Kube, Dieter

[["dc.bibliographiccitation.artnumber","1514"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Nature communications"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Feist, Maren"],["dc.contributor.author","Schwarzfischer, Philipp"],["dc.contributor.author","Heinrich, Paul"],["dc.contributor.author","Sun, Xueni"],["dc.contributor.author","Kemper, Judith"],["dc.contributor.author","von Bonin, Frederike"],["dc.contributor.author","Perez-Rubio, Paula"],["dc.contributor.author","Taruttis, Franziska"],["dc.contributor.author","Rehberg, Thorsten"],["dc.contributor.author","Dettmer, Katja"],["dc.contributor.author","Gronwald, Wolfram"],["dc.contributor.author","Reinders, Jörg"],["dc.contributor.author","Engelmann, Julia C."],["dc.contributor.author","Dudek, Jan"],["dc.contributor.author","Klapper, Wolfram"],["dc.contributor.author","Trümper, Lorenz"],["dc.contributor.author","Spang, Rainer"],["dc.contributor.author","Oefner, Peter J."],["dc.contributor.author","Kube, Dieter"],["dc.date.accessioned","2019-07-09T11:45:23Z"],["dc.date.available","2019-07-09T11:45:23Z"],["dc.date.issued","2018"],["dc.description.abstract","Knowledge of stromal factors that have a role in the transcriptional regulation of metabolic pathways aside from c-Myc is fundamental to improvements in lymphoma therapy. Using a MYC-inducible human B-cell line, we observed the cooperative activation of STAT3 and NF-κB by IL10 and CpG stimulation. We show that IL10 + CpG-mediated cell proliferation of MYClow cells depends on glutaminolysis. By 13C- and 15N-tracing of glutamine metabolism and metabolite rescue experiments, we demonstrate that GOT2 provides aspartate and nucleotides to cells with activated or aberrant Jak/STAT and NF-κB signaling. A model of GOT2 transcriptional regulation is proposed, in which the cooperative phosphorylation of STAT3 and direct joint binding of STAT3 and p65/NF-κB to the proximal GOT2 promoter are important. Furthermore, high aberrant GOT2 expression is prognostic in diffuse large B-cell lymphoma underscoring the current findings and importance of stromal factors in lymphoma biology."],["dc.identifier.doi","10.1038/s41467-018-03803-x"],["dc.identifier.pmid","29666362"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15191"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59220"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","2041-1723"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.subject.ddc","610"],["dc.title","Cooperative STAT/NF-κB signaling regulates lymphoma metabolic reprogramming and aberrant GOT2 expression."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e0197162"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","PLOS ONE"],["dc.bibliographiccitation.volume","13"],["dc.contributor.author","Wolff, Alexander"],["dc.contributor.author","Bayerlová, Michaela"],["dc.contributor.author","Gaedcke, Jochen"],["dc.contributor.author","Kube, Dieter"],["dc.contributor.author","Beißbarth, Tim"],["dc.date.accessioned","2019-07-09T11:45:42Z"],["dc.date.available","2019-07-09T11:45:42Z"],["dc.date.issued","2018"],["dc.description.abstract","BACKGROUND: Pipeline comparisons for gene expression data are highly valuable for applied real data analyses, as they enable the selection of suitable analysis strategies for the dataset at hand. Such pipelines for RNA-Seq data should include mapping of reads, counting and differential gene expression analysis or preprocessing, normalization and differential gene expression in case of microarray analysis, in order to give a global insight into pipeline performances. METHODS: Four commonly used RNA-Seq pipelines (STAR/HTSeq-Count/edgeR, STAR/RSEM/edgeR, Sailfish/edgeR, TopHat2/Cufflinks/CuffDiff)) were investigated on multiple levels (alignment and counting) and cross-compared with the microarray counterpart on the level of gene expression and gene ontology enrichment. For these comparisons we generated two matched microarray and RNA-Seq datasets: Burkitt Lymphoma cell line data and rectal cancer patient data. RESULTS: The overall mapping rate of STAR was 98.98% for the cell line dataset and 98.49% for the patient dataset. Tophat's overall mapping rate was 97.02% and 96.73%, respectively, while Sailfish had only an overall mapping rate of 84.81% and 54.44%. The correlation of gene expression in microarray and RNA-Seq data was moderately worse for the patient dataset (ρ = 0.67-0.69) than for the cell line dataset (ρ = 0.87-0.88). An exception were the correlation results of Cufflinks, which were substantially lower (ρ = 0.21-0.29 and 0.34-0.53). For both datasets we identified very low numbers of differentially expressed genes using the microarray platform. For RNA-Seq we checked the agreement of differentially expressed genes identified in the different pipelines and of GO-term enrichment results. CONCLUSION: In conclusion the combination of STAR aligner with HTSeq-Count followed by STAR aligner with RSEM and Sailfish generated differentially expressed genes best suited for the dataset at hand and in agreement with most of the other transcriptomics pipelines."],["dc.identifier.doi","10.1371/journal.pone.0197162"],["dc.identifier.pmid","29768462"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15290"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59290"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.haserratum","/handle/2/63504"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.subject.mesh","Burkitt