Survival outcome and predictors of WHO grade 2 and 3 insular gliomas: A classification based on the tumor spread.

OBJECTIVE: The study aimed to identify if clinical features and survival outcomes of insular glioma patients are associated with our classification based on the tumor spread. METHODS: Our study included 283 consecutive patients diagnosed with histological grade 2 and 3 insular gliomas. A new classification was proposed, and tumors restricted to the paralimbic system were defined as type 1. When tumors invaded the limbic system (referred to as the hippocampus and its surrounding structures in this study) simultaneously, they were defined as type 2. Tumors with additional internal capsule involvement were defined as type 3. RESULTS: Tumors defined as type 3 had a higher age at diagnosis (p = 0.002) and a higher preoperative volume (p < 0.001). Furthermore, type 3 was more likely to be diagnosed as IDH wild type (p < 0.001), with a higher rate of Ki-67 index (p = 0.015) and a lower rate of gross total resection (p < 0.001). Type 1 had a slower tumor growth rate than type 2 (mean 3.3%/month vs. 19.8%/month; p < 0.001). Multivariate Cox regression analysis revealed the extent of resection (HR 0.259, p = 0.004), IDH status (HR 3.694, p = 0.012), and tumor spread type (HR = 1.874, p = 0.012) as independent predictors of overall survival (OS). Tumor grade (HR 2.609, p = 0.008), the extent of resection (HR 0.488, p = 0.038), IDH status (HR 2.225, p = 0.025), and tumor spread type (HR 1.531, p = 0.038) were significant in predicting progression-free survival (PFS). CONCLUSION: The current study proposes a classification of the insular glioma according to the tumor spread. It indicates that the tumors defined as type 1 have a relatively better nature and biological characteristics, and those defined as type 3 can be more aggressive and refractory. Besides its predictive value for prognosis, the classification has potential value in formulating surgical strategies for patients with insular gliomas.

Serum beta2-microglobulin acts as a biomarker for severity and prognosis in glioma patients: a preliminary clinical study.

BACKGROUND: Gliomas are the deadliest malignant tumors of the adult central nervous system. We previously discovered that beta2-microglobulin (B2M) is abnormally upregulated in glioma tissues and that it exerts a range of oncogenic effects. Besides its tissue presence, serum B2M levels serve as biomarkers for various diseases. This study aimed to explore whether serum B2M levels can be used in the diagnosis and prognosis of gliomas. METHODS: Medical records from 246 glioma patients were retrospectively analyzed. The relationship between preoperative serum B2M levels and clinicopathological features was examined. Kaplan-Meier analysis, alongside uni- and multivariate Cox regression, assessed the association between B2M levels, systemic inflammatory markers, and glioma patient prognosis. Receiver operating characteristic (ROC) curve analysis evaluated the diagnostic significance of these biomarkers specifically for glioblastoma (GBM). RESULTS: Patients with malignant gliomas exhibited elevated preoperative serum B2M levels. Glioma patients with high serum B2M levels experienced shorter survival times. Multivariate Cox analysis determined the relationship between B2M levels (hazard ratio = 1.92, 95% confidence interval: 1.05-3.50, P = 0.034) and the overall survival of glioma patients. B2M demonstrated superior discriminatory power in distinguishing between GBM and non-GBM compared to inflammation indicators. Moreover, postoperative serum B2M levels were lower than preoperative levels in the majority of glioma patients. CONCLUSIONS: High preoperative serum B2M levels correlated with malignant glioma and a poor prognosis. Serum B2M shows promise as a novel biomarker for predicting patient prognosis and reflecting the therapeutic response.

High expression of BTN3A1 is associated with clinical and immunological characteristics and predicts a poor prognosis in advanced human gliomas.

