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CNS Neuroscience & Therapeutics Jun 2024Programmed death-ligand 1 (PD-L1) expression is an immune evasion mechanism that has been demonstrated in many tumors and is commonly associated with a poor prognosis....
INTRODUCTION
Programmed death-ligand 1 (PD-L1) expression is an immune evasion mechanism that has been demonstrated in many tumors and is commonly associated with a poor prognosis. Over the years, anti-PD-L1 agents have gained attention as novel anticancer therapeutics that induce durable tumor regression in numerous malignancies. They may be a new treatment choice for neurofibromatosis type 2 (NF2) patients.
AIMS
The aims of this study were to detect the expression of PD-L1 in NF2-associated meningiomas, explore the effect of PD-L1 downregulation on tumor cell characteristics and T-cell functions, and investigate the possible pathways that regulate PD-L1 expression to further dissect the possible mechanism of immune suppression in NF2 tumors and to provide new treatment options for NF2 patients.
RESULTS
PD-L1 is heterogeneously expressed in NF2-associated meningiomas. After PD-L1 knockdown in NF2-associated meningioma cells, tumor cell proliferation was significantly inhibited, and the apoptosis rate was elevated. When T cells were cocultured with siPD-L1-transfected NF2-associated meningioma cells, the expression of CD69 on both CD4 and CD8 T cells was partly reversed, and the capacity of CD8 T cells to kill siPD-L1-transfected tumor cells was partly restored. Results also showed that the PI3K-AKT-mTOR pathway regulates PD-L1 expression, and the mTOR inhibitor rapamycin rapidly and persistently suppresses PD-L1 expression. In vivo experimental results suggested that anti-PD-L1 antibody may have a synergetic effect with the mTOR inhibitor in reducing tumor cell proliferation and that reduced PD-L1 expression could contribute to antitumor efficacy.
CONCLUSIONS
Targeting PD-L1 could be helpful for restoring the function of tumor-infiltrating lymphocytes and inducing apoptosis to inhibit tumor proliferation in NF2-associated meningiomas. Dissecting the mechanisms of the PD-L1-driven tumorigenesis of NF2-associated meningioma will help to improve our understanding of the mechanisms underlying tumor progression and could facilitate further refinement of current therapies to improve the treatment of NF2 patients.
Topics: Meningioma; Humans; B7-H1 Antigen; Cell Proliferation; Meningeal Neoplasms; Animals; T-Lymphocytes; Neurofibromatosis 2; Mice; Male; Female; Neurofibromin 2; Cell Line, Tumor; Middle Aged; Mice, Nude; Apoptosis
PubMed: 38828669
DOI: 10.1111/cns.14784 -
Interventional Neuroradiology : Journal... May 2024The artery of Bernasconi and Cassinari is a small infraclinoid branch of the internal carotid artery that originates from its cavernous segment and then runs along the...
The artery of Bernasconi and Cassinari is a small infraclinoid branch of the internal carotid artery that originates from its cavernous segment and then runs along the tentorium. Because of its gracile appearance, it is often visible only when related to neoplasms and vascular lesions in the tentorial regions. Dural arteriovenous fistulas (dAVFs) are arteriovenous shunts contained within the dural leaflets, supplied largely by the regional meningeal arteries and classified based on the type of venous drainage. Tentorial dAVFs are mostly supplied by branches of the meningohypophyseal trunk, including the artery of Bernasconi and Cassinari. Unlike fistulas of other locations, tentorial fistulas are linked with a higher risk for venous hypertension and hemorrhage and thus demand immediate and appropriate treatment. Digital subtraction angiography is necessary to understand its arterial and venous components. Treatment aims to achieve complete embolization of the fistulous connection and venous portions by either a transarterial or transvenous approach, without causing serious changes in the flow dynamics..
PubMed: 38819369
DOI: 10.1177/15910199241258656 -
Acta Neurochirurgica May 2024
Topics: Humans; Meningioma; Exophthalmos; Meningeal Neoplasms; Postoperative Complications; Sphenoid Bone; Orbital Neoplasms
PubMed: 38816513
DOI: 10.1007/s00701-024-06141-8 -
Journal of Neuro-oncology Jul 2024Accurate classification of cancer subgroups is essential for precision medicine, tailoring treatments to individual patients based on their cancer subtypes. In recent...
