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.

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Gastric cancer mortality is second only to lung cancer, and its prognosis is dismal. Using surface-enhanced laser desorption/ionization-time-of-flight mass spectrometry, we previously identified a single best mass, which could separate gastric cancer from patients without cancer, with a sensitivity of 89.9% and a specificity of 90%. Using protein liquid chromatography systems with various chromatography media and MS/MS analysis, we were able to identify thrombin light chain A, a proteolytic fragment of prothrombin, as the single best mass for early detection of gastric cancer patients. These findings indicate that disturbances in the coagulation-system are early events in gastric cancer biology and that a decrease or loss of thrombin light chain A, which we termed negative serum protein profiling, may contribute to the diagnosis of cancer patients.

Gastrointestinal cancers are usually diagnosed at advanced stages, making a curative treatment difficult. Biomarkers can help to overcome this problem by allowing earlier diagnosis, and thus better therapy. Proteomics tools are novel technologies to identify such biomarkers. This review summarizes advances in biomarker detection using two-dimensional gel electrophoresis (2D-PAGE), chromatography and mass spectrometry technologies. 2D-PAGE combined with mass spectrometry has led to the identification of several differentially expressed proteins in cancer tissue. However, for serum analysis, 2D-PAGE has severe limitations. For serum-based cancer diagnosis, surface-enhanced laser desorption-ionization time-of-flight (SELDI-TOF^TM) mass spectrometry is a promising new technology. The potential of proteins identified with this technology as novel cancer biomarkers still needs to be confirmed in clinical trials.

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