Gerald W. Verhaegh

Prostate cancer is the most commonly diagnosed malignancy and the second leading cause of cancer-related deaths in the Western male population. Despite the tremendous efforts that have been made to improve the early detection of this disease and to design new treatment modalities, there is still an urgent need for new markers and therapeutic targets for the management of prostate cancer patients. Using differential display analysis to compare the mRNA expression patterns of normal versus tumor tissue of the human prostate, we identified a cDNA, DD3, which is highly overexpressed in 53 of 56 prostatic tumors in comparison to nonneoplastic prostatic tissue of the same patients. Reverse transcription-PCR analysis using DD3-specific primers indicated that the expression of DD3 is very prostate specific because no product could be amplified in 18 different normal human tissues studied. Also, in a sampling of other tumor types and a large number of cell lines, no expression of DD3 could be detected. Molecular characterization of the DD3 transcription unit revealed that alternative splicing and alternative polyadenylation occur. The fact that no extensive open reading frame could be found suggests that DD3 may function as a noncoding RNA. The DD3 gene was mapped to chromosome 9q21-22, and no homology of DD3 to any gene present in the computer databases was found. Our data indicate that DD3 is one of the most prostate cancer-specific genes yet described, and this makes DD3 a promising marker for the early diagnosis of prostate cancer and provides a powerful tool for the development of new treatment strategies for prostate cancer patients.

We identified DD3(PCA3) as one of the most prostate cancer-specific genes at present (M. J. Bussemakers et al. Cancer Res., 59: 5975-5979, 1999). Consequently, DD3(PCA3) is an interesting candidate for use as a diagnostic and/or prognostic marker. In this study we developed a method for the accurate quantification of DD3(PCA3) mRNA, using real-time quantitative reverse transcription-PCR. DD3(PCA3) was expressed at low levels in normal prostate but not in 21 selected other normal tissues, blood, or 39 tumor samples other than prostate. The diagnostic and prognostic value of DD3(PCA3) in normal, hyperplastic, and malignant prostate tissues was determined and compared with another promising tumor marker for prostate cancer, telomerase reverse transcriptase (hTERT gene), the expression of which is related to telomerase activity. Sensitivity and specificity estimates for both genes were calculated as the area under the receiver-operating characteristics curve (AUC-ROC). DD3(PCA3) (AUC-ROC, 0.98) demonstrated better diagnostic efficacy than hTERT (AUC-ROC, 0.88). Moreover, the median increase in mRNA expression in tumor tissues compared with nonmalignant prostate tissues was much higher for DD3(PCA3) (34-fold) than for hTERT (6-fold). In tumor tissues, the median expression of DD3(PCA3) was much higher than hTERT (5849 versus 10 normalized mRNA copies). A significant relationship was observed only between tumor stage and hTERT gene expression. We conclude that expression of the DD3(PCA3) gene is a very sensitive and specific marker for the detection of prostate tumor cells in a high background of normal (prostate) cells. Consequently, DD3 measurements may be used for clinical application in prostate needle biopsies or bodily fluids such as blood, ejaculate, urine, or prostate massage fluid.

Abstract Urine is commonly used for clinical diagnosis and biomedical research. The discovery of extracellular vesicles (EV) in urine opened a new fast‐growing scientific field. In the last decade urinary extracellular vesicles (uEVs) were shown to mirror molecular processes as well as physiological and pathological conditions in kidney, urothelial and prostate tissue. Therefore, several methods to isolate and characterize uEVs have been developed. However, methodological aspects of EV separation and analysis, including normalization of results, need further optimization and standardization to foster scientific advances in uEV research and a subsequent successful translation into clinical practice. This position paper is written by the Urine Task Force of the Rigor and Standardization Subcommittee of ISEV consisting of nephrologists, urologists, cardiologists and biologists with active experience in uEV research. Our aim is to present the state of the art and identify challenges and gaps in current uEV‐based analyses for clinical applications. Finally, recommendations for improved rigor, reproducibility and interoperability in uEV research are provided in order to facilitate advances in the field.

PURPOSE: Early detection of prostate cancer can increase the curative success rate for prostate cancer. We studied the diagnostic usefulness of TMPRSS2-ERG fusion transcripts as well as the combination of prostate cancer antigen 3 (PCA3) RNA and TMPRSS2-ERG fusion transcripts in urinary sediments after digital rectal examination (DRE). EXPERIMENTAL DESIGN: A total of 78 men with prostate cancer-positive biopsies and 30 men with prostate cancer-negative biopsies were included in this study. After DRE, the first voided urine was collected, and urinary sediments were obtained. We used semiquantitative reverse transcription-PCR (RT-PCR) analysis followed by Southern blot hybridization with a radiolabeled probe for the detection TMPRSS2-ERG fusion transcripts in these urinary sediments. A quantitative RT-PCR assay for PCA3 was used to determine the PCA3 score in the same sediments. RESULTS: TMPRSS2-ERG fusion transcripts can be detected in the urine after DRE with a sensitivity of 37%. In this cohort of patients, the PCA3-based assay had a sensitivity of 62%. When both markers were combined, the sensitivity increased to 73%. Especially in the cohort of men with persistently elevated serum prostate-specific antigen levels and history of negative biopsies, the high positive predictive value of 94% of TMPRSS2-ERG fusion transcripts could give a better indication which patients require repeat biopsies. CONCLUSION: In this report, we used for the first time the combination of the prostate cancer-specific biomarkers TMPRSS2-ERG and PCA3, which significantly improves the sensitivity for prostate cancer diagnosis.