TERT promoter mutation status is necessary and sufficient to diagnose IDH-wildtype diffuse astrocytic glioma with molecular features of glioblastoma

Predicting telomerase reverse transcriptase promoter mutation status in glioblastoma by whole-tumor multi-sequence magnetic resonance texture analysis

OBJECTIVE

This study aimed to determine the feasibility of preoperative multi-sequence magnetic resonance texture analysis (MRTA) for predicting TERT promoter mutation status in IDH-wildtype glioblastoma (IDHwt GB).

METHODS

The clinical and imaging data of 111 patients with IDHwt GB at our hospital between November 2018 and June 2023 were retrospectively analyzed as the training set, and those of 23 patients with IDHwt GB between July 2023 and November 2023 were interpreted as the validation set. We used molecular sequencing results to classify the training set into TERT promoter mutation and wildtype groups. Textural features of the whole-tumor volume were extracted, including T2-weighted imaging (T2WI), T2-fluid-attenuated inversion recovery, apparent diffusion coefficient (ADC) map, and contrast-enhanced T1-weighted imaging (CE-T1). All textural features were obtained using open-source pyradiomics. After feature selection, logistic regression was used to build prediction models, and a nomogram was generated. Finally, the model was validated using validation cohort.

RESULTS

The CE-T1_Model (AUC 0.704) had a better predictive ability than the T2_Model (AUC 0.684) and ADC_Model (AUC 0.624). The MRI_Combined_Model (CE-T1, T2, and ADC texture features) (AUC 0.780) had a better predictive ability than the Clinical_Model (AUC 0.758). The Combined_Model (CE-T1, T2, ADC texture features, and clinical features) had the best predictive performance (AUC 0.871), with a sensitivity, specificity, and accuracy of 82.60 %, 83.30 %, and 80.18 %, respectively. The AUC, sensitivity, specificity, and accuracy in the validation cohort were 0.775, 86.70 %, 75.00 %, and 69.57 %, respectively.

CONCLUSIONS

Whole-tumor multi-sequence MRTA can be used as non-invasive quantitative parameters to assist in the preoperative clinical prediction of TERT promoter mutation status in IDHwt GB.

Adult diffuse IDH-wildtype lower-grade gliomas with PDGFRA gain/amplification should be upgraded as glioblastoma

We explored the prognostic significance of platelet-derived growth factor receptor α (PDGFRA) gain/amplification in grade 2-4 adult gliomas to assess its value as an upgrading indicator. Fluorescence in situ hybridization was performed to detect PDGFRA gain/amplification in 321 glioma specimens from Sun Yat-sen University Cancer Center (SYSUCC). Data from 1934 cases with available next-generation sequencing results from The Cancer Genome Atlas (TCGA) and cBioPortal were also analyzed. Of the adult grade 2-4 gliomas, 12.15% (39/321), 8.76% (93/1062), and 6.88% (60/872) had PDGFRA gain/amplification in the SYSUCC, TCGA, and cBioPortal cohorts, respectively. Grade 4 glioblastomas had a greater PDGFRA gain/amplification rate than lower-grade gliomas (LGGs) in all cohorts (all P < .05). PDGFRA gain/amplification was associated with older age, greater World Health Organization grade, isocitrate dehydrogenase (IDH)-wildtype, intact 1p/19q, telomerase reverse transcriptase promoter-wildtype, greater Ki67 index, epidermal growth factor receptor amplification, and chromosome 7+/10- alterations. PDGFRA gain/amplification predicted poor overall survival (OS) in grade 2-4 gliomas, particularly IDH-wildtype LGGs, in all cohorts (all P < .05). OS was worse in PDGFRA-amplified IDH-wildtype LGGs than in IDH-wildtype glioblastomas in the cBioPortal (P = .031) and SYSUCC (P = .026) cohorts. PDGFRA gain/amplification predicted poor OS in adult diffuse IDH-wildtype LGGs and may serve as an upgrading indicator.

Comparison of Fluorescence In Situ Hybridization, Next-Generation Sequencing, and DNA Methylation Microarray for Copy Number Variation Assessment in Gliomas

Gene-level and chromosomal copy number variation (CNV) assessments are critical in the integrated diagnosis of gliomas. Whereas fluorescence in situ hybridization (FISH) has been traditionally employed for CNV detection, emerging technologies such as next-generation sequencing (NGS) and DNA methylation microarray (DMM) are available in clinical practice. Nevertheless, the comparative performance of these 3 assays and the concordance of them remain unclear. A retrospective cohort study comprising 104 patients diagnosed with gliomas was conducted at our hospital. We systematically compared FISH, NGS, and DMM for detecting the following 6 CNV-related diagnostic or prognostic parameters: epidermal growth factor receptor (EGFR), cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B), 1p, 19q, chromosome 7, and chromosome 10. All the 3 methods showed high consistency in EGFR assessment; however, FISH demonstrated relatively low concordance with NGS/DMM in detecting other parameters. In contrast, NGS and DMM exhibited strong concordance in the assessment of all the 6 parameters. Notably, discordant cases were associated with high-grade gliomas (grade 3/4; P < .05) and a high fraction of genome altered (P < .01), indicating high malignancy and genomic instability of discordant cases. This study elucidated the discrepancies and limitations of conventional FISH compared with NGS/DMM in CNV assessments. The discrepancies were associated with high-grade gliomas and genomic instability. We propose a process with recommendations on methods, highlighting the importance of integrated multiplatform assays in accurate clinical diagnosis.

Contemporary prognostic signatures and refined risk stratification of gliomas: An analysis of 4400 tumors

BACKGROUND

With the significant shift in the classification, risk stratification, and standards of care for gliomas, we sought to understand how the overall survival of patients with these tumors is impacted by molecular features, clinical metrics, and treatment received.

METHODS

We assembled a cohort of patients with histopathologically diagnosed glioma from The Cancer Genome Atlas (TCGA), Project Genomics Evidence Neoplasia Information Exchange, and Dana-Farber Cancer Institute/Brigham and Women's Hospital. This incorporated retrospective clinical, histological, and molecular data alongside a prospective assessment of patient survival.

RESULTS

Of 4400 gliomas were identified: 2195 glioblastomas, 1198 IDH1/2-mutant astrocytomas, 531 oligodendrogliomas, 271 other IDH1/2-wild-type gliomas, and 205 pediatric-type glioma. Molecular classification updated 27.2% of gliomas from their original histopathologic diagnosis. Examining the distribution of molecular alterations across glioma subtypes revealed mutually exclusive alterations within tumorigenic pathways. Non-TCGA patients had significantly improved overall survival compared to TCGA patients, with 26.7%, 55.6%, and 127.8% longer survival for glioblastoma, IDH1/2-mutant astrocytoma, and oligodendroglioma, respectively (all P < .01). Several prognostic features were characterized, including NF1 alteration and 21q loss in glioblastoma, and EGFR amplification and 22q loss in IDH1/2-mutant astrocytoma. Leveraging the size of this cohort, nomograms were generated to assess the probability of overall survival based on patient age, the molecular features of a tumor, and the treatment received.

CONCLUSIONS

By applying modern molecular criteria, we characterize the genomic diversity across glioma subtypes, identify clinically applicable prognostic features, and provide a contemporary update on patient survival to serve as a reference for ongoing investigations.

TERTp Mutation and its Prognostic Value in Glioma Patients Under the 2021 WHO Classification: A Real-World Study

BACKGROUND

The 2021 WHO Classification of Central Nervous System Tumors introduces more molecular markers for glioma reclassification, including TERT promoter (TERTp) mutation as a key feature in glioblastoma diagnosis.

AIMS

Given the changes in the entities included in each subtype under the new classification, this research investigated the distribution, prognostic value, and correlations with other molecular alterations of TERTp mutation in different subgroups under this latest classification.

METHODS

All glioma patients admitted to Peking Union Medical College Hospital for surgical resection or biopsy from 2011 to 2022 were included. Samples were analyzed for TERTp mutation and 59 other gene alterations and chromosome copy number variations.

RESULTS

A total of 207 patients were included. The occurrence of TERTp mutations varied with percentages of 4.55%, 100%, and 77.92% in astrocytoma, oligodendroglioma, and glioblastoma, respectively. 65% of all adult-type glioma patients and 42.6% of IDH-wildtype histology grade 2 or 3 patients were TERTp-mutant. Survival analysis showed that TERTp mutation was a predictor of better prognosis in IDH-mutant grade 2 gliomas (median OS (mOS): not reached (NA) (95% CI: NA-NA) vs. 75.9 (95% CI: 55.4-NA) months, HR = 0.077 (95% CI: 0.01-0.64), p = 0.003), while poor OS was associated with all Grade 4 gliomas (mOS: 17.5 (95% CI: 12.6-24.2) vs. 40.5 (95% CI: 24.4-83.8) months, HR = 2.014 (95% CI: 1.17-3.47), p = 0.01) and all IDH-wildtype histology grade 2 or 3 gliomas (median OS: 12.6 (95% CI: 11-24.2) vs. 83.8 (95% CI: 35.2-NA) months, HR = 3.768 (95% CI: 1.83-7.78), p < 0.001). Moreover, TERTp mutation tended to co-occur with EGFR, KRAS, and MET in glioblastoma. In the IDH-mutant subgroup, it tended to co-occur with CIC and FUBP1 alterations, while being mutually exclusive with ATRX and TP53 alterations. These correlations may further refine prognostic predictions.

