Comprehensive track-structure based evaluation of DNA damage by light ions from radiotherapy-relevant energies down to stopping

Comparison between the results of a recently-developed biological weighting function (V79-RBE10BWF) and thein vitroclonogenic survival RBE10of other repair-competent asynchronized normoxic mammalian cell lines and ions not used for the development of the model

728 simulated microdosimetric lineal energy spectra (26 different ions between 1H and 238U, 28 energy points from 1 to 1000 MeV/n) were used in combination with a recently-developed biological weighting function (Parisi et al., 2020) and 571 published in vitro clonogenic survival curves in order to: 1) assess prediction intervals for the in silico results by deriving an empirical indication of the experimental uncertainty from the dispersion in the in vitro hamster lung fibroblast (V79) data used for the development of the biophysical model; 2) explore the possibility of modeling the relative biological effectiveness (RBE) of the 10% clonogenic survival of asynchronized normoxic repair-competent mammalian cell lines other than the one used for the development of the model (V79); 3) investigate the predictive power of the model through a comparison between in silico results and in vitro data for 10 ions not used for the development of the model. At first, different strategies for the assessment of the in silico prediction intervals were compared. The possible sources of uncertainty responsible for the dispersion in the in vitro data were also shortly reviewed. Secondly, also because of the relevant scatter in the in vitro data, no statistically-relevant differences were found between the RBE10 of the investigated different asynchronized normoxic repair-competent mammalian cell lines. The only exception (Chinese Hamster peritoneal fibroblasts, B14FAF28), is likely due to the limited dataset (all in vitro ion data were extracted from a single publication), systematic differences in the linear energy transfer (LET) calculations for the employed very-heavy ions, and the use of reference photon survival curves extracted from a different publication. Finally, the in silico predictions for the 10 ions not used for the model development were in good agreement with the corresponding in vitro data.

Combined DNA Damage Repair Interference and Ion Beam Therapy: Development, Benchmark, and Clinical Implications of a Mechanistic Biological Model

PURPOSE

Our purpose was to develop a mechanistic model that describes and predicts radiation response after combined DNA damage repair interference (DDRi) and particle radiation therapy.

METHODS AND MATERIALS

The heterogeneous dose distributions of protons and ⁴He ions were implemented into the "UNIfied and VERSatile bio-response Engine" (UNIVERSE). Predictions for monoenergetic and mixed fields over clinically relevant dose and linear energy transfer range were compared with experimental in vitro survival data measured in this work as well as data available in the literature, including different cell lines and DDR interferences. Ultimately, UNIVERSE predictions were investigated in a patient plan.

RESULTS

UNIVERSE accurately predicts survival of cell lines with and without DDRi in clinical settings of ion beam therapy based only on 3 parameters derived from photon data. With increasing dose or linear energy transfer, the radiosensitizing effect of DDRi decreases, resulting in diminished relative biological effect of ion beam radiation for cells subjected to DDRi in comparison to cells that are not. Similar trends were observed in patient plan recalculations; however, this analysis also suggests that DDRi + particle radiation therapy may better preserve the therapeutic window in comparison to DDRi + photon radiation therapy.

CONCLUSIONS

The presented framework represents the first mechanistic model of combined DDRi and particle radiation therapy comprehensively benchmarked in clinically relevant scenarios and a step toward more personalized treatment. It reveals potential differences between DDRi + photon radiation therapy versus DDRi + particle radiation therapy, which have not been described so far. UNIVERSE could aid in appraising the clinical viability of combined administration of radiosensitizing drugs and charged particle therapy, as well as the identification of patients with known DDR deficiencies in the tumor who might benefit from therapy with light ions, freeing limited space at heavy ion therapy centers.

Modeling of cellular response after FLASH irradiation: a quantitative analysis based on the radiolytic oxygen depletion hypothesis

Purpose.Recent studies suggest ultra-high dose rate (FLASH) irradiation can spare normal tissues from radiotoxicity, while efficiently controlling the tumor, and this is known as the 'FLASH effect'. This study performed theoretical analyses about the impact of radiolytic oxygen depletion (ROD) on the cellular responses after FLASH irradiation.Methods.Monte Carlo simulation was used to model the ROD process, determine the DNA damage, and calculate the amount of oxygen depleted (L_ROD) during FLASH exposure. A mathematical model was applied to analyze oxygen tension (pO₂) distribution in human tissues and the recovery of pO₂after FLASH irradiation. DNA damage and cell survival fractions (SFs) after FLASH irradiation were calculated. The impact of initial cellular pO₂, FLASH pulse number, pulse interval, and radiation quality of the source particles on ROD and subsequent cellular responses were systematically evaluated.Results.The simulated electronL_RODrange was 0.38-0.43μM Gy^-1when pO₂ranged from 7.5 to 160 mmHg. The calculated DNA damage and SFs show that the radioprotective effect is only evident in cells with a low pO₂. Different irradiation setups alter the cellular responses by modifying the pO₂. Single pulse delivery or multi-pulse delivery with pulse intervals shorter than 10-50 ms resulted in fewer DNA damages and higher SFs. Source particles with a low linear energy transfer (LET) have a higher capacity to deplete oxygen, and thus, lead to a more conspicuous radioprotective effect.Conclusions. A systematic analysis of the cellular response following FLASH irradiation was performed to provided suggestions for future FLASH applications. The FLASH radioprotective effect due to ROD may only be observed in cells with a low pO₂. Single pulse delivery or multi-pulse delivery with short pulse intervals are suggested for FLASH irradiation to avoid oxygen tension recovery during pulse intervals. Source particles with low LET are preferred for their conspicuous radioprotective effects.

TOPAS-nBio validation for simulating water radiolysis and DNA damage under low-LET irradiation

The chemical stage of the Monte Carlo track-structure simulation code Geant4-DNA has been revised and validated. The root-mean-square (RMS) empirical parameter that dictates the displacement of water molecules after an ionization and excitation event in Geant4-DNA has been shortened to better fit experimental data. The pre-defined dissociation channels and branching ratios were not modified, but the reaction rate coefficients for simulating the chemical stage of water radiolysis were updated. The evaluation of Geant4-DNA was accomplished with TOPAS-nBio. For that, we compared predicted time-dependentGvalues in pure liquid water for^·OH, e^-_aq, and H₂with published experimental data. For H₂O₂and H^·, simulation of added scavengers at different concentrations resulted in better agreement with measurements. In addition, DNA geometry information was integrated with chemistry simulation in TOPAS-nBio to realize reactions between radiolytic chemical species and DNA. This was used in the estimation of the yield of single-strand breaks (SSB) induced by¹³⁷Csγ-ray radiolysis of supercoiled pUC18 plasmids dissolved in aerated solutions containing DMSO. The efficiency of SSB induction by reaction between radiolytic species and DNA used in the simulation was chosen to provide the best agreement with published measurements. An RMS displacement of 1.24 nm provided agreement with measured data within experimental uncertainties for time-dependentGvalues and under the presence of scavengers. SSB efficiencies of 24% and 0.5% for^·OH and H^·, respectively, led to an overall agreement of TOPAS-nBio results within experimental uncertainties. The efficiencies obtained agreed with values obtained with published non-homogeneous kinetic model and step-by-step Monte Carlo simulations but disagreed by 12% with published direct measurements. Improvement of the spatial resolution of the DNA damage model might mitigate such disagreement. In conclusion, with these improvements, Geant4-DNA/TOPAS-nBio provides a fast, accurate, and user-friendly tool for simulating DNA damage under low linear energy transfer irradiation.

Models for Translational Proton Radiobiology-From Bench to Bedside and Back

The number of proton therapy centers worldwide are increasing steadily, with more than two million cancer patients treated so far. Despite this development, pending questions on proton radiobiology still call for basic and translational preclinical research. Open issues are the on-going discussion on an energy-dependent varying proton RBE (relative biological effectiveness), a better characterization of normal tissue side effects and combination treatments with drugs originally developed for photon therapy. At the same time, novel possibilities arise, such as radioimmunotherapy, and new proton therapy schemata, such as FLASH irradiation and proton mini-beams. The study of those aspects demands for radiobiological models at different stages along the translational chain, allowing the investigation of mechanisms from the molecular level to whole organisms. Focusing on the challenges and specifics of proton research, this review summarizes the different available models, ranging from in vitro systems to animal studies of increasing complexity as well as complementing in silico approaches.

Involvement of HIF-1α in the Detection, Signaling, and Repair of DNA Double-Strand Breaks after Photon and Carbon-Ion Irradiation

Simple Summary

Hypoxia-Inducible Factor 1α (HIF-1α), the main regulator of the oxygen homeostasis, promotes cancer cell survival through proliferation, angiogenesis, metastasis and radioresistance. Previously, our group demonstrated that silencing HIF-1α under hypoxia leads to a substantial radiosensitization of Head-and-Neck Squamous Cell Carcinoma (HNSCC) cells after both photons and carbon-ions, probably resulting from an accumulation of deleterious complex DNA damage. In this study, we aimed at determining the potential role of HIF-1α in the detection, signaling, and repair of DNA Double-Strand-Breaks (DSBs) in response to both irradiations, under hypoxia, in two HNSCC cell lines and their subpopulations of Cancer-Stem Cells (CSCs). Silencing HIF-1α under hypoxia led us to demonstrate the involvement of this transcriptional regulator in DSB repair in non-CSCS and CSC, thus highlighting its targeting together with radiation as a promising therapeutic strategy against radioresistant tumor cells in hypoxic niches.

Abstract

Hypoxia-Inducible Factor 1α (HIF-1α), which promotes cancer cell survival, is the main regulator of oxygen homeostasis. Hypoxia combined with photon and carbon ion irradiation (C-ions) stabilizes HIF-1α. Silencing HIF-1α under hypoxia leads to substantial radiosensitization of Head-and-Neck Squamous Cell Carcinoma (HNSCC) cells after both photons and C-ions. Thus, this study aimed to clarify a potential involvement of HIF-1α in the detection, signaling, and repair of DNA Double-Strand-Breaks (DSBs) in response to both irradiations, in two HNSCC cell lines and their subpopulations of Cancer-Stem Cells (CSCs). After confirming the nucleoshuttling of HIF-1α in response to both exposure under hypoxia, we showed that silencing HIF-1α in non-CSCs and CSCs decreased the initiation of the DSB detection (P-ATM), and increased the residual phosphorylated H2AX (γH2AX) foci. While HIF-1α silencing did not modulate 53BP1 expression, P-DNA-PKcs (NHEJ-c) and RAD51 (HR) signals decreased. Altogether, our experiments demonstrate the involvement of HIF-1α in the detection and signaling of DSBs, but also in the main repair pathways (NHEJ-c and HR), without favoring one of them. Combining HIF-1α silencing with both types of radiation could therefore present a potential therapeutic benefit of targeting CSCs mostly present in tumor hypoxic niches.

Development of a DNA damage model that accommodates different cellular oxygen concentrations and radiation qualities

PURPOSE

Research regarding cellular responses at different oxygen concentrations (OCs) is of immense interest within the field of radiobiology. Therefore, this study aimed to develop a mechanistic model to analyze cellular responses at different OCs.

METHODS

A DNA damage model (the different cell oxygen level DNA damage [DICOLDD] model) that examines the oxygen effect was developed based on the oxygen fixation hypothesis, which states that dissolved oxygen can modify the reaction kinetics of DNA-derived radicals generated by ionizing radiation. The generation of DNA-derived radicals was simulated using the Monte Carlo method. The decay of DNA-derived radicals due to the competing processes of chemical repair, oxygen fixation, and intrinsic damaging was described using differential equations. The DICOLDD model was fitted to the previous experimental data obtained under different irradiation configurations and validated by calculating the yields of DNA double-strand breaks (DSBs) after exposure to ¹³⁷ Cs as well as cell survival fractions (SFs) using a mechanistic model of cellular survival. Moreover, we used the DICOLDD model to calculate DNA DSB damage yields after irradiation with 0.5-50 MeV protons.

RESULTS

Generally, DSB yields calculated after exposure to ¹³⁷ Cs at different OCs correspond to statistical uncertainties of previous experimental results. Calculated SFs of CHO and V79 cells exposed to photons, protons, and alpha particles at different OCs generally concur with those obtained in previous studies. Our results demonstrated that the variation in DSB yields was less than 10% when the cellular OC decreased from 21% to 5%. Additionally, DSB yields changed drastically when OC dropped below 1%.

CONCLUSIONS

We developed a DNA damage model to evaluate the oxygen effect and provide evidence that a reaction-kinetic model of DNA-derived radicals induced by ionizing radiation suffices to explain the observed oxygen effects. Therefore, the DICOLDD model is a powerful tool for the analysis of cellular responses at different OCs after exposure to different types of radiation.

DNA double-strand breaks in cancer cells as a function of proton linear energy transfer and its variation in time

PURPOSE

The complex relationship between linear energy transfer (LET) and cellular response to radiation is not yet fully elucidated. To better characterize DNA damage after irradiations with therapeutic protons, we monitored formation and disappearance of DNA double-strand breaks (DNA DSB) as a function of LET and time. Comparisons with conventional γ-rays and high LET carbon ions were also performed.

MATERIALS AND METHODS

In the present work, we performed immunofluorescence-based assay to determine the amount of DNA DSB induced by different LET values along the 62 MeV therapeutic proton Spread out Bragg peak (SOBP) in three cancer cell lines, i.e. HTB140 melanoma, MCF-7 breast adenocarcinoma and HTB177 non-small lung cancer cells. Time dependence of foci formation was followed as well. To determine irradiation positions, corresponding to the desired LET values, numerical simulations were carried out using Geant4 toolkit. We compared γ-H2AX foci persistence after irradiations with protons to that of γ-rays and carbon ions.

RESULTS

With the rise of LET values along the therapeutic proton SOBP, the increase of γ-H2AX foci number is detected in the three cell lines up to the distal end of the SOBP, while there is a decrease on its distal fall-off part. With the prolonged incubation time, the number of foci gradually drops tending to attain the residual level. For the maximum number of DNA DSB, irradiation with protons attain higher level than that of γ-rays. Carbon ions produce more DNA DSB than protons but not substantially. The number of residual foci produced by γ-rays is significantly lower than that of protons and particularly carbon ions. Carbon ions do not produce considerably higher number of foci than protons, as it could be expected due to their physical properties.

CONCLUSIONS

In situ visualization of γ-H2AX foci reveal creation of more lesions in the three cell lines by clinically relevant proton SOBP than γ-rays. The lack of significant differences in the number of γ-H2AX foci between the proton and carbon ion-irradiated samples suggests an increased complexity of DNA lesions and slower repair kinetics after carbon ions compared to protons. For all three irradiation types, there is no major difference between the three cell lines shortly after irradiations, while later on, the formation of residual foci starts to express the inherent nature of tested cells, therefore increasing discrepancy between them.

A Mechanistic DNA Repair and Survival Model (Medras): Applications to Intrinsic Radiosensitivity, Relative Biological Effectiveness and Dose-Rate

Variations in the intrinsic radiosensitivity of different cells to ionizing radiation is now widely believed to be a significant driver in differences in response to radiotherapy. While the mechanisms of radiosensitivity have been extensively studied in the laboratory, there are a lack of models which integrate this knowledge into a predictive framework. This paper presents an overview of the Medras model, which has been developed to provide a mechanistic framework in which different radiation responses can be modelled and individual responses predicted. This model simulates the repair of radiation-induced DNA damage, incorporating the overall kinetics of repair and its fidelity, to predict a range of biological endpoints including residual DNA damage, mutation, chromosome aberration, and cell death. Validation of this model against a range of exposure types is presented, including considerations of varying radiation qualities and dose-rates. This approach has the potential to inform new tools to deliver mechanistic predictions of radiation sensitivity, and support future developments in treatment personalization.

