The formation of tight tumor clusters affects the efficacy of cell cycle inhibitors: A hybrid model study

Abstract

Cyclin-dependent kinases (CDKs) are vital in regulating cell cycle progression, and, thus, in highly proliferating tumor cells CDK inhibitors are gaining interest as potential anticancer agents. Clonogenic assay experiments are frequently used to determine drug efficacy against the survival and proliferation of cancer cells. While the anticancer mechanisms of drugs are usually described at the intracellular single-cell level, the experimental measurements are sampled from the entire cancer cell population. This approach may lead to discrepancies between the experimental observations and theoretical explanations of anticipated drug mechanisms. To determine how individual cell responses to drugs that inhibit CDKs affect the growth of cancer cell populations, we developed a spatially explicit hybrid agent-based model. In this model, each cell is equipped with internal cell cycle regulation mechanisms, but it is also able to interact physically with its neighbors. We model cell cycle progression, focusing on the G1 and G2/M cell cycle checkpoints, as well as on related essential components, such as CDK1, CDK2, cell size, and DNA damage. We present detailed studies of how the emergent properties (e.g., cluster formation) of an entire cell population depend on altered physical and physiological parameters. We analyze the effects of CDK1 and CKD2 inhibitors on population growth, time-dependent changes in cell cycle distributions, and the dynamic evolution of spatial cell patterns. We show that cell cycle inhibitors that cause cell arrest at different cell cycle phases are not necessarily synergistically super-additive. Finally, we demonstrate that the physical aspects of cell population growth, such as the formation of tight cell clusters versus dispersed colonies, alter the efficacy of cell cycle inhibitors, both in 2D and 3D simulations. This finding may have implications for interpreting the treatment efficacy results of in vitro experiments, in which treatment is applied before the cells can grow to produce clusters, especially because in vivo tumors, in contrast, form large masses before they are detected and treated.

Multiscale modelling of palisade formation in gliobastoma multiforme

“…However, these conditions are not sufficient to explain the invasion of the local environment by malignant cells. Local invasion can arise by variations in the sensibility of hypoxia switch within the cellular population (or by similar mechanisms [39] fruit of a highly heterogeneous population). Pseudopalisade formation follows palisade formation, that follows invasion.…”

Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues

“…Kim et al [41] used an off-lattice agent-based model to investigate combined therapies with cell-cycle checkpoint inhibitors. The authors considered cyclin-dependent kinases (CDKs), which are crucial in the regulation of cell-cycle progression and so represent attractive targets in anti-cancer therapy.…”

Diagnostic assessment of osteosarcoma chemoresistance based on Virtual Clinical Trials

“…These results suggested that acute increase in tumor hypoxia can improve clinical efficacy of HAPs in pancreatic adenocarcinomas and other tumors. Moreover, we developed a mathematical model incorporating G1/S and G2/M cell-cycle checkpoints (39) to test the effectiveness of cyclin-dependent kinase (CDK) inhibitors on tumor growth-arrest. This in-silico study suggested that when tight tumor cell clusters are exposed to the CDK inhibitors, their growth suppression could be an effect of contact inhibition rather than of the drug mechanism, which may be important in designing the administration schedules and order of inhibitors acting at the G1/S and G2/M cell-cycle checkpoints.…”