Igor Shuryak

Cancer Risks After Radiation Exposure in Middle Age

BACKGROUND Epidemiological data show that radiation exposure during childhood is associated with larger cancer risks compared with exposure at older ages. For exposures in adulthood, however, the relative risks of radiation-induced cancer in Japanese atomic bomb survivors generally do not decrease monotonically with increasing age of adult exposure. These observations are inconsistent with most standard models of radiation-induced cancer, which predict that relative risks decrease monotonically with increasing age at exposure, at all ages. METHODS We analyzed observed cancer risk patterns as a function of age at exposure in Japanese atomic bomb survivors by using a biologically based quantitative model of radiation carcinogenesis that incorporates both radiation induction of premalignant cells (initiation) and radiation-induced promotion of premalignant damage. This approach emphasizes the kinetics of radiation-induced initiation and promotion, and tracks the yields of premalignant cells before, during, shortly after, and long after radiation exposure. RESULTS Radiation risks after exposure in younger individuals are dominated by initiation processes, whereas radiation risks after exposure at later ages are more influenced by promotion of preexisting premalignant cells. Thus, the cancer site-dependent balance between initiation and promotion determines the dependence of cancer risk on age at radiation exposure. For example, in terms of radiation induction of premalignant cells, a quantitative measure of the relative contribution of initiation vs promotion is 10-fold larger for breast cancer than for lung cancer. Reflecting this difference, radiation-induced breast cancer risks decrease with age at exposure at all ages, whereas radiation-induced lung cancer risks do not. CONCLUSION For radiation exposure in middle age, most radiation-induced cancer risks do not, as often assumed, decrease with increasing age at exposure. This observation suggests that promotional processes in radiation carcinogenesis become increasingly important as the age at exposure increases. Radiation-induced cancer risks after exposure in middle age may be up to twice as high as previously estimated, which could have implications for occupational exposure and radiological imaging.

Impact of Reduced Patient Life Expectancy on Potential Cancer Risks from Radiologic Imaging

PURPOSE To quantify the effect of reduced life expectancy on cancer risk by comparing estimated lifetime risks of lung cancer attributable to radiation from commonly used computed tomographic (CT) examinations in patients with and those without cancer or cardiac disease. MATERIALS AND METHODS With the use of clinically determined life tables, reductions in radiation-attributable lung cancer risks were estimated for coronary CT angiographic examinations in patients with multivessel coronary artery disease who underwent coronary artery bypass graft (CABG) surgery and for surveillance CT examinations in patients treated for colon cancer. Statistical uncertainties were estimated for the risk ratios in patients who underwent CABG surgery and patients with colon cancer versus the general population. RESULTS Patients with decreased life expectancy had decreased radiation-associated cancer risks. For example, for a 70-year-old patient with colon cancer, the estimated reduction in lifetime radiation-associated lung cancer risk was approximately 92% for stage IV disease, versus 8% for stage 0 or I disease. For a patient who had been treated with CABG surgery, the estimated reduction in lifetime radiation-associated lung cancer risk was approximately 57% for a 55-year-old patient, versus 12% for a 75-year-old patient. CONCLUSION The importance of radiation exposure in determining optimal imaging usage is much reduced for patients with markedly reduced life expectancies: Imaging justification and optimization criteria for patients with substantially reduced life expectancies should not necessarily be the same as for those with normal life expectancies.

A new view of radiation-induced cancer: integrating short- and long-term processes. Part II: second cancer risk estimation

As the number of cancer survivors grows, prediction of radiotherapy-induced second cancer risks becomes increasingly important. Because the latency period for solid tumors is long, the risks of recently introduced radiotherapy protocols are not yet directly measurable. In the accompanying article, we presented a new biologically based mathematical model, which, in principle, can estimate second cancer risks for any protocol. The novelty of the model is that it integrates, into a single formalism, mechanistic analyses of pre-malignant cell dynamics on two different time scales: short-term during radiotherapy and recovery; long-term during the entire life span. Here, we apply the model to nine solid cancer types (stomach, lung, colon, rectal, pancreatic, bladder, breast, central nervous system, and thyroid) using data on radiotherapy-induced second malignancies, on Japanese atomic bomb survivors, and on background US cancer incidence. Potentially, the model can be incorporated into radiotherapy treatment planning algorithms, adding second cancer risk as an optimization criterion.

