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Identifying distinct classes of bladder carcinoma using microarrays

Nature Genetics volume 33, pages 90–96 (2003)Cite this article

Abstract

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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Figure 1: Two-way hierarchical clustering and multidimensional scaling analysis of gene expression data from 40 bladder tumor biopsy samples.
Figure 2: Enlarged view of gene clusters a, c, f and g.
Figure 3: Molecular classification of bladder tumor stages and identification of genes that predict recurrence.

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Acknowledgements

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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Authors and Affiliations

  1. Department of Clinical Biochemistry, Molecular Diagnostic Laboratory, Aarhus University Hospital, Skejby, Aarhus N, DK-8200, 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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Correspondence to Torben F. Ørntoft.

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

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Dyrskjøt, L., Thykjaer, T., Kruhøffer, M. et al. Identifying distinct classes of bladder carcinoma using microarrays. Nat Genet 33, 90–96 (2003). https://doi.org/10.1038/ng1061

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