Glucose diffusion coefficients determined from concentration profiles in EMT6 tumor spheroids incubated in radioactively labeled L-glucose

Microenvironmental cooperation promotes early spread and bistability of a Warburg-like phenotype

We introduce an in silico model for the initial spread of an aberrant phenotype with Warburg-like overflow metabolism within a healthy homeostatic tissue in contact with a nutrient reservoir (the blood), aimed at characterizing the role of the microenvironment for aberrant growth. Accounting for cellular metabolic activity, competition for nutrients, spatial diffusion and their feedbacks on aberrant replication and death rates, we obtain a phase portrait where distinct asymptotic whole-tissue states are found upon varying the tissue-blood turnover rate and the level of blood-borne primary nutrient. Over a broad range of parameters, the spreading dynamics is bistable as random fluctuations can impact the final state of the tissue. Such a behaviour turns out to be linked to the re-cycling of overflow products by non-aberrant cells. Quantitative insight on the overall emerging picture is provided by a spatially homogeneous version of the model.

Comprehensive Two- and Three-Dimensional RNAi Screening Identifies PI3K Inhibition as a Complement to MEK Inhibitor AS703026 for Combination Treatment of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a major cause of death among breast cancer patients that results from intrinsic and acquired resistance to systemic chemotherapies. To identify novel targets for effective treatment of TNBC through combination strategies with MEK inhibitor (AS703026), we used a novel method of combining high-throughput two- and three-dimensional (2D and 3D) RNAi screening. TNBC cells were transfected with a kinome siRNA library comprising siRNA targeting 790 kinases under both 2D and 3D culture conditions with or without AS703026. Molecule activity predictor analysis revealed the PI3K pathway as the major target pathway in our RNAi combination studies in TNBC. We found that PI3K inhibitor SAR245409 (also called XL765) combined with AS703026 synergistically inhibited proliferation compared with either drug alone (P < 0.001). Reduced in vitro colony formation (P < 0.001) and migration and invasion ability were also observed with the combination treatment (P<0.01). Our data suggest that SAR245409 combined with AS703026 may be effective in patients with TNBC. We conclude that a novel powerful high-throughput RNAi assays were able to identify anti-cancer drugs as single or combinational agents. Integrated and multi-system RNAi screening methods can complement difference between in vitro and in vivo culture conditions, and enriches targets that are close to the in vivo condition.

Impact of metabolic heterogeneity on tumor growth, invasion, and treatment outcomes

Histopathologic knowledge that extensive heterogeneity exists between and within tumors has been confirmed and deepened recently by molecular studies. However, the impact of tumor heterogeneity on prognosis and treatment remains as poorly understood as ever. Using a hybrid multiscale mathematical model of tumor growth in vascularized tissue, we investigated the selection pressures exerted by spatial and temporal variations in tumor microenvironment and the resulting phenotypic adaptations. A key component of this model is normal and tumor metabolism and its interaction with microenvironmental factors. The metabolic phenotype of tumor cells is plastic, and microenvironmental selection leads to increased tumor glycolysis and decreased pH. Once this phenotype emerges, the tumor dramatically changes its behavior due to acid-mediated invasion, an effect that depends on both variations in the tumor cell phenotypes and their spatial distribution within the tumor. In early stages of growth, tumors are stratified, with the most aggressive cells developing within the interior of the tumor. These cells then grow to the edge of the tumor and invade into the normal tissue using acidosis. Simulations suggest that diffusible cytotoxic treatments, such as chemotherapy, may increase the metabolic aggressiveness of a tumor due to drug-mediated selection. Chemotherapy removes the metabolic stratification of the tumor and allows more aggressive cells to grow toward blood vessels and normal tissue. Antiangiogenic therapy also selects for aggressive phenotypes due to degradation of the tumor microenvironment, ultimately resulting in a more invasive tumor. In contrast, pH buffer therapy slows down the development of aggressive tumors, but only if administered when the tumor is still stratified. Overall, findings from this model highlight the risks of cytotoxic and antiangiogenic treatments in the context of tumor heterogeneity resulting from a selection for more aggressive behaviors.

Prediction of individual response to anticancer therapy: historical and future perspectives

Since the introduction of chemotherapy for cancer treatment in the early 20th century considerable efforts have been made to maximize drug efficiency and at the same time minimize side effects. As there is a great interpatient variability in response to chemotherapy, the development of predictive biomarkers is an ambitious aim for the rapidly growing research area of personalized molecular medicine. The individual prediction of response will improve treatment and thus increase survival and life quality of patients. In the past, cell cultures were used as in vitro models to predict in vivo response to chemotherapy. Several in vitro chemosensitivity assays served as tools to measure miscellaneous endpoints such as DNA damage, apoptosis and cytotoxicity or growth inhibition. Twenty years ago, the development of high-throughput technologies, e.g. cDNA microarrays enabled a more detailed analysis of drug responses. Thousands of genes were screened and expression levels were correlated to drug responses. In addition, mutation analysis became more and more important for the prediction of therapeutic success. Today, as research enters the area of -omics technologies, identification of signaling pathways is a tool to understand molecular mechanism underlying drug resistance. Combining new tissue models, e.g. 3D organoid cultures with modern technologies for biomarker discovery will offer new opportunities to identify new drug targets and in parallel predict individual responses to anticancer therapy. In this review, we present different currently used chemosensitivity assays including 2D and 3D cell culture models and several -omics approaches for the discovery of predictive biomarkers. Furthermore, we discuss the potential of these assays and biomarkers to predict the clinical outcome of individual patients and future perspectives.

Towards a Smart Encapsulation System for Small-Sized Electronic Devices: A New Approach

Miniaturized analytical chip devices like biosensors nowadays provide assistance in highly diverse fields of application such as point-of-care diagnostics and industrial bioprocess engineering. However, upon contact with fluids, the sensor requires a protective shell for its electrical components that simultaneously offers controlled access for the target analytes to the measuring units. We therefore developed a capsule that comprises a permeable and a sealed compartment consisting of variable polymers such as biocompatible and biodegradable polylactic acid (PLA) for medical applications or more economical polyvinyl chloride (PVC) and polystyrene (PS) polymers for bioengineering applications. Production of the sealed capsule compartments was performed by heat pressing of polymer pellets placed in individually designable molds. Controlled permeability of the opposite compartments was achieved by inclusion of NaCl inside the polymer matrix during heat pressing, followed by its subsequent release in aqueous solution. Correlating diffusion rates through the so made permeable capsule compartments were quantified for preselected model analytes: glucose, peroxidase, and polystyrene beads of three different diameters (1.4 μm, 4.2 μm, and 20.0 μm). In summary, the presented capsule system turned out to provide sufficient shelter for small-sized electronic devices and gives insight into its potential permeability for defined substances of analytical interest.

A spheroid-based 3-D culture model for pancreatic cancer drug testing, using the acid phosphatase assay

Current therapy for pancreatic cancer is multimodal, involving surgery and chemotherapy. However, development of pancreatic cancer therapies requires a thorough evaluation of drug efficacy in vitro before animal testing and subsequent clinical trials. Compared to two-dimensional culture of cell monolayer, three-dimensional (3-D) models more closely mimic native tissues, since the tumor microenvironment established in 3-D models often plays a significant role in cancer progression and cellular responses to the drugs. Accumulating evidence has highlighted the benefits of 3-D in vitro models of various cancers. In the present study, we have developed a spheroid-based, 3-D culture of pancreatic cancer cell lines MIAPaCa-2 and PANC-1 for pancreatic drug testing, using the acid phosphatase assay. Drug efficacy testing showed that spheroids had much higher drug resistance than monolayers. This model, which is characteristically reproducible and easy and offers rapid handling, is the preferred choice for filling the gap between monolayer cell cultures and in vivo models in the process of drug development and testing for pancreatic cancer.

