Recent developments and future directions in adult lower-grade gliomas: Society for Neuro-Oncology (SNO) and European Association of Neuro-Oncology (EANO) consensus

Ferroptosis and low-grade Glioma: The breakthrough potential of NUAK2

BACKGROUND

Low-grade glioma (LGG) is a primary brain tumor with high cellular heterogeneity and recurrence, leading to poor prognosis. Standard treatments (surgery, radiotherapy, and chemotherapy) have limited efficacy. Ferroptosis, an iron-dependent form of regulated cell death, is a potential therapeutic target, while dysregulated ferroptosis-related genes (FRGs) may drive tumor progression and therapy resistance.

METHODS

This study integrated multi-omics data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) to identify FRGs associated with LGG prognosis. Single-cell RNA sequencing (scRNA-seq) and pseudotime trajectory analysis were performed to investigate their functional roles. Key findings were validated through in vitro and in vivo experiments.

RESULTS

We identified 345 FRGs associated with LGG prognosis, which are involved in oxidative stress response, cell proliferation, and immune regulation. High-risk patients exhibited an immunosuppressive tumor microenvironment with elevated levels of M2 macrophages and Treg cells but reduced CD8+ T cell infiltration. Pseudotime trajectory analysis highlighted the dynamic roles of macrophages and astrocytes in immune evasion and microenvironment remodeling. Notably, the NUAK2 gene emerged as a key driver of tumor progression and immune suppression. In vitro and in vivo experiments confirmed that targeting NUAK2 significantly reduced tumor cell viability and growth, underscoring its critical regulatory role in LGG.

CONCLUSIONS

Our study provides comprehensive insights into the role of FRGs in LGG prognosis and tumor microenvironment regulation, with a particular focus on the NUAK2 gene. As a potential therapeutic target, NUAK2's critical role in tumor progression and immune evasion offers a new direction for LGG treatment. Future research should focus on validating NUAK2's role in larger cohorts and exploring its clinical application as a biomarker and therapeutic target.

Congress of neurological surgeons systematic review and evidence-based guidelines for the role of imaging in newly diagnosed WHO grade II diffuse glioma in adults: update

TARGET POPULATION

Adult patients with suspected or histologically proven WHO Grade II diffuse glioma. QUESTION 1: In adult patients with suspected or histologically proven WHO Grade II diffuse glioma, do advanced MRI techniques using magnetic resonance spectroscopy, perfusion weighted imaging or diffusion weighted imaging provide superior assessment of tumor grade, margins, progression, treatment-related effects, and prognosis compared to standard neuroimaging?

RECOMMENDATION

Level II: The use of diffusion imaging and dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL) sequences are suggested to differentiate WHO Grade II diffuse glioma from higher grade gliomas when this is not accomplished by T2 weighted and pre- and post-gadolinium contrast enhanced T1 weighted imaging.

LEVEL III

The use of diffusion and perfusion is suggested for obtaining information in genomics, prognosis, and post treatment monitoring when this information would be of value to the clinician and is not obtained through other methods.

LEVEL III

The use of MR Spectroscopy is suggested to differentiate WHO Grade II diffuse glioma from higher grade gliomas when this is not accomplished by standard MRI, perfusion and diffusion techniques and when such information would be of value to the clinician. QUESTION 2: In adult patients with suspected or histologically proven WHO Grade II diffuse glioma, does molecular imaging using amino acid PET tracers provide superior assessment of tumor grade, margins, progression, treatment-related effects, and prognosis compared to standard neuroimaging?

RECOMMENDATION

Level III: If not already evident by MRI studies, the addition of amino acid PET with FET and FDOPA as a tracer is suggested to help determine if a brain lesion is a low grade glioma or high grade glioma.

LEVEL III

If the standard clinical prognostic parameters are unclear and novel PET tracers are available, the clinician may consider FET to assist in determination of prognosis in an individual with grade II diffuse glioma.

LEVEL III

Clinicians may use FDOPA PET in addition to MRI if additional information is required for detection of tumor progression.

Management and survival trends for diffuse gliomas diagnosed at a single neurooncology center in China during 2000 to 2020

Currently reported survival outcomes for gliomas exhibit significant variability and controversy. In this study, we aim to provide survival data in Chinese populations by conducting a retrospective analysis of management and survival trends in a large cohort of glioma patients from a single institute in China. A total of 1206 patients with newly diagnosed gliomas treated between 2000 and 2020 were enrolled, including 537 glioblastoma (WHO grade 4), 450 astrocytomas (grade 2/3) and 219 oligodendroglial tumors (grade 2/3). The estimated overall survival at 5 years was 18.9% for glioblastoma, 58.8% for astrocytomas, and 80.7% for oligodendroglial tumors, while median survival was 17.2 months, 82.8 months, and not reached, respectively. The survival trend has increased over the past decades for all types of gliomas. Additionally, similar survival trends were observed between grade 2 and 3 IDH-mutant gliomas. Rising trends were observed in patients undergoing postsurgical radiation and chemotherapy. Multivariate analysis identified adjuvant radiochemotherapy as an independent factor for better prognosis in glioblastoma and astrocytomas. In summary, despite its retrospective nature, this cohort of glioma patients exhibits favorable survival outcomes compared to global statistics, indicating a geographical disparity in glioma prognosis. The promotion of adjuvant chemoradiotherapy contributes to improved prognosis.

Development and validation of a neutrophil extracellular traps-related gene signature for lower-grade gliomas

There is growing evidence linking neutrophil extracellular traps (NETs) to tumor genesis, growth, distant metastasis, and tumor-related thrombosis. However, the roles of NETs-related genes (NETRGs) on LGG prognosis remain unclear. The purpose of this study was to integrate multiple machine learning techniques and experiment validation to develop a reliable NETs-based signature that opens up novel approaches for assessing the prognosis and treatment response of LGG patients. Consensus clustering, k-means clustering and Nonnegative Matrix Factorization was used for the TCGA-LGG dataset and identified two NETs-related subgroups. The prognostic hallmark and nomogram for LGG were developed, which consist of five differentially expressed NETRGs (FPR1, PTAFR, SLC11A1, ICAM1, LTF) based on nine analytic approaches. The ROC curves and calibration curves of our NETRGs signature and nomogram exhibited strong and robust prognosis prediction abilities in both the TCGA-LGG training set and CGGA-325, CGGA-693 validation sets. The prognosis for LGG individuals in the low-risk category was better. The TISCH was used to examine the five NETRGs at the single-cell level. Common immunological checkpoints were expressed at greater levels in high-risk individuals. LGG individuals in the low-risk category posses a higher likelihood of being sensitive to Carmustine and Vincristine, as indicated by the drug sensitivity analysis. The qRT-PCR experiment and immunohistochemistry images confirmed that the expression of FPR1, PTAFR, SLC11A1 and ICAM1 are higher in low-grade oligodendroglioma. The NETRGs signature and nomogram can accurately and conveniently predict the LGG patients' prognosis, which can facilitate individualized treatment and the improvement of prognosis.

Influence of supratotal resection on overall survival and progression of tumor in gliomas grade 2 and 3: a systematic review and meta-analysis

BACKGROUND

Recurrence after resection is a major factor in poor prognosis for grade 2 and 3 gliomas. The effect of Supratotal Resection (STR) on recurrence timing remains debated. This meta-analysis examines overall survival (OS) and tumor progression in grade 2 and 3 gliomas after supratotal resection.

METHODS

Studies on patients with grade II and III gliomas who underwent supratotal resection were included, with comparisons to subtotal, partial, and total resections. The primary outcomes were overall survival (OS) and tumor progression, while secondary outcomes included return-to-work (RTW) rates, malignant transformations and cognitive impairments.

RESULTS

We included 954 patients from 8 studies, mean age was 39 (± 16) years. The mean OS for patients undergoing supratotal resection was 17.45 (95% CI: 3.39 to 89.74, p < 0.05) compared to TR. The OR for RTW in the STR group versus TR group was 0.12 (95% CI: 0.01 to 1.28, p = 0.08). Tumor progression OR was, no statistical significantly, 0.15 (95% CI: 0.00 to 38.00, p = 0.5), and the likelihood of malignancy was reduced 0.03 (95% CI: 0.01 to 0.18, p < 0.01) compared to the TR group. In the immediate pos-operatory, when comparing STR with TR, the OR of language impairment was 5.47 (95% CI: 2.73 to 10.97, p < 0.01) and cognitive impairment was 0.38 (95% CI: 0.17 to 0.58). During the follow-up, the OR of language impairment was 0.68 (95% CI: 0.25 to 1.81, p = 0.44) and cognitive impairment was 0.34 (95% CI: 0.03 to 3.61, p = 0.37) comparing STR with TR.

CONCLUSION

Patients with grade 2 and 3 gliomas undergoing supratotal resection showed significantly higher overall survival, fewer malignant transformations and language impairments in immediate pos-operatory. While there was a trend towards higher return-to-work rates, progression of tumor and better cognitive status during the follow-up, it was not statistically significant. Further studies are needed for definitive conclusions.

CLINICAL TRIAL NUMBER

Not applicable.

