Cell-to-Cell Variation in p53 Dynamics Leads to Fractional Killing

Abstract

Summary Many chemotherapeutic drugs kill only a fraction of cancer cells, limiting their efficacy. We used live-cell imaging to investigate the role of p53 dynamics in fractional killing of colon-cancer cells in response to chemotherapy. We found that both surviving and dying cells reach similar levels of p53, indicating that cell death is not determined by a fixed p53 threshold. Instead, a cell’s probability of death depends on the time and levels of p53. Cells must reach a threshold level of p53 to execute apoptosis and this threshold increases with time. The increase in p53 apoptotic threshold is due to drug-dependent induction of anti-apoptotic genes, predominantly in the inhibitors of apoptosis (IAP) family. Our study underlines the importance of measuring the dynamics of key players in response to chemotherapy to determine mechanisms of resistance and optimize the timing of combination therapy.

Dynamic variability in apoptotic threshold as a strategy for combating fractional killing

“…In order to reveal the qualitative effects of these regulatory 51 strategies, we compare results in the case of fixed thresholds with those in the case of 52 dynamically fluctuating thresholds, finding that in contrast to the former, the latter not 53 only accelerates threshold crossing but also keeps timing precision. This counterintuitive 54 finding interprets recent experimental observations (e.g., many chemotherapeutic drugs 55 kill only a fraction of cancer cells [25]; cell-to-cell variation in p53 dynamics leads to 56 fractional killing [26]) and has broad implications for diverse cellular processes and in 57 drug resistance.…”

“…However, a gene may reach 24 a critical threshold of expression with substantial cell-to-cell variability even among 25 isogenic cells exposed to the same constant stimulus. This variability is a necessary 26 consequence of the inherently stochastic nature of gene expression [27][28][29][30][31][32]. Apart from 27 this internal stochastic origin of timing, dynamically fluctuating thresholds can also 28 result in variability in the time required to reach a critical threshold level [9,12,26].…”

“…Such 29 a kind of threshold has a strong biological background and is ubiquitous in biological 30 regulatory systems. For example, consider a representative activity function of Hill 31 type [33][34][35][36] 32 Activation = Z n Z n + K n (1) first-passage properties of stationary threshold crossing [34][35][36][37][38][39][40], while comparatively very 42 few studies have investigated how a dynamically fluctuating threshold impacts timing 43 precision and arrival time theoretically [41][42][43][44] or experimentally [9,12,26]. 44 In this article, we formulate the timing of intracellular events as a first passage 45 time (FPT) problem, where an event is triggered when a stochastic process (in fact 46 single-cell protein level) crosses a dynamically fluctuating threshold for the first time.…”

“…Exposure of an isogenic 504 bacterial population to a cidal antibiotic typically fails to eliminate a small fraction of 505 refractory cells. In order to interpret this phenomenon, Roux J, et al [26] cancer cells in response to chemotherapy. They found that both surviving and dying 522 cells reach similar levels of p53, indicating that cell death is not determined by a fixed 523 p53 threshold.…”

“…On the one hand, 2 some important cellular processes depend on precision in the timing of key intracellular 3 events, e.g., cell fate decision presumably requires a precise control of gene expression 4 timing [2][3][4][5][6][7][8][9][10][11][12][13][14][15], and the controls of cell cycle and circadian clocks require timing precision 5 that can be crucial for the correct physiology [16][17][18][19][20][21][22][23][24]. Most of these processes are based 6 on gene expression, e.g., an activated gene may be required to reach in a precise time threshold level of p53 to execute apoptosis and this threshold increases with time [26]. 13 Similarly, fractional killing of a cancer cell population by chemotherapy depends on 14 arrival time: the shorter the arrival time is, the more are the cells killed, indicating 15 the therapeutic efficacy is better.…”