CGCG clinical practice guidelines for the management of adult diffuse gliomas

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.

Identification of a Glycolysis-Related LncRNA Signature to Predict Survival in Diffuse Glioma Patients

Glycolysis refers to one of the critical phenotypes of tumor cells, regulating tumor cell phenotypes and generating sufficient energy for glioma cells. A range of noticeable genes [such as isocitrate dehydrogenase (IDH), phosphatase, and tensin homolog (PTEN), or Ras] overall impact cell proliferation, invasion, cell cycle, and metastasis through glycolysis. Moreover, long non-coding RNAs (LncRNAs) are increasingly critical to disease progression. Accordingly, this study aimed to identify whether glycolysis-related LncRNAs have potential prognostic value for glioma patients. First, co-expression network between glycolysis-related protein-coding RNAs and LncRNAs was established according to Pearson correlation (Filter: |r| > 0.5 & P < 0.001). Furthermore, based on univariate Cox regression, the Least Absolute Shrinkage and Selection Operator (LASSO) analysis and multivariate Cox regression, a predictive model were built; vital glycolysis-related LncRNAs were identified; the risk score of every single patient was calculated. Moreover, receiver operating characteristic (ROC) curve analysis, gene set enrichment analysis (GSEA), GO and KEGG enrichment analysis were performed to assess the effect of risk score among glioma patients. 685 cases (including RNA sequences and clinical information) from two different cohorts of the Chinese Glioma Genome Atlas (CGGA) database were acquired. Based on the mentioned methods, the risk score calculation formula was yielded as follows: Risk score = (0.19 × EXP_FOXD2-AS1) + (−0.27 × EXP_AC062021.1) + (−0.16 × EXP_AF131216.5) + (−0.05 × EXP_LINC00844) + (0.11 × EXP_CRNDE) + (0.35 × EXP_LINC00665). The risk score was independently related to prognosis, and every single mentioned LncRNAs was significantly related to the overall survival of patients. Moreover, functional enrichment analysis indicated that the biologic process of the high-risk score was mainly involved in the cell cycle and DNA replication signaling pathway. This study confirmed that glycolysis-related LncRNAs significantly impact poor prognosis and short overall survival and may act as therapeutic targets in the future.

A novel gene signature based on five immune checkpoint genes predicts the survival of glioma

BACKGROUND

Glioma is the most common and fatal type of nerve neoplasm in the central nervous system. Several biomarkers have been considered for prognosis prediction, which is not accurate enough. We aimed to carry out a gene signature related to the expression of immune checkpoints which was enough for its performance in prediction.

METHODS

Gene expression of immune checkpoints in TGGA database was filtrated. The 5 selected genes underwent verification by COX and Lasso-COX regression. Next, the selected genes were included to build a novel signature for further analysis.

RESULTS

Patients were sub-grouped into high and low risk according to the novel signature. Immune response, clinicopathologic characters, and survival showed significant differences between those 2 groups. Terms including "naive," "effector," and "IL-4" were screened out by GSEA. The results showed strong relevance between the signature and immune response.

CONCLUSIONS

We constructed a gene signature with 5 immune checkpoints. The signature predicted survival effectively. The novel signature performed more functional than previous biomarkers.

A Novel Signature Constructed by RNA-Binding Protein Coding Genes to Improve Overall Survival Prediction of Glioma Patients

RNA binding proteins (RBPs) have been reported to be involved in cancer malignancy but related functions in glioma have been less studied. Herein, we screened 14 prognostic RBP genes and constructed a risk signature to predict the prognosis of glioma patients. Univariate Cox regression was used to identify overall survival (OS)-related RBP genes. Prognostic RBP genes were screened and used to establish the RBP-signature using the least absolute shrinkage and selection operator (Lasso) method in The Cancer Genome Atlas (TCGA) cohort. The 14 RBP genes signature showed robust and stable prognostic value in the TCGA training (n = 562) cohort and in three independent validation cohorts (Chinese Glioma Genome Atlas [CGGA]seq1, CGGAseq2, and GSE16011 datasets comprising 303, 619, and 250 glioma patients, respectively). Risk scores were calculated for each patient and high-risk gliomas were defined by the median risk score in each cohort. Survival analysis in subgroups of glioma patients showed that the RBP-signature retained its prognostic value in low-grade gliomas (LGGs) and glioblastomas (GBM)s. Univariate and multivariate Cox regression analysis in each dataset and the meta cohort revealed that the RBP-signature stratification could efficiently recognize high-risk gliomas [Hazard Ratio (HR):3.662, 95% confidence interval (CI): 3.187–4.208, p < 0.001] and was an independent prognostic factor for OS (HR:1.594, 95% CI: 1.244–2.043, p < 0.001). Biological process and KEGG pathway analysis revealed the RBP gene signature was associated with immune cell activation, the p53 signaling pathway, and the PI3K-Akt signaling pathway and so on. Moreover, a nomogram model was constructed for clinical application of the RBP-signature, which showed stable predictive ability. In summary, the RBP-signature could be a robust indicator for prognostic evaluation and identifying high-risk glioma patients.

A comprehensive model including preoperative peripheral blood inflammatory markers for prediction of the prognosis of diffuse spinal cord astrocytoma following surgery

PURPOSE

Due to the rarity of diffuse spinal cord astrocytoma, an effective model is still lacking to stratify their prognosis. Here, we aimed to establish a prognostic model through comprehensively evaluating clinicopathological features and preoperative peripheral blood inflammatory markers in 89 cases.

METHODS

We performed univariate and multivariate Cox regression to identify prognosis factors. The Kaplan-Meier curves and ROC curves were employed to compare the prognostic value of selected factors.

RESULTS

In addition to clinicopathological factors, we revealed the preoperative peripheral blood leukocyte count, neutrophils-to-lymphocytes ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were also significantly correlated with overall survival of spinal cord astrocytoma in univariate Cox regression, and NLR was still significant in multivariate Cox analysis. Further, we demonstrated that NLR ≤ 3.65 and preoperative McCormick score (MMS) ≤ 3 were independently correlated with better survival of WHO grade IV tumors. Meanwhile, Ki-67 < 10% and resection extent ≥ 90% were independent prognostic factors in WHO grade II/III tumors. Finally, we developed a prognostic model that had better predictive efficiencies than WHO grade and histological grade for 1-year (AUC = 76.6), 2- year (AUC = 80.9), and 3-year (AUC = 80.3) survival. This model could classify tumors into 4 classifications with increasingly poor prognosis: 1, WHO grade II/III, with Ki-67 < 10% and resection extent ≥ 90%; 2, WHO grade II/III, Ki-67 ≥ 10% or resection < 90%; 3, WHO grade IV, NLR ≤ 3.65 and MMS ≤ 3; 4, WHO grade IV, with NRL > 3.65 or MMS = 4.

CONCLUSION

We successfully constructed a comprehensive prognostic model including preoperative peripheral blood inflammatory markers, which can stratify diffuse spinal cord astrocytoma into 4 subgroups.

Predictive value of MGMT promoter methylation on the survival of TMZ treated IDH-mutant glioblastoma

Objective

O6methylguanine-DNA methyltransferase (MGMT) promoter methylation is a biomarker widely used to predict the sensitivity of IDH-wildtype glioblastoma to temozolomide therapy. Given that the IDH status has critical effects on the survival and epigenetic features of glioblastoma, we aimed to assess the role of MGMT promoter methylation in IDH-mutant glioblastoma.

Methods

This study included 187 IDH-mutant glioblastomas and used 173 IDH-wildtype glioblastomas for comparison. Kaplan-Meier curves and multivariate Cox regression were used to study the predictive effects.

Results

Compared with IDH-wildtype glioblastomas, IDH-mutant glioblastomas showed significantly higher (P < 0.0001) MGMT promoter methylation. We demonstrated that MGMT promoter methylation status, as determined by a high cutoff value (≥30%) in pyrosequencing, could be used to significantly stratify the survival of 50 IDH-mutant glioblastomas receiving temozolomide therapy (cohort A); this result was validated in another cohort of 25 IDH-mutant glioblastomas (cohort B). The median progression-free survival and median overall survival in cohort A were 9.33 and 13.76 months for unmethylated cases, and 18.37 and 41.61 months for methylated cases, and in cohort B were 6.97 and 9.10 months for unmethylated cases, and 23.40 and 26.40 months for methylated cases. In addition, we confirmed that the MGMT promoter methylation was significantly (P = 0.0001) correlated with longer OS in IDH-mutant patients with GBM, independently of age, gender distribution, tumor type (primary or recurrent/secondary), and the extent of resection.

