A New Standard DNA Damage (SDD) Data Format

Abstract

Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called “indirect” damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our under-standing of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

Influence of chromatin compaction on simulated early radiation‐induced DNA damage using Geant4‐DNA

“…Therefore, the absolute yields of DSB presented here might differ from other simulation codes. To deal with this, a new Standard to record DNA Damage (SDD) will be proposed to simplify inter‐code comparisons of DNA damage induction …”

“…To deal with this, a new Standard to record DNA Damage (SDD) will be proposed to simplify inter-code comparisons of DNA damage induction. 40…”

Minibeam radiation therapy: A micro‐ and nano‐dosimetry Monte Carlo study

“…Because of the low probability of interaction with the DNA when we simulated the whole three‐minibeam source in the water phantom, we separated these simulations into two parts. This is a commonly used method for multi‐scale studies requiring track‐structure precision in small targets with realistic RT sources . We previously verified that a one‐step simulation, that is, transporting particles from a reduced source surface in the whole water volume to the DNA, yields equivalent number of simple strand break (SSB) than the two‐step method.…”

“…This is a commonly used method for multi-scale studies requiring trackstructure precision in small targets with realistic RT sources. 36 We previously verified that a one-step simulation, that is, transporting particles from a reduced source surface in the whole water volume to the DNA, yields equivalent number of simple strand break (SSB) than the two-step method. The one-step simulation requires 1000 times the number of primary particles to get the same statistical uncertainty than with the two-step method, even with a simplified source.…”

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

“…MCTS codes have been the workhorse of theoretical microdosimetry, enabling systematic calculations of lineal energy spectra (the stochastic analog of LET), proximity functions, ionization cluster distributions, etc., which are used for explaining and predicting the quality factor or the relative biological effectiveness of different ionizing radiations [33][34][35][36][37][38][39]. In addition, quantitative estimates of the early "direct" DNA damage can be obtained by combining the spatial distribution of energy-transfer points (above a certain threshold) with the geometric structure of DNA [40][41][42][43][44][45]. The main drawback of MCTS codes is that they are computer intensive and require much more detailed physics models than currently available ones [46].…”