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OSskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles
BACKGROUND: Cutaneous melanoma is one of the most aggressive and lethal skin cancers. It is greatly important to identify prognostic biomarkers to guide the clinical management. However, it is technically challenging for untrained researchers to process high dimensional profiling data and identify p...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236197/ https://www.ncbi.nlm.nih.gov/pubmed/32467670 http://dx.doi.org/10.1186/s12935-020-01262-3 |
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author | Zhang, Lu Wang, Qiang Wang, Lijie Xie, Longxiang An, Yang Zhang, Guosen Zhu, Wan Li, Yongqiang Liu, Zhihui Zhang, Xiaochen Tang, Panpan Huo, Xiaozheng Guo, Xiangqian |
author_facet | Zhang, Lu Wang, Qiang Wang, Lijie Xie, Longxiang An, Yang Zhang, Guosen Zhu, Wan Li, Yongqiang Liu, Zhihui Zhang, Xiaochen Tang, Panpan Huo, Xiaozheng Guo, Xiangqian |
author_sort | Zhang, Lu |
collection | PubMed |
description | BACKGROUND: Cutaneous melanoma is one of the most aggressive and lethal skin cancers. It is greatly important to identify prognostic biomarkers to guide the clinical management. However, it is technically challenging for untrained researchers to process high dimensional profiling data and identify potential prognostic genes in profiling datasets. METHODS: In this study, we developed a webserver to analyze the prognostic values of genes in cutaneous melanoma using data from TCGA and GEO databases. The webserver is named Online consensus Survival webserver for Skin Cutaneous Melanoma (OSskcm) which includes 1085 clinical melanoma samples. The OSskcm is hosted in a windows tomcat server. Server-side scripts were developed in Java script. The database system is managed by a SQL Server, which integrates gene expression data and clinical data. The Kaplan–Meier (KM) survival curves, Hazard ratio (HR) and 95% confidence interval (95%CI) were calculated in a univariate Cox regression analysis. RESULTS: In OSskcm, by inputting official gene symbol and selecting proper options, users could obtain KM survival plot with log-rank P value and HR on the output web page. In addition, clinical characters including race, stage, gender, age and type of therapy could also be included in the prognosis analysis as confounding factors to constrain the analysis in a subgroup of melanoma patients. CONCLUSION: The OSskcm is highly valuable for biologists and clinicians to perform the assessment and validation of new or interested prognostic biomarkers for melanoma. OSskcm can be accessed online at: http://bioinfo.henu.edu.cn/Melanoma/MelanomaList.jsp. |
format | Online Article Text |
id | pubmed-7236197 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72361972020-05-27 OSskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles Zhang, Lu Wang, Qiang Wang, Lijie Xie, Longxiang An, Yang Zhang, Guosen Zhu, Wan Li, Yongqiang Liu, Zhihui Zhang, Xiaochen Tang, Panpan Huo, Xiaozheng Guo, Xiangqian Cancer Cell Int Primary Research BACKGROUND: Cutaneous melanoma is one of the most aggressive and lethal skin cancers. It is greatly important to identify prognostic biomarkers to guide the clinical management. However, it is technically challenging for untrained researchers to process high dimensional profiling data and identify potential prognostic genes in profiling datasets. METHODS: In this study, we developed a webserver to analyze the prognostic values of genes in cutaneous melanoma using data from TCGA and GEO databases. The webserver is named Online consensus Survival webserver for Skin Cutaneous Melanoma (OSskcm) which includes 1085 clinical melanoma samples. The OSskcm is hosted in a windows tomcat server. Server-side scripts were developed in Java script. The database system is managed by a SQL Server, which integrates gene expression data and clinical data. The Kaplan–Meier (KM) survival curves, Hazard ratio (HR) and 95% confidence interval (95%CI) were calculated in a univariate Cox regression analysis. RESULTS: In OSskcm, by inputting official gene symbol and selecting proper options, users could obtain KM survival plot with log-rank P value and HR on the output web page. In addition, clinical characters including race, stage, gender, age and type of therapy could also be included in the prognosis analysis as confounding factors to constrain the analysis in a subgroup of melanoma patients. CONCLUSION: The OSskcm is highly valuable for biologists and clinicians to perform the assessment and validation of new or interested prognostic biomarkers for melanoma. OSskcm can be accessed online at: http://bioinfo.henu.edu.cn/Melanoma/MelanomaList.jsp. BioMed Central 2020-05-19 /pmc/articles/PMC7236197/ /pubmed/32467670 http://dx.doi.org/10.1186/s12935-020-01262-3 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Primary Research Zhang, Lu Wang, Qiang Wang, Lijie Xie, Longxiang An, Yang Zhang, Guosen Zhu, Wan Li, Yongqiang Liu, Zhihui Zhang, Xiaochen Tang, Panpan Huo, Xiaozheng Guo, Xiangqian OSskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles |
title | OSskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles |
title_full | OSskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles |
title_fullStr | OSskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles |
title_full_unstemmed | OSskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles |
title_short | OSskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles |
title_sort | osskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236197/ https://www.ncbi.nlm.nih.gov/pubmed/32467670 http://dx.doi.org/10.1186/s12935-020-01262-3 |
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