NR1D1 Stimulates Antitumor Immune Responses in Breast Cancer by Activating cGAS-STING Signaling

Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer-related deaths in women worldwide (1). Breast cancer is a heterogeneous disease composed of distinct subtypes with different biological and morphologic features, and disparate responses to treatment (2). Despite great improvements in diagnosis and therapeutics, 20%–30% of patients with breast cancer may develop metastases and the 5-year overall survival rate of patients with distant metastasis is less than 20% (3). There are still limited treatment options for patients with metastatic breast cancer; thus, it is critical to identify novel therapeutic targets for the development of effective strategies against metastatic breast cancer.

In the tumor microenvironment (TME), the immune system functions as a double-edged sword in cancer, as it can protect against tumor development by eliminating neoplastic cells but promotes tumor immune escape by shaping tumor immunogenicity (4). Thus, it is of great significance to reestablish the host antitumor immune response to successfully eradicate cancer. Although breast cancer has been historically considered a poorly immunogenic tumor, it was recently reported that certain breast cancer cases have a high tumor mutational burden and are strongly infiltrated by immune cells (5). A number of clinical studies have shown that the presence of tumor-infiltrating lymphocytes (TIL) at diagnosis confers both prognostic and predictive value, especially in triple-negative breast cancer (TNBC) and HER2⁺ breast cancer (6–8). High levels of TILs are also associated with improved prognosis in metastatic breast cancer (9, 10). The extent and function of TILs are modulated by multiple factors including type I IFNs. Produced by tumor cells and infiltrating immune cells, type I IFNs promote the maturation and activation of antigen-presenting cells to facilitate T-cell cross-priming and infiltration into tumors (11). Thus, many attempts have been made to induce type I IFN responses to reshape the TME and enhance immunogenicity (11).

The stimulator of IFN genes (STING) pathway is critical for inducing type I IFNs to elicit antitumor immunity. Sensing of cytosolic DNA by cyclic guanosine monophosphate–adenosine monophosphate synthase (cGAS) leads to the activation of STING and downstream signaling molecules, including TANK-binding kinase 1 (TBK1) and IFN regulatory factor 3 (IRF3). In turn, these lead to the increased expression of type I IFNs and downstream chemokines, such as CC chemokine ligand 5 (CCL5) and C-X-C motif chemokine ligand 10 (CXCL10), which induce the infiltration and activation of cytotoxic T cells and natural killer (NK) cells to the tumor sites (12). DNA damage and the resulting leakage of genomic DNA are sources of cytoplasmic DNA, which can trigger the STING pathway and subsequent immune response in cancer cells (13). Defects in DNA repair factors such as ataxia-telangiectasia mutated (ATM), breast cancer gene 1/2 (BRCA 1/2), bloom syndrome protein, excision repair cross complementing-group 1, and ribonuclease H2 subunit A, cause high levels of cytosolic DNA, which trigger STING signaling and cell-intrinsic type I IFN responses (13). Breast tumors with a DNA damage response (DDR)-deficient signature, those recognizing loss of the Fanconi anemia/BRCA DNA repair pathway, show STING activation and CD8⁺ T-cell infiltration (14). We also showed that defect in the repair of DNA double-strand breaks (DSB) caused by the IFN γ-inducible protein 16-type I IFN axis enhances STING-mediated type I IFN signaling and antitumor immune responses in TNBC (15). Thus, DDR regulators could be good candidates to modulate the antitumor immune response.

Nuclear receptor subfamily 1 group D member 1 (NR1D1), also known as REV-ERBα, is a circadian clock component that integrates circadian rhythm and metabolism (16). NR1D1 has been implicated in a variety of pathophysiologic processes including inflammation, metabolic diseases, and cancer (17). The NR1D1 gene is coamplified with ERBB2 at the 17q12–q21 chromosomal region in breast tumors, which is associated with poor clinical outcomes (18, 19). NR1D1 has also been shown to promote the proliferation of ERBB2 (HER2)-positive breast cancer cells (20). However, recent studies have shown that NR1D1 harbors tumor-suppressive functions. NR1D1 transcript levels are significantly lower in a number of breast cancer cells compared with noncancer mammary epithelial cells (21). Activation of NR1D1 with a synthetic agonist, SR9011, suppresses the proliferation of breast cancer cells by directly targeting cyclin A2 expression and arresting the cell cycle (22). Furthermore, activation of NR1D1 by SR9009 exerts cytotoxic effects on a variety of cancer cells, including breast cancer, without affecting normal cells, by suppressing de novo lipogenesis and autophagy, which are essential cellular processes for the survival of tumor cells (23). Importantly, we previously reported that NR1D1 inhibits DNA repair in breast cancer cells through binding on DSB sites, where it suppresses further recruitment of DDR factors (24). Considering the importance of the DDR in antitumor immune responses, we investigated the role of NR1D1 and its ligands in breast cancer in the context of antitumor immunity.

