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Meningiomas are the most common primary intracranial tumour in adults1. Patients with symptoms are generally treated with surgery as there are no effective medical therapies. The World Health Organization histopathological grade of the tumour and the extent of resection at surgery (Simpson grade) are associated with the recurrence of disease; however, they do not accurately reflect the clinical behaviour of all meningiomas2. Molecular classifications of meningioma that reliably reflect tumour behaviour and inform on therapies are required. Here we introduce four consensus molecular groups of meningioma by combining DNA somatic copy-number aberrations, DNA somatic point mutations, DNA methylation and messenger RNA abundance in a unified analysis. These molecular groups more accurately predicted clinical outcomes compared with existing classification schemes. Each molecular group showed distinctive and prototypical biology (immunogenic, benign NF2 wild-type, hypermetabolic and proliferative) that informed therapeutic options. Proteogenomic characterization reinforced the robustness of the newly defined molecular groups and uncovered highly abundant and group-specific protein targets that we validated using immunohistochemistry. Single-cell RNA sequencing revealed inter-individual variations in meningioma as well as variations in intrinsic expression programs in neoplastic cells that mirrored the biology of the molecular groups identified. Multi-omics datasets are integrated to generate a unified and clinically informed molecular classification of meningiomas.

Medulloblastoma (MB) is a heterogeneous malignant childhood brain cancer, classified into four molecular subgroups, WNT, SHH, Group3, and Group4, based on transcriptional, genetic, and clinical features. We aimed to understand the tumor microenvironment of Group 3 and Group 4 tumors utilizing single-cell transcriptome data. We identified four neoplastic cell states, including stemness (TNF-α), proliferative, mesenchymal and quiescence, and 11 broad lymphoid and myeloid cell types from single-cell transcriptomes. We applied CIBERSORTx to enumerate cell type proportion and CODEFACS on 73 bulk MB RNAseq profiles to determine cell type-specific abundance and gene expression profiles. We noted significant associations (both positive and negative) between the abundance of neoplastic cell states and microenvironmental cell types in both group3 and group4 MB. For example, the invasive cell state negatively correlated with dendritic cells in Group3 and Group4 tumors, but the invasive cell state was oppositely correlated with a macrophage subset in group 3 versus group 4 tumors, Survival analysis showed a significant association of higher proliferative cell state with poorer survival in Group3 MB while in group4 elevated invasive cell state, as well as elevated α, NK, and CD4-T cell abundance showed trends for poorer prognosis. Using Ecotyper, we determined cellular ecotypes based on cell type-specific transcriptome states. An ecotype containing B cell, hematopoietic, dendritic, and proliferative cell states was associated with poor prognosis in group3 and group4 tumors. We further analyzed ligand-receptor interaction between cell type states of poor prognosis ecotype; and found several interactions between ligands from immune cells (SEMA4G, LAMB2) and receptors on neoplastic cells (PLXNB2). Conversely, extracellular matrix ligands on neoplastic cells (COL1A1/2 and FN1) were found on this analysis potentially associated with integrin receptors on immune cells. Overall, our study highlights the potential biologic and clinical significance of neoplastic and immune cell states in group3/4 MB.

The tumor micro-environment (TME) plays an important role in various cancers, including gliomas. We estimated immune cell type-specific gene expression profiles in 3 large clinically annotated glioma datasets using CIBERSORTx and LM22/LM10 blood-based immune signatures and found that the proportions and estimated gene expression patterns of specific immune cells significantly varied according to IDH mutation status. When IDH-WT and IDH-MUT tumors were considered separately, cluster-of-cluster analyses of immune cell gene expression identified groups with distinct survival outcomes. We confirmed and extended these findings by applying a signature matrix derived from single-cell RNA-sequencing data derived from 19 glioma tumor samples to the bulk profiling data, validating findings from the LM22/LM10 results. To link immune cell signatures with outcomes in checkpoint therapy, we then showed a significant association of monocytic lineage cell gene expression clusters with patient survival and with mesenchymal gene expression scores. Integrating immune cell-based gene expression with previously described malignant cell states in glioma demonstrated that macrophage M0 abundance significantly correlated with mesenchymal state in IDH-WT gliomas, with evidence of a previously implicated role of the Oncostatin-M receptor and macrophages in the mesenchymal state. Among IDH-WT tumors that were enriched for the mesenchymal cell state, the estimated M0 macrophage expression signature coordinately also trended to a mesenchymal signature. We also examined IDH-MUT tumors stratified by 1p/19q status, showing that a mesenchymal gene expression signature the M0 macrophage fraction was enriched in IDH-MUT, non-codeleted tumors. Overall, these results highlight the biological and clinical significance of the immune cell environment related to IDH mutation status, patient prognosis and the mesenchymal state in diffuse gliomas.

