Evidence map›Paper›PMID 41438758›Full record

ArticleFrontiers in immunology2025

SWI/SNF complex alterations predict immunotherapy response in bladder cancer.

Jian Zhang, Yapeng Wang, Qian Yan, Haitao Wang, Qiang Ran, Hailin Zhu, Weiming Luo, Yangkun Ao, Ying-Ang Ji, Jing Xu and 5 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

15 authors.

Jian Zhang *Department of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Yapeng Wang *Department of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Qian Yan *Department of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Haitao WangDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Qiang RanDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Hailin ZhuDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Weiming LuoDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Yangkun AoDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Ying-Ang JiDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Jing XuDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Jun ZhangDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Yao ZhangDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Jun JiangDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Qiuli LiuDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.
Weihua LanDepartment of Urology, Daping Hospital, Army Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immune checkpoint inhibitors have revolutionized the treatment of urothelial bladder cancer (UBC), yet response remains limited to a subset of patients. The SWItch/sucrose non-fermentable (SWI/SNF) chromatin remodeling complex is recurrently altered across cancers, but its prevalence, functional impact, and predictive value in UBC remain unclear. This study aimed to comprehensively delineate the mutational spectrum of SWI/SNF genes in UBC and assess their utility as predictive biomarkers for response to immune checkpoint blockade. Methods: We analyzed tumor specimens from 49 patients in the Daping Cohort and integrated data from five independent public cohorts comprising 2,280 cases in total. Somatic alterations were identified using targeted or whole-exome sequencing, and transcriptomic profiles were obtained from RNA sequencing datasets. Survival outcomes were evaluated using Kaplan-Meier survival analysis and time-dependent ROC curves. Tumor immune landscape was characterized via xCell-based deconvolution and corroborated by multiplex immunofluorescence on institutional samples. Prognostic modeling was performed across 65 machine-learning configurations, encompassing survival SVM, CoxBoost, and stepwise Cox, with external validation in independent cohorts. Results: SWI/SNF alterations were present in 42.8% of UBCs, with the highest frequencies in Conclusions: SWI/SNF alterations define an immunotherapy-responsive stratification of UBC. The accompanying genotype-specific prognostic models provide a ready-to-test framework for guiding precision immunotherapy.

Indexed as

Chromosomal Proteins, Non-HistoneImmunotherapyTranscription FactorsUrinary Bladder NeoplasmsAgedBiomarkers, TumorDNA-Binding ProteinsFemaleHumansImmune Checkpoint InhibitorsMaleMiddle AgedMutationPrognosisTreatment OutcomeTumor MicroenvironmentARID1A protein, humanBiomarkers, TumorChromosomal Proteins, Non-HistoneDNA-Binding ProteinsImmune Checkpoint InhibitorsTranscription Factorsbladder cancerimmune checkpoint inhibitorsmachine-learningprediction modelSWI/SNF

Identifiers

PMID41438758
PMCPMC12719508

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.