Three-dimensional Cancer Models Research Articles

A novel approach to engineering three-dimensional bladder tumor models for drug testing.

Bladder cancer (BCa) poses a significant health challenge, particularly affecting men with higher incidence and mortality rates. Addressing the need for improved predictive models in BCa treatment, this study introduces an innovative 3D in vitro patient-derived bladder cancer tumor model, utilizing decellularized pig bladders as scaffolds. Traditional 2D cell cultures, insufficient in replicating tumor microenvironments, have driven the development of sophisticated 3D models. The study successfully achieved pig bladder decellularization through multiple cycles of immersion in salt solutions, resulting in notable macroscopic and histological changes. This process confirmed the removal of cellular components while preserving the native extracellular matrix (ECM). Quantitative analysis demonstrated the efficacy of decellularization, with a remarkable reduction in DNA concentration, signifying the removal of over 95% of cellular material. In the development of the in vitro bladder cancer model, muscle invasive bladder cancer patients' cells were cultured within decellularized pig bladders, yielding a three-dimensional cancer model. Optimal results were attained using an air-liquid interface technique, with cells injected directly into the scaffold at three distinct time points. Histological evaluations showcased characteristics resembling in vivo tumors derived from bladder cancer patients' cells. To demonstrate the 3D cancer model's effectiveness as a drug screening platform, the study treated it with Cisplatin (Cis), Gemcitabine (Gem), and a combination of both drugs. Comprehensive cell viability assays and histological analyses illustrated changes in cell survival and proliferation. The model exhibited promising correlations with clinical outcomes, boasting an 83.3% reliability rate in predicting treatment responses. Comparison with traditional 2D cultures and spheroids underscored the 3D model's superiority in reliability, with an 83.3% predictive capacity compared to 50% for spheroids and 33.3% for 2D culture. Acknowledging limitations, such as the absence of immune and stromal components, the study suggests avenues for future improvements. In conclusion, this innovative 3D bladder cancer model, combining decellularization and patient-derived cells, marks a significant advancement in preclinical drug testing. Its potential for predicting treatment outcomes and capturing patient-specific responses opens new avenues for personalized medicine in bladder cancer therapeutics. Future refinements and validations with larger patient cohorts hold promise for revolutionizing BCa research and treatment strategies.

Routes to Chaos in a Three-Dimensional Cancer Model

Routes to Chaos in a Three-Dimensional Cancer Model

Prediction of the Change Rate of Tumor Cells, Healthy Host Cells, and Effector Immune Cells in a Three-Dimensional Cancer Model using Extended Kalman Filter

In this study, we develop and implement the Extended Kalman Filter (EKF) to forecast the rate of change in tumor cells, healthy host cells, and effector immune cells within the Itik-Banks model. This novel application of EKF in cancer dynamics modeling aims to provide precise real-time estimations of cellular interactions, especially in constructing a new state space representation from the Itik-Banks model. We use a first-order Taylor series to linearize the model. The numerical simulations were performed to analyze the accuracy of this new state space with data from William Gilpin’s GitHub repository. The results show that the EKF predictions strongly align with actual data, i.e., in the prior and posterior steps for tumor and healthy host cells, there is a strong agreement between the predictions and the actual data. The EKF captures the oscillatory nature of the tumor and healthy host cell population well. The peaks and troughs of the predictions align closely with the actual data, indicating the EKF’s effectiveness in modeling the dynamic behavior of the tumor and healthy host cells. However, for effector immune cells, the oscillatory nature of the data in these cells gives rise to slight deviations. This represents a significant challenge in the future for updating the state space representations. Despite minor discrepancies, the EKF demonstrates a strong performance in both the training and testing data, with the posterior step estimates significantly improving the prior step accuracy. This study emphasizes the importance of data availability for accurate predictions, noting a symmetric Mean Absolute Percentage Error (sMAPE) of 35.92% when data is unavailable. Prompt correction with new data is essential to maintain accuracy. This research underscores the EKF’s potential for real-time monitoring and prediction in complex biological systems.

Characterization and comparison of hypoxia inducing factors on tumor growth and metastasis between two- and three-dimensional cancer models

The monocarboxylic acid transporter 4 (Mct-4), a downstream biomarker of hypoxia inducing factor (HIF)-1α, is involved in the cellular response to hypoxia, as indicated by the hypoxic response element in its promoter region. Using a tumorsphere assay as an in vitro 3-dimensional (3D) model generated using 384-well ultra-low attachment (ULA) plates for cell proliferation analysis using a plate-based image cytometer, we identify a hypoxic response in the tumorsphere model that is distinct from that of cells grown under 2-dimensional (2D) normoxic conditions and demonstrate a key role for Mct-4 in enabling 3D growth. The tumorsphere model yields evidence of an essential role for Mct-4 in multiple cell lines, which were genetically modified to underexpress and overexpress Mct-4, evidence not apparent in a standard 2D model of growth in the same cell lines. In addition, we identify the effects of overexpressing Mct-4 in cancer cell migration using a transwell chamber assay. We also show that the response to hypoxia may be circumvented by transfection with a CMV promoter driven Mct-4, which confers constitutive 3D growth, wherein tumorsphere growth inhibition by small molecule HIF-1α inhibitors is mitigated. Finally, we demonstrate quantifiable gene/protein expression differences between 2D and 3D cancer models based on the normoxic and hypoxic conditions. Therefore, the tumorsphere 3D model generated using 384-well ULA plates in combination with high-throughput image cytometer is demonstrated to provide a convenient, robust, and reproducible tool and method for the elucidation of mechanisms of action underlying tumor growth and migration in the hypoxic tumor microenvironment.

Chaos in a Three-Dimensional Cancer Model with Piecewise Constant Arguments

In this study, we analyze a cancer model which includes the interactions among tumor cells, healthy host cells and effector immune cells. The model with continuous case has been studied in the literature and it has been shown that it exhibits chaotic behavior. In this paper, we aim to build a better understanding of how both discrete and continuous times affect the dynamic behavior of the tumor growth model. So, we reconsider the model as a system of differential equations with piecewise constant argument. To analyze dynamical behavior of the model, we consider the solution of the system in a certain subinterval which leads to the system of difference equations. Some theoretical results are obtained for local behavior of the system. In addition, we study chaotic dynamic of the system through Neimark-Sacker bifurcation by using Lyapunov exponents

Biophysical Parameters Can Induce Epithelial-to-Mesenchymal Phenotypic and Genotypic Changes in HT-29 Cells: A Preliminary Study.

Epithelial to mesenchymal transition (EMT) in cancer is the process described where cancer epithelial cells acquire mesenchymal properties which can lead to enhanced invasiveness. Three-dimensional cancer models often lack the relevant and biomimetic microenvironment parameters appropriate to the native tumour microenvironment thought to drive EMT. In this study, HT-29 epithelial colorectal cells were cultivated in different oxygen and collagen concentrations to investigate how these biophysical parameters influenced invasion patterns and EMT. Colorectal HT-29 cells were grown in physiological hypoxia (5% O2) and normoxia (21% O2) in 2D, 3D soft (60 Pa), and 3D stiff (4 kPa) collagen matrices. Physiological hypoxia was sufficient to trigger expression of markers of EMT in the HT-29 cells in 2D by day 7. This is in contrast to a control breast cancer cell line, MDA-MB-231, which expresses a mesenchymal phenotype regardless of the oxygen concentration. In 3D, HT-29 cells invaded more extensively in a stiff matrix environment with corresponding increases in the invasive genes MMP2 and RAE1. This demonstrates that the physiological environment can directly impact HT-29 cells in terms of EMT marker expression and invasion, compared to an established cell line, MDA-MB-231, which has already undergone EMT. This study highlights the importance of the biophysical microenvironment to cancer epithelial cells and how these factors can direct cell behaviour. In particular, that stiffness of the 3D matrix drives greater invasion in HT-29 cells regardless of hypoxia. It is also pertinent that some cell lines (already having undergone EMT) are not as sensitive to the biophysical features of their microenvironment.

Thermomagnetic Resonance Effect of the Extremely Low Frequency Electromagnetic Field on Three-Dimensional Cancer Models.

In our recent studies, we have developed a thermodynamic biochemical model able to select the resonant frequency of an extremely low frequency electromagnetic field (ELF-EMF) specifically affecting different types of cancer, and we have demonstrated its effects in vitro. In this work, we investigate the cellular response to the ELF electromagnetic wave in three-dimensional (3D) culture models, which mimic the features of tumors in vivo. Cell membrane was modelled as a resistor–capacitor circuit and the specific thermal resonant frequency was calculated and tested on two-dimensional (2D) and three-dimensional (3D) cell cultures of human pancreatic cancer, glioblastoma and breast cancer. Cell proliferation and the transcription of respiratory chain and adenosine triphosphate synthase subunits, as well as uncoupling proteins, were assessed. For the first time, we demonstrate that an ELF-EMF hampers growth and potentiates both the coupled and uncoupled respiration of all analyzed models. Interestingly, the metabolic shift was evident even in the 3D aggregates, making this approach particularly valuable and promising for future application in vivo, in aggressive cancer tissues characterized by resistance to treatments.

