A deterministic model for the occurrence and dynamics of multiple mutations in hierarchically organized tissues

We model a general, hierarchically organized tissue by a multi compartment approach, allowing any number of mutations within a cell. We derive closed solutions for the deterministic clonal dynamics and the reproductive capacity of single clones. Our results hold for the average dynamics in a hierarchical tissue characterized by an arbitrary combination of proliferation parameters.Comment: 4 figures, to appear in Royal Society Interfac

General No-Scale Supergravity: An F{\cal F}-SU(5)SU(5) Tale

We study the grand unification model flipped $SU(5)$ with additional vector-like particle multiplets, or ${\cal F}$-$SU(5)$ for short, in the framework of General No-Scale Supergravity. In our analysis we allow the supersymmetry (SUSY) breaking soft terms to be generically non-zero, thereby extending the phenomenologically viable parameter space beyond the highly constrained one-parameter version of ${\cal F}$-$SU(5)$. In this initial inquiry, the mSUGRA/CMSSM SUSY breaking terms are implemented. We find this easing away from the vanishing SUSY breaking terms enables a more broad mass range of vector-like particles, dubbed flippons, including flippons less than 1 TeV that could presently be observed at the LHC2, as well as a lighter gluino mass and SUSY spectrum overall. This presents heightened odds that the General No-Scale ${\cal F}$-$SU(5)$ viable parameter space can be probed at the LHC2. The phenomenology comprises both bino and higgsino dark matter, including a Higgs funnel region. Particle states emerging from the SUSY cascade decays are presented to experimentally distinguish amongst the diverse phenomenological regions.Comment: 8 pages, 4 figures, 4 tables; Version accepted for publication in Physics Letters

Cancer Biology: Infectious Tumour Cells

Cancer cells are generally viewed as a problem innate to their host, but evidence is mounting that they can evolve to become infectious agents and be transmitted between individuals. The current view of cancer development is that normal cells are transformed into tumour cells by sequential mutations that activate cancer-promoting 'oncogenes', or inhibit genes that would otherwise suppress tumours, or trigger genetic instabilities. As a consequence, every tumour is the result of a unique evolutionary process as the cancer cells adapt to out-compete their neighbours.MathematicsOrganismic and Evolutionary Biolog

Should tissue structure suppress or amplify selection to minimize cancer risk?

It has been frequently argued that tissues evolved to suppress the accumulation of growth enhancing cancer inducing mutations. A prominent example is the hierarchical structure of tissues with high cell turnover, where a small number of tissue specific stem cells produces a large number of specialized progeny during multiple differentiation steps. Another well known mechanism is the spatial organization of stem cell populations and it is thought that this organization suppresses fitness enhancing mutations. However, in small populations the suppression of advantageous mutations typically also implies an increased accumulation of deleterious mutations. Thus, it becomes an important question whether the suppression of potentially few advantageous mutations outweighs the combined effects of many deleterious mutations

How many samples are needed to infer truly clonal mutations from heterogenous tumours?

BACKGROUND: Modern cancer treatment strategies aim to target tumour specific genetic (or epigenetic) alterations. Treatment response improves if these alterations are clonal, i.e. present in all cancer cells within tumours. However, the identification of truly clonal alterations is impaired by the tremendous intra-tumour genetic heterogeneity and unavoidable sampling biases. METHODS: Here, we investigate the underlying causes of these spatial sampling biases and how the distribution and sizes of biopsies in sampling protocols can be optimised to minimize such biases. RESULTS: We find that in the ideal case, less than a handful of samples can be enough to infer truly clonal mutations. The frequency of the largest sub-clone at diagnosis is the main factor determining the accuracy of truncal mutation estimation in structured tumours. If the first sub-clone is dominating the tumour, higher spatial dispersion of samples and larger sample size can increase the accuracy of the estimation. In such an improved sampling scheme, fewer samples will enable the detection of truly clonal alterations with the same probability. CONCLUSIONS: Taking spatial tumour structure into account will decrease the probability to misclassify a sub-clonal mutation as clonal and promises better informed treatment decisions

