There is an ongoing debate on the therapeutic potential of vaso-modulatory interventions against glioma invasion. Prominent vasculature-targeting therapies involve tumour blood vessel deterioration and normalisation. The former aims at tumour infarction and nutrient deprivation induced by blood vessel occlusion/collapse. In contrast, the therapeutic intention of normalising the abnormal tumour vasculature is to improve the efficacy of conventional treatment modalities. Although these strategies have shown therapeutic potential, it remains unclear why they both often fail to control glioma growth. To shed some light on this issue, we propose a mathematical model based on the migration/proliferation dichotomy of glioma cells in order to investigate why vaso-modulatory interventions have shown limited success in terms of tumour clearance. We found the existence of a critical cell proliferation/diffusion ratio that separates glioma responses to vaso-modulatory interventions into two distinct regimes. While for tumours, belonging to one regime, vascular modulations reduce the front speed and increase the infiltration width, for those in the other regime, the invasion speed increases and infiltration width decreases. We discuss how these  Gliomas are aggressive brain tumours typically associated with poor prognosis, sharp deterioration in the patients’ quality of life and low survival rates, making this disease challenging to treat. According to the World Health Organization (WHO)245The influence of the microenvironment on glioma cell behaviour plays a crucial role in the resulting diffusive tumour growth and its invasive capacity. Hypoxia, the presence of abnormal and sustained low oxygen levels in the tumour tissue, strongly correlates with glioma invasiveness and malignancy89104101213A particularly important component of the tumour microenvironment is the vascular network. Accumulating evidence suggests the existence of various positive and negative feedback mechanisms between glioma cells and the vasculature. Indeed, gliomas are reported as highly vascularised neoplasias15171921192021The high degree of angiogenesis and vascular pathologies observed in gliomas has been the target of several therapeutic vaso-modulatory strategies24262724303128303324Mathematical modelling has the potential to improve our understanding of the complex biology of gliomas and their interactions with the microenvironment, as well as it may help in the design of more effective and personalised treatment strategies353637383940414216384445464748495051525455444546471638ρ and functional tumour vasculature v, as well as the concentrations of oxygen σ and pro-angiogenic factors a in the tumour microenvironment, where d is the dimension of the system. We develop a mathematical model that describes the growth of vascularised gliomas focusing on the interplay between the migration/proliferation dichotomy and vaso-occlusion at the margin of viable tumour tissue. The system variables are the density of glioma cells [A1] Glioma cells switch phenotypes between proliferative (normoxic) and migratory (hypoxic) depending on the oxygen concentration in the tumour microenvironment4101213[A2] Under hypoxia conditions glioma cells secrete pro-angiogenic factors151718[A3] Pro-angiogenic factors trigger the formation of blood vessels and regulate vasculature remodelling18[A4] Endothelial cells forming the vascular network uptake pro-angiogenic factors18[A5] Functional tumour blood vessels releases oxygen1517[A6] Oxygen is essential for glioma growth and progression1718[A7] Glioma cells consume oxygen provided by the functional vasculature17[A8] Prothrombotic factors and increased mechanical pressure in regions of high glioma cell density induce blood vessel occlusion and collapse192358ρ1 and proliferative (normoxic) ρ2, depending on the concentration of oxygen in the tumour microenvironment σ. More precisely, we consider two linear switching functions, f21(σ) = λ1 − σ and f12(σ) = λ2σ, that represent the rate at which glioma cells change from migratory to proliferative and vice versa, respectively. Although there is experimental evidence of a positive correlation between oxygen availability and cell proliferation, the exact functional form of the oxygen-dependent phenotypic switching remains unknown. Accordingly, we consider the simplest case, i.e. a linear switching between proliferative and migratory phenotypes, in line with previous studies61λ1 and λ2 are positive constants, see the Based on the migration/proliferation dichotomy4101213Cell motility is modelled as a diffusive process mimicking the net infiltration of glioma cells into the surrounding brain tissue, while a logistic growth term is considered for tumour cell proliferation. The system of equations for the migratory and proliferative glioma cells is given byt and spatial x coordinates in the arguments of variables have been omitted for notational simplicity. Dρ and bρ are the diffusion and proliferation coefficients of migratory and proliferative glioma cells, respectively. N represents the brain tissue carrying capacity, i.e. the maximum number of cells that can be supported by the environment. The parameters Dρ, bρ and N are positive constants.where the temporal ρ = ρ1 + ρ2 by assuming that f12(σ)ρ1 = f21(σ)ρ2. This is a plausible assumption since intracellular processes, such as signalling pathways regulating the phenotypic switch, operate at much shorter time scales than cell migration and proliferation. Thus, we assume that phenotype switching is a mechanism faster compared to cell division and motility, which allows to express ρ1 and ρ2 as a function of ρ in the following formThe system (1)-(2) can be reduced to a single equation for the total density of glioma cells where we have thatandρ1 and ρ2, the equation for the total density of (migratory and proliferative) glioma cells ρ is given bySumming equations  and 2),,2), and α(σ) and β(σ) are defined as followswhere the oxygen-dependent functions andα(σ) + β(σ) = 1, we can rewrite Then, taking into account that α(σ) and β(σ) in σ0 > 0 be the physiological oxygen concentration in the normal brain tissue. Then, by normalising Dρ = D/α(σ0) and bρ = b/β(σ0) the classical Fisher-Kolmogorov equation is recovered under the assumption of a constant oxygen concentration in the tumour microenvironment, given byNotice that 55D and b are positive parameters that represents the intrinsic diffusion and proliferation rates of glioma cells, respectively. We remark that, 164955where v. We further consider that pro-angiogenic factors are exclusively produced by glioma cells under hypoxic conditions at a rate proportional to the tumour cell density, and therefore neglecting hypoxia-independent pathways. In addition, endothelial cells forming the vascular network uptake pro-angiogenic factors which also undergo natural decay. The equation for the effective pro-angiogenic factor concentration a is given byNeovascularisation in tumours takes place when pro-angiogenic factors overcome anti-angiogenic stimuli. However, in gliomas there is evidence of a wide range of pro- and anti-angiogenic factors involved, each of them acting through different vascularisation mechanisms1524t and spatial x coordinates in the arguments of variables have been omitted for notational simplicity. Da is the diffusion coefficient of pro-angiogenic factors. Assuming the quasi-steady state approximation of where the temporal k1, k2 and k3 represent the production, consumption and natural decay rates of pro-angiogenic factors, respectively, where H(ξ), defined as H(ξ) = 1 if ξ ≤ 0 and H(ξ) = 0 if ξ > 0, given byThe positive parameters θ is a positive parameter that controls the steepness of σ is lower than the hypoxic oxygen threshold where v = 1/2. Thus, the limit case v = 0 represents an avascular tissue, while on the contrary v = 1 describes a hypothetical scenario characterised by excessive vascularisation.Histopathological studies have shown that the vascular structure and function in brain tumours is markedly abnormal1718a > 0, leading to the formation of new functional vasculature according to a logistic growth term. The rate at which functional tumour vasculature is generated follows the Michaelis-Menten kinetics depending on the pro-angiogenic factor concentration, where a constant dispersal rate of endothelial cells (vasculature) is assumed. Notice that the Michaelis-Menten term is commonly used to model a saturating response at high doses in biological systems22631923v is given byBlood vessels in gliomas are not stable, being continuously formed, occluded and destroyed. Neovascularisation takes place by different angiogenic and vasculogenic processes induced by complex signalling mechanisms that are not well understood1166t and spatial x coordinates in the arguments of variables have been omitted for notational simplicity. Dv is the diffusion coefficient representing the net dispersal of tumour vasculature, g1 is the formation rate of functional blood vessels, μ is the pro-angiogenic factor concentration at which g1 is half-maximal, g2 is the vaso-occlusion rate and n is a parameter that regulates the degree of blood vessel occlusion depending on the density of glioma cells. The vaso-occlusion term, g2vρn, models the mechanical pressure exerted on blood vessels in regions of high glioma cell density, see the 32N/2, where N is the brain tissue carrying capacityDv, g1, μ, g2 and n are positive constants.where again the temporal a is much smaller than the uptake/internalisation rate by endothelial cells, i.e. k3 ≪ k270Plugging K = μk2/k1 represents the concentration of pro-angiogenic factors at which the formation rate of functional tumour vasculature is half-maximal, see the where σ0 and that in the tumour interstitium. These assumptions result in the equation for the oxygen concentration σ given byOxygen is delivered to the brain tissue via functional blood vessels, spreads into the tumour bulk and is consumed by glioma cells. Transport of oxygen within tissues occurs by diffusion and convectiont and spatial x coordinates in the arguments of variables have been omitted for notational simplicity. Dσ is the oxygen diffusion coefficient, h1 is the permeability coefficient of functional vasculature and h2 is the oxygen consumption rate by glioma cells. The parameters Dσ, h1, σ0 and h2 are positive constants. Notice that similar assumptions have been previously considered to model oxygen dynamics in vascular tumour growthwhere the temporal The proposed glioma-vasculature interplay model comprises a system of coupled partial differential equations given byα(σ) and β(σ) are given by equations (where the oxygen-dependent functions quations –5), res, resα(σ)ρ0, σ0 and v0 are the initial density of glioma cells spatially distributed in a segment of length ε, the density of functional tumour vasculature and the oxygen concentration, respectively. The positive parameter γ controls the steepness of x − ε) with ε > 0, and L > 0 is the length of the one-dimensional computational domain. In addition, we consider an isolated host tissue in which all system behaviours arise solely due to the interaction terms in where the positive parameters Tf > 0 is an arbitrary simulation time, i.e. the end of simulations. The conditions above also imply that no cell or molecule leaves the system through the domain boundaries.where Model III, is a generalisation of two simpler models which are also of interest for the study of glioma growth and invasion. As shown in v = v0 (Model II), and also a constant oxygen concentration σ = σ0 (Model I). More precisely, Model II is obtained from Model III by setting g1 = g2 = 0 in Model I is obtained from Model II by setting h2 = 0 in The glioma-vasculature interplay model (14)–(16) referred to as Model I corresponds to the classical Fisher-Kolmogorov 55Model II given by Model II is assumed constant, the blood perfusion can be considered stable and we therefore neglect tumour-induced vascular pathologies. The latter is a reasonable assumption, particularly for low-grade gliomas, where an abnormal vascular structure is not prominentModel II is to consider tumour-associated vascularisation dynamics. This is precisely what defines Model III, which is used to investigate the effects of vaso-modulatory interventions on glioma invasion. Taking into account that Model I has been extensively studied, we begin with the analysis of Model II as an intermediate step towards analysing Model III, see ρ at the end of simulations Tf. In turn, the infiltration width is defined by the difference between the points where glioma cell density is 80% and 2% of the maximum cellular density at simulation time Tf. These specific features of tumour invasion have been reported crucial to determine glioma malignancy and predict therapeutic failure1650We characterise glioma invasion by the tumour front speed and infiltration width, see D and proliferation b rates from the effective rates that depend on the oxygen concentration in the tumour microenvironment. The effective diffusion Deff and proliferation beff rates of glioma cells are defined as followsUnlike the classical Fisher-Kolmogorov andL is the length of the one-dimensional domain of simulation. Notice that Dρ = D/α(σ0) and bρ = b/β(σ0), where D and b are the intrinsic glioma cell diffusion and proliferation rates, respectively. We then investigate the dependence of Deff and beff, as well as the tumour front speed and infiltration width, at simulation time Tf on different values of parameters h2 (glioma cell oxygen consumption) and g2 (vaso-occlusion).where Parameter values considered in the model simulations are taken from published data wherever possible or estimated to approximate physiologic conditions based on appropriate physical and biological arguments, see Deff and proliferation beff rates defined in equations (D and b. Model simulations in The proposed glioma-vasculature interplay model 14)–(16) is first considered to investigate the effects of variations in the tumour cell oxygen consumption and vaso-occlusion rates on the effective invasive behaviour of gliomas. –(16) is quations  and 18)Deff and h2 or vaso-occlusion g2 results in more diffusive and less proliferative tumours. The model supports that at high h2 and g2 values, the oxygen concentration in the tumour microenvironment significantly decreases, which may result in hypoxia and necrosis. The lack of oxygen limits the proliferative capacity of glioma cells, and in turn enhances the hypoxia-induced cell migration to better-oxygenated brain tissue areas. In particular, variations in the cell oxygen consumption and vaso-occlusion rates are predicted to have a major impact on highly infiltrative and/or rapidly growing gliomas. Thus, the precise way in which such cellular and microenviromental changes affect the overall invasive potential of tumours can be expected to depend on the specific intrinsic glioma cell features.Comparative simulation maps in D and b. In particular, these properties of tumour invasion are determined by a non-linear relationship between the effective diffusion Deff and proliferation beff rates of glioma cells. For instance, in the simplest model corresponding to the classical Fisher-Kolmogorov equation (Model I), the tumour front speed is proportional to Model II, i.e. under the assumption of a constant density of functional tumour vasculature, reveals that variations in the rate at which glioma cells consume oxygen h2 produce opposing effects on the tumour front speed. More precisely, b* for which the front speed in tumours characterised by b > b* decreases at higher values of h2, while on the contrary tumours with b < b* invade faster displaying diffusely infiltrative growth patterns. Assuming that the tumour front speed is proportional to the product of effective diffusion and proliferation rates, we can readily explain the aforementioned simulation results for variations of h2. On one hand, in tumours with glioma cell proliferation rates b above the critical threshold b*, the effective migration and proliferation mechanisms compensate each other, leaving almost-invariant the speed of the invading front. On the other hand, in the cases of tumours with b < b*, while the effective proliferation rate is not significantly affected, the migratory activity of glioma cells is higher for increasing values of h2, which results in faster tumour front propagation speeds.Analysis of the The flatness/steepness of the tumour front is proportional to a ratio of effective glioma cell diffusion and proliferation rates. When oxygen in the microenvironment is not limited, highly diffusive tumours evolve with large and flat fronts, whereas increased glioma cell proliferation results in short and steep fronts. However, under oxygen-limiting conditions the shape of the evolving tumour front is markedly influenced by the specific rate at which glioma cells consume oxygen. Model III reveal that for increasing vaso-occlusion rates g2, the tumour front speed is differently affected depending on the intrinsic diffusion and proliferation rates of glioma cells. In addition to the modulatory effects of oxygen availability on glioma growth and invasion, these processes are also influenced by vascularisation mechanisms. Comparative simulation maps in D and b inside a region delimited by a critical rate b+ and an approximate ratio between diffusion and proliferation rates Λ+ = b/D, the invading front moves faster as g2 increases. Besides, the front speed slightly decreases or remains almost constant in the rest of tumours, i.e. with parameter values of D and b outside of such region. In particular, tumours characterised by b < b+ evolve at low cellular density and thus vascular occlusive events due to increased mechanical pressure by glioma cells hardly occur. On the other hand, increasing vaso-occlusion rates in tumours with b > b+ enhances the effective cell migration towards better vascularised brain tissue regions. Although vascular occlusion limits the proliferative activity of glioma cells, faster tumour front speeds are predicted as long as the triggered migratory activity dominates over cell proliferation.Simulations of the b < b+ is almost unaffected for increasing vaso-occlusion rates as shown in b > b+ are also separated by an approximated linear relation between D and b with respect to variations in the infiltration width. In particular, more occlusion of the blood vessel results in larger flat fronts in tumours with cell proliferation/diffusion ratios above the critical value Λ+ for b > b+, while the infiltration width is reduced in the rest of tumours.The infiltration width in tumours with In this work, we proposed a deterministic mathematical model of glioma growth and invasion that is formulated as a system of reaction-diffusion partial differential equations. Our glioma-vasculature interplay model accounts for the dynamics of normoxic and hypoxic glioma cells based on the Go-or-Grow mechanism which is in turn influenced by the functional tumour vasculature and the concentration of oxygen in the microenvironment. In particular, we focused on the effect of variations in the glioma cell oxygen consumption and vascular occlusion on prognostically-relevant characteristics of tumour invasion, i.e. the front speed and infiltration width. The main model results are summarised in The model analysis revealed that increasing glioma cell oxygen consumption and vaso-occlusion rates results in more diffusive and less proliferative tumours. In both scenarios, the average oxygen concentration in the tumour microenvironment decreases, which limits glioma cell proliferation and enhances hypoxia-induced migration. This is in line with previous clinical and histopathological observations that hypoxia strongly correlates with glioma malignancy192021Model I) critical behaviours are not observed. Assuming or not tumour vascularisation dynamics, the Go-or-Grow induced criticality is expressed either in the form of a proliferation/diffusion ratio Λ+ = b/D for b > b+ or a critical proliferation rate b* of glioma cells, respectively. More precisely, the critical thresholds b* and Λ+ for b > b+ separate tumour behaviours in regimes where the front speed and infiltration width are differently affected by changes in the glioma cell oxygen consumption and vaso-occlusion rates. These findings highlight the importance of further investigating the therapeutic potential of targeting the Go-or-Grow phenomenon as a strategy to reduce glioma cell migration. Based on our model results, we can argue that one-size-fits-all vaso-modulatory interventions should be expected to fail to control glioma invasion due to the complexity of the mechanisms involved and inter-patient heterogeneity. This study supports the value of personalised medicine and provides a simplified, but useful modelling framework with predictive potential based on a precise tumour profiling from possible biopsy measurements and medical imaging. In particular, patient-based estimation of tumour cell proliferation and diffusion rates would be crucial components of such future tailored approaches to individualise treatment selection for glioma patients.Recently, it has been shown that the migration/proliferation dichotomy can introduce a critical threshold on the glioma cell density that separates tumour growth and extinction dynamics, a phenomenon called Allee effect+ = b/D for b > b+, a pro-thrombotic or an anti-vasogenic