Institute for Systems Biology

About: Institute for Systems Biology is a nonprofit organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Population & Proteomics. The organization has 1277 authors who have published 2777 publications receiving 353165 citations.

Lagrangian relaxation applied to sparse global network alignment

Abstract: Data on molecular interactions is increasing at a tremendous pace, while the development of solid methods for analyzing this network data is lagging behind. This holds in particular for the field of comparative network analysis, where one wants to identify commonalities between biological networks. Since biological functionality primarily operates at the network level, there is a clear need for topology-aware comparison methods. In this paper we present a method for global network alignment that is fast and robust, and can flexibly deal with various scoring schemes taking both node-to-node correspondences as well as network topologies into account. It is based on an integer linear programming formulation, generalizing the well-studied quadratic assignment problem. We obtain strong upper and lower bounds for the problem by improving a Lagrangian relaxation approach and introduce the software tool NATALIE 2.0, a publicly available implementation of our method. In an extensive computational study on protein interaction networks for six different species, we find that our new method outperforms alternative state-of-the-art methods with respect to quality and running time. An extended version of this paper including proofs and pseudo code is available at http://arxiv.org/pdf/1108.4358v1.

Novel Small-Molecule Inhibitors of Bcl-XL to Treat Lung Cancer

Abstract: Bcl-XL is a major antiapoptotic protein in the Bcl-2 family whose overexpression is more widely observed in human lung cancer cells than that of Bcl-2, suggesting that Bcl-XL is more biologically relevant and therefore a better therapeutic target for lung cancer. Here, we screened small molecules that selectively target the BH3 domain (aa 90-98) binding pocket of Bcl-XL using the UCSF DOCK 6.1 program suite and the NCI chemical library database. We identified two new Bcl-XL inhibitors (BXI-61 and BXI-72) that exhibit selective toxicity against lung cancer cells compared with normal human bronchial epithelial cells. Fluorescence polarization assay reveals that BXI-61 and BXI-72 preferentially bind to Bcl-XL protein but not Bcl2, Bcl-w, Bfl-1/A1, or Mcl-1 in vitro with high binding affinities. Treatment of cells with BXI-72 results in disruption of Bcl-XL/Bak or Bcl-XL/Bax interaction, oligomerization of Bak, and cytochrome c release from mitochondria. Importantly, BXI-61 and BXI-72 exhibit more potent efficacy against human lung cancer than ABT-737 but less degree in platelet reduction in vivo. BXI-72 overcomes acquired radioresistance of lung cancer. On the basis of our findings, the development of BXI(s) as a new class of anticancer agents is warranted and represents a novel strategy for improving lung cancer outcome.

Long-term adherence with non-invasive ventilation improves prognosis in obese COPD patients

Abstract: Background and objective Long-term non-invasive ventilation (NIV) has become a widespread modality of treatment in chronic obstructive pulmonary disease (COPD) patients with chronic respiratory failure. However, benefits in terms of patient-related outcomes are still under debate. Both NIV adherence and heterogeneous responses in different COPD phenotypes may contribute to the difficulty of demonstrating NIV benefits. Our aim was to assess the impact of NIV adherence on the rate of hospitalization for acute exacerbation and death. Methods This is a prospective multi-centre cohort study of COPD patients treated by long-term NIV. Comorbidities, anthropometrics, respiratory parameters were collected at inclusion in the study. Follow-up data included vital status, NIV adherence and hospitalizations. The influence of NIV adherence on prognosis was tested using an adjusted Cox model. Sensitivity analyses for obese and non-obese COPD subtypes were also conducted. Results Two hundred thirteen patients (48% obese) were included with 45.5% died during 47.7 [interquartile range = 27.8; 73] months' follow-up. Survival was better in obese COPD than non-obese COPD. The use of NIV > 9 h/day was associated with an increased risk of death or hospitalization for acute exacerbation [HR = 1.6; 95CI: 1.1–2.4]. In obese COPD, this risk described a U-shaped curve from >1 to >9 h/day NIV usage with an improvement in prognosis when NIV adherence was > 5 h/day [HR = 0.5; 95CI: 0.2–0.9]. Conclusions Adherence to NIV was associated with better prognosis only in obese COPD. NIV use > 9 h/day predicted poor outcomes.

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect.

Abstract: Most models of cancer cell population expansion assume exponential growth kinetics at low cell densities, with deviations to account for observed slowing of growth rate only at higher densities due to limited resources such as space and nutrients. However, recent preclinical and clinical observations of tumor initiation or recurrence indicate the presence of tumor growth kinetics in which growth rates scale positively with cell numbers. These observations are analogous to the cooperative behavior of species in an ecosystem described by the ecological principle of the Allee effect. In preclinical and clinical models, however, tumor growth data are limited by the lower limit of detection (i.e., a measurable lesion) and confounding variables, such as tumor microenvironment, and immune responses may cause and mask deviations from exponential growth models. In this work, we present alternative growth models to investigate the presence of an Allee effect in cancer cells seeded at low cell densities in a controlled in vitro setting. We propose a stochastic modeling framework to disentangle expected deviations due to small population size stochastic effects from cooperative growth and use the moment approach for stochastic parameter estimation to calibrate the observed growth trajectories. We validate the framework on simulated data and apply this approach to longitudinal cell proliferation data of BT-474 luminal B breast cancer cells. We find that cell population growth kinetics are best described by a model structure that considers the Allee effect, in that the birth rate of tumor cells increases with cell number in the regime of small population size. This indicates a potentially critical role of cooperative behavior among tumor cells at low cell densities with relevance to early stage growth patterns of emerging and relapsed tumors.