The BIANCA model/code of radiation-induced cell death: application to human cells exposed to different radiation types

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.

Modelling Cellular Response to Ionizing Radiation: Mechanistic, Semi-Mechanistic, and Phenomenological Approaches - A Historical Perspective

Radiation research is a multidisciplinary field, and among its many branches, mathematical and computational modelers have played a significant role in advancing boundaries of knowledge. A fundamental contribution is modelling cellular response to ionizing radiation as that is the key to not only understanding how radiation can kill cancer cells, but also cause cancer and other health issues. The invention of microdosimetry in the 1950s by Harold Rossi paved the way for brilliant scientists to study the mechanism of radiation at cellular and sub-cellular scales. This paper reviews some snippets of ingenious mathematical and computational models published in microdosimetry symposium proceedings and publications of the radiation research community. Among these are simulations of radiation tracks at atomic and molecular levels using Monte Carlo methods, models of cell survival, quantification of the amount of energy required to create a single strand break, and models of DNA-damage-repair. These models can broadly be categorized into mechanistic, semi-mechanistic, and phenomenological approaches, and this review seeks to provide historical context of their development. We salute pioneers of the field and great teachers who supported and educated the younger members of the community and showed them how to build upon their work.

The impact of dose rate on responses of human lens epithelial cells to ionizing irradiation

The knowledge on responses of human lens epithelial cells (HLECs) to ionizing radiation exposure is important to understand mechanisms of radiation cataracts that are of concern in the field of radiation protection and radiation therapy. However, biological effects in HLECs following protracted exposure have not yet fully been explored. Here, we investigated the temporal kinetics of γ-H2AX foci as a marker for DNA double-strand breaks (DSBs) and cell survival in HLECs after exposure to photon beams at various dose rates (i.e., 150 kVp X-rays at 1.82, 0.1, and 0.033 Gy/min, and 137Cs γ-rays at 0.00461 Gy/min (27.7 cGy/h) and 0.00081 Gy/min (4.9 cGy/h)), compared to those in human lung fibroblasts (WI-38). In parallel, we quantified the recovery for DSBs and cell survival using a biophysical model. The study revealed that HLECs have a lower DSB repair rate than WI-38 cells. There is no significant impact of dose rate on cell survival in both cell lines in the dose-rate range of 0.033-1.82 Gy/min. In contrast, the experimental residual γ-H2AX foci showed inverse dose rate effects (IDREs) compared to the model prediction, highlighting the importance of the IDREs in evaluating radiation effects on the ocular lens.

Modeling for predicting survival fraction of cells after ultra-high dose rate irradiation

Objective. FLASH radiotherapy (FLASH-RT) with ultra-high dose rate (UHDR) irradiation (i.e. > 40 Gy s-1) spares the function of normal tissues while preserving antitumor efficacy, known as the FLASH effect. The biological effects after conventional dose rate-radiotherapy (CONV-RT) with ≤0.1 Gy s-1have been well modeled by considering microdosimetry and DNA repair processes, meanwhile modeling of radiosensitivities under UHDR irradiation is insufficient. Here, we developed anintegrated microdosimetric-kinetic(IMK)model for UHDR-irradiationenabling the prediction of surviving fraction after UHDR irradiation.Approach.TheIMK model for UHDR-irradiationconsiders the initial DNA damage yields by the modification of indirect effects under UHDR compared to CONV dose rate. The developed model is based on the linear-quadratic (LQ) nature with the dose and dose square coefficients, considering the reduction of DNA damage yields as a function of dose rate.Main results.The estimate by the developed model could successfully reproduce thein vitroexperimental dose-response curve for various cell line types and dose rates.Significance.The developed model would be useful for predicting the biological effects under the UHDR irradiation.

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.

Application of a simple DNA damage model developed for electrons to proton irradiation

Proton beam therapy allows irradiating tumor volumes with reduced side effects on normal tissues with respect to conventional x-ray radiotherapy. Biological effects such as cell killing after proton beam irradiations depend on the proton kinetic energy, which is intrinsically related to early DNA damage induction. As such, DNA damage estimation based on Monte Carlo simulations is a research topic of worldwide interest. Such simulation is a mean of investigating the mechanisms of DNA strand break formations. However, past modellings considering chemical processes and DNA structures require long calculation times. Particle and heavy ion transport system (PHITS) is one of the general-purpose Monte Carlo codes that can simulate track structure of protons, meanwhile cannot handle radical dynamics simulation in liquid water. It also includes a simple model enabling the efficient estimation of DNA damage yields only from the spatial distribution of ionizations and excitations without DNA geometry, which was originally developed for electron track-structure simulations. In this study, we investigated the potential application of the model to protons without any modification. The yields of single-strand breaks, double-strand breaks (DSBs) and the complex DSBs were assessed as functions of the proton kinetic energy. The PHITS-based estimation showed that the DSB yields increased as the linear energy transfer (LET) increased, and reproduced the experimental and simulated yields of various DNA damage types induced by protons with LET up to about 30 keV μm−1. These results suggest that the current DNA damage model implemented in PHITS is sufficient for estimating DNA lesion yields induced after protons irradiation except at very low energies (below 1 MeV). This model contributes to evaluating early biological impacts in radiation therapy.

