Precision therapy for driver gene mutations in breast cancer: Current landscape and future perspectives

Table 3 Core challenges in precision therapy for driver genes in breast cancer

Challenge dimension	Specific problem	Impact on clinical practice
Technology and management	Lack of standardization: Non-uniform gene coverage and bioinformatics pipelines across NGS panels	Poor comparability of results, affecting reliability of treatment decisions and clinical trial enrollment[31]
Technology and management	VUS interpretation dilemma: Interpretation of “VUS” highly dependent on expert experience	Leads to clinical decision hesitancy, potentially causing patient anxiety or missed treatment opportunities[32]
Tumor biology	Spatiotemporal heterogeneity: Significant clonal evolution between primary and metastatic sites, and pre-/post-treatment	Single biopsy fails to represent the whole tumor landscape, leading to treatment failure based on localized information[34]
Tumor biology	Complex resistance mechanisms: Involve on-target mutations, bypass activation, histological transformation, etc.	Makes subsequent treatment selection extremely complex, often requiring re-biopsy for dynamic assessment[35]
Clinical translation	Drug toxicity management: e.g., hyperglycemia with alpelisib	Affects patient quality of life and treatment adherence[11]
Clinical translation	Optimization of combination strategies and sequencing: Unclear optimal order of targeted agents	Difficult to maximize efficacy and delay resistance; most combinations remain exploratory[35]

NGS: Next-generation sequencing; VUS: Variant of uncertain significance.