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NOVA: a software to analyze complexome profiling data.
Bioinformatics
PUBLISHED: 10-09-2014
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We introduce nova, a software for the analysis of complexome profiling data. nova supports the investigation of the composition of complexes, cluster analysis of the experimental data, visual inspection and comparison of experiments and many other features. Availability and implementation: nova is licensed under the Artistic License 2.0. It is freely available at http://www.bioinformatik.uni-frankfurt.de. nova requires at least Java 7 and runs under Linux, Microsoft Windows and Mac OS.
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Genome scale modeling in systems biology: algorithms and resources.
Curr. Genomics
PUBLISHED: 02-16-2014
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In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics.
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APADB: a database for alternative polyadenylation and microRNA regulation events.
Database (Oxford)
PUBLISHED: 01-01-2014
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Alternative polyadenylation (APA) is a widespread mechanism that contributes to the sophisticated dynamics of gene regulation. Approximately 50% of all protein-coding human genes harbor multiple polyadenylation (PA) sites; their selective and combinatorial use gives rise to transcript variants with differing length of their 3' untranslated region (3'UTR). Shortened variants escape UTR-mediated regulation by microRNAs (miRNAs), especially in cancer, where global 3'UTR shortening accelerates disease progression, dedifferentiation and proliferation. Here we present APADB, a database of vertebrate PA sites determined by 3' end sequencing, using massive analysis of complementary DNA ends. APADB provides (A)PA sites for coding and non-coding transcripts of human, mouse and chicken genes. For human and mouse, several tissue types, including different cancer specimens, are available. APADB records the loss of predicted miRNA binding sites and visualizes next-generation sequencing reads that support each PA site in a genome browser. The database tables can either be browsed according to organism and tissue or alternatively searched for a gene of interest. APADB is the largest database of APA in human, chicken and mouse. The stored information provides experimental evidence for thousands of PA sites and APA events. APADB combines 3' end sequencing data with prediction algorithms of miRNA binding sites, allowing to further improve prediction algorithms. Current databases lack correct information about 3'UTR lengths, especially for chicken, and APADB provides necessary information to close this gap. Database URL: http://tools.genxpro.net/apadb/.
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omiRas: a Web server for differential expression analysis of miRNAs derived from small RNA-Seq data.
Bioinformatics
PUBLISHED: 08-13-2013
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Small RNA deep sequencing is widely used to characterize non-coding RNAs (ncRNAs) differentially expressed between two conditions, e.g. healthy and diseased individuals and to reveal insights into molecular mechanisms underlying condition-specific phenotypic traits. The ncRNAome is composed of a multitude of RNAs, such as transfer RNA, small nucleolar RNA and microRNA (miRNA), to name few. Here we present omiRas, a Web server for the annotation, comparison and visualization of interaction networks of ncRNAs derived from next-generation sequencing experiments of two different conditions. The Web tool allows the user to submit raw sequencing data and results are presented as: (i) static annotation results including length distribution, mapping statistics, alignments and quantification tables for each library as well as lists of differentially expressed ncRNAs between conditions and (ii) an interactive network visualization of user-selected miRNAs and their target genes based on the combination of several miRNA-mRNA interaction databases.
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Interleukin-22 is frequently expressed in small- and large-cell lung cancer and promotes growth in chemotherapy-resistant cancer cells.
J Thorac Oncol
PUBLISHED: 06-19-2013
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In lung cancer, interleukin-22 (IL-22) expression within primary tissue has been demonstrated, but the frequency and the functional consequence of IL-22 signaling have not been addressed. This study aims at analyzing the cellular effects of IL-22 on lung carcinoma cell lines and the prognostic impact of IL-22 tissue expression in lung cancer patients.
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MonaLisa--visualization and analysis of functional modules in biochemical networks.
