Influence of glucose and oxygen supply conditions on the oxygenation of multicellular spheroids

Microdissection tools to generate organoids for modeling the tumor immune microenvironment

Patient-derived tumor organoids have emerged as promising models for predicting personalized drug responses in cancer therapy, but they typically lack immune components. Preserving the in vivo association between tumor cells and endogenous immune cells is critical for accurate testing of cancer immunotherapies. Mechanical dissection of tumor specimens into tumor fragments, as opposed to enzymatic digestion into single cells, is essential for maintaining these native tumor-immune cell spatial relationships. However, conventional mechanical dissection relying on manual mincing is time-consuming and irreproducible. This study describes two microdissection devices, the µDicer and µGrater, to facilitate the generation of intact tumor fragments from mouse B16 melanoma, a common model of human melanoma. The µDicer- and µGrater-cut tumor fragments were used to generate air‒liquid interface (ALI) organoids that copreserve tumor cells with infiltrating immune subsets without artificial reconstitution. The µDicer, consisting of a hexagonal array of silicon microblades, was employed to investigate the effect of organoid size. The viability of ALI organoid immune cells appeared insensitive to organoid sizes exceeding ~400 µm but diminished in organoids ~200 µm in size. The µGrater, consisting of an array of submillimeter holes in stainless steel, was employed to accelerate dissection. For the samples studied, the µGrater was 4.5 times faster than manual mincing. Compared with those generated by manual mincing, ALI organoids generated by the µGrater demonstrated similar viability, immune cell composition, and responses to anti-PD-1 immunotherapy. With further optimization, the µGrater holds potential for integration into clinical workflows to support the advancement of personalized cancer immunotherapy.

Live Microscopy of Multicellular Spheroids with the Multimodal Near-Infrared Nanoparticles Reveals Differences in Oxygenation Gradients

Assessment of hypoxia, nutrients, metabolite gradients, and other hallmarks of the tumor microenvironment within 3D multicellular spheroid and organoid models represents a challenging analytical task. Here, we report red/near-infrared (NIR) emitting cell staining with O2-sensitive nanoparticles, which enable measurements of spheroid oxygenation on a conventional fluorescence microscope. Nanosensor probes, termed "MMIR" (multimodal infrared), incorporate an NIR O2-sensitive metalloporphyrin (PtTPTBPF) and deep red aza-BODIPY reference dyes within a biocompatible polymer shell, allowing for oxygen gradient quantification via fluorescence ratio and phosphorescence lifetime readouts. We optimized staining techniques and evaluated the nanosensor probe characteristics and cytotoxicity. Subsequently, we applied nanosensors to the live spheroid models based on HCT116, DPSCs, and SKOV3 cells, at rest, and treated with drugs affecting cell respiration. We found that the growth medium viscosity, spheroid size, and formation method influenced spheroid oxygenation. Some spheroids produced from HCT116 and dental pulp stem cells exhibited "inverted" oxygenation gradients, with higher core oxygen levels than the periphery. This contrasted with the frequently encountered "normal" gradient of hypoxia toward the core caused by diffusion. Further microscopy analysis of spheroids with an "inverted" gradient demonstrated metabolic stratification of cells within spheroids: thus, autofluorescence FLIM of NAD(P)H indicated the formation of a glycolytic core and localization of OxPhos-active cells at the periphery. Collectively, we demonstrate a strong potential of NIR-emitting ratiometric nanosensors for advanced microscopy studies targeting live and quantitative real-time monitoring of cell metabolism and hypoxia in complex 3D tissue models.

ATF4 May Be Essential for Adaption of the Ocular Lens to Its Avascular Environment

The late embryonic mouse lens requires the transcription factor ATF4 for its survival although the underlying mechanisms were unknown. Here, RNAseq analysis revealed that E16.5 Atf4 null mouse lenses downregulate the mRNA levels of lens epithelial markers as well as known markers of late lens fiber cell differentiation. However, a comparison of this list of differentially expressed genes (DEGs) with other known transcriptional regulators of lens development indicated that ATF4 expression is not directly controlled by the previously described lens gene regulatory network. Pathway analysis revealed that the Atf4 DEG list was enriched in numerous genes involved in nutrient transport, amino acid biosynthesis, and tRNA charging. These changes in gene expression likely result in the observed reductions in lens free amino acid and glutathione levels, which would result in the observed low levels of extractable lens protein, finally leading to perinatal lens disintegration. These data demonstrate that ATF4, via its function in the integrated stress response, is likely to play a crucial role in mediating the adaption of the lens to the avascularity needed to maintain lens transparency.

A reduced model of cell metabolism to revisit the glycolysis-OXPHOS relationship in the deregulated tumor microenvironment

Cancer cells metabolism focuses the interest of the cancer research community. Although this process is intensely studied experimentally, there are very few theoretical models that address this issue. One of the main reasons is the extraordinary complexity of the metabolism that involves numerous interdependent regulatory networks which makes the computational recreation of this complexity illusory. In this study we propose a reduced model of the metabolism which focuses on the interrelation of the three main energy metabolites which are oxygen, glucose and lactate in order to better understand the dynamics of the core system of the glycolysis-OXPHOS relationship. So simple as it is, the model highlights the main rules allowing the cell to dynamically adapt its metabolism to its changing environment. It also makes it possible to address this impact at the tissue scale. The simulations carried out in a spheroid show non-trivial spatial heterogeneity of energy metabolism. It further suggests that the metabolic features that are commonly attributed to cancer cells are not necessarily due to an intrinsic abnormality of the cells. They can emerge spontaneously due to the deregulated over-acidic environment.

Microwell-based flow culture increases viability and restores drug response in prostate cancer spheroids

3D cancer spheroids represent a highly promising model for study of cancer progression and therapeutic development. Wide-scale adoption of cancer spheroids, however, remains a challenge due to the lack of control over hypoxic gradients that may cloud the assessment of cell morphology and drug response. Here, we present a Microwell Flow Device (MFD) that generates in-well laminar flow around 3D tissues via repetitive tissue sedimentation. Using a prostate cancer cell line, we demonstrate the spheroids in the MFD exhibit improved cell growth, reduced necrotic core formation, enhanced structural integrity, and downregulated expression of cell stress genes. The flow-cultured spheroids also exhibit an improved sensitivity to chemotherapy with greater transcriptional response. These results demonstrate how fluidic stimuli reveal the cellular phenotype previously masked by severe necrosis. Our platform advances 3D cellular models and enables study into hypoxia modulation, cancer metabolism, and drug screening within pathophysiological conditions.

Growth and adaptation mechanisms of tumour spheroids with time-dependent oxygen availability

Tumours are subject to external environmental variability. However, in vitro tumour spheroid experiments, used to understand cancer progression and develop cancer therapies, have been routinely performed for the past fifty years in constant external environments. Furthermore, spheroids are typically grown in ambient atmospheric oxygen (normoxia), whereas most in vivo tumours exist in hypoxic environments. Therefore, there are clear discrepancies between in vitro and in vivo conditions. We explore these discrepancies by combining tools from experimental biology, mathematical modelling, and statistical uncertainty quantification. Focusing on oxygen variability to develop our framework, we reveal key biological mechanisms governing tumour spheroid growth. Growing spheroids in time-dependent conditions, we identify and quantify novel biological adaptation mechanisms, including unexpected necrotic core removal, and transient reversal of the tumour spheroid growth phases.