First application of the BIANCA biophysical model to carbon-ion patient cases

Objective. The main objective of this work consists of applying, for the first time, the BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations) biophysical model to the RBE calculation for C-ion cancer patients, and comparing the outcomes with those obtained by the LEM I model, which is applied in clinics. Indeed, the continuous development of heavy-ion cancer therapy requires modelling of biological effects of ion beams on tumours and normal tissues. The relative biological effectiveness (RBE) of heavy ions is higher than that of protons, with a significant variation along the beam path. Therefore, it requires a precise modelling, especially for the pencil-beam scanning technique. Currently, two radiobiological models, LEM I and MKM, are in use for heavy ions in scanned pencil-beam facilities. Approach. Utilizing an interface with the FLUKA Particle Therapy Tool, BIANCA was applied to re-calculate the RBE-weighted dose distribution for carbon-ion treatment of three patients (chordoma, head-and-neck and prostate) previously irradiated at CNAO, where radiobiological optimization was based on LEM I. The predictions obtained by BIANCA were based either on chordoma cell survival (RBE surv ), or on dicentric aberrations in peripheral blood lymphocytes (RBE ab ), which are indicators of late normal tissue damage, including secondary tumours. The simulation outcomes were then compared with those provided by LEM I. Main results. While in the target and in the entrance channel BIANCA predictions were lower than those obtained by LEM I, the two models provided very similar results in the considered OAR. The observed differences between RBE surv and RBE ab (which were also dependent on fractional dose and LET) suggest that in normal tissues the information on cell survival should be integrated by information more closely related to the induction of late damage, such as chromosome aberrations. Significance. This work showed that BIANCA is suitable for treatment plan optimization in ion-beam therapy, especially considering that it can predict both cell survival and chromosome aberrations and has previously shown good agreement with carbon-ion experimental data.

Track-structure modes in particle and heavy ion transport code system (PHITS): application to radiobiological research

PURPOSE

In radiation physics, Monte Carlo radiation transport simulations are powerful tools to evaluate the cellular responses after irradiation. When investigating such radiation-induced biological effects, it is essential to perform track structure simulations by explicitly considering each atomic interaction in liquid water at the sub-cellular and DNA scales. The Particle and Heavy-Ion Transport code System (PHITS) is a Monte Carlo code which enables to calculate track structure at DNA scale by employing the track-structure modes for electrons, protons and carbon ions. In this paper, we review the recent development status and future prospects of the track-structure modes in the PHITS code.

CONCLUSIONS

To date, the physical features of these modes have been verified using the available experimental data and Monte Carlo simulation results reported in literature. These track-structure modes can be used for calculating microdosimetric distributions to estimate cell survival and for estimating initial DNA damage yields. The use of PHITS track-structure mode is expected not only to clarify the underlying mechanisms of radiation effects but also to predict curative effects in radiation therapy. The results of PHITS simulations coupled with biophysical models will contribute to the radiobiological studies by precisely predicting radiation-induced biological effects based on the Monte Carlo approach.

Investigation into the foundations of the track-event theory of cell survival and the radiation action model based on nanodosimetry

This work aims at elaborating the basic assumptions behind the "track-event theory" (TET) and its derivate "radiation action model based on nanodosimetry" (RAMN) by clearly distinguishing between effects of tracks at the cellular level and the induction of lesions in subcellular targets. It is demonstrated that the model assumptions of Poisson distribution and statistical independence of the frequency of single and clustered DNA lesions are dispensable for multi-event distributions because they follow from the Poisson distribution of the number of tracks affecting the considered target volume. It is also shown that making these assumptions for the single-event distributions of the number of lethal and sublethal lesions within a cell would lead to an essentially exponential dose dependence of survival for practically relevant values of the absorbed dose. Furthermore, it is elucidated that the model equation used for consideration of repair within the TET is based on the assumption that DNA lesions induced by different tracks are repaired independently. Consequently, the model equation is presumably inconsistent with the model assumptions and requires an additional model parameter. Furthermore, the methodology for deriving model parameters from nanodosimetric properties of particle track structure is critically assessed. Based on data from proton track simulations it is shown that the assumption of statistically independent targets leads to the prediction of negligible frequency of clustered DNA damage. An approach is outlined how track structure could be considered in determining the model parameters, and the implications for TET and RAMN are discussed.

