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Objective <p>To investigate the diagnostic value of seven lung cancer-related autoantibodies (7-AABs) and four tumor markers (4-TMs) for the early detection of lung cancer, aiming to assess their combined effectiveness compared to individual applications.</p> Methods <p>We analyzed serum samples from 110 lung cancer patients and 50 age-matched patients with benign lung nodules. Serum concentrations of 7-AABs (including SOX2, GAGE 7, CAGE, MAGE A1, P53, GBU4-5, and PGP9.5) and 4-TMs (CEA, NSE, CYFRA21‑1, and SCCA) were measured using ELISA. Receiver operating characteristic (ROC) curves were conducted to evaluate the value of combining tumor markers with serum 7-AABs for early diagnosis of lung cancer.</p> Results <p>In the malignant group, significantly elevated levels of seven autoantibodies (7-AABs), including SOX2, GAGE 7, CAGE, MAGE A1, P53, GBU4-5, and PGP9.5, as well as four tumor markers (4-TMs), namely CEA, NSE, CYFRA21‑1, and SCCA, were observed compared to the benign group, with markedly higher positivity rates for these biomarkers in the malignant group. The combined analysis of 7-AABs and 4-TMs yielded the highest diagnostic accuracy with an AUC of 0.977, significantly improving sensitivity and specificity. Notably, SOX2 and CEA showed distinct patterns across different lung cancer histological types, enhancing diagnostic differentiation. Furthermore, decision curve analysis (DCA) demonstrated the superior clinical net benefit of the 7-AABs full model over a baseline P53 model across a wide range of risk thresholds, providing a more clinically relevant metric for evaluating diagnostic performance.</p> Conclusion <p>Our findings suggest that combining autoantibodies and tumor markers may improve the early detection of lung cancer, offering a potentially non-invasive, cost-effective, and accurate diagnostic tool. However, due to the limitations of our study, such as the relatively small sample size and single-center design, these results need to be validated in larger, multi-center cohorts. This combined biomarker approach could complement existing screening methods, but further research is required to confirm its clinical utility and integration into current screening practices.</p>

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The early diagnostic value of lung cancer autoantibodies and tumor markers in lung cancer

  • 期刊论文

  • 发表日期：

    2026年3月13日

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  • Yanyan Hao,
  • Pengfei Wang,
  • Zhiping Zhao,
  • Jiande Cheng

摘要

Objective

To investigate the diagnostic value of seven lung cancer-related autoantibodies (7-AABs) and four tumor markers (4-TMs) for the early detection of lung cancer, aiming to assess their combined effectiveness compared to individual applications.

Methods

We analyzed serum samples from 110 lung cancer patients and 50 age-matched patients with benign lung nodules. Serum concentrations of 7-AABs (including SOX2, GAGE 7, CAGE, MAGE A1, P53, GBU4-5, and PGP9.5) and 4-TMs (CEA, NSE, CYFRA21‑1, and SCCA) were measured using ELISA. Receiver operating characteristic (ROC) curves were conducted to evaluate the value of combining tumor markers with serum 7-AABs for early diagnosis of lung cancer.

Results

In the malignant group, significantly elevated levels of seven autoantibodies (7-AABs), including SOX2, GAGE 7, CAGE, MAGE A1, P53, GBU4-5, and PGP9.5, as well as four tumor markers (4-TMs), namely CEA, NSE, CYFRA21‑1, and SCCA, were observed compared to the benign group, with markedly higher positivity rates for these biomarkers in the malignant group. The combined analysis of 7-AABs and 4-TMs yielded the highest diagnostic accuracy with an AUC of 0.977, significantly improving sensitivity and specificity. Notably, SOX2 and CEA showed distinct patterns across different lung cancer histological types, enhancing diagnostic differentiation. Furthermore, decision curve analysis (DCA) demonstrated the superior clinical net benefit of the 7-AABs full model over a baseline P53 model across a wide range of risk thresholds, providing a more clinically relevant metric for evaluating diagnostic performance.

Conclusion

Our findings suggest that combining autoantibodies and tumor markers may improve the early detection of lung cancer, offering a potentially non-invasive, cost-effective, and accurate diagnostic tool. However, due to the limitations of our study, such as the relatively small sample size and single-center design, these results need to be validated in larger, multi-center cohorts. This combined biomarker approach could complement existing screening methods, but further research is required to confirm its clinical utility and integration into current screening practices.