Multiomic Characterization of Meningiomas Informs Cell of Origin and Identifies Immune Dysregulation at the Blood-CSF Barrier

Multiomic Characterization of Meningiomas Informs Cell of Origin and Identifies Immune Dysregulation at the Blood-CSF Barrier | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Multiomic Characterization of Meningiomas Informs Cell of Origin and Identifies Immune Dysregulation at the Blood-CSF Barrier Michelle Wedemeyer, Ben Strickland, Norman Garrett, Alyssa Wong, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8612817/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Meningiomas represent 1/3 of adult brain tumors and arise from the meninges, a layered immune organ that forms the blood CSF-barrier. While molecular characterization has revolutionized our capacity to distinguish benign from aggressive tumors, the developmental relationship between meningiomas and the specialized layers of the meninges remains underexplored. Using single cell transcriptomics, we identify layer-specific signatures in individual meningiomas raising the intriguing possibility that the histologic and clinical diversity of meningiomas is influenced by cell of origin. Invasive tumors were transcriptionally similar to pia and exhibited an infiltrating subpopulation of myelinating cells implicating a reactivation of developmental mechanisms in the pathogenesis of invasion. Immune cells constituted ~ 1/3 of cells in a tumor, most of which were SPI1 + tissue resident border macrophages while MYB+ bone-marrow derived macrophages were lacking. WHO I meningiomas were infiltrated with LYVE1 + border macrophages while macrophages in grade II meningiomas expressed PTGDS . Estimation of immune cell composition in meningiomas profiled by DNA methylation arrays identified characteristic immune signatures of prognostically significant molecular categories of meningiomas and a previously unrecognized level of epigenetic diversity in grade 2/3 meningiomas. Meningiomas may arise from multiple layers of the meninges rather than just arachnoid cap cells with implications for clinical behavior. Biological sciences/Cancer/CNS cancer Biological sciences/Genetics/Cancer genomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Meningiomas account for more than 1/3 of all brain tumors and have long been presumed to originate from arachnoid cap cells[1]. Though the majority of meningiomas exhibit a benign clinical course, they may arise in surgically inaccessible locations, invade underlying neural elements, or cause disfiguring hyperostosis of the overlying cranium. Meningiomas present with highly variable consistency ranging from soft and necrotic to densely calcified lesions and exhibit remarkable histologic diversity with prior classification schemes recognizing 15 histologic subtypes[2, 3]. Despite identification of recurrent drivers mutations, current classification systems do not account for their highly variable consistency or clinical course. Experience with aggressive behavior from histologically benign meningiomas inspired a search for prognostic molecular markers that identified recurrent mutations in SMO, AKT12, TRAF7, KLF4, and BAP1 that are mutually exclusive with classical NF2 alterations and lead to the incorporation of molecular markers in the WHO 2021 CNS classification for meningiomas [1, 4, 5]. Given limitations of histology for prognosis, the field has explored molecular classification schemes that variably incorporate genomic profiling, DNA methylation, and gene expression signatures[6-11]. Although guidelines do not yet recommend routine molecular testing of all meningiomas, the clinical conditions for which testing is recommended to inform treatment continue to expand[12]. In parallel, the meninges are increasingly understood as a layered and compartmentalized lymphatic organ that regulates the development of the cortex and calvarium[13-17]. Single cell sequencing studies of the normal meninges have identified subtypes of meningeal fibroblasts with layer-specific roles in immune surveillance and at the blood CSF-barrier[13, 14, 18-20]. Although bulk molecular profiling can identify clinically predictive molecular subgroups, profiling of bulk samples cannot fully resolve the contribution of individual cell types [6-8, 10]. Probing of the meningioma using bulk technologies has identified a subtype with substantial immune infiltration and spatial profiling has identified spatial heterogeneity of driver mutations; however, less attention has been paid to the diversity of the meningeal fibroblasts themselves[8, 18, 21]. Considering the modern view of the meninges as a multilayered immune organ, we probed the cellular diversity of meningiomas using single cell transcriptomics and array-based DNA methylation profiling. Profiling of single cells identified transcriptional signatures within individual tumors that correspond to all three layers of the meninges, divergent transcriptional signatures of macrophages in WHO I vs II meningiomas, and depletion of infiltrating T-cell populations. These findings implicate fibroblasts and immune cells from multiple layers of the meninges in meningiomas, challenging the dogma of arachnoid cap cells as the sole cell type of origin, and suggest that meningiomas may exploit their role as the guardians of the blood-CSF barrier to evade detection and elimination by the systemic immune system. Materials and Methods Single cell RNA-sequencing Single cells were isolated from on 6 freshly resected meningiomas (n = 3 WHO 2016 grade I, n = 3 WHO 2016 grade II) using the Miltenyi Biotec brain tumor dissociation kit (Catalogue #130-095-942) and libraries generated using the 10x Genomics 3’ GEX kit v3.1 (Catalogue #: PN-1000268) prior to sequencing on a Illumina NovaSeq6000. Raw outputs were aligned to the human hg38 genome build and the GENCODE v32 reference transcriptome using 0x Genomics cellranger pipeline v6.0.2. Clinical molecular characterization was performed via MI Cancer Seek (Caris Biosciences) or UCSF500 (Supplementary Table 1)[ 22 ]. DNA methylation array profiling DNA was isolated from fresh frozen tumor using the Qiagen Allprep kit (Catalog #: 80204) followed by bisulfite conversion using the Zymo EZ-DNA Methylation Kit (Catalog #: D5002 and D5004) then analyzed the Illumina Infinium® Methylation EPIC BeadChip (Catalogue #: WG-317-1003) on an Illumina Infinium Microarray platform. Single cell RNA-seq analysis Data from the 6 new samples (GSE288349) above were combined with publicly available single cell RNA-seq data from 2 dura samples from 2 patients and 6 meningiomas including 2 meningioma-brain interface samples (GSE183655)[ 7 ]. QC, cell cycling scoring, and normalization were performed in Seurat (v4.3.0) with SCTransform with v2 regularization[ 23 ]. After filtering for low quality cells as defined by a percent.mt, nCount_RNA, nFeature_RNA, or percent.mt outside of 1.5x the log-normalized sample mean, integration across samples was performed with Harmony (v1.0.3) prior to clustering in Seurat. [ 24 ]. CONICSmat (v0.0.0.1) was utilized to calculate the posterior probability density (l) of all autosomes[ 25 ]. Values for l were log scaled across all cells and summed to identify the Zsum value for each cell. K-means clustering was performed on the scaled posterior probability matrix to identify CNV clusters. Cell type assignment was performed based on canonical markers. Given limited data on human fetal meningeal cell types, meningeal clusters were mapped to E14 Col1a1 + mouse meningeal fibroblasts (GSE150219) using anchor-based mapping with Seurat and babelgene (v22.9)[ 13 , 23 , 26 ]. PTPRC+ immune populations were mapped to a public reference of peripheral blood mononuclear cells annotated by gene expression and surface antigen expression[ 27 ]. Differences in cell type composition between samples were investigated by calculating the Cell Type Diversity Statistic and Gene set enrichment analysis was performed using the clusterProfiler (v4.14.4) with reduction of gene ontology terms by term similarity using rrvgo (v1.18.0)[ 28 – 30 ]. Communication probabilities for receptor-ligand interactions between cell types were computed with CellChat (v1.6.0)[ 31 ]. Analysis of variance was performed to identify pathways with significantly different communication probabilities between groups of interest followed by a Benjamini-Hochberg correction. A corrected p-value < 0.05 was considered significant. DNA methylation array-based classification IDAT files from Illumina DNA methylation array analysis of 20 unpublished meningiomas (GSE288351) and 31 previously published meningiomas and dura samples from our laboratory (GSE178139) were combined with an additional 789 meningiomas (GSE83933, GSE200321, GSE168726, GSE183647) for a total of 12 dura samples and 840 meningiomas [ 7 , 10 , 32 – 35 ]. Raw IDATs were imported into minfi (v1.52.1) and normalized using preprocessIllumina prior to DNA methylation-based classification using the DKFZ classifier v12.6 [ 6 , 36 – 39 ]. DNA methylation array-based immune deconvolution Immune cell composition deconvolution was performed on IDAT files using FlowSorted.Blood.EPIC (v2.0.0)[ 36 , 40 ]. Analysis of variance with Tukey’s post-hoc testing was performed with p < 0.05 considered significant. To account for updates to the World Health Organization classification system over the course of the collection of the relevant tumor samples, samples were binned as WHO 1/I, WHO 2/II, WHO III/3. Immune cell deconvolution was performed samples that classified as a meningioma with a prediction score > 0.8[ 6 ]. Due to the limited number of shared probes between 450K and EPIC arrays, principal component analysis was performed using beta values from the 770 samples analyzed with EPIC arrays using factoextra (v1.0.7). Singular value decomposition was performed on the 770 samples using ChAMP (v2.36.0). Immunostaining of meningiomas Immunostaining was performed on paraffin-embedded sections with the following antibodies: mouse IgG anti-SPI1/PU.1 (Thermo #14-9819-82, 1:1000), rabbit IgG anti-c-Myb (Abcam #ab117635, 1:3200), rabbit IgG anti-Olig1 (Abcam #:ab191694, 1:100), and mouse IgG anti-CNPase (Abcam #ab6319, 1:200) with images were acquired on a BZ-9000 microscope (Keyence). Statistical Analysis Details of analysis of single cell gene expression data are detailed above. All other statistical analysis was conducted using the base R stats package. Categorical variables were analyzed using Chi-squared tests and continuous variables