Bioinformatics
PUBLISHED: 04-05-2013
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Structural modeling of biochemical networks enables qualitative as well as quantitative analysis of those networks. Automated network decomposition into functional modules is a crucial point in network analysis. Although there exist approaches for the analysis of networks, there is no open source tool available that combines editing, visualization and the computation of steady-state functional modules. We introduce a new tool called MonaLisa, which combines computation and visualization of functional modules as well as an editor for biochemical Petri nets. The analysis techniques allow for network decomposition into functional modules, for example t-invariants (elementary modes), maximal common transition sets, minimal cut sets and t-clusters. The graphical user interface provides various functionalities to construct and modify networks as well as to visualize the results of the analysis. Availability and implementation: MonaLisa is licensed under the Artistic License 2.0. It is freely available at http://www.bioinformatik.uni-frankfurt.de/software.html. MonaLisa requires at least Java 6 and runs under Linux, Microsoft Windows and Mac OS.
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Image database analysis of Hodgkin lymphoma.
Comput Biol Chem
PUBLISHED: 03-21-2013
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Hodgkin lymphoma (HL) is a special type of B cell lymphoma, arising from germinal center B-cells. Morphological and immunohistochemical features of HL as well as the spatial distribution of malignant cells differ from other lymphoma and cancer types. Sophisticated protocols for immunostaining and the acquisition of high-resolution images become routine in pathological labs. Large and daily growing databases of high-resolution digital images are currently emerging. A systematic tissue image analysis and computer-aided exploration may provide new insights into HL pathology. The automated analysis of high resolution images, however, is a hard task in terms of required computing time and memory. Special concepts and pipelines for analyzing high-resolution images can boost the exploration of image databases. In this paper, we report an analysis of digital color images recorded in high-resolution of HL tissue slides. Applying a protocol of CD30 immunostaining to identify malignant cells, we implement a pipeline to handle and explore image data of stained HL tissue images. To the best of our knowledge, this is the first systematic application of image analysis to HL tissue slides. To illustrate the concept and methods we analyze images of two different HL types, nodular sclerosis and mixed cellularity as the most common forms and reactive lymphoid tissue for comparison. We implemented a pipeline which is adapted to the special requirements of whole slide images of HL tissue and identifies relevant regions that contain malignant cells. Using a preprocessing approach, we separate the relevant tissue region from the background. We assign pixels in the images to one of the six predefined classes: Hematoxylin(+), CD30(+), Nonspecific red, Unstained, Background, and Low intensity, applying a supervised recognition method. Local areas with pixels assigned to the class CD30(+) identify regions of interest. As expected, an increased amount of CD30(+) pixels is a characteristic feature of nodular sclerosis, and the non-lymphoma cases show a characteristically low amount of CD30(+) stain. Images of mixed cellularity samples include cases of high CD30(+) coloring as well as cases of low CD30(+) coloring.
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Hierarchical representation of supersecondary structures using a graph-theoretical approach.
Methods Mol. Biol.
PUBLISHED: 02-01-2013
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The unique representation of proteins becomes more and more important with the growing number of known protein structure data. Graph-theory provides many methods not only for the description but also for comparison and classification of protein structures. Here, we describe a graph-theoretical modeling approach of the protein supersecondary structure. The resulting linear notations are intuitive and can be used to find common substructures very fast and easily. We illustrate the necessary definitions by biological examples and discuss the representation of various supersecondary structure motifs.
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A Genome-Wide Longitudinal Transcriptome Analysis of the Aging Model Podospora anserine.
PLoS ONE
PUBLISHED: 01-01-2013
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Aging of biological systems is controlled by various processes which have a potential impact on gene expression. Here we report a genome-wide transcriptome analysis of the fungal aging model Podospora anserina. Total RNA of three individuals of defined age were pooled and analyzed by SuperSAGE (serial analysis of gene expression). A bioinformatics analysis identified different molecular pathways to be affected during aging. While the abundance of transcripts linked to ribosomes and to the proteasome quality control system were found to decrease during aging, those associated with autophagy increase, suggesting that autophagy may act as a compensatory quality control pathway. Transcript profiles associated with the energy metabolism including mitochondrial functions were identified to fluctuate during aging. Comparison of wild-type transcripts, which are continuously down-regulated during aging, with those down-regulated in the long-lived, copper-uptake mutant grisea, validated the relevance of age-related changes in cellular copper metabolism. Overall, we (i) present a unique age-related data set of a longitudinal study of the experimental aging model P. anserina which represents a reference resource for future investigations in a variety of organisms, (ii) suggest autophagy to be a key quality control pathway that becomes active once other pathways fail, and (iii) present testable predictions for subsequent experimental investigations.
