Association between chronic periodontitis and the risk of Alzheimer's disease: combination of text mining and GEO dataset.

BACKGROUND: Although chronic periodontitis has previously been reported to be linked with Alzheimer's disease (AD), the pathogenesis between the two is unclear. The purpose of this study is to analyze and screen the relevant and promising molecular markers between chronic periodontitis and Alzheimer's disease (AD). METHODS: In this paper, we analyzed three AD expression datasets and extracted differentially expressed genes (DEGs), then intersected them with chronic periodontitis genes obtained from text mining, and finally obtained integrated DEGs. We followed that by enriching the matching the matching cell signal cascade through DAVID analysis. Moreover, the MCODE of Cytoscape software was employed to uncover the protein-protein interaction (PPI) network and the matching hub gene. Finally, we verified our data using a different independent AD cohort. RESULTS: The chronic periodontitis gene set acquired from text abstracting was intersected with the previously obtained three AD groups, and 12 common genes were obtained. Functional enrichment assessment uncovered 12 cross-genes, which were mainly linked to cell morphogenesis involved in neuron differentiation, leading edge membrane, and receptor ligand activity. After PPI network creation, the ten hub genes linked to AD were retrieved, consisting of SPP1, THY1, CD44, ITGB1, HSPB3, CREB1, SST, UCHL1, CCL5 and BMP7. Finally, the function terms in the new independent dataset were used to verify the previous dataset, and we found 22 GO terms and one pathway, "ECM-receptor interaction pathways", in the overlapping functional terms. CONCLUSIONS: The establishment of the above-mentioned candidate key genes, as well as the enriched signaling cascades, provides promising molecular markers for chronic periodontitis-related AD, which may help the diagnosis and treatment of AD patients in the future.

Preoperative grading of supratentorial nonenhancing gliomas by high b-value diffusion-weighted 3 T magnetic resonance imaging.

The purpose of this study was to determine the difference in discrimination between high- and low-grade supratentorial nonenhancing gliomas (HGGs and LGGs, respectively) when using apparent diffusion coefficient (ADC) values with high or standard b-value. Thirty-nine patients underwent conventional magnetic resonance imaging and diffusion-weighted imaging (DWI) with standard and high b-values (b = 1000 and 3000 s/mm2, respectively). Minimum, maximum, and mean ADC values (ADCMIN, ADCMAX, and ADCMEAN, respectively) were measured from ADC maps with both b-values. Receiver operating curve analysis was used to determine the cutoff ADC values for distinguishing between nonenhancing HGGs and LGGs. ADCMIN, ADCMAX, and ADCMEAN values for the nonenhancing HGGs were lower than those for LGGs. These differences were much larger when a high b-value was used (all P < 0.0001) than when a standard b-value was used (P = 0.0001, <0.0001, and <0.0001, respectively). Discriminant analysis indicated that the greatest likelihood for discriminating HGGs and LGGs when ADCMEAN was obtained with a high b-value, with cutoff value of 0.814 × 10-3 mm2/s. ADC values obtained with a high b-value can be useful for grading and surgical management of nonenhancing HGGs and LGGs. The lowest degree of overlap was obtained when ADCMEAN was determined with a b-value of 3000 s/mm2.

Gamma-glutamylcyclotransferase promotes the growth of human glioma cells by activating Notch-Akt signaling.

Glioma as an aggressive type tumor is rapidly growing and has become one of the leading cause of cancer-related death worldwide. γ-Glutamylcyclotransferase (GGCT) has been shown as a diagnostic marker in various cancers. To reveal whether there is a correlation between GGCT and human glioma, GGCT expression in human glioma tissues and cell lines was first determined. We found that GGCT expression was up-regulated in human glioma tissues and cell lines. Further, we demonstrate that GGCT knockdown inhibits glioma cell T98G and U251 proliferation and colony formation, whereas GGCT overexpression leads to oppose effects. GGCT overexpression promotes the expression of Notch receptors and activates Akt signaling in glioma cells, and Notch-Akt signaling is activated in glioma tissues with high expression of GGCT. Finally, we show that inhibition of Notch-Akt signaling with Notch inhibitor MK-0752 blocks the effects of GGCT on glioma proliferation and colony formation. In conclusion, GGCT plays a critical role in glioma cell proliferation and may be a potential cancer therapeutic target.

