Marcia Alves de Inda1, Dianne van Strijp1, Eveline den Biezen-Timmermans1, Anne van Brussel1, Janneke Wrobel1, Hans van Zon1, Pieter Vos1, George S Baillie2, Pierre Tennstedt3, Thorsten Schlomm3, Miles D Houslay4, Chris Bangma5, Ralf Hoffmann6. 1. Philips Research Europe, High Tech Campus, Eindhoven, The Netherlands. 2. Institute of Cardiovascular and Medical Science, University of Glasgow, Glasgow, Scotland, UK. 3. Martini-Klinik Prostate Cancer Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 4. Institute of Pharmaceutical Science, King's College London, London, UK; Mironid Ltd, BioCity Scotland, Newhouse, Scotland, UK. 5. Department of Urology, Erasmus Medical Center, Rotterdam, The Netherlands. 6. Philips Research Europe, High Tech Campus, Eindhoven, The Netherlands; Institute of Cardiovascular and Medical Science, University of Glasgow, Glasgow, Scotland, UK. Electronic address: ralf.hoffmann@philips.com.
Abstract
BACKGROUND: The clinical metrics used to date to assess the progression risk of newly diagnosed prostate cancer patients only partly represent the true biological aggressiveness of the underlying disease. OBJECTIVE: Validation of the prognostic biomarker phosphodiesterase-4D7 (PDE4D7) in predicting longitudinal biological outcomes in a historical surgery cohort to improve postsurgical risk stratification. DESIGN, PATIENTS, AND METHODS: RNA was extracted from biopsy punches of resected tumors from 550 patients. PDE4D7 was quantified using one-step quantitative reverse transcription-polymerase chain reaction. PDE4D7 scores were calculated by normalization of PDE4D7 to reference genes. Multivariate analyses were adjusted for clinical prognostic variables. Outcomes tested were: prostate-specific antigen relapse, start of salvage treatment, progression to metastases, overall mortality, and prostate cancer-specific mortality. The PDE4D7 score was combined with the clinical risk model Cancer of the Prostate Risk Assessment Postsurgical Score (CAPRA-S) using multivariate regression modeling; the combined score was tested in post-treatment progression free survival prediction. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Correlations with outcomes were analyzed using multivariate Cox regression and logistic regression statistics. RESULTS AND LIMITATIONS: The PDE4D7 score was significantly associated with time-to-prostate specific antigen failure after prostatectomy (hazard ratio [HR]: 0.53, 95% confidence interval [CI]: 0.41-0.67 for each unit increase, p<0.0001). After adjustment for postsurgical prognostic variables the HR was 0.56 (95% CI: 0.43-0.73, p<0.0001). The PDE4D7 score remained significant after adjusting the multi-variate analysis for the CAPRA-S model categories (HR=0.54, 95% CI=0.42-0.69, p<0.0001). Combination of the PDE4D7 score with the CAPRA-S demonstrated a significant incremental value of 4-6% in 2-yr (p=0.004) or 5-yr (p=0.003) prediction of progression free survival after surgery. The combined model of PDE4D7 and CAPRA-S improves patient selection with very high risk of fast disease relapse after primary intervention. CONCLUSIONS: The PDE4D7 score has the potential to provide independent risk information and to restratify patients with clinical intermediate- to high-risk characteristics to a very low-risk profile. PATIENT SUMMARY: In this report, we studied the potential of a novel biomarker to predict outcomes of a cohort of prostate cancer patients who underwent surgery more than 10 yr ago. We found that a gene called phosphodiesterase-4D7 added extra information to the available clinical data. We conclude that the measurement of this gene in tumor tissue may contribute to more effective treatment decisions.
BACKGROUND: The clinical metrics used to date to assess the progression risk of newly diagnosed prostate cancerpatients only partly represent the true biological aggressiveness of the underlying disease. OBJECTIVE: Validation of the prognostic biomarker phosphodiesterase-4D7 (PDE4D7) in predicting longitudinal biological outcomes in a historical surgery cohort to improve postsurgical risk stratification. DESIGN, PATIENTS, AND METHODS: RNA was extracted from biopsy punches of resected tumors from 550 patients. PDE4D7 was quantified using one-step quantitative reverse transcription-polymerase chain reaction. PDE4D7 scores were calculated by normalization of PDE4D7 to reference genes. Multivariate analyses were adjusted for clinical prognostic variables. Outcomes tested were: prostate-specific antigen relapse, start of salvage treatment, progression to metastases, overall mortality, and prostate cancer-specific mortality. The PDE4D7 score was combined with the clinical risk model Cancer of the Prostate Risk Assessment Postsurgical Score (CAPRA-S) using multivariate regression modeling; the combined score was tested in post-treatment progression free survival prediction. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Correlations with outcomes were analyzed using multivariate Cox regression and logistic regression statistics. RESULTS AND LIMITATIONS: The PDE4D7 score was significantly associated with time-to-prostate specific antigenfailure after prostatectomy (hazard ratio [HR]: 0.53, 95% confidence interval [CI]: 0.41-0.67 for each unit increase, p<0.0001). After adjustment for postsurgical prognostic variables the HR was 0.56 (95% CI: 0.43-0.73, p<0.0001). The PDE4D7 score remained significant after adjusting the multi-variate analysis for the CAPRA-S model categories (HR=0.54, 95% CI=0.42-0.69, p<0.0001). Combination of the PDE4D7 score with the CAPRA-S demonstrated a significant incremental value of 4-6% in 2-yr (p=0.004) or 5-yr (p=0.003) prediction of progression free survival after surgery. The combined model of PDE4D7 and CAPRA-S improves patient selection with very high risk of fast disease relapse after primary intervention. CONCLUSIONS: The PDE4D7 score has the potential to provide independent risk information and to restratify patients with clinical intermediate- to high-risk characteristics to a very low-risk profile. PATIENT SUMMARY: In this report, we studied the potential of a novel biomarker to predict outcomes of a cohort of prostate cancerpatients who underwent surgery more than 10 yr ago. We found that a gene called phosphodiesterase-4D7 added extra information to the available clinical data. We conclude that the measurement of this gene in tumor tissue may contribute to more effective treatment decisions.
Authors: Dianne van Strijp; Christiane de Witz; Birthe Heitkötter; Sebastian Huss; Martin Bögemann; George S Baillie; Miles D Houslay; Chris Bangma; Axel Semjonow; Ralf Hoffmann Journal: Prostate Cancer Date: 2019-06-02
Authors: Dianne van Strijp; Christiane de Witz; Pieter C Vos; Eveline den Biezen-Timmermans; Anne van Brussel; Janneke Wrobel; George S Baillie; Pierre Tennstedt; Thorsten Schlomm; Birthe Heitkötter; Sebastian Huss; Martin Bögemann; Miles D Houslay; Chris Bangma; Axel Semjonow; Ralf Hoffmann Journal: Prostate Cancer Date: 2018-07-26