Single-Cell Analysis Reveals a Preexisting Drug-Resistant Subpopulation in the Luminal Breast Cancer Subtype

Author Manuscript Published OnlineFirst on July 9, 2019; DOI: 10.1158/0008-5472.CAN-19-0122 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Single-cell Analysis Reveals a Preexisting Drug-Resistant Subpopulation in the Luminal Breast Cancer Subtype

Marta Prieto-Vila1,2, Wataru Usuba1,3, Ryou-u Takahashi1,4, Iwao Shimomura1, Hideo Sasaki3, Takahiro Ochiya1,2, Yusuke Yamamoto1. 1Division of Cellular Signaling, National Cancer Center Research Institute, Tokyo, Japan. 2Department of Molecular and Cellular Medicine, Institute of Medical Science, Tokyo Medical University, Tokyo, Japan. 3Department of Urology, St. Marianna University School of Medicine, Kanagawa, Japan. 4Department of Cellular and Molecular Biology, Hiroshima University, Hiroshima, Japan.

Address correspondence to: Yusuke Yamamoto, National Cancer Center, Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan. Phone: (+81)-3-3547-5201, E-mail: [email protected]

Running title: Drug-resistant subpopulation revealed by single-cell qPCR.

Keywords: breast cancer; drug resistance; single-cell; cancer stem cell (CSC); LEF1

Financial support: The present work was supported in part by a Grant-in-Aid for Scientific Research (C) JSPS KAKENHI Grant Number: 19K16761, Grant-in-Aid for Young Scientists (A) JSPS KAKENHI Grant Number: 17H04991 and the “Development of Diagnostic Technology for Detection of miRNA in Body Fluids” grant from the Japan Agency for Medical Research and Development (AMED).

Text words: 5562 Figures: 7 Supplementary figures and tables: 7 and 2

Downloaded from cancerres.aacrjournals.org on September 24, 2021. © 2019 American Association for Cancer Research. Author Manuscript Published OnlineFirst on July 9, 2019; DOI: 10.1158/0008-5472.CAN-19-0122 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

The authors declare no potential conflicts of interest.

Abbreviations General words BSA: Bovine Serum Albumin CSC: cancer stem cell DR: docetaxel-resistance DTX: docetaxel EMT: epithelial to mesenchymal transition ER: estrogen receptor HER2: human epidermal growth factor receptor-2 LOD: limit of detection mRNA: messenger RNA miRNA, miR: microRNA PBS: phosphate buffered saline PR: progesterone receptor qPCR: quantitative polymerase chain reaction t-SNE: t-Distributed Stochastic Neighbor Embedding

Gene names ABCG2: ATP-binding cassette sub-family G member 2 ACTA2: Alpha-smooth muscle actin ACTB: β-actin AR: Androgen receptor CAV: Caveolin CCNA2: Cyclin A2 CCNB1: Cyclin B1 CCNE1: Cyclin E1 CDH1: E-cadherin CD24: Cluster of differentiation 24 CD200: Cluster of differentiation 200 CHEK1: Checkpoint kinase 1

ESR1: Estrogen receptor 1 FOXA1: Forkhead box protein A1 GAPDH: Glyceraldehyde 3-phosphate dehydrogenase GATA3: GATA family of transcription factor 3 ITGA6: Integrin alpha-6 JAG1: Jagged 1 LEF1: Lymphoid enhancer-binding factor 1 MKI67: Ki-67 protein PDGFRA: Platelet-derived growth factor alpha receptor SNAI2: Snail 1 SOX2: SRY (sex determining region Y)-box 2 TBX3: T-box 3 TGFB2: Transforming growth factor-beta 2 VCAM1: Vascular cell adhesion molecule 1 VIM: Vimentin ZEB1: Zinc finger E-box-binding homeobox 1

Abstract

Drug resistance is a major obstacle in the treatment of breast cancer. Surviving cells lead to tumor recurrence and metastasis, which remains the main cause of cancer-related mortality. Breast cancer is also highly heterogeneous which hinders the identification of individual cells with the capacity to survive anticancer treatment. To address this, we performed extensive single-cell gene expression profiling of the luminal-type breast cancer cell line MCF7 and its derivatives, including docetaxel-resistant cells. Upregulation of EMT and stemness-related genes and downregulation of cell cycle-related genes, which were mainly regulated by LEF1, were observed in the drug-resistant cells.

Interestingly, a small number of cells in the parental population exhibited a gene expression profile similar to that of the drug-resistant cells, indicating that the untreated parental cells already contained a rare subpopulation of stem-like cells with an inherent predisposition towards docetaxel resistance.

Our data suggest that during chemotherapy, this population may be positively selected leading to treatment failure.

Statement of significance

This study highlights the role of breast cancer intra-tumor heterogeneity in drug resistance at a single cell level.

Introduction

Breast cancer is the most common malignancy in women worldwide and the second cause of cancer-related death(1). Breast cancer subtypes are determined by the expression of estrogen receptor

(ER), the progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2). Among these subtypes, the luminal type (ER+, PR+) is the most common, and the majority of patients have a good prognosis if treated with endocrine therapy(2). However, a subset of patients develop drug resistance leading to treatment failure, tumor recurrence and eventually metastasis, which remains the cause of more than 90% of cancer-related deaths(3).

In recent years, large-scale sequencing analyses of solid cancers have shown the existence of intratumor spatial and temporal heterogeneity, bringing an increased awareness that this tumor heterogeneity is a critical reason for treatment failure(4,5). However, most of the genetic studies for cancer characterization have been performed on bulk samples, underestimating the gene expression of minor populations (6,7). Currently, single-cell technologies have become a powerful approach to a more detailed understanding of minor populations(8). By analyzing the transcriptome of single cells, one can detect low-abundance variations in gene expression and identify regulatory pathways responsible for driving drug resistance (9).

