Cancer genetics-guided discovery of serum biomarker signatures for diagnosis and prognosis of prostate cancer

• DOI: 10.1073/pnas.1013699108
• Publication Date: 2011-02-08T05:35:23Z
• Authors: Igor Cima; Ralph Schiess; Peter Wild; Martin Kaelin; Peter Schüffler; Vinzenz Lange; Paola Picotti; Reto Ossola; Arnoud Templeton; Olga Schubert; Thomas Fuchs; Thomas Leippold; Stephen Wyler; Jens Zehetner; Wolfram Jochum; Joachim Buhmann; Thomas Cerny; Holger Moch; Silke Gillessen; Ruedi Aebersold; Wilhelm Krek
• Keywords: Biomarker Discovery; Tensin; Cancer Biomarkers

A key barrier to the realization of personalized medicine for cancer is identification biomarkers. Here we describe a two-stage strategy discovery serum biomarker signatures corresponding specific cancer-causing mutations and its application prostate (PCa) in context commonly occurring phosphatase tensin homolog ( PTEN ) tumor-suppressor gene inactivation. In first stage our approach, identified 775 N -linked glycoproteins from sera tissue wild-type Pten -null mice. Using label-free quantitative proteomics, showed that inactivation leads measurable perturbations murine glycoproteome. Following bioinformatic prioritization, second applied targeted proteomics detect quantify 39 human ortholog candidate biomarkers PCa patients control individuals. The resulting proteomic profiles were analyzed by machine learning build predictive regression models status diagnosis grading PCa. Our approach suggests general path rational initial validation guided genetics based on integration experimental mouse models, proteomics-based technologies, computational modeling.