Why Meningiomas Are More Complex Than They Appear: Understanding Tumor Heterogeneity

Table of Contents

• Key Points
• Background: What Are Meningiomas and Why Does Heterogeneity Matter?
• How Was This Review Conducted?
• Methods Used to Assess Intratumoral Heterogeneity
• Histological and Spatial Heterogeneity
• Molecular and Genetic Heterogeneity
• Temporal Heterogeneity: How Tumors Change Over Time
• Clinical Implications: What This Means for Patients
• Future Directions and Perspectives
• Limitations of the Review
• Conclusions
• Recommendations for Patients
• Frequently Asked Questions
• Source Information

Key Points

• A review of 18 studies covering 2,952 meningioma patients found that different regions within the same tumor can have distinct genetic, cellular, and structural characteristics.
• This intratumoral heterogeneity helps explain why some meningiomas grow aggressively, recur after treatment, and resist therapy, according to the reviewed evidence.
• In the reviewed studies, deletions in chromosomes 1p, 14q, and 22q were strongly associated with poor prognosis and higher recurrence rates.
• TERT promoter mutations and CDKN2A/B deletions are now criteria for classifying a meningioma as grade 3, the most aggressive category.
• The review notes that standardized heterogeneity assessment, AI-based spatial analytics, and subclone-targeted therapies are needed next steps, but require further validation.

Background: What Are Meningiomas and Why Does Heterogeneity Matter?

Meningiomas are the most common primary tumors that start inside the skull. They account for more than one-third of all central nervous system tumors. The lifetime incidence is approximately 1% — meaning about 1 in 100 people will develop a meningioma at some point.

Most meningiomas are low-grade and grow slowly. Doctors often describe them as clinically indolent, meaning they cause few problems over a long period. However, high-grade meningiomas behave very differently. These aggressive tumors grow quickly, recur frequently, and respond poorly to treatment.

Systemic therapies — treatments that travel through the bloodstream, such as chemotherapy or targeted drugs — remain largely ineffective for meningiomas. The role of intratumoral heterogeneity (ITH, meaning differences between regions within the same tumor) and how tumors evolve during treatment is still poorly understood.

Traditionally, doctors have predicted outcomes based on two factors: the tumor's histopathologic grade (how abnormal the cells look under a microscope) and the extent of surgical removal. But emerging molecular insights have refined how doctors assess risk.

The 2021 World Health Organization (WHO) Classification of Central Nervous System tumors now integrates molecular features into diagnosis. Specifically, two genetic changes — TERT promoter mutations (changes in a gene that controls cell lifespan) and CDKN2A/B deletions (loss of genes that normally suppress tumor growth) — are now criteria for classifying a meningioma as grade 3, the most aggressive category.

Genomic patterns also vary by tumor location. Convexity meningiomas (those on the outer surface of the brain) and spinal meningiomas frequently carry loss of chromosome 22q and mutations in the NF2 gene. In contrast, skull base tumors are more likely to have alterations in AKT1, TRAF7, SMO, and PIK3CA genes. This highlights how important molecular profiling is for understanding each patient's tumor.

Despite these advances, histologic grade and genetic drivers alone do not fully capture how a meningioma will behave. Growing evidence shows that ITH plays a central role in tumor progression, treatment resistance, and recurrence. ITH spans genetic, epigenetic, transcriptional, and functional levels. Epigenetic changes affect gene activity without altering DNA sequence. Transcriptional changes refer to gene expression.

This complexity confuses current diagnostic and prognostic frameworks. It also limits how well targeted therapies work. A more comprehensive understanding of the spatial (geographic), temporal (over time), and molecular dimensions of ITH is essential to improve risk assessment, enhance prognostic accuracy, and guide better treatment strategies.

The goal of this review was to systematically characterize histo-molecular ITH in meningiomas using integrated genomic, spatial, and functional approaches. The authors aimed to clarify the mechanisms of tumor progression and inform precision diagnostic and therapeutic strategies for high-grade meningioma.

How Was This Review Conducted?

The authors performed a narrative review following PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses, a standardized framework for conducting and reporting reviews).

They searched PubMed and Google Scholar. They used Boolean operators to link the terms "Heterogeneity," "Intratumoral," "Histo-molecular," and "Meningioma." Boolean operators are a search technique. Boolean operators combine keywords with AND, OR, or NOT. The search was limited to studies published in English or French up to 28 July 2025.

