The effect of somatic mutations in mitochondrial DNA on the survival of patients with primary brain tumors.

AIM: To assess the presence of mitochondrial (mt) DNA somatic mutations, determine the relationship between clinicopathological characteristics and mutations, and assess the survival outcomes in Malay patients with primary brain tumors. METHODS: The study enrolled 54 patients with primary brain tumors. DNA extracted from paired tissue and blood samples was subjected to Sanger sequencing to identify alterations in the entire mtDNA. The associations between clinicopathological characteristics and mutations were evaluated. Cox-regression multivariate analysis was conducted to identify factors significantly associated with survival, and Kaplan-Meier analysis was used to compare the survival of patients with and without mutations. RESULTS: Overall, 29.6% of the patients harbored 19 somatic mutations distributed across 15 loci within the mtDNA. Notably, 36.8% of these mutations were not previously documented in MITOMAP. One newly identified mutation caused a frameshift in the ATPase6 gene, resulting in a premature stop codon. Three mutations were classified as deleterious in the MitImpact2 database. Overall, 1097 mtDNA polymorphisms were identified across 331 different locations. Patients with mutations exhibited significantly shorter survival than patients without mutations. CONCLUSIONS: mtDNA mutations negatively affected the survival outcomes of Malaysian patients with primary brain tumors. However, studies with larger samples are needed to confirm the association between mutation burden and survival rates.

Epithelial ovarian cancer and brain metastases: might the BRCA status, PARP inhibitor administration, and surgical treatment impact the survival?

OBJECTIVE: To evaluate disease characteristics and survival according to BRCA status, administration of poly-(ADP-ribose) polymerase inhibitors (PARPi), and surgery in patients with ovarian cancer and brain metastases. METHODS: This is a monocentric retrospective cohort of patients with ovarian cancer and brain metastases treated between 2000 and 2021. Data were collected by a retrospective review of medical records and analyzed according to: (1) BRCA mutation; (2) PARPi before and after brain metastases; (3) surgery for brain metastases. RESULTS: Eighty-five patients with ovarian cancer and brain metastasis and known BRCA status (31 BRCA mutated (BRCAm), 54 BRCA wild-type (BRCAwt)) were analyzed. Twenty-two patients had received PARPi before brain metastases diagnosis (11 BRCAm, 11 BRCAwt) and 12 after (8 BRCAm, 4 BRCAwt). Brain metastases occurred >1 year later in patients who had received previous PARPi. Survival was longer in the BRCAm group (median post-brain metastasis survival: BRCAm 23 months vs BRCAwt 8 months, p=0.0015). No differences were found based on BRCA status analyzing the population who did not receive PARPi after brain metastasis (median post-brain metastasis survival: BRCAm 8 months vs BRCAwt 8 months, p=0.31). In the BRCAm group, survival was worse in patients who had received previous PARPi (median post-brain metastasis survival: PARPi before, 7 months vs no-PARPi before, 24 months, p=0.003). If PARPi was administered after brain metastases, survival of the overall population improved (median post-brain metastasis survival: PARPi after, 46 months vs no-PARPi after, 8 months, p=0.00038).In cases of surgery for brain metastases, the prognosis seemed better (median post-brain metastasis survival: surgery 13 months vs no-surgery 8 months, p=0.036). Three variables were significantly associated with prolonged survival at multivariate analysis: BRCA mutation, multimodal treatment, and ≤1 previous chemotherapy line. CONCLUSIONS: BRCA mutations might impact brain metastasis occurrence and lead to better outcomes. In a multimodal treatment, surgery seems to affect survival even in cases of extracranial disease. PARPi use should be considered as it seems to prolong survival if administered after brain metastasis.

Survival Predictive Nomograms for Non-Surgical Brain Metastases Patients From Non-Small Cell Lung Cancer Receiving Radiotherapy: A Population-Based Study.

OBJECTIVE: A high number of Non-Small Cell Lung Cancer (NSCLC) patients with brain metastasis who have not had surgery often have a negative outlook. Radiotherapy remains a most common and effective method. Nomograms were developed to forecast the cancer-specific survival (CSS) and overall survival (OS) in NSCLC individuals with nonoperative brain metastases who underwent radiotherapy. METHODS: Information was gathered from the Surveillance, Epidemiology, and End Results (SEER) database about patients diagnosed with NSCLC who had brain metastases not suitable for surgery. Nomograms were created and tested using multivariate Cox regression models to forecast CSS and OS at intervals of 1, 2, and 3 years. RESULTS: The research involved 3413 individuals diagnosed with NSCLC brain metastases who had undergone radiotherapy but had not experienced surgery. These participants were randomly divided into two categories. The analysis revealed that gender, age, ethnicity, marital status, tumor location, tumor laterality, tumor grade, histology, T stage, N stage, chemotherapy, tumor size, lung metastasis, bone metastasis, and liver metastasis were significant independent predictors for OS and CSS. The C-index for the training set for predicting OS was .709 (95% CI, .697-.721), and for the validation set, it was .705 (95% CI, .686-.723), respectively. The C-index for predicting CSS was .710 (95% CI, .697-.722) in the training set and .703 (95% CI, .684-.722) in the validation set, respectively. The nomograms model, as suggested by the impressive C-index, exhibits outstanding differentiation ability. Moreover, the ROC and calibration curves reveal its commendable precision and distinguishing potential. CONCLUSIONS: For the first time, highly accurate and reliable nomograms were developed to predict OS and CSS in NSCLC patients with non-surgical brain metastases, who have undergone radiotherapy treatment. The nomograms may assist in tailoring counseling strategies and choosing the most effective treatment method.

mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses.

BACKGROUND: Glioblastoma multiforme (GBM) is a type of fast-growing brain glioma associated with a very poor prognosis. This study aims to identify key genes whose expression is associated with the overall survival (OS) in patients with GBM. METHODS: A systematic review was performed using PubMed, Scopus, Cochrane, and Web of Science up to Journey 2024. Two researchers independently extracted the data and assessed the study quality according to the New Castle Ottawa scale (NOS). The genes whose expression was found to be associated with survival were identified and considered in a subsequent bioinformatic study. The products of these genes were also analyzed considering protein-protein interaction (PPI) relationship analysis using STRING. Additionally, the most important genes associated with GBM patients' survival were also identified using the Cytoscape 3.9.0 software. For final validation, GEPIA and CGGA (mRNAseq_325 and mRNAseq_693) databases were used to conduct OS analyses. Gene set enrichment analysis was performed with GO Biological Process 2023. RESULTS: From an initial search of 4104 articles, 255 studies were included from 24 countries. Studies described 613 unique genes whose mRNAs were significantly associated with OS in GBM patients, of which 107 were described in 2 or more studies. Based on the NOS, 131 studies were of high quality, while 124 were considered as low-quality studies. According to the PPI network, 31 key target genes were identified. Pathway analysis revealed five hub genes (IL6, NOTCH1, TGFB1, EGFR, and KDR). However, in the validation study, only, the FN1 gene was significant in three cohorts. CONCLUSION: We successfully identified the most important 31 genes whose products may be considered as potential prognosis biomarkers as well as candidate target genes for innovative therapy of GBM tumors.

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.

Indirect functional connectivity does not predict overall survival in glioblastoma.

BACKGROUND: Lesion network mapping (LNM) is a popular framework to assess clinical syndromes following brain injury. The classical approach involves embedding lesions from patients into a normative functional connectome and using the corresponding functional maps as proxies for disconnections. However, previous studies indicated limited predictive power of this approach in behavioral deficits. We hypothesized similarly low predictiveness for overall survival (OS) in glioblastoma (GBM). METHODS: A retrospective dataset of patients with GBM was included (n = 99). Lesion masks were registered in the normative space to compute disconnectivity maps. The brain functional normative connectome consisted in data from 173 healthy subjects obtained from the Human Connectome Project. A modified version of the LNM was then applied to core regions of GBM masks. Linear regression, classification, and principal component (PCA) analyses were conducted to explore the relationship between disconnectivity and OS. OS was considered both as continuous and categorical (low, intermediate, and high survival) variable. RESULTS: The results revealed no significant associations between OS and network disconnection strength when analyzed at both voxel-wise and classification levels. Moreover, patients stratified into different OS groups did not exhibit significant differences in network connectivity patterns. The spatial similarity among the first PCA of network maps for each OS group suggested a lack of distinctive network patterns associated with survival duration. CONCLUSIONS: Compared with indirect structural measures, functional indirect mapping does not provide significant predictive power for OS in patients with GBM. These findings are consistent with previous research that demonstrated the limitations of indirect functional measures in predicting clinical outcomes, underscoring the need for more comprehensive methodologies and a deeper understanding of the factors influencing clinical outcomes in this challenging disease.

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.

Artificial neural network identified a 20-gene panel in predicting immunotherapy response and survival benefits after anti-PD1/PD-L1 treatment in glioblastoma patients.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are a promising immunotherapy approach, but glioblastoma clinical trials have not yielded satisfactory results. OBJECTIVE: To screen glioblastoma patients who may benefit from immunotherapy. METHODS: Eighty-one patients receiving anti-PD1/PD-L1 treatment from a large-scale clinical trial and 364 patients without immunotherapy from The Cancer Genome Atlas (TCGA) were included. Patients in the ICI-treated cohort were divided into responders and nonresponders according to overall survival (OS), and the most critical responder-relevant features were screened using random forest (RF). We constructed an artificial neural network (ANN) model and verified its predictive value with immunotherapy response and OS. RESULTS: We defined two groups of ICI-treated glioblastoma patients with large differences in survival benefits as nonresponders (OS ≤6 months, n = 18) and responders (OS ≥17 months, n = 8). No differentially mutated genes were observed between responders and nonresponders. We performed RF analysis to select the most critical responder-relevant features and developed an ANN with 20 input variables, five hidden neurons and one output neuron. Receiver operating characteristic analysis and the DeLong test demonstrated that the ANN had the best performance in predicting responders, with an AUC of 0.97. Survival analysis indicated that ANN-predicted responders had significantly better OS rates than nonresponders. CONCLUSION: The 20-gene panel developed by the ANN could be a promising biomarker for predicting immunotherapy response and prognostic benefits in ICI-treated GBM patients and may guide oncologists to accurately select potential responders for the preferential use of ICIs.

Profiling of Tumor-Infiltrating Immune Cells and Their Impact on Survival in Glioblastoma Patients Undergoing Immunotherapy with Dendritic Cells.

Glioblastomas (GBM) are the most common primary malignant brain tumors, comprising 2% of all cancers in adults. Their location and cellular and molecular heterogeneity, along with their highly infiltrative nature, make their treatment challenging. Recently, our research group reported promising results from a prospective phase II clinical trial involving allogeneic vaccination with dendritic cells (DCs). To date, six out of the thirty-seven reported cases remain alive without tumor recurrence. In this study, we focused on the characterization of infiltrating immune cells observed at the time of surgical resection. An analytical model employing a neural network-based predictive algorithm was used to ascertain the potential prognostic implications of immunological variables on patients' overall survival. Counterintuitively, immune phenotyping of tumor-associated macrophages (TAMs) has revealed the extracellular marker PD-L1 to be a positive predictor of overall survival. In contrast, the elevated expression of CD86 within this cellular subset emerged as a negative prognostic indicator. Fundamentally, the neural network algorithm outlined here allows a prediction of the responsiveness of patients undergoing dendritic cell vaccination in terms of overall survival based on clinical parameters and the profile of infiltrated TAMs observed at the time of tumor excision.

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.

Association between elevated preoperative red cell distribution width and mortality after brain tumor craniotomy.

BACKGROUND: Red cell distribution width (RDW) has been recognized as a potential inflammatory biomarker, with elevated levels associated with adverse outcomes in various diseases. However, its role in predicting outcomes after brain tumor craniotomy remains unclear. We aimed to assess whether preoperative RDW influences mortality and postoperative complications in patients undergoing brain tumor craniotomy. METHODS: This retrospective cohort study analyzed serum RDW levels in patients undergoing brain tumor craniotomy at West China Hospital. RDW was evaluated in two forms: RDW-CV and RDW-SD, and was categorized into four quartiles for analysis by using logistic regression and multivariate analysis to adjust for confounding. RESULTS: The study encompassed 10,978 patients undergoing brain tumor craniotomy. our analysis revealed no significant difference in 30-day mortality across various RDW-CV levels. However, we observed a dose-response relationship with preoperative RDW-CV levels in assessing long-term mortality risks. Specifically, patients with RDW-CV levels of 12.6-13.2% (HR 1.04, 95% CI 1.01-1.18), 13.2-13.9% (HR 1.12, 95% CI 1.04-1.26), and > 13.9% (HR 1.34, 95% CI 1.18-1.51) exhibited a significantly higher hazard of long-term mortality compared to those with RDW-CV < 12.6%. When preoperative RDW-CV was analyzed as a continuous variable, for each 10% increase in RDW-CV, the adjusted OR of long-term mortality was 1.09 (95% CI 1.05-1.13). we also observed significant associations between preoperative higher RDW-CV levels and certain postoperative complications including acute kidney injury (OR 1.46, 95% CI: 1.10-1.94), pneumonia infection (OR 1.19 95% CI: 1.05-1.36), myocardial infarction (OR 1.32, 95% CI: 1.05-1.66), readmission (OR 1.15, 95% CI: 1.01-1.30), and a prolonged length of hospital stay (OR 1.11, 95% CI: 1.02-1.21). For RDW-SD levels, there was no significant correlation for short-term mortality, long-term mortality, and postoperative complications. CONCLUSIONS: Our study showed elevated preoperative RDW-CV is significantly associated with increased long-term mortality and multiple postoperative complications, but no such association is observed with RDW-SD. These findings show the prognostic importance of RDW-CV, reinforcing its potential as a valuable tool for risk stratification in the preoperative evaluation of brain tumor craniotomy patients.

