Multiple Myeloma Cell Simulation Using an Agent-Based Framework Coupled with a Continuous Fluid Model

Abstract

Bone marrow mechanical conditions play a key role in multiple myeloma cancer. The complex mechanical and chemical conditions, as well as the interactions with other resident cells, hinder the development of effective treatments. Agent-based computational models, capable of defining the specific conditions for every single cell, can be a useful tool to identify the specific tumor microenvironment. In this sense, we have developed a novel hybrid 3D agent-based model with coupled fluid and particle dynamics to study multiple myeloma cells’ growth. The model, which considers cell–cell interactions, cell maturation, and cell proliferation, has been implemented by employing user-defined functions in the commercial software Fluent. To validate and calibrate the model, cell sedimentation velocity and cell proliferation rates have been compared with in vitro results, as well as with another previously in-house developed model. The results show that cell proliferation increased as cell–cell, and cell–extracellular matrix interactions increased, as a result of the reduction n maturation time. Cells in contact form cell aggregates, increasing cell–cell interactions and thus cell proliferation. Saturation in cell proliferation was observed when cell aggregates increased in size and the lack of space inhibited internal cells’ proliferation. Compared with the previous model, a huge reduction in computational costs was obtained, allowing for an increase in the number of simulated cells.

Utilizing 3D Models to Unravel the Dynamics of Myeloma Plasma Cells’ Escape from the Bone Marrow Microenvironment

“…While these studies all applied mathematical modelling to large experimental datasets, perhaps the greatest strength of computational modelling is the ability to generate a 3D virtual tumour microenvironment and demonstrate changes in cell behaviours and interactions in response to changing biochemical conditions. This was recently achieved using finite element modelling, enabling the study of cell motility, proliferation, differentiation, and apoptosis, along with interactions with native bone cells and cancer-associated cells [ 51 ]. Computational models of all types can be limited by the quality of input data and idealized representations of the in vitro environment [ 52 ].…”