NIMG-64. TYPE OF BONY INVOLVEMENT PREDICTS GENOMIC SUBGROUP IN SPHENOID WING MENINGIOMAS

Autor: Arushii Nadar, Murat Gunel, Lan Jin, Declan McGuone, Stephanie Aguilera, Tanyeri Barak, Ketu Mishra-Gorur, Benjamin L. Judson, Nicholas Blondin, Kanat Yalcin, Zeynep Erson-Omay, Robert K. Fulbright, Michael Alperovich, Shaurey Vetsa, Jennifer Moliterno, Mark W. Youngblood, Renelle Pointdujour-Lim, Trisha P Gupte, Mariam Aboian, S. Bulent Omay
Rok vydání: 2021
Předmět:
Zdroj: Neuro Oncol
ISSN: 1523-5866
1522-8517
DOI: 10.1093/neuonc/noab196.562
Popis: OBJECTIVE As sphenoid wing meningiomas (SWMs) are associated with varying degrees of bony involvement, we sought to understand potential relationships between genomic subgroup and this feature. METHODS Patients treated at Yale-New Haven Hospital for SWM were reviewed. Genomic subgroup was determined via whole exome sequencing, while the extent of bony involvement was radiographically classified as frank tumor invasion (TI), hyperostosis only (HOOs), or both (TI+HO). Among additional clinical variables collected, a subset of tumors was identified as spheno-orbital meningiomas (SOMs). Predictive logistic regression models were developed for genomic subgroups based on pre-operative clinical features. RESULTS Among 64 SWMs, 53% had HOO, 9% had TI, and 14% had TI+HO; nine SOMs were identified. Tumors with invasion (i.e., TI or TI+HO) were more likely to be WHO grade II (p: 0.028). Additionally, tumors with invasion were nearly 30 times more likely to harbor NF2 mutations (OR: 27.6; p: 0.004), while hyperostosis only (without frank tumor invasion) were over 4 times more likely to have a TRAF7 mutation (OR: 4.5; p: 0.023). SOMs were a significant predictor of underlying TRAF7 mutation (OR: 10.21; p: 0.004). CONCLUSIONS SWMs with invasion into bone tend to be higher grade and are more likely to be NF2 mutated, while SOMs and those with hyperostosis are associated with TRAF7 variants. Pre-operative prediction of molecular subtypes based on radiographic bony characteristics may have significant biological and clinical implications based on known recurrence patterns associated with genomic drivers.
Databáze: OpenAIRE
Externí odkaz: