This particular study utilizes the gene expression omnibus dataset (GEO) for the identification of novel molecular markers for LUAD. In total there are four gene expression profiles namely GSE19188, GSE18842, GSE31210 and GSE19804 were identified using GEO from 423 samples of cancerous tissuess and 190 non-cancerous samples (controls). Out of these profiles that were identified, we were able to further identify the precise genes which had been differentially expressed termed as Differentially expressed genes (DEGs) by employing web tools such as GEO2R and Venn diagrams. There were 851 DEGs identified which comprised of 240 over-expressed genes and 611 under-expressed genes. A protein-protein interaction (PPI) analysis through Cytoscape and the Cytohubba software was carried out to explain the role of these genes in the aetiology of the LUAD. This approach enabled the identification of densely interconnected gene clusters that hold potential significance for accurate prognostication of LUAD. Additional procedures including Gene ontology enrichment (GO) along with Kyoto encyclopaedia of genes and genomes (KEGG) analysis were utilized in the current study for precise study of various mechanisms of cell cycle modulation and apoptosis that are essential hallmarks for the pathogenesis of LUAD. Furthermore, the credibility of our findings was strengthened by the results obtained by UALCAN as well as HPA databases to understand hub gene expression along with its association with overall survival. Collectively, our comprehension of the molecular mechanisms is improved by identifying the DEGs (CDK1, CCNB2, CDC20, BUBIB, CCNA2, DLGAP5, ASPM, ARRB1, CAV1) and their probable role as biomarkers in the pathology of LUAD and further investigations into this concept may open up newer avenues for accurate treatment towards LUAD thereby ensuring successful therapeutic outcomes.