Recent Developments on gMicroMC: Transport Simulations of Proton and Heavy Ions and Concurrent Transport of Radicals and DNA

Mechanistic Monte Carlo (MC) simulation of radiation interaction with water and DNA is important for the understanding of biological responses induced by ionizing radiation. In our previous work, we employed the Graphical Processing Unit (GPU)-based parallel computing technique to develop a novel, highly efficient, and open-source MC simulation tool, gMicroMC, for simulating electron-induced DNA damages. In this work, we reported two new developments in gMicroMC: the transport simulation of protons and heavy ions and the concurrent transport of radicals in the presence of DNA. We modeled these transports based on electromagnetic interactions between charged particles and water molecules and the chemical reactions between radicals and DNA molecules. Various physical properties, such as Linear Energy Transfer (LET) and particle range, from our simulation agreed with data published by NIST or simulation results from other CPU-based MC packages. The simulation results of DNA damage under the concurrent transport of radicals and DNA agreed with those from nBio-Topas simulation in a comprehensive testing case. GPU parallel computing enabled high computational efficiency. It took 41 s to simultaneously transport 100 protons with an initial kinetic energy of 10 MeV in water and 470 s to transport 105 radicals up to 1 µs in the presence of DNA.

Multi-scaled Monte Carlo calculation for radon-induced cellular damage in the bronchial airway epithelium

Radon is a leading cause of lung cancer in indoor public and mining workers. Inhaled radon progeny releases alpha particles, which can damage cells in the airway epithelium. The extent and complexity of cellular damage vary depending on the alpha particle's kinetic energy and cell characteristics. We developed a framework to quantitate the cellular damage on the nanometer and micrometer scales at different intensities of exposure to radon progenies Po-218 and Po-214. Energy depositions along the tracks of alpha particles that were slowing down were simulated on a nanometer scale using the Monte Carlo code Geant4-DNA. The nano-scaled track histories in a 5 μm radius and 1 μm-thick cylindrical volume were integrated into the tracking scheme of alpha trajectories in a micron-scale bronchial epithelium segment in the user-written SNU-CDS program. Damage distribution in cellular DNA was estimated for six cell types in the epithelium. Deep-sited cell nuclei in the epithelium would have less chance of being hit, but DNA damage from a single hit would be more serious, because low-energy alpha particles of high LET would hit the nuclei. The greater damage in deep-sited nuclei was due to the 7.69 MeV alpha particles emitted from Po-214. From daily work under 1 WL of radon concentration, basal cells would respond with the highest portion of complex DSBs among the suspected progenitor cells in the most exposed regions of the lung epithelium.

Mechanistic Modelling of Slow and Fast NHEJ DNA Repair Pathways Following Radiation for G0/G1 Normal Tissue Cells

Mechanistic in silico models can provide insight into biological mechanisms and highlight uncertainties for experimental investigation. Radiation-induced double-strand breaks (DSBs) are known to be toxic lesions if not repaired correctly. Non-homologous end joining (NHEJ) is the major DSB-repair pathway available throughout the cell cycle and, recently, has been hypothesised to consist of a fast and slow component in G0/G1. The slow component has been shown to be resection-dependent, requiring the nuclease Artemis to function. However, the pathway is not yet fully understood. This study compares two hypothesised models, simulating the action of individual repair proteins on DSB ends in a step-by-step manner, enabling the modelling of both wild-type and protein-deficient cell systems. Performance is benchmarked against experimental data from 21 cell lines and 18 radiation qualities. A model where resection-dependent and independent pathways are entirely separated can only reproduce experimental repair kinetics with additional restraints on end motion and protein recruitment. However, a model where the pathways are entwined was found to effectively fit without needing additional mechanisms. It has been shown that DaMaRiS is a useful tool when analysing the connections between resection-dependent and independent NHEJ repair pathways and robustly matches with experimental results from several sources.

Microdosimetric investigation of the radiation quality of low-medium energy electrons using Geant4-DNA

The increasing clinical use of low-energy photon and electron sources (below few tens of keV) has raised concerns on the adequacy of the existing approximation of an energy-independent radiobiological effectiveness. In this work, the variation of the quality factor (Q) and relative biological effectiveness (RBE) of electrons over the low-medium energy range (0.1 keV-1 MeV) is examined using several microdosimetry-based Monte Carlo methodologies with input data obtained from Geant4-DNA track-structure simulations. The sensitivity of the results to the different methodologies, Geant4-DNA physics models, and target sizes is examined. Calculations of Q and RBE are based on the ICRU Report 40 recommendations, the Kellerer-Hahn approximation, the site version of the theory of dual radiation action (TDRA), the microdosimetric kinetic model (MKM) of cell survival, and the calculated yield of DNA double strand breaks (DSB). The stochastic energy deposition spectra needed as input in the above approaches have been calculated for nanometer spherical volumes using the different electron physics models of Geant4-DNA. Results are normalized at 100 keV electrons which is here considered the reference radiation. It is shown that in the energy range ~50 keV-1 MeV, the calculated Q and RBE are approximately unity (to within 1-2%) irrespective of the methodology, Geant4-DNA physics model, and target size. At lower energies, Q and RBE become energy-dependent reaching a maximum value of ~1.5-2.5 between ~200 and 700 eV. The detailed variation of Q and RBE at low energies depends mostly upon the adopted methodology and target size, and less so upon the Geant4-DNA physics model. Overall, the DSB yield predicts the highest RBE values (with RBE_max≈2.5) whereas the MKM the lowest RBE values (with RBE_max≈1.5). The ICRU Report 40, Kellerer-Hahn, and TDRA methods are in excellent agreement (to within 1-2%) over the whole energy range predicting a Q_max≈2. In conclusion, the approximation Q=RBE=1 was found to be valid only above ~50 keV whereas at lower energies both Q and RBE become strongly energy-dependent. It is envisioned that the present work will contribute towards establishing robust methodologies to determine theoretically the energy-dependence of radiation quality of individual electrons which may then be used in subsequent calculations involving practical electron and photon radiation sources.

Cellular Response to Proton Irradiation: A Simulation Study with TOPAS-nBio

The cellular response to ionizing radiation continues to be of significant research interest in cancer radiotherapy, and DNA is recognized as the critical target for most of the biologic effects of radiation. Incident particles can cause initial DNA damages through physical and chemical interactions within a short time scale. Initial DNA damages can undergo repair via different pathways available at different stages of the cell cycle. The misrepair of DNA damage results in genomic rearrangement and causes mutations and chromosome aberrations, which are drivers of cell death. This work presents an integrated study of simulating cell response after proton irradiation with energies of 0.5-500 MeV (LET of 60-0.2 keV/µm). A model of a whole nucleus with fractal DNA geometry was implemented in TOPAS-nBio for initial DNA damage simulations. The default physics and chemistry models in TOPAS-nBio were used to describe interactions of primary particles, secondary particles, and radiolysis products within the nucleus. The initial DNA double-strand break (DSB) yield was found to increase from 6.5 DSB/Gy/Gbp at low-linear energy transfer (LET) of 0.2 keV/µm to 21.2 DSB/Gy/Gbp at high LET of 60 keV/µm. A mechanistic repair model was applied to predict the characteristics of DNA damage repair and dose response of chromosome aberrations. It was found that more than 95% of the DSBs are repaired within the first 24 h and the misrepaired DSB fraction increases rapidly with LET and reaches 15.8% at 60 keV/µm with an estimated chromosome aberration detection threshold of 3 Mbp. The dicentric and acentric fragment yields and the dose response of micronuclei formation after proton irradiation were calculated and compared with experimental results.

Impact of hypoxia on the double-strand break repair after photon and carbon ion irradiation of radioresistant HNSCC cells

DNA double-strand breaks (DSBs) induced by photon irradiation are the most deleterious damage for cancer cells and their efficient repair may contribute to radioresistance, particularly in hypoxic conditions. Carbon ions (C-ions) act independently of the oxygen concentration and trigger complex- and clustered-DSBs difficult to repair. Understanding the interrelation between hypoxia, radiation-type, and DNA-repair is therefore essential for overcoming radioresistance. The DSBs signaling and the contribution of the canonical non-homologous end-joining (NHEJ-c) and homologous-recombination (HR) repair pathways were assessed by immunostaining in two cancer-stem-cell (CSCs) and non-CSCs HNSCC cell lines. Detection and signaling of DSBs were lower in response to C-ions than photons. Hypoxia increased the decay-rate of the detected DSBs (γH2AX) in CSCs after photons and the initiation of DSB repair signaling (P-ATM) in CSCs and non-CSCs after both radiations, but not the choice of DSB repair pathway (53BP1). Additionally, hypoxia increased the NHEJ-c (DNA-PK) and the HR pathway (RAD51) activation only after photons. Furthermore, the involvement of the HR seemed to be higher in CSCs after photons and in non-CSCs after C-ions. Taken together, our results show that C-ions may overcome the radioresistance of HNSCC associated with DNA repair, particularly in CSCs, and independently of a hypoxic microenvironment.

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).

Fully integrated Monte Carlo simulation for evaluating radiation induced DNA damage and subsequent repair using Geant4-DNA

Ionising radiation induced DNA damage and subsequent biological responses to it depend on the radiation’s track-structure and its energy loss distribution pattern. To investigate the underlying biological mechanisms involved in such complex system, there is need of predicting biological response by integrated Monte Carlo (MC) simulations across physics, chemistry and biology. Hence, in this work, we have developed an application using the open source Geant4-DNA toolkit to propose a realistic “fully integrated” MC simulation to calculate both early DNA damage and subsequent biological responses with time. We had previously developed an application allowing simulations of radiation induced early DNA damage on a naked cell nucleus model. In the new version presented in this work, we have developed three additional important features: (1) modeling of a realistic cell geometry, (2) inclusion of a biological repair model, (3) refinement of DNA damage parameters for direct damage and indirect damage scoring. The simulation results are validated with experimental data in terms of Single Strand Break (SSB) yields for plasmid and Double Strand Break (DSB) yields for plasmid/human cell. In addition, the yields of indirect DSBs are compatible with the experimental scavengeable damage fraction. The simulation application also demonstrates agreement with experimental data of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma$$\end{document}γ-H2AX yields for gamma ray irradiation. Using this application, it is now possible to predict biological response along time through track-structure MC simulations.

Exosomes and exosomal microRNA in non-targeted radiation bystander and abscopal effects in the central nervous system

Localized cranial radiotherapy is a dominant treatment for brain cancers. After being subjected to radiation, the central nervous system (CNS) exhibits targeted effects as well as non-targeted radiation bystander effects (RIBE) and abscopal effects (RIAE). Radiation-induced targeted effects in the CNS include autophagy and various changes in tumor cells due to radiation sensitivity, which can be regulated by microRNAs. Non-targeted radiation effects are mainly induced by gap junctional communication between cells, exosomes containing microRNAs can be transduced by intracellular endocytosis to regulate RIBE and RIAE. In this review, we discuss the involvement of microRNAs in radiation-induced targeted effects, as well as exosomes and/or exosomal microRNAs in non-targeted radiation effects in the CNS. As a target pathway, we also discuss the Akt pathway which is regulated by microRNAs, exosomes, and/or exosomal microRNAs in radiation-induced targeted effects and RIBE in CNS tumor cells. As the CNS-derived exosomes can cross the blood-brain-barrier (BBB) into the bloodstream and be isolated from peripheral blood, exosomes and exosomal microRNAs can emerge as promising minimally invasive biomarkers and therapeutic targets for radiation-induced targeted and non-targeted effects in the CNS.

Modeling the effect of ion-induced shock waves and DNA breakage with the reactive CHARMM force field

Ion-induced DNA damage is an important effect underlying ion beam cancer therapy. This article introduces the methodology of modeling DNA damage induced by a shock wave caused by a projectile ion. Specifically it is demonstrated how single- and double strand breaks in a DNA molecule could be described by the reactive CHARMM (rCHARMM) force field implemented in the program MBN Explorer. The entire workflow of performing the shock wave simulations, including obtaining the crucial simulation parameters, is described in seven steps. Two exemplary analyses are provided for a case study simulation serving to: (a) quantify the shock wave propagation and (b) describe the dynamics of formation of DNA breaks. The article concludes by discussing the computational cost of the simulations and revealing the possible maximal computational time for different simulation set-ups.

Independent reaction times method in Geant4-DNA: Implementation and performance

PURPOSE

The simulation of individual particle tracks and the chemical stage following water radiolysis in biological tissue is an effective means of improving our knowledge of the physico-chemical contribution to the biological effect of ionizing radiation. However, the step-by-step simulation of the reaction kinetics of radiolytic species is the most time-consuming task in Monte Carlo track-structure simulations, with long simulation times that are an impediment to research. In this work, we present the implementation of the independent reaction times (IRT) method in Geant4-DNA Monte Carlo toolkit to improve the computational efficiency of calculating G-values, defined as the number of chemical species created or lost per 100 eV of deposited energy.

METHODS

The computational efficiency of IRT, as implemented, is compared to that from available Geant4-DNA step-by-step simulations for electrons, protons and alpha particles covering a wide range of linear energy transfer (LET). The accuracy of both methods is verified using published measured data from fast electron irradiations for ^• OH and e aq - for time-dependent G-values. For IRT, simulations in the presence of scavengers irradiated by cobalt-60 γ-ray and 2 MeV protons are compared with measured data for different scavenging capacities. In addition, a qualitative assessment comparing measured LET-dependent G-values with Geant4-DNA calculations in pure liquid water is presented.

RESULTS

The IRT improved the computational efficiency by three orders of magnitude relative to the step-by-step method while differences in G-values by 3.9% at 1 μs were found. At 7 ps, ^• OH and e aq - yields calculated with IRT differed from recent published measured data by 5% ± 4% and 2% ± 4%, respectively. At 1 μs, differences were 9% ± 5% and 6% ± 7% for ^• OH and e aq - , respectively. Uncertainties are one standard deviation. Finally, G-values at different scavenging capacities and LET-dependent G-values reproduced the behavior of measurements for all radiation qualities.

CONCLUSION

The comprehensive validation of the Geant4-DNA capabilities to accurately simulate the chemistry following water radiolysis is an ongoing work. The implementation presented in this work is a necessary step to facilitate performing such a task.

Simulation of Proton-Induced DNA Damage Patterns Using an Improved Clustering Algorithm

Simulations of deoxyribonucleic acid (DNA) molecular damage use the traversal algorithm that has the disadvantages of being time-consuming, slowly converging, and requiring high-performance computer clusters. This work presents an improved version of the algorithm, "density-based spatial clustering of applications with noise" (DBSCAN), using a KD-tree approach to find neighbors of each point for calculating clustered DNA damage. The resulting algorithm considers the spatial distributions for sites of energy deposition and hydroxyl radical attack, yielding the statistical probability of (single and double) DNA strand breaks. This work achieves high accuracy and high speed at calculating clustered DNA damage that has been induced by proton treatment at the molecular level while running on an i7 quad-core CPU. The simulations focus on the indirect effect generated by hydroxyl radical attack on DNA. The obtained results are consistent with those of other published experiments and simulations. Due to the array of chemical processes triggered by proton treatment, it is possible to predict the effects that different track structures of various energy protons produce on eliciting direct and indirect damage of DNA.

Challenges in the quantification approach to a radiation relevant adverse outcome pathway for lung cancer

PURPOSE

Adverse outcome pathways (AOPs) provide a modular framework for describing sequences of biological key events (KEs) and key event relationships (KERs) across levels of biological organization. Empirical evidence across KERs can support construction of quantified AOPs (qAOPs). Using an example AOP of energy deposition from ionizing radiation onto DNA leading to lung cancer incidence, we investigate the feasibility of quantifying data from KERs supported by all types of stressors. The merits and challenges of this process in the context of AOP construction are discussed.

MATERIALS AND METHODS

Empirical evidence across studies of dose-response from four KERs of the AOP were compiled independently for quantification. Three upstream KERs comprised of evidence from various radiation types in line with AOP guidelines. For these three KERs, a focused analysis of data from alpha-particle studies was undertaken to better characterize the process to the adverse outcome (AO) for a radon gas stressor. Numerical information was extracted from tables and graphs to plot and tabulate the response of KEs. To complement areas of the AOP quantification process, Monte Carlo (MC) simulations in TOPAS-nBio were performed to model exposure conditions relevant to the AO for an example bronchial compartment of the lung with secretory cell nuclei targets.

RESULTS

Quantification of AOP KERs highlighted the relevance of radiation types under the stressor-agnostic intent of AOP design, motivating a focus on specific types. For a given type, significant differences of KE response indicate meaningful data to derive linkages from the MIE to the AO is lacking and that better response-response focused studies are required. The MC study estimates the linear energy transfer (LET) of alpha-particles emitted by radon-222 and its progeny in the secretory cell nuclei of the example lung compartment to range from 94 - 5 + 5 to 192 - 18 + 15 keV/µm.

