The non-malignant breast epithelial cell line, MCF-10A (Cat# CRL-10317), and triple-negative metastatic breast cancer cell lines MDA-MB-231 (Cat # HTB-26) and MDA-MB-468 (Cat # HTB-132) were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA). MCF-10A cells were grown in a mammary epithelial cell basal medium supplemented with 5% horse serum, 0.5 mL epidermal growth factor, 0.5 mL insulin, 0.5 mL hydrocortisone, 2 mL bovine pituitary extract (all from Lonza, Clonetics, MEGM SingleQuots kit), 10 U/mL penicillin, and 10 mg/mL streptomycin (Gibco, Life Technologies). MDA-MB-231 and MDA-MB-468 cells were maintained in the Roswell Park Memorial Institute (RPMI)-1640 medium (Invitrogen Corporation, Carlsbad, CA, USA) supplemented with 10% heat-inactivated fetal bovine serum (FBS), 10 U/mL penicillin, and 10 mg/mL streptomycin (Gibco, Life Technologies). Phenol red-free RPMI 1640 medium supplemented with 10% charcoal-stripped serum (Equitech-Bio, Kerrville, TX, USA) was utilized for all cell lines in this study. This medium was applied 48 hours before 2ME2 treatment to prevent estrogen interference and ensure the accuracy of the observed results. Mycoplasma contamination was tested using the MycoSEQ Plus Mycoplasma Detection Kits (ThermoFisher Scientific Cat # A55124). All cells were maintained at 37°C in a 5% CO₂ atmosphere.

An in vitro cell viability assay was performed as previously described (36). Briefly, MDA-MB-231, MDA-MB-468, and MCF-10A cells were seeded in a 96-well plate at a density of 5 × 10³ cells/well and incubated at 37°C. After 24 h, the cells were treated with different concentrations of 2ME2 (0, 1, 2, 5, 7.5, 10, and 20 μM) and incubated for different time periods from 24 to 72 h at 37°C. After incubation, twenty microliters of the Cell Titer 96 Aqueous One Solution Reagent (Promega) was added to each well of the 96-well assay plate containing the samples in 100 μL of the culture medium. The plates were incubated at 37°C for 4 h in a humidified 5% CO₂ atmosphere. Cell viability was determined by measuring the absorbance at 490 nm using a 96-well microplate reader (CLARIOstar; BMG LABTECH, Cary, NC, USA).

Western blotting was performed to quantify the expression of various proteins. Mammalian protein extraction reagent (Cat. no. 78501; Thermo Scientific, Rockford, IL, USA) was used to extract the total protein from whole cell lysates. Proteins were separated using SDS-PAGE and then transferred to polyvinylidene fluoride (PVDF; cat. no. IPVH00010; EMD Millipore) membranes. The membranes were blocked for 1 h with 5% bovine serum albumin (Cat. no. A7906; Sigma-Aldrich, St Louis, MO, USA) prepared in Tris-buffered saline with 0.1% Tween-20. Then, the blots were incubated with primary antibodies (pAKT, AKT, pmTOR, mTOR, pP70S6K, P70S6K, E-cadherin, N-cadherin, vimentin, slug, zinc finger E-box-binding homeobox 1 [Zeb1], cyclin-dependent kinase [CDK]4, CDK6, cyclin D1, p21, cleaved poly[ADP ribose] polymerase [PARP], cleaved caspase 3, Bcl-associated killer (BAK), Bcl-2, and β-actin) overnight at 4°C. Details regarding antibodies and their dilutions are provided in the Supplementary Materials as Table 1 . After washing thrice with TBST, the blots were incubated with the appropriate horseradish peroxidase-conjugated secondary antibodies to detect the primary antibodies and visualized using enhanced chemiluminescence.

Image Studio software was used to quantify protein expression from digitally imaged Western blots. An equal dimension rectangle tool from the analysis ribbon was used to draw lanes around the entire region where bands were present, allowing for measurement of all protein signals. Background subtraction was applied to each band within a lane to eliminate background noise from the calculations. The intensity values of the bands corresponding to the protein of interest were normalized to their respective β-actin intensity values. The data are represented as the percentage of protein expression normalized to β-actin.