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QuateXelero: an accelerated exact network motif detection algorithm.
PLoS ONE
PUBLISHED: 01-01-2013
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Finding motifs in biological, social, technological, and other types of networks has become a widespread method to gain more knowledge about these networks structure and function. However, this task is very computationally demanding, because it is highly associated with the graph isomorphism which is an NP problem (not known to belong to P or NP-complete subsets yet). Accordingly, this research is endeavoring to decrease the need to call NAUTY isomorphism detection method, which is the most time-consuming step in many existing algorithms. The work provides an extremely fast motif detection algorithm called QuateXelero, which has a Quaternary Tree data structure in the heart. The proposed algorithm is based on the well-known ESU (FANMOD) motif detection algorithm. The results of experiments on some standard model networks approve the overal superiority of the proposed algorithm, namely QuateXelero, compared with two of the fastest existing algorithms, G-Tries and Kavosh. QuateXelero is especially fastest in constructing the central data structure of the algorithm from scratch based on the input network.
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Multiplex profiling of cellular invasion in 3D cell culture models.
PLoS ONE
PUBLISHED: 01-01-2013
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To-date, most invasion or migration assays use a modified Boyden chamber-like design to assess migration as single-cell or scratch assays on coated or uncoated planar plastic surfaces. Here, we describe a 96-well microplate-based, high-content, three-dimensional cell culture assay capable of assessing invasion dynamics and molecular signatures thereof. On applying our invasion assay, we were able to demonstrate significant effects on the invasion capacity of fibroblast cell lines, as well as primary lung fibroblasts. Administration of epidermal growth factor resulted in a substantial increase of cellular invasion, thus making this technique suitable for high-throughput pharmacological screening of novel compounds regulating invasive and migratory pathways of primary cells. Our assay also correlates cellular invasiveness to molecular events. Thus, we argue of having developed a powerful and versatile toolbox for an extensive profiling of invasive cells in a 96-well format. This will have a major impact on research in disease areas like fibrosis, metastatic cancers, or chronic inflammatory states.
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Gli1 mediates lung cancer cell proliferation and Sonic Hedgehog-dependent mesenchymal cell activation.
PLoS ONE
PUBLISHED: 01-01-2013
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Non-Small-Cell-Lung-Cancer (NSCLC) represents approximately 85% of all lung cancers and remains poorly understood. While signaling pathways operative during organ development, including Sonic Hedgehog (Shh) and associated Gli transcription factors (Gli1-3), have recently been found to be reactivated in NSCLC, their functional role remains unclear. Here, we hypothesized that Shh/Gli1-3 could mediate NSCLC autonomous proliferation and epithelial/stromal signaling in the tumoral tissue. In this context, we have investigated the activity of Shh/Gli1-3 signaling in NSCLC in both, cancer and stromal cells. We report here that inhibition of Shh signaling induces a significant decrease in the proliferation of NSCLC cells. This effect is mediated by Gli1 and Gli2, but not Gli3, through regulation of cyclin D1 and cyclin D2 expression. While exogenous Shh was unable to induce signaling in either A549 lung adenocarcinoma or H520 lung squamous carcinoma cells, both cells were found to secrete Shh ligand, which induced fibroblast proliferation, survival, migration, invasion, and collagen synthesis. Furthermore, Shh secreted by NSCLC mediates the production of proangiogenic and metastatic factors in lung fibroblasts. Our results thus provide evidence that Shh plays an important role in mediating epithelial/mesenchymal crosstalk in NSCLC. While autonomous Gli activity controls NSCLC proliferation, increased Shh expression by NSCLC is associated with fibroblast activation in tumor-associated stroma. Our study highlights the relevance of studying stromal-associated cells in the context of NSCLC regarding new prognosis and therapeutic options.
