ArticleTranslational cancer research2021
Identification of key genes and pathways at the downstream of S100PBP in pancreatic cancer cells by integrated bioinformatical analysis.
Article in Translational cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 9 citations in OpenAlex.
- Prognostic Value of S100 Family mRNA Expression in Hepatocellular Carcinoma.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2024Article
- S100PBP is regulated by mutated KRAS and plays a tumour suppressor role in pancreatic cancer.Oncogene · 2023Article
- A pan-cancer analysis based on weighted gene co-expression network analysis identifies the biomarker utility of lamin B1 in human tumors.Cancer biomarkers : section A of Disease markers · 2022Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of the present study was to identify key genes and pathways downstream of S100PPBP in pancreatic cancer cells.
methodsThe microarray datasets GSE35196 (S100PBP knockdown) and GSE35198 (S100PBP overexpression) were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were obtained separately from GEO2R, and heatmaps showing clustering analysis of DEGs were generated using R software. Gene Ontology and pathway enrichment analyses were performed for identified DEGs using the Database for Annotation, Visualization, and Integrated Discovery and Kyoto Encyclopedia of Genes and Genomes, respectively. A protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes and Cytoscape software. Relevant expression datasets of key identified genes were downloaded from The Cancer Genome Atlas, and overall survival (OS) analysis was performed with R software. Finally, Gene Expression Profiling Interactive Analysis was used to evaluate the expression of key DEGs in pancreatic cancer tissues.
resultsA total of 34 DEGs (11 upregulated and 23 downregulated) were screened out from the two datasets. Gene Ontology enrichment analysis revealed that the identified DEGs were mainly functionally enriched in ATPase activity, production of siRNA involved in RNA interference, and production of miRNAs involved in gene silencing by miRNA. The pathway enrichment analysis of the identified DEGs showed enrichment mainly in apoptosis, non-homologous end-joining, and miRNA pathways in cancer. The protein-protein interaction network was composed of 21 nodes and 30 edges. After survival analysis and gene expression analysis, 4 genes associated with poor prognosis were selected, including LMNB1, PRKRA, SEPT2, and XRCC5.
conclusionsLMNB1, PRKRA, SEPT2, and XRCC5 could be key downstream genes of the S100PBP gene in the inhibition of pancreatic cancer cell adhesion.
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