Cell cycle progression and transmitotic apoptosis resistance promote escape from extrinsic apoptosis.

Extrinsic apoptosis relies on TNF-family receptor activation by immune cells or receptor-activating drugs. Here, we monitored cell cycle progression at a resolution of minutes to relate apoptosis kinetics and cell-to-cell heterogeneities in death decisions to cell cycle phases. Interestingly, we found that cells in S phase delay TRAIL receptor-induced death in favour of mitosis, thereby passing on an apoptosis-primed state to their offspring. This translates into two distinct fates, apoptosis execution post mitosis or cell survival from inefficient apoptosis. Transmitotic resistance is linked to Mcl-1 upregulation and its increased accumulation at mitochondria from mid-S phase onwards, which allows cells to pass through mitosis with activated caspase-8, and with cells escaping apoptosis after mitosis sustaining sublethal DNA damage. Antagonizing Mcl-1 suppresses cell cycle-dependent delays in apoptosis, prevents apoptosis-resistant progression through mitosis and averts unwanted survival after apoptosis induction. Cell cycle progression therefore modulates signal transduction during extrinsic apoptosis, with Mcl-1 governing decision making between death, proliferation and survival. Cell cycle progression thus is a crucial process from which cell-to-cell heterogeneities in fates and treatment outcomes emerge in isogenic cell populations during extrinsic apoptosis. This article has an associated First Person interview with the first author of the paper.

New In Vitro Interaction-Parasite Reduction Ratio Assay for Early Derisk in Clinical Development of Antimalarial Combinations.

The development and spread of drug-resistant phenotypes substantially threaten malaria control efforts. Combination therapies have the potential to minimize the risk of resistance development but require intensive preclinical studies to determine optimal combination and dosing regimens. To support the selection of new combinations, we developed a novel in vitro-in silico combination approach to help identify the pharmacodynamic interactions of the two antimalarial drugs in a combination which can be plugged into a pharmacokinetic/pharmacodynamic model built with human monotherapy parasitological data to predict the parasitological endpoints of the combination. This makes it possible to optimally select drug combinations and doses for the clinical development of antimalarials. With this assay, we successfully predicted the endpoints of two phase 2 clinical trials in patients with the artefenomel-piperaquine and artefenomel-ferroquine drug combinations. In addition, the predictive performance of our novel in vitro model was equivalent to that of the humanized mouse model outcome. Last, our more informative in vitro combination assay provided additional insights into the pharmacodynamic drug interactions compared to the in vivo systems, e.g., a concentration-dependent change in the maximum killing effect (Emax) and the concentration producing 50% of the killing maximum effect (EC50) of piperaquine or artefenomel or a directional reduction of the EC50 of ferroquine by artefenomel and a directional reduction of Emax of ferroquine by artefenomel. Overall, this novel in vitro-in silico-based technology will significantly improve and streamline the economic development of new drug combinations for malaria and potentially also in other therapeutic areas.

Characterising the blood-stage antimalarial activity of pyronaridine in healthy volunteers experimentally infected with Plasmodium falciparum.

With the spread of artemisinin resistance throughout Southeast Asia and now in Africa, the antimalarial drug pyronaridine is likely to become an increasingly important component of new antimalarial drug regimens. However, the antimalarial activity of pyronaridine in humans has not been completely characterised. This volunteer infection study aimed to determine the pharmacokinetic/pharmacodynamic (PK/PD) relationship of pyronaridine in malaria naïve adults. Volunteers were inoculated with Plasmodium falciparum-infected erythrocytes on day 0 and administered different single oral doses of pyronaridine on day 8. Parasitaemia and concentrations of pyronaridine were measured and standard safety assessments performed. Curative artemether-lumefantrine therapy was administered if parasite regrowth occurred, or on day 47 ± 2. Outcomes were parasite clearance kinetics, PK and PK/PD parameters from modelling. Ten participants were inoculated and administered 360 mg (n = 4), 540 mg (n = 4) or 720 mg (n = 1) pyronaridine. One participant was withdrawn without receiving pyronaridine. The time to maximum pyronaridine concentration was 1-2 h, the elimination half-life was 8-9 d, and the parasite clearance half-life was approximately 5 h. Parasite regrowth occurred with 360 mg (4/4 participants) and 540 mg (2/4 participants). Key efficacy parameters including the minimum inhibitory concentration (5.5 ng/mL) and minimum parasiticidal concentration leading to 90% of maximum effect (MPC90: 8 ng/mL) were derived from the PK/PD model. Adverse events considered related to pyronaridine were predominantly mild to moderate gastrointestinal symptoms. There were no serious adverse events. Data obtained in this study will support the use of pyronaridine in new antimalarial combination therapies by informing partner drug selection and dosing considerations.

Reconstructing temporal and spatial dynamics from single-cell pseudotime using prior knowledge of real scale cell densities.

Modern cytometry methods allow collecting complex, multi-dimensional data sets from heterogeneous cell populations at single-cell resolution. While methods exist to describe the progression and order of cellular processes from snapshots of such populations, these descriptions are limited to arbitrary pseudotime scales. Here we describe MAPiT, an universal transformation method that recovers real-time dynamics of cellular processes from pseudotime scales by utilising knowledge of the distributions on the real scales. As use cases, we applied MAPiT to two prominent problems in the flow-cytometric analysis of heterogeneous cell populations: (1) recovering the kinetics of cell cycle progression in unsynchronised and thus unperturbed cell populations, and (2) recovering the spatial arrangement of cells within multi-cellular spheroids prior to spheroid dissociation for cytometric analysis. Since MAPiT provides a theoretic basis for the relation of pseudotime values to real temporal and spatial scales, it can be used broadly in the analysis of cellular processes with snapshot data from heterogeneous cell populations.

The circuit-breaking algorithm for monotone systems.

In earlier work, we have introduced the circuit-breaking algorithm (CBA) for the analysis of intracellular regulation networks. This algorithm uses the network topology to construct a one-dimensional circuit-characteristic whose zeros correspond to the fixed points of the system. In this study, we apply the CBA to monotone systems whose flow preserves a partial order with respect to some orthant cone. We consider relations between stability of fixed points and the derivative of the corresponding zeros of the circuit-characteristic. In particular, we derive sufficient conditions for instability in case of global asymptotic stability of the open-loop system. Furthermore, we fully characterize stability of the fixed points if in addition the system is monotone. Combined with the theory of monotone systems, our results are used to characterize the long-term behavior of two models for different intracellular regulation processes.