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science.sciencemag.org/cgi/content/full/science.aay0939/DC1
Supplementary Materials for
Deregulation of ribosomal protein expression and translation promotes
breast cancer metastasis
Richard Y. Ebright, Sooncheol Lee, Ben S. Wittner, Kira L. Niederhoffer,
Benjamin T. Nicholson, Aditya Bardia, Samuel Truesdell, Devon F. Wiley,
Benjamin Wesley, Selena Li, Andy Mai, Nicola Aceto, Nicole Vincent-Jordan,
Annamaria Szabolcs, Brian Chirn, Johannes Kreuzer, Valentine Comaills, Mark Kalinich,
Wilhelm Haas, David T. Ting, Mehmet Toner, Shobha Vasudevan, Daniel A. Haber*,
Shyamala Maheswaran*, Douglas S. Micalizzi
*Corresponding author. Email: dhaber@mgh.harvard.edu (D.A.H.); maheswaran@helix.mgh.harvard.edu
(S.M.)
Published 6 February 2020 on Science First Release
DOI: 10.1126/science.aay0939
This PDF file includes:
Materials and Methods
Figs. S1 to S17
Table S1
Captions for Data S1 and S2
References
Other Supplementary Material for this manuscript includes the following:
(available at science.sciencemag.org/cgi/content/full/science.aay0939/DC1)
Data S1 and S2 (.xlsx)
Materials and Methods
CTC cell culture: CTCs were grown in suspension in ultra-low attachment plates
(Corning) in tumor sphere media, consisting of RPMI-1640 with GlutaMAX supplemented with
EGF (20ng/mL), FGF (20ng/mL), 1X B27, and 1X antibiotic/antimycotic (Life Technologies), in
4% O2, as previously described (6, 7). CTC lines were routinely checked for mycoplasma
(MycoAlert, Lonza), and were authenticated by RNA-seq and DNA-seq. MCF10A were grown
as previously described (51).
Lentivirus production: HEK293T cells were grown in high-glucose DMEM supplemented
with 10% fetal bovine serum and 1% penicillin/streptomycin. For CRISPR activation library
production, cells were transfected at ~80% confluency in T225 flasks. For each flask, 15.3µg
pMD2.G, 23.4µg psPAX2, and 30.6µg pooled library plasmid were transfected using 270µL
Lipofectamine 2000 and 297µL PLUS reagent, as previously described (52). 24h after
transfection, the media was changed. Virus supernatant was harvested 48h post-transfection,
filtered through a 0.45µm PVDF filter, concentrated with Lenti-X Concentrator (Clontech),
aliquoted, and stored at -80°C.
Lentiviral transduction: 5x105 CTCs were transduced with lentivirus in 6-well plates in
2mL media supplemented with 6µg/mL Polybrene. 24h after infection, media was changed. 72h
after infection, cells were selected using blasticidin (10µg/mL), hygromycin (400µg/mL), or
puromycin (3µg/mL) for 7 days. Lentiviral titers were determined by infected cells with 6
different volumes of lentivirus and counting the number of surviving cells after 7 days of
selection.
CRISPR activation screen: Brx-82 and Brx-142 cells stably expressing GFP, luciferase,
and MS2-P65-HSF1 (Addgene #89308) were transduced with the human CRISPR/Cas9 SAMv2
pooled library (Addgene #1000000078) as described above, at a MOI of 0.3, and fully selected
with blasticidin. Immediately following selection, for each cell line, 8 female NSG (NOD. Cg-
Prkscid Il2rgtm1Wjl/SzJ) mice were injected with 3x106 cells each, via the tail vein. Mice were
anesthetized with isoflurane, and a 90-day release 0.72mg estrogen pellet (Innovative Research
of America) was implanted subcutaneously behind the neck of each mouse. One Brx-142 mouse
died during this process, resulting in an average screening coverage of ~350 cells/guide in Brx-
82 and of ~300 cells/guide in Brx-142. At the same time, DNA from 21x106 cells (300
cells/guide) was isolated as an input baseline distribution of guides. After two months, mice were
sacrificed, and whole lungs were harvested. Lungs were divided into 25µg chunks and
homogenized using a TissueLyser II (Qiagen), and DNA was extracted using NucleoSpin Tissue
DNA extraction columns (Macherey-Nagel). PCR of the guides was performed using NEBNext
High Fidelity 2X Master Mix (New England Biolabs) in parallel reactions in a single-step
reaction of 35 cycles, using primers as previously described (52). PCR productions from all
reactions were pooled, purified using the QIAquick PCR Purification columns (Qiagen), and
sequenced on the Illumina MiSeq platform. All mouse handling was completed in compliance
with ethical regulations and approved in IACUC animal protocol 2010N000006.
