A Novel ACKR2-Dependent Role of Fibroblast-Derived CXCL14 in Epithelial-To-Mesenchymal Transition and Metastasis of Breast Cancer

Author Manuscript Published OnlineFirst on March 8, 2019; DOI: 10.1158/1078-0432.CCR-18-1294 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

A novel ACKR2-dependent role of fibroblast-derived CXCL14 in epithelial-to-mesenchymal transition and metastasis of breast cancer

Elin Sjöberg1, Max Meyrath2 Laura Milde3, Mercedes Herrera1, John Lövrot1, Daniel Hägerstrand1, Oliver Frings1, Margarita Bartish1, Charlotte Rolny1, Erik Sonnhammer4, Andy Chevigné2, Martin Augsten1# and Arne Östman1#*

1. Department of Oncology-Pathology, Cancer Center Karolinska (CCK), Karolinska Institutet, Stockholm, Sweden.

2. Department of Infection and Immunity, Immuno-Pharmacology and Interactomics, Luxembourg Institute of Health (LIH) Esch-sur-Alzette, Luxembourg

3. Division for Vascular Oncology and Metastasis, German Cancer Research Center (DKFZ), Heidelberg, Germany

4. Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Stockholm, Sweden

Running title: Fibroblast CXCL14/ACKR2/NOS1 signaling in breast cancer

#Authors contributed equally. *Corresponding author. Correspondence to: Arne Östman, [email protected], +468-51770232 The authors declare no potential conflicts of interest.

Downloaded from clincancerres.aacrjournals.org on October 1, 2021. © 2019 American Association for Cancer Research. Author Manuscript Published OnlineFirst on March 8, 2019; DOI: 10.1158/1078-0432.CCR-18-1294 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Abstract Purpose

Fibroblasts expressing the orphan chemokine CXCL14 have been previously shown to associate with poor breast cancer prognosis and promote cancer growth. This study explores the mechanism underlying the poor survival-associations of stromal CXCL14.

Experimental design

Tumor cell EMT, invasion and metastasis were studied in in vitro and in vivo models together with fibroblasts overexpressing CXCL14. An approach for CXCL14-receptor identification included loss-of-function studies followed by molecular and functional endpoints. The clinical relevance was further explored in publicly available gene expression datasets.

Results

CXCL14-fibroblasts stimulated breast cancer EMT, migration and invasion in breast cancer cells and in a xenograft model. Furthermore, tumor cells primed by CXCL14-fibroblasts displayed enhanced lung colonization after tail-vein injection. By loss-of function experiments the atypical GPCR ACKR2 was identified to mediate CXCL14-stimulated responses. Down-regulation of ACKR2, or CXCL14-induced NOS1, attenuated the pro-EMT and migratory capacity. CXCL14/ACKR2 expression correlated with EMT and survival in gene expression data sets.

Conclusions

Collectively, findings imply an autocrine fibroblast CXCL14/ACKR2 pathway as a clinically relevant stimulator of EMT, tumor cell invasion and metastasis. The study also identifies

ACKR2 as a novel mediator for CXCL14 function and thereby defines a pathway with drug target potential.

Translational Relevance

Autocrine fibroblast CXCL14/ACKR2 signaling is shown to induce EMT, migration and metastasis and to correlate with worse survival in breast cancer patients. The identification of

ACKR2 as a novel component in the signalling of the orphan chemokine CXCL14 is relevant for further biomarker studies and suggest novel targeting opportunities.

Introduction

Death of breast cancer patients is almost exclusively due to metastatic disease. Metastasis develops through a multi-step process, involving tissue invasion, intravasation, survival in the bloodstream and lymph system, extravasation and tissue colonization. This study develops recent correlative studies which have indicated clinical relevance, in breast cancer, of stroma- derived expression of the chemokine CXCL14 by demonstrating significant and independent associations between high stromal CXCL14 expression and shorter survival in a population- based breast cancer cohort. Notably, epithelial expression of CXCL14 did not have an impact on breast cancer outcome (1).

During the early steps of metastasis development, tumor cells loose cell-to-cell contacts and epithelial characteristics and instead gain mesenchymal traits that allow them to invade the surrounding tissue and metastasize; a process termed epithelial-to-mesenchymal transition

(EMT) (2).

EMT is controlled by distinct transcriptional programs activated by specific transcription factors, including Snail, Slug, Twist, Zeb and Gsc. Activation of these factors ultimately leads to the loss of epithelial markers including E-cadherin and cytokeratins, and the upregulation of mesenchymal markers, such as vimentin, alpha-smooth muscle actin (SMA) and matrix degrading enzymes (3). Although the classical paradigm attributing EMT a crucial role in the process of metastasis has been recently challenged by studies in genetic mouse models, other recent studies including in vivo imaging approaches demonstrated that cancer cells displaying an EMT phenotype give rise to metastases (4-6).

Induction of EMT can occur in a paracrine manner by secreted factors from cells of the tumor stroma, as for example the cancer-associated fibroblasts (CAFs) (7,8). CAFs constitute a heterogeneous cell population that contributes to cancer growth and spread by secretion of a

variety of pro-tumorigenic factors, including soluble factors. Among these CAF-secreted factors implicated in EMT and metastasis are chemokines, proteins of a size between 8-14kDa that stimulate directed cell migration by creating a gradient along which cell types expressing the corresponding receptor travel (7,9). Chemokines bind to the pertussis-sensitive Gαi- subfamily of G-protein-coupled receptors (GPCR) that engage different signaling pathways including ERK1/2, PI3K/AKT and calcium signaling (10). Besides the classical chemokine receptors, there is a subfamily of atypical chemokine receptors (ACKRs) that are predominantly involved in sequestration of chemokines (11).

In cancer, chemokines are involved in the recruitment of various cell types into tumors and thereby affecting inflammation, angiogenesis, tumor growth, invasion and metastasis (12). A paracrine chemokine-crosstalk between stromal cells and tumor cells, involving effects on

EMT, has been demonstrated to enhance formation of metastases (13-16). Expression of certain chemokines in distant tissues has also been reported to determine metastasis formation in specific organs, a process termed metastatic tropism (17)

The orphan chemokine CXCL14, earlier designated BRAK, MIP-2γ, BMAC or KS1 stimulates migration of various immune cells, including B-cells, NK cells and monocytes but not T-cells (18-21). CXCL14 expression has been shown to be up-regulated in CAFs, as compared to normal fibroblasts, in human breast and prostate cancer (22,23). Experimental studies exploring the function of CXCL14 during tumor progression and metastasis formation have demonstrated context-dependent pro- and anti-tumoral effects. The reasons for these effects remain largely unknown and could possibly dependent on the cell type that express the chemokine and on the profile of chemokine receptors and ACKRs expressed. Some studies with CXCL14 over-expression in tumor cells have demonstrated anti-tumoral effects of this chemokine (24). In contrast, tissue culture- and mouse cancer model-studies of breast and

prostate cancer, have demonstrated pro-tumoral effects of CXCL14 expressed by stromal fibroblasts, associated with CXCL14-induced changes in fibroblast secretomes (22,23,25).

The tumor-promoting roles of CAF-derived CXCL14 have been shown to depend on nitric oxide synthase 1 (Nos1) and involve stimulation of angiogenesis and recruitment of macrophages (25).

