Proton relative biological effectiveness for the induction of DNA double strand breaks based on Geant4

Uncertainties in the relative biological effectiveness (RBE) of proton remains a major barrier to the biological optimization of proton therapy. A large amount of experimental data suggest that proton RBE is variable. As an evolving Monte Carlo code toolkit, Geant4-DNA is able to simulate the initial DNA damage caused by particle beams through physical and chemical interactions at the nanometer scale over a short period of time. This contributes to evaluating the radiobiological effects induced by ionizing radiation. Based on the Geant4-DNA toolkit, this study constructed a DNA geometric model containing 6.32Gbp, simulated the relationship between radiochemical yields (G-values) and their corresponding chemical constructors, and calculated a detailed calculation of the sources of damage and the complexity of damage in DNA strand breaks. The damage model constructed in this study can simulate the relative biological effectiveness (RBE) in the proton Bragg peak region. The results indicate that: (1) When the electron energy is below 400 keV, the yield of OH·account for 18.1% to 25.3% of the total water radiolysis yields. (2) Under the influence of histone clearance function, the yield of indirect damage account for over 72.93% of the yield of DNA strand breaks (SBs). When linear energy transfer (LET) increased from 29.79 (keV/μm) to 64.29 (keV/μm), the yield of double strand breaks (DSB) increased from 17.27% to 32.65%. (3) By investigating the effect of proton Bragg peak depth on the yield of direct DSB (DSBdirect) and total DSB (DSBtotal), theRBEDSBtotandRBEDSBdirlevels of cells show that the RBE value of protons reaches 2.2 in the Bragg peak region.

Mechanistic modelling of relative biological effectiveness of carbon ion beams and comparison with experiments

Objective.Relative biological effectiveness (RBE) plays a vital role in carbon ion radiotherapy, which is a promising treatment method for reducing toxic effects on normal tissues and improving treatment efficacy. It is important to have an effective and precise way of obtaining RBE values to support clinical decisions. A method of calculating RBE from a mechanistic perspective is reported.Approach.Ratio of dose to obtain the same number of double strand breaks (DSBs) between different radiation types was used to evaluate RBE. Package gMicroMC was used to simulate DSB yields. The DSB inductions were then analyzed to calculate RBE. The RBE values were compared with experimental results.Main results.Furusawa's experiment yielded RBE values of 1.27, 2.22, 3.00 and 3.37 for carbon ion beam with dose-averaged LET of 30.3 keVμm-1, 54.5 keVμm-1, 88 keVμm-1and 137 keVμm-1, respectively. RBE values computed from gMicroMC simulations were 1.75, 2.22, 2.87 and 2.97. When it came to a more sophisticated carbon ion beam with 6 cm spread-out Bragg peak, RBE values were 1.61, 1.63, 2.19 and 2.36 for proximal, middle, distal and distal end part, respectively. Values simulated by gMicroMC were 1.50, 1.87, 2.19 and 2.34. The simulated results were in reasonable agreement with the experimental data.Significance.As a mechanistic way for the evaluation of RBE for carbon ion radiotherapy by combining the macroscopic simulation of energy spectrum and microscopic simulation of DNA damages, this work provides a promising tool for RBE calculation supporting clinical applications such as treatment planning.

Assessing radiation dosimetry for microorganisms in naturally radioactive mineral springs using GATE and Geant4-DNA Monte Carlo simulations

Mineral springs in Massif Central, France can be characterized by higher levels of natural radioactivity in comparison to the background. The biota in these waters is constantly under radiation exposure mainly from the α-emitters of the natural decay chains, with 226Ra in sediments ranging from 21 Bq/g to 43 Bq/g and 222Rn activity concentrations in water up to 4600 Bq/L. This study couples for the first time micro- and nanodosimetric approaches to radioecology by combining GATE and Geant4-DNA to assess the dose rates and DNA damages to microorganisms living in these naturally radioactive ecosystems. It focuses on unicellular eukaryotic microalgae (diatoms) which display an exceptional abundance of teratological forms in the most radioactive mineral springs in Auvergne. Using spherical geometries for the microorganisms and based on γ-spectrometric analyses, we evaluate the impact of the external exposure to 1000 Bq/L 222Rn dissolved in the water and 30 Bq/g 226Ra in the sediments. Our results show that the external dose rates for diatoms are significant (9.7 μGy/h) and comparable to the threshold (10 μGy/h) for the protection of the ecosystems suggested by the literature. In a first attempt of simulating the radiation induced DNA damage on this species, the rate of DNA Double Strand Breaks per day is estimated to 1.11E-04. Our study confirms the significant mutational pressure from natural radioactivity to which microbial biodiversity has been exposed since Earth origin in hydrothermal springs.

A Monte Carlo study on the impact of indirect action on neutron relative biological effectiveness

Recent Monte Carlo studies have linked the energy-dependent risk of neutron-induced stochastic effects to the relative biological effectiveness (RBE) of neutrons in inflicting difficult-to-repair clusters of lesions in nuclear deoxyribonucleic acid (DNA). However, an investigation on the damaging effects of indirect radiation action is missing from such studies. In this work, we extended our group's existing simulation pipeline by incorporating and validating a model for indirect action. Our updated simulation pipeline was used to study the impact of indirect action and estimate neutron RBE for inflicting clustered lesions in DNA. In our results, although indirect action significantly increased the average yield of DNA damage clusters, our neutron RBE values are lower in magnitude than previous estimates due to model limitations and the greater relative impact of indirect action in lower-linear energy transfer (LET) radiation than in higher-LET radiation.

Geant4-DNA simulation of human cancer cells irradiation with helium ion beams

PURPOSE

This study aimed to develop a computational environment for the accurate simulation of human cancer cell irradiation using Geant4-DNA. New cell geometrical models were developed and irradiated by alpha particle beams to induce DNA damage. The proposed approach may help further investigation of the benefits of external alpha irradiation therapy.

METHODS

The Geant4-DNA Monte Carlo (MC) toolkit allows the simulation of cancer cell geometries that can be combined with accurate modelling of physical, physicochemical and chemical stages of liquid water irradiation, including radiolytic processes. Geant4-DNA is used to calculate direct and non-direct DNA damage yields, such as single and double strand breaks, produced by the deposition of energy or by the interaction of DNA with free radicals.

RESULTS

In this study, the "molecularDNA" example application of Geant4-DNA was used to quantify early DNA damage in human cancer cells upon irradiation with alpha particle beams, as a function of linear energy transfer (LET). The MC simulation results are compared to experimental data, as well as previously published simulation data. The simulation results agree well with the experimental data on DSB yields in the lower LET range, while the experimental data on DSB yields are lower than the results obtained with the "molecularDNA" example in the higher LET range.

CONCLUSION

This study explored and demonstrated the possibilities of the Geant4-DNA toolkit together with the "molecularDNA" example to simulate the helium beam irradiation of cancer cell lines, to quantify the early DNA damage, or even the following DNA damage response.

In-silico calculations of DNA damage induced by α-particles in the 224Ra DaRT decay chain for a better understanding of the radiobiological effectiveness of this treatment

Diffusing alpha-emitters radiation Therapy (DaRT) is an interstitial brachytherapy technique using 224Ra seeds. For accurate treatment planning a good understanding of the early DNA damage due to α-particles is required. Geant4-DNA was used to calculate the initial DNA damage and radiobiological effectiveness due to α-particles with linear energy transfer (LET) values in the range 57.5-225.9 keV/μm from the 224Ra decay chain. The impact of DNA base pair density on DNA damage has been modelled, as this parameter varies between human cell lines. Results show that the quantity and complexity of DNA damage changes with LET as expected. Indirect damage, due to water radical reactions with the DNA, decreases and becomes less significant at higher LET values as shown in previous studies. As expected, the yield of complex double strand breaks (DSBs), which are harder for a cell to repair, increases approximately linearly with LET. The level of complexity of DSBs and radiobiological effectiveness have been found to increase with LET as expected. The quantity of DNA damage has been shown to increase for increased DNA density in the expected base pair density range of human cells. The change in damage yield as a function of base pair density is largest for higher LET α-particles, an increase of over 50% for individual strand breaks between 62.7 and 127.4 keV/μm. This change in yield shows that the DNA base pair density is an important parameter for modelling DNA damage particularly at higher LET where the DNA damage is greatest and most complex.

MINAS TIRITH: a new tool for simulating radiation-induced DNA damage at the cell population level

Objective. The mechanisms of radiation-induced DNA damage can be understood via the fundamental acquisition of knowledge through a combination of experiments and modeling. Currently, most biological experiments are performed by irradiating an entire cell population, whereas modeling of radiation-induced effects is usually performed via Monte Carlo simulations with track structure codes coupled to realistic DNA geometries of a single-cell nucleus. However, the difference in scale between the two methods hinders a direct comparison because the dose distribution in the cell population is not necessarily uniform owing to the stochastic nature of the energy deposition. Thus, this study proposed the MINAS TIRITH tool to model the distribution of radiation-induced DNA damage in a cell population.Approach. The proposed method is based on precomputed databases of microdosimetric parameters and DNA damage distributions generated using the Geant4-DNA Monte Carlo Toolkit. First, a specific energyzwas assigned to each cell of an irradiated population for a particular absorbed doseDabs,following microdosimetric formalism. Then, each cell was assigned a realistic number of DNA damage events according to the specific energyz,respecting the stochastic character of its occurrence.Main results. This study validated the MINAS TIRITH tool by comparing its results with those obtained using the Geant4-DNA track structure code and a Geant4-DNA based simulation chain for DNA damage calculation. The different elements of comparison indicated consistency between MINAS TIRITH and the Monte Carlo simulation in case of the dose distribution in the population and the calculation of the amount of DNA damage.Significance. MINAS TIRITH is a new approach for the calculation of radiation-induced DNA damage at the cell population level that facilitates reasonable simulation times compared to those obtained with track structure codes. Moreover, this tool enables a more direct comparison between modeling and biological experimentation.

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.