Conclusions

MGMT promoter methylation has predictive value in IDH-mutant glioblastoma, but its cutoff value should be higher than that for IDH-wildtype glioblastoma.

miR-665 is downregulated in glioma and inhibits tumor cell proliferation, migration and invasion by targeting high mobility group box 1

Glioma is the most common brain tumor in adults. microRNAs (miRNAs/miRs) play an essential role in tumor development and progression. The present study aimed to investigate the potential clinical significance and function of miR-665 in glioma. Reverse transcription-quantitative PCR analysis was used to detect the expression of miR-665 in glioma tissues and cells. Survival curves were constructed using the Kaplan-Meier method. Cox regression analysis was performed to investigate the prognostic significance of miR-665. Cell Counting Kit-8 and Transwell assays were used to evaluate the role of miR-665 in glioma. Bioinformatics analysis and Dual-luciferase reporter assays were used to predict the putative direct targets of miR-665. Western blotting was used to evaluate the activity of the Wnt/β-catenin pathway. The relative expression of miR-665 was decreased in glioma tissues and cells and this downregulation was significantly associated with the Karnofsky performance scale score and World Health Organisation grade. Patients with glioma with low miR-665 expression had a shorter overall survival time compared with the high expression group. Besides, overexpression of miR-665 suppressed the proliferation, migration and invasion of glioma cells, while knockdown of miR-665 promoted these cellular behaviors. High mobility group box (HMGB)1 was a direct target of miR-665. It was also demonstrated that miR-665 may suppress glioma progression by targeting HMGB1 and inhibiting the Wnt/β-catenin pathway. Taken together, these data suggested that miR-665 may have a tumor suppressor role in glioma by targeting HMGB1. Therefore, miR-665 may be a novel prognostic biomarker and the miR-665/HMGB1 axis may be a novel therapeutic target for the treatment of glioma.

An Immune Gene-Related Five-lncRNA Signature for to Predict Glioma Prognosis

Background

The tumor immune microenvironment is closely related to the malignant progression and treatment resistance of glioma. Long non-coding RNA (lncRNA) plays a regulatory role in this process. We investigated the pathological mechanisms within the glioma microenvironment and potential immunotherapy resistance related to lncRNAs.

Method

We downloaded datasets derived from glioma patients and analyzed them by hierarchical clustering. Next, we analyzed the immune microenvironment of glioma, related gene expression, and patient survival. Coexpressed lncRNAs were analyzed to generate a model of lncRNAs and immune-related genes. We analyzed the model using survival and Cox regression. Then, univariate, multivariate, receiver operating characteristic (ROC), and principle component analysis (PCA) methods were used to verify the accuracy of the model. Finally, GSEA was used to evaluate which functions and pathways were associated with the differential genes.

Results

Normal brain tissue maintains a low-medium immune state, and gliomas are clearly divided into three groups (low to high immunity). The stromal, immune, and estimate scores increased along with immunity, while tumor purity decreased. Further, human leukocyte antigen (HLA), programmed cell death-1 (PDL1), T cell immunoglobulin and mucin domain 3 (TIM-3), B7-H3, and cytotoxic T lymphocyte-associated antigen-4 (CTLA4) expression increases concomitantly with immune state, and the patient prognosis worsens. Five immune gene-related lncRNAs (AP001007.1, LBX-AS1, MIR155HG, MAPT-AS1, and LINC00515) were screened to construct risk models. We found that risk scores are related to patient prognosis and clinical characteristics, and are positively correlated with PDL1, TIM-3, and B7-H3 expression. These lncRNAs may regulate the tumor immune microenvironment through cytokine-cytokine receptor interactions, complement, and coagulation cascades, and may promote CD8 + T cell, regulatory T cell, M1 macrophage, and infiltrating neutrophils activity in the high-immunity group. In vitro, the abnormal expression of immune-related lncRNAs and the relationship between risk scores and immune-related indicators (PDL1, CTLA4, CD3, CD8, iNOS) were verified by q-PCR and immunohistochemistry (IHC).

Conclusion

For the first time, we constructed immune gene-related lncRNA risk models. The risk score may be a new biomarker for tumor immune subtypes and provide molecular targets for glioma immunotherapy.

A novel integrated system using patient-derived glioma cerebral organoids and xenografts for disease modeling and drug screening

A physiologically relevant glioma tumor model is important to the study of disease progression and screening drug candidates. However, current preclinical glioma models lack the brain microenvironment, and the established tumor cell lines do not represent glioma biology and cannot be used to evaluate the therapeutic effect. Here, we reported a real-time integrated system by generating 3D ex vivo cerebral organoids and in vivo xenograft tumors based on glioma patient-derived tissues and cells. Our system faithfully recapitulated the histological features, response to chemotherapy drugs, and clinical progression of their corresponding parental tumors. Additionally, our model successfully identified a case from a grade II astrocytoma patient with typical grade IV GBM features in both organoids and xenograft models, which mimicked the disease progression of this patient. Further genomic and transcriptomic characterization was associated with individual clinical features. We have demonstrated the "GBM-&Normal-like" signature to predict prognosis. In conclusion, we developed an integrated system of parallel models from patient-derived glioma cerebral organoids and xenografts for understanding the glioma biology and prediction of response to chemotherapy drugs, which might lead to a new strategy for personalized treatment for this deadly disease.

Redox Regulator GLRX Is Associated With Tumor Immunity in Glioma

Glutaredoxin is central to cellular redox chemistry and regulates redox homeostasis and malignant progression of many cancers. In glioma, the role of its coding gene (GLRX) remains unclear. We aimed to elucidate the role of glutaredoxin at the transcriptome level and its clinical prognostic value in glioma. In total, we evaluated 1,717 glioma samples with transcriptome data and corresponding clinical data as well as single-cell sequencing data from 6 glioma patients from publicly available databases. Gene set variation analysis and gene ontology analysis were performed to reveal the biological function of GLRX. The immune cell enrichment score was calculated by GSVA analysis. Single-cell sequencing data was visualized by t-distributed stochastic neighbor embedding analysis. The prognostic value of GLRX in glioma was verified by the Kaplan-Meier curve and multivariate COX analysis. GLRX was found to be highly enriched in gliomas of higher grades with wild-type IDH, without 1p/19q co-deletion, and with a methylated MGMT promoter. Moreover, GLRX could be a potential marker for the mesenchymal molecular subtype of gliomas. The expression of GLRX was closely related to the tumor immune process, immune checkpoints, and inflammatory factors with GLRX being specifically expressed in M0 macrophages. GLRX is also shown to be an independent prognostic factor in glioma. Altogether, our study outcomes show that GLRX is highly enriched in malignant gliomas and is closely related to the tumor immune microenvironment. Therefore, GLRX-targeted cell redox regulatory therapy may enhance the efficacy of glioma immunotherapy.

SLC39A1 contribute to malignant progression and have clinical prognostic impact in gliomas

BACKGROUND

Gliomas are one of the most common primary tumors of the central nervous system, and have an unfavorable prognosis. SLC39A1 is a zinc ion transport protein which inhibits the progression of prostate cancer. By studying the role and mechanism of SLC39A1 in the progression of gliomas, perhaps a new therapeutic target can be provided for their treatment.

METHOD

The TCGA, CCGA, GSE16011, GSE44971 and GSE11260 data sets were employed to evaluate the expression level of SLC39A1 in paracancerous and glioma tissues. In addition, Kaplan-Meier analysis, Cox analysis, and the ESTIMATE and CIBERSORT algorithms were used to analyze its prognostic value and immune infiltration correlation. A CCK-8 and flow cytometer were used to measure the effects of SLC39A1 on U87 cell proliferation or apoptosis; RT-qPCR and western blot were used to detect its effects on the expression of MMP2\MMP9.

RESULTS

SLC39A1 has up-regulated expression in glioma tissues. High SLC39A1 expression predicted significantly worse survival. Univariate and multivariate analysis show that SLC39A1 independently indicated poor prognosis in patients with gliomas. The expression of SLC39A1 is significantly correlated with clinical pathological parameters such as Grade, IDH mutation status, and 1p19q codeletion status. In vitro experimental results show that SLC39A1 promotes proliferation of glioma cells, inhibits their apoptosis, and promotes expression of MMP2\MMP9. In addition, it may affect infiltration of immune cells into the glioma microenvironment.

CONCLUSION

SLC39A1 may serve as a new prognostic biomarker and potential target for treatment of gliomas.

A novel methylation signature predicts radiotherapy sensitivity in glioma

Glioblastoma (GBM) is the most common and malignant cancer of the central nervous system, and radiotherapy is widely applied in GBM treatment; however, the sensitivity to radiotherapy varies in different patients. To solve this clinical dilemma, a radiosensitivity prediction signature was constructed in the present study based on genomic methylation. In total, 1044 primary GBM samples with clinical and methylation microarray data were involved in this study. LASSO-COX, GSVA, Kaplan–Meier survival curve analysis, and COX regression were performed for the construction and verification of predictive models. The R programming language was used as the main tool for statistical analysis and graphical work. Via the integration analysis of methylation and the survival data of primary GBM, a novel prognostic and radiosensitivity prediction signature was constructed. This signature was found to be stable in prognosis prediction in the TCGA and CGGA databases. The possible mechanism was also explored, and it was found that this signature is closely related to DNA repair functions. Most importantly, this signature could predict whether GBM patients could benefit from radiotherapy. In summary, a radiosensitivity prediction signature for GBM patients based on five methylated probes was constructed, and presents great potential for clinical application.

