Abstract

Abstract Prostate cancer (PCa) is the most frequently diagnosed malignancy among men in Western Europe and the United States. Due to PSA-testing and early detection strategies, the proportion of men diagnosed with low risk disease according to the D´Amico criteria (PSA ≤ 10ng/ml, Gleason-Score ≤ 6, clinical stage ≤ T2a) has significantly increased from 27.5% in 1990 to 1994 up to 46.4% from 2000 to 2001. Nonetheless, even among patients with low-grade and low-volume prostate cancer, more than 90% currently receive definitive treatment, e.g. surgery or radiotherapy. This in turn has raised concerns about overtreatment that may result in a decreased quality of life, typically related to an impairment of sexual or urinary function following therapies with curative intent. With the aim of reducing the risk of overtreatment in this subgroup, the strategy of active surveillance (AS) has been proposed a reasonable initial “treatment” option, which means to manage low-risk patients expectantly with the intention to treat only if signs of tumor progression emerge. Unfortunately all current models available to predict the probability of insignificant or low-risk PCa are not infallible as a considerable number of presumed low-risk tumors are misclassified. We aimed to provide additional molecular parameters that may be included into current models that help to improve the accuracy of predicting the actual PCa risk category and thus facilitate treatment planning. In this context we are searching for miRNA profiles in urine obtained after digital rectal examination (DRE) of apparently low-risk PCa patients, that in fact suffer from intermediate or high-risk PCa and thus should not be offered an AS strategy. This is a clinically pivotal issue since up to 40% of seemingly low-risk tumors are currently misclassified by clinicopathological criteria alone. Conversely, the identification of signatures that approve low-risk tumors may aid to better counsel patients eligible for AS. DRE-urine total RNA isolates of 16 patients with low-risk (Gleason score ≤ 6) and 14 of high-risk patients (GS ≥ 8) were subjected to microRNA array analysis (Exiqon A/S, 7th Gen) with a present call number of approx. 500. Unsupervised PCA analysis and two-way hierarchical clustering indicate that the samples do not separate by Gleason score. The supervised comparison of both GS groups identified 15 significantly differentially expressed miRNAs (1 upregulated, 14 downregulated), among them miR-106b, miR-20a, miR-21, and let-7a. When we compared miRNA profiles generated from PCa tissue or from blood of prostate cancer patients, our top-50 regulated DRE-urine miRNAs display a concordance of 56% (28/50). This and our experimentally optimized miRNA isolation protocol should further encourage the use of DRE-urine as a suitable non-invasive resource for generating PCa biomarkers. Citation Format: Hans Krause, Hannes Cash, Liam Stelzer, Kurt Miller, Carsten Kempkensteffen. Value of miRNA profiling in urine to predict significant prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3992. doi:10.1158/1538-7445.AM2015-3992

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