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Development and preliminary evaluation of a multivariate index assay for ovarian cancer.
PUBLISHED: 01-14-2009
Most women with a clinical presentation consistent with ovarian cancer have benign conditions. Therefore methods to distinguish women with ovarian cancer from those with benign conditions would be beneficial. We describe the development and preliminary evaluation of a serum-based multivariate assay for ovarian cancer. This hypothesis-driven study examined whether an informative pattern could be detected in stage I disease that persists through later stages.
Authors: Lee J. Pribyl, Kathleen A. Coughlin, Thanasak Sueblinvong, Kristin Shields, Yoshie Iizuka, Levi S. Downs, Rahel G. Ghebre, Martina Bazzaro.
Published: 02-04-2014
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.
19 Related JoVE Articles!
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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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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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The In ovo CAM-assay as a Xenograft Model for Sarcoma
Authors: Gwen M.L. Sys, Lore Lapeire, Nikita Stevens, Herman Favoreel, Ramses Forsyth, Marc Bracke, Olivier De Wever.
Institutions: Ghent University Hospital, Ghent University, Ghent University, Pathlicon.
Sarcoma is a very rare disease that is heterogeneous in nature, all hampering the development of new therapies. Sarcoma patients are ideal candidates for personalized medicine after stratification, explaining the current interest in developing a reproducible and low-cost xenotransplant model for this disease. The chick chorioallantoic membrane is a natural immunodeficient host capable of sustaining grafted tissues and cells without species-specific restrictions. In addition, it is easily accessed, manipulated and imaged using optical and fluorescence stereomicroscopy. Histology further allows detailed analysis of heterotypic cellular interactions. This protocol describes in detail the in ovo grafting of the chorioallantoic membrane with fresh sarcoma-derived tumor tissues, their single cell suspensions, and permanent and transient fluorescently labeled established sarcoma cell lines (Saos-2 and SW1353). The chick survival rates are up to 75%. The model is used to study graft- (viability, Ki67 proliferation index, necrosis, infiltration) and host (fibroblast infiltration, vascular ingrowth) behavior. For localized grafting of single cell suspensions, ECM gel provides significant advantages over inert containment materials. The Ki67 proliferation index is related to the distance of the cells from the surface of the CAM and the duration of application on the CAM, the latter determining a time frame for the addition of therapeutic products.
Cancer Biology, Issue 77, Medicine, Cellular Biology, Molecular Biology, Biomedical Engineering, Bioengineering, Developmental Biology, Anatomy, Physiology, Oncology, Surgery, Adipose Tissue, Connective Tissue, Neoplasm, Muscle Tissue, Sarcoma, Animal Experimentation, Cell Culture Techniques, Neoplasms, Experimental, Neoplasm Transplantation, Biological Assay, Sarcomas, CAM-assay, CAM, assay, xenograft, proliferation, invasion, cancer, tumor, in ovo, animal model
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
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Alginate Hydrogels for Three-Dimensional Organ Culture of Ovaries and Oviducts
Authors: Shelby M. King, Suzanne Quartuccio, Tyvette S. Hilliard, Kari Inoue, Joanna E. Burdette.
Institutions: University of Illinois at Chicago.
Ovarian cancer is the fifth leading cause of cancer deaths in women and has a 63% mortality rate in the United States1. The cell type of origin for ovarian cancers is still in question and might be either the ovarian surface epithelium (OSE) or the distal epithelium of the fallopian tube fimbriae2,3. Culturing the normal cells as a primary culture in vitro will enable scientists to model specific changes that might lead to ovarian cancer in the distinct epithelium, thereby definitively determining the cell type of origin. This will allow development of more accurate biomarkers, animal models with tissue-specific gene changes, and better prevention strategies targeted to this disease. Maintaining normal cells in alginate hydrogels promotes short term in vitro culture of cells in their three-dimensional context and permits introduction of plasmid DNA, siRNA, and small molecules. By culturing organs in pieces that are derived from strategic cuts using a scalpel, several cultures from a single organ can be generated, increasing the number of experiments from a single animal. These cuts model aspects of ovulation leading to proliferation of the OSE, which is associated with ovarian cancer formation. Cell types such as the OSE that do not grow well on plastic surfaces can be cultured using this method and facilitate investigation into normal cellular processes or the earliest events in cancer formation4. Alginate hydrogels can be used to support the growth of many types of tissues5. Alginate is a linear polysaccharide composed of repeating units of β-D-mannuronic acid and α-L-guluronic acid that can be crosslinked with calcium ions, resulting in a gentle gelling action that does not damage tissues6,7. Like other three-dimensional cell culture matrices such as Matrigel, alginate provides mechanical support for tissues; however, proteins are not reactive with the alginate matrix, and therefore alginate functions as a synthetic extracellular matrix that does not initiate cell signaling5. The alginate hydrogel floats in standard cell culture medium and supports the architecture of the tissue growth in vitro. A method is presented for the preparation, separation, and embedding of ovarian and oviductal organ pieces into alginate hydrogels, which can be maintained in culture for up to two weeks. The enzymatic release of cells for analysis of proteins and RNA samples from the organ culture is also described. Finally, the growth of primary cell types is possible without genetic immortalization from mice and permits investigators to use knockout and transgenic mice.
