CGCG clinical practice guidelines for the management of adult diffuse gliomas

An Immune-Related Prognostic Signature for Predicting Clinical Outcomes and Immune Landscape in IDH-Mutant Lower-Grade Gliomas

BACKGROUND

IDH mutation is the most common in diffuse LGGs, correlated with a favorable prognosis. However, the IDH-mutant LGGs patients with poor prognoses need to be identified, and the potential mechanism leading to a worse outcome and treatment options needs to be investigated.

METHODS

A six-gene immune-related prognostic signature in IDH-mutant LGGs was constructed based on two public datasets and univariate, multivariate, and LASSO Cox regression analysis. Patients were divided into low- and high-risk groups based on the median risk score in the training and validation sets. We analyzed enriched pathways and immune cell infiltration, applying the GSEA and the immune evaluation algorithms.

RESULTS

Stratification and multivariate Cox analysis unveiled that the six-gene signature was an independent prognostic factor. The signature (0.806/0.795/0.822) showed a remarkable prognostic performance, with 1-, 3-, and 5-year time-dependent AUC, higher than for grade (0.612/0.638/0.649) and 1p19q codeletion status (0.606/0.658/0.676). High-risk patients had higher infiltrating immune cells. However, the specific immune escape was observed in the high-risk group after immune activation, owing to increasing immunosuppressive cells, inhibitory cytokines, and immune checkpoint molecules. Moreover, a novel nomogram model was developed to evaluate the survival in IDH-mutant LGGs patients.

CONCLUSION

The six-gene signature could be a promising prognostic biomarker, which is promising to promote individual therapy and improve the clinical outcomes of IDH-mutant gliomas. The study also refined the current classification system of IDH-mutant gliomas, classifying patients into two subtypes with distinct immunophenotypes and overall survival.

Molecular Characterization and Clinical Relevance of ANXA1 in Gliomas via 1,018 Chinese Cohort Patients

Annexin A1 (ANXA1) is a calcium-dependent phospholipid-binding protein and has been implicated in multiple functions essential in cancer, including cell proliferation, apoptosis, chemosensitivity, metastasis, and invasion. However, the biological role and clinical behavior of ANXA1 in glioma remain unclear. In this study, RNA-seq (n = 1018 cases) and whole-exome sequencing (WES) (n = 286 cases) data on a Chinese cohort, RNA-seq data with different histological regions of glioblastoma blocks (n = 270 cases), and scRNA-seq data (n = 7630 cells) were used. We used the R software to perform statistical calculations and graph rendering. We found that ANXA1 is closely related to the malignant progression in gliomas. Meanwhile, ANXA1 is significantly associated with clinical behavior. Furthermore, the mutational profile revealed that glioma subtypes classified by ANXA1 expression showed distinct genetic features. Functional analyses suggest that ANXA1 correlates with the immune-related function and cancer hallmark. At a single-cell level, we found that ANXA1 is highly expressed in M2 macrophages and tumor cells of the mesenchymal subtype. Importantly, our result suggested that ANXA1 expression is significant with the patient’s survival outcome. Our study revealed that ANXA1 was closely related to immune response. ANXA1 plays a key factor in M2 macrophages and MES tumor cells. Patients with lower ANXA1 expression levels tended to experience improved survival. ANXA1 may become a valuable factor for the diagnosis and treatment of gliomas in clinical practice.

High Expression of C1ORF112 Predicts a Poor Outcome: A Potential Target for the Treatment of Low-Grade Gliomas

Background: Glioma is the most common primary tumor of the central nervous system and is associated with poor overall survival, creating an urgent need to identify survival-associated biomarkers. C1ORF112, an alpha-helical protein, is overexpressed in some cancers; however, its prognostic role has not yet been explored in gliomas. Thus, in this study, we attempted to address this by determining the prognostic value and potential function of C1ORF112 in low-grade gliomas (LGGs).

Methods: The expression of C1ORF112 in normal and tumor tissues was analyzed using data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Oncomine, and Rembrandt databases. The genetic changes of C1ORF112 in LGG were analyzed using cBioPortal. Survival analysis was used to evaluate the relationship between C1ORF112 expression and survival in patients with LGG. Correlation between immune infiltration and C1ORF112 expression was determined using Timer software. Additionally, data from three online platforms were integrated to identify the co-expressed genes of C1ORF112. The potential biological functions of C1ORF112 were investigated by enrichment analysis.

Results: C1ORF112 mRNA was highly expressed in LGGs (p < 0.01). Area under the ROC curve (AUC) showed that the expression of C1ORF112 in LGG was 0.673 (95% confidence interval [CI] = 0.618–0.728). Kaplan-Meier survival analysis showed that patients with high C1ORF112 expression had lower OS than patients with low C1ORF112 expression (p < 0.05). Multivariate analysis showed that high expression of C1ORF112 was an independent prognostic factor for the overall survival in patients from TCGA and CGGA databases. C1ORF112 expression was positively correlated with six immunoinfiltrating cells (all p < 0.001). The enrichment analysis suggested the enrichment of C1ORF112 and co-expressed genes in cell cycle and DNA replication.

Conclusion: This study suggested that C1ORF112 may be a prognostic biomarker and a potential immunotherapeutic target for LGG.

Integrin Alpha-2 as a Potential Prognostic and Predictive Biomarker for Patients With Lower-Grade Glioma

Diffuse gliomas are the most common malignant brain tumors with the highest mortality and recurrence rate in adults. Integrin alpha-2 (ITGA2) is involved in a series of biological processes, including cell adhesion, stemness regulation, angiogenesis, and immune/blood cell functions. The role of ITGA2 in lower-grade gliomas (LGGs) is not well defined. Firstly, we downloaded RNA sequencing and relevant clinical information from The Cancer Genome Atlas cohort, the Chinese Glioma Genome Atlas cohort, and related immune cohorts. Next, prognosis analysis, difference analysis, clinical model construction, enrichment analysis, and immune infiltration analysis are performed for this study. These analyses indicated that ITGA2 may have clinical application value and research value in LGG immunotherapy. We also detected the mRNA and protein expression of ITGA2 in three LGG cell lines and normal glial cells using quantitative real-time polymerase chain reaction assay and western blot assay. Our study not only offers a novel target for LGG immunotherapy but also can better comprehend the mechanism of the development and progression of patients with LGG. This study revealed that ITGA2 may be a potential prognostic and predictive biomarker for LGG, which can bring new insights into targeted immunotherapy.

FXYD2 mRNA expression represents a new independent factor that affects survival of glioma patients and predicts chemosensitivity of patients to temozolomide

PURPOSE

Glioma is the most common primary intracranial tumor. Owing to the poor prognosis associated with high-grade gliomas, there is an urgent need to identify biomarkers related to prognosis and treatment sensitivity. Here, we analyze the expression of FXYD2 mRNA in gliomas, and explore its clinical prognostic value and significance in this disease.

METHODS

Clinical features, FXYD2 mRNA expression levels, and survival data were analyzed for 516 glioma patients from the Chinese Glioma Genome Map Project, 481 from the cancer genome map datbase and 268 from the molecular braintumor database. The expression patterns for FXYD2 mRNA were compared using the chi-square test, and overall survival (OS) of glioma patients was evaluated according to FXYD2 mRNA expression levels. The factors affecting glioma survival were evaluated by Cox univariate and multivariate regression analysis.

RESULTS

FXYD2 mRNA expression was related to the grade of gliomas. The higher the level, the lower the expression. Meanwhile related to the pathological classification of gliomas. Oligodendroglioma, IDH-mutant and 1p/19q-codeleted was higher than Astrocytoma, IDH-mutant, higher than Glioblastoma, IDH-wildtype. Moreover, temozolomide (TMZ) chemotherapy was found to be an independent factor affecting survival in patients with high FXYD2 mRNA expression, but not in patients with low expression.

CONCLUSION

FXYD2 mRNA expression represents a new independent factor affecting the survival of glioma patients and may serve as an independent prognostic indicator to predict the sensitivity of gliomas to TMZ.

TNFSF13 Is a Novel Onco-Inflammatory Marker and Correlates With Immune Infiltration in Gliomas

Existing therapeutic strategies for gliomas are restricted; hence, exploration for novel diagnostic indicator and treatment is essential. Here, we performed bioinformatic analyses for TNFSF13 (also known as APRIL), a proliferation-inducing ligand of the tumor necrosis factor (TNF) superfamily, aiming to assess its potential for predicting glioma patient’s prognosis and targeted therapy. TNFSF13 expression was upregulated in the increase of tumor grades based on Xiangya cohort. In high TNFSF13 gliomas, somatic mutation was proved to correlate with amplification of EGFR and deletion of CDKN2A; while mutation of IDH1 was more frequently observed in low TNFSF13 group. We also confirmed the positive correlation between TNFSF13 and infiltrating immune and stromal cells in glioma microenvironment. Further, TNFSF13 was found to be involved in immunosuppression via diverse immunoregulation pathways and was associated with other immune checkpoints and inflammation. Single-cell sequencing revealed an abundant expression of TNFSF13 in neoplastic cells and M2 macrophages, which TNFSF13 might potentially regulate the cell communication via IL-8, C3, and CD44. Lastly, TNFSF13 mediated the activities of transcription factors including FOXO3, MEIS2, and IRF8. Our analyses demonstrated the relevance between TNFSF13 and glioma progress and indicated the potential of TNFSF13 as a novel diagnostic onco-inflammatory biomarker and immunotherapy target of gliomas.

