@article{SbieraKunzWeigandetal.2019, author = {Sbiera, Silviu and Kunz, Meik and Weigand, Isabel and Deutschbein, Timo and Dandekar, Thomas and Fassnacht, Martin}, title = {The new genetic landscape of Cushing's disease: deubiquitinases in the spotlight}, series = {Cancers}, volume = {11}, journal = {Cancers}, number = {11}, issn = {2072-6694}, doi = {10.3390/cancers11111761}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193194}, pages = {1761}, year = {2019}, abstract = {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.}, language = {en} } @article{KunzLiangNillaetal.2016, author = {Kunz, Meik and Liang, Chunguang and Nilla, Santosh and Cecil, Alexander and Dandekar, Thomas}, title = {The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development}, series = {Database}, volume = {2016}, journal = {Database}, doi = {10.1093/database/baw041}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147369}, pages = {baw041}, year = {2016}, abstract = {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.}, language = {en} } @phdthesis{Kunz2017, author = {Kunz, Meik}, title = {Systembiologische Analysen von Interaktionen: Zytokinine (Pflanzenpathogene), 3D-Zellkulturen (Krebstherapie) und Drugtargets}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-134911}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2017}, abstract = {Der Einsatz von computergest{\"u}tzten 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 interdisziplin{\"a}ren methodischen Ansatz. Die grundlegende Frage lautet: Wie verstehe und beschreibe ich Signalwege und wie kann ich sie beeinflussen? Der Ansatz verkn{\"u}pft verschiedene biologische Datens{\"a}tze und Datenebenen miteinander, beginnend vom Genom und Interaktionskontext {\"u}ber semiquantitative Simulationen hin zu neuen Interventionen und Experimenten, welche therapeutisch und biotechnologisch genutzt werden k{\"o}nnen. Die Analysen k{\"o}nnen auf diese Weise - zu einem besseren Verst{\"a}ndnis experimenteller Daten und biologischer Fragestellungen beitragen und erm{\"o}glichen ein systematisches Verst{\"a}ndnis der zugrunde liegenden Signalwege und Netzwerkeffekte (z.B. in Pflanzen). - Dar{\"u}ber hinaus erm{\"o}glichen sie die Identifizierung wichtiger funktioneller Hubproteine und die Entwicklung neuer therapeutischer Strategien f{\"u}r 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 erm{\"o}glicht. In einem ersten Teil wurden Analysen zum pflanzlichen Immunsystem durchgef{\"u}hrt. Mithilfe der entwickelten Methode wurden Genexpressionsdatens{\"a}tze 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 f{\"u}r 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 {\"U}berlappung der beiden Phasen der Immunantwort (PTI und ETI) in A. thaliana finden lassen. Die komplexe Immunantwort auf eine Infektion spiegelt sich zudem in einer h{\"o}heren Anzahl an funktionellen Clustern und Hubproteinen in Pst DC3000 gegen{\"u}ber den beiden untersuchten Mutanten wider, wobei sich f{\"u}r Pst DC3000 insbesondere ein stark vernetztes immunrelevantes Cluster um den JA-Signalweg zeigt. Weiterhin wurden anhand der entwickelten Methode wichtige Hubproteine f{\"u}r die Immunabwehr identifiziert. Als bedeutende Vertreter sind AHK2 und AAR14 zu nennen, welche Teil des Zweikomponentensystems der Signal{\"u}bertragung von CK sind und hierbei wichtige Modulatoren f{\"u}r 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 erkl{\"a}ren, und f{\"u}r die beiden KRAS-mutierten Zelllinien A549 und H441 des 3D-Testsystems neue prognostische und therapeutische Kandidaten identifiziert. Hierbei haben die durchgef{\"u}hrten 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 erkl{\"a}ren k{\"o}nnen. Unter Ber{\"u}cksichtigung des zelllinien-spezifischen Mutationshintergrunds wurde eine prognostische Markersignatur und daraus abgeleitet HIF1A f{\"u}r die H441-Zelllinie und AMPK f{\"u}r die A549-Zelllinie als neue therapeutische Targets gefunden, wobei die anschließend durchgef{\"u}hrten 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 f{\"u}r die verwendeten Zelllinien die HSP90-Behandlung des 3D-Testsystems computergest{\"u}tzt abgebildet werden konnte. Im weiteren Verlauf wurden im in silico-Lungentumormodell Resistenzmechanismen nach einer Gefitinib-Behandlung mit bekanntem Mutationsstatus f{\"u}r die Zelllinien HCC827 und A549 untersucht und daraus folgend neue Therapieans{\"a}tze abgeleitet, die von potentieller klinischer Bedeutung sein k{\"o}nnen. Die durchgef{\"u}hrten in silico-Simulationen f{\"u}r HCC827 konnten hierbei zeigen, dass eine EGFR- und c-MET-Koaktivierung zu einer Gefitinib-Resistenz f{\"u}hren kann, wohingegen bei den A549 eine Komutation von KRAS und IGF-1R zu einem geringen