Cellular Response to Proton Irradiation: A Simulation Study with TOPAS-nBio

The cellular response to ionizing radiation continues to be of significant research interest in cancer radiotherapy, and DNA is recognized as the critical target for most of the biologic effects of radiation. Incident particles can cause initial DNA damages through physical and chemical interactions within a short time scale. Initial DNA damages can undergo repair via different pathways available at different stages of the cell cycle. The misrepair of DNA damage results in genomic rearrangement and causes mutations and chromosome aberrations, which are drivers of cell death. This work presents an integrated study of simulating cell response after proton irradiation with energies of 0.5-500 MeV (LET of 60-0.2 keV/µm). A model of a whole nucleus with fractal DNA geometry was implemented in TOPAS-nBio for initial DNA damage simulations. The default physics and chemistry models in TOPAS-nBio were used to describe interactions of primary particles, secondary particles, and radiolysis products within the nucleus. The initial DNA double-strand break (DSB) yield was found to increase from 6.5 DSB/Gy/Gbp at low-linear energy transfer (LET) of 0.2 keV/µm to 21.2 DSB/Gy/Gbp at high LET of 60 keV/µm. A mechanistic repair model was applied to predict the characteristics of DNA damage repair and dose response of chromosome aberrations. It was found that more than 95% of the DSBs are repaired within the first 24 h and the misrepaired DSB fraction increases rapidly with LET and reaches 15.8% at 60 keV/µm with an estimated chromosome aberration detection threshold of 3 Mbp. The dicentric and acentric fragment yields and the dose response of micronuclei formation after proton irradiation were calculated and compared with experimental results.

Modelling Dose Effects from Space Irradiations: Combination of High-LET and Low-LET Radiations with a Modified Microdosimetric Kinetic Model

The Microdosimetric Kinetic Model (MKM) to predict the effects of ionizing radiation on cell colonies is studied and reformulated for the case of high-linear energy transfer (LET) radiations with a low dose. When the number of radiation events happening in a subnuclear domain follows a Poisson distribution, the MKM predicts a linear-quadratic (LQ) survival curve. We show that when few events occur, as for high-LET radiations at doses lower than the mean specific energy imparted to the nucleus, zF,n, a Poisson distribution can no longer be assumed and an initial pure linear relationship between dose and survival fraction should be observed. Predictions of survival curves for combinations of high-LET and low-LET radiations are produced under two assumptions for their comparison: independent and combined action. Survival curves from previously published articles of V79 cell colonies exposed to X-rays, α particles, Ar-ions, Fe-ions, Ne-ions and mixtures of X-rays and each one of the ions are predicted according to the modified MKM. We conclude that mixtures of high-LET and low-LET radiations may enhance the effect of individual actions due to the increase of events in domains provided by the low-LET radiation. This hypothesis is only partially validated by the analyzed experiments.

In Vivo Validation of the BIANCA Biophysical Model: Benchmarking against Rat Spinal Cord RBE Data

(1) Background: Cancer ion therapy is constantly growing thanks to its increased precision and, for heavy ions, its increased biological effectiveness (RBE) with respect to conventional photon therapy. The complex dependence of RBE on many factors demands biophysical modeling. Up to now, only the Local Effect Model (LEM), the Microdosimetric Kinetic Model (MKM), and the "mixed-beam" model are used in clinics. (2) Methods: In this work, the BIANCA biophysical model, after extensive benchmarking in vitro, was applied to develop a database predicting cell survival for different ions, energies, and doses. Following interface with the FLUKA Monte Carlo transport code, for the first time, BIANCA was benchmarked against in vivo data obtained by C-ion or proton irradiation of the rat spinal cord. The latter is a well-established model for CNS (central nervous system) late effects, which, in turn, are the main dose-limiting factors for head-and-neck tumors. Furthermore, these data have been considered to validate the LEM version applied in clinics. (3) Results: Although further benchmarking is desirable, the agreement between simulations and data suggests that BIANCA can predict RBE for C-ion or proton treatment of head-and-neck tumors. In particular, the agreement with proton data may be relevant if the current assumption of a constant proton RBE of 1.1 is revised. (4) Conclusions: This work provides the basis for future benchmarking against patient data, as well as the development of other databases for specific tumor types and/or normal tissues.

A theoretical cell-killing model to evaluate oxygen enhancement ratios at DNA damage and cell survival endpoints in radiation therapy

Radio-resistance induced under low oxygen pressure plays an important role in malignant progression in fractionated radiotherapy. For the general approach to predict cell killing under hypoxia, cell-killing models (e.g. the Linear-Quadratic model) have to be fitted to in vitro experimental survival data for both normoxia and hypoxia to obtain the oxygen enhancement ratio (OER). In such a case, model parameters for every oxygen condition needs to be considered by model-fitting approaches. This is inefficient for fractionated irradiation planning. Here, we present an efficient model for fractionated radiotherapy the integrated microdosimetric-kinetic model including cell-cycle distribution and the OER at DNA double-strand break endpoint (OER_DSB). The cell survival curves described by this model can reproduce the in vitro experimental survival data for both acute and chronic low oxygen concentrations. The OER_DSB used for calculating cell survival agrees well with experimental DSB ratio of normoxia to hypoxia. The important parameters of the model are oxygen pressure and cell-cycle distribution, which enables us to predict cell survival probabilities under chronic hypoxia and chronic anoxia. This work provides biological effective dose (BED) under various oxygen conditions including its uncertainty, which can contribute to creating fractionated regimens for multi-fractionated radiotherapy. If the oxygen concentration in a tumor can be quantified by medical imaging, the present model will make it possible to estimate the cell-killing and BED under hypoxia in more realistic intravital situations.

Modeling of chromosome aberration response functions induced by particle beams with different LET

This study is based on our already published experimental data (Kowalska et al. in Radiat Environ Biophys 58:99-108, 2019) and is devoted to modeling of chromosome aberrations in human lymphocytes induced by 22.1 MeV/u ¹¹B ions, 199 MeV/u ¹²C ions, 150 MeV and spread-out Bragg peak (SOBP) proton beams as well as by ⁶⁰Co γ rays. The curvature of the dose-effect curves determined by the linear-quadratic model was considered in the frame of a simple analytical approach taking into account increase in the irradiation dose due to overlapping interaction regions of ion tracks. The model enabled to estimate effective interaction radius which could be compared with the physical expectations. The results were also compared to the Amorphous Track Structure Model of Katz which allows to get some additional information about the ion track structure. The analysis showed that the curvature of the experimental dose-effect curves mainly results from highly efficient repair processes of the DNA damage.

Ab Initio Molecular Dynamics Simulations to Interpret the Molecular Fragmentation Induced in Deoxyribose by Synchrotron Soft X-Rays

It has been suggested that core ionization in DNA atoms could induce complex, irreparable damage. Synchrotron soft X-rays have been used to probe the damage induced by such events in thin films of DNA components. In a complementary approach, we investigate the fragmentation dynamics following a carbon or oxygen K-shell ionization in 2-deoxy-D-ribose (DR), a major component in the DNA chain. Core ionization of the sugars hydration layer is also studied. To that aim, we use state-of-the-art ab initio Density Functional Theory-based Molecular Dynamics (MD) simulations. The ultrafast dissociation dynamics of the core ionized molecule, prior Auger decay, is modeled for about 10 fs. We show that the core-ionization of oxygen atoms within DR or its hydration layer may induce proton transfers towards nearby molecules, before Auger decay. In a second step, we model an Auger effect occurring either at the beginning or at the end of the core–hole dynamics. Two electrons are removed from the deepest valence molecular orbitals localized on the initially core-ionized oxygen atom (O*), and this electronic state is propagated by means of Ehrenfest MD. We show an ultrafast dissociation of the DR2+ molecule C-O* bonds, which, in most cases, seems independent of the time at which Auger decay occurs.

First benchmarking of the BIANCA model for cell survival prediction in a clinical hadron therapy scenario

In the framework of RBE modelling for hadron therapy, the BIANCA biophysical model was extended to O-ions and was used to construct a radiobiological database describing the survival of V79 cells as a function of ion type (1  ⩽  Z  ⩽  8) and energy. This database allowed performing RBE predictions in very good agreement with experimental data. A method was then developed to construct analogous databases for different cell lines, starting from the V79 database as a reference. Following interface to the FLUKA Monte Carlo radiation transport code, BIANCA was then applied for the first time to predict cell survival in a typical patient treatment scenario, consisting of two opposing fields of range-equivalent protons or C-ions. The model predictions were found to be in good agreement with CHO cell survival data obtained at the Heidelberg ion-beam therapy (HIT) centre, as well as predictions performed by the local effect model (version LEM IV). This work shows that BIANCA can be used to predict cell survival and RBE not only for V79 and AG01522 cells, as shown previously, but also, in principle, for any cell line of interest. Furthermore, following interface to a transport code like FLUKA, BIANCA can provide predictions of 3D biological dose distributions for hadron therapy treatments, thus laying the foundations for future applications in clinics.

