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

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 125I 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.

Monte Carlo-Based Nanoscale Dosimetry Holds Promise for Radiopharmaceutical Therapy Involving Auger Electron Emitters

“…A distance threshold for DSB, denoted as dDSB, of 3, 5, and 10 BP intervals was considered. Additionally, similar definitions for SSBs were applied to the semi-cylindrical Thompson geometry, incorporating physical and chemical reactions as physical reactions within each semi-cylinder at the BP location, with a threshold energy deposition value of 17.5 eV, as detailed in relevant publications [9,17,18]. Furthermore, our simulation focused solely on the interaction between radiation and matter within the DNA structure and did not account for potential biological interactions such as nucleobase damage and its role in SSB and DSB formation.…”

ICRU Report 98, Stochastic Nature of Radiation Interactions: Microdosimetry

“…DSB = double-strand break; LET = linear energy transfer. Journal of the ICRU 23(1)1-165 2020; Sakata et al, 2019;Tang et al, 2020;Thibault et al, 2022;Thompson et al, 2022). Development of the Geant4-DNA platform for radiobiological applications included incorporation of a feature allowing for prediction of DNA rejoining kinetics and corresponding cell surviving fraction as a function of time.…”

“…The Geant4-DNA platform has since been applied in many studies of damage to the DNA molecule and its higher-order structures in mammalian cells (Figs. 9.17 and 9.18) and other organisms exposed to many radiation types, including those of interest in radiotherapy, space travel, and radiobiology (Chatzipapas et al , 2020; 2021; 2023; Dominguez-Kondo et al , 2021; Dos Santos et al , 2020; Henthorn et al , 2017; Hilgers et al , 2022; Incerti et al , 2016; 2020; Kyriakou et al , 2021; 2022; Lee and Wang, 2019; Margis et al , 2020; Moeini et al , 2020; Mokari et al , 2020; Sakata et al , 2019; Tang et al , 2020; Thibault et al , 2022; Thompson et al , 2022). Development of the Geant4-DNA platform for radiobiological applications included incorporation of a feature allowing for prediction of DNA rejoining kinetics and corresponding cell surviving fraction as a function of time.…”