Stochastic modelling of DSB repair after photon and ion irradiation

Modelling DNA damage-repair and beyond

The paper presents a review of mechanistic modelling studies of DNA damage and DNA repair, and consequences to follow in mammalian cell nucleus. We hypothesize DNA deletions are consequences of repair of double strand breaks leading to the modifications of genome that play crucial role in long term development of genetic inheritance and diseases. The aim of the paper is to review formation mechanisms underlying naturally occurring DNA deletions in the human genome and their potential relevance for bridging the gap between induced DNA double strand breaks and deletions in damaged human genome from endogenous and exogenous events. The model of the cell nucleus presented enables simulation of DNA damage at molecular level identifying the spectrum of damage induced in all chromosomal territories and loops. Our mechanistic modelling of DNA repair for double stand breaks (DSB), single strand breaks (SSB) and base damage (BD), shows the complexity of DNA damage is responsible for the longer repair times and the reason for the biphasic feature of mammalian cells repair curves. In the absence of experimentally determined data, the mechanistic model of repair predicts the in vivo rate constants for the proteins involved in the repair of DSB, SSB, and of BD.

Enhanced RBE of Particle Radiation Depends on Beam Size in the Micrometer Range

High-linear energy transfer (LET) radiation, such as heavy ions is associated with a higher relative biological effectiveness (RBE) than low-LET radiation, such as photons. Irradiation with low- and high-LET particles differ in the interaction with the cellular matter and therefore in the spatial dose distribution. When a single high-LET particle interacts with matter, it results in doses of up to thousands of gray (Gy) locally concentrated around the ion trajectory, whereas the mean dose averaged over the target, such as a cell nucleus is only in the range of a Gy. DNA damage therefore accumulates in this small volume. In contrast, up to hundreds of low-LET particle hits are required to achieve the same mean dose, resulting in a quasi-homogeneous damage distribution throughout the cell nucleus. In this study, we investigated the dependence of RBE from different spatial dose depositions using different focused beam spot sizes of proton radiation with respect to the induction of chromosome aberrations and clonogenic cell survival. Human-hamster hybrid (AL) as well as Chinese hamster ovary cells (CHO-K1) were irradiated with focused low LET protons of 20 MeV (LET = 2.6 keV/µm) beam energy with a mean dose of 1.7 Gy in a quadratic matrix pattern with point spacing of 5.4 × 5.4 µm2 and 117 protons per matrix point at the ion microbeam SNAKE using different beam spot sizes between 0.8 µm and 2.8 µm (full width at half maximum). The dose-response curves of X-ray reference radiation were used to determine the RBE after a 1.7 Gy dose of radiation. The RBE for the induction of dicentric chromosomes and cell inactivation was increased after irradiation with the smallest beam spot diameter (0.8 µm for chromosome aberration experiments and 1.0 µm for cell survival experiments) compared to homogeneous proton radiation but was still below the RBE of a corresponding high LET single ion hit. By increasing the spot size to 1.6-1.8 µm, the RBE decreased but was still higher than for homogeneously distributed protons. By further increasing the spot size to 2.7-2.8 µm, the RBE was no longer different from the homogeneous radiation. Our experiments demonstrate that varying spot size of low-LET radiation gradually modifies the RBE. This underlines that a substantial fraction of enhanced RBE originates from inhomogeneous energy concentrations on the µm scale (mean intertrack distances of low-LET particles below 0.1 µm) and quantifies the link between such energy concentration and RBE. The missing fraction of RBE enhancement when comparing with high-LET ions is attributed to the high inner track energy deposition on the nanometer scale. The results are compared with model results of PARTRAC and LEM for chromosomal aberration and cell survival, respectively, which suggest mechanistic interpretations of the observed radiation effects.

