SET domain-containing protein 4 epigenetically controls ......2019/07/13 · 1 1 SET domain-containing protein 4 epigenetically controls breast cancer stem cell quiescence 2 3 Sen

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SET domain-containing protein 4 epigenetically controls breast cancer stem cell quiescence 1

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Sen Ye1, †, Yan-Fu Ding1, †, Wen-Huan Jia2, Xiao-Li Liu2, Jing-Yi Feng2, Qian Zhu2, Sun-Li Cai2, Yao-Shun 3

Yang2, Qian-Yun Lu2, Xue-Ting Huang2, Jin-Shu Yang2, Sheng-Nan Jia3, Guo-Ping Ding3, Yue-Hong 4

Wang4, Jiao-Jiao Zhou5, Yi-Ding Chen5, and Wei-Jun Yang1,2* 5

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1MOE Laboratory of Biosystem Homeostasis and Protection, College of Life Sciences, Zhejiang University, 7

Hangzhou 310058, China. 8

2Institute of Cell and Development Biology, College of Life Sciences, Zhejiang University, Hangzhou 9

310058, China. 10

3Department of General Surgery, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, 11

Hangzhou 310016, China. 12

4Department of Respiratory Medicine, The First Affiliated Hospital, College of Medicine, Zhejiang 13

University, Hangzhou 310003, China. 14

5Department of Surgical Oncology, The Second Affiliated Hospital, College of Medicine, Zhejiang 15

University, Hangzhou 310009, China. 16

†These authors contributed equally. *Correspondence: [email protected] 17

Note: Supplementary data for this article are available at Cancer Research online 18

Funding: This work was supported by the National Major Research and Development Project 19

(2016YFA0101201) and the National Natural Science Foundation of China (Project No. 31730084). 20

Corresponding Author: Prof. Wei-Jun Yang, Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, 21

Zhejiang Province, China. Tel./Fax: +86-571-88273176; E-mail: [email protected] 22

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Abstract 24

Quiescent CSCs play important roles in tumorigenesis, relapse and resistance to chemoradiotherapy. However, 25

the determinants of CSC quiescence and how they sustain themselves to generate tumors and relapse beyond 26

resistance to chemoradiotherapy, remains unclear. Here, we found that SET domain-containing protein 4 27

(SETD4) epigenetically controls breast CSC (BCSC) quiescence by facilitating heterochromatin formation 28

Research. on August 23, 2021. © 2019 American Association for Cancercancerres.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on July 15, 2019; DOI: 10.1158/0008-5472.CAN-19-1084

http://cancerres.aacrjournals.org/

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via H4K20me3 catalysis. H4K20me3 localized to the promoter regions and regulated the expression of a set 1

of genes in quiescent BCSCs (qBCSCs). SETD4-defined qBCSCs were resistant to chemoradiotherapy and 2

promoted tumor relapse in a mouse model. Upon activation, a SETD4-defined qBCSC sustained itself in a 3

quiescent state by asymmetric division, and concurrently producing an active daughter cell that proliferated 4

to produce a cancer cell population. Single-cell sequence analysis indicated that SETD4+ qBCSCs clustered 5

together as a distinct cell type within the heterogeneous BCSC population. SETD4-defined quiescent CSCs 6

were present in multiple cancer types including gastric, cervical, ovarian, liver, and lung cancers and were 7

resistant to chemotherapy. SETD4-defined qBCSCs had a high tumorigenesis potential and correlated with 8

malignancy and chemotherapy resistance in clinical breast cancer patients. Taken together, the results from 9

our previous study and current study on six cancer types reveal an evolutionarily conserved mechanism of 10

cellular quiescence epigenetically controlled by SETD4. Our findings provide insights into the mechanism of 11

tumorigenesis and relapse promoted by SETD4-defined quiescent CSCs and have broad implications for 12

clinical therapies. 13

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Significance: Findings advance our knowledge on the epigenetic determinants of quiescence in cancer stem 15

cell populations and pave the way for future pharmacologic developments aimed at targeting drug-resistant 16

quiescent stem cells. 17

18

Introduction 19

As a major global health problem, cancer is one of the leading causes of morbidity worldwide. Due to 20

the heterogeneity of tumor cells, the efficacy of chemoradiotherapy treatment is often suboptimal, as indicated 21

by the high death rate of cancer patients (1, 2). Current therapies are particularly limited by the emergence of 22

therapy-resistant cancer cells (3-5). Increasing evidence has revealed that a small fraction of cancer cells, 23

termed cancer stem cells (CSCs), are responsible for therapeutic resistance, where the quiescence in CSCs is 24

a crucial mechanism for resistance and survival (6-9). Standard therapies mainly target the tumor bulk, but 25

they fail to eradicate the resistant CSCs that may cause relapse in patients after clinical treatments are finished 26

(2, 7, 10). 27

Cellular quiescence is a reversible and nondividing state, the counterpart to proliferation (11). Previous 28




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studies identified that quiescent CSCs were more resistant to chemotherapy and could retain the capacity to 1

proliferate after chemotherapy withdrawal (12-14). Although several molecular players in the regulation of 2

cellular quiescence have been reported, we know remarkably little about the determinants of quiescence and 3

the mechanisms of the transition between active and quiescent states in CSCs (7, 10, 15). Epigenetic studies 4

have shown that heterochromatin is involved in maintaining the reversibility of cellular quiescence, in which 5

the methylation of histones contributes to heterochromatin formation (16, 17). Heterochromatin exists in two 6

varieties, constitutive heterochromatin (cHC) and facultative heterochromatin (fHC), that silence gene 7

expression by virtue of their highly condensed structure (18, 19). The two varieties are distinguished by their 8

distinct epigenetic signatures, fHC involving high levels of trimethylation of lysine 9 of histone 3 (H3K9me3) 9

and lysine 27 of histone 3 (H3K27me3), and cHC exhibiting high levels of trimethylation of lysine 20 of 10

histone 4 (H4K20me3). By contrast, euchromatin displays a high level of acetylation of lysine 9 of histone 3 11

(H3K9ac) (16, 18, 20, 21). 12

The family of SET domain-containing proteins (SETDs), histone lysine methyltransferases, have been 13

reported to play a role in the regulation of chromatin structure, gene expression by catalyzing the methylation 14

of histone proteins and cell proliferation in several cell lines (22-25). To study cellular quiescence regulation 15

in CSCs, we used Artemia, the brine shrimp, as a model system. This primitive crustacean undergoes cellular 16

quiescence for prolonged periods during embryonic diapause, a state of obligate dormancy to cope with 17

environmental stresses (26). Previously, we reported that SETD4 regulates cellular quiescence by catalyzing 18

H4K20me3 during Artemia diapause entry (27). 19

Here, we show that SETD4 facilitates heterochromatin formation via H4K20me3 catalysis in BCSCs that 20

are located at the certain promoter regions and that it regulates the expression of a set of genes in the quiescent 21

regulation of BCSCs. Indeed, the quiescent BCSCs play critical functions in resistance to chemoradiotherapy 22

and in relapse and correlate with malignancy in clinical patients. We demonstrate an evolutionarily conserved 23

mechanism of CSC quiescence and establish a new cellular narrative for tumorigenesis and relapse. 24

