We aim to enhance and complement molecular neuroblastoma classification for clinical application in this research course. This is working towards predicting clinical phenotypes of residual and metastatic disease using liquid biopsy technologies. We intend for this information to support tailoring therapy for each patient to target minimal residual disease and metastasis to prevent or reduce treatment failure. We also expect this work to produce unique innovations in neuroblastoma diagnostics.

Liquid biopsies could better reflect tumor dynamics, intratumor heterogeneity and drug sensitivities over time in comparison with single biopsies, and contribute largely to move toward personalized treatment for high-risk neuroblastoma. We are working to create an innovative liquid biopsy diagnostics platform for the complementary analysis and molecular characterization of circulating tumor cells, cell-free nucleic acids and extracellular vesicles from biofluids as a minimally invasive alternative to sequential surgical biopsies. Our long-term goal is to sustain a more personalize approach that can better improve cure rates for very high-risk cases who have little chance of cure with current treatment protocols.

Metabolomics has emerged as a promising new OMICS technology to study human cancers, among other biological systems. It analyzes unique metabolite signatures in a biological system under a given set of conditions. Since small changes in enzyme activities can produce large changes in metabolite levels, the metabolome is regarded as the amplified output of a biological system. It can describe the cellular phenotype that is furthest downstream of changes in the genome, transcriptome and/or proteome combined with interactions from the environment of the cell. This is why it is hypothesized to carry more information about a biological phenotype than the proteome and genome. For these reasons, metabolomics may significantly contribute to cancer biomarker and therapy development.

We cooperate with the Kempa laboratory at the Berlin Institute for Medical Systems Biology (BIMSB) in Berlin-Buch to aim for a richer and more comprehensive understanding of neuroblastoma through metabolomics.

Developing more effective and less toxic targeted therapeutics should help overcome current treatment hurdles and reduce the long-term side effects of aggressive chemotherapy and radiotherapy treatments. Combining new targeted agents with conventional chemotherapeutic strategies has the best hope to minimize the onset of chemotherapy resistance, and could enable dose reduction of chemotherapeutic agents particularly at risk to cause long-term side effects.
We use combined transcriptomics, epigenomics, proteomics and metabolomics technologies to identify molecular regulatory events key to disease progression that could be exploited as drug targets. We use a number of state-of-the-art models to investigate and validate druggable targets as well as test targeted drugs in the preclinical setting. These range from established and molecularly well-characterized cell lines derived from human neuroblastomas to 3D-organoids grown in culture and patient-derived neuroblastoma xenografts maintained in mice. We maintain a particular focus on unraveling the complexity of epigenetic drug action.

We cooperate with the computational modeling groups of N. Blüthgen (Charité, Universitätsmedizin Berlin) and T. Höfer (German Cancer Research Center, Heidelberg) to investigate how gene-regulatory networks and signaling cascades are modulated by targeted therapeutics and test the theoretical concepts for combinatorial drug targeting derived from these models in our panel of preclinical neuroblastoma models. The potential novel drug targets identified in computational approaches undergo a precise functional evaluation in the wet lab. Targets that absolve the stringent validation are shunted towards our existing cooperations with industry to pursue lead and drug development.