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The RRP9-JUN axis promotes breast cancer progression via the AKT signalling pathway

Biology Direct volume 19, Article number: 131 (2024) Cite this article

Abstract

Background

Ribosomal RNA processing 9 (RRP9) is a specific component of the U3 small nucleolar ribonucleoprotein (U3 snoRNP), which is involved in physiological processes and pathological disorders. The purpose of the current study was to investigate the biological roles of RRP9 in breast cancer (BC) progression.

Methods

The expression levels of RRP9 in human BC were assessed by immunohistochemical (IHC) staining, qPCR assay and Western blot. Cells were transfected with shRNA plasmids to regulate RRP9 expression. The functional roles were explored by Celigo cell counting assay, colony formation assay, flow cytometry and Transwell assays, as well as construction of Xenograft tumor model. Furthermore, interaction between RRP9 and JUN was determined by Co-immunoprecipitation (Co-IP) assay, protein stability assay, and ubiquitination assay.

Results

RRP9 expression was substantially upregulated in BC tissues and was positively associated with lymph node metastasis and poor prognosis. Functional experiments indicated that RRP9 depletion inhibited BC progression both in vitro and in vivo. Using a prime-view human gene expression array and IPA, JUN was identified as a potential downstream target of RRP9. Mechanistically, RRP9 interacted with the JUN protein, and RRP9 deletion decreased JUN protein stability by accelerating JUN ubiquitination and led to JUN degradation via MDM2. Moreover, the regulatory effects of RRP9 on BC cell phenotypes were attenuated by JUN knockdown or the AKT signalling pathway activator SC79.

Conclusions

In conclusion, this study revealed the crucial role of RRP9 in BC progression and its probable novel mechanism, suggesting that RRP9 may be a promising candidate for the treatment of BC.

Background

Breast cancer (BC) is a common heterogeneous cancer among the female population worldwide [1]. The primary prevention and treatment of BC remain urgent public health issues due to its high incidence and mortality [2, 3]. Surgery, including mastectomy alone, breast-conserving therapy (BCT) and postmastectomy breast reconstruction, is the most common curative intervention for BC treatment [4]; however, preventing postoperative recurrence and metastasis remains a significant challenge [5]. Chemotherapy, radiotherapy, endocrine treatment and combined therapies have considerably improved BC outcomes [6]. Regrettably, these therapies have certain limitations and side effects, and many patients suffer from complications and have poor survival [7]. Recently, targeted therapy and immunotherapy have developed rapidly and have drawn broad attention due to their excellent antitumour efficacy and low toxicity [8,9,10]. However, immunotherapy may impair the immune system and has notable toxic side effects [11]. Moreover, there is a lack of effective targeted molecules for OS treatment due to the genetic heterogeneity and elusive pathogenesis of BC. Therefore, identifying novel therapeutic targets for BC is urgently needed.

Ribosomal RNA processing 9 (RRP9) is a specific component of the U3 small nucleolar ribonucleoprotein (U3 snoRNP) that localizes to the nucleolus [12]. The U3 snoRNA, a critical snoRNA [13, 14], can complex with diverse sets of proteins and play critical roles in the processing and maturation of rRNAs [15]. U3 snoRNA is reportedly required for the early cleavage steps in pre-rRNA processing, leading to an increase in the accuracy and efficiency of rRNA processing [16]. Moreover, RRP9, also known as a structural and functional homologue of the U3 small nuclear riboprotein factor 55 K (U3-55 K), has significant sequence similarity to hU3-55k, which plays a role in the production of small ribosomal subunit RNA (18 S rRNA). RRP9 neddylation increases cell proliferation by promoting pre-rRNA processing [17]. However, the biological roles of RRP9 in cancer progression have not been investigated, particularly in BC.

In the present study, high RRP9 expression was detected in BC and was correlated with poor prognosis. Moreover, the function and mechanism of RRP9 in BC progression were investigated upon downregulating or upregulating RRP9. Taken together, our results suggest that RRP9 plays a pro-oncogenic role in BC progression and may be a potential therapeutic target for BC treatment.

Methods

Tissue sample collection

A tissue microarray comprising 110 BC tissue samples and 44 adjacent tissue samples was obtained from Shanghai YBR BioSCI Res Co., Ltd. (Shanghai, China). We obtained informed consent from each patient, and this study was approved by the Ethical Committee of Shanghai Cancer Center, Fudan University (No. 050432-4-2108). Size and extent of primary tumour, regional lymph node metastasis, and resection margin were assessed according to the guidelines outlined in the eighth edition of the American Joint Committee on Cancer (AJCC) staging system. The exclusion criteria were: other malignancies; previous systemic treatment; incomplete clinical data.

