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Background: We explored the characteristics of single-cell differentiation data in glioblastoma and established prognostic markers based on CRYAB to predict the prognosis of glioblastoma patients. Aberrant expression of CRYAB is associated with invasive behavior in various tumors, including glioblastoma. However, the specific role and mechanisms of CRYAB in glioblastoma are still unclear. Methods: We assessed RNA-seq and microarray data from TCGA and GEO databases, combined with scRNA-seq data on glioma patients from GEO. Utilizing the Seurat R package, we identified distinct survival-related gene clusters in the scRNA-seq data. Prognostic pivotal genes were discovered through single-factor Cox analysis, and a prognostic model was established using LASSO and stepwise regression algorithms. Moreover, we investigated the predictive potential of these genes in the immune microenvironment and their applicability in immunotherapy. Finally, in vitro experiments confirmed the functional significance of the high-risk gene CRYAB. Results: By analyzing the ScRNA-seq data, we identified 28 cell clusters representing seven cell types. After dimensionality reduction and clustering analysis, we obtained four subpopulations within the oligodendrocyte lineage based on their differentiation trajectory. Using CRYAB as a marker gene for the terminal-stage subpopulation, we found that its expression was associated with poor prognosis. In vitro experiments demonstrated that knocking out CRYAB in U87 and LN229 cells reduced cell viability, proliferation, and invasiveness. Conclusion: The risk model based on CRYAB holds promise in accurately predicting glioblastoma. A comprehensive study of the specific mechanisms of CRYAB in glioblastoma would contribute to understanding its response to immunotherapy. Targeting the CRYAB gene may be beneficial for glioblastoma patients. [ABSTRACT FROM AUTHOR]

Human malignant gliomas are the most common and aggressive primary malignant tumors of the human central nervous system. Vasculogenic mimicry (VM), which refers to the formation of a tumor blood supply system independently of endothelial cells, contributes to the malignant progression of glioma. Therefore, VM is considered a potential target for glioma therapy. Accumulated evidence indicates that alterations in SUMOylation, a reversible post-translational modification, are involved in tumorigenesis and progression. In the present study, we found that UBA2 and RALY were upregulated in glioma tissues and cell lines. Downregulation of UBA2 and RALY inhibited the migration, invasion, and VM of glioma cells. RALY can be SUMOylated by conjugation with SUMO1, which is facilitated by the overexpression of UBA2. The SUMOylation of RALY increases its stability, which in turn increases its expression as well as its promoting effect on FOXD1 mRNA. The overexpression of FOXD1 promotes DKK1 transcription by activating its promoter, thereby promoting glioma cell migration, invasion, and VM. Remarkably, the combined knockdown of UBA2, RALY, and FOXD1 resulted in the smallest tumor volumes and the longest survivals of nude mice in vivo. UBA2/RALY/FOXD1/DKK1 axis may play crucial roles in regulating VM in glioma, which may contribute to the development of potential strategies for the treatment of gliomas. [ABSTRACT FROM AUTHOR]

Background: Gliomas are the most common highly aggressive primary malignant brain tumors in adults with different biological behaviors and clinically heterogeneous features. About the extremely poor prognosis of gliomas, the search for potential therapeutic modalities and targets is crucial. Method: We extracted the anoikis-related genes (ARG) from GeneCards and obtained differentially expressed genes in normal and glioma tissues from the GSE4290 dataset to obtain intersect differentially expressed ARG in gliomas by differential analysis. KEGG and GO analyses were used to evaluate the potential pathways and molecular processes of these genes. Based on The Cancer Genome Atlas (TCGA) training cohort, we performed the Least Absolute Shrinkage and Selection Operator (LASSO) regression and Cox regression to construct an ARG prognostic model and validated them in the TCGA testing cohort and the Chinese Glioma Genome Atlas (CGGA) validation cohort. Subsequently, we further explored the differences in clinical characteristics, tumor mutation burden (TMB), and the immune microenvironment in the high- and low-risk groups. Univariate and multifactorial regression analyses and nomogram construction were also performed. Moreover, we evaluated the expression levels of key genes via public databases, qPCR analysis and IHC staining, and further assessed the clinical prognostic value. Results: The regulatory model based on quantitative ARG prognostic models showed that patients in the high-risk group were associated with poorer survival prognosis, poorer clinical characteristics, and higher TMB levels. Moreover, the high-risk group had high levels of immune infiltration and upregulated immune checkpoint gene expression. The ARG prognostic model and the Nomogram showed good predictive performance. Expression and survival analysis of five prognostic ARG signatures (ETV4, HMOX1, MYC, NFE2L2, and UBE2C) showed that these genes have potential prognostic value. Conclusion: Our constructed ARG prognostic risk model provides a potential therapeutic target and theoretical basis for predicting the prognosis of glioma patients and guiding individualized immunotherapy. [ABSTRACT FROM AUTHOR]

