Sixuan Li1,2, Zhigang Cui1, Yuxin Zhao1, Shuwen Ma1, Yinghui Sun1, Hang Li1,2, Min Gao1,2, Na Li1,2, Ying Wang1,2, Lianwei Tong1,2, Mingyang Song1,2, Zhihua Yin3,4,5. 1. China Medical University, Shenyang, 110122, China. 2. Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China. 3. China Medical University, Shenyang, 110122, China. zhyin@cmu.edu.cn. 4. Department of Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, China. zhyin@cmu.edu.cn. 5. Key Laboratory of Cancer Etiology and Intervention, University of Liaoning Province, No.77 Puhe Road, Shenyang North New Area, Shenyang, 110122, China. zhyin@cmu.edu.cn.
Abstract
PURPOSE: The role of non-coding RNA, once thought to be dark matter, is increasingly prominent in cancer. Our article explores the effect of non-coding RNA in lung adenocarcinoma and lung squamous cell carcinoma by mining TCGA public database. METHODS: Download the data by applying the official TCGA software. The data were analyzed by R data analysis packages, 'edgeR', 'gplots' and 'survival'. We better illustrate the potential networks of lung cancer genes by constructing ceRNAs, using Cytoscape software. RESULTS: We obtained genes which were differentially expressed in lung adenocarcinoma and lung squamous cell carcinoma analysis. Within these differentially expressed genes, we also conducted a survival analysis to find differentially expressed genes associated with prognosis in both lung adenocarcinoma and lung squamous cell carcinoma. Based on genes differentially expressed of both lung adenocarcinoma and lung squamous cell carcinoma, we constructed a ceRNA network to illustrate the mechanism of lung adenocarcinoma and lung squamous cell carcinoma. Our study analyzed genes which were differentially expressed in lung adenocarcinoma and lung squamous cell carcinoma using the TCGA database. CONCLUSION: Based on this, the prognosis in both lung squamous cell carcinoma and lung adenocarcinoma was analyzed. We have also constructed a ceRNA network to provide a basis for the study of ceRNA in lung adenocarcinoma and lung squamous cell carcinoma.
PURPOSE: The role of non-coding RNA, once thought to be dark matter, is increasingly prominent in cancer. Our article explores the effect of non-coding RNA in lung adenocarcinoma and lung squamous cell carcinoma by mining TCGA public database. METHODS: Download the data by applying the official TCGA software. The data were analyzed by R data analysis packages, 'edgeR', 'gplots' and 'survival'. We better illustrate the potential networks of lung cancer genes by constructing ceRNAs, using Cytoscape software. RESULTS: We obtained genes which were differentially expressed in lung adenocarcinoma and lung squamous cell carcinoma analysis. Within these differentially expressed genes, we also conducted a survival analysis to find differentially expressed genes associated with prognosis in both lung adenocarcinoma and lung squamous cell carcinoma. Based on genes differentially expressed of both lung adenocarcinoma and lung squamous cell carcinoma, we constructed a ceRNA network to illustrate the mechanism of lung adenocarcinoma and lung squamous cell carcinoma. Our study analyzed genes which were differentially expressed in lung adenocarcinoma and lung squamous cell carcinoma using the TCGA database. CONCLUSION: Based on this, the prognosis in both lung squamous cell carcinoma and lung adenocarcinoma was analyzed. We have also constructed a ceRNA network to provide a basis for the study of ceRNA in lung adenocarcinoma and lung squamous cell carcinoma.