Long non-coding RNA NR2F1-AS1 induces breast cancer lung metastatic dormancy by regulating NR2F1 and ΔNp63

Liu, Yingjie; Zhang, Peiyuan; Wu, Qiuyao; Fang, Houqin; Wang, Yuan; Xiao, Yansen; Cong, Min; Wang, Tingting; He, Yunfei; Ma, Chengxin; Tian, Pu; Liang, Yajun; Qin, Lun-Xiu; Yang, Qingcheng; Yang, Qifeng; Liao, Lujian; Hu, Guohong

doi:10.1038/s41467-021-25552-0

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Published: 02 September 2021

Long non-coding RNA NR2F1-AS1 induces breast cancer lung metastatic dormancy by regulating NR2F1 and ΔNp63

Yingjie Liu^1,2^na1,
Peiyuan Zhang¹^na1,
Qiuyao Wu¹,
Houqin Fang³,
Yuan Wang¹,
Yansen Xiao¹,
Min Cong¹,
Tingting Wang³,
Yunfei He¹,
Chengxin Ma¹,
Pu Tian¹,
Yajun Liang¹,
Lun-Xiu Qin⁴,
Qingcheng Yang⁵,
Qifeng Yang ORCID: orcid.org/0000-0003-0576-8513⁶,
Lujian Liao³ &
…
Guohong Hu ORCID: orcid.org/0000-0002-2980-5166^1,2

Nature Communications volume 12, Article number: 5232 (2021) Cite this article

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An Author Correction to this article was published on 07 October 2021

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Abstract

Disseminated tumor cells often fall into a long term of dormant stage, characterized by decreased proliferation but sustained survival, in distant organs before awakening for metastatic growth. However, the regulatory mechanism of metastatic dormancy and awakening is largely unknown. Here, we show that the epithelial-like and mesenchymal-like subpopulations of breast cancer stem-like cells (BCSCs) demonstrate different levels of dormancy and tumorigenicity in lungs. The long non-coding RNA (lncRNA) NR2F1-AS1 (NAS1) is up-regulated in the dormant mesenchymal-like BCSCs, and functionally promotes tumor dissemination but reduces proliferation in lungs. Mechanistically, NAS1 binds to NR2F1 mRNA and recruits the RNA-binding protein PTBP1 to promote internal ribosome entry site (IRES)-mediated NR2F1 translation, thus leading to suppression of ΔNp63 transcription by NR2F1. Furthermore, ΔNp63 downregulatio results in epithelial-mesenchymal transition, reduced tumorigenicity and enhanced dormancy of cancer cells in lungs. Overall, the study links BCSC plasticity with metastatic dormancy, and reveals the lncRNA as an important regulator of both processes.

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Introduction

Breast cancer is a major threat to women’s health, and metastasis of tumor cells into vital organs such as lung, brain, liver, and bone accounts for most deaths of breast cancer patients. During the process of metastasis, disseminated tumor cells (DTCs) often fall into a long-term of dormant stage, characterized by slow proliferation, sustained survival, and resistance to adjuvant chemotherapy, in distant organs^1,2,3. Metastatic dormancy represents a menace in the clinic as solitary tumor cells or foci can exist for months, years, or even decades without being detected while with the possibility to reactivate and lead to tumor recurrence^4,5. The clinical importance of tumor dormancy has long been recognized^6,7,8,9,10. A number of elegant studies have revealed some tumor-intrinsic factors, including p38, TGFβ, and NF2F1, which regulate the dormant state of cancer cells^{11,12,13,14,15,16,17}. The tumor microenvironment has also been shown to influence the dormancy and reactivation of disseminated cancer cells^{15,16,17,18,19,20}. However, the mechanisms regulating metastatic dormancy are far from being completely understood. In particular, it is intriguing why the tumor cells fall into proliferation arrest after aggressive growth and spreading at the primary sites, and what causes their reactivation thereafter.

Previous studies have noticed that dormant tumor cells might recapitulate normal stem cells for the themes of regulation of growth arrest and prolonged pluripotency^4,21. Recently the parallels of dormant DTCs to cancer stem-like cells (CSCs) have also been discussed^22,23. More importantly, dormant tumor cells retain the capacity to initiate new tumors, a defining feature of CSCs, after a long term of quiescence. It has been reported that latent metastatic cells of breast cancer were enriched for the CD44^highCD24^low population²⁰, a typical profile of CSCs in breast cancer. However, it was also observed that the stromal bone morphogenetic protein (BMP) produced by lung resident cells induces the dormancy of DTCs via impairing their stemness, while the BMP inhibitor COCO enhances the stem-like traits of latent cells and reactivates these cells¹². Additional studies also showed that the acquisition of stem cell properties is crucial for the colonization and outgrowth of DTCs^24,25. Therefore, the current understanding of the relationship between metastatic dormancy and cancer stemness is seemingly inconsistent, and additional work is necessary to elucidate the role of CSCs in metastatic dormancy and reactivation.

In fact, CSCs, which refer to the minor subpopulation of heterogeneous tumor cells with enhanced tumor-initiating ability, could be heterogeneous in themselves. In breast cancer, CSCs were initially identified by low or negative expression of CD24 and high expression of CD44²⁶. Subsequent studies showed that high aldehyde dehydrogenase (ALDH) activity also marks breast cancer stem-like cells (BCSCs)²⁷. CD24⁻CD44⁺ BCSCs and ALDH⁺ BCSCs are largely distinct populations with mesenchymal and epithelial characteristics, respectively²⁸. Interestingly, functional studies showed that ALDH⁺ BCSCs are more proliferative and tumorigenic than CD24⁻CD44⁺ BCSCs, while ALDH⁻CD24⁻CD44⁺ mesenchymal BCSCs tend to be quiescent^27,28. This is in line with the notion that cancer cells after epithelial–mesenchymal transition (EMT) tend to be growth-arrested^29,30. These studies could indicate that CSCs heterogeneity might offer an explanation to the inconsistent observations regarding the roles of CSCs in metastatic dormancy.

Recently, lncRNAs have been found to regulate various cancer processes^31,32,33, such as EMT, proliferation, survival, and metastasis^34,35,36. The expression of a few lncRNAs has been also linked to metastatic dormancy. Gooding et al. reported the differential expression of the lncRNA BORG in dormant breast cancer cell lines^37,38. In addition, NAS1 was also found to be upregulated in the late relapse of estrogen receptor-positive (ER⁺) breast cancer and could regulate in vitro cell growth³⁹. It was also reported to regulate the progression of several other cancer types through its microRNA-sponging function^{40,41,42,43,44}. However, the functional roles of these lncRNAs in metastatic dormancy have not been validated.

In this study, we show that lncRNA NAS1 is highly expressed in mesenchymal-like BCSCs and reveal its functions to promote cancer cell dissemination and metastatic dormancy in the lungs by regulating the NR2F1-ΔNp63 axis.

