The antimalarial drug amodiaquine stabilizes p53 through ribosome biogenesis stress, independently of its autophagy-inhibitory activity

Article abstract of DOI:10.1038/s41418-019-0387-5

Pharmacological inhibition of ribosome biogenesis is a promising avenue for cancer therapy. Herein, we report a novel activity of the FDA-approved antimalarial drug amodiaquine which inhibits rRNA transcription, a rate-limiting step for ribosome biogenesi

Full text of DOI:10.1038/s41418-019-0387-5

Cell Death & Differentiation
https://doi.org/10.1038/s41418-019-0387-5
ARTICLE
The antimalarial drug amodiaquine stabilizes p53 through ribosome
biogenesis stress, independently of its autophagy-inhibitory activity
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Jordi Carreras-Puigvert1 Martin Henriksson2
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Jaime A. Espinoza
Asimina Zisi
Dimitris C. Kanellis
Daniela Hühn1 Kenji Watanabe3 Thomas Helleday2,4 Mikael S. Lindström
Jiri Bartek1,3
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Received: 14 December 2018 / Revised: 9 June 2019 / Accepted: 21 June 2019
© The Author(s) 2019. This article is published with open access
Abstract
Pharmacological inhibition of ribosome biogenesis is a promising avenue for cancer therapy. Herein, we report a novel
activity of the FDA-approved antimalarial drug amodiaquine which inhibits rRNA transcription, a rate-limiting step for
ribosome biogenesis, in a dose-dependent manner. Amodiaquine triggers degradation of the catalytic subunit of RNA
polymerase I (Pol I), with ensuing RPL5/RPL11-dependent stabilization of p53. Pol I shutdown occurs in the absence of
DNA damage and without the subsequent ATM-dependent inhibition of rRNA transcription. RNAseq analysis revealed
mechanistic similarities of amodiaquine with BMH-21, the first-in-class Pol I inhibitor, and with chloroquine, the
antimalarial analog of amodiaquine, with well-established autophagy-inhibitory activity. Interestingly, autophagy inhibition
caused by amodiaquine is not involved in the inhibition of rRNA transcription, suggesting two independent anticancer
mechanisms. In vitro, amodiaquine is more efficient than chloroquine in restraining the proliferation of human cell lines
derived from colorectal carcinomas, a cancer type with predicted susceptibility to ribosome biogenesis stress. Taken
together, our data reveal an unsuspected activity of a drug approved and used in the clinics for over 30 years, and provide
rationale for repurposing amodiaquine in cancer therapy.
Introduction
Ribosome biogenesis has emerged in recent years as a
potent therapeutic target against cancer. Fast-dividing
malignant cells require enhanced ribosome production to
meet the increased needs for protein synthesis to sustain the
elevated metabolism and proliferation [1]. High rate of
ribosome biogenesis is strongly associated with poor
prognosis across many cancer types [2, 3], and it is com-
monly regulated by oncogenic signaling pathways including
c-MYC [4], RAS-RAF-ERK [5], and PI3K–mTOR [6].
Transcription of ribosomal RNA (rRNA) is carried out
exclusively by the RNA polymerase I (Pol I) inside the
nucleolus. This process requires the presence of the upstream
binding factor UBF on the active ribosomal DNA (rDNA)
genes, enabling the recruitment of the pre-initiation complex
(PIC) and Pol I components to the rDNA gene promoter.
Each rDNA gene codes for the 47S rRNA precursor, which
is further processed to form the 18S, 5.8S and 28S mature
rRNAs. In parallel, RNA polymerase III transcribes the 5S
rRNA in the nucleoplasm, while RNA polymerase II tran-
scribes the mRNAs of the ribosomal proteins (RPs). Mature
5S rRNA and RPs are imported to the nucleolus and
Edited by D.R. Green
Supplementary information The online version of this article (https://
doi.org/10.1038/s41418-019-0387-5) contains supplementary
material, which is available to authorized users.
* Mikael S. Lindström
mikael.lindstrom@ki.se
* Jiri Bartek
jb@cancer.dk
1
Science for Life Laboratory, Division of Genome Biology,
Department of Medical Biochemistry and Biophysics, Karolinska
Institutet, S-171 21 Stockholm, Sweden
2
Science for Life Laboratory, Department of Oncology-Pathology,
Karolinska Institutet, S-171 76 Stockholm, Sweden
3
Danish Cancer Society Research Center, DK-2100
Copenhagen, Denmark
4
Weston Park Cancer Centre, Department of Oncology and
Metabolism, University of Sheffield, Sheffield S10 2RX, UK

J. A. Espinoza et al.
preassembled together with the 18S, 5.8S, and 28S RNAs to
form the 60S and 40S ribosomal subunits. Subsequently,
mature ribosomes are formed in the cytoplasm through a
series of export and maturation processes [7].
per week, as soon as the monolayer became preconfluent or
early confluent. Tests for mycoplasma detection were per-
formed monthly. To generate the RKO ATM-knockout cells
the following gRNA sequences (2.1) 5′-CACCGTGATA
GAGCTACAGAACGAA-3′ and (6.3) 5′-CACCGAAA
CAATTAAACATCTAGAT-3′ were cloned into PX458
vector (Addgene #48138) and verified by sequencing. Three
days after plasmid transfection, GFP-positive cells were
sorted and knockout/absence of ATM was confirmed by
immunoblots analysis of single clones.
Beside the deleterious effects of actinomycin D on rRNA
synthesis [8], new ribosome biogenesis inhibitors have
emerged. CX-5461 was described originally as an inhibitor of
Pol I leading to activation of p53 due to ribosome biogenesis
stress [4], however, new evidence has shown that it also sta-
bilizes DNA G-quadruplexes, induces DNA damage, inter-
feres with DNA replication [9] and activates ATM/ATR
signaling [10]. Strikingly, the recently introduced compound
BMH-21 stands out as a drug that triggers proteasomal
degradation of the catalytic subunit of Pol I, RPA194
(POLR1A), and thereby activates p53 in the absence of DNA
damage [11, 12]. Interestingly, the antineoplastic drug oxali-
platin, included in the clinical FOLFOX regimen and first-line
treatment of colorectal cancer (CRC), exerts its chemother-
apeutic effect predominantly through ribosome biogenesis
stress rather than through DNA crosslinking, as its analog
cisplatin [13]. These findings strongly support the rationale for
developing new ribosome biogenesis inhibitors against CRC.
The repurposing of FDA-approved compounds is
increasingly becoming an attractive strategy to identify new
oncological applications. This approach harnesses advan-
tages of “old” drugs: clinical safety, shorter times for drug
development, and reduced investment at early stages [14].
Recently, we have provided an example of drug repurpos-
ing in oncology by providing epidemiological support,
identifying the molecular target, mechanism of action and
the active anticancer metabolite of the old and safe alcohol-
abuse drug disulfiram [15].
Immunoblotting
Subconfluent cells were directly lysed in RIPA buffer
(Thermo, PI-89901) plus protease (cOmplete ULTRA, code
05892970001, Roche) and phosphatase inhibitors (Phos-
STOP, code 04906837001 Roche) and sonicated during 3–5
cycles of 30 s on and 30 s off, in a Bioruptor® (Diogenode).
Protein quantification was performed with the DC™ Protein
Assay Kit II (Bio-Rad, 5000112). Five to 20 μg was boiled
in Laemmli sample buffer during 5 min at 95 °C, loaded
onto SDS-PAGE gels and transferred to nitrocellulose or
PVDF membranes. Chemiluminiscence signal was detected
using SuperSignal™ West Dura (Thermo, 34076). Images
were acquired with an Amersham Imager 600 scanner.
Antibodies and their applications are listed in Supplemen-
tary Table S2.
Quantitative immunoblot was performed with Wes™
following manufacturer instructions (Protein Simple).
Briefly, cells were lysed with RIPA, sonicated and ana-
lyzed. RPA194 levels were quantitated and normalized
using β-actin as internal control.
The antimalarial drug amodiaquine (AQ) induces similar
gene expression perturbation to that induced by the BMH
family of ribosome biogenesis inhibitors, suggesting similar
mechanisms of action [16]. AQ and its analog chloroquine
(CQ) are members of the 4-aminoquinolines family of
antimalarial drugs. Although AQ and CQ are similarly potent
as autophagy inhibitors [17, 18], only AQ triggers
p53 stabilization [18, 19] and displays higher cytotoxicity
than CQ at equimolar concentrations [18]. However, the
mechanisms underlying these differences remain unknown.
Here we report the characterization of the FDA-approved
drug AQ as a ribosome biogenesis inhibitor and promising
anticancer compound.
Chemicals
Chemicals used in this study are listed in the Supplementary
Table S3. Compounds were dissolved in dimethyl sulfoxide
(DMSO) or water according to the vendor’s instructions.
Stock dilutions were aliquoted and stored at −20 °C.
Resazurin stock solution was prepared by dissolving resa-
zurin sodium salt powder in sterile DPBS, in a final con-
centration of 1 mg/mL. Resazurin working solution was
prepared fresh right before use by diluting the stock solution
in cell medium, to a final concentration of 20 μg/mL. Silver
nitrate solution was also prepared fresh before use by dis-
solving the powder in miliQ water to a final dilution of
0.5 g/mL.
Material and methods
Immunofluorescence and imaging
Cell culture
Cells grown in 96-wells imaging plates were fixed in 4%
formaldehyde for 15 min at room temperature, washed with
PBS, permeabilized in PBS 0.5% Triton X-100 during
Cell lines and culture conditions are described in Supple-
mentary Table S1. Briefly, cells were reseeded 2–3 times

