Abstract

Autoantibodies hold promise for diagnosing lung cancer. However, their effectiveness in early-stage detection needs improvement. We investigated novel IgG and IgM autoantibodies for detection of early-stage lung adenocarcinoma (Early-LUAD) across three independent cohorts of 1246 individuals. A multi-step approach, including Human proteome microarray (HuProtTM) discovery, focused array verification, and ELISA validation, was conducted on 634 individuals with Early-LUAD (stage 0-I), 280 with benign lung disease (BLD), and 332 normal healthy controls (NHC). HuProtTM profiling discovered 417 IgG/IgM candidates, and focused array verified 32 autoantibodies with distinct distributions in Early-LUAD and BLD/NHC. A novel panel of 10 autoantibodies (ELAVL4-IgM, GDA-IgM, GIMAP4-IgM, GIMAP4-IgG, MGMT-IgM, UCHL1-IgM, DCTPP1-IgM, KCMF1-IgM, UCHL1-IgG, and WWP2-IgM) demonstrated a sensitivity of 70.5% and specificities of 77.0% or 80.0% in detecting Early-LUAD from BLD or NHC in ELISA validation. Positive predictive value for distinguishing Early-LUAD from BLD with nodules ≤ 8 mm, 9 ≤ IMD ≤ 20 mm, and > 20 mm significantly increased from 47.27%, 52.00% and 62.90% [low-dose computed tomography (LDCT) alone] to 79.17%, 71.13% and 87.88% (10-autoantibody panel with LDCT), respectively. The combined risk score (CRS), based on 10-autoantibody panel, sex, and imaging maximum diameter, effectively stratified risk for Early-LUAD. Individuals with scores 10-25 and > 25 indicated a higher risk of Early-LUAD compared to the reference (scores < 10), with adjusted odds ratios of 5.28 (95% CI:3.18-8.76) and 9.05 (95% CI:5.40-15.15), respectively. This novel panel of IgG and IgM autoantibodies offers a complementary approach to LDCT in distinguishing Early-LUAD from benign nodules.

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