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 Vienna Austria
- Matteo Pecoraro
- Department of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried Germany
- Mate Rusz
- Department of Analytical Chemistry University of Vienna Vienna Austria
- Georg Oberhuber
- Patho im Zentrum St.Pölten Austria
- Maritta Wieselberg
- Department of Pathology Medical University of Vienna Vienna Austria
- Peter Haslinger
- Department of Obstetrics and Gynaecology Medical University of Vienna Vienna Austria
- Elisabeth Gurnhofer
- Department of Pathology Medical University of Vienna Vienna Austria
- Michaela Schlederer
- Department of Pathology Medical University of Vienna Vienna Austria
- Tanja Limberger
- Department of Pathology Medical University of Vienna Vienna Austria
- Sabine Lagger
- Unit of Pathology of Laboratory Animals University of Veterinary Medicine Vienna Vienna Austria
- Jan Pencik
- Department of Pathology Medical University of Vienna Vienna Austria
- Petra Kodajova
- Unit of Pathology of Laboratory Animals University of Veterinary Medicine Vienna Vienna Austria
- Sandra Högler
- Unit of Pathology of Laboratory Animals University of Veterinary Medicine Vienna Vienna Austria
- Georg Stockmaier
- Department of Biosciences University of Salzburg Salzburg Austria
- Sandra Grund‐Gröschke
- Department of Biosciences University of Salzburg Salzburg Austria
- Fritz Aberger
- Department of Biosciences University of Salzburg Salzburg Austria
- Marco Bolis
- Institute of Oncology Research (IOR) Bellinzona Switzerland
- Jean‐Philippe Theurillat
- Institute of Oncology Research (IOR) Bellinzona Switzerland
- Robert Wiebringhaus
- Department of Pathology Medical University of Vienna Vienna Austria
- Theresa Weiss
- Department of Pathology Medical University of Vienna Vienna Austria
- Andrea Haitel
- Department of Pathology Medical University of Vienna Vienna Austria
- Marc Brehme
- CBmed‐Center for Biomarker Research in Medicine GmbH Graz Austria
- Wolfgang Wadsak
- CBmed‐Center for Biomarker Research in Medicine GmbH Graz Austria
- Johannes Griss
- Department of Dermatology Medical University of Vienna Vienna Austria
- Thomas Mohr
- Department of Medicine I Medical University of Vienna Vienna Austria
- Alexandra Hofer
- Research Area Biochemical Engineering Institute of Chemical Environmental and Biological Engineering Vienna University of Technology Vienna Austria
- Anton Jäger
- Department of Pathology Medical University of Vienna Vienna Austria
- Jürgen Pollheimer
- Department of Obstetrics and Gynaecology Medical University of Vienna Vienna Austria
- Gerda Egger
- Department of Pathology Medical University of Vienna Vienna Austria
- Gunda Koellensperger
- Department of Analytical Chemistry University of Vienna Vienna Austria
- Matthias Mann
- Department of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried Germany
- Brigitte Hantusch
- Department of Pathology Medical University of Vienna Vienna Austria
- Lukas Kenner
- Department of Pathology Medical University of Vienna Vienna Austria
- DOI
- https://doi.org/10.15252/msb.20199247
- Journal volume & issue
-
Vol. 16,
no. 4
pp. n/a – n/a
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