The antimalarial drug amodiaquine stabilizes p53 through ribosome biogenesis stress, independently of. . .
10 min and blocked with PBS 3% bovine serum albumin
during 30 min. Cells were sequentially incubated with the
primary (over night) and secondary antibody (120 min),
stained with Hoechst 2 μM during 15 min. Images were
acquired using an IN Cell Analyzer 2200 (GE Healthcare).
Image segmentation and foci/vesicles quantification was
performed using Cell Profiler software [20].
RPL5, siRNA 5′-AAGGUUGGCCUGACAAAUUAUUU-3′
sequence was used. ON-TARGETplus non-targeting pool
(D-001810-10-20) and SMARTpool: ON-TARGETplus
RPL11 siRNA (L-013703-00) were purchased from Dhar-
macon. Flexitube siRNAs Hs_TP53_8 and Hs_TP53_9
were purchased from Qiagen.
Viability assay and GI50
AgNOR staining
Cell lines were seeded at 500 cells/well or 1000 cells/well
(for BJ cells) in 384-well plates (#3764, Corning®, Sigma
Aldrich) 24 h prior to treatment, in a total volume of 35 μL,
by using a MultiFlo FX Multi-Mode Dispenser (BioTek, AH
Diagnostics Sweden, SE-169 70). Plates were incubated at
room temperature for 20 min to minimize the edge effect
before placing them in a 37 °C incubator. Master plates (384
V-bottom polypropylene plates, #781280, Greiner) contain-
ing the single compounds and/or their combinations were
manually prepared at an 8× dilution in media, according to
the experimental layout. For the dose response curves
experiments twofold serially diluted concentrations of the
single compounds were used. Five microliters of compound
was transferred from the master plate to the cells to a final
volume of 40 μL using VIAFLO 384 (Integra Biosciences,
INTEGRA Biosciences AG, CH-7205, Switzerland). The
inhibitory effect of the single agents and/or their combina-
tions was determined by the resazurin assay. After 96 h
incubation with compounds, the compound-containing
medium was aspirated using a HydroSpeed microplate
washer (Tecan) leaving a residual volume of 20 µL/well, and
20 µL of resazurin working solution was added using Mul-
tiFlo FX, to a final concentration of 10 µg/mL and a final
volume of 40 µL. The plates were further incubated for 2 h
and the emitted fluorescence was measured with a microplate
reader using the 560 nm excitation/590 nm emission filter set
(Tecan Infinite M1000 Pro, Männedorf, Switzerland). The
assay was performed with three technical and three biologi-
cal recplicates including vehicle controls (DMSO-treated
cells), negative no-cell controls, and background subtraction
controls (media and compound without cells) to ensure that
the tested compounds are not autofluorescent at the applied
wavelength. Results were statistically analyzed and normal-
ized as % viability compared with the vehicle control, after
background subtraction using GraphPad Prism 7.0 (Graph
Pad Software Inc., San Diego, CA). Single-agent dose-effect
curves were plotted, by applying three-parametric nonlinear
regression. GI50 values were automatically calculated by the
software.
Cells were seeded in 8-well Chambered Cell Culture Slides
(Falcon) at a density of 104 cells/well. A vehicle well was
included, containing cells treated with DMSO if required.
The cells were fixed with 2% glutaraldehyde in PBS for
10 min at room temperature, following two sequential
washing steps with PBS and dH2O, respectively. Next, cells
were incubated with a second fixing solution (methanol:
acetic acid 3:1) for 5 min and washed thoroughly with
dH2O. Further, 200 μL of silver nitrate colloidal solution
(a 0.5 g/mL silver nitrate aqueous solution was diluted in
2% gelatin and 1% formic acid, in a proportion of 2:1) was
added to each well and incubated in the dark for 20 min, at
room temperature. Then, the slides were washed vigorously
with dH2O and coverslips were mounted using Prolong
Gold (Invitrogen, P36930). AgNOR stained foci appeared
as black brown dots within the nucleus were evaluated
under a light microscope at (×20 and ×40) magnification
(Olympus BX53). The photos were taken with a digital
color camera (Olympus DP73).
Fluorescent intercalator displacement (FID) assay
The FID assay was conducted as previously described
elsewhere [21]. Deoxyoligonucleotide oligo hairpins con-
taining an 8-bp stem region with random DNA sequences
with increasing GC content (Supplementary table S6) were
purchased from Sigma-Aldrich. Ethidium bromide (EtBr; 6
μM) was added to each well in sodium acetate buffer (35
mM NaOAc, 162.8 mM NaCl, 1.75 mM EDTA, pH 5.0),
followed by hairpin DNA (1.5 μM), and 2 μM of each
compound tested, diluted in sodium acetate buffer con-
taining 2% DMSO. For each experiment, the ratio of EtBr
to hairpin DNA was adjusted to 1 M equivalent EtBr per 2
DNA base pairs. The 0% control wells contained neither
hairpin DNA nor test compounds, while the 100% control
wells contained hairpin DNA and EtBr but no test com-
pounds. All assays were conducted in triplicate.
siRNA knockdown
Transmission electron microscopy (TEM)
Cells were transfected with 20 nM siRNA using Lipofecta-
mine™ RNAiMAX during 6 h in Opti-MEM (Gibco,
31985070) and 18 additional hours in regular DMEM. For
TEM was performed in EMil core facility at Karolinska
Institutet. Cells were fixed in 2.5% glutaraldehyde in 0.1 M

