Genes In Glioblastoma Multiforme Research Articles

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.

Integrative analysis of DNA methylation and gene expression profiles to identify biomarkers of glioblastoma

Glioblastoma multiforme (GBM) is the most common, most invasive, and malignant type of primary brain tumor with poor prognosis and poor survival rate. Using GSE22891 the expression and methylation status of same GBM patients was evaluated to identify key epigenetic genes in GBM. Using |log2FC| > 1 and FDR 〈 0.05 as the threshold, DEGs including 4910 downregulated and 2478 upregulated were screened and by |log2FC| 〉 0.2 and p-value < 0.05, 3223 DMCs were detected. By merging the results of DEGs and DMCs, 643 genes were selected for network analysis by WGCNA, and based on expression values three modules and by methylation values, one module was selected. Using STRING and Cytoscape databases, PPI network of genes of all modules were constructed separately. According to the PPI network, core genes were picked out. The expression status of core genes was evaluated using GSE77043, GSE42656, GSE30563, GSE22891, GSE15824, and GSE122498, and 50 genes were validated. The methylation status of 50 genes was explored using GSE50923, GSE22891, and GSE36245, and finally, 12 hub genes including ARHGEF7, RAB11FIP4, PPP1R16B, OLFM1, CLDN10, BCAT1, C1QB, C1QC, IFI16, NUP37, PARP9, and PCLAF were selected. Using GEPIA database, the expression and by cBioportal the survival plot and also scatterplot of methylation versus expression of 12 hub genes were extracted based on TCGA. To determine the diagnostic values of the hub genes, the receiver operating characteristic (ROC) curve and the area under the curve (AUC) were extracted based on GSE22891 and GSE122498. Finally, we evaluated the expression level of the genes in tissue of 83 GBM patients and also non-tumoral adjacent (as control) tissues.

Antiproliferative effect of GTS-21 in glioblastoma cells.

Glioblastoma multiforme (GBM) is the most common malignant brain tumour in adults. The poor prognosis and short median overall survival of patients with GBM is associated with resistance to therapy after surgical and adjuvant treatment. The expression of various acetylcholine receptors (AChR) in GBM has been widely reported. The present study aimed to investigate the expression of cholinergic system-related genes in primary GBM and to explore the antiproliferative effect of 3-(2,4-dimethoxybenzylidene) anabaseine (GTS-21) in GBM cell lines. Therefore, the expression of 28 genes associated with the cholinergic system was detected using a customized RT2 Profiler PCR Array in 44 GBM and 5 healthy control brain tissue samples. In addition, the activity of GTS-21, an alpha 7 subunit nicotinic AChR (α7 nAChR) agonist, and that of α-bungarotoxin (α-BTX), an α7 nAChR antagonist, was determined in primary and established GBM cells. Therefore, the A172, U87 and G28 cell lines and primary GBM cells were treated with GTS-21, ACh or nicotine. Cell viability was evaluated using MTT assay at 24, 48 and 72 h following cell treatment with the corresponding compounds. The results revealed that the expression of cholinergic system-related components was notably downregulated, except that of cholinergic receptor nicotinic alpha 7 subunit (CHRNA7), in primary GBM and U87 cells. However, the dominant-negative duplicate form of CHRNA7 was also downregulated. Furthermore, A172 and G28 cells exhibited a heterogeneous gene expression pattern. Additionally, GTS-21 inhibited the proliferation of GBM cells in a dose- and time-dependent manner. Interestingly, treatment with α-BTX restored the proliferation of U87 cells, but not that of A172 and G28 cells. Collectively, the findings of the present study suggested that GTS-21 may inhibit the proliferation of GBM cells and may therefore serve as a novel therapeutic approach to the treatment of GBM, which warrants further investigation.

Comprehensive Analysis of CD163 as a Prognostic Biomarker and Associated with Immune Infiltration in Glioblastoma Multiforme

Background Glioblastoma multiforme (GBM) is the most common and aggressive primary malignancy in adults with high aggression. The prognosis of GBM patients is poor. There is a critical need for novel biomarkers for the prognosis and therapy of GBM. Methods Differentially expressed genes (DEGs) in GBM were screened using TCGA cohort. Univariate and multivariate Cox regression analyses were performed on DEGs to identify the optimal prognosis-related genes. qRT-PCR was performed to verify the result. Results A total of 5216 DEGs, including 2785 upregulated and 2458 downregulated genes, were obtained. Enrichment analysis revealed that these DEGs were mainly involved in the p53 signaling pathway and cell cycle, immune response, and MAPK signaling pathways. Moreover, the top 50 DEGs were associated with drug resistance or drug sensitivity. Prognosis analysis revealed that GBM patients with a high expression of CD163 and CHI3L2 had a poor overall survival, prognosis-free survival, and disease-specific survival. The univariate and multivariate analyses revealed that CD163 and age were independent factors affecting the prognosis of GBM patients. A validation study revealed that CD163 was upregulated in GBM tissues and associated with poor overall survival. Moreover, further analysis revealed that CD163 showed significant correlation with immune cells, immune biomarkers, chemokines, and chemokine receptors. We also identified several CD163-associated kinase, miRNA, and transcription factor targets in GBM, including LCK, miR-483, and ELF1. Conclusions In conclusion, our study suggested CD163 as a prognostic biomarker and associated it with immune infiltration in GBM.

The Effectiveness of Nanoparticles on Gene Therapy for Glioblastoma Cells Apoptosis: A Systematic Review.

Glioblastoma multiforme (GBM) is the most common and fatal type of glioma. Nanoparticles (NPs) are used in new approaches for the delivery of gene therapy in the treatment of GBM. The purpose of this article was to review the efficacy of NPs as the targeted carriers in the gene therapy aimed at apoptosis in GBM. The appropriate keywords such as nanoparticle, glioblastoma, gene therapy, apoptosis, and related words were used to search from PubMed, ISI Web of Science, and Scopus for relevant publications up to September 4, 2020, with no language restrictions. The present systematic review was performed based on PRISMA protocol and reviewed the articles evaluating the effects of nanoparticles, carriers of various gene therapies essentials, on GBM cells apoptosis in vitro and in vivo. The selected articles were considered using specific scores on the quality of the articles. Data extraction and quality evaluation were performed by two reviewers. Of 101 articles retrieved, forty-two met the inclusion criteria and were, therefore, subjected to the final deduction. The most widely used NP in GBM gene therapy studies is polyamidoamine (PAMAM). The most common gene therapy approach for apoptosis in GBM is using siRNAs. In conclusion, these studies validated that NPs could be a practical choice to enhance the efficiency and specific delivery in gene therapies for GBM cell apoptosis. However, the choice of NP type and gene therapy mechanism affect the GBM cell apoptotic efficiency.

The novel roles of virus infection-associated gene CDKN1A in chemoresistance and immune infiltration of glioblastoma.

Chemoresistance is a common limitation for successful treatment of glioblastoma multiforme (GBM). Recently, virus infections have been demonstrated to be associated with tumorigenesis and chemoresistance in tumors. However, the role of infection-related genes in GBM haven’t been clearly demonstrated. Here, we explored the roles and mechanisms of human T-lymphotropic virus type-1 (HTLV-1) infections in tumorigenesis and chemoresistance in GBM. Four candidate genes, CDKN1A, MSX1, MYC and CHEK2, were identified to be the codifferentially expressed genes between three temozolomide (TMZ) chemotherapy datasets and one HTLV-1 infection gene set. Next, comprehensive bioinformatics data from several databases indicated that only CDKN1A was significantly upregulated in both GBM tissues and cells and showed the greatest prognostic value in GBM patients. Clinical data identified the correlations between CDKN1A expression and clinicopathological parameters of GBM patients. Moreover, CDKN1A was found to be involved in AKT-mediated TMZ resistance of glioma cells. In addition, KEGG analysis of CDKN1A-associated coexpression genes showed that CDKN1A was potentially involved in complement and coagulation cascades pathways in GBM. Finally, TISIDB database was used to investigate the role of CDKN1A in tumor-immune system interactions in GBM. These findings enhanced our understanding of the roles of CDKN1A in tumorigenesis and therapy response in GBM.

Identification of key modules and hub genes in glioblastoma multiforme based on co-expression network analysis.

Glioblastoma multiforme (GBM) is the most malignant primary tumour in the central nervous system, but the molecular mechanisms underlying its pathogenesis remain unclear. In this study, data set GSE50161 was used to construct a co‐expression network for weighted gene co‐expression network analysis. Two modules (dubbed brown and turquoise) were found to have the strongest correlation with GBM. Functional enrichment analysis indicated that the brown module was involved in the cell cycle, DNA replication, and pyrimidine metabolism. The turquoise module was primarily related to circadian rhythm entrainment, glutamatergic synapses, and axonal guidance. Hub genes were screened by survival analysis using The Cancer Genome Atlas and Human Protein Atlas databases and further tested using the GSE4290 and Gene Expression Profiling Interactive Analysis databases. The eight hub genes (NUSAP1, SHCBP1, KNL1, SULT4A1, SLC12A5, NUF2, NAPB, and GARNL3) were verified at both the transcriptional and translational levels, and these gene expression levels were significant based on the World Health Organization classification system. These hub genes may be potential biomarkers and therapeutic targets for the accurate diagnosis and management of GBM.

Prediction and analysis of hub genes between glioblastoma and low-grade glioma using bioinformatics analysis.

Gliomas are an intractable tumor in the central nervous system. The present study aimed to identify the differentially expressed genes (DEGs) between glioblastoma multiforme (GBM) and low-grade gliomas (LGG) in order to investigate the mechanisms of different grades of gliomas. The Cancer Genome Atlas (TCGA) database was used to identify DEGs between GBM and LGG, and 2641 genes have been found differentially expressed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to determine the related functions and pathways of DEGs. Protein–protein interaction (PPI) network extracted a total of 444 nodes and 1953 interactions, and identified the top 6 hub genes in gliomas. The microarray data of the datasets GSE52009 and GSE4412, which were obtained from Gene Expression Omnibus (GEO) database, were used to externally validate DEGs expression levels. Gene Expression Profiling Interactive Analysis (GEPIA) database which was based on TCGA was used to explore the survival of hub genes in LGG and GBM. Additionally, the Oncomine database and Chinese Glioma Genome Atlas (CGGA) database were used to validate the mRNA expression level and prognostic value of hub genes. Gene Set Enrichment Analysis (GSEA) identified further hub genes-related pathways. In summary, through biological information and survival analysis, 6 hub genes may be new biomarkers for diagnosis and for guiding the choice of treatment strategies for different grades of gliomas.

Bidirectional Relation Between Parkinson's Disease and Glioblastoma Multiforme.

Cancer and Parkinson's disease (PD) define two disease entities that include opposite concepts. Indeed, the involved mechanisms are at different ends of a spectrum related to cell survival - one due to enhanced cellular proliferation and the other due to premature cell death. There is increasing evidence indicating that patients with neurodegenerative diseases like PD have a reduced incidence for most cancers. In support, epidemiological studies demonstrate an inverse association between PD and cancer. Both conditions apparently can involve the same set of genes, however, in affected tissues the expression was inversely regulated: genes that are down-regulated in PD were found to be up-regulated in cancer and vice versa, for example p53 or PARK7. When comparing glioblastoma multiforme (GBM), a malignant brain tumor with poor overall survival, with PD, astrocytes are dysregulated in both diseases in opposite ways. In addition, common genes, that are involved in both diseases and share common key pathways of cell proliferation and metabolism, were shown to be oppositely deregulated in PD and GBM. Here, we provide an overview of the involvement of PD- and GBM-associated genes in common pathways that are dysregulated in both conditions. Moreover, we illustrate why the simultaneous study of PD and GBM regarding the role of common pathways may lead to a deeper understanding of these still incurable conditions. Eventually, considering the inverse regulation of certain genes in PD and GBM will help to understand their mechanistic basis, and thus to define novel target-based strategies for causative treatments.