PURPOSE
Accurate classification of cancer subgroups is essential for precision medicine, tailoring treatments to individual patients based on their cancer subtypes. In recent years, advances in high-throughput sequencing technologies have enabled the generation of large-scale transcriptomic data from cancer samples. These data have provided opportunities for developing computational methods that can improve cancer subtyping and enable better personalized treatment strategies.
METHODS
Here in this study, we evaluated different feature selection schemes in the context of meningioma classification. To integrate interpretable features from the bulk (n = 77 samples) and single-cell profiling (∼ 10 K cells), we developed an algorithm named CLIPPR which combines the top-performing single-cell models, RNA-inferred copy number variation (CNV) signals, and the initial bulk model to create a meta-model.
RESULTS
While the scheme relying solely on bulk transcriptomic data showed good classification accuracy, it exhibited confusion between malignant and benign molecular classes in approximately ∼ 8% of meningioma samples. In contrast, models trained on features learned from meningioma single-cell data accurately resolved the sub-groups confused by bulk-transcriptomic data but showed limited overall accuracy. CLIPPR showed superior overall accuracy and resolved benign-malignant confusion as validated on n = 789 bulk meningioma samples gathered from multiple institutions. Finally, we showed the generalizability of our algorithm using our in-house single-cell (∼ 200 K cells) and bulk TCGA glioma data (n = 711 samples).
CONCLUSION
Overall, our algorithm CLIPPR synergizes the resolution of single-cell data with the depth of bulk sequencing and enables improved cancer sub-group diagnoses and insights into their biology.
Topics: Humans; Single-Cell Analysis; Meningeal Neoplasms; Meningioma; Sequence Analysis, RNA; Algorithms; DNA Copy Number Variations; Biomarkers, Tumor; High-Throughput Nucleotide Sequencing; Transcriptome; Gene Expression Profiling
PubMed: 38811523
DOI: 10.1007/s11060-024-04710-6 -
Neurosurgical Review May 2024To analyze the correlation of KI-67-Proliferation Index (KI-67-PI) with preoperative patients and MRI characteristics, WHO grading, histological subtype and...
A comprehensive correlation of the KI-67 proliferation index to patient´s, imaging and tumor features and its value in predicting long-term course of patients with newly diagnosed intracranial meningiomas.
To analyze the correlation of KI-67-Proliferation Index (KI-67-PI) with preoperative patients and MRI characteristics, WHO grading, histological subtype and long-term-course of patients with newly diagnosed intracranial meningiomas (IM). In this single-center retrospective study, all consecutive patients with IM were analyzed from January 2007 to August 2019. Patient´s demographics (age, sex), imaging parameters (location, volume, edema, necrosis), and tumor features (WHO grade, histology) were assessed and correlated with KI-67-PI. Long-term data were retrieved from patient's last follow-up visits. This study included 463 IM in 457 surgically treated patients. Males exhibited a higher KI-67-PI than females (7.31 ± 0.22 vs. 5.37 ± 0.53; p < 0.01, Mann-Whitney U Test). Age positively correlated with KI-67-PI in both sexes (p < 0.01, Spearman), with older patients having a higher KI-67-PI. KI-67-PI was significantly higher in convexity IM compared to frontobasal IM (7.15 ± 5.56 vs. 4.66 ± 2.94; p < 0.05, ANOVA, Tukey´s HSD), while no difference in KI-67-PI expression was found when other locations were compared to each other (Tukey´s HSD). Higher KI-67-PI was significantly correlated with larger tumor volume (p < 0.01, Spearman), larger tumor necrosis and larger peritumoral edema (p < 0.01, Kruskal-Wallis). Patients with recurrent IM had a significantly higher KI-67-PI than patients without recurrence (8.24 ± 5.88 vs. 5.14 ± 3.53; p < 0.01, ANOVA, Tukey´s HSD) during a mean follow-up period of 80.92 ± 38.1 months. Atypical and anaplastic IM exhibited significantly higher KI-67-PI compared to all other WHO grade 1 histological subtypes (12.09 ± 0.73 vs. 4.51 ± 0.13; p < 0.01, Kruskal-Wallis test) and KI-67-PI was significantly higher in anaplastic IM compared to atypical meningioma (19.67 ± 1.41 vs. 11.01 ± 0.38; p < 0.01, ANOVA). Higher KI-67-PI is not only associated with atypical and anaplastic subtypes of IM, but is also significantly higher in males, positively correlates with patients age, larger tumor volume, lager peritumoral edema and necrosis on preoperative MRI and predicts tumor recurrence. Therefore, KI-67-PI may serve as a decision indicator for adjuvant treatment in patients with IM.
