The Meningioma Enhancer Landscape Delineates Novel Subgroups and Drives Druggable Dependencies.

Abstract

Meningiomas are the most common primary intracranial tumor with current classification offering limited therapeutic guidance. Here, we interrogated meningioma enhancer landscapes from 33 tumors to stratify patients based upon prognosis and identify novel meningioma-specific dependencies. Enhancers robustly stratified meningiomas into three biologically distinct groups (adipogenesis/cholesterol, mesodermal, and neural crest) distinguished by distinct hormonal lineage transcriptional regulators. Meningioma landscapes clustered with intrinsic brain tumors and hormonally responsive systemic cancers with meningioma subgroups, reflecting progesterone or androgen hormonal signaling. Enhancer classification identified a subset of tumors with poor prognosis, irrespective of histologic grading. Superenhancer signatures predicted drug dependencies with superior in vitro efficacy to treatment based upon the NF2 genomic profile. Inhibition of DUSP1, a novel and druggable meningioma target, impaired tumor growth in vivo. Collectively, epigenetic landscapes empower meningioma classification and identification of novel therapies. SIGNIFICANCE: Enhancer landscapes inform prognostic classification of aggressive meningiomas, identifying tumors at high risk of recurrence, and reveal previously unknown therapeutic targets. Druggable dependencies discovered through epigenetic profiling potentially guide treatment of intractable meningiomas.This article is highlighted in the In This Issue feature, p. 1611.

• Authors: Briana C Prager, Harish N Vasudevan, Deobrat Dixit, Jean A Bernatchez, Qiulian Wu, Lisa C Wallace, Shruti Bhargava, Derrick Lee, Bradley H King, Andrew R Morton, Ryan C Gimple, Melike Pekmezci, Zhe Zhu, Jair L Siqueira-Neto, Xiuxing Wang, Qi Xie, Clark Chen, Gene H Barnett, Michael A Vogelbaum, Stephen C Mack, Lukas Chavez, Arie Perry, David R Raleigh, Jeremy N Rich
• Journal: Cancer discovery (Cancer Discov) Vol. 10 Issue 11 Pg. 1722-1741 (11 2020) ISSN: 2159-8290 [Electronic] United States
• PMID: 32703768 (Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't)
• Copyright: ©2020 American Association for Cancer Research.

Topics

• Epigenomics (methods)
• Humans
• Meningioma (genetics, pathology)
• Prognosis