Lung adenocarcinoma (LUAD) is one of the most malignant tumor types worldwide. Our objective was to identify a genetic signature that could predict the prognosis of patients with LUAD. We extracted gene data sets from The Cancer Genome Atlas and obtained differentially expressed genes that were highly expressed at every stage. These genes were analyzed using gene set enrichment analysis to obtain four biological processes associated with LUAD. Subsequently, Cox univariate and multivariate analyses were performed to generate four optimized models (G2M checkpoint, E2F targets, mitotic spindle, and glycolysis). We identified a mitotic spindle-related signature (KIF15, BUB1, CCNB2, CDK1, KIF4A, DLGAP5, ECT2, and ANLN), which could be an independent prognostic indicator, to predict the prognosis of patients with LUAD. This new discovery should offer opportunities to explore the pathogenesis of LUAD and prove clinically useful in predicting LUAD patient prognosis.
Keywords: Cox univariate and multivariate analysis; biomarker; gene set enrichment analysis (GSEA); lung adenocarcinoma (LUAD); mitotic spindle.
© 2019 Wiley Periodicals, Inc.