Behandlungsansprechen beitr{\"a}gt. Die Simulationen lassen zudem erkennen, dass eine direkte Inhibierung der an der Resistenzentwicklung beteiligten Rezeptoren c-MET und IGF-1R in beiden F{\"a}llen nicht die bestm{\"o}gliche Therapiestrategie darstellt. In beiden Zelllinien konnte gezeigt werden, dass eine kombinierte Inhibierung von PI3K und MEK den bestm{\"o}glichen 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 f{\"u}r die HCC827-Zelllinie untersucht. Die durchgef{\"u}hrten Simulationen zeigen, dass eine miRNA-21-{\"U}berexpression 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 m{\"o}glicher Marker f{\"u}r 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 durchgef{\"u}hrt. Die Analysen f{\"u}r die infolge einer Herzhypertrophie hochregulierte lncRNA Chast haben umfassend gezeigt, dass diese Proteine und Transkriptionsfaktoren regulieren und binden kann, welche die Signal{\"u}bertragung und Genexpression regulieren, aber auch eine Verbindung zum kardiovaskul{\"a}ren System und stressinduzierter Herzhypertrophie besitzt. Anhand der Ergebnisse l{\"a}sst 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. f{\"u}r 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 durchgef{\"u}hrten Analysen f{\"u}r Chast eine Sequenz-Struktur-Konservierung in S{\"a}ugetieren aufzeigen. Weiterhin haben die Untersuchungen an zwei hypoxie-induzierten lncRNAs in Endothelzellen gezeigt, dass die lncRNA MIR503HG eine hohe Sequenz-Struktur-Konservierung in S{\"a}ugetieren besitzt, wohingegen die LINC00323-003 eine geringe Konservierung aufzeigt. Dies untermauert die Tatsache, dass lncRNAs h{\"a}ufig 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 erm{\"o}glicht Analysen einzelner Interaktionen und beteiligter Signalwege, bietet zus{\"a}tzlich aber auch verschiedene Links zu anderen Datenbanken f{\"u}r individuelle weiterf{\"u}hrende Analysen. DrumPID erm{\"o}glicht ein geeignetes Medikament u. a. f{\"u}r ein vorgegebenes Zielprotein zu finden und dessen Wirkmechanismus und Interaktionskontext zu untersuchen, was zu einem besseren experimentellen Verst{\"a}ndnis beitragen kann. Zudem erlaubt DrumPID eine potentielle chemische Leitstruktur f{\"u}r 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 f{\"u}r den t{\"a}glichen wissenschaftlichen Gebrauch auf dem Gebiet der Analyse von Protein-Pharmaka-Interaktionen und der Medikamentenentwicklung geeignet ist. Die beschriebenen Ergebnisse der Promotionsarbeit wurden in f{\"u}nf Originalarbeiten, zwei {\"U}bersichtsartikeln und einem Buchteil, u. a. in Science Translational Medicine, ver{\"o}ffentlicht, sechs dieser Publikationen erfolgten im Rahmen von Erstautorschaften.}, subject = {Systembiologie}, language = {de} } @article{NaseemKunzDandekar2014, author = {Naseem, Muhammad and Kunz, Meik and Dandekar, Thomas}, title = {Probing the unknowns in cytokinin-mediated immune defense in Arabidopsis with systems biology approaches}, series = {Bioinformatics and Biology Insights}, volume = {8}, journal = {Bioinformatics and Biology Insights}, issn = {1177-9322}, doi = {10.4137/bbi.s13462}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-120199}, pages = {35-44}, year = {2014}, abstract = {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.}, language = {en} } @article{MaerzKurlbaumRocheLancasteretal.2021, author = {M{\"a}rz, Juliane and Kurlbaum, Max and Roche-Lancaster, Oisin and Deutschbein, Timo and Peitzsch, Mirko and Prehn, Cornelia and Weismann, Dirk and Robledo, Mercedes and Adamski, Jerzy and Fassnacht, Martin and Kunz, Meik and Kroiss, Matthias}, title = {Plasma Metabolome Profiling for the Diagnosis of Catecholamine Producing Tumors}, series = {Frontiers in Endocrinology}, volume = {12}, journal = {Frontiers in Endocrinology}, issn = {1664-2392}, doi = {10.3389/fendo.2021.722656}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-245710}, year = {2021}, abstract = {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.}, language = {en} } @article{KunzWolfSchulzeetal.2016, author = {Kunz, Meik and Wolf, Beat and Schulze, Harald and Atlan, David and Walles, Thorsten and Walles, Heike and Dandekar, Thomas}, title = {Non-Coding RNAs in Lung Cancer: Contribution of Bioinformatics Analysis to the Development of Non-Invasive Diagnostic Tools}, series = {Genes}, volume = {8}, journal = {Genes}, number = {1}, doi = {10.3390/genes8010008}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147990}, pages = {8}, year = {2016}, abstract = {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.