2013 NCRI Cancer Conference

3 - 6 November 2013
The BT Convention Centre Liverpool UK
conference.ncri.org.uk

LB4

CCP Score: A novel genetic test for prostate cancer

Dan Berney1, Michael Brawer2, Matthew Cooperberg3, Gregory Swanson4, Stephen Freedland5, Julia Reid2, Gabrielle Fisher1, Gerry Lanchbury2, Alexander Gutin2, Steven Stone2, Peter Carroll3, Jack Cuzick1
1Queen Mary University of London, London, UK, 2Myriad Genetic Laboratories, Salt Lake City, USA, 3University of California, San Francisco, USA, 4University of Texas Health Science Center at San Antonio, San Antonio, USA, 5Duke University Medical Center and Durham VA Medical Center, Durham, USA

Background

The natural history of prostate cancer is highly variable and difficult to predict. Improved tools are needed to match treatment to a patient's risk of progression. We developed an expression signature composed of genes involved in cell cycle progression (Prolaris) and tested its utility in prostate cancer.

Method

We developed an expression signature composed of 31 cell cycle progression and 15 housekeeper genes. An expression score (Prolaris score) was derived as the mean of all cell cycle progression genes. The signature was tested at disease diagnosis in two conservatively managed cohorts (N=337 and 349), after radical prostatectomy in two cohorts from the U.S. (N=366 and 413), and after external beam radiation therapy (N=141). All studies were retrospective.

Results

The CCP signature was a highly significant predictor of outcome in all five studies. In conservatively managed patients, the Prolaris score was the dominant variable for predicting death from prostate cancer in univariate analysis (p = 6.1 x 10-22 after diagnosis by TURP, and p = 8.6 x 10-10 after diagnosis by needle biopsy). In both studies, the Prolaris score remained highly significant in multivariate analysis making it a stronger predictor of disease-specific mortality than other prognostic variables. After prostatectomy, Prolaris predicted biochemical recurrence (BCR) in univariate analysis (S&W p = 5.6 x 10-9; UCSF p= 2.23 x 10-6) and provided additional prognostic information in multivariate analysis (S&W p = 3.3 x10-6; UCSF 9.5 x10-5). After radiation therapy, Prolaris predicted BCR in univariate (p=0.0017) and multivariate analysis (p=0.034). In all five studies the HR per unit change in the Prolaris score was remarkably similar, ranging from 1.89 to 2.92, indicating that the effect size for the Prolaris score is robust to clinical setting and patient composition.

Conclusion

The Prolaris test predicts prostate cancer outcome in multiple patient cohorts and diverse clinical settings. In all cases, it provides information beyond clinicopathologic variables to help differentiate aggressive from indolent disease.

References

1. Prognostic value of a cell cycle progression signature for prostate cancer death in a conservatively managed needle biopsy cohort. BJC. 2012 Mar 13;106(6):1095-9. 2. Prognostic value of an RNA expression signature derived from cell cycle proliferation genes in patients with prostate cancer: a retrospective study. Lancet Oncol. 2011 Mar;12(3):245-55. 3.Prognostic utility of cell cycle progression score in men with prostate cancer after primary external beam radiation therapy. IJROBP. 2013 1;86(5):848-53 4. Validation of a cell-cycle progression gene panel to improve risk stratification in a contemporary prostatectomy cohort. JCO 2013 Apr 10;31(11):1428-34.