Molecular Systems Biology (Apr 2020)
STAT3‐dependent analysis reveals PDK4 as independent predictor of recurrence in prostate cancer
- Monika Oberhuber,
- Matteo Pecoraro,
- Mate Rusz,
- Georg Oberhuber,
- Maritta Wieselberg,
- Peter Haslinger,
- Elisabeth Gurnhofer,
- Michaela Schlederer,
- Tanja Limberger,
- Sabine Lagger,
- Jan Pencik,
- Petra Kodajova,
- Sandra Högler,
- Georg Stockmaier,
- Sandra Grund‐Gröschke,
- Fritz Aberger,
- Marco Bolis,
- Jean‐Philippe Theurillat,
- Robert Wiebringhaus,
- Theresa Weiss,
- Andrea Haitel,
- Marc Brehme,
- Wolfgang Wadsak,
- Johannes Griss,
- Thomas Mohr,
- Alexandra Hofer,
- Anton Jäger,
- Jürgen Pollheimer,
- Gerda Egger,
- Gunda Koellensperger,
- Matthias Mann,
- Brigitte Hantusch,
- Lukas Kenner
Affiliations
- Monika Oberhuber
- Department of Pathology, Medical University of Vienna
- Matteo Pecoraro
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry
- Mate Rusz
- Department of Analytical Chemistry, University of Vienna
- Georg Oberhuber
- Patho im Zentrum
- Maritta Wieselberg
- Department of Pathology, Medical University of Vienna
- Peter Haslinger
- Department of Obstetrics and Gynaecology, Medical University of Vienna
- Elisabeth Gurnhofer
- Department of Pathology, Medical University of Vienna
- Michaela Schlederer
- Department of Pathology, Medical University of Vienna
- Tanja Limberger
- Department of Pathology, Medical University of Vienna
- Sabine Lagger
- Unit of Pathology of Laboratory Animals, University of Veterinary Medicine Vienna
- Jan Pencik
- Department of Pathology, Medical University of Vienna
- Petra Kodajova
- Unit of Pathology of Laboratory Animals, University of Veterinary Medicine Vienna
- Sandra Högler
- Unit of Pathology of Laboratory Animals, University of Veterinary Medicine Vienna
- Georg Stockmaier
- Department of Biosciences, University of Salzburg
- Sandra Grund‐Gröschke
- Department of Biosciences, University of Salzburg
- Fritz Aberger
- Department of Biosciences, University of Salzburg
- Marco Bolis
- Institute of Oncology Research (IOR)
- Jean‐Philippe Theurillat
- Institute of Oncology Research (IOR)
- Robert Wiebringhaus
- Department of Pathology, Medical University of Vienna
- Theresa Weiss
- Department of Pathology, Medical University of Vienna
- Andrea Haitel
- Department of Pathology, Medical University of Vienna
- Marc Brehme
- CBmed‐Center for Biomarker Research in Medicine GmbH
- Wolfgang Wadsak
- CBmed‐Center for Biomarker Research in Medicine GmbH
- Johannes Griss
- Department of Dermatology, Medical University of Vienna
- Thomas Mohr
- Department of Medicine I, Medical University of Vienna
- Alexandra Hofer
- Research Area Biochemical Engineering, Institute of Chemical, Environmental and Biological Engineering, Vienna University of Technology
- Anton Jäger
- Department of Pathology, Medical University of Vienna
- Jürgen Pollheimer
- Department of Obstetrics and Gynaecology, Medical University of Vienna
- Gerda Egger
- Department of Pathology, Medical University of Vienna
- Gunda Koellensperger
- Department of Analytical Chemistry, University of Vienna
- Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry
- Brigitte Hantusch
- Department of Pathology, Medical University of Vienna
- Lukas Kenner
- Department of Pathology, Medical University of Vienna
- DOI
- https://doi.org/10.15252/msb.20199247
- Journal volume & issue
-
Vol. 16,
no. 4
pp. 1 – 27
Abstract
Abstract Prostate cancer (PCa) has a broad spectrum of clinical behavior; hence, biomarkers are urgently needed for risk stratification. Here, we aim to find potential biomarkers for risk stratification, by utilizing a gene co‐expression network of transcriptomics data in addition to laser‐microdissected proteomics from human and murine prostate FFPE samples. We show up‐regulation of oxidative phosphorylation (OXPHOS) in PCa on the transcriptomic level and up‐regulation of the TCA cycle/OXPHOS on the proteomic level, which is inversely correlated to STAT3 expression. We hereby identify gene expression of pyruvate dehydrogenase kinase 4 (PDK4), a key regulator of the TCA cycle, as a promising independent prognostic marker in PCa. PDK4 predicts disease recurrence independent of diagnostic risk factors such as grading, staging, and PSA level. Therefore, low PDK4 is a promising marker for PCa with dismal prognosis.
Keywords