NGS and screen hits analysis: Guide counts for each sample were normalized to the total
counts for that sample. Guide distribution for each mouse was compared to the input distribution
of guides, resulting in a fold change value for each guide for each mouse. Fold change was
averaged across all mice to yield an average fold change for each guide for each cell line. For
each cell line, the most enriched guide for each gene was determined, and corresponding genes
were rank-ordered based on enrichment, with a rank of 1 denoting most enriched. Gene rank was
averaged between the Brx-82 and Brx-142 screens and normalized to the lowest average gene
rank to generate a combined screen score value for each gene.
Validation mouse studies: Lentiviral expression constructs for RPL8 (Accession:
BC000077), RPL13 (Accession: BC014167), RPL15 (Accession: BC071672), and RPL35
(Accession: BC000348) were obtained from the CCSB-Broad Lentiviral Expression Library.
CTCs expressing GFP and luciferase were infected with these plasmids or with empty vector
(Addgene #25890) as described above. After full selection, 5x105 cells expressing target genes or
empty vector were injected into the tail veins of 4 female NSG mice per sample. Mice were
anesthetized with isoflurane, and a 90-day release 0.72mg estrogen pellet (Innovative Research
of America) was implanted subcutaneously behind the neck of each mouse. Metastatic growth
was measured bi-weekly via in vivo imaging using the IVIS Lumina II (PerkinElmer) following
intraperitoneal injection of D-luciferin (Sigma). Mice were sacrificed at 20 weeks, and lungs and
ovaries were harvested into 10% formalin for 24h for fixation prior to immunohistochemistry.
For orthotopic injections, 2.5x105 cells expressing RPL15 or empty vector were mixed into 1:1
Growth Factor Reduced Matrigel (Corning), and cell media and injected into each of the fourth
mammary fat pads of 4 female NSG mice per sample.
Histology and Immunohistochemistry: Tumors and multiple organs were fixed in 10%
formalin overnight, then preserved in 70% ethanol. The tissue was embedded in paraffin and cut
in 5-µm sections. For histologic analysis, sections were stained with hematoxylin and eosin or
immunohistochemical staining was performed. Tissues were permeabilized, and antigen retrieval
was performed in 1× citrate buffer (pH 6) for 15 min. Slides were washed and blocked for 30
min with 5% goat serum. Sections were incubated with primary antibodies against GFP (1:250;
Abcam ab183734), Ki-67 (1:50; Life Technologies 180192Z), Cleaved caspase-3 (1:1000; Cell
Signaling Technology 9664S), or HLA Class 1 (1:100; Abcam ab70328) for 1 hour at room
temperature. Slides were incubated with HRP anti-rabbit antibody (DAKO) for 30 min. After
washing with PBS, the sections were incubated in 3,3′ -diaminobenzidine (Vector Laboratories)
for 10 min. Cells were counterstained with Gill’s #2 haematoxylin for 10–15s.
Stained tissue sections were digitized using the Aperio CSO (Leica Biosystems). Tumor
foci in the lungs were quantified by counting on at least 3 independent sections and tissue area
calculated using Imagescope software.
Western blot analysis: Western blot analysis was performed on whole cell extracts
prepared with RIPA buffer. Proteins were separated on 4-15% polyacrylamide gradient-SDS gels
(Bio-Rad), and transferred onto Nitrocellulose membrane (Invitrogen). Immunoblots were
visualized with Enhanced Chemiluminescence (Perkin-Elmer). Primary antibodies were used
against GAPDH (1:2000; Millipore ABS16) and V5 tag (1:1000, Life Technologies R96025).
Quantitative Realtime PCR: RNA was isolated using RNeasy Mini Kits (Qiagen). RNA
was reverse transcribed using Superscript III First Strand Synthesis Supermix (Invitrogen).
TaqMan probe and primer sets for RPL8, RPL13, RPL15, RPL35 and GAPDH were used
(ThermoFisher Biosciences). Values represent the ratio of the relative quantity of RP transcript
to the relative quantity of GAPDH.
