Combination of a novel gene expression signature with a clinical nomogram improves the prediction of survival in high-risk bladder cancer Journal Article


Authors: Riester, M.; Taylor, J. M.; Feifer, A.; Koppie, T.; Rosenberg, J. E.; Downey, R. J.; Bochner, B. H.; Michor, F.
Article Title: Combination of a novel gene expression signature with a clinical nomogram improves the prediction of survival in high-risk bladder cancer
Abstract: Purpose: We aimed to validate and improve prognostic signatures for high-risk urothelial carcinoma of the bladder. Experimental Design: We evaluated microarray data from 93 patients with bladder cancer managed by radical cystectomy to determine gene expression patterns associated with clinical and prognostic variables. We compared our results with published bladder cancer microarray data sets 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 postcystectomy nomogram utilizing clinical and pathologic variables improves prediction of recurrence. Results: Multiple markers for muscle invasive disease with highly significant expression differences in multiple data sets were identified, such as fibronectin 1 (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 data sets, significantly improving the prediction concordance of standard staging in all data sets [meanΔC-statistic: 0.14;95%confidence interval (CI), 0.01-0.27; P < 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 < 0.005). Conclusions: Prognostic information obtained from gene expression data can aid in posttreatment prediction of bladder cancer recurrence. Our findings require further validation in external cohorts and prospectively in a clinical trial setting. ©2012 AACR.
Keywords: adult; cancer survival; controlled study; human tissue; aged; overall survival; cancer recurrence; cancer staging; gene; disease association; gene expression; gene expression profiling; bladder cancer; cancer mortality; microarray analysis; transitional cell carcinoma; nomogram; smad6 gene; cancer prognosis; fibronectin 1 gene; nnmt gene; postn gene
Journal Title: Clinical Cancer Research
Volume: 18
Issue: 5
ISSN: 1078-0432
Publisher: American Association for Cancer Research  
Date Published: 2012-03-01
Start Page: 1323
End Page: 1333
Language: English
DOI: 10.1158/1078-0432.ccr-11-2271
PROVIDER: scopus
PUBMED: 22228636
PMCID: PMC3569085
DOI/URL:
Notes: --- - "Export Date: 2 April 2012" - "CODEN: CCREF" - "Source: Scopus"
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. Jennifer Marie Taylor
    11 Taylor
  2. Andrew Feifer
    18 Feifer
  3. Bernard Bochner
    468 Bochner
  4. Robert J Downey
    254 Downey
  5. Jonathan Eric Rosenberg
    510 Rosenberg