Evidence map›Paper›PMID 41800135›Full record

ArticlePeerJ2026

Neuro-immune-related gene signatures define molecular subtypes and prognostic score in bladder cancer with SERPINE2 as a potential therapeutic target.

Qiwei Nie, Minyao Jiang, Song Wan, Ming Xi, Wei Hua, Funeng Jiang, Weide Zhong

Abstract read
In one paragraph

Article in PeerJ, 2026. 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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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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

7 authors.

Qiwei NieSchool of Medicine, Jinan University, Guangzhou, China.
Minyao JiangDepartment of Urology, Huadu District People's Hospital of Guangzhou, Huadu Institute of Medical Sciences, Guangzhou, China.
Song WanDepartment of Urology, Huadu District People's Hospital of Guangzhou, Huadu Institute of Medical Sciences, Guangzhou, China.
Ming XiDepartment of Urology, Huadu District People's Hospital of Guangzhou, Huadu Institute of Medical Sciences, Guangzhou, China.
Wei HuaDepartment of Urology, Huadu District People's Hospital of Guangzhou, Huadu Institute of Medical Sciences, Guangzhou, China.
Funeng JiangDepartment of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
Weide ZhongSchool of Medicine, Jinan University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuro-immune interactions are critical in cancer, yet their molecular features in bladder cancer remain unclear. We analyzed transcriptomic data from TCGA and UCSC Xena to investigate the expression profiles and molecular subtypes of neuro-immune-related genes, and constructed a neuro-immune-related score (NAS) model. Single-cell transcriptomic data were integrated to explore the immune microenvironmental features, and functional validation was performed by knocking down SERPINE2 with shRNA in T24 cells. The results showed that six core genes (SERPINE2, NXPH4, SERPINB2, C2orf40, SERPINB12, SERPINB10) were identified to stratify patients into high- and low-risk groups, with robust predictive power across clinical subgroups and validation cohorts. Single-cell RNA-seq data revealed significant NAS heterogeneity among cell populations. The NAS-high state was enriched in TGFβ, EGF, and FGF signaling with activation of EZH2 and SMARCA4, while the NAS-low state showed immune-regulatory features. Functional assays confirmed that SERPINE2 knockdown suppressed proliferation, migration, invasion, while increasing apoptosis of T24 cells, highlighting its oncogenic role. Moreover, genome-wide association studies (GWAS) suggested that genetic variants in SERPINE2 and related genes may increase bladder cancer susceptibility. Collectively, our findings provide novel insights into neuro-immune-driven tumor heterogeneity and immune remodeling, establish the NAS model as an innovative prognostic tool, and identify SERPINE2 as a promising therapeutic target for precision management of bladder cancer.

Indexed as

Serpin E2Urinary Bladder NeoplasmsBiomarkers, TumorCell Line, TumorCell ProliferationGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPrognosisTranscriptomeTumor MicroenvironmentBiomarkers, TumorSerpin E2SERPINE2 protein, humanBladder cancerNeuro-immune interactionsNeuro-immune–related scoreSERPINE2Single-cell RNA sequencingTranscriptomics

Identifiers

PMID41800135
PMCPMC12967077

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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.