A computational model for radiation-induced cellular transformation to in vitro irradiation of cells by acute doses of X-rays.

This research incorporates new biological concepts to improve the predictive ability of a state-vector model with respect to dose-response data on in vitro oncogenic transformation, including mechanisms of DNA damage, DNA repair, cell death, cell proliferation and intercellular communication. Experimentally recognized biological processes, including background transformation, compensatory proliferation and bystander cell-killing effect were formulated mathematically and included as model parameters. These were then adjusted with an optimization method to reproduce in vitro transformation frequency data from C3H10T1/2 mouse cells exposed to acute doses of X-rays. A plateau observed in the data at low doses is reproduced well and a dose-dependent increase above 1 Gy is predicted almost precisely. Extension of the model predictions to the dose range 0-100 mGy indicates that transformation frequencies are practically constant over this low dose region. Results suggest a protective, rather than detrimental, bystander cell-killing effect. Further analysis of model sensitivity to this bystander parameter, though, revealed uncertainties with respect to its biological plausibility in the model.

Detrimental and protective bystander effects: a model approach.

This work integrates two important cellular responses to low doses, detrimental bystander effects and apoptosis-mediated protective bystander effects, into a multistage model for chromosome aberrations and in vitro neoplastic transformation: the State-Vector Model. The new models were tested on representative data sets that show supralinear or U-shaped dose responses. The original model without the new low-dose features was also tested for consistency with LNT-shaped dose responses. Reductions of in vitro neoplastic transformation frequencies below the spontaneous level have been reported after exposure of cells to low doses of low-LET radiation. In the current study, this protective effect is explained with bystander-induced apoptosis. An important data set that shows a low-dose detrimental bystander effect for chromosome aberrations was successfully fitted by additional terms within the cell initiation stage. It was found that this approach is equivalent to bystander-induced clonal expansion of initiated cells. This study is an important step toward a comprehensive model that contains all essential biological mechanisms that can influence dose-response curves at low doses.

A model for the induction of chromosome aberrations through direct and bystander mechanisms.

A state vector model (SVM) for chromosome aberrations and neoplastic transformation has been adapted to describe detrimental bystander effects. The model describes initiation (formation of translocations) and promotion (clonal expansion and loss of contact inhibition of initiated cells). Additional terms either in the initiation model or in the rate of clonal expansion of initiated cells, describe detrimental bystander effects for chromosome aberrations as reported in the scientific literature. In the present study, the SVM with bystander effects is tested on a suitable dataset. In addition to the simulation of non-linear effects, a classical dataset for neoplastic transformation in C3H 10T1/2 cells after alpha particle irradiation is used to show that the model without bystander features can also describe LNT-like dose responses. A published model for bystander induced neoplastic transformation was adapted for chromosome aberration induction and used to compare the results obtained with the different models.

Modeling lung cancer incidence in rats following exposure to radon progeny.

Lung cancer incidence in Sprague-Dawley rats was simulated by a biologically based carcinogenesis model, which is formulated mathematically in terms of a stochastic state-vector model. Doses to the sensitive target cells in the bronchial epithelium of the rat lung were calculated by a stochastic dosimetry model, considering the distinct monopodial branching structure and the crossfire of alpha particles from alveolar tissue to bronchial epithelium. Bronchial and alveolar cellular doses could reasonably be approximated by lognormal distributions, with geometric standard deviations (GSD) between 7 and 10, depending on exposure conditions. Based on a dose-exposure conversion factor of 8.5 mGy WLM(-1) and a GSD of 8, lung cancer incidences were calculated for each cumulative exposure category in the rat inhalation study, consisting of different exposure rates and exposure times. The fair agreement between theoretical predictions and experimental data over the whole exposure range emphasises the necessity to incorporate the full cellular dose distributions rather than their mean values.

Energy deposition, cellular radiation effects and lung cancer risk by radon progeny alpha particles.

Slowing down spectra, LET spectra, hit probabilities, and radiation doses were simulated for the interaction of single 218Po and 214Po alpha particles with sensitive basal and secretory cell nuclei in the bronchial epithelium of human and rat lungs for defined exposure conditions. Probabilities per unit track length for transformation, derived from in vitro experiments with C3H 10T1/2 cells, were used to estimate transformation probabilities for randon progeny alpha particles in basal and secretory cells. Different weighting schemes were assumed to relate cellular hit probabilities, doses and transformation probabilities, obtained for different cell depths and airway generations, to lung cancer risk per unit exposure. In vitro transformation and in vivo lung cancer incidence were simulated by a state-vector model which provides a stochastic formulation of dose-rate dependent cellular transitions related to formation of double strand breaks, repair, inactivation, stimulated mitosis and promotion through loss of intercellular communication.