Nonenhancing Margin and Pial Invasion in Magnetic Resonance Imaging can Predict Isocitrate Dehydrogenase Status in Glioma Patients

BACKGROUND

The presence of isocitrate dehydrogenase (IDH) mutations and 1p/19q codeletion significantly influences the diagnosis and prognosis of patients with lower-grade gliomas (LGGs). The ability to predict these molecular signatures preoperatively can inform surgical strategies. This study sought to establish an interpretable imaging feature set for predicting molecular signatures and overall survival in LGGs.

METHODS

A cohort of 113 patients with grade 2 or 3 glioma (66 with mutated IDH and 47 with wild-type IDH) was analyzed. The feature set, chief complaints, and onset symptoms were integrated into a logistic regression model to predict IDH mutation and 1p/19q codeletion statuses. Receiver operator characteristic and area under the curve analyses were performed. The predictive model was externally validated using a public database from The Cancer Genome Atlas.

RESULTS

Smooth nonenhancing margin and pial invasion were significant predictors of IDH mutation, with odds ratio values of 3.55 (P = 0.03) and 7.89 (P = 1.0 × 10-3), respectively. Using the Visually Accessible Rembrandt Images feature set alone to predict IDH mutation status yielded an area under the curve value of 0.83, which increased to 0.85 and 0.87 when incorporating clinical information and onset symptoms for predicting IDH mutation and 1p/19q codeletion, respectively.

CONCLUSIONS

Gliomas with IDH mutations were more likely to exhibit smooth nonenhancing margins and pial invasion. In clinical practice, imaging prediction allows for the assessment of IDH mutation to shift from a postoperative outcome to a preoperative guidance indicator, facilitating more precise treatment for patients with LGGs.

Expanded Use of Vorasidenib in Non-Enhancing Recurrent CNS WHO Grade 3 Oligodendroglioma

Background/Objectives: Anaplastic oligodendrogliomas (AOs) are central nervous system (CNS) World Health Organization (WHO) grade 3 gliomas characterized by isocitrate dehydrogenase (IDH) mutation (m)IDH and 1p/19q codeletion. AOs are typically treated with surgery and chemoradiation. However, chemoradiation can cause detrimental late neurocognitive morbidities and an accelerated disease course. The recently regulatory-approved vorasidenib, a brain-penetrating oral inhibitor of IDH1/2, has altered the treatment paradigm for recurrent/residual non-enhancing surgically resected CNS WHO grade 2 mIDH gliomas. Though vorasidenib can delay the time to chemoradiation for grade 2 gliomas, the implications for vorasidenib in non-grade 2 mIDH gliomas are not well understood. Results: We present a case of a 71-year-old male with a grade 3 non-enhancing oligodendroglioma successfully treated with vorasidenib with an 11% reduction in residual tumor volume. Vorasidenib was well tolerated in our patient with a mild elevation in his liver transaminases that resolved following a brief interruption in treatment. Conclusions: Our case suggests that vorasidenib may impart therapeutic benefits in this setting. This case illustrates the need for further investigation into these less commonly addressed scenarios and treatment strategies that extend beyond current guidelines.

Clinical value of the MGMT promoter methylation score in IDHmt low-grade glioma for predicting benefit from temozolomide treatment

Background

Diffuse IDH mutant low-grade gliomas (IDHmt LGG) (World Health Organization grade 2) typically affect young adults. The outcome is variable, with survival ranging from 5 to over 20 years. The timing and choice of initial treatments after surgery remain controversial. In particular, radiotherapy is associated with early and late cognitive toxicity. Over 90% of IDHmt LGG exhibit some degree of promoter methylation of the repair gene O(6)-methylguanine-DNA methytransferase (MGMTp) that when expressed blunts the effect of alkylating agent chemotherapy, for example, temozolomide (TMZ). However, the clinical value of MGMTp methylation predicting benefit from TMZ in IDHmt LGG is unclear.

Methods

Patients treated in the EORTC-22033 phase III trial comparing TMZ versus radiotherapy served as training set to establish a cutoff based on the MGMT-STP27 methylation score. A validation cohort was established with patients treated in a single-center first-line with TMZ after surgery/surgeries.

Results

The MGMT-STP27 methylation score was associated with better progression-free survival (PFS) in the training cohort treated with TMZ, but not radiotherapy. In the validation cohort, an association with next treatment-free survival (P = .045) after TMZ was observed, and a trend using RANO criteria (P = .07). A cutoff value set above the 95% confidence interval of being methylated was significantly associated with PFS in the TMZ-treated training cohort, but not in the radiotherapy arm. However, this cutoff could not be confirmed in the test cohort.

Conclusions

While the MGMTp methylation score was associated with better outcomes in TMZ-treated IDHmt LGG, a cutoff could not be established to guide treatment decisions.

Future Directions in the Treatment of Low-Grade Gliomas

ABSTRACT

There is major interest in deintensifying therapy for isocitrate dehydrogenase-mutant low-grade gliomas, including with single-agent cytostatic isocitrate dehydrogenase inhibitors. These efforts need head-to-head comparisons with proven modalities, such as chemoradiotherapy. Ongoing clinical trials now group tumors by intrinsic molecular subtype, rather than classic clinical risk factors. Advances in imaging, surgery, and radiotherapy have improved outcomes in low-grade gliomas. Emerging biomarkers, targeted therapies, immunotherapy, radionuclides, and novel medical devices are a promising frontier for future treatment. Diverse representation in glioma research and clinical trials will help to ensure that advancements in care are realized by all groups.

Research Progress on Glioma Microenvironment and Invasiveness Utilizing Advanced Multi-Parametric Quantitative MRI

Magnetic resonance imaging (MRI) currently serves as the primary diagnostic method for glioma detection and monitoring. The integration of neurosurgery, radiation therapy, pathology, and radiology in a multi-disciplinary approach has significantly advanced its diagnosis and treatment. However, the prognosis remains unfavorable due to treatment resistance, inconsistent response rates, and high recurrence rates after surgery. These factors are closely associated with the complex molecular characteristics of the tumors, the internal heterogeneity, and the relevant external microenvironment. The complete removal of gliomas presents challenges due to their infiltrative growth pattern along the white matter fibers and perivascular space. Therefore, it is crucial to comprehensively understand the molecular features of gliomas and analyze the internal tumor heterogeneity in order to accurately characterize and quantify the tumor invasion range. The multi-parameter quantitative MRI technique provides an opportunity to investigate the microenvironment and aggressiveness of glioma tumors at the cellular, blood perfusion, and cerebrovascular response levels. Therefore, this review examines the current applications of advanced multi-parameter quantitative MRI in glioma research and explores the prospects for future development.

The characteristics of auditorial event-related potential under propofol sedation associated with preoperative cognitive performance in glioma patients

Background

Glioma patients often experience neurocognitive deficits, particularly mild cognitive impairment (MCI), which affects their perioperative safety. The use of auditory event-related potentials (AERPs) might be a promising method for reflecting perioperative cognitive function in patients, even under unresponsive sedation. In this study, we aimed to investigate the relationships between the AERP under sedation and preoperative cognitive performance in glioma patients.

Methods

Patients with primary supratentorial gliomas who were scheduled for elective craniotomy under general anesthesia were included in this prospective observational study. The patients were categorized into MCI and non-MCI groups based on their preoperative Montreal Cognitive Assessment (MoCA) scores. AERP characteristics, including mismatch negativity (MMN), P300, and event-related spectral perturbation (ERSP) in the theta bands, were analyzed under different propofol-induced sedation conditions. Differences in these parameters between groups and their relationships with preoperative cognitive performance were subsequently investigated.

Results

Twenty-nine eligible patients were included in the analysis. Compared to that in the non-MCI group, the average amplitude of the MMN component evoked by the novel stimulus significantly decreased during the recovery period in the MCI group (-3.895 ± 1.961 μV vs. -1.617 ± 1.831 μV, p = 0.003). Theta-ERSPs also differed between the two groups under standard (0.021 ± 0.658 μV2/Hz vs. 0.515 ± 0.622 μV2/Hz, p = 0.048) and novel (0.212 ± 0.584 μV2/Hz vs. 0.823 ± 0.931 μV2/Hz, p = 0.041) stimulation conditions under light sedation. After correcting for age, education level, site of lesion, WHO pathological grade and combined symptomatic epilepsy as confounders, the frontal theta-ERSP induced by standard and novel stimuli under light sedation was inversely related to the preoperative MoCA score (standard stimuli: β = -0.491, p = 0.011; novel stimuli: β = -0.594, p = 0.007), as was the average MMN amplitude induced by novel stimuli during the recovery period (β = -0.356, p = 0.035).

Conclusion

The AERP neural response characteristics of glioma patients during propofol sedation were associated with preoperative cognitive performance, which might be a potential neurophysiological indicator for monitoring perioperative cognitive function, especially theta-ERSP.

SEOM-GEINO clinical guidelines for grade 2 gliomas (2023)

The 2021 World Health Organization (WHO) classification has updated the definition of grade 2 gliomas and the presence of isocitrate dehydrogenase (IDH) mutation has been deemed the cornerstone of diagnosis. Though slow-growing and having a low proliferative index, grade 2 gliomas are incurable by surgery and complementary treatments are vital to improving prognosis. This guideline provides recommendations on the multidisciplinary treatment of grade 2 astrocytomas and oligodendrogliomas based on the best evidence available.

A Novel Mitochondrial-Related Gene Signature for the Prediction of Prognosis and Therapeutic Efficacy in Lower-Grade Glioma

Lower-grade glioma (LGG) is a common primary brain tumor with a highly heterogeneous clinical presentation, and its prognosis cannot be accurately predicted by current histopathology. It has been found that mitochondria play an important role in hypoxia, angiogenesis, and energy metabolism in glioma, and mitochondrial function may have an important impact on LGG prognosis. The goal of this study was to develop a novel prognostic model based on Mitochondrial-related genes (MRGs). We first analyzed the somatic alterations profiles of MRGs in patients with LGG and found that somatic alterations were common in LGG and correlated with prognosis. Using RNA-seq data from TCGA and CGGA, 12 prognosis-related MRGs were identified to construct a mitochondrial activation score (MiAS) model by combining univariate regression and LASSO regression analysis. The model and nomogram were evaluated using the area under the ROC curve with AUC = 0.910. The model was closely correlated with the clinical characteristics of LGG patients and performed well in predicting the prognosis of LGG patients with significantly shorter overall survival (OS) time in the high-MiAS group. GSVA and GSEA results showed that oxidative stress, pro-cancer, and immune-related pathways were significantly enriched in the high-MiAS group. CIBERSORT results showed that MiAS was significantly associated with immune cell infiltration in LGG. Macrophage M1 and follicular helper T cells had increased infiltration in the high-MiAS group. TIDE predicted a better immunotherapy outcome in patients in the low-MiAS group. Finally, using data from the CTRPv2 and GDSC2 datasets to assess chemotherapy response in LGG, it was predicted that the chemotherapeutic agents AZD6482, MG-132, and PLX-4720 might be potential agents for patients in the high-MiAS group of LGG. In addition, we performed in vitro experiments and found that knockdown of OCIAD2 expression reduced the abilities of glioma cells to proliferate, migrate, and invade. In contrast, overexpression of OCIAD2 enhanced these abilities of glioma cells. This study found that MRGs were correlated with LGG patient prognosis, which is expected to provide new treatment strategies for LGG patients with different MiAS.

Variable screening and model construction for prognosis of elderly patients with lower-grade gliomas based on LASSO-Cox regression: a population-based cohort study

Background

This study aimed to identify prognostic factors for survival and develop a prognostic nomogram to predict the survival probability of elderly patients with lower-grade gliomas (LGGs).

Methods

Elderly patients with histologically confirmed LGG were recruited from the Surveillance, Epidemiology, and End Results (SEER) database. These individuals were randomly allocated to the training and validation cohorts at a 2:1 ratio. First, Kaplan-Meier survival analysis and subgroup analysis were performed. Second, variable screening of all 13 variables and a comparison of predictive models based on full Cox regression and LASSO-Cox regression analyses were performed, and the key variables in the optimal model were selected to construct prognostic nomograms for OS and CSS. Finally, a risk stratification system and a web-based dynamic nomogram were constructed.

Results

A total of 2307 elderly patients included 1220 males and 1087 females, with a median age of 72 years and a mean age of 73.30 ± 6.22 years. Among them, 520 patients (22.5%) had Grade 2 gliomas, and 1787 (77.5%) had Grade 3 gliomas. Multivariate Cox regression analysis revealed four independent prognostic factors (age, WHO grade, surgery, and chemotherapy) that were used to construct the full Cox model. In addition, LASSO-Cox regression analysis revealed five prognostic factors (age, WHO grade, surgery, radiotherapy, and chemotherapy), and a LASSO model was constructed. A comparison of the two models revealed that the LASSO model with five variables had better predictive performance than the full Cox model with four variables. Ultimately, five key variables based on LASSO-Cox regression were utilized to develop prognostic nomograms for predicting the 1-, 2-, and 5-year OS and CSS rates. The nomograms exhibited relatively good predictive ability and clinical utility. Moreover, the risk stratification system based on the nomograms effectively divided patients into low-risk and high-risk subgroups.

Conclusion

Variable screening based on LASSO-Cox regression was used to determine the optimal prediction model in this study. Prognostic nomograms could serve as practical tools for predicting survival probabilities, categorizing these patients into different mortality risk subgroups, and developing personalized decision-making strategies for elderly patients with LGGs. Moreover, the web-based dynamic nomogram could facilitate its use in the clinic.

Prediction of Glioma enhancement pattern using a MRI radiomics-based model

Contrast-MRI scans carry risks associated with the chemical contrast agents. Accurate prediction of enhancement pattern of gliomas has potential in avoiding contrast agent administration to patients. This study aimed to develop a machine learning radiomics model that can accurately predict enhancement pattern of gliomas based on T2 fluid attenuated inversion recovery images. A total of 385 cases of pathologically-proven glioma were retrospectively collected with preoperative magnetic resonance T2 fluid attenuated inversion recovery images, which were divided into enhancing and non-enhancing groups. Predictive radiomics models based on machine learning with 6 different classifiers were established in the training cohort (n = 201), and tested both in the internal validation cohort (n = 85) and the external validation cohort (n = 99). Receiver-operator characteristic curve was used to assess the predictive performance of these radiomics models. This study demonstrated that the radiomics model comprising of 15 features using the Gaussian process as a classifier had the highest predictive performance in both the training cohort and the internal validation cohort, with the area under the curve being 0.88 and 0.80, respectively. This model showed an area under the curve, sensitivity, specificity, positive predictive value and negative predictive value of 0.81, 0.98, 0.61, 0.82, 0.76 and 0.96, respectively, in the external validation cohort. This study suggests that the T2-FLAIR-based machine learning radiomics model can accurately predict enhancement pattern of glioma.

Low-Grade Gliomas: A New Mutation, New Targeted Therapy, and Many Questions

The discovery in 2008 that many adult gliomas harbor a hitherto unknown mutation in the metabolic gene isocitrate dehydrogenase (IDH) initiated revolutionary advances in our understanding of the biology, and correspondingly our classification, of gliomas. IDH mutations are found in most nonglioblastoma adult gliomas and portend a better prognosis. Massive efforts have unraveled many of the pleiotropic cellular effects of these mutations and spawned several lines of investigation to target the effect to therapeutic benefit. In this article are reviewed the implications of the IDH mutation in gliomas, in particular focusing on recent studies that have culminated in a rare positive phase 3 trial in these generally refractory tumors.

The Potential Significance of the EMILIN3 Gene in Augmenting the Aggressiveness of Low-Grade Gliomas is Noteworthy

Purpose

Low-grade gliomas (LGG) are common brain tumors with high mortality rates. Cancer cell invasion is a significant factor in tumor metastasis. Novel biomarkers are urgently needed to predict LGG prognosis effectively.

Methods

The data for LGG were obtained from the Bioinformatics database. A consensus clustering analysis was performed to identify molecular subtypes linked with invasion in LGG. Differential expression analysis was performed to identify differentially expressed genes (DEGs) between the identified clusters. Enrichment analyses were then conducted to explore the function for DEGs. Prognostic signatures were placed, and their predictive power was assessed. Furthermore, the invasion-related prognostic signature was validated using the CGGA dataset. Subsequently, clinical specimens were procured in order to validate the expression levels of the distinct genes examined in this research, and to further explore the impact of these genes on the glioma cell line LN229 and HS-683.

Results

Two invasion-related molecular subtypes of LGG were identified, and we sifted 163 DEGs between them. The enrichment analyses indicated that DEGs are mainly related to pattern specification process. Subsequently, 10 signature genes (IGF2BP2, SRY, CHI3L1, IGF2BP3, MEOX2, ABCC3, HOXC4, OTP, METTL7B, and EMILIN3) were sifted out to construct a risk model. Besides, the survival (OS) in the high-risk group was lower. The performance of the risk model was verified. Furthermore, a highly reliable nomogram was generated. Cellular experiments revealed the ability to promote cell viability, value-addedness, migratory ability, invasive ability, and colony-forming ability of the glioma cell line LN229 and HS-683. The qRT-PCR analysis of clinical glioma samples showed that these 10 genes were expressed at higher levels in high-grade gliomas than in low-grade gliomas, suggesting that these genes are associated with poor prognosis of gliomas.

Conclusion

Our study sifted out ten invasion-related biomarkers of LGG, providing a reference for treatments and prognostic prediction in LGG.

The 2021 World Health Organization Central Nervous System Tumor Classification: The Spectrum of Diffuse Gliomas

The 2021 edition of the World Health Organization (WHO) classification of central nervous system tumors introduces significant revisions across various tumor types. These updates, encompassing changes in diagnostic techniques, genomic integration, terminology, and grading, are crucial for radiologists, who play a critical role in interpreting brain tumor imaging. Such changes impact the diagnosis and management of nearly all central nervous system tumor categories, including the reclassification, addition, and removal of specific tumor entities. Given their pivotal role in patient care, radiologists must remain conversant with these revisions to effectively contribute to multidisciplinary tumor boards and collaborate with peers in neuro-oncology, neurosurgery, radiation oncology, and neuropathology. This knowledge is essential not only for accurate diagnosis and staging, but also for understanding the molecular and genetic underpinnings of tumors, which can influence treatment decisions and prognostication. This review, therefore, focuses on the most pertinent updates concerning the classification of adult diffuse gliomas, highlighting the aspects most relevant to radiological practice. Emphasis is placed on the implications of new genetic information on tumor behavior and imaging findings, providing necessary tools to stay abreast of advancements in the field. This comprehensive overview aims to enhance the radiologist's ability to integrate new WHO classification criteria into everyday practice, ultimately improving patient outcomes through informed and precise imaging assessments.

