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.

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.

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.

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.

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.

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.

Multi-cohort comprehensive analysis unveiling the clinical value and therapeutic effect of GNAL in glioma.

Clinical data indicates that glioma patients have poor treatment outcomes and clinical prognosis. The role of olfactory signaling pathway-related genes (OSPRGs) in glioma has not been fully elucidated. In this study, we aimed to investigate the role and relationship between OSPRGs and glioma. Univariate and multivariate Cox regression analyses were performed to assess the relationship between OSPRGs and the overall survival of glioma based on public cohorts, and the target gene (G Protein Subunit Alpha L, GNAL) was screened. The association of GNAL expression with clinicopathological characteristics, gene mutation landscape, tumor immune microenvironment (TIME), deoxyribonucleic acid (DNA) methylation, and naris-occlusion controlled genes (NOCGs) was performed. Immunohistochemistry was used to evaluate GNAL level in glioma. Further analysis was conducted to evaluate the drug sensitivity, immunotherapy response, and functional enrichment of GNAL. GNAL was an independent prognostic factor, and patients with low GNAL expression have a poor prognosis. Expression of GNAL was closely associated with clinicopathological characteristics, DNA methylation, and several immune-related pathways. Immune infiltration analysis indicated that GNAL levels were negatively correlated with immune scores. GNAL low-expression group showed efficacy with anti-PD-1 therapy. Ten compounds with significantly different half-maximal inhibitory concentration (IC50) values between the GNAL high and low-expression groups were identified. Furthermore, its expression was associated with several immune cells, immune-related genes, and NOCGs. The expression of GNAL is closely associated with clinicopathological characteristics, TIME, and the response to therapeutic interventions, highlighting its potential as a prognostic biomarker for glioma.

Analysis of the sodium pump subunit ATP1A3 in glioma patients: Potential value in prognostic prediction and immunotherapy.

The ATP1A3 gene is associated with the development and progression of neurological diseases. However, the pathological function and therapeutic value of ATP1A3 in glioblastoma (GBM) remains unknown. In this study, we tried to explore the correlation between the ATP1A3 gene expression and immune features in GBM samples. We found that ATP1A3 gene expression levels showed significant negative correlation with immune checkpoints such as PD-L1, CTLA-4 and IDO1. Next, ATP1A3 gene expression levels showed significant negative correlation with the anti-cancer immune cell process, the immune score and stromal score. By grouping ATP1A3 expression levels, we found that that immunomodulator-related genes and tumor-associated immune cell effector gene expression levels were associated with lower ATP1A3 expression. In addition, immunotherapy prediction pathway activity and a majority of the anti-cancer immune cell process activity levels were also showed to be correlated with lower ATP1A3 gene expression. Further, nine prognostic factors were identified by prognostic analysis, and a GBM prognostic model (risk score) was established. We applied the model to the TCGA GBM training set sample and the GSE4412 validation set sample and found that patients in the high risk score subgroup had significantly shorter survival time, demonstrating the prognostic value and prognostic efficacy of the risk score. Furthermore, ATP1A3 overexpression has also been found to sensitize cancer cells to anti-PD-1 therapy. In conclusion, we showed that ATP1A3 is a highly promising treatment target in GBM and the risk score is an independent prognostic factor for cancer and can be used to help guide the prediction of survival time in patients with GBM.

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.

Volumetric Response and Survival of Patients With Bulky IDH-Mutated Grade 3 Glioma Managed With FET-FDG-Guided Integrated Boost IMRT.

