What are the molecular drivers in tumor progression? How can current methods of molecular medicine, sequencing, and machine learning in the clinical diagnostics and routine be transferred?

These are the topics of the Cancer Research Unit. On the one hand, she researches strategies for biomarker development
and personalized oncology at the interfaces between medical informatics, bioinformatics, and clinical care.

We integrate various omics data at the genome level, transcriptome, epigenome, proteome, and single-cell analysis for the molecular characterization of solid and liquid tumors using machine learning methods. With this, we develop predictors for tumor progression and relapse, as well as for the stratification of patient collectives.

Our research is closely embedded in the University Cancer Center Schleswig Holstein’s (UCCSH) structure and the Outlive-CRC consortium.

The second focus of our research is the translation of current research into care by the Molecular Tumor Board of the UKSH. In a cross-consortium project between HiGHmed and MIRACUM and in cooperation with the clinic for hematology and oncology and the institute for pathology at the UKSH we created digital structures to integrate patient data from the clinic with personalized sequencing and mutation analysis.

To this end, we are implementing and expanding the cBioportal as a data warehouse for routine clinical use and standardized analysis pipelines and visualization options for using omics data in routine clinical use.