Genes In Glioma Research Articles

Expression analysis of human glioma susceptibility gene and P53 in human glioma and its clinical significance based on bioinformatics.

The exact mechanism of glioblastoma multiforme (GBM) remains unclear. This study was to clarify the expression of P53 in glioma and its molecular mechanism, and to explore the possibility of P53 as a potential therapeutic target of glioma and its clinical application value, so as to provide a new theoretical basis for the treatment of glioma. Firstly, a dataset was established to analyze the expression of P53 in different stages of glioma and its relationship with prognosis by using The Cancer Genome Atlas (TCGA) database, RNA-seq data, and survival data of glioma and normal control samples in gene expression profiling and interactive analysis (GEPIA). The genes co-expressed with P53 were screened out, their differential expression between glioma and normal control group was analyzed, and their functions were analyzed by enrichment analysis. The TGGA database was used for data verification and analysis. The correlation between P53 expression and clinicopathological parameters was analyzed. Kaplan-Meier survival analysis was used to analyze the relationship between P53 expression and overall survival (OS) and progression-free survival (PFS) of glioma patients, and Cox regression analysis was used to analyze the independent factors affecting OS and PFS of glioma patients. The results of TCGA data analysis were as follows: The expression level of P53 was different from that of different stages of glioma, namely, the expression level of P53 between grade II and grade III, grade III and grade IV, and grade II and grade IV were significantly different (P<0.05). The results of P53 gene-related survival analysis showed that KNL1 high expression and low expression were significantly different in OS, and the high expression group was associated with poor prognosis (P<0.05). The P53 expression can be an effective biological indicator of poor prognosis of glioma.

T cell exhaustion assessment algorism in tumor microenvironment predicted clinical outcomes and immunotherapy effects in glioma.

Despite the recent increase in the use of immune checkpoint blockade (ICB), no ICB medications have been approved or are undergoing large-scale clinical trials for glioma. T cells, the main mediators of adaptive immunity, are important components of the tumor immune microenvironment. Depletion of T cells in tumors plays a key role in assessing the sensitivity of patients to immunotherapy. In this study, the bioinformatics approach was applied to construct T cell depletion-related risk assessment to investigate the impact of T cell depletion on prognosis and ICB response in glioma patients. The Cancer Genome Atlas (TCGA) and GSE108474 glioma cohorts and IMvigor210 immunotherapy datasets were collected, including complete mRNA expression profiles and clinical information. We used cell lines to verify the gene expression and the R 3.6.3 tool and GraphPad for bioinformatics analysis and mapping. T cell depletion in glioma patients displayed significant heterogeneity. The T cell depletion-related prognostic model was developed based on seven prognostic genes (HSPB1, HOXD10, HOXA5, SEC61G, H19, ANXA2P2, HOXC10) in glioma. The overall survival of patients with a high TEXScore was significantly lower than that of patients with a low TEXScore. In addition, high TEXScore scores were followed by intense immune responses and a more complex tumor immune microenvironment. The "hot tumors" were predominantly enriched in the high-risk group, which patients expressed high levels of suppressive immune checkpoints, such as PD1, PD-L1, and TIM3. However, patients with a low TEXScore had a more significant clinical response to immunotherapy. In addition, HSPB1 expression was higher in the U251 cells than in the normal HEB cells. In conclusion, the TEXScore related to T cell exhaustion combined with other pathological profiles can effectively assess the clinical status of glioma patients. The TEXScore constructed in this study enables the effective assessment of the immunotherapy response of glioma patients and provides therapeutic possibilities.

Bioinformatics analysis identified RGS4 as a potential tumor promoter in glioma.

Gliomas is the most common type of intracranial primary malignant tumor and it accounts for ∼80% of primary malignant tumors of the central nervous system. At present, surgical resection with adjuvant radiotherapy and temozolomide adjuvant chemotherapy combined with radiotherapy are the only standard treatments for glioma. However, but overall survival of patients is only 15 months. Glioma is resistant to radiotherapy and chemotherapy, and this malignant behavior leads to a high recurrence rate. Therefore, the use of therapeutics is usually ineffective. As a result, patients with glioma do not significantly benefit from standard treatment. There is therefore an urgent need to develop novel diagnostic approaches and, in particular, more effective treatment strategies. The application of gene expression microarrays provides a feasible and effective way to study gliomas. The present study therefore aimed to identify the key protein-coding genes of glioma using bioinformatics methods and thereby search, for novel biomarkers and therapeutic targets for the treatment of glioma. First, mRNA microarray datasets were selected and obtained from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) between gliomas and normal tissues. The DEGs were clarified using Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), Protein-Protein Interaction (PPI) network and statistical analysis. Subsequently, reverse transcription-quantitative PCR (RT-qPCR)and western blot were used to verify the results of the bioinformatics analysis. A total of 400 DEGs were identified in glioma and they were enriched in several cancer-related GO and KEGG pathways. In the PPI network, it was observed that G-protein signal regulatory protein 4 (RGS4), thymidine phosphorylase, collagen type VI alpha-1, Src homology 2 domain-containing transforming protein1(SHC1) and ring finger protein 135 exhibited a strong protein-protein interaction. Furthermore, . Subsequently, brain damaged tissues and glioma cell lines were selected for RT-qPCR and western blotting analysis. The results demonstrated that RGS4 was highly expressed in glioma cell lines. In conclusion, RGS4 may be a key protein-coding gene in glioma. RGS4 should therefore be studied further to verify its feasibility and effectiveness as a potential glioma biomarker and therapeutic target.

High levels of TIMP1 are associated with increased extracellular matrix stiffness in isocitrate dehydrogenase 1-wild type gliomas

Glioma progression is accompanied with increased tumor tissue stiffness, yet the underlying mechanisms are unclear. Herein, we employed atomic force microscopy analysis to show that tissue stiffness was higher in isocitrate dehydrogenase (IDH)-wild type gliomas than IDH-mutant gliomas. Bioinformatic analyses revealed that tissue inhibitor of metalloproteinase-1 (TIMP1) was one of the preferentially upregulated genes in IDH-wild type gliomas as compared to IDH-mutant gliomas, and its higher expression indicated worse prognosis of glioma patients. TIMP1 intensity determined by immunofluorescence staining on glioma tissues positively correlated with glioma tissue stiffness. Mechanistically, TIMP1 expression was positively correlated with the gene expression of two predominant extracellular matrix components, tenascin C and fibronectin, both of which were also highly expressed in IDH-wild type gliomas. By introducing IDH1-R132H-containing vectors into human IDH1-wild type glioma cells to obtain an IDH1-mutant cell line, we found that IDH1 mutation increased the TIMP1 promoter methylation through methylation-specific PCR. More importantly, IDH1-R132H mutation decreased both the expression of TIMP1, fibronectin, tenascin C, and the tumor tissue stiffness in IDH1-mutant glioma xenografts in contrast to IDH1-wild type counterparts. Moreover, TIMP1 knockdown in IDH-wild type glioma cells inhibited the expression of tenascin C and fibronectin, and decreased tissue stiffness in intracranial glioma xenografts. Conclusively, we revealed an IDH mutation status-mediated mechanism in regulating glioma tissue stiffness through modulating TIMP1 and downstream extracellular matrix components.The authors identified tissue inhibitor of metalloproteinase-1 (TIMP1) as an important regulator of tissue stiffness in isocitrate dehydrogenase (IDH)-wild type (WT) gliomas. TIMP1 knockdown decreases tissue stiffness, inhibited the expression of tenascin C and fibronectin, and suppressed tumor progression. These results suggest that TIMP1 could be a potential therapeutic target for IDH-WT gliomas.

Exploring the Correlation of Abnormal CXCL9 Expression with Immune Infiltration in Glioma and Patient Prognosis Based on TCGA and GTEx Databases.

In this study, we intend to identify key immune-related genes (IRGs) in gliomas using the TCGA and GTEx databases. Following collection of the RNA-seq data of lower-grade glioma (LGG) and glioblastoma (GBM) patients from the TCGA and GTEx databases, the differentially expressed IRGs (DE-IRGs) were screened. The ESTIMATE algorithm was utilized to evaluate StromalScore and ImmuneScore of LGG and GBM samples and a multifactorial Cox risk model was constructed to identify the related risk genes. The core IRGs of LGG and GBM were screened through a PPI network, followed by exploration of their correlation with glioma prognosis. The relationship between IRGs and immune cells in LGG and GBM was detected. In vitro assays were performed to detect the effect of CXCL9 on glioma cell development. We screened 403 and 492 DE-IRGs in LGG and GBM. StromalScore and ImmuneScore were related to overall survival in LGG, but not in GBM. CXCL9 was identified as a core gene in LGG and GBM and shared association with the prognosis of gliomas. Furthermore, a correlation was found between CXCL9 and immune infiltration of LGG and GBM. Glioma cell proliferation and invasion could be inhibited by silencing of CXCL9. Overall, CXCL9 is correlated to the prognosis of glioma patients and may accelerate glioma development via immune regulation.

