SRC-3 Functions As a Coactivator of T-Bet by Regulating The

Author Manuscript Published OnlineFirst on June 19, 2020; DOI: 10.1158/2326-6066.CIR-20-0181 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

SRC-3 functions as a coactivator of T-bet by regulating the

maturation and antitumor activity of natural killer cells

Mengjia Hu1, Yukai Lu1, Yan Qi1, Zihao Zhang1, Song Wang1, Yang Xu1, Fang

Chen1, Yong Tang1, Shilei Chen1, Mo Chen1, Changhong Du1, Mingqiang Shen1,

Fengchao Wang1, Yongping Su1, Youcai Deng2, Junping Wang1.

1State Key Laboratory of Trauma, Burns and Combined Injury, Institute of Combined

Injury, Chongqing Engineering Research Center for Nanomedicine, College of

Preventive Medicine, Third Military Medical University, Chongqing 400038, China.

2Institute of Materia Medica, College of Pharmacy, Third Military Medical University,

Chongqing 400038, China.

Running title: SRC-3 regulates NK cell maturation and antitumor activity

Key Words: natural killer cell, SRC-3, T-bet, coactivator, tumor surveillance

Correspondence author: Dr. & Prof. Junping Wang, State Key Laboratory of

Trauma, Burns and Combined Injury, Institute of Combined Injury, College of

Preventive Medicine, Third Military Medical University, Gaotanyan Street 30

Chongqing 400038, China. Tel: +86-023-68771515; Fax: +86-023-68752009; Email:

[email protected]

Conflict of interest: The authors declare no potential conflicts of interest.

Financial support: This work was supported by grants from the National Natural

Science Foundation of China (No. 81725019, 81930090, 81573084, 81500087), and

the Scientific Research Project of PLA (AWS16J014).

Downloaded from cancerimmunolres.aacrjournals.org on September 24, 2021. © 2020 American Association for Cancer Research. Author Manuscript Published OnlineFirst on June 19, 2020; DOI: 10.1158/2326-6066.CIR-20-0181 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

Abstract word count: 191

Main text word count: 3198

Number of figures: 6

Number of supplementary files: 2

Abstract

Natural killer (NK) cell development and maturation is a well-organized process. The

steroid receptor coactivator 3 (SRC-3) is a regulator of the hematopoietic and immune

systems; however, its role in NK cells is poorly understood. Here, SRC-3 displayed

increased nuclear translocation in NK cells during terminal differentiation and upon

inflammatory cytokine stimulation. Targeted deletion of SRC-3 altered normal NK

cell distribution and compromised NK cell maturation. SRC-3 deficiency led to

significantly impaired NK cell functions, especially their antitumor activity. The

expression of several critical T-bet target genes, including Zeb2, Prdm1 and S1pr5,

but not T-bet itself, was markedly decreased in NK cells in the absence of SRC-3.

There was a physiological interaction between SRC-3 and T-bet proteins, where SRC-

3 was recruited by T-bet to regulate the transcription of the aforementioned genes.

Collectively, our findings unmask a previously unrecognized role of SRC-3 as a

coactivator of T-bet in NK cell biology and indicate that targeting SRC-3 may be a

promising strategy to increase the tumor surveillance function of NK cells.

Introduction

Natural killer (NK) cells, innate lymphocytes (ILCs) with cytotoxic functions, are

indispensable for early immunosurveillance of tumors and elimination of infected

cells (1,2). NK cells play an important role in the regulation of the adaptive immune

response by secreting cytokines (3). Unraveling the antitumor properties of NK cells

is crucial (4,5), thus a deep understanding of the mechanisms underlying NK cell

differentiation, maturation and function may advance the development of NK cell-

based immunotherapy.

NK cells are derived from hematopoietic stem cells (HSCs) (6). After

development in the bone marrow (BM), NK cells traffic to peripheral organs (7). The

commitment of NK cell specific differentiation is characterized by the gradual

acquisition of CD122, NK1.1 and DX5 expression (8). As NK cells fully mature,

CD27 expression gradually decreases and CD11b expression gradually increases (9).

NK cell development, maturation and function are controlled by a series of intrinsic

and extrinsic factors, but these mechanisms are not fully understood (10). T-box

transcription factor T-bet plays a critical role in this transcriptional regulatory network

(11,12) with many factors, such as Ets1, Foxo1, Tox2, Gata3 and mTOR, modulating

NK cell biology by at least partially affecting T-bet (13-17). However, little is known

about how T-bet regulates downstream transcription factors or effector molecules and

whether it needs interacting partners in NK cells.

Steroid receptor coactivator 3 (SRC-3), also called NCOA3/ACTR/AIB1/pCIP, is

a coactivator of nuclear receptors (18). Similar to other p160 family members, SRC-3

can be recruited by nuclear receptors to modulate the transcription of target genes (19).

SRC-3 can regulate the activity of several nonnuclear receptor proteins, including p53,

AP-1, and E2F1, indicating a nuclear receptor-independent function (18). SRC-3 has

attracted considerable attention due to its oncogenic property, whereas its

physiological function is largely overlooked (20). SRC-3 is involved in many

important physiological processes, such as somatic growth, hematopoiesis,

immunoregulation and energy metabolism (21-23).

In this study, we evaluated the role of SRC-3 in NK cells. Based on the

observations that SRC-3 displayed increased nuclear translocation during NK cell

terminal differentiation and upon inflammatory cytokine stimulation, we generated

mice with hematopoietic and NK-specific SRC-3 deletion. SRC-3 was required to

maintain the maturation and effector function of NK cells via modulation of several

critical T-bet-dependent genes. Collectively, our study provides new insight into the

regulatory mechanism of NK cell maturation and antitumor activity via SRC-3.

Materials and methods

Animals. Normal wild-type (WT) C57BL/6J mice were purchased from the Institute

of Zoology (Chinese Academy of Sciences, Beijing, China). SRC-3flox/+ (SRC-3fl/+)

mice were generated at the Shanghai Model Organisms Center (Shanghai, China).

Ncr1-Cre mice were obtained from Beijing Biocytogen Co, Ltd (Beijing, China) (24).