The researchers screened titles, abstracts, and full texts to identify studies focused on histo-molecular ITH in meningioma. To be included, studies had to report histo-molecular ITH in meningioma and its clinical relevance. The authors excluded case reports, review articles, and studies involving non-human meningioma.

The search initially identified 70 studies. Of these, 43 studies (61.5%) were excluded during title and abstract screening. Another 9 studies (12.8%) were excluded after full-text review. A total of 18 studies (25.7%) met the inclusion criteria and were retained.

These 18 studies encompassed 2,952 meningioma samples. The mean patient age was 59.4 years (standard deviation ± 14.8 years), with a range from 16 to 85 years.

Data extraction used a standardized form that captured study design, sample size, the type of ITH assessment methodology, histological features, type of molecular heterogeneity, and clinical relevance. Because this was a narrative review, the authors did not perform a formal assessment of study quality or risk of bias. They synthesized data narratively, focusing on histo-molecular profile, genetic profile, patterns of heterogeneity, and observed correlations between heterogeneity and clinical outcomes. They also calculated pooled statistics using measures of central tendency and dispersion.

Methods Used to Assess Intratumoral Heterogeneity

Researchers have characterized ITH in meningiomas through a multimodal analytical framework. This framework integrates cytogenetic (chromosome-level), molecular, spatial, and functional approaches.

Classical cytogenetic methods include karyotyping, comparative genomic hybridization (CGH), and fluorescence in situ hybridization (FISH). Karyotyping examines the full set of chromosomes. CGH is a technique that detects gains or losses of DNA across the genome. FISH is a method that uses fluorescent probes to locate specific DNA sequences on chromosomes. These methods have identified recurrent chromosomal abnormalities such as losses of chromosome arms 1p, 14q, and 22q. They have also revealed clonal diversity across tumor grades.

Flow cytometry and immunohistochemical analyses (techniques that measure cell properties and detect specific proteins in tissue) allow rapid, quantitative assessment of proliferative heterogeneity. These methods evaluate DNA content, detect aneuploidy (an abnormal number of chromosomes), and measure cellular proliferation indices.

Recent advances in single-cell RNA sequencing (scRNA-seq, a technique that reads gene activity in individual cells) and copy number variation (CNV) analysis have enabled identification of transcriptional and genomic subclones. These subclones have distinct proliferative, metabolic, and immune-interacting phenotypes.

Spatial transcriptomics and imaging mass cytometry further map regional variations in gene expression, proliferation, and immune-vascular architecture. These techniques capture microregional heterogeneity within the tumor microenvironment.

Complementary platforms include patient-derived meningioma organoids (lab-grown miniature tumors derived from patient samples) that reproduce the native tumor's complexity. These organoids allow mechanistic investigation of subclonal behavior. Oncogenetic tree modeling reconstructs clonal evolution and predicts recurrence risk based on genetic progression patterns.

Collectively, these integrative methodologies provide a comprehensive understanding of meningioma heterogeneity and histo-molecular assessment.

Histological and Spatial Heterogeneity

Across all studies, histological and spatial heterogeneity in meningiomas are tightly interconnected. They jointly reflect regional differences in morphology (shape and structure), proliferation, and molecular architecture within the same tumor.

Low-grade (WHO grade 1) tumors often show regional architectural differences or mixed histological patterns. These patterns may include meningothelial, fibroblastic, and transitional types. Higher-grade (WHO grade 2–3) meningiomas display pronounced microregional variability in cellularity (cell density), mitotic rate (how often cells divide), necrosis (dead tissue), and vascularisation (blood vessel formation).

Intraoperative flow cytometry is a technique performed during surgery. Intraoperative flow cytometry identified significant intratumoral spatial heterogeneity in proliferative indices. This heterogeneity was found across the tumor center, periphery, and dural attachment. The dural attachment is where the tumor connects to the brain covering.

The highest proliferative fractions localized to the dural attachment in low-grade, slow-growing tumors. In contrast, higher-grade lesions showed increased proliferation within central and peripheral regions associated with pial vascular supply (blood vessels from the brain's inner covering).

Subclonal chromosomal and transcriptomic diversity mirrors histologic complexity. In high-grade meningiomas, regions with rhabdoid morphology (cells that look like muscle cells) frequently coincide with high-mitotic zones and mosaic alterations in p16, H3K27me3, and Ki-67 expression. This indicates that these aggressive phenotypes tend to cluster within the same spatially heterogeneous niches rather than occurring uniformly throughout the tumor.

