Abstract: PD65-03
Sources of Funding: None

Introduction

Genomic testing is used with increasing frequency as part of a personalized approach to managing prostate cancer. Decipher is one such test that analyzes the expression of 22 RNA biomarkers from archival prostate tissue and predicts risk of metastatic progression and prostate cancer specific mortality. The company also provides microarray analysis to characterize additional markers from the Decipher Genomic Resource Information Database (GRID) that have been implicated in prostate cancer. Traditionally, adverse pathologic features at prostatectomy have been used to predict risk of biochemical recurrence and guide adjuvant therapy after prostatectomy, but it is not clear to what extent these features correlate with genetic markers of disease aggressiveness. In this study, we sought to determine patterns of biomarker expression in African Americans, who are at higher risk of developing aggressive prostate cancer, and whether these biomarkers correlate with adverse pathologic features at prostatectomy.

Methods

We ran the Decipher test retrospectively on radical prostatectomy specimens obtained between December 2008 and April 2016 from a cohort of 72 African American men at a single institution. Data obtained included Decipher GRID expression levels of additional RNA biomarkers as well as the pathologic features at prostatectomy of each specimen. Fisher's Exact Test analysis was used to determine correlations between biomarkers and the following pathologic features: perineural invasion (PNI), extraprostatic extension (EPE), seminal vesical invasion (SVI), lymphovascular invasion (LVI), and margin positivity.

Results

The most common biomarkers expressed were SPINK1 (37.5%, n=27), ERG (18.1%, n=13), NKX3 (13.95, n=10), and PCA3 (11.1%, n=8). The triple negative genotype (ERG-/ETS-/_x000D_ SPINK-) was 38.9% (n=28). There were no statistically significant relationships between any biomarker expression levels and pathologic features associated with aggressive prostate cancer. PCA3 did show a nonsignificant association with LVI (p = 0.09). _x000D_

Conclusions

Our study employed one of the largest African American cohorts to date and failed to show a relationship between adverse pathologic features and the RNA expression patterns of markers implicated in prostate cancer. Further studies are necessary to determine the impact of these abnormal expression patterns on clinical outcomes and whether they are better predictors of disease recurrence than traditional clinicopathologic variables.

Funding

None