Prognosis Of Glioma Research Articles

Multicenter integration analysis of TRP channels revealed potential mechanisms of immunosuppressive microenvironment activation and identified a machine learning-derived signature for improving outcomes in gliomas.

This study aimed to explore the mechanisms of transient receptor potential (TRP) channels on the immune microenvironment and develop a TRP-related signature for predicting prognosis, immunotherapy response, and drug sensitivity in gliomas. Based on the unsupervised clustering algorithm, we identified novel TRP channel clusters and investigated their biological function, immune microenvironment, and genomic heterogeneity. Invitro and invivo experiments revealed the association between TRPV2 and macrophages. Subsequently, based on 96 machine learning algorithms and six independent glioma cohorts, we constructed a machine learning-based TRP channel signature (MLTS). The performance of the MLTS in predicting prognosis, immunotherapy response, and drug sensitivity was evaluated. Patients with high expression levels of TRP channel genes had worse prognoses, higher tumor mutation burden, and more activated immunosuppressive microenvironment. Meanwhile, TRPV2 was identified as the most essential regulator in TRP channels. TRPV2 activation could promote macrophages migration toward malignant cells and alleviate glioma prognosis. Furthermore, MLTS could work independently of common clinical features and present stable and superior prediction performance. This study investigated the comprehensive effect of TRP channel genes in gliomas and provided a promising tool for designing effective, precise treatment strategies.

NDC80/HEC1 promotes macrophage polarization and predicts glioma prognosis via single-cell RNA-seq and invitro experiment.

Glioma is the most frequent and lethal form of primary brain tumor. The molecular mechanism of oncogenesis and progression of glioma still remains unclear, rendering the therapeutic effect of conventional radiotherapy, chemotherapy, and surgical resection insufficient. In this study, we sought to explore the function of HEC1 (highly expressed in cancer 1)in glioma; a component of the NDC80 complex in glioma is crucial in the regulation of kinetochore. Bulk RNA and scRNA-seq analyses were used to infer HEC1 function, and invitro experiments validated its function. HEC1 overexpression was observed in glioma and was indicative of poor prognosis and malignant clinical features, which was confirmed in human glioma tissues. High HEC1 expression was correlated with more active cell cycle, DNA-associated activities, and the formation of immunosuppressive tumor microenvironment, including interaction with immune cells, and correlated strongly with infiltrating immune cells and enhanced expression of immune checkpoints. Invitro experiments and RNA-seq further confirmed the role of HEC1 in promoting cell proliferation, and the expression of DNA replication and repair pathways in glioma. Coculture assay confirmed that HEC1 promotes microglial migration and the transformation of M1 phenotype macrophage to M2 phenotype. Altogether, these findings demonstrate that HEC1 may be a potential prognostic marker and an immunotherapeutic target in glioma.

WZ-3146 acts as a novel small molecule inhibitor of KIF4A to inhibit glioma progression by inducing apoptosis