Spatial profiling further reveals that these histologically distinct niches correspond to underlying subclonal chromosomal and transcriptomic diversity. This includes compartmentalized deletions such as 1p and 22q, and localized enrichment of immune, angiogenic, and metabolic programs.

High-grade tumors, in particular, show architectural compartmentalization. Highly proliferative, immune-interacting, and angiogenic niches coexist with relatively quiescent (inactive) regions within the same mass.

These findings underscore that histological heterogeneity in meningiomas extends beyond grade classification. It reflects the interplay between regional morphology, proliferative dynamics, and underlying molecular diversity.

The coexistence of distinct histologic patterns within single tumors — particularly in higher grades — suggests that meningioma progression involves localized microenvironmental influences and subclonal evolution. Spatial variation in proliferation indices further supports the presence of functionally distinct tumor compartments. These compartments may contribute to uneven growth, recurrence risk, and treatment resistance.

Molecular and Genetic Heterogeneity

Meningiomas exhibit extensive molecular and genetic heterogeneity. This encompasses chromosomal, mutational, epigenetic, and transcriptional alterations that vary by tumor grade and subtype.

Classical cytogenetic studies revealed frequent chromosomal losses of 1p, 14q, and 22q, and gains of chromosomes 1q, 7, 9, 10, 11, 15, 17, and X. These define key subclonal populations and reflect stepwise clonal evolution.

Single-cell and FISH analyses identified both dominant clones with large-scale chromosomal deletions and minor subclones with chromosomal gains or tetraploidy (having four sets of chromosomes instead of two). This indicates progressive diversification during tumor evolution.

High-grade meningiomas show uniform and complex karyotypic abnormalities. Low-grade tumors may display only focal or cryptic changes.

Single-cell and multi-omics analyses have further delineated transcriptional heterogeneity. They reveal distinct subclones enriched for cell-cycle, immune, angiogenic, and metabolic pathways.

DNA methylation profiling (a technique that detects chemical tags on DNA that control gene activity) demonstrates intratumoral epigenetic heterogeneity. Benign, intermediate, and malignant methylation subclasses can coexist within a single tumor. High-grade tumors are further characterized by recurrent partial or complete copy number losses involving chromosomes 4 and 6.

Molecular outliers, such as SULT1E1+ subpopulations (cells with high activity of a specific enzyme), influence macrophage polarization (how immune cells are activated) and contribute to malignant behavior. MDM2 amplification (extra copies of a gene that promotes cell survival) and TERT promoter mutations arise heterogeneously during tumor progression or recurrence.

Methylation analysis further defines merlin-intact, immune-enriched, and hypermitotic groups. The hypermitotic group splits into proliferative (FOXM1-driven, with the worst prognosis) and hypermetabolic (metabolism-driven) subgroups. These subgroups refine risk prediction.

Genomics and proteomics reveal that NF2/chromosome 22 loss occurs in about half of high-grade tumors. Non-NF2 skull base benign grade tumors more often have subtypes involving TRAF7 with or without KLF4, AKT1, or SMO alterations. Within NF2 tumors, ANXA3 emerges as a targetable proliferative driver.

Molecular and genetic analyses reveal that meningiomas are highly heterogeneous tumors. They are characterized by diverse chromosomal, epigenetic, and transcriptional alterations. Recurrent copy number variations and the coexistence of multiple subclonal populations highlight a stepwise clonal evolution from low-grade to high-grade disease.

Single-cell and methylation studies further uncover functionally distinct subpopulations that drive proliferation, immune modulation, and angiogenesis. The emergence of molecular outliers, such as SULT1E1+ and TERT promoter-mutant clones, underscores the dynamic and adaptive nature of tumor evolution. This reinforces the need for integrated, multi-omics approaches to better predict behavior and guide targeted therapy.

Temporal Heterogeneity: How Tumors Change Over Time

Temporal heterogeneity in meningiomas arises from clonal evolution and progressive genetic diversification over time. This is particularly evident between primary and recurrent tumors.

Longitudinal cytogenetic and single-cell sequencing studies demonstrate that meningiomas acquire additional chromosomal losses and gains during recurrence or malignant transformation. The most common changes involve chromosomes 1p, 14q, and 22q. New subclones also emerge.

