Hypermitotic meningiomas harbor DNA methylation subgroups with distinct biological and clinical features

Meningioma transcriptomic landscape demonstrates novel subtypes with regional associated biology and patient outcome

Meningiomas, although mostly benign, can be recurrent and fatal. World Health Organization (WHO) grading of the tumor does not always identify high-risk meningioma, and better characterizations of their aggressive biology are needed. To approach this problem, we combined 13 bulk RNA sequencing (RNA-seq) datasets to create a dimension-reduced reference landscape of 1,298 meningiomas. The clinical and genomic metadata effectively correlated with landscape regions, which led to the identification of meningioma subtypes with specific biological signatures. The time to recurrence also correlated with the map location. Further, we developed an algorithm that maps new patients onto this landscape, where the nearest neighbors predict outcome. This study highlights the utility of combining bulk transcriptomic datasets to visualize the complexity of tumor populations. Further, we provide an interactive tool for understanding the disease and predicting patient outcomes. This resource is accessible via the online tool Oncoscape, where the scientific community can explore the meningioma landscape.

Spatial genomic, biochemical and cellular mechanisms underlying meningioma heterogeneity and evolution

Intratumor heterogeneity underlies cancer evolution and treatment resistance, but targetable mechanisms driving intratumor heterogeneity are poorly understood. Meningiomas are the most common primary intracranial tumors and are resistant to all medical therapies, and high-grade meningiomas have significant intratumor heterogeneity. Here we use spatial approaches to identify genomic, biochemical and cellular mechanisms linking intratumor heterogeneity to the molecular, temporal and spatial evolution of high-grade meningiomas. We show that divergent intratumor gene and protein expression programs distinguish high-grade meningiomas that are otherwise grouped together by current classification systems. Analyses of matched pairs of primary and recurrent meningiomas reveal spatial expansion of subclonal copy number variants associated with treatment resistance. Multiplexed sequential immunofluorescence and deconvolution of meningioma spatial transcriptomes using cell types from single-cell RNA sequencing show decreased immune infiltration, decreased MAPK signaling, increased PI3K-AKT signaling and increased cell proliferation, which are associated with meningioma recurrence. To translate these findings to preclinical models, we use CRISPR interference and lineage tracing approaches to identify combination therapies that target intratumor heterogeneity in meningioma cell co-cultures.

Leveraging single-cell sequencing to classify and characterize tumor subgroups in bulk RNA-sequencing data

PURPOSE

Accurate classification of cancer subgroups is essential for precision medicine, tailoring treatments to individual patients based on their cancer subtypes. In recent years, advances in high-throughput sequencing technologies have enabled the generation of large-scale transcriptomic data from cancer samples. These data have provided opportunities for developing computational methods that can improve cancer subtyping and enable better personalized treatment strategies.

METHODS

Here in this study, we evaluated different feature selection schemes in the context of meningioma classification. To integrate interpretable features from the bulk (n = 77 samples) and single-cell profiling (∼ 10 K cells), we developed an algorithm named CLIPPR which combines the top-performing single-cell models, RNA-inferred copy number variation (CNV) signals, and the initial bulk model to create a meta-model.

RESULTS

While the scheme relying solely on bulk transcriptomic data showed good classification accuracy, it exhibited confusion between malignant and benign molecular classes in approximately ∼ 8% of meningioma samples. In contrast, models trained on features learned from meningioma single-cell data accurately resolved the sub-groups confused by bulk-transcriptomic data but showed limited overall accuracy. CLIPPR showed superior overall accuracy and resolved benign-malignant confusion as validated on n = 789 bulk meningioma samples gathered from multiple institutions. Finally, we showed the generalizability of our algorithm using our in-house single-cell (∼ 200 K cells) and bulk TCGA glioma data (n = 711 samples).

CONCLUSION

Overall, our algorithm CLIPPR synergizes the resolution of single-cell data with the depth of bulk sequencing and enables improved cancer sub-group diagnoses and insights into their biology.

The Evolving Classification of Meningiomas: Integration of Molecular Discoveries to Inform Patient Care

Meningioma classification and treatment have evolved over the past eight decades. Since Bailey, Cushing, and Eisenhart's description of meningiomas in the 1920s and 1930s, there have been continual advances in clinical stratification by histopathology, radiography and, most recently, molecular profiling, to improve prognostication and predict response to therapy. Precise and accurate classification is essential to optimizing management for patients with meningioma, which involves surveillance imaging, surgery, primary or adjuvant radiotherapy, and consideration for clinical trials. Currently, the World Health Organization (WHO) grade, extent of resection (EOR), and patient characteristics are used to guide management. While these have demonstrated reliability, a substantial number of seemingly benign lesions recur, suggesting opportunities for improvement of risk stratification. Furthermore, the role of adjuvant radiotherapy for grade 1 and 2 meningioma remains controversial. Over the last decade, numerous studies investigating the molecular drivers of clinical aggressiveness have been reported, with the identification of molecular markers that carry clinical implications as well as biomarkers of radiotherapy response. Here, we review the historical context of current practices, highlight recent molecular discoveries, and discuss the challenges of translating these findings into clinical practice.

