AUTHOR=Tong Lin , Sun Jiayuan , Zhang Xiaoju , Ge Di , Li Ying , Zhou Jian , Wang Dong , Hu Xin , Liu Hao , Bai Chunxue 

TITLE=Development of an autoantibody panel for early detection of lung cancer in the Chinese population

JOURNAL=Frontiers in Medicine

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2023.1209747

DOI=10.3389/fmed.2023.1209747

ISSN=2296-858X

ABSTRACT=Tumor associated autoantibody has been revealed as a promising biomarker for early detection of lung cancer. This study was designed to develop an autoantibody panel for early detection of lung cancer in Chinese population. Recruited prospectively in 3 clinical centers, the subjects (n=991) who had definite diagnosis during follow-up were included for the development of autoantibody panel. The levels of 14 autoantibody candidates in plasma were detected. A panel of 9 autoantibody markers (named as CN9) including P53, SOX2, SSX1, HuD, NY-ESO-1, CAGE, MAGE-A4, P62 and CK20 was preferably selected from 14 candidates. The overall specificity, sensitivity and AUC were 90.5%, 40.8% and 0.64. CN9 panel demonstrated reasonable detection rate in lung cancer patients at all stages, histological types, sizes of lesion and risk levels. Its estimated overall accuracy is 85.5% and 90%, with PPV at 0.32 and 0.04, and NPV at 0.93 and 0.99 in the scenario of pulmonary nodules' characterizing and lung cancer screening, respectively. Two risk models were developed within the subgroups of malignant and benign pulmonary nodules of this study. By adding CN9 result on to Mayo model indicators, it achieved a sensitivity of 41.3% and an AUC of 0.74 at the specificity of 91.3%. By adding CN9 result on to Brock model indicators, it achieved a sensitivity of 47.7% and an AUC of 0.78 at the specificity of 91.3%. Both were improved compared with either Mayo or Brock model standalone. This multi-center prospective study indicates a panel of 9 autoantibody markers can help the detection of lung cancer and the classification of pulmonary nodules in Chinese population.