Testing extrapolation of a biologically based exposure-response model from in vitro to in vivo conditions.

Models of carcinogenesis may become so flexible as to preclude the possibility of being falsified by data. This problem is removed in part by stronger biophysical specification of processes and parameters within the model prior to fitting to in vivo data on the relationship between exposure and cancer incidence. This paper explores the use of a biophysical model of chromosomal damage, cellular transformation, repair, mitosis, initiation, promotion, progression, and cytotoxicity in developing exposure-response models for radiation-induced cancer. Many of the aspects of model form and parameter values are developed from in vitro data, and the model then is extrapolated to the in vivo setting using a dosimetric model to account for dose inhomogeneity within the lung tissue of rats exposed to radon progeny in air. The ability of the model to predict cancer incidence in the rats is assessed and is shown to be problematic at higher doses. This calls into question whether a full claim may be made about the ability of first-principle models to fully constrain models applied to in vivo data at present. Possible explanations for the discrepancy, and implications for extrapolation, are provided.

Explanation of protective effects of low doses of gamma-radiation with a mechanistic radiobiological model.

PURPOSE: To test whether data that show protective effects of low doses against spontaneous neoplastic transformation of C3H 10T1/2 cells can be explained with a biomathematical model that includes radioprotective mechanisms. To link important features of the model to known biological processes. MATERIALS AND METHODS: The model simulates double-strand break formation in transcriptionally active and in bulk DNA, translocation of DNA segments, and the fixation of damage at mitosis; promotion is also included. The model equations were solved numerically using a stiff solver. RESULTS: The data were successfully simulated by the model: cell transformation-reducing effects of low doses of gamma-radiation delivered at low dose-rates are explained by radiation-inducible DNA repair and enzymatic scavenging. CONCLUSIONS: The model successfully simulates experimental data. The highly nonlinear features of the data point to a nonlinear dose-effect relationship at low doses and indicate that linear extrapolation from moderate (or high) to low doses and dose-rates may not be justified for in vitro studies of the cell line under consideration.

A weighted composite dose-response model for human salmonellosis.

This article describes the development of a weighted composite dose-response model for human salmonellosis. Data from previously reported human challenge studies were categorized into two different groups representing low and moderately virulent/pathogenic Salmonella strains based on a disease end point. Because epidemiological data indicate that some Salmonella strains are particularly pathogenic, and in the absence of human feeding study data for such strains, Shigella dysenteriae was used as a proxy for highly virulent strains. Three single-hit dose-response models were applied to the human feeding study data and evaluated for best fit using maximum likelihood estimation: (1) the exponential (E-1pop), (2) the two-subpopulation exponential (E-2pop), and (3) the Beta-Poisson (BP). Based on the goodness-of-fit test, the E-1pop and BP were the best-fit models for low and moderately virulent/pathogenic Salmonella strains, and the E-2pop and BP models were better for highly virulent/pathogenic strains. Epistemic analysis was conducted by determining the degree of confidence associated with the selected models, which was found to be 50%/50% (E-1pop/BP) for low and moderately pathogenic Salmonella strains, and 9.8%/90.2% (E-2pop/BP) for highly virulent strains. The degree of confidence for each component model and variations in the proportion of strains within each virulence/pathogenicity category were incorporated into the overall composite model. This study describes the influence of variation in strain virulence and host susceptibility on the shape of the population dose-response relationship.

The use of a multimedia risk analysis approach in designing waste management strategies.

A pollution source may release residuals to any of several environmental media, depending on the process design and control strategies. These residuals then are subject to transfer, transport, and transformation within the interconnected compartments of the environmental system. The exposure and susceptibility of people and other receptors to pollutants are different in these various media, and so that risks imposed will vary according to the fate of the pollutants in the system. Because of interactions between compartments in the system, a single-medium approach to environmental management that mitigates problems in one environmental medium at a time independently of risk through other media may not minimize the aggregate risk a receptor receives from all pathways. Alternatively, a multimedia approach advocates focusing on the full environmental system providing pathways for exposure and selecting risk management strategies based on minimization of the aggregate and cumulative risk from all pathways and all compounds. This study combines multimedia risk analysis and an optimization framework to examine a methodology for selecting waste treatment/disposal and pollution control measures, applies the methodology to a sludge management decision problem, and considers the implications for continued use of single-medium analyses.

