Identifying key genes associated with recurrence in non-small cell lung cancer through TCGA and single-cell analysis.

ABSTRACT:

Objective

This study aims to mine the TCGA database for differentially expressed genes in recurrent lung cancer tissues, determine the relationship between these recurrent genes and lung cancer at the single-cell level, and identify potential targets for lung cancer treatment.

Methods

Data for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) were obtained from the TCGA database and grouped based on clinical recurrence information. Single-cell data from GSE131907 were downloaded from the GEO database. R was utilized to screen for differentially expressed genes (DEGs), followed by weighted gene co-expression network analysis (WGCNA) of these DEGs. Additionally, the GSEA database was employed to visualize differential pathways and identify key genes. The relat

SUBMITTER: Li W 

PROVIDER: S-EPMC12187672 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature