Space Radiation Risk Assessment

Project A: Integration and Review: A review of current knowledge from space radiation physics was accepted for publication in Reviews of Modern Physics (Durante and Cucinotta, 2011). Several Graphical Users Interface’s (GUI) of risk assessment models and computational tools were developed and published including: a) ARRBOD (Acute Radiation Risk and BRYTNRN Organ Dose); b) NSCR (NASA Space Cancer Risk) c) GERMCode (Galactic Cosmic Radiation, GCR, Event-based Risk Model); d) RITracks (Relativistic Ion Track Structure). The GERMcode was developed to accurately describe fragmentation in the NASA Space Radiation Laboratory (NSRL) beam-line and biological samples, and basic radiobiology experiments.

Project B: Cancer Risk Projection Model and Uncertainties: New findings and knowledge from NSRL and other sources were used to revise the NASA’s risk model for space radiation cancer risks:

1) Revised values for low LET risk coefficients for tissue specific cancer incidence.

2) An analysis of lung cancer and other smoking attributable cancer risks for never-smokers show significantly reduced lung cancer risks as well as overall cancer risks for astronauts as compared to the risk estimated for the average U.S. population.

3) Derivation of track structure based radiation quality functions that depend on charge number, Z, and kinetic energy, E, in place of a dependence on LET alone. The assignment of a smaller maximum in the quality function for leukemia than for solid cancers.

4) Revised uncertainty assessments for all model coefficients in the risk model (physics, low LET risk coefficients, dose and dose-rate effectiveness factor (DDREF), and quality factors), and an alternative uncertainty assessment that considers deviation from linear responses due to non-targeted effects (NTE).

Results of calculations for the average U.S. population show more restrictive dose limits for astronauts above age 40 y as compared to National Council on Radiation Protection and Measurements (NCRP) Report 132, and a modest narrowing of uncertainties if NTEs are not included and much broader uncertainties with NTEs. Risks for never-smokers compared to the average U.S. population are estimated in a mixture model to be reduced by more than 20% and 30% for males and females, respectively. A larger reduction is possible if purely multiplicative risk transfer is assumed.

Project C: Biochemical Kinetics Models of Molecular Pathways: A system biology model (Cucinotta et al., 2008) of the non-homologous end joining (NHEJ) pathway was developed and used to make quantitative descriptions of the gamma H2AX foci and double strand break (DSB) rejoining experiments. The model is extended to consider the radiation quality dependence of the relative fraction of simple and complex DSB, rejoining and associated repair defects, and the kinetics of various radiation induced foci (RIF). In further work, the addition of ataxia telangiectasia mutated (ATM) and the MRN complex to the model was achieved and the role of processing damaged ends by the Artemis proteins is being modeled (Li and Cucinotta, 2011). The interaction of several growth factors with NHEJ components was studied, including the interaction of the growth factors EGFR, IGF1, and TGFbeta-Smad with ATM and DNA-PK. New approaches to Green’s functions for stochastic treatment of molecular diffusion processes were developed (Plante et al. 2011). Flow cytometry or immune-staining considers signals in individual cells and thus provides several unique capabilities to support computation modeling using stochastic approaches. In contrast, methods that average the values of many cells such as Western blots, gene arrays, etc. are limited in elucidating events at low dose where fluctuations are expected to be important. To improve our understanding of DNA repair complexes numerical approaches to simulate immunohistochemistry (Ponomarev et al., 2008, 2009) and flow cytometry experiments (Cucinotta , in preparation, Chappell et al., 2010) were developed. These models embed a basic understanding of track structure with statistical approaches of flow cytometry data sorted by cell cycle phase, and fluorescence intensity taking into account background levels. Following flow cytometry analysis, we were able to distinguish the kinetics of these phospho-proteins in relationship to the cell cycle and to each other in an individual cell. Results revealed a unique pattern of kinetics for high vs low LET radiation, with a failure to initiate full activation of the ATM pathway being evident following High LET exposure. In the process of these studies we have noted that different populations of cells making up normal human tissues can be sorted based on intrinsic qualities of the cells and differences in their radiation sensitivity have been noted. In addition, an increase in proliferation of a specific mammary cell population was observed with low doses of radiation.

Project D: DNA Damage in Cancer Initiation and Genomic Instability: Foci size and clustering including strings of foci along high-Z high-energy (HZE) tracks, were modeled for the first time and provide a useful analysis tool of NSRL experiments on DNA damage foci. These models have been extended to predict chromosomal aberration formation including the distribution of small rings normally below detection levels with fluorescence in-situ hybridization (FISH) (<5 Mbp), and to describe complex aberrations. Stochastic track structure models were combined with a human genome model that considers random walk polymer models of each chromosomes pair built from 2 kbp monomers and constrained to nuclear territories in interphase (Ponomarev et al., 2007, 2009).

Project E: Acute Radiation Risk Models: We extended the granulopoietic model for rodents for the prediction of solar particle effects in canines, non-human primates, and humans (Hu and Cucinotta, 2011). An important feature of this approach is that the dynamics of cell populations are described by non-linear differential equations. Validation of the model was achieved by comparison to comprehensive data sets for animals exposed to acute and chronic radiation and to the Chernobyl and other radiation accident victims.