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J Clin Oncol. 2009 Aug 20;27(24):3929-37. doi: 10.1200/JCO.2008.18.5744. Epub 2009 Jul 20.

Generation of a concise gene panel for outcome prediction in urinary bladder cancer.

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  • 1Department of Pathology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Abstract

PURPOSE:

This study sought to determine if alterations in molecular pathways could supplement TNM staging to more accurately predict clinical outcome in patients with urothelial carcinoma (UC).

PATIENTS AND METHODS:

Expressions of 69 genes involved in known cancer pathways were quantified on bladder specimens from 58 patients with UC (stages Ta-T4) and five normal urothelium controls. All tumor transcript values beyond two standard deviations from the normal mean expression were designated as over- or underexpressed. Univariate and multivariable analyses were conducted to obtain a predictive expression signature. A published external data set was used to confirm the potential of the prognostic gene panels.

RESULTS:

In univariate analysis, six genes were significantly associated with time to recurrence, and 10 with overall survival. Recursive partitioning identified three genes as significant determinants for recurrence, and three for overall survival. Of all genes identified by either univariate or partitioning analysis, four were found to significantly predict both recurrence and survival (JUN, MAP2K6, STAT3, and ICAM1); overexpression was associated with worse outcome. Comparing the favorable (low or normal) expression of > or = three of four versus < or = two of four of these oncogenes showed 5-year recurrence probability of 41% versus 88%, respectively (P < .001), and 5-year overall survival probability of 61% versus 5%, respectively (P < .001). The prognostic potential of this four-gene panel was confirmed in a large independent external cohort (disease-specific survival, P = .039).

CONCLUSION:

We have documented the generation of a concise, biologically relevant four-gene panel that significantly predicts recurrence and survival and may also identify potential therapeutic targets for UC.

PMID:
19620494
[PubMed - indexed for MEDLINE]
PMCID:
PMC2799152
Free PMC Article
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