In this study, we describe an effective protocol for use in a multiplexed high-throughput antibody microarray with glycan binding protein detection that allows for the glycosylation profiling of specific proteins. Glycosylation of proteins is the most prevalent post-translational modification found on proteins, and leads diversified modifications of the physical, chemical, and biological properties of proteins. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases. However, current methods to study protein glycosylation typically are too complicated or expensive for use in most normal laboratory or clinical settings and a more practical method to study protein glycosylation is needed. The new protocol described in this study makes use of a chemically blocked antibody microarray with glycan-binding protein (GBP) detection and significantly reduces the time, cost, and lab equipment requirements needed to study protein glycosylation. In this method, multiple immobilized glycoprotein-specific antibodies are printed directly onto the microarray slides and the N-glycans on the antibodies are blocked. The blocked, immobilized glycoprotein-specific antibodies are able to capture and isolate glycoproteins from a complex sample that is applied directly onto the microarray slides. Glycan detection then can be performed by the application of biotinylated lectins and other GBPs to the microarray slide, while binding levels can be determined using Dylight 549-Streptavidin. Through the use of an antibody panel and probing with multiple biotinylated lectins, this method allows for an effective glycosylation profile of the different proteins found in a given human or animal sample to be developed.
Glycosylation of protein, which is the most ubiquitous post-translational modification on proteins, modifies the physical, chemical, and biological properties of a protein, and plays a fundamental role in various biological processes1-6. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases 7-12. In fact, most current cancer biomarkers, such as the L3 fraction of α-1 fetoprotein (AFP) for hepatocellular carcinoma 13-15, and CA199 for pancreatic cancer 16, 17 are all aberrant glycan moieties on glycoproteins. However, methods to study protein glycosylation have been complicated, and not suitable for routine laboratory and clinical settings. Chen et al. has recently invented a chemically blocked antibody microarray with a glycan-binding protein (GBP) detection method for high-throughput and multiplexed profile glycosylation of native glycoproteins in a complex sample 18. In this affinity based microarray method, multiple immobilized glycoprotein-specific antibodies capture and isolate glycoproteins from the complex mixture directly on the microarray slide, and the glycans on each individual captured protein are measured by GBPs. Because all normal antibodies contain N-glycans which could be recognized by most GBPs, the critical step of this method is to chemically block the glycans on the antibodies from binding to GBP. In the procedure, the cis-diol groups of the glycans on the antibodies were first oxidized to aldehyde groups by using NaIO4 in sodium acetate buffer avoiding light. The aldehyde groups were then conjugated to the hydrazide group of a cross-linker, 4-(4-N-MaleimidoPhenyl)butyric acid Hydrazide HCl (MPBH), followed by the conjugation of a dipeptide, Cys-Gly, to the maleimide group of the MPBH. Thus, the cis-diol groups on glycans of antibodies were converted into bulky none hydroxyl groups, which hindered the lectins and other GBPs bindings to the capture antibodies. This blocking procedure makes the GBPs and lectins bind only to the glycans of captured proteins. After this chemically blocking, serum samples were incubated with the antibody microarray, followed by the glycans detection by using different biotinylated lectins and GBPs, and visualized with Cy3-streptavidin. The parallel use of an antibody panel and multiple lectin probing provides discrete glycosylation profiles of multiple proteins in a given sample 18-20. This method has been used successfully in multiple different labs 1, 7, 13, 19-31. However, stability of MPBH and Cys-Gly, complicated and extended procedure in this method affect the reproducibility, effectiveness and efficiency of the method. In this new protocol, we replaced both MPBH and Cys-Gly with one much more stable reagent glutamic acid hydrazide (Glu-hydrazide), which significantly improved the reproducibility of the method, simplified and shorten the whole procedure so that the it can be completed within one working day. In this new protocol, we describe the detailed procedure of the protocol which can be readily adopted by normal labs for routine protein glycosylation study and techniques which are necessary to obtain reproducible and repeatable results.
