A Computational Model of Cellular Response to Modulated Radiation Fields

Intercellular pathways of cancer treatment-related cardiotoxicity and their therapeutic implications: the paradigm of radiotherapy

Advances in cancer therapeutics have improved patient survival rates. However, cancer survivors may suffer from adverse events either at the time of therapy or later in life. Cardiovascular diseases (CVD) represent a clinically important, but mechanistically understudied complication, which interfere with the continuation of best-possible care, induce life-threatening risks, and/or lead to long-term morbidity. These concerns are exacerbated by the fact that targeted therapies and immunotherapies are frequently combined with radiotherapy, which induces durable inflammatory and immunogenic responses, thereby providing a fertile ground for the development of CVDs. Stressed and dying irradiated cells produce 'danger' signals including, but not limited to, major histocompatibility complexes, cell-adhesion molecules, proinflammatory cytokines, and damage-associated molecular patterns. These factors activate intercellular signaling pathways which have potentially detrimental effects on the heart tissue homeostasis. Herein, we present the clinical crosstalk between cancer and heart diseases, describe how it is potentiated by cancer therapies, and highlight the multifactorial nature of the underlying mechanisms. We particularly focus on radiotherapy, as a case known to often induce cardiovascular complications even decades after treatment. We provide evidence that the secretome of irradiated tumors entails factors that exert systemic, remote effects on the cardiac tissue, potentially predisposing it to CVDs. We suggest how diverse disciplines can utilize pertinent state-of-the-art methods in feasible experimental workflows, to shed light on the molecular mechanisms of radiotherapy-related cardiotoxicity at the organismal level and untangle the desirable immunogenic properties of cancer therapies from their detrimental effects on heart tissue. Results of such highly collaborative efforts hold promise to be translated to next-generation regimens that maximize tumor control, minimize cardiovascular complications, and support quality of life in cancer survivors.

Bystander Effects in Spatially Fractionated Radiation Therapy: From Molecule To Organism To Clinical Implications

The standard of care for radiation therapy is numerous, low-dose fractions that are distributed homogeneously throughout the tumor. An alternative strategy under scrutiny is to apply spatially fractionated radiotherapy (high and low doses throughout the tumor) in one or several fractions, either alone or followed by conventional radiation fractionation . Spatial fractionation allows for significant sparing of normal tissue, and the regions of tumor or normal tissue that received sublethal doses can give rise to beneficial bystander effects in both cases. Bystander effects are broadly defined as biological responses that are significantly greater than would be anticipated based on the radiation dose received. Typically these effects are initiated by diffusion of reactive oxygen species and secretion of various cytokines. As demonstrated in the literature, spatial fractionation related bystander effects can occur locally from cell to cell and in what are known as "cohort effects," which tend to take the form of restructuring of the vasculature, enhanced immune infiltration, and development of immunological memory. Other bystander effects can take place at distant sites in what are known as "abscopal effects." While these events are rare, they are mediated by the immune system and can result in the eradication of secondary and metastatic disease. Currently, due to the complexity and variability of these bystander effects, they are not thoroughly understood, but as knowledge improves they may present significant opportunities for improved clinical outcomes.

Novel unconventional radiotherapy techniques: Current status and future perspectives - Report from the 2nd international radiation oncology online seminar

•Improvement of therapeutic ratio by novel unconventional radiotherapy approaches.•Immunomodulation using high-dose spatially fractionated radiotherapy.•Boosting radiation anti-tumor effects by adding an immune-mediated cell killing.

Biophysical Modeling of the Ionizing Radiation Influence on Cells Using the Stochastic (Monte Carlo) and Deterministic (Analytical) Approaches

This review article describes our simplified biophysical model for the response of a group of cells to ionizing radiation. The model, which is a product of 10 years of studies, acts as (a) a comprehensive stochastic approach based on the Monte Carlo simulation with a probability tree and (b) the thereof derived detailed deterministic models describing the selected biophysical and radiobiological phenomena in an analytical manner. Specifically, the presented model describes effects such as the risk of neoplastic transformation of cells relative to the absorbed radiation dose, the dynamics of tumor development, the priming dose effect (also called the Raper–Yonezawa effect) based on the introduced adaptive response approach, and the bystander effect. The model is also modifiable depending on users’ potential needs.