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Materials and Methods 26

Mice 27




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NOD/SCID female mice were purchased from the Shanghai Laboratory Animal Center (SLAC) of China. 1

They were housed under a 12-hr light/dark cycle (light between 06:00 and 18:00) in a temperature-controlled 2

room (22 ± 1℃) with free access to water and food. All mice were maintained with the approval of the Animal 3

Ethics Committee of the Zhejiang University and in accordance with the university's animal experiment 4

guidelines. 5

6

Cell Lines and Cell Culture 7

HEK293T, MKN45, MCF7, T47D and HCC1937 were purchased from the Tumor Cell Bank of Chinese 8

Academy of Sciences (Shanghai, China). All cells were obtained directly from cell bank and passaged in the 9

laboratory for fewer than 6 months after receipt. All cells were authenticated using short tandem repeat 10

profiling. Mycoplasma detection was performed using a Mycoplasma Detection Set (Takara) for all the cell 11

lines. They were cultured according to the vendor’s instructions at 37℃ in a humidified atmosphere with 5% 12

CO2. 13

14

Antibodies 15

H3K4me3 (Millipore; 2207275), H3K9me3 (Abcam; ab1773), H3K27me3 (Abcam; ab6174), 16

H3K36me3 (Abcam; ab9050), H3K79me3 (Abcam; ab2621), H4K20me1 (Santa Cruz Biotechnology; sc-17

134221), H4K20me2 (GeneTeX; GTX630545), H4K20me3 for WB (Cell Signaling Technology; 5737s), 18

H4K20me3 for IF (Abcam; ab9053), GAPDH (Cell Signaling Technology; 2118), H3K9ac (Abcam; ab10812), 19

HP1-α (Santa Cruz Biotechnology; sc-130446), SUV4-20h2 (Santa Cruz Biotechnology; sc-366867), H3 20

(Abcam; ab1791), H4 (Abcam;ab10158), H3S10ph (Cell Signaling Technology; 53348), RbS807/811ph (Cell 21

Signaling Technology; 9308s), Ki67 (Abcam; ab16667), SETD4-(R) (Sigma-Aldrich; HPA035405), SETD4 22

(Sigma-Aldrich; HPA024073), SETD4-(m) (Santa Cruz Biotechnology; sc-514060), CD44-FITC 23

(eBiosciences; 11-0441-81), CD44 (Cell Signaling Technology; 3570), CD24-PE (eBiosciences; 12-0242), 24

CD24 (eBiosciences; 14-0242-81), CD24-647 (Biolegend; 311110), CD133 (HuaAn-Biotec; EM1701-28), 25

Sox2 (Abcam; ab97959), Oct4 (Abcam; ab18976), Nanog (Abcam; ab109250), PCNA (Abcam; ab29), LC3B 26

(Sigma-Aldrich; L7543), Active-caspase3 (Abcam; ab32042) and H2AS139ph (γ-H2A) (Novus; NB100-384). 27

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Discrimination of BCSCs and qBCSCs 1

MCF7 or HCC1937 cells were digested by accutase (Thermo Fisher Scientific, A1110501) and solid 2

tumors from MCF7-CDXs, HCC1937-CDXs or clinical patients were cut up into small pieces and then 3

digested with ultra-pure collagenase III (Worthington; LS004180) in DMEM at 37°C for 3-4 hrs. Single cells 4

were filtered through a 45-mm nylon mesh and then resuspended in 100 µl (per 106 cells) HBSS containing 5

2% FBS for FACS. Antibodies of CD24 and CD44 were added and incubated for 20 mins on ice. Flow 6

cytometry was performed using a FACS Vantage (BD). Cells were routinely sorted twice and reanalyzed for 7

purity of 90%. The population of CD44high/CD24low was used as the BCSCs in this study. For PKH26 staining, 8

BCSCs were labeled with PKH26 (Sigma-Aldrich; PKH26GL-1KT) dye according to the manufacturer’s 9

instructions. The labeled cells were cultured under tumorsphere formation conditions for 2 weeks then the 10

tumorspheres were dissociated by accutase (Gibco; A1110501) and subjected to FACS. 11

12

Tumorsphere formation assay 13

Cells were plated at a density of 4000-8000 cells/well in the 6-well ultra-low-attachment plates and 14

cultured in tumorsphere formation conditions (DMEM/F12 (Corning; 10-092-cv) supplemented with 10% 15

serum replacement (SR; Thermo Fisher Scientific; 10828028), 20 ng/ml EGF, 5 ng/ml heparin sodium 16

(MedChemExpress; 9041-08-1), 20 ng/ml bFGF (PeproTech; 96-100-18B-500)) at 37℃ in a humidified 5% 17

CO2 incubator. 18

19

Activation of qBCSCs 20

FACS-sorted qBCSCs or chemoradio-resistance qBCSCs were cultured in tumorsphere formation 21

conditions (described above) plus 50 ng/ml exosomes that has been isolated form the cultured medium of 22

MCF7 and HCC1937 cell lines. The exosome-depleted FBS was used in the culture of the MCF7 and 23

HCC1937 cell lines. The total exosome was isolated from the cultured medium using Cell Medium Exosome 24

Isolation Kit (Life technology; 4478359) according to the manufacturer’s instructions and after 20 hrs of 25

culture, the time just before one cell begins dividing into two. These cells were used as the A-qBCSCs in this 26

study. 27

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Tumorigenesis in Mice 1

For mammary fat pad orthotopic xenograft experiments, 6-8 weeks of age (at the time of injections) 2

female NOD/SCID mice were used. Cells were resuspended in HBSS/Matrigel (Corning) and injected into 3

the lower right and left mammary pads of each mouse. Animals were euthanized when the tumors were 4

approximately 0.5-1.2 cm in the largest diameter, to avoid tumor necrosis. The tumor width (w) and length (l) 5

was recorded with a caliper and tumor size was calculated using the formula (l × w2/2). 6

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Immunofluorescence and H&E Staining 8

Section samples were fixed with 4% paraformaldehyde and embedded in OCT (Sakura; 4583). Cell 9

samples were fixed with 4% paraformaldehyde. The samples were incubated with the appropriate antibodies. 10

Tumor tissue sections were stained with hematoxylin and eosin (H&E) (Beyotime, c0105) according to the 11

manufacturer’s instructions. Briefly, samples were stained in hematoxylin staining solution for 10 minutes and 12

stained in eosin staining solution for 1 minute then dehydrated and sealed with a neutral gum and detected on 13

the microscope. 14

15

Western blot and qRT-qPCR 16

Total proteins were extracted by RIPA lysis buffer (Beyotime, P0013B) containing protease inhibitor 17

cocktail (MedChemExpress; HY-K0010) Each protein sample (25 μg) was subjected to SDS-PAGE and then 18

transferred to a nitrocellulose membrane for Western blot analysis using bio-rad system, according to the 19

manufacturer’s instructions. 20

qRT-PCR reactions were performed on the Bio-Rad MiniOpticonTM system using SYBR Premix Ex. 21

