我们旨在通过生物信息学分析和实验证实来确定肿瘤相关抗原（TAA）生物标记物，并评估针对肿瘤相关抗原（TAAbs）的自身抗体面板用于口腔癌（OC）的检测。使用GEO和TCGA数据库筛选与OC相关的显著上调基因，利用蛋白质相互作用（PPI）分析和Cystoscope软件鉴定关键基因。采用酶联免疫吸附法（ELISA）检测173例OC患者和173名正常对照的自身抗体表达水平，并使用二元Logistic回归分析构建诊断模型。通过生物信息学，我们确定了10个在OC中高表达的关键基因（AURKA、AURKB、CXCL8、CXCL10、COL1A1、FN1、FOXM1、MMP9、SPP1和UBE2C）。验证组和验证组证实了三个自身抗体（anti-AURKA、anti-CXCL10、anti-FOXM1）在OC的诊断价值。这三种自身抗体的联合评估提高了OC的诊断价值，曲线下面积（AUC），灵敏度和特异度分别为0.741（95％CI：0.690-0.793），58.4％和80.4％。此外，这三种自身抗体的联合对口腔鳞状细胞癌（OSCC）也具有较高的诊断价值，曲线下面积（AUC），灵敏度和特异度分别为0.731（95％CI：0.674,0.786），53.8％和82.1％。我们的研究揭示了AURKA、CXCL10和FOXM1可能是潜在的生物标志物，并且这三种自身抗体（anti-AURKA、anti-CXCL10和anti-FOXM1）的面板对OC具有良好的诊断价值。©2023，BioMed Central Ltd.，Springer Nature的一部分。

We aimed to identify tumor-associated antigen (TAA) biomarkers through bioinformatic analysis and experimental verification, and to evaluate a panel of autoantibodies against tumor-associated antigens (TAAbs) for the detection of oral cancer (OC).GEO and TCGA databases were used to screen significantly up-regulated genes related to OC, and protein-protein interaction (PPI) analysis and Cystoscope software were used to identify key genes. Enzyme-linked immunosorbent assay (ELISA) was used to detect the expression levels of autoantibodies in 173 OC patients and 173 normal controls, and binary logistic regression analysis was used to build a diagnostic model.Using bioinformatics, we identified 10 key genes (AURKA, AURKB, CXCL8, CXCL10, COL1A1, FN1, FOXM1, MMP9, SPP1 and UBE2C) that were highly expressed in OC. Three autoantibodies (anti-AURKA, anti-CXCL10, anti-FOXM1) were proven to have diagnostic value for OC in the verification set and the validation set. The combined assessment of these three autoantibodies improved the diagnostic value for OC, with an area under the curve (AUC), sensitivity and specificity of 0.741(95%CI:0.690-0.793),58.4% and 80.4%, respectively. In addition, the combination of these three autoantibodies also had high diagnostic value for oral squamous cell carcinoma (OSCC), with an AUC, sensitivity and specificity of 0.731(95%CI:0.674,0.786), 53.8% and 82.1%, respectively.Our study revealed that AURKA, CXCL10 and FOXM1 may be potential biomarkers and the panel of three autoantibodies (anti-AURKA, anti-CXCL10 and anti-FOXM1) had good diagnostic value for OC.© 2023. BioMed Central Ltd., part of Springer Nature.