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Molecular Diagnostics

Elevated serum levels of GPX4, NDUFS4, PRDX5, and TXNRD2 as predictive biomarkers for castration resistance in prostate cancer patients: an exploratory study

British Journal of Cancer volume 132, pages 543–557 (2025)Cite this article

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Abstract

Background

Prostate cancer (PCa) is a heterogeneous disease affecting over 14% of the male population worldwide. Although patients often respond positively to initial treatments within the first 2–3 years, many eventually develop a more lethal form of the disease known as castration-resistant PCa (CRPC). At present, no biomarkers that predict the onset of CRPC are available. This study aims to provide insights into the diagnosis and prediction of CRPC emergence.

Methods

Protein expression dynamics were analysed in drug (androgen receptor inhibitor)-tolerant persister (DTP) and drug withdrawal cells using proteomics to identify potential biomarkers. These biomarkers were subsequently validated using a mouse model, 180-paired carcinoma/benign tissues, and 482 serum samples. Five machine learning algorithms were employed to build clinical prediction models, wherein the SHapley Additive exPlanation (SHAP) framework was used to interpret the best-performing model. Moreover, three regression models were developed to determine the Time from initial PCa diagnosis to CRPC development (TPC) in patients.

Results

We identified that the protein expression levels of GPX4, NDUFS4, PRDX5, and TXNRD2 were significantly upregulated in PCa patients, particularly in those with CRPC. Among the tested machine learning models, the random forest and extreme gradient boosting models performed best on tissue and serum cohorts, achieving AUCs of 0.958 and 0.988, respectively. In addition, a significant inverse correlation was observed between TPC and serum levels of these four biomarkers. This correlation was formulated in three regression models, which achieved the smallest mean absolute error of 1.903 on independent datasets for predicting CRPC emergence.

Conclusion

Our study provides new insights into the role of DTP cells in CRPC development. The quad protein panel identified in our study, along with the post hoc and intrinsically explainable prediction models, may serve as a convenient and real-time prognostic tool, addressing the current lack of clinical biomarkers for CRPC.

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Fig. 1: Protein expression dynamics in DTP cells.
Fig. 2: Functional validation of antioxidative proteins in DTP cells.
Fig. 3: Increased expression of quad proteins in PCa patients.
Fig. 4: Prediction performances of ML models on the discrimination of clinical tissue and serum samples.
Fig. 5: Global SHAP output plot of the best XGBoost in the serum cohort for CRPC class.
Fig. 6: Local SHAP output plot of the best XGBoost in the serum cohort.
Fig. 7: Predictive value of biomarkers for TPC.
Fig. 8: Association of biomarkers with TPC.

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Data availability

All data supporting the findings of this study are available with the article, or from the corresponding author upon reasonable request. Data are also available via ProteomeXchange with the identifier PXD032983.

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Funding

This study was supported by the National Natural Science Foundation of China (No. 82403686 & 82370777 & 82302654 & 31771539); by the Basic Research Program of Jiangsu (No. BK20241620 & BK20230188); by the Singapore Ministry of Health’s National Medical Research Council (NMRC) Open Fund—Individual Research Grant (OF-IRG; to L-W Ding; MOH-OFIRG21nov-0007); by the China Postdoctoral Science Foundation (No. 2024M751160); by the Jiangsu Funding Program for Excellent Postdoctoral Talent (No. 2024ZB069); and by Medical Research Program of Affiliated Hospital of Jiangnan University (No. YJY202306).

Author information

Author notes

  1. These authors contributed equally: Rong Wang, Shaopeng Wang.

Authors and Affiliations

  1. Jiangnan University Medical Center, Jiangnan University, Wuxi, China

    Rong Wang, Shaopeng Wang, Menglu Li, Yong Q. Chen & Ninghan Feng

  2. Wuxi School of Medicine, Jiangnan University, Wuxi, China

    Rong Wang, Yong Q. Chen & Ninghan Feng

  3. Affiliated Hospital of Jiangnan University, Jiangnan University, Wuxi, China

    Yuanyuan Mi, Jun Wang, Jiang Ni & Jian Wang

  4. School of Computing, National University of Singapore, Singapore, Singapore

    Tianyi Huang

  5. Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology & School of Life Sciences and Health Engineering, Jiangnan University, Wuxi, China

    Jian Yin

  6. Department of Urology, Wuxi No.2 People’s Hospital, Nanjing Medical University, Wuxi, China

    Menglu Li & Ninghan Feng

  7. Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

    Xuebin Ran, Shuangyi Fan, Soo Yong Tan & Lingwen Ding

  8. Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore

    Xuebin Ran, H. Phillip Koeffler & Lingwen Ding

  9. Department of Neurology, National Neuroscience Institute, Singapore General Hospital, Singapore, Singapore

    Qiaoyang Sun

  10. Division of Hematology/Oncology, Cedars-Sinai Medical Center, UCLA School of Medicine, California, Los Angeles, CA, USA

    H. Phillip Koeffler

  11. Nanomedicine Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

    Lingwen Ding

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  1. Rong Wang
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Contributions

RW, SPW, NHF, YQC and LWD conceptualised the study, designed and performed experiments, developed and optimised methodology, curated data, analysed data and visualised data. YYM, TYH, JW and JN developed and optimised methodology, designed and performed experiments, curated data and visualised data. JY, MML and XBR developed and optimised methodology, analysed data and visualised data. SYF, QYS, SYT and HPK developed and optimised methodology. RW and SPW drafted the manuscript. SYT, HPK, RW, SPW, YQC and JW edited the manuscript. YQC, LWD, RW, MLL and NHF provided financial support. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Lingwen Ding, Yong Q. Chen or Ninghan Feng.

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The authors declare no competing interests.

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Patient tissue and peripheral blood samples were collected from the Affiliated Hospital of Jiangnan University. Informed consent was obtained from all participants included in this study according to ethical committee regulations (the Affiliated Hospital of Jiangnan University, approval document number: LS202128).

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Wang, R., Wang, S., Mi, Y. et al. Elevated serum levels of GPX4, NDUFS4, PRDX5, and TXNRD2 as predictive biomarkers for castration resistance in prostate cancer patients: an exploratory study. Br J Cancer 132, 543–557 (2025). https://doi.org/10.1038/s41416-025-02947-0

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