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Pubmed Article
Integrated multidimensional analysis is required for accurate prognostic biomarkers in colorectal cancer.
PUBLISHED: 01-01-2014
CRC cancer is one of the deadliest diseases in Western countries. In order to develop prognostic biomarkers for CRC (colorectal cancer) aggressiveness, we analyzed retrospectively 267 CRC patients via a novel, multidimensional biomarker platform. Using nanofluidic technology for qPCR analysis and quantitative fluorescent immunohistochemistry for protein analysis, we assessed 33 microRNAs, 124 mRNAs and 9 protein antigens. Analysis was conducted in each single dimension (microRNA, gene or protein) using both the multivariate Cox model and Kaplan-Meier method. Thereafter, we simplified the censored survival data into binary response data (aggressive vs. non aggressive cancer). Subsequently, we integrated the data into a diagnostic score using sliced inverse regression for sufficient dimension reduction. Accuracy was assessed using area under the receiver operating characteristic curve (AUC). Single dimension analysis led to the discovery of individual factors that were significant predictors of outcome. These included seven specific microRNAs, four genes, and one protein. When these factors were quantified individually as predictors of aggressive disease, the highest demonstrable area under the curve (AUC) was 0.68. By contrast, when all results from single dimensions were combined into integrated biomarkers, AUCs were dramatically increased with values approaching and even exceeding 0.9. Single dimension analysis generates statistically significant predictors, but their predictive strengths are suboptimal for clinical utility. A novel, multidimensional integrated approach overcomes these deficiencies. Newly derived integrated biomarkers have the potential to meaningfully guide the selection of therapeutic strategies for individual patients while elucidating molecular mechanisms driving disease progression.
Authors: Inti Zlobec, Guido Suter, Aurel Perren, Alessandro Lugli.
Published: 09-23-2014
Biomarker research relies on tissue microarrays (TMA). TMAs are produced by repeated transfer of small tissue cores from a ‘donor’ block into a ‘recipient’ block and then used for a variety of biomarker applications. The construction of conventional TMAs is labor intensive, imprecise, and time-consuming. Here, a protocol using next-generation Tissue Microarrays (ngTMA) is outlined. ngTMA is based on TMA planning and design, digital pathology, and automated tissue microarraying. The protocol is illustrated using an example of 134 metastatic colorectal cancer patients. Histological, statistical and logistical aspects are considered, such as the tissue type, specific histological regions, and cell types for inclusion in the TMA, the number of tissue spots, sample size, statistical analysis, and number of TMA copies. Histological slides for each patient are scanned and uploaded onto a web-based digital platform. There, they are viewed and annotated (marked) using a 0.6-2.0 mm diameter tool, multiple times using various colors to distinguish tissue areas. Donor blocks and 12 ‘recipient’ blocks are loaded into the instrument. Digital slides are retrieved and matched to donor block images. Repeated arraying of annotated regions is automatically performed resulting in an ngTMA. In this example, six ngTMAs are planned containing six different tissue types/histological zones. Two copies of the ngTMAs are desired. Three to four slides for each patient are scanned; 3 scan runs are necessary and performed overnight. All slides are annotated; different colors are used to represent the different tissues/zones, namely tumor center, invasion front, tumor/stroma, lymph node metastases, liver metastases, and normal tissue. 17 annotations/case are made; time for annotation is 2-3 min/case. 12 ngTMAs are produced containing 4,556 spots. Arraying time is 15-20 hr. Due to its precision, flexibility and speed, ngTMA is a powerful tool to further improve the quality of TMAs used in clinical and translational research.
23 Related JoVE Articles!
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Flexible Colonoscopy in Mice to Evaluate the Severity of Colitis and Colorectal Tumors Using a Validated Endoscopic Scoring System
Authors: Tomohiro Kodani, Alex Rodriguez-Palacios, Daniele Corridoni, Loris Lopetuso, Luca Di Martino, Brian Marks, James Pizarro, Theresa Pizarro, Amitabh Chak, Fabio Cominelli.
Institutions: Case Western Reserve University School of Medicine, Cleveland, Case Western Reserve University School of Medicine, Cleveland, Case Western Reserve University School of Medicine, Cleveland.
