Competitive Kinase Enrichment Proteomics Reveals That Abemaciclib Inhibits GSK3 And

Author Manuscript Published OnlineFirst on November 13, 2017; DOI: 10.1158/1541-7786.MCR-17-0468 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Competitive Kinase Enrichment Proteomics Reveals that Abemaciclib Inhibits GSK3 and

Activates WNT Signaling

Emily M. Cousins1, Dennis Goldfarb1,2, Feng Yan1, Jose Roques1, David Darr1, Gary L.

Johnson1,3, and Michael B. Major1,2,3,4*

1Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel

Hill, North Carolina 27599, USA

2Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill,

North Carolina 27599, USA

3Department of Pharmacology, Lineberger Comprehensive Cancer Center, University of North

Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA

4Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill,

Chapel Hill, North Carolina 27599, USA

Running title: Abemaciclib Inhibits GSK3β and Activates WNT Signaling

Key Words: Kinase, chemoproteomics, GSK3β, WNT signaling

Additional Information

Financial support:

This work was supported by the following: V Foundation grant number T2014-009 to MBM and

GLJ, Gabrielle’s Angel Foundation (grant number 85) to MBM, NIH/NCI grant

(5R01CA187799) to MBM, and the NIH T32 Postdoctoral Training Grant in Pulmonology

(5T32HL007106-39) to EMC.

*To whom correspondence should be addressed:

Michael B. Major, Department of Cell Biology and Physiology, Lineberger Comprehensive

Cancer Center, University of North Carolina at Chapel Hill, 450 West Drive, Lineberger

Building, CB#7295, Chapel Hill, NC, 27599, USA. Telephone: (919)-259-2695. Fax: (919)-966-

9673. Email: [email protected]

Conflict of Interest: The authors declare no potential conflicts of interest.

Abstract word count: 250

Total word count: 6482 including figure legends (excluding references and abtract)

Total number of figures and tables in manuscript: 6

Total number of supplemental figures and tables: 4

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 2

of abemaciclib revealed 83 target kinases, and dose-response MIB/MS profiling revealed

glycogen synthase kinase 3 alpha and beta (GSK3α and β and Ca2+/calmodulin-dependent

protein kinase II delta and gamma (CAMKIIδ and γ) as the most potently inhibited. Cell-based and in vitro kinase assays show that in contrast to palbociclib, abemaciclib directly inhibits

GSK3α/β and CAMKIIγ/δ kinase activity at low nanomolar concentrations. GSK3β

phosphorylates β-catenin to suppress WNT signaling, while abemaciclib (but not palbociclib or

ribociclib) potently activates β-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.

Introduction

Kinases are responsible for transferring the ATP gamma phosphate onto substrates (1). Kinases

are key components of signal transduction pathways and play roles in a large number of cellular

processes including growth, differentiation, migration, and apoptosis (2). Due to their varied roles in disease-relevant cellular phenotypes and the frequency with which kinase dysregulation contributes to disease, kinase inhibitors have promised clinical benefit (3). Imatinib (Gleevec®) was the first such small-molecule kinase inhibitor to achieve Food and Drug Administration

(FDA) approval in 2001 for Philadelphia Chromosome (BCR-ABL1) positive chronic

myelogenous leukemia (CML) (4). Currently, 38 FDA-approved kinase inhibitors are on the market, collectively targeting 31 kinases, or 6.0% of the 518 human protein kinases (4-6). In addition to those already approved for patient use, there are 1407 open clinical trials investigating the use of kinase inhibitors in various patient populations either as single agents or in combination with other compounds or biologics (clinicaltrials.gov 9/25/2017).

Though kinases share low amino acid homology, a common three-dimensional structure characterizes the ATP binding pocket (7). As such, numerous broad-spectrum and highly potent kinase inhibitors exist. We and others have used these ‘dirty’ kinase inhibitors as affinity tools to enrich the kinome. Specifically, covalent attachment of broad-spectrum kinase inhibitors to a solid-state matrix enables the affinity capture of protein kinases, an approach referred to as kinobeads or multiplexed-inhibitor beads (MIBs) (8-13). Optimization and diversification of the inhibitor-conjugated bead composition allows detection and quantitation of greater than 50% of the kinome in a single mass spectrometry run (8,11).

Kinase inhibitors are rarely selective for a single kinase or even kinase family (14). This low specificity limits kinase inhibitor utility in part through unintended clinical consequences and toxicity. Multiple studies have been conducted to assess the selectivity of various kinase inhibitors against panels of kinases using in vitro or lysate-based assays (15-18). While the resulting data are valuable, they are not without caveats. Ideally, kinase inhibitors would be evaluated in live cells or cell lysates where their targets reside in a native state, replete with post- translational modifications, physiological ATP concentrations, subcellular location, and co- complexed binding partners.

Here, we utilized the MIB/MS platform to profile the kinome following very short-term kinase inhibitor treatment of cell lysates, live cells, and mice. Inhibitor-bound kinases are 4

competitively occluded from binding the MIBs and are thus easily identified in subsequent

Western blots or by mass spectrometry (MS). We show that MIB/MS competition provides rapid

and quantitative identification of kinases targeted by various kinase inhibitors that are either

FDA-approved or in advanced clinical trials. As such, our data provide inhibitor target

annotation for several commonly administered drugs, thus providing clues to the molecular basis

of side-effect profiles and potentially offering new clinical applications for already approved

therapies.

Materials and Methods

Cell culture, treatments, and lysate preparation:

H2228, HCC827, H1703, H358, DB, and H2228 BAR/Renilla (B/R) cells were grown in RPMI

1640 supplemented with 10% fetal bovine serum (FBS). HEK293T/17 B/R, RKO B/R, L-cells,

and HEK293T/17 BAR-GreenFire cells were grown in DMEM supplemented with 10% FBS.

All cells were grown at 37˚C with 5% CO2. All cells were originally obtained by ATCC, thawed

and grown for less than 3 months, and were not further authenticated. For MIB affinity

purification Western blots and MIB/MS experiments, cells were treated with the indicated dose

of compound or vehicle for 1 hr. Cells were washed twice with cold PBS, scraped in PBS, and

pelleted via centrifugation. Cells were lysed in MIB lysis buffer (0.5% Triton X-100, 10%

glycerol, 50 mM Hepes-NaOH [pH 8.0], 150 mM NaCl, 2 mM EDTA and 2 mM DTT)

supplemented with protease and phosphatase inhibitors (Thermo Scientific, PI78439 and

PI7846).

MIB kinase enrichment: 5

Cells were lysed and normalized for protein concentration. For MIB AP WBs, 500-750 μg of protein lysate was used per sample. Lysates were incubated with MIBs and nutated at 4˚C for 15 min (8). The MIB mix contained VI16832 (22% V/V), CTx-0294885 (22% V/V), Purvalanol B

(14% V/V), PP58 (14% V/V), UNC21474 (14% V/V), and Shokat (14% V/V) inhibitors conjugated to sepharose beads (8,9,19-22). Kinase-bound MIBs were washed once each with

MIB lysis buffer, MIB low salt buffer (0.5% Triton X-100, 50 mM Hepes-NaOH [pH 8.0], 150 mM NaCl, 1 mM EDTA, and 1 mM EGTA), and MIB high salt buffer (0.5% Triton X-100, 50 mM Hepes-NaOH [pH 8.0], 1 M NaCl, 1 mM EDTA, and 1 mM EGTA). Proteins were then eluted from MIBs in 4X protein loading buffer containing DTT in a 95˚C heat block for 10 min.

