A novel CAF-cancer cell crosstalk-related gene prognostic index based on machine learning: prognostic significance and prediction of therapeutic response in head and neck squamous cell carcinoma.

Journal: Journal of translational medicine

PMID: 38982511

Abstract

BACKGROUND: Cancer-associated fibroblast (CAF)-cancer cell crosstalk (CCCT) plays an important role in tumor microenvironment shaping and immunotherapy response. Current prognostic indexes are insufficient to accurately assess immunotherapy response in patients with head and neck squamous cell carcinoma (HNSCC). This study aimed to develop a CCCT-related gene prognostic index (CCRGPI) for assessing the prognosis and response to immune checkpoint inhibitor (ICI) therapy of HNSCC patients.

Authors

Yuming Xu
Junda Li

Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, 510055, China.
Jinming Wang

Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, 510055, China. wjinm@mail.sysu.edu.cn.
Feilong Deng

Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, 510055, China. dengfl@mail.sysu.edu.cn.

Keywords

Cancer-Associated Fibroblasts Cell Communication Cell Line, Tumor Female Gene Expression Regulation, Neoplastic Head and Neck Neoplasms Humans Immune Checkpoint Inhibitors Machine Learning Male Prognosis Squamous Cell Carcinoma of Head and Neck Treatment Outcome Tumor Microenvironment

External Resources

View on PubMed Access via DOI PubMed (38982511)

A novel CAF-cancer cell crosstalk-related gene prognostic index based on machine learning: prognostic significance and prediction of therapeutic response in head and neck squamous cell carcinoma.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals