Biologically based analysis of lung cancer incidence in a large Canadian occupational cohort with low-dose ionizing radiation exposure, and comparison with Japanese atomic bomb survivors

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.

Invited Commentary: Mechanistic and Biologically Based Models in Epidemiology-A Powerful Underutilized Tool

Mechanistic and biologically based mathematical models of chronic and behavioral disease processes aim to capture the main mechanistic or biological features of the disease development and to connect these with epidemiologic outcomes. These approaches have a long history in epidemiologic research and are complementary to traditional epidemiologic or statistical approaches to investigate the role of risk factor exposures on disease risk. Simonetto et al. (Am J Epidemiol. 2022;191(10):1766-1775) present a mechanistic, process-oriented model to investigate the role of smoking, hypertension, and dyslipidemia in the development of atherosclerotic lesions and their progression to myocardial infarction. Their approach builds on and brings to cardiovascular disease the ideas and perspectives of earlier mechanistic and biologically based models for the epidemiology of cancer and other chronic diseases, providing important insights into the mechanisms and epidemiology of smoking related myocardial infarction. We argue that although mechanistic modeling approaches have demonstrated their value and place in epidemiology, they are highly underutilized. We call for efforts to grow mechanistic and biologically based modeling research, expertise, and awareness in epidemiology, including the development of training and collaboration opportunities to attract more students and researchers from science, technology, engineering, and medical field into the epidemiology field.

Advances in the Current Understanding of How Low-Dose Radiation Affects the Cell Cycle

Cells exposed to ionizing radiation undergo a series of complex responses, including DNA damage, reproductive cell death, and altered proliferation states, which are all linked to cell cycle dynamics. For many years, a great deal of research has been conducted on cell cycle checkpoints and their regulators in mammalian cells in response to high-dose exposures to ionizing radiation. However, it is unclear how low-dose ionizing radiation (LDIR) regulates the cell cycle progression. A growing body of evidence demonstrates that LDIR may have profound effects on cellular functions. In this review, we summarize the current understanding of how LDIR (of up to 200 mGy) regulates the cell cycle and cell-cycle-associated proteins in various cellular settings. In light of current findings, we also illustrate the conceptual function and possible dichotomous role of p21^Waf1, a transcriptional target of p53, in response to LDIR.

Case Studies of Gastric, Lung, and Oral Cancer Connect Etiologic Agent Prevalence to Cancer Incidence

Obtaining detailed individual-level data on both exposure and cancer outcomes is challenging, and it is difficult to understand and characterize how temporal aspects of exposures translate into cancer risk. We show that, in lieu of individual-level information, population-level data on cancer incidence and etiologic agent prevalence can be leveraged to investigate cancer mechanisms and to better characterize and predict cancer trends. We use mechanistic carcinogenesis models [multistage clonal expansion (MSCE) models] and data on smoking, Helicobacter pylori (H. pylori), and HPV infection prevalence to investigate trends of lung, gastric, and HPV-related oropharyngeal cancers. MSCE models are based on the initiation-promotion-malignant conversion paradigm and allow for interpretation of trends in terms of general biological mechanisms. We assumed the rates of initiation depend on the prevalence of the corresponding risk factors. We performed two types of analysis, using the agent prevalence and cancer incidence data to estimate the model parameters and using cancer incidence data to infer the etiologic agent prevalence as well as the model parameters. By including risk factor prevalence, MSCE models with as few as three parameters closely reproduced 40 years of age-specific cancer incidence data. We recovered trends of H. pylori prevalence in the United States and demonstrated that cohort effects can explain the observed bimodal, age-specific pattern of oral HPV prevalence in men. Our results demonstrate the potential for joint analyses of population-level cancer and risk factor data through mechanistic modeling. This approach can be a first step in systematically testing relationships between exposures and cancer risk when individual-level data is lacking.Significance: Analysis of trends in risk-factor prevalence and cancer incidence can shed light on cancer mechanisms and the way that carcinogen exposure through time shapes the risk of cancer at different ages.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/12/3386/F1.large.jpg Cancer Res; 78(12); 3386-96. ©2018 AACR.

