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Cell stiffness is a biomarker of the metastatic potential of ovarian cancer cells.
The metastatic potential of cells is an important parameter in the design of optimal strategies for the personalized treatment of cancer. Using atomic force microscopy (AFM), we show, consistent with previous studies conducted in other types of epithelial cancer, that ovarian cancer cells are generally softer and display lower intrinsic variability in cell stiffness than non-malignant ovarian epithelial cells. A detailed examination of highly invasive ovarian cancer cells (HEY A8) relative to their less invasive parental cells (HEY), demonstrates that deformability is also an accurate biomarker of metastatic potential. Comparative gene expression analyses indicate that the reduced stiffness of highly metastatic HEY A8 cells is associated with actin cytoskeleton remodeling and microscopic examination of actin fiber structure in these cell lines is consistent with this prediction. Our results indicate that cell stiffness may be a useful biomarker to evaluate the relative metastatic potential of ovarian and perhaps other types of cancer cells.
Authors: Gawain Thomas, Nancy A. Burnham, Terri Anne Camesano, Qi Wen.
Published: 06-27-2013
Mechanical properties of cells and extracellular matrix (ECM) play important roles in many biological processes including stem cell differentiation, tumor formation, and wound healing. Changes in stiffness of cells and ECM are often signs of changes in cell physiology or diseases in tissues. Hence, cell stiffness is an index to evaluate the status of cell cultures. Among the multitude of methods applied to measure the stiffness of cells and tissues, micro-indentation using an Atomic Force Microscope (AFM) provides a way to reliably measure the stiffness of living cells. This method has been widely applied to characterize the micro-scale stiffness for a variety of materials ranging from metal surfaces to soft biological tissues and cells. The basic principle of this method is to indent a cell with an AFM tip of selected geometry and measure the applied force from the bending of the AFM cantilever. Fitting the force-indentation curve to the Hertz model for the corresponding tip geometry can give quantitative measurements of material stiffness. This paper demonstrates the procedure to characterize the stiffness of living cells using AFM. Key steps including the process of AFM calibration, force-curve acquisition, and data analysis using a MATLAB routine are demonstrated. Limitations of this method are also discussed.
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Assessment of Ovarian Cancer Spheroid Attachment and Invasion of Mesothelial Cells in Real Time
Authors: Maree Bilandzic, Kaye L. Stenvers.
Institutions: MIMR-PHI Institute of Medical Research, Monash University.
Ovarian cancers metastasize by shedding into the peritoneal fluid and dispersing to distal sites within the peritoneum. Monolayer cultures do not accurately model the behaviors of cancer cells within a nonadherent environment, as cancer cells inherently aggregate into multicellular structures which contribute to the metastatic process by attaching to and invading the peritoneal lining to form secondary tumors. To model this important stage of ovarian cancer metastasis, multicellular aggregates, or spheroids, can be generated from established ovarian cancer cell lines maintained under nonadherent conditions. To mimic the peritoneal microenvironment encountered by tumor cells in vivo, a spheroid-mesothelial co-culture model was established in which preformed spheroids are plated on top of a human mesothelial cell monolayer, formed over an extracellular matrix barrier. Methods were then developed using a real-time cell analyzer to conduct quantitative real time measurements of the invasive capacity of different ovarian cancer cell lines grown as spheroids. This approach allows for the continuous measurement of invasion over long periods of time, which has several advantages over traditional endpoint assays and more laborious real time microscopy image analyses. In short, this method enables a rapid, determination of factors which regulate the interactions between ovarian cancer spheroid cells invading through mesothelial and matrix barriers over time.
Medicine, Issue 87, Ovarian cancer, metastasis, invasion, mesothelial cells, spheroids, real time analysis
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In vitro Mesothelial Clearance Assay that Models the Early Steps of Ovarian Cancer Metastasis
Authors: Rachel A. Davidowitz, Marcin P. Iwanicki, Joan S. Brugge.
Institutions: Harvard Medical School.
Ovarian cancer is the fifth leading cause of cancer related deaths in the United States1. Despite a positive initial response to therapies, 70 to 90 percent of women with ovarian cancer develop new metastases, and the recurrence is often fatal2. It is, therefore, necessary to understand how secondary metastases arise in order to develop better treatments for intermediate and late stage ovarian cancer. Ovarian cancer metastasis occurs when malignant cells detach from the primary tumor site and disseminate throughout the peritoneal cavity. The disseminated cells can form multicellular clusters, or spheroids, that will either remain unattached, or implant onto organs within the peritoneal cavity3 (Figure 1, Movie 1). All of the organs within the peritoneal cavity are lined with a single, continuous, layer of mesothelial cells4-6 (Figure 2). However, mesothelial cells are absent from underneath peritoneal tumor masses, as revealed by electron micrograph studies of excised human tumor tissue sections3,5-7 (Figure 2). This suggests that mesothelial cells are excluded from underneath the tumor mass by an unknown process. Previous in vitro experiments demonstrated that primary ovarian cancer cells attach more efficiently to extracellular matrix than to mesothelial cells8, and more recent studies showed that primary peritoneal mesothelial cells actually provide a barrier to ovarian cancer cell adhesion and invasion (as compared to adhesion and invasion on substrates that were not covered with mesothelial cells)9,10. This would suggest that mesothelial cells act as a barrier against ovarian cancer metastasis. The cellular and molecular mechanisms by which ovarian cancer cells breach this barrier, and exclude the mesothelium have, until recently, remained unknown. Here we describe the methodology for an in vitro assay that models the interaction between ovarian cancer cell spheroids and mesothelial cells in vivo (Figure 3, Movie 2). Our protocol was adapted from previously described methods for analyzing ovarian tumor cell interactions with mesothelial monolayers8-16, and was first described in a report showing that ovarian tumor cells utilize an integrin –dependent activation of myosin and traction force to promote the exclusion of the mesothelial cells from under a tumor spheroid17. This model takes advantage of time-lapse fluorescence microscopy to monitor the two cell populations in real time, providing spatial and temporal information on the interaction. The ovarian cancer cells express red fluorescent protein (RFP) while the mesothelial cells express green fluorescent protein (GFP). RFP-expressing ovarian cancer cell spheroids attach to the GFP-expressing mesothelial monolayer. The spheroids spread, invade, and force the mesothelial cells aside creating a hole in the monolayer. This hole is visualized as the negative space (black) in the GFP image. The area of the hole can then be measured to quantitatively analyze differences in clearance activity between control and experimental populations of ovarian cancer and/ or mesothelial cells. This assay requires only a small number of ovarian cancer cells (100 cells per spheroid X 20-30 spheroids per condition), so it is feasible to perform this assay using precious primary tumor cell samples. Furthermore, this assay can be easily adapted for high throughput screening.
Medicine, Issue 60, Ovarian Cancer, Metastasis, In vitro Model, Mesothelial, Spheroid
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A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies
Authors: Inti Zlobec, Guido Suter, Aurel Perren, Alessandro Lugli.
Institutions: University of Bern.
Biomarker research relies on tissue microarrays (TMA). TMAs are produced by repeated transfer of small tissue cores from a ‘donor’ block into a ‘recipient’ block and then used for a variety of biomarker applications. The construction of conventional TMAs is labor intensive, imprecise, and time-consuming. Here, a protocol using next-generation Tissue Microarrays (ngTMA) is outlined. ngTMA is based on TMA planning and design, digital pathology, and automated tissue microarraying. The protocol is illustrated using an example of 134 metastatic colorectal cancer patients. Histological, statistical and logistical aspects are considered, such as the tissue type, specific histological regions, and cell types for inclusion in the TMA, the number of tissue spots, sample size, statistical analysis, and number of TMA copies. Histological slides for each patient are scanned and uploaded onto a web-based digital platform. There, they are viewed and annotated (marked) using a 0.6-2.0 mm diameter tool, multiple times using various colors to distinguish tissue areas. Donor blocks and 12 ‘recipient’ blocks are loaded into the instrument. Digital slides are retrieved and matched to donor block images. Repeated arraying of annotated regions is automatically performed resulting in an ngTMA. In this example, six ngTMAs are planned containing six different tissue types/histological zones. Two copies of the ngTMAs are desired. Three to four slides for each patient are scanned; 3 scan runs are necessary and performed overnight. All slides are annotated; different colors are used to represent the different tissues/zones, namely tumor center, invasion front, tumor/stroma, lymph node metastases, liver metastases, and normal tissue. 17 annotations/case are made; time for annotation is 2-3 min/case. 12 ngTMAs are produced containing 4,556 spots. Arraying time is 15-20 hr. Due to its precision, flexibility and speed, ngTMA is a powerful tool to further improve the quality of TMAs used in clinical and translational research.
