Prediction of DNA rejoining kinetics and cell survival after proton irradiation for V79 cells using Geant4-DNA

Review of the geometrical developments in GEANT4-DNA: From a biological perspective

GEANT4-DNA is an expansion of the widely utilised GEANT4 Monte Carlo toolkit. This extension focuses on modelling the physical, chemical, and biological stages of ionising radiation for radiobiological applications at cellular and DNA level interactions. To date, review papers on GEANT4-DNA focus solely on evaluating a selection of the latest developments with a greater focus on mechanistic developments rather than progress in biologically specific geometries. In this work, an overview of biological analysis and biological geometries that have been developed are discussed, highlighting the latest developments and future possible development avenues for GEANT4-DNA for this application. An overview of the biological organisation levels, namely DNA, cellular, and population levels, and how GEANT4-DNA models the physical, chemical, and biological processes are also described. This review emphasises the need for persistent development of specific biological geometry accompanied by personalised DNA damage analysis parameters dependent on the biological processes considered within a specific model. It also provides an in-depth understanding of the advances at all the biological organisation levels (DNA, cellular, and population) and the use of co-operative platforms developed to model alongside GEANT4 to provide further detailed geometries and or biological damage analysis. The developments presented have been analytically discussed along with their key findings and prospects for GEANT4-DNA. Finally, a perspective on future necessary developments is portrayed since many of the advancements in the biological analysis and biological geometries discussed have not been exploited to their full potential. The development of GEANT4-DNA, using the advances discussed in this review, provides a favourable method for the evaluation of biological damage comparable to radiobiological studies.

Evaluating the biological impact of shelters on astronaut health during different solar particle events: a Geant4-DNA simulation study

Mechanistic Monte Carlo simulations have proven invaluable in tackling complex challenges in radiobiology, for example for protecting astronauts from solar particle events (SPEs) during deep space missions which remains an underexplored area. In this study, the Geant4-DNA Monte Carlo code was used to assess the DNA damage caused by SPEs and evaluate the protective effectiveness of a multilayer shelter. By examining the February 1956 and October 1989 SPEs-two extreme cases-the results showed that the proposed shelter reduced DNA damage by up to 57.9% for the October 1989 SPE and 36.7% for the February 1956 SPE. Cell repair and survival modeling further revealed enhanced cell survival with the shelter, reducing lethal DNA damage by up to 64.3% and 88.2% for February 1956 and October 1989 SPEs, respectively. The results presented here highlight the crucial importance of developing effective radiation shielding to protect astronauts during solar storms and emphasizes the need to improve predictions of solar particle events to optimize shelter design.

Targeted alpha therapies using 211At: A Geant4 simulation of dose and DNA damage

INTRODUCTION

Targeted alpha therapies show great potential for cancer treatment due to their high linear energy transfer (LET) and low range. 211At is currently employed in clinical trials. Targeted alpha therapies (TAT) are effective as an adjuvant treatment for cancer or to treat micrometastases and diffuse cancers. A deeper understanding of the induced initial damage is crucial to enhance treatment planning.

METHODS

This study shows Geant4(-DNA)-based simulations to calculate absorbed dose profiles and DNA damaging potential in intravenously administered TAT with 211At. It assumes radionuclide decay on the blood vessel wall, and calculates the DNA damage in the surrounding tissue.

RESULTS

The calculated dosimetric quantities show that the effect of such treatment is mainly due to the emitted alpha particles, and is localised in a region of up to 80μm from the blood vessel. The RBE of the treatment is in the range 2.5-4, and is calculated as a function of the number of double-strand breaks.

CONCLUSIONS

Targeted therapies with 211At are effective within the range of the emitted alpha particles. With its capacity to induce complex DNA damage in such a short range, it is very promising for localised treatment of small tumour cells or micrometastases.

Comparison of in vitro cell survival predictions using Monte Carlo methods for proton irradiation

PURPOSE

It is possible to combine theoretical models with Monte Carlo simulations to investigate the relationship between radiation-induced initial DNA damage and cell survival. Several combinations of models have been proposed in recent years, sparking interest in comparing their predictions in view of future clinical applications.