AIMS: Despite relatively favourable outcomes associated with IDH-mutant grade 3 gliomas, many patients present with diffuse non-enhancing disease involving multiple brain regions, prompting concern over both durable disease control and the morbidity associated with large volume radiation therapy. This study audits volumetric response, survival and functional outcomes in this 'large volume' subgroup that undergoes intensity modulated radiation therapy (IMRT). MATERIALS AND METHODS: From a prospective database of 187 patients with IDH-mutant grade 3 gliomas managed with IMRT between 2008 and 2020, recorded PTV was divided into quartiles. The top quartile, termed the 'large volume cohort' (LVC), was identified. IMRT involved FET-FDG guided integrated boost (59.4/54Gy in 33 fractions). Manual volumetric segmentation of baseline, four months and 13 months post-IMRT tumour were performed for T1, T2 and T1gd MRI sequences. The primary endpoint was volumetric reduction on the T1 and T2 sequences at 13 months and analysed with relapse-free survival (RFS) and overall survival (OS). Morbidity endpoints were assessed at year four post-IMRT and included performance status (ECOG PS) and employment outcomes. RESULTS: The fourth quartile (LVC) identified 44 patients for whom volumetric analysis was available. The LVC had median PTV of 320cm3 compared to 186.2cm3 for the total group. Anaplastic astrocytoma and oligodendroglioma were equally distributed and tumour sites were frontal (54%), temporal (18%) and parietal lobes (16%). Median follow-up for survivors was 71.5 months. Projected 10-year RFS and OS in LVC was 40% and 62%, compared to 53% and 62% respectively in the overall cohort. The RFS (p = 0.06) and OS (p = 0.65) of the LVC was not significantly different to other PTV quartiles; however the impact of PTV volume reached significance when analysed as a continuous variable (RFS p < 0.01; OS p = 0.02). Median T1 volumes were 26.1cm3, 8.0cm3 and 5.3cm3 at months +0, +3 and +12, respectively. The corresponding T2 volumes were 120.8cm3, 29.1cm3 and 26.3cm3. The median T1 and T2 volume reductions were 77% (q1-3: 57-92%) and 78% (q1-3: 60-85%) at 13 months post-IMRT. Initial T2 volume was associated with worse RFS (p = 0.04) but not OS (p = 0.96). There was no association between median T2 volume reduction and RFS (p = 0.77). For patients assessable at year 4 post-IMRT, no late CTCAE Grade 3/4 toxicity events were recognised. 92% of patients were ECOG PS 0-1, 45% were employed at prior capacity and 28% were working with impairment. CONCLUSION: Patients with large volume IDH-mutant Grade 3 glioma demonstrated significant tumour reduction post-IMRT, and good long-term outcomes with respect to survival and functional status. Although larger IMRT volumes were associated with poorer RFS, this was also associated with the initial volume of non-enhancing tumour.

Influence of socioeconomic status on clinical outcomes of diffuse midline glioma and diffuse intrinsic pontine glioma.

OBJECTIVE: Given the lack of a definitive treatment and the poor prognosis of patients with diffuse midline glioma (DMG) and diffuse intrinsic pontine glioma (DIPG), socioeconomic status (SES) may affect treatment access and therefore survival. Therefore, this study aimed to examine the relationship between SES and treatment modalities, progression-free survival (PFS), and overall survival (OS) in children with DMG/DIPG. METHODS: A retrospective, single-institution review was conducted of medical records of patients ≤ 18 years of age who had DMG or DIPG that was diagnosed between 2000 and 2022. Patient demographics, surgical interventions, chemotherapy, radiation therapy, clinical trial enrollment, and medical care-related travel were extracted. SES variables (education and mean income) for associated patient census tracts were collected and stratified. Statistical analysis using unpaired t-tests, chi-square analysis, and log-rank tests was conducted. RESULTS: Of the 96 patients who met the inclusion criteria, the majority were female (59%) and non-Hispanic White (57%). The median PFS, median OS, and time from diagnosis to treatment did not differ between races/ethnicities or sex. Ninety-one of 96 patients had census tract data available. Patients from higher-income census tracts (> 50% of families with annual household income greater than $50,000) had a longer median OS (480 vs 235 days, p < 0.001) and traveled significantly longer distances for medical care (1550 vs 1114 miles, p = 0.048) than families from lower-income census tracts. Patients from the highest education quartile traveled significantly farther for treatment than the lowest education quartile (mean 2964 vs 478 miles, p = 0.047). Patients who received both oral and intravenous chemotherapy were more likely to be from higher-income census tracts than those who received intravenous or no chemotherapy. Duration of PFS, rates of clinical trial enrollment, biopsy rates, H3K27 mutation status, ventriculoperitoneal shunt placement rates, and radiotherapy rates were not associated with SES variables. CONCLUSIONS: Patients from families from higher-income census tracts experienced longer OS and traveled farther for treatment. Patients from families from higher-education-level census tracts traveled more often for treatment. The authors' findings suggest that SES influences DMG and DIPG OS. More studies should be done to understand the role of SES in the outcomes of children with DMG/DIPG.

Potential value of expression of receptor accessory protein 4 for evaluating the prognosis of lower-grade glioma patients.

BACKGROUND: REEP4 is involved in the regulation of the biological process of mitosis. Lower grade glioma (LGG), as a malignant tumor, is accompanied by abnormalities in mitosis, but there have been no reports of REEP4 so far. METHODS: We collected transcriptome data, DNA methylation data and the clinical characteristics of thousands of patients with LGG. Various big data analysis methods and molecular biology experiments were employed to reveal the impact of REEP4 on the pathological process of LGG. RESULTS: It was found that the expression of REEP4 was significantly elevated and negatively regulated by its methylation site. Therefore, both the high expression of REEP4 and low methylation state of cg16311504 showed that the patients are correlated with lower patient survival rate. In addition, high REEP4 expression participates in the regulation of various cancer-related cellular signaling pathways, such as the cell cycle, MAPK signaling pathway, NOD-like receptor signaling pathway, etc. More importantly, the level of immune cell infiltration significantly increased in the high expression group of REEP4 in the LGG tumor microenvironment and REEP4 has a high positive correlation with PD-L1 and other immune checkpoints. CONCLUSIONS: In brief, this study is the first to introduce REEP4 in malignant tumors, which can be used as an independent risk factor that participates in the malignant process of LGG. More importantly, REEP4 has the potential to become a new star in the field of anti-tumor treatment.

Temporal changes in treatment and late mortality and morbidity in adult survivors of childhood glioma: a report from the Childhood Cancer Survivor Study.

Pediatric glioma therapy has evolved to delay or eliminate radiation for low-grade tumors. This study examined these temporal changes in therapy with long-term outcomes in adult survivors of childhood glioma. Among 2,501 5-year survivors of glioma in the Childhood Cancer Survivor Study diagnosed 1970-1999, exposure to radiation decreased over time. Survivors from more recent eras were at lower risk of late mortality (≥5 years from diagnosis), severe/disabling/life-threatening chronic health conditions (CHCs) and subsequent neoplasms (SNs). Adjusting for treatment exposure (surgery only, chemotherapy, or any cranial radiation) attenuated this risk (for example, CHCs (1990s versus 1970s), relative risk (95% confidence interval), 0.63 (0.49-0.80) without adjustment versus 0.93 (0.72-1.20) with adjustment). Compared to surgery alone, radiation was associated with greater than four times the risk of late mortality, CHCs and SNs. Evolving therapy, particularly avoidance of cranial radiation, has improved late outcomes for childhood glioma survivors without increased risk for late recurrence.

The Significance of the Redox Gene in the Prognosis and Therapeutic Response of Glioma.

