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

Abstract

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

DOI: 10.1073/pnas.1013699108

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@article{Cima2011CancerGD, title={Cancer genetics-guided discovery of serum biomarker signatures for diagnosis and prognosis of prostate cancer.}, author={Igor Cima and Ralph Schiess and Peter J. Wild and Martin Kaelin and Peter J. Sch{\"{u}ffler and V Lange and Paola Picotti and Reto Ossola and Arnoud J Templeton and Olga T Schubert and Thomas J. Fuchs and Thomas Leippold and Stephen Wyler and Jens Zehetner and Wolfram Jochum and Joachim M. Buhmann and Thomas Cerny and Holger Moch and Silke Gillessen and Ruedi Aebersold and Wilhelm Krek}, journal={Proceedings of the National Academy of Sciences of the United States of America}, year={2011}, volume={108 8}, pages={3342-7} }