TY - JOUR A1 - Morton, Charles Oliver A1 - Fliesser, Mirjam A1 - Dittrich, Marcus A1 - Müller, Tobias A1 - Bauer, Ruth A1 - Kneitz, Susanne A1 - Hope, William A1 - Rogers, Thomas Richard A1 - Einsele, Hermann A1 - Löffler, Jürgen T1 - Gene Expression Profiles of Human Dendritic Cells Interacting with Aspergillus fumigatus in a Bilayer Model of the Alveolar Epithelium/Endothelium Interface N2 - The initial stages of the interaction between the host and Aspergillus fumigatus at the alveolar surface of the human lung are critical in the establishment of aspergillosis. Using an in vitro bilayer model of the alveolus, including both the epithelium (human lung adenocarcinoma epithelial cell line, A549) and endothelium (human pulmonary artery epithelial cells, HPAEC) on transwell membranes, it was possible to closely replicate the in vivo conditions. Two distinct sub-groups of dendritic cells (DC), monocyte-derived DC (moDC) and myeloid DC (mDC), were included in the model to examine immune responses to fungal infection at the alveolar surface. RNA in high quantity and quality was extracted from the cell layers on the transwell membrane to allow gene expression analysis using tailored custom-made microarrays, containing probes for 117 immune-relevant genes. This microarray data indicated minimal induction of immune gene expression in A549 alveolar epithelial cells in response to germ tubes of A. fumigatus. In contrast, the addition of DC to the system greatly increased the number of differentially expressed immune genes. moDC exhibited increased expression of genes including CLEC7A, CD209 and CCL18 in the absence of A. fumigatus compared to mDC. In the presence of A. fumigatus, both DC subgroups exhibited up-regulation of genes identified in previous studies as being associated with the exposure of DC to A. fumigatus and exhibiting chemotactic properties for neutrophils, including CXCL2, CXCL5, CCL20, and IL1B. This model closely approximated the human alveolus allowing for an analysis of the host pathogen interface that complements existing animal models of IA. KW - aspergillus fumigatus KW - gene expression KW - immune receptors KW - immune response KW - denritic cells KW - B cell receptors KW - gene regulation KW - RNA extraction Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-112893 ER - TY - JOUR A1 - Schul, Daniela A1 - Schmitt, Alexandra A1 - Regneri, Janine A1 - Schartl, Manfred A1 - Wagner, Toni Ulrich T1 - Bursted BMP Triggered Receptor Kinase Activity Drives Smad1 Mediated Long-Term Target Gene Oscillation in c2c12 Cells JF - PLoS ONE N2 - Bone Morphogenetic Proteins (BMPs) are important growth factors that regulate many cellular processes. During embryogenesis they act as morphogens and play a critical role during organ development. They influence cell fates via concentration-gradients in the embryos where cells transduce this extracellular information into gene expression profiles and cell fate decisions. How receiving cells decode and quantify BMP2/4 signals is hardly understood. There is little data on the quantitative relationships between signal input, transducing molecules, their states and location, and ultimately their ability to integrate graded systemic inputs and generate qualitative responses. Understanding this signaling network on a quantitative level should be considered a prerequisite for efficient pathway modulation, as the BMP pathway is a prime target for therapeutic invention. Hence, we quantified the spatial distribution of the main signal transducer of the BMP2/4 pathway in response to different types and levels of stimuli in c2c12 cells. We found that the subcellular localization of Smad1 is independent of ligand concentration. In contrast, Smad1 phosphorylation levels relate proportionally to BMP2 ligand concentrations and they are entirely located in the nucleus. Interestingly, we found that BMP2 stimulates target gene expression in non-linear, wave-like forms. Amplitudes showed a clear concentration-dependency, for sustained and transient stimulation. We found that even burst-stimulation triggers