Primary intracranial sarcoma associated with DICER1 mutant: a case report and preclinical investigation

Primary intracranial sarcoma (PIS) is a rare and aggressive pediatric brain tumor, which is partially associated with DICER1 mutant. Although the molecular genetic characteristics of this tumor have previously been investigated, novel therapeutic targets remain unclear. Further, the lack of faithful preclinical models has hampered the development of novel therapeutic strategies. Herein, we describe a pediatric case of PIS with DICER1 mutant and describe the development of the first novel patient-derived xenograft (PDX) model of this rare tumor. Somatic genomic profiling of the tumor revealed mutations in DICER1, TP53, and ATRX. Germline analysis further revealed a pathogenic variant of DICER1, significant for the diagnosis and management of hereditary tumor predisposition syndrome. Overall, we demonstrated that the PDX model faithfully retained the phenotype and genotype of the patient's tumor, as well as the DNA methylation profile. Through high-throughput drug screening using PDX tumor cells, we found that activation of the retinoic acid receptor (RAR) signaling pathway reduced tumor cell viability. These findings indicate that the RAR signaling pathway is a potential therapeutic target for PIS in DICER1 mutant.

All-in-one bimodal DNA and RNA next-generation sequencing panel for integrative diagnosis of glioma

Previously, we constructed a DNA-based next-generation sequencing (NGS) panel for an integrated diagnosis of gliomas according to the 2021 World Health Organization classification system. The aim of the current study was to evaluate the feasibility of a modified panel to include fusion gene detection via RNA-based analysis. Using this bimodal DNA/RNA panel, we analyzed 210 cases of gliomas and others to identify fusion genes in addition to gene alterations, including TERT promoter (TERTp) mutation and 1p/19q co-deletion, in formalin-fixed paraffin-embedded tissues. Of the 210 patients, fusion genes were detected in tumors of 35 patients. Eighteen of 112 glioblastomas (GBs) harbored fusion genes, including EGFR and FGFR3 fusions. In IDH-mutant astrocytoma, 6 of 30 cases showed fusion genes such as MET and NTRK2 fusions. Eleven molecular GBs and 20 not-elsewhere-classified cases harbored no gene fusions. Other 11 tumors including ependymoma, pilocytic astrocytoma, diffuse hemispheric glioma, infant-type hemispheric glioma, and solitary fibrous tumors exhibited diagnostic fusion genes. Overall, our results suggest that the all-in-one bimodal DNA/RNA panel is reliable for detecting diagnostic gene alterations in accordance with the latest WHO classification. The integrative pathological and molecular strategy could be valuable in confirmation of diagnosis and selection of treatment options for brain tumors.

Comparative analysis of molecular and histological glioblastomas: insights into prognostic variance

PURPOSE

Whether molecular glioblastomas (GBMs) identify with a similar dismal prognosis as a "classical" histological GBM is controversial. This study aimed to compare the clinical, molecular, imaging, surgical factors, and prognosis between molecular GBMs and histological GBMs.

METHODS

Retrospective chart and imaging review was performed in 983 IDH-wildtype GBM patients (52 molecular GBMs and 931 histological GBMs) from a single institution between 2005 and 2023. Propensity score-matched analysis was additionally performed to adjust for differences in baseline variables between molecular GBMs and histological GBMs.

RESULTS

Molecular GBM patients were substantially younger (58.1 vs. 62.4, P = 0.014) with higher rate of TERTp mutation (84.6% vs. 50.3%, P < 0.001) compared with histological GBM patients. Imaging showed higher incidence of gliomatosis cerebri pattern (32.7% vs. 9.2%, P < 0.001) in molecular GBM compared with histological GBM, which resulted in lesser extent of resection (P < 0.001) in these patients. The survival was significantly better in molecular GBM compared to histological GBM (median OS 30.2 vs. 18.4 months, P = 0.001). The superior outcome was confirmed in propensity score analyses by matching histological GBM to molecular GBM (P < 0.001).

CONCLUSION

There are distinct clinical, molecular, and imaging differences between molecular GBMs and histological GBMs. Our results suggest that molecular GBMs have a more favorable prognosis than histological GBMs.

Brain gliomas: Diagnostic and therapeutic issues and the prospects of drug-targeted nano-delivery technology

Glioma is the most common intracranial malignant tumor, with severe difficulty in treatment and a low patient survival rate. Due to the heterogeneity and invasiveness of tumors, lack of personalized clinical treatment design, and physiological barriers, it is often difficult to accurately distinguish gliomas, which dramatically affects the subsequent diagnosis, imaging treatment, and prognosis. Fortunately, nano-delivery systems have demonstrated unprecedented capabilities in diagnosing and treating gliomas in recent years. They have been modified and surface modified to efficiently traverse BBB/BBTB, target lesion sites, and intelligently release therapeutic or contrast agents, thereby achieving precise imaging and treatment. In this review, we focus on nano-delivery systems. Firstly, we provide an overview of the standard and emerging diagnostic and treatment technologies for glioma in clinical practice. After induction and analysis, we focus on summarizing the delivery methods of drug delivery systems, the design of nanoparticles, and their new advances in glioma imaging and treatment in recent years. Finally, we discussed the prospects and potential challenges of drug-delivery systems in diagnosing and treating glioma.

Molecular characteristics and immune microenvironment of gastrointestinal stromal tumours: targets for therapeutic strategies

Gastrointestinal stromal tumours (GISTs) are the most common mesenchymal tumours, arising mainly from the interstitial cells of Cajal (ICCs) of the gastrointestinal tract. As radiotherapy and chemotherapy are generally ineffective for GISTs, the current primary treatment is surgical resection. However, surgical resection is not choice for most patients. Therefore, new therapeutic strategies are urgently needed. Targeted therapy, represented by tyrosine kinase inhibitors (TKIs), and immunotherapy, represented by immune checkpoint inhibitor therapies and chimeric antigen receptor T-cell immunotherapy (CAR-T), offer new therapeutic options in GISTs and have shown promising treatment responses. In this review, we summarize the molecular classification and immune microenvironment of GISTs and discuss the corresponding targeted therapy and immunotherapy options. This updated knowledge may provide more options for future therapeutic strategies and applications in GISTs.

Insights into brain tumor diagnosis: exploring in situ hybridization techniques

Objectives

Diagnosing brain tumors is critical due to their complex nature. This review explores the potential of in situ hybridization for diagnosing brain neoplasms, examining their attributes and applications in neurology and oncology.

Methods

The review surveys literature and cross-references findings with the OMIM database, examining 513 records. It pinpoints mutations suitable for in situ hybridization and identifies common chromosomal and gene anomalies in brain tumors. Emphasis is placed on mutations' clinical implications, including prognosis and drug sensitivity.

Results

Amplifications in EGFR, MDM2, and MDM4, along with Y chromosome loss, chromosome 7 polysomy, and deletions of PTEN, CDKN2/p16, TP53, and DMBT1, correlate with poor prognosis in glioma patients. Protective genetic changes in glioma include increased expression of ADGRB3/1, IL12B, DYRKA1, VEGFC, LRRC4, and BMP4. Elevated MMP24 expression worsens prognosis in glioma, oligodendroglioma, and meningioma patients. Meningioma exhibits common chromosomal anomalies like loss of chromosomes 1, 9, 17, and 22, with specific genes implicated in their development. Main occurrences in medulloblastoma include the formation of isochromosome 17q and SHH signaling pathway disruption. Increased expression of BARHL1 is associated with prolonged survival. Adenomas mutations were reviewed with a focus on adenoma-carcinoma transition and different subtypes, with MMP9 identified as the main metalloprotease implicated in tumor progression.

Discussion

Molecular-genetic diagnostics for common brain tumors involve diverse genetic anomalies. In situ hybridization shows promise for diagnosing and prognosticating tumors. Detecting tumor-specific alterations is vital for prognosis and treatment. However, many mutations require other methods, hindering in situ hybridization from becoming the primary diagnostic method.

Adult epithelioid glioblastoma exhibits an extremely poor prognosis and high frequency of SWI/SNF complex mutation: Insights from a retrospective study

Epithelioid glioblastoma (eGBM) is a rare subtype of GBM. Given the update of the definition of GBM, the understanding of the molecular characteristics and prognosis of "true" adult eGBM remains limited. Herein, we retrospectively analyzed the clinicopathological data of 39 adult eGBM cases. Adult eGBM primarily affected females, with a male-to-female ratio of 1:2.3. The average age of diagnosis was 53 years, and the tumor affected the temporal lobe in 41% of cases (16/39, 41%). Microscopically, the tumors consisted mainly or entirely of epithelioid cells. Perivascular infiltration (10/39, 25.6%) and leptomeningeal dissemination (7/39, 17.9%) were not uncommon. BRAF V600E mutation was detected in 40.9% of cases (n = 9/22). Next-generation sequencing revealed that CDKN2A/B homogeneous deletion was the most frequently mutated gene (8/10, 80%), followed by TERT promoter mutation (7/10, 70%), Cyclin-dependent kinases 4 or 6 (CDK4/6) amplification (5/10, 50%) and BRAF V600E mutation (50%, 5/10). Notably, the incidence of ARID1B mutation in eGBM was 50% (5/10), representing the first report of such a mutation in this subtype of GBM. ARID1B was known to be a subunit of the SWI/SNF chromatin remodeler. Chromosome analysis showed a 7+/10- signature in 90% (9/10) cases. Adult eGBM carried a dismal prognosis compared to GBM with IDH and H3 wild-type (typical GBM) (OS: 13.89 vs 24.30 months; P = .003) and even typical GBM without MGMT promoter methylation (OS: 13.89 vs 22.08 months; P = .036). Based on these findings, it can be concluded that adult eGBM harbors a high frequency of the 7+/10- signature and alterations in the MAPK pathway, SWI/SNF complex and cyclin-related genes and portends an extremely poor prognosis.

