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pmid:30633213

Identification of key regulators of pancreatic ductal adenocarcinoma using bioinformatics analysis of microarray data.

Nan Li · Xin Zhao · Shengyi You

Medicine · 2019 doi:10.1097/MD.0000000000014074

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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title
Identification of key regulators of pancreatic ductal adenocarcinoma using bioinformatics analysis of microarray data.
doi
10.1097/MD.0000000000014074
pmid
30633213
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[0]
Nan Li
[1]
Xin Zhao
[2]
Shengyi You
journal
Medicine
year
2019
abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal forms of cancer, and its etiology remains largely unknown. This study aimed to screen a panel of key genes and to identify their potential impact on the molecular pathways associated with the development of PDAC. Four gene expression profiles, GSE28735, GSE15471, GSE102238, and GSE43795, were downloaded from the Gene Expression Omnibus (GEO) database. The intersection of the differentially expressed genes (DEGs) in each dataset was obtained using Venn analysis. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) analysis were subsequently carried out. To screen for hub genes, a protein-protein interaction (PPI) network was constructed.The intersection of the DEGs revealed 7 upregulated and 9 downregulated genes. Upon relaxation of the selection criteria, 58 upregulated and 32 downregulated DEGs were identified. The top 5 biological processes identified by GO analysis involved peptide cross-linking, extracellular matrix (ECM) disassembly, regulation of the fibroblast growth factor receptor signaling pathway, mesoderm morphogenesis, and lipid digestion. The results of KEGG analysis revealed that the DEGs were significantly enriched in pathways involved in protein digestion and absorption, ECM-receptor interaction, pancreatic secretion, and fat digestion and absorption. The top ten hub genes were identified based on the PPI network.In conclusion, the identified hub genes may contribute to the elucidation of the underlying molecular mechanisms of PDAC and serve as promising candidates that can be utilized for the early diagnosis and prognostic prediction of PDAC. However, further experimental validation is required to confirm these results.
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The P-values, which were used to assess the significance of the differences, were calculated using a paired samples t test.
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The P-values, which were used to assess the significance of the differences, were calculated using a paired samples t test.
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The microarray gene expression profile GSE28735,[5,7] GSE15471,[13] GSE102238, and GSE43795[14] related to PDAC were downloaded from GEO (http://www.ncbi.nlm.nih.gov/geo/), which were based on the platform of GPL6244 Affymetrix Human Gene 1.0 ST Array, GPL570 Affymetrix Human Genome U133 Plus 2.0 Array, GPL19072 Agilent-052909 CBC_lncRNAmRNA_V3, and GPL10558 Illumina HumanHT-12 V4.0 expression beadchip, respectively. GSE28735 dataset contained 45 PADC tumors and 45 matching normal pancreatic tissue samples; GSE15471 contained 39 PDAC samples and 39 normal controls; GSE102238 contained 22 PDAC samples and 22 normal controls; and GSE43795 contained 6 PDAC samples and 5 normal controls were selected for subsequent analyses.
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sections[3] "Microarray data" paragraph 2
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The microarray gene expression profile GSE28735,[5,7] GSE15471,[13] GSE102238, and GSE43795[14] related to PDAC were downloaded from GEO (http://www.ncbi.nlm.nih.gov/geo/), which were based on the platform of GPL6244 Affymetrix Human Gene 1.0 ST Array, GPL570 Affymetrix Human Genome U133 Plus 2.0 Array, GPL19072 Agilent-052909 CBC_lncRNAmRNA_V3, and GPL10558 Illumina HumanHT-12 V4.0 expression beadchip, respectively. GSE28735 dataset contained 45 PADC tumors and 45 matching normal pancreatic tissue samples; GSE15471 contained 39 PDAC samples and 39 normal controls; GSE102238 contained 22 PDAC samples and 22 normal controls; and GSE43795 contained 6 PDAC samples and 5 normal controls were selected for subsequent analyses.
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The microarray gene expression profile GSE28735,[5,7] GSE15471,[13] GSE102238, and GSE43795[14] related to PDAC were downloaded from GEO (http://www.ncbi.nlm.nih.gov/geo/), which were based on the platform of GPL6244 Affymetrix Human Gene 1.0 ST Array, GPL570 Affymetrix Human Genome U133 Plus 2.0 Array, GPL19072 Agilent-052909 CBC_lncRNAmRNA_V3, and GPL10558 Illumina HumanHT-12 V4.0 expression beadchip, respectively. GSE28735 dataset contained 45 PADC tumors and 45 matching normal pancreatic tissue samples; GSE15471 contained 39 PDAC samples and 39 normal controls; GSE102238 contained 22 PDAC samples and 22 normal controls; and GSE43795 contained 6 PDAC samples and 5 normal controls were selected for subsequent analyses.
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Gene expression signatures associated with Perineural Invasion in pancreatic ductal adenocarcinoma
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Whole-Tissue Gene Expression Study of Pancreatic Ductal Adenocarcinoma
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The microarray gene expression profile GSE28735,[5,7] GSE15471,[13] GSE102238, and GSE43795[14] related to PDAC were downloaded from GEO (http://www.ncbi.nlm.nih.gov/geo/), which were based on the platform of GPL6244 Affymetrix Human Gene 1.0 ST Array, GPL570 Affymetrix Human Genome U133 Plus 2.0 Array, GPL19072 Agilent-052909 CBC_lncRNAmRNA_V3, and GPL10558 Illumina HumanHT-12 V4.0 expression beadchip, respectively. GSE28735 dataset contained 45 PADC tumors and 45 matching normal pancreatic tissue samples; GSE15471 contained 39 PDAC samples and 39 normal controls; GSE102238 contained 22 PDAC samples and 22 normal controls; and GSE43795 contained 6 PDAC samples and 5 normal controls were selected for subsequent analyses.
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Gene expression of pancreatic tumors
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The main features of 4 studies of gene expression microarray data.
