring of C57BL/6J male mice exposed to 20 mGy/day gamma-rays for 400 days (total dose: 8000 mGy), as compared to non-irradiated controls. We did not detect any difference in the size of the de novo deletions between the irradiated and the non-irradiated groups. An analysis of the life span of the offspring suggested a possibility that de novo copy-number variations may be associated with shorter life spans.

Destabilizing Effects of Ionizing Radiation on Chromosomes: Sizing up the Damage

For long-term survival and evolution, all organisms have depended on a delicate balance between processes involved in maintaining stability of their genomes and opposing processes that lead toward destabilization. At the level of mammalian somatic cells in renewal tissues, events or conditions that can tip this balance toward instability have attracted special interest in connection with carcinogenesis. Mutations affecting DNA (and its subsequent repair) would, of course, be a major consideration here. These may occur spontaneously through endogenous cellular processes or as a result of exposure to mutagenic environmental agents. It is in this context that we discuss the rather unique destabilizing effects of ionizing radiation (IR) in terms of its ability to cause large-scale structural rearrangements to the genome. We present arguments supporting the conclusion that these and other important effects of IR originate largely from microscopically visible chromosome aberrations.

Induction of somatic mutations by low concentrations of tritiated water (HTO): evidence for the possible existence of a dose-rate threshold

Tritium is a low energy beta emitter and is discharged into the aquatic environment primarily in the form of tritiated water (HTO) from nuclear power plants or from nuclear fuel reprocessing plants. Although the biological effects of HTO exposures at significant doses or dose rates have been extensively studied, there are few reports concerning the biological effects of HTO exposures at very low dose rates. In the present study using a hyper-sensitive assay system, we investigated the dose rate effect of HTO on the induction of mutations. Confluent cell populations were exposed to HTO for a total dose of 0.2 Gy at dose rates between 4.9 mGy/day and 192 mGy/day by incubating cells in medium containing HTO. HTO-induced mutant frequencies and mutation spectra were then investigated. A significant inflection point for both the mutant frequency and mutation spectra was found between 11 mGy/day and 21.6 mGy/day. Mutation spectra analysis revealed that a mechanistic change in the nature of the mutation events occurred around 11 mGy/day. The present observations and published experimental results from oral administrations of HTO to mice suggest that a threshold dose-rate for HTO exposures might exist between 11 mGy/day and 21.6 mGy/day where the nature of the mutation events induced by HTO becomes similar to those seen in spontaneous events.

The impact of dose rate on the linear no threshold hypothesis

The goal of this manuscript is to define the role of dose rate and dose protraction on the induction of biological changes at all levels of biological organization. Both total dose and the time frame over which it is delivered are important as the body has great capacity to repair all types of biological damage. The importance of dose rate has been recognized almost from the time that radiation was discovered and has been included in radiation standards as a Dose, Dose Rate, Effectiveness Factor (DDREF) and a Dose Rate Effectiveness Factor (DREF). This manuscript will evaluate the role of dose rate at the molecular, cellular, tissue, experimental animals and humans to demonstrate that dose rate is an important variable in estimating radiation cancer risk and other biological effects. The impact of low-dose rates on the Linear-No-Threshold Hypothesis (LNTH) will be reviewed since if the LNTH is not valid it is not possible to calculate a single value for a DDREF or DREF. Finally, extensive human experience is briefly reviewed to show that the radiation risks are not underestimated and that radiation at environmental levels has limited impact on total human cancer risk.

The linear No-Threshold (LNT) dose response model: A comprehensive assessment of its historical and scientific foundations

The linear no-threshold (LNT) single-hit (SH) dose response model for cancer risk assessment is comprehensively assessed with respect to its historical foundations. This paper also examines how mistakes, ideological biases, and scientific misconduct by key scientists affected the acceptance, validity, and applications of the LNT model for cancer risk assessment. In addition, the analysis demonstrates that the LNT single-hit model was inappropriately adopted for governmental risk assessment, regulatory policy, practices, and for risk communication.

From Muller to mechanism: How LNT became the default model for cancer risk assessment

This paper summarizes the historical and scientific foundations of the Linear No-Threshold (LNT) cancer risk assessment model. The story of cancer risk assessment is an extraordinary one as it was based on an initial incorrect gene mutation interpretation of Muller, the application of this incorrect assumption in the derivation of the LNT single-hit model, and a series of actions by leading radiation geneticists during the 1946-1956 period, including a National Academy of Sciences (NAS) Biological Effects of Atomic Radiation (BEAR) I Genetics Panel (Anonymous, 1956), to sustain the LNT belief via a series of deliberate obfuscations, deceptions and misrepresentations that provided the basis of modern cancer risk assessment policy and practices. The reaffirming of the LNT model by a subsequent and highly influential NAS Biological Effects of Ionizing Radiation (BEIR) I Committee (NAS/NRC, 1972) using mouse data has now been found to be inappropriate based on the discovery of a significant documented error in the historical control group that led to incorrect estimations of risk in the low dose zone. Correction of this error by the original scientists and the application of the adjusted/corrected data back to the BEIR I (NAS/NRC, 1972) report indicates that the data would have supported a threshold rather than the LNT model. Thus, cancer risk assessment has a poorly appreciated, complex and seriously flawed history that has undermined policies and practices of regulatory agencies in the U.S. and worldwide to the present time.

