Natural Compound Melatonin Suppresses Breast Cancer Development by Regulating Circadian Rhythm

The human MCF7, SKBR3, Hela, and mouse 4T1 breast cancer cell lines (zqxzbio, Shanghai, China) were cultured in Dulbecco's modified Eagle's medium (DMEM) (Gibco, Waltham, MA, USA) fortified with 10% FBS and 1% antibiotics (Gibco, Waltham, MA, USA), at 37 °C in a 5% CO₂ environment. All cell lines tested mycoplasma-negative and were authenticated using short tandem repeat (STR) profiling. Dimethyl sulfoxide (DMSO), Melatonin and SR8278 were purchased from MedChemExpress (MCE, New York, NY, USA). Melatonin and SR8278 were prepared in DMSO according to the manufacturer's protocol, aliquoted, and stored at −80 °C.

In this study, datasets from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) dataset GSE42568 were selected to conduct gene expression-related analyses. Survival analysis was performed using the "survminer" package (version 0.4.9) and "survival" package (version 3.5.7) in the R statistical environment. The Kaplan–Meier estimator was used to plot survival curves, with a p-value < 0.05 set as the threshold for determining statistical significance. Heatmaps of differentially expressed genes (DEGs) were constructed using the "pheatmap" package in the R programming environment. Gene Ontology (GO) enrichment analysis was implemented using the "clusterProfiler" package (version 4.10.0) combined with the "ggplot2" package (version 3.5.1) in R, covering three major categories: Molecular Function (MF), Biological Process (BP), and Cellular Component (CC). The criteria for enhanced significance were set as both p-value and q-value < 0.05. Additionally, Gene Set Enrichment Analysis (GSEA) was applied to detect the complete transcriptome data of all tumor samples, thereby revealing the potential mechanisms of prognosis-related genes and identifying differentially regulated pathways, with the statistical significance criterion set as a false discovery rate (FDR) < 0.05. To evaluate the binding energy and interaction mode between melatonin and BMAL1, molecular docking was performed using AutoDock Vina 1.2.2. The three-dimensional structure of melatonin was retrieved from the PubChem database, while the crystal structure of BMAL1 was obtained from the Protein Data Bank (PDB). Prior to docking, both the protein and ligand were prepared by removing water molecules, adding polar hydrogen atoms, and converting the files to PDBQT format. A grid box was set to encompass the binding domain of BMAL1, allowing sufficient space for ligand movement. The docking results were visualized using PYMOL software (version 3.0).

BMAL1 siRNA and BMAL1 overexpression plasmid were purchased from TSINGKE (Beijing, China). Lipofectamine 3000 (Invitrogen, Carlsbad, CA, USA) was utilized for transfecting BMAL1 siRNA and BMAL1 plasmids. Following transfection for 48 or 72 h, it is essential to verify transfection efficiency using qRT-PCR or Western blot analysis before moving on to further experiments. All the sequences listed above can be found in. Table S1

The processed samples underwent total RNA extraction using an RNA extraction kit (TSINGKE, Beijing, China). Subsequently, total RNA was transcribed into complementary DNA (cDNA) via one-step reverse transcription polymerase chain reaction (RT-PCR). Real-time quantitative polymerase chain reaction (qPCR) analysis was then performed using SYBR Green PCR master mix (Vazyme Biotech, Nanjing, China). Primer sequences employed in the experiment are detailed in. Table S2

The pre-treated cells were washed once with pre-chilled phosphate-buffered saline (PBS). RIPA lysis buffer was added and placed on ice for lysis. The lysate was scraped into a centrifuge tube and centrifuged at 12,000 rpm for 15 min. The supernatant (total protein) was collected, and the cellular debris pellet was discarded. After determining total protein concentration, equal volumes of protein were loaded onto an 8% SDS-PAGE gel for electrophoresis separation. Subsequently transfer to a polyvinylidene fluoride (PVDF) membrane was performed. The membrane was blocked with 5% skimmed milk for 1–2 h, then incubated with primary antibody overnight at 4 °C. The membrane was washed with TBST, and the corresponding secondary antibody was added and incubated at room temperature for 1 h. After washing again, antibody-binding signals were captured using an ECL chemiluminescent detection kit (ZETA Life, San Francisco, CA, USA). For co-immunoprecipitation (Co-IP) experiments, cells were lysed in buffer containing protease and phosphatase inhibitors. After centrifugation to collect the supernatant, anti-BMAL1 antibody, IgG antibody, and Protein A/G PLUS agarose beads were added for overnight incubation. Following bead washing, results were analysed by Western blotting. Details of antibodies used are provided in. Table S3

To evaluate the viability of the cells, a total of 5000 treated cells were plated per well in a 96-well plate, utilizing the Cell Counting Kit-8 (CCK-8) from Yisheng (Shanghai, China) to track their viability. Following a 60 min incubation period with the CCK-8 solution, the absorbance was measured at 450 nm. In the colony formation study, 400 cells were planted per 60 mm dish. Post a 2-week incubation period, cells were immobilized with paraformaldehyde for a duration of 10 min. Following fixation, the cells were stained with crystal violet (Solarbio, Beijing, China), and the colonies were counted using ImageJ software (version 1.54p).

