Modeling and simulation of genotypic Tumor Mutational Burden and Phenotypic Immunogenicity biomarkers in cancer...

In the Tumor Micro-Environment, cancer progression and its relationship with the Immune System (IS) are described in terms of cancer immunoediting (CI) phases, each of which is characterized by different types and levels of interaction between the tumor cells and elements of the IS, such as CD8+T cells. Said interactions are governed by genotypical (Tumor Mutational Burden, TMB) and phenotypical aspects pertaining to the tumor, as well as by the strength of the IS. In this work, a computational model of CI is presented that incorporates the TMB and the biomarker Tumor Immunogenic Phenotype (TIP) as its control parameters, and which employs the Ising-model Hamiltonian to characterize the system with respect to the CI phases.

Our model is a probabilistic multi-agent system with agents for tumor cells and for the IS. The computer implementation includes the parametrization of the TMB and the TIP, which is useful for identifying whether a tumor is hot or cold based on tumor immunogenicity and inflammation. For modeling the interactions between tumor and immune cells, the relevant elements are integrated under a Michaelis-Menten equation that regulates the recruitment rate of CD8+T cells and other IS elements. This novel quantification of immune cell recruitment encompasses the growth of neoantigen production, which in turn triggers the growth of CD8+T cells.

Our model reliably captures the Elimination, Equilibrium, and Escape phases of tumor-immune cell interactions, modulating the observed behaviors through the introduced parametrization of TMB and TIP biomarkers. Notably, these results align well with the combination of genotypical and phenotypical biomarkers analyzed in recent literature. A remarkable instance is the appreciable inhibition of the tumor activity during the Escape phase, observed for phenotypically hot tumors with relatively high TMB, and pointing towards improved efficacy of the IS against such tumors. The Ising-Hamiltonian provides precise quantification of diverse tumor-immune interactions across different TMB and TIP value combinations.

The presented model, formed by relatively simple agents, generates emergent behaviors through which the phases of CI are identified. The flexible choice of control parameters is robust enough and provides a plausible explanation for the mechanisms through which tumors with high TMB and high immunogenicity (i.e., hot tumors) exhibit a higher probability of responding to immunotherapy treatment. Characterization via the Ising-model Hamiltonian supports this explanation by summarizing the system's dynamics, which, in turn, facilitates its analysis and methodical improvements. The complex interplay of TMB, TIP, and individual physiology is finely captured.