Mechanistic modelling supports entwined rather than exclusively competitive DNA double-strand break repair pathway

Following radiation induced DNA damage, several repair pathways are activated to help preserve genome integrity. Double Strand Breaks (DSBs), which are highly toxic, have specified repair pathways to address them. The main repair pathways used to resolve DSBs are Non-Homologous End Joining (NHEJ) and Homologous Recombination (HR). Cell cycle phase determines the availability of HR, but the repair choice between pathways in the G2 phases where both HR and NHEJ can operate is not clearly understood. This study compares several in silico models of repair choice to experimental data published in the literature, each model representing a different possible scenario describing how repair choice takes place. Competitive only scenarios, where initial protein recruitment determines repair choice, are unable to fit the literature data. In contrast, the scenario which uses a more entwined relationship between NHEJ and HR, incorporating protein co-localisation and RNF138-dependent removal of the Ku/DNA-PK complex, is better able to predict levels of repair similar to the experimental data. Furthermore, this study concludes that co-localisation of the Mre11-Rad50-Nbs1 (MRN) complexes, with initial NHEJ proteins must be modeled to accurately depict repair choice.

Modelling of Cellular Survival Following Radiation-Induced DNA Double-Strand Breaks

A mechanistic model of cellular survival following radiation-induced DNA double-strand breaks (DSBs) was proposed in this study. DSBs were assumed as the initial lesions in the DNA of the cell nucleus induced by ionizing radiation. The non-homologous end-joining (NHEJ) pathway was considered as the domain pathway of DSB repair in mammalian cells. The model was proposed to predict the relationship between radiation-induced DSBs in nucleus and probability of cell survival, which was quantitatively described by two input parameters and six fitting parameters. One input parameter was the average number of primary particles which caused DSB, the other input parameter was the average number of DSBs yielded by each primary particle that caused DSB. The fitting parameters were used to describe the biological characteristics of the irradiated cells. By determining the fitting parameters of the model with experimental data, the model is able to estimate surviving fractions for the same type of cells exposed to particles with different physical parameters. The model further revealed the mechanism of cell death induced by the DSB effect. Relative biological effectiveness (RBE) of charged particles at different survival could be calculated with the model, which would provide reference for clinical treatment.

Geometrical structures for radiation biology research as implemented in the TOPAS-nBio toolkit

Computational simulations, such as Monte Carlo track structure simulations, offer a powerful tool for quantitatively investigating radiation interactions within cells. The modelling of the spatial distribution of energy deposition events as well as diffusion of chemical free radical species, within realistic biological geometries, can help provide a comprehensive understanding of the effects of radiation on cells. Track structure simulations, however, generally require advanced computing skills to implement. The TOPAS-nBio toolkit, an extension to TOPAS (TOol for PArticle Simulation), aims to provide users with a comprehensive framework for radiobiology simulations, without the need for advanced computing skills. This includes providing users with an extensive library of advanced, realistic, biological geometries ranging from the micrometer scale (e.g. cells and organelles) down to the nanometer scale (e.g. DNA molecules and proteins). Here we present the geometries available in TOPAS-nBio.

Analysis of Radiation-Induced Chromosomal Aberrations on a Cell-by-Cell Basis after Alpha-Particle Microbeam Irradiation: Experimental Data and Simulations

There is a continued need for further clarification of various aspects of radiation-induced chromosomal aberration, including its correlation with radiation track structure. As part of the EMRP joint research project, Biologically Weighted Quantities in Radiotherapy (BioQuaRT), we performed experimental and theoretical analyses on chromosomal aberrations in Chinese hamster ovary cells (CHO-K1) exposed to α particles with final energies of 5.5 and 17.8 MeV (absorbed doses: ∼2.3 Gy and ∼1.9 Gy, respectively), which were generated by the microbeam at the Physikalisch-Technische Bundesanstalt (PTB) in Braunschweig, Germany. In line with the differences in linear energy transfer (approximately 85 keV/μm for 5.5 MeV and 36 keV/μm for 17.8 MeV α particles), the 5.5 MeV α particles were more effective than the 17.8 MeV α particles, both in terms of the percentage of aberrant cells (57% vs. 33%) and aberration frequency. The yield of total aberrations increased by a factor of ∼2, although the increase in dicentrics plus centric rings was less pronounced than in acentric fragments. The experimental data were compared with Monte Carlo simulations based on the BIophysical ANalysis of Cell death and chromosomal Aberrations model (BIANCA). This comparison allowed interpretation of the results in terms of critical DNA damage [cluster lesions (CLs)]. More specifically, the higher aberration yields observed for the 5.5 MeV α particles were explained by taking into account that, although the nucleus was traversed by fewer particles (nominally, 11 vs. 25), each particle was much more effective (by a factor of ∼3) at inducing CLs. This led to an increased yield of CLs per cell (by a factor of ∼1.4), consistent with the increased yield of total aberrations observed in the experiments.

