A mathematical framework for separating the direct and bystander components of cellular radiation response

Radiation responses of cancer and normal cells to split dose fractions with uniform and grid fields: increasing the therapeutic ratio

PURPOSE

Radiation treatment of cancer is usually delivered in a prescribed sequence of dose fractions within which the dependence of dose on time is determined by the treatment plan. New techniques, such as stereotactic body radiation therapy (SBRT) and image guided radiation therapy (IGRT) have been introduced with the motivation of improving therapeutic outcomes, with the consequence that the time dependence of the dose within a fraction is modified. Here, we test whether an increased toxicity to cancer cells arises when a radiation treatment fraction is delivered in two equal parts, allowing time for the expression of factors, for example, RONS and cytokines, in response to the first dose which may sensitize cells to the second dose. A medium time delay between 15 and 60 minutes is proposed to allow factors to be expressed before repair takes place. A grid field is used to enhance diffusion of the factors.

MATERIALS AND METHODS

The cell lines used in the study were two prostate cancers (LNCaP and DU 145), a normal prostate (PNT1A), a non-small cell lung cancer (NCI-H460), and a glioma (Hs 683). Uniform or spatially modulated grid fields, delivering the same mean dose, were used. The results for the clonogenic survival fractions were grouped into a 'short' delay (under 10 minutes) and a 'medium' delay (between 15 and 60 minutes).

RESULTS

The medium delay with a grid field yielded a significant increase in toxicity for the four cancer cell lines. The medium delay with a uniform field gave a significant increase in toxicity for the two prostate cancer cell lines. A highly significant increase was found in the therapeutic ratio, defined as the ratio of the survival of prostate normal to prostate cancer cells.

CONCLUSIONS

The findings show that the intra-fractional dose schedule with medium time delay offers an opportunity to increase the toxicity of radiation to cancer cells, relative to a single radiation delivery. For all cancer cell lines, a grid field gives a greater toxic effect than a uniform field. The split dose treatment offers an increase in cancer toxicity while preserving normal cells, improving the outcomes of a treatment.

Computational Biophysical Modeling of the Radiation Bystander Effect in Irradiated Cells

It is well known that ionizing radiation can cause damages to cells that interact with it directly. However, many studies have shown that damages also occur in cells that have not experienced direct interaction. This is due to the so-called bystander effect, which is observed when the irradiated cell sends signals that can damage neighboring cells. Due to the complexity of this effect, it is not easy to strictly describe it biophysically, and thus it is also difficult to simulate. This article reviews various approaches to modeling and simulating the bystander effect from the point of view of radiation biophysics. In particular, the last model presented within this article is part of a larger project of modeling the response of a group of cells to ionizing radiation using Monte Carlo methods. The new approach presented here is based on the probability tree, the Poisson distribution of signals and the saturated dose-related probability distribution of the bystander effect’s appearance, which makes the model very broad and universal.

Modeling space radiation induced cognitive dysfunction using targeted and non-targeted effects

Radiation-induced cognitive dysfunction is increasingly recognized as an important risk for human exploration of distant planets. Mechanistically-motivated mathematical modeling helps to interpret and quantify this phenomenon. Here we considered two general mechanisms of ionizing radiation-induced damage: targeted effects (TE), caused by traversal of cells by ionizing tracks, and non-targeted effects (NTE), caused by responses of other cells to signals released by traversed cells. We compared the performances of 18 dose response model variants based on these concepts, fitted by robust nonlinear regression to a large published data set on novel object recognition testing in rats exposed to multiple space-relevant radiation types (H, C, O, Si, Ti and Fe ions), covering wide ranges of linear energy transfer (LET) (0.22-181 keV/µm) and dose (0.001-2 Gy). The best-fitting model (based on Akaike information criterion) was an NTE + TE variant where NTE saturate at low doses (~ 0.01 Gy) and occur at all tested LETs, whereas TE depend on dose linearly with a slope that increases with LET. The importance of NTE was also found by additional analyses of the data using quantile regression and random forests. These results suggest that NTE-based radiation effects on brain function are potentially important for astronaut health and for space mission risk assessments.

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.

Enhancing the Bystander and Abscopal Effects to Improve Radiotherapy Outcomes

In this paper, we summarize published articles and experiences related to the attempt to improve radiotherapy outcomes and, thus, to personalize the radiation treatment according to the individual characteristics of each patient. The evolution of ideas and the study of successively published data have led us to envisage new biophysical models for the interpretation of tumor and healthy normal tissue response to radiation. In the development of the model, we have shown that when mesenchymal stem cells (MSCs) and radiotherapy are administered simultaneously in experimental radiotherapy on xenotumors implanted in a murine model, the results of the treatment show the existence of a synergic mechanism that is able to enhance the local and systemic actions of the radiation both on the treated tumor and on its possible metastasis. We are convinced that, due to the physical hallmarks that characterize the neoplastic tissues, the physical-chemical tropism of MSCs, and the widespread functions of macromolecules, proteins, and exosomes released from activated MSCs, the combination of radiotherapy plus MSCs used intratumorally has the effect of counteracting the pro-tumorigenic and pro-metastatic signals that contribute to the growth, spread, and resistance of the tumor cells. Therefore, we have concluded that MSCs are appropriate for therapeutic use in a clinical trial for rectal cancer combined with radiotherapy, which we are going to start in the near future.

