An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells

In this work we describe a novel approach that combines ex vivo drug sensitivity assays and digital image analysis to estimate chemosensitivity and ...

H. Lee Moffitt Cancer Center and Research Institute

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

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

A number of successful systemic therapies are available for treatment of disseminated cancers. However, tumor response is often transient, and therapy frequently fails due to emergence of resistant populations. The latter reflects the temporal and spatial heterogeneity of the tumor microenvironment as well as the evolutionary capacity of cancer phenotypes to adapt to therapeutic perturbations. Although cancers are highly dynamic systems, cancer therapy is typically administered according to a fixed, linear protocol. Here we examine an adaptive therapeutic approach that evolves in response to the temporal and spatial variability of tumor microenvironment and cellular phenotype as well as therapy-induced perturbations. Initial mathematical models find that when resistant phenotypes arise in the untreated tumor, they are typically present in small numbers because they are less fit than the sensitive population. This reflects the "cost" of phenotypic resistance such as additional substrate and energy used to up-regulate xenobiotic metabolism, and therefore not available for proliferation, or the growth inhibitory nature of environments (i.e., ischemia or hypoxia) that confer resistance on phenotypically sensitive cells. Thus, in the Darwinian environment of a cancer, the fitter chemosensitive cells will ordinarily proliferate at the expense of the less fit chemoresistant cells. The models show that, if resistant populations are present before administration of therapy, treatments designed to kill maximum numbers of cancer cells remove this inhibitory effect and actually promote more rapid growth of the resistant populations. We present an alternative approach in which treatment is continuously modulated to achieve a fixed tumor population. The goal of adaptive therapy is to enforce a stable tumor burden by permitting a significant population of chemosensitive cells to survive so that they, in turn, suppress proliferation of the less fit but chemoresistant subpopulations. Computer simulations show that this strategy can result in prolonged survival that is substantially greater than that of high dose density or metronomic therapies. The feasibility of adaptive therapy is supported by in vivo experiments. [Cancer Res 2009;69(11):4894-903] Major FindingsWe present mathematical analysis of the evolutionary dynamics of tumor populations with and without therapy. Analytic solutions and numerical simulations show that, with pretreatment, therapy-resistant cancer subpopulations are present due to phenotypic or microenvironmental factors; maximum dose density chemotherapy hastens rapid expansion of resistant populations. The models predict that host survival can be maximized if "treatment-for-cure strategy" is replaced by "treatment-for-stability." Specifically, the models predict that an optimal treatment strategy will modulate therapy to maintain a stable population of chemosensitive cells that can, in turn, suppress the growth of resistant populations under normal tumor conditions (i.e., when therapy-induced toxicity is absent). In vivo experiments using OVCAR xenografts treated with carboplatin show that adaptive therapy is feasible and, in this system, can produce long-term survival.

Adaptive therapy.

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

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

Disseminated cancer remains a nearly uniformly fatal disease. While a number of effective chemotherapies are available, tumors inevitably evolve resistance to these drugs ultimately resulting in treatment failure and cancer progression. Causes for chemotherapy failure in cancer treatment reside in multiple levels: poor vascularization, hypoxia, intratumoral high interstitial fluid pressure, and phenotypic resistance to drug-induced toxicity through upregulated xenobiotic metabolism or DNA repair mechanisms and silencing of apoptotic pathways. We propose that in order to understand the evolutionary dynamics that allow tumors to develop chemoresistance, a comprehensive quantitative model must be used to describe the interactions of cell resistance mechanisms and tumor microenvironment during chemotherapy.Ultimately, the purpose of this model is to identify the best strategies to treat different types of tumor (tumor microenvironment, genetic/phenotypic tumor heterogeneity, tumor growth rate, etc.). We predict that the most promising strategies are those that are both cytotoxic and apply a selective pressure for a phenotype that is less fit than that of the original cancer population. This strategy, known as double bind, is different from the selection process imposed by standard chemotherapy, which tends to produce a resistant population that simply upregulates xenobiotic metabolism. In order to achieve this goal we propose to simulate different tumor progression and therapy strategies (chemotherapy and glucose restriction) targeting stabilization of tumor size and minimization of chemoresistance.

A theoretical quantitative model for evolution of cancer chemotherapy resistance.

Immunoglobulin (Ig) and T-cell receptor (TCR) gene rearrangements function as specific markers for minimal residual disease (MRD), which is one of the best predictors of outcome in childhood acute lymphoblastic leukemia (ALL). We recently reported on the prognostic value of MRD during the induction of remission through a simplified PCR method. Here, we report on gene rearrangement frequencies and offer guidelines for the application of the technique.

