Multiplatform genomic profiling and magnetic resonance imaging identify mechanisms underlying intratumor heterogeneity in meningioma

Elevated meningioma risk among individuals who are Non-Hispanic Black is strongest for grade 2-3 tumors and synergistically modified by male sex

Background

Meningioma risk factors include older age, female sex, and African-American race. There are limited data exploring how meningioma risk in African-Americans varies across the lifespan, interacts with sex, and differs by tumor grade.

Methods

The Central Brain Tumor Registry of the United States (CBTRUS) is a population-based registry covering the entire U.S. population. Meningioma diagnoses from 2004-2019 were used to calculate incidence rate ratios (IRRs) for non-Hispanic Black individuals (NHB) compared to non-Hispanic white individuals (NHW) across 10-year age intervals, and stratified by sex and by WHO tumor grade.

Results

53,890 NHB individuals and 322,373 NHW individuals with an intracranial meningioma diagnosis were included in analyses. Beginning in young adulthood, the NHB-to-NHW IRR was elevated for both grade 1 and grade 2/3 tumors. The IRR peaked in the seventh decade of life regardless of grade, and was higher for grade 2/3 tumors (IRR=1.57; 95% CI: 1.46-1.69) than grade 1 tumors (IRR=1.27; 95% CI: 1.25-1.30) in this age group. The NHB-to-NHW IRR was elevated in females (IRR=1.17; 95% CI: 1.16-1.18) and further elevated in males (IRR=1.28; 95% CI: 1.26-1.30), revealing synergistic interaction between NHB race/ethnicity and male sex (P Interaction =0.001).

Conclusions

Relative to NHW individuals, NHB individuals are at elevated risk of meningioma from young adulthood through old age. NHB race/ethnicity conferred higher risk of meningioma among men than women, and higher risk of developing WHO grade 2/3 tumors. Results identify meningioma as a significant source of racial disparities in neuro-oncology and may help to improve preoperative predictions of meningioma grade.

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

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

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

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

A systematic review of extraneural meningioma metastasis: timing, evolution and outlook

PURPOSE

Extraneural meningioma metastasis is a rare occurrence and may pose a clinical challenge due to its unclear prognosis. In this systematic review, we analyze patient demographics, clinical characteristics, management strategies, and outcomes.

METHODS

PubMed, EMBASE, Scopus, Cochrane, and Web of Science databases were searched from inception to February 23, 2024 for cases of metastatic meningioma according to PRISMA guidelines. Descriptive statistics, Mann-Whitney U test, Fisher's exact tests, Kaplan-Meier curves, and log-rank tests were used for selected analyses.

RESULTS

A total of 288 patients (52% male) were included with an average age of 49 years at meningioma diagnosis. Tumors were distributed across WHO grade 1 (38%), 2 (36%), and 3 (26%). Most patients experienced intracranial recurrence (79%) and mean time to first metastasis was approximately 8 years. No change in WHO grade between primary and metastasis was observed for most cases (65%). Treatment of the initial metastasis was most often with surgery (43%), chemotherapy (20%), or no treatment (14%). Half of the patients were alive (50%) with an average follow-up of 3 years following metastasis. Overall median survival was 36 months for the entire cohort. This differed significantly between WHO grade 1 versus 2/3 meningioma primaries (168 vs. 15 months, p < 0.005).

CONCLUSION

Metastatic meningioma appears to be associated with more positive prognosis than other brain tumor types with extra-neural metastasis or metastasis in general. This is particularly true for cases arising from a WHO grade 1 meningioma.

Functional interactions between neurofibromatosis tumor suppressors underlie Schwann cell tumor de-differentiation and treatment resistance

Schwann cell tumors are the most common cancers of the peripheral nervous system and can arise in patients with neurofibromatosis type-1 (NF-1) or neurofibromatosis type-2 (NF-2). Functional interactions between NF1 and NF2 and broader mechanisms underlying malignant transformation of the Schwann lineage are unclear. Here we integrate bulk and single-cell genomics, biochemistry, and pharmacology across human samples, cell lines, and mouse allografts to identify cellular de-differentiation mechanisms driving malignant transformation and treatment resistance. We find DNA methylation groups of Schwann cell tumors can be distinguished by differentiation programs that correlate with response to the MEK inhibitor selumetinib. Functional genomic screening in NF1-mutant tumor cells reveals NF2 loss and PAK activation underlie selumetinib resistance, and we find that concurrent MEK and PAK inhibition is effective in vivo. These data support a de-differentiation paradigm underlying malignant transformation and treatment resistance of Schwann cell tumors and elucidate a functional link between NF1 and NF2.

Pan-cancer copy number variant analysis identifies optimized size thresholds and co-occurrence models for individualized risk-stratification

Chromosome instability leading to accumulation of copy number gains or losses is a hallmark of cancer. Copy number variant (CNV) signatures are increasingly used for clinical risk-stratification, but size thresholds for defining CNVs are variable and the biological or clinical implications of CNV size heterogeneity or co-occurrence patterns are incompletely understood. Here we analyze CNV and clinical data from 565 meningiomas and 9,885 tumors from The Cancer Genome Atlas (TCGA) to develop tumor-and chromosome-specific CNV size-dependent and co-occurrence models for clinical outcomes. Our results reveal prognostic CNVs with optimized size thresholds and co-occurrence patterns that refine risk-stratification across a diversity of human cancers.

A novel patient-derived meningioma spheroid model as a tool to study and treat epithelial-to-mesenchymal transition (EMT) in meningiomas

Meningiomas are the most common intracranial brain tumours. These tumours are heterogeneous and encompass a wide spectrum of clinical aggressivity. Treatment options are limited to surgery and radiotherapy and have a risk of post-operative morbidities and radiation neurotoxicity, reflecting the need for new therapies. Three-dimensional (3D) patient-derived cell culture models have been shown to closely recapitulate in vivo tumour biology, including microenvironmental interactions and have emerged as a robust tool for drug development. Here, we established a novel easy-to-use 3D patient-derived meningioma spheroid model using a scaffold-free approach. Patient-derived meningioma spheroids were characterised and compared to patient tissues and traditional monolayer cultures by histology, genomics, and transcriptomics studies. Patient-derived meningioma spheroids closely recapitulated morphological and molecular features of matched patient tissues, including patient histology, genomic alterations, and components of the immune microenvironment, such as a CD68 + and CD163 + positive macrophage cell population. Comprehensive transcriptomic profiling revealed an increase in epithelial-to-mesenchymal transition (EMT) in meningioma spheroids compared to traditional monolayer cultures, confirming this model as a tool to elucidate EMT in meningioma. Therefore, as proof of concept study, we developed a treatment strategy to target EMT in meningioma. We found that combination therapy using the MER tyrosine kinase (MERTK) inhibitor UNC2025 and the histone deacetylase (HDAC) inhibitor Trichostatin A (TSA) effectively decreased meningioma spheroid viability and proliferation. Furthermore, we demonstrated this combination therapy significantly increased the expression of the epithelial marker E-cadherin and had a repressive effect on WHO grade 2-derived spheroid invasion, which is suggestive of a partial reversal of EMT in meningioma spheroids.

