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OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts
Potential prognostic mRNA biomarkers are exploited to assist in the clinical management and treatment of breast cancer, which is the first life-threatening tumor in women worldwide. However, it is technically challenging for untrained researchers to process high dimensional profiling data to screen...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6932997/ https://www.ncbi.nlm.nih.gov/pubmed/31921624 http://dx.doi.org/10.3389/fonc.2019.01349 |
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author | Yan, Zhongyi Wang, Qiang Sun, Xiaoxiao Ban, Bingbing Lu, Zhendong Dang, Yifang Xie, Longxiang Zhang, Lu Li, Yongqiang Zhu, Wan Guo, Xiangqian |
author_facet | Yan, Zhongyi Wang, Qiang Sun, Xiaoxiao Ban, Bingbing Lu, Zhendong Dang, Yifang Xie, Longxiang Zhang, Lu Li, Yongqiang Zhu, Wan Guo, Xiangqian |
author_sort | Yan, Zhongyi |
collection | PubMed |
description | Potential prognostic mRNA biomarkers are exploited to assist in the clinical management and treatment of breast cancer, which is the first life-threatening tumor in women worldwide. However, it is technically challenging for untrained researchers to process high dimensional profiling data to screen and validate the potential prognostic values of genes of interests in multiple cohorts. Our aim is to develop an easy-to-use web server to facilitate the screening, developing, and evaluating of prognostic biomarkers in breast cancers. Herein, we collected more than 7,400 cases of breast cancer with gene expression profiles and clinical follow-up information from The Cancer Genome Atlas and Gene Expression Omnibus data, and built an Online consensus Survival analysis web server for Breast Cancers, abbreviated OSbrca, to generate the Kaplan–Meier survival plot with a hazard ratio and log rank P-value for given genes in an interactive way. To examine the performance of OSbrca, the prognostic potency of 128 previously published biomarkers of breast cancer was reassessed in OSbrca. In conclusion, it is highly valuable for biologists and clinicians to perform the preliminary assessment and validation of novel or putative prognostic biomarkers for breast cancers. OSbrca could be accessed at http://bioinfo.henu.edu.cn/BRCA/BRCAList.jsp. |
format | Online Article Text |
id | pubmed-6932997 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-69329972020-01-09 OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts Yan, Zhongyi Wang, Qiang Sun, Xiaoxiao Ban, Bingbing Lu, Zhendong Dang, Yifang Xie, Longxiang Zhang, Lu Li, Yongqiang Zhu, Wan Guo, Xiangqian Front Oncol Oncology Potential prognostic mRNA biomarkers are exploited to assist in the clinical management and treatment of breast cancer, which is the first life-threatening tumor in women worldwide. However, it is technically challenging for untrained researchers to process high dimensional profiling data to screen and validate the potential prognostic values of genes of interests in multiple cohorts. Our aim is to develop an easy-to-use web server to facilitate the screening, developing, and evaluating of prognostic biomarkers in breast cancers. Herein, we collected more than 7,400 cases of breast cancer with gene expression profiles and clinical follow-up information from The Cancer Genome Atlas and Gene Expression Omnibus data, and built an Online consensus Survival analysis web server for Breast Cancers, abbreviated OSbrca, to generate the Kaplan–Meier survival plot with a hazard ratio and log rank P-value for given genes in an interactive way. To examine the performance of OSbrca, the prognostic potency of 128 previously published biomarkers of breast cancer was reassessed in OSbrca. In conclusion, it is highly valuable for biologists and clinicians to perform the preliminary assessment and validation of novel or putative prognostic biomarkers for breast cancers. OSbrca could be accessed at http://bioinfo.henu.edu.cn/BRCA/BRCAList.jsp. Frontiers Media S.A. 2019-12-20 /pmc/articles/PMC6932997/ /pubmed/31921624 http://dx.doi.org/10.3389/fonc.2019.01349 Text en Copyright © 2019 Yan, Wang, Sun, Ban, Lu, Dang, Xie, Zhang, Li, Zhu and Guo. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Yan, Zhongyi Wang, Qiang Sun, Xiaoxiao Ban, Bingbing Lu, Zhendong Dang, Yifang Xie, Longxiang Zhang, Lu Li, Yongqiang Zhu, Wan Guo, Xiangqian OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts |
title | OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts |
title_full | OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts |
title_fullStr | OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts |
title_full_unstemmed | OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts |
title_short | OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts |
title_sort | osbrca: a web server for breast cancer prognostic biomarker investigation with massive data from tens of cohorts |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6932997/ https://www.ncbi.nlm.nih.gov/pubmed/31921624 http://dx.doi.org/10.3389/fonc.2019.01349 |
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