Breast cancer is highly heterogeneous,and different molecular subtypes exhibit significant variations in their response to immunotherapy.While significant progress has been achieved in the development of immune checkpoint inhibitors,chimeric antigen receptor T-cell therapies,and personalized cancer vaccines for breast cancer,the immunosuppressive nature of the breast cancer tumor microenvironment,as well as drug resistance and treatment-related adverse events,limit the widespread application of immunotherapy.Biomarker-based precision stratification strategies can optimize patient selection and enhance the efficacy of personalized immunotherapy.Furthermore,adoptive cell therapy and cancer vaccines offer new directions for breast cancer immunotherapy,while multi-omics integration methods combined with artificial intelligence and big data analysis help improve the accuracy of efficacy prediction.The health policies worldwide are shifting toward a focus on integrated cancer prevention and treatment alongside long-term management,and international and domestic academic organizations and medical groups are advancing efforts regarding data-sharing protocols,data formats,system interface compatibility,and ethical review.In this context,the future efforts should focus on optimizing the personalized strategies for immunotherapy in clinical practice,developing novel and more effective immune targets,refining biomarker screening,and enhancing long-term chronic disease management models for cancers.With these efforts,personalized immunotherapy is expected to improve the long-term survival rate and quality of life for breast cancer patients.
Duan et al. (Tue,) studied this question.