Targeted gene expression profiling predicts meningioma outcomes and radiotherapy responses

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

α-SMA+ cancer-associated fibroblasts increased tumor enhancement ratio on contrast-enhanced multidetector-row computed tomography in stages I-III colon cancer

BACKGROUND AND AIM

Our prior research revealed that the tumor enhancement ratio (TER) on triphasic abdominal contrast-enhanced MDCT (CE-MDCT) scans was a prognostic factor for patients with stages I-III colon cancer. Building upon this finding, the present study aims to investigate the proteomic changes in colon cancer patients with varying TER values.

METHODS

TER was analyzed on preoperative triphasic CE-MDCT scans of 160 stages I-III colon cancer patients. The survival outcomes of those in the low-TER and high-TER groups were compared. Proteomic analysis on colon cancer tissues was performed by mass spectrometry (MS) and verified by immune-histological chemistry (IHC) assays. In vivo, mouse xenograft models were employed to test the function of target proteins identified through the MS. CE-MDCT scans were conducted on mice xenografts, and the TER values were compared.

RESULTS

Patients in the high-TER group had a significantly worse prognosis than those in the low-TER group. Proteomic analysis of colon cancer tissues revealed 153 differentially expressed proteins between the two groups. A correlation between TER and the abundance of α-SMA protein in tumor tissue was observed. IHC assays further confirmed that α-SMA protein expression was significantly increased in high-TER colon cancer, predominantly in cancer-associated fibroblasts (CAFs) within the cancer stroma. Moreover, CAFs promoted the growth of CRC xenografts in vivo and increased TER.

CONCLUSIONS

Our study identified the distinct protein changes in colon cancer with low and high TER for the first time. The presence of CAFs may promote the growth of colon cancer and contribute to an increased TER.

CDKN2A/B deletions are strongly associated with meningioma progression: a meta-analysis of individual patient data

Homozygous CDKN2A/B deletion has been associated with an increased risk of recurrence in meningiomas. However, the evidence is confined to a limited number of studies, and the importance of heterozygous CDKN2A/B deletions remains insufficiently investigated. Hence, the present meta-analysis reconstructs individual patient data (IPD) and reconstructs the probabilities of progression-free survival (PFS) stratified by CDKN2A/B status. IPD of PFS rates were extracted from published Kaplan-Meier plots using the R package IPDfromKM in R studio (RStudio, Boston, MA, USA). Reconstructed Kaplan-Meier Plots of the pooled IPD data were created. One-stage and two-stage meta-analyses were performed. Hazard ratios (HR) were used as effective measures. Of 181 records screened, four articles with 2521 participants were included. The prevalence of homozygous CDKN2A/B deletions in the included studies was 0.049 (95% CI 0.040-0.057), with higher tumor grades associated with a significantly greater proportion of CDKN2A/B deletions. The reconstructed PFS curves for the pooled cohort showed that the median PFS time of patients with a CDKN2A/B wild-type status, heterozygous or homozygous CDKN2A/B deletion was 180.0 (95% CI 145.7-214.3), 26.1 (95% CI 23.3-29.0), and 11.00 (95% CI 8.6-13.3) months, respectively (p < 0.0001). Both hetero- or homozygous CDKN2A/B deletions were significantly associated with shortened time to meningioma progression. One-stage meta-analysis showed that hetero- (HR: 5.5, 95% CI 4.0-7.6, p < 0.00001) and homozygous CDKN2A/B deletions (HR: 8.4, 95% CI 6.4-11.0, p < 0.00001) are significantly associated with shortened time to meningioma progression. Multivariable Cox regression analysis of progression in a subgroup with available covariates (age, sex, WHO grade, and TERT status) and also two-stage meta-analysis confirmed and validated the results of the one-stage analysis that both heterozygous and homozygous CDKN2A/B deletions are of prognostic importance. Further large-scale studies of WHO grade 2 and 3 meningiomas are needed to validate the importance of heterozygous CDKN2A/B deletions with consideration of established factors.

The molecular landscape of neurological disorders: insights from single-cell RNA sequencing in neurology and neurosurgery

Single-cell ribonucleic acid sequencing (scRNA-seq) has emerged as a transformative technology in neurological and neurosurgical research, revolutionising our comprehension of complex neurological disorders. In brain tumours, scRNA-seq has provided valuable insights into cancer heterogeneity, the tumour microenvironment, treatment resistance, and invasion patterns. It has also elucidated the brain tri-lineage cancer hierarchy and addressed limitations of current models. Neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis have been molecularly subtyped, dysregulated pathways have been identified, and potential therapeutic targets have been revealed using scRNA-seq. In epilepsy, scRNA-seq has explored the cellular and molecular heterogeneity underlying the condition, uncovering unique glial subpopulations and dysregulation of the immune system. ScRNA-seq has characterised distinct cellular constituents and responses to spinal cord injury in spinal cord diseases, as well as provided molecular signatures of various cell types and identified interactions involved in vascular remodelling. Furthermore, scRNA-seq has shed light on the molecular complexities of cerebrovascular diseases, such as stroke, providing insights into specific genes, cell-specific expression patterns, and potential therapeutic interventions. This review highlights the potential of scRNA-seq in guiding precision medicine approaches, identifying clinical biomarkers, and facilitating therapeutic discovery. However, challenges related to data analysis, standardisation, sample acquisition, scalability, and cost-effectiveness need to be addressed. Despite these challenges, scRNA-seq has the potential to transform clinical practice in neurological and neurosurgical research by providing personalised insights and improving patient outcomes.

Advances and Applications of Brain Organoids

Understanding the fundamental processes of human brain development and diseases is of great importance for our health. However, existing research models such as non-human primate and mouse models remain limited due to their developmental discrepancies compared with humans. Over the past years, an emerging model, the "brain organoid" integrated from human pluripotent stem cells, has been developed to mimic developmental processes of the human brain and disease-associated phenotypes to some extent, making it possible to better understand the complex structures and functions of the human brain. In this review, we summarize recent advances in brain organoid technologies and their applications in brain development and diseases, including neurodevelopmental, neurodegenerative, psychiatric diseases, and brain tumors. Finally, we also discuss current limitations and the potential of brain organoids.

Decoding meningioma heterogeneity and neoplastic cell-macrophage interaction through single-cell transcriptome profiling across pathological grades

BACKGROUND

Analyzing meningioma of distinct pathological types at the single-cell level can provide new and valuable insights into the specific biological mechanisms of each cellular subpopulation, as well as their vital interplay within the tumor microenvironment.

METHODS

We recruited patients diagnosed with four distinct types of meningioma and performed single-cell RNA sequencing on their tumor samples, concurrently analyzing a publicly available dataset for comparison. Next, we separated the cells into discrete clusters and identified their unique identities. Using pseudotime analysis, we demonstrated cellular differentiation and dynamics. To investigate biological function, we employed weighted gene co-expression network analysis, gene regulatory network, and gene set enrichment analysis. Additionally, we conducted cell-cell communication analyses to characterize interactions among different clusters and validated a crucial interaction using multiple immunofluorescence staining.

