Bayerlová, Michaela

[["dc.bibliographiccitation.artnumber","135"],["dc.bibliographiccitation.journal","Frontiers in Oncology"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Bayerlová, Michaela"],["dc.contributor.author","Menck, Kerstin"],["dc.contributor.author","Klemm, Florian"],["dc.contributor.author","Wolff, Alexander"],["dc.contributor.author","Pukrop, Tobias"],["dc.contributor.author","Binder, Claudia"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Bleckmann, Annalen"],["dc.date.accessioned","2019-07-09T11:43:27Z"],["dc.date.available","2019-07-09T11:43:27Z"],["dc.date.issued","2017"],["dc.description.abstract","Breast cancer is a heterogeneous disease and has been classified into five molecular subtypes based on gene expression profiles. Signaling processes linked to different breast cancer molecular subtypes and different clinical outcomes are still poorly understood. Aberrant regulation of Wnt signaling has been implicated in breast cancer progression. In particular Ror1/2 receptors and several other members of the non-canonical Wnt signaling pathway were associated with aggressive breast cancer behavior. However, Wnt signals are mediated via multiple complex pathways, and it is clinically important to determine which particular Wnt cascades, including their domains and targets, are deregulated in poor prognosis breast cancer. To investigate activation and outcome of the Ror2-dependent non-canonical Wnt signaling pathway, we overexpressed the Ror2 receptor in MCF-7 and MDA-MB231 breast cancer cells, stimulated the cells with its ligand Wnt5a, and we knocked-down Ror1 in MDA-MB231 cells. We measured the invasive capacity of perturbed cells to assess phenotypic changes, and mRNA was profiled to quantify gene expression changes. Differentially expressed genes were integrated into a literature-based non-canonical Wnt signaling network. The results were further used in the analysis of an independent dataset of breast cancer patients with metastasis-free survival annotation. Overexpression of the Ror2 receptor, stimulation with Wnt5a, as well as the combination of both perturbations enhanced invasiveness of MCF-7 cells. The expression-responsive targets of Ror2 overexpression in MCF-7 induced a Ror2/Wnt module of the non-canonical Wnt signaling pathway. These targets alter regulation of other pathways involved in cell remodeling processing and cell metabolism. Furthermore, the genes of the Ror2/Wnt module were assessed as a gene signature in patient gene expression data and showed an association with clinical outcome. In summary, results of this study indicate a role of a newly defined Ror2/Wnt module in breast cancer progression and present a link between Ror2 expression and increased cell invasiveness."],["dc.identifier.doi","10.3389/fonc.2017.00135"],["dc.identifier.pmid","28695110"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14538"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/58892"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.publisher","Frontiers Media S.A."],["dc.relation.eissn","2234-943X"],["dc.relation.issn","2234-943X"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.title","Ror2 Signaling and Its Relevance in Breast Cancer Progression."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Onkologie"],["dc.bibliographiccitation.volume","35"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Bayerlova, M."],["dc.contributor.author","Kramer, Franz-Josef"],["dc.contributor.author","Klemm, Florian"],["dc.contributor.author","Binder, Claudia"],["dc.contributor.author","Pukrop, Tobias"],["dc.contributor.author","Beißbarth, Tim"],["dc.date.accessioned","2018-11-07T09:04:54Z"],["dc.date.available","2018-11-07T09:04:54Z"],["dc.date.issued","2012"],["dc.format.extent","65"],["dc.identifier.isi","000310766700159"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/25203"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Karger"],["dc.publisher.place","Basel"],["dc.relation.issn","0378-584X"],["dc.title","Analyzing breast-cancer gene expression data using a newly developed graph-based WNT model in breast cancer"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1331"],["dc.bibliographiccitation.issue","8"],["dc.bibliographiccitation.journal","Glia"],["dc.bibliographiccitation.lastpage","1346"],["dc.bibliographiccitation.volume","61"],["dc.contributor.author","Chuang, Han-Ning"],["dc.contributor.author","van Rossum, Denise"],["dc.contributor.author","Sieger, Dirk"],["dc.contributor.author","Siam, Laila"],["dc.contributor.author","Klemm, Florian"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Bayerlova, Michaela"],["dc.contributor.author","Farhat, Katja"],["dc.contributor.author","Scheffel, Joerg"],["dc.contributor.author","Schulz, Matthias"],["dc.contributor.author","Dehghani, Faramarz"],["dc.contributor.author","Stadelmann, Christine"],["dc.contributor.author","Hanisch, Uwe-Karsten"],["dc.contributor.author","Binder, Claudia"],["dc.contributor.author","Pukrop, Tobias"],["dc.date.accessioned","2018-11-07T09:21:57Z"],["dc.date.available","2018-11-07T09:21:57Z"],["dc.date.issued","2013"],["dc.description.abstract","The metastatic colonization of the brain by carcinoma cells is still barely understood, in particular when considering interactions with the host tissue. The colonization comes with a substantial destruction of the surrounding host tissue. This leads to activation of damage responses by resident innate immune cells to protect, repair, and organize the wound healing, but may distract from tumoricidal actions. We recently demonstrated that microglia, innate immune cells of the CNS, assist carcinoma cell invasion. Here we report that this is a fatal side effect