Identification of Immunogenic Cell Death-Related Signature for Glioma to Predict Survival and Response to Immunotherapy.

Immunogenic cell death (ICD) is a type of regulated cell death (RCD) and is correlated with the progression, prognosis, and therapy of tumors, including glioma. Numerous studies have shown that the immunotherapeutic and chemotherapeutic agents of glioma might induce ICD. However, studies on the comprehensive analysis of the role of ICD-related genes and their correlations with overall survival (OS) in glioma are lacking. The genetic, transcriptional, and clinical data of 1896 glioma samples were acquired from five distinct databases and analyzed in terms of genes and transcription levels. The method of consensus unsupervised clustering divided the patients into two disparate molecular clusters: A and B. All of the patients were randomly divided into training and testing groups. Employing the training group data, 14 ICD-related genes were filtered out to develop a risk-score model. The correlations between our risk groups and prognosis, cells in the tumor microenvironment (TME) and immune cells infiltration, chemosensitivity and cancer stem cell (CSC) index were assessed. A highly precise nomogram model was constructed to enhance and optimize the clinical application of the risk score. The results demonstrated that the risk score could independently predict the OS rate and the immunotherapeutic response of glioma patients. This study analyzed the ICD-related genes in glioma and evaluated their role in the OS, clinicopathological characteristics, TME and immune cell infiltration of glioma. Our results may help in assessing the OS of glioma and developing better immunotherapeutic strategies.

Combined bulk RNA-seq and single-cell RNA-seq identifies a necroptosis-related prognostic signature associated with inhibitory immune microenvironment in glioma.

Necroptosis is a programmed cell death playing a significant role in cancer. Although necroptosis has been related to tumor immune environment (TIME) remodeling and cancer prognosis, however, the role of necroptosis-related genes (NRGs) in glioma is still elusive. In this study, a total of 159 NRGs were obtained, and parameters such as mutation rate, copy number variation (CNV), and relative expression level were assessed. Then, we constructed an 18-NRGs-based necroptosis-related signature (NRS) in the TCGA dataset, which could predict the patient's prognosis and was validated in two external CGGA datasets. We also explored the correlation between NRS and glioma TIME, chemotherapy sensitivity, and certain immunotherapy-related factors. The two necroptosis-related subtypes were discovered and could also distinguish the patients' prognosis. Through the glioblastoma (GBM) scRNA-seq data analysis, NRGs' expression levels in different GBM patient tissue cell subsets were investigated and the relative necroptosis status of different cell subsets was assessed, with the microglia score culminating among all. Moreover, we found a high infiltration level of immunosuppressive cells in glioma TIME, which was associated with poor prognosis in the high-NRS glioma patient group. Finally, the necroptosis suppressor CASP8 exhibited a high expression in glioma and was associated with poor prognosis. Subsequent experiments were performed in human glioma cell lines and patients' tissue specimens to verify the bioinformatic analytic findings about CASP8. Altogether, this study provides comprehensive evidence revealing a prognostic value of NRGs in glioma, which is associated with TIME regulation.

NIMG-105. DEUTERIUM METABOLIC IMAGING (DMI) DETECTS A LARGER WARBURG EFFECT IN HIGH-GRADE BRAIN TUMORS AND IN IDH WILD TYPE GLIOMAS