Diffusion of D-glucose measured in the cytosol of a single astrocyte

Astrocytes interact with neurons and endothelial cells and may mediate exchange of metabolites between capillaries and nerve terminals. In the present study, we investigated intracellular glucose diffusion in purified astrocytes after local glucose uptake. We used a fluorescence resonance energy transfer (FRET)-based nano sensor to monitor the time dependence of the intracellular glucose concentration at specific positions within the cell. We observed a delay in onset and kinetics in regions away from the glucose uptake compared with the region where we locally super-fused astrocytes with the D-glucose-rich solution. We propose a mathematical model of glucose diffusion in astrocytes. The analysis showed that after gradual uptake of glucose, the locally increased intracellular glucose concentration is rapidly spread throughout the cytosol with an apparent diffusion coefficient (D app) of (2.38 ± 0.41) × 10(-10) m(2) s(-1) (at 22-24 °C). Considering that the diffusion coefficient of D-glucose in water is D = 6.7 × 10(-10) m(2) s(-1) (at 24 °C), D app determined in astrocytes indicates that the cytosolic tortuosity, which hinders glucose molecules, is approximately three times higher than in aqueous solution. We conclude that the value of D app for glucose measured in purified rat astrocytes is consistent with the view that cytosolic diffusion may allow glucose and glucose metabolites to traverse from the endothelial cells at the blood-brain barrier to neurons and neighboring astrocytes.

Modeling intercellular transfer of biomolecules through tunneling nanotubes

Tunneling nanotubes (TNTs) have previosly been observed as long and thin transient structures forming between cells and intercellular protein transfer through them has been experimentally verified. It is hypothesized that this may be a physiologically important means of cell-cell communication. This paper attempts to give a simple model for the rates of transfer of molecules across these TNTs at different distances. We describe the transfer of both cytosolic and membrane bound molecules between neighboring populations of cells and argue how the lifetime of the TNT, the diffusion rate, distance between cells, and the size of the molecules may affect their transfer. The model described makes certain predictions and opens a number of questions to be explored experimentally.

Evolution of tumor invasiveness: the adaptive tumor microenvironment landscape model

Interactions between cancer cells and their microenvironment are crucial for promoting tumor growth and invasiveness. In the tumor adaptive landscape model, hypoxic and acidic microenvironmental conditions reduce the fitness of cancer cells and significantly restrict their proliferation. This selects for enhanced motility as cancer cells may evolve an invasive phenotype if the consequent cell movement is rewarded by proliferation. Here, we used an integrative approach combining a mathematical tumor adaptive landscape model with experimental studies to examine the evolutionary dynamics that promote an invasive cancer phenotype. Computer simulation results hypothesized an explicit coupling of motility and proliferation in cancer cells. The mathematical modeling results were also experimentally examined by selecting Panc-1 cells with enhanced motility on a fibroblast-derived 3-dimensional matrix for cells that move away from the unfavorable metabolic constraints. After multiple rounds of selection, the cells that adapted through increased motility were characterized for their phenotypic properties compared with stationary cells. Microarray and gene depletion studies showed the role of Rho-GDI2 in regulating both cell movement and proliferation. Together, this work illustrates the partnership between evolutionary mathematical modeling and experimental validation as a potentially useful approach to study the complex dynamics of the tumor microenvironment.

A local glucose-and oxygen concentration-based insulin secretion model for pancreatic islets

BACKGROUND

Because insulin is the main regulator of glucose homeostasis, quantitative models describing the dynamics of glucose-induced insulin secretion are of obvious interest. Here, a computational model is introduced that focuses not on organism-level concentrations, but on the quantitative modeling of local, cellular-level glucose-insulin dynamics by incorporating the detailed spatial distribution of the concentrations of interest within isolated avascular pancreatic islets.