The concept of cancer stem cells (CSCs) was described less than two decades ago, and its connection to drug resistance has been widely reported(10). CSCs are a small intratumoral subpopulation of cells with the capacity to self-renew and to differentiate into the heterogeneous lineages that comprise the tumor(11). As can be inferred from the name, CSCs possess erroneously activated stemness-related genes and present an undifferentiated phenotype(12). A well-described pathway in CSCs is the Wnt signaling pathway. Upon activation of Wnt signaling, β-catenin that would otherwise be degraded enters the nucleus, where it binds to the LEF/TCF complex and then

recruits other cofactors to promote the transcription of multiple molecules related to stemness (13).

The protein Lef1, a member of this complex, is highly expressed in colon cancer and leukemia

(14,15), where it has been reported to be associated with poor prognosis and essential for cancer invasion and metastasis (15–17). However, its role in drug resistance is not well known.

To analyze the dynamic alterations in drug resistance acquisition in subpopulations of luminal-type breast cancer cells, we performed extensive single-cell gene expression profiling

(single-cell qPCR) of MCF7 cells and their derivatives, including several docetaxel-resistant cells (2.5 nM and 5 nM). Here, we demonstrated that the loss of miR-27b (previously identified as a drug-resistance-related miRNA(18)), followed by further docetaxel treatment, induced the expression of components of the Wnt and EMT pathways and reduced the expression of cell cycle regulatory genes. Thus, the population presented an enrichment of cells with a CSC phenotype. Moreover, a rare cell population with the same gene pattern was identified in the original pool of MCF7 cells, suggesting preexisting drug-resistant cells within luminal-type breast cancer cells prior to treatment.

Materials and methods

Cell culture & drug resistance generation

MCF7, MDA-MB-231, ZR-75 and BT474 breast cancer cell lines were purchased from the American

Type Culture Collection (ATCC) and tested to verify the absence of mycoplasma contamination when cells were prepared. All the cell lines were authenticated by genetic profiling using polymorphic short tandem repeat loci (Promega, Japan). The cell lines were maintained in RPMI-1640 medium (Sigma,

CA, USA) supplemented with 10% heat-inactivated fetal bovine serum (FBS, Thermo Fisher

Scientific, LA) and 1× Antibiotics and Antimitotic (Gibco, LA, USA) and grown at 37°C in a 5% CO2 incubator. A previously established MCF7 anti-miR-27b cell line (18) was maintained with

RPMI-1640 supplemented with 10% FBS and 2 μg/mL of puromycin (Gibco, LA, USA). MCF7 anti-miR-27b docetaxel-resistant cell lines were generated by the addition of 0.5 nM docetaxel

(Sanofi Aventis, France) to complete medium for one month. Once the cells were adapted to this concentration, it was gradually increased by stepwise selection up to 5 nM over the course of two more months. For this study, we used 2.5 nM and 5 nM docetaxel-resistant (DR) MCF7 anti-miR-27b, which were originated from the same cells. In all cases, the medium was changed every 3 days, and the cells were passaged when they reached 70-80% confluence. In this study, the passage number of cell lines are less 15 after purchase or drug-resistance cell line establishment.

Microfluidic single-cell qRT-PCR

Single-cell capture, lysis and reverse transcription preamplification experiments were performed using the C1 Auto Prep System (Fluidigm, SF, USA) according to the manufacturer’s instructions.

Cells were trypsinized, and single cells were loaded into a C1 integrated fluidic circuit (IFC) at a concentration of 300 cells/μL in PBS(-) containing 5% FBS and 5 mM of EDTA (Nacalai Tesque, CA,

USA). After single cell isolation, cells were assessed for viability using calcein-AM and ethidium homodimer 1 staining (Live/Dead Kit, Life Technologies, LA, USA). The chips were imaged using a

BZ-X700 (KEYENCE, Osaka, Japan), and chambers containing two or more cells, no cells or dead cells were removed from further analysis. After lysis, reverse transcription (25℃ for 10 min, 42℃ for

60 min, 85℃ for 5 min) and 18 cycles of preamplification (each cycle: 95℃ for 15 s, 60 ℃ for 4 min), single-cell cDNA was harvested, transferred to a 96-well plate and diluted 6-fold with cDNA dilution buffer.

Further single-cell gene expression experiments were performed using Fluidigm’s 96.96 quantitative PCR Dynamic Array microfluidic chips (Fluidigm, SF, USA) according to the manufacturer’s instructions. Probe mixes for the individual assays were generated by loading 2.5 μL of

2× Assay Loading Reagent (Fluidigm, SF, USA) and 2.5 μL of 20× TaqMan gene expression assay into the chips (Applied Biosystems, MA, USA). Sample mixes were generated by combining 2.5 μL of 2×

TaqMan Universal PCR Master Mix (Applied Biosystems, MA, USA), 0.25 μL of 20× GE Sample

Loading Reagent (Fluidigm, SF, USA) and 2.25 μL of diluted cDNA. The plates were vortexed and centrifuged to homogenize the solutions. Before the probe assays and sample mixes were loaded into

96.96 Dynamic Array microfluidic chips, the chips were primed in an HX IFC Controller (Fluidigm,

SF, USA) machine. After priming, 5 μL of sample and the same volume of probe mix were loaded individually in the same machine. Then, the chips were transferred into a BioMarkHD real-time qPCR apparatus (Fluidigm, SF, USA) and run according to the manufacturer’s instructions. A schematic representation of the most important steps can be found in Supplementary Fig. S1.

