Genes In Glioblastoma Multiforme Research Articles

HSPA5 and FGFR1 genes in the mesenchymal subtype of glioblastoma can improve a treatment efficacy

ABSTRACT Tyrosine kinase inhibitors (TKIs) have emerged as a potential treatment strategy for glioblastoma multiforme (GBM). However, their efficacy is limited by various drug resistance mechanisms. To devise more effective treatments for GBM, genetic characteristics must be considered in addition to pre-existing treatments. We performed an integrative analysis with heterogeneous GBM datasets of genomic, transcriptomic, and proteomic data from DepMap, TCGA and CPTAC. We found that poor prognosis was induced by co-upregulation of heat shock protein family A member 5 (HSPA5) and fibroblast growth factor receptor 1 (FGFR1). Co-up regulation of these two genes could regulate the PI3K/AKT pathway. GBM cell lines with co-upregulation of these two genes showed higher drug sensitivity to PI3K inhibitors. In the mesenchymal subtype, the co-upregulation of FGFR1 and HSPA5 resulted in the most malignant subtype of GBM. Furthermore, we found this newly discovered subtype was correlated with homologous recombination deficiency (HRD) In conclusion, we discovered novel druggable candidates within the group exhibiting co-upregulation of these two genes in GBM, suggest potential strategies for combination therapy.

Identification of Novel Molecular and Clinical Biomarkers of Survival in Glioblastoma Multiforme Patients: A Study Based on The Cancer Genome Atlas Data.

Glioblastoma multiforme (GBM) is the most prevalent type of brain tumour; although advancements in treatment have been made, the median survival time for GBM patients has persisted at 15 months. This study is aimed at investigating the genetic alterations and clinical features of GBM patients to find predictors of survival. GBM patients' methylation and gene expression data along with clinical information from TCGA were retrieved. The most overrepresented pathways were identified independently for each omics dataset. From the genes found in at least 30% of these pathways, one gene that was identified in both sets was further examined using the Kaplan-Meier method for survival analysis. Additionally, three groups of patients who started radio and chemotherapy at different times were identified, and the influence of these variations in treatment modality on patient survival was evaluated. Four pathways that seemed to negatively impact survival and two with the opposite effect were identified. The methylation status of PRKCB was highlighted as a potential novel biomarker for patient survival. The study also found that treatment with chemotherapy prior to radiotherapy can have a significant impact on patient survival, which could lead to improvements in clinical management and therapeutic approaches for GBM patients.

IDH1, ATRX, p53, and Ki67 Expression in Glioblastoma patients: Their Clinical and Prognostic Significance—A Prospective Study

Abstract Context Glioblastoma multiforme (GBM) is a malignant and aggressive primary brain tumor with a poor prognosis. This adverse prognosis is due to the tumor's tendency for advancement and recurrence caused by highly intrusive nature of the persisting GBM cells that actively escape from the main tumor mass into the surrounding normal brain tissue. On the basis of biomarker illustration, it can be classified into molecular subgroups. Aims (1) To determine the expression of IDH1, ATRX, p53, and Ki67 by immunohistochemistry, in a cohort of GBMs. (2) To determine whether altered protein expression of any of these growth-control genes in GBM will show association with patient survival. (3) To establish prognostically distinct molecular subgroups of GBM, irrespective of histopathological diagnosis. Results In this prospective observational study, 35 histologically diagnosed cases of glioblastoma were enrolled. The mean age at the time of presentation was 43.46 ± 17.25 years with a male:female ratio of 1.3:1. Of the 35 cases, microvascular proliferation was seen in 23 cases. Large foci of necrosis (>50%) were seen in 10 cases and 27 cases had mitotic count ≥ 5/high power field (HPF). Of 35 cases, 5 (14.3%) cases showed IDH1 immunopositivity and 30 (85.7%) cases were negative for IDH1. ATRX was retained in 24 (68.6%) cases, while it was lost in 11 (31.4%) cases. The p53 immunoexpression was seen in 31 (88.6%) cases, whereas p53 was negative in 4 (11.4%) cases. The overall median survival (OS) was 6 months. In two protein pairs, the three compositions were IDH1–/p53+ (74.3%), ATRX +/IDH1– (62.9%), and ATRX +/p53+ (57.1%). Combined three-protein immunohistochemical analysis revealed five different molecular variants. Also, 8.6% (3/35) of the samples had aberrant protein expression of all three proteins, i.e., ATRX–/p53 +/IDH1 + , while 11.4% (4/35) were wild-type protein expression group, i.e., ATRX +/p53–/IDH1–. Conclusion In patients with single protein expression, Kaplan–Meier survival analysis showed statistically better OS in IDH1 mutant glioblastomas. In cases with double protein pairs, IDH1/p53 revealed statistically significant association with better median OS. The survival analysis of patients with IDH1/ATRX/p53 protein combinations also denoted a better OS. Hence, GBM can be grouped into prognostically relevant subgroups using these protein expression signatures individually, as well as the combined protein expression signatures.

