Abstract PR09: Prostate cancer prognostication based on an actionable metabolic pathway

Abstract

Abstract Background: We recently discovered that mRNA expression of SQLE, coding for squalene monooxygenase, the second rate-limiting enzyme of cholesterol synthesis, is associated with lethality after prostate cancer diagnosis. Here, we investigate how expression of SQLE and other key regulators of cholesterol homeostasis, identified by prior mechanistic studies, aid risk prediction for lethal prostate cancer. Methods: The Health Professionals Follow-up Study and the Physicians' Health Study prostate cancer tissue cohorts collected tissue from prostatectomy or transurethral resection of the prostate at cancer diagnosis. Whole-transcriptome profiling was performed. The outcome of interest was lethal cancer defined as prostate cancer mortality or development of metastases in contrast to non-lethal cancer without evidence of metastases after at least eight years of follow up. Discrimination for prostate lethal cancer was assessed by comparing c-statistics using bootstrap resampling. Results: Combining both cohorts, 112 men had lethal prostate cancer; 290 men had non-lethal cancer. A prognostic model for lethal cancer including Gleason grade, pathologic stage, age, and year of diagnosis had a high c = 0.885; adding body mass index, smoking status, family history of prostate cancer, and diabetes diagnosis increased c to 0.889. A model containing only SQLE (linear) achieved c = 0.663. Adding SQLE to the fully adjusted model increased c to 0.903 (p = 0.027). None of the other cholesterol regulators ABCA1, ACAT1, LDLR, and SCARB1 improved discrimination. Conclusions: SQLE performs well as a single biomarker of prostate cancer lethality after primary therapy, in contrast to other markers of intratumoral cholesterol regulation. Improvements in prognostication are minimal when SQLE is added to a model that contains a centrally re-reviewed Gleason grade. Most importantly, SQLE may be an actionable, predictive biomarker of benefit from statin therapy, which addresses the cholesterol synthesis pathway regulated by SQLE. Citation Format: Konrad H. Stopsack, Travis A. Gerke, Lorelei A. Mucci, Jennifer R. Rider. Prostate cancer prognostication based on an actionable metabolic pathway. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR09.