Inheritable cell-states shape drug-persister correlations and population dynamics in cancer cells
Drug tolerant persisters (DTPs) drive cancer therapy resistance by temporarily evading drug action, allowing multiple routes to eventual permanent resistance. Despite clear evidence for DTPs, the timing of their emergence, proliferative nature, and how their population dynamics arise from measured single-cell kinetics remain poorly understood. Here we use time-lapse microscopy data from two cancer cell lines, integrating single-cell and population measurements, to develop a quantitative description of drug persistence. Contrary to the expectation that increasing levels of genotoxic stress should lead to slower times to division and faster times to death, we observe minor changes in the single-cell intermitotic and death time distributions upon increasing cisplatin concentration. Yet, population decay rates increase 3-fold, suggesting a surprising independence of the overall dynamics from the measured birth and death rates. To explain this phenomenon, we argue that the observed lineage correlations and concentration-dependent decay rates imply cell-state dependent fate choices made both pre and post-cisplatin as opposed to just post-drug birth/death rate-based competitive fate choices. We demonstrate that these cell-states, present in the ancestors of DTP and sensitive cells, exhibit no difference in cycling speed and are inherited across 2-3 cellular generations. A stochastic model implementing these rules simultaneously recapitulates the observed decay rates and cell-fate correlations, also explaining how pre-drug fate decisions are consistent with barcoding experiments where barcode diversity remains unchanged after drug administration. Our results provide a powerful perspective on drug tolerance based on general arguments, without requiring knowledge of the underlying molecular architecture of the heterogeneous cell states.