Development of modified microdosimetric kinetic model for relative biological effectiveness in proton therapy

To predict the biological effects of ionising radiation, the quantity of biological dose is introduced instead of the physical absorbed dose. In proton therapy, a constant relative biological effectiveness (RBE) of 1.1 is usually applied clinically as recommended by the International Commission of Radiation Units and Measurements. This study presents a new model, based on the modified microdosimetric kinetic model (MMKM), for calculating variable RBE values based on experimental data on the induction of DNA double-strand breaks (DSBs) within cells. The MMKM was proposed based on experimental data for the yield of DSBs in mammalian cells, which allows modification of the yield of primary lesions in the MKM. In this approach, a unique function named f(LET), which describes the relation between RBE and linear energy transfer (LET), was considered for charged particles. In the presented model (DMMKM), the MMKM approach was developed further by considering different f(LET)s for different relevant ions involved in energy deposition events in proton therapy. Although experimental data represent the dependence of the yield of primary lesions on the ion species, the DSB yield (assumed as the main primary lesion) is assumed independent of the ion species in the MMKM. In the DMMKM, by considering the yield of primary lesions as a function of the ion species, the α and β values are in better agreement with the experimental data as compared to those of the MKM and MMKM approaches. The biological dose in the DMMKM is predicted to be lower than that in the MMKM. Further, in the proposed model, the variation of the β parameter is higher than the constant value assumed in the MKM, at the distal end of the spread-out Bragg peak (SOBP). Moreover, the level of cell death estimated by the MMKM at the SOBP region is higher than that obtained based on the DMMKM. It is concluded that considering modified f(LET)s in the model developed here is more consistent with experimental results than when MMKM and MKM approaches are considered. The DMMKM examines the biological effects with full detail and will, therefore, be effective in improving proton therapy.

Nanoscale Calculation of Proton-Induced DNA Damage Using a Chromatin Geometry Model with Geant4-DNA

Monte Carlo simulations can quantify various types of DNA damage to evaluate the biological effects of ionizing radiation at the nanometer scale. This work presents a study simulating the DNA target response after proton irradiation. A chromatin fiber model and new physics constructors with the ELastic Scattering of Electrons and Positrons by neutral Atoms (ELSEPA) model were used to describe the DNA geometry and the physical stage of water radiolysis with the Geant4-DNA toolkit, respectively. Three key parameters (the energy threshold model for strand breaks, the physics model and the maximum distance to distinguish DSB clusters) of scoring DNA damage were studied to investigate the impact on the uncertainties of DNA damage. On the basis of comparison of our results with experimental data and published findings, we were able to accurately predict the yield of various types of DNA damage. Our results indicated that the difference in physics constructor can cause up to 56.4% in the DNA double-strand break (DSB) yields. The DSB yields were quite sensitive to the energy threshold for strand breaks (SB) and the maximum distance to classify the DSB clusters, which were even more than 100 times and four times than the default configurations, respectively.

Nanodosimetric Calculations of Radiation-Induced DNA Damage in a New Nucleus Geometrical Model Based on the Isochore Theory

Double-strand breaks (DSBs) in nuclear DNA represents radiation-induced damage that has been identified as particularly deleterious. Calculating this damage using Monte Carlo track structure modeling could be a suitable indicator to better assess and anticipate the side-effects of radiation therapy. However, as already demonstrated in previous work, the geometrical description of the nucleus and the DNA content used in the simulation significantly influence damage calculations. Therefore, in order to obtain accurate results, this geometry must be as realistic as possible. In this study, a new geometrical model of an endothelial cell nucleus and DNA distribution according to the isochore theory are presented and used in a Monte Carlo simulation chain based on the Geant4-DNA toolkit. In this theory, heterochromatin and euchromatin compaction are distributed along the genome according to five different families (L1, L2, H1, H2, and H3). Each of these families is associated with a different hetero/euchromatin rate related to its compaction level. In order to compare the results with those obtained using a previous nuclear geometry, simulations were performed for protons with linear energy transfers (LETs) of 4.29 keV/µm, 19.51 keV/µm, and 43.25 keV/µm. The organization of the chromatin fibers at different compaction levels linked to isochore families increased the DSB yield by 6-10%, and it allowed the most affected part of the genome to be identified. These new results indicate that the genome core is more radiosensitive than the genome desert, with a 3-8% increase in damage depending on the LET. This work highlights the importance of using realistic distributions of chromatin compaction levels to calculate radio-induced damage using Monte Carlo simulation methods.

Track-structure modes in particle and heavy ion transport code system (PHITS): application to radiobiological research

PURPOSE

In radiation physics, Monte Carlo radiation transport simulations are powerful tools to evaluate the cellular responses after irradiation. When investigating such radiation-induced biological effects, it is essential to perform track structure simulations by explicitly considering each atomic interaction in liquid water at the sub-cellular and DNA scales. The Particle and Heavy-Ion Transport code System (PHITS) is a Monte Carlo code which enables to calculate track structure at DNA scale by employing the track-structure modes for electrons, protons and carbon ions. In this paper, we review the recent development status and future prospects of the track-structure modes in the PHITS code.

CONCLUSIONS

To date, the physical features of these modes have been verified using the available experimental data and Monte Carlo simulation results reported in literature. These track-structure modes can be used for calculating microdosimetric distributions to estimate cell survival and for estimating initial DNA damage yields. The use of PHITS track-structure mode is expected not only to clarify the underlying mechanisms of radiation effects but also to predict curative effects in radiation therapy. The results of PHITS simulations coupled with biophysical models will contribute to the radiobiological studies by precisely predicting radiation-induced biological effects based on the Monte Carlo approach.