Vav1-Cre and T-bet-/- mice were purchased from The Jackson Laboratory (Bar Harbor,

ME, USA). SRC-3fl/fl/Ncr1-Cre (or Vav1-Cre) mice were generated by crossing SRC-

3fl/fl mice with Ncr1-Cre or Vav1-Cre mice. All mice used in the experiment are 6-8

weeks old. All animal experiments were approved by the Animal Care Committee of

The Third Military Medical University.

Cell culture. NK-92, Yac-1 and B16F10 cells were purchased from BeNa Culture

Collection (Beijing, China, December 2017). NK-92 cells were grown in complete

medium containing 75% DMEM Alpha (GIBCO, Carlsbad, CA, USA; supplemented

with 0.2 mM inositol, 0.1 mM 2-mercaptoethanol, 0.02 mM folic acid and 100-200

U/ml recombinant IL-2), 12.5% horse serum (GIBCO) and 12.5% fetal bovine serum

(FBS; GIBCO). Yac-1 cells and B16F10 cells were cultured in 90% RPMI

(HyClone, Logan, UT, USA) containing 10% FBS. All cell lines were passaged up to

10 times, authenticated by flow cytometry (last authentication, November 2019) and

tested for mycoplasma contamination using a MycoFluor™ Mycoplasma Detection

Kit (Invitrogen, Carlsbad, CA, USA; last test, November 2019).

Flow cytometry. Single-cell suspensions from the BM, spleen, peripheral lymph

nodes (pLNs), lungs and liver of mice were obtained as previously described (14,22).

The following flow cytometric antibodies were used: anti-CD3e (145-2C11, #100353,

100321, dilution 1:100), anti-Gr-1 (RB6-8C5, #108417, dilution 1:100), anti-Ter119

(TER-119, #116215, dilution 1:100), anti-B220 (RA3-6B2, #103225, dilution 1:100),

anti-CD19 (6D5, #115546, 115521, dilution 1:100), anti-NK1.1 (PK136, #108718,

108732, dilution 1:100), anti-Nkp46 (29A1.4, #137608, dilution 1:100), anti-CD146

(ME-9F1, #134704, dilution 1:100), and anti-CD107a (1D4B, #1216124, dilution

1:50) from Biolegend (San Diego, CA, USA); anti-c-Kit (2B8, #14-1171-82, dilution

1:100), anti-CD244 (eBio244F4, #25-2441-82, dilution 1:100), anti-CD127 (A7R34,

#45-1271-82, dilution 1:100), anti-CD135 (A2F10, #17-1351-82, dilution 1:50), anti-

CD122 (TM-beta1, #48-1222-82, dilution 1:100), anti-CD27 (LG.7F9, #12-0271-82,

dilution 1:100), anti-CD11b (M1/70, #11-0112-82, 45-0112-82, dilution 1:200), anti-

KLRG1 (2F1, #12-5893-8, dilution 1:100), anti-Granzyme B (NGZB, #12-8898-82,

dilution 1:50), anti-Perforin (eBioOMAK-D, #12-9392-82, dilution 1:50), anti-T-bet

(4B10, #12-5825-82, dilution 1:50), anti-Ki67 (SolA15, #25-5698-82, dilution 1:200),

anti-p-STAT3Tyr705 (LUVNKLA, #12-9033-42, dilution 1:50), anti-p-STAT5Tyr694

(SRBCZX, #12-9010-42, 1:50), and anti-p-STAT4Tyr693 (4LURPIE, #17-9044-42, 6

1:50) from eBioscience (San Diego, CA, USA); anti-CD43 (S7, #561857, dilution

1:200) and anti-IFN-γ (XMG1.2, #562019, dilution 1:300) from BD Bioscience (San

Diego, CA, USA); anti-S1P5 (#ab214464, dilution 1:50) from Abcam (Cambridge,

UK); anti-SRC-3 (F-2, #sc-5305 PE, dilution 1:50) and anti-Zeb2 (E-11, #sc-271984

PE, dilution 1:50) from Santa Cruz (Dallas, TX, USA); and anti-Blimp1 (C14A4,

#9115, dilution 1:50) from Cell Signaling Technology (Danvers, MA, USA).

Ki67, Granzyme B, Perforin, T-bet, Zeb2, Blimp1 and SRC-3 protein staining was

performed using a Foxp3/Transcription Factor Staining Buffer Set (#00-5523-00,

eBioscience) according to the manufacturer’s instructions. p-STAT3Tyr705, p-

STAT5Tyr694 and p-STAT4Tyr693 staining was performed using IC Fixation Buffer

(#00-8222-49, eBioscience) according to the manufacturer’s instructions. In vivo

BrdU incorporation was analyzed using a FITC-BrdU Flow kit (#559619, BD

Pharmingen, San Diego, CA, USA) according to the manufacturer’s instructions.

Cellular apoptosis was analyzed with an APC-Annexin V Apoptosis Detection Kit

with 7-AAD (#640930, Biolegend) according to the manufacturer’s instructions. IFN-

γ production after stimulation was analyzed using eBioscience™ Cell Stimulation

Cocktail (plus protein transport inhibitors, #00-4975-93) according to the

manufacturer’s instructions. CD107a expression in NK cells after stimulation with

Yac-1 cells was analyzed as we described previously (17).

Flow cytometric detection was conducted using a FACSverse cytometer (BD

Biosciences, San Jose, CA, USA), and all data were analyzed using FlowJo10.0

software (TreeStar, San Carlos, CA, USA). Fluorescence-activated cell sorting (FACS)

was performed using a FACSAriaIII sorter (BD Biosciences). The detailed gating

strategies are shown in Supplementary Fig. S1.

In vitro cytotoxicity assay. This assay was conducted as previously described (25). In

brief, spleens of SRC-3fl/fl or SRC-3NK∆/∆ mice were harvested and grinded gently in

RPMI medium (#SH30809.01, HyClone, Logan, UT, USA) using the even end of the

syringe, and a single-cell suspension was obtained following red blood cells lysis

using a Red Blood Cell Lysis Buffer (#20120, Stem Cell Technologies Inc., Grenoble,

France) and filtration through a 70-mm filter. Next, spleen cells were stained with NK

cell surface markers (CD3, CD19, NK1.1 and Nkp46) on ice for 20 min, and the

dilution of these antibodies has been described above. After washing in ice-cold

phosphate buffer saline (PBS), NK cells (CD3- CD19- NK1.1+ NKp46+) were sorted

by flow cytometry. The detailed gating strategies are shown in Supplementary Fig. S1.

