First in vitro measurement of VHEE relative biological effectiveness (RBE) in lung and prostate cancer cells using the ARES linac at DESY.

Very high energy electrons (VHEE) are a potential candidate for radiotherapy applications. This includes tumours in inhomogeneous regions such as lung and prostate cancers, due to the insensitivity of VHEE to inhomogeneities. This study explores how electrons in the VHEE range can be used to perform successful in vitro radiobiological studies. The ARES (accelerator research experiment at SINBAD) facility at DESY, Hamburg, Germany was used to deliver 154 MeV electrons to both prostate (PC3) and lung (A549) cancer cells in suspension. Dose was delivered to samples with repeatability and uniformity, quantified with Gafchromic film. Cell survival in response to VHEE was measured using the clonogenic assay to determine the biological effectiveness of VHEE in cancer cells for the first time using this method. Equivalent experiments were performed using 300 kVp X-rays, to enable VHEE irradiated cells to be compared with conventional photons. VHEE irradiated cancer cell survival was fitted to the linear quadratic (LQ) model (R2 = 0.96-0.97). The damage from VHEE and X-ray irradiated cells at doses between 1.41 and 6.33 Gy are comparable, suggesting similar relative biological effectiveness (RBE) between the two modalities. This suggests VHEE is as damaging as photon radiotherapy and therefore could be used to successfully damage cancer cells during radiotherapy. The RBE of VHEE was quantified as the relative doses required for 50% (D0.5) and 10% (D0.1) cell survival. Using these values, VHEE RBE was measured as 0.93 (D0.5) and 0.99 (D0.1) for A549 and 0.74 (D0.5) and 0.93 (D0.1) for PC3 cell lines respectively. For the first time, this study has shown that 154 MeV electrons can be used to effectively kill lung and prostate cancer cells, suggesting that VHEE would be a viable radiotherapy modality. Several studies have shown that VHEE has characteristics that would offer significant improvements over conventional photon radiotherapy for example, electrons are relatively easy to steer and can be used to deliver dose rapidly and with high efficiency. Studies have shown improved dose distribution with VHEE in treatment plans, in comparison to VMAT, indicating that VHEE can offer improved and safer treatment plans with reduced side effects. The biological response of cancer cells to VHEE has not been sufficiently studied as of yet, however this initial study provides some initial insights into cell damage. VHEE offers significant benefits over photon radiotherapy and therefore more studies are required to fully understand the biological effectiveness of VHEE.

Effects of Differing Underlying Assumptions in In Silico Models on Predictions of DNA Damage and Repair.

The induction and repair of DNA double-strand breaks (DSBs) are critical factors in the treatment of cancer by radiotherapy. To investigate the relationship between incident radiation and cell death through DSB induction many in silico models have been developed. These models produce and use custom formats of data, specific to the investigative aims of the researchers, and often focus on particular pairings of damage and repair models. In this work we use a standard format for reporting DNA damage to evaluate combinations of different, independently developed, models. We demonstrate the capacity of such inter-comparison to determine the sensitivity of models to both known and implicit assumptions. Specifically, we report on the impact of differences in assumptions regarding patterns of DNA damage induction on predicted initial DSB yield, and the subsequent effects this has on derived DNA repair models. The observed differences highlight the importance of considering initial DNA damage on the scale of nanometres rather than micrometres. We show that the differences in DNA damage models result in subsequent repair models assuming significantly different rates of random DSB end diffusion to compensate. This in turn leads to disagreement on the mechanisms responsible for different biological endpoints, particularly when different damage and repair models are combined, demonstrating the importance of inter-model comparisons to explore underlying model assumptions.

Quantification of damage to plasmid DNA from 35 MeV electrons, 228 MeV protons and 300 kVp X-rays in varying hydroxyl radical scavenging environments.

