EN1 Is a Transcriptional Dependency in Triple- Negative Breast Cancer Associated with Brain Metastasis Guillermo Peluffo1,2, Ashim Subedee1,3, Nicholas W

Published OnlineFirst June 25, 2019; DOI: 10.1158/0008-5472.CAN-18-3264

Cancer Tumor Biology and Immunology Research

EN1 Is a Transcriptional Dependency in Triple- Negative Breast Cancer Associated with Brain Metastasis Guillermo Peluffo1,2, Ashim Subedee1,3, Nicholas W. Harper1, Natalie Kingston1, Bojana Jovanovic1,2, Felipe Flores1,4, Laura E. Stevens1,2, Francisco Beca5,6, Anne Trinh1,2, Chandra Sekhar Reddy Chilamakuri7, Evangelia K. Papachristou7, Katherine Murphy1, Ying Su1,2, Andriy Marusyk1,2, Clive S. D'Santos7, Oscar M. Rueda7, Andrew H. Beck5,6, Carlos Caldas7, Jason S. Carroll7, and Kornelia Polyak1,2,3

Abstract

To define transcriptional dependencies of triple-negative titative proteomic analyses of EN1-bound chromatin com- breast cancer (TNBC), we identified transcription factors high- plexes revealed association with transcriptional repressors and ly and specifically expressed in primary TNBCs and tested their coactivators including TLE3, TRIM24, TRIM28, and TRIM33. requirement for cell growth in a panel of breast cancer cell High expression of EN1 correlated with short overall survival lines. We found that EN1 (engrailed 1) is overexpressed in and increased risk of developing brain metastases in patients TNBCs and its downregulation preferentially and significantly with TNBC. Thus, EN1 is a prognostic marker and a potential reduced viability and tumorigenicity in TNBC cell lines. By therapeutic target in TNBC. integrating gene expression changes after EN1 downregulation with EN1 chromatin binding patterns, we identified genes Significance: These findings show that the EN1 transcrip- involved in WNT and Hedgehog signaling, neurogenesis, and tion factor regulates neurogenesis-related genes and is associ- axonal guidance as direct EN1 transcriptional targets. Quan- ated with brain metastasis in triple-negative breast cancer.

groups (1). Knowledge of the molecular properties of luminal Introduction þ þ ER and HER2 subtypes has led to the development of endocrine Breast cancer is a heterogeneous group of diseases with different and HER2-targeted therapies. However, currently there is no biological and clinical characteristics. On the basis of the presence effective targeted therapy for triple-negative breast tumors. of estrogen and progesterone receptors (ER and PR), and þ þ Triple-negative breast cancer (TNBC) constitutes 10%–20% of HER2, tumors are classified into ER , HER2 , and ER PR HER2 breast cancer cases in the United States and more commonly (triple-negative) subtypes, whereas gene expression and epige- affects younger and African-American women (2, 3). TNBCs have netic profiles divide breast tumors into luminal and basal higher risk of developing distant metastases and in general have poor clinical outcome. TNBCs are also heterogeneous and have been grouped into luminal, basal, and mesenchymal subtypes 1Department of Medical Oncology, Dana-Farber Cancer Institute Boston, based on gene expression patterns (2–4). However, these sub- Massachusetts. 2Department of Medicine, Harvard Medical School, Boston, types, besides luminal androgen receptor (AR)-positive tumors, Massachusetts. 3BBS Program, Harvard Medical School, Boston, Massachusetts. have not impacted the clinical management of patients with 4Harvard University, Cambridge, Massachusetts. 5Department of Pathology, 6 TNBC (3) highlighting the need for additional molecular markers Harvard Medical School, Boston, Massachusetts. Department of Pathology, to guide treatment decisions. TNBC genome sequencing studies Beth Israel Deaconess Medical Center, Boston, Massachusetts. 7Cambridge Research Institute, University of Cambridge, Cambridge, United Kingdom. have so far failed to identify novel recurrent mutations besides TP53, PIK3CA, and PTEN (2, 3), suggesting that TNBC phenotypes Note: Supplementary data for this article are available at Cancer Research may be driven by nongenetic alterations such as perturbed epi- Online (http://cancerres.aacrjournals.org/). genetic and transcriptional programs. G. Peluffo and A. Subedee contributed equally to this article. The luminal phenotype is defined by a set of lineage-specific Current address for A. Subedee: NIH, Rockville, Maryland; current address for transcription factors including ESR1, FOXA1, GATA3, and SPDEF Y. Su: Deciphera Pharmaceuticals, Waltham, Massachusetts; current address for that also represent transcriptional dependencies in luminal breast F. Beca: Stanford University, Stanford, California; current address for A. Marusyk: fi tumors (2, 3). We hypothesized that transcription factors (TF) Mof tt Cancer Center, Tampa, Florida; and current address for A. H. Beck: PathAI, fi Cambridge, Massachusetts. speci cally expressed in TNBCs may also exemplify such dependencies that can be exploited therapeutically and may divide Corresponding Author: Kornelia Polyak, Dana-Farber Cancer Institute, 450 TNBC into clinically relevant subsets. To test this hypothesis, first Brookline Ave, Boston, MA 02215. Phone: 617-632-2106, Fax: 617-582-8490, fi E-mail: [email protected] we selected TFs that are highly and speci cally expressed in primary TNBCs followed by a targeted cellular viability screen Cancer Res 2019;79:4173–83 for these TFs in a panel of breast cancer cell lines of different doi: 10.1158/0008-5472.CAN-18-3264 subtypes. Using this approach, we have identified several TFs 2019 American Association for Cancer Research. specifically required for the survival of TNBCs and among these

