Wang Qiang, Yan Zhongyi, Ge Linna, Li Ning, Yang Mengsi, Sun Xiaoxiao, Xie Longxiang, Zhang Guosen, Zhu Wan, Wang Yunlong, Li Yongqiang, Li Xianzhe, Guo Xiangqian
Cell Signal Transduction Laboratory, Bioinformatics Department of Predictive Medicine, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Institute of Biomedical Informatics, Henan University, Kaifeng, China.
Department of Anesthesia, Stanford University, Stanford, CA, United States.
Front Oncol. 2020 Mar 6;10:315. doi: 10.3389/fonc.2020.00315. eCollection 2020.
Esophageal Adenocarcinoma (EAC) is one of the most common gastrointestinal tumors in the world. However, molecular prognostic systems are still lacking for EAC. Hence, we developed an nline consensus urvival analysis web server for sophageal denoarcinoma (OSeac), to centralize published gene expression data and clinical follow up data of EAC patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). OSeac includes 198 EAC cases with gene expression profiling and relevant clinical long-term follow-up data, and employs the Kaplan Meier (KM) survival plot with hazard ratio (HR) and log rank test to estimate the prognostic potency of genes of interests for EAC patients. Moreover, we have determined the reliability of OSeac by using previously reported prognostic biomarkers such as , and . OSeac is free and publicly accessible at http://bioinfo.henu.edu.cn/EAC/EACList.jsp.
食管腺癌（EAC）是世界上最常见的胃肠道肿瘤之一。然而，EAC仍然缺乏分子预后系统。因此，我们开发了一个用于食管腺癌的在线共识生存分析网络服务器（OSeac），以集中来自癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）的已发表的EAC患者基因表达数据和临床随访数据。OSeac包括198例具有基因表达谱和相关临床长期随访数据的EAC病例，并采用带有风险比（HR）的Kaplan-Meier（KM）生存曲线和对数秩检验来评估感兴趣基因对EAC患者的预后效力。此外，我们通过使用先前报道的预后生物标志物（如 、 和 ）来确定OSeac的可靠性。OSeac可在http://bioinfo.henu.edu.cn/EAC/EACList.jsp免费公开访问。