The use of modern endoscopy for research purposes has greatly facilitated our understanding of gastrointestinal pathologies. In particular, experimental endoscopy has been highly useful for studies that require repeated assessments in a single laboratory animal, such as those evaluating mechanisms of chronic inflammatory bowel disease and the progression of colorectal cancer. However, the methods used across studies are highly variable. At least three endoscopic scoring systems have been published for murine colitis and published protocols for the assessment of colorectal tumors fail to address the presence of concomitant colonic inflammation. This study develops and validates a reproducible endoscopic scoring system that integrates evaluation of both inflammation and tumors simultaneously. This novel scoring system has three major components: 1) assessment of the extent and severity of colorectal inflammation (based on perianal findings, transparency of the wall, mucosal bleeding, and focal lesions), 2) quantitative recording of tumor lesions (grid map and bar graph), and 3) numerical sorting of clinical cases by their pathological and research relevance based on decimal units with assigned categories of observed lesions and endoscopic complications (decimal identifiers). The video and manuscript presented herein were prepared, following IACUC-approved protocols, to allow investigators to score their own experimental mice using a well-validated and highly reproducible endoscopic methodology, with the system option to differentiate distal from proximal endoscopic colitis (D-PECS).
Medicine, Issue 80, Crohn's disease, ulcerative colitis, colon cancer, Clostridium difficile, SAMP mice, DSS/AOM-colitis, decimal scoring identifier
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Utility of Dissociated Intrinsic Hand Muscle Atrophy in the Diagnosis of Amyotrophic Lateral Sclerosis
Authors: Parvathi Menon, Steve Vucic.
Institutions: Westmead Hospital, University of Sydney, Australia.
The split hand phenomenon refers to predominant wasting of thenar muscles and is an early and specific feature of amyotrophic lateral sclerosis (ALS). A novel split hand index (SI) was developed to quantify the split hand phenomenon, and its diagnostic utility was assessed in ALS patients. The split hand index was derived by dividing the product of the compound muscle action potential (CMAP) amplitude recorded over the abductor pollicis brevis and first dorsal interosseous muscles by the CMAP amplitude recorded over the abductor digiti minimi muscle. In order to assess the diagnostic utility of the split hand index, ALS patients were prospectively assessed and their results were compared to neuromuscular disorder patients. The split hand index was significantly reduced in ALS when compared to neuromuscular disorder patients (P<0.0001). Limb-onset ALS patients exhibited the greatest reduction in the split hand index, and a value of 5.2 or less reliably differentiated ALS from other neuromuscular disorders. Consequently, the split hand index appears to be a novel diagnostic biomarker for ALS, perhaps facilitating an earlier diagnosis.
Medicine, Issue 85, Amyotrophic Lateral Sclerosis (ALS), dissociated muscle atrophy, hypothenar muscles, motor neuron disease, split-hand index, thenar muscles
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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Authors: Johannes Felix Buyel, Rainer Fischer.
Institutions: RWTH Aachen University, Fraunhofer Gesellschaft.
Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.
Bioengineering, Issue 83, design of experiments (DoE), transient protein expression, plant-derived biopharmaceuticals, promoter, 5'UTR, fluorescent reporter protein, model building, incubation conditions, monoclonal antibody
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Adaptation of Semiautomated Circulating Tumor Cell (CTC) Assays for Clinical and Preclinical Research Applications
Authors: Lori E. Lowes, Benjamin D. Hedley, Michael Keeney, Alison L. Allan.
Institutions: London Health Sciences Centre, Western University, London Health Sciences Centre, Lawson Health Research Institute, Western University.
The majority of cancer-related deaths occur subsequent to the development of metastatic disease. This highly lethal disease stage is associated with the presence of circulating tumor cells (CTCs). These rare cells have been demonstrated to be of clinical significance in metastatic breast, prostate, and colorectal cancers. The current gold standard in clinical CTC detection and enumeration is the FDA-cleared CellSearch system (CSS). This manuscript outlines the standard protocol utilized by this platform as well as two additional adapted protocols that describe the detailed process of user-defined marker optimization for protein characterization of patient CTCs and a comparable protocol for CTC capture in very low volumes of blood, using standard CSS reagents, for studying in vivo preclinical mouse models of metastasis. In addition, differences in CTC quality between healthy donor blood spiked with cells from tissue culture versus patient blood samples are highlighted. Finally, several commonly discrepant items that can lead to CTC misclassification errors are outlined. Taken together, these protocols will provide a useful resource for users of this platform interested in preclinical and clinical research pertaining to metastasis and CTCs.
