Multiscale Cancer Modeling

Abstract

Simulating cancer behavior across multiple biological scales in space and time, i.e., multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine hypotheses, focus experiments, and enable more accurate predictions. A growing number of examples illustrate the value of this approach in providing quantitative insight on the initiation, progression, and treatment of cancer. In this review, we introduce the most recent and important multiscale cancer modeling works that have successfully established a mechanistic link between different biological scales. Biophysical, biochemical, and biomechanical factors are considered in these models. We also discuss innovative, cutting-edge modeling methods that are moving predictive multiscale cancer modeling toward clinical application. Furthermore, because the development of multiscale cancer models requires a new level of collaboration among scientists from a variety of fields such as biology, medicine, physics, mathematics, engineering, and computer science, an innovative Web-based infrastructure is needed to support this growing community.

The Influence of Nutrients Diffusion on a Metabolism-driven Model of a Multi-cellular System

“…For this reason, effective computational multi-scale models are increasingly needed to account for processes and phenomena occurring at different time/ space scales and involving populations of interacting cells, with the final goal of identifying the conditions that may lead to complex behaviours, such as tissue patterning, cellular migration, homeostasis, and the emergence of pathological states [12,13]. In this respect, many attempts have been proposed to simulate the spatial/morphological dynamics of multi-cellular systems, by employing biophysically plausible models of cells and their interactions, e.g., within tissues and organs [14,15,16].…”