CUEDC1 promotes glycolytic metabolism reprogramming through the CUEDC1/CACNG4/PI3K axis to promote ER-positive breast cancer growth

Abstract

Background

The reprogramming of energy metabolism, particularly glycolysis, upholds the malignancy of tumors. The relationship between CUE domain-containing protein-1 (CUEDC1) and glycolysis, along with its influence on the development of estrogen receptor-positive breast cancer (ER⁺ BRCA), is not well defined. This investigation explores the functional involvement of CUEDC1 in glycolysis regulation and uncovers a previously unidentified pathway contributing to the progression of ER⁺ BRCA.

Methods

Immunohistochemistry, western blotting and quantitative real-time polymerase chain reaction (qRT-PCR) were used to detect the expression of CUEDC1 in ER⁺ BRCA tissues and cell lines. A series of molecular analyses, including dual-luciferase reporter assays, RNA-seq, and chromatin immunoprecipitation (ChIP), were performed to elucidate the potential mechanisms underlying CUEDC1’s involvement in ER⁺ BRCA progression. Metabolic assays focusing on glycolysis were employed to investigate the functional roles of CUEDC1 and calcium voltage-gated channel auxiliary subunit gamma 4 (CACNG4). The Connectivity Map (CMap) database was utilized to screen CUEDC1 inhibitors.

Results

CUEDC1 is aberrantly upregulated in ER⁺ BRCA tissues and cells. Increased CUEDC1 can promote enhanced tumor growth and lead to poor clinical outcomes in patients with ER⁺ BRCA. The MYC associated zinc finger protein (MAZ) can upregulate CUEDC1 gene transcription in ER⁺ BRCA cells by directly binding to its promoter. We determined that CUEDC1 directly modulated CACNG4 to enhance phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) pathway activation, thereby facilitating tumor growth of ER⁺ BRCA. Clinical observations also revealed a positive correlation between CACNG4 expression and CUEDC1, with both factors being strongly associated with poor prognosis in patients with ER⁺ BRCA. Mechanistically, The CUEDC1/CACNG4/PI3K signal axis enhanced glycolysis through upregulating glucose transporter 1 (GLUT1), a crucial protein in glucose metabolism, thereby supporting tumor growth of ER⁺ BRCA. Furthermore, methotrexate was identified as a potential inhibitor of CUEDC1. Importantly, the combination of ipatasertib (a PI3K/AKT pathway inhibitor), with methotrexate effectively suppressed growth of ER⁺ BRCA in a mouse model.

Conclusions

Our research reveals that enhanced CUEDC1 plays an essential role to ER⁺ BRCA cell proliferation and tumor growth via the CACNG4/PI3K axis. CUEDC1 is a promising prognostic factor of ER⁺ BRCA, and the CUEDC1/CACNG4/PI3K axis can serve as a potential therapeutic target for ER⁺ BRCA treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11658-025-00819-2.

Introduction

The most prevalent malignancy among women, breast cancer, contributes to approximately one-quarter of all cancer cases and over 15% of global female cancer-related mortality [1]. About three-quarters of breast tumors express estrogen receptor-α (ERα) and generally show a more favorable prognosis than other subtypes, primarily owing to their continued reliance on ERα activity. Estrogen binding to ERs triggers dimerization and translocation, ultimately resulting in the proliferation of cancerous cells [2]. Endocrine-based treatments, notably tamoxifen (TAM) [2] and aromatase [3] inhibitors, are widely adopted in clinical settings to either inhibit ER signaling or curb estrogen production. While TAM treatment has demonstrated significant benefits for patients with ER⁺ BRCA, the emergence of endocrine therapy resistance can lead to recurrence in a subset of patients, posing a significant clinical challenge [4]. However, the mechanism underlying endocrine therapy resistance remains unclear. Consequently, identifying and conducting in-depth research on critical regulators of ER⁺ BRCA progression could facilitate the development of effective targeting strategies and new drug therapies.

The CUE domain is a small and conserved ubiquitin-binding domain consisting of approximately 40 amino acids [5]. CUE domain-containing protein 1 (CUEDC1), located on chromosome 17q22, is a ubiquitously expressed protein [6, 7]. In various primary tumors, aberrant CUEDC1 expression has been observed, with effects that can either enhance or inhibit tumor growth. Elevated CUEDC1 expression was found in metastatic cervical cancer tumors when compared with nonmetastatic tumors [8]. It has also been reported that CUEDC1 promotes tumorigenesis and malignant progression in hematological malignant tumor cells [9]. On the contrary, CUEDC1 inhibits tumor progression in lung cancer. Even though prior studies have recognized CUEDC1 as a crucial ERα target necessary in ER⁺ BRCA [10], note that the molecular mechanisms by which it promotes tumor growth in ER⁺ BRCA remain unknown.

Energy metabolic reprogramming, acknowledged as a crucial cancer hallmark, is of great significance in promoting the development of malignant tumors [11, 12]. Most cancer cells preferentially sustain their proliferation and metastatic phenotype through the energy and biosynthetic pathway generated by aerobic glycolysis [13]. Aerobic glycolysis serves as a key regulator within the microenvironments of aggressive tumors. It impacts multiple processes, including the secretion of proinflammatory factors, angiogenesis, evasion of the immune system, and the response to therapies [14–17]. Therefore, cancer cells exhibit elevated metabolic enzymes and transporters involved in glycolysis compared with normal cells [18]. Increased glycolytic activity within neoplastic cells leads to the accumulation of lactate in the tumor microenvironment (TME). This lactate build-up is associated with the advancement of malignancy and a poor prognosis in various types of cancers, including breast cancer [19, 20]. In addition, increasing studies show that the metabolic adaptation exhibited by cancer cells serves as a principal mechanism underlying resistance to treatment in ER⁺ BRCA [21–23]. ERα-related transcriptional regulation in ER⁺ BRCA has been extensively investigated [24–27]. Notably, ERα-related transcriptional activity is involved in the upregulation of key glycolytic molecules, leading to an abnormal increase in glycolytic flux of ER⁺ BRCA [28, 29]. CUEDC2, another member of the CUE structural domain-containing proteins (CUEDC) family, has been reported to promote the Warburg effect and tumorigenesis in various types of cancers by regulating GLUT3 and LDHA [30]. However, the functional role of CUEDC1 in energy metabolic reprogramming has been scarcely reported. Therefore, we are particularly interested in whether aberrant CUEDC1 expression in ER⁺ BRCA drives its progression by promoting metabolic reprogramming.

Here, we demonstrate that CUEDC1 serves as a crucial regulator in promoting neoplastic cell expansion and tumor progression within this specific breast cancer subtype. CUEDC1 can directly modulate CACNG4, which subsequently promotes the activation of the PI3K/AKT pathway, thereby enhancing glycolytic processes and accelerating tumor growth of ER⁺ BRCA. Furthermore, through extensive screening utilizing the CMap database, methotrexate emerges as a promising small-molecule inhibitor of CUEDC1 and is validated to impede CUEDC1-mediated malignant cell proliferation. Targeting CUEDC1 along with its downstream pathways holds potential for curtailing the progression of ER⁺ BRCA, thus presenting a compelling therapeutic strategy for treating this subtype of breast cancer.

Materials and methods

Samples from patients

Samples of ER⁺ BRCA and adjacent noncancerous tissues were obtained from patients diagnosed at the First Affiliated Hospital of Chongqing Medical University. Prior to obtaining tissue samples, these patients had not received any treatment. This study has been approved by our institutional ethics committee, and all participants have given informed consent for use of their specimens in scientific research.