Then, freshly sorted cells were cocultured with Yac-1 cells labeled with CFSE

(eBioscience) at 37°C at an effector:target (E:T) ratio of 1:1, 5:1 or 10:1. Six hours

later, the percentage of TOPRO3+ Yac-1 cells was assessed by flow cytometry.

In vivo labeling of sinusoidal lymphocytes. Mice were injected with 1 µg of PE-

conjugated anti-CD45 antibody (30F11, #103106, Biolegend, dilution 1:40) via the

tail vein (injection volume: 200 µl). Two minutes later, the mice were sacrificed. The

BM was collected and stained with NK cell markers, followed by flow cytometric

analysis (26,27).

In vivo tumor model. SRC-3fl/fl or SRC-3NK∆/∆ mice were injected with 2×105

B16F10 melanoma cells via the caudal vein (injection volume: 200 µl). Twelve days

later, the mice were sacrificed, and the tumor nodules in the lungs were counted under

a dissecting microscope.

Quantitative RT-PCR (qRT-PCR). Total RNA was extracted from FACS-sorted

cells using an RNAqueous kit (#AM1931, Ambion, Darmstadt, Germany) according

to the manufacturer’s instructions. RNA content was measured by NanoDrop 2000

(Thermo Scientific, Wilmington, MA, USA). Then, 1 µg of total RNA was used to

synthesize cDNA, and qRT-PCR was performed as previously reported (22). The

relative expression of each gene was normalized to Gapdh and determined by 2−ΔΔCt

methods. Each reaction was performed in triplicate. Primer sequences are provided in

Supplementary Table S1.

RNA-sequencing. NK cells were FACS-sorted from the spleen of SRC-3fl/fl and

SRC-3NK∆/∆ mice according to the above method, and total RNA was then extracted as

described above. Library construction and RNA sequencing were conducted at OE

Biotech. Co., Ltd. (Shanghai, China). Gene expression was normalized as fragments

per kilobase of exon per million fragments mapped (FPKM) values. The combined

criteria of a log2 (fold change) > 0.5 and an adjusted p-value < 0.05 were used to

identify differentially expressed genes. The raw RNA-Seq data were deposited in the

NCBI Sequence Read Archive (SRA) database (no.PRJNA588159).

Chromatin immunoprecipitation (ChIP). This assay was performed using an EZ-

ChIPTM kit (#17-371RF, Millipore, Billerica, USA), as previously described (28,29).

In brief, NK cells were freshly sorted from mouse spleen as described above. These

cells were fixed with 1% formaldehyde (Sigma, St. Louis, MO, USA) and were then

lysed in SDS lysis buffer containing 5 µl of protease inhibitors (included in the ChIP

kit as mentioned above). Subsequently, chromatin was sheared to 200-1000 bp by

sonication, and cross-linked protein/DNA was incubated with an SRC-3 (#ab2831,

Abcam, dilution 3 µg/106 cells) antibody or IgG control (#ab171870, Abcam, dilution

3 µg/106 cells) overnight at 4°C with rotation. The immunoprecipitated protein/DNA

complexes were eluted by elution buffer (included in the ChIP kit as mentioned above)

according to the manufacturer’s instructions and were reversed to free DNA by

incubating at 65°C for 5 hours. Finally, DNA was purified using spin columns and

detected by qRT-PCR as described above. Primer sequences are provided in

Supplementary Table S2.

Western blotting. Nuclear proteins were isolated using NE-PER™ Nuclear and

Cytoplasmic Extraction Reagents (#78835, Invitrogen) according to the

manufacturer’s instructions. Then, the nuclear or total protein expression was

measured by Western blot analysis as previously described (28). The following

antibodies were used: anti-SRC-3 (#ab2831, Abcam, dilution 1:1000), anti-T-bet

(#ab53174, Abcam, dilution 1:1000), anti-Lamin B1 (#ab16048, Abcam, dilution

1:5000) and anti-β-actin (#4970, Cell Signaling Technology, dilution 1:1000).

Co-immunoprecipitation (Co-IP). This experiment was performed using a

Dynabeads™ Protein G Immunoprecipitation Kit (#10007D, Invitrogen) following

the manufacturer’s instructions. Briefly, mouse primary NK cells (freshly sorted from

spleen as described above) or human NK-92 cells were first lysed. The binding of

magnetic beads to an SRC-3 antibody (#2126, Cell Signaling Technology, dilution

1:50) or T-bet antibody (#ab53174, Abcam, dilution 1:50) was carried out, and then

the magnetic bead-antibody complexes were added to the lysed samples.

Subsequently, samples were resuspended and incubated on a shaker (HY-450,

Huicheng Biological Technology Co. LTD, Wuhan, China) at the speed of 75 r/min

for 10 min at room temperature to allow the antigen to bind to the magnetic bead-

antibody complexes. After washing with washing buffer (included in the

immunoprecipitation kit as mentioned above), the target antigen was eluted by elution

buffer (included in the immunoprecipitation kit as mentioned above) according to the

manufacturer’s instructions and subjected to Western blot analysis as mentioned

above. To avoid interference from the heavy chain (55 kDa), a secondary antibody

against IgG light chain (IPKine™ HRP, Mouse Anti-Rabbit IgG LCS, #A25022,

Abbkine Inc., Redlands, CA USA) was used.

Immunofluorescence microscopy. NK cell subsets freshly sorted from murine

spleen were placed on poly-L-lysine coated slides. After fixation via 4%

paraformaldehyde for 15 min at room temperature, permeabilization and blocking,

cells were stained with an SRC-3 (#ab2831, Abcam, dilution 1:200) antibody. Then,

samples were incubated with a FITC-conjugated secondary antibody (#F-2765,

Invitrogen, dilution 1:200) and DAPI (Sigma) and were imaged using a Zeiss

LSM800 confocal microscope (Carl Zeiss, Jena, Germany).

Statistical analysis. Experimental data were analyzed using GraphPad Prism 6.0

software (La Jolla, CA, USA). Two-tailed Student’s t test and one-way analysis of

variance (ANOVA) were used to compare the differences between two groups and

multiple groups, respectively. Data are shown as mean ± standard deviation (SD). P <

0.05 was considered statistically significant.