No Intercellular Regulation of the Cell Cycle among Human Cervical Carcinoma HeLa Cells Expressing Fluorescent Ubiquitination-Based Cell-Cycle Indicators in Modulated Radiation Fields

The non-targeted effects of radiation have been known to induce significant alternations in cell survival. Although the effects might govern the progression of tumor sites following advanced radiotherapy, the impacts on the intercellular control of the cell cycle following radiation exposure with a modified field, remain to be determined. Recently, a fluorescent ubiquitination-based cell-cycle indicator (FUCCI), which can visualize the cell-cycle phases with fluorescence microscopy in real time, was developed for biological cell research. In this study, we investigated the non-targeted effects on the regulation of the cell cycle of human cervical carcinoma (HeLa) cells with imperfect p53 function that express the FUCCI (HeLa–FUCCI cells). The possible effects on the cell-cycle phases via soluble factors were analyzed following exposure to different field configurations, which were delivered using a 150 kVp X-ray irradiator. In addition, using synchrotron-generated, 5.35 keV monochromatic X-ray microbeams, high-precision 200 μm-slit microbeam irradiation was performed to investigate the possible impacts on the cell-cycle phases via cell–cell contacts. Collectively, we could not detect the intercellular regulation of the cell cycle in HeLa–FUCCI cells, which suggested that the unregulated cell growth was a malignant tumor. Our findings indicated that there was no significant intercellular control system of the cell cycle in malignant tumors during or after radiotherapy, highlighting the differences between normal tissue and tumor characteristics.

Investigating spatial fractionation and radiation induced bystander effects: a mathematical modelling approach

Radiation induced bystander effects (RIBEs) have been shown to cause death in cells receiving little or no physical dose. In standard radiotherapy, where uniform fields are delivered and all cells are directly exposed to radiation, this phenomenon can be neglected. However, the role of RIBEs may become more influential when heterogeneous fields are considered. Mathematical modelling can be used to determine how these heterogeneous fields might influence cell survival, but most established techniques account only for the direct effects of radiation. To gain a full appreciation of how non-uniform fields impact cell survival, it is also necessary to consider the indirect effects of radiation. In this work, we utilise a mathematical model that accounts for both the direct effects of radiation on cells and RIBEs. This model is used to investigate how spatially fractionated radiotherapy plans impact cell survivalin vitro. These predictions were compared to survival in normal and cancerous cells following exposure to spatially fractionated plans using a clinical linac. The model is also used to explore how spatially fractionated radiotherapy will impact tumour controlin vivo. Results suggest that spatially fractionated plans are associated with higher equivalent uniform doses than conventional uniform plans at clinically relevant doses. The model predicted only small changes changes in normal tissue complication probability, compared to the larger protection seen clinically. This contradicts a central paradigm of radiotherapy where uniform fields are assumed to maximise cell kill and may be important for future radiotherapy optimisation.

REVIEW OF QUANTITATIVE MECHANISTIC MODELS OF RADIATION-INDUCED NON-TARGETED EFFECTS (NTE)

Quantitative mechanistic modeling of the biological effects of ionizing radiation has a long rich history. Initially, it was dominated by target theory, which quantifies damage caused by traversal of cellular targets like DNA by ionizing tracks. The discovery that mutagenesis, death and/or altered behavior sometimes occur in cells that were not themselves traversed by any radiation tracks but merely interacted with traversed cells was initially seen as surprising. As more evidence of such 'non-targeted' or 'bystander' effects accumulated, the importance of their contribution to radiation-induced damage became more recognized. Understanding and modeling these processes is important for quantifying and predicting radiation-induced health risks. Here we review the variety of mechanistic mathematical models of nontargeted effects that emerged over the past 2-3 decades. This review is not intended to be exhaustive, but focuses on the main assumptions and approaches shared or distinct between models, and on identifying areas for future research.

Measuring radioenhancement by gold nanofilms: Comparison with analytical calculations

PURPOSE

To measure radioenhancement by gold nanoparticles (GNPs) using gold nanofilms (GNFs).

METHODS

GNFs of 20-100 nm thicknesses were prepared. The GNF attached to radiochromic film (RCF) was irradiated using 50, 220 kVp, and 6 MV X-rays. The radiation doses to the active layer of RCF with and without GNF were measured using an optical flatbed scanner and Raman spectrometer to estimate the dose enhancement factor (DEF). For verification, analytical calculations of DEF within the thickness of active layer and the ranges of secondary electrons were carried out.