Impact of Low-dose Ionising Radiation on the Composition of the Gut Microbiota of Mice

BACKGROUND

Although the importance of the gut microbiota in the maintenance of human health has been well established, little is known about the impact of low-dose ionising radiation (exposure to a dose of less than 0.5 Gy of low linear energy transfer radiation such as γ- or X-rays [LDR]) on the composition and functional role of the gut microbiota. The aim of the present study was to investigate and compare the composition of the gut microbiota in mice exposed to LDR.

METHODS AND MATERIALS

Male BALB/c mice were exposed to low-dose Co60 radiation. Faecal samples taken prior to and after irradiation were used for high-throughput sequencing of 16S rRNA gene sequence amplicons.

RESULTS

We observed substantial changes in the composition of the gut microbiota, including alpha diversity and beta diversity, in mice exposed to LDR compared to the non-radiated control group. Moreover, at the genus level, the abundance of Clostridium, Helicobacter and Oscilibacter increased, and those of Bacteroides and Barnesiella decreased, in a time-dependent manner in the radiated groups compared to the non-radiated control group. The functional metabolic pathway analysis indicated that Bacteroides spp. and members of the other genera that were found are predicted to play roles in bacterial toxin production, DNA repair, and Type II diabetes. Furthermore, these alterations in the gut microbiota were accompanied by changes in the abundance of multiple metabolites, which were predicted to be involved in multiple signalling pathways, including glucagon, central carbon metabolism, and type II diabetes.

CONCLUSIONS

The possibility of microbiota-mediated pathophysiology resulting from LDR may be an as yet unrecognised hazard that merits further experimental examination. This study provides a conceptual and analytical foundation for further research into the chronic effects of LDR on human health, and points to potential novel targets for intervention to prevent the adverse effects of radiation.

A Systematic Approach to Determining the Identifiability of Multistage Carcinogenesis Models

Multistage clonal expansion (MSCE) models of carcinogenesis are continuous-time Markov process models often used to relate cancer incidence to biological mechanism. Identifiability analysis determines what model parameter combinations can, theoretically, be estimated from given data. We use a systematic approach, based on differential algebra methods traditionally used for deterministic ordinary differential equation (ODE) models, to determine identifiable combinations for a generalized subclass of MSCE models with any number of preinitation stages and one clonal expansion. Additionally, we determine the identifiable combinations of the generalized MSCE model with up to four clonal expansion stages, and conjecture the results for any number of clonal expansion stages. The results improve upon previous work in a number of ways and provide a framework to find the identifiable combinations for further variations on the MSCE models. Finally, our approach, which takes advantage of the Kolmogorov backward equations for the probability generating functions of the Markov process, demonstrates that identifiability methods used in engineering and mathematics for systems of ODEs can be applied to continuous-time Markov processes.

The impact of radiation on the development of lung cancer

Environment factors such as radiation play an important role in the incidence of lung cancer. In spite of substantial efforts in experimental study and mathematical modeling, it is still a significant challenge to estimate lung cancer risk from radiation. To address this issue, we propose a stochastic model to investigate the impact of radiation on the development of lung cancer. The proposed three-stage model with clonal expansion is used to match the data of the male and female patients in the Osaka Cancer Registry (OCR) and Life Span Study (LSS) cohort of atomic bomb survivors in Hiroshima and Nagasaki. Our results indicate that the major effect of radiation on the development of lung cancer is to induce gene mutations for both male and female patients. In particular, for male patients, radiation affects the mutation in normal cells and the transformation from premalignant cells to malignant ones. However, radiation for female patients increases the mutation rates of the first two mutations in the stochastic model. The established relationship between parameters and radiation will provide insightful prediction for the lung cancer incidence in the radiation exposure.

Low-dose radiation may be a novel approach to enhance the effectiveness of cancer therapeutics

It has been generally accepted that both natural and man-made sources of ionizing radiation contribute to human exposure and consequently pose a possible risk to human health. However, accumulating evidence has shown that the biological effects of low-dose radiation (LDR) are different from those of high-dose radiation. LDR can stimulate proliferation of normal cells and activate their defense systems, while these biological effects are not observed in some cancer cell types. Although there is still no concordance on this matter, the fact that LDR has the potential to enhance the effects of cancer therapeutics and reduce the toxic side effects of anti-cancer therapy has garnered significant interest. Here, we provide an overview of the current knowledge regarding the experimental data detailing the different responses of normal and cancer tissues to LDR, the underlying mechanisms, and its significance in clinical application.

