Abstract 2259: Prostate cancer molecular subtype impacts interpretation of clinical parameters

Abstract

Abstract Background: Molecular characterization of prostate cancer has revealed distinct subtypes with underlying genomic alterations. One of these core subtypes (SPOP mutant prostate cancer) has previously only been identifiable through DNA sequencing, making the impact on prognosis and routinely utilized risk stratification parameters unclear. We aimed to identify prostate cancer molecular subtypes from transcriptional data alone and determine associations with clinicopathologic outcomes and long-term prognosis. Methods: We developed a novel gene expression signature, classifier (SCaPT), and decision tree to predict SPOP mutant subclass from RNA gene expression data and classify common prostate cancer molecular subtypes. We then validated and further interrogated the association of prostate cancer molecular subtypes with pathologic and clinical outcomes in retrospective and prospective cohorts of 8,158 patients. Associations with clinicopathologic variables, metastasis-free and prostate cancer-specific survival were the main outcomes. Findings: The SCaPT model prediction showed high sensitivity and specificity in multiple cohorts across both RNA-seq and microarray gene expression platforms. We predicted 8~9% of cases to be SPOP mutant from both retrospective and prospective cohorts. Surprisingly, we found routine clinical risk factors were disconjugate when molecular subtype was considered. The SPOP mutant subclass was associated with lower frequency of positive margins, extraprostatic extension, and seminal vesicle invasion at prostatectomy. However, SPOP mutant cancers were associated with higher pretreatment serum prostate-specific antigen (PSA). The association between SPOP mutant status and higher PSA level was validated in three independent cohorts. Despite high pre-treatment PSA, the SPOP mutant subtype was associated with a favorable prognosis with improved metastasis-free survival, particularly in patients with “high-risk” preoperative PSA levels. Interpretation: Using a novel gene expression signature to assign the SPOP mutant subclass and a decision tree algorithm to define prostate cancer molecular subclasses, we found the SPOP mutant subclass associated with higher preoperative PSA, less adverse pathological features, and favorable prognosis. These findings suggest a paradigm where interpretation of common risk stratification parameters, particularly PSA, must be modified to account for the molecular subtype of prostate cancer. Citation Format: Deli Liu. Prostate cancer molecular subtype impacts interpretation of clinical parameters [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2259.