Phytochemicals inhibit migration of triple negative breast cancer cells by targeting kinase signaling.

BACKGROUND: Cell migration and invasion are essential processes for metastatic dissemination of cancer cells. Significant progress has been made in developing new therapies against oncogenic signaling to eliminate cancer cells and shrink tumors. However, inherent heterogeneity and treatment-induced adaptation to drugs commonly enable subsets of cancer cells to survive therapy. In addition to local recurrence, these cells escape a primary tumor and migrate through the stroma to access the circulation and metastasize to different organs, leading to an incurable disease. As such, therapeutics that block migration and invasion of cancer cells may inhibit or reduce metastasis and significantly improve cancer therapy. This is particularly more important for cancers, such as triple negative breast cancer, that currently lack targeted drugs. METHODS: We used cell migration, 3D invasion, zebrafish metastasis model, and phosphorylation analysis of 43 protein kinases in nine triple negative breast cancer (TNBC) cell lines to study effects of fisetin and quercetin on inhibition of TNBC cell migration, invasion, and metastasis. RESULTS: Fisetin and quercetin were highly effective against migration of all nine TNBC cell lines with up to 76 and 74% inhibitory effects, respectively. In addition, treatments significantly reduced 3D invasion of highly motile TNBC cells from spheroids into a collagen matrix and their metastasis in vivo. Fisetin and quercetin commonly targeted different components and substrates of the oncogenic PI3K/AKT pathway and significantly reduced their activities. Additionally, both compounds disrupted activities of several protein kinases in MAPK and STAT pathways. We used molecular inhibitors specific to these signaling proteins to establish the migration-inhibitory role of the two phytochemicals against TNBC cells. CONCLUSIONS: We established that fisetin and quercetin potently inhibit migration of metastatic TNBC cells by interfering with activities of oncogenic protein kinases in multiple pathways.

Synergistic Inhibition of Kinase Pathways Overcomes Resistance of Colorectal Cancer Spheroids to Cyclic Targeted Therapies.

Cancer cells often adapt to single-agent treatments with chemotherapeutics. Activation of alternative survival pathways is a major mechanism of drug resistance. A potential approach to block this feedback signaling is using combination treatments of a pair of drugs, although toxicity has been a limiting factor. Preclinical tumor models to identify mechanisms of drug resistance and determine low but effective combination doses are critical to effectively suppress tumor growth with reduced toxicity to patients. Using our aqueous two-phase system microtechnology, we developed colorectal tumor spheroids in high-throughput and evaluated resistance of cancer cells to three mitogen-activated protein kinase inhibitors (MAPKi) in long-term cyclic treatments. Our quantitative analysis showed that the efficacy of MAPKi significantly reduced over time, leading to an increase in proliferation of HCT116 colorectal cancer cells and growth of spheroids. We established that resistance was due to feedback activation of PI3K/AKT/mTOR pathway. Using high-throughput, dose-dependent combinations of each MAPKi and a PI3K/mTOR inhibitor, we identified low-dose, synergistic combinations that blocked resistance to MAPKi and effectively suppressed the growth of colorectal tumor spheroids in long-term treatments. Our approach to study drug resistance offers the potential to determine high priority treatments to test in animal models.

Stem cell colony interspacing effect on differentiation to neural cells.

Efforts to enhance the efficiency of neural differentiation of stem cells are primarily focused on exogenous modulation of physical niche parameters such as surface topography and extracellular matrix proteins, or addition of certain growth factors or small molecules to culture media. We report a novel neurogenic niche to enhance the neural differentiation of embryonic stem cells (ESCs) without any external intervention by micropatterning ESCs into spatially organized colonies of controlled size and interspacing. Using an aqueous two-phase system cell microprinting technology, we generated pairs of uniformly sized isolated ESC colonies at defined interspacing distances over a layer of differentiation-inducing stromal cells. Our comprehensive analysis of temporal expression of neural genes and proteins of cells in colony pairs showed that interspacing two colonies at approximately 0.66 times the colony diameter (0.66D) significantly enhanced neural differentiation of ESCs. Cells in these colonies displayed higher expression of neural genes and proteins and formed thick neurite bundles between the two colonies. A computational model of spatial distribution of soluble factors of cells in interspaced colony pairs showed that the enhanced neural differentiation is due to the presence of stable concentration gradients of soluble signalling factors between the two colonies. Our results indicate that culturing ESCs in colony pairs with defined interspacing is a promising approach to efficiently derive neural cells. Additionally, this approach provides a platform for quantitative studies of molecular mechanisms that regulate neurogenesis of stem cells.