Abstract BACKGROUND The Warburg Effect (WE) is a metabolic change in which tumors favor glycolysis over oxidative phosphorylation and has been linked to cancer aggressiveness. Mutations in the isocitrate dehydrogenase (IDH) genes in gliomas are associated with improved outcomes. We deployed a magnetic resonance (MR) spectroscopic imaging technique coined Deuterium Metabolic Imaging (DMI) to measure the WE in multiple brain tumor types. METHODS Twenty-one patients underwent DMI, acquired on a Bruker 4T MR scanner after oral administration of 0.75g/kg of deuterated glucose. The WE was defined as the ratio of deuterated lactate, representing glycolysis, over deuterated glutamate and glutamine, representing oxidative phosphorylation. We devised an interval scale from 0 to 2 for the WE results. The Wilcoxon rank sum test was performed to detect differences between groups. RESULTS The WE measurements for the largest groups, by diagnosis, showed: glioblastoma (n= 9, mean= 1.67); astrocytoma, IDH-mutant, WHO grade 3 (n= 2, mean= 0.25); oligodendroglioma, WHO grade 3 (n= 3, mean= 0.5); low grade glioma, IDH-mutant (n= 2, mean= 0); and meningioma, WHO grade 2 (n= 2, mean= 0). The WE for high-grade tumors (n= 15, mean= 1.27) was significantly different from the WE for low-grade tumors (n= 5, mean= 0), with p= 0.010. The WE for IDH wild type gliomas (n= 9, mean= 1.67) was significantly different from the WE for IDH-mutant gliomas (n= 9, mean= 0.44), with p= 0.007. Analysis is ongoing. CONCLUSIONS DMI successfully and non-invasively detects the WE in many types of brain tumors. The WE was larger in high-grade tumors as compared to low-grade tumors, and the WE was larger in IDH wild type gliomas as compared to IDH-mutant gliomas. If validated with future studies, our results suggest that DMI is a useful tool to measure differences in the metabolism of brain tumors with different clinical behaviors.

IMMU-20. MODULATION OF THE PERIPHERAL T CELL BIOLOGY IN GLIOBLASTOMA

Abstract Cancer is a systemic disease. Due to the exceedingly rare occurrence of metastasis of cerebral glioma, systemic alterations have, however, not been considered to play a major role in disease progression of glioma. T cells orchestrate the adaptive immune response in an antigen-specific, cytokine mediated manner. The aim of our study was to investigate how cerebral glioma impacts systemic T cell immunobiology. We performed gene expression profiling of peripheral blood T cells in patients with IDHwt glioblastomas as well as in a murine glioma model. In addition, we analyzed the levels of soluble immune biomarkers in patient blood and performed flow-cytometric phenotyping of human peripheral blood CD3+ T cells. We discovered a significant skewing of peripheral T cell phenotypes in IDHwt glioblastoma patients compared to healthy donors (HD), showing CD4+ TH1 expansion and reduced numbers of T follicular helper cells (TFH), TH1* and mucosa associated invariant T (MAIT) cells, while TH2 and TH17 percentages remained stable. Interestingly, peripheral memory CD4+ T cells exhibited reduced Fas and PD-1 expression, while CD8 T cells were primarily affected in the non-memory CD45RA+ compartment, displaying reduced numbers of CD8+ CD127+ CD27+ cells. Compared to healthy individuals, GBM patients had significantly increased levels of soluble CD27 while levels of soluble CD25 were reduced (p &amp;lt; 0.05). GSEA and ORA analysis of differentially expressed genes in murine gliomas showed alterations in RNA binding and processing, as well as ribosomal activity in both cell types, indicating systemic modulation in translational- and cell cycle pathways in glioblastoma. Taken together, our results demonstrate a significant skewing of the peripheral T immunobiology in patients with IDHwt gliomas. Our data highlights the importance of considering malignant glioma as a systemic disease that fundamentally alters the immune repertoire in affected patients.

Knockdown of lncRNA HOXD-AS2 Improves the Prognosis of Glioma Patients by Inhibiting the Proliferation and Migration of Glioma Cells.

Increasing studies reported that long noncoding RNAs are involved in regulating glioma progression. However, the specific roles and mechanisms of lncRNAs in glioma remain unclear. Here, we sought to explore the functions of HOXD-AS2 in glioma progression. Gene expressions of lncRNAs in 5 normal brain tissue specimens and 5 glioblastoma tissue specimens were detected by gene expression profile chip technology. Bioinformatic analysis was performed to see whether differential expression of lncRNAs played any significant role in glioma occurrence and progression. The relationship between HOXD-AS2 level and clinical prognosis of the patients was analyzed. HOXD-AS2 was specifically interfered with by siRNA technology to observe its effects on U251 cell growth, proliferation, apoptosis, and invasion. The expression level of HOXD-AS2 gene in glioma was significantly higher than that in the normal brain tissue, which was related to the tumor grade. The level of HOXD-AS2 gene in patients with high-grade glioma was higher than that in patients with low-grade glioma. High expression of HOXD-AS2 gene was a risk factor for poor prognosis of glioma patients. Knocking down the expression of HOXD-AS2 in glioma cell line U251 arrested the cell cycle and reduced the cell proliferation. Furthermore, it could significantly reduce the migration ability of the cells but had no significant effect on the invasion. HOXD-AS2 is an oncogenic lncRNA associated with the poor prognosis of glioma. Knockdown of HOXD-AS2 may reduce the growth of glioma, which may provide a new avenue for treatment.

