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1.
Clin Pharmacol Ther ; 109(3): 605-618, 2021 03.
Article in English | MEDLINE | ID: mdl-32686076

ABSTRACT

Drug development in oncology commonly exploits the tools of molecular biology to gain therapeutic benefit through reprograming of cellular responses. In immuno-oncology (IO) the aim is to direct the patient's own immune system to fight cancer. After remarkable successes of antibodies targeting PD1/PD-L1 and CTLA4 receptors in targeted patient populations, the focus of further development has shifted toward combination therapies. However, the current drug-development approach of exploiting a vast number of possible combination targets and dosing regimens has proven to be challenging and is arguably inefficient. In particular, the unprecedented number of clinical trials testing different combinations may no longer be sustainable by the population of available patients. Further development in IO requires a step change in selection and validation of candidate therapies to decrease development attrition rate and limit the number of clinical trials. Quantitative systems pharmacology (QSP) proposes to tackle this challenge through mechanistic modeling and simulation. Compounds' pharmacokinetics, target binding, and mechanisms of action as well as existing knowledge on the underlying tumor and immune system biology are described by quantitative, dynamic models aiming to predict clinical results for novel combinations. Here, we review the current QSP approaches, the legacy of mathematical models available to quantitative clinical pharmacologists describing interaction between tumor and immune system, and the recent development of IO QSP platform models. We argue that QSP and virtual patients can be integrated as a new tool in existing IO drug development approaches to increase the efficiency and effectiveness of the search for novel combination therapies.


Subject(s)
Allergy and Immunology , Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Drug Development , Immune Checkpoint Inhibitors/therapeutic use , Medical Oncology , Molecular Dynamics Simulation , Neoplasms/drug therapy , Systems Biology , Antineoplastic Combined Chemotherapy Protocols/adverse effects , Antineoplastic Combined Chemotherapy Protocols/pharmacokinetics , Computer Simulation , Humans , Immune Checkpoint Inhibitors/adverse effects , Immune Checkpoint Inhibitors/pharmacokinetics , Models, Immunological , Molecular Targeted Therapy , Neoplasms/immunology , Neoplasms/metabolism , Tumor Microenvironment
2.
Phys Biol ; 15(5): 056003, 2018 05 18.
Article in English | MEDLINE | ID: mdl-29714708

ABSTRACT

Spatial relocalization of proteins is crucial for the correct functioning of living cells. An interesting example of spatial ordering is the light-induced clustering of plant photoreceptor proteins. Upon irradiation by white or red light, the red light-active phytochrome, phytochrome B, enters the nucleus and accumulates in large nuclear bodies (NBs). The underlying physical process of nuclear body formation remains unclear, but phytochrome B is thought to coagulate via a simple protein-protein binding process. We measure, for the first time, the distribution of the number of phytochrome B-containing NBs as well as their volume distribution. We show that the experimental data cannot be explained by a stochastic model of nuclear body formation via simple protein-protein binding processes using physically meaningful parameter values. Rather modelling suggests that the data is consistent with a two step process: a fast nucleation step leading to macroparticles followed by a subsequent slow step in which the macroparticles bind to form the nuclear body. An alternative explanation for the observed nuclear body distribution is that the phytochromes bind to a so far unknown molecular structure. We believe it is likely this result holds more generally for other nuclear body-forming plant photoreceptors and proteins.


Subject(s)
Arabidopsis Proteins/metabolism , Arabidopsis/metabolism , Cell Nucleus/metabolism , Phytochrome B/metabolism , Active Transport, Cell Nucleus/radiation effects , Arabidopsis/cytology , Arabidopsis/radiation effects , Arabidopsis Proteins/analysis , Cell Nucleus/radiation effects , Computer Simulation , Light , Models, Biological , Phytochrome B/analysis , Protein Binding/radiation effects , Stochastic Processes
4.
Nat Plants ; 1: 15090, 2015 Jul 06.
Article in English | MEDLINE | ID: mdl-27250256

ABSTRACT

Phytochromes are red/far-red-light detecting photoreceptors that regulate plant growth and development. They photo-interconvert between an inactive Pr (red-light absorbing) and a physiologically active Pfr (far-red-light absorbing) form, acting as light-controlled molecular switches. Although the two major plant phytochromes A (phyA) and B (phyB) share similar absorption properties, they exhibit dramatic differences in their action spectra. Since both phytochromes antagonistically regulate seedling development under vegetative shade, it is essential for plants to clearly distinguish between phyA and phyB action. This discrimination is not comprehensible solely by the molecular properties of the phytochromes, but is evidently due to the dynamics of the phytochrome system. Using an integrated experimental and mathematical modelling approach we show that phytochrome dimerization is an essential element for phyB function. Our findings reveal that light-independent Pfr to Pr relaxation (dark reversion) and association/dissociation to nuclear bodies (NBs) severely depend on the conformational state of the phyB dimer. We conclude that only Pfr-Pfr homodimers of phyB can be responsible for triggering physiological responses, leading to a suppression of phyB function in the far-red range of the light spectrum.

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