Recapitulating tumour microenvironment in chitosan–gelatin three-dimensional scaffolds: an improved in vitro tumour model

Owing to the reduced co-relationship between conventional flat Petri dish culture (two-dimensional) and the tumour microenvironment, there has been a shift towards three-dimensional culture systems that show an improved analogy to the same. In this work, an extracellular matrix (ECM)-mimicking three-dimensional scaffold based on chitosan and gelatin was fabricated and explored for its potential as a tumour model for lung cancer. It was demonstrated that the chitosan–gelatin (CG) scaffolds supported the formation of tumoroids that were similar to tumours grown in vivo for factors involved in tumour-cell–ECM interaction, invasion and metastasis, and response to anti-cancer drugs. On the other hand, the two-dimensional Petri dish surfaces did not demonstrate gene-expression profiles similar to tumours grown in vivo. Further, the three-dimensional CG scaffolds supported the formation of tumoroids, using other types of cancer cells such as breast, cervix and bone, indicating a possible wider potential for in vitro tumoroid generation. Overall, the results demonstrated that CG scaffolds can be an improved in vitro tool to study cancer progression and drug screening for solid tumours.     

Liquid biopsies for early diagnosis of brain tumours: in silico mathematical biomarker modelling

Brain tumours are the biggest cancer killer in those under 40 and reduce life expectancy more than any other cancer. Blood-based liquid biopsies may aid early diagnosis, prediction and prognosis for brain tumours. It remains unclear whether known blood-based biomarkers, such as glial fibrillary acidic protein (GFAP), have the required sensitivity and selectivity. We have developed a novel in silico model which can be used to assess and compare blood-based liquid biopsies. We focused on GFAP, a putative biomarker for astrocytic tumours and glioblastoma multi-formes (GBMs). In silico modelling was paired with experimental measurement of cell GFAP concentrations and used to predict the tumour volumes and identify key parameters which limit detection. The average GBM volumes of 449 patients at Leeds Teaching Hospitals NHS Trust were also measured and used as a benchmark. Our model predicts that the currently proposed GFAP threshold of 0.12 ng ml⁻¹ may not be suitable for early detection of GBMs, but that lower thresholds may be used. We found that the levels of GFAP in the blood are related to tumour characteristics, such as vasculature damage and rate of necrosis, which are biological markers of tumour aggressiveness. We also demonstrate how these models could be used to provide clinical insight.     

Modelling the spatial heterogeneity and molecular correlates of lymphocytic infiltration in triple-negative breast cancer

Lymphocytic infiltration is associated with a favourable prognosis and predicts response to chemotherapy in many cancer types, including the aggressive triple-negative breast cancer (TNBC). However, it is not well understood owing to the high levels of spatial heterogeneity within tumours, which is difficult to analyse by traditional pathological assessment. This paper describes an unbiased methodology to statistically model the spatial distribution of lymphocytes among tumour cells based on automated analysis of haematoxylin-and-eosin-stained whole-tumour section images, which is applied to two independent TNBC cohorts of 181 patients with matched microarray gene expression data. The novelty of the proposed methodology is the fusion of image analysis and statistical modelling for an integrative understanding of intratumour heterogeneity of lymphocytic infiltration. Using this methodology, a quantitative measure of intratumour lymphocyte ratio is developed and found to be significantly associated with disease-specific survival in both TNBC cohorts independent to standard clinical parameters. The proposed image-based measure compares favourably to a number of gene expression signatures of immune infiltration. In addition, heterogeneous immune infiltration at the morphological level is reflected at the molecular scale and correlated with increased expression of CTLA4, the target of ipilimumab. Taken together, these results support the fusion of high-throughput image analysis and statistical modelling to offer reproducible and robust biomarkers for the objective identification of patients with poor prognosis and treatment options.     