Secretory Pathway Kinase FAM20C, a Marker for Glioma Invasion and Malignancy, Predicts Poor Prognosis of Glioma

Purpose

Glioblastoma (GBM) is the most lethal primary cancer in adult central nervous system, and new strategies are desperately needed. The secretory pathway kinase or kinase-like proteins (SPKKPs) have been shown to mediate multiple physiological functions by phosphorylating extracellular proteins and proteoglycans. However, their roles in cancers, especially GBM, remain poorly defined.

Methods

The least absolute shrinkage and selection operator (LASSO) regression was employed for establishing the SPKKPs signature for IDH wild type (wt) GBM prognosis. Integrative analyses with multiple datasets were employed to identify the core member of this gene family in glioma. The receiver operator characteristic (ROC) curves and immunohistochemistry were further used for evaluating its association with progressive malignancy in glioma and GBM patients’ survival, respectively. Gene set enrichment analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to interpret its functions in GBM, which were further verified in vitro.

Results

A SPKKPs classifier was constructed with 3 genes of this family. This signature could effectively distinguish IDH wt GBM survival. Family with sequence similarity 20 C (FAM20C) was further identified as the core member of this family in glioma. Elevated FAM20C expression was not only closely correlated with glioma malignancy progression and the mesenchymal subtype of GBM but also indicated unfavorable survival of GBM patients. FAM20C was also found to be associated with the disrupted immune response in GBM microenvironment and was required for the migration of glioma and immune cells.

Conclusion

These data indicate that the potential of FAM20C serving as a predictive molecule and a therapeutic target for GBM.

Effects of oncolytic viruses and viral vectors on immunity in glioblastoma

Glioblastoma (GBM) is regarded as an incurable disease due to its poor prognosis and limited treatment options. Virotherapies were once utilized on cancers for their oncolytic effects. And they are being revived on GBM treatment, as accumulating evidence presents the immunogenic effects of virotherapies in remodeling immunosuppressive GBM microenvironment. In this review, we focus on the immune responses induced by oncolytic virotherapies and viral vectors in GBM. The current developments of GBM virotherapies are briefly summarized, followed by a detailed depiction of their immune response. Limitations and lessons inferred from earlier experiments and trials are discussed. Moreover, we highlight the importance of engaging the immune responses induced by virotherapies into the multidisciplinary management of GBM.

Circ-VPS18 Knockdown Enhances TMZ Sensitivity and Inhibits Glioma Progression by MiR-370/RUNX1 Axis

Glioma is a prevalent primary brain tumor. Temozolomide (TMZ) has been used to treat glioma. However, the resistance of TMZ to glioma poses heavy burden to glioma treatment. In this study, the effects of glioma resistance to TMZ and underlying mechanism were revealed. The expression levels of circ-VPS18, microRNA-370 (miR-370) and runt-related transcription factor 1 (RUNX1) were detected by quantitative real-time polymerase chain reaction (qRT-PCR). The protein expression of RUNX1, multidrug resistance-associated protein 1 (MRP1), and multi-drug resistance gene-1 (MDR1) was determined by western blot. The functional effects of circ-VPS18 knockdown on TMZ sensitivity and glioma progression were revealed by cell counting kit-8 proliferation (CCK-8), flow cytometry, and transwell assays. The impacts of circ-VPS18 deletion on TMZ sensitivity in vivo were illustrated by in vivo tumor formation assay. The binding relationship between miR-370 and circ-VPS18 or RUNX1 was predicted by starBase v2.0 online database and identified by dual-luciferase reporter assay. Circ-VPS18 expression and the mRNA and protein levels of RUNX1 were dramatically upregulated, and miR-370 expression was significantly downregulated in glioma cells, TMZ-resistant glioma tissues, or tissue compared with control groups. Functionally, circ-VPS18 knockdown improved TMZ sensitivity, induced cell apoptosis, whereas repressed cell viability, migration and invasion in U251/TR and LN229/TR cells, which was reversed by miR-370 inhibitor. Additionally, RUNX1 overexpression hindered the effects of miR-370 on TMZ sensitivity and glioma progression. Circ-VPS18 knockdown enhanced TMZ sensitivity in vivo. Mechanistically, circ-VPS18 functioned as a sponge of miR-370 and miR-370 targeted RUNX1. Circ-VPS18 knockdown improved TMZ sensitivity and repressed glioma progression by sponging miR-370 to downregulate RUNX1 expression, which provided a new insight in further studying glioma resistance to TMZ.

Clinical practice guidelines for the management of adult diffuse gliomas

To follow the revision of the fourth edition of WHO classification and the recent progress on the management of diffuse gliomas, the joint guideline committee of Chinese Glioma Cooperative Group (CGCG), Society for Neuro-Oncology of China (SNO-China) and Chinese Brain Cancer Association (CBCA) updated the clinical practice guideline. It provides recommendations for diagnostic and management decisions, and for limiting unnecessary treatments and cost. The recommendations focus on molecular and pathological diagnostics, and the main treatment modalities of surgery, radiotherapy, and chemotherapy. In this guideline, we also integrated the results of some clinical trials of immune therapies and target therapies, which we think are ongoing future directions. The guideline should serve as an application for all professionals involved in the management of patients with adult diffuse glioma and also a source of knowledge for insurance companies and other institutions involved in the cost regulation of cancer care in China and other countries.

Transcriptional Characteristics of IDH-Wild Type Glioma Subgroups Highlight the Biological Processes Underlying Heterogeneity of IDH-Wild Type WHO Grade IV Gliomas

Isocitric dehydrogenase (IDH)-wild type diffuse gliomas, which have a poorer prognosis than their IDH-mutant counterparts, are also accompanied with high heterogeneity. Here, we aimed to identify the key biological processes associated with the three groups of IDH-wild type diffuse gliomas in 323 patients. By The Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) update 3 recommendation, the three groups are Group A, diffuse astrocytic glioma, World Health Organization (WHO) grade II/III; Group B, diffuse astrocytic glioma, with one (or more) of the three genetic alterations: TERT promoter mutation, EGFR gene amplification, gain of chromosome 7 combined with loss of chromosome 10, WHO grade IV; and Group C, glioblastoma, WHO grade IV. Consistent with their histologic and genetic molecular features, we successfully identified that biological activities associated with “cell cycle” and “cell mitosis” are significantly elevated in Group B compared with Group A; microenvironment-related hallmarks “angiogenesis” and “hypoxia,” and biological processes of “extracellular matrix,” “immune response,” and “positive regulation of transcriptional activities” were more enriched in Group C than Group B. We also constructed a nine-gene signature from differentially expressed genes among the three groups to further stratify the WHO grade IV gliomas (Groups B and C) whose survival cannot be clearly stratified by current classification systems. This signature was an independent prognosis factor for WHO grade IV gliomas and had better prognostic value than other known factors in both training and validation dataset. In addition, the signature risk score was positively correlated with the amount of infiltrated immune cells, expression of immune checkpoints, and the genes enriched in biological processes of “immune response,” “cell cycle,” and “extracellular matrix.” The bioinformatic analysis results were also validated by immunohistochemistry and patient-derived cell proliferation assay. Overall, our findings revealed the key biological processes underlying the new classifications of IDH-wild type diffuse glioma. Meanwhile, we constructed a signature, which could properly stratify the prognosis, cell proliferation activates, extracellular matrix-mediated biological activities, and immune-microenvironment of IDH-wild type WHO grade IV gliomas.

The Prognostic Role of Glutathione Peroxidase 1 and Immune Infiltrates in Glioma Investigated Using Public Datasets

BACKGROUND Glutathione peroxidase 1 (GPX1) is an essential component of the intracellular antioxidant enzyme system, but little is known about the role of GPX1 in the progression of malignancy in gliomas. Using public datasets, this study investigated the prognostic role of GPX1 and immune infiltrates in glioma. MATERIAL AND METHODS We investigated GPX1 expression levels in different cancers using the ONCOMINE and Tumor Immune Estimation Resource (TIMER) datasets. We also explored the prognostic landscape of GPX1 in gliomas based on The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets. Some significant pathways were identified by function enrichment analysis. We then explored the association between GPX1 expression and levels of tumor-infiltrating immune cells based on TIMER and Gene Expression Profiling Interactive Analysis (GEPIA) datasets. RESULTS Expression of GPX1 in brain and central nervous system cancers is at a much high level than in normal tissues, and it is higher in glioblastoma (GBM) than in lower-grade glioma (LGG). We found GPX1 expression to be positively correlated with the malignant clinicopathologic characteristics of gliomas. Univariate analysis and multivariate analysis revealed that overexpression of GPX1 was correlated with a worse prognosis in patients, and a nomogram indicated that GPX1 expression can predict clinical prognosis of glioma. Function enrichment analysis showed that some important pathways are related to glioma malignancy. Expression of GPX1 was positively associated with infiltrating levels of 6 types of immune cells and most of their gene markers in GBM and LGG. CONCLUSIONS These results indicate that GPX1 is an independent prognostic factor and a novel biomarker for predicting the progression of malignancy in gliomas, which is associated with immune infiltration.