using an analysis of variance (ANOVA) with appropriate post-hoc analysis to test for multiple comparisons. A corrected p-value of < 0.05 was considered significant. Results Meningiomas have diminished cellular diversity To explore the cellular diversity of meningiomas, profiling of single cells was performed on a combined total of 14 meningiomas from 12 donors and 2 dura samples from 2 donors. Of the 6 newly reported meningiomas, 3 were WHO grade I (n = 2 NF2 wildtype and n = 1 NF2 mutant) and 3 were WHO grade II (n = 3 NF2 mutant, Supplementary Excel Table 1). After quality control, 126,626 cells were included in downstream analysis. Principal component analysis revealed 15 clusters consisting of meningeal, myeloid, lymphocyte, pericyte, and endothelial cells (Fig. 1A-C, Supplementary Fig. 1A-B, Supplementary Excel Table 2). Review of differentially expressed markers identified meningeal fibroblasts ( FOXC1 , OGN , DCN , SOX11 ), lymphocytes ( CD3D ), myeloid cells ( HLA - DRA ), pericytes ( PDGFRB ), and endothelial cells ( PECAM1 ). Immune cells accounted for 35.2 ± 29.4% of cells in each sample (range 5.8–89.4%). Although both dura and meningiomas contained cell types from each major cluster, dura samples exhibited a more uniform distribution of meningeal and immune populations, while meningiomas were skewed towards expansion of either the meningeal or myeloid compartments (cell type diversity statistic: dura − 0.096±0.018 vs. meningioma − 0.557±0.18, p = 2.7x10 − 16 , Supplementary Fig. 1C). Tumor cells were distinguished from normal cells based on the sum of scaled posterior probability densities[ 25 ]. Mean Zsum scores were significantly different across all cell types (ANOVA, p = 2.7x10 − 16 , Tukey post-hoc p 25 were designated tumor cells. K means clustering identified k = 4 clusters corresponding to cells with balanced, low, intermediate, and high copy number variant (CNV) burden (Fig. 1D, Supplementary Fig. 1E). While the balanced CNV cluster was predominantly derived from endothelial cells, pericytes, and immune cells, a population of stromal meningeal fibroblasts with a balanced genome was noted (Supplementary Fig. 1F). Although the high CNV cluster was primarily derived from a single meningioma (M12, M12-BTI), cells with a high CNV burden were detected in all meningiomas and both dura samples (Supplementary Fig. 1F). Individual meningiomas adopt meningeal layer-specific transcriptional signatures To explore the transcriptional diversity of fibroblasts in dura and meningiomas, meningeal fibroblasts were subclustered. Subclusters were almost entirely driven by sample of origin rather than CNV cluster (Fig. 2A-C, Supplementary Fig. 2A-C). Given the high likelihood that meningioma fibroblasts acquire fetal-like signatures, the resulting 15 subclusters were mapped to a dataset of E14 mouse meningeal fibroblasts[ 13 ]. Fibroblasts from individual meningiomas predominately expressed transcriptional signatures that mapped to either dura, arachnoid, or pia layers of the E14 embryonic mouse with one cell type, Cdh1 + dura, dominating for most meningiomas (Fig. 2D, Supplementary Fig. 2D-E). Meningeal fibroblasts from normal dura mapped to several clusters and included cells with signatures of all layers inclusive of dura, arachnoid, and pia progenitors. Dura and arachnoid-like populations expressed the meningeal identity factor FOXC1 , PTGDS , and retinoic acid binding proteins CRABP1/2 . Proliferative and pia-like cell populations expressed neural crest markers ( SOX4 , SOX11 ), collagens ( COL4A1 , COL4A2 , COL5A1 ), and secreted cell signaling genes ( WNT5A , INHBA , CXCL14 , SPP1 ) (Supplemental Fig. 2E). Although several genes were identified in nearly all clusters, top genes and biologic processes were highly variable between clusters (Fig. 2E-F, Supplementary Excel Table 3). Top biologic processes included housekeeping and RNA-related functions and developmental processes related to cell morphogenesis and neuron differentiation. Variable infiltration of myelinating populations Cluster 13 expressed transcripts associated with myelination ( CNP , MBP ) including markers of central nervous system oligodendrocytes ( OLIG2 , SOX10 ) and peripheral nervous system Schwann cells ( S100B , NGFR ) without expression of astrocyte markers ( AQP4 , ALDH1L1 ) (Fig. 3A). Although the samples with brain invasion (M11, M12) were the primary contributors to this cluster, myelinating cells were identified in both dura samples and 7/12 meningiomas. As Olig2 is a marker of oligodendrocytes, astrocytes, and oligodendrocyte progenitors, tissue from 9 meningiomas (WHO grade I: n = 3, WHO grade II: n = 3, WHO grade III: n = 3) and 1 breast cancer sample were stained for the oligodendrocyte specific transcription factor OLIG1 and the mature oligodendrocyte marker 2',3'-Cyclic Nucleotide 3' phosphodiesterase (CNP) (Fig. 3B, Supplementary Fig. 3). While OLIG1 + was absent from the breast cancer sample, 3/10 meningiomas exhibited variable infiltration of Olig1 + cells. A subset of meningiomas were noted to express CNP more broadly in agreement with the observed expression of the CNP transcript in multiple clusters of meningeal fibroblasts. Meningiomas lack immune cell diversity. To explore the immune microenvironment, PTPRC+ immune clusters were sub-clustered identifying lymphoid and myeloid populations in all samples (Fig. 4A-C). The lymphocyte to myeloid ratio was significantly reduced in meningioma relative to dura (2.19 vs. 0.32, p = 5.8x10 − 8 , Fig. 4D). Meningiomas exhibited skewed cell type proportions with expansion of the myeloid cell compartment (cell type diversity statistic: dura − 0.40±0.06 vs. meningioma − 0.69±0.10, p = 0.042, Fig. 4E). Though limited by sample size, there were no significant differences in cellular diversity between WHO I and WHO II meningiomas (cell type diversity statistic: WHO I -0.64±0.06 vs. WHO II -0.70±0.10, p = 0.37, Fig. 4F). Effector Memory T cells Infiltrate Meningiomas To determine the influence of grade and NF2 mutation status on infiltrating lymphocytes, CD3D + T-cell from the 6 molecularly defined meningiomas were subclustered and mapped to a public reference dataset of peripheral blood mononuclear cells (Fig. 5A) [ 27 ]. As reported elsewhere, clustering of T-cell populations by gene expression alone yielded significant mixing of CD4 + and CD8 + T-cells with clusters driven by expression of immune activation ( GZMK , GZMB , PRF1 ). (Fig. 4B-C, Supplementary Fig. 4A-B). While a small population of naïve T-cells expressing CCR7 and IL7R was identified, the majority of T-cells expressed the tissue resident marker CD69 [ 41 ]. The first two principal components were driven by gradients of immune checkpoint receptors ( PDCD1 ) versus makers of cytotoxicity ( PRF1 ) (Fig. 5c, Supplemental Fig. 4B). The use of a more granular definition of peripheral blood cells for anchor-based mapping classified a large proportion of cells as CD8 + tissue effector memory cells with this cell type identified in all samples (Fig. 5D-F). Aside from a small population of CD8+ / CCL4 + T-cells from a WHO grade I, NF2 mutated meningioma, all meningiomas contained a mixture of naïve, exhausted, and cytotoxic T-cell populations (Fig. 5G-H) [ 27 , 42 – 45 ]. Expanded Yolk-sack Derived Border Macrophages in Meningiomas To explore the influence of grade and NF2 status on macrophages in meningiomas, HLA-DRA+ clusters from the 6 molecularly profiled meningiomas were subclustered (Fig. 6A). Clusters were strongly associated with WHO grade and sample of origin, but not NF2 status (Fig. 6B, Supplementary Fig. C). Macrophages were strongly positive for the transcription factor SPI1 (PU.1) which identifies yolk-sac derived tissue resident macrophages and lacked expression of the transcript for the MYB transcription factor which identifies bone marrow-derived macrophage populations. Macrophages expressed a signature corresponding to dural border associated macrophages ( CD163 , CSF1R , MRC1 ) rather than microglia ( SALL1 , TMEM119 , P2RY12 ; Fig. 6C, Supplementary Fig. 4D). While macrophages from WHO I meningiomas were LYVE1 + consistent with the population of border macrophages previously noted to regulate CSF dynamics near dural lymphatics, macrophages from WHO II meningiomas expressed prostaglandin D synthase ( PTGDS ) and SPP1 which is associated with a suppressive tumor-associated macrophage phenotype [ 46 , 47 ]. WHO grade I macrophages additionally expressed the leptin receptor ( LEPR ) suggesting they may be metabolically distinct[ 48 , 49 ]. Macrophages from WHO I meningiomas strongly expressed genes associated with signaling, differentiation, and vascular development while macrophages from WHO II meningiomas were associated with cytokines and the innate immune response (Fig. 6D-E). While immunostaining of a breast cancer sample identified infiltrating MYB+ myeloid cells, MYB staining in meningiomas was rare outside of vascular structures. In contrast, yolk-sac derived PU.1+ ( SPI1 ) infiltrates were noted throughout both tumors (Fig. 6F, Supplementary Fig. 5, Supplementary Excel Table 4–5). Meningeal fibroblasts modulate immune function A net centrality plot of the net input and output communication probabilities for each cluster reveals inferred significant communication between meningeal fibroblasts and immune populations. Meningeal fibroblasts played a dominant role in both outgoing and incoming signaling (Fig. 7A). Top pathways in dura relative to meningiomas included the lymphocyte adhesion molecule 1 pathway (SELL), the tumor necrosis factor alpha (TNF) involved in polarizing macrophages to an M1-like phenotype, and the ADGRE5/CD97 pathway while top pathways in meningiomas relative to dura included the complement pathway, cell adhesion pathways (CDH, JAM, CLDN, THY1, SPP1), growth and differentiation signaling pathways such the bone morphogenic protein (BMP) and non-canonical wingless (ncWNT) pathways, and pathways with immunosuppressive functions (CD39, TIGIT) (Fig. 7B, Supplementary Excel Table 6). Relative to WHO 1/I meningiomas, WHO 2/II meningiomas exhibited high expression of growth factor pathways such as the midkine (MK), fibroblast growth factor (FGF), wingless (WNT) and bone morphogenic protein (BMP) pathways and cell adhesion pathways including (CDH, CADM, VCAM, CDH1) (Fig. 7C, Supplementary Excel Table 7). The top signaling pathways identified in all groups included cell adhesion (COLLAGEN, FN1, LAMININ), immune modulatory (MHCI, MIF, CD99), and growth (MK, PTN) pathways reflecting the functional role of the meninges as the guardians of the CSF-blood barrier and an immune interface between the brain (Fig. 6D-E, Supplementary Excel Table 8–11). In meningeal fibroblast populations of both dura and meningiomas, the net outgoing communication probability of fibroblasts exceeded that of immune populations indicative of an active regulatory role rather than an inert structural role (Fig. 7F). Summed net incoming communication probabilities indicate a receiver role for lymphocyte populations in both normal meninges and meningiomas while myeloid populations in meningiomas exert a more dominant outgoing role in cell-cell communications. Immune composition influences meningioma methylation classes derived from bulk profiling of tumor Existing molecular classification schemes for meningiomas are derived from bulk sequencing data, however, immune infiltrates account for an average of 1/3 of cells. To determine whether prognostically significant DNA methylation signatures are associated with characteristic immune infiltration patterns in a large sample of tumors, DNA methylation array data from 12 dura and 840 meningiomas were pooled (n = 505 WHO grade 1/I, n = 268 WHO grade 2/II, and n = 67 WHO grade 3/III, Supplementary Excel Table 12). Of tumors histologically classified as meningiomas at multiple experienced tertiary medical centers, the highest predicted methylation class assigned by DNA-methylation based classification was one of 7 meningioma classes for 810/840 (96.4%). Only 521/840 (62%) of tumors classified as meningiomas met a stringent predicted confidence cutoff of > 0.9 (Fig. 8A). WHO Grade 2/II and 3/III meningiomas were significantly less likely to be assigned to a meningioma methylation class than WHO Grade 1/I meningiomas (WHO 1/I: 495/505 (98.0%) vs. WHO 2/II & 3/III: 315/335 (94.0%), χ 2 = 9.8, df = 2, p = 0.002, Fig. 8B). Overall, 20/30 (66.7%) of meningiomas that were assigned to non-meningioma methylation classes were WHO 2/II & 3/III. The most frequently identified non-meningioma methylation class was solitary fibrous tumor (n = 10/31) (Supplementary Excel Table 11). Clear cell meningiomas remain the exception to this, perhaps unsurprisingly given their association with mutations in epigenetic machinery and highly aggressive behavior relative to other meningiomas. The fraction of CD4 + T-cells, CD8 + T-cells, B-cells, NK cells in each of the 840 meningiomas and 12 dura samples was estimated using IDOL (Supplementary Fig. 6A-F). Overall, estimated CD4 + T-cell fractions were significantly higher in tumors of any WHO grade than dura while fractions of NK cells were lower. BEN_1 meningiomas, characterized by chromosome 22q deletion and a benign course, exhibited a unique immune profile with low CD4+, B-cell, NK, and neutrophil fractions and an elevated monocytic fraction. Meningiomas assigned to the highly malignant clear cell meningioma class characterized by SMARCE1 mutations (MNG, CC), exhibited high fractions of CD4 + T-cells, B cells, NK cells and neutrophils with low fractions of monocytic-like cells. Although a substantial fraction of meningiomas, particularly grade 2/3 tumors, exhibited a prediction score < 90%, the predicted methylation class was by far the strongest contributor to the first 20 principal components followed by the estimated fractions of B-cells, monocytes, natural killer cells, and CD4T cells, reaffirming the utility of methylation-based classification. Singular value decomposition indicated that the estimated fraction of all immune populations except for neutrophils was a greater contributor to overall variability in the dataset than the histologic grade (Fig. 8C-D). Discussion The designation of meningiomas as a surgical disease predates the molecular era by generations and has long been enshrined in the Simpson grade which prioritizes gross total resection with margins whenever possible due to prevent late recurrence [ 50 , 51 ]. Our observation that all meningiomas and the adjacent grossly normal dura harbor a small population of cells with a high CNV burden reinforces the longstanding principles of maximal safe resection to remove cells that drive recurrence. Cap cells of the arachnoid villi have been presumed the cell of origin for meningiomas since the time of Cushing; however, much of the evidence for this conclusion relies on antiquated immunohistochemical and electron microscopy studies[ 52 – 54 ]. More recent murine studies using the PTGDS-Cre mouse to drive NF2 deletion have identified temporal, regional, and meningeal layer-specific differences in susceptibility to meningioma formation[ 55 ]. While immune populations are transcriptionally similar across multiple meningiomas, the transcriptional signatures and predominant biologic processes of meningeal fibroblasts vary widely across samples and may may arise from transcriptionally distinct cells of origin. Although this would be a departure from current teaching regarding meningiomas, the biologic behavior of other CNS tumors has long been attributed to distinct cell types of origin[ 56 ]. Furthermore, this model corroborates years of neurosurgical observations regarding the behavior of individual tumors. While some meningiomas are confined to the outer layer of dura and replicate the functions of infant dura by stimulating hyperostosis of the overlying bone, others are easily separated from the outer layer of dura and invade brain parenchyma. Although brain invasion is a well-established marker of aggressive meningiomas, spontaneous murine models that generate meningiomas via inactivation of NF2 in dura and arachnoid develop tumors in both dura and arachnoid without the brain invasion seen with models capable of targeting all three meningeal layers[ 57 – 59 ]. As the PTGDS-Cre model selectively targets the dura and arachnoid layers, there remains a possibility that more aggressive meningiomas either arise from the pia or adopt pia-like behavior that is capable of invasion. Notably, a subset of meningiomas studied here, including one meningioma with brain invasion, exhibited an increased proportion of cells with proliferative and pia-like signatures and lower expression of meningeal fibroblast markers. Notably, a cluster of cells expressed markers of myelinating cells. While this cluster was predominantly derived from two brain-invasive samples, more than half the samples contributed cells to this cluster. It remains unclear whether this population represents sampling of cortical oligodendrocytes at the site of invasion, generation of Schwann cells from CNS oligodendrocytes, infiltration of tumor by injury-responsive oligodendrocytes or whether a subset of invasive meningiomas with neural crest-like features retain the capacity to generate Schwann cells. During normal development, glial progenitor populations migrate radially from the subventricular zone along radial glial processes that terminate at the pial surface. The observation that myelinating populations infiltrate meningiomas raises the intriguing possibility that brain invasion involves a reactivation of developmental interactions between the pia and the underlying cortex. Given reports that a subset of meningiomas invade brain while otherwise behaving in a benign fashion, further study is warranted to investigate whether a subset of meningiomas have pial-like features that predispose to brain invasion without other high-risk molecular features[ 60 ]. Our observation that meningeal fibroblasts exert a dominant signaling influence on the immune populations of the meninges in dura and tumors is in keeping with the modern school of thought that the meninges are a robust immune microenvironment with layer-specific immune compartments rather than an inert structural membrane [ 13 , 61 , 62 ]. The observation that meningioma-associated macrophages represent a local response orchestrated by PU.1 + yolk-sac derived border macrophages rather than systemic response characterized by infiltrating MYB+ macrophages indicate that meningiomas represent a hypertrophic blood brain barrier with minimal systemic immune response. Unexpectedly, macrophages in WHO grade I tumors had higher expression of the lymphatic marker LYVE1 and expressed the leptin receptor which has been associated with metabolic shifts and alterations in the innate immune response to bacterial infections[ 48 , 49 ]. In contrast, macrophages from WHO II meningiomas expressed PTGDS , a meninges secreted enzyme which regulates sleep cycles, and SPP1 , a classic marker for tumor-associated macrophages[ 63 , 64 ]. These transcriptional signatures may represent recently identified border macrophage subtypes that associate with arteries and regulate CSF dynamics ( LYVE1 hi ) versus antigen presentation in the dura [ 14 , 65 , 66 ]. Although these findings would benefit from replication with a larger subset of molecularly defined meningiomas, this observation raises the intriguing possibility that meningioma behavior is related to the subtype of border macrophage that orchestrates the immune response to the tumor. Although DNA-methylation analysis sought to uncover to immune signatures of previously described histologic and methylation classes, a disproportionate fraction of WHO grade 2/II and 3/III meningiomas matched to meningioma classes with low confidence or were assigned to non-meningioma methylation classes. As data were pooled from high volume brain tumor centers with expert neuropathologists, this finding underscores the molecular diversity of high grade meningiomas. The potential for previously unrecognized molecular subtypes of grade 2/3 meningiomas is significant for enrollment in and interpretation of clinical trial results. Additionally, while genomic sequencing studies are limited to the identification of genetic drivers, epigenetic signatures capture aggregate influences from both tumor cells and any infiltrating immune population, both of which may ultimately be found to influence patient outcomes. Together, these data support the continued adoption of molecular characterization as a pre-requisite for enrollment in clinical trials. Limitations of the study include the small number of samples pooled for single cell RNA-seq analysis, which is limited by cost, and the dearth of knowledge about the biology of the normal human meninges. Single cell profiling of large sample sizes of clinically annotated meningiomas that capture the full breadth of histologic and molecular subtypes will improve our understanding of the relationship