Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 4 complete abstracts (742 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
A relatively common neoplasm of the central nervous system that arises from arachnoidal cells. The majority are well differentiated vascular tumors which grow slowly and have a low potential to be invasive, although malignant subtypes occur. Meningiomas have a predilection to arise from the parasagittal region, cerebral convexity, sphenoidal ridge, olfactory groove, and spinal canal. (From DeVita et al., Cancer: Principles and Practice of Oncology, 5th ed, pp2056-7)
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Meningiomas; Meningiomas, Multiple; Meningioma, Multiple; Multiple Meningioma; Multiple Meningiomas; Meningiomatosis; Meningiomatoses; Benign Meningioma.
Where it fits in the MeSH classification
- Broader topics
- Neoplasms, Nerve Tissue; Neoplasms, Vascular Tissue; Meningeal Neoplasms
Related concepts
- Central Nervous System
- Spinal Canal
Research landscape
PubMed indexes 23,308 records tagged with the MeSH heading “Meningioma” (counts retrieved 2026-10-29). 4,084 of them (17.5%) were published from 2020 onward, and the busiest period so far is through 1999 with 10,057 records.
Reviews account for 2,541 records (10.9%) and meta-analyses for 208. Randomized controlled trials number 42 (0.2%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.
Show the data
| Period | Records |
|---|---|
| through 1999 | 10,057 |
| 2000-2009 | 3,889 |
| 2010-2019 | 5,278 |
| 2020 onward | 4,084 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 2,541 | 10.9% |
| Meta-analyses | 208 | 0.9% |
| Randomized controlled trials | 42 | 0.2% |
Method: PubMed query "Meningioma"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.
Reading the evidence in cancer and oncology
Cancer research spans very different kinds of evidence. Laboratory studies in cell lines and animal models reveal mechanisms but often do not translate to patients. Early-phase trials mainly test safety and dosing, while phase 3 randomized trials and their meta-analyses are the usual basis for treatment conclusions. Outcomes also differ in meaning: tumour shrinkage, progression-free survival and overall survival are not interchangeable, and screening studies can be distorted by lead-time and overdiagnosis. When reading a result, check the cancer type and stage studied, the comparison treatment, and which outcome was measured.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| RNA polymerase II at histone genes predicts outcome in human cancer | 2025 | Research article Design not recorded in structured metadata | 52 | cc by PMID 39946483 · DOI · PMC12184985 |
| Chromosome 1p Loss and 1q Gain for Grading of Meningioma | 2025 | Research article Design not recorded in structured metadata | 28 | cc by PMID 40178835 · DOI · PMC11969356 |
| The Molecular and Immunological Landscape of Meningiomas | 2024 | Review article Design not recorded in structured metadata | 12 | cc by PMID 39273576 · DOI · PMC11394785 |
| A microenvironment-determined risk continuum refines subtyping in meningioma and reveals determinants of machine learning-based tumor classification | 2026 | Research article Design not recorded in structured metadata | 11 | cc by PMID 41663806 · DOI · PMC12900647 |
RNA polymerase II at histone genes predicts outcome in human cancer [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Genome-wide hypertranscription is common in human cancer and predicts poor prognosis.
- Closing excerpt
- Elevated RNAPII at histone genes in meningiomas and diverse breast cancers is consistent with histone production being rate-limiting for S-phase progression and histone gene hypertranscription driving overproliferation and aneuploidy in cancer, with general implications for precision oncology.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (129 words)
Genome-wide hypertranscription is common in human cancer and predicts poor prognosis. To understand how hypertranscription might drive cancer, we applied our formalin-fixed paraffin-embedded (FFPE)-cleavage under targeted accessible chromatin method for mapping RNA polymerase II (RNAPII) genome-wide in FFPE sections. We demonstrate global RNAPII elevations in mouse gliomas and assorted human tumors in small clinical samples and discover regional elevations corresponding to de novo HER2 amplifications punctuated by likely selective sweeps. RNAPII occupancy at S-phase-dependent histone genes correlated with WHO grade in meningiomas, accurately predicted rapid recurrence, and corresponded to whole-arm chromosome losses. Elevated RNAPII at histone genes in meningiomas and diverse breast cancers is consistent with histone production being rate-limiting for S-phase progression and histone gene hypertranscription driving overproliferation and aneuploidy in cancer, with general implications for precision oncology.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 39946483 · DOI · PMC12184985
Chromosome 1p Loss and 1q Gain for Grading of Meningioma [2]
Abstract reading summary — source excerpts
- Opening excerpt
- ImportanceThe World Health Organization (WHO) classification of central nervous system tumors (CNS) grading for meningioma was updated in 2021 to include rare molecular features, namely homozygous deletions of CDKN2A or CDKN2B and TERT promotor alterations.