MDA-MB-468 cells in logarithmic growth phase were harvested and seeded in a 6-well plate at a density of 5.0 × 10⁵ cells/well. After overnight culture, the cells were treated with 5 μM 2ME2 for 24 h, harvested, and stained with propidium iodide. The percentage of cells in each phase of the cell cycle was analyzed via flow cytometry using FACS Accuri C6 flow cytometer (BD Biosciences San Jose, CA, USA).

MDA-MB-468 cells were seeded in a 6-well plate at a density of 2.0 × 10⁵ cells/well and treated with 5 μM 2ME2 for 24, 48, and 72 h. Apoptosis was detected using the Annexin V-FITC Apoptosis Detection Kit I and analyzed using the FACS Accuri C6 flow cytometer (BD Biosciences San Jose, CA, USA), according to the manufacturers’ instructions.

The migration assay was performed using 2ME2 (2 and 5 μM)-treated MDA-MB-468 cells. Cells (5 × 10³ cells/well) were seeded in a serum free medium in the top chamber of the transwell with a non-coated polycarbonate membrane (6.5 mm diameter insert, 8.0 μm pore size; Corning Incorporated). In the lower chamber, RPMI-1640 medium with 10% FBS was added. The cells were incubated for 48 h at 37°C and 5% CO₂. Migrating cells on the lower surface of the membrane were fixed with 5% formalin and stained with 0.2% crystal violet. Non-migrating cells on the upper side of the insert were wiped off using a cotton swab. Images of the migrated cells were captured and counted in a blinded manner in five different microscopic fields at 20× magnification.

Invasive ability of MDA-MB-468 breast cancer cells was further assessed after treatment with 2ME2 (5 μM) using a matrigel-based invasion assay. Cells were seeded in a serum-free medium at a density of 0.5 × 10⁵ cells/well in the upper chamber of a 6.5-mm transwell with 8.0 mm pore polycarbonate membrane inserts (Corning) coated with matrigel (Cat. no. 354234; BD Biosciences). The lower chamber was filled with the medium containing 10% FBS and incubated for 48 h at 37°C. After incubation, matrigel from the upper chamber was gently scraped using Q-tips. The cells invaded on the other side of the membrane facing the lower chamber were rinsed with 1× PBS and the cells were fixed with 4% paraformaldehyde. The invaded cells were then stained with 0.1% crystal violet for 2 h. Then, the insert wells were washed with tap water and imaged under an inverted phase contrast microscope (Eclipse Ti; Nikon).

Colony formation assay was performed to assess the clonogenic ability of single cells under anchorage-independent growth conditions. MDA-MB-468 cells (2 × 10⁴) were seeded in 60-mm dishes containing a top layer of 0.7% agarose and bottom layer of 1% agar. The cells were treated with 2 and 5 μM 2ME2 for 24 h and incubated at 37°C for four weeks, and stained with 0.2% crystal violet. Stained colonies were imaged using an inverted microscope. Colonies containing more than 50 cells were manually counted.

miRNA profiling was performed using the Qiagen Human miRNome miScript miRNA PCR Array (Cat. no. MIHS-216Z). First, RNA was extracted from MDA-MB-468 cells using TRIzol (Life Technologies) after treatment with 2ME2 (5 μM) for 24 h. Then, whole human miRNome profiling PCR array was performed using the miScript SYBR Green PCR Kit (Qiagen). miRNA expression data were assessed using miRNet (http://www.mirnet.ca/).

Total RNA was isolated from MDA-MB-468 and MDA-MB-231 cells after treatment with 2ME2 (5 μM) for 24 h using the Trizol reagent (Life Technologies). The top 5 up-regulated and down-regulated miRNAs and its target genes were validated using RTqPCR. The appropriate primers used for each miRNA and its target genes is provided in the Supplementary Materials section as Tables 2 and 3 . The analyses were performed based on the comparative Ct method (2−ΔΔCt).

