The widespread use of Next Generation Sequencing has opened up new avenues for cancer research and diagnosis. NGS will bring huge amounts of new data on cancer, and especially cancer genetics. Current knowledge and future discoveries will make it necessary to study a huge number of genes that could be involved in a genetic predisposition to cancer. In this regard, we developed a Nextera design to study 11 complete genes involved in DNA damage repair. This protocol was developed to safely study 11 genes (ATM, BARD1, BRCA1, BRCA2, BRIP1, CHEK2, PALB2, RAD50, RAD51C, RAD80, and TP53) from promoter to 3'-UTR in 24 patients simultaneously. This protocol, based on transposase technology and gDNA enrichment, gives a great advantage in terms of time for the genetic diagnosis thanks to sample multiplexing. This protocol can be safely used with blood gDNA.
19 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
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
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
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
Ex Vivo Culture of Primary Human Fallopian Tube Epithelial Cells
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
Ex vivo Expansion of Tumor-reactive T Cells by Means of Bryostatin 1/Ionomycin and the Common Gamma Chain Cytokines Formulation
Institutions: Virginia Commonwealth University- Massey Cancer Center, Virginia Commonwealth University- Massey Cancer Center, Virginia Commonwealth University- Massey Cancer Center.
It was reported that breast cancer patients have pre-existing immune responses against their tumors1,2
. However, such immune responses fail to provide complete protection against the development or recurrence of breast cancer. To overcome this problem by increasing the frequency of tumor-reactive T cells, adoptive immunotherapy has been employed. A variety of protocols have been used for the expansion of tumor-specific T cells. These protocols, however, are restricted to the use of tumor antigens ex vivo
for the activation of antigen-specific T cells. Very recently, common gamma chain cytokines such as IL-2, IL-7, IL-15, and IL-21 have been used alone or in combination for the enhancement of anti-tumor immune responses3
. However, it is not clear what formulation would work best for the expansion of tumor-reactive T cells. Here we present a protocol for the selective activation and expansion of tumor-reactive T cells from the FVBN202 transgenic mouse model of HER-2/neu positive breast carcinoma for use in adoptive T cell therapy of breast cancer. The protocol includes activation of T cells with bryostatin-1/ionomycin (B/I) and IL-2 in the absence of tumor antigens for 16 hours. B/I activation mimics intracellular signals that result in T cell activation by increasing protein kinase C activity and intracellular calcium, respectively4
. This protocol specifically activates tumor-specific T cells while killing irrelevant T cells. The B/I-activated T cells are cultured with IL-7 and IL-15 for 24 hours and then pulsed with IL-2. After 24 hours, T cells are washed, split, and cultured with IL-7 + IL-15 for additional 4 days. Tumor-specificity and anti-tumor efficacy of the ex vivo
expanded T cells is determined.
Immunology, Issue 47, Adoptive T cell therapy, Breast Cancer, HER-2/neu, common gamma chain cytokines, Bryostatin 1, Ionomycin
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
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
A Matrigel-Based Tube Formation Assay to Assess the Vasculogenic Activity of Tumor Cells
Institutions: University of Massachusetts, University of Massachusetts, University of Massachusetts.
Over the past several decades, a tube formation assay using growth factor-reduced Matrigel has been typically employed to demonstrate the angiogenic activity of vascular endothelial cells in vitro1-5
. However, recently growing evidence has shown that this assay is not limited to test vascular behavior for endothelial cells. Instead, it also has been used to test the ability of a number of tumor cells to develop a vascular phenotype6-8
. This capability was consistent with their vasculogenic behavior identified in xenotransplanted animals, a process known as vasculogenic mimicry (VM)9
. There is a multitude of evidence demonstrating that tumor cell-mediated VM plays a vital role in the tumor development, independent of endothelial cell angiogenesis6, 10-13
. For example, tumor cells were found to participate in the blood perfused, vascular channel formation in tissue samples from melanoma and glioblastoma patients8, 10, 11
. Here, we described this tubular network assay as a useful tool in evaluation of vasculogenic activity of tumor cells. We found that some tumor cell lines such as melanoma B16F1 cells, glioblastoma U87 cells, and breast cancer MDA-MB-435 cells are able to form vascular tubules; but some do not such as colon cancer HCT116 cells. Furthermore, this vascular phenotype is dependent on cell numbers plated on the Matrigel. Therefore, this assay may serve as powerful utility to screen the vascular potential of a variety of cell types including vascular cells, tumor cells as well as other cells.
Cancer Biology, Issue 55, tumor, vascular, endothelial, tube formation, Matrigel, in vitro
Identifying the Effects of BRCA1 Mutations on Homologous Recombination using Cells that Express Endogenous Wild-type BRCA1
Institutions: The Ohio State University, Tohoku University.
The functional analysis of missense mutations can be complicated by the presence in the cell of the endogenous protein. Structure-function analyses of the BRCA1 have been complicated by the lack of a robust assay for the full length BRCA1 protein and the difficulties inherent in working with cell lines that express hypomorphic BRCA1 protein1,2,3,4,5
. We developed a system whereby the endogenous BRCA1 protein in a cell was acutely depleted by RNAi targeting the 3'-UTR of the BRCA1 mRNA and replaced by co-transfecting a plasmid expressing a BRCA1 variant. One advantage of this procedure is that the acute silencing of BRCA1 and simultaneous replacement allow the cells to grow without secondary mutations or adaptations that might arise over time to compensate for the loss of BRCA1 function. This depletion and add-back procedure was done in a HeLa-derived cell line that was readily assayed for homologous recombination activity. The homologous recombination assay is based on a previously published method whereby a recombination substrate is integrated into the genome (Figure 1)6,7,8,9
. This recombination substrate has the rare-cutting I-SceI restriction enzyme site inside an inactive GFP allele, and downstream is a second inactive GFP allele. Transfection of the plasmid that expresses I-SceI results in a double-stranded break, which may be repaired by homologous recombination, and if homologous recombination does repair the break it creates an active GFP allele that is readily scored by flow cytometry for GFP protein expression. Depletion of endogenous BRCA1 resulted in an 8-10-fold reduction in homologous recombination activity, and add-back of wild-type plasmid fully restored homologous recombination function. When specific point mutants of full length BRCA1 were expressed from co-transfected plasmids, the effect of the specific missense mutant could be scored. As an example, the expression of the BRCA1(M18T) protein, a variant of unknown clinical significance10
, was expressed in these cells, it failed to restore BRCA1-dependent homologous recombination. By contrast, expression of another variant, also of unknown significance, BRCA1(I21V) fully restored BRCA1-dependent homologous recombination function. This strategy of testing the function of BRCA1 missense mutations has been applied to another biological system assaying for centrosome function (Kais et al, unpublished observations). Overall, this approach is suitable for the analysis of missense mutants in any gene that must be analyzed recessively.
Cell Biology, Issue 48, BRCA1, homologous recombination, breast cancer, RNA interference, DNA repair
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 (http://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
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
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
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
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
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
Initiation of Metastatic Breast Carcinoma by Targeting of the Ductal Epithelium with Adenovirus-Cre: A Novel Transgenic Mouse Model of Breast Cancer
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
Tissue-simulating Phantoms for Assessing Potential Near-infrared Fluorescence Imaging Applications in Breast Cancer Surgery
Institutions: University Medical Center Groningen, Technical University of Munich.
Inaccuracies in intraoperative tumor localization and evaluation of surgical margin status result in suboptimal outcome of breast-conserving surgery (BCS). Optical imaging, in particular near-infrared fluorescence (NIRF) imaging, might reduce the frequency of positive surgical margins following BCS by providing the surgeon with a tool for pre- and intraoperative tumor localization in real-time. In the current study, the potential of NIRF-guided BCS is evaluated using tissue-simulating breast phantoms for reasons of standardization and training purposes.