Lef1 transfection

Lef1 plasmid was purchased from Origene (pLentiCmycDDK, Origene, MD). Fourteen micrograms of plasmid was added to 2×106 MCF7 cells along with Lipofectamine 2000 (Invitrogen, CA, USA) according to the manufacturer’s instructions. The medium was changed after 8 hr, and 24 hr after the addition of the plasmid, the cells were trypsinized and seeded into 96-well plates at a density of 5000 cells per well for the subsequent MTS assay. The following day, the medium was changed, and different concentrations of docetaxel (ranging from 1 μM to 0.3 nM) were added for three days for the subsequent proliferation assay.

Results

The 95-gene primer set discriminates breast cancer subtypes

To investigate the dynamic changes at the population and single-cell levels during drug resistance acquisition, we used the C1 Auto Prep System for multiplex gene expression analysis. For that purpose, we designed a 95-primer set for stemness-related genes, EMT-related genes, genes encoding hormone receptors, and genes encoding signaling factors; the genes were selected from literature research(19) and our previous work on luminal-type breast cancer(18,20) (Supplementary Fig. S1A,

Supplementary Table S1).

To evaluate the accuracy of the 95-primer set, we first developed a single-cell gene expression signature from two types of breast cancer cell lines, MCF7 and MDA-MB-231, distinctive for their luminal and basal-like subtypes, respectively (Fig. 1A and Supplementary Fig. S1A). The mRNA data from a total of 121 single MCF7 cells and 77 single MDA-MB-231 cells were normalized using

GAPDH values and analyzed with unsupervised hierarchical clustering to visualize similarities and differences. Unsupervised hierarchical clustering based on cells and genes distinguished the two subtypes clearly, presenting gene expression consistent with expected biomarker patterns. High expression of typical luminal genes, such as ESR1, CD24 and CDH1, was found in the MCF7 subpopulation, while basal-like genes, such as JAG1, VIM and ITGA6, were highly expressed in the

MDA-MB-231 subpopulation (Fig. 1A).

A two-dimensional t-SNE plot further separated the two cell lines in a similar manner (Fig. 1B, left). As in the linear hierarchical clustering, the genes were distributed into two specific subgroups according to the principal component analysis (Fig. 1B, right). The t-SNE plot distribution along with

the expression levels of individual genes demonstrated that luminal markers such as CD24, FOXA1,

GATA3, ESR1, and AR were highly expressed in MCF7. On the other hand, the expression levels of

JAG1, SOX9, ZEB1, VIM and SNAI2, which are genes specific to the basal type, had almost no expression in MCF7 cells (Fig. 1C). Interestingly, the t-SNE plot also illustrated that although a pattern in gene expression was observable, those populations presented intercellular heterogeneity.

Furthermore, few cells presented the gene expression representative of other cell lines. For example, as indicated with arrows in the ZEB1 plot, we found 3 MCF7 cells with high expression of ZEB1, a typical basal cancer marker (Fig. 1C).

Dynamic variations in the MCF7 cell subpopulation and its derivatives

We had previously reported that microRNA-27b (miR-27b) was significantly downregulated in luminal-type cancer patients who presented resistance to docetaxel (DTX) (18,20). Loss of miR-27b was described to increase the expression of ATP-binding cassette super-family G member 2 (ABCG2) and promote its localization in the membrane through the direct inhibition of the protein ENPP1 (Fig.

2A). ABCG2 is a transmembrane protein known to transport multiple molecules, including several anticancer drugs, and have a role in multi-drug resistance (21). This promoted an increased resistance to DTX in MCF7 cells, as well as the generation of the side population fraction as revealed by flow cytometry assay, corresponding to cancer stem cells (CSCs) (18). Taking this into consideration, we selected the MCF7 parental cell line and MCF7 anti-miR-27b, a cell line previously generated in our laboratory, with a stable knockdown of miR-27b using a lentiviral vector expressing the antisense sequence of miR-27b. Moreover, these cells were transfected with a sensor vector containing GFP along with two miR-27b complementary sequences in its 3’ UTR (18). MCF7 anti-miR-27b would represent an intermediate-stage cell line with high predisposition toward drug resistance. Then, using

MCF7 anti-miR-27b, we established two drug-resistant cell lines to 2.5 nM and 5 nM DTX,

respectively; MCF7 anti-miR-27b-DR 2.5 nM and MCF7 anti-miR-27b-DR 5 nM. The IC50 of MCF7 anti-miR-27b-DR 5 nM was more than 350 folds higher rather than MCF7 parental; MCF7

anti-miR-27b IC50 was situated in between, being approximately tenfold higher than MCF7 cells

(Supplementary Fig S1B).

Single-cell qPCR (sc-qPCR) analysis was performed on a total of 484 cells, which were selected after stringent filtering for data quality, as explained in the materials and methods (Supplementary Fig.

S1A). Prior to drug resistance acquisition experiments, we tested whether the insertion of the lentivirus vector itself altered gene expression profiles. We found that the insertion of the NC lentivirus did not affect the expression of any gene except PDGFRA, which was removed from the rest of the analysis (Supplementary Fig. S1C-G). The correlation between the MCF7 parental and NC lines was 0.95, indicating no artificial change after lentiviral infection (Supplementary Fig. S1C).

Accordingly, MCF7 NC clustered together with the MCF7 parental cell line in the t-SNE plot (Fig.

