Exploration of estrogen receptor-associated hub genes and potential molecular mechanisms in non-smoking females with lung adenocarcinoma using integrated bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31611968", "kind": "science-record", "revision": 7, "content_hash": "sha256:7d586dc1a14b2f48e7ed724c5b42746039064201a457a256a178ee769e0edecf", "created_at": "2026-11-01T15:40:50Z", "updated_at": "2026-11-01T22:00:54Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploration of estrogen receptor-associated hub genes and potential molecular mechanisms in non-smoking females with lung adenocarcinoma using integrated bioinformatics analysis.", "doi": "10.3892/ol.2019.10845", "pmid": "31611968", "authors": ["Hao Wang", "Zhihong Zhang", "Ke Xu", "Song Wei", "Lailing Li", "Lijun Wang"], "journal": "Oncology letters", "year": 2019, "abstract": "The present study aimed to explore important estrogen receptor-associated genes and to determine the potential pathogenic and prognostic factors for lung adenocarcinoma in non-smoking females. The gene expression profiles of the two datasets (GSE32863 and GSE75037) were downloaded from the Gene Expression Omnibus (GEO) database. Data for non-smoking female patients with lung adenocarcinoma from The Cancer Genome Atlas (TCGA) database were also downloaded. The Linear Models for Microarray Data package in R was used to explore the differentially expressed genes (DEGs) between samples from non-smoking female patients with lung adenocarcinoma and samples of adjacent non-cancerous lung tissue. The Database for Annotation, Visualization and Integrated Discovery was used for functional enrichment of the DEGs. The Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape software were used to obtain a protein-protein interaction (PPI) network and to identify the hub genes. In addition, the network between the estrogen receptor and the DEGs was constructed. A Kaplan-Meier survival plot was used to analyze the overall survival (OS). In total, 248 DEGs were identified in the GEO database, and 2,362 DEGs were identified in TCGA database. The intersection of the two datasets (DEGs in GEO and TCGA) revealed 170 DEGs, and these were selected for further investigation. Gene Ontology was used to group the 170 DEGs into biological process, molecular function and cellular component categories. Kyoto Encyclopedia of Genes and Genomes pathway analysis was subsequently performed. A total of 27 hub genes, including caveolin 1 (CAV1), matrix metallopeptidase 9 (MMP9), secreted phosphoprotein 1 (SPP1) and collagen type I α 1 chain (COL1A1), were closely associated with the estrogen receptor. CAV1 and SPP1 were associated with the OS. However, MMP9 and COL1A1 did not have any significant effect on OS. In summary, the identification of CAV1, MMP9, SPP1 and COL1A1 may provide novel insights into the molecular mechanism of lung adenocarcinoma in non-smoking female patients, and the results obtained in the current study may guide future clinical studies.", "claims": [{"id": "claim-method", "statement": "The log rank test was used to compare the survival trend.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31611968", "locator": "sections[9] \"Statistical analysis\" paragraph 2", "quote": "The log rank test was used to compare the survival trend."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed in the present study are available from the GEO repository at (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse32863) and (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse75037), and TCGA repository at (https://portal.gdc.cancer.gov/repository).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31611968", "locator": "sections[19] \"Availability of data and materials\" paragraph 2", "quote": "The datasets analyzed in the present study are available from the GEO repository at (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse32863) and (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse75037), and TCGA repository at (https://portal.gdc.cancer.gov/repository)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:31611968"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE32863"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE32863"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:31611968", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3892/ol.2019.10845", "sha256": 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