therapeutic technique may reduce the tumour front speed but at the same time leads to highly infiltrative behaviours, which makes this treatment strategy rather inappropriate. However, normalisation of the tumour blood vessels may result in faster growing gliomas with compact, less invasive morphologies. Thus, surgical resection could be considered to remove such compact tumours. In turn, the benefits of conventional treatment modalities such as chemo-, radio- and immunotherapy might significantly increase in well-vascularised and therefore normally oxygenated tumours243031We believe that this work substantially expands the theoretical concepts of the invasive behavior of gliomas, suggesting that any vasculature-targeting therapeutic intervention will inevitably lead to a trade-off between the tumour front speed and infiltration width. This result suggests that vaso-modulatory interventions should be embedded in a personalised combination of different treatment protocols, in which anti-angiogenesis might be integrated with individually adjusted strategies targeting cell proliferation, metabolic transformation or immune responses. For instance, in the case of gliomas characterised by a cell proliferation/diffusion ratio above Λin silico findings provide new insights into the impact of functional vascular changes on glioma invasion. Furthermore, the migration/proliferation dichotomy of glioma cells has been modelled in the simplest possible way and more informed formulations depending on other tumour-related factors should be considered. In turn, intratumoral genetic diversity is not directly considered, but instead we take into account phenotypic diversity depending on oxygen availability, which has long been recognized as an important therapeutic factor. The latter is supported by evidence that genetic diversity is tumour-subtype specific and not significantly affected during treatment, while phenotypic heterogeneity is significantly different before and after therapy42We conclude by pointing out a number of related future research directions, as well as discussing some limitations of this work. Although in our model the vaso-occlusion term in How to cite this article: Alfonso, J. C. L. et al. Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights. Sci. Rep.6, 37283; doi: 10.1038/srep37283 (2016).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Neuroblastoma has one of the lowest survival rates of all childhood cancers, despite the use of intensive treatment regimens. Preclinical models of neuroblastoma are essential for testing new multimodality protocols, including those that involve radiotherapy (RT). The aim of this study was to develop a robust method for RT planning and tumour response monitoring based on combined MRI and cone-beam CT (CBCT) imaging and to apply it to a widely studied mouse xenograft model of neuroblastoma, SK-N-SH.n = 8) were placed in a printed MR- and CT-compatible plastic cradle, imaged using a 4.7-T MRI scanner and then transferred to a small animal radiation research platform (SARRP) irradiator with on-board CBCT. MRI/CBCT co-registration was performed to enable RT planning using the soft-tissue contrast afforded by MRI prior to delivery of RT (5 Gy). Tumour response was assessed by serial MRI and calliper measurements.As part of a tumour growth inhibition study, SK-N-SH xenografts were generated in BALB/c nu/nu mice. Mice (SK-N-SH xenografts formed soft, deformable tumours that could not be differentiated from surrounding normal tissues using CBCT. MR images, which allowed clear delineation of tumours, were successfully co-registered with CBCT images, allowing conformal RT to be delivered. MRI measurements of tumour volume 4 days after RT correlated strongly with length of survival time.MRI allowed precision RT of SK-N-SH tumours and provided an accurate means of measuring tumour response.MRI-based RT planning of murine tumours is feasible using an SARRP irradiator. Xenograft mouse models are frequently used to study the effects of anticancer drugs and RT in vivo, and the SK-N-SH human neuroblastoma model has been widely studied for this purpose.3 The aim of this short communication was to present a method for MRI-guided RT of SK-N-SH xenografts and to track post-treatment changes using MRI and using techniques previously developed for the delivery of RT to pancreatic tumours.4 This method development study involved eight mice that were a subgroup of animals used in a larger therapy study (to be reported separately).Neuroblastoma is the most frequent extracranial tumour in infants and young children. The treatment of high-risk neuroblastoma usually consists of some mix of surgery, chemotherapy, radiotherapy (RT), stem cell transplant, immunotherapy and retinoid therapy.−1 penicillin/streptomycin .The SK-N-SH human neuroblastoma cell line was obtained from American Type Culture Collections  and cultured in Dulbecco's Modified Eagle Medium  supplemented with 10% foetal calf serum , 2-mM glutamine  and 100-U ml6) in 100 µl of matrigel were injected subcutaneously into the flanks of non-obese diabetic/severe combined immunodeficiency mice . In this mouse strain, which is profoundly immunodeficient and is therefore an excellent recipient for engrafted human cells, the success rate of xenograft development was 100%. Tumours were excised and homogenized when they reached a geometric mean diameter of 10 mm (at approximately 5 weeks). Tumour homogenates were then injected into the right flank of recipient BALB/c nu/nu mice . Following this procedure, the proportion of BALB/c nu/nu mice that developed xenograft tumours was 100%. A common method to assess tumour volume is to measure the two longest perpendicular axes in the x–y plane using callipers and then the depth is assumed to be equivalent to the shortest of the perpendicular axes. However, SK-N-SH xenografts were flat in shape and easily deformable and it was not possible to obtain accurate volume measurements using this method. Therefore, in this study, when using callipers, tumour size was reported as the maximum tumour diameter. Animals were entered into study when their tumour volume reached 500 mm3 as measured by MRI. All animal procedures were carried out in accordance with the UK Animals (Scientific Procedures) Act 1986 and with the local ethics committee approval. In preliminary experiments, the frequency of tumour development following subcutaneous injection of SK-N-SH cells into the flanks of nude athymic mice (BALB/c nu/nu) was found to be low (10%). Therefore, SK-N-SH cells (5 × 102 (70%/30% v/v). Mice were placed into the cradle in the supine position, allowing maintenance of the same geometry on transfer of animals from the MR to the SARRP-CBCT scanner . Tumours were detected with a respiratory-gated two-dimensional T2 weighted sequence  using slice-projection loop index counter-enabled reacquisition. A respiratory-gated three-dimensional balanced steady-state free-precession sequence was used as an anatomical reference for MRI/CBCT co-registration .SK-N-SH xenografts were not visible in CT images acquired using the on-board small animal radiation research platform (SARRP)-cone-beam CT (CBCT) and so, these images were unsuitable for RT planning . In cont scanner . Respira3 (at about 7 weeks after inoculation of SK-N-SH cells) and were randomly assigned to two groups: control (no treatment) or external beam RT. RT treatment  was administered using the SARRP irradiator at a dose rate of 2 Gy min−1 using a range of custom collimators depending on the tumour geometry. Dosimetry was performed using an EBT3 film  that was calibrated against absolute measurements determined by following the recommendations of the report of the American Association of Physicists in Medicine Task Group 61.5 On transfer from the MR scanner to the irradiator, MR images were imported into the SARRP system  code based on the modality independent neighbourhood descriptor algorithm for multimodal deformable registration.6 The resulting MR images were then imported into the Muriplan software , allowing the target volume to be clearly identified, enabling optimal beam delivery  were imaged weekly using MRI. Mice were euthanized when the tumour volume reached 800 mm3.Animals were entered into the study when their tumour volume reached 500 mmP system . MR imagdelivery . A singlT2 weighted slices. The tumour volume was calculated by multiplying the area of the tumour on each slice by the slice thickness and then adding these together.Image analysis was performed using ImageJ  software. Tumour volume delineation was performed manually on all adjacent post hoc test was used to assess differences in tumour volume between groups. A log-rank test was used to compare Kaplan–Meier curves. Statistical analyses were obtained with GraphPad Prism® software .All data are presented as mean ± standard deviation. One-way analysis of variance followed by Tukey's vs control groups (p = 0.14) but was apparent using MRI assessment (p < 0.001) (p < 0.01) , the tumour volume, as assessed by MRI or calliper measurements, was similar in the control and RT groups . At 4 anl groups . Interes< 0.001) . The tre < 0.01) .p < 0.01)  (R2 = 0.82 and p < 0.01)  . These s < 0.01) . There w = 0.11) . However < 0.01) .7 However, the implanted SK-N-SH cells do not form firm, well-defined masses. This presents a problem when treating tumours with external radiation, as it is difficult to define the extent of tumour infiltration, potentially increasing the risk of irradiating adjacent normal tissues or missing tumours. This is relevant to high-risk neuroblastoma in children, since it forms poorly marginated, infiltrative tumours that often lie in close proximity to radiosensitive organs such as the intra-abdominal viscera, lungs and spinal cord. To address this problem, we developed an MR-guided RT protocol using an in-house consecutive MRI-SARRP protocol. A purpose-built, plastic cradle that allows MRI and CBCT co-registration was designed and constructed. The cradle facilitated MATLAB® co-registration of MR and CBCT images, allowing the RT target volume to be planned directly on the anatomical MR image. Our results concur with those of Bolcaen et al,8 who showed that MRI was superior to CBCT for the delineation of the tumour volume prior to RT in a preclinical brain tumour model. Furthermore, this approach led to a significant normal tissue dose decrease during RT.8The SK-N-SH cell line is a preclinical model of human neuroblastoma that has been used extensively to generate xenograft tumours in mice.9 demonstrated the advantages of using 18F-fluorothymidine (FLT) positron emission tomography (PET) compared with 18F-fluorodeoxyglucose PET for tumour detection in the SK-N-SH model. Robust methods to plan and assess RT efficacy in this preclinical model is vitally important for the evaluation of new therapeutic approaches: for example, protocols that combine RT with chemotherapy and radionuclide therapy.10In the present study, measurement by calliper, a common method for the evaluation of xenograft size, was not sufficiently sensitive to detect early tumour regrowth and measurements at early time points did not correlate with survival time. This is partly owing to the physical characteristics of SK-N-SH xenografts, as they from flattened, poorly defined tumours in nude mice, making them difficult to measure by calliper . In contAn MRI-guided RT protocol for the treatment of a widely used human neuroblastoma model has been developed. MRI provides accurate monitoring of tumour volume, thereby facilitating the early detection of the RT treatment effect and its predictive value on overall survival.This work was supported through the CR-UK/MRC Oxford Institute for Radiation Oncology and the CR-UK/EPSRC Oxford Cancer Imaging Centre. MNG is supported by the NIHR University College London Hospitals Biomedical Research Centre.


Current antibody-drug conjugates (ADCs) target internalising receptors on cancer cells leading to intracellular drug release. Typically, only a subset of patients with solid tumours has sufficient expression of such a receptor, while there are suitable non-internalising receptors and stroma targets. Here, we demonstrate potent therapy in murine tumour models using a non-internalising ADC that releases its drugs upon a click reaction with a chemical activator, which is administered in a second step. This was enabled by the development of a diabody-based ADC with a high tumour uptake and very low retention in healthy tissues, allowing systemic administration of the activator 2 days later, leading to efficient and selective activation throughout the tumour. In contrast, the analogous ADC comprising the protease-cleavable linker used in the FDA approved ADC Adcetris is not effective in these tumour models. This first-in-class ADC holds promise for a broader applicability of ADCs across patient populations. Current antibody-drug conjugates (ADCs) target internalising receptors on cancer cells. Here, the authors report the development and in vivo validation of a non-internalising ADC with the capacity to target cancer cells and release its therapeutic cargo extracellularly via a chemical trigger. They are designed to bind to an internalising cancer cell receptor leading to uptake of the ADC and subsequent intracellular release of the drug by enzymes, thiols or lysosomal pH. Routing the toxin to the tumour, while minimising the peripheral damage to healthy tissue, allows the use of highly potent drugs resulting in improved therapeutic outcomes. Presently, four ADCs are approved by the American Food and Drug Administration (FDA): brentuximab vedotin (Adcetris) for Hodgkin and anaplastic large cell lymphoma, ado-trastuzumab emtansine (Kadcyla) for HER2-positive metastatic breast cancer, gemtuzumab ozogamicin (Mylotarg) for acute myeloid leukaemia and inotuzumab ozogamicin (Besponsa) for the treatment of acute lymphoblastic leukaemia. For example, Adcetris afforded a 75% overall response rate in patients with relapsed or refractory Hodgkin lymphoma and a median duration of response of 21 months3. Encouraged by these first successes, over 60 ADCs are now in clinical trials for a variety of haematologic and solid tumour malignancies3.Antibody-drug conjugates (ADCs) are a promising class of