Multiomics Analysis Reveals the Prognostic Non-tumor Cell Landscape in Glioblastoma Niches

A comprehensive characterization of non-tumor cells in the niches of primary glioblastoma is not fully established yet. This study aims to present an overview of non-malignant cells in the complex microenvironment of glioblastoma with detailed characterizations of their prognostic effects. We curate 540 gene signatures covering a total of 64 non-tumor cell types. Cell type-specific expression patterns are interrogated by normalized enrichment score across four large gene expression profiling cohorts of glioblastoma with a total number of 967 cases. The glioblastoma multiforms (GBMs) in each cohort are hierarchically clustered into negative or positive immune response classes with significantly different overall survival. Our results show that astrocytes, macrophages, monocytes, NKTs, and MSC are risk factors, while CD8 T cells, CD8 naive T cells, and plasma cells are protective factors. Moreover, we find that the immune system and organogenesis are uniformly enriched in negative immune response clusters, in contrast to the enrichment of nervous system in positive immune response clusters. Mesenchymal differentiation is also observed in the negative immune response clusters. High enrichment status of macrophages in negative immune response clusters is independently validated by analyzing scRNA-seq data from eight high-grade gliomas, revealing that negative immune response samples comprised 46.63 to 55.12% of macrophages, whereas positive immune response samples comprised only 1.70 to 8.12%, with IHC staining of samples from six short-term and six long-term survivors of GBMs confirming the results.

Characterization of METTL7B to Evaluate TME and Predict Prognosis by Integrative Analysis of Multi-Omics Data in Glioma

Glioma is the most common and aggressive type of primary brain malignant tumor with limited treatment approaches. Methyltransferase-like 7B (METTL7B) is associated with the pathogenesis of several diseases but is rarely studied in glioma. In this study, 1,493 glioma samples (data from our cohort, TCGA, and CGGA) expressing METTL7B were used to explore its prognostic value and mechanism in the immune microenvironment. Results showed that high expression of METTL7B is associated with poor prognosis and abundant immunosuppressive cells. Further, functional enrichment showed that METTL7B is involved in the negative regulation of immunity and carcinogenic signaling pathways. Moreover, a METTL7B-related prognostic signature constructed based on multi-omics showed a good prediction of the overall survival (OS) time of glioma patients. In conclusion, METTL7B is a potential prognostic biomarker. In addition, the prognostic prediction model constructed in this study can be used in clinical setups for the development of novel effective therapeutic strategies for glioma patients and improving overall survival.

Construction of Interferon-Gamma-Related Gene Signature to Characterize the Immune-Inflamed Phenotype of Glioblastoma and Predict Prognosis, Efficacy of Immunotherapy and Radiotherapy

Interferon-gamma (IFNG) has profound impacts on tumor-immune interaction and is of great clinical significance for multiple cancers. Exploring the role of IFNG in glioblastoma (GBM) may optimize the current treatment paradigm of this disease. Here, multi-dimensional data of 429 GBM samples were collected. Various bioinformatics algorithms were employed to establish a gene signature that characterizes immunological features, genomic alterations, and clinical characteristics associated with the IFNG response. In this way, a novel IFNG-related gene signature (IFNGrGS, including TGFBI, IL4I1, ACP5, and LUM) has been constructed and validated. Samples with increased IFNGrGS scores were characterized by increased neutrophil and macrophage infiltration and exuberant innate immune responses, while the activated adaptive immune response may be frustrated by multiple immunosuppressive mechanisms. Notably, the IFNG pathway as well as its antagonistic pathways including IL4, IL10, TGF-beta, and VEGF converged on the expression of immune checkpoints. Besides, gene mutations involved in the microenvironment were associated with the IFNGrGS-based stratification, where the heterogeneous prognostic significance of EGFR mutation may be related to the different degrees of IFNG response. Moreover, the IFNGrGS score had solid prognostic value and the potential to screen ICB and radiotherapy sensitive populations. Collectively, our study provided insights into the role of IFNG on the GBM immune microenvironment and offered feasible information for optimizing the treatment of GBM.

Human Mitochondrial Ribosomal RNA Modification-Based Classification Contributes to Discriminate the Prognosis and Immunotherapy Response of Glioma Patients

Background

Epigenetic regulations of the tumor microenvironment (TME) and immunotherapy have been investigated in recent years. Nevertheless, the potential value of mitochondrial ribosomal RNA (mt-rRNA) modification in regulation of the TME and immunotherapy remains unknown.

Methods

We comprehensively investigated the mt-rRNA-modification patterns in glioma patients based on nine regulators of mt-rRNA. Subsequently, these modification patterns were correlated systematically with immunologic characteristics and immunotherapy. An “mt-rRNA predictor” was constructed and validated in multiple publicly available cohorts to provide guidance for prognosis prediction and immunotherapy of glioma patients.

Results

Two distinct patterns of mt-rRNA modification were determined based on the evidence that nine regulators of mt-rRNA correlated significantly with most clinicopathologic characteristics, immunomodulators, TME, immune-checkpoint blockers (ICBs), and prognosis. Patients with mt-rRNA subtype II presented significantly poorer overall survival/progression-free survival (OS/PFS), but higher tumor mutational burden (TMB), more somatic mutations, and copy number variation (CNV). These two mt-rRNA subtypes had distinct TME patterns and responses to ICB therapy. An mt-rRNA predictor was constructed and validated in four glioma cohorts. The subtype with high mt-rRNA score, characterized by increased TMB, infiltration of immune cells, and activation of immunity, suggested an immune-activated phenotype, and was also linked to greater sensitivity to immunotherapy using anti-programmed cell death protein 1 (PD-1) but resistance to temozolomide.

Conclusions

Regulators of mt-rRNA modification have indispensable roles in the complexity and diversity of the TME and prognosis. This novel classification based on patterns of mt-rRNA modification could provide an effective prognostic predictor and guide more appropriate immunotherapy/chemotherapy strategies for glioma patients.

WAC, a novel GBM tumor suppressor, induces GBM cell apoptosis and promotes autophagy

WAC is closely related to the occurrence and development of tumors. However, its role in human glioblastoma (GBM) and its potential regulatory mechanisms have not been investigated. This study demonstrated that WAC is downregulated in GBM, and its low expression predicts a poor prognosis. We investigated the effect of WAC on the proliferation of glioma cells through a CCK-8 assay, EdU incorporation, and cell formation. The effects of WAC on apoptosis and autophagy in glioma were determined by flow cytometry, TUNEL detection, immunofluorescence, q-PCR, WB, and scanning electron microscopy. We found that overexpression of WAC inhibited the proliferation of glioma cells, promoted apoptosis, and induced autophagy. Therefore, WAC is likely to play a role as a new regulatory molecule in glioma.

Establishment of an Immune-Related Gene Signature for Risk Stratification for Patients with Glioma

Glioma is a frequently seen primary malignant intracranial tumor, characterized by poor prognosis. The study is aimed at constructing a prognostic model for risk stratification in patients suffering from glioma. Weighted gene coexpression network analysis (WGCNA), integrated transcriptome analysis, and combining immune-related genes (IRGs) were used to identify core differentially expressed IRGs (DE IRGs). Subsequently, univariate and multivariate Cox regression analyses were utilized to establish an immune-related risk score (IRRS) model for risk stratification for glioma patients. Furthermore, a nomogram was developed for predicting glioma patients' overall survival (OS). The turquoise module (cor = 0.67; P < 0.001) and its genes (n = 1092) were significantly pertinent to glioma progression. Ultimately, multivariate Cox regression analysis constructed an IRRS model based on VEGFA, SOCS3, SPP1, and TGFB2 core DE IRGs, with a C-index of 0.811 (95% CI: 0.786-0.836). Then, Kaplan-Meier (KM) survival curves revealed that patients presenting high risk had a dismal outcome (P < 0.0001). Also, this IRRS model was found to be an independent prognostic indicator of gliomas' survival prediction, with HR of 1.89 (95% CI: 1.252-2.85) and 2.17 (95% CI: 1.493-3.14) in the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets, respectively. We established the IRRS prognostic model, capable of effectively stratifying glioma population, convenient for decision-making in clinical practice.