Even minor genetic subclones present at initial diagnosis can expand and dominate subsequent tumor stages. This drives recurrence, therapeutic resistance, and malignant progression.

Transcriptomic analyses further reveal dynamic temporal shifts in proliferative, metabolic, and immune-interacting programs. These shifts reflect adaptive remodeling of the tumor microenvironment during recurrence.

Collectively, these findings indicate that meningiomas evolve through a stepwise, time-dependent accumulation of molecular alterations. This underscores the importance of longitudinal genomic monitoring to predict recurrence, refine risk stratification, and guide targeted therapeutic strategies.

Clinical Implications: What This Means for Patients

Across studies, a clear link has been established between intratumoral heterogeneity and WHO grade, prognosis, and therapeutic response in meningiomas.

Low-grade (WHO grade 1) meningiomas generally exhibit limited or regional heterogeneity. High-grade (WHO grade 2–3) tumors display extensive genetic, molecular, and spatial complexity. This increased heterogeneity correlates with more aggressive clinical behavior, earlier recurrence, and reduced responsiveness to conventional treatments.

Homogeneous and multichromosomal aberrations — particularly deletions in 1p, 14q, and 22q — are strongly associated with poor prognosis and higher recurrence rates. Tumors lacking major chromosomal alterations tend to grow more slowly and recur less frequently.

Temporal and clonal evolution contribute to malignant transformation. This emphasizes the prognostic importance of detecting minor but genetically advanced subclones that can drive recurrence and treatment resistance.

Functionally, distinct proliferative and immune-interacting subpopulations such as SULT1E1+ cells promote tumor aggressiveness, radioresistance, and macrophage polarization. However, these subpopulations also represent promising therapeutic targets.

Current evidence highlights a paradigm shift toward molecularly integrated grading and personalized management. Mapping ITH refines prognostic accuracy, guides risk stratification, and informs the development of precision therapies in meningioma care.

Several targeted therapies show promise in recurrent high-grade disease:

• Everolimus plus octreotide — a combination of an mTOR inhibitor and a somatostatin analogue
• Sunitinib — a multi-targeted receptor tyrosine kinase inhibitor
• Alpelisib with trametinib — a combination strategy that co-targets signaling pathways (PI3K and MEK inhibition)

Tumor growth rate reduction may serve as a sensitive endpoint to evaluate treatment efficacy. However, despite these advances, the management of high-grade meningiomas remains challenging and requires further validation of emerging therapies.

Future Directions and Perspectives

Despite significant advances in defining histo-molecular diversity, standardized frameworks for assessing ITH in meningiomas are still lacking. Current diagnostic workflows often rely on single-biopsy histopathology and bulk molecular analyses. These approaches fail to capture the spatial and temporal complexity of these tumors.

Tumor models, particularly patient-derived organoids, are emerging as valuable platforms to recapitulate intratumoral heterogeneity. Multiregional and single-cell sequencing studies have consistently demonstrated that histologically homogeneous meningiomas can nonetheless harbor substantial intratumoral heterogeneity. This heterogeneity is characterized by the coexistence of genetically and transcriptionally distinct clonal populations, as well as microregional variability in cellular composition and signaling states.

These findings highlight the limitations of conventional histopathological assessment in fully capturing tumor complexity. The development and adoption of standardized methodological frameworks for multiregional sampling, spatially resolved molecular profiling, and robust quantification of clonal architecture are likely to be critical.

Such standardization would enable more accurate and reproducible characterization of tumor biology. It would improve the prediction of recurrence risk and clinical outcomes. It would also enhance comparability across studies and institutions.

Moreover, implementing these approaches would support the incorporation of intratumoral heterogeneity metrics into future WHO classification systems. It would advance their integration into precision oncology strategies, ultimately facilitating more personalized and biologically informed therapeutic decision-making.

The integration of artificial intelligence (AI) and spatial transcriptomics represents a transformative opportunity for ITH characterization. AI-driven image analytics and machine learning algorithms can detect subtle histopathological and molecular correlates of heterogeneity that conventional microscopy underestimates.

Spatial omics approaches, including multiplex imaging and proteogenomic mapping, enable simultaneous visualization of gene expression, chromosomal aberrations, and immune-vascular networks within intact tumor sections. These multimodal datasets can be computationally modeled to reconstruct evolutionary trajectories, identify resistant subregions, and inform surgical margin assessment.