Cell lines

BC cell lines SK-BR-3 (RRID: HTB-30), BT-474 (RRID: HTB-20), MCF-7 (RRID: HTB-22), MDA-MB-231 (RRID: HTB-26), BT549 (RRID: HTB-122) and human mammary epithelial cells MCF-10 A (RRID: CRL-10317) were obtained from American Type Culture Collection (ATCC) (https://www.atcc.org/). MDA-MB-231 cells were cultured in Leibovitz’s L-15 medium supplemented with 10% FBS and 1% P/S, MCF-7 cells were cultured in H-DMEM supplemented with 10% FBS, MCF-10 A cells were cultured in RPMI 1640 supplemented with 10% FBS, while SK-BR-3, BT-474 and BT549 cells were cultured in DMEM. All cells were maintained in a humidified incubator at 37 °C with 5% CO2.

Transfected cells were treated with cycloheximide (CHX) (Sigma), MG-132 (Selleck Chemicals), or SC79 at the indicated time points.

Immunohistochemical (IHC) staining

Briefly, tissue sections were heated at 60 °C, dewaxed with xylene, and dehydrated using alcohol. Antigens were removed with citrate buffer, and endogenous peroxidase activity was blocked with 3% hydrogen peroxide for 5 min, followed by incubation in goat serum or bovine serum for 15 min. Sections were incubated with primary antibodies against RRP9 (Novus, Cat. No. H00009136-M01) and Ki-67 (Abcam Cat. No. ab16667) at 4 °C overnight. The following day, the sections were washed three times with 1× PBST and incubated with the secondary antibody goat anti-rabbit IgG H&L (HRP) (Abcam, Cat. No. ab97080) at 37 °C for 1 h. Subsequently, DAB was utilized for colour development, and the sections were then counterstained with haematoxylin (Baso, Cat. No. BA4041). After the sections were sealed with neutral gum, they were observed under a microscope. Each specimen was assigned a score according to the intensity of nuclear staining (no staining/not detected = 0; weak staining/light yellow = 1; moderate staining/yellowish brown = 2; and strong staining/brown = 3) and percentage of cells stained (0% = 0, 1–24% = 1; 25–49% = 2; 50–74% = 3; and 75–100% = 4).

Vector construction and transfection

Short hairpin RNA (shRNA) vectors targeting RRP9 (shRRP9: 5’-AGCCATCTTCTCTGCTGCCAA-3’) or JUN (shJUN: 5’- CGGACCTTATGGCTACAGTAA-3’), an RRP9 overexpression vector, and their corresponding scramble vectors (NC 5’-TTCTCCGAACGTGTCACGT-3’, shCtrl: 5’-CAGGAATTATAATGCTTATCTA-3’) were designed and synthesized by Shanghai Yibeirui Biosciences (Shanghai, China). Briefly, the recombinant vector was transfected into TOP10 Escherichia coli (BioSCI RES) to screen for positive clones. Highly purified plasmids harbouring the shRRP9 or shJUN sequences or the amplified sequence of SNRPB were cotransfected with packaging plasmids into 293T cells with Lipofectamine 3000 to generate recombinant lentivirus plasmids. The virus supernatant was collected 48–72 h after transfection, after which the cells were transfected into BC cell lines. Approximately 72 h later, the transfection efficiencies of the genes were verified using Western blot and qPCR. The BC cells were stably transfected with a negative control vector (shCtrl group), an empty vector (NC group), the shRRP9 vector (shRRP9 group), the RRP9 overexpression vector (RRP9 group), the shJUN vector (shJUN group), or the RRP9 overexpression and shJUN vectors (shJUN + RRP9 group).

Quantitative real-time PCR (qPCR)

Total RNA was isolated from cells with TRIzol® reagent (Invitrogen, USA) according to the manufacturer’s protocol. cDNA was generated from mRNA using a cDNA reverse transcription kit (TransGen Biotech, China). qPCR was performed using a SYBR Green kit (Vazyme, China) on a Biosystems 7500 Sequence Detection System (Applied Biosystems, USA). Relative gene expression was analysed using the 2−ΔΔCq method. GAPDH was used as an endogenous control. The primer sequences are listed in Table S1.

Western blot (WB), coimmunoprecipitation (co-IP) and ubiquitination assays

Cells were harvested and lysed in ice-cold RIPA buffer (Millipore), and proteins were collected and quantified with a BCA Protein Assay Kit (HyClone-Pierce). The proteins were separated by 10% sodium dodecyl sulfate‒polyacrylamide gel electrophoresis (SDS‒PAGE, Invitrogen) and then transferred onto PVDF membranes (Millipore, USA). Next, the membranes were blocked with 5% nonfat milk and incubated with primary antibodies at 4 °C overnight. The next day, the membranes were incubated with a secondary antibody, i.e., goat anti-rabbit IgG (Beyotime, Cat. No. A0208), for 2 h at room temperature. The Western blot bands were visualized by an enhanced chemiluminescence (ECL) plus transmembrane (TM) Western blot system kit (Millipore, USA). The antibodies used are listed in Table S2.

