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Gastric cancer (GC) is the most common type of malignant tumor within the gastrointestinal tract, and GC metastasis is associated with poor prognosis. Polypyrimidine tract binding protein 1 (PTBP1) is an RNA-binding protein implicated in various types of tumor development and metastasis. However, the role of PTBP1 in GC metastasis remains elusive. In this study, we verified that PTBP1 was upregulated in GC tissues and cell lines, and higher PTBP1 level was associated with poorer prognosis. It was shown that PTBP1 knockdown in vitro inhibited GC cell migration, whereas PTBP1 overexpression promoted the migration of GC cells. In vivo, the knockdown of PTBP1 notably reduced both the size and occurrence of metastatic nodules in a nude mice liver metastasis model. We identified phosphoglycerate kinase 1 (PGK1) as a downstream target of PTBP1 and found that PTBP1 increased the stability of PGK1 by directly binding to its mRNA. Furthermore, the PGK1/SNAIL axis could be required for PTBP1's function in the promotion of GC cell migration. These discoveries suggest that PTBP1 could be a promising therapeutic target for GC.
Pubmed ID: 38247832 RIS Download
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A software tool used for functional enrichment and interaction network analysis of genes and proteins. Users can search against a default background database or load customized database. The results can be depicted as venn, bar, column, pie and doughnut charts.
View all literature mentionsWeb server for cancer and normal gene expression profiling and interactive analyses. Interactive web server for analyzing RNA sequencing expression data of tumors and normal samples from TCGA and GTEx projects, using standard processing pipeline. Provides customizable functions such as tumor or normal differential expression analysis, profiling according to cancer types or pathological stages, patient survival analysis, similar gene detection, correlation analysis and dimensionality reduction analysis.
View all literature mentionsWeb tool for meta analysis based discovery and validation of survival biomarkers. Assesses effect of genes on survival using cancer samples including breast, ovarian, lung, and gastric cancer. Sources for databases include GEO, EGA, and TCGA.
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