a Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts.
b Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom.
Radiat Res. 2019 Jan;191(1):76-92. doi: 10.1667/RR15209.1. Epub 2018 Nov 8.
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 understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.
在过去的几十年中，我们对辐射诱导的细胞损伤的理解有了很大的提高。尽管取得了这一进展，但仍有许多障碍需要克服，才能全面了解辐射如何与生物相关的细胞成分（如 DNA）相互作用，从而导致可观察的终点，如细胞死亡。DNA 损伤被认为是细胞杀伤的主要途径之一。在建模生物学效应时，一个障碍是难以直接比较来自不同研究小组的成员生成的结果。已经开发了多种蒙特卡罗代码来模拟 DNA 尺度上的损伤诱导，而与此同时，不同的小组也开发了具有不同详细程度的描述 DNA 修复过程的模型。这些修复模型与它们开发过程中的损伤模型本质上是相关的，使得难以区分建模链中任何一部分的系统效应。这些建模链通常由物理相互作用的轨迹结构蒙特卡罗模拟组成，这些相互作用会直接对 DNA 造成损伤，然后模拟导致所谓“间接”损伤的化学物质的产生和初始反应。在 DNA 损伤的诱导之后，DNA 修复模型将模拟的损伤模式与生物模型相结合，以确定损伤的生物学后果。迄今为止，环境的影响（如分子氧（常氧与缺氧））一直被严重忽视。我们提出了一种新的标准 DNA 损伤（SDD）数据格式，以统一 DNA 损伤诱导模拟与 DNA 修复过程的生物建模之间的接口，并引入环境（分子氧或其他化合物）的影响作为灵活的参数。这样的标准极大地促进了模型之间的比较，为揭示模型假设和识别持久的潜在机制提供了理想的环境。通过模型间的比较，这种统一的标准有可能极大地促进我们对辐射诱导的 DNA 损伤的潜在机制以及当辐射参数和/或环境条件发生变化时观察到的生物学效应的理解。