In Vitro 3D Modeling of Neurodegenerative Diseases

The study of neurodegenerative diseases (such as Alzheimer's disease, Parkinson's disease, Huntington's disease, or amyotrophic lateral sclerosis) is very complex due to the difficulty in investigating the cellular dynamics within nervous tissue. Despite numerous advances in the in vivo study of these diseases, the use of in vitro analyses is proving to be a valuable tool to better understand the mechanisms implicated in these diseases. Although neural cells remain difficult to obtain from patient tissues, access to induced multipotent stem cell production now makes it possible to generate virtually all neural cells involved in these diseases (from neurons to glial cells). Many original 3D culture model approaches are currently being developed (using these different cell types together) to closely mimic degenerative nervous tissue environments. The aim of these approaches is to allow an interaction between glial cells and neurons, which reproduces pathophysiological reality by co-culturing them in structures that recapitulate embryonic development or facilitate axonal migration, local molecule exchange, and myelination (to name a few). This review details the advantages and disadvantages of techniques using scaffolds, spheroids, organoids, 3D bioprinting, microfluidic systems, and organ-on-a-chip strategies to model neurodegenerative diseases.

Targeted alpha therapy with the 224Ra/212Pb-TCMC-TP-3 dual alpha solution in a multicellular tumor spheroid model of osteosarcoma

Osteosarcoma patients with overt metastases at primary diagnosis have a 5-year survival rate of less than 20%. TP-3 is a murine IgG2b monoclonal antibody with high affinity for an epitope residing on the p80 osteosarcoma cell surface membrane antigen. The tumor-associated antigen p80 is overexpressed in osteosarcomas, and has very low normal tissue expression. We propose a novel dual alpha targeting solution containing two radionuclides from the same decay chain, including the bone-seeking ²²⁴Ra, and cancer cell-surface seeking ²¹²Pb-TCMC-TP-3 for the treatment of osteoblastic bone cancers, circulating cancer cells and micrometastases. In this in vitro study, the cytotoxic effects of ²¹²Pb-TCMC-TP-3 (single alpha solution) and ²²⁴Ra/²¹²Pb-TCMC-TP-3 (dual alpha solution) were investigated in a multicellular spheroid model mimicking micrometastatic disease in osteosarcoma. OHS spheroids with diameters of 253 ± 98 μm treated with 4.5, 2.7, and 3.3 kBq/ml of ²¹²Pb-TCMC-TP-3 for 1, 4, and 24 h, respectively, were disintegrated within 3 weeks. The ²¹²Pb-TCMC-TP-3 induced a 7-fold delay in spheroid doubling time compared to a 28-times higher dose with the non-specific ²¹²Pb-TCMC-rituximab. The ²²⁴Ra/²¹²Pb-TCMC-TP-3 completely disintegrated spheroids with diameters of 218-476 μm within 3 and 2 weeks after 4 and 24 h incubation with 5 kBq/ml, respectively. Treatment with 1 kBq/ml of ²²⁴Ra/²¹²Pb-TCMC-TP-3 for 24 h caused an 11.4-fold reduction in spheroid viability compared with unconjugated ²²⁴Ra/²¹²Pb. The single and dual alpha solutions with TP-3 showed cytotoxicity in spheroids of clinically relevant size, which warrant further testing of the dual alpha solution using in vivo osteosarcoma models.

In vitro radiosensitization of breast cancer with hypoxia-activated prodrugs

KP167 is a novel hypoxia‐activated prodrug (HAP), targeting cancer cells via DNA intercalating and alkylating properties. The single agent and radiosensitizing efficacy of KP167 and its parental comparator, AQ4N, were evaluated in 2D and 3D cultures of luminal and triple negative breast cancer (TNBC) cell lines and compared against DNA damage repair inhibitors. 2D normoxic treatment with the DNA repair inhibitors, Olaparib or KU‐55933 caused, as expected, substantial radiosensitization (sensitiser enhancement ratio, SER_0.01 of 1.60–3.42). KP167 induced greater radiosensitization in TNBC (SER_0.01 2.53 in MDAMB‐231, 2.28 in MDAMB‐468, 4.55 in MDAMB‐436) and luminal spheroids (SER_0.01 1.46 in MCF‐7 and 1.76 in T47D cells) compared with AQ4N. Significant radiosensitization was also obtained using KP167 and AQ4N in 2D normoxia. Although hypoxia induced radioresistance, radiosensitization by KP167 was still greater under 2D hypoxia, yielding SER_0.01 of 1.56–2.37 compared with AQ4N SER_0.01 of 1.13–1.94. Such data show KP167 as a promising single agent and potent radiosensitiser of both normoxic and hypoxic breast cancer cells, with greater efficacy in TNBCs.

Metabolic flux analysis of 3D spheroids reveals significant differences in glucose metabolism from matched 2D cultures of colorectal cancer and pancreatic ductal adenocarcinoma cell lines

BACKGROUND

Most in vitro cancer cell experiments have been performed using 2D models. However, 3D spheroid cultures are increasingly favored for being more representative of in vivo tumor conditions. To overcome the translational challenges with 2D cell cultures, 3D systems better model more complex cell-to-cell contact and nutrient levels present in a tumor, improving our understanding of cancer complexity. Despite this need, there are few reports on how 3D cultures differ metabolically from 2D cultures.

METHODS

Well-described cell lines from colorectal cancer (HCT116 and SW948) and pancreatic ductal adenocarcinoma (Panc-1 and MIA-Pa-Ca-2) were used to investigate metabolism in 3D spheroid models. The metabolic variation under normal glucose conditions were investigated comparing 2D and 3D cultures by metabolic flux analysis and expression of key metabolic proteins.

RESULTS

We find significant differences in glucose metabolism of 3D cultures compared to 2D cultures, both related to glycolysis and oxidative phosphorylation. Spheroids have higher ATP-linked respiration in standard nutrient conditions and higher non-aerobic ATP production in the absence of supplemented glucose. In addition, ATP-linked respiration is significantly inversely correlated with OCR/ECAR (p = 0.0096). Mitochondrial transport protein, TOMM20, expression decreases in all spheroid models compared to 2D, and monocarboxylate transporter (MCT) expression increases in 3 of the 4 spheroid models.

CONCLUSIONS

In this study of CRC and PDAC cell lines, we demonstrate that glucose metabolism in 3D spheroids differs significantly from 2D cultures, both in terms of glycolytic and oxidative phosphorylation metrics. The metabolic phenotype shift from 2D to 3D culture in one cell line is greater than the phenotypic differences between each cell line and tumor source. The results herein emphasize the need to use 3D cell models for investigating nutrient utilization and metabolic flux for a better understanding of tumor metabolism and potential metabolic therapeutic targets.