Results

NK cells had increased SRC-3 nuclear translocation during maturation

We first observed that SRC-3 was expressed in NK cells in mouse spleens

(Supplementary Fig. S2A), consistent with the data from the BioGPS dataset

(Supplementary Fig. S2B). However, neither the mRNA nor the protein expression of

SRC-3 changed during NK cell terminal differentiation (Fig. 1A, B). We observed a 11

gradual increase in nuclear SRC-3 expression in NK cells during the CD27+ CD11b+

to CD27- CD11b+ transition (Fig. 1B). The evident translocation of SRC-3 from the

cytoplasm to the nucleus was further confirmed by immunofluorescence staining (Fig.

1C), indicating a potential role of SRC-3 in this process. SRC-3 is increased in

response to multiple hormones, growth factors or inflammatory factors (30,31).

Considering that several inflammatory cytokines, such as IL-2, IL-12 and IL-15 (6,8),

play important roles in regulating NK cell development and/or function, we tested if

these inflammatory cytokines could also affect the subcellular localization of SRC-3

in NK cells. IL-2, IL-12 or IL-15 stimulation promoted SRC-3 nuclear translocation

in a time-dependent manner but did not affect total SRC-3 expression in mouse NK

cells (Fig. 1D-F). Similar results were obtained from human NK-92 cells

(Supplementary Fig. S2C-E). These findings suggested that SRC-3 may be involved

in NK cell maturation and/or activation.

Conditional ablation of SRC-3 altered NK cell distribution in mice.

To assess whether SRC-3 regulated NK cell lineage development, we established a

mouse model with hematopoietic deletion of SRC-3 (SRC-3fl/fl/Vav1-Cre+ mice and

the littermate SRC-3fl/fl/Vav1-Cre- mice were referred to as SRC-3∆/∆ and Control

mice, respectively) by crossing SRC-3fl/fl mice with Vav1-Cre mice (Supplementary

Fig. S3A-C). Initial flow cytometric analysis revealed that hematopoietic SRC-3

deficiency did not affect common lymphoid progenitors (CLPs) and NK progenitors

(NKPs), including pre-NKPs and rNKPs, in mouse BM (Supplementary Fig. S3D, E).

Hematopoietic deletion of SRC-3 did not significantly alter the percentage and

number of Lin- CD122+ cells or the proportions of NK1.1- Nkp46-, NK1.1+ Nkp46-, or

NK1.1+ Nkp46+ cells in Lin- CD122+ compartments (Fig. 2A). These results suggest

that SRC-3 was dispensable for the early stages of NK development. The percentage 12

and number of NK cells were modestly increased in the BM but significantly

decreased in spleen, pLNs, lungs and liver of SRC-3∆/∆ mice (Fig. 2B and

Supplementary Fig. S3F). To determine the exact role of SRC-3 in NK cells, we used

NK-specific SRC-3 knockout mice (SRC-3fl/fl/Ncr1-Cre+ mice and the littermate

SRC-3fl/fl/Ncr1-Cre- mice are referred to as SRC-3NK∆/∆ and SRC-3fl/fl mice,

respectively) (Supplementary Fig. S4A, B). Indeed, similar results were observed in

SRC-3NK∆/∆ mice (Fig. 2C and Supplementary Fig. S4C).

We then evaluated whether the decrease in NK cells in the peripheral organs of

these mice was due to their blocked egress from the BM. As anticipated, the

expression of S1pr5, a key gene that controls NK cell egress from the BM (27), was

markedly reduced in NK cells from SRC-3NK∆/∆ mice (Fig. 2D, E). Consistent with

this finding, a lower percentage of sinusoidal NK cells was detected in the BM of

SRC-3NK∆/∆ mice (Fig. 2F). These data illustrated that SRC-3 was needed for the

maintenance of a normal NK cell distribution in mice.

Targeted deletion of SRC-3 inhibited NK cell maturation and viability.

We next assessed whether SRC-3 deficiency affected NK cell maturation. The results

of flow cytometric analyses showed that in the BM, spleen and pLNs of SRC-3NK∆/∆

mice, the proportion of most mature CD27- CD11b+ NK cells was decreased, whereas

the proportion of CD27+ CD11b- and CD27+ CD11b+ NK cells were increased (Fig.

3A). In SRC-3NK∆/∆ mice, these organs exhibited a strongly reduced ratio of

CD27−/CD27+ cells in the CD11b+ NK cell population (Fig. 3B). Terminal NK cell

maturation is associated with the upregulation of CD43 and KLRG1 (17). Specifically,

the percentage of CD43+ KLRG1+ cells was evidently decreased in NK cells in the

absence of SRC-3 (Fig. 3C). CD146, another marker of NK cell maturation (32), was

significantly downregulated, and c-Kit (33), a marker of immature NK cells, was 13

markedly upregulated in NK cells when SRC-3 was deleted (Fig. 3D, E). Similar

maturational defects were observed in hematopoietic-specific SRC-3-null mice

(Supplementary Fig. S5A, B).

Immature NK cells have a higher basal proliferation rate than mature NK cells. As

expected, NK cells from both the BM and spleen of SRC-3NK∆/∆ mice exhibited a

significant increase in proliferation as assessed by Ki67 staining and BrdU assays

(Supplementary Fig. S6A, B). The Annexin V/7-AAD staining results showed that the

viability of freshly isolated NK cells from SRC-3NK∆/∆ mice was decreased

(Supplementary Fig. S6C). The accelerated apoptosis may, to some extent, have

limited the number of NK cells in the BM and peripheral organs. However, these

observations were not due to an impairment in STATs signaling induced by SRC-3

deficiency (Supplementary Fig. S7). Collectively, these results indicated a role of

SCR-3 in facilitating NK cell maturation and survival.

SRC-3 deficiency significantly impaired NK cell function.

Our finding that loss of SRC-3 compromised NK cell maturation prompted us to

determine whether SRC-3 was also involved in modulating NK cell function. We then

found that IFN-γ production was reduced on a “per-cell” basis as determined by the

decrease in the mean fluorescence intensity (MFI) of IFN-γ+ cells in SRC-3-deficient

NK cells after IL-12+IL-18 or PMA+ionomycin stimulation, although the percentage

of IFN-γ+ cells was unchanged (Fig. 4A). However, the expression of CD107a, a

marker of NK cell degranulation (34), was substantially reduced in all NK cell subsets

isolated from SRC-3NK∆/∆ mice after stimulation with Yac-1 cells (Fig. 4B). In

addition, depletion of SRC-3 in NK cells resulted in reduced mRNA and protein

production of two critical cytotoxic molecules, granzyme B and perforin (3) (Fig. 4C-

E). 14

Given that SRC-3 functions mainly in the nucleus, we speculated that the demand

for nuclear SRC-3 in NK cells may increase when performing their antitumor function.