Abstract 2632: A new paradigm for brain tumors treatment: Guadecitabine as a fundamental player to improve tumor immune response

Abstract Background:Glioblastoma multiforme (GBM) is a highly aggressive primary brain tumor refractory to standard treatments and to immunotherapy with immune-checkpoint inhibitors (ICI) (PMID: 35626018). Interestingly, melanoma brain metastases (MM-BM), sharing the same niche as GBM, often respond to current ICI immunotherapies (PMID: 36521332). The role of epigenetic modifications in regulating GBM cellular proliferation, invasion, and prognosis, as well as their impact on the cross-talk between GBM and immune cells in the tumor milieu, has become evident (PMID: 34361090). Consequently, manipulating the epigenome has emerged as a therapeutic opportunity in GBM. Methods:Microarray transcriptional and methylation profiles, followed by gene set enrichment and IPA analyses, were conducted to study the differences in constitutive expression profiles between GBM and MM-BM cells compared to extracranial MM cells. Additionally, the modulatory effects of the DNA hypomethylating agent (DHA) guadecitabine on different tumor cells were investigated. The prognostic relevance of DHA-modulated genes was assessed through Cox analysis in a TCGA GBM patients' cohort. Results:The most notable differences between constitutive GBM and MM-BM cells lie in the enrichment of biological processes associated with tumor growth, invasion, and extravasation, as well as the inhibition of MHC class II antigen processing/presentation in GBM cells. Guadecitabine treatment appeared to shrink these differences, shifting the phenotype of GBM cells towards the more immunogenic MM-BM profile. This was achieved through promoter hypomethylation and subsequent up-regulation of genes mainly associated with the activation, proliferation, and migration of T and B cells, along with MHC class II antigen processing/presentation. Among DHA-modulated genes in GBM, 7.6% exhibited significant prognostic relevance. Moreover, a substantial set of immune-related upstream regulators (URs) were commonly modulated by DHA in GBM, MM-BM, and/or MM cells: DHA-activated URs enriched biological processes mainly involved in the regulation of cytokines and chemokines production, inflammatory response, and Type I/II/III IFN-mediated signaling. DHA-inhibited URs were associated with metabolic and proliferative pathways. Conclusions:Epigenetic remodeling of GBM by DHA represents a promising strategy to enhance the efficacy of cancer immunotherapy, supporting the rationale for developing new combinatorial approaches for the treatment of brain malignancies. Citation Format: Maria Fortunata Lofiego, Francesca Piazzini, Francesca Pia Caruso, Francesco Marzani, Laura Solmonese, Emma Bello, Fabrizio Celesti, Maria Claudia Costa, Teresa Maria Noviello, Roberta Mortarini, Andrea Anichini, Michele Ceccarelli, Sandra Coral, Anna Maria Di Giacomo, Michele Maio, Alessia Covre. A new paradigm for brain tumors treatment: Guadecitabine as a fundamental player to improve tumor immune response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2632.

Systematic analysis based on the cuproptosis-related genes identifies ferredoxin 1 as an immune regulator and therapeutic target for glioblastoma

Glioblastoma multiforme (GBM) is recognized as the prevailing malignant and aggressive primary brain tumor, characterized by an exceedingly unfavorable prognosis. Cuproptosis, a recently identified form of programmed cell death, exhibits a strong association with cancer progression, therapeutic response, and prognostic outcomes. However, the specific impact of cuproptosis on GBM remains uncertain. To address this knowledge gap, we obtained transcriptional and clinical data pertaining to GBM tissues and their corresponding normal samples from various datasets, including TCGA, CGGA, GEO, and GTEx. R software was utilized for the analysis of various statistical techniques, including survival analysis, cluster analysis, Cox regression, Lasso regression, gene enrichment analysis, drug sensitivity analysis, and immune microenvironment analysis. Multiple assays were conducted to investigate the expression of genes related to cuproptosis and their impact on the proliferation, invasion, and migration of glioblastoma multiforme (GBM) cells. The datasets were obtained and prognostic risk score models were constructed and validated using differentially expressed genes (DEGs) associated with cuproptosis. To enhance the practicality of these models, a nomogram was developed.Patients with glioblastoma multiforme (GBM) who were classified as high risk exhibited a more unfavorable prognosis and shorter overall survival compared to those in the low risk group. Additionally, we specifically chose FDX1 from the differentially expressed genes (DEGs) within the high risk group to assess its expression, prognostic value, biological functionality, drug responsiveness, and immune cell infiltration. The findings demonstrated that FDX1 was significantly upregulated and associated with a poorer prognosis in GBM. Furthermore, its elevated expression appeared to be linked to various metabolic processes and the susceptibility to chemotherapy drugs. Moreover, FDX1 was found to be involved in immune cell infiltration and exhibited correlations with multiple immunosuppressive genes, including TGFBR1 and PDCD1LG2. The aforementioned studies offer substantial assistance in informing the chemotherapy and immunotherapy approaches for GBM. In summary, these findings contribute to a deeper comprehension of cuproptosis and offer novel perspectives on the involvement of cuproptosis-related genes in GBM, thereby presenting a promising therapeutic strategy for GBM patients.

Identification of CDK1, PBK, and CHEK1 as an Oncogenic Signature in Glioblastoma: A Bioinformatics Approach to Repurpose Dapagliflozin as a Therapeutic Agent.

Glioblastoma multiforme (GBM) is the most aggressive and lethal primary brain tumor whose median survival is less than 15 months. The current treatment regimen comprising surgical resectioning, chemotherapy with Temozolomide (TMZ), and adjuvant radiotherapy does not achieve total patient cure. Stem cells' presence and GBM tumor heterogeneity increase their resistance to TMZ, hence the poor overall survival of patients. A dysregulated cell cycle in glioblastoma enhances the rapid progression of GBM by evading senescence or apoptosis through an over-expression of cyclin-dependent kinases and other protein kinases that are the cell cycle's main regulatory proteins. Herein, we identified and validated the biomarker and predictive properties of a chemoradio-resistant oncogenic signature in GBM comprising CDK1, PBK, and CHEK1 through our comprehensive in silico analysis. We found that CDK1/PBK/CHEK1 overexpression drives the cell cycle, subsequently promoting GBM tumor progression. In addition, our Kaplan-Meier survival estimates validated the poor patient survival associated with an overexpression of these genes in GBM. We used in silico molecular docking to analyze and validate our objective to repurpose Dapagliflozin against CDK1/PBK/CHEK1. Our results showed that Dapagliflozin forms putative conventional hydrogen bonds with CDK1, PBK, and CHEK1 and arrests the cell cycle with the lowest energies as Abemaciclib.

Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies.

Glioblastoma multiforme (GBM) is one of the most aggressive cancers with a low overall survival rate. The treatment of GBM is challenging due to the presence of the blood-brain barrier (BBB), which hinders drug delivery. Invasive procedures alone are not effective at completely removing such tumors. Hence, identifying the crucial pathways and biomarkers for the treatment of GBM is of prime importance. We conducted this study to identify the pathways associated with GBM. We used The Cancer Genome Atlas (TCGA) GBM genomic dataset to identify differentially expressed genes (DEGs). We investigated the prognostic values of the guanine nucleotide-binding protein G(i) alpha subunit (GNAI) family of genes in GBM using a Chinese Glioma Genome Atlas (CGGA) dataset. Within this dataset, we observed the association in the tumor microenvironment between the gene expression of GNAI subunit 3 (GNAI3) and a poor prognosis. MetaCore and gene ontology (GO) analyses were conducted to explore the role of GNAI3 in co-expressed genes and associated signaling pathways using a transcript analysis. Notable pathways included "Cytoskeleton remodeling regulation of actin cytoskeleton organization by the kinase effectors of Rho GTPases" and "Immune response B cell antigen receptor (BCR) pathway". A single-cell analysis was used to assess GNAI3 expression in GBM. The results demonstrated that GNAI family genes, specifically GNAI3, were significantly associated with carcinogenesis and malignancy in GBM patients. Our findings suggest that the GNAI3 gene holds potential as a prognostic biomarker for GBM.