Introduction: Gliomas represent the most prevalent and aggressive tumors within the central nervous system. Despite the current standard treatments, the median survival time for glioblastoma patients remains dismal, hovering around 14 months. While attempts have been made to inhibit the PD-1/PD-L1 and CTLA-4/CD80-CD86 axes through immunotherapy, the outcomes have yet to demonstrate significant efficacy. The immune checkpoint Butyrophilin 3A1 (BTN3A1) can either be involved in advantageous or detrimental function depending on the cancer type. Methods: In our study, we utilized a Moroccan cohort to delve into the role of BTN3A1 in gliomas. A transcriptomic analysis was conducted on 34 patients, which was then corroborated through a protein analysis in 27 patients and validated using the TCGA database (n = 667). Results: Our results revealed an elevated expression of BTN3A1 in glioblastoma (grade 4), as evidenced in both the TCGA database and our cohort of Moroccan glioma patients. Within the TCGA cohort, BTN3A1 expression was notably higher in patients with wild-type IDH. We observed a positive correlation between BTN3A1 expression and immune infiltration of B cells, CD8+ T cells, naive CD4+ T cells, and M2 macrophages. Patients exhibiting increased BTN3A1 expression also presented elevated levels of TGF-ß, IL-10, and TIM-3 compared to those with reduced BTN3A1 expression. Notably, patients with high BTN3A1 expression were associated with a poorer prognosis than their counterparts with lower expression. Conclussion: Our findings suggest that BTN3A1 might promote the establishment of an immunosuppressive microenvironment. Consequently, targeting BTN3A1 could offer novel therapeutic avenues for the management of advanced gliomas.

Tumor treating fields for newly diagnosed high-grade glioma based on the criteria of 2021 WHO CNS5: A retrospective analysis of Chinese patients in a single center.

BACKGROUND AND OBJECTIVE: High-grade glioma (HGG) is known to be characterized by a high degree of malignancy and a worse prognosis. The classical treatment is safe resection supplemented by radiotherapy and chemotherapy. Tumor treating fields (TTFields), an emerging physiotherapeutic modality that targets malignant solid tumors using medium-frequency, low-intensity, alternating electric fields to interfere with cell division, have been used for the treatment of new diagnosis of glioblastoma, however, their administration in HGG requires further clinical evidence. The efficacy and safety of TTFields in Chinese patients with HGG were retrospectively evaluated by us in a single center. METHODS: We enrolled and analyzed 52 patients with newly diagnosed HGG undergoing surgery and standard chemoradiotherapy regimens from December 2019 to June 2022, and followed them until June 2023. Based on whether they used TTFields, they were divided into a TTFields group and a non-TTFields group. Progression-free survival (PFS) and overall survival (OS) were compared between the two groups. RESULTS: There were 26 cases in the TTFields group and 26 cases in the non-TTFields group. In the TTFields group, the median PFS was 14.2 months (95% CI: 9.50-18.90), the median OS was 19.7 months (95% CI: 14.95-24.25) , the median interval from surgery to the start of treatment with TTFields was 2.47 months (95% CI: 1.47-4.13), and the median duration of treatment with TTFields was 10.6 months (95% CI: 9.57-11.63). 15 (57.69%) patients experienced an adverse event and no serious adverse event was reported. In the non-TTFields group, the median PFS was 9.57 months (95% CI: 6.23-12.91) and the median OS was 16.07 months (95% CI: 12.90-19.24). There was a statistically significant difference in PFS (p = 0.005) and OS (p = 0.007) between the two groups. CONCLUSIONS: In this retrospective analysis, TTFields were observed to improve newly diagnosed HGG patients' median PFS and OS. Compliance was much higher than reported in clinical trials and safety remained good.

Frailty in patients with IDH-mutant gliomas: experience from a high-volume tumor center.

PURPOSE: Gliomas are increasingly diagnosed in an aging population, with treatment outcomes influenced by factors like tumor genetics and patient frailty. This study focused on IDH-mutant gliomas and assessed how frailty affects 30-day readmission and overall survival (OS). We aimed to address a gap in understanding the impact of frailty on this specific glioma subtype. METHODS: 136 patients with an IDH-mutant glioma between 2007 and 2021 were identified at our institution. High frailty was classified by scores ≥ 1 on the 5-factor modified frailty index (mFI-5) and ≥ 3 on the Charlson Comorbidity Index (CCI). Patient and tumor characteristics including age, sex, race, Karnofsky Performance Status (KPS), Body Mass Index (BMI), tumor type and location, type of operation, and therapy course were recorded. Outcomes measured included 30-day readmission and overall survival (OS). Analysis was conducted utilizing logistic regression and Kaplan-Meier curves. RESULTS: Of the 136 patients, 52 (38%) had high frailty: 18 with CCI ≥ 3, 34 with mFI-5 ≥ 1. High frailty correlated with increased BMI (CCI: 30.2, mFI-5: 30.1 kg/m2), more neurological deficits (CCI: 61%, mFI-5: 56%), and older age at surgery (CCI: 63, mFI-5: 48 years). Hospital readmission within 30 days occurred in 8 (5.9%) patients. Logistic regression indicated no significant difference in 30-day readmission rates (CCI: p = 0.30, mFI-5: p = 0.62) or median OS between high and low frailty groups. However, patients treated at our institution with newly diagnosed tumors with high mFI-5 had a 6.79 times higher adjusted death hazard than those with low mFI-5 (p = .049). CONCLUSION: Our analysis revealed that CCI and mFI-5 were not significantly associated with 30-day nor OS. However, in patients with non-recurrent tumors, there was a significant association of mFI-5 with OS. Further study of frailty with larger cohorts is warranted to enhance prognostication of outcome after neurosurgical treatment.

