Precision Medicine Approaches in Breast Cancer: Current Strategies and Future Directions

Abstract

Precision medicine has revolutionized the approach to breast cancer treatment by leveraging molecular subtyping, biomarker identification, genomic profiling, and targeted therapies. This comprehensive review explores the significance of breast cancer subtypes—Luminal A, Luminal B, HER2+, and triple-negative—and their respective molecular characteristics and prognoses. It discusses the pivotal role of biomarkers such as HER2, estrogen receptors (ER), and progesterone receptors (PR) in predicting prognosis and therapy response. The review delves into advanced genomic profiling techniques, including next-generation sequencing (NGS) and fluorescence in situ hybridization (FISH), and their implications for personalized treatment plans. Furthermore, it highlights the potential of liquid biopsies and circulating tumor DNA (ctDNA) in non-invasive cancer diagnostics and monitoring. The integration of machine learning and artificial intelligence in predictive modeling and treatment algorithms is examined, along with the challenges posed by tumor heterogeneity and access to genomic testing. Future prospects, such as the expansion of CRISPR-based technologies and machine learning, are also discussed. Finally, strategies for integrating precision medicine into clinical practice and future innovations in the field are highlighted, emphasizing the importance of collaboration, patient education, and shared decision-making.