Cancer therapeutic potential of combinatorial immuno- and vasomodulatory interventions

Currently, most of the basic mechanisms governing tumour–immune system interactions, in combination with modulations of tumour-associated vasculature, are far from being completely understood. Here, we propose a mathematical model of vascularized tumour growth, where the main novelty is the modelling of the interplay between functional tumour vasculature and effector cell recruitment dynamics. Parameters are calibrated on the basis of different in vivo immunocompromised Rag1^−/− and wild-type (WT) BALB/c murine tumour growth experiments. The model analysis supports that tumour vasculature normalization can be a plausible and effective strategy to treat cancer when combined with appropriate immunostimulations. We find that improved levels of functional tumour vasculature, potentially mediated by normalization or stress alleviation strategies, can provide beneficial outcomes in terms of tumour burden reduction and growth control. Normalization of tumour blood vessels opens a therapeutic window of opportunity to augment the antitumour immune responses, as well as to reduce intratumoral immunosuppression and induced hypoxia due to vascular abnormalities. The potential success of normalizing tumour-associated vasculature closely depends on the effector cell recruitment dynamics and tumour sizes. Furthermore, an arbitrary increase in the initial effector cell concentration does not necessarily imply better tumour control. We evidence the existence of an optimal concentration range of effector cells for tumour shrinkage. Based on these findings, we suggest a theory-driven therapeutic proposal that optimally combines immuno- and vasomodulatory interventions.     

A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET

Glioblastoma multiforme (GBM) is a highly invasive primary brain tumour that has poor prognosis despite aggressive treatment. A hallmark of these tumours is diffuse invasion into the surrounding brain, necessitating a multi-modal treatment approach, including surgery, radiation and chemotherapy. We have previously demonstrated the ability of our model to predict radiographic response immediately following radiation therapy in individual GBM patients using a simplified geometry of the brain and theoretical radiation dose. Using only two pre-treatment magnetic resonance imaging scans, we calculate net rates of proliferation and invasion as well as radiation sensitivity for a patient''s disease. Here, we present the application of our clinically targeted modelling approach to a single glioblastoma patient as a demonstration of our method. We apply our model in the full three-dimensional architecture of the brain to quantify the effects of regional resistance to radiation owing to hypoxia in vivo determined by [¹⁸F]-fluoromisonidazole positron emission tomography (FMISO-PET) and the patient-specific three-dimensional radiation treatment plan. Incorporation of hypoxia into our model with FMISO-PET increases the model–data agreement by an order of magnitude. This improvement was robust to our definition of hypoxia or the degree of radiation resistance quantified with the FMISO-PET image and our computational model, respectively. This work demonstrates a useful application of patient-specific modelling in personalized medicine and how mathematical modelling has the potential to unify multi-modality imaging and radiation treatment planning.     

Mathematical and computational models of drug transport in tumours

The ability to predict how far a drug will penetrate into the tumour microenvironment within its pharmacokinetic (PK) lifespan would provide valuable information about therapeutic response. As the PK profile is directly related to the route and schedule of drug administration, an in silico tool that can predict the drug administration schedule that results in optimal drug delivery to tumours would streamline clinical trial design. This paper investigates the application of mathematical and computational modelling techniques to help improve our understanding of the fundamental mechanisms underlying drug delivery, and compares the performance of a simple model with more complex approaches. Three models of drug transport are developed, all based on the same drug binding model and parametrized by bespoke in vitro experiments. Their predictions, compared for a ‘tumour cord’ geometry, are qualitatively and quantitatively similar. We assess the effect of varying the PK profile of the supplied drug, and the binding affinity of the drug to tumour cells, on the concentration of drug reaching cells and the accumulated exposure of cells to drug at arbitrary distances from a supplying blood vessel. This is a contribution towards developing a useful drug transport modelling tool for informing strategies for the treatment of tumour cells which are ‘pharmacokinetically resistant’ to chemotherapeutic strategies.     