A new view of radiation-induced cancer: integrating short- and long-term processes. Part I: Approach

Mathematical models of radiation carcinogenesis are important for understanding mechanisms and for interpreting or extrapolating risk. There are two classes of such models: (1) long-term formalisms that track pre-malignant cell numbers throughout an entire lifetime but treat initial radiation dose–response simplistically and (2) short-term formalisms that provide a detailed initial dose–response even for complicated radiation protocols, but address its modulation during the subsequent cancer latency period only indirectly. We argue that integrating short- and long-term models is needed. As an example of this novel approach, we integrate a stochastic short-term initiation/inactivation/repopulation model with a deterministic two-stage long-term model. Within this new formalism, the following assumptions are implemented: radiation initiates, promotes, or kills pre-malignant cells; a pre-malignant cell generates a clone, which, if it survives, quickly reaches a size limitation; the clone subsequently grows more slowly and can eventually generate a malignant cell; the carcinogenic potential of pre-malignant cells decreases with age.

Adapting the γ-H2AX Assay for Automated Processing in Human Lymphocytes. 1. Technological Aspects

Abstract The immunofluorescence-based detection of γ-H2AX is a reliable and sensitive method for quantitatively measuring DNA double-strand breaks (DSBs) in irradiated samples. Since H2AX phosphorylation is highly linear with radiation dose, this well-established biomarker is in current use in radiation biodosimetry. At the Center for High-Throughput Minimally Invasive Radiation Biodosimetry, we have developed a fully automated high-throughput system, the RABIT (Rapid Automated Biodosimetry Tool), that can be used to measure γ-H2AX yields from fingerstick-derived samples of blood. The RABIT workstation has been designed to fully automate the γ-H2AX immunocytochemical protocol, from the isolation of human blood lymphocytes in heparin-coated PVC capillaries to the immunolabeling of γ-H2AX protein and image acquisition to determine fluorescence yield. High throughput is achieved through the use of purpose-built robotics, lymphocyte handling in 96-well filter-bottomed plates, and high-speed imaging. The goal of the present study was to optimize and validate the performance of the RABIT system for the reproducible and quantitative detection of γ-H2AX total fluorescence in lymphocytes in a multiwell format. Validation of our biodosimetry platform was achieved by the linear detection of a dose-dependent increase in γ-H2AX fluorescence in peripheral blood samples irradiated ex vivo with γ rays over the range 0 to 8 Gy. This study demonstrates for the first time the optimization and use of our robotically based biodosimetry workstation to successfully quantify γ-H2AX total fluorescence in irradiated peripheral lymphocytes.

Biophysical Models of Radiation Bystander Effects: 1. Spatial Effects in Three-Dimensional Tissues

Abstract Shuryak, I., Sachs, R. K. and Brenner, D. J. Biophysical Models of Radiation Bystander Effects: 1. Spatial Effects in Three-Dimensional Tissues. Radiat. Res. 168, 741–749 (2007). Non-targeted (bystander) effects of ionizing radiation are caused by intercellular signaling; they include production of DNA damage and alterations in cell fate (i.e. apoptosis, differentiation, senescence or proliferation). Biophysical models capable of quantifying these effects may improve cancer risk estimation at radiation doses below the epidemiological detection threshold. Understanding the spatial patterns of bystander responses is important, because it provides estimates of how many bystander cells are affected per irradiated cell. In a first approach to modeling of bystander spatial effects in a three-dimensional artificial tissue, we assume the following: (1) The bystander phenomenon results from signaling molecules (S) that rapidly propagate from irradiated cells and decrease in concentration (exponentially in the case of planar symmetry) as distance increases. (2) These signals can convert cells to a long-lived epigenetically activated state, e.g. a state of oxidative stress; cells in this state are more prone to DNA damage and behavior alterations than normal and therefore exhibit an increased response (R) for many end points (e.g. apoptosis, differentiation, micronucleation). These assumptions are implemented by a mathematical formalism and computational algorithms. The model adequately describes data on bystander responses in the 3D system using a small number of adjustable parameters.

High-dose and fractionation effects in stereotactic radiation therapy: Analysis of tumor control data from 2965 patients.

BACKGROUND AND PURPOSE Two aspects of stereotactic radiotherapy (SRT) require clarification: First, are tumoricidal mechanisms at high-doses/fraction the same as at lower doses? Second, is single high-dose SRT treatment advantageous for tumor control (TCP) vs. multi-fraction SRT? MATERIAL AND METHODS We analyzed published TCP data for lung tumors or brain metastases from 2965 SRT patients, covering a wide range of doses and fraction numbers. We used: (a) a linear-quadratic model (including heterogeneity), which assumes the same mechanisms at all doses, and (b) alternative models with terms describing distinct tumoricidal mechanisms at high doses. RESULTS Both for lung and brain data, the LQ model provided a significantly better fit over the entire range of treatment doses than did any of the models requiring extra terms at high doses. Analyzing the data as a function of fractionation (1 fraction vs. >1 fraction), there was no significant effect on TCP in the lung data, whereas for brain data multi-fraction SRT was associated with higher TCP than single-fraction treatment. CONCLUSION Our analysis suggests that distinct tumoricidal mechanisms do not determine tumor control at high doses/fraction. In addition, there is evidence suggesting that multi-fraction SRT is superior to single-dose SRT.