Prognostic relevance of radiological findings on early postoperative MRI for 187 consecutive glioblastoma patients receiving standard therapy.

Several prognostic factors are known to influence survival for patients treated with IDH-wildtype glioblastoma, but unknown factors may remain. We aimed to investigate the prognostic implications of early postoperative MRI findings. A total of 187 glioblastoma patients treated with standard therapy were consecutively included. Patients either underwent a biopsy or surgery followed by an early postoperative MRI. Progression-free survival (PFS) and overall survival (OS) were analysed for known prognostic factors and MRI-derived candidate factors: resection status as defined by the response assessment in neuro-oncology (RANO)-working group (no contrast-enhancing residual tumour, non-measurable contrast-enhancing residual tumour, or measurable contrast-enhancing residual tumour) with biopsy as reference, contrast enhancement patterns (no enhancement, thin linear, thick linear, diffuse, nodular), and the presence of distant tumours. In the multivariate analysis, patients with no contrast-enhancing residual tumour or non-measurable contrast-enhancing residual tumour on the early postoperative MRI displayed a significantly improved progression-free survival compared with patients receiving only a biopsy. Only patients with non-measurable contrast-enhancing residual tumour showed improved overall survival in the multivariate analysis. Contrast enhancement patterns were not associated with survival. The presence of distant tumours was significantly associated with both poor progression-free survival and overall survival and should be considered incorporated into prognostic models.

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.

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.

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.

Clinical role of NDRG2-based methylation status on survival pattern of glioblastoma.

OBJECTIVES: Gliobalstoma is the most common primary brain tumor in adults with an extensive genetic and transcriptional heterogeneity, still identification of the role of DNA methylation, as one of epigenetic alterations, is emerged. Authors aimed to study the clinical role of N-myc downstream-regulated gene 2 (NDRG2) -based methylation among GBM patients versus benign neurological diseases (BND), investigate its prognostic role and its relation with survival outcomes. METHODS: A total of 78 FFPE specimens were recruited as follows: GBM (n = 58) and BND (n = 20) then analyzed for NDRG2 methylation using Methyl II quantitative PCR system. The sensitivity and specificity of methylation was detected using receiver operating characteristic (ROC) curve and the relation with clinicopathological criteria for GBM and response to treatment were studied. Survival patterns; progression free survival (PFS) and overall survival (OS) were analyzed using Kaplan-Meier analyses. RESULTS: Mean methylation NDRG2 level was significantly increased in GBM patients as compared to BND and its sensitivity and specificity were 96.55% and 95%, respectively with area under curve (AUC) equals 0.973. Among the clinical characteristic factors, mean methylation level reported significant difference with ECOG and tumor site. Survival out comes revealed that NDRG2 methylation increased with worse PFS and OS at significant level (long rank test X2 = 13.3, p < .0001; and X2 = 7.1, p = .008, respectively). CONCLUSION: Current findings highlight the importance of studying DNA methylation of NDRG2 as a key factor to understand the role of epigenetic alterations in GBM.

Anti-epileptic drug use during adjuvant chemo-radiotherapy is associated with poorer survival in patients with glioblastoma: A nationwide population-based cohort study.

INTRODUCTION: There are emerging but inconsistent evidences about anti-epileptic drugs (AEDs) as radio- or chemo-sensitizers to improve survival in glioblastoma patients. We conducted a nationwide population-based study to evaluate the impact of concurrent AED during post-operative chemo-radiotherapy on outcome. MATERIAL AND METHODS: A total of 1057 glioblastoma patients were identified by National Health Insurance Research Database and Cancer Registry in 2008-2015. Eligible criteria included those receiving surgery, adjuvant radiotherapy and temozolomide, and without other cancer diagnoses. Survival between patients taking concurrent AED for 14 days or more during chemo-radiotherapy (AED group) and those who did not (non-AED group) were compared, and subgroup analyses for those with valproic acid (VPA), levetiracetam (LEV), or phenytoin were performed. Multivariate analyses were used to adjust for confounding factors. RESULTS: There were 642 patients in the AED group, whereas 415 in the non-AED group. The demographic data was balanced except trend of more patients in the AED group had previous drug history of AEDs (22.6% vs. 18%, P 0.078). Overall, the AED group had significantly increased risk of mortality (HR = 1.18, P 0.016) compared to the non-AED group. Besides, an adverse dose-dependent relationship on survival was also demonstrated in the AED group (HR = 1.118, P 0.0003). In subgroup analyses, the significant detrimental effect was demonstrated in VPA group (HR = 1.29,P 0.0002), but not in LEV (HR = 1.18, P 0.079) and phenytoin (HR = 0.98, P 0.862). CONCLUSIONS: Improved survival was not observed in patients with concurrent AEDs during chemo-radiotherapy. Our real-world data did not support prophylactic use of AEDs for glioblastoma 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.