Experimental and mathematical modelling of magnetically labelled mesenchymal stromal cell delivery

A key challenge for stem cell therapies is the delivery of therapeutic cells to the repair site. Magnetic targeting has been proposed as a platform for defining clinical sites of delivery more effectively. In this paper, we use a combined in vitro experimental and mathematical modelling approach to explore the magnetic targeting of mesenchymal stromal cells (MSCs) labelled with magnetic nanoparticles using an external magnet. This study aims to (i) demonstrate the potential of magnetic tagging for MSC delivery, (ii) examine the effect of red blood cells (RBCs) on MSC capture efficacy and (iii) highlight how mathematical models can provide both insight into mechanics of therapy and predictions about cell targeting in vivo. In vitro MSCs are cultured with magnetic nanoparticles and circulated with RBCs over an external magnet. Cell capture efficacy is measured for varying magnetic field strengths and RBC percentages. We use a 2D continuum mathematical model to represent the flow of magnetically tagged MSCs with RBCs. Numerical simulations demonstrate qualitative agreement with experimental results showing better capture with stronger magnetic fields and lower levels of RBCs. We additionally exploit the mathematical model to make hypotheses about the role of extravasation and identify future in vitro experiments to quantify this effect.     

Evaluation of two Compton camera models for scintimammography

We study the performance of a Si/LaBr₃:Ce Compton camera model for scintimammography, and compare it with a Si/NaI(Tl) model of similar geometry. The GEANT4 simulation toolkit was used to study the behaviour of the cameras at 511 keV. Certain simulation steps, such as the modelling of radionuclide decay times, scintillation photon transport and interactions with photomultipliers, as well as detector dead time corrections were included to make the modelling of the cameras more realistic than previous studies. The Si/LaBr₃:Ce Compton camera shows superior efficiency of 2.0×10⁻³ and resolution of 5.3 mm over the Si/NaI(Tl) Compton camera model which has the efficiency of 1.6×10⁻³ and resolution of 6.9 mm at a source-to-scatterer distance of interest, 2.5 cm. A similar result sequence is obtained for two breast tumours of 5 mm diameter embedded in the medial region of an average-size breast phantom of thickness 5 cm. Notably, the signal-to-noise ratios (SNR) obtained for the Si/LaBr₃:Ce camera are 9.7 and 3.4 for tumour/background radiation uptakes of 10:1 and 6:1, whereas 6.8 and 2.4 were obtained for the Si/NaI(Tl) camera model for the same tumour/background radiation uptakes respectively. It is therefore envisioned that with lower cost, LaBr₃:Ce could replace NaI(Tl) as the Compton camera absorber.     

PEG‐Citrate dendrimer second generation: is this a good carrier for imaging agents In Vitro and In Vivo ?

While cancer is the leading cause of human''s deaths worldwide, finding an imaging agent which can detect cancer tumours is needed for cancer diagnosis. In the present study, PEG‐citrate dendrimer‐G₂ was used as a nano‐carrier of FITC dye and Iohexol to help passive targeting and uptake of both imaging agents in cancer cells/tumour in vitro and in vivo. Dendrimer was synthesisedand the product characterised using LC‐MS, FT‐IR, DLS, ELS, AFM, and ¹ HNMR. After FITC loading into dendrimer, MTT was performed to determine the cytotoxicity of formulation on HEK‐293 and MCF‐7 cells. In vitro imaging using dendrimer‐FITC was done via fluorescent microscope thereafter. Moreover, CT imaging using Iohexol was employed to show the targeting nature and ability of the complex to use as imaging agent in vivo. Data yielded in this study corroborate the notion that the promised dendrimer was synthesised properly and had no toxicity along with FITC on normal cell. Furthermore, CT and fluorescent images showed the targeting nature and imaging ability of Iohexol/FITC loaded dendrimer in vitro and in vivo. Overall, results showed promising characteristics of the novel complexes using dendrimer‐G₂ both in vitro and in vivo.Inspec keywords: drug delivery systems, cellular biophysics, molecular biophysics, fluorescence, cancer, tumours, drugs, nanomedicine, biomedical materials, dyes, toxicologyOther keywords: imaging agent, cancer tumours, cancer diagnosis, PEG‐citrate dendrimer‐G, FITC dye, cancer cells, FITC loading, vitro imaging, dendrimer‐FITC, CT imaging, targeting nature, promised dendrimer, fluorescent images, imaging ability, Iohexol/FITC     

Estimating Young's modulus of zona pellucida by micropipette aspiration in combination with theoretical models of ovum