The pBR322 plasmid DNA was irradiated with 35 MeV electrons, 228 MeV protons and 300 kVp X-rays to quantify DNA damage and make comparisons of DNA damage between radiation modalities. Plasmid was irradiated in a medium containing hydroxyl radical scavengers in varying concentrations. This altered the amount of indirect hydroxyl-mediated DNA damage, to create an environment that is more closely associated with a biological cell. We show that increasing hydroxyl scavenger concentration significantly reduced post-irradiation DNA damage to pBR322 plasmid DNA consistently and equally with three radiation modalities. At low scavenging capacities, irradiation with both 35 MeV electrons and 228 MeV protons resulted in increased DNA damage per dose compared with 300 kVp X-rays. We quantify both single-strand break (SSB) and double-strand break (DSB) induction between the modalities as a ratio of yields relative to X-rays, referred to as relative biological effectiveness (RBE). RBESSB values of 1.16 ± 0.15 and 1.18 ± 0.08 were calculated for protons and electrons, respectively, in a low hydroxyl scavenging environment containing 1 mM Tris-HCl for SSB induction. In higher hydroxyl scavenging capacity environments (above 1.1 × 106 s-1), no significant differences in DNA damage induction were found between radiation modalities when using SSB induction as a measure of RBE. Considering DSB induction, significant differences were only found between X-rays and 35 MeV electrons, with an RBEDSB of 1.72 ± 0.91 for 35 MeV electrons, indicating that electrons result in significantly more SSBs and DSBs per unit of dose than 300 kVp X-rays.

Proposing a Clinical Model for RBE Based on Proton Track-End Counts.

PURPOSE: In proton therapy, the clinical application of linear energy transfer (LET) optimization remains contentious, in part because of challenges associated with the definition and calculation of LET and its exact relationship with relative biological effectiveness (RBE) because of large variation in experimental in vitro data. This has raised interest in other metrics with favorable properties for biological optimization, such as the number of proton track ends in a voxel. In this work, we propose a novel model for clinical calculations of RBE, based on proton track end counts. METHODS AND MATERIALS: We developed an effective dose concept to translate between the total proton track-end count per unit mass in a voxel and a proton RBE value. Dose, track end, and dose-averaged LET (LETd) distributions were simulated using Monte Carlo models for a series of water phantoms, in vitro radiobiological studies, and patient treatment plans. We evaluated the correlation between track ends and regions of elevated biological effectiveness in comparison to LETd-based models of RBE. RESULTS: Track ends were found to correlate with biological effects in in vitro experiments with an accuracy comparable to LETd. In patient simulations, our track end model identified the same biological hotspots as predicted by LETd-based radiobiological models of proton RBE. CONCLUSIONS: These results suggest that, for clinical optimization and evaluation, an RBE model based on proton track end counts may match LETd-based models in terms of information provided while also offering superior statistical properties.

A computational approach to quantifying miscounting of radiation-induced double-strand break immunofluorescent foci.

Immunofluorescent tagging of DNA double-strand break (DSB) markers, such as γ-H2AX and other DSB repair proteins, are powerful tools in understanding biological consequences following irradiation. However, whilst the technique is widespread, there are many uncertainties related to its ability to resolve and reliably deduce the number of foci when counting using microscopy. We present a new tool for simulating radiation-induced foci in order to evaluate microscope performance within in silico immunofluorescent images. Simulations of the DSB distributions were generated using Monte Carlo track-structure simulation. For each DSB distribution, a corresponding DNA repair process was modelled and the un-repaired DSBs were recorded at several time points. Corresponding microscopy images for both a DSB and (γ-H2AX) fluorescent marker were generated and compared for different microscopes, radiation types and doses. Statistically significant differences in miscounting were found across most of the tested scenarios. These inconsistencies were propagated through to repair kinetics where there was a perceived change between radiation-types. These changes did not reflect the underlying repair rate and were caused by inconsistencies in foci counting. We conclude that these underlying uncertainties must be considered when analysing images of DNA damage markers to ensure differences observed are real and are not caused by non-systematic miscounting.

The suitability of micronuclei as markers of relative biological effect.