Identification of Iron Metabolism-Related Genes as Prognostic Indicators for Lower-Grade Glioma

Lower-grade glioma (LGG) is characterized by genetic and transcriptional heterogeneity, and a dismal prognosis. Iron metabolism is considered central for glioma tumorigenesis, tumor progression and tumor microenvironment, although key iron metabolism-related genes are unclear. Here we developed and validated an iron metabolism-related gene signature LGG prognosis. RNA-sequence and clinicopathological data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were downloaded. Prognostic iron metabolism-related genes were screened and used to construct a risk-score model via differential gene expression analysis, univariate Cox analysis, and the Least Absolute Shrinkage and Selection Operator (LASSO)-regression algorithm. All LGG patients were stratified into high- and low-risk groups, based on the risk score. The prognostic significance of the risk-score model in the TCGA and CGGA cohorts was evaluated with Kaplan-Meier (KM) survival and receiver operating characteristic (ROC) curve analysis. Risk- score distributions in subgroups were stratified by age, gender, the World Health Organization (WHO) grade, isocitrate dehydrogenase 1 (IDH1) mutation status, the O6-methylguanine-DNA methyl-transferase (MGMT) promoter-methylation status, and the 1p/19q co-deletion status. Furthermore, a nomogram model with a risk score was developed, and its predictive performance was validated with the TCGA and CGGA cohorts. Additionally, the gene set enrichment analysis (GSEA) identified signaling pathways and pathological processes enriched in the high-risk group. Finally, immune infiltration and immune checkpoint analysis were utilized to investigate the tumor microenvironment characteristics related to the risk score. We identified a prognostic 15-gene iron metabolism-related signature and constructed a risk-score model. High risk scores were associated with an age of > 40, wild-type IDH1, a WHO grade of III, an unmethylated MGMT promoter, and 1p/19q non-codeletion. ROC analysis indicated that the risk-score model accurately predicted 1-, 3-, and 5-year overall survival rates of LGG patients in the both TCGA and CGGA cohorts. KM analysis showed that the high-risk group had a much lower overall survival than the low-risk group (P < 0.0001). The nomogram model showed a strong ability to predict the overall survival of LGG patients in the TCGA and CGGA cohorts. GSEA analysis indicated that inflammatory responses, tumor-associated pathways, and pathological processes were enriched in high-risk group. Moreover, a high risk score correlated with the infiltration immune cells (dendritic cells, macrophages, CD4+ T cells, and B cells) and expression of immune checkpoint (PD1, PDL1, TIM3, and CD48). Our prognostic model was based on iron metabolism-related genes in LGG, can potentially aid in LGG prognosis, and provides potential targets against gliomas.

AEG-1 silencing attenuates M2-polarization of glioma-associated microglia/macrophages and sensitizes glioma cells to temozolomide

Glioma is the most frequent primary malignancy in the brain; temozolomide (TMZ) is the first-line chemotherapeutic agent used to combat this tumor. We showed here that astrocyte elevated gene-1 (AEG-1) was overexpressed in glioma tissues and associated with a worse subtype and a poor prognosis. CCK-8 proliferation assays and clone formation experiments presented that AEG-1 knockdown sensitizes glioma cells to TMZ. The γH2AX foci formation assays indicated that AEG-1 silencing promotes TMZ-induced DNA damage in glioma cells. Glioma-associated microglia/macrophages (GAMs), the largest subpopulation infiltrating glioma, play important roles in the tumor microenvironment. Bioinformatics analyses and functional studies demonstrated that AEG-1 silencing decreased M2-polarization of HMC3 microglia and the secretion of tumor supportive cytokines IL-6 and TGF-β1. The expression of AEG-1 was positively associated with M2 markers in glioma tissues varified by IHC staining. Based on the results of Affymetrix microarray and GSEA analyses, Western blot and Co-Immunoprecipitation assays were conducted to show that AEG-1 activates Wnt/β-catenin signaling by directly interacting with GSK-3β. The co-localization of AEG-1 and GSK-3β in the cytoplasm of glioma cells was detected through immunofluorescence staining. This study raises the possibility that targeting AEG-1 might improve the efficiency of chemotherapy and reduce immunosuppressive M2 GAMs in glioma.

Molecular subtyping of diffuse gliomas using magnetic resonance imaging: comparison and correlation between radiomics and deep learning

OBJECTIVES

The molecular subtyping of diffuse gliomas is important. The aim of this study was to establish predictive models based on preoperative multiparametric MRI.

METHODS

A total of 1016 diffuse glioma patients were retrospectively collected from Beijing Tiantan Hospital. Patients were randomly divided into the training (n = 780) and validation (n = 236) sets. According to the 2016 WHO classification, diffuse gliomas can be classified into four binary classification tasks (tasks I-IV). Predictive models based on radiomics and deep convolutional neural network (DCNN) were developed respectively, and their performances were compared with receiver operating characteristic (ROC) curves. Additionally, the radiomics and DCNN features were visualized and compared with the t-distributed stochastic neighbor embedding technique and Spearman's correlation test.

RESULTS

In the training set, areas under the curves (AUCs) of the DCNN models (ranging from 0.99 to 1.00) outperformed the radiomics models in all tasks, and the accuracies of the DCNN models (ranging from 0.90 to 0.94) outperformed the radiomics models in tasks I, II, and III. In the independent validation set, the accuracies of the DCNN models outperformed the radiomics models in all tasks (0.74-0.83), and the AUCs of the DCNN models (0.85-0.89) outperformed the radiomics models in tasks I, II, and III. DCNN features demonstrated more superior discriminative capability than the radiomics features in feature visualization analysis, and their general correlations were weak.

CONCLUSIONS

Both the radiomics and DCNN models could preoperatively predict the molecular subtypes of diffuse gliomas, and the latter performed better in most circumstances.

KEY POINTS

• The molecular subtypes of diffuse gliomas could be predicted with MRI. • Deep learning features tend to outperform radiomics features in large cohorts. • The correlation between the radiomics features and DCNN features was low.

The clinical characteristics and prognostic value of IGFBP6 in glioma

BACKGROUND

Glioma is the most common intrinsic tumor in central nervous system and is characterized by their diffuse infiltration of the brain tissue. Insulin-like Growth Factor Binding Protein-6 (IGFBP6) was associated with the insulin-like growth factor binding and insulin-like growth factor II binding processes in many cancers. Herein, we aimed to investigate the biological functions and clinical features of IGFBP6 in gliomas.

METHODS

Totally, we collected 325 RNA sequencing data from CGGA dataset as training cohort, and 969 RNA sequencing data from TCGA dataset as validation cohort. The clinical and molecular characteristics analysis and gene ontology analysis of IGFBP6 were performed. All analyses and graphs were produced based on R language.

RESULTS

We found that IGFBP6 expression was significantly upregulated in GBM patients and downregulated in IDH mutant patients. Receiver Operating Characteristic (ROC) analysis revealed that IGFBP6 could be used as a biomarker to predict TCGA mesenchymal subtype. GO analysis revealed that IGFBP6 was correlated with immunological functions and inflammation activities. Meanwhile, higher expression of IGFBP6 suggested significant relationship with worse prognosis in glioma patients.

CONCLUSIONS

Our findings improved the understanding of IGFBP6 in glioma, and IGFBP6 might be a potential therapeutic target for glioma patients in future clinical trials.

Molecular Characterization of AEBP1 at Transcriptional Level in Glioma

Background

Glioma is the most common malignant tumor of the brain in adult patients. The standardized treatment protocol is based on surgical therapy, supplemented with radiotherapy and chemotherapy. However, the prognosis is still unsatisfied. Chemoresistance is one of the most important reason for the poor prognosis of glioma patients. It has confirmed that glioma stem cell (GSC) is one of the reasons for chemoresistance.

Methods

In this study, three datasets (GSE23806, COSMIC, and TCGA) were used to perform the analysis to search for the key genes related to GSC, temozolomide (TMZ) resistance, and prognosis. The key gene for further research was selected by reviewing the previous studies. The selected gene investigated the relation between expression levels and clinical characteristics in both TCGA and CGGA dataset. The bioinformatics analysis was performed by Gene Ontology (GO) analysis. The survival analysis was performed by Kaplan–Meier survival analysis.

Results

AE binding protein 1 (AEBP1) was selected for further analysis. AEBP1 was overexpressed in GSCs and TMZ resistance cells. In both TCGA and CGGA dataset, the results showed that the expression level of AEBP1 was increased in glioblastoma (GBM) samples, IDH wild-type samples, and MGMT promoter unmethylated samples. Meanwhile, AEBP1 expression was positively related to several GSC markers. GO analysis showed that AEBP1 was related to immune response, cell adhesion, apoptotic process, inflammatory response, positive regulation of cell proliferation, angiogenesis, response to drug, and response to hypoxia. The survival analysis showed that the overexpressed level of AEBP1 was correlated with short survival time in both glioma and GBM patients.

Conclusion

In summary, AEBP1 was related with GSC-induced TMZ resistance. Our study showed that AEBP1 might be an oncogene and a new effective therapeutic target for the treatment of glioma.

Glutamate-Oxaloacetate Transaminase 1 Impairs Glycolysis by Interacting with Pyruvate Carboxylase and Further Inhibits the Malignant Phenotypes of Glioblastoma Cells

BACKGROUND

Glycolysis is an important metabolic manner in glioblastoma multiforme (GBM)'s rapid growth. It has been reported that glutamate-oxaloacetate transaminase 1 (GOT1) is low-expressed in GBM and patients with high-expressed GOT1 have better prognosis. However, the effect and mechanism of GOT1 on glycolysis and malignant phenotypes of GBM cells are still unclear.

METHODS

The expression differences of GOT1 between GBM parenchyma and adjacent tissues were detected. The prognosis and clinical data with different levels of GOT1 were also analyzed. The glucose consumption, production of lactate and pyruvate were measured after GOT1 was knocked down or overexpressed. The effects of GOT1 on GBM cell's malignant phenotypes were analyzed by Western blot, CCK-8 assay, and flow cytometry. The relationship between GOT1 and pyruvate carboxylase (PC) was examined by immunoprecipitation and immunofluorescence.

RESULTS

GOT1 was expressed little in GBM, and patients with highly expressed GOT1 had longer survival periods. Overexpressed GOT1 inhibited the glycolysis and malignant phenotypes of GBM cells. 2-DG treatment could partially reverse the enhancement of malignant phenotypes caused by knockdown of GOT1. The expression of GOT1 was positively correlated with PC. The inhibitory effect of GOT1 on glycolysis could be partially reversed by PC's knockdown.

