Abstract

Abstract Background: Identification of biomarkers for early detection of lung cancer (LC) may lead to more effective treatment and reduction of mortality. Methods: Serological proteome analysis (SERPA) was used to identify proteins around 34 kDa, which had been previously recognized by autoantibody in sera from LC patients. We have validated autoantibody response in sera from 90 LC patients, 89 normal controls by using immunoassay. Another independent cohort of 25 LC patients with 219 serial serum samples and 56 matched normal controls were examined to evaluate whether the autoantibody can be detected in the preclinical stage. Results: The proteins with molecular weight of 34 kDa were identified as ECH1, GAPDH and HNRNPA2B1. In the validation study, autoantibody to ECH1 achieved an area under the curve (AUC) of 0.799 with sensitivity of 62.2% and specificity of 95.5% in discriminating LC from normal individuals, and showed negative correlation with tumor size (rs=0.-256, p=0.023). Autoantibody to HNRNPA2B1 performed an AUC of 0.874 with sensitivity of 72.2% and specificity of 95.5%, and showed negative correlation with lymph node metastasis (rs=0.-279, P=0.012). By using longitudinal preclinical samples, autoantibody to ECH1 showed an AUC of 0.763 with sensitivity of 60.0% and specificity of 89.3% in distinguishing LC with matched normal controls, and elevated autoantibody levels could be detected greater than two years prior to LC diagnosis. Conclusions: ECH1 and HNRNPA2B1 are autoantigens that elicit autoimmune responses in LC and can be used as potential biomarkers for the early detection of LC. Funding support: This work was supported by the National Natural Science Foundation of China (81672917, 81372371) and the National Institutes of Health (SC1CA166016 and U01CA086137). Citation Format: Liping Dai, Jitian Li, Jun-Chieh J. Tsay, Xiao Wang, John S. Munger, Harvey Pass, William N. Rom, Eng M. Tan, Jian-Ying Zhang. Identification of autoantibody to ECH1 & HNRNPA2B1 as potential biomarkers in the early detection of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 710. doi:10.1158/1538-7445.AM2017-710

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