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.

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.

On the Inclusion of Short-distance Bystander Effects into a Logistic Tumor Control Probability Model

Currently, interactions between voxels are neglected in the tumor control probability (TCP) models used in biologically-driven intensity-modulated radiotherapy treatment planning. However, experimental data suggests that this may not always be justified when bystander effects are important. We propose a model inspired by the Ising model, a short-range interaction model, to investigate if and when it is important to include voxel to voxel interactions in biologically-driven treatment planning. This Ising-like model for TCP is derived by first showing that the logistic model of tumor control is mathematically equivalent to a non-interacting Ising model. Using this correspondence, the parameters of the logistic model are mapped to the parameters of an Ising-like model and bystander interactions are introduced as a short-range interaction as is the case for the Ising model. As an example, we apply the model to study the effect of bystander interactions in the case of radiation therapy for prostate cancer. The model shows that it is adequate to neglect bystander interactions for dose distributions that completely cover the treatment target and yield TCP estimates that lie in the shoulder of the dose response curve. However, for dose distributions that yield TCP estimates that lie on the steep part of the dose response curve or for inhomogeneous dose distributions having significant hot and/or cold regions, bystander effects may be important. Furthermore, the proposed model highlights a previously unexplored and potentially fruitful connection between the fields of statistical mechanics and tumor control probability/normal tissue complication probability modeling.

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.

Melanoma: Last call for radiotherapy

Melanoma is traditionally considered to be a radioresistant tumor. However, radiotherapy and immunotherapy latest developments might upset this radiobiological dogma. Stereotactic radiotherapy allows high dose per fraction delivery, with high dose rate. More DNA lethal damages, less sublethal damages reparation, endothelial cell apoptosis, and finally clonogenic cell dysfunction are produced, resulting in improved local control. Radiotherapy can also enhance immune responses, inducing neoantigens formation, tumor antigen presentation, and cytokines release. A synergic effect of radiotherapy with immunotherapy is expected, and might lead to abscopal effects. If hadrontherapy biological properties seem able to suppress hypoxia-induced radioresistance and increase biological efficacy, ballistic advantages over photon radiations might also improve radiotherapy outcomes on usually poor prognosis locations. The present review addresses biological and clinical effects of high fraction dose, bystander effect, abscopal effect, and hadrontherapy features in melanoma. Clinical trials results are warranted to establish indications of innovative radiotherapy in melanoma.

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.

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.

Impact of fractionation on out-of-field survival and DNA damage responses following exposure to intensity modulated radiation fields

To limit toxicity to normal tissues adjacent to the target tumour volume, radiotherapy is delivered using fractionated regimes whereby the total prescribed dose is given as a series of sequential smaller doses separated by specific time intervals. The impact of fractionation on out-of-field survival and DNA damage responses was determined in AGO-1522 primary human fibroblasts and MCF-7 breast tumour cells using uniform and modulated exposures delivered using a 225 kVp x-ray source. Responses to fractionated schedules (two equal fractions delivered with time intervals from 4 h to 48 h) were compared to those following acute exposures. Cell survival and DNA damage repair measurements indicate that cellular responses to fractionated non-uniform exposures differ from those seen in uniform exposures for the investigated cell lines. Specifically, there is a consistent lack of repair observed in the out-of-field populations during intervals between fractions, confirming the importance of cell signalling to out-of-field responses in a fractionated radiation schedule, and this needs to be confirmed for a wider range of cell lines and conditions.

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.

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.

Direct and bystander radiation effects: a biophysical model and clinical perspectives

In planning treatment for each new patient, radiation oncologists pay attention to the aspects that they control. Thus their attention is usually focused on volume and dose. The dilemma for the physician is how to protract the treatment in a way that maximizes control of the tumor and minimizes normal tissue injury. The initial radiation-induced damage to DNA may be a biological indicator of the quantity of energy transferred to the DNA. However, until now the biophysical models proposed cannot explain either the early or the late adverse effects of radiation, and a more general theory appears to be required. The bystander component of tumor cell death after radiotherapy measured in many experimental works highlights the importance of confirming these observations in a clinical situation.

Bystander signalling: exploring clinical relevance through new approaches and new models

Classical radiation biology research has centred on nuclear DNA as the main target of radiation-induced damage. Over the past two decades, this has been challenged by a significant amount of scientific evidence clearly showing radiation-induced cell signalling effects to have important roles in mediating overall radiobiological response. These effects, generally termed radiation-induced bystander effects (RIBEs) have challenged the traditional DNA targeted theory in radiation biology and highlighted an important role for cells not directly traversed by radiation. The multiplicity of experimental systems and exposure conditions in which RIBEs have been observed has hindered precise definitions of these effects. However, RIBEs have recently been classified for different relevant human radiation exposure scenarios in an attempt to clarify their role in vivo. Despite significant research efforts in this area, there is little direct evidence for their role in clinically relevant exposure scenarios. In this review, we explore the clinical relevance of RIBEs from classical experimental approaches through to novel models that have been used to further determine their potential implications in the clinic.