J. A. Espinoza et al.
phosphate buffer, pH 7.4 at room temperature for 30 min.
The cells were scraped and transferred to Eppendorf tube
and further fixed over night in the refrigerator. After fixation
cells were rinsed in 0.1 M phosphate buffer and centrifuged.
The pellets were then postfixed in 2% osmium tetroxide
(TAAB, Berks, England) in 0.1 M phosphate buffer, pH 7.4
at 4 °C for 2 h, dehydrated in ethanol followed by acetone
and embedded in LX-112 (Ladd, Burlington, Vermont,
USA). Ultrathin sections (~50–60 nm) were cut by a Leica
EM UC 6 (Leica, Wien, Austria). Sections were contrasted
with uranyl acetate followed by lead citrate and examined in
a Hitachi HT 7700 (Tokyo, Japan) at 80 kV. Digital images
were taken by using a Veleta camera (Olympus Soft Ima-
ging Solutions, GmbH, Münster, Germany). Cells were
trypsinized, harvested, and pelleted before fixation with
glutaraldehyde.
with a RIN above nine were included. Library was prepared
with Illumina TruSeq Stranded mRNA using Poly-A
selection. Samples were sequenced on HiSeq2500. RNA-
seq data are available in the ArrayExpress database
(http://www.ebi.ac.uk/arrayexpress) under accession num-
ber E-MTAB-7616. File processing was carried by NGI-
RNAseq bioinformatics pipeline. Briefly, Fastq files where
aligned using STAR (v2.5.1b) in two pass mode against
reference genome (Homo sapiens, GRCh37). Read counting
was performed using StringTie (v1.3.3) to further use pre-
pDE python script. Differential expression analysis was
performed using DESeq2 (v1.16.1). For further compar-
isons across the different treatments, gene list where filtered
using a 0.5 linear fold change. Threshold and 0.001 adjusted
p-value were performed on RStudio (v0.99.489, R 3.4.1).
ClueGO is a cytoscape plug in app that visualizes non-
redundant biological terms for large clusters of gene sets in
a functionally grouped network [23]. In our study, the
enrichment analysis of gene-GO terms and pathways was
perfomed using GO term Biological Process-EBI-
QuickGO-GOA, KEGG pathways, REACTOME pathways
and WikiPathways, date version 20-11-2017. Clusters with
a p-value < 0.001 were included in figure, with the excep-
tion of BMH-21 specific genes, where was applied a Bon-
ferroni correction and p-value < 0.05.
Quantitative real-time reverse transcription PCR
Total RNA was extracted with the PureLink™ RNA Mini
Kit (ThermoFisher) following manufacturer’s instructions,
and qPCR was performed using the Power SYBR® Green
RNA-to-CT™ 1-Step Kit (4389986, ThermoFisher) in a
QuantStudio 5 PCR System. Cycling parameters: Reverse
transcription at 48 °C for 30 min, initial denaturation at
95 °C for 30 s, and 40 cycles of 95 °C for 15 s and 62 °C for
60 s. Melt curve analysis: 95 °C for 15 and a gradual
increase in temperature to 95 °C (0.075 °C/s). Triplicate
treatment samples and three technical replicates per sample
were analyzed. Relative quantity was analyzed with the
ΔΔCt method using ACTB mRNA as internal normalizer.
Primer sequences are listed in Supplementary Table S4.
Primers sequences for 47S rRNA processing were obtained
from [22].
Chemical synthesis
Starting materials and intermediates used in the synthesis of
compounds described herein are commercially available
from Sigma-Aldrich, Enamine, and Combi-Blocks. Flash
column chromatography was performed in a ISCO combi
flash system using Merck silica gel 60 Å (40−63 mm mesh).
1H NMR spectra were recorded on a Bruker DRX-400.
Chemical shifts are expressed in parts per million (ppm) and
referenced to the residual solvent peak. Analytical HPLC-
MS was performed on an Agilent MSD mass spectrometer
connected to an Agilent 1100 system with: Method acidic
pH, Column ACE 3 C8 (50 mm × 3.0 mm), H2O (+0.1%
TFA), and MeCN were used as mobile phases at a flow rate
of 1 mL/min, with a gradient time of 3.0 min. Detection was
made by UV using the 180−305 nM range and MS (ESI+).
Synthesis of 7-chloro-N-{3-[(diethylamino)methyl]phenyl}
quinolin-4-amine (Amodiaquine analog; deshydroxy-amo-
diaquine; DH-AQ): A mixture of 3-[(diethylamino)methyl]
aniline (64 mg, 0.36 mmol), 4,7-dichloroquinoline (71 mg,
0.36 mmol), ethanol (2 mL), and 12 M HCl (30 µL, 0.36
mmol) was heated in the micro wave oven at 150 °C for 30
min. The solvent was removed in a rotavapor. Water (3 mL)
and 5 M NaOH (0.5 mL) were added to the crude material
and the mixture was extracted with dichloromethane (2 mL).
The organic phase was dried over Na2SO4 and the product
was purified by column chromatography on silica (10 g,
Chromatin immunoprecipitation
U2OS cells were fixed with 1% formaldehyde and pro-
cessed using the Pierce Agarose ChIP Kit (26156, Thermo
Scientific) following manufacturer’s instructions. qPCR was
performed using Power SYBR™ Green PCR Master Mix
(ThermoFisher). Primer sequences are listed in Supple-
mentary Table S5 and were obtained from [12]. Analysis of
the qPCR data was performed using the fold enrichment
method, adjusting nonspecific amplification with the
Mock IgG.
RNA sequencing and gene ontology analysis
RNA sequencing was performed by National Genomics
Infrastructure at Science for Life Laboratory Stockholm,
Sweden. RNA quality was assessed by electrophoresis
using a TapeStation Instrument (Agilent). Only samples

