From tumor microenvironment to immuno-therapeutic outcomes for solid tumors: A systems theoretic approach

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From tumor microenvironment to immuno-therapeutic outcomes for solid tumors: A systems theoretic approach

Authors

Bhattacharya, P.; Vadigepalli, R.

Abstract

Increasing evidence suggests the tumor microenvironment (TME) governs solid tumor response to immune checkpoint inhibition (ICI). Decoding the relationship between the cell compositional diversity of the tumor microenvironment (TME) and the therapeutic outcomes has been a longstanding problem in solid tumor research. In this work, we develop a systems-theoretic formalism to decipher the key mechanisms of growth, proliferation, immune evasion, and drug resistance that run common across solid tumors in the context of Immune Checkpoint Inhibitors (ICI). We reconstructed a core TME network in common across most solid tumors, containing multiple tumor and non-tumor cell types in distinct functional states, and molecular agents mediating cellular signaling and cell-cell interactions. Our analysis shows that the core TME network is sufficient to yield a multiplicity of attractors corresponding to clinically observed TME subtypes namely, immune or fibro dominated, immune or fibro desert, and immune and fibro deficient. Importantly, the reachability around the pre-ICI attractors governs the response to ICI explaining the TME subtype-specific therapy outcomes. We analyzed the attractor transition network to identify subtype-specific combination therapies that can drive unresponsive TME to a responsive subtype. We derived mathematical conditions relating TME balances to determine the limits of the efficacy of combination therapies. Our results hold for a large class of smooth biochemical kinetics with monotone and bounded interactions and (semi-)concave proliferation rules. The analytical findings have been verified with extensive simulation of different TME sub-types. Overall, we propose a generalized systems formalism that accounts for the TME properties governing ICI response and can aid in designing intervention strategies for improved tumor prognosis.

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