Abstract
Several master transcription factors (TF) can activate the epithelial-to-mesenchymal transition (EMT). However, their individual and combinatorial contributions to EMT in breast cancer are not defined. We show that overexpression of EMT-TFs individually in epithelial cells upregulated endogenous SNAI2, ZEB1/2, TCF4, and TWIST1/2 as a result of positive feedback mediated in part by suppression of their negative regulator miRNAs miR200s/203/205. We identified TCF4 as a potential new target of miR200s. Expression of ZEB1/2 strongly correlated with the mesenchymal phenotype in breast cancer cells, with the CD24−/CD44+ stemness profile, and with lower expression of core epithelial genes in human breast tumors. Knockdown of EMT-TFs identified the key role of ZEB1 and its functional cooperation with other EMT-TFs in the maintenance of the mesenchymal state. Inducible ZEB1+2 knockdown in xenograft models inhibited pulmonary metastasis, emphasizing their critical role in dissemination from primary site and in extravasation. However, ZEB1+2 depletion one-week after intravenous injection did not inhibit lung colonization, suggesting that ZEB1/2 and EMT are not essential for macrometastatic outgrowth. These results provide strong evidence that EMT is orchestrated by coordinated expression of several EMT-TFs and establish ZEB1 as a key master regulator of EMT and metastasis in breast cancer.
The EMT program is orchestrated by coordinated expression of multiple EMT transcription factors, whereas ZEB1 integrates the EMT master regulatory network and plays the major role in promoting EMT and metastasis.
Introduction
The epithelial-to-mesenchymal transition (EMT) is an evolutionarily conserved transdifferentiation program that plays an important role in embryonic development and tissue specialization (1). In adult organisms, EMT has been implicated in wound healing, fibrosis, and cancer. Though formally dispensable for tumor initiation, EMT promotes stemness, metastasis and confers increased therapeutic resistance (2).
A handful of master EMT transcription factors (TF) have been identified on the basis of their ability to induce EMT when overexpressed individually in epithelial cells, including C2H2-type zinc finger family members SNAI1/2and ZEB1/2, and bHLH family members TWIST1/2 and TCF3/4 (3–5). Though being sufficient for EMT induction, some of them form positive feedback loops leading to activation of other EMT regulators in the same cell. For example, overexpression of SNAI1 (and SNAI2) in many systems activates SNAI2 (6, 7), ZEB1/2 (8, 9), TWIST1 (10, 11), and TCF4 (3, 10). ZEB1 and ZEB2 can activate each other (7, 12), whereas TWIST1-induced EMT is dependent on activation of SNAI2 (13). The functional significance of this apparent redundancy and hierarchy between the EMT-TFs has not been thoroughly investigated.
It has been well-established that epithelial–mesenchymal balance in cells is maintained in large part through double-negative feedback loops between EMT-TFs and epithelial-specific miRNAs, namely between ZEB1/2 and the miR200 family (miR200c,141;200b,200a,429 – collectively miR200s; refs. 12, 14, 15), miR203 (16, 17), and miR205 (18, 19); between SNAI2 and the miR200 family (20); between SNAI1/2 and miR203 (21, 22) and the miR34 family (2).
Association analyses showed that transcript levels of multiple EMT-TFs in primary breast tumors correlate with worse patient outcome, whereas expression of the miR200 family miRNAs predicts better outcome (23, 24). Similarly, protein expression of multiple EMT-TFs analyzed by IHC predicts poor prognosis in metastatic breast cancer (25).
Although the evidence for a pivotal role of EMT in invasion and metastasis obtained from cell culture and tumor xenograft experiments is compelling, it is rather fragmentary from in vivo studies (26, 27). Recent attempts have begun to address the role of EMT in metastasis in genetically engineered mouse tumor models and lineage-tracing experiments (28). Surprisingly, genetic ablation of the Snai1 or Twist1 genes in a pancreatic mouse tumor model did not affect metastasis (29). However, Zeb1 gene deletion in the same model impaired metastatic dissemination (30), indicating that different EMT-TFs might be required for metastasis in specific contexts. Furthermore, deletion of a single EMT-TF may not be sufficient to prevent EMT due to the redundancy and mutual activation of multiple EMT-TFs during EMT.
Given the significant role EMT plays in tumor metastasis and drug resistance, defining the EMT-TFs crosstalk network will provide critical mechanistic insight allowing the development of novel strategies for the prevention or treatment of metastasis.
Materials and Methods
Reagents and antibodies
Doxycycline hydrochloride (Dox; Fisher, BP2653). SNAI1/Snail (C15D3; Cell Signaling Technology, 3879), SNAI2/Slug (C19G7; Cell Signaling Technology, 9585), ZEB1 (Sigma, HPA027524), ZEB2/SIP1 (Bethyl Laboratories, A302–474A), TCF3/E2A (V-18; Santa Cruz Biotechnology, sc-349), TCF4/ITF-2 (C-1; Santa Cruz Biotechnology, sc-393255), TWIST1 (Twist2C1a; Santa Cruz Biotechnology, sc-81417), E-cadherin (BD Biosciences, 610181), Claudin1 (JAY.8; Invitrogen, 51–9000), Claudin3 (Z23.JM; Invitrogen, 34–1700), Claudin4 (3E2C1; Invitrogen, 32–9400), Pan-Cytokeratin (C11; Santa Cruz Biotechnology, sc-8018), Vimentin (V-9; Santa Cruz Biotechnology, sc-6260), N-Cadherin (cl.32; BD Biosciences, 610920), CD44/HCAM (F-4; Santa Cruz Biotechnology, sc-9960), PDGFRβ (28E1; Cell Signaling Technology, 3169) CD133 (C24B9; Cell Signaling Technology, 3663), CD49f/ITGA6 (Cell Signaling Technology, 3570), ALDH1/2 (H-8; Santa Cruz Biotechnology, sc-166362), MET (C-28; Santa Cruz Biotechnology, sc-161), GAPDH (Millipore, MAB374), Tubulin α (Sigma, T9026), NEDD9 (2G9; Santa Cruz Biotechnology, sc-33659), ESRP1/2 (23A7; Novus, NBP1–77971); secondary horseradish peroxidase–conjugated antibodies against mouse and rabbit (Jackson ImmunoResearch).
Cell lines and cell culture
Primary human mammary epithelial cells (HMEC) were purchased from Lonza and Invitrogen and grown in mammary epithelial growth medium with Bullet Kit (Lonza, CC-3150). HMLE cells were described previously (31) and were grown in DMEM/F12 50/50 (Thermo Fisher, MT10092CV) supplemented with 5% horse serum (HS; Life Technologies, 16050122), 20 ng/mL EGF (Sigma, E4127), 10 μg/mL Insulin (Sigma, I5500), and 0.5 μg/mL hydrocortisone (Sigma, H4001). MCF10A cells were cultured in the HMLE media plus 100 ng/mL cholera toxin (Sigma, C8052). MDA-MB-231-luc-D3H2LN (MDA231LN) cells were purchased from Caliper Life Science (RRID:CVCL_D257) and grown in Alpha modification of Eagle's medium (AMEM; Thermo Fisher, MT15012CV) supplemented with 10% heat-inactivated FBS (HI FBS; HyClone). Parental MDA-MB-231 cells and its three derivative super-metastatic sublines (LM2–4175, BoM-1833, BrM-831) were kindly provided by Dr. Joan Massague (HHMI). The other cell lines were purchased from and authenticated by the ATCC and were grown in DMEM (Thermo Fisher, MT10013CV) supplemented with 10% FBS (HyClone). All DMEM/AMEM media were also supplemented with 29.2 mg/mL l-glutamine, 100 U/mL penicillin, and 100 μg/mL streptomycin (Thermo Fisher, MT30009CI). All cells were maintained at 37°C in a 5% CO2 incubator. Established cell lines were tested for Mycoplasma using the MycoAlert Mycoplasma Detection Kit (Lonza, LT07–318), expanded, frozen and each experiment was started with a new vial from the frozen stock to minimize passaging.