of a physiological damage response of the brain tissue. In a brain slice coculture model, contact with both benign and malignant epithelial cells induced a response by microglia and astrocytes comparable to that seen at the interface of human cerebral metastases. While the glial damage response intended to protect the brain from intrusion of benign epithelial cells by inducing apoptosis, it proved ineffective against various malignant cell types. They did not undergo apoptosis and actually exploited the local tissue reaction to invade instead. Gene expression and functional analyses revealed that the C-X-C chemokine receptor type 4 (CXCR4) and WNT signaling were involved in this process. Furthermore, CXCR4-regulated microglia were recruited to sites of brain injury in a zebrafish model and CXCR4 was expressed in human stroke patients, suggesting a conserved role in damage responses to various types of brain injuries. Together, our findings point to a detrimental misuse of the glial damage response program by carcinoma cells resistant to glia-induced apoptosis. GLIA 2013;61:1331-1346"],["dc.identifier.doi","10.1002/glia.22518"],["dc.identifier.isi","000321983400011"],["dc.identifier.pmid","23832647"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10955"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/29226"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.relation.issn","0894-1491"],["dc.rights","CC BY 3.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/3.0"],["dc.title","Carcinoma cells misuse the host tissue damage response to invade the brain"],["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.artnumber","334"],["dc.bibliographiccitation.journal","BMC Bioinformatics"],["dc.bibliographiccitation.volume","16"],["dc.contributor.author","Bayerlová, Michaela"],["dc.contributor.author","Jung, Klaus"],["dc.contributor.author","Kramer, Frank"],["dc.contributor.author","Klemm, Florian"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Beißbarth, Tim"],["dc.date.accessioned","2018-11-07T09:50:02Z"],["dc.date.available","2018-11-07T09:50:02Z"],["dc.date.issued","2015"],["dc.description.abstract","Background: Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach considers a pathway as a simple gene list disregarding any knowledge of gene or protein interactions. In contrast, the new group of so called pathway topology-based methods integrates the topological structure of a pathway into the analysis. Methods: We comparatively investigated gene set and pathway topology-based enrichment approaches, considering three gene set and four topological methods. These methods were compared in two extensive simulation studies and on a benchmark of 36 real datasets, providing the same pathway input data for all methods. Results: In the benchmark data analysis both types of methods showed a comparable ability to detect enriched pathways. The first simulation study was conducted with KEGG pathways, which showed considerable gene overlaps between each other. In this study with original KEGG pathways, none of the topology-based methods outperformed the gene set approach. Therefore, a second simulation study was performed on non-overlapping pathways created by unique gene IDs. Here, methods accounting for pathway topology reached higher accuracy than the gene set methods, however their sensitivity was lower. Conclusions: We conducted one of the first comprehensive comparative works on evaluating gene set against pathway topology-based enrichment methods. The topological methods showed better performance in the simulation scenarios with non-overlapping pathways, however, they were not conclusively better in the other scenarios. This suggests that simple gene set approach might be sufficient to detect an enriched pathway under realistic circumstances. Nevertheless, more extensive studies and further benchmark data are needed to systematically evaluate these methods and to assess what gain and cost pathway topology information introduces into enrichment analysis. Both types of methods for enrichment analysis require further improvements in order to deal with the problem of pathway overlaps."],["dc.description.sponsorship","Open-Access Publikationsfonds 2015"],["dc.identifier.doi","10.1186/s12859-015-0751-5"],["dc.identifier.isi","000363615900001"],["dc.identifier.pmid","26489510"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/12346"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35629"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Biomed Central Ltd"],["dc.relation.issn","1471-2105"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Comparative study on gene set and pathway topology-based enrichment methods"],["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.artnumber","e0144014"],["dc.bibliographiccitation.issue","12"],["dc.bibliographiccitation.journal","PLoS ONE"],["dc.bibliographiccitation.volume","10"],["dc.contributor.author","Bayerlová, Michaela"],["dc.contributor.author","Klemm, Florian"],["dc.contributor.author","Kramer, Frank"],["dc.contributor.author","Pukrop, Tobias"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Bleckmann, Annalen"],["dc.date.accessioned","2018-11-07T09:47:50Z"],["dc.date.available","2018-11-07T09:47:50Z"],["dc.date.issued","2015"],["dc.description.abstract","Introduction WNT signaling is a complex process comprising multiple pathways: the canonical beta-catenin- dependent pathway and several alternative non-canonical pathways that act in a beta-catenin- independent manner. Representing these intricate signaling mechanisms through bioinformatic approaches is challenging. Nevertheless, a simplified but reliable bioinformatic WNT pathway model is needed, which can be further utilized to decipher specific WNT activation states within e.g. high-throughput data. Results In order to build such a model, we collected, parsed, and curated available WNT signaling knowledge from different pathway databases. The data were assembled to construct computationally suitable models of different WNT signaling cascades in the form of directed signaling graphs. This resulted in four networks representing canonical WNT signaling, non-canonical WNT signaling, the inhibition of canonical WNT signaling and the regulation of WNT signaling pathways, respectively. Furthermore, these networks were integrated with microarray and RNA sequencing data to gain deeper insight into the underlying biology of gene expression differences between MCF-7 and MDA-MB-231 breast cancer cell lines, representing weakly and highly invasive breast carcinomas, respectively. Differential genes up-regulated in the MDA-MB-231 compared to the MCF-7 cell line were found to display enrichment in the gene set originating from the non-canonical network. Moreover, we identified and validated differentially regulated modules representing canonical and non-canonical WNT pathway components specific for the aggressive basal-like breast cancer subtype. Conclusions In conclusion, we demonstrated that these newly constructed WNT networks reliably reflect distinct WNT signaling processes. Using transcriptomic data, we shaped these networks into comprehensive modules of the genes implicated in the aggressive basal-like breast cancer subtype and demonstrated that non-canonical WNT signaling is important in this context. The topology of these networks can be further refined in the future by integration with complementary data such as protein-protein interactions, in order to gain greater insight into signaling processes."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2015"],["dc.identifier.doi","10.1371/journal.pone.0144014"],["dc.identifier.isi","000366040000042"],["dc.identifier.pmid","26632845"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/12616"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/35182"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Public Library Science"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Newly Constructed Network Models of Different WNT Signaling Cascades Applied to Breast Cancer Expression Data"],["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","Glia"],["dc.bibliographiccitation.volume","61"],["dc.contributor.author","Chuang, H.-N."],["dc.contributor.author","vanRossum, D. V."],["dc.contributor.author","Sieger, Dirk"],["dc.contributor.author","Siam, Laila"],["dc.contributor.author","Klemm, Florian"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Bayerlova, M."],["dc.contributor.author","Wenske, Britta"],["dc.contributor.author","Farhat, Katja"],["dc.contributor.author","Scheffel, Joerg"],["dc.contributor.author","Schulz, M."],["dc.contributor.author","Dehghani, Faramarz"],["dc.contributor.author","Stadelmann, Christine"],["dc.contributor.author","Hanisch, U.-K."],["dc.contributor.author","Binder, Claudia"],["dc.contributor.author","Pukrop, Tobias"],["dc.date.accessioned","2018-11-07T09:23:22Z"],["dc.date.available","2018-11-07T09:23:22Z"],["dc.date.issued","2013"],["dc.format.extent","S216"],["dc.identifier.isi","000320408400701"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/29559"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Wiley-blackwell"],["dc.publisher.place","Hoboken"],["dc.relation.eventlocation","Berlin, GERMANY"],["dc.relation.issn","0894-1491"],["dc.title","CARCINOMA CELLS MISUSE THE HOST TISSUE DANGER RESPONSE TO INVADE THE BRAIN"],["dc.type","conference_abstract"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","520"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Bioinformatics"],["dc.bibliographiccitation.lastpage","522"],["dc.bibliographiccitation.volume","29"],["dc.contributor.author","Kramer, Frank"],["dc.contributor.author","Bayerlová, Michaela"],["dc.contributor.author","Klemm, Florian"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Beißbarth, Tim"],["dc.date.accessioned","2018-11-07T09:28:07Z"],["dc.date.available","2018-11-07T09:28:07Z"],["dc.date.issued","2013"],["dc.description.abstract","Motivation: Biological pathway data, stored in structured databases, is a useful source of knowledge for a wide range of bioinformatics algorithms and tools. The Biological Pathway Exchange (BioPAX) language has been established as a standard to store and annotate pathway information. However, use of these data within statistical analyses can be tedious. On the other hand, the statistical computing environment R has become the standard for bioinformatics analysis of large-scale genomics data. With this package, we hope to enable R users to work with BioPAX data and make use of the always increasing amount of biological pathway knowledge within data analysis methods. Results: rBiopaxParser is a software package that provides a comprehensive set of functions for parsing, viewing and modifying BioPAX pathway data within R. These functions enable the user to access and modify specific parts of the BioPAX model. Furthermore, it allows to generate and layout regulatory graphs of controlling interactions and to visualize BioPAX pathways."],["dc.identifier.doi","10.1093/bioinformatics/bts710"],["dc.identifier.isi","000315158500022"],["dc.identifier.pmid","23274212"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/30697"],["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","rBiopaxParser-an R package to parse, modify and visualize BioPAX data"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dspace.entity.type","Publication"]]