Results

The mesenchymal subpopulation of BCSCs is prone to metastatic dormancy in the lungs

A number of studies have reported the heterogeneity of BCSCs. Previously we also found two CSC subpopulations in breast cancer with different CD44 staining intensities and metastatic capacities⁴⁵. By CD44 and CD24 flow cytometry, a CD24⁻CD44^med subpopulation (referred to as P1 thereafter) with positive but weak CD44 staining, and a CD24⁻CD44^high subpopulation (referred to as P2 thereafter) with stronger CD44 staining were observed in breast tumors and the isogenic MCF10 breast cancer cell line series that include MCF10AT, MCF10CA1h, and MCF10CA1a⁴⁶. Both P1 and P2 subpopulations demonstrated enhanced tumorigenic capacity as compared to the non-CSC cells, but only P1 tumors resulted in lung metastases in mice⁴⁵. Interestingly, P1 and the metastatic cell line MCF10CA1a that is enriched with P1 cells (Supplementary Fig. 1a) demonstrated epithelial morphology and expressed the epithelial marker CDH1, while P2 was mesenchymal-like with enhanced in vitro migratory and invasive properties (Supplementary Fig. 1b–e). Partial conversion from P1 to P2 cells was observed after multiple passages in serum-containing culture media, but not in serum-free media. When the cells were orthotopically injected into mice, P2 tumors also displayed higher invasive capacity (Fig. 1a) and resulted in more circulating cancer cells than P1 tumors in the blood of mice (Supplementary Fig. 1f). The less metastatic cell line MCF10CA1h, containing both P1 and P2 cells, displayed mesenchymal appearance in the majority but with occasional epithelial cell clusters (Supplementary Fig. 1a, b). In addition, we found that P1 contained a significantly higher ALDH⁺ fraction as compared to P2 (Supplementary Fig. 1g). MCF10CA1a also displayed higher ALDH activity than MCF10CA1h (Supplementary Fig. 1g, h). These observations were in line with the previous study²⁸ reporting that ALDH and CD44 mark epithelial-like and mesenchymal-like, respectively, subsets of BCSCs. Furthermore, we performed RNA-sequencing profiling of MCF10CA1h and its P1 and P2 subpopulations (named as CA1h-P1 and CA1h-P2 thereafter), as well as MCF10CA1a, followed by gene set enrichment analysis (GSEA). The analyses showed that the previously reported epithelial-like BCSC (E-BCSC) signature and mesenchymal-like BCSC (M-BCSC) signature²⁸ were enriched in the metastatic (MCF10CA1a and CA1h-P1) and less metastatic (MCF10CA1h and CA1h-P2) cells, respectively (Supplementary Fig. 1i).

**Fig. 1: The P2 BCSC subpopulation displays a dormant phenotype in the lungs.**

Since mesenchymal-like P2 cells display higher capacities of migration, invasion, and dissemination but are less lung-metastatic than the epithelial-like P1 cells⁴⁵, we sought to analyze the post-dissemination process of metastasis for these cells. MCF10CA1a and MCF10CA1h, as well as CA1h-P1 and CA1h-P2, were labeled with firefly luciferase and GFP, and intravenously inoculated into athymic mice for analysis of lung metastasis. The proliferation of tumor cells seeded in the lungs was analyzed by 5-ethynyl-2′-deoxyuridine (EdU) labeling 24 h prior to lung harvest. It was observed that more GFP⁺ MCF10CA1h and CA1h-P2 cells were seeded in lungs compared with MCF10CA1a and CA1h-P1, respectively, after intravenous inoculation (Fig. 1b, c). However, lower percentages of MCF10CA1h and CA1h-P2 cells were active in proliferation at different time points of the early stage of colonization (Fig. 1b, c). Concordantly, in vitro analysis showed that although these cells only displayed minor differences of cell cycle distribution in nutrition-sufficient culture (Supplementary Fig. 2a), significantly more CA1h-P2 cells were arrested in G0/G1 phases than CA1h-P1 in serum-free culture (Supplementary Fig. 2b). Long-term metastasis monitoring by bioluminescent imaging (BLI) of the mice also showed the steady growth of CA1h-P1 tumors in lungs after the initial seeding phase, while the signals of CA1h-P2 cells remained almost unchanged after 18 weeks albeit with a stronger initial intensity (Fig. 1d). Significantly more mice inoculated with MCF10CA1a and CA1h-P1 cells developed lung metastasis in the end (Fig. 1e), with apparent tumor nodules in the lung surface (Fig. 1f) and aggressive tumor areas in the lung sections (Fig. 1g), while MCF10CA1h and CA1h-P2 remained as single cells or small foci for 20 weeks (Fig. 1g, h), and led to much fewer tumor nodules (Fig. 1f). These results showed that MCF10CA1h and CA1h-P2, rather than MCFCA1a or CA1h-P1, display a dormant phenotype in the lungs.

NR2F1-AS1 is upregulated in latent cells and promotes metastatic dormancy

Then we compared the RNA sequencing profiles between the lung-dormant cells (MCF10CA1h and CA1h-P2) and the lung-metastatic cells (MCF10CA1a and CA1h-P1), as well as MCF10AT, which forms the only carcinoma in situ and cannot disseminate to lungs in mice⁴⁶. We primarily focused on lncRNAs whose roles were barely explored in metastatic dormancy and identified 18 upregulated and 7 downregulated lncRNAs in the lung-dormant cells (Fig. 2a). Notably, NR2F1-AS1 (termed as NAS1 thereafter), located upstream of the protein-encoding gene NR2F1 but transcribed in the opposite direction, was among the upregulated lncRNAs. In addition, analysis of a triple-negative breast cancer clinical cohort⁴⁷ showed that NAS1 was upregulated in late-recurring tumors (relapsed after 2 years following diagnosis) than the tumors that relapsed within the first 2 years after diagnosis (Supplementary Fig. 3a). The latest study by Sanchez Calle et al.³⁹ also reported the correlation of NAS1 expression to late recurrence of ER⁺ breast cancer. Re-analysis of the ER⁺ cohort in this study confirmed the upregulation of NAS1 in the late relapse of breast cancer (Supplementary Fig. 3b). Furthermore, fluorescence in situ hybridization analyses of NAS1 showed NAS1 was expressed in primary tumors and small tumor cell clusters in the lungs of MCF10CA1h, but not in the large lung metastatic nodules of the cells (Supplementary Fig. 3c). These results indicated an association of NAS1 expression with relapse latency.

**Fig. 2: *NR2F1-AS1* (*NAS1*) promotes metastatic dormancy of breast cancer.**

Bioinformatic analyses by PhyloCSF⁴⁸ and Coding Potential Calculator⁴⁹ both confirmed the lack of coding potential of NAS1 (Supplementary Fig. 4a, b). Therefore, we performed 5′ and 3′ rapid amplification of cDNA ends (RACE) assays of NAS1 (Supplementary Fig. 4c) and discovered its full length of 2956 bp (Supplementary Table 1), which was consistent with that shown by Northern blotting of NAS1 (Fig. 2b). We also analyzed the subcellular distribution of NAS1 and observed uniform expression in both the cytoplasm and nucleus of the cancer cells (Supplementary Fig. 4d). Importantly, quantitative polymerase chain reaction (qPCR) analyses confirmed the elevated expression of NAS1 in lung-dormant MCF10CA1h and CA1h-P2 cells (Supplementary Fig. 4e, f).

To study the role of NAS1 in metastatic dormancy, we knocked down NAS1 with short hairpin RNAs (shRNAs) in CA1h-P2 (Fig. 2b and Supplementary Fig. 4g). NAS1 knockdown resulted in transcriptomic changes of CA1h-P2 toward the P1-like state as shown by GSEA analysis (Supplementary Fig. 5a), and promoted the proliferation of CA1h-P2 cells under nutrient stress (Supplementary Fig. 5b). Importantly, when the cells were intravenously inoculated into nude mice, we observed fewer GFP⁺ cancer cells initially seeded in the lungs after NAS1 knockdown, but these cells were more proliferative (Fig. 2c), leading to enhanced metastatic outgrowth and significantly more metastatic nodules, instead of solitary tumor cells, in lungs after 4 months (Fig. 2d, e). In contrast, NAS1 overexpression in MCF10AT and CA1h-P1 (Supplementary Fig. 4g) enhanced initial cancer cell seeding in lungs, but reduced the proliferation of seeded tumor (Fig. 2f), resulting in persistent single tumor cells in lungs and fewer metastatic tumor nodules in the end (Fig. 2g, h). To further analyze the role of NAS1 in the entire metastasis process, NAS1 was overexpressed in 4175-LM2 (Supplementary Fig. 4g), a lung-metastatic subline of MDA-MB-231 breast cancer cells⁵⁰, followed by orthotopic injection of the cells into the mammary fat pad of mice. Subsequent analysis showed that NAS1 enhanced the local invasion of the tumors (Fig. 2i), but resulted in more long-term solitary tumor cell foci and fewer metastatic nodules in the lungs (Fig. 2j, k). These data suggested that NAS1 promotes the metastatic seeding of tumor cells, but inhibits their proliferation for metastatic outgrowth, leading to the dormancy of breast cancer cells in lungs.

