Identification of Core Genes and Screening of Potential Targets in Glioblastoma Multiforme by Integrated Bioinformatic Analysis

Glioblastoma multiforme is the most common primary intracranial malignancy, but its etiology and pathogenesis are still unclear. With the deepening of human genome research, the research of glioma subtype screening based on core molecules has become more in-depth. In the present study, we screened out differentially expressed genes (DEGs) through reanalyzing the glioblastoma multiforme (GBM) datasets GSE90598 from the Gene Expression Omnibus (GEO), the GBM dataset TCGA-GBM and the low-grade glioma (LGG) dataset TCGA-LGG from the Cancer Genome Atlas (TCGA). A total of 150 intersecting DEGs were found, of which 48 were upregulated and 102 were downregulated. These DEGs from GSE90598 dataset were enriched using the overrepresentation method, and multiple enriched gene ontology (GO) function terms were significantly correlated with neural cell signal transduction. DEGs between GBM and LGG were analyzed by gene set enrichment analysis (GSEA), and the significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in synapse signaling and oxytocin signaling pathways. Then, a protein-protein interaction (PPI) network was constructed to assess the interaction of proteins encoded by the DEGs. MCODE identified 2 modules from the PPI network. The 11 genes with the highest degrees in module 1 were designated as core molecules, namely, GABRD, KCNC1, KCNA1, SYT1, CACNG3, OPALIN, CD163, HPCAL4, ANK3, KIF5A, and MS4A6A, which were mainly enriched in ionic signaling-related pathways. Survival analysis of the GSE83300 dataset verified the significant relationship between expression levels of the 11 core genes and survival. Finally, the core molecules of GBM and the DrugBank database were assessed by a hypergeometric test to identify 10 drugs included tetrachlorodecaoxide related to cancer and neuropsychiatric diseases. Further studies are required to explore these core genes for their potentiality in diagnosis, prognosis, and targeted therapy and explain the relationship among ionic signaling-related pathways, neuropsychiatric diseases and neurological tumors.

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Immunogenomic Profiling Demonstrate AC003092.1 as an Immune-Related eRNA in Glioblastoma Multiforme

Frontiers in Genetics ◽

10.3389/fgene.2021.633812 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xiao-Yu Guo ◽

Sheng Zhong ◽

Zhen-Ning Wang ◽

Tian Xie ◽

Hao Duan ◽

...

Keyword(s):

Glioblastoma Multiforme ◽

Immune Therapy ◽

Critical Role ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Rank Test ◽

Low Grade

Enhancer RNAs, a type of long non-coding RNAs (lncRNAs), play a critical role in the occurrence and development of glioma. RNA-seq data from 161 glioblastoma multiforme (GBM) samples were acquired from The Cancer Genome Atlas database. Then, 70 eRNAs were identified as prognosis-related genes, which had significant relations with overall survival (log-rank test, p < 0.05). AC003092.1 was demonstrated as an immune-related eRNA by functional enrichment analysis. We divided samples into two groups based on AC003092.1 expression: AC003092.1 High (AC003092.1_H) and AC003092.1 Low (AC003092.1_L) and systematically analyzed the influence of AC003092.1 on the immune microenvironment by single-sample gene-set enrichment analysis and CIBERSORTx. We quantified AC003092.1 and TFPI2 levels in 11 high-grade gliomas, 5 low-grade gliomas, and 7 GBM cell lines. Our study indicates that AC003092.1 is related to glioma-immunosuppressive microenvironment, and these results offer innovative sights into GBM immune therapy.

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A Six-lncRNA Signature for Immunophenotype Prediction of Glioblastoma Multiforme

Frontiers in Genetics ◽

10.3389/fgene.2020.604655 ◽

2021 ◽

Vol 11 ◽

Author(s):

Ming Gao ◽

Xinzhuang Wang ◽

Dayong Han ◽

Enzhou Lu ◽

Jian Zhang ◽

...