RESULTS

The DEFs for GNFs of 20 to 100 nm thicknesses measured by an optical scanner ranged from 2.1 to 6.1 at 50 kVp and 1.6 to 4.9 at 220 kVp. Similarly, the DEFs measured by Raman spectroscopy ranged from 2.6 to 4.6 at 50 kVp and 2.2 to 4.8 at 220 kVp. The calculated DEFs ranged from 1.5 to 3.6 at 50 kVp and from 1.7 to 4.7 at 220 kVp. Almost no dose enhancement was observed in 6 MV X-ray. The analytical DEFs seemed to be underestimated by averaging local enhancement over the entire active layer. However, analytical DEFs within the ranges of secondary electrons was much higher than the measured macroscopic DEFs.

CONCLUSIONS

The experimental and analytical approaches developed in this study could quantitatively estimate radioenhancement by GNPs. Due to a short range of low-energy electrons emitted from gold, the microscopic radioenhancement within the ranges of low-energy electrons would be particularly important in a cell.

Analysis of the high-dose-range radioresistance of prostate cancer cells, including cancer stem cells, based on a stochastic model

In radiotherapy, cancer stem cells (CSCs) are well recognized as one of the radioresistant cell types. Even in a small subpopulation, CSCs may have an influence on tumor control probability, represented by cell killing after irradiation. However, the relationship between the percentage content of CSCs and the cell survival dose-response curve has not yet been quantitatively clarified. In this study, we developed a cell-killing model for two cell populations (CSCs and progeny cells) to predict the surviving fractions, and compared it with the conventional linear-quadratic (LQ) model. Three prostate cancer cell lines (DU145, PC3 and LNCaP) were exposed to X-rays at doses ranging from 0 to 10 Gy. After the irradiation, we performed clonogenic survival assays to generate the cell survival curves, and carried out flow-cytometric analyses to estimate the percentage content of CSCs for each cell line. The cell survival curves for DU145 cells and PC3 cells seemed not to follow the conventional LQ model in the high dose range (>8 Gy). However, the outputs of the developed model agreed better with the experimental cell survival curves than those of the LQ model. The percentage content of CSCs predicted by the developed model was almost coincident with the measured percentage content for both DU145 cells and PC3 cells. The experiments and model analyses indicate that a small subpopulation of radioresistant CSCs has lower radiosensitivity in the high-dose range, which may lessen the clinical outcome for patients with prostate cancer after high-dose radiation therapy.

Preclinical Evaluation of Dose-Volume Effects and Lung Toxicity Occurring In and Out-of-Field

PURPOSE

The aim of this study was to define the dose and dose-volume relationship of radiation-induced pulmonary toxicities occurring in and out-of-field in mouse models of early inflammatory and late fibrotic response.

MATERIALS AND METHODS

Early radiation-induced inflammation and fibrosis were investigated in C3H/NeJ and C57BL/6J mice, respectively. Animals were irradiated with 20 Gy delivered to the upper region of the right lung as a single fraction or as 3 consecutive fractions using the Small Animal Radiation Research Platform (Xstrahl Inc, Camberley, UK). Cone beam computed tomography was performed for image guidance before irradiation and to monitor late toxicity. Histologic sections were examined for neutrophil and macrophage infiltration as markers of early inflammatory response and type I collagen staining as a marker of late-occurring fibrosis. Correlation was evaluated with the dose-volume histogram parameters calculated for individual mice and changes in the observed cone beam computed tomography values.

RESULTS

Mean lung dose and the volume receiving over 10 Gy (V10) showed significant correlation with late responses for single and fractionated exposures in directly targeted volumes. Responses observed outside the target volume were attributed to nontargeted effects and showed no dependence on either mean lung dose or V10.

CONCLUSIONS

Quantitative assessment of normal tissue response closely correlates early and late pulmonary response with clinical parameters, demonstrating this approach as a potential tool to facilitate clinical translation of preclinical studies. Out-of-field effects were observed but did not correlate with dosimetric parameters, suggesting that nontargeted effects may have a role in driving toxicities outside the treatment field.