Shape‐Mediated Magnetocrystalline Anisotropy and Relaxation Controls by Cobalt Ferrite Core–Shell Heterostructures for Magnetothermal Penetration Delivery

Simultaneous delivery of therapeutic agents and energy by magnetic nanoparticles (MNPs) at targeted sites can boost cancer therapy and alleviate side effects. To achieve this goal, however, the magnetic fluid hyperthermia (MFH) usually exhibits the unsufficient thermal efficiency due to their narrow magnetization curves. Besides, an inappropriately large administration concentration also causes health deterioration as shown in an animal model. In this study, the core–shell cube that enhances the coercivity and magnetization related to single‐compositional MNPs by elaborately tuning their interface relaxation via the magnetocrystalline and surface anisotropy is developed. Néel and Brownian relaxation can be adjusted by the particles’ structures to maximize the hyperthermia efficacy upon an alternating‐magnetic‐field (AMF). Furthermore, temozolomide and lactoferrin‐coated CoFe2O4@Fe3O4 core–shell cubes are rapidly internalized by targeting cancer cells and penetrate into tumor spheroids while subjecting to AMF. The targeted cubes with the capabilities of enhanced coercivity, AMF‐induced drug penetration into tumors, and magnetothermal ablation for cancer therapy display potentials for clinical uses.

A continuum mechanical framework for modeling tumor growth and treatment in two- and three-phase systems

The growth and treatment of tumors is an important problem to society that involves the manifestation of cellular phenomena at length scales on the order of centimeters. Continuum mechanical approaches are being increasingly used to model tumors at the largest length scales of concern. The issue of how to best connect such descriptions to smaller-scale descriptions remains open. We formulate a framework to derive macroscale models of tumor behavior using the thermodynamically constrained averaging theory (TCAT), which provides a firm connection with the microscale and constraints on permissible forms of closure relations. We build on developments in the porous medium mechanics literature to formulate fundamental entropy inequality expressions for a general class of three-phase, compositional models at the macroscale. We use the general framework derived to formulate two classes of models, a two-phase model and a three-phase model. The general TCAT framework derived forms the basis for a wide range of potential models of varying sophistication, which can be derived, approximated, and applied to understand not only tumor growth but also the effectiveness of various treatment modalities.

Prediction and validation of avascular tumor growth pattern in different metabolic conditions using in silico and in vitro models

Objectives: In recent years, scientists have taken many efforts for in vitro and in silico modeling of cancerous tumors. In fact, three-dimensional (3D) cultures of multicellular tumor spheroids (MCTSs) are good validators for computational results. The goal of this study is to simulate the 3D early growth of avascular tumors using MCTSs and to compare the in vitro models with the results and predictions of a specific computational modeling framework. Using these two types of models, the importance of metabolic condition on tumor growth behavior and necrosis could be predicted. Materials and methods: We took advantage of a previously developed computational model of tumor growth (constructed by integrating a generic metabolic network model of cancer cells with a multiscale agent-based framework). Among the computational predictions is the importance of glucose accessibility on tumor growth behavior. To study the effect of glucose concentration experimentally, MCTSs were grown in high and low glucose culture media. After that, tumor growth pattern was analyzed by MTT assay, cell counting and propidium iodide (PI) staining. Results: We obviously observed that the rate of necrosis increases and the rate of tumor growth and cell activity decreases as the glucose availability reduces, which is in line with the computational model prediction.

Spatially resolved metabolomics combined with multicellular tumor spheroids to discover cancer tissue relevant metabolic signatures

Spatially resolved metabolomics offers unprecedented opportunities for elucidating metabolic mechanisms during cancer progression. It facilitated the discovery of aberrant cellular metabolism with clinical application potential. Here, we developed a novel strategy to discover cancer tissue relevant metabolic signatures by high spatially resolved metabolomics combined with a multicellular tumor spheroid (MCTS) in vitro model. Esophageal cancer MCTS were generated using KYSE-30 human esophageal cancer cells to fully mimic the 3D microenvironment under physiological conditions. Then, the spatial features and temporal variation of metabolites and metabolic pathways in MCTS were accurately mapped by using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) with a spatial resolution at ∼12 μm. Metabolites, such as glutamate, tyrosine, inosine and various types of lipids displayed heterogeneous distributions in different microregions inside the MCTS, revealing the metabolic heterogenicity of cancer cells under different proliferative states. Subsequently, through joint analysis of metabolomic data of clinical cancer tissue samples, cancer tissue relevant metabolic signatures in esophageal cancer MCTS were identified, including glutamine metabolism, fatty acid metabolism, de novo synthesis phosphatidylcholine (PC) and phosphatidylethanolamine (PE), etc. In addition, the abnormal expression of the involved metabolic enzymes, i.e., GLS, FASN, CHKA and cPLA2, was further confirmed and showed similar tendencies in esophageal cancer MCTS and cancer tissues. The MALDI-MSI combined with MCTS approach offers molecular insights into cancer metabolism with real-word relevance, which would potentially benefit the biomarker discovery and metabolic mechanism studies.

The Importance of Proper Oxygenation in 3D Culture

Cell culture typically employs inexpensive, disposable plasticware, and standard humidified CO₂/room air incubators (5% CO₂, ∼20% oxygen). These methods have historically proven adequate for the maintenance of viability, function, and proliferation of many cell types, but with broad variation in culture practices. With technological advances it is becoming increasingly clear that cell culture is not a “one size fits all” procedure. Recently, there is a shift toward comprehension of the individual physiological niches of cultured cells. As scale-up production of single cell and 3D aggregates for therapeutic applications has expanded, researchers have focused on understanding the role of many environmental metabolites/forces on cell function and viability. Oxygen, due to its role in cell processes and the requirement for adequate supply to maintain critical energy generation, is one such metabolite gaining increased focus. With the advent of improved sensing technologies and computational predictive modeling, it is becoming evident that parameters such as cell seeding density, culture media height, cellular oxygen consumption rate, and aggregate dimensions should be considered for experimental reproducibility. In this review, we will examine the role of oxygen in 3D cell culture with particular emphasis on primary islets of Langerhans and stem cell-derived insulin-producing SC-β cells, both known for their high metabolic demands. We will implement finite element modeling (FEM) to simulate historical and current culture methods in referenced manuscripts and innovations focusing on oxygen distribution. Our group and others have shown that oxygen plays a key role in proliferation, differentiation, and function of these 3D aggregates. Their culture in plastic consistently results in core regions of hypoxia/anoxia exacerbated by increased media height, aggregate dimensions, and oxygen consumption rates. Static gas permeable systems ameliorate this problem. The use of rotational culture and other dynamic culture systems also have advantages in terms of oxygen supply but come with the caveat that these endocrine aggregates are also exquisitely sensitive to mechanical perturbation. As recent work demonstrates, there is a strong rationale for the use of alternate in vitro systems to maintain physio-normal environments for cell growth and function for better phenotypic approximation of in vivo counterparts.