Computational modeling and a Geant4-DNA study of the rejoining of direct and indirect DNA damage induced by low energy electrons and carbon ions

PURPOSE

DNA double-strand breaks (DSBs) created by ionizing radiations are considered as the most detrimental lesion, which could result in the cell death or sterilization. As the empirical evidence gathered from the cellular and molecular radiation biology has demonstrated significant correlations between the initial and lasting levels of DSBs, gaining knowledge into the DSB repair mechanisms proves vital. Much effort has been invested into understanding the mechanisms triggering the repair and processes engaged after irradiation of cells. Given a mechanistic model, we performed - to our knowledge - the first Monte Carlo study of the expected repair kinetics of carbon ions and electrons using on the one hand Geant4-DNA simulations of electrons for benchmarking purposes and on the other hand quantifying the influence of direct and indirect damage. Our objective was to calculate the DSB repair rates using a repair mechanism for G1 and early S phases of the cell cycle in conjunction with simulations of the DNA damage.

MATERIALS AND METHODS

Based on Geant4-DNA simulations of DSB damage caused by electrons and carbon ions - using a B-DNA model and a water sphere of 3 μm radius resembling the mean size of human cells - we derived the kinetics of various biochemical repair processes.

RESULTS

The overall repair times of carbon ions increased with the DSB complexity. Comparison of the DSB complexity (DSBc) and repair times as a function of carbon-ion energy suggested that the repair time of no specific fraction of DSBs could solely be explained as a function of DSB complexity.

CONCLUSION

Analysis of the carbon-ion repair kinetics indicated that, given a fraction of DSBs, decreasing the energy would result in an increase of the repair time. The disagreements of the calculated and experimental repair kinetics for electrons could, among others, be due to larger damage complexity predicted by simulations or created actually by electrons of comparable energies to x-rays. They are also due to the employed repair mechanisms, which introduce no inherent dependence on the radiation type but make direct use of the simulated DSBs.

Geometrical Properties of the Nucleus and Chromosome Intermingling Are Possible Major Parameters of Chromosome Aberration Formation

Ionizing radiation causes chromosome aberrations, which are possible biomarkers to assess space radiation cancer risks. Using the Monte Carlo codes Relativistic Ion Tracks (RITRACKS) and Radiation-Induced Tracks, Chromosome Aberrations, Repair and Damage (RITCARD), we investigated how geometrical properties of the cell nucleus, irradiated with ion beams of linear energy transfer (LET) ranging from 0.22 keV/μm to 195 keV/μm, influence the yield of simple and complex exchanges. We focused on the effect of (1) nuclear volume by considering spherical nuclei of varying radii; (2) nuclear shape by considering ellipsoidal nuclei of varying thicknesses; (3) beam orientation; and (4) chromosome intermingling by constraining or not constraining chromosomes in non-overlapping domains. In general, small nuclear volumes yield a higher number of complex exchanges, as compared to larger nuclear volumes, and a higher number of simple exchanges for LET < 40 keV/μm. Nuclear flattening reduces complex exchanges for high-LET beams when irradiated along the flattened axis. The beam orientation also affects yields for ellipsoidal nuclei. Reducing chromosome intermingling decreases both simple and complex exchanges. Our results suggest that the beam orientation, the geometry of the cell nucleus, and the organization of the chromosomes within are important parameters for the formation of aberrations that must be considered to model and translate in vitro results to in vivo risks.

Nanoscale Calculation of Proton-Induced DNA Damage Using a Chromatin Geometry Model with Geant4-DNA

Monte Carlo simulations can quantify various types of DNA damage to evaluate the biological effects of ionizing radiation at the nanometer scale. This work presents a study simulating the DNA target response after proton irradiation. A chromatin fiber model and new physics constructors with the ELastic Scattering of Electrons and Positrons by neutral Atoms (ELSEPA) model were used to describe the DNA geometry and the physical stage of water radiolysis with the Geant4-DNA toolkit, respectively. Three key parameters (the energy threshold model for strand breaks, the physics model and the maximum distance to distinguish DSB clusters) of scoring DNA damage were studied to investigate the impact on the uncertainties of DNA damage. On the basis of comparison of our results with experimental data and published findings, we were able to accurately predict the yield of various types of DNA damage. Our results indicated that the difference in physics constructor can cause up to 56.4% in the DNA double-strand break (DSB) yields. The DSB yields were quite sensitive to the energy threshold for strand breaks (SB) and the maximum distance to classify the DSB clusters, which were even more than 100 times and four times than the default configurations, respectively.

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.

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.

Analytical formulas representing track-structure simulations on DNA damage induced by protons and light ions at radiotherapy-relevant energies

Track structure based simulations valuably complement experimental research on biological effects of ionizing radiation. They provide information at the highest level of detail on initial DNA damage induced by diverse types of radiation. Simulations with the biophysical Monte Carlo code PARTRAC have been used for testing working hypotheses on radiation action mechanisms, for benchmarking other damage codes and as input for modelling subsequent biological processes. To facilitate such applications and in particular to enable extending the simulations to mixed radiation field conditions, we present analytical formulas that capture PARTRAC simulation results on DNA single- and double-strand breaks and their clusters induced in cells irradiated by ions ranging from hydrogen to neon at energies from 0.5 GeV/u down to their stopping. These functions offer a means by which radiation transport codes at the macroscopic scale could easily be extended to predict biological effects, exploiting a large database of results from micro-/nanoscale simulations, without having to deal with the coupling of spatial scales and running full track-structure calculations.

BIOPHYSICAL SIMULATION TOOL PARTRAC: MODELLING PROTON BEAMS AT THERAPY-RELEVANT ENERGIES

The biophysical simulation tool PARTRAC has been primarily developed to model radiation physics, chemistry and biology on nanometre to micrometre scales. However, the tool can be applied in simulating radiation effects in an event-by-event manner over macroscopic volumes as well. Benchmark simulations are reported showing that PARTRAC does reproduce the macroscopic Bragg peaks of proton beams, although the penetration depths are underestimated by a few per cent for high-energy beams. PARTRAC also quantifies the increase in DNA damage and its complexity along the beam penetration depth. Enhanced biological effectiveness is predicted in particular within distal Bragg peak parts of therapeutic proton beams.

Enhancing low-dose risk assessment using mechanistic mathematical models of radiation effects

Mechanistic mathematical modeling of ionizing radiation (IR) effects has a long history spanning several decades. Models that mathematically represent current knowledge and hypotheses about how radiation damages cells and organs, leading to deleterious outcomes such as carcinogenesis, are particularly useful for estimating radiation risks at doses that are relevant for radiation protection, but are too low to provide a strong 'signal-to-noise ratio' in epidemiological or experimental studies with realistic sample sizes. Here, I discuss examples of models in several relevant areas, including radionuclide biokinetics, non-targeted IR effects, DNA double-strand break (DSB) rejoining and radiation carcinogenesis. I do not provide a detailed review of the vast modeling literature in these fields, but focus on concepts that we have implemented, such as using continuous probability distributions of exponential rates to model radionuclide biokinetics and DSB rejoining, and combining short and long time scales in carcinogenesis models. Improvements in models, including the ability to generate new hypotheses based on model predictions, may come from the introduction of additional novel concepts and from integrating multiple data types.