Identification of tryptophan metabolic gene-related subtypes, development of prognostic models, and characterization of tumor microenvironment infiltration in gliomas.

Epigenetic regulation and immunotherapy of tumor microenvironment (TME) is a hot topic in recent years. However, the potential value of tryptophan metabolism genes in regulating TME and immunotherapy is still unclear. A comprehensive study of glioma patients was carried out based on 40 tryptophan metabolic genes. Subsequently, these prognostic tryptophan metabolic genes are systematically associated with immunological characteristics and immunotherapy. A risk score model was constructed and verified in the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) cohorts to provide guidance for prognosis prediction and immunotherapy of glioma patients. We described the changes of tryptophan metabolism genes in 966 glioma samples from genetic and transcriptional fields and evaluated their expression patterns from two independent data sets. We identified two different molecular subtypes and found that two subtypes were associated with clinicopathological features, prognosis, TME cell infiltration, and immune checkpoint blockers (ICBs). Then, four genes (IL4I1, CYP1A1, OGDHL, and ASMT) were screened out by univariate and multivariate cox regression analysis of tryptophan metabolism genes, and a risk score model for predicting the overall survival (OS) of glioma patients was constructed. And its predictive ability is verified using the CGGA database. At the same time, we verified the expression of IL4I1, CYP1A1, OGDHL, and ASMT four genes in glioma specimens and cell lines in GES4260 and GES15824. Therefore, we constructed a nomogram to improve the clinical applicability of the risk assessment model. The high risk score group, characterized by increased TMB and immune cell infiltration, was also sensitive to temozolomide immunotherapy. Our comprehensive analysis of tryptophan metabolic genes in gliomas shows that they play a potential role in tumor immune stromal microenvironment, clinicopathological features, and prognosis. Tryptophan metabolism genes play an indispensable role in the complexity, diversity, and prognosis of TME. This risk score model based on tryptophan metabolism gene is a new predictor of clinical prognosis and immunotherapy response of glioma, and guides a more appropriate immunotherapy strategy for glioma patients.

Single-cell transcriptome analysis of multigrade glioma heterogeneity and immune microenvironment revealed potential prognostic biomarkers

Glioma, the most common intrinsic tumor of the central nervous system, is characterized by its high incidence and poor prognosis. The aim of this study was to identify differentially expressed genes (DEGs) between glioblastoma multiforme (GBM) and low-grade glioma (LGG) to explore prognostic factors of different grades of gliomas. Single-cell transcriptome sequencing data of gliomas were collected from the NCBI Gene Expression Omnibus (GEO), which included a total of 29 097 cell samples from three datasets. For the analysis of human gliomas of different grades, 21 071 cells were obtained by filtering, and 70 genes were screened from differentially expressed genes by gene ontology (GO) analysis, Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, from which the gene DLL3 was focused by reviewing the literature. The TCGA-based gene expression profiling interactive analysis (GEPIA) database was used to explore the survival curves of genes in LGG and GBM, and the gene expression profiling interactive analysis and tumor immune estimation resource (TIMER) database was used to study the expression of key genes in gliomas of different grades, predicting biomarkers that were closely related to immunotherapy. The cBioPortal database was used to explore the relationship between DLL3 expression and 25 immune checkpoints. Gene set enrichment analysis (GSEA) further identified pathways associated with central genes. Finally, the efficacy of biomarkers in prognosis and prediction was validated in the Chinese glioma genome atlas (CGGA). These results demonstrated that prognostic genes are associated with tumor proliferation and progression. Analysis of biological information and survival suggested that these genes might serve as a promising prognostic biomarker and as new targets for selecting therapeutic strategies.

CENPA acts as a prognostic factor that relates to immune infiltrates in gliomas.

