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Bladder Cancer Stage and Outcome by Array-Based Comparative Genomic Hybridization

Authors' Affiliations: Departments of ¹ Laboratory Medicine, ² Cancer Center, ³ Urology, and ⁴ Pathology, University of California San Francisco, San Francisco, California

Requests for reprints: Frederic Waldman, Department of Laboratory Medicine, University of California San Francisco Comprehensive Cancer Center, San Francisco, CA 94143-0808. Phone: 415-476-3821; Fax: 415-476-8218; E-mail: waldman{at}cc.ucsf.edu.

Purpose: Bladder carcinogenesis is believed to follow alternative pathways of disease progression driven by an accumulation of genetic alterations. The purpose of this study was to evaluate associations between measures of genomic instability and bladder cancer clinical phenotype.

Experimental Design: Genome-wide copy number profiles were obtained for 98 bladder tumors of diverse stages (29 pT_a, 14 pT₁, 55 pT_2-4) and grades (21 low-grade and 8 high-grade superficial tumors) by array-based comparative genomic hybridization (CGH). Each array contained 2,464 bacterial artificial chromosome and P1 clones, providing an average resolution of 1.5 Mb across the genome. A total of 54 muscle-invasive cases had follow-up information available. Overall outcome analysis was done for patients with muscle-invasive tumors having "good" (alive >2 years) versus "bad" (dead in <2 years) prognosis.

Results: Array CGH analysis showed significant increases in copy number alterations and genomic instability with increasing stage and with outcome. The fraction of genome altered (FGA) was significantly different between tumors of different stages (pT_a versus pT₁, P = 0.0003; pT_a versus pT_2-4, P = 0.02; and pT₁ versus pT_2-4, P = 0.03). Individual clones that differed significantly between different tumor stages were identified after adjustment for multiple comparisons (false discovery rate < 0.05). For muscle-invasive tumors, the FGA was associated with patient outcome (bad versus good prognosis patients, P = 0.002) and was identified as the only independent predictor of overall outcome based on a multivariate Cox proportional hazards method. Unsupervised hierarchical clustering separated "good" and "bad" prognosis muscle-invasive tumors into clusters that showed significant association with FGA and survival (Kaplan-Meier, P = 0.019). Supervised tumor classification (prediction analysis for microarrays) had a 71% classification success rate based on 102 unique clones.

Conclusions: Array-based CGH identified quantitative and qualitative differences in DNA copy number alterations at high resolution according to tumor stage and grade. Fraction genome altered was associated with worse outcome in muscle-invasive tumors, independent of other clinicopathologic parameters. Measures of genomic instability add independent power to outcome prediction of bladder tumors.

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