images.nature.com · Web viewSingleQuot Kit Supplements & Growth Factors, and as negative control...

Canonical WNT signaling in Hodgkin Lymphoma

SupplementarySupplementary Methods

Cell culture

The HL cell lines L428 and KM-H2 were cultured in RPMI1640 medium with 2 mM

glutamine (Lonza, Basel, Switzerland) supplemented with 10 % fetal calf serum

(Biochrom AG, Berlin, Germany), 200 U/ml Penicillin and 200 μg/ml Streptomycin (both

Sigma-Aldrich, St. Louis, USA). Cells were maintained at 37 °C in 5 % CO 2 and seeded

at a density of 5 x 105 cells/ml the day before the experiment.

Stable LEF-1 knockdown KM-H2 cells have been generated by lentiviral transduction of

KM-H2 with the GIPZ plasmid containing either LEFsh or nonsense (ns) sequence (GE

Healthcare Dharmacon, Lafayette, USA). Successfully transfected KM-H2 cells have

been selected using 2 µg/ml puromycin.

Human Umbilical Vein Endothelial Cells (HUVEC) cells were cultured in EBM2 medium

supplemented with EGM-2 MV SingleQuot Kit Supplements & Growth Factors (all

Lonza, Basel, Switzerland). For the experiments HUVEC cells with a confluence of 80-

90% and till passage six have been applied.

All cell lines have been tested regularly for mycoplasma contamination.

HL-cell conditioned medium

For the production of conditioned HL medium L428 or KM-H2 cells have been seeded at

a density of 5 x 105 cells/ml and incubated in RPMI 1640 medium supplemented with 10

% (v/v) FCS, 200 U/ml Penicillin and 200 μg/ml Streptomycin for two days. Cell

supernatant was centrifuged at 300 g for 10 minutes at 4 °C, sterile filtered and stored at

4 °C for a maximum of two weeks.

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VEGF-A ELISA

VEGF-A ELISA (Human VEGF Quantikine ELISA Kit, R&D, Minneapolis, USA) has been

performed with the indicated CMs of siRNA transfected L428 and KM-H2 cells according

to the manufacturer’s instructions or as published before (1).

Inhibitor treatment

For inhibition of the canonical WNT pathway the CKI inhibitor PF670462, the tankyrases

inhibitor XAV939 (both Millipore, Billerica, USA) or DKK1 and DKK2 (both R&D,

Minneapolis, USA) have been added to the cell culture medium at a final concentration

of 50 nM (PF670462) or 5 µM (XAV939) or 100 ng/ml (DKK1, DKK2) in DMSO

(PF670462, XAV939), PBS (DKK2) or PBS with 0.1 % BSA (DKK1) respectively for 24

hours.

Nucleofection

For nucleofection of siRNA the corresponding Cell Line Nucleofector Kit L (for L428) or T

(for KM-H2) (both Lonza, Basel, Switzerland) has been used according to the

manufacturer’s instructions. After the nucleofection, cells were incubated in pre-warmed

RPMI 1640 supplemented with 10 % (v/v) FCS, 200 U/ml Penicillin, 200 μg/ml

Streptomycin, 1 mM Sodium pyruvate and 10 mM Hepes for 48 hours at 37 °C in

5 % CO2. Knock-down quality was verified with qRT-PCR and immunoblotting.

Applied siRNA (2 µg siRNA per two million cells) included LEF-1 (pool of ID108840,

IDs27618, IDs27617, IDs27616) (Life Technologies, Carlsbad, USA), β-catenin (pool of

ID J-003482-09, ID J-003482-12) (GE Healthcare Dharmacon, Lafayette, USA).

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Adhesion assay

Briefly, 96 well plates were coated with 1 mg/ml type-collagen (Trevigen,

Gaithersburg, USA) or seeded with HUVEC cells overnight. Pretreated HL cells were

added to the wells (15.000 cells/well in 320 μl) in quadruplicates and incubated for 1

hour at 37 °C in 5 % CO2. For discrimination between adherent and non-adherent cells

the plate was turned up-side down and incubated for 2 more hours at 37 °C in 5 % CO2.

