Identification of Regulators of
Polyploidization Presents Therapeutic
Targets for Treatment of AMKL
Qiang Wen,1Benjamin Goldenson,1Serena J. Silver,2Monica Schenone,2Vlado Dancik,2Zan Huang,1Ling-Zhi Wang,3
Timothy A. Lewis,2W. Frank An,2Xiaoyu Li,2Mark-Anthony Bray,2Clarisse Thiollier,4Lauren Diebold,1Laure Gilles,1
Martha S. Vokes,2Christopher B. Moore,2Meghan Bliss-Moreau,2Lynn VerPlank,2Nicola J. Tolliday,2Rama Mishra,5
Sasidhar Vemula,6Jianjian Shi,6Lei Wei,6Reuben Kapur,6Ce ´cile K. Lopez,4Bastien Gerby,7Paola Ballerini,8
Francoise Pflumio,7D. Gary Gilliland,9Liat Goldberg,10Yehudit Birger,10Shai Izraeli,10Alan S. Gamis,11
Franklin O. Smith,12William G. Woods,13Jeffrey Taub,14Christina A. Scherer,2James E. Bradner,2,15Boon-Cher Goh,3
Thomas Mercher,4Anne E. Carpenter,2Robert J. Gould,2Paul A. Clemons,2Steven A. Carr,2David E. Root,2
Stuart L. Schreiber,2Andrew M. Stern,2,* and John D. Crispino1,*
1Division of Hematology/Oncology, Northwestern University, Chicago, IL 60611, USA
2Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
3Cancer Science Institute, National University of Singapore 117599, Singapore
4Institut Gustave Roussy, INSERM U985, 94800 Villejuif, France
5Center for Molecular Innovation and Drug Discovery (CMIDD), Evanston, Northwestern University, Chicago, IL 60208, USA
6Department of Pediatrics, Indiana University, Indianapolis, IN 46202, USA
7INSERM UMR967, Institut de radiobiologie cellulaire et mole ´culaire, CEA-EA 92265 Fontenay-aux-Roses, France
8Ho ˆpital Trousseau, AP-HP, 75571 Paris, France
9Merck, West Point, PA 19446, USA
10Sheba Medical Center, Tel Aviv University, Ramat Gan 52621, Israel
11Children’s Mercy Hospital and Clinics, Kansas City, MO 64108, USA
12University of Cincinnati Cancer Institute, Cincinnati, OH 45229, USA
13Aflac Cancer Center, Children’s Healthcare of Atlanta and Emory University, Atlanta, GA 30322, USA
14Children’s Hospital of Michigan, Detroit, MI 48201, USA
15Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
*Correspondence: email@example.com (A.M.S.), firstname.lastname@example.org (J.D.C.)
The mechanism by which cells decide to skip mitosis
to become polyploid is largely undefined. Here we
used a high-content image-based screen to identify
small-molecule probes that induce polyploidization
of megakaryocytic leukemia cells and serve as
perturbagens to help understand this process.
Our study implicates five networks of kinases
that regulate the switch to polyploidy. Moreover,
we find that dimethylfasudil (diMF, H-1152P) selec-
tively increased polyploidization, mature cell-surface
marker expression, and apoptosis of malignant
megakaryocytes. An integrated target identification
approach employing proteomic and shRNA screen-
ing revealed that a major target of diMF is Aurora
kinase A (AURKA). We further find that MLN8237
(Alisertib), a selective inhibitor of AURKA, induced
polyploidization and expression of mature megakar-
yocyte markers in acute megakaryocytic leukemia
(AMKL) blasts and displayed potent anti-AMKL
activity in vivo. Our findings provide a rationale to
support clinical trials of MLN8237 and other inducers
of polyploidization and differentiation in AMKL.
Megakaryocytes are one of the few cell types that undergo
a modified form of the cell cycle termed endomitosis, in which
cells skip the late stages of mitosis to become polyploid (Bluteau
et al., 2009) (Figure 1A). Murine and human megakaryocytes
commonly reach modal ploidy states of 32N and 16N, respec-
tively, and can sometimes achieve DNA contents as high as
128N. Although the mechanism of polyploidization is still not
well understood, altered expression of genes including D and E
type cyclins, spindle checkpoint proteins, and chromosome
passenger proteins has been implicated (Wen et al., 2011).
Acute megakaryoblastic leukemia (AMKL), a rare and deadly
form of acute myeloid leukemia, is characterized by expansion
fibrosis that interferes with normal blood development (Malinge
et al., 2009). Pediatric AMKL is frequently associated with chro-
mosomal abnormalities, including trisomy 21 in Down syndrome
AMKL (DS-AMKL) and t(1;22), which leads to expression of the
OTT-MAL fusion protein in non-DS-AMKL (Ma et al., 2001;
Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc. 575
Mercher et al., 2001). Mutations in GATA1, a transcription factor
yocytes, are present in nearly all cases of DS-AMKL, whereas
mutations in JAK3, MPL, KIT, and FLT3 are associated with
a smaller subset of AMKL patients (Malinge et al., 2009; Wechs-
ler et al., 2002). Although many DS-AMKL patients respond to
current therapies, including low-dose cytosine arabinoside
chemotherapy, adults with non-DS-AMKL have a very poor
prognosis, with the vast majority relapsing within 1 year of the
primary treatment (Tallman et al., 2000). New therapeutic strate-
gies are desperately needed.
Given that leukemic blasts from AMKL patients are hyperpro-
liferative and fail to undergo differentiation or polyploidization,
and that megakaryocytes are poised to undergo polyploidization
in the normal course of development, we hypothesized that
small-molecule inducers of polyploidization would drive these
cells to exit the proliferative cell cycle and undergo terminal
differentiation. These small-molecule probes could also serve
to help understand the mechanism(s) underlying polyploidiza-
antileukemia activity in vitro and in vivo. We used an integrative
approach to target identification that allowed intelligent prioriti-
zation and testing of candidate targets, and we show that
AURKA kinase is an essential negative regulator of polyploidiza-
tion in AMKL blasts and a potential therapeutic target for this
subtype of leukemia.
Figure 1. Cell-Based, High-Content Imaging Screen for Compounds that Induce Megakaryocyte Polyploidization
(A) Schematic of megakaryocyte development. MEP, megakaryocyte-erythroid progenitor; BFU-MK, burst-forming unit megakaryocyte; CFU-MK, colony-
forming unit megakaryocyte.
(B) Schematic of the image-based high-throughput screen to identify small molecules that induce polyploidization of leukemic megakaryocytes.
