title: Multi-pathway cellular analysis of compound selectivity.
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.
authors.affiliation: Discovery Assays and Services, Invitrogen, Part of Life Technologies, Madison, WI 53719, USA.
authors.forename: Michael K
authors.initials: MK
authors.lastname: Hancock
authors.forename: Connie S
authors.initials: CS
authors.lastname: Lebakken
authors.forename: Jun
authors.initials: J
authors.lastname: Wang
authors.forename: Kun
authors.initials: K
authors.lastname: Bi
mesh_terms: D002460:Cell Line; D006801:Humans; D011494:Protein Kinases / Q000378:metabolism*; D015398:Signal Transduction; D013379:Substrate Specificity; D001618:beta-Lactamases / Q000378:metabolism
chemical_list: D011494:Protein Kinases; D001618:beta-Lactamases