Topics: Humans; Meningioma; Male; Female; Ki-67 Antigen; Middle Aged; Adult; Aged; Meningeal Neoplasms; Retrospective Studies; Magnetic Resonance Imaging; Young Adult; Aged, 80 and over; Cell Proliferation; Adolescent
PubMed: 38806958
DOI: 10.1007/s10143-024-02485-y -
Neurosurgical Review May 2024Meningioma is the most common type of primary brain tumor which presents with a variety of neurological manifestations. Surgical resection tends to be the preferred... (Meta-Analysis)
Meta-Analysis Review
Meningioma is the most common type of primary brain tumor which presents with a variety of neurological manifestations. Surgical resection tends to be the preferred treatment. The occurrence of seizures after resection is common, which occur either early, within seven days of operation, or late. Our meta-analysis investigated the possible predictors of early and late postoperative seizures. We assessed the relevant observational studies on predictors of postoperative seizures published in PubMed, Scopus, and Web of Science from January 2000 to September 2022, and those that met inclusion criteria were included. We calculated the association between potential predicting factors and postoperative seizures, odds ratios (ORs) with 95% confidence intervals (CIs) applying either random or fixed-effect models. The early and late postoperative seizures were evaluated individually. Thirteen observational studies involving 4176 patients were included. Seizures occurred in 250 (6%) and 584 (14%) patients, respectively, in the early and late postoperative phases. Shared predictors for early and late seizures included tumors involving the motor cortex (OR = 2.7; 95% CI: 1.67-4.38, OR = 2.46; 95% CI: 1.68-3.61), postoperative neurological deficit (OR = 4.68; 95% CI: 2.67-8.22, OR = 2.01; 95% CI: 1.39-2.92), and preoperative seizures (OR = 2.52; 95% CI: 1.82-3.49, OR = 4.35; 95% CI: 3.29-5.75). Peritumoral edema (OR = 1.99; 95% CI: 1.49-2.64) was a significant factor only among late postoperative seizure patients while surgical complications (OR = 3.77; 95% CI: 2.39-5.93) was a significant factor solely for early postoperative seizures. Meningioma patients commonly experience early and late postoperative seizures. Identifying predictors of postoperative seizures is essential to diagnose and manage them effectively.
Topics: Meningioma; Humans; Seizures; Postoperative Complications; Meningeal Neoplasms; Neurosurgical Procedures
PubMed: 38806755
DOI: 10.1007/s10143-024-02487-w -
Annals of Clinical and Laboratory... Mar 2024Meningioma is the most common primary adult intracranial neoplasm, and proliferation indices (PI) rise with increasing grade from WHO CNS grade 1 to 3. Ki-67... (Review)
Review
OBJECTIVE
Meningioma is the most common primary adult intracranial neoplasm, and proliferation indices (PI) rise with increasing grade from WHO CNS grade 1 to 3. Ki-67 immunohistochemistry (IHC) poses a variety of technical and interpretative challenges. Here, we specifically investigated the staining intensity and its effect on interpretation and final diagnosis.
METHODS
124 high and low-grade meningiomas of various grades were blindly evaluated using different counting strategies (CS) based on the staining intensity of the nuclei as darkest (CS1), darkest+intermediate (CS2), and any staining (CS3) in hot-spots (HS) and in the context of overall proliferative activity (OPA).
RESULT
CSs in HS, OPA, and their average results were significantly different between low-grade and high-grade groups. PI obtained using CS3 yielded results that matched best with values expected for the corresponding WHO grade. CS had a profound impact on whether a LG meningioma would be diagnosed as one with a "high proliferation index."
CONCLUSION
A large body of work exists on the counting methods, clinically significant cut-off values, and inter- and intra-observer variability for Ki-67 PI interpretation. We show that Ki-67 IHC staining intensity, which to our knowledge has not been previously systematically investigated, can have a significant effect on PI interpretation in settings that influence diagnostic and clinical management decisions.
Topics: Humans; Meningioma; Ki-67 Antigen; Cell Proliferation; Meningeal Neoplasms; Immunohistochemistry; Neoplasm Grading; Female; Staining and Labeling; Male; Middle Aged; Aged; Adult; Mitotic Index
PubMed: 38802155
DOI: No ID Found -
Genes, Chromosomes & Cancer May 2024Meningiomas are non-glial tumors that are the most common primary brain tumors in adults. Although meningioma can possibly be cured with surgical excision, variations in... (Review)
Review
Meningiomas are non-glial tumors that are the most common primary brain tumors in adults. Although meningioma can possibly be cured with surgical excision, variations in atypical/anaplastic meningioma have a high recurrence rate and a poor prognosis. As a result, it is critical to develop novel therapeutic options for high-grade meningiomas. This review highlights the current histology of meningiomas, prevalent genetic and molecular changes, and the most extensively researched signaling pathways and therapies in meningiomas. It also reviews current clinical studies and novel meningioma treatments, including immunotherapy, microRNAs, cancer stem cell methods, and targeted interventions within the glycolysis pathway. Through the examination of the complex landscape of meningioma biology and the highlighting of promising therapeutic pathways, this review opens the way for future research efforts aimed at improving patient outcomes in this prevalent intracranial tumor entity.
Topics: Humans; Meningioma; Meningeal Neoplasms; MicroRNAs; Immunotherapy; Signal Transduction
PubMed: 38801095
DOI: 10.1002/gcc.23248 -
Neurosurgical Review May 2024This study investigated the value of whole tumor apparent diffusion coefficient (ADC) histogram parameters and magnetic resonance imaging (MRI) semantic features in...
PURPOSE
This study investigated the value of whole tumor apparent diffusion coefficient (ADC) histogram parameters and magnetic resonance imaging (MRI) semantic features in predicting meningioma progesterone receptor (PR) expression.
MATERIALS AND METHODS
The imaging, pathological, and clinical data of 53 patients with PR-negative meningiomas and 52 patients with PR-positive meningiomas were retrospectively reviewed. The whole tumor was outlined using Firevoxel software, and the ADC histogram parameters were calculated. The differences in ADC histogram parameters and MRI semantic features were compared between the two groups. The predictive values of parameters for PR expression were assessed using receiver operating characteristic curves. The correlation between whole-tumor ADC histogram parameters and PR expression in meningiomas was also analyzed.
RESULTS
Grading was able to predict the PR expression in meningiomas (p = 0.012), though the semantic features of MRI were not (all p > 0.05). The mean, Perc.01, Perc.05, Perc.10, Perc.25, and Perc.50 histogram parameters were able to predict meningioma PR expression (all p < 0.05). The predictive performance of the combined histogram parameters improved, and the combination of grade and histogram parameters provided the optimal predictive value, with an area under the curve of 0.849 (95%CI: 0.766-0.911) and sensitivity, specificity, ACC, PPV, and NPV of 73.08%, 81.13%, 77.14%, 79.20%, and 75.40%, respectively. The mean, Perc.01, Perc.05, Perc.10, Perc.25, and Perc.50 histogram parameters were positively correlated with PR expression (all p < 0.05).
CONCLUSION
Whole tumor ADC histogram parameters have additional clinical value in predicting PR expression in meningiomas.
Topics: Humans; Meningioma; Female; Middle Aged; Male; Meningeal Neoplasms; Receptors, Progesterone; Adult; Diffusion Magnetic Resonance Imaging; Aged; Retrospective Studies; Predictive Value of Tests
PubMed: 38795181
DOI: 10.1007/s10143-024-02482-1 -
Cell Genomics Jun 2024Meningiomas, although mostly benign, can be recurrent and fatal. World Health Organization (WHO) grading of the tumor does not always identify high-risk meningioma, and...
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.
Topics: Meningioma; Humans; Transcriptome; Meningeal Neoplasms; Male; Female; Middle Aged; Gene Expression Regulation, Neoplastic; Algorithms; Gene Expression Profiling
PubMed: 38788713
DOI: 10.1016/j.xgen.2024.100566