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Exhaustive analysis of the modular structure of the spliceosomal assembly network: a petri net approach.
Stud Health Technol Inform
PUBLISHED: 06-21-2011
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Spliceosomes are macro-complexes involving hundreds of proteins with many functional interactions. Spliceosome assembly belongs to the key processes that enable splicing of mRNA and modulate alternative splicing. A detailed list of factors involved in spliceosomal reactions has been assorted over the past decade, but, their functional interplay is often unknown and most of the present biological models cover only parts of the complete assembly process. It is a challenging task to build a computational model that integrates dispersed knowledge and combines a multitude of reaction schemes proposed earlier. Because for most reactions involved in spliceosome assembly kinetic parameters are not available, we propose a discrete modeling using Petri nets, through which we are enabled to get insights into the systems behavior via computation of structural and dynamic properties. In this paper, we compile and examine reactions from experimental reports that contribute to a functional spliceosome. All these reactions form a network, which describes the inventory and conditions necessary to perform the splicing process. The analysis is mainly based on system invariants. Transition invariants (T-invariants) can be interpreted as signaling routes through the network. Due to the huge number of T-invariants that arise with increasing network size and complexity, maximal common transition sets (MCTS) and T-clusters were used for further analysis. Additionally, we introduce a false color map representation, which allows a quick survey of network modules and the visual detection of single reactions or reaction sequences, which participate in more than one signaling route. We designed a structured model of spliceosome assembly, which combines the demands on a platform that i) can display involved factors and concurrent processes, ii) offers the possibility to run computational methods for knowledge extraction, and iii) is successively extendable as new insights into spliceosome function are reported by experimental reports. The network consists of 161 transitions (reactions) and 140 places (reactants). All reactions are part of at least one of the 71 T-invariants. These T-invariants define pathways, which are in good agreement with the current knowledge and known hypotheses on reaction sequences during spliceosome assembly, hence contributing to a functional spliceosome. We demonstrate that present knowledge, in particular of the initial part of the assembly process, describes parallelism and interaction of signaling routes, which indicate functional redundancy and reflect the dependency of spliceosome assembly initiation on different cellular conditions. The complexity of the network is further increased by two switches, which introduce alternative routes during A-complex formation in early spliceosome assembly and upon transition from the B-complex to the C-complex. By compiling known reactions into a complete network, the combinatorial nature of invariant computation leads to pathways that have previously not been described as connected routes, although their constituents were known. T-clusters divide the network into modules, which we interpret as building blocks in spliceosome maturation. We conclude that Petri net representations of large biological networks and system invariants, are well-suited as a means for validating the integration of experimental knowledge into a consistent model. Based on this network model, the design of further experiments is facilitated.
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STEPP - Search Tool for Exploration of Petri net Paths: A New Tool for Petri Net-Based Path Analysis in Biochemical Networks.
Stud Health Technol Inform
PUBLISHED: 06-21-2011
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To understand biochemical processes caused by, e.g., mutations or deletions in the genome, the knowledge of possible alternative paths between two arbitrary chemical compounds is of increasing interest for biotechnology, pharmacology, medicine, and drug design. With the steadily increasing amount of data from high-throughput experiments new biochemical networks can be constructed and existing ones can be extended, which results in many large metabolic, signal transduction, and gene regulatory networks. The search for alternative paths within these complex and large networks can provide a huge amount of solutions, which can not be handled manually. Moreover, not all of the alternative paths are generally of interest. Therefore, we have developed and implemented a method, which allows us to define constraints to reduce the set of all structurally possible paths to the truly interesting path set. The paper describes the search algorithm and the constraints definition language. We give examples for path searches using this dedicated special language for a Petri net model of the sucrose-to-starch breakdown in the potato tuber. Availability: http://sanaga.tfh-berlin.de/~stepp/
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Petri nets for steady state analysis of metabolic systems.