The antimalarial drug amodiaquine stabilizes p53 through ribosome biogenesis stress, independently of. . .
0–100% ethylacetate in iso-hexane as eluent) to generate
7-chloro-N-{3-[(diethylamino)methyl]phenyl}quinolin-4-
amine (25 mg, 20%) [M + H] + m/z 340; 1H NMR
(400 MHz, DMSO-d6) ppm 0.98 (t, J = 7.1 Hz, 6H),
2.44–2.50 (m, 4H, partly under solvent peak), 3.54 (s, 2H),
6.91 (d, J = 5.4 Hz, 1H), 7.07–7.11 (m, 1H), 7.20–7.26 (m,
1H), 7.30–7.39 (m, 2H), 7.56 (dd, J = 9.0, 2.4 Hz, 1H), 7.89
(d, J = 2.2 Hz, 1H), 8.40–8.47 (m, 2H), 9.10 (s, 1H).
Synthesis of 7-chloro-N-[3-(pyrrolidin-1-ylmethyl)phenyl]
quinolin-4-amine (Amopyroquine analog: deshydroxy-
amopyroquine; DH-ApQ): A mixture of 3-(pyrrolidin-1-
ylmethyl)aniline (70 mg, 0.40 mmol), 4,7-dichloroquinoline
(79 mg, 0.40 mmol), acetonitrile (1 mL), water (1 mL), and
12 M HCl (33 µL, 0.40 mmol) was heated in a sealed tube at
110 °C for 4 h. The reaction was cooled to r.t., and 5 M
NaOH (160 µL, 0.79 mmol) was added to the stirred solu-
tion. The product was collected by filtration and ½ of this
crude material was purified by column chromatography on
silica (10 g, 0–100% ethylacetate in iso-hexane as eluent)
to generate 7-chloro-N-[3-(pyrrolidin-1-ylmethyl)phenyl]
quinolin-4-amine (25 mg, yield 19%). LCMS [M + H] +
m/z 338; 1H NMR (400 MHz, DMSO-d6) ppm 1.64–1.74
(m, 4H), 2.39–2.48 (m, 4H), 3.59 (s, 2H), 6.92 (d, J = 5.4
Hz, 1H), 7.06–7.11 (m, 1H), 7.22–7.27 (m, 1H), 7.29–7.34
(m, 1H), 7.35 (t, J = 7.4 Hz, 1H), 7.56 (dd, J = 9.0, 2.2 Hz,
1H), 7.89 (d, J = 2.2 Hz, 1H), 8.43 (d, J = 9.0 Hz, 1H), 8.46
(d, J = 5.4 Hz, 1H), 9.09 (s, 1H).
upstream (positions −988 and −410) and the 5′ETS region
(positions 851 and 1297). In contrast, UBF was only
slightly affected (Fig. 1c).
We hypothesized that the mechanism by which AQ alters
ribosome biogenesis may resemble the effects of BMH-21,
an inhibitor of ribosome biogenesis that also triggers a
ubiquitin-proteasome-dependent degradation of RPA194
[25]. Indeed, proteasome inhibition partially rescued the
levels of RPA194 upon treatment with AQ (Fig. 1d). The
protein translation inhibitor cycloheximide caused reduction
in RPA194 levels after 3 h of treatment (Fig. 1e). We
assessed the transcriptional status of genes which products
compose the complex. Both AQ and BMH-21 induced a
significant downregulation of POLR1D, POLR1E, and
TAF1B components of the Pol I PIC. BMH-21 down-
regulated UBFT, TWISTNB, and POLR1A and upregulation
of POLR1B, POLR1C, TAF1C, and TAF1D (Supplemen-
tary Fig. 1).
Under nucleolar stress conditions [26, 27], areas of
rDNA repeats called nucleolar caps are reorganized toward
the nucleolar periphery. These can be induced either by
DNA damage or compounds with affinity for GC rich
regions of DNA such as actinomycin D [28] and BMH-21
[12]. To assess changes in nucleolar structure upon AQ
exposure, we used immunofluorescence for proteins located
in the three nucleolar compartments: RPA194 located at the
fibrillar center and fibrillarin in the dense fibrillary com-
ponent (DFC) both translocate to nucleolar caps, while
nucleolin, mainly located at the granular component,
translocates to the nucleoplasm under stress [29]. An AQ-
dose-dependent dismantling of the nucleolus was observed
as indicated by the reduction of fibrillarin area (Fig. 1f, g),
and decreased RPA194 intensity (Fig. 1f, h) along with the
generation of nucleolar caps (Fig. 1f, white arrows) and
nucleolin translocation into the nucleoplasm (Fig. 1i),
without altering its total level (Fig. 1a). Moreover, AQ also
induced translocation into the nucleoplasm of the nucleolar
helicase DDX21 (Supplementary Fig. 2), an enzyme
involved in the synthesis and processing of rRNA [30].
We then asked whether the nucleolar changes observed
for AQ: (i) can be reproduced by its analog CQ; and (ii) are
comparable with those induced by BMH-21. For this, we
employed electron microscopy in order to detect subtle
changes. AQ induced dramatic condensation of the
nucleolar chromatin along with loss of the distinctive
nucleolar regions FC, DFC, and GC, similarly to BMH-21
(Fig. 1j and Supplementary Fig. 3). In contrast, CQ did not
affect chromatin and the nucleolar subcompartments
remained preserved (Fig. 1j), consistent with AgNOR
staining that detects argyrophilic proteins located at the FC/
DFC regions [31]. AQ and BHM-21, but not CQ, induced a
collapse of the FC/DFC regions toward nucleolar borders
detected as ring-shaped structures (Fig. 1j). These results
Results
AQ inhibits rRNA transcription and induces
degradation of the catalytic subunit of Pol I
While searching for Pol I inhibitors among FDA-approved
drugs, we assessed the impact of AQ on levels of 47S
rRNA, using a set of primers targeting mature 18S, 5.8S and
28S rRNAs and six primers for regions present exclusively
in the 47S precursor rRNA. Precursor-specific regions
showed a dose-dependent decrease in 47S synthesis
(Fig. 1a; red bars), without affecting the levels of mature
ribosomes (Fig. 1a; green bars). Furthermore, we observed a
dose-dependent degradation of the RPA194 subunit of Pol I
and p53 accumulation (Fig. 1b). As expected, AQ also
induced accumulation of autophagosome marker LC3-II
and lysosomal marker LAMP1 (Fig. 1b) [18]. To explore
the transcriptional status of the rDNA, we analyzed the
effect of AQ on UBF and RPA194 association with rDNA
using chromatin immunoprecipitation (ChiP). UBF is
essential for the formation of the PIC and further recruit-
ment of the Pol I complex to the rDNA [24]. After AQ
exposure, RPA194 dissociated from the rDNA (Fig. 1c),
particularly the promoter region (positions −48 and −46),