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further characterized EN1, a TF with known roles in brain (5, 6) PBS, cells were plated in fresh medium into collagen-coated and dermomyotome (7) development. plates. Cells were collected at 0, 3, 9, 12, and 24-hour timepoints for FACS and immunoblot analyses. For cell-cycle analysis, cells were harvested, washed in PBS, and fixed in ice-cold 70% ethanol Materials and Methods at 20C overnight. Fixed cells were resuspended in a solution Cell lines containing 100 mg/mL RNase and incubated for 30 minutes at Breast and colon cancer cell lines were obtained from ATCC or 37C with agitation. The cells were then resuspended in a solution generously provided by Steve Ethier (SUM149 and SUM159 cell containing 40 mg/mL propidium iodide (Sigma), and the analysis lines, University of Michigan, Ann Arbor, MI). Cells were cultured was performed on a FACS Aria II Cytometer (BD Biosciences). in media recommended by the provider, except SUM149 and SUM159 cells were cultured in DMEM/F12 supplemented METABRIC expression and survival analysis with 5% FBS, 10 mmol/L HEPES pH7.4, 1 mg/mL hydrocortisone, Expression analysis was performed on METABRIC dataset. 5 mg/mL insulin, 50 U/mL penicillin, and 50 mg/mL streptomycin. Using the EN1 mRNA expression distribution we separated EN1 MCF7 cells were cultured in 4.5mg/L glucose DMEM supplemen- expression into four clusters using a univariate Gaussian mixture ted with 10% FBS, 10 mg/mL insulin, 50 U/mL penicillin, and model–based clustering (mclust version 5.4.2 package for R; 50 mg/mL streptomycin. Cells were cultured at 37 C with 5% CO2. refs. 8–10). Using the EN1-defined clusters, Kaplan–Meier sur- The identities of the cell lines were confirmed by short tandem vival curves were plotted and a log-rank P value was computed repeat analysis; and they were regularly tested for Mycoplasma. using the function km.coxph.plot in the R package survcomp. Next, the survival in the C4 cluster was compared with the other Generation of cell line derivates clusters. A univariable Cox proportional hazards analysis was SUM149 and SUM159 cells expressing TET-inducible short performed using the coxph function in R to assess the association hairpin RNAs (shRNA) targeting EN1, CTNNB1,orNLGN4X in of EN1 mRNA expression with overall survival. A multivariable pLKO lentiviral vector were generated by selecting with 5 mg/mL Cox proportional hazard analysis was performed using the coxph puromycin for 5 days after lentiviral infection. Entry cDNA open function in R, and the age, the Nottingham Prognostic Index, and reading frame (ORF) for EN1 in pENTR221 was obtained from continuous EN1 expression were considered. The EN1 expression human ORFeome collection v5.1. pCDNA3-CTNNB1 and z-scores of 243 triple-negative tumors from the METABRIC cohort pCDNA3-CTNNB1S33Y were obtained from Addgene. Lentiviral were computed and the mean levels in the primary tumor for expression constructs were generated by Gateway swap into patients that had a brain metastasis (n ¼ 17) and patients that did pLenti6.3/V5-Dest Vector (Life Technologies) and sequence ver- not (n ¼ 226) were compared using a two-sided t test. Differential ified. MCF7-lacZ and MCF7-EN1 cells were selected with 5 mg/mL gene expression was performed using two-class unpaired signif- blasticidin. icance of microarray analysis (SAM 2.0 package, R 3.2.2) in basal carcinomas in the C1, C2, and C3 cluster and the C4 cluster. Next, Colony growth assays we performed a preranked GSEA (gene set enrichment analysis) A total of 500–1,500 cells expressing TET-inducible EN1- or using software provided by the Broad Institute (http://www.broad CTNNB1-targeting shRNAs were plated into each well of a 6-well institute.org/gsea/msigdb/annotate.jsp) on a ranked gene list plate. Next day, regular media (no doxycycline control) or ranked (after exclusion of EN1 gene) based on the d-statistic media containing 500 ng/mL doxycycline were added to induce computed from the differential expression analysis, and we shRNA-mediated downregulation. The media was changed every assessed enrichment using the Broad Institute's Molecular Signa- 2 days and colonies stained with 0.5% crystal violet solution after tures Database (mSigDB) Hallmark gene sets collection (n ¼ 50). 10–15 days. Statistical analysis Xenograft assays Unpaired two-tailed Student t tests were used except otherwise Animal experiments were approved by DFCI Institutional stated. P < 0.05 was defined as statistically significant. Animal Care and Use Committee under protocol #11-023. SUM149 or SUM159 cells (1 106) expressing TET-inducible Accession codes luciferase or EN1-targeting shRNAs were resuspended in 50% Gene Expression Omnibus (GEO): RNA-seq and chromatin Matrigel (BD Biosciences) and injected orthotopically into the immunoprecipitation–sequencing (ChIP-seq) datasets have been mammary fat pads of 6-week-old female NOG mice (Taconic). deposited to GEO with accession number GSE120957. When the tumors became palpable, shRNAs were induced in the treatment group by administering a doxycycline diet (625 ppm). Animals were euthanized and tumors were harvested when Results tumors in the control group reached approximately 1.5 cm size. TNBC-specific transcription factors For histologic analyses, 5-mm sections of formalin-fixed, paraffin- We previously analyzed the inheritance pattern of basal/ embedded tissue slides were stained with hematoxylin and eosin mesenchymal and luminal phenotypes by generating and char- using standard protocols. acterizing somatic cell fusions between luminal and basal/ mesenchymal breast cancer cell lines (11). We determined that Cell-cycle analyses the basal/mesenchymal phenotype is dominant, and it is defined Thirty-six hours after induction of EN1 shRNA with doxycy- by epigenetic factors. We also identified 17 TFs, the expression cline, these cells and the control cells were treated with nocoda- of which strongly correlated with the inheritance of basal/ zole (200 ng/mL) for 12 hours. Plates were tapped multiple times mesenchymal phenotype and was also significantly higher in to detach cells arrested in G2–M-phase. After washing twice with TNBCs compared with other subtypes in the The Cancer Genome

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A C METABRIC dataset TNBC (n = 42) Non-TNBC (n = 364) 6 ZNF639 TRIP13 MYBL1 MED30 PPARD 4 HMGA1 FOSL1 CEBPB ETV5 EN1 2 DEPDC7 IFI16 AIM2 JAG1 TBX18 mRNA Expression (z-score) ATF3 0 CEBPD EN1

Row min Row max

Basal Clau HER2 LumA LumB Norm Unclass B E 199 199 220 679 461 140 6 SUM149 SUM159 1,200 P = 0.0077 P < 0.0001 HCC70 HS578T MDAMB231 SUM149 MCF-12A MCF7 BT474 MDAMB453 SUM190 SKBR3 BT-549 HCC38 HCC1954 MDAMB468 SUM159 MCF-10A ZR75-1 T47D 1,400 AIM2 1,000 1,200 P < 0.0001 P < 0.0001 ATF3 800 1,000 CEBPB CEBPD 600 800 DEPDC7 600 EN1 400 Tumor weight (g) 400

ETV5 Tumor weight (g) 200 200 FOSL1 HMGA1 0 0 IFI16 Doxycycline ---+ ++Doxycycline ---+ ++ JAG1 shluc shEN1-1 shEN1-2 shluc shEN1-1 shEN1-2 1,400 MED30 1,200 shluc shluc MYBL1 1,000 shluc +dox 1,200 shluc +dox EN1 EN1 PPARD sh -1 1,000 sh -1 TBX18 800 shEN1-1 +dox shEN1-1 +dox EN1 800 EN1 TRIP13 sh -2 sh -2 600 EN1 EN1 ZNF639 sh -2 +dox 600 sh -2 +dox

Tumor weight (g) 400 % Viability 400 Tumor weight (g) 0 100 0 100 0 100 200 200 0 0 5 1015202530 5 1015202530 D Days Days

) 70 SUM149 3 F shLuc shEN1-1 shEN1-2 60 shLuc Dox -+ --++ 50 shLuc + dox shEN1-1 40 shEN1-1 + dox EN1 30 sh -2 shEN1-2 + dox P < 0.0001 20 10 SUM149 Cell number (×10 P < 0.0001 SMA 0 DAPI 012345 Days

) 90 3 SUM159 80 70 60 50 SUM159 40 SMA DAPI 30 P < 0.0001 20 P < 0.0001 Time after release from G/2M arrest

