Analysis of Compound Synergy in High-Throughput Cellular Screens by Population-Based Lifetime Modeling

Despite the successful introduction of potent anti-cancer therapeutics, most of these drugs lead to only modest tumor-shrinkage or transient responses, followed by re-growth of tumors. Combining different compounds has resulted in enhanced tumor control and prolonged survival. However, methods querying the efficacy of such combinations have been hampered by limited scalability, analytical resolution, statistical feasibility, or a combination thereof. We have developed a theoretical framework modeling cellular viability as a stochastic lifetime process to determine synergistic compound combinations from high-throughput cellular screens. We apply our method to data derived from chemical perturbations of 65 cancer cell lines with two inhibitors. Our analysis revealed synergy for the combination of both compounds in subsets of cell lines. By contrast, in cell lines in which inhibition of one of both targets was sufficient to induce cell death, no synergy was detected, compatible with the topology of the oncogenically activated signaling network. In summary, we provide a tool for the measurement of synergy strength for combination perturbation experiments that might help define pathway topologies and direct clinical trials

Growing topography due to contrasting rock types in a tectonically dead landscape

Many mountain ranges survive in a phase of erosional decay for millions of years (Myr) following the cessation of tectonic activity. Landscape dynamics in these post-orogenic settings have long puzzled geologists due to the expectation that topographic relief should decline with time. Our understanding of how denudation rates, crustal dynamics, bedrock erodibility, climate, and mantle-driven processes interact to dictate the persistence of relief in the absence of ongoing tectonics is incomplete. Here we explore how lateral variations in rock type, ranging from resistant quartzites to less-resistant schists and phyllites and up to the least-resistant gneisses and granitic rocks, have affected rates and patterns of denudation and topographic forms in a humid semitropical, high-relief, post-orogenic landscape in Brazil where active tectonics ended hundreds of Myr ago. We show that denudation rates are negatively correlated to topographic relief, channel steepness and modern precipitation rates. Denudation instead correlates with inferred bedrock strength, with resistant rocks denuding more slowly relative to more erodible rock units, and suggest that the efficiency of fluvial erosion varies primarily due to these bedrock differences. Variations in erodibility continue to drive contrasts in rates of denudation in a tectonically inactive landscape evolving for hundreds of Myr, suggesting that equilibrium is not a natural attractor state and that relief continues to grow through time. Over the long timescales of post-orogenic development, exposure at the surface of rock types with differential erodibility can become a dominant control on landscape dynamics by producing spatial variations in geomorphic processes and rates, promoting the survival of relief, and determining spatial differences in erosional response timescales long after cessation of mountain building

IRODS metadata management for a cancer genome analysis workflow

Background: The massive amounts of data from next generation sequencing (NGS) methods pose various challenges with respect to data security, storage and metadata management. While there is a broad range of data analysis pipelines, these challenges remain largely unaddressed to date. Results: We describe the integration of the open-source metadata management system iRODS (Integrated Rule-Oriented Data System) with a cancer genome analysis pipeline in a high performance computing environment. The system allows for customized metadata attributes as well as fine-grained protection rules and is augmented by a user-friendly front-end for metadata input. This results in a robust, efficient end-to-end workflow under consideration of data security, central storage and unified metadata information. Conclusions: Integrating iRODS with an NGS data analysis pipeline is a suitable method for addressing the challenges of data security, storage and metadata management in NGS environments. Document type: Articl

Zebrafish as model system for the biological characterization of CK1 inhibitors

Introduction: The CK1 family is involved in a variety of physiological processes by regulating different signaling pathways, including the Wnt/β-catenin, the Hedgehog and the p53 signaling pathways. Mutations or dysregulation of kinases in general and of CK1 in particular are known to promote the development of cancer, neurodegenerative diseases and inflammation. There is increasing evidence that CK1 isoform specific small molecule inhibitors, including CK1δ- and CK1ε-specific inhibitors of Wnt production (IWP)-based small molecules with structural similarity to benzimidazole compounds, have promising therapeutic potential.Methods: In this study, we investigated the suitability of the zebrafish model system for the evaluation of such CK1 inhibitors. To this end, the kinetic parameters of human CK1 isoforms were compared with those of zebrafish orthologues. Furthermore, the effects of selective CK1δ inhibition during zebrafish embryonic development were analyzed in vivo.Results: The results revealed that zebrafish CK1δA and CK1δB were inhibited as effectively as human CK1δ by compounds G2-2 with IC50 values of 345 and 270 nM for CK1δA and CK1δB versus 503 nM for human CK1δ and G2-3 exhibiting IC50 values of 514 and 561 nM for zebrafish CK1δA and B, and 562 nM for human CK1δ. Furthermore, the effects of selective CK1δ inhibition on zebrafish embryonic development in vivo revealed phenotypic abnormalities indicative of downregulation of CK1δ. Treatment of zebrafish embryos with selected inhibitors resulted in marked phenotypic changes including blood stasis, heart failure, and tail malformations.Conclusion: The results suggest that the zebrafish is a suitable in vivo assay model system for initial studies of the biological relevance of CK1δ inhibition

Hybrid optimization method with general switching strategy for parameter estimation

This article is available from: http://www.biomedcentral.com/1752-0509/2/26[Background] Modeling and simulation of cellular signaling and metabolic pathways as networks of biochemical reactions yields sets of non-linear ordinary differential equations. These models usually depend on several parameters and initial conditions. If these parameters are unknown, results from simulation studies can be misleading. Such a scenario can be avoided by fitting the model to experimental data before analyzing the system. This involves parameter estimation which is usually performed by minimizing a cost function which quantifies the difference between model predictions and measurements. Mathematically, this is formulated as a non-linear optimization problem which often results to be multi-modal (non-convex), rendering local optimization methods detrimental.[Results] In this work we propose a new hybrid global method, based on the combination of an evolutionary search strategy with a local multiple-shooting approach, which offers a reliable and efficient alternative for the solution of large scale parameter estimation problems.[Conclusion] The presented new hybrid strategy offers two main advantages over previous approaches: First, it is equipped with a switching strategy which allows the systematic determination of the transition from the local to global search. This avoids computationally expensive tests in advance. Second, using multiple-shooting as the local search procedure reduces the multi-modality of the non-linear optimization problem significantly. Because multiple-shooting avoids possible spurious solutions in the vicinity of the global optimum it often outperforms the frequently used initial value approach (single-shooting). Thereby, the use of multiple-shooting yields an enhanced robustness of the hybrid approach.This work was supported by the European Community as part of the FP6 COSBICS Project (STREP FP6-512060), the German Federal Ministry of Education and Research, BMBF-project FRISYS (grant 0313921) and Xunta de Galicia (PGIDIT05PXIC40201PM).Peer reviewe