Metformin suppressed epithelial-mesenchymal transition, cisplatin resistance and metastatic potential of ovarian cancer via inhibiting TGF-β1/Smads

Introduction

Ovarian cancer (OC) is one of the most common gynecologic tumors worldwide (1). Due to the lack of heterogeneous symptoms in the early stages, most patients are often diagnosed in the late stages (2). Currently, the main treatment for OC includes surgical resection and chemotherapy (3). However, patients with OC have a poor prognosis, with a 5-year survival rate of 30% to 50% (4). Many patients still suffer from recurrence, metastasis and drug resistance after therapy. Therefore, it is urgent to discover new drugs overcoming drug resistance and metastasis in OC to improve treatment efficacy and patient prognosis.

Epithelial-mesenchymal transition (EMT) is a crucial process in embryonic development and tissue regeneration. The abnormal reactivation of EMT promotes the malignancy of tumors, thereby facilitating cancer progression and metastasis (5). The cancer cells undergoing EMT may share common traits with high invasion and treatment-resistance, as they lose epithelial characteristics and adhesive capabilities, while gaining increased mobility (6). Therefore, inhibiting EMT progression has become a promising strategy for tumor intervention. It is known that the occurrence of EMT is closely related to abnormal activation of transforming growth factor beta (TGF-β) signaling, which has emerged as a critical regulatory pathway in tumor biology due to its central role in governing EMT and tumor metastasis. TGF-β signaling can drive EMT and promote metastatic behavior in various malignant tumors. In cervical cancer, TGF-β signaling is activated by CDR1as, initiating EMT to enhance cancer cell metastasis potential (7). In breast cancer, TGF-β exerts its effect through its type I receptor TβRI, inducing EMT-like molecular changes and lung metastasis (8). In small cell lung cancer, TGF-β/Smad signaling can be regulated by ESRP1/CARM1 axis, which in turn promotes EMT-mediated cell migration and drug resistance (9). Inhibition of TGF-β signaling has been demonstrated to effectively suppress EMT processes, reduce metastatic potential, and counteract multidrug resistance in tumor cells (10). Thus, TGF-β signaling pathway represents a promising therapeutic target for intervening during caner EMT progression.

There is growing evidence that routine drugs for some diseases may be repurposed to treat others. Metformin is a clinical drug used for treating type 2 diabetes with obesity. Recent studies have shown that metformin can directly activate AMPK and inhibit mTOR to suppress proliferation and metastasis of tumor cells (11). It has also been found that metformin acts as a sensitizer in cancer treatment, enhancing the efficacy of LW6 against pancreatic cancer (12). Notably, although metformin has exerted suppressive properties for tumor progression in multiple cancers, including breast cancer, colorectal cancer, lung cancer and endometrial cancer (13-16), the role and mechanism of metformin in OC metastasis and drug resistance are yet to be fully elucidated.

In this study, we aimed to investigate the effect of metformin on EMT progression of OC. The results revealed that metformin simultaneously decreased metastatic potential and cisplatin (cDDP) resistance of OC cells. Furthermore, metformin was found to inhibit TGF-β1/Smads signaling, thereby suppressing EMT, metastatic potential and drug resistance in OC cells. These findings provided a novel strategy for improving the efficacy of OC treatment. It is valuable to elucidate the anticancer effects of metformin in OC and to advance its application in the development of novel therapeutic agents. We present this article in accordance with the MDAR reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2599/rc).

Methods

Cell culture

The human OC cell line SKOV3 and its cDDP-resistant subline SKOV3/cDDP were cultured in McCoy’s 5A medium supplemented with 10% fetal bovine serum and 1% penicillin-streptomycin. All cells were maintained in a humidified incubator at 37 ℃ with 5% CO₂. When cell confluence reached 80–90%, cells were digested with 0.25% trypsin-ethylenediaminetetraacetic acid (EDTA) for passage. Prior to the experiment, all cell lines were authenticated by short tandem repeat (STR) profiling, and routine testing ensured the absence of mycoplasma contamination.