(C) Structures of representative hit compounds and their effects on megakaryocyte polyploidization. Structures (left) and histograms of DNA content as
measured by CellProfiler (right) are shown. Light gray lines depict DMSO control, and black lines depict ploidy states of cells cultured with the respective
See also Table S1.
576 Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc.
A High-Content Screen Identifies Small Molecules that
Induce Polyploidization in Human Megakaryocytes
To identify compounds that induce megakaryocyte polyploidiza-
tion, we developed an imaging assay capable of measuring
DNA content in cultured AMKL cell lines (Figure 1). Small-
molecule screening was performed with a human cell line
derived from a patient with DS-AMKL (CMK) (Sato et al., 1989)
and a chemically diverse small-molecule library. Following
a 3 day incubation, cells were fixed and stained with Hoechst
dye, and individual wells were imaged by automated epifluores-
cence microscopy (ImageXpress Micro; Molecular Devices)
and then analyzed for nuclear morphology and fluorescence
intensity with CellProfiler (Carpenter et al., 2006). SU6656,
a Src kinase inhibitor known to induce polyploidization of
awide spectrumof cells, was used asa positive control (Lannutti
et al., 2005). This assay had an average Z0factor (Zhang et al.,
1999) > 0.7 over the study. Among approximately 9,000
compounds screened, we identified 206 positives that signifi-
cantly increased the fraction of cells with DNA content beyond
a cutoff (between 4N and 8N) as compared to DMSO (Figure 1C
and Table S1). Among these compounds were the expected
microtubule-disrupting and -stabilizing agents and actin-dis-
rupting agents, including cytochalasin B and latrunculin B, which
were predicted to cause alterations in spindle formation or cyto-
kinesis and result in polyploidization. In addition, a number of
compounds annotated as kinase inhibitors were identified,
including dimethylfasudil (diMF, H1152P, BRD4911), reversine,
K252a, and JAK3 inhibitor VI. Dose-ranging secondary studies
of assay positives found 149 of the 206 compounds to exhibit
an EC50% 100 mM (Table S1).
A Subset of Assay Positives Induces Both
Polyploidization and Features of Megakaryocyte
Despite the temporal association between polyploidization and
upregulation of megakaryocyte-specific genes, recent findings
suggest that these two processes can be uncoupled (Muntean
et al., 2007). In order to assess whether small-molecule inducers
of polyploidization also induced megakaryocyte maturation,
we selected several compounds for more detailed analysis.
This list included diMF and K252a; latrunculin B, an actin
polymerization inhibitor; JAK3 inhibitor VI; reversine, a molecule
that induces dedifferentiation and polyploidization (D’Alise
et al., 2008); NP003964, a natural product; and SU6656.
Compared to SU6656, diMF induced much higher polyploidiza-
tion in CMK cells over a much wider dose range (Figure 2B and
data not shown). Although each of these compounds inhibited
proliferation while inducing polyploidization and apoptosis,
only diMF and NP003964 also induced expression of the mega-
karyocyte-specific markers CD41 and CD42 (Figure 2 and data
diMF was tested against a panel of megakaryocytic cell lines
and found to induce robust polyploidization and expression of
differentiation markers in every line tested, including CMS,
CHRF, Meg01, K562, Y10, and G1ME cells (Stachura et al.,
2006) (Figure S1A). diMF also induced polyploidization and
CD41 expression in an AMKL cell line derived from Ets-related
gene (ERG)transgenic mice (tg-ERG) (L.G., Y.B,and S.I., unpub-
lished data), which express the ERG transcription factor under
the control of the vav promoter (Figure S1B).
Next, we examined the effect of diMF on primary murine
hematopoietic progenitor cells cultured in the presence of
thrombopoietin (THPO). Treatment with diMF led to a dose-
dependent increase in polyploidization and upregulation of
CD41 and CD42 expression in murine bone marrow-derived
megakaryocytes (Figures S2A–S2C). At 5 mM, diMF upregulated
CD41 and CD42 expression by 9- and 18-fold, respectively,
while increasing the mean polyploidy of CD41+cells from 5.8N
to 10.7N. diMF also induced polyploidization and upregulation
of CD41 and CD42 in GATA-1s-KI fetal liver megakaryocytes,
which mimic DS-AMKL cells in that they express the shortened
leukemic isoform of GATA-1 called GATA-1s (Li et al., 2005;
Wechsler et al., 2002) (Figure S2D and data not shown). More-
over, when human primary bone marrow mononuclear cells
were cultured in the presence of THPO, diMF induced polyploid-
ization of CD41+cells but not the CD41?fraction (Figure S2E).
Thus, diMF selectively induces polyploidization of the megakar-
yocyte lineage and can override the proliferative defect caused
by mutations in GATA1.
diMF Has Antileukemia Activity
A subset of pediatric non-DS-AMKL patients harbors the
(1;22)(p13;q13) chromosomal translocation, which results in
expression of the OTT-MAL fusion protein. Transgenic mice
that express OTT-MAL develop AMKL with a low penetrance
and long latency, whereas recipients of OTT-MAL bone marrow
expressing MPLW515L rapidly develop AMKL with high pene-
trance (Mercher et al., 2009). 6133/MPL cells, which were
derived from OTT-MAL transgenic mice and engineered to
express MPLW515L, are quite sensitive to diMF: treatment of
6133/MPL cells with 3 mM diMF led to strong upregulation of
CD41 and CD42, polyploidy, and apoptosis (Figures 3A and 3B
and data not shown).
To assess whether diMF induces an irreversible proliferative
arrest that would prevent development of leukemia in transplant
for 24 hr and then transplanted 1 million viable cells into recipient
mice. Transplantation of vehicle-treated 6133/MPL cells into
sublethally irradiated C57Bl/6 mice led to a fulminant AMKL
with a short latency, with all of the animals developing leukemia
and dying within 3 weeks (Figures 3C and 3D). The disease was
characterized by splenomegaly, disruption of splenic architec-
ture, and a high proportion of GFP-labeled 6133/MPL cells in
the peripheral blood, bone marrow, spleen, and liver (data not
shown). Strikingly, none of the mice transplanted with diMF-pre-
treated 6133/MPL cells developed leukemia (Figure 3D). Thus,
brief exposure of 6133/MPL cells to diMF is sufficient to block
their leukemia-inducing activity.
Next, we assessed the oral pharmacokinetics of diMF in vivo.
C57Bl/6 mice were fed a single dose of 66 mg/kg diMF, and
plasma concentrations were measured. The mean maximum
concentration achieved was 5.8 mM (Cmax) at 5 min (Tmax) (Fig-
ure 3E), which is higher than the dose of diMF necessary to
induce maximum polyploidization of 6133/MPL cells. Having
Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc. 577
Figure 2. Lead Compounds Induce Polyploidization, Expression of Differentiation Markers, and Apoptosis of a Human Megakaryocytic Cell
(A) Left, images of Hoechst-stained CMK cells treated with DMSO or diMF. Right, EC50determination for diMF induction of polyploidization > 8N. Scale bar:
(B–G) K252a (5 mM), latrunculin B (5 mM), SU6656 (4 mM), and diMF (5 mM) induced polyploidization (B and E), apoptosis (C and F), proliferative arrest (D), and
expression of CD41 and CD42 (G) in CMK cells 72 hr after treatment. Representative flow cytometry plots are shown. Bar graphs depict mean ± SD of two
independent experiments conducted in triplicate; *p < 0.05, **p < 0.01.
See also Figures S1 and S2.
578 Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc.
shown that biologically active concentrations of diMF were
achieved in vivo after oral administration, we fed healthy
C57Bl/6 mice with vehicle or diMF by oral gavage twice a day
for 7 days and evaluated their body weight and hematopoietic
indices. diMF was well tolerated: we did not observe significant
changes in body weight or peripheral blood indices, including
platelet counts (Figures S3A–S3E).
planted sublethally irradiated recipient C57Bl/6 mice with 1
million 6133/MPL cells. Forty-eight hours after transplantation,
we detected GFP-positive cells in the spleen and bone marrow
of recipient mice, confirming engraftment of the 6133/MPL cells.
Mice were then fed vehicle or diMF twice a day for 10 days.
Whereas all the vehicle-treated mice died within 20 days, 43%
of the mice treated with 66 mg/kg diMF and 29% of mice fed
33 mg/kg diMF survived at least 70 days post-transplantation
(Figure 3F). diMF also significantly increased the survival of
mice when treatment was initiated 7 days after transplantation,
when the percentage of GFP-positive cells in the peripheral
blood was near 20% (data not shown). Importantly, we observed
a significant increase in DNA content, expression of CD41, and
apoptosis of 6133/MPL cells in the bone marrows of recipient
mice 72 hr after treatment with 66 mg/kg diMF (Figures 3G,
S3F, and S3G). We also noted that diMF reduced the number
of GFP-positive 6133/MPL cells in recipient animals (Figures
of transplanted mice by inducing polyploidization of 6133/MPL
cells in vivo.
We next treated human non-DS-AMKL blasts isolated from
primary immunodeficient (NOD/LtSz-scid IL2Rgc null; NSG)
recipient mice with vehicle or diMF. In vitro, 5 mM diMF signifi-
cantly increased polyploidization and inhibited proliferation of
the AMKL blasts (Figure 3H). Secondary recipient NSG mice
transplanted with non-DS-AMKL blasts showed decreased
tumor burden of human CD41+cells (Figures 3I and 3J) when
treated with diMF at 30 mg/kg or 60 mg/kg. diMF also signifi-
cantly increased the polyploidization of human CD41+cells in
the spleens of recipient mice (Figure 3K). Finally, we cultured
primary human DS-AMKL bone marrow specimens with DMSO
or diMF and monitored the growth of the leukemic cells in colony
assays. In all five patient samples studied, diMF significantly
reduced the colony formation of AMKL blasts (Figure 3L).
An Integrated Target Identification Method Identifies
Candidate Physiologic Targets of diMF in AMKL
To address the challenge of determining the mode of action of
small molecules identified from phenotypic screens (Terstappen
et al., 2007), we implemented an integrative approach for identi-
fying the targets of diMF in megakaryoblasts (Figure 4A). diMF is
an ATP competitive inhibitor of several kinases that include the
Rho kinase family (Ikenoya et al., 2002), but other Rho kinase
inhibitors such as fasudil did not fully recapitulate the strong
phenotype induced by diMF in AMKL-derived cells (data not
shown). Thus we began with the hypothesis that diMF produced
this phenotype by acting as a kinase inhibitor but perhaps not
exclusively through Rho kinase family members.
First, we performed an Ambit KinomeScan analysis and
compared the kinase-binding profiles of diMF to those of the
closely related compound fasudil (Fabian et al., 2005; Karaman
et al., 2008). From 402 purified kinases tested, we identified
117 kinases whose binding to the immobilized ligand was in-
hibited by more than 65% in the presence of 5 mM diMF relative
to the control that contained no competing ligand (Table S2). In
contrast, only 27 kinases were inhibited to a similar extent
when fasudil was used as the competing ligand. Among the
differentially affected kinases, the Aurora kinase family (A, B,
and C) was notable for being strongly inhibited by diMF but not
at all by fasudil.
To identify protein binders of diMF in CMK cells, we used
a modified version of our previously published method (Ong
et al., 2009) (Figure 4B). Using the broad specificity kinase ligand
K252a (shown to induce polyploidization; Figure 2B), immobi-
lized on beads as bait (Ong et al., 2009), and preincubating
CMK cell lysates with excess soluble diMF, we identified 68
proteins that were significantly and specifically competed
away from K252a by diMF (Table S3; Figures 4B and 4C). The
majority of these proteins are kinases or known to associate
To obtain an orthogonal data set to the proteomic and
biochemical methods, we performed an RNAi screen to identify
kinases whose knockdowns induced polyploidization in CMK
cells, either on their own (phenocopy screen) or in conjunction
with a dose of diMF that produces 5%–10% of its maximum pol-
yploidization induction effect (1 mM; modifier screen) (Figures 4A
and S4). The modifier screen complements the phenocopy
screen in that combining a low dose of diMF with RNAi-based
gene knockdown may provide selectivity for genes directly
involved in the diMF mechanism of action. Large increases in
high-ploidy cells were produced by hit small hairpin RNAs
(shRNAs); in untreated control wells, 3%–5% of cells were high
ploidy, whereas the top 2% of shRNAs produced wells with
30%–80% high-ploidy cells in both the DMSO and diMF
screens. Genes were ranked for the effect on ploidy of their
two top-scoring shRNAs (see Experimental Procedures for
details). Knockdown of 54 kinases increased the fraction of
high-ploidy cells in DMSO treatment. In cells treated with 1 mM
diMF, knockdown of 43 kinases increased the fraction of high-
ploidy cells versus diMF treatment alone. We also ranked
shRNAs by their differential effect in the two screens; 47 genes
showed significant increase in induction of polyploidy upon
knockdown under diMF treatment versus vehicle alone (Table
S4 and Figure 4D). Using these threecriteria, a total of 95 distinct
genes were selected for further analyses.
