Zhang MY, et al. - Researchers studied differentially expressed genes (DEGs) using Gene Expression Omnibus (GEO) 2R software to identify the gene signature linked to forecasting of smoking-related lung adenocarcinoma. They verified the overall survival (OS) and recurrence-free survival (RFS) by using an independent cohort from the Cancer Genome Atlas (TCGA) database. They recognized 58 DEGs which mainly enriched in ECM-receptor interaction, platelet activation, and PPAR signaling pathway and 3 genes, AURKA, CDC20 and TPX2 were found with some role in governing tumor cell cycle and cell division. They observed no link between these genes and recurrence-free survival (RFS) suggesting many agents might influence RFS. mRNA signature of these genes was recognized as a potential biomarker for predicting poor prognosis of smoking-related lung adenocarcinoma.