Association of NID2 SNPs with Glioma Risk and Prognosis in the Chinese Population.

Glioma is the most common primary intracranial tumor with high mortality and poor prognosis. The purpose of this study was to investigate how single-nucleotide polymorphisms (SNPs) of the NID2 gene affect glioma risk and prognosis. Four candidate SNPs of NID2 in 529 glioma patients and 478 healthy controls were successfully genotyped by Agena MassARRAY mass spectrometer. Logistic regression was utilized to assess the associations between NID2 SNPs and glioma risk under different genetic models. Furthermore, the relationship between risk-related SNPs in NID2 and the prognosis of glioma patients was explored through Kaplan-Meier (KM) survival curve and Cox proportional hazard regression analysis. The results showed that rs11846847 (OR 1.24, p = 0.017) and rs1874569 (OR 1.22, p = 0.026) were significantly associated with an increased risk of glioma, and rs11846847 also had a risk-increasing effect on glioma in participants ≤ 40 years old. The interaction model of rs11846847 and rs1874569 could be more suitable for forecasting glioma risk. We also discovered a significant association between rs1874569 and poor prognosis in glioma patients (HR 1.32, p = 0.039) and especially CC genotype was relevant to shorter overall survival (OS) and progression-free survival (PFS) in patients with high-grade glioma. Additionally, the study demonstrated that gross total resection or chemotherapy improve glioma prognosis in the Chinese Han population. This study is the first to provide evidence for the association of NID2 SNPs with glioma risk and prognosis, suggesting that NID2 variants might be potential factors for glioma.

A cuproptosis-based prognostic model for predicting survival in low-grade glioma.

BACKGROUND: It is unknown what variables contribute to the formation and multiplication of low-grade gliomas (LGG). An emerging process of cell death is called cuproptosis. Our research aims to increase therapeutic options and gain a better understanding of the role that cuproptosis-related genes play in the physical characteristics of low-grade gliomas. METHODS: The TCGA database was utilized to find cuproptosis genes that may be used to develop LGG risk model. Cox analysis in three different formats: univariate, multivariate, and LASSO. The gene signature's independent predictive ability was assessed using ROC curves and Cox regression analysis based on overall survival. Use of CGGA data and nomogram model for external validation Immunohistochemistry, gene mutation, and functional enrichment analysis are also employed to clarify risk models' involvement. Next, we analyzed changes in the immunological microenvironment in the risk model and forecasted possible chemotherapeutic drugs to target each group. Finally, we validated the protein expression levels of cuproptosis-related genes using LGG and adjacent normal tissues in a small self-case-control study. RESULTS: This study developed a glioma predictive model based on five cuproptosis-associated genes. Compared to the high-risk group, the low-risk group's OS was significantly longer. The ROC curves showed high genetic signature performance in both groups. The signature-based categorisation was also linked to clinical characteristics and molecular subgroups. The prognosis of individuals with grade 2 or 3 glioma is also influenced by our risk model. Immunological testing revealed that the high-risk group had more immune cells and immunological function. The risk model also predicted immunotherapy and chemotherapy medication results. Also, this study confirmed that the expression of cuproptosis-related genes by Western blot. CONCLUSION: We developed a prediction model for LGG patients using genes associated with cuproptosis. With acceptable prediction performance, this risk model may effectively stratify the prognosis of glioma patients.

The relationship between imaging features, therapeutic response, and overall survival in pediatric diffuse intrinsic pontine glioma.