The 5-Ethynyl-2′-deoxyuridine (EdU) experiment was conducted using the EdU Assay Kit (Beyotime Biotechnology, Shanghai, China). The specific procedure was as follows: cells were first incubated with the EdU solution for 4 h, followed by brief fixation with a 4% paraformaldehyde solution. To enhance cell permeability, cells were treated with PBS containing 0.3% Triton X-100. Next, cells were placed in Click reagent solution for 30 min at room temperature for staining. Nuclear counterstaining was performed using DAPI (Beyotime Biotechnology, Shanghai, China). Finally, images were acquired using a Thermo Fisher Scientific EVOS M5000 fluorescence microscope (Thermo Fisher Scientific, Waltham, MA, USA).

Chromatin immunoprecipitation (ChIP) experiments were conducted using the SimpleChIP Plus Enzymatic Chromatin IP Kit (Cell Signaling Technology, Danvers, MA, USA), with procedures strictly adhering to the protocol. The procedure was as follows: approximately 1.2 × 10⁷ MCF7 cells were taken and fixed using a 1% formaldehyde solution; glycine was subsequently added to terminate the cross-linking reaction. Thereafter, the adherent cells were scraped, and the cell pellet was collected by centrifuging at 2000× g for 5 min. The DNA was digested to an appropriate length using micrococcal nuclease, and the enzymatic reaction was terminated by adding 0.5 M EDTA. Following ultrasonic disruption of the nuclear membrane, the supernatant containing cross-linked chromatin was collected. BMAL1 antibody and IgG antibody were added to the samples and incubated overnight at 4 °C. Subsequently, magnetic beads were added to each reaction system, and incubation was continued under continuous agitation. Following incubation, the magnetic beads were sequentially washed using buffers. Finally, chromatin was eluted from the magnetic beads, and reverse cross-linking was performed. The samples were purified via spin columns and detected using real-time quantitative PCR (qRT-PCR). Primer sequences for ChIP-qPCR are provided in Table S2.

Paraffin-embedded tumor tissue sections underwent dewaxing and rehydration, followed by antigen retrieval. Sections were blocked with 3% bovine serum albumin (BSA) and then incubated overnight at 4 °C with the following primary antibodies: Ki67 (1:300, Abcam, Cambridge, UK), BMAL1 (1:200, Proteintech, Rosemont, IL, USA), and ALDH3A1 (1:200, Origene, Rockville, MD, USA). Sections were washed with phosphate-buffered saline (PBS), followed by staining with 3,3′-Diaminobenzidine (DAB) peroxidase substrate (Vector Laboratories, Oxfordshire, UK). Finally, stained sections were digitally acquired and processed using a digital slide scanning system (WINMEDIC, Shandong, China).

A volume of 150 μL of 1.5% agarose solution was dispensed into each well of a 48-well culture plate. After the agarose had solidified, 10,000 tumor cells were suspended in 200 μL of culture medium, and this suspension was applied onto the agarose-coated surface. Subsequently, the plate was centrifuged at 1000× g for 10 min, followed by incubation under standard culture conditions.

Apoptosis assays employed Annexin V-FITC/PI dual staining (BestBio, Shanghai, China). Following staining, samples were analysed by flow cytometry to distinguish viable cells, apoptotic cells, and necrotic cells. Data acquisition and subsequent analysis were performed using Novo Express software (version 1.4.1) (ACEA Biosciences, San Diego, CA, USA).

Metabolic assays for glucose uptake and lactate production in the culture medium of breast cancer cells were conducted using commercially available kits (Beyotime Biotechnology, Shanghai, China).

The interaction between BMAL1 and the ALDH3A1 promoter was validated using a dual luciferase reporter assay. The ALDH3A1 promoter fragment (region 841–1141 relative to the transcription start site) was cloned into the pGL3-Basic vector (GeneCreate Biotech, Wuhan, China). Twenty-four hours later, the reporter plasmid, pRL-TK control vector, and BMAL1 overexpression plasmid (or empty vector) were co-transfected into cells using Lipofectamine 3000. Detection was performed using a dual luciferase reporter assay kit (Vazyme Biotech, Nanjing, China).