gene-expression wave-like modulations that are detectable for at least 30 h. Finally, we show here that target gene expression oscillations depend on receptor kinase activity, as the kinase drives further expression pulses without receptor reactivation and the target gene expression breaks off after inhibitor treatment in c2c12 cells. KW - gene expression KW - BMP signaling KW - SMAD signaling KW - genetic oscillators KW - cell fusion KW - DNA-binding proteins KW - luciferase KW - kinase inhibitors Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-130131 VL - 8 IS - 4 ER - TY - JOUR A1 - Wolf, Annette A1 - Akrap, Nina A1 - Marg, Berenice A1 - Galliardt, Helena A1 - Heiligentag, Martyna A1 - Humpert, Fabian A1 - Sauer, Markus A1 - Kaltschmidt, Barbara A1 - Kaltschmidt, Christian A1 - Seidel, Thorsten T1 - Elements of Transcriptional Machinery Are Compatible among Plants and Mammals JF - PLoS ONE N2 - In the present work, the objective has been to analyse the compatibility of plant and human transcriptional machinery. The experiments revealed that nuclear import and export are conserved among plants and mammals. Further it has been shown that transactivation of a human promoter occurs by human transcription factor NF-\(\kappa\) B in plant cells, demonstrating that the transcriptional machinery is highly conserved in both kingdoms. Functionality was also seen for regulatory elements of NF-\(\kappa\) B such as its inhibitor I\(\kappa\)B isoform \(\alpha\) that negatively regulated the transactivation activity of the p50/RelA heterodimer by interaction with NF-\(\kappa\)B in plant cells. Nuclear export of RelA could be demonstrated by FRAP-measurements so that RelA shows nucleo-cytoplasmic shuttling as reported for RelA in mammalian cells. The data reveals the high level of compatibility of human transcriptional elements with the plant transcriptional machinery. Thus, Arabidopsis thaliana mesophyll protoplasts might provide a new heterologous expression system for the investigation of the human NF-\(\kappa\)B signaling pathways. The system successfully enabled the controlled manipulation of NF-\(\kappa\)B activity. We suggest the plant protoplast system as a tool for reconstitution and analyses of mammalian pathways and for direct observation of responses to e. g. pharmaceuticals. The major advantage of the system is the absence of interference with endogenous factors that affect and crosstalk with the pathway. KW - complexes KW - in vivo KW - DNA-binding KW - nuclear proe KW - gene expression KW - NF-KAPPA-B KW - RNA-binding protein KW - alpha KW - inflammation KW - homodimers Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-131203 VL - 8 IS - 1 ER - TY - JOUR A1 - Buchner, Erich A1 - Blanco Redondo, Beatriz A1 - Bunz, Melanie A1 - Halder, Partho A1 - Sadanandappa, Madhumala K. A1 - Mühlbauer, Barbara A1 - Erwin, Felix A1 - Hofbauer, Alois A1 - Rodrigues, Veronica A1 - VijayRaghavan, K. A1 - Ramaswami, Mani A1 - Rieger, Dirk A1 - Wegener, Christian A1 - Förster, Charlotte T1 - Identification and Structural Characterization of Interneurons of the Drosophila Brain by Monoclonal Antibodies of the Würzburg Hybridoma Library JF - PLoS ONE N2 - Several novel synaptic proteins have been identified by monoclonal antibodies (mAbs) of the Würzburg hybridoma library generated against homogenized Drosophila brains, e.g. cysteine string protein, synapse-associated protein of 47 kDa, and Bruchpilot. However, at present no routine technique exists to identify the antigens of mAbs of our library that label only a small number of cells in the brain. Yet these antibodies can be used to reproducibly label and thereby identify these cells by immunohistochemical staining. Here we describe the staining patterns in the Drosophila brain for ten mAbs of the Würzburg hybridoma library. Besides revealing the neuroanatomical structure and distribution of ten different sets of cells we compare the staining patterns with those of antibodies against known antigens and GFP expression patterns driven by selected Gal4 lines employing regulatory sequences of neuronal genes. We