TY - JOUR A1 - Sbiera, Silviu A1 - Kunz, Meik A1 - Weigand, Isabel A1 - Deutschbein, Timo A1 - Dandekar, Thomas A1 - Fassnacht, Martin T1 - The new genetic landscape of Cushing’s disease: deubiquitinases in the spotlight JF - Cancers N2 - Cushing’s disease (CD) is a rare condition caused by adrenocorticotropic hormone (ACTH)-producing adenomas of the pituitary, which lead to hypercortisolism that is associated with high morbidity and mortality. Treatment options in case of persistent or recurrent disease are limited, but new insights into the pathogenesis of CD are raising hope for new therapeutic avenues. Here, we have performed a meta-analysis of the available sequencing data in CD to create a comprehensive picture of CD’s genetics. Our analyses clearly indicate that somatic mutations in the deubiquitinases are the key drivers in CD, namely USP8 (36.5%) and USP48 (13.3%). While in USP48 only Met415 is affected by mutations, in USP8 there are 26 different mutations described. However, these different mutations are clustering in the same hotspot region (affecting in 94.5% of cases Ser718 and Pro720). In contrast, pathogenic variants classically associated with tumorigenesis in genes like TP53 and BRAF are also present in CD but with low incidence (12.5% and 7%). Importantly, several of these mutations might have therapeutic potential as there are drugs already investigated in preclinical and clinical setting for other diseases. Furthermore, network and pathway analyses of all somatic mutations in CD suggest a rather unified picture hinting towards converging oncogenic pathways. KW - Cushing’s disease KW - pathogenesis KW - somatic mutations KW - deubiquitinases Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193194 SN - 2072-6694 VL - 11 IS - 11 ER - TY - JOUR A1 - Kunz, Meik A1 - Liang, Chunguang A1 - Nilla, Santosh A1 - Cecil, Alexander A1 - Dandekar, Thomas T1 - The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development JF - Database N2 - The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure–activity relationships. KW - drug-minded protein KW - database Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-147369 VL - 2016 ER - TY - THES A1 - Kunz, Meik T1 - Systembiologische Analysen von Interaktionen: Zytokinine (Pflanzenpathogene), 3D-Zellkulturen (Krebstherapie) und Drugtargets T1 - Systems biology analysis of interactions: Cytokinins (plant pathogens), 3D cell cultures (cancer therapy) and drug targets N2 - Der Einsatz von computergestützten Analysen hat sich zu einem festen Bestandteil der biowissenschaftlichen Forschung etabliert. Im Rahmen dieser vorliegenden Arbeit wurden systembiologische Untersuchungen auf verschiedene biologische Themengebiete und Organismen angewendet. In diesem Zusammenhang liefert die Arbeit einen innovativen und interdisziplinären methodischen Ansatz. Die grundlegende Frage lautet: Wie verstehe und beschreibe ich Signalwege und wie kann ich sie beeinflussen? Der Ansatz verknüpft verschiedene biologische Datensätze und Datenebenen miteinander, beginnend vom Genom und Interaktionskontext über semiquantitative Simulationen hin zu neuen Interventionen und Experimenten, welche therapeutisch und biotechnologisch genutzt werden können. Die Analysen können auf diese Weise - zu einem besseren Verständnis experimenteller Daten und biologischer Fragestellungen beitragen und ermöglichen ein systematisches Verständnis der zugrunde liegenden Signalwege und Netzwerkeffekte (z.B. in Pflanzen). - Darüber hinaus ermöglichen sie die Identifizierung wichtiger funktioneller Hubproteine und die Entwicklung neuer therapeutischer Strategien für weitere experimentelle Testungen (z.B. Tumormodelle), - stellen zudem einen hilfreichen Schritt auf dem Weg zur personalisierten Medizin (z.B. lncRNAs und Tumormodelle) und Medikamentenentwicklung (z.B. Datenbank DrumPID) dar. (i) Als Grundlage wurde hierzu eine integrierte systembiologische Methode entwickelt, welche experimentelle Daten (z.B. Transkriptomdaten) hinsichtlich ihrer biologischen Funktionen untersucht und die Identifizierung relevanter funktioneller Cluster und Hubproteine ermöglicht. In einem ersten Teil wurden Analysen zum pflanzlichen Immunsystem durchgeführt. Mithilfe der entwickelten Methode wurden Genexpressionsdatensätze von A. thaliana, die mit dem Pathogen Pst DC3000 infiziert wurden, untersucht, um den Einfluss verschiedener Virulenzfaktoren auf das Interaktom der Wirtspflanze zu untersuchen und neue Modulatoren einer CK-vermittelten Immunabwehr zu finden. In diesem Zusammenhang konnte gezeigt werden, dass die von Pst DC3000 sekretierten Abwehrstoffe wichtige pflanzliche Hormonsignalwege für die Immunabwehr in A. thaliana beeinflussen. Die Ergebnisse zeigen zudem, dass sich der Einfluss auf das Netzwerkverhalten der Effektorproteine und COR-Phytotoxine von dem der