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.
21 Related JoVE Articles!
Method for Obtaining Primary Ovarian Cancer Cells From Solid Specimens
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
An Orthotopic Model of Serous Ovarian Cancer in Immunocompetent Mice for in vivo Tumor Imaging and Monitoring of Tumor Immune Responses
Institutions: University of Pennsylvania-School of Medicine, Fox Chase Cancer Center.
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.
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.
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.
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
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
One-step Metabolomics: Carbohydrates, Organic and Amino Acids Quantified in a Single Procedure
Institutions: Saint Louis University School of Medicine.
Every infant born in the US is now screened for up to 42 rare genetic disorders called "inborn errors of metabolism". The screening method is based on tandem mass spectrometry and quantifies acylcarnitines as a screen for organic acidemias and also measures amino acids. All states also perform enzymatic testing for carbohydrate disorders such as galactosemia. Because the results can be non-specific, follow-up testing of positive results is required using a more definitive method. The present report describes the "urease" method of sample preparation for inborn error screening. Crystalline urease enzyme is used to remove urea from body fluids which permits most other water-soluble metabolites to be dehydrated and derivatized for gas chromatography in a single procedure. Dehydration by evaporation in a nitrogen stream is facilitated by adding acetonitrile and methylene chloride. Then, trimethylsilylation takes place in the presence of a unique catalyst, triethylammonium trifluoroacetate. Automated injection and chromatography is followed by macro-driven custom quantification of 192 metabolites and semi-quantification of every major component using specialized libraries of mass spectra of TMS derivatized biological compounds. The analysis may be performed on the widely-used Chemstation platform using the macros and libraries available from the author. In our laboratory, over 16,000 patient samples have been analyzed using the method with a diagnostic yield of about 17%--that is, 17% of the samples results reveal findings that should be acted upon by the ordering physician. Included in these are over 180 confirmed inborn errors, of which about 38% could not have been diagnosed using previous methods.
Biochemistry, Issue 40, metabolomics, gas chromatography/mass spectrometry, GC/MS, inborn errors, vitamin deficiency, BNA analyses, carbohydrate, amino acid, organic acid, urease
Enrichment for Chemoresistant Ovarian Cancer Stem Cells from Human Cell Lines
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
Assessment of Ovarian Cancer Spheroid Attachment and Invasion of Mesothelial Cells in Real Time
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
An Orthotopic Murine Model of Human Prostate Cancer Metastasis
Institutions: Northwestern University, Northwestern University, Northwestern University.
Our laboratory has developed a novel orthotopic implantation model of human prostate cancer (PCa). As PCa death is not due to the primary tumor, but rather the formation of distinct metastasis, the ability to effectively model this progression pre-clinically is of high value. In this model, cells are directly implanted into the ventral lobe of the prostate in Balb/c athymic mice, and allowed to progress for 4-6 weeks. At experiment termination, several distinct endpoints can be measured, such as size and molecular characterization of the primary tumor, the presence and quantification of circulating tumor cells in the blood and bone marrow, and formation of metastasis to the lung. In addition to a variety of endpoints, this model provides a picture of a cells ability to invade and escape the primary organ, enter and survive in the circulatory system, and implant and grow in a secondary site. This model has been used effectively to measure metastatic response to both changes in protein expression as well as to response to small molecule therapeutics, in a short turnaround time.
Medicine, Issue 79, Urogenital System, Male Urogenital Diseases, Surgical Procedures, Operative, Life Sciences (General), Prostate Cancer, Metastasis, Mouse Model, Drug Discovery, Molecular Biology
Ex Vivo Treatment Response of Primary Tumors and/or Associated Metastases for Preclinical and Clinical Development of Therapeutics
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
Adaptation of Semiautomated Circulating Tumor Cell (CTC) Assays for Clinical and Preclinical Research Applications
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
In vitro Mesothelial Clearance Assay that Models the Early Steps of Ovarian Cancer Metastasis
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
Dithranol as a Matrix for Matrix Assisted Laser Desorption/Ionization Imaging on a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer
Institutions: University of Victoria, University of Victoria.