We aimed to evaluate the relationship between imaging features, therapeutic responses (comparative cross-product and volumetric measurements), and overall survival (OS) in pediatric diffuse intrinsic pontine glioma (DIPG). A total of 134 patients (≤ 18 years) diagnosed with DIPG were included. Univariate and multivariate analyses were performed to evaluate correlations of clinical and imaging features and therapeutic responses with OS. The correlation between cross-product (CP) and volume thresholds in partial response (PR) was evaluated by linear regression. The log-rank test was used to compare OS patients with discordant therapeutic response classifications and those with concordant classifications. In univariate analysis, characteristics related to worse OS included lower Karnofsky, larger extrapontine extension, ring-enhancement, necrosis, non-PR, and increased ring enhancement post-radiotherapy. In the multivariate analysis, Karnofsky, necrosis, extrapontine extension, and therapeutic response can predict OS. A 25% CP reduction (PR) correlated with a 32% volume reduction (R2 = 0.888). Eight patients had discordant therapeutic response classifications according to CP (25%) and volume (32%). This eight patients' median survival time was 13.0 months, significantly higher than that in the non-PR group (8.9 months), in which responses were consistently classified as non-PR based on CP (25%) and volume (32%). We identified correlations between imaging features, therapeutic responses, and OS; this information is crucial for future clinical trials. Tumor volume may represent the DIPG growth pattern more accurately than CP measurement and can be used to evaluate therapeutic response.

Clinical characteristics and prognostic factors of adult brainstem gliomas: A retrospective analysis of histologically-proven 40 cases.

To illustrate the clinical characteristics and prognostic factors of adult patients pathologically confirmed with brainstem gliomas (BSGs). Clinical data of 40 adult patients pathologically diagnosed with BSGs admitted to Beijing Shijitan Hospital from 2009 to 2022 were recorded and retrospectively analyzed. The primary parameters included relevant symptoms, duration of symptoms, Karnofsky performance status (KPS), tumor location, type of surgical resection, diagnosis, treatment, and survival. Univariate and multivariate analyses were evaluated by Cox regression models. The gliomas were located in the midbrain of 9 patients, in the pons of 14 cases, in the medulla of 5 cases, in the midbrain and pons of 6 cases and invading the medulla and pons of 6 cases, respectively. The proportion of patients with low-grade BSGs was 42.5%. Relevant symptoms consisted of visual disturbance, facial paralysis, dizziness, extremity weakness, ataxia, paresthesia, headache, bucking, dysphagia, dysacousia, nausea, dysphasia, dysosmia, hypomnesia and nystagmus. 23 (57.5%) patients accepted stereotactic biopsy, 17 (42.5%) patients underwent surgical resection. 39 patients received radiotherapy and 34 cases were treated with temozolomide. The median overall survival (OS) of all patients was 26.2 months and 21.5 months for the median progression-free survival (PFS). Both duration of symptoms (P = .007) and tumor grading (P = .002) were the influencing factors for OS, and tumor grading was significantly associated with PFS (P = .001). Duration of symptoms for more than 2 months and low-grade are favorable prognostic factors for adult patients with BSGs.

Crosstalk of different cell-death patterns predicts prognosis and drug sensitivity in glioma.

BACKGROUND: Glioma is a malignant brain tumor originating from glial cells, and there still a challenge to accurately predict the prognosis. Programmed cell death (PCD) plays a key role in tumorigenesis and immune response. However, the crosstalk and potential role of various PCDs in prognosis and tumor microenvironment remains unknown. Therefore, we comprehensively discussed the relationship between different models of PCD and the prognosis of glioma and provided new ideas for the optimal targeted therapy of glioma. MATERIALS AND METHODS: We compared and analyzed the role of 14 PCD patterns on the prognosis from different levels. We constructed the cell death risk score (CDRS) index and conducted a comprehensive analysis of CDRS and TME characteristics, clinical characteristics, and drug response. RESULTS: Effects of different PCDs at the genomic, functional, and immune microenvironment levels were discussed. CDRS index containing 6 gene signatures and a nomogram were established. High CDRS is associated with a worse prognosis. Through transcriptome and single-cell data, we found that patients with high CDRS showed stronger immunosuppressive characteristics. Moreover, the high-CDRS group was resistant to the traditional glioma chemotherapy drug Vincristine, but more sensitive to the Temozolomide and the clinical experimental drug Bortezomib. In addition, we identified 19 key potential therapeutic targets during malignant differentiation of tumor cells. CONCLUSION: Overall, we provide the first systematic description of the role of 14 PCDs in glioma. A new CDRS model was built to predict the prognosis and to provide a new idea for the targeted therapy of glioma.

