Competitive Kinase Enrichment Proteomics Reveals that Abemaciclib Inhibits GSK3b and Activates WNT Signaling

Emily M. Cousins, Dennis Goldfarb, Feng Yan, Jose Roques, David Darr, Gary L. Johnson, Michael B. Major

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

The cellular and organismal phenotypic response to a small-molecule kinase inhibitor is defined collectively by the inhibitor's targets and their functions. The selectivity of small-molecule kinase inhibitors is commonly determined in vitro, using purified kinases and substrates. Recently, competitive chemical proteomics has emerged as a complementary, unbiased, cell-based methodology to define the target landscape of kinase inhibitors. Here, we evaluated and optimized a competitive multiplexed inhibitor bead mass spectrometry (MIB/MS) platform using cell lysates, live cells, and treated mice. Several clinically active kinase inhibitors were profiled, including trametinib, BMS-777607, dasatinib, abemaciclib, and palbociclib. MIB/MS competition analyses of the cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors abemaciclib and palbociclib revealed overlapping and unique kinase targets. Competitive MIB/MS analysis of abemaciclib revealed 83 target kinases, and dose–response MIB/MS profiling revealed glycogen synthase kinase 3 alpha and beta (GSK3a and b) and Ca2þ/calmodulin-dependent protein kinase II delta and gamma (CAMKIId and g) as the most potently inhibited. Cell-based and in vitro kinase assays show that in contrast to palbociclib, abemaciclib directly inhibits GSK3a/b and CAMKIIg/d kinase activity at low nanomolar concentrations. GSK3b phosphorylates b-catenin to suppress WNT signaling, while abemaciclib (but not palbociclib or ribociclib) potently activates b-catenin-dependent WNT signaling. These data illustrate the power of competitive chemical proteomics to define kinase target specificities for kinase inhibitors, thus informing clinical efficacy, dose-limiting toxicities, and drug-repurposing efforts. Implications: This study uses a rapid and quantitative proteomics approach to define inhibitor-target data for commonly administered therapeutics and provides a cell-based alternative to in vitro kinome profiling.

Original languageEnglish
Pages (from-to)333-344
Number of pages12
JournalMolecular Cancer Research
Volume16
Issue number2
DOIs
StatePublished - Feb 1 2018

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