scholarly journals Validation of the Functions and Prognostic Values of Synapse Associated Proteins in Lower-Grade Glioma

2020 ◽  
Author(s):  
Han Lin ◽  
Yong Yang ◽  
Chongxian Hou ◽  
Jiantao Zheng ◽  
Guangzhao Lv ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Prognostic Models ◽  
Normal Brain ◽  
Lower Grade ◽  
Associated Proteins ◽  
Genome Atlas

Abstract BackgroundSynapse and synapse associated proteins (SAPs) play critical roles in various neurodegeneration diseases and brain tumors. However, in lower-grade gliomas (LGG), SAPs have not been explored systematically. Herein, we are going to explore SAPs expression profile and its clinicopathological significance in LGG which can offer new insights to glioma therapy. MethodIn this study, we used five sources including, Venkatesh, Shen, Colón, Jüttner R, Gene Ontology (GO) project to integrate a list of SAPs that covered 231 proteins with synaptogenesis activity and post synapse formation. The LGG RNA-seq data were downloaded from gene expression omnibus (GEO) database, The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA). The differentially expressed SAPs were filtered out and constructed PPI to search for key modules and SAPs. Then, using Kaplan–Meier survival analysis, least absolute shrinkage and selection operator (LASSO), and multicox regression analysis, the prognostic significance of these key SAPs was evaluated. CGGA database, Human Protein Altas (HPA) and quantitative real-time PCR were used to verify our findings. ResultData from function enrichment analysis revealed functions of differentially expressed SAPs in synapse organization and glutamatergic receptor pathway in LGGs. Survival analysis revealed four SAPs, GRIK2, GABRD, GRID2, ARC that were correlate with the prognosis of LGG patients and used to construct the prognostic models. Among them, the expression of GABRD was lower in glioma tissue than normal brain tissue, but higher in seizure LGG patients than non-seizure patients. The four-SAPs signature was revealed as an independent prognostic factor in gliomas. ConclusionOur study presented a novel strategy to assess the prognostic risks of LGGs, based on the expression of SAPs. Also, we revealed that several SAPs upregulated in patients with seizures, indicating that they are linked to the pathogenesis of seizures in glioma patients.

scholarly journals Validation of the Functions and Prognostic Values of Synapse Associated Proteins in Lower-Grade Glioma

2020 ◽  
Author(s):  
Han Lin ◽  
Yong Yang ◽  
Chongxian Hou ◽  
Jiantao Zheng ◽  
Guangzhao Lv ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Prognostic Models ◽  
Normal Brain ◽  
Lower Grade ◽  
Associated Proteins ◽  
Genome Atlas

Abstract Background: Synapse and synapse associated proteins (SAPs) play critical roles in various neurodegeneration diseases and brain tumors. However, in lower-grade gliomas (LGG), SAPs have not been explored systematically. Herein, we are going to explore SAPs expression profile and its clinicopathological significance in LGG which can offer new insights to glioma therapy. Method: In this study, we used five sources including, Venkatesh, Shen, Colón, Jüttner R, Gene Ontology (GO) project to integrate a list of SAPs that covered 231 proteins with synaptogenesis activity and post synapse formation. The LGG RNA-seq data were downloaded from gene expression omnibus (GEO) database, The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA). The differentially expressed SAPs were filtered out and constructed PPI to search for key modules and SAPs. Then, using Kaplan–Meier survival analysis, least absolute shrinkage and selection operator (LASSO), and multicox regression analysis, the prognostic significance of these key SAPs was evaluated. CGGA database, Human Protein Altas (HPA) and quantitative real-time PCR were used to verify our findings. Result: Data from function enrichment analysis revealed functions of differentially expressed SAPs in synapse organization and glutamatergic receptor pathway in LGGs. Survival analysis revealed four SAPs, GRIK2, GABRD, GRID2, ARC that were correlate with the prognosis of LGG patients and used to construct the prognostic models. Among them, the expression of GABRD was lower in glioma tissue than normal brain tissue, but higher in seizure LGG patients than non-seizure patients. The four-SAPs signature was revealed as an independent prognostic factor in gliomas.Conclusion: Our study presented a novel strategy to assess the prognostic risks of LGGs, based on the expression of SAPs. Also, we revealed that several SAPs upregulated in patients with seizures, indicating that they are linked to the pathogenesis of seizures in glioma patients.

scholarly journals Identification and Validation of an Energy Metabolism-Related lncRNA-mRNA Signature for Lower-Grade Glioma

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Jingwei Zhao ◽  
Le Wang ◽  
Bo Wei
Keyword(s):  
Energy Metabolism ◽  
Risk Score ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Coexpression Network ◽  
Normal Brain ◽  
Lower Grade ◽  
Prognostic Signature ◽  
Lower Grade Glioma ◽  
Genome Atlas

Energy metabolic processes play important roles for tumor malignancy, indicating that related protein-coding genes and regulatory upstream genes (such as long noncoding RNAs (lncRNAs)) may represent potential biomarkers for prognostic prediction. This study will develop a new energy metabolism-related lncRNA-mRNA prognostic signature for lower-grade glioma (LGG) patients. A GSE4290 dataset obtained from Gene Expression Omnibus was used for screening the differentially expressed genes (DEGs) and lncRNAs (DELs). The Cancer Genome Atlas (TCGA) dataset was used as the prognosis training set, while the Chinese Glioma Genome Atlas (CGGA) was for the validation set. Energy metabolism-related genes were collected from the Molecular Signatures Database (MsigDB), and a coexpression network was established between energy metabolism-related DEGs and DELs to identify energy metabolism-related DELs. Least absolute shrinkage and selection operator (LASSO) analysis was performed to filter the prognostic signature which underwent survival analysis and nomogram construction. A total of 1613 DEGs and 37 DELs were identified between LGG and normal brain tissues. One hundred and ten DEGs were overlapped with energy metabolism-related genes. Twenty-seven DELs could coexpress with 67 metabolism-related DEGs. LASSO regression analysis showed that 9 genes in the coexpression network were the optimal signature and used to construct the risk score. Kaplan-Meier curve analysis showed that patients with a high risk score had significantly worse OS than those with a low risk score (TCGA: HR=3.192, 95%CI=2.182‐4.670; CGGA: HR=1.922, 95%CI=1.431‐2.583). The predictive accuracy of the risk score was also high according to the AUC of the ROC curve (TCGA: 0.827; CGGA: 0.806). Multivariate Cox regression analyses revealed age, IDH1 mutation, and risk score as independent prognostic factors, and thus, a prognostic nomogram was established based on these three variables. The excellent prognostic performance of the nomogram was confirmed by calibration and discrimination analyses. In conclusion, our findings provided a new biomarker for the stratification of LGG patients with poor prognosis.

scholarly journals Integrin Alpha-2 as a Potential Prognostic and Predictive Biomarker for Patients With Lower-Grade Glioma

2021 ◽  
Vol 11 ◽  
Author(s):  
Li Lin ◽  
Kai Huang ◽  
Zewei Tu ◽  
Xingen Zhu ◽  
Jingying Li ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Clinical Information ◽  
Predictive Biomarker ◽  
The Cancer Genome Atlas ◽  
Lower Grade ◽  
Western Blot Assay ◽  
Clinical Model ◽  
Cell Functions ◽  
Novel Target ◽  
Genome Atlas