Stud Health Technol Inform
PUBLISHED: 06-21-2011
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Computer assisted analysis and simulation of biochemical pathways can improve the understanding of the structure and the dynamics of cell processes considerably. The construction and quantitative analysis of kinetic models is often impeded by the lack of reliable data. However, as the topological structure of biochemical systems can be regarded to remain constant in time, a qualitative analysis of a pathway model was shown to be quite promising as it can render a lot of useful knowledge, e. g., about its structural invariants. The topic of this paper are pathways whose substances have reached a dynamic concentration equilibrium (steady state). It is argued that appreciated tools from biochemistry and also low-level Petri nets can yield only part of the desired results, whereas executable high-level net models lead to a number of valuable additional insights by combining symbolic analysis and simulation.
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ADAM17 regulates epidermal growth factor receptor expression through the activation of Notch1 in non-small cell lung cancer.
Cancer Res.
PUBLISHED: 06-15-2010
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Epidermal growth factor receptor (EGFR) overexpression and activation are hallmarks of non-small cell lung carcinoma (NSCLC). Although EGFR-targeted therapies are used, the prognosis of NSCLC remains poor. ADAM17 induces activation of the EGFR through ligand cleavage. However, we show that inhibition or knockdown of ADAM17 markedly reduces tumorigenesis and survival to a large part independently from EGFR ligand shedding in NSCLC cells. These findings strongly indicate additional oncogenic mechanisms regulated by ADAM17. We identified Notch1 signaling as an ADAM17-controlled pathway and a critical regulator of anchorage-independent growth by using both Notch1 shRNA and ectopic expression of the active intracellular Notch1 fragment. Strikingly, Notch1 knockdown led to a strong reduction of EGFR expression in all analyzed cell lines. Proliferation, survival, and colony formation of Notch1-deficient cells were insensitive to EGF stimulation. Moreover, targeting Notch1 or ADAM17 resulted in substantial cell death, whereas EGFR inhibition predominantly induced cell cycle arrest. Immunohistochemical analysis of primary human tissue revealed a significant correlation between ADAM17, Notch1 signaling, and high EGFR expression levels. In conclusion, this article describes a novel molecular circuitry in NSCLC, incorporating ADAM17 as a regulator of EGFR expression through the activation of Notch1. Due to their central role in tumorigenesis and survival of NSCLC cells, both ADAM17 and Notch1 constitute promising targets for the treatment of NSCLC.
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PTGL: a database for secondary structure-based protein topologies.
Nucleic Acids Res.
PUBLISHED: 11-11-2009
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With growing amount of experimental data, the number of known protein structures also increases continuously. Classification of protein structures helps to understand relationships between protein structure and function. The main classification methods based on secondary structures are SCOP, CATH and TOPS, which all classify under different aspects, and therefore can lead to different results. We developed a mathematically unique representation of protein structure topologies at a higher abstraction level providing new aspects of classification and enabling for a fast search through the data. Protein Topology Graph Library (PTGL; http://ptgl.zib.de) aims at providing a database on protein secondary structure topologies, including search facilities, the visualization as intuitive topology diagrams as well as in the 3D structure, and additional information. Secondary structure-based protein topologies are represented uniquely as undirected labeled graphs in four different ways allowing for exploration under different aspects. The linear notations, and the 2D and 3D diagrams of each notation facilitate a deeper understanding of protein topologies. Several search functions for topologies and sub-topologies, BLAST search possibility, and links to SCOP, CATH and PDBsum support individual and large-scale investigation of protein structures. Currently, PTGL comprises topologies of 54,859 protein structures. Main structural patterns for common structural motifs like TIM-barrel or Jelly Roll are pre-implemented, and can easily be searched.
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Efficient shRNA delivery into B and T lymphoma cells using lentiviral vector-mediated transfer.
