Optimizing the treatment strategy of breast cancer

Breast cancer is a global health problem and the leading cause of cancer-related death in women. The aim of this thesis is to explore new techniques that may support the refinement of surgical treatment for breast cancer and to assess characteristics of the primary tumor and its associated immune microenvironment that may support more optimized systemic therapy. We developed and externally validated a mathematical model to predict the risk of axillary lymph node metastasis. Using this model, we are able to preoperatively identify a group of low-risk patients who may be candidates for the omission of axillary surgery. We explored the feasibility and accuracy of two novel techniques (fluorescent optical molecular imaging and micro-CT scanning) for intraoperative surgical margin assessment. Both techniques are feasible as intraoperative tools and can potentially support improved surgical margin assessment in breast-conserving surgery. We described the androgen receptor (AR) expression and tumor immune microenvironment of primary HER2-positive breast cancer. AR expression is inversely correlated with immune cell infiltration. Based on tumor AR expression and the composition of infiltrated immune cells, different subsets of HER2-positive breast cancers can be identified, which may require different treatment strategies. Surgical treatment for breast cancer has developed towards a less invasive procedure and systemic treatment has been increasingly tumor biology-based. Our studies provide clinicians new tools to learn about the possible residual tumor in the breast or axilla and new insights into the tumor biology of breast cancer. This may support the optimization of the treatment strategy of this disease