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OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma.

作者信息

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

机构信息

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.

出版信息

Front Oncol. 2020 Mar 6;10:315. doi: 10.3389/fonc.2020.00315. eCollection 2020.

DOI:10.3389/fonc.2020.00315
PMID:32211334
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7067743/
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 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.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70d3/7067743/3b9da8763df6/fonc-10-00315-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70d3/7067743/a7f19db153d8/fonc-10-00315-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70d3/7067743/3b9da8763df6/fonc-10-00315-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70d3/7067743/a7f19db153d8/fonc-10-00315-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/70d3/7067743/3b9da8763df6/fonc-10-00315-g0002.jpg

相似文献

[1]
OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma.

Front Oncol. 2020-3-6

[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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引用本文的文献

[1]
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Sci Rep. 2024-9-4

[2]
Nomograms for prognosis prediction in esophageal adenocarcinoma: realities and challenges.

Clin Transl Oncol. 2025-2

[3]
Identification of key genes associated with esophageal adenocarcinoma based on bioinformatics analysis.

Ann Transl Med. 2021-12

[4]
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Int J Biol Sci. 2020-9-30

[5]
ECCDIA: an interactive web tool for the comprehensive analysis of clinical and survival data of esophageal cancer patients.

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[6]
Integrated PPI- and WGCNA-Retrieval of Hub Gene Signatures Shared Between Barrett's Esophagus and Esophageal Adenocarcinoma.

Front Pharmacol. 2020-7-31

本文引用的文献

[1]
Interactive online consensus survival tool for esophageal squamous cell carcinoma prognosis analysis.

Oncol Lett. 2019-8

[2]
OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer Patients.

Front Oncol. 2019-6-4

[3]
OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma.

Front Oncol. 2019-3-29

[4]
An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics.

Cell. 2018-4-5

[5]
The clinical significance of cysteine dioxygenase type 1 methylation in Barrett esophagus adenocarcinoma.

Dis Esophagus. 2017-3-1

[6]
Integrated genomic characterization of oesophageal carcinoma.

Nature. 2017-1-12

[7]
Mutational signatures in esophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance.

Nat Genet. 2016-10

[8]
Expression of RAP1B is associated with poor prognosis and promotes an aggressive phenotype in gastric cancer.

Oncol Rep. 2015-11

[9]
The role of Dickkopf-3 overexpression in esophageal adenocarcinoma.

J Thorac Cardiovasc Surg. 2015-8

[10]
Global cancer statistics, 2012.

CA Cancer J Clin. 2015-2-4

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