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.

Purpose. To further validate the prognostic power of the biomarker PDE4D7, we investigated the correlation of PDE4D7 scores adjusted for presurgical clinical variables with longitudinal postsurgical biological outcomes. Methods. RNA was extracted from biopsy punches of resected tumors (550 patients; RP cohort) and diagnostic needle biopsies (168 patients; DB cohort). Cox regression and survival were applied to correlate PDE4D7 scores with patient outcomes. Logistic regression was used to combine the clinical CAPRA score with PDE4D7. Results. In univariate analysis, the PDE4D7 score was significantly associated with PSA recurrence after prostatectomy in both studied patient cohorts' analysis (HR 0.53; 95% CI 0.41-0.67; p<1.0E-04 and HR 0.47; 95% CI 0.33-0.65; p<1.0E-04, respectively). After adjustment for the presurgical clinical variables preoperative PSA, PSA density, biopsy Gleason, clinical stage, percentage tumor in the biopsy (data only available for RP cohort), and percentage of positive biopsies, the HR was 0.49 (95% CI 0.38-0.64; p<1.0E-04) and 0.43 (95% CI 0.29-0.63; p<1.0E-04), respectively. The addition of the PDE4D7 to the clinical CAPRA score increased the AUC by 5% over the CAPRA score alone (0.82 versus 0.77; p=0.004). This combination model stratified 14.6% patients of the DB cohort to no risk of biochemical relapse (NPV 100%) over a follow-up period of up to 15 years. Conclusions. The PDE4D7 score provides independent risk information for pretreatment risk stratification. Combining CAPRA with PDE4D7 scores significantly improved the clinical risk stratification before surgery.

e15606 Background: Precision medicine refers to tailoring of treatment to each individual patient, although identifying tumor driving signaling pathways (SP) that are functionally active is still a challenge. OncoSignal pathway tests quantitatively measure activity of SP such as estrogen receptor (ER), androgen receptor (AR), PI3K, MAPK, Hedgehog (HH), TGF-β, Notch on fresh frozen and formalin-fixed paraffin-embedded (FFPE) tissue samples. OncoSignal pathway analysis aimed at assessing clinically actionable SP and retrospectively predicting targeted drug response on a series of patients’ (pts) samples from the MOSCATO trial run at Gustave Roussy. Methods: OncoSignal pathway analysis (ER, AR, PI3K, MAPK, HH, Notch, TGF-β) was performed blinded by Molecular Pathway Dx (Philips, Eindhoven) on metastatic tumor tissue samples from breast cancer (BC), prostate (PC), and high grade serous ovarian cancers (OC). Using Affymetrix expression array data from public GEO datasets, SP activity was analyzed in healthy prostate, breast, and ovarian tissue to define abnormal SP activity thresholds for tumor tissue pathway analysis. For each individual sample, SP alterations were considered tumor driving SP if sample SP activity exceeded the 95th percentile of SP activity within healthy tissue. Results by OncoSignal were also combined with clinical characteristics and molecular alterations identified in the MOSCATO trial. Results: Identified tumor driving SP were ER, AR, MAPK-AP1, HH, PI3K pathway in BC (n = 5), AR in PC (n = 30); AP1, Notch, TGFβ in OC (n = 17). OncoSignal identified clinically actionable tumor driving pathways in all BC samples (median tumor cellularity [MTC]: 40%, range 15-80%); 30/31 PC samples (MTC: 62%, range 25-90%), 16/17 OC samples (MTC 62%, range 15-80%). Actionable mutations were previously identified in 4/5 BC; 13/31 PC; 6/17 OC. Seven pts with BC and PC were treated with targeted therapy. OncoSignal pathway analysis correctly predicted response/resistance in 4 of these pts (57%). Conclusions: OncoSignal pathway analysis correctly identified SP activity alterations and predicted targeted drug response in this series of patients. OncoSignal will be further validated prospectively in precision medicine studies at Gustave Roussy in which patients are stratified for targeted treatment by mutation analysis.