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

DNA-damage RBE assessment for combined boron and gadolinium neutron capture therapy

PURPOSE

Neutron capture therapy (NCT) by 10B and 157Gd agents is a unique irradiation-based method which can be used to treat brain tumors. Current study aims to quantitatively evaluate the relative biological effectiveness (RBE) and dose distributions during the combined BNCT and GdNCT modalities through a hybrid Monte Carlo (MC) simulation approach.

METHODS

Snyder head phantom as well as a cubic hypothetical tumor was at first modeled by Geant4 MC Code. Then, the energy spectra and dose distribution relevant to the released secondary particles during the combined Gd/BNCT were scored for different concentrations of 157Gd and 10B inside tumor volume. Finally, the scored energy spectra were imported to the MCDS code to estimate both RBESSB and RBEDSB values for different 157Gd concentrations.

RESULTS

The results showed that combined Gd/BNCT increases the fluence-averaged RBESSB values by about 1.7 times when 157Gd concentration increments from 0 to 2000 µg/g for both considered cell oxygen levels (pO2 = 10% and 100%). Besides, a reduction of about 26% was found for fluence-averaged RBEDSB values with an increment of 157Gd concentration in tumor volume.

CONCLUSION

From the results, it can be concluded that combined Gd/BNCT technique can improve tumor coverage with higher dose levels but in the expense of RBEDSB reduction which can affect the clinical efficacy of the NCT technique.

RadPhysBio: A Radiobiological Database for the Prediction of Cell Survival upon Exposure to Ionizing Radiation

Based on the need for radiobiological databases, in this work, we mined experimental ionizing radiation data of human cells treated with X-rays, γ-rays, carbon ions, protons and α-particles, by manually searching the relevant literature in PubMed from 1980 until 2024. In order to calculate normal and tumor cell survival α and β coefficients of the linear quadratic (LQ) established model, as well as the initial values of the double-strand breaks (DSBs) in DNA, we used WebPlotDigitizer and Python programming language. We also produced complex DNA damage results through the fast Monte Carlo code MCDS in order to complete any missing data. The calculated α/β values are in good agreement with those valued reported in the literature, where α shows a relatively good association with linear energy transfer (LET), but not β. In general, a positive correlation between DSBs and LET was observed as far as the experimental values are concerned. Furthermore, we developed a biophysical prediction model by using machine learning, which showed a good performance for α, while it underscored LET as the most important feature for its prediction. In this study, we designed and developed the novel radiobiological 'RadPhysBio' database for the prediction of irradiated cell survival (α and β coefficients of the LQ model). The incorporation of machine learning and repair models increases the applicability of our results and the spectrum of potential users.

Impact of gadolinium concentration and cell oxygen levels on radiobiological characteristics of gadolinium neutron capture therapy technique in brain tumor treatment

Neutron capture therapy (NCT) with various concentrations of gadolinium (157Gd) is one of the treatment modalities for glioblastoma (GBM) tumors. Current study aims to evaluate how variations of 157Gd concentration and cell oxygen levels can affect the relative biological effectiveness (RBE) of gadolinium neutron capture therapy (GdNCT) technique through a hybrid Monte Carlo (MC) simulation approach. At first, Snyder phantom including a spherical tumor was simulated by Geant4 MC code and relevant energy electron spectra to different 157Gd concentrations including 100, 250, 500, and 1000 ppm were calculated following the neutron irradiation of simulated phantom. Scored energy electron spectra were then imported to Monte Carlo damage simulation (MCDS) code to estimate RBE values (both RBESSB and RBEDSB) at different gadolinium concentrations and oxygen levels from 10 to 100%. The results indicate that variations of 157Gd can affect the energy spectrum of released secondary electrons including Auger electrons. Variation of gadolinium concentration from 100 to 1000 ppm in tumor region can change RBESSB and RBEDSB values by about 0.1% and 0.5%, respectively. Besides, maximum variations of 4.3% and 2% were calculated for RBEDSB and RBESSB when cell oxygen level changed from 10 to 100%. From the results, variations of considered gadolinium and oxygen concentrations during GdNCT can influence RBE values. Nevertheless, due to the not remarkable changes in the intensity of Auger electrons, a slight difference in RBE values would be expected at various 157Gd concentrations, although considerable RBE changes were calculated relevant to the oxygen alternations inside tumor tissue.

The Effects of Particle LET and Fluence on the Complexity and Frequency of Clustered DNA Damage

Motivation

Clustered DNA-lesions are predominantly induced by ionizing radiation, particularly by high-LET particles, and considered as lethal damage. Quantification of this specific type of damage as a function of radiation parameters such as LET, dose rate, dose, and particle type can be informative for the prediction of biological outcome in radiobiological studies. This study investigated the induction and complexity of clustered DNA damage for three different types of particles at an LET range of 0.5-250 keV/μm.

Methods

Nanometric volumes (36.0 nm3) of 15 base-pair DNA with its hydration shell was modeled. Electron, proton, and alpha particles at various energies were simulated to irradiate the nanometric volumes. The number of ionization events, low-energy electron spectra, and chemical yields for the formation of °OH, H°, e aq - , and H2O2 were calculated for each particle as a function of LET. Single- and double-strand breaks (SSB and DSB), base release, and clustered DNA-lesions were computed from the Monte-Carlo based quantification of the reactive species and measured yields of the species responsible for the DNA lesion formation.

Results

The total amount of DNA damage depends on particle type and LET. The number of ionization events underestimates the quantity of DNA damage at LETs higher than 10 keV/μm. Minimum LETs of 9.4 and 11.5 keV/μm are required to induce clustered damage by a single track of proton and alpha particles, respectively. For a given radiation dose, an increase in LET reduces the number of particle tracks, leading to more complex clustered DNA damage, but a smaller number of separated clustered damage sites.

Conclusions

The dependency of the number and the complexity of clustered DNA damage on LET and fluence suggests that the quantification of this damage can be a useful method for the estimation of the biological effectiveness of radiation. These results also suggest that medium-LET particles are more appropriate for the treatment of bulk targets, whereas high-LET particles can be more effective for small targets.

A Dosimetric Comparative Study of Carbon-Ion Radiotherapy Versus X-ray Volumetric Modulated Arc Therapy for Stage III Non-Small-Cell Lung Cancer

BACKGROUND

Compared to photon beam, carbon-ion radiotherapy (CIRT) has both physical and biological advantages.

AIM

To examine whether two-dimensional (2D) CIRT is dosimetrically superior to photon beam volume-modulated arc therapy (VMAT) in protecting the normal tissues for stage III non-small-cell lung cancer (NSCLC).

SUBJECTS AND METHODS

A retrospective study was conducted. Thirteen patients with stage III NSCLC treated in our center with curative CIRT and a sham photon beam VMAT treatment planning with the same normal tissue dose constraints were included for analysis. Target dose distributions and the homogeneity index (HI) within the planning target volumes were compared.

RESULTS

Both CIRT and VMAT plans have good tumor coverage with no significant differences in D98, D95, and D50 of Planning target volume 1 (PTV1) between the two plans. The HIs between the two plans are similar. The HI of PTV2 is superior in the CIRT plan (CIRT vs. VMAT: 0.08 vs. 0.16, P < 0.05). In general, CIRT results in a lower dose of the organ-at-risk (OAR) than the photon plans. The V5, V10, V20, V30, V40, and Dmean of the contralateral lung in the CIRT plan are significantly lower than that of the photon VMAT. For the ipsilateral lung, the V5 of CIRT is significantly lower. The CIRT also had significantly lower spinal cord Dmax, esophageal Dmean and V50, V10 and V30 of bone, and V50 of the trachea and bronchial tree.

CONCLUSIONS

Compared with photon VMAT, 2D-CIRT using the passive beam scanning technique significantly reduces the radiation dose to the OARs in curative radiotherapy of stage III NSCLC, suggesting a better protection of the normal tissues.

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.

Spectral composition of secondary electrons based on the Kiefer-Straaten ion track structure model

The major part of energy deposition of ionizing radiation is caused by secondary electrons, independent of the primary radiation type. However, their spatial concentration and their spectral properties strongly depend on the primary radiation type and finally determine the pattern of molecular damage e.g. to biological targets as the DNA, and thus the final effect of the radiation exposure. To describe the physical and to predict the biological consequences of charged ion irradiation, amorphous track structure approaches have proven to be pragmatic and helpful. There, the local dose deposition in the ion track is equated by considering the emission and slowing down of the secondary electrons from the primary particle track. In the present work we exploit the model of Kiefer and Straaten and derive the spectral composition of secondary electrons as function of the distance to the track center. The spectral composition indicates differences to spectra of low linear energy transfer (LET) photon radiation, which we confirm by a comparison with Monte Carlo studies. We demonstrate that the amorphous track structure approach provides a simple tool for evaluating the spectral electron properties within the track structure. Predictions of the LET of electrons across the track structure as well as the electronic dose build-up effect are derived. Implications for biological effects and corresponding predicting models based on amorphous track structure are discussed.

An inter-comparison between radiobiological characteristics of a commercial low-energy IORT system by Geant4-DNA and MCDS Monte Carlo codes

INTRODUCTION

The need for accurate relative biological effectiveness (RBE) estimation for low energy therapeutic X-rays (corresponding to 50 kV nominal energy of a commercial low-energy IORT system (INTRABEAM)) is a crucial issue due to increased radiobiological effects, respect to high energy photons. Modeling of radiation-induced DNA damage through Monte Carlo (MC) simulation approaches can give useful information. Hence, this study aimed to evaluate and compare RBE of low energy therapeutic X-rays using Geant4-DNA toolkit and Monte Carlo damage simulation (MCDS) code.

MATERIALS AND METHODS

RBE calculations were performed considering the emitted secondary electron spectra through interactions of low energy X-rays inside the medium. In Geant4-DNA, the DNA strand breaks were obtained by employing a B-DNA model in physical stage with 10.79 eV energy-threshold and the probability of hydroxyl radical's chemical reactions of about 0.13%. Furthermore, RBE estimations by MCDS code were performed under fully aerobic conditions.

RESULTS

Acquired results by two considered MC codes showed that the same trend is found for RBEDSB and RBESSB variations. Totally, a reasonable agreement between the calculated RBE values (both RBESSB and RBEDSB) existed between the two considered MC codes. The mean differences of 9.2% and 1.8% were obtained between the estimated RBESSB and RBEDSB values by two codes, respectively.

CONCLUSION

Based on the obtained results, it can be concluded that a tolerable accordance is found between the calculated RBEDSB values through MCDS and Geant4-DNA, a fact which appropriates both codes for RBE evaluations of low energy therapeutic X-rays, especially in the case of RBEDSB where lethal damages are regarded.

Experimental validation in a neutron exposure frame of the MINAS TIRITH for cell damage simulation

In the domains of medicine and space exploration, refining risk assessment models for protecting healthy tissue from ionizing radiation is crucial. Understanding radiation-induced effects requires biological experimentations at the cellular population level and the cellular scale modeling using Monte Carlo track structure codes. We present MINAS TIRITH, a tool using Geant4-DNA Monte Carlo-generated databases to study DNA damage distribution at the cell population scale. It introduces a DNA damage location module and proposes a method to convert double-strand breaks (DSB) into DNA Damage Response foci. We evaluate damage location precision and DSB-foci conversion parameters. MINAS TIRITH's accuracy is validated againstγ-H2AX foci distribution from cell population exposed to monoenergetic neutron beams (2.5 or 15.1 MeV) under different configurations, yielding mixed radiation fields. Strong agreement between simulation and experimental results was found demonstrating MINAS TIRITH's predictive precision in radiation-induced DNA damage topology. Additionally, modeling intercellular damage variability within a population subjected to a specific macroscopic dose identifies subpopulations, enhancing realistic fate models. This approach advances our understanding of radiation-induced effects on cellular systems for risk assessment improvement.

Monte Carlo simulations of cell survival in proton SOBP

Objective. The objective of this study is to develop a multi-scale modeling approach that accurately predicts radiation-induced DNA damage and survival fraction in specific cell lines.Approach. A Monte Carlo based simulation framework was employed to make the predictions. The FLUKA Monte Carlo code was utilized to estimate absorbed doses and fluence energy spectra, which were then used in the Monte Carlo Damage Simulation code to compute DNA damage yields in Chinese hamster V79 cell lines. The outputs were converted into cell survival fractions using a previously published theoretical model. To reduce the uncertainties of the predictions, new values for the parameters of the theoretical model were computed, expanding the database of experimental points considered in the previous estimation. Simulated results were validated against experimental data, confirming the applicability of the framework for proton beams up to 230 MeV. Additionally, the impact of secondary particles on cell survival was estimated.Main results. The simulated survival fraction versus depth in a glycerol phantom is reported for eighteen different configurations. Two proton spread out Bragg peaks at several doses were simulated and compared with experimental data. In all cases, the simulations follow the experimental trends, demonstrating the accuracy of the predictions up to 230 MeV.Significance. This study holds significant importance as it contributes to the advancement of models for predicting biological responses to radiation, ultimately contributing to more effective cancer treatment in proton therapy.

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.

Kinetics of radiation-induced DNA double-strand breaks through coarse-grained simulations

Double-strand breaks (DSBs), i.e., the covalent cut of the DNA backbone over both strands, are a detrimental outcome of cell irradiation, bearing chromosomal aberrations and leading to cell apoptosis. In the early stages of the evolution of a DSB, the disruption of the residual interactions between the DNA moieties drives the fracture of the helical layout; in spite of its biological significance, the details of this process are still largely uncertain. Here, we address the mechanical rupture of DNA by DSBs via coarse-grained molecular dynamics simulations: the setup involves a 3855-bp DNA filament and diverse DSB motifs, i.e., within a range of distances between strand breaks (or DSB distance). By employing a coarse-grained model of DNA, we access the molecular details and characteristic timescales of the rupturing process. A sequence-nonspecific, linear correlation is observed between the DSB distance and the internal energy contribution to the disruption of the residual (Watson-Crick and stacking) contacts between DNA moieties, which is seemingly driven by an abrupt, cooperative process. Moreover, we infer an exponential dependence of the characteristic rupture times on the DSB distances, which we associate to an Arrhenius-like law of thermally-activated processes. This work lays the foundations of a detailed, mechanistic assessment of DSBs in silico as a benchmark to both numerical simulations and data from single-molecule experiments.

Radiation-induced double-strand breaks by internal ex vivo irradiation of lymphocytes: Validation of a Monte Carlo simulation model using GATE and Geant4-DNA

This study describes a method to validate a radiation transport model that quantifies the number of DNA double-strand breaks (DSB) produced in the lymphocyte nucleus by internal ex vivo irradiation of whole blood with the radionuclides 90Y, 99mTc, 123I, 131I, 177Lu, 223Ra, and 225Ac in a test vial using the GATE/Geant4 code at the macroscopic level and the Geant4-DNA code at the microscopic level.

METHODS

The simulation at the macroscopic level reproduces an 8 mL cylindrical water-equivalent medium contained in a vial that mimics the geometry for internal ex vivo blood irradiation. The lymphocytes were simulated as spheres of 3.75 µm radius randomly distributed, with a concentration of 125 spheres/mL. A phase-space actor was attached to each sphere to register all the entering particles. The simulation at the microscopic level for each radionuclide was performed using the Geant4-DNA tool kit, which includes the clustering example centered on a density-based spatial clustering of applications with noise (DBSCAN) algorithm. The irradiation source was constructed by generating a single phase space from the sum of all phase spaces. The lymphocyte nucleus was defined as a water sphere of a 3.1 µm radius. The absorbed dose coefficients for lymphocyte nuclei (dLymph) were calculated and compared with macroscopic whole blood absorbed dose coefficients (dBlood). The DBSCAN algorithm was used to calculate the number of DSBs. Lastly, the number of DSB∙cell-1∙mGy-1 (simulation) was compared with the number of radiation-induced foci per cell and absorbed dose (RIF∙cell-1∙mGy-1) provided by experimental data for gamma and beta emitting radionuclides. For alpha emitters, dLymph and the number of α-tracks∙100 cell-1∙mGy-1 and DBSs∙µm-1 were calculated using experiment-based thresholds for the α-track lengths and DBSs/track values. The results were compared with the results of an ex vivo study with 223Ra.

RESULTS

The dLymph values differed from the dBlood values by -1.0% (90Y), -5.2% (99mTc), -22.3% (123I), 0.35% (131I), 2.4% (177Lu), -5.6% (223Ra) and -6.1% (225Ac). The number of DSB∙cell-1∙mGy-1 for each radionuclide was 0.015 DSB∙cell-1∙mGy-1 (90Y), 0.012 DSB∙cell-1∙mGy-1 (99mTc), 0.014DSB∙cell-1∙mGy-1 (123I), 0.012 DSB∙cell-1∙mGy-1 (131I), and 0.016 DSB∙cell-1∙mGy-1 (177Lu). These values agree very well with experimental data. The number of α-tracks∙100 cells-1∙mGy-1 for 223Ra and 225Ac where 0.144 α-tracks∙100 cells-1∙mGy-1 and 0.151 α-tracks∙100 cells-1∙mGy-1, respectively. These values agree very well with experimental data. Moreover, the linear density of DSBs per micrometer α-track length were 11.13 ± 0.04 DSB/µm and 10.86 ± 0.06 DSB/µm for 223Ra and 225Ac, respectively.

CONCLUSION

This study describes a model to simulate the DNA DSB damage in lymphocyte nuclei validated by experimental data obtained from internal ex vivo blood irradiation with radionuclides frequently used in diagnostic and therapeutic procedures in nuclear medicine.

Ionization detail parameters and cluster dose: a mathematical model for selection of nanodosimetric quantities for use in treatment planning in charged particle radiotherapy

Objective. To propose a mathematical model for applying ionization detail (ID), the detailed spatial distribution of ionization along a particle track, to proton and ion beam radiotherapy treatment planning (RTP).Approach. Our model provides for selection of preferred ID parameters (Ip) for RTP, that associate closest to biological effects. Cluster dose is proposed to bridge the large gap between nanoscopicIpand macroscopic RTP. Selection ofIpis demonstrated using published cell survival measurements for protons through argon, comparing results for nineteenIp:Nk,k= 2, 3, …, 10, the number of ionizations in clusters ofkor more per particle, andFk,k= 1, 2, …, 10, the number of clusters ofkor more per particle. We then describe application of the model to ID-based RTP and propose a path to clinical translation.Main results. The preferredIpwereN4andF5for aerobic cells,N5andF7for hypoxic cells. Significant differences were found in cell survival for beams having the same LET or the preferredNk. Conversely, there was no significant difference forF5for aerobic cells andF7for hypoxic cells, regardless of ion beam atomic number or energy. Further, cells irradiated with the same cluster dose for theseIphad the same cell survival. Based on these preliminary results and other compelling results in nanodosimetry, it is reasonable to assert thatIpexist that are more closely associated with biological effects than current LET-based approaches and microdosimetric RBE-based models used in particle RTP. However, more biological variables such as cell line and cycle phase, as well as ion beam pulse structure and rate still need investigation.Significance. Our model provides a practical means to select preferredIpfrom radiobiological data, and to convertIpto the macroscopic cluster dose for particle RTP.