Cell number (×10 10 G 0 h 3 h 9 h 24 h 0 012345 Dox Days ) 3 60 MCF7

50 - P < 0.0003 40 P < 0.0001 30 20 sh EN1-2 10 Cell number (×10 0 012345

Days +

Figure 1. TFs in nonluminal breast cancers. A, Expression of selected TFs in TNBC and non-TNBC breast tumors in the TCGA dataset. Colors reflect z-scores normalized to depict relative values for each factor. B, Heatmap depicting cell viability siRNA screen for 17 TFs in 18 breast cancer cell lines: 9 nonluminal (red), 2 immortalized mammary epithelial cell lines (orange), and 7 luminal (blue). Shading indicates percentage (0%–100%) of viable cells after siRNA-mediated downregulation of the selected factors compared with nontargeting siRNA control. C, Boxplot depicting the expression of EN1 in breast tumor subtypes (basal, claudin-low, HER2, luminal A, luminal B, normal-like, and unclassified) in the METABRIC dataset. Numbers indicate number of tumors in each subtype. D, Proliferation of SUM149, SUM159, and MCF7 cell lines following downregulation of EN1 by TET-inducible shRNAs. shluc was used as control. E, Plots depicting tumor volume and weights at 30 days after injection of TET-inducible shluc- or shEN1-expressing SUM149 and SUM159 cells, respectively, in the presence (þDox) and absence (Dox) of doxycycline. F, Immunofluorescence staining of SMA expression in SUM149 and SUM159 xenografts expressing TET-inducible shluc or shEN1 grown in presence (þ) or absence () of doxycycline. Scale bars, 50 mm. G, Cell-cycle profile of SUM159 cells expressing TET-inducible shEN1 grown in presence (þ) or absence () of doxycycline, synchronized in G2–M-phase, and analyzed at different timepoints (0, 3, 9, and 24 hours) after release.

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Atlas (TCGA) dataset (Fig. 1A; ref. 12) and in basal compared with downregulation (Fig. 1F). To determine whether this is due to other breast tumors in the Gene Expression-Based Outcome for increased recruitment of mouse stroma, we performed immuno- Breast Cancer Online (GOBO) dataset (Supplementary Fig. S1A; FISH using mouse and human-specific DNA probes combined þ ref. 13). To determine whether these TFs are specifically required with SMA immunofluorescence and confirmed that SMA cells for the survival or proliferation of TNBC cells, we performed a are mouse myofibroblasts (Supplementary Fig. S2D). In line with targeted siRNA screen of all 17 TFs in 18 breast cancer cell lines of this, IHC analysis of p63, a basal cell–specific TF, showed no different subtypes. Downregulation of multiple factors (CEBPB, significant change in expression following EN1 downregulation EN1, JAG1, MED30, PPARD, and TRIP13) led to a more than 50% (Supplementary Fig. S2E). decrease in viable cell numbers in multiple basal/mesenchymal To investigate mechanisms underlying EN1 loss–induced cell lines with only modest reduction of viability in a few luminal decrease in cellular viability, we analyzed the cell-cycle profile of lines (Fig. 1B; Supplementary Fig. S1B). This subtype specificity of synchronized SUM159 cells following downregulation of EN1. difference in cellular viability was statistically significant (P < SUM159 cells expressing TET-inducible EN1-targeting shRNAs 0.05) for EN1, PPARD, and TRIP13. EN1 displayed the most were synchronized in G2–M-phase with nocodazole 36 hours TNBC-specific expression pattern in primary tumors and the most after induction of shEN1. Upon release from G2–M-phase block- significant and specific effect on viability in basal/mesenchymal ade by washing off nocodazole and replating the cells in fresh versus luminal breast cancer cell lines; thus, we investigated it in medium, cells with downregulation of EN1 arrested in G1, where- further detail. as the majority of control cells progressed to S and G2–M-phase by 9 and 24 hours, respectively (Fig. 1G). The relatively low levels of High expression and essential role of EN1 in TNBC phospho-histone H3 (phosphorylated in metaphase of mitosis) We further explored the expression of EN1 in primary breast in control cells at 24 hours (Supplementary Fig. S2F) despite the tumors by analyzing the METABRIC (14), TCGA, and GOBO high fraction of cells with 4n DNA content based on FACS could datasets, and confirmed its specific and high expression in basal be due to the cells being more in G2/early–M-phase than in later breast tumors compared with other subtypes (Fig. 1C; Supple- phases of mitosis when histone H3 is phosphorylated. The down- mentary Fig. S1C). Similarly, EN1 was highly expressed in non- regulation of EN1 in synchronized cells led to a notable reduction luminal compared with luminal breast cancer cell lines (Supple- of CCND1 and c-MYC protein levels that was the most significant mentary Fig. S1D) and there was a highly significant correlation at later (9 and 24 hour) time-points after release when control 2 (R ¼ 0.85; P < 0.0001) between EN1 mRNA levels and the degree cells entered S/G2–phase of the cell cycle (Supplementary Fig. of loss of cellular viability following its downregulation by siRNAs S2F). This decrease in cyclin D1 and c-MYC could directly play a (Supplementary Fig. S1E). We could detect neither endogenous role in the EN1 loss–mediated growth suppression. CCND1 and EN1 protein levels nor the effect of shEN1 on EN1 protein due to c-MYC are targets of the WNT signaling pathway and EN1 is a our inability to reliably detect EN1 with any of the 13 commer- known WNT target during brain development (15). Thus, the cially available EN1 antibodies tested (see Supplementary Mate- decrease in CCND1 and c-MYC levels following EN1 loss in rials and Methods). SUM159 cells could potentially indicate downregulation of WNT We validated the results of siRNA-mediated downregulation of signaling. At later timepoints following EN1 downregulation, we EN1 by TET-inducible EN1-targeting shRNAs (Supplementary Fig. observed an increase in apoptosis based on an increase in sub-G1 S1F). shRNA mediated downregulation of EN1 in SUM149 basal population by FACS (Supplementary Fig. S2G and S2H) and and SUM159 mesenchymal TNBC lines, but not in non-TNBC increase in cleaved caspase-3 levels (Supplementary Fig. S2I). MCF7 luminal cells showed significant reduction in cellular These results correlate with the antiapoptotic function of EN1 in viability (Fig. 1D). Overexpression of a constitutively expressed dopaminergic neurons and suggest similar roles for EN1 in EN1 in SUM159 cells was able to partially rescue this growth TNBC (16). inhibition in a dose-dependent manner confirming the specificity of shEN1 (Supplementary Fig. S1G). Unfortunately, we could not Transcriptional and genomic targets of EN1 in TNBCs identify an shRNA targeting the noncoding region of EN1, thus, Next, we examined changes in gene expression profiles of the overexpressed EN1 was still sensitive to the shRNA, leading to SUM149 and SUM159 cells expressing TET-inducible shEN1 at partial rescue likely due to this. Downregulation of EN1 also led to 3 days and 5 days after doxycycline treatment. A large fraction of significant reduction of colony forming ability of SUM149 and genes displayed similar expression changes in both cell lines SUM159 cells, but not in the MDA-MB-231 TNBC cell line that has analyzed (Fig. 2A; Supplementary Fig. S3A and S3B; Supplemen- no detectable levels of EN1 mRNA further supporting that the tary Table S1). We also performed RNA-seq on SUM149 and decrease in cell viability after shEN1 expression is due to down- SUM159 xenografts from control and doxycycline-treated mice. regulation of EN1 (Supplementary Figs. S1D and S2A). The number of differentially expressed genes was significantly To determine whether EN1 is essential for tumor growth in vivo, higher in cell culture at relatively early timepoints after EN1 we performed xenograft studies using SUM149 and SUM159 downregulation compared with the xenografts that were collected cells expressing two independent TET-inducible EN1-targeting 30 days after injection into mice. Furthermore, residual tumors shRNAs. Xenografts were allowed to grow to palpable size before observed in doxycycline-treated mice apparently escaped the inducing shRNA expression (Supplementary Fig. S2B). Down- shRNA effect based on the lack of significant differences in EN1 regulation of EN1 significantly reduced tumor weight, volume, mRNA levels between control and doxycycline conditions (Sup- and cellularity in xenografts derived from both SUM149 and plementary Table S1). Functional analysis of genes differentially SUM159 cell lines (Fig. 1E; Supplementary Fig. S2C). Immuno- expressed after EN1 knockdown in vitro or in vivo using Meta- fluorescence analysis of smooth muscle actin (SMA), a marker of core (17) revealed enrichment in development, inflammation, stromal myofibroblasts and myoepithelial cells, demonstrated a and cell adhesion/migration-related pathways including WNT þ significant increase in SMA cells within tumors following EN1 and Hh signaling, and neurogenesis (Fig. 2B). We analyzed the