INTRODUCTION Interactions between neoplastic cell characteristics and the immune microenvironment is an important yet understudied area in diffuse gliomas. We examined this by analyzing single cell RNAseq data (n=290,738) from 35 glioma patients (in-house and GSE182109) including 24 IDH-wildtype and 11 IDH-mutant tumors at the single cell level. Cells were assigned to specific classes, including neoplastic cell states and myeloid components, based on established methods. We used these data to develop a signature matrix to deconvolve bulk RNAseq data from TCGA diffuse gliomas. RESULTS Clustering of neoplastic cells revealed 4 cell states: proneural, mesenchymal, proliferative and cancer signaling. Elevated proneural cell state was, as expected, positively correlated with IDH-mutant tumors, and elevated mesenchymal cell state was correlated with IDH wildtype tumors (both p< 0.01, chi-square), Among IDH-mutant tumors, 1p/19q co-deletion was associated with the proneural state. Fourteen distinct myeloid cell subtypes were identified, and among them several were enriched for either microglial or macrophage (or both) markers. We examined relationships of neoplastic cell state with myeloid cell type abundance and significant associations were identified in both IDH-mutant tumors and IDH-wildtype tumors between specific myeloid cell states and myeloid clusters. Among IDH-mutant tumors, 1p/19q-co-deletion status was positively associated with abundance of a specific microglial cell cluster but negatively associated with abundance of 3 other myeloid cell clusters, suggesting substantial microenvironmental differences based on 1p/19q status in IDH-mutant tumors. In survival analyses, a specific myeloid cluster group proved interesting, with increased abundance of this group showing improved survival in both IDH-mutant and -wildtype tumors, in a manner that was enriched in specific neoplastic cell states. Overall, results suggest specific interactions between neoplastic cell characteristics, (cell states, IDH- and 1p/19q status), with myeloid cell and highlight the need of further studies understand the biological significance of the immune cell environment in diffuse gliomas.

Meningiomas are the most common primary intracranial tumour in adults

The tumor micro-environment (TME) plays an important role in the biology of cancer, including gliomas. Single cell studies have highlighted the role of specific TME components in gliomas, and the methods to deconvolve bulk profiling data may serve to complement these studies on clinically annotated tumors. In this study, we estimated cell type proportions in 3 large glioma datasets (TCGA, CGGA-325, CGGA-693) using CIBERSORTx. Using a signature matrix comprising 22 immune cell types, we identified IDH mutation status-specific immune cell distributions and found that the proportions of 10 cell types were significantly different between IDHmut and IDHwt tumors across the 3 datasets. Looking further within IDHmut tumors, we found that monocytes were enriched in 1p/19q non-co-deleted tumors across the 3 glioma datasets, consistent with prior single cell studies. We then examined estimated gene expression among immune cell types relative to IDH mutation status and found clear separation of gene expression in 15 of 22 cell types in all 3 datasets. When we applied these 22 gene expression signatures in each tumor sample onto cluster-of-cluster analyses to identify tumor groups with distinct immune signature patterns, we found that samples were distributed largely according to the IDH status in all 3 datasets, confirming that immune cell expression is distinct based on IDH status. Among IDH-specific groups, cluster-of-cluster analyses showed that immune cell-based cluster groups had distinct survival outcomes, and that IDHwt samples were distributed significantly based on tumor grades as well as based on EGFR overexpression. Among IDHmut tumors, the distributions of tumor grade and 1p/19q co-deletion status were significantly different in the immune-based clusters in 2 of the 3 datasets examined. Overall, these results highlight the biological and clinical significance of the immune cell environment in gliomas, including distinctions based on IDH mutation status as well as prognosis within IDH-specific groups.