NAS1 promotes EMT and invasion but inhibits the tumor-initiating capacity of cancer cells

To analyze why NAS1 promotes cancer cell seeding but inhibits metastatic outgrowth in the lungs, we firstly analyzed the EMT status and invasiveness of cancer cells. NAS1 knockdown in CA1h-P2 CSC subpopulation partially induced mesenchymal–epithelial transition (MET), as shown by cellular morphology and expression of various EMT markers (Fig. 3a and Supplementary Fig. 5c, d), accompanied by decreases in cell migration, invasion, and resistance to anti-proliferative drugs including paclitaxel and doxorubicin (Supplementary Fig. 5e–h). Furthermore, orthotopic xenograft tumors of CA1h-P2 showed less invasion into the para-tumor stroma after NAS1 knockdown (Supplementary Fig. 5i). In the epithelial MCF10AT cells, NAS1 overexpression resulted in EMT changes (Fig. 3a and Supplementary Fig. 5j, k), together with elevated migratory and invasive capacities of the cells (Supplementary Fig. 5l, m). Importantly, NAS1 overexpression in MCF10CA1a followed by orthotopic injection of the cells into mice resulted in more circulating tumor cells in the blood of mice, indicating enhanced tumor dissemination (Supplementary Fig. 5n). In addition, we also observed that NAS1 knockdown led to CD44 downregulation but ALDH upregulation in CA1h-P2 cells, while NAS1 overexpression promoted the transition of ALDH⁺ cells, previously known as the epithelial-like CSCs²⁸, to the CD44^high mesenchymal-like CSCs in MCF10AT (Fig. 3b–e), corroborating the EMT-promoting role of NAS1.

**Fig. 3: *NAS1* promotes EMT but inhibits tumorigenicity of breast cancer cells.**

Metastatic outgrowth requires the capacity of disseminated cancer cells to initiate a new tumor. Thus, we further assessed the role of NAS1 in tumor initiation. NAS1 knockdown significantly increased the capacity of CA1h-P2 to form three-dimensional tumorspheres (Fig. 3f). More importantly, limiting dilution assays of tumorigenesis showed that NAS1 knockdown greatly increased the in vivo tumor initiation, as well as tumor growth of CA1h-P2 (Fig. 3g, h). In contrast, NAS1 overexpression in MCF10AT impaired tumorsphere formation (Fig. 3i). Similar results were also observed in MCF7, in which NAS1 activation by CRISPR/Cas9 synergistic activation mediator (SAM)⁵¹ reduced tumorsphere formation (Supplementary Fig. 5o). In addition, NAS1 overexpression in MCF10CA1a (Supplementary Fig. 4g) diminished the tumorigenic capacity of cells in mice (Fig. 3j), as well as the rate of tumor recurrence after surgical removal of the primary tumors (Fig. 3k). Overall, these data suggested that NAS1 promotes cancer cell traits prerequisite for tumor spreading and dissemination, including EMT, migration, and invasion, but inhibits the capacity to initiate new tumor growth, thus leading to post-dissemination dormancy.

NAS1 promotes dormancy by upregulating NR2F1

Then we interrogated the molecular mechanism of NAS1 in the regulation of metastasis. We firstly focused on the gene NR2F1, which is located in proximity to NAS1 and encodes a transcription factor known to promote tumor dormancy^14,16,52,53. We found that NR2F1 was also differentially expressed in the MCF10cells with varied metastatic capacities and, importantly, was upregulated by NAS1 (Fig. 4a). On the contrary, the expression NAS1 was not affected by NR2F1 in cancer cells (Supplementary Fig. 6a, b). In addition, NR2F1 overexpression showed a NAS1-mimicking effect to induce cellular EMT (Fig. 4b) and a shift from ALDH⁺ to CD44^high cell population (Fig. 3c, e), together with inhibition of tumorsphere formation (Fig. 4c) in multiple cell lines.

**Fig. 4: *NAS1* suppresses breast cancer lung metastasis by NR2F1.**

To further validate that NR2F1 acts downstream of NAS1 in the regulation of metastatic dormancy, NR2F1 was overexpressed in CA1h-P2 cells with NAS1 knockdown. NR2F1 efficiently restored the mesenchymal-like phenotype of these cells (Fig. 4d). In addition, NR2F1 reduced the ALDH⁺ content and tumorsphere-forming capacity of the cells that were enhanced by NAS1 knockdown (Fig. 4e, f). More importantly, when CA1h-P2 cells were inoculated into the mice, NR2F1 overexpression abrogated the effect of NAS1 knockdown and inhibited tumor cell proliferation after seeding (Fig. 4g), leading to reduced metastatic outgrowth and formation of tumor nodules in lungs (Fig. 4h, i). Reciprocally, NR2F1 knockdown in MCF10CA1a cells with NAS1 overexpression resulted in reverse of NAS1-induced EMT changes (Supplementary Fig. 7a). Tumorsphere formation and ALDH⁺ fraction of the cancer cells that were impaired by NAS1 were also rescued by NR2F1 knockdown (Supplementary Fig. 7b, c). These data suggested that NAS1 promotes metastatic dormancy of breast cancer by regulating NR2F1.

NAS1 and PTBP1 cooperatively enhance the IRES activity of NR2F1-5′UTR

To further explore how NAS1 regulates NR2F1 expression, we performed RNA pulldown assays of NAS1, followed by mass spectrometry (MS) analyses either directly and after sodium dodecyl sulfate-polyacrylamide gel electrophoresis of the pulldown elution (Supplementary Fig. 8a), to identify the proteins interacting with NAS1. Among the NAS1-bound proteins (Supplementary Table 2), polypyrimidine tract-binding protein 1 (PTBP1) ranked as a top candidate that was abundantly and consistently enriched by NAS1 pulldown. NAS1 pulldown of PTBP1 was verified by Western blotting (WB) (Fig. 5a). Further analyses with various truncations of the NAS1 sequence showed that it was the 3′ fragment of NAS1 that was bound to PTBP1 (Supplementary Fig. 8b, c). In addition, NAS1 RNA was detected in the immunoprecipitates of PTBP1 by RNA immunoprecipitation (RIP) assays, further demonstrating the binding of NAS1 to PTBP1 (Fig. 5b). Notably, PTBP1 was expressed in both cytoplasm and nucleus of MCF10CA1h (Supplementary Fig. 8d), a pattern similar to NAS1 expression (Supplementary Fig. 4d).

**Fig. 5: *NAS1* and PTBP1 cooperatively enhance the IRES function of *NR2F1*-5′UTR.**

Thus we analyzed the function of PTBP1 in NR2F1 expression. Overexpressing PTBP1 in MCF10AT upregulated NR2F1 while interfering PTBP1 by siRNAs obviously decreased the protein level of NR2F1 in MCF10CA1h (Supplementary Fig. 8e), implying the involvement of PTBP1 in NAS1 regulation of NR2F1 expression. Indeed, PTBP1 knockdown in MCF10AT with NAS1 overexpression completely blocked the upregulation of NR2F1 by NAS1, while PTBP1 overexpression in CA1h-P2 with NAS1 knockdown recovered the protein level of NR2F1 (Fig. 5c), affirming that PTBP1 mediates the function of NAS1 in NR2F1 regulation.

Then we analyzed how PTBP1 regulates NR2F1 expression. Previous studies showed that PTBP1 could bind to gene promoter regions to regulate transcription⁵⁴, or bind to the polypyrimidine regions of mRNAs to regulate post-transcriptional processes including alternative splicing^55,56, mRNA decay⁵⁷, and IRES-dependent translation^58,59,60. We first tested the effect of PTBP1 and NAS1 on NR2F1 promoter via luciferase reporter assays and found that NR2F1 promoter activity was not obviously changed by either PTBP1 or NAS1 (Supplementary Fig. 8f). Chromatin immunoprecipitation (ChIP)-qPCR analysis also detected no binding of PTBP1 on NR2F1 promoter (Supplementary Fig. 8g), hence excluding the possibility of PTBP1 regulation of NR2F1 promoter activity.

Alternatively, RIP assays showed that NR2F1 mRNA was bound by PTBP1 (Fig. 5d). The MS2–GFP fusion protein immunoprecipitating assays of MS2-tagged NAS1 also showed the binding of NAS1 RNA to NR2F1 mRNA (Fig. 5e). Truncation analysis of NAS1 further revealed the preferential binding of NR2F1 mRNA to the 5′ fragment of NAS1 RNA (Supplementary Fig. 8b, h). Together with the above observations of PTBP1–NAS1 interaction (Fig. 5a, b), these data demonstrated the interactions between each pair of PTBP1 protein, NAS1 RNA, and NR2F1 mRNA. In addition, we found that NAS1 knockdown impaired the binding of PTBP1 and NR2F1 mRNA (Fig. 5f and Supplementary Fig. 8i). In contrast, PTBP1 inhibition led to no obvious changes in the amount of NR2F1 mRNA pulled down by NAS1 (Fig. 5g and Supplementary Fig. 8j). Thus, these data indicated that NAS1 promotes the binding of PTBP1 and NR2F1 mRNA.

We then analyzed how NAS1 and PTBP1 regulate NR2F1 mRNA. We identified four possible splicing variants of NR2F1 in the RNA-sequencing data of CA1h-P2 cells, but the expression levels of none of these variants were obviously changed by NAS1 knockdown (Supplementary Fig. 8k), excluding the possibility that NAS1 regulates alternative splicing of NR2F1 mRNA. We also tested the stability of NR2F1 mRNA by treating cells with actinomycin D and found no effects by NAS1 overexpression or knockdown (Supplementary Fig. 8l). Then we noticed multiple polypyrimidine regions in the 5′UTR of NR2F1 mRNA and thus speculated that PTBP1 and NAS1 might facilitate the IRES function of NR2F1-5′UTR. To verify this hypothesis, we constructed an IRES activity reporter plasmid (Fig. 5h) and cloned the full 1.8 kb 5′UTR sequence upstream of AUG of NR2F1 mRNA and its two truncations, the 0.8 kb polypyrimidine region (termed as 5′UTR-PT) and the rest 1.0 kb region that is GC-rich (termed as 5′UTR-GC) (Supplementary Table 3) into the plasmid (Fig. 5h). IRES reporter assays revealed that the full 5′UTR had a mild activity to initiate translation. Interestingly, 5′UTR-PT showed a much stronger IRES activity. On the contrary, 5′UTR-GC has no IRES activity at all (Fig. 5i). To confirm that such an effect of 5′UTR-PT to activate the downstream gene is due to regulation of translation rather than transcription, we also assessed the potential promoter activity of these regions using the pGL3 reporter. Although mild promoter activities of 5′UTR and 5′UTR-GC were detected, 5′UTR-PT had no ability to initiate transcription (Supplementary Fig. 8m). Therefore, these data suggested that the polypyrimidine region of NR2R1 5′UTR possesses an innate IRES activity, while the existence of downstream GC-rich sequence hinders such activity for mRNA translation.

Interestingly, bioinformatic analyses with protein–RNA and RNA–RNA interaction-predicting tools (catRAPID⁶¹ and IntaRNA^62,63,64,65) suggested that PTBP1 and NAS1 bind to the polypyrimidine and GC-rich regions, respectively, of NR2F1-5′UTR (Fig. 5j). RIP and RNA pulldown assays with various NR2F1 mRNA areas confirmed that NAS1 RNA preferentially bound to 5′UTR-GC (Fig. 5k), and PTBP1 specifically interacted with 5′UTR-PT but not other regions, including 5′UTR-GC, CDS or 3′UTR of NR2F1 mRNA (Fig. 5l). Importantly, PTBP1 inhibition led to the suppression of 5′UTR-PT IRES activity (Fig. 5m). Reciprocally, NAS1 overexpression could enhance IRES activity of 5′UTR, but such regulation is dependent on the presence of the GC-rich region. The strong IRES activity of 5′UTR-PT was not affected by NAS1 (Fig. 5n). Taken together, these data indicated that PTBP1 binds to the polypyrimidine region of NR2F1-5′UTR to initiate IRES activity, but the NR2F1 translation process is suppressed by the downstream GC-rich region. Such suppression can be relieved by the binding of NAS1, probably by remodeling of the RNA structure formed in this GC-rich area (Fig. 5o).

NR2F1 represses the expression of ΔNp63

We continued to analyze the downstream molecular events of NAS1–NR2F1 to promote tumor cell dormancy, by RNA-sequencing analysis of cancer cells after NAS1 knockdown or NR2F1 overexpression. Among the genes commonly regulated by both NAS1 and NR2F1 (Fig. 6a and Supplementary Table 4), the microRNA miR-205 and the TP63 gene variant ΔNp63, which is a transcriptional regulator of miR-205^66,67, were noticed. miR-205 is known to suppress EMT of tumor cells by targeting ZEB1 and SIP1⁶⁸. ΔNp63 is a marker of epithelial stem cells with well-studied functions to regulate cell stemness by activating signaling pathways including WNT⁶⁹ and NOTCH⁷⁰ and to maintain the epithelial feature of cells by activating miR-205⁶⁷. Our analyses showed that expression of both miR-205 and ΔNp63 was significantly suppressed by NAS1 and NR2F1 (Fig. 6a), which was further confirmed by qPCR and WB assays (Fig. 6b–d). In addition, NR2F1 completely blocked the upregulation of ΔNp63 by NAS1 knockdown in CA1h-P2 cells (Fig. 4d). PTBP1 also suppressed the expression of ΔNp63 (Supplementary Fig. 8e).

**Fig. 6: NR2F1 mediates the role of *NAS1* in dormancy by inhibiting *ΔNp63* transcription.**

Thus, we investigated the role of ΔNp63 in NAS1-induced EMT and suppression of tumorigenicity. ΔNp63 inhibition by a reported shRNA⁶⁹ in CA1h-P2 cells with NAS1 knockdown reversed the MET phenotype, leading to regain of mesenchymal morphology and marker expression (Fig. 6e and Supplementary Fig. 9a). Tumorsphere formation that was enhanced by NAS1 knockdown was also effectively suppressed by ΔNp63 shRNA (Fig. 6f). Furthermore, GSEA analysis of control and NR2F1-overexpressing MCF7 cells showed that the previously identified gene sets downregulated and upregulated by ΔNp63⁷¹ (Supplementary Table 4) were enriched in the cells with or without NR2F1 overexpression, respectively (Fig. 6g), indicating that NR2F1 adversely affects the downstream genes of ΔNp63. ChIP-qPCR analysis showed the binding of NR2F1 on ΔNp63 promoter (Fig. 6h). NR2F1 inhibition led to the activation of ΔNp63 promoter activity (Supplementary Fig. 9b), suggesting the direct regulation of ΔNp63 by NR2F1. Altogether, these data demonstrated that NR2F1 mediates the dormant-promoting function of NAS1 by inhibiting the expression of ΔNp63.

In addition, we found that ΔNp63 activated miR-205 expression while ΔNp63 knockdown inhibited miR-205 expression in breast cancer cells (Supplementary Fig. 9c, d), corroborating previous reports showing that ΔNp63 transcriptionally regulates miR-205⁶⁶. Importantly, NAS1 and NR2F1 inhibited the expression of miR-205, while the effect of NAS1 on miR-205 was effectively blocked by ΔNp63 (Supplementary Fig. 9c–e), indicating that NAS1 regulates miR-205 by suppressing ΔNp63. Furthermore, miR-205 inhibition restored the mesenchymal phenotype of CA1h-P2 cells with NAS1 knockdown (Supplementary Fig. 9f), while treating NAS1-overexpressing MCF10AT with miR-205 mimics induced epithelial restoration of the cells (Fig. 6i and Supplementary Fig. 9g). In addition, miR-205 inhibition also blocked the MET changes of CA1h-P2 cells that were induced by NR2F1 knockdown (Supplementary Fig. 9h). Therefore, miR-205 acts downstream of NAS1–NR2F1–ΔNp63 signaling axis to regulate cellular EMT.

NAS1 correlates with NR2F1, EMT markers, and reduced metastasis in human breast tumors

Finally, we assessed the clinical significance of NAS1 expression in clinical breast tumor samples. First, a positive correlation of NAS1 RNA and NR2F1 protein levels was observed in tumor samples of breast cancer patients (Fig. 7a), supporting the role of NAS1 in regulating NR2F1. Then, by analyzing the RNA sequencing data of the TCGA breast cancer cohort, we found that NAS1 significantly correlates with a wide array of EMT-related genes (Fig. 7b). A positive correlation of NAS1 with NR2F1 expression and ∆Np63 with miR-205 was also observed in the TCGA pan-cancer cohort, while the expression of NR2F1 was negatively correlated with the expression of both ∆Np63 and miR-205 (Supplementary Table 5). In the Fudan triple-negative breast cancer cohort⁴⁷, NAS1 was also positively correlated with enrichment of the previously reported M-BCSC²⁸ and EMT⁷² gene signatures, as well as a deficit of the E-BCSC signature²⁸, as shown by single-sample GSEA (ssGSEA)⁷³ (Fig. 7c). Next, analysis of 89 breast cancer samples collected from Qilu Hospital revealed that high NAS1 expression of the tumors was associated to a lower risk of metastasis and tumor relapse (Fig. 7d, e). Meanwhile, analyses of the Kaplan–Meier Plotter clinical database⁷⁴ also displayed the link of NAS1 to improved recurrence-free survival of breast cancer patients (Supplementary Fig. 10a–d). Concordantly, the expression of the gene sets upregulated by NAS1 knockdown or NR2F1 overexpression, identified by our transcriptomic sequencing analyses (Supplementary Table 4), was linked to accelerated and decelerated metastasis, respectively, in the Netherlands Cancer Institute breast cancer cohort⁷⁵ (Fig. 7f, g). Immunostaining of a breast cancer tissue microarray also revealed that NR2F1 expression was linked to improved relapse-free survival of the patients (Supplementary Fig. 10e, f). Finally, we also observed downregulation of NAS1 in breast tumors compared with the normal mammary tissues in the TCGA cohort (Supplementary Fig. 10g), supporting a role of NAS1 to suppress tumorigenicity. In summary, these data suggested that NAS1 correlates with expression of NR2F1 and EMT markers, and links to better prognosis in human clinical breast cancer.

**Fig. 7: The clinical relevance of *NAS1* expression in human breast tumors.**

Discussion

Previously NAS1 has been reported by several studies to regulate proliferation and migration of different cancer types, including hepatocellular carcinoma⁴⁰, endometrial cancer⁴¹, thyroid cancer^42,43, and osteosarcoma⁴⁴. These functions of NAS1 have been attributed to its microRNA-sponging function. A most recent study³⁹ also demonstrated the link of NAS1 expression to late recurrence of ER⁺ breast cancer. Here we not only report a role of NAS1 to promote metastatic dormancy of breast cancer, consistent with the recent study³⁹ but also reveal a previously unidentified functional mechanism of NAS1, by which NAS1 binds to the GC-rich 5′UTR area of NR2F1 mRNA and recruits PTBP1 to enhance the IRES-dependent translation of NR2F1. Further NR2F1 suppresses ΔNp63 expression, leading to cellular EMT changes and impaired tumorigenicity (Fig. 7h). NR2F1 plays a well-established role in dormancy. It has been shown to induce cancer cell quiescence and tumor dormancy in various cancer types including breast cancer, prostate cancer, and head and neck squamous cell carcinoma^14,16,53. Clinical analyses also demonstrated the correlation of NR2F1 expression to the dormancy of human tumors^14,52. Our study corroborates these reports and reveals a unique mechanism of NR2F1 in metastatic dormancy. Notably, our data indicate that both NAS1 and NR2F1 play dual roles in cancer to promote tumor invasion but inhibit proliferation, which is seemingly conflicting for cancer progression but actually both contribute to the accumulation of dormant DTCs in metastatic organs. The link of NAS1 expression to the improved prognosis of cancer patients is likely attributed to its anti-proliferation role, which results in tumor suppression in the primary site and metastatic dormancy in secondary organs, but not the pro-dissemination effect of NAS1. These findings will deepen our understanding of the roles of lncRNAs and NR2F1 in metastatic dormancy.

Importantly, our study demonstrates a scenario, by mesenchymal-like tumor cells in particular, of dormancy amid the multi-step process of metastasis. These cells are equipped with all the traits for leaving the primary tumors and arriving at the new organs, including migration, invasion, and resistance to adjuvant chemotherapy, but they are less capable to initiate a new tumor and colonize the target organs. This will lead to the accumulation of solitary tumor cells or small foci in secondary organs, i.e., metastatic dormancy. Other types of cells, either not capable of tumor dissemination (such as MCF10AT) or prone to active proliferation once reaching the new sites (such as MCF10CA1a), will not demonstrate such a dormant stage of metastasis. It has been speculated that EMT may cause dormancy³⁰. Our data provide the evidence for such speculation and also recall previous studies showing that metastatic colonization of mesenchymal tumor cells requires the reversal to epithelial type^24,25,76 and that epithelial-like circulating tumor cells are the culprit of tumor metastasis^77,78.

Our study will also help delineate the role of CSCs in metastatic dormancy. As metastatic growth from single DTCs is essentially the tumor-initiating feature of CSCs, activation from dormancy is often thought to be accompanied by gain of stem-like characteristics^8,12. However, some studies also indicate dormant cells are CSCs due to the similar phenotypes and shared mechanisms of these two cell types in slow cell cycle, drug resistance, and long-term survival^22,23. This apparent contradiction could be reconciled by the heterogeneity of CSCs. Our data suggest that the mesenchymal-like CD24⁻CD44^high BCSCs are prone to tumor dissemination and dormancy, while the epithelial-like ALDH⁺ BCSCs are metastasis-competent and represent awakening from dormancy. This model is also consistent with previous findings that dormant breast cancer cells are enriched of the CD44^highCD24^low population²⁰ and that the CD44^highCD24^low profile defines the mesenchymal type of BCSCs which are relatively less tumorigenic than the ALDH⁺ BCSCs^27,28. In addition, tumor initiation and drug resistance have been often considered as the two defining features of CSCs. However, studies of CSC heterogeneity indicate that these two features might be separate in different CSC subsets, although it could still hold true that CSCs as a whole population is more aggressive in both tumorigenicity and drug resilience than non-CSCs. This is particularly noteworthy to reconsider how to define CSCs using in vitro or in vivo assays, and how to target CSCs for precision medicine.

