Targeting EphA3 inhibits cancer growth by disrupting the tumor stromal microenvironment.

Eph receptor tyrosine kinases are critical for cell-cell communication during normal and oncogenic tissue patterning and tumor growth. Somatic mutation profiles of several cancer genomes suggest EphA3 as a tumor suppressor, but its oncogenic expression pattern and role in tumorigenesis remain largely undefined. Here, we report unexpected EphA3 overexpression within the microenvironment of a range of human cancers and mouse tumor xenografts where its activation inhibits tumor growth. EphA3 is found on mouse bone marrow-derived cells with mesenchymal and myeloid phenotypes, and activation of EphA3(+)/CD90(+)/Sca1(+) mesenchymal/stromal cells with an EphA3 agonist leads to cell contraction, cell-cell segregation, and apoptosis. Treatment of mice with an agonistic α-EphA3 antibody inhibits tumor growth by severely disrupting the integrity and function of newly formed tumor stroma and microvasculature. Our data define EphA3 as a novel target for selective ablation of the tumor microenvironment and demonstrate the potential of EphA3 agonists for anticancer therapy.

A global sensitivity tool for cardiac cell modeling: Application to ionic current balance and hypertrophic signaling.

Cardiovascular diseases are the major cause of death in the developed countries. Identifying key cellular processes involved in generation of the electrical signal and in regulation of signal transduction pathways is essential for unraveling the underlying mechanisms of heart rhythm behavior. Computational cardiac models provide important insights into cardiovascular function and disease. Sensitivity analysis presents a key tool for exploring the large parameter space of such models, in order to determine the key factors determining and controlling the underlying physiological processes. We developed a new global sensitivity analysis tool which implements the Morris method, a global sensitivity screening algorithm, onto a Nimrod platform, which is a distributed resources software toolkit. The newly developed tool has been validated using the model of IP3-calcineurin signal transduction pathway model which has 30 parameters. The key driving factors of the IP3 transient behaviour have been calculated and confirmed to agree with previously published data. We next demonstrated the use of this method as an assessment tool for characterizing the structure of cardiac ionic models. In three latest human ventricular myocyte models, we examined the contribution of transmembrane currents to the shape of the electrical signal (i.e. on the action potential duration). The resulting profiles of the ionic current balance demonstrated the highly nonlinear nature of cardiac ionic models and identified key players in different models. Such profiling suggests new avenues for development of methodologies to predict drug action effects in cardiac cells.

High-throughput cardiac science on the Grid.

Cardiac electrophysiology is a mature discipline, with the first model of a cardiac cell action potential having been developed in 1962. Current models range from single ion channels, through very complex models of individual cardiac cells, to geometrically and anatomically detailed models of the electrical activity in whole ventricles. A critical issue for model developers is how to choose parameters that allow the model to faithfully reproduce observed physiological effects without over-fitting. In this paper, we discuss the use of a parametric modelling toolkit, called Nimrod, that makes it possible both to explore model behaviour as parameters are changed and also to tune parameters by optimizing model output. Importantly, Nimrod leverages computers on the Grid, accelerating experiments by using available high-performance platforms. We illustrate the use of Nimrod with two case studies, one at the cardiac tissue level and one at the cellular level.