Cell culture

The experimental study utilized multiple cellular models, including the nontumorigenic mammary epithelial cell line MCF-10A and a panel of breast cancer cell lines (BT-474, MDA-MB-231, MCF-7, T47D, HCC1806, BT-549, and MDA-MB-468) along with HEK293T cells, all obtained from the American Type Culture Collection (ATCC, USA). Cell culture conditions were maintained according to standard protocols, with MCF-10A, MDA-MB-231, and HEK293T cells grown in Dulbecco’s modified Eagle’s medium (DMEM, Gibco, USA) supplemented with 10% fetal bovine serum (FBS) (HyClone) and 1% antibiotic–antimycotic solution (penicillin/streptomycin; Beyotime Biotechnology, Shanghai, China). The remaining cell lines were propagated in Roswell Park Memorial Institute (RPMI) 1640 medium (Gibco, USA) containing identical concentrations of 10% FBS and antibiotics. All cell cultures were incubated at 37 °C with 5% CO₂.

Western blotting

The total protein concentration of lysates extracted from ER⁺ BRCA tumor tissues or cell lines was determined using a bicinchoninic acid (BCA) protein assay kit (Beyotime, China). The proteins were separated by sodium dodecyl sulfate (SDS)-polyacrylamide gel electrophoresis (PAGE) electrophoresis and transferred onto polyvinylidene fluoride (PVDF) membranes (Bio-Rad, USA). Subsequently, the membrane was sealed with 5% skim milk prepared in Tris-buffered saline with Tween 20 (TBST) for 2 h. The membrane was placed in a specific primary antibody working solution and reacted overnight at 4 °C. The primary antibody was as follows: CUEDC1 (DF14596; Affinity), CACNG4 (ER1803-13; HUABIO), MAZ (21068-1-AP; Proteintech), GLUT1 (66290-1-Ig; Proteintech), AKT (ET1609-51; HUABIO), PI3K (ET1608-70; HUABIO), p-AKT (ET1607-73; HUABIO), and β-actin (M1210-2; HUABIO). Following a 2-h incubation with horseradish peroxidase (HRP)-conjugated secondary antibodies at room temperature, images were captured using a chemiluminescence imager. β-Actin was used as the loading control, and band intensities were quantified using ImageJ.

RNA preparation and quantitative real-time PCR (qRT‑PCR)

Firstly, RNA was isolated using TRIzol reagent (Takara, Japan). Subsequently, complementary DNA (cDNA) was prepared according to the instructions of the PrimeScript RT Kit (Takara, Japan). Finally, qRT-PCR was performed using the SYBR Premix Ex Taq II Kit (Takara, Japan). The primer sequences are provided in Supplementary Table S2.

Lentiviral, small interfering RNA, and plasmid transfection

To construct stable cell lines, lentiviral particles which contained CUEDC1 knockdown, CACNG4 knockdown and CACNG4 overexpression plasmids were purchased from GenePharma (Shanghai, China). Lentivirus-mediated shRNA or ectopic gene was used to infect T47D, BT-474, and MCF-7 cells to generate stable CUEDC1 knockdown, CUEDC1 overexpression, CACNG4 knockdown, and CACNG4 overexpression, and corresponding control group cells.

For transient transfection, GeneChem (Shanghai, China) synthesized ESR1 and CACNG4-specific siRNA. Lipofectamine 3000 (Invitrogen, Life Technologies) was utilized to transfect cells with the siRNA following the manufacturer’s instructions. The sequences of ESR1 siRNA, CUEDC1 shRNAs, CACNG4 shRNAs, and CACNG4 siRNA are presented in Supplementary Table S3.

Immunohistochemistry (IHC)

Following the manufacturer’s protocol, IHC staining was carried out on tissue sections from patients or mice. In brief, sections underwent deparaffinization, rehydration, antigen retrieval, and sealing in goat serum, followed by incubation with antibodies against Ki67 (AF02778, Aifang Biotechnology), CUEDC1 (DF14596; Affinity), and CACNG4 (ER1803-13; HUABIO) overnight at 4 °C. Following 1-h incubation of the sections with secondary antibodies at room temperature, the staining process was carried out with a diaminobenzidine (DAB) kit (Beyotime, China). Then, a Nikon Eclipse 80i microscope (Tokyo, Japan) was utilized to capture the images.

Colony formation assay

For cell counting resuspension, T47D (1100 cells/well), BT-474 (1500 cells/well), and MCF-7(800 cells/well) cells were dropped evenly into six-well plates, and cultured for 10–14 days. The colonies were fixed with methanol for 30 min, and afterwards stained with Crystal Violet. Finally, colony counting (50 or more cells) was counted under a microscope.

Cell counting kit-8 (CCK-8) assay

T47D cells (4000 cells/well), BT-474 cells (4000 cells/well), or MCF-7 cells (1200 cells/well) were placed in sextuples into 96-well plates. CCK-8 1:10 ratio working fluid (APExBIO, USA) was added to the cell suspension, followed by incubation at 37 °C for 1.5 h. Absorbance was detected at 450 nm with an Eon microplate reader (BioTek, USA).

EdU incorporation assay

The 5-ethynyl-2′-deoxyuridine (EdU) assay was carried out using a kFlour647 Click-iT EdU Kit (KeyGEN Biotech, China). In brief, T47D, BT-474, and MCF-7 cells were subjected to incubation with 2× EdU for 2 h, then 1 ml paraformaldehyde was used to fix the cells. Subsequently, the cells were permeabilized using Triton X-100 for 15 min, and then underwent incubation for 30 min using 500 μl of Click reaction cocktail. The cells underwent staining with Hoechst 33,342. Finally, photos were taken under a microscope.

Chromatin immunoprecipitation (ChIP) assay

A ChIP assay kit (Bersin Bio, China) was used to conduct the ChIP assay in MCF-7 cells,and 2 × 10⁷ cells were collected. Then, DNA cross-linking was carried out using 1% formaldehyde. Lysis buffer was used to isolate the nuclear contents from the washed precipitates. After that, the enrichment of ultrasonically segmented DNA was enhanced by incubating with an antibody overnight at 4 °C. The following day, extraction of the enriched DNA from the mixture was carried out after the mixture had undergone inverse crosslinking at 65 °C overnight, then quantification analyses was performed using qPCR. The MAZ antibody (21068-1-AP, Proteintech) was utilized to finish this assay. The ChIP-qPCR primer sequences can be found in Supplementary Table S4.

Dual-luciferase reporter assay

First, HEK293T or MCF-7 cells were seed into 24-well plates and cotransfected with the CUEDC1 promoter-driven luciferase reporter gene plasmid for 48 h. After collecting the cell lysates, the Dual-Luciferase Reporter Assay System (Promega, USA) was used to measure Renilla and firefly luciferase activities following the manufacturer’s instructions.

RNA sequencing

The extraction of total RNA from CUEDC1-knockdown and control T47D cells was performed with a Nano Drop and Agilent 2100 bioanalyzer (Thermo Fisher Scientific, Waltham, MA, USA). Subsequent RNA sequencing was carried out by BGI (Shenzhen, Guangdong, China). Differentially expressed genes (DEGs) were selected based on ǀlog₂ FCǀ > 1. All subsequent analyses (unless noted) were performed on the Dr. Tom analysis system.

Glucose uptake assay

Glucose concentration was determined using a commercially available colorimetric detection kit (AAT Bioquest) following the manufacturer’s protocol. Fluorescence intensity measurements were conducted at excitation and emission wavelengths of 570 and 610 nm, respectively, utilizing a TECAN SPARK multimode microplate reader for quantitative analysis.