The zona pellucida (ZP) is the spherical layer that surrounds the mammalian oocyte. The physical hardness of this layer plays a crucial role in fertilization and is largely unknown because of the lack of appropriate measuring and modelling methods. The aim of this study is to measure the biomechanical properties of the ZP of human/mouse ovum and to test the hypothesis that Young''s modulus of the ZP varies with fertilization. Young''s moduli of ZP are determined before and after fertilization by using the micropipette aspiration technique, coupled with theoretical models of the oocyte as an elastic incompressible half-space (half-space model), an elastic compressible bilayer (layered model) or an elastic compressible shell (shell model). Comparison of the models shows that incorporation of the layered geometry of the ovum and the compressibility of the ZP in the layered and shell models may provide a means of more accurately characterizing ZP elasticity. Evaluation of results shows that although the results of the models are different, all confirm that the hardening of ZP will increase following fertilization. As can be seen, different choices of models and experimental parameters can affect the interpretation of experimental data and lead to differing mechanical properties.     

Topology optimization of creeping fluid flows using a Darcy–Stokes finite element

A new methodology is proposed for the topology optimization of fluid in Stokes flow. The binary design variable and no‐slip condition along the solid–fluid interface are regularized to allow for the use of continuous mathematical programming techniques. The regularization is achieved by treating the solid phase of the topology as a porous medium with flow governed by Darcy's law. Fluid flow throughout the design domain is then expressed as a single system of equations created by combining and scaling the Stokes and Darcy equations. The mixed formulation of the new Darcy–Stokes system is solved numerically using existing stabilized finite element methods for the individual flow problems. Convergence to the no‐slip condition is demonstrated by assigning a low permeability to solid phase and results suggest that auxiliary boundary conditions along the solid–fluid interface are not needed. The optimization objective considered is to minimize dissipated power and the technique is used to solve examples previously examined in literature. The advantages of the Darcy–Stokes approach include that it uses existing stabilization techniques to solve the finite element problem, it produces 0–1 (void–solid) topologies (i.e. there are no regions of artificial material), and that it can potentially be used to optimize the layout of a microscopically porous material. Copyright © 2005 John Wiley & Sons, Ltd.     

Cerebrospinal fluid dynamics in the human cranial subarachnoid space: an overlooked mediator of cerebral disease. II. In vitro arachnoid outflow model

The arachnoid membrane (AM) and granulations (AGs) are important in cerebrospinal fluid (CSF) homeostasis, regulating intracranial pressure in health and disease. We offer a functional perspective of the human AM''s transport mechanism to clarify the role of AM in the movement of CSF and metabolites. Using cultures of human AG cells and a specialized perfusion system, we have shown that this in vitro model mimics the in vivo characteristics of unidirectional fluid transport and we present the first report of serum-free permeability values (92.5 µl min⁻¹ mm Hg⁻¹ cm⁻²), which in turn are in agreement with the CSF outflow rates derived from a dynamic, in vivo magnetic resonance imaging-based computational model of the subarachnoid cranial space (130.9 µl min⁻¹ mm Hg⁻¹ cm⁻²). Lucifer yellow permeability experiments have verified the maintenance of tight junctions by the arachnoidal cells with a peak occurring around 21 days post-seeding, which is when all perfusion experiments were conducted. Addition of ruthenium red to the perfusate, and subsequent analysis of its distribution post-perfusion, has verified the passage of perfusate via both paracellular and transcellular mechanisms with intracellular vacuoles of approximately 1 µm in diameter being the predominant transport mechanism. The comparison of the computational and in vitro models is the first report to measure human CSF dynamics functionally and structurally, enabling the development of innovative approaches to modify CSF outflow and will change concepts and management of neurodegenerative diseases resulting from CSF stagnation.     