TaqTM (TaKaRa Bio; RR420A). Gene-specific primers were used (Supplementary Table S1). The relative 22

amounts of mRNAs were analyzed using the comparative CT method, as described previously (28). 23

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Overexpression and RNAi of SETD4 25

Based on the sequence of the human SETD4 gene (NM_017438.4) in GenBank, the pLent-EF1a-SETD4 26

-P2A-GFP-CMV-Puro overexpression plasmid (Vigene biosciences; LT88002) was synthesized and 27

transfected with a viral packaging plasmid of 10 μg of plasmid containing the vector of SETD4, 10 μg of 28




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pMD2.G (Addgene; 12259) and 15 μg of psPAX2 (Addgene; 12260) by Lipo 3000 (Invitrogen; L3000015) 1

into HEK293T cells overnight, and the viral supernatant was collected 48 hours later. The viral supernatant 2

was filtered through a 0.45 μm filter, and the freshly sorted BCSCs were used for infection in the presence of 3

5 μg/ml Polybrene (Sigma-Aldrich; 107689-10G). RNAi was performed to knockdown the over-expressed 4

SETD4 gene at post-transfection day 3, and images were obtained after further incubation with Scramble or 5

SETD4 siRNA (Santa Cruz Biotechnology; sc-91446) for 4 days, respectively. The SETD4 and control siRNA 6

(100 pM per 10000 cells) were transfected into over-expressed SETD4 BCSCs using the siRNA transfection 7

system (Santa Cruz Biotechnology; sc-45064), according to the manufacturer’s instructions. 8

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EdU incorporation assay 10

SETD4+ qBCSCs asymmetric division was determined by the incorporation of EdU (Ribobio; C00054). 11

The SETD4+ qBCSCs (n=20) were incubated in tumorsphere formation medium containing 50 μM EdU for 12

40 and 60 hrs. All samples were fixed with 4% paraformaldehyde for immunofluorescence analysis of SETD4 13

or Ki67 by detect with second antibody conjugated with Alexa Fluor 594, and EdU were incubated with Alexa 14

488-conjugated Apollo® staining reaction solution (Ribobio; C10310-3) for 30 mins. 15

16

In vitro Histone Methylation Transferase (HMT) assay 17

Construction of GST-SETD4 and SETD4 mutants: The open reading frame of GST-SETD4 and four GST-18

SETD4 mutants were cloned using specific primers (Supplementary Table S1).The in vitro HMT reactions 19

were modified versions of protocols described previously (29) and were performed in 50 μl of methylase 20

activity buffer containing 10 μg of core histones as substrates, 10 mM AdoMet (Sangon; A6555-5g) as a 21

methyl donor, and GST, GST-SETD4, dose enhanced GST-SETD4 and four mutant types of SETD4 as 22

catalyzers. After incubation for 60 min at 30℃, the reaction products were examined by Western blotting or 23

Mass spectrometry analyses. 24

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TEM analysis 26

Samples were fixed with 2.5% glutaraldehyde overnight and dehydrated with ethanol, then infiltrated 27

with the mixture of absolute acetone and Spurr resin at room temperature. After infiltration, samples were 28




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sectioned in ultratome (Leica EM UC7) and then observed using a transmission electron microscope (JEM-1

1230, JEOL Inc, Japan) at 80 kV. Images of the cells were captured using a digital camera. 2

3

Chemical drug and radiation treatments 4

Cells were seeded into ultra-low attachment 6-well plates at a density of 8000 cells per well. The cells 5

were incubated with 100 nM Taxol (Sangon; A601183-0100) and 1 mM 5-FU (Sangon; A100597-0001) for 6

10 days and/or exposed to X-ray with 30 Gy and cultured for the further 4 days. The medium was changed 7

every 2 days. After treatments, trypan blue (Beyotime; C0011) analysis was performed according to the 8

manufacturer’s instructions. The surviving cells were harvested using a dead cell removal kit (Miltenyibiotec; 9

130-090-101). 10

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Single-cell RNA sequencing 12

Cellular suspensions were loaded on a Single-cell Instrument (10x Genomics, Pleasanton, CA) to 13

generate single cell GEMs. Sequencing libraries were loaded on an Illumina Hiseq PE150 a 150 bp paired-14

end module. The Cell Ranger Single Cell Software Suite 1.3 was used to perform sample demultiplexing, 15

barcode processing and UMI counting. All barcodes the total UMI counts of which exceed m/10, are 16

considered as cells. For visualizing data in 2-d space, Cell Ranger passes the PCA-reduced data into t-SNE (t-17

Stochastic Neighbor Embedding). The graph-based clustering algorithm consists of building a sparse nearest-18

neighbor graph, followed by Louvain Modularity Optimization (30). The value of k, the number of nearest 19

neighbors, is set to scale logarithmically with the number of cells. 20

21

Bulk-cell RNA sequencing 22

The RNAs of bulk cells were extracted using TRIzol, reverse-transcribed and included in the cDNA 23

library. The library of bulk cells was sequenced on an Illumina Hiseq X Ten platform with a 150 bp paired-24

end module. Cuffdiff (v2.2.1) was used to calculate FPKMs for the coding genes of each sample. Genes with 25

corrected p values less than 0.05 and the absolute value of |log2 (fold change)| >2 were assigned as 26

significantly differentially expressed. The significantly differentially expressed genes which were selected 27

(also reported in the previous literature related to stem cell quiescence regulations) and showed in the heatmap. 28




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GO enrichment analysis of differentially expressed genes was implemented with Perl module 1

(GO::TermFinder). R functions (q value) were used to test for statistical enrichment of differentially expressed 2

genes among the KEGG pathways. Gene Set Enrichment Analysis (GSEA) was performed according to the 3

instructions provided on the GSEA website (http://software.broadinstitute.org/gsea/). 4

5

Chromatin Immunoprecipitation sequencing (ChIP-Seq) 6

Chromatin immuno-precipitation sequencing (ChIP-seq) was performed using Anti-H4K20me3 7

according to the manufacturer’s instructions of Millipore EZ ChIP kit (Millipore; 17-371). The DNA were 8

constructed for the library and sequenced on an Illumina Hiseq 2500 platform. Peaks were called for aligned 9

reads using MACS2. Differentiated enriched peaks were analyzed using differential peaks and notated using 10

notate peaks.pl in the homer software. Heat maps were created to present the differentiated enriched peaks, 11

according to the peak enrichment value. Illustrative read coverage graphs of H4K20me3 patterns across 12

candidate genes were analyzed by the Integrative Genomics Viewer. 13

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Assay for Transposase-Accessible Chromatin with high throughput sequencing (ATAC-seq) 15