Detection of clonal immunoglobulin and T-cell receptor gene rearrangements in childhood acute lymphoblastic leukemia using a low-cost PCR strategy.

The bone marrow is necessary for renewal of all hematopoietic cells and critical for maintenance of a wide range of physiologic functions. Multiple human diseases result from bone marrow dysfunction. It is also the site in which liquid tumors, including leukemia and multiple myeloma, develop as well as a frequent site of metastases. Understanding the complex cellular and microenvironmental interactions that govern normal bone marrow function as well as diseases and cancers of the bone marrow would be a valuable medical advance. Our goal is the development of a spatially-explicit in silico model of the bone marrow to understand both its normal function and the evolutionary dynamics that govern the emergence of bone marrow malignancy. Here we introduce a multiscale computational model of the bone marrow that incorporates three distinct spatial scales, cell, hematopoietic subunit, whole marrow. Our results, using parameter estimates from literature, recapitulates normal bone marrow function and suggest an explanation for the fractal-like structure of trabeculae and sinuses in the marrow, which would be an optimization of the hematopoietic function in order to maximize the number of mature blood cells produced daily within the volumetric restrictions of the marrow.

A multiscale model of the bone marrow and hematopoiesis.

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

Evolution of tumor invasiveness: the adaptive tumor microenvironment landscape model.

Aberrant mutations of centrocytes in germinal centers (GC) can generate two completely different diseases: B-cell lymphomas and monoclonal gammopathy of undetermined significance (MGUS). In this article we use computational models to examine the evolutionary dynamics by which initial adaptation to survival in the GC allows naive MGUS cells to proliferate in the bone marrow and initiate the evolutionary process that will lead to aggressive multiple myeloma (MM). Our simulations show that MGUS cells may generate bone marrow tumors ranging from indolent to aggressive, depending on the original adaptation in the GC. All these tumors, however, are limited to approximately 15% of the marrow cellularity due to hypoxia-induced quiescence (this correlates with the cellularity that separates MGUS and MM, ∼10%). Resistance to hypoxia-induced quiescence and cell death was one of the two major bone marrow adaptations that allowed continued tumor growth and establishment of paracrine cytokine loops, known to increase MM cell replication and de novo multidrug resistance. The second major adaptation was an increase in IL-6-independent growth rate, which correlates with the mutations observed in advanced stage patients. Even though there was an increase in the microvessel density in all simulations, the "angiogenic switch" was not due to a MM angiogenic phenotype, but rather the response of MM cells to the regional hypoxia caused by the increased tumor burden. These results indicate that treatments targeting the adaptation to survival and proliferation in hypoxia, in conjunction with currently available therapies, may have synergistic effects, by delaying tumor growth and reducing cytokine paracrine loops mediated by angiogenic factors.

Adaptation to survival in germinal center is the initial step in onset of indolent stage of multiple myeloma.

Many cancers adapt to chemotherapeutic agents by upregulating membrane efflux pumps that export drugs from the cytoplasm, but this response comes at an energetic cost. In breast cancer patients, expression of these pumps is low in tumors before therapy but increases after treatment. While the evolution of therapeutic resistance is virtually inevitable, proliferation of resistant clones is not, suggesting strategies of adaptive therapy. Chemoresistant cells must consume excess resources to maintain resistance mechanisms, so adaptive therapy strategies explicitly aim to maintain a stable population of therapy-sensitive cells to suppress growth of resistant phenotypes through intratumoral competition. We used computational models parameterized by in vitro experiments to illustrate the efficacy of such approaches. Here, we show that low doses of verapamil and 2-deoxyglucose, to accentuate the cost of resistance and to decrease energy production, respectively, could suppress the proliferation of drug-resistant clones in vivo. Compared with standard high-dose-density treatment, the novel treatment we developed achieved a 2-fold to 10-fold increase in time to progression in tumor models. Our findings challenge the existing flawed paradigm of maximum dose treatment, a strategy that inevitably produces drug resistance that can be avoided by the adaptive therapy strategies we describe.

Evolutionary approaches to prolong progression-free survival in breast cancer.