For the co-IP assay, cellular proteins were prepared and incubated with anti-JUN, anti-RRP9, or control IgG antibodies at 4 °C overnight. Antibody-protein complexes were precipitated using protein A + G agarose beads (Beyotime). The agarose-associated antibody-protein complexes were then separated via SDS‒PAGE, and the bound proteins were probed with antibodies. Proteins were detected by WB. Equal amounts of samples were mixed with normal IgG as a negative control. The antibodies used are listed in Table S3.

For the ubiquitination assay, cells were transfected with ubiquitin and the relevant plasmids for 48 h and treated with MG-132 for 6 h before collection. Then, the cells were lysed using denaturing buffer (6 M guanidine-HCl, 100 mM Na2HPO4/NaH2PO4, and 10 mM imidazole) and incubated with nickel beads for 3 h. The precipitated proteins were analysed via WB analysis.

Celigo cell counting assay

Transfected cells were seeded into 96-well plates at 2000 cells per well and cultured at 37 °C with 5% CO2. The next day, the cells were detected by a Celigo image cytometer (Nexcelom Bioscience) for 5 days (at the same time each day). The medium was changed every 2 days. Finally, a cell proliferation curve was generated.

Colony formation assay

Briefly, transfected cells were seeded in 6-well plates at 600 cells/well in triplicate and cultured with or without 10 µM SC79 for 14 days. The culture medium was changed every 2 days. Fourteen days later, the cells were photographed under a fluorescence microscope and then fixed with 4% neutralized formalin, followed by staining with 0.02% crystal violet. Colonies comprising more than approximately 50 cells were counted.

Flow cytometry

MDA-MB-231 and BT549 cells were seeded in 6-well plates at a density of 2,000 cells per well in triplicate and further cultured for 5 days with 10 µM SC79. The cells were collected, trypsinized and then resuspended in complete medium. After centrifugation, the cells were collected for apoptosis and cell cycle analyses.

For the apoptosis assay, the cells were washed with 4 °C ice-cold D-Hanks, resuspended in 200 µL of 1× binding buffer and then stained with 10 µL of Annexin V-APC and 5 µL of PI for 10–15 min in the dark. Finally, 300 µl of 1× binding buffer was added, and the percentage of apoptotic cells was measured by using a Guava easyCyte HT flow cytometry system (Millipore, Schwalbach, Germany).

For the cell cycle analysis, the cells were washed with cold PBS (pH = 7.2 ~ 7.4) at 4 °C, fixed with precooled 70% ethanol for 1 h, and subsequently stained with PI solution (40 × PI, 2 mg/mL: 100 × RNase; 10 mg/mL: 1 × PBS = 25:10:1000). The distribution of cells in the G1, S, and G2 phases was determined using FACSCalibur flow cytometry.

Transwell assay

Briefly, transfected cells were resuspended in 100 µL of serum-free medium. Then, 600 µL of medium containing 15% FBS was added to the lower chamber of the well, and 100 µL of diluted cell suspension (1.5 × 105 cell/well) was added to the upper compartment of the chamber. The migrated cells were fixed and stained with crystal violet. Each experiment was repeated in triplicate. The stained cells were photographed through a microscope.

Xenograft model

BALB/c nude mice were purchased from Jiangsu Jicui Yaokang Biotechnology Co., Ltd. (SCXK (Su) 2018-0008). Animal experiments were approved by the Institutional Animal Care and Use Committee of Shanghai Cancer Center, Fudan University (No. FUSCC-IACUC-S2023-0419). MDA-MB-231 cells transfected with shRRP9 or shCtrl were harvested and resuspended in D-Hanks solution. Subsequently, 4–5-week-old mice were randomly divided into two groups (n = 5 mice per group) and subcutaneously injected with 1 × 107 cells. Tumour formation was monitored daily, and the tumour sizes were assessed weekly, and the tumour volume was calculated as length × width2 × 0.5. All the mice were sacrificed 34 days later, the tumours were harvested, weighed and then photographed. Additionally, the tumours were subjected to Ki-67 staining.

Microarray experiment

Gene expression profiling was performed with an Affymetrix GeneChip Prime View (Affymetrix). Total RNA was extracted from BT549 cells transfected with shCtrl or shRRP9 using TRIzol reagent according to the manufacturer’s instructions, after which the RNA was analysed with a NanoDrop 2000 (Thermo Fisher Scientific, MA, USA). Subsequently, the RNA was reverse-transcribed into cDNA, labelled with 3’ IVT Biotin Label to generate biotin-labelled cRNA, and then hybridized using the GeneChip Prime-view Human Gene Expression Array according to the manufacturer’s instructions (Affymetrix, Santa Clara, CA). A difference in gene expression was considered significant when the fold change > 1.3 and P < 0.05. The differentially expressed genes (DEGs) identified in the microarray analysis were subjected to analysis via the Ingenuity Pathway Analysis (IPA) server. The genes were mapped to the genomic database and subjected to pathway and gene network analysis. The criteria that were included in the upload were gene symbols, fold changes, and adjusted p values.

Protein stability assays

In brief, the cells were incubated in the presence of cycloheximide (CHX) for 0, 2, 4, or 8 h. Then, the cells were collected and lysed, and the lysates were separated via SDS‒PAGE for Western blot analysis of protein abundance at each time point.

Statistical analysis

The statistical analysis was performed with SPSS 19.0 software or GraphPad Prism 6.01 software. Correlation analysis was performed using Spearman correlation analysis. The data are shown as the mean ± standard deviation (SD). K‒M analysis was performed for survival analysis. The variance between two groups was analysed using Student’s t tests. A value of p < 0.05 was considered to indicate statistical significance.

Results

RRP9 was upregulated in BC tissue, and a stable model of RRP9 knockdown was constructed

To investigate the involvement of RRP9 in breast cancer (BC) progression, we assessed its expression in BC and normal samples using TCGA database. The results showed that RRP9 expression was significantly higher in BC compared to normal samples (Fig. 1A). Subsequently, we validated the expression of RRP9 in BC tumour tissues and para-carcinoma tissues through IHC assays (Fig. 1B). Moreover, high RRP9 expression was more prevalent in BC tissues (51.8%, 57/110) than that in para-carcinoma tissues (6.8%, 3/44) (p < 0.001) (Table 1). Furthermore, the expression of RRP9 was correlated with the size and extent of primary tumour and Ki-67 nuclear positive and HER2 expression at the cell membrane (Tables 2 and 3). Notably, the expression of RRP9 was independent of HER2 FISH data and breast cancer molecular subtype including luminal A, luminal B, HER2-positive, and triple-negative breast cancer (Tables 2 and 3). K‒M survival analysis revealed that high RRP9 expression in BC patients was significantly correlated with shorter overall survival (OS) (Fig. 1C), indicating that RRP9 was a critical factor for poor prognosis in BC patients. Furthermore, RRP9 was more highly expressed in BC cell lines (SK-BR-3, BT-474, MCF-7, MDA-MB-231 and BT549), especially in the MDA-MB-231 and BT549 cell lines, than in the human mammary epithelial line MCF-10 A (Fig. 1D). Overall, these findings underscored the crucial role of RRP9 in BC progression.

Fig. 1
figure 1

Expression and prognostic value of RRP9 in BC patients and assessment of transfection efficiency in vitro. A, The expression of RRP9 in breast cancer (BC) and normal samples was analyzed using TCGA database. B, IHC staining for RRP9 in representative BC tissues and adjacent tissues. C, Kaplan‒Meier analysis of the overall survival rate of BC patients stratified according to RRP9 expression. D, The mRNA levels of RRP9 in BC cell lines and the human mammary epithelial cell line MCF-10 A. **P < 0.01 and ***P < 0.001

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Table 1 Expression patterns in breast cancer tissues and para-carcinoma tissues revealed in immunohistochemistry analysis
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Table 2 Relationship between RRP9 expression and tumor characteristics in patients with breast cancer
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Table 3 Relationship between RRP9 expression and tumor characteristics in patients with breast cancer
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The effects of RRP9 knockdown on the progression of BC in vitro

To probe the functional contribution of RRP9, stable models of RRP9 knockdown were established in the BC cell lines. Briefly, three shRNA sequences targeting RRP9 were designed (Fig. 2A), and shRRP9-1, exhibiting the best knockdown efficiency, was selected for subsequent experiments. It was confirmed that RRP9 was effectively silenced in BC cells (Fig. 2B-C, Fig. S1A). After 5 days of cell culture, silencing RRP9 significantly inhibited cell proliferation, particularly in MDA-MB-231 and BT549 cells (Fig. 2D, Fig. S2). Considering the highest expression level of RRP9 in MDA-MB-231 and BT549 cells in comparison to other cell lines, along with the substantial inhibitory effect observed in these two cell lines upon knocking down RRP9, we focused our functional studies on MDA-MB-231 and BT549 cells. Similarly, silencing RRP9 significantly reduced the colony number of MDA-MB-231 and BT549 cells (Fig. 2E). Compared with that in the shCtrl group, the number of cells in the G1 phase was lower in the RRP9 knockdown group, and the number of cells in the G2 phase was higher in both cell lines, suggesting that shRRP9-mediated cell cycle arrest occurs in the G2 phase (Fig. 2F). Furthermore, our results revealed that RRP9 knockdown significantly increased the apoptosis of MDA-MB-231 and BT549 cells (Fig. 2G). Further analysis of the expression of apoptosis-related proteins also confirmed the role of RRP9 depletion in promoting cell apoptosis (Fig. S3A). Additionally, the results of the Transwell assay showed that RRP9 silencing reduced the migration of MDA-MB-231 and BT549 cells (Fig. 2H). In brief, these findings suggested that RRP9 knockdown decreased the proliferative and migratory capacities, induced G2 arrest, and accelerated the apoptosis of BC cells.