ATAC-seq was performed as previously reported (31). Briefly, nuclei were extracted from BCSCsSETD4 16

and BCSCsGFP, and the nuclei pellet was resuspended in the Tn5 transposase reaction mix. The transposition 17

reaction was incubated at 37°C for 30 min. Libraries were purified using AMPure beads and then sequenced 18

on an Illumina Hiseq X ten platform. The data analysis methods were described in the ChIP-seq sections above. 19

20

Quantification and statistical analysis 21

For quantification, at least three experiments were analyzed using ImageJ software. All statistical 22

analyses of the data were performed using means ± SD. For statistical comparison, we performed a one-tailed 23

Student’s t-test. The value of p < 0.05 was considered significant (p >0.05 considered not significant (NS)) 24

and the exact p value is stated in the figures. 25

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Data availability 27

All deep sequencing data that support the findings of this study have been deposited in the Gene 28



http://software.broadinstitute.org/gsea/


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Expression Omnibus (GEO). The accession number for the RNA-seq data of BCSCs, qBCSCs and A-qBCSCs 1

is GSE123810. The RNA-seq data of BCSCsSETD4 and BCSCsGFP have been deposited under the accession 2

code GSE123842. The single cell RNA-seq data of BCSCs from solid tumors taken from mice and BCSCs 3

from MCF7 cell lines are available under accession codes GSE124888 and GSE124887, respectively. ChIP-4

seq data have been deposited under accession code GSE123842. ATAC-seq data are available under accession 5

codes GSE131586. 6

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Results 8

Identification and Characterization of Quiescent BCSCs 9

Based on previous studies (32, 33), we obtained BCSCs by isolating a population of CD44high/CD24low 10

cells using FACS from luminal type (MCF7) and basal type (HCC1937) human breast cancer cell lines (left 11

FACS plots in Fig. 1A), which expressed high levels of pluripotency markers, such as ALDH-1, Sox2, Oct4, 12

Nanog and displayed abilities of tumorsphere formation and tumorigenesis in NOD/SCID mice 13

(Supplementary Fig. S1A-D). PKH26 has been used for marking non-dividing or quiescent cells in previous 14

reports (10, 12, 14) and in the current study. A few cells with PKH26 label retention (PKH26+) were identified 15

in the BCSC formed tumorspheres (Fig. 1A), indicating that they were in a nondividing or quiescent state and 16

named as qBCSCs. The PKH26+ qBCSCs isolated from the tumorspheres (middle FACS plots in Fig. 1A) 17

could be activated in a tumorsphere formation medium, named as Activated qBCSCs (A-qBCSCs) and it was 18

these that subsequently formed the tumorspheres (Fig. 1A). However, we did not observe tumorsphere 19

formation or tumorigenesis in the PKH26- population dissociated from the tumorspheres. We found that both 20

the FACS-sorted qBCSCs and the qBCSCs in tumorspheres had very low expression levels of the proliferation 21

markers Ki67 and PCNA (Fig. 1B-D), and very low phosphorylation levels of H3S10 (H3S10ph) and 22

RbS807/S811 (RbS807/S811ph), in contrast to BCSCs and A-qBCSCs (Fig. 1E). Furthermore, FACS-sorted 23

qBCSCs, BCSCs and A-qBCSCs all exhibited CD44high/CD24low, ALDH-1high and similar levels of the 24

pluripotency markers (Supplementary Fig. S1E-S1G). Importantly, A-qBCSCs were more capable of 25

tumorsphere formation and tumorigenesis than BCSCs (Fig. 1F and 1G). However, no tumor formation was 26

observed following injection of the same numbers of qBCSCs from the tumorspheres. In this study, we found 27

that qBCSCs could be activated under conditions of tumorsphere formation medium and the addition of 28




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exosomes from the culture medium of MCF7 and HCC1937 accelerated the activation of qBCSCs, especially 1

for tumorigenesis of A-qBCSCs in mice. These results indicate that PKH26+ cells in tumorspheres are qBCSCs, 2

and have a high tumorigenesis potential upon activation. 3

4

Molecular signatures and specific expression of SETD4 in qBCSCs 5

To characterize the molecular signatures of qBCSCs, RNA sequencing of BCSCs, qBCSCs and A-6

qBCSCs from the MCF7 cell lines were performed. The differentially expressed genes in qBCSCs are showed 7

in the heat map (Fig. 2A and Supplementary Fig. S2A). GSEA showed downregulated expression of genes 8

involved in cell activation, proliferation, and signaling pathways of Wnt, TGFβ, Notch, and JAK-STAT3, and 9

upregulated expression of genes in BMP, p53, BMI1, hedgehog, Brac1, and HES1 in qBCSCs pathways, as 10

compared with A-qBCSCs (Fig. 2B and Supplementary Fig. S2B). This pattern has previously been reported 11

as a signature of quiescent stem cells (7, 8, 34-40). The differential expression of related genes in qBCSCs 12

was also validated by qRT-PCR (Supplementary Fig. S2C). Gene Ontology (GO) analysis showed that the 13

expression of specific genes up- or downregulated in qBCSCs were significantly enriched for GO terms linked 14

to the regulation of chromatin stability, proliferation, differentiation, metabolism and related signaling 15

pathways (Supplementary Fig. S2D). 16

In our previous report, we found that SETD4 was expressed abundantly in the quiescent cells of Artemia 17

diapause embryos (27). Similarly, we also found high expression levels of SETD4 in qBCSCs (PKH26+) as 18

compared with PKH26- cells in tumorspheres (Fig. 2C). To further confirm the specificity of SETD4 19

expression in qBCSCs, we analyzed SETD4 expression in various cells, including FACS-sorted BCSCs, 20

qBCSCs, A-qBCSCs and four cancer cell lines (T47D, MKN45, MCF7, HCC1937). The results showed that 21

SETD4 was abundantly expressed only in qBCSCs, while its expression was very low in BCSCs and A-22

qBCSCs (Fig. 2D and 2E) and remained undetected in any of the four cancer cell lines or in the arrest state as 23

triggered by starvation treatment (Supplementary Fig. S3A). 24

Since SETD4 was detected at a high level in qBCSCs, but at a low level in BCSCs, and to explore the 25

function of SETD4 in the regulation of BCSC quiescence, GFP-fused SETD4 (GFP-SETD4) was 26

overexpressed in BCSCs (BCSCsSETD4) (Supplementary Fig. 3B). We found that the capability of tumorsphere 27

formation and the expression levels of Ki67, H3S10ph, and RbS807/S811ph in BCSCs were all inhibited by 28




12

the overexpression of GFP-SETD4, but not inhibited in BCSCs that were overexpressing GFP (BCSCsGFP) 1

(Fig. 2F and 2G, Supplementary Fig. S3C). To validate the function of over-expressed SETD4 in the regulation 2

of BCSC quiescence, RNAi was performed to knock down the over-expressed SETD4 gene. The BCSCsSETD4 3

treated with scramble siRNA were maintained in a quiescent state and could not divide to form tumorspheres. 4