Biophysical properties of hydrogels for mimicking tumor extracellular matrix.

The extracellular matrix (ECM) is an essential component of the tumor microenvironment. It plays a critical role in regulating cell-cell and cell-matrix interactions. However, there is lack of systematic and comparative studies on different widely-used ECM mimicking hydrogels and their properties, making the selection of suitable hydrogels for mimicking different in vivo conditions quite random. This study systematically evaluates the biophysical attributes of three widely used natural hydrogels (Matrigel, collagen gel and agarose gel) including complex modulus, loss tangent, diffusive permeability and pore size. A new and facile method was developed combining Critical Point Drying, Scanning Electron Microscopy imaging and a MATLAB image processing program (CSM method) for the characterization of hydrogel microstructures. This CSM method allows accurate measurement of the hydrogel pore size down to nanometer resolution. Furthermore, a microfluidic device was implemented to measure the hydrogel permeability (Pd) as a function of particle size and gel concentration. Among the three gels, collagen gel has the lowest complex modulus, medium pore size, and the highest loss tangent. Agarose gel exhibits the highest complex modulus, the lowest loss tangent and the smallest pore size. Collagen gel and Matrigel produced complex moduli close to that estimated for cancer ECM. The Pd of these hydrogels decreases significantly with the increase of particle size. By assessing different hydrogels' biophysical characteristics, this study provides valuable insights for tailoring their properties for various three-dimensional cancer models.

An Optimized Workflow for the Analysis of Metabolic Fluxes in Cancer Spheroids Using Seahorse Technology.

Three-dimensional cancer models, such as spheroids, are increasingly being used to study cancer metabolism because they can better recapitulate the molecular and physiological aspects of the tumor architecture than conventional monolayer cultures. Although Agilent Seahorse XFe96 (Agilent Technologies, Santa Clara, CA, United States) is a valuable technology for studying metabolic alterations occurring in cancer cells, its application to three-dimensional cultures is still poorly optimized. We present a reliable and reproducible workflow for the Seahorse metabolic analysis of three-dimensional cultures. An optimized protocol enables the formation of spheroids highly regular in shape and homogenous in size, reducing variability in metabolic parameters among the experimental replicates, both under basal and drug treatment conditions. High-resolution imaging allows the calculation of the number of viable cells in each spheroid, the normalization of metabolic parameters on a per-cell basis, and grouping of the spheroids as a function of their size. Multivariate statistical tests on metabolic parameters determined by the Mito Stress test on two breast cancer cell lines show that metabolic differences among the studied spheroids are mostly related to the cell line rather than to the size of the spheroid. The optimized workflow allows high-resolution metabolic characterization of three-dimensional cultures, their comparison with monolayer cultures, and may aid in the design and interpretation of (multi)drug protocols.

RNA Sequencing and Cell Models of Virus-Associated Cancer (Review).

The review summarizes findings from the studies based on the application of technologies for transcriptome analysis to modern cellular model systems of human papillomavirus-associated cancer (HPV) (cervical cancer, head and neck tumors). A diversity of three-dimensional cancer models, such as spheroids, organoids (organotypic cultures), explants, mouse xenografts, are addressed. Particular attention is paid to the use of patient-derived biomaterial for establishing short-term cultures of primary tumor cells, as well as generating multicomponent (heterocellular) systems that comprise, together with the tumor component, other elements of its microenvironment. A number of unique biological properties of HPV-induced neoplasia are discussed, which make generating cell models a unique task.The novel findings in the field of molecular mechanisms of the onset and progression of HPV-associated cancer achieved by using RNA sequencing are presented for each variant of the model systems. These findings are considered in regard to applied aspects of their use, in terms of the opportunities for preclinical testing of new drugs, personalized diagnostics and selection of individual, most effective treatment regimens. The issues of drug resistance development, molecular-cellular heterogeneity, epigenetic reprogramming, and the role of the stromal microenvironment are reviewed. The paper accentuates the problems related to the limitations of the applicability of a particular model system. The areas with a significant lagging behind in omics research of virus-associated cancer in comparison with other types of oncological pathology and possible causes of this lag are noted. The future prospects for the development of model systems of HPV-associated tumors in the field of high-tech tissue engineering, in particular, the use of bioprinting and microfluidic biochips, are also outlined. The combination of these techniques with the methods of whole genome profiling will significantly increase the translational potential of the described model cell systems.