While holding the plate still up-side down the supernatant with the non-adherent cells

was carefully transferred to a second plate. In addition, for standard curve calculation

five different cell concentrations were added to this second plate. To quantify cell

numbers MTT solution to a final concentration of 0,5 mg/ml was added and incubated

with the non-adherent cells, and the cells for the standard curve for 3 hours at 37 °C in 5

% CO2. Optical density was determined at 560 nm using Tecan Infinite F50 Reader

(Tecan Group Ltd., Männedorf, Switzerland). Standard curves were calculated for each

condition and the amount of adherent cells was presented in percentage of the total

number.

Migration, Invasion and Chemotaxis Assays

5x104/50 µl L428 or KM-H2 cells per well in RPMI 1640 medium migrated for 6 hours

towards RPMI 1640 supplemented with 10 % (v/v) FCS and 50 nM CCL19. For analysis

only the migrated cells in the lower chamber were counted. Cell migration towards

RPMI 1640 medium of the control cells was set as one.

For invasion assays the membrane was coated with 1 mg/ml type-1 collagen (Trevigen,

Gaithersburg, USA) and invasion was measured after 16 hours as described above.

For HUVEC invasion assay the Boyden chamber with 8 µm porous membranes coated

with 1 mg/ml type-collagen (Trevigen, Gaithersburg, USA) was used. 1.5x104/50 µl

HUVEC cells per well migrated for 4 hours towards the conditioned media (CM) of cHL

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cell lines as indicated. As positive control EBM2 medium supplemented with EGM-2 MV

SingleQuot Kit Supplements & Growth Factors, and as negative control RPMI medium

(all Lonza, Basel, Switzerland) were used. For analysis, the upper side was cleaned

from resident HUVECs. The specimens were fixed with 4% PFA, stained and

photographed at 100x magnification. In three representative photos per well migrated

cells were counted and the mean calculated.

For monitoring real-time cell movements KM-H2 cells (3 x 106 cells/ml) in 1,5 mg/ml

type-1collagen were added into the µ-Slide chemotaxis3D chamber (Ibidi, Martinsried,

Germany). Chemotaxis against 10 % (v/v) FCS and 50 nM MIP-3β was documented for

6 hours with one photo per 5 minutes by time-lapse microscopy (Olympus IX81 with

Olympus XM-10 camera; Olympus, Shinjuka, Japan). For trajectory analysis of 50 cells

per condition ImageJ 1.45s (National Institutes of Health, Bethesda, USA) and the Ibidi

software “Chemotaxis and Migration Tool” were used. Cell track analysis using shape

fingerprint descriptors is described below.

Cell track analysis using shape fingerprint descriptors – a.k.a. autocorrelation vector analysis

To derive a condensed depiction for the observed track space, we performed an

analysis using 2D shape fingerprints, which were derived from the internal distance

distribution for each track, like it is common for the shape description of chemical

compounds in cheminformatics (2).

Software

We used KNIME version 2.11.3 (3) to organize the analysis of cell tracks and perform

preprocessing, the final analysis steps like deriving the fingerprints, hierarchical

clustering and plotting where done with corresponding R-nodes in KNIME using R

version 3.0.2. (4).

Deriving cell track fingerprints

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To derive the individual track fingerprint we implemented the following steps as an R

function:

1. Generating intra-track distance matrices per track →we transformed the xy-coordinate

collection for each track into an individual distance matrix representation, thus mapping

the occurring internal distances of each track.

2. Estimating the binning parameters → To achieve a comparable scaled binning of the

resulting correlation vectors we scanned the individual track distance matrices for the

global max distance reported, then we used the global maximum of intra-track distances

to set the binning algorithms required max distance to be used for all tracks. The

number of bins was set to n=100; which seems a reasonable choice given that 50 time

steps were recorded per track and the global max distance was ≈ 250 μm, while a

typical eukaryotic cell diameter is ≈ 10 µm.

3. Deriving the shape fingerprints → The use of a binning vector function (using a range

[0; global_max_distance], and #_of_bins = 100), allowed to transform each distance

matrix into a correlation vector representation. For each occurring distance within a track

the corresponding bin position to count up in the n-dimensional correlation vector can be

simply calculated using: bin_position = floor((current_distance –

global_minimal_distance) / (global_max_distance – global_minimal_distance) *

#_of_bins).

4. Resulting correlation vector table containing fingerprints →having derived the shape

fingerprint vector for each track we used the vector representations for our similarity

calculations; e.g., hierarchical clustering, heat map representations

Similarity analysis using cell track fingerprints

We used the fingerprints to explore the track space. The analysis can be divided into the

following sequential steps:

1. Hierarchical clustering of the tracks → We used the fingerprints to derive dendrogram

representations of the track space using Manhattan distance for all distance calculations

and complete linkage method for the tree construction.