A validated predictive model of coronary fractional flow reserve

Myocardial fractional flow reserve (FFR), an important index of coronary stenosis, is measured by a pressure sensor guidewire. The determination of FFR, only based on the dimensions (lumen diameters and length) of stenosis and hyperaemic coronary flow with no other ad hoc parameters, is currently not possible. We propose an analytical model derived from conservation of energy, which considers various energy losses along the length of a stenosis, i.e. convective and diffusive energy losses as well as energy loss due to sudden constriction and expansion in lumen area. In vitro (constrictions were created in isolated arteries using symmetric and asymmetric tubes as well as an inflatable occluder cuff) and in vivo (constrictions were induced in coronary arteries of eight swine by an occluder cuff) experiments were used to validate the proposed analytical model. The proposed model agreed well with the experimental measurements. A least-squares fit showed a linear relation as (Δp or FFR)_experiment = a(Δp or FFR)_theory + b, where a and b were 1.08 and −1.15 mmHg (r² = 0.99) for in vitro Δp, 0.96 and 1.79 mmHg (r² = 0.75) for in vivo Δp, and 0.85 and 0.1 (r² = 0.7) for FFR. Flow pulsatility and stenosis shape (e.g. eccentricity, exit angle divergence, etc.) had a negligible effect on myocardial FFR, while the entrance effect in a coronary stenosis was found to contribute significantly to the pressure drop. We present a physics-based experimentally validated analytical model of coronary stenosis, which allows prediction of FFR based on stenosis dimensions and hyperaemic coronary flow with no empirical parameters.     

Occam’s razor gets a new edge: the use of symmetries in model selection

We demonstrate the power of using symmetries for model selection in the context of mechanistic modelling. We analyse two different models called the power law model (PLM) and the immunological model (IM) describing the increase in cancer risk with age, due to mutation accumulation or immunosenescence, respectively. The IM fits several cancer types better than the PLM implying that it would be selected based on minimizing residuals. However, recently a symmetry-based method for model selection has been developed, which has been successfully used in an in silico setting to find the correct model when traditional model fitting has failed. Here, we apply this method in a real-world setting to investigate the mechanisms of carcinogenesis. First, we derive distinct symmetry transformations of the two models and then we select the model which not only fits the original data but is also invariant under transformations by its symmetry. Contrary to the initial conclusion, we conclude that the PLM realistically describes the mechanism underlying the colon cancer dataset. These conclusions agree with experimental knowledge, and this work demonstrates how a model selection criterion based on biological properties can be implemented using symmetries.     

BBN conjugated GNPs: a new targeting contrast agent for imaging of breast cancer in radiology

Using of targeted contrast agents in X‐ray imaging of breast cancer can improve the accuracy of diagnosis, staging, and treatment planning by providing early detection and superior definition of tumour volume. This study demonstrates a new class of X‐ray contrast agents based on gold nanoparticles (GNPs) and bombesin (BBN) for imaging of breast cancer in radiology. GNPs were synthesised in spherical shape in the size range of 15 ± 2 nm and conjugated with BBN followed by coating with polyethyleneglycol (PEG). The in vitro and in vivo behaviour of PEG‐coated GNPs‐BBN conjugate was investigated performing cytotoxicity, binding, and internalisation assays as well as biodistribution and X‐ray imaging studies in mouse bearing breast tumour. Cytotoxicity study showed biocompatibility of the prepared bioconjugate. The binding and internalisation studies using T47D cell line approved the targeting ability of new agent. The biodistribution study showed the considerable accumulation of prepared conjugate in breast tumour in mouse model. The breast tumour was clearly visualised in X‐ray images taken from the mouse model. The results showed the potential of PEG‐coated GNPs‐BBN conjugate as a contrast agent in X‐ray imaging of breast tumour in humans that need further investigations.Inspec keywords: diagnostic radiography, cancer, tumours, radiology, gold, nanoparticles, nanomedicine, polymers, coatings, toxicology, cellular biophysicsOther keywords: bombesin conjugated gold nanoparticles, breast cancer, radiology, targeted contrast agents, X‐ray imaging, X‐ray contrast agents, spherical shape, polyethyleneglycol, coating, in vitro behaviour, in vivo behaviour, cytotoxicity, internalisation assays, biodistribution, mouse bearing breast tumour, biocompatibility, bioconjugate, T47D cell line, Au     

Mechanical regulation of the early stages of angiogenesis

Favouring or thwarting the development of a vascular network is essential in fields as diverse as oncology, cardiovascular disease or tissue engineering. As a result, understanding and controlling angiogenesis has become a major scientific challenge. Mechanical factors play a fundamental role in angiogenesis and can potentially be exploited for optimizing the architecture of the resulting vascular network. Largely focusing on in vitro systems but also supported by some in vivo evidence, the aim of this Highlight Review is dual. First, we describe the current knowledge with particular focus on the effects of fluid and solid mechanical stimuli on the early stages of the angiogenic process, most notably the destabilization of existing vessels and the initiation and elongation of new vessels. Second, we explore inherent difficulties in the field and propose future perspectives on the use of in vitro and physics-based modelling to overcome these difficulties.     