BackgroundGlioma is considered the most common primary malignant tumor of the central nervous system. Although traditional treatments have not achieved satisfactory outcomes, recently, targeted therapies for glioma have shown promising efficacy. However, due to the single-target nature of targeted therapy, traditional targeted therapies are ineffective; thus, novel therapeutic targets are urgently needed.MethodsThe gene expression data for glioma patients were derived from the GEO (GSE4290, GSE50161), TCGA and CGGA databases. Next, the upregulated genes obtained from the above databases were cross-analyzed, finally, 10 overlapping genes (BIRC5, FOXM1, EZH2, CDK1, KIF11, KIF4A, NDC80, PBK, RRM2, and TOP2A) were ultimately screened and only KIF4A expression has the strongest correlation with clinical characteristics in glioma patients. Futher, the TCGA and CGGA database were utilized to explore the correlation of KIF4A expression with glioma prognosis. Then, qRT-PCR and Western blot was used to detect the KIF4A mRNA and protein expression level in glioma cells, respectively. And WZ-3146, the small molecule inhibitor targeting KIF4A, were screened by Cmap analysis. Subsequently, the effect of KIF4A knockdown or WZ-3146 treatment on glioma was measured by the MTT, EdU, Colony formation assay and Transwell assay. Ultimately, GSEA enrichment analysis was performed to find that the apoptotic pathway could be regulated by KIF4A in glioma, in addition, the effect of WZ-3146 on glioma apoptosis was detected by flow cytometry and Western blot.ResultsIn the present study, we confirmed that KIF4A is abnormally overexpressed in glioma. In addition, KIF4A overexpression is a key indicator of glioma prognosis; moreover, suppressing KIF4A expression can inhibit glioma progression. We also discovered that WZ-3146, a small molecule inhibitor of KIF4A, can induce apoptosis in glioma cells and exhibit antiglioma effects.ConclusionIn conclusion, these observations demonstrated that targeting KIF4A can inhibit glioma progression. With further research, WZ-3146, a small molecule inhibitor of KIF4A, could be combined with other molecular targeted drugs to cooperatively inhibit glioma progression.

Single-cell transcriptomic analysis identifies downregulated phosphodiesterase 8B as a novel oncogene in IDH-mutant glioma.

Glioma, a prevalent and deadly brain tumor, is marked by significant cellular heterogeneity and metabolic alterations. However, the comprehensive cell-of-origin and metabolic landscape in high-grade (Glioblastoma Multiforme, WHO grade IV) and low-grade (Oligoastrocytoma, WHO grade II) gliomas remains elusive. In this study, we undertook single-cell transcriptome sequencing of these glioma grades to elucidate their cellular and metabolic distinctions. Following the identification of cell types, we compared metabolic pathway activities and gene expressions between high-grade and low-grade gliomas. Notably, astrocytes and oligodendrocyte progenitor cells (OPCs) exhibited the most substantial differences in both metabolic pathways and gene expression, indicative of their distinct origins. The comprehensive analysis identified the most altered metabolic pathways (MCPs) and genes across all cell types, which were further validated against TCGA and CGGA datasets for clinical relevance. Crucially, the metabolic enzyme phosphodiesterase 8B (PDE8B) was found to be exclusively expressed and progressively downregulated in astrocytes and OPCs in higher-grade gliomas. This decreased expression identifies PDE8B as a metabolism-related oncogene in IDH-mutant glioma, marking its dual role as both a protective marker for glioma grading and prognosis and as a facilitator in glioma progression.

Pan-cancer multi-omics analysis of PTBP1 reveals it as an inflammatory, progressive and prognostic marker in glioma

PTBP1 is an oncogene that regulates the splicing of precursor mRNA. However, the relationship between PTBP1 expression and gene methylation, cancer prognosis, and tumor microenvironment remains unclear. The expression profiles of PTBP1 across various cancers were derived from the TCGA, as well as the GTEx and CGGA databases. The CGGA mRNA_325, CGGA mRNA_301, and CGGA mRNA_693 datasets were utilized as validation cohorts. Immune cell infiltration scores were approximated using the TIMER 2.0 tool. Functional enrichment analysis for groups with high and low PTBP1 expression was conducted using Gene Set Enrichment Analysis (GSEA). Methylation data were predominantly sourced from the SMART and Mexpress databases. Linked-omics analysis was employed to perform functional enrichment analysis of genes related to PTBP1 methylation, as well as to conduct protein functional enrichment analysis. Single-cell transcriptome analysis and spatial transcriptome analysis were carried out using Seurat version 4.10. Compared to normal tissues, PTBP1 is significantly overexpressed and hypomethylated in various cancers. It is implicated in prognosis, immune cell infiltration, immune checkpoint expression, genomic variation, tumor neoantigen load, and tumor mutational burden across a spectrum of cancers, with particularly notable effects in low-grade gliomas. In the context of gliomas, PTBP1 expression correlates with WHO grade and IDH1 mutation status. PTBP1 expression and methylation play an important role in a variety of cancers. PTBP1 can be used as a marker of inflammation, progression and prognosis in gliomas.