Inhibition of Wnt/ß-catenin signal is alleviated reactive gliosis in rats with hydrocephalus.

BACKGROUND: Reactive gliosis has been implicated in the pathogenesis of communicating hydrocephalus. Because the activation of Wnt/ß-catenin signaling pathway is considered as a significant factor to contribute to brain development, neurodegenerative process, and reactive gliosis, we target this pathway for intervention by using sFRP-l and investigated the expression of ß-catenin, cyclin D-1, and glial fibrillary acidic protein (GFAP) in the brain of experimental hydrocephalic rats in terms of protein and gene expression. METHODS: Therefore, 30 adult SD rats were randomly divided into the normal group (n = 5), the sham operation group (n = 5), the hydrocephalus group (n = 10), and the sFRP-l group (n = 10). Hydrocephalic rat models were induced by intraventricular injections of 3% kaolin while sFRP-l group was treated by sFRP-l with kaolin injections. The ventricular dilatation was examinated by MRI at 2-week post-operation. After that, ß-catenin, cyclin D-1, and GFAP were qualified by Western blot and immunohistochemistry. RESULTS: According to the result, the expression of ß-catenin and cyclin D-1 increased (P < 0. 05) in the brain tissue of the hydrocephalus group compared with that of the sham group, while GFAP expression in the hydrocephalus group is more obvious (P < 0. 05). In the sFRP-l group, the expression of ß-catenin and cyclin D-1 and GFAP expression is lower (P < 0. 05) compared with those of the hydrocephalus group. We demonstrated that the Wnt/ß-catenin pathway is activated in the experimental hydrocephalic rat brain. sFRP-l inhibited the expression of ß-catenin and cyclin D-1 and alleviated reactive gliosis in the hydrocephalic rat brain tissue, while the development of hydrocephalus was delayed. CONCLUSION: These results suggest that regulating Wnt/ß-catenin signaling pathway may provide new therapeutic methods for hydrocephalic patients.

Hematoma Enlargement After Intracerebral Hemorrhage: A Bibliometric Analysis.

OBJECTIVE: To conduct a quantitative analysis of published studies on hematoma enlargement after intracerebral hemorrhage. METHODS: Studies on hematoma enlargement after cerebral hemorrhage were retrieved from the Web of Science database on June 30, 2023. Microsoft Excel, VOSviewer, and CiteSpace software were used for bibliometric analysis and visualization, focusing on the quantitative characteristics of the literature. RESULTS: A total of 444 articles were published in 161 journals, with 2161 authors from 41 countries and 717 institutions. The most published authors, countries, and institutions were Goldstein, the USA, and Massachusetts General Hospital. Stroke published the most studies, but the average citation number per year of Lancet Neurology far exceeded that of other journals. The research field of hematoma enlargement is mainly divided into 3 focuses, including mechanisms, identification (computed tomography signs, predictive models), and treatment (hemostasis, antihypertensive therapy). Most bursts in publication number have been since 2010, where the highest burst was from research on spot signs, and the latest burst focused on tranexamic acid. Treatment using tranexamic acid based on different computed tomography signs is a focus of current research, but the effectiveness still requires further exploration. CONCLUSIONS: This bibliometric analysis analyzed the research framework and hotspots on hematoma enlargement after cerebral hemorrhage, which can help researchers better understand this field and provide potential suggestions for collaborations and research.

Proteomic and metabolomic analyses illustrate the mechanisms of expression of the O6 -methylguanine-DNA methyltransferase gene in glioblastoma.

