2026 Proffered Presentations
S108: METABOLOMIC PROFILING OF MENINGIOMAS REVEALS TUMOR-SPECIFIC FEATURES BUT DOES NOT DISTINGUISH MENINGIOMA SUBTYPES
Mark C Dougherty, MD1; Hashim S Syed, MD2; Linjing Xu3; Eric B Taylor, PhD3; Marlan R Hansen, MD3; 1Johns Hopkins University School of Medicine; 2Mayo Clinic Florida; 3University of Iowa
Introduction: Meningiomas are the most common primary CNS tumor. Yet when surgery and radiation fail, treatment options are extremely limited. There have been dramatic advances in molecular classifications of meningiomas in recent years, stemming from advanced multi-omic analyses. However, still relatively little is known about meningioma metabolism.
Metabolomics is the study of metabolic networks and has been used to discover new treatments in various cancers. We hypothesized that metabolomic profiling could identify distinct metabolic fingerprints in meningiomas, which may facilitate future treatment discovery.
Methods: Written informed consent was obtained from all patients prior to tissue collection. All research was approved by the local Institutional Review Board. Primary meningiomas and adjacent normal dura were obtained from patients undergoing surgical resection and immediately flash-frozen in liquid nitrogen. Metabolomic profiling was performed on the samples using mass spectrometry (gas and liquid chromatography). Data was analyzed using MetaboAnalyst 6.0. For sporadic cranial meningiomas with sufficient tissue, genomic DNA was isolated, and genome-wide methylation profiling was obtained with the Illumina MethylationEPIC 850K bead array. DNA methylation was used to classify tumors as Merlin Intact, Immune Enriched, or Hypermitotic as described in Choudhury et al (2022).1
Results: 46 meningiomas (25 convexity, 19 skull base, 2 spinal) and 13 dural samples underwent metabolomic profiling, measuring 156 total metabolites. 38 tumors were also classified into molecular groups with DNA methylation profiling: 21 Merlin Intact, 8 Immune Enriched, and 9 Hypermitotic. Clear metabolic differences were identified between the tumors and the non-neoplastic dura, with 68 metabolites significantly increased and 27 significantly decreased in tumors as compared to dura (Figures 1 & 2, significance defined as P<0.05 and Fold Change > 2.0). In contrast, minimal metabolomic differences were seen between meningioma subgroups including molecular group, tumor location, WHO grade, and prior surgery (Figure 3).
Conclusions: Meningioma metabolism clearly differs from that of matched non-neoplastic tissues, which may indicate potential for future targeted therapies. In contrast, meningioma subgroup-specific metabolic features were not identified in the current study, although this is likely limited by small sample size.
References:
1.Choudhury A, Magill ST, Eaton CD, et al. Meningioma DNA methylation groups identify biological drivers and therapeutic vulnerabilities. Nat Genet. 2022;54(5):649-659. doi:10.1038/s41588-022-01061-8
