Abstract
The gut microbiome has emerged as a key regulator of response to cancer immunotherapy. However, there is a gap in our understanding of the underlying mechanisms by which the microbiome influences immunotherapy. To this end, we developed a mathematical model based on i) gut microbiome data derived from preclinical studies on melanomas after fecal microbiota transplant, ii) mechanistic modeling of antitumor immune response, and iii) robust association analysis of murine and human microbiome profiles with model-predicted immune profiles. Using our model, we could distill the complexity of these murine and human studies on microbiome modulation in terms of just two model parameters: the activation and killing rate constants of immune cells. We further investigated associations between specific bacterial taxonomies and antitumor immunity and immunotherapy efficacy. This model can guide the design of studies to refine and validate mechanistic links between the microbiome and immune system.