Prediction of Lung Cells Oncogenic Transformation for Induced Radon Progeny Alpha Particles Using Sugarscape Cellular Automata

authors:

avatar Samaneh Baradaran 1 , * , avatar Niaz Maleknasr 2 , avatar Saeed Setayeshi 3 , avatar Mohammad Esmaeil Akbari 4

Dept. of Medical Radiation Engineering, Amirkabir University of Technology, Tehran, Iran; National Radaition Protection Department, Iranian Nuclear Regulatory Authority, Tehran, Iran
Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Dept. of Medical Radiation Engineering, Amirkabir University of Technology, Tehran, Iran
Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran

how to cite: Baradaran S , Maleknasr N, Setayeshi S, Akbari M E. Prediction of Lung Cells Oncogenic Transformation for Induced Radon Progeny Alpha Particles Using Sugarscape Cellular Automata. Int J Cancer Manag. 2014;7(1):e80508. 

Abstract

Background: Alpha particle irradiation from radon progeny is one of the major natural sources of effective dose in the public population. Oncogenic transformation is a biological effectiveness of radon progeny alpha particle hits. The biological effects which has caused by exposure to radon, were the main result of a complex series of physical, chemical, biological and physiological interactions. The cellular and molecular mechanisms for radoninduced carcinogenesis have not been clear yet.
Methods: Various biological models, including cultured cells and animals, have been found useful for studying the carcinogenesis effects of radon progeny alpha particles. In this paper, sugars cape cellular automata have been presented for computational study of complex biological effect of radon progeny alpha particles in lung bronchial airways. The model has included mechanism of DNA damage, which has been induced alpha particles hits, and then formation of transformation in the lung cells. Biomarkers were an objective measure or evaluation of normal or abnormal biological processes. In the model, the metabolism rate of infected cell has been induced alpha particles traversals, as a biomarker, has been followed to reach oncogenic transformation.
Results: The model results have successfully validated in comparison with “in vitro oncogenic transformation data” for C3H 10T1/2 cells. This model has provided an opportunity to study the cellular and molecular changes, at the various stages in radiation carcinogenesis, involving human cells.
Conclusion: It has become well known that simulation could be used to investigate complex biomedical systems, in situations where traditional methodologies were difficult or too costly to employ.

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