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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