DIPG-25. RELATIONSHIP BETWEEN MOLECULAR CLASSIFICATION, ORIGIN AND PROGNOSIS IN DIFFUSE MALIGNANT GLIOMA IN CHILDREN

Abstract INTRODUCTION Diffuse malignant gliomas that occurs in childhood is recognized as a biologically different disease from that in adults. Furthermore, with the recent development of molecular diagnostics, diffuse midline glioma (DMG), which occurs mainly in the thalamus and brainstem, frequently occurs in childhood and have poor prognosis. We report the relationship between imaging findings, origin, and prognosis of diffuse malignant glioma in children or young adult based on our case series. PATIENTS AND METHODS 43 cases of malignant glioma that occurred from childhood to young adult (below 30 years old) and were treated at our hospital since 2004 were registered in the analysis. Of the 42 cases, 24 cases were in brain stem, 11 cases in cerebral hemisphere, 6 cases in thalamus, and 1 case in cerebellar hemisphere. Histological diagnosis was possible in 31 cases, but without histological verification in 11 brain stem lesions. Histological diagnosis included 13 high-grade glioma (GBM, including NOS and G34R mutations), 11 DMG, and 7 anaplastic astrocytoma. RESULTS Of 13 cases of hemispheric high-grade gliomas, 2 cases had long-term survival (both cases received WT1 peptide vaccination), and 1 case survived for more than 5 years (total resection, MGMT methylation). Among the DMGs, 7 cases were found in brain stem (5 pons, 2 pontomedullary junction, 1 cerebellar peduncle, and 1 midbrain), 3 cases in the thalamus. Two cases of onset at the pontomedullary junction were found incidentally, and the symptoms gradually increased during follow-up, and multidisciplinary treatment was performed. Bilateral thalamus DMG with HIST1H3B mutation showed slowly growing and invasion. SUMMARY There were cases of pediatric hemisphere glioblastoma with long-term survival. In addition, the origin and imaging findings of DMG were various, and tumors that originate at the pontomedullary junction may be relatively favorable.

The molecular signature and prognosis of glioma with preoperative intratumoral hemorrhage: a retrospective cohort analysis

BackgroundIntratumoral hemorrhage, though less common, could be the first clinical manifestation of glioma and is detectable via MRI; however, its exact impacts on patient outcomes remain unclear and controversial. The 2021 WHO CNS 5 classification emphasised genetic and molecular features, initiating the necessity to establish the correlation between hemorrhage and molecular alterations. This study aims to determine the prevalence of intratumoral hemorrhage in glioma subtypes and identify associated molecular and clinical characteristics to improve patient management.MethodsIntegrated clinical data and imaging studies of patients who underwent surgery at the Department of Neurosurgery at Peking Union Medical College Hospital from January 2011 to January 2022 with pathological confirmation of glioma were retrospectively reviewed. Patients were divided into hemorrhage and non-hemorrhage groups based on preoperative magnetic resonance imaging. A comparison and survival analysis were conducted with the two groups. In terms of subgroup analysis, we classified patients into astrocytoma, IDH-mutant; oligodendroglioma, IDH-mutant, 1p/19q-codeleted; glioblastoma, IDH-wildtype; pediatric-type gliomas; or circumscribed glioma using integrated histological and molecular characteristics, according to WHO CNS 5 classifications.Results457 patients were enrolled in the analysis, including 67 (14.7%) patients with intratumoral hemorrhage. The hemorrhage group was significantly older and had worse preoperative Karnofsky performance scores. The hemorrhage group had a higher occurrence of neurological impairment and a higher Ki-67 index. Molecular analysis indicated that CDKN2B, KMT5B, and PIK3CA alteration occurred more in the hemorrhage group (CDKN2B, 84.4% vs. 62.2%, p = 0.029; KMT5B, 25.0% vs. 8.9%, p = 0.029; and PIK3CA, 81.3% vs. 58.5%, p = 0.029). Survival analysis showed significantly worse prognoses for the hemorrhage group (hemorrhage 18.4 months vs. non-hemorrhage 39.1 months, p = 0.01). In subgroup analysis, the multivariate analysis showed that intra-tumoral hemorrhage is an independent risk factor only in glioblastoma, IDH-wildtype (162 cases of 457 overall, HR = 1.72, p = 0.026), but not in other types of gliomas. The molecular alteration of CDK6 (hemorrhage group p = 0.004, non-hemorrhage group p < 0.001), EGFR (hemorrhage group p = 0.003, non-hemorrhage group p = 0.001), and FGFR2 (hemorrhage group p = 0.007, non-hemorrhage group p = 0.001) was associated with shorter overall survival time in both hemorrhage and non-hemorrhage groups.ConclusionsGlioma patients with preoperative intratumoral hemorrhage had unfavorable prognoses compared to their nonhemorrhage counterparts. CDKN2B, KMT5B, and PIK3CA alterations were associated with an increased occurrence of intratumoral hemorrhage, which might be future targets for further investigation of intratumoral hemorrhage.