Modeling the interplay between DNA-PK, Artemis, and ATM in non-homologous end-joining repair in G1 phase of the cell cycle

Modeling a biological process equips us with more comprehensive insight into the process and a more advantageous experimental design. Non-homologous end joining (NHEJ) is a major double-strand break (DSB) repair pathway that occurs throughout the cell cycle. The objective of the current work is to model the fast and slow phases of NHEJ in G1 phase of the cell cycle following exposure to ionizing radiation (IR). The fast phase contains the major components of NHEJ; Ku70/80 complex, DNA-dependent protein kinase catalytic subunit (DNA-PKcs), and XLF/XRCC4/ligase IV complex (XXL). The slow phase in G1 phase of the cell cycle is associated with more complex lesions and involves ATM and Artemis proteins in addition to the major components. Parameters are mainly obtained from experimental data. The model is successful in predicting the kinetics of DSB foci in 13 normal, ATM-deficient, and Artemis-deficient mammalian fibroblast cell lines in G1 phase of the cell cycle after exposure to low doses of IR. The involvement of ATM provides the model with the potency to be connected to different signaling pathways. Ku70/80 concentration and DNA-binding rate as well as XXL concentration and enzymatic activity are introduced as the best targets for affecting NHEJ DSB repair process. On the basis of the current model, decreasing concentration and DNA binding rate of DNA-PKcs is more effective than inhibiting its activity towards the Artemis protein.

Computational analysis of androgen receptor dependent radiosensitivity in prostate cancer

In this study, we quantitatively analyze the mechanism by which androgen deprivation therapy (ADT) is enhancing radiosensitivity in prostate cancer (PCa) patients. It has been shown in laboratory experiments, as well as in patient data in the literature, that the androgen receptor (AR) reduces the effectiveness of ionizing radiation treatment by enhancing the non-homologous end joining (NHEJ) repair of radiation damage. The suppression of AR by ADT suppresses the activity of NHEJ that leads to radiosensitivity in PCa patients. In this paper, we have studied this positive interaction between AR and NHEJ using mathematical models of the NHEJ that we have developed using both the experimental and clinical data for PCa. Our results show that the biological observation of suppression of AR by ADT leading to down-regulation of the first NHEJ protein Ku and NHEJ is a plausible biological mechanism that explains both the experimental and clinical observations in the literature. The presented analysis is the first step in quantitatively analyzing possible treatment scenarios to find the optimal treatment strategies for PCa using the combination treatment with ADT, NHEJ inhibitors, and IR.

Recent progress and open challenges in modeling p53 dynamics in single cells

In mammalian cells, the tumor suppressor p53 is activated upon a variety of cellular stresses and ensures an appropriate response ranging from arrest and repair to the induction of senescence and apoptosis. Quantitative measurements in individual living cells showed stimulus-dependent dynamics of p53 accumulation upon stress induction. Due to the complexity of the underlying biochemical interactions, mathematical models were indispensable for understanding the topology of the network regulating p53 dynamics. Recent work provides furhter insights into the causes of heterogeneous responses in individual cells, the rewiring of the network in response to different inputs and the role of the downstream processes in determining the cellular fate upon stress.

Radiation track, DNA damage and response-a review

The purpose of this paper has been to review the current status and progress of the field of radiation biophysics, and draw attention to the fact that physics, in general, and radiation physics in particular, with the aid of mathematical modeling, can help elucidate biological mechanisms and cancer therapies. We hypothesize that concepts of condensed-matter physics along with the new genomic knowledge and technologies and mechanistic mathematical modeling in conjunction with advances in experimental DNA (Deoxyrinonucleic acid molecule) repair and cell signaling have now provided us with unprecedented opportunities in radiation biophysics to address problems in targeted cancer therapy, and genetic risk estimation in humans. Obviously, one is not dealing with 'low-hanging fruit', but it will be a major scientific achievement if it becomes possible to state, in another decade or so, that we can link mechanistically the stages between the initial radiation-induced DNA damage; in particular, at doses of radiation less than 2 Gy and with structural changes in genomic DNA as a precursor to cell inactivation and/or mutations leading to genetic diseases. The paper presents recent development in the physics of radiation track structure contained in the computer code system KURBUC, in particular for low-energy electrons in the condensed phase of water for which we provide a comprehensive discussion of the dielectric response function approach. The state-of-the-art in the simulation of proton and carbon ion tracks in the Bragg peak region is also presented. The paper presents a critical discussion of the models used for elastic scattering, and the validity of the trajectory approach in low-electron transport. Brief discussions of mechanistic and quantitative aspects of microdosimetry, DNA damage and DNA repair are also included as developed by the authors' work.

