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

in Cancer discovery by 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

TLDR

  • The study uses enhancer landscapes to classify meningiomas and identify novel therapeutic targets, including a previously unknown target, DUSP1.
  • The classification system informs prognostic classification of aggressive meningiomas and identifies tumors at high risk of recurrence.
  • The results have the potential to guide treatment of intractable meningiomas.

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 superiorefficacy to treatment based upon thegenomic profile. Inhibition of DUSP1, a novel and druggable meningioma target, impaired tumor growth. 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..

Overview

  • The study investigated meningioma enhancer landscapes to classify patients based on prognosis and identify novel dependencies.
  • Enhancers robustly stratified meningiomas into three biologically distinct groups based on hormonal lineage transcriptional regulators.
  • The study aimed to identify novel therapeutic targets and classify meningiomas with poor prognosis, regardless of histologic grading.

Comparative Analysis & Findings

  • Enhancer landscapes clustered with intrinsic brain tumors and hormonally responsive systemic cancers.
  • Meningioma subgroups reflected progesterone or androgen hormonal signaling.
  • Enhancer classification identified a subset of tumors with poor prognosis, regardless of histologic grading.

Implications and Future Directions

  • Epigenetic landscapes empower meningioma classification and identification of novel therapies.
  • Druggable dependencies discovered through epigenetic profiling potentially guide treatment of intractable meningiomas.
  • Future studies could investigate the efficacy of novel targets and refine classification systems.
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