Medicine, Issue 91, tissue microarray, biomarkers, prognostic, predictive, digital pathology, slide scanning
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Enrichment for Chemoresistant Ovarian Cancer Stem Cells from Human Cell Lines
Authors: Jennifer M. Cole, Stancy Joseph, Christopher G. Sudhahar, Karen D. Cowden Dahl.
Institutions: Indiana University School of Medicine.
Cancer stem cells (CSCs) are defined as a subset of slow cycling and undifferentiated cells that divide asymmetrically to generate highly proliferative, invasive, and chemoresistant tumor cells. Therefore, CSCs are an attractive population of cells to target therapeutically. CSCs are predicted to contribute to a number of types of malignancies including those in the blood, brain, lung, gastrointestinal tract, prostate, and ovary. Isolating and enriching a tumor cell population for CSCs will enable researchers to study the properties, genetics, and therapeutic response of CSCs. We generated a protocol that reproducibly enriches for ovarian cancer CSCs from ovarian cancer cell lines (SKOV3 and OVCA429). Cell lines are treated with 20 µM cisplatin for 3 days. Surviving cells are isolated and cultured in a serum-free stem cell media containing cytokines and growth factors. We demonstrate an enrichment of these purified CSCs by analyzing the isolated cells for known stem cell markers Oct4, Nanog, and Prom1 (CD133) and cell surface expression of CD177 and CD133. The CSCs exhibit increased chemoresistance. This method for isolation of CSCs is a useful tool for studying the role of CSCs in chemoresistance and tumor relapse.
Medicine, Issue 91, cancer stem cells, stem cell markers, ovarian cancer, chemoresistance, cisplatin, cancer progression
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Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Authors: Natalia J. Sumi, Eydis Lima, John Pizzonia, Sean P. Orton, Vinicius Craveiro, Wonduk Joo, Jennie C. Holmberg, Marta Gurrea, Yang Yang-Hartwich, Ayesha Alvero, Gil Mor.
Institutions: Yale University School of Medicine, NatureMost Laboratories, Bruker Preclinical Imaging.
Epithelial ovarian cancer is the most lethal gynecologic malignancy in the United States. Although patients initially respond to the current standard of care consisting of surgical debulking and combination chemotherapy consisting of platinum and taxane compounds, almost 90% of patients recur within a few years. In these patients the development of chemoresistant disease limits the efficacy of currently available chemotherapy agents and therefore contributes to the high mortality. To discover novel therapy options that can target recurrent disease, appropriate animal models that closely mimic the clinical profile of patients with recurrent ovarian cancer are required. The challenge in monitoring intra-peritoneal (i.p.) disease limits the use of i.p. models and thus most xenografts are established subcutaneously. We have developed a sensitive optical imaging platform that allows the detection and anatomical location of i.p. tumor mass. The platform includes the use of optical reporters that extend from the visible light range to near infrared, which in combination with 2-dimensional X-ray co-registration can provide anatomical location of molecular signals. Detection is significantly improved by the use of a rotation system that drives the animal to multiple angular positions for 360 degree imaging, allowing the identification of tumors that are not visible in single orientation. This platform provides a unique model to non-invasively monitor tumor growth and evaluate the efficacy of new therapies for the prevention or treatment of recurrent ovarian cancer.
Cancer Biology, Issue 93, ovarian cancer, recurrence, in vivo imaging, tumor burden, cancer stem cells, chemotherapy
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Method for Obtaining Primary Ovarian Cancer Cells From Solid Specimens
Authors: Lee J. Pribyl, Kathleen A. Coughlin, Thanasak Sueblinvong, Kristin Shields, Yoshie Iizuka, Levi S. Downs, Rahel G. Ghebre, Martina Bazzaro.