AIM: Glioblastoma (GBM) has been reported to be the most common high-grade primary malignant brain tumor in clinical practice and has a poor prognosis. O6 -methylguanine-DNA methyltransferase (MGMT) promoter methylation has been related to prolonged overall survival (OS) in GBM patients after temozolomide treatment. METHODS: Proteomics and metabolomics were combined to explore the dysregulated metabolites and possible protein expression alterations in white matter (control group), MGMT promoter unmethylated GBM (GBM group) or MGMT promoter methylation positive GBM (MGMT group). RESULTS: In total, 2745 upregulated and 969 downregulated proteins were identified in the GBM group compared to the control group, and 131 upregulated and 299 downregulated proteins were identified in the MGMT group compared to the GBM group. Furthermore, 131 upregulated and 299 downregulated metabolites were identified in the GBM group compared to the control group, and 187 upregulated and 147 downregulated metabolites were identified in the MGMT group compared to the GBM group. The results showed that 94 upregulated and 19 downregulated proteins and 20 upregulated and 16 downregulated metabolites in the MGMT group were associated with DNA repair. KEGG pathway enrichment analysis illustrated that the dysregulated proteins and metabolites were involved in multiple metabolic pathways, including the synthesis and degradation of ketone bodies, amino sugar and nucleotide sugar metabolism. Moreover, integrated metabolomics and proteomics analysis was performed, and six key proteins were identified in the MGMT group and GBM group. Three key pathways were recognized as potential biomarkers for recognizing MGMT promoter unmethylated GBM and MGMT promoter methylation positive GBM from GBM patient samples, with areas under the curve of 0.7895, 0.7326 and 0.7026, respectively. CONCLUSION: This study provides novel mechanisms to understand methylation in GBM and identifies some biomarkers for the prognosis of two different GBM types, MGMT promoter unmethylated or methylated GBM, by using metabolomics and proteomics analyses.

FZD1/KLF10-hsa-miR-4762-5p/miR-224-3p-circular RNAs axis as prognostic biomarkers and therapeutic targets for glioblastoma: a comprehensive report.

BACKGROUND: The circular RNA (circRNA) plays a vital role in the pathogenesis of tumors as a competitive endogenous RNA (ceRNA). Given the high aggressiveness and fatality rate of glioblastoma (GBM) as well as poor prognosis, it is necessary to construct a circRNA-related ceRNA network for further studies on the mechanism of GBM and identify possible biomarkers as well as therapeutic drugs. METHODS: Three datasets from the gene expression omnibus (GEO) database were downloaded to distinguish differential circRNAs, microRNAs, and messenger RNAs respectively in GBM. With the help of GEPIA2, circBank, CSCD, TargetScan, miRDB, and miRTarBase databases, we established a circRNAs-related ceRNA network in GBM. Functional enrichments were employed to profile the most relevant mRNAs to indirectly clarify the mechanisms of the ceRNA network. Based on the expression profile data and survival information of GBM patients from the GEO and the cancer genome atlas (TCGA) databases, we performed survival analysis to select prognostic mRNAs and constructed a novel circRNA-miRNA-mRNA central regulatory subnetwork. The DGIdb database was used to find potential drug-gene interactions. RESULTS: The datasets obtained from the GEO and TCGA databases were analyzed, and 504 differentially expressed mRNAs (DEmRNAs), 71 differentially expressed microRNAs (DEmiRNAs), and 270 differentially expressed circRNAs (DEcircRNAs) were screened out. The novel ceRNA regulatory network included 22 circRNAs, 11 miRNAs, and 15 mRNAs. FZD1 and KLF10 were significantly correlated with the overall survival rate of patients with GBM (P < 0.05). The final survival subnetwork contained six circRNAs, two miRNAs, and two mRNAs. Two small-molecule compounds and one antibody could be used as therapeutic drugs for GBM. Interestingly, the Wnt signaling pathway appeared in both KEGG and GO functional terms. CONCLUSIONS: Results of this study demonstrate that FZD1 and KLF10 may exert regulatory functions in GBM, and the ceRNA-mediated network could be a therapeutic strategy for GBM.

The CDK inhibitor AT7519 inhibits human glioblastoma cell growth by inducing apoptosis, pyroptosis and cell cycle arrest.

