In silico tumor control induced via alternating immunostimulating and immunosuppressive phases

Abstract

Keywords: tumor-immune system interactions, immuno-modulatory interventions, mathematical modeling Despite recent advances in the field of Oncoimmunology, the success potential of immunomodulatory therapies against cancer remains to be elucidated. One of the reasons is the lack of understanding on the complex interplay between tumor growth dynamics and the associated immune system responses. Toward this goal, we consider a mathematical model of vascularized tumor growth and the corresponding effector cell recruitment dynamics. Bifurcation analysis allows for the exploration of model's dynamic behavior and the determination of these parameter regimes that result in immune-mediated tumor control. In this work, we focus on a particular tumor evasion regime that involves tumor and effector cell concentration oscillations of slowly increasing and decreasing amplitude, respectively. Considering a temporal multiscale analysis, we derive an analytically tractable mapping of model solutions onto a weakly negatively damped harmonic oscillator. Based on our analysis, we propose a theory-driven intervention strategy involving immunostimulating and immunosuppressive phases to induce long-term tumor control.

The biology and mathematical modelling of glioma invasion: a review

“…These results are promising, but further studies need to be done to demonstrate effectiveness in humans. Mathematical modelling has been demonstrated useful to predict patientspecific responses to treatment (such as anti-angiogenic therapy, chemotherapy, radiotherapy and immunotherapy) and suggest novel therapeutic avenues against cancer [176,[193][194][195][196][197][198][199][200][201][202][203][204][205][206][207][208][209]. In the future, appropriate mathematical models should be considered to optimize treatment plans and help to identify causes underlying glioma treatment resistance.…”

Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights

“…In particular, we focus on the interplay between the migration/proliferation dichotomy of glioma cells and modulations of functional tumour vasculature. Mathematical modelling has the potential to improve our understanding of the complex biology of tumours and their interactions with the microenvironment, as well as may help to design more effective and personalised therapeutic strategies [35][36][37][38][39][40][41][42][43]. Several mathematical models have been developed to identify mechanisms that facilitate proliferation and migration of glioma cells [16,38,[44][45][46][47][48][49][50][51][52][53], see also [54,55] for reviews.…”

Therapeutic Potential of Bacteria against Solid Tumors

“…Then, we use a mathematical model that combines vascularized tumor growth and effector cell recruitment dynamics to gain insights into the possible reasons of success or failure of bacterial therapies. Mathematical models have been rather successful in investigating the biology of cancer (23)(24)(25)(26) and are becoming an increasingly important resource to address immunologic questions (27)(28)(29), as well as useful for optimizing and predicting antitumor therapy outcomes (9,27,(30)(31)(32)(33)(34)(35)(36). Model analysis not only provides a qualitative and quantitative explanation of experimental results, but also allows for novel therapeutic strategies.…”

“…Indeed, model analysis demonstrates the existence of a critical tumor radius R S , above which tumors evade immune surveillance (9,34). Considering the mean values of the estimated parameters ( Supplementary Table S2), we can calculate a critical tumor radius, R S ¼ 4.1 mm that corresponds to a critical volume V S ¼ 288.82 mm 3 , which correctly predicts tumor escape in experiments 2 and 6 as R 0 > R S at the time of injection (Fig.…”