Continued exploration of the roles of CXCL14 in tumor biology and possible exploitation of this chemokine as a therapeutic target depend on the identification of critical mediators of

CXCL14 signalling, including receptors. This study therefore aimed at providing a better understanding of the molecular mechanism underlying the documented poor-survival association of stroma-derived CXCL14.

Materials and Methods

Cell lines and chemicals

The mouse fibroblast cell line NIH3T3 (and derivatives), the breast cancer cell lines MCF7,

SKBR3 MDA-MB-231, 4T1 and Hs578t were cultured in DMEM (Hyclone), supplemented with 10% Fetal Bovine Serum (FBS) (Hyclone), 1% Glutamine (Hyclone) and 1%

Penicillin/Streptomycin (Hyclone). DMEM-F12 (Hyclone), supplemented with horse serum

(Biochrom), 1% Glutamine and 1% Penicillin/Streptomycin was used for culturing the

MCF10-DCIS cell line. Starvation was performed in medium without serum. All cells were maintained at 37°C in humidified air with 5% CO2. NIH-ctr and NIH-CXCL14 fibroblasts have been characterized earlier, and fibroblasts secrete physiological levels of CXCL14 (22).

Cell lines were purchased from ATCC or received from collaboration partners and continually tested for mycoplasma infection during the study. The identity of the cell lines used was confirmed by short tandem repeat (STR) profiling at Uppsala Genome Center. All experiments were performed with cells of passage 3-20.

Western blot analyses used antibodies against p-ERK (#9101), ERK (#9102), E-cadherin

(#3195), Snail (#3879), Nos1 (#4234) (Cell Signaling Technology), -Actin (A1978) and α- tubulin (T5201) (Sigma-Aldrich). Primary antibodies detecting E-cadherin (#3195),

Cytokeratin 8/18 (#4546) and PDGFR (#3169) (Cell Signaling Technology) together by fluorescent-linked secondary antibodies, were used for immunofluorescence staining of xenograft tumors.

Pertussis toxin was purchased from Sigma-Aldrich and recombinant CXCL14 and CCL5 from R&D Systems and PeproTech.

Alexa Fluor 647-coupled chemokines were purchased from Almac (Craigavon UK).

RNA isolation, cDNA synthesis and qRT-PCR analysis

RNA was isolated from xenograft tumors or overnight-starved cells using GeneEluteTM

Mammalian Total RNA Miniprep Kit (Sigma-Aldrich). cDNA synthesis was performed with the SuperScript III First-Strand Synthesis System for RT-PCR (Invitrogen), using PolydT primers, in accordance with the manufactures instructions. The qRT-PCR reaction using

SYBRgreen Universal PCR Master Mix (Applied Biosystems) was performed with the 7500

Real-Time PCR system (Applied Biosystems). The concentration of primers was 200nM, and expression levels were normalized to the housekeeping gene glyceraldehyde-3-phosphate dehydrogenase (GAPDH). The primer sequences for primers obtained from Sigma-Aldrich are shown in Supplementary Table 4. Other primers were QuantiTect primers obtained from

Qiagen.

Immunoblotting, immunofluorescence and secretome analyses

Immunoblotting- and Immunofluorescence analyses were performed as previously described

(Augsten et al, 2009). In short, for analysis of CXCL14 induced p-ERK signaling by immunoblotting, over-night serum starved cells was stimulated with recombinant CXCL14

(R&D or PeproTech) for 7 minutes. For experiments with pertussis toxin, cells were treated with the toxin for 1h at 37°C and 5% CO2 prior to CXCL14 stimulation. Cell lysates were prepared and SDS/PAGE were performed followed by transfer to PVDF membranes

(Millipore). Immunoblotting with p-ERK and ERK antibodies (Cell Signaling Technology), diluted 1:1000, were performed and signals were detected with ImageQuant LAS4000 (GE

Healthcare) and quantified using Image J (http://imagej.nih.gov.proxy.kib.ki.se/ij).

Analysis of EMT markers was performed for 48-72h after stimulation with fibroblast- conditioned medium or co-culture of breast cancer cells and fibroblasts at a 1:1 ratio. The conditioned medium was generated by seeding the same number of NIH-ctr and NIH-

CXCL14 cells. The next day medium was changed to DMEM containing low serum (1%

FBS) and the conditioned medium was collected after for 48 hours, sterile filtered with a

0.2μm filter. Antibodies for immunoblotting, including E-cadherin, Snail were diluted 1:1000 and Nos1 1:500. For immunofluorescence analysis E-cadherin, Cytokeratin 8/18 and

PDGFR antibodies where diluted 1:100.

To analyze the secretome from CXCL14-fibroblasts a protein array was performed. 7.0x105

NIH-CXCL14 and NIH-ctr were seeded in 10cm dishes. The next day medium was changed from medium with 10% FBS to low serum (1% FBS). Conditioned medium was collected following 48h incubation at 37°C, sterile filtered and stored at -20°C. Aliquots of conditioned medium (1ml) from NIH-CXCL14 and NIH-ctr fibroblasts were subjected to the proteome profiler (mouse angiogenesis array kit ary015, R&D systems), performed according to the manufacturers protocol. Array images obtained were analyzed using the ImageJ software. For all spots the average background signal from negative control spots was subtracted. The average signal from positive control spots of each membrane was used to normalize the two different types of fibroblast conditions. The relative differences in protein expression between NIH-CXCL14 and NIH-ctr cells was expressed as ratio (fold of NIH-ctr).

In vitro growth, migration and invasion assays

To study the effect of siRNA and shRNA-mediated knockdown of ACKR2 on growth of

NIH-ctr and NIH-CXCL14 fibroblasts, 2x104 cells were seeded per well of a 24-well plate

(Sarstedt), in quadruplicates in serum-reduced media. After 3 days of culture AlamarBlue

(BioRad) was used to determine the cell number. 350μL of a 1:10 dilution of AlamarBlue dye in DMEM was added to each well and cells were incubated at 37°C with 5% CO2 for 2.5h. To measure the conversion of the dye, 100μL was transferred into each well of a white 96-well plate (Costar) and absorbance was measured at a wavelength of 570nm.

To study cell migration of breast cancer cells a transwell migration assay was used. 2.5x104 breast cancer cells were seeded in transwell inserts (Corning) with an 8.0m pore-sized membrane and placed in a 24-well plate (Corning), in duplicates. For analysis of CXCL14- fibroblast induced migration, 2.5x104 CXCL14- or control fibroblasts were seeded in the lower chamber. To determine the impact of MAP Kinase or PI3 Kinase signaling on CXCL14 fibroblast-induced migration, cancer cells were treated with 10M of the MEK1/2 inhibitor

U0126 (Cell Signaling Technology) or 1M of the PI3K inhibitor Wortmannin (Cell

Signaling Technology) during the migration assay.

For migration experiments, lasting for 16-24h, the inside of the insert was wiped with cotton swabs, washed with PBS and cells were fixed in ice cold methanol. The membrane was cut out and placed on Superfrost Plus slides (Menzel-Gläser) and stained with Vectashield

Mounting Medium with DAPI (Vector Laboratories). Quantification of cell migration was performed by counting cell nuclei of the migrated cells. The same principles were used for the invasion assays, with inserts containing a thin Matrigel layer (Corning). Invasion was allowed to occur for 72h.