Fig. 2
figure 2

Knockdown of RRP9 suppressed the proliferation and migration of BC cells. A. Screening for effective interference targets of RRP9 by qRT‒PCR. B-C, RRP9 knockdown in MDA-MB-231 and BT549 cells was confirmed by qRT‒PCR analysis (B) and Western blot (C) 48 h post-transfection. D-E, Cell proliferation was measured in MDA-MB-231 and BT549 cells at the indicated time points by a Celigo cell counting assay (D) and colony formation assay (E). F, The cell cycle distribution of MDA-MB-231 and BT549 cells upon RRP9 depletion was assessed via flow cytometry. G, Changes in the apoptosis rate of BC cells were induced by RRP9 depletion, as determined via flow cytometry. H, The impaired migration capacity of MDA-MB-231 and BT549 cells was evaluated via Transwell assays. **P < 0.01 and ***P < 0.001

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RRP9 knockdown inhibited BC tumour progression in vivo

To further determine the effect of RRP9 on tumorigenesis in vivo, xenograft models were generated in nude mice by the subcutaneous injection of MDA-MB-231 cells. As shown in Fig. 3A, compared to the shCtrl, RRP9 knockdown significantly delayed tumour growth. Moreover, there was less tumour tissue in the shRRP9 group than in the shCtrl group, and the weight of the tumour tissue was also lower in the RRP9 knockdown group (Fig. 3B). Consistent with these findings, RRP9 knockdown reduced the expression level of Ki-67, a cell proliferation marker, relative to that in the shCtrl group (Fig. 3C). Furthermore, RRP9 knockdown reduced the protein levels of stem cell markers (CD133 and OCT4) and chemotactic cytokines (MIP-1α) (Fig. 3D). Taken together, these results confirmed that the downregulation of RRP9 was involved in the progression of BC in vitro and in vivo.

Fig. 3
figure 3

Knockdown of RRP9 inhibited tumour growth in vivo. A, Changes in tumour volume were measured 5 times from feeding to sacrifice. B, Image and tumour weight of xenograft tumours in the shRRP9 or shCtrl group. C, Ki-67 expression in xenograft tumours was examined via IHC staining (200× and 400×). D, The protein levels of stem cell markers (CD133 and OCT4) and chemotactic cytokines (MIP-1α) were assessed by WB assays in MDA-MB-231 cells with or without RRP9 knockdown. **P < 0.01

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JUN as a downstream target of RRP9 in BC

To further dissect the downstream regulatory mechanism underlying the inhibitory effects of RRP9 on BC progression, a prime-view human gene expression array was used to identify genes downstream of RRP9. After RRP9 was knocked down, 3394 upregulated genes and 4289 downregulated genes were identified (Fig. 4A). The enrichment of DEGs related to disease/function was subsequently analysed via IPA. Subsequently, several DEGs with the highest fold changes were selected for validation by WB and qPCR. As shown in Fig. 4B-C, the expression of PIK3R1, JUN, and ITGA4 decreased at both the mRNA and protein levels after RRP9 knockdown (P < 0.05). To further screen genes downstream of RRP9, the expression of these proteins was knocked down to examine their effects on cell proliferation. As shown in Fig. 4D, cell proliferation was significantly inhibited after JUN knockdown. Based on an analysis of the TCGA database, there was a strong positive correlation between RRP9 and JUN in BC patients (Fig. 4E). Thus, we hypothesized that JUN serves as the main downstream target of RRP9 in BC progression. The interaction between RRP9 and JUN was confirmed by co-IP assay (Fig. 4F). Subsequent CHX chase assay showed that RRP9 knockdown accelerated the degradation of JUN (Fig. 4G). In addition, treatment with MG132 (a proteasome inhibitor) blocked JUN degradation induced by RRP9 knockdown (Fig. 4H). Consistently, the ubiquitination of JUN was increased RRP9 depletion (Fig. 4I), while decreased by RRP9 overexpression (Fig. S4A). Collectively, RRP9 may destabilize JUN protein by promoting its ubiquitination degradation.

