Supplementary Materials for

The transcription factor ATF2 promotes melanoma metastasis by

suppressing protein fucosylation

Eric Lau,* Yongmei Feng, Giuseppina Claps, Michiko N. Fukuda, Ally Perlina,

Dylan Donn, Lucia Jilaveanu, Harriet Kluger, Hudson H. Freeze, Ze’ev A. Ronai*

*Corresponding author. E-mail: eric.lau@moffitt.org (E.L.); zeev@ronailab.net (Z.A.R.)

Published 8 December 2015, Sci. Signal. 8, ra124 (2015)

DOI: 10.1126/scisignal.aac6479

The PDF file includes:

Methods

Fig. S1. Transcriptional regulation of FUK by ATF2 and L-fucose uptake in

melanoma cells.

Fig. S2. Increasing melanoma fucosylation slows motility and invasiveness.

Fig. S3. Increasing melanoma tumor fucosylation increases intratumoral CD45+ and

NKp46+ immune cell infiltrates.

Table S1. Primers.

www.sciencesignaling.org/cgi/content/full/8/406/ra124/DC1

Supplementary Methods: FUK and ATF2 expression correlation analysis of TCGA

cutaneous melanoma

Briefly, using Illumina HiSeq data from a TCGA cutaneous melanoma study (473

samples), we computed the correlation between FUK and ATF2 and visualized

expression patterns in the UCSC Cancer Genome browser (https://genome-

cancer.ucsc.edu/proj/site/hgHeatmap/; filename: TCGA_SKCM_exp_HiSeqV2-2015-02-

24.tgz; version: 2015-02-24). The data were acquired from the UCSC Genome browser

and analyzed as follows:

1. Follow this link:

https://genome-cancer.ucsc.edu/proj/site/hgHeatmap

2. Close out of the dataset displayed by default by hitting the blue “X” on the right side

3. Click “Add Dataset” gray button on the left

4. In the search window type SKCM and click to expand the folder called “SKCM skin

cutaneous melanoma.”

5. Hover over the dataset as shown below to see the download button and to also be

able to add the dataset to the browser, get more info, and perform analyses through

the browser web portal by clicking on the file itself:

when hovering over the file, clicking “i” will bring up the dataset info:

About Dataset: SKCM gene expression (IlluminaHiSeq)

TCGA skin cutaneous melanoma (SKCM) gene expression by RNAseq.

The gene expression profile was measured experimentally using the Illumina HiSeq

2000 RNA Sequencing platform by the University of North Carolina TCGA genome

characterization center. Level 3 interpreted level data was downloaded from TCGA data

coordination center. This dataset shows the gene-level transcription estimates, as in

RSEM normalized count. Genes are mapped onto the human genome coordinates using

UCSC cgData HUGO probeMap. Reference to method description from University of

North Carolina TCGA genome characterization center: DCC description

In order to more easily view the differential expression between samples, we set the

default view to center each gene or exon to zero by independently subtracting the mean

of the genomic location on the fly. Users can view the original non-normalized values by

uncheck the "Normalize" option. For more information on how to use the cancer

browser, please refer to the help page.

Processed

Data Download version: 2015-02-24

Label TCGA skin cutaneous melanoma (SKCM) gene expression by RNAseq

(IlluminaHiSeq)

Authors University of North Carolina TCGA genome characterization center

Raw Data

https://tcga-

data.nci.nih.gov/tcgafiles/ftp_auth/distro_ftpusers/anonymous/tumor/skcm/cgcc/

unc.edu/illuminahiseq_rnaseqv2/rnaseqv2/

# Samples 473

Dataset ID TCGA_SKCM_exp_HiSeqV2

Authorized

Project Public data

Wrangler cgData TCGAscript RNAseq processed on 2015-01-27

Wrangling

Procedure

Level_3 Data (file names: *.rsem.genes.normalized_results) download from

TCGA DCC, log2(x+1) transformed, and processed at UCSC into cgData

repository

Clinical

Fields

age at initial pathologic diagnosis

bcr_followup_barcode

breslow depth value

days to birth

days to collection

days to death

days to initial pathologic diagnosis

days to last followup

days to new tumor event additional surgery procedure

days to new tumor event after initial treatment

days to submitted specimen diagnosis

distant metastasis anatomic site

followup case report form submission reason

form_completion_date

gender

height

history of neoadjuvant treatment

ICD-O-3 histology

ICD-O-3 site

informed consent verified

initial weight

interferon 90 day prior excision admin indicator

International Classification of Diseases, tenth revision (ICD-10)