AURKA Is a Target of diMF and a Mediator of
Polyploidization of Malignant Megakaryocytes
We performed an integrated analysis of the results of the Kino-
meScan, the SILAC-based protein-binding assay, and the
RNAi screenfor polyploidization. Weassigned combined pvalue
scores based on the p values of each individual approach and
evidence counts and identified 15 kinases with scores less
than 0.05(Table S5). The top five kinases that showed significant
enrichment by this analysis include Aurora kinase B (AURKB),
protein kinase C delta (PRKCD), feline sarcoma oncogene
(FES), AURKA, and v-src sarcoma (Schmidt-Ruppin A-2; SRC).
In contrast to AURKB, a well-studied component of the
Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc. 579
Figure 3. diMF Displays Antileukemic Activity Both In Vitro and In Vivo
(A and B) diMF-induced polyploidization (A) and expression of CD41 and CD42 (B) in 6133/MPL cells 48 hr after treatment. Data are representative of two
(C) Transplantation of 6133/MPL cells causes AMKL in sublethally irradiated recipient mice. H&E-stained spleen sections revealed massive infiltration of tumor
cells in transplanted mice but not control mice. Scale bar: 50 mm.
(D) Survival curve of mice transplanted with 6133/MPL cells pretreated with vehicle or 10 mM diMF for 24 hr. n = 7 mice per group; p = 0.0002.
(E) Measurement of drug concentration in plasma after asingle dose of diMF. C57Bl/6 mice were dosed orally with 66 mg/kg of diMF, and plasma concentrations
of the drug were assessed at multiple time points post-treatment; n = 3 animals per time point. The insert depicts decay over 2 hr.
(F) Survival curve of mice transplanted with 1 million 6133/MPL cells and treated with vehicle or diMF at 33 or 66 mg/kg for 10 days, beginning 2 days after
transplantation; n = 7 mice per group. Results are representative of two independent experiments.
(G) diMF induction of polyploidization of 6133/MPL cells in vivo. Forty-eight hours after transplantation, mice were fed vehicle or 66 mg/kg diMF
by oral gavage twice a day for 3 days, and the DNA content of the transplanted cells in bone marrow was evaluated by flow cytometry; n = 3 animals per
(H) diMF-induced polyploidizationof human non-DS-AMKLblasts. Human CD41+non-DS-AMKLblasts from primary NSG recipientswere treated withvehicle or
5 mM diMF for 6 days.
580 Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc.
chromosome passenger complex that is known to control both
normal and endomitotic cell cycles (Lordier et al., 2010), less is
known about AURKA with respect to polyploidization. AURKA
regulates microtubule-organizing center localization, chromo-
some dynamics, and histone H3 phosphorylation in oocytes
(Ding et al., 2011) and is required for bipolar spindle formation
and early development (Cowley et al., 2009). AURKA is regarded
as an important target of anticancer therapy, and several small-
molecule inhibitors have been developed, including the highly
selective compound MLN8237, which displays 200-fold selec-
tivity for AURKA relative to AURKB in cells (Go ¨rgu ¨n et al.,
2010; Manfredi et al., 2011). Expression of MLN8237-resistant
(I–K) diMF reduced tumor burden and induced polyploidization of NSG mice transplanted with human non-DS-AMKL blasts from primary NSG recipients.
Secondary NSGrecipients were treated withvehicle or diMF at 30 or 60mg/kg for 10 days. diMF reduced human CD41+cells in spleen (I) and peripheralblood(J)
and induced polyploidization (K) of human CD41+cells in the spleen.
(L) diMF inhibition of DS-AMKL blast colony formation. Bone marrow specimens from pediatric patients with DS-AMKL were cultured in Megacult-C media with
THPO and either DMSO or 5 mM diMF for 10–12 days. Representative images of anti-CD41 antibody-stained colonies are shown; scale bar: 100 mm.
All bar graphs depict means ± SD; *p<0.05. See also Figure S3.
Figure 4. An Integrated Target ID Approach Identifies AURKA as a Target of diMF in AMKL
(A) Schematic representation of the integrated target identification workflow. CMK cells were transduced with shRNAs targeting the human kinome, and the
effects of knockdown were studied in the presence of DMSO (phenocopy screen) or a minimally effective dose of diMF at 1 mM (modifier screen).
(B) Quantitative proteomic strategy for identification of specific diMF-protein interactions. Proteins in cell populations were fully metabolically labeled with light
(yellow) and heavy amino acids lysine and arginine (red) using SILAC methodology. Cell lysates were incubated either with K252a-loaded beads (K252a-Beads)
for specific) were enriched in the heavy state over the light and identified with differential ratios in the mass spectrometer. Nonspecific (via binding to the bead) or
K252a (NS) interactions of proteins were enriched equally in both states and have ratios close to unity.
(C) Identification of significant targets of diMF using affinity proteomics with SILAC. Scatter plot of two replicate experiments of diMF at 50-fold excess
over K252a on beads is shown. Each data point is a single protein with kinases (Manning et al., 2002), represented as red diamonds and blue diamonds
denoting nonkinases. Six hundred and ninety-eight proteins were identified and quantified in at least three experiments, resulting in 68 proteins with a combined
q value < 0.05.
(D) Venn diagram of genes scored as hits in each type of comparison from the RNAi screen.
See also Figure S4 and Tables S2, S3, S4, and S5.
Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc. 581
Figure 5. Inhibition of AURKA Phenocopies diMF
(A–E)MLN8237andAZD1152-HQPA inducedproliferation arrest(A),polyploidization (B), expression ofCD41 and CD42 (Cand D),and apoptosis (E)inCMKcells
72 hr after treatment. Data are representative of two experiments conducted in duplicate. Line graphs depict mean ± SD.
(F) MLN8237 and diMF increased the phosphorylation of histone H3, whereas AZD1152-HQPA decreased its levels.
(G) MLN8237, AZD1152-HQPA, and diMF differentially inhibited phosphorylation of Aurora kinases. CMK cells were incubated with 0.1 mM paclitaxel
for 18 hr, then DMSO, MLN8237, AZD1152-HQPA, or diMF was added and incubated for 2 hr. The degree of phosphorylation of the Aurora kinases in each
582 Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc.
AURKA mutantshas previouslyvalidated AURKA asthetarget of
this molecule in cells (Sloane et al., 2010).