Medicine, Issue 84, Metastasis, circulating tumor cells (CTCs), CellSearch system, user defined marker characterization, in vivo, preclinical mouse model, clinical research
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Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells
Authors: Anne Katchy, Cecilia Williams.
Institutions: University of Houston.
Estrogen plays vital roles in mammary gland development and breast cancer progression. It mediates its function by binding to and activating the estrogen receptors (ERs), ERα, and ERβ. ERα is frequently upregulated in breast cancer and drives the proliferation of breast cancer cells. The ERs function as transcription factors and regulate gene expression. Whereas ERα's regulation of protein-coding genes is well established, its regulation of noncoding microRNA (miRNA) is less explored. miRNAs play a major role in the post-transcriptional regulation of genes, inhibiting their translation or degrading their mRNA. miRNAs can function as oncogenes or tumor suppressors and are also promising biomarkers. Among the miRNA assays available, microarray and quantitative real-time polymerase chain reaction (qPCR) have been extensively used to detect and quantify miRNA levels. To identify miRNAs regulated by estrogen signaling in breast cancer, their expression in ERα-positive breast cancer cell lines were compared before and after estrogen-activation using both the µParaflo-microfluidic microarrays and Dual Labeled Probes-low density arrays. Results were validated using specific qPCR assays, applying both Cyanine dye-based and Dual Labeled Probes-based chemistry. Furthermore, a time-point assay was used to identify regulations over time. Advantages of the miRNA assay approach used in this study is that it enables a fast screening of mature miRNA regulations in numerous samples, even with limited sample amounts. The layout, including the specific conditions for cell culture and estrogen treatment, biological and technical replicates, and large-scale screening followed by in-depth confirmations using separate techniques, ensures a robust detection of miRNA regulations, and eliminates false positives and other artifacts. However, mutated or unknown miRNAs, or regulations at the primary and precursor transcript level, will not be detected. The method presented here represents a thorough investigation of estrogen-mediated miRNA regulation.
Medicine, Issue 84, breast cancer, microRNA, estrogen, estrogen receptor, microarray, qPCR
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Isolation of Small Noncoding RNAs from Human Serum
Authors: Samantha Khoury, Pamela Ajuyah, Nham Tran.
Institutions: University of Technology, Sydney, University of Technology, Sydney, Royal Prince Alfred Hospital.
The analysis of RNA and its expression is a common feature in many laboratories. Of significance is the emergence of small RNAs like microRNAs, which are found in mammalian cells. These small RNAs are potent gene regulators controlling vital pathways such as growth, development and death and much interest has been directed at their expression in bodily fluids. This is due to their dysregulation in human diseases such as cancer and their potential application as serum biomarkers. However, the analysis of miRNA expression in serum may be problematic. In most cases the amount of serum is limiting and serum contains low amounts of total RNA, of which small RNAs only constitute 0.4-0.5%1. Thus the isolation of sufficient amounts of quality RNA from serum is a major challenge to researchers today. In this technical paper, we demonstrate a method which uses only 400 µl of human serum to obtain sufficient RNA for either DNA arrays or qPCR analysis. The advantages of this method are its simplicity and ability to yield high quality RNA. It requires no specialized columns for purification of small RNAs and utilizes general reagents and hardware found in common laboratories. Our method utilizes a Phase Lock Gel to eliminate phenol contamination while at the same time yielding high quality RNA. We also introduce an additional step to further remove all contaminants during the isolation step. This protocol is very effective in isolating yields of total RNA of up to 100 ng/µl from serum but can also be adapted for other biological tissues.
Bioengineering, Issue 88, small noncoding RNA isolation, microRNAs, human serum, qPCR, guanidinium thiocyanate , Phase Lock Gels, arrays
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Molecular Profiling of the Invasive Tumor Microenvironment in a 3-Dimensional Model of Colorectal Cancer Cells and Ex vivo Fibroblasts
Authors: Marc D. Bullock, Max Mellone, Karen M. Pickard, Abdulkadir Emre Sayan, Richard Mitter, John N. Primrose, Graham K. Packham, Gareth Thomas, Alexander H. Mirnezami.
Institutions: University of Southampton School of Medicine, University of Southampton School of Medicine, London Research Institute, Cancer Research UK.