Glioblastoma multiforme (GBM) is the most lethal primary brain tumor with a poor median survival of less than 15 months. However, clinical strategies and effective therapies are limited. Here, we found that the second-generation small molecule multi-CDK inhibitor AT7519 is a potential drug for GBM treatment according to high-throughput screening via the Approved Drug Library and Clinical Compound Library (2718 compounds). We found that AT7519 significantly inhibited the cell viability and proliferation of U87MG, U251, and patient-derived primary GBM cells in a dose-dependent manner. Furthermore, AT7519 also inhibited the phosphorylation of CDK1/2 and arrested the cell cycle at the G1-S and G2-M phases. More importantly, AT7519 induced intrinsic apoptosis and pyroptosis via caspase-3-mediated cleavage of gasdermin E (GSDME). In the glioblastoma intracranial and subcutaneous xenograft assays, tumor volume was significantly reduced after treatment with AT7519. In summary, AT7519 induces cell death through multiple pathways and inhibits glioblastoma growth, indicating that AT7519 is a potential chemical available for GBM treatment.

Minocycline reduces reactive gliosis in the rat model of hydrocephalus.

BACKGROUND: Reactive gliosis had been implicated in injury and recovery patterns associated with hydrocephalus. Our aim is to determine the efficacy of minocycline, an antibiotic known for its anti-inflammatory properties, to reduce reactive gliosis and inhibit the development of hydrocephalus. RESULTS: The ventricular dilatation were evaluated by MRI at 1-week post drugs treated, while GFAP and Iba-1were detected by RT-PCR, Immunohistochemistry and Western blot. The expression of GFAP and Iba-1 was significantly higher in hydrocephalic group compared with saline control group (p < 0.05). Minocycline treatment of hydrocephalic animals reduced the expression of GFAP and Iba-1 significantly (p < 0.05). Likewise, the severity of ventricular dilatation is lower in minocycline treated hydrocephalic animals compared with the no minocycline group (p < 0.05). CONCLUSION: Minocycline treatment is effective in reducing the gliosis and delaying the development of hydrocephalus with prospective to be the auxiliary therapeutic method of hydrocephalus.

Transgenic nude mouse with green fluorescent protein expression-based human glioblastoma multiforme animal model with EGFR expression and invasiveness.

Previously, we developed an orthotopic xenograft model of human glioblastoma multiforme (GBM) with high EGFR expression and invasiveness in Balb/c nu/nu nude mice. Now we also developed the same orthotopic xenograft model in transgenic nude mice with green fluorescent protein (GFP) expression. The present orthotopic xenografts labeled by phycoerythrin fluorescing red showed high EGFR expression profile, and invasive behavior under a bright green-red dual-color fluorescence background. A striking advantage in the present human GBM model is that the change of tumor growth can be observed visually instead of sacrificing animals in our further antitumor therapy studies.

Awake craniotomy for removal of gliomas in eloquent areas: An analysis of 21 cases.

OBJECTIVE: To discuss the techniques and methods in respective operation of brain gliomas located in eloquent brain region under awake anesthesia state METHODS: 21 patients admitted into Department of Neurosurgery of the First Affiliated Hospital of Xiamen University were chosen as subject. Diagnosed with brain gliomas, they received operation with neuronavigation, intraoperative ultrasonography for locating the lesion and intraoperative direct electric stimulation for functional mapping of the eloquent brain region after receiving awake anesthesia. All patients were followed up from post-surgical 3 months to 18 months. RESULTS: Applied with MRI scanning during post-surgical 60-90d, resection results shows that 5 cases (23.8%) received total resection of lesions, 10 cases (47.6%) received subtotal resection while 6 cases (28.6%) received partial resection. Post-surgical performance shows 8 cases (38.1%) of transitory postoperative aphasia, 5 cases(23.8%) of transitory postoperative dyskinesia and 1 case(4.8%) of permanent dyskinesia. Recovery was achieved in the patients except for the 1 case of permanent dyskinesia. CONCLUSIONS: Comprehensive application of awake anesthesia, neuronavigation, intraoperative ultrasonography and intraoperative direct electrical stimulation facilitates recognition of clear position relationship between gliomas and eloquent brain region, and maximum safe resection of gliomas in eloquent brain region with maximal protection of brain function.

Identification of ubiquitin-specific protease 32 as an oncogene in glioblastoma and the underlying mechanisms.