Chemokine binding assay

HEK-293 cells or HEK-293 cells stably expressing ACKR2 (under 200μg/ml hygromycin selection) were distributed into 96-well plates (2x105 cells per well) and incubated with increasing concentrations ranging from 10 pM to 100 nM of Alexa Fluor 647-labelled CCL5 or CXCL14 for 90 min on ice. After a washing step, Zombie Green Fixable Viability Kit

(BioLegend, San Diego, CA) was used to gate on living cells only. The experiments were performed in PBS containing 1% BSA and 0.1% NaN3 (FACS buffer). Chemokine binding was quantified by mean fluorescence intensity (MFI) of 10 000 gated cells on a BD FACS

Fortessa cytometer (BD Biosciences, Franklin Lakes, NJ).

β-arrestin recruitment assay

Chemokine induced β-arrestin-1 recruitment to ACKR2 was monitored by Nanoluciferase complementation assay (NanoBiT, Promega) as described previously(26,27). 5x106 HEK cells were plated in 10 cm-culture dishes and 24h later transfected with plasmids containing human

β-arrestin-1 N-terminally fused to LgBiT and ACKR2 C-terminally fused to SmBiT. 24h post transfection, cells were harvested, incubated 30 min at 37°C with 200-fold diluted Nano-Glo

Live Cell substrate and distributed into a white 96-well plate (1x105 cells per well). β-arrestin-

1 recruitment was measured over 25 minutes with a Mithras LB940 luminometer (Berthold

Technologies, Bad Wildbad, Germany). For each experiment, signal measured with a saturating concentration (300 nM) of the full agonist (i.e. CCL5) was set as 100%.

Bioinformatic analyses

Sequence analyses for novel chemokine receptors started from Pfam family PF00001

(7tm_1), using the 1679 human domains from 1664 human sequences in the full alignment. A neighbor-joining tree of these was built using scoredist distances with Belvu (28). A subtree of 114 cytokines was cut out. After removing fragment sequences and >99% identical sequences, 32 sequences were left. Following exclusion of DUFFY, not being part of the

23760 homologs in the Pfam family, a candidate list of 31 candidates was established

(Supplementary Fig. 6).

Transfection of siRNA and generation of stable cell lines

For transfection of siRNA, 1.0-2.0x105 cells were seeded in 6-well plates (Sarstedt) and transfected for 48 hours with 100nM siRNA (ACKR2 target sequence; 5’-

CTCAATTAGCGTTATTGGCAA-3’) (Qiagen) using HiPerFect transfection reagent

(Qiagen). To determine the efficiency of siRNA-mediated knockdown of genes of interest,

RNA extraction, cDNA synthesis and qRT-PCR analysis was performed.

Fibroblast-derivatives with stable knockdown of ACKR2 were established using shRNA procedures, as described previously (25). In brief, phoenix cells were transfected with 2 unique 29mer shRNA constructs against ACKR2, Gene ID = 59289 (shACKR2:A and shACKR2:B) or non-targeting control shRNA (shCtr) in retroviral vectors (Origene). After

48h, the supernatant was collected, filtered and added to NIH-ctr and NIH-CXCL14 cells for

5h. Cells were subsequently selected in 30g/ml blasticidin for 2 weeks. The knockdown of

ACKR2 was confirmed by qRT-PCR (Fig. 4A). Generation of NIH-ctr and NIH-CXCL14 fibroblasts with a stable knockdown of NOS1 have been described earlier (25).

Animal experiments

The animal experiments were conducted in accordance with national guidelines and approved by the Stockholm North Ethical Committee on Animal Experiments. The generation of xenograft tumors was performed as described previously (25).

The analyses of lung metastasis formation were performed after tail-vein injection of 2x105 breast cancer cells in three groups of 8-week-old female SCID mice, without any further randomization. The sample size of 10 mice in each group was determined by the 3R criteria together with previous experience. After 4 weeks, mice were sacrificed and lungs were collected, washed in PBS (Hyclone) and snap frozen (for qRT-PCR analysis) or embedded in

OCT and snap frozen (for histological analysis). No animals were excluded from the study.

For RNA extraction 1mL of trizol (Life Technologies) was added to the lung tissue and homogenized with a polytron for 3x10 seconds. A volume of 0.2 mL chloroform was added and the samples were shaken for 15 seconds, and incubated for 2 min at room temperature.

The samples were centrifuged at 12 000 x g for 15 min at 4°C and the aqueous phase was

placed in a new tube. RNA was precipitated by addition of 0.5mL 100% isopropanol (Merck) to the samples and incubation for 10 min at room temperature. Following centrifugation at

12000 x g for 10 min at 4°C the RNA pellet was washed with 75% ethanol and air dried before re-suspension in nuclease free water (Ambion). The RNA concentration of each sample was determined using the Nanodrop ND-1000 spectrophotometer (NanoDrop

Technologies). cDNA were synthetized and subsequent qRT-PCR analysis was performed as described previously, with human- and mouse-specific primers. Percentages of human cells in mice lungs were quantified as described in Malek et al. (29).

Ten frozen sections (10μm) were made from the OCT embedded lungs. Five sections were thrown in between each saved frozen section. Stainings were performed with the human specific antibody Stem121 (Takara Bio) and the positive cells were counted in each section and results are displayed as average number per lung (Fig. 3D). The tail-vein injections were performed blinded and the analyses of lung-metastasis were performed un-blinded.

Clinical cohorts

The relation between CXCL14 transcript abundance and EMT as assessed by an EMT gene- expression signature was investigated in clinical breast cancer cohorts with publicly available transcriptome data: the Uppsala (30), Stockholm (31), Rotterdam (32) and METABRIC (33) cohorts, as well as the The Cancer Genome Atlas (TCGA) (34). Each study site in

METABRIC is treated as a separate cohort. The Cancer Genome Atlas (TCGA) gene expression datasets for breast cancer, ovarian cancer and prostate cancer was used to investigate the levels of EMT markers and survival associations in CXCL14/ACKR2 subgroups was additionally performed in gene expression datasets for bladder cancer, clear cell renal cell carcinoma (ccRCC), colorectal cancer, esophageal cancer, glioblastoma multiforme (GBM), low grade glioma, head and neck cancer (HNCC), lung adenocarcinoma,

pancreas cancer and stomach cancer (34).

Gene-expression data analysis

An EMT gene-expression signature score was derived for each tumor in the panel of clinical cohorts as described previously (35). In brief, the signature was identified from the changes in gene-expression shared by up-regulation of Gsc, Snail, Twist, and TGF-1 and by downregulation of E-cadherin. PAM50 intrinsic subtype classification was performed as described previously (36). Individual patient data meta-analysis (IPDMA) of all cohorts with a linear mixed effects-model was performed using the R package nlme (R syntax lme(groupedData(ScaledEMTscore ~ scaledCXCL14 | cohort, data))). All gene expression data analysis was performed in R/Bioconductor and SPSS 21.0. The EMT score and CXCL14 data are first centered and scaled to unit standard deviation within cohorts to facilitate comparison between cohorts. Hence, the slope of a linear regression in each cohort in

Supplementary Fig. 10A is mathematically equivalent to the Pearson’s correlation coefficient.