METHODS

All nutrient consumption and hormone release rates were assumed to follow Hill-type sigmoid dependences on local concentrations. Insulin secretion rates depend on both the glucose concentration and its time-gradient, resulting in second-and first-phase responses, respectively. Since hypoxia may also be an important limiting factor in avascular islets, oxygen and cell viability considerations were also built in by incorporating and extending our previous islet cell oxygen consumption model. A finite element method (FEM) framework is used to combine reactive rates with mass transport by convection and diffusion as well as fluid-mechanics.

RESULTS

The model was calibrated using experimental results from dynamic glucose-stimulated insulin release (GSIR) perifusion studies with isolated islets. Further optimization is still needed, but calculated insulin responses to stepwise increments in the incoming glucose concentration are in good agreement with existing experimental insulin release data characterizing glucose and oxygen dependence. The model makes possible the detailed description of the intraislet spatial distributions of insulin, glucose, and oxygen levels. In agreement with recent observations, modeling also suggests that smaller islets perform better when transplanted and/or encapsulated.

CONCLUSIONS

An insulin secretion model was implemented by coupling local consumption and release rates to calculations of the spatial distributions of all species of interest. The resulting glucose-insulin control system fits in the general framework of a sigmoid proportional-integral-derivative controller, a generalized PID controller, more suitable for biological systems, which are always nonlinear due to the maximum response being limited. Because of the general framework of the implementation, simulations can be carried out for arbitrary geometries including cultured, perifused, transplanted, and encapsulated islets.

A review of three-dimensional in vitro tissue models for drug discovery and transport studies

The use of animal models in drug discovery studies presents issues with feasibility and ethical concerns. To address these limitations, in vitro tissue models have been developed to provide a means for systematic, repetitive, and quantitative investigation of drugs. By eliminating or reducing the need for animal subjects, these models can serve as platforms for more tightly controlled, high-throughput screening of drugs and for pharmacokinetic and pharmacodynamic analyses of drugs. The focus of this review is three-dimensional (3D) tissue models that can capture cell-cell and cell-matrix interactions. Compared to the 2D culture of cell monolayers, 3D models more closely mimic native tissues since the cellular microenvironment established in the 3D models often plays a significant role in disease progression and cellular responses to drugs. A growing body of research has been published in the literature, which highlights the benefits of the 3D in vitro models of various tissues. This review provides an overview of some successful 3D in vitro models that have been developed to mimic liver, breast, cardiac, muscle, bone, and corneal tissues as well as malignant tissues in solid tumors.

A theoretical quantitative model for evolution of cancer chemotherapy resistance

Background

Disseminated cancer remains a nearly uniformly fatal disease. While a number of effective chemotherapies are available, tumors inevitably evolve resistance to these drugs ultimately resulting in treatment failure and cancer progression. Causes for chemotherapy failure in cancer treatment reside in multiple levels: poor vascularization, hypoxia, intratumoral high interstitial fluid pressure, and phenotypic resistance to drug-induced toxicity through upregulated xenobiotic metabolism or DNA repair mechanisms and silencing of apoptotic pathways. We propose that in order to understand the evolutionary dynamics that allow tumors to develop chemoresistance, a comprehensive quantitative model must be used to describe the interactions of cell resistance mechanisms and tumor microenvironment during chemotherapy.

Ultimately, the purpose of this model is to identify the best strategies to treat different types of tumor (tumor microenvironment, genetic/phenotypic tumor heterogeneity, tumor growth rate, etc.). We predict that the most promising strategies are those that are both cytotoxic and apply a selective pressure for a phenotype that is less fit than that of the original cancer population. This strategy, known as double bind, is different from the selection process imposed by standard chemotherapy, which tends to produce a resistant population that simply upregulates xenobiotic metabolism. In order to achieve this goal we propose to simulate different tumor progression and therapy strategies (chemotherapy and glucose restriction) targeting stabilization of tumor size and minimization of chemoresistance.