RESULTS

The single-cell transcriptomic profiles for five meningioma of different pathological types demonstrated that neoplastic cells exhibited high inter-sample heterogeneity and diverse biological functions featured by metabolic regulation. A small cluster of neoplastic cells (N5 cluster, < 3%) was most proliferative, indicated by high expression of MKI67 and TOP2A. They were primarily observed in our atypical and transitional meningioma samples and located at the beginning of the pseudotime differentiation branch for neoplastic cells. Macrophages, the most abundant immune cells present, showed two distinct developmental trajectories, one promoting and the other suppressing meningioma growth, with the MIF-CD74 interaction serving as the primary signaling pathway for MIF signals in the tumor environment. Unexpectedly, despite its small cluster size, the N5 cluster demonstrated a significant contribution in this interaction. By staining pathological sections of more samples, we found that this interaction was widely present in different types of meningiomas.

CONCLUSIONS

Meningioma neoplastic cells' diverse types cause inter-sample heterogeneity and a wide range of functions. Some proliferative neoplastic cell may educate macrophages, which promotes tumorigenesis possibly through the MIF-CD74 interaction. It provides novel clues for future potential therapeutic avenues.

Applications of organoid technology to brain tumors

Lacking appropriate model impedes basic and preclinical researches of brain tumors. Organoids technology applying on brain tumors enables great recapitulation of the original tumors. Here, we compared brain tumor organoids (BTOs) with common models including cell lines, tumor spheroids, and patient-derived xenografts. Different BTOs can be customized to research objectives and particular brain tumor features. We systematically introduce the establishments and strengths of four different BTOs. BTOs derived from patient somatic cells are suitable for mimicking brain tumors caused by germline mutations and abnormal neurodevelopment, such as the tuberous sclerosis complex. BTOs derived from human pluripotent stem cells with genetic manipulations endow for identifying and understanding the roles of oncogenes and processes of oncogenesis. Brain tumoroids are the most clinically applicable BTOs, which could be generated within clinically relevant timescale and applied for drug screening, immunotherapy testing, biobanking, and investigating brain tumor mechanisms, such as cancer stem cells and therapy resistance. Brain organoids co-cultured with brain tumors (BO-BTs) own the greatest recapitulation of brain tumors. Tumor invasion and interactions between tumor cells and brain components could be greatly explored in this model. BO-BTs also offer a humanized platform for testing the therapeutic efficacy and side effects on neurons in preclinical trials. We also introduce the BTOs establishment fused with other advanced techniques, such as 3D bioprinting. So far, over 11 brain tumor types of BTOs have been established, especially for glioblastoma. We conclude BTOs could be a reliable model to understand brain tumors and develop targeted therapies.

Molecular Features of Resected Melanoma Brain Metastases, Clinical Outcomes, and Responses to Immunotherapy

Importance

Central nervous system (CNS)-penetrant systemic therapies have significantly advanced care for patients with melanoma brain metastases. However, improved understanding of the molecular landscape and microenvironment of these lesions is needed to both optimize patient selection and advance treatment approaches.

Objective

To evaluate how bulk and single-cell genomic features of melanoma brain metastases are associated with clinical outcome and treatment response.

Design, Setting, and Participants

This cohort study analyzed bulk DNA sequencing and single nuclear RNA-sequencing data from resected melanoma brain metastases and included 94 consecutive patients with a histopathologically confirmed diagnosis of melanoma brain metastasis who underwent surgical resection at a single National Comprehensive Cancer Network cancer center in San Francisco, California, from January 1, 2009, to December 31, 2022.

Exposure

A Clinical Laboratory Improvement Amendments-certified targeted sequencing assay was used to analyze tumor resection specimens, with a focus on BRAF V600E alteration. For frozen pathologic specimens from CNS treatment-naive patients undergoing surgical resection, commercial single nuclear RNA sequencing approaches were used.

Main Outcomes and Measures

The primary outcome was overall survival (OS). Secondary outcomes included CNS progression-free survival (PFS), microenvironmental composition with decreased T-cell and macrophage populations, and responses to immunotherapy.

Results

To correlate molecular status with clinical outcome, Kaplan-Meier survival analysis of 94 consecutive patients (median age, 64 years [range, 24-82 years]; 70 men [74%]) with targeted BRAF alteration testing showed worse median intracranial PFS (BRAF variant: 3.6 months [IQR, 0.1-30.6 months]; BRAF wildtype: 11.0 months [IQR, 0.8-81.5 months]; P < .001) and OS (BRAF variant: 9.8 months [IQR, 2.5-69.4 months]; BRAF wildtype: 23.2 months [IQR, 1.1-102.5 months]; P = .005; log-rank test) in BRAF V600E variant tumors. Multivariable Cox proportional hazards regression analysis revealed that BRAF V600E status was an independent variable significantly associated with both PFS (hazard ratio [HR], 2.65; 95% CI, 1.54-4.57; P < .001) and OS (HR, 1.96; 95% CI, 1.08-3.55; P = .03). For the 45 patients with resected melanoma brain metastases undergoing targeted DNA sequencing, molecular classification recapitulated The Cancer Genome Atlas groups (NRAS variant, BRAF variant, NF1 variant, and triple wildtype) with no subtype enrichment within the brain metastasis cohort. On a molecular level, BRAF V600E variant lesions were found to have a significantly decreased tumor mutation burden. Moreover, single nuclear RNA sequencing of treatment-naive BRAF V600E variant (n = 3) brain metastases compared with BRAF wildtype (n = 3) brain metastases revealed increased immune cell populations in BRAF wildtype tumors (mean [SD], 11% [4.1%] vs 3% [1.6%] CD45-positive cells; P = .04). Survival analysis of postoperative immunotherapy responses by BRAF status revealed that BRAF wildtype lesions were associated with a response to checkpoint inhibition (median OS: with immunotherapy, undefined; without immunotherapy, 13.0 months [range, 1.1-61.7 months]; P = .001; log-rank test) while BRAF variant lesions (median OS: with immunotherapy, 9.8 months [range, 2.9-39.8 months]; without immunotherapy, 9.5 months [range, 2.5-67.2 months]; P = .81; log-rank test) were not.

Conclusions and Relevance

This molecular analysis of patients with resected melanoma brain metastases found that BRAF V600E alteration is an important translational biomarker associated with worse clinical outcomes, differential microenvironmental composition, and benefit from immunotherapy. Patients with BRAF V600E variant melanoma brain metastases may thus benefit from alternative CNS-penetrant systemic regimens.

Modeling brain and neural crest neoplasms with human pluripotent stem cells

Pluripotent stem cells offer unique avenues to study human-specific aspects of disease and are a highly versatile tool in cancer research. Oncogenic processes and developmental programs often share overlapping transcriptomic and epigenetic signatures, which can be reactivated in induced pluripotent stem cells. With the emergence of brain organoids, the ability to recapitulate brain development and structure has vastly improved, making in vitro models more realistic and hence more suitable for biomedical modeling. This review highlights recent research and current challenges in human pluripotent stem cell modeling of brain and neural crest neoplasms, and concludes with a call for more rigorous quality control and for the development of models for rare tumor subtypes.