Open reading frames (ORFs) for the eight EMT-TFs and genomic fragments for the four miRNA genes/clusters were PCR-amplified using PfuUltraII DNA polymerase and cloned into Dox-inducible pLUT lentiviral expression vector (Supplementary Fig. S9) using primers and templates described in Supplementary Table S1. All constructs were sequenced to verify absence of mutations.
TCF4 and ZEB1 translational reporters
Firefly luciferase reporter vector was prepared by cloning luc2 gene from pGL4.10 into pcDNA3.1-zeo using PCR with #5Luc2-Nhe fwd primer (5′-AGAGGCTAGC-CACCATGGAAGATGC-3′) and #3Luc2-H rev primer (5′-AGAGAAGCTT-ATTACACGGCGATCTTGCC-3′). TCF4 and ZEB1 3′-untranslated regions (UTR) were then cloned downstream of luc2 in resulting pcDNA3.1-Luc2-zeo. A 1.66-kb cDNA fragment (nt 3589–5260 of accession NM_001243226) representing the partial 3′UTR of human TCF4 sequence was generated by PCR using #5TCF4 3UTR1-B fwd primer (5′-GAGAGGATCC-TGTGTAGCCGAAGTAGTGT-3′) and #3TCF4 3UTR1-RI rev primer (5′-AGAGAATTC-CTCCACATTTTAGGAACTTATCAACAAATC-3′) on oligo-dT generated total cDNA from HMEC cells. TCF4 reporter with mutations in the miR200c-seed complementary regions was generated by QuickChange PCR mutagenesis using following primer pairs: #5TCF4 200cseed2mt (5′-GAGGAGGGGTAGTGAAATACTTCTCTGGCCAGTATG-3′) and #3TCF4 200cseed2mt (5′-CATACTGGCCAGAGAAGTATTTCACTACCCCTCCTC-3′); #5TCF4 200cseedX1mt (5′-GCCACACAATTCTTGGGCTGTACTAAGAAAAAAAAAAATCCCTGT-3′) and #3TCF4 200cseedX1mt (5′-ACAGGGATTTTTTTTTTTCTTAGTACAGCCCAAGAATTGTGTGGC-3′). A 1.73-kb cDNA fragment (nt 4062–5642 of accession NM_001128128) representing the partial 3′UTR of human ZEB1 sequence was generated by PCR using #5ZEB1 3UTR1-RI fwd primer (5′-AGAGAATTC-GCCTGAACCTCAGACCTAG-3′) and #3ZEB1 3UTR1-X rev primer (5′-AGACTCGAG-ATGCATTTTATTGTGAGATGGGAG-3′) on pCI-neo-RL-ZEB1 plasmid template (Addgene, 35535; ref. 18).
Luciferase reporter assays
MDA231 cells on a 12-well plate were reverse transfected with 50 ng of pcDNA3.1-Luc2 reporter vector, with or without TCF4/ZEB1 3′UTR, 20 ng of pRL-TK (Promega) and 25 nmol/L of mirVana miRNA Mimic hsa-miR-200c or Negative Control #1. Briefly, lipid–DNA complexes were allowed to form by incubation of TransIT-LT1 (Mirus Bio) and reporter DNA plasmids. In a separate tube, lipid–RNA complexes were allowed to form by incubation of Lipofectamine RNAiMAX transfection reagent (Invitrogen) and miRNA mimics. Lipid–DNA and lipid–RNA complexes were then added to plate wells. Following trypsinization, MDA231 cells were resuspended in Opti-MEM and 5×104 cells were added to each well bringing the total volume to 0.5 mL. Plates were incubated for 2 hours at 37°C in 5% CO2, and then 1 mL of complete growth medium was added to each well. 48 hours post-transfection Dual-Luciferase Reporter Assays System (Promega, E1910) was used to measure reporter activity. Signals were normalized to empty vector.
EMT-TFs and miRNAs overexpression and knockdown
Dox-inducible pLUT-zeo or -puro lentiviral vector (Supplementary Fig. S9) was used for overexpression of EMT-TFs ORFs and miRNA genes. Constitutive pGIPZ or Dox-inducible pTRIPZ lentiviral vectors (Dharmacon/Horizon) were used for expression of shRNAs, see Supplementary Table S2 for details. Briefly, lentiviral particles were packaged in HEK293T cells (RRID:CVCL_0063) following calcium phosphate cotransfection of transfer vector, psPAX2 (Addgene, 12260), and pCMV-VSV-G (Addgene, 8454). After 2 to 4 rounds of infection with lentiviral particles, cells were selected in zeocin (50 μg/mL) or puromycin (1 μg/mL) containing media for 10 days. Mass culture pools representing hundreds of drug-resistant clones were used in all experiments. Double expressing cell lines were established by superinfection with the second shRNA vector. Expression of ORFs or shRNAs was induced by addition of 0.5 μg/mL doxycycline to cell culture media for 7 to 10 days. pLUT expressing turbo red fluorescent protein and pGIPZ/TRIPZ expressing non-targeting shRNA were used as appropriate controls.
Cell proliferation assay
A total of 2×104 cells were plated in triplicates in 6-well plates, cultured for 2, 4, 6, and 8 days, trypsinized, and counted on Countess (Invitrogen).
RNA isolation and quantitative RT-qPCR
Total RNA was extracted using the mirVana miRNA Isolation Kit (Ambion, AM1560) following the manufacturer's instructions. Two micrograms of total RNA was reverse transcribed using Maxima RT (Thermo Fisher, EP0742) and dT20 primer. Primers were designed using Real-Time qPCR Assay Tool (IDT). From two to six primer sets were tested for each gene and the best one was chosen for analysis. A water negative control did not produce significant amplification product. Quantitative PCR (qPCR) primer sequences are listed in Supplementary Table S3. Mature miRNAs were reverse transcribed using the TaqMan MicroRNA Reverse Transcription Kit (ABI, 4366596) and analyzed using ABI's miRNA-specific assays described in Supplementary Table S4. qPCR was performed in an ABI-7500 Real-Time PCR Cycler using SYBR Green (Sigma, S4438) or TaqMan Universal (ABI, 4440038) master mixes and analyzed using ABI SDS2.06 software. Transcript levels in the breast cancer cell line panel (Supplementary Fig. S2A–S2E) were normalized to the geometrical mean of UBC, PCNA, RPL13A, and tubulin genes; in HMLE sublines expressing ectopic EMT-TFs and MDA231 super-metastatic sublines by the geometrical mean of UBC, PCNA, and B2M; in HMLE CD24+/CD44− and CD24−/CD44+ cells by the geometrical mean of UBC, PCNA, and RPL13A. MiRNA levels were normalized to U6 small nuclear RNA level. Fold changes were calculated using the comparative Ct method (ΔΔCt).
