TY - JOUR A1 - Loeffler-Wirth, Henry A1 - Kreuz, Markus A1 - Hopp, Lydia A1 - Arakelyan, Arsen A1 - Haake, Andrea A1 - Cogliatti, Sergio B. A1 - Feller, Alfred C. A1 - Hansmann, Martin-Leo A1 - Lenze, Dido A1 - Möller, Peter A1 - Müller-Hermelink, Hans Konrad A1 - Fortenbacher, Erik A1 - Willscher, Edith A1 - Ott, German A1 - Rosenwald, Andreas A1 - Pott, Christiane A1 - Schwaenen, Carsten A1 - Trautmann, Heiko A1 - Wessendorf, Swen A1 - Stein, Harald A1 - Szczepanowski, Monika A1 - Trümper, Lorenz A1 - Hummel, Michael A1 - Klapper, Wolfram A1 - Siebert, Reiner A1 - Loeffler, Markus A1 - Binder, Hans T1 - A modular transcriptome map of mature B cell lymphomas JF - Genome Medicine N2 - Background Germinal center-derived B cell lymphomas are tumors of the lymphoid tissues representing one of the most heterogeneous malignancies. Here we characterize the variety of transcriptomic phenotypes of this disease based on 873 biopsy specimens collected in the German Cancer Aid MMML (Molecular Mechanisms in Malignant Lymphoma) consortium. They include diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt’s lymphoma, mixed FL/DLBCL lymphomas, primary mediastinal large B cell lymphoma, multiple myeloma, IRF4-rearranged large cell lymphoma, MYC-negative Burkitt-like lymphoma with chr. 11q aberration and mantle cell lymphoma. Methods We apply self-organizing map (SOM) machine learning to microarray-derived expression data to generate a holistic view on the transcriptome landscape of lymphomas, to describe the multidimensional nature of gene regulation and to pursue a modular view on co-expression. Expression data were complemented by pathological, genetic and clinical characteristics. Results We present a transcriptome map of B cell lymphomas that allows visual comparison between the SOM portraits of different lymphoma strata and individual cases. It decomposes into one dozen modules of co-expressed genes related to different functional categories, to genetic defects and to the pathogenesis of lymphomas. On a molecular level, this disease rather forms a continuum of expression states than clearly separated phenotypes. We introduced the concept of combinatorial pattern types (PATs) that stratifies the lymphomas into nine PAT groups and, on a coarser level, into five prominent cancer hallmark types with proliferation, inflammation and stroma signatures. Inflammation signatures in combination with healthy B cell and tonsil characteristics associate with better overall survival rates, while proliferation in combination with inflammation and plasma cell characteristics worsens it. A phenotypic similarity tree is presented that reveals possible progression paths along the transcriptional dimensions. Our analysis provided a novel look on the transition range between FL and DLBCL, on DLBCL with poor prognosis showing expression patterns resembling that of Burkitt’s lymphoma and particularly on ‘double-hit’ MYC and BCL2 transformed lymphomas. Conclusions The transcriptome map provides a tool that aggregates, refines and visualizes the data collected in the MMML study and interprets them in the light of previous knowledge to provide orientation and support in current and future studies on lymphomas and on other cancer entities. KW - tumor heterogeneity KW - B cell malignancies KW - gene regulation KW - molecular subtypes KW - machine learning Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-237262 VL - 11 ER - TY - THES A1 - Haake, Markus T1 - Stat6-vermittelte Genregulation in eukaryontischen Zellen T1 - Stat6 mediated gene regulation in eucariotic cells N2 - Der Transkriptionsfaktor Stat6 vermittelt zentrale Wirkungen von IL-4 und IL-13, die in der Pathologie atopischer Erkrankungen eine Rolle spielen. Seine Spezifität für diese beiden allergieassoziierten Cytokine ist eine wesentliche Motivation ihn näher zu untersuchen. In dieser Arbeit sollte mehr über die Funktion von Stat6 herausgefunden werden. Außerdem wurden Möglichkeiten untersucht dieses Verhalten zu beinflussen. Einen Schwerpunkt der Arbeit bildete die Regulation des Eotaxin-1-Promotors. Eotaxin-1 ist einer der stärksten Rekrutierungsfaktoren für Eosinophile, die eine zentrale Rolle bei der Immunpathologie allergischer Erkrankungen spielen. Mit Hilfe der Daten konnte eine neue Hypothese zur Regulation des Eotaxin-1-Promotors entwickelt werden. Zum Vergleich wurde mit der Untersuchung des Promotors eines weiteren Chemokins, des MCP-4, begonnen. In Zusammenarbeit mit Dr. Sascha Stolzenberger wurde ein Weg untersucht den Stat6-Signalweg zu hemmen. Dabei wurden mit Hilfe des Antennapedia-Peptides Stat6-Bindepeptide in die Zelle transportiert, um dort über eine kompetitive Hemmung