Standard WB techniques were then utilized for analysis.

For MIB/MS experiments, 5 mg of protein lysate was brought to 1 M NaCl and then added to gravity flow columns containing 100 μl of packed sepharose beads (8); the unbound fraction was then passed over gravity columns containing 175 μl of packed MIBs. MIB-bound proteins were washed once each with MIB high salt buffer, MIB low salt buffer, and MIB low salt buffer containing 0.1% SDS. MIB-bound proteins were eluted by boiling in MIB elution buffer (0.5% SDS, 1% β-mercaptoethanol, and 100 mM Tris-HCl [pH 6.8]). Samples were then reduced with DTT, alkylated with chloroacetamide, and concentrated prior to precipitation of proteins by methanol-chloroform extraction. Proteins were trypsinized overnight, desalted via a

C18 spin column, and finally extracted three times with ethyl acetate to remove detergents.

For TMT experiments, cells or cell lysate were treated with DMSO or abemaciclib for 1 hr, and MIB/MS samples were prepared as above. Tryptic peptides were buffer exchanged into

100 mM TEAB prior to the addition of TMT label reagents (Thermo Scientific, 90111). Peptide labeling was conducted according to the manufacturer’s instructions. Peptides from vehicle and 6

abemaciclib-treated cells were then mixed 1:1:1:1:1 prior to desalting via a C18 spin column and detergent removal by ethyl acetate extraction as described above. For the first biological replicate of treated H2228 cells, the following TMT reagent tags were used: DMSO (TMT10-126), 0.006

μM abemaciclib (TMT10-127N), 0.06 μM abemaciclib (TMT10-127C), 0.6 μM abemaciclib

(TMT10-128N), and 6 μM abemaciclib (TMT10-128C). For the second biological replicate of treated H2228 cells, the following TMT reagent tags were used: DMSO (TMT10-129N), 0.006

μM abemaciclib (TMT10-129C), 0.06 μM abemaciclib (TMT10-130N), 0.6 μM abemaciclib

(TMT10-130C), and 6 μM abemaciclib (TMT10-131). For the TMT 10-plex experiment conducted in H2228 abemaciclib-treated lysates, the following TMT labels were used: DMSO- treated lysate (TMT10-126 [replicate 1], TMT10-127C [replicate 2]), 0.006 μM abemaciclib- treated lysate (TMT10-127N [replicate 1], TMT10-128C [replicate 2]), 0.06 μM abemaciclib- treated lysate (TMT10-128N [replicate 1], TMT10-129C [replicate 2]), 0.6 μM abemaciclib- treated lysate (TMT10-129N [replicate 1], TMT10-130C [replicate 2]), and 6 μM abemaciclib- treated lysate (TMT10-130N [replicate 1], TMT10-131 [replicate 2]). TMT-labeled peptides were mixed 1:1:1:1:1:1:1:1:1:1 prior to LC/MS. For the TMT 5-plex experiments conducted in DB cells, the following TMT labels were used: DMSO-treated lysate (TMT10-126 [replicate 1],

TMT10-127N [replicate 2]), 0.006 μM abemaciclib-treated lysate (TMT10-127N [replicate 1],

TMT10-127C [replicate 2]), 0.06 μM abemaciclib-treated lysate (TMT10-127C [replicate 1],

TMT10-128N [replicate 2]), 0.6 μM abemaciclib-treated lysate (TMT10-128N [replicate 1],

TMT10-128C [replicate 2]), and 6 μM abemaciclib-treated lysate (TMT10-128C [replicate 1],

TMT10-129N [replicate 2]). For each replicate, TMT-labeled peptides were mixed 1:1:1:1:1 prior to LC/MS.

Antibodies, compounds, and recombinant protein:

The CDK4 (A304-225A) antibody was purchased from Bethyl Laboratories (Montgomery, TX).

AXL (4566), CAMKII (4436), CDK6 (13331), MEK1/2 (8727), MET (8198), MERTK (4319), and SRC (2109) were obtained from Cell Signaling Technology (Danvers, MA). β-catenin

(610153) and GSK3β (610201) antibodies were purchased from BD Biosciences (San Jose, CA).

GAPDH (G8795) and β-tubulin (T7816) antibodies were obtained from Sigma-Aldrich (St.

Louis, MO). Secondary antibodies were purchased from LI-COR Biosciences (Lincoln, NE):

IRDye® 800CW Goat anti-Mouse IgG (925-32210), IRDye® 680LT Goat anti-Mouse IgG (925-

68020), IRDye®800CW Goat anti-Rabbit IgG (925-32211), and IRDye® 680LT Goat anti-

Rabbit IgG (925-68021). The following chemicals were purchased from Cayman Chemicals

(Ann Arbor, MI): abemaciclib (17740), CHIR-99021 (13122), dasatinib (11498), and ribociclib

(17666). BMS-777607 (S1561) and palbociclib (S1579) were ordered from Selleck Chemicals

(Houston, TX). Recombinant Wnt3A (315-20) was purchased from PeproTech (Rocky Hill, NJ).

In vitro kinase activity assays:

Abemaciclib and palbociclib were sent to Reaction Biology Corporation (Malvern, PA) for in vitro kinase activity assays. Briefly, kinase substrates were diluted in base reaction buffer (20 mM Hepes [pH 7.5], 10 mM MgCl2, 1 mM EGTA, 0.02% Brij-35, 0.02 mg/ml BSA, 0.1 mM

Na3VO4, 2 mM DTT, and 1% DMSO). Individual kinases were then added to the substrate solution and gently mixed. Compounds diluted in 100% DMSO were added to the kinase reaction mixture by acoustic technology (Echo550 Liquid Handler by Labcyte; nanoliter range) and incubated for 20 min at room temperature prior to the addition of 33P-ATP (specific activity

10 μCu/μl). Reactions were incubated for 2 h at room temperature, and radioactivity was 8

detected by filter binding methods. Kinase activity data were expressed as the percent remaining kinase activity in test samples compared to vehicle (DMSO) reactions. IC50 values and curve fits were obtained using GraphPad Prism software.

Dual Glo® Luciferase and IncuCyte live cell imaging:

HEK293T/17 B/R (1.25x104 cells/well), RKO B/R (1.25x104 cells/well), and H2228 B/R

(7.5x103 cells/well) cells were plated in 96-well plates one day prior to treatment with test compounds. Cells were treated with DMSO, 1 μM CHIR-99021, L-cell or WNT3A conditioned media (CM, described by ATCC), abemaciclib, or palbociclib for 20 hr. Cells were then lysed in

1X Passive Lysis Buffer (Promega); 10 μl of lysate was transferred to white well 96-well plates with black bottoms prior to the addition of luciferase reagents according to the manufacturer’s instructions. Plates were read on an Enspire 2300 Plate Reader (PerkinElmer; Waltham, MA).

