<p>One of the most prevalent cancers and the primary cause of cancer- related mortality worldwide is lung cancer. Nevertheless, the genomic profile of lung cancer metastases is frequently inadequately understood. This study employs an integrative analysis of multiple data sources to investigate the molecular landscape of advanced-stage non-small cell lung cancer, with a particular emphasis on adenocarcinoma. For analysis, four microarray datasets were chosen from the the Gene Expression Omnibus database. TAC and R tools were used to identify genes that were differentially expressed. Hub genes were then found using Cytoscape and the STRING database. The networks of protein-protein interactions (PPI) involving these hub genes were then visualized using Gephi software. The Enrichr database in the KEGG pathway was used to perform gene enrichment analysis. Furthermore, Gene Expression Profiling Interactive Analysis (GEPIA) was used to validate the hub genes’ expression levels and prognostic data. Common genes across these datasets were identified. Fourteen genes were discovered to be shared by all of the microarray datasets that were examined. Additionally, these genes were shared by 15 biological pathways in the datasets. Important pathways including p53 signaling pathway, Pyrimidine metabolism, Glutathione metabolism, PI3K-Akt signaling pathway were discovered via the re-enrichment of these ubiquitous genes. These first bioinformatics findings may guide future research and perhaps aid in the creation of focused diagnostics and medicines, subject to comprehensive validation via laboratory tests and clinical trials.</p>