Statistical analysis of multi-dimensional, temporal gene expression of stem cells to elucidate colony size-dependent neural differentiation.

High throughput gene expression analysis using qPCR is commonly used to identify molecular markers of complex cellular processes. However, statistical analysis of multi-dimensional, temporal gene expression data is complicated by limited biological replicates and large number of measurements. Moreover, many available statistical tools for analysis of time series data assume that the data sequence is static and does not evolve over time. With this assumption, the parameters used to model the time series are fixed and thus, can be estimated by pooling data together. However, in many cases, dynamic processes of biological systems involve abrupt changes at unknown time points, making the assumption of stationary time series break down. We addressed this problem using a combination of statistical methods including hierarchical clustering, change point detection, and multiple testing. We applied this multi-step method to multi-dimensional, temporal gene expression data that resulted from our study of colony size-dependent neural cell differentiation of stem cells. The gene expression data were time series as the observations were recorded sequentially over time. Hierarchical clustering segregated the genes into three distinct clusters based on their temporal expression profiles; change point detection identified specific time points at which the entire dataset was divided into several homogenous subsets to allow a separate analysis of each subset; and multiple testing procedure identified the differentially expressed genes in each cluster within each subset of data. We established that our multi-step approach pinpoints specific sets of genes that underlie colony size-mediated neural differentiation of stem cells and demonstrated its advantages over conventional parametric and non-parametric tests that do not take into account temporal dynamics of the data. Importantly, our proposed approach is broadly applicable to any multivariate data sets of limited sample size from high throughput and high content screening such as in drug and biomarker discovery studies.

Microprinted Stem Cell Niches Reveal Compounding Effect of Colony Size on Stromal Cells-Mediated Neural Differentiation.

Microenvironmental factors have a major impact on differentiation of embryonic stem cells (ESCs). Here, a novel phenomenon that size of ESC colonies has a significant regulatory role on stromal cells induced differentiation of ESCs to neural cells is reported. Using a robotic cell microprinting technology, defined densities of ESCs are confined within aqueous nanodrops over a layer of supporting stromal cells immersed in a second, immiscible aqueous phase to generate ESC colonies of defined sizes. Temporal protein and gene expression studies demonstrate that larger ESC colonies generate disproportionally more neural cells and longer neurite processes. Unlike previous studies that attribute neural differentiation of ESCs solely to interactions with stromal cells, it is found that increased intercellular signaling of ESCs significantly enhances neural differentiation. This study offers an approach to generate neural cells with improved efficiency for potential use in translational research.

Colony size effect on neural differentiation of embryonic stem cells microprinted on stromal cells.

Controlling cellular microenvironment to induce neural differentiation of embryonic stem cells (ESCs) remains a major challenge. We address this need by introducing a micro-engineered co-culture system that resembles embryonic development in terms of direct intercellular interactions and induces neural differentiation of ESCs. A polymeric aqueous two-phase system (ATPS)-mediated robotic microprinting technology allows precise localization of mouse ESCs (mESCs) over a layer of supporting stromal cells. mESCs proliferate over a 2-week culture period into a single colony of defined size. Physical and chemical cues from the stromal cells guide mESCs to differentiate toward specific neural lineages. We generated mESC colonies of three different sizes from 100, 250 and 500 single cells and showed that size of mESC colonies is an important factor determining the yield of neural cells. Expression of early neural cell markers nestin denoting neural stem cells, NCAM specifying neural progenitors, and ß-III tubulin (TuJ) indicating post mitotic neurons escalated from day 4. Differentiation into specific neural cells astrocytes marked by GFAP, oligodendrocytes indicated by CNPase, and TH-positive dopaminergic neurons was observed during the second week of culture. Unexpectedly, analysis of protein expression revealed a disproportionate increase in neural differentiation of mESCs by increase in the colony size. For the first time, our study establishes colony size as an important regulator of fate of ESCs in this heterocellular niche. This approach of deriving neural cells may make a major impact on stem cell research for treating neurodegenerative diseases.

