Evidence map›Paper›PMID 41264154›Full record

ReviewDiscover oncology2025

Research progress on the role of AGC kinase family in bladder cancer.

Peng Su, Ying Yang, Xiulan Luo, Neng Zhang, Hong Zheng

Abstract readReview
In one paragraph

Review in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Peng SuDepartment of Urology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, China.
Ying YangDepartment of Pathology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, China.
Xiulan LuoDepartment of Pathology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, China.
Neng ZhangDepartment of Urology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, China. energy20170118@hotmail.com.
Hong ZhengDepartment of Pathology, Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, Guizhou, China. zhenghonghq@hotmail.com.

Funding

the Science and Technology Fund Project of Guizhou Provincial Health Commission of China gzwkj2025-063the Zunyi Municipal Science and Technology Program Zunshi Kehe HZ [2024] 189
6 · The paper itself

Abstract

Bladder cancer is a common malignant tumor worldwide, with rising incidence and mortality rates. In recent years, the role of the AGC kinase family (including PKA, PKC, PKG, etc.) in the initiation, progression, and metastasis of bladder cancer has attracted widespread attention. AGC kinases regulate various cellular processes such as proliferation, migration, metabolism, and apoptosis through phosphorylation of specific substrates. Aberrant activation or expression of these kinases is closely associated with the malignant progression of bladder cancer. This review summarizes the current research on the AGC kinase family in bladder cancer, focusing on the roles of PKA, PKC, and PKG in bladder cancer cell biology, and discusses key signaling pathways related to these kinases, such as the PI3K/Akt and MAPK/ERK pathways. Furthermore, the potential of AGC kinases as therapeutic targets has been extensively explored, with preclinical studies showing promising results for targeted inhibitors and combination therapies. Finally, we discuss future research directions, including molecular mechanisms of AGC kinases, the development of targeted therapies, and clinical trial design, aiming to provide a theoretical basis and strategy for bladder cancer treatment.

Indexed as

AGC kinaseBladder cancerFuture research directionsPotential targetsSignaling pathways

Identifiers

PMID41264154
PMCPMC12923714

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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 Socratic graph.