Expression levels of NR1D1 in breast cancer and adjacent normal tissues obtained from The Cancer Genome Atlas (TCGA) RNA-sequencing (RNA-seq) database were analyzed using the Breast Cancer Integrative Platform (BCIP; http://www.omicsnet.org/bcancer/; ref. 25). The GSE37751 dataset was downloaded from NCBI Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/; ref. 26). Kaplan–Meier plotter mRNA breast cancer database (http://kmplot.com/analysis/) was utilized to assess the prognostic value of NR1D1 in breast cancer (probe ID 31637_s_at or 204760_s_at; ref. 27). The processed data including normalization procedures were obtained from the corresponding websites, and no additional transformations were performed.

Human breast tissue microarray slides (BN08111, BR1191, and BR247a) that contains breast carcinoma tissues, normal adjacent breast tissues, and normal breast tissues were purchased from TissueArray.Com LLC. The slides were subjected to immunostaining with anti-NR1D1 antibody (Supplementary Table S1). Imaging and quantification was performed using the Vectra Polaris Automated Quantitative Pathology Imaging System and inForm software (Akoya Biosciences).

Nr1d1 knockout (KO) mouse in FVB/N (RRID: MGI:6112021) or in C57BL/6J (RRID: IMSR_JAX:000664) were generated using the CRISPR/Cas9 system (ToolGen, Inc.); mixture of 100 ng/μL Cas9 protein (M0646T, New England Biolabs) and 50 ng/μL gRNA was injected to the cytoplasm of pronuclei (Supplementary Table S2). Indel mutations in F1 mice were identified by sequencing. All mice were genotyped at 4 weeks after birth and housed according to their gender (Supplementary Table S2). FVB/N-Nr1d1^+/− mice were crossbred with mouse mammary tumor virus–polyoma middle tumor-antigen (MMTV-PyMT; designated as PyMT) mice (RRID: IMSR_JAX:002374). At 14 weeks of age, mice were sacrificed and mammary tumors and lung were removed and fixed in formalin, and paraffin-embedded for further analyses. To visualize system-wide tumor burden, Nr1d1^+/−;PyMT mice were crossbred with MMTV-FP635 (designated as FP635) mice (kindly provided by Prof. Jiyoung Park in UNIST, Ulsan, South Korea), in which fluorescence is exclusively expressed in the mammary ductal epithelium under the control of MMTV promoter (28). Tumor progression in Nr1d1;FP635;PyMT mice was monitored using the IVIS 200 imaging system (Xenogen Corporation) and signal intensity was analyzed with Living image software (version 4.5.5; PerkinElmer).

For the orthotopic xenograft, control-Py230 or Nr1d1 KO-Py230 cells (established as described below) resuspended in Matrigel (BD Biosciences) were injected into the mammary fat pads of C57BL/6J-Nr1d1^+/+ [designated as Nr1d1 wild-type (WT)] or Nr1d1^−/− (Nr1d1 KO) mice. Eight weeks after the injection of tumor cells, mice were sacrificed and primary tumor and lungs were removed. To examine the effects of SR9009 on tumor growth in MMTV-PyMT model, mice were administrated with vehicle or 100 mg/kg SR9009 for 5 times a week for 6 weeks by intraperitoneal injection. All mice were sacrificed at 10 am considering that Nr1d1 is a circadian clock gene. The animal studies were reviewed and approved by the Institutional Animal Care and Use Committee (IACUC) of the National Cancer Center Research Institute (NCCRI; protocols: NCC-20–545, NCC-21–714, and NCC-21–678), which is an Association for Assessment and Accreditation of Laboratory Animal Care International accredited facility that abides by the Institute of Laboratory Animal Resources guide. All animal experiments were performed in accordance with the guidelines for the Care and Use of Laboratory Animals of the IACUC of the National Cancer Center Research Institute.