Epidemiology Without Biology: False Paradigms, Unfounded Assumptions, and Specious Statistics in Radiation Science (with Commentaries by Inge Schmitz-Feuerhake and Christopher Busby and a Reply by the Authors)

Radiation science is dominated by a paradigm based on an assumption without empirical foundation. Known as the linear no-threshold (LNT) hypothesis, it holds that all ionizing radiation is harmful no matter how low the dose or dose rate. Epidemiological studies that claim to confirm LNT either neglect experimental and/or observational discoveries at the cellular, tissue, and organismal levels, or mention them only to distort or dismiss them. The appearance of validity in these studies rests on circular reasoning, cherry picking, faulty experimental design, and/or misleading inferences from weak statistical evidence. In contrast, studies based on biological discoveries demonstrate the reality of hormesis: the stimulation of biological responses that defend the organism against damage from environmental agents. Normal metabolic processes are far more damaging than all but the most extreme exposures to radiation. However, evolution has provided all extant plants and animals with defenses that repair such damage or remove the damaged cells, conferring on the organism even greater ability to defend against subsequent damage. Editors of medical journals now admit that perhaps half of the scientific literature may be untrue. Radiation science falls into that category. Belief in LNT informs the practice of radiology, radiation regulatory policies, and popular culture through the media. The result is mass radiophobia and harmful outcomes, including forced relocations of populations near nuclear power plant accidents, reluctance to avail oneself of needed medical imaging studies, and aversion to nuclear energy-all unwarranted and all harmful to millions of people.

Age Effects and Temporal Trends in HPV-Related and HPV-Unrelated Oral Cancer in the United States: A Multistage Carcinogenesis Modeling Analysis

Differences in prognosis in HPV-positive and HPV-negative oral (oropharyngeal and oral cavity) squamous cell carcinomas (OSCCs) and increasing incidence of HPV-related cancers have spurred interest in demographic and temporal trends in OSCC incidence. We leverage multistage clonal expansion (MSCE) models coupled with age-period-cohort (APC) epidemiological models to analyze OSCC data in the SEER cancer registry (1973-2012). MSCE models are based on the initiation-promotion-malignant conversion paradigm in carcinogenesis and allow for interpretation of trends in terms of biological mechanisms. APC models seek to differentiate between the temporal effects of age, period, and birth cohort on cancer risk. Previous studies have looked at the effect of period and cohort on tumor initiation, and we extend this to compare model fits of period and cohort effects on each of tumor initiation, promotion, and malignant conversion rates. HPV-related, HPV-unrelated except oral tongue, and HPV-unrelated oral tongue sites are best described by placing period and cohort effects on the initiation rate. HPV-related and non-oral-tongue HPV-unrelated cancers have similar promotion rates, suggesting similar tumorigenesis dynamics once initiated. Estimates of promotion rates at oral tongue sites are lower, corresponding to a longer sojourn time; this finding is consistent with the hypothesis of an etiology distinct from HPV or alcohol and tobacco use. Finally, for the three subsite groups, men have higher initiation rates than women of the same race, and black people have higher promotion than white people of the same sex. These differences explain part of the racial and sex differences in OSCC incidence.

Benefits and harms of computed tomography lung cancer screening strategies: a comparative modeling study for the U.S. Preventive Services Task Force

BACKGROUND

The optimum screening policy for lung cancer is unknown.

OBJECTIVE

To identify efficient computed tomography (CT) screening scenarios in which relatively more lung cancer deaths are averted for fewer CT screening examinations.

DESIGN

Comparative modeling study using 5 independent models.

DATA SOURCES

The National Lung Screening Trial; the Prostate, Lung, Colorectal, and Ovarian Cancer Screening trial; the Surveillance, Epidemiology, and End Results program; and the U.S. Smoking History Generator.

TARGET POPULATION

U.S. cohort born in 1950.

TIME HORIZON

Cohort followed from ages 45 to 90 years.

PERSPECTIVE

Societal.

INTERVENTION

576 scenarios with varying eligibility criteria (age, pack-years of smoking, years since quitting) and screening intervals.