Glioblastoma (GBM) patients present poor prognosis. Deubiquitination by deubiquitinating enzymes (DUBs) is a critical process in cancer progression. Ubiquitin-specific proteases (USPs) constitute the largest sub-family of DUBs. Evaluate the role of USP32 in GBM progression and provide a potential target for GBM treatment. Clinical significance of USP32 was investigated using Gene Expression Omnibus databases. Effects of USP32 on cell growth and metastasis were studied in vitro and in vivo. Differentially expressive genes between USP32-knockdown U-87 MG cells and negative control cells were detected using RNA sequencing and used for Gene Ontology and Kyoto Encyclopedia of Genes and Genomic pathway enrichment analyses. Finally, RT-qPCR was used to validate the divergent expression of genes involved in the enriched pathways. USP32 was upregulated in GBM patients, being correlated to poor prognosis. USP32 downregulation inhibited cell growth and metastasis in vitro. Furthermore, USP32 knockdown inhibited tumorigenesis in vivo. In addition, UPS32 was identified as a crucial regulator in different pathways including cell cycle, cellular senescence, DNA replication, base excision repair, and mismatch repair pathways. USP32 acts as an oncogene in GBM through regulating several biological processes/pathways. It could be a potential target for GBM treatment.

The localization of hnRNP A2/B1 in nuclear matrix and the aberrant expression during the RA-induced differentiation of human neuroblastoma SK-N-SH cells.

Heterogeneous nuclear ribonucleoprotein (hnRNP) A2/B1 is involved in the synthesis of RNA. Its expression is up-regulated in many tumor cell lines. In this study, we investigated the distribution of hnRNP A2/B1 in the nuclear matrix, including its co-localization with expression products of related genes. Results from 2-DE PAGE and MS showed that hnRNP A2/B1 is involved with components of nuclear matrix proteins of SK-N-SH cells, and that its expression level is down-regulated after retinoic acid (RA) treatment. Protein immunoblotting results further confirm the existence of hnRNP A2/B1 in the nuclear matrix, as well as its down-regulation after RA treatment. Immunofluorescence microscopy observation showed that hnRNP A2/B1 localized in nuclear matrix of SK-N-SH cells and its distribution regions were altered after RA treatment. Laser scanning confocal microscopy observation showed that hnRNP A2/B1 co-localized with c-Myc, c-Fos, P53, and Rb in SK-N-SH cells. The co-localized region was altered as a result of RA treatment. Our data proved that hnRNP A2/B1 is a nuclear matrix protein and can be up-regulated in human neuroblastoma. The expression and distribution of hnRNP A2/B1 can affect the differentiation of SK-N-SH cells, as well as its co-localization with related oncogenes and tumor suppressor genes.

A Meta-analysis of the Predictive Significance of the Island Sign for Hematoma Expansion in Intracerebral Hemorrhage.

BACKGROUND: The island sign of non-contrast computed tomography is a risk factor for hematoma expansion (HE) after spontaneous intracerebral hemorrhage, but has inconsistent conclusions. A meta-analysis was performed to investigate the predictive accuracy of island sign for HE. METHODS: A systematic review of published literature on island sign and hematoma expansion was conducted. The pooled sensitivity, specificity, and summary receiver operating characteristics curve (SROC) were generated. The publication bias was assessed by Deeks' funnel plot asymmetry test. RESULTS: Nine studies with a total of 2939 patients were included in the present study. The pooled sensitivity and specificity of island sign for predicting hematoma expansion was 0.50 and 0.89, respectively. The area under the curve was 0.73 in the SROC curve. There was no significant publication bias. CONCLUSIONS: This meta-analysis suggests that island sign of non-contrast computed tomography has a good predictive accuracy for hematoma enlargement in intracerebral hemorrhage.

Evolutionary Multitasking-Based Multiobjective Optimization Algorithm for Channel Selection in Hybrid Brain Computer Interfacing Systems.