Reagents and antibodies

cDDP (Cat. No. HY-17394) and TGF-β1 (Cat. No. HY-17394) were purchased from MedChem Express (Monmouth Junction, NJ, USA). McCoy’s 5A (M5A, Cat. No. PM150710) and penicillin and streptomycin mixed solution (Cat. No. PB180120) were purchased from Pricella Biotechnology (Wuhan, China). Fetal bovine serum (FBS) (Cat. No. F8318) was procured from Sigma-Aldrich (St. Louis, MO, USA). Primary antibodies against E-Cadherin (Cat. No. 3195), N-Cadherin (Cat. No. 13116), Snail (Cat. No. 3879), Slug (Cat. No. 9585), and Zeb-1 (Cat. No. 9585) were procured from Cell Signaling Technology (Danvers, MA, USA). Primary antibodies against Smad2 (Cat. No. PTM-5153), Smad3 (Cat. No. PTM-20090), and β-tubulin (Cat. No. PTM-6414) were procured from PTM BioLab (Hangzhou, China). Primary antibodies against Smad4 (Cat. No. ET1604-12), p-Smad2 (Cat. No. ET1612-32), p-Smad3 (Cat. No. ET1609-41), and GAPDH (Cat. No. ET1601-4) were procured from Huaan Biotechnology (Hangzhou, China). BCA protein assay kit (Cat. No. P0011), RIPA lysate (Cat. No. P0013B), cell counting kit-8 (CCK-8) (Cat. No. C0038), Crystal Violet (Cat. No. C0121), and Matrix-Gel^TM (Cat. No. C0371) were purchased from Beyotime (Shanghai, China). Primary antibodies against TGFβR I (Cat. No. 30117-1-AP), TGFβR II (Cat. No. 66636-1-Ig), the horseradish peroxidase (HRP)-coupled secondary antibody, rabbit IgG (Cat. No. RGAR001), mouse IgG (Cat. No. RGAM001), and the TGF-β1 enzyme-linked immunosorbent assay (ELISA) kit (Cat. No. KE00002) were purchased from Proteintech (Wuhan, China). Primary antibodies against p-TGFβR I (Cat. No. ab112095) were purchased from Abcam (Cambridge, UK). Primary antibodies against p-TGFβR II (Cat. No. bs-18067R) was purchased from Bioss (Beijing, China). The 0.2 µm polyvinylidene difluoride (PVDF) membranes (Cat. No. ISEQ00010) was purchased from Merck Millipore (Billerica, MA, USA). The ultra-sensitive enhanced chemiluminescence kit (Cat. No. ECL-0100) was purchased from SmartBuffers (Uppsala, Sweden). The sources of additional materials were indicated in the text accordingly.

CCK-8 assays

CCK-8 were performed to analyze the effect of metformin (0, 5, 10, 20, 40, 80 and 160 mM) or cDDP (0, 3, 6, 12, 24, 48, 96 and 192 µM) on cytotoxicity in SKOV3 and SKOV3/cDDP cells, as indicated. When TGF-β1 (10 ng/mL) was used in the experiment, cells needed to be pretreated with TGF-β1 for 48 h. Approximately, 7.5×10³ well cells were inoculated into the 96-well plate. Metformin or cDDP plus metformin (20mM) was given the next day. Then cells were cultured for 48 h at 37 ℃. Finally, after 1 h incubation with CCK-8 at 37 ℃, optical density (OD) value at 450 nm was detected for calculating cell viability. The half-maximal inhibitory concentration (IC₅₀) of cDDP was determined from dose-response curves fitted using a sigmoidal model in GraphPad Prism 8.0.2, applying the four-parameter logistic (4PL) model for calculation.

Colony formation

A total of 1×10³ SKOV3 and SKOV3/cDDP cells were seeded into six-well plates and treated with metformin (0, 10, 20 mM) for 7 days. The cells were then fixed with 4% paraformaldehyde for 15 min at room temperature, stained with 1% crystal violet for 10 min at room temperature, and washed three times with reverse osmosis water. Finally, colonies were counted.

Wound healing

SKOV3 and SKOV3/cDDP cells were inoculated in a 6-well plate and incubated for 24 h. When the cells formed a single layer, a straight scratch was made across the cell layer using a sterile 10 µL pipette tip. The cell debris was washed off with serum-free medium, and then the cells were maintained in serum-free medium containing metformin (0, 5, 10, 20, 40 mM) for the duration of the experiment. The wounds were imaged under a microscope at 0, 24, and 48 h. The cell wound area was calculated using ImageJ.

Transwell assay

Cell migration and invasion capacities were evaluated using transwell assay. For invasion assays, the upper chamber was coated with Matrigel for at least 4 h before seeding cells, while migration assays were performed without Matrigel. SKOV3 and SKOV3/cDDP cells were separately resuspended in 200 µL of serum-free medium containing metformin (0, 10, 20 mM) and added to the upper chamber, with 500 µL of complete medium containing 10% fetal bovine serum placed in the lower chamber. Cells were incubated at 37 ℃ in a 5% CO₂ incubator for 48 h. After washing with phosphate buffered saline (PBS), cells were fixed with 4% paraformaldehyde and stained with crystal violet. An upright microscope was used to take pictures and count the number of cells.

Western blot analysis

Cell lysates were prepared from SKOV3 and SKOV3/cDDP cells using RIPA strong lysate. Protein concentrations were quantified with a BCA protein assay kit. Then, the protein samples (60 µg/lane) were separated using 10% Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to 0.2 µm PVDF membranes. Following this, the membranes were blocked with 5% nonfat milk, incubated with primary antibodies overnight at 4 ℃, and washed three times with Tris buffered saline with Tween 20 (TBST). Subsequently, HRP-conjugated anti-rabbit or anti-mouse IgG secondary antibody was incubated with the membranes for 1 h at room temperature, and then the membranes washed by TBST three times. Protein signals were detected using an ultra-sensitive enhanced chemiluminescence kit (SmartBuffers, Uppsala, Sweden) and Bio-Rad Molecular Imager (Bio-Rad, California, USA). ImageJ software was used for relative expression analysis.

