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01.12.2015 | Database | Ausgabe 1/2015 Open Access

BMC Urology 1/2015

An online tool for evaluating diagnostic and prognostic gene expression biomarkers in bladder cancer

BMC Urology > Ausgabe 1/2015
Garrett M. Dancik
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​s12894-015-0056-z) contains supplementary material, which is available to authorized users.

Competing interests

The author declares that they have no competing interests.

Author contributions

GD conceived of, designed, and implemented the database, and wrote the manuscript.



In the past ~15 years, the identification of diagnostic and prognostic biomarkers from gene expression data has increased our understanding of cancer biology and has led to advances in the personalized treatment of many cancers. A diagnostic biomarker is indicative of tumor status such as tumor stage, while a prognostic biomarker is indicative of disease outcome. Despite these advances, however, there are no clinically approved biomarkers for the treatment of bladder cancer, which is the fourth most common cancer in males in the United States and one of the most expensive cancers to treat. Although gene expression profiles of bladder cancer patients are publicly available, biomarker identification requires bioinformatics expertise that is not available to many research laboratories.


We collected gene expression data from 13 publicly available patient cohorts (N = 1454) and developed BC-BET, an online Bladder Cancer Biomarker Evaluation Tool for evaluating candidate diagnostic and prognostic gene expression biomarkers in bladder cancer. A user simply selects a gene, and BC-BET evaluates the utility of that gene’s expression as a diagnostic and prognostic biomarker. Specifically, BC-BET calculates how strongly a gene’s expression is associated with tumor presence (distinguishing tumor from normal samples), tumor grade (distinguishing low- from high-grade tumors), tumor stage (distinguishing non-muscle invasive from muscle invasive samples), and patient outcome (e.g., disease-specific survival) across all patients in each cohort. Patients with low-grade, non-muscle invasive tumors and patients with high-grade, muscle invasive tumors are also analyzed separately in order to evaluate whether the biomarker of interest has prognostic value independent of grade and stage.


Although bladder cancer gene expression datasets are publicly available, their analysis is computationally intensive and requires bioinformatics expertise. BC-BET is an easy-to-use tool for rapidly evaluating bladder cancer gene expression biomarkers across multiple patient cohorts.
Additional file 1: Table S1. Summary of patient cohorts, sample exclusion and processing for BC-BET. The Complete cohort columns correspond to all samples available at the given accession number or publication, while the BC-BET columns corresponds to the samples included in the database. Table S2. Association of stage (MI vs. NMI) and grade (HG vs. LG) with the best available endpoint. Statistically significant associations (P < 0.05) are highlighted in bold.
Additional file 2: Figure S1. Association of treatment with outcome in CNUH and DFCI cohorts. Kaplan-Meier curves for CNUH cohort showing association of disease-specific survival (DSS) and overall survival (OS) with (A) intravesical Bacillus Calmette-Guerin (BCG) therapy in patients with NMI tumors and (B) cisplatin-based adjuvant chemotherapy in patients with MI tumors. C, Association of recurrence-free survival (RFS) with adjuvant chemotherapy in patients with MI tumors in DFCI chort. P-values are calculated by log-rank test. Abbreviations: HR, hazard ratio; N+, nodal involvement (pN1-pN3); M+, distant metastasis.
Additional file 3: Table S3. BC-BET results: evaluation of FGFR3. The spreadsheet consists of multiple sheets with a description of each sheet at the top. The TUMOR, GRADE, and STAGE sheets contain the results of the diagnostic biomarker evaluation comparing tumor vs. normal samples, HG vs. LG tumors, and MI vs. NMI tumors, respectively. The SURVIVAL, SURVIVAL.LG.NMI, SURVIVAL.HG.MI sheets contain the results of the prognostic biomarker evaluation in patients with both NMI and MI tumors, patients with LG, NMI tumors, and patients with HG, MI tumors, respectively.
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