PAMPs unterscheidet, sich jedoch auch eine Regulierung gemeinsamer Signalwege und eine Überlappung der beiden Phasen der Immunantwort (PTI und ETI) in A. thaliana finden lassen. Die komplexe Immunantwort auf eine Infektion spiegelt sich zudem in einer höheren Anzahl an funktionellen Clustern und Hubproteinen in Pst DC3000 gegenüber den beiden untersuchten Mutanten wider, wobei sich für Pst DC3000 insbesondere ein stark vernetztes immunrelevantes Cluster um den JA-Signalweg zeigt. Weiterhin wurden anhand der entwickelten Methode wichtige Hubproteine für die Immunabwehr identifiziert. Als bedeutende Vertreter sind AHK2 und AAR14 zu nennen, welche Teil des Zweikomponentensystems der Signalübertragung von CK sind und hierbei wichtige Modulatoren für eine CK-vermittelte Immunabwehr darstellen. (ii) Im zweiten Teil der Arbeit schließen sich Untersuchungen an einem in vitro-Experiment einer 2D- und 3D-Zellkultur einer HSP90-Behandlung in einem Lungentumormodell an. In diesem Zusammenhang wurden mithilfe der entwickelten Methode Unterschiede zwischen den beiden Zellkultursystemen gefunden, die das unterschiedliche Behandlungsansprechen erklären, und für die beiden KRAS-mutierten Zelllinien A549 und H441 des 3D-Testsystems neue prognostische und therapeutische Kandidaten identifiziert. Hierbei haben die durchgeführten Analysen zwei funktionelle Cluster von Protein-Interaktionen um p53 und die STAT-Familie gefunden, welche eine Verbindung zu HSP90 haben und die entsprechenden Behandlungsunterschiede nach einer HSP90-Inhibierung zwischen den beiden Zellkultursystemen erklären können. Unter Berücksichtigung des zelllinien-spezifischen Mutationshintergrunds wurde eine prognostische Markersignatur und daraus abgeleitet HIF1A für die H441-Zelllinie und AMPK für die A549-Zelllinie als neue therapeutische Targets gefunden, wobei die anschließend durchgeführten in silico-Simulationen einen potentiellen therapeutischen Effekt aufzeigen konnten. Weiterhin wurden wichtige experimentelle Readout-Parameter in ein in silico-Lungentumormodell integriert, wobei unter Einbeziehung des Mutationshintergrunds für die verwendeten Zelllinien die HSP90-Behandlung des 3D-Testsystems computergestützt abgebildet werden konnte. Im weiteren Verlauf wurden im in silico-Lungentumormodell Resistenzmechanismen nach einer Gefitinib-Behandlung mit bekanntem Mutationsstatus für die Zelllinien HCC827 und A549 untersucht und daraus folgend neue Therapieansätze abgeleitet, die von potentieller klinischer Bedeutung sein können. Die durchgeführten in silico-Simulationen für HCC827 konnten hierbei zeigen, dass eine EGFR- und c-MET-Koaktivierung zu einer Gefitinib-Resistenz führen kann, wohingegen bei den A549 eine Komutation von KRAS und IGF-1R zu einem geringen Behandlungsansprechen beiträgt. Die Simulationen lassen zudem erkennen, dass eine direkte Inhibierung der an der Resistenzentwicklung beteiligten Rezeptoren c-MET und IGF-1R in beiden Fällen nicht die bestmögliche Therapiestrategie darstellt. In beiden Zelllinien konnte gezeigt werden, dass eine kombinierte Inhibierung von PI3K und MEK den bestmöglichen therapeutischen Effekt liefert, was demnach einen vielversprechenden Therapieansatz bei Gefitinib-resistenten Lungentumorpatienten darstellt. In einem weiteren Schritt wurde das therapeutische Potential der miRNA-21 im in silico-Modell für die HCC827-Zelllinie untersucht. Die durchgeführten Simulationen zeigen, dass eine miRNA-21-Überexpression zu einer Resistenzentwickung nach Gefitinib-Behandlung beitragen kann, wobei eine Inhibierung der miRNA-21 diesen Effekt umkehren kann. Die Ergebnisse lassen zudem erkennen, dass eine PTEN-Aktivierung als potentieller Marker einer erfolgreichen therapeutischen Inhibierung der miRNA-21 fungieren kann, wohingegen eine reduzierte miRNA-21-Expression als möglicher Marker für eine erfolgreiche Gefitinib-Behandlung dienen kann. (iii) Im dritten Teil der Arbeit wurden systematisch RNA- und Protein-Interaktionen untersucht. Hierzu wurden integrierte systembiologische Analysen an neu identifizierten und funktionell bislang unbekannten lncRNAs durchgeführt. Die Analysen für die infolge einer Herzhypertrophie hochregulierte lncRNA Chast haben umfassend gezeigt, dass diese Proteine und Transkriptionsfaktoren regulieren und binden kann, welche die Signalübertragung und Genexpression regulieren, aber auch eine Verbindung zum kardiovaskulären System und stressinduzierter Herzhypertrophie besitzt. Anhand der Ergebnisse lässt sich schlussfolgern, dass Chast direkt und indirekt (a) Proteine binden und die Translation beeinflussen kann, zudem eine Chromatin-modifizierende Funktion besitzt und so die Transkription, z.B. für herz- und stress-assoziierte Gene, reguliert, und/oder (b) in einem negativen Feedbackloop seine eigene Transkription reguliert. Obwohl lncRNAs meist eine geringe