Hybrid-modality brain-computer Interfaces (BCIs), which combine motor imagery (MI) bio-signals and steady-state visual evoked potentials (SSVEPs), has attracted wide attention in the research field of neural engineering. The number of channels should be as small as possible for real-life applications. However, most of recent works about channel selection only focus on either the performance of classification task or the effectiveness of device control. Few works conduct channel selection for MI and SSVEP classification tasks simultaneously. In this paper, a multitasking-based multiobjective evolutionary algorithm (EMMOA) was proposed to select appropriate channels for these two classification tasks at the same time. Moreover, a two-stage framework was introduced to balance the number of selected channels and the classification accuracy in the proposed algorithm. The experimental results verified the feasibility of multiobjective optimization methodology for channel selection of hybrid BCI tasks.

Computational screening of potential glioma-related genes and drugs based on analysis of GEO dataset and text mining.

BACKGROUND: Considering the high invasiveness and mortality of glioma as well as the unclear key genes and signaling pathways involved in the development of gliomas, there is a strong need to find potential gene biomarkers and available drugs. METHODS: Eight glioma samples and twelve control samples were analyzed on the GSE31095 datasets, and differentially expressed genes (DEGs) were obtained via the R software. The related glioma genes were further acquired from the text mining. Additionally, Venny program was used to screen out the common genes of the two gene sets and DAVID analysis was used to conduct the corresponding gene ontology analysis and cell signal pathway enrichment. We also constructed the protein interaction network of common genes through STRING, and selected the important modules for further drug-gene analysis. The existing antitumor drugs that targeted these module genes were screened to explore their efficacy in glioma treatment. RESULTS: The gene set obtained from text mining was intersected with the previously obtained DEGs, and 128 common genes were obtained. Through the functional enrichment analysis of the identified 128 DEGs, a hub gene module containing 25 genes was obtained. Combined with the functional terms in GSE109857 dataset, some overlap of the enriched function terms are both in GSE31095 and GSE109857. Finally, 4 antitumor drugs were identified through drug-gene interaction analysis. CONCLUSIONS: In this study, we identified that two potential genes and their corresponding four antitumor agents could be used as targets and drugs for glioma exploration.

Automatic Seizure Classification Based on Domain-Invariant Deep Representation of EEG.

Accurate identification of the type of seizure is very important for the treatment plan and drug prescription of epileptic patients. Artificial intelligence has shown considerable potential in the fields of automated EEG analysis and seizure classification. However, the highly personalized representation of epileptic seizures in EEG has led to many research results that are not satisfactory in clinical applications. In order to improve the clinical adaptability of the algorithm, this paper proposes an adversarial learning-driven domain-invariant deep feature representation method, which enables the hybrid deep networks (HDN) to reliably identify seizure types. In the train phase, we first use the labeled multi-lead EEG short samples to train squeeze-and-excitation networks (SENet) to extract short-term features, and then use the compressed samples to train the long short-term memory networks (LSTM) to extract long-time features and construct a classifier. In the inference phase, we first adjust the feature mapping of LSTM through the adversarial learning between LSTM and clustering subnet so that the EEG of the target patient and the EEG in the database obey the same distribution in the deep feature space. Finally, we use the adjusted classifier to identify the type of seizure. Experiments were carried out based on the TUH EEG Seizure Corpus and CHB-MIT seizure database. The experimental results show that the proposed domain adaptive deep feature representation improves the classification accuracy of the hybrid deep model in the target set by 5%. It is of great significance for the clinical application of EEG automatic analysis equipment.

New Autophagy-Ferroptosis Gene Signature Predicts Survival in Glioma.

