Abstracts 2009

Abstract : The main conclusion is that systems biology approaches can indeed advance cancer research, having already proved successful in a very wide variety of cancer-related areas, and are likely to prove superior to many current research strategies. Major points include:

• Systems biology and computational approaches can make important contributions to research and development in key clinical aspects of cancer and of cancer treatment, and should be developed for understanding and application to diagnosis, biomarkers, cancer progression, drug development and treatment strategies.
• Development of new measurement technologies is central to successful systems approaches, and should be strongly encouraged. The systems view of disease combined with these new technologies and novel computational tools will over the next 5–20 years lead to medicine that is predictive, personalized, preventive and participatory (P4 medicine).
• Major initiatives are in progress to gather extremely wide ranges of data for both somatic and germ-line genetic variations, as well as gene, transcript, protein and metabolite expression profiles that are cancer-relevant. Electronic databases and repositories play a central role to store and analyze these data. These resources need to be developed and sustained.
• Understanding cellular pathways is crucial in cancer research, and these pathways need to be considered in the context of the progression of cancer at various stages. At all stages of cancer progression, major areas require modelling via systems and developmental biology methods including immune system reactions, angiogenesis and tumour progression.
• A number of mathematical models of an analytical or computational nature have been developed that can give detailed insights into the dynamics of cancerrelevant systems. These models should be further integrated across multiple levels of biological organization in conjunction with analysis of laboratory and clinical data.
• Biomarkers represent major tools in determining the presence of cancer, its progression and the responses to treatments. There is a need for sets of high-quality annotated clinical samples, enabling comparisons across different diseases and the quantitative simulation of major pathways leading to biomarker development and analysis of drug effects.
• Education is recognized as a key component in the success of any systems biology programme, especially for applications to cancer research. It is recognized that a balance needs to be found between the need to be interdisciplinary and the necessity of having extensive specialist knowledge in particular areas.
• A proposal from this workshop is to explore one or more types of cancer over the full scale of their progression, for example glioblastoma or colon cancer. Such an exemplar project would require all the experimental and computational tools available for the generation and analysis of quantitative data over the entire hierarchy of biological information. These tools and approaches could be mobilized to understand, detect and treat cancerous processes and establish methods applicable across a wide range of cancers.

Abstract : We use an automaton model for the cell cycle to assess the toxicity of various circadian patterns of anticancer drug delivery so as to enhance the efficiency of cancer chronotherapy. Based on the sequential transitions between the successive phases G1, S (DNA replication), G2, and M (mitosis) of the cell cycle, the model allows us to simulate the distribution of cell cycle phases as well as entrainment by the circadian clock. We use the model to evaluate circadian patterns of administration of two anticancer drugs, 5-fluorouracil (5-FU) and oxaliplatin (l-OHP). We first consider the case of 5-FU, which exerts its cytotoxic effects on cells in S phase. We compare various circadian patterns of drug administration differing by the time of maximum drug delivery. The model explains why minimum cytotoxicity is obtained when the time of peak delivery is close to 4 a.m., which temporal pattern of drug administration is used clinically for 5-FU.We also determine how cytotoxicity is affected by the variability in duration of cell cycle phases and by cell cycle length in the presence or absence of entrainment by the circadian clock. The results indicate that the same temporal pattern of drug administration can have minimum cytotoxicity toward one cell population, e.g. of normal cells, and at the same time can display high cytotoxicity toward a second cell population, e.g. of tumour cells. Thus the model allows us to uncover factors that may contribute to improve simultaneously chronotolerance and chronoefficacy of anticancer drugs. We next consider the case of oxaliplatin, which, in contrast to 5-FU, kills cells in different phases of the cell cycle.We incorporate into the model the pharmacokinetics of plasma thiols and intracellular glutathione, which interfere with the action of the drug by forming with it inactive complexes. The model shows how circadian changes in l-OHP cytotoxicity may arise from circadian variations in the levels of plasma thiols and glutathione. Corroborating experimental and clinical results, the simulations of the model account for the observation that the temporal profiles minimizing l-OHP cytotoxicity are in antiphase with those minimizing cytotoxicity for 5-FU.

Abstract : In most cells, Ca2+ increases in response to external stimulation are organized in the form of oscillations and waves that sometimes propagate from one cell to another. Numerous experimental and theoretical studies reveal that this spatiotemporal organization contains a non-negligible level of stochasticity. In this study, we extend the previous work based on a statistical analysis of experimental Ca2+ traces in isolated, hormone-stimulated hepatocytes and on stochastic simulations of Ca2+ oscillations based on the GillespieŐs algorithm. Comparison of the coefficients of variation in the periods of experimental and simulated Ca2+ spikes provides information about the clustering and the specific subtypes of the Ca2+ channels. In hepatocytes coupled by gap junctions, the global perfusion with a hormone leads to successive Ca2+ responses, giving the appearance of an intercellular wave. Statistical analysis of experimental Ca2+ oscillations in coupled hepatocytes confirms that this coordinated Ca2+ spiking corresponds to a phase wave but suggests the existence of an additional coupling mechanism.

