Integrated Modelling of Cell Responses after Irradiation for DNA-Targeted Effects and Non-Targeted Effects

LET-based approximation of the microdosimetric kinetic model for proton radiotherapy

BACKGROUND

Phenomenological relative biological effectiveness (RBE) models for proton therapy, based on the dose-averaged linear energy transfer (LET), have been developed to address the apparent RBE increase towards the end of the proton range. The results of these phenomenological models substantially differ due to varying empirical assumptions and fitting functions. In contrast, more theory-based approaches are used in carbon ion radiotherapy, such as the microdosimetric kinetic model (MKM). However, implementing microdosimetry-based models in LET-based proton therapy treatment planning systems poses challenges.

PURPOSE

This work presents a LET-based version of the MKM that is practical for clinical use in proton radiotherapy.

METHODS

At first, we derived an approximation of the Mayo Clinic Florida (MCF) MKM for relatively-sparsely ionizing radiation such as protons. The mathematical formalism of the proposed model is equivalent to the original MKM, but it maintains some key features of the MCF MKM, such as the determination of model parameters from measurable cell characteristics. Subsequently, we carried out Monte Carlo calculations with PHITS in different simulated scenarios to establish a heuristic correlation between microdosimetric quantities and the dose averaged LET of protons.

RESULTS

A simple allometric function was found able to describe the relationship between the dose-averaged LET of protons and the dose-mean lineal energy, which includes the contributions of secondary particles. The LET-based MKM was used to model the in vitro clonogenic survival RBE of five human and rodent cell lines (A549, AG01522, CHO, T98G, and U87) exposed to pristine and spread-out Bragg peak (SOBP) proton beams. The results of the LET-based MKM agree well with the biological data in a comparable or better way with respect to the other models included in the study. A sensitivity analysis on the model results was also performed.

CONCLUSIONS

The LET-based MKM integrates the predictive theoretical framework of the MCF MKM with a straightforward mathematical description of the RBE based on the dose-averaged LET, a physical quantity readily available in modern treatment planning systems for proton therapy.

The impact of dose rate on responses of human lens epithelial cells to ionizing irradiation

The knowledge on responses of human lens epithelial cells (HLECs) to ionizing radiation exposure is important to understand mechanisms of radiation cataracts that are of concern in the field of radiation protection and radiation therapy. However, biological effects in HLECs following protracted exposure have not yet fully been explored. Here, we investigated the temporal kinetics of γ-H2AX foci as a marker for DNA double-strand breaks (DSBs) and cell survival in HLECs after exposure to photon beams at various dose rates (i.e., 150 kVp X-rays at 1.82, 0.1, and 0.033 Gy/min, and 137Cs γ-rays at 0.00461 Gy/min (27.7 cGy/h) and 0.00081 Gy/min (4.9 cGy/h)), compared to those in human lung fibroblasts (WI-38). In parallel, we quantified the recovery for DSBs and cell survival using a biophysical model. The study revealed that HLECs have a lower DSB repair rate than WI-38 cells. There is no significant impact of dose rate on cell survival in both cell lines in the dose-rate range of 0.033-1.82 Gy/min. In contrast, the experimental residual γ-H2AX foci showed inverse dose rate effects (IDREs) compared to the model prediction, highlighting the importance of the IDREs in evaluating radiation effects on the ocular lens.

Formulation of Time-Dependent Cell Survival with Saturable Repairability of Radiation Damage