Mechanistic Modelling and Bayesian Inference Elucidates the Variable Dynamics of Double-Strand Break Repair

DNA double-strand breaks are lesions that form during metabolism, DNA replication and exposure to mutagens. When a double-strand break occurs one of a number of repair mechanisms is recruited, all of which have differing propensities for mutational events. Despite DNA repair being of crucial importance, the relative contribution of these mechanisms and their regulatory interactions remain to be fully elucidated. Understanding these mutational processes will have a profound impact on our knowledge of genomic instability, with implications across health, disease and evolution. Here we present a new method to model the combined activation of non-homologous end joining, single strand annealing and alternative end joining, following exposure to ionising radiation. We use Bayesian statistics to integrate eight biological data sets of double-strand break repair curves under varying genetic knockouts and confirm that our model is predictive by re-simulating and comparing to additional data. Analysis of the model suggests that there are at least three disjoint modes of repair, which we assign as fast, slow and intermediate. Our results show that when multiple data sets are combined, the rate for intermediate repair is variable amongst genetic knockouts. Further analysis suggests that the ratio between slow and intermediate repair depends on the presence or absence of DNA-PKcs and Ku70, which implies that non-homologous end joining and alternative end joining are not independent. Finally, we consider the proportion of double-strand breaks within each mechanism as a time series and predict activity as a function of repair rate. We outline how our insights can be directly tested using imaging and sequencing techniques and conclude that there is evidence of variable dynamics in alternative repair pathways. Our approach is an important step towards providing a unifying theoretical framework for the dynamics of DNA repair processes.

Insights into the use of gadolinium and gadolinium/boron-based agents in imaging-guided neutron capture therapy applications

Gadolinium neutron capture therapy (Gd-NCT) is currently under development as an alternative approach for cancer therapy. All of the clinical experience to date with NCT is done with (10)B, known as boron neutron capture therapy (BNCT), a binary treatment combining neutron irradiation with the delivery of boron-containing compounds to tumors. Currently, the use of Gd for NCT has been getting more attention because of its highest neutron cross-section. Although Gd-NCT was first proposed many years ago, its development has suffered due to lack of appropriate tumor-selective Gd agents. This review aims to highlight the recent advances for the design, synthesis and biological testing of new Gd- and B-Gd-containing compounds with the task of finding the best systems able to improve the NCT clinical outcome.

Cellular automaton-based model for radiation-induced bystander effects

BACKGROUND

The radiation-induced bystander effect is a biological response observed in non-irradiated cells surrounding an irradiated cell. The bystander effect is known to be induced by two intercellular signaling pathways, the medium-mediated pathway (MDP) and the gap junctional pathway (GJP). To investigate the relative contribution of each signaling pathway, we have developed a mathematical model of the cellular response through these two pathways, with a particular focus on cell-cycle modification.

METHODS

The model is based on a cellular automaton and consists of four components: (1) irradiation, (2) generation and diffusion of intercellular signals, (3) induction of DNA double-strand breaks (DSBs), and (4) cell-cycle modification or cell death. The intercellular signals are generated in and released from irradiated cells. The signals through the MDP and the GJP are modeled independently based on diffusion equations. The irradiation and both signals raise the number of DSBs, which determines transitions of cellular states, such as cell-cycle arrest or cell death.

RESULTS

Our model reproduced fairly well previously reported experimental data on the number of DSBs and cell survival curves. We examined how radiation dose and intercellular signaling dynamically affect the cell cycle. The analysis of model dynamics for the bystander cells revealed that the number of arrested cells did not increase linearly with dose. Arrested cells were more efficiently accumulated by the GJP than by the MDP.