The Father of Wisdom: "The Influence of Surgical Experience on Overall Survival in Patients with Malignant Gliomas".

BACKGROUND: The role of surgery in the management of malignant gliomas has been feverishly deliberated after the publication of the first expansive case series, the last two decades reinvigorating the discussion regarding the value of total removal in improving survivability. Despite numerous technologies being implemented to increase the resection rates of malignant gliomas, the role of surgical experience has been largely overlooked. This article aims to discuss the importance of a single surgeon's experience in treating high-grade gliomas over a period of 20 years. MATERIAL AND METHODS: In order to demonstrate the role of surgical experience, we divided the patients operated by a single neurosurgeon into two distinct intervals: between 2000 and 2009 and between 2012 and 2020, respectively. Only cases with subsequent adjuvant radio-chemotherapy were included. For objective reasons, no technologies that could assist the extent of resection (EOR) such as intraoperative MRI (iMRI) or 5-ALA could be used in the country of our study. Gross total resection was the main goal whenever possible, whereas subtotal removal was defined as a clear remnant on contrasted MRI or CT performed 24-48 h postoperatively. Using the Kaplan-Meier method, we analyzed the survival and disease-free interval of our patients according to age, pathology, and degree of resection. RESULTS: In the 20-year interval of our retrospective study, the main author (ISF) operated 1591 cases of gliomas in a total of 1878 surgeries, including recurrences. The number of high-grade glioma (HGG) patients was 909 (57.10%), 495 of which were male (54.5%) and 414 (45.5%) female. The mean age of the HGG population was 51.9 years. The most common type of HGG subtype were glioblastomas with a total number 620 cases (68.2%). Regarding overall survival (OS), average survival at 12 months was better by 1.6%, and 12.1% improved at 18 months and 17.8% longer at 24 months in the 2012-2020 interval. The mean OS in the earlier interval was 11.00 months compared to the second when it reached 13.441 months (CI, 12.642-14.24). CONCLUSION: Surgical treatment represents a critical step in the multimodal treatment of malignant gliomas. According to our results, surgical experience improves not only overall survival in a manner equivalent to adjuvant chemotherapy but also the quality of life. As such, a special qualification in neurooncology may prove necessary in offering these patients a second chance at life.

Tumour growth rate predicts overall survival in patients with recurrent WHO grade 4 glioma.

PURPOSE: Accurate prognostication may aid in the selection of patients who will benefit from surgery at recurrent WHO grade 4 glioma. This study aimed to evaluate the role of serial tumour volumetric measurements for prognostication at first tumour recurrence. METHODS: We retrospectively analyzed patients with histologically-diagnosed WHO grade 4 glioma at initial and at first tumour recurrence at a tertiary hospital between May 2000 and September 2018. We performed auto-segmentation using ITK-SNAP software, followed by manual adjustment to measure serial contrast-enhanced T1W (CE-T1W) and T2W lesional volume changes on all MRI images performed between initial resection and repeat surgery. RESULTS: Thirty patients met inclusion criteria; the median overall survival using Kaplan-Meier analysis from second surgery was 10.5 months. Seventeen (56.7%) patients received treatment post second surgery. Univariate cox regression analysis showed that greater rate of increase in lesional volume on CE-T1W (HR = 2.57; 95% CI [1.18, 5.57]; p = 0.02) in the last 2 MRI scans leading up to the second surgery was associated with a higher mortality likelihood. Patients with higher Karnofsky Performance Score (KPS) (HR = 0.97; 95% CI [0.95, 0.99]; p = 0.01) and who received further treatment following second surgery (HR = 0.43; 95% CI [0.19, 0.98]; p = 0.04) were shown to have a better survival. CONCLUSION: Higher rate of CE-T1W lesional growth on the last 2 MRI images prior to surgery at recurrence was associated with increase mortality risk. A larger prospective study is required to determine and validate the threshold to distinguish rapidly progressive tumour with poor prognosis.

IL-6 significantly correlated with the prognosis in low-grade glioma and the mediating effect of immune microenvironment.