This study aims to provide a model that compounds historically proposed ideas regarding cell survival irradiated with X rays or particles. The parameters used in this model have simple meanings and are closely related to cell death-related phenomena. The model is adaptable to a wide range of doses and dose rates and thus can consistently explain previously published cell survival data. The formulas of the model were derived by using five basic ideas: 1. "Poisson's law"; 2. "DNA affected damage"; 3. "repair"; 4. "clustered affected damage"; and 5. "saturation of reparability". The concept of affected damage is close to but not the same as the effect caused by the double-strand break (DSB). The parameters used in the formula are related to seven phenomena: 1. "linear coefficient of radiation dose"; 2. "probability of making affected damage"; 3. "cell-specific repairability", 4. "irreparable damage by adjacent affected damage"; 5. "recovery of temporally changed repairability"; 6. "recovery of simple damage which will make the affected damage"; 7. "cell division". By using the second parameter, this model includes cases where a single hit results in repairable-lethal and double-hit results in repairable-lethal. The fitting performance of the model for the experimental data was evaluated based on the Akaike information criterion, and practical results were obtained for the published experiments irradiated with a wide range of doses (up to several 10 Gy) and dose rates (0.17 Gy/h to 55.8 Gy/h). The direct association of parameters with cell death-related phenomena has made it possible to systematically fit survival data of different cell types and different radiation types by using crossover parameters.

High-LET-Radiation-Induced Persistent DNA Damage Response Signaling and Gastrointestinal Cancer Development

Ionizing radiation (IR) dose, dose rate, and linear energy transfer (LET) determine cellular DNA damage quality and quantity. High-LET heavy ions are prevalent in the deep space environment and can deposit a much greater fraction of total energy in a shorter distance within a cell, causing extensive DNA damage relative to the same dose of low-LET photon radiation. Based on the DNA damage tolerance of a cell, cellular responses are initiated for recovery, cell death, senescence, or proliferation, which are determined through a concerted action of signaling networks classified as DNA damage response (DDR) signaling. The IR-induced DDR initiates cell cycle arrest to repair damaged DNA. When DNA damage is beyond the cellular repair capacity, the DDR for cell death is initiated. An alternative DDR-associated anti-proliferative pathway is the onset of cellular senescence with persistent cell cycle arrest, which is primarily a defense mechanism against oncogenesis. Ongoing DNA damage accumulation below the cell death threshold but above the senescence threshold, along with persistent SASP signaling after chronic exposure to space radiation, pose an increased risk of tumorigenesis in the proliferative gastrointestinal (GI) epithelium, where a subset of IR-induced senescent cells can acquire a senescence-associated secretory phenotype (SASP) and potentially drive oncogenic signaling in nearby bystander cells. Moreover, DDR alterations could result in both somatic gene mutations as well as activation of the pro-inflammatory, pro-oncogenic SASP signaling known to accelerate adenoma-to-carcinoma progression during radiation-induced GI cancer development. In this review, we describe the complex interplay between persistent DNA damage, DDR, cellular senescence, and SASP-associated pro-inflammatory oncogenic signaling in the context of GI carcinogenesis.

Application of a simple DNA damage model developed for electrons to proton irradiation

Proton beam therapy allows irradiating tumor volumes with reduced side effects on normal tissues with respect to conventional x-ray radiotherapy. Biological effects such as cell killing after proton beam irradiations depend on the proton kinetic energy, which is intrinsically related to early DNA damage induction. As such, DNA damage estimation based on Monte Carlo simulations is a research topic of worldwide interest. Such simulation is a mean of investigating the mechanisms of DNA strand break formations. However, past modellings considering chemical processes and DNA structures require long calculation times. Particle and heavy ion transport system (PHITS) is one of the general-purpose Monte Carlo codes that can simulate track structure of protons, meanwhile cannot handle radical dynamics simulation in liquid water. It also includes a simple model enabling the efficient estimation of DNA damage yields only from the spatial distribution of ionizations and excitations without DNA geometry, which was originally developed for electron track-structure simulations. In this study, we investigated the potential application of the model to protons without any modification. The yields of single-strand breaks, double-strand breaks (DSBs) and the complex DSBs were assessed as functions of the proton kinetic energy. The PHITS-based estimation showed that the DSB yields increased as the linear energy transfer (LET) increased, and reproduced the experimental and simulated yields of various DNA damage types induced by protons with LET up to about 30 keV μm−1. These results suggest that the current DNA damage model implemented in PHITS is sufficient for estimating DNA lesion yields induced after protons irradiation except at very low energies (below 1 MeV). This model contributes to evaluating early biological impacts in radiation therapy.

Datasets of in vitro clonogenic assays showing low dose hyper-radiosensitivity and induced radioresistance

Low dose hyper-radiosensitivity and induced radioresistance are primarily observed in surviving fractions of cell populations exposed to ionizing radiation, plotted as the function of absorbed dose. Several biophysical models have been developed to quantitatively describe these phenomena. However, there is a lack of raw, openly available experimental data to support the development and validation of quantitative models. The aim of this study was to set up a database of experimental data from the public literature. Using Google Scholar search, 46 publications with 101 datasets on the dose-dependence of surviving fractions, with clear evidence of low dose hyper-radiosensitivity, were identified. Surviving fractions, their uncertainties, and the corresponding absorbed doses were digitized from graphs of the publications. The characteristics of the cell line and the irradiation were also recorded, along with the parameters of the linear-quadratic model and/or the induced repair model if they were provided. The database is available in STOREDB, and can be used for meta-analysis, for comparison with new experiments, and for development and validation of biophysical models.

Radiobiology of stereotactic radiotherapy

This paper focuses on the radiobiological mechanisms underlying the effects of stereotactic radiotherapy (SRT ) which, despite SRT expansion, have not yet been fully elucidated. Some authors postulated that radiobiology principles, as applied to conventional fractionations (5R: reoxygenation, repair, repopulation, redistribution, radioresistence), suffice in themselves to account for the excellent clinical results of SRT; others argued that the role of the 5R was limited. Recent preclinical data showed that hypofractionated ablative treatments altered the microenvironment, thus determining cell death either directly or indirectly. Furthermore, dead tumor cells released quantities of antigens, which stimulated antitumor immunity, thus reducing the risk of relapse and metastasis. Better understanding of the radiobiological mechanisms underlying response to high-dose radiation treatment is essential for predicting its short- and long-term effects on the tumor and surrounding healthy tissues and, consequently, for improving its related therapeutic index.

Improving astronaut cancer risk assessment from space radiation with an ensemble model framework

A new approach to NASA space radiation risk modeling has successfully extended the current NASA probabilistic cancer risk model to an ensemble framework able to consider sub-model parameter uncertainty as well as model-form uncertainty associated with differing theoretical or empirical formalisms. Ensemble methodologies are already widely used in weather prediction, modeling of infectious disease outbreaks, and certain terrestrial radiation protection applications to better understand how uncertainty may influence risk decision-making. Applying ensemble methodologies to space radiation risk projections offers the potential to efficiently incorporate emerging research results, allow for the incorporation of future models, improve uncertainty quantification, and reduce the impact of subjective bias. Moreover, risk forecasting across an ensemble of multiple predictive models can provide stakeholders additional information on risk acceptance if current health/medical standards cannot be met for future space exploration missions, such as human missions to Mars. In this work, ensemble risk projections implementing multiple sub-models of radiation quality, dose and dose-rate effectiveness factors, excess risk, and latency are presented. Initial consensus methods for ensemble model weights and correlations to account for individual model bias are discussed. In these analyses, the ensemble forecast compares well to results from NASA's current operational cancer risk projection model used to assess permissible mission durations for astronauts. However, a large range of projected risk values are obtained at the upper 95th confidence level where models must extrapolate beyond available biological data sets. Closer agreement is seen at the median ± one sigma due to the inherent similarities in available models. Identification of potential new models, epidemiological data, and methods for statistical correlation between predictive ensemble members are discussed. Alternate ways of communicating risk and acceptable uncertainty with respect to NASA's current permissible exposure limits are explored.

Implementation of simplified stochastic microdosimetric kinetic models into PHITS for application to radiation treatment planning

PURPOSE

The stochastic microdosimetric kinetic (SMK) model is one of the most sophisticated and precise models used in the estimation of the relative biological effectiveness of carbon-ion radiotherapy (CRT) and boron neutron capture therapy (BNCT). However, because of its complicated and time-consuming calculation procedures, it is nearly impractical to directly incorporate this model into a radiation treatment-planning system.