Data are plotted as the average Firefly/Renilla ratio from 4 technical replicates, and error bars represent standard deviation from one biological replicate. Data are representative of three independent biological replicates. For live cell imaging using the IncuCyte Zoom Live Cell

Imaging system (Essen Instruments; Ann Arbor, MI), 7.5x104 HEK293T/17 BAR-GreenFire cells were seeded with 1% (V/V) Nuclight Red BacMam 3.0 reagent (Essen Bioscience, catalog number 4621) per well in a 48-well plate one day prior to drug treatment. Cells were then treated with DMSO, 1 μM CHIR-99021, L-cell CM, WNT3A CM, abemaciclib, or palbociclib. Four independent wells were treated for all conditions, and the entire experiment was conducted in three independent biological replicates. Cells were monitored for GFP (BAR activity), RFP

(nuclear staining for cell number normalization) and phase (cell density) every hr for 24 hr using a 20X objective. Data were plotted as the average total integrated intensity for green 9

fluorescence across 4 images per well and 4 quadruplicate wells; error bars represent standard deviations from the mean. The count fluorescent objects parameter was used in the red channel to determine the number of cells per well. Phase data were plotted as the percentage of the image occupied by cells.

Mass spectrometry, bioinformatics, and data filtering:

Trypsinized peptides were separated via reverse-phase nano-HPLC using a nanoACQUITY

UPLC system (Waters Corporation; Milford, MA). Peptides were trapped in a 2 cm column

(Pepmap 100, 3 μm particle size, 100 Å pore size) and separated in a 25 cm EASYspray

analytical column (75 μm ID, 2.0 μm C18 particle size, 100 Å pore size) at 300 nl/min and 35˚C.

For non-TMT experiments, a 180 min gradient utilized 2-25% buffer B (0.1% formic acid in

acetonitrile), and an Orbitrap Elite mass spectrometer (Thermo Scientific; Waltham, MA)

performed the analysis. Settings for the ion source and data acquisition were described

previously (23).

TMT experiments were performed on an Orbitrap Fusion Lumos (Thermo Scientific) with a 180 min gradient from 2-30% buffer B. MS1 scans were performed in the Orbitrap at

120k resolution with an automated gain control (AGC) target of 4e5 and max injection time of

100 ms. MS2 scans were performed in the ion trap following collision induced dissociation

(CID) on the 10 most intense ions. MS2 settings were AGC = 1.8e4, max injection time = 120 ms, CID collision energy = 30%, and quadrupole isolation width = 0.7 m/z. Precursors were filtered for monoisotopic peaks and charge states 2-7. Dynamic exclusion was set to 30 s and a mass tolerance of 10 ppm. MS3 scans were collected on the 10 most intense MS2 fragment ions using synchronous-precursor-selection (SPS) and performed in the Orbitrap. MS3 settings were 10

AGC = 1.2e5, max injection time = 120 ms, resolution = 60k, and higher-energy collision dissociation collision energy = 55%. For MS3 scans, the isolation windows were set specifically for each precursor charge state. For precursor of z = 2: the MS1 isolation width = 1.3 m/z and

MS2 isolation width = 2 m/z. For z = 3: MS1 width = 1 m/z and MS2 width = 3 m/z. For z = 4:

MS1 isolation = 0.8 m/z and MS2 width = 3 m/z. For z = 5-7: MS1 width = 0.7 m/z and MS2

width = 3 m/z.

Raw mass spectrometry data files were searched in MaxQuant (version 1.5.2.6) using the

following parameters: specific tryptic digestion with up to 2 missed cleavages, carbamidomethyl

fixed modification, variable protein N-terminal acetylation and methionine oxidation, match

between runs (alignment time window: 20 min; matching time window: 0.7 min), label free

quantification (LFQ), minimum ratio count of 2, and the UniProtKB/Swiss-Prot human

canonical sequence database (release 07/2013). The two TMT 5-plex biological replicates in

H2228 cells were searched separately, and the utilized labels were chosen for quantification (two

different sets of five labels from TMT10). The H2228 abemaciclib-treated lysate biological

duplicates were shot as a single TMT 10-plex sample, utilizing all 10 TMT labels in a single MS

run. Data from TMT10-129N (0.6 µM abemaciclib-treated H2228 lysate) were dropped from the analysis due to a >10-fold reduction in MS3 intensity for this label. The two 5-plex TMT

replicates in DB abemaciclib-treated lysates were searched together, and utilized labels were

used for quantification (different sets of five labels). Further bioinformatics steps are described in

the Statistics section. The MS proteomics data have been deposited to the ProteomeXchange

Consortium via the PRIDE partner repository with the dataset identifier PXD006139 (24).

Statistics 11

Searched files were imported into Perseus (version 1.5.1.6) for further filtering and data visualization. A 1% false discovery rate (FDR) was applied to all proteins; decoys, non-kinase proteins, and kinases with <3 unique reads were removed. LFQ intensities were log2- transformed, and missing values were imputed from a fitted normal distribution with a down- shift of 1.8 and distribution width of 0.4. For the volcano plots depicting MS data, p-values were calculated via standard two-tailed t-test, and the FDR was determined by the Benjamini-

Hochberg procedure. Additional statistical methods were also tested and compared (permutation

test within Perseus and the open-source software MS Stats); these methods yielded overly

optimistic results. Thus, we chose the more conservative Benjamini-Hochberg procedure in an

attempt to limit false-positives.

Study Approval

All animal handling and experiments were conducted under NIH guidelines and were approved

by the UNC Institutional Animal Care and Use Committee. Female FVB/NJ (The Jackson

Laboratory, 001800) mice were treated with DMSO (n=4) or 0.3 mg/kg trametinib (n=5) by oral

gavage. Mice were sacrificed 2 hr post-treatment; kidneys were harvested and snap frozen.

Tissue was homogenized and lysed as described above.

Results

Method validation: multiplexed inhibitor bead competition proteomics identifies targets of

trametinib.

Trametinib (GlaxoSmithKline) targets mitogen-activated protein kinase kinase 1 and 2

(MAP2K1 and MAP2K2, also known as MEK1 and 2) and was approved by the FDA in 2013 as a single-agent therapy for unresectable or metastatic melanoma harboring BRAFV600E or

BRAFV600K mutations (25). To evaluate and optimize the MIB competition experimental approach, we comparatively evaluated MIB-enriched kinases in trametinib-treated cell lysate, live cells, and in mice. Trametinib was chosen for these studies due to its high specificity for

MEK1 and 2 at doses in the low nanomolar range (26). First, H2228 non-small cell lung cancer

(NSCLC) cell lysate was incubated with trametinib for 1 hour prior to affinity purification (AP)

with MIBs. Trametinib inhibited MEK1 and MEK2 binding at the highest dose, while the MIB

binding of AXL kinase was not affected (Figure 1A). Second, treatment of live H2228 cells for 1

hour with increasing doses of trametinib blocked MEK1/2 binding to MIBs (Figure 1B). Third,

H2228 cell lysate was pre-incubated with MIBs for 15 minutes to allow kinase binding prior to

the addition of trametinib or DMSO for the indicated time. Trametinib was able to compete off

pre-bound MEK1/2, but not AXL, from the MIBs (Figure 1C).

To fully evaluate the kinome for responsiveness to trametinib, H2228 cells were treated

with 30 nM trametinib for an hour prior to MIB/MS analysis in biological triplicate (Figure 1D).

Cumulatively, 241 kinases were identified across all mass spectrometry runs with a minimum of

three unique peptides in at least two of three replicates. Following short-term trametinib

treatment, only MEK1 and MEK2 exhibited significantly decreased MIB binding. The p-values

in the volcano plots were calculated via a two-sided t-test, while the 5% false discovery rate

(FDR) was determined using the Benjamini-Hochberg procedure. A very conservative FDR

threshold was chosen for all mass spectrometry experiments to ensure that follow-up studies

were conducted on kinase “hits” that were most likely to be true positives. These results suggest 13

that trametinib is exquisitely selective for MEK1/2 and has little effect on the other 239 kinases identified across the samples. A similar experiment was conducted in trametinib-treated mice to determine if MIB/MS competition could identify drug targets in tissue from treated animals.

Mice were treated with DMSO or 0.3 mg/kg trametinib by oral gavage, and kidneys were

harvested two hours post-treatment. MIB/MS revealed significant reduction in MEK1 binding to

MIBs in trametinib-treated kidneys compared to DMSO-treated kidneys (Figure 1E). MEK2

protein levels were also reduced in mouse kidneys treated with trametinib as compared to

DMSO, though this reduction did not meet the stringent 5% FDR as determined by the

Benjamini-Hochberg procedure (Figure 1E).

The competitive MIB/MS platform was also validated on two additional kinase inhibitors in Supplementary Figure 1. Here, BMS-777607 was shown by MIB/AP WB and MIB/MS to target its known targets MERTK, MET, and AXL in H2228 treated cells (Supplementary Figure

1A and 1D). Dasatinib, a SRC family kinase inhibitor, was effective at inhibiting SRC binding to

MIBs in two NSCLC cell lines (Supplementary Figure 1B and 1C). By MIB/MS analyses,

dasatinib prevented MIB binding of several SRC family members (LYN, FYN, YES1, and SRC)

following short-term inhibitor treatment (Supplementary Figure 1E). Together, these results

illustrate the power of MIB/MS competition for rapid kinase target identification in cell lysates,

live cells, and in animals.

Kinase enrichment proteomics reveals novel targets of abemaciclib

Next, we used the MIB/MS competition platform to evaluate targets of two cyclin-

dependent kinase 4 and 6 inhibitors. Abemaciclib (LY2835219) is in late stage clinical trials for

glioblastoma, breast cancer, and NSCLC and recently received FDA approval for the treatment 14

of HR+/HER2- breast cancer both as a monotherapy and in combination with fulvestrant.

Palbociclib (PD-0332991) is FDA-approved for the treatment of ER+/HER2- and HR+/HER2-

breast cancers. Abemaciclib and palbociclib were tested for their ability to inhibit CDK4 and

CDK6 binding to MIBs. One hour treatment of H2228 cells with abemaciclib and palbociclib

prevented the binding of CDK4/6 to MIBs, while AXL binding was unaffected (Figure 2A and

2B).

MIB/MS competition was then performed for abemaciclib and palbociclib. Across three

biological replicate experiments, one hour abemaciclib treatment decreased the binding of 83

kinases to MIBs (>2-fold reduction at a 5% FDR) (Figure 2C). In addition to CDK4/6,

abemaciclib suppressed MIB capture of glycogen synthase kinase 3 (GSK3) α and β and several

members of the CDK, mitogen-activated protein kinase (MAPK), and Ca2+/calmodulin-

dependent protein kinase (CAMK) families (Figure 2C and Supplementary Table S1). Previous

studies have identified some of these kinases as abemaciclib targets, including GSK3β, though

no follow-up studies were reported for GSK3β (27,28). Supplemental Table S2 contains a list of

all potential abemaciclib kinase targets identified by the MIB/MS approach described here and in vitro kinase assays described previously (27,28).

Palbociclib treatment resulted in the loss of PIP4K2β binding to MIBs, using a 2-fold

cutoff and 5% FDR calculated from biological replicate experiments (Figure 2D). PIP4K2β has

been previously identified as a target of palbociclib in lung squamous carcinoma (29). CDK4 and

CDK6 exhibited a >8-fold reduction in MIB binding at an 11% FDR following palbociclib

treatment of H2228 cells (see methods for description of FDR calculation). These initial

MIB/MS competition studies suggest that abemaciclib and palbociclib have very distinct kinase

target profiles with the exception of CDK4 and CDK6. 15

Abemaciclib dose-dependently inhibits GSK3β MIB binding.

To further quantify abemaciclib-responsive kinases, dose-response MIB/MS competition experiments were conducted in H2228 cells using isobaric tandem mass tag (TMT) technology

(Figure 3) (30). TMT labeling of peptides allows for direct quantitation at the peptide level by measuring the ratio of TMT labels in a MS3 scan. H2228 cells were treated for an hour with increasing doses of abemaciclib prior to kinase enrichment and peptide labeling with TMTs

(Figure 3A). Quantitation of 128 kinases across two biological replicates revealed that abemaciclib inhibits GSK3β MIB binding at concentrations lower than that required to inhibit

CDK4/6 MIB binding (Figure 3A). Many previous kinase chemoproteomic studies have chosen to treat cell lysates as opposed to live cells. To address the possibility of differential inhibitor target profiles derived from treated cells versus treated lysates, a similar dose-response experiment was conducted in H2228 abemaciclib-treated cell lysates. Abemaciclib treatment of

H2228 lysates yielded similar results to H2228 treated cells, whereby TMT ratios were quantified on 133 kinases observed in both biological replicates. As before, GSK3α and β are preferentially precluded from MIB binding over CDK4/6 (Figure 3B). To further confirm that these findings are not specific to H2228 cells, a similar experiment was conducted in vehicle or abemaciclib-treated DB cell lysates (diffuse large B cell lymphoma cell line, Supplementary

Figure 2). Again, GKS3α and β MIB binding are inhibited at lower doses than that required to inhibit CDK4/6 MIB binding (148 quantified kinases across both replicates, Supplementary

Figure 2).

GSK3β is an abemaciclib-specific target. 16

GSK3β is an integral kinase within the β-catenin destruction complex. GSK3β phosphorylates β-catenin, leading to β-catenin ubiquitylation and proteasome-mediated degradation (31). Free β-catenin can then translocate to the nucleus, bind TCF/LEF, and initiate transcription of target genes. Importantly, mutations within the canonical WNT pathway have been linked to numerous types of cancer, autoimmune disease, and bone density disorders (32).