2B). The MCF7 anti-miR-27b cell line clustered in the same region as the luminal cell type but closer to MDA-MB-231, indicating the activation of several genes inducing a basal-like phenotype (Fig. 2B), as is characteristic of the MDA-MB-231 cell line.

Thus, we investigated population variations during drug resistance acquisition. Figure 2C portrays a t-SNE plot containing MCF7, MCF7 NC, MCF7 anti-miR-27b, MCF7 anti-miR-27b-DR

2.5 nM and 5 nM. Remarkably, the t-SNE plot dissected into the 5 original cell lines to illustrate the differences, showed two distinct groups: one consisting of MCF7 parental and MCF7 NC (r2=0.955) and one consisting of MCF7 anti-miR-27b-DR 2.5 nM and 5 nM (r2=0.979). The correlation coefficients further confirmed the similarity within each group (Supplementary Fig. S1C and D). The

MCF7 anti-miR-27b cell line was situated between these two groups in a broader, undefined manner.

A portion of the cells seemed to be located within the population of drug-resistant cells, suggesting that MCF7 anti-miR-27b contains cells that are enriched under docetaxel treatment.

Induction of the CSC profile in MCF7 cells with miR-27b knockdown

To identify the genes responsible for drug resistance, we compared the differential gene expression among MCF7 NC, MCF7 anti-miR-27b, and MCF7 anti-miR-27b-DR 2.5 nM and 5 nM

(Supplementary Fig. S2). A total of 27 genes were deemed relevant to drug resistance. These genes were comprised in pathways related to EMT, stemness and cell cycle regulation. The upregulated genes included CAV1, CAV2, LEF1, SOX2, ACTA2, TGFB2, VIM, and ABCG2 (Fig. 3A), suggesting an EMT activation as well as an increase in stemness accompanied by drug-resistance marker genes.

The downregulated genes included CDH1 (E-cadherin), TBX3, MKI67, CCNA2, CHEK1 and CCNB1

(Fig. 3A, B), which suggested that a subset of cells had a slow cell cycle or were in a dormant state

(Fig. 3B circled, 3C in white box). EMT and stemness activation along with a dormant state suggested a CSC subpopulation.

To further confirm the importance of this gene set, we clustered the cells once more with a reduced primer set composed of 27 genes (Fig. 3C). The previous stratification by the t-SNE plot (Fig.

2C) was corroborated by the hierarchical clustering, which displayed the same grouping into 3 obvious clusters based on the selected 27-gene set.

The expression of CAV1 and CAV2 was highly correlated with EMT and Wnt signaling pathway genes

The upregulation of a number of genes in the stemness and EMT pathways in MCF7 anti-miR-27b and MCF7 anti-miR-27b-DR 2.5 nM and 5 nM at the population level prompted us to speculate that

similar correlations of these gene expressions could occur at the single-cell level. Moreover, we hypothesized that the integrated activation of these pathways could be responsible for drug resistance induction. Thus, we analyzed Spearman’s correlation between these genes. A correlation analysis of

14 gene expression levels showed high internal correlation within two generic groups. The first included EMT and stemness-related genes, and the second included cell cycle regulator genes (Fig.

4A).

The gradual increase in VIM and decrease in CDH1 (Supplementary Fig. S3A) in relation to drug resistance acquisition indicated an induction of the EMT phenotype starting in MCF7 with miR-27b knockdown, which was pronounced after DTX treatment. Moreover, TGFB2, which is known to be upstream of ACTA2 and related to EMT induction, was also significantly upregulated and correlated with ACTA2 (Fig. 4A)(22). The stemness-regulating Wnt pathway was also highly activated, as indicated by the transcription factor LEF1(23,24). LEF1 was mostly not expressed in MCF7 parental cells nor MCF7 NC cells but was expressed moderately in MCF7 anti-miR-27b cells and even more in DTX-treated cells in a dose-dependent manner (Fig. 3A). Interestingly, it has been reported that

ABCG2 and β-catenin expression are tightly related to epirubicin, taxol and 5-fluorouracil drug resistance(25). In our cells, there was also a moderate Spearman’s correlation between LEF1 and

ABCG2 (r2=0.42). Furthermore, the coexpression of these two genes was restricted to MCF7 anti-miR-27b, MCF7 anti-miR-27b-DR 2.5 nM and MCF7 anti-miR-27b-DR 5 nM cells

(Supplementary Fig. S3B).

The genes with the most remarkable expression changes during drug resistance acquisition were

CAV1 and CAV2, which have been widely described to interact with each other to activate multiple signaling cascades(26). As our data indicate, CAV1 and CAV2 presented a high Spearman’s correlation (r2=0.81), and coexpression increased along with drug resistance rates (Fig. 4B). Moreover,

this pattern also correlated with most of the other genes involved in the TGF-β and Wnt signaling pathways, as well as with ABCG2 expression (Fig. 4C). Cell cycle regulators were highly correlated with each other (Fig. 4A) and downregulated in a specific subpopulation of docetaxel-treated cells

(Fig. 3B and C). The correlation between CCNA2 and MKI67 was especially high (r2=0.93)

(Supplementary Fig. S3C). This expression was inversely correlated with ACTA2, CAV1 and CAV2, indicating that cells expressing genes in the EMT and stemness pathways also presented slower cell cycles than other cells. Indeed, these characteristics are typical of the CSC subpopulation.

