AUTHOR=Wang Qiang , Xie Longxiang , Dang Yifang , Sun Xiaoxiao , Xie Tiantian , Guo Jinshuai , Han Yali , Yan Zhongyi , Zhu Wan , Wang Yunlong , Li Wei , Guo Xiangqian 

TITLE=OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma

JOURNAL=Frontiers in Oncology

VOLUME=9

YEAR=2019

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2019.00190

DOI=10.3389/fonc.2019.00190

ISSN=2234-943X

ABSTRACT=<p>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 <underline><bold>O</bold></underline>nline consensus <underline><bold>S</bold></underline>urvival analysis of <underline><bold>l</bold></underline>eio<underline><bold>m</bold></underline>yo<underline><bold>s</bold></underline>arcoma (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 of 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 <ext-link ext-link-type="uri" xlink:href="http://bioinfo.henu.edu.cn/LMS/LMSList.jsp" xmlns:xlink="http://www.w3.org/1999/xlink">http://bioinfo.henu.edu.cn/LMS/LMSList.jsp</ext-link>.</p>