Meningioma: current updates on genetics, classification, and mouse modeling

Meningiomas, the most common primary brain tumors in adults, are often benign and curable by surgical resection. However, a subset is of higher grade, shows aggressive growth behavior as well as brain invasion, and often recurs even after several rounds of surgery. Increasing evidence suggests that tumor classification and grading primarily based on histopathology do not always accurately predict tumor aggressiveness and recurrence behavior. The underlying biology of aggressive treatment-resistant meningiomas and the impact of specific genetic aberrations present in these high-grade tumors is still only insufficiently understood. Therefore, an in-depth research into the biology of this tumor type is warranted. More recent studies based on large-scale molecular data such as whole exome/genome sequencing, DNA methylation sequencing, and RNA sequencing have provided new insights into the biology of meningiomas and have revealed new risk factors and prognostic subtypes. The most common genetic aberration in meningiomas is functional loss of NF2 and occurs in both low- and high-grade meningiomas, whereas NF2-wildtype meningiomas are enriched for recurrent mutations in TRAF7, KLF4, AKT1, PI3KCA, and SMO and are more frequently benign. Most meningioma mouse models are based on patient-derived xenografts and only recently have new genetically engineered mouse models of meningioma been developed that will aid in the systematic evaluation of specific mutations found in meningioma and their impact on tumor behavior. In this article, we review recent advances in the understanding of meningioma biology and classification and highlight the most common genetic mutations, as well as discuss new genetically engineered mouse models of meningioma.

Preclinical evaluation of the third-generation, bi-steric mechanistic target of rapamycin complex 1-selective inhibitor RMC-6272 in NF2-deficient models

Background

NF2-associated meningiomas are progressive, highly morbid, and nonresponsive to chemotherapies, highlighting the need for improved treatments. We have established aberrant activation of the mechanistic target of rapamycin (mTOR) signaling in NF2-deficient tumors, leading to clinical trials with first- and second-generation mTOR inhibitors. However, results have been mixed, showing stabilized tumor growth without shrinkage offset by adverse side effects. To address these limitations, here we explored the potential of third-generation, bi-steric mTOR complex 1 (mTORC1) inhibitors using the preclinical tool compound RMC-6272.

Methods

Employing human NF2-deficient meningioma lines, we compared mTOR inhibitors rapamycin (first-generation), INK128 (second-generation), and RMC-6272 (third-generation) using in vitro dose-response testing, cell-cycle analysis, and immunoblotting. Furthermore, the efficacy of RMC-6272 was assessed in NF2-null 3D-spheroid meningioma models, and its in vivo potential was evaluated in 2 orthotopic meningioma mouse models.

Results

Treatment of meningioma cells revealed that, unlike rapamycin, RMC-6272 demonstrated superior growth inhibitory effects, cell-cycle arrest, and complete inhibition of phosphorylated 4E-BP1 (mTORC1 readout). Moreover, RMC-6272 had a longer retention time than INK128 and inhibited the expression of several eIF4E-sensitive targets on the protein level. RMC-6272 treatment of NF2 spheroids showed significant shrinkage in size as well as reduced proliferation. Furthermore, in vivo studies in mice revealed effective blockage of meningioma growth by RMC-6272, compared with vehicle controls.

Conclusions

Our study in preclinical models of NF2 supports possible future clinical evaluation of third-generation, investigational mTORC1 inhibitors, such as RMC-5552, as a potential treatment strategy for NF2.

A novel BRAF::PTPRN2 fusion in meningioma: a case report

Gene fusion events have been linked to oncogenesis in many cancers. However, gene fusions in meningioma are understudied compared to somatic mutations, chromosomal gains/losses, and epigenetic changes. Fusions involving B-raf proto-oncogene, serine/threonine kinase (BRAF) are subtypes of oncogenic BRAF genetic abnormalities that have been reported in certain cases of brain tumors, such as pilocytic astrocytomas. However, BRAF fusions have not been recognized in meningioma. We present the case of an adult female presenting with episodic partial seizures characterized by déjà vu, confusion, and cognitive changes. Brain imaging revealed a cavernous sinus and sphenoid wing mass and she underwent resection. Histopathology revealed a World Health Organization (WHO) grade 1 meningioma. Genetic profiling with next generation sequencing and microarray analysis revealed an in-frame BRAF::PTPRN2 fusion affecting the BRAF kinase domain as well as chromothripsis of chromosome 7q resulting in multiple segmental gains and losses including amplifications of cyclin dependent kinase 6 (CDK6), tyrosine protein-kinase Met (MET), and smoothened (SMO). Elevated pERK staining in tumor cells provided evidence of activated mitogen-activated protein kinase (MAPK) signaling. This report raises the possibility that gene fusion events may be involved in meningioma pathogenesis and warrant further investigation.

Targeted gene expression profiling predicts meningioma outcomes and radiotherapy responses

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems tested (N = 9) in the clinical validation cohort for local recurrence (5-year area under the curve (AUC) 0.81) and overall survival (5-year AUC 0.80). The increase in AUC compared with the standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval 0.07 to 0.17, P < 0.001). The gene expression biomarker identified meningiomas benefiting from postoperative radiotherapy (hazard ratio 0.54, 95% confidence interval 0.37 to 0.78, P = 0.0001) and suggested postoperative management could be refined for 29.8% of patients. In sum, our results identify a targeted gene expression biomarker that improves discrimination of meningioma outcomes, including prediction of postoperative radiotherapy responses.

NOTCH3 drives meningioma tumorigenesis and resistance to radiotherapy

Meningiomas are the most common primary intracranial tumors1-3. Treatments for patients with meningiomas are limited to surgery and radiotherapy, and systemic therapies remain ineffective or experimental4,5. Resistance to radiotherapy is common in high-grade meningiomas6, and the cell types and signaling mechanisms driving meningioma tumorigenesis or resistance to radiotherapy are incompletely understood. Here we report NOTCH3 drives meningioma tumorigenesis and resistance to radiotherapy and find NOTCH3+ meningioma mural cells are conserved across meningiomas from humans, dogs, and mice. NOTCH3+ cells are restricted to the perivascular niche during meningeal development and homeostasis and in low-grade meningiomas but are expressed throughout high-grade meningiomas that are resistant to radiotherapy. Integrating single-cell transcriptomics with lineage tracing and imaging approaches across mouse genetic and xenograft models, we show NOTCH3 drives tumor initiating capacity, cell proliferation, angiogenesis, and resistance to radiotherapy to increase meningioma growth and reduce survival. An antibody stabilizing the extracellular negative regulatory region of NOTCH37,8 blocks meningioma tumorigenesis and sensitizes meningiomas to radiotherapy, reducing tumor growth and improving survival in preclinical models. In summary, our results identify a conserved cell type and signaling mechanism that underlie meningioma tumorigenesis and resistance to radiotherapy, revealing a new therapeutic vulnerability to treat meningiomas that are resistant to standard interventions.

Increased mRNA expression of CDKN2A is a transcriptomic marker of clinically aggressive meningiomas

Homozygous deletion of CDKN2A/B was recently incorporated into the World Health Organization classification for grade 3 meningiomas. While this marker is overall rare in meningiomas, its relationship to other CDKN2A alterations on a transcriptomic, epigenomic, and copy number level has not yet been determined. We therefore utilized multidimensional molecular data of 1577 meningioma samples from 6 independent cohorts enriched for clinically aggressive meningiomas to comprehensively interrogate the spectrum of CDKN2A alterations through DNA methylation, copy number variation, transcriptomics, and proteomics using an integrated molecular approach. Homozygous CDKN2A/B deletions were identified in only 7.1% of cases but were associated with significantly poorer outcomes compared to tumors without these deletions. Heterozygous CDKN2A/B deletions were identified in 2.6% of cases and had similarly poor outcomes as those with homozygous deletions. Among tumors with intact CDKN2A/B (without a homozygous or heterozygous deletion), we found a distinct difference in outcome based on mRNA expression of CDKN2A, with meningiomas that had elevated mRNA expression (CDKN2A^high) having a significantly shorter time to recurrence. The expression of CDKN2A was independently prognostic after accounting for copy number loss and consistently increased with WHO grade and more aggressive molecular and methylation groups irrespective of cohort. Despite the discordant and mutually exclusive status of the CDKN2A gene in these groups, both CDKN2A^high meningiomas and meningiomas with CDKN2A deletions were enriched for similar cell cycle pathways but at different checkpoints. High mRNA expression of CDKN2A was also associated with gene hypermethylation, Rb-deficiency, and lack of response to CDK inhibition. p16 immunohistochemistry could not reliably differentiate between meningiomas with and without CDKN2A deletions but appeared to correlate better with mRNA expression. These findings support the role of CDKN2A mRNA expression as a biomarker of clinically aggressive meningiomas with potential therapeutic implications.