CONCLUSIONS

GOT1 could impair glycolysis by interacting with PC and further inhibit the malignant phenotypes of GBM cells.

Comprehensive Analysis of the Clinical and Biological Significances of Endoplasmic Reticulum Stress in Diffuse Gliomas

Background

As a critical organelle for protein and lipid synthesis, the dysfunction of endoplasmic reticulum has a significant impact on multiple biological processes of cells. Thus, in this study, we constructed an ER stress-related risk signature to investigate the functional roles of ER stress in gliomas.

Methods

A total of 626 samples from TCGA RNA-seq dataset (training cohort) and 310 samples from CGGA RNA-seq dataset (validation cohort) were enrolled in this study. Clinical information and genomic profiles were also obtained. The ER stress signature was developed by the LASSO regression model. The prognostic value of the risk signature was evaluated by Cox regression, Kaplan-Meier and ROC Curve analyses. Bioinformatics analysis and experiment in vitro were performed to explore the biological implication of this signature.

Results

We found that the ER stress-related signature was tightly associated with major clinicopathological features and genomic alterations of gliomas. Kaplan-Meier curve and Cox regression analysis indicated that ER stress activation was an independent prognostic factor for patients with glioma. Besides, we also constructed an individualized prognosis prediction model through Nomogram and ROC Curve analysis. Bioinformatics analysis suggested that ER stress activation also promoted the malignant progression of glioma and participated in the regulation of tumor immune microenvironment, especially the infiltration of macrophages in M2 phase. These results were further validated in IHC analysis and cell biology experiments.

Conclusion

The ER stress activation had a high prognostic value and could serve as a promising target for developing individualized treatment of glioma.

Glioma-related epilepsy in patients with diffuse high-grade glioma after the 2016 WHO update: seizure characteristics, risk factors, and clinical outcomes

OBJECTIVE

The aim of this study was to investigate the epidemiological characteristics, associated risk factors, and prognostic value of glioma-related epilepsy in patients with diffuse high-grade gliomas (DHGGs) that were diagnosed after the 2016 updated WHO classification was released.

METHODS

Data from 449 patients with DHGGs were retrospectively collected. Definitive diagnosis was reaffirmed according to the 2016 WHO classification. Seizure outcome was assessed using the Engel classification at 12 months after surgery. Univariate and multivariate analyses were performed to identify risk factors associated with preoperative and postoperative glioma-related epilepsy. Lastly, the prognostic value of glioma-related epilepsy was evaluated by Kaplan-Meier and Cox analysis.

RESULTS

The incidence of glioma-related epilepsy decreased gradually as the malignancy of the tumor increased. Age < 45 years (OR 2.601, p < 0.001), normal neurological function (OR 3.024, p < 0.001), and lower WHO grade (OR 2.028, p = 0.010) were independently associated with preoperative glioma-related epilepsy, while preoperative glioma-related epilepsy (OR 7.554, p < 0.001), temporal lobe involvement (OR 1.954, p = 0.033), non-gross-total resection (OR 2.286, p = 0.012), and lower WHO grade (OR 2.130, p = 0.021) were identified as independent predictors of poor seizure outcome. Furthermore, postoperative glioma-related epilepsy, rather than preoperative glioma-related epilepsy, was demonstrated as an independent prognostic factor for overall survival (OR 0.610, p = 0.010).

CONCLUSIONS

The updated WHO classification seems conducive to reveal the distribution of glioma-related epilepsy in DHGG patients. For DHGG patients with high-risk predictors of poor seizure control, timely antiepileptic interventions could be beneficial. Moreover, glioma-related epilepsy (especially postoperative glioma-related epilepsy) is associated with favorable overall survival.

Preoperative Radiomics Analysis of 1p/19q Status in WHO Grade II Gliomas

Purpose

The present study aimed to preoperatively predict the status of 1p/19q based on radiomics analysis in patients with World Health Organization (WHO) grade II gliomas.

Methods

This retrospective study enrolled 157 patients with WHO grade II gliomas (76 patients with astrocytomas with mutant IDH, 16 patients with astrocytomas with wild-type IDH, and 65 patients with oligodendrogliomas with mutant IDH and 1p/19q codeletion). Radiomic features were extracted from magnetic resonance images, including T1-weighted, T2-weighted, and contrast T1-weighted images. Elastic net and support vector machines with radial basis function kernel were applied in nested 10-fold cross-validation loops to predict the 1p/19q status. Receiver operating characteristic analysis and precision-recall analysis were used to evaluate the model performance. Student’s t-tests were then used to compare the posterior probabilities of 1p/19q co-deletion prediction in the group with different 1p/19q status.

Results

Six valuable radiomic features, along with age, were selected with the nested 10-fold cross-validation loops. Five features showed significant difference in patients with different 1p/19q status. The area under curve and accuracy of the predictive model were 0.8079 (95% confidence interval, 0.733–0.8755) and 0.758 (0.6879–0.8217), respectively, and the F1-score of the precision-recall curve achieved 0.6667 (0.5201–0.7705). The posterior probabilities in the 1p/19q co-deletion group were significantly different from the non-deletion group.

Conclusion

Combined radiomics analysis and machine learning showed potential clinical utility in the preoperative prediction of 1p/19q status, which can aid in making customized neurosurgery plans and glioma management strategies before postoperative pathology.

Systematic Profiling of mRNA Splicing Reveals the Prognostic Predictor and Potential Therapeutic Target for Glioblastoma Multiforme

Despite many changes in alternative splicing events (ASEs) are frequently involved in various cancers, prognosis-related ASEs and drug treatment targets in glioblastoma multiforme (GBM) have not been well explored. ASEs participate in many biological behaviors in the initiation and progression of tumors, the aberrant ASE has been considered another hallmark of cancer, and the systematic study of alternative splicing may provide potential biomarkers for malignancies. In this study, we carried out a systematic analysis to characterize the ASE signatures in GBM cohort. Through comparing GBM tissues and nontumor tissues, a total of 48,191 differently expressed ASEs from 10,727 genes were obtained, and these aberrant ASEs play an important role in the oncogenic process. Then, we identified 514 ASEs independently associated with patient survival in GBM by univariate and multivariate Cox regression, including exon skip in CD3D, alternate acceptor site in POLD2, and exon skip in DCN. Those prognostic models built on ASEs of each splice type can accurately predict the outcome of GBM patients, and values for the area under curve were 0.97 in the predictive model based on alternate acceptor site. In addition, the splicing-regulatory network revealed an interesting correlation between survival-associated splicing factors and prognostic ASE corresponding genes. Moreover, these three hub splicing factors in splicing regulation network are the potential targets of some drugs. In conclusion, a systematic analysis of ASE signatures in GBM could serve as an indicator for identifying novel prognostic biomarkers and guiding clinical treatment.

Prognostic Value of Immune-Related lncRNA SBF2-AS1 in Diffuse Lower-Grade Glioma

LncRNA SET-binding factor 2 (SBF2) antisense RNA1 (SBF2-AS1) has been proven to play an oncogenic role in various types of tumors, but the prognostic role of SBF2-AS1 in tumors, especially in diffuse lower-grade glioma (LGG), is still unclear. Here, we aimed to investigate the prognostic value of SBF2-AS1 in LGG. The LGG expression profiles from The Cancer Genome Atlas (TCGA, n = 524) and Chinese Glioma Genome Atlas (CGGA, n = 431) were mined by Kaplan-Meier analysis, Cox regression analysis, Chi-square test and GSEA analysis. Through Kaplan-Meier analysis, we found the prognosis of LGG patients with high expression of SBF2-AS1 were worse than that of patients with low expression (Log Rank P < 0.001). Cox analysis showed SBF2-AS1 was an independent prognostic factor for poorer overall survival in LGG (P < 0.05). SBF2-AS1 was found to be significantly related to IDH mutation status and SBF2-AS1 was highly expressed in IDH wildtype group. GSEA analysis obtained a total of 126 GO terms and 6 KEGG pathways that were significantly enriched in SBF2-AS1 high expression phenotype (NOM P value < 0.05). We found these 126 GO terms and KEGG pathways were mainly related to immunity. In conclusion, lncRNA SBF2-AS1 expression is an immune-related lncRNA associated with unfavorable overall survival in LGG. SBF2-AS1 could be a reliable prognostic biomarker for patients with LGG.

A comprehensive prognostic signature for glioblastoma patients based on transcriptomics and single cell sequencing

PURPOSE

Glioblastoma (GBM) is the most common and deadly brain tumor. We aimed to reveal potential prognostic GBM marker genes, elaborate their functions, and build an effective a prognostic model for GBM patients.

METHODS

Through data mining of The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), we screened for significantly differentially expressed genes (DEGs) to calculate risk scores for individual patients. Published data of somatic mutation and copy number variation profiles were analyzed for distinct genomic alterations associated with risk scores. In addition, single-cell sequencing was used to explore the biological functions of the identified prognostic marker genes. By combining risk scores and other clinical features, we built a comprehensive prognostic GBM model.

RESULTS

Seven DEGs (CLEC5A, HOXC6, HOXA5, CCL2, GPRASP1, BSCL2 and PTX3) were identified as being prognostic for GBM. Expression of these genes was confirmed in different GBM cell lines using real-time PCR. Risk scores calculated from the seven DEGs revealed prognostic value irrespective of other clinical factors, including IDH mutation status, and were negatively correlated with TP53 expression. The prognostic genes were found to be associated with tumor proliferation and progression based on pseudo-time analysis in neoplastic cells. A final prognostic model was developed and validated with a good performance, especially in geriatric GBM patients.

