Presentation Authors: Michael Kiebish, Boston, MA, Jennifer Cullen, Prachi Mishra*, Alagarsamy Srinivasan, Inger Rosner, David McLeod, Rockville, MD, Amina Ali, Bethesda, MD, Leonardo Rodrigues, Viatcheslav Akmaev, Rangaprasad Sarangarajan, Niven Narain, Boston, MA, Albert Dobi, Shiv Srivastava, Rockville, MD
Introduction: Predicting the clinical course of prostate cancer is challenging due to the wide biological spectrum of the disease. Development of prognostic panels that include multiple type of analytes requires sensitive and reproducible detection methods and advanced bioinformatics platforms. The objective of our study was to identify prostate cancer prognostic markers employing an advanced multi-omics discovery platform.
Methods: Pre-surgery serum samples were evaluated among a longitudinally followed (median 10 years), racially diverse prostate cancer patient group (N=385). Samples were analyzed by mass spectrometry including proteomic, metabolomic and lipidomic (multi-omics analyses) to differentiate disease progression-free patients (N=310) from patients with disease progression (N=75) through regression and Bayesian computational approaches.
Results: The integration of disease progression data with multi-omics profiles identified the combined predictive performance of two proteins (Tenascin C and Apolipoprotein AIV), a metabolite (1-Methyladenosine) and a phospholipid molecular species (phosphatidic acid PA 18:0-22:0) with a cumulative performance of AUC= 0.78 for differentiating patients with progression-free survival from patients with disease progression. The combination of two clinical features, pathological measurement of T-Stage and Gleason score, along with molecular analytes further increased the AUC to 0.89 with a NPV of 0.96 and an odds ratio of 12.4.
Conclusions: We identified a panel of multi-analytes and clinical features with robust performance in predicting progression-free disease survival of patients with prostate cancer by evaluating pre-surgery serum samples. This panel offers new opportunities with potential impact on primary treatment and surveillance strategies.
Source of Funding: This research was supported by the USUHS-CPDR fund (HU0001-10-2-0002) to I.L.R. and S.S.; P.M. was the recipient of the Colonel (Ret.) David G. McLeod Prostate Cancer Research Fellowship supported by Berg Health.