Targeted gene expression profiling predicts meningioma outcomes and radiotherapy responses

Background

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and current indications for postoperative radiotherapy are controversial. Recent studies have proposed prognostic meningioma classification systems using DNA methylation profiling, copy number variants, DNA sequencing, RNA sequencing, histology, or integrated models based on multiple combined features. Targeted gene expression profiling has generated robust biomarkers integrating multiple molecular features for other cancers, but is understudied for meningiomas.

Methods

Targeted gene expression profiling was performed on 173 meningiomas and an optimized gene expression biomarker (34 genes) and risk score (0 to 1) was developed to predict clinical outcomes. Clinical and analytical validation was performed on independent meningiomas from 12 institutions across 3 continents (N = 1856), including 103 meningiomas from a prospective clinical trial. Gene expression biomarker performance was compared to 9 other classification systems.

Results

The gene expression biomarker improved discrimination of postoperative meningioma outcomes compared to all other classification systems tested in the independent clinical validation cohort for local recurrence (5-year area under the curve [AUC] 0.81) and overall survival (5-year AUC 0.80). The increase in area under the curve compared to the current standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval [CI] 0.07-0.17, P < 0.001). The gene expression biomarker identified meningiomas benefiting from postoperative radiotherapy (hazard ratio 0.54, 95% CI 0.37-0.78, P = 0.0001) and re-classified up to 52.0% meningiomas compared to conventional clinical criteria, suggesting postoperative management could be refined for 29.8% of patients.

Conclusions

A targeted gene expression biomarker improves discrimination of meningioma outcomes compared to recent classification systems and predicts postoperative radiotherapy responses.

MerlinS13 phosphorylation controls meningioma Wnt signaling and magnetic resonance imaging features

Meningiomas are the most common primary intracranial tumors and are associated with inactivation of the tumor suppressor NF2/Merlin, but one-third of meningiomas retain Merlin expression and typically have favorable clinical outcomes. Biochemical mechanisms underlying Merlin-intact meningioma growth are incompletely understood, and non-invasive biomarkers that predict meningioma outcomes and could be used to guide treatment de-escalation or imaging surveillance of Merlin-intact meningiomas are lacking. Here we integrate single-cell RNA sequencing, proximity-labeling proteomic mass spectrometry, mechanistic and functional approaches, and magnetic resonance imaging (MRI) across meningioma cells, xenografts, and human patients to define biochemical mechanisms and an imaging biomarker that distinguish Merlin-intact meningiomas with favorable clinical outcomes from meningiomas with unfavorable clinical outcomes. We find Merlin drives meningioma Wnt signaling and tumor growth through a feed-forward mechanism that requires Merlin dephosphorylation on serine 13 (S13) to attenuate inhibitory interactions with β-catenin and activate the Wnt pathway. Meningioma MRI analyses of xenografts and human patients show Merlin-intact meningiomas with S13 phosphorylation and favorable clinical outcomes are associated with high apparent diffusion coefficient (ADC) on diffusion-weighted imaging. In sum, our results shed light on Merlin posttranslational modifications that regulate meningioma Wnt signaling and tumor growth in tumors without NF2/Merlin inactivation. To translate these findings to clinical practice, we establish a non-invasive imaging biomarker that could be used to guide treatment de-escalation or imaging surveillance for patients with favorable meningiomas.

The multiomic landscape of meningiomas: a review and update

PURPOSE

Meningiomas are the most common primary brain tumor in adults. Traditionally they have been understudied compared to other central nervous system (CNS) tumors. However over the last decade, there has been renewed interest in uncovering the molecular topography of these tumors, with landmark studies identifying key driver alterations contributing to meningioma development and progression. Recent work from several independent research groups have integrated different genomic and epigenomic platforms to develop a molecular-based classification scheme for meningiomas that could supersede histopathological grading in terms of diagnostic accuracy, biological relevance, and outcome prediction, keeping pace with contemporary grading schemes for other CNS tumors including gliomas and medulloblastomas.

METHODS

Here we summarize the studies that have uncovered key alterations in meningiomas which builds towards the discovery of consensus molecular groups in meningiomas by integrating these findings. These groups supersede WHO grade and other clinical factors in being able to accurately predict tumor biology and clinical outcomes following surgery.

RESULTS

Despite differences in the nomenclature of recently uncovered molecular groups across different studies, the biological similarities between these groups enables us to likely reconciliate these groups into four consensus molecular groups: two benign groups largely dichotomized by NF2-status, and two clinically aggressive groups defined by their hypermetabolic transcriptome, and by their preponderance of proliferative, cell-cycling pathways respectively.

CONCLUSION

Future work, including by our group and others are underway to validate these molecular groups and harmonize the nomenclature for routine clinical use.