Commentary: Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in cholangiocarcinoma

被引:13
|
作者
Wu, Liusheng [1 ,2 ]
Li, Xiaoqiang [3 ]
Yan, Jun [1 ]
机构
[1] Tsinghua Univ, Beijing Tsinghua Changgung Hosp, Ctr Hepatobiliary Pancreat Dis, Sch Clin Med, Beijing 100084, Peoples R China
[2] Natl Univ Singapore, Yong Loo Lin Sch Med, Singapore 119077, Singapore
[3] Peking Univ, Shenzhen Hosp, Dept Thorac Surg, Shenzhen 518036, Guangdong, Peoples R China
来源
TRANSLATIONAL ONCOLOGY | 2024年 / 45卷
关键词
Machine learning; Intratumor heterogeneity signature; Survival prognosis; Cholangiocarcinoma; Immune microenvironment; Commentary;
D O I
10.1016/j.tranon.2024.101995
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Machine learning has made great progress in the field of medicine, especially in oncology research showing significant potential. In this paper, the application of machine learning in the study of cholangiocarcinoma was discussed. By developing a novel intra-tumor heterogeneity feature, the study successfully achieved accurate prediction of prognosis and immunotherapy effect in patients with cholangiocarcinoma. This study not only provides strong support for personalized treatment, but also provides key information for clinicians to develop more effective treatment strategies. This breakthrough marks the continuous evolution of machine learning in cancer research and brings new hope for the future development of the medical field. Our study lays a solid foundation for deepening the understanding of the biological characteristics of cholangiocarcinoma and improving the therapeutic effect, and provides a useful reference for more extensive cancer research.
引用
收藏
页数:3
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