Invading colorectal cancer (CRC) cells have acquired the capacity to break free from their sister cells, infiltrate the stroma, and remodel the extracellular matrix (ECM). Characterizing the biology of this phenotypically distinct group of cells could substantially improve our understanding of early events during the metastatic cascade. Tumor invasion is a dynamic process facilitated by bidirectional interactions between malignant epithelium and the cancer associated stroma. In order to examine cell-specific responses at the tumor stroma-interface we have combined organotypic co-culture and laser micro-dissection techniques. Organotypic models, in which key stromal constituents such as fibroblasts are 3-dimentioanally co-cultured with cancer epithelial cells, are highly manipulatable experimental tools which enable invasion and cancer-stroma interactions to be studied in near-physiological conditions. Laser microdissection (LMD) is a technique which entails the surgical dissection and extraction of the various strata within tumor tissue, with micron level precision. By combining these techniques with genomic, transcriptomic and epigenetic profiling we aim to develop a deeper understanding of the molecular characteristics of invading tumor cells and surrounding stromal tissue, and in doing so potentially reveal novel biomarkers and opportunities for drug development in CRC.   
Medicine, Issue 86, Colorectal cancer, Cancer metastasis, organotypic culture, laser microdissection, molecular profiling, invasion, tumor microenvironment, stromal tissue, epithelium, fibroblasts
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Modeling Astrocytoma Pathogenesis In Vitro and In Vivo Using Cortical Astrocytes or Neural Stem Cells from Conditional, Genetically Engineered Mice
Authors: Robert S. McNeill, Ralf S. Schmid, Ryan E. Bash, Mark Vitucci, Kristen K. White, Andrea M. Werneke, Brian H. Constance, Byron Huff, C. Ryan Miller.
Institutions: University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, Emory University School of Medicine, University of North Carolina School of Medicine.
Current astrocytoma models are limited in their ability to define the roles of oncogenic mutations in specific brain cell types during disease pathogenesis and their utility for preclinical drug development. In order to design a better model system for these applications, phenotypically wild-type cortical astrocytes and neural stem cells (NSC) from conditional, genetically engineered mice (GEM) that harbor various combinations of floxed oncogenic alleles were harvested and grown in culture. Genetic recombination was induced in vitro using adenoviral Cre-mediated recombination, resulting in expression of mutated oncogenes and deletion of tumor suppressor genes. The phenotypic consequences of these mutations were defined by measuring proliferation, transformation, and drug response in vitro. Orthotopic allograft models, whereby transformed cells are stereotactically injected into the brains of immune-competent, syngeneic littermates, were developed to define the role of oncogenic mutations and cell type on tumorigenesis in vivo. Unlike most established human glioblastoma cell line xenografts, injection of transformed GEM-derived cortical astrocytes into the brains of immune-competent littermates produced astrocytomas, including the most aggressive subtype, glioblastoma, that recapitulated the histopathological hallmarks of human astrocytomas, including diffuse invasion of normal brain parenchyma. Bioluminescence imaging of orthotopic allografts from transformed astrocytes engineered to express luciferase was utilized to monitor in vivo tumor growth over time. Thus, astrocytoma models using astrocytes and NSC harvested from GEM with conditional oncogenic alleles provide an integrated system to study the genetics and cell biology of astrocytoma pathogenesis in vitro and in vivo and may be useful in preclinical drug development for these devastating diseases.
Neuroscience, Issue 90, astrocytoma, cortical astrocytes, genetically engineered mice, glioblastoma, neural stem cells, orthotopic allograft
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Hydrogel Nanoparticle Harvesting of Plasma or Urine for Detecting Low Abundance Proteins
Authors: Ruben Magni, Benjamin H. Espina, Lance A. Liotta, Alessandra Luchini, Virginia Espina.
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
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Murine Endoscopy for In Vivo Multimodal Imaging of Carcinogenesis and Assessment of Intestinal Wound Healing and Inflammation
Authors: Markus Brückner, Philipp Lenz, Tobias M. Nowacki, Friederike Pott, Dirk Foell, Dominik Bettenworth.
Institutions: University Hospital Münster, University Children's Hospital Münster.
