During exposure to ionizing radiation, sub-lethal damage repair (SLDR) competes with DNA damage induction in cultured cells. By virtue of SLDR, cell survival increases with decrease of dose-rate, so-called dose-rate effects (DREs). Here, we focused on a wide dose-rate range and investigated the change of cell-cycle distribution during X-ray protracted exposure and dose-response curves via hybrid analysis with a combination of in vitro experiments and mathematical modelling. In the course of flow-cytometric cell-cycle analysis and clonogenic assays, we found the following responses in CHO-K1 cells: (1) The fraction of cells in S phase gradually increases during 6 h exposure at 3.0 Gy/h, which leads to radio-resistance. (2) Slight cell accumulation in S and G₂/M phases is observed after exposure at 6.0 Gy/h for more than 10 hours. This suggests that an increase of SLDR rate for cells in S phase during irradiation may be a reproducible factor to describe changes in the dose-response curve at dose-rates of 3.0 and 6.0 Gy/h. By re-evaluating cell survival for various dose-rates of 0.186–60.0 Gy/h considering experimental-based DNA content and SLDR, it is suggested that the change of S phase fraction during irradiation modulates the dose-response curve and is possibly responsible for some inverse DREs.

DNA double-strand breaks (DSBs) are thought to be the main cause of cell death after irradiation. In this study, we estimated the probability distribution of the number of DSBs per cell nucleus by considering the DNA amount in a cell nucleus (which depends on the cell cycle) and the statistical variation in the energy imparted to the cell nucleus by X-ray irradiation. The probability estimation of DSB induction was made following these procedures: (i) making use of the Chinese Hamster Ovary (CHO)-K1 cell line as the target example, the amounts of DNA per nucleus in the logarithmic and the plateau phases of the growth curve were measured by flow cytometry with propidium iodide (PI) dyeing; (ii) the probability distribution of the DSB number per cell nucleus for each phase after irradiation with 1.0 Gy of 200 kVp X-rays was measured by means of γ-H2AX immunofluorescent staining; (iii) the distribution of the cell-specific energy deposition via secondary electrons produced by the incident X-rays was calculated by WLTrack (in-house Monte Carlo code); (iv) according to a mathematical model for estimating the DSB number per nucleus, we deduced the induction probability density of DSBs based on the measured DNA amount (depending on the cell cycle) and the calculated dose per nucleus. The model exhibited DSB induction probabilities in good agreement with the experimental results for the two phases, suggesting that the DNA amount (depending on the cell cycle) and the statistical variation in the local energy deposition are essential for estimating the DSB induction probability after X-ray exposure.

The microdosimetric-kinetic (MK) model is one of the models that can describe the fraction of cells surviving after exposure to ionizing radiation. In the MK model, there are specific parameters, k and y_D, where k is an inherent parameter to represent the number of potentially lethal lesions (PLLs) and y_D indicates the dose-mean lineal energy in keV/μm. Assuming the PLLs to be DNA double-strand breaks (DSBs), the rate equations are derived for evaluating the DSB number in the cell nucleus. In this study, we estimated the ratio of DSBs for two types of photon irradiation (6 MV and 200 kVp X-rays) in Chinese hamster ovary (CHO-K1) cells and human non-small cell lung cancer (H1299) cells by observing the surviving fraction. The estimated ratio was then compared with the ratio of γ-H2AX foci using immunofluorescent staining. For making a comparison of the number of DSBs among a variety of radiation energy cases, we next utilized the survival data in the literature for both cells exposed to other photon types, such as ⁶⁰Co γ-rays, ¹³⁷Cs γ-rays and 100 kVp X-rays. The ratio of DSBs based on the MK model with conventional data was consistent with the ratio of γ-H2AX foci numbers, confirming that the γ-H2AX focus is indicative of DSBs. It was also shown that the larger y_D is, the larger the DSB number is. These results suggest that k and y_D represent the characteristics of the surviving fraction and the biological effects for photon irradiation.