Micronucleus (MN) formation is routinely used as a biodosimeter for radiation exposures and has historically been used as a measure of DNA damage in cells. Strongly correlating with dose, MN are also suggested to indicate radiation quality, differentiating between particle and photon irradiation. The "gold standard" for measuring MN formation is Fenech's cytokinesis-block micronucleus (CBMN) cytome assay, which uses the cytokinesis blocking agent cytochalasin-B. Here, we present a comprehensive analysis of the literature investigating MN induction trends in vitro, collating 193 publications, with 2476 data points. Data were collected from original studies that used the CBMN assay to quantify MN in response to ionizing radiation in vitro. Overall, the meta-analysis showed that individual studies mostly have a linear increase of MN with dose [85% of MN per cell (MNPC) datasets and 89% of percentage containing MN (PCMN) datasets had an R2 greater than 0.90]. However, there is high variation between studies, resulting in a low R2 when data are combined (0.47 for MNPC datasets and 0.60 for PCMN datasets). Particle type, species, cell type, and cytochalasin-B concentration were suggested to influence MN frequency. However, variation in the data meant that the effects could not be strongly correlated with the experimental parameters investigated. There is less variation between studies when comparing the PCMN rather than the number of MNPC. Deviation from CBMN protocol specified timings did not have a large effect on MN induction. However, further analysis showed less variation between studies following Fenech's protocol closely, which provided more reliable results. By limiting the cell type and species as well as only selecting studies following the Fenech protocol, R2 was increased to 0.64 for both measures. We therefore determine that due to variation between studies, MN are currently a poor predictor of radiation-induced DNA damage and make recommendations for futures studies assessing MN to improve consistency between datasets.

Estimating the percentage of patients who might benefit from proton beam therapy instead of X-ray radiotherapy.

OBJECTIVES: High-energy Proton Beam Therapy (PBT) commenced in England in 2018 and NHS England commissions PBT for 1.5% of patients receiving radical radiotherapy. We sought expert opinion on the level of provision. METHODS: Invitations were sent to 41 colleagues working in PBT, most at one UK centre, to contribute by completing a spreadsheet. 39 responded: 23 (59%) completed the spreadsheet; 16 (41%) declined, arguing that clinical outcome data are lacking, but joined six additional site-specialist oncologists for two consensus meetings. The spreadsheet was pre-populated with incidence data from Cancer Research UK and radiotherapy use data from the National Cancer Registration and Analysis Service. 'Mechanisms of Benefit' of reduced growth impairment, reduced toxicity, dose escalation and reduced second cancer risk were examined. RESULTS: The most reliable figure for percentage of radical radiotherapy patients likely to benefit from PBT was that agreed by 95% of the 23 respondents at 4.3%, slightly larger than current provision. The median was 15% (range 4-92%) and consensus median 13%. The biggest estimated potential benefit was from reducing toxicity, median benefit to 15% (range 4-92%), followed by dose escalation median 3% (range 0 to 47%); consensus values were 12 and 3%. Reduced growth impairment and reduced second cancer risk were calculated to benefit 0.5% and 0.1%. CONCLUSIONS: The most secure estimate of percentage benefit was 4.3% but insufficient clinical outcome data exist for confident estimates. The study supports the NHS approach of using the evidence base and developing it through randomised trials, non-randomised studies and outcomes tracking. ADVANCES IN KNOWLEDGE: Less is known about the percentage of patients who may benefit from PBT than is generally acknowledged. Expert opinion varies widely. Insufficient clinical outcome data exist to provide robust estimates. Considerable further work is needed to address this, including international collaboration; much is already underway but will take time to provide mature data.

Hi-C implementation of genome structure for in silico models of radiation-induced DNA damage.

Developments in the genome organisation field has resulted in the recent methodology to infer spatial conformations of the genome directly from experimentally measured genome contacts (Hi-C data). This provides a detailed description of both intra- and inter-chromosomal arrangements. Chromosomal intermingling is an important driver for radiation-induced DNA mis-repair. Which is a key biological endpoint of relevance to the fields of cancer therapy (radiotherapy), public health (biodosimetry) and space travel. For the first time, we leverage these methods of inferring genome organisation and couple them to nano-dosimetric radiation track structure modelling to predict quantities and distribution of DNA damage within cell-type specific geometries. These nano-dosimetric simulations are highly dependent on geometry and are benefited from the inclusion of experimentally driven chromosome conformations. We show how the changes in Hi-C contract maps impact the inferred geometries resulting in significant differences in chromosomal intermingling. We demonstrate how these differences propagate through to significant changes in the distribution of DNA damage throughout the cell nucleus, suggesting implications for DNA repair fidelity and subsequent cell fate. We suggest that differences in the geometric clustering for the chromosomes between the cell-types are a plausible factor leading to changes in cellular radiosensitivity. Furthermore, we investigate changes in cell shape, such as flattening, and show that this greatly impacts the distribution of DNA damage. This should be considered when comparing in vitro results to in vivo systems. The effect may be especially important when attempting to translate radiosensitivity measurements at the experimental in vitro level to the patient or human level.