OUTCOME MEASURES

Benefits included lung cancer deaths averted or life-years gained. Harms included CT examinations, false-positive results (including those obtained from biopsy/surgery), overdiagnosed cases, and radiation-related deaths.

RESULTS OF BEST-CASE SCENARIO

The most advantageous strategy was annual screening from ages 55 through 80 years for ever-smokers with a smoking history of at least 30 pack-years and ex-smokers with less than 15 years since quitting. It would lead to 50% (model ranges, 45% to 54%) of cases of cancer being detected at an early stage (stage I/II), 575 screening examinations per lung cancer death averted, a 14% (range, 8.2% to 23.5%) reduction in lung cancer mortality, 497 lung cancer deaths averted, and 5250 life-years gained per the 100,000-member cohort. Harms would include 67,550 false-positive test results, 910 biopsies or surgeries for benign lesions, and 190 overdiagnosed cases of cancer (3.7% of all cases of lung cancer [model ranges, 1.4% to 8.3%]).

RESULTS OF SENSITIVITY ANALYSIS

The number of cancer deaths averted for the scenario varied across models between 177 and 862; the number of overdiagnosed cases of cancer varied between 72 and 426.

LIMITATIONS

Scenarios assumed 100% screening adherence. Data derived from trials with short duration were extrapolated to lifetime follow-up.

CONCLUSION

Annual CT screening for lung cancer has a favorable benefit-harm ratio for individuals aged 55 through 80 years with 30 or more pack-years' exposure to smoking.

PRIMARY FUNDING SOURCE

National Cancer Institute.

Chapter 8: The FHCRC lung cancer model

As a member of the Cancer Intervention and Surveillance Modeling Network (CISNET), the lung cancer (LC) group at Fred Hutchinson Cancer Research Center (FHCRC) developed a model for evaluating U.S. lung cancer mortality trends and the impact of changing tobacco consumption. Model components include a biologically based two-stage clonal expansion (TSCE) model; a smoking simulator to generate smoking histories and other cause mortality; and adjustments for period and birth cohort to improve calibration to U.S. LC mortality. The TSCE model was first calibrated to five substantial cohorts: British doctors, American Cancer Society CPS-I and CPS-II, Health Professionals' Follow-Up Study (HPFS), and Nurses' Health Study (NHS). The NHS and HPFS cohorts included the most detailed smoking histories and were chosen to represent the effects of smoking on U.S. LC mortality. The calibrated TSCE model and smoking simulator were used to simulate U.S. LC mortality. Further adjustments were necessary to account for unknown factors. This provided excellent fits between simulated and observed U.S. LC mortality for ages 30-84 and calendar years 1975-2000. The FHCRC LC model may be used to study the effects of public health information on U.S. LC trends and the impact of tobacco control policy. For example, we estimated that over 500,000 males and 200,000 females avoided LC death between 1975 and 2000 due to increasing awareness since the mid 1950s of the harmful effects of smoking. We estimated that 1.1 million male and 0.6 million female LC deaths were avoidable if smokers quit smoking in 1965.

Oxidative damage in various tissues of rats exposed to radon

Oxidative damage can be induced by many environmental stressors. 8-Hydroxydeoxyguanosine (8-OHdG) has been used as a biomarker of oxidative DNA damage in both in vitro and in vivo studies. In the present study, Wistar rats were exposed to radon gas at a concentration of 100,000Bq/m(3) for 12 h/d for 30, 60, and 120 d, equivalent to cumulative doses of 60, 120, and 240 working level months (WLM), respectively. Changes in levels of 8-OHdG, reactive oxygen species (ROS), and total antioxidant (T-AOC), as well as expressions of some DNA repair enzymes such as 8-oxoguanine DNA glycosylase (OGG1) and MutT homolog 1 (oxidized purine nucleoside triphosphatase, MTH1), were determined in rat urine, peripheral blood lymphocytes, and lung after exposure to radon. The results revealed an increase in 8-OHdG and ROS levels, a decrease in T-AOC levels, and reduced OGG1 and MTH1 expression levels. The elevated amount of 8-OHdG in urine or lymphocytes was positively correlated with the cumulative exposure dose, whereas OGG1 and MHT1 expression levels in lung were inversely correlated with cumulative exposure dose. These findings indicate that oxidative damage induced by radon may be involved in radon-induced carcinogenesis.