CONCLUSIONS

Using genetic profiles, age, IDH mutation status, and chemotherapy and radiotherapy, we constructed a comprehensive prognostic model for GBM patients. The model has a good performance, especially in geriatric GBM patients.

Investigation of Genetic Determinants of Glioma Immune Phenotype by Integrative Immunogenomic Scale Analysis

The immunosuppressive mechanisms of the surrounding microenvironment and distinct immunogenomic features in glioblastoma (GBM) have not been elucidated to date. To fill this gap, useful data were extracted from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), GSE16011, GSE43378, GSE23806, and GSE12907. With the ssGSEA method and the ESTIMATE and CIBERSORT algorithms, four microenvironmental signatures were used to identify glioma microenvironment genes, and the samples were reasonably classified into three immune phenotypes. The molecular and clinical features of these phenotypes were characterized via key gene set expression, tumor mutation burden, fraction of immune cell infiltration, and functional enrichment. Exhausted CD8+ T cell (GET) signature construction with the predictive response to commonly used antitumor drugs and peritumoral edema assisted in further characterizing the immune phenotype features. A total of 2,466 glioma samples with gene expression profiles were enrolled. Tumor purity, ESTIMATE, and immune and stromal scores served as the 4 microenvironment signatures used to classify gliomas into immune-high, immune-middle and immune-low groups, which had distinct immune heterogeneity and clinicopathological characteristics. The immune-H phenotype had higher expression of four immune signatures; however, most checkpoint molecules exhibited poor survival. Enriched pathways among the subtypes were related to immunity. The GET score was similar among the three phenotypes, while immune-L was more sensitive to bortezomib, cisplatin, docetaxel, lapatinib, and rapamycin prescriptions and displayed mild peritumor edema. The three novel immune phenotypes with distinct immunogenetic features could have utility for understanding glioma microenvironment regulation and determining prognosis. These results contribute to classifying glioma subtypes, remodeling the immunosuppressive microenvironment and informing novel cancer immunotherapy in the era of precision immuno-oncology.

TROAP regulates cell cycle and promotes tumor progression through Wnt/β-Catenin signaling pathway in glioma cells

AIMS

Experimental evidence demonstrated a crucial role of TROAP (Trophinin-associated protein) in regulating the cell proliferation of multiple tumors, while TROAP expression and function were largely unknown in glioma. We aimed to investigate the oncogenic role of TROAP and its potential mechanisms in gliomagenesis.

METHODS

Four gene expression databases (GEO, TCGA, GTEx and CCLE) were enrolled in our study and used for TROAP expression and survival analysis. TROAP expression was quantified by qRT-PCR, western blot and immunohistochemistry assays in glioma tissues and cell lines. TROAP knockdown and overexpression vector were constructed and transfected into glioma cells. CCK-8, colony formation, transwell, and wound healing assays were used to evaluate cell viability, migration and invasion, flow cytometry to determine cell cycle arrest. Gene set enrichment analysis (GSEA) was conducted to screen the pathway involved in TROAP-high phenotype. The expression of cell cycle and Wnt/β-Catenin signaling proteins were analyzed by immunofluorescence and western blot.

RESULTS

Based on the bioinformatic analysis and a series of functional assays, we found the TROAP was enriched in glioma tissues and cell lines, its overexpression was correlated with the clinicopathologic characteristics and poor prognosis. TROAP knockdown inhibited cell proliferation, migration, invasion, and G1/S cell cycle arrest compared with control group in glioma. Mechanism analysis revealed that TROAP activated Wnt/β-Catenin pathway and upregulated its downstream targets expression, while silencing β-Catenin or Axin2 could reverse the tumor-promoting effects caused by TROAP, confirming that TROAP-induced malignant phenotype and tumorigenesis via Wnt/β-Catenin signaling pathway.

CONCLUSION

The present study found that TROAP accelerated the progression of gliomagenesis through Wnt/β-Catenin pathway, and TROAP might be considered as a novel target for glioma therapy.

SLC39A7 promotes malignant behaviors in glioma via the TNF-α-mediated NF-κB signaling pathway

Purpose: Several studies have indicated that SLC39A7 plays an important role in tumor progression; however, little is known about the function and mechanism of SLC39A7 in glioma. In this study, we aimed to explore the role of SLC39A7 in glioma development. Patients and methods: Bioinformatic analysis was used to predict the role of SLC39A7 in glioma. Cell viability and Edu assays were used to detect the proliferation of glioma cells. A transwell assay was used to measure the invasion and migration of glioma cells. Western blotting, qPCR and ELISA were used to detect the expression of all molecules. Results: SLC39A7 was found to be highly expressed in high-grade glioma patients with a poor prognosis. Our results indicated that SLC39A7 significantly promoted the proliferation, invasion and migration of glioma cells. Furthermore, SLC39A7 promoted tumorigenesis in orthotopic models. We determined that SLC39A7 promotes the malignant behaviors of glioma by activating the TNF-α-mediated NF-κB signaling pathway. Conclusion: Our study revealed that SLC39A7 promotes the proliferation, invasion and migration of glioma cells via the TNF-α-mediated NF-κB signaling pathway, which provides potential targets for glioma therapy.

Aging-related genes are potential prognostic biomarkers for patients with gliomas

Aging has a significant role in the proliferation and development of cancers. This study explored the expression profiles, prognostic value, and potential roles of aging-related genes in gliomas. We designed risk score and cluster models based on aging-related genes and glioma cases using LASSO Cox regression analysis, consensus clustering analysis and univariate cox regression analyses. High risk score was related to malignant clinical features and poor prognosis based on 10 datasets, 2953 cases altogether. Genetic alterations analysis revealed that high risk scores were associated with genomic aberrations of aging-related oncogenes. GSVA analysis exhibited the potential function of the aging-related genes. More immune cell infiltration was found in high-risk group cases, and glioma patients in high-risk group may be more responsive to immunotherapy. Knock-down of CTSC, an aging-related gene, can inhibit cell cycle progression, colony formation, cell proliferation and increase cell senescence in glioma cell lines in vitro. Indeed, high expression of CTSC was associated with poor prognosis in glioma cases. In conclusion, this study revealed that aging-related genes have prognostic potential for glioma patients and further identified potential mechanisms for aging-related genes in tumorigenesis and progression in gliomas.

METTL3 enhances the stability of MALAT1 with the assistance of HuR via m6A modification and activates NF-κB to promote the malignant progression of IDH-wildtype glioma

Understanding the role of N6-methyladenosine (m⁶A) in tumorigenesis and stem cell maintenance is an emerging field in glioma research. However, it is necessary to study the function of m⁶A in IDH-mutation and IDH-wildtype gliomas separately. Here, we aimed to elucidate the role and mechanism of the m⁶A writer METTL3 in regulating the malignant progression of IDH-wildtype gliomas. We demonstrated that METTL3 expression is positively associated with a higher malignant grade and poorer prognosis of IDH-wildtype gliomas but not IDH-mutant gliomas. METTL3 could also promote the malignant progression of gliomas in both in vitro and in vivo models. Mechanistically, METTL3 upregulated MALAT1 expression by enhancing its stability via m⁶A modification. We further revealed that HuR was essential for METTL3-mediated MALAT1 stabilization, and upregulated MALAT1 subsequently activated NF-κB. Taken together, our findings confirmed that METTL3 promoted the malignant progression of IDH-wildtype gliomas and revealed important insight into the upstream regulatory mechanism of MALAT1 and NF-κB with a primary focus on m6A modification.

Genomic Analysis of Glioblastoma Multiforme Reveals a Key Transcription Factor Signature Relevant to Prognosis and the Immune Processes

Introduction

Glioblastoma multiforme (GBM) develops through the accumulation of both genetic and expression alterations. Although many gene signatures have been developed as prognostic and predictive biomarkers, their robustness and functional aspects are less well characterized. The expression of most genes is regulated by transcription factors (TFs); therefore, we aimed to investigate a TF signature relevant to GBM prognosis.

Methods

We used bioinformatic methods and data from public databases to establish four clusters of key TF genes, among which cluster 1, comprising 24 TFs, showed significant prognostic value. Further in silico functional analyses were applied to investigate the utility of the TF signature.

Results

Different mutation and copy number variation patterns were observed between different risk score groups (based on the TF signature). In silico analyses suggested that the cases with relative high risk scores were involved in immune and inflammatory processes or pathways.

Conclusion

The TF signature has significant prognostic value in different cohorts or subgroups of patients with GBM and could lead to the development immunotherapy for GBM.

Identification of a mesenchymal-related signature associated with clinical prognosis in glioma

Malignant glioma with a mesenchymal (MES) signature is characterized by shorter survival time due to aggressive dissemination and resistance to chemoradiotherapy. Here, this study used the TCGA database as the training set and the CGGA database as the testing set. Consensus clustering was performed on the two data sets, and it was found that two groups had distinguished prognostic and molecular features. Cox analysis and Lasso regression analysis were used to construct MES signature-based risk score model of glioma. Our results show that MES signature-based risk score model can be used to assess the prognosis of glioma. Three methods (ROC curve analyses, univariate Cox regression analysis, multivariate Cox regression analysis) were used to investigate the prognostic role of texture parameters. The result showed that the MES-related gene signature was proved to be an independent prognostic factor for glioma. Furthermore, functional analysis of the gene related to the risk signature showed that the genes sets were closely related to the malignant process of tumors. Finally, FCGR2A and EHD2 were selected for functional verification. Silencing these two genes inhibited the proliferation, migration and invasion of gliomas and reduced the expression of mesenchymal marker genes. Collectively, MES-related risk signature seems to provide a novel target for predicting the prognosis and treatment of glioma.

Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients

Glioblastoma (GBM) is the most malignant and lethal intracranial tumor, with extremely limited treatment options. Immunotherapy has been widely studied in GBM, but none can significantly prolong the overall survival (OS) of patients without selection. Considering that GBM cancer stem cells (CSCs) play a non-negligible role in tumorigenesis and chemoradiotherapy resistance, we proposed a novel stemness-based classification of GBM and screened out certain population more responsive to immunotherapy. The one-class logistic regression algorithm was used to calculate the stemness index (mRNAsi) of 518 GBM patients from The Cancer Genome Atlas (TCGA) database based on transcriptomics of GBM and pluripotent stem cells. Based on their stemness signature, GBM patients were divided into two subtypes via consensus clustering, and patients in Stemness Subtype I presented significantly better OS but poorer progression-free survival than Stemness Subtype II. Genomic variations revealed patients in Stemness Subtype I had higher somatic mutation loads and copy number alteration burdens. Additionally, two stemness subtypes had distinct tumor immune microenvironment patterns. Tumor Immune Dysfunction and Exclusion and subclass mapping analysis further demonstrated patients in Stemness Subtype I were more likely to respond to immunotherapy, especially anti-PD1 treatment. The pRRophetic algorithm also indicated patients in Stemness Subtype I were more resistant to temozolomide therapy. Finally, multiple machine learning algorithms were used to develop a 7-gene Stemness Subtype Predictor, which were further validated in two external independent GBM cohorts. This novel stemness-based classification could provide a promising prognostic predictor for GBM and may guide physicians in selecting potential responders for preferential use of immunotherapy.

MYD88 Is a Potential Prognostic Gene and Immune Signature of Tumor Microenvironment for Gliomas

Purpose

To explore the profiles of immune and stromal components of the tumor microenvironment (TME) and their related key genes in gliomas.

Methods

We applied bioinformatic techniques to identify the core gene that participated in the regulation of the TME of the gliomas. And immunohistochemistry staining was used to calculate the gene expressions in clinical cases.

Results

The CIBERSORT and ESTIMATE were used to figure out the composition of TME in 698 glioma cases from The Cancer Genome Atlas (TCGA) database. Differential expression analysis identified 2103 genes between the high and the low-score group. Then the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, univariate Cox regression analysis, and protein–protein interaction (PPI) network construction were conducted based on these genes. MYD88 was identified as the key gene by the combination univariate Cox and PPI analysis. Furthermore, MYD88 expression was significantly associated with the overall survival and WHO grade of glioma patients. The genes in the high-expression MYD88 group were mainly in immune-related pathways in the Gene Set Enrichment Analysis (GSEA). We found that macrophage M2 accounted for the largest portion with an average of 27.6% in the glioma TIICs and was associated with high expression of MYD88. The results were verified in CGGA database and clinical cases in our hospital. Furthermore, we also found the MYD88 expression was higher in IDH1 wild types. The methylation rate was lower in high grade gliomas.

Conclusion

MYD88 had predictive prognostic value in glioma patients by influencing TIICs dysregulation especially the M2-type macrophages.

Expression and survival analysis of the STAT gene family in diffuse gliomas using integrated bioinformatics

Signal Transducer and Activator of Transcription (STAT) belongs to the acyltransferase family and participates in cell viability response to different cell stimuli and pathogens. By mediating the expression of a variety of genes, the STAT family plays a prominent part in mammal immunity, proliferation and differentiation. Dysregulations and mutations of STAT factors have been revealed in many kinds of cancers including diffuse gliomas; however, expression characteristic and prognostic value of STAT in diffuse gliomas remain to be elucidated. In this study, we analyzed the transcriptional and survival data of gliomas using ONCOMINE, cBioPortal, GEPIA, COXPRESDB and WEBGESTALTR databases. The results demonstrated that the transcriptional level of STAT1, STAT3 and STAT5A in gliomas was significantly higher than that in normal tissue. Furthermore, dysregulations of STAT1, STAT3, STAT4, STAT5B and STAT6 were referred to as the potential biomarkers to sub-group analysis of gliomas. Survival analysis by the Kaplan-Meier Plotter suggested that glioma patients with high expression of STAT1, STAT3 and STAT5B tended to have poor survival. These data revealed that the STAT family may be an essential aspect of glioma progression and prognosis.

Increasing the accumulation of aptamer AS1411 and verapamil conjugated silver nanoparticles in tumor cells to enhance the radiosensitivity of glioma

Radioresistance significantly decreases the efficacy of radiotherapy, which can ultimately lead to tumor recurrence and metastasis. As a novel type of nano-radiosensitizer, silver nanoparticles (AgNPs) have shown promising radiosensitizing properties in the radiotherapy of glioma, but their ability to efficiently enter and accumulate in tumor cells needs to be improved. In the current study, AS1411 and verapamil (VRP) conjugated bovine serum albumin (BSA) coated AgNPs (AgNPs@BSA-AS-VRP) were synthesized and characterized. Dark-field imaging and inductively coupled plasma mass spectrometry were applied to investigate the accumulation of AgNPs@BSA-AS and AgNPs@BSA-AS-VRP mixed in different ratios in U251 glioma cells. To assess the influences of 19:1 mixed AgNPs@BSA-AS and AgNPs@BSA-AS-VRP on the P-glycoprotein (P-gp) efflux activity, rhodamine 123 accumulation assay was carried out. Colony formation assay and tumor-bearing nude mice model were employed to examine the radiosensitizing potential of 19:1 mixed AgNPs@BSA-AS and AgNPs@BSA-AS-VRP. Thioredoxin Reductase (TrxR) Assay Kit was used to detect the TrxR activity in cells treated with different functionally modified AgNPs. Characterization results revealed that AgNPs@BSA-AS-VRP were successfully constructed. When AgNPs@BSA-AS and AgNPs@BSA-AS-VRP were mixed in a ratio of 19:1, the amount of intracellular nanoparticles increased greatly through AS1411-mediated active targeting and inhibition of P-gp activity. In vitro and in vivo experiments clearly showed that the radiosensitization efficacy of 19:1 mixed AgNPs@BSA-AS and AgNPs@BSA-AS-VRP was much stronger than that of AgNPs@BSA and AgNPs@BSA-AS. It was also found that 19:1 mixed AgNPs@BSA-AS and AgNPs@BSA-AS-VRP significantly inhibited intracellular TrxR activity. These results indicate that 19:1 mixed AgNPs@BSA-AS and AgNPs@BSA-AS-VRP can effectively accumulate in tumor cells and have great potential as high-efficiency nano-radiosensitizers in the radiotherapy of glioma.

Integrated analysis of the genomic and transcriptional profile of high-grade gliomas in different age groups

BACKGROUND

Age is a powerful prognostic factor of high-grade glioma (HGG). However, the underlying genetic mechanisms of the discrepant prognosis among different age groups remain elusive.

METHODS

A total of 953 and 559 HGG patients from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) cohorts were enrolled and assigned as young, intermediate, elderly groups. The data of clinicopathological characteristics, mRNA, mutation, copy number alteration was analyzed.

RESULTS

Transcriptomic analysis revealed that diverse biological processes including immune response are altered between the young and elderly groups. Combined with the analysis of infiltrating immune cells and immune checkpoints, our results suggest an immune suppression status in the elderly group. Patients from different age groups exhibit different mutation and copy number alteration profiles.

CONCLUSIONS

A multi-omics analysis is conducted to explore the biological basis of HGG patients of different age groups. This study suggests an immune-suppressive environment in elderly patients.

High-dose radiation associated with improved survival in IDH-wildtype low-grade glioma

BACKGROUND

As molecular advances have deepened the knowledge on low-grade glioma (LGG), we investigated the effect of higher radiation dose on the survival of IDH-wildtype (IDHwt) LGG.

METHODS

In the current study, 52 IDHwt LGG patients who received radiotherapy were enrolled from the Chinese Glioma Genome Atlas dataset. Radiation doses > 54 Gy were defined as high-dose, whereas doses ≤ 54 Gy were defined as low-dose. We performed univariate and multivariate survival analyses to examine the prognostic role of high-dose radiotherapy.

RESULTS

In total, the radiation dose ranged from 48.6 Gy to 61.2 Gy, with a median of 55.8 Gy, and 31 patients were grouped into high-dose radiation. Univariate survival analysis indicated that high-dose radiotherapy (p = 0.015), tumors located in the frontal lobe (p = 0.009), and pathology of astrocytoma (p = 0.037) were significantly prognostic factors for overall survival. In multivariate survival analysis, high-dose radiotherapy (p = 0.028) and tumors located in the frontal lobe (p = 0.016) were independently associated with better overall survival.

CONCLUSIONS

In conclusion, high-dose radiotherapy independently improved the survival of IDHwt LGG. This can guide treatments for glioma with known molecular characteristics.