Abstract : We propose an integrated computational model for the network of cyclin-dependent kinases (Cdks) that controls the dynamics of the mammalian cell cycle. The model contains four Cdk modules regulated by reversible phosphorylation, Cdk inhibitors, and protein synthesis or degradation. Growth factors (GFs) trigger the transition from a quiescent, stable steady state to self-sustained oscillations in the Cdk network. These oscillations correspond to the repetitive, transient activation of cyclin D/Cdk4Đ6 in G1, cyclin E/Cdk2 at the G1/S transition, cyclin A/Cdk2 in S and at the S/G2 transition, and cyclin B/Cdk1 at the G2/M transition. The model accounts for the following major properties of the mammalian cell cycle: (i) repetitive cell cycling in the presence of suprathreshold amounts of GF; (ii) control of cell-cycle progression by the balance between antagonistic effects of the tumor suppressor retinoblastoma protein (pRB) and the transcription factor E2F; and (iii) existence of a restriction point in G1, beyond which completion of the cell cycle becomes independent of GF. The model also accounts for endoreplication. Incorporating the DNA replication checkpoint mediated by kinases ATR and Chk1 slows down the dynamics of the cell cycle without altering its oscillatory nature and leads to better separation of the S and M phases. The model for the mammalian cell cycle shows how the regulatory structure of the Cdk network results in its temporal self-organization, leading to the repetitive, sequential activation of the four Cdk modules that brings about the orderly progression along cell-cycle phases.

Abstract : Circadian rhythms, which occur spontaneously with a period of about 24 h in a variety of organisms, allow their adaptation to the periodic variations of the environment. These rhythms are generated by a genetic regulatory network involving a negative feedback loop on transcription. Mathematical models based on the negative autoregulation of gene expression by the protein product of a clock gene account for the occurrence of selfsustained circadian oscillations. These models differ by their degree of complexity and, hence, by the number of variables considered. Some of these models can be considered as minimal because they contain a reduced number of biochemical processes and variables capable of producing sustained oscillations. In three of these minimal models, the period of the oscillations significantly changes with the rate of degradation of the clock protein. However, depending on the model considered, the period increases, decreases or passes through a maximum as a function of the protein degradation rate. We clarify the bases for these markedly different results by bringing to light the roles of (i) protein phosphorylation, which is required for protein degradation, and (ii) the velocity and degree of saturation of mRNA and protein degradation. Changes in the parameter values of the more complex of the minimal models can produce the period profiles observed in the other two models. The analysis allows us to reconcile the contradictory predictions for the dependence of the period on the clock protein degradation rate in three minimal models used to describe circadian rhythms.

Abstract : The molecular mechanism of circadian clocks is complex: it involves many genes and several interlocked positive and negative feedback loops. However mathematical models predict that a simple delayed negative regulatory feedback involving a single gene would be sufficient to produce self-sustained 24 hours oscillations. The design principles of the genetic network responsible for oscillations are not yet elucidated. Synthetic biology provides a means to tackle this issue. A recent publication in Nature addressed this question by designing an artificial clock that relies on a minimal mechanism. Guided by a mathematical model, this system was implemented in cultured mammalian cells and produced in vivo self-sustained oscillations. Besides providing insights in the functioning of a genetic oscillator, this first realization of a synthetic clock in a mammalian cell opens promising perspectives for cell therapy.

Abstract : Circadian clocks are based on a molecular mechanism regulated at the transcriptional, translational and post-translational levels. Recent experimental data unravel a complex role of the phosphorylations in these clocks. In mammals, several kinases play differential roles in the regulation of circadian rhythmicity. A dysfunction in the phosphorylation of one clock protein could lead to sleep disorders such as the Familial Advanced Sleep Phase Disorder, FASPS. Moreover, several drugs are targeting kinases of the circadian clocks and can be used in cancer chronotherapy or to treat mood disorders. In Drosophila, recent experimental observations also revealed a complex role of the phosphorylations. Because of its high degree of homology with mammals, the Drosophila system is of particular interest. In the circadian clock of cyanobacteria, an atypical regulatory mechanism is based only on three clock proteins (KaiA, KaiB, KaiC) and ATP and is sufficient to produce robust temperature-compensated circadian oscillations of KaiC phosphorylation. This review will show how computational modeling has become a powerful and useful tool in investigating the regulatory mechanism of circadian clocks, but also how models can give rise to testable predictions or reveal unexpected results.