Radiation-induced carcinogenesis: mechanistically based differences between gamma-rays and neutrons, and interactions with DMBA

Different types of ionizing radiation produce different dependences of cancer risk on radiation dose/dose rate. Sparsely ionizing radiation (e.g. γ-rays) generally produces linear or upwardly curving dose responses at low doses, and the risk decreases when the dose rate is reduced (direct dose rate effect). Densely ionizing radiation (e.g. neutrons) often produces downwardly curving dose responses, where the risk initially grows with dose, but eventually stabilizes or decreases. When the dose rate is reduced, the risk increases (inverse dose rate effect). These qualitative differences suggest qualitative differences in carcinogenesis mechanisms. We hypothesize that the dominant mechanism for induction of many solid cancers by sparsely ionizing radiation is initiation of stem cells to a pre-malignant state, but for densely ionizing radiation the dominant mechanism is radiation-bystander-effect mediated promotion of already pre-malignant cell clone growth. Here we present a mathematical model based on these assumptions and test it using data on the incidence of dysplastic growths and tumors in the mammary glands of mice exposed to high or low dose rates of γ-rays and neutrons, either with or without pre-treatment with the chemical carcinogen 7,12-dimethylbenz-alpha-anthracene (DMBA). The model provides a mechanistic and quantitative explanation which is consistent with the data and may provide useful insight into human carcinogenesis.

Modeling progression in radiation-induced lung adenocarcinomas

Quantitative multistage carcinogenesis models are used in radiobiology to estimate cancer risks and latency periods (time from exposure to clinical cancer). Steps such as initiation, promotion and transformation have been modeled in detail. However, progression, a later step during which malignant cells can develop into clinical symptomatic cancer, has often been approximated simply as a fixed lag time. This approach discounts important stochastic mechanisms in progression and evidence on the high prevalence of dormant tumors. Modeling progression more accurately is therefore important for risk assessment. Unlike models of earlier steps, progression models can readily utilize not only experimental and epidemiological data but also clinical data such as the results of modern screening and imaging. Here, a stochastic progression model is presented. We describe, with minimal parameterization: the initial growth or extinction of a malignant clone after formation of a malignant cell; the likely dormancy caused, for example, by nutrient and oxygen deprivation; and possible escape from dormancy resulting in a clinical cancer. It is shown, using cohort simulations with parameters appropriate for lung adenocarcinomas, that incorporating such processes can dramatically lengthen predicted latency periods. Such long latency periods together with data on timing of radiation-induced cancers suggest that radiation may influence progression itself.

Stochastic population dynamic effects for lung cancer progression

The multistage paradigm is widely used in quantitative analyses of radiation-influenced carcinogenesis. Steps such as initiation, promotion and transformation have been investigated in detail. However, progression, a later step during which malignant cells produced in the earlier steps can develop into clinical cancer, has received less attention in computational radiobiology; it has often been approximated deterministically as a fixed, comparatively short, lag time. This approach overlooks important mechanisms in progression, including stochastic extinction, possible radiation effects on tumor growth, immune suppression and angiogenic bottlenecks. Here we analyze tumor progression in background and in radiation-induced lung cancers, emphasizing tumor latent times and the stochastic extinction of malignant lesions. A Monte Carlo cell population dynamics formalism is developed by supplementing the standard two-stage clonal expansion (TSCE) model with a stochastic birth-death model for proliferation of malignant cells. Simulation results for small cell lung cancers and lung adenocarcinomas show that the effects of stochastic malignant cell extinction broaden progression time distributions drastically. We suggest that fully stochastic cancer progression models incorporating malignant cell kinetics, dormancy (a phase in which tumors remain asymptomatic), escape from dormancy, and invasiveness, with radiation able to act directly on each phase, need to be considered for a better assessment of radiation-induced lung cancer risks.