To screen immune-related prognostic biomarkers in low-grade glioma (LGG), and reveal the potential regulatory mechanism. The differential expressed genes (DEGs) between alive and dead patients were initially identified, then the key common genes between DEGs and immune-related genes were obtained. Regarding the key DEGs associated with the overall survival (OS), their clinical value was assessed by Kaplan-Meier, RCS, logistic regression, ROC, and decision curve analysis methods. We also assessed the role of immune infiltration on the association between key DEGs and OS. All the analyses were based on the TGCA-LGG data. Finally, we conducted the molecular docking analysis to explore the targeting binding of key DEGs with the therapeutic agents in LGG. Among 146 DEGs, only interleukin-6 (IL-6) was finally screened as an immune-related biomarker. High expression of IL-6 significantly correlated with poor OS time (all P < .05), showing a linear relationship. The combination of IL-6 with IDH1 mutation had the most favorable prediction performance on survival status and they achieved a good clinical net benefit. Next, we found a significant relationship between IL-6 and immune microenvironment score, and the immune microenvironment played a mediating effect on the association of IL-6 with survival (all P < .05). Detailly, IL-6 was positively related to M1 macrophage infiltration abundance and its biomarkers (all P < .05). Finally, we obtained 4 therapeutic agents in LGG targeting IL-6, and their targeting binding relationships were all verified. IL6, as an immune-related biomarker, was associated with the prognosis in LGG, and it can be a therapeutic target in LGG.

Identification and clinical validation of diverse cell-death patterns-associated prognostic features among low-grade gliomas.

Low-grade glioma (LGG) is heterogeneous at biological and transcriptomic levels, and it is still controversial for the definition and typing of LGG. Therefore, there is an urgent need for specific and practical molecular signatures for accurate diagnosis, individualized therapy, and prognostic evaluation of LGG. Cell death is essential for maintaining homeostasis, developing and preventing hyperproliferative malignancies. Based on diverse programmed cell death (PCD) related genes and prognostic characteristics of LGG, this study constructed a model to explore the mechanism and treatment strategies for LGG cell metastasis and invasion. We screened 1161 genes associated with PCD and divided 512 LGG samples into C1 and C2 subtypes by consistent cluster analysis. We analyzed the two subtypes' differentially expressed genes (DEGs) and performed functional enrichment analysis. Using R packages such as ESTIMATE, CIBERSOTR, and MCPcounter, we assessed immune cell scores for both subtypes. Compared with C1, the C2 subtype has a poor prognosis and a higher immune score, and patients in the C2 subtype are more strongly associated with tumor progression. LASSO and COX regression analysis screened four characteristic genes (CLU, FHL3, GIMAP2, and HVCN1). Using data sets from different platforms to validate the four-gene feature, we found that the expression and prognostic correlation of the four-gene feature had a high degree of stability, showing stable predictive effects. Besides, we found downregulation of CLU, FHL3, and GIMAP2 significantly impairs the growth, migration, and invasive potential of LGG cells. Take together, the four-gene feature constructed based on PCD-related genes provides valuable information for further study of the pathogenesis and clinical treatment of LGG.

Revisiting prognostic factors of gliomatosis cerebri in adult-type diffuse gliomas.

PURPOSE: There is lack of comprehensive analysis evaluating the impact of clinical, molecular, imaging, and surgical data on survival of patients with gliomatosis cerebri (GC). This study aimed to investigate prognostic factors of GC in adult-type diffuse glioma patients. METHODS: Retrospective chart and imaging review was performed in 99 GC patients from adult-type diffuse glioma (among 1,211 patients; 6 oligodendroglioma, 16 IDH-mutant astrocytoma, and 77 IDH-wildtype glioblastoma) from a single institution between 2005 and 2021. Predictors of overall survival (OS) of entire patients and IDH-wildtype glioblastoma patients were determined. RESULTS: The median OS was 16.7 months (95% confidence interval [CI] 14.2-22.2) in entire patients and 14.3 months (95% CI 12.2-61.9) in IDH-wildtype glioblastoma patients. In entire patients, KPS (hazard ratio [HR] = 0.98, P = 0.004), no 1p/19q codeletion (HR = 10.75, P = 0.019), MGMTp methylation (HR = 0.54, P = 0.028), and hemorrhage (HR = 3.45, P = 0.001) were independent prognostic factors on multivariable analysis. In IDH-wildtype glioblastoma patients, KPS (HR = 2.24, P = 0.075) was the only independent prognostic factor on multivariable analysis. In subgroup of IDH-wildtype glioblastoma with CE tumors, total resection of CE tumor did not remain as a significant prognostic factor (HR = 1.13, P = 0.685). CONCLUSIONS: The prognosis of GC patients is determined by its underlying molecular type and patient performance status. Compared with diffuse glioma without GC, aggressive surgery of CE tumor in GC patients does not improve survival.