BIANCA, a biophysical model of cell survival and chromosome damage by protons, C-ions and He-ions at energies and doses used in hadrontherapy

An upgraded version of the BIANCA II biophysical model, which describes more realistically interphase chromosome organization and the link between chromosome aberrations and cell death, was applied to V79 and AG01522 cells exposed to protons, C-ions and He-ions over a wide LET interval (0.6-502 keV µm^-1), as well as proton-irradiated U87 cells. The model assumes that (i) ionizing radiation induces DNA 'cluster lesions' (CLs), where by definition each CL produces two independent chromosome fragments; (ii) fragment (distance-dependent) mis-rejoining, or un-rejoining, produces chromosome aberrations; (iii) some aberrations lead to cell death. The CL yield, which mainly depends on radiation quality but is also modulated by the target cell, is an adjustable parameter. The fragment un-rejoining probability, f, is the second, and last, parameter. The value of f, which is assumed to depend on the cell type but not on radiation quality, was taken from previous studies, and only the CL yield was adjusted in the present work. Good agreement between simulations and experimental data was obtained, suggesting that BIANCA II is suitable for calculating the biological effectiveness of hadrontherapy beams. For both V79 and AG01522 cells, the mean number of CLs per micrometer was found to increase with LET in a linear-quadratic fashion before the over-killing region, where a less rapid increase, with a tendency to saturation, was observed. Although the over-killing region deserves further investigation, the possibility of fitting the CL yields is an important feature for hadrontherapy, because it allows performing predictions also at LET values where experimental data are not available. Finally, an approach was proposed to predict the ion-response of the cell line(s) of interest from the ion-response of a reference cell line and the photon response of both. A pilot study on proton-irradiated AG01522 and U87 cells, taking V79 cells as a reference, showed encouraging results.

Proximity effects in chromosome aberration induction: Dependence on radiation quality, cell type and dose

It is widely accepted that, in chromosome-aberration induction, the (mis-)rejoining probability of two chromosome fragments depends on their initial distance, r. However, several aspects of these "proximity effects" need to be clarified, also considering that they can vary with radiation quality, cell type and dose. A previous work performed by the BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations) biophysical model has suggested that, in human lymphocytes and fibroblasts exposed to low-LET radiation, an exponential function of the form exp(-r/r₀), which is consistent with free-end (confined) diffusion, describes proximity effects better than a Gaussian function. Herein, the investigation was extended to intermediate- and high-LET. Since the r₀ values (0.8 μm for lymphocytes and 0.7 μm for fibroblasts) were taken from the low-LET study, the results were obtained by adjusting only one model parameter, i.e. the yield of "Cluster Lesions" (CLs), where a CL was defined as a critical DNA damage producing two independent chromosome fragments. In lymphocytes, the exponential model allowed reproducing both dose-response curves for different aberrations (dicentrics, centric rings and excess acentrics), and values of F-ratio (dicentrics to centric rings) and G-ratio (interstitial deletions to centric rings). In fibroblasts, a good correspondence was found with the dose-response curves, whereas the G-ratio (and, to a lesser extent, the F-ratio) was underestimated. With increasing LET, F decreased and G increased in both cell types, supporting their role as "fingerprints" of high-LET exposure. A dose-dependence was also found at high LET, where F increased with dose and G decreased, possibly due to inter-track effects. We therefore conclude that, independent of radiation quality, in lymphocytes an exponential function can describe proximity effects at both inter- and intra-chromosomal level; on the contrary, in fibroblasts further studies (experimental and theoretical) are needed to explain the strong bias for intra-arm relative to inter-arm exchanges.

