Wachter, Astrid

[["dc.bibliographiccitation.firstpage","549"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Cancer Cell"],["dc.bibliographiccitation.lastpage","+"],["dc.bibliographiccitation.volume","31"],["dc.contributor.author","Mohr, Sebastian"],["dc.contributor.author","Döbele, Carmen"],["dc.contributor.author","Comoglio, Federico"],["dc.contributor.author","Berg, Tobias"],["dc.contributor.author","Beck, Julia"],["dc.contributor.author","Bohnenberger, Hanibal"],["dc.contributor.author","Alexe, Gabriela"],["dc.contributor.author","Corso, Jasmin"],["dc.contributor.author","Ströbel, Philipp"],["dc.contributor.author","Wachter, Astrid"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Schnuetgen, Frank"],["dc.contributor.author","Cremer, Anjali"],["dc.contributor.author","Haetscher, Nadine"],["dc.contributor.author","Goellner, Stefanie"],["dc.contributor.author","Rouhi, Arefeh"],["dc.contributor.author","Palmqvist, Lars"],["dc.contributor.author","Rieger, Michael A."],["dc.contributor.author","Schroeder, Timm"],["dc.contributor.author","Boenig, Halvard"],["dc.contributor.author","Meuller-Tidow, Carsten"],["dc.contributor.author","Kuchenbauer, Florian"],["dc.contributor.author","Schuetz, Ekkehard"],["dc.contributor.author","Green, Anthony R."],["dc.contributor.author","Urlaub, Henning"],["dc.contributor.author","Stegmaier, Kimberly"],["dc.contributor.author","Humphries, R. Keith"],["dc.contributor.author","Serve, Hubert"],["dc.contributor.author","Oellerich, Thomas"],["dc.date.accessioned","2018-11-07T10:25:02Z"],["dc.date.available","2018-11-07T10:25:02Z"],["dc.date.issued","2017"],["dc.description.abstract","The transcription factor Meis1 drives myeloid leukemogenesis in the context of Hox gene overexpression but is currently considered undruggable. We therefore investigated whether myeloid progenitor cells transformed by Hoxa9 and Meis1 become addicted to targetable signaling pathways. A comprehensive (phospho) proteomic analysis revealed that Meis1 increased Syk protein expression and activity. Syk upregulation occurs through a Meis1-dependent feedback loop. By dissecting this loop, we show that Syk is a direct target of miR-146a, whose expression is indirectly regulated by Meis1 through the transcription factor PU. 1. In the context of Hoxa9 overexpression, Syk signaling induces Meis1, recapitulating several leukemogenic features of Hoxa9/Meis1-driven leukemia. Finally, Syk inhibition disrupts the identified regulatory loop, prolonging survival of mice with Hoxa9/Meis1-driven leukemia."],["dc.identifier.doi","10.1016/j.ccell.2017.03.001"],["dc.identifier.isi","000398670600010"],["dc.identifier.pmid","28399410"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14438"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/42772"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Cell Press"],["dc.relation.issn","1878-3686"],["dc.relation.issn","1535-6108"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Hoxa9 and Meis1 Cooperatively Induce Addiction to Syk Signaling by Suppressing miR-146a in Acute Myeloid Leukemia"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Haematologica"],["dc.bibliographiccitation.volume","100"],["dc.contributor.author","Oellerich, Thomas"],["dc.contributor.author","Corso, Jasmin"],["dc.contributor.author","Beck, J."],["dc.contributor.author","Pan, K.-T."],["dc.contributor.author","Döbele, Carmen"],["dc.contributor.author","Wachter, Astrid"],["dc.contributor.author","Lenz, Christof"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Schuetz, Eckehardt"],["dc.contributor.author","Tomska, Katarzyna"],["dc.contributor.author","Sellner, L."],["dc.contributor.author","Zenz, Thorsten"],["dc.contributor.author","Serve, Hubert"],["dc.contributor.author","Urlaub, Henning"],["dc.date.accessioned","2018-11-07T09:56:10Z"],["dc.date.available","2018-11-07T09:56:10Z"],["dc.date.issued","2015"],["dc.format.extent","178"],["dc.identifier.isi","000361204901386"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/36907"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Ferrata Storti Foundation"],["dc.publisher.place","Pavia"],["dc.relation.eventlocation","Vienna, AUSTRIA"],["dc.relation.issn","0390-6078"],["dc.title","THE B CELL RECEPTOR SIGNALING OUTPUT IN BURKITT'S LYMPHOMA IS GENOTYPE-SPECIFIC AND IMPACTS SENSITIVITY TOWARDS BCR SIGNALING INHIBITORS"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","035006"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Biomedical physics & engineering