Background: Efferocytosis is a biological process in which phagocytes remove apoptotic cells and vesicles from tissues. This process is initiated by the release of inflammatory mediators from apoptotic cells and plays a crucial role in resolving inflammation. The signals associated with efferocytosis have been found to regulate the inflammatory response and the tumor microenvironment (TME), which promotes the immune escape of tumor cells. However, the role of efferocytosis in glioblastoma multiforme (GBM) is not well understood and requires further investigation. Methods: In this study, we conducted a comprehensive analysis of 22 efferocytosis-related genes (ERGs) by searching for studies related to efferocytosis. Using bulk RNA-Seq and single-cell sequencing data, we analyzed the expression and mutational characteristics of these ERGs. By using an unsupervised clustering algorithm, we obtained ERG clusters from 549 GBM patients and evaluated the immune infiltration characteristics of each cluster. We then identified differential genes (DEGs) in the two ERG clusters and classified GBM patients into different gene clusters using univariate cox analysis and unsupervised clustering algorithms. Finally, we utilized the Boruta algorithm to screen for prognostic genes and reduce dimensionality, and the PCA algorithm was applied to create a novel efferocytosis-related scoring system. Results: Differential expression of ERGs in glioma cell lines and normal cells was analyzed by rt-PCR. Cell function experiments, on the other hand, validated TIMD4 as a tumor risk factor in GBM. We found that different ERG clusters and gene clusters have distinct prognostic and immune infiltration profiles. The ERG signature we developed provides insight into the tumor microenvironment of GBM. Patients with lower ERG scores have a better survival rate and a higher likelihood of benefiting from immunotherapy. Conclusions: Our novel efferocytosis-related signature has the potential to be used in clinical practice for risk stratification of GBM patients and for selecting individuals who are likely to respond to immunotherapy. This can help clinicians design appropriate targeted therapies before initiating clinical treatment. [ABSTRACT FROM AUTHOR]

Glioblastoma, the most common and heterogeneous tumor affecting brain parenchyma, is dismally characterized by a very poor prognosis. Thus, the search of new, more effective treatments is a vital need. Here, we will review the druggable epigenetic features of glioblastomas that are, indeed, currently explored in preclinical studies and in clinical trials for the development of more effective, personalized treatments. In detail, we will review the studies that have led to the identification of epigenetic signatures, IDH mutations, MGMT gene methylation, histone modification alterations, H3K27 mutations and epitranscriptome landscapes of glioblastomas, in each case discussing the corresponding targeted therapies and their potential efficacy. Finally, we will emphasize how recent technological improvements permit to routinely investigate many glioblastoma epigenetic biomarkers in clinical practice, further enforcing the hope that personalized drugs, targeting specific epigenetic features, could be in future a therapeutic option for selected patients. [ABSTRACT FROM AUTHOR]

Gliomas are the most aggressive of all brain tumors. In this study, it was found that there is a significant expression of transmembrane-like 131 (TMEM131L) in glioma tissues. The relevance of TMEM131L in the diagnosis and clinical prognosis of GBM and LGG was verified by additional clinical correlation and survival analysis. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve reflected the diagnostic effect of TMEM131L on the clinicopathologic features of glioma. As a unique molecular marker for the poor prognosis of overall survival (OS), PFI, and DSS in patients with GCB and LGG, TMEM131L might be employed, according to time-dependent ROC curves and Kaplan–Meier survival analysis at 1, 3, and 5 years. The potential methylation sites of TMEM131L were selected by correlation analysis between TMEM131L and DNA methylation sites. Meanwhile, TMEM131L was significantly correlated with matrix, immunity, and estimated scores of GBM and LGG. The CIBERSORT analysis revealed a significant correlation between immune checkpoint and infiltration of 22 different kinds of immune cells. Coexpression genes of TMEM131L associated with oxidative stress phenotype were screened by the LASSO logistic regression analysis. Nomogram and calibration curves further confirmed that the prognostic model composed of SYT1, CREB3L3, ITPR1, RASGRF2, PDX1, and RASGRF1 has good stability and potential application value for poor prognosis in patients with glioma. [ABSTRACT FROM AUTHOR]