Gibbs process distinguishes survival and reveals contact-inhibition genes in Glioblastoma multiforme.

Tumor growth is a spatiotemporal birth-and-death process with loss of heterotypic contact-inhibition of locomotion (CIL) of tumor cells promoting invasion and metastasis. Therefore, representing tumor cells as two-dimensional points, we can expect the tumor tissues in histology slides to reflect realizations of spatial birth-and-death process which can be mathematically modeled to reveal molecular mechanisms of CIL, provided the mathematics models the inhibitory interactions. Gibbs process as an inhibitory point process is a natural choice since it is an equilibrium process of the spatial birth-and-death process. That is if the tumor cells maintain homotypic contact inhibition, the spatial distributions of tumor cells will result in Gibbs hard core process over long time scales. In order to verify if this is the case, we applied the Gibbs process to 411 TCGA Glioblastoma multiforme patient images. Our imaging dataset included all cases for which diagnostic slide images were available. The model revealed two groups of patients, one of which - the "Gibbs group," showed the convergence of the Gibbs process with significant survival difference. Further smoothing the discretized (and noisy) inhibition metric, for both increasing and randomized survival time, we found a significant association of the patients in the Gibbs group with increasing survival time. The mean inhibition metric also revealed the point at which the homotypic CIL establishes in tumor cells. Besides, RNAseq analysis between patients with loss of heterotypic CIL and intact homotypic CIL in the Gibbs group unveiled cell movement gene signatures and differences in Actin cytoskeleton and RhoA signaling pathways as key molecular alterations. These genes and pathways have established roles in CIL. Taken together, our integrated analysis of patient images and RNAseq data provides for the first time a mathematical basis for CIL in tumors, explains survival as well as uncovers the underlying molecular landscape for this key tumor invasion and metastatic phenomenon.

Comprehensive analysis of the prognosis and immune infiltrates for the BET protein family reveals the significance of BRD4 in glioblastoma multiforme.

Background: Glioblastoma multiforme (GBM) is the most common and invasive primary central nervous system tumor. The prognosis after surgery, radiation and chemotherapy is very poor. Bromodomain (BRD) proteins have been identified in oncogenic rearrangements, and play a key role in the development of multiple cancers. However, the relationship between BET proteins and prognosis of GBM are still worth exploring, and the distinct functions of BET proteins and tumor immunology in GBM have not been fully elucidated. Therefore, it is particularly important to develop effective biomarkers to predict the prognosis of GBM patients. Methods: Metascape, David, Kaplan-Meier Plotter, Oncomine, GEPIA, TCGA, TIMER, and LinkedOmics databases were used to assess the expression and prognosis for BET proteins in GBM. ROC analysis of risk model was established to identify the correlation between BET genes and overall survival in GBM patients. TIMER and GEPIA databases were used to comprehensively investigate the correlation between BET genes and tumor immune infiltration cells. Moreover, the image of immunohistochemistry staining of BET proteins in normal tissue and tumor tissue were retrived from the HPA database. In addition, differential analysis and pathway enrichment analysis of BRD4 gene expression profile were also carried out. Finally, immune-fluorescence and Western blot were used to clarify the expression of BRD4 in GBM cells. Results: Bioinformatics analysis showed that the expression levels of BET genes in GBM may play an important role in oncogenesis. Specifically, bioinformatic and immunohistochemistry analysis showed that BRD4 protein was more highly expressed in tumor tissues than that in normal tissues. The high expression of BRD4 was associated with poor prognosis in GBM. The expression of BET genes were closely related to the immune checkpoint in GBM. The correlation effect of BRD4 was significantly higher than other BET genes, which represented negative correlation with immune checkpoint. The expression of BRD4 was positively associated with tumor purity, and negatively associated with immune infiltration abundance of macrophage, neutrophil and CD8+ T-cell, respectively. Cox analysis showed that the model had good survival prediction and prognosis discrimination ability. In addition, the expression levels of BRD4 protein was significantly higher in U-251MGcells than that in normal cells, which was consistent with the results of bioinformatics data. Conclusion: This study implied that BRD4 could be hopeful prognostic biomarker in GBM. The increased expression of BRD4 may act as a molecular marker to identify GBM patients with high-risk subgroups. BRD4 may be a valuable prognostic biomarker, and a potential target of precision therapy against GBM.

Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: A neuro-oncological investigation

BackgroundThe O6-methylguanine-DNA methyltransferase (MGMT) is a deoxyribonucleic acid (DNA) repairing enzyme that has been established as an essential clinical brain tumor biomarker for Glioblastoma Multiforme (GBM). Knowing the status of MGMT methylation biomarkers using multi-parametric MRI (mp-MRI) helps neuro-oncologists to analyze GBM and its treatment plan. MethodThe hand-crafted radiomics feature extraction of GBM's subregions, such as edema(ED), tumor core (TC), and enhancing tumor (ET) in the machine learning (ML) framework, was investigated using support vector machine(SVM), K-Nearest Neighbours (KNN), random forest (RF), LightGBM, and extreme gradient boosting (XGB). For tissue-level analysis of the promotor genes in GBM, we used the deep residual neural network (ResNet-18) with 3D architecture, followed by EfficientNet-based investigation for variants as B0 and B1. Lastly, we analyzed the fused deep learning (FDL) framework that combines ML and DL frameworks. ResultStructural mp-MRI consisting of T1, T2, FLAIR, and T1GD having a size of 400 and 185 patients, respectively, for discovery and replication cohorts. Using the CV protocol in the ResNet-3D framework, MGMT methylation status prediction in mp-MRI gave the AUC of 0.753 (p < 0.0001) and 0.72 (p < 0.0001) for the discovery and replication cohort, respectively. We presented that the FDL is ∼7% superior to solo DL and ∼15% to solo ML. ConclusionThe proposed study aims to provide solutions for building an efficient predictive model of MGMT for GBM patients using deep radiomics features obtained from mp-MRI with the end-to-end ResNet-18 3D and FDL imaging signatures.

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.

Network pharmacological analysis of active components of Xiaoliu decoction in the treatment of glioblastoma multiforme.

Background: Glioblastoma multiforme (GBM) is the most aggressive primary nervous system brain tumor. There is still a lack of effective methods to control its progression and recurrence in clinical treatment. It is clinically found that Xiaoliu Decoction (XLD) has the effect of treating brain tumors and preventing tumor recurrence. However, its mechanism is still unclear. Methods: Search the Traditional Chinese Medicine System Pharmacology Database (TCSMP) for efficient substances for the treatment of XLD in the treatment of GBM, and target the targeted genes of the effective ingredients to construct a network. At the same time, download GBM-related gene expression data from the TCGA and GTEX databases, screen differential expression bases, and establish a drug target disease network. Through bioinformatics analysis, the target genes and shared genes of the selected Chinese medicines are analyzed. Finally, molecular docking was performed to further clarify the possibility of XLD in multiple GBMs. Results: We screened 894 differentially expressed genes in GBM, 230 XLD active ingredients and 169 predicted targets of its active compounds, of which 19 target genes are related to the differential expression of GBM. Bioinformatics analysis shows that these targets are closely related to cell proliferation, cell cycle regulation, and DNA synthesis. Finally, through molecular docking, it was further confirmed that Tanshinone IIA, the active ingredient of XLD, was tightly bound to key proteins. Conclusion: To sum up, the results of this study suggest that the mechanism of XLD in the treatment of GBM involves multiple targets and signal pathways related to tumorigenesis and development. This study not only provides a new theoretical basis for the treatment of glioblastoma multiforme with traditional Chinese medicine, but also provides a new idea for the research and development of targeted drugs for the treatment of glioblastoma multiforme.

Downregulated ferroptosis-related gene SQLE facilitates temozolomide chemoresistance, and invasion and affects immune regulation in glioblastoma.