UBA2 as a Prognostic Biomarker and Potential Therapeutic Target in Glioma.

BACKGROUND: Gliomas are characterized by aggressive behavior, leading to severe disability and high mortality. Ubiquitin-like modifier activating enzyme 2 (UBA2) is a subunit of the E1-activating enzyme involved in the SUMOylation (SUMO, small ubiquitin-related modifier) of numerous proteins. Although the abnormality of UBA2 is linked to the progression of various tumor types, the role of UBA2 in glioma is still unknown. METHODS: A bioinformatic analysis using several public databases was conducted to examine the expression level, clinicopathological correlations, and prognostic significance of UBA2 in glioma. The correlation between UBA2 expression and drug sensitivity in cancers was also explored. Multiple cellular experiments were conducted to validate the role of UBA2 in glioma. RESULTS: Analysis of multiple databases and cellular experiments revealed that UBA2 was overexpressed in glioma tissues and cell lines, respectively. UBA2 expression in gliomas correlated with World Health Organization (WHO) grade, IDH gene status, 1p19q deletion, histological type, and immune cell infiltration in glioma. UBA2 expression in carcinomas also correlated with drug sensitivity. Kaplan-Meier analysis revealed that high expression of UBA2 predicted poorer survival in glioma patients. A nomogram model containing UBA2 expression was constructed for clinical practice. Knockdown of UBA2 was observed to suppress glioma cell progression and sensitize glioma cells to irradiation in vitro. CONCLUSION: Overall, this research showed that UBA2 might be involved not only in the development of glioma but also in the regulation of immunity, drug sensitivity, and radiosensitivity. Therefore, UBA2 may be a potential target for therapy and a candidate biomarker for glioma diagnosis and prognosis.

Relationship between chemokine/chemokine receptor and glioma prognosis and outcomes: Systematic review and meta-analysis.

BACKGROUND: Glioma is a primary tumor originating from the central nervous system, and despite ongoing efforts to improve treatment, its overall survival rate remains low. There are a limited number of reports regarding the clinical grading, prognostic impact, and utility of chemokines. Therefore, conducting a meta-analysis is necessary to obtain convincing and conclusive results. METHODS: A comprehensive literature search was conducted using various databases, including PubMed, Web of Science, The Cochrane Library, Embase, Ovid Medline, CNKI, Wanfang Database, VIP, and CBM. The search encompassed articles published from the inception of the databases until March 2024. The estimated odds ratio (ORs), standard mean difference (SMDs), and hazard ratio (HR) with their corresponding 95% confidence intervals (95% CI) were calculated to assess the predictive value of chemokine and receptor levels in glioma risk. Additionally, heterogeneity tests and bias tests were performed to evaluate the reliability of the findings. RESULTS: This meta-analysis included a total of 36 studies, involving 2,480 patients diagnosed with glioma. The results revealed a significant association between the expression levels of CXCR4 (n = 8; OR = 22.28; 95 % CI = 11.47-43.30; p = 0.000), CXCL12 (n = 4; OR = 10.69; 95 % CI = 7.03-16.24; p = 0.000), CCL2 (n = 6; SMD = -0.83; 95 % CI = -0.98--0.67; p = 0.000), CXCL8 (n = 3; SMD = 0.75; 95 % CI = 0.47-1.04; p = 0.000), CXCR7 (n = 3; OR = 20.66; 95 % CI = 10.20-41.82; p = 0.000), CXCL10 (n = 2; SMD = 3.27; 95 % CI = 2.91-3.62; p = 0.000) and the risk of glioma. Additionally, a significant correlation was observed between CXCR4 (n = 8; OR = 4.39; 95 % CI = 3.04-6.32; p = 0.000), (n = 6; SMD = 1.37; 95 % CI = 1.09-1.65; p = 0.000), CXCL12 (n = 6; OR = 6.30; 95 % CI = 3.87-10.25; p = 0.000), (n = 5; ES = 2.25; 95 % CI = 1.15-3.34; p = 0.041), CCL2 (n = 3; OR = 9.65; 95 % CI = 4.55-20.45; p = 0.000), (n = 4; SMD = -1.47; 95 % CI = -1.68--1.26; p = 0.000), and CCL18 (n = 3; SMD = 1.62; 95 % CI = 1.30-1.93; p = 0.000) expression levels and high-grade glioma (grades 3-4). Furthermore, CXCR4 (HR = 2.38, 95 % CI = 1.66-3.40; p = 0.000) exhibited a strong correlation with poor overall survival (OS) rates in glioma patients. CONCLUSION: The findings of this study showed a robust association between elevated levels of CXCR4, CXCL12, CCL2, CXCL8, CXCL10 and CXCR7 with a higher risk of glioma. Furthermore, the WHO grading system was validated by the strong correlation shown between higher expression of CXCR4, CXCL12, CCL2, and CCL18 and WHO high-grade gliomas (grades 3-4). Furthermore, the results of the meta-analysis suggested that CXCR4 might be a helpful biomarker for predicting the worse prognosis of glioma patients.

Diffusion- and Perfusion-Weighted MRI Radiomics for Survival Prediction in Patients with Lower-Grade Gliomas.

PURPOSE: Lower-grade gliomas of histologic grades 2 and 3 follow heterogenous clinical outcomes, which necessitates risk stratification. This study aimed to evaluate whether diffusion-weighted and perfusion-weighted MRI radiomics allow overall survival (OS) prediction in patients with lower-grade gliomas and investigate its prognostic value. MATERIALS AND METHODS: In this retrospective study, radiomic features were extracted from apparent diffusion coefficient, relative cerebral blood volume map, and Ktrans map in patients with pathologically confirmed lower-grade gliomas (January 2012-February 2019). The radiomics risk score (RRS) calculated from selected features constituted a radiomics model. Multivariable Cox regression analysis, including clinical features and RRS, was performed. The models' integrated area under the receiver operating characteristic curves (iAUCs) were compared. The radiomics model combined with clinical features was presented as a nomogram. RESULTS: The study included 129 patients (median age, 44 years; interquartile range, 37-57 years; 63 female): 90 patients for training set and 39 patients for test set. The RRS was an independent risk factor for OS with a hazard ratio of 6.01. The combined clinical and radiomics model achieved superior performance for OS prediction compared to the clinical model in both training (iAUC, 0.82 vs. 0.72, p=0.002) and test sets (0.88 vs. 0.76, p=0.04). The radiomics nomogram combined with clinical features exhibited good agreement between the actual and predicted OS with C-index of 0.83 and 0.87 in the training and test sets, respectively. CONCLUSION: Adding diffusion- and perfusion-weighted MRI radiomics to clinical features improved survival prediction in lower-grade glioma.

A multi-omics analysis-based model to predict the prognosis of low-grade gliomas.

Lower-grade gliomas (LGGs) exhibit highly variable clinical behaviors, while classic histology characteristics cannot accurately reflect the authentic biological behaviors, clinical outcomes, and prognosis of LGGs. In this study, we carried out analyses of whole exome sequencing, RNA sequencing and DNA methylation in primary vs. recurrent LGG samples, and also combined the multi-omics data to construct a prognostic prediction model. TCGA-LGG dataset was searched for LGG samples. 523 samples were used for whole exome sequencing analysis, 532 for transcriptional analysis, and 529 for DNA methylation analysis. LASSO regression was used to screen genes with significant association with LGG survival from the frequently mutated genes, differentially expressed genes, and differentially methylated genes, whereby a prediction model for prognosis of LGG was further constructed and validated. The most frequently mutated diver genes in LGGs were IDH1 (77%), TP53 (48%), ATRX (37%), etc. Top significantly up-regulated genes were C6orf15, DAO, MEOX2, etc., and top significantly down-regulated genes were DMBX1, GPR50, HMX2, etc. 2077 genes were more and 299 were less methylated in recurrent vs. primary LGG samples. Thirty-nine genes from the above analysis were included to establish a prediction model of survival, which showed that the high-score group had a very significantly shorter survival than the low-score group in both training and testing sets. ROC analysis showed that AUC was 0.817 for the training set and 0.819 for the testing set. This study will be beneficial to accurately predict the survival of LGGs to identify patients with poor prognosis to take specific treatment as early, which will help improve the treatment outcomes and prognosis of LGG.