Survival Analysis of Patients Undergoing Intraoperative Contrast-enhanced Ultrasound in the Surgical Treatment of Malignant Glioma

OBJECTIVE

Complete resection of malignant gliomas is often challenging. Our previous study indicated that intraoperative contrast-enhanced ultrasound (ICEUS) could aid in the detection of residual tumor remnants and the total removal of brain lesions. This study aimed to investigate the survival rates of patients undergoing resection with or without the use of ICEUS and to assess the impact of ICEUS on the prognosis of patients with malignant glioma.

METHODS

A total of 64 patients diagnosed with malignant glioma (WHO grade HI and IV) who underwent surgery between 2012 and 2018 were included. Among them, 29 patients received ICEUS. The effects of ICEUS on overall survival (OS) and progression-free survival (PFS) of patients were evaluated. A quantitative analysis was performed to compare ICEUS parameters between gliomas and the surrounding tissues.

RESULTS

The ICEUS group showed better survival rates both in OS and PFS than the control group. The univariate analysis revealed that age, pathology and ICEUS were significant prognostic factors for PFS, with only age being a significant prognostic factor for OS. In multivariate analysis, age and ICEUS were significant prognostic factors for both OS and PFS. The quantitative analysis showed that the intensity and transit time of microbubbles reaching the tumors were significantly different from those of microbubbles reaching the surrounding tissue.

CONCLUSION

ICEUS facilitates the identification of residual tumors. Age and ICEUS are prognostic factors for malignant glioma surgery, and use of ICEUS offers a better prognosis for patients with malignant glioma.

Identification of a novel disulfideptosis-related gene signature for prognostic implication in lower-grade gliomas

Lower-grade gliomas (GBMLGG) are common, fatal, and difficult-to-treat cancers. The current treatment choices have impressive efficacy constraints. As a result, the development of effective treatments and the identification of new therapeutic targets are urgent requirements. Disulfide metabolism is the cause of the non-apoptotic programmed cell death known as disulfideptosis, which was only recently discovered. The mRNA expression data and related clinical information of GBMLGG patients downloaded from public databases were used in this study to investigate the prognostic significance of genes involved in disulfideptosis. In the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohort, our findings showed that many disulfidptosis-related genes were expressed differently in normal and GBMLGG tissues. It was discovered that IQ motif-containing GTPase-activating protein 1 (IQGAP1) is a key gene that influences the outcome of GBMLGG. Besides, a nomogram model was built to foresee the visualization of GBMLGG patients. In addition, in vivo and in vitro validation of IQGAP1's cancer-promoting function was done. In conclusion, we discovered a gene signature associated with disulfideptosis that can effectively predict OS in GBMLGG patients. As a result, treating disulfideptosis may be a viable alternative for GBMLGG patients.

Complement and coagulation cascades are associated with prognosis and the immune microenvironment of lower-grade glioma

Background

Abnormal coagulation is a common feature of glioma. There is a strong correlation between coagulation and the complement system, named complement and coagulation cascades (CCC). However, the role of CCC genes in lower-grade glioma (LGG) remains unclear. This study aimed to investigate the role of CCC genes in LGG.

Methods

In total, 5,628 differential expressed genes were identified between 498 LGG tissues from The Cancer Genome Atlas (TCGA) and 207 normal brain tissues from Genotype-Tissue Expression Project (GTEx). Among them, 20 overlapped CCC genes were identified as differentially expressed CCC genes. Then, comprehensive bioinformatics analysis was used to investigate the role of CCC genes in LGG; 271 LGG tissues from the Chinese Glioma Genome Atlas (CGGA) were used as the validation dataset. Cell Counting Kit-8 (CCK8) proliferation assay, colony formation assay, and wound healing assay were conducted to explore the anti-glioma effect of the sensitive drugs we predicted.

Results

We constructed a risk signature consisting of six CCC genes, including F2R, SERPINA1, TFPI, C1QC, C2, and C3AR1. The CCC gene-based risk signature could accurately predict the prognosis of patients with LGG. In addition, we found that the JAK-STAT, NOD-like receptor, Notch, PI3K-Akt, and Rap1 signaling pathways might be activated and had crosstalk with CCC in the high-risk group. Our findings analyses demonstrated that samples in high- and low-risk groups had different immune landscapes. Moreover, patients in the high-risk group might have greater resistance to immunotherapy. We validated the accuracy of the risk signature in predicting immunotherapy response in two public immunotherapy cohorts, GSE135222 and GSE78220. By means of oncoPredict, MG-132, BMS-536924, PLX-4720, and AZD6482 were identified as potential sensitive drugs for high-risk patients, of which MG-132 was particularly recommended for high-risk patients. We performed in vitro experiments to explore the anti-glioma effect of MG-132, and the results demonstrated MG-132 could inhibit the proliferation and migration of glioma cells.

Conclusions

Our findings show that CCC genes are associated with the prognosis and immune infiltration of LGG and provide possible immunotherapeutic and novel chemotherapeutic strategies for patients with LGG based on the risk signature.

[Predicting cerebral glioma enhancement pattern using a machine learning-based magnetic resonance imaging radiomics model]

OBJECTIVE

To establish a machine learning radiomics model that can accurately predict MRI enhancement patterns of glioma based on T2 fluid attenuated inversion recovery (T2-FLAIR) images for optimizing the workflow of magnetic resonance imaging (MRI) examinations of glioma patients.

METHODS

We retrospectively collected preoperative MR T2-FLAIR images from 385 patients with pathologically confirmed glioma, who were divided into enhancing and non-enhancing groups according to the enhancement pattern. Predictive radiomics models were established using Gaussian Process, Linear Regression, Linear Regression-Least absolute shrinkage and selection operator, Support Vector Machine, Linear Discriminant Analysis or Naive Bayes as the classifiers in the training cohort (n=201)and tested both in the internal (n=85) and external validation cohorts (n=99). The receiver-operating characteristic curve was used to assess the predictive performance of the models.

RESULTS

The predictive model constructed based on 15 radiomics features using Gaussian Process as the classifier had the best predictive performance in both the training cohort and the internal validation cohort, with areas under the curve (AUC) of 0.88 (95% CI: 0.81-0.94) and 0.80 (95% CI: 0.71-0.88), respectively. In the external validation cohort, the model showed an AUC of 0.81 (95% CI: 0.71-0.90) with sensitivity, specificity, positive predictive value and negative predictive value of 0.98, 0.61, 0.76 and 0.96, respectively.

CONCLUSION

The T2-FLAIR-based machine learning radiomics model can accurately predict the enhancement pattern of gliomas on MRI.

Development of an m6A-Related lncRNAs Signature Predicts Tumor Stemness and Prognosis for Low-Grade Glioma Patients

Background

Growing evidence has revealed that m6A modification of long noncoding RNAs (lncRNAs) dynamically controls tumor stemness and tumorigenesis-related processes. However, the prognostic significance of m6A-related lncRNAs and their associations with stemness in low-grade glioma (LGG) remain to be clarified.

Methods

A multicenter transcriptome analysis of lncRNA expression in 1,247 LGG samples was performed in this study. The stemness landscape of LGG tumors was presented and associations with clinical features were revealed. The m6A-related lncRNAs were identified between stemness groups and were further prioritized via least absolute shrinkage and selection operator Cox regression analysis. A risk score model based on m6A-related lncRNAs was constructed and validated in external LGG datasets.

Results

Based on the expression of LINC02984, PFKP-DT, and CRNDE, a risk model and nomogram were constructed; they successfully predicted the survival of patients and were extended to external datasets. Significant correlations were observed between the risk score and tumor stemness. Moreover, patients in different risk groups exhibited distinct tumor immune microenvironments and immune signatures. We finally provided several potential compounds suitable for specific risk groups, which may aid in LGG treatment.

Conclusions

This novel signature presents noteworthy value in the prediction of prognosis and stemness status for LGG patients and will foster future research on the development of clinical regimens.

Tumor Volume Growth Rates and Doubling Times during Active Surveillance of IDH-mutant Low-Grade Glioma

PURPOSE

Isocitrate dehydrogenase-mutant (IDH-mt) gliomas are incurable primary brain tumors characterized by a slow-growing phase over several years followed by a rapid-growing malignant phase. We hypothesized that tumor volume growth rate (TVGR) on MRI may act as an earlier measure of clinical benefit during the active surveillance period.

EXPERIMENTAL DESIGN

We integrated three-dimensional volumetric measurements with clinical, radiologic, and molecular data in a retrospective cohort of IDH-mt gliomas that were observed after surgical resection in order to understand tumor growth kinetics and the impact of molecular genetics.

