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. 2024 Jul 4;16(13):2453.
doi: 10.3390/cancers16132453.

Transcript Markers from Urinary Extracellular Vesicles for Predicting Risk Reclassification of Prostate Cancer Patients on Active Surveillance

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Transcript Markers from Urinary Extracellular Vesicles for Predicting Risk Reclassification of Prostate Cancer Patients on Active Surveillance

Kati Erdmann et al. Cancers (Basel). .

Abstract

Serum prostate-specific antigen (PSA), its derivatives, and magnetic resonance tomography (MRI) lack sufficient specificity and sensitivity for the prediction of risk reclassification of prostate cancer (PCa) patients on active surveillance (AS). We investigated selected transcripts in urinary extracellular vesicles (uEV) from PCa patients on AS to predict PCa risk reclassification (defined by ISUP 1 with PSA > 10 ng/mL or ISUP 2-5 with any PSA level) in control biopsy. Before the control biopsy, urine samples were prospectively collected from 72 patients, of whom 43% were reclassified during AS. Following RNA isolation from uEV, multiplexed reverse transcription, and pre-amplification, 29 PCa-associated transcripts were quantified by quantitative PCR. The predictive ability of the transcripts to indicate PCa risk reclassification was assessed by receiver operating characteristic (ROC) curve analyses via calculation of the area under the curve (AUC) and was then compared to clinical parameters followed by multivariate regression analysis. ROC curve analyses revealed a predictive potential for AMACR, HPN, MALAT1, PCA3, and PCAT29 (AUC = 0.614-0.655, p < 0.1). PSA, PSA density, PSA velocity, and MRI maxPI-RADS showed AUC values of 0.681-0.747 (p < 0.05), with accuracies for indicating a PCa risk reclassification of 64-68%. A model including AMACR, MALAT1, PCAT29, PSA density, and MRI maxPI-RADS resulted in an AUC of 0.867 (p < 0.001) with a sensitivity, specificity, and accuracy of 87%, 83%, and 85%, respectively, thus surpassing the predictive power of the individual markers. These findings highlight the potential of uEV transcripts in combination with clinical parameters as monitoring markers during the AS of PCa.

Keywords: active surveillance; biomarker; liquid biopsy; monitoring; prediction; prostate cancer; quantitative PCR; risk reclassification; transcripts; urinary extracellular vesicles.

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Conflict of interest statement

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Characterization of isolated uEV by Western blotting. Exemplary Western blots probing for the established EV markers TSG101, CD63, and CD9, as well as the cellular marker calnexin in selected control samples. The PCa cell lines PC-3 and LNCaP served as positive controls for cellular components. PL: protein ladder. The uncropped Western blots are shown in Figure S1.
Figure 2
Figure 2
Relative expression levels of (A) AMACR, (B) HPN, (C) MALAT1, (D) PCA3, and (E) PCAT29 in uEV from stable and reclassified patients at control biopsy. Depicted are the median relative transcript levels ± 95% CI of the evaluated transcripts (normalized to geoM of PPIA, RPLP0, and TBP). p values were calculated by the Mann–Whitney U test.
Figure 3
Figure 3
ROC curve analysis of (A) PSA, (B) PSAD, (C) PSAV, (D) maxPI-RADS, (E) AMACR, (F) HPN, (G) MALAT1, (H) PCA3, and (I) PCAT29 to discriminate between stable disease and PCa risk reclassification.
Figure 4
Figure 4
ROC curve analysis of the 2C-3T-Score (PSAD, maxPI-RADS, AMACR, MALAT1, and PCAT29), 2C-Score (PSAD and maxPI-RADS), and 3T-Score (AMACR, MALAT1, and PCAT29) to discriminate between stable disease and PCa risk reclassification.

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