19 Related JoVE Articles!
Heterotypic Three-dimensional In Vitro Modeling of Stromal-Epithelial Interactions During Ovarian Cancer Initiation and Progression
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
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
A Sensitive and Specific Quantitation Method for Determination of Serum Cardiac Myosin Binding Protein-C by Electrochemiluminescence Immunoassay
Institutions: Loyola University Chicago.
Biomarkers are becoming increasingly more important in clinical decision-making, as well as basic science. Diagnosing myocardial infarction (MI) is largely driven by detecting cardiac-specific proteins in patients' serum or plasma as an indicator of myocardial injury. Having recently shown that cardiac myosin binding protein-C (cMyBP-C) is detectable in the serum after MI, we have proposed it as a potential biomarker for MI. Biomarkers are typically detected by traditional sandwich enzyme-linked immunosorbent assays. However, this technique requires a large sample volume, has a small dynamic range, and can measure only one protein at a time.
Here we show a multiplex immunoassay in which three cardiac proteins can be measured simultaneously with high sensitivity. Measuring cMyBP-C in uniplex or together with creatine kinase MB and cardiac troponin I showed comparable sensitivity. This technique uses the Meso Scale Discovery (MSD) method of multiplexing in a 96-well plate combined with electrochemiluminescence for detection. While only small sample volumes are required, high sensitivity and a large dynamic range are achieved. Using this technique, we measured cMyBP-C, creatine kinase MB, and cardiac troponin I levels in serum samples from 16 subjects with MI and compared the results with 16 control subjects. We were able to detect all three markers in these samples and found all three biomarkers to be increased after MI. This technique is, therefore, suitable for the sensitive detection of cardiac biomarkers in serum samples.
Molecular Biology, Issue 78, Cellular Biology, Biochemistry, Genetics, Biomedical Engineering, Medicine, Cardiology, Heart Diseases, Myocardial Ischemia, Myocardial Infarction, Cardiovascular Diseases, cardiovascular disease, immunoassay, cardiac myosin binding protein-C, cardiac troponin I, creatine kinase MB, electrochemiluminescence, multiplex biomarkers, ELISA, assay
Induction of Invasive Transitional Cell Bladder Carcinoma in Immune Intact Human MUC1 Transgenic Mice: A Model for Immunotherapy Development
Institutions: University of California, Davis, University of California, Davis, Merck KGaA, Darmstadt, Germany.
A preclinical model of invasive bladder cancer was developed in human mucin 1 (MUC1) transgenic (MUC1.Tg) mice for the purpose of evaluating immunotherapy and/or cytotoxic chemotherapy. To induce bladder cancer, C57BL/6 mice (MUC1.Tg and wild type) were treated orally with the carcinogen N-butyl-N-(4-hydroxybutyl)nitrosamine (OH-BBN) at 3.0 mg/day, 5 days/week for 12 weeks. To assess the effects of OH-BBN on serum cytokine profile during tumor development, whole blood was collected via submandibular bleeds prior to treatment and every four weeks. In addition, a MUC1-targeted peptide vaccine and placebo were administered to groups of mice weekly for eight weeks. Multiplex fluorometric microbead immunoanalyses of serum cytokines during tumor development and following vaccination were performed. At termination, interferon gamma (IFN-γ)/interleukin-4 (IL-4) ELISpot analysis for MUC1 specific T-cell immune response and histopathological evaluations of tumor type and grade were performed. The results showed that: (1) the incidence of bladder cancer in both MUC1.Tg and wild type mice was 67%; (2) transitional cell carcinomas (TCC) developed at a 2:1 ratio compared to squamous cell carcinomas (SCC); (3) inflammatory cytokines increased with time during tumor development; and (4) administration of the peptide vaccine induces a Th1-polarized serum cytokine profile and a MUC1 specific T-cell response. All tumors in MUC1.Tg mice were positive for MUC1 expression, and half of all tumors in MUC1.Tg and wild type mice were invasive. In conclusion, using a team approach through the coordination of the efforts of pharmacologists, immunologists, pathologists and molecular biologists, we have developed an immune intact transgenic mouse model of bladder cancer that expresses hMUC1.
