Identification of autoantibodies to ECH1 and HNRNPA2B1 as potential biomarkers in the early detection of lung cancer

ABSTRACT

Identification of biomarkers for early detection of lung cancer (LC) is important, in turn leading to more effective treatment and reduction of mortality. Serological proteome analysis (SERPA) was used to identify proteins around 34 kD as ECH1 and HNRNPA2B1, which had been recognized by serum autoantibody from 25 LC patients. In the validation study, including 90 sera from LC patients and 89 sera from normal individuals, 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 (r_s = −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 (r_s = −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 early stage LC from matched normal controls, and elevated autoantibody levels could be detected greater than 2 y before LC diagnosis. ECH1 and HNRNPA2B1 are autoantigens that elicit autoimmune responses in LC and their autoantibody can be the potential biomarkers for the early detection of LC.

KEYWORDS:

• Autoantibody
• ECH1
• HNRNPA2B1
• lung cancer
• serological proteome analysis (SERPA)

Disclosure of potential conflicts of interest

No potential conflicts of interest were disclosed.

Acknowledgments

We thank the Border Biological Research Center (BBRC) Core Facilities at The University of Texas at El Paso (UTEP) for their support, which were funded by RCMI-NIMHD-NIH grant (8G12MD007592).

Funding

This work was supported by the National Institutes of Health under grant (number: SC1CA166016 and U01CA086137); National Natural Science Foundation of China under grant (number: 81672917, 81372371); and the Major Project of Science and Technology in Henan Province under grant (number: 161100311400).