biopharmaceuticals that combine the target-specificity of monoclonal antibodies (mAbs) or mAb fragments with the potency of small molecule toxins4. On the other hand, therapy of solid tumours is hampered by the relatively limited number of suitable cancer-specific targets and the poor intratumoral distribution of ADCs4. The elevated interstitial pressure in solid tumours impedes penetration by large constructs such as ADCs5. This penetration can also be affected by the binding to cancer cells in the perivascular space and to antigens in the interstitial space, shed from dying cells7. The heterogeneous receptor expression observed in solid tumours further confounds homogeneous drug delivery5. Importantly, the number of solid tumour-specific receptors that ensure efficient internalisation and drug release is relatively limited. Low receptor copy numbers, slow internalisation kinetics, inefficient subcellular trafficking and receptor expression levels in normal tissues all complicate the selection of solid tumour targets for the current ADC approaches9. Furthermore, contrary to haematologic targets, solid tumour targets are typically only overexpressed in a subset of patient populations8. For example, only 20% of breast cancer patients have sufficient HER2 expression to be eligible for treatment with Kadcyla.Nevertheless, the current strategies do have some limitations, especially with respect to solid tumours. Haematologic tumours typically exhibit specific and homogenous expression of the target antigen and are well perfused and, therefore, accessible to the ADC15. Such targets may become amendable to ADC therapy by using a bioorthogonal chemical reaction for selective antibody-drug cleavage in vivo instead of relying on intracellular biological activation mechanisms. In this two-step approach, tumour binding of the ADC and blood clearance of the unbound fraction would be followed by systemic administration of an activator that reacts with the ADC linker, leading to drug release and subsequent uptake into surrounding cancer cells as well as tumour-supporting stromal cells  reaction, the inverse-electron-demand Diels−Alder (IEDDA) conjugation between trans-cyclooctene (TCO) and tetrazine derivatives, is now an established method for bioconjugations in mice18. We showed that this IEDDA conjugation could be transformed into an IEDDA pyridazine elimination reaction leading to the cleavage of allylic carbamates from TCO upon reaction with tetrazine19, opening up bioorthogonal “click-to-release” applications in vitro and in vivo24. This reaction seemed well suited for the envisioned chemically triggered ADC therapy, which may address the relatively limited number of clinically validated solid tumour targets for the current systems.An approach that functions by means of extracellular drug release would expand the number of potential ADC targets as there are sufficient non-internalising receptors and extracellular matrix targets that are selectively present in solid tumoursHerein, we report the first example of such click-to-release ADC therapy in tumour-bearing mice, enabled by the development of a diabody conjugate with a high tumour uptake combined with a fast blood clearance, and a new tetrazine activator that gives near-quantitative drug release Fig. . Biodist1. Tumour-associated glycoprotein-72 (TAG72) was selected as the cancer target, as it does not internalise, has slow shedding, and is widely expressed in a range of epithelial-derived human adenocarcinomas such as breast, colorectal, stomach, lung, pancreatic, prostate and ovarian cancer, while TAG72 expression in normal adult tissues is very low15. The TAG72 targeting mAb CC49 has been used in the clinic for (pretargeted) radioimmunotherapy of ovarian, colorectal, lung, prostate and breast cancer26 and for preclinical on-tumour IEDDA conjugation and elimination reactions28. Due to the slow clearance of mAbs from blood, a mAb-based ADC would require a very long interval between ADC and activator administration in order to prevent undesired drug release in circulation and well perfused tissues. To minimise this interval, we decided to develop a faster clearing PEGylated CC49 diabody conjugate instead. Conjugation of PEG24 residues to a CC49 diabody had previously been shown to afford superior imaging properties compared to both the native diabody and the parent mAb, owing to a high tumour uptake combined with a complete blood clearance within 2–3 days29. In addition to the likelihood of very low off-target activation levels, a smaller ADC lacking an Fc region could also improve tumour penetration and preclude the toxicities from Fc cross reaction with normal tissues as seen for current ADCs30. In the context of pretargeted radioimmunoimaging it had been demonstrated that mAb-conjugated TCO can be isomerised to the unreactive cis-isomer through contact with copper-binding sites in the serum proteins albumin and ceruloplasmin and that this deactivation can be slowed down to half-lives of 5 days or more in mice by reducing the mAb-TCO spacer length, thereby shielding the TCO31. To achieve the same in the ADC, we prepared a drug linker comprising a lysine-branched spacer designed to have the TCO-MMAE shielded by the vicinity of the diabody as well as the PEG24 moiety   and especially in non-target tissues for both models indicated that an interval of 2 days between ADC and activator administration should lead to ADC activation with good tumour selectivity. To assess the serum protein-induced deactivation rate of the TCO linker in vivo, mice were administered 125I-labelled tc-ADC and blood samples were obtained over time and reacted ex vivo with an excess of the highly reactive 177Lu-labelled 3,6-bispyridyl-tetrazine-DOTA probe 4  administered ice Fig.  and 4 asice Fig. . The cleice Fig. , at whic−1) Fig. , matchintc-ADC held promise for efficient tumour therapy provided that a tetrazine activator could be found that enables quantitative reaction with the tumour-bound ADC and exhibits a high release yield. The 3,6-bisalkyl-tetrazine and 3-alkyl-6-aryl-tetrazine structures that afford cleavage have a lower reactivity compared to the highly reactive but poorly releasing 3,6-bispyridyl-tetrazine motif (present in 4), which has successfully been used in IEDDA conjugations in vivo32. As small molecules, these less reactive tetrazines likely clear from circulation too fast, precluding quantitative on-tumour ADC reaction23. For example, small 3,6-bisalkyl-tetrazines have been shown to clear with half-lives of ca. 1 min34. Conjugation to 10 kDa dextran with a clearance half-life of ca. 6 min35 partially remedied this but at the expense of a substantially lower maximal release yield of 50%, possibly due to the dextran microenvironment affecting the formation of the releasing intermediate23. We, therefore, aimed to replace the dextran by a smaller moiety that would slow down the blood clearance without negatively impacting the release yield provided by the 3,6-bisalkyl-tetrazine motif. Intrigued by the relatively slow clearance  of the 3,6-bispyridyl-tetrazine imaging probe 4, containing a tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) chelate, used