This equivalence does not hold in subgroups as in Supplementary Fig. 10B.

The TCGA gene expression data (Fig 5A, Supplementary Fig 12 and 13) are displayed as Z- scores obtained from cbioportal. For the breast cancer gene expression dataset CXCL14low and high groups are divided according to the 50 percentile, whereas ACKR2low and high expression was determined by fitting a mixture of two normal distributions using the R package mixtools, resulting in a dichotomisation below and above the 90.7 precentile. For the

TCGA ovarian and prostate cancer gene expression datasets the ACKR2low and high subgroups were divided by the 4th quartile.

Statistical methods

Statistical calculations were performed using excel 2011 for Mac (Microsoft office),

R/Bioconductor or the statistical package SPSS 21.0 (SPSS Inc.) All data are expressed as mean or median values, and error bars represent the s.d or s.e.m. Data that are being statistically compared, relevant for the conclusions, exhibit similar variation. Statistical differences between groups were determined using two-sided, unpaired student t test or

Mann-Whitney U-test. Pearson’s correlation was used to analyze correlations between different parameters. The Kaplan-Meier method and log-rank test method was performed to estimate overall survival. Cox proportional hazards model was used to compare hazard ratios in both uni- and multivariable analyses. The multivariable analysis included known clinical relevant parameters, including T-stage, N-stage, M-stage and molecular subtypes of breast cancer. Results are presented in the multivariable analysis as hazard ratios including 95% confidence interval. For all analysis, P values below 0.05 were considered significant. *p <

0.05, **p < 0.01, ***p < 0.001. All relevant data are available from the authors.

Results

CXCL14-fibroblasts induce loss of epithelial markers and enhance expression of mesenchymal markers and EMT transcription factors in breast tumor xenografts

The findings of stromal CXCL14 as a poor prognostic marker in breast cancer (1), prompted analyses of the potential effects of CAF-derived CXCL14 on tumor cell invasion and metastasis.

We first studied the expression levels of EMT markers as an indicator of a pro-invasive phenotype in xenograft tumors formed following co-injection of the epithelial breast cancer cell line MCF7 and either control fibroblasts or CXCL14-fibroblasts (25).

Immunofluorescence staining of xenograft tumor-sections demonstrated a significant loss of tumor cell E-cadherin and Cytokeratin 8/18 in CXCL14-breast tumors, as compared to control tumors (Fig. 1A, Supplementary Fig. 1A and Supplementary Table 1). Nos1, an oxidative stress-induced enzyme, was previously shown to functionally contribute to the pro- tumorigenic actions of CXCL14-expressing fibroblasts (25). EMT markers were therefore also analyzed in MCF7/NIH-CXCL14 tumors with a stable NOS1 downregulation in the fibroblasts. Impaired expression of NOS1 was sufficient to reverse the decrease in epithelial markers induced by CXCL14-fibroblasts in vivo (Fig. 1A, Supplementary Fig. 1A and

Supplementary Table 1). Furthermore, CXCL14-fibroblasts also reduced cancer cell

Cytokeratin 8/18 levels, in a Nos1-dependent manner, in a xenograft co-injection model of prostate cancer (Supplementary Fig. 1B and Supplementary Table 1).

Analyses of mRNA levels of EMT markers substantiated these findings and uncovered a reduction of epithelial markers including E-cadherin (CDH1), Cytokeratin 18 (KRT18) and

Cytokeratin 8 (KRT8), and increase in mesenchymal markers including Vimentin (VIM), α-

SMA (ACTA2) and MMP2 (MMP2), and an increase in EMT transcription factors including

Slug (SNAI2), and Twist (TWIST1) in CXCL14-breast tumors (Fig. 1B). Furthermore, analyses of MCF7/NIH-CXCL14 tumors with a stable NOS1 knockdown in fibroblasts demonstrated Nos1-dependency of these gene-expression changes (Fig. 1B). However, mesenchymal markers, including Fibronectin (FN1), FAP (FAP), and MMP9 (MMP9) were up regulated in CXCL14-tumors independently of Nos1 expression (Supplementary Fig. 1C).

Additional analyses were performed to investigate if the CXCL14-dependent EMT phenotype also was associated with a more invasive growth pattern. As shown in Fig. 1C, MCF7/NIH-

CXCL14 tumors displayed a more invasive growth pattern with a significantly higher number of budding cells in the tumor periphery, as compared to MCF7/NIH-ctr tumors.

These data collectively demonstrate that cancer cells co-injected with CXCL14-fibroblasts exhibit enhanced EMT and invasion in vivo.

CXCL14-fibroblasts stimulate EMT in vitro and induce a mesenchymal morphology of breast cancer cells

Next, the direct impact of CXCL14-expressing fibroblasts on the modulation of EMT markers in MCF7 breast cancer cells and MCF10-DCIS (DCIS) cells was investigated under in vitro co-culture conditions. Western blot analysis demonstrated a reduction of E-cadherin in both

MCF7- and DCIS cells after direct co-culture with CXCL14-fibroblasts that was not seen with control fibroblasts (Fig. 2A). To confirm that the downregulation occurred in the breast cancer cells and not reflected changes in fibroblast properties or abundance, immunofluorescence co-staining for E-cadherin or Cytokeratin 8/18 together with the fibroblast marker PDGFRβ was performed on MCF7-fibroblast co-cultures. As shown in Fig.

2B, there was a specific loss of E-cadherin (left panel) and Cytokeratin 8/18 (right panel) in

the breast cancer cells when MCF7 cells were co-culture with CXCL14 fibroblasts but not in the presence of control fibroblasts. Similar findings of altered EMT markers in MCF7- and

DCIS cells were detected after treatment with conditioned media (CM) from CXCL14 fibroblasts (Supplementary Fig. 2A and B). Another breast cancer cell line, SKBR3 that has lost E-Cadherin, showed increased levels of the EMT transcription factor Snail when treated with CM from NIH-CXCL14 compared to CM from NIH-ctr (Supplementary Fig. 2B).

Furthermore, treatment of MCF7, DCIS and SKBR3 breast cancer cells with CM from

CXCL14-fibroblasts induced changes in cell morphology. The tumor cells formed filopodium-like protrusions and obtained a mesenchymal-like morphology when cultured in

CM from CXCL14 fibroblasts, but not in CM from control fibroblasts or in standard DMEM

(Fig. 2C and Supplementary Fig. 2C). These phenotypes induced by CXCL14-fibroblasts were not seen in the mesenchymal metastatic breast cancer cell line MDA-MB-231, a cell line that already has undergone EMT (Supplementary Fig. 2C).

These results demonstrate the ability of CXCL14-fibroblasts to induce an EMT-phenotype in certain breast cancer cells, in a paracrine manner independent of cell-to-cell contact.

CXCL14-fibroblasts enhance migration and invasion of breast cancer cells

The induction of EMT suggested functional effects of CXCL14-fibroblasts on breast cancer cells. Thus, we compared the ability of NIH-ctr and NIH-CXCL14 fibroblasts to stimulate the migration and invasion of MCF7, DCIS and SKBR3 cells. Transwell migration assays were performed to analyze if the changes in EMT markers and in morphology were accompanied by an increase in cell motility. CXCL14-fibroblasts displayed a stronger ability to stimulate the migration of MCF7, DCIS and SKBR3 cells, as compared to control fibroblasts (Fig. 3A).