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2. Identifying the main clusters → we used the cut-tree function to derive the main

clusters in track space.

3. Identifying cluster representatives → for each cluster we derived the representative

track, by identifying the track fingerprint with the smallest cumulative distance to the

other cluster members.

4. Mapping tracks from different experiments to the clusters → after successful

inspection of the cluster representatives to represent the required distinction level, we

mapped the tracks respective experiment type to the dendrogram leafs. Extracting the

cluster group members we thus could derive the count of the tracks per experiment per

cluster. Finally scaling the count per experiment resulted in the relative distribution of

track types per experiment.

Scratch Assay

HUVECs were grown to 80% density and scratched using a pipette tip. Cells were

washed twice with PBS and incubated with pGIPZ-KM-H2 conditioned medium in equal

parts with EBM2 medium supplemented with EGM-2 MV SingleQuot kit, supplements

and growth factors (all Lonza, Basel, Switzerland). Photos of the scratch were taken for

each well and cells incubated for 16 hours at 37 °C in 5% CO2. HUVECs of the positive

controls (complete EBM2 medium supplemented with EGM-2 MV SingleQuot kit,

supplements and growth factors) closed the scratch completely. Photos were taken for

each well at the previously marked positions. For each well the relation between the

width of the scratch after 0 hours and 16 hours was measured and calculated using

ImageJ software 1.45s (National Institutes of Health, Bethesda, USA).

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Sprouting Assay

Sprouting was studied with endothelial spheroids. For spheroid generation, HUVECs

were mixed with 1.2% methyl cellulose in EC medium and incubated in 96 well plates for

24 hours Spheroids formed, which were harvested and seeded with Matrigel (BD

Bioscience, Franklin Lakes, USA) mixed with one part matrigel and two parts KM-H2

conditioned medium in 96-well plates for 48 hours. At least 12 spheroids were used per

condition. For positive controls spheroids were seeded with EBM2 medium

supplemented with EGM-2 MV SingleQuot Kit supplements and growth factors (Lonza,

Basel, Switzerland). Photos of each spheroid were taken after 48 hours and sprouting

frequency was calculated as relation between sprouted spheroids and totally seeded

spheroids per condition. From each spheroid sprout numbers and total sprout length

were calculated with ImageJ software 1.45s (National Institutes of Health, Bethesda,

USA).

Tube Formation Assay

HUVECs were seeded as single cell suspension in Matrigel (BD Bioscience) mixed with

two parts of the particular cHL conditioned medium and one part EC medium in 96-well

plates. Four wells per condition were used. After 24 hours, tubes formed throughout the

well. Three photos per well were taken and total tube lengths was measured using

ImageJ software 1.45s (National Institutes of Health, Bethesda, USA).

Western Blot

Cells were lysed in NP-40 lysis buffer (50mM tris (pH 7.4), 150mM NaCl, 1mM EDTA,

0.5% NP-40) and 20 µg of total protein was used for SDS page. SDS page was used for

size-fractionation of the proteins, which were transferred to Immobilon PVDF

membranes (Millipore, Billerica, USA). Blots were air-dried, rehydrated and incubated in 7

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blocking buffer (5 % BSA or milk powder, 0.1 % Tween in tris-buffered saline) at room

temperature for one hour and afterwards incubated with primary antibody in blocking

buffer overnight at 4 °C. After washing, blots were incubated with the respective

peroxidase-coupled secondary antibody for 1h at room temperature. Enhanced

chemiluminescence detection was used to visualize the immune reaction (Image Reader

LAS-4000mini, Fujifilm). For re-probing with other antibodies blots were incubated in

Reblot Mild Plus Buffer (Millipore, Billerica, USA) at room temperature for 15 minutes.

For Wnt5a immunoblotting lysates have not been boiled for SDS page but transferred

semi-dry onto a nitrocellulose membrane (Life Technologies, Carlsbad, USA).

Micro-CT scans of CAM tumors

CT scans of the PTA stained and agarose gel embedded samples have been performed

with the Phoenix Nanotom CT (GE Measurement & Control, USA) . The system was

operated with the following parameters: tube voltage 100 kVp, tube current 135 µA, 360°

rotation with 1800 projection images, exposure time per projection 250ms, detector

binning 2x2 resulting in a pixel size of ~ 5 x 5 x 5 μm3. In order to increase the signal-to-

noise ratio every projection data has been acquired six times and averaged.

Vascularization Score of CAM tumors

Vascularization index is based on three criteria: appearance of hemorrhages, intensity

of hemorrhages and relative area covered by hemorrhages. For each criterion, zero to

three points were given, leading to a maximum of nine points per tumor. For the

evaluation process light microscopic pictures of each tumor were blinded and then

evaluated by a group member, who was not involved in the experiments.

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Microarray data analyses

Analysis of available microarray mRNA expression data was conducted using the

Oncomine web platform (Life Technologies) (5). The Steidl Lymphoma, Brune

Lymphoma and the Basso Lymphoma datasets were used (6–8). In the Steidl study 130

HL samples were analyzed using Human Genome U133 Plus 2.0 Array (19 574 genes,

54 675 reporters). To determine the cut-off for high and low VEGFA gene expression

levels the software Cut-off Finder was used (9). In the Brune study 42 malignant

lymphoma samples and 25 normal B-cell samples of various types were analyzed using

as well the Human Genome U133 Plus 2.0 Array. In the Basso study 336 B-cell samples

(normal, tumor, cell line, and cell line perturbation samples) were analyzed using the

Affymetrix U95Av2 Array (8,603 genes, 12,651 reporters). Data were analyzed using

GraphPad Prism 6.04 (GraphPad Software Inc., La Jolla, USA).

Preparing FFPE tissue blocks

Hodgkin and other lymphoma cases from all age groups that were routinely diagnosed

between 2001 and 2014 were identified within the files of the Lymph Node Registry Kiel.

Lymphoma biopsy specimens were routinely fixed in 10% buffered formalin, embedded

in paraffin (FFPE), cut into 3-5 µm sections and mounted on coated glass slides for

conventional immunohistochemistry.

Preparing Tissue Micro Arrays

Cases with sufficient FFPE tissue were arranged in a tissue microarray (TMA) with

duplicate cores 0.6 mm in diameter for each lymphoma. TMA and whole tissue sections

were subsequently subjected to immunohistochemistry.

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Immunohistochemistry on FFPE sections

The 3-5 µm paraffin TMA and whole tissue sections were placed onto coated glass

slides and dried over night at 37°C. Deparaffinization steps were followed by hydration.

The conventional immunohistochemical staining for LEF-1 was carried out according to

standard procedures including endogen peroxidase blocking (10 min in methanol/H2O2)

and antigen retrieval (3 min at 100°C in 10 mM citrate buffer, pH 6.0) prior to incubation

with the rabbit monoclonal anti-LEF-1 antibody (#2230S, Cell Signalling, Frankfurt,

Germany) at a dilution of 1:50 for 1 h. The detection was performed using the

ZytoChemPlus (HRP) Polymer Bulk Kit (Zytomed Systems GmbH, Berlin, Germany).

The counterstaining was performed with Haemalaun after Meyer (1:4) (Merck,

Darmstadt, Germany) for 3-5 min and rinsing in water for 10 min. After dehydration the

section was covered with the mounting medium Pertex (Histolab Products AB;

Göteborg, Sweden).

The double-staining for LEF-1 and CD3 was performed according to the standard

procedure described above for LEF-1. The mouse monoclonal anti-CD3 antibody

(#NCL-L-CD3-565, NovoCastra, XXX) was applied at a dilution of 1:100 for 1 h together

with the anti-LEF-1 antibody further following the described protocol.

Scoring system of immunohistochemical stainings

Whole tissue slides and Tissue Microarrays of lymphoma samples were scored

according to their percentage content of LEF-1 positive tumor cells from 0 to 4 (0=0%;

1=1-25%; 2=26-50%; 3=51-75%; 4=76-100%).

