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

Abstract

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 O nline consensus S urvival analysis of l eio m yo s 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 http://bioinfo.henu.edu.cn/LMS/LMSList.jsp .

OSpaad: An online tool to perform survival analysis by integrating gene expression profiling and long‐term follow‐up data of 1319 pancreatic carcinoma patients

“…OSpaad is developed as we previously reported. [10][11][12][13] OSpaad is developed in a Windows server system. Front-end application was | 305 "pancreatic cancer," "prognostic biomarker," "survival analysis," and "gene expression."…”

OSeac: An Online Survival Analysis Tool for Esophageal Adenocarcinoma

“…The OSeac server is developed as we previously described (17)(18)(19), and hosted in a windows server and adopts Appache Tomcat as web application server. Use HTML and JSP for the front end page and server side code is compiled to Java.…”

“…However, these biomarkers need independent further validation to increase their sensitivity and specificity before clinical application. The advanced bioinformatic methods and resources have been developed for breast cancer, bladder cancer, esophageal squamous cell carcinoma, leiomyosarcoma, and lung cancer to analyze the prognostic abilities of genes (14)(15)(16)(17)(18)(19), and greatly facilitate the development of cancer prognostic biomarkers. However, there is a lack of prognostic analysis system for EAC.…”

Identification of Prognostic Genes in Leiomyosarcoma by Gene Co-Expression Network Analysis

“…org/) (Tang et al, 2017). Then, the overall survival and event-free survival analysis of hub genes were performed using Kaplan-Meier curve in Kaplan Meier plotter (https://kmplot.com/ analysis/index.php?p=background) (Nagy et al, 2018) and LOGpc (Long-term Outcome and Gene Expression Profiling Database of pan-cancers) (http://bioinfo.henu.edu.cn/ DatabaseList.jsp) (Wang et al, 2019). Finally, we performed multi-factor COX analysis on three key genes, established a ris k m odel , and p erfor med su rv iv al analysis and model identification.…”