Correlation Between DNA Double-Strand Break Distribution in 3D Genome and Ionizing Radiation-Induced Cell Death

The target theory is the most classical hypothesis explaining radiation-induced cell death, yet the physical or biological nature of the "target" remains ambiguous. This study hypothesizes that the distribution of DNA double-strand breaks (DSBs) within the 3D genome is a pivotal factor affecting the probability of radiation-induced cell death. We propose that clustered DSBs in DNA segments with high-interaction frequencies are more susceptible to leading to cell death than isolated DSBs. Topologically associating domains (TAD) can be regarded as the reference unit for evaluating the impact of DSB clustering in the 3D genome. To quantify this correlation between the DSB distribution in 3D genome and radiation-induced effect, we developed a simplified model considering the DSB distribution across TADs. Utilizing track-structure Monte Carlo codes to simulate the electron and carbon ion irradiation, and we calculated the incidence of each DSB case across a variety of radiation doses and linear energy transfers (LETs). Our simulation results indicate that DSBs in TADs with frequent interactions (case 3) are significantly more likely to induce cell death than clustered DSBs within a single TAD (case 2). Moreover, case 2 is significantly more likely to induce cell death than isolated DSBs (case 1). The curves of the incidence of cases 2 and 3 compared with LETs have a similar shape to the radiation quality factor (Q) used in radiation protection. This indicates that these two cases are also associated with the stochastic effects induced by high-LET radiation. Our study underscores the crucial significance of the 3D genome structure in the fundamental mechanisms of radiobiological effects. The hypothesis in our research offers novel perspectives on the mechanisms that regulate radiobiological effects. Moreover, it serves as a valuable reference for the establishment of mechanistic models that can predict cell survival under different doses and LETs.