Immunofluorescence staining

To investigate cytoskeletal organization and Smad localization, SKOV3 and SKOV3/cDDP cells were plated on coverslips in 24-well plate, and treated with 20 mM metformin or vehicle control for 48 h. Cells were subsequently fixed with 4% paraformaldehyde and permeabilized. For F-actin visualization, cells were stained with Actin-Tracker Green-488 phalloidin (Beyotime, Shanghai, China) for 15 min. For immunofluorescence detection of Smad2, Smad3 and Smad4, the fixed cells were blocked with 2% bovine serum albumin (BSA) and incubated with primary antibodies at 4 ℃ overnight, followed by incubation with a Cy3-conjugated secondary antibody for 2 h at room temperature. Nuclei were counterstained with DAPI prior to imaging. Confocal microscopes were performed to capture the images.

ELISA

The secretion of TGF-β1 was quantified in cell culture supernatants using a commercial human TGF-β1 ELISA kit. The supernatants were collected from SKOV3 and SKOV3/cDDP cells treated with the indicated concentrations (0, 10, 20 mM) of metformin for 48 h. According to the manufacturer’s protocol, latent TGF-β1 was activated by acidification and neutralization. Activated samples and serially diluted standards were incubated in antibody-precoated plate for 2 h at 37 ℃. After washing, a biotin-conjugated detection antibody was added, followed by incubation with streptavidin-HRP. Colorimetric reaction was developed using tetramethylbenzidine (TMB) substrate and stopped with sulfuric acid. Absorbance was measured at 450 nm using a microplate reader. TGF-β1 concentrations were calculated based on a recombinant protein standard curve.

Statistical analysis

All experimental data were repeated three times, averaged and expressed as mean ± standard deviation (SD). GraphPad Prism 8.0.2 software (La Jolla, CA, USA) was used for statistical analysis. T-test was used to compare the means of two samples and one-way analysis of variance (ANOVA) was used to compare the means of multiple groups. P<0.05 was considered as the difference was statistically significant (*P<0.05, **P<0.01, ***P<0.001).

Results

Metformin suppressed cDDP chemoresistance and metastatic potential in OC cells

To investigate the effect of metformin on drug resistance of OC cells, we established cDDP-resistant SKOV3/cDDP cells from parental SKOV3 cells via concentration gradient induction (Figure 1A,1B). Subsequently, gradient concentrations of metformin were applied to SKOV3 and SKOV3/cDDP cells, which revealed metformin suppressed cell viability and clonogenicity in a dose-dependent manner (Figure 1C-1E). Based on cell survival and colony formation, 20 mM metformin was selected as the optimal concentration for subsequent in vitro experiments. Further treatment with combinations of cDDP and metformin demonstrated that metformin enhanced the inhibitory effect of cDDP in both cell lines, leading to a higher inhibition rate and a significant reduction in the IC₅₀ of cDDP (SKOV3/cDDP: 13.71±2.25 vs. 25.73±1.55; SKOV3: 5.13±0.52 vs. 11.70±0.61) (Figure 1F-1I). Additionally, we assessed metformin’s impact on cell metastatic properties. Wound healing assays showed concentration-dependent impairment of wound closure (Figure 1J-1M), while transwell assays revealed the reduction of migratory and invasive potentials (Figure 1N-1Q). These data confirmed that metformin not only reduced cDDP resistance in OC but also effectively inhibited its metastatic potential.

Figure 1 Metformin promoted cisplatin chemosensitivity and restrained metastasis in OC cells. (A,B) CCK-8 for cell viability of SKOV3 and SKOV3/cDDP treated with cDDP for 48 h, and the IC₅₀ of cDDP. (C) CCK-8 assay for cell viability of SKOV3 and SKOV3/cDDP cells treated with metformin for 48 h. (D,E) Colony formation assay was used to analyze the number of colonies in SKOV3 and SKOV3/cDDP cells treated with metformin for 10 days (crystal violet staining). (F-I) CCK-8 for cell viability of SKOV3 and SKOV3/cDDP treated with 20 mM metformin and cDDP for 48 h, and the IC₅₀ of cDDP. (J-M) Scratch wound assay for the effect of metformin on wound healing ability in SKOV3 and SKOV3/cDDP cells (magnification, ×100). (N,O) Transwell assay for the effect of metformin on the migratory ability of OC cells (crystal violet staining; magnification, ×100), and (P,Q) the invasive ability. All experiments were repeated three times independently. Data are presented as mean ± SD. P<0.05 was considered statistically significant: *, P<0.05; **, P<0.01; ***, P<0.001. CCK-8, cell counting kit-8; cDDP, cisplatin; IC₅₀, half-maximal inhibitory concentration; OC, ovarian cancer; SD, standard deviation.

Metformin impaired EMT in OC cells

To further explore how metformin inhibited OC chemoresistance and metastatic potential, we evaluated its effect on EMT. Acquired data showed that metformin dose-dependently increased the expression of epithelial marker E-cadherin, while decreased the expression of mesenchymal marker N-cadherin (Figure 2A-2D). Additionally, metformin inhibited the expression of key EMT transcription factors, including Snail, Slug and Zeb-1 (Figure 2E-2H). Furthermore, immunofluorescence showed that metformin treatment altered cell morphology to a more oval or polygonal appearance, while disrupted mesenchymal-like stress fiber architecture and promoted cortical actin localization, indicative of a shift toward an epithelial phenotype (Figure 2I,2J). These results indicated that metformin suppressed EMT in OC cells.