As anticipated, mouse splenic NK cells challenged with Yac-1 cells or B16F10

melanoma cells displayed increased SRC-3 nuclear translocation, although total SRC-

3 expression was unchanged (Fig. 4F, G). Consistent with these results, NK cells

sorted from SRC-3NK∆/∆ mice displayed a compromised ability to specifically lyse

target Yac-1 cells in vitro (Fig. 4H). To further verify whether SRC-3 deficiency

impaired the tumor surveillance function of NK cells in vivo, we injected

an equal number of B16F10 melanoma cells into SRC-3fl/fl and SRC-3NK∆/∆ mice via

the caudal vein. As shown in Fig. 4I, compared with their littermate controls, SRC-

3NK∆/∆ mice exhibited significantly increased metastasis of melanoma cells to the lung.

Hence, these findings provide strong evidence that SRC-3 was required to maintain

the normal effector function of NK cells.

SRC-3 modulated the expression of NK cell-associated genes.

To further elucidate the underlying mechanism by which SRC-3 regulated NK cell

maturation and function, we performed RNA-seq analysis of NK cells sorted from the

spleen of SRC-3fl/fl and SRC-3NK∆/∆ mice (Fig. 5A). By using the criteria (log2 (fold

change) > 0.5, adjusted p-value < 0.05), we identified a total of 413 differentially

expressed genes, 260 of which were upregulated and 153 of which were

downregulated in NK cells after SRC-3 ablation (Fig. 5B and Supplementary Table

S3). Consistent with our above results, the differential expression of several genes

(such as S1pr5, Klrg1, Gzmb, Prf1, Kit, etc.) was also observed in these data (Fig. 5B,

C). As noted above, the defects observed in SRC-3NK∆/∆ mice were reminiscent of

those displayed by T-bet-/- mice (12,14,26). However, neither the mRNA nor protein

expression of T-bet was changed in NK cells with SRC-3 deficiency (Fig. 5D, E). 15

Two critical T-bet target genes, Zeb2 and Prdm1, which control NK cell maturation

(26,35), were significantly downregulated in SRC-3-deficient NK cells (Fig. 5C, D, F,

G). The mRNA expression of other NK-associated transcription factors, including

Ets1, Id2, Tox, Irf2, Elf4, Nfil3, Gata3, Eomes, Stat5a, Stat5b, Smad4 and Foxo1

(13,16,25,36-41), were similar in SRC-3fl/fl and SRC-3NK∆/∆ NK cells (Fig. 5D). SRC-

3 is a coactivator that cannot directly bind to DNA but regulates the transcriptional

activity of nuclear receptors and several nonnuclear receptor proteins (18). Combined

with these findings, we reasoned that SRC-3 may be required for T-bet-dependent

regulation of the expression of several genes in NK cells, which was in line with the

above findings.

SRC-3 coactivated T-bet to regulate target gene expression in NK cells.

To confirm whether SRC-3 was a coactivator of T-bet in NK cells, we performed a

Co-IP assay. Specifically, we observed a physical interaction between the SRC-3 and

T-bet proteins in freshly sorted murine NK cells (Fig. 6A). Similar results were

observed in human NK-92 cells (Fig. 6B). On the other hand, data from a published

chromatin immunoprecipitation-sequencing (ChIP-seq) study revealed that Zeb2 and

Prdm1 loci contain several T-bet binding sites (42) (Fig. 6C). The recruitment of

SRC-3 to prominent T-bet binding sites in the promoter regions of these genes was

observed in normal but not SRC-3-null NK cells (Fig. 6D, E). In addition, studies

have reported that S1pr5 is another target gene of T-bet. Indeed, SRC-3 was bound to

a T-bet binding site in the S1pr5 locus (-1.65 kb) (Fig. 6C, F). However, these

bindings were lost in T-bet-/- NK cells (Fig. 6G), indicating that the functions of SRC-

3 were dependent on T-bet. Finally, we wondered whether there was a regulatory

feedback loop between T-bet and SRC-3 in NK cells. Actually, knockout of T-bet did

not significantly affect SRC-3 expression in NK cells (Fig. 6H, I). Collectively, our 16

data demonstrated that SRC-3 could coactivate T-bet to regulate the expression of

several target genes, which was needed for NK cell maturation (Fig. 6J).

Discussion

NK cells are innate immune cells with immunosurveillance and immunoregulatory

functions. The development and maturation of NK cells are harmoniously controlled

by a complex transcriptional regulatory network (6,10). Although many critical

regulatory factors have been identified, the underlying molecular basis is not

completely understood. Here, we showed for the first time that SRC-3 act as a

coactivator of T-bet to regulate the maturation and function of NK cells, therefore

adding a novel mechanism to T-bet-mediated NK cell biology.

As a member of the p160 protein family, SRC-3 was widely expressed and

involved in many biological processes (18). Here, we observed that SRC-3 was

abundant in NK cells in mice. However, using SRC-3fl/fl/Vav1-Cre (hematopoietic-

specific) mice, we found that SRC-3 deficiency did not significantly affect the early

development of NK cells, as there was normal expression of transcription factors

associated with early development of NK cells, such as Nfil3. Targeted ablation of

SRC-3 altered the normal distribution of NK cells due to the downregulation of S1pr5.

Knockout of T-bet or its target gene, S1pr5, blocks the egress of NK cells from the

BM and pLNs (12,27). However, mice with conditional deletion of SRC-3 displayed

reduced NK cell numbers in pLNs, possibly because of alterations in other NK cell

trafficking-associated molecules, similar to observations in Zeb2-/- mice (26).