Control and numerical analysis for cancer chaotic system

This article investigates the problem of control of chaotic dynamics of tumor cells, immune system cells, and healthy tissue cells in a three-dimensional cancer model by adaptive control technique. Adaptive control law is derived such that the trajectory of controlled system asymptotically approaches equilibrium point with estimated parameter converges to stabilizing values. A nonlinear control law is designed which change the original chaotic system into a controlled one linear system. In addition, we present and analyze numerical solution of the cancer dynamical system with the help of a discretization technique. Achieved solutions show a comparable results with Runge–Kutta methods. The reliability and accuracy of the proposed technique is presented by comparing numerical results. The used technique has displayed a brilliant prospective in dealing with the numerical solutions of nonlinear dynamical systems.

Chaos in a three-cell population cancer model with variable-order fractional derivative with power, exponential and Mittag-Leffler memories

Abstract In this work, a three-dimensional cancer model which includes the interactions between tumor cells, healthy tissue cells, and activated immune system cells was considered via Liouville–Caputo, Caputo–Fabrizio, Atangana–Baleanu, and fractional conformable derivative. We show a numerical method based on two-step Lagrange polynomial interpolation to achieve numerical approximations to these derivatives. Besides, also we analyze the dynamics observed via sensitivity to initial conditions, Lyapunov exponent estimation, square sum error, and phase-space diagrams. Novel attractors were obtained and all of them depicted novel chaotic behaviors by choosing a fractional variable-order.

Nonlinear Control for Growth of Cancerous Tumor Cells

In this research work, a Three-Dimensional Cancer model (TDCM) has been used and nonlinear controllers; Lyapunov Redesign, Synergetic and Sliding Mode based controllers have been designed in order to reduce the growth of tumor cells to a level where they become harmless, to maintain the hunting predator cells to their maximum possible value and to retain resting predator cells to 40% of the hunting predator cells. The proposed controllers have been developed for chemotherapy and their effect on different cells has been studied. Asymptotic stability of the proposed controllers has been studied using Lyapunov stability theory. Theoretical analysis has been supported by simulation results using MATLAB/Simulink. Under the proposed controllers, the system behaves very nicely even in the presence of un-modeled disturbances and noise.

Nonlinear active control of a cancerous tumour

This paper deals with the control of a cancerous tumour growth. The model used is a Three-Dimensional Cancer Model (TDCM). The competition terms include tumour cells, healthy cells, and immune cells. Nature of the competition among the populations of tumour cells, healthy host cells, and immune cells results in a chaotic behaviour. In this paper, a nonlinear active control has been used to control the growth of a tumour. Effect of chemotherapy drug on the different cell populations has been studied. Our control objective is to control the tumour growth and minimize its population to a small value which can be considered as harmless.Along with the above objective, the normal cell population is also be maintained at a particular level. This work has been done completely inin-sillico environment. The simulation results are shown extensively to support the theoretical analysis and confirmed that the preliminary objectives of the paper are attained.

Chaos in a Cancer Model via Fractional Derivatives with Exponential Decay and Mittag-Leffler Law

In this paper, a three-dimensional cancer model was considered using the Caputo-Fabrizio-Caputo and the new fractional derivative with Mittag-Leffler kernel in Liouville-Caputo sense. Special solutions using an iterative scheme via Laplace transform, Sumudu-Picard integration method and Adams-Moulton rule were obtained. We studied the uniqueness and existence of the solutions. Novel chaotic attractors with total order less than three are obtained.

Molecular and functional assessment of multicellular cancer spheroids produced in double emulsions enabled by efficient airway resistance based selective surface treatment

Multicellular spheroids have garnered significant attention as an in vitro three-dimensional cancer model which can mimick the in vivo microenvironmental features. While microfluidics generated double emulsions have become a potential method to generate spheroids, challenges remain on the tedious procedures. Enabled by a novel ‘airway resistance’ based selective surface treatment, this study presents an easy and facile generation of double emulsions for the initiation and cultivation of multicellular spheroids in a scaffold-free format. Combining with our previously developed DNA nanosensors, intestinal spheroids produced in the double emulsions have shown an elevated activities of an essential DNA modifying enzyme, the topoisomerase I. The observed molecular and functional characteristics of spheroids produced in double emulsions are similar to the counterparts produced by the commercially available ultra-low attachment plates. However, the double emulsions excel for their improved uniformity, and the consistency of the results obtained by subsequent analysis of the spheroids. The presented technique is expected to ease the burden of producing spheroids and to promote the spheroids model for cancer or stem cell study.