Malignant peripheral nerve sheath tumors (MPNSTs) are highly aggressive Schwann-cell derived sarcomas. These tumors are resistant to all current therapies, with exception to gross total surgical resection, and unresectable or metastatic tumors are considered incurable. Our understanding of the molecular alterations driving malignant transformation is limited, and to date, targeted therapies have proven ineffective. In this study, we leverage multi-platform genomic and epigenomic profiling of human MPNSTs and neurofibromas to identify targetable molecular pathways that lead to malignant transformation. Unsupervised consensus hierarchical clustering of the top 20K most variable methylated probes yielded seven stable and robust subgroups that are clinically relevant. The high-grade MPNSTs formed two distinct methylation-based clusters (MPNST-G1 and MPNST-G2). MPNST-G1 had worse prognosis compared to MPNST-G2 (0.6 years versus 1.4 years, p < 0.05). PTCH1 loss or SMO gain was prevalent in MPNST-G1 compared to MPNST-G2 (75% vs 12.5%, p < 0.05). In addition, MPNST-G1 harbored PTCH1 CpG island promoter hypermethylation in (87.5% vs 12.5%, p < 0.001). Transcriptome profiling recapitulated the two distinct MPNST subgroups. We next demonstrated that that RB1 signaling pathways are aberrant in both MPNST-G1 and MPNST-G2. However, SHH pathway activation is observed in MPNST-G1, while WNT/CCND1/ ß-catenin pathway activation is observed in MPNST-G2. Network-based drug-disease proximity analysis identified SMO inhibitors as a potential FDA approved drug as a potential targeted therapy. To determine if SHH pathway activation is sufficient for malignant transformation, we knocked out PTCH1 in immortalized neurofibroma cells lines. In 3 different cell lines with PTCH1 knockout, we observed induction of a malignant phenotype, with increased cellular proliferation and invasion. Most importantly, in-vitro and in-vivo models confirm that targeting the SHH pathway, with sonidegib, was effective in inhibiting tumor growth proving SMO inhibition to be a novel therapeutic option in these lethal cancers.

Non-coding RNAs have critical functions across biological processes that regulate glioma initiation and progression, and deregulated expression of long non-coding RNAs (lncRNAs) have been implicated in the onset and progression of malignancies. The majority of these transcripts exhibit tissue- and cancer-specific expression but little has been investigated at the single-cell level. We performed single cell RNA Sequencing (10x Genomics) for 9 IDH-wild-type glioblastomas from 7 patients. In total 66,825 cells dissociated from tumor tissues and not sorted were included in this analysis which encompassed 41,989 mean sequencing reads and 2,619 median coding genes per cell. Single cell analysis of lncRNAs in captured 190 median lncRNAs per cell and demonstrated a distinct lncRNA expression profile for glioma cells compared to the non-tumor cells with SOX2-OT significantly upregulated (2X) in glioma cells. Consistent with this finding, SOX2-OT is known to be overexpressed in a variety of cancers and has been previously implicated in glioma proliferation and migration. We then examined patterns of lncRNA expression in GBM expression subtypes. Subtype correlation indicated overexpression of RMST (classical subtype), PCED1B-AS1 (mesenchymal) and LINC00689 (proneural) lncRNAs in these expression subtypes. Consistent with these findings, upregulation of each of these 3 lncRNAs have previously been implicated on pro-tumorigenic effects, including in glioma. Examination of an independent published single cell GBM dataset also validated PCED1B-AS1 in the mesenchymal subtype. Comparison with bulk tumor GBM profiles (IDHwt TCGA GBM dataset) also showed correlations with the expression of RMST, PCED1B-AS1 and LINC00689 lncRNAs in the classical, mesenchymal and proneural subtypes respectively. Overall, these results indicate lncRNA expression can be determined in 10x-generated glioma single cell data and may reveal additional insights about cellular state and glioma biology.