A Geant4-DNA Evaluation of Radiation-Induced DNA Damage on a Human Fibroblast

Simple Summary

DNA damage caused by ionizing radiation in a human fibroblast cell evaluated by the Geant4-DNA Monte Carlo toolkit is presented. A validation study using a computational geometric human DNA model was then carried out, and the calculated DNA damage as a function of particle type and energy is presented. The results of this work showed a significant improvement on past work and were consistent with recent radiobiological experimental data, such as damage yields. This work and the developed methodology could impact a broad number of research fields in which the understanding of radiation effects is crucial, such as cancer radiotherapy, space science, and medical physics.

Abstract

Accurately modeling the radiobiological mechanisms responsible for the induction of DNA damage remains a major scientific challenge, particularly for understanding the effects of low doses of ionizing radiation on living beings, such as the induction of carcinogenesis. A computational approach based on the Monte Carlo technique to simulate track structures in a biological medium is currently the most reliable method for calculating the early effects induced by ionizing radiation on DNA, the primary cellular target of such effects. The Geant4-DNA Monte Carlo toolkit can simulate not only the physical, but also the physico-chemical and chemical stages of water radiolysis. These stages can be combined with simplified geometric models of biological targets, such as DNA, to assess direct and indirect early DNA damage. In this study, DNA damage induced in a human fibroblast cell was evaluated using Geant4-DNA as a function of incident particle type (gammas, protons, and alphas) and energy. The resulting double-strand break yields as a function of linear energy transfer closely reproduced recent experimental data. Other quantities, such as fragment length distribution, scavengeable damage fraction, and time evolution of damage within an analytical repair model also supported the plausibility of predicting DNA damage using Geant4-DNA.The complete simulation chain application “molecularDNA”, an example for users of Geant4-DNA, will soon be distributed through Geant4.

Strong Shift to ATR-Dependent Regulation of the G2-Checkpoint after Exposure to High-LET Radiation

The utilization of high linear-energy-transfer (LET) ionizing radiation (IR) modalities is rapidly growing worldwide, causing excitement but also raising concerns, because our understanding of their biological effects is incomplete. Charged particles such as protons and heavy ions have increasing potential in cancer therapy, due to their advantageous physical properties over X-rays (photons), but are also present in the space environment, adding to the health risks of space missions. Therapy improvements and the protection of humans during space travel will benefit from a better understanding of the mechanisms underpinning the biological effects of high-LET IR. There is evidence that high-LET IR induces DNA double-strand breaks (DSBs) of increasing complexity, causing enhanced cell killing, owing, at least partly, to the frequent engagement of a low-fidelity DSB-repair pathway: alternative end-joining (alt-EJ), which is known to frequently induce severe structural chromosomal abnormalities (SCAs). Here, we evaluate the radiosensitivity of A549 lung adenocarcinoma cells to X-rays, α-particles and ⁵⁶Fe ions, as well as of HCT116 colorectal cancer cells to X-rays and α-particles. We observe the expected increase in cell killing following high-LET irradiation that correlates with the increased formation of SCAs as detected by mFISH. Furthermore, we report that cells exposed to low doses of α-particles and ⁵⁶Fe ions show an enhanced G₂-checkpoint response which is mainly regulated by ATR, rather than the coordinated ATM/ATR-dependent regulation observed after exposure to low doses of X-rays. These observations advance our understanding of the mechanisms underpinning high-LET IR effects, and suggest the potential utility for ATR inhibitors in high-LET radiation therapy.

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.

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.

Modern Radiotherapy and Risk of Cardiotoxicity

Despite the advancements of modern radiotherapy, radiation-induced heart disease remains a common cause of morbidity and mortality amongst cancer survivors. This review outlines the basic mechanism, clinical presentation, risk stratification, early detection, possible mitigation, and treatment of this condition.

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.

Occam's broom and the dirty DSB: cytogenetic perspectives on cellular response to changes in track structure and ionization density

Given equal doses, it is well-known that densely ionizing radiations are more potent in causing a number of biological effects compared to sparsely ionizing radiations, such as x- or gamma rays. According to classical models of radiation action, this results from differences in the spatial distribution of lesions along charged particle tracks. In recent years investigators have been barraged with the alternative narrative that this is instead due to 'qualitative' differences in the types of molecular lesions that each type of radiation produces. The present review discusses, mainly from a cytogenetic perspective, the merits and shortcomings of these seemingly contradictory viewpoints. There may be a kernel of truth to the idea that qualitative differences in the types of molecular lesions produced at the nanometer level affect RBE/LET relationships, but to ignore the fact that such differences result from longer-range spatial distributions of lesions produced along charged particle tracks is an unjustifiably narrow stance tantamount to employing Occam's Broom. Not only are such spatial considerations indispensable in explaining the impact of ionization density upon higher-order biological endpoints, particularly chromosome aberrations, the explanations they provide render arguments based principally on the quality of IR damage largely superfluous.

SIMULATION OF EARLY RADIATION-INDUCED DNA DAMAGE ON DIFFERENT TYPES OF CELL NUCLEI

This work presents a comparison of simulated early radiation-induced DNA damage represented by yields of double-strand breaks (DSB) in three different human cell nuclei geometries representing fibroblasts, lymphocytes and endothelial cells for protons and alpha particles of different energies and for different irradiation configurations. Each cell nucleus model includes a multi-scale description of the DNA target from the molecular level to the whole human genome representation (6 Gbp) in the G0/G1 phase of the cell cycle and was generated with the DnaFabric software. The three nuclei differ in shape, volume, and therefore DNA density. A calculation chain based on Geant4-DNA that takes into account the physical, physico-chemical and chemical stages was used to simulate the irradiation of the different cell nuclei. Results show an increase of DSB/primary/μm with an increase of DNA density and an increase of DSB/Gy/Gbp with an increase of the cell nucleus volume which indicates that the cell nucleus shape and size have an impact on early DNA damage, which may play a role in latter effects.