CONCLUSION

Quantifying AOP components provides a means to assemble empirical evidence across different studies. This highlights challenges in the context of studies examining similar endpoints using different radiation types. Data linking KERs to a MIE of 'deposition of energy' is shown to be non-compatible with the stressor-agnostic principles of AOP design. Limiting data to that describing response-response relationships between adjacent KERs may better delineate studies relevant to the damage that drives a pathway to the next KE and still support an 'all hazards' approach. Such data remains limited and future investigations in the radiation field may consider this approach when designing experiments and reporting their results and outcomes.

Modeling double-strand breaks from direct and indirect action in a complete human genome single cell Geant4 model

The aim of this work is to develop and validate a computational model to investigate direct and indirect DNA damage by directly quantifying DNA strand breaks. A detailed geometrical target model was created in the Monte Carlo toolkit Geant4 to represent the nucleus of a single human cell with complete human genome. A calculation framework to simulate double-strand breaks (DSBs) was implemented using this single cell model in the Geant4-DNA extension. A detailed ellipsoidal single cell model was implemented using a compacted DNA structure representing the fibroblast cell in the G0/G1 phase of the cycle using a total of 6 Gbp within the nucleus to represent the complete human genome. This geometry was developed from the publicly available Geant4-DNA example (wholeNuclearDNA), and modified to record DNA damage for both the physical and chemical stages. A clustering algorithm was implemented in the analysis process in order to quantify direct, indirect, and mixed DSBs. The model was validated against published experimental and computational results for DSB Gy^-1Gbp^-1and the relative biological effectiveness (RBE) values for 250 kVp and Co-60 photons, as well as 2-100 MeV mono-energetic protons. A general agreement was observed over the whole simulated proton energy range, Co-60 beam, and 250 kVp in terms of the yield of DSB Gy^-1Gbp^-1and RBE. The DSB yield was 8.0 ± 0.3 DSB Gy^-1Gbp^-1for Co-60, and 9.2 ± 0.2 DSB Gy^-1Gbp^-1for 250 kVp, and between 11.1 ± 0.9 and 8.1 ± 0.5 DSB Gy^-1Gbp^-1for 2-100 MeV protons. The results also show mixed DSBs composed of direct and indirect SSBs make up more than half of the total DSBs. The results presented indicate that the current model reliably predicts the DSB yield and RBE for proton and photon irradiations, and allows for the detailed computational investigation of direct and indirect effects in DNA damage.

Analytical formulas representing track-structure simulations on DNA damage induced by protons and light ions at radiotherapy-relevant energies

Track structure based simulations valuably complement experimental research on biological effects of ionizing radiation. They provide information at the highest level of detail on initial DNA damage induced by diverse types of radiation. Simulations with the biophysical Monte Carlo code PARTRAC have been used for testing working hypotheses on radiation action mechanisms, for benchmarking other damage codes and as input for modelling subsequent biological processes. To facilitate such applications and in particular to enable extending the simulations to mixed radiation field conditions, we present analytical formulas that capture PARTRAC simulation results on DNA single- and double-strand breaks and their clusters induced in cells irradiated by ions ranging from hydrogen to neon at energies from 0.5 GeV/u down to their stopping. These functions offer a means by which radiation transport codes at the macroscopic scale could easily be extended to predict biological effects, exploiting a large database of results from micro-/nanoscale simulations, without having to deal with the coupling of spatial scales and running full track-structure calculations.

Simultaneous Exposure of Cultured Human Lymphoblastic Cells to Simulated Microgravity and Radiation Increases Chromosome Aberrations

During space travel, humans are continuously exposed to two major environmental stresses, microgravity (μG) and space radiation. One of the fundamental questions is whether the two stressors are interactive. For over half a century, many studies were carried out in space, as well as using devices that simulated μG on the ground to investigate gravity effects on cells and organisms, and we have gained insights into how living organisms respond to μG. However, our knowledge on how to assess and manage human health risks in long-term mission to the Moon or Mars is drastically limited. For example, little information is available on how cells respond to simultaneous exposure to space radiation and μG. In this study, we analyzed the frequencies of chromosome aberrations (CA) in cultured human lymphoblastic TK6 cells exposed to X-ray or carbon ion under the simulated μG conditions. A higher frequency of both simple and complex types of CA were observed in cells exposed to radiation and μG simultaneously compared to CA frequency in cells exposed to radiation only. Our study shows that the dose response data on space radiation obtained at the 1G condition could lead to the underestimation of astronauts' potential risk for health deterioration, including cancer. This study also emphasizes the importance of obtaining data on the molecular and cellular responses to irradiation under μG conditions.

A parameter sensitivity study for simulating DNA damage after proton irradiation using TOPAS-nBio

Monte Carlo (MC) track structure simulation tools are commonly used for predicting radiation induced DNA damage by modeling the physical and chemical reactions at the nanometer scale. However, the outcome of these MC simulations is particularly sensitive to the adopted parameters which vary significantly across studies. In this study, a previously developed full model of nuclear DNA was used to describe the DNA geometry. The TOPAS-nBio MC toolkit was used to investigate the impact of physics and chemistry models as well as three key parameters (the energy threshold for direct damage, the chemical stage time length, and the probability of damage between hydroxyl radical reactions with DNA) on the induction of DNA damage. Our results show that the difference in physics and chemistry models alone can cause differences up to 34% and 16% in the DNA double strand break (DSB) yield, respectively. Additionally, changing the direct damage threshold, chemical stage length, and hydroxyl damage probability can cause differences of up to 28%, 51%, and 71% in predicted DSB yields, respectively, for the configurations in this study.

A microdosimetric analysis of the interactions of mono-energetic neutrons with human tissue

Nuclear reactions induced during high-energy radiotherapy produce secondary neutrons that, due to their carcinogenic potential, constitute an important risk for the development of iatrogenic cancer. Experimental and epidemiological findings indicate a marked energy dependence of neutron relative biological effectiveness (RBE) for carcinogenesis, but little is reported on its physical basis. While the exact mechanism of radiation carcinogenesis is yet to be fully elucidated, numerical microdosimetry can be used to predict the biological consequences of a given irradiation based on its microscopic pattern of energy depositions. Building on recent studies, this work investigated the physics underlying neutron RBE by using the microdosimetric quantity dose-mean lineal energy (y‾_D) as a proxy. A simulation pipeline was constructed to explicitly calculate the y‾_D of radiation fields that consisted of (i) the open source Monte Carlo toolkit Geant4, (ii) its radiobiological extension Geant4-DNA, and (iii) a weighted track-sampling algorithm. This approach was used to study mono-energetic neutrons with initial kinetic energies between 1 eV and 10 MeV at multiple depths in a tissue-equivalent phantom. Spherical sampling volumes with diameters between 2 nm and 1 μm were considered. To obtain a measure of RBE, the neutron y‾_D values were divided by those of 250 keV X-rays that were calculated in the same way. Qualitative agreement was found with published radiation protection factors and simulation data, allowing for the dependencies of neutron RBE on depth and energy to be discussed in the context of the neutron interaction cross sections and secondary particle distributions in human tissue.

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

Ionizing radiation is a common tool in medical procedures. Monte Carlo (MC) techniques are widely used when dosimetry is the matter of investigation. The scientific community has invested, over the last 20 years, a lot of effort into improving the knowledge of radiation biology. The present article aims to summarize the understanding of the field of DNA damage response (DDR) to ionizing radiation by providing an overview on MC simulation studies that try to explain several aspects of radiation biology. The need for accurate techniques for the quantification of DNA damage is crucial, as it becomes a clinical need to evaluate the outcome of various applications including both low- and high-energy radiation medical procedures. Understanding DNA repair processes would improve radiation therapy procedures. Monte Carlo simulations are a promising tool in radiobiology studies, as there are clear prospects for more advanced tools that could be used in multidisciplinary studies, in the fields of physics, medicine, biology and chemistry. Still, lot of effort is needed to evolve MC simulation tools and apply them in multiscale studies starting from small DNA segments and reaching a population of cells.