Modeling Meningiomas: Optimizing Treatment Approach

Preclinical meningioma models offer a setting to test molecular mechanisms of tumor development and targeted treatment options but historically have been challenging to generate. Few spontaneous tumor models in rodents have been established, but cell culture and in vivo rodent models have emerged along with artificial intelligence, radiomics, and neural networks to differentiate the clinical heterogeneity of meningiomas. We reviewed 127 studies using PRISMA guideline methodology, including laboratory and animal studies, that addressed preclinical modeling. Our evaluation identified that meningioma preclinical models provide valuable molecular insight into disease progression and effective chemotherapeutic and radiation approaches for specific tumor types.

Impact of Shape Irregularity in Medial Sphenoid Wing Meningiomas on Postoperative Cranial Nerve Functioning, Proliferation, and Progression-Free Survival

Medial sphenoid wing meningiomas (MSWM) are surgically challenging skull base tumors. Irregular tumor shapes are thought to be linked to histopathology. The present study aims to investigate the impact of tumor shape on postoperative functioning, progression-free survival, and neuropathology. This monocentric study included 74 patients who underwent surgery for primary sporadic MSWM (WHO grades 1 and 2) between 2010 and 2021. Furthermore, a systematic review of the literature regarding meningioma shape and the MIB-1 index was performed. Irregular MSWM shapes were identified in 31 patients (41.9%). Multivariable analysis revealed that irregular shape was associated with postoperative cranial nerve deficits (OR: 5.75, 95% CI: 1.15-28.63, p = 0.033). In multivariable Cox regression analysis, irregular MSWM shape was independently associated with tumor progression (HR:8.0, 95% CI: 1.04-62.10, p = 0.046). Multivariable regression analysis showed that irregular shape is independently associated with an increased MIB-1 index (OR: 7.59, 95% CI: 2.04-28.25, p = 0.003). A systematic review of the literature and pooled data analysis, including the present study, showed that irregularly shaped meningiomas had an increase of 1.98 (95% CI: 1.38-2.59, p < 0.001) in the MIB-1 index. Irregular MSWM shape is independently associated with an increased risk of postoperative cranial nerve deficits and a shortened time to tumor progression. Irregular MSWM shapes might be caused by highly proliferative tumors.

Application of radiomics to meningiomas: A systematic review

BACKGROUND

Quantitative imaging analysis through radiomics is a powerful technology to non-invasively assess molecular correlates and guide clinical decision-making. There has been growing interest in image-based phenotyping for meningiomas given the complexities in management.

METHODS

We systematically reviewed meningioma radiomics analyses published in PubMed, Embase, and Web of Science until December 20, 2021. We compiled performance data and assessed publication quality using the radiomics quality score (RQS).

RESULTS

A total of 170 publications were grouped into 5 categories of radiomics applications to meningiomas: Tumor detection and segmentation (21%), classification across neurologic diseases (54%), grading (14%), feature correlation (3%), and prognostication (8%). A majority focused on technical model development (73%) versus clinical applications (27%), with increasing adoption of deep learning. Studies utilized either private institutional (50%) or public (49%) datasets, with only 68% using a validation dataset. For detection and segmentation, radiomic models had a mean accuracy of 93.1 ± 8.1% and a dice coefficient of 88.8 ± 7.9%. Meningioma classification had a mean accuracy of 95.2 ± 4.0%. Tumor grading had a mean area-under-the-curve (AUC) of 0.85 ± 0.08. Correlation with meningioma biological features had a mean AUC of 0.89 ± 0.07. Prognostication of the clinical course had a mean AUC of 0.83 ± 0.08. While clinical studies had a higher mean RQS compared to technical studies, quality was low overall with a mean RQS of 6.7 ± 5.9 (possible range -8 to 36).

CONCLUSIONS

There has been global growth in meningioma radiomics, driven by data accessibility and novel computational methodology. Translatability toward complex tasks such as prognostication requires studies that improve quality, develop comprehensive patient datasets, and engage in prospective trials.

Novel Human Meningioma Organoids Recapitulate the Aggressiveness of the Initiating Cell Subpopulations Identified by ScRNA-Seq

High-grade meningioma has an unsatisfactory outcome despite surgery and postoperative radiotherapy; however, the factors driving its malignancy and recurrence remain largely unknown, which limits the development of systemic treatments. Single-cell RNA sequencing (scRNA-Seq) technology is a powerful tool for studying intratumoral cellular heterogeneity and revealing the roles of various cell types in oncogenesis. In this study, scRNA-Seq is used to identify a unique initiating cell subpopulation (SULT1E1⁺ ) in high-grade meningiomas. This subpopulation modulates the polarization of M2-type macrophages and promotes meningioma progression and recurrence. A novel patient-derived meningioma organoid (MO) model is established to characterize this unique subpopulation. The resulting MOs fully retain the aggressiveness of SULT1E1⁺ and exhibit invasiveness in the brain after orthotopic transplantation. By targeting SULT1E1⁺ in MOs, the synthetic compound SRT1720 is identified as a potential agent for systemic treatment and radiation sensitization. These findings shed light on the mechanism underlying the malignancy of high-grade meningiomas and provide a novel therapeutic target for refractory high-grade meningioma.

Protein Tyrosine Phosphatase Receptor Zeta 1 as a Potential Target in Cancer Therapy and Diagnosis

Protein tyrosine phosphatase receptor zeta 1 (PTPRZ1) is a type V transmembrane tyrosine phosphatase that is highly expressed during embryonic development, while its expression during adulthood is limited. PTPRZ1 is highly detected in the central nervous system, affecting oligodendrocytes' survival and maturation. In gliomas, PTPRZ1 expression is significantly upregulated and is being studied as a potential cancer driver and as a target for therapy. PTPRZ1 expression is also increased in other cancer types, but there are no data on the potential functional significance of this finding. On the other hand, low PTPRZ1 expression seems to be related to a worse prognosis in some cancer types, suggesting that in some cases, it may act as a tumor-suppressor gene. These discrepancies may be due to our limited understanding of PTPRZ1 signaling and tumor microenvironments. In this review, we present evidence on the role of PTPRZ1 in angiogenesis and cancer and discuss the phenomenal differences among the different types of cancer, depending on the regulation of its tyrosine phosphatase activity or ligand binding. Clarifying the involved signaling pathways will lead to its efficient exploitation as a novel therapeutic target or as a biomarker, and the development of proper therapeutic approaches.

Targeted gene expression profiling predicts meningioma outcomes and radiotherapy responses

Background

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

Methods

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

Results

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

Conclusions

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

MerlinS13 phosphorylation controls meningioma Wnt signaling and magnetic resonance imaging features

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

Evaluating risk of recurrence in patients with meningioma

OBJECTIVE

Meningioma prognostication and treatment continues to evolve with an increasing understanding of tumor biology. In this study, the authors aimed to test conventional predictors of meningioma recurrence, histopathology variables for which there exists some controversy (brain invasion), as well as a novel molecular-based location paradigm.