Accounting for radiation-induced indirect damage on DNA with the Geant 4-DNA code

The use of Monte Carlo (MC) simulations remains a powerful tool to study the biological effects induced by ionizing radiation on living beings. Several MC codes are commonly used in research fields such as nanodosimetry, radiotherapy, radiation protection, and space radiation. This work presents an enhancement of an existing model [1] for radiobiological purposes, to account for the indirect DNA damage induced by ionizing particles. The Geant4-DNA simulation toolkit was used to simulate the physical, pre-chemical, and chemical stages of early DNA damage induced by protons and α-particles. Liquid water was used as the medium for simulations. Two phase-space files were generated, one containing the energy deposition events and another with the position of chemical species produced by water radiolysis from 0.1 ps up to 1 ns. These files were used as input in the radiobiological code that contains the genetic material model with atomic resolution, consisting of several copies of 30 nm chromatin fibers. The B-DNA configuration was used. This work focused on the indirect damage produced by the hydroxyl radical (OH) attack on the sugar-phosphate group. The approach followed to account for the indirect DNA damage was the same as those used by other radiobiological codes [2,3]. The critical parameter considered here was the reaction radius, which was calculated from the Smoluchowski's diffusion equation. Single, double, and total strand break yields produced by direct, indirect, and mixed mechanisms are reported. The obtained results are consistent with experimental and calculation data sets published in the literature.

Simulation of early DNA damage after the irradiation of a fibroblast cell nucleus using Geant4-DNA

In order to improve the understanding of the mechanisms involved in the generation of early DNA damage, a new calculation chain based on the Geant4-DNA toolkit was developed. This work presents for the first time the simulation of the physical, physicochemical and chemical stages of early radiation damage at the scale of an entire human genome (fibroblast, male) and using Geant4-DNA models. The DnaFabric software was extended to generate and export this nucleus model to a text file with a specific format that can be read by Geant4 user applications. This calculation chain was used to simulate the irradiation of the nucleus by primary protons of different energies (0,5; 0,7; 0,8; 1; 1,5; 2; 3; 4; 5; 10; 20 MeV) and the results, in terms of DNA double strand breaks, agree with experimental data found in the literature (pulsed field electrophoresis technique). These results show that the simulation is consistent and that its parameters are well balanced. Among the different parameters that can be adjusted, our results demonstrate that the criterion used to select direct strand break appears to have a very significant role on the final number of simulated double strand breaks.

Proton and light ion RBE for the induction of direct DNA double strand breaks

PURPOSE

To present and characterize a Monte Carlo (MC) tool for the simulation of the relative biological effectiveness for the induction of direct DNA double strand breaks (RBEDSB (direct)) for protons and light ions.

METHODS

The MC tool uses a pregenerated event-by-event tracks library of protons and light ions that are overlaid on a cell nucleus model. The cell nucleus model is a cylindrical arrangement of nucleosome structures consisting of 198 DNA base pairs. An algorithm relying on k-dimensional trees and cylindrical symmetries is used to search coincidences of energy deposition sites with volumes corresponding to the sugar-phosphate backbone of the DNA molecule. Strand breaks (SBs) are scored when energy higher than a threshold is reached in these volumes. Based on the number of affected strands, they are categorized into either single strand break (SSB) or double strand break (DSB) lesions. The number of SBs composing each lesion (i.e., its size) is also recorded. RBEDSB (direct) is obtained by taking the ratio of DSB yields of a given radiation field to a (60)Co field. The MC tool was used to obtain SSB yields, DSB yields, and RBEDSB (direct) as a function of linear energy transfer (LET) for protons ((1)H(+)), (4)He(2+), (7)Li(3+), and (12)C(6+) ions.

RESULTS

For protons, the SSB yields decreased and the DSB yields increased with LET. At ≈24.5 keV μm(-1), protons generated 15% more DSBs than (12)C(6+) ions. The RBEDSB (direct) varied between 1.24 and 1.77 for proton fields between 8.5 and 30.2 keV μm(-1), and it was higher for iso-LET ions with lowest atomic number. The SSB and DSB lesion sizes showed significant differences for all radiation fields. Generally, the yields of SSB lesions of sizes ≥2 and the yields of DSB lesions of sizes ≥3 increased with LET and increased for iso-LET ions of lower atomic number. On the other hand, the ratios of SSB to DSB lesions of sizes 2-4 did not show variability with LET nor projectile atomic number, suggesting that these metrics are independent of the radiation quality. Finally, a variance of up to 8% in the DSB yields was observed as a function of the particle incidence angle on the cell nucleus. This simulation effect is due to the preferential alignment of ion tracks with the DNA nucleosomes at specific angles.

CONCLUSIONS

The MC tool can predict SSB and DSB yields for light ions of various LET and estimate RBEDSB (direct). In addition, it can calculate the frequencies of different DNA lesion sizes, which is of interest in the context of biologically relevant absolute dosimetry of particle beams.