Unveiling divergent treatment prognoses in IDHwt-GBM subtypes through multiomics clustering: a swift dual MRI-mRNA model for precise subtype prediction

BACKGROUND

IDH1-wildtype glioblastoma multiforme (IDHwt-GBM) is a highly heterogeneous and aggressive brain tumour characterised by a dismal prognosis and significant challenges in accurately predicting patient outcomes. To address these issues and personalise treatment approaches, we aimed to develop and validate robust multiomics molecular subtypes of IDHwt-GBM. Through this, we sought to uncover the distinct molecular signatures underlying these subtypes, paving the way for improved diagnosis and targeted therapy for this challenging disease.

METHODS

To identify stable molecular subtypes among 184 IDHwt-GBM patients from TCGA, we used the consensus clustering method to consolidate the results from ten advanced multiomics clustering approaches based on mRNA, lncRNA, and mutation data. We developed subtype prediction models using the PAM and machine learning algorithms based on mRNA and MRI data for enhanced clinical utility. These models were validated in five independent datasets, and an online interactive system was created. We conducted a comprehensive assessment of the clinical impact, drug treatment response, and molecular associations of the IDHwt-GBM subtypes.

RESULTS

In the TCGA cohort, two molecular subtypes, class 1 and class 2, were identified through multiomics clustering of IDHwt-GBM patients. There was a significant difference in survival between Class 1 and Class 2 patients, with a hazard ratio (HR) of 1.68 [1.15-2.47]. This difference was validated in other datasets (CGGA: HR = 1.75[1.04, 2.94]; CPTAC: HR = 1.79[1.09-2.91]; GALSS: HR = 1.66[1.09-2.54]; UCSF: HR = 1.33[1.00-1.77]; UPENN HR = 1.29[1.04-1.58]). Additionally, class 2 was more sensitive to treatment with radiotherapy combined with temozolomide, and this sensitivity was validated in the GLASS cohort. Correspondingly, class 2 and class 1 exhibited significant differences in mutation patterns, enriched pathways, programmed cell death (PCD), and the tumour immune microenvironment. Class 2 had more mutation signatures associated with defective DNA mismatch repair (P = 0.0021). Enriched pathways of differentially expressed genes in class 1 and class 2 (P-adjust < 0.05) were mainly related to ferroptosis, the PD-1 checkpoint pathway, the JAK-STAT signalling pathway, and other programmed cell death and immune-related pathways. The different cell death modes and immune microenvironments were validated across multiple datasets. Finally, our developed survival prediction model, which integrates molecular subtypes, age, and sex, demonstrated clinical benefits based on the decision curve in the test set. We deployed the molecular subtyping prediction model and survival prediction model online, allowing interactive use and facilitating user convenience.

CONCLUSIONS

Molecular subtypes were identified and verified through multiomics clustering in IDHwt-GBM patients. These subtypes are linked to specific mutation patterns, the immune microenvironment, prognoses, and treatment responses.

The molecular signature and prognosis of glioma with preoperative intratumoral hemorrhage: a retrospective cohort analysis

BACKGROUND

Intratumoral hemorrhage, though less common, could be the first clinical manifestation of glioma and is detectable via MRI; however, its exact impacts on patient outcomes remain unclear and controversial. The 2021 WHO CNS 5 classification emphasised genetic and molecular features, initiating the necessity to establish the correlation between hemorrhage and molecular alterations. This study aims to determine the prevalence of intratumoral hemorrhage in glioma subtypes and identify associated molecular and clinical characteristics to improve patient management.

METHODS

Integrated clinical data and imaging studies of patients who underwent surgery at the Department of Neurosurgery at Peking Union Medical College Hospital from January 2011 to January 2022 with pathological confirmation of glioma were retrospectively reviewed. Patients were divided into hemorrhage and non-hemorrhage groups based on preoperative magnetic resonance imaging. A comparison and survival analysis were conducted with the two groups. In terms of subgroup analysis, we classified patients into astrocytoma, IDH-mutant; oligodendroglioma, IDH-mutant, 1p/19q-codeleted; glioblastoma, IDH-wildtype; pediatric-type gliomas; or circumscribed glioma using integrated histological and molecular characteristics, according to WHO CNS 5 classifications.

RESULTS

457 patients were enrolled in the analysis, including 67 (14.7%) patients with intratumoral hemorrhage. The hemorrhage group was significantly older and had worse preoperative Karnofsky performance scores. The hemorrhage group had a higher occurrence of neurological impairment and a higher Ki-67 index. Molecular analysis indicated that CDKN2B, KMT5B, and PIK3CA alteration occurred more in the hemorrhage group (CDKN2B, 84.4% vs. 62.2%, p = 0.029; KMT5B, 25.0% vs. 8.9%, p = 0.029; and PIK3CA, 81.3% vs. 58.5%, p = 0.029). Survival analysis showed significantly worse prognoses for the hemorrhage group (hemorrhage 18.4 months vs. non-hemorrhage 39.1 months, p = 0.01). In subgroup analysis, the multivariate analysis showed that intra-tumoral hemorrhage is an independent risk factor only in glioblastoma, IDH-wildtype (162 cases of 457 overall, HR = 1.72, p = 0.026), but not in other types of gliomas. The molecular alteration of CDK6 (hemorrhage group p = 0.004, non-hemorrhage group p < 0.001), EGFR (hemorrhage group p = 0.003, non-hemorrhage group p = 0.001), and FGFR2 (hemorrhage group p = 0.007, non-hemorrhage group p = 0.001) was associated with shorter overall survival time in both hemorrhage and non-hemorrhage groups.

CONCLUSIONS

Glioma patients with preoperative intratumoral hemorrhage had unfavorable prognoses compared to their nonhemorrhage counterparts. CDKN2B, KMT5B, and PIK3CA alterations were associated with an increased occurrence of intratumoral hemorrhage, which might be future targets for further investigation of intratumoral hemorrhage.

Association of body mass index with clinical outcome of primary WHO grade 4 glioma

Background

The prognostic value of body mass index (BMI) in primary WHO grade 4 gliomas is not widely acknowledged. This study aims to assess the survival outcomes of patients with different BMIs.

Methods

Real-world data of patients diagnosed with primary WHO grade 4 (2021 version) glioma was assessed. All 127 patients admitted in this study were administered with standard-of-care from September 2018 to September 2021. The outcomes of overall survival and progression-free survival were analyzed.

Results

The baseline characteristics of clinical features, molecular features, and secondary treatment in BMI subsets showed no significant difference. The survival analyses showed a significantly superior overall survival (OS) in the overweight group compared to the normal weight group. A trend of better OS in the overweight group compared to the obesity group was observed. The univariate Cox regression demonstrated patients of round-BMI 25 and 26 had superior OS outcomes.

Conclusion

In this real-world setting, patients with a BMI between 24 and 28 have superior overall survival. Patients in the proper BMI range may acquire survival benefits undergoing standard-of-care of primary WHO grade 4 gliomas. The prospective studies on a larger scale on these subsets of patients are necessary to solve the paradox of BMI in glioma.

The regulatory role and clinical application prospects of circRNA in the occurrence and development of CNS tumors

BACKGROUND

Central nervous system (CNS) tumors originate from the spinal cord or brain. The study showed that even with aggressive treatment, malignant CNS tumors have high mortality rates. However, CNS tumor risk factors and molecular mechanisms have not been verified. Due to the reasons mentioned above, diagnosis and treatment of CNS tumors in clinical practice are currently fraught with difficulties. Circular RNAs (circRNAs), single-stranded ncRNAs with covalently closed continuous structures, are essential to CNS tumor development. Growing evidence has proved the numeral critical biological functions of circRNAs for disease progression: sponging to miRNAs, regulating gene transcription and splicing, interacting with proteins, encoding proteins/peptides, and expressing in exosomes.

AIMS

This review aims to summarize current progress regarding the molecular mechanism of circRNA in CNS tumors and to explore the possibilities of clinical application based on circRNA in CNS tumors.

METHODS

We have summarized studies of circRNA in CNS tumors in Pubmed.

RESULTS

This review summarized their connection with CNS tumors and their functions, biogenesis, and biological properties. Furthermore, we introduced current advances in clinical RNA-related technologies. Then we discussed the diagnostic and therapeutic potential (especially for immunotherapy, chemotherapy, and radiotherapy) of circRNA in CNS tumors in the context of the recent advanced research and application of RNA in clinics.

CONCLUSIONS

CircRNA are increasingly proven to participate in decveloping CNS tumors. An in-depth study of the causal mechanisms of circRNAs in CNS tomor progression will ultimately advance their implementation in the clinic and developing new strategies for preventing and treating CNS tumors.