Medicine, Issue 80, Urinary Bladder, Animals, Genetically Modified, Cancer Vaccines, Immunotherapy, Animal Experimentation, Models, Neoplasms Bladder Cancer, C57BL/6 Mouse, MUC1, Immunotherapy, Preclinical Model
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 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
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
Hydrogel Nanoparticle Harvesting of Plasma or Urine for Detecting Low Abundance Proteins
Institutions: George Mason University, Ceres Nanosciences.
Novel biomarker discovery plays a crucial role in providing more sensitive and specific disease detection. Unfortunately many low-abundance biomarkers that exist in biological fluids cannot be easily detected with mass spectrometry or immunoassays because they are present in very low concentration, are labile, and are often masked by high-abundance proteins such as albumin or immunoglobulin. Bait containing poly(N-isopropylacrylamide) (NIPAm) based nanoparticles are able to overcome these physiological barriers. In one step they are able to capture, concentrate and preserve biomarkers from body fluids. Low-molecular weight analytes enter the core of the nanoparticle and are captured by different organic chemical dyes, which act as high affinity protein baits. The nanoparticles are able to concentrate the proteins of interest by several orders of magnitude. This concentration factor is sufficient to increase the protein level such that the proteins are within the detection limit of current mass spectrometers, western blotting, and immunoassays. Nanoparticles can be incubated with a plethora of biological fluids and they are able to greatly enrich the concentration of low-molecular weight proteins and peptides while excluding albumin and other high-molecular weight proteins. Our data show that a 10,000 fold amplification in the concentration of a particular analyte can be achieved, enabling mass spectrometry and immunoassays to detect previously undetectable biomarkers.
Bioengineering, Issue 90, biomarker, hydrogel, low abundance, mass spectrometry, nanoparticle, plasma, protein, urine
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
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
Multiplexed Fluorescent Microarray for Human Salivary Protein Analysis Using Polymer Microspheres and Fiber-optic Bundles
Institutions: Tufts University, Complutense University (Spain), Tufts University.
Herein, we describe a protocol for simultaneously measuring six proteins in saliva using a fiber-optic microsphere-based antibody array. The immuno-array technology employed combines the advantages of microsphere-based suspension array fabrication with the use of fluorescence microscopy. As described in the video protocol, commercially available 4.5 μm polymer microspheres were encoded into seven different types, differentiated by the concentration of two fluorescent dyes physically trapped inside the microspheres. The encoded microspheres containing surface carboxyl groups were modified with monoclonal capture antibodies through EDC/NHS coupling chemistry. To assemble the protein microarray, the different types of encoded and functionalized microspheres were mixed and randomly deposited in 4.5 μm microwells, which were chemically etched at the proximal end of a fiber-optic bundle. The fiber-optic bundle was used as both a carrier and for imaging the microspheres. Once assembled, the microarray was used to capture proteins in the saliva supernatant collected from the clinic. The detection was based on a sandwich immunoassay using a mixture of biotinylated detection antibodies for different analytes with a streptavidin-conjugated fluorescent probe, R-phycoerythrin. The microarray was imaged by fluorescence microscopy in three different channels, two for microsphere registration and one for the assay signal. The fluorescence micrographs were then decoded and analyzed using a homemade algorithm in MATLAB.
Chemistry, Issue 80, protein sensing, microarray, multiplexed fluorescent quantification, fiber-optic biosensor, microsphere-based immunoassays, saliva analysis, microsphere encoding
Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Institutions: Joint Unit Hospices de Lyon-bioMérieux, BioMérieux, Hospices Civils de Lyon, Lyon 1 University, BioMérieux, Hospices Civils de Lyon, Hospices Civils de Lyon.