Fig. 4
figure 4

JUN as a downstream target of RRP9 in BC. A, Hierarchical clustering analysis of differentially expressed genes according to RNA-Seq. B-C, mRNA and protein expression levels of JUN in the shCtrl and shRRP9 groups were assessed by qRT‒PCR and Western blot, respectively. D, Proliferation assays were performed to further confirm the expression of candidate genes. E, Correlation between RRP9 expression and JUN expression in patients with BC. F, Co-IP assay confirmed the interaction between RRP9 and JUN. G, Decrease of JUN stability by RRP9 knockdown demonstrated by CHX assay. H, Acceleration of JUN degradation by RRP9 knockdown. I, Ubiquitination assay showed that JUN ubiquitination was increased by RRP9 depletion. J, The E3 ubiquitin ligases of JUN were predicted with UbiBrowser (http://ubibrowser.ncpsb.org.cn/ubibrowser/). The query substrate is positioned at the centre of the canvas, which is surrounded by the predicted E3 ligases. The colours and labels of the nodes reflect the type of E3 ligase. The edge width, node size, and edge shade are adjusted based on the confidence score. The node size, edge colour intensity, and edge width are proportionate to the confidence score. R denotes RING, H denotes HECT, F denotes F-box, U denotes UBOX, and S denotes SOCS. K-L, co-IP assays was performed to determine the specific interactions of MDM2 with RRP9 and JUN. M, Western blot was used to assess JUN levels after 0, 4, and 8 h of CHX treatment in modified MDA-MB-231 cells. N, Cells were treated with MG132 to inhibit the proteasome, after which the protein level of JUN was detected. O, Western blot analysis of the endogenous ubiquitination of JUN in MDA-MB-231 cells upon MDM2 overexpression. *P < 0.05, **P < 0.01 and ***P < 0.001

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Next, to investigate the in-depth mechanism by which RRP9 regulates JUN in BC, we employed UbiBrowser (http://ubibrowser.ncpsb.org.cn/ubibrowser/) to predict the E3 ubiquitin ligases that mediate the ubiquitination and degradation of JUN. Our analysis revealed that MDM2 serves as a primary E3 ligase for JUN (Fig. 4J). The co-IP assays determined that MDM2 interacted with RRP9 and JUN (Fig. 4K-L and Fig. S4C). Notably, MDM2 mRNA expression increased following RRP9 knockdown (Fig. S4B). Therefore, we hypothesized that RRP9 regulated the expression of JUN by regulating the expression of MDM2 E3 ubiquitin protein ligase. The CHX assay indicated that MDM2 overexpression could dramatically shortened the half-life of JUN protein (Fig. 4M), implying that RRP9 regulated JUN protein stability via MDM2. Additionally, MDM2 overexpression markedly accelerated the protein degradation of JUN (Fig. 4N) and consequently elevated JUN ubiquitination (Fig. 4O). Taken together, these results suggested that RRP9 affects the protein stability of JUN via the regulation of ubiquitination mediated by MDM2.

RRP9 depletion regulated cell proliferation and migration by targeting JUN

The knockdown efficiency of the construct was determined to evaluate the success of knocking down JUN or overexpressing RRP9 (Fig. 5A and Fig. S1B). Subsequent cell function experiments showed that RRP9 overexpression strongly promoted cell proliferation (Fig. 5B) and colony formation ability (Fig. 5C), inhibited cell apoptosis (Fig. 5D), and enhanced the migration of MDA-MB-231 cells (Fig. 5E). Moreover, JUN knockdown suppressed cell proliferation and migration and promoted apoptosis (Fig. 5B and E). These findings indicated that JUN knockdown has similar effects on the depletion of RRP9. Moreover, JUN depletion attenuated the effects of RRP9 overexpression on the proliferation, apoptosis and migration of MDA-MB-231 cells (Figs. 5B and 6E). Taken together, these results demonstrated that JUN plays an essential role in the progression of BC induced by RRP9 upregulation.

