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Molecular Diagnostics

A nomogram based on autoantibodies for noninvasive detection of AFP-negative hepatocellular carcinoma: a multicenter study

British Journal of Cancer volume 133, pages 1896–1906 (2025) Cite this article

Subjects

Abstract

Background

Diagnosing AFP-negative hepatocellular carcinoma (HCC) is challenging. Autoantibodies to tumor-associated antigens have been extensively investigated as serum biomarkers.

Methods

We employed serological proteome analysis and protein microarray to identify potential autoantibodies for HCC, followed by a two-center and two-independent-phase validation and evaluation using ELISA in patients with AFP-negative HCC (ANHCC). LASSO regression addressed multicollinearity among biomarkers. Four machine-learning methods developed diagnostic models for ANHCC. ROC analysis and various evaluation indicators were applied to assess the performance.

Results

Eight autoantibodies out of sixteen candidates, including Survivin, NPM1, GNAS, SRSF2, GNA11, PTCH1, GAPDH, and HSP90, were validated as superior biomarkers. The Logistic regression model was optimal for ANHCC, achieving an area under the ROC (AUC) of 0.883 in the training dataset and an AUC of 0.840 in the validation dataset. When tested on the entire HCC patient cohort, which included both ANHCC and AFP-positive patients (APHCC), with ANHCC accounting for 37.5%, the AUC reached 0.825, with a sensitivity of 66.4%, and a specificity of 84.2%. Combining this model with AFP improved efficacy, yielding an AUC of 0.945, an IDI of 23.1%, and an NRI of 21.1% compared to using AFP alone.

Conclusion

The Logistic regression model demonstrates superior diagnostic performance for ANHCC. Integrating this model with AFP enhances the entire HCC diagnosis.

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Fig. 1: Flow chart of the study.
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Fig. 2: The findings from SERPA.
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Fig. 3: Distribution of candidate biomarkers discovered from protein microarray among three groups (ANHCC, APHCC, HD).
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Fig. 4: The existence and resolution of collinearity.
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Fig. 5: The Logistic regression model.
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Fig. 6: The evaluation of the Logistic regression model and AFP in HCC.
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Data availability

The supporting materials were all included in the manuscript; raw data can be obtained from the corresponding author at reasonable request.

Code availability

All statistical analyses and visualizations were conducted by SPSS 21.0 or R4.2.2 software. The computer code used in the study can be obtained from the corresponding author at a reasonable request.

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Acknowledgements

The authors thank the Henan Key Laboratory for Pharmacology of Liver Diseases for kindly providing the experimental platform.

Funding

This research was funded by the Project of Basic Research Fund of Henan Institute of Medical and Pharmacological Sciences under Grant no. 2025BP0103-2; the National Science and Technology Major Project of China under Grant no. 2018ZX10302205.

Author information

Authors and Affiliations

  1. Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450052, China

    Keyan Wang, Wenzhuo Xiong, Xuehui Duan, Qing Li, Jingjing Liu, Renle Du, Jianxiang Shi & Liping Dai

  2. Henan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, China

    Keyan Wang, Hua Ye, Jianxiang Shi, Peng Wang & Liping Dai

  3. Henan Key Medical Laboratory of Tumor Molecular Biomarkers, Zhengzhou, China

    Keyan Wang, Wenzhuo Xiong, Xuehui Duan, Qing Li, Jingjing Liu, Renle Du & Liping Dai

  4. Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China

    Pengfei Ren

  5. Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China

    Hua Ye & Peng Wang

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Contributions

PW, KW, and LD designed the research; LD and PW managed the project and were responsible for sample acquisition; KW, WX, and XD primarily conducted the experiments, analysed the data, generated the figures and tables, and drafted the initial manuscript; QL, PR, HY, JS, RD, and JL provided input on data analysis and interpretation of results. All authors revised the manuscript critically for important intellectual content and have read and approved the final version of the manuscript.

Corresponding authors

Correspondence to Peng Wang or Liping Dai.

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The authors declare no competing interests.

Ethics

This study was reviewed and approved by the Ethics Committee of Zhengzhou University, with the approval number: [ZZURIB 2019-001].

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All participants/patients (or their proxies/legal guardians) provided informed consent to participate in the study.

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Wang, K., Xiong, W., Duan, X. et al. A nomogram based on autoantibodies for noninvasive detection of AFP-negative hepatocellular carcinoma: a multicenter study. Br J Cancer 133, 1896–1906 (2025). https://doi.org/10.1038/s41416-025-03215-x

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