Preexistence of putative drug-resistant cells in the MCF7 parental population

When cells were distributed in the t-SNE plot using all 95-primer sets, a small subset of MCF7 and

MCF7 NC cells (3 and 2 cells, respectively) were clustered together with a majority of the docetaxel-treated cells (Fig. 2C and 5A). To further analyze the reason for this similarity, we identified the cells and closely analyzed the expression of the preselected genes involved in drug resistance in those individual cells. This expression is presented as a spider plot (Fig. 5B). This graph represents the fold change in each cell in comparison to the average gene expression in the parental population. Because the population of MCF7 was very similar to that of MCF7 NC (Supplementary

Fig. S1C, r2 > 0.95), the two were combined to calculate the average parental gene expression. The identified cells presented a gene expression pattern much closer to that of docetaxel-treated cells than to that of parental MCF7 cells (Fig. 5B). The similar genes included CAV1, CAV2, ABCG2, LEF1, and VIM, while ACTA2 presented a much higher expression. Interestingly, most of these cells did not present reduced cell proliferation (deduced through the expression of cell cycle regulators) as

DTX-treated cells did. These data indicated that the induction of dormancy might be an effect caused by DTX treatment.

Lef1, Vimentin and Cav1 protein levels were found in clinical samples

To confirm whether the RNA transcripts were translated to protein, we selected a gene representative of EMT (VIM), one representative of the Wnt signaling pathway (LEF1), and the most strongly correlated gene (CAV1). Their protein expression was analyzed by immunofluorescence (IF) in parental MCF7 cells and MCF7 anti-miR-27b-DR 5 nM. As found by sc-qPCR, IF also revealed intercellular heterogeneity, with different levels of expression of the proteins among different cells

(Fig. 6A). The expression of the proteins was almost undetectable in MCF7, whereas they were highly expressed in DTX-resistant cells. The protein expression of Lef1, Vimentin and Cav1 was found in

0.8%, 1.92% and 0.22% of the MCF7 cells, respectively (Supplementary Fig. S4A, B). The percentage of cells positive for those three proteins was greatly increased to 30.71%, 21.1% and

17.11%, respectively, in MCF7 anti-miR-27b-DR 5 nM cells (Supplementary Fig. S4A, B).

Importantly, in co-expression IF by pair of genes (Vim-Lef1 and Vim-Cav1) showed high co-expression of those genes, even in parental MCF7 with a percentage of 0.11%, and 0.074% in

Vim-Cav1 (Fig. 6A). Independently, the activation of TGF-β signaling pathway was analyzed by western blot using the antibodies against Phosphorilated-samd2(p-smad2) and smad2, which their ratio is known to indicate TGFβ signaling pathway activation (27). In MCF7 anti-miR-27b-DR 5 nM presented not only highly activation of TGFβ signaling, but also higher levels of smad2 (Fig. 6B).

This prompted us to analyze the expression by IF, showing similar results to Vim (Fig 6C,

Supplementary Fig. S4A). On the other hand, and despite the RNA-protein correlation, protein expression of the TGF-β pathway downstream ACTA2, which was highly expressed at the mRNA level, was not found by IF. This lack of ACTA2 protein translation was also corroborated by western blot (Supplementary Fig. S4C), suggesting a different function for TGFβ signaling pathway.

To exclude this as a mere phenomenon occurring in MCF7 cell line, we co-stained the same genes in one more Luminal A cell line (ZR75) and its DTX resistant derivative (ZR75 anti-miR27b-DR

0.5nM) as well as in the Luminal B cell line, BT474. All the parental cell lines contained a small population of co-stained positive cells in a low proportion, while the drug resistant ZR75 anti-miR27b-DR 0.5nM cell line, presented a more moderated staining, although not as much as

MCF7 anti-miR27b-DR 5nM (Supplementary Fig. S4D, E).

To further confirm the presence of these genes not only in cell lines but also in clinical specimens, we used two breast cancer tissue microarrays for immunohistochemical (IHC) analysis of

Lef1, Vimentin and Cav1. Consecutive slides confirmed not only positive cells but also high concordance among the expression levels of these proteins. While negative samples for Lef1 tended to also present low expression of Vimentin and Cav1, Lef1-positive samples clearly presented high expression of Vimentin and Cav1. Moreover, the expression of these proteins was found in the same region. In Lef1-negative samples, Vimentin-positive cells are mainly stromal cells and Cav1-positive cells are only found in the ductolobular system, as previously described(28–30) (Fig 6D,

Supplementary Fig. S5A). However, in Lef1-positive samples, the expression of Vimentin and Cav1 was found in epithelial-like cancer cells, as shown in Fig. 6D and Supplementary Fig. S5A-C.

To further classify and analyze the samples, we separated them by cancer subtype and Lef1 expression into the following categories: no Lef1 expression, moderate positive expression (including

1-70% of positive cells per visual field) and positive (more than 70% of positive cells per field).

Examples of each type can be found in Supplementary Fig. S5. We found that approximately half of luminal samples were positive for Lef1, for most of the samples the expression of Lef1 was reduced to a very small number of cells, and its expression was not as intense as the one showed in figure 6D

(+) (Fig. 6E, Supplementary Fig. 5C and Supplementary table S2) resembling the parental cell lines.

Interestingly, this percentage was not significantly different among cancer subtypes, although an increase in Lef1-positive samples in the basal subtype could be intuited (Supplementary Fig. S6A).

Similarly, no correlation with ER, PR or HER2 expression was found for Lef1 (Supplementary Fig.

S6B-D). Furthermore, Lef1 expression did not correlate with tumor stage or patient age

(Supplementary Fig. S6E and F).

Lef1 contributed to drug resistance by inducing the expression of the other genes.

