A kinetic-based model of radiation-induced intercellular signalling

Clinical Implementation and Dosimetric Evaluation of a Robust Proton Lattice Planning Strategy Using Primary and Robust Complementary Beams

PURPOSE

Pencil-beam scanning proton therapy has been considered a potential modality for the 3D form of spatially fractionated radiation therapy called lattice therapy. However, few practical solutions have been introduced in the clinic. Existing limitations include degradation in plan quality and robustness when using single-field versus multifield lattice plans, respectively. We propose a practical and robust proton lattice (RPL) planning method using multifield and evaluate its dosimetric characteristics compared to clinically acceptable photon lattice plans.

METHODS AND MATERIALS

Seven cases previously treated with photon lattice therapy were used to evaluate a novel RPL planning technique using 2-orthogonal beams: a primary beam (PB) and a robust complementary beam (RCB) that deliver 67% and 33%, respectively, of the prescribed dose to vertices inside the gross target volume (GTV). Only RCB is robustly optimized for setup and range uncertainties. The number and volume of vertices, peak-to-valley dose ratios (PVDRs), and volume of low dose to GTV of proton and photon plans were compared. The RPL technique was then used in the treatment of 2 patients and their dosimetric parameters were reported.

RESULTS

The RPL strategy was able to achieve the clinical planning goals. Compared to previously treated photon plans, the average number of vertices increased by 30%, the average vertex volume by 49% (18.2 ± 25.9 cc vs 12.2 ± 14.5 cc, P = .21), and higher PVDR (10.5 ± 4.8 vs 2.5 ± 0.9, P < .005) was achieved. In addition, RPL plans show more conformal dose with less low dose to GTV (V30%, 60.9% ± 7.2% vs 81.6% ± 13.9% and V10%, 88.3% ± 4.5% vs 98.6% ± 3.6% [P < .01]). The RPL plan for 2 treated patients showed PVDRs of 4.61 and 14.85 with vertices-to-GTV ratios of 1.52% and 1.30%, respectively.

CONCLUSIONS

A novel RPL planning strategy using a pair of orthogonal beams was developed and successfully translated to the clinic. The proposed method can generate better quality plans, a higher number of vertices, and higher PVDRs than currently used photon lattice plans.

Modelling radiobiology

Radiotherapy has played an essential role in cancer treatment for over a century, and remains one of the best-studied methods of cancer treatment. Because of its close links with the physical sciences, it has been the subject of extensive quantitative mathematical modelling, but a complete understanding of the mechanisms of radiotherapy has remained elusive. In part this is because of the complexity and range of scales involved in radiotherapy-from physical radiation interactions occurring over nanometres to evolution of patient responses over months and years. This review presents the current status and ongoing research in modelling radiotherapy responses across these scales, including basic physical mechanisms of DNA damage, the immediate biological responses this triggers, and genetic- and patient-level determinants of response. Finally, some of the major challenges in this field and potential avenues for future improvements are also discussed.

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.

Mechanistic model of radiotherapy-induced lung fibrosis using coupled 3D agent-based and Monte Carlo simulations

BACKGROUND

Mechanistic modelling of normal tissue toxicities is unfolding as an alternative to the phenomenological normal tissue complication probability models. The latter, currently used in the clinics, rely exclusively on limited patient data and neglect spatial dose distribution information. Among the various approaches, agent-based models are appealing as they provide the means to include patient-specific parameters and simulate long-term effects in complex systems. However, Monte Carlo tools remain the state-of-the-art for modelling radiation transport and provide measurements of the delivered dose with unmatched precision.

METHODS

In this work, we develop and characterize a coupled 3D agent-based - Monte Carlo model that mechanistically simulates the onset of the radiation-induced lung fibrosis in an alveolar segment. To the best of our knowledge, this is the first such model.

RESULTS

Our model replicates extracellular matrix patterns, radiation-induced lung fibrosis severity indexes and functional subunits survivals that show qualitative agreement with experimental studies and are consistent with our past results. Moreover, in accordance with experimental results, higher functional subunits survival and lower radiation-induced lung fibrosis severity indexes are achieved when a 5-fractions treatment is simulated. Finally, the model shows increased sensitivity to more uniform protons dose distributions with respect to more heterogeneous ones from photon irradiation.

CONCLUSIONS

This study lays thus the groundwork for further investigating the effects of different radiotherapeutic treatments on the onset of radiation-induced lung fibrosis via mechanistic modelling.

Evaluation of the effect of intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc radiotherapy (VMAT) techniques on survival response in cell lines with a new radiobiological modeling

BACKGROUND

The optimal radiobiological model, which assesses the biological effects of novel radiotherapy techniques that concurrently modify multiple physical factors, has not yet been defined. This study aimed to investigate the impact of intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) on cellular response in head and neck cancer and melanoma models.