MATERIALS AND METHODS

Through the introduction of Taylor expansion (TE) or fast Fourier transform (FFT), we developed two simplified SMK models and implemented them into the Particle and Heavy Ion Transport code System (PHITS). To verify the implementation, we calculated the photon isoeffective doses in a cylindrical phantom placed in the radiation fields of passive CRT and accelerator-based BNCT.

RESULTS AND DISCUSSION

Our calculation suggested that both TE-based and FFT-based SMK models can reproduce the data obtained from the original SMK model very well for absorbed doses approximately below 5 Gy, whereas the TE-based SMK model overestimates the original data at higher doses. In terms of computational efficiency, the TE-based SMK model is much faster than the FFT-based SMK model.

CONCLUSION

This study enables the instantaneous calculation of the photo isoeffective dose for CRT and BNCT, considering their cellular-scale dose heterogeneities. Treatment-planning systems that use the improved PHITS as a dose-calculation engine are under development.

A "Failed" Assay Development for the Discovery of Rescuing Small Molecules from the Radiation Damage

With improving survival rates for cancer patients, the side effects of radiation therapy, especially for pediatric or more sensitive adult patients, have raised interest in preventive or rescue treatment to overcome the detrimental effects of efficient radiation therapies. For the discovery of rescuing small molecules for radiation damage to the endothelium, we have been developing a 96-well microplate-based in vitro assay for high-throughput compatible measurement of radiation-induced cell damage and its rescue by phenotypic high-content imaging. In contrast to traditional radiation assays with detached cells for clonogenic formation, we observed cells with live-cell imaging in two different kinds of endothelial cells, up to three different cell densities, two gamma-infrared radiation dose rates, more than four different radiation doses, and acute (within 24 h with one to two h intervals) and chronic (up to 7 days) responses by phenotypic changes (digital phase contrast) and functional assays (nuclear, live-cell, and dead-cell staining) at the end of the assay. Multiple potential small molecules, which have been reported for rescuing radiation damage, have been tested as assay controls with dose responses. At the end, we did not move ahead with the pilot screening. The lessons learned from this "failed" assay development are shared.

4-Methylumbelliferone administration enhances radiosensitivity of human fibrosarcoma by intercellular communication

Hyaluronan synthesis inhibitor 4-methylumbelliferone (4-MU) is a candidate of radiosensitizers which enables both anti-tumour and anti-metastasis effects in X-ray therapy. The curative effects under such 4-MU administration have been investigated in vitro; however, the radiosensitizing mechanisms remain unclear. Here, we investigated the radiosensitizing effects under 4-MU treatment from cell experiments and model estimations. We generated experimental surviving fractions of human fibrosarcoma cells (HT1080) after 4-MU treatment combined with X-ray irradiation. Meanwhilst, we also modelled the pharmacological effects of 4-MU treatment and theoretically analyzed the synergetic effects between 4-MU treatment and X-ray irradiation. The results show that the enhancement of cell killing by 4-MU treatment is the greatest in the intermediate dose range of around 4 Gy, which can be reproduced by considering intercellular communication (so called non-targeted effects) through the model analysis. As supposed to be the involvement of intercellular communication in radiosensitization, the oxidative stress level associated with reactive oxygen species (ROS), which leads to DNA damage induction, is significantly higher by the combination of 4-MU treatment and irradiation than only by X-ray irradiation, and the radiosensitization by 4-MU can be suppressed by the ROS inhibitors. These findings suggest that the synergetic effects between 4-MU treatment and irradiation are predominantly attributed to intercellular communication and provide more efficient tumour control than conventional X-ray therapy.

Development of a new microdosimetric biological weighting function for the RBE10 assessment in case of the V79 cell line exposed to ions from 1H to 238U

An improved biological weighting function (IBWF) is proposed to phenomenologically relate microdosimetric lineal energy probability density distributions with the relative biological effectiveness (RBE) for the in vitro clonogenic cell survival (surviving fraction = 10%) of the most commonly used mammalian cell line, i.e. the Chinese hamster lung fibroblasts (V79). The IBWF, intended as a simple and robust tool for a fast RBE assessment to compare different exposure conditions in particle therapy beams, was determined through an iterative global-fitting process aimed to minimize the average relative deviation between RBE calculations and literature in vitro data in case of exposure to various types of ions from ¹H to ²³⁸U. By using a single particle- and energy- independent function, it was possible to establish an univocal correlation between lineal energy and clonogenic cell survival for particles spanning over an unrestricted linear energy transfer range of almost five orders of magnitude (0.2 keV µm^-1 to 15 000 keV µm^-1 in liquid water). The average deviation between IBWF-derived RBE values and the published in vitro data was ∼14%. The IBWF results were also compared with corresponding calculations (in vitro RBE₁₀ for the V79 cell line) performed using the modified microdosimetric kinetic model (modified MKM). Furthermore, RBE values computed with the reference biological weighting function (BWF) for the in vivo early intestine tolerance in mice were included for comparison and to further explore potential correlations between the BWF results and the in vitro RBE as reported in previous studies. The results suggest that the modified MKM possess limitations in reproducing the experimental in vitro RBE₁₀ for the V79 cell line in case of ions heavier than ²⁰Ne. Furthermore, due to the different modelled endpoint, marked deviations were found between the RBE values assessed using the reference BWF and the IBWF for ions heavier than ²H. Finally, the IBWF was unchangingly applied to calculate RBE values by processing lineal energy density distributions experimentally measured with eight different microdosimeters in 19 ¹H and ¹²C beams at ten different facilities (eight clinical and two research ones). Despite the differences between the detectors, irradiation facilities, beam profiles (pristine or spread out Bragg peak), maximum beam energy, beam delivery (passive or active scanning), energy degradation system (water, PMMA, polyamide or low-density polyethylene), the obtained IBWF-based RBE trends were found to be in good agreement with the corresponding ones in case of computer-simulated microdosimetric spectra (average relative deviation equal to 0.8% and 5.7% for ¹H and ¹²C ions respectively).

Modelling Dose Effects from Space Irradiations: Combination of High-LET and Low-LET Radiations with a Modified Microdosimetric Kinetic Model

The Microdosimetric Kinetic Model (MKM) to predict the effects of ionizing radiation on cell colonies is studied and reformulated for the case of high-linear energy transfer (LET) radiations with a low dose. When the number of radiation events happening in a subnuclear domain follows a Poisson distribution, the MKM predicts a linear-quadratic (LQ) survival curve. We show that when few events occur, as for high-LET radiations at doses lower than the mean specific energy imparted to the nucleus, zF,n, a Poisson distribution can no longer be assumed and an initial pure linear relationship between dose and survival fraction should be observed. Predictions of survival curves for combinations of high-LET and low-LET radiations are produced under two assumptions for their comparison: independent and combined action. Survival curves from previously published articles of V79 cell colonies exposed to X-rays, α particles, Ar-ions, Fe-ions, Ne-ions and mixtures of X-rays and each one of the ions are predicted according to the modified MKM. We conclude that mixtures of high-LET and low-LET radiations may enhance the effect of individual actions due to the increase of events in domains provided by the low-LET radiation. This hypothesis is only partially validated by the analyzed experiments.

A model of radiation action based on nanodosimetry and the application to ultra-soft X-rays

A radiation action model based on nanodosimetry is presented. It is motivated by the finding that the biological effects of various types of ionizing radiation lack a consistent relation with absorbed dose. It is postulated that the common fundamental cause of these effects is the production of elementary sublesions (DSB), which are created at a rate that is proportional to the probability to produce more than two ionisations within a volume of 10 base pairs of the DNA. The concepts of nanodosimetry allow for a quantitative characterization of this process in terms of the cumulative probability F₂. The induced sublesions can interact in two ways to produce lethal damage. First, if two or more sublesions accumulate in a locally limited spherical volume of 3-10 nm in diameter, clustered DNA damage is produced. Second, consequent interactions or rearrangements of some of the initial damage over larger distances (~ µm) can produce additional lethal damage. From the comparison of theoretical predictions deduced from this concept with experimental data on relative biological effectiveness, a cluster volume with a diameter of 7.5 nm could be determined. It is shown that, for electrons, the predictions agree well with experimental data over a wide energy range. The only free parameter needed to model cell survival is the intersection cross-section which includes all relevant cell-specific factors. Using ultra-soft X-rays it could be shown that the energy dependence of cell survival is directly governed by the nanodosimetric characteristics of the radiation track structure. The cell survival model derived in this work exhibits exponential cell survival at a high dose and a finite gradient of cell survival at vanishing dose, as well as the dependence on dose-rate.

A Model for Estimating Dose-Rate Effects on Cell-Killing of Human Melanoma after Boron Neutron Capture Therapy

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.

A theoretical cell-killing model to evaluate oxygen enhancement ratios at DNA damage and cell survival endpoints in radiation therapy

Radio-resistance induced under low oxygen pressure plays an important role in malignant progression in fractionated radiotherapy. For the general approach to predict cell killing under hypoxia, cell-killing models (e.g. the Linear-Quadratic model) have to be fitted to in vitro experimental survival data for both normoxia and hypoxia to obtain the oxygen enhancement ratio (OER). In such a case, model parameters for every oxygen condition needs to be considered by model-fitting approaches. This is inefficient for fractionated irradiation planning. Here, we present an efficient model for fractionated radiotherapy the integrated microdosimetric-kinetic model including cell-cycle distribution and the OER at DNA double-strand break endpoint (OER_DSB). The cell survival curves described by this model can reproduce the in vitro experimental survival data for both acute and chronic low oxygen concentrations. The OER_DSB used for calculating cell survival agrees well with experimental DSB ratio of normoxia to hypoxia. The important parameters of the model are oxygen pressure and cell-cycle distribution, which enables us to predict cell survival probabilities under chronic hypoxia and chronic anoxia. This work provides biological effective dose (BED) under various oxygen conditions including its uncertainty, which can contribute to creating fractionated regimens for multi-fractionated radiotherapy. If the oxygen concentration in a tumor can be quantified by medical imaging, the present model will make it possible to estimate the cell-killing and BED under hypoxia in more realistic intravital situations.

Coupling of cell fate selection model enhances DNA damage response and may underlie BE phenomenon

Double-strand break-induced (DSB) cells send signal that induces DSBs in neighbour cells, resulting in the interaction among cells sharing the same medium. Since p53 network gives oscillatory response to DSBs, such interaction among cells could be modelled as an excitatory coupling of p53 network oscillators. This study proposes a plausible coupling model of three-mode two-dimensional oscillators, which models the p53-mediated cell fate selection in globally coupled DSB-induced cells. The coupled model consists of ATM and Wip1 proteins as variables. The coupling mechanism is realised through ATM variable via a mean-field modelling the bystander signal in the intercellular medium. Investigation of the model reveals that the coupling generates more sensitive DNA damage response by affecting cell fate selection. Additionally, the authors search for the cause-effect relationship between coupled p53 network oscillators and bystander effect (BE) endpoints. For this, they search for the possible values of uncertain parameters that may replicate BE experiments' results. At certain parametric regions, there is a correlation between the outcomes of cell fate and endpoints of BE, suggesting that the intercellular coupling of p53 network may manifest itself as the form of observed BEs.