A novel DNA repair-related nomogram predicts survival in low-grade gliomas

Aims

We aimed to create a tumor recurrent‐based prediction model to predict recurrence and survival in patients with low‐grade glioma.

Methods

This study enrolled 291 patients (188 in the training group and 103 in the validation group) with clinicopathological information and transcriptome sequencing data. LASSO‐COX algorithm was applied to shrink predictive factor size and build a predictive recurrent signature. GO, KEGG, and GSVA analyses were performed for function annotations of the recurrent signature. The calibration curves and C‐Index were assessed to evaluate the nomogram's performance.

Results

This study found that DNA repair functions of tumor cells were significantly enriched in recurrent low‐grade gliomas. A predictive recurrent signature, built by the LASSO‐COX algorithm, was significantly associated with overall survival and progression‐free survival in low‐grade gliomas. Moreover, function annotations analysis of the predictive recurrent signature exhibited that the signature was associated with DNA repair functions. The nomogram, combining the predictive recurrent signature and clinical prognostic predictors, showed powerful prognostic ability in the training and validation groups.

Conclusion

An individualized prediction model was created to predict 1‐, 2‐, 3‐, 5‐, and 10‐year survival and recurrent rate of patients with low‐grade glioma, which may serve as a potential tool to guide postoperative individualized care.

Single-Cell RNA-Sequencing Shift in the Interaction Pattern Between Glioma Stem Cells and Immune Cells During Tumorigenesis

Glioblastoma is one of the most common neoplasms in the central nervous system characterized by limited immune response and unlimited expansion capability. Cancer stem cells (GSCs), a small fraction of the tumor cells, possess a pivotal regulation capability in the tumor microenvironment with a superior proliferation ability. We aimed to reveal the interaction between glioma stem cells (GSCs) and immune cells during tumorigenesis. Single-cell sequencing data from seven surgical specimens of glioblastoma patients and patient-derived GSCs cocultured with peripheral leukocytes were used for the analysis. Cell grouping and trajectory analysis were performed using Seurat and Monocle 3 packages in R software. The gene set of Cancer Genome Anatomy Project was used to define different cell types. Cells with the ability of proliferation and differentiation in glioblastoma tissue were defined as GSCs, which had a similar expression pattern to that in the GSCs in vitro. Astrocytes in glioblastoma were mainly derived from differentiated GSCs, while oligodendrocytes were most likely to be derived from different precursor cells. No remarkable evolutionary trajectory was observed among the subgroups of T cells in glioblastoma. The immune checkpoint interaction between GSCs and immune cells was changed from stimulatory to inhibitory during tumorigenesis. The patient-derived GSCs system is an ideal model for GSC research. The above research revealed that the interaction pattern between GSC glioma stem cells and immune cells during tumorigenesis provides a theoretical basis for GSC glioma stem cell-targeted immunotherapy.

Long-term efficacy of surgical resection with or without adjuvant therapy for treatment of secondary glioblastoma in adults

Background

There are limited studies on treatment strategies and associated clinical outcomes in patients with secondary glioblastoma (sGBM). We sought to investigate the prognostic factors and treatment decisions in a retrospective cohort of patients with sGBM.

Methods

One hundred and seventy-one patients with sGBM who met the screening criteria were included in this study. Kaplan–Meier survival analysis and Cox survival analysis were used to detect prognostic factors. R (v3.5.0) and SPSS software (v25.0, IBM) were used to perform statistical analyses.

Results

The median overall survival was 303 days (range 23–2237 days) and the median progression-free survival was 229 days (range 33–1964 days) in patients with sGBM. When assessing the relationship between adjuvant treatment outcome and extent of resection (EOR), the results showed that patients underwent gross total resection can benefit from postoperative radiotherapy and chemotherapy, but not in patients underwent subtotal resection. In addition, we also found that aggressive adjuvant therapy can significantly improve clinical outcomes of IDH1-mutated patients but no significant prognostic value for IDH1-wildtyped patients. The univariate Cox regression analyses demonstrated that EOR, adjuvant therapy, and postoperative Karnofsky Performance Scores were prognostic factors for patients with sGBM, and multivariate COX analysis confirmed that adjuvant therapy and EOR were independent prognostic factors.

Conclusions

For patients with sGBM, aggressive postoperative adjuvant therapy after gross total resection was recommended. However, we did not detect a benefit in IDH1-wildtype patients in our cohort.

Characterization and prognostic significance of alternative splicing events in lower-grade diffuse gliomas

Alternative splicing (AS) is assumed to play important roles in the progression and prognosis of cancer. Currently, the comprehensive analysis and clinical relevance of AS in lower-grade diffuse gliomas have not been systematically addressed. Here, we gathered alternative splicing data of lower-grade diffuse gliomas from SpliceSeq. Based on the Percent Spliced In (PSI) values of 515 lower-grade diffuse glioma patients from the Cancer Genome Atlas (TCGA), we performed subtype-differential AS analysis and consensus clustering to determine robust clusters of patients. A total of 48 050 AS events in 10 787 genes in lower-grade diffuse gliomas were profiled. Subtype-differential splicing analysis and functional annotation revealed that spliced genes were significantly enriched in numerous cancer-related biological phenotypes and signalling pathways. Consensus clustering using AS events identified three robust clusters of patients with distinguished pathological and prognostic features. Moreover, each cluster was also associated with distinct genomic alterations. Finally, we developed and validated an AS-related signature with Cox proportional hazards model. The signature, significantly associated with clinical and molecular features, could serve as an independent prognostic factor for lower-grade diffuse gliomas. Thus, our results indicated that AS events could discriminate molecular subtypes and have prognostic impact in lower-grade diffuse gliomas.

Proteomics identifies EGF-like domain multiple 7 as a potential therapeutic target for epidermal growth factor receptor-positive glioma

Background

Glioma, the most frequent primary tumor of the central nervous system, has poor prognosis. The epidermal growth factor receptor (EGFR) pathway and angiogenesis play important roles in glioma growth, invasion, and recurrence. The present study aimed to use proteomic methods to probe into the role of the EGF‐EGFR‐angiogenesis axis in the tumorigenesis of glioma and access the therapeutic efficacy of selumetinib on glioma.

Methods

Proteomic profiling was used to characterize 200 paired EGFR‐positive and EGFR‐negative glioma tissues of all pathological types. The quantitative mass spectrometry data were used for systematic analysis of the proteomic profiles of 10 EGFR‐positive and 10 EGFR‐negative glioma cases. Consensus‐clustering analysis was used to screen target proteins. Immunofluorescence analysis, cell growth assay, and intracranial xenograft experiments were used to verify and test the therapeutic effect of selumetinib on glioma.

Results

Advanced proteomic screening demonstrated that the expression of EGF‐like domain multiple 7 (EGFL7) was higher in EGFR‐positive tumor tissues than in EGFR‐negative tumor tissues. In addition, EGFL7 could act as an activator in vitro and in vivo to promote glioma cell proliferation. EGFL7 was associated strongly with EGFR and prognosis. EGFL7 knockdown effectively suppressed glioma cell proliferation. Selumetinib treatment showed tumor reduction effect in EGFR‐positive glioblastoma xenograft mouse model.

Conclusions

EGFL7 is a potential diagnostic biomarker and therapeutic target of glioma. Selumetinib could target the EGFR pathway and possibly improve the prognosis of EGFR‐positive glioma.

Interventions to reduce the time to diagnosis of brain tumours

BACKGROUND

Brain tumours are recognised as one of the most difficult cancers to diagnose because presenting symptoms, such as headache, cognitive symptoms, and seizures, may be more commonly attributable to other, more benign conditions. Interventions to reduce the time to diagnosis of brain tumours include national awareness initiatives, expedited pathways, and protocols to diagnose brain tumours, based on a person's presenting symptoms and signs; and interventions to reduce waiting times for brain imaging pathways. If such interventions reduce the time to diagnosis, it may make it less likely that people experience clinical deterioration, and different treatment options may be available.

OBJECTIVES

To systematically evaluate evidence on the effectiveness of interventions that may influence: symptomatic participants to present early (shortening the patient interval), thresholds for primary care referral (shortening the primary care interval), and time to imaging diagnosis (shortening the secondary care interval and diagnostic interval). To produce a brief economic commentary, summarising the economic evaluations relevant to these interventions.

SEARCH METHODS

For evidence on effectiveness, we searched CENTRAL, MEDLINE, and Embase from January 2000 to January 2020; Clinicaltrials.gov to May 2020, and conference proceedings from 2014 to 2018. For economic evidence, we searched the UK National Health Services Economic Evaluation Database from 2000 to December 2014.

SELECTION CRITERIA

We planned to include studies evaluating any active intervention that may influence the diagnostic pathway, e.g. clinical guidelines, direct access imaging, public health campaigns, educational initiatives, and other interventions that might lead to early identification of primary brain tumours. We planned to include randomised and non-randomised comparative studies. Included studies would include people of any age, with a presentation that might suggest a brain tumour.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed titles identified by the search strategy, and the full texts of potentially eligible studies. We resolved discrepancies through discussion or, if required, by consulting another review author.