Results

This work confirms the prediction of previous mathematical models and simulations that suggested that administration of chemotherapy with the goal of tumor stabilization instead of eradication would yield better results (longer subject survival) than the use of maximum tolerated doses. Our simulations also indicate that the simultaneous administration of chemotherapy and 2-deoxy-glucose does not optimize treatment outcome because when simultaneously administered these drugs are antagonists. The best results were obtained when 2-deoxy-glucose was followed by chemotherapy in two separate doses.

Conclusions

These results suggest that the maximum potential of a combined therapy may depend on how each of the drugs modifies the evolutionary landscape and that a rational use of these properties may prevent or at least delay relapse.

Reviewers

This article was reviewed by Dr Marek Kimmel and Dr Mark Little.

Nonlinear modelling of cancer: bridging the gap between cells and tumours

Despite major scientific, medical and technological advances over the last few decades, a cure for cancer remains elusive. The disease initiation is complex, and including initiation and avascular growth, onset of hypoxia and acidosis due to accumulation of cells beyond normal physiological conditions, inducement of angiogenesis from the surrounding vasculature, tumour vascularization and further growth, and invasion of surrounding tissue and metastasis. Although the focus historically has been to study these events through experimental and clinical observations, mathematical modelling and simulation that enable analysis at multiple time and spatial scales have also complemented these efforts. Here, we provide an overview of this multiscale modelling focusing on the growth phase of tumours and bypassing the initial stage of tumourigenesis. While we briefly review discrete modelling, our focus is on the continuum approach. We limit the scope further by considering models of tumour progression that do not distinguish tumour cells by their age. We also do not consider immune system interactions nor do we describe models of therapy. We do discuss hybrid-modelling frameworks, where the tumour tissue is modelled using both discrete (cell-scale) and continuum (tumour-scale) elements, thus connecting the micrometre to the centimetre tumour scale. We review recent examples that incorporate experimental data into model parameters. We show that recent mathematical modelling predicts that transport limitations of cell nutrients, oxygen and growth factors may result in cell death that leads to morphological instability, providing a mechanism for invasion via tumour fingering and fragmentation. These conditions induce selection pressure for cell survivability, and may lead to additional genetic mutations. Mathematical modelling further shows that parameters that control the tumour mass shape also control its ability to invade. Thus, tumour morphology may serve as a predictor of invasiveness and treatment prognosis.

A quantitative theoretical model for the development of malignancy in ductal carcinoma in situ

Mathematical models and clinical observations have demonstrated that microenvironmental hypoxia and acidosis are important selection factors during the later stages of the somatic evolution of breast cancer. The consequent promotion of constitutive upregulation of glycolysis and resistance to acid-induced cellular toxicity is hypothesized to be critical for the ability of cancer cells to invade host tissue. In this work we developed a 3D fixed lattice cellular automata model to study the role of these two phenotypes in determining morphology and the potential for invasion of ductal carcinoma in situ (DCIS), which in this work is defined as the erosion of a healthy epithelial cell layer and direct contact with the basement membrane. The model was conceived as a 40-cell wide epithelial duct surrounded by blood vessels and composed of a basement membrane and one internal layer of epithelial cells. Our results show that an increment in the order of 8-fold in glucose metabolism and an increase in acid resistance corresponding to pH thresholds of approximately 6.8 and 6.45 for quiescence and death, respectively, are required for the tumor to breach through the layer of healthy epithelial cells and reach the basement membrane as a first step for invasion. Our model also suggests correlations between classic morphologies and different values of hyperglycolytic and acid-resistant phenotypes, indicating that immunohistochemistry studies targeting these genes may improve the predictive power of morphological analyses of biopsies.