Predicting the prognosis of glioma patients with TERT promoter mutations and guiding the specific immune profile of immune checkpoint blockade therapy

The telomerase reverse transcriptase promoter (TERTp) is frequently mutated in gliomas. This study sought to identify immune biomarkers of gliomas with TERTp mutations. Data from TCGA were used to identify and validate survival-associated gene signatures, and immune and stromal scores were calculated using the ESTIMATE algorithm. High stromal or immune scores in patients with TERTp-mutant gliomas correlated with shorter overall survival compared to cases with low stromal or immune scores. Among TERTp-mutant gliomas with both high immune and high stromal scores, 213 commonly shared DEGs were identified. Among 71 interacting DEGs representing candidate hub genes in a PPI network, HOXC6, WT1, CD70, and OTP showed significant ability in establishing subgroups of high- and low-risk patients. A risk model based on these 4 genes showed strong prognostic potential for gliomas with mutated TERTp, but was inapplicable for TERTp-wild-type gliomas. TERTp-mutant gliomas with high-risk scores displayed a greater percentage of naïve B cells, plasma cells, naïve CD4 T cells, and activated mast cells than low-risk score gliomas. TIDE analysis indicated that immune checkpoint blockade (ICB) therapy may benefit glioma patients with TERTp mutations. The present risk model can help predict prognosis of glioma patients with TERTp mutations and aid ICB treatment options.

Artificial Intelligence Imaging for Predicting High-risk Molecular Markers of Gliomas

Gliomas, the most prevalent primary malignant tumors of the central nervous system, present significant challenges in diagnosis and prognosis. The fifth edition of the World Health Organization Classification of Tumors of the Central Nervous System (WHO CNS5) published in 2021, has emphasized the role of high-risk molecular markers in gliomas. These markers are crucial for enhancing glioma grading and influencing survival and prognosis. Noninvasive prediction of these high-risk molecular markers is vital. Genetic testing after biopsy, the current standard for determining molecular type, is invasive and time-consuming. Magnetic resonance imaging (MRI) offers a non-invasive alternative, providing structural and functional insights into gliomas. Advanced MRI methods can potentially reflect the pathological characteristics associated with glioma molecular markers; however, they struggle to fully represent gliomas' high heterogeneity. Artificial intelligence (AI) imaging, capable of processing vast medical image datasets, can extract critical molecular information. AI imaging thus emerges as a noninvasive and efficient method for identifying high-risk molecular markers in gliomas, a recent focus of research. This review presents a comprehensive analysis of AI imaging's role in predicting glioma high-risk molecular markers, highlighting challenges and future directions.

The C250T Mutation of TERTp Might Grant a Better Prognosis to Glioblastoma by Exerting Less Biological Effect on Telomeres and Chromosomes Than the C228T Mutation

The aim of this study was to determine how TERTp mutations impact glioblastoma prognosis.

MATERIALS AND METHODS

TERTp mutations were assessed in a retrospective cohort of 258 uniformly treated glioblastoma patients. RNA-sequencing and whole exome sequencing results were available in a subset of patients.

RESULTS

Overall, there were no differences in outcomes between patients with mutated TERTp-wt or TERTp. However, we found significant differences according to the type of TERTp mutation. Progression-free survival (mPFS) was 9.1 months for those with the C250T mutation and 7 months for those with either the C228T mutation or TERTp-wt (p = 0.016). Overall survival (mOS) was 21.9 and 15 months, respectively (p = 0.026). This differential effect was more pronounced in patients with MGMTp methylation (mPFS: p = 0.008; mOS: p = 0.021). Multivariate analysis identified the C250T mutation as an independent prognostic factor for longer mOS (HR 0.69; p = 0.044). We found no differences according to TERTp mutation status in molecular alterations common in glioblastoma, nor in copy number variants in genes related to alternative lengthening of telomeres. Nevertheless, in the gene enrichment analysis adjusted for MGMTp methylation status, some Reactome gene sets were differentially enriched, suggesting that the C250T mutation may exert a lesser effect on telomeres or chromosomes.

CONCLUSIONS

In our series, patients exhibiting the C250T mutation had a more favorable prognosis compared to those with either TERPp-wt or TERTp C228T mutations. Additionally, our findings suggest a reduced involvement of the C250T mutation in the underlying biological mechanisms related to telomeres.

Decoding the DNA methylome of central nervous system tumors: An emerging modality for integrated diagnosis

The definitive diagnosis and classification of individual cancers are crucial for patient care and cancer research. To achieve a robust diagnosis of central nervous system (CNS) tumors, a genotype-phenotype integrated diagnostic approach was introduced in recent versions of the World Health Organization classification, followed by the incorporation of a genome-wide DNA methylome-based classification. Microarray-based platforms are widely used to obtain DNA methylome data, and the German Cancer Research Center (Deutsches Krebsforschungszentrum [DKFZ]) has a webtool for a DNA methylation-based classifier (DKFZ classifier). Integration of DNA methylome will further enhance the precision of CNS tumor classification, especially in diagnostically challenging cases. However, in the clinical application of DNA methylome-based classification, challenges related to data interpretation persist, in addition to technical caveats, regulations, and limited accessibility. Dimensionality reduction (DMR) can complement integrated diagnosis by visualizing a profile and comparing it with other known samples. Therefore, DNA methylome-based classification is a highly useful research tool for auxiliary analysis in challenging diagnostic and rare disease cases, and for establishing novel tumor concepts. Decoding the DNA methylome, especially by DMR in addition to DKFZ classifier, emphasizes the capability of grasping the fundamental biological principles that provide new perspectives on CNS tumors.

Peritumoral Radiomics for Identification of Telomerase Reverse Transcriptase Promoter Mutation in Patients With Glioblastoma Based on Preoperative MRI

Purpose: To evaluate the value of intra- and peritumoral deep learning (DL) features based on multi-parametric magnetic resonance imaging (MRI) for identifying telomerase reverse transcriptase (TERT) promoter mutation in glioblastoma (GBM). Methods: In this study, we included 229 patients with GBM who underwent preoperative MRI in two hospitals between November 2016 and September 2022. We used four 2D Convolutional Neural Networks (GoogLeNet, DenseNet121, VGG16, and MobileNetV3-Large) to extract intra- and peritumoral DL features. The Mann-Whitney U test, Pearson correlation analysis, least absolute shrinkage and selection operator, and logistic regression analysis were used for feature selection and construction of DL radiomics (DLR) signatures in different regions. These multi-parametric and multi-region signatures were combined to identify TERT promoter mutation. The area under the receiver operating characteristic curve (AUC) was used to evaluate the effects of the signatures. Results: The signatures based on the DL features from the peritumoral regions with expansion distances of 2 mm, 8 mm, and 10 mm using the GoogLeNet architecture correlated with the optimal AUC values (test set: .823, .753, and .768) in the T2-weighted, T1-weighted contrast-enhanced, and T1-weighted images. Using the stacking fusion method, DLR with multi-parameter and multi-region fusion achieved the best discrimination with AUC values of .948 and .902 in the training and test sets, respectively. Conclusions: The radiomics model based on the fusion of multi-parameter MRI intra- and peritumoral DLR signatures may help to identify TERT promoter mutation in patients with GBM.

The regulations of telomerase reverse transcriptase (TERT) in cancer

Abnormal activation of telomerase occurs in most cancer types, which facilitates escaping from cell senescence. As the key component of telomerase, telomerase reverse transcriptase (TERT) is regulated by various regulation pathways. TERT gene changing in its promoter and phosphorylation respectively leads to TERT ectopic expression at the transcription and protein levels. The co-interacting factors play an important role in the regulation of TERT in different cancer types. In this review, we focus on the regulators of TERT and these downstream functions in cancer regulation. Determining the specific regulatory mechanism will help to facilitate the development of a cancer treatment strategy that targets telomerase and cancer cell senescence. As the most important catalytic subunit component of telomerase, TERT is rapidly regulated by transcriptional factors and PTM-related activation. These changes directly influence TERT-related telomere maintenance by regulating telomerase activity in telomerase-positive cancer cells, telomerase assembly with telomere-binding proteins, and recruiting telomerase to the telomere. Besides, there are also non-canonical functions that are influenced by TERT, including the basic biological functions of cancer cells, such as proliferation, apoptosis, cell cycle regulation, initiating cell formation, EMT, and cell invasion. Other downstream effects are the results of the influence of transcriptional factors by TERT. Currently, some small molecular inhibitors of TERT and TERT vaccine are under research as a clinical therapeutic target. Purposeful work is in progress.

Glioma: bridging the tumor microenvironment, patient immune profiles and novel personalized immunotherapy

Glioma is the most common primary brain tumor, characterized by a consistently high patient mortality rate and a dismal prognosis affecting both survival and quality of life. Substantial evidence underscores the vital role of the immune system in eradicating tumors effectively and preventing metastasis, underscoring the importance of cancer immunotherapy which could potentially address the challenges in glioma therapy. Although glioma immunotherapies have shown promise in preclinical and early-phase clinical trials, they face specific limitations and challenges that have hindered their success in further phase III trials. Resistance to therapy has been a major challenge across many experimental approaches, and as of now, no immunotherapies have been approved. In addition, there are several other limitations facing glioma immunotherapy in clinical trials, such as high intra- and inter-tumoral heterogeneity, an inherently immunosuppressive microenvironment, the unique tissue-specific interactions between the central nervous system and the peripheral immune system, the existence of the blood-brain barrier, which is a physical barrier to drug delivery, and the immunosuppressive effects of standard therapy. Therefore, in this review, we delve into several challenges that need to be addressed to achieve boosted immunotherapy against gliomas. First, we discuss the hurdles posed by the glioma microenvironment, particularly its primary cellular inhabitants, in particular tumor-associated microglia and macrophages (TAMs), and myeloid cells, which represent a significant barrier to effective immunotherapy. Here we emphasize the impact of inducing immunogenic cell death (ICD) on the migration of Th17 cells into the tumor microenvironment, converting it into an immunologically "hot" environment and enhancing the effectiveness of ongoing immunotherapy. Next, we address the challenge associated with the accurate identification and characterization of the primary immune profiles of gliomas, and their implications for patient prognosis, which can facilitate the selection of personalized treatment regimens and predict the patient's response to immunotherapy. Finally, we explore a prospective approach to developing highly personalized vaccination strategies against gliomas, based on the search for patient-specific neoantigens. All the pertinent challenges discussed in this review will serve as a compass for future developments in immunotherapeutic strategies against gliomas, paving the way for upcoming preclinical and clinical research endeavors.

