Glioblastoma multiforme (GBM) is categorized by rapid malignant cellular growth in the central nervous system (CNS) tumors. It is one of the most prevailing primary brain tumors, particularly in human male adults. Even though the combination therapy comprises surgery, chemotherapy, and adjuvant therapies, the survival rate is on average 14.6 months. Glioma stem cells (GSCs) have key roles in tumorigenesis, progression, and counteracting chemotherapy and radiotherapy. In our study, firstly, the gene expression dataset GSE45117 was retrieved and differentially expressed genes (DEGs) were spotted. The co-expression network analysis was employed on DEGs to find the significant modules. The most significant module resulting from co-expression analysis was the turquoise module. The turquoise module related to the tumor cells, hypoxia, normoxic treatments of glioblastoma tumor (GBT), and GSCs were screened. Sixty-one common genes in the turquoise module were selected generated through the co-expression analysis and protein-protein interaction (PPI) network. Moreover, the GO and KEGG pathway enrichment results were studied. Twenty common hub genes were screened by the NetworkAnalyst web instrument constructed on the PPI network through the STRING database. After survival analysis via the Kaplan-Meier (KM) plotter from The Cancer Genome Atlas (TCGA) database, we identified the five most significant hub genes strongly related to the progression of GBM. We further observed these five most significant hub genes also up-regulated in another GBM gene expression dataset. The protein-protein interaction (PPI) network of the turquoise module genes was constructed and a KEGG pathway enrichments study of the turquoise module genes was performed. The VEGF signaling pathway was emphasized because of the strong link with GBM. A gene-disease association network was further constructed to demonstrate the information of the progression of GBM and other related brain neoplasms. All hub genes assessed through this study would be potential markers for the prognosis and diagnosis of GBM.
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http://dx.doi.org/10.3390/genes13030518 | DOI Listing |
Mol Neurobiol
January 2025
Department of Neurology, School of Medicine, Affiliated ZhongDa Hospital, Southeast University, Dingjiaqiao 87, Nanjing, 210009, Jiangsu, China.
The dysregulation of lipid metabolism has been associated with the etiology and progression of the neurological pathology. However, the roles of lipid metabolism and the molecular mechanism in epilepsy and the use of antiepileptic drugs (AEDs) are relatively understudied. Gene expression profiles of GSE143272 from blood samples were included for differential analysis, and the lipid metabolism-related differentially expressed genes (DEGs) were identified.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine, No. 58, Yuelu District, Changsha, 410006, Hunan, China.
Objective: Rosmarinic acid (RosA) is a natural polyphenol compound that has been shown to be effective in the treatment of inflammatory disease and a variety of malignant tumors. However, its specific mechanism for the treatment of lung adenocarcinoma (LUAD) has not been fully elucidated. Therefore, this study aims to clarify the mechanism of RosA in the treatment of LUAD by integrating bioinformatics, network pharmacology and in vivo experiments, and to explore the potential of the active ingredients of traditional Chinese medicine in treating LUAD.
View Article and Find Full Text PDFCurr Pharm Biotechnol
January 2025
Department of Intensive Care Unit, Affiliated Hospital of Guangdong Medical University, 524000 Zhanjiang, China.
Objectives: This study aimed to comprehensively investigate the molecular landscape of gastric cancer (GC) by integrating various bioinformatics tools and experimental validations.
Methodology: GSE79973 dataset, limma package, STRING, UALCAN, GEPIA, OncoDB, cBioPortal, DAVID, TISIDB, Gene Set Cancer Analysis (GSCA), tissue samples, RT-qPCR, and cell proliferation assay were employed in this study.
Results: Analysis of the GSE79973 dataset identified 300 differentially expressed genes (DEGs), from which COL1A1, COL1A2, CHN1, and FN1 emerged as pivotal hub genes using protein-protein interaction network analysis.
BMC Med Inform Decis Mak
January 2025
Department of Pharmacy, Hangzhou Third People's Hospital, Hangzhou Third Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Background: Alopecia areata (AA) is a common non-scarring hair loss disorder associated with autoimmune conditions. However, the pathobiology of AA is not well understood, and there is no targeted therapy available for AA. METHODS: In this study, differential gene expression analysis, immune status assessment, weighted correlation network analysis (WGCNA), and functional enrichment analysis were performed to identify shared genes associated with both immunological response and AA.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Research, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway.
Testicular germ cell tumour (TGCT) is a malignancy with known inherited risk factors, affecting young men. We have previously identified several hundred differentially abundant circulating RNAs in pre-diagnostic serum from TGCT cases compared to healthy controls. In this study, we performed Weighted Gene Co-expression Network Analysis (WGCNA) on mRNA and miRNA data from these samples.
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