present examples where our antibodies apparently stain the same cells in different Gal4 lines suggesting that the corresponding regulatory sequences can be exploited by the split-Gal4 technique for transgene expression exclusively in these cells. The detection of Gal4 expression in cells labeled by mAbs may also help in the identification of the antigens recognized by the antibodies which then in addition to their value for neuroanatomy will represent important tools for the characterization of the antigens. Implications and future strategies for the identification of the antigens are discussed. KW - cell staining KW - drosophila melanogaster KW - gene expression KW - hybridomas KW - immune serum KW - library screening KW - monoclonal antibodies KW - neurons Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-97109 ER - TY - JOUR A1 - Gaubatz, Stefan A1 - Esterlechner, Jasmina A1 - Reichert, Nina A1 - Iltzsche, Fabian A1 - Krause, Michael A1 - Finkernagel, Florian T1 - LIN9, a Subunit of the DREAM Complex, Regulates Mitotic Gene Expression and Proliferation of Embryonic Stem Cells JF - PLoS ONE N2 - The DREAM complex plays an important role in regulation of gene expression during the cell cycle. We have previously shown that the DREAM subunit LIN9 is required for early embryonic development and for the maintenance of the inner cell mass in vitro. In this study we examined the effect of knocking down LIN9 on ESCs. We demonstrate that depletion of LIN9 alters the cell cycle distribution of ESCs and results in an accumulation of cells in G2 and M and in an increase of polyploid cells. Genome-wide expression studies showed that the depletion of LIN9 results in downregulation of mitotic genes and in upregulation of differentiation-specific genes. ChIP-on chip experiments showed that mitotic genes are direct targets of LIN9 while lineage specific markers are regulated indirectly. Importantly, depletion of LIN9 does not alter the expression of pluripotency markers SOX2, OCT4 and Nanog and LIN9 depleted ESCs retain alkaline phosphatase activity. We conclude that LIN9 is essential for proliferation and genome stability of ESCs by activating genes with important functions in mitosis and cytokinesis. KW - cell cycle KW - cell division KW - cell differentation KW - DNA-binding proteins KW - gene expression KW - gene regulation KW - gene targeting KW - microarrays KW - pluripotency Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-96922 ER - TY - JOUR A1 - Schubert, Maria A1 - Spahn, Martin A1 - Kneitz, Susanne A1 - Scholz, Claus Jürgen A1 - Joniau, Steven A1 - Stroebel, Philipp A1 - Riedmiller, Hubertus A1 - Kneitz, Burkhard T1 - Distinct microRNA Expression Profile in Prostate Cancer Patients with Early Clinical Failure and the Impact of let-7 as Prognostic Marker in High-Risk Prostate Cancer JF - PLoS ONE N2 - Background The identification of additional prognostic markers to improve risk stratification and to avoid overtreatment is one of the most urgent clinical needs in prostate cancer (PCa). MicroRNAs, being important regulators of gene expression, are promising biomarkers in various cancer entities, though the impact as prognostic predictors in PCa is poorly understood. The aim of this study was to identify specific miRNAs as potential prognostic markers in high-risk PCa and to validate their clinical impact. Methodology and Principal Findings We performed miRNA-microarray analysis in a high-risk PCa study group selected by their clinical outcome (clinical progression free survival (CPFS) vs. clinical failure (CF)). We identified seven candidate miRNAs (let-7a/b/c, miR-515-3p/5p, -181b, -146b, and -361) that showed differential expression between both groups. Further qRT-PCR analysis revealed down-regulation of members of the let-7 family in the majority of a large, well-characterized high-risk PCa cohort (n = 98). Expression of let-7a/b/and -c was correlated to clinical outcome parameters of this group. While let-7a showed no association or correlation with clinical relevant data, let-7b and let-7c were associated with CF in PCa patients and