Among all the molecules important for drug resistance, we focused on Lef1. Lef1 is a transcription factor in the Wnt signaling pathway and thus, is involved in stemness regulation. Additionally, Lef1 has been described to act independently from β-catenin and to activate several EMT-related genes

(31).

We overexpressed Lef1 in MCF7 (MCF7 Lef1 o/e), and the mRNA levels of a set of genes were analyzed. After transfection, LEF1 mRNA levels were greatly increased, followed by a more moderate increase in ABCG2, VIM, CAV1, ACTA2 and SMAD2 (Fig. 7A). In parallel to mRNA, protein levels were measured at days 1 and 4 after transfection. Likewise, Lef1 protein expression was increased to similar levels as in MCF7 anti-miR-27b DR 5nM, especially at day 1 (Fig. 7B, C and

Supplementary Fig. S7A). Vimentin and ABCG2 levels also reflected this increase, but the change was not observable until day 4 (Fig. 7B, C). Unexpectedly, Cav1 expression was not induced (Fig.

7B). Because Lef1 is known to be activated and interact with DNA after binding directly to

β-catenin(32), the protein levels of β-catenin were measured in MCF7 Lef1 o/e. However, we found no significant increases, suggesting that the relationship of Lef1 with drug resistance might be independent of β-catenin (Fig. 7B, C). The activation of TGF-β signaling pathway after overexpression of Lef1 was also analyzed by western blot. The protein expression of smad2 and

p-smad2 were upregulated (Fig. D). The expression of p-smad2 was higher on the 4th day, increasing considerably the p-smad2/smad2 ratio, which indicated a TGF-β signaling activation (Fig. 7E).

Finally, MCF7 Lef1 o/e cells were used to confirm the effect of Lef1 on DTX resistance through

a proliferation assay (Fig. 7F). We observed that MCF7 Lef1 o/e cells presented an IC50 more than

4.5-fold higher than MCF7 cells (3.82 nM and 17.55 nM, respectively). Taken together, these data suggest that the Wnt signaling pathway transcription factor Lef1 activated the transcription of several genes, including at least ABCG2 and Vimentin, and increased resistance to DTX in a luminal-subtype breast cancer cell line.

Discussion

The luminal A subtype is the most common breast cancer subtype and presents a relatively good prognosis(2). However, a subset of patients develop drug resistance leading to treatment failure, tumor recurrence and eventually metastasis, which dramatically reduce their 5-year survival rate (3).

The mechanisms by which drug-resistant cells appear are still unclear but have been strongly linked to intratumor heterogeneity. Breast cancer presents high intratumor heterogeneity, making bulk analysis inviable. Even commercially available cell lines, which are thought to be highly homogeneous, are now known to present a certain level of heterogeneity(33). In this study, we performed extensive single-cell gene expression profiling (sc-qPCR) of MCF7 cells and a few derivatives to elucidate intercellular heterogeneity and to find rare populations of cells related to drug resistance. Sc-qPCR allowed us to observe not only the dynamic changes at the population level but also the concrete changes induced at the single-cell level in luminal-type breast cancer cells subjected to DTX treatment. Here, we identified a gene expression pattern characteristic of drug-resistant cells, which was also found in a rare population within the untreated parental cell line.

These genes were mainly related to EMT, stemness and cell cycle regulation. EMT induction was clearly observed by the loss of the epithelial marker CDH1 and the gain of the mesenchymal marker VIM (34–36). Furthermore, the TGF-β signaling pathway was also activated, since both TGFB and its downstream target ACTA2 (22) were increased in MCF7-anti-miR-27b-DR. Correlated with

EMT at the single-cell level, stemness pathways were activated, as revealed by LEF1, a central transcription mediator of Wnt signaling pathway (16,24). High expression of LEF1 was found in the drug-resistant derivatives, while it was almost imperceptible in the parental cell line. At the same time, a subset of DTX-resistant cells were found to express low levels of several cell cycle regulatory genes, suggesting G2/M cell cycle arrest(37). Previous reports have linked the low expression of CCNA2,

MKI67 and CCNB1 with cell cycle arrest and even dormancy(38,39). The gene expression dynamics indicated that the cells with activation of EMT and stemness genes also presented a slow cell cycle.

Thus, our results were consistent with previous reports showing that EMT promotes stemness (40) and that cells with acquired stemness and dormancy states, namely, CSCs, present an especially high degree of drug resistance(41). This CSC gene expression pattern in the drug-resistant population is also supported by our previous studies, in which the knockdown of miR-27b induced the generation of the SP fraction identified by a FACS assay(18). Nonetheless, it is also important to keep in mind that the subpopulation with slow proliferation is a fraction of MCF7 anti-miR-27b-DR 2.5 nM and 5 nM, which are docetaxel-treated cells. Considering that DTX treatment leads to cell cycle arrest by binding to the β-subunit of tubulin and repressing the dynamic instability of mitotic spindles(42), we cannot exclude the possibility that the reduced cell proliferation could be an effect of DTX treatment.

Importantly, we identified a small subset of MCF7 and MCF7 NC cells that were clustered together with the majority of DTX-treated cells in the t-SNE plot. When the gene expression of these single cells was closely analyzed, we found that their expression pattern most closely resembled that of

MCF7 anti-miR-27b-DR cells, but normal cell cycle-related genes expression. Our data suggested that the primary non-drug-resistant cell line contains a rare population of stem-like cells with inherent higher potential to be DTX resistant and that during chemotherapy, this population is positively selected and becomes the major cell population, giving rise to treatment failure.

Because mRNA does not always correlate with protein translation, some representatives of the gene expression pattern were investigated in cell lines and breast cancer tissue samples.