METHODS

Clonogenic analysis, DNA double-strand break analysis, apoptosis, and cell cycle analysis were performed on cancer stem cell models, cancer models, and normal tissue cell models to assess radiation sensitivity.

RESULTS

The segmented radiation approach used in IMRT applications enhanced radiosensitivity and cytotoxicity in the cancer models, while changes in dose rate had varying effects on cytotoxicity depending on the tumor cell type. VMAT increased cellular resistance, favoring treatment outcomes.

CONCLUSIONS

The biological processes were influenced differently by dose rate, IMRT, and VMAT depending on the tumor cell type. The selection of the most appropriate technique is crucial in representing new radiotherapy approaches. The obtained data can serve as a model to address clinical questions in daily practice. The integration of non-standard outcomes with standard applications should be considered in clinical settings.

The Metabolic Footprint of Systemic Effects in the Blood Caused by Radiotherapy and Inflammatory Conditions: A Systematic Review

Response to radiotherapy (RT) includes tissue toxicity, which may involve inflammatory reactions. We aimed to compare changes in metabolic patterns induced at the systemic level by radiation and inflammation itself. Patients treated with RT due to head and neck cancer and patients with inflammation-related diseases located in the corresponding anatomical regions were selected. PubMed and Web of Science databases were searched from 1 January 2000 to 10 August 2023. Twenty-five relevant studies where serum/plasma metabolic profiles were analyzed using different metabolomics approaches were identified. The studies showed different metabolic patterns of acute and chronic inflammatory diseases, yet changes in metabolites linked to the urea cycle and metabolism of arginine and proline were common features of both conditions. Although the reviewed reports showed only a few specific metabolites common for early RT response and inflammatory diseases, partly due to differences in metabolomics approaches, several common metabolic pathways linked to metabolites affected by radiation and inflammation were revealed. They included pathways involved in energy metabolism (e.g., metabolism of ketone bodies, mitochondrial electron transport chain, Warburg effect, citric acid cycle, urea cycle) and metabolism of certain amino acids (Arg, Pro, Gly, Ser, Met, Ala, Glu) and lipids (glycerolipids, branched-chain fatty acids). However, metabolites common for RT and inflammation-related diseases could show opposite patterns of changes. This could be exemplified by the lysophosphatidylcholine to phosphatidylcholine ratio (LPC/PC) that increased during chronic inflammation and decreased during the early phase of response to RT. One should be aware of dynamic metabolic changes during different phases of response to radiation, which involve increased levels of LPC in later phases. Hence, metabolomics studies that would address molecular features of both types of biological responses using comparable analytical and clinical approaches are needed to unravel the complexities of these phenomena, ultimately contributing to a deeper understanding of their impact on biological systems.

An Agent-Based Model of Radiation-Induced Lung Fibrosis

Early- and late-phase radiation-induced lung injuries, namely pneumonitis and lung fibrosis (RILF), severely constrain the maximum dose and irradiated volume in thoracic radiotherapy. As the most radiosensitive targets, epithelial cells respond to radiation either by undergoing apoptosis or switching to a senescent phenotype that triggers the immune system and damages surrounding healthy cells. Unresolved inflammation stimulates mesenchymal cells' proliferation and extracellular matrix (ECM) secretion, which irreversibly stiffens the alveolar walls and leads to respiratory failure. Although a thorough understanding is lacking, RILF and idiopathic pulmonary fibrosis share multiple pathways and would mutually benefit from further insights into disease progression. Furthermore, current normal tissue complication probability (NTCP) models rely on clinical experience to set tolerance doses for organs at risk and leave aside mechanistic interpretations of the undergoing processes. To these aims, we implemented a 3D agent-based model (ABM) of an alveolar duct that simulates cell dynamics and substance diffusion following radiation injury. Emphasis was placed on cell repopulation, senescent clearance, and intra/inter-alveolar bystander senescence while tracking ECM deposition. Our ABM successfully replicates early and late fibrotic response patterns reported in the literature along with the ECM sigmoidal dose-response curve. Moreover, surrogate measures of RILF severity via a custom indicator show qualitative agreement with published fibrosis indices. Finally, our ABM provides a fully mechanistic alveolar survival curve highlighting the need to include bystander damage in lung NTCP models.