In contrast, those treated with siRNA of SETD4 produced tumorspheres in a similar manner to BCSCsGFP (Fig. 5

2H). Additionally, we found very low levels of H3S10ph and RbS807/S811ph and distinct lack of any Ki67 6

signal in BCSCsSETD4 in contrast to the BCSCsGFP (Supplementary Fig. S3D and S3E). These results indicate 7

that SETD4 is required for maintenance of BCSCs quiescence. 8

9

SETD4 catalyzed H4K20me3 in heterochromatin formation in qBCSCs 10

We previously established that SETD4 catalyzes H4K20me3 during diapause formation and regulates 11

cell quiescence in Artemia (27). Here, we found a specific enrichment of H4K20me3 in qBCSCs (PKH26+) 12

in tumorsphere and in FACS-sorted qBCSCs, but not in BCSCs or A-qBCSCs (Fig. 3A-C). An in vitro HMT 13

assay showed that the level of H4K20me3 was enhanced upon the supplementation of GST-SETD4 14

(Supplementary Fig. S4A-C). We repeated the assay using four SETD4 mutations, none of the four mutants 15

of SETD4 showed any methyltransferase activity on H4K20me3 (Supplementary Fig. S4D). Moreover, we 16

observed that H4K20me3 was increased in BCSCsSETD4 but not in BCSCsGFP (Fig. 3D and Supplementary Fig. 17

S4E), and this effect was eliminated by knockdown of the overexpressed GFP-SETD4 (Fig. 3E and 18

Supplementary Fig. S4F). Likewise, SETD4 overexpression also induced the increase of H4K20me3 in MCF-19

7 and HCC1937 cell lines (Supplementary Fig. S4G). These results indicate that SETD4 functions in the 20

specific catalysis of H4K20me3 in the qBCSCs. 21

Analysis of TEM revealed a striking increase of condensed heterochromatin in the nuclei of qBCSCs 22

(Fig. 3F) and BCSCsSETD4 (Fig. 3G), in contrast to that in BCSCs, A-qBCSCs and BCSCsGFP. In addition, we 23

observed increased H4K20me3 (a marker for cHC) and low levels of H3K9ac (a marker for euchromatin) in 24

qBCSCs (Fig. 3C and Supplementary Fig. S5A) and BCSCsSETD4 (Supplementary Fig. S5B-D), in contrast to 25

those in BCSCs, A-qBCSCs and BCSCsGFP. Here, we found that HP1-α, which plays an essential role in 26

heterochromatin formation (41), was also enriched in qBCSCs and BCSCsSETD4 (Fig. 3C and Supplementary 27

Fig. S5A, S5B, S5E). However, we did not observe any significant differences in levels of the fHC markers 28




13

of H3K9me3 and H3K27me3 between BCSCs, qBCSCs and A-qBCSCs or between BCSCsSETD4 and 1

BCSCsGFP (Supplementary Fig. S5A, S5B and S5F-I). These results indicate that qBCSCs and BCSCsSETD4 2

contain more cHC and less euchromatin than BCSCs, A-qBCSCs and BCSCsGFP. Thus, we conclude that 3

SETD4 controls BCSCs quiescence by cHC formation via H4K20me3 catalysis. 4

5

H4K20me3 enhanced by SETD4 is located at certain promoter regions and regulates the expression of 6

a set of genes in the quiescent BCSCs. 7

In epigenetic regulation, local gene expression is influenced through modifications of chromatin that 8

recruit transcription factors that can either activate or repress gene transcription (42). To explore epigenetic 9

regulation by H4K20me3 in BCSCs quiescence, we performed ChIP-seq in BCSCsSETD4 and BCSCsGFP from 10

the MCF7 cell line. We found that, in BCSCsSETD4, H4K20me3 was distributed on all 23 chromosomes 11

(Supplementary Fig. S6A). Interestingly, quiescent BCSCsSETD4 showed marked enrichment of H4K20me3 12

modifications relative to BCSCsGFP, a result compatible with widespread repression of gene expression. The 13

overall pattern of H4K20me3 modifications for the unique signature genes of BCSCsSETD4 (versus BCSCsGFP) 14

is shown as a heat map (Supplementary Fig. S6B). 15

Illustrative read coverage graphs of H4K20me3 patterns across candidate genes showed that, in 16

BCSCsSETD4, H4K20me3 was typically enriched at the promoter regions and negatively correlated with the 17

expression of the genes of MYC, WNT1, EEF1A1, IGF1, SMAD4, but was decreased at the promoter region 18

and upregulated the expression of TP53 gene (Fig. 3H). In addition, ATAC-seq was performed. We found 19

lower open chromatin enriched peaks in BCSCsSETD4 than that in BCSCsGFP, in which BCSCsSETD4 showed 20

more widespread repressions of gene expressions relative to BCSCsGFP (Supplementary Fig. S6A and S6B). 21

Notably, we found week ATAC-seq signals at the MYC, WNT1, EEF1A1, IGF1 and SMAD4 promoters in 22

BCSCsSETD4, which likely explains their repressed gene expression status (Fig. 3I); however, the TP53 23

promoter exhibited stronger ATAC-seq signals in BCSCsSETD4 than BCSCsGFP, suggesting the upregulated 24

gene expression status of TP53 in BCSCsSETD4. The results of ATAC-seq indicated a lower chromatin 25

accessibility and widespread repression of gene expression in BCSCsSETD4, which were also consistent with 26

the results of our prior H4K20me3 ChIP-seq analysis (Fig. 3H). 27

We also compared the gene expression profiles of BCSCsSETD4 and BCSCsGFP using bulk RNA 28




14

sequencing analysis (Supplementary Fig. S6C). Consistent with our analysis of GO terms and qRT-PCR results, 1

KEGG pathway analysis revealed that genes correlated with cell activation and proliferation were 2

downregulated in BCSCsSETD4 (Supplementary Fig. S6D and S6E). Our data shows that SETD4-3

overexpressed BCSCs (BCSCsSETD4) is similar to qBCSCs in terms of its global gene expression pattern based 4

on the analysis of transcriptome (Fig. 2A, 2B and Supplementary Fig. S2A-S2D, Supplementary Fig. S6C-5

S6E). Thus, SETD4 promotes cHC formation in qBCSCs and epigenetically regulates the expression of a set 6

of genes by catalyzing the H4K20me3 located at the promoter regions. 7

8

SETD4 defined qBCSCs are resistant to chemoradiotherapy and cause tumor relapse. 9

To investigate BCSCs’ resistance to chemoradiotherapy, FACS-sorted BCSCs from MCF7 and HCC1937 10

cell lines were treated with drugs and radiation. Interestingly, a few cells (average 3.28% and 2.92% of MCF7-11

BCSCs, average 3.64% and 3.38% of HCC1937-BCSCs) were survived after the drug and radiation treatments, 12

respectively, as determined by trypan blue staining (Fig. 4A). Importantly, we found that all tested surviving 13

cells were SETD4 positive and Ki67 negative (Fig. 4A and 4B), indicating that these surviving BCSCs were 14

in quiescent state or SETD4 defined qBCSCs. Analysis of TEM revealed that they contained more condensed 15

heterochromatin (Fig. 4C). In addition, Western blot analysis revealed that these SETD4 defined qBCSCs had 16

also abundant H4K20me3, HP1-α and low amounts of H3K9ac, indicating that they contain more cHC and 17

less euchromatin than did the BCSCs before treatments (Supplementary Fig. S7A). To confirm the resistance 18

of SETD4 defined qBCSCs to chemoradiotherapy, we performed drug and radiation treatments on FACS-19

sorted BCSCs, qBCSCs and A-qBCSCs. As expected, FACS-sorted qBCSCs had high survival rates (55.56% 20

and 67.02%) after drug and radiation treatments compare to BCSCs (2.82% and 5.52%) and A-qBCSCs (0.42% 21

and 1.03%) (Fig. 4D). Moreover, overexpressed SETD4 enabled BCSCs to survive with resistance to both 22

treatments of chemical drugs and radiation, whereas BCSCsGFP were all sensitive to the treatments and 23

exhibited widespread cell death (Fig. 4E). However, BCSCsSETD4 treated with siRNA to SETD4 lost 24

chemoradiotherapy resistance and died, but BCSCsSETD4 treated with scrambled siRNA maintained their 25

quiescent state and retained resistance to the treatments (Supplementary Fig. S7B). These results indicated 26

that SETD4 defined qBCSCs were resistant to chemoradiotherapy. 27

To reveal the cellular response of SETD4 defined qBCSCs to chemoradiotherapy, we also analyzed the 28




15

activities of autophagy, apoptosis, and DNA damage after chemoradiotherapy. As shown in Supplementary 1

Fig. S7C-E, no signals were detected for LC3B, activated caspase3 and γ-H2AX in SETD4 defined qBCSCs, 2

while high levels were observed in BCSCs and A-qBCSCs after drug and radiation treatment. The results 3

indicate that SETD4 defined qBCSCs are resistant to chemoradiotherapy and display no evident cellular 4

damage beyond it, in contrast to BCSCs and A-qBCSCs. 5

We then investigated whether SETD4 defined qBCSCs were able to cause tumor relapse in MCF7 and 6

HCC1937 cell derived xenografts (CDXs) after development of resistance to chemotherapy. Tumors were 7

generated in NOD/SCID mice and had reached their minimum size after chemotherapeutic treatment. Tumors 8

had then relapsed after chemotherapy’s completion (Fig. 4F and 4G). Upon the completion of chemotherapy 9

treatment, high percentage of surviving tumor cells (34.82% in MCF7-CDXs and 32.75% in HCC1937-CDXs) 10

were SETD4+ in contrast to the situation of pre-chemotherapy treatment tumors (1.08% in MCF7-CDXs and 11

1.32% in HCC1937-CDXs) and the relapsed tumors 2 weeks beyond treatment (2.71% in MCF7-CDXs and 12

2.19% in HCC1937-CDXs) (Fig. 4H). Analysis of Western blot also showed significantly high expression 13

level of SETD4 in the solid tumors after chemotherapy (Fig. 4I). Using immunofluorescence analysis, we 14

found that SETD4+ cells in the tumors were CD44high/CD24low (Fig. 4J and Supplementary Fig. S8A), had a 15

low level of Ki67 expression (Fig. 4K and Supplementary Fig. S8B). These results suggest that SETD4 defined 16

qBCSCs in tumor are able to cause the relapse beyond resistance to chemoradiotherapy. In addition, the 17

chemotherapy-resistant SETD4+ qBCSCs in post-chemo treatment tumors had a high level of HP1α expression 18

and the enrichment of H4K30me3, but a low abundance of H3K9ac, indicating that they contained more cHC, 19

but less euchromatin than that in pre-chemo treatment tumor cells or relapsed tumor cells (Supplementary Fig. 20

S8C-E). 21

22

SETD4 Defined qBCSCs Sustain Themselves by Asymmetric Division 23

Interestingly, we found that these SETD4 defined qBCSCs could survive for more than 2 months in the 24

presence of chemical drugs, and sustained themselves and formed typical tumorspheres after the drugs were 25

removed in vitro (Fig. 5A). To address how SETD4 defined qBCSCs balances self-renewal during 26

tumorigenesis and relapse, two independent experiments were performed (Fig. 5B). In the first experiment, a 27

SETD4 defined qBCSC divided into two cells after approximately 40 hours activation. One cell was 28




16

SETD4+/EdU-/Ki67- and the other was SETD4-/EdU+/Ki67+, indicating that the SETD4+ qBCSC sustained 1

itself in a quiescent state with two original DNA strands by an asymmetric division, whilst producing a 2

daughter cell. The daughter cell subsequently divided symmetrically into two SETD4-/EdU+/Ki67+ cells under 3

conditions without EdU, indicating that the daughter cell contains two newly synthesized DNA strands. In the 4

second experiment, EdU was added only after the SETD4+ qBCSC had already divided into three cells. This 5

resulted in the generation of one SETD4+/EdU-/Ki67- cell and four SETD4-/EdU+/Ki67+ cells that could 6

proliferate to produce a population of cells, indicating that the SETD4+ qBCSC is always maintained in a 7

quiescent state during the proliferation process. We conclude that SETD4 defined qBCSCs are able to sustain 8

themselves by asymmetric division, and concurrently produce a daughter cell which then proliferates into a 9

population of cancer cells by symmetric divisions. 10

11

Identification of distinct clusters of SETD4 defined qBCSCs within the heterogeneous BCSCs 12

population 13

Recent advances in single-cell gene expression analysis offers an opportunity to greatly improve the 14

identification and classification of different cell types within a heterogeneous cell population (43, 44). We 15

performed single-cell profiling of 3765 BCSCs from tumors of MCF7 CDXs and identified clusters using t-16

SNE analysis. BCSCs were distributed in seven clearly delineated clusters, in which all clusters showed 17

characteristic CD44high/CD24low expression (Fig. 6A). Importantly, the BCSCs population contained 5.42% 18

SETD4+ qBCSCs (204 cells) in the BCSC population (3765 cells) that had partitioned into a cluster (cluster 19

7) as a distinct cell type with high cellular component homogeneity. In addition, sequence data from 3037 20

single BCSCs FACS-sorted from tumors of MCF7 CDXs showed that, after drug treatment, 93.45% of the 21

surviving BCSCs were in the defined cluster of SETD4+ qBCSCs, and 6.55% were SETD4- and spread into 22

other clusters of BCSCs (Fig. 6B). 23

Differential gene expression analysis identified molecular signatures for each cell type and provided a 24

comprehensive genetic module repertoire for the BCSCs population (Fig. 6C). Our t-SNE analysis showed 25

that in expression of related genes some become enhanced (such as HES1, TP53, and BMP2) and others 26

suppressed (such as MKI67, TGFBR3, and WNT10A) in the SETD4+ qBCSCs cluster (Fig. 6D). This matched 27

the expression known in quiescent cell types (7, 8, 34-40). We also identified new consensus markers, 28




17

including SETD4, ANGPTL4 (an inhibitor of tumor angiogenesis (45), and CA9 (a transmembrane protein of 1

carbonic anhydrase (46) (Fig. 6E). Similar results were also observed using t-SNE analysis of single-cell 2

sequences on 3575 BCSCs and 1175 drug resistant qBCSCs derived from the MCF-7 cell line (Supplementary 3

Fig. S9A-E). Taken together, our results show that SETD4 defined qBCSCs present as a small population 4

(approximately 5%) in BCSCs, representing a distinct cell type within heterogeneous BCSCs and play critical 5

functions in resistance to chemoradiotherapy and relapse. 6

7

SETD4 defined qBCSCs correlates with malignancy and chemotherapy resistance in clinic breast 8

cancer patients and are identified in multiple types of cancer 9

We next focused on the role of SETD4 defined qBCSCs in tumorigenesis, chemotherapy resistant and 10

relapse in clinical breast cancer patients. We obtained solid tumors that had been removed from breast cancer 11

patients, dissociated cancerous cells from them, and subjected these cells to treatment with chemotherapy 12

drugs and radiation. We found that all surviving cells were SETD4+, CD44high/CD24low and Ki67- (Fig. 7A), 13

suggesting that they were SETD4 defined qBCSCs. Furthermore, the high levels of H4K20me3 and HP1α and 14

low levels of H3K9ac indicated that these SETD4 defined qBCSCs carried higher contents of cHC and lower 15

contents of euchromatin (Supplementary Fig. S10A). Subsequently, these SETD4 defined qBCSCs could be 16

activated in tumorsphere formation medium for 20 hrs and then transplanted into NOD/SCID mice. 17

Interestingly, eight weeks after injection of only 10 of these cells, tumors had all occurred in all such 18

NOD/SCID mice (Fig. 7B). However, we did not observe tumorigenesis when the same numbers of BCSCs 19

from the same tumors of breast cancer patients were injected. This indicate that SETD4 defined qBCSCs have 20

roles as the originators of tumor and relapse. 21

Analysis of clinical samples showed that the ratio of SETD4 defined qBCSCs in solid tumors from the 22

advanced stage (stage III) patients were more than 3-fold higher than in tumors obtained from the early stage 23

(stages I and II) patients (Fig. 7C and Supplementary Fig. S10B). Moreover, the ratio of SETD4 defined 24

qBCSCs was more than 3-fold higher in solid tumors obtained from patients who had received chemotherapy 25

treatment than in tumors from patients who had not received treatment prior to surgery (Fig. 7D and 26

Supplementary Fig. S10C). These results suggest that the presence of SETD4 defined qBCSCs may correlate 27

with malignancy and chemotherapy resistance in clinical breast cancer patients. We next assessed whether 28




18

SETD4 defined quiescent CSCs were present in other types of cancer. We obtained solid tumors that had been 1

removed from patients with gastric, cervical, ovarian, liver, and lung cancers (Supplementary Fig. S10D), 2

disaggregated the cells, and subjected them to the chemical drug treatments. We found that all chemotherapy 3

resistant cells tested from each of the five solid tumors were SETD4+, Ki67- and high levels of the cancer stem 4

cell marker (Fig. 7E), indicating that SETD4 defined quiescent CSCs were also present in all examined cancer 5

types. Our results are summarized in Fig. 7F. 6

7

Discussion 8

Taken together, the results from our previous study on diapause cysts of Artemia (27) and our current 9

work on six types of cancer reveal an evolutionarily conserved mechanism of cellular quiescence 10

epigenetically controlled by SETD4. Although Suv4-20h2 has previously been reported as responsible for 11

catalyzing H4K20me3 in mouse and human fibroblasts (47, 48), we did not observe any significant differences 12

in Suv4-20h2 expression in response to H4K20me3 enrichment in qBCSCs (Supplementary Fig. S11A). We 13

also did not observe SETD4 expression in response to the increase in H4K20me3 in the quiescence of mouse 14

embryonic fibroblasts induced by contact-inhibition, in which Suv4-20h2 catalyzes H4K20me3 15

(Supplementary Fig. S11B). It seems that both Suv4-20h2 and SETD4 are able to catalyze H4K20me3, but 16

they function in different types of cell. Although, SETD4 has been studied in the regulation of gene expression 17

and cell proliferation in several cell lines (24, 49). We propose that SETD4 is a determinant of quiescence 18

specifically in CSCs, but not in cancer cells. Thus, SETD4 can be applied to define quiescent CSCs occurring 19

within the large heterogeneity of tumor cells and even, more specifically within the wider CSCs population. 20

In this study, we did not find any tumor occurrence by injection of qBCSCs during the period of six 21

months. Our results indicate that the activation of qBCSCs is required for the tumor occurrence. Based on 22

evidence of a strong correlation between SETD4 defined qBCSCs and malignancy and chemoresistance in 23

breast cancer patients, it may be possible to use the SETD4 and/or SETD4 defined qBCSCs as important 24

indicators for assessing the grade of malignancy and likelihood of tumor recurrence in a clinical setting. In the 25

current study, we found that the ability of chemoradiotherapy resistance disappeared completely after SETD4 26

defined qBCSCs were activated, and therefore activating BCSCs may enable their eradication by subsequent 27

treatments with standard chemoradiotherapy. Our findings suggest that SETD4 and/or SETD4 defined qCSCs 28




19

could be also used as key targets in clinical treatment for a wide range of cancers. 1

2

Disclosure of Potential Conflicts of Interest 3

No potential conflicts of interest were disclosed. 4

5

Acknowledgments 6

We thank S. Zhang for the help with the laser microscopy, X. Song for flow cytometry analysis, J. Li for 7

transmission electron microscopy, Y. Xu for mass spectrometer analysis and X. Xu for mouse husbandry 8

support. We would like to express our sincere gratitude to Mr. C. Wood for critical reading of the manuscript. 9

10

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24

Figure 1.

Identification and Isolation of BCSCs, qBCSCs and A-qBCSCs from MCF7 and HCC1937 cell lines. A,

Discrimination of BCSCs, PKH26 labeling of qBCSCs and activation of the qBCSCs. Red: PKH26 retained

cells. Scale bar: 50 μm. B-C, Immunofluorescent analysis of Ki67 (B) and PCNA (C) in BCSCs, qBCSCs and

A-qBCSCs, n=3. Scale bar: 10 μm. D, Fluorescence microscopy of tumorsphere with PKH26 retention,

immunostained for PCNA and Ki67, n=10. Scale bar: 20 μm. E, Western blot analysis of H3S10ph and

RbS807/S811ph in BCSCs, qBCSCs, and A-qBCSCs. n=3. F, Tumorsphere formation assay of BCSCs and A-

qBCSCs. n=3, Scale bar: 100 μm. G, Tumorigenesis rates of BCSCs, qBCSCs and A-qBCSCs from MCF7

cell line in NOD/SCID mice.

