Wolff, Alexander

[["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.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"]]