Institutions: University of Minnesota, Maricopa Medical Center and St Josephs Hospital and Medical Center, University of Minnesota.
Reliable tools for investigating ovarian cancer initiation and progression are urgently needed. While the use of ovarian cancer cell lines remains a valuable tool for understanding ovarian cancer, their use has many limitations. These include the lack of heterogeneity and the plethora of genetic alterations associated with extended in vitro passaging. Here we describe a method that allows for rapid establishment of primary ovarian cancer cells form solid clinical specimens collected at the time of surgery. The method consists of subjecting clinical specimens to enzymatic digestion for 30 min. The isolated cell suspension is allowed to grow and can be used for downstream application including drug screening. The advantage of primary ovarian cancer cell lines over established ovarian cancer cell lines is that they are representative of the original specific clinical specimens they are derived from and can be derived from different sites whether primary or metastatic ovarian cancer.
Medicine, Issue 84, Neoplasms, Ovarian Cancer, Primary cell lines, Clinical Specimens, Downstream Applications, Targeted Therapies, Epithelial Cultures
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Longitudinal Measurement of Extracellular Matrix Rigidity in 3D Tumor Models Using Particle-tracking Microrheology
Authors: Dustin P. Jones, William Hanna, Hamid El-Hamidi, Jonathan P. Celli.
Institutions: University of Massachusetts Boston.
The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and modified as part of a set of complex, two-way mechanosensitive interactions. While the development of biologically-relevant 3D tumor models have facilitated mechanistic studies on the impact of matrix rheology on tumor growth, the inverse problem of mapping changes in the mechanical environment induced by tumors remains challenging. Here, we describe the implementation of particle-tracking microrheology (PTM) in conjunction with 3D models of pancreatic cancer as part of a robust and viable approach for longitudinally monitoring physical changes in the tumor microenvironment, in situ. The methodology described here integrates a system of preparing in vitro 3D models embedded in a model extracellular matrix (ECM) scaffold of Type I collagen with fluorescently labeled probes uniformly distributed for position- and time-dependent microrheology measurements throughout the specimen. In vitro tumors are plated and probed in parallel conditions using multiwell imaging plates. Drawing on established methods, videos of tracer probe movements are transformed via the Generalized Stokes Einstein Relation (GSER) to report the complex frequency-dependent viscoelastic shear modulus, G*(ω). Because this approach is imaging-based, mechanical characterization is also mapped onto large transmitted-light spatial fields to simultaneously report qualitative changes in 3D tumor size and phenotype. Representative results showing contrasting mechanical response in sub-regions associated with localized invasion-induced matrix degradation as well as system calibration, validation data are presented. Undesirable outcomes from common experimental errors and troubleshooting of these issues are also presented. The 96-well 3D culture plating format implemented in this protocol is conducive to correlation of microrheology measurements with therapeutic screening assays or molecular imaging to gain new insights into impact of treatments or biochemical stimuli on the mechanical microenvironment.
Bioengineering, Issue 88, viscoelasticity, mechanobiology, extracellular matrix (ECM), matrix remodeling, 3D tumor models, tumor microenvironment, stroma, matrix metalloprotease (MMP), epithelial-mesenchymal transition (EMT)
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Adaptation of Semiautomated Circulating Tumor Cell (CTC) Assays for Clinical and Preclinical Research Applications
Authors: Lori E. Lowes, Benjamin D. Hedley, Michael Keeney, Alison L. Allan.
Institutions: London Health Sciences Centre, Western University, London Health Sciences Centre, Lawson Health Research Institute, Western University.
The majority of cancer-related deaths occur subsequent to the development of metastatic disease. This highly lethal disease stage is associated with the presence of circulating tumor cells (CTCs). These rare cells have been demonstrated to be of clinical significance in metastatic breast, prostate, and colorectal cancers. The current gold standard in clinical CTC detection and enumeration is the FDA-cleared CellSearch system (CSS). This manuscript outlines the standard protocol utilized by this platform as well as two additional adapted protocols that describe the detailed process of user-defined marker optimization for protein characterization of patient CTCs and a comparable protocol for CTC capture in very low volumes of blood, using standard CSS reagents, for studying in vivo preclinical mouse models of metastasis. In addition, differences in CTC quality between healthy donor blood spiked with cells from tissue culture versus patient blood samples are highlighted. Finally, several commonly discrepant items that can lead to CTC misclassification errors are outlined. Taken together, these protocols will provide a useful resource for users of this platform interested in preclinical and clinical research pertaining to metastasis and CTCs.
