five

Identification of Notch Signaling Pathway Gene Mutations as a Prognostic Biomarker for Bladder Cancer

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://figshare.com/articles/dataset/Identification_of_Notch_Signaling_Pathway_Gene_Mutations_as_a_Prognostic_Biomarker_for_Bladder_Cancer/28219645
下载链接
链接失效反馈
官方服务:
资源简介:
Purpose: The authors aimed to identify Notch signaling pathway gene mutations as a prognostic biomarker for bladder cancer. Methods: First, critical Notch signaling pathway genes were screened using The Cancer Genome Atlas and validation sets. Second, immune infiltration, protein–protein interaction network, Kyoto Encyclopedia of Genes and Genomes and Gene Set Enrichment Analysis analyses were performed. Finally, potential immunotherapy drug targets were screened using T-cell receptors, B-cell receptors and CERES scores for bladder cancer. Results: The NOTCH7 gene was identified, with a significant difference in immune infiltration level between mutant and wild type in bladder cancer, mainly related to T cells. NOTCH7 was an immunotherapy prognostic factor, and IRF1 and B2M were the potential drug targets for NOTCH7 mutation in bladder cancer. Conclusion:NOTCH7 gene mutation can be used as an immunotherapy biomarker for bladder cancer. Studies have shown that 43% of bladder cancer patients harbor somatic mutations in genes associated with the Notch signaling pathway. However, it is not clear whether these mutations impact the efficacy of immunotherapy in bladder cancer patients. In the present study, the authors aimed to elucidate whether Notch signaling pathway gene mutations are effective biomarkers for predicting immunotherapy response and prognosis in patients with bladder cancer. Results of the present study suggested that seven genes – CNTN6, CREBBP, EP300, NCOR1, NCOR2, NOTCH2 and SPEN – involved in the Notch signaling pathway can be used to predict the response of patients to immunotherapy. In addition, IRF1 and B2M can act as combination drug targets with these seven genes.
创建时间:
2025-01-16
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作