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.

Radiation-induced liver disease: beyond DNA damage

Radiation-induced liver disease (RILD), also known as radiation hepatitis, is a serious side effect of radiotherapy (RT) for hepatocellular carcinoma. The therapeutic dose of RT can damage normal liver tissue, and the toxicity that accumulates around the irradiated liver tissue is related to numerous physiological and pathological processes. RILD may restrict treatment use or eventually deteriorate into liver fibrosis. However, the research on the mechanism of radiation-induced liver injury has seen little progress compared with that on radiation injury in other tissues, and no targeted clinical pharmacological treatment for RILD exists. The DNA damage response caused by ionizing radiation plays an important role in the pathogenesis and development of RILD. Therefore, in this review, we systematically summarize the molecular and cellular mechanisms involved in RILD. Such an analysis is essential for preventing the occurrence and development of RILD and further exploring the potential treatment of this disease.

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.

An Analytical Method for Quantifying the Yields of DNA Double-Strand Breaks Coupled with Strand Breaks by γ-H2AX Focus Formation Assay Based on Track-Structure Simulation

Complex DNA double-strand break (DSB), which is defined as a DSB coupled with additional strand breaks within 10 bp in this study, induced after ionizing radiation or X-rays, is recognized as fatal damage which can induce cell death with a certain probability. In general, a DSB site inside the nucleus of live cells can be experimentally detected using the γ-H2AX focus formation assay. DSB complexity is believed to be detected by analyzing the focus size using such an assay. However, the relationship between focus size and DSB complexity remains uncertain. In this study, using Monte Carlo (MC) track-structure simulation codes, i.e., an in-house WLTrack code and a Particle and Heavy Ion Transport code System (PHITS), we developed an analytical method for qualifying the DSB complexity induced by photon irradiation from the microscopic image of γ-H2AX foci. First, assuming that events (i.e., ionization and excitation) potentially induce DNA strand breaks, we scored the number of events in a water cube (5.03 × 5.03 × 5.03 nm³) along electron tracks. Second, we obtained the relationship between the number of events and the foci size experimentally measured by the γ-H2AX focus formation assay. Third, using this relationship, we evaluated the degree of DSB complexity induced after photon irradiation for various X-ray spectra using the foci size, and the experimental DSB complexity was compared to the results estimated by the well-verified DNA damage estimation model in the PHITS code. The number of events in a water cube was found to be proportional to foci size, suggesting that the number of events intrinsically related to DSB complexity at the DNA scale. The developed method was applicable to focus data measured for various X-ray spectral situations (i.e., diagnostic kV X-rays and therapeutic MV X-rays). This method would contribute to a precise understanding of the early biological impacts of photon irradiation by means of the γ-H2AX focus formation assay.

Nanoscopic biodosimetry using plasmid DNA in radiotherapy with metallic nanoparticles

Nanoscopic lesions (complex damages), are the most lethal lesions for the cells. As nanoparticles have become increasingly popular in radiation therapy and the importance of analyzing nanoscopic dose enhancement has increased, a reliable tool for nanodosimetry has become indispensable. In this regard, the DNA plasmid is a widely used tool as a nanodosimetry probe in radiobiology and nano-radiosensitization studies. This approach is helpful for unraveling the radiosensitization role of nanoparticles in terms of physical and physicochemical effects and for quantifying radiation-induced biological damage. This review discusses the potential of using plasmid DNA assays for assessing the relative effects of nano-radiosensitizers, which can provide a theoretical basis for the development of nanoscopic biodosimetry and nanoparticle-based radiotherapy.

CONVERSION OF DOSE DISTRIBUTION TO CELL SURVIVAL FRACTION THROUGH DNA DAMAGE: A MONTE CARLO STUDY

Ionizing radiation plays an important role in cancer treatment. Radiation is able to damage the genetic material of cells, blocking their ability to divide and proliferate further. Since radiation affects both healthy and malignant tissues, for all radiation treatments, the design of an accurate treatment plan is fundamental. Usually, weight factors, such as the relative biological effectiveness, are applied to estimate the impact of the kind of radiation and the irradiated medium on the dose deposition. However, these factors can only provide a partial estimation of the real effect on tissues. In this work, a flexible system that is able to predict cell survival fractions according to the planned dose distribution is presented. Dose deposition and subsequent DNA damage were simulated with a multi-scale modeling approach by first applying the FLUKA Monte Carlo (MC) code to estimate the absorbed doses and fluence energy spectra and then using the MC Damage Simulation code to compute the DNA damage yields. Lastly, the results are converted into cell survival fraction using a theoretical model. The comparisons between the simulated survival fractions with experimental data are reported for a proton spread out Bragg peak at several doses. The presented approach helps to elucidate radiobiological responses along the Bragg curve and has the flexibility to be extended to a wide range of situations of clinical interest.

Unraveling Mitochondrial Determinants of Tumor Response to Radiation Therapy

Radiotherapy represents a highly targeted and efficient treatment choice in many cancer types, both with curative and palliative intents. Nevertheless, radioresistance, consisting in the adaptive response of the tumor to radiation-induced damage, represents a major clinical problem. A growing body of the literature suggests that mechanisms related to mitochondrial changes and metabolic remodeling might play a major role in radioresistance development. In this work, the main contributors to the acquired cellular radioresistance and their relation with mitochondrial changes in terms of reactive oxygen species, hypoxia, and epigenetic alterations have been discussed. We focused on recent findings pointing to a major role of mitochondria in response to radiotherapy, along with their implication in the mechanisms underlying radioresistance and radiosensitivity, and briefly summarized some of the recently proposed mitochondria-targeting strategies to overcome the radioresistant phenotype in cancer.

A double-strand-break model for the relative biological effectiveness of electrons based on ionization clustering

BACKGROUND

The effectiveness of ionizing radiation regarding DNA damage induction depends on its spatial energy deposition pattern. For electrons an increased effectiveness is observed at low kinetic energies due to the enhanced density of energy deposition events at electron track ends.

PURPOSE

A model is presented, which enables the calculation of the double-strand-break (DSB) yield and the relative biological effectiveness (RBE) for DSB induction of electrons.

METHODS

The model applies the mean free path between two ionizations and the assumption that two ionizations within a certain threshold distance are necessary to potentially lead to a DSB. Next to an expression for the electron RBE according to its common definition, a local RBE is determined, which describes the electrons' local effectiveness at a defined point on their track.