Western blotting
Cells were washed with PBS and lysed in nonreducing Laemmli buffer (50 mmol/L Tris-HCl, pH 6.8, 2% SDS, 10% glycerol). Lysates were boiled for 5 minutes to shear DNA. Total protein was quantified by bicinchoninic acid assay (Thermo Fisher), then lysates were supplemented with β-mercaptoethanol (final concentration 200 mmol/L) and boiled for 5 minutes. Equal amounts of total protein (typically 30 μg) were separated on 4%–12% NuPAGE Bis-Tris gels (Invitrogen) in MOPS SDS buffer and transferred to a polyvinylidene difluoride membrane (Pierce, 88518) using liquid transfer in Tris-Glycine buffer supplemented with 10% methanol. Membranes were blocked in 5% skim milk dissolved in PBS-T (PBS plus 0.05% Tween-20) at room temperature for 1 hour. All antibody incubations and washes were performed in PBS-T at room temperature. Protein bands were detected using standard chemiluminescence techniques. Blots were stripped in Restore PLUS Stripping Buffer (Thermo Fisher, 46430) and re-probed with multiple antibodies.
Immunofluorescence
Cells grown on glass coverslips in 12-well plate for 48 hours were fixed in 4% paraformaldehyde, rinsed once in PBS and twice in PBS-X (PBS plus 0.1% Triton-X100), then permeabilized with methanol for 10 minutes at −20°C, rinsed twice with PBS and blocked with 5% BSA in PBS for 1 hour, incubated with anti–E-Cadherin (BD Biosciences, 610181) and then anti-mouse AlexaFluor-647 (Thermo Fisher) antibodies. Coverslips were mounted on slides using ProLong Gold Antifade Mountant with DAPI (Thermo Fisher). Images were acquired on Nikon A1R confocal with N-SIM E microscope and ×60 Plan Apo objective.
Fluorescence-activated cell sorting and flow cytometry
Cells were prepared according to standard protocols and suspended in DPBS containing 2.5 mmol/L EDTA, 25 mmol/L HEPES pH=7.0 and 1% FBS on ice. For FACSorting on a BD FACSAria III, CD24-PE (BD Biosciences, 555428), CD44-FITC (BD Biosciences, 555478), and FITC Mouse IgG2b κ Isotype Control (BD Biosciences, 555742) antibodies were used. 7-AAD (BD Biosciences, 559925) was used to exclude dead cells. For flow cytometry analysis, cocktail of four antibodies (Miltenyi Biotec) CD44-FITC (130–115–867), CD24-APC (130–112–657), CD104/ITGB4-PE-Vio770 (130–101–441), EpCAM-VioBlue (130–113–266), and LIVE/DEAD Fixable Near-IR Dead Cell Stain (Invitrogen, L34975) were used. Data were collected and analyzed on BD LSR Fortessa using BD FACSDiva 8.0 Software (BD Biosciences).
Transwell invasion assay
A 24-well BD BioCoat Tumor Invasion System (BD Biosciences, 354483; membrane with 8 um diameter pores, covered with a layer of growth factor reduced Matrigel) was used according to the manufacturer's instructions. Briefly, a total of 15,000 cells resuspended in serum-free media were plated in the apical chambers and were allowed to invade toward the basal chambers containing media with 10% FBS for 10 hours. Following the incubation, non-invaded cells on the upper surface of the membrane were removed with a cotton swab. The inserts were labeled with 4 μg/mL calcein AM in Hanks' balanced salt solution for 1 hour. Fluorescently labeled cells were visualized using a Typhoon 9410 imager at 488/526 nm with 25-μm resolution, and signals were quantified using ImageJ software as mean gray values for each well. The experiments were performed at least in triplicates.
Animal studies and bioluminescence imaging
NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mice were obtained from the Jackson Laboratory. Luciferase-expressing MDA231LN cells were resuspended in PBS and 2×106 cells in 100 μL were injected into the fourth mammary fat pad or 2×105 cells in 250 μL were injected into the tail vein of 7–9-week-old NSG mice. Mice were maintained on a control diet or diet supplemented with doxycycline 200 mg/kg (Bio-Serv) to induce shRNA expression. Xenograft tumors were measured with calipers every week and tumor volume was calculated using the formula V = (π/6)(LxW2), where L is the length of the tumor and W its width. Primary tumors and lungs were collected at the endpoint of study, fixed in formalin, and analyzed for number of metastases by a pathologist. Portions of primary tumors were lysed for Western blot analysis. For bioluminescent imaging, about 150 mg/kg D-luciferin (Caliper Life Sciences) was injected into the peritoneum. Images were obtained using the IVIS Lumina-II Imaging System and Living Image-4.0 software as described previously (32).
TCGA data analysis
Breast TCGA (The Cancer Genome Atlas) data were downloaded from (http://cancergenome.nih.gov/). Statistical programming software R (version 3.0.1) was used to assemble and process the data as described previously (32). These data from 105 normal, 354 LumA, 203 LumB, 97 HER2, and 137 basal samples were used to generate boxplots for protein-coding genes in Supplementary Fig. S4. Boxplots for miRNA genes in Supplementary Figs. S4 and S5 were generated from 87 normal, 232 LumA, 114 LumB, 46 HER2, and 82 basal samples. The Pearson's correlations described in Fig. 3, Supplementary Fig. S6 and Supplementary File S2 were carried out using log-transformed values and were generated from 112 normal, 359 LumA, 170 LumB, 60 HER2, and 122 basal samples described in ref. (33). A cutoff Pearson's R value of ≥|0.25| and a P value of <0.05 was selected on the basis of the minimal sample size of n=60 in HER2 subtype.
Statistical analysis
Statistical analyses and graphs were generated with GraphPad Prism5 software using one-way ANOVA with Dunnett's post-test.
Data availability
All data supporting the findings in this study are available from the corresponding author upon reasonable request.
Results
Convergence of positive feedback from multiple EMT-TFs to upregulate ZEB1/2, TWIST1/2, SNAI2, and TCF4 in epithelial cells undergoing EMT
The EMT-TFs bind similar E-box DNA consensus sequences (Supplementary Fig. S1) and regulate overlapping sets of genes (9, 10), primarily through direct repression of epithelial targets bearing an E-box(es) in their promoters (4, 14). To gain further insight into their individual functions, we expressed the eight EMT-TFs in a Dox-inducible manner in immortalized human mammary epithelial HMLE cells. The kinetics of EMT induction was established in a time course experiment with SNAI1. Addition of doxycycline led to rapid induction of SNAI1 protein within hours, upregulation of mesenchymal markers CD44 and vimentin, and concomitant downregulation of epithelial protein claudin1 within 24 hours (Fig. 1A). However, significant suppression of E-cadherin was observed only after 5 days likely due to slow decay of stable E-cadherin protein (Fig. 1A). When expressed for 10 days, six of the eight EMT-TFs induced characteristic changes in cell morphology (Fig. 1B) and expression of specific marker proteins indicative of EMT, including dramatic suppression of E-cadherin, cytokeratins and claudins, and elevated expression of vimentin and CD44 (Fig. 1C). Unexpectedly, high TWIST1/2 overexpression led to suppression of cell growth and limited EMT induction (not shown), suggesting that high TWIST overexpression could be cytotoxic as demonstrated previously (34). Therefore, we excluded TWIST1/2-overexpressing cells from further analysis. Though each of the other six TFs induced EMT, there were distinct differences between the TF families in regard to specific targets. For example, N-cadherin and PDGFR β were induced by ZEB1/2 and TCF3/4 but not by SNAI1/2, NEDD9 was induced by SNAI1/2 only and c-MET was repressed by TCF3/4 only (Fig. 1C). Furthermore, overexpression of ZEB1/2 led to increase in cell number, whereas ectopic SNAI1/2 and TCF3/4 slowed cell growth down (Fig. 1D), indicating that the effects of EMT on cell proliferation are EMT-TF–specific.
Endogenous SNAI2 protein was upregulated by each of the other five EMT-TFs (Fig. 1C). ZEB1 and ZEB2 proteins were generally induced by SNAI1/2, ZEB1/2, and TCF3/4, whereas ZEB1 was most dramatically upregulated by TCF3/4. Interestingly, expression of endogenous TWIST1 protein correlated with the induction of ZEB1. We were unable to detect endogenous levels of TCF3/4 and TWIST2 proteins in HMLE cells and relied on RT-qPCR for their expression analysis. Levels of endogenous TCF4 mRNA were modestly upregulated by SNAI1/2 and ZEB1, whereas TCF3 mRNA levels were marginally repressed by ZEB1/2 (Fig. 1E). These results revealed distinct positive feedback loops orchestrating the expression of multiple EMT-TFs when only one is initially activated.
Suppression of the miR200 family, miR205 and miR203 miRNAs by multiple EMT-TFs correlates with secondary upregulation of endogenous EMT-TFs
The observed secondary upregulation of multiple EMT-TFs during forced EMT could be due to repression of one or more of their common negative regulator miRNAs. We compared the mRNA sequences of the eight EMT-TFs for the presence of established and predicted binding sites for miR200s/203/205 miRNAs and found that ZEB1/2, TCF4, and to a lesser extent SNAI2 bear the highest number of these sites (Fig. 2A and B). To determine whether miR200s miRNAs can also directly target TCF4, we subcloned its 3′UTR downstream of a luciferase gene and performed reporter assays in mesenchymal MDA231 cells expressing very low endogenous levels of miR200s. MiR200c mimic repressed expression of the TCF4 3′UTR luciferase reporter as efficiently as of the control ZEB1 3′UTR reporter (Fig. 2C). Mutation of the two predicted miR200c-binding sites in the TCF4 3′UTR (Fig. 2B) abolished the repression (Fig. 2C), indicating that TCF4 is a putative target of miR200s.
The miR200 family consists of five miRNAs arranged into two gene clusters encoding miR200c/141 and miR200b/200a/429, so we profiled the leading members of each cluster: miR200c and miR200b, which are typically expressed at higher levels. Overexpression of ZEB1 and TCF3/4 led to dramatic suppression of the miR200s and miR205 miRNAs, whereas SNAI1/2 repressed them only modestly (Fig. 2D). Conversely, miR203 was significantly downregulated by SNAI1/2 andTCF3/4, and less efficiently by ZEB1/2. These data indicate that upregulation of endogenous ZEB1/2, TCF4, and SNAI2 by ectopic EMT-TFs strongly correlated with suppression of their common negative regulators miR200s/205/203.
To confirm that the epithelial miRNAs can inhibit multiple EMT-TFs, we overexpressed miR203, miR205, miR200b/a/429 or miR200c/141 clusters in mesenchymal BT549 and HS578T cells that express multiple EMT-TFs. As expected, expression of the miR200s miRNAs led to dramatic downregulation of ZEB1/2 and significant downregulation of TCF4, SNAI2, and TWIST1 proteins, concomitant with reactivation of E-cadherin (Fig. 2E). These results indicate that the epithelial miRNAs coordinately suppress multiple EMT-TFs during MET (Fig. 2F).
Expression of ZEB1/2 correlates with the mesenchymal phenotype in breast cancer cell lines
To correlate the expression of each of the eight EMT-TFs with the mesenchymal phenotype, we first profiled a panel of 17 human tumor cell lines representing luminal/ER+ or basal/triple-negative breast cancer subtypes (35, 36), two independent isolates of primary HMECs and two immortalized mammary cell lines, HMLE and MCF10A. The vast majority of cell lines in our panel maintained the epithelial phenotype, that is, high expression of E-cadherin, cytokeratins, ESRP1/2, claudins, and CD24 (Fig. 3A; Supplementary Fig. S2E). MDA453 cells carry homozygous nonsense mutation W638* in CDH1 gene (COSMIC database) and do not express E-cadherin protein but maintain overall luminal gene expression profile (Fig. 3A; ref. 36). A subset of basal cell lines in our panel have undergone full EMT, that is, silenced the epithelial genes and gained high expression of mesenchymal markers vimentin, N-cadherin and CD44 (Fig. 3A). Given this clear distinction, we referred to these four cell lines HCC1395, MDA231 (and its derivative MDA231LN), BT549, and HS578T as mesenchymal (M). These cell lines have also been previously shown to be the most invasive (35). In addition, they exhibited the stemness phenotype associated with CD24low/CD44high markers but not with CD133, CD49f or ALDH1/2 (Fig. 3A; Supplementary Fig. S2E).
Compared with HMECs, expression of SNAI1 protein was higher in most cell lines, especially in basal subtype (Fig. 3A; Supplementary Fig. S2A), suggesting that SNAI1 is commonly expressed in breast cancer cells. In contrast, SNAI2 protein was undetectable in all luminal and many basal lines. Interestingly, ZEB1/2 were consistently detected at high levels in all mesenchymal cell lines, but not in other subtypes (Fig. 3A; Supplementary Fig. S2B). High TWIST1/2 levels correlated with high ZEB1/2 levels in mesenchymal cell lines (and ZEB1 in HCC1143), with the exception of MDA231 and MDA231LN, where TWIST1/2 were undetectable (Supplementary Fig. S2C). Compared with HMECs, TCF4 levels were low in all cells except three mesenchymal cell lines and basal HCC38, whereas the levels of TCF3 were either similar or modestly lower (Fig. 3A; Supplementary Fig. S2D).
These data show that high endogenous expression of an individual EMT-TF does not necessarily elicit full EMT, as is exemplified by SNAI1 (Fig. 3A). Highest level of SNAI1 was observed in basal MDA157 cells reaching approximately 600-fold over the HMECs level (Fig. 3A; Supplementary Fig. S2A). Though some epithelial markers were decreased in these cells (i.e., cytokeratins), others, such as E-cadherin, CD24 and ESRP1/2 were expressed at levels comparable with many basal and luminal cell lines (Fig. 3A), indicating that MDA157 cells have undergone only partial EMT.
