A novel immunodiagnosis panel for hepatocellular carcinoma based on bioinformatics and the autoantibody‐antigen system

作者：Jinyu Wu, Peng Wang, Zhuo Han, Tiandong Li, Chuncheng Yi, Cuipeng Qiu, Qian Yang, Guiying Sun, Liping Dai, Jianxiang Shi, Keyan Wang, Hua Ye · 发表于：Cancer Science · 年份：2021 · DOI：10.1111/cas.15217 · 被引用次数：42 · 研究领域：Monoclonal and Polyclonal Antibodies Research、Immunotherapy and Immune Responses、vaccines and immunoinformatics approaches

Hepatocellular carcinoma (HCC) is a malignancy with a dismal survival rate. The novel autoantibodies panel may provide new insights for the diagnosis of HCC. Biomarkers screened by two methods (bioinformatics and the antigen-antibody system) were taken as candidate tumor-associated antigens (TAAs). Enzyme-linked immunosorbent assay was used to detect the corresponding autoantibodies in 888 samples of verification and validation cohorts. The verification cohort was used to verify the autoantibodies. Samples in the validation cohort were randomly divided into a train set and a test set with the ratio of 6:4. A diagnostic model was established by support vector machines within the train set. The 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. The titer of these autoantibodies had an increasing tendency. 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 area under the curve (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 alpha-fetoprotein (AFP)-negative patients ...