Breast phantoms with optical characteristics comparable to those of normal breast tissue were used to simulate breast conserving surgery. Tumor-simulating inclusions containing the fluorescent dye indocyanine green (ICG) were incorporated in the phantoms at predefined locations and imaged for pre- and intraoperative tumor localization, real-time NIRF-guided tumor resection, NIRF-guided evaluation on the extent of surgery, and postoperative assessment of surgical margins. A customized NIRF camera was used as a clinical prototype for imaging purposes.
Breast phantoms containing tumor-simulating inclusions offer a simple, inexpensive, and versatile tool to simulate and evaluate intraoperative tumor imaging. The gelatinous phantoms have elastic properties similar to human tissue and can be cut using conventional surgical instruments. Moreover, the phantoms contain hemoglobin and intralipid for mimicking absorption and scattering of photons, respectively, creating uniform optical properties similar to human breast tissue. The main drawback of NIRF imaging is the limited penetration depth of photons when propagating through tissue, which hinders (noninvasive) imaging of deep-seated tumors with epi-illumination strategies.
Medicine, Issue 91, Breast cancer, tissue-simulating phantoms, NIRF imaging, tumor-simulating inclusions, fluorescence, intraoperative imaging
A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
Institutions: Universite de Montreal, Universite de Montreal, Universite de Montreal.
There are several lines of evidence supporting the role of de novo
mutations as a mechanism for common disorders, such as autism and schizophrenia. First, the de novo
mutation rate in humans is relatively high, so new mutations are generated at a high frequency in the population. However, de novo
mutations have not been reported in most common diseases. Mutations in genes leading to severe diseases where there is a strong negative selection against the phenotype, such as lethality in embryonic stages or reduced reproductive fitness, will not be transmitted to multiple family members, and therefore will not be detected by linkage gene mapping or association studies. The observation of very high concordance in monozygotic twins and very low concordance in dizygotic twins also strongly supports the hypothesis that a significant fraction of cases may result from new mutations. Such is the case for diseases such as autism and schizophrenia. Second, despite reduced reproductive fitness1
and extremely variable environmental factors, the incidence of some diseases is maintained worldwide at a relatively high and constant rate. This is the case for autism and schizophrenia, with an incidence of approximately 1% worldwide. Mutational load can be thought of as a balance between selection for or against a deleterious mutation and its production by de novo
mutation. Lower rates of reproduction constitute a negative selection factor that should reduce the number of mutant alleles in the population, ultimately leading to decreased disease prevalence. These selective pressures tend to be of different intensity in different environments. Nonetheless, these severe mental disorders have been maintained at a constant relatively high prevalence in the worldwide population across a wide range of cultures and countries despite a strong negative selection against them2
. This is not what one would predict in diseases with reduced reproductive fitness, unless there was a high new mutation rate. Finally, the effects of paternal age: there is a significantly increased risk of the disease with increasing paternal age, which could result from the age related increase in paternal de novo
mutations. This is the case for autism and schizophrenia3
. The male-to-female ratio of mutation rate is estimated at about 4–6:1, presumably due to a higher number of germ-cell divisions with age in males. Therefore, one would predict that de novo
mutations would more frequently come from males, particularly older males4
. A high rate of new mutations may in part explain why genetic studies have so far failed to identify many genes predisposing to complexes diseases genes, such as autism and schizophrenia, and why diseases have been identified for a mere 3% of genes in the human genome. Identification for de novo
mutations as a cause of a disease requires a targeted molecular approach, which includes studying parents and affected subjects. The process for determining if the genetic basis of a disease may result in part from de novo
mutations and the molecular approach to establish this link will be illustrated, using autism and schizophrenia as examples.
Medicine, Issue 52, de novo mutation, complex diseases, schizophrenia, autism, rare variations, DNA sequencing