title: Non-invasive prognostic protein biomarker signatures associated with colorectal cancer.
abstract: The current management of colorectal cancer (CRC) would greatly benefit from non-invasive prognostic biomarkers indicative of clinicopathological tumor characteristics. Here, we employed targeted proteomic profiling of 80 glycoprotein biomarker candidates across plasma samples of a well-annotated patient cohort with comprehensive CRC characteristics. Clinical data included 8-year overall survival, tumor staging, histological grading, regional localization, and molecular tumor characteristics. The acquired quantitative proteomic dataset was subjected to the development of biomarker signatures predicting prognostic clinical endpoints. Protein candidates were selected into the signatures based on significance testing and a stepwise protein selection, each within 10-fold cross-validation. A six-protein biomarker signature of patient outcome could predict survival beyond clinical stage and was able to stratify patients into groups of better and worse prognosis. We further evaluated the performance of the signature on the mRNA level and assessed its prognostic value in the context of previously published transcriptional signatures. Additional signatures predicting regional tumor localization and disease dissemination were also identified. The integration of rich clinical data, quantitative proteomic technologies, and tailored computational modeling facilitated the characterization of these signatures in patient circulation. These findings highlight the value of a simultaneous assessment of important prognostic disease characteristics within a single measurement.
authors.affiliation: Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
authors.forename: Silvia
authors.initials: S
authors.lastname: Surinova
authors.affiliation: Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University, Olomouc, Czech Republic.
authors.forename: Lenka
authors.initials: L
authors.lastname: Radová
authors.affiliation: Department of Statistics, Purdue University, West Lafayette, IN, USA.
authors.forename: Meena
authors.initials: M
authors.lastname: Choi
authors.affiliation: Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University, Olomouc, Czech Republic.
authors.forename: Josef
authors.initials: J
authors.lastname: Srovnal
authors.affiliation: Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
authors.forename: Hermann
authors.initials: H
authors.lastname: Brenner
authors.affiliation: Department of Statistics, Purdue University, West Lafayette, IN, USA Department of Computer Science, Purdue University, West Lafayette, IN, USA College of Science and College of Computer and Information Science, Northeastern University, Boston, MA, USA o.vitek@neu.edu aebersold@imsb.biol.ethz.ch.
authors.forename: Olga
authors.initials: O
authors.lastname: Vitek
authors.affiliation: Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University, Olomouc, Czech Republic.
authors.forename: Marián
authors.initials: M
authors.lastname: Hajdúch
authors.affiliation: Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland Faculty of Science, University of Zurich, Zurich, Switzerland o.vitek@neu.edu aebersold@imsb.biol.ethz.ch.
authors.forename: Ruedi
authors.initials: R
authors.lastname: Aebersold
mesh_terms: D014408:Biomarkers, Tumor / Q000097:blood*; D019411:Clinical Laboratory Techniques / Q000379:methods*; D015179:Colorectal Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D006801:Humans; D010949:Plasma / Q000737:chemistry*; D011379:Prognosis; D040901:Proteomics / Q000379:methods*
chemical_list: D014408:Biomarkers, Tumor
keywords: colorectal cancer; prognostic protein biomarker; targeted proteomics