Proximity effects in chromosome aberration induction by low-LET ionizing radiation

Although chromosome aberrations are known to derive from distance-dependent mis-rejoining of chromosome fragments, evaluating whether a certain model describes such "proximity effects" better than another one is complicated by the fact that different approaches have often been tested under different conditions. Herein, a biophysical model ("BIANCA", i.e. BIophysical ANalysis of Cell death and chromosome Aberrations) was upgraded, implementing explicit chromosome-arm domains and two new models for the dependence of the rejoining probability on the fragment initial distance, r. Such probability was described either by an exponential function like exp(-r/r₀), or by a Gaussian function like exp(-r²/2σ²), where r₀ and σ were adjustable parameters. The second, and last, parameters was the yield of "Cluster Lesions" (CL), where "Cluster Lesion" defines a critical DNA damage producing two independent chromosome fragments. The model was applied to low-LET-irradiated lymphocytes (doses: 1-4Gy) and fibroblasts (1-6.1Gy). Good agreement with experimental yields of dicentrics and centric rings, and thus their ratio ("F-ratio"), was found by both the exponential model (with r₀=0.8μm for lymphocytes and 0.7μm for fibroblasts) and the Gaussian model (with σ=1.1μm for lymphocytes and 1.3μm for fibroblasts). While the former also allowed reproducing dose-responses for excess acentric fragments, the latter substantially underestimated the experimental curves. Both models provided G-ratios (ratio of acentric to centric rings) higher than those expected from randomness, although the values calculated by the Gaussian model were lower than those calculated by the exponential one. For lymphocytes the calculated G-ratios were in good agreement with the experimental ones, whereas for fibroblasts both models substantially underestimated the experimental results, which deserves further investigation. This work suggested that, although both models performed better than a step model (which previously allowed reproducing the F-ratio but underestimated the G-ratio), an exponential function describes proximity effects better than a Gaussian one.

Metastatic disease in uveal melanoma: importance of a genetic profile?

Mutation of SF3B1 has been identified in low-grade uveal melanoma with a good prognosis. In this study, we compare chromosomal aberrations and gene mutations between a primary uveal melanoma and its multiple hepatic and peripancreatic metastases. DNA was isolated from a large primary uveal melanoma after fractionated stereotactic radiotherapy and three distinct metastases (two liver samples and one peripancreatic lymph node) to perform single-nucleotide polymorphism array and fluorescent in-situ hybridization. We analyzed mutations in uveal melanoma target genes BAP1, GNAQ, GNA11, SF3B1, and EIF1AX. The primary tumor showed no abnormalities in chromosome 3, whereas metastases showed deletion of at least 3q12.1-q24 and the BAP1 gene was not mutated. All samples indicated the following consistent chromosomal aberrations: loss of 1p, gain of 6p, and gain of 8q. Subsequently, heterozygous SF3B1 and heterozygous GNA11 mutations were observed. The metastases showed more genetic aberrations than the primary tumor and may therefore represent the genetic status of the tumor before irradiation, whereas the current primary tumor shows presumably irradiation artifacts. An early occurring mutation in GNA11 was observed in all samples. The SF3B1 mutation seems to predispose for late metastatic disease in the absence of a BAP1 mutation.

Calculating Variations in Biological Effectiveness for a 62 MeV Proton Beam

A biophysical model of radiation-induced cell death and chromosome aberrations [called BIophysical ANalysis of Cell death and chromosome Aberrations (BIANCA)] was further developed and applied to therapeutic protons. The model assumes a pivotal role of DNA cluster damage, which can lead to clonogenic cell death following three main steps: (i) a DNA “cluster lesion” (CL) produces two independent chromosome fragments; (ii) fragment mis-rejoining within a threshold distance d gives rise to chromosome aberrations; (iii) certain aberration types (dicentrics, rings, and large deletions) lead to clonogenic inactivation. The yield of CLs and the probability, f, that a chromosome fragment remains un-rejoined even if other fragment(s) are present within d, were adjustable parameters. The model, implemented as a MC code providing simulated dose–responses directly comparable with experimental data, was applied to pristine and modulated Bragg peaks of the proton beam used to treat eye melanoma at INFN-LNS in Catania, Italy. Experimental survival curves for AG01522 cells exposed to the Catania beam were reproduced, supporting the model assumptions. Furthermore, cell death and chromosome aberrations at different depths along a spread-out Bragg peak (SOBP) dose profile were predicted. Both endpoints showed an increase along the plateau, and high levels of damage were found also beyond the distal dose fall-off, due to low-energy protons. Cell death and chromosome aberrations were also predicted for V79 cells, in the same irradiation scenario as that used for AG01522 cells. In line with other studies, this work indicated that assuming a constant relative biological effectiveness (RBE) along a proton SOBP may be sub-optimal. Furthermore, it provided qualitative and quantitative evaluations of the dependence of the beam effectiveness on the considered endpoint and dose. More generally, this work represents an example of therapeutic beam characterization avoiding the use of experimental RBE values, which can be source of uncertainties.

