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.

This paper presents the influence of electron elastic scattering models, electron thermalization models, and chemical parameters on Geant4-DNA simulations of liquid water radiolysis under mega-electron-volt electron irradiation. The radiochemical yields are simulated using a new Geant4-DNA example. In particular, the influence of the new elastic scattering model recently developed is presented as well as the influence of improved electron thermalization models. The influence of a new chemistry constructor using parameters of another Monte Carlo track structure code is also described. The results calculated using these different models are compared with each other and with experimental data. For sub-mega-electron-volt electron simulations, the combination of the “G4EmDNAPhysics_option2” physics constructor with the recently developed elastic scattering model, the Meesungnoen electron thermalization model, and the “G4EmDNAChemistry_option1” chemistry constructor is recommended.

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

High-Z metallic nanoparticles (NPs) are new players in the therapeutic arsenal against cancer, especially radioresistant cells. Indeed, the presence of these NPs inside malignant cells is believed to enhance the effect of ionizing radiation by locally increasing the dose deposition. In this context, the potential of platinum nanoparticles (PtNPs) as radiosensitizers was investigated in two breast cancer cell lines, T47D and MDA-MB-231, showing a different radiation sensitivity. PtNPs were internalized in the two cell lines and localized in lysosomes and multivesicular bodies. Analyses of cell responses in terms of clonogenicity, survival, mortality, cell-cycle distribution, oxidative stress, and DNA double-strand breaks did not reveal any significant enhancement effect when cells were pre-exposed to PtNPs before being irradiated, as compared to radiation alone. This result is different from that reported in a previous study performed, under the same conditions, on cervical cancer HeLa cells. This shows that the efficacy of radio-enhancement is strongly cell-type-dependent. Simulation of the early stage ionization processes, taking into account the irradiation characteristics and realistic physical parameters in the biological sample, indicated that PtNPs could weakly increase the dose deposition (by 3%) in the immediate vicinity of the nanoparticles. Some features that are potentially responsible for the biological effect could not be taken into account in the simulation. Thus, chemical and biological effects could explain this discrepancy. For instance, we showed that, in these breast cancer cell lines, PtNPs exhibited ambivalent redox properties, with an antioxidant potential which could counteract the radio-enhancement effect. This work shows that the efficacy of PtNPs for enhancing radiation effects is strongly cell-dependent and that no effect is observed in the case of the breast cancer cell lines T47D and MDA-MB-231. Thus, more extensive experiments using other relevant biological models are needed in order to evaluate such combined strategies, since several clinical trials have already demonstrated the success of combining nanoagents with radiotherapy in the treatment of a range of tumor types.

The chemical stage of the Monte Carlo track-structure simulation code Geant4-DNA has been revised and validated. The root-mean-square (RMS) empirical parameter that dictates the displacement of water molecules after an ionization and excitation event in Geant4-DNA has been shortened to better fit experimental data. The pre-defined dissociation channels and branching ratios were not modified, but the reaction rate coefficients for simulating the chemical stage of water radiolysis were updated. The evaluation of Geant4-DNA was accomplished with TOPAS-nBio. For that, we compared predicted time-dependent G values in pure liquid water for ^· OH, e ^– _aq , and H ₂ with published experimental data. For H ₂ O ₂ and H ^· , simulation of added scavengers at different concentrations resulted in better agreement with measurements. In addition, DNA geometry information was integrated with chemistry simulation in TOPAS-nBio to realize reactions between radiolytic chemical species and DNA. This was used in the estimation of the yield of single-strand breaks (SSB) induced by ¹³⁷ Cs γ -ray radiolysis of supercoiled pUC18 plasmids dissolved in aerated solutions containing DMSO. The efficiency of SSB induction by reaction between radiolytic species and DNA used in the simulation was chosen to provide the best agreement with published measurements. An RMS displacement of 1.24 nm provided agreement with measured data within experimental uncertainties for time-dependent G values and under the presence of scavengers. SSB efficiencies of 24% and 0.5% for ^· OH and H ^· , respectively, led to an overall agreement of TOPAS-nBio results within experimental uncertainties. The efficiencies obtained agreed with values obtained with published non-homogeneous kinetic model and step-by-step Monte Carlo simulations but disagreed by 12% with published direct measurements. Improvement of the spatial resolution of the DNA damage model might mitigate such disagreement. In conclusion, with these improvements, Geant4-DNA/TOPAS-nBio provides a fast, accurate, and user-friendly tool for simulating DNA damage under low linear energy transfer irradiation.