Figure 2 Metformin inhibited EMT of OC cells. (A-D) The expressions of E-cadherin and N-cadherin in SKOV3 and SKOV3/cDDP cells treated with metformin for 48 h were detected by western blot analysis. (E-H) The expressions of Snail, Slug and Zeb-1 in SKOV3 and SKOV3/cDDP cells treated with metformin for 48 h were examined by western blot analysis. The relative protein levels were determined by ImageJ software. β-tubulin was used as an internal reference. (I,J) Immunofluorescence images of SKOV3 and SKOV3/cDDP cells treated with or without 20 mM metformin for 48 h (magnification, ×100). F-actin cytoskeleton was visualized by phalloidin staining (green), and nuclei were counterstained with DAPI (blue). All experiments were repeated three times independently. Data are presented as mean ± SD. P<0.05 was considered statistically significant: *, P<0.05; **, P<0.01; ***, P<0.001. cDDP, cisplatin; EMT, epithelial-mesenchymal transition; OC, ovarian cancer; SD, standard deviation.

Metformin exerted inhibitory effect on TGF‑β1/Smads signaling

We next assessed the effect of metformin on TGF-β1/Smads signaling. ELISA assay showed that metformin treatment reduced TGF-β1 secretion in supernatants of SKOV3 and SKOV3/cDDP cells (Figure 3A,3B). At TGF-β receptor level, metformin downregulated both the expression and phosphorylation of TGFβR I and TGFβR II (Figure 3C-3F). Moreover, immunofluorescence staining showed that metformin attenuated the cytoplasmic and nuclear localizations of Smad2, Smad3 and Smad4 (Figure 3G,3H). Furthermore, metformin also decreased the protein and phosphorylation levels of Smad2, Smad3 and Smad4 (Figure 3I-3L). In rescue experiments, exogenous TGF-β1 restored metformin‑suppressed expression of total and phosphorylated Smad proteins (Figure 3M-3P). These results suggested that metformin inhibited TGF-β1/Smads pathway at multiple level.

Figure 3 Metformin inhibited TGF-β1/Smads pathway in OC cells. (A,B) TGF-β1 secretion in the supernatants of SKOV3 and SKOV3/cDDP cells treated with metformin for 48 h was measured by ELISA. (C-F) The expression and phosphorylation of TGFβR I/II in metformin-treated OC cells were analyzed by western blot. (G,H) Immunofluorescence showing the subcellular localization of Smad2/3/4 (red) upon metformin treatment. Nuclei were counterstained with DAPI (blue) (magnification, ×100). (I-L) The expression and phosphorylation of Smad2/3/4 in metformin-treated OC cells were analyzed by western blot. (M-P) Smad2/3/4 protein level in OC cells treated with TGF-β1 (10 ng/mL) combined with metformin (20 mM) for 48 h were detected by western blot. The relative protein levels were determined by ImageJ software. GAPDH was used as an internal reference. All experiments were repeated three times independently. Data are presented as mean ± SD. P<0.05 was considered statistically significant: *, P<0.05; **, P<0.01; ***, P<0.001. cDDP, cisplatin; ELISA, enzyme-linked immunosorbent assay; OC, ovarian cancer; SD, standard deviation.

TGF-β/Smads was critical for metformin-regulated EMT

To further investigate underlying mechanism by which metformin inhibited EMT in OC cells, we assessed the influence of TGF-β1 on the expression of EMT markers controlled by metformin. In SKOV3 and SKOV3/cDDP cells, although metformin increased epithelial marker E-cadherin and downregulated mesenchymal marker N-cadherin, TGF-β1 significantly reversed these changes (Figure 4A-4D). Similarly, TGF-β1 restored metformin-induced downregulation of EMT transcription factors including Snail and Slug (Figure 4E-4H). These data suggested that metformin restrained EMT progression of OC cells via suppressing TGF-β/Smad signaling.

Figure 4 The role TGF-β/Smads in metformin-mediated EMT. (A-D) The protein levels of E-cadherin and N-cadherin, (E-H) as well as Snail and Slug, in SKOV3 and SKOV3/cDDP cells treated with TGF-β1 (10 ng/mL) combined with metformin (20 mM) for 48 h were detected by western blot analysis. GAPDH was used as an internal reference. The relative protein expressions were determined by ImageJ software. All experiments were repeated three times independently. Data are presented as mean ± SD. P<0.05 was considered statistically significant: *, P<0.05; **, P<0.01. cDDP, cisplatin; EMT, epithelial-mesenchymal transition; SD, standard deviation.

Metformin inhibited cDDP resistance and metastatic potential via TGF-β/Smads

We further elevated the role of TGF-β/Smads in metformin-regulated chemoresistance and metastatic potential in OC cells. The result showed that cDDP chemosensitivities were decreased in SKOV3 (IC₅₀: 7.30±0.36 vs. 5.13±0.51) and SKOV3/cDDP (IC₅₀: 18.69±0.63 vs. 10.73±0.51) cells cotreated with TGF-β1 and metformin, compared with the metformin alone (Figure 5A-5D). These results suggested that TGF-β/Smads activation weaken metformin-enhanced cDDP chemosensitivity in OC cells. As expected, transwell assays demonstrated that the migratory and invasive potentials were significantly enhanced in SKOV3 and SKOV3/cDDP cells with cotreatment with TGF-β1 and metformin, compared with the metformin alone (Figure 5E-5H). Above data indicated that metformin inhibited TGF-β1/Smads signaling to restrain cDDP chemoresistance and metastatic potential of OC.