Lactate measurement

The quantification of intracellular lactate levels was performed using a commercially available lactate assay kit (BC2235, Solarbio). Following cell lysis through ultrasonication for 3 min, the resulting homogenate was subjected to centrifugation to obtain the supernatant. Optical density measurements at 530 nm wavelength were conducted for both the cellular supernatant and a series of standard solutions, with the absorbance values demonstrating a linear correlation with lactate concentration. The lactate concentration in the cellular supernatant was subsequently determined through interpolation from the established standard curve.

ECAR

MCF-7 cells (6000) were plated into each well of the XFe96 microplate. The Seahorse XFe96 Analyzer (Agilent Technologies, Santa Clara, CA) was used in conjunction with the Seahorse glycolysis and mitochondrial stress test kits, following the guidelines provided by the manufacturer. For the glycolysis stress test, glucose (10 mM), oligomycin (1 µM), and 2-deoxyglucose (2-DG, 50 mM) were utilized. Subsequently, the results were analyzed by using Seahorse Wave 2.6.1 software.

Animal experiments

The experimental protocols involving animal subjects were conducted in accordance with ethical guidelines and received formal approval from the Institutional Animal Care and Use Committee at Chongqing Medical University. For the in vivo investigations, female athymic nude mice (6 weeks old) were obtained from Beijing HFK Bioscience Co., Ltd (Beijing, China) and maintained under specific pathogen-free conditions throughout the study period. One week before injection, 30 μg of estradiol (cypionate) in 30 μL of corn oil was intramuscularly injected to boost estrogen-dependent MCF-7 cell proliferation, and estradiol was supplemented every 7 days. MCF-7 cells (5 × 10⁶) from the control or treated group were resuspended in a 1:1 mix of PBS and BD Matrigel^®. These cells were orthotopically injected into the mammary fat pads of nude mice (n = 5 per group). To assess whether ipatasertib and methotrexate inhibit in vivo tumor growth, each group received intraperitoneal injections of ipatasertib (30 mg/kg) or methotrexate (10 mg/kg) twice a week. Following tumor cell implantation, xenograft growth was systematically monitored through weekly measurements. Tumor dimensions were quantified using the standard ellipsoid volume calculation formula: V = 0.5 × (short axis)² × (long axis). Upon reaching experimental endpoints, animals were humanely sacrificed according to institutional guidelines, followed by surgical resection of tumor masses. The excised tissues were subsequently weighed, processed, and preserved for comprehensive histopathological examination and molecular characterization studies.

Bioinformatics analysis

RNA sequencing data from the TCGA-BRCA (Breast Invasive Carcinoma) project, processed through the STAR pipeline, were downloaded and processed from the TCGA portal (https://portal.gdc.cancer.gov). Transcripts per million (TPM) formatted data were extracted. Samples without clinical information and normal samples were excluded, and only luminal subtype breast cancer samples with clinical data were retained for further analysis. The study was analyzed using the Wilcoxon rank-sum test, paired t-test, Kruskal–Wallis test, log₂(value + 1) transformation, and Spearman correlation. RStudio (version 4.2.1) was used as the analysis software, with data ID conversion conducted using the org.Hs.eg.db package. Data analysis was performed using the cluster Profiler, stats (version 4.2.1), and car (version 3.1–0) packages, and data visualization was carried out with ggplot2. To perform survival analysis using the Kaplan–Meier plotter, we used the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/) with the following datasets: GSE26971, GSE7930, and GSE6532. Target gene-related transcription factors were predicted using online databases, including ENCODE (https://www.encodeproject.org/), ChIP-Atlas (http://chip-atlas.org/), and PROMO (http://alggen.lsi.upc.es/cgi-bin/promo_v3/promo/promoinit.cgi?dirDB=TF_8.3). Transcription factor binding sites and related target genes were further predicted using the JASPAR database (https://jaspar.elixir.no/). Gene filtering related to breast cancer was performed using the UALCAN database (https://ualcan.path.uab.edu/).

Statistical analysis

Each of the experiments was replicated three times. Quantitative data are shown as mean ± standard deviation (SD), qualitative as frequencies/percentages. GraphPad Prism 8.0 was used for statistics. We applied paired t-test, unpaired Student’s t-test, or chi-squared test for two-group comparisons; a one-way analysis of variance (ANOVA) was performed to compare multiple groups. Pearson’s correlation coefficient was used to analyze the correlation between the corresponding gene expressions. P < 0.05 was considered statistically significant.

Results

Elevated CUEDC1 expression is associated with poor prognosis in ER⁺ BRCA.

Initially, we undertook a comparative analysis of CUEDC1 expression within the TCGA database. The result revealed an upregulation of CUEDC1 in primary tumor tissues, in contrast to its expression in normal tissues (Fig. 1A, B). Moreover, elevated CUEDC1 expression significantly correlated with the pathological stage of breast cancer (Fig. 1C). Interestingly, our TCGA database analysis revealed higher CUEDC1 expression in ER⁺ BRCA than in other breast cancer subtypes (Fig. 1D). Further assessment of CUEDC1 expression in a cohort of patients with various breast cancer subtypes also showed more abundant CUEDC1 in ER⁺ BRCA tumor tissues (Fig. 1E). The increased CUEDC1 proteins levels were further confirmed by western blotting using fresh ER⁺ BRCA tumor tissues versus adjacent para-cancerous tissues (Fig. 1F) and immunohistochemical (IHC) staining (Fig. 1G). We further proved that the ER⁺ BRCA tumor patients with CUEDC1 overexpression accounted for 90% (Fig. 1H). In addition, the elevated CUEDC1 was closely correlated with clinical features of ER⁺ BRCA (Supplementary Table S1), and an inverse correlation with the survival in patients with ER⁺ BRCA (Fig. 1I). Overall, these data demonstrate that upregulated CUEDC1 expression correlates with worse prognosis in ER⁺ BRCA.

Fig. 1.

Elevated levels of CUEDC1 exhibit a notable correlation with adverse progression in ER⁺ BRCA. A, B Analysis of CUEDC1 expression patterns in the TCGA-BRCA cohort. C The correlation between CUEDC1 mRNA levels and pathological stages of breast cancer patients was investigated by analyzing data from the TCGA database. D Analysis of CUEDC1 mRNA expression across different breast cancer subtypes in the TCGA database. E Immunohistochemical (IHC) staining was employed to obtain representative images depicting CUEDC1 expression across diverse breast cancer subtypes (n = 6). Scale bar, 50 µm. F CUEDC1 protein levels in patients with ER⁺ BRCA were analyzed by western blotting (n = 12). G, H CUEDC1 levels in ER⁺ BRCA (n = 50) versus para-cancerous tissues (n = 33) were quantified and visualized. Scale bar, 50 µm. I Kaplan–Meier analysis to show patients’ progression of ER⁺ BRCA with high or low level of CUEDC1. Data are representative of three independent experiments. All data are presented as mean ± SD. ***P < 0.001

Considering that CUEDC1 is significantly higher expression in ER⁺ BRCA, we hypothesized that CUEDC1 may be regulated by estrogen signaling. As expected, 17β-estradiol (E2) treatment markedly induced CUEDC1 mRNA and protein expression in T47D and MCF-7 cells (Supplementary Fig. S1A–C). Notably, the E2-mediated upregulation was blocked by either the ERα antagonist fulvestrant (Supplementary Fig. S1D–F) or by a specific siRNA that silences ERα expression (Supplementary Fig. S1G, H). Consistent with the prior finding that CUEDC1 serves as a functional target gene of ERα, we confirmed a putative role of ERα-mediated signaling in modulating CUEDC1 expression of ER⁺ BRCA cells [10]. Collectively, these data indicate that ERα signaling is significantly critical in modulating CUEDC1 expression.