Boron neutron capture therapy (BNCT) is a type of radiation therapy for eradicating tumor cells through a ¹⁰B(n,α)⁷Li reaction in the presence of ¹⁰B in cancer cells. When delivering a high absorbed dose to cancer cells using BNCT, both the timeline of ¹⁰B concentrations and the relative long dose-delivery time compared to photon therapy must be considered. Changes in radiosensitivity during such a long dose-delivery time can reduce the probability of tumor control; however, such changes have not yet been evaluated. Here, we propose an improved integrated microdosimetric-kinetic model that accounts for changes in microdosimetric quantities and dose rates depending on the ¹⁰B concentration and investigate the cell recovery (dose-rate effects) of melanoma during BNCT irradiation. The integrated microdosimetric–kinetic model used in this study considers both sub-lethal damage repair and changes in microdosimetric quantities during irradiation. The model, coupled with the Monte Carlo track structure simulation code of the Particle and Heavy Ion Transport code System, shows good agreement with in vitro experimental data for acute exposure to ⁶⁰Co γ-rays, thermal neutrons, and BNCT with ¹⁰B concentrations of 10 ppm. This indicates that microdosimetric quantities are important parameters for predicting dose-response curves for cell survival under BNCT irradiations. Furthermore, the model estimation at the endpoint of the mean activation dose exhibits a reduced impact of cell recovery during BNCT irradiations with high linear energy transfer (LET) compared to ⁶⁰Co γ-rays irradiation with low LET. Throughout this study, we discuss the advantages of BNCT for enhancing the killing of cancer cells with a reduced dose-rate dependency. If the neutron spectrum and the timelines for drug and dose delivery are provided, the present model will make it possible to predict radiosensitivity for more realistic dose-delivery schemes in BNCT irradiations.

Intercellular communication after ionizing radiation exposure, so-called non-targeted effects (NTEs), reduces cell survival. Here we describe an integrated cell-killing model considering NTEs and DNA damage along radiation particle tracks, known as DNA-targeted effects (TEs) based on repair kinetics of DNA damage. The proposed model was applied to a series of experimental data, i.e., signal concentration, DNA damage kinetics, cell survival curve and medium transfer bystander effects (MTBEs). To reproduce the experimental data, the model considers the following assumptions: (i) the linear-quadratic (LQ) function as absorbed dose to express the hit probability to emit cell-killing signals, (ii) the potentially repair of DNA lesions induced by NTEs, and (iii) lower efficiency of repair for the damage in NTEs than that in TEs. By comparing the model results with experimental data, we found that signal-induced DNA damage and lower repair efficiency in non-hit cells are responsible for NTE-related repair kinetics of DNA damage, cell survival curve with low-dose hyper-radiosensitivity (HRS) and MTBEs. From the standpoint of modelling, the integrated cell-killing model with the LQ relation and a different repair function for NTEs provide a reasonable signal-emission probability and a new estimation of low-dose HRS linked to DNA repair efficiency.

We have investigated the dose rate effects on cell damage caused by photon-beam irradiation. During a relatively long dose-delivery time with a low dose rate, lesions created in cells may undergo some reactions, such as DNA repair. In order to investigate these reactions quantitatively, we adopted the microdosimetric–kinetic (MK) model and deduced a cell surviving fraction (SF) formula for continuous irradiation. This model enabled us to estimate the SF from dose and dose rate. The parameters in the MK model were determined so as to generate the SF, and we attempted to evaluate the dose rate effects on the SF. To deduce the cell-specific parameters in the SF formula, including the dose rate, we performed a split-dose experiment and a single-dose experiment with a constant dose-delivery time (10 min) (to retain the condition for equivalent behavior of cell lesions) by means of a clonogenic assay. Then, using the MK model parameters, the SFs were reproduced for a variety of dose rates (1.0, 0.31, 0.18, 0.025 and 0.0031 Gy/min) and were compared with reported experimental data. The SF curves predicted by the MK model agreed well with the experimental data, suggesting that the dose rate effects appear in the kinetics of cell lesions during the dose-delivery time. From fitting the analysis of the model formula to the experimental data, it was shown that the MK model could illustrate the characteristics of log-SF in a rectilinear form at a high dose range with a relatively low dose rate.