We aim to uncover biomarkers of glioblastoma invasiveness and treatment resistance that are important for patient classification and prognosis, as well as for predicting patient response to treatment. Our approach addresses two major challenges that prevent efficient GBM treatment: invasive cancer cells and tumor heterogeneity that enable tumor reoccurrence.
The multimodal approach combining different scientific disciplines – oncology, cell biology, radiology and computer science, and the application of the combination of molecular and radiographic features of GBM using artificial intelligence approaches will provide crucial insights into the characteristics of GBM and enable insights into the clinical potential of the identified biomarkers.
This project is financed by the Slovenian Research and Innovation Agency (ARIS).
Project ID: ID: J7-70250
Duration: 1.3.2026 – 28.2.2029
