Identification and validation of a diagnostic and prognostic model based on immune escape and cancer-associated fibroblast-related genes in lung adenocarcinoma.

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

SUBMITTER: Ma Y 

PROVIDER: S-EPMC12622665 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature