Autoantibody signatures discovered by HuProt protein microarray to enhance the diagnosis of lung cancer

This study aims to discover novel autoantibodies against tumor-associated antigens (TAAs) and establish diag-nostic models for assisting in the diagnosis of lung cancer and discrimination of pulmonary nodules (PNs). Ten autoantibodies to TAAbs (TAAbs) were discovered by means of protein microarray and their serum level was also higher in 212 LC patients than that in 212 NC of validation cohort 1 (P < 0.05). The model 1 comprising 4 TAAbs and CEA reached an AUC of 0.813 (95%CI: 0.762-0.864) for diagnosing LC from normal individuals. Five TAAbs existed a significant difference between 105 malignant pulmonary nodules (MPNs) and 105 benign pulmonary nodules (BPNs) patients in validation cohort 2 (P < 0.05). Model 2 could distinguish MPNs from BPNs with an AUC of 0.845. High-throughput protein microarray is an efficient approach in discovering novel TAAbs which could be used as biomarkers in lung cancer diagnosis.

Automated summary

This study aims to discover new autoantibodies against tumor-associated antigens (TAAs) and establish diagnostic models for the diagnosis of lung cancer and discrimination of pulmonary nodules (PNs). Ten TAAs autoantibodies were discovered using protein microarray, and their serum level in lung cancer patients was higher than that in normal individuals. A diagnostic model consisting of 4 TAAs and CEA could effectively diagnose lung cancer. Additionally, five TAAs showed significant differences between malignant and benign pulmonary nodules, and a model was developed for distinguishing between the two.