Ribosome Profiling: Ribosome profiling was performed as previously described (14).
Briefly, 10 million RPL15- or control-expressing Brx-142 cells were treated with 0.1 mg/ml
cyclohexamide for 1 minute, washed with cold PBS containing cycloheximide and lysed. A
range of RNase I (Thermofisher) concentrations was tested, and an optimal concentration was
chosen that did not lead to degradation of the ribosome protected fragments. RNase I
(Thermofisher) treatment was performed and the monosomes were isolated by gel filtration
MicroSpin S-400 HR Columns (GE Healthcare). After RNA extraction using RNA Clean &
Concentrator-25 kit (Zymo Research), rRNA was depleted (Ribo-Zero Gold rRNA Removal Kit,
Illumina), and ribosome-protected fragments were purified by PAGE. The fragments were end-
repaired with PNK (NEB). Libraries were prepared using a TruSeq small RNA Library Prep Kit
(Illumina) and sequenced on a NextSeq 500 Illumina (50 bp single-end reads). Reads were
mapped to the sense strand of the entire human RefSeq transcript sequence library. Ribosome
profiling was performed in duplicate. Correlation between the two replicates of ribosome
profiling show an R2 = 0.96 for both the control and RPL15-CTCs.
RNA-sequencing: RNA was extracted using the RNeasy Mini Kit (Qiagen). To generate
libraries for RNA-seq, the SMART-Seq HT Kit (Takara Bio USA) was used according to the
manufacturer’s instructions. Pooled libraries were sequenced on an Illumina NextSeq sequencer.
Polysome Profiling of CTC cells: Polysome analysis was conducted as described
previously (53). 15% and 50% (w/v) sucrose solutions were prepared in buffer A (10 mM Tris-
HCl, pH 7.4, 100 mM KCl, 5 mM MgCl2, 100 µg/ml cycloheximide and 2 mM DTT). Sucrose
density gradients were prepared as previously described (54, 55). Before harvesting, the cells
were treated with 100 µg/ml cycloheximide at 37°C for 5 min. Collected cells were washed with
cold PBS containing cycloheximide and then lysed in buffer A containing 1.5% Triton X-100
and 40 units/µl murine RNase Inhibitor (NEB) for 20 min. Cleared cell lysates were loaded on
sucrose gradients followed by ultracentrifugation (Beckman Coulter Optima L90) for 2 hours at
38,000 rpm at 4°C in an SW40 rotor. Samples were fractionated by density gradient fractionation
system (Isco). The heavy polysome fractions were pooled, and RNA was isolated via RNeasy
Micro Kit (Qiagen). Polysome traces were digitalized and the areas under the curve for
monosome and polysome peaks were calculated using Image J.
Total RNA Quantification: Total RNA from 1x106 CTCs was isolated via TRIzol Reagent
extraction (Invitrogen). RNA was quantified via NanoDrop (ThermoFisher).
Nascent Protein Measurement: Global translation was measured using two independent
methods. For OP-Puro analysis, CTCs were treated with OP-puro for 30 minutes followed by
fluorescent labeling of nascent peptides with OP-puro incorporation using the Protein Synthesis
Assay Kit (Abcam). For analytical flow cytometry, cells were sorted using a BD Biosciences
LSR II Cell Sorter. FACS plots are representative of at least four experiments per sample. For
L-AHA labeling, 250,000 cells were plated in methionine-free media for 4 hours. The cells were
then labeled with L-AHA (50µM) for 24 hours. The cells were harvested in lysis buffer and the
protein incubated with biotin-labelled alkyne detection reagent (Invitrogen). Then a CuSO4
solution was added. The protein was methanol extracted and then separated on 4-15%
polyacrylamide gradient-SDS gels (Bio-Rad), and transferred onto Nitrocellulose membrane
(Invitrogen). The blots were probed with a horse radish peroxidase conjugated streptavidin and
developed with Enhanced Chemiluminescence (Perkin-Elmer).