Surgical management and outcome of newly diagnosed glioblastoma without contrast enhancement (low-grade appearance): a report of the RANO resect group

BACKGROUND

Resection of the contrast-enhancing (CE) tumor represents the standard of care in newly diagnosed glioblastoma. However, some tumors ultimately diagnosed as glioblastoma lack contrast enhancement and have a 'low-grade appearance' on imaging (non-CE glioblastoma). We aimed to (a) volumetrically define the value of non-CE tumor resection in the absence of contrast enhancement, and to (b) delineate outcome differences between glioblastoma patients with and without contrast enhancement.

METHODS

The RANO resect group retrospectively compiled a global, eight-center cohort of patients with newly diagnosed glioblastoma per WHO 2021 classification. The associations between postoperative tumor volumes and outcome were analyzed. Propensity score-matched analyses were constructed to compare glioblastomas with and without contrast enhancement.

RESULTS

Among 1323 newly diagnosed IDH-wildtype glioblastomas, we identified 98 patients (7.4%) without contrast enhancement. In such patients, smaller postoperative tumor volumes were associated with more favorable outcome. There was an exponential increase in risk for death with larger residual non-CE tumor. Accordingly, extensive resection was associated with improved survival compared to lesion biopsy. These findings were retained on a multivariable analysis adjusting for demographic and clinical markers. Compared to CE glioblastoma, patients with non-CE glioblastoma had a more favorable clinical profile and superior outcome as confirmed in propensity score analyses by matching the patients with non-CE glioblastoma to patients with CE glioblastoma using a large set of clinical variables.

CONCLUSIONS

The absence of contrast enhancement characterizes a less aggressive clinical phenotype of IDH-wildtype glioblastomas. Maximal resection of non-CE tumors has prognostic implications and translates into favorable outcome.

Intraoperative Integrated Diagnostic System for Malignant Central Nervous System Tumors

PURPOSE

The 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors uses an integrated approach involving histopathology and molecular profiling. Because majority of adult malignant brain tumors are gliomas and primary CNS lymphomas (PCNSL), rapid differentiation of these diseases is required for therapeutic decisions. In addition, diffuse gliomas require molecular information on single-nucleotide variants (SNV), such as IDH1/2. Here, we report an intraoperative integrated diagnostic (i-ID) system to classify CNS malignant tumors, which updates legacy frozen-section (FS) diagnosis through incorporation of a qPCR-based genotyping assay.

EXPERIMENTAL DESIGN

FS evaluation, including GFAP and CD20 rapid IHC, was performed on adult malignant CNS tumors. PCNSL was diagnosed through positive CD20 and negative GFAP immunostaining. For suspected glioma, genotyping for IDH1/2, TERT SNV, and CDKN2A copy-number alteration was routinely performed, whereas H3F3A and BRAF SNV were assessed for selected cases. i-ID was determined on the basis of the 2021 WHO classification and compared with the permanent integrated diagnosis (p-ID) to assess its reliability.

RESULTS

After retrospectively analyzing 153 cases, 101 cases were prospectively examined using the i-ID system. Assessment of IDH1/2, TERT, H3F3AK27M, BRAFV600E, and CDKN2A alterations with i-ID and permanent genomic analysis was concordant in 100%, 100%, 100%, 100%, and 96.4%, respectively. Combination with FS and intraoperative genotyping assay improved diagnostic accuracy in gliomas. Overall, i-ID matched with p-ID in 80/82 (97.6%) patients with glioma and 18/19 (94.7%) with PCNSL.

CONCLUSIONS

The i-ID system provides reliable integrated diagnosis of adult malignant CNS tumors.

Advances in Molecular Pathology, Diagnosis and Treatment of Spinal Cord Astrocytomas

Spinal cord astrocytoma (SCA) is a rare subtype of astrocytoma, posing challenges in diagnosis and treatment. Low-grade SCA can achieve long-term survival solely through surgery, while high-grade has a disappointing prognosis even with comprehensive treatment. Diagnostic criteria and standard treatment of intracranial astrocytoma have shown obvious limitations in SCA. Research on the molecular mechanism in SCA is lagging far behind that on intracranial astrocytoma. In recent years, huge breakthroughs have been made in molecular pathology of astrocytoma, and novel techniques have emerged, including DNA methylation analysis and radiomics. These advances are now making it possible to provide a precise diagnosis and develop corresponding treatment strategies in SCA. Our aim is to review the current status of diagnosis and treatment of SCA, and summarize the latest research advancement, including tumor subtype, molecular characteristics, diagnostic technology, and potential therapy strategies, thus deepening our understanding of this uncommon tumor type and providing guidance for accurate diagnosis and treatment.

Bioactive compounds from Actinidia arguta fruit as a new strategy to fight glioblastoma

In recent years, there has been a significant demand for natural products as a mean of disease prevention or as an alternative to conventional medications. The driving force for this change is the growing recognition of the abundant presence of valuable bioactive compounds in natural products. On recent years Actinia arguta fruit, also known as kiwiberry, has attracted a lot of attention from scientific community due to its richness in bioactive compounds, including phenolic compounds, organic acids, vitamins, carotenoids and fiber. These bioactive compounds contribute to the fruit's diverse outstanding biological activities such as antioxidant, anti-inflammatory, neuroprotective, immunomodulatory, and anti-cancer properties. Due to these properties, the fruit may have the potential to be used in the treatment/prevention of various types of cancer, including glioblastoma. Glioblastoma is the most aggressive form of brain cancer, displaying 90 % of recurrence rate within a span of 2 years. Despite the employment of an aggressive approach, the prognosis remains unfavorable, emphasizing the urgent requirement for the development of new effective treatments. The preclinical evidence suggests that kiwiberry has potential impact on glioblastoma by reducing the cancer self-renewal, modulating the signaling pathways involved in the regulation of the cell phenotype and metabolism, and influencing the consolidation of the tumor microenvironment. Even though, challenges such as the imprecise composition and concentration of bioactive compounds, and its low bioavailability after oral administration may be drawbacks to the development of kiwiberry-based treatments, being urgent to ensure the safety and efficacy of kiwiberry for the prevention and treatment of glioblastoma. This review aims to highlight the potential impact of A. arguta bioactive compounds on glioblastoma, providing novel insights into their applicability as complementary or alternative therapies.

The Biological and Clinical Role of the Telomerase Reverse Transcriptase Gene in Glioblastoma: A Potential Therapeutic Target?

Glioblastoma IDH-wildtype represents the most lethal and frequent primary tumor of the central nervous system. Thanks to important scientific efforts, we can now investigate its deep genomic assessment, elucidating mutated genes and altered biological mechanisms in addition to its clinical aggressiveness. The telomerase reverse transcriptase gene (TERT) is the most frequently altered gene in solid tumors, including brain tumors and GBM IDH-wildtype. In particular, it can be observed in approximately 80-90% of GBM IDH-wildtype cases. Its clonal distribution on almost all cancer cells makes this gene an optimal target. However, the research of effective TERT inhibitors is complicated by several biological and clinical obstacles which can be only partially surmounted. Very recently, novel immunological approaches leading to TERT inhibition have been investigated, offering the potential to develop an effective target for this altered protein. Here, we perform a narrative review investigating the biological role of TERT alterations on glioblastoma and the principal obstacles associated with TERT inhibitions in this population. Moreover, we discuss possible combination treatment strategies to overcome these limitations.

Multimodal MRI-based radiomic nomogram for predicting telomerase reverse transcriptase promoter mutation in IDH-wildtype histological lower-grade gliomas

The presence of TERTp mutation in isocitrate dehydrogenase-wildtype (IDHwt) histologically lower-grade glioma (LGA) has been linked to a poor prognosis. In this study, we aimed to develop and validate a radiomic nomogram based on multimodal MRI for predicting TERTp mutations in IDHwt LGA. One hundred and nine IDH wildtype glioma patients (TERTp-mutant, 78; TERTp-wildtype, 31) with clinical, radiomic, and molecular information were collected and randomly divided into training and validation set. Clinical model, fusion radiomic model, and combined radiomic nomogram were constructed for the discrimination. Radiomic features were screened with 3 algorithms (Wilcoxon rank sum test, elastic net, and the recursive feature elimination) and the clinical characteristics of combined radiomic nomogram were screened by the Akaike information criterion. Finally, receiver operating characteristic curve, calibration curve, Hosmer-Lemeshow test, and decision curve analysis were utilized to assess these models. Fusion radiomic model with 4 radiomic features achieved an area under the curve value of 0.876 and 0.845 in the training and validation set. And, the combined radiomic nomogram achieved area under the curve value of 0.897 (training set) and 0.882 (validation set). Above that, calibration curve and Hosmer-Lemeshow test showed that the radiomic model and combined radiomic nomogram had good agreement between observations and predictions in the training set and the validation set. Finally, the decision curve analysis revealed that the 2 models had good clinical usefulness for the prediction of TERTp mutation status in IDHwt LGA. The combined radiomics nomogram performed great performance and high sensitivity in prediction of TERTp mutation status in IDHwt LGA, and has good clinical application.

