Integration of Quantitative Methods and Mathematical Approaches for the Modeling of Cancer Cell Proliferation Dynamics

Physiological processes rely on control of cell proliferation in time and space and dysregulation of cell growth underlies pathological conditions, including cancer. Mathematical modeling can provide new insights into the complex regulation of cell proliferation dynamics. In this review, we first examine quantitative experimental approaches for measuring cell proliferation dynamics in vitro and compare the various types of data that can be obtained in these settings. We then explore the toolbox of common mathematical modeling frameworks that can describe cell behavior, dynamics, and interactions of proliferation. We discuss how these wet-lab studies may be integrated with different mathematical modeling approaches to aid interpretation of the results and to enable prediction of cell behaviors, specifically in the context of cancer.