functioned partially as independent prognostic marker. Validation of the data using an independent high-risk study cohort revealed that let-7b, but not let-7c, has impact as an independent prognostic marker for BCR and CF. Furthermore, we identified HMGA1, a non-histone protein, as a new target of let-7b and found correlation of let-7b down-regulation with HMGA1 over-expression in primary PCa samples. Conclusion Our findings define a distinct miRNA expression profile in PCa cases with early CF and identified let-7b as prognostic biomarker in high-risk PCa. This study highlights the importance of let-7b as tumor suppressor miRNA in high-risk PCa and presents a basis to improve individual therapy for high-risk PCa patients. KW - biomarkers KW - gene expression KW - gene targeting KW - luciferase KW - MircoRNA KW - microarrays KW - oncogenes KW - prostate cancer Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-96825 ER - TY - JOUR A1 - Deeken, Rosalia A1 - Gohlke, Jochen A1 - Scholz, Claus-Juergen A1 - Kneitz, Susanne A1 - Weber, Dana A1 - Fuchs, Joerg A1 - Hedrich, Rainer T1 - DNA Methylation Mediated Control of Gene Expression Is Critical for Development of Crown Gall Tumors JF - PLoS Genetics N2 - Crown gall tumors develop after integration of the T-DNA of virulent Agrobacterium tumefaciens strains into the plant genome. Expression of the T-DNA–encoded oncogenes triggers proliferation and differentiation of transformed plant cells. Crown gall development is known to be accompanied by global changes in transcription, metabolite levels, and physiological processes. High levels of abscisic acid (ABA) in crown galls regulate expression of drought stress responsive genes and mediate drought stress acclimation, which is essential for wild-type-like tumor growth. An impact of epigenetic processes such as DNA methylation on crown gall development has been suggested; however, it has not yet been investigated comprehensively. In this study, the methylation pattern of Arabidopsis thaliana crown galls was analyzed on a genome-wide scale as well as at the single gene level. Bisulfite sequencing analysis revealed that the oncogenes Ipt, IaaH, and IaaM were unmethylated in crown galls. Nevertheless, the oncogenes were susceptible to siRNA–mediated methylation, which inhibited their expression and subsequently crown gall growth. Genome arrays, hybridized with methylated DNA obtained by immunoprecipitation, revealed a globally hypermethylated crown gall genome, while promoters were rather hypomethylated. Mutants with reduced non-CG methylation developed larger tumors than the wild-type controls, indicating that hypermethylation inhibits plant tumor growth. The differential methylation pattern of crown galls and the stem tissue from which they originate correlated with transcriptional changes. Genes known to be transcriptionally inhibited by ABA and methylated in crown galls became promoter methylated upon treatment of A. thaliana with ABA. This suggests that the high ABA levels in crown galls may mediate DNA methylation and regulate expression of genes involved in drought stress protection. In summary, our studies provide evidence that epigenetic processes regulate gene expression, physiological processes, and the development of crown gall tumors. KW - DNA methylation KW - DNA transcription KW - gene expression KW - oncogenes KW - plant genomics KW - sequence motif analysis KW - arabidopsis thaliana KW - agrobacterium tumefaciens Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-96318 ER - TY - THES A1 - Engelmann, Julia Cathérine T1 - DNA microarrays: applications and novel approaches for analysis and interpretation T1 - DNA Mikroarrays: Anwendungen und neue Ansätze für die Analyse und Interpretation N2 - In der vorliegenden Dissertation wird die Entwicklung eines phylogenetischen DNA Microarrays, die Analyse von mehreren Microarray-Genexpressionsdatensätzen und neue Ansätze für die Datenanalyse und Interpretation der Ergebnisse vorgestellt. Die Entwicklung und Analyse der Daten eines phylogenetischen DNA Microarrays wird in der ersten Publikation