Chemoresistance in patients with glioblastoma multiforme (GBM) is a common reason hindering the success of treatment. Recently, ferroptosis has been reported to be associated with chemoresistance in different types of cancer, while the role of ferroptosis-related genes in GBM have not been fully elucidated. This study aimed to demonstrate the roles and mechanism of ferroptosis-related genes in chemoresistance and metastasis of GBM. First, two candidate genes, squalene epoxidase (SQLE) and FANCD2, were identified to be associated with ferroptosis-related chemoresistance in GBM from three temozolomide (TMZ) therapeutic datasets and one ferroptosis-related gene dataset. Then, comprehensive bio-informatics data from different databases testified that SQLE was significantly downregulated both in GBM tissue and cells and displayed a better prognosis in GBM. Clinical data identified lower expression of SQLE was significantly associated with WHO grade and 1p/19q codeletion. Moreover, through in vitro experiments, SQLE was confirmed to suppress ERK-mediated TMZ chemoresistance and metastasis of GBM cells. The KEGG analysis of SQLE-associated co-expressed genes indicated SQLE was potentially involved in the cell cycle. Furthermore, SQLE was found to have the most significant correlations with tumor-infiltrating lymphocytes and immunomodulators. These findings highlighted that SQLE could be a potential target and a biomarker for therapy and prognosis of patients with GBM.

Construction of an immune-related gene signature for the prognosis and diagnosis of glioblastoma multiforme.

BackgroundIncreasing evidence has suggested that inflammation is related to tumorigenesis and tumor progression. However, the roles of immune-related genes in the occurrence, development, and prognosis of glioblastoma multiforme (GBM) remain to be studied.MethodsThe GBM-related RNA sequencing (RNA-seq), survival, and clinical data were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) databases. Immune-related genes were obtained from the Molecular Signatures Database (MSigDB). Differently expressed immune-related genes (DE-IRGs) between GBM and normal samples were identified. Prognostic genes associated with GBM were selected by Kaplan–Meier survival analysis, Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox regression analysis, and multivariate Cox analysis. An immune-related gene signature was developed and validated in TCGA and CGGA databases separately. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore biological functions of the signature. The correlation between immune cell infiltration and the signature was analyzed by single-sample gene set enrichment analysis (ssGSEA), and the diagnostic value was investigated. The gene set enrichment analysis (GSEA) was performed to explore the potential function of the signature genes in GBM, and the protein–protein interaction (PPI) network was constructed.ResultsThree DE-IRGs [Pentraxin 3 (PTX3), TNFSF9, and bone morphogenetic protein 2 (BMP2)] were used to construct an immune-related gene signature. Receiver operating characteristic (ROC) curves and Cox analyses confirmed that the 3-gene-based prognostic signature was a good independent prognostic factor for GBM patients. We found that the signature was mainly involved in immune-related biological processes and pathways, and multiple immune cells were disordered between the high- and low-risk groups. GSEA suggested that PTX3 and TNFSF9 were mainly correlated with interleukin (IL)-17 signaling pathway, nuclear factor kappa B (NF-κB) signaling pathway, tumor necrosis factor (TNF) signaling pathway, and Toll-like receptor signaling pathway, and the PPI network indicated that they could interact directly or indirectly with inflammatory pathway proteins. Quantitative real-time PCR (qRT-PCR) indicated that the three genes were significantly different between target tissues.ConclusionThe signature with three immune-related genes might be an independent prognostic factor for GBM patients and could be associated with the immune cell infiltration of GBM patients.

LncRNA H19 promotes glioblastoma multiforme development by activating autophagy by sponging miR-491-5p

ABSTRACT Glioblastoma multiforme (GBM) is a malignant cancer with severely poor survival, and the cells continue to thrive during hypoxia and toxic stress through autophagy. To validate the oncogenic role of long noncoding RNA H19 in GBM progression and examine whether autophagy and/or miR-491-5p participate in the process. The expression of H19 and autophagy-related genes in GBM and healthy control tissues was assessed via quantitative polymerase chain reaction. In addition, cell viability, proliferation, apoptosis and autophagy were respectively determined via cell counting kit-8 assay, clone formation assay, flow cytometry, western blotting and green fluorescent protein–microtubule-associated protein 1 light chain 3 alpha fluorescence analysis in vitro. Furthermore, a rescue assay was performed using rapamycin or miR-491-5p antagomir to examine the role of autophagy or miR-491-5p in H19-mediated regulation of proliferation and apoptosis. RNA pull-down and dual-luciferase reporter assays were employed to analyze the interaction between H19 and miR-491-5p. Additionally, tumor growth in a xenograft-bearing mouse model and autophagy in tumor mass were analyzed in vivo. The expression H19 was increased in GBM and was positively correlated with LC3 or Beclin-1. Silencing H19 inhibited growth and promoted apoptosis in GBM cells both in vitro and in vivo, and miR-491-5p was identified as one of the important mediators. H19 regulated the autophagy signaling pathway at least partly via miR-491-5p. Increased H19 expression in GBM exerts oncogenic effects by sponging miR-491-5p and enhancing autophagy. Therefore, H19 may be explored as a target for GBM therapy.