Bioinformatics analysis of high-throughput data to validate potential novel biomarkers and small molecule drugs for glioblastoma multiforme.

ObjectiveThere have been no recent improvements in the glioblastoma multiforme (GBM) outcome, with median survival remaining 15 months. Consequently, the need to identify novel biomarkers for GBM diagnosis and prognosis, and to develop targeted therapies is high. This study aimed to establish biomarkers for GBM pathogenesis and prognosis.MethodsIn total, 220 overlapping differentially expressed genes (DEGs) were obtained by integrating four microarray datasets from the Gene Expression Omnibus database (GSE4290, GSE12657, GSE15824, and GSE68848). Then a 140-node protein–protein interaction network with 343 interactions was constructed.ResultsThe immune response and cell adhesion molecules were the most significantly enriched functions and pathways, respectively, among DEGs. The designated hub genes ITGB5 and RGS4, which have a high degree of connectivity, were closely correlated with patient prognosis, and GEPIA database mining further confirmed their differential expression in GBM versus normal tissue. We also determined the 20 most appropriate small molecules that could potentially reverse GBM gene expression, Prestwick-1080 was the most promising and had the highest negative scores.ConclusionsThis study identified ITGB5 and RGS4 as potential biomarkers for GBM diagnosis and prognosis. Insights into molecular mechanisms governing GBM occurrence and progression will help identify alternative biomarkers for clinical practice.

Identification of potential crucial genes and molecular mechanisms in glioblastoma multiforme by bioinformatics analysis.

Glioblastoma multiforme (GBM) is the most common and malignant brain tumor of the adult central nervous system and is associated with poor prognosis. The present study aimed to identify the hub genes in GBM in order to improve the current understanding of the underlying mechanism of GBM. The RNA-seq data were downloaded from The Cancer Genome Atlas database. The edgeR package in R software was used to identify differentially expressed genes (DEGs) between two groups: Glioblastoma samples and normal brain samples. Gene Ontology (GO) functional enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed using Database for Annotation, Visualization and Integrated Discovery software. Additionally, Cytoscape and Search Tool for the Retrieval of Interacting Genes/Proteins tools were used for the protein-protein interaction network, while the highly connected modules were extracted from this network using the Minimal Common Oncology Data Elements plugin. Next, the prognostic significance of the candidate hub genes was analyzed using UALCAN. In addition, the identified hub genes were verified by reverse transcription-quantitative (RT-q) PCR. In total, 1,483 DEGs were identified between GBM and control samples, including 954 upregulated genes and 529 downregulated genes (P<0.01; fold-change >16) and these genes were involved in different GO terms and signaling pathways. Furthermore, CDK1, BUB1, BUB1B, CENPA and GNG3 were identified as key genes in the GBM samples. The UALCAN tool verified that higher expression level of CENPA was relevant to poorer overall survival rates. In conclusion, CDK1, BUB1, BUB1B, CENPA and GNG3 were found to be potential biomarkers for GBM. Additionally, ‘cell cycle’ and ‘γ-aminobutyric acid signaling’ pathways may serve a significant role in the pathogenesis of GBM.

Identification of aberrantly methylated differentially expressed genes in glioblastoma multiforme and their association with patient survival.

Glioblastoma multiforme (GBM) is the most malignant primary tumour type of the central nervous system with limited therapeutic options and poor prognosis, and its pathogenic mechanisms have remained to be fully elucidated. Aberrant DNA methylation is involved in multiple biological processes and may contribute to the occurrence and development of GBM by affecting the expression of certain genes. However, the specific molecular mechanisms remain to be fully elucidated. The present study focused on uncovering differentially expressed genes with altered methylation status in GBM and aimed to discover novel biomarkers for the diagnosis and treatment of GBM. These genes were identified by combined analysis of multiple gene expression and methylation datasets from gene expression omnibus (GSE16011, GSE50161 and GSE 50923) to increase the reliability. In addition, The Cancer Genome Atlas (TCGA) dataset for GBM was used to test the stability of the results. Overall, 251 hypomethylated upregulated genes (Hypo-UGs) and 199 hypermethylated downregulated genes (Hyper-DGs) were identified in the present study. Functional enrichment analysis revealed that the Hypo-UGs are involved in the regulation of immune- and infection-associated signalling, while the Hyper-DGs are involved in the regulation of synaptic transmission. The three hub genes for Hyper-DGs (somatostatin, neuropeptide Y and adenylate cyclase 2) and five hub genes for Hypo-UGs [interleukin-8, matrix metalloproteinase (MMP)9, cyclin-dependent kinase 1, 2′-5′-oligoadenylate synthetase 1, C-X-C motif chemokine ligand 10 and MMP2] were identified by protein-protein interaction network analysis. Among the Hypo-UGs and Hyper-DGs, overexpression of C-type lectin domain containing 5A, epithelial membrane protein 3, solute carrier family 43 member 3, STEAP3 metalloreductase, tumour necrosis factor α-induced protein 6 and apolipoprotein B mRNA editing enzyme catalytic subunit 3G was significantly associated with poor prognosis in the TCGA and GSE16011 datasets (P<0.001). In conclusion, the present study uncovered numerous novel aberrantly methylated genes and pathways associated with GBM. Methylation-based markers, including the hub genes and prognostic genes identified, may potentially serve as markers for the diagnosis of GBM and targets for its treatment.

Absent in melanoma 2 regulates tumor cell proliferation in glioblastoma multiforme.

Inflammation is a key aspect of glioblastoma multiforme (GBM) although it remains unclear how it contributes to GBM pathogenesis. Inflammasomes are intracellular multi-protein complexes that are involved in innate immunity and are activated by cellular stress, principally in macrophages. This study examined the expression of inflammasome-associated genes in GBM, particularly absent in melanoma 2 (AIM2). Tissue samples from surgically-resected GBM tumors (n = 10) were compared to resected brain specimens from patients with epilepsy (age- and sex-matched Other Disease Controls (ODC, n=5)) by qRT-PCR, western blotting and immunofluorescence. Gene expression studies in human astrocytoma U251 cells were performed and the effects of deleting the absent in melanoma 2 (AIM2) gene using the CRISPR-Cas9 system were analyzed. GBM tissues showed significantly elevated expression of multiple immune (CD3E, CD163, CD68, MX1, ARG1) and inflammasome (AIM2, NLRP1, IL18, CASP1, and IL-33) genes compared to ODC tissues, without induction of IL1B, IFNG or TNFA. An insert-containing AIM2 variant transcript was highly expressed in GBM tissues and in U251 cells. AIM2 immunoreactivity was concentrated in the tumor core in the absence of PCNA immunodetection and showed a predominant 52 kDa immunoreactive band on western blot. Deletion of AIM2 resulted in significantly enhanced proliferation of U251 cells, which also displayed increased resistance to temozolomide treatment. GBM tumors express a distinct profile of inflammasome-associated genes in a tumor-specific manner. AIM2 expression in tumor cells suppressed cell proliferation while also conferring increased susceptibility to contemporary GBM therapy.

DNA methylation profiling identifies potentially significant epigenetically-regulated genes in glioblastoma multiforme.

Glioblastoma multiforme (GBM) is one of the most lethal and damaging types of human cancer. The current study was conducted to identify differentially methylated genes (DMGs) between GBM and normal controls, and to improve our understanding of GBM at the epigenetic level. The DNA methylation profile of GBM was downloaded from the Gene Expression Omnibus (GEO) database using the accession number GSE50923. The MethyAnalysis package was applied to identify DMGs between GBM and controls, which were then analyzed by functional enrichment analysis. Protein-protein interaction (PPI) networks were constructed using the hypermethylated and hypomethylated genes. Finally, transcription factors (TFs) that can regulate the hypermethylated and hypomethylated genes were predicted, followed by construction of transcriptional regulatory networks. Furthermore, another relevant dataset, GSE22867, was downloaded from the GEO database for data validation. A total of 476 hypermethylated and 850 hypomethylated genes were identified, which were mainly associated with the functions of ‘G-protein-coupled receptors ligand binding’, ‘cytokine activity’, ‘cytokine-cytokine receptor interaction’, and ‘D-glutamine and D-glutamate metabolism’. The hypermethylated gene neuropeptide Y (NPY) and the hypomethylated gene tumor necrosis factor (TNF) demonstrated high degrees in the PPI network. Forkhead box protein A1 (FOXA1), potassium voltage-gated channel subfamily C member 3 (KCNC3) and caspase-8 (CASP8) exhibited high degrees in the transcriptional regulatory networks. In addition, the methylation profiles of NPY, TNF, FOXA1, KCNC3 and CASP8 were confirmed by another dataset. In summary, the present study systematically analyzed the DNA methylation profile of GBM using bioinformatics approaches and identified several abnormally methylated genes, providing insight into the molecular mechanism underlying GBM.

Prognostic significance of contactin 3 expression and associated genes in glioblastoma multiforme.

Contactin 3 (CNTN3) is a member of the contactin family that is primarily expressed in the nervous system. However, to the best of our knowledge, expression of contactin and its role in the development and progression of brain tumours has not been studied. Although glioblastoma multiforme (GBM) is the most common malignant brain tumour, advances in therapeutic options for patients with GBM have been modest due to an incomplete understanding of the molecular mechanisms underlying development and progression. The aim of the present study was to examine the correlation between CNTN3 and its associated genes and the clinical outcome in patients with GBM. CNTN3 and the expression levels of associated genes were analysed in GBM datasets obtained from the SAGE Anatomical viewer website, Gene Expression Omnibus, Oncomine and The Cancer Genome Atlas. CNTN3 was significantly downregulated in patients with GBM. Subsequently, the expression of CNTN3 was further validated using immunohistochemistry in a cohort of GBM specimens. The immunohistochemistry results were consistent with the in silico analyses. Kaplan-Meier analysis indicated that patients with lower expression levels of CNTN3 had a significantly shorter overall survival (OS) time compared with patients with higher levels of CNTN3 expression. Univariate and multivariate Cox regression analyses demonstrated that CNTN3 expression was an independent prognostic indicator in patients with GBM. Furthermore, gene set enrichment analysis revealed that CNTN3 was associated with the receptor tyrosine-protein kinase (ErbB) signalling pathway. In the ErbB signalling pathway, epidermal growth factor receptor (EGFR) was negatively correlated with CNTN3. Taken together, these data suggest that lower expression levels of CNTN3 may be an independent biomarker that predicts poor OS time in patients with GBM, and that EGFR expression in the ErbB pathway may be associated with CNTN3 expression.

Integrated Transcriptomic Analysis of Necrosis-related Gene in Diffuse Gliomas.

Glioblastoma multiforme (GBM), an aggressive brain tumor, is characterized histologically by the presence of a necrotic center surrounded by so-called pseudopalisading cells. Pseudopalisading necrosis has long been used as a prognostic feature. However, the underlying molecular mechanism regulating the progression of GBMs remains unclear. We hypothesized that the gene expression profiles of individual cancers, specifically necrosis-related genes, would provide objective information that would allow for the creation of a prognostic index. Gene expression profiles of necrotic and nonnecrotic areas were obtained from the Ivy Glioblastoma Atlas Project (IVY GAP) database to explore the differentially expressed genes.A robust signature of seven genes was identified as a predictor for glioblastoma and low-grade glioma (GBM/LGG) in patients from The Cancer Genome Atlas (TCGA) cohort. This set of genes was able to stratify GBM/LGG and GBM patients into high-risk and low-risk groups in the training set as well as the validation set. The TCGA, Repository for Molecular Brain Neoplasia Data (Rembrandt), and GSE16011 databases were then used to validate the expression level of these seven genes in GBMs and LGGs. Finally, the differentially expressed genes (DEGs) in the high-risk and low-risk groups were subjected to gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes pathway, and gene set enrichment analyses, and they revealed that these DEGs were associated with immune and inflammatory responses. In conclusion, our study identified a novel seven-gene signature that may guide the prognostic prediction and development of therapeutic applications.

