Evidence map›Paper›PMID 41189032›Full record

ArticleCell & bioscience2025

PA2G4 in CAFs promotes biochemical recurrence of prostate cancer via H3K18la.

Shiyu Ji, Zhen Xi, Tiewen Li, Gaozhen Jia, Yu Zhang, Chenghao Zheng, Wenhao Wang, Wanze Ni, Yichen Zhang, Zeng Zhou and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell & bioscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Shiyu Ji *Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Zhen Xi *Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Tiewen Li *Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Gaozhen JiaDepartment of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Yu ZhangDepartment of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Chenghao ZhengDepartment of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Wenhao WangDepartment of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Wanze NiDepartment of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Yichen ZhangDepartment of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Zeng ZhouDepartment of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China.
Wenbo WuDepartment of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China. hamstorm@sjtu.edu.cn.
Qi JiangDepartment of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 100 Haining Road, Shanghai, 200080, China. jiangqigi@alumni.sjtu.edu.cn.

Funding

National Natural Science Foundation of China 81972407
6 · The paper itself

Abstract

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.

Indexed as

CAFsLactate metabolismPCaPredictive signature

Identifiers

PMID41189032
PMCPMC12584258

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.