Figure 5 TGF-β/Smads was required for metformin-inhibited cisplatin resistance and metastatic potential. (A-D) SKOV3 and SKOV3/cDDP cells were pretreated with TGF-β1 for 48 h, then incubated with 20 mM metformin and varying concentrations of cisplatin for an additional 48 h. Cell viability was assessed using CCK-8 assay. The IC₅₀ of cisplatin was calculated from cell inhibition curve using GraphPad Prism. (E-H) SKOV3 and SKOV3/cDDP cells were pretreated with TGF-β1 for 48 h, then treated with 20 mM metformin for an additional 48 h. Cell migratory and invasive potentials were analyzed by transwell assay (crystal violet staining; magnification, ×100). All experiments were repeated three times independently. Data are presented as mean ± SD. P<0.05 was considered statistically significant: **, P<0.01; ***, P<0.001. CCK-8, cell counting kit-8; cDDP, cisplatin; SD, standard deviation.

Discussion

Currently, OC has become a significant deadly threat, ranking third in incidence and second in mortality among gynecologic malignancies in Chinese women (17). Due to the absence of specific early clinical symptoms and diverse molecular mechanisms involved, more than 70% of patients are diagnosed at an advanced stage (18). Despite substantial advances in treatment techniques for OC, the 5-year survival rate of patients remains low, with persistent challenges including recurrence, metastasis and drug resistance (11,19). Therefore, addressing the challenges of drug resistance and metastasis were crucial for improving treatment strategies and prognosis of OC patients.

For decades, metformin has been globally recognized for its efficacy and safety in the clinical treatment of type 2 diabetes. Recent studies have found that beyond its role in treating diabetes, metformin also exhibits anticancer properties (20). Accumulating data have revealed that metformin suppresses metastatic activity in hepatocellular carcinoma cells by disrupting mitochondrial oxidative phosphorylation and adenosine triphosphate (ATP) production (21). In gastric cancer, it has also been found that metformin inhibits proliferation and metastasis of tumor cells by activating adenosine monophosphate (AMP)-activated protein kinase and regulating expression of cell cycle-related proteins and microRNAs (22). However, little research is conducted on the role and mechanism of metformin simultaneously inhibiting drug resistance and metastasis in OC cells. This study demonstrated that metformin not only reduced cell viability, migratory and invasive capacity but also enhanced chemosensitivity of cDDP-resistant OC cells.

It is well-known that EMT refers to the transformation of quiescent epithelial cells into motile mesenchymal cells, which plays a crucial role in tumor therapy resistance and metastasis (23). It has been found that chemoresistance and metastatic potential were synchronously promoted in gastric cancer cells undergoing EMT (24). Repressing EMT progression can promote oxaliplatin sensitivity and inhibit distant organ metastasis in colorectal cancer and prostate cancer cells (25,26). Therefore, targeting tumor EMT may provide a new insight into cancer therapy. EMT progression is regulated by a series of transcription factors including Snail, Slug and Zeb1 (27). Snail, a pivotal EMT inducer, is aberrantly overexpressed in lung metastatic tissues of colorectal cancer (28). This ectopic expression is significantly involved in EMT-mediated tumor invasiveness and metastatic potential (29). Moreover, the inhibition of snail-induced EMT has been also shown to reverse cDDP resistance (30). Additionally, it has been reported that downregulation of Slug expression can abrogate EMT progression, thereby suppressing malignant phenotype of OC cells (31). Here, we assessed the impact of metformin on expression of EMT surface markers (E-cadherin and N-cadherin) and transcription factors (Snail, Slug and Zeb-1). The present study found that metformin inhibited EMT-like molecular changes confirmed by upregulation of E-cadherin, as well as downregulations of N-cadherin, Snail, Slug and Zeb-1. These results further indicated that metformin inhibited EMT progression in OC, highlighting its potential as a promising candidate agent for improving OC therapy.

To elucidate the potential mechanism by which metformin inhibited EMT in OC, we investigated the effect of metformin on TGF-β/Smads signaling, which is critical for EMT during development and wound healing, and in disease conditions including fibrosis and cancer (32). Within TGF-β/Smads signaling, TGF-β1 regulates gene expression primarily through Smad transcription factors (33). Upon activation by TGF-β receptor I/II complex, Smad2 and Smad3 are phosphorylated. The activated Smad2/3 then forms complexes with Smad4, and translocate into the nucleus, where it modulates the expression of target genes, including those involved in EMT (34). Studies have demonstrated that silencing TGF-β/Smads signaling can suppress the expression of EMT transcription factors including Snail and Slug, which downregulate epithelial markers and upregulate mesenchymal markers (35,36). Inhibition of TGF-β/Smads powerfully hinders cell proliferation, EMT and metastasis in colorectal cancer (37). In cervical cancer, attenuated TGF-β/Smads activity enhances cDDP chemosensitivity (38). In the present study, we found that metformin inhibited the TGF-β1 ligand production, expression and phosphorylation of TGFβR I/II and Smads, as well as reduced the nuclear translocation of Smads. These results suggested that metformin inhibited activity of TGF-β/Smads signaling. Critically, TGF-β1 reversed metformin-mediated inhibition of EMT, cDDP resistance and metastatic potential in cDDP-resistant and its parent OC cells. The above results indicated that metformin suppressed TGF-β1/Smads to decrease EMT and metastatic potential, and enhance chemosensitivity in OC, supporting its potential as a novel therapeutic agent for improving treatment outcomes.

