Abstract
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 Online consensus Survival analysis web server for Esophageal Adenocarcinoma (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 DKK3, CTO1, and TXNIP. OSeac is free and publicly accessible at http://bioinfo.henu.edu.cn/EAC/EACList.jsp.
Highlights
Esophageal cancer is a common malignant tumor of digestive tract
As most researchers may concern the accuracy rate and potential error from OSeac, for example, we performed the prognosis analysis for one gene each time in OSeac, the gene will be regarded significant for prognosis when P-value is
The Esophageal Adenocarcinoma (EAC) expression datasets may come from different analyzing platforms/technologies, or from different ethnicities, all these may influence the results of prognosis analysis
Summary
Esophageal cancer is a common malignant tumor of digestive tract. The incidence of esophageal cancer is eighth in all tumors and sixth in fatal cancer [1]. EAC is one of the most common histological types of esophageal cancer [2, 3] and has increased markedly in Western countries in recent decades [4, 5]. Esophagectomy with the addition of perioperative chemotherapy or chemoradiotherapy had improved prognosis of EAC [6,7,8], not all EAC patients got cured. The use of molecularly targeted agents are not satisfied so far for EAC and it has lagged behind other cancers [9]. It is necessary to identify new predictive and prognostic biomarkers for EAC patients to improve clinical outcome
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