Nitric Oxide Is Involved in Heavy Ion-Induced Non-Targeted Effects in Human Fibroblasts

Previously, we investigated the dose response for chromosomal aberration (CA) for exposures corresponding to less than one particle traversal per cell nucleus by high energy and charge (HZE) particles, and showed that the dose responses for simple exchanges for human fibroblast irradiated under confluent culture conditions were best fit by non-linear models motivated by a non-targeted effect (NTE). Our results suggested that the simple exchanges in normal human fibroblasts have an important NTE contribution at low particle fluence. Nitric oxide (NO) has been reported as a candidate for intercellular signaling for NTE in many studies. In order to estimate the contribution of NTE components in induced CA, we measured CA with and without an NO scavenger in normal skin fibroblasts cells after exposure to 600 MeV/u and 1 GeV/u 56Fe ions, less than one direct particle traversal per cell nucleus. Yields of CA were significantly lower in fibroblasts exposed to the NO scavenger compared to controls, suggesting involvement of NO in cell signaling for induction of CA. Media transferred from irradiated cells induced CA in non-irradiated cells, and this effect was abrogated with NO scavengers. Our results strongly support the importance of NTE contributions in the formation of CA at low-particle fluence in fibroblasts.

Intensity Modulated Radiation Fields Induce Protective Effects and Reduce Importance of Dose-Rate Effects

In advanced radiotherapy, intensity modulated radiation fields and complex dose-delivery are utilized to prescribe higher doses to tumours. Here, we investigated the impact of modulated radiation fields on radio-sensitivity and cell recovery during dose delivery. We generated experimental survival data after single-dose, split-dose and fractionated irradiation in normal human skin fibroblast cells (AGO1522) and human prostate cancer cells (DU145). The dose was delivered to either 50% of the area of a T25 flask containing the cells (half-field) or 100% of the flask (uniform-field). We also modelled the impact of dose-rate effects and intercellular signalling on cell-killing. Applying the model to the survival data, it is found that (i) in-field cell survival under half-field exposure is higher than uniform-field exposure for the same delivered dose; (ii) the importance of sub-lethal damage repair (SLDR) in AGO1522 cells is reduced under half-field exposure; (iii) the yield of initial DNA lesions measured with half-field exposure is smaller than that with uniform-field exposure. These results suggest that increased cell survival under half-field exposure is predominantly attributed not to rescue effects (increased SLDR) but protective effects (reduced induction of initial DNA lesions). In support of these protective effects, the reduced DNA damage leads to modulation of cell-cycle dynamics, i.e., less G₁ arrest 6 h after irradiation. These findings provide a new understanding of the impact of dose-rate effects and protective effects measured after modulated field irradiation.

Analysis of the high-dose-range radioresistance of prostate cancer cells, including cancer stem cells, based on a stochastic model

In radiotherapy, cancer stem cells (CSCs) are well recognized as one of the radioresistant cell types. Even in a small subpopulation, CSCs may have an influence on tumor control probability, represented by cell killing after irradiation. However, the relationship between the percentage content of CSCs and the cell survival dose-response curve has not yet been quantitatively clarified. In this study, we developed a cell-killing model for two cell populations (CSCs and progeny cells) to predict the surviving fractions, and compared it with the conventional linear-quadratic (LQ) model. Three prostate cancer cell lines (DU145, PC3 and LNCaP) were exposed to X-rays at doses ranging from 0 to 10 Gy. After the irradiation, we performed clonogenic survival assays to generate the cell survival curves, and carried out flow-cytometric analyses to estimate the percentage content of CSCs for each cell line. The cell survival curves for DU145 cells and PC3 cells seemed not to follow the conventional LQ model in the high dose range (>8 Gy). However, the outputs of the developed model agreed better with the experimental cell survival curves than those of the LQ model. The percentage content of CSCs predicted by the developed model was almost coincident with the measured percentage content for both DU145 cells and PC3 cells. The experiments and model analyses indicate that a small subpopulation of radioresistant CSCs has lower radiosensitivity in the high-dose range, which may lessen the clinical outcome for patients with prostate cancer after high-dose radiation therapy.