Modeling putative therapeutic implications of exosome exchange between tumor and immune cells

Significance A better understanding of mechanisms of immune evasion by cancer cells and the role of the tumor microenvironment is crucial for developing new effective cancer therapeutic strategies. The challenge is posed by the enormous complexity of both the immune system and the tumor microenvironment, and the intricate cancer–immunity signaling network. Here, we develop a tractable theoretical framework to study the putative role of exosome communication in the cancer–immunity interplay. Exosomes are small (30–200 nm) vesicles that transfer proteins, mRNAs, and microRNAs to nearby and faraway cells. Guided by this model, we compare the effectiveness of administering radiation therapy alone or in combination with immunotherapy, illustrating how the model can shed light on the design and assessments of combination therapies. Development of effective strategies to mobilize the immune system as a therapeutic modality in cancer necessitates a better understanding of the contribution of the tumor microenvironment to the complex interplay between cancer cells and the immune response. Recently, effort has been directed at unraveling the functional role of exosomes and their cargo of messengers in this interplay. Exosomes are small vesicles (30–200 nm) that mediate local and long-range communication through the horizontal transfer of information, such as combinations of proteins, mRNAs and microRNAs. Here, we develop a tractable theoretical framework to study the putative role of exosome-mediated cell–cell communication in the cancer–immunity interplay. We reduce the complex interplay into a generic model whose three components are cancer cells, dendritic cells (consisting of precursor, immature, and mature types), and killer cells (consisting of cytotoxic T cells, helper T cells, effector B cells, and natural killer cells). The framework also incorporates the effects of exosome exchange on enhancement/reduction of cell maturation, proliferation, apoptosis, immune recognition, and activation/inhibition. We reveal tristability—possible existence of three cancer states: a low cancer load with intermediate immune level state, an intermediate cancer load with high immune level state, and a high cancer load with low immune-level state, and establish the corresponding effective landscape for the cancer–immunity network. We illustrate how the framework can contribute to the design and assessments of combination therapies.