Longitudinal Analysis and Therapeutic Exploitation of Radiotherapy Resistance Mechanisms in Gliomas [R2-GLIO]

• Applicant: Dr. Emre Kocakavuk
• Subject Area: Molecular and Cellular Neurology and Neuropathology ; Hematology, Oncology
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 541076190

Diffuse gliomas are the most prevalent and aggressive brain tumor in adults. Despite multimodal treatment, universal relapse is associated with dismal prognosis. Longitudinal studies provided insights into cancer evolutionary trajectories and resistance mechanisms. I discovered that RT is associated with a genomic deletion signature (RTscars), arising from the erroneous repair of RT-induced DSBs via c-NHEJ. This signature is associated with RT-resistance and marks tumors with particularly poor outcomes. On non-genetic levels, RTscars shape cellular transitions towards a more aggressive and proliferative E2F/EZH2- driven stem-like phenotype. This offers potential vulnerabilities to specific RT drug combinations for increased radio-sensitivity. Lastly, the RTscars signature is associated with an increase in frameshift-derived neoantigens, providing a rationale for combining RT and immuno-oncology. While the TME of glioma is known to be immunosuppressive, specific combinations of immunostimulatory treatment have the potential to enhance anti-tumor immunity. I have exclusive access to and manage the most recent, unpublished version of the GLASS dataset, which constitutes the largest sequenced matched primary-recurrent glioma cohort. Leveraging this advantageous position, I set out to comprehensively characterize and exploit RT-resistance mechanisms for therapeutic purposes by dissecting the longitudinal cellular ecosystem changes. This will be accomplished via leveraging the large-scale multi-omic GLASS and non-glioma HMF sequencing datasets. Moreover, a preclinical platform for pan-glioma functional studies will be employed, which combines in vitro patient-derived cell lines with in vivo GEMM models for low- and high-grade adult glioma. The proposed research builds on substantial preliminary data and employs innovative state-of- the-art computational and functional technologies. These include multi-omic sequencing, computational cell state and ecosystem inference, CRISPR/Cas9- and pharmacological targeting, longitudinal in vivo imaging, scRNA sequencing and immune/cytokine profiling. Based on these considerations, I formulated three specific aims stemming from three hypotheses: Hypothesis 1: Treatment-induced genomic changes, specifically RTscars, drive transcriptional cellular state transitions and shape the cancer cellular ecosystem. Aim 1: Comprehensive molecular characterization of RT-associated changes in cancer cell states and cellular ecosystems. Hypothesis 2: Stemness and senescence signatures contribute to RT resistance and can be targeted epigenetically. Aim 2: Genetic and pharmacological targeting of actionable (stemness and senescence) signatures in RT-resistant glioma cells. Hypothesis 3: RT-induced changes in the cellular ecosystem may display an actionable immuno-oncological target. Aim 3: Functional validation of cancer RT and immuno-oncology drug combinations in immune-competent glioma mouse models.

• DFG Programme: Independent Junior Research Groups