Konservierung aufweisen, konnten die durchgeführten Analysen für Chast eine Sequenz-Struktur-Konservierung in Säugetieren aufzeigen. Weiterhin haben die Untersuchungen an zwei hypoxie-induzierten lncRNAs in Endothelzellen gezeigt, dass die lncRNA MIR503HG eine hohe Sequenz-Struktur-Konservierung in Säugetieren besitzt, wohingegen die LINC00323-003 eine geringe Konservierung aufzeigt. Dies untermauert die Tatsache, dass lncRNAs häufig eine geringe Konservierung aufweisen, was Untersuchungen in Modellorganismen hinsichtlich einer therapeutischen Nutzung schwierig machen. Da sich zahlreiche Untersuchungen auf Interaktionen und Signalwege konzentriert haben, wurde abschließend eine Datenbank entwickelt, welche Analysen von Protein-Interaktionen und Signalwegen nachhaltig voranbringt. Die entwickelte DrumPID-Datenbank stellt insbesondere die Interaktion zwischen einem Medikament und seinem Target in den Fokus und ermöglicht Analysen einzelner Interaktionen und beteiligter Signalwege, bietet zusätzlich aber auch verschiedene Links zu anderen Datenbanken für individuelle weiterführende Analysen. DrumPID ermöglicht ein geeignetes Medikament u. a. für ein vorgegebenes Zielprotein zu finden und dessen Wirkmechanismus und Interaktionskontext zu untersuchen, was zu einem besseren experimentellen Verständnis beitragen kann. Zudem erlaubt DrumPID eine potentielle chemische Leitstruktur für ein Zielprotein zu entwickeln, was z.B. spezifisch ein parasitisches Protein inhibiert, ohne dabei einen toxischen Effekt im Menschen zu haben. Zahlreiche weitere Pharmakabeispiele belegen, dass DrumPID für den täglichen wissenschaftlichen Gebrauch auf dem Gebiet der Analyse von Protein-Pharmaka-Interaktionen und der Medikamentenentwicklung geeignet ist. Die beschriebenen Ergebnisse der Promotionsarbeit wurden in fünf Originalarbeiten, zwei Übersichtsartikeln und einem Buchteil, u. a. in Science Translational Medicine, veröffentlicht, sechs dieser Publikationen erfolgten im Rahmen von Erstautorschaften. N2 - The use of computer-based analysis has become an integral part of life science research. Within this thesis, systems biology investigations have been applied to various biological topics and organisms which provides an innovative and interdisciplinary methodological approach. The basic question was: How do I understand and describe signaling pathways and how can I influence them? The approach combines various biological data sets and data levels starting from the genome and interaction context over semiquantitative simulations towards new interventions and experiments which can be used therapeutically and biotechnologically. The analysis can contribute to - a better understanding of experimental data and biological questions and enables a systematic understanding of the signaling pathways and network effects (e.g. in plants). - They enable the identification of important functional hub nodes as well as the development of new therapeutic strategies for further experimental testing (e.g. tumor models), - also representing a helpful step on the path to personalized medicine (e.g. lncRNAs and tumor models) and drug development (e.g. database DrumPID). (i) As a basis, an integrated systems biology methodology was developed which examines experimental data sets (e.g. transcriptome data) with respect to their biological functions and enables the identification of relevant functional clusters and hub nodes. In the first part of the thesis, analyzes regarding the plant immune system were accomplished. Using the developed methodology, gene expression datasets of A. thaliana infected with the pathogen Pst DC3000 were analyzed in order to investigate the influence of different virulence factors on the host interactome, and to find new modulators of CK-mediated immune defense. In this context, the analysis could show that the secreted defense compounds of Pst DC3000 influence important plant hormone signaling pathways for the immune defense in A. thaliana. Moreover, the results show that the impact on the network behavior of the effector proteins and COR phytotoxins differ from the PAMPs, but there also exists an overlap in common regulated signal pathways as well as an overlap between the two phases of immune response (PTI and ETI) in A. thaliana. In addition, the complex immune response to an infection is also reflected by a higher number of functional clusters and hub nodes in Pst DC3000 compared to the two studied mutants, whereby for Pst DC3000 a highly connected immune-relevant cluster around the JA pathway has been found. Furthermore, using the developed methodology several important hub nodes for the immune defense have been identified. As most important candidates, AHK2 and AAR14 have to be highlighted which are part of the two-component-system of signal transduction of CK and represent in