is_ffpe

lactate dehydrogenase result

lost follow up

malignant neoplasm mitotic count rate

melanoma clark level value

melanoma origin skin anatomic site

melanoma ulceration indicator

new neoplasm event occurrence anatomic site

new neoplasm event type

new non melanoma event histologic type text

new primary melanoma anatomic site

new tumor additional drug treatment

new tumor additional radiation treatment

new tumor diagnosis prior submitted specimen dx

new tumor event additional surgery procedure

new tumor event after initial treatment

new tumor metastasis anatomic site

new tumor metastasis anatomic site other text

OCT embedded (OCT is an embedding medium used for frozen tissue)

pathologic_M

pathologic_N

pathologic_stage

pathologic_T

pathology_report_file_name

percent_lymphocyte_infiltration_TOP

percent_monocyte_infiltration_TOP

percent_necrosis_TOP

percent_neutrophil_infiltration_TOP

percent_normal_cells_TOP

percent_stromal_cells_TOP

percent_tumor_cells_TOP

percent_tumor_nuclei_TOP

person neoplasm cancer status

postoperative drug treatment

primary anatomic site count

primary melanoma at diagnosis count

primary neoplasm melanoma diagnosis

primary tumor multiple present indicator

prior diagnosis

prior systemic therapy type

radiation therapy

sample type

sample type id

subsequent primary melanoma during followup

system_version

tissue prospective collection indicator

tissue retrospective collection indicator

tissue source site

tumor tissue site

vial number

vital status

weight

year of initial pathologic diagnosis

_anatomical_origin

_cohort

_EVENT overall survival indicator 1=death 0=censor

_GENOMIC_ID

_GENOMIC_ID_TCGA_SKCM_exp_HiSeqV2

_GENOMIC_ID_TCGA_SKCM_exp_HiSeqV2_exon

_GENOMIC_ID_TCGA_SKCM_exp_HiSeqV2_PANCAN

_GENOMIC_ID_TCGA_SKCM_exp_HiSeqV2_percentile

_GENOMIC_ID_TCGA_SKCM_gistic2

_GENOMIC_ID_TCGA_SKCM_gistic2thd

_GENOMIC_ID_TCGA_SKCM_GSNP6noCNV

_GENOMIC_ID_TCGA_SKCM_GSNP6raw

_GENOMIC_ID_TCGA_SKCM_hMethyl450

_GENOMIC_ID_TCGA_SKCM_miRNA_HiSeq

_GENOMIC_ID_TCGA_SKCM_mutation

_GENOMIC_ID_TCGA_SKCM_mutation_bcm_gene

_GENOMIC_ID_TCGA_SKCM_mutation_broad_gene

_GENOMIC_ID_TCGA_SKCM_mutation_ucsc_maf_gene

_GENOMIC_ID_TCGA_SKCM_mutation_ucsc_vcf_gene

_GENOMIC_ID_TCGA_SKCM_RPPA

_OS overall survival in days

_OS_IND overall survival indicator 1=death 0=censor

_PATIENT_ID

_primary_disease

_RFS recurrence free survival in days

_RFS_IND recurrence free survival indicator 1=new tumor; 0=otherwise

_SAMPLE_ID

_TIME_TO_EVENT overall survival in days

Following dataset info, more description was available from the following location:

https://tcga-

data.nci.nih.gov/tcgafiles/ftp_auth/distro_ftpusers/anonymous/tumor/skcm/cgcc/unc.edu/i

lluminahiseq_rnaseqv2/rnaseqv2/unc.edu_SKCM.IlluminaHiSeq_RNASeqV2.Level_3.1.

13.0/DESCRIPTION.txt:

V1_BWAtoTranscriptome, V1_RNASeqQuantification: UNC V1 RNA-Seq Workflow -

BWA Alignment to Transcriptome

Date: 20101108 Authors: * Sara Grimm <sacheek@med.unc.edu> * Brian O'Connor

<brianoc@email.unc.edu>

Versions: This analysis was carried out using the SeqWare Pipeline project, version

0.7.0. The workflow was "RNASeqAlignmentBWA" version 0.7.x. UNC provides all our

analysis software through this open source project. Users can download this software to

run the identical RNA-Seq analysis described in the steps below. See the project

website at http://seqware.sf.net for more information. The UNCIDs provided in file names

are identifiers unique to UNC and can be used to provide data/analysis provenance

tracking.