Mechanistic Modelling of Radiation Responses

Radiobiological modelling has been a key part of radiation biology and therapy for many decades, and many aspects of clinical practice are guided by tools such as the linear-quadratic model. However, most of the models in regular clinical use are abstract and empirical, and do not provide significant scope for mechanistic interpretation or making predictions in novel cell lines or therapies. In this review, we will discuss the key areas of ongoing mechanistic research in radiation biology, including physical, chemical, and biological steps, and review a range of mechanistic modelling approaches which are being applied in each area, highlighting the possible opportunities and challenges presented by these techniques.

A New Standard DNA Damage (SDD) Data Format

Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called "indirect" damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

Investigation of dose-rate effects and cell-cycle distribution under protracted exposure to ionizing radiation for various dose-rates

During exposure to ionizing radiation, sub-lethal damage repair (SLDR) competes with DNA damage induction in cultured cells. By virtue of SLDR, cell survival increases with decrease of dose-rate, so-called dose-rate effects (DREs). Here, we focused on a wide dose-rate range and investigated the change of cell-cycle distribution during X-ray protracted exposure and dose-response curves via hybrid analysis with a combination of in vitro experiments and mathematical modelling. In the course of flow-cytometric cell-cycle analysis and clonogenic assays, we found the following responses in CHO-K1 cells: (1) The fraction of cells in S phase gradually increases during 6 h exposure at 3.0 Gy/h, which leads to radio-resistance. (2) Slight cell accumulation in S and G2/M phases is observed after exposure at 6.0 Gy/h for more than 10 hours. This suggests that an increase of SLDR rate for cells in S phase during irradiation may be a reproducible factor to describe changes in the dose-response curve at dose-rates of 3.0 and 6.0 Gy/h. By re-evaluating cell survival for various dose-rates of 0.186-60.0 Gy/h considering experimental-based DNA content and SLDR, it is suggested that the change of S phase fraction during irradiation modulates the dose-response curve and is possibly responsible for some inverse DREs.

Investigation of dose-rate effects and cell-cycle distribution under protracted exposure to ionizing radiation for various dose-rates

During exposure to ionizing radiation, sub-lethal damage repair (SLDR) competes with DNA damage induction in cultured cells. By virtue of SLDR, cell survival increases with decrease of dose-rate, so-called dose-rate effects (DREs). Here, we focused on a wide dose-rate range and investigated the change of cell-cycle distribution during X-ray protracted exposure and dose-response curves via hybrid analysis with a combination of in vitro experiments and mathematical modelling. In the course of flow-cytometric cell-cycle analysis and clonogenic assays, we found the following responses in CHO-K1 cells: (1) The fraction of cells in S phase gradually increases during 6 h exposure at 3.0 Gy/h, which leads to radio-resistance. (2) Slight cell accumulation in S and G₂/M phases is observed after exposure at 6.0 Gy/h for more than 10 hours. This suggests that an increase of SLDR rate for cells in S phase during irradiation may be a reproducible factor to describe changes in the dose-response curve at dose-rates of 3.0 and 6.0 Gy/h. By re-evaluating cell survival for various dose-rates of 0.186-60.0 Gy/h considering experimental-based DNA content and SLDR, it is suggested that the change of S phase fraction during irradiation modulates the dose-response curve and is possibly responsible for some inverse DREs.

The Impact of Hypoxia on Out-of-Field Cell Survival after Exposure to Modulated Radiation Fields

Advanced radiotherapy techniques such as intensity modulated radiation therapy achieve highly conformal dose distributions within target tumor volumes through the sequential delivery of multiple spatially and temporally modulated radiation fields and have been shown to influence radiobiological response. The goals of this study were to determine the effect of hypoxia on the cell survival responses of different cell models (H460, DU145, A549, MDA231 and FADU) to modulated fields and to characterize the time dependency of signaling under oxic conditions, following reoxygenation and after prolonged hypoxia. Hypoxia was induced by incubating cells at 95% nitrogen and 5% carbon dioxide for 4 h prior to irradiation. The out-of-field response in MDA231 cells was oxygen dependent and therefore selected for co-culture studies to determine the signaling kinetics at different time intervals after irradiation under oxic and hypoxic conditions. Under both oxic and hypoxic conditions, significant increases in cell survival were observed in-field with significant decreases in survival observed out-of-field (P < 0.05), which were dependent on intercellular communication. The in-field response of MDA231 cells showed no significant time dependency up to 24 h postirradiation, while out-of-field survival decreased significantly during the first 6 h postirradiation (P < 0.05). While in-field responses were oxygen dependent, out-of-field effects were observed to be independent of oxygen, with similar or greater cell killing under hypoxic conditions. This study provides further understanding of intercellular signaling under hypoxic conditions and highlights the need for further refinement of established radiobiological models for future applications in advanced radiotherapies.