die Signaltransduktion zu unterbinden. Ergebnis dieser Arbeiten ist ein hochspezifischer, aber nur transient wirkender Stat6 Inhibitor. Die Stat6/DNA-Wechselwirkung wurde mit der Magnetobead-Technik untersucht. Dabei werden Promotorfragmente an Magnetkügelchen gekoppelt und unter Ausnutzung der Magnetisierung an die DNA bindende Proteine isoliert und über SDS-PAGE/Immunoblotanalyse untersucht. Mit dem Verfahren konnte die Stat6-Bindung an acht verschiedene Promotoren nachgewiesen werden. In Zusammenarbeit mit der Arbeitsgruppe Pallardy aus Paris wurde die Wechselwirkung von Stat6 mit dem Glucocorticoid-Rezeptor untersucht. Glucocorticoide kontrollieren Entzündungen und Interaktionen des aktivierten Rezeptors mit anderen Proteinen aus der Stat-Familie sind seit längerem bekannt. Wie in dieser Arbeit gezeigt wurde, interagiert Stat6 mit dem Glucocorticoidrezeptor unabhängig von einer Bindung an DNA. Zusätzlich wurde der Mucin-2-Promotor auf Stat6-Regulierung untersucht. Mucine sind wichtige Bestandteile des Schleimes. Verstärkte Schleim-Sekretion ist ein klinisches Symptom asthmatischer Erkrankungen und trägt zur Zerstörung der Lunge bei. Ein potentiell Stat6 reguliertes Fragment aus dem Mucinpromoter wurde mit Hilfe von PCR-Techniken isoliert und in Reportergenvektoren kloniert. N2 - The transcriptionfactor Stat6 mediates central effects of the interleukins (IL)-4 and -13, that play important roles in the pathology of Allergy and Asthma. The specificity of these both Allergy-associated cytokines is a strong motivation to investigate the detailed functions of Stat6 and to search for possibilities to influence the behaviour of this transcriptionfactor. The main focus of this work was the regulation of the Eotaxin-1-promoter. The Eotaxin-1 chemokine is one of the most potent recruiting factors for eosinophils, that play a central role in the immunopathology of allergic diseases. On the basis of these data a new model for the regulation was created. In addition to this the investigation of another chemokine promoter, the MCP-4-promoter, was started. In another part of this work a specific Stat6-binding-peptide to inhibit the IL-4 signaltransduction pathway was established. Using the Antennapedia-carrier-peptide allowed to shuttle Stat6-binding peptides into cells where they prevented Stat6 mediated signalling by competitive inhibition. Thus the Stat6-binding-peptide came out to be a transient Stat6 inhibitor with high specificity. The Stat6/DNA-interaction was investigated by DNA-pull-down assays with magnetobeads. Fragments of different promoters are linked to magnetobeads and by using magnetic forces the DNA binding proteins are isolated. This application was used to show Stat6-binding to 8 different promoters. Another subject of this work was the interaction of Stat6 with the glucocorticoid receptor. It is well known that glucocorticoids control inflammation and that the activated receptor interacts with different proteins of the Stat-family. In collaboration with the group of Marc Pallardy in Paris we were able to show that Stat6 interacts with the glucocorticoid receptor independently of DNA binding. In association with Stat6 the regulation of the Mucin-2-promoter seemed to be an interesting aspect. Mucins are essential components of mucus (slime). Enhanced mucus-secretion is a symptom of asthmatic diseases and contributes to the destruction of the lung. A potentially Stat6 regulated fragment was isolated by PCR-techniques and cloned into reportergene vectors. KW - Interleukin 4 KW - Interleukin 13 KW - Transkriptionsfaktor KW - Allergie KW - Signaltransduktion KW - Interleukin-4 KW - IL-4 KW - Stat6 KW - Allergie KW - Eotaxin KW - Signaltransduktion KW - interleukin-4 KW - IL-4 KW - Stat6 KW - Allergy KW - Eotaxin KW - signaltransduction Y1 - 2001 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-1181580 ER - TY - JOUR A1 - Herrmann, Johannes A1 - Lotz, Christopher A1 - Karagiannidis, Christian A1 - Weber-Carstens, Steffen A1 - Kluge, Stefan A1 - Putensen, Christian A1 - Wehrfritz, Andreas A1 - Schmidt, Karsten A1 - Ellerkmann, Richard K. A1 - Oswald, Daniel A1 - Lotz, Gösta A1 - Zotzmann, Viviane A1 - Moerer, Onnen A1 - Kühn, Christian A1 - Kochanek, Matthias A1 - Muellenbach, Ralf A1 - Gaertner, Matthias A1 - Fichtner, Falk A1 - Brettner, Florian A1 - Findeisen, Michael A1 - Heim, Markus A1 - Lahmer, Tobias A1 - Rosenow, Felix A1 - Haake, Nils A1 - Lepper, Philipp M. A1 - Rosenberger, Peter A1 - Braune, Stephan A1 - Kohls, Mirjam A1 - Heuschmann, Peter A1 - Meybohm, Patrick T1 - Key characteristics impacting survival of COVID-19 extracorporeal membrane oxygenation JF - Critical Care N2 - Background Severe COVID-19 