Internal microdosimetry of alpha-emitting radionuclides

At the tissue level, energy deposition in cells is determined by the microdistribution of alpha-emitting radionuclides in relation to sensitive target cells. Furthermore, the highly localized energy deposition of alpha particle tracks and the limited range of alpha particles in tissue produce a highly inhomogeneous energy deposition in traversed cell nuclei. Thus, energy deposition in cell nuclei in a given tissue is characterized by the probability of alpha particle hits and, in the case of a hit, by the energy deposited there. In classical microdosimetry, the randomness of energy deposition in cellular sites is described by a stochastic quantity, the specific energy, which approximates the macroscopic dose for a sufficiently large number of energy deposition events. Typical examples of the alpha-emitting radionuclides in internal microdosimetry are radon progeny and plutonium in the lungs, plutonium and americium in bones, and radium in targeted radionuclide therapy. Several microdosimetric approaches have been proposed to relate specific energy distributions to radiobiological effects, such as hit-related concepts, LET and track length-based models, effect-specific interpretations of specific energy distributions, such as the dual radiation action theory or the hit-size effectiveness function, and finally track structure models. Since microdosimetry characterizes only the initial step of energy deposition, microdosimetric concepts are most successful in exposure situations where biological effects are dominated by energy deposition, but not by subsequently operating biological mechanisms. Indeed, the simulation of the combined action of physical and biological factors may eventually require the application of track structure models at the nanometer scale.

Modeling of chromosome aberration response functions induced by particle beams with different LET

This study is based on our already published experimental data (Kowalska et al. in Radiat Environ Biophys 58:99-108, 2019) and is devoted to modeling of chromosome aberrations in human lymphocytes induced by 22.1 MeV/u ¹¹B ions, 199 MeV/u ¹²C ions, 150 MeV and spread-out Bragg peak (SOBP) proton beams as well as by ⁶⁰Co γ rays. The curvature of the dose-effect curves determined by the linear-quadratic model was considered in the frame of a simple analytical approach taking into account increase in the irradiation dose due to overlapping interaction regions of ion tracks. The model enabled to estimate effective interaction radius which could be compared with the physical expectations. The results were also compared to the Amorphous Track Structure Model of Katz which allows to get some additional information about the ion track structure. The analysis showed that the curvature of the experimental dose-effect curves mainly results from highly efficient repair processes of the DNA damage.

A new open-source GPU-based microscopic Monte Carlo simulation tool for the calculations of DNA damages caused by ionizing radiation - Part II: sensitivity and uncertainty analysis

PURPOSE

Calculations of deoxyribonucleic acid (DNA) damages involve many parameters in the computation process. As these parameters are often subject to uncertainties, it is of central importance to comprehensively quantify their impacts on DNA single-strand break (SSB) and double-strand break (DSB) yields. This has been a challenging task due to the required large number of simulations and the relatively low computational efficiency using CPU-based MC packages. In this study, we present comprehensive evaluations on sensitivities and uncertainties of DNA SSB and DSB yields on 12 parameters using our GPU-based MC tool, gMicroMC.

METHODS

We sampled one electron at a time in a water sphere containing a human lymphocyte nucleus and transport the electrons and generated radicals until 2 Gy dose was accumulated in the nucleus. We computed DNA damages caused by electron energy deposition events in the physical stage and the hydroxyl radicals at the end of the chemical stage. We repeated the computations by varying 12 parameters: (a) physics cross section, (b) cutoff energy for electron transport, (c)-(e) three branching ratios of hydroxyl radicals in the de-excitation of excited water molecules, (f) temporal length of the chemical stage, (g)-(h) reaction radii for direct and indirect damages, (i) threshold energy defining the threshold damage model to generate a physics damage, (j)-(k) minimum and maximum energy values defining the linear-probability damage model to generate a physics damage, and (l) probability to generate a damage by a radical. We quantified sensitivity of SSB and DSB yields with respect to these parameters for cases with 1.0 and 4.5 keV electrons. We further estimated uncertainty of SSB and DSB yields caused by uncertainties of these parameters.

RESULTS

Using a threshold of 10% uncertainty as a criterion, threshold energy in the threshold damage model, maximum energy in the linear-probability damage model, and probability for a radical to generate a damage were found to cause large uncertainties in both SSB and DSB yields. The scaling factor of the cross section, cutoff energy, physics reaction radius, and minimum energy in the linear-probability damage model were found to generate large uncertainties in DSB yields.

CONCLUSIONS

We identified parameters that can generate large uncertainties in the calculations of SSB and DSB yields. Our study could serve as a guidance to reduce uncertainties of parameters and hence uncertainties of the simulation results.

Microdosimetric calculations of the direct DNA damage induced by low energy electrons using the Geant4-DNA Monte Carlo code

To calculate the yield of direct DNA damage induced by low energy electrons using Monte Carlo generated microdosimetric spectra at the nanometer scale and examine the influence of various simulation inputs. The potential of classical microdosimetry to offer a viable and simpler alternative to more elaborate mechanistic approaches for practical applications is discussed. Track-structure simulations with the Geant4-DNA low-energy extension of the Geant4 Monte Carlo toolkit were used for calculating lineal energy spectra in spherical volumes with dimensions relevant to double-strand-break (DSB) induction. The microdosimetric spectra were then used to calculate the yield of simple and clustered DSB based on literature values of the threshold energy of DNA damage. The influence of the different implementations of the dielectric function of liquid water available in Geant4-DNA (Option 2 and Option 4 constructors), as well as the effect of particle tracking cutoff energy and target size are examined. Frequency- and dose-mean lineal energies in liquid-water spheres of 2, 2.3, 2.6, and 3.4 nm diameter, as well as, number of simple and clustered DSB/Gy/cell are presented for electrons over the 100 eV to 100 keV energy range. Results are presented for both the 'default' (Option 2) and 'Ioannina' (Option 4) physics models of Geant4-DNA applying several commonly used tracking cutoff energies (10, 20, 50, 100 eV). Overall, the choice of the physics model and target diameter has a moderate effect (up to ~10%-30%) on the DSB yield whereas the effect of the tracking cutoff energy may be significant (>100%). Importantly, the yield of both simple and clustered DSB was found to vary significantly (by a factor of 2 or more) with electron energy over the examined range. The yields of electron-induced simple and clustered DSB exhibit a strong energy dependence over the 100 eV-100 keV range with implications to radiation quality issues. It is shown that a classical microdosimetry approach for the calculation of DNA damage based on lineal energy spectra in nanometer-size targets predicts comparable results to computationally intensive mechanistic approaches which use detailed atomistic DNA geometries, thus, offering a relatively simple and robust alternative for some practical applications.

Radiation Track Structure: How the Spatial Distribution of Energy Deposition Drives Biological Response

Ionising radiation is incredibly effective at causing biological effects. This is due to the unique way energy is deposited along highly structured tracks of ionisation and excitation events, which results in correlation with sites of DNA damage from the nanometre to the micrometre scale. Correlation of these events along the track on the nanometre scale results in clustered damage, which not only results in the formation of DNA double-strand breaks (DSB), but also more difficult to repair complex DSB, which include additional damage within a few base pairs. The track structure varies significantly with radiation quality and the increase in relative biological effectiveness observed with increasing linear energy transfer in part corresponds to an increase in the probability and complexity of clustered DNA damage produced. Likewise, correlation over larger scales, associated with packing of DNA and associated chromosomes within the cell nucleus, can also have a major impact on the biological response. The proximity of the correlated damage along the track increases the probability of miss-repair through pairwise interactions resulting in an increase in probability and complexity of DNA fragments/deletions, mutations and chromosomal rearrangements. Understanding the mechanisms underlying the biological effectiveness of ionising radiation can provide an important insight into ways of increasing the efficacy of radiotherapy, as well as the risks associated with exposure. This requires a multi-scale approach for modelling, not only considering the physics of the track structure from the millimetre scale down to the nanometre scale, but also the structural packing of the DNA within the nucleus, the resulting chemistry in the context of the highly reactive environment of the nucleus, together with the subsequent biological response.

Minibeam radiation therapy: A micro- and nano-dosimetry Monte Carlo study

PURPOSE

Minibeam radiation therapy (MBRT) is an innovative strategy based on a distinct dose delivery method that is administered using a series of narrow (submillimetric) parallel beams. To shed light on the biological effects of MBRT irradiation, we explored the micro- and nanodosimetric characteristics of three promising MBRT modalities (photon, electron, and proton) using Monte Carlo (MC) calculations.