Comprehensive Oncogenic Features of Coronavirus Receptors in Glioblastoma Multiforme.

The COVID-19 pandemic caused by SARS-CoV-2 infection has placed health systems under excessive pressure and especially elderly people with cancer. Glioblastoma multiforme (GBM) is a malignant brain tumor with an increasing incidence in elderly individuals, and thereby GBM patients are a vulnerable population during the COVID-19 outbreak. Accumulating studies have implied that SARS-CoV-2 might invade the brain directly via coronavirus receptors. However, little is known about SARS-CoV-2 infection in the clinical development of GBM. Here, we explored the oncogenic roles of six coronavirus receptors (ACE2, DPP4, ANPEP, AXL, TMPRSS2, and ENPEP) in GBM using bioinformatics and experimental approaches. We found that ANPEP and ENPEP were significantly increased at both the mRNA and protein levels in GBM compared with normal brain tissue. Kaplan–Meier survival curves and Cox regression analysis demonstrated that high expressions of ANPEP and ENPEP are associated with poor prognosis and survival. Moreover, all receptors are positively correlated with the immune infiltration levels of monocyte. Furthermore, we identified 245 genes between COVID-19 and coronavirus receptors–correlated genes in GBM and performed a thorough analysis of their protein–protein interaction network, functional signaling pathway and molecular process. Our work explores for the first time the association of coronavirus receptors with GBM and suggests ANPEP and ENPEP as potential therapeutic targets of GBM irrespective of COVID-19.

Expression Profiles of HOXC6 Predict the Survival of Glioblastoma Patients and Correlate with Cell Cycle.

The goal of this study was to investigate the homeobox (HOX) gene expression status and its prognostic value in glioblastoma multiforme (GBM) and to uncover the biological processes related to its expression. The prognostic value of HOX genes in GBM was systematically investigated by a genome-wide analysis of HOX gene expression profiles in GBM patient samples in The Cancer Genome Atlas (TCGA) project (microarray dataset) and validation datasets. Using the differentially expressed gene (DEG) analysis and a Cox regression model, we discovered that the HOXC6 could stratify patients into significantly different survival (p = 0.0012, log-rank test) groups in the training cohort. TCGA RNA-seq and GSE16011 datasets were used for validation. Multivariate Cox and stratification analysis indicated that HOXC6 was an independent prognostic factor after adjusting for other clinical covariates. Bioinformatic analysis suggested that the HOXC6 might be involved in the cell cycle-related biological processes and pathways that are well established in the context of glioblastoma tumorigenesis. We further explored the bioinformatic implications by gene set enrichment analysis (GSEA). Tumor cell biology experiments verified the role of HOXC6 in proliferation and cell cycle progression. In conclusion, HOXC6 might be a candidate biomarker gene for individual treatment optimization of glioblastoma. HOXC6 expression has a significant prognostic value and is related to the cell cycle process in glioblastoma.

Screening the Significant Hub Genes by Comparing Tumor Cells, Normoxic and Hypoxic Glioblastoma Stem-like Cell Lines Using Co-Expression Analysis in Glioblastoma.

Glioblastoma multiforme (GBM) is categorized by rapid malignant cellular growth in the central nervous system (CNS) tumors. It is one of the most prevailing primary brain tumors, particularly in human male adults. Even though the combination therapy comprises surgery, chemotherapy, and adjuvant therapies, the survival rate is on average 14.6 months. Glioma stem cells (GSCs) have key roles in tumorigenesis, progression, and counteracting chemotherapy and radiotherapy. In our study, firstly, the gene expression dataset GSE45117 was retrieved and differentially expressed genes (DEGs) were spotted. The co-expression network analysis was employed on DEGs to find the significant modules. The most significant module resulting from co-expression analysis was the turquoise module. The turquoise module related to the tumor cells, hypoxia, normoxic treatments of glioblastoma tumor (GBT), and GSCs were screened. Sixty-one common genes in the turquoise module were selected generated through the co-expression analysis and protein–protein interaction (PPI) network. Moreover, the GO and KEGG pathway enrichment results were studied. Twenty common hub genes were screened by the NetworkAnalyst web instrument constructed on the PPI network through the STRING database. After survival analysis via the Kaplan–Meier (KM) plotter from The Cancer Genome Atlas (TCGA) database, we identified the five most significant hub genes strongly related to the progression of GBM. We further observed these five most significant hub genes also up-regulated in another GBM gene expression dataset. The protein–protein interaction (PPI) network of the turquoise module genes was constructed and a KEGG pathway enrichments study of the turquoise module genes was performed. The VEGF signaling pathway was emphasized because of the strong link with GBM. A gene–disease association network was further constructed to demonstrate the information of the progression of GBM and other related brain neoplasms. All hub genes assessed through this study would be potential markers for the prognosis and diagnosis of GBM.