The prostate-specific antigen (PSA) is the main diagnostic biomarker for prostate cancer in clinical use, but it lacks specificity and sensitivity, particularly in low dosage values1
. ‘How to use PSA' remains a current issue, either for diagnosis as a gray zone corresponding to a concentration in serum of 2.5-10 ng/ml which does not allow a clear differentiation to be made between cancer and noncancer2
or for patient follow-up as analysis of post-operative PSA kinetic parameters can pose considerable challenges for their practical application3,4
. Alternatively, noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease, e.g.
PCA3 in prostate cancer5,6
and to reveal uncharacterized aspects of tumor biology. Moreover, data from the ENCODE project published in 2012 showed that different RNA types cover about 62% of the genome. It also appears that the amount of transcriptional regulatory motifs is at least 4.5x higher than the one corresponding to protein-coding exons. Thus, long terminal repeats (LTRs) of human endogenous retroviruses (HERVs) constitute a wide range of putative/candidate transcriptional regulatory sequences, as it is their primary function in infectious retroviruses. HERVs, which are spread throughout the human genome, originate from ancestral and independent infections within the germ line, followed by copy-paste propagation processes and leading to multicopy families occupying 8% of the human genome (note that exons span 2% of our genome). Some HERV loci still express proteins that have been associated with several pathologies including cancer7-10
. We have designed a high-density microarray, in Affymetrix format, aiming to optimally characterize individual HERV loci expression, in order to better understand whether they can be active, if they drive ncRNA transcription or modulate coding gene expression. This tool has been applied in the prostate cancer field (Figure 1
Medicine, Issue 81, Cancer Biology, Genetics, Molecular Biology, Prostate, Retroviridae, Biomarkers, Pharmacological, Tumor Markers, Biological, Prostatectomy, Microarray Analysis, Gene Expression, Diagnosis, Human Endogenous Retroviruses, HERV, microarray, Transcriptome, prostate cancer, Affymetrix
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
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
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
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
Quantification of Proteins Using Peptide Immunoaffinity Enrichment Coupled with Mass Spectrometry
Institutions: Fred Hutchinson Cancer Research Center - FHCRC, University of Victoria, Broad Institute of MIT and Harvard, University of Victoria, Plasma Proteome Institute.
There is a great need for quantitative assays in measuring proteins. Traditional sandwich immunoassays, largely considered the gold standard in quantitation, are associated with a high cost, long lead time, and are fraught with drawbacks (e.g. heterophilic antibodies, autoantibody interference, 'hook-effect').1
An alternative technique is affinity enrichment of peptides coupled with quantitative mass spectrometry, commonly referred to as SISCAPA
(Stable Isotope Standards and Capture by Anti-Peptide Antibodies).2
In this technique, affinity enrichment of peptides with stable isotope dilution and detection by selected/multiple reaction monitoring mass spectrometry (SRM/MRM-MS
) provides quantitative measurement of peptides as surrogates for their respective proteins. SRM/MRM-MS is well established for accurate quantitation of small molecules 3, 4
and more recently has been adapted to measure the concentrations of proteins in plasma and cell lysates.5-7
To achieve quantitation of proteins, these larger molecules are digested to component peptides using an enzyme such as trypsin. One or more selected peptides whose sequence is unique to the target protein in that species (i.e. "proteotypic" peptides) are then enriched from the sample using anti-peptide antibodies and measured as quantitative stoichiometric surrogates for protein concentration in the sample. Hence, coupled to stable isotope dilution (SID
) methods (i.e. a spiked-in stable isotope labeled peptide standard), SRM/MRM can be used to measure concentrations of proteotypic peptides as surrogates for quantification of proteins in complex biological matrices. The assays have several advantages compared to traditional immunoassays. The reagents are relatively less expensive to generate, the specificity for the analyte is excellent, the assays can be highly multiplexed, enrichment can be performed from neat plasma (no depletion required), and the technique is amenable to a wide array of proteins or modifications of interest.8-13
In this video we demonstrate the basic protocol as adapted to a magnetic bead platform.
Molecular Biology, Issue 53, Mass spectrometry, targeted assay, peptide, MRM, SISCAPA, protein quantitation
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
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
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