Genetic alterations that deregulate RB and PDGFRA signaling pathways drive tumor progression in IDH2-mutant astrocytoma

In IDH-mutant astrocytoma, IDH2 mutation is quite rare and biological mechanisms underlying tumor progression in IDH2-mutant astrocytoma remain elusive. Here, we report a unique case of IDH2 mutant astrocytoma, CNS WHO grade 3 that developed tumor progression. We performed a comprehensive genomic and epigenomic analysis for primary and recurrent tumors and found that both tumors harbored recurrent IDH2R172K and TP53R248W mutation with CDKN2A/B hemizygous deletion. We also found amplifications of CDK4 and MDM2 with PDGFRA gain in the recurrent tumor and upregulated protein expressions of these genes. We further developed, for the first time, a xenograft mouse model of IDH2R172K and TP53R248W mutant astrocytoma from the recurrent tumor, but not from the primary tumor. Consistent with parent recurrent tumor cells, amplifications of CDK4 and MDM2 and PDGFRA gain were found, while CDKN2A/B was identified as homozygous deletion in the xenografts, qualifying for integrated diagnosis of astrocytoma, IDH2-mutant, CNS WHO grade 4. Cell viability assay found that CDK4/6 inhibitor and PDGFR inhibitor potently decreased cell viability in recurrent tumor cells, as compared to primary tumor cells. These findings suggest that gene alterations that activate retinoblastoma (RB) signaling pathways and PDGFR may drive tumor progression and xenograft formation in IDH2-mutant astrocytoma, which is equivalent to progressive IDH1-mutant astrocytoma. Also, our findings suggest that these genomic alterations may represent therapeutic targets in IDH2-mutant astrocytoma.

Deep Learning Radiomics for the Assessment of Telomerase Reverse Transcriptase Promoter Mutation Status in Patients With Glioblastoma Using Multiparametric MRI

BACKGROUND

Studies have shown that magnetic resonance imaging (MRI)-based deep learning radiomics (DLR) has the potential to assess glioma grade; however, its role in predicting telomerase reverse transcriptase (TERT) promoter mutation status in patients with glioblastoma (GBM) remains unclear.

PURPOSE

To evaluate the value of deep learning (DL) in multiparametric MRI-based radiomics in identifying TERT promoter mutations in patients with GBM preoperatively.

STUDY TYPE

Retrospective.

POPULATION

A total of 274 patients with isocitrate dehydrogenase-wildtype GBM were included in the study. The training and external validation cohorts included 156 (54.3 ± 12.7 years; 96 males) and 118 (54 .2 ± 13.4 years; 73 males) patients, respectively.

FIELD STRENGTH/SEQUENCE

Axial contrast-enhanced T1-weighted spin-echo inversion recovery sequence (T1CE), T1-weighted spin-echo inversion recovery sequence (T1WI), and T2-weighted spin-echo inversion recovery sequence (T2WI) on 1.5-T and 3.0-T scanners were used in this study.

ASSESSMENT

Overall tumor area regions (the tumor core and edema) were segmented, and the radiomics and DL features were extracted from preprocessed multiparameter preoperative brain MRI images-T1WI, T1CE, and T2WI. A model based on the DLR signature, clinical signature, and clinical DLR (CDLR) nomogram was developed and validated to identify TERT promoter mutation status.

STATISTICAL TESTS

The Mann-Whitney U test, Pearson test, least absolute shrinkage and selection operator, and logistic regression analysis were applied for feature selection and construction of radiomics and DL signatures. Results were considered statistically significant at P-value <0.05.

RESULTS

The DLR signature showed the best discriminative power for predicting TERT promoter mutations, yielding an AUC of 0.990 and 0.890 in the training and external validation cohorts, respectively. Furthermore, the DLR signature outperformed CDLR nomogram (P = 0.670) and significantly outperformed clinical models in the validation cohort.

DATA CONCLUSION

The multiparameter MRI-based DLR signature exhibited a promising performance for the assessment of TERT promoter mutations in patients with GBM, which could provide information for individualized treatment.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

BTN2A2, a new biomarker and therapeutic target for glioma

BACKGROUND

Protein casein 2A2 (BTN2A2) is a costimulatory molecule first identified in antigen-presenting cells. Studies have shown the involvement of BTN2A2 in immunity. However, the exact role and the mechanism of BTN2A2 in tumors are still unclear.

METHODS

First, we performed real-time PCR to measure BTN2A2 expression in glioma cell lines. Next, we performed Genes Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to understand the mechanism of BTN2A2 in glioma. Next, we used the "ESTIMATE", "ssGSEA" and "CIBERSORT" algorithms to analyze the correlation between BTN2A2 and immune cell infiltration (ICI). Finally, we performed immunohistochemistry, growth curve, transwell, and colony formation assays to determine the functions of BTN2A2 in glioma.

RESULTS

Our results showed an increase in BTN2A2 expression levels in glioma tissues and cells. Next, we determined that BTN2A2 was correlated with the prognosis of patients with glioma. Then, using the ESTIMATE, ssGSEA, and CIBERSORT algorithms, we discovered that BTN2A2 was significantly associated with immune cell infiltration (ICI) in glioma. We observed an increase in BTN2A2 expression levels with an increase in the patient's tumor grade. Furthermore, BTN2A2 significantly enhanced the proliferative and migratory abilities of glioma cells.

CONCLUSIONS

Our results showed a significant increase in BTN2A2 expression levels in glioma cells and tissues. Furthermore, the prognosis of patients expressing high BTN2A2 levels was poor. Moreover, BTN2A2 was correlated with progression and ICI in patients with glioma. Together, this indicates that BTN2A2 could be a therapeutic target for patients with glioma.

Development and validation of cuproptosis molecular subtype-related signature for predicting immune prognostic characterization in gliomas

PURPOSE

Cuproptosis, a novel programmed cell death, plays an important role in glioma growth, angiogenesis, and immune response. Nonetheless, the role of cuproptosis-related genes (CRGs) in the prognosis and tumor microenvironment (TME) of gliomas remains unknown.

METHODS

By non-negative matrix factorization consensus clustering, 1286 glioma patients were classified based on the mRNA expression levels of 27 CRGs and investigated the association of immune infiltration and clinical characteristics with cuproptosis subtypes. A CRG-score system was constructed using LASSO and multivariate Cox regression methods and validated in independent cohorts to predict the prognosis of glioma patients.

RESULTS

Glioma patients were divided into two cuproptosis subtypes. Cluster C2 was enriched in immune-related pathways, had higher macrophage M2, neutrophils, and CD8 + T cells, and poorer prognosis compared with cluster C1 which was enriched in metabolism-related pathways. We further constructed and validated the ten-gene CRG risk scores. Glioma patients in the high CRG-score group had higher tumor mutation burden, higher TME scores, and poorer prognoses compared with the low CRG-score group. Additionally, the AUC value of the CRG-score was 0.778 in predicting the prognosis of gliomas. WHO grading, IDH mutation, 1p/19q codeletion, and MGMT methylation were significant differences between high and low CRG-score groups.

CONCLUSION

This study demonstrated that CRG-score was related to immune cell infiltration and could accurately predict gliomas' prognosis. Our findings may provide a novel understanding of the potential role of cuproptosis molecular pattern and TME in the immune response and prognosis of glioma patients.

The prognostic power of [11C]methionine PET in IDH-wildtype diffuse gliomas with lower-grade histological features: venturing beyond WHO classification

PURPOSE

IDH-wildtype (IDH-wt) diffuse gliomas with histological features of lower-grade gliomas (LGGs) are rare and heterogeneous primary brain tumours. [11C]Methionine (MET) positron emission tomography (PET) is commonly used to evaluate glial neoplasms at diagnosis. The present study aimed to assess the prognostic value of MET PET in newly diagnosed, treatment naïve IDH-wt gliomas with histological features of LGGs.

METHODS

Patients with a histological diagnosis of IDH-wt LGG who underwent preoperative (< 100 days) MET PET/CT and surgery were retrospectively included. Qualitative and semi-quantitative analyses of MET PET images were performed. Progression-free survival (PFS) and overall survival (OS) were analysed by Kaplan-Meier curves. Cox proportional-hazards regression was used to test the association of imaging and clinical data to PFS and OS.

RESULTS

We included 48 patients (M:F = 25:23; median age 55). 39 lesions were positive and 9 negative at MET PET. Positive MET PET was significantly associated with shorter median PFS (15.7 months vs. not reached, p = 0.0146) and OS time (32.6 months vs. not reached, p = 0.0253). Incomplete surgical resection and higher TBRmean values were independent predictors of shorter PFS on multivariate analysis (p < 0.001 for both). Higher tumour grade and incomplete surgical resection were independent predictors of OS at multivariate analysis (p = 0.027 and p = 0.01, respectively).

CONCLUSION

MET PET is useful for the prognostic stratification of patients with IDH-wt glial neoplasms with histological LGGs features. Considering their huge biological heterogeneity, the combination of MET PET and molecular analyses may help to improve the prognostic accuracy in these diffuse gliomas subset and influence therapeutic choices accordingly.

Advances in molecular and imaging biomarkers in lower-grade gliomas

INTRODUCTION

Lower-grade (grade 2-3) gliomas (LGGs) constitutes a group of primary brain tumors with variable clinical behaviors and treatment responses. Recent advancements in molecular biology have redefined their classification, and novel imaging modalities emerged for the noninvasive diagnosis and follow-up.