J. A. Espinoza et al.

The antimalarial drug amodiaquine stabilizes p53 through ribosome biogenesis stress, independently of. . .
Fig. 1 Amodiaquine inhibits ribosome biogenesis. a RT-qPCR ana-
lysis of 47S rRNA precursor demonstrated a reduction of 47S tran-
scription in U2OS cells treated with increasing concentrations of AQ.
Red bars: 47S-specific primers; Green bars: regions shared with
mature rRNAs. Data shown as mean SD of triplicate wells and are
representative of triplicate treatments; Statistical significance was
calculated by one-way ANOVA using log-transformed data and
Dunnett’s multiple test comparison (*p < 0.05, **p < 0.01, ***p <
0.001, ****p < 0.001). b Immunoblot analysis of U2O2 cells treated as
in a shows reduction of RPA194 protein, along with p53 activation
and LC3-II and LAMP1 accumulation in U2OS cells treated with
increasing doses of AQ during 6 h. Nucleolin (NCL) levels show no
change. c Chip-qPCR analyses revealed a reduction of RPA194
binding to rDNA sequence, but UBF binding was less affected. U2OS
cells treated with 20 µM of AQ during 6 h (n = 3). Data shown as
mean SD of triplicate wells and are representative of three inde-
pendent experiments. d Degradation of RPA194 induced by AQ is
proteasome dependent. U2OS cells were treated with proteasome
inhibitor MG-132 during 1 h before addition of AQ and BMH-21
during 6 h. e U2OS cells were incubated with cyclohexamide (CHX)
in the absence and presence of AQ during 6 h. f Immunofluorescence
analysis showed a decrease in RPA194 signal and disruption of
fibrillarin’s localization pattern. U2OS cells treated with 20 µM of AQ
during 6 h. Nuclear DNA was counterstained with DAPI. White
arrows indicate nucleolar caps. Scale bars, 10 µm. g, h Quantification
of fibrillarin area and RPA194 intensity in >800 cells per condition,
treated as in f. Data shown as mean SD and is representative of two
independent experiments; Statistical significance was calculated by
one-way ANOVA using Kruskal–Wallis test and Dunn’s multiple test
comparison (*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.001). i
Nucleolin is translocated into the nucleoplasm. Nuclear DNA was
counterstained with DAPI. U2OS cells treated with increasing doses of
AQ during 6 h. Scale bars, 10 µm j U2OS cells were treated with CQ,
AQ and BHM-21 during 6 h and fixed for transmission electron
microscopy (TEM) for nucleoli analysis. Scale bars, 1 µm; GC gran-
ular component, FC fibrillar center, DFC dense fibrillar component.
AgNOR staining was used to identify changes in nucleolar organizer
regions. Blue arrows indicate nucleolus. Scale bars, 10 µm
CQ treatment (Fig. 2a). Thus, the RPL5/RPL11/5S rRNA
checkpoint mediates the AQ-induced p53 stabilization.
Transcription of rDNA becomes inhibited upon DNA
damage by ATM kinase-mediated signaling [33, 34]. We
observed that AQ is capable of intercalating DNA
depending on GC content, analogous to BMH-21 (Supple-
mentary Fig. 4). To assess potential DNA damaging effects,
we measured γ-H2AX foci formation in U2OS cells
exposed to diverse compounds for 24 h, compared with the
topoisomerase II inhibitor and DNA intercalator doxor-
ubicin as a positive control [35]. Both AQ and CQ produced
similar amounts of foci comparable with actinomycin D,
while the foci levels induced by BMH-21 were slightly
higher (Fig. 2b), yet still lower than the γ-H2AX foci
induced by CX-5461. Indeed, both BMH-21 and CX-5461
inhibit rRNA synthesis; however, they differ in their gen-
otoxic capacity. Whereas BMH-21 inhibits rDNA tran-
scription without significant DNA damage [11], CX-5461
causes DNA damage and activates ATM/ATR signaling
[9, 10]. To investigate any role of ATM in AQ-dependent
impact on RPA194 and p53 levels, we exposed ATM-
knockout cells to AQ, CQ, and doxorubicin. AQ-induced
RPA194 degradation and p53 stabilization were evidenced
even in the absence of ATM (Fig. 2c). Doxorubicin does
not induce RPA194 degradation; however, it triggers
p53 stabilization as well as phosphorylation of the DNA
damage markers KAP1 and H2AX (Fig. 2c). As doxor-
ubicin also partly inhibits rRNA synthesis [36], yet does not
induce RPA194 degradation, DNA damage is not directly
linked to RPA194 degradation. Consistently, preincubation
with the ATM inhibitor KU60019 did not rescue the
RPA194 degradation induced by AQ and BMH-21
(Fig. 2d). Upon induction of double-strand breaks in the
rDNA, ATM signaling leads to generation of nucleolar caps
and chromatin remodeling. However, chemically induced
nucleolar caps are not prevented by ATM inhibition [37].
Similarly, we observed that nucleolar caps are induced by
AQ at similar levels regardless of ATM status, analogous to
caps induced by BMH-21 and actinomycin D (Fig. 2f).
Taken together, these results show that RPA194 degrada-
tion, p53 stabilization and nucleolar caps induced by AQ
occur independently of ATM signaling.
showed extensive inhibition of rRNA synthesis and
nucleolar remodeling induced by AQ.
AQ stabilizes p53 via the RPL5/RPL11-5S rRNA
checkpoint, independent of ATM
AQ is more efficient than CQ in stabilizing p53 at equi-
molar concentrations [18, 19], however, the mechanism
underlying this difference is unknown. Ribosome biogen-
esis stress leads to p53 activation mainly through the
interaction between the RPL5/RPL11/5S rRNA complex
and MDM2, inhibiting MDM2’s ubiquitin ligase activity
and thereby stabilizing/activating p53 [32]. To examine
whether this checkpoint is triggered by AQ, we depleted the
nuclear pools of RPL5 and RPL11 using siRNA knock-
down. After AQ exposure, stabilization of p53 was reduced
to control levels when knocking down either RPL5 or
RPL11 (Fig. 2a), indicating that the AQ-induced p53 acti-
vation reflects ribosome biogenesis stress. Consistently, p53
activation induced by BHM-21 was partially reversed by
RPL5/11 knockdown, while p53 remained unaffected upon
AQ induces ribosome biogenesis stress
independently of its autophagy-inhibitory activity
AQ, along with other members of the 4-aminoquinoline
family, including CQ, hydroxychloroquine (H-CQ), and
Lys-05 (dimeric CQ) inhibit autophagy [17]. While 4-
aminoquinolines were thought to inhibit autophagy by
increasing lysosomal pH [17], recent evidence challenges
this idea [38]. Cells treated with 1–10 μM AQ for 6 h
accumulated lysosomes (LAMP1-positive puncta) (Fig. 3a,

J. A. Espinoza et al.
Fig. 2 Amodiaquine stabilizes p53 through RPL5/RPL11 nucleolar
checkpoint and does not require ATM activation. a Knockdown of
RPL5 and RPL11 prevent p53 activation after exposure to AQ. Cells
were treated with siRNA against RPL5 and RPL11 for 24 h. After,
cells were incubated with AQ, CQ, and BHM-21 during an additional
6 h. β-actin levels were used as loading control. b Quantification of
γ-H2AX positive foci number per nucleus after 24 h of incubation with
CQ, AQ, actinomycin D, BMH-21, CX-5461 and doxorubicin (>1000
cells per group). Data shown as mean SD of duplicate wells and are
representative of two independent experiments. (c) ATM is not
required for RPA194 degradation and p53 activation induced by AQ.
Immunoblot analysis for ATM, RPA194, KAP1, p-KAP1, p53,
p-H2AX, and β-actin in WT RKO colon cancer cell line and two ATM
knockout clones. Cells were incubated with doxorubicin, AQ, and CQ
during 6 h. d ATM inhibition does not prevent RPA194 degradation.
U2OS cells were pretreated with the ATM inhibitor KU60019 during
1 h and then incubated with AQ, CQ, and BMH-21 during 6 h.
e Nucleolar caps induced by AQ do not require ATM. Immuno-
fluorescence staining of RPA194 and fibrillarin in WT RKO colon
cancer cell line and two ATM knockout clones treated as in c. Scale
bars, 10 µm
b) while concentrations between 10 and 20 μM further
enhanced autophagosome accumulation (Fig. 3c, d; LC3B
puncta). Notably, 10–20 μM AQ also induced generation of
nucleolar caps (Fig. 3c), showing that both autophagy
inhibition and nucleolar stress take place simultaneously.
Strikingly, even though AQ and CQ showed similar levels
of lipidated LC3 (LC3-II) (Fig. 2a) and accumulation of
cytoplasmic vesicles (Fig. 3e), only AQ caused remarkable
condensation of nucleolar chromatin (Fig. 3e). Therefore,
we asked whether autophagy inhibition contributes to the
AQ-induced nucleolar stress and how does this relate to
other 4-aminoquinoline family members and other
mechanisms of autophagy inhibition. To elucidate these
issues, we treated U2OS cells with cathepsin inhibitors
pepstatin A and aloxistatin (a.k.a E64d), that prevent
autophagy through suppression of protein cleavage inside
lysosomes; and bafilomycin-A1, an inhibitor of the
vacuolar-type H+-ATPase that maintains acidic pH inside
the lysosomes. Increase in pH inhibits hydrolases and
autophagy [17]. Although treatments with aloxistatin/pep-
statin A and bafilomycin-A1 induce accumulation of LC3-II
and prevent p62 degradation, no effect was observed on
either RPA194 protein levels or p53 stabilization, in con-
trast to effects of AQ, at 6 and 24 h of treatment (Fig. 3f).
Among the 4-aminoquinoline family members, CQ and
H-CQ inhibit autophagy with efficiency similar to AQ, but