MAIN RESULTS

We did not identify any studies for inclusion in this review. We excluded 115 studies. The main reason for exclusion of potentially eligible intervention studies was their study design, due to a lack of control groups. We found no economic evidence to inform a brief economic commentary on this topic.

AUTHORS' CONCLUSIONS

In this version of the review, we did not identify any studies that met the review inclusion criteria for either effectiveness or cost-effectiveness. Therefore, there is no evidence from good quality studies on the best strategies to reduce the time to diagnosis of brain tumours, despite the prioritisation of research on early diagnosis by the James Lind Alliance in 2015. This review highlights the need for research in this area.

Classification of diffuse lower-grade glioma based on immunological profiling

Transcriptomic data derived from bulk sequencing have been applied to delineate the tumor microenvironment (TME) and define immune subtypes in various cancers, which may facilitate the design of immunotherapy treatment strategies. We herein gathered published gene expression data from diffuse lower-grade glioma (LGG) patients to identify immune subtypes. Based on the immune gene profiles of 402 LGG patients from The Cancer Genome Atlas, we performed consensus clustering to determine robust clusters of patients, and evaluated their reproducibility in three Chinese Glioma Genome Atlas cohorts. We further integrated immunogenomics methods to characterize the immune environment of each subtype. Our analysis identified and validated three immune subtypes-Im1, Im2, and Im3-characterized by differences in lymphocyte signatures, somatic DNA alterations, and clinical outcomes. Im1 had a higher infiltration of CD8+ T cells, Th17, and mast cells. Im2 was defined by elevated cytolytic activity, exhausted CD8+ T cells, macrophages, higher levels of aneuploidy, and tumor mutation burden, and these patients had worst outcome. Im3 displayed more prominent T helper cell and APC coinhibition signatures, with elevated pDCs and macrophages. Each subtype was associated with distinct somatic alterations. Moreover, we applied graph structure learning-based dimensionality reduction to the immune landscape and revealed significant intracluster heterogeneity with Im2 subtype. Finally, we developed and validated an immune signature with better performance of prognosis prediction. Our results demonstrated the immunological heterogeneity within diffuse LGG and provided valuable stratification for the design of future immunotherapy.

Bioinformatic Profiling of Prognosis-Related Genes in Malignant Glioma Microenvironment

BACKGROUND Gliomas are the most common primary tumors of the brain and spinal cord. The tumor microenvironment (TME) is the cellular environment in which tumors exist. This study aimed to identify the role of the TME and the effects of genes involved in the TME of malignant glioma. MATERIAL AND METHODS The ESTIMATE algorithms in the R package were used to calculate the immune and stromal scores of samples in the TCGA and GSE4290 datasets. The associations of stromal and immune scores with clinicopathological characteristics and overall survival of malignant glioma patients were assessed by analysis of variance and Kaplan-Meier analysis. Differentially expressed genes (DEGs) were obtained through the median immune and stromal score using the R package "limma". Functional enrichment analysis and the PPI network MCODE were used to analyze DEGs. RESULTS Increased immune and stromal scores were closely related with advanced glioma grade and poor prognosis (all P<0.01). In total, 558 DEGs were found and most were related to tumor prognosis. Functional enrichment analysis showed that DEGs were associated with cell-matrix regulation and immune response. Four hub modules related to tumor angiogenesis, collagen formation, and immune response were found and analyzed. Previously overlooked microenvironment-related genes such as LAMB1, FN1, ACTN1, TRIM, SERPINH1, CYBA, LAIR1, and LILRB2 showed prognostic values in malignant glioma patients. CONCLUSIONS The glioma stromal/immune scores are closely related to glioma grade, histology, and survival time. Some glioma microenvironment-related genes including LAMB1, FN1, ACTN1, TRIM6, SERPINH1, CYBA, LAIR1, and LILRB2 show prognostic values in malignant gliomas and serve as potential biomarkers.

Clinicopathological characteristics and survival of spinal cord astrocytomas

Background

Due to their rarity, the clinicopathological characteristics and prognostic factors of spinal cord gliomas are still unclear. Here, we aimed to clarify these issues in a cohort of 108 spinal cord astrocytomas.

Methods

We characterized the clinicopathological characteristics, including 2016 World Health Organization (WHO) grade, age, sex, location, segment length, resection, pre‐ and postsurgery, Modified McCormick Scale (MMS), radio‐ and chemotherapy, and Ki‐67 and H3 K27M mutations, in 108 spinal cord astrocytomas through heatmaps. The Cox regression analysis and Kaplan‐Meier curves were used to study the prognostic value of these clinicopathological features.

Results

There are a total 38 H3 K27M‐mutant tumors, including 31 cases with histological grade II/III tumors. The age of low‐grade astrocytoma patients (WHO grade I/II, n = 54) was significantly younger (27.0 vs 35.5 years, P = .001) than those with high‐grade tumors (WHO grade III/IV, n = 54). All patients underwent surgical resection with neurophysiological monitoring, and the surgery did not result in significant changes in MMS. The presurgery MMS was associated with overall survival in the high‐grade subgroup (P = .008) but not in the low‐grade subgroup (P = .312). While, the high content of resection improved the survival of only patients with low‐grade astrocytomas (P = .016) but not those with high‐grade astrocytomas (P = .475). Both the low‐grade and high‐grade astrocytomas had no obvious benefit from neither adjuvant chemotherapy nor radiotherapy (all P > .05).

Conclusions

We characterized the clinicopathological characteristics and their prognostic values in 108 spinal cord astrocytomas, which could help with evidence‐based management of spinal cord astrocytomas.

ABCC8 mRNA expression is an independent prognostic factor for glioma and can predict chemosensitivity

Glioma is the most common primary intracranial tumor and is associated with very low survival rates. The development of reliable biomarkers can help to elucidate the molecular mechanisms involved in glioma development. Here the expression of ABCC8 mRNA, clinical characteristics, and survival information based on 1893 glioma samples from four independent databases were analyzed. The expression patterns of ABCC8 mRNA were compared by a Chi square test. The overall survival rate of gliomas was evaluated according to the expression level of ABCC8 mRNA. The prognostic value of this marker in gliomas was tested using Cox single factor and multi factor regression analyses. We found patients with low WHO grade, oligodendrocytoma, low molecular grade, IDH mutation, and 1p19q combined deletion had high ABCC8 mRNA expression. The patients with high expression of ABCC8 mRNA had longer survival. ABCC8 mRNA expression was a new independent prognostic index for glioma. Temozolomide chemotherapy was an independent index to prolong overall survival in high ABCC8 mRNA expression glioma patients, whereas in patients with low expression, there was no significant difference. So ABCC8 mRNA expression could be an independent prognostic indicator for glioma patients and could predict the sensitivity of glioma to temozolomide.

RPP30, a transcriptional regulator, is a potential pathogenic factor in glioblastoma

Background: Old age has been demonstrated to be a risk factor for GBM, but the underlying biological mechanism is still unclear. We designed this study intending to determine a mechanistic explanation for the link between age and pathogenesis in GBM.

Results: The expression of RPP30, an independent prognostic factor in GBM, was negatively correlated with age in both tumor and non-tumor brain samples. However, the post-transcriptional modifications carried out by RPP30 were different in primary GBM and non-tumor brain samples. RPP30 affected protein expression of cancer pathways by performing RNA modifications. Further, we found that RPP30 was related to drug metabolism pathways important in GBM. The decreased expression of RPP30 in older patients might be a pathogenic factor for GBM.

Conclusion: This study revealed the role of RPP30 in gliomagenesis and provided the theoretical foundation for targeted therapy.

Methods: In total, 616 primary GBM samples and 41 non-tumor brain samples were enrolled in this study. Transcriptome data and clinical information were obtained from the CGGA, TCGA, and GSE53890 databases. Gene Set Variation Analysis and Gene Ontology analyses were the primary analytical methods used in this study. All statistical analyses were performed using R.

N6-Methylandenosine-Related lncRNAs Are Potential Biomarkers for Predicting the Overall Survival of Lower-Grade Glioma Patients

The prognostic value of N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) was investigated in 646 lower-grade glioma (LGG) samples from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) datasets. We implemented Pearson correlation analysis to explore the m6A-related lncRNAs, and then univariate Cox regression analysis was performed to screen their prognostic roles in LGG patients. Twenty-four prognostic m6A-related lncRNAs were identified as prognostic lncRNAs and they were inputted in a least absolute shrinkage and selection operator (LASSO) Cox regression to establish a m6A-related lncRNA prognostic signature (m6A-LPS, including 9 m6A-related prognostic lncRNAs) in the TCGA dataset. Corresponding risk scores of patients were calculated and divided LGG patients into low- and high-risk subgroups by the median value of risk scores in each dataset. The m6A-LPS was validated in the CGGA dataset and it showed a robust prognostic ability in the stratification analysis. Principal component analysis showed that the low- and high-risk subgroups had distinct m6A status. Enrichment analysis indicated that malignancy-associated biological processes, pathways and hallmarks were more common in the high-risk subgroup. Moreover, we constructed a nomogram (based on m6A-LPS, age and World Health Organization grade) that had a strong ability to forecast the overall survival (OS) of the LGG patients in both datasets. We also establish a competing endogenous RNA (ceRNA) network based on seven of the twenty-four m6A-related lncRNAs. Besides, we also detected five m6A-related lncRNA expression levels in 22 clinical samples using quantitative real-time polymerase chain reaction assay.

Clinico-neuropathological features of isocitrate dehydrogenase 2 gene mutations in lower-grade gliomas

Background:

Mutations in the isocitrate dehydrogenase 1 (IDH1) and IDH2 genes are important for both the integrated diagnosis and the prognosis of diffuse gliomas. The p.R132H mutation of IDH1 is the most frequently observed IDH mutation, while IDH2 mutations were relatively rarely studied. The aim of the study was to determine the pathological and genetic characteristics of lower-grade gliomas that carry IDH2 mutations.

Methods:

Data from 238 adult patients with lower-grade gliomas were retrospectively analyzed. The status of IDH1/2 gene mutations, telomerase reverse transcriptase (TERT) promoter mutations, O⁶-methylguanine-DNA-methyltransferase (MGMT) promoter methylation, 1p/19q co-deletion and the expressions of IDH1 R132H, alpha-thalassemia X-linked mental retardation, and p53 were evaluated. Progression-free survival (PFS) and overall survival (OS) were calculated via Kaplan-Meier estimation using the log-rank test.

Results:

Totally, 71% (169/238) of patients were positive for IDH mutations, including 12 patients harboring mutations in IDH2. Among the 12 patients with IDH2 mutations, ten patients harbored the R172K mutation, one patient harbored the R172S mutation and one harbored the R172W mutation. Of these, 11 tumors occurred in the frontal lobe and showed morphology typical of oligodendroglioma. The proportion of grade II tumors was higher than that of grade III tumors in IDH2 mutant-gliomas. IDH2 mutations were frequently associated with TERT promoter mutations, 1p/19q co-deletion and MGMT promoter methylation. IDH2 mutations were associated with better outcomes compared with IDH wild-type gliomas (P < 0.05). However, the PFS and OS did not differ from that of IDH1 mutant patients (P = 0.95 and P = 0.60, respectively).

Conclusions:

IDH2 mutations are more frequent in oligodendrogliomas and associated with a better prognosis. IDH2 mutations may segregate in distinct clinico-pathological and genetic subtypes of gliomas, and therefore may merit routine investigation.

PD-1/PD-L1 immune checkpoint inhibitors in glioblastoma: clinical studies, challenges and potential

Immune checkpoint inhibitors (CIs) have changed the landscape of tumor immunotherapy. Glioblastoma (GBM) remains the most common primary malignant brain tumor in adults and has a very poor prognosis. Due to the high invasiveness and aggressiveness of GBM, there is considerable interest in programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) treatment. However, the immunosuppressive and immune-privileged characteristics of GBM limit the efficacy of CIs. While clinical studies of CI monotherapies have shown unsatisfactory survival benefits, new treatment strategies have received attention. Multiple clinical studies have focused on combination of standard therapy (temozolomide, radiotherapy), targeted therapy and other immunotherapies, and some have reported results. Here, we reviewed recent clinical trials of anti-PD-1/PD-L1 monotherapy, studies with neoadjuvant strategies, and preclinical and clinical studies of combination immunotherapies for GBM. The preliminary clinical reports in certain subsets of patients with hypermutated or mismatch repair system deficiency GBM are also discussed.

Interfering with long non-coding RNA MIR22HG processing inhibits glioblastoma progression through suppression of Wnt/β-catenin signalling

Long non-coding RNAs play critical roles in tumour progression. Through analysis of publicly available genomic datasets, we found that MIR22HG, the host gene of microRNAs miR-22-3p and miR-22-5p, is ranked among the most dysregulated long non-coding RNAs in glioblastoma. The main purpose of this work was to determine the impact of MIR22HG on glioblastoma growth and invasion and to elucidate its mechanistic function. The MIR22HG/miR-22 axis was highly expressed in glioblastoma as well as in glioma stem-like cells compared to normal neural stem cells. In glioblastoma, increased expression of MIR22HG is associated with poor prognosis. Through a number of functional studies, we show that MIR22HG silencing inhibits the Wnt/β-catenin signalling pathway through loss of miR-22-3p and -5p. This leads to attenuated cell proliferation, invasion and in vivo tumour growth. We further show that two genes, SFRP2 and PCDH15, are direct targets of miR-22-3p and -5p and inhibit Wnt signalling in glioblastoma. Finally, based on the 3D structure of the pre-miR-22, we identified a specific small-molecule inhibitor, AC1L6JTK, that inhibits the enzyme Dicer to block processing of pre-miR-22 into mature miR-22. AC1L6JTK treatment caused an inhibition of tumour growth in vivo. Our findings show that MIR22HG is a critical inducer of the Wnt/β-catenin signalling pathway, and that its targeting may represent a novel therapeutic strategy in glioblastoma patients.

Potential roads for reaching the summit: an overview on target therapies for high-grade gliomas

Background:

The tailored targeting of specific oncogenes represents a new frontier in the treatment of high-grade glioma in the pursuit of innovative and personalized approaches. The present study consists in a wide-ranging overview of the target therapies and related translational challenges in neuro-oncology.

Methods:

A review of the literature on PubMed/MEDLINE on recent advances concerning the target therapies for treatment of central nervous system malignancies was carried out. In the Medical Subject Headings, the terms “Target Therapy”, “Target drug” and “Tailored Therapy” were combined with the terms “High-grade gliomas”, “Malignant brain tumor” and “Glioblastoma”. Articles published in the last five years were further sorted, based on the best match and relevance. The ClinicalTrials.gov website was used as a source of the main trials, where the search terms were “Central Nervous System Tumor”, “Malignant Brain Tumor”, “Brain Cancer”, “Brain Neoplasms” and “High-grade gliomas”.

Results:

A total of 137 relevant articles and 79 trials were selected. Target therapies entailed inhibitors of tyrosine kinases, PI3K/AKT/mTOR pathway, farnesyl transferase enzymes, p53 and pRB proteins, isocitrate dehydrogenases, histone deacetylases, integrins and proteasome complexes. The clinical trials mostly involved combined approaches. They were phase I, II, I/II and III in 33%, 42%, 16%, and 9% of the cases, respectively.

Conclusion:

Tyrosine kinase and angiogenesis inhibitors, in combination with standard of care, have shown most evidence of the effectiveness in glioblastoma. Resistance remains an issue. A deeper understanding of the molecular pathways involved in gliomagenesis is the key aspect on which the translational research is focusing, in order to optimize the target therapies of newly diagnosed and recurrent brain gliomas. (www.actabiomedica.it)

Gene therapies for high-grade gliomas: from the bench to the bedside

Background:

Gene therapy is the most attractive therapeutic approach against high-grade gliomas (HGGs). This is because of its theoretical capability to rework gene makeup in order to yield oncolytic effects. However, some factors still limit the upgrade of these therapies at a clinical level of evidence. We report an overview of glioblastoma gene therapies, mainly focused on the rationale, classification, advances and translational challenges.

Methods:

An extensive review of the online literature on gene therapy for HGGs was carried out. The PubMed/MEDLINE and ClinicalTrials.gov websites were the main sources. Articles in English published in the last five years were sorted according to the best match with the multiple relevant keywords chosen. A descriptive analysis of the clinical trials was also reported.

Results:

A total of 85 articles and 45 clinical trials were selected. The main types of gene therapies are the suicide gene, tumor suppressor gene, immunomodulatory gene and oncolytic therapies (virotherapies). The transfer of genetic material entails replication-deficient and replication-competent oncolytic viruses and nanoparticles, such as liposomes and cationic polymers, each of them having advantages and drawbacks. Forty-eight clinical trials were collected, mostly phase I/II.

Conclusion:

Gene therapies constitute a promising approach against HGGs. The selection of new and more effective target genes, the implementation of gene-delivery vectors capable of greater and safer spreading capacity, and the optimization of the administration routes constitute the main translational challenges of this approach. (www.actabiomedica.it)

Immune and Clinical Features of CD96 Expression in Glioma by in silico Analysis

Background

Immune checkpoints target regulatory pathways in T cells that enhance antitumor immune responses and elicit durable clinical responses. As a novel immune checkpoint, CD96 is an attractive key target for cancer immunotherapy. However, there has been no integrative investigation of CD96 in glioma. Our study explored the relationship between CD96 expression and clinical prognosis in glioma.

Methods

RNA and clinical data for a total of 1,001 samples were included in this study, including 325 samples from the Chinese Glioma Genome Atlas (CGGA) database and 676 samples from The Cancer Genome Atlas (TCGA) dataset. The R programming language was employed to perform statistical analysis and draw figures.

