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Prostate Cancer
Volume 2019, Article ID 8107807, 14 pages
Research Article

The Association of the Long Prostate Cancer Expressed PDE4D Transcripts to Poor Patient Outcome Depends on the Tumour’s TMPRSS2-ERG Fusion Status

1Philips Research Europe, 5656AE Eindhoven, Netherlands
2Gerhard-Domagk-Institute of Pathology, University Hospital Münster, 48149 Münster, Germany
3Prostate Center, University Hospital Münster, 48149 Münster, Germany
4Institute of Cardiovascular and Medical Science, University of Glasgow, G12 8TA Glasgow, Scotland, UK
5Institute of Pharmaceutical Science, King’s College London, 150 Stamford Street, London, WC2R 2LS London, UK
6Mironid Ltd, BioCity Scotland, ML1 5UH Newhouse, Scotland, UK
7Department of Urology, 3000CA Erasmus Medical Center, Rotterdam, Netherlands

Correspondence should be addressed to Ralf Hoffmann; moc.spilihp@nnamffoh.flar

Received 27 January 2019; Revised 10 April 2019; Accepted 21 April 2019; Published 2 June 2019

Guest Editor: Anna Ferrari

Copyright © 2019 Dianne van Strijp et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Objectives. To investigate the added value of assessing transcripts for the long cAMP phosphodiesterase-4D (PDE4D) isoforms, PDE4D5 and PDE4D9, regarding the prognostic power of the ‘CAPRA & PDE4D7’ combination risk model to predict longitudinal postsurgical biological outcomes in prostate cancer. Patients and Methods. RNA was extracted from both biopsy punches of resected tumours (606 patients; RP cohort) and diagnostic needle biopsies (168 patients; DB cohort). RT-qPCR was performed in order to determine PDE4D5, PDE4D7, and PDE4D9 transcript scores in both study cohorts. By RNA sequencing, we determined the TMPRSS2-ERG fusion status of each tumour sample in the RP cohort. Kaplan-Meier survival analyses were then applied to correlate the PDE4D5, PDE4D7 and PDE4D9 scores with postsurgical patient outcomes. Logistic regression was then used to combine the clinical CAPRA score with PDE4D5, PDE4D7, and PDE4D9 scores in order to build a ‘CAPRA & PDE4D5/7/9’ regression model. ROC and decision curve analysis was used to estimate the net benefit of the ‘CAPRA & PDE4D5/7/9’ risk model. Results. Kaplan-Meier survival analysis, on the RP cohort, revealed a significant association of the PDE4D7 score with postsurgical biochemical recurrence (BCR) in the presence of the TMPRSS2-ERG gene rearrangement (logrank p<0.0001), compared to the absence of this gene fusion event (logrank p=0.08). In contrast, the PDE4D5 score was only significantly associated with BCR in TMPRSS2-ERG fusion negative tumours (logrank p<0.0001 vs. logrank p=0.4 for TMPRSS2-ERG+ tumours). This was similar for the PDE4D9 score although less pronounced compared to that of the PDE4D5 score (TMPRSS2ERG- logrank p<0.0001 vs. TMPRSS2ERG+ logrank p<0.005). In order to predict BCR after primary treatment, we undertook ROC analysis of the logistic regression combination model of the CAPRA score with the PDE4D5, PDE4D7, and PDE4D9 scores. For the DB cohort, this demonstrated significant differences in the AUC between the CAPRA and the PDE4D5/7/9 regression model vs. the CAPRA and PDE4D7 risk model (AUC 0.87 vs. 0.82; p=0.049) vs. the CAPRA score alone (AUC 0.87 vs. 0.77; p=0.005). The CAPRA and PDE4D5/7/9 risk model stratified 19.2% patients of the DB cohort to either ‘no risk of biochemical relapse’ (NPV 100%) or the ‘start of any secondary treatment (NPV 100%)’, over a follow-up period of up to 15 years. Decision curve analysis presented a clear, net benefit for the use of the novel CAPRA & PDE4D5/7/9 risk model compared to the clinical CAPRA score alone or the CAPRA and PDE4D7 model across all decision thresholds. Conclusion. Association of the long PDE4D5, PDE4D7, and PDE4D9 transcript scores to prostate cancer patient outcome, after primary intervention, varies in opposite directions depending on the TMPRSS2-ERG genomic fusion background of the tumour. Adding transcript scores for the long PDE4D isoforms, PDE4D5 and PDE4D9, to our previously presented combination risk model of the combined ‘CAPRA & PDE4D7’ score, in order to generate the CAPRA and PDE4D5/7/9 score, significantly improves the prognostic power of the model in predicting postsurgical biological outcomes in prostate cancer patients.