Wei Chen1, Lianming Liao2, Haichun Lai1, Xuehan Yi1, Desheng Wang3. 1. Department of Otolaryngology, Fujian Medical University Union Hospital, 29# Xinquan Road, Fujian, 350001, Fuzhou, China. 2. Department of Laboratory Medicine, Fujian Medical University Union Hospital, Fujian, 350001, Fuzhou, China. 3. Department of Otolaryngology, Fujian Medical University Union Hospital, 29# Xinquan Road, Fujian, 350001, Fuzhou, China. wangds@fjmu.edu.cn.
Abstract
PURPOSE: Despite advances in the treatment of laryngeal squamous-cell carcinoma (LSCC), the survival rate of LSCC remains poor. Thereby, it is urgent to identify novel diagnostic and prognostic biomarkers for LSCC. The study aimed to identify potential core genes associated with the pathogenesis and prognosis of LSCC. METHODS: Differentially expressed genes between LSCC and normal laryngeal tissue samples were screened by an integrated analysis of data from GEO and TCGA databases. Core genes related to the pathogenesis and prognosis of LSCC were identified by employing protein-protein interaction network and Cox proportional hazards model analyses. RESULTS: Ten hub genes (AURKA, AURKB, CDC45, KIF2C, NDC80, EXO1, TYMS, RAD51AP1, ITGA3, and UBE2T) that might be highly related to the pathogenesis of LSCC were identified. An eight-gene prognostic signature consisted of ZG16B, STATH, RTN4R, MSRA, CBX8, SLC5A1, EFNB1 and CNTFR was constructed with a good performance in predicting overall survivals. CONCLUSION: Our findings might shed some new light on the pathogenesis of LSCC and help identify new therapeutic targets of LSCC.
PURPOSE: Despite advances in the treatment of laryngeal squamous-cell carcinoma (LSCC), the survival rate of LSCC remains poor. Thereby, it is urgent to identify novel diagnostic and prognostic biomarkers for LSCC. The study aimed to identify potential core genes associated with the pathogenesis and prognosis of LSCC. METHODS: Differentially expressed genes between LSCC and normal laryngeal tissue samples were screened by an integrated analysis of data from GEO and TCGA databases. Core genes related to the pathogenesis and prognosis of LSCC were identified by employing protein-protein interaction network and Cox proportional hazards model analyses. RESULTS: Ten hub genes (AURKA, AURKB, CDC45, KIF2C, NDC80, EXO1, TYMS, RAD51AP1, ITGA3, and UBE2T) that might be highly related to the pathogenesis of LSCC were identified. An eight-gene prognostic signature consisted of ZG16B, STATH, RTN4R, MSRA, CBX8, SLC5A1, EFNB1 and CNTFR was constructed with a good performance in predicting overall survivals. CONCLUSION: Our findings might shed some new light on the pathogenesis of LSCC and help identify new therapeutic targets of LSCC.
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