Medicine, Issue 84, Metastasis, circulating tumor cells (CTCs), CellSearch system, user defined marker characterization, in vivo, preclinical mouse model, clinical research
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In vivo Imaging and Therapeutic Treatments in an Orthotopic Mouse Model of Ovarian Cancer
Authors: Alexis B. Cordero, Youngjoo Kwon, Xiang Hua, Andrew K. Godwin.
Institutions: Women's Cancer Program, Fox Chase Cancer Center.
Human cancer and response to therapy is better represented in orthotopic animal models. This paper describes the development of an orthotopic mouse model of ovarian cancer, treatment of cancer via oral delivery of drugs, and monitoring of tumor cell behavior in response to drug treatment in real time using in vivo imaging system. In this orthotopic model, ovarian tumor cells expressing luciferase are applied topically by injecting them directly into the mouse bursa where each ovary is enclosed. Upon injection of D-luciferin, a substrate of firefly luciferase, luciferase-expressing cells generate bioluminescence signals. This signal is detected by the in vivo imaging system and allows for a non-invasive means of monitoring tumor growth, distribution, and regression in individual animals. Drug administration via oral gavage allows for a maximum dosing volume of 10 mL/kg body weight to be delivered directly to the stomach and closely resembles delivery of drugs in clinical treatments. Therefore, techniques described here, development of an orthotopic mouse model of ovarian cancer, oral delivery of drugs, and in vivo imaging, are useful for better understanding of human ovarian cancer and treatment and will improve targeting this disease.
Cellular Biology, Issue 42, Ovarian cancer, orthotopic mouse model, intrabursal injection, oral gavage, bioluminescence, in vivo imaging
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Heterotypic Three-dimensional In Vitro Modeling of Stromal-Epithelial Interactions During Ovarian Cancer Initiation and Progression
Authors: Kate Lawrenson, Barbara Grun, Simon A. Gayther.
Institutions: University of Southern California, University College London.
Epithelial ovarian cancers (EOCs) are the leading cause of death from gynecological malignancy in Western societies. Despite advances in surgical treatments and improved platinum-based chemotherapies, there has been little improvement in EOC survival rates for more than four decades 1,2. Whilst stage I tumors have 5-year survival rates >85%, survival rates for stage III/IV disease are <40%. Thus, the high rates of mortality for EOC could be significantly decreased if tumors were detected at earlier, more treatable, stages 3-5. At present, the molecular genetic and biological basis of early stage disease development is poorly understood. More specifically, little is known about the role of the microenvironment during tumor initiation; but known risk factors for EOCs (e.g. age and parity) suggest that the microenvironment plays a key role in the early genesis of EOCs. We therefore developed three-dimensional heterotypic models of both the normal ovary and of early stage ovarian cancers. For the normal ovary, we co-cultured normal ovarian surface epithelial (IOSE) and normal stromal fibroblast (INOF) cells, immortalized by retrovrial transduction of the catalytic subunit of human telomerase holoenzyme (hTERT) to extend the lifespan of these cells in culture. To model the earliest stages of ovarian epithelial cell transformation, overexpression of the CMYC oncogene in IOSE cells, again co-cultured with INOF cells. These heterotypic models were used to investigate the effects of aging and senescence on the transformation and invasion of epithelial cells. Here we describe the methodological steps in development of these three-dimensional model; these methodologies aren't specific to the development of normal ovary and ovarian cancer tissues, and could be used to study other tissue types where stromal and epithelial cell interactions are a fundamental aspect of the tissue maintenance and disease development.