The FKBP51s Splice Isoform Predicts Unfavorable Prognosis in Patients with Glioblastoma.

The primary treatment for glioblastoma (GBM) is removing the tumor mass as defined by MRI. However, MRI has limited diagnostic and predictive value. Tumor-associated macrophages (TAM) are abundant in GBM tumor microenvironment (TME) and are found in peripheral blood (PB). FKBP51 expression, with its canonical and spliced isoforms, is constitutive in immune cells and aberrant in GBM. Spliced FKBP51s supports M2 polarization. To find an immunologic signature that combined with MRI could advance in diagnosis, we immunophenotyped the macrophages of TME and PB from 37 patients with GBM using FKBP51s and classical M1-M2 markers. We also determined the tumor levels of FKBP51s, PD-L1, and HLA-DR. Tumors expressing FKBP51s showed an increase in various M2 phenotypes and regulatory T cells in PB, indicating immunosuppression. Tumors expressing FKBP51s also activated STAT3 and were associated with reduced survival. Correlative studies with MRI and tumor/macrophages cocultures allowed to interpret TAMs. Tumor volume correlated with M1 infiltration of TME. Cocultures with spheroids produced M1 polarization, suggesting that M1 macrophages may infiltrate alongside cancer stem cells. Cocultures of adherent cells developed the M2 phenotype CD163/FKBP51s expressing pSTAT6, a transcription factor enabling migration and invasion. In patients with recurrences, increased counts of CD163/FKBP51s monocyte/macrophages in PB correlated with callosal infiltration and were accompanied by a concomitant decrease in TME-infiltrating M1 macrophages. PB PD-L1/FKBP51s connoted necrotic tumors. In conclusion, FKBP51s identifies a GBM subtype that significantly impairs the immune system. Moreover, FKBP51s marks PB macrophages associated with MRI features of glioma malignancy that can aid in patient monitoring. SIGNIFICANCE: Our research suggests that by combining imaging with analysis of monocyte/macrophage subsets in patients with GBM, we can enhance our understanding of the disease and assist in its treatment. We discovered a similarity in the macrophage composition between the TME and PB, and through association with imaging, we could interpret macrophages. In addition, we identified a predictive biomarker that drew more attention to immune suppression of patients with GBM.

Diagnostic and Prognostic Value of Circulating DNA Fragments in Glioblastoma Multiforme Patients.

Novel blood-circulating molecules, as potential biomarkers for glioblastoma multiforme (GBM) diagnosis and monitoring, are attracting particular attention due to limitations of imaging modalities and invasive tissue biopsy procedures. This study aims to assess the diagnostic and prognostic values of circulating cell-free DNA (cfDNA) in relation to inflammatory status in GBM patients and to determine the concentration and average size of DNA fragments typical of tumour-derived DNA fractions. Preoperative plasma samples from 40 patients (GBM 65.0 ± 11.3 years) and 40 healthy controls (HC 70.4 ± 5.4 years) were compared. The cfDNA concentrations and lengths were measured using the electrophoresis platform, and inflammatory indices (NLR, PLR, LMR, and SII) were calculated from complete blood cell analysis. More fragmented cfDNA and 4-fold higher 50-700 bp cfDNA concentrations were detected in GBM patients than in healthy controls. The average cfDNA size in the GBM group was significantly longer (median 336 bp) than in the HC group (median 271 bp). Optimal threshold values were 1265 pg/µL for 50-700 bp cfDNA (AUC = 0.857) and 290 bp for average cfDNA size (AUC = 0.814). A Kaplan-Meier survival curves analysis also demonstrated a higher mortality risk in the GBM group with a cut-off >303 bp cfDNA. This study is the first to have revealed glioblastoma association with high levels of cfDNA > 1000 pg/µL of 50-700 bp in length, which can be aggravated by immunoinflammatory reactivity.