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Mechanisms of Disease: biomarkers and molecular targets from microarray gene expression studies in prostate cancer

Nature Clinical Practice Urology volume 4, pages 677–687 (2007)Cite this article

Abstract

Molecular biomarkers can serve as useful diagnostic markers, as prognostic markers for predicting clinical behavior, or as targets for new therapeutic strategies. Application of expression microarray technology, which allows the expression of all or most of the genes in the human genome to be analyzed simultaneously, has dramatically enhanced the discovery of prostate cancer biomarkers. The diagnostic markers identified include AMACR (α-methylacyl CoA racemase), a protein that has already been translated into clinical use as an aid in distinguishing prostate cancer from benign disease. Individual genes, such as the polycomb gene EZH2 whose expression indicates poor survival, have been identified. The power of microarray technology is that it has allowed the identification of gene signatures (each composed of multiple genes) that might provide improved prediction of clinical outcomes in human prostate cancer. The development of a new method for analyzing expression microarray data, called COPA, has led to the discovery of TMPRSS2–ERG gene fusion involvement in the development of prostate cancer, while expression analysis of castration-resistant prostate cancer has suggested the use of novel therapeutic approaches for advanced disease. Despite these successes, there are limitations in the application of microarray technology to prostate cancer; for example, unlike with other cancers, this approach has failed to provide a consistent unsupervised classification of the disease. Overcoming the reasons for these failures represents a major challenge for future research endeavors.

Key Points

  • Analyses of expression microarray data have resulted in the identification of many individual diagnostic and prognostic markers, including AMACR, EZH2, AZGP1, MEMD/CD166 and CD24

  • Cancer outlier profile analysis of expression microarray data demonstrated that ERG and ETV1 genes are overexpressed in a subset of cancers, leading to the discovery that these genes are activated by the formation of TMPRSS2–ERG and TMPRSS2–ETV1 gene fusions

  • Observations from microarray expression studies that the androgen receptor pathway is still activated in castration-resistant prostate cancer (CRPC) has led to the discovery that total androgen blockade with abiraterone might be an effective treatment for CRPC

  • Published expression microarray datasets are relatively small (maximum 79 prostate cancers); there is an urgent need to collect larger datasets that take issues such as genetic heterogeneity and cancer multifocality into consideration during the preparation of RNA samples used in microarray studies

  • Elucidation of the role of microRNAs in the development and clinical management of prostate cancer represents an important goal for future research

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Figure 1: Principle of expression microarray technology.
Figure 2: Latent process decomposition of the Glinsky et al.4 prostate expression microarray dataset.
Figure 3: Structure of TMPRSS2–ERG and TMPRSS2–ETV1 transcripts.

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Author information

Authors and Affiliations

  1. CS Cooper is a Professor, and S Jhavar is a clinical research fellow at the Male Urological Cancer Research Centre, Institute of Cancer Research, Sutton, UK.,

    Colin S Cooper & Sameer Jhavar

  2. C Campbell is a lecturer in Bioinformatics in the Advanced Computing Research Centre at the University of Bristol, UK.,

    Colin Campbell

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Correspondence to Colin S Cooper.

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Cooper, C., Campbell, C. & Jhavar, S. Mechanisms of Disease: biomarkers and molecular targets from microarray gene expression studies in prostate cancer. Nat Rev Urol 4, 677–687 (2007). https://doi.org/10.1038/ncpuro0946

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