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Chick Chorio-Allantoic Membrane (CAM) Assay

Chicken eggs (Valo BioMedia GmbH, Osterholz-Scharmbeck, Germany) have been

bred and regularly turned for 4 days at 37.8 °C and 80 % air humidity. For the in ovo

assay, an approximately 0.75 cm² window has been sawed into the egg shell at the

fourth day of chicken embryo development. For the ex ovo assay, eggs have been

cracked into small bowls and incubated in cell culture flasks for the following days. At

day eleven of chicken embryo development 2x106 L428 cells or 3x106 KM-H2 cells each

embedded in 20 µl Matrigel (BD Bioscience, Franklin Lakes, USA) were inoculated onto

the CAM. After 4 days of incubation on the CAM tumors have been cut out, evaluated,

photographed (Motic SMZ-161, Motic Asia, Hong Kong, China; camera: Moticam 3.0)

and fixed either in Bouin’s solution or 4 % paraformaldehyde solution with a subsequent

ascending series of saccharose. For histological analysis tumors were embedded in

paraffin or Tissue Tek (Poysciences Inc., Warrington, USA) and cut into 3 µm or 11 µm

thick sections. Tumor areas have been measured using the light microspcopy photos

and ImageJ software 1.45s (National Institutes of Health, Bethesda, USA). CAM tumors

smaller than 0.1 cm2 were excluded from the evaluation because those “tumors” were

considered as matrigel rest and not as grown tumors.

Quantification of intracellular metabolites using NMR spectroscopy

Sample preparation: Acetonitrile extraction (10) was employed to quench cell

metabolism and to quantitatively extract low molecular weight compounds from HL cell

lines. Acetonitrile fraction was subjected to overnight lyophilisation. Dried extracts were

resuspended in 550 µl of D2O (Sigma-Aldrich) containing 0.005% sodium 3-

(trimethylsilyl)propionate-2,2,3,3-d4 (TSP) (Sigma-Aldrich) used as both chemical shift

reference and internal standard for metabolite quantification.

NMR spectroscopy: Information on concentration of metabolites in individual samples

was derived from volumes of corresponding signals in 1D 1H NMR spectrum.

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Assignment of signals in NMR spectra of individual samples to particular metabolite was

achieved via comparison of a sample spectrum with spectra of pure metabolites (Sigma-

Aldrich). The 1D 1H spectra were measured at 700 MHz using a Bruker Avance III NMR

spectrometer equipped with a triple resonance room temperature probe using the

WATERGATE pulse sequence (11), including 1-ms rectangular selective pulses to

suppress the residual signal of water. All spectra were acquired at 20ºC and processed

using TopSpin 3.2 (Bruker, USA). To make comparison of metabolite concentration

profiles among various samples possible, the signals intensities in individual samples

were normalized to total protein concentration.

Flow cytometry

Cells were stained with saturating amounts of antibody for 20 min at 4°C in PBS

supplemented with 1% FCS and washed two times with PBS. Samples were collected

on a FACSCantoII flow cytometer (BD Bioscience, Franklin Lakes, USA) and data

analyzed using the FlowJo software (FlowJo LLC, Ashland, USA). Cells were gated

based upon their forward and side scatter parameters for size, shape and granularity.

FSC-A/FSC-H plots were used to gate on single cells. Mean fluorescence intensity ratios

(MFIRs) were calculated by dividing the mean fluorescence intensity for CCR7 by the

mean fluorescence intensity of the isotype control.

Statistical Analyses

Results are shown as mean or as mean ± standard deviation (mean ± SD) of the

indicated number of samples. The statistical significance of the values was determined

using the Student's t-test. If applicable group results were compared using the ANOVA-

method (One-way or Two-way Analysis of Variance) with a subsequent Bonferroni’s

post-hoc test to correct for multiple comparisons as indicated. Normal distribution and

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homogeneity of variance has been tested using the Kolmogorov–Smirnov Test and the

F-test. For nonparametric group results Kruskal-Wallis test with Dunn’s post-hoc test has

been performed. Significance levels are indicated as *=p<0.05, **=p<0.01, ***=p<0.001.

All statistical analyses and plots were done with GraphPad Prism 6.04 (GraphPad

Software Inc., La Jolla, USA).

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Supplementary References

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3. Berthold MR, Cebron N, Dill F, Gabriel T, Kötter T, Meinl T, et al. KNIME: The

Konstanz Information Miner, In Studies in Classification, Data Analysis, and

Knowledge Organization. GfKL 2007. Springer International Publishing; 2007.

4. Development Core Team, R: A language and environment for statistical

computing. R Foundation for Statistical Computing, Vienna, Austria. 2011.

5. Rhodes DR, Yu J, Shanker K, Deshpande N, Varambally R, Ghosh D, et al.

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Platform1. Neoplasia. 2004;6:1–6.

6. Steidl C, Lee T, Shah SP, Farinha P, Han G, Nayar T, et al. Tumor-Associated

Makrophages and Survival in Classic Hodgkin’s Lymphoma. N Engl J Med.

