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EMBO Mol Med. 2015 Sep;7(9):1166-78. doi: 10.15252/emmm.201404873.

Prediction of colorectal cancer diagnosis based on circulating plasma proteins.

Author information

1
Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
2
Department of Statistics, Purdue University, West Lafayette, IN, USA.
3
Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
4
Department of Computer Science, Institute for Machine Learning, ETH Zurich, Zurich, Switzerland.
5
Department of Surgery, University Hospital in Olomouc, Olomouc, Czech Republic.
6
Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacký University, Olomouc, Czech Republic.
7
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.
8
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.
9
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.

Abstract

Non-invasive detection of colorectal cancer with blood-based markers is a critical clinical need. Here we describe a phased mass spectrometry-based approach for the discovery, screening, and validation of circulating protein biomarkers with diagnostic value. Initially, we profiled human primary tumor tissue epithelia and characterized about 300 secreted and cell surface candidate glycoproteins. These candidates were then screened in patient systemic circulation to identify detectable candidates in blood plasma. An 88-plex targeting method was established to systematically monitor these proteins in two large and independent cohorts of plasma samples, which generated quantitative clinical datasets at an unprecedented scale. The data were deployed to develop and evaluate a five-protein biomarker signature for colorectal cancer detection.

KEYWORDS:

colorectal cancer; diagnostic protein biomarker; discovery‐driven and targeted proteomics

PMID:
26253081
PMCID:
PMC4568950
DOI:
10.15252/emmm.201404873
[Indexed for MEDLINE]
Free PMC Article

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