Bertolet Alejandro, Chamseddine Ibrahim, Paganetti Harald, Schuemann Jan
Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
Front Oncol. 2023 Jun 16;13:1196502. doi: 10.3389/fonc.2023.1196502. eCollection 2023.
DNA damage is the main predictor of response to radiation therapy for cancer. Its Q8 quantification and characterization are paramount for treatment optimization, particularly in advanced modalities such as proton and alpha-targeted therapy.
We present a novel approach called the Microdosimetric Gamma Model (MGM) to address this important issue. The MGM uses the theory of microdosimetry, specifically the mean energy imparted to small sites, as a predictor of DNA damage properties. MGM provides the number of DNA damage sites and their complexity, which were determined using Monte Carlo simulations with the TOPAS-nBio toolkit for monoenergetic protons and alpha particles. Complexity was used together with a illustrative and simplistic repair model to depict the differences between high and low LET radiations.
DNA damage complexity distributions were were found to follow a Gamma distribution for all monoenergetic particles studied. The MGM functions allowed to predict number of DNA damage sites and their complexity for particles not simulated with microdosimetric measurements (yF) in the range of those studied.
Compared to current methods, MGM allows for the characterization of DNA damage induced by beams composed of multi-energy components distributed over any time configuration and spatial distribution. The output can be plugged into ad hoc repair models that can predict cell killing, protein recruitment at repair sites, chromosome aberrations, and other biological effects, as opposed to current models solely focusing on cell survival. These features are particularly important in targeted alpha-therapy, for which biological effects remain largely uncertain. The MGM provides a flexible framework to study the energy, time, and spatial aspects of ionizing radiation and offers an excellent tool for studying and optimizing the biological effects of these radiotherapy modalities.
DNA损伤是癌症放射治疗反应的主要预测指标。对其进行量化和表征对于优化治疗至关重要，尤其是在质子和α粒子靶向治疗等先进治疗方式中。
我们提出了一种名为微剂量伽马模型（MGM）的新方法来解决这一重要问题。MGM利用微剂量学理论，特别是赋予小位点的平均能量，作为DNA损伤特性的预测指标。MGM提供DNA损伤位点的数量及其复杂性，这些是使用TOPAS-nBio工具包对单能质子和α粒子进行蒙特卡罗模拟确定的。复杂性与一个直观且简单的修复模型一起用于描述高LET和低LET辐射之间的差异。
发现所有研究的单能粒子的DNA损伤复杂性分布均遵循伽马分布。MGM函数能够预测在所研究范围内未通过微剂量测量模拟的粒子（yF）的DNA损伤位点数量及其复杂性。
与当前方法相比，MGM能够表征由分布在任何时间配置和空间分布上的多能量成分组成的束流所诱导的DNA损伤。其输出可以插入到能够预测细胞杀伤、修复位点的蛋白质募集、染色体畸变和其他生物学效应的特设修复模型中，而当前模型仅关注细胞存活。这些特性在靶向α治疗中尤为重要，因为其生物学效应在很大程度上仍不确定。MGM提供了一个灵活的框架来研究电离辐射的能量、时间和空间方面，并为研究和优化这些放射治疗方式的生物学效应提供了一个出色的工具。