Chaos Control in Three Dimensional Cancer Model by State Space Exact Linearization Based on Lie Algebra

This study deals with the control of chaotic dynamics of tumor cells, healthy host cells, and effector immune cells in a chaotic Three Dimensional Cancer Model (TDCM) by State Space Exact Linearization (SSEL) technique based on Lie algebra. A non-linear feedback control law is designed which induces a coordinate transformation thereby changing the original chaotic TDCM system into a controlled one linear system. Numerical simulation has been carried using Mathematica that witness the robustness of the technique implemented on the chosen chaotic system.

Engineering a three-dimensional cancer model from lung extracellular matrix hydrogel

Event Abstract Back to Event Engineering a three-dimensional cancer model from lung extracellular matrix hydrogel Jinglei Wu1, 2, Kytai T. Nguyen1, 2 and Yi Hong1, 2 1 University of Texas at Arlington, Department of Bioengineering, United States 2 University of Texas Southwestern Medical Center, Joint Graduate Program in Biomedical Engineering, United States Introduction: Lung cancer represents the leading cause of cancer-related death and continues to have the highest new cases in the United States[1]. An accurate model that mimics the microenvironment of tumor could promote the discovery of new drugs and effective treatments of lung cancer. Cancer cells cultured within a three-dimensional (3D) environment behave significantly different in proliferation and signal pathway compared with two-dimensional (2D) substrates[2]. Furthermore, 3D models closely simulate the physiological and pathological conditions of animal models, allowing inexpensive studies in vitro. This study aimed to develop a decellularized lung extracellular matrix (DL-ECM) hydrogel as a 3D lung cancer model. Materials and Methods: Adult porcine lungs were collected from a local slaughterhouse and stored at -80 oC. The frozen lungs were sliced and decellularized using 0.5% sodium dodecyl sulfate (SDS) for 3 d followed by thorough resining with deionized water and then lyophilized to obtain DL-ECM. The DL-ECM hydrogel was prepared using an enzymatic digestion method as ref[3],[4]. Briefly, DL-ECM was digested with pepsin in 0.01 M HCl at ECM/pepsin ratio of 10/1 for 2-3 days, until no visible particle was found. The digest was neutralized with 0.1 M NaOH and 10X PBS to obtain pre-gel solution, which was then diluted into pre-determined ECM concentrations and solidified at 37 oC for 30 min to form hydrogels. The DL-ECM hydrogels were characterized in morphologies, gelation behaviors and compressive mechanical properties using scanning electron microscope (SEM), turbidimetric absorbance and MTS Insight machine, respectively. The biocompatibility was assessed by seeding the hydrogel with A549 cells. The cells were mixed with the pre-gel solution at the cell density of 1×107 cells/mL and induced to hydrogels at 37 oC, and then maintained in an incubator with 5% CO2 and 95% humidity. Live/dead staining was performed 3 d after seeding to demonstrate cell viability. Results and Discussion: The DL-ECM had the major component of collagen and a minor component of glycosaminoglycan (data not shown) and was processed into hydrogels. SEM image showed that the hydrogel had a porous, fibrous structure with good interconnection (Fig.1A). The gelation curves indicated that the hydrogel could firmly form within 30 min, and the gelation behavior was independent of ECM concentration (Fig. 1B). The peak compressions of the hydrogels increased from 162 ±12 to 698 ± 26 Pa as the ECM concentration increased from 9 to 18 mg/mL (Fig. 1C). It was notable that higher ECM concentrations (15 and 18 mg/mL) resulted in significantly greater peak compressions. The mechanical properties of hydrogels could be easily altered by varying ECM concentration, which is desirable to create a microenvironment mechanically similar to lung tumor and to modulate cell-matrix interactions. A549 cells were mixed with pre-gel solution and evenly distributed in the hydrogel (Fig. 1D). It was observed that the A549 cells exhibited circular morphology with predominate live cells (green dots) throughout the hydrogel after 3 d, indicating a high survival rate. Therefore, the DL-ECM hydrogel was highly biocompatible and might provide a good platform for cancer cell proliferation and tumor formation in vitro. In addition, the ECM hydrogel could be delivered into body by injection, which might efficiently fill the gaps between in vitro and in vivo studies [4]. Figure 1. (A) SEM image of the DL-ECM hydrogel (insert is the macroscopic image). (B) gelation curves and (C) compressive stresses of the hydrogels at different ECM concentrations. (D) live/dead staining of A549 cells encapsulated in the hydrogel for 3d. Conclusions: We developed a DL-ECM hydrogel and elucidated its excellent characteristics that were biochemically similar to native ECM and mechanically tunable. The hydrogel was biocompatible to support lung cancer cell growth. These findings provided proof-of-principle for further study of using the hydrogel as a 3D model to explore effective treatments for lung cancer diseases. Startup grant of the University of Texas at Arlington