Background: Glioblastoma (GBM, WHO grade IV) is an aggressive, primary brain tumor. Despite extensive tumor resection followed by radio- and chemotherapy, life expectancy of GBM patients did not improve over decades. Several studies reported transcription deregulation in GBMs, but regulatory mechanisms driving overexpression of GBM-specific genes remain largely unknown. Transcription in open chromatin regions is directed by transcription factors (TFs) that bind to specific motifs, recruit co-activators/repressors and the transcriptional machinery. Identification of GBM-related TFs-gene regulatory networks may reveal new and targetable mechanisms of gliomagenesis. Results: We predicted TFs-regulated networks in GBMs in silico and intersected them with putative TF binding sites identified in the accessible chromatin in human glioma cells and GBM patient samples. The Cancer Genome Atlas and Glioma Atlas datasets (DNA methylation, H3K27 acetylation, transcriptomic profiles) were explored to elucidate TFs-gene regulatory networks and effects of the epigenetic background. In contrast to the majority of tumors, c-Jun expression was higher in GBMs than in normal brain and c-Jun binding sites were found in multiple genes overexpressed in GBMs, including VIM, FOSL2 or UPP1. Binding of c-Jun to the VIM gene promoter was stronger in GBM-derived cells than in cells derived from benign glioma as evidenced by gel shift and supershift assays. Regulatory regions of the majority of c-Jun targets have distinct DNA methylation patterns in GBMs as compared to benign gliomas, suggesting the contribution of DNA methylation to the c-Jun-dependent gene expression. Conclusions: GBM-specific TFs-gene networks identified in GBMs differ from regulatory pathways attributed to benign brain tumors and imply a decisive role of c-Jun in controlling genes that drive glioma growth and invasion as well as a modulatory role of DNA methylation. [ABSTRACT FROM AUTHOR]

Glioblastoma is the most lethal form of brain tumor with a recurrence rate of almost 90% and a survival time of only 15 months post-diagnosis. It is a highly heterogeneous, aggressive, and extensively studied tumor. Multiple studies have proposed therapeutic approaches to mitigate or improve the survival for patients with glioblastoma. In this article, we review the loss of the 5′-methylthioadenosine phosphorylase (MTAP) gene as a potential therapeutic approach for treating glioblastoma. MTAP encodes a metabolic enzyme required for the metabolism of polyamines and purines leading to DNA synthesis. Multiple studies have explored the loss of this gene and have shown its relevance as a therapeutic approach to glioblastoma tumor mitigation; however, other studies show that the loss of MTAP does not have a major impact on the course of the disease. This article reviews the contrasting findings of MTAP loss with regard to mitigating the effects of glioblastoma, and also focuses on multiple aspects of MTAP loss in glioblastoma by providing insights into the known findings and some of the unexplored areas of this field where new approaches can be imagined for novel glioblastoma therapeutics. [ABSTRACT FROM AUTHOR]