AREAS COVERED

This review comprehensively analyses the current knowledge on molecular and imaging biomarkers in LGGs. Key molecular alterations, such as IDH mutations and 1p/19q codeletion, are discussed for their prognostic and predictive implications in guiding treatment decisions. Moreover, the authors explore theranostic biomarkers for the potential of tailored therapies. Additionally, they also describe the utility of advanced imaging modalities, including widely available techniques, as dynamic susceptibility contrast perfusion-weighted imaging and less validated, emerging approaches, for the noninvasive LGGs characterization and follow-up.

EXPERT OPINION

The integration of molecular markers enhanced the stratification of LGGs, leading to the new concept of integrated histomolecular classification. While the IDH mutation is an established key prognostic and predictive marker, recent results from IDH inhibitors trials showed its potential value as a theranostic marker. In this setting, advanced MRI techniques such as 2-D-hydroxyglutarate spectroscopy are very promising for the noninvasive diagnosis and monitoring of LGGs. This progress offers exciting prospects for personalized medicine and improved treatment outcomes in LGGs.

Predicting TERT promoter mutation status using 1H-MR spectroscopy and stretched-exponential model of diffusion-weighted imaging in IDH-wildtype diffuse astrocytic glioma without intense enhancement

PURPOSE

Isocitrate dehydrogenase (IDH)-wildtype diffuse astrocytic glioma with telomerase reverse transcriptase (TERT) promoter mutation is defined as glioblastoma by the WHO 2021 criteria, revealing that TERT promotor mutation is highly associated with tumor aggressiveness. The aim of this study was to identify features from MR spectroscopy (MRS) and multi-exponential models of DWI distinguishing wild-type TERT (TERTw) from TERT promoter mutation (TERTm) in IDH-wildtype diffuse astrocytic glioma.

METHODS

Participants comprised 25 adult patients with IDH-wildtype diffuse astrocytic glioma. Participants were classified into TERTw and TERTm groups. Point-resolved spectroscopy sequences were used for MRS data acquisition. DWI was performed with 13 different b-factors. Peak height ratios of NAA/Cr and Cho/Cr were calculated from MRS data. Mean apparent diffusion coefficient (ADC), perfusion fraction (f), diffusion coefficient (D), pseudo-diffusion coefficient (D*), distributed diffusion coefficient (DDC), and heterogeneity index (α) were obtained using multi-exponential models from DWI data. Each parameter was compared between TERTw and TERTm using the Mann-Whitney U test. Correlations between parameters derived from MRS and DWI were also evaluated.

RESULTS

NAA/Cr and Cho/Cr were both higher for TERTw than for TERTm. The α of TERTw was smaller than that of TERTm, while the f of TERTw was higher than that of TERTm. NAA/Cr correlated negatively with α, but not with other DWI parameters. Cho/Cr did not show significant correlations with any DWI parameters.

CONCLUSION

The combination of NAA/Cr and α may have merit in clinical situation to predict the TERT mutation status of IDH-wildtype diffuse astrocytic glioma without intense enhancement.

Imaging Cancer in Neuroradiology

Neuroimaging plays a pivotal role in the diagnosis, management, and prognostication of brain tumors. Recently, the World Health Organization published the fifth edition of the WHO Classification of Tumors of the Central Nervous System (CNS5), which places greater emphasis on tumor genetics and molecular markers to complement the existing histological and immunohistochemical approaches. Recent advances in computational power allowed modern neuro-oncological imaging to move from a strictly morphology-based discipline to advanced neuroimaging techniques with quantifiable tissue characteristics such as tumor cellularity, microstructural organization, hemodynamic, functional, and metabolic features, providing more precise tumor diagnosis and management. The aim of this review is to highlight the key imaging features of the recently published CNS5, outlining the current imaging standards and summarizing the latest advances in neuro-oncological imaging techniques and their role in complementing traditional brain tumor imaging and management.

IDH wild-type lower-grade gliomas with glioblastoma molecular features: a systematic review and meta-analysis

The WHO 2021 classification defines IDH wild type (IDHw) histologically lower-grade glioma (hLGG) as molecular glioblastoma (mGBM) if TERT promoter mutation (pTERTm), EGFR amplification or chromosome seven gain and ten loss aberrations are indicated. We systematically reviewed articles of IDHw hLGGs studies (49 studies, N = 3748) and meta-analyzed mGBM prevalence and overall survival (OS) according to the PRISMA statement. mGBM rates in IDHw hLGG were significantly lower in Asian regions (43.7%, 95% confidence interval [CI: 35.8-52.0]) when compared to non-Asian regions (65.0%, [CI: 52.9-75.4]) (P = 0.005) and were significantly lower in fresh-frozen specimen when compared to formalin-fixed paraffin-embedded samples (P = 0.015). IDHw hLGGs without pTERTm rarely expressed other molecular markers in Asian studies when compared to non-Asian studies. Patients with mGBM had significantly longer OS times when compared to histological GBM (hGBM) (pooled hazard ratio (pHR) 0.824, [CI: 0.694-0.98], P = 0.03)). In patients with mGBM, histological grade was a significant prognostic factor (pHR 1.633, [CI: 1.09-2.447], P = 0.018), as was age (P = 0.001) and surgical extent (P = 0.018). Although bias risk across studies was moderate, mGBM with grade II histology showed better OS rates when compared to hGBM.

From Theory to Practice: Implementing the WHO 2021 Classification of Adult Diffuse Gliomas in Neuropathology Diagnosis

Diffuse gliomas are the most common type of primary central nervous system (CNS) neoplasm to affect the adult population. The diagnosis of adult diffuse gliomas is dependent upon the integration of morphological features of the tumour with its underlying molecular alterations, and the integrative diagnosis has become of increased importance in the fifth edition of the WHO classification of CNS neoplasms (WHO CNS5). The three major diagnostic entities of adult diffuse gliomas are as follows: (1) astrocytoma, IDH-mutant; (2) oligodendroglioma, IDH-mutant and 1p/19q-codeleted; and (3) glioblastoma, IDH-wildtype. The aim of this review is to summarize the pathophysiology, pathology, molecular characteristics, and major diagnostic updates encountered in WHO CNS5 of adult diffuse gliomas. Finally, the application of implementing the necessary molecular tests for diagnostic workup of these entities in the pathology laboratory setting is discussed.

Mutational landscape of primary spinal cord astrocytoma

Primary spinal cord astrocytoma (SCA) is a rare disease. Knowledge about the molecular profiles of SCAs mostly comes from intracranial glioma; the pattern of genetic alterations of SCAs is not well understood. Herein, we describe genome-sequencing analyses of primary SCAs, aiming to characterize the mutational landscape of primary SCAs. We utilized whole exome sequencing (WES) to analyze somatic nucleotide variants (SNVs) and copy number variants (CNVs) among 51 primary SCAs. Driver genes were searched using four algorithms. GISTIC2 was used to detect significant CNVs. Additionally, recurrently mutated pathways were also summarized. A total of 12 driver genes were identified. Of those, H3F3A (47.1%), TP53 (29.4%), NF1 (19.6%), ATRX (17.6%), and PPM1D (17.6%) were the most frequently mutated genes. Furthermore, three novel driver genes seldom reported in glioma were identified: HNRNPC, SYNE1, and RBM10. Several germline mutations, including three variants (SLC16A8 rs2235573, LMF1 rs3751667, FAM20C rs774848096) that were associated with risk of brain glioma, were frequently observed in SCAs. Moreover, 12q14.1 (13.7%) encompassing the oncogene CDK4 was recurrently amplified and negatively affected patient prognosis. Besides frequently mutated RTK/RAS pathway and PI3K pathway, the cell cycle pathway controlling the phosphorylation of retinoblastoma protein (RB) was mutated in 39.2% of patients. Overall, a considerable degree of the somatic mutation landscape is shared between SCAs and brainstem glioma. Our work provides a key insight into the molecular profiling of primary SCAs, which might represent candidate drug targets and complement the molecular atlas of glioma. © 2023 The Pathological Society of Great Britain and Ireland.

Prediction of the Molecular Subtype of IDH Mutation Combined with MGMT Promoter Methylation in Gliomas via Radiomics Based on Preoperative MRI

BACKGROUND

The molecular subtype of IDH mut combined with MGMT meth in gliomas suggests a good prognosis and potential benefit from TMZ chemotherapy. The aim of this study was to establish a radiomics model to predict this molecular subtype.

METHOD

The preoperative MR images and genetic data of 498 patients with gliomas were retrospectively collected from our institution and the TCGA/TCIA dataset. A total of 1702 radiomics features were extracted from the tumour region of interest (ROI) of CE-T1 and T2-FLAIR MR images. Least absolute shrinkage and selection operator (LASSO) and logistic regression were used for feature selection and model building. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the predictive performance of the model.

RESULTS

Regarding clinical variables, age and tumour grade were significantly different between the two molecular subtypes in the training, test and independent validation cohorts (p < 0.05). The areas under the curve (AUCs) of the radiomics model based on 16 selected features in the SMOTE training cohort, un-SMOTE training cohort, test set and independent TCGA/TCIA validation cohort were 0.936, 0.932, 0.916 and 0.866, respectively, and the corresponding F1-scores were 0.860, 0.797, 0.880 and 0.802. The AUC of the independent validation cohort increased to 0.930 for the combined model when integrating the clinical risk factors and radiomics signature.

CONCLUSIONS

radiomics based on preoperative MRI can effectively predict the molecular subtype of IDH mut combined with MGMT meth.

