Literature DB >> 17637676

Common effector processing mediates cell-specific responses to stimuli.

Kathryn Miller-Jensen1, Kevin A Janes, Joan S Brugge, Douglas A Lauffenburger.   

Abstract

The fundamental components of many signalling pathways are common to all cells. However, stimulating or perturbing the intracellular network often causes distinct phenotypes that are specific to a given cell type. This 'cell specificity' presents a challenge in understanding how intracellular networks regulate cell behaviour and an obstacle to developing drugs that treat signalling dysfunctions. Here we apply a systems-modelling approach to investigate how cell-specific signalling events are integrated through effector proteins to cause cell-specific outcomes. We focus on the synergy between tumour necrosis factor and an adenoviral vector as a therapeutically relevant stimulus that induces cell-specific responses. By constructing models that estimate how kinase-signalling events are processed into phenotypes through effector substrates, we find that accurate predictions of cell specificity are possible when different cell types share a common 'effector-processing' mechanism. Partial-least-squares regression models based on common effector processing accurately predict cell-specific apoptosis, chemokine release, gene induction, and drug sensitivity across divergent epithelial cell lines. We conclude that cell specificity originates from the differential activation of kinases and other upstream transducers, which together enable different cell types to use common effectors to generate diverse outcomes. The common processing of network signals by downstream effectors points towards an important cell biological principle, which can be applied to the understanding of cell-specific responses to targeted drug therapies.

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Year:  2007        PMID: 17637676     DOI: 10.1038/nature06001

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  93 in total

1.  Cross-talk between receptor tyrosine kinase and tumor necrosis factor-α signaling networks regulates apoptosis but not proliferation.

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2.  Dramatic reduction of dimensionality in large biochemical networks owing to strong pair correlations.

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3.  Systems pharmacology of arrhythmias.

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4.  Predicting cytotoxic T-cell age from multivariate analysis of static and dynamic biomarkers.

Authors:  Catherine A Rivet; Abby S Hill; Hang Lu; Melissa L Kemp
Journal:  Mol Cell Proteomics       Date:  2010-12-30       Impact factor: 5.911

5.  A multivariate model of ErbB network composition predicts ovarian cancer cell response to canertinib.

Authors:  Rexxi D Prasasya; Kang Z Vang; Pamela K Kreeger
Journal:  Biotechnol Bioeng       Date:  2011-08-23       Impact factor: 4.530

6.  An inducible autocrine cascade regulates rat hepatocyte proliferation and apoptosis responses to tumor necrosis factor-alpha.

Authors:  Benjamin D Cosgrove; Connie Cheng; Justin R Pritchard; Donna B Stolz; Douglas A Lauffenburger; Linda G Griffith
Journal:  Hepatology       Date:  2008-07       Impact factor: 17.425

Review 7.  Models of signalling networks - what cell biologists can gain from them and give to them.

Authors:  Kevin A Janes; Douglas A Lauffenburger
Journal:  J Cell Sci       Date:  2013-05-01       Impact factor: 5.285

8.  Sporadic activation of an oxidative stress-dependent NRF2-p53 signaling network in breast epithelial spheroids and premalignancies.

Authors:  Elizabeth J Pereira; Joseph S Burns; Christina Y Lee; Taylor Marohl; Delia Calderon; Lixin Wang; Kristen A Atkins; Chun-Chao Wang; Kevin A Janes
Journal:  Sci Signal       Date:  2020-04-14       Impact factor: 8.192

9.  Cytokine-induced signaling networks prioritize dynamic range over signal strength.

Authors:  Kevin A Janes; H Christian Reinhardt; Michael B Yaffe
Journal:  Cell       Date:  2008-10-17       Impact factor: 41.582

10.  A multipathway phosphoproteomic signaling network model of idiosyncratic drug- and inflammatory cytokine-induced toxicity in human hepatocytes.

Authors:  Benjamin D Cosgrove; Leonidas G Alexopoulos; Julio Saez-Rodriguez; Linda G Griffith; Douglas A Lauffenburger
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009
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