Literature DB >> 20593073

Multi-pathway cellular analysis of compound selectivity.

Michael K Hancock1, Connie S Lebakken, Jun Wang, Kun Bi.   

Abstract

Signaling pathways and their protein target constituents (e.g. kinases) have become important therapeutic targets in many disease areas. Traditional selectivity profiling for kinase inhibitors has relied upon screening panels of recombinant enzymes in biochemical assay formats. Recent studies have highlighted the importance of using cellular assays to better approximate true biological selectivity. We have developed a portfolio of CellSensor beta-lactamase transcriptional reporter gene assays that can be used to screen for perturbagens of various endogenous signaling pathways. Here we describe a multi-pathway profiling approach for generating compound-pathway selectivity maps. To demonstrate the utility of this approach, we have screened 32 known compounds across a diverse panel of 12 key signaling pathways and generated the first comprehensive cellular pathway selectivity profiles of several clinically approved kinase and other well-known bioactive inhibitors. Selectivity score comparisons identified several kinase inhibitors that were more promiscuous than predicted by traditional biochemical profiling methods. For example, we identified effects of sorafenib on the JAK/STAT pathway and demonstrated the potential therapeutic indication of sorafenib in treating leukemia/myeloproliferative disorder patients harboring TEL-JAK2 or JAK2V617F mutations. Our results indicate that multi-pathway profiling can efficiently characterize both on and off-pathway compound activities, revealing potential novel pathways and opportunities for drug repositioning purposes and/or safety liabilities in one profiling campaign.

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Year:  2010        PMID: 20593073     DOI: 10.1039/c003669b

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  4 in total

1.  A facile method for simultaneously measuring neuronal cell viability and neurite outgrowth.

Authors:  Michael K Hancock; Leisha Kopp; Navjot Kaur; Bonnie J Hanson
Journal:  Curr Chem Genom Transl Med       Date:  2015-02-27

2.  The use of novel selectivity metrics in kinase research.

Authors:  Nicolas Bosc; Christophe Meyer; Pascal Bonnet
Journal:  BMC Bioinformatics       Date:  2017-01-05       Impact factor: 3.169

3.  Defining a therapeutic window for kinase inhibitors in leukemia to avoid neutropenia.

Authors:  Christopher J Burns; Ben A Croker; Kate McArthur; Akshay A D'Cruz; David Segal; Kurt Lackovic; Andrew F Wilks; Joanne A O'Donnell; Cameron J Nowell; Motti Gerlic; David C S Huang
Journal:  Oncotarget       Date:  2017-07-28

4.  A data mining approach for identifying pathway-gene biomarkers for predicting clinical outcome: A case study of erlotinib and sorafenib.

Authors:  David G Covell
Journal:  PLoS One       Date:  2017-08-08       Impact factor: 3.240

  4 in total

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