KLK3, PCA3, and TMPRSS2-ERG expression in the peripheral blood mononuclear cell fraction from castration-resistant prostate cancer patients and response to docetaxel treatment.

BACKGROUND: To monitor systemic disease activity, the potential of circulating tumor cells (CTCs) bears great promise. As surrogate for CTCs we measured KLK3, PCA3, and TMPRSS2-ERG messenger RNA (mRNA) in the peripheral blood mononuclear cell (PBMC) fraction from a castration-resistant prostate cancer (CRPC) patient cohort and three control groups. Moreover, biomarker response to docetaxel treatment was evaluated in the patient group. METHODS: Blood samples from 20 CRPC patients were analyzed at four different time points (prior to docetaxel treatment, at 9 weeks, 27 weeks, and 2 months after treatment). Blood was drawn once from three control groups (10 age-matched men, 10 men under 35 years of age, 12 women). All samples were analyzed for KLK3, PCA3, and TMPRSS2-ERG mRNA by using a quantitative nucleic acid amplification assay with gene-specific primers in the complementary DNA synthesis. RESULTS: At baseline, mRNA for KLK3 was detected in 17 (89%, 95% CI 76-100%), PCA3 in 10 (53%, 95% CI 30-75%), and TMPRSS2-ERG in seven of 19 evaluable patients (37%, 95% CI 15-59%). In contrast, the blood samples from all 32 healthy volunteers were reproducible negative for all markers. In response to docetaxel treatment, KLK3 levels decreased in 80% (95% CI 60-100%), PCA3 in 89% (95% CI 68-100%), and TMPRSS2-ERG in 86% (95% CI 60-100%) of patients. CONCLUSIONS: The feasibility of a highly sensitive modified nucleic acid amplification assay to assess KLK3, PCA3, and TMPRSS2-ERG mRNA in the PBMC fraction from CRPC patients was demonstrated. Moreover, response of these markers to systemic treatment was shown.

Prostate cancer biomarker profiles in urinary sediments and exosomes.

PURPOSE: Urinary biomarker tests for diagnosing prostate cancer have gained considerable interest. Urine is a complex mixture that can be subfractionated. We evaluated 2 urinary fractions that contain nucleic acids, ie cell pellets and exosomes. The influence of digital rectal examination before urine collection was also studied and the prostate cancer specific biomarkers PCA3 and TMPRSS2-ERG were assayed. MATERIALS AND METHODS: Urine samples were prospectively obtained before and after digital rectal examination from 30 men scheduled for prostate biopsy. Cell pellet and exosomes were isolated and used for biomarker analysis. Analytical and diagnostic performance was tested using the Student t-test and ROC curves. RESULTS: Unlike the exosome fraction, urinary sediment gene expression analysis was compromised by amorphous precipitation in 10% of all specimens. Digital rectal examination resulted in increased mRNA levels in each fraction. This was particularly relevant for the exosomal fraction since after digital rectal examination the number of samples decreased in which cancer specific markers were below the analytical detection limit. Biomarker diagnostic performance was comparable to that in large clinical studies. In exosomes the biomarkers had to be normalized for prostate specific antigen mRNA while cell pellet absolute PCA3 levels had diagnostic value. CONCLUSIONS: Exosomes have characteristics that enable them to serve as a stable substrate for biomarker analysis. Thus, digital rectal examination enhances the analytical performance of biomarker analysis in exosomes and cell pellets. The diagnostic performance of biomarkers in exosomes differs from that of cell pellets. Clinical usefulness must be prospectively assessed in larger clinical cohorts.

Value of PCA3 to predict biopsy outcome and its potential role in selecting patients for multiparametric MRI.