Analysis of behaviour transitions in tumour growth using a cellular automaton simulation

The authors used computational biology as an approach for analysing the emergent dynamics of tumour growth at cellular level. They applied cellular automata for modelling the behaviour of cells when the main cancer cell hallmarks are present. Their model is oriented to mimic the development of multicellular spheroids of tumour cells. In their modelling, cells have a genome associated with the different cancer hallmarks, indicating if those are acquired as a consequence of mutations. The presence of the cancer hallmarks defines cell states and cell mitotic behaviours. These hallmarks are associated with a series of parameters, and depending on their values and the activation of the hallmarks in each of the cells, the system can evolve to different dynamics. With the simulation tool the authors performed an analysis of the first phases of cancer growth, using different and alternative strategies: firstly, studying the evolution of cancer cells and hallmarks in different representative situations regarding initial conditions and parameters, analysing the relative importance of the hallmarks for tumour progression; secondly, being the focus of this work, inspecting the behaviour transitions when the cancer cells are killed with a given probability during the cellular system progression.Inspec keywords: tumours, cellular biophysics, cancer, cellular automata, probabilityOther keywords: behaviour transition analysis, tumour growth, cellular automaton simulation, computational biology, cellular level, cellular automata, cancer cell hallmarks, multicellular spheroids, tumour cells, cell mitotic behaviours, tumour progression, probability, cellular system progression     

A stochastic mathematical model of 4D tumour spheroids with real-time fluorescent cell cycle labelling

In vitro tumour spheroids have been used to study avascular tumour growth and drug design for over 50 years. Tumour spheroids exhibit heterogeneity within the growing population that is thought to be related to spatial and temporal differences in nutrient availability. The recent development of real-time fluorescent cell cycle imaging allows us to identify the position and cell cycle status of individual cells within the growing spheroid, giving rise to the notion of a four-dimensional (4D) tumour spheroid. We develop the first stochastic individual-based model (IBM) of a 4D tumour spheroid and show that IBM simulation data compares well with experimental data using a primary human melanoma cell line. The IBM provides quantitative information about nutrient availability within the spheroid, which is important because it is difficult to measure these data experimentally.     

The effect of remodelling and contractility of the actin cytoskeleton on the shear resistance of single cells: a computational and experimental investigation

The biomechanisms that govern the response of chondrocytes to mechanical stimuli are poorly understood. In this study, a series of in vitro tests are performed, in which single chondrocytes are subjected to shear deformation by a horizontally moving probe. Dramatically different probe force–indentation curves are obtained for untreated cells and for cells in which the actin cytoskeleton has been disrupted. Untreated cells exhibit a rapid increase in force upon probe contact followed by yielding behaviour. Cells in which the contractile actin cytoskeleton was removed exhibit a linear force–indentation response. In order to investigate the mechanisms underlying this behaviour, a three-dimensional active modelling framework incorporating stress fibre (SF) remodelling and contractility is used to simulate the in vitro tests. Simulations reveal that the characteristic force–indentation curve observed for untreated chondrocytes occurs as a result of two factors: (i) yielding of SFs due to stretching of the cytoplasm near the probe and (ii) dissociation of SFs due to reduced cytoplasm tension at the front of the cell. In contrast, a passive hyperelastic model predicts a linear force–indentation curve similar to that observed for cells in which the actin cytoskeleton has been disrupted. This combined modelling–experimental study offers a novel insight into the role of the active contractility and remodelling of the actin cytoskeleton in the response of chondrocytes to mechanical loading.