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PURPOSE: New methods to accurately predict an individual tumor behavior are urgently required to improve the treatment of cancer. We previously found that promoter hypermethylation can be an accurate predictor of bladder cancer progression, but it is not cancer specific. Here, we investigate a panel of methylated loci in a prospectively collected cohort of bladder tumors to determine whether hypermethylation has a useful role in the management of patients with bladder cancer. EXPERIMENTAL DESIGN: Quantitative methylation-specific PCR was done at 17 gene promoters, suspected to be associated with tumor progression, in 96 malignant and 30 normal urothelial samples. Statistical analysis and artificial intelligence techniques were used to interrogate the results. RESULTS: Using log-rank analysis, five loci were associated with progression to more advanced disease (RASSF1a, E-cadherin, TNFSR25, EDNRB, and APC; P < 0.05). Multivariate analysis revealed that the overall degree of methylation was more significantly associated with subsequent progression and death (Cox, P = 0.002) than tumor stage (Cox, P = 0.008). Neuro-fuzzy modeling confirmed that these five loci were those most associated with tumor progression. Epigenetic predictive models developed using artificial intelligence techniques identified the presence and timing of tumor progression with 97% specificity and 75% sensitivity. CONCLUSION: Promoter hypermethylation seems a reliable predictor of tumor progression in bladder cancer. It is associated with aggressive tumors and could be used to identify patients with either superficial disease requiring radical treatment or a low progression risk suitable for less intensive surveillance. Multicenter studies are warranted to validate this marker.

Original publication

DOI

10.1158/1078-0432.CCR-06-2476

Type

Journal article

Journal

Clin Cancer Res

Publication Date

01/04/2007

Volume

13

Pages

2046 - 2053

Keywords

Aged, Aged, 80 and over, Biomarkers, Tumor, DNA Methylation, Disease Progression, Epigenesis, Genetic, Female, Fuzzy Logic, Humans, Male, Middle Aged, Models, Genetic, Neoplasm Staging, Polymerase Chain Reaction, Prognosis, Promoter Regions, Genetic, Sensitivity and Specificity, Urinary Bladder Neoplasms