express"],["dc.bibliographiccitation.volume","2"],["dc.contributor.author","Pohl, A."],["dc.contributor.author","Wachter, A."],["dc.contributor.author","Hatam, N."],["dc.contributor.author","Leonhardt, S."],["dc.date.accessioned","2020-12-10T18:16:00Z"],["dc.date.available","2020-12-10T18:16:00Z"],["dc.date.issued","2016"],["dc.identifier.doi","10.1088/2057-1976/2/3/035006"],["dc.identifier.eissn","2057-1976"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/75020"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","A computational model of a human single sinoatrial node cell"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","1296"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","BMC Cancer"],["dc.bibliographiccitation.volume","21"],["dc.contributor.author","Giacomelli, Chiara"],["dc.contributor.author","Jung, Janine"],["dc.contributor.author","Wachter, Astrid"],["dc.contributor.author","Ibing, Susanne"],["dc.contributor.author","Will, Rainer"],["dc.contributor.author","Uhlmann, Stefan"],["dc.contributor.author","Mannsperger, Heiko"],["dc.contributor.author","Sahin, Özgür"],["dc.contributor.author","Yarden, Yosef"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Wiemann, Stefan"],["dc.date.accessioned","2022-01-11T14:06:08Z"],["dc.date.available","2022-01-11T14:06:08Z"],["dc.date.issued","2021"],["dc.description.abstract","Abstract Background Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC). Treatment options for TNBC patients are limited and further insights into disease aetiology are needed to develop better therapeutic approaches. microRNAs’ ability to regulate multiple targets could hold a promising discovery approach to pathways relevant for TNBC aggressiveness. Thus, we address the role of miRNAs in controlling three signalling pathways relevant to the biology of TNBC, and their downstream phenotypes. Methods To identify miRNAs regulating WNT/β-catenin, c-Met, and integrin signalling pathways, we performed a high-throughput targeted proteomic approach, investigating the effect of 800 miRNAs on the expression of 62 proteins in the MDA-MB-231 TNBC cell line. We then developed a novel network analysis, Pathway Coregulatory (PC) score, to detect miRNAs regulating these three pathways. Using in vitro assays for cell growth, migration, apoptosis, and stem-cell content, we validated the function of candidate miRNAs. Bioinformatic analyses using BC patients’ datasets were employed to assess expression of miRNAs as well as their pathological relevance in TNBC patients. Results We identified six candidate miRNAs coordinately regulating the three signalling pathways. Quantifying cell growth of three TNBC cell lines upon miRNA gain-of-function experiments, we characterised miR-193b as a strong and consistent repressor of proliferation. Importantly, the effects of miR-193b were stronger than chemical inhibition of the individual pathways. We further demonstrated that miR-193b induced apoptosis, repressed migration, and regulated stem-cell markers in MDA-MB-231 cells. Furthermore, miR-193b expression was the lowest in patients classified as TNBC or Basal compared to other subtypes. Gene Set Enrichment Analysis showed that miR-193b expression was significantly associated with reduced activity of WNT/β-catenin and c-Met signalling pathways in TNBC patients. Conclusions Integrating miRNA-mediated effects and protein functions on networks, we show that miRNAs predominantly act in a coordinated fashion to activate or repress connected signalling pathways responsible for metastatic traits in TNBC. We further demonstrate that our top candidate, miR-193b, regulates these phenotypes to an extent stronger than individual pathway inhibition, thus emphasizing that its effect on TNBC aggressiveness is mediated by the coordinated repression of these functionally interconnected pathways."],["dc.description.abstract","Abstract Background Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC). Treatment options for TNBC patients are limited and further insights into disease aetiology are needed to develop better therapeutic approaches. microRNAs\\’ ability to regulate multiple targets could hold a promising discovery approach to pathways relevant for TNBC aggressiveness. Thus, we address the role of miRNAs in controlling three signalling pathways relevant to the biology of TNBC, and their downstream phenotypes. Methods To identify miRNAs regulating WNT/β-catenin, c-Met, and integrin signalling pathways, we performed a high-throughput targeted proteomic approach, investigating the effect of 800 miRNAs on the expression of 62 proteins in the MDA-MB-231 TNBC cell line. We then developed a novel network analysis, Pathway Coregulatory (PC) score, to detect miRNAs regulating these three pathways. Using in vitro assays for cell growth, migration, apoptosis, and stem-cell content, we validated the function of candidate miRNAs. Bioinformatic analyses using BC patients\\’ datasets were employed to assess expression of miRNAs as well as their pathological relevance in TNBC patients. Results We identified six candidate miRNAs coordinately regulating the three signalling pathways. Quantifying cell growth of three TNBC cell lines upon miRNA gain-of-function experiments, we characterised miR-193b as a strong and consistent repressor of proliferation. Importantly, the effects of miR-193b were stronger than chemical inhibition of the individual pathways. We further demonstrated that miR-193b induced apoptosis, repressed migration, and regulated stem-cell markers in MDA-MB-231 cells. Furthermore, miR-193b expression was the lowest in patients classified as TNBC or Basal compared to other subtypes. Gene Set Enrichment Analysis showed that miR-193b expression was significantly associated with reduced activity of WNT/β-catenin and c-Met signalling pathways in TNBC patients. Conclusions Integrating miRNA-mediated effects and protein functions on networks, we show that miRNAs predominantly act in a coordinated fashion to activate or repress connected signalling pathways responsible for metastatic traits in TNBC. We further demonstrate that our top candidate, miR-193b, regulates these phenotypes to an extent stronger than individual pathway inhibition, thus emphasizing that its effect on TNBC aggressiveness is mediated by the coordinated repression of these functionally interconnected pathways."],["dc.identifier.doi","10.1186/s12885-021-08955-6"],["dc.identifier.pii","8955"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/97833"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-507"],["dc.relation.eissn","1471-2407"],["dc.title","Coordinated regulation of WNT/β-catenin, c-Met, and integrin signalling pathways by miR-193b controls triple negative breast cancer metastatic traits"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Der Internist"],["dc.bibliographiccitation.volume","57"],["dc.contributor.author","Schroeter, M."],["dc.contributor.author","Koehler, H."],["dc.contributor.author","Wachter, Astrid"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Schillinger, Wolfgang"],["dc.date.accessioned","2018-11-07T10:15:55Z"],["dc.date.available","2018-11-07T10:15:55Z"],["dc.date.issued","2016"],["dc.format.extent","S30"],["dc.identifier.isi","000375417500054"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/40917"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.publisher.place","New york"],["dc.relation.issn","1432-1289"],["dc.relation.issn","0020-9554"],["dc.title","The Early use of Impella-Ventricular Assist Devices in Patients with acute Coronary Syndrome and cardiogenic Shock is Based on the Advantage of 1-Year Mortality"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","3072"],["dc.bibliographiccitation.issue","18"],["dc.bibliographiccitation.journal","Bioinformatics"],["dc.bibliographiccitation.lastpage","3074"],["dc.bibliographiccitation.volume","31"],["dc.contributor.author","Wachter, Astrid"],["dc.contributor.author","Beißbarth, Tim"],["dc.date.accessioned","2018-11-07T09:51:37Z"],["dc.date.available","2018-11-07T09:51:37Z"],["dc.date.issued","2015"],["dc.description.abstract","Characterization of biological processes is progressively enabled with the increased generation of omics data on different signaling levels. Here we present a straightforward approach for the integrative analysis of data from different high-throughput technologies based on pathway and interaction models from public databases. pwOmics performs pathway-based level-specific data comparison of coupled human proteomic and genomic/transcriptomic datasets based on their log fold changes. Separate downstream and upstream analyses results on the functional levels of pathways, transcription factors and genes/transcripts are performed in the cross-platform consensus analysis. These provide a basis for the combined interpretation of regulatory effects over time. Via network reconstruction and inference methods (Steiner tree, dynamic Bayesian network inference) consensus graphical networks can be generated for further analyses and visualization."],["dc.identifier.doi","10.1093/bioinformatics/btv323"],["dc.identifier.isi","000361757500025"],["dc.identifier.pmid","26002883"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35953"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Oxford Univ Press"],["dc.relation.issn","1460-2059"],["dc.relation.issn","1367-4803"],["dc.title","pwOmics: an R package for pathway-based integration of time-series omics data using public database knowledge"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","112"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Breast Cancer Research"],["dc.bibliographiccitation.volume","19"],["dc.contributor.author","Bernhardt, Stephan"],["dc.contributor.author","Bayerlová, Michaela"],["dc.contributor.author","Vetter, Martina"],["dc.contributor.author","Wachter, Astrid"],["dc.contributor.author","Mitra, Devina"],["dc.contributor.author","Hanf, Volker"],["dc.contributor.author","Lantzsch, Tilmann"],["dc.contributor.author","Uleer, Christoph"],["dc.contributor.author","Peschel, Susanne"],["dc.contributor.author","John, Jutta"],["dc.contributor.author","Buchmann, Jörg"],["dc.contributor.author","Weigert, Edith"],["dc.contributor.author","Bürrig, Karl-Friedrich"],["dc.contributor.author","Thomssen, Christoph"],["dc.contributor.author","Korf, Ulrike"],["dc.contributor.author","Beissbarth, Tim"],["dc.contributor.author","Wiemann, Stefan"],["dc.contributor.author","Kantelhardt, Eva Johanna"],["dc.date.accessioned","2020-12-10T18:39:04Z"],["dc.date.available","2020-12-10T18:39:04Z"],["dc.date.issued","2017"],["dc.description.abstract","Abstract Background Breast cancer tumors are known to be highly heterogeneous and differences in their metabolic phenotypes, especially at protein level, are less well-understood. Profiling of metabolism-related proteins harbors the potential to establish new patient stratification regimes and biomarkers promoting individualized therapy. In our study, we aimed to examine the relationship between metabolism-associated protein expression profiles and clinicopathological characteristics in a large cohort of breast cancer patients. Methods Breast cancer specimens from 801 consecutive patients, diagnosed between 2009 and 2011, were investigated using reverse phase protein arrays (RPPA). Patients were treated in accordance with national guidelines in five certified German breast centers. To obtain quantitative expression data, 37 antibodies detecting proteins relevant to cancer metabolism, were applied. Hierarchical cluster analysis and individual target characterization were performed. Clustering results and individual protein expression patterns were associated with clinical data. The Kaplan-Meier method was used to estimate survival functions. Univariate and multivariate Cox regression models were applied to assess the impact of protein expression and other clinicopathological features on survival. Results We identified three metabolic clusters of breast cancer, which do not reflect the receptor-defined subtypes, but are significantly correlated with overall survival (OS, p ≤ 0.03) and recurrence-free survival (RFS, p ≤ 0.01). Furthermore, univariate and multivariate analysis of individual protein expression profiles demonstrated the central role of serine hydroxymethyltransferase 2 (SHMT2) and amino acid transporter ASCT2 (SLC1A5) as independent prognostic factors in breast cancer patients. High SHMT2 protein expression was significantly correlated with poor OS (hazard ratio (HR) = 1.53, 95% confidence interval (CI) = 1.10–2.12, p ≤ 0.01) and RFS (HR = 1.54, 95% CI = 1.16–2.04, p ≤ 0.01). High protein expression of ASCT2 was significantly correlated with poor RFS (HR = 1.31, 95% CI = 1.01–1.71, p ≤ 0.05). Conclusions Our data confirm the heterogeneity of breast tumors at a functional proteomic level and dissects the relationship between metabolism-related proteins, pathological features and patient survival. These observations highlight the importance of SHMT2 and ASCT2 as valuable individual prognostic markers and potential targets for personalized breast cancer therapy. Trial registration ClinicalTrials.gov, NCT01592825 . Registered on 3 May 2012."],["dc.identifier.doi","10.1186/s13058-017-0905-7"],["dc.identifier.eissn","1465-542X"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15161"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/77532"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.intern","Merged from goescholar"],["dc.notes.intern","In goescholar not merged with http://resolver.sub.uni-goettingen.de/purl?gs-1/16987 but duplicate"],["dc.publisher","BioMed Central"],["dc.rights","CC BY 4.0"],["dc.rights.holder","The Author(s)."],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Proteomic profiling of breast cancer metabolism identifies SHMT2 and ASCT2 as prognostic factors"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","793"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","Acta Neurochirurgica"],["dc.bibliographiccitation.lastpage","799"],["dc.bibliographiccitation.volume","143"],["dc.contributor.author","Mursch, K."],["dc.contributor.author","Wachter, Astrid"],["dc.contributor.author","Radke, K."],["dc.contributor.author","Buhre, W."],["dc.contributor.author","Al-Sufi, S."],["dc.contributor.author","Munzel, U."],["dc.contributor.author","Behnke-Mursch, J."],["dc.contributor.author","Kolenda, H."],["dc.date.accessioned","2018-11-07T09:27:33Z"],["dc.date.available","2018-11-07T09:27:33Z"],["dc.date.issued","2001"],["dc.description.abstract","Background. Early