Keyword(s):

Glioblastoma Multiforme ◽

Immune Cell ◽

Area Under The Curve ◽

Principal Component ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Non Coding Rna ◽

Cancer Genome Atlas ◽

The Central Nervous System

Glioblastoma multiforme (GBM) is the most aggressive primary tumor of the central nervous system. As biomedicine advances, the researcher has found the development of GBM is closely related to immunity. In this study, we evaluated the GBM tumor immunoreactivity and defined the Immune-High (IH) and Immune-Low (IL) immunophenotypes using transcriptome data from 144 tumors profiled by The Cancer Genome Atlas (TCGA) project based on the single-sample gene set enrichment analysis (ssGSEA) of five immune expression signatures (IFN-γ response, macrophages, lymphocyte infiltration, TGF-β response, and wound healing). Next, we identified six immunophenotype-related long non-coding RNA biomarkers (im-lncRNAs, USP30-AS1, HCP5, PSMB8-AS1, AL133264.2, LINC01684, and LINC01506) by employing a machine learning computational framework combining minimum redundancy maximum relevance algorithm (mRMR) and random forest model. Moreover, the expression level of identified im-lncRNAs was converted into an im-lncScore using the normalized principal component analysis. The im-lncScore showed a promising performance for distinguishing the GBM immunophenotypes with an area under the curve (AUC) of 0.928. Furthermore, the im-lncRNAs were also closely associated with the levels of tumor immune cell infiltration in GBM. In summary, the im-lncRNA signature had important clinical implications for tumor immunophenotyping and guiding immunotherapy in glioblastoma patients in future.

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Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis

10.21203/rs.3.rs-19937/v2 ◽

2020 ◽

Author(s):

Zhenhua Yin ◽

Dejun Wu ◽

Jianping Shi ◽

Xiyi Wei ◽

Nuyun Jin ◽

...

Keyword(s):

Gene Expression ◽

Reference Value ◽

Enrichment Analysis ◽

Predictive Marker ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Fatty Aldehyde ◽

Low Grade

Abstract Background: Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further.Methods: In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database.Results: Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4.Conclusion: We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

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Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis

10.21203/rs.3.rs-19937/v3 ◽

2020 ◽

Author(s):

Zhenhua Yin ◽

Dejun Wu ◽

Jianping Shi ◽

Xiyi Wei ◽

Nuyun Jin ◽

...

Keyword(s):

Gene Expression ◽

Reference Value ◽

Enrichment Analysis ◽

Predictive Marker ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Fatty Aldehyde ◽

Low Grade

Abstract Background: Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further. Methods: In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Results: Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4. Conclusion: We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

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Prognostic Biomarker SYK and its Correlation with Immune Infiltrates in Glioma

10.21203/rs.3.rs-839283/v1 ◽

2021 ◽

Author(s):

Pei Liu ◽

Jiamin Guo ◽

Xiaoxiao Xu ◽

Haixin Sun ◽

Zheng Gong

Keyword(s):

Development Process ◽

Prognostic Biomarker ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Ppi Network ◽

Glioma Patient ◽

Gene Set Enrichment ◽

Protein Protein Interaction ◽

Cancer Genome Atlas

Abstract Background: Tumor microenvironment (TME) has great effects on the development process of glioma, and we sought to identify effective prognostic factors by analyzing data from patients with glioma. In this paper, CIBERSORT and ESTIMATE calculations were employed to figure up the ratio of tumor-infiltrating immune cells (TICs) and the quantity of immune and stromal components in 698 glioma dates from The Cancer Genome Atlas (TCGA) database. In addition, differentially expressed genes (DEGs) were studied by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and single genes associated with prognosis were identified by PPI network and COX combined analysis. Results: Immune and stromal scores of TME were significantly correlated with glioma patient survival. Through protein–protein interaction (PPI) network and regression analysis of COX, we finally determined that SYK was the best prognostic factor for patients with glioma. Gene Set Enrichment Analysis (GSEA) and CIBERSORT analysis were also employed, with the former showed that high-expression SYK group’s genes are principally enriched immune-related activities and the latter revealed that SYK expression was positively associated with T cells CD4 memory resting and Monocytes. All the above experimental analyses provided the theoretical basis for the biological prediction of SYK.Conclusions: SYK contributes to immune predictors in glioma patients by facilitating the shift of TME from immune dominance to metabolic activity, which provides promising insights into the treatment of glioma.

