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ProstaTrend - a multivariable prognostic RNA expression score for aggressive prostate cancer

: Kreuz, Markus; Otto, J. Dominik; Füssel, Susanne; Blumert, Conny; Bertram, Catharina; Bartsch, Sophie; Löffler, Dennis; Puppel, Sven Holger; Rade, Michael; Buschmann, Tilo; Christ, Sabine; Erdmann, Kati; Friedrich, Maik; Fröhner, Michael; Muders, Michael H.; Schreiber, Stephan; Specht, Michael; Toma, Marieta I.; Benigini, Fabio; Freschi, Massimo; Gandaglia, Giorgio; Briganti, Alberto; Baretton, Gustavo B.; Loeffler, Markus; Hackermüller, Jörg; Reiche, Kristin; Wirth, Manfred P.; Horn, Friedemann


European urology (2020), Online First, 8 S.
ISSN: 0302-2838
Fraunhofer IZI ()
Biomarker; molecular diagnostic testing; molecular pathology; next generation sequencing; Prostate Cancer

Background: Prostate cancer (PCa) is the most prevalent solid cancer among men in Western Countries. The clinical behavior of localized PCa is highly variable. Some cancers are aggressive leading to death, while others can even be monitored safely. Hence, there is a high clinical need for precise biomarkers for identification of aggressive disease in addition to established clinical parameters.
Objective: To develop an RNA expression-based score for the prediction of PCa prognosis that facilitates clinical decision making.
Design, setting, and participants: We assessed 233 tissue specimens of PCa patients with long-term follow-up data from fresh-frozen radical prostatectomies (RPs), from formalin-fixed and paraffin-embedded RP specimens and biopsies by transcriptome-wide next-generation sequencing and customized expression microarrays.
Outcome measurements and statistical analysis: We applied Cox proportional hazard models to the cohorts from different platforms and specimen types. Evidence from these models was combined by fixed-effect meta-analysis to identify genes predictive of the time to death of disease (DoD). Genes were combined by a weighted median approach into a prognostic score called ProstaTrend and transferred for the prediction of biochemical recurrence (BCR) after RP in an independent cohort of The Cancer Genome Atlas (TCGA).
Results and limitations: ProstaTrend comprising ∼1400 genes was significantly associated with DoD in the training cohort of PCa patients treated by RP (leave-one-out cross-validation, Cox regression: p = 2e-09) and with BCR in the TCGA validation cohort (Cox regression: p = 3e-06). The prognostic impact persisted after multivariable Cox regression analysis adjusting for Gleason grading group (GG) ≥3 and resection status (p = 0.001; DoD, training cohort) and for GG ≥ 3, pathological stage ≥T3, and resection state (p = 0.037; BCR, validation cohort).
Conclusions: ProstaTrend is a transcriptome-based score that predicts DoD and BCR in cohorts of PCa patients treated with RP.