Many transcription factors related to NK cell maturation, such as T-bet, Zeb2,

Aiolos and Smad4, are gradually upregulated during NK cell terminal differentiation

(12,26,41,43). Although SRC-3 expression was unchanged, its translocation from the

cytoplasm to the nucleus is increased during this process, revealing an increased 17

demand for SRC-3 upon NK cell maturation. As a result, loss of SRC-3 significantly

impaired the maturation of NK cells. SRC-3 is present mainly in the cytoplasm under

steady-state conditions, and its subcellular distribution may be altered after

stimulation (30,44). SRC-3 displayed increased nuclear translocation upon stimulation

with several proinflammatory cytokines. These data indicated that the nuclear

translocation of SRC-3 may be a key checkpoint for NK cell activation. In addition,

although IL-2, IL-12 or IL-15 can appreciably induce SRC-3 nuclear translocation,

SRC-3 deficiency did not significantly affect the phosphorylation of STAT3, STAT4

or STAT5 in NK cells after stimulation with these cytokines. One reason may be that

SRC-3 is downstream of the STATs signaling (16,36).

SRC-3 promotes cancer cell progression by activating multiple cell proliferation-

associated pathways or directly regulating cell-cycle proteins (45). In contrast, our

data showed that SRC-3 inhibits the proliferation of NK cells, suggesting that SRC-3

plays a unique role in NK cells. We found a significant decrease in the expression of

Prdm1, which has a role in inhibiting NK cell proliferation, which may also account

for the finding observed in SRC-3NK∆/∆ mice. However, the enhanced proliferation did

not lead to a significant increase in NK cell number, possibly due to the simultaneous

increase in apoptosis induced by SRC-3 deficiency.

NK cells play a crucial role in early immunosurveillance of tumors. Here, we

found that CD107a expression was decreased in all subsets of SRC-3-deficient NK

cells after Yac-1 cells stimulation, indicating a reduced “per-cell” cytotoxic potential

of SRC-3-null NK cells against Yac-1 target cells. Consistent with this finding,

deletion of SRC-3 led to significant decreases in the expression of granzyme B and

perforin, critical cytotoxic molecules that kill target cells, in all NK cell subsets.

These findings indicated that SRC-3 may have participated in regulating NK cell

effector function. However, we did not perform direct in vitro cytotoxicity of each

NK cell subset between SRC-3fl/fl or SRC-3NK∆/∆ mice. These assays may have

provided evidence supporting our conclusion. It will also be worthwhile to knock out

SRC-3 using in vitro-expressed TAT-Cre recombinant protein in NK cells derived

from SRC-3fl/fl mice and analyze the effector functions.

T-box transcription factor T-bet is a master transcriptional regulatory factor in NK

cells (11). Since the role of T-bet in NK cells was first reported by Michael et al., it

has received great attention (12). However, a clear understanding of the molecular

mechanisms by which T-bet works is still lacking. SRC/p160 coactivator SRC-2 can

regulate the expression of pro-opiomelanocortin (POMC) mediated by another T-box

transcription factor Tpit after hormonal stimulation (46). T-bet can recruit the

transcriptional cofactor Bhlhe40 to modulate IFN-γ generation in invariant natural

killer T (iNKT) cells (47). Hence, the T-box family of transcription factors may need

transcriptional regulators to synergistically control target gene expression in a cell

context-specific manner. In this study, we showed that the phenotype of SRC-3-null

NK cells resembled that observed in T-bet knockout mice. We identified an

interaction between the SRC-3 and T-bet proteins under physiological conditions.

SRC-3 can be recruited to the promoter regions of Zeb2, Prdm1 and S1pr5, all of

which are T-bet target genes (26,27,35). However, these effects were abrogated in NK

cells when T-bet was knocked out, indicating that SRC-3 acted in a manner dependent

on T-bet. Taken together, these results indicated that SRC-3 may be a critical

component of the T-bet-dependent transcriptional regulatory complex in NK cells,

although we could not exclude other T-bet-independent mechanisms that will need

further investigation.

Prdm1 and Zeb2 partially mediate the role of T-bet in terminal NK cell maturation

(26,35). NK cells from Prdm1-/- and Zeb2-/- mice have some maturational defects

similar to those from T-bet-/- mice, which are also observed, albeit to a lesser extent,

in SRC-3NK∆/∆ mice. The expression of both transcription factors were markedly

decreased in SRC-3-deficient NK cells. Hence, we believe that SRC-3 promoted NK

cell maturation at least partially by regulating the T-bet-dependent expression of Zeb2

and Prdm1. T-bet regulates the expression of several target genes in NK cells and T

cells in cooperation with Zeb2 (48). Therefore, decreased expression of Zeb2 may

further compromise the transcriptional activity of T-bet in SRC-3-deficient NK cells.

Indeed, the expression of many target genes coinduced (such as Klrg1, Gzma, Gzmb,

Mcam and Cx3cr1) or corepressed (such as Socx3 and Dusp6) by Zeb2 and T-bet

were significantly changed in SRC-3-null NK cells.

In conclusion, our findings demonstrated that SRC-3 was involved in the regulation

of the maturation and antitumor function of NK cells at least in part by coactivating T-

bet. These data not only reveal a new molecular mechanism related to T-bet in NK

cells, but also provide a potential target to increase the tumor surveillance and viral

elimination functions of NK cells upon SRC-3 nuclear translocation.

Acknowledgements

We thank Yang Liu for technical support in flow cytometry, and Liting Wang for

technical assistance in immunofluorescence microscopy. This work was supported by

grants from the National Natural Science Foundation of China (No. 81725019,

81930090, 81573084, 81500087), and the Scientific Research Project of PLA

(AWS16J014).

Author Contributions

M.H. designed the study, performed experiments and wrote the manuscript. Y.L.,

Y.Q., Z.Z. and S.W. performed experiments and analyzed data. Y.X., F.C. and M.C.

participated in the animal experiments. Y.T., S.C., C.D. and M.S. contributed to the in

vitro experiments. F.W., Y.S. and Y.D. participated in the initial experimental design.

J.W. and Y.D. conceived and supervised the study, and revised the manuscript.