Mouse models are widely used to study pathogenesis of human diseases and to evaluate diagnostic procedures as well as therapeutic interventions preclinically. However, valid assessment of pathological alterations often requires histological analysis, and when performed ex vivo, necessitates death of the animal. Therefore in conventional experimental settings, intra-individual follow-up examinations are rarely possible. Thus, development of murine endoscopy in live mice enables investigators for the first time to both directly visualize the gastrointestinal mucosa and also repeat the procedure to monitor for alterations. Numerous applications for in vivo murine endoscopy exist, including studying intestinal inflammation or wound healing, obtaining mucosal biopsies repeatedly, and to locally administer diagnostic or therapeutic agents using miniature injection catheters. Most recently, molecular imaging has extended diagnostic imaging modalities allowing specific detection of distinct target molecules using specific photoprobes. In conclusion, murine endoscopy has emerged as a novel cutting-edge technology for diagnostic experimental in vivo imaging and may significantly impact on preclinical research in various fields.
Medicine, Issue 90, gastroenterology, in vivo imaging, murine endoscopy, diagnostic imaging, carcinogenesis, intestinal wound healing, experimental colitis
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Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Authors: Philippe Pérot, Valérie Cheynet, Myriam Decaussin-Petrucci, Guy Oriol, Nathalie Mugnier, Claire Rodriguez-Lafrasse, Alain Ruffion, François Mallet.
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
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
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 (, 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
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Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
Authors: Cila Herman, Muge Pirtini Cetingul.
Institutions: The Johns Hopkins University.
In 2010 approximately 68,720 melanomas will be diagnosed in the US alone, with around 8,650 resulting in death 1. To date, the only effective treatment for melanoma remains surgical excision, therefore, the key to extended survival is early detection 2,3. Considering the large numbers of patients diagnosed every year and the limitations in accessing specialized care quickly, the development of objective in vivo diagnostic instruments to aid the diagnosis is essential. New techniques to detect skin cancer, especially non-invasive diagnostic tools, are being explored in numerous laboratories. Along with the surgical methods, techniques such as digital photography, dermoscopy, multispectral imaging systems (MelaFind), laser-based systems (confocal scanning laser microscopy, laser doppler perfusion imaging, optical coherence tomography), ultrasound, magnetic resonance imaging, are being tested. Each technique offers unique advantages and disadvantages, many of which pose a compromise between effectiveness and accuracy versus ease of use and cost considerations. Details about these techniques and comparisons are available in the literature 4. Infrared (IR) imaging was shown to be a useful method to diagnose the signs of certain diseases by measuring the local skin temperature. There is a large body of evidence showing that disease or deviation from normal functioning are accompanied by changes of the temperature of the body, which again affect the temperature of the skin 5,6. Accurate data about the temperature of the human body and skin can provide a wealth of information on the processes responsible for heat generation and thermoregulation, in particular the deviation from normal conditions, often caused by disease. However, IR imaging has not been widely recognized in medicine due to the premature use of the technology 7,8 several decades ago, when temperature measurement accuracy and the spatial resolution were inadequate and sophisticated image processing tools were unavailable. This situation changed dramatically in the late 1990s-2000s. Advances in IR instrumentation, implementation of digital image processing algorithms and dynamic IR imaging, which enables scientists to analyze not only the spatial, but also the temporal thermal behavior of the skin 9, allowed breakthroughs in the field. In our research, we explore the feasibility of IR imaging, combined with theoretical and experimental studies, as a cost effective, non-invasive, in vivo optical measurement technique for tumor detection, with emphasis on the screening and early detection of melanoma 10-13. In this study, we show data obtained in a patient study in which patients that possess a pigmented lesion with a clinical indication for biopsy are selected for imaging. We compared the difference in thermal responses between healthy and malignant tissue and compared our data with biopsy results. We concluded that the increased metabolic activity of the melanoma lesion can be detected by dynamic infrared imaging.
Medicine, Issue 51, Infrared imaging, quantitative thermal analysis, image processing, skin cancer, melanoma, transient thermal response, skin thermal models, skin phantom experiment, patient study
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Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing
Authors: Jerry Zhou, Larissa Belov, Michael J. Solomon, Charles Chan, Stephen J. Clarke, Richard I. Christopherson.
Institutions: University of Sydney, Royal Prince Alfred Hospital, Department of Anatomical Pathology, Concord Repatriation General Hospital.
