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OSlihc: An Online Prognostic Biomarker Analysis Tool for Hepatocellular Carcinoma

Liver hepatocellular carcinoma (LIHC) is one of the most common malignant tumors in the world with an increasing number of fatalities. Identification of novel prognosis biomarker for LIHC may improve treatment and therefore patient outcomes. The availability of public gene expression profiling data...

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Autores principales: An, Yang, Wang, Qiang, Zhang, Guosen, Sun, Fengjie, Zhang, Lu, Li, Haojie, Li, Yingkun, Peng, Yanyu, Zhu, Wan, Ji, Shaoping, Guo, Xiangqian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298068/
https://www.ncbi.nlm.nih.gov/pubmed/32587519
http://dx.doi.org/10.3389/fphar.2020.00875
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author An, Yang
Wang, Qiang
Zhang, Guosen
Sun, Fengjie
Zhang, Lu
Li, Haojie
Li, Yingkun
Peng, Yanyu
Zhu, Wan
Ji, Shaoping
Guo, Xiangqian
author_facet An, Yang
Wang, Qiang
Zhang, Guosen
Sun, Fengjie
Zhang, Lu
Li, Haojie
Li, Yingkun
Peng, Yanyu
Zhu, Wan
Ji, Shaoping
Guo, Xiangqian
author_sort An, Yang
collection PubMed
description Liver hepatocellular carcinoma (LIHC) is one of the most common malignant tumors in the world with an increasing number of fatalities. Identification of novel prognosis biomarker for LIHC may improve treatment and therefore patient outcomes. The availability of public gene expression profiling data offers the opportunity to discover prognosis biomarkers for LIHC. We developed an online consensus survival analysis tool named OSlihc using gene expression profiling and long-term follow-up data to identify new prognosis biomarkers. OSlihc consists of 637 cases from four independent cohorts. As a risk assessment tool, OSlihc generates the Kaplan–Meier survival plot with hazard ratio (HR) and p value to evaluate the prognostic value of a gene of interest. To test the reliability of OSlihc, we analyzed 65 previous reported prognostic biomarkers in OSlihc and showed that all of which have significant prognostic values. Furthermore, we identified four novel potential prognostic biomarkers (ATG9A, WIPI1, CXCL1, and CSNK2A2) for LIHC, the elevated expression of which predict the unfavorable survival outcomes. These genes (ATG9A, WIPI1, CXCL1, and CSNK2A2) may be potentially new biomarkers to identify at-risk LIHC patients when further validated. By OSlihc, users can evaluate the prognostic abilities of genes of their interest, which provides a platform for researchers to identify prognostic biomarkers to further develop targeted therapy strategies for LIHC patients. OSlihc is public and free to the users at http://bioinfo.henu.edu.cn/LIHC/LIHCList.jsp.
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spelling pubmed-72980682020-06-24 OSlihc: An Online Prognostic Biomarker Analysis Tool for Hepatocellular Carcinoma An, Yang Wang, Qiang Zhang, Guosen Sun, Fengjie Zhang, Lu Li, Haojie Li, Yingkun Peng, Yanyu Zhu, Wan Ji, Shaoping Guo, Xiangqian Front Pharmacol Pharmacology Liver hepatocellular carcinoma (LIHC) is one of the most common malignant tumors in the world with an increasing number of fatalities. Identification of novel prognosis biomarker for LIHC may improve treatment and therefore patient outcomes. The availability of public gene expression profiling data offers the opportunity to discover prognosis biomarkers for LIHC. We developed an online consensus survival analysis tool named OSlihc using gene expression profiling and long-term follow-up data to identify new prognosis biomarkers. OSlihc consists of 637 cases from four independent cohorts. As a risk assessment tool, OSlihc generates the Kaplan–Meier survival plot with hazard ratio (HR) and p value to evaluate the prognostic value of a gene of interest. To test the reliability of OSlihc, we analyzed 65 previous reported prognostic biomarkers in OSlihc and showed that all of which have significant prognostic values. Furthermore, we identified four novel potential prognostic biomarkers (ATG9A, WIPI1, CXCL1, and CSNK2A2) for LIHC, the elevated expression of which predict the unfavorable survival outcomes. These genes (ATG9A, WIPI1, CXCL1, and CSNK2A2) may be potentially new biomarkers to identify at-risk LIHC patients when further validated. By OSlihc, users can evaluate the prognostic abilities of genes of their interest, which provides a platform for researchers to identify prognostic biomarkers to further develop targeted therapy strategies for LIHC patients. OSlihc is public and free to the users at http://bioinfo.henu.edu.cn/LIHC/LIHCList.jsp. Frontiers Media S.A. 2020-06-10 /pmc/articles/PMC7298068/ /pubmed/32587519 http://dx.doi.org/10.3389/fphar.2020.00875 Text en Copyright © 2020 An, Wang, Zhang, Sun, Zhang, Li, Li, Peng, Zhu, Ji 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 Pharmacology
An, Yang
Wang, Qiang
Zhang, Guosen
Sun, Fengjie
Zhang, Lu
Li, Haojie
Li, Yingkun
Peng, Yanyu
Zhu, Wan
Ji, Shaoping
Guo, Xiangqian
OSlihc: An Online Prognostic Biomarker Analysis Tool for Hepatocellular Carcinoma
title OSlihc: An Online Prognostic Biomarker Analysis Tool for Hepatocellular Carcinoma
title_full OSlihc: An Online Prognostic Biomarker Analysis Tool for Hepatocellular Carcinoma
title_fullStr OSlihc: An Online Prognostic Biomarker Analysis Tool for Hepatocellular Carcinoma
title_full_unstemmed OSlihc: An Online Prognostic Biomarker Analysis Tool for Hepatocellular Carcinoma
title_short OSlihc: An Online Prognostic Biomarker Analysis Tool for Hepatocellular Carcinoma
title_sort oslihc: an online prognostic biomarker analysis tool for hepatocellular carcinoma
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298068/
https://www.ncbi.nlm.nih.gov/pubmed/32587519
http://dx.doi.org/10.3389/fphar.2020.00875
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