Calculation of the initial DNA damage induced by alpha particles in comparison with protons and electrons using Geant4-DNA

Radiation-induced DNA damage by proton, helium and carbon ions in human fibroblast cell: Geant4-DNA and MCDS-based study

Background. Radiation-induced DNA damages such as Single Strand Break (SSB), Double Strand Break (DSB) and Complex DSB (cDSB) are critical aspects of radiobiology with implications in radiotherapy and radiation protection applications.Materials and Methods. This study presents a thorough investigation into the effects of protons (0.1-100 MeV/u), helium ions (0.13-100 MeV/u) and carbon ions (0.5-480 MeV/u) on DNA of human fibroblast cells using Geant4-DNA track structure code coupled with DBSCAN algorithm and Monte Carlo Damage Simulations (MCDS) code. Geant4-DNA-based simulations consider 1μm × 1μm × 0.5μm water box as the target to calculate energy deposition on event-by-event basis and the three-dimensional coordinates of the interaction location, and then DBSCAN algorithm is used to calculate yields of SSB, DSB and cDSB in human fibroblast cell. The study investigated the influence of Linear Energy Transfer (LET) of protons, helium ions and carbon ions on the yields of DNA damages. Influence of cellular oxygenation on DNA damage patterns is investigated using MCDS code.Results. The study shows that DSB and SSB yields are influenced by the LET of the particles, with distinct trends observed for different particles. The cellular oxygenation is a key factor, with anoxic cells exhibiting reduced SSB and DSB yields, underscoring the intricate relationship between cellular oxygen levels and DNA damage. The study introduced DSB/SSB ratio as an informative metric for evaluating the severity of radiation-induced DNA damage, particularly in higher LET regions.Conclusions. The study highlights the importance of considering particle type, LET, and cellular oxygenation in assessing the biological effects of ionizing radiation.

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.

Calculation of the DNA damage yield and relative biological effectiveness in boron neutron capture therapy via the Monte Carlo track structure simulation

Objective.Boron neutron capture therapy (BNCT) is an advanced cellular-level hadron therapy that has exhibited remarkable therapeutic efficacy in the treatment of locally invasive malignancies. Despite its clinical success, the intricate nature of relative biological effectiveness (RBE) and mechanisms responsible for DNA damage remains elusive. This work aims to quantify the RBE of compound particles (i.e. alpha and lithium) in BNCT based on the calculation of DNA damage yields via the Monte Carlo track structure (MCTS) simulation.Approach. The TOPAS-nBio toolkit was employed to conduct MCTS simulations. The calculations encompassed four steps: determination of the angle and energy spectra on the nuclear membrane, quantification of the database containing DNA damage yields for ions with specific angle and energy, accumulation of the database and spectra to obtain the DNA damage yields of compound particles, and calculation of the RBE by comparison yields of double-strand break (DSB) with the reference gamma-ray. Furthermore, the impact of cell size and microscopic boron distribution was thoroughly discussed.Main results. The DSB yields induced by compound particles in three types of spherical cells (radius equal to 10, 8, and 6μm) were found to be 13.28, 17.34, 22.15 Gy Gbp-1for boronophenylalanine (BPA), and 1.07, 3.45, 8.32 Gy Gbp-1for sodium borocaptate (BSH). The corresponding DSB-based RBE values were determined to be 1.90, 2.48, 3.16 for BPA and 0.15, 0.49, 1.19 for BSH. The calculated DSB-based RBE showed agreement with experimentally values of compound biological effectiveness for melanoma and gliosarcoma. Besides, the DNA damage yield and DSB-based RBE value exhibited an increasing trend as the cell radius decreased. The impact of the boron concentration ratio on RBE diminished once the drug enrichment surpasses a certain threshold.Significance. This work is potential to provide valuable guidance for accurate biological-weighted dose evaluation in BNCT.

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.

Computational modeling and a Geant4-DNA study of the rejoining of direct and indirect DNA damage induced by low energy electrons and carbon ions

PURPOSE

DNA double-strand breaks (DSBs) created by ionizing radiations are considered as the most detrimental lesion, which could result in the cell death or sterilization. As the empirical evidence gathered from the cellular and molecular radiation biology has demonstrated significant correlations between the initial and lasting levels of DSBs, gaining knowledge into the DSB repair mechanisms proves vital. Much effort has been invested into understanding the mechanisms triggering the repair and processes engaged after irradiation of cells. Given a mechanistic model, we performed - to our knowledge - the first Monte Carlo study of the expected repair kinetics of carbon ions and electrons using on the one hand Geant4-DNA simulations of electrons for benchmarking purposes and on the other hand quantifying the influence of direct and indirect damage. Our objective was to calculate the DSB repair rates using a repair mechanism for G1 and early S phases of the cell cycle in conjunction with simulations of the DNA damage.

MATERIALS AND METHODS

Based on Geant4-DNA simulations of DSB damage caused by electrons and carbon ions - using a B-DNA model and a water sphere of 3 μm radius resembling the mean size of human cells - we derived the kinetics of various biochemical repair processes.

RESULTS

The overall repair times of carbon ions increased with the DSB complexity. Comparison of the DSB complexity (DSBc) and repair times as a function of carbon-ion energy suggested that the repair time of no specific fraction of DSBs could solely be explained as a function of DSB complexity.

CONCLUSION

Analysis of the carbon-ion repair kinetics indicated that, given a fraction of DSBs, decreasing the energy would result in an increase of the repair time. The disagreements of the calculated and experimental repair kinetics for electrons could, among others, be due to larger damage complexity predicted by simulations or created actually by electrons of comparable energies to x-rays. They are also due to the employed repair mechanisms, which introduce no inherent dependence on the radiation type but make direct use of the simulated DSBs.

DNA damage and microdosimetry for carbon ions: Track structure simulations as the key to quantitative modeling of radiation-induced damage

PURPOSE

Dose distribution in carbon-ion irradiations is generally envisaged to have therapeutic advantages over protons, primarily due to the carbon-ion's comparatively higher relative biological effectiveness (RBE) in the tumor than in the encompassing healthy tissues. The objective of this work was to simulate the overall physical and chemical reactions of primary carbon ions impinging on liquid water and, as such, to investigate the DNA-damage yields in the form of strand breaks (SBs) and in connection with the expected microdosimetric quantities.

MATERIALS AND METHODS

Using a B-DNA model and Geant4-DNA, we simulated the primary and secondary interactions in a spherical medium of water. Subsequently, we categorized DNA damages based on their complexity utilizing the concept of μ-randomness. We assumed a threshold of 17.5 eV for a direct SB and a probability of 0.13 for an indirect SB triggered by chemical reactions of hydroxyl radicals. Microdosimetric quantities were extracted for three cylindrical volumes representing typical sub-cellular organisms.

RESULTS

For fully-ionized carbons of 8 to 256 MeV/u, the yield results appeared to be considerably influenced by the chemical reactions - indicating the important role of secondary electrons in inflicting damage. However, it was mostly the direct-damage spectrum that determined the overall shape of the damage spectrum. At all primary energies, it was more probable to break each DNA strand at one point - the two points being less than 10 bp apart - than to break only one strand at two random points. Unlike proton's mean-specific-energy results, which showed more sensitivity to the volume increase of the smallest cylinder than of the larger ones, carbon-ion results showed no such sensitivity.

CONCLUSION

The growth of the yield ratio of the single- and double-strand breaks (SSB and DSB) with the particle energy was estimated for protons to be about two times that of alphas and 92 times that of carbon ions. Unlike the proton results, which suggested significant correlations between the DSB yields and mean specific (and lineal) energies, carbon ions exhibited no such correlations. This article is protected by copyright. All rights reserved.

Calculation of microdosimetric spectra for protons using Geant4-DNA and a μ-randomness sampling algorithm for the nanometric structures

PURPOSE

Through introducing stochastic quantities that can be connected to the dimensions of the microscopic structures exposed to radiations, microdosimetry is concerned with the substantive specifications of radiation quality that could help gain insight into radiation effects. Utilizing the μ-randomness method and Geant4-DNA code, we calculated microdosimetry quantities for nanometric structures in a spherical body of water irradiated with protons. To gain more insight into the effects of radiation on microscopic structures and validate the code parameters, we made a comparison between our results obtained within Geant4-DNA and results from other simulations.

MATERIALS AND METHODS

We calculated microdosimetric quantities through irradiating a spherical body of water of 6 μm diameter with 0.5-100 MeV protons. Microdosimetric quantities were derived for cylinders with diameter × height values of 23 × 23, 50 × 100, and 300 × 300 Å × Å, which would resemble the typical sizes of sub-cellular organisms such as the DNA, nucleosome, and chromatin fiber. We exploited the concept of μ-randomness to introduce convex bodies of random positions and directions for calculating microdosimetric quantities. We used the Geant4-DNA Monte Carlo simulation toolkit for transporting protons and secondary particles and calculating the frequency- and dose-mean lineal and specific energies in cylindrical volumes. Specifically, for same-sized cylindrical volumes, microdosimetric parameters obtained by Nikjoo et al. using the KURBUC code were used for evaluation.

RESULTS

For the energy range investigated, the frequency-mean lineal energy, dose-mean lineal energy, frequency-mean specific energy, and dose-mean specific energy vary within [2.34,47.06] (keV/μm), [10.40,68.55] (keV/μm), [0.04,39.38] × 10⁶ cGy, and [0.16,90.29] × 10⁶ cGy, respectively. Regardless of the proton energy, our specific-energy results showed higher sensitivity to volume change, for smaller cylinder volumes rather than larger ones. Regardless of both proton energy and volume of the cylinder under study, we observed a generally better agreement between our frequency-mean, than dose-mean, specific energy results and the KURBUC results.

CONCLUSION

Using Geant4-DNA to account for the stochastic nature of energy depositions due to physical interactions between radiation and matter, we calculated microdosimetry parameters concerning proton irradiation. By employing microdosimetry concepts in conjunction with simulation results of our previous work on radiation effects on the DNA, we pinpointed and quantified correlations between microdosimetry parameters and DNA damage. As such, for a volume with comparable mass and mean chord length to the DNA, we could observe the clear correspondence of the mean lineal and specific energy results with the double-strand-break yields of protons in Gy^-1.Gbp^-1.

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.