Phenotypic Therapy and Immune Escape in Cancer

Project 8Translational validation of genetic and gene expression networks determining the phenotypic switch and therapy resistance of tumor cells

‚ÄčProjekt 8 Grau

In project 8 of this joint research effort we intend to use comprehensive biosampling combined with 'big data' analyses for uncovering phenotypic switch mechanisms behind therapy resistance. Melanoma resistance to current immune checkpoint inhibition is our main research focus. Utilizing high quality clinical data with survival endpoints and large-scale analyses incorporating exome and transcriptome data, we want to clarify why these advanced therapies fail in a subset of patients. Bio samples are prepared for genetic, epigenetic, and proteomic analyses. In-house, the skin cancer samples are streamed to automated protein staining and high-throughput sequencing of 29 selected melanoma genes. We then integrate comprehensive bioinformatic analyses of our own genetically and transcriptionally profiled samples and of publicly available datasets. Analyses of our in-hose datasets comprise univariate and multivariate survival analyses with overall and progression-free survival as well as best response endpoints. We perform differential gene expression analysis of responders and non-responders of anti-PD-1/PD-L1 treated patients. Beyond in-house data, public datasets provide great opportunities for discovery approaches as well as hypothesis testing when candidate markers exist. Single cell RNAseq data of melanoma tumors for instance tell us about the many different cells that make up a tumor's phenotype, including closely associated cells. Also, TCGA data provide information on gene-associated survival for a variety of cancer entities.

 

Contact

Prof. Dr. med. Dirk Schadendorf
Department of Dermatology
German Cancer Consortium (DKTK)
University Hospital Essen

Dr. rer. nat. Susanne Horn
Department of Dermatology
University Hospital Essen

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