{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["104(46)"],"submitter":["Ma Y"],"pubmed_abstract":["Lung adenocarcinoma (LUAD), a common type of non-small cell lung cancer, is associated with low survival rates and challenges in early detection. Therefore, identifying prognostic biomarkers is crucial for improving patient outcomes. This study utilized 2 datasets - the Cancer Genome Atlas-Lung Adenocarcinoma (TCGA-LUAD) and GSE72094 - along with 182 immune escape-related genes and 597 cancer-associated fibroblast-related genes. Weighted gene co-expression network analysis was used to identify module genes. Differential expression analysis of TCGA-LUAD data revealed LUAD-associated differentially expressed genes, which were then intersected with module genes to identify LUAD-specific differentially expressed immune escape-cancer fibroblast-related genes. To identify potential biomarkers an"],"journal":["Medicine"],"pagination":["e45756"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12622665"],"repository":["biostudies-literature"],"pubmed_title":["Identification and validation of a diagnostic and prognostic model based on immune escape and cancer-associated fibroblast-related genes in lung adenocarcinoma."],"pmcid":["PMC12622665"],"pubmed_authors":["Li X","Geng R","Song B","Ma Y","Wang X","Hao Y","Su W"],"additional_accession":[]},"is_claimable":false,"name":"Identification and validation of a diagnostic and prognostic model based on immune escape and cancer-associated fibroblast-related genes in lung adenocarcinoma.","description":"Lung adenocarcinoma (LUAD), a common type of non-small cell lung cancer, is associated with low survival rates and challenges in early detection. Therefore, identifying prognostic biomarkers is crucial for improving patient outcomes. This study utilized 2 datasets - the Cancer Genome Atlas-Lung Adenocarcinoma (TCGA-LUAD) and GSE72094 - along with 182 immune escape-related genes and 597 cancer-associated fibroblast-related genes. Weighted gene co-expression network analysis was used to identify module genes. Differential expression analysis of TCGA-LUAD data revealed LUAD-associated differentially expressed genes, which were then intersected with module genes to identify LUAD-specific differentially expressed immune escape-cancer fibroblast-related genes. To identify potential biomarkers an","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Nov","modification":"2026-06-05T16:36:15.585Z","creation":"2026-05-18T03:13:18.699Z"},"accession":"S-EPMC12622665","cross_references":{"pubmed":["41239716"],"doi":["10.1097/MD.0000000000045756"]}}