To determine whether inhibition of Aurora kinases could
phenocopy diMF, we treated CMK cells with their inhibitors
and assayed proliferation, survival, and megakaryocyte cell-
surface marker expression. Both MLN8237, a specific inhibitor
of AURKA, and AZD1152-HQPA, a specific inhibitor of AURKB,
restricted proliferation and induced robust polyploidization,
differentiation as assessed by CD41 and CD42 expression,
and apoptosis of CMK cells (Figures 5A–5E). In the 6133/MPL
murine cell line, they increased polyploidization, CD41 and
CD42 expression, and apoptosis (Figures S5A–S5D). Moreover,
both compounds induced proliferation arrest and megakaryo-
cyte lineage-specific surface marker expression of tg-ERG cells
(data not shown). MLN8237 induced polyploidization and
expression of CD41 and CD42 in primary mouse bone marrow
cells cultured ex vivo (Figures S5E–S5G), and both MLN8237
and AZD1152-HQPA induced robust and selective polyploidiza-
tion of primary human megakaryocytes expanded from human
CD34+cells (Figure S5H and data not shown).
We next compared the effects of diMF, AZD1152-HQPA, and
MLN8237 on cellular biomarkers. diMF and MLN8237 induced
a similar degree of accumulation of phospho-histone H3, and
both compounds reduced AURKA autophosphorylation (Figures
5F and 5G), two hallmarks of selective AURKA inhibition
(Carmena and Earnshaw, 2003; Lok et al., 2010). Importantly,
0.1 mM MLN8237, which induced polyploidization, proliferation
arrest, upregulation of megakaryocyte lineage-specific markers,
and apoptosis of CMK cells, inhibited autophosphorylation of
AURKA but not AURKB. This result indicates that MLN8237
inhibits AMKL cell growth and induces polyploidization by selec-
tive inhibition of AURKA. In contrast, AZD1152-HQPA led to
of both Aurora A and B kinases at the concentrations that inhibit
AMKL cell growth (Figures 5F and 5G and data not shown). Of
note, diMF inhibited phosphorylation of both Aurora A and B
kinases but led to a dramatic increase in the levels of phos-
pho-histone H3 (Figure 5F), consistent with a dominant inhibition
of AURKA. Inhibition of AURKB phosphorylation by diMF at 3
and 5 mM parallels the finding that diMF binds to AURKB in the
Ambit KinomeScan assay (Table S2). A purified kinase assay
further confirmed that diMF inhibits AURKA, albeit more weakly
than MLN8237 (Figure 5H). Although RNAi-targeted knockdown
of AURKB or pharmacologic inhibition by AZD1152-HQPA of its
encoded kinase induces polyploidization in megakaryocyte
precursors, this phenotype is not exclusive to the megakaryo-
cyte lineage (Wilkinson et al., 2007). The lineage-selective
induction of polyploidization appears, however, to result from
inhibition of AURKA, a major target of diMF mode of action in
We also performed in silico docking studies to compare the
binding of diMF and MLN8237 to Rho kinase I (ROCK1), a known
target of diMF, and to AURKA. Using the LigPrep, Macromodel,
and Glide-XP (Extra Precision) modules incorporated in the
Schrodinger software package, we found that both MLN8237
anddiMFarepredicted toformastronghydrogen-bond network
with the hinge residues of the ATP-binding site of AURKA (Fig-
ure 5I). In contrast, diMF, but not MLN8237, appears to bind to
the active site of ROCK1. This failure of MLN8237 to dock with
ROCK1 further supports that AURKA is a common target for
both diMF and MLN8237.
To further confirm that loss of function of AURKA promotes
polyploidization of megakaryocytes, we assayed the effect of
Aurka deletion on megakaryocytes. Bone marrow cells from
Aurka conditional knockout mice (Aurkaflox/flox) were infected
with a retrovirus harboring Cre recombinase (MIGR1-Cre-
IRES-GFP) and then cultured for 72 hr in the presence of
THPO to foster megakaryocyte development. As predicted,
depletion of AURKA by expression of Cre (GFP+fraction) led to
a marked increase in the degree of polyploidization of CD41+
megakaryocytes (Figure 5J), reminiscent of the phenotypes
induced by MLN8237 and diMF in primary mouse bone marrow
cells (Figures S2A and S5G). No appreciable depletion of Aurkb
mRNA was detected in GFP+cells (data not shown). Further-
more, expression of Cre in wild-type bone marrow cells does
not alter polyploidization of megakaryocytes (Wen et al., 2009,
MLN8237 Shows Potent Antileukemia Activity In Vitro
and In Vivo
Given that MLN8237 and AZD1152-HQPA, acting by distinct
mechanisms, affected the in vitro growth of CMK and 6133/
MPL cells in a manner similar to that of diMF, we investigated
the extent to which these AURK-specific compounds could be
used as antimegakaryocytic leukemia agents. As seen with
diMF (Figures 3C and 3D), 24 hr pretreatment of 6133/MPL cells
with MLN8237 significantly reduced their ability to induce
leukemia in recipient mice, with 80% of the animals surviving
up to 120 days (Figure 6A). In contrast, 24 hr pretreatment with
AZD1152-HQPA failed to significantly interfere with leukemia
development in vivo (Figure 6A). Pharmacokinetic studies, per-
formed in C57Bl/6 mice following a single oral administration of
15 mg/kg MLN8237, revealed excellent bioavailability (Fig-
ure 6B). Rapid absorption was observed reaching the peak
sample was determined by western blot. Treatment of cells with 1 mM AZD1152-HQPA also led to complete loss of phospho-AURKA and -AURKB (data not
(H) MLN8237 and diMF inhibit AURKA. Purified AURKA was incubated with MLN8237 or diMF, and the change of AURKA phosphorylation was determined by
spectrophotometry. Data are representative of two experiments conducted in triplicate.
(I) Docking studies were performed to evaluate the binding of MLN8237 and diMF to AURKA using Schrodinger software. Both MLN8237 and diMF showed
a strong hydrogen-bond network with the hinge residues of AURKA.
(J) Excision of Aurka leads to enhanced polyploidization of megakaryocytes. Bone marrow cells from Aurkaflox/floxmice were transduced with MIGR1-Cre-IRES-
GFP, and the cells were cultured in the presence of THPO for 72 hr. (Left) The DNA contents of CD41+cells from GFP+(Cre-expressing) or GFP?(without Cre
expression) populations of the same culture are shown. (Right) The levels of Aurka mRNA in sorted GFP-positive or GFP-negative cells were assayed by qRT-
PCR. Bar graph depicts means ± SD. Data are representative of two experiments.
