Delineation of prognostic biomarkers in prostate cancer

Saravana M. Dhanasekaran, Terrence R. Barrette, Debashis Ghosh, Rajal Shah, Sooryanarayana Varambally, Kotoku Kurachi, Kenneth J. Pienta, Mark A. Rubin and Arul M. Chinnaiyan ()
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Saravana M. Dhanasekaran: University of Michigan Medical School
Terrence R. Barrette: University of Michigan Medical School
Debashis Ghosh: University of Michigan Medical School
Rajal Shah: University of Michigan Medical School
Sooryanarayana Varambally: University of Michigan Medical School
Kotoku Kurachi: University of Michigan Medical School
Kenneth J. Pienta: University of Michigan Medical School
Mark A. Rubin: University of Michigan Medical School
Arul M. Chinnaiyan: University of Michigan Medical School

Nature, 2001, vol. 412, issue 6849, 822-826

Abstract: Abstract 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.

Date: 2001
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DOI: 10.1038/35090585

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