Clinical outcome, radiological findings, and genetic features of IDH-mutant brainstem glioma in adults.

With the recent advent of genetic testing, IDH-mutant glioma has been found among adult brainstem gliomas. However, the clinical outcome and prognosis of IDH-mutant brainstem gliomas in adults have not been elucidated. This study aimed to investigate the clinical outcome, radiological findings, and genetic features of adult patients with IDH-mutant diffuse brainstem gliomas. Data from adult patients with brainstem glioma at Hokkaido University Hospital between 2006 and 2022 were retrospectively analyzed. Patient characteristics, treatment methods, genetic features, and prognosis were evaluated. Of 12 patients with brainstem glioma with proven histopathology, 4 were identified with IDH mutation. All patients underwent local radiotherapy with 54 Gray in 27 fractions combined with chemotherapy with temozolomide. Three patients had IDH1 R132H mutation and one had IDH2 R172G mutation. The median progression-free survival and overall survival were 68.4months and 85.2months, respectively, longer than that for IDH-wildtype gliomas (5.6months and 12.0months, respectively). At the time of initial onset, contrast-enhanced lesions were observed in two of the four cases in magnetic resonance imaging. As some adult brainstem gliomas have IDH mutations, and a clearly different prognosis from those with IDH-wildtype, biopsies are proactively considered to confirm the genotype.

Survival rate of patient with glioblastoma: a population-based study

IntroductionGlioblastoma, as the most common and lethal primary malignant brain tumor, has estimated mean survival of 15 months. GBM is reported more in men. Malignant glioma is the cause of 2.5% of cancer deaths. The standard therapy for patients with newly diagnosed GBM includes tumor resection surgeries, followed by radiotherapy and chemotherapy. The prognosis of glioma is a major challenge, and the outcome of GBM has remained almost unchanged for past years. The present study aimed to determine patient survival.MethodsPatients with glioblastoma tumors who visited Al-Zahra and Kashani hospitals from 2013 to 2021 were included in this study. All patients were classified with morphological codes according to the International Classification of Diseases for Oncology. The patients’ information was recorded in the checklist, and then, the patients were followed up by phone. The data were measured regarding age, gender, exposure to chemicals, body mass index (BMI), and survival from the patient's surgery to death. Several questions were asked from the families of deceased patients and survivors based on the KPS Status Scale. Finally, the sample was analyzed with SPSS version 26.ResultThe patient's mean age was 51.93 years, and the male–female ratio was 1:1.7. The patients' mean overall survival was 29 months and a total of 9 patients survived. There was a significant difference between the age groups in terms of 1-year survival so that more deaths were observed in the age group of more than 50 years. The mean tumor size was 5.2 ± 2.1 cm. The survival analysis indicated that the temporal lobe was more than the other in 2-year survival. The most common symptom of patients before surgery was headache (31.8%) followed by motor dysfunction. The 1-year, 2-year, 5-year, and overall survival of the patients was 4.5%, 18.38%, 37.13%, and 33.68%, respectively.ConclusionsThe results of the present study indicated that the patients' survival improved over time with the advancement of adjuvant therapies. Therefore, if patients care get better for the first year after surgery, their survival will improve from the second year after the operation.

