Beißbarth, Tim

[["dc.bibliographiccitation.firstpage","20"],["dc.bibliographiccitation.journal","BMC systems biology"],["dc.bibliographiccitation.volume","3"],["dc.contributor.author","Sahin, Özgür"],["dc.contributor.author","Fröhlich, Holger"],["dc.contributor.author","Löbke, Christian"],["dc.contributor.author","Korf, Ulrike"],["dc.contributor.author","Burmester, Sara"],["dc.contributor.author","Majety, Meher"],["dc.contributor.author","Mattern, Jens"],["dc.contributor.author","Schupp, Ingo"],["dc.contributor.author","Chaouiya, Claudine"],["dc.contributor.author","Thieffry, Denis"],["dc.contributor.author","Poustka, Annemarie"],["dc.contributor.author","Wiemann, Stefan"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Arlt, Dorit"],["dc.date.accessioned","2019-07-09T11:52:38Z"],["dc.date.available","2019-07-09T11:52:38Z"],["dc.date.issued","2009"],["dc.description.abstract","In breast cancer, overexpression of the transmembrane tyrosine kinase ERBB2 is an adverse prognostic marker, and occurs in almost 30% of the patients. For therapeutic intervention, ERBB2 is targeted by monoclonal antibody trastuzumab in adjuvant settings; however, de novo resistance to this antibody is still a serious issue, requiring the identification of additional targets to overcome resistance. In this study, we have combined computational simulations, experimental testing of simulation results, and finally reverse engineering of a protein interaction network to define potential therapeutic strategies for de novo trastuzumab resistant breast cancer."],["dc.description.abstract","First, we employed Boolean logic to model regulatory interactions and simulated single and multiple protein loss-of-functions. Then, our simulation results were tested experimentally by producing single and double knockdowns of the network components and measuring their effects on G1/S transition during cell cycle progression. Combinatorial targeting of ERBB2 and EGFR did not affect the response to trastuzumab in de novo resistant cells, which might be due to decoupling of receptor activation and cell cycle progression. Furthermore, examination of c-MYC in resistant as well as in sensitive cell lines, using a specific chemical inhibitor of c-MYC (alone or in combination with trastuzumab), demonstrated that both trastuzumab sensitive and resistant cells responded to c-MYC perturbation."],["dc.description.abstract","In this study, we connected ERBB signaling with G1/S transition of the cell cycle via two major cell signaling pathways and two key transcription factors, to model an interaction network that allows for the identification of novel targets in the treatment of trastuzumab resistant breast cancer. Applying this new strategy, we found that, in contrast to trastuzumab sensitive breast cancer cells, combinatorial targeting of ERBB receptors or of key signaling intermediates does not have potential for treatment of de novo trastuzumab resistant cells. Instead, c-MYC was identified as a novel potential target protein in breast cancer cells."],["dc.identifier.doi","10.1186/1752-0509-3-1"],["dc.identifier.pmid","19118495"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/5813"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/60247"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","1752-0509"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.subject.ddc","610"],["dc.subject.mesh","Antibodies, Monoclonal"],["dc.subject.mesh","Blotting, Western"],["dc.subject.mesh","Breast Neoplasms"],["dc.subject.mesh","Cell Line, Tumor"],["dc.subject.mesh","Computer Simulation"],["dc.subject.mesh","DNA-Binding Proteins"],["dc.subject.mesh","Drug Delivery Systems"],["dc.subject.mesh","Female"],["dc.subject.mesh","G1 Phase"],["dc.subject.mesh","Humans"],["dc.subject.mesh","Models, Biological"],["dc.subject.mesh","Protein Engineering"],["dc.subject.mesh","Receptor, Epidermal Growth Factor"],["dc.subject.mesh","Reverse Transcriptase Polymerase Chain Reaction"],["dc.subject.mesh","Signal Transduction"],["dc.subject.mesh","Transcription Factors"],["dc.title","Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance."],["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.firstpage","12574"],["dc.bibliographiccitation.issue","14"],["dc.bibliographiccitation.journal","Oncotarget"],["dc.bibliographiccitation.lastpage","12586"],["dc.bibliographiccitation.volume","6"],["dc.contributor.author","Srinivas, Upadhyayula Sai"],["dc.contributor.author","Dyczkowski, Jerzy"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Gaedcke, Jochen"],["dc.contributor.author","Mansour, Wael Y."],["dc.contributor.author","Borgmann, Kerstin"],["dc.contributor.author","Dobbelstein, Matthias"],["dc.date.accessioned","2019-07-09T11:42:37Z"],["dc.date.available","2019-07-09T11:42:37Z"],["dc.date.issued","2015-05-20"],["dc.description.abstract","Malignant tumors of the rectum are treated by neoadjuvant radiochemotherapy. This involves a combination of 5-fluorouracil (5-FU) and double stranded DNA-break (DSB)-inducing radiotherapy. Here we explored how 5-FU cooperates with DSB-induction to achieve sustainable DNA damage in colorectal cancer (CRC) cells. After DSB induction by neocarzinostatin, phosphorylated histone 2AX (γ-H2AX) rapidly accumulated but then largely vanished within a few hours. In contrast, when CRC cells were pre-treated with 5-FU, gammaH2AX remained for at least 24 hours. GFP-reporter assays revealed that 5-FU decreases the efficiency of homologous recombination (HR) repair. However, 5-FU did not prevent the initial steps of HR repair, such as the accumulation of RPA and Rad51 at nuclear foci. Thus, we propose that 5-FU interferes with the continuation of HR repair, e. g. the synthesis of new DNA strands. Two key mediators of HR, Rad51 and BRCA2, were found upregulated in CRC biopsies as compared to normal mucosa. Inhibition of HR by targeting Rad51 enhanced DNA damage upon DSB-inducing treatment, outlining an alternative way of enhancing therapeutic efficacy. Taken together, our results strongly suggest that interfering with HR represents a key mechanism to enhance the efficacy when treating CRC with DNA-damaging therapy."],["dc.identifier.doi","10.18632/oncotarget.3728"],["dc.identifier.fs","612071"],["dc.identifier.pmid","25909291"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/13608"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/58708"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","1949-2553"],["dc.rights","CC BY 3.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/3.0"],["dc.subject.mesh","Antineoplastic Agents"],["dc.subject.mesh","Cell Line, Tumor"],["dc.subject.mesh","Chemoradiotherapy"],["dc.subject.mesh","Colorectal Neoplasms"],["dc.subject.mesh","DNA Breaks, Double-Stranded"],["dc.subject.mesh","Flow Cytometry"],["dc.subject.mesh","Fluorouracil"],["dc.subject.mesh","Humans"],["dc.subject.mesh","Immunoblotting"],["dc.subject.mesh","Microscopy, Confocal"],["dc.subject.mesh","Microscopy, Fluorescence"],["dc.subject.mesh","Oligonucleotide Array Sequence Analysis"],["dc.subject.mesh","Recombinational DNA Repair"],["dc.subject.mesh","Reverse Transcriptase Polymerase Chain Reaction"],["dc.title","5-Fluorouracil sensitizes colorectal tumor cells towards double stranded DNA breaks by interfering with homologous recombination repair."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]