Predicting the results of competition between two breast cancer lines grown in 3-D spheroid culture

This study develops a novel model of a consumer-resource system with mobility included, in order to explain a novel experiment of competition between two breast cancer cell lines grown in 3D in vitro spheroid culture. The model reproduces observed differences in monoculture, such as overshoot phenomena and final size. It also explains both theoretically and through simulation the inevitable triumph of the same cell line in co-culture, independent of initial conditions. The mobility of one cell line (MDA-MB-231) is required to explain both the success and the rapidity with which that species dominates the population and drives the other species (MCF-7) to extinction. It is shown that mobility directly interferes with the other species and that the cost of that mobility is in resource usage rate.

Frequency-dependent interactions determine outcome of competition between two breast cancer cell lines

Tumors are highly dynamic ecosystems in which diverse cancer cell subpopulations compete for space and resources. These complex, often non-linear interactions govern continuous spatial and temporal changes in the size and phenotypic properties of these subpopulations. Because intra-tumoral blood flow is often chaotic, competition for resources may be a critical selection factor in progression and prognosis. Here, we quantify resource competition using 3D spheroid cultures with MDA-MB-231 and MCF-7 breast cancer cells. We hypothesized that MCF-7 cells, which primarily rely on efficient aerobic glucose metabolism, would dominate the population under normal pH and low glucose conditions; and MDA-MB-231 cells, which exhibit high levels of glycolytic metabolism, would dominate under low pH and high glucose conditions. In spheroids with single populations, MCF-7 cells exhibited equal or superior intrinsic growth rates (density-independent measure of success) and carrying capacities (density-dependent measure of success) when compared to MDA-MB-231 cells under all pH and nutrient conditions. Despite these advantages, when grown together, MCF-7 cells do not always outcompete MDA-MB-231 cells. MDA-MB-231 cells outcompete MCF-7 cells in low glucose conditions and coexistence is achieved in low pH conditions. Under all conditions, MDA-MB-231 has a stronger competitive effect (frequency-dependent interaction) on MCF-7 cells than vice-versa. This, and the inability of growth rate or carrying capacity when grown individually to predict the outcome of competition, suggests a reliance on frequency-dependent interactions and the need for competition assays. We frame these results in a game-theoretic (frequency-dependent) model of cancer cell interactions and conclude that competition assays can demonstrate critical density-independent, density-dependent and frequency-dependent interactions that likely contribute to in vivo outcomes.

An on-lattice agent-based Monte Carlo model simulating the growth kinetics of multicellular tumor spheroids

PURPOSE

To develop an on-lattice agent-based model describing the growth of multicellular tumor spheroids using simple Monte Carlo tools.

METHODS

Cells are situated on the vertices of a cubic grid. Different cell states (proliferative, hypoxic or dead) and cell evolution rules, driven by 10 parameters, and the effects of the culture medium are included. About twenty spheroids of MCF-7 human breast cancer were cultivated and the experimental data were used for tuning the model parameters.

RESULTS

Simulated spheroids showed adequate sizes of the necrotic nuclei and of the hypoxic and proliferative cell phases as a function of the growth time, mimicking the overall characteristics of the experimental spheroids. The relation between the radii of the necrotic nucleus and the whole spheroid obtained in the simulations was similar to the experimental one and the number of cells, as a function of the spheroid volume, was well reproduced. The statistical variability of the Monte Carlo model described the whole volume range observed for the experimental spheroids. Assuming that the model parameters vary within Gaussian distributions it was obtained a sample of spheroids that reproduced much better the experimental findings.

CONCLUSIONS

The model developed allows describing the growth of in vitro multicellular spheroids and the experimental variability can be well reproduced. Its flexibility permits to vary both the agents involved and the rules that govern the spheroid growth. More general situations, such as, e. g., tumor vascularization, radiotherapy effects on solid tumors, or the validity of the tumor growth mathematical models can be studied.

Agent-based model of multicellular tumor spheroid evolution including cell metabolism

Computational models aiming at the spatio-temporal description of cancer evolution are a suitable framework for testing biological hypotheses from experimental data, and generating new ones. Building on our recent work (J. Theor. Biol. 389, 146 (2016)) we develop a 3D agent-based model, capable of tracking hundreds of thousands of interacting cells, over time scales ranging from seconds to years. Cell dynamics is driven by a Monte Carlo solver, incorporating partial differential equations to describe chemical pathways and the activation/repression of "genes", leading to the up- or down-regulation of specific cell markers. Each cell-agent of different kind (stem, cancer, stromal etc.) runs through its cycle, undergoes division, can exit to a dormant, senescent, necrotic state, or apoptosis, according to the inputs from its systemic network. The basic network at this stage describes glucose/oxygen/ATP cycling, and can be readily extended to cancer-cell specific markers. Eventual accumulation of chemical/radiation damage to each cell's DNA is described by a Markov chain of internal states, and by a damage-repair network, whose evolution is linked to the cell systemic network. Aimed at a direct comparison with experiments of tumorsphere growth from stem cells, the present model will allow to quantitatively study the role of transcription factors involved in the reprogramming and variable radio-resistance of simulated cancer-stem cells, evolving in a realistic computer simulation of a growing multicellular tumorsphere.

Circulating Tumour Cells in Predictive Molecular Pathology: Focus on Drug-Sensitive Assays and 3D Culture

Molecular cytopathology is a rapidly evolving field of cytopathology that provides biological information about the response to personalised therapy and about the prognosis of neoplasms diagnosed on cytological samples. Biomarkers such as circulating tumour cells and circulating tumour DNA are increasingly being evaluated in blood and in other body fluids. Such liquid biopsies are non-invasive, repeatable, and feasible also in patients with severe comorbidities. However, liquid biopsy may be challenging due to a low concentration of biomarkers. In such cases, biomarkers can be detected with highly sensitive molecular techniques, which in turn should be validated and integrated in a complex algorithm that includes tissue-based molecular assessments. The aim of this review is to provide the cytopathologist with practical information that is relevant to daily practice, particularly regarding the emerging role of circulating tumour cells in the field of predictive molecular pathology.

Human 3D Cultures as Models for Evaluating Magnetic Nanoparticle CNS Cytotoxicity after Short- and Repeated Long-Term Exposure

Since nanoparticles (NPs) can translocate to the brain and impact the highly vulnerable central nervous system (CNS), novel in vitro tools for the assessment of NP-induced neurotoxicity are advocated. In this study, two types of CNS spheroids have been developed from human D384 astrocyte- and SH-SY5Y neuronal-like cells, and optimized in combination with standard assays (viability readout and cell morphology) to test neurotoxic effects caused by Fe₃O₄NPs, as NP-model, after short- (24–48 h; 1–100µg/ml) and long-term repeated exposure (30days; 0.1–25µg/ml). Short-term exposure of 3D-spheroids to Fe₃O₄NP induced cytotoxicity at 10 µg/mL in astrocytes and 25 µg/mL neurons. After long-term repeated dose regimen, spheroids showed concentration- and time-dependent cell mortality at 10 µg/mL for D384 and 0.5 µg/mL for SH-SY5Y, indicating a higher susceptibility of neurons than astrocytes. Both spheroid types displayed cell disaggregation after the first week of treatment at ≥0.1 µg/mL and becoming considerably evident at higher concentrations and over time. Recreating the 3D-spatial environment of the CNS allows cells to behave in vitro more closely to the in vivo situations, therefore providing a model that can be used as a stand-alone test or as a part of integrated testing strategies. These models could drive an improvement in the species-relevant predictivity of toxicity testing.