The deadly metastasis results from the accumulation of multiple aggressive features of tumor cells including proliferation and motility. However, previous seminal studies^79,80,81 have shown that these two features may not be simultaneously present, or even be mutually exclusive in the same tumor cells. Our data re-emphasize such a notion and unravel a dual-role molecular route for such mutual exclusivity. Importantly, the segregation of proliferative and migratory features of tumor cells might underlie the phenomenon of metastatic dormancy in which migratory cancer cells cease metastatic growth after dissemination, while reactivation from dormancy requires the switch of tumor cells back to the proliferative state. Understanding the dynamics of proliferative and migratory states of tumors may provide opportunities to target dormant cancer cells and keep them from regaining the growing momentum.

Methods

Constructs and reagents

The sequences of primers used in this work were provided in Supplementary Table 6. The full length of human NR2F1-AS1 (NAS1) was determined by RACE and cloned into the pLVX-CMV-PGK-puro vector, and the open reading frames of NR2F1, PTBP1 and ΔNp63 with the HA tag at 3′ end were inserted into pLVX-CMV-IRES-puro/blasticidin for overexpression. For NAS1 knockdown, shRNAs were designed with the online software sfold⁸², then the annealed sense and antisense oligonucleotides were cloned into the BglII and HindIII sites of pSuper-Retro-hygro (Oligo Engine). For PTBP1 and ∆Np63 knockdown, shRNAs were obtained from the MISSION shRNA library (Sigma) and a previous report⁶⁹, respectively, then annealed and cloned into the pLKO.1.puro/blasticidin vectors. PTBP1-siRNAs, miR-205 mimics and inhibitors were purchased from GenePharma. The sequences of all siRNAs and shRNAs used in this study are provided in Supplementary Table 6. The pGF plasmid was modified from pLVX-CMV-IRES-puro vector by cloning GFP into the EcoRI and XbaI sites and firefly luciferase (Fluc) into the BamHI and MluI sites. The NR2F1-5′UTR (1,802 bp) sequence was inferred according to the NCBI database and its two segments 5′UTR-PT (1–800 bp) and 5′UTR-GC (781–1802 bp) were inserted between GFP and Fluc of pGF vector for IRES activity assays. For promoter activity analysis, the −2000 to +691 sequence flanking the transcription start site of NR2F1, as well as NR2F1-5′UTR, 5′UTR-PT, and 5′UTR-GC segments, was cloned into pGL3-basic (Promega) with MluI and BglII sites. All cell lines were tested as Mycoplasma free.

For WB, flow cytometry, RIP, ChIP, immunohistochemistry (IHC), and IF analyses, the following antibodies were used: APC mouse anti-human CD24 (Biolegend, 311118, 5 µl/10⁶ cells/100 µl staining volume), FITC mouse anti-human CD44 (BD Pharmingen, 555478, 20 µl/10⁶ cells/100 µl staining volume), PE mouse anti-human CD44 (BD Pharmingen, 555479, 20 µl/10⁶ cells/100 µl staining volume), chicken polyclonal GFP antibody (Abcam, ab13970, ICC: 1/1000), Anti-GFP antibody (Abcam, ab290, RIP: 1 µl/10⁶ cells), donkey anti-Chicken IgY (FITC) secondary antibody (Invitrogen, SA172000, 1/500), E-Cadherin (24E10) rabbit mAb (Cell Signaling technology, 3195S, IF: 1/200, WB: 1/2000), N-Cadherin mouse antibody (BD Pharmingen, 610920, IF: 1/100, WB: 1/1000), Fibronectin mouse antibody (Santa Cruz, sc-59826, WB: 1:1000), Vimentin (D21H3) XP^® rabbit mAb (Cell Signaling technology, 5741S, IF: 1/100, WB: 1/1000), ZEB1 rabbit polyclonal antibody (proteintech, 21544-1-AP, WB: 1/1000), mouse anti-Twist antibody (Abcam, ab50887, WB:1/2000), Alexa Fluor 488 donkey anti-rabbit IgG (Invitrogen, A-21206, 1/1000), Alexa Fluor 555 donkey anti-mouse IgG (Invitrogen, A31570, 1/500), rabbit anti-human GAPDH (Merck/Millipore, SAB2103104, WB: 1/5000), rabbit anti-COUP TF1 (NR2F1) antibody (Abcam, ab181137, IHC: 1/200, WB: 1/1000), p63-α (D2K8X) XP^® rabbit mAb (Cell Signaling technology, 13109S, WB: 1/1000), PTBP1 (E4I3Q) rabbit mAb (Cell Signaling technology, 57246, WB: 1/1000), Lamin A/C rabbit polyclonal antibody (proteintech, cat#10298-1-AP, WB: 1/1000), rabbit anti-HA (Cell Signaling technology, 3724S, RIP and ChIP: 1/50), HRP-conjugated Goat Anti-mouse IgG (Merck/Millipore, 401,215, 1/10,000), HRP-conjugated Goat Anti-rabbit IgG (Merck /Millipore, 401315, 1/10,000), normal rabbit IgG (Cell Signaling technology, 2729S, RIP and ChIP: 1/50).

Real-time quantitative PCR (qPCR)

Total RNA was extracted by Trizol reagent (Invitrogen, 15596018) and reverse transcribed by Primescript Reverse transcriptase (Takara, D2680C). Then, FastStart Universal SYBR Green Master (Roche, 4913914001) was used for qPCR detection. Briefly, poly(A) tailing was performed with Escherichia coli poly(A) polymerase (NEB, M0276S) before reverse transcription with an RT primer. Then qPCR was performed with primers designed with miRprimer⁸³. All primers used in this study, including those for miRNA reverse transcription and qPCR, were provided in Supplementary Table 6.

Northern Blot

Total RNA was extracted from CA1h-P2 cells using the Trizol reagent (Invitrogen, 15596018). The NAS1 probe was obtained by in vitro transcription, and the transcription template was amplified with primers probe-F and probe-R (see primer sequences in Supplementary Table 6), and the obtained fragment (approximately 900 bp) was cloned into the vector pcDNA3.1. Then the template fragment containing the T7 promoter was amplified by polymerase chain reaction (PCR) with primers T7-F and probe-R. A 20 μg RNA was loaded for blotting with the DIG Northern Starter Kit (Roche, 12039672910).

RNA immunoprecipitation

RIP assays by PTBP1 were performed in MCF10CA1h with PTBP1-HA overexpression or CA1h-P2 with NAS1 knockdown using HA antibody or PTBP1 antibody, respectively. For RNA–RNA interaction, the MS2 binding site-tagged RNA was expressed in MCF10CA1h with stable MS2–GFP overexpression, and the GFP antibody was used for RIP. Cells were collected and resuspended in polysome lysis buffer (100 mM KCl, 5 mM MgCl₂, 10 mM HEPES, 0.5% Nonidet P-40, 100 U/mL Recombinant RNase Inhibitor, 400 μM ribonucleoside vanadyl complex, 1 mM DTT), and were lysed for 15 min at 4 °C, then the supernatant was collected after centrifuging. Next, the supernatant was divided into two equal parts, and control IgG and antibodies were added for overnight incubation at 4 °C. At the same time, protein A beads (GE Healthcare Life Sciences, 17046901) were washed by NT2 buffer (50 mM Tris-HCl pH 7.4, 150 mM NaCl, 1 mM MgCl₂, 0.05% Nonidet P-40, 0.1 mg/mL bovine serum albumin (BSA)) and were added to each sample following continued incubation for 3 h. After washing beads 4 times with NT2 buffer, 500 μL Trizol reagent was directly added to the beads for RNA extraction. Finally, RNA was reverse transcribed for qPCR detection.