Mass spectrometry imaging (MSI) determines the spatial localization and distribution patterns of compounds on the surface of a tissue section, mainly using MALDI (matrix assisted laser desorption/ionization)-based analytical techniques. New matrices for small-molecule MSI, which can improve the analysis of low-molecular weight (MW) compounds, are needed. These matrices should provide increased analyte signals while decreasing MALDI background signals. In addition, the use of ultrahigh-resolution instruments, such as Fourier transform ion cyclotron resonance (FTICR) mass spectrometers, has the ability to resolve analyte signals from matrix signals, and this can partially overcome many problems associated with the background originating from the MALDI matrix. The reduction in the intensities of the metastable matrix clusters by FTICR MS can also help to overcome some of the interferences associated with matrix peaks on other instruments. High-resolution instruments such as the FTICR mass spectrometers are advantageous as they can produce distribution patterns of many compounds simultaneously while still providing confidence in chemical identifications. Dithranol (DT; 1,8-dihydroxy-9,10-dihydroanthracen-9-one) has previously been reported as a MALDI matrix for tissue imaging. In this work, a protocol for the use of DT for MALDI imaging of endogenous lipids from the surfaces of mammalian tissue sections, by positive-ion MALDI-MS, on an ultrahigh-resolution hybrid quadrupole FTICR instrument has been provided.
Basic Protocol, Issue 81, eye, molecular imaging, chemistry technique, analytical, mass spectrometry, matrix assisted laser desorption/ionization (MALDI), tandem mass spectrometry, lipid, tissue imaging, bovine lens, dithranol, matrix, FTICR (Fourier Transform Ion Cyclotron Resonance)
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Institutions: Princeton University.
The aim of de novo
protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo
protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity.
To disseminate these methods for broader use we present Protein WISDOM (https://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
Institutions: Colorado State University.
Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to investigate metabolism. The approach offers an unbiased and in-depth analysis that can enable the development of diagnostic tests, novel therapies, and further our understanding of disease processes. The inherent chemical diversity of the metabolome creates significant analytical challenges and there is no single experimental approach that can detect all metabolites. Additionally, the biological variation in individual metabolism and the dependence of metabolism on environmental factors necessitates large sample numbers to achieve the appropriate statistical power required for meaningful biological interpretation. To address these challenges, this tutorial outlines an analytical workflow for large scale non-targeted metabolite profiling of serum by UPLC-MS. The procedure includes guidelines for sample organization and preparation, data acquisition, quality control, and metabolite identification and will enable reliable acquisition of data for large experiments and provide a starting point for laboratories new to non-targeted metabolite profiling by UPLC-MS.
Chemistry, Issue 73, Biochemistry, Genetics, Molecular Biology, Physiology, Genomics, Proteins, Proteomics, Metabolomics, Metabolite Profiling, Non-targeted metabolite profiling, mass spectrometry, Ultra Performance Liquid Chromatography, UPLC-MS, serum, spectrometry
Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)
Institutions: University of Pennsylvania .
Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first separated into polar and non-polar fractions by a liquid-liquid phase extraction, and partially purified to facilitate downstream analysis. Both aqueous (polar metabolites) and organic (non-polar metabolites) phases of the initial extraction are processed to survey a broad range of metabolites. Metabolites are separated by different liquid chromatography methods based upon their partition properties. In this method, we present microflow ultra-performance (UP)LC methods, but the protocol is scalable to higher flows and lower pressures. Introduction into the mass spectrometer can be through either general or compound optimized source conditions. Detection of a broad range of ions is carried out in full scan mode in both positive and negative mode over a broad m/z
range using high resolution on a recently calibrated instrument. Label-free differential analysis is carried out on bioinformatics platforms. Applications of this approach include metabolic pathway screening, biomarker discovery, and drug development.
Biochemistry, Issue 75, Chemistry, Molecular Biology, Cellular Biology, Physiology, Medicine, Pharmacology, Genetics, Genomics, Mass Spectrometry, MS, Metabolism, Metabolomics, untargeted, extraction, lipids, accurate mass, liquid chromatography, ultraperformance liquid chromatography, UPLC, high resolution mass spectrometry, HRMS, spectrometry
Alginate Hydrogels for Three-Dimensional Organ Culture of Ovaries and Oviducts
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
In vivo Imaging and Therapeutic Treatments in an Orthotopic Mouse Model of Ovarian Cancer
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
Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
Institutions: National Jewish Health, University of Colorado Denver.
Metabolomics is an emerging field which enables profiling of samples from living organisms in order to obtain insight into biological processes. A vital aspect of metabolomics is sample preparation whereby inconsistent techniques generate unreliable results. This technique encompasses protein precipitation, liquid-liquid extraction, and solid-phase extraction as a means of fractionating metabolites into four distinct classes. Improved enrichment of low abundance molecules with a resulting increase in sensitivity is obtained, and ultimately results in more confident identification of molecules. This technique has been applied to plasma, bronchoalveolar lavage fluid, and cerebrospinal fluid samples with volumes as low as 50 µl. Samples can be used for multiple downstream applications; for example, the pellet resulting from protein precipitation can be stored for later analysis. The supernatant from that step undergoes liquid-liquid extraction using water and strong organic solvent to separate the hydrophilic and hydrophobic compounds. Once fractionated, the hydrophilic layer can be processed for later analysis or discarded if not needed. The hydrophobic fraction is further treated with a series of solvents during three solid-phase extraction steps to separate it into fatty acids, neutral lipids, and phospholipids. This allows the technician the flexibility to choose which class of compounds is preferred for analysis. It also aids in more reliable metabolite identification since some knowledge of chemical class exists.