High CUEDC1 expression accelerates tumor growth of ER⁺ BRCA

To assess the potential function of CUEDC1 in ER⁺ BRCA progression, we first detected CUEDC1 expression in multiple breast cancer cell lines, to further confirm that CUEDC1 expression is enhanced in ER⁺ BRCA cell lines, such as T47D, MCF-7, and BT-474 cells, and relatively lower expression in HER2-positive breast cancer and TNBC cells (Supplementary Fig. S2A; Fig. 2A). Using the lentiviral packaging system, CUEDC1 was stably knocked down in T47D and BT-474 cells (Supplementary Fig. S2B, C; Fig. 2B) and overexpressed in MCF-7 cells (Supplementary Fig. S2D, E; Fig. 2C). CUEDC1 efficient knockdown remarkably inhibited T47D and BT-474 cell proliferation (Fig. 2D; Supplementary Fig. S2F). Reversely, ectopic CUEDC1 overexpression significantly promoted MCF-7 cell proliferation (Fig. 2E; Supplementary Fig. S2G). Similar results were obtained using the CCK-8 assay (Fig. 2F, G).

Fig. 2.

Higher CUEDC1 expression enhances the proliferative ability of ER⁺ BRCA cells. A Western blotting to assess CUEDC1 protein levels in breast cancer cells (BT-474, MDA-MB-231, MCF-7, T47D, HCC1806, BT-549, and MDA-MB-468) and human normal mammary epithelial cells (MCF-10A) (n = 3). B, C Western blotting was utilized to evaluate CUEDC1 knockdown efficiency in T47D or BT-474 cells (B) and CUEDC1 overexpressing efficiency in MCF-7 cells (C). D, E Colony formation to assess cell proliferation in the indicated ER⁺ BRCA cells (n = 3). Representative images are shown. F, G CCK-8 assay was performed to evaluate proliferation of the CUEDC1-knocked down T47D and BT-474 cells (F), and the ectopic CUEDC1 overexpressing MCF-7 cells (G) (n = 6). H Xenografts derived from MCF-7 CUEDC1 overexpressing cells and relative controls (n = 5). I Tumor weights were compared between the control and experimental groups (n = 5). J Tumor volumes were measured at the designed time points to construct a growth curve (n = 5). K The efficiency of CUEDC1 overexpression in vivo was evaluated by western blotting (n = 5). L, M IHC shows that CUEDC1 (L) and Ki-67 (M) proteins were markedly stronger in tumor masses originating from ectopic CUEDC1 overexpressing MCF-7 cells (n = 5). N The correlation between CUEDC1 and Ki-67 expression by Pearson’s correlation analysis in ER⁺ BRCA samples using TCGA database. Data are representative of at least three independent experiments. All data presented as mean ± SD. ***P < 0.001

To confirm the vital function of CUEDC1 in vivo, we established a subcutaneous xenograft model in female BALB/c nude mice using CUEDC1-overexpressing MCF-7 cells and their control MCF-7 cells. CUEDC1 overexpression significantly increased the tumor size and weight in comparison with control group (Fig. 2H–J), and the increased CUEDC1 in tumor was proved by western blotting (Fig. 2K, Supplementary Fig. S2H) and IHC (Fig. 2L). Moreover, CUEDC1-overexpressed MCF-7 tumors had stronger Ki-67 expression than those in the control groups (Fig. 2M). Indeed, the stronger Ki-67 mRNA level was closely correlated with CUEDC1 expression in patients with ER⁺ BRCA in the TCGA database (Fig. 2N). Thus, these data indicate that CUEDC1 is critical for ER⁺ BRCA cell proliferation and tumor growth.

MAZ upregulates CUEDC1 expression by directly binding to its promoter

To uncover the potential mechanism of elevated CUEDC1 expression in ER⁺ BRCA, we probed into the upstream transcription factors regulating its expression. Differential transcription factors in ER⁺ BRCA were analyzed via the TCGA database (Supplementary Fig. S3A). Then, we searched the PROMO, ENCODE, CHIP-ATLAS, and TCGA databases for transcription factors that may activate CUEDC1 transcription in ER⁺ BRCA. Four transcription factors (ESR1, MAZ, STAT1, and USF1) overlapped (Fig. 3A). Among the three transcription factors with the highest matched scores from the JASPAR database, MAZ, encoded by a 2.7-kb gene on chromosome 16p11.2 [31], was found to have the strongest positive correlation with CUEDC1 in the TCGA database (Fig. 3B, C; Supplementary Fig. S3B), suggesting that MAZ potentially regulates CUEDC1 expression. Furthermore, we uncovered that MAZ was highly expressed in breast cancer particularly in ER⁺ BRCA (Fig. 3D, E). Additionally, MAZ was increased in ER⁺ BRCA cells compared with MCF-10A cells (Supplementary Fig. S3C, D; Fig. 3F). Subsequently, further analyses performed using the JASPAR database unveiled potential MAZ binding sites in the CUEDC1 promoter (Fig. 3G). Two predicted binding sites were present in this genomic segment (Fig. 3H). The chromatin immunoprecipitation (ChIP) assay revealed that MAZ could directly bind to the CUEDC1 promoter in ER⁺ BRCA cells (Fig. 3I). Dual-luciferase reporter assays demonstrated that deletion of mutant site 1 significantly affected the binding of MAZ to the CUEDC1 promoter region. This highlights the crucial role of site 1 in mediating MAZ-induced CUEDC1 transcriptional activity (Fig. 3J). Correspondingly, MAZ knockdown obviously led to decreased CUEDC1 mRNAs (Fig. 3K) and proteins (Fig. 3L, Supplementary Fig. S3E) in T47D and MCF-7 cells. Similar results were obtained from BT-474 cells (Supplementary Fig. S3F, G). Taken together, the increased MAZ in ER⁺ BRCA contributes to CUEDC1 upregulation by directly binding to its promoter.

Fig. 3.

CUEDC1 is positively regulated by MAZ. A A Venn diagram to show the potential transcription factors (TFs) of CUEDC1, as forecasted by TCGA, ENCODE, PROMO, and ChIP-Atlas. B The JASPAR database identified four TFs that bind to the CUEDC1 promoter. C The correlation between CUEDC1 and MAZ mRNA levels in the TCGA database. D, E MAZ mRNA expression in different subtypes of breast cancer from TCGA database. F MAZ expression was validated by western blotting in ER⁺ BRCA cells (T47D, MCF-7, and BT-474) and MCF-10A (n = 3). G The MAZ binding sites in CUEDC1 promoter. H Two potential binding sites of MAZ on the CUEDC1 promoter predicted by the JASPAR database. I ChIP assay was used to confirm the binding capacity of MAZ to the CUEDC1 promoter in MCF-7 cells (n = 3). J A dual-luciferase reporter assay to assess transcriptional activity of MAZ on CUEDC1 in MCF-7 (left panel) and 293 T (right panel) cells (n = 3). K, L qRT-PCR (K) and western blotting (L) to evaluate the regulation of MAZ to CUEDC1 in MAZ silenced T47D and MCF-7 cells (n = 3). NS, not significant. Data are representative of at least three independent experiments. Data shown as mean ± SD. ***P < 0.001

