{"title":"The identification of key genes and pathways in glioblastoma by bioinformatics analysis.","authors":"Zahra Farsi, Najaf Allahyari Fard","doi":"10.1080/23723556.2023.2246657","DOIUrl":null,"url":null,"abstract":"<p><p>GBM is the most common and aggressive type of brain tumor. It is classified as a grade IV tumor by the WHO, the highest grade. Prognosis is generally poor, with most patients surviving only about a year. Only 5% of patients survive longer than 5 years. Understanding the molecular mechanisms that drive GBM progression is critical for developing better diagnostic and treatment strategies. Identifying key genes involved in GBM pathogenesis is essential to fully understand the disease and develop targeted therapies. In this study two datasets, GSE108474 and GSE50161, were obtained from the Gene Expression Omnibus (GEO) to compare gene expression between GBM and normal samples. Differentially expressed genes (DEGs) were identified and analyzed. To construct a protein-protein interaction (PPI) network of the commonly up-regulated and down-regulated genes, the STRING 11.5 and Cytoscape 3.9.1 were utilized. Key genes were identified through this network analysis. The GEPIA database was used to confirm the expression levels of these key genes and their association with survival. Functional and pathway enrichment analyses on the DEGs were conducted using the Enrichr server. In total, 698 DEGs were identified, consisting of 377 up-regulated genes and 318 down-regulated genes. Within the PPI network, 11 key up-regulated genes and 13 key down-regulated genes associated with GBM were identified. NOTCH1, TOP2A, CD44, PTPRC, CDK4, HNRNPU, and PDGFRA were found to be important targets for potential drug design against GBM. Additionally, functional enrichment analysis revealed the significant impact of Epstein-Barr virus (EBV), Cell Cycle, and P53 signaling pathways on GBM.</p>","PeriodicalId":37292,"journal":{"name":"Molecular and Cellular Oncology","volume":"10 1","pages":"2246657"},"PeriodicalIF":2.6000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10431734/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular and Cellular Oncology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23723556.2023.2246657","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
GBM is the most common and aggressive type of brain tumor. It is classified as a grade IV tumor by the WHO, the highest grade. Prognosis is generally poor, with most patients surviving only about a year. Only 5% of patients survive longer than 5 years. Understanding the molecular mechanisms that drive GBM progression is critical for developing better diagnostic and treatment strategies. Identifying key genes involved in GBM pathogenesis is essential to fully understand the disease and develop targeted therapies. In this study two datasets, GSE108474 and GSE50161, were obtained from the Gene Expression Omnibus (GEO) to compare gene expression between GBM and normal samples. Differentially expressed genes (DEGs) were identified and analyzed. To construct a protein-protein interaction (PPI) network of the commonly up-regulated and down-regulated genes, the STRING 11.5 and Cytoscape 3.9.1 were utilized. Key genes were identified through this network analysis. The GEPIA database was used to confirm the expression levels of these key genes and their association with survival. Functional and pathway enrichment analyses on the DEGs were conducted using the Enrichr server. In total, 698 DEGs were identified, consisting of 377 up-regulated genes and 318 down-regulated genes. Within the PPI network, 11 key up-regulated genes and 13 key down-regulated genes associated with GBM were identified. NOTCH1, TOP2A, CD44, PTPRC, CDK4, HNRNPU, and PDGFRA were found to be important targets for potential drug design against GBM. Additionally, functional enrichment analysis revealed the significant impact of Epstein-Barr virus (EBV), Cell Cycle, and P53 signaling pathways on GBM.
期刊介绍:
For a long time, solid neoplasms have been viewed as relatively homogeneous entities composed for the most part of malignant cells. It is now clear that tumors are highly heterogeneous structures that evolve in the context of intimate interactions between cancer cells and endothelial, stromal as well as immune cells. During the past few years, experimental and clinical oncologists have witnessed several conceptual transitions of this type. Molecular and Cellular Oncology (MCO) emerges within this conceptual framework as a high-profile forum for the publication of fundamental, translational and clinical research on cancer. The scope of MCO is broad. Submissions dealing with all aspects of oncogenesis, tumor progression and response to therapy will be welcome, irrespective of whether they focus on solid or hematological neoplasms. MCO has gathered leading scientists with expertise in multiple areas of cancer research and other fields of investigation to constitute a large, interdisciplinary, Editorial Board that will ensure the quality of articles accepted for publication. MCO will publish Original Research Articles, Brief Reports, Reviews, Short Reviews, Commentaries, Author Views (auto-commentaries) and Meeting Reports dealing with all aspects of cancer research.