Targeting breast cancer cells and their microenvironment: Pre-clinical models and translational studies

Breast cancer is the most common cause of cancer death among women worldwide. It also occurs in men, although far less frequently. It is increasingly recognized that not only the tumor cells, but also the tissue embedding the tumor cells, the tumor microenvironment, plays an important role in tumor progression. The microenvironment consists of several cellular and soluble components as well as the extracellular matrix. This thesis aimed to further characterize the influence of the microenvironment on breast cancer behavior via different approaches and to describe strategies for exploiting the microenvironment for improved breast cancer treatment. An important component of the breast cancer microenvironment comprises the interaction between cancer cells and the immune system. Using immunohistochemistry to characterize the microenvironment of male breast cancer, we observed lower expression of immune factor PD-L1 in the male breast cancer samples compared to the female samples. Moreover, PD-L1 expression was related to adverse factors such as lymph node positive disease and higher tumor grade. Treating breast cancer cells combined with stromal cells with zoledronic acid showed the possibility of using the microenvironment to target breast cancer cells. This drug exerted an anti-breast cancer effect only in the presence of stromal cells. To study the tumor microenvironment interaction, we have developed an imaging model for the visualization of tumor cell characteristics. By means of IVIS imaging, fluorescent labeled antibodies showed excellent tumor specific uptake when injected in the vasculature of fertilized chicken embryos. Imaging techniques can also provide information regarding tumor heterogeneity in patients. By using PET scans to visualize expression of the estrogen receptor, we have shown that uptake of this tracer is heterogeneous in both tumor and normal tissue uptake and is influenced by site of metastasis. Different patterns could be distinguished, which could improve insight in differences between patients with ER positive tumors