We also investigated if CXCL14-fibroblast-induced EMT and migration could be observed in

breast cancer cell lines representing the basal (triple negative) molecular subgroup of breast cancer, including 4T1 cells and Hs578t cells (Supplementary Fig. 3A and B). NIH-CXCL14 cells significantly enhanced the migration (Supplementary Fig. 3A) and stimulated EMT

(Supplementary Figure 3B) of 4T1 cells, as compared to NIH-ctr cells. There was a trend toward enhanced migration of Hs578t cells, although not significant, possibly explained by the fact that these cells already have undergone EMT (Supplementary Fig. 3A).

Furthermore, invasion of MCF7 and SKBR3 cells through a layer of Matrigel was enhanced by NIH-CXCL14 fibroblasts, as compared to control fibroblasts (Supplementary Fig. 3C).

Together these results demonstrate that the CXCL14-fibroblasts-induced changes in EMT markers are accompanied by an enhanced capacity of breast cancer cells to migrate and invade in vitro.

CXCL14-fibroblasts enhance lung colonization of MCF7 cells following tail-vein injection

The findings of CXCL14-induced effects on migration, invasion and EMT, together with previous findings revealing a pro-tumorigenic role of CXCL14, prompted in vivo-studies to explore the effects of CXCL14-fibroblasts.

Tail-vein experiments monitor the ability of cancer cells to survive in the circulation, extravasate and colonize metastatic sites. These abilities have previously been linked to EMT

(37-39). Therefore, lung colonization of tail-vein injected MCF7 cells, “primed” in vitro in a co-culture format together with CXCL14-fibroblasts or control fibroblasts prior to injection, was studied (Fig. 3B).

Abundance of breast cancer cells in the lungs, four weeks after injection, was determined by qRT-PCR analyses with human-specific primers as described previously (29). As shown in

Fig. 3C, a significantly higher number of MCF7 cells were detected in the lungs of mice that had been injected with cancer cells “primed” with CXCL14-fibroblasts, as compared to mice injected with control fibroblast-primed cancer cells.

These findings were independently validated by immunohistochemical analyses of tissue sections from lungs of mice subjected to tail-vein injection of co-culture primed cancer cells.

As shown in Fig. 3D, these analyses demonstrated a significantly higher number of breast cancer cells in the lungs of mice that had been injected with NIH-CXCL14-primed breast cancer cells.

These experiments thus demonstrate that CXCL14-fibroblasts, as compared to control fibroblasts, more potently stimulate lung colonization of blood-circulating breast cancer cells.

CXCL14-induced molecular signaling and cellular responses are mediated by the atypical G-protein coupled receptor ACKR2

Next we aimed at identifying key signalling components mediating the cellular and pro- tumorigenic effects of the orphan chemokine CXCL14.

We have previously found that CXCL14 enhances MAPK-signaling in certain cancer cells and defined them as CXCL14-responsive cell lines (22). Initial experiments, analyzing ERK phosphorylation subsequent to stimulation with recombinant CXCL14, identified a panel of

CXCL14-responsive cell lines (MCF7, DCIS, SKBR3, NIH-3T3) and non-responsive cell lines (MDA-MB-231 and LNCaP) (Supplementary Fig. 4) (22). Treatment of the CXCL14- responsive cell lines MCF7 and NIH-3T3 with pertussis toxin, that specifically inhibits the

Gαi-subfamily of GPCRs, blocked CXCL14-induced ERK signaling in both cell types

(Supplementary Fig. 5). This finding suggests that CXCL14, as other chemokines, signals through the Gαi-subfamily of GPCRs.

Next, a sequence alignment-approach was initiated to identify GPCRs that exhibit similarities with known chemokine receptors (see Material and Methods for details) (Supplementary Fig

6). CXCL14 is a highly evolutionary conserved chemokine and the absence of chemokine receptor-orthologs in species expressing CXCL14 limited the number of potential candidates

(40). Furthermore, CXCL14 is a highly selective chemokine for trophoblasts of the placenta, immature dendritic cells, B-cells and NK-cells and does not induce chemotaxis of T- lymphocytes. Therefore, mediators of CXCL14 signalling are likely present on trophoblasts, and on certain immune cells, but not expressed on T-cells (18-21,41). These considerations led to the selection for continued studies of 11 candidate proteins from the original list.

Expression levels of these receptors were tested in CXCL14-responsive and non-responsive cell lines (Supplementary Table 2). These results reduced the candidate set to six candidates, which were analyzed in preliminary siRNA experiments that led to continued studies on

ACKR2, CXCR4, GPR25 and GPR182.

Initial experiments, using CXCL14-induced ERK phosphorylation as an endpoint, were performed in the CXCL14-responsive MCF7 cells. As shown in Supplementary Fig. 7A and

B, down-regulation of ACKR2 significantly reduced CXCL14-induced ERK phosphorylation.

In contrast, down-regulation of CXCR4, GPR25 and GPR182 did not affect CXCL14-induced

ERK phosphorylation (Supplementary Fig. 7A and C). ACKR2-down-regulated cells maintained ERK responses following stimulation with CXCL12, indicating specificity of the effects of ACKR2 down-regulation on CXCL14 signaling (Supplementary Fig. 7D).

These initial findings were extended in two other CXCL14-responsive cell lines with the same endpoint. As shown in Supplementary Fig. 8A-E, CXCL14-induced ERK phosphorylation in NIH-3T3 and SKBR3 cells was also attenuated after siRNA-mediated down-regulation of ACKR2. Moreover, the enhanced growth of CXCL14-fibroblasts was significantly reduced after down-regulation of ACKR2 (Supplementary Fig. 8F). In contrast,

no effect on cell growth was observed after down-regulation of CXCR4, GPR182 and GPR25

(Supplementary Fig. 8F).

These findings prompted generation of derivatives of NIH-ctr and NIH-CXCL14 cells with stable ACKR2 down-regulation with two different ACKR2 shRNAs (Fig. 4A). In agreement with findings above, CXCL14-induced ERK-phosphorylation was significantly attenuated in

NIH-3T3 cells with stable down-regulation of ACKR2 (Fig. 4B and C). As an additional endpoint, CXCL14-induced upregulation of NOS1 was studied. As shown in Fig. 4D and E, stable ACKR2 down-regulation reduced NOS1 protein and mRNA levels in NIH-CXCL14 cells but not in control cells. Finally, CXCL14-induced proliferation of NIH3T3 cells was analyzed with regard to ACKR2-dependency. Notably, down-regulation of ACKR2 reduced the growth capacity of CXCL14-fibroblasts, whereas no effect of ACKR2 down-regulation was detected in NIH-ctr cells (Fig. 4F).

The above data prompted binding studies to analyze if CXCL14 directly interacts with

ACKR2. However, contrarily to CCL5, a high affinity ligand of ACKR2, binding of CXCL14 was only weakly detectable at high concentrations on cells overexpressing ACKR2 and was not different compared to cells that lack ACKR2 (Supplementary Fig. 9A). Furthermore, in a

β-arrestin1 recruitment assay, a dose dependent recruitment of β-arrestin1 towards ACKR2 could only be detected upon CCL5, but not upon CXCL14 stimulation (Supplementary Fig.

9B).

In summary, these results derived from analyses of different cell types and using multiple end-points identify ACKR2 as a critical mediator of CXCL14-induced signalling, although no direct interaction between CXCL14 and ACKR2 could be found.

ACKR2 and CXCL14 expression correlates with an EMT-gene expression signature and poor prognosis in clinical datasets of breast cancer

To explore the clinical relevance of the experimental findings of pro-EMT effects of

CXCL14-fibroblasts, correlative analyses were performed in publicly available gene expression datasets of breast cancer to investigate potential associations between

CXCL14/ACKR2 expression and clinical features (35).

The analyses revealed significant positive correlations between expression of CXCL14 and the EMT gene expression signature in a meta-analysis of nine breast cancer cohorts

(Supplementary Fig. 10A). Analysis of the CXCL14:EMT correlation in intrinsic subtypes of breast cancer across all cohorts revealed no major difference among the molecular subgroups of breast cancer, but a slightly stronger correlation in the Basal-subgroup (Supplementary Fig.

10B). Correlations between CXCL14 and EMT were not affected by the amount of tumor stroma (Supplementary Fig. 11). This indicates that the CXCL14:EMT correlation truly is driven by cancer cell EMT rather than reflecting stroma abundance.

To extend these studies additional analyses were performed which focused on relationships between CXCL14 expression and individual EMT-related genes. As shown in Supplementary

Fig. 12, CXCL14-high breast cancer displayed, in general, an EMT-profile characterized by e.g. reduced expression of E-cadherin and increased expression of EMT transcription factors including SNAI2, TWIST1 and ZEB1 and mesenchymal markers including VIM, ACTA2, FN1 and collagens. Based on earlier studies implying a tumor promoting function of CXCL14 in prostate and ovarian cancer (22,25,42), analyses were also performed on the ovarian and prostate cancer TCGA datasets. These demonstrated results similar to those seen in the breast cancer analyses (Supplementary Fig. 12).

Based on the experimental studies these associations were also analyzed in subsets defined by their combined CXCL14 and ACKR2 status. In agreement with a functional link between

CXCL14 and ACKR2 the association with the EMT profile was most prominent in the

CXCL14(high)/ACKR2(high) subgroup (Fig. 5A). This pattern was also seen in prostate and ovarian cancer datasets (Supplementary Fig. 13).

Survival data in the TCGA datasets was also used to explore survival associations of the four

CXCL14/ACKR2-defined subgroups. Initial analyses with all four groups in the breast cancer dataset indicated a particularly poor prognosis of the group with high expression of CXCL14 and ACKR2 (Supplementary Fig. 14). Notably, a significant poor survival association was seen for the combined CXCL14(high)/ACKR2(high) group, when contrasted with the rest of the TCGA population (p=0.007) (Fig. 5B). A Cox proportional hazard model revealed an increased risk of death for patients in the CXCL14(high)/ACKR2(high) subgroup (HR =

2.494, CI = 1.27-5.33). This poor prognosis association of the CXCL14(high)/ACKR2(high) subgroup in breast cancer also remained significant in multivariable analyses with clinico- pathological characteristics including breast cancer molecular subsets (Supplementary Table

3). Survival correlations of the CXCL14(high)/ACKR2(high) subgroup were also explored in publicly available datasets, representing 12 other tumor types (Supplementary table 4).

Besides breast cancer, the CXCL14(high)/ACKR2(high) subgroup was significantly correlated to worse survival of low grade glioma, prostate cancer, clear cell renal cancer and stomach cancer (Supplementary table 4).

Together, these correlative analyses support the notion that the previously observed poor- prognosis association of stroma-derived CXCL14 in breast cancer is related to a molecular pathway that also involves ACKR2.

Paracrine effects of CXCL14-NIH3T3 cells depend on autocrine CXCL14-signaling

Data presented above do not clearly resolve if the poor-prognosis associated

CXCL14/ACKR2 pathway reflects autocrine CXCL14/ACKR2 signaling, supporting EMT and metastasis in a paracrine manner, or rather reflects paracrine actions of CXCL14- activated fibroblasts that involves ACKR2 on breast cancer cells.

As shown in Fig. 6A and B, CXCL14-fibroblast-induced cancer cell migration and E-

Cadherin down-regulation was significantly inhibited by knock down of ACKR2 in fibroblasts. Of note, ACKR2-down-regulation in control fibroblasts did not affect migration or E-Cadherin levels of co-cultured MCF7 cells.

Further evidence supporting autocrine CXCL14-signaling as the driver of the pro-metastatic effects was provided by analyses of the effects of down-regulation of NOS1; an earlier identified downstream component of CXCL14 fibroblast signalling (25). As shown in Fig.

6C, down-regulation of NOS1 significantly reduced the ability of CXCL14 fibroblasts to stimulate migration of MCF7 cells. Notably, NOS1 down-regulation did not affect cancer cell migration induced by control-fibroblasts (Fig. 6C). The reduction of NOS1-signaling also attenuated the CXCL14-fibroblast-induced down-regulation of E-cadherin and up-regulation of Snail in CM-treated MCF7 cells (Fig. 6D and E).

The reduced paracrine effects of CXCL14-fibroblasts following down-regulation of ACKR2 or NOS1 suggest that CXCL14 itself is not promoting EMT but rather stimulates the expression of EMT-regulators in fibroblasts in an ACKR2-/ NOS1-dependent manner. To identify such putative EMT-regulating soluble factors derived from CXCL14-fibroblasts we used a protein profiler and compared the secretome of NIH-CXCL14 and NIH-ctr fibroblasts.

Among the factors that are more abundantly expressed by CXCL14-fibroblasts

(Supplementary Fig. 15) are pro-angiogenic factors (e.g. FGF-2, Angiogenin, VEGF-A), supporting the previous notion that NIH-CXCL14 cells stimulate angiogenesis (22), molecules involved in matrix remodeling such as Adamts1, MMP8, TIMP-1 as well as inducers and effectors of EMT including CXCL1, CX3CL1, TIMP-1, FGF2, HGF and tissue factor.

These data, together with findings of Fig. 1 which show reduced EMT in the tumors formed after co-injection with NOS1-downregulated CXCL14 fibroblasts, indicate that the pro- migratory and EMT-modulatory effects of CXCL14-fibroblasts depend on autocrine

CXCL14/ACKR2/NOS1-signaling.

Discussion

This study extends earlier findings which have identified stroma-derived CXCL14 as a poor prognosis factor in breast cancer. Mechanistic and correlative studies together suggest a novel pro-metastatic pathway composed of autocrine CXCL14/ACKR2/NOS1 signaling in fibroblasts which generates a fibroblast-phenotype that supports cancer cell migration, invasion, EMT and metastasis (Supplementary Fig. 16).

The finding of pro-metastatic effects of CXCL14 adds to earlier literature indicating the involvement of chemokines in metastasis development. CCL5 secreted from bone marrow derived mesenchymal cells, recruited to the breast tumor stroma, was identified a key player in promoting tumor cell invasion and development of metastasis in SCID mice (13). In another study, paracrine crosstalk between tumor cells, myeloid cells and endothelial cells, involving CXCL1 and CXCL2 signaling, was shown to drive metastasis and chemo-resistance in the MMTV-PyMT mouse model of breast cancer (14). In addition, in experimental breast tumors, CXCL12 secreted from CAFs was shown to select for clones of cancer cells with a high Src activity, and the ability to specifically form metastasis in bone with a CXCL12-rich microenvironment (15).