Quantitative Proteomics: Frozen cell pellets were lysed in 500 µL lysis buffer (75mM
NaCl, 50mM HEPES pH 8.5, 10mM sodium pyrophosphate, 10mM sodium fluoride, 10mM -
glycerophosphate, 10mM sodium orthovanadate, Roche complete mini EDTA free protease
inhibitors, 3% SDS, 10mM PMSF). Disulfide bonds were reduced by adding dithiothreitol
(DTT) to a final concentration of 5 mM and incubation at 56 °C for 30 min, and free cysteine
thiol groups were alkylated with iodoacetamide (15 mM) in the dark at room temperature for 20
min. The alkylation reaction was stopped by adding DTT to a final concentration of 5 mM and
an incubation in the dark at room temperature for 15 minutes. Proteins were extracted by
precipitation through adding one part of trichloroacetic acid (TCA) to 4 parts (v/v) of protein
solution and incubation for 10 min on ice. The precipitated protein was pelleted by centrifugation
(15,000 g, 10 min, 5 °C) and washed twice with prechilled acetone (-20 °C, 300 µL, 15,000 g, 10
min, 5 °C). Protein pellets were resuspended in 500µL 1 M urea, 50 mM HEPES (pH 8.5) and
digested overnight at room temperature with 1 µg/µL endoproteinase Lys-C (Wako) followed by
a digestion with sequencing-grade trypsin (Promega) at a final concentration of 1 ng/μL 6 h at 37
°C. The digestion was quenched with 1% trifluoroacetic acid (TFA), and peptides were desalted
using Sep-Pak C18 solid-phase extraction (SPE) cartridges (Waters). The peptide concentration
of each sample was determined using a BCA assay (Thermo Scientific).
For labeling with TMT-11plex reagents (Thermo Scientific), 50 µg of peptides were dried and
resuspended in 50 µL of 200 mM HEPES (pH 8.5), 30% acetonitrile (ACN). Labeling was
performed by adding 150 μg TMT reagent in anhydrous ACN and incubating at room
temperature for 1 h. The reaction was stopped by addition of 5% (w/v) hydroxylamine in 200
mM HEPES (pH 8.5) to a final concentration of 0.5% hydroxylamine and incubation at room
temperature for 15 min. Samples were acidified with 1% TFA, and samples were combined and
desalted over Sep- Pak C18 SPE cartridges as described (56) and subjected to fractionation by
basic pH reversed phase HPLC (HPRP) (56). Twelve fractions were resuspended in 5%
ACN/5% formic acid and analyzed in 3-hour runs via reversed phase LC-M2/MS3 on an
Orbitrap Fusion mass spectrometer using the Simultaneous Precursor Selection (SPS) supported
MS3 method (57, 58) essentially as described previously (59). The analysis was performed in a
data-dependent mode beginning with an MS1 scan ranging from 500-1,200 m/z with the Orbitrap
analyzer at a resolution of 6x104, automatic gain control (AGC) of 5x105, and 100 ms maximum
injection time. Fragment ions were subjected to MS2 scans based on abundance and MS2 and
MS3 scan were done within a 5 second cycle. For doubly charged ions from an m/z range of
600-1200, and for triply and quadruply charged ions a m/z range of 500-1200 was selected for
MS2 scans. The isolation window was set to 0.5 m/z. Peptides were fragmented using CID at 30
% normalized collision energy at the rapid scan rate using an AGC target of 1x104 and a
maximum ion injection time of 35 ms using the ion trap. For MS3 analysis, synchronous
precursor selection (SPS) (57, 58) was used with up to 6 fragment ions to be simultaneously
isolated and subjected to MS3. MS3 analysis was performed with an isolation window of 2.5 m/z
and HCD fragmentation at 55% normalized collision energy. MS3 spectra were acquired at a
resolution of 5x104 with an AGC target of 5x104 and a maximum ion injection time of 86 ms.
MS2 spectra were assigned using a SEQUEST-based (60) in-house built proteomics analysis
platform (61) and applying a target-decoy database-based search strategy to assist filtering for a
false-discovery rate (FDR) of less than 1% for peptide and protein assignments (62). For peptide
assignment filtering we used linear discriminant analysis (62) and we calculated likelihoods of
incorrect assignment using a posterior error histogram. These probabilities were combined
through multiplication to calculate a likelihood of correct protein assignment. Protein
assignments were then sorted based on their likelihood of incorrect assignment and decoy
database matches were used for the final filtering (61) to a 1% FDR. Peptides that matched to
more than one protein were assigned to that protein containing the largest number of matched
redundant peptide sequences following the law of parsimony (61). MS3 TMT reporter ion
intensities were extracted from the most intense ion within a 0.003 m/z window centered at the
predicted m/z value for each reporter ion and spectra were used for quantification if the average
S/N value for all TMT channels was ≥ 40 and the isolation specificity (57) for the precursor ion
was ≥ 0.75. Protein intensities were calculated by summing the TMT reporter ions for all
peptides assigned to a protein. Intensities were first normalized by the average intensity across
all TMT channels relative to the median average across all proteins. In a second normalization
step protein intensities measured for each sample were normalized by the average of the median
protein intensities measured across the samples (59).
