Evaluating Iodine-125 DNA Damage Benchmarks of Monte Carlo DNA Damage Models

SIMPLE SUMMARY: Simulation of initial radiation-induced DNA damage remains a major area of research, with numerous Monte Carlo models having been developed to model radiation effects on the cellular scale. While many models have been reasonably fit to a range of biological endpoints, there remains a lack of robust benchmarking data. Here, we investigate the application of a dataset on strand breaking in a single DNA strand through incorporation of radioactive Iodine-125 to distinguish between different Monte Carlo nanoscale physics models. We find that, while all models are able to effectively fit this data, they do so using significantly different best-fitting parameters and make substantially different predictions for other endpoints. These observations suggest that most nanoscale models broadly agree on the distribution of energy and can be made to fit to single datasets, but robust, multi-endpoint analysis is required to fully optimize and validate these approaches. ABSTRACT: A wide range of Monte Carlo models have been applied to predict yields of DNA damage based on nanoscale track structure calculations. While often similar on the macroscopic scale, these models frequently employ different assumptions which lead to significant differences in nanoscale dose deposition. However, the impact of these differences on key biological readouts remains unclear. A major challenge in this area is the lack of robust datasets which can be used to benchmark models, due to a lack of resolution at the base pair level required to deeply test nanoscale dose deposition. Studies investigating the distribution of strand breakage in short DNA strands following the decay of incorporated (125)I offer one of the few benchmarks for model predictions on this scale. In this work, we have used TOPAS-nBio to evaluate the performance of three Geant4-DNA physics models at predicting the distribution and yield of strand breaks in this irradiation scenario. For each model, energy and OH radical distributions were simulated and used to generate predictions of strand breakage, varying energy thresholds for strand breakage and OH interaction rates to fit to the experimental data. All three models could fit well to the observed data, although the best-fitting strand break energy thresholds ranged from 29.5 to 32.5 eV, significantly higher than previous studies. However, despite well describing the resulting DNA fragment distribution, these fit models differed significantly with other endpoints, such as the total yield of breaks, which varied by 70%. Limitations in the underlying data due to inherent normalisation mean it is not possible to distinguish clearly between the models in terms of total yield. This suggests that, while these physics models can effectively fit some biological data, they may not always generalise in the same way to other endpoints, requiring caution in their extrapolation to new systems and the use of multiple different data sources for robust model benchmarking.