ArticleDisease markers2018
Identification of Core Biomarkers Associated with Outcome in Glioma: Evidence from Bioinformatics Analysis.
Article in Disease markers, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Bioinformatics Analysis of the miR-15 Family Members and Their Potential Target Genes in Breast Cancer Progression.Advanced biomedical research · 2026Article
- Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches.Scientific reports · 2024Article
- Bioinformatics Analysis and Experimental Validation for Exploring Key Molecular Markers for Glioblastoma.Applied biochemistry and biotechnology · 2024Article
- Antitumor Effect of Poplar Propolis on Human Cutaneous Squamous Cell Carcinoma A431 Cells.International journal of molecular sciences · 2023Article
- Molecular basis of retinal remodeling in a zebrafish model of retinitis pigmentosa.Cellular and molecular life sciences : CMLS · 2023Article
- PriPath: identifying dysregulated pathways from differential gene expression via grouping, scoring, and modeling with an embedded feature selection approach.BMC bioinformatics · 2023Article
- Upregulation of KIF11 in TP53 Mutant Glioma Promotes Tumor Stemness and Drug Resistance.Cellular and molecular neurobiology · 2022Article
- Identification of hub genes and biological pathways in glioma via integrated bioinformatics analysis.The Journal of international medical research · 2022Article
- Article
- Glioma Subtypes Based on the Activity Changes of Immunologic and Hallmark Gene Sets in Cancer.Frontiers in endocrinology · 2022Article
- LASSO-based screening for potential prognostic biomarkers associated with glioblastoma.Frontiers in oncology · 2022Article
- Screening and identification of LMNB1 and DLGAP5, two key biomarkers in gliomas.Bioscience reports · 2021Article
- Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Pediatric Sepsis.Medical science monitor : international medical journal of experimental and clinical research · 2020Article
- Identification of hub genes associated with outcome of clear cell renal cell carcinoma.Oncology letters · 2020Article
- Profiling Analysis Reveals the Crucial Role of the Endogenous Peptides in Bladder Cancer Progression.OncoTargets and therapy · 2020Article
- Analysis of Long Noncoding RNA ZNF667-AS1 as a Potential Biomarker for Diagnosis and Prognosis of Glioma Patients.Disease markers · 2020Article
- Alterations in Immune-Related Genes as Potential Marker of Prognosis in Breast Cancer.Frontiers in oncology · 2020Article
- Article
- Identification of Core Gene Biomarkers in Patients with Diabetic Cardiomyopathy.Disease markers · 2018Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioma is the most common neoplasm of the central nervous system (CNS); the progression and outcomes of which are affected by a complicated network of genes and pathways. We chose a gene expression profile of GSE66354 from GEO database to search core biomarkers during the occurrence and development of glioma. A total of 149 samples, involving 136 glioma and 13 normal brain tissues, were enrolled in this article. 1980 differentially expressed genes (DEGs) including 697 upregulated genes and 1283 downregulated genes between glioma patients and healthy individuals were selected using GeoDiver and GEO2R tool. Then, gene ontology (GO) analysis as well as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were carried out using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING) and Molecular Complex Detection (MCODE) plug-in was employed to imagine protein-protein interaction (PPI) of these DEGs. The upregulated genes were enriched in cell cycle, ECM-receptor interaction, and p53 signaling pathway, while the downregulated genes were enriched in retrograde endocannabinoid signaling, glutamatergic synapse, morphine addiction, GABAergic synapse, and calcium signaling pathway. Subsequently, 4 typical modules were discovered by the PPI network utilizing MCODE software. Besides, 15 hub genes were chosen according to the degree of connectivity, including TP53, CDK1, CCNB1, and CCNB2, the Kaplan-Meier analysis of which was further identified. In conclusion, this bioinformatics analysis indicated that DEGs and core genes, such as TP53, might influence the development of glioma, especially in tumor proliferation, which were expected to be promising biomarkers for diagnosis and treatment of glioma.
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