Modeling gold nanoparticle radiosensitization using a clustering algorithm to quantitate DNA double‐strand breaks with mixed‐physics Monte Carlo simulation

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.

Quantification of gold nanoparticle photon radiosensitization from direct and indirect effects using a complete human genome single cell model based on Geant4

PURPOSE

To investigate the radiosensitization properties of gold nanoparticles (GNPs) and better understand the intricate deoxyribonucleic acid (DNA) damage induction mechanisms involved in GNP-aided radiotherapy, a single cell model with complete human genome based on the Geant4 Monte Carlo toolkit was applied.

MATERIALS AND METHODS

A Geant4-DNA model was implemented to simulate direct and indirect DNA damage generated in the physical and chemical stages. In the physical stage, a mixed-physics approach was taken by using Geant4-DNA in water and Livermore in gold. Water radiolysis was created posteriorly in the physicochemical and chemical stages to simulate indirect damage from reactions between DNA molecules and OH• radicals. A mono-energetic photon beam (100 keV) and two clinical photon sources (250-kVp, 6-MV flattening-filter free) were simulated for modeling the irradiation of a single cell with or without GNPs. In order to study the effects of GNP size on radiosensitization, 15, 30, and 100 nm GNPs were simulated. The effects of intracellular distribution were simulated using 90-nm GNPs with different characteristics of distribution within the cell. The time dependence of DNA damage enhancement was also studied with chemistry stage simulation end-time no larger than 10 ns.

RESULTS

Double strand break (DSB) enhancement due to direct and indirect action was quantified under different scenarios. Under realistic cellular uptake condition, the 100-nm GNPs had the most significant increase in DSBs: 40.9% and 28.5% for 100 keV and 250-kVp photon irradiation, respectively. The intracellular localization showed differing levels of radiosensitization with a maximum of 64%, 27%, and 6% DSB enhancements for 100 keV, 250-kVp, and 6-MV respectively, when 90-nm GNPs congregate around the nucleus.

CONCLUSION

The results indicate that photon energy, GNP size, and intracellular distribution play an important role in the enhancement of DSB from direct and indirect damage under scenarios close to cell experiments. The radiosensitization effects due to indirect damage are significant and should be considered carefully.

On the Equivalence of the Biological Effect Induced by Irradiation of Clusters of Heavy Atom Nanoparticles and Homogeneous Heavy Atom-Water Mixtures

A multiscale local effect model (LEM)-based framework was implemented to study the cell damage caused by the irradiation of clusters of gold nanoparticles (GNPs) under clinically relevant conditions. The results were compared with those obtained by a homogeneous mixture of water and gold (MixNP) irradiated under similar conditions. To that end, Monte Carlo simulations were performed for the irradiation of GNP clusters of different sizes and MixNPs with a 6 MV Linac spectrum to calculate the dose enhancement factor in water. The capabilities of our framework for the prediction of cell damage trends are examined and discussed. We found that the difference of the main parameter driving the cell damage between a cluster of GNPs and the MixNP was less than 1.6% for all cluster sizes. Our results demonstrate for the first time a simple route to intuit the radiobiological effects of clusters of nanoparticles through the consideration of an equivalent homogenous gold/water mixture. Furthermore, the negligible difference on cell damage between a cluster of GNPs and MixNP simplifies the modelling for the complex geometries of nanoparticle aggregations and saves computational resources.

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.

Development of a coupled simulation toolkit for computational radiation biology based on Geant4 and CompuCell3D

Understanding and designing clinical radiation therapy is one of the most important areas of state-of-the-art oncological treatment regimens. Decades of research have gone into developing sophisticated treatment devices and optimization protocols for schedules and dosages. In this paper, we presented a comprehensive computational platform that facilitates building of the sophisticated multi-cell-based model of how radiation affects the biology of living tissue. We designed and implemented a coupled simulation method, including a radiation transport model, and a cell biology model, to simulate the tumor response after irradiation. The radiation transport simulation was implemented through Geant4 which is an open-source Monte Carlo simulation platform that provides many flexibilities for users, as well as low energy DNA damage simulation physics, Geant4-DNA. The cell biology simulation was implemented using CompuCell3D (CC3D) which is a cell biology simulation platform. In order to couple Geant4 solver with CC3D, we developed a 'bridging' module, RADCELL, that extracts tumor cellular geometry of the CC3D simulation (including specification of the individual cells) and ported it to the Geant4 for radiation transport simulation. The cell dose and cell DNA damage distribution in multicellular system were obtained using Geant4. The tumor response was simulated using cell-based tissue models based on CC3D, and the cell dose and cell DNA damage information were fed back through RADCELL to CC3D for updating the cell properties. By merging two powerful and widely used modeling platforms, CC3D and Geant4, we delivered a novel tool that can give us the ability to simulate the dynamics of biological tissue in the presence of ionizing radiation, which provides a framework for quantifying the biological consequences of radiation therapy. In this introductory methods paper, we described our modeling platform in detail and showed how it can be applied to study the application of radiotherapy to a vascularized tumor.

