Dataset Information

Achieving high signal-to-noise in cell regulatory systems: Spatial organization of multiprotein transmembrane assemblies of FGFR and MET receptors.

ABSTRACT: How is information communicated both within and between cells of living systems with high signal to noise? We discuss transmembrane signaling models involving two receptor tyrosine kinases: the fibroblast growth factor receptor (FGFR) and the MET receptor. We suggest that simple dimerization models might occur opportunistically giving rise to noise but cooperative clustering of the receptor tyrosine kinases observed in these systems is likely to be important for signal transduction. We propose that this may be a more general prerequisite for high signal to noise in transmembrane receptor signaling.

SUBMITTER: Blaszczyk M

PROVIDER: S-EPMC4832006 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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Achieving high signal-to-noise in cell regulatory systems: Spatial organization of multiprotein transmembrane assemblies of FGFR and MET receptors.

Blaszczyk Michal M Harmer Nicholas J NJ Chirgadze Dimitri Y DY Ascher David B DB Blundell Tom L TL

Progress in biophysics and molecular biology 20150505 3

How is information communicated both within and between cells of living systems with high signal to noise? We discuss transmembrane signaling models involving two receptor tyrosine kinases: the fibroblast growth factor receptor (FGFR) and the MET receptor. We suggest that simple dimerization models might occur opportunistically giving rise to noise but cooperative clustering of the receptor tyrosine kinases observed in these systems is likely to be important for signal transduction. We propose t ...[more]

PMID: 25957048

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Project description:Deregulation of fibroblast growth factor receptors (FGFRs) signaling, as a result of FGFR amplification, chromosomal translocation, or mutations, is involved in both initiation and progression of a wide range of human cancers. Clinical data demonstrating the dependence of cancer cells on FGFRs signaling clearly indicate these receptors as the molecular targets of anti-cancer therapies. Despite the increasing number of tyrosine kinase inhibitors (TKIs) being investigated in clinical trials, acquired resistance to these drugs poses a serious therapeutic problem. In this study, we focused on a novel pan-FGFR inhibitor-CPL304110, currently being investigated in phase I clinical trials in adults with advanced solid malignancies. We analyzed the sensitivity of 17 cell lines derived from cancers with aberrant FGFR signaling, i.e. non-small cell lung cancer, gastric and bladder cancer to CPL304110. In order to explore the mechanism of acquired resistance to this FGFR inhibitor, we developed from sensitive cell lines their variants resistant to CPL304110. Herein, for the first time we revealed that the process of acquired resistance to the novel FGFR inhibitor was associated with increased expression of MET in lung, gastric, and bladder cancer cells. Overexpression of MET in NCI-H1703, SNU-16, RT-112 cells as well as treatment with HGF resulted in the impaired response to inhibition of FGFR activity. Moreover, we demonstrated that cells with acquired resistance to FGFR inhibitor as well as cells overexpressing MET displayed enhanced migratory abilities what was accompanied with increased levels of Pyk2 expression. Importantly, inhibition of both MET and Pyk2 activity restored sensitivity to FGFR inhibition in these cells. Our results demonstrate that the HGF/MET-Pyk2 signaling axis confers resistance to the novel FGFR inhibitor, and this mechanism is common for lung, gastric, and bladder cancer cells. Our study suggests that targeting of MET/Pyk2 could be an approach to overcome resistance to FGFR inhibition.

Project description:Metabarcoding is a powerful molecular tool for simultaneously surveying hundreds to thousands of species from a single sample, underpinning microbiome and environmental DNA (eDNA) methods. Deriving quantitative estimates of underlying biological communities from metabarcoding is critical for enhancing the utility of such approaches for health and conservation. Recent work has demonstrated that correcting for amplification biases in genetic metabarcoding data can yield quantitative estimates of template DNA concentrations. However, a major source of uncertainty in metabarcoding data stems from non-detections across technical PCR replicates where one replicate fails to detect a species observed in other replicates. Such non-detections are a special case of variability among technical replicates in metabarcoding data. While many sampling and amplification processes underlie observed variation in metabarcoding data, understanding the causes of non-detections is an important step in distinguishing signal from noise in metabarcoding studies. Here, we use both simulated and empirical data to 1) suggest how non-detections may arise in metabarcoding data, 2) outline steps to recognize uninformative data in practice, and 3) identify the conditions under which amplicon sequence data can reliably detect underlying biological signals. We show with both simulations and empirical data that, for a given species, the rate of non-detections among technical replicates is a function of both the template DNA concentration and species-specific amplification efficiency. Consequently, we conclude metabarcoding datasets are strongly affected by (1) deterministic amplification biases during PCR and (2) stochastic sampling of amplicons during sequencing-both of which we can model-but also by (3) stochastic sampling of rare molecules prior to PCR, which remains a frontier for quantitative metabarcoding. Our results highlight the importance of estimating species-specific amplification efficiencies and critically evaluating patterns of non-detection in metabarcoding datasets to better distinguish environmental signal from the noise inherent in molecular detections of rare targets.

Dataset Information

Achieving high signal-to-noise in cell regulatory systems: Spatial organization of multiprotein transmembrane assemblies of FGFR and MET receptors.

Publications

Achieving high signal-to-noise in cell regulatory systems: Spatial organization of multiprotein transmembrane assemblies of FGFR and MET receptors.

Similar Datasets

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