Fig. 5
figure 5

RRP9 promoted proliferation and migration in BC cells by targeting JUN. A, The mRNA levels of RRRP9 and JUN were evaluated by qPCR to confirm successful transfection. B, The effects of RRP9 overexpression alone, JUN knockdown alone, or simultaneous RRP9 overexpression and JUN knockdown on the proliferation rate of MDA-MB-231 cells were assessed via a Celigo cell counting assay. C, Representative images (upper panel) and quantification of colony number (lower panel) determined via a colony formation assay. D, Apoptosis was assessed by flow cytometry. E, The migration capacity of MDA-MB-231 cells was examined by transwell assays. *P < 0.05, **P < 0.01 and ***P < 0.001

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Fig. 6
figure 6

RRP9 regulated cell proliferation and apoptosis in BC via the AKT signalling pathway A, Upstream regulatory pathways identified via IPA. Nodes are displayed using various shapes that represent the functional class of the gene. Arrows indicate the direction of signalling. The genes from the gene expression lists (focus molecules) are represented as red and green based on their fold change in expression. The downregulated genes are shown in green, and the upregulated genes are shown in red. B, Western blot was performed to assess the levels of proteins in the AKT signalling pathway. C, The percentages of apoptotic BT549 cells after RRP9 depletion or SC79 treatment were determined via flow cytometry. D, The protein and phospho-protein levels of AKT in BT549 cells after RRP9 depletion or SC79 treatment were detected via WB assays. *P < 0.05, **P < 0.01 and ***P < 0.001

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RRP9 regulated cell proliferation and apoptosis in BC via the AKT signaling pathway

To elucidate the underlying mechanism of RRP9 in BC progression, we utilized the IPA platform to perform core biological network analysis of the DEGs. IPA network analysis revealed that the DEGs were significantly enriched in the PI3K/AKT signalling pathway (Fig. 6A). Specifically, RRP9 knockdown resulted in suppressed AKT phosphorylation, whereas JUN overexpression led to enhanced AKT phosphorylation (Fig. S3B). We thus hypothesize that the RRP9-JUN axis modulates BC progression via the AKT signalling pathway. Our WB results revealed that depletion of RRP9 decreased the protein levels of p-AKT, CCND1 and CDK1 in BT549 cells (Fig. 6B). Notably, the AKT signalling pathway, which is crucial for BC progression [18, 19] and cell proliferation [20], was activated in this study using the AKT activator SC79 in BT549 cells. AKT activation is known to promote cell proliferation [21]. Herein, our results showed that SC79 inhibited BT549 cell apoptosis and alleviated the promotive effect of RRP9 knockdown on cell apoptosis (Fig. 6C). Additionally, SC79 or JUN overexpression strongly weakened the inhibitory effect of RRP9 knockdown on the phosphorylation of AKT (Fig. 6D and Fig. S3B). Overall, our results demonstrated that RRP9- JUN axis likely regulates the BC progression via the AKT signalling pathway (Fig. 7).

Fig. 7
figure 7

The RRP9-JUN axis on BC progression through the AKT signalling pathway

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Discussion

In this study, we found that RRP9 was upregulated in BC tumour tissues and cells. RRP9 knockdown decreased the oncogenic features of BC cells in vitro and inhibited tumour growth in vivo. Mechanistic studies revealed that RRP9 interacted with the JUN protein and that the downregulation of RRP9 enhanced the ubiquitination of JUN, thereby reducing JUN protein levels. Further functional studies revealed that the effects of RRP9 overexpression could be counteracted by JUN downregulation. Additionally, RRP9 may promote the malignant behaviours of BC by activating the AKT signalling pathway. Taken together, these findings indicate that RRP9 may represent a novel therapeutic target for BC treatment.

RRP9 is the neddylation substrate of Smurf1 and is required for cleavage at sites A0, A1, and A2 [22]. The upregulation of RRP9 has been reported to be positively correlated with human colon cancer progression [17]. In the present study, RRP9 overexpression was found in BC tissue and was correlated with poor prognosis. A previous study suggested that RRP9 could influence cell growth [23]. RRP9 deficiency leads to a strongly elevated level of the cauliflower mosaic virus 35 S primary transcript [24]. Herein, our results demonstrated that RRP9 knockdown inhibited cell growth and migration, promoted cell apoptosis in MDA-MB-231 and BT549 cell lines, and suppressed tumour formation in mice. Notably, RRP9 knockdown upregulated the expression of antiapoptotic proteins but inhibited the expression of proapoptotic proteins, further confirming that the depletion of RRP9 promotes cell apoptosis.

Recent studies have reported that cancer stem cells play crucial roles in therapeutic resistance, as well as in tumour formation, growth, recurrence and metastasis [25, 26]. CD133 and OCT4 are considered stem cell markers [27] and may serve as prognostic markers for cancer. This study revealed that RRP9 knockdown reduced the protein levels of CD133 and OCT4, suggesting that cancer stem cells are also involved in BC progression. Furthermore, RRP9 knockdown was accompanied by the downregulation of MIP-1α, a chemotactic cytokine that may affect cancer progression directly or indirectly. These results suggested that RRP9 plays a crucial role in BC progression; however, the underlying mechanisms by which RRP9 contributes to BC progression remain to be elucidated.