Earlier studies have also linked chemokines and their receptors specifically to EMT. A constitutively active form of CXCR4, the receptor for CXCL12, has been shown to be involved in modulation of breast tumor cell EMT markers and to enhance formation of lymph node metastasis in mice (43). CCR7, the receptor for CCL21, and CXCR5 and its ligand

CXCL13 have been shown to significantly correlate with EMT markers and enhanced lymph node metastasis of human breast tumors (44,45). Moreover, a GM-CSF-CCL18 positive feedback loop have been implied in EMT and breast tumor metastasis in mice and associated with worse outcome in breast cancer patients (16).

The comparison of proteins secreted by NIH-CXCL14 and NIH-ctr cells provided new insight in CXCL14-signaling in fibroblasts and revealed a set of candidates that mediate EMT stimulated by CXCL14-expressing fibroblasts either individually and/ or in combination. For example, CXCL1, CX3CL1, HGF and TIMP-1 and tissue factor have previously been demonstrated to affect EMT and metastasis of breast cancer cells (39,46-48). Recently, Wang et al. identified CCL17 derived from CXCL14-activated fibroblasts as another mediator of

CXCL14-stimulated breast cancer EMT and metastasis (49). Furthermore, CXCL14 was shown to act as a chemoattractant for M2 macrophages that are known to promote EMT

(16,50,51). Together, these findings suggest that CXCL14 operates different axis of stromal signaling shifting the phenotype of stromal cells towards tumor progression and metastasis.

A key finding of the present study is the demonstration that CXCL14-induced molecular signalling and cellular responses depend on ACKR2, classified as an atypical chemokine receptor. ACKR2-dependent CXCL14 signaling was shown in cell types of different origin

(breast cancer cells and fibroblasts) and the downregulation of ACKR2 almost completely abolished CXCL14-induced effects. These data suggest that ACKR2 is a required component of CXCL14 signaling. Findings of ACKR2 expression on some breast cancer cells

(Supplementary Table 2) also suggest the possibility that CXCL14, in certain settings, might be pro-metastatic or EMT-stimulatory through direct effects on malignant cells. This topic should be further explored in future studies. Continued mechanistic analyses are also warranted regarding the roles of CXCL14/ACKR2 on other steps of the metastatic process than those covered by the analyses of the invasive border (Fig. 1) and the “tail-vein” experiment (Fig. 3).

Studies have suggested the chemokine receptors CXCR4 and GPR85 to directly bind

CXCL14 and modulating signalling (49,52). However, Otte et al. demonstrated that CXCL14 does not bind and impact on CXCR4 signaling (53). In line with these data we found that

siRNA-mediated downregulation of CXCR4 did not affect CXCL14-induced MAPK- signaling in MCF7 breast cancer cells (Supplementary Fig. 7C) suggesting that the functions of CXCL14 might be more complex than for other chemokines and might require formation of chemokine- or receptor- heterocomplexes which may explain the difficulty to precisely define its signaling components (54).

These atypical chemokine receptors have earlier been defined as scavenging receptors that bind chemokines with high affinity but are unable to induce signaling and cell migration (11).

Absence of the well-conserved DRYLAIVHA motif (DKYLEIVHA in ACKR2) has been assumed to explain the inability of atypical chemokine receptors to induce downstream receptor signaling subsequent to ligand binding.

In the present study we observe an impact of ACKR2 on the molecular signaling, including

MAPK activation (Fig. 4A-C, Supplementary Fig. 7B and 8A-E) and cellular functions, including enhanced fibroblast proliferation (Fig. 4F and Supplementary Fig. 8F) in response to CXCL14. Independent recent evidence indeed does support signaling functions for some of the atypical chemokine receptors. These signalling properties were proposed to be possibly cell type dependent as in one study, experiments demonstrated coupling of ACKR3 to Gi- proteins and induction of CXCL12-dependent conformational changes, but no activation of calcium signalling (55). Another study confirmed the binding of ACKR3 to PTX sensitive

Gi-proteins and revealed activation of calcium mobilization, ERK- and AKT signalling and enhanced migration and proliferation, subsequent to CXCL12 binding in rodent astrocytes and human glioma cell lines (56). Earlier overexpression-studies have also demonstrated

ACKR2-induced calcium mobilization by murine ACKR2 (57). A recent study also proposed

G protein independent, β-arrestin-dependent, activation of the cofilin pathway (Rac1-p21- activated kinase 1 (PAK1)-LIM kinase 1 (LIMK1) cascade) following ACKR2 stimulation

suggesting that ACKR2 is not a totally silent receptor (58). Taken together, these findings challenge the definition of ACKRs as exclusive non-signalling, chemokine scavenger receptors.

Earlier studies have identified stromal, but not epithelial, CXCL14 as a bad prognosis marker in breast cancer (1). The correlative data of the present study support the notion of functional clinical relevant interaction between CXCL14 and ACKR2. As shown in Fig. 5, the association between CXCL14 and an “EMT-profile” is enhanced when ACKR2-status is integrated in patient classification (Fig. 5A). Similarly, the survival association of CXCL14 in the breast cancer TCGA gene-expression dataset is only detected in analyses that also consider ACKR2 status (Fig. 5B and Supplementary Fig. 14). Importantly, the combined

CXCL14/ACKR2 metric is also a significant marker in multivariable analyses including molecular breast cancer subtypes (Supplementary Table 3). It is recognized that the TCGA- based analyses fails to assign the prognostically relevant ACKR2 expression to the stromal or epithelial compartment. However, the mechanistic studies of the present report suggest that autocrine CXCL14/ACKR2 signalling in the stroma contributes to the survival- and EMT- associations. Compartment-specific analyses of ACKR2 are prompted by the findings of the present study.

In summary, this study thus identifies a novel potentially druggable CXCL14/ACKR2- pathway involved in breast cancer EMT and metastasis. Important tasks for future studies include development of inhibitory agents for initial testing in experimental breast cancer models and further exploration of relevance of this pathway in other tumor types.

Furthermore, these results also encourage continued studies exploring biological activity of

ACKRs and to decipher the exact interplay between CXCL14 with classical and atypical chemokines receptors.

Acknowledgements

Members of the AÖ group are acknowledged for support throughout the studies. Studies were supported by grants from the Swedish Cancer Society, BRECT, the Linné STARGET grant from Swedish Research Council and the KI/AZ-collaborative initiative, the Luxembourg

Institute of Health (LIH) MESR (grants 20160116 and 20170113), Luxembourg National

Research Fund PhD fellows (grants AFR-3004509 and INTER/FWO “Nanokine” - grant

15/10358798). Technical support was provided by the histo-pathology unit of Cancer

Centrum Karolinska. Animal experiments benefited from the expertise of the MTC animal facility.