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The most significant up- and downregulated DEGs in GSE28735, GSE15471, GSE102238, and GSE43795.
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Identification of DEGs from the 4 selected GEO datasets
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The most significant up- and downregulated DEGs in GSE28735, GSE15471, GSE102238, and GSE43795.
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KEGG pathway analysis of differentially expressed genes.
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The core genes and their corresponding degree.
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Module screening of the PPI network and pathway enrichment analysis
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The core genes and their corresponding degree.
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The microarray gene expression profile GSE28735,[5,7] GSE15471,[13] GSE102238, and GSE43795[14] related to PDAC were downloaded from GEO (http://www.ncbi.nlm.nih.gov/geo/), which were based on the platform of GPL6244 Affymetrix Human Gene 1.0 ST Array, GPL570 Affymetrix Human Genome U133 Plus 2.0 Array, GPL19072 Agilent-052909 CBC_lncRNAmRNA_V3, and GPL10558 Illumina HumanHT-12 V4.0 expression beadchip, respectively. GSE28735 dataset contained 45 PADC tumors and 45 matching normal pancreatic tissue samples; GSE15471 contained 39 PDAC samples and 39 normal controls; GSE102238 contained 22 PDAC samples and 22 normal controls; and GSE43795 contained 6 PDAC samples and 5 normal controls were selected for subsequent analyses.
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The paper names GSE28735, GSE15471, GSE102238, GSE43795 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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Four gene expression profiles, GSE28735, GSE15471, GSE102238, and GSE43795, were downloaded from the Gene Expression Omnibus (GEO) database. The intersection of the differentially expressed genes (DEGs) in each dataset was obtained using Venn analysis. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) analysis were subsequently carried out. To screen for hub genes, a protein-protein interaction (PPI) network was constructed.The intersection of the DEGs revealed 7 upregulated and 9 downregulated genes. Upon relaxation of the selection criteria, 58 upregulated and 32 downregulated DEGs were identified. The top 5 biological processes identified by GO analysis involved peptide cross-linking, extracellular matrix (ECM) disassembly, regulation of the fibroblast growth factor receptor signaling pathway, mesoderm morphogenesis, and lipid digestion. The results of KEGG analysis revealed that the DEGs were significantly enriched in pathways involved in protein digestion and absorption, ECM-receptor interaction, pancreatic secretion, and fat digestion and absorption. The top ten hub genes were identified based on the PPI network.In conclusion, the identified hub genes may contribute to the elucidation of the underlying molecular mechanisms of PDAC and serve as promising candidates that can be utilized for the early diagnosis and prognostic prediction of PDAC. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE28735", "GSE15471", "GSE102238", "GSE43795"], "resolved_accessions": ["GSE28735", "GSE15471", "GSE102238", "GSE43795"], "statements": ["The microarray gene expression profile GSE28735,[5,7] GSE15471,[13] GSE102238, and GSE43795[14] related to PDAC were downloaded from GEO (http://www.ncbi.nlm.nih.gov/geo/), which were based on the platform of GPL6244 Affymetrix Human Gene 1.0 ST Array, GPL570 Affymetrix Human Genome U133 Plus 2.0 Array, GPL19072 Agilent-052909 CBC_lncRNAmRNA_V3, and GPL10558 Illumina HumanHT-12 V4.0 expression beadchip, respectively. GSE28735 dataset contained 45 PADC tumors and 45 matching normal pancreatic tissue samples; GSE15471 contained 39 PDAC samples and 39 normal controls; GSE102238 contained 22 PDAC samples and 22 normal controls; and GSE43795 contained 6 PDAC samples and 5 normal controls were selected for subsequent analyses."], "basis": "The paper names GSE28735, GSE15471, GSE102238, GSE43795 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "assets": ["source:pmid:30633213", "data:geo:GSE102238", "asset:table:pmid:30633213:1", "asset:table:pmid:30633213:2", "asset:table:pmid:30633213:3", "asset:table:pmid:30633213:4"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE102238"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:13:22Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 3, "usage": {"prompt_tokens": 29630, "completion_tokens": 2136, "cached_tokens": 784}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:30633213", "type": "paper", "label": "pmid:30633213"}, {"id": "source:pmid:30633213", "type": "manuscript", "label": "PMID 30633213 full text"}, {"id": "data:geo:GSE102238", "type": "dataset", "label": "GEO GSE102238"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:30633213", "type": "paper", "label": "pmid:30633213"}, {"id": "source:pmid:30633213", "type": "manuscript", "label": "PMID 30633213 full text"}, {"id": "data:geo:GSE102238", "type": "dataset", "label": "GEO GSE102238"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-30633213", "type": "extraction", "used": ["source:pmid:30633213"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE102238", "type": "accession_resolution", "used": ["data:geo:GSE102238"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:30633213", "parent_hash": "sha256:8450f7107becb8269c184cb79ffae95fb3737206190bde283ec357ca3ccd53f1", "fork_of": null, "generation": 7}, "gaps": ["asset:data:geo:GSE102238 licence not read", "asset:data:geo:GSE102238 not downloaded", "asset:data:geo:GSE15471 licence not read", "asset:data:geo:GSE15471 not downloaded", "asset:data:geo:GSE28735 licence not read", "asset:data:geo:GSE28735 not downloaded", "asset:data:geo:GSE43795 licence not read", "asset:data:geo:GSE43795 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["nocarcinoma using bioinformatics analysis of microarray data."], "order_basis": "paper_text_order:57", "id": "assay:1"}, {"role": "analysis", "definition_id": "network_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["protein-protein interaction"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}