Reply: Evolutionary game theory: lessons and limitations, a cancer perspective

SCOPUS: le.jinfo:eu-repo/semantics/publishe

Fixation times in evolutionary games under weak selection

In evolutionary game dynamics, reproductive success increases with the performance in an evolutionary game. If strategy $A$ performs better than strategy $B$, strategy $A$ will spread in the population. Under stochastic dynamics, a single mutant will sooner or later take over the entire population or go extinct. We analyze the mean exit times (or average fixation times) associated with this process. We show analytically that these times depend on the payoff matrix of the game in an amazingly simple way under weak selection, ie strong stochasticity: The payoff difference $\Delta \pi$ is a linear function of the number of $A$ individuals $i$, $\Delta \pi = u i + v$. The unconditional mean exit time depends only on the constant term $v$. Given that a single $A$ mutant takes over the population, the corresponding conditional mean exit time depends only on the density dependent term $u$. We demonstrate this finding for two commonly applied microscopic evolutionary processes.Comment: Forthcoming in New Journal of Physic

Enhanced inflammatory responses to toll-like receptor 2/4 stimulation in type 1 diabetic coronary artery endothelial cells: the effect of insulin

<p>Abstract</p> <p>Background</p> <p>Endothelial inflammatory responses mediated by Toll-like receptors (TLRs), particularly TLR2 and TLR4, play an important role in atherogenesis. While Type 1 diabetes (T1D) promotes the development and progression of atherosclerosis, the effect of T1D on TLR2/4-mediated inflammatory responses in coronary artery endothelial cells (CAECs) remains unclear.</p> <p>Methods</p> <p>We tested the hypothesis that diabetic CAECs have enhanced inflammatory responses to TLR2/4 stimulation. Non-diabetic and diabetic CAECs were treated with TLR2 agonist peptidoglycan and TLR4 agonist lipopolysaccharide. The expression of ICAM-1, IL-6 and IL-8 were analyzed by real-time PCR, immunoblotting and ELISA, and NF-κB activation by immunoblotting and immunostaining. In additional experiments, insulin was added before TLR stimulation to determine whether insulin deficiency alone is responsible for the alteration of TLR2/4-mediated inflammatory responses.</p> <p>Results</p> <p>Stimulation of TLR2 or TLR4 induced NF-κB activation, and the expression of ICAM-1, IL-6 and IL-8. Interestingly, the expression of inflammatory mediators was significantly enhanced in diabetic cells. The enhanced inflammatory responses correlated with augmented NF-κB activation in the absence of a change in TLR2 or TLR4 protein levels. Further, pretreatment of diabetic cells with insulin failed to suppress the enhanced inflammatory responses.</p> <p>Conclusions</p> <p>Diabetic CAECs have enhanced inflammatory responses to stimulation of TLR2 or TLR4, and insulin alone is insufficient to correct the hyper-inflammatory responses. The mechanism underlying the enhanced inflammatory responses appears to be augmentation of pro-inflammatory signaling, rather than up-regulation of levels of TLR2 and TLR4. These findings suggest that diabetic CAECs adopt a hyper-inflammatory phenotype and that this endothelial phenotypic change may predispose coronary artery to atherogenesis.</p

Cancer phenotype as the outcome of an evolutionary game between normal and malignant cells

There is variability in the cancer phenotype across individuals: two patients with the same tumour may experience different disease life histories, resulting from genetic variation within the tumour and from the interaction between tumour and host. Until now, phenotypic variability has precluded a clear-cut identification of the fundamental characteristics of a given tumour type.Journal ArticleResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Eml1 loss impairs apical progenitor spindle length and soma shape in the developing cerebral cortex

The ventricular zone (VZ) of the developing cerebral cortex is a pseudostratified epithelium that contains progenitors undergoing precisely regulated divisions at its most apical side, the ventricular lining (VL). Mitotic perturbations can contribute to pathological mechanisms leading to cortical malformations. The HeCo mutant mouse exhibits subcortical band heterotopia (SBH), likely to be initiated by progenitor delamination from the VZ early during corticogenesis. The causes for this are however, currently unknown. Eml1, a microtubule (MT)-associated protein of the EMAP family, is impaired in these mice. We first show that MT dynamics are perturbed in mutant progenitor cells in vitro. These may influence interphase and mitotic MT mechanisms and indeed, centrosome and primary cilia were altered and spindles were found to be abnormally long in HeCo progenitors. Consistently, MT and spindle length regulators were identified in EML1 pulldowns from embryonic brain extracts. Finally, we found that mitotic cell shape is also abnormal in the mutant VZ. These previously unidentified VZ characteristics suggest altered cell constraints which may contribute to cell delamination