Grid therapy using high definition multileaf collimators: realizing benefits of the bystander effect

BACKGROUND

In microbeam radiotherapy (MRT), parallel arrays of high-intensity synchrotron x-ray beams achieve normal tissue sparing without compromising tumor control. Grid-therapy using clinical linacs has spatial modulation on a larger scale and achieves promising results for palliative treatments of bulky tumors. The availability of high definition multileaf collimators (HDMLCs) with 2.5 mm leaves provides an opportunity for grid-therapy to more closely approach MRT. However, challenges to the wider implementation of grid-therapy remain because spatial modulation of the target volume runs counter to current radiotherapy practice and mechanisms for the beneficial effects of MRT are not fully understood. Without more knowledge of cell dose responses, a quantitative basis for planning treatments is difficult. The aim of this study is to determine if therapeutic benefits of MRT can be achieved using a linac with HDMLCs and if so, to develop a predictive model to support treatment planning.

MATERIAL AND METHODS

HD120-MLCs of a Varian Novalis TX^TM were used to generate grid patterns of 2.5 and 5.0 mm spacing, which were characterized dosimetrically using Gafchromic^TM EBT3 film. Clonogenic survival of normal (HUVEC) and cancer (NCI-H460, HCC-1954) cell lines following irradiation under the grid and open fields using a 6 MV photon beam were compared in-vitro for the same average dose.

RESULTS AND CONCLUSIONS

Relative to an open field, survival of normal cells in a 2.5 mm striped field was the same, while the survival of both cancer cell lines was significantly lower. A mathematical model was developed to incorporate dose gradients of the spatial modulation into the standard linear quadratic model. Our new bystander extended LQ model assumes spatial gradients drive the diffusion of soluble factors that influence survival through bystander effects, successfully predicting the experimental results that show an increased therapeutic ratio. Our results challenge conventional radiotherapy practice and propose that additional gain can be realized by prescribing spatially modulated treatments to harness the bystander effect.

Modelling responses to spatially fractionated radiation fields using preclinical image-guided radiotherapy

OBJECTIVE

Radiotherapy is planned to achieve the optimal physical dose distribution to the target tumour volume whilst minimizing dose to the surrounding normal tissue. Recent in vitro experimental evidence has demonstrated an important role for intercellular communication in radiobiological responses following non-uniform exposures. This study aimed to model the impact of these effects in the context of techniques involving highly modulated radiation fields or spatially fractionated treatments such as spatially fractionated radiotherapy (GRID).

METHODS

Using the small-animal radiotherapy research platform as a key enabling technology to deliver precision imaged-guided radiotherapy, it is possible to achieve spatially modulated dose distributions that model typical clinical scenarios. In this work, we planned uniform and spatially fractionated dose distributions using multiple isocentres with beam sizes of 0.5-5 mm to obtain 50% volume coverage in a subcutaneous murine tumour model and applied a model of cellular response that incorporates intercellular communication to assess the potential impact of signalling effects with different ranges.

RESULTS

Models of GRID treatment plans which incorporate intercellular signalling showed increased cell killing within the low-dose region. This results in an increase in the equivalent uniform dose for GRID exposures compared with standard models, with some GRID exposures being predicted to be more effective than uniform delivery of the same physical dose.

CONCLUSION

This study demonstrates the potential impact of radiation-induced signalling on tumour cell response for spatially fractionated therapies and identifies key experiments to validate this model and quantify these effects in vivo. Advances in knowledge: This study highlights the unique opportunities now possible using advanced preclinical techniques to develop a foundation for biophysical optimization in radiotherapy treatment planning.