Patient Selection, CTC Isolation and Single Cell Amplification and Sequencing:
Patients with a diagnosis of ER and/or PR positive metastatic breast cancer provided informed
consent for de-identified blood collection, as per institutional review board approved protocol
(DF/HCC 05-300) at Massachusetts General Hospital. Approximately 6-12 mL of fresh whole
blood was processed through the microfluidic CTC-iChip as previously described (5) within 4
hours from the blood draw. Before processing, whole blood samples were incubated with
biotinylated antibodies against CD45 (R&D Systems, clone 2D1), CD66b (AbD Serotec, clone
80H3) and followed by incubation with Dynabeads MyOne Streptavidin T1 (Invitrogen) to
achieve magnetic labelling of white blood cells. This mixture was processed through the CTC-
iChip. To identify CTCs, the CTC-enriched product was stained with Alexa Fluor 488–
conjugated antibodies against EpCAM (Cell Signaling Technology, #5198), Cadherin 11 (R&D
Systems, FAB17901G), and HER2 (BioLegend, #324410). To identify contaminating white
blood cells the product was stained with TexasRed-conjugated antibodies against CD45 (BD
Biosciences, BDB562279), CD14 (BD Biosciences, BDB562334), and CD16 (BD Biosciences,
BDB562320). The stained product was viewed under a fluorescent microscope where single
CTCs were identified based on intact cellular morphology, Alexa Fluor 488-positive staining and
lack of TexasRed staining. Cells of interest were individually micromanipulated with a 10 mm
transfer tip on an Eppendorf Transfer-Man NK 2 micromanipulator and lysed. Single cell
amplification and sequencing was performed as previously described (63).
TGF-β treatment and Polysome Profiling of MCF10A cells: MCF10A cells were split
the day before initiating treatment with TGF-β (5ng/mL) for 3 days and then harvested or split
and re-treated with TGF-β for a total of 6 days. Untreated control cells and TGF-β treated cells
were harvested for Click-it L-AHA translational analysis as described above, RNA isolation or
polysome profiling. Polysome profiling performed as above. Polysome fractions were combined
and RNA isolated with TRIzol reagent and samples analyzed using microarray analysis
(Affymetrix Human Gene 2.0 ST Array).
In Vitro Drug Treatments: 2000 CTCs were seeded in tumor sphere media in 96-well
ultra-low attachment plates (Corning) in triplicate wells 24h before the addition of omacetaxine
(Fisher Scientific) and palbociclib (Selleckchem). Cell viability was assayed 5d after drug
treatment with CellTiter-Glo (Promega) and was normalized to untreated cells.
In Vivo Drug Treatments: 2.5x105 CTCs expressing RPL15 or empty vector were injected
into the left ventricles of female NSG mice per sample. Mice were anesthetized with isoflurane,
and a 90-day release 0.72mg estrogen pellet (Innovative Research of America) was implanted
subcutaneously behind the neck of each mouse. For each sample, half of each cohort received
daily oral gavage of palbociclib (25mg/kg) and IP injection of omacetaxine (0.5mg/kg), while
the other half of each cohort received daily oral gavage and IP injection of vehicle. Combined
treatment was begun one day prior to cardiac injection and continued for seven days post cardiac
injection, at which point palbociclib treatment was halted. Daily omacetaxine treatment was
continued. Metastatic growth was measured weekly via in vivo imaging using the IVIS Lumina
II (PerkinElmer) following intraperitoneal injection of D-luciferin (Sigma).