Non-negative matrix factorization and differential expression analyses identify hub genes linked to progression and prognosis of glioblastoma multiforme

One of the most prevailing primary brain tumors in adult human male is glioblastoma multiforme (GBM), which is categorized by rapid cellular growth. Even though the combination therapy comprises surgery, chemotherapy, and adjuvant therapies, the survival rate, on average, is 14.6 months. Glioma stem cells (GSCs) have key roles in tumorigenesis, progression, and defiance against chemotherapy and radiotherapy. In our study, firstly, the gene expression dataset GSE124145 was retrieved; the non-negative matrix factorization (NMF) method was applied on GBM dataset, and differentially expressed genes analysis (DEGs) was performed. After which, overlapping genes between metagenes and DEGs were detected to examine the Gene Ontology (GO) categories in the biological process (BP) in the stemness of GBM. The common hub genes were used to construct protein–protein interaction (PPI) network and further GO, while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway was utilized to pinpoint the real hub genes. The analysis of hub genes particular for the same GO categories demonstrated that specific hub genes triggered distinct features of the same biological processes. After utilizing GSE124145 and The Cancer Genome Atlas (TCGA) dataset for survival analysis, we screened five real hub genes: GUCA1A, RFC2, GNG11, MMP19, and NRG1, which are strongly associated with the progression and prognosis of GBM. The DEGs analysis revealed that all real hub genes were overexpressed in GBM and TCGA datasets, which further validates our results. The constructed study of PPI, GO, and KEGG pathway on common hub genes was performed. Finally, the KEGG pathways performed on the top 15 candidate hub genes (including six real hub genes) of the PPI network in the GBM gene expression dataset study found mitogen-activated protein kinase (Mapk) signaling pathway to be the most significant pathway. The rest of the hub genes reviewed throughout the analysis might be favorable targets for diagnosing and treating GBM and lower-grade gliomas.

Novel Biomarker Genes for Prognosis of Survival and Treatment of Glioma.

Glioblastoma multiforme (GBM) is the most aggressive malignant primary central nervous system tumor. Although surgery, radiotherapy, and chemotherapy treatments are available, the 5-year survival rate of GBM is only 5.8%. Therefore, it is imperative to find novel biomarker for the prognosis and treatment of GBM. In this study, a total of 141 differentially expressed genes (DEGs) in GBM were identified by analyzing the GSE12657, GSE90886, and GSE90598 datasets. After reducing the data dimensionality, Kaplan-Meier survival analysis indicated that expression of PTPRN and RIM-BP2 were downregulated in GBM tissues when compared with that of normal tissues and that the expression of these genes was a good prognostic biomarker for GBM (p<0.05). Then, the GSE46531 dataset and the Genomics of Drug Sensitivity in Cancer (GDSC) database were used to examine the relationship between sensitivity radiotherapy (RT) and chemotherapy for GBM and expression of PTPRN and RIM-BP2. The expression of PTPRN was significantly high in RT-resistant patients (p<0.05) but it was not related to temozolomide (TMZ) resistance. The expression level of RIM-BP2 was not associated with RT or TMZ treatment. Among the chemotherapeutic drugs, cisplatin and erlotinib had a significantly good treatment effect for glioma with expression of PTPRN or RIM-BP2 and in lower-grade glioma (LGG) with IDH mutation. (p < 0.05). The tumor mutational burden (TMB) score in the low PTPRN expression group was significantly higher than that in the high PTPRN expression group (p=0.013), with a large degree of tumor immune cell infiltration. In conclusion, these findings contributed to the discovery process of potential biomarkers and therapeutic targets for glioma patients.