Identification and analysis of genes associated with lung adenocarcinoma by integrated bioinformatics methods.

Lung adenocarcinoma (LUAD) is one of the most common forms of lung cancer, with a very high mortality rate. Although the treatments available for LUAD have become more effective in recent years, significant improvement is still needed. Advances in sequencing technologies and bioinformatics analysis have enabled new approaches to be developed for identifying drug targets. In this work we utilized data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify hub genes related to LUAD through Weighted Gene Correlation Network Analysis (WGCNA) and other bioinformatics methods, with the goal of identifying new drug targets for cancer treatment.