}, language = {en} } @article{KuehnemundtLeifeldSchergetal.2021, author = {K{\"u}hnemundt, Johanna and Leifeld, Heidi and Scherg, Florian and Schmitt, Matthias and Nelke, Lena C. and Schmitt, Tina and Bauer, Florentin and G{\"o}ttlich, Claudia and Fuchs, Maximilian and Kunz, Meik and Peindl, Matthias and Br{\"a}hler, Caroline and Kronenthaler, Corinna and Wischhusen, J{\"o}rg and Prelog, Martina and Walles, Heike and Dandekar, Thomas and Dandekar, Gudrun and Nietzer, Sarah L.}, title = {Modular micro-physiological human tumor/tissue models based on decellularized tissue for improved preclinical testing}, series = {ALTEX}, volume = {38}, journal = {ALTEX}, doi = {10.14573/altex.2008141}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-231465}, pages = {289-306}, year = {2021}, abstract = {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.}, language = {en} } @article{KunzGoettlichWallesetal.2017, author = {Kunz, Meik and G{\"o}ttlich, Claudia and Walles, Thorsten and Nietzer, Sarah and Dandekar, Gudrun and Dandekar, Thomas}, title = {MicroRNA-21 versus microRNA-34: Lung cancer promoting and inhibitory microRNAs analysed in silico and in vitro and their clinical impact}, series = {Tumor Biology}, volume = {39}, journal = {Tumor Biology}, number = {7}, doi = {10.1177/1010428317706430}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-158399}, year = {2017}, abstract = {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.}, language = {en} } @article{TemmeFriebeSchmidtetal.2017, author = {Temme, Sebastian and Friebe, Daniela and Schmidt, Timo and Poschmann, Gereon and Hesse, Julia and Steckel, Bodo and St{\"u}hler, Kai and Kunz, Meik and Dandekar, Thomas and Ding, Zhaoping and Akhyari, Payam and Lichtenberg, Artur and Schrader, J{\"u}rgen}, title = {Genetic profiling and surface proteome analysis of human atrial stromal cells and rat ventricular epicardium-derived cells reveals novel insights into their cardiogenic potential}, series = {Stem Cell Research}, volume = {25}, journal = {Stem Cell Research}, doi = {10.1016/j.scr.2017.11.006}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-172716}, pages = {183-190}, year = {2017}, abstract = {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.}, language = {en} } @article{BaurNietzerKunzetal.2020, author = {Baur, Florentin and Nietzer, Sarah L. and Kunz, Meik and Saal, Fabian and Jeromin, Julian and Matschos, Stephanie and Linnebacher, Michael and Walles, Heike and Dandekar, Thomas and Dandekar, Gudrun}, title = {Connecting cancer pathways to tumor engines: a stratification tool for colorectal cancer combining human in vitro tissue models with boolean in silico models}, series = {Cancers}, volume = {12}, journal = {Cancers}, number = {1}, issn = {2072-6694}, doi = {10.3390/cancers12010028}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193798}, pages = {28}, year = {2020}, abstract = {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.}, language = {en} } @article{StojanovićFuchsFiedleretal.2020, author = {Stojanović, Stevan D. and Fuchs, Maximilian and Fiedler, Jan and Xiao, Ke and Meinecke, Anna and Just, Annette and Pich, Andreas and Thum, Thomas and Kunz, Meik}, title = {Comprehensive bioinformatics identifies key microRNA players in ATG7-deficient lung fibroblasts}, series = {International Journal of Molecular Sciences}, volume = {21}, journal = {International Journal of Molecular Sciences}, number = {11}, issn = {1422-0067}, doi = {10.3390/ijms21114126}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-285181}, year = {2020}, abstract = {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.}, language = {en} } @article{KannKunzHansenetal.2020, author = {Kann, Simone and Kunz, Meik and Hansen, Jessica and Sievertsen, J{\"u}rgen and Crespo, Jose J. and Loperena, Aristides and Arriens, Sandra and Dandekar, Thomas}, title = {Chagas disease: detection of Trypanosoma cruzi by a new, high-specific real time PCR}, series = {Journal of Clinical Medicine}, volume = {9}, journal = {Journal of Clinical Medicine}, number = {5}, issn = {2077-0383}, doi = {10.3390/jcm9051517}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-205746}, year = {2020}, abstract = {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.}, language = {en} } @article{VeyKapsnerFuchsetal.2019, author = {Vey, Johannes and Kapsner, Lorenz A. and Fuchs, Maximilian and Unberath, Philipp and Veronesi, Giulia and Kunz, Meik}, title = {A toolbox for functional analysis and the systematic identification of diagnostic and prognostic gene expression signatures combining meta-analysis and machine learning}, series = {Cancers}, volume = {11}, journal = {Cancers}, number = {10}, issn = {2072-6694}, doi = {10.3390/cancers11101606}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-193240}, year = {2019}, abstract = {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.}, language = {en} }