Dataset Information

OSskcm: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles.

ABSTRACT:

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.

SUBMITTER: Zhang L

PROVIDER: S-EPMC7236197 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

<i>OSskcm</i>: an online survival analysis webserver for skin cutaneous melanoma based on 1085 transcriptomic profiles.

Zhang Lu L Wang Qiang Q Wang Lijie L Xie Longxiang L An Yang Y Zhang Guosen G Zhu Wan W Li Yongqiang Y Liu Zhihui Z Zhang Xiaochen X Tang Panpan P Huo Xiaozheng X Guo Xiangqian X Guo Xiangqian X

Cancer cell international 20200519

<h4>Background</h4>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.<h4>Methods</h4>In this study, we developed a webserver to analyze the prognostic values of genes in cutaneous melanoma using data from TCGA and ...[more]

PMID: 32467670

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