Identification of gastric cancer patients by serum protein profiling.
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.
Ebert
Matthias P A
MP
Department of Gastroenterology, Otto-von-Guericke University, D-39120 Magdeburg, Germany. Matthias.Ebert@medizin.uni-magdeburg.de
Meuer
Jörn
J
Wiemer
Jan C
JC
Schulz
Hans-Ulrich
HU
Reymond
Marc A
MA
Traugott
Ulrich
U
Malfertheiner
Peter
P
Röcken
Christoph
C
D000465:Algorithms; D001798:Blood Proteins / Q000032:analysis*; D016022:Case-Control Studies; D006801:Humans; D013058:Mass Spectrometry; D009363:Neoplasm Proteins / Q000097:blood*; D040081:Protein Array Analysis; D012680:Sensitivity and Specificity; D013274:Stomach Neoplasms / Q000097:blood / Q000175:diagnosis*
D001798:Blood Proteins; D009363:Neoplasm Proteins