EXPERIMENTAL DESIGN: We evaluated microarray data from 93 bladder cancer patients managed by radical cystectomy to determine gene expression patterns associated with clinical and prognostic variables. We compared our results with published bladder cancer microarray datasets comprising 578 additional patients, and with 49 published gene signatures from multiple cancer types. Hierarchical clustering was utilized to identify subtypes associated with differences in survival. We then investigated whether the addition of survival-associated gene expression information to a validated post-cystectomy nomogram utilizing clinical and pathologic variables improves prediction of recurrence.
RESULTS: Multiple markers for muscle invasive disease with highly significant expression differences in multiple datasets were identified, such as FN1, NNMT, POSTN and SMAD6. We identified signatures associated with pathologic stage and the likelihood of developing metastasis and death from bladder cancer, as well as with two distinct clustering subtypes of bladder cancer. Our novel signature correlated with overall survival in multiple independent datasets, significantly improving the prediction concordance of standard staging in all datasets (mean ΔC-statistic: 0.14, 95% CI 0.01-0.27; P is less than 0.001). Tested in our patient cohort, it significantly enhanced the performance of a postoperative survival nomogram (ΔC-statistic: 0.08, 95% CI -0.04-0.20; P is less than 0.005).
CONCLUSIONS: Prognostic information obtained from gene expression data can aid in post-treatment prediction of bladder cancer recurrence. Our findings require further validation in external cohorts and prospectively in a clinical trial setting.
Written by:
Riester M, Taylor J, Feifer A, Koppie TM, Rosenberg J, Downey RJ, Bochner BH, Michor F. Are you the author?
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 450 Brookline Avenue, DFCI, Mailstop CLS-11007, Boston, Massachusetts, 02115, United States.
Reference: Clin Cancer Res. 2012 Jan 6. Epub ahead of print.
doi: 10.1158/1078-0432.CCR-11-2271
PubMed Abstract
PMID: 22228636
UroToday.com Bladder Cancer Section
