Deciphering and Controlling Protein Activity Networks in Glioblastoma

• Applicant: Igor Cima, Ph.D.
• Subject Area: Molecular and Cellular Neurology and Neuropathology ; Bioinformatics and Theoretical Biology ; Medical Informatics and Medical Bioinformatics ; Cell Biology
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 555481836

Glioblastoma is an incurable brain tumor, with about 50% of patients experiencing recurrence within 7 months and a median survival time of just 15 months under current treatment modalities. Targeted therapies have occasionally improved survival in patients with tumors harboring specific oncogenic drivers, such as NTRK fusions. This suggests that treatments tailored to active oncogenic drivers may lead to better outcomes. Beyond these rare instances, analysis of genomic data has not provided a significant benefit for personalized glioblastoma treatments. Therefore, there is an urgent need for alternative strategies for the stratification of patients towards effective molecularly-matched therapies. This grant proposal aims to establish and validate a novel approach for mapping and controlling oncogenic driver activities in glioblastoma. Our preliminary data demonstrate that it is possible to quantify, rank, and model the activity of hundreds of cancer drivers using transcriptome data from glioblastoma patient-derived models. We provide initial benchmarking data with current gold standards and we show that targeting highly ranked oncogenic activities identified by our approach effectively kills glioblastoma cells ex-vivo. The proposal has three specific goals: 1. To create a comprehensive reference for the unbiased quantification of all known oncogenic driver activities (n=591) in glioblastoma. 2. To map networks of oncogenic driver activity in ex-vivo models of glioblastoma recurrence and in residual tumor cells post-surgery. 3. To understand and control oncogenic driver activities in models subjected to selective CDK4/6 inhibitor treatment pressure. This proposal is, in our opinion, a significant step towards understanding and controlling the global network of oncogenic driver activities in glioblastoma. Our method may not only complement current genomic sequencing approaches, but also uncover novel therapeutic strategies and improve the effectiveness of patient stratification to molecularly matched therapies.

• DFG Programme: Research Grants
• Co-Investigator: Professor Dr. Björn Scheffler