Track to the future: historical perspective on the importance of radiation track structure and DNA as a radiobiological target

Development of a simple multiple mutation detection system using seed-coat flavonoid pigments in irradiated Arabidopsis M1 plants

Ionizing radiation induces genetic variations in plants, which makes it useful for plant breeding. A theory that the induced mutations occur randomly in the genome has long been accepted, but is now controversial. Nevertheless, a comparative analysis of the mutations at multiple loci has not been conducted using irradiated M₁ genomes that contain all types of mutations. In this study, we identified Arabidopsis mutants (pab2 and pab3) in a mutagenized population of an anthocyanin-positive seed mutant (ban). Both pab2 and pab3 were revealed to be double mutants (tt4 ban and tt8 ban, respectively) that produced similar anthocyanin-less immature seeds, but differentially colored mature seeds. These features enabled the seed color-based detection of de novo M₁ mutations in TT4 or TT8 following the irradiation of double heterozygous plants (TT4/tt4 TT8/tt8 ban/ban). Most of the irradiated double heterozygous plants produced anthocyanin-positive immature seeds, but 19 plants produced anthocyanin-less immature seeds. Of these 19 mutants, 2 and 17 exhibited tt4- and tt8-type mature seed coloration, respectively. The molecular analysis of the seed coat DNA from randomly selected anthocyanin-less seeds detected mutations at the locus predicted on the basis of the phenotype. Thus, the simple system developed in this study can reliably detect radiation-induced mutations at multiple loci in irradiated Arabidopsis M₁ plants.

A matter of space: how the spatial heterogeneity in energy deposition determines the biological outcome of radiation exposure

The outcome of the exposure of living organisms to ionizing radiation is determined by the distribution of the associated energy deposition at different spatial scales. Radiation proceeds through ionizations and excitations of hit molecules with an ~ nm spacing. Approaches such as nanodosimetry/microdosimetry and Monte Carlo track-structure simulations have been successfully adopted to investigate radiation quality effects: they allow to explore correlations between the spatial clustering of such energy depositions at the scales of DNA or chromosome domains and their biological consequences at the cellular level. Physical features alone, however, are not enough to assess the entity and complexity of radiation-induced DNA damage: this latter is the result of an interplay between radiation track structure and the spatial architecture of chromatin, and further depends on the chromatin dynamic response, affecting the activation and efficiency of the repair machinery. The heterogeneity of radiation energy depositions at the single-cell level affects the trade-off between cell inactivation and induction of viable mutations and hence influences radiation-induced carcinogenesis. In radiation therapy, where the goal is cancer cell inactivation, the delivery of a homogenous dose to the tumour has been the traditional approach in clinical practice. However, evidence is accumulating that introducing heterogeneity with spatially fractionated beams (mini- and microbeam therapy) can lead to significant advantages, particularly in sparing normal tissues. Such findings cannot be explained in merely physical terms, and their interpretation requires considering the scales at play in the underlying biological mechanisms, suggesting a systemic response to radiation.

Chromatin and the Cellular Response to Particle Radiation-Induced Oxidative and Clustered DNA Damage

Exposure to environmental ionizing radiation is prevalent, with greatest lifetime doses typically from high Linear Energy Transfer (high-LET) alpha particles via the radioactive decay of radon gas in indoor air. Particle radiation is highly genotoxic, inducing DNA damage including oxidative base lesions and DNA double strand breaks. Due to the ionization density of high-LET radiation, the consequent damage is highly clustered wherein ≥2 distinct DNA lesions occur within 1–2 helical turns of one another. These multiply-damaged sites are difficult for eukaryotic cells to resolve either quickly or accurately, resulting in the persistence of DNA damage and/or the accumulation of mutations at a greater rate per absorbed dose, relative to lower LET radiation types. The proximity of the same and different types of DNA lesions to one another is challenging for DNA repair processes, with diverse pathways often confounding or interplaying with one another in complex ways. In this context, understanding the state of the higher order chromatin compaction and arrangements is essential, as it influences the density of damage produced by high-LET radiation and regulates the recruitment and activity of DNA repair factors. This review will summarize the latest research exploring the processes by which clustered DNA damage sites are induced, detected, and repaired in the context of chromatin.

Applications of nanodosimetry in particle therapy planning and beyond

This topical review summarizes underlying concepts of nanodosimetry. It describes the development and current status of nanodosimetric detector technology. It also gives an overview of Monte Carlo track structure simulations that can provide nanodosimetric parameters for treatment planning of proton and ion therapy. Classical and modern radiobiological assays that can be used to demonstrate the relationship between the frequency and complexity of DNA lesion clusters and nanodosimetric parameters are reviewed. At the end of the review, existing approaches of treatment planning based on relative biological effectiveness (RBE) models or dose-averaged linear energy transfer are contrasted with an RBE-independent approach based on nandosimetric parameters. Beyond treatment planning, nanodosimetry is also expected to have applications and give new insights into radiation protection dosimetry.