In contrast, high ZEB1/2 expression correlated well with full EMT/mesenchymal phenotype (Fig. 3A). TCF4, SNAI2, and TWIST1/2 were also expressed in mesenchymal cells, but they were present at similar levels in some epithelial cell lines and HMECs (Fig. 3A; Supplementary Fig. S2A, S2C, and S2D), suggesting that individually they were not sufficient to induce full EMT. Interestingly, TCF4 and TWIST1/2 levels were very low in MDA231, indicating that they were not necessary for full EMT in these cells. Together, these results indicate that though many EMT-TFs could be upregulated in breast cancer cells, high expression of ZEB1/2 strongly correlated with full EMT/mesenchymal phenotype. In addition, TCF4, SNAI2, and TWIST1/2 were upregulated in the mesenchymal cell lines, suggesting that full EMT is orchestrated by cooperative action of multiple EMT-TFs. In agreement with the role of miR200s/205/203 as negative regulators of ZEB1/2, TCF4 and SNAI2, endogenous levels of these miRNAs were consistently low in mesenchymal cell lines (Supplementary Fig. S3).
Differential expression of EMT-TFs and miR200s/203/205 miRNAs in human breast cancer subtypes
To correlate our observations in cell lines with patient data, we analyzed expression of the eight EMT-TFs, miRNAs, and EMT marker genes in the breast TCGA RNA-Seq dataset representing approximately 100 normal breast tissue samples and approximately 900 primary breast tumors of luminal A, luminal B, HER2 and basal subtypes (33). Compared with normal breast tissue, ZEB1/2, TWIST1/2, TCF4, and SNAI2 were expressed at lower levels in all four intrinsic subtypes and SNAI1 in both luminal subtypes (Supplementary Fig. S4). In contrast, TCF3 levels were higher in all subtypes, whereas SNAI1 levels were elevated in basal tumors. The observed lower expression of the majority of EMT-TFs in tumors (Supplementary Fig. S4) is concordant with dramatic suppression of the major inducer of EMT, the TGF-β tumor-suppressor pathway (via downregulation of TGFBR2 and TGFBR3 receptors) in all subtypes (Supplementary Fig. S4), that is commonly observed in primary breast tumors (37, 38). Consistently, compared with normal breast tissue, the tumors expressed higher levels of the majority of epithelial markers and epithelial miRNAs, demonstrating apparent tumor epithelialization (Supplementary Figs. S4 and S5A; Supplementary File S1). Arguably, this could potentially be due to reorganization of diseased breast tissue via changes in composition of stromal components and should be investigated in the future. When analyzed only within tumors, ZEB1 and TCF4 levels were lower, whereas SNAI1 and TCF3 levels were higher in basal compared with other subtypes. In agreement with their antagonistic regulation, highest levels of epithelial-specific miR200s and miR203 in basal subtype correlated with lowest levels of ZEB1 and TCF4 (Supplementary Fig. S4). Levels of miR34 family miRNAs did not change significantly across subtypes (Supplementary Fig. S5B), indicating that increased SNAI1 level in basal tumors is not due to miR34 change.
ZEB1/2, TCF4 and SNAI2 expression is strongly correlated in breast tumors
Simultaneous expression of multiple EMT-TFs in the mesenchymal cells lines (Fig. 3A) prompted us to analyze correlation of expression among the EMT-TFs in the breast TCGA dataset (Supplementary File S2). SNAI2 expression has been previously shown to be restricted to mammary myoepithelial/basal cells (31, 39). TCF3 was the only EMT-TF that correlated positively with SNAI2 in normal breast tissue (R = 0.33), whereas the other six EMT-TFs correlated negatively with both SNAI2 and TCF3 (Fig. 3B, neon green arrow and boxes), suggesting that TCF3 expression is also myoepithelial-specific. The strongest correlations in normal tissue were observed between ZEB1/2 and TCF4 (R ∼ 0.95; Fig. 3B, red boxes), which together modestly correlated with TWIST1/2 (R = 0.53–0.65). TWIST1/2 most strongly correlated with each other (R = 0.81) and with ZEB1/2, TCF4, and SNAI1 (R = 0.48–0.65; Fig. 3B, blue boxes), whereas SNAI1 equally weakly correlated with TWIST1/2, ZEB1/2, and TCF4 (R = 0.4–0.51; Fig. 3B, dark green box).
Surprisingly, patterns of SNAI2 correlation with ZEB1/2 and TCF4 flipped from negative in normal tissue to strong positive in breast tumors (Fig. 3B, red boxes). Similarly, negative correlation of TCF3 with the six EMT-TFs observed in normal tissue mostly dissipated in tumors. The reversal in SNAI2 (and to some extent in TCF3) correlations with other EMT-TFs could be due to myoepithelial lineage depletion in tumors as discussed below. Strong correlation between ZEB1/2 and TCF4 observed in normal tissue maintained in all subtypes (R = 0.68–0.93, red boxes), whereas patterns of TWIST1/2 and SNAI1 correlations were preserved only in luminal A (Fig. 3B, blue and dark green boxes, respectively).
These data indicate that in breast tumors the expression of ZEB1/2, TCF4, and SNAI2 is highly correlated (R = 0.6–0.93). In addition, these four EMT-TFs moderately correlate with TWIST1/2 (R = 0.26–0.71), suggesting that the EMT program is tightly coordinated by several EMT-TFs.
Correlation of EMT-TFs with epithelial markers in normal breast tissue and primary breast tumors
To assess potential functional role of the EMT-TFs in regulation of EMT markers, their correlation of expression was computed for normal breast tissue and breast tumors (Supplementary File S2). Three published breast EMT signatures (9, 40, 41) were used to select EMT markers. We narrowed our analysis to epithelial genes, assuming that they are specific to tumor cells, whereas mesenchymal markers could be expressed in partially EMT'ed tumors as well as in mesenchymal stromal components (42, 43). In addition, most of the EMT-TFs are bona fide direct repressors of epithelial genes (4, 14), whereas their effect on upregulation of mesenchymal genes could be indirect. To avoid subtype-specific effects, we further focused on a 100-core epithelial markers expressed at similar levels across all four intrinsic subtypes (<2-fold difference, P < 0.01; see Materials and Methods).
As expected, majority of the epithelial markers correlated negatively with multiple EMT-TFs in normal breast tissue (Supplementary Fig. S6). Though, the number of negatively correlated epithelial genes was similar for each of ZEB1/2, TCF4, and TWIST1/2 (66–76 genes), stronger correlations were observed for ZEB1/2 and TCF4 (R ∼ −0.9 to −0.55) followed by TWIST1/2 (R ∼ −0.7 to −0.3) and SNAI1 (R ∼ −0.4 to −0.25; Fig. 3C; Supplementary Fig. S6). As discussed above, SNAI2 and TCF3 were specific for myoepithelial lineage and correlated positively with majority of the epithelial markers in normal breast tissue (Fig. 3C; Supplementary Fig. S6).
Luminal A tumors featured number of pairwise negative gene correlations similar to normal tissue (Fig. 3C). However, the relative strengths of these correlations were markedly different (Supplementary Fig. S6). Fewer epithelial gene EMT-TF correlations of weaker strengths were observed in the other subtypes (Fig. 3C). Remarkably, SNAI2 and TCF3 switched from generally strong positive correlation with epithelial markers in normal tissue to mostly negative correlation in tumors (Fig. 3C; Supplementary Fig. S6). This phenomenon is likely a result of depletion of myoepithelial lineage and its gene expression patterns in tumors, which are proposed to originate from luminal progenitors (44). In all tumor subtypes, ZEB1/2 and TCF4 negatively correlated with a larger number of epithelial genes compared with other EMT-TFs, and with stronger R values (Fig. 3C; Supplementary Fig. S6). Interestingly, higher expression of SNAI1 and TCF3 in basal subtype (Supplementary Fig. S4) did not result in an increase in number of their negatively correlated core epithelial genes compared with the other subtypes or compared with the other EMT-TFs (Fig. 3C; Supplementary Fig. S6). These data are in agreement with recent report, indicating that SNAI1 appears to exert little effect on EMT program in tumors in vivo (45).
Altogether, these results indicate that among the eight EMT-TFs, ZEB1/2 and TCF4 negatively correlated with more core epithelial genes and with stronger R values in normal breast and in tumors, suggesting that they may play more prominent role in their repression.
ZEB1 plays dominant role in maintenance of the mesenchymal/stem-like phenotype of human mammary epithelial cells
Low expression of many EMT-TFs in primary breast tumors (46) prompted us to investigate if any of them are enriched in mammary stem cells, which constitute a small cell population in tissue and are considered to be potential precursors of tumor-initiating cells (47). Heterogeneous cell populations of primary HMECs and derivative immortalized HMEC line HMLE contain a small proportion of cells (0.5%–3%) expressing CD24−/CD44+ (or CD24low/CD44hi) stemness profile (31, 48). When purified by flow cytometry, CD24−/CD44+ cells exhibit hallmarks of stem cells, that is, greatly increased capacity to form mammospheres in vitro and the ability to reconstitute the mammary gland in mice (31). We purified the CD24−/CD44+ subpopulation from HMLE cells (Supplementary Fig. S7) and confirmed that they adopt the mesenchymal state (Fig. 4A–C), consistent with previous reports (31, 48). Among the eight EMT-TFs, expression levels of ZEB1 (∼500-fold), ZEB2 (∼90-fold), TWIST1 (∼60-fold), and TWIST2 (∼10-fold) were markedly higher in CD24−/CD44+ compared with CD24+/CD44− HMLE cells, whereas expression of SNAI1/2 and TCF3/4 was not significantly different (Fig. 4A and B). Concomitantly, miR200s/203/205 levels were drastically lower in CD24−/CD44+ cells (Fig. 4C). These results suggest that though the stemness phenotype could be induced by forced expression of many EMT-TFs, including SNAI1/2 and TCF3/4 (Fig. 1C; ref. 31), the subpopulation of normal mammary stem-like cells naturally overexpresses ZEB1/2 and TWIST1/2.
To determine which of these two families of EMT-TFs plays a major role in the maintenance of the mesenchymal phenotype, we knocked down highly expressed members TWIST1 or ZEB1, or both in CD24−/CD44+ HMLE cells. Depletion of TWIST1 resulted in a modest increase in E-cadherin expression, whereas knockdown of ZEB1 led to significant upregulation of E-cadherin and downregulation of CD44 and N-cadherin (Fig. 4D). Interestingly, depletion of TWIST1 in addition to ZEB1 did not result in further inhibition of EMT (Fig. 4D). These results suggest that ZEB1 plays a more dominant role in maintenance of the mesenchymal phenotype of normal mammary stem-like cells.
ZEB1 plays a major role in maintenance of the mesenchymal phenotype of breast cancer cells
Remarkably, the expression pattern of EMT-TFs in normal mammary stem-like cells resembled the pattern observed in fully EMT'ed breast cancer cell lines (compare Figs. 4A and 3A). To establish a functional requirement of individual EMT-TFs for maintenance of the mesenchymal phenotype in tumor cells, we initially focused on the mesenchymal cell line MDA231LN (49). Parental MDA231 is the most commonly used cell line in mouse xenograft models of breast cancer metastasis due to its superior invasiveness (35). Its derivative subline MDA231LN, isolated from a mouse lymph node metastasis, acquired increased metastatic potential (49). Importantly, parental and MDA231LN cells express high levels of SNAI1/2 and ZEB1/2, but low levels of TWIST1/2 and TCF4 (Fig. 3A; Supplementary Fig. S2A–S2D), which makes them suitable for interrogation of the individual roles of SNAI1/2 and ZEB1/2 in EMT. Individual knockdowns of each of these four EMT-TFs by two independent shRNAs showed that although depletion of SNAI2 and ZEB2 resulted in a modest upregulation of E-cadherin, indicative of partial MET, suppression of ZEB1 led to dramatic re-expression of epithelial E-cadherin and cytokeratins, and significant downregulation of the mesenchymal marker CD44 (Fig. 5A). In agreement with previous report (50), knockdown of SNAI1 was insufficient to significantly upregulate E-cadherin. Interestingly, knockdown of each of the four EMT-TFs in MDA231LN cells did not significantly affect the expression of the others (Fig. 5A). This is likely because none of the epithelial-specific miRNAs (miR200s/203/205), which may target multiple EMT-TFs, was reactivated by either SNAI or ZEB knockdowns (not shown).
Next, we used mesenchymal BT549 cells, which express high levels of ZEB1/2, TWIST1/2 and TCF4 and low levels of SNAI1/2 (Fig. 3A; Supplementary Fig. S2A–S2D). Knockdown of TWIST1 by two different shRNAs showed no significant change in expression of EMT markers, whereas depletion of ZEB1 led to marked re-expression of epithelial E-cadherin and claudins and downregulation of the mesenchymal marker N-cadherin (Fig. 5B). Depletion of TWIST1 in addition to ZEB1 did not result in further MET.
Together, these results indicate that ZEB1 is one of the most critical regulators of the mesenchymal phenotype in breast cancer cells.
Cooperation of multiple EMT-TFs in control of cell proliferation, invasion, and metastasis of MDA231LN cells
Though ZEB1 played the dominant role, partial MET induced by knockdowns of ZEB2 and SNAI2 in MDA231LN cells indicated that multiple EMT-TFs contribute to the mesenchymal phenotype. To confirm this, we generated MDA231LN cells with double knockdowns of SNAI1+2, ZEB1+2, and ZEB1+SNAI2. Depletion of ZEB2 or SNAI2 in addition to ZEB1 resulted in more profound suppression of EMT and reactivation of E-cadherin to the levels observed in epithelial HMLE cells, whereas double SNAI1+2 knockdown had only a partial effect (Fig. 5C). The knockdowns also led to upregulation of epithelial cytokeratins and downregulation of mesenchymal CD44 and vimentin. Notably, miR200s miRNAs were not reactivated in response to double knockdowns (not shown), indicating that certain EMT-TFs targets may remain stably silenced even in the absence of EMT-TFs expression.
Interestingly, knockdowns of SNAI1+2 and especially ZEB1+2 and ZEB1+SNAI2 led to dramatic change in cell morphology (Fig. 5D) and decreased cell proliferation in vitro (Fig. 5E). Furthermore, progressive suppression of EMT among the double knockdown lines correlated with decreased invasion in vitro (Fig. 5F) and a drastic suppression of spontaneous lung metastasis in a mouse orthotopic xenograft model (Fig. 5G).
Together, these results indicate that multiple EMT-TFs expressed in MDA231LN cells contribute to the mesenchymal phenotype characterized as mesenchymal gene expression pattern, increased invasion and metastasis. At the same time, the relative contribution between them varies significantly, with ZEB1 being the most potent.
ZEB1 expression correlates with increased metastatic potential of MDA231 sublines
Dr. Joan Massague's group has selected several independent sublines of MDA231 cells with much higher propensity to metastasize and colonize specific distant organs, including lung (MDA231-LM2), bone (MDA231-BoM), and brain (MDA231-BrM; ref. 51). To determine whether their super-metastatic potential correlates with EMT, we analyzed expression of EMT-TFs and EMT markers in these sublines. Parental MDA231 cells obtained from Dr. Joan Massague's laboratory and from the ATCC were used as controls. Surprisingly, we found that ZEB1 protein but not mRNA levels were significantly upregulated in all three super-metastatic sublines (Fig. 6A and B), indicating that the increase in ZEB1 expression have occurred at the post-transcriptional level. Consistently, miR200s miRNAs were downregulated in these cells (Fig. 6C). In addition, ZEB2 and TCF4 mRNAs were upregulated in BrM cells and in BoM and BrM cells, respectively (Fig. 6B). Surprisingly, SNAI1 and to a lesser extent SNAI2 proteins were downregulated in super-metastatic sublines compared with controls (Fig. 6A). Increased ZEB1 expression correlated with progressive EMT of super-metastatic sublines, that is, elevated levels of vimentin and decreased levels of cytokeratins, claudin4 and epithelial-specific splice isoforms of CD44 (Fig. 6A), and increased cell proliferation (Fig. 6D).
These results indicate that increased metastatic potential of the MDA231-LM2, MDA231-BoM, and MDA231-BrM sublines is associated with progressive EMT and elevated levels of ZEB1/2 and TCF4.
Suppression of ZEB1+2 and EMT at early stages of tumor growth blocks metastasis in an orthotopic xenograft mouse model
To determine the effect of ZEB1+2 knockdown and EMT suppression on different stages of metastasis, we generated MDA231LN cells with Dox-inducible shRNAs targeting ZEB1+2. Addition of doxycycline led to dramatic downregulation of ZEB1 protein within 5 days and concomitant suppression of EMT, loss of spindle-like cell morphology, activation and membranous localization of E-cadherin, and reversal in expression of the CD24−/CD44+ stemness markers (Fig. 7A and B; Supplementary Fig. S8). Interestingly, wash-out of doxycycline and culturing cells for 16 days resulted in re-expression of ZEB1 and reactivation of the EMT program, indicating that MET was reversible (Fig. 7A, lanes 11–12).
To test the requirement of EMT for initial stages of metastasis, we used a mouse orthotopic xenograft model and conditionally inhibited ZEB1+2 expression in MDA231LN cells in a time-resolved manner. The timeline of the experiment is schematically outlined in Fig. 7C. The control mouse group never received doxycycline and cells remained in the mesenchymal state for the whole duration of the experiment (M group). For other two groups, doxycycline (resulting in ZEB1+2 KD) was administered at different time points relative to the injection time (day 0): One week before injection to inhibit EMT before the start of tumor growth (E group) and one week after injection (M>E group) to inhibit EMT after the primary tumor has formed. Five weeks after injection the tumors and lungs were removed and analyzed. Western blot analysis on tumor lysates from the E and M>E groups confirmed equally efficient ZEB1 knockdown and suppression of EMT in vivo, for example, reactivation of epithelial markers and downregulation of CD44 (Fig. 7D). Suppression of EMT in vivo did not significantly affect primary tumor growth (Fig. 7F) or histology (Fig. 7E, top). However, EMT inhibition led to a >100-fold decrease in the number of lung metastases (Fig. 7G and E bottom). Unexpectedly, lung metastasis was also greatly suppressed in the M>E (mesenchymal-turned-epithelial) group (Fig. 7G), indicating that EMT suppression during the initial stage of tumor growth is effective in preventing metastasis. These results showed that inhibition of ZEB1+2 and EMT at early stages of tumor growth is sufficient to effectively block metastasis.
Expression of ZEB1+2 and EMT are critical for the extravasation stage of metastasis and is dispensable for outgrowth of seeded macrometastases
To test a role of ZEB1+2 in outgrowth of already disseminated cells, we injected MDA231LN cells directly into the blood stream and allowed them sufficient time to establish micrometastases (52), that is, one week before inhibiting EMT (Fig. 7C). To monitor the injected tumor cell survival and growth, bioluminescence in the lungs was measured on the day of injection (day 0) and then weekly for 3 weeks (Fig. 7H and I). As expected, the control M group produced high metastatic outgrowth (Fig. 7H–J). The epithelial E group yielded significantly reduced metastasis, suggesting that the extravasation or/and later stages of metastasis are inhibited by suppression of EMT. Surprisingly, the M>E group, in which mesenchymal cells were switched to the epithelial state one week after injection, produced a similar number of metastases to the control M group (Fig. 7I and J), indicating that one week time was sufficient for mesenchymal cells to extravasate and that EMT is not essential for outgrowth of seeded macrometastases. These results indicate that ZEB1+2 expression and EMT are necessary for the transition of circulating cancer cells into the lungs but are not required for the macrometastatic outgrowth.
Discussion
Here, we characterized EMT-TF network expression across cancer models and human breast tumors, and used conditional knockdown to demonstrate a critical role of ZEB1/2 as regulators of metastasis. We established ZEB1/2, SNAI2, TCF4, and TWIST1/2 as commonly and cooperatively upregulated during forced EMT of normal mammary epithelial cells. A likely mechanism for the observed secondary upregulation is repression of the common negative regulators of EMT-TFs, the epithelial-specific miRNAs miR200s/203/205 that can target multiple EMT-TFs (9, 20, 21, 53), summarized in Fig. 2F. We found that in addition to ZEB1/2 and SNAI2, miR200c could target TCF4 (Fig. 2).
We correlated expression of EMT-TFs and EMT markers in multiple breast cancer cells lines. All analyzed mesenchymal cell lines expressed high levels of ZEB1/2, indicating that full EMT is consistently associated with activation of ZEB1/2. In addition to ZEB1/2, mesenchymal cell lines expressed high levels of other EMT-TFs, including in various combinations SNAI2, TCF4, TWIST1/2 and SNAI1, suggesting that a combined action of multiple EMT-TFs may contribute to full EMT.