CACNG4 is positively regulated by CUEDC1

To investigate the molecular mechanisms of CUEDC1-induced proliferation in ER⁺ BRCA cells, we performed RNA sequencing to compare mRNA expression profiles between shNC and shCUEDC1 T47D cells. Volcano maps (Fig. 4A) and a heatmap (Fig. 4B) showed differentially expressed genes. Additionally, 156 CUEDC1-correlated genes in breast cancer were retrieved from the UALCAN database. Compared the two gene sets, two potential CUEDC1 target genes were found, including CACNG4 and RNF43 (Fig. 4C). Upon further analysis of the expression levels of these two genes in the respective cell lines, it was observed that the absence of CUEDC1 resulted in a marked decrease in CACNG4 expression (Fig. 4D; Supplementary Fig. S4A, B), while the overexpression of CUEDC1 significantly upregulated CACNG4 (Fig. 4E; Supplementary Fig. S4C), suggesting that CACNG4 is the downstream molecule of CUEDC1. To further elucidate the clinical relevance of CACNG4 in ER⁺ BRCA, we conducted an expression analysis using the TCGA breast cancer database. This analysis revealed a consistent upregulation of CACNG4 expression across breast cancer samples (Fig. 4F), especially in ER⁺ BRCA (Fig. 4G; Supplementary Fig. S4D). And the increased CACNG4 was significantly associated with the pathologic stage (Supplementary Fig. S4E), poor survival (Fig. 4H), and disease progression in patients (Supplementary Fig. S4F). Additionally, in paired ER⁺ BRCA tissues and their matched adjacent non-cancerous tissues, CACNG4 proteins were significantly elevated in CUEDC1^high tumor tissues, while they were notably reduced in CUEDC1^low tumor tissues (R² = 0.4444, P = 0.0179, Supplementary Fig.S4G; Fig. 4I). Consistently, the positive relationship between CUEDC1 and CACNG4 protein expression was further confirmed in ER⁺ BRCA and para-cancerous tissues using IHC analysis (Fig. 4J). Together, these results support that CUEDC1 directly increases CACNG4 expression in ER⁺ BRCA tissues and cells.

Fig. 4.

CACNG4 is a direct target of CUEDC1. A, B Volcano plots and heatmap show differentially expressed genes between shNC and shCUEDC1 T47D cells (n = 3), fold-change cutoff > 1.0 and P < 0.05. C Two target genes acquired using RNA-seq and UALCAN database. D, E qRT-PCR to detect two target genes mRNA levels in CUEDC1-knocked-down T47D or BT-474 cells (D), and ectopic CUEDC1 overexpressing MCF-7 cells (E) (n = 3). F Analysis of CACNG4 expression in human breast cancer in TCGA breast cancer datasets. G Comparison of CUEDC1 expression in various breast cancer subtypes using the TCGA datasets. H Kaplan–Meier analysis of ER⁺ BRCA overall survival regulated by CACNG4. I Western blotting to determine correlation between CUEDC1 and CACNG4 proteins levels in ER⁺ BRCA tissues (n = 12). J Representative immunohistochemical images of CUEDC1 and CACNG4 in ER⁺ breast cancer (n = 8). Scale bar, 50 µm. Results from western blotting assay were quantified and analyzed by linear regression and correlation. NS, not significant. The results are representative of at least three independent experiments. Data shown as mean ± SD. *P < 0.05, ***P < 0.001

CACNG4 is required for CUEDC1-mediated malignancy in ER⁺ BRCA cells

To determine the role of CACNG4 in CUEDC1-induced malignant proliferation in ER⁺ BRCA, we first detected CACNG4 expression in ER⁺ BRCA cells, and found that CACNG4 was highly expressed in ER⁺ BRCA cells compared with MCF-10A cells (Supplementary Fig. S5A, B). Then, CACNG4 was stably knocked down in MCF-7 and BT-474 cells (Supplementary Fig. S5C–F), and overexpressed in T47D cells (Supplementary Fig. S5G, H). Consistent with the CUEDC1-inducing malignant results, CACNG4 deficiency significantly inhibited cell proliferation, whereas increased CACNG4 had the opposite effects in comparison with the control cells (Fig. 5A, B; Supplementary Fig.S6A, B). Furthermore, the depletion of CACNG4 led to a significant inhibition of tumor growth in vivo, as evidenced by a reduction in tumor size, volume, and weight. (Fig. 5C–E).

Fig. 5.

The malignant effects of CUEDC1 rely on the high expression of CACNG4 in ER⁺ BRCA cells. A, B Colony formation (A) (n = 3) and CCK-8 (B) assays (n = 6) to test the proliferation ability of CACNG4-deficient MCF-7 cells or ectopic CACNG4 overexpressing T47D cells. C–E Loss of CACNG4 decreases tumor size (C), tumor weight (D), as well as tumor growth (E) (n = 5). F Western blotting to assess CACNG4 reexpression efficiency in CUEDC1-deficient T47D cells (n = 3). G Western blotting to test CACNG4 knockdown efficiency in ectopic CUEDC1-overexpressing MCF-7 cells (n = 3). H–L CCK-8 (H, I) (n = 6), EdU incorporation (J, K) (n = 3), and colony formation assays (L, M) (n = 3) to test cell proliferation in indicated ER⁺ BRCA cells. Scale bar, 50 µm. Data are representative of at least three independent experiments. Data shown as mean ± SD. ***P < 0.001

Considering the functional roles of CUEDC1 in regulating CACNG4 expression and driving the progression of ER⁺ BRCA, we speculated that CUEDC1 may promote ER⁺ BRCA progression dependent on CACNG4. CACNG4 was thus ectopically overexpressed in CUEDC1 knockdown T47D cells (Fig. 5F; Supplementary Fig. S6C) and BT-474 cells (Supplementary Fig. S6D), and knocked down in CUEDC1 overexpressed MCF-7 cells for rescue experiments (Fig. 5G; Supplementary Fig. S6E). Interestingly, CACNG4 overexpression largely restored the proliferation ability of CUEDC1-silenced T47D cells. Conversely, the CUEDC1-mediated promotion of MCF-7 cell proliferation could be largely reversed by CACNG4 knockdown (Fig. 5H–M; Supplementary Fig. S6F, G). Collectively, these findings validate that CACNG4 is essential for the CUEDC1-driven malignant proliferation of ER⁺ BRCA cells in vitro.

The CUEDC1/CACNG4 axis is involved in regulating tumor growth via activating PI3K/AKT signaling

To further investigate the downstream targets of the CUEDC1–CACNG4 axis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was performed to investigate the CUEDC1-related downstream pathway using RNA sequencing data, indicating that PI3K/AKT signaling was closely related to CUEDC1 in T47D cells (Fig. 6A). Meanwhile, CUEDC1 was further proved to activate the PI3K/AKT pathway on large-scale ER⁺ BRCA datasets by comparing CUEDC1^high and CUEDC1^low tumors from the TCGA database (Fig. 6B). Therefore, we hypothesized that CUEDC1 could promote the activation of PI3K/AKT to facilitate tumor growth of ER⁺ BRCA cells. Indeed, knockdown of CUEDC1 resulted in PI3K/AKT pathway suppression compared with control cells (Fig. 6C, D). Similar results were obtained with CACNG4 knockdown cells (Supplementary Fig. S7A, B). These data effectively indicated that CUEDC1-CACNG4 axis was indeed involved in activation of PI3K/AKT signaling. We further explored whether CUEDC1 promoted the activation of PI3K/AKT via upregulating CACNG4 to facilitate tumor growth of ER⁺ BRCA. Indeed, we found the activation of PI3K/AKT signaling induced by CUEDC1 dependent on CACNG4 (Fig. 6E; Supplementary Fig. S7C). Taken together, these data reveal that enhanced CUEDC1 expression leads to activation of PI3K/AKT pathway through regulating CACNG4.

Fig. 6.

