Controversies in the Therapy of Low-Grade Gliomas

Glutathione metabolism-related gene signature predicts prognosis and treatment response in low-grade glioma

Cancer cells can induce molecular changes that reshape cellular metabolism, creating specific vulnerabilities for targeted therapeutic interventions. Given the importance of reactive oxygen species (ROS) in tumor development and drug resistance, and the abundance of reduced glutathione (GSH) as the primary cellular antioxidant, we examined an integrated panel of 56 glutathione metabolism-related genes (GMRGs) across diverse cancer types. This analysis revealed a remarkable association between GMRGs and low-grade glioma (LGG) survival. Unsupervised clustering and a GMRGs-based risk score (GS) categorized LGG patients into two groups, linking elevated glutathione metabolism to poorer prognosis and treatment outcomes. Our GS model outperformed established clinical prognostic factors, acting as an independent prognostic factor. GS also exhibited correlations with pro-tumor M2 macrophage infiltration, upregulated immunosuppressive genes, and diminished responses to various cancer therapies. Experimental validation in glioma cell lines confirmed the critical role of glutathione metabolism in glioma cell proliferation and chemoresistance. Our findings highlight the presence of a unique metabolic susceptibility in LGG and introduce a novel GS system as a highly effective tool for predicting the prognosis of LGG.

Simultaneous quantification of perfusion, permeability, and leakage effects in brain gliomas using dynamic spin-and-gradient-echo echoplanar imaging MRI

OBJECTIVE

To determine the feasibility and biologic correlations of dynamic susceptibility contrast (DSC), dynamic contrast enhanced (DCE), and quantitative maps derived from contrast leakage effects obtained simultaneously in gliomas using dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI) during a single contrast injection.

MATERIALS AND METHODS

Thirty-eight patients with enhancing brain gliomas were prospectively imaged with dynamic SAGE-EPI, which was processed to compute traditional DSC metrics (normalized relative cerebral blood flow [nrCBV], percentage of signal recovery [PSR]), DCE metrics (volume transfer constant [Ktrans], extravascular compartment [ve]), and leakage effect metrics: ΔR2,ss* (reflecting T2*-leakage effects), ΔR1,ss (reflecting T1-leakage effects), and the transverse relaxivity at tracer equilibrium (TRATE, reflecting the balance between ΔR2,ss* and ΔR1,ss). These metrics were compared between patient subgroups (treatment-naïve [TN] vs recurrent [R]) and biological features (IDH status, Ki67 expression).

RESULTS

In IDH wild-type gliomas (IDHwt-i.e., glioblastomas), previous exposure to treatment determined lower TRATE (p = 0.002), as well as higher PSR (p = 0.006), Ktrans (p = 0.17), ΔR1,ss (p = 0.035), ve (p = 0.006), and ADC (p = 0.016). In IDH-mutant gliomas (IDHm), previous treatment determined higher Ktrans and ΔR1,ss (p = 0.026). In TN-gliomas, dynamic SAGE-EPI metrics tended to be influenced by IDH status (p ranging 0.09-0.14). TRATE values above 142 mM-1s-1 were exclusively seen in TN-IDHwt, and, in TN-gliomas, this cutoff had 89% sensitivity and 80% specificity as a predictor of Ki67 > 10%.

CONCLUSIONS

Dynamic SAGE-EPI enables simultaneous quantification of brain tumor perfusion and permeability, as well as mapping of novel metrics related to cytoarchitecture (TRATE) and blood-brain barrier disruption (ΔR1,ss), with a single contrast injection.

CLINICAL RELEVANCE STATEMENT

Simultaneous DSC and DCE analysis with dynamic SAGE-EPI reduces scanning time and contrast dose, respectively alleviating concerns about imaging protocol length and gadolinium adverse effects and accumulation, while providing novel leakage effect metrics reflecting blood-brain barrier disruption and tumor tissue cytoarchitecture.

