Cansu Dinçer, 3D Spatial Organization and Network-Guided Comparison of Mutation Profiles in Glioblastoma
Accumulation of genomic alterations can lead to tumorigenesis. One of the deadliest brain tumor type, Glioblastoma is well-known for its genomic heterogeneity which makes the disease as incurable. In this thesis, we aimed to decrease the heterogeneity among Glioblastoma patients from The Cancer Genome Atlas (TCGA), classify the patients and propose therapeutic hypothesis for patient groups by using patient mutation profiles. We therefore implemented a systems level approach using three dimensional (3D) spatial organization of the mutations (mutation patches), organization of mutated proteins in patient specific protein interaction networks, and drug responses of the GBM cell lines.
Date: 28.08.2019 / 11:00 Place: A-212