between the 15 histologic subtypes and immune infiltrates contribute to patient outcomes. Current murine models of meningioma best model germline conditions that give rise to the rare pediatric meningiomas; however, meningiomas are overwhelmingly a disease of adults. Adult dura heals after primary closure during neurosurgical procedures indicating that stem-like progenitors persist in the adult meninges and may represent the cell of origin for adult meningiomas. Characterization of the progenitor populations that contribute to healing of dura after intradural procedures may provide further insight into the heterogeneity of meningioma fibroblasts and the potential cell of origin for different histologic subclasses of meningiomas. With wider application of technologies such as single cell RNA-sequencing, our understanding of the complex biology of the human meninges in health and disease can only deepen. Declarations Competing Interests: The authors have no conflicts of interests to disclose. Author Contributions: MAW, BAS, GZ were responsible for study conceptualization. MAW, GZ, JH, EARG, and SF developed the study. Software development was performed by MAW, DNB, and GS and formal analysis was performed by MAW, GS, and DNB. The remaining investigation including histology was performed by MAW, BAS, DNB, GS, NEG, AW, OA. Resources were provided by GZ, MAW, AI, and JRL. Data curation was performed by MAW, BAS, NG, TD, and GS. Figure generation for visualization was performed by MAW, JH. The original manuscript was drafted by MAW with input from all authors for further review and editing. Acknowledgements: Single cell RNA-sequencing and DNA methylation array profiling was performed by the University of Southern California Genomics Core. Data were presented in an oral format at the 2024 Congress of Neurological Surgeons Meeting. Data Availability Statement: Data have been deposited in the Gene Expression Omnibus as SuperSeries GSE288351. Code may be accessed at http://github.com/Wedemeyer-Lab/meningioma_cell_diversity . Please direct any requests to the corresponding author: [email protected] . References Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D et al . The 2021 WHO Classification of Tumors of the Central Nervous System: a summary. Neuro Oncol 2021; 23: 1231–1251. Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK et al . The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathol 2016; 131: 803–820. 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4","description":"","filename":"SupFig4immune.ai","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/f782999c09e4e022d33a443d.ai"},{"id":101442278,"identity":"e8abd013-69a4-4abb-ab5a-1a6b13b10672","added_by":"auto","created_at":"2026-01-29 17:22:58","extension":"ai","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":55695324,"visible":true,"origin":"","legend":"Supplementary Figure 2","description":"","filename":"SuppFig2meninges.ai","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/2b379100bef79e357102e5ea.ai"},{"id":101751388,"identity":"b95db0de-6b9c-4ac0-8025-d603a9fda67f","added_by":"auto","created_at":"2026-02-03 10:19:55","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":325375,"visible":true,"origin":"","legend":"Graphical abstract publication 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1","description":"","filename":"SuppFig1.ai","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/ce34b43e7eb027220422951b.ai"},{"id":101442282,"identity":"c93f3257-148f-4740-8c3d-91f389e6e050","added_by":"auto","created_at":"2026-01-29 17:23:00","extension":"ai","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":213063466,"visible":true,"origin":"","legend":"Supplementary Figure 3","description":"","filename":"SuppFig3Olig1CNP.ai","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/66c5dd2377b08d8d51c7c947.ai"},{"id":101442283,"identity":"a60e0be9-38be-4260-b937-e129eda6f1e6","added_by":"auto","created_at":"2026-01-29 17:23:00","extension":"ai","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":246842174,"visible":true,"origin":"","legend":"Supplementary Figure 5","description":"","filename":"SuppFig5ImmuneMYBPU1.ai","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/7694cb845d5f7e40074296c3.ai"},{"id":101751328,"identity":"06ebaaf9-de2b-4f3e-8629-7afcfbdab1a9","added_by":"auto","created_at":"2026-02-03 10:19:20","extension":"ai","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":2244909,"visible":true,"origin":"","legend":"Supplemental Figure 6","description":"","filename":"SuppFig6immunomethylome.ai","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/e6db014989a9d50ea2891fea.ai"},{"id":101442276,"identity":"b372b8d6-438a-450d-98c2-2381d4629298","added_by":"auto","created_at":"2026-01-29 17:22:58","extension":"ai","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":8005063,"visible":true,"origin":"","legend":"Supplemental Figure 4","description":"","filename":"Fig4Immune.ai","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/7aceb123ec16ee14c59065eb.ai"},{"id":101442286,"identity":"595c117e-69da-4414-b5e9-2a5f6436fcf0","added_by":"auto","created_at":"2026-01-29 17:23:05","extension":"ai","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":55688417,"visible":true,"origin":"","legend":"Supplemental Figure 2","description":"","filename":"SuppFig2meninges.ai","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/ba0ce0bbd2586abb70f256f3.ai"},{"id":101442285,"identity":"acc3cc00-e974-4196-bd29-891c086acb93","added_by":"auto","created_at":"2026-01-29 17:23:04","extension":"ai","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":218178034,"visible":true,"origin":"","legend":"Supplemental Figure 3","description":"","filename":"SuppFig3Olig1CNP.ai","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/6e78e754e592ff9c46acff5f.ai"},{"id":101442284,"identity":"ebc65556-4ff2-42e7-88ab-d30d286cdff1","added_by":"auto","created_at":"2026-01-29 17:23:01","extension":"ai","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":247186689,"visible":true,"origin":"","legend":"Supplemental Figure 5","description":"","filename":"SuppFig5ImmuneMYBPU1.ai","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/eff400663d5714ea0da2049e.ai"},{"id":101751389,"identity":"b15f6b55-0e2b-40c4-ba95-a7860a225422","added_by":"auto","created_at":"2026-02-03 10:19:55","extension":"ai","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":127833443,"visible":true,"origin":"","legend":"Supplemental Figure 1","description":"","filename":"SuppFig1.ai","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/a39a56571cfe3fc6fbc439a5.ai"},{"id":101442271,"identity":"90eada4f-35c2-4a70-a82b-b91e19f8c7ad","added_by":"auto","created_at":"2026-01-29 17:22:57","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":263474,"visible":true,"origin":"","legend":"Supplementary Figure 6","description":"","filename":"SuppFig6immunomethylome.png","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/a047a5abba5d7585f1f59ffb.png"},{"id":101751692,"identity":"e17ff212-44f0-47b9-9f19-6f0e3781c609","added_by":"auto","created_at":"2026-02-03 10:22:29","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":3534658,"visible":true,"origin":"","legend":"Supplementary Figure 3","description":"","filename":"SuppFig3Olig1CNP.png","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/9965dbbc3bac628d9407ce29.png"},{"id":101751205,"identity":"1582d456-d3d6-452f-b230-3ebe5bf5a4fb","added_by":"auto","created_at":"2026-02-03 10:18:15","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":590431,"visible":true,"origin":"","legend":"Supplementary Figure 2","description":"","filename":"SuppFig2meninges.png","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/1c48a0dcdd3c47f473d94530.png"},{"id":101442280,"identity":"23cd4b21-1cc3-4c5d-8c8b-cb012eb3f60e","added_by":"auto","created_at":"2026-01-29 17:22:59","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"supplement","size":4133626,"visible":true,"origin":"","legend":"Supplementary Figure 5","description":"","filename":"SuppFig5ImmuneMYBPU1.png","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/125fef70a76ea2d5d682df71.png"},{"id":101442277,"identity":"e4414796-dc86-47f9-835e-f5ad05f0c635","added_by":"auto","created_at":"2026-01-29 17:22:58","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"supplement","size":383465,"visible":true,"origin":"","legend":"Supplementary Figure 4","description":"","filename":"SupFig4immune.png","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/c602d60d2724c7effb8b655d.png"},{"id":101442274,"identity":"0a08f576-6cef-443d-8760-be7ce4077a3f","added_by":"auto","created_at":"2026-01-29 17:22:57","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"supplement","size":456670,"visible":true,"origin":"","legend":"Supplementary Figure 1","description":"","filename":"SuppFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-8612817/v1/8681927474f7bff4eda5e51d.png"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Multiomic Characterization of Meningiomas Informs Cell of Origin and Identifies Immune Dysregulation at the Blood-CSF Barrier","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMeningiomas account for more than 1/3 of all brain tumors and have long been presumed to originate from arachnoid cap cells[1]. Though the majority of meningiomas exhibit a benign clinical course, they may arise in surgically inaccessible locations, invade underlying neural elements, or cause disfiguring hyperostosis of the overlying cranium. Meningiomas present with highly variable consistency ranging from soft and necrotic to densely calcified lesions and exhibit remarkable histologic diversity with prior classification schemes recognizing 15 histologic subtypes[2, 3]. Despite identification of recurrent drivers mutations, current classification systems do not account for their highly variable consistency or clinical course.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Experience with aggressive behavior from histologically benign meningiomas inspired a search for prognostic molecular markers that identified recurrent mutations in SMO, AKT12, TRAF7, KLF4, and BAP1 that are mutually exclusive with classical NF2 alterations and lead to the incorporation of molecular markers in the WHO 2021 CNS classification for meningiomas [1, 4, 5]. Given limitations of histology for prognosis, the field has explored molecular classification schemes that variably incorporate genomic profiling, DNA methylation, and gene expression signatures[6-11]. Although guidelines do not yet recommend routine molecular testing of all meningiomas, the clinical conditions for which testing is recommended to inform treatment continue to expand[12].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;In parallel, the meninges are increasingly understood as a layered and compartmentalized lymphatic organ that regulates the development of the cortex and calvarium[13-17]. Single cell sequencing studies of the normal meninges have identified subtypes of meningeal fibroblasts with layer-specific roles in immune surveillance and at the blood CSF-barrier[13, 14, 18-20].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Although bulk molecular profiling can identify clinically predictive molecular subgroups, profiling of bulk samples cannot fully resolve the contribution of individual cell types [6-8, 10]. Probing of the meningioma using bulk technologies has identified a subtype with substantial immune infiltration and spatial profiling has identified spatial heterogeneity of driver mutations; however, less attention has been paid to the diversity of the meningeal fibroblasts themselves[8, 18, 21]. Considering the modern view of the meninges as a multilayered immune organ, we probed the cellular diversity of meningiomas using single cell transcriptomics and array-based DNA methylation profiling. Profiling of single cells identified transcriptional signatures within individual tumors that correspond to all three layers of the meninges, divergent transcriptional signatures of macrophages in WHO I vs II meningiomas, and depletion of infiltrating T-cell populations. These findings implicate fibroblasts and immune cells from multiple layers of the meninges in meningiomas, challenging the dogma of arachnoid cap cells as the sole cell type of origin, and suggest that meningiomas may exploit their role as the guardians of the blood-CSF barrier to evade detection and elimination by the systemic immune system.\u0026nbsp;\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eSingle cell RNA-sequencing\u003c/h2\u003e \u003cp\u003eSingle cells were isolated from on 6 freshly resected meningiomas (n\u0026thinsp;=\u0026thinsp;3 WHO 2016 grade I, n\u0026thinsp;=\u0026thinsp;3 WHO 2016 grade II) using the Miltenyi Biotec brain tumor dissociation kit (Catalogue #130-095-942) and libraries generated using the 10x Genomics 3\u0026rsquo; GEX kit v3.1 (Catalogue #: PN-1000268) prior to sequencing on a Illumina NovaSeq6000. Raw outputs were aligned to the human hg38 genome build and the GENCODE v32 reference transcriptome using 0x Genomics cellranger pipeline v6.0.2. Clinical molecular characterization was performed via MI Cancer Seek (Caris Biosciences) or UCSF500 (Supplementary Table\u0026nbsp;1)[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDNA methylation array profiling\u003c/h2\u003e \u003cp\u003eDNA was isolated from fresh frozen tumor using the Qiagen Allprep kit (Catalog #: 80204) followed by bisulfite conversion using the Zymo EZ-DNA Methylation Kit (Catalog #: D5002 and D5004) then analyzed the Illumina Infinium\u0026reg; Methylation EPIC BeadChip (Catalogue #: WG-317-1003) on an Illumina Infinium Microarray platform.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSingle cell RNA-seq analysis\u003c/h3\u003e\n\u003cp\u003eData from the 6 new samples (GSE288349) above were combined with publicly available single cell RNA-seq data from 2 dura samples from 2 patients and 6 meningiomas including 2 meningioma-brain interface samples (GSE183655)[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. QC, cell cycling scoring, and normalization were performed in Seurat (v4.3.0) with SCTransform with v2 regularization[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. After filtering for low quality cells as defined by a percent.mt, nCount_RNA, nFeature_RNA, or percent.mt outside of 1.5x the log-normalized sample mean, integration across samples was performed with Harmony (v1.0.3) prior to clustering in Seurat. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. CONICSmat (v0.0.0.1) was utilized to calculate the posterior probability density (l) of all autosomes[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Values for l were log scaled across all cells and summed to identify the Zsum value for each cell. K-means clustering was performed on the scaled posterior probability matrix to identify CNV clusters.\u003c/p\u003e \u003cp\u003eCell type assignment was performed based on canonical markers. Given limited data on human fetal meningeal cell types, meningeal clusters were mapped to E14 Col1a1\u0026thinsp;+\u0026thinsp;mouse meningeal fibroblasts (GSE150219) using anchor-based mapping with Seurat and babelgene (v22.9)[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. PTPRC+ immune populations were mapped to a public reference of peripheral blood mononuclear cells annotated by gene expression and surface antigen expression[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDifferences in cell type composition between samples were investigated by calculating the Cell Type Diversity Statistic and Gene set enrichment analysis was performed using the clusterProfiler (v4.14.4) with reduction of gene ontology terms by term similarity using rrvgo (v1.18.0)[\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCommunication probabilities for receptor-ligand interactions between cell types were computed with CellChat (v1.6.0)[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Analysis of variance was performed to identify pathways with significantly different communication probabilities between groups of interest followed by a Benjamini-Hochberg correction. A corrected p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant.\u003c/p\u003e\n\u003ch3\u003eDNA methylation array-based classification\u003c/h3\u003e\n\u003cp\u003eIDAT files from Illumina DNA methylation array analysis of 20 unpublished meningiomas (GSE288351) and 31 previously published meningiomas and dura samples from our laboratory (GSE178139) were combined with an additional 789 meningiomas (GSE83933, GSE200321, GSE168726, GSE183647) for a total of 12 dura samples and 840 meningiomas [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR33 CR34\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Raw IDATs were imported into minfi (v1.52.1) and normalized using preprocessIllumina prior to DNA methylation-based classification using the DKFZ classifier v12.6 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eDNA methylation array-based immune deconvolution\u003c/h3\u003e\n\u003cp\u003eImmune cell composition deconvolution was performed on IDAT files using FlowSorted.Blood.EPIC (v2.0.0)[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Analysis of variance with Tukey\u0026rsquo;s post-hoc testing was performed with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered significant. To account for updates to the World Health Organization classification system over the course of the collection of the relevant tumor samples, samples were binned as WHO 1/I, WHO 2/II, WHO III/3. Immune cell deconvolution was performed samples that classified as a meningioma with a prediction score\u0026thinsp;\u0026gt;\u0026thinsp;0.8[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDue to the limited number of shared probes between 450K and EPIC arrays, principal component analysis was performed using beta values from the 770 samples analyzed with EPIC arrays using factoextra (v1.0.7). Singular value decomposition was performed on the 770 samples using ChAMP (v2.36.0).\u003c/p\u003e\n\u003ch3\u003eImmunostaining of meningiomas\u003c/h3\u003e\n\u003cp\u003eImmunostaining was performed on paraffin-embedded sections with the following antibodies: mouse IgG anti-SPI1/PU.1 (Thermo #14-9819-82, 1:1000), rabbit IgG anti-c-Myb (Abcam #ab117635, 1:3200), rabbit IgG anti-Olig1 (Abcam #:ab191694, 1:100), and mouse IgG anti-CNPase (Abcam #ab6319, 1:200) with images were acquired on a BZ-9000 microscope (Keyence).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDetails of analysis of single cell gene expression data are detailed above. All other statistical analysis was conducted using the base R stats package. Categorical variables were analyzed using Chi-squared tests and continuous variables using an analysis of variance (ANOVA) with appropriate post-hoc analysis to test for multiple comparisons. A corrected p-value of \u0026lt;\u0026thinsp;0.05 was considered significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMeningiomas have diminished cellular diversity\u003c/h2\u003e \u003cp\u003eTo explore the cellular diversity of meningiomas, profiling of single cells was performed on a combined total of 14 meningiomas from 12 donors and 2 dura samples from 2 donors. Of the 6 newly reported meningiomas, 3 were WHO grade I (n\u0026thinsp;=\u0026thinsp;2 NF2 wildtype and n\u0026thinsp;=\u0026thinsp;1 NF2 mutant) and 3 were WHO grade II (n\u0026thinsp;=\u0026thinsp;3 NF2 mutant, Supplementary Excel Table\u0026nbsp;1). After quality control, 126,626 cells were included in downstream analysis. Principal component analysis revealed 15 clusters consisting of meningeal, myeloid, lymphocyte, pericyte, and endothelial cells (Fig.\u0026nbsp;1A-C, Supplementary Fig.\u0026nbsp;1A-B, Supplementary Excel Table\u0026nbsp;2). Review of differentially expressed markers identified meningeal fibroblasts (\u003cem\u003eFOXC1\u003c/em\u003e, \u003cem\u003eOGN\u003c/em\u003e, \u003cem\u003eDCN\u003c/em\u003e, \u003cem\u003eSOX11\u003c/em\u003e), lymphocytes ( \u003cem\u003eCD3D\u003c/em\u003e), myeloid cells (\u003cem\u003eHLA\u003c/em\u003e-\u003cem\u003eDRA\u003c/em\u003e), pericytes (\u003cem\u003ePDGFRB\u003c/em\u003e), and endothelial cells (\u003cem\u003ePECAM1\u003c/em\u003e). Immune cells accounted for 35.2 \u0026plusmn; 29.4% of cells in each sample (range 5.8\u0026ndash;89.4%). Although both dura and meningiomas contained cell types from each major cluster, dura samples exhibited a more uniform distribution of meningeal and immune populations, while meningiomas were skewed towards expansion of either the meningeal or myeloid compartments (cell type diversity statistic: dura\u0026thinsp;\u0026minus;\u0026thinsp;0.096\u0026plusmn;0.018 vs. meningioma\u0026thinsp;\u0026minus;\u0026thinsp;0.557\u0026plusmn;0.18, p\u0026thinsp;=\u0026thinsp;2.7x10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e, Supplementary Fig.\u0026nbsp;1C).