It should be noted that although the metformin concentrations (5–40 mM) in this study exceeds typical clinical plasma levels, this choice is based on the distinctive metabolic features of ovarian cancer and is consistent with prior in vitro mechanistic investigations in this disease context (39-43). Clinically relevant plasma concentrations are often insufficient to induce anticancer effects in conventional two-dimensional cell cultures, as these systems lack critical physiological components of tumor microenvironment and differ from in vivo tumors in terms of drug uptake and metabolic activity (44-46). Accordingly, the present dosing strategy was designed not to replicate therapeutic plasma levels, but to enable mechanistic exploration. Supporting this approach, earlier studies have demonstrated that OC cells require high-dose metformin (10 mM) under glucose-limited conditions to trigger metabolic stress and growth inhibition, suggesting that high-dose metformin represents a rational in vitro strategy to uncover mechanistic insights in OC (39). In line with this rationale, our experiments showed that metformin treatment significantly suppressed malignant progression of OC cells via TGF-β1/Smads pathway. The value of this finding lies in providing an important theoretical basis for subsequent research that may aim to achieve similar effects at lower, clinically achievable doses.

Taken together, this study focused on the therapeutic potential of metformin in OC, with particular emphasis on its inhibitory effect on EMT. Mechanistically, we demonstrated that metformin acted as an inhibitor of the TGF-β1/Smads to reduce EMT, and exerted its dual effects in inhibiting drug resistance and metastatic potential of OC. Therefore, metformin holds promise as a novel anticancer agent for the treatment of OC in the future. Although our study revealed that metformin exerted anticancer activity in OC via TGF-β1/Smads, its specific target remains to be further identified. Moreover, in addition to TGF-β1/Smads, other signaling pathways are involved in regulating EMT progression in cancers, such as Wnt, MAPK and NF-κB (47). Thus, in future work, it is necessary to further explore whether other signaling pathways affect metformin-mediated inhibition of chemoresistance and metastasis traits in OC. Furthermore, previous clinical studies reveal that factors including aging, higher tumor grade and TNM stage, along with the presence of selected endocrine disorders and metabolic abnormalities, may modify tumor microenvironment, thereby influencing cancer treatment outcomes (48). Therefore, further research is required to clarify the specific clinical or pathological conditions under which metformin enhances cDDP chemosensitivity and reduces metastatic potential in ovarian cancer.

Conclusions

In summary, our findings demonstrated that metformin suppressed EMT, reduced cDDP resistance, and inhibited metastatic potential in ovarian cancer cells. Mechanistically, these beneficial effects were mediated through inhibition of TGF-β1/Smads signaling. The present study highlighted metformin’s role as a novel inhibitor of TGF-β1/Smads signaling in ovarian cancer, providing a rationale for its potential repurposing as an adjunctive therapeutic agent against chemoresistance and metastasis.

Acknowledgments

We would like to thank members of our research group for the helpful discussions. We would also like to thank the staff of the Biomedicine Laboratory of Chengdu Medical College, Sichuan Higher Education Institute Key Laboratory of Major Disease Target Discovery and Protein Drug Development and Irradiation Preservation and Effect Key Laboratory of Sichuan Province for their contributions to this study.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2599/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2599/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2599/prf

