Hepatocellular carcinoma (HCC) is a malignancy with dismal survival rate. The novel autoantibodies panel may provide new insights for the diagnosis of HCC. Biomarkers screened by two methods (bioinformatics and antigen-antibody system) were taken as candidate tumor-associated antigens. Enzyme-linked immunosorbent assay was used to detect the corresponding autoantibodies in 888 samples of verification and validation cohorts. Verification cohort was used to verify the autoantibodies. Samples in validation cohort were randomly divided into train-set and test-set with the ratio of 6:4. A diagnostic model was established by support vector machines within train-set. Test-set further verified the model. Eleven TAAs were selected (AAGAB, C17orf75, CDC37L1, DUSP6, EID3, PDIA2, RGS20, PCNA, TAF7L, TBC1D13 and ZIC2). The titer of six autoantibodies (PCNA, AAGAB, CDC37L1, TAF7L, DUSP6, and ZIC2) had a significant difference in any of the pairwise comparisons among the HCC, liver cirrhosis and normal control groups. These autoantibodies titer tended to upward. Finally, an optimum diagnostic model was constructed with the six autoantibodies. The AUCs were 0.826 in the train-set and 0.773 in the test-set. The AUC of this panel for diagnosing early HCC was 0.889. The diagnostic ability of the panel reduced with the progress of HCC. The positive rate of the panel in diagnosing AFP(Alpha-fetoprotein) negative patients was 75.6%. For the early HCC, the sensitivity of combination of AFP with panel was 90.9% and superior to 53.2% of AFP alone. The novel immunodiagnosis panel combining AFP may be a new approach for the diagnosis of HCC, especially for early HCC.