PATH-36. INTRATUMOR HETEROGENEITY AND BIOINFORMATIC DIFFERENCES INFLUENCE MENINGIOMA MOLECULAR CLASSIFICATION. (12th November 2021)

• Record Type: Journal Article
• Authors: Vasudevan, Harish; Choudhury, Abrar; Hilz, Stephanie; Villanueva-Meyer, Javier; Chen, William; Lucas, Calixto; Braunstein, Steve; Oberheim-Bush, Nancy Ann; Butowski, Nicholas; Pekmezci, Melike; McDermott, Michael; Perry, Arie; Solomon, David; Magill, Stephen; Raleigh, David
• Is Part Of: Neuro-oncology. Volume 23: Supplement 6(2021)
• Page Start: vi123
• Page End: vi123
• Publication Date: 2021-11-12
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noab196.488
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Molecular alterations such as CDKN2A inactivation and TERT promoter mutation are new criteria for grade 3 meningiomas in the 5 th edition of the WHO Classification of Tumors of the Central Nervous System. However, consensus approaches to identify copy number variants (CNVs) and short somatic variants in meningiomas are lacking. Here, we performed integrated DNA methylation profiling, RNA-sequencing, and targeted DNA mutational profiling on 10 stereotactically-collected, regionally-distinct samples from 4 meningiomas. Targeted DNA sequencing revealed numerous private short somatic variants from multiple sites within individual meningiomas, including a TERT promoter mutation in only 1 of 2 samples from the same tumor. DNA methylation profiling revealed differences in biologic groups and immune cell enrichment between regionally-distinct samples within individual meningiomas. CNV status was evaluated using DNA methylation profiling and RNA sequencing on 14 stereotactically-collected, regionally-distinct samples from 2 meningiomas. Phylogenetic architectures from DNA methylation profiling and targeted DNA sequencing were highly concordant and shared 99.12% of CNVs while RNA sequencing identified only 39% of the CNVs called from DNA based approaches. Finally, CNV analysis based on single-cell RNA sequencing revealed partially overlapping CNVs across meningioma cells within an individual tumor, suggesting subclonal populations may influence CNV-based meningioma molecular classification and underlie limitations in defining CNVs from bulk RNA-sequencing. In sum, these data highlight the relative strengths and weaknesses of various approaches for molecular analysis of meningiomas complicated by intratumor heterogeneity due to non-tumor cells and subclonal populations of meningioma cells. Future efforts to incorporate molecular analysis into the diagnostic paradigm for meningiomas may require orthogonal validation across multiple platforms or image-guided meningioma sampling to select the most aggressive regions for molecular profiling.