Lymphoma"],["dc.subject.mesh","Cell Line, Tumor"],["dc.subject.mesh","Gene Expression Regulation, Neoplastic"],["dc.subject.mesh","High-Throughput Nucleotide Sequencing"],["dc.subject.mesh","Humans"],["dc.subject.mesh","Oligonucleotide Array Sequence Analysis"],["dc.subject.mesh","RNA, Neoplasm"],["dc.subject.mesh","Rectal Neoplasms"],["dc.title","A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","Suppl 1"],["dc.bibliographiccitation.journal","Cell Communication and Signaling"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Kube, D."],["dc.contributor.author","Matulewicz, K."],["dc.contributor.author","Schrader, A."],["dc.contributor.author","Bentink, S."],["dc.contributor.author","Spang, R."],["dc.contributor.author","Murray, P."],["dc.contributor.author","Vockerodt, M."],["dc.contributor.author","Trümper, L."],["dc.date.accessioned","2011-04-15T08:48:01Z"],["dc.date.accessioned","2021-10-27T13:22:36Z"],["dc.date.available","2011-04-15T08:48:01Z"],["dc.date.available","2021-10-27T13:22:36Z"],["dc.date.issued","2009"],["dc.identifier.doi","10.1186/1478-811X-7-S1-A33"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/6143"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/92110"],["dc.language.iso","en"],["dc.notes.intern","Migrated from goescholar"],["dc.relation.orgunit","Universitätsmedizin Göttingen"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.subject.ddc","610"],["dc.title","Dissecting the molecular pathogenisis of Burkitt lymphoma"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3170"],["dc.bibliographiccitation.issue","11"],["dc.bibliographiccitation.journal","International Journal of Cancer"],["dc.bibliographiccitation.lastpage","3183"],["dc.bibliographiccitation.volume","146"],["dc.contributor.author","Blazquez, Raquel"],["dc.contributor.author","Rietkötter, Eva"],["dc.contributor.author","Wenske, Britta"],["dc.contributor.author","Wlochowitz, Darius"],["dc.contributor.author","Sparrer, Daniela"],["dc.contributor.author","Vollmer, Elena"],["dc.contributor.author","Müller, Gunnar"],["dc.contributor.author","Seegerer, Julia"],["dc.contributor.author","Sun, Xueni"],["dc.contributor.author","Dettmer, Katja"],["dc.contributor.author","Barrantes‐Freer, Alonso"],["dc.contributor.author","Stange, Lena"],["dc.contributor.author","Utpatel, Kirsten"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Treiber, Hannes"],["dc.contributor.author","Bohnenberger, Hanibal"],["dc.contributor.author","Lenz, Christof"],["dc.contributor.author","Schulz, Matthias"],["dc.contributor.author","Reimelt, Christian"],["dc.contributor.author","Hackl, Christina"],["dc.contributor.author","Grade, Marian"],["dc.contributor.author","Büyüktas, Deram"],["dc.contributor.author","Siam, Laila"],["dc.contributor.author","Balkenhol, Marko"],["dc.contributor.author","Stadelmann, Christine"],["dc.contributor.author","Kube, Dieter"],["dc.contributor.author","Krahn, Michael P."],["dc.contributor.author","Proescholdt, Martin A."],["dc.contributor.author","Riemenschneider, Markus J."],["dc.contributor.author","Evert, Matthias"],["dc.contributor.author","Oefner, Peter J."],["dc.contributor.author","Klein, Chistoph A."],["dc.contributor.author","Hanisch, Uwe K."],["dc.contributor.author","Binder, Claudia"],["dc.contributor.author","Pukrop, Tobias"],["dc.date.accessioned","2019-12-09T11:26:05Z"],["dc.date.accessioned","2021-10-27T13:21:49Z"],["dc.date.available","2019-12-09T11:26:05Z"],["dc.date.available","2021-10-27T13:21:49Z"],["dc.date.issued","2020"],["dc.description.abstract","More than half of all brain metastases show infiltrating rather than displacing growth at the macro-metastasis/organ parenchyma interface (MMPI), a finding associated with shorter survival. The lymphoid enhancer-binding factor-1 (LEF1) is an epithelial-mesenchymal transition (EMT) transcription factor that is commonly overexpressed in brain-colonizing cancer cells. Here, we overexpressed LEF1 in an in vivo breast cancer brain colonization model. It shortened survival, albeit without engaging EMT at the MMPI. By differential proteome analysis, we identified a novel function of LEF1 as a regulator of the glutathione (GSH) system, the principal cellular redox buffer. LEF1 overexpression also conferred resistance against therapeutic GSH depletion during brain colonization and improved management of intracellular ROS. We conclude that besides EMT, LEF1 facilitates metastasis by improving the antioxidative capacity of epithelial breast cancer cells, in particular during colonization of the brain parenchyma."],["dc.identifier.doi","10.1002/ijc.32742"],["dc.identifier.eissn","1097-0215"],["dc.identifier.issn","0020-7136"],["dc.identifier.pmid","31626715"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/16874"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/92047"],["dc.language.iso","en"],["dc.notes.intern","Migrated from goescholar"],["dc.relation.eissn","1097-0215"],["dc.relation.issn","1097-0215"],["dc.relation.issn","0020-7136"],["dc.relation.orgunit","Universitätsmedizin Göttingen"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.title","LEF1 supports metastatic brain colonization by regulating glutathione metabolism and increasing ROS resistance in breast cancer"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]