Simulating Space Radiation-Induced Breast Tumor Incidence Using Automata

Abstract

Abstract:11 Heuskin A.C., Osseiran A., Tang J. and Costes S.V., Simulating Space Radiation-Induced Breast Tumor 12Incidence Using Automata, Radiat. Res. 13Estimating cancer risk from space radiation has been an ongoing challenge for decades primarily 14 because most epidemiological data showing evidence of cancer risk from ionizing radiation are derived 15 from studies of atomic bomb survivors, where individuals were exposed to acute dose of gamma-rays 16 instead of chronic exposure of high-LET cosmic radiation. In this work, we introduce a formalism using 17 cellular automata to model the long-term effects of ionizing radiation in human breast for different 18 radiation quality. We first validate and tune parameters for an automata-based two stage clonal 19 expansion model which simulates the age dependence of spontaneous breast cancer incidence in 20 unexposed US population. We then test the impact of radiation perturbation in the model by modifying 21 parameters to reflect both targeted and non-targeted effects of ionizing radiation. 22Targeted effects (TE) reflect the immediate impact of radiation on cell's DNA with classic endpoints 23 being gene mutations and cell death. They are well known and are directly derived from experimental 24 data. In contrast, non-targeted effects (NTE) are persistent radiation effects affecting both damaged and 25 undamaged cells, they are non-linear with dose and they are not well characterized in the literature. TE 26 is first introduced in the model and predictions are compared to epidemiologic data of the A-bomb 27 cohort. TE alone is not sufficient to induce enough cancer and genomic instability which last ~100 days 28 post-exposure independently of dose needs to be added to predict accurately the dose dependence of 29 breast cancer induced by gamma-rays. Finally, by integrating experimental RBE for TE and keeping 30 radiation-induced genomic instability constant with dose and LET, the model predicts that RBE for breast 31 cancer induced by cosmic radiation would be maximum at 220 keV/µm. This work is well suited to 32 explore next the impact of chronic low dose exposure, inter-individual variation and more complex 33 space radiation scenarii. 34 3

Fundamental Biological Features of Spaceflight: Advancing the Field to Enable Deep-Space Exploration

“…Thus, it is critical to establish and utilize a multi-omic approach as outlined in Figure 4 to further study these health risks and individual responses, including comprehensive monitoring of these molecular and cellular responses to enable personalized aerospace medicine, even on Mars (Nangle et al, 2020). In addition, multi-omics approachs have been used to predict risks of spaceflight hazards on individuals (Heuskin et al, 2016), as well as identify protection (Cortese et al, 2018). These models are made all the more accurate as data feed in from measurements and biomarker monitoring of the real astronaut environment through telemetry, dosimetry, microbiology, and even microgravity sequencing (McIntyre et al, 2016).…”

DNA break clustering inside repair domains predicts cell death and mutation frequency in human fibroblasts and in Chinese hamster cells for a 103x range of linear energy transfers

“…One consequence of the elevated ionization power of HZE particles is a relatively higher cancer risk compared to low-LET radiation exposure [2,15]. Predictions for tumorigenesis induced by HZE are classically scaled linearly from low-LET cancer incidence using the concept of Relative Biological Effectiveness (RBE), defined as the ratio of the dose of a reference radiation (e.g., gamma rays) to the dose of the radiation of interest to produce the same biological effect [16,17].…”

“…In this work, we focus on two interrelated cellular events important for carcinogenesis: radiation-induced clonogenic death and mutation [2]. These events have been studied previously for V79 Chinese hamster cells and demonstrated distinct LET dependence for mutation and inactivation RBE [24,25].…”

Ionizing radiation-induced risks to the central nervous system and countermeasures in cellular and rodent models

“…Radiation-induced damage to CNS, as to any other organ, can be classified as a combination of targeted effects of direct DNA damage and non-targeted effects that are primarily mediated by oxidative stress responses and cause cellular damage and death eventually leading to damage at tissue and organ levels (Heuskin et al 2016). Thus, CNS responses to radiation, as shown in Figure 2, can also be analyzed and mitigated at different levels: from molecular (DNA damage, reactive oxygen species), to cellular (cell membrane damage, cell death), to vascular leakage and disrupted electrochemical connections between neurons, to tissue and organ damage that eventually culminates in behavioral deficits (Greene-Schloesser and .…”