Human breast cancer cell lines MDA-MB-231 (RRID: CVCL_0062), SKBR3 (RRID: CVCL_0033), MCF7 (RRID: CVCL_0031), T47D (RRID: CVCL_0553), BT474 (RRID: CVCL_0553), BT549 (RRID: CVCL_1092), and Hs578T (RRID: CVCL_0332), a murine breast cancer cell line, Py230 (RRID: CVCL_AQ08), and a human nontumorigenic breast epithelial cell line, MCF10A (RRID: CVCL_0598), were obtained from the ATCC. MDA-MB-231, MCF7, BT474, and Hs578T cells were maintained in DMEM supplemented with 10% FBS. SKBR3, T47D, and BT549 cells were maintained in RPMI1640 medium supplemented with 10% FBS. Py230 cells were maintained in Ham F-12K (Kaighn's) medium supplemented with 5% FBS. MCF10A cells were maintained in DMEM‐F12 (1:1) medium supplemented with 5% FBS, 20 ng/mL EGF, 0.5 μg/mL hydrocortisone, and 10 μg/mL insulin. To generate NR1D1 KO sublines, cells were transfected with an NR1D1 CRISPR/Cas9 KO plasmid (sc-401211 or sc-432177, Santa Cruz Biotechnology) or a control plasmid (sc-418922) using Lipofectamine 2000 (Thermo Fisher Scientific). GFP-positive cells were sorted by FACS Aria (BD Biosciences), and NR1D1 KO was confirmed by Western blotting after expansion of clones. The cells were grown in an incubator with 5% CO₂/95% air at 37°C. Cells were authenticated using short tandem repeat analysis and routinely certified free of Mycoplasma contamination using the MycoAlert Mycoplasma Detection Kit (Lonza). H₂O₂, doxorubicin, cisplatin, and GSK4112 were purchased from Sigma-Aldrich. SR9009 were purchased from APExBIO.

For RNA-seq analysis, total RNA was obtained from the mammary gland tumor tissues of 14-week-old FVB/N-Nr1d1 WT;PyMT and Nr1d1 KO;PyMT mice. mRNA enrichment and library preparation were performed using the NEBNext Ultra II Directional RNA-Seq Kit (New England Biolabs) following the manufacturer's protocol. mRNA was isolated using the Poly(A) RNA Selection Kit (LEXOGEN, Inc.) and used for the cDNA synthesis and shearing. Indexing was performed using the Illumina indexes 1–12. After enrichment step was carried out using PCR, the libraries were evaluated using the TapeStation HS D1000 Screen Tape (Agilent Technologies) for the mean fragment size. Quantification was performed using the library quantification kit using a StepOne Real-Time PCR System (Life Technologies, Inc.). High-throughput sequencing was performed as paired-end 100 sequencing using NovaSeq 6000 (Illumina, Inc.). A quality of raw sequencing data was controlled using FastQC. After adapter and low quality reads (<Q20) were removed using FASTX_Trimmer and BBMap, trimmed reads were mapped to the reference genome using TopHat. Gene expression levels were estimated using Fragments Per kb per Million reads (FPKM) values by Cufflinks. The FPKM values were normalized on the basis of quantile normalization method using EdgeR within R. Gene-set enrichment analysis (GSEA) was conducted using GSEA software v4.2.3 with the “log2_Ratio_of_Classes” metric to generate a ranked list and a “phenotype” permutation type. Gene sets that contain fewer than 50 genes and more than 500 were excluded in the analysis.

For microarray, total RNA was extracted from MDA-MB-231 control or NR1D1 KO cells treated with 200 μmol/L H₂O₂ for 72 hours. cDNA was synthesized using the GeneChip Whole Transcript amplification kit as described by the manufacturer. The sense cDNA was then fragmented and biotin-labeled with terminal deoxynucleotidyl transferase using the GeneChip Whole Transcript terminal labeling kit. Approximately 5.5 μg of labeled DNA target was hybridized to the Affymetrix GeneChip Human Gene 2.0 ST Array at 45°C for 16 hours. Hybridized arrays were washed and stained on a GeneChip Fluidics Station 450 and scanned on a GCS3000 Scanner (Affymetrix). The probe cell intensity data computation and a CEL file generation was performed using Affymetrix GeneChip Command Console Software. Gene ontology term analysis was performed using DAVID 2021 software (https://david.ncifcrf.gov/). Protein–protein interaction network analysis was performed using STRING v11.5 database (http://string-db.org).