The pivotal role of angiogenesis in a multi-scale modeling of tumor growth exhibiting the avascular and vascular phases

The mechanisms involved in tumor growth mainly occur at the microenvironment, where the interactions between the intracellular, intercellular and extracellular scales mediate the dynamics of tumor. In this work, we present a multi-scale model of solid tumor dynamics to simulate the avascular and vascular growth as well as tumor-induced angiogenesis. The extracellular and intercellular scales are modeled using partial differential equations and cellular Potts model, respectively. Also, few biochemical and biophysical rules control the dynamics of intracellular level. On the other hand, the growth of melanoma tumors is modeled in an animal in-vivo study to evaluate the simulation. The simulation shows that the model successfully reproduces a completed image of processes involved in tumor growth such as avascular and vascular growth as well as angiogenesis. The model incorporates the phenotypes of cancerous cells including proliferating, quiescent and necrotic cells, as well as endothelial cells during angiogenesis. The results clearly demonstrate the pivotal effect of angiogenesis on the progression of cancerous cells. Also, the model exhibits important events in tumor-induced angiogenesis like anastomosis. Moreover, the computational trend of tumor growth closely follows the observations in the experimental study.

Obstacles in the Application of Microencapsulation in Islet Transplantation

Several factors stand in the way of successful clinical transplantation of alginate-polylysine-alginate microencapsulated pancreatic islets. These obstacles can be classified into three categories. The first regards the technical aspects of the production process. Limiting factors are the insufficient ability to produce small capsules with an adequate production rate, and insufficient insight into the factors determining the optimal chemical and mechanical properties of the capsules. The second category regards the functional aspects of the microencapsulated islets, such as the limitations of the transplantation site and the absence of a physiologic insulin response of the encapsulated islets to elevated blood glucose levels. The third category regards the fact that survival times of encapsulated islet grafts are still limited to several weeks or months, which is mainly explained by a pericapsular fibrotic overgrowth reaction as a consequence of the bioincom-patibility of the capsule membrane. This study describes these obstacles, and thereby summarizes the requirements needed for successful clinical application of encapsulated islet transplantation.

Induction of hypoxia and necrosis in multicellular tumor spheroids is associated with resistance to chemotherapy treatment

Culture of cancerous cells in standard monolayer conditions poorly mirrors growth in three-dimensional architectures typically observed in a wide majority of cancers of different histological origin. Multicellular tumor spheroid (MCTS) culture models were developed to mimic these features. However, in vivo tumor growth is also characterized by the presence of ischemic and necrotic areas generated by oxygenation gradients and differential access to nutrients. Hypoxia and necrosis play key roles in tumor progression and resistance to treatment. To provide in vitro models recapitulating these events in highly controlled and standardized conditions, we have generated colorectal cancer (CRC) cell spheroids of different sizes and analyzed their gene expression profiles and sensitivity to treatment with 5FU, currently used in therapeutic protocols. Here we identify three MCTS stages, corresponding to defined spheroid sizes, characterized by normoxia, hypoxia, and hypoxia plus necrosis, respectively. Importantly, we show that MCTS including both hypoxic and necrotic areas most closely mimic gene expression profiles of in vivo-developing tumors and display the highest resistance to 5FU. Taken together, our data indicate that MCTS may mimic in vitro generation of ischemic and necrotic areas in highly standardized and controlled conditions, thereby qualifying as relevant models for drug screening purposes.

Ex Vivo Profiling of PD-1 Blockade Using Organotypic Tumor Spheroids

Ex vivo systems that incorporate features of the tumor microenvironment and model the dynamic response to immune checkpoint blockade (ICB) may facilitate efforts in precision immuno-oncology and the development of effective combination therapies. Here, we demonstrate the ability to interrogate ex vivo response to ICB using murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS). MDOTS/PDOTS isolated from mouse and human tumors retain autologous lymphoid and myeloid cell populations and respond to ICB in short-term three-dimensional microfluidic culture. Response and resistance to ICB was recapitulated using MDOTS derived from established immunocompetent mouse tumor models. MDOTS profiling demonstrated that TBK1/IKKε inhibition enhanced response to PD-1 blockade, which effectively predicted tumor response in vivo Systematic profiling of secreted cytokines in PDOTS captured key features associated with response and resistance to PD-1 blockade. Thus, MDOTS/PDOTS profiling represents a novel platform to evaluate ICB using established murine models as well as clinically relevant patient specimens.Significance: Resistance to PD-1 blockade remains a challenge for many patients, and biomarkers to guide treatment are lacking. Here, we demonstrate feasibility of ex vivo profiling of PD-1 blockade to interrogate the tumor immune microenvironment, develop therapeutic combinations, and facilitate precision immuno-oncology efforts. Cancer Discov; 8(2); 196-215. ©2017 AACR.See related commentary by Balko and Sosman, p. 143See related article by Deng et al., p. 216This article is highlighted in the In This Issue feature, p. 127.

Evaluating the influence of mechanical stress on anticancer treatments through a multiphase porous media model

Drug resistance is one of the leading causes of poor therapy outcomes in cancer. As several chemotherapeutics are designed to target rapidly dividing cells, the presence of a low-proliferating cell population contributes significantly to treatment resistance. Interestingly, recent studies have shown that compressive stresses acting on tumor spheroids are able to hinder cell proliferation, through a mechanism of growth inhibition. However, studies analyzing the influence of mechanical compression on therapeutic treatment efficacy have still to be performed. In this work, we start from an existing mathematical model for avascular tumors, including the description of mechanical compression. We introduce governing equations for transport and uptake of a chemotherapeutic agent, acting on cell proliferation. Then, model equations are adapted for tumor spheroids and the combined effect of compressive stresses and drug action is investigated. Interestingly, we find that the variation in tumor spheroid volume, due to the presence of a drug targeting cell proliferation, considerably depends on the compressive stress level of the cell aggregate. Our results suggest that mechanical compression of tumors may compromise the efficacy of chemotherapeutic agents. In particular, a drug dose that is effective in reducing tumor volume for stress-free conditions may not perform equally well in a mechanically compressed environment.

The role of necrosis, acute hypoxia and chronic hypoxia in 18F-FMISO PET image contrast: a computational modelling study

Positron emission tomography (PET) using 18F-fluoromisonidazole (FMISO) is a promising technique for imaging tumour hypoxia, and a potential target for radiotherapy dose-painting. However, the relationship between FMISO uptake and oxygen partial pressure ([Formula: see text]) is yet to be quantified fully. Tissue oxygenation varies over distances much smaller than clinical PET resolution (<100 μm versus  ∼4 mm), and cyclic variations in tumour perfusion have been observed on timescales shorter than typical FMISO PET studies (∼20 min versus a few hours). Furthermore, tracer uptake may be decreased in voxels containing some degree of necrosis. This work develops a computational model of FMISO uptake in millimetre-scale tumour regions. Coupled partial differential equations govern the evolution of oxygen and FMISO distributions, and a dynamic vascular source map represents temporal variations in perfusion. Local FMISO binding capacity is modulated by the necrotic fraction. Outputs include spatiotemporal maps of [Formula: see text] and tracer accumulation, enabling calculation of tissue-to-blood ratios (TBRs) and time-activity curves (TACs) as a function of mean tissue oxygenation. The model is characterised using experimental data, finding half-maximal FMISO binding at local [Formula: see text] of 1.4 mmHg (95% CI: 0.3-2.6 mmHg) and half-maximal necrosis at 1.2 mmHg (0.1-4.9 mmHg). Simulations predict a non-linear non-monotonic relationship between FMISO activity (4 hr post-injection) and mean tissue [Formula: see text] : tracer uptake rises sharply from negligible levels in avascular tissue, peaking at  ∼5 mmHg and declining towards blood activity in well-oxygenated conditions. Greater temporal variation in perfusion increases peak TBRs (range 2.20-5.27) as a result of smaller predicted necrotic fraction, rather than fundamental differences in FMISO accumulation under acute hypoxia. Identical late FMISO uptake can occur in regions with differing [Formula: see text] and necrotic fraction, but simulated TACs indicate that additional early-phase information may allow discrimination of hypoxic and necrotic signals. We conclude that a robust approach to FMISO interpretation (and dose-painting prescription) is likely to be based on dynamic PET analysis.

Tissue-scale, personalized modeling and simulation of prostate cancer growth

Recently, mathematical modeling and simulation of diseases and their treatments have enabled the prediction of clinical outcomes and the design of optimal therapies on a personalized (i.e., patient-specific) basis. This new trend in medical research has been termed "predictive medicine." Prostate cancer (PCa) is a major health problem and an ideal candidate to explore tissue-scale, personalized modeling of cancer growth for two main reasons: First, it is a small organ, and, second, tumor growth can be estimated by measuring serum prostate-specific antigen (PSA, a PCa biomarker in blood), which may enable in vivo validation. In this paper, we present a simple continuous model that reproduces the growth patterns of PCa. We use the phase-field method to account for the transformation of healthy cells to cancer cells and use diffusion-reaction equations to compute nutrient consumption and PSA production. To accurately and efficiently compute tumor growth, our simulations leverage isogeometric analysis (IGA). Our model is shown to reproduce a known shape instability from a spheroidal pattern to fingered growth. Results of our computations indicate that such shift is a tumor response to escape starvation, hypoxia, and, eventually, necrosis. Thus, branching enables the tumor to minimize the distance from inner cells to external nutrients, contributing to cancer survival and further development. We have also used our model to perform tissue-scale, personalized simulation of a PCa patient, based on prostatic anatomy extracted from computed tomography images. This simulation shows tumor progression similar to that seen in clinical practice.

Eradicating Quiescent Tumor Cells by Targeting Mitochondrial Bioenergetics

The presence of quiescent cell populations in solid tumors represents a major challenge for disease eradication. Such cells are generally present in poorly vascularized tumor areas, show limited sensitivity to traditional chemotherapeutical drugs, and tend to resume proliferation, resulting in tumor reseeding and growth. There is growing recognition of the importance of developing therapies that target these quiescent cell populations to achieve long-lasting remission. Recent studies have shown that the combination of hypoxia and reduced nutrient availability in poorly vascularized areas results in limited tumor metabolic plasticity coupled with an increased sensitivity to perturbations in mitochondrial flux. Targeting of mitochondrial bioenergetics in these quiescent cell tumor populations may enable tumor eradication and improve the prognosis of patients with cancer.

Phenomenological modelling and simulation of cell clusters in 3D cultures

Cell clustering and aggregation are fundamental processes in the development of several tissues and the progression of many diseases. The formation of these aggregates also has a direct impact on the oxygen concentration in their surroundings due to cellular respiration and poor oxygen diffusion through clusters. In this work, we propose a mathematical model that is capable of simulating cell cluster formation in 3D cultures through combining a particle-based and a finite element approach to recreate complex experimental conditions. Cells are modelled considering cell proliferation, cell death and cell-cell mechanical interactions. Additionally, the oxygen concentration profile is calculated through finite element analysis using a reaction-diffusion model that considers cell oxygen consumption and diffusion through the extracellular matrix and the cell clusters. In our model, the local oxygen concentration in the medium determines both cell proliferation and cell death. Numerical predictions are also compared with experimental data from the literature. The simulation results indicate that our model can predict cell clustering, cluster growth and oxygen distribution in 3D cultures. We conclude that the initial cell distribution, cell death and cell proliferation dynamics determine the size and density of clusters. Moreover, these phenomena are directly affected by the oxygen transport in the 3D culture.

Introduction to a new cell transplantation platform via recombinant peptide petaloid pieces and its application to islet transplantation with mesenchymal stem cells

Cell death cluster in transplanted cells remains a critical obstacle for regeneration strategies. This study describes a novel platform for cell transplantation (CellSaic) consisting of human mesenchymal stem cells (hMSCs) and petaloid pieces of recombinant peptide (RCP), which can prevent cell death by arranging the cells in a mosaic. When hMSC CellSaics were subcutaneously implanted into NOD/SCID mice, hMSC CellSaics prevented cell death and accelerated angiogenesis in the graft, compared to the findings obtained on solely implanting cell spheroids. Additionally, we examined the application of CellSaic for subcutaneous cotransplantation of 200 rat islets with 2 × 10(5) hMSCs into diabetic mice. As the results of blood glucose levels at 1 m, the islet-only group was 398 ± 30 mg/dl and the islets with hMSCs group were 180 ± 65 mg/dl. On the other hand, the islets with hMSCs CellSaic group showed 129 ± 15 mg/dl and significantly improved glucose tolerance (P < 0.05). Additionally, we showed that the surface texture of the RCP petaloid pieces played an important role in graft survival and angiogenesis. It is anticipated that CellSaic will be used as a new platform for cell transplantation and tissue regeneration.

Micro-dissected tumor tissues on chip: an ex vivo method for drug testing and personalized therapy

In cancer research and personalized medicine, new tissue culture models are needed to better predict the response of patients to therapies. With a concern for the small volume of tissue typically obtained through a biopsy, we describe a method to reproducibly section live tumor tissue to submillimeter sizes. These micro-dissected tissues (MDTs) share with spheroids the advantages of being easily manipulated on-chip and kept alive for periods extending over one week, while being biologically relevant for numerous assays. At dimensions below ~420 μm in diameter, as suggested by a simple metabolite transport model and confirmed experimentally, continuous perfusion is not required to keep samples alive, considerably simplifying the technical challenges. For the long-term culture of MDTs, we describe a simple microfluidic platform that can reliably trap samples in a low shear stress environment. We report the analysis of MDT viability for eight different types of tissues (four mouse xenografts derived from human cancer cell lines, three from ovarian and prostate cancer patients, and one from a patient with benign prostatic hyperplasia) analyzed by both confocal microscopy and flow cytometry over an 8-day incubation period. Finally, we provide a proof of principle for chemosensitivity testing of human tissue from a cancer patient performed using the described MDT chip method. This technology has the potential to improve treatment success rates by identifying potential responders earlier during the course of treatment and providing opportunities for direct drug testing on patient tissues in early drug development stages.

Predicting the growth of glioblastoma multiforme spheroids using a multiphase porous media model

Tumor spheroids constitute an effective in vitro tool to investigate the avascular stage of tumor growth. These three-dimensional cell aggregates reproduce the nutrient and proliferation gradients found in the early stages of cancer and can be grown with a strict control of their environmental conditions. In the last years, new experimental techniques have been developed to determine the effect of mechanical stress on the growth of tumor spheroids. These studies report a reduction in cell proliferation as a function of increasingly applied stress on the surface of the spheroids. This work presents a specialization for tumor spheroid growth of a previous more general multiphase model. The equations of the model are derived in the framework of porous media theory, and constitutive relations for the mass transfer terms and the stress are formulated on the basis of experimental observations. A set of experiments is performed, investigating the growth of U-87MG spheroids both freely growing in the culture medium and subjected to an external mechanical pressure induced by a Dextran solution. The growth curves of the model are compared to the experimental data, with good agreement for both the experimental settings. A new mathematical law regulating the inhibitory effect of mechanical compression on cancer cell proliferation is presented at the end of the paper. This new law is validated against experimental data and provides better results compared to other expressions in the literature.

A Glycolysis-Based In Silico Model for the Solid Tumor Growth

Cancer-tumor growth is a complex process depending on several biological factors, such as the chemical microenvironment of the tumor, the cellular metabolic profile, and its proliferation rate. Several mathematical models have been developed for identifying the interactions between tumor cells and tissue microenvironment, since they play an important role in tumor formation and progression. Toward this direction we propose a new continuum model of avascular glioma-tumor growth, which incorporates a new factor, namely, the glycolytic potential of cancer cells, to express the interactions of three different tumor-cell populations (proliferative, hypoxic, and necrotic) with their tissue microenvironment. The glycolytic potential engages three vital nutrients, i.e., oxygen, glucose, and lactate, which provide cells with the necessary energy for their survival and proliferation. Extensive simulations are performed for different evolution times and various proliferation rates, in order to investigate how the tumor growth is affected. According to medical experts, the experimental observations indicate that the model predicts quite satisfactorily the overall tumor growth as well as the expansion of each region separately. Following extensive evaluation, the proposed model may provide an essential tool for patient-specific tumor simulation and reliable prediction of glioma spatiotemporal expansion.

Targeting Mitochondrial Function to Treat Quiescent Tumor Cells in Solid Tumors

The disorganized nature of tumor vasculature results in the generation of microenvironments characterized by nutrient starvation, hypoxia and accumulation of acidic metabolites. Tumor cell populations in such areas are often slowly proliferating and thus refractory to chemotherapeutical drugs that are dependent on an active cell cycle. There is an urgent need for alternative therapeutic interventions that circumvent growth dependency. The screening of drug libraries using multicellular tumor spheroids (MCTS) or glucose-starved tumor cells has led to the identification of several compounds with promising therapeutic potential and that display activity on quiescent tumor cells. Interestingly, a common theme of these drug screens is the recurrent identification of agents that affect mitochondrial function. Such data suggest that, contrary to the classical Warburg view, tumor cells in nutritionally-compromised microenvironments are dependent on mitochondrial function for energy metabolism and survival. These findings suggest that mitochondria may represent an “Achilles heel” for the survival of slowly-proliferating tumor cells and suggest strategies for the development of therapy to target these cell populations.

An in silico model to demonstrate the effects of Maspin on cancer cell dynamics

Most cancer treatments efficacy depends on tumor metastasis suppression, where tumor suppressor genes play an important role. Maspin (Mammary Serine Protease Inhibitor), an non-inhibitory serpin has been reported as a potential tumor suppressor to influence cell migration, adhesion, proliferation and apoptosis in in vitro and in vivo experiments in last two decades. Lack of computational investigations hinders its ability to go through clinical trials. Previously, we reported first computational model for maspin effects on tumor growth using artificial neural network and cellular automata paradigm with in vitro data support. This paper extends the previous in silico model by encompassing how maspin influences cell migration and the cell-extracellular matrix interaction in subcellular level. A feedforward neural network was used to define each cell behavior (proliferation, quiescence, apoptosis) which followed a cell-cycle algorithm to show the microenvironment impacts over tumor growth. Furthermore, the model concentrates how the in silico experiments results can further confirm the fact that maspin reduces cell migration using specific in vitro data verification method. The data collected from in vitro and in silico experiments formulates an unsupervised learning problem which can be solved by using different clustering algorithms. A density based clustering technique was developed to measure the similarity between two datasets based on the number of links between instances. Our proposed clustering algorithm first finds the nearest neighbors of each instance, and then redefines the similarity between pairs of instances in terms of how many nearest neighbors share the two instances. The number of links between two instances is defined as the number of common neighbors they have. The results showed significant resemblances with in vitro experimental data. The results also offer a new insight into the dynamics of maspin and establish as a metastasis suppressor gene for further molecular research.

Inhibition of hexokinase-2 with targeted liposomal 3-bromopyruvate in an ovarian tumor spheroid model of aerobic glycolysis

BACKGROUND

The objective of this study was to evaluate the expression levels of glycolytic markers, especially hexokinase-2 (HK2), using a three-dimensional multicellular spheroid model of human ovarian adenocarcinoma (SKOV-3) cells and to develop an epidermal growth factor receptor-targeted liposomal formulation for improving inhibition of HK2 and the cytotoxicity of 3-bromopyruvate (3-BPA).

METHODS

Multicellular SKOV-3 tumor spheroids were developed using the hanging drop method and expression levels of glycolytic markers were examined. Non-targeted and epidermal growth factor receptor-targeted liposomal formulations of 3-BPA were formulated and characterized. Permeability and cellular uptake of the liposomal formulations in three-dimensional SKOV-3 spheroids was evaluated using confocal microscopy. The cytotoxicity and HK2 inhibition potential of solution form of 3-BPA was compared to the corresponding liposomal formulation by using cell proliferation and HK2 enzymatic assays.

RESULTS

SKOV-3 spheroids were reproducibly developed using the 96-well hanging drop method, with an average size of 900 µm by day 5. HK2 enzyme activity levels under hypoxic conditions were found to be higher than under normoxic conditions (P<0.0001, Student's t-test, unpaired and two-tailed). Liposomal formulations (both non-targeted and targeted) of 3-BPA showed a more potent inhibitory effect (P<0.001, Student's t-test, unpaired and two-tailed) at a dose of 50 µM than the aqueous solution form at 3, 6, and 24 hours post administration. Similarly, the cytotoxic activity 3-BPA at various concentrations (10 µM-100 µM) showed that the liposomal formulations had an enhanced cytotoxic effect of 2-5-fold (P<0.0001, Student's t-test, unpaired and two-tailed) when compared to the aqueous solution form for both 10 µM and 25 µM concentrations.