- Closing excerpt
- 01-∞] years; log-rank P Conclusions and relevanceThese findings highlight a role for cytogenetic profiling in the next iteration of CNS WHO grading, with a specific focus on chromosome 1p loss and 1q gain, suggesting that chromosome 1p loss, in addition to 22q loss, should be added as a criterion for a CNS WHO grade of 2 and addition of 1q gain as a criterion for a CNS WHO grade of 3.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (302 words)
ImportanceThe World Health Organization (WHO) classification of central nervous system tumors (CNS) grading for meningioma was updated in 2021 to include rare molecular features, namely homozygous deletions of CDKN2A or CDKN2B and TERT promotor alterations. Previous work, including the cIMPACT-NOW statement, has discussed the potential value of including chromosomal copy number alterations to help refine the current grading system.ObjectiveTo identify chromosomal copy number alterations that could be used to improve the current CNS WHO grading of meningioma.Design, setting, and participantsIn this cohort study, patients with surgically treated meningioma were followed-up until recurrence or progression of disease or death. Chromosomal copy number alterations were then correlated with progression-free survival (PFS) to identify new outcome biomarkers. This study included patients with a histopathological diagnosis of meningioma from multiple institutions in Canada, the US, and Germany, with molecular data collection starting in 2016. Data were analyzed from January to September 2024.ExposuresAll patients underwent surgery for meningioma and a subset underwent radiation therapy.Main outcomes and measuresThe main outcome was PFS. Cox regression analysis was used to identify copy number alterations associated with outcomes in the context of WHO grading.ResultsAmong 1964 patients with meningioma (1256 female; median [IQR] age, 58 [48-69] years) assessed, loss of chromosome 1p in WHO grade 1 meningiomas was associated with significantly worse outcomes compared with tumors without loss of 1p (median PFS, 5.83 [95% CI, 4.36-∞] years vs 34.54 [95% CI, 16.01-∞] years; log-rank P Conclusions and relevanceThese findings highlight a role for cytogenetic profiling in the next iteration of CNS WHO grading, with a specific focus on chromosome 1p loss and 1q gain, suggesting that chromosome 1p loss, in addition to 22q loss, should be added as a criterion for a CNS WHO grade of 2 and addition of 1q gain as a criterion for a CNS WHO grade of 3.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 40178835 · DOI · PMC11969356
The Molecular and Immunological Landscape of Meningiomas [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Meningiomas are the most common primary intracranial tumors in adults and typically have a slow-growing and benign nature.
- Closing excerpt
- In this review, we aim to summarize the current knowledge on the molecular and immunological landscape of meningiomas in detail and provide current and progressive ideas for future directions.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (160 words)
Meningiomas are the most common primary intracranial tumors in adults and typically have a slow-growing and benign nature. However, there is also a substantial subset of meningiomas that shows aggressive clinical behavior and is refractory to standard treatment modalities, which are still limited to surgery and/or radiotherapy. Despite intensive research, no systemic treatment options are yet available in the clinic for these challenging tumors, resulting in poor patient outcome. Intensive research on the molecular pathogenesis of meningiomas has led to improved diagnostic tools, but so far there is no standardized implementation for the molecular profiling of these tumors for clinical practice. Recent research advances have also focused on the immunophenotyping of meningiomas, leading to several clinical trials examining the use of immune checkpoint blockade therapy in patients with clinically aggressive subtypes. In this review, we aim to summarize the current knowledge on the molecular and immunological landscape of meningiomas in detail and provide current and progressive ideas for future directions.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 39273576 · DOI · PMC11394785
A microenvironment-determined risk continuum refines subtyping in meningioma and reveals determinants of machine learning-based tumor classification [4]
Abstract reading summary — source excerpts
- Opening excerpt
- Classification of tumors in neuro-oncology today relies on molecular patterns (mostly DNA methylation) and their machine learning-supported interpretation.
