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P7: Integrative molecular understanding of the epigenetics of urothelial carcinoma

Subject Area Reproductive Medicine, Urology
Term since 2023
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 493802833
 
This project will leverage powerful cutting-edge technologies based on next-generation sequencing to facilitate numerous aspects of the research program of the Research Unit, with the ultimate goal of gaining fundamental insights into the role of dysregulated epigenetics in urothelial carcinoma formation and progression. We will provide a service to all UcarE Research Unit projects with respect to planning, integrative analyses and modelling of high-dimensional data. This will involve the diverse sources of the high- dimensional data generated in the Research Unit including Exome (WES), ATAC-, ChIP-, CUT&RUN, bulk- and single cell (sc) RNA-sequencing, DNA methylation analyses, interactome proteomics, CRISPR/Cas9 sgRNA library screening and multi-plex microscopy analyses. We will not only perform the bioinformatic analysis for the individual projects, but we will also use the data in an integrative approach to compare and contrast the effects of different mutations. Thus, we aim to identify biological properties associated with altered epigenetics in bladder urothelial carcinoma, in particular those that relate to cancer invasion and metastasis, that cannot be determined by individual studies. In order to make the generated data available within the Research Unit, we will develop a web-based tool to display the existing data sets with the corresponding metadata information as well as to allow integrative analyses of multiple complementary datasets to allow non-bioinformatician investigators to quickly extract und visualize gene expression and epigenetic information. A final goal of our work will be to identify an RNA signature of invasive behaviour of urothelial carcinoma and to integrate this with clinical parameters to investigate the utility of this signature as a potential new diagnostic approach to predict the progression of urothelial carcinomas.
DFG Programme Research Units
 
 

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