CONCLUSION

SKOV-3 spheroids developed by the hanging drop method can be used as a tumor aerobic glycolysis model for evaluation of therapies targeting the glycolytic pathway in cancer cells. Encapsulation of 3-BPA in a liposomal formulation improved permeability, HK2 inhibition, and cytotoxicity in the multicellular spheroid model.

Multidrug resistance characterization in multicellular tumour spheroids from two human lung cancer cell lines

Background

Most of the knowledge about the mechanisms of multidrug resistance in lung cancer has been achieved through the use of cell lines isolated from tumours cultivated either in suspensions of isolated cells or in monolayers and following exposition to different cytostatic agents. However, tumour cell lines growing as multicellular tumour spheroids (MTS) frequently develop multicellular resistance in a drug-independent form. The aim of this study was to characterize the phenotypic and functional differences between two human NSCLC cell lines (INER-37 and INER-51) grown as traditional monolayer cultures versus as MTS.

Methods

After 72 hours treatment with anticancer drugs, chemosensitivity in monolayers and tumour spheroids cultures was assessed using MTT assay. Reverse transcription-polymerase chain reaction was employed to detect the mRNAs of multidrug resistance-related genes. The expression of P-gp was analyzed by immunohistochemical staining and cell cycle profiles were analyzed using FACS.

Results

The results indicate that when grown as MTS each lung cancer cell line had different morphologies as well as and abrogation of cell proliferation with decrease of the G₂/M phase. Also, MTS acquired multicellular resistance to several chemotherapeutic agents in only a few days of culture which were accomplished by significant changes in the expression of MDR-related genes.

Conclusion

Overall, the MTS culture changed the cellular response to drugs nevertheless each of the cell lines studied seems to implement different mechanisms to acquire multicellular resistance.

A tumor growth model with deformable ECM

Existing tumor growth models based on fluid analogy for the cells do not generally include the extracellular matrix (ECM), or if present, take it as rigid. The three-fluid model originally proposed by the authors and comprising tumor cells (TC), host cells (HC), interstitial fluid (IF) and an ECM, considered up to now only a rigid ECM in the applications. This limitation is here relaxed and the deformability of the ECM is investigated in detail. The ECM is modeled as a porous solid matrix with Green-elastic and elasto-visco-plastic material behavior within a large strain approach. Jauman and Truesdell objective stress measures are adopted together with the deformation rate tensor. Numerical results are first compared with those of a reference experiment of a multicellular tumor spheroid (MTS) growing in vitro, then three different tumor cases are studied: growth of an MTS in a decellularized ECM, growth of a spheroid in the presence of host cells and growth of a melanoma. The influence of the stiffness of the ECM is evidenced and comparison with the case of a rigid ECM is made. The processes in a deformable ECM are more rapid than in a rigid ECM and the obtained growth pattern differs. The reasons for this are due to the changes in porosity induced by the tumor growth. These changes are inhibited in a rigid ECM. This enhanced computational model emphasizes the importance of properly characterizing the biomechanical behavior of the malignant mass in all its components to correctly predict its temporal and spatial pattern evolution.

Influence of individual cell motility on the 2D front roughness dynamics of tumour cell colonies

The dynamics of in situ 2D HeLa cell quasi-linear and quasi-radial colony fronts in a standard culture medium is investigated. For quasi-radial colonies, as the cell population increased, a kinetic transition from an exponential to a constant front average velocity regime was observed. Special attention was paid to individual cell motility evolution under constant average colony front velocity looking for its impact on the dynamics of the 2D colony front roughness. From the directionalities and velocity components of cell trajectories in colonies with different cell populations, the influence of both local cell density and cell crowding effects on individual cell motility was determined. The average dynamic behaviour of individual cells in the colony and its dependence on both local spatio-temporal heterogeneities and growth geometry suggested that cell motion undergoes under a concerted cell migration mechanism, in which both a limiting random walk-like and a limiting ballistic-like contribution were involved. These results were interesting to infer how biased cell trajectories influenced both the 2D colony spreading dynamics and the front roughness characteristics by local biased contributions to individual cell motion. These data are consistent with previous experimental and theoretical cell colony spreading data and provide additional evidence of the validity of the Kardar-Parisi-Zhang equation, within a certain range of time and colony front size, for describing the dynamics of 2D colony front roughness.

3D cell culture systems modeling tumor growth determinants in cancer target discovery

Phenotypic heterogeneity of cancer cells, cell biological context, heterotypic crosstalk and the microenvironment are key determinants of the multistep process of tumor development. They sign responsible, to a significant extent, for the limited response and resistance of cancer cells to molecular-targeted therapies. Better functional knowledge of the complex intra- and intercellular signaling circuits underlying communication between the different cell types populating a tumor tissue and of the systemic and local factors that shape the tumor microenvironment is therefore imperative. Sophisticated 3D multicellular tumor spheroid (MCTS) systems provide an emerging tool to model the phenotypic and cellular heterogeneity as well as microenvironmental aspects of in vivo tumor growth. In this review we discuss the cellular, chemical and physical factors contributing to zonation and cellular crosstalk within tumor masses. On this basis, we further describe 3D cell culture technologies for growth of MCTS as advanced tools for exploring molecular tumor growth determinants and facilitating drug discovery efforts. We conclude with a synopsis on technological aspects for on-line analysis and post-processing of 3D MCTS models.

Polymers in cell encapsulation from an enveloped cell perspective

In the past two decades, many polymers have been proposed for producing immunoprotective capsules. Examples include the natural polymers alginate, agarose, chitosan, cellulose, collagen, and xanthan and synthetic polymers poly(ethylene glycol), polyvinyl alcohol, polyurethane, poly(ether-sulfone), polypropylene, sodium polystyrene sulfate, and polyacrylate poly(acrylonitrile-sodium methallylsulfonate). The biocompatibility of these polymers is discussed in terms of tissue responses in both the host and matrix to accommodate the functional survival of the cells. Cells should grow and function in the polymer network as adequately as in their natural environment. This is critical when therapeutic cells from scarce cadaveric donors are considered, such as pancreatic islets. Additionally, the cell mass in capsules is discussed from the perspective of emerging new insights into the release of so-called danger-associated molecular pattern molecules by clumps of necrotic therapeutic cells. We conclude that despite two decades of intensive research, drawing conclusions about which polymer is most adequate for clinical application is still difficult. This is because of the lack of documentation on critical information, such as the composition of the polymer, the presence or absence of confounding factors that induce immune responses, toxicity to enveloped cells, and the permeability of the polymer network. Only alginate has been studied extensively and currently qualifies for application. This review also discusses critical issues that are not directly related to polymers and are not discussed in the other reviews in this issue, such as the functional performance of encapsulated cells in vivo. Physiological endocrine responses may indeed not be expected because of the many barriers that the metabolites encounter when traveling from the blood stream to the enveloped cells and back to circulation. However, despite these diffusion barriers, many studies have shown optimal regulation, allowing us to conclude that encapsulated grafts do not always follow nature's course but are still a possible solution for many endocrine disorders for which the minute-to-minute regulation of metabolites is mandatory.