Unveiling the role of metabolic rates variation in driving tumor heterogeneity and controlling growth and invasion: insights from an integrated multiscale in-vitro in-silico framework

Abstract The three-dimensional (3D) structure of solid tumors inherently limits oxygen and nutrient diffusion to deeper cells, resulting in morphological and metabolic variations. Non-physiological levels of oxygen and nutrients within the tumors result in heterogeneous cell populations that exhibit distinct necrotic, hypoxic, and proliferative zones. Among these zonal cellular properties, metabolic rates strongly affect the overall growth and invasion of tumors. Here we report on a hybrid discrete-continuum (HDC) mathematical framework that uses data from a biomimetic three-dimensional (3D) in vitro cancer model to accurately predict cancer growth and treatment response. The mathematical model integrates the continuum field of variables with a discrete approach and incorporates the random walk method for individual cell migration. By tracking the moving boundary of tumoroids, the HDC model separates volumetric growth from invasion. Invasion direction asymmetries were incorporated into the model by involving a randomness component in cellular migration mechanisms when determining the invasion direction. The model also accounts for mechanical and cellular interactions in tumor microenvironment (TME) as key factors characterizing tumor progression. The in-vitro model is composed of tumor organoids (called tumoroids) co-cultured with healthy neurons all embedded within a hydrogel matrix. Results indicated that the HDC model quantitatively predicts volumetric growth and invasion length and tracks the finger-type invasion pattern observed in the in-vitro model. This model has the potential to investigate inhibitory drug effects with the addition of a reaction-diffusion equation and incorporation of targeted signaling pathways in the continuum and discrete modules, respectively.