Paraffin-embedded tumor tissues were cut into 4–μm sections and mounted onto silane-coated glass slides. To visualize cytosolic DNA, PicoGreen staining was performed using Quant-iT PicoGreen dsDNA Assay Kit (Thermo Fisher Scientific; ref. 15). Briefly, after deparaffinization and antigen retrieval, slides were subjected to staining with PicoGreen dsDNA reagent together with Alexa Fluor 594-conjugated wheat germ agglutinin (WGA), which labels plasma membrane. The slides were mounted and analyzed using a confocal microscope (Carl Zeiss LSM710). For IHC, sections of paraffin-embedded tissues were subjected to staining using specific antibodies (Supplementary Table S1). Quantification was performed using whole-slide scan images by Vectra Polaris Automated Quantitative Pathology Imaging System and inForm software (Akoya Biosciences). Representative images were obtained using a brightfield microscopy with a 40× objective lens (Olympus, BX53).

For flow cytometry, tumor tissues were dissociated into single cells using the Tumor Dissociation Kit (#130–096–730) and the gentleMACS Octo Dissociator (Miltenyi Biotec). For staining of surface antigens, single cells were resuspended and incubated for 30 minutes at 4°C with specific antibodies shown in Supplementary Table S1. For staining of intracellular proteins, cells were fixed and permeabilized using a transcription factor buffer set (BD Pharmingen), and stained with specific antibodies (Supplementary Table S1). Cells were acquired on flow cytometry (LSR Fortessa, BD Biosciences) and analyzed by FlowJo software (TreeStar, Tree Star Inc.).

For Western blotting, cells were lysed in lysis buffer (50 mmol/L Tris-HCl pH 7.4, 150 mmol/L NaCl, 5 mmol/L EDTA, 1% NP-40, protease inhibitor, and phosphatase inhibitor) and incubated on ice for 30 minutes. After centrifugation, the supernatants were collected, and protein concentrations were measured using BCA assay (15, 29). Equal amounts of proteins were separated on SDS-PAGE, followed by semi-dry transfer onto polyvinylidene difluoride membrane (Millipore). The membranes were blocked with 5% BSA or 5% nonfat milk in 0.1% PBST, and then primary antibodies were exposed overnight at 4°C. Secondary horseradish peroxidase–conjugated antibodies were exposed for 1 hour at room temperature (Supplementary Table S1). Detection was performed using Amersham ECL Western Blotting Detection Reagent (Cytiva). Band intensities of proteins were quantified with ImageJ software. The level of cGAMP in mammary tumor tissues was measured using 2′3′-cGAMP ELISA kit (#501700, Cayman Chemical). The amounts of proteins in culture supernatants were measured using commercially available ELISA kits [IFNα and IFNβ (MBS2506739 and MBS2513798, respectively; MyBioSource), CCL5 and CXCL10 (DRN00B and DIP100, respectively; R&D Systems)]. For immunofluorescence staining, cells were fixed with acetone, blocked with 5% BSA in PBS, and then incubated with a primary antibody at 4°C overnight. Cells were incubated with Alexa Fluor 488–conjugated secondary antibody for 1 hour at room temperature and stained with 4′,6-diamidino-2-phenylindole (DAPI; Supplementary Table S1; ref. 30). Images were analyzed using a confocal microscope (Carl Zeiss LSM710).

Statistical analyses were performed using GraphPad Prism 9 software. Experimental results are given as the mean ± SD, unless indicated otherwise. Statistically significant differences were determined using the nonparametric Mann–Whitney U test (two-tailed) or the unpaired Student t test, as indicated in figure legends. P < 0.05 was considered statistically significant.

The RNA-seq and microarray data generated in this study are deposited in GEO at GSE222645 and GSE231652, respectively. TCGA database was obtained and analyzed in the Breast Cancer Integrative Platform (BCIP; http://www.omicsnet.org/bcancer/). The GSE37751 dataset was downloaded from GEO (http://www.ncbi.nlm.nih.gov/geo/). Kaplan–Meier plotter mRNA breast cancer database (http://kmplot.com/analysis/) was utilized to assess the prognostic value of NR1D1 in breast cancer. All other raw data are available upon request from the corresponding author.