induced acute respiratory distress syndrome (ARDS) often requires extracorporeal membrane oxygenation (ECMO). Recent German health insurance data revealed low ICU survival rates. Patient characteristics and experience of the ECMO center may determine intensive care unit (ICU) survival. The current study aimed to identify factors affecting ICU survival of COVID-19 ECMO patients. Methods 673 COVID-19 ARDS ECMO patients treated in 26 centers between January 1st 2020 and March 22nd 2021 were included. Data on clinical characteristics, adjunct therapies, complications, and outcome were documented. Block wise logistic regression analysis was applied to identify variables associated with ICU-survival. Results Most patients were between 50 and 70 years of age. PaO\(_{2}\)/FiO\(_{2}\) ratio prior to ECMO was 72 mmHg (IQR: 58–99). ICU survival was 31.4%. Survival was significantly lower during the 2nd wave of the COVID-19 pandemic. A subgroup of 284 (42%) patients fulfilling modified EOLIA criteria had a higher survival (38%) (p = 0.0014, OR 0.64 (CI 0.41–0.99)). Survival differed between low, intermediate, and high-volume centers with 20%, 30%, and 38%, respectively (p = 0.0024). Treatment in high volume centers resulted in an odds ratio of 0.55 (CI 0.28–1.02) compared to low volume centers. Additional factors associated with survival were younger age, shorter time between intubation and ECMO initiation, BMI > 35 (compared to < 25), absence of renal replacement therapy or major bleeding/thromboembolic events. Conclusions Structural and patient-related factors, including age, comorbidities and ECMO case volume, determined the survival of COVID-19 ECMO. These factors combined with a more liberal ECMO indication during the 2nd wave may explain the reasonably overall low survival rate. Careful selection of patients and treatment in high volume ECMO centers was associated with higher odds of ICU survival. KW - Covid-19 KW - extracorporeal membrane oxygenation (ECMO) KW - intensive care unit Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-299686 VL - 26 IS - 1 ER - TY - JOUR A1 - Lüke, Florian A1 - Haller, Florian A1 - Utpatel, Kirsten A1 - Krebs, Markus A1 - Meidenbauer, Norbert A1 - Scheiter, Alexander A1 - Spoerl, Silvia A1 - Heudobler, Daniel A1 - Sparrer, Daniela A1 - Kaiser, Ulrich A1 - Keil, Felix A1 - Schubart, Christoph A1 - Tögel, Lars A1 - Einhell, Sabine A1 - Dietmaier, Wolfgang A1 - Huss, Ralf A1 - Dintner, Sebastian A1 - Sommer, Sebastian A1 - Jordan, Frank A1 - Goebeler, Maria-Elisabeth A1 - Metz, Michaela A1 - Haake, Diana A1 - Scheytt, Mithun A1 - Gerhard-Hartmann, Elena A1 - Maurus, Katja A1 - Brändlein, Stephanie A1 - Rosenwald, Andreas A1 - Hartmann, Arndt A1 - Märkl, Bruno A1 - Einsele, Hermann A1 - Mackensen, Andreas A1 - Herr, Wolfgang A1 - Kunzmann, Volker A1 - Bargou, Ralf A1 - Beckmann, Matthias W. A1 - Pukrop, Tobias A1 - Trepel, Martin A1 - Evert, Matthias A1 - Claus, Rainer A1 - Kerscher, Alexander T1 - Identification of disparities in personalized cancer care — a joint approach of the German WERA consortium JF - Cancers N2 - (1) Background: molecular tumor boards (MTBs) are crucial instruments for discussing and allocating targeted therapies to suitable cancer patients based on genetic findings. Currently, limited evidence is available regarding the regional impact and the outreach component of MTBs; (2) Methods: we analyzed MTB patient data from four neighboring Bavarian tertiary care oncology centers in Würzburg, Erlangen, Regensburg, and Augsburg, together constituting the WERA Alliance. Absolute patient numbers and regional distribution across the WERA-wide catchment area were weighted with local population densities; (3) Results: the highest MTB patient numbers were found close to the four cancer centers. However, peaks in absolute patient numbers were also detected in more distant and rural areas. Moreover, weighting absolute numbers with local population density allowed for identifying so-called white spots—regions within our catchment that were relatively underrepresented in WERA MTBs; (4) Conclusions: investigating patient data from four neighboring cancer centers, we comprehensively assessed the regional impact of our MTBs. The results confirmed the success of existing collaborative structures with our regional partners. Additionally, our results help identifying potential white spots in providing precision oncology and help establishing a joint WERA-wide outreach strategy. KW - precision oncology KW - MTB KW - patient access KW - cancer care KW - outreach KW - real world data KW - outcomes research Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-290311 SN - 2072-6694 VL - 14 IS - 20 ER -