Statistical Analysis: RNA counts and RPM were computed as in (19) for the cohort of 135
CTCs or CTC-clusters and as in (7) for the independent cohort of 109 CTCs and for total mRNA
of the RPL15-CTCs and controls. Counts and RPM for ribosome protected mRNA were
computed as follows. Trim_galore was used to remove adapters and low-quality base-calls with
quality set to 20, stringency set to 3, and length set to 25. Bowtie2 was used to attempt to align
the resulting reads to the hg19_rmsk rRNA FASTA file from the UCSC table browser. Reads
that aligned were discarded and the others were aligned to the hg19 refGene transcriptome from
UCSC with additions for ERCC92 and RGC spike-ins using tophat with the no-novel-juncs
option set. Only uniquely aligned reads were kept and then duplicates were removed using
samtools rmdup. Read counts for all the genes were then created using htseq-count.
To identify differentially expressed genes, we used edgeR with common-dispersion set to 0.12 to
estimate fold-change and FDR. Genes that had fold-change greater than 2 and FDR less than
0.05 were considered differentially expressed.
To determine gene set enrichment, we used the hypergeometric test with the universe of genes
set to all genes for which counts had been determined. The resulting p-values were then
submitted to the Benjamini-Hochberg algorithm to estimate FDR. We used gene sets from
version 6.0 of the Broad Institute’s MSigDB.
For the unsupervised clustering in Figure 4A, we began with 176 CTCs or CTC-clusters from 52
patients. We removed samples for which the number of reads uniquely mapped to genes was less
than 105. We then removed samples for which the log10(RPM + 1) for PTPRC or FCGR3A is
above 0.4 due to suspicion that they might be white blood cells. That left us with 135 samples
from 45 patients. We then kept the 2000 rows with the highest RPM variance and then median
polished the resulting log10(RPM+1) expression matrix. We then used agglomerative hierarchical
clustering with average linkage and metric equal to one minus the Pearson correlation
coefficient. The clustering in Figure S9 and S11 was done using only the expression of the core
ribosomal genes, which are shown in those figures. We used agglomerative hierarchical
clustering with average linkage and Euclidean metric. The column ordering and dendrogram
determined for Figure S9 was also used for Figure 4B. P-values given in Figures 4B, S9, and S11
are two-sided and are computed either by the Wilcoxon test for continuous valued variables or
the Fisher’s exact test for categorical values. For Figure S11, we started with 195 samples from
41 patients. We removed samples with too few reads mapped to genes and samples that might be
white blood cells as was done in (7). This left us with 109 samples from 33 patients.
The survival analysis in Figure 4E begins with computing the average log10(RPM + 1) gene
expression for the core ribosomal proteins for each CTC or CTC-cluster. These are then
averaged for all the CTCs or CTC-clusters from a particular blood draw from a particular patient.
The resulting values are divided into high and low groups by Otsu’s method. The time to death
or loss of follow-up is computed from the date of the blood draw.
The CEL files from the microarray analysis of TGF-β treatment of MCF10A cells were
processed by the RMA method as implemented by Bioconductor. We applied the mapping from
probe-set ID to gene provided by Affymetrix. For each gene to which multiple probe-sets
mapped, the probe-set for which the unlogged RMA values had the highest variance was kept
and the others were discarded. For 3 or 6 days, the logged RMA values for the untreated
polysome fraction and total RNA were subtracted from the logged RMA values for the treated
polysome fraction and total RNA. The resulting values for the total RNA were then subtracted
from the values for the polysome fraction. The resulting difference was then provided as input to
the Broad Institute’s GSEA software running in pre-ranked mode and using version 6.0 of the
Broad Institute’s MSigDB.
Fig. S1.
Ribosome Crystal Structure: Solvent-facing (A) and subunit interface (B) view of the large
subunit of the ribosome with the central protuberance (CP), L1 stalk, L7/L12 and polypeptide
exit channel labeled. RPL13 (blue), RPL15 (red) RPL35 (green), 5.8S (pink), 5S (yellow), 25S
(tan), large subunit proteins (gray).
BA
Fig. S2.
Overexpression of RP Proteins: (A) Western blot for V5-tagged RPL8, RPL13, RPL35 and
RPL15 in RP-overexpressing CTCs and control. GAPDH as a loading control. (B) RT-qPCR for
RPL8, RPL13, RPL35 and RPL15 in RP-CTCs overexpressing the respective RP compared to
control CTCs. Error bars represent SEM.
A B
Ctr
l
RP
L8
RP
L13
RP
L35
RP
L15
0
1
2
3
4
3 0
4 0
5 0
Re
lati
ve
Ex
pre
ss
ion C tr l
R P L 8
R P L 1 3
R P L 3 5
R P L 1 5
Fig. S3.
