SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis
Top Cited Papers
Open Access
- 16 September 2013
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 8 (9), e74250
- https://doi.org/10.1371/journal.pone.0074250
Abstract
Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included). The website was implemented in JSP, JavaScript, MySQL, and R.Keywords
This publication has 28 references indexed in Scilit:
- bc-GenExMiner 3.0: new mining module computes breast cancer gene expression correlation analysesDatabase: The Journal of Biological Databases and Curation, 2013
- Comprehensive molecular portraits of human breast tumoursNature, 2012
- Disease Ontology: a backbone for disease semantic integrationNucleic Acids Research, 2011
- Correlation of microarray-based breast cancer molecular subtypes and clinical outcomes: implications for treatment optimizationBMC Cancer, 2011
- Gene Expression-Based Prognostic Signatures in Lung Cancer: Ready for Clinical Use?JNCI Journal of the National Cancer Institute, 2010
- Survival Online: a web-based service for the analysis of correlations between gene expression and clinical and follow-up dataBMC Bioinformatics, 2009
- Prognostic gene signatures for non-small-cell lung cancerProceedings of the National Academy of Sciences, 2009
- Gene expression–based survival prediction in lung adenocarcinoma: a multi-site, blinded validation studyNature Medicine, 2008
- Oncogenic pathway signatures in human cancers as a guide to targeted therapiesNature, 2005
- A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast CancerNew England Journal of Medicine, 2004