Three-dimensional cancer models mimic cell-matrix interactions in the tumour microenvironment

Basic in vitro systems can be used to model and assess complex diseases, such as cancer. Recent advances in this field include the incorporation of multiple cell types and extracellular matrix proteins into three-dimensional (3D) models to recapitulate the structure, organization and functionality of live tissue in situ. Cells within such a 3D environment behave very differently from cells on two-dimensional (2D) substrates, as cell-matrix interactions trigger signalling pathways and cellular responses in 3D, which may not be observed in 2D. Thus, the use of 3D systems can be advantageous for the assessment of disease progression over 2D set-ups alone. Here, we highlight the current advantages and challenges of employing 3D systems in the study of cancer and provide an overview to guide the appropriate use of distinct models in cancer research.

Abstract C64: Polystyrene scaffolds: A novel tool for in vitro three-dimensional cancer models

Abstract It is well known that three-dimensional (3D) cultures can more accurately represent physiological cell responses, and that two-dimensional (2D) in vitro cell culture systems fall short in predicting tumor cell behavior in vivo. Major shortcomings of 2D cell culture systems include altered cell morphologies, reduced aggression, and an inaccurate representation of the dynamic 3D cellular environment experienced by cells in vivo. These 2D cell culture obstacles become even more deleterious to research when performing drug screenings or studying disease pathogenesis. Hence, cancer research demands a more biologically relevant in vitro model system that can improve drug discovery success rates to combat rising rates of cancer and other diseases. Moreover, an accurate and reproducible in vitro model will accelerate the drug discovery process and significantly reduce development costs. To this end, we have engineered a novel transparent 3D polystyrene (PS) scaffold to meet the emerging demand. We hypothesize that these 3D PS scaffolds are a superior 3D in vitro model for tumor pathogenesis research and drug discovery and development. To test our hypothesis we cultured and observe the growth of two cancer cell lines, human epithelial MCF-7 cells and HepG2 hepatocarcinoma cells, on both 2D PS-tissue culture plates (TCP) and 3D PS scaffolds (3D Insert™-PS). Observation by an inverted light microscope indicated that MCF-7 and HepG2 cells cultured on the 3D PS scaffolds formed cell aggregates along scaffold fibers and within pores, whereas cells cultured on the 2D PS-TCPs adopted a phenotype characteristically seen in cells growing in flat monolayers. Proliferation time-course assays performed with MCF-7 and HepG2 cells demonstrated that growth rates and metabolic activities of cells cultured on 3D scaffolds were significantly enhanced at numerous time points when compared with cells cultured on 2D TCPs, as determined by Alamar blue and MTT assays. These data suggest that 3D Insert™-PS scaffolds provide an improved in vitro culture environment. The susceptibility of both 2D and 3D cultured MCF-7 and HepG2 cells to anticancer drugs was assessed by tamoxifen (TAM) [10-6 M and 10-5 M] and methotrexate (MTX) [25 µM and 100 µM] treatments, respectively. The cellular cytotoxic response to TAM and MTX was measured by MTT and LDH assays and was found to be significantly lower in MCF-7 and HepG2 cultured on 3D scaffolds compared with cells cultured in 2D TCPs. Taken together, these data indicate that cancer cells cultured on 3D Insert™-PS scaffolds are more robust and resistant to anticancer drug treatments than cells cultured on traditional 2D TCPs. Furthermore, 3D Insert™-PS scaffolds do not have the same limitations encountered with traditional 2D cell culture. In conclusion, using 3D Insert™-PS scaffolds as in vitro 3D tumor models will provide a superior 3D cell culture environment for cancer research and the evaluation of new anticancer drugs. Citation Information: Cancer Res 2009;69(23 Suppl):C64.