The current prognosis and classification of CRC relies on staging systems that integrate histopathologic and clinical findings. However, in the majority of CRC cases, cell dysfunction is the result of numerous mutations that modify protein expression and post-translational modification1. A number of cell surface antigens, including cluster of differentiation (CD) antigens, have been identified as potential prognostic or metastatic biomarkers in CRC. These antigens make ideal biomarkers as their expression often changes with tumour progression or interactions with other cell types, such as tumour-infiltrating lymphocytes (TILs) and tumour-associated macrophages (TAMs). The use of immunohistochemistry (IHC) for cancer sub-classification and prognostication is well established for some tumour types2,3. However, no single ‘marker’ has shown prognostic significance greater than clinico-pathological staging or gained wide acceptance for use in routine pathology reporting of all CRC cases. A more recent approach to prognostic stratification of disease phenotypes relies on surface protein profiles using multiple 'markers'. While expression profiling of tumours using proteomic techniques such as iTRAQ is a powerful tool for the discovery of biomarkers4, it is not optimal for routine use in diagnostic laboratories and cannot distinguish different cell types in a mixed population. In addition, large amounts of tumour tissue are required for the profiling of purified plasma membrane glycoproteins by these methods. In this video we described a simple method for surface proteome profiling of viable cells from disaggregated CRC samples using a DotScan CRC antibody microarray. The 122-antibody microarray consists of a standard 82-antibody region recognizing a range of lineage-specific leukocyte markers, adhesion molecules, receptors and markers of inflammation and immune response5, together with a satellite region for detection of 40 potentially prognostic markers for CRC. Cells are captured only on antibodies for which they express the corresponding antigen. The cell density per dot, determined by optical scanning, reflects the proportion of cells expressing that antigen, the level of expression of the antigen and affinity of the antibody6. For CRC tissue or normal intestinal mucosa, optical scans reflect the immunophenotype of mixed populations of cells. Fluorescence multiplexing can then be used to profile selected sub-populations of cells of interest captured on the array. For example, Alexa 647-anti-epithelial cell adhesion molecule (EpCAM; CD326), is a pan-epithelial differentiation antigen that was used to detect CRC cells and also epithelial cells of normal intestinal mucosa, while Phycoerythrin-anti-CD3, was used to detect infiltrating T-cells7. The DotScan CRC microarray should be the prototype for a diagnostic alternative to the anatomically-based CRC staging system.
Immunology, Issue 55, colorectal cancer, leukocytes, antibody microarray, multiplexing, fluorescence, CD antigens
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Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Authors: Dana Faratian, Jason Christiansen, Mark Gustavson, Christine Jones, Christopher Scott, InHwa Um, David J. Harrison.
Institutions: University of Edinburgh, HistoRx Inc..
Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor1,2, and some of these sub-clones give rise to metastatic (and therefore lethal) disease. Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension3, or on macrodissection4. A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue5, providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ. We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system6. Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index7. To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.
Medicine, Issue 56, quantitative immunofluorescence, heterogeneity, cancer, biomarker, targeted therapy, immunohistochemistry, proteomics, histopathology
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Chemically-blocked Antibody Microarray for Multiplexed High-throughput Profiling of Specific Protein Glycosylation in Complex Samples
Authors: Chen Lu, Joshua L. Wonsidler, Jianwei Li, Yanming Du, Timothy Block, Brian Haab, Songming Chen.
Institutions: Institute for Hepatitis and Virus Research, Thomas Jefferson University , Drexel University College of Medicine, Van Andel Research Institute, Serome Biosciences Inc..
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. Introduction 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.
Molecular Biology, Issue 63, Glycoproteins, glycan-binding protein, specific protein glycosylation, multiplexed high-throughput glycan blocked antibody microarray
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MicroRNA Detection in Prostate Tumors by Quantitative Real-time PCR (qPCR)
Authors: Aida Gordanpour, Robert K. Nam, Linda Sugar, Stephanie Bacopulos, Arun Seth.
Institutions: University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Canada, Sunnybrook Health Sciences Centre, Toronto, Canada, Sunnybrook Research Institute.
