Identification of anti-SF3B1 autoantibody as a diagnostic marker in patients with hepatocellular carcinoma.

BACKGROUND: Tumor-associated (TA) autoantibodies, which are generated by the immune system upon the recognition of abnormal TA antigens, are promising biomarkers for the early detection of tumors. In order to detect autoantibody biomarkers effectively, antibody-specific epitopes in the diagnostic test should maintain the specific conformations that are as close as possible to those presenting in the body. However, when using patients' serum as a source of TA autoantibodies the characterization of the autoantibody-specific epitope is not easy due to the limited amount of patient-derived serum. METHODS: To overcome these limits, we constructed a B cell hybridoma pool derived from a hepatocellular carcinoma (HCC) model HBx-transgenic mouse and characterized autoantibodies derived from them as tumor biomarkers. Their target antigens were identified by mass spectrometry and the correlations with HCC were examined. With the assumption that TA autoantibodies generated in the tumor mouse model are induced in human cancer patients, the enzyme-linked immunosorbent assays (ELISA) based on the characteristics of mouse TA autoantibodies were developed for the detection of autoantibody biomarkers in human serum. To mimic natural antigenic structures, the specific epitopes against autoantibodies were screened from the phage display cyclic random heptapeptide library, and the streptavidin antigens fused with the specific epitopes were used as coating antigens. RESULTS: In this study, one of HCC-associated autoantibodies derived from HBx-transgenic mouse, XC24, was characterized. Its target antigen was identified as splicing factor 3b subunit 1 (SF3B1) and the high expression of SF3B1 was confirmed in HCC tissues. The specific peptide epitopes against XC24 were selected and, among them, XC24p11 cyclic peptide (-CDATPPRLC-) was used as an epitope of anti-SF3B1 autoantibody ELISA. With this epitope, we could effectively distinguish between serum samples from HCC patients (n = 102) and healthy subjects (n = 85) with 73.53% sensitivity and 91.76% specificity (AUC = 0.8731). Moreover, the simultaneous detection of anti-XC24p11 epitope autoantibody and AFP enhanced the efficiency of HCC diagnosis with 87.25% sensitivity and 90.59% specificity (AUC = 0.9081). CONCLUSIONS: ELISA using XC24p11 peptide epitope that reacts against anti-SF3B1 autoantibody can be used as a novel test to enhance the diagnostic efficiency of HCC.

Serum anti-EIF3A autoantibody as a potential diagnostic marker for hepatocellular carcinoma.

Tumor-associated autoantibodies are promising diagnostic biomarkers for early detection of tumors. We have screened a novel tumor-associated autoantibody in hepatocellular carcinoma (HCC) model mice. Its target antigen was identified as eukaryotic translation initiation factor 3 subunit A (EIF3A) by proteomic analysis, and the elevated expression of EIF3A in HCC tissues of tumor model mice as well as human patients was shown. Also, its existence in tumor-derived exosomes was revealed, which seem to be the cause of tumor-associated autoantibody production. To use serum anti-EIF3A autoantibody as biomarker, ELISA detecting anti-EIF3A autoantibody in human serum was performed using autoantibody-specific epitope. For the sensitive detection of serum autoantibodies its specific conformational epitopes were screened from the random cyclic peptide library, and a streptavidin antigen displaying anti-EIF3A autoantibody-specific epitope, XC90p2(-CPVRSGFPC-), was used as capture antigen. It distinguished patients with HCC (n = 102) from healthy controls (n = 0285) with a sensitivity of 79.4% and specificity of 83.5% (AUC = 0.87). Also, by simultaneously detecting with other HCC biomarkers, including alpha-fetoprotein, HCC diagnostic sensitivity improved from 79.4% to 85%. Collectively, we suggest that serum anti-EIF3A autoantibody is a useful biomarker for the diagnosis of HCC and the combinational detection of related biomarkers can enhance the accuracy of the cancer diagnosis.