Evidence map›Paper›PMID 39995998›Full record

ArticlePeerJ2025

Construction and verification of a prognostic model for bladder cancer based on disulfidptosis-related angiogenesis genes.

Zhihao Zhou, Yuwei Zhang, Yuhua Zhou, Jiayu Gu, Jufa Li, Jianfeng Shao, Ninghan Feng

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

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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

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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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.

Zhihao Zhou *Wuxi School of Medicine, Jiangnan University, Wuxi, China.
Yuwei Zhang *Medical School of Nantong University, Nantong, China.
Yuhua ZhouWuxi School of Medicine, Jiangnan University, Wuxi, China.
Jiayu GuWuxi School of Medicine, Jiangnan University, Wuxi, China.
Jufa LiWuxi School of Medicine, Jiangnan University, Wuxi, China.
Jianfeng ShaoWuxi School of Medicine, Jiangnan University, Wuxi, China.
Ninghan FengWuxi School of Medicine, Jiangnan University, Wuxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Bladder cancer (BLCA) is the most common malignancy of the urinary system and one of the most common cancers worldwide. This study seeks to examine the influence of angiogenesis-related genes (ARGs) linked to disulfidptosis on BLCA patients and to formulate a prognostic model for evaluating their prognosis and response to immunotherapy. Methods: This study used sequencing data of BLCA in the Cancer Genome Atlas (TCGA) database. Unsupervised consensus clustering analysis, cox regression analysis, and least absolute shrinkage and selection operator (LASSO) regression analysis were used to screen hub genes and construct a related prognostic risk model. The receiver operating characteristic (ROC) curve and independent prognostic analysis were then used to verify the predictive performance of the signature genes. Clinical characteristics, immune status, and Tumor Mutation Burden (TMB) of the prognostic risk model were evaluated. The expression levels of model genes within standard bladder epithelial cell lines (SV-HUC-1) and bladder cancer cell lines (T24 and SW1710) were quantified through qRT-PCR. Results: The constructed prognostic risk model can be used as an independent risk indicator for BLCA and was validated in an external dataset. Immune cell infiltration analysis showed that CD8+T cells, Tregs and dendritic cells were significantly different between the two groups. A significant increase was observed in the Stromal score, Immune score and ESTIMATE score in the high-risk group compared with the low-risk group. The Immune Exclusion score and Tumor Immune Dysfunction and Exclusion (TIDE) score of the high-risk group were higher than those of the low-risk score group. Compared with the normal bladder epithelial cell line (SV-HUC-1), the expression levels of 2 model genes (COL5A2 and SCG2) in bladder cancer cell lines (T24 and SW1710) were significantly elevated. Conclusion: This study helps us understand the characteristics of disulfidptosis-related subgroups. The characteristics of disulfidptosis-related ARGs may be used to evaluate the prognosis and immunotherapy response of BLCA patients.

Indexed as

Neovascularization, PathologicUrinary Bladder NeoplasmsAgedAngiogenesisBiomarkers, TumorCell Line, TumorDisulfidptosisFemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisBiomarkers, TumorAngiogenesisBladder cancerDisulfidptosisImmunePrognostic model

Identifiers

PMID39995998
PMCPMC11849515

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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.