OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma

OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma

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 ex...

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Main Authors: Qiang Wang, Zhongyi Yan, Linna Ge, Ning Li, Mengsi Yang, Xiaoxiao Sun, Longxiang Xie, Guosen Zhang, Wan Zhu, Yunlong Wang, Yongqiang Li, Xianzhe Li, Xiangqian Guo
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-03-01
Series:Frontiers in Oncology
Subjects:
EAC
prognostic
survival analysis
biomarker
web server
Online Access:https://www.frontiersin.org/article/10.3389/fonc.2020.00315/full
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record_format Article
collection DOAJ
language English
format Article
sources DOAJ
author Qiang Wang
Zhongyi Yan
Linna Ge
Ning Li
Mengsi Yang
Xiaoxiao Sun
Longxiang Xie
Guosen Zhang
Wan Zhu
Yunlong Wang
Yongqiang Li
Xianzhe Li
Xiangqian Guo
spellingShingle Qiang Wang
Zhongyi Yan
Linna Ge
Ning Li
Mengsi Yang
Xiaoxiao Sun
Longxiang Xie
Guosen Zhang
Wan Zhu
Yunlong Wang
Yongqiang Li
Xianzhe Li
Xiangqian Guo
OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma
Frontiers in Oncology
EAC
prognostic
survival analysis
biomarker
web server
author_facet Qiang Wang
Zhongyi Yan
Linna Ge
Ning Li
Mengsi Yang
Xiaoxiao Sun
Longxiang Xie
Guosen Zhang
Wan Zhu
Yunlong Wang
Yongqiang Li
Xianzhe Li
Xiangqian Guo
author_sort Qiang Wang
title OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma
title_short OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma
title_full OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma
title_fullStr OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma
title_full_unstemmed OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma
title_sort oseac: an online survival analysis tool for esophageal adenocarcinoma
publisher Frontiers Media S.A.
series Frontiers in Oncology
issn 2234-943X
publishDate 2020-03-01
description 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.
topic EAC
prognostic
survival analysis
biomarker
web server
url https://www.frontiersin.org/article/10.3389/fonc.2020.00315/full
work_keys_str_mv AT qiangwang oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT zhongyiyan oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT linnage oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT ningli oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT mengsiyang oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT xiaoxiaosun oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT longxiangxie oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT guosenzhang oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT wanzhu oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT yunlongwang oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT yongqiangli oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT xianzheli oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
AT xiangqianguo oseacanonlinesurvivalanalysistoolforesophagealadenocarcinoma
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spelling doaj-b42a300dd5bb4b3e83abcd3c9bbc772e2020-11-25T01:23:41ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2020-03-011010.3389/fonc.2020.00315490584OSeac: An Online Survival Analysis Tool for Esophageal AdenocarcinomaQiang Wang0Zhongyi Yan1Linna Ge2Ning Li3Mengsi Yang4Xiaoxiao Sun5Longxiang Xie6Guosen Zhang7Wan Zhu8Yunlong Wang9Yongqiang Li10Xianzhe Li11Xiangqian Guo12Cell 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, ChinaCell 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, ChinaCell 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, ChinaCell 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, ChinaCell 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, ChinaCell 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, ChinaCell 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, ChinaCell 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, ChinaDepartment of Anesthesia, Stanford University, Stanford, CA, United StatesHenan Bioengineering Research Center, Zhengzhou, ChinaCell 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, ChinaDepartment of Thoracic Surgery, The Affiliated Nanshi Hospital of Henan University, Nanyang, ChinaCell 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, ChinaEsophageal 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.https://www.frontiersin.org/article/10.3389/fonc.2020.00315/fullEACprognosticsurvival analysisbiomarkerweb server

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