Diffuse gliomas are the most common malignant brain tumors with the highest mortality and recurrence rate in adults. Integrin alpha-2 (ITGA2) is involved in a series of biological processes, including cell adhesion, stemness regulation, angiogenesis, and immune/blood cell functions. The role of ITGA2 in lower-grade gliomas (LGGs) is not well defined. Firstly, we downloaded RNA sequencing and relevant clinical information from The Cancer Genome Atlas cohort, the Chinese Glioma Genome Atlas cohort, and related immune cohorts. Next, prognosis analysis, difference analysis, clinical model construction, enrichment analysis, and immune infiltration analysis are performed for this study. These analyses indicated that ITGA2 may have clinical application value and research value in LGG immunotherapy. We also detected the mRNA and protein expression of ITGA2 in three LGG cell lines and normal glial cells using quantitative real-time polymerase chain reaction assay and western blot assay. Our study not only offers a novel target for LGG immunotherapy but also can better comprehend the mechanism of the development and progression of patients with LGG. This study revealed that ITGA2 may be a potential prognostic and predictive biomarker for LGG, which can bring new insights into targeted immunotherapy.

scholarly journals Bioinformatics analysis of potential core genes for glioblastoma

2020 ◽  
Vol 40 (7) ◽  
Author(s):  
Yu Zhang ◽  
Xin Yang ◽  
Xiao-Lin Zhu ◽  
Jia-Qi Hao ◽  
Hao Bai ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Protein Interactions ◽  
Poor Prognosis ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Normal Brain ◽  
Hub Genes ◽  
Potential Core ◽  
Core Genes

Abstract Background: Glioblastoma (GBM) has a high degree of malignancy, aggressiveness and recurrence rate. However, there are limited options available for the treatment of GBM, and they often result in poor prognosis and unsatisfactory outcomes. Materials and methods: In order to identify potential core genes in GBM that may provide new therapeutic insights, we analyzed three gene chips (GSE2223, GSE4290 and GSE50161) screened from the GEO database. Differentially expressed genes (DEG) from the tissues of GBM and normal brain were screened using GEO2R. To determine the functional annotation and pathway of DEG, Gene Ontology (GO) and KEGG pathway enrichment analysis were conducted using DAVID database. Protein interactions of DEG were visualized using PPI network on Cytoscape software. Next, 10 Hub nodes were screened from the differentially expressed network using MCC algorithm on CytoHubba software and subsequently identified as Hub genes. Finally, the relationship between Hub genes and the prognosis of GBM patients was described using GEPIA2 survival analysis web tool. Results: A total of 37 up-regulated and 187 down-regulated genes were identified through microarray analysis. Amongst the 10 Hub genes selected, SV2B appeared to be the only gene associated with poor prognosis in glioblastoma based on the survival analysis. Conclusion: Our study suggests that high expression of SV2B is associated with poor prognosis in GBM patients. Whether SV2B can be used as a new therapeutic target for GBM requires further validation.

scholarly journals Validation of the Functions and Prognostic Values of Synapse Associated Proteins in Lower-grade Glioma

2021 ◽  
Author(s):  
Han Lin ◽  
Yong Yang ◽  
Chongxian Hou ◽  
Yuqing Huang ◽  
Liting Zhou ◽  
...  
Keyword(s):  
Synapse Formation ◽  
Enrichment Analysis ◽  
Normal Brain ◽  
Lower Grade ◽  
Protein Protein Interaction ◽  
Reverse Transcription Pcr ◽  
Function Enrichment Analysis ◽  
Associated Proteins ◽  
Clinicopathological Significance ◽  
Novel Strategy

Synapse and synapse associated proteins (SAPs) play critical roles in various neurodegeneration diseases and brain tumors. However, in lower-grade gliomas (LGG), SAPs have not been explored systematically. Herein, we are going to explore SAPs expression profile and its clinicopathological significance in LGG which can offer new insights to glioma therapy. In this study, we integrate a list of SAPs that covered 231 proteins with synaptogenesis activity and post synapse formation. The LGG RNA-seq data were downloaded from GEO, TCGA and CGGA database. The prognosis associated SAPs in key modules of PPI (protein-protein interaction networks) was regarded as hub SAPs. Western blot, quantitative reverse transcription PCR (qRT-PCR) and immunochemistry results from HPA database were used to verify the expression of hub SAPs. There were 68 upregulated SAPs and 44 downregulated SAPs in LGG tissue compared with normal brain tissue. Data from function enrichment analysis revealed functions of differentially expressed SAPs in synapse organization and glutamatergic receptor pathway in LGGs. Survival analysis revealed that four SAPs, GRIK2, GABRD, GRID2 and ARC were correlate with the prognosis of LGG patients. Interestingly, we found that GABRD were upregulated in LGG patients with seizures, indicating that SAPs may link to the pathogenesis of seizures in glioma patients. The four-SAPs signature was revealed as an independent prognostic factor in gliomas. Our study presented a novel strategy to assess the prognostic risks of LGGs, based on the expression of SAPs.