Transcription Factors in the Cellular Response to Charged Particle Exposure

Charged particles, such as carbon ions, bear the promise of a more effective cancer therapy. In human spaceflight, exposure to charged particles represents an important risk factor for chronic and late effects such as cancer. Biological effects elicited by charged particle exposure depend on their characteristics, e.g., on linear energy transfer (LET). For diverse outcomes (cell death, mutation, transformation, and cell-cycle arrest), an LET dependency of the effect size was observed. These outcomes result from activation of a complex network of signaling pathways in the DNA damage response, which result in cell-protective (DNA repair and cell-cycle arrest) or cell-destructive (cell death) reactions. Triggering of these pathways converges among others in the activation of transcription factors, such as p53, nuclear factor κB (NF-κB), activated protein 1 (AP-1), nuclear erythroid-derived 2-related factor 2 (Nrf2), and cAMP responsive element binding protein (CREB). Depending on dose, radiation quality, and tissue, p53 induces apoptosis or cell-cycle arrest. In low LET radiation therapy, p53 mutations are often associated with therapy resistance, while the outcome of carbon ion therapy seems to be independent of the tumor's p53 status. NF-κB is a central transcription factor in the immune system and exhibits pro-survival effects. Both p53 and NF-κB are activated after ionizing radiation exposure in an ataxia telangiectasia mutated (ATM)-dependent manner. The NF-κB activation was shown to strongly depend on charged particles' LET, with a maximal activation in the LET range of 90-300 keV/μm. AP-1 controls proliferation, senescence, differentiation, and apoptosis. Nrf2 can induce cellular antioxidant defense systems, CREB might also be involved in survival responses. The extent of activation of these transcription factors by charged particles and their interaction in the cellular radiation response greatly influences the destiny of the irradiated and also neighboring cells in the bystander effect.

Monte Carlo simulations of the relative biological effectiveness for DNA double strand breaks from 300 MeV u(-1) carbon-ion beams

Monte Carlo simulations are used to calculate the relative biological effectiveness (RBE) of 300 MeV u(-1) carbon-ion beams at different depths in a cylindrical water phantom of 10 cm radius and 30 cm long. RBE values for the induction of DNA double strand breaks (DSB), a biological endpoint closely related to cell inactivation, are estimated for monoenergetic and energy-modulated carbon ion beams. Individual contributions to the RBE from primary ions and secondary nuclear fragments are simulated separately. These simulations are based on a multi-scale modelling approach by first applying the FLUKA (version 2011.2.17) transport code to estimate the absorbed doses and fluence energy spectra, then using the MCDS (version 3.10A) damage code for DSB yields. The approach is efficient since it separates the non-stochastic dosimetry problem from the stochastic DNA damage problem. The MCDS code predicts the major trends of the DSB yields from detailed track structure simulations. It is found that, as depth is increasing, RBE values increase slowly from the entrance depth to the plateau region and change substantially in the Bragg peak region. RBE values reach their maxima at the distal edge of the Bragg peak. Beyond this edge, contributions to RBE are entirely from nuclear fragments. Maximum RBE values at the distal edges of the Bragg peak and the spread-out Bragg peak are, respectively, 3.0 and 2.8. The present approach has the flexibility to weight RBE contributions from different DSB classes, i.e. DSB0, DSB+ and DSB++.

DSB repair model for mammalian cells in early S and G1 phases of the cell cycle: application to damage induced by ionizing radiation of different quality

The purpose of this work is to test the hypothesis that kinetics of double strand breaks (DSB) repair is governed by complexity of DSB. To test the hypothesis we used our recent published mechanistic mathematical model of DSB repair for DSB induced by selected protons, deuterons, and helium ions of different energies representing radiations of different qualities. In light of recent advances in experimental and computational techniques, the most appropriate method to study cellular responses in radiation therapy, and exposures to low doses of ionizing radiations is using mechanistic approaches. To this end, we proposed a 'bottom-up' approach to study cellular response that starts with the DNA damage. Monte Carlo track structure method was employed to simulate initial damage induced in the genomic DNA by direct and indirect effects. Among the different types of DNA damage, DSB are known to be induced in simple and complex forms. The DSB repair model in G1 and early S phases of the cell cycle was employed to calculate the repair kinetics. The model considers the repair of simple and complex DSB, and the DSB produced in the heterochromatin. The inverse sampling method was used to calculate the repair kinetics for each individual DSB. The overall repair kinetics for 500 DSB induced by single tracks of the radiation under test were compared with experimental results. The results show that the model is capable of predicting the repair kinetics for the DSB induced by radiations of different qualities within an accepted range of uncertainty.