2010;362:875–85.

7. Basso K, Margolin AA, Stolovitzky G, Klein U, Dalla-Favera R, Califano A.

Reverse engineering of regulatory networks in human B cells. Nat Genet.

2005;37:382–90.

8. Brune V, Tiacci E, Pfeil I, Döring C, Eckerle S, van Noesel CJM, et al. Origin and

pathogenesis of nodular lymphocyte-predominant Hodgkin lymphoma as revealed

by global gene expression analysis. J Exp Med. 2008;205:2251–68.

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9. Budczies J, Klauschen F, Sinn B V., Gyorffy B, Schmitt WD, Darb-Esfahani S, et

al. Cutoff Finder: A Comprehensive and Straightforward Web Application Enabling

Rapid Biomarker Cutoff Optimization. PLoS One. 2012;7:1–7.

10. Dietmair S, Timmins NE, Gray PP, Nielsen LK, Krömer JO. Towards quantitative

metabolomics of mammalian cells: development of a metabolite extraction

protocol. Anal Biochem. 2010;404:155–64.

11. Piotto M, Saudek V, Sklenár V. Gradient-tailored excitation for single-quantum

NMR spectroscopy of aqueous solutions. J Biomol NMR. 1992;2:661–5.

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Supplementary Figures

Suppl Fig S1

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Suppl Fig S9

Case Processing Summarya,b,c

Cases

Valid Missing Total

N Percent N Percent N Percent

40 88,9 5 11,1 45 100,0

a. Protein factor = 1

b. Squared Euclidean Distance used

c. Average Linkage (Between Groups)

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Supplementary Figure Legends

Supplementary Figure S1: Inhibition of canonical WNT signaling inhibits CCL19 guided chemotaxis of L1236 cells.

(A) Migration of L1236 cells for 6 hours after 24 h pre-treatment with 100ng/ml DKK1,

DKK2 or DKK1 plus DKK2 was performed towards CCL19 in Boyden chamber assays.

(mean ± SD, n=3; Kruskal-Wallis test,). (***P < 0.001)

(B) Migration of L1236 cells for 6 hours after 24 h pre-treatment with 5 µM XAV939 or

0.05 µM PF670462 was performed towards CCL19 in Boyden chamber assays. (mean

± SD, n=3; 1-way ANOVA and Bonferroni’s post-hoc test). (***P < 0.001)

Supplementary Figure S2: Inhibition of canonical WNT signaling does not affect cHL cell viability.

(A) Relative cell numbers of L428 and KM-H2 after 24 hours treatment with DKK1 and

DKK2. (mean ± SD, n=3, 2-way ANOVA with Bonferroni’s post-hoc test).

(B) Relative cell numbers of L428 and KM-H2 after 24 hours treatment PF670462.

(mean ± SD, n=3, 2-way ANOVA with Bonferroni’s post-hoc test)

(C) Relative cell numbers of L428 and KM-H2 after 24 hours treatment XAV939. Of note,

no significant difference in cell viability has been caused by inhibitor treatments. (mean ±

SD, n=3, 2-way ANOVA with Bonferroni’s post-hoc test)

Supplementary Figure S3: CCR7 cell surface expression is not affected by inhibitor treatment.

(A) Gating scheme for CCR7 cell surface expression by flow cytometry. Representative

pictures of CCR7 expression on DMSO treated L428 cells.

(B) No differences in CCR7 cell surface expression between DMSO or inhibitor treated

L428 cells (mean ± SD, n=3). 25

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(C) No differences in CCR7 cell surface expression between DMSO or inhibitor treated

KMH2 cells (mean ± SD, n=3).

Supplementary Figure S4: KM-H2 cells show constitutive active canonical WNT signaling. Western Blot of cytosolic and nuclear fractions of KM-H2 cells stimulated for

24 hour or 48 hours with conditioned medium (CM). Note the increased nuclear β-

catenin fraction after CM stimulation. As controls, nuclear HDAC and cytosolic HSP90

was used. Relative β-catenin intensities compared to the respective cytosolic and

nuclear controls are shown beneath.

Supplementary Figure S5: Stable LEF-1 knockdown reduces cHL migration.

(A) Migration of L428 cells after stable LEF-1 knockdown is significantly reduced. (mean

± SD, n=3, unpaired, 2-tailed t-test).