in earlier extracellular pretargeted imaging studies28, we set out to identify the governing factor. We prepared an analogue of 4 comprising a PEG11-linked DOTA as well as an oxime linkage to an 18F-labelled fluorobenzaldehyde  (we chose to use LuCl3 as it has a 26-fold higher LD50 than InCl3). Next, we assessed the blood clearance and biodistribution of 3 spiked with 177Lu and found a clearance half-life of 12 min  2 days later is followed by administration of the highly reactive [177Lu]Lu-4 to bind to TCO linker that has not already reacted with 3, thereby providing a read out on the reaction between tc-ADC and 3. LS147T-tumour-bearing mice were i.v. administered 125I-labelled tc-ADC  and nonradioactive activator 3 (0.335 mmol kg−1) 48 h later, followed by [177Lu]Lu-4 (0.335 µmol kg−1) at 50 h. Biodistribution at 53 h confirmed the high tumour uptake of the ADC . Despite the ca. 100-fold lower reactivity of 3 , affording nb-ADC . The mice that received 1 mg kg−1tc-ADC doses did not respond to therapy  and an extended median survival of 34 and 39 days. On the contrary, despite an initial transient effect of vc-ADC, this ADC and tc-ADC without activator 3, the activator alone, and nb-ADC in combination with 3 all failed to control tumour growth when given in four cycles  followed by activator 3  already showed a dose-dependent therapeutic response, despite heterogeneous tumour growth  with 3 resulted in a pronounced and durable tumour regression with barely palpable residual tumour masses until the end of the 4 month study, with 7 out of 8 mice surviving  and had to be removed from the study within 2 months  is, for example, still one to two orders of magnitude lower than the doses typically used for iodinated CT contrast agents in the clinic. The combination of ADC and activator led to a strong anticancer activity in vitro (EC50 185 and 35 pM), and in vivo in mice bearing, respectively, colorectal (LS174T) and ovarian (OVCAR-3) cancer xenografts. In addition to controlling tumour growth in the aggressive LS174T model, the click-cleavable conjugate resulted in a strong and durable response in OVCAR-3 mice at practical dose levels, leading to survival without any signs of toxicity for 4 months. On the contrary, the gold standard control, the same diabody conjugated with the protease-cleavable linker-payload combination used in the FDA approved Adcetris, was not effective in these tumour models, underlining the need for alternative activation mechanisms to complement the existing ADC therapies. Although a two-step approach requires the clinical development of two components and the optimisation of their dosing, this may partially be off-set by developing an ADC against a pan-carcinoma target and by the fact that the same activator can be used for different targets. In this respect, the CC49 diabody conjugate is very interesting as TAG72 is expressed in a wide range of solid cancers, but the click-to-release concept can also be extended to other targets and targeting agents. Furthermore, extracellular cleavage may hold promise for a more homogeneous drug distribution in tumours, possibly even reaching cancer stem cells8. Another tempting avenue to explore is whether extracellular release can augment the recently observed activation of tumour-resident dendritic cells by tubulin inhibitors leading to antitumour immune responses40. In summary, with one FDA approved solid tumour ADC and approx. 5 more in pivotal trials there is a need to increase the number of viable targets. This study clearly suggests that a click-to-release system can expand the scope of the successful ADC concept to non-internalising receptors and stroma targets that have so far remained out of reach of ADC therapy.ADCs have the potential to improve chemotherapy of solid tumours, as they allow the use of toxins with orders of magnitude higher potencies. However, the current approaches are limited to efficiently internalising receptors, which are typically only overexpressed in a subset of solid tumour patient populations. There are non-internalising receptors and stroma proteins that would be attractive targets if there were a way to selectively release the drug extracellularly. We hypothesised that the use of exogenous chemistry instead of relying on endogenous drug release mechanisms may enable the development of a novel class of ADCs that does not require internalisation, complementing current approaches and thereby expanding the application scope of this powerful therapeutic modality. Herein we report the first example of therapy using bioorthogonally triggered drug release from a targeting agent in vivo. To this end, we developed a fast clearing ADC based on a diabody, designed to release MMAE through the IEDDA pyridazine elimination. While ADCs based on mAb fragments are usually hampered by low or modest target uptake due to fast clearance after i.v. injection, reducing the renal clearance rate by PEGylation led to a favourable combination of characteristics of mAbs and peptides. The diabody ADC matched the high tumour localisation of its parent mAb but cleared much faster from blood allowing the i.v. administration of the tetrazine activator 2 days later, leading to efficient extracellular activation and high MMAE tumour levels with no or minimal washout. This temporally controlled and traceless cleavage was independent from endogenous release mechanisms and tumour selective due to the very low retention of the diabody conjugate in non-target tissues, minimising toxicity. This is exemplified by the 2 orders of magnitude lower levels of MMAE in plasma and liver for Additional methods and corresponding figures are provided in the Supplementary Methods and Supplementary Figures, including synthesis and characterisation of all new compounds  and 5% dimethylsulfoxide (DMSO)) was diluted with PBS (90 μL), and analysed with high-performance liquid chromatography (HPLC)-QTOF-MS. This procedure was repeated over the course of several months . No degradation of the diabody conjugates was observed in this time frame  were diluted with PBS (90 μL), mixed with activator 3  and incubated at 37 °C for 1 h. Subsequent HPLC-QTOF-MS analysis demonstrated the formation of free MMAE (m/z = + 718.51 Da) and the diabody reaction products without MMAE . An aliquot of the stock solution  was incubated in 50% mouse serum in PBS (0.7 mL) at 37 °C (n = 3). At t = 0, 30 min, 1, 2 and 3 h, 100 µL aliquots of the mixture were taken, treated with 100 µL ice-cold acetonitrile, mixed and centrifuged for 5 min at 13,000 rpm. More than 90% of the radioactivity was recovered in the supernatant at all time points. The supernatant was filtered through a 0.22 µm filter, 2.5-fold diluted with PBS and analysed by radio-HPLC. Linear regression of the % intact activator  was tenfold diluted with PBS. Subsequently 50 μL of this solution was twofold diluted with mouse serum and activator 3 was added  followed by incubation at 37 °C. After 10 min, 1 h and 20 h aliquots of the solution were taken and proteins were precipitated by adding two parts of ice-cold acetonitrile. After vortexing, 10 min standing at −20 °C and centrifugation , the supernatants were separated from the protein pellets, diluted with five parts of PBS and analysed by HPLC-QTOF-MS , tc-ADC (2.36 µg µL−1 in EDTA-PB containing 5% DMSO) and MMAE (63 µM in DMSO) were serially diluted in pre-warmed culture medium immediately before the experiment and added to the wells . The tc-ADC was either added alone or followed by 3 µM activator (5 eq. with respect to the highest TCO concentration). After 72 h incubation at 37 °C, cell proliferation was assessed by an MTT assay. The proliferation assay was performed in triplicate. EC50 values . The human ovary carcinoma NIH:OVCAR-3 cell line was cultured in RPMI-1640 medium supplemented with 1 mM sodium pyruvate, 10 mM HEPES, 2 mM glutamine, 10 µg mLhttp://homepage.stat.uiowa.edu/~rlenth/Power/index.html). Female BALB/c nude mice  were subcutaneously inoculated ca. 3 × 106 LS174T cells (in 100 µL complete culture medium), ca. 5 × 106 NIH:OVCAR-3 cells (in 100 µL 1:1 RPMI-1640: matrigel) or 5 × 106 HT-29 cells (in 100 µL complete culture medium) in the hind limb. Tumour size was determined by caliper measurements in three dimensions (tumour volume = ½ × l × w × h) once per week (OVCAR-3) or three times per week (LS174T) by a blinded biotechnician. Biodistribution and imaging studies started when the tumours reached 0.1–0.2 cm3. Animals were randomly allocated to treatments groups. At the end of the studies, the animals were euthanized, blood was obtained by cardiac puncture and organs and tissues of interest were harvested, blotted dry, weighed, added with 1 mL PBS and the sample radioactivity was measured in a shielded well-type γ-counter together with aliquots of the injected dose to calculate % ID g−1 and % ID. Stomachs and intestines were not emptied before γ-counting.The animal studies were performed in accordance with the principles established by the revised Dutch Act on Animal Experimentation (1997) and were approved by the institutional Animal Welfare Committee of the Radboud University Nijmegen. To determine the appropriate group sizes for the different experiments, the sample size calculation tool from the University of Iowa was used (n = 4) were injected with 125I-labelled tc-ADC at 1 and 5 mg kg−1 dose . The mice were serially bled via the vena saphena (ca. 20 µL samples) at various times between 5 min and 72 h post-injection. Four days post-injection the mice were euthanized, one last blood sample was obtained via cardiac puncture and selected organs and tissues were harvested for γ-counting (Supplementary Table Two groups of tumour-free mice n =  were injn = 3–4) were injected with 125I-labelled tc-ADC, vc-ADC or nb-ADC at 2 mg kg−1 dose . All mice were euthanized 48 h post-ADC injection and blood, tumours and other organs were harvested for γ-counting.Groups of mice bearing subcutaneous LS174T, OVCAR-3 or HT-29 xenografts (S4 (see Supplementary Methods) was radiolabelled with 177Lu at ca. 1 MBq nmol−1 molar activity and the resulting product was used to spike the nonradioactive activator 3. Two groups of four tumour-free mice were injected with [177Lu]Lu-3 . One group was euthanized 1 h post-injection. The second group was serially bled at various times between 2 and 90 min post-injection and euthanized 24 h post-injection. Selected organs and tissues were harvested from all mice for γ-counting (Supplementary Table The activator precursor n = 4) bearing LS174T or OVCAR-3 xenografts were injected with 125I-labelled tc-ADC  followed 48 h later by activator 3  and, after 1 h, by [177Lu]Lu-4 . Two more groups of mice (n = 4 for LS174T and n = 3 for OVCAR-3) were injected with the same amount of 125I-labelled ADC followed only by probe 4 49 h later. All mice were euthanized 3 h post-probe injection and the 125I/177Lu uptake in tumours and other organs and tissues was measured by γ-counting with a dual-isotope protocol with cross contamination correction. To evaluate the effect of ADC dose on the reaction efficacy with 3 (0.335 mmol kg−1), three more groups of mice bearing LS174T xenografts were injected with 125I-labelled tc-ADC at 1, 5 and 10 mg kg−1 dose  and evaluated as outlined above.Two groups of mice  and two non-pretreated mice were injected with 111In-labelled activator 3 , derived from precursor S4. Two more tc-ADC pretreated mice were injected with 111In-labelled probe 4 . The mice that received [111In]In-3 were euthanized 3 h post-activator injection, bladders were voided of residual radioactive urine and the mice were imaged post-mortem. The mice that received [111In]In-4 were anaesthetised 2 h post-injection and were imaged under anaesthesia (ca. 45 min imaging). Representative SPECT/CT images of a non-pretreated mouse injected with [111In]In-3 are depicted in Supplementary Fig. Two LS174T tumour-bearing mice pretreated with 3 LS174T tumour size, 5–7 days post-cell inoculation; 115 ± 43 mm3 OVCAR-3 tumour size, 6–8 weeks post-cell inoculation). A pilot (single-dose) therapy study in mice bearing OVCAR-3 xenografts is reported in the Supplementary Information  received four cycles of TCO-containing ADC (tc-ADC or nb-ADC) at a 3.75 mg kg−1 dose (in 100 µL PBS containing 5% DMSO) and activator 3 (0.335 mmol kg−1 in 130 µL PBS containing 5% DMSO). Two groups of mice (n = 8) were injected with four cycles of vc-ADC or tc-ADC at the same dose followed by vehicle and, finally, two more groups of mice (n = 8) received four cycles of either the activator or vehicle. Four groups of LS174T tumour-bearing mice (n = 8–10) were injected with four cycles of increasing doses of tc-ADC  or nb-ADC (3 mg kg−1) and activator 3 (0.335 mmol kg−1 in 130 µL PBS containing 5% DMSO). Two groups of mice (n = 10) were administered four cycles of 3 mg kg−1vc-ADC or tc-ADC followed by vehicle and two more groups of mice (n = 10) received four cycles of either the activator or vehicle only. In both experiments, the animals were randomly grouped, monitored daily by experienced biotechnicians, and were removed from the study in case of poor physical condition , in case of excessive body weight loss (>20% with respect to baseline or >15% in two consecutive measurements) or when tumours reached a 1 cm3 size. If none of these conditions occurred the mice were maintained in the study for up to 2 months (LS174T tumour model) or 4 months (OVCAR-3 tumour model). At mouse euthanasia, selected organs  were harvested and formaldehyde-fixed for histopathology.Therapy studies where performed when tumours were clearly palpable (55 ± 26 mmn = 3) received four cycles of tc-ADC (5 mg kg−1) and activator 3 (0.335 nmol kg−1), tc-ADC only, activator only or vehicle, according to the injection scheme in Supplementary Fig. 1012.Four separate groups of tumour-free mice  test. Differences between data sets were considered significant when P < 0.05.Curve fitting, linear regressions and area-under-the-curve calculations were performed with GraphPad Prism (v 5.01). Group comparisons were performed with one-way ANOVA (with Bonferroni’s post-tests) or two-tailed The data that support the findings reported herein are available on reasonable request from the corresponding author.Supplementary InformationPeer Review File