METHODS

Two in silico methods for calculating cell survival fractions were optimized for proton irradiation of the Chinese hamster V79 cell line, for LET values ranging from 3.40 and 100 keV/μm. These methods, based on different Monte Carlo codes and theoretical models, were benchmarked against published V79 cell survival data to identify the sources of discrepancies.

RESULTS

The predictive capacities of the methods were evaluated for several proton LET values using an external dataset. After recalibrating model parameters, multiple methods were assessed. This approach helped identify sources of variation, the main one being the simulated number of DSBs, which differed by a factor up to 3 between the two Monte Carlo codes. In this process a new method was defined, that, in all but one case, allows for a reduction in prediction error of up to 56%. Additionally, a freely available GUI for computing cell survival was refined, to facilitate further comparison of diverse theoretical models.

CONCLUSION

The systematic comparison of two predictive chains, characterized by distinct applicability ranges and features, was conducted. Optimization and analysis of various combinations were undertaken to elucidate differences. Addressing and minimizing such discrepancies will be crucial for further enhancing the reliability of predictive models of cell survival, aiming for biologically informed treatment planning.

Simulation of cell cycle effects on DNA strand break induction due to α-particles

PURPOSE

Understanding cell cycle variations in radiosensitivity is important for α-particle therapies. Differences are due to both repair response mechanisms and the quantity of initial radiation-induced DNA strand breaks. Genome compaction within the nucleus has been shown to impact the yield of strand breaks. Compaction changes during the cell cycle are therefore likely to contribute to radiosensitivity differences. Simulation allows the strand break yield to be calculated independently of repair mechanisms which would be challenging experimentally.

METHODS

Using Geant4 the impact of genome compaction changes on strand break induction due to α-particles was simulated. Genome compaction is considered to be described by three metrics: global base pair density, chromatin fibre packing fraction and chromosome condensation. Nuclei in the G1, S, G2 and M phases from two cancer cell lines and one normal cell line are simulated. Repair mechanisms are not considered to study only the impact of genome compaction changes.

RESULTS

The three compaction metrics have differing effects on the strand break yield. For all cell lines the strand break yield is greatest in G2 cells and least in G1 cells. More strand breaks are induced in the two cancer cell lines than in the normal cell line.

CONCLUSIONS

Compaction of the genome affects the initial yield of strand breaks. Some radiosensitivity differences between cell lines can be attributed to genome compaction changes between the phases of the cell cycle. This study provides a basis for further analysis of how repair deficiencies impact radiation-induced lethality in normal and malignant cells.

TOPAS-Tissue: A Framework for the Simulation of the Biological Response to Ionizing Radiation at the Multi-Cellular Level

This work aims to develop and validate a framework for the multiscale simulation of the biological response to ionizing radiation in a population of cells forming a tissue. We present TOPAS-Tissue, a framework to allow coupling two Monte Carlo (MC) codes: TOPAS with the TOPAS-nBio extension, capable of handling the track-structure simulation and subsequent chemistry, and CompuCell3D, an agent-based model simulator for biological and environmental behavior of a population of cells. We verified the implementation by simulating the experimental conditions for a clonogenic survival assay of a 2-D PC-3 cell culture model (10 cells in 10,000 µm2) irradiated by MV X-rays at several absorbed dose values from 0-8 Gy. The simulation considered cell growth and division, irradiation, DSB induction, DNA repair, and cellular response. The survival was obtained by counting the number of colonies, defined as a surviving primary (or seeded) cell with progeny, at 2.7 simulated days after irradiation. DNA repair was simulated with an MC implementation of the two-lesion kinetic model and the cell response with a p53 protein-pulse model. The simulated survival curve followed the theoretical linear-quadratic response with dose. The fitted coefficients α = 0.280 ± 0.025/Gy and β = 0.042 ± 0.006/Gy2 agreed with published experimental data within two standard deviations. TOPAS-Tissue extends previous works by simulating in an end-to-end way the effects of radiation in a cell population, from irradiation and DNA damage leading to the cell fate. In conclusion, TOPAS-Tissue offers an extensible all-in-one simulation framework that successfully couples Compucell3D and TOPAS for multiscale simulation of the biological response to radiation.

