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      Ras-Mediated Deregulation of the Circadian Clock in Cancer


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          Circadian rhythms are essential to the temporal regulation of molecular processes in living systems and as such to life itself. Deregulation of these rhythms leads to failures in biological processes and eventually to the manifestation of pathological phenotypes including cancer. To address the questions as to what are the elicitors of a disrupted clock in cancer, we applied a systems biology approach to correlate experimental, bioinformatics and modelling data from several cell line models for colorectal and skin cancer. We found strong and weak circadian oscillators within the same type of cancer and identified a set of genes, which allows the discrimination between the two oscillator-types. Among those genes are IFNGR2, PITX2, RFWD2, PPARγ, LOXL2, Rab6 and SPARC, all involved in cancer-related pathways. Using a bioinformatics approach, we extended the core-clock network and present its interconnection to the discriminative set of genes. Interestingly, such gene signatures link the clock to oncogenic pathways like the RAS/MAPK pathway. To investigate the potential impact of the RAS/MAPK pathway - a major driver of colorectal carcinogenesis - on the circadian clock, we used a computational model which predicted that perturbation of BMAL1-mediated transcription can generate the circadian phenotypes similar to those observed in metastatic cell lines. Using an inducible RAS expression system, we show that overexpression of RAS disrupts the circadian clock and leads to an increase of the circadian period while RAS inhibition causes a shortening of period length, as predicted by our mathematical simulations. Together, our data demonstrate that perturbations induced by a single oncogene are sufficient to deregulate the mammalian circadian clock.

          Author Summary

          Living systems possess an endogenous time-generating system – the circadian clock - accountable for a 24 hours oscillation in the expression of about 10% of all genes. In mammals, disruption of oscillations is associated to several diseases including cancer. In this manuscript, we address the following question: what are the elicitors of a disrupted clock in cancer? We applied a systems biology approach to correlate experimental, bioinformatics and modelling data and could thereby identify key genes which discriminate strong and weak oscillators among cancer cell lines. Most of the discriminative genes play important roles in cell cycle regulation, DNA repair, immune system and metabolism and are involved in oncogenic pathways such as the RAS/MAPK. To investigate the potential impact of the Ras oncogene in the circadian clock we generated experimental models harbouring conditionally active Ras oncogenes. We put forward a direct correlation between the perturbation of Ras oncogene and an effect in the expression of clock genes, found by means of mathematical simulations and validated experimentally. Our study shows that perturbations of a single oncogene are sufficient to deregulate the mammalian circadian clock and opens new ways in which the circadian clock can influence disease and possibly play a role in therapy.

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          Most cited references73

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          Coordinated transcription of key pathways in the mouse by the circadian clock.

          In mammals, circadian control of physiology and behavior is driven by a master pacemaker located in the suprachiasmatic nuclei (SCN) of the hypothalamus. We have used gene expression profiling to identify cycling transcripts in the SCN and in the liver. Our analysis revealed approximately 650 cycling transcripts and showed that the majority of these were specific to either the SCN or the liver. Genetic and genomic analysis suggests that a relatively small number of output genes are directly regulated by core oscillator components. Major processes regulated by the SCN and liver were found to be under circadian regulation. Importantly, rate-limiting steps in these various pathways were key sites of circadian control, highlighting the fundamental role that circadian clocks play in cellular and organismal physiology.
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            The genetics of mammalian circadian order and disorder: implications for physiology and disease.

            Circadian cycles affect a variety of physiological processes, and disruptions of normal circadian biology therefore have the potential to influence a range of disease-related pathways. The genetic basis of circadian rhythms is well studied in model organisms and, more recently, studies of the genetic basis of circadian disorders has confirmed the conservation of key players in circadian biology from invertebrates to humans. In addition, important advances have been made in understanding how these molecules influence physiological functions in tissues throughout the body. Together, these studies set the scene for applying our knowledge of circadian biology to the understanding and treatment of a range of human diseases, including cancer and metabolic and behavioural disorders.
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              Early aging and age-related pathologies in mice deficient in BMAL1, the core componentof the circadian clock.

              Mice deficient in the circadian transcription factor BMAL1 (brain and muscle ARNT-like protein) have impaired circadian behavior and demonstrate loss of rhythmicity in the expression of target genes. Here we report that Bmal1(-/-) mice have reduced lifespans and display various symptoms of premature aging including sarcopenia, cataracts, less subcutaneous fat, organ shrinkage, and others. The early aging phenotype correlates with increased levels of reactive oxygen species in some tissues of the Bmal1(-/- )animals. These findings, together with data on CLOCK/BMAL1-dependent control of stress responses, may provide a mechanistic explanation for the early onset of age-related pathologies in the absence of BMAL1.

                Author and article information

                Role: Editor
                PLoS Genet
                PLoS Genet
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                May 2014
                29 May 2014
                : 10
                : 5
                [1 ]Institute for Theoretical Biology, Charité - Universitätsmedizin and Humboldt-Universität zu Berlin, Berlin, Germany
                [2 ]Knowledge Management in Bioinformatics, Institute for Computer Science, Humboldt-Universität zu Berlin, Berlin, Germany
                [3 ]Laboratory of Molecular Tumor Pathology, Charité - Universitätsmedizin Berlin, Berlin, Germany
                [4 ]Laboratory of Chronobiology, Institute for Medical Immunology Charité - Universitätsmedizin Berlin, Berlin, Germany
                [5 ]German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
                INSERM, France
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: AK AR CS. Performed the experiments: BM EG PMP PR SMF SR. Analyzed the data: AK AR BM CS EG HH PMP PT RS SB UL. Contributed reagents/materials/analysis tools: AR BM CS PT RS SB. Wrote the paper: AR CS. Critically read and contributed for writing the manuscript: AK AR CS HH PMP PT RS SB UL.


                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Pages: 17
                This work was funded by the BMBF (ColoNET; grant to AK, CS, HH, PT, RS, UL, and OncoPATH grant to CS, PR, RS, UL), the Berliner Krebsgesellschaft (grant to EG), the Rahel-Hirsch fellowship of Charité Universitätsmedizin Berlin (grant to AR) and the Deutsche Forschungsgemeinschaft (SFB 618/A1 A3 A4). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Research Article
                Biology and Life Sciences
                Computational Biology
                Systems Biology
                Theoretical Biology
                Computer and Information Sciences
                Information Technology
                Text Mining
                Computer Modeling
                Computerized Simulations
                Medicine and Health Sciences
                Basic Cancer Research



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