10292- CBMS-7 HISTOLOGICAL GRADING AND MOLECULAR GENETIC BACKGROUND OF MENINGIOMAS

Abstract OBJECTIVES In recent years, due to advances in omics analysis, new findings regarding the malignancy, growth potential, and prognosis of meningiomas have been reported. A classification based on molecular biology and genetic findings has a higher correlation with prognosis. Here, we report a comparative study of the histological malignancy and molecular genetic background of meningiomas using multi-omics analysis. MATERIALS & METHODS This study focused on 42 meningioma specimens including 17 meningothelial (G1), 18 atypical (G2) and 7 anaplastic (G3) subtypes, that were removed at our hospital. Metabolome and transcriptome analyses were performed on frozen specimens, multivariate analysis including PCA and PLS-DA was performed on the data obtained from the former, and DEG analysis, GO/pathway and hierarchical cluster analysis were performed on the latter data. RESULTS As a result of metabolome analysis, four samples were identified in G2 that had significantly different metabolic profiles from the others. These were designated as the G2 subtype (G2m). Transcriptome analysis confirmed the expression of just under 54,000 genes, and DEG analysis of these revealed that G2m had a significantly different gene expression profile from other G2s. Furthermore, pathway analysis revealed that the MAPK signaling pathway was enhanced in G2m, which was similar to that in G3. However, hierarchical cluster analysis showed that G2m was not similar to any of the profiles of G1-3 in the metabolome hierarchy. DISCUSSIONS / CONCLUSIONS It has been shown that among atypical meningiomas, there are subtypes that are molecular genetic similar to anaplastic meningiomas. It is thought that some subtypes of atypical meningiomas exhibit behavior similar to G1, while others are closer to G3. Furthermore, the influence of heterogeneity cannot be ignored even within the same tumor. In the future, it will be necessary to proceed with studies using single-cell RNA analysis.