MicroRNAs (miRNAs) are single-stranded, 18–24 nucleotide long, non-coding RNA molecules. They are involved in virtually every cellular process including development1, apoptosis2, and cell cycle regulation3. MiRNAs are estimated to regulate the expression of 30% to 90% of human genes4 by binding to their target messenger RNAs (mRNAs)5. Widespread dysregulation of miRNAs has been reported in various diseases and cancer subtypes6. Due to their prevalence and unique structure, these small molecules are likely to be the next generation of biomarkers, therapeutic agents and/or targets. Methods used to investigate miRNA expression include SYBR green I dye- based as well as Taqman-probe based qPCR. If miRNAs are to be effectively used in the clinical setting, it is imperative that their detection in fresh and/or archived clinical samples be accurate, reproducible, and specific. qPCR has been widely used for validating expression of miRNAs in whole genome analyses such as microarray studies7. The samples used in this protocol were from patients who underwent radical prostatectomy for clinically localized prostate cancer; however other tissues and cell lines can be substituted in. Prostate specimens were snap-frozen in liquid nitrogen after resection. Clinical variables and follow-up information for each patient were collected for subsequent analysis8. Quantification of miRNA levels in prostate tumor samples. The main steps in qPCR analysis of tumors are: Total RNA extraction, cDNA synthesis, and detection of qPCR products using miRNA-specific primers. Total RNA, which includes mRNA, miRNA, and other small RNAs were extracted from specimens using TRIzol reagent. Qiagen's miScript System was used to synthesize cDNA and perform qPCR (Figure 1). Endogenous miRNAs are not polyadenylated, therefore during the reverse transcription process, a poly(A) polymerase polyadenylates the miRNA. The miRNA is used as a template to synthesize cDNA using oligo-dT and Reverse Transcriptase. A universal tag sequence on the 5' end of oligo-dT primers facilitates the amplification of cDNA in the PCR step. PCR product amplification is detected by the level of fluorescence emitted by SYBR Green, a dye which intercalates into double stranded DNA. Specific miRNA primers, along with a Universal Primer that binds to the universal tag sequence will amplify specific miRNA sequences. The miScript Primer Assays are available for over a thousand human-specific miRNAs, and hundreds of murine-specific miRNAs. Relative quantification method was used here to quantify the expression of miRNAs. To correct for variability amongst different samples, expression levels of a target miRNA is normalized to the expression levels of a reference gene. The choice of a gene on which to normalize the expression of targets is critical in relative quantification method of analysis. Examples of reference genes typically used in this capacity are the small RNAs RNU6B, RNU44, and RNU48 as they are considered to be stably expressed across most samples. In this protocol, RNU6B is used as the reference gene.
Cancer Biology, Issue 63, Medicine, cancer, primer assay, Prostate, microRNA, tumor, qPCR
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Telomere Length and Telomerase Activity; A Yin and Yang of Cell Senescence
Authors: Mary Derasmo Axelrad, Temuri Budagov, Gil Atzmon.
Institutions: Albert Einstein College of Medicine , Albert Einstein College of Medicine , Albert Einstein College of Medicine .
Telomeres are repeating DNA sequences at the tip ends of the chromosomes that are diverse in length and in humans can reach a length of 15,000 base pairs. The telomere serves as a bioprotective mechanism of chromosome attrition at each cell division. At a certain length, telomeres become too short to allow replication, a process that may lead to chromosome instability or cell death. Telomere length is regulated by two opposing mechanisms: attrition and elongation. Attrition occurs as each cell divides. In contrast, elongation is partially modulated by the enzyme telomerase, which adds repeating sequences to the ends of the chromosomes. In this way, telomerase could possibly reverse an aging mechanism and rejuvenates cell viability. These are crucial elements in maintaining cell life and are used to assess cellular aging. In this manuscript we will describe an accurate, short, sophisticated and cheap method to assess telomere length in multiple tissues and species. This method takes advantage of two key elements, the tandem repeat of the telomere sequence and the sensitivity of the qRT-PCR to detect differential copy numbers of tested samples. In addition, we will describe a simple assay to assess telomerase activity as a complementary backbone test for telomere length.
Genetics, Issue 75, Molecular Biology, Cellular Biology, Medicine, Biomedical Engineering, Genomics, Telomere length, telomerase activity, telomerase, telomeres, telomere, DNA, PCR, polymerase chain reaction, qRT-PCR, sequencing, aging, telomerase assay
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Purification and microRNA Profiling of Exosomes Derived from Blood and Culture Media
Authors: Marguerite K. McDonald, Kathryn E. Capasso, Seena K. Ajit.
Institutions: Drexel University College of Medicine.
