{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Cai K"],"funding":["Basic and Applied Basic Research Foundation of Guangdong Province","National College Students Innovation and Entrepreneurship Training Program"],"pagination":["2152432"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9876670"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["2023"],"pubmed_abstract":["Objective
To analyze and identify the core genes related to the expression and prognosis of lung cancer including lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) by bioinformatics technology, with the aim of providing a reference for clinical treatment.Methods
Five sets of gene chips, GSE7670, GSE151102, GSE33532, GSE43458, and GSE19804, were obtained from the Gene Expression Omnibus (GEO) database. After using GEO2R to analyze the differentially expressed genes (DEGs) between lung cancer and normal tissues online, the common DEGs of the five sets of chips were obtained using a Venn online tool and imported into the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database for Gene Ontology (GO) enrichment and Kyoto Encyclopedia of"],"journal":["BioMed research international"],"pubmed_title":["Identification of Potential Key Genes and Prognostic Biomarkers of Lung Cancer Based on Bioinformatics."],"pmcid":["PMC9876670"],"funding_grant_id":["202110571011","2022A1515012190","202210571036","2021B1515140067","202110571008"],"pubmed_authors":["Xiong Y","Liu Y","Wu J","Gan S","Xie Z","Cai K","Wang X","Song H","Sun Y","Liu W"],"additional_accession":[]},"is_claimable":false,"name":"Identification of Potential Key Genes and Prognostic Biomarkers of Lung Cancer Based on Bioinformatics.","description":"Objective
To analyze and identify the core genes related to the expression and prognosis of lung cancer including lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) by bioinformatics technology, with the aim of providing a reference for clinical treatment.Methods
Five sets of gene chips, GSE7670, GSE151102, GSE33532, GSE43458, and GSE19804, were obtained from the Gene Expression Omnibus (GEO) database. After using GEO2R to analyze the differentially expressed genes (DEGs) between lung cancer and normal tissues online, the common DEGs of the five sets of chips were obtained using a Venn online tool and imported into the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database for Gene Ontology (GO) enrichment and Kyoto Encyclopedia of","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023","modification":"2026-07-15T22:32:24.141Z","creation":"2025-04-07T03:18:28.304Z"},"accession":"S-EPMC9876670","cross_references":{"pubmed":["36714024"],"doi":["10.1155/2023/2152432"]}}