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.

A simulation study of the radiation-induced bystander effect: modeling with stochastically defined signal reemission

The radiation-induced bystander effect (RIBE) has been experimentally observed for different types of radiation, cell types, and cell culture conditions. However, the behavior of signal transmission between unirradiated and irradiated cells is not well known. In this study, we have developed a new model for RIBE based on the diffusion of soluble factors in cell cultures using a Monte Carlo technique. The model involves the signal emission probability from bystander cells following Poisson statistics. Simulations with this model show that the spatial configuration of the bystander cells agrees well with that of corresponding experiments, where the optimal emission probability is estimated through a large number of simulation runs. It was suggested that the most likely probability falls within 0.63–0.92 for mean number of the emission signals ranging from 1.0 to 2.5.

The importance of bystander effects in radiation therapy in melanoma skin-cancer cells and umbilical-cord stromal stem cells

PURPOSE

To examine direct and bystander radiation-induced effects in normal umbilical-cord stromal stem cell (HCSSC) lines and in human cancer cells.

MATERIALS AND METHODS

The UCSSC lines used in this study were obtained in our laboratory. Two cell lines (UCSSC 35 and UCSSC 37) and two human melanoma skin-cancer cells (A375 and G361) were exposed to ionizing radiation to measure acute radiation-dosage cell-survival curves and radiation-induced bystander cell-death response. Normal cells, although extremely sensitive to ionizing radiation, were resistant to the bystander effect whilst tumor cells were sensitive to irradiated cell-conditioned media, showing a dose-response relationship that became saturated at relatively low doses. We applied a biophysical model to describe bystander cell-death through the binding of a ligand to the cells. This model allowed us to calculate the maximum cell death (χ(max)) produced by the bystander effect together with its association constant (K(By)) in terms of dose equivalence (Gy). The values obtained for K(By) in A375 and G361 cells were 0.23 and 0.29 Gy, respectively.

CONCLUSION

Our findings help to understand how anticancer therapy could have an additional decisive effect in that the response of sub-lethally hit tumor cells to damage might be required for therapy to be successful because the survival of cells communicating with irradiated cells is reduced.

Cell survival responses after exposure to modulated radiation fields

In the present study survival responses were determined in cells with differing radiosensitivity, specifically primary fibroblast (AG0-1522B), human breast cancer (MDA-MB-231), human prostate cancer (DU-145) and human glioma (T98G) cells, after exposure to modulated radiation fields delivered by shielding 50% of the tissue culture flask. A significant decrease (P < 0.05) in cell survival was observed in the shielded area, outside the primary treatment field (out-of-field), that was lower than predicted when compared to uniform exposures fitted to the linear-quadratic model. Cellular radiosensitivity was demonstrated to be an important factor in the level of response for both the in- and out-of-field regions. These responses were shown to be dependent on secretion-mediated intercellular communication, because inhibition of cellular secreted factors between the in- and out-of-field regions abrogated the response. Out-of-field cell survival was shown to increase after pretreatment of cells with agents known to inhibit factors involved in mediating radiation-induced bystander signaling (aminoguanidine, DMSO or cPTIO). These data illustrate a significant decrease in survival out-of-field, dependent upon intercellular communication, in several cell lines with varying radiosensitivity after exposure to a modulated radiation field. This study provides further evidence for the importance of intercellular signaling in modulated exposures, where dose gradients are present, and may inform the refinement of established radiobiological models to facilitate the optimization of advanced radiotherapy treatment plans.

A review of in vitro experimental evidence for the effect of spatial and temporal modulation of radiation dose on response

BACKGROUND

Intensity modulated radiation therapy introduces strong spatial and temporal modulation of the dose delivery that may have therapeutic benefits, as yet unrealized.

MATERIAL AND METHODS

Experimental evidence for spatial and temporal modulation affecting the cell survival following in vitro irradiation has been derived using clonogenic assays.

RESULTS AND DISCUSSION

The experimental results show that the survival status of a cell is strongly influenced by the spatial dose modulation. The classical bystander effect of decreased survival has now been supplemented by observations of increased survival, which may result from the same or different signaling mechanisms. Temporal dose modulation experiments show that dose protraction significantly increases cell survival. An appropriate choice of temporal dose modulation pattern enables cell death to be maximized or minimized for a constant dose and delivery time.

CONCLUSION

Bystander effects challenge the assumption that outcome is solely dependent on local dose. Intra-fractional temporal modulation via protracted treatments and time varying dose delivery both affect the cell survival. The presence of bystander and temporal effects emphasize the need for a mathematical framework which incorporates their influence on cell survival.