Identification of Gastric Cancer Patients by Serum Protein Profiling
- 20 October 2004
- journal article
- research article
- Published by American Chemical Society (ACS) in Journal of Proteome Research
- Vol. 3 (6) , 1261-1266
- https://doi.org/10.1021/pr049865s
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 • SELDIKeywords
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