In gratitude of the loyal support of our members, the CNS is offering complimentary 2021 Annual Meeting registration to all members! Learn more.

  • Meningioma with Multiple Drivers: Genomic Landscape and Clinical Correlations

    Final Number:
    141

    Authors:
    Evgeniya Tyrtova; Chang Li*; Mark Youngblood; Daniel Duran MD; Julio D. Montejo BA, MHSc, MD; Süleyman Coskun; Danielle F Miyagishima BA; Kaya Bilguvar MD; . International Meningioma Study Group; Murat Gunel MD

    Study Design:
    Laboratory Investigation

    Subject Category:

    Meeting: Congress of Neurological Surgeons 2018 Annual Meeting

    Introduction: The majority of meningioma cluster into mutually exclusive groups with distinctive clinical correlations based on a mutation in one of the well-established drivers (NF2, TRAF7, KLF4(+/-TRAF7), PI3K(+/-TRAF7) and Sonic Hedgehog signaling pathways, SMARCB1/SMARCE1(+/-NF2), POLR2A) [1-6]. However, some tumors concomitantly harbor two or more of these typically mutually exclusive driver mutations and they have not been previously investigated. Our objective is to characterize the genomic landscape and clinical features of meningioma with multiple drivers.

    Methods: In our lab, we performed targeted molecular inversion probe sequencing (MIPS) followed by confirmatory Sanger sequencing and qPCR for chromosome 22 (Chr22) loss to screen for the presence of established driver mutations in over 3000 meningioma. Subsequently, we identified and characterized a cohort of meningioma with multiple drivers. For the analysis of clinical features (patient gender and age at surgery, tumor anatomical location, recurrence, WHO grade, and histology type), we utilized two-tailed Fisher’s exact tests for nominal data and Kruskal-Wallis tests for ordinal data followed by multiple-comparison correction.

    Results: Out of ~2,400 meningioma with confirmed drivers, approximately 2% of tumors had multiple drivers. Compared with the “single driver” meningioma group, tumors with multiple drivers were significantly more recurrent, had higher grade, and demonstrated distinct anatomical and histological distribution. Meningioma with multiple drivers harbored significantly more NF2 mutation/Chr22 loss (77%) than “single driver” tumors (54%). Interestingly, compared to “single driver” tumors with NF2 mutation/Chr22 loss only, “multiple driver” meningiomas that harbored NF2 mutation/Chr22 loss demonstrated skull base predilection and distinct histological distribution. Within “multiple driver” meningioma with NF2 mutation/Chr22 loss, we further discovered specific associations between different groups of concurrent non-NF2 drivers and clinical features.

    Conclusions: Meningioma with multiple drivers demonstrate distinct genomic and clinical features with potential prognostic and therapeutic significance. These tumors can provide unique insight into meningioma heterogeneity, which requires further investigation.

    Patient Care: Meningioma is the most common primary brain tumor and can cause significant morbidity and mortality. Specifically, tumors that are clinically aggressive and those arising in the skull base present a therapeutic challenge. We investigated a subset of meningioma with multiple driver mutations, which indeed tend to be higher grade, more recurrent, and have a predilection to surgically challenging anatomical locations compared to other meningioma genomic subgroups. Better characterization of these tumors has a potential to improve meningioma diagnostics and prognostication and incite further investigations of targets for rational therapy design.

    Learning Objectives: By the conclusion of this session, participants should be able to: - Recognize the existence of distinct subset of meningioma that concomitantly harbors multiple driver mutations - Appreciate genomic landscape and clinical correlations of multiple driver meningioma and distinguish associations between particular drivers and clinical features in these tumors - Consider the role of multiple driver gene mutations in meningioma heterogeneity and its potential clinical implications

    References: 1. Clark VE, Erson-Omay EZ, Serin A, et al. Genomic Analysis of Non-NF2 Meningiomas Reveals Mutations in TRAF7, KLF4, AKT1, and SMO. Science (New York, N.Y.). 2013; 339(6123):1077-1080. 2. Brastianos PK, Horowitz PM, Santagata S, et al. Genomic sequencing of meningiomas identifies oncogenic SMO and AKT1 mutations. Nat Genet. 2013; 45(3):285-289. 3. Clark VE, Harmanci AS, Bai H, et al. Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas. Nat Genet. 2016; 48(10):1253-1259. 4. Harmanci AS, Youngblood MW, Clark VE, Coskun S, Henegariu O, Duran D, Erson-Omay EZ, Kaulen LD, Lee TI, Abraham BJ, Simon M, Krischek B, Timmer M, et al. Integrated genomic analyses of de novo pathways underlying atypical meningiomas. Nat Commun. 2017;8:14433. 5. Smith MJ, O'Sullivan J, Bhaskar SS, et al. Loss-of-function mutations in SMARCE1 cause an inherited disorder of multiple spinal meningiomas. Nat Genet. 2013;45(3):295–298. 6. Abedalthagafi M, Bi WL, Aizer AA, et al. Oncogenic PI3K mutations are as common as AKT1 and SMO mutations in meningioma. Neuro Oncol 2016;18:649-55.

We use cookies to improve the performance of our site, to analyze the traffic to our site, and to personalize your experience of the site. You can control cookies through your browser settings. Please find more information on the cookies used on our site. Privacy Policy