SP 3
A model of T-cell – epithelial cell interaction in lymphocytic lobulitis at the interface of hereditary breast cancer and adjacent tissue
In this subproject, we will develop a dynamic mathematical model of the interaction between immune cells and epithelial cells in normal lobular epithelium, and in lobular epithelium adjacent to, or infiltrated by cancer cells. The rationale for this scientific objective is the "lymphocytic lobulitis" (LLO), a recurrent, currently poorly understood pattern of inflammation frequently observed in hereditary breast cancer. The distinctive pattern of inflammation could inform us about underlying inflammatory processes associated with development and spread of cancer, and has a potential for discovery of novel biomarkers.
The observed interaction patterns between immune cell and epithelial cells at the invasive tumor edge will be compared with non-neoplastic epithelium in adjacent breast tissue, in larger distance to the tumor, and with normal epithelium. Joining spatial statistical analysis of multiple sections of lobules in different parts of the immunohistochemically stained tissue slides along with novel methodologies adapted from material sciences, we will draw conclusions about the interactions between immune cells and lobular epithelial cells. In combination with literature-curated rules, we will develop a mathematical model that will allow for the study of the functional role of LLO, for example its relation to tumor invasion. The model will be validated and iteratively improved by increasing numbers of observations on real cases. Advanced prototype versions of the mathematical model will then be used to study the effect of perturbations of the system, including simulations of the potential effect of novel therapies targeting the inflammatory tumor microenvironment (iTME). Finally, in close collaboration with subproject 4, we will attempt to conclude on the prognostic role of LLO to in hereditary breast cancer, and potentially propose additional criteria for biopsy evaluation that are currently not part of the routine diagnostic workflow.