For example, loss-of-function mutations in adenomatous polyposis coli (APC) or gain-of-

function mutations within β-catenin are causative for colorectal cancer and hepatocellular

carcinoma (33-35). Due to the importance of WNT signaling in cancer, we sought to test the

relationship between abemaciclib, GSK3β activity, and WNT pathway activation.

MIB/AP Western blot experiments were performed to validate a subset of abemaciclib

targets. Abemaciclib blocked the binding of CDK6, CAMKIIβ/δ/γ, and GSK3β to MIBs (Figure

4A). In contrast, palbociclib treatment did not alter GSK3β MIB binding and only moderately

suppressed CAMKIIβ/δ/γ at the highest dose (Figure 4B). AXL binding to MIBs was retained in

the presence of both kinase inhibitors (Figures 4A and 4B). A third CDK4/6 inhibitor was

assessed for its ability to inhibit GSK3β binding to MIBs. Ribociclib (LEE011) was recently

granted FDA approval for the treatment of HR+/HER2- breast cancer when used in combination

with aromatase inhibitors. While short-term (one hour) treatment of H2228 cells with ribociclib

inhibited CDK4 and 6 binding to MIBs, GSK3β was completely unaffected at doses up to 10 μM

(Figure 4C). Furthermore, abemaciclib, but not palbociclib, precluded GSK3β and CAMKIIβ/δ/γ

MIB binding in a second NSCLC cell line (H1703 cells, Figure 4D).

Abemaciclib directly inhibits GSK3β

To test whether GSK3β kinase activity was directly inhibited by abemaciclib, in vitro kinase activity assays were performed on a panel of kinases (Figure 5). These experiments

confirmed that both abemaciclib and palbociclib comparably suppressed their cognate targets:

CDK4/cyclin D1 (IC50 values of 0.46 nM [abemaciclib, A] and 1.3 nM [palbociclib, P]),

CDK6/cyclin D1 (0.43 nM [A], 0.43 nM [P]), CDK4/cyclin D3 (6.2 nM [A], 7.0 nM [P]), and

CDK6/cyclin D3 (8.9 nM [A], 5.1 nM [P]) (Figure 5A-5D). Abemaciclib was >1000-fold more

potent for GSK3β than palbociclib (IC50 of 8.67 nM [A], 11.2 μM [P]; Figure 5E). Both

compounds were also tested for their ability to inhibit CAMKIIβ, CAMKIIδ, and CAMKIIγ.

Abemaciclib was >100 times more specific for the CAMKII proteins when compared to

palbociclib (CAMKIIβ: IC50 of 3.5 nM [A], 1.6 μM [P]; CAMKIIδ: 2.6 nM [A], 610 nM [P];

CAMKIIγ: 52 nM [A], 9.4 μM [P]) as show in Figure 5F-5H.

Abemaciclib activates WNT signaling via its inhibition of GSK3β.

Having established that abemaciclib directly inhibits GSK3β in the low nanomolar range,

we tested whether abemaciclib-mediated inhibition of GSK3β resulted in stabilization of β-

catenin protein and induction of β-catenin-dependent transcription. β-catenin transcriptional

activity was quantified in multiple cell lines using the β-catenin Activated Reporter (BAR)

Firefly luciferase reporter (36). As expected, abemaciclib, but not palbociclib, demonstrated a

dose-dependent activation of the BAR reporter in RKO colorectal adenocarcinoma cells,

HEK293T/17 embryonic kidney cells, and H2228 NSCLC cells across three biological replicates

(Figure 6A). WNT3A-conditioned media (CM) and the GSK3β inhibitor CHIR-99021 served as

positive controls (Figure 6A). To evaluate WNT pathway activation over time, HEK293T/17

cells carrying a β-catenin-driven GFP reporter (HEK293T/17 BAR-GreenFire) were treated with 18

vehicle, CHIR-99021, WNT3A CM, abemaciclib, or palbociclib and monitored by live cell

imaging over 24 hours. Abemaciclib, but not palbociclib, induced GFP expression in a dose-

dependent manner (Figure 6B and 6C). As expected, WNT3A CM and CHIR-99021 also

activated the reporter (Figure 6B and 6C).

Next, β-catenin protein levels were assessed by Western blot of RKO cells treated with

vehicle, abemaciclib, palbociclib, CHIR-99021, or recombinant WNT3A (rWnt3A) for 6 hours.

Abemaciclib dose-dependently stabilized β-catenin protein levels, while palbociclib treatment had no effect (Figure 6D). These observations were confirmed in a second cell line (Figure 6E).

Finally, to determine whether abemaciclib and CHIR-99021 induce β-catenin protein

stabilization with similar kinetics, a time course experiment was performed. RKO and L-cells

were treated with abemaciclib, CHIR-99021, or palbociclib for up to 6 hours. β-catenin protein

stabilization occurred within 30 minutes of CHIR-99021 or abemaciclib treatment and continued

throughout the time course (Figure 6F and 6G). Conversely, six hour vehicle or palbociclib

treatment did not affect β-catenin protein abundance (Figure 6F and 6G). These data indicate that abemaciclib-mediated inhibition of GSK3β activates WNT signaling via β-catenin protein

stabilization and transcriptional activity.

Discussion

The MIB/MS competition platform described here provides a powerful approach for identifying putative targets of kinase inhibitors in cell lysate, live cells, and in tissues. We

discovered known and novel targets for several kinase inhibitors. Our data and conclusions

support the widely-held view that understanding the kinase inhibitor target profile of clinically-

active drugs may help to inform toxicities associated with the inhibition of ‘other targets’ and 19

offers experimental support for drug repurposing strategies (37). We suggest that target profile annotation via MIB/MS or kinobead competition might be incorporated into drug development pipelines prior to clinical use to minimize unintended consequences and to maximize patient safety. Future work using competitive chemical proteomics for all FDA-approved kinase inhibitors and promising clinical candidates is warranted.

Previous studies have reported similar competitive kinase enrichment proteomic platforms (11,13,29). The majority of these experiments evaluated differential kinase capture in

treated protein lysates as opposed to the live cell treatments used here. Interpretation of live cell

competitive MIB data includes assumptions of physiological protein-protein interactions,

subcellular locations, and ATP/ADP concentrations. How these variables impact a lysate- versus

cell-based competitive chemical proteomics dataset remains to be fully examined. Data presented

here suggest that inhibitor-treated cells and lysates yield similar results by competitive MIB/MS,

though further experiments are necessary to comprehensively evaluate potential differences

using multiple kinase inhibitors in lysates and in live cells. Secondly, although not tested in this

study, competitive MIB experiments in treated mice should reveal tissue-restricted kinase drug

targets, owing to differential kinase expression and drug bioavailability. Third, comparative

analyses of MIB- or kinobead-based approaches, whether in cells or lysates, must incorporate an

understanding of differences in the chemical bead mixtures employed, the length of time the

beads are incubated with the protein extract, and the quantitative proteomic approaches used.