JUN is a member of the AP-1 transcription factor family, which is essential for different developmental programs [28]. JUN is a key regulator in many diseases, such as ischaemia [29], fibrotic diseases [30], and glioma [31]. JUN, which is an oncogene, contributes to oncogenesis in different settings, leading to increases in invasive and malignant phenotypes [32]. Additionally, JUN family members have been found to be expressed in BC and may be potential biomarkers of BC [33]. Consistent with these results, the expression of JUN was found to increase in BC cells; however, its specific roles and mechanism in BC remain unclear. MDM2 is a functional E3 ligase that mediates the ubiquitination and degradation of protein substrates [34]. The co-IP data indicated that RRP9 might interact with JUN via MDM2. We further confirmed the regulatory effect of RRP9 on the protein stability of JUN via an ubiquitination mechanism. Accordingly, the upregulation of RRP9 partly reversed the phenotypic alterations in BC cells induced by JUN knockdown.

The AKT signalling pathway is generally known to be involved in breast carcinogenesis [35]. According to the IPA results, the AKT signalling pathway is closely associated with RRP9. In agreement with previous studies, both JUN and RRP9 can regulate AKT phosphorylation. Furthermore, JUN overexpression weakened the inhibitory effect of RRP9 knockdown on AKT phosphorylation. Additionally, RRP9 has been shown to promote pancreatic cancer progression through the activation of the AKT signalling pathway [36]. Notably, our results suggested that the AKT activator SC79 alleviated the inhibitory effects of RRP9 knockdown on the malignant phenotypes of BC cells. Collectively, these data support the hypothesis that the regulatory effects of the RRP9-JUN axis on BC progression through the AKT signalling pathway (Fig. 7). However, further investigation is needed to elucidate the exact mechanism by which the RRP9-JUN axis affects AKT signalling transduction.

In conclusion, this study indicated that RRP9 regulated BC cell proliferation and migration in vitro and tumour growth in vivo. Mechanistic studies revealed that RRP9 regulated the expression of the JUN protein. Additionally, the RRP9 axis promoted BC progression via the AKT signalling pathway. These findings highlight the critical role of RRP9 in BC and suggest its potential as a molecular therapeutic target. However, our findings require further validation with a larger sample size. Moreover, additional studies are needed to explore the functions of RRP9 under both physiological and pathological conditions. Additionally, the specific mechanisms through which RRP9 regulates the progression of different BC subtypes need to be elucidated through more intensive molecular biology studies.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

RRP9:

Ribosomal RNA processing 9

U3 snoRNP:

U3 small nucleolar ribonucleoprotein

BC:

Breast cancer

IHC:

Immunohistochemical

Co-IP:

Coimmunoprecipitation

BCT:

Breast-conserving therapy

ATCC:

American Type Culture Collection

CHX:

Cycloheximide

IPA:

Ingenuity Pathway Analysis

SD:

Standard deviation

OS:

overall survival

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Author notes

  1. Jinliang Huan and Xiaojun Liu contributed equally as joint first authors.

Authors and Affiliations

  1. Department of Medical Oncology, Fudan University Shanghai Cancer Center, No. 4333, Kangxin Road, Shanghai, 201318, China

    Xiaojun Liu, Yuxin Mu & Yiqun Du

  2. Department of Oncology, Shanghai Medical College, Fudan University, No. 270, Dong’an Road, Shanghai, 200032, China

    Xiaojun Liu, Yuxin Mu & Yiqun Du

  3. Department of General Surgery, Shanghai Eighth People’s Hospital, Affiliated Hospital of Jiangsu University, No. 8, Caobao Road, Shanghai, 200235, China

    Jinliang Huan

  4. Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University Shanghai Cancer Center, Fudan University, No. 270, Dong’an Road, Shanghai, 200032, China

    Na Wang & Ling Li

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Yiqun Du designed this research. Jinliang Huan, Xiaojun Liu, Na Wang and Ling Li performed the experiments. Yiqun Du, Jinliang Huan, Xiaojun Liu, and Yuxin Mu conducted the data processing and analysis. Jinliang Huan and Xiaojun Liu completed the manuscript, which was reviewed by Yiqun Du. All the authors have confirmed the submission of this manuscript.

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Correspondence to Yiqun Du.

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The study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Ethics Committee of Shanghai Cancer Center (No. 050432-4-2108) and the Institutional Animal Care and Use Committee of Shanghai Cancer Center (No. FUSCC-IACUC-S2023-0419), Fudan University. Informed consent was obtained from each patient.

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Huan, J., Liu, X., Wang, N. et al. The RRP9-JUN axis promotes breast cancer progression via the AKT signalling pathway. Biol Direct 19, 131 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13062-024-00578-8

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