RESULTS

Using log-linear mixed modeling, the entire cohort (n = 128) had a continuous %TVGR per 6 months of 10.46% [95% confidence interval (CI), 9.11%-11.83%] and a doubling time of 3.5 years (95% CI, 3.10-3.98). High molecular grade IDH-mt gliomas, defined by the presence of homozygous deletion of CDKN2A/B, had %TVGR per 6 months of 19.17% (95% CI, 15.57%-22.89%) which was significantly different from low molecular grade IDH-mt gliomas with a growth rate per 6 months of 9.54% (95% CI, 7.32%-11.80%; P < 0.0001). Using joint modeling to comodel the longitudinal course of TVGR and overall survival, we found each one natural logarithm tumor volume increase resulted in more than a 3-fold increase in risk of death (HR = 3.83; 95% CI, 2.32-6.30; P < 0.0001).

CONCLUSIONS

TVGR may be used as an earlier measure of clinical benefit and correlates well with the WHO 2021 molecular classification of gliomas and survival. Incorporation of TVGR as a surrogate endpoint into future prospective studies of IDH-mt gliomas may accelerate drug development.

Lower-grade gliomas surgery guided by GRPR-targeting PET/NIR dual-modality image probe: a prospective and single-arm clinical trial

Purpose: Lower-grade gliomas (LGGs) are a group of infiltrative growing glial brain tumors characterized by intricate intratumoral heterogeneity and subtle visual appearance differences from non-tumor tissue, which can lead to errors in pathologic tissue sampling. Although 5-ALA fluorescence has been an essential method for visualizing gliomas during surgery, its effectiveness is limited in the case of LGGs due to low sensitivity. Therefore, we developed a novel PET/NIR dual-modality image probe targeting gastrin-releasing peptide receptor (GRPR) in glioma cells to enhance tumor visualization and improve the accuracy of sampling. Methods: A prospective, non-randomized, single-center feasibility clinical trial (NCT03407781) was conducted in the referral center from October 21, 2016, to August 17, 2018. Consecutive enrollment included patients suspected of having LGGs and considered suitable candidates for surgical removal. Group 1 comprised ten patients who underwent preoperative 68Ga-IRDye800CW-BBN PET/MRI assessment followed by intraoperative fluorescence-guided surgery. Group 2 included 42 patients who underwent IRDye800CW-BBN fluorescence-guided surgery. The primary endpoints were the predictive value of preoperative PET imaging for intraoperative fluorescence and the sensitivity and specificity of fluorescence-guided sampling. Results: Thirty-nine patients were included in the in-depth analysis of endpoints, with 25 (64.1%) exhibiting visible fluorescence, while 14 (35.9%) did not. The preoperative positive PET uptake exhibited a greater accuracy in predicting intraoperative fluorescence compared to MRI enhancement (100% [10/10] vs. 87.2% [34/39]). A total of 125 samples were harvested during surgery. Compared with pathology, subjective fluorescence intensity showed a sensitivity of 88.6% and a specificity of 88.2% in identifying WHO grade III samples. For WHO grade II samples, the sensitivity and specificity of fluorescence were 54.7% and 88.2%, respectively. Conclusion: This study has demonstrated the feasibility of the novel dual-modality imaging technique for integrated pre- and intraoperative targeted imaging via the same molecular receptor in surgeries for LGGs. The PET/NIR dual-modality probe exhibits promise for preoperative surgical planning in fluorescence-guided surgery and provides greater accuracy in guiding tumor sampling compared to 5-ALA in patients with LGGs.

Cuproptosis-related gene-located DNA methylation in lower-grade glioma: Prognosis and tumor microenvironment

Cuproptosis a novel copper-dependent cell death modality, plays a crucial part in the oncogenesis, progression and prognosis of tumors. However, the relationships among DNA-methylation located in cuproptosis-related genes (CRGs), overall survival (OS) and the tumor microenvironment remain undefined. In this study, we systematically assessed the prognostic value of CRG-located DNA-methylation for lower-grade glioma (LGG). Clinical and molecular data were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We employed Cox hazard regression to examine the associations between CRG-located DNA-methylation and OS, leading to the development of a prognostic signature. Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses were utilized to gauge the accuracy of the signature. Gene Set Enrichment Analysis (GSEA) was applied to uncover potential biological functions of differentially expressed genes between high- and low-risk groups. A three CRG-located DNA-methylation prognostic signature was established based on TCGA database and validated in GEO dataset. The 1-year, 3-year, and 5-year area under the curve (AUC) of ROC curves in the TCGA dataset were 0.884, 0.888, and 0.859 while those in the GEO dataset were 0.943, 0.761 and 0.725, respectively. Cox-regression-analyses revealed the risk signature as an independent risk factor for LGG patients. Immunogenomic profiling suggested that the signature was associated with immune infiltration level and immune checkpoints. Functional enrichment analysis indicated differential enrichment in cell differentiation in the hindbrain, ECM receptor interactions, glycolysis and reactive oxygen species pathway across different groups. We developed and verified a novel CRG-located DNA-methylation signature to predict the prognosis in LGG patients. Our findings emphasize the potential clinical implications of CRG-located DNA-methylation indicating that it may serve as a promising therapeutic target for LGG patients.

Anatomical changes in resection cavity during brain radiotherapy

BACKGROUND AND PURPOSE

Brain tumors are in general treated with a maximal safe resection followed by radiotherapy of remaining tumor including the resection cavity (RC) and chemotherapy. Anatomical changes of the RC during radiotherapy can have impact on the coverage of the target volume. The aim of the current study was to quantify the potential changes of the RC and to identify risk factors for RC changes.

MATERIALS AND METHODS

Sixteen patients treated with pencil beam scanning proton therapy between October 2019 and April 2020 were retrospectively analyzed. The RC was delineated on pre-treatment computed tomography (CT) and magnetic resonance imaging, and weekly CT-scans during treatment. Isotropic expansions were applied to the pre-treatment RC (1-5 mm). The percentage of volume of the RC during treatment within the expanded pre-treatment volumes was quantified. Potential risk factors (volume of RC, time interval surgery-radiotherapy and relationship of RC to the ventricles) were evaluated using Spearman's rank correlation coefficient.

RESULTS

The average variation in relative RC volume during treatment was 26.1% (SD 34.6%). An expansion of 4 mm was required to cover > 95% of the RC volume in > 90% of patients. There was a significant relationship between the absolute volume of the pre-treatment RC and the volume changes during treatment (Spearman's ρ = - 0.644; p = 0.007).

CONCLUSION

RCs are dynamic after surgery. Potentially, an additional margin in brain cancer patients with an RC should be considered, to avoid insufficient target coverage. Future research on local recurrence patterns is recommended.

Integrated machine learning survival framework develops a prognostic model based on inter-crosstalk definition of mitochondrial function and cell death patterns in a large multicenter cohort for lower-grade glioma

BACKGROUND

Lower-grade glioma (LGG) is a highly heterogeneous disease that presents challenges in accurately predicting patient prognosis. Mitochondria play a central role in the energy metabolism of eukaryotic cells and can influence cell death mechanisms, which are critical in tumorigenesis and progression. However, the prognostic significance of the interplay between mitochondrial function and cell death in LGG requires further investigation.

METHODS

We employed a robust computational framework to investigate the relationship between mitochondrial function and 18 cell death patterns in a cohort of 1467 LGG patients from six multicenter cohorts worldwide. A total of 10 commonly used machine learning algorithms were collected and subsequently combined into 101 unique combinations. Ultimately, we devised the mitochondria-associated programmed cell death index (mtPCDI) using machine learning models that exhibited optimal performance.

RESULTS

The mtPCDI, generated by combining 18 highly influential genes, demonstrated strong predictive performance for prognosis in LGG patients. Biologically, mtPCDI exhibited a significant correlation with immune and metabolic signatures. The high mtPCDI group exhibited enriched metabolic pathways and a heightened immune activity profile. Of particular importance, our mtPCDI maintains its status as the most potent prognostic indicator even following adjustment for potential confounding factors, surpassing established clinical models in predictive strength.

CONCLUSION

Our utilization of a robust machine learning framework highlights the significant potential of mtPCDI in providing personalized risk assessment and tailored recommendations for metabolic and immunotherapy interventions for individuals diagnosed with LGG. Of particular significance, the signature features highly influential genes that present further prospects for future investigations into the role of PCD within mitochondrial function.

Characterization and clinical implications of different malignant transformation patterns in diffuse low-grade gliomas

Malignant transformation (MT) of low-grade gliomas (LGGs) to a higher-grade variant seems inevitable, yet it remains unclear which LGG patients will progress to grade 3 or even directly to grade 4 after receiving a long course of treatment. To elucidate this, we conducted a retrospective cohort study based on 229 adults with recurrent LGG. Our study aimed to disclose the characteristics of different MT patterns and to build predictive models for patients with LGG. Patients were allocated into group 2-2 (n = 81, 35.4%), group 2-3 (n = 91, 39.7%), and group 2-4 (n = 57, 24.9%), based on their MT patterns. Patients who underwent MT showed lower Karnofsky performance scale (KPS) scores, larger tumor sizes, smaller extents of resection (EOR), higher Ki-67 indices, lower rates of 1p/19q codeletion, but higher rates of subventricular involvement, radiotherapy, chemotherapy, astrocytoma, and post-progression enhancement (PPE) compared with those in group 2-2 (p < 0.01). On multivariate logistic regression, 1p/19q codeletion, Ki-67 index, radiotherapy, EOR, and KPS score were independently associated with MT (p < 0.05). Survival analyses demonstrated that patients in group 2-2 had the longest survival, followed by group 2-3 and then group 2-4 (p < 0.0001). Based on these independent parameters, we constructed a nomogram model that exhibited superior potential (sensitivity: 0.864, specificity: 0.814, and accuracy: 0.843) compared with PPE in early prediction of MT. Combining the factors of 1p/19q codeletion, Ki-67 index, radiotherapy, EOR, and KPS score that were presented at initial diagnosis could precisely forecast the subsequent MT patterns of patients with LGG.

Exploration of 2D and 3D-QSAR analysis and docking studies for novel dihydropteridone derivatives as promising therapeutic agents targeting glioblastoma

Background: Dihydropteridone derivatives represent a novel class of PLK1 inhibitors, exhibiting promising anticancer activity and potential as chemotherapeutic drugs for glioblastoma. Objective: The aim of this study is to develop 2D and 3D-QSAR models to validate the anticancer activity of dihydropteridone derivatives and identify optimal structural characteristics for the design of new therapeutic agents. Methods: The Heuristic method (HM) was employed to construct a 2D-linear QSAR model, while the gene expression programming (GEP) algorithm was utilized to develop a 2D-nonlinear QSAR model. Additionally, the CoMSIA approach was introduced to investigate the impact of drug structure on activity. A total of 200 novel anti-glioma dihydropteridone compounds were designed, and their activity levels were predicted using chemical descriptors and molecular field maps. The compounds with the highest activity were subjected to molecular docking to confirm their binding affinity. Results: Within the analytical purview, the coefficient of determination (R2) for the HM linear model is elucidated at 0.6682, accompanied by an R2 cv of 0.5669 and a residual sum of squares (S2) of 0.0199. The GEP nonlinear model delineates coefficients of determination for the training and validation sets at 0.79 and 0.76, respectively. Empirical modeling outcomes underscore the preeminence of the 3D-QSAR model, succeeded by the GEP nonlinear model, whilst the HM linear model manifested suboptimal efficacy. The 3D paradigm evinced an exemplary fit, characterized by formidable Q2 (0.628) and R2 (0.928) values, complemented by an impressive F-value (12.194) and a minimized standard error of estimate (SEE) at 0.160. The most significant molecular descriptor in the 2D model, which included six descriptors, was identified as "Min exchange energy for a C-N bond" (MECN). By combining the MECN descriptor with the hydrophobic field, suggestions for the creation of novel medications were generated. This led to the identification of compound 21E.153, a novel dihydropteridone derivative, which exhibited outstanding antitumor properties and docking capabilities. Conclusion: The development of 2D and 3D-QSAR models, along with the innovative integration of contour maps and molecular descriptors, offer novel concepts and techniques for the design of glioblastoma chemotherapeutic agents.

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.

Electroencephalography characteristics of patients with supratentorial glioma in different consciousness states induced by propofol

Gliomas are the most common primary intracranial malignant tumors. Some of these patients exhibit previously clinically undetected neurological deficits after sedation. The absence of neurophysiological evidence for this phenomenon limits the use of time-sensitive monitoring methods. The study aims to compare differences between glioma patients under sedation and those without intracranial lesions by comparing their EEG features. Twenty-one patients without intracranial tumors and 21 with frontal lobe supratentorial gliomas were enrolled. The EEG power spectrum of the glioma group was comparable to that of the control group for both sides of the brain (P>0.05 for all frequencies). Compared with those without intracranial lesions, the weighted phase lag index (wPLI) in the alpha and beta bands on the non-occupied side decreased. Glioma patients had weaker functional connectivity during sedation than patients without intracranial lesions, manifesting as reduced functional connectivity on the non-occupied side.

Molecular subtypes based on centrosome-related genes can predict prognosis and therapeutic responsiveness in patients with low-grade gliomas

Background

Abnormalities in centrosome regulatory genes can induce chromosome instability, cell differentiation errors, and tumorigenesis. However, a limited number of comprehensive analyses of centrosome-related genes have been performed in low-grade gliomas (LGG).

Methods

LGG data were extracted from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. The ConsensusClusterPlus” R package was used for unsupervised clustering. We constructed a centrosome-related genes (CRGs) signature using a random forest model, lasso Cox model, and multivariate Cox model, and quantified the centrosome-related risk score (centS). The prognostic prediction efficacy of centS was evaluated using a Receiver Operating Characteristic (ROC) curve. Immune cell infiltration and genomic mutational landscapes were evaluated using the ESTIMATE algorithm, single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm, and “maftools” R package, respectively. Differences in clinical features, isocitrate dehydrogenase (IDH) mutation, 1p19q codeletion, O6-methylguanine-DNA methyltransferase promoter (MGMTp) methylation, and response to antitumor therapy between the high- and low-centS groups were explored. “pRRophetic” R packages were used for temozolomide (TMZ) sensitivity analysis. qRT-PCR verified the differential expression of the centrosomal gene team, the core of which is CEP135, between LGG cells and normal cells.

Results

Two distinct CRG-based clusters were identified using consensus unsupervised clustering analysis. The prognosis, biological characteristics, and immune cell infiltration of the two clusters differed significantly. A well-performing centS signature was developed to predict the prognosis of patients with LGG based on 12 potential CRGs. We found that patients in the high-centS group showed poorer prognosis and lower proportion of IDH mutation and 1p19q codeletion compared to those in the low-centS group. Furthermore, patients in the high-centS group showed higher sensitivity to TMZ, higher tumor mutation burden, and immune cell infiltration. Finally, we identified a centrosomal gene team whose core was CEP135, and verified their differential expression between LGG cells and normal glial cells.

Conclusion

Our findings reveal a novel centrosome-related signature for predicting the prognosis and therapeutic responsiveness of patients with LGG. This may be helpful for the accurate clinical treatment of LGG.

Global survival trends for brain tumors, by histology: analysis of individual records for 556,237 adults diagnosed in 59 countries during 2000-2014 (CONCORD-3)

BACKGROUND

Survival is a key metric of the effectiveness of a health system in managing cancer. We set out to provide a comprehensive examination of worldwide variation and trends in survival from brain tumors in adults, by histology.

METHODS

We analyzed individual data for adults (15-99 years) diagnosed with a brain tumor (ICD-O-3 topography code C71) during 2000-2014, regardless of tumor behavior. Data underwent a 3-phase quality control as part of CONCORD-3. We estimated net survival for 11 histology groups, using the unbiased nonparametric Pohar Perme estimator.

RESULTS

The study included 556,237 adults. In 2010-2014, the global range in age-standardized 5-year net survival for the most common sub-types was broad: in the range 20%-38% for diffuse and anaplastic astrocytoma, from 4% to 17% for glioblastoma, and between 32% and 69% for oligodendroglioma. For patients with glioblastoma, the largest gains in survival occurred between 2000-2004 and 2005-2009. These improvements were more noticeable among adults diagnosed aged 40-70 years than among younger adults.

CONCLUSIONS

To the best of our knowledge, this study provides the largest account to date of global trends in population-based survival for brain tumors by histology in adults. We have highlighted remarkable gains in 5-year survival from glioblastoma since 2005, providing large-scale empirical evidence on the uptake of chemoradiation at population level. Worldwide, survival improvements have been extensive, but some countries still lag behind. Our findings may help clinicians involved in national and international tumor pathway boards to promote initiatives aimed at more extensive implementation of clinical guidelines.

DNA Methylation and Histone Modification in Low-Grade Gliomas: Current Understanding and Potential Clinical Targets

Gliomas, the most common type of malignant primary brain tumor, were conventionally classified through WHO Grades I-IV (now 1-4), with low-grade gliomas being entities belonging to Grades 1 or 2. While the focus of the WHO Classification for Central Nervous System (CNS) tumors had historically been on histopathological attributes, the recently released fifth edition of the classification (WHO CNS5) characterizes brain tumors, including gliomas, using an integration of histological and molecular features, including their epigenetic changes such as histone methylation, DNA methylation, and histone acetylation, which are increasingly being used for the classification of low-grade gliomas. This review describes the current understanding of the role of DNA methylation, demethylation, and histone modification in pathogenesis, clinical behavior, and outcomes of brain tumors, in particular of low-grade gliomas. The review also highlights potential diagnostic and/or therapeutic targets in associated cellular biomolecules, structures, and processes. Targeting of MGMT promoter methylation, TET-hTDG-BER pathway, association of G-CIMP with key gene mutations, PARP inhibition, IDH and 2-HG-associated processes, TERT mutation and ARL9-associated pathways, DNA Methyltransferase (DNMT) inhibition, Histone Deacetylase (HDAC) inhibition, BET inhibition, CpG site DNA methylation signatures, along with others, present exciting avenues for translational research. This review also summarizes the current clinical trial landscape associated with the therapeutic utility of epigenetics in low-grade gliomas. Much of the evidence currently remains restricted to preclinical studies, warranting further investigation to demonstrate true clinical utility.

Isocitrate dehydrogenase (IDH) mutant gliomas: A Society for Neuro-Oncology (SNO) consensus review on diagnosis, management, and future directions

Isocitrate dehydrogenase (IDH) mutant gliomas are the most common adult, malignant primary brain tumors diagnosed in patients younger than 50, constituting an important cause of morbidity and mortality. In recent years, there has been significant progress in understanding the molecular pathogenesis and biology of these tumors, sparking multiple efforts to improve their diagnosis and treatment. In this consensus review from the Society for Neuro-Oncology (SNO), the current diagnosis and management of IDH-mutant gliomas will be discussed. In addition, novel therapies, such as targeted molecular therapies and immunotherapies, will be reviewed. Current challenges and future directions for research will be discussed.

Prognostic value of γ‐aminobutyric acidergic synapse-associated signature for lower-grade gliomas

Background

Synapse-associated proteins (SAPs) play important roles in central nervous system (CNS) tumors. Recent studies have reported that γ-aminobutyric acidergic (GABAergic) synapses also play critical roles in the development of gliomas. However, biomarkers of GABAergic synapses in low-grade gliomas (LGGs) have not yet been reported.

Methods

mRNA data from normal brain tissue and gliomas were obtained from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases, respectively. A validation dataset was also obtained from the Chinese Glioma Genome Atlas (CGGA) database. The expression patterns of GABAergic synapse-related genes (GSRGs) were evaluated with difference analysis in LGGs. Then, a GABAergic synapse-related risk signature (GSRS) was constructed with least absolute shrinkage and selection operator (LASSO) Cox regression analysis. According to the expression value and coefficients of identified GSRGs, the risk scores of all LGG samples were calculated. Univariate and multivariate Cox regression analyses were conducted to evaluate related risk scores for prognostic ability. Correlations between characteristics of the tumor microenvironment (TME) and risk scores were explored with single-sample gene set enrichment analysis (ssGSEA) and immunity profiles in LGGs. The GSRS-related pathways were investigated by gene set variation analysis (GSVA). Real-time PCR and the Human Protein Atlas (HPA) database were applied to explore related expression of hub genes selected in the GSRS.

Results

Compared with normal brain samples, 25 genes of 31 GSRGs were differentially expressed in LGG samples. A constructed five-gene GSRS was related to clinicopathological features and prognosis of LGGs by the LASSO algorithm. It was shown that the risk score level was positively related to the infiltrating level of native CD4 T cells and activated dendritic cells. GSVA identified several cancer-related pathways associated with the GSRS, such as P53 pathways and the JAK-STAT signaling pathway. Additionally, CA2, PTEN, OXTR, and SLC6A1 (hub genes identified in the GSRS) were regarded as the potential predictors in LGGs.

Conclusion

A new five-gene GSRS was identified and verified by bioinformatics methods. The GSRS provides a new perspective in LGG that may contribute to more accurate prediction of prognosis of LGGs.

Development of a Hallmark Pathway-Related Gene Signature Associated with Immune Response for Lower Grade Gliomas

Although some biomarkers have been used to predict prognosis of lower-grade gliomas (LGGs), a pathway-related signature associated with immune response has not been developed. A key signaling pathway was determined according to the lowest adjusted p value among 50 hallmark pathways. The least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox analyses were performed to construct a pathway-related gene signature. Somatic mutation, drug sensitivity and prediction of immunotherapy analyses were conducted to reveal the value of this signature in targeted therapies. In this study, an allograft rejection (AR) pathway was considered as a crucial signaling pathway, and we constructed an AR-related five-gene signature, which can independently predict the prognosis of LGGs. High-AR LGG patients had higher tumor mutation burden (TMB), Immunophenscore (IPS), IMmuno-PREdictive Score (IMPRES), T cell-inflamed gene expression profile (GEP) score and MHC I association immunoscore (MIAS) than low-AR patients. Most importantly, our signature can be validated in four immunotherapy cohorts. Furthermore, IC50 values of the six classic chemotherapeutic drugs were significantly elevated in the low-AR group compared with the high-AR group. This signature might be regarded as an underlying biomarker in predicting prognosis for LGGs, possibly providing more therapeutic strategies for future clinical research.

A Bioinformatics-Based Analysis of an Anoikis-Related Gene Signature Predicts the Prognosis of Patients with Low-Grade Gliomas

Low-grade glioma (LGG) is a highly aggressive disease in the skull. On the other hand, anoikis, a specific form of cell death induced by the loss of cell contact with the extracellular matrix, plays a key role in cancer metastasis. In this study, anoikis-related genes (ANRGs) were used to identify LGG subtypes and to construct a prognostic model for LGG patients. In addition, we explored the immune microenvironment and enrichment pathways between different subtypes. We constructed an anoikis-related gene signature using the TCGA (The Cancer Genome Atlas) cohort and investigated the differences between different risk groups in clinical features, mutational landscape, immune cell infiltration (ICI), etc. Kaplan-Meier analysis showed that the characteristics of ANRGs in the high-risk group were associated with poor prognosis in LGG patients. The risk score was identified as an independent prognostic factor. The high-risk group had higher ICI, tumor mutation load (TMB), immune checkpoint gene expression, and therapeutic response to immune checkpoint blockers (ICB). Functional analysis showed that these high-risk and low-risk groups had different immune statuses and drug sensitivity. Risk scores were used together with LGG clinicopathological features to construct a nomogram, and Decision Curve Analysis (DCA) showed that the model could enable patients to benefit from clinical treatment strategies.

N6-methyladenosine-related microRNAs risk model trumps the isocitrate dehydrogenase mutation status as a predictive biomarker for the prognosis and immunotherapy in lower grade gliomas

Aim

Lower grade gliomas [LGGs; World Health Organization (WHO) grades 2 and 3], owing to the heterogeneity of their clinical behavior, present a therapeutic challenge to neurosurgeons. The aim of this study was to explore the N6-methyladenosine (m6A) modification landscape in the LGGs and to develop an m6A-related microRNA (miRNA) risk model to provide new perspectives for the treatment and prognostic assessment of LGGs.

Methods

Messenger RNA (mRNA) and miRNA expression data of LGGs were extracted from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. An m6A-related miRNA risk model was constructed via least absolute shrinkage and selection operator (LASSO), univariate, and multivariate Cox regression analysis. Next, Kaplan-Meier analysis, principal-component analysis (PCA), functional enrichment analysis, immune infiltrate analysis, dynamic nomogram, and drug sensitivity prediction were used to evaluate this risk model.

Results

Firstly, six m6A-related miRNAs with independent prognostic value were selected based on clinical information and used to construct a risk model. Subsequently, compared with low-risk group, LGGs in the high-risk group had a higher m6A writer and reader scores, but a lower eraser score. Moreover, LGGs in the high-risk group had a significantly worse clinical prognosis than those in the low-risk group. Simultaneously, this risk model outperformed other clinicopathological variables in the prognosis prediction of LGGs. Immune infiltrate analysis revealed that the proportion of M2 macrophages, regulatory T (Treg) cells, and the expression levels of exhausted immune response markers were significantly higher in the high-risk group than in the low-risk group. Finally, this study constructed an easy-to-use and free dynamic nomogram to help clinicians use this risk model to aid in diagnosis and prognosis assessment.

Conclusions

This study developed a m6A-related risk model and uncovered two different m6A modification landscapes in LGGs. Moreover, this risk model may provide guidance and help in clinical prognosis assessment and immunotherapy response prediction for LGGs.

Prognostic Factors of Low-Grade Gliomas in Adults

Adult low-grade gliomas are a rare and aggressive pathology of the central nervous system. Some of their characteristics contribute to the patient's life expectancy and to their management. This study aimed to characterize and identify the main prognostic factors of low-grade gliomas. The six-year retrospective study statistically analyzed the demographic, imaging, and morphogenetic characteristics of the patient group through appropriate parameters. Immunohistochemical tests were performed: IDH1, Ki-67, p53, and Nestin, as well as FISH tests on the CDKN2A gene and 1p/19q codeletion. The pathology was prevalent in females, with patients having an average age of 56.31 years. The average tumor volume was 41.61 cm³, producing a midline shift with an average of 7.5 mm. Its displacement had a negative impact on survival. The presence of a residual tumor resulted in decreased survival and is an independent risk factor for mortality. Positivity for p53 identified a low survival rate. CDKN2A mutations were an independent risk factor for mortality. We identified that a negative prognosis is influenced by the association of epilepsy with headache, tumor volume, and immunoreactivity to IDH1 and p53. Independent factors associated with mortality were midline shift, presence of tumor residue, and CDKN2A gene deletions and amplifications.

