Identification of molecular targets for immunotherapy of lymphoma using causal modeling
Malignant lymphomas persuade immune cells not to attack the tumor. In this project we focus on the reprogramming of tumor-associated macrophages (TAMs). We study the molecular composition of the lymphoma secretome and model its effect on the gene expression phenotype of a macrophage. Algorithms of causal inference allow us to identify proteins or metabolites in the secretome that causally affect the macrophage and reprogram it. From these analyzes, we identify molecular targets to therapeutically interfere with the communication between tumor and immune system.