RESULTS

This local RBE allows a better understanding of microscopic processes resulting from radiation and can be used, for instance, to describe the mean effectiveness of the mixed electron radiation field as a function of the radial distance to the center of an ion track.

CONCLUSIONS

The presented model reflects the experimentally observed increased effectiveness of low-energetic electrons. It will be used in a future work to improve RBE predictions for ions performed with the local effect model.

Inelastic scattering of electrons in water from first principles: cross sections and inelastic mean free path for use in Monte Carlo track-structure simulations of biological damage

Modelling the inelastic scattering of electrons in water is fundamental, given their crucial role in biological damage. In Monte Carlo track-structure (MC-TS) codes used to assess biological damage, the energy loss function (ELF), from which cross sections are extracted, is derived from different semi-empirical optical models. Only recently have first ab initio results for the ELF and cross sections in water become available. For benchmarking purpose, in this work, we present ab initio linear-response time-dependent density functional theory calculations of the ELF of liquid water. We calculated the inelastic scattering cross sections, inelastic mean free paths, and electronic stopping power and compared our results with recent calculations and experimental data showing a good agreement. In addition, we provide an in-depth analysis of the contributions of different molecular orbitals, species and orbital angular momenta to the total ELF. Moreover, we present single-differential cross sections computed for each molecular orbital channel, which should prove useful for MC-TS simulations.

Inelastic scattering of electrons in water from first principles: cross sections and inelastic mean free path for use in Monte Carlo track-structure simulations of biological damage

Modelling the inelastic scattering of electrons in water is fundamental, given their crucial role in biological damage. In Monte Carlo track-structure (MC-TS) codes used to assess biological damage, the energy loss function (ELF), from which cross sections are extracted, is derived from different semi-empirical optical models. Only recently have first ab initio results for the ELF and cross sections in water become available. For benchmarking purpose, in this work, we present ab initio linear-response time-dependent density functional theory calculations of the ELF of liquid water. We calculated the inelastic scattering cross sections, inelastic mean free paths, and electronic stopping power and compared our results with recent calculations and experimental data showing a good agreement. In addition, we provide an in-depth analysis of the contributions of different molecular orbitals, species and orbital angular momenta to the total ELF. Moreover, we present single-differential cross sections computed for each molecular orbital channel, which should prove useful for MC-TS simulations.

Radiation exposure of microorganisms living in radioactive mineral springs

The TIRAMISU collaboration gathers expertise from biologists, physicists, radiochemists and geologists within the Zone-Atelier Territoires Uranifères (ZATU) in France to analyze the radiation exposure of microorganisms living in naturally radioactive mineral springs. These springs are small waterbodies that are extremely stable over geological time scales and display different physicochemical and radiological parameters compared to their surroundings. Water and sediment samples collected in 27 mineral springs of the volcanic Auvergne region (Massif Central, France) have been studied for their microbial biodiversity and their radionuclide content. Among the microorganisms present, microalgae (diatoms), widely used as environmental indicators of water quality, have shown to display an exceptional abundance of teratogenic forms in the most radioactive springs studied (radon activity up to 3700 Bq/L). The current work presents a first assessment of the dose received by the diatoms inhabiting these ecosystems. According to ERICA tool, microorganisms living in most of the sampled mineral springs were exposed to dose rates above 10 μGy/h due to the large concentration of radium in the sediments (up to 50 Bq/g). Radiological analyses of water and sediments were used as inputs to Monte Carlo simulations at micro-(GATE) and nano- (Geant4-DNA) scale in order to assess the direct and indirect damages on the diatom DNA.

Key biological mechanisms involved in high-LET radiation therapies with a focus on DNA damage and repair

DNA damage and repair studies are at the core of the radiation biology field and represent also the fundamental principles informing radiation therapy (RT). DNA damage levels are a function of radiation dose, whereas the type of damage and biological effects such as DNA damage complexity, depend on radiation quality that is linear energy transfer (LET). Both levels and types of DNA damage determine cell fate, which can include necrosis, apoptosis, senescence or autophagy. Herein, we present an overview of current RT modalities in the light of DNA damage and repair with emphasis on medium to high-LET radiation. Proton radiation is discussed along with its new adaptation of FLASH RT. RT based on α-particles includes brachytherapy and nuclear-RT, that is proton-boron capture therapy (PBCT) and boron-neutron capture therapy (BNCT). We also discuss carbon ion therapy along with combinatorial immune-based therapies and high-LET RT. For each RT modality, we summarise relevant DNA damage studies. Finally, we provide an update of the role of DNA repair in high-LET RT and we explore the biological responses triggered by differential LET and dose.

The Effect of Hypoxia on Relative Biological Effectiveness and Oxygen Enhancement Ratio for Cells Irradiated with Grenz Rays

Grenz-ray therapy (GT) is commonly used for dermatological radiotherapy and has a higher linear energy transfer, relative biological effectiveness (RBE) and oxygen enhancement ratio (OER). GT is a treatment option for lentigo maligna and lentigo maligna melanoma. This study aims to calculate the RBE for DNA double-strand break (DSB) induction and cell survival under hypoxic conditions for GT. The yield of DSBs induced by GT is calculated at the aerobic and hypoxic conditions, using a Monte Carlo damage simulation (MCDS) software. The RBE value for cell survival is calculated using the repair–misrepair–fixation (RMF) model. The RBE values for cell survival for cells irradiated by 15 kV, 10 kV and 10 kVp and titanium K-shell X-rays (4.55 kV) relative to 60Co γ-rays are 1.0–1.6 at the aerobic conditions and moderate hypoxia (2% O2), respectively, but increase to 1.2, 1.4 and 1.9 and 2.1 in conditions of severe hypoxia (0.1% O2). The OER values for DSB induction relative to 60Co γ-rays are about constant and ~2.4 for GT, but the OER for cell survival is 2.8–2.0 as photon energy decreases from 15 kV to 4.55 kV. The results indicate that GT results in more DSB induction and allows effective tumor control for superficial and hypoxic tumors.

