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<p>Cancer-associated fibroblasts (CAFs) exhibit heterogeneity and play diverse roles in prostate cancer (PCa) progression, yet their specific impact via lactate metabolism remains unexplored. This study identifies a CAFs lactate metabolism-associated transcriptomic signature (CLS) through multi-omics analysis and establishes a Lactate Metabolism-Related Clinical Prognostic Index (LMCAFCPI) using machine learning. Lactate metabolism genes from MsigDB, were used to derive CLS from single-cell RNA sequencing (scRNA-seq). Unsupervised clustering divided samples into two risk subgroups, and GSVA and ssGSEA assessed biological functions and immune features. The LMCAFCPI demonstrated superior prognostic performance. A nomogram incorporating Gleason grade, PSA, T-stage, and LMCAFCPI showed stable biochemical recurrence (BCR) prediction. The study also revealed positive correlations between LMCAFCPI and specific immune cells, and validated signature genes in cellular models. CUT-TAG sequence confirmed PA2G4 knockdown in CAFs suppresses PCa proliferation and metastasis by inhibit H3K18la. Overall, LMCAFCPI offers a novel prognostic tool for PCa management and highlights potential targets for future research, with PA2G4 emerging as a potential therapeutic target due to its inhibition of H3K18la in PCa.</p>

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PA2G4 in CAFs promotes biochemical recurrence of prostate cancer via H3K18la

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月4日

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  • Shiyu Ji,
  • Zhen Xi,
  • Tiewen Li,
  • Gaozhen Jia,
  • Yu Zhang,
  • Chenghao Zheng,
  • Wenhao Wang,
  • Wanze Ni,
  • Yichen Zhang,
  • Zeng Zhou,
  • Wenbo Wu,
  • Qi Jiang

摘要

Cancer-associated fibroblasts (CAFs) exhibit heterogeneity and play diverse roles in prostate cancer (PCa) progression, yet their specific impact via lactate metabolism remains unexplored. This study identifies a CAFs lactate metabolism-associated transcriptomic signature (CLS) through multi-omics analysis and establishes a Lactate Metabolism-Related Clinical Prognostic Index (LMCAFCPI) using machine learning. Lactate metabolism genes from MsigDB, were used to derive CLS from single-cell RNA sequencing (scRNA-seq). Unsupervised clustering divided samples into two risk subgroups, and GSVA and ssGSEA assessed biological functions and immune features. The LMCAFCPI demonstrated superior prognostic performance. A nomogram incorporating Gleason grade, PSA, T-stage, and LMCAFCPI showed stable biochemical recurrence (BCR) prediction. The study also revealed positive correlations between LMCAFCPI and specific immune cells, and validated signature genes in cellular models. CUT-TAG sequence confirmed PA2G4 knockdown in CAFs suppresses PCa proliferation and metastasis by inhibit H3K18la. Overall, LMCAFCPI offers a novel prognostic tool for PCa management and highlights potential targets for future research, with PA2G4 emerging as a potential therapeutic target due to its inhibition of H3K18la in PCa.