Observation of the delineation of the target volume of radiotherapy in adult-type diffuse gliomas after temozolomide-based chemoradiotherapy: analysis of recurrence patterns and predictive factors

BACKGROUND

Radiation therapy is the cornerstone of treatment for adult-type diffuse gliomas, but recurrences are inevitable. Our study assessed the prognosis and recurrence pattern of different radiotherapy volumes after temozolomide-based chemoradiation in our institution.

METHODS

The treatment plans were classified into two groups, the plan 1 intentionally involved the entire edema area while plan 2 did not. Retrospectively investigate the differences in outcomes of 118 adult-type diffuse gliomas patients between these two treatment plans. Then, patients who underwent relapse were selected to analyze their recurrence patterns. Continuous dynamic magnetic resonance images (MRI) were collected to categorized the recurrence patterns into central, in-field, marginal, distant, and cerebrospinal fluid dissemination (CSF-d) recurrence. Finally, the clinical and molecular characteristics which influenced progression were analyzed.

RESULTS

Plan 1 (n = 63) showed a median progression-free survival (PFS) and overall survival (OS) of 9.5 and 26.4 months while plan 2 (n = 55) showed a median PFS and OS of 9.4 and 36.5 months (p = 0.418; p = 0.388). Treatment target volume had no effect on the outcome in patients with adult-type diffuse gliomas. And there was no difference in radiation toxicity (p = 0.388). Among the 90 relapsed patients, a total of 58 (64.4%) patients had central recurrence, 10 (11.1%) patients had in-field recurrence, 3 (3.3%) patients had marginal recurrence, 11 (12.2.%) patients had distant recurrence, and 8 (8.9%) patients had CSF-d recurrence. By treatment plans, the recurrence patterns were similar and there was no significant difference in survival. Reclassifying the progression pattern into local and non-local groups, we observed that oligodendroglioma (n = 10) all relapsed in local and no difference in PFS and OS between the two groups (p > 0.05). Multivariable analysis showed that subventricular zone (SVZ) involvement was the independent risk factor for non-local recurrence in patients with GBM (p < 0.05).

CONCLUSION

In our study, deliberately including or not the entire edema had no impact on prognosis and recurrence. Patients with varied recurrence patterns had diverse clinical and genetic features.

Molecular Characterization of Adult Tumors Diagnosed as Cerebellar Glioblastomas Identifies Subgroups Associated With Prognosis

Adult tumors diagnosed as cerebellar glioblastoma (cGBM) are rare and their optimal classification remains to be determined. The aim of this study was to identify subgroups of cGBM based on targeted molecular analysis. cGBM diagnosed between 2003 and 2017 were identified from the French Brain Tumor Database and reviewed according to the WHO 2021 classification. The following molecular alterations were studied: IDH1/2 , H3F3A , FGFR1 , BRAF , TERT promoter mutations, EGFR amplification, MGMT promoter methylation, and alternative lengthening of telomere status. DNA methylation profile was assessed in a subset of cases. Eighty-three cGBM were included and could be classified into 6 mutually exclusive subgroups associated with median age at diagnosis (MA) and prognosis: TERT -mutant and/or EGFR -amplified tumors (n=22, 26.5%, MA=62 y, median overall survival [OS]=4 mo), H3K27M-mutant tumors (n=15, 18.1%, MA=48 y, median OS=8 mo), mitogen-activated protein kinases (MAPK) pathway-activated tumors ( FGFR1 , BRAF mutation, or occurring in neurofibromatosis type I patients, n=15, 18.1%, MA=48 y, median OS=57 mo), radiation-associated tumors (n=5, 6%, MA=47 y, median OS=5 mo), IDH-mutant tumors (n=1), and unclassified tumors (n=25, 30.1%, MA=63 y, median OS=17 mo). Most MAPK pathway-activated tumors corresponded to high-grade astrocytomas with piloid features based on DNA methylation profiling. In multivariate analysis, MAPK pathway-activating alterations, ATRX loss of expression, and alternative lengthening of telomere positivity were independently associated with a better outcome and TERT / EGFR alterations with a worse outcome. cGBM display an important intertumoral heterogeneity. Targeted molecular analysis enables to classify the majority of tumors diagnosed as cGBM into mutually exclusive and clinically relevant subgroups. The presence of MAPK pathway alterations is associated with a much better prognosis.

Genetic Alteration May Proceed with a Histological Change in Glioblastoma: A Report from Initially Diagnosed as Nontumor Lesion Cases

Despite recent signs of progress in diagnostic radiology, it is quite rare that a glioblastoma (GBM) is detected asymptomatically. We describe two patients with asymptomatic nonenhancing GBMs that were not diagnosed with neoplasia at first. The patients had brain scans as medical checkups, and incidentally lesions were detected. In both cases, surgical specimens histopathologically showed no evidence of neoplasia, whereas molecular genetic findings were isocitrate dehydrogenase (IDH)-wildtype, O⁶-methylguanine-DNA methyltransferase promoter (pMGMT) unmethylated, and telomerase reverse transcriptase (TERT) promoter mutated, which matched to GBM. One patient was observed without adjuvant therapy and the tumor recurred 7 months later. Reoperation was performed, and histopathologically GBM was confirmed with the same molecular diagnosis as the first surgical specimen. Another patient was carefully observed, and chemoradiotherapy was begun 6 months after the operation following the extension of the lesion. Eventually, because of disease progression, both patients deceased. We postulate that in each case, the tumor was not lower-grade glioma but corresponded to the early growth phase of GBM cells. Thus far, cases of malignant transformation from lower-grade glioma or asymptomatic GBM with typical histologic features are reported. Nevertheless, to the best of our knowledge, no such case of nonenhancing, nonhistologically confirmed GBM was reported. We conjecture these cases shed light on the yet unknown natural history of GBM. GBM can take the form of radiological nonenhancing and histological nonneoplastic fashion before typical morphology. Molecular genetic analysis can diagnose atypical preceding GBM, and we recommend early surgical removal and adjuvant treatment.

Clinical characteristics and survival of glioblastoma complicated with non-central nervous system tumors

BACKGROUND

Diagnosis and treatment of patients with glioblastoma (GBM) who are also diagnosed with primary non-central nervous system (CNS) tumors remain a challenge, yet little is known about the clinical characteristics and prognosis of these patients. The data presented here compared the clinical and pathological features between glioblastoma patients with or without primary non-CNS tumors, trying to further explore this complex situation.

METHODS

Statistical analysis was based on the clinical and pathological data of 45 patients who were diagnosed with isocitrate dehydrogenase (IDH) wild-type glioblastoma accompanied by non-CNS tumors between January 2019 and February 2022 in Beijing Tiantan Hospital. Univariate COX proportional hazard regression model was used to determine risk factors for overall survival.

RESULTS

It turned out to be no significant difference in the overall survival (OS) of the 45 patients with IDH-wild-type GBM plus non-CNS tumors, compared with the 112 patients who were only diagnosed with IDH-wild-type GBM. However, there was a significant difference in OS of GBM patients with benign tumors compared to those with malignant tumors.

CONCLUSIONS

Implications for the non-central nervous system tumors on survival of glioblastomas were not found in this research. However, glioblastomas complicated with other malignant tumors still showed worse clinical outcomes.

WHO 2021 and beyond: new types, molecular markers and tools for brain tumor classification

PURPOSE OF REVIEW

The fifth edition of the WHO classification of central nervous system tumors was published in 2021. It implemented major advances in the current diagnostic practice such as DNA methylation profiling. The review addresses how our understanding of the diversity of brain tumors has recently much improved through omics analysis and derived molecular biomarkers.

RECENT FINDINGS

Latest impactful studies identifying new diagnostic or prognostic biomarkers in frequent tumors and describing new rare tumor types are summarized about adult and pediatric gliomas, rare neuroepithelial tumors, ependymomas, medulloblastomas and meningiomas. Some controversies are debated. The role of methylation classes and surrogate immunohistochemical markers is highlighted.

SUMMARY

New diagnostic criteria and better definitions of tumor types aim at improving the management of brain tumor patients and at better evaluating new treatments in clinical trials. The rapidly evolving field of brain tumor classification opens exciting perspectives and many challenges to integrate clinical, radiological, histological and molecular information into a framework relevant for care and research.

Phenotype and Neuronal Cytotoxic Function of Glioblastoma Extracellular Vesicles

Glioblastoma (GBM) is the most aggressive and lethal form of brain tumor. Extracellular vesicles (EVs) released by tumor cells play a critical role in cellular communication in the tumor microenvironment promoting tumor progression and invasion. We hypothesized that GBM EVs possess unique characteristics which exert effects on endogenous CNS cells including neurons, producing dose-dependent neuronal cytotoxicity. We purified EVs from the plasma of 20 GBM patients, 20 meningioma patients, and 21 healthy controls, and characterized EV phenotypes by electron microscopy, nanoparticle tracking analysis, protein concentration, and proteomics. We evaluated GBM EV functions by determining their cytotoxicity in primary neurons and the neuroblastoma cell line SH-SY5Y. In addition, we determined levels of IgG antibodies in the plasma in GBM (n = 82), MMA (n = 83), and controls (non-tumor CNS disorders and healthy donors, n = 50) with capture ELISA. We discovered that GBM plasma EVs are smaller in size and had no relationship between size and concentration. Importantly, GBM EVs purified from both plasma and tumor cell lines produced IgG-mediated, complement-dependent apoptosis and necrosis in primary human neurons, mouse brain slices, and neuroblastoma cells. The unique phenotype of GBM EVs may contribute to its neuronal cytotoxicity, providing insight into its role in tumor pathogenesis.