Identification of gene signatures and potential therapeutic targets for acquired chemotherapy resistance in gastric cancer patients.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34012635", "kind": "science-record", "revision": 5, "content_hash": "sha256:8d230d09993c95c001185c4c5122a737c78f33cccc22c78e1fa189d33affba4a", "created_at": "2026-11-01T17:35:18Z", "updated_at": "2026-11-01T22:46:43Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of gene signatures and potential therapeutic targets for acquired chemotherapy resistance in gastric cancer patients.", "doi": "10.21037/jgo-21-81", "pmid": "34012635", "authors": ["Jie Sun", "Jingjing Zhao", "Zhenkun Yang", "Zhiyi Zhou", "Peihua Lu"], "journal": "Journal of gastrointestinal oncology", "year": 2021, "abstract": "BACKGROUND: Gastric cancer (GC) is the most common type of gastrointestinal cancer, and has been studied extensively. However, resistance to chemotherapeutic agents has become a major problem, leading to treatment failure. This study aimed to investigate the molecular mechanisms mediating acquired resistance to cisplatin and fluorouracil (CF) combination-based chemotherapy in GC patients.\nMETHODS: The microarray datasets (GSE14209, GSE30070) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) using the limma package in R/Bioconductor. Possible targets of the DEMs were predicted using miRWalk, and the putative miRNA-mRNA regulatory network was constructed using Cytoscape software. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) analyses were then conducted and visualized using the Search Tool for Retrieval of Interacting Genes (STRING) and Cytoscape. The prognostic value of hub genes was revealed by Kaplan-Meier Plotter. The causal relationships and interactions between proteins were displayed using DisNor. Finally, similarity analysis was conducted using the Connectivity Map (CMap) profiles to predict a group of small molecules in GC treatment.\nRESULTS: A total of 394 DEGs and 31 DEMs were identified after analysis of pre- and post-treatment samples of clinical responders to CF therapy. TM9SF4, hsa-miR-185-5p, and hsa-miR-145-5p were found to be critical in the miRNA-mRNA regulatory network. The DEGs were found to be mainly enriched in the processes of ribonucleoprotein complex assembly, catalytic activity acting on RNA, mitochondrial matrix, and thermogenesis. The DEMs were predominantly found to be involved in single-stranded RNA binding and endoplasmic reticulum lumen. HDAC5, DDX17, ILF3, and SDHC were identified as hub genes in the PPI network. Of these, HDAC5, DDX17, and ILF3 were found to be closely related to the overall survival of GC patients. DisNor identified the first neighbors of the key genes. Furthermore, CMap profiles predicted a group of small molecules, including several histone deacetylase inhibitors (HDACIs), menadione, and mibefradil, which could serve as promising therapeutic agents to reverse acquired resistance to CF therapy.\nCONCLUSIONS: Our findings reveal new targets and alternative therapies to overcome the acquired resistance of GC patients to CF treatment.", "claims": [{"id": "claim-method", "statement": "The microarray datasets (GSE14209, GSE30070) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) using the limma package in R/Bioconductor.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34012635", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The microarray datasets (GSE14209, GSE30070) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) using the limma package in R/Bioconductor."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The microarray datasets (GSE14209, GSE30070) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) using the limma package in R/Bioconductor.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34012635", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The microarray datasets (GSE14209, GSE30070) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) using the limma package in R/Bioconductor."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 394 DEGs and 31 DEMs were identified after analysis of pre- and post-treatment samples of clinical responders to CF therapy.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34012635", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 394 DEGs and 31 DEMs were identified after analysis of pre- and post-treatment samples of clinical responders to CF therapy."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A total of 394 DEGs and 31 DEMs were identified after analysis of pre- and post-treatment samples of clinical responders to CF therapy.", "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:34012635"], "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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