Molecular Analysis of Stromal Cells-Induced Neural Differentiation of Mouse Embryonic Stem Cells.

Deriving specific neural cells from embryonic stem cells (ESCs) is a promising approach for cell replacement therapies of neurodegenerative diseases. When co-cultured with certain stromal cells, mouse ESCs (mESCs) differentiate efficiently to neural cells. In this study, a comprehensive gene and protein expression analysis of differentiating mESCs is performed over a two-week culture period to track temporal progression of cells from a pluripotent state to specific terminally-differentiated neural cells such as neurons, astrocytes, and oligodendrocytes. Expression levels of 26 genes consisting of marker genes for pluripotency, neural progenitors, and specific neuronal, astroglial, and oligodendrocytic cells are tracked using real time q-PCR. The time-course gene expression analysis of differentiating mESCs is combined with the hierarchal clustering and functional principal component analysis (FPCA) to elucidate the evolution of specific neural cells from mESCs at a molecular level. These statistical analyses identify three major gene clusters representing distinct phases of transition of stem cells from a pluripotent state to a terminally-differentiated neuronal or glial state. Temporal protein expression studies using immunohistochemistry demonstrate the generation of neural stem/progenitor cells and specific neural lineages and show a close agreement with the gene expression profiles of selected markers. Importantly, parallel gene and protein expression analysis elucidates long-term stability of certain proteins compared to those with a quick turnover. Describing the molecular regulation of neural cells commitment of mESCs due to stromal signaling will help identify major promoters of differentiation into specific cell types for use in cell replacement therapy applications.

Liquid-based three-dimensional tumor models for cancer research and drug discovery.

Tumors are three-dimensional tissues where close contacts between cancer cells, intercellular interactions between cancer and stromal cells, adhesion of cancer cells to the extracellular matrix, and signaling of soluble factors modulate functions of cancer cells and their response to therapeutics. Three-dimensional cultures of cancer cells overcome limitations of traditionally used monolayer cultures and recreate essential characteristics of tumors such as spatial gradients of oxygen, growth factors, and metabolites and presence of necrotic, hypoxic, quiescent, and proliferative cells. As such, three-dimensional tumor models provide a valuable tool for cancer research and oncology drug discovery. Here, we describe different tumor models and primarily focus on a model known as tumor spheroid. We summarize different technologies of spheroid formation, and discuss the use of spheroids to address the influence of stromal fibroblasts and immune cells on cancer cells in tumor microenvironment, study cancer stem cells, and facilitate compound screening in the drug discovery process. We review major techniques for quantification of cellular responses to drugs and discuss challenges ahead to enable broad utility of tumor spheroids in research laboratories, integrate spheroid models into drug development and discovery pipeline, and use primary tumor cells for drug screening studies to realize personalized cancer treatment.

Engineered Breast Cancer Cell Spheroids Reproduce Biologic Properties of Solid Tumors.