scholarly journals Identification and Potential Mechanisms of a 7-MicroRNA Signature That Predicts Prognosis in Patients with Lower-Grade Glioma

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhizheng Liu ◽  
Hongliang Meng ◽  
Miaoxian Fang ◽  
Wenlong Guo
Keyword(s):  
Signaling Pathway ◽  
Predictive Accuracy ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Lower Grade ◽  
Clinical Practices ◽  
Lower Grade Glioma ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background. Lower-grade glioma is an intracranial cancer that may develop into glioblastoma with high mortality. The main objective of our study is to develop microRNA for LGG patients which will provide novel prognostic biomarkers along with therapeutic targets. Methods. Clinicopathological data of LGG patients and their RNA expression profile were downloaded through The Cancer Genome Atlas Relevant expression profiles of RNA, and clinicopathological data of the LGG patients had been extracted from the database of “The Cancer Genome Atlas.” Differential expression analysis had been conducted for identification of the differentially expressed microRNAs as well as mRNAs in LGG samples and normal ones. ROC curves and K–M plots were plotted to confirm performance and for predictive accuracy. For the confirmation of microRNAs as an independent prognostic factor, an independent prognosis analysis was conducted. Moreover, target differentially expressed genes of these identified prognostic microRNAs that were extracted and protein-protein interaction networks were developed. Moreover, the biological functions of signature were determined through Genome Ontology analysis, genome pathway analysis, and Kyoto Encyclopedia of Genes. Results. 7-microRNA signature was identified that has the ability of categorization of individuals with LGG into high- and low-risk groups on the basis of significant difference in survival during training and testing cohorts (P < 0.001). The 7-microRNA signature had appeared to be robust in predictive accuracy (all AUC> 0.65). It was also approved with multivariate Cox regression along with some traditional clinical practices that we can use 7-microRNA signature for therapeutic purposes as a self-regulating predictive OS factor (P < 0.001). KEGG and Gene Ontology (GO) analyses reported that 7-microRNAs had mainly developed in important pathways related with glioma, e.g., the “cAMP signaling pathway,” “glutamatergic synapses,” and “calcium signaling pathway”. Conclusion. A newly discovered 7-microRNA signature could be a potential target for the diagnosis and treatment for LGG patients.

The Solute Carrier Family 7 Genes Are Potential Diagnostic and Prognostic Biomarkers in Lower Grade Glioma

2021 ◽  
Author(s):  
Wentao Liu ◽  
Yu Ji ◽  
Rijun Ren ◽  
Gentang Zhang
Keyword(s):  
Gene Expression ◽  
Amino Acid ◽  
The Cancer Genome Atlas ◽  
Normal Brain ◽  
Lower Grade ◽  
Lower Grade Glioma ◽  
Family Gene ◽  
Solute Carrier ◽  
Genome Atlas ◽  
Brain Tissues

