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Identifying distinct classes of bladder carcinoma using microarrays

Nature Genetics volume 33, pages 9096 (2003) | Download Citation



Bladder cancer is a common malignant disease characterized by frequent recurrences1,2. The stage of disease at diagnosis and the presence of surrounding carcinoma in situ are important in determining the disease course of an affected individual3. Despite considerable effort, no accepted immunohistological or molecular markers have been identified to define clinically relevant subsets of bladder cancer. Here we report the identification of clinically relevant subclasses of bladder carcinoma using expression microarray analysis of 40 well characterized bladder tumors. Hierarchical cluster analysis identified three major stages, Ta, T1 and T2-4, with the Ta tumors further classified into subgroups. We built a 32-gene molecular classifier using a cross-validation approach that was able to classify benign and muscle-invasive tumors with close correlation to pathological staging in an independent test set of 68 tumors. The classifier provided new predictive information on disease progression in Ta tumors compared with conventional staging (P < 0.005). To delineate non-recurring Ta tumors from frequently recurring Ta tumors, we analyzed expression patterns in 31 tumors by applying a supervised learning classification methodology, which classified 75% of the samples correctly (P < 0.006). Furthermore, gene expression profiles characterizing each stage and subtype identified their biological properties, producing new potential targets for therapy.

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We thank K.Y. Jonsdottir for computational assistance, H. Steen, B. Pytlick, J.C. Djurhuus, B. Stougaard and B. Devantié for excellent assistance, and the staff at the Departments of Urology, Clinical Biochemistry and Pathology at Aarhus University Hospital. We acknowledge support from the Karen Elise Jensen Foundation, The Danish Cancer Society, EOS Biotechnology, the John and Birthe Meyers Foundation, The Institute of Experimental Clinical Research, The University and County of Aarhus and the Danish Research Council.

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  1. Molecular Diagnostic Laboratory, Department of Clinical Biochemistry, Aarhus University Hospital, Skejby, DK-8200 Aarhus N, Denmark.

    • Lars Dyrskjøt
    • , Thomas Thykjaer
    •  & Torben F. Ørntoft
  2. Aros Applied Biotechnology, SciencePark Aarhus, Gustav Wiedsvej, Aarhus C, Denmark.

    • Thomas Thykjaer
  3. Department of Urology, Aarhus University Hospital, Skejby, Aarhus N, Denmark.

    • Mogens Kruhøffer
    •  & Hans Wolf
  4. Department of Theoretical Statistics, Department of Mathematical Sciences, Ny Munkegade, Aarhus C, Denmark.

    • Jens Ledet Jensen
  5. University Institute of Pathology, Aarhus University Hospital, Aarhus C, Denmark.

    • Niels Marcussen
    •  & Stephen Hamilton-Dutoit


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Competing interests

T.F.O., T.T. and M.K. co-founded AROS Applied Biotechnology ApS in the year 2000.

Corresponding author

Correspondence to Torben F. Ørntoft.

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