Canadian National Dose Registry of radiation workers: overview of research from 1951 through 2007

The National Dose Registry (NDR) of Canada is a unique resource for a direct estimation of the potential health risks associated with low doses of ionizing radiation. This is the largest national occupational radiation exposure database, comprising records for about 600,000 nuclear, industrial, medical and dental workers. An analysis of the NDR data based on a cohort of about 200,000 workers first exposed before 1984 and followed through 1987 and 1988 for mortality and cancer incidence, respectively, revealed that the mortality from most causes of death considered was lower than that in the general population, which is typical of occupational cohorts. Although the same was also observed for cancer incidence, there was a significant increase in the incidence of thyroid cancer and melanoma which, however, was not clearly related to radiation exposure. A significant dose-response was found for mortality from all causes, all cancers, lung cancer, cardiovascular diseases, accidents, for incidence of all cancers, cancers of the rectum and lung, leukaemia, all cancers except lung, and all cancers except leukaemia. In addition, in male workers, a significant dose-response was found for the incidence of colon, pancreatic, and testicular cancers. The estimates of cancer risks (mortality and incidence) were higher than those in most other occupational cohorts and in the studies on atomic bomb survivors. The biologically based dose-response models used to describe lung cancer incidence in the NDR showed that for a protracted exposure to low radiation doses there was a significant radiation effect on the promotion and malignant conversion, but not on the initiation stage of carcinogenesis. This stands in contrast to the findings for high-dose acute exposures in A-bomb survivors, where the initiation and possibly promotion were found to be affected by radiation exposure. Evidence of an inverse dose-rate effect (i.e. an increase in the risk with a protraction of a given cumulative dose) was found in the NDR cohort.

Multistage modeling of leukemia in benzene workers: a simple approach to fitting the 2-stage clonal expansion model

A simple SAS software program (SAS Institute, Inc., Cary, North Carolina) was developed for fitting an exact formulation of the 2-stage clonal expansion model accommodating piecewise constant exposures and left and right censoring of observations. Data on leukemia mortality and occupational exposure to benzene among rubber hydrochloride production workers in Ohio (1940-1996) were analyzed by using this approach. A model in which benzene exposure increased clonal expansion fit these data well; little evidence of an association between benzene exposure and initiation of leukemia was found. The estimated exposure-response association increased in magnitude with age at exposure and decreased with time since exposure. This analysis shows that the 2-stage clonal expansion model can be readily fit to epidemiologic cohort data by using a simple SAS program. The illustrative analyses of leukemia mortality among rubber hydrochloride workers suggest that the effect of benzene on leukemia risk is due to an exposure-induced increase in the proliferation of initiated cells.

Systems biological and mechanistic modelling of radiation-induced cancer

This paper summarises the five presentations at the First International Workshop on Systems Radiation Biology that were concerned with mechanistic models for carcinogenesis. The mathematical description of various hypotheses about the carcinogenic process, and its comparison with available data is an example of systems biology. It promises better understanding of effects at the whole body level based on properties of cells and signalling mechanisms between them. Of these five presentations, three dealt with multistage carcinogenesis within the framework of stochastic multistage clonal expansion models, another presented a deterministic multistage model incorporating chromosomal aberrations and neoplastic transformation, and the last presented a model of DNA double-strand break repair pathways for second breast cancers following radiation therapy.

Adverse effects attributed to long-term radon inhalation in rats

The aim of this study was to investigate the adverse effect of long-term radon exposure on lung and blood cells in rats exposed to different radiation doses. Sprague-Dawley rats were exposed to radon for cumulative doses up to 66, 111, and 174 WLM (work level month). Total number and differential cells counts were determined in the bronchoalveolar lavage fluid (BALF) and the peripheral blood, as well as the activity of lactate dehydrogenase (LDH) and levels of glutathione (GSH) and total protein. DNA damage and interleukin (IL)-6 mRNA expression in BALF cells and peripheral blood mononuclear cells (PBMC) were detected by single cell gel electrophoresis (SCGE) and reverse-transcription polymerase chain reaction (RT-PCR), respectively. The results showed that radon-exposed lymphocytes were significantly lower and granulocytes higher in BALF compared to blood in exposed groups. The distance of DNA migration in the BALF and PBMC increased in a dose-dependent manner. A positive correlation between the PBMC and BALF cells in terms of DNA damage was noted. These findings suggested that PBMC might be used as a surrogate for BALF cells and thus the easier non-invasive ability to obtain PBMC may be useful in detection of lung DNA damage induced by radon.