Evidence map›Paper›PMID 40948763›Full record

ArticleFrontiers in immunology2025

Angiogenesis-related gene NID2 profiling and immune infiltration in bladder cancer: prognostic implications and immunotherapy response.

Jinxia Cao, Wang Zheng

Abstract read
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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.

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2citing papers in PubMed
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1 · What the graph read from it

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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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5 · Who and what money

Authors and funding

2 authors.

Jinxia CaoDepartment of Hematology, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, Hunan, China.
Wang ZhengDepartment of Organ Transplantation, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Immunotherapy has progressively gained prominence as a cornerstone therapeutic modality across diverse oncological contexts, with its clinical efficacy intricately linked to the dynamic interactions between the tumor microenvironment (TME) and neoplastic cells. Central to this paradigm is angiogenesis-a quintessential hallmark of cancer-which not only sustains tumor growth but also orchestrates immunomodulatory networks within the TME, thereby profoundly influencing therapeutic responsiveness. However, in the field of bladder cancer (BC), the relationship among angiogenesis and prognosis, immunotherapy response, and immune cell infiltration remains to be further explored. Methods: To systematically uncover this relationship, we carried out an exhaustive assessment of 36 genes linked to angiogenesis (AAGs) and explored the relationship between angiogenesis and transcript, prognostic outcomes, as well as the infiltration of immune cells. By constructing an AAG_score, we quantified the angiogenic subtype characteristics of each patient. Subsequently, we evaluated the value of these characteristics in foreseeing BC prognosis and the response of treatment, and concurrently analyzed the performance of AAGs in diffuse large B-cell lymphoma for comparative study. Through RT-qPCR, CCK8 and other experiments, we verified the role of NID2 in bladder cancer. Results: This study explored different types of AAGs mutations in BC samples at the genetic level and elucidated the expression patterns of AAGs. Through in-depth analysis, we identified two distinct molecular subpopulations and found significant associations between AAG mutations and patients' clinicopathological features, prognosis, and invasive TME. We found that patients with low AAG_score showed increased microsatellite instability, high mutation tendency, and immune motivation, and had a better prognosis. NID2 plays a role in promoting proliferation in bladder cancer and evaluate in diffuse large B-cell lymphoma. In addition, our study found a significant correlation between index of cancer stem cell and AAG_score in drug sensitivity. Conclusion: In summary, our study successfully identified prognosis-related AAG characteristics in BC patients. These characteristics not only contribute to a clearer understanding of TME properties but also provide an important basis for exploring more effective immunotherapy strategies.

Indexed as

Neovascularization, PathologicUrinary Bladder NeoplasmsAgedAngiogenesisBiomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansImmunotherapyLymphocytes, Tumor-InfiltratingMaleMiddle AgedMutationPrognosisTumor MicroenvironmentBiomarkers, Tumorangiogenesisbladder cancerimmunotherapy responseTMEtumor microenvironment

Identifiers

PMID40948763
PMCPMC12426854

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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.