DNA methylation is increasingly used for tumour classification and has expanded upon the > 100 currently known brain tumour entities. A correct diagnosis is the basis for suitable treatment for patients with brain tumours, which is the leading cause of cancer-related death in children. DNA methylation profiling is required for diagnosis of certain tumours, and used clinically for paediatric brain tumours in several countries. We therefore evaluated if the methylation-based classification is robust in different locations of the same tumour, and determined how the methylation pattern changed over time to relapse. We sampled 3–7 spatially separated biopsies per patient, and collected samples from paired primary and relapse brain tumours from children. Altogether, 121 samples from 46 paediatric patients with brain tumours were profiled with EPIC methylation arrays. The methylation-based classification was mainly homogeneous for all included tumour types that were successfully classified, which is promising for clinical diagnostics. There were indications of multiple subclasses within tumours and switches in the relapse setting, but not confirmed as the classification scores were below the threshold. Site-specific methylation alterations did occur within the tumours and varied significantly between tumour types for the temporal samples, and as a trend in spatial samples. More alterations were present in high-grade tumours compared to low-grade, and significantly more alterations with longer relapse times. The alterations in the spatial and temporal samples were significantly depleted in CpG islands, exons and transcription start sites, while enriched in OpenSea and regions not affiliated with a gene, suggesting a random location of the alterations in less conserved regions. In conclusion, more DNA methylation changes accumulated over time and more alterations occurred in high-grade tumours. The alterations mainly occurred in regions without gene affiliation, and did not affect the methylation-based classification, which largely remained homogeneous in paediatric brain tumours. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the clinical efficacy of early postoperative intensity-modulated radiotherapy (IMRT) combined with temozolomide chemotherapy in the treatment of patients with malignant glioma. Methods: In this retrospective cohort study 80 patients with glioma surgery admitted to Chengde Central Hospital from January 2019 to January 2021 were selected and divided into two groups according to postoperative treatment: the experimental group and the control group, with 40 cases in each group. Patients in the experimental group received IMRT combined with temozolomide chemotherapy postoperatively, while those in the control group received IMRT alone. The clinical effects of patients were analyzed before treatment and three months after treatment, and the incidence of adverse reactions such as bone marrow suppression, gastrointestinal reactions, fever, and liver dysfunction were analyzed in the two groups within one month after treatment. Before treatment and two months after treatment, MMSE scale, QOL scale and KPS were used to compare the cognitive function and health status of the patients. All patients were followed up for one year after treatment, and the difference of disease progression-free survival and overall survival rate between the two groups was analyzed. Results: The effective rate of the experimental group was 70% after treatment, while that of the control group was 43.3%, with a statistically significant difference (P=0.04). The incidence of adverse reactions was 50% in the experimental group and 40% in the control group, with no statistically significant difference between the two groups (P=0.25). After treatment, MMSE score, QOL score and KPS score of the experimental group were significantly improved compared with those of the control group, with statistically significant differences between the two groups (MMSE score, QOL, P=0.00; KPS, P=0.01). Moreover, the two groups of patients were followed up for one year after treatment. The disease progression-free survival rate of the experimental group was 70% and that of the control group was 47.5%, with a statistically significant difference (P=0.04), and the overall survival rate of the experimental group was significantly higher than that of the control group after treatment, with a statistically significant difference (P=0.03). Conclusion: Early postoperative IMRT combined with temozolomide chemotherapy is an effective treatment regimen for patients with malignant glioma, boasting a variety of advantages such as high efficiency, cognitive function, favorable recovery of health status, significantly improved progression-free survival rate and overall survival rate, and no significant increase in adverse reactions. [ABSTRACT FROM AUTHOR]

Identification of prognostic or predictive molecular markers in glioblastoma resection specimens may lead to strategies for therapy stratification and personalized treatment planning. Here, we analyzed in primary glioblastoma stem cell (pGSC) cultures the mRNA abundances of seven stem cell (MSI1, Notch1, nestin, Sox2, Oct4, FABP7 and ALDH1A3), and three radioresistance or invasion markers (CXCR4, IKCa and BKCa). From these abundances, an mRNA signature was deduced which describes the mesenchymal‐to‐proneural expression profile of an individual GSC culture. To assess its functional significance, we associated the GSC mRNA signature with the clonogenic survival after irradiation with 4 Gy and the fibrin matrix invasion of the GSC cells. In addition, we compared the molecular pGSC mRNA signature with the tumor recurrence pattern and the overall survival of the glioblastoma patients from whom the pGSC cultures were derived. As a result, the molecular pGSC mRNA signature correlated positively with the pGSC radioresistance and matrix invasion capability in vitro. Moreover, patients with a mesenchymal (>median) mRNA signature in their pGSC cultures exhibited predominantly a multifocal tumor recurrence and a significantly (univariate log rank test) shorter overall survival than patients with proneural (≤median mRNA signature) pGSCs. The tumors of the latter recurred predominately unifocally. We conclude that our pGSC cultures induce/select those cell subpopulations of the heterogeneous brain tumor that determine disease progression and therapy outcome. In addition, we further postulate a clinically relevant prognostic/predictive value for the 10 mRNAs‐based mesenchymal‐to‐proneural signature of the GSC subpopulations in glioblastoma. [ABSTRACT FROM AUTHOR]

Background: Lower-grade gliomas (LGGs) are characterized by remarkable genetic heterogeneity and different clinical outcomes. Classification of LGGs is improved by the development of molecular stratification markers including IDH mutation and 1p/19q chromosomal integrity, which are used as a hallmark of survival and therapy sensitivity of LGG patients. However, the reproducibility and sensitivity of the current classification remain ambiguous. This study aimed to construct more accurate risk-stratification approaches. Methods: According to bioinformatics, the sequencing profiles of methylation and transcription and imaging data derived from LGG patients were analyzed and developed predictable risk score and radiomics score. Moreover, the performance of predictable models was further validated. Results: In this study, we determined a cluster of 6 genes that were correlated with IDH mutation/1p19q co-deletion status. Risk score model was calculated based on 6 genes and showed gratifying sensitivity and specificity for survival prediction and therapy response of LGG patients. Furthermore, a radiomics risk score model was established to noninvasively assist judgment of risk score in pre-surgery. Taken together, a predictable nomogram that combined transcriptional signatures and clinical characteristics was established and validated to be preferable to the histopathological classification. Our novel multi-omics nomograms showed a satisfying performance. To establish a user-friendly application, the nomogram was further developed into a web-based platform: https://drw576223193.shinyapps.io/Nomo/ , which could be used as a supporting method in addition to the current histopathological-based classification of gliomas. Conclusions: Our novel multi-omics nomograms showed the satisfying performance of LGG patients and assisted clinicians to draw up individualized clinical management. [ABSTRACT FROM AUTHOR]