- Closing excerpt
- In addition, we apply these learnings to devise and validate a simple diagnostic approach for increased clinical prediction accuracy based on immunohistochemistry, which is also applicable in resource-limited settings.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (151 words)
Classification of tumors in neuro-oncology today relies on molecular patterns (mostly DNA methylation) and their machine learning-supported interpretation. Understanding the process of algorithmic interpretation is essential for safe application in clinical routine. This is paradigmatically true for the most common primary intracranial tumor in adults, meningioma. Here, by applying multiomic profiling and multiple lines of orthogonal computational evaluation in multiple independent datasets, we found that not only tumor cell characteristics but also incremental changes in the tumor microenvironment (TME) have impact on epigenetic meningioma classification and clinical outcome. Besides revealing the decisive role of non-neoplastic cells in the CNS methylation classifier, this challenges the model of distinct meningioma subgroups toward a TME-determined risk continuum. This refines current controversies in molecular meningioma subtyping. In addition, we apply these learnings to devise and validate a simple diagnostic approach for increased clinical prediction accuracy based on immunohistochemistry, which is also applicable in resource-limited settings.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41663806 · DOI · PMC12900647
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Clinical implications of the 2021 edition of the WHO classification of central nervous system tumours [5]
- Research article Meningioma: International Consortium on Meningiomas consensus review on scientific advances and treatment paradigms for clinicians, researchers, and patients [6]
- Research article Seizures in supratentorial meningioma: a systematic review and meta-analysis [7]
- Research article Incidental intracranial meningiomas: a systematic review and meta-analysis of prognostic factors and outcomes [8]
- Research article cIMPACT-NOW update 8: Clarifications on molecular risk parameters and recommendations for WHO grading of meningiomas [9]
- Research article The prognostic role of Ki-67/MIB-1 in meningioma: A systematic review with meta-analysis [10]
References
- Henikoff S, Zheng Y, Paranal RM, Xu Y, Greene JE, Henikoff JG, et al.. RNA polymerase II at histone genes predicts outcome in human cancer. . 2025. PMID 39946483 · DOI · PMC12184985
- Landry AP, Wang JZ, Patil V, Liu J, Gui C, Ellenbogen Y, et al.. Chromosome 1p Loss and 1q Gain for Grading of Meningioma. . 2025. PMID 40178835 · DOI · PMC11969356
- Lotsch C, Warta R, Herold-Mende C. The Molecular and Immunological Landscape of Meningiomas. . 2024. PMID 39273576 · DOI · PMC11394785
- Maas SLN, Tang Y, Stutheit-Zhao E, Rahmanzade R, Blume C, Hielscher T, et al.. A microenvironment-determined risk continuum refines subtyping in meningioma and reveals determinants of machine learning-based tumor classification. . 2026. PMID 41663806 · DOI · PMC12900647
- Horbinski C, Berger T, Packer RJ, Wen PY. Clinical implications of the 2021 edition of the WHO classification of central nervous system tumours. Nat Rev Neurol. 2022. PMID 35729337 · DOI
- Wang JZ, Landry AP, Raleigh DR, Sahm F, Walsh KM, Goldbrunner R, et al.. Meningioma: International Consortium on Meningiomas consensus review on scientific advances and treatment paradigms for clinicians, researchers, and patients. Neuro Oncol. 2024. PMID 38695575 · DOI · PMC11449035
- Englot DJ, Magill ST, Han SJ, Chang EF, Berger MS, McDermott MW. Seizures in supratentorial meningioma: a systematic review and meta-analysis. J Neurosurg. 2016. PMID 26636386 · DOI · PMC4889504
- Islim AI, Mohan M, Moon RDC, Srikandarajah N, Mills SJ, Brodbelt AR, et al.. Incidental intracranial meningiomas: a systematic review and meta-analysis of prognostic factors and outcomes. J Neurooncol. 2019. PMID 30656531 · DOI · PMC6449307
- Sahm F, Aldape KD, Brastianos PK, Brat DJ, Dahiya S, von Deimling A, et al.. cIMPACT-NOW update 8: Clarifications on molecular risk parameters and recommendations for WHO grading of meningiomas. Neuro Oncol. 2025. PMID 39212325 · DOI · PMC11812049
- Liu N, Song SY, Jiang JB, Wang TJ, Yan CX. The prognostic role of Ki-67/MIB-1 in meningioma: A systematic review with meta-analysis. Medicine (Baltimore). 2020. PMID 32118704 · DOI · PMC7478528
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-10-29.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.