KEY POINTS

• Traditionally, perfusion and permeability imaging for brain tumors requires two separate contrast injections and acquisitions. • Dynamic spin-and-gradient-echo echoplanar imaging enables simultaneous perfusion and permeability imaging. • Dynamic spin-and-gradient-echo echoplanar imaging provides new image contrasts reflecting blood-brain barrier disruption and cytoarchitecture characteristics.

Risk prediction and treatment assessment in glioma patients using SEER database: a prospective observational study

OBJECTIVES

To use a nomogram to predict the risk of mortality and estimate the impact of current treatment on the prognosis of glioma patients.

METHODS

A total of 3798 cases were obtained from the Surveillance Epidemiology and End Results database according to the selection criteria. A nomogram was built on the independent clinical factors screened by the variance inflation factor, univariate analyses and a multivariate Cox regression model. Then, categorising the overall population into high-risk, medium-risk and low-risk groups using nomogram-derived risk scores, to study the impact of treatment on different subgroups' survival outcomes. Furthermore, based on the postmatch cohorts, the influences of treatment on survival outcomes were assessed by the log-rank test.

RESULT

Age, race, stage of disease, histological type, histological grade, surgery, radiotherapy and chemotherapy were identified as the independent prognostic factors. A nomogram with good discrimination and consistency was built. Generally, the patients who underwent surgery, radiotherapy and chemotherapy were more likely to achieve better prognosis than those who did not, except for those who received radiotherapy in the low-risk cohort and those who underwent surgery in the high-risk cohort. Furthermore, the isocitrate dehydrogenase 1/2 (IDH1/2) wild-type patients with surgery, radiotherapy or chemotherapy tended to have higher survival probabilities, while some inconsistent results were observed in the IDH mutant-type cohort.

CONCLUSION

Surgery, radiotherapy and chemotherapy improved the prognosis, while appropriate selection of topical treatment for the low-risk or high-risk patients deserves further consideration. IDH status gene might be a reliable indicator of therapeutic effectiveness.

A prognostic signature based on snoRNA predicts the overall survival of lower-grade glioma patients

Introduction

Small nucleolar RNAs (snoRNAs) are a group of non-coding RNAs enriched in the nucleus which direct post-transcriptional modifications of rRNAs, snRNAs and other molecules. Recent studies have suggested that snoRNAs have a significant role in tumor oncogenesis and can be served as prognostic markers for predicting the overall survival of tumor patients.

Methods

We screened 122 survival-related snoRNAs from public databases and eventually selected 7 snoRNAs that were most relevant to the prognosis of lower-grade glioma (LGG) patients for the establishment of the 7-snoRNA prognostic signature. Further, we combined clinical characteristics related to the prognosis of glioma patients and the 7-snoRNA prognostic signature to construct a nomogram.

Results

The prognostic model displayed greater predictive power in both validation set and stratification analysis. Results of enrichment analysis revealed that these snoRNAs mainly participated in the post-transcriptional process such as RNA splicing, metabolism and modifications. In addition, 7-snoRNA prognostic signature were positively correlated with immune scores and expression levels of multiple immune checkpoint molecules, which can be used as potential biomarkers for immunotherapy prediction. From the results of bioinformatics analysis, we inferred that SNORD88C has a major role in the development of glioma, and then performed in vitro experiments to validate it. The results revealed that SNORD88C could promote the proliferation, invasion and migration of glioma cells.

Discussion

We established a 7-snoRNA prognostic signature and nomogram that can be applied to evaluate the survival of LGG patients with good sensitivity and specificity. In addition, SNORD88C could promote the proliferation, migration and invasion of glioma cells and is involved in a variety of biological processes related to DNA and RNA.

Effectiveness and Safety of Different Postoperative Adjuvant Regimens in Patients with Low-Grade Gliomas: A Network Meta-Analysis

OBJECTIVE

This study aimed to investigate the effectiveness and safety of various adjuvant regimens in patients with low-grade gliomas and to further explore the optimal adjuvant treatment for patients with low-grade gliomas and the differences in the efficacy of each treatment regimens in different tumor types.