KEGG pathway analysis comprises pathway maps that help our understanding of molecular interactions, reactions, and relational networks in various categories, including Metabolism, Genetic Information Processing, Environmental Information Processing, Cellular Processes, Organismal Systems, Human Diseases, Drug Development, etc. Altered pathways were studied using KEGG and GO after 2ME2 treatment. Enriched pathway analysis was performed via hierarchical genome-wide visualization using the Reactome Analysis Tool (http://reactome.org). Significantly enriched pathways are shown in yellow, whereas less significantly enriched pathways are shown in gray. Then, miRNA target genes were uploaded to the Reactome database and significantly enriched pathways had a false discovery rate < 0.05.

Using the miRNA target genes, we explored the possible genetic alterations, including truncation, in-frame mutations, missense mutations, gene amplification (overexpression), and deletions, caused by 2ME2 treatment. Our differentially expressed gene dataset was uploaded to the cBioPortal (http://cbioportal.org/) database. In the cBioPortal database, we validated genes using The Cancer Genome Atlas (TCGA) and analyzed the overall survival of patients with either high or low expression of miRNA target genes after 2ME2 treatment. Kaplan–Meier plots were generated using breast carcinoma samples from TCGA database using Kmplot.com and UALCAN. Genetic alterations were visualized using Oncoprint diagrams of breast carcinoma samples. Using the Xena platform (http://xenabrowser.net), we further determined the changes in the gene expression profiles of TCGA breast cancer samples after 2ME2 treatment.

All data were analyzed using GraphPad Prism 9 (Dotmatics). All in vitro experiments were repeated at least three times and had 3–6 replicates. Student’s t-test was performed to compare between two groups and one-way ANOVA and Tukey post hoc test were used for analysis when more than two groups were compared, and statistical significance was set at P < 0.05.

To determine the efficacy of 2ME2 for TNBC treatment, we evaluated its effects on the growth and proliferation of TNBC cells. TNBC (MDA-MB-231 and MDA-MB-468) and non-malignant breast epithelial (MCF-10A) cell lines were treated with various concentrations of 2ME2 (0, 1, 2, 5, 7.5, 10, and 20 μM). High doses of 2ME2 increased the death of TNBC cells but did not exert any significant effects on MCF10A cells. After 24-h treatment, none of the tested doses induced 50% cell death in the cell lines. Treatment with 2 and 5 μM of 2ME2 for 48 h inhibited the proliferation of MDA-MB-468 cells by approximately 50% ( Figure 1A ). Even though 2 μM of 2ME2 was effective 5 μM dose was closest to the IC₅₀ value, so we chose to use this dose for our experiments. In contrast, even high doses of 2ME2 (20 μM) did not have a major impact on MCF-10a cell proliferation. MDA-MB-231 cell proliferation was inhibited by 2ME2 in a dose-dependent manner but higher doses of 2ME2 were required ( Figure 1A ). Therefore, MDA-MB-468 cells were used for subsequent analyses. AKT/mTOR signaling pathway is hyperactive in cancer cells, facilitating cancer cell growth and proliferation (37, 38). Here, treatment with 5 μM 2ME2 for 24 h decreased the phosphorylation of AKT and mTOR ( Figure 1B and Supplementary Figure 1A ). We also observed decreased phosphorylation of AKT in MDA-MB-231 cells treated with 2ME2 ( Supplementary Figures 1B, C ). Next, we focused on the ribosomal protein kinase, P70S6K, which acts downstream of mTOR and regulates cell growth via G1 phase cell cycle progression (37, 39). Here, the active form of P70S6K was minimally expressed in 2ME2-treated cells ( Figure 1C and Supplementary Figure 1D ). 2ME2 effectively inhibited cell proliferation by reducing the activation of AKT, mTOR and P70s6Kinase. However, further analysis is needed to better understand the involvement of the PI3K/AKT signaling pathway by 2ME2 as a crucial mechanism in controlling TNBC proliferation.