The antimalarial drug amodiaquine stabilizes p53 through ribosome biogenesis stress, independently of. . .
RPA194 degradation and p53 stabilization was only
induced by AQ (Fig. 3f). At 6 h, Lys-05 induced the
strongest LC3-II accumulation compared with AQ, CQ, and
H-CQ (Fig. 3f), consistently with previous results [39].
However, at 6 h the effect of Lys-05 on RPA194
degradation was subtle and there was no p53 stabilization.
Furthermore, only AQ induced a strong reduction of 47S
rRNA synthesis among all autophagy inhibitors tested
(Fig. 3g). Overall, these findings indicate that ribosome
biogenesis stress is not a general consequence of autophagy

J. A. Espinoza et al.
Fig. 3 Ribosome biogenesis stress induced by amodiaquine is not
related to its autophagy inhibition activity. a AQ induces accumulation
of LAMP1-positive and c LC3-positive puncta along with RPA194
positive nucleolar caps. U2OS cells were treated with increasing doses
of AQ during 6 h and stained. White arrows indicates nucleolar caps.
Scale bars, 5 µm. b Quantification of LAMP1-positive and d LC3B-
positive puncta in cells treated as in a and c. Statistical significance
was calculated by one-way ANOVA using Kruskal–Wallis test and
Dunn’s multiple test comparison (*p < 0.05, **p < 0.01, ***p < 0.001,
****p < 0.001). e Ultrastructural analysis shows accumulation of
cytoplasmic vesicles along with alteration of nucleolar structure
induced by AQ. Transmission electron microscopy of U2OS cells
treated during 6 h with CQ and AQ. N nucleolus; eA early autopha-
gosome; lA late autophagosome. f Comparison between autophagy
inhibitors shows that only AQ induces degradation of RPA194 and
activation of p53. Immunoblot analysis of RPA194, p53, beclin-1,
p62, LC3B, and β-actin in U2OS cells treated with aloxistatin +
pepstatin A, bafilomycin-A1 (Baf-A1), amodiaquine (AQ), chlor-
oquine (CQ), hidroxychloroquine (H-CQ) and Lys-05 during 6 and 24
h. g RT-qPCR analysis of 18S 3′and 18S 5′ junction of the 47S rRNA
precursor in cells treated as in f. Data shown as mean SD of triplicate
wells and are representative of three independent experiments
Among the CQ-regulated genes, 37% (85 out of 228)
were also regulated by AQ, including transcripts enriched
for cholesterol biosynthesis, response to hypoxia and blood
vessel development (Fig. 4d). Indeed, CQ impairs choles-
terol uptake and reduces processing of extracellularly
derived cholesterol esters, rendering cells dependent on the
cholesterol biosynthesis [41]. The impact of CQ on vessel
normalization reflects lysosomal dysfunction and sustained
activation of Notch1. The latter, autophagy-independent
mechanism, seems to underlie the antineoplastic effect of
CQ in vivo [42]. Interestingly, we observed that AQ and CQ
induce expression of the endoplasmic reticulum (ER) stress-
related genes GADD34 (PPP1R15A), CHOP (DDIT3),
REDD1 (DDIT4), BNIP3 and BNIP3L (Nix). In a more
detailed biochemical analysis of ER stress, we observed
moderate activation of ATF4, together with phosphorylation
of PERK and eIF2α, indicating activation of the PERK
branch of the unfolded protein response [43], in the absence
of ATF6 cleavage and lack of translation of spliced XBP1
(Supplementary Fig. 5). The transcriptional overlap between
AQ and CQ suggests that AQ shares most of the autophagy/
lysosome-disrupting mechanisms with CQ.
Furthermore, 1041 genes were specifically affected by
AQ, enriched in angiogenesis/VEGF, autophagy and cell
adhesion pathways. Among all genes perturbed by the three
compounds, 33.9% overlapped between AQ and BMH-21,
including those related to cell-cycle arrest, DNA replication
stress, and p53 signaling, consistent with our results and
previous studies [18, 25]. Among the p53-regulated genes
we observed higher expression of the cyclin dependent
kinase inhibitor CDKN1A (p21) and the proapoptotic genes
PMAIP1 (Noxa) and BBC3 (Puma). Upon siRNA mediated
knockdown of p53, the AQ-induced increase in expression
of these genes was decreased, often to a degree that was no
longer significant compared with vehicle-treated cells
(Supplementary Fig. 6). These results implicate the p53-
mediated checkpoint signaling in response to AQ-induced
ribosome biogenesis stress as a significant contributor to the
observed cellular transcriptional responses with likely
impact toward cell-cycle inhibition and cell death machi-
neries (Supplementary Fig. 6). BMH-21 alone perturbed
the expression specifically of 1687 genes, implicated
in carboxylic acid synthesis and downregulating components
of tRNA aminoacylation, including AARS, CARS,
EPRS, GARS, IARS WARS, YARS, and VARS. A total
of 101 perturbed genes (2.3%) were shared by all three
compounds.
inhibition and that AQ stands out among the
4-aminoquinoline family as a compound operating through
two independent mechanisms: autophagy inhibition in the
cytoplasm and ribosome biogenesis stress in the nucleolus.
AQ perturbs transcription analogous to CQ and
BMH-21
Transcriptome analysis can identify shared and unique
mechanisms of action among compounds, pointing to
links between biological activities and diseases [40].
Unlike CQ, AQ triggers ribosome biogenesis stress,
reminiscent of mechanistic features of BMH-21. To elu-
cidate the transcriptional networks underlying these fea-
tures, we performed a transcriptome analysis using
RNAseq on U2OS cells treated with AQ, CQ, and BMH-
21 (Fig. 4a). BMH-21 inhibited rRNA synthesis at lower
concentrations than AQ (Fig. 4b), while CQ did not
impact the 47S rRNA level (Fig. 4b). Principal component
analysis showed that AQ segregated separately from CQ
and BMH-21, suggesting unique properties (Fig. 4c).
To gain further mechanistic insights, we performed a
differential expression analysis between each compound
and the vehicle using the DEseq algorithm, applying as
cut-off a Bonferroni corrected p value < 0.001 and gene
expression fold changes >0.6 and <−0.6. Under equi-
molar concentrations, AQ induced more gene expression
changes than CQ (2774 vs 228 genes, respectively).
Notably, BMH-21 induced the most dramatic perturba-
tion, with 3316 affected genes. Differentially expressed
genes were further sorted among the three compounds
using Venn diagrams to identify common and unique gene
perturbations.
These results reveal that AQ induces transcriptional
changes that overlap with those induced specifically either
by CQ or BMH-21, thereby overall consistent with the
concept that AQ impacts cells simultaneously through two
mechanisms of action: autophagy inhibition and ribosome
biogenesis stress.