Risk and Risk Reduction of Major Coronary Events Associated With Contemporary Breast Radiotherapy

Author Affiliations: Department of Emergency Medicine, University of California, San Francisco (Brownell, Hsia); medical student, School of Medicine, University of California, San Francisco (Wang); Division of Geriatrics, Department of Medicine, University of California, San Francisco (Smith); Geriatrics, Palliative and Extended Care, San Francisco Veterans Affairs Medical Center (Smith, Stephens); Department of Community Health Systems, University of California, San Francisco (Stephens).

Reducing Second Breast Cancers: A Potential Role for Prophylactic Mammary Irradiation

Breast-conserving surgery followed by radiotherapy is the standard of care for most women with early-stage breast cancer, resulting in excellent long-term survival. Post-treatment, however, the rate of second breast cancers is significant; for example, the average ipsilateral second-cancer rate from four long-term studies is 13% after 15 years, and increases with still longer follow-up times. Rates in the contralateral breast are typically only slightly lower. We focus here on the rate of second cancers, which are genetically independent of the primary (ie, not recurrences); this rate is much higher than could be explained from the natural background rate of breast cancer in the general population, for both breasts. After conservative surgery, the ipsilateral breast is typically administered a fractionated whole-breast radiotherapeutic dose of at least 45 Gy, followed by a local boost to the tumor site. There is now considerable evidence that such large radiation doses to the breast result in significantly increased breast cancer risks. For example, recent long-term studies of Hodgkin’s disease patients who underwent radiotherapy show large radiation-induced breast cancer risks at sites exposed to doses 40 Gy, with excess relative risks in the range of 10 to 30. That tissues exposed to fractionated radiation doses as high as 40 to 50 Gy are at significant risk for radiation-induced cancer has only recently become apparent. Early models of radiation-induced cancer had predicted that virtually all radiation-mutated cells would be killed by such large doses, and thus the risk of radiationinduced cancer would be minimal. However, the epidemiologic data showing high risks of radiation-induced cancer at high radiation doses have made it apparent that simple models of radiation carcinogenesis involving radiation-induction of premalignant cells, modulated solely by cell killing, are not adequate at high radiation doses. Consequently, more recent models take into account repopulation of normal and of premalignant cells by proliferation, occurring during and after fractionated radiotherapy, whereby some repopulating cells carry and pass on radiationinduced premalignant damage. Including repopulation in models of radiation-induced cancer results in predictions of substantial cancer risks at high radiation doses, consistent with epidemiologic data. Thus, recent epidemiologic data and theory both lead to the expectation that women who receive a whole breast dose of 45 to 50 Gy will be at significant long-term risk for radiation-induced breast cancer, for all relevant ages. Here we estimate the cancer risks associated with adjuvant whole-breast irradiation after lumpectomy, both in the ipsilateral and contralateral breasts, and compare the predictions with the measured long-term risks of genetically independent second cancers in each breast. This allows an assessment for each breast of the relative importance of tumor recurrence, background risk, and radiation risk. The resulting insights in turn suggest potential strategies for reducing these risks.

Minimizing second cancer risk following radiotherapy: current perspectives

Secondary cancer risk following radiotherapy is an increasingly important topic in clinical oncology with impact on treatment decision making and on patient management. Much of the evidence that underlies our understanding of secondary cancer risks and our risk estimates are derived from large epidemiologic studies and predictive models of earlier decades with large uncertainties. The modern era is characterized by more conformal radiotherapy technologies, molecular and genetic marker approaches, genome-wide studies and risk stratifications, and sophisticated biologically based predictive models of the carcinogenesis process. Four key areas that have strong evidence toward affecting secondary cancer risks are 1) the patient age at time of radiation treatment, 2) genetic risk factors, 3) the organ and tissue site receiving radiation, and 4) the dose and volume of tissue being irradiated by a particular radiation technology. This review attempts to summarize our current understanding on the impact on secondary cancer risks for each of these known risk factors. We review the recent advances in genetic studies and carcinogenesis models that are providing insight into the biologic processes that occur from tissue irradiation to the development of a secondary malignancy. Finally, we discuss current approaches toward minimizing the risk of radiation-associated secondary malignancies, an important goal of clinical radiation oncology.