A mechanistic simulation of induced DNA damage in a bacterial cell by X- and gamma rays: a parameter study

Mechanistic Monte Carlo simulations calculating DNA damage caused by ionizing radiation are highly dependent on the simulation parameters. In the present study, using the Geant4-DNA toolkit, the impact of different parameters on DNA damage induced in a bacterial cell by X- and gamma-ray irradiation was investigated. Three geometry configurations, including the simple (without DNA details), the random (a random multiplication of identical DNA segments), and the fractal (a regular replication of DNA segments using fractal Hilbert curves), were simulated. Also, three physics constructors implemented in Geant4-DNA, i.e., G4EmDNAPhysics_option2, G4EmDNAPhysics_option4, and G4EmDNAPhysics_option6, with two energy thresholds of 17.5 eV and 5-37.5 eV were compared for direct DNA damage calculations. Finally, a previously developed mathematical model of cell repair called MEDRAS (Mechanistic DNA Repair and Survival) was employed to compare the impact of physics constructors on the cell survival curve. The simple geometry leads to undesirable results compared to the random and fractal ones, highlighting the importance of simulating complex DNA structures in mechanistic simulation studies. Under the same conditions, the DNA damage calculated in the fractal geometry was more consistent with the experimental data. All physics constructors can be used alternatively with the fractal geometry, provided that an energy threshold of 17.5 eV is considered for recording direct DNA damage. All physics constructors represent a similar behavior in generating cell survival curves, although the slopes of the curves are different. Since the inverse of the slope of a bacterial cell survival curve (i.e., the D10-value) is highly sensitive to the simulation parameters, it is not logical to determine an optimal set of parameters for calculating the D10-value by Monte Carlo simulation.

Dose and DNA damage modelling of diffusing alpha-emitters radiation therapy using Geant4

PURPOSE

Diffusing alpha-emitters radiation therapy (DaRT) is a brachytherapy technique using α-particles to treat solid tumours. The high linear energy transfer (LET) and short range of α-particles make them good candidates for the targeted treatment of cancer. Treatment planning of DaRT requires a good understanding of the dose from α-particles and the other particles released in the 224Ra decay chain.

METHODS

The Geant4 Monte Carlo toolkit has been used to simulate a DaRT seed to better understand the dose contribution from all particles and simulate the DNA damage due to this treatment.

RESULTS

Close to the seed α-particles deliver the majority of dose, however at radial distances greater than 4 mm, the contribution of β-particles is greater. The RBE has been estimated as a function of number of double strand breaks (DSBs) and complex DSBs. A maximum seed spacing of 5.5 mm and 6.5 mm was found to deliver at least 20 Gy RBE weighted dose between the seeds for RBEDSB and RBEcDSB respectively.

CONCLUSIONS

The DNA damage changes with radial distance from the seed and has been found to become less complex with distance, which is potentially easier for the cell to repair. Close to the seed α-particles contribute the majority of dose, however the contribution from other particles cannot be neglected and may influence the choice of seed spacing.

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.

Simulation of DNA damage using Geant4-DNA: an overview of the "molecularDNA" example application

Purpose

The scientific community shows great interest in the study of DNA damage induction, DNA damage repair, and the biological effects on cells and cellular systems after exposure to ionizing radiation. Several in silico methods have been proposed so far to study these mechanisms using Monte Carlo simulations. This study outlines a Geant4-DNA example application, named "molecularDNA", publicly released in the 11.1 version of Geant4 (December 2022).

Methods

It was developed for novice Geant4 users and requires only a basic understanding of scripting languages to get started. The example includes two different DNA-scale geometries of biological targets, namely "cylinders" and "human cell". This public version is based on a previous prototype and includes new features, such as: the adoption of a new approach for the modeling of the chemical stage, the use of the standard DNA damage format to describe radiation-induced DNA damage, and upgraded computational tools to estimate DNA damage response.

Results

Simulation data in terms of single-strand break and double-strand break yields were produced using each of the available geometries. The results were compared with the literature, to validate the example, producing less than 5% difference in all cases. Conclusion: "molecularDNA" is a prototype tool that can be applied in a wide variety of radiobiology studies, providing the scientific community with an open-access base for DNA damage quantification calculations. New DNA and cell geometries for the "molecularDNA" example will be included in future versions of Geant4-DNA.