Editing in microRNAs, particularly in seed can significantly alter the choice of their target genes. We show that out of 13 different human tissues, different regions of brain showed higher adenosine to inosine (A-to-I) editing in mature miRNAs. These events were enriched in seed sequence (73.33%), which was not observed for cytosine to uracil (17.86%) editing. More than half of the edited miRNAs showed increased stability, 72.7% of which had ΔΔG values less than −6.0 Kcal/mole and for all of them the edited adenosines mis-paired with cytosines on the pre-miRNA structure. A seed-editing event in hsa-miR-411 (with A – C mismatch) lead to increased expression of the mature form compared to the unedited version in cell culture experiments. Further, small RNA sequencing of GBM patients identified significant miRNA hypoediting which correlated with downregulation of ADAR2 both in metadata and qRT-PCR based validation. Twenty-two significant (11 novel) A-to-I hypoediting events were identified in GBM samples. This study highlights the importance of specific sequence and structural requirements of pre-miRNA for editing along with a suggestive crucial role for ADAR2. Enrichment of A-to-I editing in seed sequence highlights this as an important layer for genomic regulation in health and disease, especially in human brain.

Somatic variation in DNA can cause cells to deviate from the preordained\ud genomic path in both disease and healthy conditions. Here, using exome\ud sequencing of paired tissue samples, we show that the normal human brain\ud harbors somatic single base variations measuring up to 0.48% of the total\ud variations. Interestingly, about 64% of these somatic variations in the brain are\ud expected to lead to non-synonymous changes, and as much as 87% of these\ud represent G:C>T:A transversion events. Further, the transversion events in the\ud brain were mostly found in the frontal cortex, whereas the corpus callosum from\ud the same individuals harbors the reference genotype. We found a significantly\ud higher amount of 8-OHdG (oxidative stress marker) in the frontal cortex\ud compared to the corpus callosum of the same subjects (pT:A transversions in the cortex. We found significant\ud enrichment for axon guidance and related pathways for genes harbouring\ud somatic variations. This could represent either a directed selection of genetic\ud variations in these pathways or increased susceptibility of some loci towards\ud oxidative stress. This study highlights that oxidative stress possibly influence\ud single nucleotide somatic variations in normal human brain.

Method Genome-wide data was generated on 364 POAG cases and 365 controls on Illumina 660W-Quad arrays and CNVs were called using PennCNV. Copy number variant regions (CNVRs) were analyzed for association. A publicly available dataset of POAG cohort of 866 cases and 495 controls from Caucasian origin (GLAUGEN study) was used as a validation cohort. Representative CNVs were validated using real-time PCR.

PURPOSE: Large copy number variations (CNV) can contribute to increased burden for neurodegenerative diseases. In this study, we analyzed the genome-wide burden of large CNVs > 100 kb in primary open angle glaucoma (POAG), a neurodegenerative disease of the eye that is the largest cause of irreversible blindness. METHODS: Genome-wide analysis of CNVs > 100 kb were analyzed in a total of 1720 individuals, including an Indian cohort (347 POAG cases and 345 controls) and a Caucasian cohort (624 cases and 404 controls). All the CNV data were obtained from experiments performed on Illumina 660W-Quad (infinium) arrays. RESULTS: We observed that for both the populations CNVs > 1 Mb was significantly enriched for gene-rich regions unique to the POAG cases (P 1 Mb (39 calls) in patients influenced 125 genes while in controls 31 such CNVs influenced only 5 genes with no overlap. In both cohorts we observed 1.9-fold gene enrichment in patients for deletions compared to duplications, while such a bias was not observed in controls (0.3-fold). Overall duplications > 1 Mb were more than deletions (Del/Dup = 0.82) confirming that the enrichment of gene-rich deletions in patients was associated with the disease. Of the 39 CNVs > 1 Mb from Indian patients, 28 (72%) also were implicated in other neurodegenerative disorders, like autism, schizophrenia, sensorineural hearing loss, and so forth. We found one large duplication encompassing CNTN4 gene in Indian and Caucasian POAG patients that was absent in the controls. CONCLUSIONS: To our knowledge, our study is the first report on large CNV bias for gene-rich regions in glaucomatous neurodegeneration, implicating its impact across populations of contrasting ethnicities. We identified CNTN4 as a novel candidate gene for POAG.