Abstract Background: The solute carrier (SLC) 7 family genes are a group of cationic amino acid/glycoprotein transporters and of importance to the maintenance of amino acid nutrition and survival of tumour cells. This study was to investigate the diagnostic values of SLC7 family genes and their associations with overall survival (OS) and relapse-free survival (RFS) in Lower grade glioma (LGG). Methods: SLC7 family gene expression and clinical data were retrieved from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas database. The expression difference of SLC7 family genes was compared between 523 LGG and 1141 normal brain tissues. The associations between gene expression, clinicopathologic factors, patients’ OS and RFS were analysed by various statistical methods in the two datasets. Results: As compared to normal brain tissues, SLC7A10 expression was significantly down-regulated, while SLC7A5, SLC7A7 expression was significantly up-regulated in LGG tissues. Multivariate analysis and validation analysis confirmed that increased SLC7A7 expression was associated with increased mortality (P≤0.001, Odd ratio [OR]:2.66, 95% Confidence interval [CI]: 1.56–4.6). While, increased SLC7A4 and SLC7A14 expression was associated with reduced mortality (P=0.02, OR:0.38, 95% CI: 0.16–0.81; P≤0.001, OR:0.38, 95% CI: 0.21–0.67; respectively). Increased SLC7A11 expression was associated with decreased RFS (P=0.01, OR:0.61, 95% CI: 0.43–0.88). Conclusion: SLC7A5, SLC7A7, SLC7A10 might serve as diagnostic biomarkers in LGG. High SLC7A4, SLC7A7 and SLC7A14 expression is significantly associated with OS. SLC7 family gene expression represents a potentially diagnostic and prognostic biomarker to predict survival in LGG.

scholarly journals Prognostic Model and Nomogram Construction Based on a Novel Ferroptosis-Related Gene Signature in Lower-Grade Glioma

2021 ◽  
Vol 12 ◽  
Author(s):  
Junsheng Zhao ◽  
Zhengtao Liu ◽  
Xiaoping Zheng ◽  
Hainv Gao ◽  
Lanjuan Li
Keyword(s):  
Risk Model ◽  
Survival Curve ◽  
External Validation ◽  
Enrichment Analysis ◽  
Predictive Performance ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Low Grade ◽  
Lower Grade ◽  
Genome Atlas

Background: Low-grade glioma (LGG) is considered a fatal disease for young adults, with overall survival widely ranging from 1 to 15 years depending on histopathologic and molecular subtypes. As a novel type of programmed cell death, ferroptosis was reported to be involved in tumorigenesis and development, which has been intensively studied in recent years.Methods: For the discovery cohort, data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were used to identify the differentially expressed and prognostic ferroptosis-related genes (FRGs). The least absolute shrinkage and selection operator (LASSO) and multivariate Cox were used to establish a prognostic signature with the above-selected FRGs. Then, the signature was developed and validated in TCGA and Chinese Glioma Genome Atlas (CGGA) databases. By combining clinicopathological features and the FRG signature, a nomogram was established to predict individuals’ one-, three-, and five-year survival probability, and its predictive performance was evaluated by Harrell’s concordance index (C-index) and calibration curves. Enrichment analysis was performed to explore the signaling pathways regulated by the signature.Results: A novel risk signature contains seven FRGs that were constructed and were used to divide patients into two groups. Kaplan–Meier (K−M) survival curve and receiver-operating characteristic (ROC) curve analyses confirmed the prognostic performance of the risk model, followed by external validation based on data from the CGGA. The nomogram based on the risk signature and clinical traits was validated to perform well for predicting the survival rate of LGG. Finally, functional analysis revealed that the immune statuses were different between the two risk groups, which might help explain the underlying mechanisms of ferroptosis in LGG.Conclusion: In conclusion, this study constructed a novel and robust seven-FRG signature and established a prognostic nomogram for LGG survival prediction.

scholarly journals CD74 Correlated With Malignancies and Immune Microenvironment in Gliomas

2021 ◽  
Vol 8 ◽  
Author(s):  
Shengchao Xu ◽  
Xizhe Li ◽  
Lu Tang ◽  
Zhixiong Liu ◽  
Kui Yang ◽  
...  
Keyword(s):  
Immune Cells ◽  
Predictive Accuracy ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Normal Brain ◽  
Lower Grade ◽  
Characteristic Analysis ◽  
Immune Microenvironment ◽  
Immune Infiltration ◽  
Genome Atlas