RPL35 Overexpression Increases CTC Metastatic Potential: (A) Representative sections of
lung (left and middle panels) and ovarian (right panel) histology after staining with anti-GFP
antibody (brown) and counter-stained with hematoxylin from mice injected with RPL35-CTCs
or control. Scale bars: Left panel 200μm; Middle panel 50μm; Right panel 2mm. (B)
Quantitation of the number and size of tumor foci per cm2 identified by anti-GFP staining of lung
histologic sections from mice injected with RPL35-CTCs or control (n = 4 mice per group).
Error bars represent SEM. *: p<0.05 by two-tailed unpaired Student’s t test.
A
B
Fig. S4.
RPL15 Overexpression Increases Proliferation Without Affecting Apoptosis: Representative
sections of ovarian histology after staining with anti-Ki-67 (top) or anti-cleaved caspase-3
(bottom) antibody (brown) and counter-stained with hematoxylin from control and RPL15-CTC
mice. Scale bars: 50μm.
Fig. S5.
Quality Control for Ribosome Profiling of RPL15-CTCs and Control: (A) Histogram of the
read lengths of ribosome profiling. Short monosome-protected fragments (15-24 nt, orange),
long monosome-protected fragments (25-34 nt, black) and disome-protected fragments (40-80 nt,
purple). The distribution for each of the three colors is normalized to sum to 1. (B) Triplet
periodicity shown by histogram of the distance (in nucleotides) from the 5’ end of the read to the
start of the open reading frame in control (upper panel) and RPL15-CTCs (lower panel). (C)
Metagene analysis with a plot of the fragment length versus the distance from the 3’ end of the
read to the end of the CDS. Stop codon position indicated by ***. Color bar represents number
of reads. Upper panel representing metagene analysis from control CTC and middle panel from
RPL15-CTCs. For comparison, lower panel shows metagene analysis for a total RNA profile.
A
C
B
Fig. S6
Polysome Profiling of Control and RPL15 CTCs: (A) Polysome-to-monosome ratio of
indicated RP transcripts measured by RT-qPCR. Error bars represent SEM. ***: p<0.001 by
two-tailed unpaired Student’s t test. (B) Traces from polysome fractionation for control and
RPL15-CTCs. Shaded represent ribonucleotide protein peak (green), monosome peak (pink) and
polysome area (blue). (C) Ratio of the polysome-to-monosome area under the curve shown in
(B). Error bars represent SEM. *: p<0.05 by two-tailed paired Student’s t test.
A
C
B
Fig. S7.
Ribosomal content and global translation in RPL15-CTCs: (A) Measurement of total RNA as
a surrogate for ribosomal content. (B) Upper panel with global translation as measured by
median mCherry signal for control or RPL15-CTCs labeled with OP-Puro. Lower panel with
representative histogram of flow cytometric analysis. (C) Global translational activity of control
and RPL15-CTCs labeled with L-AHA and detected by Click-it chemistry. Error bars represent
SEM. *: p<0.05 by two-tailed paired Student’s t test.
A B C
Fig. S8.
Correlation Plot of E2F Targets for Ribosome Profiling with Proteomics: (A) Log2(fold
change) in RPL15-CTCs versus control for E2F target genes for ribosome profiling (y-axis) and
proteomics (x-axis). Pearson correlation with r2 = 0.1079; p<0.001 for two-tailed p value for a
non-zero slope.
***
Fig. S9.
A Subset of Patient-Derived CTCs Exhibits Coordinate RP Expression: Supervised
clustering of breast CTC samples based on RP gene expression. RP genes are listed in order of
decreasing variance in expression across the entire dataset.
Fig. S10.
Analysis of Gene Expression of Gene Sets within RP-High and RP-Low CTC Subsets: Dot
plot analysis of the mean log10(RPM +1) for all genes included in the indicated gene set: (A) core
ribosomal proteins, (B) proliferation signature, (C) Hallmarks of Cancer E2F targets, (D) EMT
signature.
A B
RP-HighRP-LowRP-High RP-Low
RP-High RP-Low
Me
an
lo
g1
0(R
PM
+1
)
Me
an
lo
g1
0(R
PM
+1
)
Me
an
lo
g1
0(R
PM
+1
)
C
RP-High RP-Low
Me
an lo
g 10(R
PM
+1)
D
Fig. S11.