METHODS

Irradiation with proton (100 MeV), electron (300 MeV), and photon (effective energy of 69 keV) minibeams were simulated using Geant4 MC code and the Geant4-DNA extension, which allows the simulation of energy transfer points with nanometric accuracy. As the target of the simulations, cells containing spherical nuclei with or without a detailed description of the DNA (deoxyribonucleic acid) geometry were placed at different depths in peak and valley regions in a water phantom. The energy deposition and number of events in the cell nuclei were recorded in the microdosimetry study, and the number of DNA breaks and their complexity were determined in the nanodosimetric study, where a multi-scale simulation approach was used for the latter. For DNA damage assessment, an adapted DBSCAN clustering algorithm was used. To compare the photon MBRT (xMBRT), electron MBRT (eMBRT), and proton MBRT (pMBRT) approaches, we considered the treatment of a brain tumor located at a depth of 75 mm.

RESULTS

Both mean energy deposition at micrometric scale and DNA damage in the "valley" cell nuclei were very low as compared with these parameters in the peak region at all depths for xMBRT and at depths of 0 to 30 mm and 0 to 50 mm for eMBRT and pMBRT, respectively. Only the charged minibeams were favorable for tumor control by producing similar effects in peak and valley cells after 70 mm. At the micrometer scale, the energy deposited per event pointed to a potential advantage of proton beams for tumor control, as more aggressive events could be expected at the end of their tracks. At the nanometer scale, all three MBRT modalities produced direct clustered DNA breaks, although the majority of damage (>93%) was composed of isolated single strand breaks. The pMBRT led to a significant increase in the proportion of clustered single strand breaks and double-strand breaks at the end of its range as compared to the entrance (7% at 75 mm vs 3% at 10 mm) in contrast to eMBRT and xMBRT. In the latter cases, the proportions of complex breaks remained constant, irrespective of the depth and region (peak or valley).

CONCLUSIONS

Enhanced normal tissue sparing can be expected with these three MBRT techniques. Among the three modalities, pMBRT offers an additional gain for radioresistant tumors, as it resulted in a higher number of complex DNA damage clusters in the tumor region. These results can aid understanding of the biological mechanisms of MBRT.

Clustered DNA Double-Strand Breaks: Biological Effects and Relevance to Cancer Radiotherapy

Cells manage to survive, thrive, and divide with high accuracy despite the constant threat of DNA damage. Cells have evolved with several systems that efficiently repair spontaneous, isolated DNA lesions with a high degree of accuracy. Ionizing radiation and a few radiomimetic chemicals can produce clustered DNA damage comprising complex arrangements of single-strand damage and DNA double-strand breaks (DSBs). There is substantial evidence that clustered DNA damage is more mutagenic and cytotoxic than isolated damage. Radiation-induced clustered DNA damage has proven difficult to study because the spectrum of induced lesions is very complex, and lesions are randomly distributed throughout the genome. Nonetheless, it is fairly well-established that radiation-induced clustered DNA damage, including non-DSB and DSB clustered lesions, are poorly repaired or fail to repair, accounting for the greater mutagenic and cytotoxic effects of clustered lesions compared to isolated lesions. High linear energy transfer (LET) charged particle radiation is more cytotoxic per unit dose than low LET radiation because high LET radiation produces more clustered DNA damage. Studies with I-SceI nuclease demonstrate that nuclease-induced DSB clusters are also cytotoxic, indicating that this cytotoxicity is independent of radiogenic lesions, including single-strand lesions and chemically "dirty" DSB ends. The poor repair of clustered DSBs at least in part reflects inhibition of canonical NHEJ by short DNA fragments. This shifts repair toward HR and perhaps alternative NHEJ, and can result in chromothripsis-mediated genome instability or cell death. These principals are important for cancer treatment by low and high LET radiation.

Intercomparison of dose enhancement ratio and secondary electron spectra for gold nanoparticles irradiated by X-rays calculated using multiple Monte Carlo simulation codes

PURPOSE

Targeted radiation therapy has seen an increased interest in the past decade. In vitro and in vivo experiments showed enhanced radiation doses due to gold nanoparticles (GNPs) to tumors in mice and demonstrated a high potential for clinical application. However, finding a functionalized molecular formulation for actively targeting GNPs in tumor cells is challenging. Furthermore, the enhanced energy deposition by secondary electrons around GNPs, particularly by short-ranged Auger electrons is difficult to measure. Computational models, such as Monte Carlo (MC) radiation transport codes, have been used to estimate the physical quantities and effects of GNPs. However, as these codes differ from one to another, the reliability of physical and dosimetric quantities needs to be established at cellular and molecular levels, so that the subsequent biological effects can be assessed quantitatively.

METHODS

In this work, irradiation of single GNPs of 50 nm and 100 nm diameter by X-ray spectra generated by 50 and 100 peak kilovoltages was simulated for a defined geometry setup, by applying multiple MC codes in the EURADOS framework.

RESULTS

The mean dose enhancement ratio of the first 10 nm-thick water shell around a 100 nm GNP ranges from 400 for 100 kVp X-rays to 600 for 50 kVp X-rays with large uncertainty factors up to 2.3.

CONCLUSIONS

It is concluded that the absolute dose enhancement effects have large uncertainties and need an inter-code intercomparison for a high quality assurance; relative properties may be a better measure until more experimental data is available to constrain the models.

BIOPHYSICAL SIMULATION TOOL PARTRAC: MODELLING PROTON BEAMS AT THERAPY-RELEVANT ENERGIES

The biophysical simulation tool PARTRAC has been primarily developed to model radiation physics, chemistry and biology on nanometre to micrometre scales. However, the tool can be applied in simulating radiation effects in an event-by-event manner over macroscopic volumes as well. Benchmark simulations are reported showing that PARTRAC does reproduce the macroscopic Bragg peaks of proton beams, although the penetration depths are underestimated by a few per cent for high-energy beams. PARTRAC also quantifies the increase in DNA damage and its complexity along the beam penetration depth. Enhanced biological effectiveness is predicted in particular within distal Bragg peak parts of therapeutic proton beams.

Comparative photon and proton dosimetry for patients with mediastinal lymphoma in the era of Monte Carlo treatment planning and variable relative biological effectiveness

Background

Existing pencil beam analytical (PBA) algorithms for proton therapy treatment planning are not ideal for sites with heterogeneous tissue density and do not account for the spatial variations in proton relative biological effectiveness (vRBE). Using a commercially available Monte Carlo (MC) treatment planning system, we compared various dosimetric endpoints between proton PBA, proton MC, and photon treatment plans among patients with mediastinal lymphoma.

Methods

Eight mediastinal lymphoma patients with both free breathing (FB) and deep inspiration breath hold (DIBH) CT simulation scans were analyzed. The original PBA plans were re-calculated with MC. New proton plans that used MC for both optimization and dose calculation with equivalent CTV/ITV coverage were also created. A vRBE model, which uses a published model for DNA double strand break (DSB) induction, was applied on MC plans to study the potential impact of vRBE on cardiac doses. Comparative photon plans were generated on the DIBH scan.

Results

Re-calculation of FB PBA plans with MC demonstrated significant under coverage of the ITV V99 and V95. Target coverage was recovered by re-optimizing the PT plan with MC with minimal change to OAR doses. Compared to photons with DIBH, MC-optimized FB and DIBH proton plans had significantly lower dose to the mean lung, lung V5, breast tissue, and spinal cord for similar target coverage. Even with application of vRBE in the proton plans, the putative increase in RBE at the end of range did not decrease the dosimetric advantages of proton therapy in cardiac substructures.

Conclusions

MC should be used for PT treatment planning of mediastinal lymphoma to ensure adequate coverage of target volumes. Our preliminary data suggests that MC-optimized PT plans have better sparing of the lung and breast tissue compared to photons. Also, the potential for end of range RBE effects are unlikely to be large enough to offset the dosimetric advantages of proton therapy in cardiac substructures for mediastinal targets, although these dosimetric findings require validation with late toxicity data.