The melanocortin 1 receptor (MC1R) is overexpressed in most melanoma metastases, making it a promising target for imaging of melanomas. In this study, the expression of MC1R in a large fraction of patients with melanoma was confirmed using mRNA and tissue microarray. Here, we have characterized the in vivo tumor and tissue distribution and pharmacokinetics (PK) of uptake and clearance of a MC1R specific peptidomimetic ligand conjugated to a near-infrared fluorescent dye. We propose an interdisciplinary framework to bridge the different time and space scales of ligand-tumor-host interactions: intravital fluorescence microscopy to quantify probe internalization at the cellular level, a xenograft tumor model for whole body pharmacokinetics, and a computational pharmacokinetic model for integration and interpretation of experimental data. Administration of the probe into mice bearing tumors with high and low MC1R expression demonstrated normalized image intensities that correlated with expression levels (p < 0.05). The biodistribution study showed high kidney uptake as early as 30 min postinjection. The PK computational model predicted the presence of receptors in the kidneys with a lower affinity, but at higher numbers than in the tumors. As the mouse kidney is known to express the MC5R, this hypothesis was confirmed by both coinjection of a ligand with higher MC5R affinity compared to MC1R and by injection of lower probe concentrations (e.g., 1 nmol/kg), both leading to decreased kidney accumulation of the MC1R ligand. In addition, through this interdisciplinary approach we could predict the rates of ligand accumulation and clearance into and from organs and tumors, and the amount of injected ligand required to have maximum specific retention in tumors. These predictions have potential to aid in the translation of a targeted agent from lab to the clinic. In conclusion, the characterized MC1R-specific probe has excellent potential for in vivo detection of melanoma metastases. The process of cell-surface marker validation, targeted imaging probe development, and in vitro, in vivo, and in silico characterization described in this study can be generally applied to preclinical development of targeted agents.

In vivo and in silico pharmacokinetics and biodistribution of a melanocortin receptor 1 targeted agent in preclinical models of melanoma.

Accurate preclinical predictions of the clinical efficacy of experimental cancer drugs are highly desired but often haphazard. Such predictions might be improved by incorporating elements of the tumor microenvironment in preclinical models by providing a more physiological setting. In generating improved xenograft models, it is generally accepted that the use of primary tumors from patients are preferable to clonal tumor cell lines. Here we describe an interdisciplinary platform to study drug response in multiple myeloma, an incurable cancer of the bone marrow. This platform uses microfluidic technology to minimize the number of cells per experiment, while incorporating three-dimensional extracellular matrix and mesenchymal cells derived from the tumor microenvironment. We used sequential imaging and a novel digital imaging analysis algorithm to quantify changes in cell viability. Computational models were used to convert experimental data into dose-exposure-response "surfaces," which offered predictive utility. Using this platform, we predicted chemosensitivity to bortezomib and melphalan, two clinical multiple myeloma treatments, in three multiple myeloma cell lines and seven patient-derived primary multiple myeloma cell populations. We also demonstrated how this system could be used to investigate environment-mediated drug resistance and drug combinations that target it. This interdisciplinary preclinical assay is capable of generating quantitative data that can be used in computational models of clinical response, demonstrating its utility as a tool to contribute to personalized oncology.

A preclinical assay for chemosensitivity in multiple myeloma.

Oral administration of pH buffers can reduce the development of spontaneous and experimental metastases in mice, and has been proposed in clinical trials. Effectiveness of buffer therapy is likely to be affected by diet, which could contribute or interfere with the therapeutic alkalinizing effect. Little data on food pH buffering capacity was available. This study evaluated the pH and buffering capacity of different foods to guide prospective trials and test the effect of the same buffer (lysine) at two different ionization states. Food groups were derived from the Harvard Food Frequency Questionnaire. Foods were blended and pH titrated with acid from initial pH values until 4.0 to determine "buffering score", in mmol H(+)/pH unit. A "buffering score" was derived as the mEq H(+) consumed per serving size to lower from initial to a pH 4.0, the postprandial pH of the distal duodenum. To differentiate buffering effect from any metabolic byproduct effects, we compared the effects of oral lysine buffers prepared at either pH 10.0 or 8.4, which contain 2 and 1 free base amines, respectively. The effect of these on experimental metastases formation in mice following tail vein injection of PC-3M prostate cancer cells were monitored with in vivo bioluminescence. Carbohydrates and dairy products' buffering score varied between 0.5 and 19. Fruits and vegetables showed a low to zero buffering score. The score of meats varied between 6 and 22. Wine and juices had negative scores. Among supplements, sodium bicarbonate and Tums(®) had the highest buffering capacities, with scores of 11 and 20 per serving size, respectively. The "de-buffered" lysine had a less pronounced effect of prevention of metastases compared to lysine at pH 10. This study has demonstrated the anti-cancer effects of buffer therapy and suggests foods that can contribute to or compete with this approach to manage cancer.

Ariosto Silva

Department of Cancer Imaging and Metabolism

H. Lee Moffitt Cancer Center and Research Institute

An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells

Ariosto Silva

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Cancer Imaging and Metabolism

H. Lee Moffitt Cancer Center and Research Institute

An Organotypic High Throughput System for Characterization of Drug Sensitivity of Primary Multiple Myeloma Cells

Department of Cancer Imaging and Metabolism