Evaluating Iodine-125 DNA Damage Benchmarks of Monte Carlo DNA Damage Models

Simple Summary

Simulation of initial radiation-induced DNA damage remains a major area of research, with numerous Monte Carlo models having been developed to model radiation effects on the cellular scale. While many models have been reasonably fit to a range of biological endpoints, there remains a lack of robust benchmarking data. Here, we investigate the application of a dataset on strand breaking in a single DNA strand through incorporation of radioactive Iodine-125 to distinguish between different Monte Carlo nanoscale physics models. We find that, while all models are able to effectively fit this data, they do so using significantly different best-fitting parameters and make substantially different predictions for other endpoints. These observations suggest that most nanoscale models broadly agree on the distribution of energy and can be made to fit to single datasets, but robust, multi-endpoint analysis is required to fully optimize and validate these approaches.

Abstract

A wide range of Monte Carlo models have been applied to predict yields of DNA damage based on nanoscale track structure calculations. While often similar on the macroscopic scale, these models frequently employ different assumptions which lead to significant differences in nanoscale dose deposition. However, the impact of these differences on key biological readouts remains unclear. A major challenge in this area is the lack of robust datasets which can be used to benchmark models, due to a lack of resolution at the base pair level required to deeply test nanoscale dose deposition. Studies investigating the distribution of strand breakage in short DNA strands following the decay of incorporated ¹²⁵I offer one of the few benchmarks for model predictions on this scale. In this work, we have used TOPAS-nBio to evaluate the performance of three Geant4-DNA physics models at predicting the distribution and yield of strand breaks in this irradiation scenario. For each model, energy and OH radical distributions were simulated and used to generate predictions of strand breakage, varying energy thresholds for strand breakage and OH interaction rates to fit to the experimental data. All three models could fit well to the observed data, although the best-fitting strand break energy thresholds ranged from 29.5 to 32.5 eV, significantly higher than previous studies. However, despite well describing the resulting DNA fragment distribution, these fit models differed significantly with other endpoints, such as the total yield of breaks, which varied by 70%. Limitations in the underlying data due to inherent normalisation mean it is not possible to distinguish clearly between the models in terms of total yield. This suggests that, while these physics models can effectively fit some biological data, they may not always generalise in the same way to other endpoints, requiring caution in their extrapolation to new systems and the use of multiple different data sources for robust model benchmarking.

Lethal DNA damage caused by ion-induced shock waves in cells

The elucidation of fundamental mechanisms underlying ion-induced radiation damage of biological systems is crucial for advancing radiotherapy with ion beams and for radiation protection in space. The study of ion-induced biodamage using the phenomenon-based multiscale approach (MSA) to the physics of radiation damage with ions has led to the prediction of nanoscale shock waves created by ions in a biological medium at the high linear energy transfer (LET). The high-LET regime corresponds to the keV and higher-energy losses by ions per nanometer, which is typical for ions heavier than carbon at the Bragg peak region in biological media. This paper reveals that the thermomechanical stress of the DNA molecule caused by the ion-induced shock wave becomes the dominant mechanism of complex DNA damage at the high-LET ion irradiation. Damage of the DNA molecule in water caused by a projectile-ion-induced shock wave is studied by means of reactive molecular dynamics simulations. Five projectile ions (carbon, oxygen, silicon, argon, and iron) at the Bragg peak energies are considered. For the chosen segment of the DNA molecule and the collision geometry, the number of DNA strand breaks is evaluated for each projectile ion as a function of the bond dissociation energy and the distance from the ion's path to the DNA strands. Simulations reveal that argon and especially iron ions induce the breakage of multiple bonds in a DNA double convolution containing 20 DNA base pairs. The DNA damage produced in segments of such size leads to complex irreparable lesions in a cell. This makes the shock-wave-induced thermomechanical stress the dominant mechanism of complex DNA damage at the high-LET ion irradiation. A detailed theory for evaluating the DNA damage caused by ions at high-LET is formulated and integrated into the MSA formalism. The theoretical analysis reveals that a single ion hitting a cell nucleus at high-LET is sufficient to produce highly complex, lethal damages to a cell by the shock-wave-induced thermomechanical stress. Accounting for the shock-wave-induced thermomechanical mechanism of DNA damage provides an explanation for the "overkill" effect observed experimentally in the dependence of cell survival probabilities on the radiation dose delivered with iron ions. This important observation provides strong experimental evidence of the ion-induced shock-wave effect and the related mechanism of radiation damage in cells.

Review of the Geant4-DNA Simulation Toolkit for Radiobiological Applications at the Cellular and DNA Level

Simple Summary

A brief description of the methodologies to simulate ionizing radiation transport in biologically relevant matter is presented. Emphasis is given to the physical, chemical, and biological models of Geant4-DNA that enable mechanistic radiobiological modeling at the cellular and DNA level, important to improve the efficacy of existing and novel radiotherapeutic modalities for the treatment of cancer.

Abstract

The Geant4-DNA low energy extension of the Geant4 Monte Carlo (MC) toolkit is a continuously evolving MC simulation code permitting mechanistic studies of cellular radiobiological effects. Geant4-DNA considers the physical, chemical, and biological stages of the action of ionizing radiation (in the form of x- and γ-ray photons, electrons and β^±-rays, hadrons, α-particles, and a set of heavier ions) in living cells towards a variety of applications ranging from predicting radiotherapy outcomes to radiation protection both on earth and in space. In this work, we provide a brief, yet concise, overview of the progress that has been achieved so far concerning the different physical, physicochemical, chemical, and biological models implemented into Geant4-DNA, highlighting the latest developments. Specifically, the “dnadamage1” and “molecularDNA” applications which enable, for the first time within an open-source platform, quantitative predictions of early DNA damage in terms of single-strand-breaks (SSBs), double-strand-breaks (DSBs), and more complex clustered lesions for different DNA structures ranging from the nucleotide level to the entire genome. These developments are critically presented and discussed along with key benchmarking results. The Geant4-DNA toolkit, through its different set of models and functionalities, offers unique capabilities for elucidating the problem of radiation quality or the relative biological effectiveness (RBE) of different ionizing radiations which underlines nearly the whole spectrum of radiotherapeutic modalities, from external high-energy hadron beams to internal low-energy gamma and beta emitters that are used in brachytherapy sources and radiopharmaceuticals, respectively.

Applications of nanodosimetry in particle therapy planning and beyond

This topical review summarizes underlying concepts of nanodosimetry. It describes the development and current status of nanodosimetric detector technology. It also gives an overview of Monte Carlo track structure simulations that can provide nanodosimetric parameters for treatment planning of proton and ion therapy. Classical and modern radiobiological assays that can be used to demonstrate the relationship between the frequency and complexity of DNA lesion clusters and nanodosimetric parameters are reviewed. At the end of the review, existing approaches of treatment planning based on relative biological effectiveness (RBE) models or dose-averaged linear energy transfer are contrasted with an RBE-independent approach based on nandosimetric parameters. Beyond treatment planning, nanodosimetry is also expected to have applications and give new insights into radiation protection dosimetry.