To assess the clinical implications of NR1D1, we first analyzed the expression level of NR1D1 in breast cancer and adjacent normal tissues using TCGA database. The expression level of NR1D1 in breast cancer tissues was significantly lower than that in adjacent normal tissues (P < 0.0001; Fig. 1A). Consistently, immunostaining of NR1D1 protein in tissue microarray showed that NR1D1 level in tumor tissues was lower than that in normal and adjacent normal tissues (Fig. 1B). Analysis of the GSE37751 dataset showed that the expression level of NR1D1 was inversely correlated with tumor grade in patients with breast cancer (Fig. 1C). We previously reported that high NR1D1 expression is correlated with improved clinical outcomes in patients with breast cancer who received chemotherapy (24, 31). We analyzed the prognostic value of NR1D1 in breast cancer more thoroughly using the Kaplan–Meier plotter database, which integrates tumor samples from multiple GEO datasets. Survival analyses of patients with breast cancer showed that overall survival and postprogression survival were improved in the high-NR1D1 expression group compared with the low-NR1D1 expression group (Fig. 1D). Furthermore, the high expression of NR1D1 was associated with improved distant metastasis-free survival, particularly in patients with lymph node–positive breast cancer, indicating the involvement of NR1D1 in breast cancer progression and metastasis (Fig. 1D). These data suggest that high NR1D1 expression has a favorable impact on patient outcomes and may be an important prognostic factor in patients with breast cancer.

To elucidate the role of NR1D1 in the progression of breast cancer, we generated a genetically mutated mouse line lacking the Nr1d1 gene using the CRISPR-Cas9 system (Supplementary Fig. S1A–S1D). The mouse line was crossbred with MMTV–PyMT mice, which is an aggressive mammary adenocarcinoma model that develops invasive carcinoma and pulmonary metastasis (Fig. 2A; ref. 32). We observed that mammary gland tumor weight was significantly higher in Nr1d1 KO;PyMT mice than in Nr1d1 WT;PyMT mice (Fig. 2B). The tumor-free survival rate was lower in Nr1d1 KO;PyMT mice compared with control mice (Fig. 2C). Furthermore, the lung metastatic burden was higher in Nr1d1 KO;PyMT mice than in control mice (Fig. 2D). When monitoring tumor burden in living Nr1d1;FP635;PyMT mice, fluorescence indicating tumors was observed in both the mammary glands and lungs of 14-week-old mice. The intensity was higher in Nr1d1 KO;FP635;PyMT mice compared with Nr1d1 WT;FP635;PyMT mice (Fig. 2E). These results show that NR1D1 deficiency affects the growth and metastatic ability of mammary gland tumors.

Because we used the systemic Nr1d1 KO strategy, we wanted to determine whether the altered tumor progression associated with NR1D1 was due to NR1D1 in tumor cells or in other components such as immune cells in the TME. To this end, we used a syngeneic orthotopic transplant mouse model with Nr1d1-deficient Py230, which was derived from a PyMT C57BL/6 female mouse, Nr1d1 KO-Py230 (33). Control and Nr1d1 KO-Py230 cells were implanted into the mammary fat pads of Nr1d1 WT or KO C57BL/6 mice. Nr1d1 KO-Py230 tumors were larger than Py230 control tumors in both Nr1d1 WT and KO C57BL/6 mice (Fig. 2F). The tumor-free survival rate was lower in Nr1d1 KO-Py230—implanted mice than in control-Py230–implanted mice (Fig. 2G). Furthermore, Nr1d1 KO-Py230 tumors showed a higher degree of lung metastasis than Py230 control tumors (Fig. 2H). However, Nr1d1 expression in the host had no significant effects on tumor growth and lung metastasis (Fig. 2F–H). These results indicate that NR1D1 loss in cancer cells induces an increase in mammary tumor growth and metastasis.

