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Updated: Feb 16, 2026

Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing
Published on: October 10, 2025
Early detection of lung cancer by using an autoantibody panel in Chinese population
Shengxiang Ren1, Shucai Zhang2, Tao Jiang1
1Department of Medical Oncology, Shanghai Pulmonary Hospital, Thoracic Cancer Institute, Tongji University School of Medicine, Shanghai, China.
Abstract:
We have previously identified a panel of autoantibodies (AABs), including p53, GAGE7, PGP9.5, CAGE, MAGEA1, SOX2 and GBU4-5, that was helpful in the early diagnosis of lung cancer. This large-scale, multicenter study was undertaken to validate the clinical value of this 7-AABs panel for early detection of lung cancer in a Chinese population. Two independent sets of plasma samples from 2308 participants were available for the assay of AABs (training set = 300; validation set = 2008). The concentrations of AABs were quantitated by enzyme-linked immunosorbent assay (ELISA), and the optimal cutoff value for each AAB was determined in the training set and then applied in the validation set. The value of the 7-AABs panel for the early detection of lung cancer was assessed in 540 patients who presented with ground-glass nodules (GGNs) and/or solid nodules. In the validation set, the sensitivity and specificity of the 7-AABs panel were 61% and 90%, respectively. For stage I and stage II non-small cell lung cancer (NSCLC), the sensitivity of the 7-AABs panel was 62% and 59%, respectively, and for limited stage small cell lung cancer (SCLC) it was 59%; these sensitivity values were considerably higher than for traditional biomarkers (including CEA, NSE and CYFRA21-1). Importantly, the combination of the 7-AABs panel and low-dose computed tomography (CT) scanning significantly improved the diagnostic yield in patients presenting with GGNs and/or solid nodules. In conclusion, our 7-AABs panel has clinical value for early detection of lung cancer, including early-stage lung cancer presenting as GGNs.
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