Pediatric Neuro-Oncogenomics (Dr Marc Remke)
Children with brain tumors are often treated with neurosurgery, radiotherapy and chemotherapy. Brain tumors remain the number one cause of death in children diagnosed with cancer despite improved multimodal therapy approaches. Our main aim is to gain a better understanding of the underlying biology causing tumorigenesis and aggressiveness of these tumors. This is necessary to improve treatment approaches and develop novel therapy options. Our strategy is based on two complimentary approaches:
By incorporating clinical criteria and biological research results, we can better define individual risk profiles of children with brain tumors. Genome-wide analyses platforms (including high throughput sequencing and mass spectrometry) allow us to identify alterations linked to particularly good or bad prognoses. A specific focus here lies in the discovery of long non-coding RNAs with highly conserved temporo-spatial expression patterns pinpointing to the cell of origin of distinct tumor entities, and holding great promise as prognostic biomarkers.
To selectively target tumor cells, we focus on the biologically distinct features of tumors in comparison to normal tissue. Functional genome studies support our genome-wide analyses and give us mechanistic insights to refine targeted therapy formats and eventually identify novel drugs for clinical trials. To this end, we have established an automated drug screening pipeline allowing the standardized evaluation of several hundred established anti-cancer drugs and targeted agents currently tested in phase 3 or 4 clinical trials. We utilize this platform to determine drug response profiles dependent on mutational signatures to identify predictive biomarkers.
We strongly believe that pediatric neoplasias may serve as ideal models to study cancer-specific perturbations as the mutational landscape is less complex compared to most of their adult counterparts. Thus, we plan to utilize the functional networks identified in pediatric brain tumors to provide a better understanding of the complex interaction of oncogenic pathways in adult cancers. Such insights will be essential, for example, in identifying patient cohorts across all age groups that will benefit from selected targeted therapeutic agents to guide clinical decision making in the future.