Coordinate RP Expression in a Validation Cohort: Heat map of the expression level of RP
genes, selected E2F target genes and epithelial and mesenchymal genes. Dendrogram represents
supervised clustering of the CTC samples based on RP gene expression. Color bar illustrates
metagene analysis of core RPs, a proliferation signature, E2F targets, and an EMT signature and
associated p values.
Fig S12.
Analysis of Gene Expression of Gene Sets within RP-High and RP-Low CTC Subsets in a
Validation Cohort: Dot plot analysis of the mean log10(RPM +1) for all genes included in the
indicated gene set: (A) core ribosomal proteins, (B) proliferation signature, (C) Hallmarks of
Cancer E2F targets, (D) EMT signature.
A B
C
RP-High RP-Low RP-HighRP-Low
RP-HighRP-Low
Me
an
lo
g1
0(R
PM
+1
)
Me
an
lo
g1
0(R
PM
+1
)
Me
an
lo
g1
0(R
PM
+1
)
RP-High RP-Low
Me
an
lo
g1
0(R
PM
+1
)
D
Fig. S13.
Global Translation and Translational Regulation of RPs during EMT: (A) Global
translational activity detected by Click-it chemistry after labeling with L-AHA. Blot represents
labeling of untreated and TGF-β-treated MCF10A cells for 3 or 6 days. (B) Expression of rRNA
in control and TGF-β-treated MCF10A cells, as detected by RT-qPCR. Error bars represent
SEM. ***: p<0.001 by two-tailed paired Student’s t test. (C) GSEA for KEGG and Reactome
gene sets for genes depleted from polysomes compared to total RNA in MCF10A cells treated
with TGF-β for 6 days to induce EMT. (D) Scatter plot representing the translational efficiency
of individual RP gene transcripts in MCF10A cells treated with TGF-β. The y-axis represents the
log2(fold change in total RNA), and the x-axis represents the log2(fold change in polysome
fractions). The shaded region represents transcripts that have decreased translational efficiency
relative to the level of the transcript. (E) Heat map representing the log2(fold change) of total
RNA and polysome-associated RNA for the RPs in MCF10A cells treated with TGF-β for 6
days. Translational efficiency represents the ratio of polysome-associated transcripts to total
RNA.
A B
D
E
C
Fig. S14.
Ribosome Proteins are Enriched in the Genes Correlating with Worse Overall Survival:
(A) Volcano plot of the log2(hazard ratio) versus the -log10(FDR) demonstrating genes
correlating with better or worse overall survival. Highlighted are genes with hazard ratio >1.25
and FDR <0.25. (B) GSEA demonstrating enrichment for structural constituents of the ribosome.
(C) GSEA of genes that correlate with worse overall survival. Upper diagram represents the -
log10(Cox2 proportional hazard ratio p value) for each gene found within the gene sets listed in
the lower panel.
A B
C
Fig. S15.
Overall Survival of RPL15-high and RPL15-low CTCs: Kaplan-Meier analysis of the overall
survival for patients with high average RPL15 gene expression versus low average RPL15 gene
expression. The RPL15-high and RPL15-low subgroups were determined based on average
RPL15 gene expression for each patient blood draw. *: p<0.05 by log rank test.
Ov
era
ll S
urv
iva
l
Days
*
Fig. S16.
Expression of RPL Proteins or RPS Proteins Correlates with Poor Prognosis: Progression
free survival of breast cancer patients with high or low average large ribosome proteins (RPL)
(A) or small ribosome proteins (RPS) (B) expression from the KM Plotter website. High and low
expression is defined as above or below the median expression value.
RPL Proteins RPS Proteins A B
Fig. S17.
Treatment of Control and RPL15-CTCs with Omacetaxine: (A) Measurement of global
translation by OP-Puro flow cytometric assay in untreated and omacetaxine-treated CTCs. (B)
Heat map representing relative cell number for RPL15-CTCs and control treated with increasing
doses of palbociclib and omacetaxine.
A B
Table S1.
Overlap Between Genes Correlating with Poor Prognosis in the CTC Dataset and Publicly
Available Datasets
Data S1. (separate file)
CRISPRa Screen Results
Data S2. (separate file)
Clinical Outcome Data and Mutational Information For CTCs Collected from Metastatic Breast
Cancer Patients
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