Reference

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Figure legends

Fig. 1. SRC-3 displayed increased nuclear translocation in NK cells during

maturation and upon inflammatory cytokine stimulation. (A) QRT-PCR analysis

of the expression of SRC-3 mRNA in NK cell subsets (CD27+ CD11b-, CD27+

CD11b+ and CD27- CD11b+) sorted from the spleen of normal WT C57 mice (n = 4

mice per group). Data are representative of three independent experiments. (B)

Western blotting analysis of the expression of total or nuclear SRC-3 protein in NK

cell subsets (CD27+ CD11b-, CD27+ CD11b+ and CD27- CD11b+) sorted from the

spleen of normal WT C57 mice (pooled from 20 mice). Representative images from

three independent experiments are shown. (C) Representative immunofluorescence

images from three independent experiments showing the subcellular localization of

SRC-3 protein in NK cell subsets (CD27+ CD11b-, CD27+ CD11b+ and CD27-

CD11b+) sorted from the spleen of normal WT C57 mice (n = 5 mice). The scale bar

indicates 10 μm. (D-F) Total NK cells freshly sorted from mouse spleen were

stimulated with (D) IL-2 (200 IU/ml), (E) IL-12 (10 ng/ml) or (F) IL-15 (100 ng/ml).

At indicated time after stimulation, the expression of total or nuclear SRC-3 protein in

NK cells was analyzed by Western blot. Nuclear or total SRC-3 protein was

normalized to Lamin B1 or β-actin, respectively. Representative images are shown in

the left, and densitometry quantified data from three independent experiments are

shown in the right (All data was compared with 0 min group). Data are shown as

mean ± SD (A, D-F). *P < 0.05, **P < 0.01, ***P < 0.001. one-way ANOVA (A, D-

F).

Fig. 2. Conditional ablation of SRC-3 altered NK cell distribution in mice. (A)

Flow cytometric analysis of the percentage and number of Lin- CD122+ cells in the

BM, as well as the percentages of NK1.1- Nkp46-, NK1.1+ Nkp46- and NK1.1+

Nkp46+ cells in Lin- CD122+ compartments, from Control and SRC-3∆/∆

(hematopoietic-specific) mice (n = 8 mice per group). Lineage (Lin) includes CD3,

CD19, Ter119 and Gr-1. Data are representative of three independent experiments. (B)

Flow cytometric analysis of the percentage and number of CD3- CD19- NK1.1+ NK

cells in the BM, spleen and pLNs of Control and SRC-3∆/∆ (hematopoietic-specific)

mice (n = 8 mice per group). Data are representative of three independent experiments.

NK cells in the BM, spleen and pLNs of SRC-3fl/fl and SRC-3NK∆/∆ (NK-specific)

mice (n = 8 mice per group). Data are representative of three independent experiments.

(D) QRT-PCR analysis of the relative expression of S1pr5 mRNA in total NK cells

(CD3- CD19- NK1.1+ NKp46+) sorted from the spleen of SRC-3fl/fl and SRC-3NK∆/∆

mice (n = 4 mice per group). Data are representative of three independent experiments.

(E) Flow cytometric analysis of the MFI of S1P5 (S1pr5 is the gene name of S1P5) in

total NK cells (CD3- CD19- NK1.1+ NKp46+) from the spleen of SRC-3fl/fl and SRC-

3NK∆/∆ mice (n = 6 mice per group). MFI, mean fluorescence intensity. Data are

representative of three independent experiments. (F) SRC-3fl/fl and SRC-3NK∆/∆ mice

were injected with 1 µg PE-CD45 antibody via the tail vein. Two minutes later, mice

were sacrificed, and the percentage of CD45+ cells in total NK cell cells (CD3- CD19-

NK1.1+ NKp46+) from their BM was analyzed by flow cytometry (n = 6 mice per

group). Data are representative of three independent experiments. Data are shown as

mean ± SD (A-F). *P < 0.05, **P < 0.01, ***P < 0.001. Student’s t-test (A-F).

Fig. 3. Targeted deletion of SRC-3 inhibited NK cell maturation. (A) Flow

cytometric analysis of the percentages of CD27+ CD11b-, CD27+ CD11b+ and CD27-

CD11b+ cells in total NK cells (CD3- CD19- NK1.1+ NKp46+) from the BM, spleen 26

and pLNs of SRC-3fl/fl and SRC-3NK∆/∆ mice (n = 8 mice per group). Data are

representative of three independent experiments. (B) The ratio of CD27−/CD27+

among CD11b+ NK cells from the BM, spleen and pLNs of SRC-3fl/fl and SRC-3NK∆/∆

mice (n = 8 mice per group). Data are representative of three independent experiments.

cells (CD3- CD19- NK1.1+ NKp46+) from the BM, spleen and pLNs of SRC-3fl/fl and

SRC-3NK∆/∆ mice (n = 8 mice per group). Data are representative of three independent

experiments. (D) Flow cytometric analysis of the percentage of CD146+ cells in total

NK cells (CD3- CD19- NK1.1+ NKp46+) from the BM, spleen and pLNs of SRC-3fl/fl

and SRC-3NK∆/∆ mice (n = 8 mice per group). Data are representative of three

independent experiments. (E) QRT-PCR analysis of the relative expression of Kit

mRNA in total NK cells (CD3- CD19- NK1.1+ NKp46+) sorted from the spleen of

SRC-3fl/fl and SRC-3NK∆/∆ mice (n = 4 mice per group). Data are representative of

three independent experiments. (F) Flow cytometric analysis of the expression of c-

Kit in NK cell subsets from the spleen of SRC-3fl/fl and SRC-3NK∆/∆ mice (n = 6 mice

per group). Representative images of three independent experiments obtained from

CD27+ CD11b- NK cells are shown in the left. Data are shown as mean ± SD (A-F).

*P < 0.05, **P < 0.01, ***P < 0.001. Student’s t-test (A-F).

Fig. 4. SRC-3 deficiency significantly impaired NK cell function. (A) Spleen cells

obtained from SRC-3fl/fl and SRC-3NK∆/∆ mice were stimulated with None, IL-12 (25

ng/ml) + IL-18 (20 ng/ml), or PMA (5 ng/mL) + ionomycin (50 ng/mL) in the

presence of brefeldin A and monensin for 6 hours. Then, the expression of IFN-γ in

total NK cells (CD3- CD19- NK1.1+ NKp46+) was analyzed by flow cytometry (n = 8

mice per group). Data are representative of three independent experiments. (B) Spleen

cells obtained from SRC-3fl/fl and SRC-3NK∆/∆ mice were cocultured with Yac-1 cells 27

(E:T ratio = 2:1) in the presence of brefeldin A, monensin and anti-CD107a for 6

hours. Then, the percentage of CD107a+ cells in total NK cells (CD3- CD19- NK1.1+

NKp46+) and their subsets were analyzed by flow cytometry (n = 8 mice per group).