Stable miRNAs are present in all body fluids and some circulating miRNAs are protected from degradation by sequestration in small vesicles called exosomes. Exosomes can fuse with the plasma membrane resulting in the transfer of RNA and proteins to the target cell. Their biological functions include immune response, antigen presentation, and intracellular communication. Delivery of miRNAs that can regulate gene expression in the recipient cells via blood has opened novel avenues for target intervention. In addition to offering a strategy for delivery of drugs or RNA therapeutic agents, exosomal contents can serve as biomarkers that can aid in diagnosis, determining treatment options and prognosis. Here we will describe the procedure for quantitatively analyzing miRNAs and messenger RNAs (mRNA) from exosomes secreted in blood and cell culture media. Purified exosomes will be characterized using western blot analysis for exosomal markers and PCR for mRNAs of interest. Transmission electron microscopy (TEM) and immunogold labeling will be used to validate exosomal morphology and integrity. Total RNA will be purified from these exosomes to ensure that we can study both mRNA and miRNA from the same sample. After validating RNA integrity by Bioanalyzer, we will perform a medium throughput quantitative real time PCR (qPCR) to identify the exosomal miRNA using Taqman Low Density Array (TLDA) cards and gene expression studies for transcripts of interest. These protocols can be used to quantify changes in exosomal miRNAs in patients, rodent models and cell culture media before and after pharmacological intervention. Exosomal contents vary due to the source of origin and the physiological conditions of cells that secrete exosomes. These variations can provide insight on how cells and systems cope with stress or physiological perturbations. Our representative data show variations in miRNAs present in exosomes purified from mouse blood, human blood and human cell culture media. Here we will describe the procedure for quantitatively analyzing miRNAs and messenger RNAs (mRNA) from exosomes secreted in blood and cell culture media. Purified exosomes will be characterized using western blot analysis for exosomal markers and PCR for mRNAs of interest. Transmission electron microscopy (TEM) and immunogold labeling will be used to validate exosomal morphology and integrity. Total RNA will be purified from these exosomes to ensure that we can study both mRNA and miRNA from the same sample. After validating RNA integrity by Bioanalyzer, we will perform a medium throughput quantitative real time PCR (qPCR) to identify the exosomal miRNA using Taqman Low Density Array (TLDA) cards and gene expression studies for transcripts of interest. These protocols can be used to quantify changes in exosomal miRNAs in patients, rodent models and cell culture media before and after pharmacological intervention. Exosomal contents vary due to the source of origin and the physiological conditions of cells that secrete exosomes. These variations can provide insight on how cells and systems cope with stress or physiological perturbations. Our representative data show variations in miRNAs present in exosomes purified from mouse blood, human blood and human cell culture media
Genetics, Issue 76, Molecular Biology, Cellular Biology, Medicine, Biochemistry, Genomics, Pharmacology, Exosomes, RNA, MicroRNAs, Biomarkers, Pharmacological, Exosomes, microRNA, qPCR, PCR, blood, biomarker, TLDA, profiling, sequencing, cell culture
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
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Basics of Multivariate Analysis in Neuroimaging Data
Authors: Christian Georg Habeck.
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
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Interview: Glycolipid Antigen Presentation by CD1d and the Therapeutic Potential of NKT cell Activation
Authors: Mitchell Kronenberg.
Institutions: La Jolla Institute for Allergy and Immunology.
Natural Killer T cells (NKT) are critical determinants of the immune response to cancer, regulation of autioimmune disease, clearance of infectious agents, and the development of artheriosclerotic plaques. In this interview, Mitch Kronenberg discusses his laboratory's efforts to understand the mechanism through which NKT cells are activated by glycolipid antigens. Central to these studies is CD1d - the antigen presenting molecule that presents glycolipids to NKT cells. The advent of CD1d tetramer technology, a technique developed by the Kronenberg lab, is critical for the sorting and identification of subsets of specific glycolipid-reactive T cells. Mitch explains how glycolipid agonists are being used as therapeutic agents to activate NKT cells in cancer patients and how CD1d tetramers can be used to assess the state of the NKT cell population in vivo following glycolipid agonist therapy. Current status of ongoing clinical trials using these agonists are discussed as well as Mitch's prediction for areas in the field of immunology that will have emerging importance in the near future.
Immunology, Issue 10, Natural Killer T cells, NKT cells, CD1 Tetramers, antigen presentation, glycolipid antigens, CD1d, Mucosal Immunity, Translational Research
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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