Assessing biomarkers for patients with breast cancer who are suited for adjuvant therapy.

Biomarker-guided stratification is essential for optimizing adjuvant systemic therapy in early-stage breast cancer, requiring a balance between therapeutic benefit and avoidance of overtreatment. This review summarizes established and emerging prognostic and predictive biomarkers guiding adjuvant therapy selection. Evidence was synthesized from structured searches of PubMed, EMBASE, clinical trial databases and author expertise, focusing on morphological and molecular biomarkers, including multigene assays, protein and immune-based markers, mutation profiling, liquid biopsy and artificial intelligence (AI). Although clinicopathological factors such as tumor size, grade, and nodal status remain fundamental, clinical decision-making is increasingly driven by biologically informed precision. ER and HER2 status continue to underpin prognostic and predictive assessment. In hormone receptor-positive disease, multigene assays refine recurrence risk and chemotherapy benefit, while tools such as HER2DX improve stratification in HER2-positive tumors. Immune and DNA-repair biomarkers inform targeted therapy in HER2-positive and triple-negative subtypes. Mutation profiling of ESR1, PIK3CA, AKT, mTOR, and PTEN increasingly informs targeted treatment, particularly in advanced disease. Emerging approaches, including liquid biopsy, AI, and multi-omics integration, offer dynamic insights but require prospective validation. Future progress depends on assay standardization, equitable access, and validation within adaptive clinical trial frameworks, supporting integrated molecular-clinical and AI-enhanced models for personalized therapy.