DNA break clustering as a predictor of cell death across various radiation qualities: influence of cell size, cell asymmetry, and beam orientation.

IF 1.5 4区 生物学 Q4 CELL BIOLOGY Integrative Biology Pub Date : 2024-01-23 DOI:10.1093/intbio/zyae015
Floriane Poignant, Eloise Pariset, Ianik Plante, Artem L Ponomarev, Trevor Evain, Louise Viger, Tony C Slaba, Steve R Blattnig, Sylvain V Costes
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Abstract

Cosmic radiation, composed of high charge and energy (HZE) particles, causes cellular DNA damage that can result in cell death or mutation that can evolve into cancer. In this work, a cell death model is applied to several cell lines exposed to HZE ions spanning a broad range of linear energy transfer (LET) values. We hypothesize that chromatin movement leads to the clustering of multiple double strand breaks (DSB) within one radiation-induced foci (RIF). The survival probability of a cell population is determined by averaging the survival probabilities of individual cells, which is function of the number of pairwise DSB interactions within RIF. The simulation code RITCARD was used to compute DSB. Two clustering approaches were applied to determine the number of RIF per cell. RITCARD outputs were combined with experimental data from four normal human cell lines to derive the model parameters and expand its predictions in response to ions with LET ranging from ~0.2 keV/μm to ~3000 keV/μm. Spherical and ellipsoidal nuclear shapes and two ion beam orientations were modeled to assess the impact of geometrical properties on cell death. The calculated average number of RIF per cell reproduces the saturation trend for high doses and high-LET values that is usually experimentally observed. The cell survival model generates the recognizable bell shape of LET dependence for the relative biological effectiveness (RBE). At low LET, smaller nuclei have lower survival due to increased DNA density and DSB clustering. At high LET, nuclei with a smaller irradiation area-either because of a smaller size or a change in beam orientation-have a higher survival rate due to a change in the distribution of DSB/RIF per cell. If confirmed experimentally, the geometric characteristics of cells would become a significant factor in predicting radiation-induced biological effects. Insight Box: High-charge and energy (HZE) ions are characterized by dense linear energy transfer (LET) that induce unique spatial distributions of DNA damage in cell nuclei that result in a greater biological effect than sparsely ionizing radiation like X-rays. HZE ions are a prominent component of galactic cosmic ray exposure during human spaceflight and specific ions are being used for radiotherapy. Here, we model DNA damage clustering at sub-micrometer scale to predict cell survival. The model is in good agreement with experimental data for a broad range of LET. Notably, the model indicates that nuclear geometry and ion beam orientation affect DNA damage clustering, which reveals their possible role in mediating cell radiosensitivity.

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DNA断裂聚类作为各种辐射质量下细胞死亡的预测因子:细胞大小、细胞不对称和光束方向的影响。
由高电荷和高能量(HZE)粒子组成的宇宙辐射会造成细胞 DNA 损伤,从而导致细胞死亡或突变,进而演变成癌症。在这项研究中,我们将细胞死亡模型应用于暴露在线性能量转移(LET)值范围广泛的 HZE 离子下的几种细胞系。我们假设染色质运动导致多个双链断裂(DSB)聚集在一个辐射诱发灶(RIF)内。细胞群的存活概率由单个细胞的存活概率平均值决定,而单个细胞的存活概率是 RIF 内成对 DSB 相互作用数量的函数。模拟代码 RITCARD 用于计算 DSB。采用两种聚类方法来确定每个细胞的 RIF 数量。RITCARD 的输出结果与四个正常人细胞系的实验数据相结合,得出了模型参数,并扩展了模型对 LET 从 ~0.2 keV/μm 到 ~3000 keV/μm 的离子的预测。对球形和椭圆形核形状以及两种离子束方向进行了建模,以评估几何特性对细胞死亡的影响。计算得出的每个细胞的平均 RIF 数量再现了实验中通常观察到的高剂量和高 LET 值的饱和趋势。细胞存活模型为相对生物效应(RBE)生成了可识别的钟形 LET 依赖性。在低 LET 下,由于 DNA 密度增加和 DSB 聚集,较小的细胞核存活率较低。在高 LET 下,由于每个细胞中 DSB/RIF 的分布发生变化,辐照面积较小的细胞核--可能因为尺寸较小,也可能因为光束方向发生变化--存活率较高。如果得到实验证实,细胞的几何特征将成为预测辐射诱导生物效应的一个重要因素。洞察方框:高电荷和高能量(HZE)离子的特点是密集的线性能量转移(LET),可在细胞核中诱导独特的 DNA 损伤空间分布,从而产生比 X 射线等稀疏电离辐射更大的生物效应。HZE 离子是人类太空飞行期间受到银河宇宙射线照射的主要成分,特定离子正被用于放射治疗。在这里,我们建立了亚微米尺度的 DNA 损伤集群模型,以预测细胞存活率。该模型与大范围 LET 的实验数据非常吻合。值得注意的是,模型表明核几何形状和离子束方向会影响 DNA 损伤聚类,这揭示了它们在介导细胞放射敏感性方面可能发挥的作用。
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来源期刊
Integrative Biology
Integrative Biology 生物-细胞生物学
CiteScore
4.90
自引率
0.00%
发文量
15
审稿时长
1 months
期刊介绍: Integrative Biology publishes original biological research based on innovative experimental and theoretical methodologies that answer biological questions. The journal is multi- and inter-disciplinary, calling upon expertise and technologies from the physical sciences, engineering, computation, imaging, and mathematics to address critical questions in biological systems. Research using experimental or computational quantitative technologies to characterise biological systems at the molecular, cellular, tissue and population levels is welcomed. Of particular interest are submissions contributing to quantitative understanding of how component properties at one level in the dimensional scale (nano to micro) determine system behaviour at a higher level of complexity. Studies of synthetic systems, whether used to elucidate fundamental principles of biological function or as the basis for novel applications are also of interest.
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