Background: Cluster of differentiation 74 (CD74) is found to be highly involved in the development of various types of cancers and could affect the activities of infiltrated cells in the tumor microenvironment. However, these studies only focus on a few types of immune cells. Our study aims to comprehensively explore the role of CD74 in glioma prognosis and immune microenvironment.Methods: A total of 40 glioma specimens were collected in this study. We extracted data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene-Expression Omnibus (GEO) databases to explore the expression pattern of CD74 in gliomas. gene sets enrichment analysis and gene set variation analysis analyses were conducted to characterize the immune features of CD74. ESTIMATE, ssGSEA, Tumor IMmune Estimation Resource, and CIBERSORT algorithms were applied to assess the immune infiltration. Kaplan-Meier analysis was used for survival analysis. Receiver operating characteristic analysis was used to evaluate the predictive accuracy of CD74 in glioma diagnosis and prognosis.Results: A total of 2,399 glioma patients were included in our study. CD74 was highly expressed in glioma tissue compared to normal brain tissue and its expression was significantly higher in the high-grade glioma compared to the lower grade glioma at transcriptional and translational levels. Besides, CD74 was positively associated with immune checkpoints and inflammatory cytokines as well as immune processes including cytokine secretion and leukocyte activation. The high expression of CD74 indicated a high infiltration of immune cells such as macrophages, dendritic cells, and neutrophils. Moreover, patients with high expression of CD74 had poor prognoses. CD74 had moderate predictive accuracy in the diagnosis of glioblastoma and prediction of survival.Conclusions: In conclusion, our study revealed that the high expression of CD74 was associated with poor prognosis and high immune infiltration. CD74 could be used as a potential target for glioma treatment and as a biomarker to predict the prognosis of glioma patients.

scholarly journals High Expression of C1ORF112 Predicts a Poor Outcome: A Potential Target for the Treatment of Low-Grade Gliomas

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhe Zhang ◽  
Zilong Tan ◽  
Qiaoli Lv ◽  
Lichong Wang ◽  
Kai Yu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Survival Analysis ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Low Grade ◽  
Poor Overall Survival ◽  
Genetic Changes ◽  
Low Grade Gliomas ◽  
Genome Atlas

Background: Glioma is the most common primary tumor of the central nervous system and is associated with poor overall survival, creating an urgent need to identify survival-associated biomarkers. C1ORF112, an alpha-helical protein, is overexpressed in some cancers; however, its prognostic role has not yet been explored in gliomas. Thus, in this study, we attempted to address this by determining the prognostic value and potential function of C1ORF112 in low-grade gliomas (LGGs).Methods: The expression of C1ORF112 in normal and tumor tissues was analyzed using data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Oncomine, and Rembrandt databases. The genetic changes of C1ORF112 in LGG were analyzed using cBioPortal. Survival analysis was used to evaluate the relationship between C1ORF112 expression and survival in patients with LGG. Correlation between immune infiltration and C1ORF112 expression was determined using Timer software. Additionally, data from three online platforms were integrated to identify the co-expressed genes of C1ORF112. The potential biological functions of C1ORF112 were investigated by enrichment analysis.Results: C1ORF112 mRNA was highly expressed in LGGs (p &lt; 0.01). Area under the ROC curve (AUC) showed that the expression of C1ORF112 in LGG was 0.673 (95% confidence interval [CI] = 0.618–0.728). Kaplan-Meier survival analysis showed that patients with high C1ORF112 expression had lower OS than patients with low C1ORF112 expression (p &lt; 0.05). Multivariate analysis showed that high expression of C1ORF112 was an independent prognostic factor for the overall survival in patients from TCGA and CGGA databases. C1ORF112 expression was positively correlated with six immunoinfiltrating cells (all p &lt; 0.001). The enrichment analysis suggested the enrichment of C1ORF112 and co-expressed genes in cell cycle and DNA replication.Conclusion: This study suggested that C1ORF112 may be a prognostic biomarker and a potential immunotherapeutic target for LGG.

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