An automated fitting procedure and software for dose-response curves with multiphasic features.

In cancer pharmacology (and many other areas), most dose-response curves are satisfactorily described by a classical Hill equation (i.e. 4 parameters logistical). Nevertheless, there are instances where the marked presence of more than one point of inflection, or the presence of combined agonist and antagonist effects, prevents straight-forward modelling of the data via a standard Hill equation. Here we propose a modified model and automated fitting procedure to describe dose-response curves with multiphasic features. The resulting general model enables interpreting each phase of the dose-response as an independent dose-dependent process. We developed an algorithm which automatically generates and ranks dose-response models with varying degrees of multiphasic features. The algorithm was implemented in new freely available Dr Fit software (sourceforge.net/projects/drfit/). We show how our approach is successful in describing dose-response curves with multiphasic features. Additionally, we analysed a large cancer cell viability screen involving 11650 dose-response curves. Based on our algorithm, we found that 28% of cases were better described by a multiphasic model than by the Hill model. We thus provide a robust approach to fit dose-response curves with various degrees of complexity, which, together with the provided software implementation, should enable a wide audience to easily process their own data.This work was funded by Cancer Research UK grant C14303/A17197.This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/srep1470

Dallas with balls: televized sport, soap opera and male and female pleasures

Two of the most popular of television genres, soap opera and sports coverage have been very much differentiated along gender lines in terms of their audiences. Soap opera has been regarded very much as a 'gynocentric' genre with a large female viewing audience while the audiences for television sport have been predominantly male. Gender differentiation between the genres has had implications for the popular image of each. Soap opera has been perceived as inferior; as mere fantasy and escapism for women while television sports has been perceived as a legitimate, even edifying experience for men. In this article the authors challenge the view that soap opera and television sport are radically different and argue that they are, in fact, very similar in a number of significant ways. They suggest that both genres invoke similar structures of feeling and sensibility in their respective audiences and that television sport is a 'male soap opera'. They consider the ways in which the viewing context of each genre is related to domestic life and leisure, the ways in which the textual structure and conventions of each genre invoke emotional identification, and finally, the ways in which both genres re-affirm gender identities

Modelling of the cancer cell cycle as a tool for rational drug development: A systems pharmacology approach to cyclotherapy

The dynamic of cancer is intimately linked to a dysregulation of the cell cycle and signalling pathways. It has been argued that selectivity of treatments could exploit loss of checkpoint function in cancer cells, a concept termed "cyclotherapy". Quantitative approaches that describe these dysregulations can provide guidance in the design of novel or existing cancer therapies. We describe and illustrate this strategy via a mathematical model of the cell cycle that includes descriptions of the G1-S checkpoint and the spindle assembly checkpoint (SAC), the EGF signalling pathway and apoptosis. We incorporated sites of action of four drugs (palbociclib, gemcitabine, paclitaxel and actinomycin D) to illustrate potential applications of this approach. We show how drug effects on multiple cell populations can be simulated, facilitating simultaneous prediction of effects on normal and transformed cells. The consequences of aberrant signalling pathways or of altered expression of pro- or anti-apoptotic proteins can thus be compared. We suggest that this approach, particularly if used in conjunction with pharmacokinetic modelling, could be used to predict effects of specific oncogene expression patterns on drug response. The strategy could be used to search for synthetic lethality and optimise combination protocol designs

CYCLOPS simulations of actinomycin D and paclitaxel combinations.

<p><b>(a)</b> Actinomycin D dose-response are shown for malignant (left) and normal (right) cells. <b>(b)</b> Combination dose-response for actinomycin D+paclitaxel for simultaneous administration (24 hours) and <b>(c)</b> when delaying actinomycin D by 12 hours (malignant left, normal right). Arrows highlight magnitude of antagonistic effect when adding paclitaxel to 30nM actinomycin D.</p

Simulations of palbociclib and gemcitabine effects.

<p><b>(a)</b> palbociclib effects on malignant (left) and normal (right) at several concentrations (“proportion cells” correspond to the increase in number of cells i.e. 10 = 10 times more cells). <b>(b)</b> Modulation of the cell cycle distribution (left malignant, right normal, arrows indicate changes with increasing concentrations). <b>(c)</b> gemcitabine effects on malignant (left) and normal (right) at several concentrations. <b>(d)</b> Simulated dose-response surface for the palbociclib+gemcitabine combination. The arrow shows the rise of antagonistic effect with normal cells when increasing palbociclib concentration. <b>(e)</b> gemcitabine delayed administration protocol. (f) Effects of varying the time delay on normal (blue line, shown as % control) and malignant cells (red line). The ratio of normal to malignant is shown in green.</p

Simulation in CYCLOPS of cell cycle and ligand modulation.

<p>EGF stimulation of malignant <b>(a)</b> and normal cells <b>(b)</b>. “Proportion cells” correspond to the increase in number of cells i.e. 10 = 10 times more cells.</p