Potential therapeutic targets and small molecular drugs for pediatric B-precursor acute lymphoblastic leukemia treatment based on microarray data.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:28789378", "kind": "science-record", "revision": 9, "content_hash": "sha256:04a321d3bb486ee8e109be0c0f4914bc8e7cb4a857e2b327eca0d53e6537f9fa", "created_at": "2026-11-01T15:40:27Z", "updated_at": "2026-11-01T22:43:04Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Potential therapeutic targets and small molecular drugs for pediatric B-precursor acute lymphoblastic leukemia treatment based on microarray data.", "doi": "10.3892/ol.2017.6343", "pmid": "28789378", "authors": ["Limei Kong", "Xiaowei Zhang", "Chao Li", "Liping Zhou"], "journal": "Oncology letters", "year": 2017, "abstract": "The current study investigated the molecular mechanisms underlying pediatric acute lymphoblastic leukemia (ALL) and screened for small molecular drugs as supplementary drugs to aid current therapy. Gene expression data of Gene Expression Omnibus (GEO) DataSet GSE42221, which consists of 7 primary human B-precursor samples and 4 control B-cell progenitor lymphoblast samples from patients with pediatric ALL, were downloaded from the public GEO database. Linear Models for Microarray Analysis package for R statistical software was used to identify differentially expressed genes (DEGs). Subsequently, biclustering analysis of DEGs was performed using pheatmap package for R. Functional enrichment analysis of DEGs was conducted using the Database for Annotation, Visualization and Integrated Discovery tool. Additionally, Search Tool for the Retrieval of Interacting Genes software was used to screen protein-protein interactions (PPIs) of the DEGs, and Connectivity Map database was employed to obtain small-molecule drugs that were significantly associated with DEGs. In total, 116 genes were identified as DEGs in pediatric ALL, including 56 downregulated and 60 upregulated genes. Functional enrichment analysis identified that upregulated DEGs, including marker of proliferation Ki-67, cyclin F and nucleolar and spindle associated protein 1, were significantly enriched in mesenchymal cell differentiation and development processes, whilst downregulated DEGs, including bone marrow morphogenetic protein 2, semaphoring 3F and ephrin B1 were enriched in cell cycle process. Amongst the DEGs, 169 PPIs were identified. Notably, carbimazole and quinostatin were associated with DEGs. Additionally, a number of DEGs were targeted by the two drugs, including signal transducer and activator of transcription 3, nucleolar and spindle associated protein 1 and cell division cycle 20. Mesenchymal cell differentiation and development as well as cell cycle processes may be important for pediatric ALL. Quinostatin may be used as a potent supplementary drug for treating pediatric ALL.", "claims": [{"id": "claim-method", "statement": "DEGs were screened for each sample using Linear Models for Microarray Analysis (limma) package of R language (http://www.bioconductor.org/packages/release/bioc/html/limma.html) (14), in which the Benjamini and Hochberg method was applied for multiple testing correction (15).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28789378", "locator": "sections[5] \"Data preprocessing and differential analysis\" paragraph 2", "quote": "DEGs were screened for each sample using Linear Models for Microarray Analysis (limma) package of R language (http://www.bioconductor.org/packages/release/bioc/html/limma.html) (14), in which the Benjamini and Hochberg method was applied for multiple testing correction (15)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study downloaded GEO dataset GSE42221 from the public GEO database, used the Linear Models for Microarray Analysis (limma) package to identify DEGs, and identified 116 DEGs, comprising 56 downregulated and 60 upregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:28789378", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Gene expression data of Gene Expression Omnibus (GEO) DataSet GSE42221, which consists of 7 primary human B-precursor samples and 4 control B-cell progenitor lymphoblast samples from patients with pediatric ALL, were downloaded from the public GEO database."}, {"asset": "source:pmid:28789378", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Linear Models for Microarray Analysis package for R statistical software was used to identify differentially expressed genes (DEGs)."}, {"asset": "source:pmid:28789378", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "In total, 116 genes were identified as DEGs in pediatric ALL, including 56 downregulated and 60 upregulated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study downloaded GEO dataset GSE42221 from the public GEO database, used the Linear Models for Microarray Analysis (limma) package to identify DEGs, and identified 116 DEGs, comprising 56 downregulated and 60 upregulated genes.", "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:28789378"], "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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