title: Simulating Space Radiation-Induced Breast Tumor Incidence Using Automata.
abstract: Estimating cancer risk from space radiation has been an ongoing challenge for decades primarily because most of the reported epidemiological data on radiation-induced risks are derived from studies of atomic bomb survivors who were exposed to an acute dose of gamma rays instead of chronic high-LET cosmic radiation. In this study, we introduce a formalism using cellular automata to model the long-term effects of ionizing radiation in human breast for different radiation qualities. We first validated and tuned parameters for an automata-based two-stage clonal expansion model simulating the age dependence of spontaneous breast cancer incidence in an unexposed U.S.
  
  
  
  We then tested the impact of radiation perturbation in the model by modifying parameters to reflect both targeted and nontargeted radiation effects. Targeted effects (TE) reflect the immediate impact of radiation on a cell's DNA with classic end points being gene mutations and cell death. They are well known and are directly derived from experimental data. In contrast, nontargeted effects (NTE) are persistent and affect both damaged and undamaged cells, are nonlinear with dose and are not well characterized in the literature. In this study, we introduced TE in our model and compared predictions against epidemiologic data of the atomic bomb survivor cohort. TE alone are not sufficient for inducing enough cancer. NTE independent of dose and lasting ∼100 days postirradiation need to be added to accurately predict dose dependence of breast cancer induced by gamma rays. Finally, by integrating experimental relative biological effectiveness (RBE) for TE and keeping NTE (i.e., radiation-induced genomic instability) constant with dose and LET, the model predicts that RBE for breast cancer induced by cosmic radiation would be maximum at 220 keV/μm. This approach lays the groundwork for further investigation into the impact of chronic low-dose exposure, inter-individual variation and more complex space radiation scenarios.
authors.affiliation: a   Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California.|c   NAmur Research Institute for Life Sciences (NARILIS), Research Center for the Physics of Matter and Radiation (PMR), University of Namur, Namur, Belgium.
authors.forename: A C
authors.initials: AC
authors.lastname: Heuskin
authors.affiliation: a   Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California.
authors.forename: A I
authors.initials: AI
authors.lastname: Osseiran
authors.affiliation: b   Exogen Biotechnology Inc., Berkeley, California.
authors.forename: J
authors.initials: J
authors.lastname: Tang
authors.affiliation: a   Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California.
authors.forename: S V
authors.initials: SV
authors.lastname: Costes
mesh_terms: D001943:Breast Neoplasms / Q000209:etiology* / Q000235:genetics / Q000473:pathology*; D003359:Cosmic Radiation / Q000009:adverse effects; D005118:Extraterrestrial Environment; D006801:Humans; D015994:Incidence; D018499:Linear Energy Transfer; D008954:Models, Biological; D059645:Mutation Rate; D009381:Neoplasms, Radiation-Induced / Q000209:etiology* / Q000235:genetics / Q000473:pathology*; D012062:Relative Biological Effectiveness; D018570:Risk Assessment