GLIO-COMBO

Background & Rationale: Pediatric High-Grade Gliomas (pHGGs) represent 10% of all childhood brain tumors but contribute to more than 40% of all brain cancer-related deaths in children. Although recent molecular profiling studies have identified different genetic drivers and allowed the stratification of pHGG patients, first line therapy almost always involves intensive cranial irradiation. However, it is palliative by nature with less than 10% of patients surviving 2 years post-diagnosis. There is an urgent need to address therapeutic resistance in pHGGs and devise innovative models to enable the rational design of novel combinatorial treatments.
Hypothesis: Tumor heterogeneity directly contributes to therapeutic resistance of pHGGs and its targeting via biology-guided combinatory treatments could lead to long-term control of the disease.
Aims: Our proposal is structured around three complementary work packages that aim at (i) defining how tumor heterogeneity contributes to treatment resistance using innovative in vitro models of pHGG, (ii) exploiting this knowledge to develop optimal treatment combinations using combination screening and finally (iii) evaluating the therapeutic potential of these novel combinatorial treatments using multiple clinically-relevant and complementary models of pHGG.
Methods: Robust patient-derived models of pHGGs have been established by members of our consortium and will be considerably expanded as part of this project. They will be used to reveal the inter- and intra-tumor heterogeneity of pHGGs using single-cell RNA sequencing before and after treatment. Two types of therapies will be studied: standard of care (radiotherapy and chemotherapy) and small-molecules in clinical development for the treatment of pHGG (e.g., capmatinib, ONC201). This large-scale analysis will be used to identify key pathways activated in treatment persistent cells and design a dedicated drug library targeting these pathways. This biology-guided library will then be screened alone and in combination with standard of care or small molecules in pHGG patient-derived neurospheres to reveal potent combinatorial treatments. Their potential will finally be evaluated by using models incorporating the microenvironment at different scales (i.e., organotypic co-culture, PDX and immunocompetent genetically-engineered murine models) to move toward the clinic.
Expected results & potential impact: Our project will reveal the high degree of inter- and intra-tumoral heterogeneity among pHGGs and how it contributes to treatment resistance. It will also molecularly dissect escape mechanisms, thus unveiling targetable vulnerabilities that could be therapeutically leveraged. Our unique biology-guided drug combination screen may lead to the discovery of potent combinatory treatments against specific molecular subtypes of pHGGs, thus ethically and effectively contributing to the improvement of precision medicine algorithms for pediatric brain tumors.