Furthermore, we identified ZEB1/2, TCF4, and SNAI2 as a group of EMT-TFs with tightly coordinated expression in major breast cancer subtypes (Fig. 3B and C). ZEB1/2 and TCF4 negatively correlated with a larger number of core epithelial genes and with stronger R values compared with the other EMT-TFs, suggesting that they may play a more prominent role in EMT.
The most striking difference of the patient data with the cell line panel was the absence of true mesenchymal/full EMT subtype in primary breast tumors, suggesting that the mesenchymal cells are likely present in small subpopulations within a tumor or appear at later stages of tumor progression. Generally, low expression of EMT-TFs in the bulk of epithelial tumors (46) suggests that EMT is likely to occur in distinct cell subpopulations that play key roles in tumor progression and metastatic dissemination (27). Because cancer stem cells (CSC) have been proposed as the driving force of tumorigenesis and the source of metastases (47), it is, therefore, logical to consider CSC as preferentially malleable to EMT. In fact, stemness and EMT features often significantly overlap, but the degree to which EMT and stemness are coupled or independent is a topic of current debate (54). Remarkably, activation of the EMT program in non-transformed epithelial cells confers properties of stem cells that are associated with the CD24−/CD44+ phenotype (31, 42). We found that ZEB1/2 and TWIST1/2 are significantly upregulated in CD24−/CD44+ mammary stem-like cells and showed that ZEB1 plays a major role in maintenance of the mesenchymal status of CD24−/CD44+ stem-like cells. Consistent with this, ZEB1/2 were significantly enriched in CD24−/CD44+ CSC populations isolated from primary human breast cancers (55).
Remarkably, the expression pattern of EMT-TFs in CD24−/CD44+ normal mammary stem-like cells resembles those of the mesenchymal breast cancer cells, suggesting that the latter may represent tumor cells permanently locked in the ultimate stemness phenotype due to compounding genetic alterations. We showed that ZEB1 knockdown led to marked suppression of EMT in mesenchymal breast cancer cells. At the same time, depletion of SNAI1/2, ZEB2 or TWIST1 had only minor effect, indicating that ZEB1 is the major TF required for full EMT. These results are corroborated by earlier genetic studies in mouse embryonic fibroblasts (MEF), which similarly express Zeb1/2 and Snai1/2. Thus, deletion of Zeb1 in MEFs led to reactivation of E-cadherin and downregulation of vimentin (56), whereas knockout of Snai1 did not (57). We showed that though knockdown of ZEB1 alone was sufficient to induce MET, simultaneous depletion of ZEB1 with ZEB2 or SNAI2 led to more profound suppression of EMT. Interestingly, knocking out Zeb1 in a mouse pancreatic tumor model resulted in a strong but still incomplete suppression of metastatic ability (30), suggesting that other EMT-TFs may partially substitute for Zeb1 loss.
Importantly, there was a distinct difference in the control of the EMT network between normal mammary epithelial cells and mesenchymal breast cancer cells. Although normal epithelial cells, induced to undergo EMT, maintained positive feedback for coordinated upregulation of multiple endogenous EMT-TFs, mediated through downregulation of their inhibitory miRNAs, mesenchymal cells, induced to undergo MET, demonstrated impaired or lost co-regulation of EMT-TFs. Similarly, deletion of Zeb1 or Snai1 in MEFs did not significantly affect expression of the other EMT-TFs (56, 57). We did not detect miR200s reactivation in response to ZEB1 knockdown in MDA231LN cells despite overt MET and reactivation of E-cadherin, suggesting that cancer cells could maintain silenced chromatin at specific targets even in the absence of an active repressor. This may have important implications for future therapeutic treatment strategies aimed at reverting EMT. Thus, addition of epigenetic drugs targeting DNA methylation or histone modifications could facilitate reactivation of the epithelial program (53, 58).
MDA231 cells have been widely used as a model human cell line to study invasion and breast cancer metastasis due to its ability to produce spontaneous metastases in immunocompromised mice. Parental MDA231 cells are considered moderately metastatic, and several successful attempts have been made to select super-metastatic variants of MDA231 cells with preferential organ-specific seeding to lung, bone or brain (51). We showed that all three MDA231 super-metastatic sublines express higher levels of ZEB1 and lower levels of miR200s, indicating that their increased metastatic potential is associated with enhanced EMT.
Using Dox-inducible shRNAs, we showed that depletion of ZEB1+2 and suppression of EMT at initial stages of tumor growth blocks spontaneous lung metastasis, suggesting that administration of anti-EMT drugs at early tumor stages could potentially be effective in preventing metastasis. This is consistent with established role of ZEB1 in local invasion and transendothelial migration (59). Next, we showed that EMT is required for later stages of metastasis, after cancer cells enter the circulation. Depletion of ZEB1+2 and suppression of EMT before tail vein injection significantly reduced lung metastasis of MDA231LN. Previously, we have shown that MDA231LN cells injected into the tail vein form micrometastases and resume proliferation in lungs by around 3 days after injection (52). Remarkably, silencing of ZEB1+2 and inhibition of EMT 7 days after intravenous injection of MDA231LN cells did not reduce metastatic outgrowth in lungs, indicating that EMT may facilitate earlier extravasation and establishment of micrometastases but is dispensable for progression toward macrometastases (27, 60).
Authors’ Disclosures
E.N. Pugacheva reports grants from NCI during the conduct of the study. A.V. Ivanov reports grants from Susan G. Komen Foundation, American Cancer Society, and National Institutes of Health during the conduct of the study. No disclosures were reported by the other authors.
Authors' Contributions
J.B. Addison: Formal analysis, investigation. M.A. Voronkova: Data curation, formal analysis, investigation. J.H. Fugett: Formal analysis, investigation. C.C. Lin: Formal analysis, investigation. N.C. Linville: Resources. B. Trinh: Resources. R.H. Livengood: Investigation. M.B. Smolkin: Investigation. M.D. Schaller: Writing–review and editing. J.M. Ruppert: Writing–review and editing. E.N. Pugacheva: Funding acquisition, writing–review and editing. C.J. Creighton: Data curation, software, formal analysis, funding acquisition, investigation. A.V. Ivanov: Conceptualization, data curation, formal analysis, supervision, funding acquisition, validation, investigation, visualization, methodology, writing–original draft, project administration, writing–review and editing.
Acknowledgments
We thank Sarah McLaughlin, Dr. Katherine Brundage, Fengju Chen, Yuriy Loskutov, Kristina Marinak-Whately, and Sila Yanardag for technical assistance, Drs. Steven Frisch and Peter Stoilov for critically reading the article, Drs. Joan Massague, Gregory Goodall, and Russ Carstens for providing reagents. This work was supported by grants from Susan G. Komen Foundation (KG110350 to A.V. Ivanov; KG100539 to E.N. Pugacheva) American Cancer Society (ACS-IRG-09-061-01) and NIH/NCRR (P20RR016440 to A.V. Ivanov), NIH/NCI (R01CA148671 to E.N. Pugacheva), and from NIH/NCI (P30CA125123 to C.J. Creighton) and in part from NIH/NIGMS (WV-INBRE P20GM103434). The WVU flow cytometry and animal models and imaging facilities were supported by NIH/NIGMS grants CoBRE P30GM103488, WV-INBRE P20GM103434, and WV-CTSI U54GM104942.
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