Therapeutic efficacy of 166Holmium siloxane in microbrachytherapy of induced glioblastoma in minipig tumor model

Glioblastoma is considered the most common malignant primary tumor of central nervous system. In spite of the current standard and multimodal treatment, the prognosis of glioblastoma is poor. For this reason, new therapeutic approaches need to be developed to improve the survival time of the glioblastoma patient. In this study, we performed a preclinical experiment to evaluate therapeutic efficacy of 166Ho microparticle suspension administered by microbrachytherapy on a minipig glioblastoma model. Twelve minipigs were divided in 3 groups. Minipigs had injections into the tumor, containing microparticle suspensions of either 166Ho (group 1; n = 6) or 165Ho (group 2; n = 3) and control group (group 3; n = 3). The survival time from treatment to euthanasia was 66 days with a good state of health of all minipigs in group 1. The median survival time from treatment to tumor related death were 8.6 and 7.3 days in groups 2 and control, respectively. Statistically, the prolonged life of group 1 was significantly different from the two other groups (p < 0.01), and no significant difference was observed between group 2 and control (p=0.09). Our trial on the therapeutic effect of the 166Ho microparticle demonstrated an excellent efficacy in tumor control. The histological and immunohistochemical analysis showed that the efficacy was related to a severe 166Ho induced necrosis combined with an immune response due to the presence of the radioactive microparticles inside the tumors. The absence of reflux following the injections confirms the safety of the injection device.

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

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

Can dose convolution modelling explain bath and shower effects in rat spinal cord?

Objective. ‘Bath and shower’ effects were first seen in proton irradiations of rat spinal cord, where a low dose ‘bath’ reduced the smaller field ‘shower’ dose needed for limb paralysis giving the appearance of sensitisation of the cord or disproportionate response. This was difficult to reconcile with existing tissue complication models. The purpose of this investigation is to explore a different approach using a dose convolution algorithm to model the 50% isoeffect endpoint. Approach. Bath and shower dose distributions were convolved with Gaussian functions with widths specified by the σ parameter. The hypothesis was that the maximum value from the convolved distributions was constant for isoeffect across the modelled scenarios. A simpler field length dependent relative biological effectiveness (FLRBE) approach was also used for a subset of the data which gave results independent of σ. Main results. The maximum values from the convolved distributions were constant within ±17% across the bath and shower experiments for σ = 3.5 mm, whereas the maximum dose varied by a factor of four. The FLRBE results were also within ±14% confirming the validity of the dose convolution approach. Significance. A simple approach using dose convolution modelling of the 50% isotoxicity gave compelling consistency with the full range of bath and shower results, while the FLRBE approach confirmed the results for the symmetric field data. Convolution modelling and the effect of time interval were consistent with a signalling factor diffusion mechanism such as the ‘bystander effect’. The results suggest biological effectiveness is reduced for very small field sizes, requiring a higher isoeffect dose. By implication, the bath dose does not sensitise the cord to the shower dose; when biological effectiveness is accounted for, a small increase in the bath dose requires a significantly larger reduction in shower dose for isoeffect.

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.

The role of the spatially fractionated radiation therapy in the management of advanced bulky tumors

Spatially fractionated radiation therapy (SFRT) refers to the delivery of a single large dose of radiation within the target volume in a heterogeneous pattern using either a custom GRID block, multileaf collimators, and virtual methods such as helical tomotherapy or synchrotron-based microbeams. The potential impact of this technique on the regression of bulky deep-seated tumors that do not respond well to conventional radiotherapy has been remarkable. To date, a large number of patients have been treated using the SFRT techniques. However, there are yet many technical and medical challenges that have limited their routine use to a handful of clinics, most commonly for palliative intent. There is also a poor understanding of the biological mechanisms underlying the clinical efficacy of this approach. In this article, the methods of SFRT delivery together with its potential biological mechanisms are presented. Furthermore, technical challenges and clinical achievements along with the radiobiological models used to evaluate the efficacy and safety of SFRT are highlighted.

4-Methylumbelliferone administration enhances radiosensitivity of human fibrosarcoma by intercellular communication

Hyaluronan synthesis inhibitor 4-methylumbelliferone (4-MU) is a candidate of radiosensitizers which enables both anti-tumour and anti-metastasis effects in X-ray therapy. The curative effects under such 4-MU administration have been investigated in vitro; however, the radiosensitizing mechanisms remain unclear. Here, we investigated the radiosensitizing effects under 4-MU treatment from cell experiments and model estimations. We generated experimental surviving fractions of human fibrosarcoma cells (HT1080) after 4-MU treatment combined with X-ray irradiation. Meanwhilst, we also modelled the pharmacological effects of 4-MU treatment and theoretically analyzed the synergetic effects between 4-MU treatment and X-ray irradiation. The results show that the enhancement of cell killing by 4-MU treatment is the greatest in the intermediate dose range of around 4 Gy, which can be reproduced by considering intercellular communication (so called non-targeted effects) through the model analysis. As supposed to be the involvement of intercellular communication in radiosensitization, the oxidative stress level associated with reactive oxygen species (ROS), which leads to DNA damage induction, is significantly higher by the combination of 4-MU treatment and irradiation than only by X-ray irradiation, and the radiosensitization by 4-MU can be suppressed by the ROS inhibitors. These findings suggest that the synergetic effects between 4-MU treatment and irradiation are predominantly attributed to intercellular communication and provide more efficient tumour control than conventional X-ray therapy.