METHODS

This is a retrospective study of a consecutive series of patients with WHO grade I-III meningioma resected at The University of Texas Southwestern Medical Center between 1994 and 2015. Time to meningioma recurrence (i.e., recurrence-free survival [RFS]) was the primary endpoint measured. Kaplan-Meier curves were constructed and compared using log-rank tests. Cox univariate and multivariate analyses were performed to identify predictors of RFS.

RESULTS

A total of 703 consecutive patients with meningioma underwent resection at The University of Texas Southwestern Medical Center between the years 1994 and 2015. A total of 158 patients were excluded for insufficient follow-up (< 3 months). The median age of the cohort was 55 years (range 16-88 years) and 69.5% (n = 379) were female. The median follow-up was 48 months (range 3-289 months). There was not a significantly increased risk of recurrence in patients with evidence of brain invasion, in patients with otherwise WHO grade I meningioma (Cox univariate HR 0.92, 95% CI 0.44-1.91, p = 0.82, power 4.4%). Adjuvant radiosurgery to subtotally resected WHO grade I meningiomas did not prolong the time to recurrence (n = 52, Cox univariate HR 0.21, 95% CI 0.03-1.61, p = 0.13, power 71.6%). Location (midline skull base, lateral skull base, and paravenous) was significantly associated with RFS (p < 0.01, log-rank test). In patients with high-grade meningiomas (WHO grade II or III), location was predictive of RFS (p = 0.03, log-rank test), with paravenous meningiomas exhibiting the highest rates of recurrence. Location was not significant on multivariate analysis.

CONCLUSIONS

The data suggest that brain invasion does not increase the risk of recurrence in otherwise WHO grade I meningioma. Adjuvant radiosurgery to subtotally resected WHO grade I meningiomas did not prolong the time to recurrence. Location categorized by distinct molecular signatures did not predict RFS in a multivariate model. Larger studies are needed to confirm these findings.

Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes

The increasing number of available anti-cancer drugs presents a challenge for oncologists, who must choose the most effective treatment for the patient. Precision cancer medicine relies on matching a drug with a tumor's molecular profile to optimize the therapeutic benefit. However, current precision medicine approaches do not fully account for intra-tumoral heterogeneity. Different mutation profiles and cell behaviors within a single heterogeneous tumor can significantly impact therapy response and patient outcomes. Patient-derived avatar models recapitulate a patient's tumor in an animal or dish and provide the means to functionally assess heterogeneity's impact on drug response. Mouse xenograft and organoid avatars are well-established, but the time required to generate these models is not practical for clinical decision-making. Zebrafish are emerging as a time-efficient and cost-effective cancer avatar model. In this review, we highlight recent developments in zebrafish cancer avatar models and discuss the unique features of zebrafish that make them ideal for the interrogation of cancer heterogeneity and as part of precision cancer medicine pipelines.

The Role of Pharmacotherapy in Treatment of Meningioma: A Systematic Review

The safety and efficacy of various pharmacotherapeutic regimens on refractory meningiomas have been the focus of investigations. We present a comprehensive review of the previous efforts and the current state of ongoing clinical trials. A PRISMA-compliant review of the MEDLINE and ClinicalTrial.gov databases of the National Library of Medicine were performed. The primary outcomes of interest for included articles were radiographic response, overall survival, progression-free survival, six-month progression-free survival, and adverse events. Overall, 34 completed trials and 27 ongoing clinical trials were eligible. Six-month progression-free survival was reported in 6-100% of patients in the completed studies. Hematological disorders were the most common adverse events. Of the ongoing clinical trials identified, nine studies are phase I clinical trials, eleven are phase II trials, two are phase I and II trials, one is phase II and III, and two trials do not have a designated phase. Currently, there is no effective chemotherapy for refractory or recurrent meningiomas. Several promising targeted agents have been developed and are currently being investigated in the hope of identifying novel therapeutic strategies for the treatment of this pathology.

Recent advances in the molecular prognostication of meningiomas

Meningiomas are the most common primary intracranial neoplasm. While traditionally viewed as benign, meningiomas are associated with significant patient morbidity, and certain meningioma subgroups display more aggressive and malignant behavior with higher rates of recurrence. Historically, the risk stratification of meningioma recurrence has been primarily associated with the World Health Organization histopathological grade and surgical extent of resection. However, a growing body of literature has highlighted the value of utilizing molecular characteristics to assess meningioma aggressiveness and recurrence risk. In this review, we discuss preclinical and clinical evidence surrounding the use of molecular classification schemes for meningioma prognostication. We also highlight how molecular data may inform meningioma treatment strategies and future directions.

Clinical Management of Supratentorial Non-Skull Base Meningiomas

Supratentorial non-skull base meningiomas are the most common primary central nervous system tumor subtype. An understanding of their pathophysiology, imaging characteristics, and clinical management options will prove of substantial value to the multi-disciplinary team which may be involved in their care. Extensive review of the broad literature on the topic is conducted. Narrowing the scope to meningiomas located in the supratentorial non-skull base anatomic location highlights nuances specific to this tumor subtype. Advances in our understanding of the natural history of the disease and how findings from both molecular pathology and neuroimaging have impacted our understanding are discussed. Clinical management and the rationale underlying specific approaches including observation, surgery, radiation, and investigational systemic therapies is covered in detail. Future directions for probable advances in the near and intermediate term are reviewed.

A Machine Learning Model Based on Unsupervised Clustering Multihabitat to Predict the Pathological Grading of Meningiomas

Purpose

We aim to develop and validate a machine learning model by enhanced MRI to determine the pathological grading of meningiomas with unsupervised clustering image analysis method, which are multihabitat to reflect the inherent heterogeneity of tumors.

Materials and Methods

A total of 120 patients with meningiomas confirmed by postoperative pathology were included in the study, including 60 patients with low-grade meningiomas (WHO grade I) and 60 patients with high-grade meningiomas (WHO grade II and WHO grade III). All patients underwent complete head enhanced magnetic resonance scans before surgery or any anti-tumor treatment. Enrolled patients in the group received surgical resection and obtained postoperative pathological data. The patients in the training group (84 people) and the test group (36 people) were randomly divided into two groups according to the ratio of 7 to 3. Multi-habitat features were extracted from MRI images based on enhanced T1. Machine learning method was used to model, which was used to distinguish high-grade meningioma from low-grade meningioma. At the same time, the obtained machine learning model was calibrated and evaluated.

Results

In patients with low-grade meningioma and high-grade meningioma, we found significant differences in Silhouette coefficient (P<0.05). In the machine learning model, the area under the curve was 0.838 in the training group (sensitivity, 67.65%; specificity, 88.82%) and 0.73 in the test group (sensitivity, 69.05%; specificity, 71.43%). After the analysis of calibration curve and decision curve analysis, the model had shown the potential of great application value.