To understand the molecular function of NR1D1, we analyzed the global gene expression pattern in mammary tumors from Nr1d1 KO;PyMT mice and their control littermates by RNA-seq. We identified a strong differential pattern: that is, a total of 818 genes were significantly upregulated, whereas 1,325 genes were downregulated in the Nr1d1 KO;PyMT mammary tumors compared with control tumors (Fig. 3A and B; Supplementary Fig. S2A). Gene Ontology biological process (GOBP) revealed that the most enriched gene set was signal transduction in response to DNA damage, consistent with our previous observation of the role of NR1D1 in the regulation of DDR (Fig. 3C; ref. 24). Notably, the top 10 GOBP enriched in Nr1d1 WT;PyMT tumors included regulation of T cell–mediated immunity and T-cell proliferation and activation (Fig. 3C and D; Supplementary Fig. S2B). To elucidate the role of NR1D1 in cancer cells, we established NR1D1 KO-MDA-MB-231 sublines using the CRISPR-Cas9 system (Supplementary Fig. S2C). We analyzed alteration of global gene expression pattern in the NR1D1 KO cells. Depletion of NR1D1 induced a marked shift in the transcriptomic profile, with a total of 326 genes significantly upregulated and 501 genes downregulated (Fig. 3E). Gene Ontology enrichment analyses showed that the biological processes of inflammatory responses and innate immune responses were significantly downregulated by depleting NR1D1 (Fig. 3F; Supplementary Fig. S2D). The STRING-generated interaction network revealed interactive clusters, such as the cytosolic DNA-sensing pathway, response to type I IFN, and regulation of T-cell activation (Fig. 3G). These results suggest that NR1D1 may have a role in type I IFN–mediated immune activation during the progression of breast cancer.

Therefore, we hypothesized that NR1D1-induced DNA repair impairment leads to the activation of cGAS-STING signaling and T cell–mediated immunity. To test this hypothesis, we first evaluated the degree of DNA repair by γH2AX staining in the tumor sections from Nr1d1 KO;PyMT mice and control mice. Consistent with our previous report, the number of γH2AX-positive cells was lower in the mammary glands and lung-metastasized tumors of Nr1d1 KO;PyMT than control mice (Fig. 4A; ref. 24). The differences were not observed in the mammary glands of Nr1d1 KO and control mice without crossing to the PyMT model, suggesting that NR1D1 may affect DDR particularly under conditions of DNA damage (Supplementary Fig. S3A). The level of PicoGreen-stained cytosolic DNA was lower in the tumors of Nr1d1 KO;PyMT mice than control mice (Fig. 4B). The amount of cGAMP, produced by cGAS in response to cytosolic DNA, was lower in Nr1d1 KO;PyMT tumors compared with control tumors (Fig. 4C). The levels of phosphorylated STING (pSTING), IFNα, and IFNβ were lower in the tumors of Nr1d1 KO;PyMT mice than control mice (Fig. 4D; Supplementary Fig. S3B). Next, we examined the immune status of the TME including immune infiltration in the mouse model. Significant decreases in the numbers of infiltrated CD3⁺ T lymphocytes, CD8⁺ T cells, and intratumoral NK1.1⁺ NK cells were observed in the mammary and lung metastatic tumors of Nr1d1 KO;PyMT mice (Fig. 5A). Consistent with IHC data, flow cytometry showed a significant decrease in the percentages of CD3⁺ T lymphocytes, CD8⁺ T cells and NK cells, and a higher CD4⁺/CD8⁺ ratio in Nr1d1 KO;PyMT tumors compared with control tumors (Fig. 5B; Supplementary Fig. S4). However, the relative numbers of tumor-associated neutrophils (TAN), tumor-associated macrophages (TAM), and regulatory T cells (Treg) were higher in Nr1d1 KO;PyMT than in Nr1d1 WT;PyMT tumors (Fig. 5B). Analyses of tumor tissues from Py230 orthotopic allografted mice showed that the expression of pSTING and IFNβ, and infiltration of CD8⁺ T cells were lower in Nr1d1 KO-Py230 tumors, irrespective of Nr1d1 expression in the host mice, confirming the importance of Nr1d1 in tumor cells (Supplementary Fig. S5). Taken together, these data suggest that NR1D1 deficiency induces DNA damage–induced cGAS-STING signaling pathway in mammary gland and lung metastatic tumors, which promote antitumor immunity.

To demonstrate the direct role of NR1D1 in inducing STING signaling, we analyzed DDR and STING signaling in the NR1D1 KO-MDA-MB-231 cells. First, we confirmed the role of NR1D1 in DNA repair by showing that the number of oxidative stress–induced γH2AX foci was far less in NR1D1 KO cells compared with control cells (Fig. 6A; ref. 24). The level of cytosolic DNA increased consistently after hydrogen peroxide (H₂O₂) or doxorubicin treatment of the control cells but was lower in the NR1D1 KO cells (Fig. 6B). Phosphorylation of STING and its downstream proteins, such as TBK1 and IRF3, increased after H₂O₂ or doxorubicin treatment of control but not NR1D1 KO cells (Fig. 6C; Supplementary Fig. S6A). We also found that the levels of IFNα, IFNβ, CCL5, and CXCL10 were increased after H₂O₂ or doxorubicin treatment of control cells, but were barely increased in NR1D1 KO cells (Fig. 6D; Supplementary Fig. S6B). The levels of chemokines induced by cisplatin were lower in the NR1D1 KO cells compared with control cells (Supplementary Fig. S6B). Depletion of cGAS or STING attenuated the H₂O₂-induced expression of chemokines, indicating that the effects were cGAS/STING dependent (Supplementary Fig. S6C). The SKBR3 sublines that lacked NR1D1 showed similar results (Supplementary Fig. S7A–S7D). Taken together, these results show that NR1D1 activates DNA damage–induced STING signaling in breast cancer cells.

