Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer

Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer

Abstract Prostate cancer (PCa) remains a leading cause of cancer-related mortality, necessitating robust prognostic models and personalized therapeutic strategies. This study integrated bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics to construct a prognostic...

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Bibliographic Details
Main Authors: Zhenwei Wang, Zhihong Dai, Yuren Gao, Zhongxiang Zhao, Zhen Li, Liang Wang, Xiang Gao, Qiuqiu Qiu, Xiaofu Qiu, Zhiyu Liu
Format: Article
Language:English
Published: Springer 2025-05-01
Series:Discover Oncology
Subjects:
Prostate cancer
Machine learning
Tumor microenvironment
Fatty acid metabolism
Ferroptosis
Multi-omics
Online Access:https://doi.org/10.1007/s12672-025-02484-5
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https://doi.org/10.1007/s12672-025-02484-5

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