Glioma is the most common primary tumor of the central nervous system (CNS). Centromere protein A (CENPA) plays an essential role in ensuring that mitosis proceeds normally. The effect of CENPA on glioma is rarely reported. However, the current study aims to explore whether aberrant CENPA expression promotes glioma progression and the potential mechanisms involved. The GEPIA website, The Cancer Genome Atlas, and the Gene Expression Omnibus (GEO) were used to assess the expression of CENPA in glioma. The results were validated by real-time quantitative polymerase chain reaction and immunohistochemical staining of clinical samples. The relationship between the expression and prognostic value of the CENPA gene in glioma was investigated by Kaplan-Meier (KM) survival analysis with RNA-seq and clinical profiles downloaded from the Chinese Glioma Genome Atlas (CGGA) and UCSC Xena. The association between CENPA and clinical characteristics was also evaluated. Cell Counting Kit-8 (CCK8) assay, wound healing assay using two glioma cell lines, gene set enrichment analysis (GSEA), KEGG and gene ontology (GO) enrichment analysis, immune infiltration analysis, temozolomide (TMZ) sensitivity analysis, and single-cell sequence analysis were performed to explore the underlying mechanisms of high CENPA expression and its effect on glioma development. Finally, we performed a Cox analysis based on the expression of CENPA to predict patient prognosis. CENPA was significantly upregulated in glioma tissue samples and correlated with patient prognosis. Moreover, the downregulation of CENPA inhibited the migration and proliferation of glioma cells. In addition, the expression level of CENPA was significantly correlated with the grade, primary-recurrent-secondary (PRS) type, IDH mutation status, and 1p19q codeletion status. Furthermore, CENPA could serve as an independent prognostic factor for glioma that mainly interferes with the normal progression of mitosis and regulates the tumor immune microenvironment favoring glioma development. CENPA may act as a prognostic factor in patients with glioma and provide a novel target for the treatment of gliomas.

Comprehensive analyses reveal the role of histone deacetylase genes in prognosis and immune response in low-grade glioma.

Many studies have shown that Histone deacetylases (HDAC) is involved in the occurrence of malignant tumors and regulates the occurrence, proliferation, invasion, and migration of malignant tumors through a variety of signaling pathways. In the present, we explored the role of Histone deacetylases genes in prognosis and immune response in low-grade glioma. Using consensus clustering, we built the new molecular clusters. Using HDAC genes, we constructed and validated the prognostic model in two independent cohort datasets. Patients were divided into high-risk and low-risk groups. Then, we explored the molecular characteristics, clinical characteristics, tumor microenvironment and immune infiltration levels of two clusters and risk groups. Receiver operating characteristic analyses were built for model assessment. We finally detected the expression levels of signature genes between tumor and normal tissues. Low-grade can be separated into two molecular clusters using 11 HDACs genes. Two clusters had different clinical characteristics and prognosis. Nex, we constructed a prognosis model using six HDAC genes (HDAC1, HDAC4, HDAC5, HDAC7, HDAC9, and HDAC10), which was also validated in an independent cohort dataset. Furthermore, multivariate cox regression indicated that the calculated risk score was independently associated with prognosis in low-grade glioma, and risk score can predict the five-year survival probability of low-grade glioma well. High-risk patients can be attributed to multiple complex function and molecular signaling pathways, and the genes alterations of high- and low-risk patients were significantly different. We also found that different survival outcomes of high- and low- risk patients could be involved in the differences of immune filtration level and tumor microenvironment. Subsequently, using signature genes, we identified several small molecular compounds that could be useful for low-grade glioma patients' treatment. Finally, we detected the expression levels of signature genes in tumor tissues. our study uncovers the biology function role of HDAC genes in low-grade glioma. We identified new molecular subtypes and established a prognostic model based on six HDAC genes, which was well applied in two independent cohort data. The regulation of HDAC genes in low-grade glioma involved in multiple molecular function and signaling pathways and immune infiltration levels. Further experiments in vivo and vitro were required to confirm the present findings.

Expression of eIF4E Gene in Glioma and Its Sensitivity to Oxidative Stress.