See also Figure S5.
Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc. 583
concentration at 0.5 hr (Tmax) with a maximum concentration
of 34.8 mM (Cmax). Mean plasma concentrations remained above
0.5 mM for at least 12 hr with a moderate elimination (terminal
half-life of 3.1 hr). These results indicate that MLN8237 is
easily absorbed orally, has very high exposure in circulation,
and demonstrates moderate metabolism in vivo. Moreover,
MLN8237 is well tolerated in mice (Maris et al., 2010). Healthy
animals fed 15 mg/kg MLN8237 twice a day for 2 weeks with
a dosing regimen of 5 days on, 2 days off showed no changes
in body weight or peripheral blood counts (Figure S6).
We treated 6133/MPL-transplanted mice with 15 mg/kg
MLN8237 for 2 weeks and compared leukemia burden with
animals treated with vehicle alone. MLN8237 significantly
reduced peripheral white blood cell count and spleen and liver
weights of transplanted animals (Figures 6C–6E). There was
also a striking reduction of infiltration of leukemic cells (Figures
6F and 6G). Similar to diMF, MLN8237 induced polyploidization
of the malignant cells in vivo (Figure 6H). MLN8237 also induced
both polyploidization and proliferative arrest of human non-DS-
AMKL cells cultured ex vivo (Figures 6I and 6J). Taken together,
MLN8237, like diMF, displayed potent antimegakaryocytic
leukemia activity both in vitro and in vivo.
Network Analysis Reveals Five Networks that Control
Next, we sought to use our proteomic, biochemical, and func-
tional data to infer the broader network of interacting proteins
that lead to megakaryocyte polyploidy and differentiation. We
Figure 6. MLN8237 Shows Antileukemic Activity In Vitro and In Vivo
(A) Pretreatment with MLN8237, but not AZD1152-HQPA, impaired the ability of 6133/MPL cells to induce leukemia. 6133/MPL cells were incubated with 1 mM
MLN8237 or 3 mM AZD1152-HQPA. One million live cells were transplanted to mice, and survival of the mice was monitored. n = 6 (DMSO), n = 5 (MLN8237), and
n = 4 (AZD1152-HQPA). MLN versus DMSO, p = 0.0067; AZD versus DMSO, p = 0.26.
(B) Measurement of drug concentration in plasma after a single dose of MLN8237. C57Bl/6 mice were dosed orally with 15 mg/kg of MLN8237, and plasma
concentrations of the drug were assessed at different time points post-treatment; n = 3 animals per time point.
(C–G) MLN8237 reduced tumor load of 6133/MPL cell-transplanted mice. Forty-eight hours after transplantation of 6133/MPL cells, mice were fed arginine
(solvent for MLN8237) or MLN8237 at 10 and 15 mg/kg by oral gavage twice a day for 10 days. MLN8237 reduced white cell count in the peripheral blood (C) and
decreasedspleenand liverweightoftransplantedmice(DandE).H&Estaining oftissuesectionsindicated thatMLN8237 reducedinfiltrationofmegakaryoblasts
in the liver (F) and lung (G) in transplanted mice.
(H) MLN8237 induced polyploidization of 6133/MPL cells in vivo. Forty-eight hours after transplantation of 6133/MPL cells, mice were given arginine or 15 mg/kg
MLN8237 by oral gavage twice a day for 3 days, and the DNA content of the transplanted cells in bone marrow was evaluated by flow cytometry. Left, repre-
sentative flow plots. Right, bar graph of mean ± SD; **p < 0.01. n = 4 animals per group.
(I and J) MLN8237 induced polyploidization and inhibited proliferation of human non DS-AMKL blasts. Human CD41+non-DS-AMKL blasts isolated from primary
NSG recipients were treated with DMSO or 0.1 mM MLN8237 for 6 days. Results are representative of two independent experiments in duplicate. Error bars
represent mean ± SD; *p < 0.05, **p < 0.01.
See also Figure S6.
584 Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc.
performed a network analysis using the protein-protein interac-
tion database Reactome (Vastrik et al., 2007). Reactome anal-
ysis integrating the data from the three approaches yielded
117 proteins that were mapped to five networks with 116 nodes
and 194 connections in the Reactome database (Figure 7A). As
expected, genes that control cytokinesis, including ROCK1,
ROCK2, AURKB, and polo-like kinases, were present. Known
negative regulators of megakaryopoiesis, the SRC kinase LYN
and PTK2 (focal adhesion kinase, FAK) (Hitchcock et al., 2008;
Lannutti et al., 2006), were also evident, along with known medi-
ators of thrombopoietin signaling, the JAK kinases. Unexpected
factors, whose functions in megakaryocytes and polyploidiza-
tion have not been described, included several members of the
MAP kinase pathway, the CAM kinase family, and AURKA.
We confirmed the polyploidy-inducing effects of inhibition or
knockdown of a subset of kinases. First, small-molecule inhibi-
tors of JAK3, PLK1, CDK1, and CDK2 induced polyploidization
of CMK cells (Figure 7B). Second, knockdown of AURKB was
observed to cause a robust increase in the extent of polyploid-
ization of megakaryocytes (Figure 7C). Third, although knock-
down of RPS6KA4 or MYLK2 did not induce polyploidy on its
own, reduced expression of these kinases sensitized CMK cells
to diMF treatment (Figure 7D). Finally, analysis of the ploidy state
of megakaryocytes derived from Rock1 null mice and their wild-
type littermates demonstrated that loss of Rock1 leads to
increased polyploidization in vivo (Figure 7E). Together, these
data reveal that the protein network constructed based on our
proteomic and genomic studies can serve as road map for
further studies of function of genes in megakaryocyte polyploid-
In general, cell-based, phenotypic approaches for initial
discovery of novel probes provide a rich data set, but efforts to
determine how these leads might be exploited for therapy are
often complicated by uncertainty regarding the cellular target.
This problem is clearly evident in the case of diMF, which is
a broad kinase inhibitor. Each of the individual approaches
used in this study to target identification identified a large
number of possible targets that might not have warranted
follow-up given only one line of evidence. We show that the
ability to integrate approaches and organize the disparate data
types in a disciplined and rigorous manner led to testable
hypotheses and not only identified the physiologically relevant
target of diMF but also a potential therapeutic target for AMKL.
Moreover, network analysis of these data suggests a compre-
hensive analysis of kinases that control the endomitotic process.