PDIA3 correlates with clinical malignant features and immune signature in human gliomas

Since therapeutic strategies are limited in gliomas, new molecules or biomarkers are essential for diagnosis and therapy. Here, we investigated expression of protein disulfide isomerase family A member 3 (PDIA3) in gliomas to evaluate its potential as a promising immune target or biomarker. Transcriptome level, genomic profiles and its association with clinical practice from TCGA and CGGA databases were analyzed. All statistical analyses were performed using R project. In gliomas with high PDIA3 expression, somatic mutations showed the correlation with loss of PTEN and amplification of EGFR; meanwhile, in PDIA3 low gliomas, mutations in isocitrate dehydrogenase (IDH) took 80%. Moreover, PDIA3 was found to positively correlate with ESTIMATE scores and diverse infiltrating immune and stromal cell types localizing in tumor microenvironment. PDIA3 was found to be highly correlated with macrophage and T cells based on single cell sequencing. Additionally, PDIA3 was also involved in suppression of anti-tumor immunity via multiple immune regulatory processes. Finally, PDIA3 was observed to correlate with other immune checkpoint inhibitors and associated with inflammation. Our findings identified the significance of PDIA3 in the process of gliomas and demonstrated the potential of PDIA3 as a molecular target in prognosis and immune related treatment of gliomas

Plasminogen Activator Urokinase Receptor Implies Immunosuppressive Features and Acts as an Unfavorable Prognostic Biomarker in Glioma

BACKGROUND

Clinical outcomes of patients with glioma are still poor, even after standard treatments, including surgery combined with radiotherapy and chemotherapy. New therapeutic strategies and targets for glioma are urgently needed. Plasminogen activator urokinase receptor (PLAUR), a highly glycosylated integral membrane protein, is reported to modulate plasminogen activation and extracellular matrix degradation in many malignant cancers, but its role in gliomas remains unclear.

METHODS

Glioma samples with mRNA sequencing data and clinical information from the Chinese Glioma Genome Atlas (n = 310) data set and The Cancer Genome Atlas (n = 611) data set were collected for this study. Analyses using Kaplan-Meier plots, time-dependent receiver operating characteristic curves, Cox regression, and nomograms were conducted to evaluate the prognostic performance of PLAUR expression. Analyses using Metascape, ESTIMATE, EPIC, and immunohistochemical staining were performed to reveal the potential biological mechanism. The statistical analysis and graphical work were completed using SPSS, R language, and GraphPad Prism.

RESULTS

PLAUR was highly expressed in phenotypes associated with glioma malignancy and could serve as an independent prognostic indicator. Functional analysis revealed the correlation between PLAUR and immune response. Further studies found that samples with higher PLAUR expression were infiltrated with fewer CD8 T cells and many more M2 macrophages. Strong positive correlation was demonstrated between PLAUR expression and some immunosuppressive markers, including immune checkpoints and cytokines. These findings were also confirmed in patient samples.

CONCLUSION

Our results elucidated the clinical significance and immunosuppressive effect of PLAUR in gliomas, which might provide some clues in glioma immunotherapy.

IMPLICATIONS FOR PRACTICE

Although the efficacy of immunotherapy has been verified in other tumors, its application in glioma is impeded because of the unique microenvironment. Tumor-associated macrophages, which are particularly abundant in a glioma mass, contribute much to the immunosuppressive microenvironment and offer new opportunities in glioma immunotherapy. The results of this study identified plasminogen activator urokinase receptor (PLAUR) expression as a potential marker to predict the infiltration of macrophages and the status of immune microenvironment in patients with glioma, suggesting that treatment decisions could be based on PLAUR level when administering immunotherapeutics. The soluble PLAUR in blood and other body fluids would make this approach easy to implement in the clinic.

Prognostic value of pretreatment circulating basophils in patients with glioblastoma

Accumulating evidence demonstrated that atopic diseases were inversely related to glioma susceptibility and associated with improved prognosis of patients with glioma. This study aimed to elucidate the impacts of basophils, one of the important effector cells in the pathobiology of atopic disease, on prognosis of patients with glioblastoma (GBM). A total of 268 patients were newly diagnosed with GBM and treated with operation at our institution from January 2010 to December 2017. The association between pre-operation circulating eosinophil, basophil, neutrophil, lymphocyte, monocyte count and GBM progression free survival (PFS) was investigated. Moreover, based on the results of multivariate analysis, a prognostic nomogram was established and evaluated. Kaplan-Meier method showed that basophils ≥0.015 × 10⁹/L (p = 0.015) and lymphocytes ≥1.555 × 10⁹/L (p = 0.005) were correlated with better PFS. Cox regression model showed that basophils ≥0.015 × 10⁹/L were an independent prognostic factor for PFS. Prognostic nomogram was established and the concordance index (C-index) for PFS prediction was 0.629. The calibration plots for the probability of 0.5-, 1- and 3-year PFS showed optimal consistency between the prediction by nomogram and actual observation. Increased pre-operation circulating basophils portend better PFS, which might be a useful and novel marker for the prognosis of GBM patients.

Upregulation of circ-ASPH contributes to glioma cell proliferation and aggressiveness by targeting the miR-599/AR/SOCS2-AS1 signaling pathway

Glioma (GM) is the most common type of malignant brain tumor with a high recurrence rate. Circular RNAs (circRNAs) play a key role in mediating tumorigenesis. However, the functions and mechanisms of circRNAs in GM are still not fully understood. A circRNA microarray was performed to identify differentially expressed circRNAs in GM and non-cancerous specimens. Reverse transcription-quantitative PCR was used to detect circ-aspartyl/asparaginyl β-hydroxylase (ASPH) expression in GM tissues and cells. The clinical importance of circ-ASPH was investigated using Kaplan-Meier analysis. The functions of circ-ASPH were investigated in LN229 and U87MG cells. Bioinformatics, RNA immunoprecipitation, RNA pull-down and luciferase reporter assays were used to explore the mechanisms of circ-ASPH in GM. circ-ASPH levels were upregulated in GM specimens and cells. The prognostic role of circ-ASPH was identified in patients with GM. Loss/gain of function assays demonstrated that circ-ASPH increased cell proliferation, migration and invasion in GM cells. Mechanistically, circ-ASPH counteracted microRNA (miR)-599-mediated androgen receptor (AR) suppression by acting as a sponge for miR-599. Rescue assays indicated that circ-ASPH facilitated cell progression by regulating AR expression. Moreover, AR activated long non-coding RNA suppressor of cytokine signaling 2-antisense RNA 1 (SOCS2-AS1) expression in GM cells. Taken together, circ-ASPH/miR-599/AR/SOCS2-AS1 signaling may be a promising biomarker/therapeutic target for GM.

YAP promotes autophagy and progression of gliomas via upregulating HMGB1

BACKGROUND

Due to the hypoxia and nutrient deficiency microenvironment, glioblastoma (GBM) exhibits high autophagy activity and autophagy plays an important role in the progression of GBM. However, the molecular mechanism of autophagy in GBM progression remains unclear. The aim of this study is to delve out the role and mechanism of yes-associated protein (YAP) in GBM autophagy and progression.

METHODS

The level of autophagy or autophagy flux were assessed by using western blotting, GFP-LC3 puncta (Live) imaging, transmission electron microscopy and GFP-RFP-LC3 assay. The GBM progression was detected by using CCK8, EdU, nude mouse xenograft and Ki67 staining. Isobaric tags for relative and absolute quantification (iTraq) quantitative proteomics was used to find out the mediator of YAP in autophagy. Expression levels of YAP and HMGB1 in tissue samples from GBM patients were examined by Western blotting, tissue microarray and immunohistochemistry.

RESULTS

YAP over-expression enhanced glioma cell autophagy under basal and induced conditions. In addition, blocking autophagy by chloroquine abolished the promoting effect of YAP on glioma growth. Mechanistically, YAP over-expression promoted the transcription and translocation of high mobility group box 1(HMGB1), a well-known regulator of autophagy, from nucleus to cytoplasm. Down-regulation of HMGB1 abolished the promoting effect of YAP on autophagy and glioma growth. Furthermore, the expression of YAP and HMGB1 were positively associated with each other and suggested poor prognosis for clinical GBM.

CONCLUSION

YAP promoted glioma progression by enhancing HMGB1-mediated autophagy, indicating that YAP-HMGB1 axis was a feasible therapeutic target for GBM. Our study revealed a clinical opportunity involving the combination of chemo-radiotherapy with pharmacological autophagy inhibition for treating GBM patients with YAP high expression.

Transcriptome analysis revealed CENPF associated with glioma prognosis

Gliomas are common malignant tumors of the central nervous system. Despite the surgical resection and postoperative radiotherapy and chemotherapy, the prognosis of glioma remains poor. Therefore, it is important to reveal the molecular mechanisms that promotes glioma progression. Microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. The GEO2R tool was used to identify 428 differentially expressed genes (DEGs) and a core module from three microarray datasets. Heat maps were drawn based on DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the DAVID database. The core module was significantly involved in several KEGG pathways, such as "cell cycle", "viral carcinogenesis", "progesterone-mediated oocyte maturation", "p53 signaling pathway". The protein-protein interaction (PPI) networks and modules were built using the STRING database and the MCODE plugin, respectively, which were visualized using Cytoscape software. Identification of hub genes in the core module using the CytoHubba plugin. The top modular genes AURKA, CDC20, CDK1, CENPF, and TOP2A were associated with glioma development and prognosis. In the Human Protein Atlas (HPA) database, CDC20, CENPF and TOP2A have significant protein expression. Univariate and multivariate cox regression analysis showed that only CENPF had independent influencing factors in the CGGA database. GSEA analysis found that CENPF was significantly enriched in the cell cycle, P53 signaling pathway, MAPK signaling pathway, DNA replication, spliceosome, ubiquitin-mediated proteolysis, focal adhesion, pathway in cancer, glioma, which was highly consistent with previous studies. Our study revealed a core module that was highly correlated with glioma development. The key gene CENPF and signaling pathways were identified through a series of bioinformatics analysis. CENPF was identified as a candidate biomarker molecule.

Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients

Gliomas are the most common and malignant intracranial tumors in adults. Recent studies have revealed the significance of functional genomics for glioma pathophysiological studies and treatments. However, access to comprehensive genomic data and analytical platforms is often limited. Here, we developed the Chinese Glioma Genome Atlas (CGGA), a user-friendly data portal for the storage and interactive exploration of cross-omics data, including nearly 2000 primary and recurrent glioma samples from Chinese cohort. Currently, open access is provided to whole-exome sequencing data (286 samples), mRNA sequencing (1018 samples) and microarray data (301 samples), DNA methylation microarray data (159 samples), and microRNA microarray data (198 samples), and to detailed clinical information (age, gender, chemoradiotherapy status, WHO grade, histological type, critical molecular pathological information, and survival data). In addition, we have developed several tools for users to analyze the mutation profiles, mRNA/microRNA expression, and DNA methylation profiles, and to perform survival and gene correlation analyses of specific glioma subtypes. This database removes the barriers for researchers, providing rapid and convenient access to high‐quality functional genomic data resources for biological studies and clinical applications. CGGA is available at http://www.cgga.org.cn.

A potentially effective drug for patients with recurrent glioma: sermorelin

Background

Treatment insensitivity is the main cause of glioma. This study was designed to screen out effective drugs for recurrent gliomas based on the transcriptomics data.

Methods

A total of 1,018 glioma patients with transcriptome sequencing data and clinical data were included in this study. There were 325 patients in the discovery cohort, including 229 primary patients and 92 recurrent patients. There were 693 patients in the validation cohort, including 422 primary patients and 271 relapsed patients. Drug Resistant Scores (DRS) of 4,865 drugs of each patient were used for screening. The analysis and drawing in this study were mainly based on R language.

Results

After high-throughput drug screening, we found that recurrent glioma patients were most sensitive to sermorelin. Further analysis revealed that sermorelin was suitable for recurrent patients with high grade, IDH-wildtype and 1p/19q non-codeletion status. GO and KEGG analyses found that sermorelin may inhibit tumor cell proliferation by cell cycle blocking. Moreover, sermorelin was also related to the immune system process and negatively regulated immune checkpoints and M0 macrophages. Lastly, the Kaplan-Meier method showed the patient's benefit from sermorelin was independent of postoperative adjuvant treatment.

Conclusions

Recurrent glioma patients are sensitive to sermorelin and it makes effect through glioma cells proliferation inhibiting and immune response enhancing.

Mutation-based clustering and classification analysis reveals distinctive age groups and age-related biomarkers for glioma

BACKGROUND

Malignant brain tumor diseases exhibit differences within molecular features depending on the patient's age.

METHODS

In this work, we use gene mutation data from public resources to explore age specifics about glioma. We use both an explainable clustering as well as classification approach to find and interpret age-based differences in brain tumor diseases. We estimate age clusters and correlate age specific biomarkers.

RESULTS

Age group classification shows known age specifics but also points out several genes which, so far, have not been associated with glioma classification.

CONCLUSIONS

We highlight mutated genes to be characteristic for certain age groups and suggest novel age-based biomarkers and targets.

Systematic and Multi-Omics Prognostic Analysis of Lysine Acetylation Regulators in Glioma

Lysine acetylation modification, which has key roles in cellular homeostasis as well as cancer malignancy, is dynamically regulated by lysine acetylation regulators (LARs). In our study, we found that most of 33 evaluated LARs were differentially expressed among 1,125 gliomas grouped by different clinicopathological characteristics. Consensus clustering was applied to 33 LARs, resulting in three glioma subtypes (LA1, 2, and 3). The LA3 subgroup was associated with the poorest clinical outcome, higher WHO grade, fewer isocitrate dehydrogenase mutations, and lower frequency of 1p/19q codeletion. Furthermore, gene set enrichment analysis indicated that eight tumor hallmarks were highly enriched in the LA3 subgroup. These results suggested that LARs are significantly related to glioma malignancy. We then designed a LAR-signature based on 14 overall survival (overall survival)-related LARs, and showed that the LAR-signature possesses strong and independent prognostic value for glioma patients in both training and validation datasets. Moreover, by interrogating single nucleotide polymorphism and copy number variation (CNV) data in The Cancer Genome Atlas dataset, we found that higher score of our risk signature is correlated with the hypermutation status of gliomas and that HDAC1(1p) was one of the oncogenes lost in 1p/19q codeletion events, while SIRT2(19q) and EP300(22q) may act as tumor suppressors in gliomas with 19q or 22q deletions, respectively. In conclusion, LARs are critical for the malignant development of gliomas, and our results are useful for prognostic stratification and development of novel assessment strategies for the prognosis of glioma patients.

Putting Proteomics Into Immunotherapy for Glioblastoma

In glioblastoma, the most aggressive brain cancer, a complex microenvironment of heterogeneity and immunosuppression, are considerable hurdles to classify the subtypes and promote treatment progression. Treatments for glioblastoma are similar to standard therapies for many other cancers and do not effectively prolong the survival of patients, due to the unique location and heterogeneous characteristics of glioblastoma. Immunotherapy has shown a promising effect for many other tumors, but its application for glioma still has some challenges. The recent breakthrough of high-throughput liquid chromatography-mass spectrometry (LC-MS/MS) systems has allowed researchers to update their strategy for identifying and quantifying thousands of proteins in a much shorter time with lesser effort. The protein maps can contribute to generating a complete map of regulatory systems to elucidate tumor mechanisms. In particular, newly developed unicellular proteomics could be used to determine the microenvironment and heterogeneity. In addition, a large scale of differentiated proteins provides more ways to precisely classify tumor subtypes and construct a larger library for biomarkers and biotargets, especially for immunotherapy. A series of advanced proteomic studies have been devoted to the different aspects of immunotherapy for glioma, including monoclonal antibodies, oncolytic viruses, dendritic cell (DC) vaccines, and chimeric antigen receptor (CAR) T cells. Thus, the application of proteomics in immunotherapy may accelerate research on the treatment of glioblastoma. In this review, we evaluate the frontline applications of proteomics strategies for immunotherapy in glioblastoma research.

PDIA5 is Correlated With Immune Infiltration and Predicts Poor Prognosis in Gliomas

Gliomas are the most common and lethal primary malignant tumor of the brain. Routine treatment including surgical resection, chemotherapy, and radiotherapy produced limited therapeutic effect, while immunotherapy targeting the glioma microenvironment has offered a novel therapeutic option. PDIA5 protein is the member of PDI family, which is highly expressed in glioma and participates in glioma progression. Based on large-scale bioinformatics analysis, we discovered that PDIA5 expression level is upregulated in aggressive gliomas, with high PDIA5 expression predicting poor clinical outcomes. We also observed positive correlation between PDIA5 and immune infiltrating cells, immune related pathways, inflammatory activities, and other immune checkpoint members. Patients with high PDIA5 high-expression benefited from immunotherapies. Additionally, immunohistochemistry revealed that PDIA5 and macrophage biomarker CD68 were upregulated in high-grade gliomas, and patients with low PDIA5 level experienced favorable outcomes among 33 glioma patients. Single cell RNA sequencing exhibited that PDIA5 was in high level presenting in neoplastic cells and macrophages. Cell transfection and co-culture of glioma cells and macrophages revealed that PDIA5 in tumor cells mediated macrophages exhausting. Altogether, our findings indicate that PDIA5 overexpression is associated with immune infiltration in gliomas, and may be a promising therapeutic target for glioma immunotherapy.

Novel roles of VAT1 expression in the immunosuppressive action of diffuse gliomas

Standard treatment regimen of gliomas has almost reached a bottleneck in terms of survival benefit. Immunotherapy has been explored and applied in glioma treatment. Immunosuppression, as a hallmark of glioma, could be alleviated by inhibiting certain abnormally expressed biomarkers. Here, transcriptome data of 325 whole grade gliomas were collected from the CGGA database. The TCGA RNA sequencing database was used for validation. Western blot was used to verify the expression level of VAT1 on cellular level. The results showed that the expression of VAT1 was positively correlated with the grades of glioma as classified by WHO. A higher expression level of VAT1 was observed in the mesenchymal subtype of gliomas. The area under the curve suggested that the expression level of VAT1 might be a potential prognostic marker of mesenchymal subtype. In survival analysis, we found that patients with high VAT1 expression level tended to have shorter overall survival, which indicated the prognostic value of VAT1 expression. The results of gene ontology analysis showed that most biological processes of VAT1-related genes were involved in immune and inflammatory responses. The results of GSEA analysis showed a negative correlation between VAT1 expression and immune cells. We also identified that the expression of immune checkpoints increased with VAT1 expression. Therefore, the high expression level of VAT1 in patients with glioma was a potential indicator of a lower survival rate for patients with gliomas. Remarkably, VAT1 contributed to glioma-induced immunosuppression and might be a novel target in glioma immunotherapy.