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Front. Oncol. | doi: 10.3389/fonc.2019.00190

OSlms: a Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma

 Qiang Wang1,  Longxiang Xie1, Yifang Dang1,  Xiaoxiao Sun1,  Tiantian Xie1,  Jinshuai Guo1, Yali Han1, Zhongyi Yan1, Wan Zhu2, Yunlong Wang3,  Wei Li4 and  Xiangqian Guo1*
  • 1Henan University, China
  • 2Stanford University, United States
  • 3Henan Bioengineering Technology Research Center, China
  • 4Baylor College of Medicine, United States

The availability of transcriptome data and clinical annotation offers the opportunity to identify prognosis biomarkers in cancer. However, efficient online prognosis analysis tools are still lacking. Herein, we developed a user-friendly web server, namely Online consensus Survival analysis of leiomyosarcoma (OSlms), to centralize published gene expression data and clinical datasets of leiomyosarcoma (LMS) patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). OSlms comprises a total of 268 samples from three independent datasets, and employs the Kaplan Meier survival plot with hazard ratio (HR) and log rank test to estimate the prognostic potency of genes of interests for LMS patients. Using OSlms, clinicians and basic researchers could determine the prognostic significance of genes of interests and get opportunities to identify novel potential important molecules for LMS. OSlms is free and publicly accessible at http://bioinfo.henu.edu.cn/LMS/LMSList.jsp.

Keywords: Leiomyosarcoma, prognostic, Web server, database, survival analysis

Received: 31 Jan 2019; Accepted: 05 Mar 2019.

Edited by:

Jianguang Ji, Lund University, Sweden

Reviewed by:

Chunbo Zhang, Nanchang University, China
Liguo Wang, Mayo Clinic, United States  

Copyright: © 2019 Wang, Xie, Dang, Sun, Xie, Guo, Han, Yan, Zhu, Wang, Li and Guo. 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.

* Correspondence: Prof. Xiangqian Guo, Henan University, Kaifeng, China, xqguo@henu.edu.cn