PCA3 (prostate cancer gene 3) and multiparametric 3 tesla MRI are new promising diagnostic tools in the detection of PCa. Our aim was to study the clinical value of the Progensa PCA3-test: its predictive value for biopsy outcome, Gleason score and MRI outcome. We evaluated, retrospectively, 591 patients who underwent a Progensa PCA3-test at the Radboud University Nijmegen Medical Centre between May 2006 and December 2009. Prostate biopsies were performed in 290 patients; a multiparametric 3 tesla MRI of the prostate was performed in 163/591 patients. The PCA3-score was correlated to biopsy results and MRI outcome. The results show that PCA3 was highly predictive for biopsy outcome (p < 0.001); there was no correlation with the Gleason score upon biopsy (p = 0.194). The PCA3-score of patients with a suspicious region for PCa on MRI was significantly higher (p < 0.001) than in patients with no suspicious region on MRI (52 vs. 21). In conclusion, PCA3 is a valuable diagnostic biomarker for PCa; it did not correlate with the Gleason score. Furthermore, multiparametric MRI outcome was significantly correlated with the PCA3-score. Thus, PCA3 could be used to select patients that require MRI. However, in patients with a negative PCA3 and high clinical suspicion of PCa, a multiparametric MRI should also be done.

Detection of High-grade Prostate Cancer Using a Urinary Molecular Biomarker-Based Risk Score.

BACKGROUND: To reduce overdiagnosis and overtreatment, a test is urgently needed to detect clinically significant prostate cancer (PCa). OBJECTIVE: To develop a multimodal model, incorporating previously identified messenger RNA (mRNA) biomarkers and traditional risk factors that could be used to identify patients with high-grade PCa (Gleason score ≥7) on prostate biopsy. DESIGN, SETTING, AND PARTICIPANTS: In two prospective multicenter studies, urine was collected for mRNA profiling after digital rectal examination (DRE) and prior to prostate biopsy. The multimodal risk score was developed on a first cohort (n=519) and subsequently validated clinically in an independent cohort (n=386). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The mRNA levels were measured using reverse transcription quantitative polymerase chain reaction. Logistic regression was used to model patient risk and combine risk factors. Models were compared using the area under the curve (AUC) of the receiver operating characteristic, and clinical utility was evaluated with a decision curve analysis (DCA). RESULTS AND LIMITATIONS: HOXC6 and DLX1 mRNA levels were shown to be good predictors for the detection of high-grade PCa. The multimodal approach reached an overall AUC of 0.90 (95% confidence interval [CI], 0.85-0.95) in the validation cohort (AUC 0.86 in the training cohort), with the mRNA signature, prostate-specific antigen (PSA) density, and previous cancer-negative prostate biopsies as the strongest, most significant components, in addition to nonsignificant model contributions of PSA, age, and family history. For another model, which included DRE as an additional risk factor, an AUC of 0.86 (95% CI, 0.80-0.92) was obtained (AUC 0.90 in the training cohort). Both models were successfully validated, with no significant change in AUC in the validation cohort, and DCA indicated a strong net benefit and the best reduction in unnecessary biopsies compared with other clinical decision-making tools, such as the Prostate Cancer Prevention Trial risk calculator and the PCA3 assay. CONCLUSIONS: The risk score based on the mRNA liquid biopsy assay combined with traditional clinical risk factors identified men at risk of harboring high-grade PCa and resulted in a better patient risk stratification compared with current methods in clinical practice. Therefore, the risk score could reduce the number of unnecessary prostate biopsies. PATIENT SUMMARY: This study evaluated a novel urine-based assay that could be used as a noninvasive diagnostic aid for high-grade prostate cancer (PCa). When results of this assay are combined with traditional clinical risk factors, risk stratification for high-grade PCa and biopsy decision making are improved.

Identification of a Candidate Gene Panel for the Early Diagnosis of Prostate Cancer.