Bioengineering, Issue 52, alginate hydrogel, ovarian organ culture, oviductal organ culture, three-dimensional, primary cell
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Ex Vivo Culture of Primary Human Fallopian Tube Epithelial Cells
Authors: Susan Fotheringham, Keren Levanon, Ronny Drapkin.
Institutions: Dana-Farber Cancer Institute, Boston, MA, Chaim Sheba Medical Center, Brigham and Women's Hospital.
Epithelial ovarian cancer is a leading cause of female cancer mortality in the United States. In contrast to other women-specific cancers, like breast and uterine carcinomas, where death rates have fallen in recent years, ovarian cancer cure rates have remained relatively unchanged over the past two decades 1. This is largely due to the lack of appropriate screening tools for detection of early stage disease where surgery and chemotherapy are most effective 2, 3. As a result, most patients present with advanced stage disease and diffuse abdominal involvement. This is further complicated by the fact that ovarian cancer is a heterogeneous disease with multiple histologic subtypes 4, 5. Serous ovarian carcinoma (SOC) is the most common and aggressive subtype and the form most often associated with mutations in the BRCA genes. Current experimental models in this field involve the use of cancer cell lines and mouse models to better understand the initiating genetic events and pathogenesis of disease 6, 7. Recently, the fallopian tube has emerged as a novel site for the origin of SOC, with the fallopian tube (FT) secretory epithelial cell (FTSEC) as the proposed cell of origin 8, 9. There are currently no cell lines or culture systems available to study the FT epithelium or the FTSEC. Here we describe a novel ex vivo culture system where primary human FT epithelial cells are cultured in a manner that preserves their architecture, polarity, immunophenotype, and response to physiologic and genotoxic stressors. This ex vivo model provides a useful tool for the study of SOC, allowing a better understanding of how tumors can arise from this tissue, and the mechanisms involved in tumor initiation and progression.
Cellular Biology, Issue 51, Primary human epithelial cells, ovarian cancer, serous, ex-vivo, cell biology, fallopian tube, fimbria
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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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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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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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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
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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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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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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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Therapeutic Gene Delivery and Transfection in Human Pancreatic Cancer Cells using Epidermal Growth Factor Receptor-targeted Gelatin Nanoparticles
Authors: Jing Xu, Mansoor Amiji.
Institutions: Northeastern University.
More than 32,000 patients are diagnosed with pancreatic cancer in the United States per year and the disease is associated with very high mortality 1. Urgent need exists to develop novel clinically-translatable therapeutic strategies that can improve on the dismal survival statistics of pancreatic cancer patients. Although gene therapy in cancer has shown a tremendous promise, the major challenge is in the development of safe and effective delivery system, which can lead to sustained transgene expression. Gelatin is one of the most versatile natural biopolymer, widely used in food and pharmaceutical products. Previous studies from our laboratory have shown that type B gelatin could physical encapsulate DNA, which preserved the supercoiled structure of the plasmid and improved transfection efficiency upon intracellular delivery. By thiolation of gelatin, the sulfhydryl groups could be introduced into the polymer and would form disulfide bond within nanoparticles, which stabilizes the whole complex and once disulfide bond is broken due to the presence of glutathione in cytosol, payload would be released 2-5. Poly(ethylene glycol) (PEG)-modified GENS, when administered into the systemic circulation, provides long-circulation times and preferentially targets to the tumor mass due to the hyper-permeability of the neovasculature by the enhanced permeability and retention effect 6. Studies have shown over-expression of the epidermal growth factor receptor (EGFR) on Panc-1 human pancreatic adenocarcinoma cells 7. In order to actively target pancreatic cancer cell line, EGFR specific peptide was conjugated on the particle surface through a PEG spacer.8 Most anti-tumor gene therapies are focused on administration of the tumor suppressor genes, such as wild-type p53 (wt-p53), to restore the pro-apoptotic function in the cells 9. The p53 mechanism functions as a critical signaling pathway in cell growth, which regulates apoptosis, cell cycle arrest, metabolism and other processes 10. In pancreatic cancer, most cells have mutations in p53 protein, causing the loss of apoptotic activity. With the introduction of wt-p53, the apoptosis could be repaired and further triggers cell death in cancer cells 11. Based on the above rationale, we have designed EGFR targeting peptide-modified thiolated gelatin nanoparticles for wt-p53 gene delivery and evaluated delivery efficiency and transfection in Panc-1 cells.
