Figure 1.

Description of the approach followed in this study to relate immune profiling with microbiome data and schematic of mathematical model components. Our approach involves the reproduction of tumor growth curves with the deterministic mathematical model to set up model parameters and validate model predictions. The tumor growth data as well as the microbiome profiling data are derived from clinical and preclinical studies on melanomas after fecal microbiota transplant and administration of immunotherapy. The validated deterministic model generates the immune profile data for each tumor and the predicted immune profile is associated with the experimentally derived microbiome profiling data. Schematic of mathematical model’s components. The arrows represent the interactions among model components. The intensity of each interaction is associated with the value of a model parameter. Some arrows represent the killing rate constant ($K_{rc}$) and activation rate constant ($A_{rc}$). The model includes the cytolytic effect of CD8+ T cells and Natural killer cells that induce the tumor cells to become antigen. M1 macrophages and immature dendritic cells interact with tumor cells and become antigen-presenting cells (APCs). APCs and Neutrophils interact with tumor cells and antigen inducing phagocytosis. APCs also activate naïve CD4+ and naïve CD8+ T cells to become effector CD4+ and CD8+ T cells, respectively. CD4+ T cells help the activation of Naïve B cells in becoming Plasma and Memory B cells. Plasma cells produce antibodies, which bind to tumor cells. Phagocytosis/apoptosis arrows represent the killing rate constant ($K_{rc}$). The wider the stroke the higher the value of the $K_{rc}$ parameter. Also, some interactions are affected negatively by the binding of PD-1 to anti-PD-L1. Anti-PD-L1and anti-PD-1 reduce the binding of PD1 to PDL1, increasing the intensity of the interaction. In addition, the model incorporates the effects of pro- and anti-inflammatory cytokines and the regulatory effects of M2 macrophages and regulatory T cells (Tregs). Created with BioRender.com