Conventions: Please note our spljxn.quantification.txt, exon.quantification.txt, and the

GAF file above use the convention of chr:smaller_int-larger_int:+ for plus strand features

and chr:larger_int-smaller_int:- for negative strand features. Carefully examine future

versions of these annotation and quantification files since this convension is subject to

change.

Column Headers: These are just brief descriptions of the column headers you will find in

the various level 3 files. See the DESCRIPTION.txt file in the mage-tab bunlde for more

detailed methods on how each of these files were created. File:

*.trimmed.annotated.gene.quantification.txt * gene: This is the Entrez/LocusLink gene

symbol followed by the Entrez/LocusLink gene ID. * raw_counts: The number of reads

mapping to this gene. * median_length_normalized: This is the total aligned bases to all

transcript models associated with this gene divided by the mean transcript length. *

RPKM: See the DESCRIPTION.txt file in the mage-tab bunlde for information on how

this is calculated. File: *.trimmed.annotated.exon.quantification.txt * exon: This is the

location of the exon in hg19 (GRCh37) based on the UCSC Gene standard track

(December 2009 version). * raw_counts: The number of reads mapping to this exon. *

median_length_normalized: This is the total aligned bases to this exon divided by the

exon length. * RPKM: See the DESCRIPTION.txt file in the mage-tab bunlde for

information on how this is calculated. File: *.trimmed.annotated.spljxn.quantification.txt

This file does not include normalized counts since splice junctions are a fixed size. *

junction: This is the location of the splice junction in hg19 (GRCh37) based on the

UCSC Gene standard track (December 2009 version). * raw_counts: The number of

reads mapping to this splice junction. File: *.wig This is a WIG file format that

represents coverage, see http://genome.ucsc.edu/FAQ/FAQformat.html#format6 for

more information.

V2_MapSpliceRSEM: UNC V2 RNA-Seq Workflow - MapSplice genome alignment and

RSEM estimation of GAF 2.1 Date: 05-10-2012 Contacts: * Lisle Mose

<lmose@email.unc.edu> * Joel Parker <parkerjs@email.unc.edu> Versions: This

analysis was carried out using the SeqWare Pipeline project, version 0.7.0. The

workflow was "MapspliceRSEM" version 0.7.x. UNC provides all our analysis software

through this open source project.

Conventions: Please note our junction_quantification.txt, exon_quantification.txt, and

the GAF file above use the convention of chr:smaller_int-larger_int:+ for plus strand

features and chr:larger_int-smaller_int:- for negative strand features. Carefully examine

future versions of these annotation and quantification files since this convension is

subject to change. Column Headers: RSEM abundance estimation results in two files,

gene and isoform level quantification. More information regarding the content of these

output files can be found on the RSEM website

(http://deweylab.biostat.wisc.edu/rsem/rsem-calculate-expression.html#output). In short,

the format indicates the feature name in column 1, esimated count in colum 2, scaled

estimate in column 3, and contributing isoforms in column 4 (gene level only). These

files will have the following extensions: rsem.genes.results rsem.isoforms.results

RSEM expression estimates are normalized to set the upper quartile count at 1000 for

gene level and 300 for isoform level estimates. These files have two columns, feature

name and normalized count, and correspond to the following extensions:

rsem.genes.normalized_results rsem.isoforms.normalized_results Exon and junction

level quantification are provided in a similar format as described for V1, although the

Mapsplice genome alignments are used for overlap counting in V2. The exon counts are

formatted as exon location in column 1 (hg19 based on the UCSC Gene standard track,

December 2009 version), number of reads in column 2, fraction of bases covered in

column 3, and RPKM (calculated as described for V1) in column 4. The exon count files

have the extension: bt.exon_quantification.txt The file format for junction counts is

identical to V1 and has the extension: junction_quantification.txt

6. After clicking on the file name, the dataset thumbnail will appear on the left and the

current info window can be closed. Click on the thumbnail to start exploring the

dataset and switch from “chromosome” to “gene” view

7. Click “Advanced Genes” and type in FUK, then ATF2

8. Click on gene signatures to set FUK as a gene signature containing FUK and ATF2

as the gene signature containing ATF2

9. To visualize differential expression between samples, the default view was set to

center each gene at zero by independently subtracting the mean of the genomic

location. The gene signatures feature was used to create two custom gene

signatures one each exclusively for FUK and for ATF2, where the FUK expression

signature was mobilized to the leftmost column and sorted from lowest to highest

expression on the final display. The range of values was set from -1 (lowest, green)

to 1 (highest, red).

10. This data was also downloaded and used for heatmap generation outside of the

cancer browser for extra confirmation purposes, and the same results were

achieved.

Specifically for the generation of fig. S1C, which used the dataset from above: the

correlation coefficient calculation was derived from Pearson Product-Moment Correlation

formula. The gene expression profile was measured experimentally using the Illumina

HiSeq 2000 RNA Sequencing platform by the University of North Carolina TCGA

genome characterization center. Level 3 interpreted level data was downloaded from

TCGA data coordination center. This dataset shows the gene-level transcription

estimates as RSEM normalized counts. Genes are mapped onto the human genome

coordinates using UCSC cgData HUGO probeMap. Method description available here:

https://tcga-

data.nci.nih.gov/tcgafiles/ftp_auth/distro_ftpusers/anonymous/tumor/skcm/cgcc/unc.edu/i

lluminahiseq_rnaseqv2/rnaseqv2/unc.edu_SKCM.IlluminaHiSeq_RNASeqV2.Level_3.1.

13.0/DESCRIPTION.txt

Figure S1. Transcriptional regulation of FUK by ATF2 and L-fucose uptake in

melanoma cells. (A) Upper: (left) qRT-PCR analysis of ATF2 knockdown using shATF2

in WM793 cells. These knockdown cells were used for reconstitution transfection with

ATF2 WT and T52 mutants as shown in the immunoblot analysis (right) of WM793 cells

transfected with HA-tagged ATF2WT, ATF2T52A, and ATF2T52E using the indicated

antibodies. Lower: FUK mRNA expression were quantitated by qRT-PCR in WM1346

(left) and WM1366 (right) melanoma cells that were infected either with control shRNA

(EV) or endogenous ATF2-targeted shRNA (shATF2), or shATF2 and reconstituted with

ATF2WT, ATF2T52A, or ATF2T52E. (B) qRT-PCR analysis of FX, FPGT (isoforms 1, 2, and

3), and GMD (isoforms 1, 2) in WM793 cells that were depleted of endogenous ATF2

and reconstituted with ATF2WT (black), ATF2T52A (dark grey) or ATF2T52E (light grey). No

significant variation in expression was observed. (C) The heatmap shows gene-level

RNA-Seq expression values for 473 melanoma samples from a study obtained from

TCGA. The samples were ordered according to FUK expression, lowest (green) to

highest (red). Each horizontal line corresponds to a sample. ATF2 gene-level data is

displayed side-by-side with that of FUK, but was not used for ranking or sorting the

samples. This visually recapitulates the inverse correlation calculated for these genes (-

0.36). (D) Left: Immunoblot analysis of WM793 cells transfected with empty vector (EV),

HA-tagged ATFT52E, or caPKC using the indicated antibodies. Right: qRT-PCR analysis

of FUK mRNA expression in the presence or absence of shFUK-A3 or shFUK-B3.

shFUK-B3 was used in all other experiments and referred to as “shFUK”. (E) WM1346

(upper) and WM1366 (lower) were transfected with either empty vector (EV), ATF2T52E,

or caPKC for 48 hours, and subjected to immunoblot analysis with indicated antibodies

(left) or probed with either UEA1, LCA, or PSA lectins, and subjected to FACS analysis

(right). (F) UEA1 FACS analysis was performed to measure fucosylated protein

abundance in 501Mel (left) or LU1205 (right) cells transfected with empty vector (EV) or

FUK. (G) FACS analysis of UEA1 signal in the presence of the indicated concentrations

of supplemented L-fucose for a 36-hour treatment period in WM793 (left) and WM1346

(center), or WM1366 (right) cells. (H) Left: Soluble [H3]-L-fucose uptake assessment of

WM793, WM1346, HEK293, and 501Mel cells after 1 hour of labeling followed by

scintillation counts of soluble fractions. No significant variation in uptake was observed.

Right: Quantitation of phosphorylated (fucose-1-phosphate) by QAE binding and

scintillation counting of soluble [H3]-L-fucose fractions from WM793, WM1346, 501Mel,

and HEK293 cells. Data are means ± SD from 3 biological replicates. * p < 0.05. • p <

0.005 by a standard t-test of individual conditions or time points compared to either EV,

shCTL, or to 0 hour time point.

