Prediction of lung cancer risk for radon exposures based on cellular alpha particle hits

To explore the role of the multiplicity of cellular hits by radon progeny alpha particles for lung cancer incidence, the number of single and multiple alpha particle hits were computed for basal and secretory cells in the bronchial epithelium of human airway bifurcations. Hot spots of alpha particle...

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Bibliographic Details
Published in:Radiation protection dosimetry 2011-05, Vol.145 (2-3), p.218-223
Main Authors: Truta-Popa, L-A, Hofmann, W, Cosma, C
Format: Article
Language:English
Subjects:
Alpha Particles - adverse effects
Animals
Bronchi - radiation effects
Epithelial Cells - radiation effects
Humans
Lung Neoplasms - etiology
Mice
Mice, Inbred C3H
Neoplasms, Radiation-Induced - etiology
Predictive Value of Tests
Radon - analysis
Radon Daughters - analysis
Rats
Risk Factors
Trachea - radiation effects
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Summary:To explore the role of the multiplicity of cellular hits by radon progeny alpha particles for lung cancer incidence, the number of single and multiple alpha particle hits were computed for basal and secretory cells in the bronchial epithelium of human airway bifurcations. Hot spots of alpha particle hits were observed at the branching points of bronchial airway bifurcations. The effect of single and multiple alpha particle intersections of bronchial cells during a given exposure period, selected from a Poisson distribution, on lung cancer risk were simulated by a transformation frequency--tissue response model, based on experimentally observed cellular transformation and survival functions. Calculations of lung cancer risk at low radon exposure levels suggest that single hits produce a linear-dose response relationship, while the superposition of single and increasing multiple hits at higher exposure levels may also be approximated by a quasi-linear dose-effect curve. The simulations predict a carcinogenic enhancement effect for radon progeny accumulations at bifurcation branching sites, which may increase current risk estimates.
ISSN:0144-8420
1742-3406
DOI:10.1093/rpd/ncr082