Data are representative of three independent experiments. (C) QRT-PCR analysis of

the relative expression of Gzmb and Prf1 mRNA in total NK cells (CD3- CD19-

NK1.1+ NKp46+) sorted from the spleen of SRC-3fl/fl and SRC-3NK∆/∆ mice (n = 4

mice per group). Data are representative of three independent experiments. (D, E)

Flow cytometric analysis of the MFI of (D) Granzyme B and (E) Perforin in total NK

cells (CD3- CD19- NK1.1+ NKp46+) and their subsets from the spleen of SRC-3fl/fl

and SRC-3NK∆/∆ mice (n = 8 mice per group). Data are representative of three

independent experiments. (F, G) NK cells sorted from mouse spleen were cocultured

with CFSE-labeled (F) Yac-1 cells or (G) B16F10 cells (E:T ratio = 2:1) for 6 hours.

Then, NK cells were isolated by flow cytometry and the expression of total or nuclear

SRC-3 protein was detected by western blot (pooled from 8-10 mice per group).

Nuclear and total SRC-3 protein was normalized to Lamin B1 and β-actin,

respectively. Representative images are shown in the left, and densitometry quantified

data from three independent experiments are shown in the right. (H) NK cells sorted

from the spleen of SRC-3fl/fl or SRC-3NK∆/∆ mice were cocultured with CFSE-labeled

Yac-1 cells at indicated E:T ratio for 6 hours. Then, the percentage of TOPRO3

positive Yac-1 cells was detected by flow cytometry (n = 6 mice per group). Data are

representative of three independent experiments. (I) The number of tumor nodules in

lungs of SRC-3fl/fl or SRC-3NK∆/∆ mice after challenged with B16F10 melanoma cells

(n = 8 mice per group). Data are representative of three independent experiments.

Data are shown as mean ± SD (A-I). *P < 0.05, **P < 0.01, ***P < 0.001. Student’s t-

test (A-I).

Fig. 5. SRC-3 modulated the expression of NK cell-associated genes. (A) RNA-seq

analysis workflow. (B) Scatter plot of genes in total NK cells (CD3- CD19- NK1.1+

NKp46+) from the spleen of SRC-3fl/fl or SRC-3NK∆/∆ mice. Several previously

recognized NK-associated genes are outlined in black. (C) Heatmap of significantly

changed genes in total NK cells (CD3- CD19- NK1.1+ NKp46+) from the spleen of

SRC-3fl/fl or SRC-3NK∆/∆ mice. Representative 41 differentially expressed genes are

shown. (A-C) RNAseq data was obtained from one experiment. (D) QRT-PCR

analysis of the relative expression of Ets1, Tox, Nfil3, Gata3, Eomes, Id2, Stat5a,

Stat5b, Irf2, Elf4, Smad4, Foxo1, Tbx21, Zeb2 and Prdm1 mRNA in total NK cells

(CD3- CD19- NK1.1+ NKp46+) sorted from the spleen of SRC-3fl/fl and SRC-3NK∆/∆

mice (n = 4 mice per group). Data are representative of three independent experiments.

(E-G) Flow cytometric analysis of the expression of (E) T-bet, (F) Zeb2 and (G)

Blimp1 (Prdm1 is the gene name of Blimp1) in total NK cells (CD3- CD19- NK1.1+

NKp46+) and their subsets from the spleen of SRC-3fl/fl and SRC-3NK∆/∆ mice (n = 6

mice per group). Representative images of three independent experiments obtained

from total NK cells are shown in the left. Data are shown as mean ± SD (D-G). **P <

0.01, ***P < 0.001. Student’s t-test (D-G).

Fig. 6. SRC-3 coactivated T-bet to regulate target gene expression in NK cells. (A,

B) Co-IP analysis of the interaction of T-bet and SRC-3 proteins in (A) mouse

primary NK cells (pooled from 10-12 mice) and (B) human NK-92 cells. Data shown

are representative of three independent experiments. IP, immunoprecipitation; WB,

Western blot. (C) ChIP-seq analysis performed on mouse splenic NK cells showing

T-bet binding at indicated sites of Zeb2, Prdm1 and S1pr5 loci. Results were obtained

from a published data (reference genome: mm9) (42). TSS, transcriptional start site.

(D-F) ChIP analysis of SRC-3 binding at (D) Zeb2 locus (about-1.65 kb and TSS), (E) 29

Prdm1 locus (about -0.1 kb) and (F) S1pr5 locus (about -1.85 kb) in splenic NK cells

from SRC-3fl/fl and SRC-3NK∆/∆ mice (pooled from 8-10 mice per group). Data are

representative of three independent experiments. (G) ChIP analysis of SRC-3 binding

at Zeb2 locus (about-1.65 kb), Prdm1 locus (about -0.1 kb) and S1pr5 locus (about -

1.85 kb) in splenic NK cells from WT and T-bet-/- mice (pooled from 8-10 mice per

group). Data are representative of three independent experiments. (H) QRT-PCR

analysis of the relative expression of SRC-3 mRNA in total NK cells (CD3- CD19-

NK1.1+ NKp46+) sorted from the spleen of WT and T-bet-/- mice (n = 4 mice per

group). Data are representative of three independent experiments. (I) Flow cytometric

analysis of the MFI of SRC-3 in total NK cells (CD3- CD19- NK1.1+ NKp46+) from

the spleen of WT and T-bet-/- mice (n = 6 mice per group). Data are representative of

three independent experiments. (J) Schematic of proposed model demonstrating how

SRC-3 regulates the maturation and function of NK cells by coactivating T-bet. Data

are shown as mean ± SD (D-I). **P < 0.01. Student’s t-test (D-I).

SRC-3 functions as a coactivator of T-bet by regulating the maturation and antitumor activity of natural killer cells

Mengjia Hu, Yukai Lu, Yan Qi, et al.

Cancer Immunol Res Published OnlineFirst June 19, 2020.

Updated version Access the most recent version of this article at: doi:10.1158/2326-6066.CIR-20-0181

Supplementary Access the most recent supplemental material at: Material http://cancerimmunolres.aacrjournals.org/content/suppl/2020/06/19/2326-6066.CIR-20-0181.D C1

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