Conclusions

Multi-habitat analysis based on enhanced MRI (T1) could accurately predict the pathological grading of meningiomas. This unsupervised image-based method could reflect the direct heterogeneity between high-grade meningiomas and low-grade meningiomas, which is of great significance for patients' treatment and prevention of recurrence.

Matched Paired Primary and Recurrent Meningiomas Points to Cell-Death Program Contributions to Genomic and Epigenomic Instability along Tumor Progression

Meningioma (MN) is an important cause of disability, and predictive tools for estimating the risk of recurrence are still scarce. The need for objective and cost-effective techniques addressed to this purpose is well known. In this study, we present methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) as a friendly method for deepening the understanding of the mechanisms underlying meningioma progression. A large follow-up allowed us to obtain 50 samples, which included the primary tumor of 20 patients in which half of them are suffering one recurrence and the other half are suffering more than one. We histologically characterized the samples and performed MS-MLPA assays validated by FISH to assess their copy number alterations (CNA) and epigenetic status. Interestingly, we determined the increase in tumor instability with higher values of CNA during the progression accompanied by an increase in epigenetic damage. We also found a loss of HIC1 and the hypermethylation of CDKN2B and PTEN as independent prognostic markers. Comparison between grade 1 and higher primary MN's self-evolution pointed to a central role of GSTP1 in the first stages of the disease. Finally, a high rate of alterations in genes that are related to apoptosis and autophagy, such as DAPK1, PARK2, BCL2, FHIT, or VHL, underlines an important influence on cell-death programs through different pathways.

Molecular determinants of outcomes in meningiomas

Meningiomas are the most common intracranial primary tumor in adults. Surgery is the predominant therapeutic modality for symptomatic meningiomas. Although the majority of meningiomas are benign, there exists a subset of meningiomas that are clinically aggressive. Recent advances in genetics and epigenetics have uncovered molecular alterations that drive tumor meningioma biology with prognostic and therapeutic implications. In this review, we will discuss the advances on molecular determinants of therapeutic response in meningiomas to date and discuss findings of targeted therapies in meningiomas.

A paediatric dysembryoplastic neuroepithelial tumour (DNET) with deregulated stem cell markers: a case report

BACKGROUND

Dysembryoplastic neuroepithelial tumours (DNETs) are rare, with only a few reported lethal cases. Currently, there are focused efforts by neuro-oncology professionals to reveal the molecular characterisations of individual central nervous system tumours (CNSTs). Here, we report the status of cancer stem cell (CSC) genes associated with resilience and drug resistance in a paediatric DNET, since the deregulations and variations of CSC genes may prove critical to these tumours' molecular characterisations.

CASE DESCRIPTION

Immunofluorescence, clonogenic assay and whole exome sequencing (WES) were applied to the patient's tissue and its corresponding cell line. The case is for of a 6-year-old boy with intractable epilepsy and unremarkable physical and neurological examinations. Following magnetic resonance imaging (MRI) and histopathological tests, the patient was diagnosed with DNET. The child underwent a right posterior temporoparietooccipital neuronavigation-assisted craniotomy. Several CSC markers were upregulated in situ, including the metastasis-related protein, anterior gradient 2 (AGR2; 67%), and the Wnt-signalling-related protein, frizzled class receptor 9 (FZD9; 79%). The cell line possessed a similar DNA profile as the original tissue, stained positive for the tumorigenic marker [BMI1 proto-oncogene (BMI)] and CSC markers, and displayed drug resistance. Variants identified in the tissue DNA, which are listed in the catalogue of somatic mutations in cancer (COSMIC) database for genes previously known to be necessary for the development of the embryonic brain, included variants in the cell division cycle 27 (CDC27) gene.

CONCLUSIONS

we report the in situ and in vitro presence of CSCs in a paediatric DNET.

Single-cell profiling of human dura and meningioma reveals cellular meningeal landscape and insights into meningioma immune response

BACKGROUND

Recent investigations of the meninges have highlighted the importance of the dura layer in central nervous system immune surveillance beyond a purely structural role. However, our understanding of the meninges largely stems from the use of pre-clinical models rather than human samples.

METHODS

Single-cell RNA sequencing of seven non-tumor-associated human dura samples and six primary meningioma tumor samples (4 matched and 2 non-matched) was performed. Cell type identities, gene expression profiles, and T cell receptor expression were analyzed. Copy number variant (CNV) analysis was performed to identify putative tumor cells and analyze intratumoral CNV heterogeneity. Immunohistochemistry and imaging mass cytometry was performed on selected samples to validate protein expression and reveal spatial localization of select protein markers.

RESULTS

In this study, we use single-cell RNA sequencing to perform the first characterization of both non-tumor-associated human dura and primary meningioma samples. First, we reveal a complex immune microenvironment in human dura that is transcriptionally distinct from that of meningioma. In addition, we characterize a functionally diverse and heterogenous landscape of non-immune cells including endothelial cells and fibroblasts. Through imaging mass cytometry, we highlight the spatial relationship among immune cell types and vasculature in non-tumor-associated dura. Utilizing T cell receptor sequencing, we show significant TCR overlap between matched dura and meningioma samples. Finally, we report copy number variant heterogeneity within our meningioma samples.

CONCLUSIONS

Our comprehensive investigation of both the immune and non-immune cellular landscapes of human dura and meningioma at single-cell resolution builds upon previously published data in murine models and provides new insight into previously uncharacterized roles of human dura.

Meningioma DNA methylation groups identify biological drivers and therapeutic vulnerabilities

Meningiomas are the most common primary intracranial tumors. There are no effective medical therapies for meningioma patients, and new treatments have been encumbered by limited understanding of meningioma biology. Here, we use DNA methylation profiling on 565 meningiomas integrated with genetic, transcriptomic, biochemical, proteomic and single-cell approaches to show meningiomas are composed of three DNA methylation groups with distinct clinical outcomes, biological drivers and therapeutic vulnerabilities. Merlin-intact meningiomas (34%) have the best outcomes and are distinguished by NF2/Merlin regulation of susceptibility to cytotoxic therapy. Immune-enriched meningiomas (38%) have intermediate outcomes and are distinguished by immune infiltration, HLA expression and lymphatic vessels. Hypermitotic meningiomas (28%) have the worst outcomes and are distinguished by convergent genetic and epigenetic mechanisms driving the cell cycle and resistance to cytotoxic therapy. To translate these findings into clinical practice, we show cytostatic cell cycle inhibitors attenuate meningioma growth in cell culture, organoids, xenografts and patients.

Potential Therapeutic Applications of N-Cadherin Antagonists and Agonists

This review focuses on the cell adhesion molecule (CAM), known as neural (N)-cadherin (CDH2). The molecular basis of N-cadherin-mediated intercellular adhesion is discussed, as well as the intracellular signaling pathways regulated by this CAM. N-cadherin antagonists and agonists are then described, and several potential therapeutic applications of these intercellular adhesion modulators are considered. The usefulness of N-cadherin antagonists in treating fibrotic diseases and cancer, as well as manipulating vascular function are emphasized. Biomaterials incorporating N-cadherin modulators for tissue regeneration are also presented. N-cadherin antagonists and agonists have potential for broad utility in the treatment of numerous maladies.

