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Identification of Gastric Cancer Patients by Serum Protein Profiling
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Jan C. Wiemer, Hans-Ulrich Schulz,§ Marc A. Reymond,§ Ulrich Traugott, Peter Malfertheiner,† and Christoph Röcken‡To whom correspondence should be addressed. Tel: +49-391-6721520. Fax: +49-391-67190054. E-mail: Matthias.Ebert@medizin.uni-magdeburg.de.
Department of Gastroenterology, Hepatology and Infectious Diseases, Otto-von-Guericke University.
Europroteome AG.
Department of General Surgery, Otto-von-Guericke University.
Department of Pathology, Otto-von-Guericke University.
Abstract
Using surface-enhanced laser desorption ionization mass spectrometry (SELDI/TOF−MS) and ProteinChip technology, coupled with a pattern-matching algorithm and serum samples, we screened for protein patterns to differentiate gastric cancer patients from noncancer patients. A classifier ensemble, consisting of 50 decision trees, correctly classified all gastric cancers and all controls of a training set (100% sensitivity and 100% specificity). Eight of 9 stage I gastric cancers (88.9% sensitivity for stage I) were correctly classified. In addition, 28 sera from gastric cancer patients taken in different hospitals were correctly classified (100% sensitivity). Furthermore, all 11 control sera obtained from patients without gastric cancer (100% specificity) were classified correctly and 29 of 30 healthy blood-donors were classified as noncancerous. ProteinChip technology in conjunction with bioinformatics allows the highly sensitive and specific recognition of gastric cancer patients.
Keywords: Proteomics • diagnosis • stomach • SELDI
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History
- Published In Issue December 13, 2004
- Received August 4, 2004
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