The CUEDC1/CACNG4 axis activates the PI3K/AKT pathway. A KEGG analysis enriched PI3K-AKT signaling pathway in CUEDC1^high T47D cells. B GSEA analysis showing the enriched PI3K-AKT signaling in ER⁺ BRCA tumors from TCGA datasets. C-D Western blotting to assess PI3K/AKT activity in CUEDC1 knockdown T47D (C) and BT-474 (D) cells (n = 3). E CACNG4 was reexpressed in CUEDC1 knockdown T47D (left panel) and BT-474 cells (right panel). Western blotting to evaluate activation of PI3K/AKT signaling (n = 3). F, G CCK-8 (F) (n = 6) and colony formation assay (G) (n = 3) to detect proliferation capacity of CUEDC1 knockdown T47D and BT-474 cells treated with SC79, an agonist of PI3K-AKT signaling. H, I Tumor sizes (H) and tumor weights (I) of ectopic CUEDC1-overexpressing MCF-7 cells assessed in mice under treated with or without PI3K/AKT pathway inhibitor (ipatasertib) (n = 5). J Western blotting to check p-AKT protein levels in mouse tumor tissues under different treatments (left panel) (n = 3). Results from western blotting assays were quantified and analyzed statistically (right panel). Data are representative of at least three independent experiments. All data shown as mean ± SD. ***P < 0.001

To further investigate whether the malignant proliferation of ER⁺ BRCA cells caused by the CUEDC1–CACNG4 axis depends on activated PI3K/AKT signaling, we employed SC79, a PI3K/AKT signaling pathway agonist, as well as ipatasertib, an inhibitor of PI3K/AKT signaling, to treat the ER⁺ BRCA cells and evaluate cell proliferation abilities. SC79 could partially restore cell proliferation in CUEDC1-knockdown ER⁺ BRCA cells (Fig. 6F, G). In contrast, malignant proliferation induced by ectopic expression CUEDC1 in MCF-7 was attenuated by ipatasertib treatment (Supplementary Fig. S7D, E). Consistently, administrating ipatasertib to tumor-burden mice injected with ectopic CUEDC1 overexpressing MCF-7 cells caused a significant reduction of tumor growth (Fig. 6H, I). Correspondingly, ectopic CUEDC1 induced activation of PI3K/AKT was dramatically weakened in ipatasertib-treated tumors (Fig. 6J). Taken together, these findings demonstrate that elevated CUEDC1 activates PI3K/AKT signaling to promote ER⁺ breast tumor growth.

CUEDC1–CACNG4 axis activates PI3K/AKT pathway to coordinate glycolysis for ER⁺ breast tumor growth

It has been reported that PI3K/AKT signaling plays a central role in promoting glucose uptake and glycolysis in cancers [32]. In addition, CACNG4 is associated with glycolysis in colon cancer [33]. Previous studies have also shown that most cancer cells preferentially sustain their proliferation relying on energy and biosynthesis from aerobic glycolysis [13]. Consequently, we raised a hypothesis that the activated CUEDC1/CACNG4/PI3K axis in ER⁺ BRCA might promote tumor growth through PI3K/AKT-mediated glycolysis. In line with this, CUEDC1 overexpression increased glucose uptake and lactate production (Fig. 7A, B) and caused higher ECAR, an indicator of overall glycolytic flux (Fig. 7C). Conversely, knockdown of CUEDC1 inhibited glucose uptake and lactate production (Fig. 7D, E). In addition, CACNG4 knockdown also led to decreased glucose uptake (Supplementary Fig. S8A) and lower lactate production (Supplementary Fig. S8B), and corresponding decrease of ECAR (Supplementary Fig. S8C) in ER⁺ BRCA cells. Treatment with ipatasertib largely counteracted ectopic CUEDC1-induced increase of glucose uptake and lactate production (Fig. 7F, G). To gain deeper insight into the mechanism driving CUEDC1/CACNG4-mediated glycolysis, we first analyzed the relationship between CACNG4 levels and the expression of key glucose metabolism-related genes (ALDOA, ENO1, HK2, HK3, LDHA, PDK1, PDK2, PDK3, PGAM1, PGK1, and GLUT1) using the TCGA databases in ER⁺ BRCA. GLUT1 was found to have the strongest positive correlation with CACNG4 in BRCA (Fig. 7H). Similar results were obtained using the qRT-PCR assay (Supplementary Fig. S8D–F). In line with this, GLUT1 were significantly downregulated in CACNG4 knockdown ER⁺ BRCA cells (Fig. 7I; Supplementary Fig. S8G, H). Reversely, upregulated CACNG4 led to an increased GLUT1 expression in ER⁺ BRCA cells (Fig. 7J; Supplementary Fig. S8I). Similar results were obtained in CUEDC1 knockdown T47D or BT-474 cells, and ectopic CUEDC1-overexpressing MCF-7 cells (Supplementary Fig. S8J, K). GLUT, the glucose transporter, enables the transport of glucose across the plasma membrane [34]. As a major member of the glucose transporter family, GLUT1, acting as a rate-limiting factor for glucose transport, supports glycolysis and mediates tumor metabolism reprogramming events [35, 36]. Aberrant GLUT1 expression, coupled with altered hexose affinities, may enable cancer cells to fine-tune their energy supply, thereby offering a critical advantage for tumor growth [37, 38]. Collectively, our data support that the CUEDC1/CACNG4/PI3K axis promotes glycolysis by regulating GLUT1 expression in ER⁺ BRCA cells.

Fig. 7.

CUEDC1/CACNG4/PI3K signaling axis promotes glycolysis via upregulating GLUT1 expression in ER⁺ BRCA. A, B Glucose consumption (A) and lactate production (B) in ectopic CUEDC1-overexpressing MCF-7 cells (n = 4). C The ECAR profile measured in ectopic CUEDC1-overexpressing MCF-7 cells using the Seahorse XF24 analyzer (n = 3). Metabolic inhibitors were sequentially injected at the designed time points as shown. D, E Glucose consumption (D) and lactate production (E) in CUEDC1-knocked-down BT-474 cells (n = 4). F, G Glucose consumption (F) and lactate production (G) in ectopic CUEDC1-overexpressing MCF-7 cells with or without ipatasertib treatment (n = 4). H Correlation analysis of CACNG4 expression with metabolism-related genes in ER⁺ BRCA tumors from TCGA datasets. I, J The regulation of CACNG4 to GLUT1 was determined by western blotting in CACNG4-knocked-down MCF-7 and BT-474 cells (I) and the ectopic CACNG4 overexpressing T47D cells (J) (n = 3). K, L T47D or BT-474 cells and MCF-7 cells were treated with or without glycolytic hexokinase inhibitor (2-DG) and subjected to the colony formation assay to test cell proliferation of the CUEDC1 knockdown T47D or BT-474 cells (K), and ectopic CUEDC1-overexpressing MCF-7 cells (L) (n = 3). Representative images are shown. M, N Tumor sizes (M) and tumor weights (N) of ectopic CUEDC1-overexpressing MCF-7 cells assessed in mice with or without 2-DG treatment (n = 5). Data are representative of at least three independent experiments. All data presented as mean ± SD. **P < 0.01, ***P < 0.001

Subsequently, we wondered whether CUEDC1/CACNG4/PI3K axis-mediated energy metabolic reprogramming could affect ER⁺ BRCA tumor growth. 2-Deoxyglucose (2-DG), an inhibitor to glycolytic hexokinase, was employed. Knockdown of CUEDC1 combined with 2-DG treatment further reduced ER⁺ BRCA cells’ proliferation (Fig. 7K). In contrast, administrating treatment with 2-DG in CUEDC1 overexpressed ER⁺ BRCA cells with 2-DG notably mitigated the malignant proliferation (Fig. 7L) and tumor growth (Fig. 7M, N). Overall, CUEDC1/CACNG4/PI3K axis-mediated glycolysis is critical for ER⁺ BRCA cell proliferation and tumor growth.