Last, while a few kinases have been shown to bind specific beads in an activity-dependent manner, the MIBs experimental platform described here reports competitive kinase capture independent of kinase activity.

Comparative analysis of our abemaciclib competitive MIB/MS data with previously

reported abemaciclib targets obtained from in vitro kinase activity and mobility shift assays reveal overlaps and unique discoveries (Supplementary Table 2). Common targets across these experiments include multiple CDKs (1, 2, 5, 7, and 9), GSK3 α and β, CAMKII β and δ, IRAK1,

SLK, PKN1, and others (Supplemental Table 2) (27,28). New abemaciclib targets not previously

reported include several additional CDKs (12, 13, 14, 15, 16, 17, and 19), AAK1, IKBKB, MET,

PLK4, and others (Supplemental Table 2). Discordance between kinase targets observed via in

vitro versus in vivo methods are likely driven by 1) differences in the dose of abemaciclib tested,

2) mass spectrometry detection limitations, 3) capacity of MIBs to bind the kinase, 4) kinase

expression in a given cell line or tissue, and 5) differences in ATP and/or cofactor

concentrations.

The value of studying target profiles of kinase inhibitors is well illustrated by our analysis

of the clinically active and FDA-approved CDK4/6 inhibitors. Distinct side effect profiles are

observed in treated patients. Palbociclib leads to hematologic toxicity and neutropenia, while

abemeciclib treatment results in gastrointestinal (GI) toxicity and more efficient blood brain

barrier penetration (38,39). Furthermore, abemaciclib is effective as a single agent whereas

palbociclib is given in combination with letrozole (39). Neutropenia and leukopenia were the most commonly reported grade 3 or 4 adverse event in ribociclib-treated patients in a recent phase 3 trial (40). The differential target profiles of these compounds likely contributes to their

differential dose-limiting toxicities.

Our data show that abemaciclib potently and directly inhibits GSK3β and consequently

activates WNT/β-catenin signal transduction. Palbociclib and ribociclib do not impact GSK3β or

WNT signaling. Further studies are needed to determine if abemaciclib activates WNT signaling 21

in patients and whether this activation contributes to observed toxicities, particularly within the

GI tract. WNT signaling contributes significantly to bone density disorders, a myriad of cancers,

metabolic disorders, and neuro-developmental and degenerative diseases (32). Abemaciclib is

generally dosed continuously in patients at up to 200 mg every 12 hr for two to three weeks (41).

As such, long-term exposure to abemaciclib may lead to continuous WNT signaling in these

patients, a potentially harmful side effect that should be considered.

In addition to GSK3β, our data and those of previous reports indicate that abemaciclib

inhibits members of the Ca2+/calmodulin-dependent kinase II (CAMKII) family; in vitro studies

described here demonstrate that this inhibition is direct and occurs in the low nanomolar range

(27,28). Four human CAMKII isoforms exist (α, β, δ, and γ), and they are serine/threonine

kinases that perform many functions and are responsive to calcium signaling (42,43). CAMKIIγ

has been shown to play roles in cell growth and survival in liver cancer and CML while

CAMKIIα depletion led to reduced growth of osteosarcoma cell lines (44-46). In T cell

lymphoma, CAMKIIγ phosphorylates cMYC at serine 62, leading to stabilization of cMYC

protein (47). Furthermore, inhibition of CAMKIIγ resulted in decreased tumor loads, suggesting that CAMKIIγ could be exploited as a therapeutic target in T cell lymphoma (47).

Phosphorylation of CAMKII at threonine 286 was increased in breast cancer tissue compared to

matched normal tissue, and phosphorylated T286 CAMKII regulated metastatic potential of

breast cancer cells (48). Due to the roles of CAMKII in cell growth and invasion in multiple

tumor types, CAMKII is a rational therapeutic target. Berbamine is a natural product derived

from the Berberis amurensis shrub and has been shown to inhibit CAMKII in Huh7 cells with an

IC50 of 5.2 ug/ml (7.6 uM given berbamine MW of 681.65) (45). Data presented here suggest

that abemaciclib is a better inhibitor of CAMKII as in vitro kinase activity assays calculated 22

IC50 values between 2 and 52 nM depending on the CAMKII isoform. Furthermore, treatment of

live H2228 NSCLC cells with 60 nM abemaciclib led to a >60% reduction in CAMKIIδ and

CAMKIIγ MIB binding (Figure 3 and Supplementary Table 1). Based on these data and previous

reports, future studies should be conducted to determine whether abemaciclib could be

repurposed as a CAMKII inhibitor for the treatment of CAMKII-driven disease.

Acknowledgments

The authors thank members of the Major Laboratory and Johnny Castillo for feedback, reagents,

and expertise regarding project design and experimental procedures.

References

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Figure 1. MIB/MS competition identifies targets of trametinib.

A.WB analysis of H2228 cell lysate incubated with trametinib for 1 hr prior to MIB enrichment.

B. MIB/WB analysis of H2228 cells treated with trametinib for 1 hr. C. H2228 cell lysate was

pre-bound to MIBs, washed, and then incubated for the indicated time with 300 nM trametinib.

D. MIB/MS competition analysis of H2228 cells treated with DMSO or 30 nM trametinib for 1

hr. In the volcano plot, vertical dashed lines indicate 2-fold label free quantitation (LFQ) change,

and horizontal dashed line depicts a 5% FDR threshold across 3 biological replicates. The p-

values were calculated via two-tailed t-test, and the FDR was determined by the Benjamini-

Hochberg procedure. 241 kinases were observed in two of three biological replicates in at least

one treatment condition with a minimum of three unique peptides. E. Mice were treated with

DMSO (n=4) or 0.3 mg/kg trametinib (n=5) for 2 hr. Kidneys were extracted, detergent solubilized, and subjected to MIB/MS. Volcano plot as in (D).

Figure 2. MIB/MS competition reveals novel targets of abemaciclib.

A. MIB/AP WB of H2228 cells treated with abemaciclib or DMSO for 1 hr. B. MIB/AP WB of

H2228 cells treated with palbociclib or DMSO for 1 hr. C. Volcano plot of DMSO versus 6 μM

abemaciclib (3 biological replicates) in H2228 cells. In the volcano plot, vertical dashed lines

indicate 2-fold label free quantitation (LFQ) change, and horizontal dashed line depicts a 5%

FDR threshold across 3 biological replicates. The p-values were calculated via two-tailed t-test,

and the FDR was determined by the Benjamini-Hochberg procedure. Filled red circles denote

kinases meeting a 5% FDR and >2-fold LFQ decrease in abemaciclib-treated cells; of these,

kinases meeting a 1% FDR are labeled. D. Volcano plot of DMSO versus 6 uM palbociclib (2 biological replicates for palbociclib and 3 biological replicates for DMSO) as described in (C).

Filled purple circles denote CDK4 and 6. Filled blue circles indicate kinases that are targeted by abemaciclib but not palbociclib.