CONCLUSIONS

We present here a mathematical model that integrates various bystander responses, such as MDP and GJP signaling, DSB induction, cell-cycle arrest, and cell death. Because it simulates spatial and temporal conditions of irradiation and cellular characteristics, our model will be a powerful tool to predict dynamical radiobiological responses of a cellular population in which irradiated and non-irradiated cells co-exist.

Modelling proton bunches focussed to submicrometre scales: low-LET radiation damage in high-LET-like spatial structure

Microbeam experiments approximating high-LET tracks by bunches of lower-LET particles focussed to submicrometre scales (Schmid et al. 2012, Phys. Med. Biol. 57, 5889) provide an unprecedented benchmark for models of biological effects of radiation. PARTRAC track structure-based Monte Carlo simulations have verified that focussed 20 MeV proton bunches resemble the radial dose distributions of single 55 MeV carbon ions as used in the experiments. However, the predicted yields of double-strand break and short (<1 kbp) DNA fragments by focussed protons correspond to homogeneous proton irradiation and are much smaller than for carbon tracks. The calculated yields of dicentrics overestimate the effect of focussing but reproduce the fourfold difference between carbon ions and homogeneously distributed protons. The extent to which focussed low-LET particles approximate high-LET radiation is limited by the achievable focussing: submicrometre focussing of proton bunches cannot reproduce local nanometre clustering, i.e. DNA damage complexity characteristic of high-LET radiation.

Chromosome aberration model combining radiation tracks, chromatin structure, DSB repair and chromatin mobility

The module that simulates the kinetics and yields of radiation-induced chromosome aberrations within the biophysical code PARTRAC is described. Radiation track structures simulated by Monte Carlo methods are overlapped with multi-scale models of DNA and chromatin to assess the resulting DNA damage. Spatial mobility of individual DNA ends from double-strand breaks is modelled simultaneously with their processing by the non-homologous end-joining enzymes. To score diverse types of chromosome aberrations, the joined ends are classified regarding their original chromosomal location, orientation and the involvement of centromeres. A comparison with experimental data on dicentrics induced by gamma and alpha particles shows that their relative dose dependence is predicted correctly, although the absolute yields are overestimated. The critical model assumptions on chromatin mobility and on the initial damage recognition and chromatin remodelling steps and their future refinements to solve this issue are discussed.

Nanoscale analysis of clustered DNA damage after high-LET irradiation by quantitative electron microscopy--the heavy burden to repair

Low- and high-linear energy transfer (LET) ionising radiation are effective cancer therapies, but produce structurally different forms of DNA damage. Isolated DNA damage is repaired efficiently; however, clustered lesions may be more difficult to repair, and are considered as significant biological endpoints. We investigated the formation and repair of DNA double-strand breaks (DSBs) and clustered lesions in human fibroblasts after exposure to sparsely (low-LET; delivered by photons) and densely (high-LET; delivered by carbon ions) ionising radiation. DNA repair factors (pKu70, 53BP1, γH2AX, and pXRCC1) were detected using immunogold-labelling and electron microscopy, and spatiotemporal DNA damage patterns were analysed within the nuclear ultrastructure at the nanoscale level. By labelling activated Ku-heterodimers (pKu70) the number of DSBs was determined in electron-lucent euchromatin and electron-dense heterochromatin. Directly after low-LET exposure (5 min post-irradiation), single pKu70 dimers, which reflect isolated DSBs, were randomly distributed throughout the entire nucleus with a linear dose correlation up to 30 Gy. Most euchromatic DSBs were sensed and repaired within 40 min, whereas heterochromatic DSBs were processed with slower kinetics. Essentially all DNA lesions induced by low-LET irradiation were efficiently rejoined within 24h post-irradiation. High-LET irradiation caused localised energy deposition within the particle tracks, and generated highly clustered DNA lesions with multiple DSBs in close proximity. The dimensions of these clustered lesions along the particle trajectories depended on the chromatin packing density, with huge DSB clusters predominantly localised in condensed heterochromatin. High-LET irradiation-induced clearly higher DSB yields than low-LET irradiation, with up to ∼ 500 DSBs per μm(3) track volume, and large fractions of these heterochromatic DSBs remained unrepaired. Hence, the spacing and quantity of DSBs in clustered lesions influence DNA repair efficiency, and may determine the radiobiological outcome.