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ABDay 3 Day 5 MMP3 Cell adhesion 6 8 cytoskeleton, Development Inflammation MMP3 proteolysis immune resp. RPSAP52 SCEL GBP6 4 HLH MMP1

CRYM 4 ESM1 GGT8P MMP1 SERPINB2 2 fold change fold change 2 2

0 0 SUM159 log SUM159 log

−2 CDKN3 STAC2 −4 OR7A5 300 PIPOX Count CYP4B1

CASP14 0 SLC30A2 08 − −4 DMGDH log10 (FDR) −5.0 −2.5 0.0 2.5 5.0 7.5 −5 0 5 Th17−derived cytokines Regulation of cytoskeleton rearrangement Cell−matrix interactions Amyloid proteins Synaptic contact Integrin−mediated cell−matrix adhesion Attractive and repulsive receptors Cell junctions Cytoplasmic microtubules Cytoskeleton_actin filaments Spindle microtubules ECM remodeling WNT signaling Hedgehog signaling Blood vessel morphogenesis Neurogenesis_axonal guidance Regulation of angiogenesis Cartilage development Neurogenesis_synaptogenesis Skeletal muscle development FGF_ErbB signaling MIF signaling Kallikrein−kinin system Innate inflammatory response Histamine signaling Complement system IL−6 signaling Interferon signaling Amphoterin signaling Intermediate filaments Regulation of epithelial−to−mesenchymal transition Neurogenesis in general Platelet−endothelium−leucocyte interactions Neutrophil activation Protein C signaling Innate immune response to RNA viral infection SUM149 log2 fold change SUM149 log2 fold change Connective tissue degradation IL−10 anti−inflammatory response Day5 SUM159 C SUM149 SUM159 Day3 2 Day5 1 D SUM149 sh EN1 -2 2 Day3 in vitro 3 1 shEN1-2 SUM159 shLuc Up shEN1-2 0 SUM149 Luc SUM149 −2.0 2.0 − 2.0 2.0 sh in vivo 100 Static (background) Day5 SUM159 Upregulate (1.1e−05) Day3 Downregulate (0.000276) Day5 0.8 80 SUM149 in vitro Day3 sh EN1 -2 shEN1-2 60 shLuc SUM159 Down shEN1-2 0.7 SUM149

Luc in vivo 40 sh

20 0.6 E proteolysis Cell adhesion

1 (2,971) 0 Cell−matrix interactions Cumulative fraction of genes% 0 1,000 2,000 3,000 4,000 5,000 6,000 Synaptic contact 0.5 Rank of genes based on Regulatory Potential Score Attractive and repulsive receptors Connective tissue degradation

SUM159 Blood vessel morphogenesis Develop 100 Static (background) Neurogenesis_axonal guidance 0.4 Upregulate (0.964) Neurogenesis_synaptogenesis 80 Downregulate (0.307) Regulation of angiogenesis

GnRH signaling pathway neurop hysiology signaling Reproduction FSH−beta signaling pathway 0.3 60 Gonadotropin regulation 40 Progesterone signaling WNT signaling MIF signaling 0.2 20 Transmission of nerve impulse 2 (840) Color key 0 30 Cumulative fraction of genes% 0.1 0 500 1,000 1,500 2,000 2,500 3,000 3,500 Rank of genes based on Regulatory Potential Score 15 SUM149 SUM159 SUM159 SUM149 Count 3 (383)

Down Up 0 0.0 02 −2.0 2.0 −2.0 2.0 − Gene distance (kbp) log10 (FDR)

F 92 kb SUM149

SUM159

TCF7L1

44 kb SUM149

SUM159

WISP1

Figure 2. Transcriptional and genomic targets of EN1 in TNBC cells. A, Gene expression changes in SUM149 (x-axis) and SUM159 (y-axis) cells expressing TET-inducible shEN1 grown in presence of doxycycline for 3 or 5 days. Red and blue indicates significantly up- and downregulated genes, respectively, in both cell lines. B, Top process networks significantly enriched in genes differentially expressed following EN1 downregulation in SUM149 and SUM159 cell lines grown in cell culture (in vitro) or as xenografts (in vivo). C, Plot of ChIP-seq signal of the EN1 peaks in SUM149 and SUM159 cells. Numbers indicate cell line unique and overlapping peaks. D, BETA factor function prediction analysis to predict EN1 direct transcriptional function (activating/repressing) in SUM149 and SUM159 cells. Red and blue lines, up- and downregulated genes following EN1 knockdown. Black dashed line, static genes. Genes are ranked by regulatory potential score, and significance relative to static genes was determined by Kolmogorov–Smirnov test. E, Top process networks significantly enriched in genes that were direct genomic targets of EN1 and were differentially expressed 3 days following EN1 downregulation in SUM149 and SUM159 cell lines. Each ChIP-seq peak is assigned to the gene whose transcription start site is closest to the peak, defining the factors direct genomic targets. F, EN1 ChIP-seq signal at selected genes in SUM149 (red) and SUM159 (green) cells. Thick black lines below the signal tracks denote peaks.

