Developing angiogenesis-related prognostic biomarkers and therapeutic strategies in bladder cancer using deep learning and machine learning

Developing angiogenesis-related prognostic biomarkers and therapeutic strategies in bladder cancer using deep learning and machine learning

Abstract Bladder cancer (BLCA) is a prevalent urological malignancy that exhibits a high degree of tumor heterogeneity and morbidity. Tumor angiogenesis, a vital hallmark of cancer, greatly influences the tumor microenvironment (TME). The emergence of anti-angiogenic drugs has provided a new turning...

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Bibliographic Details
Main Authors: Yutong Li, Ling Zuo, Xingyu Song, Yuyang Huang, Ke Zou, Xuan Dong, Hongwei Liu
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Bladder cancer
Artificial intelligence-driven drug design
Machine learning
Antibody-drug conjugates
Saikosaponin D
Protein homology modeling
Online Access:https://doi.org/10.1038/s41598-025-08945-9
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https://doi.org/10.1038/s41598-025-08945-9

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