The function of NR1D1 is modulated by its ligands; therefore, we examined the effects of GSK4112 and SR9009, two well-known NR1D1 ligands, on the activation of STING-mediated type I IFN signaling in mammary tumors (34). Treatment with these ligands increased the expression of type I IFNs, CCL5, and CXCL10 in MDA-MB-231 cells, but expression was lower in NR1D1 KO-MDA-MB-231 cells (Supplementary Fig. S8). These results demonstrated that GSK4112 and SR9009 increased STING-mediated type I IFN production in an NR1D1-dependent manner. Administration of SR9009 (100 mg/kg) significantly delayed tumor onset and reduced tumor weight in Nr1d1 WT;PyMT mice, whereas it did not have this effect on Nr1d1 KO;PyMT mice (Fig. 7A). Lung metastatic burden and the numbers of metastatic nodules and were markedly reduced in Nr1d1 WT;PyMT mice but not in Nr1d1 KO;PyMT mice after administration of SR9009 (Fig. 7B). IHC staining showed that the number of cells with γH2AX foci, pSTING, IFNα, or IFNβ increased in the SR9009-treated group only in Nr1d1 WT;PyMT mice (Fig. 7C; Supplementary Fig. S9). Furthermore, administration of SR9009 promoted tumor infiltration of CD3⁺ T cells, CD8⁺ T cells, and NK cells in Nr1d1 WT;PyMT mice, but not in Nr1d1 KO;PyMT mice (Fig. 7C; Supplementary Fig. S9). These results indicate that NR1D1 agonists enhance type I IFN–mediated antitumor immunity in an NR1D1-dependent manner.

To date, several mechanisms underlying the antitumor effect of NR1D1 have been suggested in various cancer types. Activation of NR1D1 by synthetic agonists cause cancer cell death by suppressing de novo lipogenesis and autophagy in breast cancer, melanoma, and small-cell lung cancer (23, 35). NR1D1 suppresses the growth of ovarian cancer cells by inhibiting the JAK/STAT3 signaling pathway (36). However, these studies had limitations in exploring the immune system since the antitumor effects of NR1D1 were examined in a xenograft model with immunodeficient mice. Here, we explored the role of NR1D1 in spontaneous tumors that developed in MMTV–PyMT mice with an intact immune system. We demonstrated that deletion of Nr1d1 markedly suppressed immune cell infiltration and activation, accompanied by enhanced tumor growth and metastasis. In line with our previous findings that NR1D1 inhibits DNA repair against DNA damage induced by oxidative stress or DNA-damaging agents (24, 37), NR1D1 probably elicited antitumor T-cell response by inhibiting DNA repair. Because the mechanism of NR1D1 in inhibiting DNA repair involves its recruitment to DSB sites, thereby hindering the recruitment of DDR factors, NR1D1 might also have a nongenomic function aside from its genomic transcriptional repressor function. The coregulation of genomic and nongenomic actions are crucial and common for the full response of nuclear receptors, such as steroid hormone, thyroid, and retinoic acid receptors (38–40). Interestingly, NR1D1-induced type I IFN expression was observed only in breast cancer cells but not in MCF10A nontumorigenic breast epithelial cells (Supplementary Fig. S10). In addition, the level of γH2AX in normal mammary gland was not significantly different between Nr1d1 WT and KO mice, contrary to what observed in the tumor sections of Nr1d1 WT;PyMT and KO;PyMT mice (Supplementary Fig. S3A). Cancer cells are highly burdened by genomic instability and replication stress, which cause genome-wide DNA damage; therefore, the role of NR1D1 in inhibiting DNA repair is predominant in cells with hyperdependent on DDR signaling, especially breast cancer cells with mutations of BRCA1/2, ATM, and tumor protein 53.

