Identification of key genes and pathways at the downstream of S100PBP in pancreatic cancer cells by integrated bioinformatical analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35116411", "kind": "science-record", "revision": 6, "content_hash": "sha256:fab6b1ab6c193a9ac625438e1753e54ac4cbe5089d7b00560fa60e44954ac041", "created_at": "2026-11-01T17:36:50Z", "updated_at": "2026-11-01T22:48:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key genes and pathways at the downstream of S100PBP in pancreatic cancer cells by integrated bioinformatical analysis.", "doi": "10.21037/tcr-20-2531", "pmid": "35116411", "authors": ["Yu-Jie Lu", "Yi Yang", "Ting-Hui Hu", "Wei-Ming Duan"], "journal": "Translational cancer research", "year": 2021, "abstract": "BACKGROUND: The aim of the present study was to identify key genes and pathways downstream of S100PPBP in pancreatic cancer cells.\nMETHODS: The 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.\nRESULTS: A 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.\nCONCLUSIONS: LMNB1, PRKRA, SEPT2, and XRCC5 could be key downstream genes of the S100PBP gene in the inhibition of pancreatic cancer cell adhesion.", "claims": [{"id": "claim-method", "statement": "Limma package was used to identify the different expression of genes by linear modelling. Survival plots were showed by the Kaplan-Meier method, and the significance was estimated by the log-rank test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35116411", "locator": "sections[5] \"Data processing\" paragraph 2", "quote": "Limma package was used to identify the different expression of genes by linear modelling."}, {"asset": "source:pmid:35116411", "locator": "sections[9] \"Statistical analysis\" paragraph 2", "quote": "Survival plots were showed by the Kaplan-Meier method, and the significance was estimated by the log-rank test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All information from GEO is available and free for public, so the agreement of the medical ethics committee board was not necessary.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35116411", "locator": "sections[10] \"Ethical statement\" paragraph 2", "quote": "All information from GEO is available and free for public, so the agreement of the medical ethics committee board was not necessary."}], "state": "complete"}, {"id": "claim-target-result", "statement": "After survival analysis and gene expression analysis, 4 genes associated with poor prognosis were selected, including LMNB1, PRKRA, SEPT2, and XRCC5.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35116411", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "After survival analysis and gene expression analysis, 4 genes associated with poor prognosis were selected, including LMNB1, PRKRA, SEPT2, and XRCC5."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "After survival analysis and gene expression analysis, 4 genes associated with poor prognosis were selected, including LMNB1, PRKRA, SEPT2, and XRCC5.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35116411"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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