Proteomic analysis of genetically stratified grade-I meningioma

Introduction: Meningioma is the most common primary intracranial tumour. Although often benign in nature, at least 20% have high rates of recurrence. Surgical resection and radiotherapy are the main therapeutic approach, yet tumour location can hamper complete resection and chemotherapies are ineffective. Therefore, more accurate prognostic biomarkers are needed to improve the clinical management of meningioma. The mutational profile of mutant meningioma is well defined, including in addition to most common NF2 loss, mutations of TRAF7, KLF4, and AKT1. The aim of this study is to identify novel biomarkers and therapeutic targets of genetically stratified meningioma by characterising the proteomic landscape. Materials and methods: Frozen meningioma tissue samples were stratified according to mutational background: AKT1E17K/TRAF7, KLF4K409Q/TRAF7 and NF2-/-. For global proteomics, proteins were fractionated by SDS-PAGE followed by in-gel tryptic digestion and sample preparation for LCMS analysis. Raw mass spectrometry data files were analysed using MaxQuant (1.6.2.10) and Perseus software (1.6.1.3). Quantitative phosphoproteomics was performed using TMT 10plex labelling approach followed by kinase prediction using KinswingR. GO enrichment analyses were performed using DAVID against all human proteins. Proteomics data were also further analysed for pathway analysis by the Ingenuity® Pathway Analysis (IPA®) software. Followed by mutational subtype specific potential protein and kinase candidates were validated via Western blot and immunohistochemistry techniques. Results: In total, 4162 proteins were quantified across all meningioma mutational subtypes and normal meninges (n=31). Hierarchical clustering analysis showed distinct proteomic profiles of meningioma mutational subtypes and corresponding clusters of differentially expressed proteins. Comparative analysis showed only 10 proteins were commonly significantly upregulated (log2 fold-change≥1; p<0.05) among all mutational subtypes vs. normal meninges which indicates mutational subtypes are very different from each other at their protein expression level. Mutational subtypes specific analysis identified 156 proteins to be commonly significantly upregulated (log2 fold-change≥1; p