Mechanistic Modelling of DNA Repair and Cellular Survival Following Radiation-Induced DNA Damage

Characterising and predicting the effects of ionising radiation on cells remains challenging, with the lack of robust models of the underlying mechanism of radiation responses providing a significant limitation to the development of personalised radiotherapy. In this paper we present a mechanistic model of cellular response to radiation that incorporates the kinetics of different DNA repair processes, the spatial distribution of double strand breaks and the resulting probability and severity of misrepair. This model enables predictions to be made of a range of key biological endpoints (DNA repair kinetics, chromosome aberration and mutation formation, survival) across a range of cell types based on a set of 11 mechanistic fitting parameters that are common across all cells. Applying this model to cellular survival showed its capacity to stratify the radiosensitivity of cells based on aspects of their phenotype and experimental conditions such as cell cycle phase and plating delay (correlation between modelled and observed Mean Inactivation Doses R(2) > 0.9). By explicitly incorporating underlying mechanistic factors, this model can integrate knowledge from a wide range of biological studies to provide robust predictions and may act as a foundation for future calculations of individualised radiosensitivity.

Bystander effects and their implications for clinical radiation therapy: Insights from multiscale in silico experiments

Radiotherapy is a commonly used treatment for cancer and is usually given in varying doses. At low radiation doses relatively few cells die as a direct response to radiation but secondary radiation effects, such as DNA mutation or bystander phenomena, may affect many cells. Consequently it is at low radiation levels where an understanding of bystander effects is essential in designing novel therapies with superior clinical outcomes. In this paper, we use a hybrid multiscale mathematical model to study the direct effects of radiation as well as radiation-induced bystander effects on both tumour cells and normal cells. We show that bystander responses play a major role in mediating radiation damage to cells at low-doses of radiotherapy, doing more damage than that due to direct radiation. The survival curves derived from our computational simulations showed an area of hyper-radiosensitivity at low-doses that are not obtained using a traditional radiobiological model.

The relative biological effectiveness of out-of-field dose

PURPOSE

using simulations and models derived from existing literature, this work investigates relative biological effectiveness (RBE) for out-of-field radiation and attempts to quantify the relative magnitudes of different contributing phenomena (spectral, bystander, and low dose hypersensitivity effects). Specific attention is paid to external beam radiotherapy treatments for prostate cancer.

MATERIALS AND METHODS

using different biological models that account for spectral, bystander, and low dose hypersensitivity effects, the RBE was calculated for different points moving radially out from isocentre for a typical single arc VMAT prostate case. The RBE was found by taking the ratio of the equivalent dose with the physical dose. Equivalent doses were calculated by determining what physical dose would be necessary to produce the same overall biological effect as that predicted using the different biological models.

RESULTS

spectral effects changed the RBE out-of-field less than 2%, whereas response models incorporating low dose hypersensitivity and bystander effects resulted in a much more profound change of the RBE for out-of-field doses. The bystander effect had the largest RBE for points located just outside the edge of the primary radiation beam in the cranial caudal (z-direction) compared to low dose hypersensitivity and spectral effects. In the coplanar direction, bystander effect played the largest role in enhancing the RBE for points up to 8.75 cm from isocentre.

CONCLUSIONS

spectral, bystander, and low dose hypersensitivity effects can all increase the RBE for out-of-field radiation doses. In most cases, bystander effects seem to play the largest role followed by low dose hypersensitivity. Spectral effects were unlikely to be of any clinical significance. Bystander, low dose hypersensitivity, and spectral effect increased the RBE much more in the cranial caudal direction (z-direction) compared with the coplanar directions.

Roadmap to Clinical Use of Gold Nanoparticles for Radiation Sensitization

The past decade has seen a dramatic increase in interest in the use of gold nanoparticles (GNPs) as radiation sensitizers for radiation therapy. This interest was initially driven by their strong absorption of ionizing radiation and the resulting ability to increase dose deposited within target volumes even at relatively low concentrations. These early observations are supported by extensive experimental validation, showing GNPs' efficacy at sensitizing tumors in both in vitro and in vivo systems to a range of types of ionizing radiation, including kilovoltage and megavoltage X rays as well as charged particles. Despite this experimental validation, there has been limited translation of GNP-mediated radiation sensitization to a clinical setting. One of the key challenges in this area is the wide range of experimental systems that have been investigated, spanning a range of particle sizes, shapes, and preparations. As a result, mechanisms of uptake and radiation sensitization have remained difficult to clearly identify. This has proven a significant impediment to the identification of optimal GNP formulations which strike a balance among their radiation sensitizing properties, their specificity to the tumors, their biocompatibility, and their imageability in vivo. This white paper reviews the current state of knowledge in each of the areas concerning the use of GNPs as radiosensitizers, and outlines the steps which will be required to advance GNP-enhanced radiation therapy from their current pre-clinical setting to clinical trials and eventual routine usage.