METHODS

A comprehensive search of the PubMed, Cochrane Library, Ovid, Embase, and Web of Science databases was conducted to screen randomized and nonrandomized controlled trials related to adjuvant therapy in patients with low-grade gliomas. The Cochrane quality assessment method and the Newcastle-Ottawa Scale were used to assess the quality of the included randomized and nonrandomized controlled trials, respectively. The data from previous studies were extracted using Excel and GetData Graph Digitizer 2.26 software, and network meta-analysis was performed using RevMan 5.3 and Stata 16.0 statistical software.

RESULTS

The specific ranking of 5-year progression-free survival (5-year PFS) for each treatment regimen from the best to the worst in patients with low-grade gliomas was surgery (S) combined with procarbazine, lomustine, and vincristine (S + PCV); surgery combined with standard radiotherapy and PCV multidrug chemotherapy (S + RT + PCV); surgery combined with standard radiotherapy and temozolomide monotherapy (S + RT + TMZ); surgery combined with enhanced radiotherapy (S + H-RT); surgery combined with standard radiotherapy (S + RT); surgery combined with TMZ (S + TMZ); and S. The 5-year overall survival (OS) ranking was S + RT + TMZ, S + RT + PCV, surgery combined with enhanced radiotherapy and TMZ monotherapy (S + H-RT + TMZ), S + H-RT, S + RT, and S. The 2-year progression-free survival ranking was S + RT + TMZ, S + PCV, S + RT, S + RT + PCV, S + TMZ, S + H-RT, and S. The 2-year overall survival ranking was S + RT + TMZ, S + H-RT + TMZ, S + RT, S + RT + PCV, S + H-RT, and S. The incidence of adverse events (≥3) was ranked from highest to lowest as follows: S + RT + PCV, S + RT + TMZ, S + PCV, S + H-RT, S + TMZ, and S + RT. In the isocitrate dehydrogenase 1/2 mutation nonchromosome 1p and 19q chromosome whole arm codeletion (IDHmt/noncoder) group, the S + RT + PCV and S + H-RT regimens had better 5-year PFS and 5-year OS. In the isocitrate dehydrogenase 1/2 mutation and chromosome 1p and 19q chromosome whole arm codeletion (IDHmt/coder) group, the 5-year PFS of each treatment regimen ranked from the best to the worst was S + RT + TMZ, S + RT + PCV, S + H-RT, S + RT, S + TMZ, and S. The order of 5-year OS from the best to the worst was S + H-RT, S + RT + TMZ, S + RT + PCV, S + RT, and S. In the isocitrate dehydrogenase 1/2 wild-type (IDHwt) group, the S + H-RT and S + TMZ regimens had better 5-year PFS.

CONCLUSIONS

This study revealed that both the S + RT + TMZ and S + RT + PCV regimens might be effective therapies for treating patients with low-grade gliomas. Among these, the S + RT + TMZ regimen seemed to be safer but might lead to tumor deterioration. In the IDHmt/coder type, the S + RT + TMZ scheme might have a significant advantage. In the IDHmt/noncoder type, the S + RT + PCV scheme might be more dominant, while in the IDHwt type, the S + H-RT and S + TMZ schemes also might be good treatment options.

Reasoning and causal inference regarding surgical options for patients with low-grade gliomas using machine learning: A SEER-based study

BACKGROUND

Due to the heterogeneity of low-grade gliomas (LGGs), the lack of randomized control trials, and strong clinical evidence, the effect of the extent of resection (EOR) is currently controversial.

AIM

To determine the best choice between subtotal resection (STR) and gross-total resection (GTR) for individual patients and to identify features that are potentially relevant to treatment heterogeneity.