The role of DNA cluster damage and chromosome aberrations in radiation-induced cell killing: a theoretical approach

The role played by DNA cluster damage and chromosome aberrations in radiation-induced cell killing was investigated, assuming that certain chromosome aberrations (dicentrics, rings and large deletions, or 'lethal aberrations') lead to clonogenic inactivation and that chromosome aberrations are due to micrometre-scale rejoining of chromosome fragments derived from DNA cluster lesions (CLs). The CL yield and the threshold distance governing fragment rejoining were left as model parameters. The model, implemented as a Monte Carlo code called BIANCA (BIophysical ANalysis of Cell death and chromosome Aberrations), provided simulated survival curves that were compared with survival data on AG1522 and V79 cells exposed to different radiation types, including heavy ions. The agreement between simulation outcomes and experimental data suggests that lethal aberrations are likely to play an important role in cell killing not only for AG1522 cells exposed to X rays, as already reported by others, but also for other radiation types and other cells. Furthermore, the results are consistent with the hypothesis that the critical DNA lesions leading to cell death and chromosome aberrations are double-strand break clusters (possibly involving the ∼1000-10 000 bp scale) and that the effects of such clusters are modulated by micrometre-scale proximity effects during DNA damage processing.

Modeling radiation-induced cell death: role of different levels of DNA damage clustering

Some open questions on the mechanisms underlying radiation-induced cell death were addressed by a biophysical model, focusing on DNA damage clustering and its consequences. DNA "cluster lesions" (CLs) were assumed to produce independent chromosome fragments that, if created within a micrometer-scale threshold distance (d), can lead to chromosome aberrations following mis-rejoining; in turn, certain aberrations (dicentrics, rings and large deletions) were assumed to lead to clonogenic cell death. The CL yield and d were the only adjustable parameters. The model, implemented as a Monte Carlo code called BIophysical ANalysis of Cell death and chromosome Aberrations (BIANCA), provided simulated survival curves that were directly compared with experimental data on human and hamster cells exposed to photons, protons, α-particles and heavier ions including carbon and iron. d = 5 μm, independent of radiation quality, and CL yields in the range ~2-20 CLs Gy(-1) cell(-1), depending on particle type and energy, led to good agreement between simulations and data. This supports the hypothesis of a pivotal role of DNA cluster damage at sub-micrometric scale, modulated by chromosome fragment mis-rejoining at micrometric scale. To investigate the features of such critical damage, the CL yields were compared with experimental or theoretical yields of DNA fragments of different sizes, focusing on the base-pair scale (related to the so-called local clustering), the kbp scale ("regional clustering") and the Mbp scale, corresponding to chromatin loops. Interestingly, the CL yields showed better agreement with kbp fragments rather than bp fragments or Mbp fragments; this suggests that also regional clustering, in addition to other clustering levels, may play an important role, possibly due to its relationship with nucleosome organization in the chromatin fiber.

The cytoplasm as a radiation target: an in silico study of microbeam cell irradiation

We performed in silico microbeam cell irradiation modelling to quantitatively investigate ionisations resulting from soft x-ray and alpha particle microbeams targeting the cytoplasm of a realistic cell model. Our results on the spatial distribution of ionisations show that as x-rays are susceptible to scatter within a cell that can lead to ionisations in the nucleus, soft x-ray microbeams may not be suitable for investigating the DNA damage response to radiation targeting the cytoplasm alone. In contrast, ionisations from an ideal alpha microbeam are tightly confined to the cytoplasm, but a realistic alpha microbeam degrades upon interaction with components upstream of the cellular target. Thus it is difficult to completely rule out a contribution from alpha particle hits to the nucleus when investigating DNA damage response to cytoplasmic irradiation. We find that although the cytoplasm targeting efficiency of an alpha microbeam is better than that of a soft x-ray microbeam (the probability of stray alphas hitting the nucleus is 0.2% compared to 3.6% for x-rays), stray alphas produce more ionisations in the nucleus and thus have greater potential for initiating damage responses therein. Our results suggest that observed biological responses to cytoplasmic irradiation include a small component that can be attributed to stray ionisations in the nucleus resulting from the stochastic nature of particle interactions that cause out-of-beam scatter. This contribution is difficult to isolate experimentally, thus demonstrating the value of the in silico approach.