Proteomic overview and perspectives of the radiation-induced bystander effects

Radiation proteomics is a recent, promising and powerful tool to identify protein markers of direct and indirect consequences of ionizing radiation. The main challenges of modern radiobiology is to predict radio-sensitivity of patients and radio-resistance of tumor to be treated, but considerable evidences are now available regarding the significance of a bystander effect at low and high doses. This "radiation-induced bystander effect" (RIBE) is defined as the biological responses of non-irradiated cells that received signals from neighboring irradiated cells. Such intercellular signal is no more considered as a minor side-effect of radiotherapy in surrounding healthy tissue and its occurrence should be considered in adapting radiotherapy protocols, to limit the risk for radiation-induced secondary cancer. There is no consensus on a precise designation of RIBE, which involves a number of distinct signal-mediated effects within or outside the irradiated volume. Indeed, several cellular mechanisms were proposed, including the secretion of soluble factors by irradiated cells in the extracellular matrix, or the direct communication between irradiated and neighboring non-irradiated cells via gap junctions. This phenomenon is observed in a context of major local inflammation, linked with a global imbalance of oxidative metabolism which makes its analysis challenging using in vitro model systems. In this review article, the authors first define the radiation-induced bystander effect as a function of radiation type, in vitro analysis protocols, and cell type. In a second time, the authors present the current status of protein biomarkers and proteomic-based findings and discuss the capacities, limits and perspectives of such global approaches to explore these complex intercellular mechanisms.

Potential implications of the bystander effect on TCP and EUD when considering target volume dose heterogeneity

PURPOSE

In light of in vitro evidence suggesting that radiation-induced bystander effects may enhance non-local cell killing, there is potential for impact on radiotherapy treatment planning paradigms such as the goal of delivering a uniform dose throughout the clinical target volume (CTV). This work applies a bystander effect model to calculate equivalent uniform dose (EUD) and tumor control probability (TCP) for external beam prostate treatment and compares the results with a more common model where local response is dictated exclusively by local absorbed dose. The broad assumptions applied in the bystander effect model are intended to place an upper limit on the extent of the results in a clinical context.

MATERIALS AND METHODS

EUD and TCP of a prostate cancer target volume under conditions of increasing dose heterogeneity were calculated using two models: One incorporating bystander effects derived from previously published in vitro bystander data ( McMahon et al. 2012 , 2013a); and one using a common linear-quadratic (LQ) response that relies exclusively on local absorbed dose. Dose through the CTV was modelled as a normal distribution, where the degree of heterogeneity was then dictated by changing the standard deviation (SD). Also, a representative clinical dose distribution was examined as cold (low dose) sub-volumes were systematically introduced.

RESULTS

The bystander model suggests a moderate degree of dose heterogeneity throughout a target volume will yield as good or better outcome compared to a uniform dose in terms of EUD and TCP. For a typical intermediate risk prostate prescription of 78 Gy over 39 fractions maxima in EUD and TCP as a function of increasing SD occurred at SD ∼ 5 Gy. The plots only dropped below the uniform dose values for SD ∼ 10 Gy, almost 13% of the prescribed dose. Small, but potentially significant differences in the outcome metrics between the models were identified in the clinically-derived dose distribution as cold sub-volumes were introduced.

CONCLUSIONS

In terms of EUD and TCP, the bystander model demonstrates the potential to deviate from the common local LQ model predictions as dose heterogeneity through a prostate CTV varies. The results suggest, at least in a limiting sense, the potential for allowing some degree of dose heterogeneity within a CTV, although further investigation of the assumptions of the bystander model are warranted.

Potential implications on TCP for external beam prostate cancer treatment when considering the bystander effect in partial exposure scenarios

PURPOSE

This work investigated the potential implications on tumour control probability (TCP) for external beam prostate cancer treatment when considering the bystander effect in partial exposure scenarios.