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Figure legends

Figure 1. CXCL14 affects regulators of EMT and invasion in a xenograft tumor model of breast cancer. (A) Xenograft tumors of MCF7 cells co-injected with NIH-ctr or NIH-

CXCL14 fibroblasts were stained for E-cadherin. White arrowheads indicate epithelial cells with weak E-cadherin expression. Scale bar 50μm. (B) qRT-PCR analysis of transcript levels of genes encoding EMT-regulated markers in xenograft tumors. The analysis comprises epithelial marker (E-cadherin, Cytokeratin 18 and Cytokeratin 8), mesenchymal marker

(Vimentin, α-SMA (encoded by ACTA2) and MMP2), and the EMT transcription factors Slug and Twist (n=5) (C) Staining of xenograft tumors formed following co-injection of MCF7 cells and NIH-ctr or NIH-CXCL14 fibroblasts with the human specific antibody Stem121.

Budding cells (cluster of up to three cells) in the border of the tumor were counted in ten vision fields and results are shown as mean number of cells/vision field (n=5). Scale bar

100μm. . p-values were derived from unpaired two-sided student t-tests. *** p < 0.001, ** p <

0.01 and * p < 0.05. Error bars represent the s.e.m.

Figure 2. CXCL14-fibroblasts induce loss of epithelial marker in breast cancer cells. (A)

Protein levels of E-cadherin in MCF7 and DCIS cells upon co-culture with NIH-ctr or NIH-

CXCL14 fibroblasts were detected by Western blot. Representative blots are shown in the upper panel and quantifications of three independent experiments are shown in the lower panel. (B) Immunofluorescence of MCF7 cells (green) co-cultured with NIH-ctr or NIH-

CXCL14 fibroblasts (red) for the markers depicted in the figure. Arrowheads mark sites of loss of E-cadherin or Cytokeratin 8/18. Scale bar 50μm. (C) Light microscopy pictures of

MCF7 cells exposed for 48 hours to conditioned medium collected from NIH-ctr or NIH-

CXCL14 cells (10x magnification). The number of cells with protrusions was counted in five vision fields in three independent experiments. Results are shown as fold of untreated MCF7

cells. p-values were derived from unpaired two-sided student t-tests. *** p < 0.001, ** p <

0.01 and * p < 0.05. Error bars represent the s.d.

Figure 3. CXCL14-expressing fibroblasts enhance migration stimulate lung colonization of breast cancer cells. (A) MCF7, DCIS and SKBR3 cells were allowed to migrate towards

NIH-ctr or NIH-CXCL14 fibroblasts in a transwell migration assay for 24 hours. Migration was determined by counting DAPI-stained cells that had moved through an 8μm pore size membrane of the transwell (see details in Material & Methods). Results are derived from three independent experiments and are presented as fold of MCF7, DCIS or SKBR3 cells alone. (B) MCF7 cells primed for 72 hours in a transwell co-culture assay with NIH-ctr or

NIH-CXCL14 fibroblasts were injected into the tail-vein of eight-week-old SCID mice

(n=10). (C) Lungs were harvested four weeks after injection of the cancer cells. The number of MCF7 cells (human origin) in mouse lungs was semi-quantitatively assessed by qRT-PCR using human- and mouse-specific primers (see details in Material & Methods). (D) Lung sections from the tail-vein experiment were stained for the human specific marker Stem121.

The number of MCF7 cells in the lung was counted in 10 sections/lung and are depicted as average (n=10). Arrowheads indicate tumor cells. Scale bar 100μm. p-values were derived from unpaired two-sided student t-tests. *** p < 0.001, ** p < 0.01 and * p < 0.05. Error bars represent the s.e.m.

Figure 4: ACKR2 mediates CXCL14-stimulated signaling in fibroblasts. (A) The suppression of ACKR2 expression following introduction of two different ACKR2-targeting shRNA (A and B) in NIH-ctr and NIH-CXCL14 fibroblasts was analyzed by qRT-PCR.

Results are obtained from three independent experiments. (B) The activation of ERK1/2- signaling following CXCL14-stimulation was monitored by Western blot in NIH-3T3

fibroblasts with and without stable downregulation of ACKR2. (C) Quantifications of three independent experiments from (B). (D) Analysis of Nos1 transcript (qRT-PCR) and (E) Nos1 protein (Western blot) levels in NIH-ctr and NIH-CXCL14 derivatives with or without stable downregulation of ACKR2. Panel (E) shows one representative blot together with the quantification of three independent experiments. (F) The growth of NIH-ctr and NIH-

CXCL14 fibroblasts with or without stable down-regulation of ACKR2 was evaluated by the

AlamarBlue assay (see details in Material & Methods) after culture for three days in serum- reduced medium. The results of three independent experiments are summarized in the figure. p-values were derived from unpaired two-sided student t-tests. *** p < 0.001, ** p < 0.01 and

* p < 0.05. Error bars represent the s.d. or s.e.m.

Figure 5: Breast cancer patients expressing high levels of CXCL14 and ACKR2 show enhanced EMT and adverse overall survival. (A) Z-scores of EMT-genes in the TCGA breast cancer gene expression data set, in patients divided in different subgroups with high or low expression levels of CXCL14 and ACKR2 (B) Kaplan-Meier analysis of the

CXCL14high/ACKR2high subgroup compared to the rest of the population (n=1100 patients). p- value is derived from Log-Rank test and HR including confidence interval is from univariate

Cox Regression analyses.

Figure 6: Paracrine effects of fibroblast-derived CXCL14 depend on NOS1 and ACKR2.

(A) Migration of MCF7 cells for 24h in response to NIH-ctr or NIHCXCL14 derivatives without (shCtr) or with stable knockdown of ACKR2 (shACKR2:A and shACKR2:B). (B)

Western blot- analysis and quantification of E-cadherin levels in MCF7 cells subsequent to co-culture with control (shCtr) or ACKR2-targeting (shACKR2:A) NIH-ctr or NIH-CXCL14 fibroblasts for 48h. (C) MCF7 cells were allowed to migrate for 24h towards NIH-ctr or NIH-

CXCL14 derivatives without (shCtr) or with stable knockdown of NOS1 (shNOS1:A and shNOS1:B). (D) Western blot analysis of E-cadherin and Snail levels in MCF7 cells following co-culture with NIH-ctr or NIH-CXCL14 fibroblasts with or without stable suppression of

NOS1 expression. (E) Quantification of Western blots as shown in (B) for E-cadherin (left panel) and Snail (right panel) expression from three independent experiments. Representative blots are shown and quantifications are based on three independent experiments. p-values were derived from unpaired two-sided student t-tests. *** p < 0.001, ** p < 0.01 and * p <

0.05. Error bars represent the s.d. or s.e.m.

Figure 1.

MCF7 + NIH-ctr/shCtr

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CDH1 KRT8 KRT18 KRT19 TSPAN13 SNAI1 SNAI2 SNAI3 TWIST1 GSC ZEB1 ZEB2 CDH2 VIM ACTA2 FN1 MMP2 MMP3 MMP9 COL1A2 COL3A1 COL5A2 SPARC TCF4 WNT5A WNT5B CALD1 GNG11 ITGAV ITGA5 1

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A novel ACKR2-dependent role of fibroblast-derived CXCL14 in epithelial-to-mesenchymal transition and metastasis of breast cancer

Elin Sjöberg, Max Meyrath, Laura Milde, et al.

Clin Cancer Res Published OnlineFirst March 8, 2019.

Updated version Access the most recent version of this article at: doi:10.1158/1078-0432.CCR-18-1294

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