Cancer Biology, Issue 66, Medicine, Tissue Engineering, three-dimensional cultures, stromal-epithelial interactions, epithelial ovarian cancer, ovarian surface epithelium, ovarian fibroblasts, tumor initiation
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Micropipette Aspiration of Substrate-attached Cells to Estimate Cell Stiffness
Authors: Myung-Jin Oh, Frank Kuhr, Fitzroy Byfield, Irena Levitan.
Institutions: University of Illinois, University of Pennsylvania .
Growing number of studies show that biomechanical properties of individual cells play major roles in multiple cellular functions, including cell proliferation, differentiation, migration and cell-cell interactions. The two key parameters of cellular biomechanics are cellular deformability or stiffness and the ability of the cells to contract and generate force. Here we describe a quick and simple method to estimate cell stiffness by measuring the degree of membrane deformation in response to negative pressure applied by a glass micropipette to the cell surface, a technique that is called Micropipette Aspiration or Microaspiration. Microaspiration is performed by pulling a glass capillary to create a micropipette with a very small tip (2-50 μm diameter depending on the size of a cell or a tissue sample), which is then connected to a pneumatic pressure transducer and brought to a close vicinity of a cell under a microscope. When the tip of the pipette touches a cell, a step of negative pressure is applied to the pipette by the pneumatic pressure transducer generating well-defined pressure on the cell membrane. In response to pressure, the membrane is aspirated into the pipette and progressive membrane deformation or "membrane projection" into the pipette is measured as a function of time. The basic principle of this experimental approach is that the degree of membrane deformation in response to a defined mechanical force is a function of membrane stiffness. The stiffer the membrane is, the slower the rate of membrane deformation and the shorter the steady-state aspiration length.The technique can be performed on isolated cells, both in suspension and substrate-attached, large organelles, and liposomes. Analysis is performed by comparing maximal membrane deformations achieved under a given pressure for different cell populations or experimental conditions. A "stiffness coefficient" is estimated by plotting the aspirated length of membrane deformation as a function of the applied pressure. Furthermore, the data can be further analyzed to estimate the Young's modulus of the cells (E), the most common parameter to characterize stiffness of materials. It is important to note that plasma membranes of eukaryotic cells can be viewed as a bi-component system where membrane lipid bilayer is underlied by the sub-membrane cytoskeleton and that it is the cytoskeleton that constitutes the mechanical scaffold of the membrane and dominates the deformability of the cellular envelope. This approach, therefore, allows probing the biomechanical properties of the sub-membrane cytoskeleton.
Bioengineering, Issue 67, Biophysics, Biomedical Engineering, Medicine, Cellular Biology, Cell stiffness, biomechanics, microaspiration, cell membrane, cytoskeleton
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Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Authors: Dana Faratian, Jason Christiansen, Mark Gustavson, Christine Jones, Christopher Scott, InHwa Um, David J. Harrison.
Institutions: University of Edinburgh, HistoRx Inc..
Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor1,2, and some of these sub-clones give rise to metastatic (and therefore lethal) disease. Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension3, or on macrodissection4. A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue5, providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ. We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system6. Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index7. To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.
Medicine, Issue 56, quantitative immunofluorescence, heterogeneity, cancer, biomarker, targeted therapy, immunohistochemistry, proteomics, histopathology
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An In Vitro System to Study Tumor Dormancy and the Switch to Metastatic Growth
Authors: Dalit Barkan, Jeffrey E. Green.
Institutions: University of Haifa, National Cancer Institute.
Recurrence of breast cancer often follows a long latent period in which there are no signs of cancer, and metastases may not become clinically apparent until many years after removal of the primary tumor and adjuvant therapy. A likely explanation of this phenomenon is that tumor cells have seeded metastatic sites, are resistant to conventional therapies, and remain dormant for long periods of time 1-4. The existence of dormant cancer cells at secondary sites has been described previously as quiescent solitary cells that neither proliferate nor undergo apoptosis 5-7. Moreover, these solitary cells has been shown to disseminate from the primary tumor at an early stage of disease progression 8-10 and reside growth-arrested in the patients' bone marrow, blood and lymph nodes 1,4,11. Therefore, understanding mechanisms that regulate dormancy or the switch to a proliferative state is critical for discovering novel targets and interventions to prevent disease recurrence. However, unraveling the mechanisms regulating the switch from tumor dormancy to metastatic growth has been hampered by the lack of available model systems. in vivo and ex vivo model systems to study metastatic progression of tumor cells have been described previously 1,12-14. However these model systems have not provided in real time and in a high throughput manner mechanistic insights into what triggers the emergence of solitary dormant tumor cells to proliferate as metastatic disease. We have recently developed a 3D in vitro system to model the in vivo growth characteristics of cells that exhibit either dormant (D2.OR, MCF7, K7M2-AS.46) or proliferative (D2A1, MDA-MB-231, K7M2) metastatic behavior in vivo . We demonstrated that tumor cells that exhibit dormancy in vivo at a metastatic site remain quiescent when cultured in a 3-dimension (3D) basement membrane extract (BME), whereas cells highly metastatic in vivo readily proliferate in 3D culture after variable, but relatively short periods of quiescence. Importantly by utilizing the 3D in vitro model system we demonstrated for the first time that the ECM composition plays an important role in regulating whether dormant tumor cells will switch to a proliferative state and have confirmed this in in vivo studies15-17. Hence, the model system described in this report provides an in vitro method to model tumor dormancy and study the transition to proliferative growth induced by the microenvironment.
Medicine, Issue 54, Tumor dormancy, cancer recurrence, metastasis, reconstituted basement membrane extract (BME), 3D culture, breast cancer
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A Real-time Electrical Impedance Based Technique to Measure Invasion of Endothelial Cell Monolayer by Cancer Cells
Authors: Said Rahim, Aykut Üren.
Institutions: Georgetown University.
Metastatic dissemination of malignant cells requires degradation of basement membrane, attachment of tumor cells to vascular endothelium, retraction of endothelial junctions and finally invasion and migration of tumor cells through the endothelial layer to enter the bloodstream as a means of transport to distant sites in the host1-3. Once in the circulatory system, cancer cells adhere to capillary walls and extravasate to the surrounding tissue to form metastatic tumors4,5. The various components of tumor cell-endothelial cell interaction can be replicated in vitro by challenging a monolayer of human umbilical vein endothelial cells (HUVEC) with cancer cells. Studies performed with electron and phase-contrast microscopy suggest that the in vitro sequence of events fairly represent the in vivo metastatic process6. Here, we describe an electrical-impedance based technique that monitors and quantifies in real-time the invasion of endothelial cells by malignant tumor cells. Giaever and Keese first described a technique for measuring fluctuations in impedance when a population of cells grow on the surface of electrodes7,8. The xCELLigence instrument, manufactured by Roche, utilizes a similar technique to measure changes in electrical impedance as cells attach and spread in a culture dish covered with a gold microelectrode array that covers approximately 80% of the area on the bottom of a well. As cells attach and spread on the electrode surface, it leads to an increase in electrical impedance9-12. The impedance is displayed as a dimensionless parameter termed cell-index, which is directly proportional to the total area of tissue-culture well that is covered by cells. Hence, the cell-index can be used to monitor cell adhesion, spreading, morphology and cell density. The invasion assay described in this article is based on changes in electrical impedance at the electrode/cell interphase, as a population of malignant cells invade through a HUVEC monolayer (Figure 1). The disruption of endothelial junctions, retraction of endothelial monolayer and replacement by tumor cells lead to large changes in impedance. These changes directly correlate with the invasive capacity of tumor cells, i.e., invasion by highly aggressive cells lead to large changes in cell impedance and vice versa. This technique provides a two-fold advantage over existing methods of measuring invasion, such as boyden chamber and matrigel assays: 1) the endothelial cell-tumor cell interaction more closely mimics the in vivo process, and 2) the data is obtained in real-time and is more easily quantifiable, as opposed to end-point analysis for other methods.
Cellular Biology, Issue 50, Invasion, HUVEC, xCELLigence, impedance, real-time, cell-index
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An Orthotopic Model of Serous Ovarian Cancer in Immunocompetent Mice for in vivo Tumor Imaging and Monitoring of Tumor Immune Responses
Authors: Selene Nunez-Cruz, Denise C. Connolly, Nathalie Scholler.
Institutions: University of Pennsylvania-School of Medicine, Fox Chase Cancer Center.
Background: Ovarian cancer is generally diagnosed at an advanced stage where the case/fatality ratio is high and thus remains the most lethal of all gynecologic malignancies among US women 1,2,3. Serous tumors are the most widespread forms of ovarian cancer and 4,5 the Tg-MISIIR-TAg transgenic represents the only mouse model that spontaneously develops this type of tumors. Tg-MISIIR-TAg mice express SV40 transforming region under control of the Mullerian Inhibitory Substance type II Receptor (MISIIR) gene promoter 6. Additional transgenic lines have been identified that express the SV40 TAg transgene, but do not develop ovarian tumors. Non-tumor prone mice exhibit typical lifespan for C57Bl/6 mice and are fertile. These mice can be used as syngeneic allograft recipients for tumor cells isolated from Tg-MISIIR-TAg-DR26 mice. Objective: Although tumor imaging is possible 7, early detection of deep tumors is challenging in small living animals. To enable preclinical studies in an immunologically intact animal model for serous ovarian cancer, we describe a syngeneic mouse model for this type of ovarian cancer that permits in vivo imaging, studies of the tumor microenvironment and tumor immune responses. Methods: We first derived a TAg+ mouse cancer cell line (MOV1) from a spontaneous ovarian tumor harvested in a 26 week-old DR26 Tg-MISIIR-TAg female. Then, we stably transduced MOV1 cells with TurboFP635 Lentivirus mammalian vector that encodes Katushka, a far-red mutant of the red fluorescent protein from sea anemone Entacmaea quadricolor with excitation/emission maxima at 588/635 nm 8,9,10. We orthotopically implanted MOV1Kat in the ovary 11,12,13,14 of non-tumor prone Tg-MISIIR-TAg female mice. Tumor progression was followed by in vivo optical imaging and tumor microenvironment was analyzed by immunohistochemistry. Results: Orthotopically implanted MOV1Kat cells developed serous ovarian tumors. MOV1Kat tumors could be visualized by in vivo imaging up to three weeks after implantation (fig. 1) and were infiltrated with leukocytes, as observed in human ovarian cancers 15 (fig. 2). Conclusions: We describe an orthotopic model of ovarian cancer suitable for in vivo imaging of early tumors due to the high pH-stability and photostability of Katushka in deep tissues. We propose the use of this novel syngeneic model of serous ovarian cancer for in vivo imaging studies and monitoring of tumor immune responses and immunotherapies.
Immunology, Issue 45, Ovarian cancer, syngeneic, orthotopic, katushka (TurboFP635), in vivo imaging, immunocompetent mouse model of ovarian cancer, deep tumors
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Ex Vivo Treatment Response of Primary Tumors and/or Associated Metastases for Preclinical and Clinical Development of Therapeutics
Authors: Adriana D. Corben, Mohammad M. Uddin, Brooke Crawford, Mohammad Farooq, Shanu Modi, John Gerecitano, Gabriela Chiosis, Mary L. Alpaugh.
Institutions: Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center.
The molecular analysis of established cancer cell lines has been the mainstay of cancer research for the past several decades. Cell culture provides both direct and rapid analysis of therapeutic sensitivity and resistance. However, recent evidence suggests that therapeutic response is not exclusive to the inherent molecular composition of cancer cells but rather is greatly influenced by the tumor cell microenvironment, a feature that cannot be recapitulated by traditional culturing methods. Even implementation of tumor xenografts, though providing a wealth of information on drug delivery/efficacy, cannot capture the tumor cell/microenvironment crosstalk (i.e., soluble factors) that occurs within human tumors and greatly impacts tumor response. To this extent, we have developed an ex vivo (fresh tissue sectioning) technique which allows for the direct assessment of treatment response for preclinical and clinical therapeutics development. This technique maintains tissue integrity and cellular architecture within the tumor cell/microenvironment context throughout treatment response providing a more precise means to assess drug efficacy.
Cancer Biology, Issue 92, Ex vivo sectioning, Treatment response, Sensitivity/Resistance, Drug development, Patient tumors, Preclinical and Clinical
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.