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Integrated proteogenomic characterization of localized prostate cancer identifies biological insights and subtype-specific therapeutic strategies

Author

Listed:
  • Wei Ou

    (Sun Yat-sen University)

  • Xin-Xin Zhang

    (Sun Yat-sen University)

  • Bin Li

    (Sun Yat-sen University)

  • Ying Tuo

    (Sun Yat-sen University)

  • Ren-Xuan Lin

    (Sun Yat-sen University)

  • Peng-Fei Liu

    (Ltd)

  • Jian-Ping Guo

    (Guangzhou)

  • Hio-Cheng Un

    (Sun Yat-sen University)

  • Ming-Hao Li

    (Sun Yat-sen University)

  • Jia-Hao Lei

    (Sun Yat-sen University)

  • Xiao-Jing Gao

    (Ltd)

  • Fu-Fu Zheng

    (Sun Yat-sen University)

  • Ling-Wu Chen

    (Sun Yat-sen University)

  • Ling-Li Long

    (Sun Yat-sen University)

  • Zong-Ren Wang

    (Sun Yat-sen University)

Abstract

Localized prostate cancer (PCa) is highly variable in their response to therapies. Although a fraction of this heterogeneity can be explained by clinical factors or genomic and transcriptomic profiling, the proteomic-based profiling of aggressive PCa remains poorly understood. Here, we profiled the genome, transcriptome, proteome and phosphoproteome of 145 cases of localized PCa in Chinese patients. Proteome-based stratification of localized PCa revealed three subtypes with distinct molecular features: immune subgroup, arachidonic acid metabolic subgroup and sialic acid metabolic subgroup with highest biochemical recurrence (BCR) rates. Further, we nominated NANS protein, a key enzyme in sialic acid synthesis as a potential prognostic biomarker for aggressive PCa and validated in two independent cohorts. Finally, taking advantage of cell-derived orthotopic transplanted mouse models, single-cell RNA sequencing (scRNA-seq) and immunofluorescence analysis, we revealed that targeting NANS can reverse the immunosuppressive microenvironment through restricting the sialoglycan-sialic acid-recognizing immunoglobulin superfamily lectin (Siglec) axis, thereby inhibiting tumor growth of PCa. In sum, we integrate multi-omic data to refine molecular subtyping of localized PCa, and identify NANS as a potential prognostic biomarker and therapeutic option for aggressive PCa.

Suggested Citation

  • Wei Ou & Xin-Xin Zhang & Bin Li & Ying Tuo & Ren-Xuan Lin & Peng-Fei Liu & Jian-Ping Guo & Hio-Cheng Un & Ming-Hao Li & Jia-Hao Lei & Xiao-Jing Gao & Fu-Fu Zheng & Ling-Wu Chen & Ling-Li Long & Zong-R, 2025. "Integrated proteogenomic characterization of localized prostate cancer identifies biological insights and subtype-specific therapeutic strategies," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-58569-w
    DOI: 10.1038/s41467-025-58569-w
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    References listed on IDEAS

    as
    1. Yujin Hoshida, 2010. "Nearest Template Prediction: A Single-Sample-Based Flexible Class Prediction with Confidence Assessment," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-8, November.
    2. Jing Li & Chuanliang Xu & Hyung Joo Lee & Shancheng Ren & Xiaoyuan Zi & Zhiming Zhang & Haifeng Wang & Yongwei Yu & Chenghua Yang & Xiaofeng Gao & Jianguo Hou & Linhui Wang & Bo Yang & Qing Yang & Hua, 2020. "A genomic and epigenomic atlas of prostate cancer in Asian populations," Nature, Nature, vol. 580(7801), pages 93-99, April.
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