Screening and Evaluating Novel Autoantibodies Based on Proteomic Chips in Diagnosis of Esophageal Squamous Cell Carcinoma

Abstract

Background More and more studies have confirmed that TAAbs could be used as potential biomarkers for tumor patients. The aim of this study is to identify novel TAAbs through proteomic chips and construct a diagnostic model to discriminate esophageal squamous cell carcinoma (ESCC) cases from benign esophageal diseases cases and normal controls (NCs). Methods The human proteomic chips were used to screen TAAbs. Enzyme-linked immunosorbent assay (ELISA) was adopted to verify and validate the candidate TAAbs which were screened by the chips in verification phase (90 ESCC cases and 90 NCs) and validation phase (126 ESCC cases, 237 benign esophageal diseases cases and 126 NCs). Based on the candidate TAAbs, then the diagnostic model for ESCC was constructed by logistic regression analysis in the training group and validated in the testing group. Results Firstly, thirteen potential candidate TAAbs were identified by proteomic chips. In verification phase, the titers of six TAAbs (anti-MAGEA1, anti-VCL, anti-PRKCZ, anti-TP53, anti-NFKB1 and anti- MAGEA4) in ESCC cases were higher than those in NCs while other seven TAAbs showed no difference. Subsequently, six candidate TAAbs were validated further in validation phase. Finally, the logistic regression model with 3 TAAbs (anti-MAGEA1, anti-VCL, anti-TP53) could discriminate ESCC cases from NCs with area under curve(AUC)of 0.80 in the training group and 0.73 in the testing group, respectively. Meanwhile, the model could discriminate ESCC cases from benign esophageal diseases cases with AUC of 0.74. Conclusion The study has identified six novel TAAbs through protein chips and constructed a diagnostic model. The panel showed great performance to distinguish ESCC cases from benign esophageal diseases cases and NCs.