ProstaTrend-A Multivariable Prognostic RNA Expression Score for Aggressive Prostate Cancer.

Biomarker Molecular diagnostic testing Molecular pathology Next-generation sequencing Personalized medicine Prostate cancer Transcriptome

Journal

European urology
ISSN: 1873-7560
Titre abrégé: Eur Urol
Pays: Switzerland
ID NLM: 7512719

Informations de publication

Date de publication:
09 2020
Historique:
received: 12 11 2019
accepted: 02 06 2020
pubmed: 8 7 2020
medline: 16 7 2021
entrez: 8 7 2020
Statut: ppublish

Résumé

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. To develop an RNA expression-based score for the prediction of PCa prognosis that facilitates clinical decision making. 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. 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). 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). ProstaTrend is a transcriptome-based score that predicts DoD and BCR in cohorts of PCa patients treated with RP. ProstaTrend provides molecular patient risk stratification after radical prostatectomy.

Sections du résumé

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.
PATIENT SUMMARY
ProstaTrend provides molecular patient risk stratification after radical prostatectomy.

Identifiants

pubmed: 32631745
pii: S0302-2838(20)30428-0
doi: 10.1016/j.eururo.2020.06.001
pii:
doi:

Substances chimiques

RNA, Neoplasm 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

452-459

Informations de copyright

Copyright © 2020. Published by Elsevier B.V.

Auteurs

Markus Kreuz (M)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany; Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.

Dominik J Otto (DJ)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany; Institute of Clinical Immunology, Faculty of Medicine, University of Leipzig, Leipzig, Germany.

Susanne Fuessel (S)

Department of Urology, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.

Conny Blumert (C)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany; Institute of Clinical Immunology, Faculty of Medicine, University of Leipzig, Leipzig, Germany.

Catharina Bertram (C)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany.

Sophie Bartsch (S)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany.

Dennis Loeffler (D)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany; Institute of Clinical Immunology, Faculty of Medicine, University of Leipzig, Leipzig, Germany.

Sven-Holger Puppel (SH)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany.

Michael Rade (M)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany.

Tilo Buschmann (T)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany.

Sabina Christ (S)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany.

Kati Erdmann (K)

Department of Urology, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany; National Center for Tumor Diseases (NCT), Dresden, Germany.

Maik Friedrich (M)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany; Institute of Clinical Immunology, Faculty of Medicine, University of Leipzig, Leipzig, Germany.

Michael Froehner (M)

Department of Urology, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany; Department of Urology, Zeisigwaldkliniken Bethanien, Chemnitz, Germany.

Michael H Muders (MH)

Institute of Pathology, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany; Rudolf-Becker-Laboratory for Prostate Cancer Research, Institute of Pathology, University of Bonn Medical Center, Bonn, Germany.

Stephan Schreiber (S)

Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany.

Michael Specht (M)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany.

Marieta I Toma (MI)

Institute of Pathology, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.

Fabio Benigni (F)

Department of Urology and Division of Experimental Oncology, URI, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy.

Massimo Freschi (M)

Pathology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.

Giorgio Gandaglia (G)

Department of Urology and Division of Experimental Oncology, URI, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy.

Alberto Briganti (A)

Department of Urology and Division of Experimental Oncology, URI, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy.

Gustavo B Baretton (GB)

Institute of Pathology, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.

Markus Loeffler (M)

Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.

Jörg Hackermüller (J)

Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany.

Kristin Reiche (K)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany; Institute of Clinical Immunology, Faculty of Medicine, University of Leipzig, Leipzig, Germany. Electronic address: kristin.reiche@izi.fraunhofer.de.

Manfred Wirth (M)

Department of Urology, University Hospital and Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.

Friedemann Horn (F)

Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany; Institute of Clinical Immunology, Faculty of Medicine, University of Leipzig, Leipzig, Germany.

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