Stochastic state-vector model of radiation carcinogenesis applied to radon-induced lung cancer risk

A biophysical multi-stage state-vector model (SVM) of radiation carcinogenesis has been extended to incorporate stochasticity of transitions and spatial inhomogeneity of cellular doses. Dose-rate dependent cellular transitions between the stages are related to formation of double stranded DNA breaks, repair of breaks, interactions (translocations) between breaks, fixation of breaks, cellular inactivation, stimulated mitosis and promotion through loss of intercellular communication. Each of these transitions from the normal state 0 to the tumour state 7 is simulated stochastically in time through Monte Carlo sampling of the competing events. The stochastic SVM has been applied here to in vitro transformation frequencies by monoenergetic alpha particles and to in vivo lung cancer incidence in uranium miners and laboratory rats exposed to radon progeny. Predictions of the transformation frequency per surviving cell compare favourably with the experimental in vitro data over a wide range of LETs and doses. When incorporating in vivo features of cell differentiation, stimulated cell division and heterogeneity of cellular doses, fair agreement could be obtained between model predictions and lung cancer data from human epidemiological studies as well as from rat inhalation experiments. The model predicts a nonlinear dose-response relationship at low doses, producing a risk, which is approximately a factor 2 smaller at 20 WLM than current risk estimates. The effect of cigarette smoke on the promotion of intermediate cells initiated by alpha radiation produces an increased risk at low exposures, eventually saturating at high exposure levels.