Immunostaining revealed that most of the mRNA levels correlated with protein levels and drug resistance capacity. Thus, the presence of a rare population with inherent drug resistance within the parental cell line was confirmed at the protein level by few cells lines representatives for luminal A and B subtype of breast cancer. Tissue-array IHC showed that half of luminal samples were positive for Lef1 and that most of them presented a moderate to low percentage of positive cells. Although

Lef1 expression did not correlate with tumor stage, patient age or receptor expression (ER, PR,

HER2), correlations in expression level and approximate location with Vimentin and Cav1 were apparent. Vimentin is commonly found in stromal, and Cav1 in ductal cells, while Lef1 is not expressed in healthy breast tissue or commonly expressed in luminal breast cancer (28–30,43).

However, in Lef1-positive samples, these molecules were all found to be expressed in epithelial cells situated in close regions. The low proportion of stained cells in the tissues adverted to a rare population, correlating with the results of sc-qPCR and protein expression in the cell lines. It is important to note that bulk assays would not detect this subpopulation, which highlights the importance of single-cell technology.

We hypothesized that Lef1 could be a key molecule for the gene regulation responsible for drug resistance, since it has been linked not only to stemness but also to EMT induction. High expression of LEF1 has been associated with poor prognosis and has been reported to be essential for cancer

invasion and metastasis(15–17). Lef1 overexpression (Lef1 o/e) in MCF7 cells induced the expression of other molecules such as Vimentin and ABCG2 at the mRNA and protein levels and activated TGFβ

signaling pathway. This overexpression caused an increase in DTX resistance, raising the IC50 of

MCF7 cells more than four folds. Moreover, Lef1 has been described to induce EMT both by inhibiting E-cadherin (44) and by inducing Vimentin expression (45), as we found in

MCF7-anti-miR-27b-DR cells. Interestingly, the induction of EMT by Lef1 has also been reported to be independent of β-catenin. Kobayashi et al. showed that a mutant form of Lef1 with an altered

β-catenin binding site increased the EMT potential of cancer cells(31). Moreover, during embryogenesis it has been described that Lef1 recruits p-smad2, and not β-catenin, to regulate the expression of several genes, such as E-cadherin and Xtwn (44,46). Accordingly, when we examined

β-catenin expression in Lef1 o/e cells, we found no significant increase. It was not smad2 but also its activated forms p-smad2, which was highly activated in those cells. This suggests that the relationship between Lef1 and drug resistance could be independent of β-catenin, and probably related to TGF-β, although this hypothesis should be confirmed in future experiments.

Despite the controversy over CAV1’s role in breast cancer (47), the expression levels of the members of the caveolin family presented the strongest dynamic alteration upon DTX treatment.

Cav1 and Cav2, found in caveolae, mediate vesicular transport and several signal transduction pathways, modulating the expression of multiple genes such as ESR1, ERBB2, TGFB, NGF and

MTOR(26). We found that the expression of CAV1 and CAV2 was highly correlated with that of most of the genes represented in CSC features. These results are consistent with those of Wang et al., who reported that isolated CSCs presented higher expression of CAV1 than the non-CSC population in breast cancer(25) and that CSCs are highly resistant to conventional chemotherapy and radiotherapy(48). Using single-cell analyses, we confirmed that only a very small proportion of

parental MCF7 cells expressed CAV1, as described in luminal breast cancer (49). This low expression was increased in MCF7-anti-miR-27b and further enriched during DTX treatment. Cav1 protein levels corresponded with these results in cell lines and in clinical samples, existing a correlation between Cav1, Lef1 and Vim expression. Similarly, Cav1 expression has been found in drug-resistant cells in lung, colon and HER2-positive breast cancer(50,51). However, under experimental Lef1 o/e in MCF7, although CAV1 mRNA increased, we did not observe increased Cav1 protein expression.

Therefore, we could not conclude that Lef1 regulated Cav1 as happened with the other genes. Cav1 regulation might be related to miR-27b loss rather than Lef1 o/e, as there is a known relationship between ABCG2 and Cav1(25,52).

Despite our efforts to identify a population of drug-resistant cells within several cell lines, from luminal A and B subtypes of breast cancer, we cannot ignore the several reports regarding the differences between cell lines and patient-derived tissue’s heterogeneity(53). In spite of finding similar patterns of gene expression between cell lines and clinical samples, we could not obtain information regarding the drug-response of those samples. Thus, the results may not be conclusive in in vivo systems. In the future, we plan to keep using single-cell approaches to study drug resistance in clinical samples.

In this study, we used single-cell qPCR analysis to identify a group of genes that were collectively expressed in drug-resistant cells and regulated the CSC phenotype. Furthermore, this group of genes was mainly regulated by Lef1, a central molecule within the Wnt signaling pathway.

The gene pattern characteristic of drug-resistant cells was also found in a small subset of MCF7 parental cells, suggesting that the untreated primary cells contained a rare subpopulation of stem-like cells showing an inherent predisposition to docetaxel resistance. Our data suggest that during chemotherapy, this population may be positively selected and become the major cell population,

causing treatment failure. Although preliminary, our findings could be of particular interest for understanding the collective role of genes driving docetaxel resistance in minor cell populations.

Moreover, the specific roles of Lef1 and its possible inhibition as a target for drug treatment should be considered in future experiments.

