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Abstract

IDH-mutant Astrocytoma are malignant brain tumours with highly variable biological behaviour and clinical prognosis. The prognostic significance of current histopathological grading for lower-grade IDH-mutated astrocytoma remains controversial. This thesis investigates the prognostic potential of the IDH-mutant Astrocytoma proteome by linking protein abundance with clinical outcomes, characterising associated biological processes and evaluating its relevance for risk stratification of lower grade IDH-mutated astrocytoma. DIA- based whole proteome profiling of 80 treatment naive IDH-mutant Astrocytoma (31 WHO grade 2; 30 WHO grade 3; 19 WHO grade 4) identified 11 623 different proteins. Unsupervised analysis revealed three biologically and clinically distinct subtypes: a neuronal subtype linked with favourable overall survival, a metabolic with intermediate outcome (p <0.001; HR=8.53) and a mesenchymal linked with the worst outcome (p <0.001; HR=16.46). In-depth analysis of the intermediate group showed striking upregulation of proteins linked to mitochondrial biogenesis as well as amino acid and lipid metabolism with simultaneous dysregulation of subunits of the electron transport chain (ETC) complexes I. Enrichment of MYC target proteins supported the presence of a MYC driven metabolic reprogramming. A decision-tree prediction model trained on these findings demonstrated robust performance (BACC = 1) and demonstrated biological and clinical reproducibility across two in-house and two publicly available datasets. This thesis provides novel molecular and clinical insight into IDH-mutant astrocytoma through comprehensive proteomic characterisation. The discovered subtypes exhibit distinct clinical trajectories linked with distinct biological phenotypes offering potential for an improved risk stratification. Moreover, the unexpected discovery of distinct metabolic alterations in the intermediate group provides potential explanations on how these tumours gain partial independence from the IDH mutation. Finally, the introduced decision-tree model may serve as a potential framework for enhancing clinical stratification of lower grade IDH mutant astrocytoma patients.