Office of Biological and Environmental Research

DOE Low Dose Radiation Program Workshop V

2005 Abstract

Title: Modeling Intercellular Interactions During Radiation Carcinogenesis

Authors: Rainer K Sachs,¹ Michael Chan,² Lynn Hlatky,³ Philip Hahnfeldt³

Institutions: ¹Departments of Mathematics and Physics, University of California Berkeley California; ²School of Medicine, University of California at San Diego, La Jolla California; ³Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston Massachusetts

Abstract

By modulating the microenvironment of malignant or pre-malignant epithelial cells, inhibitory or stimulatory signals from nearby cells, including those in stromal and vascular tissues, can play a key role in carcinogenesis; cancer is ultimately a disease of a whole-cell community, not just of a single cell, clone, or cell lineage. However, current commonly used quantitative models for induction of cancers by ionizing radiation focus on single cells and their progeny. This is true for most primarily statistical and epidemiological formalisms and for most biologically based models of the kind that may eventually be useful in extrapolating to low doses. Intercellular interactions are neglected or assumed to be confined to unidirectional radiation bystander effect signals among epithelial cells.

We have formulated a biologically based, minimally parameterized two-stage logistic (TSL) carcinogenesis model that incorporates some effects of intercellular interactions in that cells that have been initiated, by radiation or otherwise, are considered to be under density-dependent growth control. The model considers initiation, promotion, transformation, and progression steps, and it uses average cell numbers, i.e., stochastic fluctuations of the cell numbers are neglected.

We show that for baseline tumor incidence and mortality rates, involving no radiation apart from background radiation, this TSL model gives fits to data wholly equivalent to the fits given by the commonly used, stochastic, two-stage clonal expansion (TSCE) model, which has been applied to a wide variety of human and animal results. The number of parameters is the same and for appropriately matching parameter choices, the predicted curves are the same. The biological interpretations differ somewhat, mainly because initiated cell growth deceleration is attributed to growth control in the TSL model but to stochastic effects in the TSCE model.

For perturbations of baseline rates, including radiation perturbations, the models differ and the new, TSL model involves fewer adjustable parameters than the TSCE model. We argue from epidemiological and laboratory evidence, especially results on the atomic bomb survivors, that for radiation carcinogenesis the TSL model gives results at least as realistic as the TSCE or similar models, despite the reduction in parameter number. In particular, if the main effect of acute radiation is to initiate additional cells, the TSL model predicts that excess relative risk decreases monotonically with time since irradiation, in qualitative agreement with the data for solid tumors in the atomic bomb victims. In this case the TSL model involves one fewer parameter than the TSCE model.

Research funded by the Low Dose Radiation Research Program, Office of Biological and Environmental Research (BER), U.S. Department of Energy, grant DE-FG02-03ER63668 (RKS), NIH grant R01-GM68423-01 (MC), NASA grant NSCOR04-0014-0017 (LH) and NIH grant 1RO1-CA78496-04 (PH).

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