Genome-based, mechanism-driven computational modeling of risks of ionizing radiation: The next frontier in genetic risk estimation?

Research activity in the field of estimation of genetic risks of ionizing radiation to human populations started in the late 1940s and now appears to be passing through a plateau phase. This paper provides a background to the concepts, findings and methods of risk estimation that guided the field through the period of its growth to the beginning of the 21st century. It draws attention to several key facts: (a) thus far, genetic risk estimates have been made indirectly using mutation data collected in mouse radiation studies; (b) important uncertainties and unsolved problems remain, one notable example being that we still do not know the sensitivity of human female germ cells to radiation-induced mutations; and (c) the concept that dominated the field thus far, namely, that radiation exposures to germ cells can result in single gene diseases in the descendants of those exposed has been replaced by the concept that radiation exposure can cause DNA deletions, often involving more than one gene. Genetic risk estimation now encompasses work devoted to studies on DNA deletions induced in human germ cells, their expected frequencies, and phenotypes and associated clinical consequences in the progeny. We argue that the time is ripe to embark on a human genome-based, mechanism-driven, computational modeling of genetic risks of ionizing radiation, and we present a provisional framework for catalyzing research in the field in the 21st century.

Generalized time-dependent model of radiation-induced chromosomal aberrations in normal and repair-deficient human cells

We have developed a model that can simulate the yield of radiation-induced chromosomal aberrations (CAs) and unrejoined chromosome breaks in normal and repair-deficient cells. The model predicts the kinetics of chromosomal aberration formation after exposure in the G₀/G₁ phase of the cell cycle to either low- or high-LET radiation. A previously formulated model based on a stochastic Monte Carlo approach was updated to consider the time dependence of DNA double-strand break (DSB) repair (proper or improper), and different cell types were assigned different kinetics of DSB repair. The distribution of the DSB free ends was derived from a mechanistic model that takes into account the structure of chromatin and DSB clustering from high-LET radiation. The kinetics of chromosomal aberration formation were derived from experimental data on DSB repair kinetics in normal and repair-deficient cell lines. We assessed different types of chromosomal aberrations with the focus on simple and complex exchanges, and predicted the DSB rejoining kinetics and misrepair probabilities for different cell types. The results identify major cell-dependent factors, such as a greater yield of chromosome misrepair in ataxia telangiectasia (AT) cells and slower rejoining in Nijmegen (NBS) cells relative to the wild-type. The model's predictions suggest that two mechanisms could exist for the inefficiency of DSB repair in AT and NBS cells, one that depends on the overall speed of joining (either proper or improper) of DNA broken ends, and another that depends on geometric factors, such as the Euclidian distance between DNA broken ends, which influences the relative frequency of misrepair.

Ionizing radiation and genetic risks. XVII. Formation mechanisms underlying naturally occurring DNA deletions in the human genome and their potential relevance for bridging the gap between induced DNA double-strand breaks and deletions in irradiated germ cells

While much is known about radiation-induced DNA double-strand breaks (DSBs) and their repair, the question of how deletions of different sizes arise as a result of the processing of DSBs by the cell's repair systems has not been fully answered. In order to bridge this gap between DSBs and deletions, we critically reviewed published data on mechanisms pertaining to: (a) repair of DNA DSBs (from basic studies in this area); (b) formation of naturally occurring structural variation (SV) - especially of deletions - in the human genome (from genomic studies) and (c) radiation-induced mutations and structural chromosomal aberrations in mammalian somatic cells (from radiation mutagenesis and radiation cytogenetic studies). The specific aim was to assess the relative importance of the postulated mechanisms in generating deletions in the human genome and examine whether empirical data on radiation-induced deletions in mouse germ cells are consistent with predictions of these mechanisms. The mechanisms include (a) NHEJ, a DSB repair process that does not require any homology and which functions in all stages of the cell cycle (and is of particular relevance in G0/G1); (b) MMEJ, also a DSB repair process but which requires microhomology and which presumably functions in all cell cycle stages; (c) NAHR, a recombination-based DSB repair mechanism which operates in prophase I of meiosis in germ cells; (d) MMBIR, a microhomology-mediated, replication-based mechanism which operates in the S phase of the cell cycle, and (e) strand slippage during replication (involved in the origin of small insertions and deletions (INDELs). Our analysis permits the inference that, between them, these five mechanisms can explain nearly all naturally occurring deletions of different sizes identified in the human genome, NAHR and MMBIR being potentially more versatile in this regard. With respect to radiation-induced deletions, the basic studies suggest that those arising as a result of the operation of NHEJ/MMEJ processes, as currently formulated, are expected to be relatively small. However, data on induced mutations in mouse spermatogonial stem cells (irradiation in G0/G1 phase of the cell cycle and DSB repair presumed to be via NHEJ predominantly) show that most are associated with deletions of different sizes, some in the megabase range. There is thus a 'discrepancy' between what the basic studies suggest and the empirical observations in mutagenesis studies. This discrepancy, however, is only an apparent but not a real one. It can be resolved by considering the issue of deletions in the broader context of and in conjunction with the organization of chromatin in chromosomes and nuclear architecture, the conceptual framework for which already exists in studies carried out during the past fifteen years or so. In this paper, we specifically hypothesize that repair of DSBs induced in chromatin loops may offer a basis to explain the induction of deletions of different sizes and suggest an approach to test the hypothesis. We emphasize that the bridging of the gap between induced DSB and resulting deletions of different sizes is critical for current efforts in computational modeling of genetic risks.

Integration of Monte Carlo simulations with PFGE experimental data yields constant RBE of 2.3 for DNA double-strand break induction by nitrogen ions between 125 and 225 keV/μm LET

The number of small radiation-induced DNA fragments can be heavily underestimated when determined from measurements of DNA mass fractions by gel electrophoresis, leading to a consequent underestimation of the initial DNA damage induction. In this study we reanalyzed the experimental results for DNA fragmentation and DNA double-strand break (DSB) yields in human fibroblasts irradiated with γ rays and nitrogen ion beams with linear energy transfer (LET) equal to 80, 125, 175 and 225 keV/μm, originally measured by Höglund et al. (Radiat Res 155, 818-825, 2001 and Int J Radiat Biol 76, 539-547, 2000). In that study the authors converted the measured distributions of fragment masses into DNA fragment distributions using mid-range values of the measured fragment length intervals, in particular they assumed fragments with lengths in the interval of 0-48 kbp had the mid-range value of 24 kbp. However, our recent detailed simulations with the Monte Carlo code PARTRAC, while reasonably in agreement with the mass distributions, indicate significantly increased yields of very short fragments by high-LET radiation, so that the actual average fragment lengths, in the interval 0-48 kbp, 2.4 kbp for 225 keV/μm nitrogen ions were much shorter than the assumed mid-range value of 24 kbp. When the measured distributions of fragment masses are converted into fragment distributions using the average fragment lengths calculated by PARTRAC, significantly higher yields of DSB related to short fragments were obtained and resulted in a constant relative biological effectiveness (RBE) for DSB induction yield of 2.3 for nitrogen ions at 125-225 keV/μm LET. The previously reported downward trend of the RBE values over this LET range for DSB induction appears to be an artifact of an inadequate average fragment length in the smallest interval.