Significance of cell-cycle delay, multiple initiation pathways, misrepair and replication errors in a model of radiobiological effects.

PURPOSE: To advance a biomathematical model of radiocarcinogenesis by describing multiple pathways for initiation, a radiologically induced cell-cycle delay, misrepair and spontaneous DNA damages caused by replication. It was investigated whether the incorporation of these biological features would improve the fit of the model to data showing plateaus in in vitro irradiations of different cell lines and whether the fit parameters were then more biologically realistic. MATERIALS AND METHODS: A biomathematical submodel was developed based on a previous State-Vector Model that mathematically described enhanced DNA repair and radical scavenging following irradiation. RESULTS: With the two initiation pathways and cell-cycle delay, the simulations better explained the mouse data but not the rat data, and for both data sets the fit parameters were biologically more realistic than previously assumed. Inclusion of misrepair and replicational errors did not significantly affect the fit. CONCLUSIONS: A plateau in the dose-effect relationship for in vitro irradiation of different cell lines can be explained by radioprotective mechanisms. The plateau-type dose-response relationships point to a non-linear dose- effect relationship at low doses and indicate that linear extrapolation from moderate (or high) to low doses may not be justified for in vitro studies of these cell lines.

Correlated hit probability and cell transformation in an effect-specific track length model applied to in vitro alpha irradiation.

In estimating the risk from low doses of alpha particles such as those emitted by radon progeny, it is important to consider the correlation between cellular inactivation and transformation that can exist at the cellular level. A phenomenological model of radiation-induced cellular inactivation and transformation at this level is presented here which incorporates aspects of a state vector model of radiation carcinogenesis and of correlated hit probabilities for inactivation and transformation. The general form of the model assumes that both inactivation and initial initiation damage are produced through the interaction of sublesions induced by radiation passing through cell nuclei, with the production of sublesions governed by hit probabilities and a characteristic probability-per-unit track length. The inactivation and initiation events are partially correlated through the use of hit probabilities. In addition, promotional events are incorporated for the case of cellular transformation based on a previously published state vector model. The model provides good fits to available data on the relationship between inactivation, transformation and LET for doses of alpha above 0.1 Gy in the range of LETs commonly produced by radon and progeny; by "good fits" we mean here the ability to yield the correct shapes of dose-response data using parameter values that vary smoothly with LET and using inactivation parameters that are applied consistently between inactivation and transformation assays. The resulting model correctly predicts recent findings indicating an increased transformation frequency per surviving cell when a population receives a distribution of hits compared to irradiation where all cells receive the same number of hits.

The effects of internal radiation exposure on cancer mortality in nuclear workers at Rocketdyne/Atomics International.

We examined the effects of chronic exposure to radionuclides, primarily uranium and mixed-fission products, on cancer mortality in a retrospective cohort study of workers enrolled in the radiation-monitoring program of a nuclear research and development facility. Between 1950 and 1994, 2,297 workers were monitored for internal radiation exposures, and 441 workers died, 134 (30.4%) of them from cancer as the underlying cause. We calculated internal lung-dose estimates based on urinalysis and whole-body and lung counts reported for individual workers. We examined cancer mortality of workers exposed at different cumulative lung-dose levels using complete risk-set analysis for cohort data, adjusting for age, pay type, time since first radiation monitored, and external radiation. In addition, we examined the potential for confounding due to chemical exposures and smoking, explored whether external radiation exposure modifies the effects of internal exposure, and estimated effects after excluding exposures likely to have been unrelated to disease onset. Dose-response relations were observed for death from hemato- and lymphopoietic cancers and from upper aerodigestive tract cancers, adjusting for age, time since first monitored, pay type, and external (gamma) radiation dose. No association was found for other cancers, including cancers of the lung. Despite the small number of exposed deaths from specific cancer types and possible bias due to measurement error and confounding, the positive findings and strong dose-response gradients observed suggest carcinogenic effects of internal radiation to the upper aerodigestive tract and the blood and lymph system in this occupational cohort. However, causal inferences require replication of our results in other populations or confirmation with an extended follow-up of this cohort.

Evaluation of biologically based dose-response modeling for developmental toxicity: a workshop report.