Chromatin immunoprecipitation (ChIP)

The ChIP assays were performed for the NR2F1 and ∆Np63 promoters bound by PTBP1 and NR2F1, respectively. Briefly, HeLa cells were transfected with PTBP1-HA for ChIP of NR2F1 promoter, and MCF10CA1h cells stably expressing NR2F1-HA were used for ChIP of ∆Np63 promoter. Briefly, >10⁷ cells were crosslinked with 1% formaldehyde and quenched by 125 mM glycine. The cell membrane was destroyed and the nucleus was collected. Cell nuclear lysate was sonicated and incubated with control IgG or anti-HA antibody for immunoprecipitation. The complex was captured and precipitated by protein A agarose beads. Captured genomic DNA was reverse-crosslinked and purified by ethanol precipitation with Dr. GenTLE Precipitation Carrier (Takara, 9094). Purified genomic DNA was used for qPCR analysis. The qPCR primers used in these assays are provided in Supplementary Table 6.

RNA pull-down

NAS1 and segments of NR2F1 mRNA were transcribed in vitro by T7 RNA polymerase (Promega, P2075) and biotin labeling mix (Roche, 11685597910). Then, MCF10CA1h cells were lysed by polysome lysis buffer (100 mM KCl, 5 mM MgCl₂, 10 mM HEPES, 0.5% Nonidet P-40, 100 U/mL recombinant RNase inhibitor, 400 μM ribonucleoside vanadyl complex, 1 mM DTT) for 15 min at 4 °C, and the supernatant was collected by centrifuging. A 3 μg Biotin-labeled RNA was added to 50 μL RNA structure buffer (10 mM Tris pH 7.0, 1 M KCl, 10 mM MgCl₂), then was denatured at 95 °C for 2 min, iced for 3 min and incubated at room temperature for 30 min step by step. Next, the RNA and the supernatant containing about 1 mg protein were added to 500 μL RIP buffer (150 mM KCl, 25 mM Tris pH 7.4, 0.5 mM DTT, 0.5% Nonidet P-40, 1 mM PMSF, protease inhibitors), and the complex was incubated for 2 h at room temperature. After 3–5 times of washing with DEPC water, streptavidin-packaged beads (Invitrogen, SA10004) were added to the complex for another 2 h incubation at room temperature. Finally, after washing beads 5 times by RIP buffer and 3 times by phosphate-buffered saline (PBS), proteins pulled down by RNA were eluted by SDS loading buffer for MS analyses or Western blotting.

Cytoplasm/nucleus separation

The PARIS^TM Kit (Invitrogen, AM1921) was used for separating cytoplasmic/nuclear components of cells. Briefly, 10⁶–10⁷ cells were resuspended by 300 μL pre-cooled cell fractionation buffer gently and were lysed on ice for 5 min. Then the supernatant obtained by centrifugation was the cytoplasmic component. The precipitate was washed one time by cell fractionation buffer, and the remaining precipitate was the nuclear component, which could be lysed by 100–200 μL cell disruption buffer. The cytoplasm and nuclear components can be used for extracting RNA or protein.

Mouse experiments

Female BALB/c nude mice and NOD/SCID mice aged 6–8 weeks were used in all animal experiments. For establishing the metastatic dormancy model in Fig. 1, nude mice were intravenously injected with 2 × 10⁵ cells, and bioluminescence imaging data were collected by IndiGo v2.0.5.0. For the EdU labeling assay, nude mice were intravenously injected with 2 × 10⁵ cells and were intraperitoneally injected with 100 ng/mouse EdU (ThermoFisher, C10640) 24 h before lung harvest. For analysis of the effect of NAS1 on long-term metastasis, nude mice have intravenously injected with 5 × 10⁵ CA1h-P1 cells or 2 × 10⁶ CA1h-P2 cells, and NOD/SCID mice were orthotopically inoculated with 2 × 10⁵ 4175-LM2 cells, for which the orthotopic tumors were surgically removed at the size of about 1 cm³. For limiting dilution tumorigenesis assays, NOD/SCID mice were orthotopically injected with different numbers of cells as indicated in the figures. The depth of local invasion was measured from the tumor edges to the deepest points of invasive fronts after H&E staining of paraffin-embedded sections using the methods reported by previously studies^84,85. To analyze circulating tumor cells, GFP-labeled breast tumor cells were orthotopically injected into mice. Mice were anesthetized when tumor volumes reached 0.5 cm³ and 200 μL of blood was collected from the left ventricle. Genomic DNA was extracted from the blood samples with a DNA extraction kit (Tiangen, DP318-02) according to the manufacturer’s protocol, followed by the qPCR analysis of the amount of GFP DNA in 100 ng genome DNA of each sample for relative quantitation of GFP + tumor cells. Investigators were not blinded to outcome assessment. All animal studies were approved by the Institutional Animal Care and Use Committee of Shanghai Institute of Nutrition and Health.

Transcriptomic sequencing and GSEA analyses

Transcriptomic sequencing was firstly performed in MCF10 breast cancer cell line series that include MCF10AT, MCF10CA1h, MCF10CA1a, CA1h-P1, and CA1h-P2. LncRNAs with expression fold changes >1.5 were identified by comparing MCF10CA1h with MCF10AT or MCF10CA1a and comparing CA1h-P2 with CA1h-P1, after excluding some lncRNAs with ultra-low abundance. Then the transcriptomes of CA1h-P2 with NAS1 knockdown, MCF10CA1h, and MCF7 with NR2F1 overexpression were sequenced to find the molecules affected by both NAS1 and NR2F1. Genes with expression fold changes >1.5 were identified as the gene sets regulated by NAS1 knockdown or NR2F1 overexpression and further used for ssGSEA analysis. The genes with fold changes >3 were shown in the heatmap (Fig. 6a).

For GSEA, gene sets MCF7_ΔNp63_UP and MCF7_ΔNp63_DOWN were derived from the public expression profiles of MCF7 cells with ΔNp63 overexpression from the GEO database (GSE64953), and genes with expression fold changes >3 were selected. The signatures for epithelial and mesenchymal BCSCs (E-BCSC and M-BCSC) were derived from the data of Liu et al.²⁸ (GSE52262) by selecting genes with fold changes >4 in CD44⁺/ALDH⁻ cells versus non-CD44⁺/ALDH⁻ cells and in CD44⁻/ALDH⁺ cells versus non-CD44⁺/ALDH⁻ cells, respectively. The EMT signature was derived from the study of Mak et al.⁷². All the gene sets used for GSEA and ssGSEA are listed in Supplementary Table 4.

Flow cytometry analyses

For CD24/CD44 analyses, single-cell suspensions were incubated with the antibodies in recommended concentrations by the manufacturers’ instructions at 4 °C for 30 min. After 3 times of PBS washing, cells were sorted by a MoFlo Astrios Flow Cytometer (Beckman, software: Summit 6.3.1) or analyzed by a Gallios Analyzer (Beckman, software: Gallios software 1.2). For ALDH activity analyses, the ALDEFLUOR Kit (StemCell, 1700) was used according to the manufacturer’s protocol. The specific ALDH inhibitor Diethylaminobenzaldehyde (DEAB) was used as a negative control. For cell cycle analyses, cells were fixed in pre-cooled 70% ethanol at 4 °C overnight. Then cells were washed with PBS and resuspended in PBS containing 100 μg/mL RNase A, following incubation at 37 °C for 30 min. Propidium iodide (PI) was then added to a final concentration of 20 μg/mL. After 15 min incubation at 4 °C, cells were analyzed by Gallios Analyzer. Flow cytometry data processing was performed with FlowJov10 (Tree Star, USA) and ModFit LT (Verity Software House, USA). The gating strategy of flow cytometric analyses was shown as Supplementary Fig. 12.