Figure 2.

Molecular signatures of qBCSCs and specific expression of SETD4 in qBCSCs. A, Heat map of

differentially expressed genes in qBCSCs. The color bar represents the log10(FPKM+1). n=3. B, GSEA of

qBCSCs compared with A-qBCSCs. The green line shows the enrichment profile. C and D,

Immunofluorescent analysis of SETD4 in tumorsphere cells with PKH26 retention (C) and in FACS sorted

BCSCs, qBCSCs, and A-qBCSCs (D). n=3. Scale bar: 10 μm. E, SETD4 levels in BCSCs, qBCSCs, and A-

qBCSCs, as determined by Western blot analysis. n=3. F, Representative images and rates of tumorspheres

formed by BCSCsSETD4 and BCSCsGFP, n=3. Scale bar: 100 μm. G, Immunofluorescent analysis of Ki67 in

BCSCsGFP and BCSCsSETD4. n=3. Scale bar: 20 μm. H, Representative images and rates of tumorspheres

formed by siRNAs (Si Scramble or Si SETD4) treated BCSCsSETD4 and BCSCsGFP. Scale bar: 100 μm. n=3.

Figure 3.

SETD4 catalyzed H4K20me3 in heterochromatin formation and epigenetic regulation in qBCSCs. A,

Fluorescence microscopy and levels of immunostained for H4K20me3 in the tumorsphere. n=10. Scale bar:

10 μm. B, Levels of H4K20me3 (indicated by a box) and other methylation of histones in BCSCs, qBCSCs,

and A-qBCSCs, as determined by Western blot analysis. n=3. C, Fluorescence microscopy and levels of

BCSCs, qBCSCs and A-qBCSCs immunostained for H4K20me3, H3K9ac and HP1-α. n=3. Scale bar: 10 μm.

D and E, Levels of H4K20me3 (indicated by a box) in BCSCsGFP and BCSCsSETD4 (D) and in siRNAs (Si

Scramble and Si SETD4) treated BCSCsSETD4 and BCSCsGFP (E) as determined by Western blot analysis. n=3.

F and G, TEM images of condensed heterochromatin and percentages of heterochromatin in the nuclei of

BCSCs, qBCSCs, and A-qBCSCs (F), and in BCSCsSETD4 and BCSCsGFP (G). n=10. Scale bar: 2 μm. H and

I, Representative gene read coverage graphs of enriched H4K20me3 distribution by ChIP-seq (H) and the

chromatin accessibility around the candidate gene by ATAC-seq (I). Dashed boxes indicate the promoter

regions of the genes.

Figure 4.

SETD4 defined qBCSCs are resistant to chemoradiotherapy and cause tumor relapse. A, Representative

images of BCSCs after treatments with drugs or radiation. Blue cells stained by trypan blue were died cells.

Red arrows indicate surviving cells. Immunofluorescence analysis of SETD4 and Ki67 in the surviving

BCSCs. Scale bar: 20μm. n=3. B, Western Blot analysis of SETD4 and Ki67 in BCSCs before treatment (pre-

treatment), surviving BCSCs after drug and radiation treatments. n=3. C, Representative TEM images and

levels of heterochromatin in the nuclei of BCSCs before treatment (pre-treatment), surviving cells after drug

and radiation treatments. scale bar: 2 μm. n=10. D and E, Representative images and survival rates of BCSCs,

qBCSCs, and A-qBCSCs (D), BCSCsSETD4 and BCSCsGFP (E) after treatments with drugs or radiation. Scale

bar: 20μm. n=3. F, Chemotherapy and tumor relapse of MCF7 CDXs and HCC1937 CDXs. Representative

tumor size of pre-chemo, post-chemo and relapse in NOD/SCID mice. Scale bar: 0.5 cm. n=3. G, HE staining




25

of pre-chemo, post-chemo and relapse tumors. n=3. Scale bar: 50 μm. H and I, Immunofluorescent analysis

(H) and Western blot analysis (I) of SETD4 in pre-chemo, post-chemo and relapsed tumors. n=3. Scale bar:

50 μm. J and K, Levels of CD44 and CD24 (J), and Ki67 (K) in pre-chemo, post-chemo and relapsed tumors.

n=3. Scale bar: 50 μm.

Figure 5.

SETD4 defined qBCSCs sustain themselves by asymmetric division upon activation. A, Tumorsphere

formation of chemotherapy-resistant SETD4 defined qBCSCs after withdraw chemical drugs treatment during

two months. n=10. Scale bar: 50 μm. B, Asymmetric division of SETD4 defined qBCSCs. Fluorescence

microscopy and levels of SETD4 defined qBCSC during proliferation, immunostained for EdU, SETD4 and

Ki67. Arrows indicate sustained quiescent BCSCs (EdU-/SETD4+/Ki67-). n=20. Scale bar: 10 μm.

Figure 6.

Identification of distinct clusters of SETD4 defined qBCSCs within BCSCs population from MCF7

CDXs. A, t-SNE maps of BCSCs FACS-sorted from MCF7 CDXs colored by cluster assignment. The SETD4+

qBCSCs cluster (blue) is outlined. t-SNE maps of BCSCs with cell color based on the expression of CD44

and CD24. Gene expression levels (log2 mean UMI) are indicated by shades of red. B, Classification of

surviving BCSCs in BCSCs population after drug treatment were showed in the t-SNE maps. C, Heat map of

differential gene expression for each cell cluster. Color bar represents the log2 fold change. D and E, t-SNE

maps of BCSCs with cell color based on the expression of marker genes for quiescent cells (D) and newly

identified consensus marker genes (E) for SETD4 defined qBCSCs.

Figure 7.

SETD4 defined qBCSCs correlates with malignancy and chemotherapy resistance in clinic breast

cancer patients and identified in multiple types of cancer. A, Fluorescence microscopy and levels of

SETD4, Ki67, CD44 and CD24 in the surviving cells isolated from a solid tumor of breast cancer patient. n=3.

Scale bar: 10 μm. B, Ten of A-qBCSCs were used to generate tumors in NOD/SCID mice. C and D, Analysis

of SETD4 defined qBCSCs in tumors from different stage of breast cancer patients (C) and in tumors from

breast cancer patients who had or had not received chemotherapy (D). Each dot represents data of a patient.

n=8 patients. E, Fluorescence microscopy of SETD4 defined quiescent CSCs in multiple types of cancer. n=3.

Scale bar: 10 μm. F, Summary of this study.




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Published OnlineFirst July 15, 2019.Cancer Res Sen Ye, Yan-Fu Ding, Wen-Huan Jia, et al. breast cancer stem cell quiescenceSET domain-containing protein 4 epigenetically controls

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