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Imaging, Diagnosis, Prognosis |
Authors' Affiliations: 1 Molecular Diagnostic Laboratory, Department of Clinical Biochemistry, 2 Department of Urology, and 3 University Institute of Pathology, Aarhus University Hospital; 4 Departments of Theoretical Statistics and Mathematical Sciences, University of Aarhus; 5 Aros Applied Biotechnology, Aarhus, Denmark; and 6 Eos Biotechnology/Protein Design Labs, Fremont, California
Requests for reprints: Torben F. Ørntoft, Molecular Diagnostic Laboratory, Department of Clinical Biochemistry, Aarhus University Hospital, Skejby, DK-8200 Aarhus N, Denmark. Phone: 45-89495100; Fax: 45-89496018; E-mail: orntoft{at}ki.au.dk.
Purpose: Cancer of the urinary bladder is a common malignant disease in the western countries. The majority of patients presents with superficial tumors with a high recurrence frequency, a minor fraction of these patients experience disease progression to a muscle invasive stage. No clinical useful molecular markers exist to identify patients showing later disease progression. The purpose of this study was to identify markers of disease progression using full-genome expression analysis.
Experimental Design: We did a full-genome expression analysis (59,619 genes and expressed sequence tags) of superficial bladder tumors from 29 bladder cancer patients (13 without later disease progression and 16 with later disease progression) using high-density oligonucleotide microarrays. We used supervised learning for identification of the optimal genes for predicting disease progression. The identified genes were validated on an independent test set (74 superficial tumor samples) using in house-fabricated 60-mer oligonucleotide microarrays.
Results: We identified a 45-gene signature of disease progression. By monitoring this progression signature in an independent test set, we found a significant correlation between our classifications and the clinical outcome (P < 0.03). The genes identified as differentially expressed were involved in regulating apoptosis, cell differentiation, and cell cycle and hence may represent potential therapeutic targets.
Conclusions: Our results indicate that it may be possible to identify patients with a high risk of disease progression at an early stage using a molecular signature present already in the superficial tumors. In this way, better treatment and follow-up regimens could be assigned to patients suffering from superficial bladder cancer.
Key Words: microarray • diagnosis • prognosis • classification
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