Multi-omics Analysis Revealed that the CCN Family Regulates Cell Crosstalk, Extracellular Matrix, and Immune Escape, Leading to a Poor Prognosis of Glioma.

The CCN family is a group of matricellular proteins associated with the extracellular matrix. This study aims to explore the role of the CCN family in glioma development and its implications in the tumor microenvironment. Through analysis of bulk RNA-seq cohorts, correlations between CCN family expression and glioma subtypes, patient survival, and bioactive pathway enrichment were investigated. Additionally, single-cell datasets were employed to identify novel cell subgroups, followed by analyses of cell communication and transcription factors. Spatial transcriptomic analysis was utilized to validate the CCN family's involvement in glioma. Results indicate overexpression of CYR61,CTGF, and WISP1 in glioma, associated with unfavorable subtypes and reduced survival. Enrichment analyses revealed associations with oncogenic pathways, while CTGF and WISP1 expression correlated with increased infiltration of regulatory T cells and M2 macrophages. Single-cell analysis identified MES-like cells as the highest CCN expression. Moreover, intercellular signal transduction analysis demonstrated active pathways, including SPP1-CD44, in cell subgroups with elevated CYR61 and CTGF expression. Spatial transcriptomic analysis confirmed co-localization of CYR61,CTGF and SPP1-CD44 with high oncogenic pathway activity. These findings suggest that CCN family members may serve as potential prognostic biomarkers and therapeutic targets for glioma.

The Promise of Tumor Mutation Burden and Microenvironment as Biomarkers in Glioma Treatment

Gliomas, particularly high-grade gliomas like glioblastomas, represent some of the most formidable challenges in oncology. These brain tumors are notorious for their resistance to conventional therapies, including surgery, chemotherapy, and radiation. The recent systematic review and meta-analysis protocol offers a promising direction by focusing on Tumor Mutation Burden (TMB) and Tumor Microenvironment (TME) as potential biomarkers for treatment outcomes and prognosis in gliomas.

A cuproptosis-related gene DLAT as a novel prognostic marker and its relevance to immune infiltration in low-grade gliomas

DLAT has been recognized as a cuproptosis-related gene that is crucial for cuproptosis in earlier research. The study is to look at how DLAT affects individuals with low-grade glioma's prognosis and immune infiltration. The Genotype-Tissue Expression (GTEx) database and the TCGA database were used in this work to download RNAseq data in TPM format. DLAT was found to be overexpressed in LGG by comparing DLAT expression levels between LGG and normal brain tissue, and the expression of DLAT was verified by immunohistochemistry and semi-quantitative analysis. Then, the functional enrichment analysis revealed that the biological functional pathways and possible signal transduction pathways involved were primarily focused on extracellular matrix organization, transmembrane transporter complex, ion channel complex, channel activity, neuroactive ligand-receptor interaction, complement and coagulation cascades, and channel activity. The level of immune cell infiltration by plasmacytoid dendritic cells and CD8 T cells was subsequently evaluated using single-sample gene set enrichment analysis, which showed that high DLAT expression was inversely connected with that level of infiltration. The link between the methylation and mRNA transcription of DLAT was then further investigated via the MethSurv database, and the results showed that DLAT's hypomethylation status was linked to a poor outcome. Finally, by evaluating the prognostic value of DLAT using the Cox regression analysis and Kaplan-Meier technique, a column line graph was created to forecast the overall survival (OS) rate at 1, 3, and 5 years after LGG identification. The aforementioned results demonstrated that high DLAT expression significantly decreased OS and DSS, and that overexpression of DLAT in LGG was significantly linked with WHO grade, IDH status, primary therapy outcome, overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) events. DLAT was discovered as a separate predictive sign of OS in the end. DLAT might thus represent a brand-new predictive biomarker.