Small molecules that induce megakaryocyte polyploidization,
such as diMF, appear to be promising therapeutic agents for
AMKL for multiple reasons. First, because diMF targets poly-
ploidization, a normal element of megakaryocyte differentiation
and maturation, we predict that it would be active against all
we show that diMF inhibits proliferation and induces polyploid-
ization and upregulation of megakaryocyte markers of cells
with GATA1, and MPL mutations as well as cells harboring +21
orthe (1;22) translocation. However, diMFdidnotinduce platelet
production of GATA1, mutant cells. This finding suggests that
diMF cannot overcome all of the requirements for key develop-
mentalregulators interminal differentiation. Asecond advantage
to the use of these compounds in AMKL is illustrated by the
ability of diMF and MLN8237 to block the growth of cells that
express the MPLW515L-activating allele associated with human
myeloproliferative disorders. Thus, we predict that polyploidiza-
tion therapy may also be useful for disorders, such as essential
thrombocytosis (ET) and primary myelofibrosis (PMF), that
involve hyperproliferation of megakaryocytes. The third benefit
lies in the propensity of megakaryocytes to become polyploid.
diMF and MLN8237 induced robust polyploidization of the
CD41+but not CD41?cells, reflecting the inherent susceptibility
of megakaryocytes to polyploidization-inducing agents.
A recent study has demonstrated that ROCK1 is required for
the survival and proliferation of leukemia blasts that harbor acti-
vated oncogenic forms of KIT, FLT3, and BCR-ABL (Mali et al.,
2011). Knockdown of ROCK1, or inhibition with diMF or fasudil,
restricted the growth of these leukemia cells both in vivo and
in vitro. It is interesting to note that diMF thus shows activity
against multiple forms of AML through distinct targets: ROCK1
in nonmegakaryocytic AML blasts that bear activated KIT,
FLT3, or BCR-ABL, and AURKA in megakaryocytic AML. The
lack of activity of fasudil in AMKL provides further evidence
that diMF inhibits different kinase pathways in the two subtypes.
Of note, the small-molecule inhibitor MLN8237 is under clinical
investigation for a variety of tumors, including acute myeloid
leukemia. Despite the notion that Aurora kinase inhibitors should
be broadly considered for treatment of AML, however, our
studies suggest that MLN8237 (Alisertib) would be especially
effective against the megakaryocytic leukemia subtype. Given
the urgent unmet medical need, clinical studies with inducers
of megakaryocyte polyploidization, such as MLN8237, should
JAK3 inhibitor VI, latrunculin B, K252a, PLK1 inhibitor, CDK1 inhibitor, CDK2
inhibitor, and SU6656 were purchased from EMD Chemicals (Gibbstown,
NJ, USA). diMF, MLN8237, AZD1152, and AZD1152-HQPA (Mortlock et al.,
2007) were prepared according to literature methods, and characterization
reports. Small-molecule screening was performed with a chemically diverse
small-molecule library, including known bioactive molecules, HDAC inhibitors,
and natural products.
1H NMR (and optical rotation for diMF) was consistent with literature
High-Content Chemical Screening
Fourthousand CMKcells per wellwereseededintoblack384-wellplates. Fifty
nanoliters of each compound was pin-transferred in duplicate into each well.
After 72 hr, cells were fixed and stained with 1 mg/ml Hoechst 33342. The cells
were imaged with a 203 objective at nine sites within each well using Image-
Express Micro. CellProfiler was employed to identify isolated nuclei and
measure the integrated intensity of the DNA stain within each nucleus
(Carpenter et al., 2006). The numerical data were analyzed using R Project
to identify DNA content and to make histograms for each treatment. A
compound was scored as a hit if the fraction of nuclear DNA content greater
than the cutoff for the compound was significantly greater than that induced
by DMSO. Confirmatory assays were conducted using eight concentrations
(0.16, 0.31, 0.63, 1.25, 2.5, 5, 10, and 20 mM) for each hit compound under
the same imaging and data-analysis conditions.
Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc. 585
586 Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc.
For drug treatment of nontransplanted mice, vehicle or test compound was
given to mice by oral gavage twice a day for 7 or 14 days. Mice were sacrificed
on day 14 after initiation of treatment. For the drug pretreatment experiment,
6133/MPL cells were treated with vehicle or compound for 24 hr. Mice were
sublethally irradiated at 600 cGy, and 106live 6133/MPL cells were injected
into the tail vein of each mouse. For drug treatment after transplantation,
1 million 6133/MPL cells were transplanted into sublethally irradiated mice.
Forty-eight hours later, vehicle or compound was fed to mice by oral gavage
twice aday.For drug treatment of mice transplantedwith human AMKL blasts,
bone marrow cells from a non-DS-AMKL patient were injected into sublethally
irradiated primary NSG recipients at 300 cGy. Twelve weeks later, bone
marrow cells were collected from primary NSG recipients and injected into
sublethally irradiated secondary recipients. Five weeks after transplantation,
the treatment was performed with vehicle, 30, or 60 mg/kg of diMF by oral
gavage twice a day for 10 days and analyzed at the end of the treatment.
Rock1 null mice have been previously described (Vemula et al., 2010).
AURKA conditional knockout (Aurkaflox/flox) mice were generously provided
by Dr. Terry Van Dyke of the University of North Carolina at Chapel Hill (Cowley
et al., 2009).
Affinity Enrichment with SILAC-Mediated Quantitative Proteomics
Stable isotope-labeled amino acid in cell culture (SILAC)-labeled cells were
used in affinity enrichment experiments using K252a-loaded affinity matrices
and diMF as soluble competitor at 10- and 50-fold excess over K252a on
bead. Proteins bound to the solid matrices were separated by SDS-PAGE
and identified and quantified by high-performance mass spectrometry
(MS). SILAC ratios from relative abundances of proteins enriched in the pres-
ence or absence of soluble competitor pull-down experiments were modeled
with an empirical Bayes-based statistical framework to identify specific
protein targets interacting with small molecules. Detailed methods for the
experimental procedures are provided in the Extended Experimental
For the RNAi screen, 1,000 CMK cells per well were seeded in 384-well plate
for 2 days to allow knockdown. Vehicle control or 1 mM diMF was added to
each well and incubated for 48 hr, after which cells were fixed and stained.
The images were acquired and analyzed as in the small-molecule screen.