MATERIALS AND METHODS

The biological response of a prostate cancer target volume under conditions where a sub-volume of the target volume was not directly irradiated was modelled in terms of surviving fraction (SF) and Poisson-based TCP. A direct comparison was made between the linear-quadratic (LQ) response model, and a response model that incorporates bystander effects as derived from published in vitro data by McMahon et al. in 2012 and 2013. Scenarios of random and systematic misses were considered.

RESULTS

Our results suggested the potential for the bystander effect to deviate from LQ predictions when even very small (< 1%) sub-volumes of the target volume were directly irradiated. Under conditions of random misses for each fraction, the bystander model predicts a 3% and 1% improvement in tumour control compared to that predicted by an LQ model when only 90% and 95% of the prostate cells randomly receive the intended dose. Under conditions of systematic miss, if even a small portion of the target volume is not directly exposed, the LQ model predicts a TCP approaching zero, whereas the bystander model suggests TCP will improve starting at exposed volumes of around 85%.

CONCLUSIONS

The bystander model, when applied to clinically relevant scenarios, demonstrates the potential to deviate from the TCP predictions of the common local LQ model when sub-volumes of a target volume are randomly or systematically missed over a course of fractionated radiation therapy.

Bystander effects as manifestation of intercellular communication of DNA damage and of the cellular oxidative status

It is becoming increasingly clear that cells exposed to ionizing radiation (IR) and other genotoxic agents (targeted cells) can communicate their DNA damage response (DDR) status to cells that have not been directly irradiated (bystander cells). The term radiation-induced bystander effects (RIBE) describes facets of this phenomenon, but its molecular underpinnings are incompletely characterized. Consequences of DDR in bystander cells have been extensively studied and include transformation and mutation induction; micronuclei, chromosome aberration and sister chromatid exchange formation; as well as modulations in gene expression, proliferation and differentiation patterns. A fundamental question arising from such observations is why targeted cells induce DNA damage in non-targeted, bystander cells threatening thus their genomic stability and risking the induction of cancer. Here, we review and synthesize available literature to gather support for a model according to which targeted cells modulate as part of DDR their redox status and use it as a source to generate signals for neighboring cells. Such signals can be either small molecules transported to adjacent non-targeted cells via gap-junction intercellular communication (GJIC), or secreted factors that can reach remote, non-targeted cells by diffusion or through the circulation. We review evidence that such signals can induce in the recipient cell modulations of redox status similar to those seen in the originating targeted cell - occasionally though self-amplifying feedback loops. The resulting increase of oxidative stress in bystander cells induces, often in conjunction with DNA replication, the observed DDR-like responses that are at times strong enough to cause apoptosis. We reason that RIBE reflect the function of intercellular communication mechanisms designed to spread within tissues, or the entire organism, information about DNA damage inflicted to individual, constituent cells. Such responses are thought to protect the organism by enhancing repair in a community of cells and by eliminating severely damaged cells.

The complex interactions between radiation induced non-targeted effects and cancer

Radiation induced non-targeted effects have been widely investigated in the last two decades for their potential impact on low dose radiation risk. In this paper we will give an overview of the most relevant aspects related to these effects, starting from the definition of the low dose scenarios. We will underline the role of radiation quality, both in terms of mechanisms of interaction with the biological matter and for the importance of charged particles as powerful tools for low dose effects investigation. We will focus on cell communication, representing a common feature of non-targeted effects, giving also an overview of cancer models that have explicitly considered such effects.

A kinetic-based model of radiation-induced intercellular signalling

It is now widely accepted that intercellular communication can cause significant variations in cellular responses to genotoxic stress. The radiation-induced bystander effect is a prime example of this effect, where cells shielded from radiation exposure see a significant reduction in survival when cultured with irradiated cells. However, there is a lack of robust, quantitative models of this effect which are widely applicable. In this work, we present a novel mathematical model of radiation-induced intercellular signalling which incorporates signal production and response kinetics together with the effects of direct irradiation, and test it against published data sets, including modulated field exposures. This model suggests that these so-called “bystander” effects play a significant role in determining cellular survival, even in directly irradiated populations, meaning that the inclusion of intercellular communication may be essential to produce robust models of radio-biological outcomes in clinically relevant in vivo situations.