The antimalarial drug amodiaquine stabilizes p53 through ribosome biogenesis stress, independently of. . .
AQ kills CRC cells
inhibition [18, 44]. Unlike for AQ, the CQ-induced cell
death depends on glucose [44]. These differences suggest
that the unique impact of AQ on rDNA transcription
may explain its higher cytotoxicity. Recently, ribosome
AQ is more cytotoxic against cancer cells than CQ [18, 44],
albeit AQ displays similar or lower autophagy/lysosome

J. A. Espinoza et al.
Fig. 4 Transcriptional perturbation induced by Amodiaquine resem-
bles that of Chloroquine and BMH-21. a Experimental design for
RNAseq analysis. b AQ reduces the synthesis of 47S with less
intensity than BMH-21. RT-qPCR analysis for the 18S 3′ and 5′
junctions in the 47S rRNA transcript for cells treated as in a. Data
shown as mean SD of three treatments. c Principal component ana-
lysis based on RNAseq data, color-coded according to each treatment.
The scatter plot shows the position of samples based on the two first
principal components. d Gene ontology and pathway analysis com-
paring common and unique features among differentially expressed
genes disrupted by AQ, CQ, and BMH-21. ClueGO integrates GO
terms and pathways to create a functionally organized network. Node
size represents amount of mapped genes and node color is assigned
randomly. Nodes with two colors contains genes that converged from
different databases
bind proteins covalently, generating protein adducts that are
suspected to be responsible for the toxicity [18, 49]. To
assess whether the reactive group in the AQ metabolite
contributes to the nucleolar impairment, we synthesized an
AQ analog removing the hydroxyl group to disrupt the
aminophenol moiety (deshydroxy-amodiaquine, DH-AQ;
Fig. 6a). The DH-AQ still caused p53 activation, RPA194
degradation (Fig. 6b), nucleolar cap formation and dis-
sipation of nucleolin, only slightly lower than AQ (Fig. 6c).
This implies that the reactive metabolite does not determine
the nucleolar stress, since the (–OH) group does not
robustly affect the nucleolar impact of AQ. However, by
modulating the electrochemical behavior of the compound,
the (-OH) may improve interactions with rDNA and/or
RPA194.
biogenesis was highlighted as a clinically relevant target in
CRC [13]. While testing toxicity in cell culture, the growth-
inhibitory concentrations (GI50s) of AQ were consistently
lower than for CQ in a panel of 18 human cancer and
immortalized cell lines (Fig. 5a, b). The CQ:AQ GI50s
ratios were higher among the CRC cell lines, supporting
higher sensitivity to AQ (Fig. 5c). When correlating the
sensitivities among all cell lines (GI50s) with the extent of
AQ-induced RPA194 degradation as a marker for ribosome
biogenesis stress, a R2 of 0.22 was found (Fig. 5d). Such
partial correlation implies that RPA194 degradation per se
cannot serve as a universal predictor of AQ-induced cell
death under this type of nucleolar stress, the overall out-
come of which likely reflects also additional factors such as
the p53 status or adaptive pro-survival pathways that impact
the fate of AQ-treated cells. Notably, when RPA194
degradation was analyzed in nontransformed human cell
types, we observed either only partial degradation (IMR-90)
or complete lack of RPA194 degradation (BJ fibroblasts and
HEKa primary keratinocytes), overall indicative of resis-
tance to AQ compared with cancer cells (Supplementary
Fig. 7).
The CYP450 isoform CYP2C8 promotes generation of
N-desethylamodiaquine (DE-AQ) [50], the main stable
metabolite of AQ, responsible for the antimalarial activity.
We observed that DE-AQ retains AQ’s autophagy- and
ribosome biogenesis-inhibitory activities (Supplementary
Fig. 8). Furthermore, the cytochromes CYP2C8, CYP2C9,
CYP2D6, and CYP3A4 contribute to bioactivation of AQ
into protein-reactive quinoneimines [51]. The human
hepatoma cell line HepG2, a proposed model for hepatic
toxicity, shows high expression and activity of cytochromes
[52]. Compared with U2OS, the HepG2 cells expressed
higher mRNA levels of all cytochrome genes we tested,
particularly of CYP3A4. HepG2 cell line is affected by DH-
AQ in a similar way as U2OS, inducing p53 activation and
RPA194 degradation (Supplementary Fig. 9). Capillary
immunoblotting using an anti-AQ antibody detected AQ-
induced protein adduction in both HepG2 and U2OS cells,
generating a smear between ~60 and ~120 kDa, with a
stronger signal for HepG2 (Fig. 6d), and an intense signal
around ~12 kDa (Fig. 6d), probably corresponding to AQ-
glutathione adducts, the detoxification product catalyzed by
glutathione S-transferases. This reaction is observed for AQ
and reactive metabolites derived from other drugs [53].
Importantly, the absence of the reactive group in DH-AQ
completely abrogated the formation of protein adducts,
however, DH-AQ still triggered RPA194 degradation in
U2OS cells and weaker p53 activation in both cell lines.
(Fig. 6d). In addition, in order to inhibit cytochrome
activity, cells were treated with the potent nonselective
cytochrome inhibitor clotrimazole, which has been shown
to inhibit CYP2C8, CYP2C9, CYP2D6, and CYP3A4
[54, 55]. In both cell lines, the treatment with clotrimazole
reduced the levels of AQ-protein adducts, however, in
HepG2, DH-AQ is still capable of slightly decreasing
RPA194 levels and activating p53 while in U2OS, DH-AQ
induces the same level of degradation of RPA194, showing
that cytochrome activity is not required for the nucleolar
effects induced by AQ.
The reactive metabolite of AQ is not involved in
nucleolar activity
AQ combined with artesunate is indicated by the WHO for
the treatment of uncomplicated Plasmodium falciparum and
Plasmodium vivax infections and seasonal malaria chemo-
prevention [45], while AQ treatment for malaria prophy-
laxis declined during the 80s following reports of
idiosyncratic hepatotoxicity and agranulocytosis [46]. The
precise origin of these idiosyncratic reactions is not yet
understood. AQ contains a p-aminophenol moiety and
undergoes extensive bioactivation with formation of a
reactive quinoneimine intermediate that strongly depends
on cytochrome P450 activity in the liver [47] and myelo-
peroxidase in neutrophils [48]. This reactive metabolite can