Background: Ferroptosis plays an important role in glioma and significantly affects the prognosis, but the specific mechanism has not yet been elucidated. Recent studies suggest that autophagy regulates the process of ferroptosis. This study aimed to find potential autophagy-ferroptosis genes and explore the prognostic significance in glioma. Methods: Ferroptosis and autophagy genes were obtained from two online databases (zhounan.org/ferrdb and autophagy.lu/). The RNAseq data and clinical information were obtained from the Chinese Glioma Genome Atlas (CGGA) database (http://www.cgga.org.cn/). Univariate, multivariate, lasso and Cox regression analysis screened out prognosis-related genes, and a risk model was constructed. Receiver operating characteristic (ROC) curve analysis evaluated the predictive efficiency of the model. Finally, a nomogram was constructed to more accurately predict the prognosis of glioma. Results: We developed a Venn diagram showing 23 autophagy-ferroptosis genes. A total of 660 cases (including RNA sequences and complete clinical information) from two different cohorts (training group n = 413, verification group n = 247) of the CGGA database was acquired. Cohorts were screened to include five prognosis-related genes (MTOR, BID, HSPA5, CDKN2A, GABARAPLA2). Kaplan-Meier curves showed that the risk model was a good prognostic indicator (p < 0.001). ROC analysis showed good efficacy of the risk model. Multivariate Cox analysis also revealed that the risk model was suitable for clinical factors related to prognosis, including type of disease (primary, recurrence), grade (III-IV), age, temozolomide treatment, and 1p19q state. Using the five prognosis-related genes and the risk score, we constructed a nomogram assessed by C-index (0.7205) and a calibration plot that could more accurately predict glioma prognosis. Conclusion: Using a current database of autophagy and ferroptosis genes, we confirmed the prognostic significance of autophagy-ferroptosis genes in glioma, and we constructed a prognostic model to help guide treatment for high grade glioma in the future.

Development of an Immune-Related Prognostic Index Associated With Glioblastoma.

Background: Although the tumor microenvironment (TME) is known to influence the prognosis of glioblastoma (GBM), the underlying mechanisms are not clear. This study aims to identify hub genes in the TME that affect the prognosis of GBM. Methods: The transcriptome profiles of the central nervous systems of GBM patients were downloaded from The Cancer Genome Atlas (TCGA). The ESTIMATE scoring algorithm was used to calculate immune and stromal scores. The application of these scores in histology classification was tested. Univariate Cox regression analysis was conducted to identify genes with prognostic value. Subsequently, functional enrichment analysis and protein-protein interaction (PPI) network analysis were performed to reveal the pathways and biological functions associated with the genes. Next, these prognosis genes were validated in an independent GBM cohort from the Chinese Glioma Genome Atlas (CGGA). Finally, the efficacy of current antitumor drugs targeting these genes against glioma was evaluated. Results: Gene expression profiles and clinical data of 309 GBM samples were obtained from TCGA database. Higher immune and stromal scores were found to be significantly correlated with tissue type and poor overall survival (OS) (p = 0.15 and 0.77, respectively). Functional enrichment analysis identified 860 upregulated and 162 downregulated cross genes, which were mainly linked to immune response, inflammatory response, cell membrane, and receptor activity. Survival analysis identified 228 differentially expressed genes associated with the prognosis of GBM (p ≤ 0.05). A total of 48 hub genes were identified by the Cytoscape tool, and pathway enrichment analysis of the genes was performed using Database for Annotation, Visualization and Integrated Discovery (DAVID). The 228 genes were validated in an independent GBM cohort from the CGGA. In total, 10 genes were found to be significantly associated with prognosis of GBM. Finally, 14 antitumor drugs were identified by drug-gene interaction analysis. Conclusions: Here, 10 TME-related genes and 14 corresponding antitumor agents were found to be associated with the prognosis and OS of GBM.

Decreased pygopus 2 expression suppresses glioblastoma U251 cell growth.

Gliomas are common malignant tumors of the human neural system, and Wnt signaling activation is closely related to glioma malignancy. Human Pygopus 2 (Pygo2) was recently discovered to be a component of the Wnt signaling pathway, which is required for ß-catenin/Tcf-dependent transcription. However, the role of Pygo2 in glioblastoma cell growth and survival remains uncertain. In the present study, Pygo2 expression was evaluated in 80 glioma tissue samples. Results demonstrated that tumor grade exhibited a positive correlation with overexpression of Pygo2. In addition, small hairpin RNA (shRNA) was used to specifically knockdown Pygo2 expression in human glioblastoma U251 cell lines. Results showed that inhibition of Pygo2 expression resulted in inhibited cell proliferation and invasiveness, as well as increased cell cycle arrest at the G(1) stage and decreased expression of the Wnt target gene cyclin D1. These results demonstrated that Pygo2 was highly expressed in glioma tissue and required for growth of glioblastoma cells.