Isolation of time-dependent DNA damage induced by energetic carbon ions and their fragments using fluorescent nuclear track detectors

PURPOSE

High energetic carbon (C-) ion beams undergo nuclear interactions with tissue, producing secondary nuclear fragments. Thus, at depth, C-ion beams are composed of a mixture of different particles with different linear energy transfer (LET) values. We developed a technique to enable isolation of DNA damage response (DDR) in mixed radiation fields using beam line microscopy coupled with fluorescence nuclear track detectors (FNTDs).

METHODS

We imaged live cells on a coverslip made of FNTDs right after C-ion, proton or photon irradiation using an in-house built confocal microscope placed in the beam path. We used the FNTD to link track traversals with DNA damage and separated DNA damage induced by primary particles from fragments.

RESULTS

We were able to spatially link physical parameters of radiation tracks to DDR in live cells to investigate spatiotemporal DDR in multi-ion radiation fields in real time, which was previously not possible. We demonstrated that the response of lesions produced by the high-LET primary particles associates most strongly with cell death in a multi-LET radiation field, and that this association is not seen when analyzing radiation induced foci in aggregate without primary/fragment classification.

CONCLUSIONS

We report a new method that uses confocal microscopy in combination with FNTDs to provide submicrometer spatial-resolution measurements of radiation tracks in live cells. Our method facilitates expansion of the radiation-induced DDR research because it can be used in any particle beam line including particle therapy beam lines.

CATEGORY

Biological Physics and Response Prediction.

Ionizing Radiation and Complex DNA Damage: From Prediction to Detection Challenges and Biological Significance

Biological responses to ionizing radiation (IR) have been studied for many years, generally showing the dependence of these responses on the quality of radiation, i.e., the radiation particle type and energy, types of DNA damage, dose and dose rate, type of cells, etc. There is accumulating evidence on the pivotal role of complex (clustered) DNA damage towards the determination of the final biological or even clinical outcome after exposure to IR. In this review, we provide literature evidence about the significant role of damage clustering and advancements that have been made through the years in its detection and prediction using Monte Carlo (MC) simulations. We conclude that in the future, emphasis should be given to a better understanding of the mechanistic links between the induction of complex DNA damage, its processing, and systemic effects at the organism level, like genomic instability and immune responses.

Proton transport modeling in a realistic biological environment by using TILDA-V

Whether it is in radiobiology to identify DNA lesions or in medicine to adapt the radiotherapeutic protocols, a detailed understanding of the radiation-induced interactions in living matter is required. Monte Carlo track-structure codes have been successfully developed to describe these interactions and predict the radiation-induced energy deposits at the nanoscale level in the medium of interest. In this work, the quantum-mechanically based Monte Carlo track-structure code TILDA-V has been used to compute the slowing-down of protons in water and DNA. Stopping power and range are then reported and compared with existing data. Then, a first application of TILDA-V to cellular irradiations is also reported in order to highlight the absolute necessity of taking into account a realistic description of the cellular environment in microdosimetry.

Predicting DNA damage foci and their experimental readout with 2D microscopy: a unified approach applied to photon and neutron exposures

The consideration of how a given technique affects results of experimental measurements is a must to achieve correct data interpretation. This might be challenging when it comes to measurements on biological systems, where it is unrealistic to have full control (e.g. through a software replica) of all steps in the measurement chain. In this work we address how the effectiveness of different radiation qualities in inducing biological damage can be assessed measuring DNA damage foci yields, only provided that artefacts related to the scoring technique are adequately considered. To this aim, we developed a unified stochastic modelling approach that, starting from radiation tracks, predicts both the induction, spatial distribution and complexity of DNA damage, and the experimental readout of foci when immunocytochemistry coupled to 2D fluorescence microscopy is used. The approach is used to interpret γ-H2AX data for photon and neutron exposures. When foci are reconstructed in the whole cell nucleus, we obtain information on damage characteristics "behind" experimental observations, as the average damage content of a focus. We reproduce how the detection technique affects experimental findings, e.g. contributing to the saturation of foci yields scored at 30 minutes after exposure with increasing dose and to the lack of dose dependence for yields at 24 hours.

[Study of clustered damage in DNA after proton irradiation based on density-based spatial clustering of applications with noise algorithm]

The deoxyribonucleic acid (DNA) molecule damage simulations with an atom level geometric model use the traversal algorithm that has the disadvantages of quite time-consuming, slow convergence and high-performance computer requirement. Therefore, this work presents a density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm based on the spatial distributions of energy depositions and hydroxyl radicals (·OH). The algorithm with probability and statistics can quickly get the DNA strand break yields and help to study the variation pattern of the clustered DNA damage. Firstly, we simulated the transportation of protons and secondary particles through the nucleus, as well as the ionization and excitation of water molecules by using Geant4-DNA that is the Monte Carlo simulation toolkit for radiobiology, and got the distributions of energy depositions and hydroxyl radicals. Then we used the damage probability functions to get the spatial distribution dataset of DNA damage points in a simplified geometric model. The DBSCAN clustering algorithm based on damage points density was used to determine the single-strand break (SSB) yield and double-strand break (DSB) yield. Finally, we analyzed the DNA strand break yield variation trend with particle linear energy transfer (LET) and summarized the variation pattern of damage clusters. The simulation results show that the new algorithm has a faster simulation speed than the traversal algorithm and a good precision result. The simulation results have consistency when compared to other experiments and simulations. This work achieves more precise information on clustered DNA damage induced by proton radiation at the molecular level with high speed, so that it provides an essential and powerful research method for the study of radiation biological damage mechanism.

Reaction of Electrons with DNA: Radiation Damage to Radiosensitization

This review article provides a concise overview of electron involvement in DNA radiation damage. The review begins with the various states of radiation-produced electrons: Secondary electrons (SE), low energy electrons (LEE), electrons at near zero kinetic energy in water (quasi-free electrons, (e-qf)) electrons in the process of solvation in water (presolvated electrons, e-pre), and fully solvated electrons (e-aq). A current summary of the structure of e-aq, and its reactions with DNA-model systems is presented. Theoretical works on reduction potentials of DNA-bases were found to be in agreement with experiments. This review points out the proposed role of LEE-induced frank DNA-strand breaks in ion-beam irradiated DNA. The final section presents radiation-produced electron-mediated site-specific formation of oxidative neutral aminyl radicals from azidonucleosides and the evidence of radiosensitization provided by these aminyl radicals in azidonucleoside-incorporated breast cancer cells.

Nonhomologous End Joining Is More Important Than Proton Linear Energy Transfer in Dictating Cell Death

PURPOSE

This study seeks to identify biological factors that may yield a therapeutic advantage of proton therapy versus photon therapy. Specifically, we address the role of nonhomologous end-joining (NHEJ) and homologous recombination (HR) in the survival of cells in response to clinical photon and proton beams.

METHODS AND MATERIALS

We irradiated HT1080, M059K (DNA-PKcs^+/+), and HCC1937 human cancer cell lines and their isogenic counterparts HT1080-shDNA-PKcs, HT1080-shRAD51^IND, M059J (DNA-PKcs^-/-), and HCC1937-BRCA1 (BRCA1 complemented) to assess cell clonogenic survival and γ-H2AX radiation-induced foci. Cells were irradiated with either clinically relevant photons or 1 of 3 proton linear energy transfer (LET) values.

RESULTS

Our results indicate that NHEJ deficiency is more important in dictating cell survival than proton LET. Cells with disrupted HR through BRCA1 mutation showed increased radiosensitivity only for high-LET protons whereas RAD51 depletion showed increased radiosensitivity for both photons and protons. DNA double strand breaks, assessed by γ-H2AX radiation-induced foci, showed greater numbers after 24 hours in cells exposed to higher LET protons. We also observed that NHEJ-deficient cells were unable to repair the vast majority of double strand breaks after 24 hours.

CONCLUSIONS

BRCA1 mutation significantly sensitizes cells to protons, but not photons. Loss of NHEJ renders cells hypersensitive to radiation, whereas the relative importance of HR increases with LET across several cell lines. This may be attributable to the more clustered damage induced by higher LET protons, which are harder to repair through NHEJ. This highlights the importance of tumor biology in dictating treatment modality and suggests BRCA1 as a potential biomarker for proton therapy response. Our data also support the use of pharmacologic inhibitors of DNA repair to enhance the sensitivity to different radiation types, although this raises issues for normal tissue toxicity.