As the activity of NR1D1 is modulated by ligands, specific ligands that pharmacologically target this nuclear receptor have been explored in various pathologic conditions including sleep disorders, inflammatory diseases, metabolic disorders, and cancer (23, 35, 41, 42). The first synthetic ligand for NR1D1, GSK4112, has been widely used as an in vitro probe of NR1D1 function, but it has limited in vivo exposure due to its poor pharmacokinetic properties (43). SR9009 and SR9011 have shown as promising pharmaceutical agents with potent in vivo activities (41). However, the specificity of SR9009 on NR1D1 regarding the cytotoxic effects on cancer cells has been controversial. Studies have demonstrated that SR9009 exerts antitumor effects through the NR1D1-mediated repression of downstream genes in multiple cancer types including glioblastoma, small-cell lung cancer, and breast cancer (23, 35). However, Dierickx and colleagues (2019) demonstrated that SR9009 reduced the viability of cancer cells and embryonic stem cells in an NR1D1-independent manner, although the mechanisms remain unknown (44). In our study, the antitumor effects of SR9009 were abolished upon administrated in Nr1d1 KO;PyMT mice, accompanied by the inactivation of STING signaling and aborted recruitment of CD8⁺ T cells and NK cells, demonstrating the NR1D1-dependent action of SR9009 (Fig. 7). We speculate that SR9009 exerts its antitumor effects through NR1D1-mediated DNA repair inhibition, since our previous study showed that GSK4112 enhanced the physical interaction of NR1D1 with PARP1, which is an essential step for the inhibition of DNA repair (24). NR1D1 ligands may induce a conformational change in NR1D1 for the optimal binding to PARP1, particularly under conditions of massive DNA damage. Recently, novel selective ligands for NR1D1, such as GSK2945 and SR12418, with more potent and better pharmacokinetic properties than SR9009, have been identified (42, 45). On the basis of our finding that NR1D1 suppresses breast cancer growth and metastasis, these NR1D1 ligands should be examined for their therapeutic potential against breast cancer, particularly in high NR1D1-expressing tumors.

Current clinical efforts are focused on developing effective immunotherapy for patients with breast cancer (46). Recently, pembrolizumab, an anti–programmed death 1 mAb, was approved by the FDA for patients with TNBC, expanding treatment options for breast cancer (47). Nevertheless, a large subset of breast cancer represents poor T-cell priming and expansion, which remains the major challenge in breast cancer immunotherapy (48). Thus, recent efforts are being made to develop strategies to enhance immunogenicity and tumor responses to immune checkpoint blockade. Several chemotherapeutic agents, such as taxanes, anthracyclines, and cyclophosphamide, as well as radiotherapy that promotes immunogenic cell death, are currently being investigated in clinical trials in combination with immunotherapy (49). Small molecules, such as STING agonists, toll-like receptor agonists, and indoleamine-2,3-dioxygenase 1 inhibitors, are also being explored as promising combination partners for immune checkpoint blockade (50). In this study, we demonstrated that NR1D1 plays a crucial role in enhancing STING-mediated type I IFN signaling, which leads to the activation and infiltration of CD8⁺ T cells into tumors and suppresses TANs, TAMs, and Tregs (Fig. 5). On the basis of our findings, we suggest that NR1D1 agonists may be good therapeutic candidates to convert immunologically “cold” to “hot” tumors that enhance breast cancer responsiveness to immunotherapy.

No disclosures were reported.

N.-L. Ka: Conceptualization, formal analysis, funding acquisition, validation, investigation, visualization, writing–original draft, writing–review and editing. M.K. Park: Conceptualization, formal analysis, validation, investigation, visualization, writing–original draft, writing–review and editing. S.-S. Kim: Data curation, investigation, visualization. Y. Jeon: Resources, methodology. S. Hwang: Investigation, methodology. S.M. Kim: Investigation, methodology. G.Y. Lim: Investigation, methodology. H. Lee: Conceptualization, supervision, funding acquisition, writing–original draft, project administration, writing–review and editing. M.-O. Lee: Conceptualization, supervision, funding acquisition, validation, writing–original draft, project administration, writing–review and editing.

This project was supported by grants from the National Research Foundation of Korea (2018R1A5A2024425, 2022R1A2C2006318, and 2022R1C1C2012270), a grant from the National Cancer Center of Korean government (2010271), and Korea Mouse Phenotyping Project (NRF-2014M3A9D5A01073556 and 2014M3A9D5A01075128).

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