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.firstpage","342"],["dc.bibliographiccitation.journal","BMC Cancer"],["dc.bibliographiccitation.volume","17"],["dc.contributor.author","Bocuk, Derya"],["dc.contributor.author","Wolff, Alexander"],["dc.contributor.author","Krause, Petra"],["dc.contributor.author","Salinas, Gabriella"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Hackl, Christina"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Koenig, Sarah"],["dc.date.accessioned","2018-10-10T10:45:50Z"],["dc.date.available","2018-10-10T10:45:50Z"],["dc.date.issued","2017"],["dc.description.abstract","Colorectal cancer (CRC) is the second leading cause of cancer-related death in men and women. Systemic disease with metastatic spread to distant sites such as the liver reduces the survival rate considerably. The aim of this study was to investigate the changes in gene expression that occur on invasion and expansion of CRC cells when forming metastases in the liver. The livers of syngeneic C57BL/6NCrl mice were inoculated with 1 million CRC cells (CMT-93) via the portal vein, leading to the stable formation of metastases within 4 weeks. RNA sequencing performed on the Illumina platform was employed to evaluate the expression profiles of more than 14,000 genes, utilizing the RNA of the cell line cells and liver metastases as well as from corresponding tumour-free liver. A total of 3329 differentially expressed genes (DEGs) were identified when cultured CMT-93 cells propagated as metastases in the liver. Hierarchical clustering on heat maps demonstrated the clear changes in gene expression of CMT-93 cells on propagation in the liver. Gene ontology analysis determined inflammation, angiogenesis, and signal transduction as the top three relevant biological processes involved. Using a selection list, matrix metallopeptidases 2, 7, and 9, wnt inhibitory factor, and chemokine receptor 4 were the top five significantly dysregulated genes. Bioinformatics assists in elucidating the factors and processes involved in CRC liver metastasis. Our results support the notion of an invasion-metastasis cascade involving CRC cells forming metastases on successful invasion and expansion within the liver. Furthermore, we identified a gene expression signature correlating strongly with invasiveness and migration. Our findings may guide future research on novel therapeutic targets in the treatment of CRC liver metastasis."],["dc.identifier.doi","10.1186/s12885-017-3342-1"],["dc.identifier.gro","630797"],["dc.identifier.pmid","28525976"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14459"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/15943"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","final"],["dc.relation.eissn","1471-2407"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","The adaptation of colorectal cancer cells when forming metastases in the liver: expression of associated genes and pathways in a mouse model"],["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.artnumber","42"],["dc.bibliographiccitation.journal","Frontiers in Genetics"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Wlochowitz, Darius"],["dc.contributor.author","Haubrock, Martin"],["dc.contributor.author","Arackal, Jetcy"],["dc.contributor.author","Bleckmann, Annalen"],["dc.contributor.author","Wolff, Alexander"],["dc.contributor.author","Beißbarth, Tim"],["dc.contributor.author","Wingender, Edgar"],["dc.contributor.author","Gueltas, Mehmet"],["dc.date.accessioned","2018-11-07T10:15:38Z"],["dc.date.available","2018-11-07T10:15:38Z"],["dc.date.issued","2016"],["dc.description.abstract","Transcription factors (TFs) are gene regulatory proteins that are essential for an effective regulation of the transcriptional machinery. Today, it is known that their expression plays an important role in several types of cancer. Computational identification of key players in specific cancer cell lines is still an open challenge in cancer research. In this study, we present a systematic approach which combines colorectal cancer (CRC) cell lines, namely 1638N-T1 and CMT-93, and well-established computational methods in order to compare these cell lines on the level of transcriptional regulation as well as on a pathway level, i.e, the cancer cell-intrinsic pathway repertoire. For this purpose, we firstly applied the Trinity platform to detect signature genes, and then applied analyses of the geneXplain platform to these for detection of upstream transcriptional regulators and their regulatory networks. We created a CRC-specific position weight matrix (PWM) library based on the TRANSFAC database (release 2014.1) to minimize the rate of false predictions in the promoter analyses. Using our proposed workflow, we specifically focused on revealing the similarities and differences in transcriptional regulation between the two CRC cell lines, and report a number of well-known, cancer-associated TFs with significantly enriched binding sites in the promoter regions of the signature genes. We show that, although the signature genes of both cell lines show no overlap, they may still be regulated by common TFs in CRC. Based on our findings, we suggest that canonical Wnt signaling is activated in 1638N-T1, but inhibited in CMT-93 through cross-talks of Wnt signaling with the VDR signaling pathway and/or LXR-related pathways. Furthermore, our findings provide indication of several master regulators being present such as MLK3 and Mapk1 (FRK2) which might be important in cell proliferation, migration, and invasion of 1638N-T1 and CMT-93, respectively. Taken together, we provide new insights into the invasive potential of these cell lines, which can be used for development of effective cancer therapy."],["dc.description.sponsorship","Open-Access Publikationsfonds 2016"],["dc.identifier.doi","10.3389/fgene.2016.00042"],["dc.identifier.isi","000373477200001"],["dc.identifier.pmid","27092172"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/13174"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/40848"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Frontiers Media S.A."],["dc.relation.eissn","1664-8021"],["dc.relation.issn","1664-8021"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Computational Identification of Key Regulators in Two Different Colorectal Cancer Cell Lines"],["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"]]