Objective Increased expression of eIF4E has been observed in various cancers, which makes eIF4E an attractive target of anticancer drugs. This study mainly discussed eIF4E gene expression in glioma and its sensitivity to oxidative stress (OS). Methods Relevant data from The Cancer Genome Atlas (TCGA) database regarding eIF4E gene expression and its prognostic significance in glioma samples were analyzed. Additionally, we measured eIF4E at mRNA and protein levels in clinical samples collected between July 2019 and September 2021, as well as glioma cell strains. U251 cells cultured in vitro were treated with OS injury induced by hydrogen peroxide (H2O2) and then transfected with si-eIF4E to determine changes in cell multiplication, invasiveness, and migration capacities as well as apoptosis rate. ELISA quantified cell malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) concentrations, and flow cytometry measured reactive oxygen species (ROS) level. Results In glioma samples from the TCGA database, eIF4E showed obviously elevated levels in LGG and GBM patients, which was usually associated with adverse patient prognosis (P < 0.05). eIF4E was also upregulated in glioma cell strains than in HBE cells. In comparison with the blank control group, transfection of si-eIF4E statistically suppressed the capacity of U251 cells to proliferate, invade and migrate, and enhance apoptosis rate, while reducing SOD and GSH-Px and increasing MDA and ROS. In addition, H2O2 induced the upregulation of eIF4E in U251 cells. H2O2 + si-eIF4E exhibited reduced multiplication and number of clone cell formation, invasion, and migration of U251 cells, as well as increased apoptosis rate than H2O2 + si-NC group. Conclusions eIF4E is highly expressed in glioma. Knocking down eIF4E can effectively inhibit the capacity of U251 to proliferate, invade and migrate, and significantly increase apoptosis. In addition, eIF4E knock-down is able to lower OS reaction under H2O2 inducement and enhance U251 cells' sensitivity to OS.

Deep multilayer brain omics identifies the potential involvement of menopause molecular networks in Gliomas' disease progression.

The risk of high-grade gliomas is lower in young females, however, its incidence enhances after menopause, suggesting potential protective roles of female sex hormones. Hormone oscillations after menopause have received attention as a possible risk factor. Little is known about risk factors for adult gliomas. We examined the association of the aging brain after menopause, determining the risk of gliomas with proteomics and the MALDI-MSI experiment. Menopause caused low neurotransmitter levels such as GABA and ACH, high inflammatory factor levels like il-1β, and increased lipid metabolism-related levels like triglycerides in the brain. Upregulated and downregulated proteins after menopause were correlated with differentially expressed glioma genes, such as ACTA2, CAMK2D, FNBPIL, ARL1, HEBP1, CAST, CLIC1, LPCAT4, MAST3, and DOCK9. Furthermore, differential gene expression analysis of monocytes showed that the downregulated gene LPCAT4 could be used as a marker to prevent menopausal gliomas in women. Our findings regarding the association of menopause with the risk of gliomas are consistent with several extensive cohort studies. In view of the available evidence, postmenopausal status is likely to represent a significant risk factor for gliomas.

An integrative bioinformatics investigation and experimental validation of critically involved genes in high-grade gliomas

BackgroundLack of knowledge around underlying mechanisms of gliomas mandates intense research efforts to improve the disease outcomes. Identification of high-grade gliomas pathogenesis which is known for poor prognosis and low survival is of particular importance. Distinguishing the differentially expressed genes is one of the core approaches to clarify the causative factors.MethodsMicroarray datasets of the treatment-naïve gliomas were provided from the Gene Expression Omnibus considering the similar platform and batch effect removal. Interacting recovery of the top differentially expressed genes was performed on the STRING and Cytoscape platforms. Kaplan–Meier analysis was piloted using RNA sequencing data and the survival rate of glioma patients was checked considering selected genes. To validate the bioinformatics results, the gene expression was elucidated by real-time RT-qPCR in a series of low and high-grade fresh tumor samples.ResultsWe identified 323 up-regulated and 253 down-regulated genes. The top 20 network analysis indicated that PTX3, TIMP1, CHI3L1, LTF and IGFBP3 comprise a crucial role in gliomas progression. The survival was inversely linked to the levels of all selected genes. Further analysis of RNA sequencing data indicated a significant increase in all five genes in high-grade tumors. Among them, PTX3, TIMP1 and LTF did not show any change in low-grade versus controls. Real-time RT-qPCR confirmed the in-silico results and revealed significantly higher expression of selected genes in high-grade samples compared to low-grade.ConclusionsOur results highlighted the role of PTX3 and TIMP1 which were previously considered in glioma tumorigenesis as well as LTF as a new potential biomarker.

Pyroptosis: a novel signature to predict prognosis and immunotherapy response in gliomas.

