Fractional killing arises from cell‐to‐cell variability in overcoming a caspase activity threshold

Abstract

When cells are exposed to death ligands such as TRAIL, a fraction undergoes apoptosis and a fraction survives; if surviving cells are re-exposed to TRAIL, fractional killing is once again observed. Therapeutic antibodies directed against TRAIL receptors also cause fractional killing, even at saturating concentrations, limiting their effectiveness. Fractional killing arises from cell-to-cell fluctuations in protein levels (extrinsic noise), but how this results in a clean bifurcation between life and death remains unclear. In this paper, we identify a threshold in the rate and timing of initiator caspase activation that distinguishes cells that live from those that die; by mapping this threshold, we can predict fractional killing of cells exposed to natural and synthetic agonists alone or in combination with sensitizing drugs such as bortezomib. A phenomenological model of the threshold also quantifies the contributions of two resistance genes (c-FLIP and Bcl-2), providing new insight into the control of cell fate by opposing pro-death and pro-survival proteins and suggesting new criteria for evaluating the efficacy of therapeutic TRAIL receptor agonists.

L’hétérogénéité intraclonale des tumeurs et son impact sur la médecine de précision

“…Cependant, bien que réalisées à l'échelon de la cellule individuelle, ces études restent encore essentiellement corrélatives, joignant les signatures génomiques/protéomiques des cellules d'un échantillon à la valeur moyenne d'une mesure phénotypique (diagnostic histologique, taille de la tumeur, pourcentage de cellules apoptotiques, croissance cellulaire, etc.). Plus récemment, les techniques d'imagerie de cellules vivantes ont montré que des cellules issues d'une même population monoclonale, peuvent géné-rer une diversité phénotypique extraordinaire, indépendamment du cycle cellulaire : ainsi, des deux cellules soeurs issues d'une seule division, l'une répon-dra à une molécule thérapeutique et l'autre non (hétérogénéité intraclonale) (Figure 1) [5]. La cellule survivante pourra participer à la récidive tumorale.…”

“…La génomique et la protéomique, quant à elles, offrent des possibilités d'analyses simultanées (multiplex) très importantes qui peuvent être effectuées sur des cellules non modifiées, directement issues d'échantillons de patient. Mais ces techniques ne permettent pas le suivi de cellules individuelles dans le temps (signature dynamique), ce qui peut masquer l'effet de la thérapie et empêche l'évaluation de l'efficacité antitumorale du médicament pour chaque cellule (Figure 2 intraclonale) [5]. Cette différence fondamentale de réponse cellulaire n'est observable qu'en suivant le devenir de la cellule par imagerie de cellules vivantes.…”

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

“…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].…”

“…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.…”

“…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.…”