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Abstract

The 2016 WHO Classification of Tumors of the Central Nervous System separates IDH-mutant gliomas into two distinct subtypes depending on the preservation or deletion of the chromosome arms of 1p and 19q termed “astrocytomas, IDH-mutant” and “oligodendrogliomas, IDH-mutant and 1p/19q-codeleted”. Currently, the assessment of the chromosomal copy number profile of 1p and 19q are essential to distinguish between the two tumor entities. An additional challenge is the WHO grading of astrocytomas which shows low correlation with survival. Biomarkers for facilitating the differential diagnosis of IDH-mutant glioma are of high clinical relevance. Therefore, there is a need for new markers and screening methods to effectively detect tumor malignancy and predict prognosis. Over the past decades mass spectrometry has become the method of choice for proteomic investigations in medical scientific areas. This study integrates a proteomic workflow into a clinical environment and explores the proteome of IDH-mutant gliomas with the aim of finding novel diagnostic and prognostic biomarkers for astrocytoma and oligodendroglioma. For this, sample preparation techniques and protocols for fresh frozen as well as formalin-fixed-paraffin-embedded tissues were established and tumor samples analyzed using different mass spectrometry platforms. A dual surrogate biomarker for 1p/19q status in IDH-mutant gliomas was discovered which could simplify the diagnosis of these tumors, making it less dependent on elaborative genetic analyses. Furthermore, it was observed that protein abundances correlate in sum with copy number of their respective chromosomes in mutant gliomas. Potential prognostic biomarkers were found which could not only improve the grading of IDH-mutant astrocytomas, but also help us further understand how these tumors overcome oxidative stress. Taken together, this study shows the potential impact of proteomic pipelines in a clinical environment and how it can complement already existing diagnostic infrastructures in the neuropathology. Importantly, it shows how a novel technology can help reveal novel potential biomarkers, which could be used by institutions where no genetic or proteomic analyses are available.