The Radiobiology of Radiopharmaceuticals

Radiopharmaceutical therapy or targeted radionuclide therapy (TRT) is a well-established class of cancer therapeutics that includes a growing number of FDA-approved drugs and a promising pipeline of experimental therapeutics. Radiobiology is fundamental to a mechanistic understanding of the therapeutic capacity of these agents and their potential toxicities. However, the field of radiobiology has historically focused on external beam radiation. Critical differences exist between TRT and external beam radiotherapy with respect to dosimetry, dose rate, linear energy transfer, duration of treatment delivery, fractionation, range, and target volume. These distinctions simultaneously make it difficult to extrapolate from the radiobiology of external beam radiation to that of TRT and pose considerable challenges for preclinical and clinical studies investigating TRT. Here, we discuss these challenges and explore the current understanding of the radiobiology of radiopharmaceuticals.

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.

Modelling Dose Effects from Space Irradiations: Combination of High-LET and Low-LET Radiations with a Modified Microdosimetric Kinetic Model

The Microdosimetric Kinetic Model (MKM) to predict the effects of ionizing radiation on cell colonies is studied and reformulated for the case of high-linear energy transfer (LET) radiations with a low dose. When the number of radiation events happening in a subnuclear domain follows a Poisson distribution, the MKM predicts a linear-quadratic (LQ) survival curve. We show that when few events occur, as for high-LET radiations at doses lower than the mean specific energy imparted to the nucleus, zF,n, a Poisson distribution can no longer be assumed and an initial pure linear relationship between dose and survival fraction should be observed. Predictions of survival curves for combinations of high-LET and low-LET radiations are produced under two assumptions for their comparison: independent and combined action. Survival curves from previously published articles of V79 cell colonies exposed to X-rays, α particles, Ar-ions, Fe-ions, Ne-ions and mixtures of X-rays and each one of the ions are predicted according to the modified MKM. We conclude that mixtures of high-LET and low-LET radiations may enhance the effect of individual actions due to the increase of events in domains provided by the low-LET radiation. This hypothesis is only partially validated by the analyzed experiments.

Radiation-induced bystander and abscopal effects: important lessons from preclinical models

Radiotherapy is a pivotal component in the curative treatment of patients with localised cancer and isolated metastasis, as well as being used as a palliative strategy for patients with disseminated disease. The clinical efficacy of radiotherapy has traditionally been attributed to the local effects of ionising radiation, which induces cell death by directly and indirectly inducing DNA damage, but substantial work has uncovered an unexpected and dual relationship between tumour irradiation and the host immune system. In clinical practice, it is, therefore, tempting to tailor immunotherapies with radiotherapy in order to synergise innate and adaptive immunity against cancer cells, as well as to bypass immune tolerance and exhaustion, with the aim of facilitating tumour regression. However, our understanding of how radiation impacts on immune system activation is still in its early stages, and concerns and challenges regarding therapeutic applications still need to be overcome. With the increasing use of immunotherapy and its common combination with ionising radiation, this review briefly delineates current knowledge about the non-targeted effects of radiotherapy, and aims to provide insights, at the preclinical level, into the mechanisms that are involved with the potential to yield clinically relevant combinatorial approaches of radiotherapy and immunotherapy.

Intensity Modulated Radiation Fields Induce Protective Effects and Reduce Importance of Dose-Rate Effects

In advanced radiotherapy, intensity modulated radiation fields and complex dose-delivery are utilized to prescribe higher doses to tumours. Here, we investigated the impact of modulated radiation fields on radio-sensitivity and cell recovery during dose delivery. We generated experimental survival data after single-dose, split-dose and fractionated irradiation in normal human skin fibroblast cells (AGO1522) and human prostate cancer cells (DU145). The dose was delivered to either 50% of the area of a T25 flask containing the cells (half-field) or 100% of the flask (uniform-field). We also modelled the impact of dose-rate effects and intercellular signalling on cell-killing. Applying the model to the survival data, it is found that (i) in-field cell survival under half-field exposure is higher than uniform-field exposure for the same delivered dose; (ii) the importance of sub-lethal damage repair (SLDR) in AGO1522 cells is reduced under half-field exposure; (iii) the yield of initial DNA lesions measured with half-field exposure is smaller than that with uniform-field exposure. These results suggest that increased cell survival under half-field exposure is predominantly attributed not to rescue effects (increased SLDR) but protective effects (reduced induction of initial DNA lesions). In support of these protective effects, the reduced DNA damage leads to modulation of cell-cycle dynamics, i.e., less G₁ arrest 6 h after irradiation. These findings provide a new understanding of the impact of dose-rate effects and protective effects measured after modulated field irradiation.