Funding: This study was supported by National Natural Science Foundation of China (Nos. 82272658 and 81872451), Sichuan Science and Technology Program (Nos. 2022JDRC0042 and 2022NSFSC0777), Chengdu Medical College (CMC) Excellent-talent Program (No. 2024kjTzn03), Organized Research Projects of Chengdu Medical College (No. CYYZZ24-01), Clinical Science Research Foundations of Collaborative Innovation Center of Sichuan for Elderly Care and Health (Nos. 2022LHTD-02 and 2020LHJYPJ-02), Sichuan Higher Education Institute Key Laboratory of Major Disease Target Discovery and Protein Drug Development (Nos. 23LHNBZZD07, 24LHBBYY1-08, and 24LHBBYY1-09), and Development and Regeneration Key Lab of Sichuan Province (No. 24LHFYSZ1-27).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2599/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024;74:229-63. [Crossref] [PubMed]
2. Mauro LJ, Spartz A, Austin JR, et al. Reevaluating the Role of Progesterone in Ovarian Cancer: Is Progesterone Always Protective? Endocr Rev 2023;44:1029-46. [Crossref] [PubMed]
3. Solidoro R, Centonze A, Miciaccia M, et al. Fluorescent imaging probes for in vivo ovarian cancer targeted detection and surgery. Med Res Rev 2024;44:1800-66. [Crossref] [PubMed]
4. Caruso G, Weroha SJ, Cliby W. Ovarian Cancer: A Review. JAMA 2025;334:1278-91. [Crossref] [PubMed]
5. Huang Y, Hong W, Wei X. The molecular mechanisms and therapeutic strategies of EMT in tumor progression and metastasis. J Hematol Oncol 2022;15:129. [Crossref] [PubMed]
6. Farahzadi R, Valipour B, Fathi E, et al. Oxidative stress regulation and related metabolic pathways in epithelial-mesenchymal transition of breast cancer stem cells. Stem Cell Res Ther 2023;14:342. [Crossref] [PubMed]
7. Zhong G, Zhao Q, Chen Z, et al. TGF-β signaling promotes cervical cancer metastasis via CDR1as. Mol Cancer 2023;22:66. [Crossref] [PubMed]
8. Shi Q, Huang F, Wang Y, et al. HER2 phosphorylation induced by TGF-β promotes mammary morphogenesis and breast cancer progression. J Cell Biol 2024;223:e202307138. [Crossref] [PubMed]
9. Zheng M, Niu Y, Bu J, et al. ESRP1 regulates alternative splicing of CARM1 to sensitize small cell lung cancer cells to chemotherapy by inhibiting TGF-β/Smad signaling. Aging (Albany NY) 2021;13:3554-72. [Crossref] [PubMed]
10. Xu D, Wang Y, Wu J, et al. Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma. Cancer Cell Int 2021;21:621. [Crossref] [PubMed]
11. Yang L, Xie HJ, Li YY, et al. Molecular mechanisms of platinum-based chemotherapy resistance in ovarian cancer Oncol Rep 2022;47:82. (Review). [Crossref] [PubMed]
12. Arioka M, Miura K, Han R, et al. Mammalian target of differentiation-inducing factor-1 is mitochondrial malate dehydrogenase for activation of AMP-activated protein kinase and induction of mitochondrial fission. Life Sci 2024;351:122807. [Crossref] [PubMed]
13. Deng C, Xiong L, Chen Y, et al. Metformin induces ferroptosis through the Nrf2/HO-1 signaling in lung cancer. BMC Pulm Med 2023;23:360. [Crossref] [PubMed]
14. Barczyński B, Frąszczak K, Kotarski J. Perspectives of metformin use in endometrial cancer and other gynaecological malignancies. J Drug Target 2022;30:359-67. [Crossref] [PubMed]
15. Yang J, Zhou Y, Xie S, et al. Metformin induces Ferroptosis by inhibiting UFMylation of SLC7A11 in breast cancer. J Exp Clin Cancer Res 2021;40:206. [Crossref] [PubMed]
16. Huang X, Sun T, Wang J, et al. Metformin Reprograms Tryptophan Metabolism to Stimulate CD8+ T-cell Function in Colorectal Cancer. Cancer Res 2023;83:2358-71. [Crossref] [PubMed]
17. Han B, Zheng R, Zeng H, et al. Cancer incidence and mortality in China, 2022. J Natl Cancer Cent 2024;4:47-53. [Crossref] [PubMed]
18. Raspaglio G, Buttarelli M, Cappoli N, et al. Exploring the Control of PARP1 Levels in High-Grade Serous Ovarian Cancer. Cancers (Basel) 2023;15:2361. [Crossref] [PubMed]
19. Song M, Cui M, Liu K. Therapeutic strategies to overcome cisplatin resistance in ovarian cancer. Eur J Med Chem 2022;232:114205. [Crossref] [PubMed]
20. Yu OHY, Suissa S. Metformin and Cancer: Solutions to a Real-World Evidence Failure. Diabetes Care 2023;46:904-12. [Crossref] [PubMed]
21. Jin P, Jiang J, Zhou L, et al. Disrupting metformin adaptation of liver cancer cells by targeting the TOMM34/ATP5B axis. EMBO Mol Med 2022;14:e16082. [Crossref] [PubMed]
22. Lan WH, Lin TY, Yeh JA, et al. Mechanism Underlying Metformin Action and Its Potential to Reduce Gastric Cancer Risk. Int J Mol Sci 2022;23:14163. [Crossref] [PubMed]
23. Sadrkhanloo M, Entezari M, Orouei S, et al. STAT3-EMT axis in tumors: Modulation of cancer metastasis, stemness and therapy response. Pharmacol Res 2022;182:106311. [Crossref] [PubMed]
24. Chen K, Xu J, Tong YL, et al. Rab31 promotes metastasis and cisplatin resistance in stomach adenocarcinoma through Twist1-mediated EMT. Cell Death Dis 2023;14:115. [Crossref] [PubMed]
