| Abstract: | Autoantibodies obtained from cancer patients have been identified as useful tools for cancer diagnostics, prognostics, and as potential targets for immunotherapy. Serological proteome analysis in combination with 2‐DE is a classic strategy for identification of tumor‐associated antigens in the serum of cancer patients. However, serological proteome analysis cannot always indicate the true antigen out of a complex proteome identified from a single protein spot because the most abundant protein is not always the most antigenic. To address this problem, we utilized multiple parallel separation (MPS) for proteome separation. The common identities present in the fractions obtained using different separation methods were regarded as the true antigens. The merit of our MPS technique was validated using anti‐ARPC2 and anti‐PTEN antibodies. Next, we applied the MPS technique for the identification of glycyl‐tRNA synthetase as the cognate antigen for an autoantibody that was overexpressed in the plasma of breast cancer patients. These results reveal that MPS can unambiguously identify an antibody cognate antigen by reducing false‐positives. Therefore, MPS could be used for the characterization of diagnostic antibodies raised in laboratory animals as well as autoantibodies isolated from diseased patients. |
