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      Systems Chronotherapeutics


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          Chronotherapeutics aim at treating illnesses according to the endogenous biologic rhythms, which moderate xenobiotic metabolism and cellular drug response. The molecular clocks present in individual cells involve approximately fifteen clock genes interconnected in regulatory feedback loops. They are coordinated by the suprachiasmatic nuclei, a hypothalamic pacemaker, which also adjusts the circadian rhythms to environmental cycles. As a result, many mechanisms of diseases and drug effects are controlled by the circadian timing system. Thus, the tolerability of nearly 500 medications varies by up to fivefold according to circadian scheduling, both in experimental models and/or patients. Moreover, treatment itself disrupted, maintained, or improved the circadian timing system as a function of drug timing. Improved patient outcomes on circadian-based treatments (chronotherapy) have been demonstrated in randomized clinical trials, especially for cancer and inflammatory diseases. However, recent technological advances have highlighted large interpatient differences in circadian functions resulting in significant variability in chronotherapy response. Such findings advocate for the advancement of personalized chronotherapeutics through interdisciplinary systems approaches. Thus, the combination of mathematical, statistical, technological, experimental, and clinical expertise is now shaping the development of dedicated devices and diagnostic and delivery algorithms enabling treatment individualization. In particular, multiscale systems chronopharmacology approaches currently combine mathematical modeling based on cellular and whole-body physiology to preclinical and clinical investigations toward the design of patient-tailored chronotherapies. We review recent systems research works aiming to the individualization of disease treatment, with emphasis on both cancer management and circadian timing system–resetting strategies for improving chronic disease control and patient outcomes.


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          Transcriptional architecture and chromatin landscape of the core circadian clock in mammals.

          The mammalian circadian clock involves a transcriptional feed back loop in which CLOCK and BMAL1 activate the Period and Cryptochrome genes, which then feedback and repress their own transcription. We have interrogated the transcriptional architecture of the circadian transcriptional regulatory loop on a genome scale in mouse liver and find a stereotyped, time-dependent pattern of transcription factor binding, RNA polymerase II (RNAPII) recruitment, RNA expression, and chromatin states. We find that the circadian transcriptional cycle of the clock consists of three distinct phases: a poised state, a coordinated de novo transcriptional activation state, and a repressed state. Only 22% of messenger RNA (mRNA) cycling genes are driven by de novo transcription, suggesting that both transcriptional and posttranscriptional mechanisms underlie the mammalian circadian clock. We also find that circadian modulation of RNAPII recruitment and chromatin remodeling occurs on a genome-wide scale far greater than that seen previously by gene expression profiling.
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            Transcriptional architecture of the mammalian circadian clock

            Next-generation sequencing approaches have yielded new insights into circadian function. Here, Takahashi reviews genome-wide analyses of the clock transcriptional feedback loop in mammals, which reveal a global circadian regulation of transcription factor occupancy, RNA polymerase II recruitment and initiation, nascent transcription and chromatin remodelling.
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              Loss of a circadian adrenal corticosterone rhythm following suprachiasmatic lesions in the rat.


                Author and article information

                Role: ASSOCIATE EDITOR
                Pharmacol Rev
                Pharmacol. Rev
                Pharmacol Rev
                Pharmacological Reviews
                The American Society for Pharmacology and Experimental Therapeutics (Bethesda, MD )
                April 2017
                April 2017
                April 2017
                : 69
                : 2
                : 161-199
                [1]Warwick Medical School (A.B., P.F.I., R.D., F.A.L.) and Warwick Mathematics Institute (A.B., D.A.R.), University of Warwick, Coventry, United Kingdom; Warwick Systems Biology and Infectious Disease Epidemiological Research Centre, Senate House, Coventry, United Kingdom (A.B., P.F.I., R.D., D.A.R., F.A.L.); INSERM–Warwick European Associated Laboratory “Personalising Cancer Chronotherapy through Systems Medicine” (C2SysMed), Unité mixte de Recherche Scientifique 935, Centre National de Recherche Scientifique Campus, Villejuif, France (A.B., P.F.I., R.D., D.A.R., F.A.L.); and Queen Elisabeth Hospital Birmingham, University Hospitals Birmingham National Health Service Foundation Trust, Cancer Unit, Edgbaston Birmingham, United Kingdom (P.F.I., F.A.L.)
                Author notes
                Address correspondence to: Dr. Annabelle Ballesta, University of Warwick–Senate House, Coventry CV4 7AL, United Kingdom. E-mail: a.c.ballesta@ 123456warwick.ac.uk
                Copyright © 2017 by The Author(s)

                This is an open access article distributed under the CC BY Attribution 4.0 International license.

                Page count
                Figures: 10, Tables: 1, Equations: 0, References: 412, Pages: 39
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