Biologically based dose-response (BBDR) modeling represents a novel approach for quantitative assessment of health risk by incorporating pharmacokinetic and pharmacodynamic characteristics of a chemical and by relating the immediate cellular responses to a cascade of aberrant biological actions that leads to detectable adverse outcomes. The quantitative relationship of each of the intervening events can be described in mathematical forms that are amenable for adjustment and extrapolation over a range of doses and across species. A team of investigators at the Reproductive Toxicology Division of the U.S. Environmental Protection Agency has explored the feasibility of BBDR modeling by examining the developmental toxicity of a known teratogen, 5-fluorouracil. A panel of researchers from academic and industrial laboratories, biomathematical modelers, and risk assessment scientists was convened in a workshop to evaluate the approaches undertaken by the EPA team and to discuss the future prospects of BBDR modeling. This report summarizes the lessons learned from one approach to BBDR modeling and comments from the panelists: while it is possible to incorporate mechanistic information into quantitative dose-response models for the assessment of health risks, the process is enormously data-intensive and costly; in addition, the confidence of the model is directly proportional to our current understanding of basic biology and can be enhanced only through the ongoing novel discoveries. More importantly, the extent of "uncertainty" (inherent with the default assumptions associated with the NOAEL or benchmark approach) reducible by BBDR modeling requires further scrutiny and comparison.

A case control study of multiple myeloma at four nuclear facilities.

PURPOSE: Reported elevations of multiple myeloma among nuclear workers exposed to external penetrating ionizing radiation, based on small numbers of cases, prompted this multi-facility study of workers at US Department of Energy facilities. METHODS: Ninety-eight multiple myeloma deaths and 391 age-matched controls were selected from the combined roster of 115,143 workers hired before 1979 at Hanford, Los Alamos National Laboratory, Oak Ridge National Laboratory, and the Savannah River site. These workers were followed for vital status through 1990 (1986 for Hanford). Demographic, work history, and occupational exposure data were derived from personnel, occupational medicine, industrial hygiene, and health physics records. Exposure-disease associations were evaluated using conditional logistic regression. RESULTS: Cases were disproportionately African American, male, and hired prior to 1948. Lifetime cumulative whole body ionizing radiation dose was not associated with multiple myeloma, however, there was a significant effect of age at exposure, with positive associations between multiple myeloma and doses received at older ages. Dose response associations increased in magnitude with exposure age (from 40 to 50) and lag assumption (from 5 to 15 years), while a likelihood ratio goodness of fit test reached the highest value for cumulative doses received at ages above 45 with a 5-year lag (X2=5.43,1 df; relative risk = 6.9% per 10 mSv). Dose response associations persisted with adjustment for potential confounders. CONCLUSIONS: Multiple myeloma was associated with low level whole body penetrating ionizing radiation doses at older ages. The exposure age effect is at odds with interpretations of A-bomb survivor studies but in agreement with several studies of cancer among nuclear workers.

Modeling energy deposition and cellular radiation effects in human bronchial epithelium by radon progeny alpha particles.

Energy deposition and cellular radiation effects arising from the interaction of single 218Po and 214Po alpha particles with basal and secretory cell nuclei were simulated for different target cell depths in the bronchial epithelium of human airway generations 2, 4, 6, and 10. To relate the random chord lengths of alpha particle tracks through spherical cell nuclei to the resulting biological endpoints, probabilities per unit track length for different cellular radiation effects as functions of LET were derived from in vitro experiments. The radiobiological data employed in the present study were inactivation and mutation (mutant frequency at the HPRT gene) in V79 Chinese hamster cells and inactivation and transformation in C3H 10T1/2 cells. Based on computed LET spectra and relative frequencies of target cells, probabilities for transformation, mutation, and cell killing in basal and secretory cells were computed for a lifetime exposure of 20 WLM. While predicted transformation probabilities were about two orders of magnitude higher than mutation probabilities, they were still about two orders of magnitude lower than inactivation probabilities. Furthermore transformation probabilities for basal cells are generally higher than those for secretory cells, and 214Po alpha particles are primarily responsible for transformations in bronchial target cells.

Adaptive response and dose-response plateaus for initiation in a state-vector model of carcinogenesis.

PURPOSE: To investigate whether it is possible to explain dose-response plateaus for in-vitro X-ray irradiation of different cell lines with radioprotective mechanisms such as radiologically induced expression of scavengers and repair enzymes. MATERIALS AND METHODS: A biomathematical model was developed based on a previous state-vector model. New features of the model are a mathematical description of enhanced repair and radical scavenging as a result of irradiation. RESULTS: The model produces a plateau in the dose-response for in-vitro tranformations between 0.5 and 1 Gy and for chromosome aberrations and it predicts an inverse-fractionation effect within a selected range of doses. CONCLUSIONS: Adaptive response mechanisms within a state-vector model provide a coherent explanation of the dose-response characteristics for in-vitro transformations and chromosomal aberrations. These results suggest the need for new experimental studies described in the paper.