Ultimately, integrating AI-based morpho-molecular analytics with spatial omics has the potential to refine tumor classification and guide adaptive, patient-specific therapeutic strategies.

Therapeutically, elucidating ITH provides a foundation for targeted and combined treatment strategies in high-grade and recurrent meningiomas. The identification of SULT1E1+ initiating clones and COL6A3-mediated macrophage-tumor interactions underscores the potential for selectively targeting malignant and immune-regulatory subpopulations to suppress progression and recurrence.

The heterogeneity of TERT promoter mutations, MDM2 amplification, and DNA methylation subtypes highlights the need for adaptive molecular therapies that address dynamic clonal evolution. Future clinical trials should incorporate ITH-informed biomarkers for patient stratification and personalized therapy. These trials should integrate small-molecule inhibitors, immune modulators, and radiosensitizers such as SRT1720.

The convergence of real-time ITH profiling, AI-based predictive modeling, and molecularly guided therapy promises to significantly advance precision neuro-oncology for refractory and high-grade meningiomas.

Limitations of the Review

This narrative review has several limitations that patients and clinicians should consider.

First, there was substantial heterogeneity in study design, sample size, and methodology across the included studies. Additionally, age data were missing in 10 of the 18 studies. These factors introduce variability that limits direct quantitative comparisons between studies.

Second, most available studies focus on small, regionally sampled cohorts. These studies often lack standardized protocols for multiregional or longitudinal assessment of ITH.

Third, data integration across molecular, spatial, and clinical domains remains incomplete. There is limited validation in prospective or therapeutic contexts.

Despite these limitations, this review summarizes the most comprehensive, up-to-date evidence on histo-molecular heterogeneity and its clinical implications in meningioma biology.

Conclusions

Intratumoral histo-molecular heterogeneity represents a defining feature of meningioma biology. It shapes tumor evolution, recurrence risk, and therapeutic response.

Multimodal approaches have revealed that meningiomas evolve through stepwise clonal diversification. Genetic, epigenetic, and immune-driven mechanisms underpin malignant progression. These approaches include:

• Single-cell and spatial transcriptomics
• Advanced cytogenetics
• Functional assays such as intraoperative flow cytometry
• DNA ploidy and proliferation index analysis
• Immunohistochemical proliferation markers
• Patient-derived organoid models with drug and radiosensitivity testing

High-grade tumors exhibit spatially compartmentalized subclones and temporal genomic evolution. These features challenge conventional grading and necessitate molecularly integrated diagnostics.

Standardized ITH assessment, AI-assisted spatial analytics, and subclone-targeted therapeutics hold promise for translating biological complexity into precision care. Future research should aim to validate these integrative approaches in longitudinal clinical settings, fostering the transition toward personalized neuro-oncology in meningioma management.

Recommendations for Patients

Based on this review, here are key points for patients diagnosed with meningioma:

1. Ask about molecular profiling. Beyond standard pathology, ask your medical team whether molecular testing (such as methylation profiling or chromosomal analysis) has been performed on your tumor. This information can refine your prognosis and treatment options.
2. Understand that one biopsy may not tell the whole story. Because different regions of a meningioma can have different characteristics, a single biopsy sample may not capture the full picture of your tumor's biology.
3. Discuss recurrence monitoring. High-grade meningiomas can acquire new genetic changes over time. Regular imaging follow-up and, when appropriate, molecular monitoring of recurrent tumors can help guide treatment decisions.
4. Inquire about clinical trials. Several targeted therapies are being studied for recurrent high-grade meningiomas, including everolimus plus octreotide, sunitinib, and combination approaches like alpelisib with trametinib. Ask your oncologist whether any clinical trials are appropriate for your situation.
5. Seek care at specialized centers. Given the complexity of meningioma biology, treatment at a center with expertise in neuro-oncology and access to advanced molecular diagnostics may provide more personalized care.

Frequently Asked Questions

What is intratumoral heterogeneity in a meningioma?

Intratumoral heterogeneity means different regions within the same meningioma can have distinct genetic, cellular, and structural characteristics. A review of 18 studies covering 2,952 meningioma patients found this diversity helps explain why some tumors grow aggressively, recur after treatment, and resist therapy. It also means one biopsy sample may not capture the full picture of your tumor's biology.