this context important modulators for a CK mediated immune defense. (ii) In the second part of the thesis, analyzes of a HSP90 treatment in lung cancer in an in vitro experiment in 2D and 3D cell cultures were accomplished. In this context using the developed methodology, differences between the two cell cultures explaining the differences in treatment responses were found, and for the two KRAS mutated cell lines A549 and H441 of the 3D test system new prognostic marker and therapeutic drug candidates were identified. However, the analyzes found two functional clusters of protein interactions around p53 and the STAT family which have a connection to HSP90 and might explain the observed treatment differences for the HSP90 inhibition between the two cell culture systems. Considering the mutational background of the cell lines, a prognostic marker signature were found and derived from it HIF1A for the H441 cell line and AMPK for the A549 cell line as new therapeutic drug targets. Moreover, the subsequently performed in silico simulations could show a potential therapeutic effect of the identified drug targets. Furthermore, important experimental read-out parameters were integrated into the in silico lung tumor model, and by considering the mutation background of the used cell lines the HSP90 treatment of the 3D test system could be in silico simulated. In the further course of the thesis, resistance mechanisms after gefitinib treatment with known mutation status for the HCC827 and A549 cell lines were investigated in the in silico lung tumor model and consequently new therapeutic approaches were derived which may be of potential clinical relevance. Here, the in silico simulations for HCC827 cells show that a co-activation of EGFR and c-MET can lead to a gefitinib resistance, whereas in the A549 a co-mutation of KRAS and IGF-1R can contribute to the reduced treatment response. In addition, the simulations reveal that a direct inhibition of the resistance contributing receptors c-MET and IGF-1R reflect not the best treatment strategy in both cases. However, in both cell lines a combined inhibition of PI3K and MEK provides the best therapeutic effect, thus representing a promising new therapeutic approach in gefitinib resistant lung cancer patients. In a further step, the therapeutic potential of the miRNA-21 was examined in the in silico model for the HCC827 cells. The simulations show that an overexpression of the miRNA-21 can contribute to a resistance development after gefitinib treatment, in which an inhibition of the miRNA-21 reverses this effect. Moreover, the results show that a PTEN activation can function as a potential marker of therapeutic success of miRNA-21 inhibition whereas a reduced miRNA-21 expression may serve as a potential marker for a successful gefitinib treatment. (iii) In the third part of the thesis, systematic RNA and protein interactions were investigated. For this, integrated systems biology analyzes were carried out on new identified and previously functional unknown lncRNAs. The analyzes of the cardiac hypertrophy caused upregulated lncRNA Chast have extensive demonstrated that Chast can regulate and bind proteins and transcription factors which regulate signal transduction and gene expression, but it has also a connection to the cardiovascular system and stress-induced cardiac hypertrophy. Based on the results, it can be concluded that Chast can directly and indirectly (a) bind proteins and influence the translation but also possess a chromatin-modifying function and regulate transcription e.g. for cardiac and stress-associated genes, and/or (b) regulate its own transcription in a negative feedback loop. Although lncRNAs often have a low conservation the analysis could show a sequence-structure-conservation for Chast in mammalians. Furthermore, the investigations for two hypoxia induced endothelial lncRNAs have shown that the lncRNA MIR503HG represents a high sequence-structure-conservation in mammalians, whereas the LINC00323-003 shows a low conservation. This underscores the fact that lncRNAs often have a low conservation thereby making studies regarding the therapeutic potential in model organisms difficult. Finally, as numerous analyzes in this thesis have focused on interactions and signaling pathways, a database was developed which brings a sustainable progress in analysis of protein interactions and signaling pathways. The developed DrumPID database puts especially the interaction between a drug and its target into its focus and allows analysis of individual interactions and involved signaling pathways but, additionally, provides various crosslinks to other databases for individual further analysis. DrumPID enables to find a suitable drug, e.g. for a given target protein, and to analyze its mechanism of action as well as interaction context which can contribute to a better understanding of experimental data. Moreover, DrumPID allows to develop a potential chemical lead structure for a target protein which e.g. specifically inhibits a parasitic protein but has no toxic effect in humans. Numerous additional pharmaceutical examples verify that DrumPID is suitable for the daily scientific usage in the field of analysis of protein-drug-interactions and drug development. The described results of the doctoral thesis were published in five research papers, two review articles and a book chapter, e.g. in Science Translational Medicine, including six first authorships. KW - Systembiologie KW - Interaktionen KW - Zytokinine (Pflanzenpathogene) KW - 3D-Zellkulturen (Krebstherapie) KW - Drugtargets KW - Systembiologische Analysen Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-134911 ER - TY - JOUR A1 - Naseem, Muhammad A1 - Kunz, Meik A1 - Dandekar, Thomas T1 - Probing the unknowns in cytokinin-mediated immune defense in Arabidopsis with systems biology approaches JF - Bioinformatics and Biology Insights N2 - Plant hormones involving salicylic acid (SA), jasmonic acid (JA), ethylene (Et), and auxin, gibberellins, and abscisic acid (ABA) are known to regulate host immune responses. However, plant hormone cytokinin has the potential to modulate defense signaling including SA and JA. It promotes plant pathogen and herbivore resistance; underlying mechanisms are still unknown. Using systems biology approaches, we unravel hub points of immune interaction mediated by cytokinin signaling in Arabidopsis. High-confidence Arabidopsis protein-protein interactions (PPI) are coupled to changes in cytokinin-mediated gene expression. Nodes of the cellular interactome that are enriched in immune functions also reconstitute sub-networks. Topological analyses and their specific immunological relevance lead to the identification of functional hubs in cellular interactome. We discuss our identified immune hubs in light of an emerging model of cytokinin-mediated immune defense against pathogen infection in plants. KW - plant hormones KW - systems biology KW - interaction networks KW - gene expression KW - cytokinin Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-120199 SN - 1177-9322 VL - 8 ER - TY - JOUR A1 - März, Juliane A1 - Kurlbaum, Max A1 - Roche-Lancaster, Oisin A1 - Deutschbein, Timo A1 - Peitzsch, Mirko A1 - Prehn, Cornelia A1 - Weismann, Dirk A1 - Robledo, Mercedes A1 - Adamski, Jerzy A1 - Fassnacht, Martin A1 - Kunz, Meik A1 - Kroiss, Matthias T1 - Plasma Metabolome Profiling for the Diagnosis of Catecholamine Producing Tumors JF - Frontiers in Endocrinology N2 - Context Pheochromocytomas and paragangliomas (PPGL) cause catecholamine excess leading to a characteristic clinical phenotype. Intra-individual changes at metabolome level have been described after surgical PPGL removal. The value of metabolomics for the diagnosis of PPGL has not been studied yet. Objective Evaluation of quantitative metabolomics as a diagnostic tool for PPGL. Design Targeted metabolomics by liquid chromatography-tandem mass spectrometry of plasma specimens and statistical modeling using ML-based feature selection approaches in a clinically well characterized cohort study. Patients Prospectively enrolled patients (n=36, 17 female) from the Prospective Monoamine-producing Tumor Study (PMT) with hormonally active PPGL and 36 matched controls in whom PPGL was rigorously excluded. Results Among 188 measured metabolites, only without considering false discovery rate, 4 exhibited statistically significant differences between patients with PPGL and controls (histidine p=0.004, threonine p=0.008, lyso PC a C28:0 p=0.044, sum of hexoses p=0.018). Weak, but significant correlations for histidine, threonine and lyso PC a C28:0 with total urine catecholamine levels were identified. Only the sum of hexoses (reflecting glucose) showed significant correlations with plasma metanephrines. By using ML-based feature selection approaches, we identified diagnostic signatures which all exhibited low accuracy and sensitivity. The best predictive value (sensitivity 87.5%, accuracy 67.3%) was obtained by using Gradient Boosting Machine Modelling. Conclusions The diabetogenic effect of catecholamine excess dominates the plasma metabolome in PPGL patients. While curative surgery for PPGL led to normalization of catecholamine-induced alterations of metabolomics in individual patients, plasma metabolomics are not useful for diagnostic purposes, most likely due to inter-individual variability. KW - adrenal KW - pheochromocytoma KW - paraganglioma KW - targeted metabolomics KW - mass spectronomy KW - catecholamines KW - machine learning KW - feature selection Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-245710 SN - 1664-2392 VL - 12 ER - TY - JOUR A1 - Kunz, Meik A1 - Wolf, Beat A1 - Schulze, Harald A1 - Atlan, David A1 - Walles, Thorsten A1 - Walles, Heike A1 - Dandekar, Thomas T1 - Non-Coding RNAs in Lung Cancer: Contribution of Bioinformatics Analysis to the Development of Non-Invasive Diagnostic Tools JF - Genes N2 - Lung cancer is currently the leading cause of cancer related mortality due to late diagnosis and limited treatment intervention. Non-coding RNAs are not translated into proteins and have emerged as fundamental regulators of gene expression. Recent studies reported that microRNAs and long non-coding RNAs are involved in lung cancer development and progression. Moreover, they appear as new promising non-invasive biomarkers for early lung cancer diagnosis. Here, we highlight their potential as biomarker in lung cancer and present how bioinformatics can contribute to the development of non-invasive diagnostic tools. For this, we discuss several bioinformatics algorithms and software tools for a comprehensive understanding and functional characterization of microRNAs and long non-coding RNAs. KW - lung cancer KW - non-invasive biomarkers KW - miRNAs KW - lncRNAs KW - bioinformatics KW - early diagnosis KW - algorithm Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-147990 VL - 8 IS - 1 ER - TY - JOUR A1 - Kühnemundt, Johanna A1 - Leifeld, Heidi A1 - Scherg, Florian A1 - Schmitt, Matthias A1 - Nelke, Lena C. A1 - Schmitt, Tina A1 - Bauer, Florentin A1 - Göttlich, Claudia A1 - Fuchs, Maximilian A1 - Kunz, Meik A1 - Peindl, Matthias A1 - Brähler, Caroline A1 - Kronenthaler, Corinna A1 - Wischhusen, Jörg A1 - Prelog, Martina A1 - Walles, Heike A1 - Dandekar, Thomas A1 - Dandekar, Gudrun A1 - Nietzer, Sarah L. T1 - Modular micro-physiological human tumor/tissue models based on decellularized tissue for improved preclinical testing JF - ALTEX N2 - High attrition-rates entailed by drug testing in 2D cell culture and animal models stress the need for improved modeling of human tumor tissues. In previous studies our 3D models on a decellularized tissue matrix have shown better predictivity and higher chemoresistance. A single porcine intestine yields material for 150 3D models of breast, lung, colorectal cancer (CRC) or leukemia. The uniquely preserved structure of the basement membrane enables physiological anchorage of endothelial cells and epithelial-derived carcinoma cells. The matrix provides different niches for cell growth: on top as monolayer, in crypts as aggregates and within deeper layers. Dynamic culture in bioreactors enhances cell growth. Comparing gene expression between 2D and 3D cultures, we observed changes related to proliferation, apoptosis and stemness. For drug target predictions, we utilize tumor-specific sequencing data in our in silico model finding an additive effect of metformin and gefitinib treatment for lung cancer in silico, validated in vitro. To analyze mode-of-action, immune therapies such as trispecific T-cell engagers in leukemia, as well as toxicity on non-cancer cells, the model can be modularly enriched with human endothelial cells (hECs), immune cells and fibroblasts. Upon addition of hECs, transmigration of immune cells through the endothelial barrier can be investigated. In an allogenic CRC model we observe a lower basic apoptosis rate after applying PBMCs in 3D compared to 2D, which offers new options to mirror antigen-specific immunotherapies in vitro. In conclusion, we present modular human 3D tumor models with tissue-like features for preclinical testing to reduce animal experiments. KW - modular tumor tissue models KW - invasiveness KW - bioreactor culture KW - combinatorial drug predictions KW - immunotherapies Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-231465 VL - 38 ER - TY - JOUR A1 - Kunz, Meik A1 - Göttlich, Claudia A1 - Walles, Thorsten A1 - Nietzer, Sarah A1 - Dandekar, Gudrun A1 - Dandekar, Thomas T1 - MicroRNA-21 versus microRNA-34: Lung cancer promoting and inhibitory microRNAs analysed in silico and in vitro and their clinical impact JF - Tumor Biology N2 - MicroRNAs are well-known strong RNA regulators modulating whole functional units in complex signaling networks. Regarding clinical application, they have potential as biomarkers for prognosis, diagnosis, and therapy. In this review, we focus on two microRNAs centrally involved in lung cancer progression. MicroRNA-21 promotes and microRNA-34 inhibits cancer progression. We elucidate here involved pathways and imbed these antagonistic microRNAs in a network of interactions, stressing their cancer microRNA biology, followed by experimental and bioinformatics analysis of such microRNAs and their targets. This background is then illuminated from a clinical perspective on microRNA-21 and microRNA-34 as general examples for the complex microRNA biology in lung cancer and its