CNSC-20. PROTEOMIC ANALYSIS OF GLIOMA BIOPSIES SHOWS CONSISTENCY WITH GLIOMA GRADING. (14th November 2022)

• Record Type: Journal Article
• Authors: Leu, Severina; Boulay, Jean-Louis; le Amer, Michè; Ritz, Marie-Françoise; Halbeisen, Florian Samuel; Schmidt, Alexander; Buczak, Katarzyna; Hutter, Gregor
• Is Part Of: Neuro-oncology. Volume 24(2022)Supplement 7
• Page Start: vii26
• Page End: vii26
• Publication Date: 2022-11-14
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noac209.101
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: BACKGROUND: Glioma are currently classified according to integrated histopathologic and molecular genetic (WHO 2021 classification) as well as methylomic criteria (Capper 2018). However, little is known about proteomic profiling of these subgroups, which may reveal specific biomarkers and pathways potentially activated or inactivated. Material and METHODS: Eighty-six glioma biopsy samples were prospectively collected from patients undergoing surgery at the University Hospital of Basel between 2017 and 2019. Samples were classified into seven distinct glioma subgroups based on integrated WHO 2016 and methylome profiling criteria. Proteins were extracted from fresh frozen samples devoid of necrosis/haemorrhage and processed for mass spectrometry analysis. RESULTS: For each tumour sample, a total of 8'855 proteins were identified and quantified. 950 proteins were differentially expressed between at least two glioma subgroups. Strikingly, most significant differences in expression are related to tumor grading rather than to glioma subgroups. Proteins SSDH and GABT, involved in Gamma-aminobutyric acid (GABA) catabolism, show the strongest increase between low grade glioma (LGG) and high grade glioma (HGG), whereas S10AA and ANXA2, part of pathways involved in coagulation, cell adhesion and immune response, appear increased in HGG. CONCLUSION: Tumor grading turns out to be dominant over genetic and epigenetic criteria for proteomic classification. Most significant protein level variations may represent potential glioma grade-specific therapeutic targets.