Multiple approaches converge on three biological subtypes of meningioma and extract new insights from published studies

One-fifth of meningiomas classified as benign by World Health Organization (WHO) histopathological grading will behave malignantly. To better diagnose these tumors, several groups turned to DNA methylation, whereas we combined RNA-sequencing (RNA-seq) and cytogenetics. Both approaches were more accurate than histopathology in identifying aggressive tumors, but whether they revealed similar tumor types was unclear. We therefore performed unbiased DNA methylation, RNA-seq, and cytogenetic profiling on 110 primary meningiomas WHO grade I and II). Each technique distinguished the same three groups (two benign and one malignant) as our previous molecular classification; integrating these methods into one classifier further improved accuracy. Computational modeling revealed strong correlations between transcription and cytogenetic changes, particularly loss of chromosome 1p, in malignant tumors. Applying our classifier to data from previous studies also resolved certain anomalies entailed by grouping tumors by WHO grade. Accurate classification will therefore elucidate meningioma biology as well as improve diagnosis and prognosis.

Spatial heterogeneity in DNA methylation and chromosomal alterations in diffuse gliomas and meningiomas

Adult-type diffuse gliomas and meningiomas are the most common primary intracranial tumors of the central nervous system. DNA methylation profiling is a novel diagnostic technique increasingly used also in the clinic. Although molecular heterogeneity is well described in these tumors, DNA methylation heterogeneity is less studied. We therefore investigated the intratumor genetic and epigenetic heterogeneity in diffuse gliomas and meningiomas, with focus on potential clinical implications. We further investigated tumor purity as a source for heterogeneity in the tumors. We analyzed genome-wide DNA methylation profiles generated from 126 spatially separated tumor biopsies from 39 diffuse gliomas and meningiomas. Moreover, we evaluated five methods for measurement of tumor purity and investigated intratumor heterogeneity by assessing DNA methylation-based classification, chromosomal copy number alterations and molecular markers. Our results demonstrated homogeneous methylation-based classification of IDH-mutant gliomas and further corroborates subtype heterogeneity in glioblastoma IDH-wildtype and high-grade meningioma patients after excluding samples with low tumor purity. We detected a large number of differentially methylated CpG sites within diffuse gliomas and meningiomas, particularly in tumors of higher grades. The presence of CDKN2A/B homozygous deletion differed in one out of two patients with IDH-mutant astrocytomas, CNS WHO grade 4. We conclude that diffuse gliomas and high-grade meningiomas are characterized by intratumor heterogeneity, which should be considered in clinical diagnostics and in the assessment of methylation-based and molecular markers.

Differentiating atypical meningioma from anaplastic meningioma using diffusion weighted imaging

PURPOSE

To explore the value of MRI conventional features and apparent diffusion coefficient (ADC) on the differential diagnosis of atypical meningioma (AtM) and anaplastic meningioma (AnM).

MATERIALS AND METHODS

This retrospective study analyzed the preoperative clinical data, MRI conventional features, and DWI data of 55 AtM and 25 AnM confirmed by pathology in our hospital. The clinical features, MRI conventional features, ADCmean, ADCmin, and relative ADC (rADC) values were compared between the two tumors by Chi-square test or an independent sample t-test. Receiver operating characteristic curve (ROC) and binary logistic regression analysis were used to evaluate the diagnostic efficacy of each parameter to differentiate between these tumors.

RESULTS

The MRI conventional features had a certain ability to distinguish AnM and AtM, with an area under the curve value (AUC) of 0.824 (95% CI, 0.723-0.900). The ADCmean, ADCmin, and rADC values were significantly higher in AtM compared to AnM (all P < 0.05). ADCmean had the best identification effect with an AUC of 0.867 (95% CI, 0.772-0.933) among them, at an cut-off of 0.817 × 10^-3 mm²/s, the sensitivity and specificity of distinguishing AtM from AnM were 78.18% and 88.00%, respectively. A combination of ADCmean and MRI conventional features showed the optimum discrimination ability for the two tumors, the AUC, sensitivity, specificity, and accuracy were 0.918 (95% CI, 0.835-0.967), 80.00%, 94.55%, and 90.00%, respectively.

CONCLUSION

MRI conventional features combined with ADCmean, as a non-invasive method, has potential clinical value in the preoperative diagnosis of AtM and AnM.

Cell-of-Origin and Genetic, Epigenetic, and Microenvironmental Factors Contribute to the Intra-Tumoral Heterogeneity of Pediatric Intracranial Ependymoma

Intra-tumoral heterogeneity (ITH) is a complex multifaceted phenomenon that posits major challenges for the clinical management of cancer patients. Genetic, epigenetic, and microenvironmental factors are concurrent drivers of diversity among the distinct populations of cancer cells. ITH may also be installed by cancer stem cells (CSCs), that foster unidirectional hierarchy of cellular phenotypes or, alternatively, shift dynamically between distinct cellular states. Ependymoma (EPN), a molecularly heterogeneous group of tumors, shows a specific spatiotemporal distribution that suggests a link between ependymomagenesis and alterations of the biological processes involved in embryonic brain development. In children, EPN most often arises intra-cranially and is associated with an adverse outcome. Emerging evidence shows that EPN displays large intra-patient heterogeneity. In this review, after touching on EPN inter-tumoral heterogeneity, we focus on the sources of ITH in pediatric intra-cranial EPN in the framework of the CSC paradigm. We also examine how single-cell technology has shed new light on the complexity and developmental origins of EPN and the potential impact that this understanding may have on the therapeutic strategies against this deadly pediatric malignancy.

Receptor Tyrosine Kinases as Candidate Prognostic Biomarkers and Therapeutic Targets in Meningioma

Meningioma (MGM) is the most common type of intracranial tumor in adults. The validation of novel prognostic biomarkers to better inform tumor stratification and clinical prognosis is urgently needed. Many molecular and cellular alterations have been described in MGM tumors over the past few years, providing a rational basis for the identification of biomarkers and therapeutic targets. The role of receptor tyrosine kinases (RTKs) as oncogenes, including those of the ErbB family of receptors, has been well established in several cancer types. Here, we review histological, molecular, and clinical evidence suggesting that RTKs, including the epidermal growth factor receptor (EGFR, ErbB1), as well as other members of the ErbB family, may be useful as biomarkers and therapeutic targets in MGM.

Machine Learning Using Multiparametric Magnetic Resonance Imaging Radiomic Feature Analysis to Predict Ki-67 in World Health Organization Grade I Meningiomas

BACKGROUND

Although World Health Organization (WHO) grade I meningiomas are considered "benign" tumors, an elevated Ki-67 is one crucial factor that has been shown to influence tumor behavior and clinical outcomes. The ability to preoperatively discern Ki-67 would confer the ability to guide surgical strategy.

OBJECTIVE

In this study, we develop a machine learning (ML) algorithm using radiomic feature analysis to predict Ki-67 in WHO grade I meningiomas.

