Projects
Building a next-generation precision oncology platform for childhood cancer Ghent University
Improved patient tailored, more potent and durable treatment of childhood cancer is an urgent medical need. Childhood cancers are often still treated by a ‘one-fits-all’ approach, given the limited available entry points for targeted therapy. Molecular dissection of pediatric cancers, using multiple layers of information (so-called ‘omics’) up to the single cell level, is nowadays yielding fundamental insights into novel putative targets and ...
Integrated Personalized & Precision Oncology Network (IPPON). University of Antwerp
Forwarding precision oncology by integrating cohort-derived molecular and clinical information. Ghent University
Combining molecular data and clinical annotation of tumor cohorts, now available in a public, but increasingly also in a clinical context has the potential to greatly advance clinical practice. However, the integration of these data is non-trivial. Therefore, we will develop methods to analyze such cohort-derived molecular and clinical information and apply them in the context of drug-based precision oncology.
Tenure track professorship in pediatric precision oncology Ghent University
A tenure track appointment grants one the privilege of focusing primarily on research for a period of 5 years, with a limited teaching load.
Exploring the use of extracellular RNA in liquid biopsies for precision oncology purposes Ghent University
The discovery that cancer cells actively and passively release their content into the blood stream has opened enormous opportunities for characterizing cancer cells without the need for surgery to access tumor tissue Instead, a simple drop of blood is sufficient to detect and characterize cancer cells inside a patient’ body The use of circulating DNA molecules has spurred this field, but the study of circulating RNA molecules also seems ...
Individualized Paediatric Cure: Cloud-based virtual-patient models for precision paediatric oncology Ghent University
Effective personalized medicine for paediatric cancers must address a multitude of challenges, including domainspecific challenges. To overcome these challenges, we propose a comprehensive computational effort to combine knowledge-base, machine-learning, and mechanistic models to predict optimal standard and experimental therapies for each child. Our approach is based on virtual patient models–in-silico avatars whose analysis can inform ...
Preventing therapy-induced stemness as a salvage strategy to precision oncology KU Leuven
We aim at gaining insights into the biology of a neural crest stem cell subpopulation. We wish to identify pharmacological avenues that specifically target a particular drug-tolerant state, with the ultimate goal to design rational combination therapies that prevent the occurence of relapse.
Functional Precision Oncology: Next-generation treatment rationale for glioblastoma Mapping the drug response heterogeneity using single cell protein analysis KU Leuven
Glioblastoma (GBM) is the most aggressive brain cancer in adults. In spite of intensive treatment, median survival is still only 15 months. Reasons that explain failure to develop more efficient therapies include the high invasiveness of the tumor, its complex genetics, and interpatient and intra-tumoral heterogeneity. Understanding and mapping the complexity of the different tumour cell populations and how each of these respond to therapy, ...