Results

CD96 had a consistently positive relationship with glioblastoma and was highly enriched in IDH-wildtype and mesenchymal subtype glioma. Gene ontology enrichment and gene set variation analysis analyses suggested that CD96 was mostly involved in immune functions and was especially related to T cell-mediated immune response in glioma. Subsequent immune infiltration analysis showed that CD96 was positively correlated with infiltrating levels of CD4 + T and CD8 + T cells, macrophages, neutrophils, and DCs in glioblastoma multiforme and low-grade glioma. Additionally, CD96 was tightly associated with other immune checkpoints, including PD-1, CTLA-4, TIGIT, and TIM-3. Univariate and multivariate Cox analysis demonstrated that CD96 acts as an independent indicator of poor prognosis in glioma.

Conclusion

CD96 expression was increased in malignant phenotype and negatively associated with overall survival in glioma. CD96 also showed a positive correlation with other immune checkpoints, immune response, and inflammatory activity. Our findings indicate that CD96 is a promising clinical target for further immunotherapeutic use in glioma patients.

Systematic identification, development, and validation of prognostic biomarkers involving the tumor-immune microenvironment for glioblastoma

Gliomas are infiltrative neoplasms with a highly invasive nature. Due to its distinct genomic, genetic and epigenetic features, the immune prognostic signature (IPS) and immune microenvironment of glioblastoma (GBM) merit further research. We aimed to explore prognosis-related immune genes and develop an IPS model for predicting prognosis in GBM. RNA-sequencing data, as well as clinical information, from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) public cohorts were analyzed. To develop the IPS, least absolute shrinkage and selection operator (LASSO) Cox analysis was performed for immune-related genes that were differentially expressed between GBM and normal tissues. Then, interaction effects of the IPS on the immune microenvironment were systematically analyzed; the precise prognostic model was developed based on the IPS and clinical data and was then further validated. A total of 21 immune prognostic genes were identified based on GBM microenvironment status. An 8-gene IPS was established, and the GBM patients were effectively stratified into low- and high-risk groups in the TCGA cohort as a training set. Univariate and multivariate Cox analyses revealed that IPS was an independent prognostic factor, and the prognostic performance of individual IPS genes was systematically illustrated. In addition, a comprehensive and novel nomogram model was initially established to estimate overall survival in TCGA-GBM patients, and high-risk patients had higher levels of dendritic cell and neutrophil infiltration. Furthermore, the nomogram model was developed and validated in the CGGA validation set. The low-risk IPS was linked to a stronger response to anti-PD-L1 immunotherapy and clinical advantages in the IMvigor210 cohort. This novel IPS with promising biomarkers classifies GBM patients into subgroups with distinct clinical outcomes and immunophenotypes. Our findings and this resource may help to characterize the immune microenvironment, inform cancer immunotherapy and facilitate the development of precision immuno-oncology.

Quantitative Improvement in Brain Tumor MRI Through Structured Reporting (BT-RADS)

RATIONALE AND OBJECTIVES

Determine the objective benefits of structured reporting of brain tumors through Brain tumor-RADS (BT-RADS) by analyzing discrete quantifiable metrics of the reports themselves.

MATERIALS AND METHODS

Following Institutional Review Board approval, post-treatment glioma reports were acquired from two matched 3-month time periods for pre- and postimplementation of BT-RADS. The reports were analyzed for presence of history words, such as "Avastin" and "methylguanine-DNA methyltransferase," as well as hedge words, such as "Possibly" and "Likely." The word counts of the total report and of the impression section were also assessed, as well as whether or not the report contained addenda.

RESULTS

In total, 211 pre-BT-RADS and 172 post-BT-RADS reports were analyzed. Post-BT-RADS reports demonstrated greater reporting of history words, including "Avastin" (7.6% vs. 20.9%, p < 0.001) and "methylguanine-DNA methyltransferase" (10.9% vs. 31.4%, p < 0.0001). They also demonstrated reduced usage of hedge words, including "Possibly" (3.8% vs. 0.6%, p < 0.05) and "Likely" (49.8% vs. 28.5%, p < 0.01). Furthermore, post-BT-RADS reports possessed fewer words in total report length (389 vs. 245.2, p < 0.001), as well as in the impression section (53.7 vs. 42.6, p < 0.01). Finally, fewer post-BT-RADS reports contained addenda (10% vs. 1.2%, p < 0.01).

CONCLUSION

Following implementation of BT-RADS, glioma reports demonstrated greater consistency and completeness of clinical history, less ambiguity, and more conciseness.

Identification of an ATP metabolism-related signature associated with prognosis and immune microenvironment in gliomas

As the core element of material and energy metabolism pathways, the biological functions and prognostic significance of ATP metabolism in diffuse gliomas have so far remained unclear. Based on comprehensive analysis of ATP metabolism‐related gene expression profiles, we constructed an ATP metabolism‐related risk signature to determine the role of ATP metabolism. We found that this ATP metabolism‐related gene expression profile could divide patients into 2 robust groups with distinct clinical characteristics and prognosis. Patients in the high‐risk group tended to be predicted as malignant entities, indicating that the activation of ATP metabolism may promote the malignant progress of diffuse gliomas. Cox regression and Kaplan‐Meier analyses suggested that this risk signature was an independent predictor for prognosis. Furthermore, we constructed an individualized prognosis prediction model through nomogram and time‐dependent receiver operating characteristic (ROC) curve analyses. Functional analysis suggested that, in addition to material and energy metabolism, ATP metabolism also played an essential role in the regulation of the tumor immune microenvironment. In brief, the ATP metabolism‐related signature was tightly associated with regulation of the tumor immune microenvironment and could serve as an independent prognostic biomarker in diffuse gliomas.

Systematically characterize the clinical and biological significances of 1p19q genes in 1p/19q non-codeletion glioma

1p/19q codeletion, which leads to the abnormal expression of 1p19q genes in oligodendroglioma, is associated with chemosensitivity and favorable prognosis. Here, we aimed to explore the clinical implications of 1p19q gene expression in 1p/19q non-codel gliomas. We analyzed expression of 1p19q genes in 668 1p/19q non-codel gliomas obtained from The Cancer Genome Atlas (n = 447) and the Chinese Glioma Genome Atlas (n = 221) for training and validation, respectively. The expression of 1p19q genes was significantly correlated with the clinicopathological features and overall survival of 1p/19q non-codel gliomas. Then, we derived a risk signature of 25 selected 1p19q genes that not only had prognosis value in total 1p/19q non-codel gliomas but also had prognosis value in stratified gliomas. The prognosis value of the risk signature was superior than known clinicopathological features in 1p/19q non-codel gliomas and was also highly associated with the following features: loss of CDKN2A/B copy number in mutant-IDH-astrocytoma; telomerase reverse transcriptase (TERT) promoter mutation, combined chromosome 7 gain/chromosome 10 loss and epidermal growth factor receptor amplification in wild-type-IDH-astrocytoma; classical and mesenchymal subtypes in glioblastoma. Furthermore, genes enriched in the biological processes of cell division, extracellular matrix, angiogenesis significantly correlated to the signature risk score, and this is also supported by the immunohistochemistry and cell biology experiments. In conclusion, the expression profile of 1p19q genes is highly associated with the malignancy and prognosis of 1p/19q non-codel gliomas. A 25-1p19q-gene signature has powerfully predictive value for both malignant molecular pathological features and prognosis across distinct subgroups of 1p/19q non-codel gliomas.

Knockdown of the long noncoding RNA XIST suppresses glioma progression by upregulating miR-204-5p

Background: Gliomas are the most prevalent primary malignant tumors of the central nervous system. Our previous study showed that miR-204-5p is a tumor suppressor gene in glioma. Bioinformatic analyses suggest that long noncoding RNA (lncRNA) X-inactive specific transcript (XIST) is a potential target gene of miR-204-5p.

Methods: We analyzed the expression of XIST and miR-204-5p in glioma tissues and the correlation with glioma grade. A series of in vitro experiments were carried out to elucidate the role of XIST in glioma progression. A mouse xenograft model was established to detect whether knockdown of XIST can inhibit glioma growth. A luciferase assay was performed to determine whether XIST can bind to miR-204-5p and the binding specificity. Cells stably expressing shXIST or shNC were transfected with anti-miR-204-5p or anti-miR-204-5p-NC to evaluate whether XIST mediates the tumor-suppressive effects of miR-204-5p.

Results: XIST was upregulated in glioma tissues compared with normal brain tissues (NBTs), while miR-204-5p expression was significantly decreased in glioma tissues compared with NBTs. Both XIST and miR-204-5p expression levels were clearly related to glioma grade, and the expression of XIST was obviously negatively correlated with miR-204-5p expression. Knockdown of XIST inhibited glioma cell proliferation, migration, and invasion, promoted apoptosis of glioma cells, inhibited tumor growth and increased the survival time in nude mice. miR-204-5p could directly bind to XIST and negatively regulate XIST expression. XIST mediated glioma progression by targeting miR-204-5p in glioma cells. XIST crosstalk with miR-204-5p regulated Bcl-2 expression to promote apoptosis.