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.

Kinetic modeling of tumor regression incorporating the concept of cancer stem-like cells for patients with locally advanced lung cancer

Background

Personalized medicine for patients receiving radiation therapy remains an elusive goal due, in part, to the limits in our understanding of the underlying mechanisms governing tumor response to radiation. The purpose of this study was to develop a kinetic model, in the context of locally advanced lung cancer, connecting cancer cell subpopulations with tumor volumes measured during the course of radiation treatment for understanding treatment outcome for individual patients.

Methods

The kinetic model consists of three cell compartments: cancer stem-like cells (CSCs), non-stem tumor cells (TCs) and dead cells (DCs). A set of ordinary differential equations were developed to describe the time evolution of each compartment, and the analytic solution of these equations was iterated to be aligned with the day-to-day tumor volume changes during the course of radiation treatment. A least squares fitting method was used to estimate the parameters of the model that include the proportion of CSCs and their radio-sensitivities. This model was applied to five patients with stage III lung cancer, and tumor volumes were measured from 33 cone-beam computed tomography (CBCT) images for each of these patients. The analytical solution of these differential equations was compared with numerically simulated results.

Results

For the five patients with late stage lung cancer, the derived proportions of CSCs are 0.3 on average, the average probability of the symmetry division is 0.057 and the average surviving fractions of CSCs is 0.967, respectively. The derived parameters are comparable to the results from literature and our experiments. The preliminary results suggest that the CSC self-renewal rate is relatively small, compared to the proportion of CSCs for locally advanced lung cancers.

Conclusions

A novel mathematical model has been developed to connect the population of cancer stem-like cells with tumor volumes measured from a sequence of CBCT images. This model may help improve our understanding of tumor response to radiation therapy, and is valuable for development of new treatment regimens for patients with locally advanced lung cancer.

A quantitative assessment of the consequences of allowing dose heterogeneity in prostate radiation therapy planning

Target dose uniformity has been historically an aim of volumetric modulated arc therapy (VMAT) planning. However, for some sites, this may not be strictly necessary and removing this constraint could theoretically improve organ‐at‐risk (OAR) sparing and tumor control probability (TCP). This study systematically investigates the consequences of PTV dose uniformity that results from the application or removal of an upper dose constraint (UDC) in the inverse planning process for prostate VMAT treatments. OAR sparing, target coverage, hotspots, and plan complexity were compared between prostate VMAT plans with and without the PTV UDC optimized using the progressive resolution optimizer (PRO, Varian Medical Systems, Palo Alto, CA). Removing the PTV UDC, the median D1cc reached 144.6% for the CTV and the PTV, and an average increase of 3.2% TCP was demonstrated, while CTV and PTV coverage evaluated by D99% was decreased by less than 0.6% with statistical significance. Moreover, systematic improvement in the rectum dose volume histograms was shown (a 5–10% decrease in the volume receiving 50% to 75% prescribed dose), resulting in an average decrease of 1.3% (P < 0.01) in the rectum normal tissue complication probability. Additional consequences included potentially increased dose to the urethra as evaluated by PTV D0.035cc (median: 153.4%), delivering 283 extra monitor units (MUs), and slightly higher degrees of modulation. In general, the results were consistent when a different optimizer (Photon Optimizer, Varian Medical Systems) was used. In conclusion, removing the PTV UDC is acceptable for localized prostate cases given the systematic improvement of rectal dose and TCP. It can be particularly useful for cases that do not meet the rectum dose constraints with the PTV UDC on. This comes with the foreseeable consequences of increased dose heterogeneity in the PTV and an increase in MUs and plan complexity. It also has a higher requirement for reproducing the position and size of the target and OARs during treatment. Finally, with the PTV UDC completely removed, in some cases the maximum doses within the PTV did approach levels that may be of concern for urethral toxicity and therefore in clinical implementation it may still be necessary to include a PTV UDC, but one based on limiting toxicity rather than enforcing dose homogeneity.

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.

Integrated Modelling of Cell Responses after Irradiation for DNA-Targeted Effects and Non-Targeted Effects

Intercellular communication after ionizing radiation exposure, so-called non-targeted effects (NTEs), reduces cell survival. Here we describe an integrated cell-killing model considering NTEs and DNA damage along radiation particle tracks, known as DNA-targeted effects (TEs) based on repair kinetics of DNA damage. The proposed model was applied to a series of experimental data, i.e., signal concentration, DNA damage kinetics, cell survival curve and medium transfer bystander effects (MTBEs). To reproduce the experimental data, the model considers the following assumptions: (i) the linear-quadratic (LQ) function as absorbed dose to express the hit probability to emit cell-killing signals, (ii) the potentially repair of DNA lesions induced by NTEs, and (iii) lower efficiency of repair for the damage in NTEs than that in TEs. By comparing the model results with experimental data, we found that signal-induced DNA damage and lower repair efficiency in non-hit cells are responsible for NTE-related repair kinetics of DNA damage, cell survival curve with low-dose hyper-radiosensitivity (HRS) and MTBEs. From the standpoint of modelling, the integrated cell-killing model with the LQ relation and a different repair function for NTEs provide a reasonable signal-emission probability and a new estimation of low-dose HRS linked to DNA repair efficiency.