Construction of Potential Glioblastoma Multiforme-Related miRNA-mRNA Regulatory Network.

Background: Glioblastoma multiforme (GBM), the most common and aggressive human malignant brain tumor, is notorious for its limited treatment options and poor prognosis. MicroRNAs (miRNAs) are found to be involved in tumorigenesis of GBM. However, a comprehensive miRNA-mRNA regulatory network has still not been established.Methods: A miRNA microarray dataset (GSE90603) was obtained from GEO database. Then, we employed GEO2R tool to perform differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The GBM mRNA dataset were downloaded from TCGA database for identifying differentially expressed genes (DEGs). Next, GO annotation and KEGG pathway enrichment analysis was conducted. PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes was further evaluated.Results: Total 33 DE-miRNAs, consisting of 10 upregulated DE-miRNAs and 23 downregulated DE-miRNAs, were screened. SP1 was predicted to potentially regulate most of screened DE-miRNAs. Three thousand and twenty seven and 3,879 predicted target genes were obtained for upregulated and downregulated DE-miRNAs, respectively. Subsequently, 1,715 upregulated DEGs and 1,259 downregulated DEGs were identified. Then, 149 and 295 potential downregulated and upregulated genes commonly appeared in target genes of DE-miRNAs and DEGs were selected for GO annotation and KEGG pathway enrichment analysis. The downregulated genes were significantly enriched in cGMP-PKG signaling pathway and calcium signaling pathway whereas the upregulated genes were enriched in pathways in cancer and PI3K-Akt signaling pathway. Construction and analysis of PPI network showed that STXBP1 and TP53 were recognized as hub genes with the highest connectivity degrees. Expression analytic result of the top 20 hub genes in GBM using GEPIA database was generally identical with previous differential expression analysis for TCGA data. EGFR, PPP3CB, and MYO5A expression was significantly associated with patients' OS.Conclusions: In this study, we established a potential GBM-related miRNA-mRNA regulatory network, which explores a comprehensive understanding of the molecular mechanisms and provides key clues in seeking novel therapeutic targets for GBM. In the future, more experiments need to be performed to validate our current findings.

Insilico analysis identified miRNA‑based therapeutic agents against glioblastoma multiforme.

MicroRNAs (miRNAs or miRs) contribute to the development of various malignant neoplasms, including glioblastoma multiforme (GBM). The present study aimed to explore the pathogenesis of GBM and to identify latent therapeutic agents for patients with GBM, based on an in silico analysis. Gene chips that provide miRNA expression profiling in GBM were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEMs) were also determined via the RobustRankAggreg algorithm. The target genes of DEMs were predicted and then intersected with GBM-associated genes that were collected from the Gene Expression Profiling Interactive Analysis. Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of the overlapping genes were then performed. Simultaneously, a connectivity map (CMap) analysis was performed to screen for potential therapeutic agents for GBM. A total of 10 DEMs (hsa-miR-196a, hsa-miR-10b, hsa-miR-196b, hsa-miR-18b, hsa-miR-542-3p, hsa-miR-129-3p, hsa-miR-1224-5p, hsa-miR-876-3p and hsa-miR-770-5p) were obtained from three GEO gene chips (GSE25631, GSE42657 and GSE61710). Then, 1,720 target genes of the 10 miRNAs and 4,185 differently expressed genes in GBM were collected. By intersecting the aforementioned gene clusters, the present study identified 390 overlapping genes. GO and KEGG analyses of the 390 genes demonstrated that these genes were involved in certain cancer-associated biological functions and pathways. Eight genes [(GTPase NRas (NRAS), calcium/calmodulin-dependent protein kinase type II subunit Gamma (CAMK2G), platelet-derived growth factor receptor alpha (PDGFRA), calmodulin 3 (CALM3), cyclin-dependent kinase 6 (CDK6), calcium/calmodulin-dependent protein kinase type II subunit beta (CAMK2B), retinoblastoma-associated protein (RB1) and protein kinase C beta type (PRKCB)] that were centralized in the glioma pathway were selected for CMap analysis. Three chemicals (W-13, gefitinib and exemestane) were identified as putative therapeutic agents for GBM. In summary, the present study identified three miRNA-based chemicals for use as a therapy for GBM. However, more experimental data are needed to verify the therapeutic properties of these latent drugs in GBM.

