Letters to Nature

Nature 412, 822-826 (23 August 2001) | doi:10.1038/35090585; Received 16 January 2001; Accepted 26 June 2001

Delineation of prognostic biomarkers in prostate cancer

Saravana M. Dhanasekaran1, Terrence R. Barrette1, Debashis Ghosh2, Rajal Shah1, Sooryanarayana Varambally1, Kotoku Kurachi3, Kenneth J. Pienta4,5,6, Mark A. Rubin1,4,6,7 & Arul M. Chinnaiyan1,4,6,7

  1. Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA
  2. Department of Biostatistics, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA
  3. Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA
  4. Department of Urology, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA
  5. Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA
  6. Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA
  7. These authors share senior authorship

Correspondence to: Arul M. Chinnaiyan1,4,6,7 Correspondence and requests for materials should be addressed to A.M.C. (e-mail: Email: arul@umich.edu).

Prostate cancer is the most frequently diagnosed cancer in American men1, 2. Screening for prostate-specific antigen (PSA) has led to earlier detection of prostate cancer3, but elevated serum PSA levels may be present in non-malignant conditions such as benign prostatic hyperlasia (BPH). Characterization of gene-expression profiles that molecularly distinguish prostatic neoplasms may identify genes involved in prostate carcinogenesis, elucidate clinical biomarkers, and lead to an improved classification of prostate cancer4, 5, 6. Using microarrays of complementary DNA, we examined gene-expression profiles of more than 50 normal and neoplastic prostate specimens and three common prostate-cancer cell lines. Signature expression profiles of normal adjacent prostate (NAP), BPH, localized prostate cancer, and metastatic, hormone-refractory prostate cancer were determined. Here we establish many associations between genes and prostate cancer. We assessed two of these genes—hepsin, a transmembrane serine protease, and pim-1, a serine/threonine kinase—at the protein level using tissue microarrays consisting of over 700 clinically stratified prostate-cancer specimens. Expression of hepsin and pim-1 proteins was significantly correlated with measures of clinical outcome. Thus, the integration of cDNA microarray, high-density tissue microarray, and linked clinical and pathology data is a powerful approach to molecular profiling of human cancer.