25. Liu W, Tang J, Gao W, et al. PPP2R1B abolishes colorectal cancer liver metastasis and sensitizes Oxaliplatin by inhibiting MAPK/ERK signaling pathway. Cancer Cell Int 2024;24:90. [Crossref] [PubMed]
26. Xuan Z, Chen C, Sun H, et al. NDR1/FBXO11 promotes phosphorylation-mediated ubiquitination of β-catenin to suppress metastasis in prostate cancer. Int J Biol Sci 2024;20:4957-77. [Crossref] [PubMed]
27. Wang R, Xu H, Hu C, et al. HOPX regulates the invasion and migration abilities of hepatocellular carcinoma by targeting SNAIL. Sci Rep 2025;15:29739. [Crossref] [PubMed]
28. Bao Z, Zeng W, Zhang D, et al. SNAIL Induces EMT and Lung Metastasis of Tumours Secreting CXCL2 to Promote the Invasion of M2-Type Immunosuppressed Macrophages in Colorectal Cancer. Int J Biol Sci 2022;18:2867-81. [Crossref] [PubMed]
29. Poyil PK, Siraj AK, Padmaja D, et al. Overexpression of the pro-protein convertase furin predicts prognosis and promotes papillary thyroid carcinoma progression and metastasis through RAF/MEK signaling. Mol Oncol 2023;17:1324-42. [Crossref] [PubMed]
30. Cheng HY, Hsieh CH, Lin PH, et al. Snail-regulated exosomal microRNA-21 suppresses NLRP3 inflammasome activity to enhance cisplatin resistance. J Immunother Cancer 2022;10:e004832. [Crossref] [PubMed]
31. Cutano V, Ferreira Mendes JM, Escudeiro-Lopes S, et al. LACTB exerts tumor suppressor properties in epithelial ovarian cancer through regulation of Slug. Life Sci Alliance 2023;6:e202201510. [Crossref] [PubMed]
32. Xin X, Cheng X, Zeng F, et al. The Role of TGF-β/SMAD Signaling in Hepatocellular Carcinoma: from Mechanism to Therapy and Prognosis. Int J Biol Sci 2024;20:1436-51. [Crossref] [PubMed]
33. Fu H, Itoh Y, Sawaguchi T, et al. Identification of a Distal Enhancer That Regulates TGF-β-Induced SNAI1 Expression. Cancer Sci 2025;116:2137-49. [Crossref] [PubMed]
34. Wang S, Xu D, Xiao L, et al. Radiation-induced lung injury: from mechanism to prognosis and drug therapy. Radiat Oncol 2025;20:39. [Crossref] [PubMed]
35. Chen J, Song T, Yang S, et al. Snail mediates GDF-8-stimulated human extravillous trophoblast cell invasion by upregulating MMP2 expression. Cell Commun Signal 2023;21:93. [Crossref] [PubMed]
36. Caruso JA, Chen-Tanyolac C, Tlsty TD. A hybrid epithelial-mesenchymal transition program enables basal epithelial cells to bypass stress-induced stasis and contributes to a metaplastic breast cancer progenitor state. Breast Cancer Res 2024;26:184. [Crossref] [PubMed]
37. Liu A, Yu C, Qiu C, et al. PRMT5 methylating SMAD4 activates TGF-β signaling and promotes colorectal cancer metastasis. Oncogene 2023;42:1572-84. [Crossref] [PubMed]
38. Zheng H, Liu M, Shi S, et al. MAP4K4 and WT1 mediate SOX6-induced cellular senescence by synergistically activating the ATF2-TGFβ2-Smad2/3 signaling pathway in cervical cancer. Mol Oncol 2024;18:1327-46. [Crossref] [PubMed]
39. Šimčíková D, Gardáš D, Hložková K, et al. Loss of hexokinase 1 sensitizes ovarian cancer to high-dose metformin. Cancer Metab 2021;9:41. [Crossref] [PubMed]
40. Abbasi R, Nejati V, Rezaie J. Exosomes biogenesis was increased in metformin-treated human ovary cancer cells; possibly to mediate resistance. Cancer Cell Int 2024;24:137. [Crossref] [PubMed]
41. Fan Y, Cheng H, Liu Y, et al. Metformin anticancer: Reverses tumor hypoxia induced by bevacizumab and reduces the expression of cancer stem cell markers CD44/CD117 in human ovarian cancer SKOV3 cells. Front Pharmacol 2022;13:955984. [Crossref] [PubMed]
42. Gralewska P, Gajek A, Marczak A, et al. Metformin Affects Olaparib Sensitivity through Induction of Apoptosis in Epithelial Ovarian Cancer Cell Lines. Int J Mol Sci 2021;22:10557. [Crossref] [PubMed]
43. Zhou W, Ma X, Xiao J, et al. Exploiting the Warburg Effect: Co-Delivery of Metformin and FOXK2 siRNA for Ovarian Cancer Therapy. Small Sci 2024;4:2300192. [Crossref] [PubMed]
44. Flickinger KM, Wilson KM, Rossiter NJ, et al. Conditional lethality profiling reveals anticancer mechanisms of action and drug-nutrient interactions. Sci Adv 2024;10:eadq3591. [Crossref] [PubMed]
45. Abbott KL, Ali A, Casalena D, et al. Screening in serum-derived medium reveals differential response to compounds targeting metabolism. Cell Chem Biol 2023;30:1156-1168.e7. [Crossref] [PubMed]
46. Wang J, Xu W, Qian J, et al. Photo-crosslinked hyaluronic acid hydrogel as a biomimic extracellular matrix to recapitulate in vivo features of breast cancer cells. Colloids Surf B Biointerfaces 2022;209:112159. [Crossref] [PubMed]
47. Lin ZY, Yun QZ, Wu L, et al. Pharmacological basis and new insights of deguelin concerning its anticancer effects. Pharmacol Res 2021;174:105935. [Crossref] [PubMed]
48. Powell MK, Cempirkova D, Dundr P, et al. Metformin Treatment for Diabetes Mellitus Correlates with Progression and Survival in Colorectal Carcinoma. Transl Oncol 2020;13:383-92. [Crossref] [PubMed]