Evidence map›Paper›PMID 42682403›Full record

ArticleInternational journal of surgery (London, England)2026

Potential of RAD51C as a hub gene and therapeutic target in bladder cancer: insights from bioinformatics and experimental analysis.

Ying Xiao, Xiang Zhang, Zhe Xie, Li Tao, Xingwei Jin, Xianjin Wang, Boke Liu, Xuejian Zhou, Junwei Pan, Yuan Shao

Abstract read
In one paragraph

Article in International journal of surgery (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Ying XiaoDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0009-0001-0000-0874
Xiang ZhangDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhe XieDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Li TaoDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xingwei JinDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xianjin WangDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Boke LiuDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xuejian ZhouDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Junwei PanDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yuan ShaoDepartment of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The global incidence of tumors is rising sharply. Immune checkpoint inhibitors (ICIs) represent the mainstream of immunotherapeutic approaches. Despite the remarkable clinical benefits of immunotherapy in various tumors, ICIs resistance remains an urgent challenge to be addressed. The transcription factors cAMP response element-binding protein 1(CREB1) and c-Jun converge to regulate oncogenesis and immune modulation. Methods: Based on the 'CREBP1CJUN_01' gene set from the Molecular Signatures Database and single-cell RNA sequencing data, we identified 116 CREB-c-Jun transcription factor target-related differential genes (CR.Sig) and refined to 20 CREB-c-Jun transcription factor target-related important feature genes (Hub-CR.Sig) through multi-algorithm machine learning. This Hub-CR.Sig enabled prognostic risk modeling, molecular subtyping of bladder cancer, and somatic mutation stratification. Results: Among these 20 signatures, RAD51C emerged as a top-ranked driver that was correlated with advanced T/N/M stages, associated with poor survival outcomes and is highly expressed in bladder cancer tissues. Functional assessment revealed that RAD51C knockdown suppressed bladder cancer cell proliferation, invasion, migration, and DNA repair capacity Conclusions: The study establishes the Hub-CR.Sig as an immunotherapy response classifier and nominates RAD51C targeting as a promising therapeutic strategy for bladder cancer.

Indexed as

bladder cancerCREB–c-junmachine learningRAD51Csingle-cell sequencing

Identifiers

PMID42682403
PMCPMC13336610

What Socratic holds

Textmetadata
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.