Abstract B036: Integrative Genomic Profiling Reveals Epigenomic, Structural, and Spatial Complexity in Meningioma

Abstract While histology and WHO grade form the foundation of meningiomas, it does not fully capture the underlying biological complexity and clinically relevant genomic heterogeneity that influence prognosis and treatment. Although methylation profiling has improved meningioma classification, it reflects epigenetic outcomes rather than structural tumor drivers. Analyzing gene dosage alterations from chromosomal aneuploidy and shifts in the higher-order spatial genomic organization clarifies the meningioma genomic landscape, thereby partially addressing this gap. Building on this, we assessed these complementary genomic features within a DNA methylation framework, underscoring the need for a multidimensional approach to address meningioma complexity. We analyzed formalin-fixed paraffin-embedded tumor tissue from 25 patients and classified each using the EPIC v2 DNA methylation microarray, definitively identifying 16 tumors as benign and 9 as intermediate (mean class score, 0.92). We used intensity signals from methylated and unmethylated probes to detect CNVs and fully characterize chromosomal gains and losses. Our analysis identified recurrent autosomal variants associated with higher-risk meningioma, specifically losses of chromosome (chr) 22 (68%), 1p (36%), 7p (20%), and 14q (16%). Loss of chr-14 was significant (Fisher's exact test: odds ratio = 8.75, p = 0.034) in intermediate tumors (56%) compared to benign tumors (13%). Intermediate subtypes consistently exhibited greater CNV complexity than benign subtypes. Beyond confirming autosomal variation, Hi-C analysis also revealed X- or Y-chromosome loss in some cases. Structural rearrangements were observed in tumors with high CNV burden (Spearman's ρ = 0.53, p = 0.006) indicating an unstable genomic state and a potentially more aggressive tumor biology. Our findings show that the complexity of meningioma biology cannot be captured by unimodal diagnostics, even with improved DNA methylation profiling. By integrating CNV inference and Hi-C–based 3D genomic profiling within a DNA methylation framework, we demonstrate that combining epigenetic, structural, and spatial data provides greater clarity for clinically discordant cases. This approach reveals meaningful tumor heterogeneity and supports a multilayered risk-stratification approach alongside current standards. Citation Format: Zac Carver, Roy Khalife, Jared Rice, Abha Banerjee, Shivani Shah, Jon Belton, Chris Roberts, Jose Otero, Anthony Magliocco. Integrative Genomic Profiling Reveals Epigenomic, Structural, and Spatial Complexity in Meningioma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr B036.