dargestellt. Ich konnte zeigen, dass die Spezies-Detektion mit phylogenetischen Microarrays durch die Datenanalyse mit einem linearen Regressionsansatz signifikant verbessert werden kann. Standard-Methoden haben bislang nur Signalintensitäten betrachtet und eine Spezies als an- oder abwesend bezeichnet, wenn die Signalintensität ihres Messpunktes oberhalb eines willkürlich gesetzten Schwellenwertes lag. Dieses Verfahren ist allerdings aufgrund von Kreuz-Hybridisierungen nicht auf sehr nah verwandte Spezies mit hoher Sequenzidentität anwendbar. Durch die Modellierung des Hybridisierungs und Kreuz-Hybridisierungsverhaltens mit einem linearen Regressionsmodell konnte ich zeigen, dass Spezies mit einer Sequenzähnlichkeit von 97% im Markergen immer noch unterschieden werden können. Ein weiterer Vorteil der Modellierung ist, dass auch Mischungen verschiedener Spezies zuverlässig vorhergesagt werden können. Theoretisch sind auch quantitative Vorhersagen mit diesem Modell möglich. Um die großen Datenmengen, die in öffentlichen Microarray-Datenbanken abgelegt sind besser nutzen zu können, bieten sich Meta-Analysen an. In der zweiten Publikation wird eine explorative Meta-Analyse auf Arabidopsis thaliana-Datensätzen vorgestellt. Mit der Analyse verschiedener Datensätze, die den Einfluss von Pflanzenhormonen, Pathogenen oder verschiedenen Mutationen auf die Genexpression untersucht haben, konnten die Datensätze anhand ihrer Genexpressionsprofile in drei große Gruppen eingeordnet werden: Experimente mit Indol-3-Essigsäure (IAA), mit Pathogenen und andere Experimente. Gene, die charakteristisch für die Gruppe der IAA-Datensätze beziehungsweise für die Gruppe der Pathogen-Datensätze sind, wurden näher betrachtet. Diese Gene hatten Funktionen, die bereits mit Pathogenbefall bzw. dem Einfluss von IAA in Verbindung gebracht wurden. Außerdem wurden Hypothesen über die Funktionen von bislang nicht annotierten Genen aufgestellt. In dieser Arbeit werden auch Primäranalysen von einzelnen Arabidopsis thaliana Genexpressions-Datensätzen vorgestellt. In der dritten Publikation wird ein Experiment beschrieben, das durchgeführt wurde um herauszufinden ob Mikrowellen-Strahlung einen Einfluss auf die Genexpression einer Zellkultur hat. Dazu wurden explorative Analysemethoden angewendet. Es wurden geringe aber signifikante Veränderungen in einer sehr kleinen Anzahl von Genen beobachtet, die experimentell bestätigt werden konnten. Die Funktionen der regulierten Gene und eine Meta-Analyse mit öffentlich zugänglichen Datensätzen einer Datenbank deuten darauf hin, dass die pflanzliche Zellkultur die Strahlung als eine Art Energiequelle ähnlich dem Licht wahrnimmt. Des weiteren wird in der vierten Publikation die funktionelle Analyse eines Arabidopsis thaliana Genexpressionsdatensatzes beschrieben. Die Analyse der Genexpressions eines pflanzlichen Tumores zeigte, dass er seinen Stoffwechsel von aerob und auxotroph auf anaerob und heterotroph umstellt. Gene der Photosynthese werden im Tumorgewebe reprimiert, Gene des Aminosäure- und Fettstoffwechsels, der Zellwand und Transportkanäle werden so reguliert, dass Wachstum und Entwicklung des Tumors gefördert werden. In der fünften Publikation in dieser Arbeit wird GEPAT (Genome Expression Pathway Analysis Tool) beschrieben. Es besteht aus einer Internet- Anwendung und einer Datenbank, die das einfache Hochladen von Datensätzen in die Datenbank und viele Möglichkeiten der Datenanalyse und die Integration anderer Datentypen erlaubt. In den folgenden zwei Publikationen (Publikation 6 und Publikation 7) wird GEPAT auf humane Microarray-Datensätze angewendet um Genexpressionsdaten mit weiteren Datentypen zu verknüpfen. Genexpressionsdaten und Daten aus vergleichender Genom-Hybridisierung (CGH) von primären Tumoren von 71 Mantel-Zell-Lymphom (MCL) Patienten ermöglichte die Ermittlung eines Prädiktors, der die Vorhersage der Überlebensdauer von Patienten gegenüber herkömmlichen Methoden verbessert. Die Analyse der CGH Daten zeigte, dass auch diese für die Vorhersage der Überlebensdauer geeignet sind. Für den Datensatz von Patienten