(B) Migration of KM-H2 cells after stable LEF-1 knockdown is significantly reduced.

(mean ± SD, n=3, unpaired, 2-tailed t-test with Welch correction).

(C) Relative cell numbers of L428 after LEF-1 and β-catenin knockdown. Of note, no

significant difference in cell viability has been caused by the knockdowns. (mean ± SD,

n=3, 1-way ANOVA with Bonferroni’s post-hoc test)

(D) Relative cell numbers of L428 and KM-H2 after stable LEF-1 knockdown. Of note, no

significant difference in cell viability has been caused by the knockdowns. (mean ± SD,

n=3, 2-way ANOVA with Bonferroni’s post-hoc test)

Supplementary Figure S6: CCR7 cell surface expression is not affected by LEF-1 or β-catenin knockdown.

(A) Gating scheme for CCR7 cell surface expression by flow cytometry. Representative

pictures of CCR7 expression on L428 cells scr si control.

(B) No differences in CCR7 cell surface expression between L428 scr si control and

LEF-1 or β-catenin knockdown cells (mean ± SD, n=3). 26

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(C) No differences in CCR7 cell surface expression between KMH2 scr si control and

LEF-1 or β-catenin knockdown cells (mean ± SD, n=3).

Supplementary Figure S7: Cell tracks of KM-H2 LEF-1si and β-catenin si cluster separately from scr control cells. Heat map displaying the results of the hierarchical

clustering of movement patterns of scr si, LEF-1si and β-catenin si KM-H2 cells based

on shape fingerprints according to the form and length of each track. The x-axis of the

heat map corresponds to the internal distances within single tracks, with short distances

mapped to the left and longer distances to the right. The color of the heat map tiles

represents the number of counts for specific distances per track ('square root

transformed' to enhance contrast). Experimental group membership is encoded by

colors on the left side of the heat map with black (scr si), green (LEF-1si) and orange

(β-catenin).

Supplementary Figure S8: LEF-1 and β-catenin modify cHL adhesion and the influence of cHL cells on endothelial cell viability and migration.

(A) Migration of HUVEC cells towards CM of L428, ns control and LEF-1 sh cells. As

positive control HUVEC migration towards EBM2 medium supplemented with EGM-2

MV SingleQuot Kit Supplements & Growth Factors and as negative control RPMI

medium have been used. (mean ± SD, n=3, Kruskal-Wallis test with Bonferroni’s post-

hoc test).

(B-C) Scratch assay of HUVEC cells towards CM of L428, ns control and LEF-1 sh cells.

As positive control HUVEC migration towards EBM2 medium supplemented with EGM-2

MV SingleQuot Kit Supplements & Growth Factors and as negative control RPMI

medium have been used. Note the decrease in HUVEC migration towards CM of L428

after LEF-1 knockdown (KD). (mean ± SD, n=3; Kruskal-Wallis test with Bonferroni’s

post-hoc test).

(D) Adhesion of scr si control, LEF-1si and β-catenin si L428 cells on either HUVEC

(white) or collagen I (grey). Note the decrease of adhesion in LEF-1si and β-catenin si

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cells compared to scr si cells. (mean ± SD, n=4, 2-way ANOVA and Bonferroni’s post-

hoc test).

(E) MTT test of HUVEC cells treated CM of ns control and LEF-1 KD KM-H2 cells (mean

± SD, n=4, Kruskal-Wallis test with Bonferroni’s post-hoc test).

(F) MTT test of HUVEC cells treated CM of ns control and LEF-1 KD L428 cells (mean ±

SD, n=4, 1-way ANOVA and Bonferroni’s post-hoc test). Note decrease of HUVEC

viability in LEF-1 knockdown CM. (*P < 0.05, **P < 0.01 and ***P < 0.001)

Supplementary Figure S9: NMR analyses reveal no significant differences in metabolites after LEF-1 KD.

Metabolomics NMR analysis data from three independent experimental sets

(KM-H2/L428; parental, LEF1sh, ns ctr) were normalized by total protein amount in each

sample and their metabolic profile (based on 25 metabolites) was analyzed using

Cluster analysis (Euclidean distance; Ward´s method; link distance scaled as

percentage of maximal link distance). The LEF-1 knockdown does not cause any

obvious change in the metabolism of Hodgkin lymphoma cell lines KM-H2 and L428.

Burkitt lymphoma line BL41 was used as an external control.

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