PURPOSE: Serum PSA (sPSA) testing has led to the identification of patients with indolent prostate cancer, and inevitably overtreatment has become a concern. Progensa PCA3 urine testing was shown to improve the diagnosis of prostate cancer, but its diagnostic value for aggressive prostate cancer is limited. Therefore, urinary biomarkers that can be used for prediction of Gleason score ≥7 prostate cancer in biopsies are urgently needed. EXPERIMENTAL DESIGN: Using gene expression profiling data, 39 prostate cancer biomarkers were identified. After quantitative PCR analysis on tissue specimens and urinary sediments, eight promising biomarkers for the urinary detection of prostate cancer were selected (ONECUT2, HOXC4, HOXC6, DLX1, TDRD1, NKAIN1, MS4A8B, PPFIA2). The hypothesis that biomarker combinations improve the diagnostic value for aggressive prostate cancer was tested on 358 urinary sediments of an intention-to-treat cohort. RESULTS: A urinary three-gene panel (HOXC6, TDRD1, and DLX1) had higher accuracy [area under the curve (AUC), 0.77; 95% confidence interval (CI), 0.71-0.83] to predict Gleason score ≥7 prostate cancer in biopsies compared with Progensa PCA3 (AUC, 0.68; 95% CI, 0.62-0.75) or sPSA (AUC, 0.72; 95% CI, 0.65-0.78). Combining the three-gene panel with sPSA further improved the predictive accuracy (AUC, 0.81; 95% CI, 0.75-0.86). The accuracy of the three-gene predictive model was maintained in subgroups with low sPSA concentrations. CONCLUSIONS: The urinary three-gene panel (HOXC6, TDRD1, and DLX1) represents a promising tool to identify patients with aggressive prostate cancer, also in those with low sPSA values. The combination of the urinary three-gene panel with sPSA bears great potential for the early diagnosis of patients with clinically significant prostate cancer.

Prospective multicentre evaluation of PCA3 and TMPRSS2-ERG gene fusions as diagnostic and prognostic urinary biomarkers for prostate cancer.

BACKGROUND: Prostate cancer antigen 3 (PCA3) and v-ets erythroblastosis virus E26 oncogene homolog (TMPRSS2-ERG) gene fusions are promising prostate cancer (PCa) specific biomarkers that can be measured in urine. OBJECTIVE: To evaluate the diagnostic and prognostic value of Progensa PCA3 and TMPRSS2-ERG gene fusions (as individual biomarkers and as a panel) for PCa in a prospective multicentre setting. DESIGN, SETTING, AND PARTICIPANTS: At six centres, post-digital rectal examination first-catch urine specimens prior to prostate biopsies were prospectively collected from 497 men. We assessed the predictive value of Progensa PCA3 and TMPRSS2-ERG (quantitative nucleic acid amplification assay to detect TMPRSS2-ERG messenger RNA [mRNA]) for PCa, Gleason score, clinical tumour stage, and PCa significance (individually and as a marker panel). This was compared with serum prostate-specific antigen and the European Randomised Study of Screening for Prostate Cancer (ERSPC) risk calculator. In a subgroup (n=61) we evaluated biomarker association with prostatectomy outcome. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Univariate and multivariate logistic regression analysis and receiver operating curves were used. RESULTS AND LIMITATIONS: Urine samples of 443 men contained sufficient mRNA for marker analysis. PCa was diagnosed in 196 of 443 men. Both PCA3 and TMPRSS2-ERG had significant additional predictive value to the ERSPC risk calculator parameters in multivariate analysis (p<0.001 and resp. p=0.002). The area under the curve (AUC) increased from 0.799 (ERSPC risk calculator), to 0.833 (ERSPC risk calculator plus PCA3), to 0.842 (ERSPC risk calculator plus PCA3 plus TMPRSS2-ERG) to predict PCa. Sensitivity of PCA3 increased from 68% to 76% when combined with TMPRSS2-ERG. TMPRSS2-ERG added significant predictive value to the ERSPC risk calculator to predict biopsy Gleason score (p<0.001) and clinical tumour stage (p=0.023), whereas PCA3 did not. CONCLUSIONS: TMPRSS2-ERG had independent additional predictive value to PCA3 and the ERSPC risk calculator parameters for predicting PCa. TMPRSS2-ERG had prognostic value, whereas PCA3 did not. Implementing the novel urinary biomarker panel PCA3 and TMPRSS2-ERG into clinical practice would lead to a considerable reduction of the number of prostate biopsies.

Personalized management in low-risk prostate cancer: the role of biomarkers.

Current criteria to predict low-risk prostate cancer (PCa) are still subject to discussion as a substantial number of PCa patients who progress to a more aggressive disease seem to be missed, using these criteria. The main challenge in PCa diagnosis, therefore, is to distinguish patients with low-risk PCa who will show slow progression of disease from patients at risk for progression to a more aggressive cancer. The current discovered biomarkers could potentially guide in this management and improve detection, staging, and prognosis. This paper provides an overview of the current available serum-, urine-, and tissue-based biomarkers in PCa and evaluates the clinical usefulness of these biomarkers in the detection and management of low-risk PCa.