Identification of a panel of genes as a prognostic biomarker for glioblastoma.

BackgroundGlioblastoma multiforme (GBM) is a fatal disease without effective therapy. Identification of new biomarkers for prognosis would enable more rational selections of strategies to cure patients with GBM and prevent disease relapse.MethodsSeven datasets derived from GBM patients using microarray or next generation sequencing in R2 online database (http://r2.amc.nl) were extracted and then analyzed using JMP software. The survival distribution was calculated according to the Kaplan-Meier method and the significance was determined using log-rank statistics. The sensitivity of a panel of GBM cell lines in response to temozolomide (TMZ), salinomycin, celastrol, and triptolide treatments was evaluated using MTS and tumor-sphere formation assay.FindingsWe identified that CD44, ATP binding cassette subfamily C member 3 (ABCC3), and tumor necrosis factor receptor subfamily member 1A (TNFRSF1A) as highly expressed genes in GBMs are associated with patients' poor outcomes and therapy resistance. Furthermore, these three markers combined with MGMT, a conventional GBM marker, can classify GBM patients into five new subtypes with different overall survival time in response to treatment. The four-gene signature and the therapy response of GBMs to a panel of therapeutic compounds were confirmed in a panel of GBM cell lines.InterpretationThe data indicate that the four-gene panel can be used as a therapy response index for GBM patients and potential therapeutic targets. These results provide important new insights into the early diagnosis and the prognosis for GBM patients and introduce potential targets for GBM therapeutics.FundBaylor Scott & White Health Startup Fund (E.W.); Collaborative Faculty Research Investment Program (CFRIP) of Baylor University, Baylor Scott & White Health, and Baylor College of Medicine (E.W., T.S., J.H.H.); NIH R01 NS067435 (J.H.H.); Scott & White Plummer Foundation Grant (J.H.H.); National Natural Science Foundation of China 816280007 (J.H.H. and Fu.W.).

Candidate Biomarkers and Molecular Mechanism Investigation for Glioblastoma Multiforme Utilizing WGCNA.

To reveal the potential molecular mechanism of glioblastoma multiforme (GBM) and provide the candidate biomarkers for GBM gene therapy. Microarray dataset GSE50161 was obtained from GEO database. The differentially expressed genes (DEGs) were identified between GBM samples and control samples, followed by the module partition analysis based on WGCNA. Then, the pathway and functional enrichment analyses of DEGs were performed. The hub genes were further investigated, followed by the survival analysis and data validation. A total of 1913 DEGs were investigated between two groups, followed by analysis of 5 modules using WGCNA. These DEGs were mainly enriched in functions like inflammatory response. The hub genes including upregulated N-Myc and STAT Interactor (NMI), Capping Actin Protein-Gelsolin Like (CAPG), and Proteasome Subunit Beta 8 (PSMB8) were revealed as potential liquid biopsy molecules for GBM diagnose. Moreover, Nucleolar and Spindle Associated Protein 1 (NUSAP1) and G Protein-Coupled Receptor 65 (GPR65) were outstanding genes in survival analysis. Our results suggested that CPNE6, HAPLN2, CMTM3, NMI, CAPG, and PSMB8 might be used as potential molecules for liquid biopsy of GBM. NUSAP1 and GPR65 might be novel prognostic targets for GBM gene therapy. Furthermore, the upregulated NMI might play an important role in GBM progression via inflammatory response.