A Diagnostic Model With IgM Autoantibodies and Carcinoembryonic Antigen for Early Detection of Lung Adenocarcinoma

Frontiers in Immunology

Tingting Wang¹  Xiao Wang¹  Jiaqi Li¹  Man Liu¹  Yulin Wang²  Di Jiang²  Xue Zhang²  Xiuzhi Zhang²  Liping Dai³  Jianying Zhang⁵  Fenghui Liu⁷  Lu Pei⁸ 

[1] Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou University, Zhengzhou, China;School of Basic Medical Sciences, Academy of Medical Science, Zhengzhou University, Zhengzhou, China;Department of Clinical Laboratory, Fuwai Central China Cardiovascular Hospital, Zhengzhou, China;Department of Clinical Laboratory, Zhengzhou Hospital of Traditional Chinese Medicine, Zhengzhou, China;Department of Pathology, Henan Medical College, Zhengzhou, China;Department of Respiratory and Sleep Medicine in the First Affiliated Hospital, Zhengzhou University, Zhengzhou, China;;Henan Institute of Medical and Pharmaceutical Sciences &;Henan Key Laboratory of Tumor Epidemiology &

关键词: lung adenocarcinoma (LUAD);    IgM autoantibody;    carcinoembryonic antigen (CEA);    protein array;    cancer driver gene;    diagnostic model;   

DOI  :  10.3389/fimmu.2021.728853

来源: DOAJ

【 摘 要 】

Immunoglobulin M (IgM) autoantibodies, as the early appearing antibodies in humoral immunity when stimulated by antigens, might be excellent biomarkers for the early detection of lung cancer (LC). We aimed to develop a multi-analyte integrative model combining IgM autoantibodies and a traditional tumor biomarker that could be a valuable and powerful auxiliary diagnostic tool and might improve the accuracy of early detection of lung adenocarcinoma (LUAD). A customized protein array based on cancer driver genes was constructed and applied in the discovery cohort consisting of 68 LUAD patients and 68 normal controls (NCs); 31 differentially expressed IgM autoantibodies were identified. The top 5 candidate IgM autoantibodies [based on the area under the receiver operating characteristic curve (AUC) ranking], namely, TSHR, ERBB2, survivin, PIK3CA, and JAK2, were validated in the validation cohort using enzyme-linked immunosorbent assay (ELISA), which included 147 LUAD samples, 72 lung squamous cell carcinoma (LUSC) samples, 44 small cell lung carcinoma (SCLC) samples, and 147 NCs. These indicators presented diagnostic capacity for LUAD, with AUCs of 0.599, 0.613, 0.579, 0.601, and 0.633, respectively (p < 0.05). However, none of them showed a significant difference between the SCLC and NC groups, and only the IgM autoantibody against JAK2 showed a higher expression in LUSC than in NC (p = 0.046). Through logistic regression analysis, with the five IgM autoantibodies and carcinoembryonic antigen (CEA), one diagnostic model was constructed for LUAD. The model yielded an AUC of 0.827 (sensitivity = 56.63%, specificity = 93.98%). The diagnostic efficiency was superior to that of either CEA (AUC = 0.692) or IgM autoantibodies alone (AUC = 0.698). Notably, the accuracy of this model in early-stage LUAD reached 83.02%. In conclusion, we discovered and identified five novel IgM indicators and developed a multi-analyte model combining IgM autoantibodies and CEA, which could be a valuable and powerful auxiliary diagnostic tool and might improve the accuracy of early detection of LUAD.

【 授权许可】

Unknown