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expression of genes involved in WNT signaling in further detail (Supplementary Fig. S4A–S4C). Similarly, downregulation of and found that the majority showed decreased levels after shEN1 CTNNB1 in SUM159 cells did not affect cellular viability and expression in both cell lines and timepoints highlighting the colony growth (Supplementary Fig. S4D–S4F). Finally, we impact of EN1 expression on WNT pathway activation (Supple- tested the effect of several compounds targeting different steps mentary Fig. S3C). We validated the expression of WISP1 and of the canonical WNT signaling pathway (i.e., porcupine, WISP2, direct transcriptional targets of b-catenin (3), by immu- tankyrase, and WNT inhibitors, and Axin2 activator) on the noblot analysis of cell lysates from cell cultures and xenografts and growth of TNBC (SUM149 and SUM159, high EN1 expression) þ confirmed their decline after shEN1 expression (Supplementary and luminal ER (MCF7 and T47D, no EN1 expression) breast Fig. S3D and S3E). cancer cells, but did not find any significant subtype-specific To identify the direct genomic targets of EN1, we performed differences or associations with the degree of growth inhibition ChIP-seq in SUM149 and SUM159 cells for EN1 and histone H3 and endogenous b-catenin or EN1 levels (Supplementary Fig. lysine 27 acetyl (H3K27ac) associated with transcriptionally S4G and S4H). Thus, EN1 appears to modulate WNT signaling active regions to define super enhancers (SE) (18). The validity in TNBC cells via alternative mechanisms not directly involving of the EN1 ChIP-seq data was confirmed based on (i) the data CTNNB1 itself. passing all quality control in the ChiLin 2.0 pipeline, (ii) ChIP-seq using the antibody against endogenous EN1 and V5-tagged EN-1 The effect of EN1 expression in luminal breast cancer cells showed high correlation in all three cell lines tested (Supplemen- Our prior data demonstrated that EN1 was one of the few TFs tary Fig. S3F), (iii) the number of peaks correlated with endog- that were able to switch MCF7 luminal breast cancer cells to a enous EN1 levels; for example, SUM149 cells have higher endog- more basal/mesenchymal phenotype (11). To investigate whether enous EN1 than SUM159 cells and have more EN1 ChIP-seq this is due to the reprogramming of the epigenetic landscape by peaks than SUM159 cells (3,354 vs.1,223), and (iv) the peaks EN1, we expressed EN1 in MCF7 cells and confirmed the switch to showed enrichment in EN1 sequence motif (Supplementary Fig. a more mesenchymal phenotype based on morphologic changes, S3G). The majority of EN1 peaks were located in nonpromoter as well as increased migration and invasion (Fig. 3A), although regions in both cell lines (Supplementary Fig. S3H) and a signif- the cells maintained their estrogen dependence for growth (Sup- icant fraction overlapped between the two cell lines with SUM149 plementary Fig. S5A). Interestingly, EN1 expression did not have cells having more unique peaks consistent with the higher expres- the same effect in the T47D luminal breast cancer cell line sion level of EN1 in this cell line (Fig. 2C). EN1 and H3K27ac highlighting the importance of cellular context (Supplementary peaks also demonstrated significant overlap in both cell lines Fig. S5B). Similar context-dependent observations were also made (Supplementary Fig. S3I). Analysis of SEs for core regulatory for several other EMT-inducing TFs including ZEB1 and circuits (19) revealed ZNF217, POU3F3, ELF5, and KLF4 as master TWIST (21). However, genes differentially expressed after EN1 TF key for the establishment of the SE landscape in SUM159 cells, downregulation in SUM159 and SUM149 cells that are also direct whereas in SUM149 cells it uncovered a larger set of TFs including EN1 targets did classify primary breast tumors into basal and EN1 that formed an interconnected network centered around nonbasal subsets highlighting the role of EN1 and its targets in MYC based on STRING protein interaction network analysis regulating luminal and basal subtypes (Supplementary Fig. S5C). (Supplementary Fig. S3I; ref. 20). To examine whether EN1 binds to and regulates the same Next, we explored whether the up- or downregulated genes set of genes in MCF7 cells as it does in TNBC cell lines, we were more likely to be direct EN1 targets at different timepoints performed RNA-seq and EN1 ChIP-seq comparing MCF7-lacZ after EN1 downregulation. On the basis of the fraction of direct and MCF7-EN1 cells. We found that a subset of EN1 peaks EN1 targets up- or downregulated (Supplementary Fig. S3K) and overlapped among the three cell lines, but there were numerous on BETA analysis (Fig. 2D; Supplementary Fig. S3L), EN1 appears MCF7-specific EN1 peaks as well. (Fig. 3B). Integrating EN1 ChIP- to both positively and negatively regulate gene expression in both seq and RNA-seq data demonstrated that EN1 targets in MCF7 TNBC cell lines with more genes being up than downregulated in cells include genes both up- and downregulated after EN1 expres- SUM149 cells. The top process networks enriched for direct EN1 sion (Supplementary Fig. S5D and S5E; Supplementary Table S3). targets that were up- or downregulated after shEN1 expression, Functional analysis of differentially expressed genes that are EN1 were essentially the same as observed for differentially expressed targets showed higher number of process networks enriched in genes with WNT signaling and neurogenesis-related functions downregulated genes after EN1 overexpression including many showing the most significant enrichment (Fig. 2E). Examples for development- and neurogenesis-related pathways such as axonal EN1 targets include TCF7L1 transcription factor and WISP1- guidance, WNT, and NOTCH signaling (Fig. 3C). secreted growth factor mediating WNT signaling (Fig. 2F; Sup- To determine whether the luminal-to-mesenchymal switch plementary Table S2). Thus, similar to brain and dermomyotome, observed in EN1-expressing MCF7 cells is due to the EN1's EN1 may modulate WNT signaling and neural-related functions modulation of chromatin binding of luminal TFs such as FOXA1, in TNBC (15). a lineage determining TF, we performed FOXA1 ChIP-seq on To investigate the EN1–WNT pathway link in more detail, we LacZ- and EN1-expressing MCF7 cells. Overall there was a sub- tested the effects of wild-type or a constitutively active S33Y stantial overlap between FOXA1 and EN1 peaks, and while mutant b-catenin overexpression or CTNNB1 downregulation in we identified some FOXA1 peaks that were only detected in SUM159 and SUM149 cells. Endogenous b-catenin and phospho- MCF7-lacZ or in MCF7-EN1 cells (Supplementary Fig. S5F and b-catenin levels were higher in SUM149 compared with SUM159 S5G; Supplementary Table S4), the majority of FOXA1 peaks were cells, but downregulation of EN1 had no effect on these in either the same in the two cells. These data imply that EN1 expression cell line (Supplementary Fig. S4A). Overexpression of CTNNB1 does not significantly affect FOXA1 chromatin binding, although and CTNNB1S33Y in SUM159 cells had no effect on cellular it might still modulate FOXA1 transcriptional activity for a subset viability and did not rescue the EN1 loss–induced growth arrest of its target genes.

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WNT signaling A Migration Invasion C D PPP1R8 TGF−beta, GDF and Activin signaling MCF7 NCOR2NOSIP 500 P 140 P MSH6 < 0.0001 = 0.0362 NOTCH signaling HTATSF1ZMYND8CBX3 NAB2 120 WDHD1OGT DPF2 400 Cholecystokinin signaling SIN3ATRPS1CEBPBGTF2I 100 FSH−beta signaling pathway FEN1 NELFBPSMD5 HAT1TLE1 TRIM28 300 80 Neurogenesis_axonal guidance TRIM33 EN1 Cartilage development RXRA 60 WIZ CSE1L 200 ANP32ETLE3GNL1USP7 8 Blood vessel morphogenesis TRIM24 PUS1 40 Keratinocyte differentiation CBX1FANCI 100 Count PPM1GSMAD3MSH2 04 XPO5 20 012 Regulation of angiogenesis MORC3 ZNF217