Figure 3. Abemaciclib dose-dependently inhibits GSK3β from binding MIBs

A. Abemaciclib dose-response in H2228 cells using isobaric TMT labeling. Data are plotted as

the mean log2 fold-change compared to vehicle ± SE for 2 biological replicate experiments. TMT ratios for 128 kinases were quantified across both biological replicates. B. Abemaciclib dose-

response in H2228 lysate using isobaric TMT labeling. Data are plotted as the mean log2 fold-

change compared to vehicle ± SE for 2 biological replicate experiments as in (A). TMT ratios for

133 kinases were quantified across both biological replicates.

Figure 4. GSK3β is an abemaciclib-specific target.

A. MIB/AP WB validation of GSK3β and CAMKIIβ/δ/γ following abemaciclib treatment of

H2228 cells. B. MIB/AP WB confirming that palbociclib does not affect GSK3β or

CAMKIIβ/δ/γ MIB binding. C. MIB/AP WB indicating that ribociclib does not preclude GSK3β

from binding MIBs. D. MIB/AP WB in H1703 cells indicating abemaciclib-specific effects on

GSK3β and CAMKIIβ/δ/γ MIB binding in a second cell line.

Figure 5. In vitro kinase activity assays indicate that abemaciclib directly inhibits GSK3β.

In vitro kinase activity assays for abemaciclib and palbociclib against CDK4/cyclin D1 (A),

CDK6/cyclin D1 (B), CDK4/cyclin D3 (C), CDK6/cyclin D3 (D), GSK3β (E), CAMKIIβ (F),

CAMKIIδ (G), and CAMKIIγ (H).

Figure 6. Abemaciclib activates WNT signaling.

A. Dual-Glo luciferase assays in cell lines stably expressing the WNT reporter (BAR). Bars

represent mean Firefly/Renilla ratios ± SD from 4 independent wells. The following abemaciclib and palbociclib ranges were used: 0.3125 μM – 5 μM (RKO B/R and HEK293T/17 B/R) or

0.625 μM – 10 μM (H2228 B/R). CHIR-99021 was treated at 1 μM. Data are representative of one biological replicate from three independent experiments. B. IncuCyte live cell imaging of

HEK293T/17 BAR-GreenFire cells treated with DMSO, palbociclib, abemaciclib, 1 μM CHIR-

99021, or WNT or L-cell CM for 24 hr. Data are plotted as total green integrated intensity ± SD.

Data are representative of one biological replicate from three independent experiments. C.

Representative GFP fluorescent images corresponding to the experiment described in (B) at 22 hr post-treatment. Scale bar = 200 μm. D-E. Evaluation of β-catenin levels by WB analysis after

6 hr treatment of DMSO, abemaciclib (0.1-10 μM), palbociclib (0.1-10 μM), 1 μM CHIR-99021,

or recombinant WNT3A (rWNT3A, 200 ng/ml) in RKO B/R cells (D) or murine L-cells (E). F-

G. Evaluation of β-catenin levels by WB analysis of RKO B/R cells (F) or L-cells (G) following

treatment with DMSO, 5 μM abemaciclib, 5 μM CHIR-99021, or 10 μM palbociclib over a 30

min – 6 hr time course.

Downloaded from mcr.aacrjournals.org on October 6, 2021. © 2017 American Association for Cancer Research. Author Manuscript Published OnlineFirst on November 13, 2017; DOI: 10.1158/1541-7786.MCR-17-0468 A. Author manuscripts have been peer B.reviewed and accepted for publicationC. but have not yet been edited. Input AP:MIB Input AP:MIB Input AP:MIB Trametinib (nM) Trametinib (nM) Tramet. (nM) Tramet. (nM) Trametinib Trametinib Veh Veh 4 0.5 1 2 4 4 0.5 1 2 4 Time (h) 3 30 300 3000 3 30 300 3000 Veh Veh Veh 3 30 300 3000 Veh 3 30 300 3000

MEK1/2 MEK1/2 MEK1/2

AXL AXL AXL GAPDH GAPDH GAPDH H2228 cells H2228 cells H2228 lysate

Trametinib vs. Vehicle Trametinib vs. Vehicle D. H2228 cells E. Mouse kidney 2.0 MAP2K1 Map2k1 5% FDR

1.5 MAP2K2 1.0 5% FDR Map2k2 q-value 1.0 q-value 10 10 −Log −Log 0.5

0.5

0.0 0.0

−4 −3 −2 −1 0 1 2 3 4 −2 −1 0 1 2

Log2 fold-change Log2 fold-change

Figure 1

A. Input AP:MIB B. Input AP:MIB

Abemaciclib (μM) Abemaciclib (μM) Palbociclib (μM) Palbociclib (μM) Veh Veh 0.006 0.06 0.6 6 0.006 0.06 0.6 6 Veh 0.006 0.06 0.6 6 Veh 0.006 0.06 0.6 6 CDK6 CDK6

CDK4 CDK4

AXL AXL

GAPDH BTUBB

H2228 cells H2228 cells

C. D. Abemaciclib vs. Vehicle Palbociclib vs. Vehicle H2228 cells H2228 cells CAMK2G CDC42BPB CSNK2A2 1.5 TAOK3 MAP2K4 PIP4K2B CAMK2D CDK9 CDK17 5% FDR CSNK2A1 AAK1 ROCK2 GSK3A 3 PRKCA PRKCQ CDK4 EIF2AK2 PRKD2 RPS6KA5 GSK3B ADK CDK4 CDK6 DAPK3 1.0 CDK6 CDK16 CLK2 PRKCD PKN2 2 IRAK1 PRKD3 PIKFYVE q-value q-value CAMK2G 10 10 −Log NEK1 5% FDR −Log 0.5 CAMK2D 1 GSK3B

0 0.0

−10 −8 −6 −4 −2 0 2 4 6 8 10 −5 −4 −3 −2 −1 0 1 2 3 4 5

Log2 fold-change Log2 fold-change

Figure 2

Downloaded from mcr.aacrjournals.org on October 6, 2021. © 2017 American Association for Cancer Research. AuthorAbemaciclib Manuscript Dose-Response Published OnlineFirst on November 13, 2017; DOI: 10.1158/1541-7786.MCR-17-0468 A. Author manuscriptsH2228 cells have been peer reviewed and accepted for publication but have not yet been edited.