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Expression profiling of LncRNA and miRNA in SDF-1-induced articular chondrocyte degeneration

10.21203/rs.3.rs-36488/v1 ◽

2020 ◽

Author(s):

Guoliang Wang ◽

Jiali Zheng ◽

Lu He ◽

YaoYu Xiang ◽

Yanlin Li

Keyword(s):

Molecular Mechanisms ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Ppi Network ◽

Articular Chondrocyte ◽

Gene Regulation Network ◽

Protein Protein Interaction ◽

Regulation Network ◽

The Difference ◽

Core Genes

Abstract Background With the in-depth exploration of the gene regulation network associated with the pathogenesis of osteoarthritis (OA), lncRNA has been found to play a major role in regulating the development of osteoarthritis. In this study, the expressions of miRNAs and lncRNAs in chondrocytes (2 days) of SDF-1-induced articular chondrocyte degeneration model and in normal chondrocytes were detected and the difference between them was visualized. The bioinformatics analysis was performed in parallel to elucidate the interactions between miRNAs and protein molecules. Results It was found that 186 lncRNA changes had significant statistical differences, of which 88 lncRNA were up-regulated and 98 lncRNA were down-regulated. A total of 684 miRNA had significant statistical differences in their expression changes. Gene Ontology and Kyoto Encyclopedia of Genes were performed for the gene set enrichment analysis to determine the key biological processes and pathways. The protein-protein interaction (PPI) network indicated that CXCL10, ISG15, MYC, MX1, OASL, FIICT1, RSAD2, MX2, IFI44, and LBST2 are the ten core genes. The PPI network identified the most important functional modules to elucidate the differential expression of miRNA. Conclusions These data may provide new insights into the molecular mechanisms of osteoarthritis chondrocyte degeneration, and the identification of lncRNA and miRNA can provide potential therapeutic targets for the diagnosis and differential diagnosis of osteoarthritis.

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Tumor mutational burden predicts survival in patients with low-grade gliomas expressing mutated IDH1

Neuro-Oncology Advances ◽

10.1093/noajnl/vdaa042 ◽

2020 ◽

Vol 2 (1) ◽

Cited By ~ 2

Author(s):

Mahmoud S Alghamri ◽

Rohit Thalla ◽

Ruthvik P Avvari ◽

Ali Dabaja ◽

Ayman Taher ◽

...

Keyword(s):

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Low Grade ◽

Low Grade Gliomas ◽

Mutational Burden ◽

Gene Sets ◽

Tumor Mutational Burden ◽

Cancer Genome Atlas ◽

Gene Ontologies

Abstract Background Gliomas are the most common primary brain tumors. High-Grade Gliomas have a median survival (MS) of 18 months, while Low-Grade Gliomas (LGGs) have an MS of approximately 7.3 years. Seventy-six percent of patients with LGG express mutated isocitrate dehydrogenase (mIDH) enzyme. Survival of these patients ranges from 1 to 15 years, and tumor mutational burden ranges from 0.28 to 3.85 somatic mutations/megabase per tumor. We tested the hypothesis that the tumor mutational burden would predict the survival of patients with tumors bearing mIDH. Methods We analyzed the effect of tumor mutational burden on patients’ survival using clinical and genomic data of 1199 glioma patients from The Cancer Genome Atlas and validated our results using the Glioma Longitudinal AnalySiS consortium. Results High tumor mutational burden negatively correlates with the survival of patients with LGG harboring mIDH (P = .005). This effect was significant for both Oligodendroglioma (LGG-mIDH-O; MS = 2379 vs 4459 days in high vs low, respectively; P = .005) and Astrocytoma (LGG-mIDH-A; MS = 2286 vs 4412 days in high vs low respectively; P = .005). There was no differential representation of frequently mutated genes (eg, TP53, ATRX, CIC, and FUBP) in either group. Gene set enrichment analysis revealed an enrichment in Gene Ontologies related to cell cycle, DNA-damage response in high versus low tumor mutational burden. Finally, we identified 6 gene sets that predict survival for LGG-mIDH-A and LGG-mIDH-O. Conclusions we demonstrate that tumor mutational burden is a powerful, robust, and clinically relevant prognostic factor of MS in mIDH patients.

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Malignant tumor purity reveals the correlation between CD3E and low grade glioma microenvironment

10.21203/rs.3.rs-93487/v1 ◽

2020 ◽

Author(s):

WangRui Liu ◽

Chuanyu Li ◽

Wenhao Xu ◽

Hao Lian ◽

Yuanyuan Qu ◽

...