METHODS

Patients were enrolled from the SEER database. We used a novel DL approach to make treatment recommendations for patients with LGG. We also made causal inference of the average treatment effect (ATE) of GTR compared with STR.

RESULTS

The patients were divided into the Consis. and In-consis. groups based on whether their actual treatment and model recommendations were consistent. Better brain cancer-specific survival (BCSS) outcomes in the Consis. group was observed. Overall, we also identified two subgroups that showed strong heterogeneity in response to GTR. By interpreting the models, we identified numerous variables that may be related to treatment heterogeneity.

CONCLUSIONS

This is the first study to infer the individual treatment effect, make treatment recommendation, and guide surgical options through deep learning approach in LGG research. Through causal inference, we found that heterogeneous responses to STR and GTR exist in patients with LGG. Visualization of the model yielded several factors that contribute to treatment heterogeneity, which are worthy of further discussion.

Decapping enzyme 2 is a novel immune-related biomarker that predicts poor prognosis in glioma

This study analyzed sequencing and clinical data from the Cancer Genome Atlas (TCGA) and gene expression synthesis, and used Chinese glioma Genome Atlas (CGGA) data for external validation. The expression of DCP2 in normal brain and tumor tissue was compared. We analyzed the clinical and molecular characteristics and prognostic value of DCP2 in glioma. In addition, DCP2 expression levels were evaluated in 30 glioma tissue samples and upregulated in glioma samples compared to normal brain tissue (p < 0.001). Multivariate data analysis from TCGA showed that increased DCP2 expression was an independent risk factor for overall survival and prognosis of glioma patients. As indicated by the analysis of the TCGA data set. The expression level of DCP2 is closely related to tumor immunity, including tumor immune cell infiltration, immune score, and co-expression of multiple immune-related genes. In addition, DCP2 was positively correlated with IL-6 and IL-7. Glioma cell proliferation and invasion were evaluated using cell viability, colony formation, wound healing, and transwell assays.Apoptosis and cell cycle were detected by flow cytometry. DCP2 promoted the proliferation, invasion and migration of glioma cells T98G and U251, inhibited apoptosis and blocked the S phase of the cell cycle. As a result of the altered expression of DCP2, a new prognostic biomarker may be identified that can improve patient survival.These findings suggest DCP2 as a potential biomarker for the prognosis of glioma and a candidate immunotherapy target.

An in silico approach to the identification of diagnostic and prognostic markers in low-grade gliomas

Low-grade gliomas (LGG) are central nervous system Grade I tumors, and as they progress they are becoming one of the deadliest brain tumors. There is still great need for timely and accurate diagnosis and prognosis of LGG. Herein, we aimed to identify diagnostic and prognostic biomarkers associated with LGG, by employing diverse computational approaches. For this purpose, differential gene expression analysis on high-throughput transcriptomics data of LGG versus corresponding healthy brain tissue, derived from TCGA and GTEx, respectively, was performed. Weighted gene co-expression network analysis of the detected differentially expressed genes was carried out in order to identify modules of co-expressed genes significantly correlated with LGG clinical traits. The genes comprising these modules were further used to construct gene co-expression and protein-protein interaction networks. Based on the network analyses, we derived a consensus of eighteen hub genes, namely, CD74, CD86, CDC25A, CYBB, HLA-DMA, ITGB2, KIF11, KIFC1, LAPTM5, LMNB1, MKI67, NCKAP1L, NUSAP1, SLC7A7, TBXAS1, TOP2A, TYROBP, and WDFY4. All detected hub genes were up-regulated in LGG, and were also associated with unfavorable prognosis in LGG patients. The findings of this study could be applicable in the clinical setting for diagnosing and monitoring LGG.

Risk factors for early progression of diffuse low-grade glioma in adults

Background

To explore the risk factors for early progression of diffuse low-grade glioma in adults.

Methods

A retrospective analysis of pathologic and clinical data of patients diagnosed with diffuse low-grade gliomas at Southwest Hospital between January 2010 and December 2014. The progression-free survival (PFS) less than 60 months was classified as the early progress group, and the PFS greater than 60 months was the control group for comparative analysis.

Results

A total of 138 patients were included in this study, including 94 cases of astrocytoma and 44 cases of oligodendroglioma. There were 63 cases with 100% resection, 56 cases with 90–100% resection degree, and 19 cases with resection degree < 90%. The average follow-up time was 60 months, of which 80 patients progressed and 58 patients did not progress. The average progression-free survival was 61 months. The median progression-free survival was 60 months. There were 68 patients with PFS≤ 60 months and 70 patients with PFS > 60 months. The two groups were compared for statistical analysis. In univariate analysis, there were significant differences in tumor subtype (p = 0.005), range (p = 0.011), volume (p = 0.005), location (p = 0.000), and extent of resection (p = 0.000). Multifactor analysis shows tumor location (HR = 4.549, 95% CI: 1.324–15.634, p = 0.016) and tumor subtype (HR = 3.347, 95% CI = 1.373–8.157, p = 0.008), and imcomplete resection is factors influencing early progression of low-grade glioma.

Conclusions

Low-grade gliomas involving deep location such as basal ganglia, inner capsule, and corpus callosum are more likely to progress early, while incomplete resection is a risk factor in early progression of astrocytoma.

Neuroplasticity of Glioma Patients: Brain Structure and Topological Network

Glioma is the most common primary malignant brain tumor in adults. It accounts for about 75% of such tumors and occurs more commonly in men. The incidence rate has been increasing in the past 30 years. Moreover, the 5-year overall survival rate of glioma patients is < 35%. Different locations, grades, and molecular characteristics of gliomas can lead to different behavioral deficits and prognosis, which are closely related to patients' quality of life and associated with neuroplasticity. Some advanced magnetic resonance imaging (MRI) technologies can explore the neuroplasticity of structural, topological, biochemical metabolism, and related mechanisms, which may contribute to the improvement of prognosis and function in glioma patients. In this review, we summarized the studies conducted on structural and topological plasticity of glioma patients through different MRI technologies and discussed future research directions. Previous studies have found that glioma itself and related functional impairments can lead to structural and topological plasticity using multimodal MRI. However, neuroplasticity caused by highly heterogeneous gliomas is not fully understood, and should be further explored through multimodal MRI. In addition, the individualized prediction of functional prognosis of glioma patients from the functional level based on machine learning (ML) is promising. These approaches and the introduction of ML can further shed light on the neuroplasticity and related mechanism of the brain, which will be helpful for management of glioma patients.

Prognostic value of O 6-methylguanine-DNA methyltransferase methylation in isocitrate dehydrogenase mutant gliomas

Background

Patients with isocitrate dehydrogenase (IDH) mutant gliomas have been associated with longer survival time than those that are IDH wild-type. Previous studies have shown the prognostic value of O ⁶ -methylguanine-DNA methyltransferase (MGMT) promoter methylation for glioblastoma multiforme (GBM), which are predominantly IDH wild-type. Little is known of the prognostic value of MGMT methylation status for IDH mutant gliomas.

Methods

We retrospectively identified IDH mutant gliomas patients between 2011 and 2020 that were tested for MGMT promoter methylation. We generated Kaplan-Meier estimator curves and performed Cox proportional hazard models for overall survival (OS) and progression-free survival (PFS) to compare the outcomes of MGMT promoter methylated versus MGMT unmethylated patients.

Results

Of 419 IDH mutant gliomas with MGMT promoter methylation testing, we identified 54 GBMs, 223 astrocytomas, and 142 oligodendrogliomas. 62.3% patients had MGMT methylated tumors while 37.7% were MGMT unmethylated. On Kaplan-Meier analysis, median OS for all MGMT methylated patients was 17.7 years and 14.6 years for unmethylated patients. Median PFS for all MGMT methylated patients was 7.0 years and for unmethylated patients 5.2 years. After univariate subgroup analysis, MGMT methylation is only prognostic for OS and PFS in GBM, and for OS in anaplastic oligodendroglioma and anaplastic oligodendroglioma for OS. In multivariate analysis, MGMT unmethylated GBM patients carry a higher risk of death (HR 7.72, 95% CI 2.10-28.33) and recurrence (HR 3.85, 95% CI 1.35-10.96).

Conclusions

MGMT promoter methylation is associated with better OS and PFS for IDH mutant GBM. MGMT promoter methylation testing for other IDH mutant glioma subtypes may not provide additional information on prognostication.

Contralesional Structural Plasticity in Different Molecular Pathologic Subtypes of Insular Glioma

Neuroplasticity may preserve neurologic function in insular glioma, thereby improving prognosis following resection. However, the anatomic and molecular bases of this phenomenon are not known. To address this gap in knowledge, the present study investigated contralesional compensation in different molecular pathologic subtypes of insular glioma by high-resolution three-dimensional T1-weighted structural magnetic resonance imaging. A total of 52 patients with insular glioma were examined. We compared the gray matter volume (GMV) of the contralesional insula according to histological grade [low-grade glioma (LGG) and high-grade glioma (HGG)] and molecular pathology status [isocitrate dehydrogenase (IDH) mutation, telomerase reverse-transcriptase (TERT) promoter mutation, and 1p19q codeletion] by voxel-based morphometry (VBM). A cluster of 320 voxels in contralesional insula with higher GMV was observed in glioma with IDH mutation as compared to IDH wild-type tumors by region of interest-based VBM analysis (family-wise error-corrected at p < 0.05). The GMV of the entire contralesional insula was also larger in insular glioma patients with IDH mutation than in patients with wild-type IDH. However, there was no association between histological grade, TERT promoter mutation, or 1p19q codeletion and GMV in the contralesional insula. Thus, IDH mutation is associated with greater structural compensation in insular glioma. These findings may be useful for predicting neurocognitive and functional outcomes in patients undergoing resection surgery.

Tumor Suppressor microRNA-138 Suppresses Low-Grade Glioma Development and Metastasis via Regulating IGF2BP2

Background

Low-grade gliomas (LGG), approximately constitute one-third of all types of gliomas, are prone to relapse and metastasis. MicroRNA-138 (miR-138) is reported to be dysregulated in diverse human tumors and mainly function as a tumor suppressor. In this study, we analyzed the expression profile and function of miR-138 in LGG.

Methods

Quantitative PCR (qPCR) and public database bioinformatics analysis were performed to determine the miR-138 levels in LGG. MiR-138 overexpression in LGG cells was achieved by miR-138 mimics transfection. Cell proliferation was assessed by CCK8, EdU and colony formation assays. Cell invasion and migration were analyzed by transwell and wound-healing assays. Xenograft model was employed to study the role of miR-138 in LGG growth in vivo. The target of miR-138 was validated by multiple methods, such as luciferase reporter assay, RT-qPCR and Western blot. Bioinformatics analysis was conducted to explore the molecular mechanisms by which miR-138 contributed to LGG progression.

Results

miR-138 was significantly downregulated in LGG tumor tissues and low expression of miR-138 was significantly associated with poor prognosis as well as relapse and metastasis in LGG patients. Functional analysis indicated that ectopic miR-138 expression suppressed LGG cell growth and invasive phenotype in vitro, and inhibited tumor development in vivo. Moreover, miR-138 directly targeted and repressed insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) by targeting the 3ʹ-UTR of IGF2BP2, inhibiting epithelial to mesenchymal transition (EMT) to attenuate LGG aggressiveness. In addition, we found that elevated IGF2BP2 expression correlates with poor survival of LGG patients.

Conclusion

miR-138 may function as a tumor inhibitor by directly inhibiting IGF2BP2 and suppressing EMT in the progression of LGG.