AUTHOR=Groves Sarah M. , Quaranta Vito TITLE=Quantifying cancer cell plasticity with gene regulatory networks and single-cell dynamics JOURNAL=Frontiers in Network Physiology VOLUME=3 YEAR=2023 URL=https://www.frontiersin.org/journals/network-physiology/articles/10.3389/fnetp.2023.1225736 DOI=10.3389/fnetp.2023.1225736 ISSN=2674-0109 ABSTRACT=

Phenotypic plasticity of cancer cells can lead to complex cell state dynamics during tumor progression and acquired resistance. Highly plastic stem-like states may be inherently drug-resistant. Moreover, cell state dynamics in response to therapy allow a tumor to evade treatment. In both scenarios, quantifying plasticity is essential for identifying high-plasticity states or elucidating transition paths between states. Currently, methods to quantify plasticity tend to focus on 1) quantification of quasi-potential based on the underlying gene regulatory network dynamics of the system; or 2) inference of cell potency based on trajectory inference or lineage tracing in single-cell dynamics. Here, we explore both of these approaches and associated computational tools. We then discuss implications of each approach to plasticity metrics, and relevance to cancer treatment strategies.