Identification of a panel of mitotic spindle-related genes as a signature predicting survival in lung adenocarcinoma |
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| Authors: | Liwen Zhang Miao He Wenjing Zhu Xuemei Lv Yanyun Zhao Yuanyuan Yan Xueping Li Longyang Jiang Lin Zhao Yue Fan Panpan Su Mengcong Gao Heyao Ma Kai Li Minjie Wei |
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| Affiliation: | 1. Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, Liaoning, China;2. Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, Liaoning, China Liaoning Engineering Technology Research Center for the Research, Development and Industrialization of Innovative Peptide Drugs, China Medical University, Shenyang, Liaoning, China;3. Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China |
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| Abstract: | 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. |
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| Keywords: | biomarker Cox univariate and multivariate analysis gene set enrichment analysis (GSEA) lung adenocarcinoma (LUAD) mitotic spindle |
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