METHODS

A retrospective analysis was performed for a cohort of 306 patients who underwent surgical resection of WHO grade I meningiomas. Preoperative magnetic resonance imaging was used to perform radiomic feature extraction followed by ML modeling using least absolute shrinkage and selection operator wrapped with support vector machine through nested cross-validation on a discovery cohort (n = 230), to stratify tumors based on Ki-67 <5% and ≥5%. The final model was independently tested on a replication cohort (n = 76).

RESULTS

An area under the receiver operating curve (AUC) of 0.84 (95% CI: 0.78-0.90) with a sensitivity of 84.1% and specificity of 73.3% was achieved in the discovery cohort. When this model was applied to the replication cohort, a similar high performance was achieved, with an AUC of 0.83 (95% CI: 0.73-0.94), sensitivity and specificity of 82.6% and 85.5%, respectively. The model demonstrated similar efficacy when applied to skull base and nonskull base tumors.

CONCLUSION

Our proposed radiomic feature analysis can be used to stratify WHO grade I meningiomas based on Ki-67 with excellent accuracy and can be applied to skull base and nonskull base tumors with similar performance achieved.

Human TERT Promoter Mutations in Atypical and Anaplastic Meningiomas

Background: The role of telomerase reverse transcriptase (TERT) gene promoter mutations (pTERT) in atypical and anaplastic meningiomas remains controversial. This study aimed to evaluate their impact on the histologic diagnosis and prognosis in a retrospective series of 74 patients with atypical and anaplastic meningioma, including disease progression and relapse. A supplementary panel of 21 benign tumours was used as a control cohort. Materials and Methods: The mutation rate of the pTERT gene was assessed by Sanger sequencing. ATRX protein expression was detected by immunohistochemistry. The phenotypic and genotypic intra-tumour heterogeneity was studied in a sub-group of 12 cases using a Molecular Machines & Industries (MMI) CellCut laser microdissection (LMD) system. Results: pTERT mutations were detected in 12/74 (17.6%) malignant meningiomas. The mutation rate was significantly higher in anaplastic meningiomas (7/23, 30.4%) compared to atypical tumours (5/48, 10.4%) (p = 0.0443). In contrast, the mutation rate was < 5% in benign tumours. All pTERT mutant cases retained nuclear ATRX immunoreactivity. pTERT mutations were significantly associated with the histologic grade (p = 0.0443) and were adverse prognostic factors for anaplastic tumours (p = 0.06). Conclusion: We reported on the pTERT mutation spectrum in malignant meningiomas, supporting their use in the prognostic classification.

Biomarkers for differentiating grade II meningiomas from grade I: a systematic review

INTRODUCTION

There are a number of prognostic markers (methylation, CDKN2A/B) described to be useful for the stratification of meningiomas. However, there are currently no clinically validated biomarkers for the preoperative prediction of meningioma grade, which is determined by the histological analysis of tissue obtained from surgery. Accurate preoperative biomarkers would inform the pre-surgical assessment of these tumours, their grade and prognosis and refine the decision-making process for treatment. This review is focused on the more controversial grade II tumours, where debate still surrounds the need for adjuvant therapy, repeat surgery and frequency of follow up.

METHODS

We evaluated current literature for potential grade II meningioma clinical biomarkers, focusing on radiological, biochemical (blood assays) and immunohistochemical markers for diagnosis and prognosis, and how they can be used to differentiate them from grade I meningiomas using the post-2016 WHO classification. To do this, we conducted a PUBMED, SCOPUS, OVID SP, SciELO, and INFORMA search using the keywords; 'biomarker', 'diagnosis', 'atypical', 'meningioma', 'prognosis', 'grade I', 'grade 1', 'grade II' and 'grade 2'.

RESULTS

We identified 1779 papers, 20 of which were eligible for systematic review according to the defined inclusion and exclusion criteria. From the review, we identified radiological characteristics (irregular tumour shape, tumour growth rate faster than 3cm³/year, high peri-tumoural blood flow), blood markers (low serum TIMP1/2, high serum HER2, high plasma Fibulin-2) and histological markers (low H3K27me3, low SMARCE1, low AKAP12, high ARIDB4) that may aid in differentiating grade II from grade I meningiomas.

CONCLUSION

Being able to predict meningioma grade at presentation using the radiological and blood markers described may influence management as the likely grade II tumours will be followed up or treated more aggressively, while the histological markers may prognosticate progression or post-treatment recurrence. This to an extent offers a more personalised treatment approach for patients.

Advancing Drug Discovery for Neurological Disorders Using iPSC-Derived Neural Organoids

In the last decade, different research groups in the academic setting have developed induced pluripotent stem cell-based protocols to generate three-dimensional, multicellular, neural organoids. Their use to model brain biology, early neural development, and human diseases has provided new insights into the pathophysiology of neuropsychiatric and neurological disorders, including microcephaly, autism, Parkinson’s disease, and Alzheimer’s disease. However, the adoption of organoid technology for large-scale drug screening in the industry has been hampered by challenges with reproducibility, scalability, and translatability to human disease. Potential technical solutions to expand their use in drug discovery pipelines include Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) to create isogenic models, single-cell RNA sequencing to characterize the model at a cellular level, and machine learning to analyze complex data sets. In addition, high-content imaging, automated liquid handling, and standardized assays represent other valuable tools toward this goal. Though several open issues still hamper the full implementation of the organoid technology outside academia, rapid progress in this field will help to prompt its translation toward large-scale drug screening for neurological disorders.

Fibulin-2: A Novel Biomarker for Differentiating Grade II from Grade I Meningiomas

There is an unmet need for the identification of biomarkers to aid in the diagnosis, clinical management, prognosis and follow-up of meningiomas. There is currently no consensus on the optimum management of WHO grade II meningiomas. In this study, we identified the calcium binding extracellular matrix glycoprotein, Fibulin-2, via mass-spectrometry-based proteomics, assessed its expression in grade I and II meningiomas and explored its potential as a grade II biomarker. A total of 87 grade I and 91 grade II different meningioma cells, tissue and plasma samples were used for the various experimental techniques employed to assess Fibulin-2 expression. The tumours were reviewed and classified according to the 2016 edition of the Classification of the Tumours of the central nervous system (CNS). Mass spectrometry proteomic analysis identified Fibulin-2 as a differentially expressed protein between grade I and II meningioma cell cultures. Fibulin-2 levels were further evaluated in meningioma cells using Western blotting and Real-time Quantitative Polymerase Chain Reaction (RT-qPCR); in meningioma tissues via immunohistochemistry and RT-qPCR; and in plasma via Enzyme-Linked Immunosorbent Assay (ELISA). Proteomic analyses (p < 0.05), Western blotting (p < 0.05) and RT-qPCR (p < 0.01) confirmed significantly higher Fibulin-2 (FBLN2) expression levels in grade II meningiomas compared to grade I. Fibulin-2 blood plasma levels were also significantly higher in grade II meningioma patients compared to grade I patients. This study suggests that elevated Fibulin-2 might be a novel grade II meningioma biomarker, when differentiating them from the grade I tumours. The trend of Fibulin-2 expression observed in plasma may serve as a useful non-invasive biomarker.