Methotrexate, a screened CUEDC1 inhibitor, combined with ipatasertib improves therapeutic benefits for ER⁺ BRCA

Numerous studies have shown that PI3K/AKT signaling is hyperactivated in breast cancer [39–41]. Accordingly, the combination of a PI3Kα-selective inhibitor with an estrogen receptor (ER) antagonist is approved for advanced HR⁺ disease, however, the benefits of therapy are still limited [42]. To evaluate the potential therapeutic enhancement for ER⁺ breast cancer under CUEDC1 targeting in combination with a PI3K/AKT signaling pathway inhibitor, we tried to utilize the Connectivity Map (CMap) database (https://clue.io/) to obtain the prioritized pharmacological compound. This platform, which systematically catalogs gene expression alterations in human cells following exposure to diverse pharmacological and genetic perturbations [43], was employed to identify potential CUEDC1 inhibitors. After computational integration of our RNA sequencing datasets with the reference profiles in CMap database, we generated a prioritized list of pharmacological compounds on the basis of their connectivity metrics. This identified a list of candidate drugs that exhibited the highest connectivity scores (Fig. 8A). These drug-induced gene expression profiles closely resembled those observed in CUEDC1-knocked-down tumor cells, thus identifying potential inhibitors of CUEDC1. Methotrexate, ranked at the top, is an antifolate metabolite that impedes DNA synthesis, repair, and cellular replication, and possesses both anti-inflammatory and immunomodulatory properties [44, 45]. To assess the effect of methotrexate on the inhibition of CUEDC1, we first measured its half-maximum inhibitory concentration (IC₅₀) value in ER⁺ BRCA tumor cells (Supplementary Fig. S9A). As expected, treating ER⁺ BRCA cells with methotrexate showed a similar gene expression profile to that induced by CUEDC1 knockdown. Importantly, CACNG4, the downstream target of CUEDC1, was markedly downregulated in methotrexate-treated cells, suggesting that methotrexate can inhibit CUEDC1 activity (Fig. 8B, C; Supplementary Fig. S9B–D). We further revealed that methotrexate combined with ipatasertib could significantly inhibit ER⁺ BRCA cell proliferation (Supplementary Fig. S9E–G) and tumor growth (Supplementary Fig. S9H, I).

Fig. 8.

Targeting CUEDC1 combined with ipatasertib improves therapeutic benefits for ER⁺ BRCA in vitro and in vivo. A A potential inhibitor targeting CUEDC1 was obtained using CMap database. B, C mRNA levels of CUEDC1 and CACNG4 in ER⁺ BRCA cells under treatment with or without methotrexate (n = 3). D–F T47D, MCF-7, and BT-474 cells treated with or without low-dose methotrexate in combination with ipatasertib, CCK-8 (D) (n = 6) and colony formation (E, F) (n = 3) to evaluate cell proliferation. G Representative photographs of tumor from MCF-7 cells in mice administered with a combination of lower-dose methotrexate and ipatasertib (n = 5). H–J Tumor weights (H), body weight (I), liver-to-body weight ratio (J), and spleen-to-body weight ratio (K) were checked in mice under treatment with a combination of methotrexate and ipatasertib (n = 5). NS, not significant. Data are representative of at least three independent experiments. All data presented as mean ± SD. ***P < 0.01

Methotrexate is widely employed in treatment of various cancers, either as monotherapy or in combination, including breast cancer, head and neck cancers, and childhood acute lymphoblastic leukemia (ALL), in addition to its use in rheumatoid arthritis and certain dermatologic disorders [46]. However, its clinical application as a chemotherapy agent is often limited by the necessity for high dose, the development of resistance, and neurological side effects [47]. Therefore, we further evaluated the therapeutic effect of low-dose methotrexate in combination with ipatasertib in ER⁺ BRCA. As expected, compared with control group, low-dose methotrexate combined with ipatasertib could still significantly inhibit ER⁺ BRCA cell proliferation (Fig. 8D–F) and tumor growth (Fig. 8G, H). Interestingly, there were no significant alterations in body weight, liver and spleen volumes of nude mice, indicating that these treatments were well tolerated without significant toxicity (Fig. 8I–K). In conclusion, methotrexate is a potential inhibitor of CUEDC1, and methotrexate combined with ipatasertib can act synergistically to suppress ER⁺ BRCA tumor growth, highlighting its therapeutic potentials for patients with ER⁺ BRCA.

Discussion

Elevated aerobic glycolysis is increasingly acknowledged as a characteristic feature of diverse cancer types. ER⁺ BRCA is distinguished by uncontrolled proliferation, invasive behavior, metastatic potential, and upregulated glycolysis, leading to rapid tumor progression [48]. Here, we uncover the crucial role of CUEDC1 in promoting ER⁺ BRCA growth. CUEDC1 is significantly elevated in ER⁺ BRCA cells and tumor tissues and is involved in regulating CACNG4 expression, contributing to activation of PI3K/AKT signaling, thus being involved in regulation of glycolysis in ER⁺ BRCA cells to mediate tumor growth. Methotrexate was screened as a CUEDC1 inhibitor. In summary, our findings highlight that CUEDC1 accelerates tumor growth in ER⁺ BRCA, and the newly identified CUEDC1/CACNG4/PI3K axis represents a promising therapeutic target for ER⁺ BRCA malignancy.

CUE domain-containing protein-1 (CUEDC1), a 42-kDa protein, consisting of 386 amino acids, is a member of the CUE structural domain-containing proteins (CUEDC) family [49]. Reports have uncovered the crucial involvement of CUEDC2 in the progression of various cancers, with breast cancer being one of the key examples [50, 51]. However, the exact molecular role of CUEDC1 in ER⁺ BRCA progression remains unclear. In this study, we show that CUEDC1 works as crucial driver in ER⁺ BRCA progression. Increased CUEDC1 leads to augmented malignancy, including rapid cell proliferation and glycolytic reprogramming. The close relationship between elevated CUEDC1 and poor disease progression of ER⁺ BRCA indicates that CUEDC1 may serve as a promising diagnostic biomarker for ER⁺ BRCA. Moreover, both bioinformatic and experimental evidence confirm that MAZ is an upstream transcriptional regulator of CUEDC1, suggesting that targeting the MAZ/CUEDC1 axis could be a promising therapeutic strategy for ER⁺ BRCA.

CACNG4, acting as the gamma subunit of the L-type voltage-gated calcium channel, is a key target of CUEDC1. Prior studies show that CACNG4 may be a valuable biomarker for breast cancer diagnosis [52] and a potential therapeutic target of tumors; for example, upregulated CACNG4 occurs in EGFR inhibitor (erlotinib)-resistant tumor cell lines [53]. In hepatocellular carcinoma, CACNG4 plays a role in maintaining cancer stem cells [54]. In this study, we validate that CACNG4 is a key effective factor of CUEDC1-mediated tumor growth of ER⁺ BRCA, further emphasizing its substantial role in CUEDC1-induced tumor development. However, the detailed molecular mechanism of how CUEDC1 regulates CACNG4 expression in ER⁺ BRCA needs to be explored in the future. Clinically, we confirmed that the increased CACNG4 is positively correlated with CUEDC1 in ER⁺ BRCA tissues, suggesting the potentially biological and diagnostic value of CUEDC1 and CACNG4 in ER⁺ BRCA tumors.