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.

Microdosimetric investigation of the radiation quality of low-medium energy electrons using Geant4-DNA

The increasing clinical use of low-energy photon and electron sources (below few tens of keV) has raised concerns on the adequacy of the existing approximation of an energy-independent radiobiological effectiveness. In this work, the variation of the quality factor (Q) and relative biological effectiveness (RBE) of electrons over the low-medium energy range (0.1 keV-1 MeV) is examined using several microdosimetry-based Monte Carlo methodologies with input data obtained from Geant4-DNA track-structure simulations. The sensitivity of the results to the different methodologies, Geant4-DNA physics models, and target sizes is examined. Calculations of Q and RBE are based on the ICRU Report 40 recommendations, the Kellerer-Hahn approximation, the site version of the theory of dual radiation action (TDRA), the microdosimetric kinetic model (MKM) of cell survival, and the calculated yield of DNA double strand breaks (DSB). The stochastic energy deposition spectra needed as input in the above approaches have been calculated for nanometer spherical volumes using the different electron physics models of Geant4-DNA. Results are normalized at 100 keV electrons which is here considered the reference radiation. It is shown that in the energy range ~50 keV-1 MeV, the calculated Q and RBE are approximately unity (to within 1-2%) irrespective of the methodology, Geant4-DNA physics model, and target size. At lower energies, Q and RBE become energy-dependent reaching a maximum value of ~1.5-2.5 between ~200 and 700 eV. The detailed variation of Q and RBE at low energies depends mostly upon the adopted methodology and target size, and less so upon the Geant4-DNA physics model. Overall, the DSB yield predicts the highest RBE values (with RBE_max≈2.5) whereas the MKM the lowest RBE values (with RBE_max≈1.5). The ICRU Report 40, Kellerer-Hahn, and TDRA methods are in excellent agreement (to within 1-2%) over the whole energy range predicting a Q_max≈2. In conclusion, the approximation Q=RBE=1 was found to be valid only above ~50 keV whereas at lower energies both Q and RBE become strongly energy-dependent. It is envisioned that the present work will contribute towards establishing robust methodologies to determine theoretically the energy-dependence of radiation quality of individual electrons which may then be used in subsequent calculations involving practical electron and photon radiation sources.

Repurposing Drugs for Cancer Radiotherapy: Early Successes and Emerging Opportunities

It has long been recognized that combining radiotherapy with cytotoxic drugs such as cisplatin can improve efficacy. However, while concurrent chemoradiotherapy improves patient outcomes, it comes at costs of increased toxicity. A tremendous opportunity remains to investigate drug combinations in the clinical setting that might increase the benefits of radiation without additional toxicity. This chapter highlights opportunities to apply repurposing of drugs along with a mechanistic understanding of radiation effects on cancer and normal tissue to discover new therapy-modifying drugs and help rapidly translate them to the clinic. We survey candidate radiosensitizers that alter DNA repair, decrease hypoxia, block tumor survival signaling, modify tumor metabolism, block growth factor signaling, slow tumor invasiveness, impair angiogenesis, or stimulate antitumor immunity. Promising agents include widely used drugs such as aspirin, metformin, and statins, offering the potential to improve outcomes, decrease radiation doses, and lower costs. Many other candidate drugs are also discussed.

Internal microdosimetry of alpha-emitting radionuclides

At the tissue level, energy deposition in cells is determined by the microdistribution of alpha-emitting radionuclides in relation to sensitive target cells. Furthermore, the highly localized energy deposition of alpha particle tracks and the limited range of alpha particles in tissue produce a highly inhomogeneous energy deposition in traversed cell nuclei. Thus, energy deposition in cell nuclei in a given tissue is characterized by the probability of alpha particle hits and, in the case of a hit, by the energy deposited there. In classical microdosimetry, the randomness of energy deposition in cellular sites is described by a stochastic quantity, the specific energy, which approximates the macroscopic dose for a sufficiently large number of energy deposition events. Typical examples of the alpha-emitting radionuclides in internal microdosimetry are radon progeny and plutonium in the lungs, plutonium and americium in bones, and radium in targeted radionuclide therapy. Several microdosimetric approaches have been proposed to relate specific energy distributions to radiobiological effects, such as hit-related concepts, LET and track length-based models, effect-specific interpretations of specific energy distributions, such as the dual radiation action theory or the hit-size effectiveness function, and finally track structure models. Since microdosimetry characterizes only the initial step of energy deposition, microdosimetric concepts are most successful in exposure situations where biological effects are dominated by energy deposition, but not by subsequently operating biological mechanisms. Indeed, the simulation of the combined action of physical and biological factors may eventually require the application of track structure models at the nanometer scale.

Ionizing Radiation and Complex DNA Damage: From Prediction to Detection Challenges and Biological Significance

Biological responses to ionizing radiation (IR) have been studied for many years, generally showing the dependence of these responses on the quality of radiation, i.e., the radiation particle type and energy, types of DNA damage, dose and dose rate, type of cells, etc. There is accumulating evidence on the pivotal role of complex (clustered) DNA damage towards the determination of the final biological or even clinical outcome after exposure to IR. In this review, we provide literature evidence about the significant role of damage clustering and advancements that have been made through the years in its detection and prediction using Monte Carlo (MC) simulations. We conclude that in the future, emphasis should be given to a better understanding of the mechanistic links between the induction of complex DNA damage, its processing, and systemic effects at the organism level, like genomic instability and immune responses.

Cullin Ring Ubiquitin Ligases (CRLs) in Cancer: Responses to Ionizing Radiation (IR) Treatment

Treatment with ionizing radiation (IR) remains the cornerstone of therapy for multiple cancer types, including disseminated and aggressive diseases in the palliative setting. Radiotherapy efficacy could be improved in combination with drugs that regulate the ubiquitin-proteasome system (UPS), many of which are currently being tested in clinical trials. The UPS operates through the covalent attachment of ATP-activated ubiquitin molecules onto substrates following the transfer of ubiquitin from an E1, to an E2, and then to the substrate via an E3 enzyme. The specificity of ubiquitin ligation is dictated by E3 ligases, which select substrates to be ubiquitylated. Among the E3s, cullin ring ubiquitin ligases (CRLs) represent prototypical multi-subunit E3s, which use the cullin subunit as a central assembling scaffold. CRLs have crucial roles in controlling the cell cycle, hypoxia signaling, reactive oxygen species clearance and DNA repair; pivotal factors regulating the cancer and normal tissue response to IR. Here, we summarize the findings on the involvement of CRLs in the response of cancer cells to IR, and we discuss the therapeutic approaches to target the CRLs which could be exploited in the clinic.

Predicting DNA damage foci and their experimental readout with 2D microscopy: a unified approach applied to photon and neutron exposures

The consideration of how a given technique affects results of experimental measurements is a must to achieve correct data interpretation. This might be challenging when it comes to measurements on biological systems, where it is unrealistic to have full control (e.g. through a software replica) of all steps in the measurement chain. In this work we address how the effectiveness of different radiation qualities in inducing biological damage can be assessed measuring DNA damage foci yields, only provided that artefacts related to the scoring technique are adequately considered. To this aim, we developed a unified stochastic modelling approach that, starting from radiation tracks, predicts both the induction, spatial distribution and complexity of DNA damage, and the experimental readout of foci when immunocytochemistry coupled to 2D fluorescence microscopy is used. The approach is used to interpret γ-H2AX data for photon and neutron exposures. When foci are reconstructed in the whole cell nucleus, we obtain information on damage characteristics "behind" experimental observations, as the average damage content of a focus. We reproduce how the detection technique affects experimental findings, e.g. contributing to the saturation of foci yields scored at 30 minutes after exposure with increasing dose and to the lack of dose dependence for yields at 24 hours.

Clustered DNA Damages induced by 0.5 to 30 eV Electrons

Low-energy electrons (LEEs) of energies ≤30 eV are generated in large quantities by ionizing radiation. These electrons can damage DNA; particularly, they can induce the more detrimental clustered lesions in cells. This type of lesions, which are responsible for a large portion of the genotoxic stress generated by ionizing radiation, is described in the Introduction. The reactions initiated by the collisions of 0.5-30 eV electrons with oligonucleotides, duplex DNA, and DNA bound to chemotherapeutic platinum drugs are explained and reviewed in the subsequent sections. The experimental methods of LEE irradiation and DNA damage analysis are described with an emphasis on the detection of cluster lesions, which are considerably enhanced in DNA-Pt-drug complexes. Based on the energy dependence of damage yields and cross-sections, a mechanism responsible for the clustered lesions can be attributed to the capture of a single electron by the electron affinity of an excited state of a base, leading to the formation of transient anions at 6 and 10 eV. The initial capture is followed by electronic excitation of the base and dissociative attachment-at other DNA sites-of the electron reemitted from the temporary base anion. The mechanism is expected to be universal in the cellular environment and plays an important role in the formation of clustered lesions.