Noninvasive Delineation of Glioma Infiltration with Combined 7T Chemical Exchange Saturation Transfer Imaging and MR Spectroscopy: A Diagnostic Accuracy Study

For precise delineation of glioma extent, amino acid PET is superior to conventional MR imaging. Since metabolic MR sequences such as chemical exchange saturation transfer (CEST) imaging and MR spectroscopy (MRS) were developed, we aimed to evaluate the diagnostic accuracy of combined CEST and MRS to predict glioma infiltration. Eighteen glioma patients of different tumor grades were enrolled in this study; 18F-fluoroethyltyrosine (FET)-PET, amide proton transfer CEST at 7 Tesla(T), MRS and conventional MR at 3T were conducted preoperatively. Multi modalities and their association were evaluated using Pearson correlation analysis patient-wise and voxel-wise. Both CEST (R = 0.736, p < 0.001) and MRS (R = 0.495, p = 0.037) correlated with FET-PET, while the correlation between CEST and MRS was weaker. In subgroup analysis, APT values were significantly higher in high grade glioma (3.923 ± 1.239) and IDH wildtype group (3.932 ± 1.264) than low grade glioma (3.317 ± 0.868, p < 0.001) or IDH mutant group (3.358 ± 0.847, p < 0.001). Using high FET uptake as the standard, the CEST/MRS combination (AUC, 95% CI: 0.910, 0.907−0.913) predicted tumor infiltration better than CEST (0.812, 0.808−0.815) or MRS (0.888, 0.885−0.891) alone, consistent with contrast-enhancing and T2-hyperintense areas. Probability maps of tumor presence constructed from the CEST/MRS combination were preliminarily verified by multi-region biopsies. The combination of 7T CEST/MRS might serve as a promising non-radioactive alternative to delineate glioma infiltration, thus reshaping the guidance for tumor resection and irradiation.

Glycosylation modification patterns reveal distinct tumor metabolism and immune microenvironment landscape in lower-grade gliomas

Glycosylation alterations, a key driver throughout tumorigenesis and tumor progression, could regulate the microenvironment and immune response as well as lead to harmful metabolism and cell signaling. In this study, we first comprehensively evaluated the glycosylation modification patterns of LGGs based on glycosyltransferase family genes and systematically integrated these modification patterns with tumor metabolism and immune microenvironment characteristics. Glycosylation score was also developed to quantify glycosylation modification patterns of individuals. As a result, two glycosylation modification patterns were identified, with distinct prognosis, metabolism, and immune microenvironment features. The glycosylation subtype A and cluster A were characterized by higher carbohydrates and amino acid metabolism activity, higher levels of infiltrating cells, and poor prognosis, whereas an opposite modification pattern was observed in glycosylation subtype B and cluster B. In addition, a high glycosylation score is closer to a microenvironment characterized by chronic inflammation, immunosuppression, and tumor promotion. Following analysis and validation, the glycosylation score was a reliable and independent prognostic index. More importantly, the glycosylation score influenced the response to immunotherapy, chemotherapy, or targeted therapy, which provided a novel insight into promoting personalized therapy in the future and may contribute to developing novel therapeutic drugs or exploring promising drug combination therapy strategies.

Identification of a novel cuproptosis-related gene signature and integrative analyses in patients with lower-grade gliomas

Background

Cuproptosis is a newly discovered unique non-apoptotic programmed cell death distinguished from known death mechanisms like ferroptosis, pyroptosis, and necroptosis. However, the prognostic value of cuproptosis and the correlation between cuproptosis and the tumor microenvironment (TME) in lower-grade gliomas (LGGs) remain unknown.

Methods

In this study, we systematically investigated the genetic and transcriptional variation, prognostic value, and expression patterns of cuproptosis-related genes (CRGs). The CRG score was applied to quantify the cuproptosis subtypes. We then evaluated their values in the TME, prognostic prediction, and therapeutic responses in LGG. Lastly, we collected five paired LGG and matched normal adjacent tissue samples from Sun Yat-sen University Cancer Center (SYSUCC) to verify the expression of signature genes by quantitative real-time PCR (qRT-PCR) and Western blotting (WB).

Results

Two distinct cuproptosis-related clusters were identified using consensus unsupervised clustering analysis. The correlation between multilayer CRG alterations with clinical characteristics, prognosis, and TME cell infiltration were observed. Then, a well-performed cuproptosis-related risk model (CRG score) was developed to predict LGG patients' prognosis, which was evaluated and validated in two external cohorts. We classified patients into high- and low-risk groups according to the CRG score and found that patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (P<0.001). A high CRG score implies higher TME scores, more significant TME cell infiltration, and increased mutation burden. Meanwhile, the CRG score was significantly correlated with the cancer stem cell index, chemoradiotherapy sensitivity-related genes and immune checkpoint genes, and chemotherapeutic sensitivity, indicating the association with CRGs and treatment responses. Univariate and multivariate Cox regression analyses revealed that the CRG score was an independent prognostic predictor for LGG patients. Subsequently, a highly accurate predictive model was established for facilitating the clinical application of the CRG score, showing good predictive ability and calibration. Additionally, crucial CRGs were further validated by qRT-PCR and WB.

Conclusion

Collectively, we demonstrated a comprehensive overview of CRG profiles in LGG and established a novel risk model for LGG patients' therapy status and prognosis. Our findings highlight the potential clinical implications of CRGs, suggesting that cuproptosis may be the potential therapeutic target for patients with LGG.

Current Considerations in the Treatment of Grade 3 Gliomas

OPINION STATEMENT

Treatment recommendations for grade 3 gliomas are guided by their histopathologic and molecular phenotype. In the 2021 WHO classification, these tumors are categorized into two types, grade 3 IDH mutant (IDHmt), 1p/19q codeleted oligodendroglioma and IDH mutant astrocytoma. Treatment consists of maximal safe surgery, followed by radiation therapy (RT) and alkylating agent-based chemotherapy. Based on the updated CATNON result, RT followed by temozolomide improves outcome in patients with non-codeleted grade 3 IDHmt astrocytoma. In patients with IDHmt, codeleted oligodendroglioma, the addition of procarbazine, CCNU, and vincristine regimen is the recommended treatment, based on large randomized controlled trials. These current treatments prolong the overall survival to up to 10 years in patients with grade 3 IDHmt astrocytoma and 14 years in grade 3 IDHmt codeleted oligodendroglioma. Treatment options at recurrence include re-resection, re-irradiation, and other cytotoxic chemotherapy; however, these are of limited benefit. Novel agents targeting IDH mutation and its metabolic effects are currently under investigation to improve the outcome of these patients.

Simple approach for the histomolecular diagnosis of central nervous system gliomas based on 2021 World Health Organization Classification

The classification of central nervous system (CNS) glioma went through a sequence of developments, between 2006 and 2021, started with only histological approach then has been aided with a major emphasis on molecular signatures in the 4th and 5th editions of the World Health Organization (WHO). The recent reformation in the 5th edition of the WHO classification has focused more on the molecularly defined entities with better characterized natural histories as well as new tumor types and subtypes in the adult and pediatric populations. These new subclassified entities have been incorporated in the 5^th edition after the continuous exploration of new genomic, epigenomic and transcriptomic discovery. Indeed, the current guidelines of 2021 WHO classification of CNS tumors and European Association of Neuro-Oncology (EANO) exploited the molecular signatures in the diagnostic approach of CNS gliomas. Our current review presents a practical diagnostic approach for diffuse CNS gliomas and circumscribed astrocytomas using histomolecular criteria adopted by the recent WHO classification. We also describe the treatment strategies for these tumors based on EANO guidelines.

Molecular Aberrations Stratify Grade 2 Astrocytomas Into Several Rare Entities: Prognostic and Therapeutic Implications

The identification of specific molecular aberrations guides the prognostic stratification and management of grade 2 astrocytomas. Mutations in isocitrate dehydrogenase (IDH) 1 and 2, found in the majority of adult diffuse low-grade glioma (DLGG), seem to relate to a favorable prognosis compared to IDH wild-type (IDH-wt) counterparts. Moreover, the IDH-wt group can develop additional molecular alterations worsening the prognosis, such as epidermal growth factor receptor amplification (EGFR-amp) and mutation of the promoter of telomerase reverse transcriptase (pTERT-mut). This review analyzes the prognostic impact and therapeutic implications of genetic alterations in adult LGG.

High-dose salvage re-irradiation in recurrent/progressive adult diffuse gliomas: development of a novel prognostic scoring system

PURPOSE

Over the past two decades, high-dose salvage re-irradiation (re-RT) has been used increasingly in the multimodality management of adults with recurrent/progressive diffuse glioma. Several factors that determine outcomes following re-RT have been incorporated into prognostic models to guide patient selection. We aimed to develop a novel four-tiered prognostic model incorporating relevant molecular markers from our single-institutional cohort of patients treated with high-dose salvage re-RT for recurrent/progressive diffuse glioma.

MATERIAL AND METHODS

Various patient, disease, and treatment-related factors impacting upon survival following salvage re-RT were identified through univariate analysis. Each of these prognostic factors was further subdivided and assigned scores of 0 (low-risk), 1 (intermediate-risk), or 2 (high-risk). Scores from individual prognostic factors were added to derive the cumulative score (ranging from 0 to 16), with increasing scores indicating worsening prognosis.

RESULTS

A total of 111 adults with recurrent/progressive diffuse glioma treated with salvage high-dose re-RT were included. We could assign patients into four prognostic subgroups (A=15 patients, score 0-3); (B=50 patients, score 4-7); (C=33 patients, score 8-10); and (D=13 patients, score 11-16) with completely non-overlapping survival curves suggesting the good discriminatory ability. Post-re-RT survival was significantly higher in Group A compared to groups B, C, and D, respectively (stratified log-rank p-value <0.0001).

CONCLUSION

There exists a lack of universally acceptable 'standard-of-care' salvage therapy for recurrent/progressive diffuse glioma. A novel four-tiered prognostic scoring system incorporating traditional factors as well as relevant molecular markers is proposed for selecting patients appropriately for high-dose salvage re-RT that warrants validation in a non-overlapping cohort.