Predicting the therapeutic efficacy of TLR stimulated macrophages for cancer treatment

Abstract Macrophages play a variety of roles in immunity including both pro- and anti-inflammatory functions, which can be controlled by toll-like receptor (TLR) stimulation. Previously, we generated computational model interconnected TLR signaling cascades validated the using experimental data from THP-1 monocyte cell line. This project aimed to adapt provide insights into activation bone marrow-derived macrophages (BMDM) enable accurate prediction BMDM therapeutic efficacy following Initially, quantitated expression genes encoding proteins cells found distinct differences between types. For instance, IRAK2 was expressed at level over 150 times cells, while other genes, such as TLR4, were relatively similar levels. Next, these used BMDM. In order determine whether predicted optimal way activate BMDM, treated with lipopolysaccharide flagellin IL-1b production quantified ELISA. The revealed that did not predict achieve pro-inflammatory cytokine We are currently altering improve its ability addition, studies underway exploring TLR-stimulated murine mammary carcinoma model. ultimate goal this is produce capable predicting how respond stimulation use anti-tumor