Does a single biopsy show everything about my meningioma?

Not necessarily. Because different regions of a meningioma can have different characteristics, a single biopsy sample may not capture the full picture of your tumor's biology. The review of 18 studies covering 2,952 patients found that histologically similar tumors can still contain genetically and transcriptionally distinct cell populations, so asking your team about molecular profiling may help refine your prognosis.

Why do some meningiomas come back after treatment?

In the reviewed studies, high-grade meningiomas can acquire new genetic changes over time, and minor subclones present at diagnosis can expand and dominate later stages. This stepwise evolution drives recurrence, treatment resistance, and malignant progression. The review found that deletions in chromosomes 1p, 14q, and 22q were strongly associated with poor prognosis and higher recurrence rates.

What molecular tests might my medical team consider?

The review describes molecular testing such as DNA methylation profiling, chromosomal analysis, and single-cell or spatial techniques. Two genetic changes, TERT promoter mutations and CDKN2A/B deletions, are now criteria for classifying a meningioma as grade 3. Asking whether molecular testing has been performed on your tumor can help refine prognosis and treatment options.

Are there targeted therapies for recurrent high-grade meningiomas?

The review notes several targeted therapies showing promise in recurrent high-grade disease: everolimus plus octreotide, sunitinib, and alpelisib with trametinib. However, management of high-grade meningiomas remains challenging and these emerging therapies still require further validation. Ask your oncologist whether any clinical trials are appropriate for your situation, since systemic therapies remain largely ineffective for meningiomas overall.

How common are meningiomas, and are they usually slow-growing?

Meningiomas are the most common primary tumors that start inside the skull, accounting for more than one-third of all central nervous system tumors. Lifetime incidence is approximately 1%, meaning about 1 in 100 people will develop one. Most are low-grade and grow slowly, but high-grade meningiomas grow quickly, recur frequently, and respond poorly to treatment.

What are the limitations of the evidence on tumor heterogeneity?

The review of 18 studies covering 2,952 patients had limitations. Study designs, sample sizes, and methods varied substantially, and age data were missing in 10 of the 18 studies. Most studies used small, regionally sampled cohorts without standardized multiregional or longitudinal protocols, and data integration across molecular, spatial, and clinical domains remains incomplete with limited prospective validation.

My meningioma was diagnosed from one biopsy — when should I get a second opinion on the pathology and molecular testing?

A single biopsy may not capture a meningioma's full biology, because different regions of the same tumor can have distinct genetic, cellular and structural characteristics, and benign, intermediate and malignant methylation subclasses can coexist within one tumor. Molecular profiling, including methylation and chromosomal analysis, refines prognosis and treatment options beyond standard pathology. A second opinion is reasonable when only single-biopsy histopathology and bulk molecular analysis were used, when the grade or molecular findings will drive decisions about targeted therapy or clinical trial eligibility, or when a high-grade tumor recurs and new genetic changes may have emerged. Diagnostic Detectives Network provides independent expert second opinions.

Source Information

Original Article Title: Histo-Molecular Intratumoral Heterogeneity in Meningiomas: A Narrative Review.

License: CC BY (open access)

Authors: Bankole NDA, Le Van T, Kerherve L, Morlaix E, Bellus JF, Belhajali K, Lopez J, De Buck P, Houidi AS, Farah W, Lleu M, Baland O, Cao C, El Cadhi A, Beaurain J, Picart T, Berhouma M.

Affiliations: Neurosurgery Department, Dijon University Hospital Center, Dijon, France; INSERM Imaging Brain & Neuropsychiatry iBrain U1253, Université de Tours, Tours, France; Neurosurgery Department, Hospices Civils de Lyon-Pierre Wertheimer Hospital, Bron, France; INSERM 1052 UMR 5286, Research Cancerology Center of Lyon, Lyon, France; Functional and Molecular Imaging Team, Centre National de la Recherche Scientifique 6302, Molecular Chemistry Institute (ICMUB), University of Bourgogne, Dijon, France

Journal: Cancers, 2026, Volume 18, Article 1206

Publication Date: Published 10 April 2026

DOI: https://doi.org/10.3390/cancers18081206

Note: This patient-friendly article is based on peer-reviewed research. The original study was a narrative review of 18 studies including 2,952 meningioma patients. This review received no external funding, and the authors declared no conflicts of interest.