The antimalarial drug amodiaquine stabilizes p53 through ribosome biogenesis stress, independently of. . .
Fig. 5 Amodiaquine is more cytotoxic than chloroquine, particularly in
colorectal cancer cells a Dose responses curves and b growth-
inhibitory concentrations (GI50s) of AQ and CQ in a panel of color-
ectal (CRC) and non-CRC cell lines. Cells were incubated with
compounds for 72 h. Fitted dose response curves display mean and
standard deviation from three experiments. In a, dashed vertical lines
represent the growth-inhibitory concentrations (GI50). c CRC cell
lines are more sensitive to AQ than non-CRC lines. Comparison of
GI50 shift between AQ and CQ in CRC and non-CRC cell lines using
CQ/AQ ratios calculated from triplicate dose response curves. Ratios
were analyzed using unpaired t test; *P value < 0.05. d Correlation
between GI50s obtained after 72 h and RPA194 degradation obtained
by quantitative immunoblot after 6 h of incubation with AQ
These results provide an additional mechanistic feature
of AQ, showing that the nucleolar activity is retained in
the absence of the reactive intermediates, and supporting
feasibility of chemical optimization of AQ to enhance
the nucleolar disruption capacity while eliminating idio-
syncratic side effects.
An AQ-derived analog that inhibits both autophagy
and ribosome biogenesis
To investigate whether chemical optimization of AQ could
increase its efficiency of rDNA transcription inhibition, we
first tested amopyroquine (ApQ), a commercially available

J. A. Espinoza et al.
Fig. 6 AQ-induced protein adduction is not involved in nucleolar
stress a Chemical structures of amodiaquine and its analog without the
reactive group, deshydroxy-amodiaquine (DH-AQ). b Immunoblot
analysis of RPA194, p53 and LC3 in U2OS cells treated with
increasing doses of AQ and its nonreactive analog DH-AQ during 6 h.
c Nucleolin translocation and UBF-positive nucleolar (white arrows)
caps were detected by immunofluorescence in U2OS cells treated as in
a. Scale bars, 10 µm. d Capillary immunoblot of HepG2 and U2OS
cells treated with 20 µM of AQ and DH-AQ during 6 h. Cells were
treated with 20 µM of clotrimazole for 1 h prior to adding AQ and DH-
AQ, maintaining the same concentration of clotrimazole for the next
6 h of incubation. AQ-adducts were detected using a monoclonal
antibody against AQ
structural analog of AQ. In ApQ, the 2-diethylamino side
chain is replaced by a cyclic pyrrolidone one (Fig. 7a).
Notably, ApQ was more potent than AQ in inducing
RPA194 degradation and p53 stabilization, with compar-
able amounts of LC3-II generation (Fig. 7b) and similar
accumulation of LC3 and LAMP1 puncta (Fig. 7c). ApQ
contains the p-aminophenol moiety that could potentially
generate reactive intermediates. We chemically modified
ApQ by removing the hydroxyl group (deshydroxy-amo-
pyroquine DH-ApQ; Fig. 7d). Whereas DH-ApQ still trig-
gered nucleolar stress, nucleolin dissipation and UBF-
positive nucleolar caps (Fig. 7e), the extent of RPA194
degradation and p53 stabilization were slightly affected
(Fig. 7d). These findings showed that side chain-modified
AQ analogs may preserve or even increase the nucleolar
disruption capacity, thereby supporting the notion that
optimized analogs deserve future exploration as candidate
anticancer compounds.
Discussion
Our findings show that the FDA-approved antimalarial
drug AQ inhibits ribosome biogenesis, an activity not
shared by other 4-aminoquinoline family members. AQ
triggers proteasome-dependent degradation of RPA194
(POLR1A), a feature reported for the experimental drugs
BMH-21 [12] and BMH-22 [25, 56]. Notably, this is the
first example of a FDA-approved drug capable of triggering
Pol I degradation.

The antimalarial drug amodiaquine stabilizes p53 through ribosome biogenesis stress, independently of. . .
Fig. 7 Amopyroquine exerts nucleolar stress in a similar way as its
analog amodiaquine a Chemical structure of amopyroquine (ApQ). b
ApQ induces similar alterations to those of AQ. Immunoblot analysis
of RPA194, p53, LC3, LAMP1, and nucleolin in U2OS cells treated
with increasing doses of AQ during 6 h. c Quantification of LC3B and
LAMP1-positive puncta in cells treated as in b. d ApQ analog without
the reactive group (deshydroxy-amopyroquine; DH-ApQ) shows
somewhat less activation of p53 and less RPA194 degradation.
Immunoblot analysis of RPA194 and p53 in U2OS cells treated with
increasing doses of ApQ and its analog DH-ApQ during 6 h. e DH-
ApQ has less activity than ApQ inducing nucleolin translocation and
generation of UBF-positive nucleolar. Immunofluorescence analysis
of U2OS cells treated as in d. White arrows indicate nucleolin trans-
location into nucleoplasm and UBF-positive nucleolar caps. Scale
bars, 10 µm
Targeting ribosome biogenesis has been proposed as a
therapeutic strategy for hematological malignancies [57],
ovarian [58], prostate [59], and MYC-driven cancers [60].
Relevance to CRC has been highlighted by the discovery
that oxaliplatin, used as standard-of-care for CRC
patients, kills cancer cells mainly due to its capacity to
impair ribosome synthesis [13]. In this context, the
identification of molecular subtypes with greater sensi-
tivity to ribosomal stress will enable the selection of
patients who might benefit from the use of ribosome
biogenesis inhibitors [1].
Ongoing clinical trials are addressing the potential of CQ
and H-CQ in combinatorial treatments for various cancer
types. Most such trials were designed with the rationale to
increase the efficacy of other anticancer therapies through
inhibition of treatment-induced autophagy. Although it is too
early to draw any conclusions, data from first clinical trials and
additional preclinical data suggest a potential for implement-
ing these drugs in anticancer treatment [61]. To the best of our
knowledge, no cancer clinical trial has yet been reported for
AQ. Our findings show that while AQ and CQ share similar
autophagy-inhibitory activity, AQ also displays an additional,
potent mechanism to restrain cancer cell growth. Thus, the
dual activity of AQ in the cytoplasm and the nucleolus makes
this drug a promising candidate for cancer therapy.
In conclusion, we have demonstrated that AQ inhibits
ribosome biogenesis and disrupts nucleolar structure, trig-
gering degradation of RNA polymerase I. Moreover, AQ
exerts high cytotoxic activity against CRC, a neoplasia with
predicted sensitivity to ribosome biogenesis inhibitors. Our
study supports the rationale for repurposing an old and
inexpensive drug to target an emerging vulnerability in
cancer, which may translate into more affordable and
accessible therapies.

J. A. Espinoza et al.
Acknowledgements The authors acknowledge support from Science
for Life Laboratory, the National Genomics Infrastructure, NGI, and
Uppmax for assistance in massive parallel sequencing and computa-
tional infrastructure, and Eduardo A. Sagredo for support in the ana-
lysis of RNAseq data. The work was funded by grants from the
Karolinska Institutet, the Swedish Cancer Society (No. 170176), the
Swedish Research Council (VR-MH 2014-46602-117891-30), the
Novo Nordisk Foundation (no. 16854), the Danish National Research
Foundation (project CARD: no. DNRF125) to J.B, and the King
Gustaf Vʼs Jubilee Foundation to M.L. (No. 134082). For this study,
T.H. acknowledge funding by the European Research Council
(TAROX Programme), Swedish Research Council and the Swedish
Cancer Society.
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use, you will need to obtain permission directly from the copyright
holder. To view a copy of this license, visit http://creativecommons.
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