Following Cell Profiler analysis of DNA content per cell, custom R scripts
were designed to determine the relationship between Hoescht staining and
DNA content. An shRNA was scored as a hit if the DNA was significantly
greater than that induced by vector DNA in presence of DMSO or 1 mM
diMF. A comparison was also made between these two conditions. To reduce
the off-target effects of shRNA, a gene was called a hit only when two or more
shRNAs of the gene scored as positive. The top 5% of genes in any one of
three categories of comparison were considered to be hits.
Protein Network Analysis with Reactome
Toassist withtheinterpretation of hits, we turnedto network analysis usingthe
protein-protein interaction database Reactome (Vastrik et al., 2007). The deci-
sion of which proteins to include was made for each component (SILAC, RNAi,
KinomeScan) separately. Proteins detected by SILAC were analyzed using an
empirical Bayesian method (Margolin et al., 2009), and we included those with
false discovery rates below 0.05. For RNAi, we included genes with p values
below 0.05 in any of the three modes (shRNA alone, shRNA with minimally
effective dose of diMF, and difference between the two). For kinases profiled
by Ambit KinomeScan, we included those that had % activations reduced by
diMF below 35%. We used random graphs with given expected degrees
(Pradines et al., 2005) to assess the statistical significance and obtained
a p value of 7.1 3 10?64.
For quantitative assays, treatment groups were reported as mean ± standard
deviation (SD) and compared using the unpaired Student’s t test. When
multiple comparisons were necessary, one-way or two-way analysis of vari-
ance with post-test Bonferroni correction was used. Statistical significance
was established at p less than or equal to 0.05, labeled as *, p < 0.05 and **,
p < 0.01. Mouse survival data were evaluated by log-rank analysis, adjusted
by multiple comparison test when necessary. The analysis was performed
using GraphPad Prism Version 4.01 for Windows (GraphPad Software).
figures, and fivetables andcan befoundwiththisarticleonline athttp://dx.doi.
The authors thank Sandeep Gurbuxani, Alex Minella, and Lou Dore ´ for critical
reading of the manuscript and Bang Wong for valuable advice on figures of the
manuscript. This research was funded by grants from the Samuel Waxman
Foundation (to S.I. and J.D.C.), the Leukemia and Lymphoma Society Trans-
lational Research Program (J.D.C.), the Children with Leukaemia UK (S.I.),
the Israel Science Foundation (S.I.), European Hematology Association
(Y.B.), and the Leukemia Research Foundation (Y.B.) and by NIH grants
CA101774 (J.D.C.), HL077177 (R.K.), HL075816 (R.K.), and HL081111 (R.K.).
Other support included an NIH grant to A.E.C. supporting CellProfiler
HG005032), NIH Genomics Based Drug DiscoveryU54grants DiscoveryPipe-
line RL1-CA133834, and Driving Medical Projects RL1-GM084437, adminis-
tratively linked to NIH grants RL1-HG004671 and UL1-DE019585 (A.E.C.,
P.A.C., V.D., C.B.M., A.M.S., C.A.S., and M.S.). Y.B. is a European Hema-
ported by Foundation Gustave Roussy and Jose ´ Carreras Leukemia Founda-
tion- European Hematology Association (T.M.), CEA-EA, Ligue Nationale
Figure 7. Pathways that Regulate Polyploidization of Megakaryocytes
(A) Reactome analysis integrating the data from the KinomeScan, SILAC, and RNAi screen yielded 117 proteins that were mapped to 116 nodes and 194
connections. In the protein network, shapes of nodes correspond to the source: squares for SILAC, circles for RNAi, rounded squares for both SILAC and RNAi,
and triangles for Kinome scan only. Colors of the nodes correspond to false discovery rates of SILAC ratio in the range 0.05 (red) ? 1.0 (blue) or gray for proteins
not detected by SILAC. Colors of connections correspond to the type of interaction: direct complex (orange), indirect complex (yellow), reaction (blue), or
neighboring reaction (cyan). Kinases that were validated in separate experiments are circled.
(B–E) Validation of kinases in the network. (B) Induction of CMK polyploidization after 72 hr of treatment with JAK3 inhibitor VI (1 mM), PLK1 inhibitor (1 mM), CDK1
inhibitor (3 mM), and CDK2 inhibitor (3 mM) is shown. (C) Knockdown of Aurkb induced polyploidization of megakaryocytes. 6133/MPL cells were transduced with
PLKO1 control vector or shRNA against Aurkb. (D) Knockdown of RPS6KA4 or MYLK2 sensitized CMK cells to diMF treatment. CMK cells transduced with
luciferase control viruses or shRNAs against RPS6KA4 or MYLK2 were cultured with DMSO or diMF (3 mM) for 72 hr. The extent of gene knockdown as assessed
by qRT-PCR is shown. Results are representative of two independent experiments performed in duplicate. (E) Left, megakaryocytes (CD41+) derived from the
bone marrow of Rock1 null mice showed increased degree of polyploidization relative to megakaryocytes from their wild-type littermates. Middle, bar graphs
depict the percentages of cells with DNA contents R 8N. Error bars represent mean ± SD; *p < 0.05; n = 5 mice per group. Right, expression of ROCK1 was
assessed by western blot in extracts from murine bone marrow mononuclear cells.
Cell 150, 575–589, August 3, 2012 ª2012 Elsevier Inc. 587
Contre le Cancer (F.P.), Association Laurette Fugain (F.P.), Socie ´te ´ Franc ¸aise
d’He ´matologie(B.G.,F.P.),and Foundationpourla RechercheMe ´dicale (C.T.).
The authors would also like to thank Jason Berman, Soheil Meshinchi, Todd
Alonzo, and Sommer Castro and the Children’s Oncology Group (COG) for
their assistance with DS-AMKL specimens. Research with DS-AMKL samples
was supported by the Chair’s Grant U10 CA98543 (to COG) from the National
Cancer Institute (NCI). The project has also been funded in part with Federal
funds from the NCI’s Initiative for Chemical Genetics under Contract N01-
CO-12400. The content of this publication is solely the responsibility of the
authors and does not necessarily reflect the views or policies of the Depart-
ment of Health and Human Services, nor does mention of trade names,
commercial products, or organizations imply endorsement by the U.S.
ChemCore at the Center for Molecular Innovation and Drug Discovery
(CMIDD),which is funded by theChicago BiomedicalConsortium with support
from The Searle Funds at The Chicago Community Trust. D.G.G. is an
employee and shareholder of Merck and Co., Inc. R.J.G. is an employee,
shareholder, and board member of Epizyme, Inc. and a member of the SAB
of the Michael J. Fox Foundation.
Received: November 16, 2011
Revised: February 3, 2012
Accepted: June 4, 2012
Published: August 2, 2012
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