Immunofluorescence (IF) staining

Cells were seeded on coverslips in 24-well plates and were fixed with 4% paraformaldehyde for 15 min when growing to 60% confluence. 0.3% Triton X-100 containing PBS was used to permeate the cell membrane at room temperature for 10 min. The cover slides were then blocked in 3% BSA/PBS at room temperature for 1 h, and incubated with the primary antibody and fluorescent-labeled secondary antibody overnight at 4 °C and for 1 h at room temperature, respectively. Next, the nucleus was stained by DAPI (Roche, 10236276001) before mounting (Dako, S3023). Observation and photographing were performed with the confocal microscopy Cell Observer (ZEISS, Germany), and image processing and analysis were performed with Zen blue edition software (ZEISS, Germany). For tissue sections, lungs of mice were harvested at the designated time points with PBS lavage and fixed in 4% PFA for 1 h on ice, then were dehydrated by 30% sucrose PBS solution overnight and embedded in OCT (Sakura, 4583), followed by freezing at −80 °C. Tissues were sectioned to 10 µm thickness, and the IF staining and observation were performed as described above. For EdU staining, CLICK PLUS EdU 647 Imaging Kit (ThermoFisher, C10640) was used.

Rapid amplification of cDNA ends (RACE) experiment

The 5′/3′ RACE Kit, 2nd Generation (Roche, 03353621001) was used to amplify the 5′ and 3′ ends of NAS1. The experiments were carried out according to the manufacturer’s instructions.

Luciferase dual-reporter assay

HeLa cells cultured in 48-well plates were transfected with the indicated firefly luciferase reporter plasmids, a Renilla luciferase plasmid, and the overexpression vectors or siRNAs. A 48 h later, the medium was discarded and cells were lysed with 60 μL luciferase lysis buffer (2 mM EDTA, 20 mM DTT, 10% glycerol, 1% Triton X-100 and 25 mM Tris-base, pH 7.8) for 1 h at room temperature. 10 μL lysate was added with 30 μL firefly luciferase assay buffer (25 mM glycylglycine, 15 mM potassium phosphate, 15 mM MgSO₄, 4 mM EGTA, 2 mM ATP, 10 mM DTT and 1 mM D-luciferin, pH 7.8) or 30 μL renilla luciferase assay buffer (0.5 M NaCl, 1 mM EDTA, 0.1 M potassium phosphate, 0.04% BSA and 2 μM coelenterazine, pH 7.4), then the luminescence was detected immediately by a Multimode Plate Reader (PerkinElmer, USA).

Tumorsphere formation assay

Totally, 5000 cells/well were seeded in 6-well ultra-low attachment plates (Corning, 3471) in 1:1 DMEM/F-12 supplemented with 1:50 B27 (Thermo Fisher Scientific, 12587010), 20 ng/mL epidermal growth factor (EGF, Thermo Fisher Scientific, PHG0311), 10 ng/mL basic fibroblast growth factor (bFGF, Sigma-Aldrich, F0291), 5 µg/mL heparin sulfate (Sigma-Aldrich, H3149), 5 µg/mL insulin (Roche, 11376497001) and 0.5 μg/mL hydrocortisone (Merck, 3867). For MCF7 cells, the heparin sulfate and hydrocortisone were not supplemented. Spheres with diameters larger than 100 µm were counted under the microscope after 2 weeks of culturing.

Clinical analysis

Breast cancer tissues for the correlation analysis of NAS1 and NR2F1 were obtained from the clinical sample database of the Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences. RNA and protein of these samples were extracted for NAS1 and NR2F1 detection, respectively. NR2F1 and GAPDH protein bands by Western blotting were analyzed by software Image J (National Institutes of Health, USA) to calculate the relative expression level of NR2F1. For analyses of recurrence-free and metastasis-free survival of breast cancer patients, breast cancer tissues of 89 patients treated at Qilu Hospital of Shandong University were used for RNA extraction, and the expression level of NAS1 was analyzed by qPCR. The effect of NAS1 on recurrence-free survival was also analyzed by Kaplan–Meier Plotter clinical database⁷⁴. Then, the RNA sequencing data of the TCGA breast cancer clinical cohort were used for correlation analyses of NAS1 and EMT markers. Samples and prognostic information were obtained with informed patient consent and the approval from Research Review Boards of the Institute of Nutrition and Health and Qilu Hospital of Shandong University.

Statistics and reproducibility

The data presentation and statistical analyses are described in the figure legends. Data analyses were performed by GraphPad Prism 8 (GraphPad Software, USA). P values < 0.05 were considered statistically significant. The experiments in vitro were repeated independently at least 3 times with similar results.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The RNA sequencing data generated in this study have been deposited in the Genome Sequence Archive (GSA) under accession code PRJCA006136 and National Omics Data Encyclopedia (NODE) under accession code OEP000853. The source data underlying Figs. 1a–f, 2a, c, d, f, g, i, j, 3f, h, i, k, 4c, f–I, 5b, d–g, i, k, m, n, 6a–c, f, h-I, 7a–g and Supplementary Figs. 1d–f, 2a, b, 3a, b, 4d–g, 5b, d–I, k–o, 6a, b, 7b, 8f–h, j–m, 9b-f, 10f–g are provided as a Source Data file. All the other data supporting the findings of this study are available within the article and its Supplementary information files and from the corresponding author upon reasonable request. A reporting summary for this article is available as a Supplementary Information file. Source data are provided with this paper.

Change history

07 October 2021
A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-26292-x

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Acknowledgements

We thank Zheng Yan, Xiang Miao, Lin Qiu, Yifan Bu, Yumei Wang, Kai Wang, Yujia Zhai, Yiting Yuan, Shuyang Yan and Jun Li at the Institute of Nutrition and Health core facilities for technical support. The study was funded by the Ministry of Science and Technology of China (2020YFA0112302, 2017YFA0103502), Chinese Academy of Sciences (QYZDB-SSW-SMC013), National Natural Science Foundation of China (81725017, 81872367, 82003090), and Postdoctoral Science Foundation of China (2020M671257).

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These authors contributed equally: Yingjie Liu, Peiyuan Zhang.

Authors and Affiliations

CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
Yingjie Liu, Peiyuan Zhang, Qiuyao Wu, Yuan Wang, Yansen Xiao, Min Cong, Yunfei He, Chengxin Ma, Pu Tian, Yajun Liang & Guohong Hu
Shanghai Institute of Nutrition and Health, Shanghai Jiao Tong University School of Medicine (SJTUSM) & Chinese Academy of Sciences, Shanghai, China
Yingjie Liu & Guohong Hu
Shanghai Key Laboratory of Regulatory Biology, School of Life Sciences, East China Normal University, Shanghai, China
Houqin Fang, Tingting Wang & Lujian Liao
Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, China
Lun-Xiu Qin
Department of Orthopedics, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
Qingcheng Yang
Department of Breast Surgery, Qilu Hospital of Shandong University, Ji’nan, China
Qifeng Yang

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Yingjie Liu
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Peiyuan Zhang
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Qiuyao Wu
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Yuan Wang
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Min Cong
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Qifeng Yang
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Contributions

G.H. supervised this work. Y. Liu, P.Z., and G.H. designed the experiments and drafted the paper. Y. Liu, P.Z., Q.W., H.F., T.W., Y.W., Y.X., Y.H., P.T., M.C., C.M., and Y. Liang performed the experiments. L.Q., Qingcheng Y., and Qifeng Y. contributed in clinical sample collection and analysis. L.L. designed and supervised the mass spectrometry analysis. All authors discussed the results and commented on the paper.

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Correspondence to Guohong Hu.

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Liu, Y., Zhang, P., Wu, Q. et al. Long non-coding RNA NR2F1-AS1 induces breast cancer lung metastatic dormancy by regulating NR2F1 and ΔNp63. Nat Commun 12, 5232 (2021). https://doi.org/10.1038/s41467-021-25552-0

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Received: 21 October 2020
Accepted: 17 August 2021
Published: 02 September 2021
DOI: https://doi.org/10.1038/s41467-021-25552-0

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