Evidence map›Paper›PMID 41162406›Full record

ArticleScientific reports2025

Comprehensive analysis of coagulation-associated gene signature in bladder cancer diagnosis, prognosis, and immunotherapy.

Guicao Yin, Shengqi Zheng, Jialong Wang, Tianchi Hua, Wei Zhang, Xiang Pan, Wei Sha, Yifan Li

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

8 authors.

Guicao Yin *Department of Urology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, 225000, Jiangsu, China.
Shengqi Zheng *Department of Urology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, 225000, Jiangsu, China.
Jialong Wang *Department of Urology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, 225000, Jiangsu, China.
Tianchi HuaDepartment of Urology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, 225000, Jiangsu, China.
Wei ZhangDepartment of Urology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, 225000, Jiangsu, China.
Xiang PanOrgan Transplant Center, General Hospital of Northern Theater Command, Shenyang, China. docpanxiang@163.com.
Wei ShaDepartment of Urology, Xuyi People's Hospital, Yangzhou University, Huaian, 211700, Jiangsu, China. 605995837@qq.com.
Yifan LiDepartment of Urology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, 225000, Jiangsu, China. 092107@yzu.edu.cn.

Funding

Yangzhou Science and Technology Commission YZ2024120
6 · The paper itself

Abstract

In recent years, research on the relationship between coagulation system abnormalities and tumor immunity has been widely reported. Bladder cancer (BC), as an immunogenic tumor, holds great promise in immunotherapy. The role of coagulation-related genes in predicting the prognosis of BC patients and the efficacy of immunotherapy remains to be explored. In this study, we utilized the TCGA data system to analyze the biological functions of coagulation-related genes (CRGs) in BC patients. Additionally, we employed multiple machine learning methods (LASSO regression, SVM-RFE regression, and random forest) to establish diagnostic and prognostic signatures for BC based on CRGs. Univariate and multivariate Cox analyses indicated that the prognostic signature is an independent risk factor. Combining risk scores and independent clinical parameters, we established a Nomogram with a C-index of 0.812. Furthermore, we applied CRGs to cluster BC patients, and significant differences were observed between the two clusters in terms of immune cell infiltration, immune cell pathway activity, and response to immunotherapy. In conclusion, we systematically analyzed the value of CRGs in the diagnosis, prognosis, and personalized treatment of BC patients.

Indexed as

Blood CoagulationImmunotherapyTranscriptomeUrinary Bladder NeoplasmsAgedBiomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMachine LearningMaleMiddle AgedNomogramsPrognosisBiomarkers, TumorBladder cancerCoagulation-related geneDiagnostic signaturePrognostic signature

Identifiers

PMID41162406
PMCPMC12572289

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