Metastatic characteristics of cancer cells are defined by their ability to migrate, invade, and form a niche (colony) in other tissues/organs (40). This makes cancer more aggressive and difficult to treat. In this study, the metastatic characteristics of TNBC cells were assessed in the presence of 2ME2. We found that TNBC cell migration was inhibited by 58 and 77% after treatment with 2 and 5 μM 2ME2, respectively ( Figures 1D, E ). Invasion and colony formation were reduced in 2ME2-treated MDA-MB-468 cells than in the untreated cells ( Figures 1F–I ). Similarly, MDA-MB-231 cells treated with 2ME2 showed a significant reduction in migration and invasion capabilities ( Supplementary Figures 1E, F ) respectively. Change in cellular morphology from epithelial to mesenchymal, known as the epithelial–mesenchymal transition, is a prerequisite for metastasis (41). Treatment with 2ME2 decreased the levels of mesenchymal markers, such as N-cadherin, vimentin, slug, and Zeb1, but increased the levels of the epithelial marker, E-cadherin ( Figure 1J and Supplementary Figure 1G ). MDA-MB-231 cells also responded similarly to 2ME2 in terms of E-cadherin and N-cadherin regulation ( Supplementary Figures 1H–J ) respectively. These data demonstrate the potent roles of 2ME2 in inhibiting the aggressiveness and metastatic characteristics of TNBC cells.

Ribosomal protein P70S6K is active during the G1 phase of cell cycle and regulates the cellular machinery via protein synthesis required for cell division (42). P70S6K phosphorylates and regulates the functions of the 40s ribosomal protein (S6), eukaryotic initiation factor 4B, and eukaryotic elongation factor 2 kinase that are required for protein synthesis (43–45). The potent role of P70S6K in the cell cycle and its low activation in 2ME2-treated cells lead us to further analyze the cell cycle in 2ME2-treated MDA-MB-468 cell lines. We analyzed the effect of 2ME2 on the cell cycle using flow cytometry. Studies on many cancer types, including breast cancer, have reported that 2ME2 accumulates and arrests cells in almost all phases of the cell cycle, including the G0/G1, G2/M, M phases (46–49). However, its exact roles during specific phases of the cell cycle remain unknown. Our analysis of the cell cycle in 2ME2-treated MDA-MB-468 cells revealed minute changes in the cell population in S-phase (6.46% more cell population was arrested in the S-phase in 2ME2-treated cells compared to that in the non-treated cells) ( Figures 2A, B ). However, analysis of the markers of the G0/G1 or G1/S transition phases revealed a significant difference in the expression patterns of cell cycle regulators ( Figures 2C, D ). Cyclin D1 is a proto-oncogene that forms a complex with CDK-4 and -6 to regulate cell cycle progression at G1 and G1/S phases (50). The active form of cyclin D1, CDK4–CDK6 complex, phosphorylates and inactivates the tumor suppressor gene, retinoblastoma (Rb) (50, 51). Hence, high levels of cyclin D1, CDK4, and CDK6 are often observed in most patients with breast cancer (52, 53). Accordingly, we observed high levels of cyclin D1, CDK4, and CDK6 in MDA-MB-468 cells, which were significantly reduced by 2ME2 treatment in this study ( Figures 2C, D ). MDA-MB-231 cells also exhibited a similar response to 2ME2 in terms of Cyclin D1 regulation ( Supplementary Figures 2A, B ). Similarly, we analyzed the levels of the cell cycle inhibitor, p21, which inhibits the activity of CDK4 during the G1 phase of the cell cycle (54). p21 protein levels were higher in 2ME2-treated MDA-MB-468 cells than in the untreated control cells ( Figures 2C, D ). Our results demonstrate that 2ME2 induced cell cycle arrest in TNBC cells.

Cell death or apoptosis is poorly regulated in cancer cells, resulting in their uncontrolled growth (55). Here, we investigated whether 2ME2 induces apoptosis in MDA-MB-468 breast cancer cells. We used the Annexin V-FITC Apoptosis Detection Kit I with flow cytometry to evaluate apoptosis/cell death in 2ME2-treated TNBC cells. Cells treated with 2ME2 showed 9.2, 15.9, and 24.5% apoptotic death 24, 48, and 72 h after treatment, respectively ( Figures 2E, F ). To confirm this, we analyzed the regulators of apoptosis based on the expression levels of different apoptotic markers using immunoblotting analysis. Notably, 2ME2 treatment significantly increased the levels of cleaved PARP, cleaved caspase 3 and BAK but decreased the levels of Bcl-2 ( Figures 2G, H ). Finally, we investigated the effect of 2ME2 on Bak and cleaved caspase-3 expression using MDA-MB-231 cells, which demonstrated the activation of these apoptotic markers at all tested time points ( Supplementary Figures 2C, D ). This finding indicates that 2ME2 acts as an anti-cancer agent by inducing intrinsic mediated apoptosis in TNBC cells.