A reevaluation of cancer incidence near the Three Mile Island nuclear plant: the collision of evidence and assumptions.

Previous studies concluded that there was no evidence that the 1979 nuclear accident at Three Mile Island (TMI) affected cancer incidence in the surrounding area; however, there were logical and methodological problems in earlier reports that led us to reconsider data previously collected. A 10-mile area around TMI was divided into 69 study tracts, which were assigned radiation dose estimates based on radiation reading and models of atmospheric dispersion. Incident cancers from 1975 to 1985 were ascertained from hospital records and assigned to study tracts. Associations between accident doses and incidence rates of leukemia, lung cancer, and all cancer were assessed using relative dose estimates calculated by the earlier investigators. Adjustments were made for age, sex, socioeconomic characteristics, and preaccident variation in incidence. Considering a 2-year latency, the estimated percent increase per dose unit +/- standard error was 0.020 +/- 0.012 for all cancer, 0.082 +/- 0.032 for lung cancer, and 0.116 +/- 0.067 for leukemia. Adjustment for socioeconomic variables increased the estimates to 0.034 +/- 0.013, 0.103 +/- 0.035, and 0.139 +/- 0.073 for all cancer, lung cancer, and leukemia, respectively. Associations were generally larger considering a 5-year latency, but were based on smaller numbers of cases. Results support the hypothesis that radiation doses are related to increased cancer incidence around TMI. The analysis avoids medical detection bias, but suffers from inaccurate dose classification; therefore, results may underestimate the magnitude of the association between radiation and cancer incidence. These associations would not be expected, based on previous estimates of near-background levels of radiation exposure following the accident.

Extension of a generalized state-vector model of radiation carcinogenesis to consideration of dose rate.

Mathematical models for radiation carcinogenesis typically employ transition rates that either are a function of the dose to specific cells or are purely empirical constructs unrelated to biophysical theory. These functions either ignore or do not explicitly model interactions between the fates of cells in a community. This paper extends a model of mitosis, cell transformation, promotion, and progression to cases in which interacting cellular communities are irradiated at specific dose rates. The model predicts that lower dose rates are less effective at producing cancer when irradiation is by X- or gamma rays but are generally more effective in instances of irradiation by alpha particles up to a dose rate in excess of 0.01 Gy/day. The resulting predictions are compared with existing experimental data.

Modeling the modification of the risk of radon-induced lung cancer by environmental tobacco smoke.

The presence of environmental tobacco smoke (ETS) in homes has been implicated in the causation of lung cancer. While of interest in its own right, ETS also influences the risk imposed by radon and its decay products. The interaction between radon progeny and ETS alters the exposure, intake, uptake, biokinetics, dosimetry, and radiobiology of those progeny. The present paper details model predictions of the various influences of ETS on these factors in the U.S. population and provides estimates of the resulting change in the risk from average levels of radon progeny. It is predicted that the presence of ETS produces a very small (perhaps unmeasurable) increase in the risk of radiation-induced tracheobronchial cancer in homes with initially very high particle concentrations for both active and never-smokers, but significantly lowers the risk in homes with initially lower particle concentrations for both groups when generation 4 of the lung is considered the target site. For generation 16, the presence of ETS generally increases the radon-induced risk of lung cancer, although the increase should be unmeasurable at high initial particle concentrations. The net effect of ETS on human health is suggested to be a complicated function of the initial housing conditions, the concentration of particles introduced by smoking, the target generation considered, and the smoking status of exposed populations. This situation precludes any simple statements concerning the role of ETS in governing the incidence of lung cancer in a population.

An effect-specific track-length model for radiations of intermediate to high LET.

A model for the induction of transformation, mutation, and cell killing by radiations of intermediate to high linear energy transfer (LET) is presented. The mathematical formulation presupposes a constant probability per unit path length for damaging multiple subcellular targets by radiation of a fixed LET. The coupling between effects is accounted for through an explicit calculation of the probability that any specific combination of effects occurs in a given cell. This feature avoids the false assumption that cell killing and mutation (or transformation) are independent events. The resulting model then is applied to data on the in vitro survival, mutation, and transformation of cells by radiations of varying LET. A summary of estimated parameter values is provided and calculations of the effect of cellular flattening on transformation are presented.