OBJECTIVES: Glioblastoma (GBM) is a fatal adult central nervous system tumor. Due to its high heterogeneity, the survival rate and prognosis of patients are poor. Thousands of people die of this disease every year all over the world. At present, the treatment of GBM is mainly through surgical resection and the combination of later drugs, radiotherapy, and chemotherapy. An abnormal redox system is involved in the malignant progression and treatment tolerance of glioma, which is the main reason for poor survival and prognosis. The construction of a GBM redox-related prognostic model may be helpful in improving the redox immunotherapy and prognosis of GBM. METHODS: Based on glioma transcriptome data and clinical data from The Cancer Genome Atlas, databases, a risk model of redox genes was constructed by univariate and multivariate Cox analysis. The good prediction performance of the model was verified by the internal validation set of The Cancer Genome Atlas, and the external data of Chinese Glioma Genome Atlas. RESULTS: The results confirmed that the higher the risk score, the worse the survival of patients. Age and isocitrate dehydrogenase status were significantly correlated with risk scores. The analysis of immune infiltration and immunotherapy found that there were significant differences in the immune score, matrix score, and ESTIMATE score between high and low-risk groups. reverse transcription polymerase chain reaction and immunohistochemical staining of glioma samples confirmed the expression of the hub gene. CONCLUSION: Our study suggests that the 5 oxidative-related genes nitricoxidesynthase3 , NCF2 , VASN , FKBP1B , and TXNDC2 are hub genes, which may provide a reliable prognostic tool for glioma clinical treatment.

Development and internal validation of machine learning models for personalized survival predictions in spinal cord glioma patients.

BACKGROUND CONTEXT: Numerous factors have been associated with the survival outcomes in patients with spinal cord gliomas (SCG). Recognizing these specific determinants is crucial, yet it is also vital to establish a reliable and precise prognostic model for estimating individual survival outcomes. OBJECTIVE: The objectives of this study are twofold: first, to create an array of interpretable machine learning (ML) models developed for predicting survival outcomes among SCG patients; and second, to integrate these models into an easily navigable online calculator to showcase their prospective clinical applicability. STUDY DESIGN: This was a retrospective, population-based cohort study aiming to predict the outcomes of interest, which were binary categorical variables, in SCG patients with ML models. PATIENT SAMPLE: The National Cancer Database (NCDB) was utilized to identify adults aged 18 years or older who were diagnosed with histologically confirmed SCGs between 2010 and 2019. OUTCOME MEASURES: The outcomes of interest were survival outcomes at three specific time points postdiagnosis: 1, 3, and 5 years. These outcomes were formed by combining the "Vital Status" and "Last Contact or Death (Months from Diagnosis)" variables. Model performance was evaluated visually and numerically. The visual evaluation utilized receiver operating characteristic (ROC) curves, precision-recall curves (PRCs), and calibration curves. The numerical evaluation involved metrics such as sensitivity, specificity, accuracy, area under the PRC (AUPRC), area under the ROC curve (AUROC), and Brier Score. METHODS: We employed five ML algorithms-TabPFN, CatBoost, XGBoost, LightGBM, and Random Forest-along with the Optuna library for hyperparameter optimization. The models that yielded the highest AUROC values were chosen for integration into the online calculator. To enhance the explicability of our models, we utilized SHapley Additive exPlanations (SHAP) for assessing the relative significance of predictor variables and incorporated partial dependence plots (PDPs) to delineate the influence of singular variables on the predictions made by the top performing models. RESULTS: For the 1-year survival analysis, 4,913 patients [5.6% with 1-year mortality]; for the 3-year survival analysis, 4,027 patients (11.5% with 3-year mortality]; and for the 5-year survival analysis, 2,854 patients (20.4% with 5-year mortality) were included. The top models achieved AUROCs of 0.938 for 1-year mortality (TabPFN), 0.907 for 3-year mortality (LightGBM), and 0.902 for 5-year mortality (Random Forest). Global SHAP analyses across survival outcomes at different time points identified histology, tumor grade, age, surgery, radiotherapy, and tumor size as the most significant predictor variables for the top-performing models. CONCLUSIONS: This study demonstrates ML techniques can develop highly accurate prognostic models for SCG patients with excellent discriminatory ability. The interactive online calculator provides a tool for assessment by physicians (https://huggingface.co/spaces/MSHS-Neurosurgery-Research/NCDB-SCG). Local interpretability informs prediction influences for a given individual. External validation across diverse datasets could further substantiate potential utility and generalizability. This robust, interpretable methodology aligns with the goals of precision medicine, establishing a foundation for continued research leveraging ML's predictive power to enhance patient counseling.