Advances in modelling gold nanoparticle radiosensitization using new Geant4-DNA physics models

Gold nanoparticles have demonstrated significant radiosensitization of cancer treatment with x-ray radiotherapy. To understand the mechanisms at the basis of nanoparticle radiosensitization, Monte Carlo simulations are used to investigate the dose enhancement, given a certain nanoparticle concentration and distribution in the biological medium. Earlier studies have ordinarily used condensed history physics models to predict nanoscale dose enhancement with nanoparticles. This study uses Geant4-DNA complemented with novel track structure physics models to accurately describe electron interactions in gold and to calculate the dose surrounding gold nanoparticle structures at nanoscale level. The computed dose in silico due to a clinical kilovoltage beam and the presence of gold nanoparticles was related to in vitro brain cancer cell survival using the local effect model. The comparison of the simulation results with radiobiological experimental measurements shows that Geant4-DNA and local effect model can be used to predict cell survival in silico in the case of x-ray kilovoltage beams.

Modeling double-strand breaks from direct and indirect action in a complete human genome single cell Geant4 model

The aim of this work is to develop and validate a computational model to investigate direct and indirect DNA damage by directly quantifying DNA strand breaks. A detailed geometrical target model was created in the Monte Carlo toolkit Geant4 to represent the nucleus of a single human cell with complete human genome. A calculation framework to simulate double-strand breaks (DSBs) was implemented using this single cell model in the Geant4-DNA extension. A detailed ellipsoidal single cell model was implemented using a compacted DNA structure representing the fibroblast cell in the G0/G1 phase of the cycle using a total of 6 Gbp within the nucleus to represent the complete human genome. This geometry was developed from the publicly available Geant4-DNA example (wholeNuclearDNA), and modified to record DNA damage for both the physical and chemical stages. A clustering algorithm was implemented in the analysis process in order to quantify direct, indirect, and mixed DSBs. The model was validated against published experimental and computational results for DSB Gy^-1Gbp^-1and the relative biological effectiveness (RBE) values for 250 kVp and Co-60 photons, as well as 2-100 MeV mono-energetic protons. A general agreement was observed over the whole simulated proton energy range, Co-60 beam, and 250 kVp in terms of the yield of DSB Gy^-1Gbp^-1and RBE. The DSB yield was 8.0 ± 0.3 DSB Gy^-1Gbp^-1for Co-60, and 9.2 ± 0.2 DSB Gy^-1Gbp^-1for 250 kVp, and between 11.1 ± 0.9 and 8.1 ± 0.5 DSB Gy^-1Gbp^-1for 2-100 MeV protons. The results also show mixed DSBs composed of direct and indirect SSBs make up more than half of the total DSBs. The results presented indicate that the current model reliably predicts the DSB yield and RBE for proton and photon irradiations, and allows for the detailed computational investigation of direct and indirect effects in DNA damage.

Tumor-targeted pH-low insertion peptide delivery of theranostic gadolinium nanoparticles for image-guided nanoparticle-enhanced radiation therapy

Tumor targeting studies using metallic nanoparticles (NPs) have shown that the enhanced permeability and retention effect may not be sufficient to deliver the amount of intratumoral and intracellular NPs needed for effective in vivo radiosensitization. This work describes a pH-Low Insertion Peptide (pHLIP) targeted theranostic agent to enable image-guided NP-enhanced radiotherapy using a clinically feasible amount of injected NPs. Conventional gadolinium (Gd) NPs were conjugated to pHLIPs and evaluated in vitro for radiosensitivity and in vivo for mouse MRI. Cultured A549 human lung cancer cells were incubated with 0.5 mM of pHLIP-GdNP or conventional GdNP. Mass spectrometry showed 78-fold more cellular Gd uptake with pHLIP-GdNPs, and clonogenic survival assays showed 44% more enhanced radiosensitivity by 5 Gy irradiation with pHLIP-GdNPs at pH 6.2. In contrast to conventional GdNPs, MR imaging of tumor-bearing mice showed pHLIP-GdNPs had a long retention time in the tumor (>9 h), suitable for radiotherapy, and penetrated into the poorly-vascularized tumor core. The Gd-enhanced tumor corresponded with low-pH areas also independently measured by an in vivo molecular MRI technique. pHLIPs actively target cell surface acidity from tumor cell metabolism and deliver GdNPs into cells in solid tumors. Intracellular delivery enhances the effect of short-range radiosensitizing photoelectrons and Auger electrons. Because acidity is a general hallmark of tumor cells, the delivery is more general than antibody targeting. Imaging the in vivo NP biodistribution and more acidic (often more aggressive) tumors has the potential for quantitative radiotherapy treatment planning and pre-selecting patients who will likely benefit more from NP radiation enhancement.

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

Ionizing radiation is a common tool in medical procedures. Monte Carlo (MC) techniques are widely used when dosimetry is the matter of investigation. The scientific community has invested, over the last 20 years, a lot of effort into improving the knowledge of radiation biology. The present article aims to summarize the understanding of the field of DNA damage response (DDR) to ionizing radiation by providing an overview on MC simulation studies that try to explain several aspects of radiation biology. The need for accurate techniques for the quantification of DNA damage is crucial, as it becomes a clinical need to evaluate the outcome of various applications including both low- and high-energy radiation medical procedures. Understanding DNA repair processes would improve radiation therapy procedures. Monte Carlo simulations are a promising tool in radiobiology studies, as there are clear prospects for more advanced tools that could be used in multidisciplinary studies, in the fields of physics, medicine, biology and chemistry. Still, lot of effort is needed to evolve MC simulation tools and apply them in multiscale studies starting from small DNA segments and reaching a population of cells.