Conclusion: Our results provide evidence that XIST, miR-204-5p and Bcl-2 form a regulatory axis that controls glioma progression and can serve as a potential therapeutic target for glioma.

Role of molecular biomarkers in glioma resection: a systematic review

New discoveries based on genetic and epigenetic evidence have significantly expanded the understanding of diffuse gliomas. Molecular biomarkers detected in diffuse gliomas are not only potential targets for radiotherapy, chemotherapy, and immunotherapy, but are also able to guide surgical treatment. Previous studies have suggested that the optimal extent of resection of diffuse gliomas varies according to the expression of specific molecular biomarkers. However, the specific guiding role of these biomarkers in the resection of diffuse gliomas has not been systemically analyzed. This review summarizes several critical molecular biomarkers of tumorigenesis and progression in diffuse gliomas and discusses different strategies of tumor resection in the context of varying genetic expression. With ongoing study and advances in technology, molecular biomarkers will play a more important role in glioma resection and maximize the survival benefit from surgery for diffuse gliomas.

m6A RNA methylation regulators contribute to malignant progression and have clinical prognostic impact in gliomas

N6-methyladenosine (m⁶A) RNA methylation, associated with cancer initiation and progression, is dynamically regulated by the m⁶A RNA methylation regulators (“writers”, “erasers” and “readers”). Here, we demonstrate that most of the thirteen main m⁶A RNA methylation regulators are differentially expressed among gliomas stratified by different clinicopathological features in 904 gliomas. We identified two subgroups of gliomas (RM1/2) by applying consensus clustering to m⁶A RNA methylation regulators. Compared with the RM1 subgroup, the RM2 subgroup correlates with a poorer prognosis, higher WHO grade, and lower frequency of IDH mutation. Moreover, the hallmarks of epithelial-mesenchymal transition and TNFα signaling via NF-κB are also significantly enriched in the RM2 subgroup. This finding indicates that m⁶A RNA methylation regulators are closely associated with glioma malignancy. Based on this finding, we derived a risk signature, using seven m⁶A RNA methylation regulators, that is not only an independent prognostic marker but can also predict the clinicopathological features of gliomas. Moreover, m⁶A regulators are associated with the mesenchymal subtype and TMZ sensitivity in GBM. In conclusion, m⁶A RNA methylation regulators are crucial participants in the malignant progression of gliomas and are potentially useful for prognostic stratification and treatment strategy development.

MiR-210-3p Inhibits Proliferation and Migration of C6 Cells by Targeting Iscu

Glioma is the most common primary brain tumor and the most malignant type of glioma is glioblastoma with the character of high mortality, high recurrence rate and poor prognosis. MicroRNAs act as an important component in glioma development and thus may be a potential target for the treatment of glioma. There were some researches indicated that miR-210-3p played a role in glioma development, but if it can inhibit glioma growth, as well as the underlying mechanism, is still uncertain. In the present study, we investigated the effects of miR-210-3p and its potential target gene Iscu on glioma (C6) cells proliferation and migration in vitro as well as the influence of miR-210-3p on glioma growth in vivo. The results showed that miR-210-3p inhibited the proliferation and migration of C6 cells by regulating the expression of its target gene Iscu in vitro. We also demonstrated that glioma growth was suppressed in immunodeficient mice when they were implanted with C6 cells overexpressing miR-210-3p. Our data indicated that miR-210-3p played an important role in the prevention of glioma growth by targeting Iscu and so miR-210-3p/Iscu axis might be a potential target for the treatment of glioma.

Association of tumor growth rates with molecular biomarker status: a longitudinal study of high-grade glioma

To determine the association of molecular biomarkers with tumor growth in patients with high-grade gliomas (HGGs), the tumor growth rates and molecular biomarker status in 109 patients with HGGs were evaluated. Mean tumor diameter was assessed on at least two pre-surgical T₂-weighted and contrast-enhancement T_1-weighted magnetic resonance images (MRIs). Tumor growth rates were calculated based on tumor volume and diameter using various methods. The association of biomarkers with increased or decreased tumor growth was calculated using linear mixed-effects models. HGGs exhibited rapid growth rates, with an equivalent volume doubling time of 63.4 days and an equivalent velocity of diameter expansion of 51.6 mm/year. The WHO grade was an independent clinical factor of eVDEs. TERT promoter mutation C250T and MGMT promoter methylation was significantly associated with tumor growth in univariable analysis but not in multivariable analysis. Molecular groups of IDH1, TERT, and 1p/19q and IDH1 and MGMT were independently associated with tumor growth. In addition, tumor enhanced area had a faster growth rate than a tumor entity in incomplete enhanced HGGs (p = 0.006). Our findings provide crucial information for the prediction of preoperative tumor growth in HGGs, and aided in the decision making for aggressive resection and adjuvant treatment strategies.

Identification of long non-coding RNA HERC2P2 as a tumor suppressor in glioma

Long non-coding RNAs (lncRNAs) have been reported to play important roles in glioma; however, most of them promote glioma progression. We constructed a competing endogenous (ceRNA) network based on the Chinese Glioma Genome Atlas dataset, and lncRNA hect domain and RLD 2 pseudogene 2 (HERC2P2) is the core of this network. Highly connected genes in the ceRNA network classified the glioma patients into three clusters with significantly different survival rates. The expression of HERC2P2 is positively correlated with survival and negatively correlated with clinical grade. Cell colony formation, Transwell and cell scratch tests were performed to evaluate the role of HERC2P2 in glioblastoma growth. Furthermore, we overexpressed HERC2P2 in U87 cells and established a mouse intracranial glioma model to examine the function of HERC2P2 in vivo. In conclusion, we identified a lncRNA with tumor suppressor functions in glioma that could be a potential biomarker for glioma patients.

Awake craniotomy for gliomas involving motor-related areas: classification and function recovery

PURPOSE

Motor mapping with direct cortical stimulation (DCS) is useful for motor function preservation. Nevertheless, many patients still experience postoperative motor dysfunction after motor mapping. This study aimed to provide a classification of gliomas involved in motor-related areas to help understand which types of gliomas are prone to induce postoperative motor impairments.

METHODS

Sixty-four patients were retrospectively recruited. Based on tumor location, four types of gliomas were identified: (I) precentral gyrus; (II) premotor and/or supplementary motor areas but not invading pre-central gyrus; (III) adjacent to the posterior limb of the internal capsule; and (IV) other supra-tentorial area. The recovery of motor function was evaluated by muscle strength testing before surgery and 3 days, 7 days, 14 days, and 3 months after surgery.

RESULTS

Half of the patients experienced postoperative transient motor impairment within a week. Six patients suffered from permanent motor dysfunction, and four of them had type III glioma. Compared with types I and IV, patients with type III gliomas took more than three times as long to recover. Furthermore, patients with types I and II gliomas were more susceptible to preoperative epilepsy than those with types III and IV. There was no difference in postoperative seizure control between the four types.

CONCLUSIONS

Our classification of gliomas involving motor-related eloquent areas was useful for predicting postoperative motor functional prognosis in patients who underwent motor mapping with DCS. Even if no positive sites were detected, a conservative strategy of tumor resection is recommended in cases that gliomas located close to the posterior limb of the internal capsule.

Survival Risk Prediction Models of Gliomas Based on IDH and 1p/19q

Gliomas have been classified into different molecular subtypes based on their molecular features. To explore the prognostic factors of different subtypes of gliomas, we performed a univariate survival analysis based on the RNA-seq data of 653 patients obtained from The Cancer Genome Atlas. We identified 12205 (20.18%), 6125 (10.13%) and 5206 (8.61%) genes associated with the overall survival (OS) of the IDH-wildtype, IDH-mutation 1p/19q intact and IDH-mutation 1p/19q codeletion gliomas, respectively. Pathway enrichment analysis revealed that OS related genes were mainly involved in alcoholism, systemic lupus erythematosus, hematopoietic cell lineage and diabetes. The OS related genes were further selected using Lasso regression, and three prognostic risk score models were constructed to effectively predict the OS of the patients with different subtypes of gliomas. In total, 76 signature genes were identified and were selected to construct the three models. Moreover, neither of the 76 genes overlapped between different models, which suggested the enormous difference among the three subtypes, although some signature genes (SERPINA5, RP11.229A12.2 and RP11.62F24.2) were also identified as the OS related genes in different glioma subtypes. Interestingly, five genes (RP11.229A12.2, RP11.62F24.2, C3orf67, RP11.275H4.1 and TBX3) played opposing roles (protective or risk factor) in different subtypes. Additionally, the prognosis models consisted of a substantial proportion of non-coding RNA (58.74%, 70.13% and 58.11% in the IDH-wildtype, IDH-mutation 1p/19q intact and IDH-mutation 1p/19q codeletion). Furthermore, multivariate analysis integrating clinical variables demonstrated that risk group predicted by the prognostic models was an independent prognostic factor for gliomas. In conclusion, we have constructed and validated three models that have the potential to predict the prognosis of glioma patients. The genes and pathways identified in this study require further investigation for their underlying mechanisms and potential clinical significance in improving the OS of the glioma patients.