Performance Evaluation for Repair of HSGc-C5 Carcinoma Cell Using Geant4-DNA

Track-structure Monte Carlo simulations are useful tools to evaluate initial DNA damage induced by irradiation. In the previous study, we have developed a Gean4-DNA-based application to estimate the cell surviving fraction of V79 cells after irradiation, bridging the gap between the initial DNA damage and the DNA rejoining kinetics by means of the two-lesion kinetics (TLK) model. However, since the DNA repair performance depends on cell line, the same model parameters cannot be used for different cell lines. Thus, we extended the Geant4-DNA application with a TLK model for the evaluation of DNA damage repair performance in HSGc-C5 carcinoma cells which are typically used for evaluating proton/carbon radiation treatment effects. For this evaluation, we also performed experimental measurements for cell surviving fractions and DNA rejoining kinetics of the HSGc-C5 cells irradiated by 70 MeV protons at the cyclotron facility at the National Institutes for Quantum and Radiological Science and Technology (QST). Concerning fast- and slow-DNA rejoining, the TLK model parameters were adequately optimized with the simulated initial DNA damage. The optimized DNA rejoining speeds were reasonably agreed with the experimental DNA rejoining speeds. Using the optimized TLK model, the Geant4-DNA simulation is now able to predict cell survival and DNA-rejoining kinetics for HSGc-C5 cells.

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.

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.

Incorporating oxygenation levels in analytical DNA-damage models-quantifying the oxygen fixation mechanism

Purpose.To develop a framework to include oxygenation effects in radiation therapy treatment planning which is valid for all modalities, energy spectra and oxygen levels. The framework is based on predicting the difference in DNA-damage resulting from ionising radiation at variable oxygenation levels.Methods.Oxygen fixation is treated as a statistical process in a simplified model of complex and simple damage. We show that a linear transformation of the microscopic oxygen fixation process allows to extend this to all energies and modalities, resulting in a relatively simple rational polynomial expression. The model is expanded such that it can be applied for polyenergetic beams. The methodology is validated using Microdosimetric Monte Carlo Damage Simulation code (MCDS). This serves as a bootstrap to determine relevant parameters in the analytical expression, as MCDS is shown to be extensively verified with published empirical data. Double-strand break induction as calculated by this methodology is compared to published proton experiments. Finally, an example is worked out where the oxygen enhancement ratio (OER) is calculated at different positions in a clinically relevant spread out Bragg peak (SOBP) dose deposition in water. This dose deposition is obtained using a general Monte Carlo code (FLUKA) to determine dose deposition and locate fluence spectra.Results.For all modalities (electrons, protons), the damage categorised as complex could be parameterised to within 0.3% of the value calculated using microdosimetric Monte Carlo. The proton beam implementation showed some variation in OERs which differed slightly depending on where the assessment was made; before the SOBP, mid-SOBP or at the distal edge. Environment oxygenation was seen to be the more important variable.Conclusions.An analytic expression calculating complex damage depending on modality, energy spectrum, and oxygenation levels was shown to be effective and can be readily incorporated in treatment planning software, to take into account the impact of variable oxygenation, forming a first step to an optimised treatment based on biological factors.

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.

Impact of Hypoxia on Relative Biological Effectiveness and Oxygen Enhancement Ratio for a 62-MeV Therapeutic Proton Beam

This study uses the yields of double-strand breaks (DSBs) to determine the relative biological effectiveness (RBE) of proton beams, using cell survival as a biological endpoint. DSB induction is determined when cells locate at different depths (6 positions) along the track of 62 MeV proton beams. The DNA damage yields are estimated using Monte Carlo Damage Simulation (MCDS) software. The repair outcomes are estimated using Monte Carlo excision repair (MCER) simulations. The RBE for cell survival at different oxygen concentrations is calculated using the repair-misrepair-fixation (RMF) model. Using 60Co γ-rays (linear energy transfer (LET) = 2.4 keV/μm) as the reference radiation, the RBE for DSB induction and enzymatic DSB under aerobic condition (21% O2) are in the range 1.0-1.5 and 1.0-1.6 along the track depth, respectively. In accord with RBE obtained from experimental data, RMF model-derived RBE values for cell survival are in the range of 1.0-3.0. The oxygen enhancement ratio (OER) for cell survival (10%) decreases from 3.0 to 2.5 as LET increases from 1.1 to 22.6 keV/μm. The RBE values for severe hypoxia (0.1% O2) are in the range of 1.1-4.4 as LET increases, indicating greater contributions of direct effects for protons. Compared with photon therapy, the overall effect of 62 MeV proton beams results in greater cell death and is further intensified under hypoxic conditions.

Effect of spatial distribution of boron and oxygen concentration on DNA damage induced from boron neutron capture therapy using Monte Carlo simulations

PURPOSE

This paper aims to investigate how the spatial distribution of boron in cells and oxygen concentration affect the DNA damage induced by charged particles in boron neutron capture therapy (BNCT) by Monte Carlo simulations, and further to evaluate the relative biological effectiveness (RBE) of DNA double-strand breaks (DSBs) induction.

MATERIALS AND METHODS

The kinetic energy spectra of α, ⁷Li particles in BNCT arriving at the nucleus surface were obtained from GEANT4 (Geant4 10.05.p01). The DNA damage caused by BNCT was then evaluated using MCDS (MCDS 3.10A).

RESULTS

When α or ⁷Li particles were distributed in the cytomembrane or cytoplasm, the difference in DNA damage of the same types was less than 0.5%. Taking the 137Cs photons as the reference radiation, when the oxygen concentration varied from 0% to 50%, the RBE of 0.54MeV protons and recoil protons varied from 5 to 2, whereas it decreased from 10 to 3 for α or ⁷Li particles.

CONCLUSION

The RBE of DSB induction all charged particles in BNCT decreased with the increase of oxygen concentration. This work indicated that the RBE of different radiation particles of BNCT might be affected by many factors, which should be paid attention to in theoretical research or clinical application.

IDDRRA: A novel platform, based on Geant4-DNA to quantify DNA damage by ionizing radiation

PURPOSE

This study proposes a novel computational platform that we refer to as IDDRRA (DNA Damage Response to Ionizing RAdiation), which uses Monte Carlo (MC) simulations to score radiation induced DNA damage. MC simulations provide results of high accuracy on the interaction of radiation with matter while scoring the energy deposition based on state-of-the-art physics and chemistry models and probabilistic methods.