Relative biological effectiveness (RBE) values for proton beam therapy. Variations as a function of biological endpoint, dose, and linear energy transfer

Proton therapy treatments are based on a proton RBE (relative biological effectiveness) relative to high-energy photons of 1.1. The use of this generic, spatially invariant RBE within tumors and normal tissues disregards the evidence that proton RBE varies with linear energy transfer (LET), physiological and biological factors, and clinical endpoint. Based on the available experimental data from published literature, this review analyzes relationships of RBE with dose, biological endpoint and physical properties of proton beams. The review distinguishes between endpoints relevant for tumor control probability and those potentially relevant for normal tissue complication. Numerous endpoints and experiments on sub-cellular damage and repair effects are discussed. Despite the large amount of data, considerable uncertainties in proton RBE values remain. As an average RBE for cell survival in the center of a typical spread-out Bragg peak (SOBP), the data support a value of ~1.15 at 2 Gy/fraction. The proton RBE increases with increasing LETd and thus with depth in an SOBP from ~1.1 in the entrance region, to ~1.15 in the center, ~1.35 at the distal edge and ~1.7 in the distal fall-off (when averaged over all cell lines, which may not be clinically representative). For small modulation widths the values could be increased. Furthermore, there is a trend of an increase in RBE as (α/β)x decreases. In most cases the RBE also increases with decreasing dose, specifically for systems with low (α/β)x. Data on RBE for endpoints other than clonogenic cell survival are too diverse to allow general statements other than that the RBE is, on average, in line with a value of ~1.1. This review can serve as a source for defining input parameters for applying or refining biophysical models and to identify endpoints where additional radiobiological data are needed in order to reduce the uncertainties to clinically acceptable levels.

Influence of chromatin condensation on the number of direct DSB damages induced by ions studied using a Monte Carlo code

The purpose of this work is to evaluate the influence of the chromatin condensation on the number of direct double-strand break (DSB) damages induced by ions. Two geometries of chromosome territories containing either condensed or decondensed chromatin were implemented as biological targets in the Geant4 Monte Carlo simulation code and proton and alpha irradiation was simulated using the Geant4-DNA processes. A DBSCAN algorithm was used in order to detect energy deposition clusters that could give rise to single-strand breaks or DSBs on the DNA molecule. The results of this study show an increase in the number and complexity of DNA DSBs in condensed chromatin when compared with decondensed chromatin.

Integration of Monte Carlo simulations with PFGE experimental data yields constant RBE of 2.3 for DNA double-strand break induction by nitrogen ions between 125 and 225 keV/μm LET

The number of small radiation-induced DNA fragments can be heavily underestimated when determined from measurements of DNA mass fractions by gel electrophoresis, leading to a consequent underestimation of the initial DNA damage induction. In this study we reanalyzed the experimental results for DNA fragmentation and DNA double-strand break (DSB) yields in human fibroblasts irradiated with γ rays and nitrogen ion beams with linear energy transfer (LET) equal to 80, 125, 175 and 225 keV/μm, originally measured by Höglund et al. (Radiat Res 155, 818-825, 2001 and Int J Radiat Biol 76, 539-547, 2000). In that study the authors converted the measured distributions of fragment masses into DNA fragment distributions using mid-range values of the measured fragment length intervals, in particular they assumed fragments with lengths in the interval of 0-48 kbp had the mid-range value of 24 kbp. However, our recent detailed simulations with the Monte Carlo code PARTRAC, while reasonably in agreement with the mass distributions, indicate significantly increased yields of very short fragments by high-LET radiation, so that the actual average fragment lengths, in the interval 0-48 kbp, 2.4 kbp for 225 keV/μm nitrogen ions were much shorter than the assumed mid-range value of 24 kbp. When the measured distributions of fragment masses are converted into fragment distributions using the average fragment lengths calculated by PARTRAC, significantly higher yields of DSB related to short fragments were obtained and resulted in a constant relative biological effectiveness (RBE) for DSB induction yield of 2.3 for nitrogen ions at 125-225 keV/μm LET. The previously reported downward trend of the RBE values over this LET range for DSB induction appears to be an artifact of an inadequate average fragment length in the smallest interval.

Estimated yield of double-strand breaks from internal exposure to tritium

Internal exposure to tritium may result in DNA lesions. Of those, DNA double-strand breaks (DSBs) are believed to be important. However, experimental and computational data of DSBs induction by tritium are very limited. In this study, microdosimetric characteristics of uniformly distributed tritium were determined in dimensions of critical significance in DNA DSBs. Those characteristics were used to identify other particles comparable to tritium in terms of microscopic energy deposition. The yield of DSBs could be strongly dependent on biological systems and cellular environments. After reviewing theoretically predicted and experimentally determined DSB yields available in the literature for low-energy electrons and high-energy protons of comparable microdosimetric characteristics to tritium in the dimensions relevant to DSBs, it is estimated that the average DSB yields of 2.7 × 10(-11), 0.93 × 10(-11), 2.4 × 10(-11) and 1.6 × 10(-11) DSBs Gy(-1) Da(-1) could be reasonable estimates for tritium in plasmid DNAs, yeast cells, Chinese hamster V79 cells and human fibroblasts, respectively. If a biological system is not specified, the DSB yield from tritium exposure can be estimated as (2.3 ± 0.7) × 10(-11) DSBs Gy(-1) Da(-1), which is a simple average over experimentally determined yields of DSBs for low-energy electrons in various biological systems without considerations of variations caused by different techniques used and obvious differences among different biological systems where the DSB yield was measured.