The activated CUEDC1/CACNG4/PI3K axis is necessary for ER⁺ BRCA growth. It is well known that PI3K/AKT/mTOR signaling is a key regulatory cascade for many cellular biological behaviors, including growth, metabolism, and survival [55]. In luminal breast cancer, the robust PI3K/AKT signaling is believed to be involved in driving tumor malignancy and progression [56]. Thus, specific targeting of PI3K/AKT signaling has been considered a good strategy for ER⁺ BRCA treatment [57, 58]. In this study, CUEDC1 was found to positively regulate the activation of PI3K/AKT signaling via CACNG4, contributing to ER⁺ breast tumor growth. Ipatasertib, which is in a current clinical phase II trial as an AKT-targeting drug for human breast cancer [59], was found to effectively counteract CUEDC1-mediated tumor-promoting effects, significantly reducing both cell proliferation and tumor growth. Our findings emphasize a key role of the CUEDC1–CACNG4 axis in propelling ER⁺ BRCA progression via PI3K/AKT signaling activation.

Our work reveals that CUEDC1-mediated glycolysis is critical for ER⁺ BRCA growth. Generally, activated glucose metabolism is an important factor fueling the progression of various tumors. For instance, estrogen (E2) substantially boosts ER-dependent rapid signaling, which enables ERα-positive breast cancer cells to augment glucose uptake to accelerate cell proliferation [60]. In other studies, the role of the PI3K/AKT pathway in glucose metabolism is firmly established [61, 62]. Additionally, multiple studies have indicated that CUEDC2 has a notable role in metabolic reprogramming [30]. However, whether CUEDC1 regulates the PI3K/AKT cascade to affect glucose metabolism remains unknown. In the current study, we uncover CUEDC1–CACNG4 axis-mediated glucose metabolism via PI3K/AKT signaling-regulated GLUT1 expression. GLUT1 is the primary glucose transporter [63], responsible for importing glucose from the extracellular environment into the cytoplasm, thereby supporting glycolysis reprogramming to fuel tumor development [35, 36, 64]. These studies suggest that targeting GLUT1 may eliminate the malignant proliferation of ER⁺ BRCA cells mediated by the CUEDC1/CACNG4 axis. Indeed, several studies have shown that GLUT1-targeted inhibition has significant therapeutic efficacy [65–68]. We intend to explore in depth whether targeted inhibition of GLUT1 can suppress the malignant proliferation of ER⁺ BRCA cells mediated by the CUEDC1/CACNG4 axis in the future.

More importantly, our study identifies a potential inhibitor of CUEDC1. Using the CMap database, a comprehensive platform with detailed gene expression profiles from almost 5000 small-molecule compounds, which may help pinpoint promising therapeutic candidates [43, 69], we compiled a list of potential CUEDC1 inhibitors on the basis of their ability to induce gene expression profiles similar to those observed in CUEDC1 knockdown. Among them, methotrexate (MTX) was selected as the strongest candidate to target CUEDC1. A previous study showed that methotrexate can inhibit DNA replication in rapidly proliferating cancer cells [70]. However, high doses of methotrexate potentially result in severe toxic side effects. Therefore, reducing the methotrexate dosage in combination with other drugs, such as ipatasertib in our study, could be a rational approach for improved treatment. The combined treatment with low-dose methotrexate and ipatasertib exhibits remarkable antitumor growth effects, suggesting that targeting CUEDC1 is an efficacious treatment for ER⁺ BRCA.

In summary, our study discloses a hitherto-unrecognized regulatory mechanism by which CUEDC1 regulates CACNG4 expression and PI3K/AKT activation to trigger glycolysis, contributing to ER⁺ BRCA progression. The combination of methotrexate, a CUEDC1 inhibitor, with ipatasertib exerts a synergistic effect in suppressing ER⁺ BRCA proliferation.

Conclusions

Our findings underscore the critical tumor-promoting role of CUEDC1 in the progression of ER⁺ BRCA. CACNG4/PI3K signaling caused by CUEDC1 promotes progression of ER-positive breast cancer via augmenting glycolysis. This novel insight into the molecular mechanism of ER⁺ BRCA progression may provide promising opportunities for the development of ER⁺ BRCA diagnosis and therapeutic strategies (Fig. 9).

Fig. 9.

Molecular mechanism diagram of this study. The schematic shows the function of CUEDC1 in promoting ER⁺ BRCA tumor growth. Elevated MAZ in ER⁺ BRCA contributes to CUEDC1 transcription, leading to increased CUEDC1. The enhanced CUEDC1 directly modulates CACNG4 to stimulate activation of the PI3K/AKT signaling pathway, thereby enhancing glycolytic processes and accelerating tumor growth of ER⁺ BRCA. Targeting CUEDC1 combined with ipatasertib reduces ER⁺ BRCA tumor growth

Abbreviations

BRCA

Breast cancer

ER

Estrogen receptor

TAM

Tamoxifen

CUEDC2

CUE domain-containing protein-2

CUEDC1

CUE domain-containing protein-1

ESR1

Estrogen receptor 1

shRNA

Short hairpin RNA

MAZ

MYC-associated zinc finger protein

RNF43

Ring finger protein 43

CACNG4

Calcium voltage-gated channel auxiliary subunit gamma 4

siRNA

Small interfering RNA

ECAR

Extracellular acidification rate

GLUT1

Glucose transporter 1

PI3K

Phosphoinositide 3-kinase

AKT

Protein kinase B

p-AKT

Phosphorylated AKT

TME

Tumor microenvironment

LDHA

Lactate dehydrogenase A

GLUT3

Glucose transporter 3

ALL

Acute lymphoblastic leukemia

STAT3

Signal transducer and activator of transcription 3

HER2

Human epidermal growth factor receptor 2

TNBC

Triple-negative breast cancer

GLUT4

Glucose transporter 4

mTOR

Mammalian target of rapamycin

EGFR

Epidermal growth factor receptor

HR

Hormone receptor

Authors’ contributions

Lingfeng Tang and Manran Liu conceptualized and designed this study, and revised the draft. Zexiu Lu, Ming Lei, and Jian Chen performed the majority of the experiments and data analysis, and drafted the manuscript. Ao Deng, Jing Chen, Die Meng, and Chao Chang assisted with experimental work. Rui Wang, Xueying Wan, and Gang Tu collected patient samples and helped to organize the figures. All authors have read and agreed to the published version of the article.

Funding

This work was supported by the Clinical College Clinical Medicine first-class discipline construction project to the Department of Breast and Thyroid Surgery (CYYY-BSYJSCXXW-202322), and also partly by the Outstanding Professorship Program of Chongqing Medical University (2019-R10005) to Manran Liu.

Data availability

All data are available upon reasonable request. The RNA-seq data have been deposited in the Gene Expression Omnibus (GSE306470).

Declarations

Ethics approval and consent to participate

The research adhered to the Declaration of Helsinki and both national and international ethical standards. The Ethics Committee of The First Affiliated Hospital of Chongqing Medical University approved the use of clinical materials (approval no. 2020–202, 29 April 2020; approval no. K2023-514, 11 October 2023), and informed consent was obtained from all patients before this research. All animal experiments were performed in accordance with the International Council for Laboratory Animal Science (ICLAS) guidelines and approved by the Institutional Animal Care and Use Committee of Chongqing Medical University (approval no. IACUC-CQMU-2023–0267, 28 September 2023).

Consent for publication

All authors approved the manuscript for submission and gave their consent for publication.

Competing interests

The authors declare that they have no competing interests.