\u003c/p\u003e \u003cp\u003eTumor cells were distinguished from normal cells based on the sum of scaled posterior probability densities[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Mean Zsum scores were significantly different across all cell types (ANOVA, p\u0026thinsp;=\u0026thinsp;2.7x10\u003csup\u003e\u0026minus;\u0026thinsp;16\u003c/sup\u003e, Tukey post-hoc p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all comparisons) with the greatest variability noted in meningeal fibroblasts, Supplementary Fig.\u0026nbsp;1D). Based on review of mean Zsum for each cell type, cells with a Zsum of \u0026gt;\u0026thinsp;25 were designated tumor cells. K means clustering identified k\u0026thinsp;=\u0026thinsp;4 clusters corresponding to cells with balanced, low, intermediate, and high copy number variant (CNV) burden (Fig.\u0026nbsp;1D, Supplementary Fig.\u0026nbsp;1E). While the balanced CNV cluster was predominantly derived from endothelial cells, pericytes, and immune cells, a population of stromal meningeal fibroblasts with a balanced genome was noted (Supplementary Fig.\u0026nbsp;1F). Although the high CNV cluster was primarily derived from a single meningioma (M12, M12-BTI), cells with a high CNV burden were detected in all meningiomas and both dura samples (Supplementary Fig.\u0026nbsp;1F).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eIndividual meningiomas adopt meningeal layer-specific transcriptional signatures\u003c/h2\u003e \u003cp\u003eTo explore the transcriptional diversity of fibroblasts in dura and meningiomas, meningeal fibroblasts were subclustered. Subclusters were almost entirely driven by sample of origin rather than CNV cluster (Fig.\u0026nbsp;2A-C, Supplementary Fig.\u0026nbsp;2A-C). Given the high likelihood that meningioma fibroblasts acquire fetal-like signatures, the resulting 15 subclusters were mapped to a dataset of E14 mouse meningeal fibroblasts[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Fibroblasts from individual meningiomas predominately expressed transcriptional signatures that mapped to either dura, arachnoid, or pia layers of the E14 embryonic mouse with one cell type, Cdh1\u0026thinsp;+\u0026thinsp;dura, dominating for most meningiomas (Fig.\u0026nbsp;2D, Supplementary Fig.\u0026nbsp;2D-E). Meningeal fibroblasts from normal dura mapped to several clusters and included cells with signatures of all layers inclusive of dura, arachnoid, and pia progenitors. Dura and arachnoid-like populations expressed the meningeal identity factor \u003cem\u003eFOXC1\u003c/em\u003e, \u003cem\u003ePTGDS\u003c/em\u003e, and retinoic acid binding proteins \u003cem\u003eCRABP1/2\u003c/em\u003e. Proliferative and pia-like cell populations expressed neural crest markers (\u003cem\u003eSOX4\u003c/em\u003e, \u003cem\u003eSOX11\u003c/em\u003e), collagens (\u003cem\u003eCOL4A1\u003c/em\u003e, \u003cem\u003eCOL4A2\u003c/em\u003e, \u003cem\u003eCOL5A1\u003c/em\u003e), and secreted cell signaling genes (\u003cem\u003eWNT5A\u003c/em\u003e, \u003cem\u003eINHBA\u003c/em\u003e, \u003cem\u003eCXCL14\u003c/em\u003e, \u003cem\u003eSPP1\u003c/em\u003e) (Supplemental Fig.\u0026nbsp;2E). Although several genes were identified in nearly all clusters, top genes and biologic processes were highly variable between clusters (Fig.\u0026nbsp;2E-F, Supplementary Excel Table\u0026nbsp;3). Top biologic processes included housekeeping and RNA-related functions and developmental processes related to cell morphogenesis and neuron differentiation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eVariable infiltration of myelinating populations\u003c/h2\u003e \u003cp\u003eCluster 13 expressed transcripts associated with myelination (\u003cem\u003eCNP\u003c/em\u003e, \u003cem\u003eMBP\u003c/em\u003e) including markers of central nervous system oligodendrocytes (\u003cem\u003eOLIG2\u003c/em\u003e, \u003cem\u003eSOX10\u003c/em\u003e) and peripheral nervous system Schwann cells (\u003cem\u003eS100B\u003c/em\u003e, \u003cem\u003eNGFR\u003c/em\u003e) without expression of astrocyte markers (\u003cem\u003eAQP4\u003c/em\u003e, \u003cem\u003eALDH1L1\u003c/em\u003e) (Fig.\u0026nbsp;3A). Although the samples with brain invasion (M11, M12) were the primary contributors to this cluster, myelinating cells were identified in both dura samples and 7/12 meningiomas. As Olig2 is a marker of oligodendrocytes, astrocytes, and oligodendrocyte progenitors, tissue from 9 meningiomas (WHO grade I: n\u0026thinsp;=\u0026thinsp;3, WHO grade II: n\u0026thinsp;=\u0026thinsp;3, WHO grade III: n\u0026thinsp;=\u0026thinsp;3) and 1 breast cancer sample were stained for the oligodendrocyte specific transcription factor OLIG1 and the mature oligodendrocyte marker 2',3'-Cyclic Nucleotide 3' phosphodiesterase (CNP) (Fig.\u0026nbsp;3B, Supplementary Fig.\u0026nbsp;3). While OLIG1\u0026thinsp;+\u0026thinsp;was absent from the breast cancer sample, 3/10 meningiomas exhibited variable infiltration of Olig1\u0026thinsp;+\u0026thinsp;cells. A subset of meningiomas were noted to express CNP more broadly in agreement with the observed expression of the CNP transcript in multiple clusters of meningeal fibroblasts.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMeningiomas lack immune cell diversity.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo explore the immune microenvironment, \u003cem\u003ePTPRC+\u003c/em\u003e immune clusters were sub-clustered identifying lymphoid and myeloid populations in all samples (Fig.\u0026nbsp;4A-C). The lymphocyte to myeloid ratio was significantly reduced in meningioma relative to dura (2.19 vs. 0.32, p\u0026thinsp;=\u0026thinsp;5.8x10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e, Fig.\u0026nbsp;4D). Meningiomas exhibited skewed cell type proportions with expansion of the myeloid cell compartment (cell type diversity statistic: dura\u0026thinsp;\u0026minus;\u0026thinsp;0.40\u0026plusmn;0.06 vs. meningioma\u0026thinsp;\u0026minus;\u0026thinsp;0.69\u0026plusmn;0.10, p\u0026thinsp;=\u0026thinsp;0.042, Fig.\u0026nbsp;4E). Though limited by sample size, there were no significant differences in cellular diversity between WHO I and WHO II meningiomas (cell type diversity statistic: WHO I -0.64\u0026plusmn;0.06 vs. WHO II -0.70\u0026plusmn;0.10, p\u0026thinsp;=\u0026thinsp;0.37, Fig.\u0026nbsp;4F).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEffector Memory T cells Infiltrate Meningiomas\u003c/h2\u003e \u003cp\u003eTo determine the influence of grade and NF2 mutation status on infiltrating lymphocytes, CD3D\u0026thinsp;+\u0026thinsp;T-cell from the 6 molecularly defined meningiomas were subclustered and mapped to a public reference dataset of peripheral blood mononuclear cells (Fig.\u0026nbsp;5A) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. As reported elsewhere, clustering of T-cell populations by gene expression alone yielded significant mixing of CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T-cells with clusters driven by expression of immune activation (\u003cem\u003eGZMK\u003c/em\u003e, \u003cem\u003eGZMB\u003c/em\u003e, \u003cem\u003ePRF1\u003c/em\u003e). (Fig.\u0026nbsp;4B-C, Supplementary Fig.\u0026nbsp;4A-B). While a small population of na\u0026iuml;ve T-cells expressing \u003cem\u003eCCR7\u003c/em\u003e and \u003cem\u003eIL7R\u003c/em\u003e was identified, the majority of T-cells expressed the tissue resident marker \u003cem\u003eCD69\u003c/em\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The first two principal components were driven by gradients of immune checkpoint receptors (\u003cem\u003ePDCD1\u003c/em\u003e) versus makers of cytotoxicity (\u003cem\u003ePRF1\u003c/em\u003e) (Fig.\u0026nbsp;5c, Supplemental Fig.\u0026nbsp;4B). The use of a more granular definition of peripheral blood cells for anchor-based mapping classified a large proportion of cells as CD8\u0026thinsp;+\u0026thinsp;tissue effector memory cells with this cell type identified in all samples (Fig.\u0026nbsp;5D-F). Aside from a small population of \u003cem\u003eCD8+\u003c/em\u003e/\u003cem\u003eCCL4\u0026thinsp;+\u003c/em\u003e\u0026thinsp;T-cells from a WHO grade I, NF2 mutated meningioma, all meningiomas contained a mixture of na\u0026iuml;ve, exhausted, and cytotoxic T-cell populations (Fig.\u0026nbsp;5G-H) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan additionalcitationids=\"CR43 CR44\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eExpanded Yolk-sack Derived Border Macrophages in Meningiomas\u003c/h2\u003e \u003cp\u003eTo explore the influence of grade and NF2 status on macrophages in meningiomas, HLA-DRA+ clusters from the 6 molecularly profiled meningiomas were subclustered (Fig.\u0026nbsp;6A). Clusters were strongly associated with WHO grade and sample of origin, but not NF2 status (Fig.\u0026nbsp;6B, Supplementary Fig. C). Macrophages were strongly positive for the transcription factor \u003cem\u003eSPI1\u003c/em\u003e (PU.1) which identifies yolk-sac derived tissue resident macrophages and lacked expression of the transcript for the \u003cem\u003eMYB\u003c/em\u003e transcription factor which identifies bone marrow-derived macrophage populations. Macrophages expressed a signature corresponding to dural border associated macrophages (\u003cem\u003eCD163\u003c/em\u003e, \u003cem\u003eCSF1R\u003c/em\u003e, \u003cem\u003eMRC1\u003c/em\u003e) rather than microglia (\u003cem\u003eSALL1\u003c/em\u003e, \u003cem\u003eTMEM119\u003c/em\u003e, \u003cem\u003eP2RY12\u003c/em\u003e; Fig.\u0026nbsp;6C, Supplementary Fig.\u0026nbsp;4D). While macrophages from WHO I meningiomas were \u003cem\u003eLYVE1\u003c/em\u003e\u0026thinsp;+\u0026thinsp;consistent with the population of border macrophages previously noted to regulate CSF dynamics near dural lymphatics, macrophages from WHO II meningiomas expressed prostaglandin D synthase (\u003cem\u003ePTGDS\u003c/em\u003e) and \u003cem\u003eSPP1\u003c/em\u003e which is associated with a suppressive tumor-associated macrophage phenotype [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. WHO grade I macrophages additionally expressed the leptin receptor (\u003cem\u003eLEPR\u003c/em\u003e) suggesting they may be metabolically distinct[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Macrophages from WHO I meningiomas strongly expressed genes associated with signaling, differentiation, and vascular development while macrophages from WHO II meningiomas were associated with cytokines and the innate immune response (Fig.\u0026nbsp;6D-E). While immunostaining of a breast cancer sample identified infiltrating MYB+ myeloid cells, MYB staining in meningiomas was rare outside of vascular structures. In contrast, yolk-sac derived PU.1+ (\u003cem\u003eSPI1\u003c/em\u003e) infiltrates were noted throughout both tumors (Fig.\u0026nbsp;6F, Supplementary Fig.\u0026nbsp;5, Supplementary Excel Table\u0026nbsp;4\u0026ndash;5).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMeningeal fibroblasts modulate immune function\u003c/h2\u003e \u003cp\u003eA net centrality plot of the net input and output communication probabilities for each cluster reveals inferred significant communication between meningeal fibroblasts and immune populations. Meningeal fibroblasts played a dominant role in both outgoing and incoming signaling (Fig.\u0026nbsp;7A). Top pathways in dura relative to meningiomas included the lymphocyte adhesion molecule 1 pathway (SELL), the tumor necrosis factor alpha (TNF) involved in polarizing macrophages to an M1-like phenotype, and the ADGRE5/CD97 pathway while top pathways in meningiomas relative to dura included the complement pathway, cell adhesion pathways (CDH, JAM, CLDN, THY1, SPP1), growth and differentiation signaling pathways such the bone morphogenic protein (BMP) and non-canonical wingless (ncWNT) pathways, and pathways with immunosuppressive functions (CD39, TIGIT) (Fig.\u0026nbsp;7B, Supplementary Excel Table\u0026nbsp;6). Relative to WHO 1/I meningiomas, WHO 2/II meningiomas exhibited high expression of growth factor pathways such as the midkine (MK), fibroblast growth factor (FGF), wingless (WNT) and bone morphogenic protein (BMP) pathways and cell adhesion pathways including (CDH, CADM, VCAM, CDH1) (Fig.\u0026nbsp;7C, Supplementary Excel Table\u0026nbsp;7).\u003c/p\u003e \u003cp\u003eThe top signaling pathways identified in all groups included cell adhesion (COLLAGEN, FN1, LAMININ), immune modulatory (MHCI, MIF, CD99), and growth (MK, PTN) pathways reflecting the functional role of the meninges as the guardians of the CSF-blood barrier and an immune interface between the brain (Fig.\u0026nbsp;6D-E, Supplementary Excel Table\u0026nbsp;8\u0026ndash;11). In meningeal fibroblast populations of both dura and meningiomas, the net outgoing communication probability of fibroblasts exceeded that of immune populations indicative of an active regulatory role rather than an inert structural role (Fig.\u0026nbsp;7F). Summed net incoming communication probabilities indicate a receiver role for lymphocyte populations in both normal meninges and meningiomas while myeloid populations in meningiomas exert a more dominant outgoing role in cell-cell communications.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eImmune composition influences meningioma methylation classes derived from bulk profiling of tumor\u003c/h2\u003e \u003cp\u003eExisting molecular classification schemes for meningiomas are derived from bulk sequencing data, however, immune infiltrates account for an average of 1/3 of cells. To determine whether prognostically significant DNA methylation signatures are associated with characteristic immune infiltration patterns in a large sample of tumors, DNA methylation array data from 12 dura and 840 meningiomas were pooled (n\u0026thinsp;=\u0026thinsp;505 WHO grade 1/I, n\u0026thinsp;=\u0026thinsp;268 WHO grade 2/II, and n\u0026thinsp;=\u0026thinsp;67 WHO grade 3/III, Supplementary Excel Table\u0026nbsp;12). Of tumors histologically classified as meningiomas at multiple experienced tertiary medical centers, the highest predicted methylation class assigned by DNA-methylation based classification was one of 7 meningioma classes for 810/840 (96.4%). Only 521/840 (62%) of tumors classified as meningiomas met a stringent predicted confidence cutoff of \u0026gt;\u0026thinsp;0.9 (Fig.\u0026nbsp;8A). WHO Grade 2/II and 3/III meningiomas were significantly less likely to be assigned to a meningioma methylation class than WHO Grade 1/I meningiomas (WHO 1/I: 495/505 (98.0%) vs. WHO 2/II \u0026amp; 3/III: 315/335 (94.0%), χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;9.8, df\u0026thinsp;=\u0026thinsp;2, p\u0026thinsp;=\u0026thinsp;0.002, Fig.\u0026nbsp;8B). Overall, 20/30 (66.7%) of meningiomas that were assigned to non-meningioma methylation classes were WHO 2/II \u0026amp; 3/III. The most frequently identified non-meningioma methylation class was solitary fibrous tumor (n\u0026thinsp;=\u0026thinsp;10/31) (Supplementary Excel Table\u0026nbsp;11). Clear cell meningiomas remain the exception to this, perhaps unsurprisingly given their association with mutations in epigenetic machinery and highly aggressive behavior relative to other meningiomas.\u003c/p\u003e \u003cp\u003eThe fraction of CD4\u0026thinsp;+\u0026thinsp;T-cells, CD8\u0026thinsp;+\u0026thinsp;T-cells, B-cells, NK cells in each of the 840 meningiomas and 12 dura samples was estimated using IDOL (Supplementary Fig.\u0026nbsp;6A-F). Overall, estimated CD4\u0026thinsp;+\u0026thinsp;T-cell fractions were significantly higher in tumors of any WHO grade than dura while fractions of NK cells were lower. BEN_1 meningiomas, characterized by chromosome 22q deletion and a benign course, exhibited a unique immune profile with low CD4+, B-cell, NK, and neutrophil fractions and an elevated monocytic fraction. Meningiomas assigned to the highly malignant clear cell meningioma class characterized by SMARCE1 mutations (MNG, CC), exhibited high fractions of CD4\u0026thinsp;+\u0026thinsp;T-cells, B cells, NK cells and neutrophils with low fractions of monocytic-like cells. Although a substantial fraction of meningiomas, particularly grade 2/3 tumors, exhibited a prediction score\u0026thinsp;\u0026lt;\u0026thinsp;90%, the predicted methylation class was by far the strongest contributor to the first 20 principal components followed by the estimated fractions of B-cells, monocytes, natural killer cells, and CD4T cells, reaffirming the utility of methylation-based classification. Singular value decomposition indicated that the estimated fraction of all immune populations except for neutrophils was a greater contributor to overall variability in the dataset than the histologic grade (Fig.\u0026nbsp;8C-D).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe designation of meningiomas as a surgical disease predates the molecular era by generations and has long been enshrined in the Simpson grade which prioritizes gross total resection with margins whenever possible due to prevent late recurrence [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Our observation that all meningiomas and the adjacent grossly normal dura harbor a small population of cells with a high CNV burden reinforces the longstanding principles of maximal safe resection to remove cells that drive recurrence.\u003c/p\u003e \u003cp\u003eCap cells of the arachnoid villi have been presumed the cell of origin for meningiomas since the time of Cushing; however, much of the evidence for this conclusion relies on antiquated immunohistochemical and electron microscopy studies[\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. More recent murine studies using the \u003cem\u003ePTGDS-Cre\u003c/em\u003e mouse to drive \u003cem\u003eNF2\u003c/em\u003e deletion have identified temporal, regional, and meningeal layer-specific differences in susceptibility to meningioma formation[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. While immune populations are transcriptionally similar across multiple meningiomas, the transcriptional signatures and predominant biologic processes of meningeal fibroblasts vary widely across samples and may may arise from transcriptionally distinct cells of origin. Although this would be a departure from current teaching regarding meningiomas, the biologic behavior of other CNS tumors has long been attributed to distinct cell types of origin[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Furthermore, this model corroborates years of neurosurgical observations regarding the behavior of individual tumors. While some meningiomas are confined to the outer layer of dura and replicate the functions of infant dura by stimulating hyperostosis of the overlying bone, others are easily separated from the outer layer of dura and invade brain parenchyma.\u003c/p\u003e \u003cp\u003eAlthough brain invasion is a well-established marker of aggressive meningiomas, spontaneous murine models that generate meningiomas via inactivation of \u003cem\u003eNF2\u003c/em\u003e in dura and arachnoid develop tumors in both dura and arachnoid without the brain invasion seen with models capable of targeting all three meningeal layers[\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. As the \u003cem\u003ePTGDS-Cre\u003c/em\u003e model selectively targets the dura and arachnoid layers, there remains a possibility that more aggressive meningiomas either arise from the pia or adopt pia-like behavior that is capable of invasion. Notably, a subset of meningiomas studied here, including one meningioma with brain invasion, exhibited an increased proportion of cells with proliferative and pia-like signatures and lower expression of meningeal fibroblast markers. Notably, a cluster of cells expressed markers of myelinating cells. While this cluster was predominantly derived from two brain-invasive samples, more than half the samples contributed cells to this cluster. It remains unclear whether this population represents sampling of cortical oligodendrocytes at the site of invasion, generation of Schwann cells from CNS oligodendrocytes, infiltration of tumor by injury-responsive oligodendrocytes or whether a subset of invasive meningiomas with neural crest-like features retain the capacity to generate Schwann cells. During normal development, glial progenitor populations migrate radially from the subventricular zone along radial glial processes that terminate at the pial surface. The observation that myelinating populations infiltrate meningiomas raises the intriguing possibility that brain invasion involves a reactivation of developmental interactions between the pia and the underlying cortex. Given reports that a subset of meningiomas invade brain while otherwise behaving in a benign fashion, further study is warranted to investigate whether a subset of meningiomas have pial-like features that predispose to brain invasion without other high-risk molecular features[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur observation that meningeal fibroblasts exert a dominant signaling influence on the immune populations of the meninges in dura and tumors is in keeping with the modern school of thought that the meninges are a robust immune microenvironment with layer-specific immune compartments rather than an inert structural membrane [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. The observation that meningioma-associated macrophages represent a local response orchestrated by PU.1\u0026thinsp;+\u0026thinsp;yolk-sac derived border macrophages rather than systemic response characterized by infiltrating MYB+ macrophages indicate that meningiomas represent a hypertrophic blood brain barrier with minimal systemic immune response. Unexpectedly, macrophages in WHO grade I tumors had higher expression of the lymphatic marker \u003cem\u003eLYVE1\u003c/em\u003e and expressed the leptin receptor which has been associated with metabolic shifts and alterations in the innate immune response to bacterial infections[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In contrast, macrophages from WHO II meningiomas expressed \u003cem\u003ePTGDS\u003c/em\u003e, a meninges secreted enzyme which regulates sleep cycles, and \u003cem\u003eSPP1\u003c/em\u003e, a classic marker for tumor-associated macrophages[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. These transcriptional signatures may represent recently identified border macrophage subtypes that associate with arteries and regulate CSF dynamics (\u003cem\u003eLYVE1\u003c/em\u003e\u003csup\u003e\u003cem\u003ehi\u003c/em\u003e\u003c/sup\u003e) versus antigen presentation in the dura [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Although these findings would benefit from replication with a larger subset of molecularly defined meningiomas, this observation raises the intriguing possibility that meningioma behavior is related to the subtype of border macrophage that orchestrates the immune response to the tumor.\u003c/p\u003e \u003cp\u003eAlthough DNA-methylation analysis sought to uncover to immune signatures of previously described histologic and methylation classes, a disproportionate fraction of WHO grade 2/II and 3/III meningiomas matched to meningioma classes with low confidence or were assigned to non-meningioma methylation classes. As data were pooled from high volume brain tumor centers with expert neuropathologists, this finding underscores the molecular diversity of high grade meningiomas. The potential for previously unrecognized molecular subtypes of grade 2/3 meningiomas is significant for enrollment in and interpretation of clinical trial results. Additionally, while genomic sequencing studies are limited to the identification of genetic drivers, epigenetic signatures capture aggregate influences from both tumor cells and any infiltrating immune population, both of which may ultimately be found to influence patient outcomes. Together, these data support the continued adoption of molecular characterization as a pre-requisite for enrollment in clinical trials.\u003c/p\u003e \u003cp\u003eLimitations of the study include the small number of samples pooled for single cell RNA-seq analysis, which is limited by cost, and the dearth of knowledge about the biology of the normal human meninges. Single cell profiling of large sample sizes of clinically annotated meningiomas that capture the full breadth of histologic and molecular subtypes will improve our understanding of the relationship between the 15 histologic subtypes and immune infiltrates contribute to patient outcomes. Current murine models of meningioma best model germline conditions that give rise to the rare pediatric meningiomas; however, meningiomas are overwhelmingly a disease of adults. Adult dura heals after primary closure during neurosurgical procedures indicating that stem-like progenitors persist in the adult meninges and may represent the cell of origin for adult meningiomas. Characterization of the progenitor populations that contribute to healing of dura after intradural procedures may provide further insight into the heterogeneity of meningioma fibroblasts and the potential cell of origin for different histologic subclasses of meningiomas. With wider application of technologies such as single cell RNA-sequencing, our understanding of the complex biology of the human meninges in health and disease can only deepen.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting Interests:\u003c/h2\u003e \u003cp\u003eThe authors have no conflicts of interests to disclose.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contributions:\u003c/h2\u003e \u003cp\u003eMAW, BAS, GZ were responsible for study conceptualization. MAW, GZ, JH, EARG, and SF developed the study. Software development was performed by MAW, DNB, and GS and formal analysis was performed by MAW, GS, and DNB. The remaining investigation including histology was performed by MAW, BAS, DNB, GS, NEG, AW, OA. Resources were provided by GZ, MAW, AI, and JRL. Data curation was performed by MAW, BAS, NG, TD, and GS. Figure generation for visualization was performed by MAW, JH. The original manuscript was drafted by MAW with input from all authors for further review and editing.\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e \u003cp\u003eSingle cell RNA-sequencing and DNA methylation array profiling was performed by the University of Southern California Genomics Core.\u003c/p\u003e \u003cp\u003eData were presented in an oral format at the 2024 Congress of Neurological Surgeons Meeting.\u003c/p\u003e\u003ch2\u003eData Availability Statement:\u003c/h2\u003e \u003cp\u003eData have been deposited in the Gene Expression Omnibus as SuperSeries GSE288351. Code may be accessed at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://github.com/Wedemeyer-Lab/meningioma_cell_diversity\u003c/span\u003e\u003cspan address=\"http://github.com/Wedemeyer-Lab/meningioma_cell_diversity\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Please direct any requests to the corresponding author: [email protected].\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLouis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D \u003cem\u003eet al\u003c/em\u003e. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary. \u003cem\u003eNeuro Oncol\u003c/em\u003e 2021; 23: 1231\u0026ndash;1251.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLouis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK \u003cem\u003eet al\u003c/em\u003e. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. \u003cem\u003eActa Neuropathol\u003c/em\u003e 2016; 131: 803\u0026ndash;820.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah I, Chung RS, Liu K, Cote DJ, Briggs RG, Guerra G \u003cem\u003eet al\u003c/em\u003e. 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Parenchymal border macrophages regulate the flow dynamics of the cerebrospinal fluid. \u003cem\u003eNature\u003c/em\u003e 2022; 611: 585\u0026ndash;593.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"oncogene","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"onc","sideBox":"Learn more about [Oncogene](http://www.nature.com/onc/)","snPcode":"41388","submissionUrl":"https://mts-onc.nature.com/cgi-bin/main.plex","title":"Oncogene","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8612817/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8612817/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMeningiomas represent 1/3 of adult brain tumors and arise from the meninges, a layered immune organ that forms the blood CSF-barrier. While molecular characterization has revolutionized our capacity to distinguish benign from aggressive tumors, the developmental relationship between meningiomas and the specialized layers of the meninges remains underexplored. Using single cell transcriptomics, we identify layer-specific signatures in individual meningiomas raising the intriguing possibility that the histologic and clinical diversity of meningiomas is influenced by cell of origin. Invasive tumors were transcriptionally similar to pia and exhibited an infiltrating subpopulation of myelinating cells implicating a reactivation of developmental mechanisms in the pathogenesis of invasion. Immune cells constituted ~ 1/3 of cells in a tumor, most of which were \u003cem\u003eSPI1\u003c/em\u003e + tissue resident border macrophages while MYB+ bone-marrow derived macrophages were lacking. WHO I meningiomas were infiltrated with \u003cem\u003eLYVE1\u003c/em\u003e + border macrophages while macrophages in grade II meningiomas expressed \u003cem\u003ePTGDS\u003c/em\u003e. Estimation of immune cell composition in meningiomas profiled by DNA methylation arrays identified characteristic immune signatures of prognostically significant molecular categories of meningiomas and a previously unrecognized level of epigenetic diversity in grade 2/3 meningiomas. Meningiomas may arise from multiple layers of the meninges rather than just arachnoid cap cells with implications for clinical behavior.\u003c/p\u003e","manuscriptTitle":"Multiomic Characterization of Meningiomas Informs Cell of Origin and Identifies Immune Dysregulation at the Blood-CSF Barrier","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-29 17:22:52","doi":"10.21203/rs.3.rs-8612817/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"This content is not available.","date":"2026-02-24T14:32:07+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-02-23T20:41:01+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2026-02-05T05:37:31+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2026-01-26T22:47:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-23T14:49:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Oncogene","date":"2026-01-22T20:22:34+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2026-01-16T14:21:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-15T17:38:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"oncogene","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"onc","sideBox":"Learn more about [Oncogene](http://www.nature.com/onc/)","snPcode":"41388","submissionUrl":"https://mts-onc.nature.com/cgi-bin/main.plex","title":"Oncogene","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"27997ae1-fb52-4538-9d72-fd6da0e8dc58","owner":[],"postedDate":"January 29th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":61782860,"name":"Biological sciences/Cancer/CNS cancer"},{"id":61782861,"name":"Biological sciences/Genetics/Cancer genomics"}],"tags":[],"updatedAt":"2026-01-29T17:22:52+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-29 17:22:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8612817","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8612817","identity":"rs-8612817","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}