mit großzellig diffusem B-Zell-Lymphom DLBCL konnte aus den Genexpressionsdaten ebenfalls ein neuer Prädiktor vorgeschlagen werden. Mit den zwischen lang und kurz überlebenden Patienten differentiell exprimierten Genen der MCL Patienten und mit den Genen, die zwischen den beiden Untergruppen von DLBCL reguliert sind, wurden Interaktionsnetzwerke gebildet. Diese zeigen, dass bei beiden Krebstypen Gene des Zellzyklus und der Proliferation zwischen Patienten mit kurzer und langer Überlebensdauer unterschiedlich reguliert sind. N2 - In this thesis, the development of a phylogenetic DNA microarray, the analysis of several gene expression microarray datasets and new approaches for improved data analysis and interpretation are described. In the first publication, the development and analysis of a phylogenetic microarray is presented. I could show that species detection with phylogenetic DNA microarrays can be significantly improved when the microarray data is analyzed with a linear regression modeling approach. Standard methods have so far relied on pure signal intensities of the array spots and a simple cutoff criterion was applied to call a species present or absent. This procedure is not applicable to very closely related species with high sequence similarity because cross-hybridization of non-target DNA renders species detection impossible based on signal intensities alone. By modeling hybridization and cross-hybridization with linear regression, as I have presented in this thesis, even species with a sequence similarity of 97% in the marker gene can be detected and distinguished from related species. Another advantage of the modeling approach over existing methods is that the model also performs well on mixtures of different species. In principle, also quantitative predictions can be made. To make better use of the large amounts of microarray data stored in public databases, meta-analysis approaches need to be developed. In the second publication, an explorative meta-analysis exemplified on Arabidopsis thaliana gene expression datasets is presented. Integrating datasets studying effects such as the influence of plant hormones, pathogens and different mutations on gene expression levels, clusters of similarly treated datasets could be found. From the clusters of pathogen-treated and indole-3-acetic acid (IAA) treated datasets, representative genes were selected which pointed to functions which had been associated with pathogen attack or IAA effects previously. Additionally, hypotheses about the functions of so far uncharacterized genes could be set up. Thus, this kind of meta-analysis could be used to propose gene functions and their regulation under different conditions. In this work, also primary data analysis of Arabidopsis thaliana datasets is presented. In the third publication, an experiment which was conducted to find out if microwave irradiation has an effect on the gene expression of a plant cell culture is described. During the first steps, the data analysis was carried out blinded and exploratory analysis methods were applied to find out if the irradiation had an effect on gene expression of plant cells. Small but statistically significant changes in a few genes were found and could be experimentally confirmed. From the functions of the regulated genes and a meta-analysis with publicly available microarray data, it could be suspected that the plant cell culture somehow perceived the irradiation as energy, similar to perceiving light rays. The fourth publication describes the functional analysis of another Arabidopsis thaliana gene expression dataset. The gene expression data of the plant tumor dataset pointed to a switch from a mainly aerobic, auxotrophic to an anaerobic and heterotrophic metabolism in the plant tumor. Genes involved in photosynthesis were found to be repressed in tumors; genes of amino acid and lipid metabolism, cell wall and solute transporters were regulated in a way that sustains tumor growth and development. Furthermore, in the fifth publication, GEPAT (Genome Expression Pathway Analysis Tool), a tool for the