Bioengineering, Issue 59, Gelatin Nanoparticle, Gene Therapy, Targeted Delivery, Pancreatic Cancer, Epidermal Growth Factor Receptor, EGFR
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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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Initiation of Metastatic Breast Carcinoma by Targeting of the Ductal Epithelium with Adenovirus-Cre: A Novel Transgenic Mouse Model of Breast Cancer
Authors: Melanie R. Rutkowski, Michael J. Allegrezza, Nikolaos Svoronos, Amelia J. Tesone, Tom L. Stephen, Alfredo Perales-Puchalt, Jenny Nguyen, Paul J. Zhang, Steven N. Fiering, Julia Tchou, Jose R. Conejo-Garcia.
Institutions: Wistar Institute, University of Pennsylvania, Geisel School of Medicine at Dartmouth, University of Pennsylvania, University of Pennsylvania, University of Pennsylvania.
Breast cancer is a heterogeneous disease involving complex cellular interactions between the developing tumor and immune system, eventually resulting in exponential tumor growth and metastasis to distal tissues and the collapse of anti-tumor immunity. Many useful animal models exist to study breast cancer, but none completely recapitulate the disease progression that occurs in humans. In order to gain a better understanding of the cellular interactions that result in the formation of latent metastasis and decreased survival, we have generated an inducible transgenic mouse model of YFP-expressing ductal carcinoma that develops after sexual maturity in immune-competent mice and is driven by consistent, endocrine-independent oncogene expression. Activation of YFP, ablation of p53, and expression of an oncogenic form of K-ras was achieved by the delivery of an adenovirus expressing Cre-recombinase into the mammary duct of sexually mature, virgin female mice. Tumors begin to appear 6 weeks after the initiation of oncogenic events. After tumors become apparent, they progress slowly for approximately two weeks before they begin to grow exponentially. After 7-8 weeks post-adenovirus injection, vasculature is observed connecting the tumor mass to distal lymph nodes, with eventual lymphovascular invasion of YFP+ tumor cells to the distal axillary lymph nodes. Infiltrating leukocyte populations are similar to those found in human breast carcinomas, including the presence of αβ and γδ T cells, macrophages and MDSCs. This unique model will facilitate the study of cellular and immunological mechanisms involved in latent metastasis and dormancy in addition to being useful for designing novel immunotherapeutic interventions to treat invasive breast cancer.
Medicine, Issue 85, Transgenic mice, breast cancer, metastasis, intraductal injection, latent mutations, adenovirus-Cre
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Experimental Approaches to Tissue Engineering
Authors: Ali Khademhosseini.
Institutions: Brigham and Women's Hospital.
Issue 7, Cell Biology, tissue engineering, microfluidics, stem cells
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Using Micro-Electro-Mechanical Systems (MEMS) to Develop Diagnostic Tools
Authors: Utkan Demirci.
Institutions: Brigham and Women's Hospital.
Cellular Biology, Issue 8, microfluidics, diagnostics, capture, blood, HIV, bioengineering
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Interview: Glycolipid Antigen Presentation by CD1d and the Therapeutic Potential of NKT cell Activation
Authors: Mitchell Kronenberg.
Institutions: La Jolla Institute for Allergy and Immunology.
Natural Killer T cells (NKT) are critical determinants of the immune response to cancer, regulation of autioimmune disease, clearance of infectious agents, and the development of artheriosclerotic plaques. In this interview, Mitch Kronenberg discusses his laboratory's efforts to understand the mechanism through which NKT cells are activated by glycolipid antigens. Central to these studies is CD1d - the antigen presenting molecule that presents glycolipids to NKT cells. The advent of CD1d tetramer technology, a technique developed by the Kronenberg lab, is critical for the sorting and identification of subsets of specific glycolipid-reactive T cells. Mitch explains how glycolipid agonists are being used as therapeutic agents to activate NKT cells in cancer patients and how CD1d tetramers can be used to assess the state of the NKT cell population in vivo following glycolipid agonist therapy. Current status of ongoing clinical trials using these agonists are discussed as well as Mitch's prediction for areas in the field of immunology that will have emerging importance in the near future.
Immunology, Issue 10, Natural Killer T cells, NKT cells, CD1 Tetramers, antigen presentation, glycolipid antigens, CD1d, Mucosal Immunity, Translational Research
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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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.