Mutation induction by inhaled radon progeny modeled at the tissue level

The observable responses of living systems to ionizing radiation depend on the level of biological organization studied. Understanding the relationships between the responses characteristic of the different levels of organization is of crucial importance. The main objective of the present study is to investigate how some cellular effects of radiation manifest at the tissue level by modeling mutation induction due to chronic exposure to inhaled radon progeny. For this purpose, a mathematical model of the bronchial epithelium was elaborated to quantify cell nucleus hits and cell doses. Mutagenesis was modeled considering endogenous as well as radiation-induced DNA damages and cell cycle shortening due to cell inactivation. The model parameters describing the cellular effects of radiation are obtained from experimental data. Cell nucleus hits, cell doses, and mutation induction were computed for the activity hot spots of the large bronchi at different exposures. Results demonstrate that the mutagenic effect of densely ionizing radiation is dominated by cell cycle shortening due to cell inactivation and not by DNA damages. This suggests that radiation burdens of non-progenitor cells play a significant role in mutagenesis in case of protracted exposures to densely ionizing radiation. Mutation rate as a function of dose rate exhibits a convex shape below a threshold. This threshold indicates the exhaustion of the tissue regeneration capacity of local progenitor cells. It is suggested that progenitor cell hyperplasia occurs beyond the threshold dose rate, giving a possible explanation of the inverse dose-rate effect observed in the epidemiology of lung cancer among uranium miners.

Response of primary human fibroblasts exposed to solar particle event protons

Solar particle events (SPEs) present a major radiation-related risk for manned exploratory missions in deep space. Within a short period the astronauts may absorb doses that engender acute effects, in addition to the risk of late effects, such as the induction of cancer. Using primary human cells, we studied clonogenic survival and the induction of neoplastic transformation after exposure to a worst case scenario SPE. We simulated such an SPE with monoenergetic protons (50, 100, 1000 MeV) delivered at a dose rate of 1.65 cGy min⁻¹ in a dose range from 0 to 3 Gy. For comparison, we exposed the cells to a high dose rate of 33.3 cGy min⁻¹. X rays (100 kVp, 8 mA, 1.7 mm Al filter) were used as a reference radiation. Overall, we observed a significant sparing effect of the SPE dose rate on cell survival. High-dose-rate protons were also more efficient in induction of transformation in the dose range below 30 cGy. However, as dose accumulated at high dose rate, the transformation levels declined, while at the SPE dose rate, the number of transformants continued to increase up to about 1 Gy. These findings suggest that considering dose-rate effects may be important in evaluating the biological effects of exposure to space radiation. Our analyses of the data based on particle fluence showed that lethality and transforming potential per particle clearly increased with increasing linear energy transfer (LET) and thus with the decreasing energy of protons. Further, we found that the biological response was determined not only by LET but also type of radiation, e.g. particles and photons. This suggests that using γ or X rays may not be ideal for assessing risk associated with SPE exposures.

Track structures, DNA targets and radiation effects in the biophysical Monte Carlo simulation code PARTRAC

This review describes the PARTRAC suite of comprehensive Monte Carlo simulation tools for calculations of track structures of a variety of ionizing radiation qualities and their biological effects. A multi-scale target model characterizes essential structures of the whole genomic DNA within human fibroblasts and lymphocytes in atomic resolution. Calculation methods and essential results are recapitulated regarding the physical, physico-chemical and chemical stage of track structure development of radiation damage induction. Recent model extension towards DNA repair processes extends the time dimension by about 12 orders of magnitude and paves the way for superior predictions of radiation risks.

RBE of low energy electrons and photons

Relative biological effectiveness (RBE) compares the severity of damage induced by a radiation under test at a dose D relative to the reference radiation D(x) for the same biological endpoint. RBE is an important parameter in estimation of risk from exposure to ionizing radiation (IR). The present work provides a review of the recently published data and the knowledge of the RBE of low energy electrons and photons. The review presents RBE values derived from experimental data and model calculations including cell inactivation, chromosome aberration, cell transformation, micronuclei formation and induction of double-strand breaks. Biophysical models, including physical features of radiation track, and microdosimetry parameters are presented, analysed and compared with experimental data. The biological effects of low energy electrons and photons are of particular interest in radiation biology as these are strongly absorbed in micrometer and sub-micrometer layers of tissue. RBE values not only depend on the electron and photon energies but also on the irradiation condition, cell type and experimental conditions.

The RBE of 3.4 MeV alpha-particles and 0.565 MeV neutrons relative to 60Co gamma-rays for neoplastic transformation of human hybrid cells and the impact of culture conditions

The neoplastic transformation of human hybrid CGL1 cells is affected by perturbations from external influences such as serum batch and concentration, the number of medium changes during the 21-day expression period and cell seeding density. Nevertheless, for doses up to 1.5 Gy, published transformation frequencies for low linear energy transfer (LET) radiations (gamma-rays, MeV electrons or photons) are in good agreement, whereas for higher doses larger variations are reported. The (60)Co gamma-ray data here for doses up to 1.5 Gy, using a low-yield serum batch and only one medium change, are in agreement with published frequencies of neoplastic transformation of human hybrid cells. For 3.4 MeV alpha-particles (LET = 124 keV/mum) and 0.565 MeV monoenergetic neutrons relative to low doses of (60)Co gamma-rays, a maximum relative biological effectiveness (RBE(M)) of 2.8 +/- 0.2 and 1.5 +/- 0.2, respectively, was calculated. Surprisingly, at higher doses of (60)Co gamma-rays lower frequencies of neoplastic transformation were observed. This non-monotonic dose relationship for neoplastic transformation by (60)Co gamma-rays is likely due to the lack of a G2/M arrest observed at low doses resulting in higher transformation frequencies per dose, whereas the lower frequencies per dose observed for higher doses are likely related to the induction of a G2/M arrest.