Seven-week-old female Balb/c mice were maintained under a 12 h light/12 h dark cycle. Under isoflurane anesthesia, mice received injections of 5 × 10⁵ 4T1 cells into the fat pad of the fourth mammary gland. Ten days post-injection, the mice were randomly assigned to four experimental groups using a computer-generated random number table (n = 5 per group) and administered intraperitoneally with either phosphate-buffered saline (PBS), melatonin (40 mg/kg), SR8278 (20 mg/kg), or a combination of SR8278 and melatonin, twice weekly for a duration of three weeks. To maintain the circadian rhythm of mice, drug administration was conducted at night throughout the whole experiment. Images were obtained utilizing a PerkinElmer IVIS preclinical in vivo imaging system. At the study endpoint, all mice were euthanized by CO₂ asphyxiation. Tumors and relevant organs were then collected and processed with care to preserve structural integrity. The samples were gently rinsed with PBS, weighed on a precision balance, and fixed in 4% paraformaldehyde for subsequent examination. The animal study was reviewed and approved by the Ethics Committee of the Fourth Military Medical University (approval number: 20230930).

Statistical analyses and graphical representations were performed using GraphPad Prism version 8.0.2. Comparisons between two groups were conducted using Student's t-test, while one-way analysis of variance (ANOVA) was employed for comparisons involving multiple groups. Each experiment was independently replicated a minimum of three times, and the results are expressed as means ± standard deviation (SD). Statistical significance is denoted as follows: * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001. NS indicates no significant difference.

Given melatonin's demonstrated potential anti-tumor activity, to further elucidate its role and effect characteristics in breast cancer, two breast cancer cell lines—MCF7 and SKBR3—were exposed to a gradient concentration of melatonin and incubated under appropriate culture conditions for 24 h. Subsequently, cell viability was quantified across different treatment groups using the Cell Counting Kit-8 (CCK-8) assay, which measures absorbance values. Results demonstrated a gradient decrease in cell viability with increasing melatonin concentrations. The half-maximal inhibitory concentration (IC₅₀) for MCF7 cells was 1.217 mM, while that for SKBR3 cells was 2.023 mM (Figure 1A). Based on these IC50 values, four different concentrations of melatonin were selected for subsequent experiments. Melatonin reduced the viability of BC cells (Figure 1B), as well as their colony-forming (Figure 1C) and proliferative (Figure 1D) abilities. Tumor cells are cultured in conditions lacking suitable attachment surfaces, thereby promoting cellular aggregation into spheroids. This tumor spheroid model simulates the three-dimensional growth microenvironment of in vivo tumors, enabling subsequent evaluation of biological characteristics such as tumor cell self-renewal, drug resistance, and invasive capacity [20]. SKBR3 cells were cultured to form dense spheroids. After treatment with melatonin, their spheroid-forming capacity and size were measured, and the results showed that melatonin could inhibit the growth of tumor spheroids (Figure 1E). Notably, melatonin suppresses cell proliferation in a dose-dependent manner. Exposure to 2 mM melatonin significantly inhibited cell proliferation; furthermore, elevating the concentration to 4 and 6 mM produced a more substantial inhibitory effect in both MCF7 and SKBR3 cell lines. The findings from the apoptosis assays further indicated that the cytotoxic effects of melatonin exhibit a dose-dependent relationship (Figure 1F). Western blot analysis demonstrated that melatonin treatment significantly increased the expression of Bim, a pro-apoptotic protein, while concurrently reducing the levels of Bcl-2, an anti-apoptotic protein (Figure 1G). In summary, our findings indicate that melatonin administration demonstrated a significant and dose-dependent inhibitory impact on cell proliferation.