recognition of emerging delayed neurological deficits (DND) in patients after subarachnoid haemorrhage (SAH) is not always possible by transcranial Doppler sonography. Aim of this study was to investigate a) whether determination of blood flow velocities in deep cerebral basal veins can predict DND in these patients b) the correlation of venous flow velocity to cerebral blood flow (CBF). Methods, a) We prospectively investigated the mean flow velocity in the basal vein (V-BVR), in the middle cerebral artery (V-MCA) and in the extracranial internal carotid artery (V-ICA) in 66 patients after spontaneous SAH. Examinations were performed daily during the first 10 days, using transcranial duplex sonography. Thirty-seven patients had VMCA exceeding 120 cm/s. They were categorised in three groups: I: no delayed neurological deficit; II: transient DND; III: permanent DND or death associated with vasospasm. b) In another group of 14 patients, interdiane variations in global cerebral blood flow (CBF) measured by the Kety-Schmidt-method were correlated with variations in V-BVR, V-MCA, and V-ICA. Findings. a) In patients without deficit, V-BVR was significantly elevated above normal values the first day (p < 0.05), and days 5 and 6 (p < 0.1) after V-MCA exceeding 120 cm/s. In group III (permanent deficit), flow velocities in the BVR were significantly below normal on day 5 (p < 0.05) and 9 (p < OA). b) The correlation between changes in VBVR to changes in CBF (r = 0.78, p < 0.001) was closer than between changes in V-MCA to the changes in CBF (r = 0.54, p < 0.05). Interpretation. In case of elevated V-MCA, patients with higher V-BVR seem to have a better outcome. Changes in CBF correlate better with V-BVR than with arterial flow velocities."],["dc.identifier.doi","10.1007/s007010170033"],["dc.identifier.isi","000170817400017"],["dc.identifier.pmid","11678400"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/30564"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Springer"],["dc.publisher.place","Wien"],["dc.relation.issn","0001-6268"],["dc.title","Blood flow velocities in the basal vein after subarachnoid haemorrhage a prospective study using transcranial duplex sonography"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1700"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Leukemia"],["dc.bibliographiccitation.lastpage","1712"],["dc.bibliographiccitation.volume","33"],["dc.contributor.author","Hoang, Van T."],["dc.contributor.author","Verma, Divij"],["dc.contributor.author","Godavarthy, Parimala Sonika"],["dc.contributor.author","Llavona, Pablo"],["dc.contributor.author","Steiner, Marlene"],["dc.contributor.author","Gerlach, Katharina"],["dc.contributor.author","Michels, Birgitta E."],["dc.contributor.author","Bohnenberger, Hanibal"],["dc.contributor.author","Wachter, Astrid"],["dc.contributor.author","Oellerich, Thomas"],["dc.contributor.author","Müller-Kuller, Uta"],["dc.contributor.author","Weissenberger, Eva"],["dc.contributor.author","Voutsinas, Jenna M."],["dc.contributor.author","Oehler, Vivian G."],["dc.contributor.author","Farin, Henner F."],["dc.contributor.author","Zörnig, Martin"],["dc.contributor.author","Krause, Daniela S."],["dc.date.accessioned","2020-12-10T18:09:34Z"],["dc.date.available","2020-12-10T18:09:34Z"],["dc.date.issued","2019"],["dc.identifier.doi","10.1038/s41375-018-0358-8"],["dc.identifier.eissn","1476-5551"],["dc.identifier.issn","0887-6924"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/73695"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","The transcriptional regulator FUBP1 influences disease outcome in murine and human myeloid leukemia"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Oncology Research and Treatment"],["dc.bibliographiccitation.volume","38"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Wachter, Astrid"],["dc.contributor.author","Conradi, Lena-Christin"],["dc.contributor.author","Wolff, Alexander"],["dc.contributor.author","Hoppenau, C."],["dc.contributor.author","Korf, Ulrike"],["dc.contributor.author","Schildhaus, Hans-Ulrich"],["dc.contributor.author","Homayounfar, Kia"],["dc.contributor.author","Pukrop, Tobias"],["dc.contributor.author","Beissbarth, Timothy"],["dc.date.accessioned","2018-11-07T09:50:36Z"],["dc.date.available","2018-11-07T09:50:36Z"],["dc.date.issued","2015"],["dc.identifier.isi","000364268800134"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35738"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Karger"],["dc.publisher.place","Basel"],["dc.title","Heterogeneity of colorectal cancer liver metastasis - analysis of WNT pathway patterns via High-throughput and bioinformatics profiling"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]