J Hematop
PUBLISHED: 08-12-2009
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RNA interference is a powerful tool for the functional analysis of proteins by specific gene knockdown. In this study, we devised a rapid and efficient way to screen suitable siRNA sequences and subsequently employ them for specific gene knockdown in usually hard-to-transfect lymphoid cell lines, using a self-inactivating lentiviral vector. Two proteins with different half-lives were chosen, cyclin D1 and STAT3. A specific lacZ reporter fusion assay was used to identify highly effective siRNA sequences. Only siRNA molecules with more than 85% of knockdown efficiency were selected for the generation of lentiviral transfer vectors. Transduction rates of 75-99% were achieved in the lymphoma cell lines Granta 519 (mantle cell lymphoma), Karpas 299, and SUDHL-1 (anaplastic large T cell lymphoma), as demonstrated by green fluorescent protein expression in fluorescence-activated cell sorting analysis. The high level of transduction efficiency allows RNA interference studies to be performed on transduced cells without further manipulation, such as cell sorting or cloning. The LacZ reporter system together with the lentivirus technology is a very important tool in the hematology field, which enables experiments in lymphoid cells that were not possible before.
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Differential diagnosis of cyclin D2+ mantle cell lymphoma based on fluorescence in situ hybridization and quantitative real-time-PCR.
Haematologica
PUBLISHED: 07-16-2009
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Mantle cell lymphoma is characterized by the t(11;14) chromosomal translocation, resulting in the overexpression of cyclin D1 (CycD1). Recently, cases of mantle cell lymphoma negative for cycD1 but positive for cycD2 or cycD3 were identified by gene expression profiling and confirmed by immunohistochemistry. We analyzed 4 cases of cycD2(+) mantle cell lymphoma with a translocation involving the CCND2 locus, and its differential diagnosis from 35 mature B-cell non-Hodgkins lymphomas based on immunohistochemistry, quantitative RT-PCR and FISH analysis. Bona fide cycD2(+) mantle cell lymphoma carried translocations involving the CCND2 gene, and IGH and IGK loci were identified as partners. As a result of this translocation, cycD2 mRNA was highly over-expressed when compared with normal lymphoid tissue and other B-cell non-Hodgkins lymphomas, including chronic lymphocytic leukemia, making this technique ideally suited to identify cycD2(+)mantle cell lymphoma. In contrast, positive immunostaining for cycD2 was found in most B-cell non-Hodgkins lymphomas, and therefore, it is not specific for a diagnosis of cycD2(+)mantle cell lymphoma.
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Complexome profiling identifies TMEM126B as a component of the mitochondrial complex I assembly complex.
Cell Metab.
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Macromolecular complexes are essential players in numerous biological processes. They are often large, dynamic, and rather labile; approaches to study them are scarce. Covering masses up to ?30 MDa, we separated the native complexome of rat heart mitochondria by blue-native and large-pore blue-native gel electrophoresis to analyze its constituents by mass spectrometry. Similarities in migration patterns allowed hierarchical clustering into interaction profiles representing a comprehensive analysis of soluble and membrane-bound complexes of an entire organelle. The power of this bottom-up approach was validated with well-characterized mitochondrial multiprotein complexes. TMEM126B was found to comigrate with known assembly factors of mitochondrial complex I, namely CIA30, Ecsit, and Acad9. We propose terming this complex mitochondrial complex I assembly (MCIA) complex. Furthermore, we demonstrate that TMEM126B is required for assembly of complex I. In summary, complexome profiling is a powerful and unbiased technique allowing the identification of previously overlooked components of large multiprotein complexes.
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The impact of cyclin D1 mRNA isoforms, morphology and p53 in mantle cell lymphoma: p53 alterations and blastoid morphology are strong predictors of a high proliferation index.
Haematologica
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Mantle cell lymphoma is a clinically heterogeneous disease characterized by overexpression of cyclin D1 protein. Blastoid morphology, high proliferation, and secondary genetic aberrations are markers of aggressive behavior. Expression profiling of mantle cell lymphoma revealed that predominance of the 3UTR-deficient, short cyclin D1 mRNA isoform was associated with high cyclin D1 levels, a high "proliferation signature" and poor prognosis.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.