Background: This study investigates the gene expression characteristics of glioma-initiating cells (GIC), an important subgroup of glioblastoma (GBM), after knockdown of PBK (PDZ-binding kinase). Differentially expressed genes (DEGs) between PBK knockdown GIC and control groups were screened through bioinformatics methods. The authors analyzed the mechanisms and roles of these DEGs in GBM tumorigenesis and patient prognosis.
Methods: Microarray data (GSE53800) were obtained from the Gene Expression Omnibus (GEO) database, selecting 18 GIC cell line samples with or without PBK knockdown. Each control and knockdown group contained three samples. DEGs were screened using R software. GO enrichment analysis, KEGG pathway analysis, PPI network analysis, and hub gene identification were conducted to explore DEG mechanisms. Western blot analysis was also performed to detect EIF4E protein expression, one of the key hub genes, after PBK knockdown in the HS683 glioma cell line.
Results: A total of 175 upregulated and 145 downregulated genes were identified. GO analysis showed that DEGs were mainly enriched in the positive regulation of cell proliferation, cell adhesion, and angiogenesis. KEGG pathway analysis revealed that DEGs were mainly involved in neuroactive ligand-receptor interactions, calcium signaling, and HIF-1 signaling pathways. Western blot results indicated that EIF4E was downregulated after PBK knockdown.
Conclusion: A group of genes, such as EIF4E, were closely associated with PBK expression and functions. These findings may provide insight into the molecular mechanism of PBK in GBM.
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http://dx.doi.org/10.1097/MS9.0000000000002708 | DOI Listing |
Ann Med Surg (Lond)
December 2024
Medicine Faculty, University of Tübingen, Tübingen, Germany.
Background: This study investigates the gene expression characteristics of glioma-initiating cells (GIC), an important subgroup of glioblastoma (GBM), after knockdown of PBK (PDZ-binding kinase). Differentially expressed genes (DEGs) between PBK knockdown GIC and control groups were screened through bioinformatics methods. The authors analyzed the mechanisms and roles of these DEGs in GBM tumorigenesis and patient prognosis.
View Article and Find Full Text PDFCancer Cell Int
June 2024
Department of Neurosurgery, Linyi People's Hospital, Shandong Second Medical University, Linyi, Shandong Province, 276000, China.
Background: Glioma is considered the most common primary malignant tumor of the central nervous system. Although traditional treatments have not achieved satisfactory outcomes, recently, targeted therapies for glioma have shown promising efficacy. However, due to the single-target nature of targeted therapy, traditional targeted therapies are ineffective; thus, novel therapeutic targets are urgently needed.
View Article and Find Full Text PDFMed Oncol
January 2024
Department of Cell Biology, School of Pharmacy, Binzhou Medical University, Yantai, 264003, Shandong, China.
Peroxicedoxin 4 (PRDX4), a member of the peroxicedoxins (PRDXs), has been reported in many cancer-related studies, but its role in uterine corpus endometrial carcinoma (UCEC) is not fully understood. In the present study, we found that PRDX4 was highly expressed in UCEC tissues and cell lines through the combination of bioinformatics analysis and experiments, and elevated PRDX4 levels were associated with poor prognosis. Knockdown of PRDX4 significantly blocked the proliferation and migration of the UCEC cell line Ishikawa and reduced degree of cell confluence.
View Article and Find Full Text PDFGenome Med
January 2024
Beijing Neurosurgical Institute, Capital Medical University, Beijing, 100070, China.
Background: Pituitary neuroendocrine tumors (PitNETs) are one of the most common types of intracranial tumors. Currently, the cellular characteristics of normal pituitary and various other types of PitNETs are still not completely understood.
Methods: We performed single-cell RNA sequencing (scRNA-seq) on 4 normal samples and 24 PitNET samples for comprehensive bioinformatics analysis.
BMC Cancer
January 2024
School of Medicine, Anhui University of Science and Technology, Chongren Building, No 168, Taifeng St, Huainan, 232001, P.R. China.
Objection: Investigating the key genes and mechanisms that influence stemness in lung adenocarcinoma.
Methods: First, consistent clustering analysis was performed on lung adenocarcinoma patients using stemness scoring to classify them. Subsequently, WGCNA was utilized to identify key modules and hub genes.
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