Number of invading cells GRHL2 − ZMYM2 Number of migrating cells log (FDR) RNH1 10 G −S Interleukin regulation CBX5RTFDC1CHD4 0 0 1 SUDS3TBL1XR1SART3 LacZ EN1 LacZ EN1 G0−G1 GTF3C1 G1−S Growth factor regulation SUM159 ZMYND8PRPF31 Negative regulation of cell proliferation KIF4AWDHD1TRIM24 B MSH6 TBL1XR1 Down Up ANP32E MCF7 SUM149 SUM159 PSME3 NOSIP 1 (2,070) TLE3 peaks RNH1 2 (2,843) XRCC6 TLE3EN1FKBP5FANCI 2 3 (823) Control shEN1 EN1 peaks PSMD5 TRIM33 USP7 4 (126) RPA1 5 (17) 2 1 (11,428) MTA2 SIN3A 6 (365) F 2 (7,150) IRX2RSRC2PREBNCOR1 7 (18) 3 (616) 4 (16,604) PPM1G CC2D1B 5 (24) PXN 0 6 (152) TRIM28AKAP13 HCFC1 -2.0 2.0 −2.0 2.0 −2.0 2.0 7 (428) SEC13 0 GNL1ATG2A 0.7 -2.0 2.0 −2.0 2.0 −2.0 2.0 MORC3 UBAP2 0.8 MNAT1PUS1LONP1 ZYXCHD4 CEBPBCALCOCO2XPO5 MAGEC2HTATSF1PUF60 FAM192AHDAC2 1 0.6 0.7 1 E Apoptotic nucleus Cell cycle Apoptosis Meiosis 0.6 0.5 Mitosis S-phase BER−NER repair

0.5 DNA damage 2 0.4 Checkpoint Core 0.4 3 2 DBS Repair 0.3 MMR Repair Androgen receptor nuclear signaling Transcription Signal transduction 0.3 ESR1−Nuclear pathway 0.2 ESR2 pathway

4 0.2 Chromatin modification Transcription by RNA polymerase II 3 0.1 Color key

0.1 8 4 5 4 MCF7 Count 6 SUM159 0

7 0.0 −2.0 2.0 −2.0 2.0 −2.0 2.0 765 0.0 048 −2.0 2.0 −2.0 2.0 −2.0 2.0 Peak distance (kbp) Peak distance (kbp) Peak distance (kbp) −log10(FDR) Peak distance (kbp) Development G Cartilage development Cell adhesion Neurogenesis_axonal guidance H Attractive and repulsive receptors Ossification and bone remodeling Inflammation Regulation of angiogenesis Interferon signaling Blood vessel morphogenesis Reproduction Development_neurogenesis Gonadotropin regulation Axonal guidance GnRH signaling pathway Development FSH−beta signaling pathway Blood vessel morphogenesis Progesterone signaling Inflammation Feeding and neurohormone signaling

Proteolysis Cytoskeleton, Cell adhesion NK cell cytotoxicity ECM remodeling Platelet aggregation Chemotaxis Cadherins Regulation of cytoskeleton rearrangement Signal transduction Cell−matrix interactions WNT signaling Connective tissue degradation Inflammation MIF signaling Immune resp. Inflammation Histamine signaling Kallikrein−kinin system Reproduction Histamine signaling Progesterone signaling IL−10 anti−inflammatory response Muscle contraction Th17−derived cytokines Negative regulation of cell proliferation Apoptosis Proliferat. Cell adhesion Anti−apoptosis by ext signals via PI3K/AKT Integrin priming Up Anti−apoptosis by ext signals via MAPK and JAK/STAT Signal transduction Down Cholecystokinin signaling Up Up Up Up 0123 Count Down Down Down Down 40 100 -log(FDR)

-Dox+Dox -Dox+Dox 0 02 − SUM149 SUM159 log10(FDR)

Figure 3. EN1-associated chromatin complexes in breast cancer cells. A, Cell migration and invasion of MCF7 cells expressing lacZ or EN1. P value of difference indicated (t test). B, Plot of ChIP-seq signal of the EN1 peaks in SUM149, SUM159, and MCF7 cells. Numbers indicate cell line unique and overlapping peaks. C, Top process networks signiﬁcantly enriched in genes that were direct genomic targets of EN1 and were differentially expressed following EN1 expression in MCF7 cells. D, Word clouds illustrating top EN1-associated proteins in MCF7 and SUM159 cells. E, Top process networks enriched in EN1-interacting proteins in MCF7 and SUM159 cells. F, Heatmap and clustering of TLE3 and EN1 peaks in SUM159 cells. G, Top process networks enriched in differentially expressed genes after EN1 knockdown associated with TLE3-EN1 overlapping peaks in either control (-dox) or shEN1 (þdox) conditions. H, Top process networks enriched in b-catenin peaks in SUM149 cells associated with genes differentially expressed after EN1 knockdown.

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EN1 interacting proteins in breast cancer cells However, even within basal breast cancers there was a significant During brain development, EN1 function is modulated by its heterogeneity for EN1 expression and tumors could be divided interaction with coactivators and corepressors such as PITX3 (22) into four groups based on EN1 expression distribution using finite and TLE3 (23). To identify EN1-associated factors in MCF7 normal mixture modelling (mclust package for R, version 5.4.2; and SUM159 breast cancer cells that exogenously express EN1 Fig. 4A; Supplementary Fig. S6A; refs. 8, 9). Tumors with the with a V5 tag, we performed qPLEX-RIME (quantitative multi- highest EN1 expression were enriched for WNT signaling and plexed rapid immunoprecipitation mass spectrometry of endog- MYC target genes (Fig. 4B) and showed worse overall survival enous proteins; ref. 24) using the anti-V5 antibody. We identified (Fig. 4C). A Cox multiple regression model including tumor numerous EN1-associated proteins in both cell lines, which we grade, size, and numbers of positive lymph nodes demonstrated also confirmed by coimmunoprecipitation (Fig. 3D; Supplemen- statistically significant (P ¼ 0.0085) association between metas- tary Fig. S5H). EN1-associated proteins showed significant enrich- tasis-free survival and EN1 expression. Similarly, in the TCGA ment in chromatin modification, AR signaling, and DNA damage dataset, basal breast tumors with high EN1 expression had worse functional categories (Fig. 3E). Several of the EN1-interacting overall survival than those with low EN1 levels, but this did not proteins common between the two cell lines represent transcrip- reach statistical significance likely due to the relatively smaller size tional cofactors TLE3 and TRIM28 (25), and nuclear hormone of this cohort and more limited numbers of basal breast cancers receptor coactivators TRIM33 and TRIM24. Interestingly TRIM28 (Supplementary Fig. S6B). EN1 expression significantly associated was recently identified as a critical regulator of TRIM24, an with overall survival in a Cox simple regression model. A multiple oncogene in prostate cancer (26) and TRIM24–TRIM28–TRIM33 regression model adjusted for the Nottingham Prognosis Index complex has previously been identified as a suppressor of murine and age also showed significant association between overall hepatocellular carcinoma growth (27). Because of prior data survival and EN1 expression. implying a functional role for the TLE3–EN1 interaction during The short survival of patients with TNBC with high EN1 development (23), we further explored the relevance of this expression suggested that these patients might be more likely to association in breast cancer cells. develop brain metastases commonly associated with shorter To confirm that EN1 and TLE3 bind to the same genomic survival in patients with breast cancer. Indeed, patients with TNBC regions and to test whether downregulating EN1 changes TLE3 who developed brain metastases had primary tumors with sig- chromatin binding patterns, we performed TLE3 ChIP-seq in nificantly higher EN1 levels than those who did not (Fig. 4D). The SUM149 and SUM159 cells /þ induction of shEN1. We significant association with brain metastases was still observed detected a significant overlap between TLE3 and EN1 peaks when compared with patients with metastases in other and a subset of the TLE3 peaks showed decreased (11,428) or organs (28). We also analyzed gene expression data of matched increased (7,150) signal in shEN1-expressing cells (Fig. 3F; primary tumors and brain metastases and found EN1 transcrip- Supplementary Fig. S5I; Supplementary Table S5). To investi- tional targets were significantly enriched in genes differentially gate the functional relevance of TLE3–EN1 interaction, we expressed between primary breast tumors and brain metastasis integrated TLE3 ChIP-seq and differential gene expression after (Fig. 4E). These results suggest that high expression of EN1 in shEN1 induction and performed Metacore analyses. We found primary TNBCs may increase the risk of brain metastases poten- that the most significant network process enrichment in both tially due to its regulation of WNT signaling and neurogenesis- SUM149 and SUM159 cells was in progesterone and GnRH related pathways including the expression of several neuroligins signaling, angiogenesis and ECM remodeling–related pathways in these breast tumors. Neural activity–induced NLGN3 was by genes associated with TLE3 peaks present only in shEN1 cells shown to promote the growth of high-grade brain tumors such and upregulated after shEN1 (Fig. 3G). These data suggest that as glioblastoma and DIPG (29), thus, their upregulation in EN1 may suppress the expression of these genes by preventing primary TNBCs may select for tumors with preferential growth TLE3 binding. in the brain. To investigate whether the EN1-mediated changes in the Interestingly, in our prior breast cancer somatic cell fusion expression of genes involved in WNT signaling is due to direct studies the only SNP that was significantly associated with effects on b-catenin transcriptional activity, we also performed the inheritance of SUM159 mesenchymal cell features was within b-catenin ChIP-seq in cells with or without EN1 expression and the NLGN4X gene (11), implying that NLGN4X plays an essential integrated b-catenin chromatin binding patterns with gene expres- role in these cells. In both SUM149 and SUM159 cell lines the sion changes. We observed a significant enrichment in WNT expression of NLGN4X, and other neuroligins, decreased follow- signaling pathway among genes that are direct b-catenin targets ing EN1 knockdown (Supplementary Fig. S6C). To test whether are downregulated after shEN1, implying that EN1 loss may affect NLGN4X expression in SUM159 breast cancer cells may reflect a b-catenin transcriptional activity (Fig. 3H). However, EN1 expres- dependency for this neural growth factor, we downregulated its sion did not significantly impact b-catenin chromatin binding, expression using TET-inducible shRNAs (Supplementary Fig. thus, EN1 may regulate the WNT signaling pathway via other S6D) and analyzed changes in cell viability and proliferation. indirect mechanisms. We detected a significant decrease in cell number 5 days following induction of two independent shNLGN4X confirming that High EN1 is associated with poor prognosis and brain NLGN4X positively affects SUM159 cell growth (Fig. 4F). To metastasis in TNBC investigate potential mechanisms by which loss of NLGN4X leads To investigate the clinical relevance of EN1 in breast cancer, we to decreased cell growth, we analyzed gene expression changes analyzed associations between EN1 expression and clinical out- after shNLGN4X induction. We found that downregulated genes come using the METABRIC and TCGA datasets. EN1 is highly showed significant enrichment in muscle contraction (e.g., expressed in TNBCs compared with non-TNBC and also in basal CAPN3, CALR3, and VIPR1), whereas upregulated genes were breast cancers compared with other subtypes (Fig. 1A and C). enriched in cell adhesion (e.g., NRXN1, TNC) and neurogenesis

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n = 30 A C 1.00

6,000 0.75

0.50

4,000 n = 135 0.25

Overall survival probability non−C4 C4 P = 0.0018 0.00 2,000 02468101214 Number at risk Time (years)

EN1 mRNA expression n = 52 non−C4 251 207 164 127 102 82 59 24 C4 27 19 12 9 8 6 4 3 n = 114 02468101214 0 Time (years) D P = 0.006 1234 6 B Expression clusters SPERMATOGENESIS KRAS_SIGNALING_DN High in cluster 4 WNT_BETA_CATENIN_SIGNALING E2F_TARGETS 4 MITOTIC_SPINDLE G2M_CHECKPOINT MYC_TARGETS_V2 COMPLEMENT EPITHELIAL_MESENCHYMAL_TRANSITION INTERFERON_GAMMA_RESPONSE 2 ALLOGRAFT_REJECTION KRAS_SIGNALING_UP COAGULATION ADIPOGENESIS TNFA_SIGNALING_VIA_NFKB INFLAMMATORY_RESPONSE

OXIDATIVE_PHOSPHORYLATION EN1 mRNA expression z−score 0 FATTY_ACID_METABOLISM MTORC1_SIGNALING APOPTOSIS INTERFERON_ALPHA_RESPONSE ANDROGEN_RESPONSE XENOBIOTIC_METABOLISM No brain metastasis Brain metastasis REACTIVE_OXIGEN_SPECIES_PATHWAY n BILE_ACID_METABOLISM ( = 226) (17) IL2_STAT5_SIGNALING F ANGIOGENESIS × 6 P53_PATHWAY 8 10 IL6_JAK_STAT3_SIGNALING PROTEIN_SECRETION UV_RESPONSE_DN P < 0.001 P < 0.001 HYPOXIA × 6 PEROXISOME 6 10 PANCREAS_BETA_CELLS PI3K_AKT_MTOR_SIGNALING ESTROGEN_RESPONSE_LATE HEME_METABOLISM × 6 APICAL_SURFACE 4 10 ESTROGEN_RESPONSE_EARLY TGF_BETA_SIGNALING GLYCOLYSIS Cell number MYC_TARGETS_V1 2×106 CHOLESTEROL_HOMEOSTASIS Low in cluster 4 APICAL_JUNCTION DNA_REPAIR 012 Normalized enrichment score 0 E - + - + Dox 5 µg/mL shNLGN4X-1 shNLGN4X-2 0.175 0.150 G 0.125 0.100 0.075 Increased risk of brain metastasis Shorter survival 0.050 0.025 0.000 − Enrichment score 0.025 TNBC with high EN1 −0.050

Activation of WNT and Hh signaling high expression of neuroligins and Zero cross at 12,412 neural-related proteins

0 5,000 10,000 15,000 20,000 25,000

Ranked list metric (PreRanked) Rank in ordered dataset Enrichment profile Hits Ranking metric scores

Figure 4. EN1 expression in breast cancer and clinical outcome. A, Basal breast cancers in METABRIC dataset divided into four different clusters based on EN1 mRNA expression. The number of tumor samples in each cluster is indicated. B, GSEA of genes differentially expressed between tumors in cluster 4 versus clusters 1–3 combined. C, Kaplan–Meier survival plot showing overall survival of patients with basal breast cancer in the METABRIC cohort classiﬁed into cluster 4 (C4) and all other clusters (cluster 1–3) combined based on EN1 expression. P value indicated the statistical signiﬁcance of the observed difference. D, The expression of EN1 in primary TNBCs with and without brain metastasis in the METABRIC cohort. E, GSEA analysis depicting enrichment of matched primary versus brain metastatic TNBC samples in genes that go up after EN1 knockdown in SUM149 and SUM159 cells (P ¼ 0.01). F, Cellular viability after NLGN4X downregulation in SUM159 cells. G, Schematic summary of our EN1 data.

