Gastric cancer (GC) is traditionally considered a difficult disease to diagnose and treat. The search for new markers for GC is an extremely urgent purpose. Previously has been shown, that serum anti-glycan antibodies (AGAT) are very large reservoir of markers which can be reliably detected using an instrument called glycoarray (PGA). A “;signature”; approach, i.e. searching of combinations of diagnostically significant markers – AGAT detected by PGA, is used in this study.

The cohort of the serum of apparently healthy donors from the National Medical Research Center of Oncology (NMRC) (n = 55, 69%/31% - m/f) and previously untreated patients with an established diagnosis of GC I-IV stages from the NMRC (n = 146, 52%/48% - m/f) were collected. To study serum AGATs glycoarray containing 300 different glycans was used. To search for a diagnostic signature, the mathematical apparatus “;Immunoruler”; [Int. J. Bioinformatics Res. Appl., 7, 402-426 (2011)] was applied.

Using glycoarray IgG and IgM profiles of donors and GC patients were obtained and data quality control has been performed. The mathematical apparatus Immunoruler was applied to the resulting database and a signature was obtained. It includes antibodies to 11 glycans: 7 IgM (directed to KDNb6’LN-C3, b3’SLN, LN-C8, Aa4A, TF, 3’SiaLeC and Tn3Su) and 4 IgG (GN6Su, TF, para-Fs and bGU). The quality of the developed diagnostic approach was assessed: the AUC value was 0.87, and the accuracy was 0.81.

Thus, the use of glycoarray technology in combination with a mathematical signature search apparatus has made it possible to find a reliable combination of molecular markers for the diagnosis of gastric cancer. Since the tumor can dramatically change as it progresses, the AGAT profile can also change. This opens up the possibility for a differentiated diagnosis of GC depending on the stage of the disease and, first of all, to develop early diagnosis of this disease.