analysis and integration of microarray data with other data types, is described. It consists of a web application and database which allows comfortable data upload and data analysis. In later chapters of this thesis (publication 6 and publication 7), GEPAT is used to analyze human microarray datasets and to integrate results from gene expression analysis with other datatypes. Gene expression and comparative genomic hybridization data from 71 Mantle Cell Lymphoma (MCL) patients was analyzed and allowed proposing a seven gene predictor which facilitates survival predictions for patients compared to existing predictors. In this study, it was shown that CGH data can be used for survival predictions. For the dataset of Diffuse Large B-cell lymphoma (DLBCL) patients, an improved survival predictor could be found based on the gene expression data. From the genes differentially expressed between long and short surviving MCL patients as well as for regulated genes of DLBCL patients, interaction networks could be set up. They point to differences in regulation for cell cycle and proliferation genes between patients with good and bad prognosis. KW - Microarray KW - Differentielle Genexpression KW - Genexpression KW - Statistische Analyse KW - Cluster-Analyse KW - Datenanalyse KW - Explorative Datenanalyse KW - Non-Hodgkin-Lymphom KW - B-Zell-Lymphom KW - Metabolom KW - Tumorklassifikation KW - Tumor KW - Krebs KW - Schmalwa KW - phylogenetische Arrays KW - Interaktionsnetzwerke KW - lineare Regression KW - DNA microarray KW - gene expression KW - statistical analysis KW - clustering KW - classification KW - interaction networks Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-29747 ER - TY - THES A1 - Blenk, Steffen T1 - Bioinformatical analysis of B-cell lymphomas T1 - Bioinformatische Analyse von B-Zell Lymphomen N2 - Background: The frequency of the most observed cancer, Non Hodgkin Lymphoma (NHL), is further rising. Diffuse large B-cell lymphoma (DLBCL) is the most common of the NHLs. There are two subgroups of DLBCL with different gene expression patterns: ABC (“Activated B-like DLBCL”) and GCB (“Germinal Center B-like DLBCL”). Without therapy the patients often die within a few months, the ABC type exhibits the more aggressive behaviour. A further B-cell lymphoma is the Mantle cell lymphoma (MCL). It is rare and shows very poor prognosis. There is no cure yet. Methods: In this project these B-cell lymphomas were examined with methods from bioinformatics, to find new characteristics or undiscovered events on the molecular level. This would improve understanding and therapy of lymphomas. For this purpose we used survival, gene expression and comparative genomic hybridization (CGH) data. In some clinical studies, you get large data sets, from which one can reveal yet unknown trends. Results (MCL): The published proliferation signature correlates directly with survival. Exploratory analyses of gene expression and CGH data of MCL samples (n=71) revealed a valid grouping according to the median of the proliferation signature values. The second axis of correspondence analysis distinguishes between good and bad prognosis. Statistical testing (moderate t-test, Wilcoxon rank-sum test) showed differences in the cell cycle and delivered a network of kinases, which are responsible for the difference between good and bad prognosis. A set of seven genes (CENPE, CDC20, HPRT1, CDC2, BIRC5, ASPM, IGF2BP3) predicted, similarly well, survival patterns as proliferation signature with 20 genes. Furthermore, some bands could be associated with prognosis in the explorative analysis (chromosome 9: 9p24, 9p23, 9p22, 9p21, 9q33 and 9q34). Results (DLBCL): New normalization of gene expression data of DLBCL patients revealed better separation of risk groups by the 2002 published signature based predictor. We could achieve, similarly well, a separation with six genes. Exploratory analysis of gene expression data could confirm the subgroups ABC and GCB. We recognized a clear difference in early and late cell cycle stages of cell cycle genes, which can separate ABC and