Urine TMPRSS2:ERG Plus PCA3 for Individualized Prostate Cancer Risk Assessment

Abstract

Background

TMPRSS2:ERG (T2:ERG) and prostate cancer antigen 3 (PCA3) are the most advanced urine-based prostate cancer (PCa) early detection biomarkers.

Objective

Validate logistic regression models, termed Mi-Prostate Score (MiPS), that incorporate serum prostate-specific antigen (PSA; or the multivariate Prostate Cancer Prevention Trial risk calculator version 1.0 [PCPTrc]) and urine T2:ERG and PCA3 scores for predicting PCa and high-grade PCa on biopsy.

Design, setting, and participants

T2:ERG and PCA3 scores were generated using clinical-grade transcription-mediated amplification assays. Pretrained MiPS models were applied to a validation cohort of whole urine samples prospectively collected after digital rectal examination from 1244 men presenting for biopsy.

Outcome measurements and statistical analysis

Area under the curve (AUC) was used to compare the performance of serum PSA (or the PCPTrc) alone and MiPS models. Decision curve analysis (DCA) was used to assess clinical benefit.

Results and limitations

Among informative validation cohort samples (n = 1225 [98%], 80% from patients presenting for initial biopsy), models incorporating T2:ERG had significantly greater AUC than PSA (or PCPTrc) for predicting PCa (PSA: 0.693 vs 0.585; PCPTrc: 0.718 vs 0.639; both p < 0.001) or high-grade (Gleason score >6) PCa on biopsy (PSA: 0.729 vs 0.651, p < 0.001; PCPTrc: 0.754 vs 0.707, p = 0.006). MiPS models incorporating T2:ERG score had significantly greater AUC (all p < 0.001) than models incorporating only PCA3 plus PSA (or PCPTrc or high-grade cancer PCPTrc [PCPThg]). DCA demonstrated net benefit of the MiPS_PCPTrc (or MiPS_PCPThg) model compared with the PCPTrc (or PCPThg) across relevant threshold probabilities.

Conclusions

Incorporating urine T2:ERG and PCA3 scores improves the performance of serum PSA (or PCPTrc) for predicting PCa and high-grade PCa on biopsy.

Patient summary

Incorporation of two prostate cancer (PCa)-specific biomarkers (TMPRSS2:ERG and PCA3) measured in the urine improved on serum prostate-specific antigen (or a multivariate risk calculator) for predicting the presence of PCa and high-grade PCa on biopsy. A combined test, Mi-Prostate Score, uses models validated in this study and is clinically available to provide individualized risk estimates.

Introduction

Approximately 1 million men undergo prostate biopsy each year in the United States, most for elevated serum prostate-specific antigen (PSA or KLK3). Serum PSA's lack of prostate cancer (PCa) specificity, the unclear benefits of PSA screening for reducing PCa deaths, and the harms of overdiagnosing indolent disease have called PSA screening into question [1], [2], [3]. Although aggressive PCa-specific biomarkers may eventually replace serum PSA, at present, methods to individualize management of elevated PSA are needed. Such approaches include multivariate risk models, such as the Prostate Cancer Prevention Trial risk calculator (PCPTrc), which includes serum PSA and clinical factors [4], [5], [6]. Likewise, multiple PSA derivatives and other related kallikreins have been advanced as early detection biomarkers, including free PSA and [−2]proPSA (both of which are incorporated, with total PSA, in the Prostate Health Index [PHI]), with free PSA and PHI approved by the US Food and Drug Administration (FDA) for PCa risk estimation in men with serum PSA of 4–10 ng/ml [7], [8], [9]. Similarly, a panel of free and total PSA, single-chain intact PSA, and a related kallikrein (KLK2) outperforms serum PSA alone for predicting PCa on biopsy, and a test incorporating these kallikreins along with clinical parameters (4Kscore) is available [7], [9].

An alternative to using tissue-specific biomarkers, such as serum PSA and other kallikreins, for predicting the presence of PCa is to utilize PCa-specific biomarkers. Prostate cancer antigen 3 (PCA3; a noncoding RNA) and TMPRSS2:ERG (T2:ERG) gene fusions are the most advanced PCa-specific early detection biomarkers [10], [11], [12], [13]. In tissues, both biomarkers show markedly improved PCa specificity compared with PSA or derivatives or related kallikreins [12], [14], [15]. In addition, both PCA3 and T2:ERG transcripts are detectable and quantifiable in urine collected after digital rectal examination (DRE) [10], [11], [12], [13]. The Progensa PCA3 test (Hologic Inc, Bedford, MA, USA), which reports a quantitative PCA3 score using a transcription-mediated amplification (TMA) assay, has been extensively studied as a urine-based PCa biomarker [11], [12], [13] and is FDA approved for estimating PCa risk following a negative biopsy.

Previously, we reported the development and application of a clinical-grade TMA assay for quantifying T2:ERG messenger RNA (mRNA), which generates a T2:ERG score by normalizing urine T2:ERG mRNA to urine PSA mRNA (to control for prostate cell and mRNA abundance) [16]. This assay is based on the same technology as the Progensa PCA3 test and can be performed on the same post-DRE whole urine sample. Previously, we applied initial T2:ERG TMA assay versions to post-DRE whole urine from 1312 men presenting for biopsy or prostatectomy at multiple centers [16]. More recently, we and others have evaluated the performance of a final clinical-grade T2:ERG TMA assay [17], [18], [19], [20]. In this study, we evaluated pretrained multivariate regression models combining urine T2:ERG and/or PCA3 scores with serum PSA (or the PCPTrc) in a large independent validation cohort to develop methods for individualized PCa risk estimates.