The potential role of systemic buffers in reducing intratumoral extracellular pH and acid-mediated invasion

A number of studies have shown that the extracellular pH (pHe) in cancers is typically lower than that in normal tissue and that an acidic pHe promotes invasive tumor growth in primary and metastatic cancers. Here, we investigate the hypothesis that increased systemic concentrations of pH buffers reduce intratumoral and peritumoral acidosis and, as a result, inhibit malignant growth. Computer simulations are used to quantify the ability of systemic pH buffers to increase the acidic pHe of tumors in vivo and investigate the chemical specifications of an optimal buffer for such purpose. We show that increased serum concentrations of the sodium bicarbonate (NaHCO(3)) can be achieved by ingesting amounts that have been used in published clinical trials. Furthermore, we find that consequent reduction of tumor acid concentrations significantly reduces tumor growth and invasion without altering the pH of blood or normal tissues. The simulations also show that the critical parameter governing buffer effectiveness is its pK(a). This indicates that NaHCO(3), with a pK(a) of 6.1, is not an ideal intratumoral buffer and that greater intratumoral pHe changes could be obtained using a buffer with a pK(a) of approximately 7. The simulations support the hypothesis that systemic pH buffers can be used to increase the tumor pHe and inhibit tumor invasion.

Metabolic changes during carcinogenesis: potential impact on invasiveness

Successful adaptation to varying microenvironmental constraints plays a crucial role during carcinogenesis. We develop a hybrid cellular automation approach to investigate the cell-microenvironmental interactions that mediate somatic evolution of cancer cells. This allows investigation of the hypothesis that regions of premalignant lesions develop a substrate-limited environment as proliferation carries cells away from blood vessels which remain separated by the intact basement membrane. We find that selective forces in tumoural regions furthest from the blood supply act to favour cells whose metabolism is best suited to respond to local changes in oxygen, glucose and pH levels. The model predicts three phases of somatic evolution. Initially, cell survival and proliferation is limited due to diminished oxygen levels. This promotes adaptation to a second phase of growth dominated by cells with constitutively up-regulated glycolysis, less reliant on oxygen for ATP production. Increased glycolysis induces acidification of the local environment, limiting proliferation and inducing cell death through necrosis and apoptosis. This promotes a third phase of cellular evolution, with emergence of phenotypes resistant to acid-induced toxicity. This emergent cellular phenotype has a significant proliferative advantage because it will consistently acidify the local environment in a way that is toxic to its competitors but harmless to itself. The model's results suggest this sequence is essential in the transition from self-limited premalignant growth to invasive cancer, and, therefore, that this transition may be delayed or prevented through novel strategies directed towards interrupting the hypoxia-glycolysis-acidosis cycle.

The use of 3-D cultures for high-throughput screening: the multicellular spheroid model

Over the past few years, establishment and adaptation of cell-based assays for drug development and testing has become an important topic in high-throughput screening (HTS). Most new assays are designed to rapidly detect specific cellular effects reflecting action at various targets. However, although more complex than cell-free biochemical test systems, HTS assays using monolayer or suspension cultures still reflect a highly artificial cellular environment and may thus have limited predictive value for the clinical efficacy of a compound. Today's strategies for drug discovery and development, be they hypothesis free or mechanism based, require facile, HTS-amenable test systems that mimic the human tissue environment with increasing accuracy in order to optimize preclinical and preanimal selection of the most active molecules from a large pool of potential effectors, for example, against solid tumors. Indeed, it is recognized that 3-dimensional cell culture systems better reflect the in vivo behavior of most cell types. However, these 3-D test systems have not yet been incorporated into mainstream drug development operations. This article addresses the relevance and potential of 3-D in vitro systems for drug development, with a focus on screening for novel antitumor drugs. Examples of 3-D cell models used in cancer research are given, and the advantages and limitations of these systems of intermediate complexity are discussed in comparison with both 2-D culture and in vivo models. The most commonly used 3-D cell culture systems, multicellular spheroids, are emphasized due to their advantages and potential for rapid development as HTS systems. Thus, multicellular tumor spheroids are an ideal basis for the next step in creating HTS assays, which are predictive of in vivo antitumor efficacy.

Tissue gradients of energy metabolites mirror oxygen tension gradients in a rat mammary carcinoma model

PURPOSE

It has been shown that oxygen gradients exist in R3230AC tumors grown in window chambers. The fascial surface is better oxygenated than the tumor surface. The purpose of the present study was to determine whether gradients exist for energy metabolites and other end points related to oxygen transport.