Induction of somatic mutations by low-dose X-rays: the challenge in recognizing radiation-induced events

It is difficult to distinguish radiation-induced events from spontaneous events during induction of stochastic effects, especially in the case of low-dose or low-dose-rate exposures. By using a hypersensitive system for detecting somatic mutations at the HPRT1 locus, we investigated the frequency and spectrum of mutations induced by low-dose X-rays. The mutant frequencies induced by doses of >0.15 Gy were statistically significant when compared with the spontaneous frequency, and a clear dose dependency was also observed for mutant frequencies at doses of >0.15 Gy. In contrast, mutant frequencies at doses of <0.1 Gy occurred at non-significant levels. The mutation spectrum in HPRT-deficient mutants revealed that the type of mutations induced by low-dose exposures was similar to that seen in spontaneous mutants. An apparent change in mutation type was observed for mutants induced by doses of >0.2 Gy. Our observations suggest that there could be a critical dose for mutation induction at between 0.1 Gy and 0.2 Gy, where mutagenic events are induced by multiple DNA double-strand breaks (DSBs). These observations also suggest that low-dose radiation delivered at doses of <0.1 Gy may not result in DSB-induced mutations but may enhance spontaneous mutagenesis events.

Flaws in the LNT single-hit model for cancer risk: An historical assessment

The LNT single-hit model was derived from the Nobel Prize-winning research of Herman J. Muller who showed that x-rays could induce gene mutations in Drosophila and that the dose response for these so-called mutational events was linear. Lewis J. Stadler, another well-known and respected geneticist at the time, strongly disagreed with and challenged Muller's claims. Detailed evaluations by Stadler over a prolonged series of investigations revealed that Muller's experiments had induced gross heritable chromosomal damage instead of specific gene mutations as had been claimed by Muller at his Nobel Lecture. These X-ray-induced alterations became progressively more frequent and were of larger magnitude (more destructive) with increasing doses. Thus, Muller's claim of having induced discrete gene mutations represented a substantial speculative overreach and was, in fact, without proof. The post hoc arguments of Muller to support his gene mutation hypothesis were significantly challenged and weakened by a series of new findings in the areas of cytogenetics, reverse mutation, adaptive and repair processes, and modern molecular methods for estimating induced genetic damage. These findings represented critical and substantial limitations to Muller's hypothesis of X-ray-induced gene mutations. Furthermore, they challenged the scientific foundations used in support of the LNT single-hit model by severing the logical nexus between Muller's data on radiation-induced inheritable alterations and the LNT single-hit model. These findings exposed fundamental scientific flaws that undermined not only the seminal recommendation of the 1956 BEAR I Genetics Panel to adopt the LNT single-hit Model for risk assessment but also any rationale for its continued use in the present day.

The role of dose rate in radiation cancer risk: evaluating the effect of dose rate at the molecular, cellular and tissue levels using key events in critical pathways following exposure to low LET radiation

PURPOSE

This review evaluates the role of dose rate on cell and molecular responses. It focuses on the influence of dose rate on key events in critical pathways in the development of cancer. This approach is similar to that used by the U.S. EPA and others to evaluate risk from chemicals. It provides a mechanistic method to account for the influence of the dose rate from low-LET radiation, especially in the low-dose region on cancer risk assessment. Molecular, cellular, and tissues changes are observed in many key events and change as a function of dose rate. The magnitude and direction of change can be used to help establish an appropriate dose rate effectiveness factor (DREF).

CONCLUSIONS

Extensive data on key events suggest that exposure to low dose-rates are less effective in producing changes than high dose rates. Most of these data at the molecular and cellular level support a large (2-30) DREF. In addition, some evidence suggests that doses delivered at a low dose rate decrease damage to levels below that observed in the controls. However, there are some data human and mechanistic data that support a dose-rate effectiveness factor of 1. In summary, a review of the available molecular, cellular and tissue data indicates that not only is dose rate an important variable in understanding radiation risk but it also supports the selection of a DREF greater than one as currently recommended by ICRP ( 2007 ) and BEIR VII (NRC/NAS 2006 ).

Evaluating biomarkers to model cancer risk post cosmic ray exposure

Robust predictive models are essential to manage the risk of radiation-induced carcinogenesis. Chronic exposure to cosmic rays in the context of the complex deep space environment may place astronauts at high cancer risk. To estimate this risk, it is critical to understand how radiation-induced cellular stress impacts cell fate decisions and how this in turn alters the risk of carcinogenesis. Exposure to the heavy ion component of cosmic rays triggers a multitude of cellular changes, depending on the rate of exposure, the type of damage incurred and individual susceptibility. Heterogeneity in dose, dose rate, radiation quality, energy and particle flux contribute to the complexity of risk assessment. To unravel the impact of each of these factors, it is critical to identify sensitive biomarkers that can serve as inputs for robust modeling of individual risk of cancer or other long-term health consequences of exposure. Limitations in sensitivity of biomarkers to dose and dose rate, and the complexity of longitudinal monitoring, are some of the factors that increase uncertainties in the output from risk prediction models. Here, we critically evaluate candidate early and late biomarkers of radiation exposure and discuss their usefulness in predicting cell fate decisions. Some of the biomarkers we have reviewed include complex clustered DNA damage, persistent DNA repair foci, reactive oxygen species, chromosome aberrations and inflammation. Other biomarkers discussed, often assayed for at longer points post exposure, include mutations, chromosome aberrations, reactive oxygen species and telomere length changes. We discuss the relationship of biomarkers to different potential cell fates, including proliferation, apoptosis, senescence, and loss of stemness, which can propagate genomic instability and alter tissue composition and the underlying mRNA signatures that contribute to cell fate decisions. Our goal is to highlight factors that are important in choosing biomarkers and to evaluate the potential for biomarkers to inform models of post exposure cancer risk. Because cellular stress response pathways to space radiation and environmental carcinogens share common nodes, biomarker-driven risk models may be broadly applicable for estimating risks for other carcinogens.