Acknowledgements

We appreciate the contribution of Dr. Isaku Kohama for helpful discussion. Dr. Daisuke

Shiokawa for his helpful discussion and nice recommendations. The present work was

supported in part by a Grant-in-Aid for Scientific Research (C) JSPS KAKENHI Grant

Number: 19K16761, Grant-in-Aid for Young Scientists (A) JSPS KAKENHI Grant Number:

17H04991 and the “Development of Diagnostic Technology for Detection of miRNA in

Body Fluids” grant from the Japan Agency for Medical Research and Development (AMED)

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Figure Legends

Figure 1. The 95-primer set classifies luminal- and basal-type breast cancer. (A). Unsupervised hierarchical clustering of MCF7 and MDA-MB-231 cells separated by luminal-type versus basal-type genes. (B) t-SNE plot (left) for distinct cell populations and PCA map (right) for clustering of genes by cancer type. PCA, principal component analysis. (C) t-SNE plots, along with expression at the single-cell level represented on a green-red color scale, of several genes representative of the luminal and basal subtypes. Arrows in the ZEB1 plot indicate three cells with unusual expression.

Figure 2. Population changes accompanying miR-27b knockdown and subsequent docetaxel treatment. (A) A schematic image of the function of miR-27b knockdown in MCF7 cells, previously described in (18). Right panels show phase and GFP images of MCF7 cells and MCF7 anti-miR-27b-DR 5 nM, GFP indicates the loss of miR-27b. Scale bar: 50 μm. (B) A t-SNE plot

showing the distribution of MCF7 derivatives (red, orange and purple) and MDA-MB-231 cells

(black). (C) t-SNE plots representing the dynamic alterations in MCF7 cells and their derivatives.

Figure 3. Docetaxel treatment induced the expression of stemness-related genes, EMT-related genes, and drug-resistance genes and decreased the expression of genes related to cell cycle regulation. (A) Violin plots showing the changes in the cell population with DTX treatment at the population level. (B) t-SNE plots, along with single-cell expression levels represented on a green-red color scale, of cell cycle regulatory genes. The black circle indicates a subpopulation of cells with low expression of cell cycle regulatory genes. (C) A heatmap using only 27 genes for the cell classification. The white box indicates the subpopulation of cells with low expression of cell cycle regulatory genes.

Figure 4. Correlation between genes involved in drug resistance. (A) Correlation plots of candidate genes. The large orange circle indicates a strong positive correlation, while the large purple circles indicate a strong negative correlation. The circle size indicates the strength of the correlation.

(B) Spearman’s correlation of CAV1 and CAV2, showing the relationship between increased caveolin levels and drug resistance. (C) The expression levels of ABCG2, TGFB2, LEF1 and ACTA2 in relation to CAV1-CAV2. Red circles indicate the highly expressed genes in each cell.

Figure 5. The parental population includes a few cells whose expression patterns are similar to those from drug-resistant cell lines. (A) t-SNE plots representing cells (left), parental MCF7 cells

(middle) and MCF7 NC cells (right). Arrows indicate cells that clustered close to docetaxel-resistant

cells. (B) A spider plot showing the expression of several genes including genes relevant to the Wnt signaling pathway, EMT, drug resistance and cell cycle regulation. The gene expression levels are normalized to MCF7 parental cells (thick gray line). The black line represents the average gene expression levels in docetaxel-resistant cells. The expression levels in Cells A to E are plotted in different colors.

Figure 6. mRNA levels found by sc-qPCR mostly correlate with protein translation. (A)

Immunofluorescent detection of Cav1 and Lef1 (red) costained with Vimentin (green) in MCF7 and

MCF7 anti-miR-27b-DR 5 nM cells. The nuclei were stained with 4,6-diamidino-2-phenylindole

(DAPI, blue) only in the parental cell line. Scale bar: 100 μm. (B) Representative western blot of

Smad2 and p-Smad2 in MCF7 and MCF7-anti-miR-27b-DR and its ratio showing an activation of its signaling pathway TGFβ, of 4 folds in the drug resistant cell line. (C) Immunofluorescence of Smad2 in in MCF7 and MCF7 anti-miR-27b-DR 5 nM cell. The nuclei were stained with DAPI (blue). Scale bar: 100 μm. (D) Representative immunohistochemistry images of samples that are negative (upper panels) and highly positive (lower panels) for protein expression of Lef1, Vimentin and Cav1 in the luminal subtype of breast cancer. Scale bar: 25 μm. (E) Graph displaying the percentage of cells expressing Lef1 levels among all the luminal samples.

Figure 7. Lef1 overexpression induces docetaxel resistance in MCF7 cells by inducing the expression of ABCG2 and Vimentin. (A) Gene expression patterns induced by Lef1 overexpression in MCF7 cells (n=4). (B) Representative western blot image after Lef1 overexpression showing the levels of ABCG2, Vimentin, Cav1 and β-catenin. (C) Quantity of protein relative to day 0 (n=4). (D)

Representative Western blot image of Smad2 and p-Smad2 after Lef1 overexpression on MCF7 cells

(E) Ratio of p-Smad2-Smad2 indicating a TGFβ signaling activation after Lef1 overexpression. (F)

Proliferation assay of MCF7 and MCF7 Lef1 o/e under docetaxel treatment. The IC50 values are as follows: MCF7=3.82 nM and MCF7 Lef1 o/e=17.55 nM. (n=4) p < 0.05.

Single-cell Analysis Reveals a Preexisting Drug-Resistant Subpopulation in the Luminal Breast Cancer Subtype

Marta Prieto-Vila, Wataru Usuba, Ryou-u Takahashi, et al.

Cancer Res Published OnlineFirst July 9, 2019.

Updated version Access the most recent version of this article at: doi:10.1158/0008-5472.CAN-19-0122

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