Machine learning‐based identification of a cell death‐related signature associated with prognosis and immune infiltration in glioma

AbstractAccumulating evidence suggests that a wide variety of cell deaths are deeply involved in cancer immunity. However, their roles in glioma have not been explored. We employed a logistic regression model with the shrinkage regularization operator (LASSO) Cox combined with seven machine learning algorithms to analyse the patterns of cell death (including cuproptosis, ferroptosis, pyroptosis, apoptosis and necrosis) in The Cancer Genome Atlas (TCGA) cohort. The performance of the nomogram was assessed through the use of receiver operating characteristic (ROC) curves and calibration curves. Cell‐type identification was estimated by using the cell‐type identification by estimating relative subsets of known RNA transcripts (CIBERSORT) and single sample gene set enrichment analysis methods. Hub genes associated with the prognostic model were screened through machine learning techniques. The expression pattern and clinical significance of MYD88 were investigated via immunohistochemistry (IHC). The cell death score represents an independent prognostic factor for poor outcomes in glioma patients and has a distinctly superior accuracy to that of 10 published signatures. The nomogram performed well in predicting outcomes according to time‐dependent ROC and calibration plots. In addition, a high‐risk score was significantly related to high expression of immune checkpoint molecules and dense infiltration of protumor cells, these findings were associated with a cell death‐based prognostic model. Upregulated MYD88 expression was associated with malignant phenotypes and undesirable prognoses according to the IHC. Furthermore, high MYD88 expression was associated with poor clinical outcomes and was positively related to CD163, PD‐L1 and vimentin expression in the in‐horse cohort. The cell death score provides a precise stratification and immune status for glioma. MYD88 was found to be an outstanding representative that might play an important role in glioma.

Mitochondrial RNA modification-based signature to predict prognosis of lower grade glioma: a multi-omics exploration and verification study

Mitochondrial RNA modification (MRM) plays a crucial role in regulating the expression of key mitochondrial genes and promoting tumor metastasis. Despite its significance, comprehensive studies on MRM in lower grade gliomas (LGGs) remain unknown. Single-cell RNA-seq data (GSE89567) was used to evaluate the distribution functional status, and correlation of MRM-related genes in different cell types of LGG microenvironment. We developed an MRM scoring system by selecting potential MRM-related genes using LASSO regression analysis and the Random Survival Forest algorithm, based on multiple bulk RNA-seq datasets from TCGA, CGGA, GSE16011, and E-MTAB-3892. Analysis was performed on prognostic and immunological features, signaling pathways, metabolism, somatic mutations and copy number variations (CNVs), treatment responses, and forecasting of potential small-molecule agents. A total of 35 MRM-related genes were selected from the literature. Differential expression analysis of 1120 normal brain tissues and 529 LGGs revealed that 22 and 10 genes were upregulated and downregulated, respectively. Most genes were associated with prognosis of LGG. METLL8, METLL2A, TRMT112, and METTL2B were extensively expressed in all cell types and different cell cycle of each cell type. Almost all cell types had clusters related to mitochondrial RNA processing, ribosome biogenesis, or oxidative phosphorylation. Cell–cell communication and Pearson correlation analyses indicated that MRM may promoting the development of microenvironment beneficial to malignant progression via modulating NCMA signaling pathway and ICP expression. A total of 11 and 9 MRM-related genes were observed by LASSO and the RSF algorithm, respectively, and finally 6 MRM-related genes were used to establish MRM scoring system (TRMT2B, TRMT11, METTL6, METTL8, TRMT6, and TRUB2). The six MRM-related genes were then validated by qPCR in glioma and normal tissues. MRM score can predict the malignant clinical characteristics, abundance of immune infiltration, gene variation, clinical outcome, the enrichment of signaling pathways and metabolism. In vitro experiments demonstrated that silencing METTL8 significantly curbs glioma cell proliferation and enhances apoptosis. Patients with a high MRM score showed a better response to immunotherapies and small-molecule agents such as arachidonyl trifluoromethyl ketone, MS.275, AH.6809, tacrolimus, and TTNPB. These novel insights into the biological impacts of MRM within the glioma microenvironment underscore its potential as a target for developing precise therapies, including immunotherapeutic approaches.

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

Low-grade gliomas (LGG) are common brain tumors with high mortality rates. Cancer cell invasion is a significant factor in tumor metastasis. Novel biomarkers are urgently needed to predict LGG prognosis effectively. The data for LGG were obtained from the Bioinformatics database. A consensus clustering analysis was performed to identify molecular subtypes linked with invasion in LGG. Differential expression analysis was performed to identify differentially expressed genes (DEGs) between the identified clusters. Enrichment analyses were then conducted to explore the function for DEGs. Prognostic signatures were placed, and their predictive power was assessed. Furthermore, the invasion-related prognostic signature was validated using the CGGA dataset. Subsequently, clinical specimens were procured in order to validate the expression levels of the distinct genes examined in this research, and to further explore the impact of these genes on the glioma cell line LN229 and HS-683. Two invasion-related molecular subtypes of LGG were identified, and we sifted 163 DEGs between them. The enrichment analyses indicated that DEGs are mainly related to pattern specification process. Subsequently, 10 signature genes (IGF2BP2, SRY, CHI3L1, IGF2BP3, MEOX2, ABCC3, HOXC4, OTP, METTL7B, and EMILIN3) were sifted out to construct a risk model. Besides, the survival (OS) in the high-risk group was lower. The performance of the risk model was verified. Furthermore, a highly reliable nomogram was generated. Cellular experiments revealed the ability to promote cell viability, value-addedness, migratory ability, invasive ability, and colony-forming ability of the glioma cell line LN229 and HS-683. The qRT-PCR analysis of clinical glioma samples showed that these 10 genes were expressed at higher levels in high-grade gliomas than in low-grade gliomas, suggesting that these genes are associated with poor prognosis of gliomas. Our study sifted out ten invasion-related biomarkers of LGG, providing a reference for treatments and prognostic prediction in LGG.

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

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

A novel lateral myelotomy approach for the treatment of lateral or ventrolateral spinal gliomas.

To describe a novel surgical approach in which myelotomy was performed lateral to the dorsal root entry zone (LDREZ), for the treatment of lateral or ventrolateral spinal intramedullary glioma. This study reviewed six patients with lateral or ventrolateral spinal intramedullary glioma who received surgical treatments by using myelotomy technique of LDREZ approach. The patient's clinical characteristics, magnetic resonance imaging (MRI) results, and follow-up outcomes were analyzed. The neurological function of patients before and after operation was assessed based on the Frankel scale system. The anatomical feasibility, surgical techniques, advantages and disadvantages of LDREZ approach were analyzed. Myelotomy technique of LDREZ approach was employed in all 6 patients. Gross total resections were achieved in 4 patients, and 2 patients with astrocytoma (case 2, 6) underwent partial removal. The perioperative recovery was all smooth and all the patients were discharged on schedule. All the patients who suffered from neuropathic pain were relieved. After surgery, neurological function remained unchanged in 3 patients. 2 patients improved from Frankel grade B to C, and 1 patient deteriorated from Frankel grade D to C immediately after surgery and returned to Frankel grade D at 3 months follow-up. Regarding to the poor prognosis of high-grade glioma, the two cases with WHO IV glioma didn't achieve long survival. LDREZ approach is feasible and safe for the surgical removal of lateral or ventrolateral spinal gliomas. This approach can provide a direct pathway to lateral or ventrolateral spinal gliomas with minimal damage to normal spinal cord.