diagnostic value. Moreover, we discuss the immense potential that microRNAs such as microRNA-21 and microRNA-34 imply by their broad regulatory effects. These should be explored for novel therapeutic strategies in the clinic. KW - biomarker KW - microRNA–target interaction KW - microRNAs KW - lung cancer KW - therapeutic strategy KW - bioinformatics Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-158399 VL - 39 IS - 7 ER - TY - JOUR A1 - Temme, Sebastian A1 - Friebe, Daniela A1 - Schmidt, Timo A1 - Poschmann, Gereon A1 - Hesse, Julia A1 - Steckel, Bodo A1 - Stühler, Kai A1 - Kunz, Meik A1 - Dandekar, Thomas A1 - Ding, Zhaoping A1 - Akhyari, Payam A1 - Lichtenberg, Artur A1 - Schrader, Jürgen T1 - Genetic profiling and surface proteome analysis of human atrial stromal cells and rat ventricular epicardium-derived cells reveals novel insights into their cardiogenic potential JF - Stem Cell Research N2 - Epicardium-derived cells (EPDC) and atrial stromal cells (ASC) display cardio-regenerative potential, but the molecular details are still unexplored. Signals which induce activation, migration and differentiation of these cells are largely unknown. Here we have isolated rat ventricular EPDC and rat/human ASC and performed genetic and proteomic profiling. EPDC and ASC expressed epicardial/mesenchymal markers (WT-1, Tbx18, CD73,CD90, CD44, CD105), cardiac markers (Gata4, Tbx5, troponin T) and also contained phosphocreatine. We used cell surface biotinylation to isolate plasma membrane proteins of rEPDC and hASC, Nano-liquid chromatography with subsequent mass spectrometry and bioinformatics analysis identified 396 rat and 239 human plasma membrane proteins with 149 overlapping proteins. Functional GO-term analysis revealed several significantly enriched categories related to extracellular matrix (ECM), cell migration/differentiation, immunology or angiogenesis. We identified receptors for ephrin and growth factors (IGF, PDGF, EGF, anthrax toxin) known to be involved in cardiac repair and regeneration. Functional category enrichment identified clusters around integrins, PI3K/Akt-signaling and various cardiomyopathies. Our study indicates that EPDC and ASC have a similar molecular phenotype related to cardiac healing/regeneration. The cell surface proteome repository will help to further unravel the molecular details of their cardio-regenerative potential and their role in cardiac diseases. KW - Biology KW - Epicardium-derived cells KW - Human atrial stromal cells KW - Cell surface proteomics Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-172716 VL - 25 ER - TY - JOUR A1 - Baur, Florentin A1 - Nietzer, Sarah L. A1 - Kunz, Meik A1 - Saal, Fabian A1 - Jeromin, Julian A1 - Matschos, Stephanie A1 - Linnebacher, Michael A1 - Walles, Heike A1 - Dandekar, Thomas A1 - Dandekar, Gudrun T1 - Connecting cancer pathways to tumor engines: a stratification tool for colorectal cancer combining human in vitro tissue models with boolean in silico models JF - Cancers N2 - To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with BRAF-mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is—in contrast to melanoma—not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification. KW - in silico simulation KW - 3D tissue models KW - colorectal cancer KW - BRAF mutation KW - targeted therapy KW - stratification Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193798 SN - 2072-6694 VL - 12 IS - 1 ER - TY - JOUR A1 - Stojanović, Stevan D. A1 - Fuchs, Maximilian A1 - Fiedler, Jan A1 - Xiao, Ke A1 - Meinecke, Anna A1 - Just, Annette A1 - Pich, Andreas A1 - Thum, Thomas A1 - Kunz, Meik T1 - Comprehensive bioinformatics identifies key microRNA players in ATG7-deficient lung fibroblasts JF - International Journal of Molecular Sciences N2 - Background: Deficient autophagy has been recently implicated as a driver of pulmonary fibrosis, yet bioinformatics approaches to study this cellular process are lacking. Autophagy-related 5 and 7 (ATG5/ATG7) are critical elements of macro-autophagy. However, an alternative ATG5/ATG7-independent macro-autophagy pathway was recently discovered, its regulation being unknown. Using a bioinformatics proteome profiling analysis of ATG7-deficient human fibroblasts, we aimed to identify key microRNA (miR) regulators in autophagy. Method: We have generated ATG7-knockout MRC-5 fibroblasts and performed mass spectrometry to generate a large-scale proteomics dataset. We further quantified the interactions between various proteins combining bioinformatics molecular network reconstruction and functional enrichment analysis. The predicted key regulatory miRs were validated via quantitative polymerase chain reaction. Results: The functional enrichment analysis of the 26 deregulated proteins showed decreased cellular trafficking, increased mitophagy and senescence as the major overarching processes in ATG7-deficient lung fibroblasts. The 26 proteins reconstitute a protein interactome of 46 nodes and miR-regulated interactome of 834 nodes. The miR network shows three functional cluster modules around miR-16-5p, miR-17-5p and let-7a-5p related to multiple deregulated proteins. Confirming these results in a biological setting, serially passaged wild-type and autophagy-deficient fibroblasts displayed senescence-dependent expression profiles of miR-16-5p and miR-17-5p. Conclusions: We have developed a bioinformatics proteome profiling approach that successfully identifies biologically relevant miR regulators from a proteomics dataset of the ATG-7-deficient milieu in lung fibroblasts, and thus may be used to elucidate key molecular players in complex fibrotic pathological processes. The approach is not limited to a specific cell-type and disease, thus highlighting its high relevance in proteome and non-coding RNA research. KW - bioinformatics KW - miR KW - proteomics KW - functional network analysis KW - senescence KW - lung fibrosis KW - autophagy Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-285181 SN - 1422-0067 VL - 21 IS - 11 ER - TY - JOUR A1 - Kann, Simone A1 - Kunz, Meik A1 - Hansen, Jessica A1 - Sievertsen, Jürgen A1 - Crespo, Jose J. A1 - Loperena, Aristides A1 - Arriens, Sandra A1 - Dandekar, Thomas T1 - Chagas disease: detection of Trypanosoma cruzi by a new, high-specific real time PCR JF - Journal of Clinical Medicine N2 - Background: Chagas disease (CD) is a major burden in Latin America, expanding also to non-endemic countries. A gold standard to detect the CD causing pathogen Trypanosoma cruzi is currently not available. Existing real time polymerase chain reactions (RT-PCRs) lack sensitivity and/or specificity. We present a new, highly specific RT-PCR for the diagnosis and monitoring of CD. Material and Methods: We analyzed 352 serum samples from Indigenous people living in high endemic CD areas of Colombia using three leading RT-PCRs (k-DNA-, TCZ-, 18S rRNA-PCR), the newly developed one (NDO-PCR), a Rapid Test/enzyme-linked immuno sorbent assay (ELISA), and immunofluorescence. Eighty-seven PCR-products were verified by sequence analysis after plasmid vector preparation. Results: The NDO-PCR showed the highest sensitivity (92.3%), specificity (100%), and accuracy (94.3%) for T. cruzi detection in the 87 sequenced samples. Sensitivities and specificities of the kDNA-PCR were 89.2%/22.7%, 20.5%/100% for TCZ-PCR, and 1.5%/100% for the 18S rRNA-PCR. The kDNA-PCR revealed a 77.3% false positive rate, mostly due to cross-reactions with T. rangeli (NDO-PCR 0%). TCZ- and 18S rRNA-PCR showed a false negative rate of 79.5% and 98.5% (NDO-PCR 7.7%), respectively. Conclusions: The NDO-PCR demonstrated the highest specificity, sensitivity, and accuracy compared to leading PCRs. Together with serologic tests, it can be considered as a reliable tool for CD detection and can improve CD management significantly. KW - Chagas disease KW - Chagas diagnosis KW - Chagas monitoring KW - Chagas real time PCR KW - Trypanosoma cruzi Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-205746 SN - 2077-0383 VL - 9 IS - 5 ER - TY - JOUR A1 - Vey, Johannes A1 - Kapsner, Lorenz A. A1 - Fuchs, Maximilian A1 - Unberath, Philipp A1 - Veronesi, Giulia A1 - Kunz, Meik T1 - A toolbox for functional analysis and the systematic identification of diagnostic and prognostic gene expression signatures combining meta-analysis and machine learning JF - Cancers N2 - The identification of biomarker signatures is important for cancer diagnosis and prognosis. However, the detection of clinical reliable signatures is influenced by limited data availability, which may restrict statistical power. Moreover, methods for integration of large sample cohorts and signature identification are limited. We present a step-by-step computational protocol for functional gene expression analysis and the identification of diagnostic and prognostic signatures by combining meta-analysis with machine learning and survival analysis. The novelty of the toolbox lies in its all-in-one functionality, generic design, and modularity. It is exemplified for lung cancer, including a comprehensive evaluation using different validation strategies. However, the protocol is not restricted to specific disease types and can therefore be used by a broad community. The accompanying R package vignette runs in ~1 h and describes the workflow in detail for use by researchers with limited bioinformatics training. KW - bioinformatics tool KW - R package KW - machine learning KW - meta-analysis KW - biomarker signature KW - gene expression analysis KW - survival analysis KW - functional analysis Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-193240 SN - 2072-6694 VL - 11 IS - 10 ER -