Cancer Research Translational Cancer Medicine 2008: Cancer Clinical Trials and Personalized Medicine  Candidate Pathways, Whole Genome Scans
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Cancer Research 68, 645-649, February 1, 2008. doi: 10.1158/0008-5472.CAN-07-3224
© 2008 American Association for Cancer Research

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Priority Reports

A First-Generation Multiplex Biomarker Analysis of Urine for the Early Detection of Prostate Cancer

Bharathi Laxman1,2, David S. Morris1,3, Jianjun Yu1,2,4, Javed Siddiqui1,2, Jie Cao1,2, Rohit Mehra1,2,5, Robert J. Lonigro1,5, Alex Tsodikov1,6, John T. Wei1,3,5, Scott A. Tomlins1,2 and Arul M. Chinnaiyan1,2,3,4,5

1 Michigan Center for Translational Pathology, 2 Department of Pathology, 3 Department of Urology, 4 Bioinformatics Program, and 5 Comprehensive Cancer Center, University of Michigan Medical School; and 6 Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan

Requests for reprints: Arul M. Chinnaiyan, University of Michigan Medical School, 1400 East Medical Center Drive, 5316 CCGC, Ann Arbor, MI 48109-0602. Phone: 734-615-4062; Fax: 734-615-4498; E-mail: arul{at}umich.edu.

Key Words: prostate cancer • biomarker • urine detection • serum PSA • PCA3

Although prostate-specific antigen (PSA) serum level is currently the standard of care for prostate cancer screening in the United States, it lacks ideal specificity and additional biomarkers are needed to supplement or potentially replace serum PSA testing. Emerging evidence suggests that monitoring the noncoding RNA transcript PCA3 in urine may be useful in detecting prostate cancer in patients with elevated PSA levels. Here, we show that a multiplex panel of urine transcripts outperforms PCA3 transcript alone for the detection of prostate cancer. We measured the expression of seven putative prostate cancer biomarkers, including PCA3, in sedimented urine using quantitative PCR on a cohort of 234 patients presenting for biopsy or radical prostatectomy. By univariate analysis, we found that increased GOLPH2, SPINK1, and PCA3 transcript expression and TMPRSS2:ERG fusion status were significant predictors of prostate cancer. Multivariate regression analysis showed that a multiplexed model, including these biomarkers, outperformed serum PSA or PCA3 alone in detecting prostate cancer. The area under the receiver-operating characteristic curve was 0.758 for the multiplexed model versus 0.662 for PCA3 alone (P = 0.003). The sensitivity and specificity for the multiplexed model were 65.9% and 76.0%, respectively, and the positive and negative predictive values were 79.8% and 60.8%, respectively. Taken together, these results provide the framework for the development of highly optimized, multiplex urine biomarker tests for more accurate detection of prostate cancer. [Cancer Res 2008;68(3):645–9]







HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Cell Growth & Differentiation
Copyright © 2008 by the American Association for Cancer Research.