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Gene Panel Model Predictive of Outcome in Men at High-Risk of Systemic Progression and Death From Prostate Cancer After Radical Retropubic Prostatectomy

John C. Cheville, R. Jeffrey Karnes, Terry M. Therneau, Farhad Kosari, Jan-Marie Munz, Lori Tillmans, Eati Basal, Laureano J. Rangel, Eric Bergstralh, Irina V. Kovtun, C.D. Savci-Heijink, Eric W. Klee, George Vasmatzis

From the Departments of Laboratory Medicine and Pathology and Urology, Division of Biostatistics; and the Departments of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN

Corresponding author: George Vasmatzis, PhD, and John C. Cheville, MD, Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First St SW, Rochester, MN 55905; e-mail: vasmatzis.george{at}mayo.edu

Purpose In men who are at high-risk of prostate cancer, progression and death from cancer after radical retropubic prostatectomy (RRP), limited prognostic information is provided by established prognostic features. The objective of this study was to develop a model predictive of outcome in this group of patients.

Methods Candidate genes were identified from microarray expression data from 102 laser capture microdissected prostate tissue samples. Candidates were overexpressed in tumor compared with normal prostate and more frequently in Gleason patterns 4 and 5 than in 3. A case control study of 157 high-risk patients, matched on Gleason score and stage with systemic progression or death of prostate cancer as the end point, was used to evaluate the expression of candidate genes and build a multivariate model. Tumor was collected from the highest Gleason score in paraffin-embedded blocks and the gene expression was quantified by real-time reverse transcription polymerase chain reaction. Validation of the final model was performed on a separate case-control study of 57 high-risk patients who underwent RRP.

Results A model incorporating gene expression of topoisomerase-2a, cadherin-10, the fusion status based on ERG, ETV1, and ETV4 expression, and the aneuploidy status resulted in a 0.81 area under the curve (AUC) in receiver operating characteristic statistical analysis for the identification of men with systemic progression and death from high grade prostate cancer. The AUC was 0.79 in the independent validation study.

Conclusion The model can identify men with high-risk prostate cancer who may benefit from more intensive postoperative follow-up and adjuvant therapies.

Supported by a generous gift from The Richard M. Schulze Family Foundation; the Mayo Clinic Comprehensive Cancer Center; the Department of Laboratory Medicine and Pathology and the SPORE in Prostate Cancer Grant No. CA91956 from the National Cancer Institute, US National Institutes of Health.

Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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