Low-grade gliomas (LGG) are heterogeneous, and the current predictive models for LGG are either unsatisfactory or not user-friendly. The objective of this study was to establish a nomogram based on methylation-driven genes, combined with clinicopathological parameters for predicting prognosis in LGG. Differential expression, methylation correlation, and survival analysis were performed in 516 LGG patients using RNA and methylation sequencing data, with accompanying clinicopathological parameters from The Cancer Genome Atlas. LASSO regression was further applied to select optimal prognosis-related genes. The final prognostic nomogram was implemented together with prognostic clinicopathological parameters. The predictive efficiency of the nomogram was internally validated in training and testing groups, and externally validated in the Chinese Glioma Genome Atlas database. Three DNA methylation-driven genes , ARL9, CMYA5 , and STEAP3 , were identified as independent prognostic factors. Together with IDH1 mutation status, age, and sex, the final prognostic nomogram achieved the highest AUC value of 0.930, and demonstrated stable consistency in both internal and external validations. The prognostic nomogram could predict personal survival probabilities for patients with LGG, and serve as a user-friendly tool for prognostic evaluation, optimizing therapeutic regimes, and managing LGG patients. [ABSTRACT FROM AUTHOR]

Glioma is the most malignant and aggressive type of brain tumour with high heterogeneity and mortality. Although some clinicopathological factors have been identified as prognostic biomarkers, the individual variants and risk stratification in patients with lower grade glioma (LGG) have not been fully elucidated. The primary aim of this study was to identify an efficient DNA methylation combination biomarker for risk stratification and prognosis in LGG. We conducted a retrospective cohort study by analysing whole genome DNA methylation data of 646 patients with LGG from the TCGA and GEO database. Cox proportional hazard analysis was carried out to screen and construct biomarker model that predicted overall survival (OS). The Kaplan‐Meier survival curves and time‐dependent ROC were constructed to prove the efficiency of the signature. Then, another independent cohort was used to further validate the finding. A two‐CpG site DNA methylation signature was identified by multivariate Cox proportional hazard analysis. Further analysis indicated that the signature was an independent survival predictor from other clinical factors and exhibited higher predictive accuracy compared with known biomarkers. This signature was significantly correlated with immune‐checkpoint blockade, immunotherapy‐related signatures and ferroptosis regulator genes. The expression pattern and functional analysis showed that these two genes corresponding with two methylation sites contained in the model were correlated with immune infiltration level, and involved in MAPK and Rap1 signalling pathway. The signature may contribute to improve the risk stratification of patients and provide a more accurate assessment for precision medicine in the clinic. [ABSTRACT FROM AUTHOR]

RPP25, a 25 kDa protein subunit of ribonuclease P (RNase P), is a protein-coding gene. Disorders associated with RPP25 include chromosome 15Q24 deletion syndrome and diffuse scleroderma, while systemic sclerosis can be complicated by malignancy. However, the functional role of RPP25 expression in glioblastoma multiforme (GBM) is unclear. In this study, comprehensive bioinformatics analysis was used to evaluate the impact of RPP25 on GBM occurrence and prognosis. Differential analysis of multiple databases showed that RPP25 was commonly highly expressed in multiple cancers but lowly expressed in GBM. Survival prognostic results showed that RPP25 was prognostically relevant in six tumors (CESC, GBM, LAML, LUAD, SKCM, and UVM), but high RPP25 expression was significantly associated with poor patient prognosis except for CESC. Analysis of RPP25 expression in GBM alone revealed that RPP25 was significantly downregulated in GBM compared with normal tissue. Receiver operating characteristic (ROC) combined with Kaplan-Meier (KM) analysis and Cox regression analysis showed that high RPP25 expression was a prognostic risk factor for GBM and had a predictive value for the 1-year, 2-year, and 3-year survival of GBM patients. In addition, the expression of RPP25 was correlated with the level of immune cell infiltration. The gene set enrichment analysis (GSEA) results showed that RPP25 was mainly associated with signalling pathways related to tumor progression and tumor metabolism. [ABSTRACT FROM AUTHOR]