In this study, a differential analysis was conducted on two microarray datasets (TCGA and GSE42568), and subsequently, a volcano plot was generated to visually present the differentially expressed genes (Figure 2A). Gene Ontology (GO) enrichment analysis of differentially expressed genes (DEGs) identified significant associations with biological processes (BP), cellular components (CC), and molecular functions (MF). The top 5 GO items were listed (Figure 2B). The results revealed that the rhythmic process, the circadian rhythm, was significantly altered. Notably, the enrichment of circadian rhythm-related processes suggests that dysregulation of circadian genes may contribute to BC proliferation. An intersection analysis was conducted on the results derived from the four datasets, yielding ten common key feature genes (Figure 2C). These ten identified genes were subsequently submitted to the STRING database to construct a protein–protein interaction (PPI) network (Figure 2D). We observed that three genes were situated within the network's core region and exhibited a higher number of connecting edges, suggesting they may perform key regulatory functions within the melatonin action mechanism. To further elucidate the expression patterns of these key genes, RNA was extracted from BC cells treated with 2 mM melatonin for 24 h, followed by quantitative real-time reverse transcription PCR analysis. Results revealed a significant upregulation trend in BMAL1 gene expression compared to control cells (Figure 2E). Then, we explored the expression status of BMAL1 in BC samples and found that BMAL1 was significantly down-regulated in BC tissues compared with normal breast tissues (Figure 2F). The survival analysis indicated that patients exhibiting reduced BMAL1 expression levels are associated with decreased overall survival durations (Figure 2G). Molecular docking analysis revealed that BMAL1 and melatonin could form a stable binding conformation (Figure 2H), with a binding energy of −5.193 kcal/mol. These results collectively suggest the possibility of direct binding between the two, but this conclusion requires further experimental verification. Data analysis and experimental verification show that BMAL1, as a key circadian rhythm-related gene, is down-regulated in breast cancer and is associated with poor prognosis. BMAL1 may be an important mediating mechanism of melatonin regulating breast cancer.

Melatonin treatment reprogrammed the circadian expression profile of BMAL1 mRNA, resulting in a transition from a high-amplitude rhythm to a low-amplitude oscillation (Figure 3A). Melatonin generates a robust and stable BMAL1 expression landscape. Western blot analysis revealed that melatonin enhances BMAL1 protein expression in a manner dependent on its concentration (Figure 3B). SR8278 is a synthetic competitive antagonist of the nuclear receptor REV-ERB. It exerts its effect by competitively binding to target DNA sequences of REV-ERB, such as the REV-ERB response element (RORE) within the BMAL1 promoter region. This action releases the inhibitory control of REV-ERB over BMAL1 transcription, thereby promoting the transcriptional expression of BMAL1 [21]. Using the CCK-8 assay to detect and calculate the half-maximal inhibitory concentration (IC₅₀), it was found that SR8278 exhibited a pronounced dose-dependent inhibitory effect on the viability of both MCF7 and SKBR3 cell lines, with successful fitting yielding IC₅₀ values for both cell types (Figure 3C). Further Western blot analysis revealed that following treatment with SR8278, BMAL1 protein expression levels were significantly upregulated in both cell lines. This finding correlates with the inhibitory effect of SR8278 on cell viability (Figure 3D). SR8278 and the endogenous hormone melatonin converge on elevating BMAL1 protein levels. These preliminary research results indicate that melatonin can effectively promote the upregulation of BMAL1 protein expression levels. However, the specific molecular mechanism of its action still needs to be systematically clarified through subsequent experiments. This suggests its role as an intrinsic molecular regulator. Notably, further analysis of BMAL1-regulated differentially expressed genes (DEGs) revealed significant enrichment in glycolytic metabolic pathways. Glycolysis not only supplies ample ATP and intermediate metabolites for rapid tumor proliferation but also plays an irreplaceable role in critical progression processes such as tumor invasion, metastasis, and drug resistance development. This suggests BMAL1 may influence the biological behaviour of breast cancer by regulating the glycolytic pathway (Figure 3E) and exhibits a negative correlation with glycolysis (Figure 3F). Heatmap plot of the top genes with the biggest variances after BMAL1 downregulation (Figure 3G). We found ALDH3A1 as one of the differentially expressed genes. Aldehyde dehydrogenase 3A1 (ALDH3A1) is an enzyme that relies on NAD⁺ as a cofactor to catalyze the oxidation of a range of endogenous and exogenous aldehydes into their corresponding carboxylic acids [22]. Some studies have shown that ALDH3A1 promotes glycolysis and lactate accumulation through activation of the LDHA pathway; inhibition of ALDH3A1 reduces lactate levels and inhibits tumor cell proliferation [23]. Collectively, our data support a model whereby melatonin upregulates the expression of BMAL1, which is associated with ALDH3A1, thereby affecting the glycolytic process and ultimately influencing the proliferation of breast cancer cells.