The specific effects of 2ME2 on TNBC miRNomes remain unknown. Therefore, in this study, we explored the miRNA disruptions. MDA-MB-468 cells treated with 2ME2 (5 µg for 24 h) were subjected to miRNome analysis. Over 1,000 mature miRNAs were studied using the miScript miRNA PCR array (miRNome V16). We identified the top 20 most upregulated and downregulated miRNAs ( Figure 3A ). We validated the differential expression of top 5 up- and down-regulated miRNAs using RTPCR in 2ME2 treated MDA-MB-468 ( Supplementary Figures 3A, B ) and MDA-MB-231 cells ( Supplementary Figures 3C, D ). Here, we aimed to identify the target genes of both the upregulated and downregulated miRNAs. In silico analysis was performed using the miRNet database to identify the miRNA target genes ( Figures 3B, C ). Moreover, we used the miRNet database to identify the signaling pathways associated with the genes altered by 2ME2 through miRNAs. KEGG pathway analysis demonstrated that the upregulated miRNA target genes were mainly involved in mTOR signaling, cancer-related, and p53 signaling pathways ( Figure 3D ). Downregulated miRNA target genes were also involved in cancer-related, p53 signaling, mitogen-activated protein kinase (MAPK) signaling, and apoptosis pathways ( Figure 3E ). Further, the impact of some of the differentially regulated miRNAs on overall survival was assessed using Kmplot and UALCAN, which demonstrated that the miRNAs upregulated (hsa-miR-600, hsa-miR-2117 & hsa-miR-3200) and downregulated miRNAs (hsa-miR-96, hsa-miR-19a & hsa-miR-19b-2) by 2ME2 increased survival of triple negative breast cancer patients ( Supplementary Figures 4A, B ). These data demonstrate that 2ME2 effectively alters miRNome.

After identifying the miRNA target genes using the miRNet database, we uploaded the target genes to the Xena browser to study their expression patterns. Xena browser database enabled the exploration of gene expression directly using the human samples profiled from TCGA database. Then, the expression patterns of miRNA target genes from mTOR signaling, cancer signaling, focal adhesion, p53 signaling, carbohydrate digestion and absorption, insulin signaling, cell cycle, JAK-STAT, ErBb signaling, and adherens junction pathways were plotted ( Figures 4A–E and Supplementary Figures 5A–E ). Downregulated miRNA target genes were associated with neurotrophin signaling, cancer signaling, p53 signaling, MAPK signaling, apoptosis, T cell receptor signaling, endocytosis, insulin signaling, cell cycle, and ErBb signaling pathways ( Figures 5A–D and Supplementary Figures 6A–F ). PIK3R1, HSP90AA1, ERBB2, CCND1, and PTPRF were the target genes of the top five upregulated miRNAs ( Figures 6A , B ). Meanwhile, CDC42, HSP90B1, CCND1, HSPA8, PRKAR1A, AKT1, RAB5B, FASN, and GRB2 were the target genes of the top downregulated miRNAs ( Figure 6C ). The expression of these genes were validated using RTqPCR. In general the all the target genes of up-regulated miRNAs were down regulated significantly by 2ME2 treatment in both TNBC cell lines. Interestingly, we also observed that some of the target genes of the down-regulated miRNAs were significantly upregulated ( Supplementary Figures 7A-D ). These genes have been shown to influence overall survival of breast cancer patients. When we analyzed combined effect of these up- and down-regulated genes on overall survival, we observed the expected trends but they were not statistically significant. ( Figure 6D ).

Pathway topology analysis of miRNA target genes was performed using the Reactome pathway identifier database. In silico analysis enabled the identification of the differentially expressed genes mapped to different pathways. Interestingly, 2ME2 treatment led to the activation of various pathways, including the development, signal transduction, immune system, and vehicle-mediated transport pathways ( Figure 7 ).