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.

A parameter sensitivity study for simulating DNA damage after proton irradiation using TOPAS-nBio.

Monte Carlo (MC) track structure simulation tools are commonly used for predicting radiation induced DNA damage by modeling the physical and chemical reactions at the nanometer scale. However, the outcome of these MC simulations is particularly sensitive to the adopted parameters which vary significantly across studies. In this study, a previously developed full model of nuclear DNA was used to describe the DNA geometry. The TOPAS-nBio MC toolkit was used to investigate the impact of physics and chemistry models as well as three key parameters (the energy threshold for direct damage, the chemical stage time length, and the probability of damage between hydroxyl radical reactions with DNA) on the induction of DNA damage. Our results show that the difference in physics and chemistry models alone can cause differences up to 34% and 16% in the DNA double strand break (DSB) yield, respectively. Additionally, changing the direct damage threshold, chemical stage length, and hydroxyl damage probability can cause differences of up to 28%, 51%, and 71% in predicted DSB yields, respectively, for the configurations in this study.

Insights into the non-homologous end joining pathway and double strand break end mobility provided by mechanistic in silico modelling.

After radiation exposure, one of the critical processes for cellular survival is the repair of DNA double strand breaks. The pathways involved in this response are complex in nature and involve many individual steps that act across different time scales, all of which combine to produce an overall behaviour. It is therefore experimentally challenging to unambiguously determine the mechanisms involved and how they interact whilst maintaining strict control of all confounding variables. In silico methods can provide further insight into results produced by focused experimental investigations through testing of the hypotheses generated. Such computational testing can asses competing hypotheses by investigating their effects across all time scales concurrently, highlighting areas where further experimental work can have the most significance. We describe the construction of a mechanistic model by combination of several hypothesised mechanisms reported in the literature and supported by experiment. Compatibility of these mechanisms was tested by fitting simulation to results reported in the literature. To avoid over-fitting, we used an approach of sequentially testing individual mechanisms within this pathway. We demonstrate that using this approach the model is capable of reproducing published protein kinetics and overall repair trends. This provides evidence supporting the feasibility of the proposed mechanisms and revealed how they interact to produce an overall behaviour. Furthermore, we show that the assumed motion of individual double strand break ends plays a crucial role in determining overall system behaviour.

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.

Modelling direct DNA damage for gold nanoparticle enhanced proton therapy.

Gold nanoparticles have been proven as potential radiosensitizer when combined with protons. Initially the radiosensitization effect was attributed to the physical interactions of radiation with the gold and the production of secondary electrons that induce DNA damage. However, emerging data challenge this hypothesis, supporting the existence of alternative or supplementary radiosensitization mechanisms. In this work we incorporate a realistic cell model with detailed DNA geometry and a realistic gold nanoparticle biodistribution based on experimental data. The DNA single and double strand breaks, and damage complexity are counted under various scenarios of different gold nanoparticle size, biodistribution and concentration, and proton energy. The locality of the effect, i.e. the existence of higher damage at a location close to the gold distribution, is also addressed by investigating the DNA damage at a chromosomal territory. In all the cases we do not observe any significant increase in the single/double strand break yield or damage complexity in the presence of gold nanoparticles under proton irradiation; nor there is a locality to the effect. Our results show for the first time that the physical interactions of protons with the gold nanoparticles should not be considered directly responsible for the observed radiosensitization effect. The model used only accounts for DNA damage from direct interactions, whilst considering the indirect effect, and it is possible the radiosensitization effect to be due to other physical effects, although we consider that possibility unlikely. Our conclusion suggests that other mechanisms might have greater contribution to the radiosensitization effect and further investigation should be conducted.