[CANCER RESEARCH 63, 4196 – 4203, July 15, 2003] Survival Analysis of Genome-Wide Gene Expression Profiles of Prostate Cancers Identifies New Prognostic Targets of Disease Relapse 1,2 Susan M. Henshall, Daniel E. H. Afar, 3 Jordan Hiller, 3 Lisa G. Horvath, David I. Quinn, Krishan K. Rasiah, Kurt Gish, 3 Dorian Willhite, James G. Kench, Margaret Gardiner-Garden, Phillip D. Stricker, Howard I. Scher, John J. Grygiel, David B. Agus, David H. Mack, and Robert L. Sutherland 4 Cancer Research Program, Garvan Institute of Medical Research, St. Vincent’s Hospital, Darlinghurst, Sydney, New South Wales 2010, Australia [S. M. H., L. G. H., D. I. Q., K. K. R., J. G. K., M. G-G., R. L. S.]; Genomics Research, Eos Biotechnology, South San Francisco, California [D. E. H. A., J. H., K. G., D. W., D. H. M.]; Department of Medical Oncology (J. J. G.), and Department of Urology, St. Vincent’s Hospital, Darlinghurst, Sydney, New South Wales 2010, Australia [P. D. S.]; Cedars-Sinai Prostate Cancer Center, Los Angeles, California [D. B. A.]; and Genitourinary Oncology Service, Memorial Sloan-Kettering Cancer Center, New York, New York [H. S.] ABSTRACT Current models of prostate cancer classification are poor at distinguish- ing between tumors that have similar histopathological features but vary in clinical course and outcome. Here, we applied classical survival analysis to genome-wide gene expression profiles of prostate cancers and pre- operative prostate-specific antigen (PSA) levels from each patient, to identify prognostic markers of disease relapse that provide additional predictive value relative to PSA concentration. Three of 200 probesets showing strongest correlation with relapse were identified as the gene for the putative calcium channel protein, trp-p8, with loss of trp-p8 mRNA expression associated with a significantly shorter time to PSA relapse-free survival. We observed subsequently that trp-p8 is lost in the transition to androgen independence in a prostate cancer xenograft model and in prostate cancer tissue from patients treated preoperatively with anti- androgen therapy, suggesting that trp-p8 is androgen regulated, and its loss may be associated with more advanced disease. The identification of trp-p8 and other proteins implicated in the phosphatidylinositol signal transduction pathway that are associated with prostate cancer outcome, both here and in other published work, suggests an integral role for this pathway in prostate carcinogenesis. Thus, our findings demonstrate that multivariable survival analysis can be applied to gene expression profiles of prostate cancers with censored follow-up data and used to identify molecular markers of prostate cancer relapse with strong predictive power and relevance to the etiology of this disease. INTRODUCTION Prostate cancer will account for an estimated 30% (189,000) of new cancer cases in men in the United States in 2002 (1). Many of these newly diagnosed cases are a result of the extensive use of PSA 5 screening and the subsequent diagnosis of prostate cancer at an early stage and age. However, despite the introduction of PSA screening, the mortality from prostate cancer has remained relatively constant. The implications of this are that: (a) there are a large group of men diagnosed with prostate cancer for whom radical treatment is probably unnecessary and who will die with their prostate cancer rather than from it; and (b) there are a group of men for whom early detection offers the possibility of cure that may be denied by delay. Conse- quently, identifying these groups of men at the time of diagnosis is critical to the optimal management of prostate cancer. Although the benefits of PSA screening are widely debated, this serum marker remains one of only a few preoperative parameters of prognostic utility. To enhance the predictive value of individual parameters with outcomes, nomograms have been developed that incorporate parameters that are measured routinely in clinical practice to predict the probability of PSA relapse-free survival of individual patients both before and after therapy (2– 6). Models such as these currently form the basis of routine clinical decision-making, but such classification systems cannot explore differences in outcomes ob- served between cancers with similar histopathological features. Hence, there remains a critical need for increased accuracy in the subcategorization of prostate cancers to identify those with an aggres- sive phenotype. One approach is to define patterns of gene expression that correlate with disease phenotype and patient outcome. Here, we undertook a systematic search for novel biomarkers of prostate cancer prognosis by outcome-based analyses of transcript profiles. MATERIALS AND METHODS Tissue Collection and Preparation of RNA. A cohort of 72 fresh-frozen prostate cancers was collected from patients with localized prostate cancer treated by RP at St. Vincent’s Hospital. The primary outcome, disease-specific relapse, was measured from the date of RP and was defined as a rise in serum PSA 0.3 ng/ml with subsequent additional rises. After inking of the external limits of the prostate immediately after removal and before formalin-fixation, up to six 5-mm core biopsies were taken and stored at -80°C for later RNA extraction. The proportion of invasive cancer in the biopsy sample was then estimated retrospectively by either frozen sectioning of the biopsy and H&E staining, or by examination of archival formalin-fixed, paraffin-embedded tissue surrounding the biopsy site. Only those biopsies that contained 75% invasive cancer were used for subsequent transcript profiling. Only one biopsy per patient was analyzed. Xenograft Model. The androgen-dependent LuCaP-35 (7) prostate cancer xenograft (generously provided by Robert L. Vessella, University of Wash- ington, Seattle, WA) was grown as s.c. tumors in nude male mice. To study the androgen-withdrawal process, tumor-bearing mice were castrated and moni- tored for tumor regression and PSA levels. Tumors were harvested from mice before castration and at various time points (1–100 days) postcastration, and were processed for microarray analysis. For data analysis and identification of androgen-regulated genes, i.e., genes that behaved similar to PSA, the Lu- CaP-35 xenografts were binned into two groups (days 0 –2 postcastration versus 5–100 days postcastration), because PSA levels were high at days 0 –2 and dropped precipitously at day 5 postcastration. Genes that showed a significant (P  0.01) difference in the means of each group were identified by a standard Student’s t test. RNA Extraction and Microarray Protocols. Preparation of total RNA from fresh-frozen prostate and xenograft tissue was performed by extraction with Trizol reagent (Life Technologies, Inc., Gaithersburg, MD) and was reverse transcribed using a primer containing oligodeoxythymidylic acid and a T7 promoter sequence. The resulting cDNAs were then in vitro transcribed in the presence of biotinylated nucleotides (Bio-11-CTP and Bio-16-UTP) using the T7 MEGAscript kit (Ambion, Austin, TX). Received 10/25/02; accepted 5/15/03. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. 1 Supported by grants from the National Health and Medical Research Council of Australia, The Cancer Council New South Wales, the R. T. Hall Trust, Freedman Foundation, Royal Australasian College of Surgeons, Australasian Urological Foundation, Prostate Cancer Foundation of Australia, and David Wilson Trust. 3 Present address: Protein Design Labs Inc., Fremont, CA 94555. 2 Supplementary data are submitted for review as part of this manuscript. 4 To whom correspondence should be addressed, at Cancer Research Program, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, New South Wales, 2010 Australia. Phone: 612-9295-8322; Fax: 612-9295-8321; E-mail: r.sutherland@garvan.org.au. 5 The abbreviations: PSA, prostate-specific antigen; Ca 2+ , calcium; HR, hazard ratio; IQR, interquartile range; IP3R, inositol triphosphate receptor; ISH, in situ hybridization; NHT, neoadjuvant hormone therapy; pFDR, positive false discovery rate; RP, radical prostatectomy; EST, expressed sequence tag; Gn-RH, gonadotrophin-releasing hormone; DIG, digoxigenin. 4196