METHODS AND MATERIALS

Imaging bioluminescence was used to measure ATP, glucose, and lactate in cryosections of R3230AC tumors. Mean vessel density and hypoxic tissue fraction were assessed using immunohistochemistry. Tumor redox ratio was assessed by redox ratio scanning.

RESULTS

Lactate content and hypoxic fraction increased, whereas ATP, glucose, redox ratio, and vessel density decreased from the fascial to the tumor surface.

CONCLUSIONS

The data support a switch from aerobic to anaerobic metabolism concomitant with the PO2 gradient. The vascular hypoxia that exists in perfused vessels at the tumor surface leads to macroscopic tissue regions with restricted oxygen availability and altered metabolic status. Methods to reduce tumor hypoxia may have to take this into account if such gradients exist in human tumors. The results also have implications for hypoxia imaging, because macroscopic changes in PO2 (or related parameters) will be easier to see than PO2 gradients limited to the diffusion distance of oxygen.

Localized delivery of proteins in the brain: can transport be customized?

Certain central nervous system (CNS) diseases are characterized by the degeneration of specific cell populations. One strategy for treating neurodegenerative diseases is long-term, controlled delivery of proteins such as epidermal growth factor (EGF) and nerve growth factor (NGF). Since proteins permeate through brain capillaries very slowly, local administration using polymeric implants, continuous infusion pumps, or transplanted, protein-secreting cells may be required to achieve therapeutic concentrations in the tissue. The efficiency of local distribution, and hence effectiveness of local therapy, depends on the rate of protein migration through tissue. The rate of dispersion of molecules in a quiescent, isotropic medium can be characterized by the molecular diffusion coefficient, D, which can be measured by techniques such as quantitative autoradiography, iontophoresis, and fluorescence photobleaching recovery (FPR). These methods are reviewed, with an emphasis on their application to measurement of D for proteins in the brain. Biophysical techniques yield quantitative descriptions of local protein distribution and may enable discrimination of mechanisms of protein transport in the brain. This capability suggests a new paradigm for design of protein therapies, in which proteins and delivery systems are collectively customized to provide sustained protein availability over predetermined volumes of tissue.

An experimental and mathematical model for the extravascular transport of a DNA intercalator in tumours

A new in vitro model has been developed for investigating extravascular diffusion of therapeutic agents in tumour tissue. V79-171b or EMT6/Ak cells are grown on porous Teflon support membranes and submerged in a large reservoir of medium, to give diffusion-limited 'multicellular membranes' (MMs) c. 200 microm in thickness. MMs are histologically similar to multicellular spheroids, but their planar rather than spherical geometry facilitates direct measurement of the flux of radiolabelled agents through the multicellular structure. For [14C]urea, flux kinetics through V79-171b MMs was modelled as simple diffusion, yielding a diffusion coefficient in the MM (DMM) of 1.45 x 10(-6) cm2 s(-1), 11-fold lower than in culture medium. Flux of the 3H-labelled DNA intercalator 9-[3-(N,N-dimethylamino)propylamino]acridine (DAPA) was dramatically slower than urea. Modelling this over the first 5 h gave a DMM of 1.3 x 10(-8) cm2 s(-1), but over longer times the kinetics was not consistent with simple diffusion. Flux of DAPA was markedly increased in the presence of 50 mM ammonium chloride, indicating that sequestration in acidic endosomes is a major impediment to flux. Accumulation in cytoplasmic vesicles was confirmed by fluorescence microscopy. The DAPA flux kinetics, with and without ammonium chloride, was well fitted by a reaction-diffusion model with reversible cellular uptake (modelled as binding), using uptake parameters determined in separate experiments with V79-171b single-cell suspensions. This study demonstrates the utility of the MM model for determining extravascular transport parameters, and indicates that much of the impediment to diffusion of basic DNA intercalators in tumour tissue may arise from lysosomal sequestration rather than DNA binding.