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axonal guidance (e.g., SEMA3B and SEMA7A) proteins (Supple- onic development, EN1 is expressed in the dermal precursors mentary Fig. S6E; Supplementary Table S6). These results support and later on its expression is detected in dermal progenitors. our hypothesis that neural survival–related pathways play an Because the mammary gland is derived from the dermis, it is important role in a subset of TNBCs with high EN1 expression. tempting to speculate that there could be rare EN1-expressing mammary progenitors and that a subset of TNBCs may orig- inate from these cells. Discussion We showed that EN1 was specifically and highly expressed in In a targeted cellular viability screen for TFs selected on the triple-negative and basal breast cancers. However, we also found basis of their high expression in TNBCs we identified EN1, a significant heterogeneity in EN1 expression and patients with the neural-specific homeo-domain TF (30) with functional and highest expression of EN1 had worse overall survival in both clinical relevance in TNBCs. During embryonic development, METABRIC and TCGA datasets. Furthermore, patients with TNBC EN1 plays essential roles in mid-hindbrain pattern formation, with high expression of EN1 were more likely to develop brain axonal guidance, and neuron specification (5). EN1 is highly metastases potentially due to the expression and dependency of expressed in dopaminergic neurons both during development these tumors for neural survival factors such as NLGN4X and and in adulthood, and it is essential for their differentiation, other neuroligins. Besides neural cells, neurexins and neuroligins maintenance, and survival (16). High expression of EN2 was are also expressed in the vasculature and they promote the reported in prostate, breast, and ovarian carcinomas (31), and maturation and formation of blood vessels (36). Thus, the upre- EN2 has an oncogenic function in breast cancer (32). In gulation of neuroligins by EN1 in breast tumors could promote agreement with our findings, a recent study also reported that the growth of the primary tumor, enhance their ability to dis- the downregulation of EN1 reduces cellular viability in the seminate, and also promote the growth of metastatic lesions, SUM149 TNBC cell line (33). especially in the brain. We demonstrated an oncogenic role for EN1 in TNBCs based In summary, we identified EN1 as a TNBC-specific TF, the on the observation that its downregulation leads to G1 arrest expression of which is associated with neural features, angiogen- and apoptosis, and reduced tumor growth. These findings esis, and brain metastasis of breast cancer leading to poor clinical correlate with the antiapoptotic function of EN1 in dopami- outcome (Fig. 4G). Thus, targeting EN1 and neuroligins might be nergic neurons, where EN1 modulates mitochondrial signals explored as a potential therapeutic strategy for the prevention and and upregulates cell survival pathways (34). Functional enrich- treatment of brain metastases of TNBC. ment analysis of genes differentially expressed following EN1 fi downregulation for process networks and pathways identi ed Disclosure of Potential Conflicts of Interest WNT and Hh signaling as top enriched networks. In the brain, A.H. Beck has ownership interest (including stock, patents, etc.) in PathAI. EN1 is a downstream target of WNT, and EN1 and WNT C. Caldas reports receiving a commercial research grant from AstraZeneca, pathway genes cooperate in mid-hindbrain development (15). Genentech, Roche, and Servier and is a consultant/advisory board member for EN1 was also shown to negatively regulate b-catenin transcrip- AstraZeneca and Illumina. J.S. Carroll is director of biology at AstraZeneca and is tional activity in a cell culture model (23). The identification of a consultant/advisory board member for Azeria Therapeutics. K. Polyak is a WNT as top enriched process network positively regulated by consultant/advisory board member for Mitra Biotech and Acrivon Therapeutics. No potential conflicts of interest were disclosed. EN1 in TNBC suggests similar interactions between EN1 and WNT signaling in TNBCs. Indeed, our b-catenin ChIP-seq analysis showed that a subset of genes differentially expressed Authors' Contributions after EN1 downregulation are direct b-catenin targets. Conception and design: G. Peluffo, A. Subedee, K. Polyak We defined the genomic targets of EN1 by ChIP-seq for endog- Development of methodology: G. Peluffo, A. Subedee, Y. Su enous EN1 in SUM159 and SUM149 TNBC and for exogenously Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): G. Peluffo, A. Subedee, N. Kingston, B. Jovanovic, expressed EN1 in MCF7 luminal breast cancer cells and deter- L.E. Stevens, K. Murphy, Y. Su, C. Caldas, J.S. Carroll mined that EN1 can both positively and negatively affect gene Analysis and interpretation of data (e.g., statistical analysis, biostatistics, transcription depending on the cell line and its association with computational analysis): G. Peluffo, A. Subedee, N.W. Harper, B. Jovanovic, other transcriptional regulators. Direct EN1 targets that show F. Flores, L.E. Stevens, F. Beca, A. Trinh, C.S.R. Chilamakuri, O.M. Rueda, expression changes after EN1 knockdown also showed highest A.H. Beck, C. Caldas, J.S. Carroll enrichment for WNT and Hh signaling, and neural-related func- Writing, review, and/or revision of the manuscript: G. Peluffo, A. Subedee, B. Jovanovic, F. Beca, A. Trinh, C.S.R. Chilamakuri, C. Caldas, J.S. Carroll, tions. Among others, neuroligins and their receptors are direct K. Polyak targets and regulated by EN1 in breast cancer cells. On the basis of Administrative, technical, or material support (i.e., reporting or organizing qPLEX-RIME we identified TLE3, TRIM24, TRIM28, and TRIM33 data, constructing databases): G. Peluffo, A. Subedee, C. Caldas as EN1-interacting proteins in breast cancer cells. ChIP-seq for Study supervision: A. Subedee, C. Caldas, K. Polyak TLE3 revealed that the TLE3–EN1 complex may have a negative Other (mass spectrometry analysis): E.K. Papachristou, C.S. D'Santos fi effect on the expression of genes involved in angiogenesis and Other (was involved in co-mentoring the co- rst author of this study (A. Subedee), advising on experimental design and analysis, and provided ECM remodeling, because TLE3 peaks present in shEN1-expres- assistance with some of the earlier experiments for this study.): A. Marusyk sing cells were preferentially associated with genes showing upregulation after EN1 knockdown. Besides brain and neural development, EN1 is essential Acknowledgments for the specification of dorsal dermal fate via transmitting We thank Ramesh Shivdasani and members of our laboratory for their critical reading of the article and for useful discussions. This work WNT signaling (7) and it is implicated as a regulator of was supported by the NCI R35CA197623 (to K. Polyak), CDRMP W81XWH- dermal-derived fibroblasts involved in wound healing and 09-1-0131 (to K. Polyak), W81XWH-14-1-0212 (to K. Polyak), W81XWH- cancer-associated stroma formation (35). During early embry- 09-1-0561 (to A. Marusyk), W81XWH-18-1-0027 (to B. Jovanovic), the

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Susan G. Komen Foundation (to Y. Su and F. Beca), and CRUK core funding advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate and an ERC Consolidator award (to J.S. Carroll). this fact.

The costs of publication of this article were defrayed in part by the Received October 15, 2018; revised March 28, 2019; accepted June 14, 2019; payment of page charges. This article must therefore be hereby marked published ﬁrst June 25, 2019.

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www.aacrjournals.org Cancer Res; 79(16) August 15, 2019 4183

EN1 Is a Transcriptional Dependency in Triple-Negative Breast Cancer Associated with Brain Metastasis

Guillermo Peluffo, Ashim Subedee, Nicholas W. Harper, et al.

Cancer Res 2019;79:4173-4183. Published OnlineFirst June 25, 2019.

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