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.

A reaction-diffusion model for radiation-induced bystander effects

We develop and analyze a reaction-diffusion model to investigate the dynamics of the lifespan of a bystander signal emitted when cells are exposed to radiation. Experimental studies by Mothersill and Seymour 1997, using malignant epithelial cell lines, found that an emitted bystander signal can still cause bystander effects in cells even 60 h after its emission. Several other experiments have also shown that the signal can persist for months and even years. Also, bystander effects have been hypothesized as one of the factors responsible for the phenomenon of low-dose hyper-radiosensitivity and increased radioresistance (HRS/IRR). Here, we confirm this hypothesis with a mathematical model, which we fit to Joiner's data on HRS/IRR in a T98G glioma cell line. Furthermore, we use phase plane analysis to understand the full dynamics of the signal's lifespan. We find that both single and multiple radiation exposure can lead to bystander signals that either persist temporarily or permanently. We also found that, in an heterogeneous environment, the size of the domain exposed to radiation and the number of radiation exposures can determine whether a signal will persist temporarily or permanently. Finally, we use sensitivity analysis to identify those cell parameters that affect the signal's lifespan and the signal-induced cell death the most.

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.

Dose enhancement effects to the nucleus and mitochondria from gold nanoparticles in the cytosol

Gold nanoparticles (GNPs) have shown potential as dose enhancers for radiation therapy. Since damage to the genome affects the viability of a cell, it is generally assumed that GNPs have to localise within the cell nucleus. In practice, however, GNPs tend to localise in the cytoplasm yet still appear to have a dose enhancing effect on the cell. Whether this effect can be attributed to stress-induced biological mechanisms or to physical damage to extra-nuclear cellular targets is still unclear. There is however growing evidence to suggest that the cellular response to radiation can also be influenced by indirect processes induced when the nucleus is not directly targeted by radiation. The mitochondrion in particular may be an effective extra-nuclear radiation target given its many important functional roles in the cell. To more accurately predict the physical effect of radiation within different cell organelles, we measured the full chemical composition of a whole human lymphocytic JURKAT cell as well as two separate organelles; the cell nucleus and the mitochondrion. The experimental measurements found that all three biological materials had similar ionisation energies  ∼70 eV, substantially lower than that of liquid water  ∼78 eV. Monte Carlo simulations for 10-50 keV incident photons showed higher energy deposition and ionisation numbers in the cell and organelle materials compared to liquid water. Adding a 1% mass fraction of gold to each material increased the energy deposition by a factor of  ∼1.8 when averaged over all incident photon energies. Simulations of a realistic compartmentalised cell show that the presence of gold in the cytosol increases the energy deposition in the mitochondrial volume more than within the nuclear volume. We find this is due to sub-micron delocalisation of energy by photoelectrons, making the mitochondria a potentially viable indirect radiation target for GNPs that localise to the cytosol.

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.

Systemic mechanisms and effects of ionizing radiation: A new 'old' paradigm of how the bystanders and distant can become the players

Exposure of cells to any form of ionizing radiation (IR) is expected to induce a variety of DNA lesions, including double strand breaks (DSBs), single strand breaks (SSBs) and oxidized bases, as well as loss of bases, i.e., abasic sites. The damaging potential of IR is primarily related to the generation of electrons, which through their interaction with water produce free radicals. In their turn, free radicals attack DNA, proteins and lipids. Damage is induced also through direct deposition of energy. These types of IR interactions with biological materials are collectively called 'targeted effects', since they refer only to the irradiated cells. Earlier and sometimes 'anecdotal' findings were pointing to the possibility of IR actions unrelated to the irradiated cells or area, i.e., a type of systemic response with unknown mechanistic basis. Over the last years, significant experimental evidence has accumulated, showing a variety of radiation effects for 'out-of-field' areas (non-targeted effects-NTE). The NTE involve the release of chemical and biological mediators from the 'in-field' area and thus the communication of the radiation insult via the so called 'danger' signals. The NTE can be separated in two major groups: bystander and distant (systemic). In this review, we have collected a detailed list of proteins implicated in either bystander or systemic effects, including the clinically relevant abscopal phenomenon, using improved text-mining and bioinformatics tools from the literature. We have identified which of these genes belong to the DNA damage response and repair pathway (DDR/R) and made protein-protein interaction (PPi) networks. Our analysis supports that the apoptosis, TLR-like and NOD-like receptor signaling pathways are the main pathways participating in NTE. Based on this analysis, we formulate a biophysical hypothesis for the regulation of NTE, based on DNA damage and apoptosis gradients between the irradiation point and various distances corresponding to bystander (5mm) or distant effects (5cm). Last but not least, in order to provide a more realistic support for our model, we calculate the expected DSB and non-DSB clusters along the central axis of a representative 200.6MeV pencil beam calculated using Monte Carlo DNA damage simulation software (MCDS) based on the actual beam energy-to-depth curves used in therapy.