Gliomas are the most common primary brain tumors and are highly malignant with a poor prognosis. Pyroptosis, an inflammatory form of programmed cell death, promotes the inflammatory cell death of cancer. Studies have demonstrated that pyroptosis can promote the inflammatory cell death (ICD) of cancer, thus affecting the prognosis of cancer patients. Therefore, genes that control pyroptosis could be a promising candidate bio-indicator in tumor therapy. The function of pyroptosis-related genes (PRGs) in gliomas was investigated based on the Chinese Glioma Genome Atlas (CGGA), the Cancer Genome Atlas (TCGA) and the Repository of Molecular Brain Neoplasia Data (Rembrandt) databases. In this study, using the non-negative matrix factorization (NMF) clustering method, 26 PRGs from the RNA sequencing data were divided into two subgroups. The LASSO and Cox regression was used to develop a 4-gene (BAX, Caspase-4, Caspase-8, PLCG1) risk signature, and all glioma patients in the CGGA, TCGA and Rembrandt cohorts were divided into low- and high-risk groups. The results demonstrate that the gene risk signature related to clinical features can be used as an independent prognostic indicator in glioma patients. Moreover, the high-risk subtype had rich immune infiltration and high expression of immune checkpoint genes in the tumor immune microenvironment (TIME). The analysis of the Submap algorithm shows that patients in the high-risk group could benefit more from anti-PD1 treatment. The risk characteristics associated with pyroptosis proposed in this study play an essential role in TIME and can potentially predict the prognosis and immunotherapeutic response of glioma patients.

FAIM2 is a potential pan-cancer biomarker for prognosis and immune infiltration.

Fas apoptosis inhibitory molecule 2 (FAIM2) is an important member of the transmembrane BAX inhibitor motif containing (TMBIM) family. However, the role of FAIM2 in tumor prognosis and immune infiltration has rarely been studied. Here, we conducted a pan-cancer analysis to explore the role of FAIM2 in various tumors and further verified the results in glioma through molecular biology experiment. FAIM2 expression and clinical stages in tumor samples and para-cancerous samples were analyzed by TIMER2 database, GEPIA database, and the TISIDB database. The role of FAIM2 on prognosis was analyzed via GEPIA2. We utilized the ESTIMATE algorithm to evaluate the ImmuneScore and StromalScore of various tumors. In addition, we explored the correlation between FAIM2 expression and tumor immune cell infiltration by the TIMER2 database. The immune checkpoint genes, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methylation related to FAIM2 were analyzed based on the TCGA database. The correlation between FAIM2 expression with Copy number variations (CNV) and methylation is explored by GSCA database. Protein-Protein Interaction (PPI) analysis was obtained from the STRING database and the CellMiner database was used to explore the association between FAIM2 expression and drug response. FAIM2 co-expression genes were studied by the LinkedOmics database. Immunohistochemistry, Western Blotting Analysis, Cell Viability Assay, Colony Formation Assay, and Edu staining assay were used in the molecular biology experiments section. The FAIM2 expression was down-regulated in most tumors and highly expressed FAIM2 was associated with a better prognosis in several cancers. FAIM2 plays an essential role in the tumor microenvironment and is closely associated with immune Infiltration in various tumors. The expression of FAIM2 was closely correlated to TMB, MSI, MMR, CNV, and DNA methylation. Furthermore, FAIM2 related genes in the PPI network and its co-expression genes in glioma are involved in a large number of immune-related pathways. Molecular biology experiments verified a cancer suppressor role for FAIM2 in glioma. FAIM2 may serve as a potential pan-cancer biomarker for prognosis and immune infiltration, especially in glioma. Moreover, this study might provide a potential target for tumor immunotherapy.

Integrative analysis of a novel 5 methylated snoRNA genesprognostic signature in patients with glioma.

Aim: To explore the prognostic value of methylated snoRNA genes in glioma and construct a prognostic risk signature. Materials & methods: We retrieved clinical information and 450K methylation data from The Cancer Genome Atlas and obtained five methylated snoRNA genes. Thenwe established a risk signature and verified the effect of SNORA71B on glioma cells with functional assays. Results: A risk signature containing five methylated snoRNA genes was constructed and demonstrated to be an independent predictor of glioma prognosis. Silencing SNORA71B restrained the proliferation, migration and invasion of glioma cells and reduced the expression of mesenchymal and cell cycle marker proteins. Conclusion: This study constructed a methylated snoRNA gene risk signature, which may provide a reference for glioma patients' prognosis assessment.