Figure S2. Increasing melanoma fucosylation slows motility and invasiveness. (A)

FACS analysis of UEA1 on 501Mel cells treated with control (5 µl water) or 25 µM ac-

GDP-L-fucose. (B) WM1346 (left) or WM1366 (right) cells were transfected with empty

vector (EV), ATF2T52E, or shFUK and subjected to a scratch assay over a 6-hour period.

(C) UEA1 FACS analysis of HEK293 cells transfected with empty vector (EV) or FUK.

(D) Empty vector (EV)- or FUK-expressing LU1205 spheroid invasion into Matrigel plugs

was quantitated over the indicated time points. (E) Empty vector (EV)- or FUK-

expressing HEK293 spheroid invasion into Matrigel plugs over the indicated time points

(left and center), as well as migration through transwells (right) was assessed.

Representative spheroid images (left) and quantitation of invasion (center) are shown.

Red dashed lines indicate invaded boundaries of spheroids. Data are means ± SD from

3 biological replicates for UEA1 and wound healing assays; spheroid invasion assay

results were derived from 5 spheroids per condition. * p < 0.05; • p < 0.005 by a standard

t-test of individual time points compared to 0 hour time point. Scale bars, 100 µm.

Figure S3. Increasing melanoma tumor fucosylation increases intratumoral CD45+

and NKp46+ immune cell infiltrates. (A) Quantitation of protein fucosylation as a

measure of UEA1 staining (within DAPI area) of tumor sections from 3 representative

tumors of control or 100 mM L-fucose-supplemented mice. Fluorescence is relative to

that in the representative control, tumor #1. (B) qRT-PCR analysis of mFuk mRNA

expression of 3 representative EV- and mFuk-expressing tumors. mFuk expression

shown is relative to representative EV tumor #1. (C) Quantitation of UEA1 staining

(within DAPI area) of tumor sections from 3 representative EV- or mFuk-expressing

tumors from mice provided control water or 100 mM L-fucose (Fucose)-supplemented

water. (D and E) Representative CD45-positive (D) or NKp46-positive (E) tumor sections

[counter stained with 4',6-diamidino-2-phenylindole (DAPI)] from control or 100 mM

fucose-supplemented mice. (F and G) Quantitation of CD45-positive (F) or NKp46-

positive (G) cells in 3 representative EV- or mFuk-expressing tumors from control water-

or 100mM L-fucose (Fucose)-supplemented water mice. • p < 0.005; # p <0.0005 by a

standard t-test of individual conditions compared to control or EV samples. Scale bars,

100 µm. Insets are magnified 3-fold from the original image.

Primer Sequence (5’-3’)

FUK promoter

Wild-type, full-length f: CGCGGAATTCATGCAGTTCTCAGCTTGACTTTTCCC r: CGCGAAGCTTCAGCTGCCAGCAGGTCCG

E1 site mutant f: CTTTTCCCTTCACCTTAGTGACTTTGGG r: TCAAGCTGAGAACTGCATAG

E2 site mutant f: GGCAGGTACGGAGGTCCGCGAGGGTCGCCG r: GTCGCCCGGCGCTCGGCG

E3 site mutant f: GCACCCTCCCCACCTGGGAGCACC r: ACCGGAAAGCTGAGGGGG

qRT-PCR

H3A (human and mouse)

f: AAGCAGACTGCCCGCAAAT

r: GGCCTGTAACGATGAGGTTTC

FUK (human) f: CAGATTGTGCACTCCCAGGT

r: CTGTATCCAGGCCAGTCACC

Fuk (mouse) f: ACTTCCGCCGAGATCTGTTC

r: GGATCAGTGGACGTAGGCAG

PRKCE (human,

encodes PKCε)

f: TGACGTGGACTGCACAATGA

r: CCATGCTGGTGGAGGAACAT

Prkce (mouse) f: CTCTCCAGTCTTGGTCCCAT

r: CGAACGTTTCAAACCACAAC

FUK promoter, E1 site f: TTCCCAAAAGGTCCGCAGAT

r: GGTTTGCGCTGGTTTCATCA

FUK promoter, E2/3 site f: ATCTCCCTTCTGGATTGCAGC

r: CGGACTGACGTACCTGCC

Expression vector

mouse Fuk construct

(mFuk)

f: CGCGCGTCTAGAATGGAGCAGTCAGAGGGAGTCAATTG r:

CGCGCGGCTAGCCTAGGTGGTGCCCACTTCAGAG

Table S1: Primers. Sequences (shown 5’ to 3’) for the primers used in this study. f, forward; r, reverse.