OSacc: Gene Expression-Based Survival Analysis Web Tool For Adrenocortical Carcinoma

Longxiang Xie; Qiang Wang; Fangmei Nan; Linna Ge; Yifang Dang; Xiaoxiao Sun; Ning Li; Huan Dong; Yali Han; Guosen Zhang; Wan Zhu; Xiangqian Guo

doi:10.2147/CMAR.S215586

OSacc: Gene Expression-Based Survival Analysis Web Tool For Adrenocortical Carcinoma

Cancer Manag Res. 2019 Oct 24:11:9145-9152. doi: 10.2147/CMAR.S215586. eCollection 2019.

Authors

Longxiang Xie¹, Qiang Wang¹, Fangmei Nan¹, Linna Ge¹, Yifang Dang¹, Xiaoxiao Sun¹, Ning Li¹, Huan Dong¹, Yali Han¹, Guosen Zhang¹, Wan Zhu², Xiangqian Guo¹

Affiliations

¹ Bioinformatics Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, People's Republic of China.
² Department of Anesthesia, Stanford University, Stanford, CA, USA.

Abstract

Gene expression profiling data with long-term clinical follow-up information are great resources to screen, develop, evaluate and validate prognostic biomarkers in translational cancer research. However, an easy-to-use interactive online tool is needed to analyze these profiling and clinical data. In the current work, we developed OSacc (Online consensus Survival analysis of ACC), a web tool that provides rapid and user-friendly survival analysis based on seven independent transcriptomic profiles with long-term clinical follow-up information of 259 ACC patients gathered from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. OSacc allows researchers and clinicians to evaluate the prognostic value of genes of interest by Kaplan-Meier (KM) survival plot with hazard ratio (HR) and log-rank test in ACC. OSacc is freely available at http://bioinfo.henu.edu.cn/ACC/ACCList.jsp.

Keywords: ACC; KM plot; over survival; prognostic marker; web tool.