Bioengineering, Issue 89, plasma, chemistry techniques, analytical, solid phase extraction, mass spectrometry, metabolomics, fluids and secretions, profiling, small molecules, lipids, liquid chromatography, liquid-liquid extraction, cerebrospinal fluid, bronchoalveolar lavage fluid
A Strategy for Sensitive, Large Scale Quantitative Metabolomics
Institutions: Cornell University, Cornell University.
Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously. Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases.
Chemistry, Issue 87, high-resolution mass spectrometry, metabolomics, positive/negative switching, low mass calibration, Orbitrap
The ChroP Approach Combines ChIP and Mass Spectrometry to Dissect Locus-specific Proteomic Landscapes of Chromatin
Institutions: European Institute of Oncology.
Chromatin is a highly dynamic nucleoprotein complex made of DNA and proteins that controls various DNA-dependent processes. Chromatin structure and function at specific regions is regulated by the local enrichment of histone post-translational modifications (hPTMs) and variants, chromatin-binding proteins, including transcription factors, and DNA methylation. The proteomic characterization of chromatin composition at distinct functional regions has been so far hampered by the lack of efficient protocols to enrich such domains at the appropriate purity and amount for the subsequent in-depth analysis by Mass Spectrometry (MS). We describe here a newly designed chromatin proteomics strategy, named ChroP (Chromatin Proteomics
), whereby a preparative chromatin immunoprecipitation is used to isolate distinct chromatin regions whose features, in terms of hPTMs, variants and co-associated non-histonic proteins, are analyzed by MS. We illustrate here the setting up of ChroP for the enrichment and analysis of transcriptionally silent heterochromatic regions, marked by the presence of tri-methylation of lysine 9 on histone H3. The results achieved demonstrate the potential of ChroP
in thoroughly characterizing the heterochromatin proteome and prove it as a powerful analytical strategy for understanding how the distinct protein determinants of chromatin interact and synergize to establish locus-specific structural and functional configurations.
Biochemistry, Issue 86, chromatin, histone post-translational modifications (hPTMs), epigenetics, mass spectrometry, proteomics, SILAC, chromatin immunoprecipitation , histone variants, chromatome, hPTMs cross-talks
Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts
Institutions: Aix-Marseille Université, Aix-Marseille Université.
Studies of gene expression on the RNA and protein levels have long been used to explore biological processes underlying disease. More recently, genomics and proteomics have been complemented by comprehensive quantitative analysis of the metabolite pool present in biological systems. This strategy, termed metabolomics, strives to provide a global characterization of the small-molecule complement involved in metabolism. While the genome and the proteome define the tasks cells can perform, the metabolome is part of the actual phenotype. Among the methods currently used in metabolomics, spectroscopic techniques are of special interest because they allow one to simultaneously analyze a large number of metabolites without prior selection for specific biochemical pathways, thus enabling a broad unbiased approach. Here, an optimized experimental protocol for metabolomic analysis by high-resolution NMR spectroscopy is presented, which is the method of choice for efficient quantification of tissue metabolites. Important strengths of this method are (i) the use of crude extracts, without the need to purify the sample and/or separate metabolites; (ii) the intrinsically quantitative nature of NMR, permitting quantitation of all metabolites represented by an NMR spectrum with one reference compound only; and (iii) the nondestructive nature of NMR enabling repeated use of the same sample for multiple measurements. The dynamic range of metabolite concentrations that can be covered is considerable due to the linear response of NMR signals, although metabolites occurring at extremely low concentrations may be difficult to detect. For the least abundant compounds, the highly sensitive mass spectrometry method may be advantageous although this technique requires more intricate sample preparation and quantification procedures than NMR spectroscopy. We present here an NMR protocol adjusted to rat brain analysis; however, the same protocol can be applied to other tissues with minor modifications.
Neuroscience, Issue 91, metabolomics, brain tissue, rodents, neurochemistry, tissue extracts, NMR spectroscopy, quantitative metabolite analysis, cerebral metabolism, metabolic profile
Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
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
Dissection of Drosophila Ovaries
Institutions: Princeton University.
Neuroscience, Issue 1, Protocol, Stem Cells, Cerebral Cortex, Brain Development, Electroporation, Intra Uterine Injections, transfection