GCB. Classical lymphoma and best separating genes form a network, which can classify and explain the ABC and GCB groups. Together with gene sets which identify ABC and GCB we get a network, which can classify and explain the ABC and GCB groups (ASB13, BCL2, BCL6, BCL7A, CCND2, COL3A1, CTGF, FN1, FOXP1, IGHM, IRF4, LMO2, LRMP, MAPK10, MME, MYBL1, NEIL1 and SH3BP5; Altogether these findings are useful for diagnosis, prognosis and therapy (cytostatic drugs). N2 - Hintergrund: Die Häufigkeit von Non-Hodgkin-Lymphomen (NHL), den am meisten beobachteten Krebserkrankungen, steigt weiter an. Von den aggressiven Non-Hodgkin-Lymphomen (NHL) macht das “großzellige, diffuse B-Zell-Lymphom” (DLBCL) den größten Anteil aus. Durch Genexpressionsmuster wurden zwei Subtypen definiert: ACB (“Activated B-like DLBCL”) und GCB (“Germinal Center B-like DLBCL”). Die Patienten der Gruppe ABC sterben ohne Therapie oft innerhalb weniger Monate, weil der ABC Typ einen aggressiveren Krankheitsverlauf aufweist. Ein weiteres, von einer malignen Entartung der B-Lymphozyten ausgehendes Lymphom, ist das “Mantelzell Lymphom” (MCL). Es tritt selten auf und ist ebenfalls mit einer schlechten Prognose verbunden. Eine vollständige Heilung nach der Therapie ist sehr selten. Methoden: In diesem Projekt wurden diese B-zell Lymphome mit bioinformatischen Methoden untersucht, um auf molekularer Ebene neue Eigenschaften oder bisher unentdeckte Zusammenhänge zu finden. Das würde das Verständnis und damit auch die Therapie voranbringen. Dafür standen uns Überlebens-, Genexpressions- und chromosomale Aberrationsdaten zur Verfügung. Sie sind die bevorzugte Wahl der Mittel, um genetische Veränderungen in Tumorzellen zu bestimmen. Hierbei fallen oft große Datenmengen an, aus welchen man mit bioinformatischen Methoden vorher unerkannte Trends und Hinweise identifizieren kann. Ergebnisse (MCL): Explorative Analysen sowohl der Genexpressions- (zweite Hauptachse der Korrespondenz Analyse) als auch der chromosomalen Aberrationsdaten des Mantelzell-Lymphom zeigten uns hierbei, daß es trotz der linearen Korrelation zwischen der veröffentlichten Proliferationssignatur und der Überlebenszeit sinnvoll ist, in den Patienten (n=71) zwei Ausprägungen zu betrachten: Patienten mit schlechter und mit guter Prognose. Statistische Tests (moderate t-test, Wilcoxon rank-sum test) dieser beiden Typen zeigten Unterschiede im Zellzyklus und ein Netzwerk von Kinasen auf, welche für den Unterschied zwischen guter und schlechter Prognose verantwortlich sind. Sieben Gene (CENPE, CDC20, HPRT1, CDC2, BIRC5, ASPM, IGF2BP3) konnten gefunden werden, die eine ähnliche gute Prognose für Überlebenszeiten ermöglichen, wie eine früher veröffentlichte Proliferationssignatur mit 20 Genen. Außerdem konnten chromosomale Banden durch eine explorative Analyse mit der Prognose assoziiert werden (Chromosom 9: 9p24, 9p23, 9p22, 9p21, 9q33 and 9q34). Ergebnisse (DLBCL): Durch geeignete Normalisierung der Genexpressionsdaten von 248 DLBCL-Patienten trennte der Signatur basierte Predictor die Risikogruppen nun besser auf. Eine ähnlich gute Auftrennung konnte von uns sogar mit sechs Genen erreicht werden. Die explorative Analyse der Genexpressionsdaten konnte die Subtypen ABC und GCB als valide Gruppen bestätigen. In den Genen, die ABC und GCB unterscheiden, ergab sich eine Häufung in späten und frühen Zellzyklusstadien. Klassische Lymphommarker, neu aufgefundene spezielle Gene und Zellzyklusgene bilden ein Netzwerk, das die ABC und GCB Gruppen klassifizieren und Unterschiede in deren Regulation erklären kann (ASB13, BCL2, BCL6, BCL7A, CCND2, COL3A1, CTGF, FN1, FOXP1, IGHM, IRF4, LMO2, LRMP, MAPK10, MME, MYBL1, NEIL1 and SH3BP5. Dies ist auch für die Diagnose, Prognose und Therapie (Zytostatika) interessant. KW - Bioinformatik KW - Genexpression KW - Auswertung KW - B-Zell-Lymphom KW - Diffuses großzelliges B-Zell-Lymphom KW - Mantelzell-Lymphom KW - Bioinformatics KW - gene expression KW - B-cell lymphoma KW - Diffuse large B-cell lymphoma (DLBCL) KW - Mantle cell lymphoma (MCL) Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-27421 ER -