Given that BMAL1 may represent a downstream target of melatonin, this study further investigated the regulatory effects of BMAL1 overexpression on the biological behaviour of breast cancer cells. Following construction of a BMAL1 overexpression plasmid and its transfection into BC cells, apoptosis levels were assessed via flow cytometry. Results demonstrated a significantly elevated apoptosis rate in the BMAL1 overexpression group compared to the empty vector control group (Figure 4A). Colony formation assessment, CCK-8, and EdU assays showed a significantly lower clonogenicity, cell viability, and proportions of proliferating cells in MCF7 and SKBR3 cells with BMAL1 overexpression (Figure 4B–D). Additionally, expression of glycolysis-related genes was decreased at the protein level, and the decrease was more pronounced when melatonin was co-administered (Figure 4E). Prior research indicates that BMAL1 may modulate the proliferative potential of breast cancer cells through the regulation of glycolytic processes. To investigate the involvement of glycolytic dysregulation in breast cancer progression, this study evaluated two critical metabolites within the glycolytic pathway: glucose uptake and lactate production. The findings revealed that, consistent with expectations, overexpression of BMAL1 markedly decreased both the glucose uptake capacity (Figure 4F) and lactate production (Figure 4G) in breast cancer cells. In summary, overexpression of BMAL1 exerts an inhibitory effect on breast cancer cells by promoting apoptosis, suppressing proliferation, and downregulating glycolysis-related pathways. The inhibitory effects of BMAL1 overexpression were potentiated by co-treatment with melatonin, indicating that melatonin's anti-tumor effects are consistent with and may amplify the BMAL1-mediated suppression of glycolysis and proliferation.

To investigate whether silencing BMAL1 can reverse the decrease in breast cancer cell viability and clonogenicity induced by melatonin treatment in vitro, we conducted relevant experiments. The results showed that silencing BMAL1 reduced cell apoptosis (Figure 5A); further observations via colony formation assays and CCK-8 assays (Figure 5B,C) revealed that it could restore the proliferative capacity of breast cancer cells (Figure 5D). Meanwhile, the protein expression levels of glycolysis-related genes were restored (Figure 5E), and both glucose uptake (Figure 5F) and lactate production (Figure 5G) were also recovered. These results indicate that silencing BMAL1 can reverse the pro-apoptotic effect of melatonin treatment on breast cancer cells, restore their proliferative activity and glycolytic function, and thus validate from the reverse perspective that BMAL1 plays a key mediating role in the regulation of breast cancer by melatonin.

Drawing upon the findings from prior experiments, we hypothesized that ALDH3A1 functions as a downstream gene regulated by BMAL1 in BC cells. Western blot analysis revealed that in both MCF7 and SKBR3 breast cancer cell lines, the protein expression levels of ALDH3A1 exhibited a negative correlation with BMAL1 expression status. Upon silencing BMAL1, ALDH3A1 expression was significantly upregulated in the cells; conversely, when BMAL1 was overexpressed via transfection with an overexpression plasmid, ALDH3A1 expression was markedly reduced (Figure 6A). Western blot analysis indicates that melatonin treatment resulted in decreased ALDH3A1 protein expression levels. Considering this finding alongside the regulatory relationship between BMAL1 and ALDH3A1, this downregulation effect may be associated with melatonin's upregulation of BMAL1 expression (Figure 6B). To investigate how BMAL1 influences ALDH3A1, co-immunoprecipitation (co-IP) assay was performed. The results showed that BMAL1 did not directly interact with ALDH3A1 in MCF7 cells (Figure 6C). BMAL1 is a transcription factor that has been extensively studied to date. Its core mechanism of action involves binding to the promoter regions of downstream target genes, thereby initiating and activating the transcription process of these target genes. Chromatin immunoprecipitation (ChIP) analysis demonstrated that BMAL1 is capable of binding to site 2 within the promoter region of ALDH3A1 (Figure 6D). Luciferase reporter assay unveiled that the site2 was critical to BMAL1-mediated suppression of ALDH3A1 expression (Figure 6E). These findings thus demonstrate that BMAL1 can specifically bind to site 2 of the ALDH3A1 promoter, thereby suppressing ALDH3A1 expression at the transcriptional level. This establishes ALDH3A1 as a downstream target gene regulated by BMAL1.

Subsequently, animal models were established to examine the effects of melatonin and SR8278 on the tumorigenesis of 4T1 cells in vivo (Figure 7A). The findings demonstrated that treatment with either melatonin or SR8278 significantly inhibited tumor growth, with their combined administration resulting in a further reduction in tumor size (Figure 7B–D). No significant differences in body weight were observed among the experimental groups (Figure 7E). Consistent with expectations, assessments revealed no evidence of nephrotoxicity, hepatotoxicity, or splenic toxicity across all four groups, suggesting that melatonin and SR8278 do not induce severe toxicity or adverse effects on these organs (Figure 7F). Furthermore, immunohistochemical analysis indicated that the combined treatment with SR8278 and melatonin markedly upregulated BMAL1 expression while concurrently suppressing the expression of Ki67 and ALDH3A1 (Figure 7G).