METHODS

The IDDRRA software is based on the Geant4-DNA toolkit together with new tools that were developed for the purpose of this study, including a new algorithm that was developed in Python for the design of the DNA molecules. New classes were developed in C++ to integrate the GUI and produce the simulation's output in text format. An algorithm was also developed to analyze the simulation's output in terms of energy deposition, Single Strand Breaks (SSB), Double Strand Breaks (DSB) and Cluster Damage Sites (CDS). Finally, a new tool was developed to implement probabilistic SSB and DSB repair models using MC techniques.

RESULTS

This article provides the first benchmarks that the user of the IDDRRA tool can use to validate the functionality of the software as well as to provide a starting point to produce different types of DNA simulations. These benchmarks incorporate different kind of particles (e-, e+, protons, electron spectrum) and DNA molecules.

CONCLUSION

We have developed the IDDRRA tool and demonstrated its use to study various aspects of the modeling and simulation of a DNA irradiation experiment. The tool is expandable and can be expanded by other users with new benchmarks and applications based on the user's needs and experience. New functionality will be added over time, including the quantification of the indirect damage.

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.

Clinical Progress in Proton Radiotherapy: Biological Unknowns

Simple Summary

Proton radiation therapy is a more recent type of radiotherapy that uses proton beams instead of classical photon or X-rays beams. The clinical benefit of proton therapy is that it allows to treat tumors more precisely. As a result, proton radiotherapy induces less toxicity to healthy tissue near the tumor site. Despite the experience in the clinical use of protons, the response of cells to proton radiation, the radiobiology, is less understood. In this review, we describe the current knowledge about proton radiobiology.

Abstract

Clinical use of proton radiation has massively increased over the past years. The main reason for this is the beneficial depth-dose distribution of protons that allows to reduce toxicity to normal tissues surrounding the tumor. Despite the experience in the clinical use of protons, the radiobiology after proton irradiation compared to photon irradiation remains to be completely elucidated. Proton radiation may lead to differential damages and activation of biological processes. Here, we will review the current knowledge of proton radiobiology in terms of induction of reactive oxygen species, hypoxia, DNA damage response, as well as cell death after proton irradiation and radioresistance.

Generalized stochastic microdosimetric model: The main formulation

The present work introduces a rigorous stochastic model, called the generalized stochastic microdosimetric model (GSM^{2}), to describe biological damage induced by ionizing radiation. Starting from the microdosimetric spectra of energy deposition in tissue, we derive a master equation describing the time evolution of the probability density function of lethal and potentially lethal DNA damage induced by a given radiation to a cell nucleus. The resulting probability distribution is not required to satisfy any a priori conditions. After the initial assumption of instantaneous irradiation, we generalized the master equation to consider damage induced by a continuous dose delivery. In addition, spatial features and damage movement inside the nucleus have been taken into account. In doing so, we provide a general mathematical setting to fully describe the spatiotemporal damage formation and evolution in a cell nucleus. Finally, we provide numerical solutions of the master equation exploiting Monte Carlo simulations to validate the accuracy of GSM^{2}. Development of GSM^{2} can lead to improved modeling of radiation damage to both tumor and normal tissues, and thereby impact treatment regimens for better tumor control and reduced normal tissue toxicities.

Role of DNA Damage and Repair in Detrimental Effects of Ionizing Radiation

Ionizing radiation (IR) is considered a traditional mutagen and genotoxic agent. Exposure to IR affects in all cases biological systems and living organisms from plants to humans mostly in a pernicious way. At low (<0.1 Gy) and low-to-medium doses (0.1–1 Gy), one can find in the literature a variety of findings indicating sometimes a positive-like anti-inflammatory effect or detrimental-like toxicity. In this Special Issue and in general in the current research, we would like to acquire works and more knowledge on the role(s) of DNA damage and its repair induced by ionizing radiations as instigators of the full range of biological responses to radiation. Emphasis should be given to advances offering mechanistic insights into the ability of radiations with different qualities to severely impact cells or tissues. High-quality research or review studies on different species projected to humans are welcome. Technical advances reporting on the methodologies to accurately measure DNA or other types of biological damage must be highly considered for the near future in our research community, as well. Last but not least, clinical trials or protocols with improvements to radiation therapy and radiation protection are also included in our vision for the advancement of research regarding biological effects of IR.

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.

Interphase Cytogenetic Analysis of G0 Lymphocytes Exposed to α-Particles, C-Ions, and Protons Reveals their Enhanced Effectiveness for Localized Chromosome Shattering-A Critical Risk for Chromothripsis

For precision cancer radiotherapy, high linear energy transfer (LET) particle irradiation offers a substantial advantage over photon-based irradiation. In contrast to the sparse deposition of low-density energy by χ- or γ-rays, particle irradiation causes focal DNA damage through high-density energy deposition along the particle tracks. This is characterized by the formation of multiple damage sites, comprising localized clustered patterns of DNA single- and double-strand breaks as well as base damage. These clustered DNA lesions are key determinants of the enhanced relative biological effectiveness (RBE) of energetic nuclei. However, the search for a fingerprint of particle exposure remains open, while the mechanisms underlying the induction of chromothripsis-like chromosomal rearrangements by high-LET radiation (resembling chromothripsis in tumors) await to be elucidated. In this work, we investigate the transformation of clustered DNA lesions into chromosome fragmentation, as indicated by the induction and post-irradiation repair of chromosomal damage under the dynamics of premature chromosome condensation in G0 human lymphocytes. Specifically, this study provides, for the first time, experimental evidence that particle irradiation induces localized shattering of targeted chromosome domains. Yields of chromosome fragments and shattered domains are compared with those generated by γ-rays; and the RBE values obtained are up to 28.6 for α-particles (92 keV/μm), 10.5 for C-ions (295 keV/μm), and 4.9 for protons (28.5 keV/μm). Furthermore, we test the hypothesis that particle radiation-induced persistent clustered DNA lesions and chromatin decompaction at damage sites evolve into localized chromosome shattering by subsequent chromatin condensation in a single catastrophic event—posing a critical risk for random rejoining, chromothripsis, and carcinogenesis. Consistent with this hypothesis, our results highlight the potential use of shattered chromosome domains as a fingerprint of high-LET exposure, while conforming to the new model we propose for the mechanistic origin of chromothripsis-like rearrangements.