Developing an immune signature for triple-negative breast cancer to predict prognosis and immune checkpoint inhibitor response.

Autor: Wang C; Department of Biostatistics, School of Public Health, & The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing 100083, China., Feng G; Big Data & Engineering Research Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing 100083, China., Zhu J; Department of Biostatistics, School of Public Health, & The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China., Wei K; Department of Biostatistics, School of Public Health, & The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China., Huang C; Department of Biostatistics, School of Public Health, & The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China., Wu Z; Department of Biostatistics, School of Public Health, & The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China., Yu Y; Department of Biostatistics, School of Public Health, & The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China., Qin G; Department of Biostatistics, School of Public Health, & The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing 100083, China.
Jazyk: angličtina
Zdroj: Future oncology (London, England) [Future Oncol] 2022 Mar; Vol. 18 (9), pp. 1055-1066. Date of Electronic Publication: 2022 Feb 02.
DOI: 10.2217/fon-2021-0600
Abstrakt: Aim: We aimed to develop a new signature based on immune-related genes to predict prognosis and response to immune checkpoint inhibitors in patients with triple-negative breast cancer (TNBC). Materials & methods: Single-sample gene set enrichment was used to develop an immune-based prognostic signature (IPRS) for TNBC patients. We conducted multivariate Cox analysis to evaluate the prognosis value of the IPRS. Result: An IPRS based on 66 prognostic genes was developed. Multivariate Cox analysis indicated that the IPRS was an independent factor for prognosis. PD-1 , PD-L1 , PD-L2 and CTLA4 gene expression was higher in the low-risk group, suggesting IPRS could predict the response to immune checkpoint inhibitors. Conclusion: The IPRS might be a reliable signature to predict TNBC patients' prognosis and response to immune checkpoint inhibitors, but needs prospective validation.
Databáze: MEDLINE