0 AXL

−2

CDK4 (fold change from vehicle)

2 CDK6

Log −4 CAMK2D CAMK2G GSK3A GSK3B Veh 0.006 0.06 0.6 6 Abemaciclib concentration (µM)

B. Abemaciclib Dose-Response H2228 lysate

AXL

CDK4 −2 CDK6 CAMK2G GSK3B (fold change from vehicle)

2 CAMK2D

Log −4

GSK3A

Veh 0.006 0.06 0.6 6 Abemaciclib concentration (µM)

Figure 3

Downloaded from mcr.aacrjournals.org on October 6, 2021. © 2017 American Association for Cancer Research. A. Author Manuscript PublishedB. OnlineFirst on November 13, 2017; DOI: 10.1158/1541-7786.MCR-17-0468 Input AuthorAP:MIB manuscripts have been peer Inputreviewed and acceptedAP:MIB for publication but have not yet been edited. Abemaciclib (μM) Abemaciclib (μM) Palbociclib (μM) Palbociclib (μM) Veh 0.006 0.06 0.6 6 Veh 0.006 0.06 0.6 6 0.006 0.06 0.6 6 0.006 0.06 0.6 6 Veh Veh

CDK6 CDK6

GSK3β GSK3β

AXL AXL

CAMKII pan CAMKII pan

GAPDH GAPDH

H2228 cells H2228 cells

C. D. Input AP:MIB Input AP:MIB Ribociclib (μM) Ribociclib (μM) Abema. (μM) Palbo. (μM) Abema. (μM) Palbo. (μM) Veh 0.01 0.1 10 Veh 0.01 0.1 1 10 1 Veh 0.006 0.06 0.6 6 Veh 0.006 0.06 0.6 6 Veh 0.006 0.06 0.6 6 CDK6 Veh 0.006 0.06 0.6 6 CAMKII pan CDK4 GSK3β GSK3β AXL AXL GAPDH

GAPDH H1703 cells

H2228 cells

Figure 4

Downloaded from mcr.aacrjournals.org on October 6, 2021. © 2017 American Association for Cancer Research. A. CDK4/cyclinAuthor D1 Manuscript PublishedB. OnlineFirstCDK6/cyclin on November D1 13, 2017; DOI: 10.1158/1541-7786.MCR-17-0468 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. 120 Abemaciclib 120 Abemaciclib Palbociclib Palbociclib 100 100 80 80 60 60 % Activity % Activity 40 40 20 20 0 0 -11 -10 -9 -8 -7 -6 -11 -10 -9 -8 -7 -6 Log [Compound] (M) Log [Compound] (M) Abemaciclib Palbociclib Abemaciclib Palbociclib HillSlope -1.31 -0.88 HillSlope -0.96 -1.09 IC50 [M] 4.6e-010 1.3e-009 IC50 [M] 4.3e-010 4.3e-010

C. CDK4/cyclin D3 D. CDK6/cyclin D3 120 120 Abemaciclib Abemaciclib 100 Palbociclib 100 Palbociclib 80 80 60 60 % Activity 40 % Activity 40 20 20 0 0 -11 -10 -9 -8 -7 -6 -11 -10 -9 -8 -7 -6 Log [Compound] (M) Log [Compound] (M) Abemaciclib Palbociclib Abemaciclib Palbociclib HillSlope -1.81 -1.41 HillSlope -0.76 -0.79 IC50 [M] 6.2e-009 7.0e-009 IC50 [M] 8.9e-009 5.1e-009

E. GSK3β F. CAMKIIβ 120 120 Abemaciclib Abemaciclib 100 Palbociclib 100 Palbociclib 80 80 60 60 % Activity % Activity 40 40 20 20 0 0 -9 -8 -7 -6 -5 -4 -3 -9 -8 -7 -6 -5 -4 -3 Log [Compound] (M) Log [Compound] (M) Abemaciclib Palbociclib Abemaciclib Palbociclib HillSlope -0.95 -0.84 HillSlope -0.77 -0.80 IC50 [M] 8.7e-009 1.1e-005 IC50 [M] 3.5e-009 1.6e-006

G. CAMKIIδ H. CAMKIIγ 120 120 Abemaciclib Abemaciclib 100 Palbociclib 100 Palbociclib 80 80 60 60 % Activity 40 % Activity 40 20 20 0 0 -9 -8 -7 -6 -5 -4 -3 -9 -8 -7 -6 -5 -4 -3 Log [Compound] (M) Log [Compound] (M) Abemaciclib Palbociclib Abemaciclib Palbociclib HillSlope -0.86 -0.84 HillSlope -0.81 -0.93 IC50 [M] 2.6e-009 6.1e-007 IC50 [M] 5.2e-008 9.4e-006

Figure 5

Downloaded from mcr.aacrjournals.org on October 6, 2021. © 2017 American Association for Cancer Research. Author Manuscript Published OnlineFirst on November 13, 2017; DOI: 10.1158/1541-7786.MCR-17-0468 A. Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. RKO B/R HEK293T/17 B/R H2228 B/R 8 0.9 0.35 7 0.8 0.30 6 0.7 0.6 0.05 5 0.5 0.04 4 0.4 0.03 3 0.3 0.02 2 0.2 1 0.1 0.01 Firefly/ Renilla (arbitrary units) Firefly/ Renilla (arbitrary units) 0 0 Firefly/ Renilla (arbitrary units) 0

Palbociclib Abemaciclib Palbociclib Abemaciclib Palbociclib Abemaciclib CHIR-99021 WNT3A CM Veh L cell CM L Veh CHIR-99021 WNT3A CM cell CM L Veh CHIR-99021 WNT3A CM L cell CM L Treatment Treatment Treatment

B. C. 6x105 WNT CM L-cell CM 1 uM CHIR-99021 DMSO 0.625 uM Abema 0.625 uM Palbo DMSO L-cell CM CTPalbociclib (2.5 µM)

5 1.25 uM Abema 1.25 uM Palbo 5x10 2.5 uM Abema 2.5 uM Palbo 5 uM Abema 5 uM Palbo

4x105

3x105 CHIR-99021 (1 µM) WNT3A CM Abemaciclib (2.5 µM)

2x105

Total Green Integrated Intensity Intensity Integrated Green Total 1x105

0 0 2 4 6 8 10 12 14 16 18 20 22 Hours post-treatment

D. F. Abema. (μM) Palbo. (μM) Abemaciclib (5 μM) CHIR-99021 (5 μM) Veh Palbociclib

6 0.5 1 2 3 4 6 0.5 1 2 3 4 6 6 Time (h) 0.1 2.5 5 10 0.1 2.5 5 10 untreated Veh CHIR-99021 rWnt3A

β-catenin β-catenin

GSK3β GSK3β

GAPDH GAPDH

RKO B/R cells RKO B/R cells

E. G.

Abema. (μM) Palbo. (μM) Abemaciclib (5 μM) CHIR-99021 (5 μM) Veh Palbociclib Time (h)

5 5 6 0.5 1 2 3 4 6 0.5 1 2 3 4 6 6 untreated Veh CHIR-99021 rWnt3A 0.1 2.5 10 0.1 2.5 10

β-catenin β-catenin

GSK3β GSK3β

GAPDH GAPDH

L-cells (murine) L-cells (murine)

Figure 6

Competitive Kinase Enrichment Proteomics Reveals that Abemaciclib Inhibits GSK3 β and Activates WNT Signaling

Emily M Cousins, Dennis Goldfarb, Feng Yan, et al.

Mol Cancer Res Published OnlineFirst November 13, 2017.

Updated version Access the most recent version of this article at: doi:10.1158/1541-7786.MCR-17-0468

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