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

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. 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). 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-β, 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. 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.

Accurate and rapid molecular subgrouping of high-grade glioma via deep learning-assisted label-free fiber-optic Raman spectroscopy.

Molecular genetics is highly related with prognosis of high-grade glioma. Accordingly, the latest WHO guideline recommends that molecular subgroups of the genes, including IDH, 1p/19q, MGMT, TERT, EGFR, Chromosome 7/10, CDKN2A/B, need to be detected to better classify glioma and guide surgery and treatment. Unfortunately, there is no preoperative or intraoperative technology available for accurate and comprehensive molecular subgrouping of glioma. Here, we develop a deep learning-assisted fiber-optic Raman diagnostic platform for accurate and rapid molecular subgrouping of high-grade glioma. Specifically, a total of 2,354 fingerprint Raman spectra was obtained from 743 tissue sites (astrocytoma: 151; oligodendroglioma: 150; glioblastoma (GBM): 442) of 44 high-grade glioma patients. The convolutional neural networks (ResNet) model was then established and optimized for molecular subgrouping. The mean area under receiver operating characteristic curves (AUC) for identifying the molecular subgroups of high-grade glioma reached 0.904, with mean sensitivity of 83.3%, mean specificity of 85.0%, mean accuracy of 83.3%, and mean time expense of 10.6 s. The diagnosis performance using ResNet model was shown to be superior to PCA-SVM and UMAP models, suggesting that high dimensional information from Raman spectra would be helpful. In addition, for the molecular subgroups of GBM, the mean AUC reached 0.932, with mean sensitivity of 87.8%, mean specificity of 83.6%, and mean accuracy of 84.1%. Furthermore, according to saliency maps, the specific Raman features corresponding to tumor-associated biomolecules (e.g. nucleic acid, tyrosine, tryptophan, cholesteryl ester, fatty acid, and collagen) were found to contribute to the accurate molecular subgrouping. Collectively, this study opens up new opportunities for accurate and rapid molecular subgrouping of high-grade glioma, which would assist optimal surgical resection and instant post-operative decision-making.

CLEC7A regulates M2 macrophages to suppress the immune microenvironment and implies poorer prognosis of glioma.

Gliomas constitute a category of malignant tumors originating from brain tissue, representing the majority of intracranial malignancies. Previous research has demonstrated the pivotal role of CLEC7A in the progression of various cancers, yet its specific implications within gliomas remain elusive. The primary objective of this study was to investigate the prognostic significance and immune therapeutic potential of CLEC7A in gliomas through the integration of bioinformatics and clinical pathological analyses. This investigation involved examining and validating the relationship between CLEC7A and glioma using samples from Hospital, along with data from TCGA, GEO, GTEx, and CGGA datasets. Subsequently, we explored its prognostic value, biological functions, expression location, and impact on immune cells within gliomas. Finally, we investigated its potential impact on the chemotaxis and polarization of macrophages. The expression of CLEC7A is upregulated in gliomas, and its levels escalate with the malignancy of tumors, establishing it as an independent prognostic factor. Functional enrichment analysis revealed a significant correlation between CLEC7A and immune function. Subsequent examination of immune cell differential expression demonstrated a robust association between CLEC7A and M2 macrophages. This conclusion was further substantiated through single-cell analysis, immunofluorescence, and correlation studies. Finally, the knockout of CLEC7A in M2 macrophages resulted in a noteworthy reduction in macrophage chemotaxis and polarization factors. CLEC7A expression is intricately linked to the pathology and molecular characteristics of gliomas, establishing its role as an independent prognostic factor for gliomas and influencing macrophage function. It could be a promising target for immunotherapy in gliomas.