Keyword(s):

Cox Regression ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Low Grade Glioma ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Low Grade ◽

Tumor Purity ◽

Immune Related Genes

Abstract Background: Tumor microenvironment (TME) contributes to the initiation and progression of low grade glioma (LGG); however, we are still unclear about the specifics of LGG's TME. Methods: In this article, we selected 161 LGG patients from the Cancer Genome Atlas (TCGA) as data, and calculated the percentage of tumor infiltrating immune cells (TICs) in LGG and the tumor purity of LGG through ESTIMATE and CIBERSORT calculation methods. Immune-related genes were screened out through Cox regression and protein-protein interaction (PPI) network. The data in Gene Expression Omnibus (GEO) was selected to screen out clinically relevant genes. After combining the two, CD3E is selected as the predictor. Finally, we conducted verification at the Affiliated Hospital of YouJiang Medical University for Nationalities (AHYMUN) center. Results: We found that the higher the expression of CD3E, the lower the purity of LGG tumors and the worse the prognosis of patients. Gene Set Enrichment Analysis (GSEA) showed that genes in the high-expressing CD3E group are mainly involved in immune-related activities. This suggests that CD3E may be responsible for regulating LGG's TME and tumor purity.Conclusion: In short, the tumor purity of LGG has a considerable impact on clinical, genomic and biological status. The expression level of CD3E may help doctors evaluate the prognosis of LGG patients and develop personalized immunotherapy plans for patients. Evaluating the ratio of different tumor purity and the new role of CD3E may provide additional insights into the complex role of the LGG microenvironment and clinical treatment.

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Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis

BMC Cancer ◽

10.1186/s12885-020-07493-x ◽

2020 ◽

Vol 20 (1) ◽

Cited By ~ 1

Author(s):

Zhenhua Yin ◽

Dejun Wu ◽

Jianping Shi ◽

Xiyi Wei ◽

Nuyun Jin ◽

...

Keyword(s):

Gene Expression ◽

Reference Value ◽

Enrichment Analysis ◽

Predictive Marker ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Fatty Aldehyde ◽

Low Grade

Abstract Background Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further. Methods In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Results Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4. Conclusion We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

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Identification of hub genes and construction of an mRNA-miRNA-lncRNA network of gastric carcinoma using integrated bioinformatics analysis

PLoS ONE ◽

10.1371/journal.pone.0261728 ◽

2021 ◽

Vol 16 (12) ◽

pp. e0261728

Author(s):

Gang Wei ◽

Youhong Dong ◽

Zhongshi He ◽

Hu Qiu ◽

Yong Wu ◽

...

Keyword(s):

Gene Expression ◽

Gastric Carcinoma ◽

Regulatory Network ◽

Messenger Rna ◽

Enrichment Analysis ◽

Bioinformatic Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Hub Genes ◽

Incidence And Mortality

Background Gastric carcinoma (GC) is one of the most common cancer globally. Despite its worldwide decline in incidence and mortality over the past decades, gastric cancer still has a poor prognosis. However, the key regulators driving this process and their exact mechanisms have not been thoroughly studied. This study aimed to identify hub genes to improve the prognostic prediction of GC and construct a messenger RNA-microRNA-long non-coding RNA(mRNA-miRNA-lncRNA) regulatory network. Methods The GSE66229 dataset, from the Gene Expression Omnibus (GEO) database, and The Cancer Genome Atlas (TCGA) database were used for the bioinformatic analysis. Differential gene expression analysis methods and Weighted Gene Co-expression Network Analysis (WGCNA) were used to identify a common set of differentially co-expressed genes in GC. The genes were validated using samples from TCGA database and further validation using the online tools GEPIA database and Kaplan-Meier(KM) plotter database. Gene set enrichment analysis(GSEA) was used to identify hub genes related to signaling pathways in GC. The RNAInter database and Cytoscape software were used to construct an mRNA-miRNA-lncRNA network. Results A total of 12 genes were identified as the common set of differentially co-expressed genes in GC. After verification of these genes, 3 hub genes, namely CTHRC1, FNDC1, and INHBA, were found to be upregulated in tumor and associated with poor GC patient survival. In addition, an mRNA-miRNA-lncRNA regulatory network was established, which included 12 lncRNAs, 5 miRNAs, and the 3 hub genes. Conclusions In summary, the identification of these hub genes and the establishment of the mRNA-miRNA-lncRNA regulatory network provide new insights into the underlying mechanisms of gastric carcinogenesis. In addition, the identified hub genes, CTHRC1, FNDC1, and INHBA, may serve as novel prognostic biomarkers and therapeutic targets.

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