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.

Mechanistic modelling of radiation-induced bystander effects

A model of radiation-induced bystander effects is presented that explicitly takes into account the transient nature of bystander signal emission post-irradiation, signal lifetime and the non-linear cellular response to the signals. Data are analysed on mutagenesis induced in human lymphoblasts in medium transfer experiments, in which the signal build-up time, medium dilution and the duration of reporter cells' exposure to the medium were varied. The model implies that the cellular release of bystander signals decreases rather slowly, with a characteristic time of about a day, whereas the signal itself decays with a lifetime of about an hour.

Model assembly for estimating cell surviving fraction for both targeted and nontargeted effects based on microdosimetric probability densities

We here propose a new model assembly for estimating the surviving fraction of cells irradiated with various types of ionizing radiation, considering both targeted and nontargeted effects in the same framework. The probability densities of specific energies in two scales, which are the cell nucleus and its substructure called a domain, were employed as the physical index for characterizing the radiation fields. In the model assembly, our previously established double stochastic microdosimetric kinetic (DSMK) model was used to express the targeted effect, whereas a newly developed model was used to express the nontargeted effect. The radioresistance caused by overexpression of anti-apoptotic protein Bcl-2 known to frequently occur in human cancer was also considered by introducing the concept of the adaptive response in the DSMK model. The accuracy of the model assembly was examined by comparing the computationally and experimentally determined surviving fraction of Bcl-2 cells (Bcl-2 overexpressing HeLa cells) and Neo cells (neomycin resistant gene-expressing HeLa cells) irradiated with microbeam or broadbeam of energetic heavy ions, as well as the WI-38 normal human fibroblasts irradiated with X-ray microbeam. The model assembly reproduced very well the experimentally determined surviving fraction over a wide range of dose and linear energy transfer (LET) values. Our newly established model assembly will be worth being incorporated into treatment planning systems for heavy-ion therapy, brachytherapy, and boron neutron capture therapy, given critical roles of the frequent Bcl-2 overexpression and the nontargeted effect in estimating therapeutic outcomes and harmful effects of such advanced therapeutic modalities.

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.

The role of TGF-β1-miR-21-ROS pathway in bystander responses induced by irradiated non-small-cell lung cancer cells

Background:

Many studies have indicated an important implication of radiation-induced bystander effects (RIBEs) in cancer radiotherapy, but the detailed signalling remains unclear.

Methods:

The roles of tumour growth factor-beta1 (TGF-β1) and miR-21 in medium-mediated RIBEs in H1299 non-small-cell lung cancer cells were investigated using DNA damage, changes in proliferation and levels of reactive oxygen species (ROS) as end points. SB431542, a specific inhibitor of TGF-β type 1 receptor kinases, was used to inhibit TGF-β1 pathways in irradiated and bystander cells. Exogenous miR-21 regulation was achieved through inhibitor or mimic transfection.

Results:

Compared with relative sham-radiation-conditioned medium, radiation-conditioned medium (RCM) from irradiated cells 1 h post radiation (1-h RCM) caused an increase in ROS levels and DNA damage in bystander cells, while 18-h RCM induced cell cycle delay and proliferation inhibition. All these effects were eliminated by TGF-βR1 inhibition. One-hour RCM upregulated miR-21 expression in bystander cells, and miR-21 inhibitor abolished bystander oxidative stress and DNA damage. Eighteen-hour RCM downregulated miR-21 of bystander cells, and miR-21 mimic eliminated bystander proliferation inhibition. Furthermore, the dysregulation of miR-21 was attenuated by TGF-βR1 inhibition.

Conclusions:

The TGF-β1–miR-21–ROS pathway of bystander cells has an important mediating role in RIBEs in H1299 cells.

Microdosimetric analysis confirms similar biological effectiveness of external exposure to gamma-rays and internal exposure to 137Cs, 134Cs, and 131I

The risk of internal exposure to 137Cs, 134Cs, and 131I is of great public concern after the accident at the Fukushima-Daiichi nuclear power plant. The relative biological effectiveness (RBE, defined herein as effectiveness of internal exposure relative to the external exposure to γ-rays) is occasionally believed to be much greater than unity due to insufficient discussions on the difference of their microdosimetric profiles. We therefore performed a Monte Carlo particle transport simulation in ideally aligned cell systems to calculate the probability densities of absorbed doses in subcellular and intranuclear scales for internal exposures to electrons emitted from 137Cs, 134Cs, and 131I, as well as the external exposure to 662 keV photons. The RBE due to the inhomogeneous radioactive isotope (RI) distribution in subcellular structures and the high ionization density around the particle trajectories was then derived from the calculated microdosimetric probability density. The RBE for the bystander effect was also estimated from the probability density, considering its non-linear dose response. The RBE due to the high ionization density and that for the bystander effect were very close to 1, because the microdosimetric probability densities were nearly identical between the internal exposures and the external exposure from the 662 keV photons. On the other hand, the RBE due to the RI inhomogeneity largely depended on the intranuclear RI concentration and cell size, but their maximum possible RBE was only 1.04 even under conservative assumptions. Thus, it can be concluded from the microdosimetric viewpoint that the risk from internal exposures to 137Cs, 134Cs, and 131I should be nearly equivalent to that of external exposure to γ-rays at the same absorbed dose level, as suggested in the current recommendations of the International Commission on Radiological Protection.

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.

Low dose effects of ionizing radiation on normal tissue stem cells

In recent years, there has been growing evidence for the involvement of stem cells in cancer initiation. As a result of their long life span, stem cells may have an increased propensity to accumulate genetic damage relative to differentiated cells. Therefore, stem cells of normal tissues may be important targets for radiation-induced carcinogenesis. Knowledge of the effects of ionizing radiation (IR) on normal stem cells and on the processes involved in carcinogenesis is very limited. The influence of high doses of IR (>5Gy) on proliferation, cell cycle and induction of senescence has been demonstrated in stem cells. There have been limited studies of the effects of moderate (0.5-5Gy) and low doses (<0.5Gy) of IR on stem cells however, the effect of low dose IR (LD-IR) on normal stem cells as possible targets for radiation-induced carcinogenesis has not been studied in any depth. There may also be important parallels between stem cell responses and those of cancer stem cells, which may highlight potential key common mechanisms of their response and radiosensitivity. This review will provide an overview of the current knowledge of radiation-induced effects on normal stem cells, with particular focus on low and moderate doses of IR.

The biological effect of large single doses: a possible role for non-targeted effects in cell inactivation

BACKGROUND AND PURPOSE

Novel radiotherapy techniques increasingly use very large dose fractions. It has been argued that the biological effect of large dose fractions may differ from that of conventional fraction sizes. The purpose was to study the biological effect of large single doses.

MATERIAL AND METHODS

Clonogenic cell survival of MCF7 and MDA-MB-231 cells was determined after direct X-ray irradiation, irradiation of feeder cells, or transfer of conditioned medium (CM). Cell-cycle distributions and the apoptotic sub-G1 fraction were measured by flow cytometry. Cytokines in CM were quantified by a cytokine antibody array. γH2AX foci were detected by immunofluorescence microscopy.

RESULTS

The surviving fraction of MCF7 cells irradiated in vitro with 12 Gy showed an 8.5-fold decrease (95% c.i.: 4.4-16.3; P<0.0001) when the density of irradiated cells was increased from 10 to 50×10(3) cells per flask. Part of this effect was due to a dose-dependent transferrable factor as shown in CM experiments in the dose range 5-15 Gy. While no effect on apoptosis and cell cycle distribution was observed, and no differentially expressed cytokine could be identified, the transferable factor induced prolonged expression of γH2AX DNA repair foci at 1-12 h.

CONCLUSIONS

A dose-dependent non-targeted effect on clonogenic cell survival was found in the dose range 5-15 Gy. The dependence of SF on cell numbers at high doses would represent a "cohort effect" in vivo. These results support the hypothesis that non-targeted effects may contribute to the efficacy of very large dose fractions in radiotherapy.

High dose bystander effects in spatially fractionated radiation therapy

Traditional radiotherapy of bulky tumors has certain limitations. Spatially fractionated radiation therapy (GRID) and intensity modulated radiotherapy (IMRT) are examples of advanced modulated beam therapies that help in significant reductions in normal tissue damage. GRID refers to the delivery of a single high dose of radiation to a large treatment area that is divided into several smaller fields, while IMRT allows improved dose conformity to the tumor target compared to conventional three-dimensional conformal radiotherapy. In this review, we consider spatially fractionated radiotherapy approaches focusing on GRID and IMRT, and present complementary evidence from different studies which support the role of radiation induced signaling effects in the overall radiobiological rationale for these treatments.