Solid tumors develop as 3D tissue constructs. As tumors grow larger, spatial gradients of nutrients and oxygen and inadequate diffusive supply to cells distant from vasculature develops. Hypoxia initiates signaling and transcriptional alterations to promote survival of cancer cells and generation of cancer stem cells (CSCs) that have self-renewal and tumor-initiation capabilities. Both hypoxia and CSCs are associated with resistance to therapies and tumor relapse. This study demonstrates that 3D cancer cell models, known as tumor spheroids, generated with a polymeric aqueous two-phase system (ATPS) technology capture these important biological processes. Similar to solid tumors, spheroids of triple negative breast cancer cells deposit major extracellular matrix proteins. The molecular analysis establishes presence of hypoxic cells in the core region and expression of CSC gene and protein markers including CD24, CD133, and Nanog. Importantly, these spheroids resist treatment with chemotherapy drugs. A combination treatment approach using a hypoxia-activated prodrug, TH-302, and a chemotherapy drug, doxorubicin, successfully targets drug resistant spheroids. This study demonstrates that ATPS spheroids recapitulate important biological and functional properties of solid tumors and provide a unique model for studies in cancer research.

Microengineered embryonic stem cells niche to induce neural differentiation.

A major challenge in therapeutic use of embryonic stem cells (ESCs) for treating neurodegenerative diseases is creating a niche in vitro for controlled neural-specific differentiation of ESCs. We employ a niche microengineering approach to derive neural cells from ESCs by mimicking embryonic development in terms of direct intercellular interactions. Using a polymeric aqueous two-phase system (ATPS) microprinting technology, murine ESCs (mESCs) are precisely localized over a monolayer of supporting stromal cells to allow formation of individual mESC colonies. Polyethylene glycol (PEG) and dextran (DEX) are dissolved in culture media to form two immiscible aqueous solutions. A robotic liquid handler is used to print a nanoliter-volume drop of the denser DEX phase solution containing mESCs onto a confluent layer of supporting PA6 stromal cells submerged in the aqueous PEG phase. mESCs proliferate into isolated colonies of uniform size. For the first time, a comprehensive protein expression analysis of individual mESC colonies is performed over a two-week culture period to track temporal progression of cells from a pluripotent stage to specific neural cells. Starting from day 4, the expression of nestin, neural cell adhesion molecule (NCAM), and beta-III tubulin shows a significant increase but then levels off after the first week of culture. The expression of specific neural cell markers glial fibrillary acidic protein (GFAP), 2',3'-cyclic-nucleotide 3'-phosphodiesterase (CNPase), and tyrosine hydroxylase (TH) is elevated during the second week of culture. This microengineering approach to control ESCs differentiation niche combined with the time-course protein expression analysis of individual differentiating colonies facilitates understanding of evolution of specific neural cells from ESCs and identifying underlying molecular markers.

Interfacial Tension Effect on Cell Partition in Aqueous Two-Phase Systems.

Aqueous two-phase systems (ATPS) provide a mild environment for the partition and separation of cells. We report a combined experimental and theoretical study on the effect of interfacial tension of polymeric ATPS on the partitioning of cells between two phases and their interface. Two-phase systems are generated using polyethylene glycol and dextran of specific properties as phase-forming polymers and culture media as the solvent component. Ultralow interfacial tensions of the solutions are precisely measured using an axisymmetric drop shape analysis method. Partition experiments show that two-phase systems with an interfacial tension of 30 µJ/m(2) result in distribution of majority of cells to the bottom dextran phase. An increase in the interfacial tension results in a distribution of cells toward the interface. An independent cancer cell spheroid formation assay confirms these observations: a drop of the dextran phase containing cancer cells is dispensed into the immersion polyethylene glycol phase to form a cell-containing drop. Only at very small interfacial tensions do cells remain within the drop to aggregate into a spheroid. We perform a thermodynamic modeling of cell partition to determine variations of free energy associated with displacement of cells in ATPS with respect to the ultralow interfacial tensions. This modeling corroborates with the experimental results and demonstrates that at the smallest interfacial tension of 30 µJ/m(2), the free energy is a minimum with cells in the bottom phase. Increasing the interfacial tension shifts the minimum energy and partition of cells toward the interfacial region of the two aqueous phases. Examining differences in the partition behavior and minimum free energy modeling of A431.H9 cancer cells and mouse embryonic stem cells shows that the surface properties of cells further modulate partition in ATPS. This combined approach provides a fundamental understanding of interfacial tension role on cell partition in ATPS and a framework for future studies.