Persistence to anti-cancer treatments in the stationary to proliferating transition

Abstract

The heterogeneous responses of clonal cancer cells to treatment is understood to be caused by several factors, including stochasticity, cell-cycle dynamics, and different micro-environments. In a tumor, cancer cells may encounter fluctuating conditions and transit from a stationary culture to a proliferating state, for example this may occur following treatment. Here, we undertake a quantitative evaluation of the response of single cancerous lymphoblasts (L1210 cells) to various treatments administered during this transition. Additionally, we developed an experimental system, a “Mammalian Mother Machine,” that tracks the fate of thousands of mammalian cells over several generations under transient exposure to chemotherapeutic drugs. Using our developed system, we were able to follow the same cell under repeated treatments and continuously track many generations. We found that the dynamics of the transition between stationary and proliferative states are highly variable and affect the response to drug treatment. Using cell-cycle markers, we were able to isolate a subpopulation of persister cells with distinctly higher than average survival probability. The higher survival rate encountered with cell-cycle phase specific drugs was associated with a significantly longer time-till-division, and was reduced by a non cell-cycle specific drug. Our results suggest that the variability of transition times from the stationary to the proliferating state may be an obstacle hampering the effectiveness of drugs and should be taken into account when designing treatment regimens.

Controlling Depth of Cellular Quiescence by an Rb-E2F Network Switch

“…Factors in these networks have been identified to modulate the corresponding response thresholds to cellular and environmental signals, thereby affecting the proportion of cells in different network states. Meanwhile, quiescence-like growth-arrest states in bacterial and mammalian cells are often correlated with persistence or resistance to drug treatment (Pearl Mizrahi et al, 2016; Rotem et al, 2010; Sharma et al, 2010). Identifying the effective modulators of activation/transition thresholds in the underlying regulatory networks may help reduce the stability of these drug-resistant states and enhance therapeutic efficacy.…”

Drug persistence – From antibiotics to cancer therapies

“…For example, a study found that E. coli treated intermittently with Ampicillin for different durations quickly evolved population lag times (the time it takes to transition from stationary to exponential growth phase) to match the duration of the antibiotic exposure, while the maximal growth rate did not change [50]. To our knowledge, there is only one example of such ‘tolerance by lag’ [5] in the cancer literature [51]. Nevertheless, since cancer therapies often involve drug administration at regular time intervals, it is at least conceivable that similar selective pressures might also affect cancer cell populations.…”

Converse Smith-Martin cell cycle kinetics by transformed B lymphocytes

“…First, the time for G1 with later cell cycle phases in individual lymphoma cells showed only weak, if any, correlation, in contrast to the relatively strong concordance in primary B lymphocytes [17]. Second, the time taken to traverse G1 was short, as observed with other lymphoblast lines [32], resulting in the bulk of the variation in cell cycle time being attributable to the S/G2/M phase.…”