NCOA4-driven ferritinophagy and GSH reprogramming underlie maslinic acid-induced ferroptosis and autophagy in breast cancer

Introduction

Breast cancer has become the most commonly diagnosed cancer worldwide (1), poseing a serious threat to women’s lives and health. Traditional chemotherapy and targeted therapy have limited efficacy and are prone to drug resistance; thus, identifying safe and effective therapeutic drugs remains an urgent clinical issue.

Maslinic acid (MA), a pentacyclic triterpenoid acid, exhibits a wide array of biological activities, such as hypoglycemic, anti-inflammatory, and anti-parasitic effects (2). In recent years, its role in anti-tumor treatment has also attracted extensive attention. Studies have demonstrated that MA exerts anti-cancer effects against malignant tumors like colon cancer (3), prostate cancer (4), and pancreatic cancer (5). A comprehensive analysis revealed that the anti-cancer mechanism of MA mainly encompasses inhibiting cell proliferation (6), arresting the cell cycle (7), inducing cell apoptosis (5), autophagy and ferroptosis (4).

Ferroptosis, a programmed cell-death modality characterized by iron-dependence, is primarily triggered by excessive iron-dependent lipid peroxidation (8). This process results in iron-mediated oxidative damage to the cell membrane and elevated intracellular reactive oxygen species (ROS) levels (9,10). Research has demonstrated that ferroptosis plays a pivotal role in determining the fate of cancer cells and their responsiveness to various cancer treatments, including chemotherapy, radiation therapy, and immunotherapy (11). Tumor cells with drug-resistance and high metastatic potential display heightened sensitivity to ferroptosis (12). Additionally, studies have reported that some natural compounds inhibit the proliferation of triple-negative breast cancer (TNBC) cells through inducing ferroptosis (4,13,14). For example, ursolic acid inhibits the proliferation of TNBC stem like cells through nuclear factor erythroid 2-related factor 2 (NRF2) mediated ferroptosis (14), while rosmarinic acid promotes mitochondrial fission and induces ferroptosis in TNBC cells (13). Hu et al. discovered that MA induces autophagy and ferroptosis through transcriptomic and metabolomic reprogramming, thus inhibiting the growth of prostate cancer cells both in vitro and in vivo (4). Currently, limited research exists on the mechanism by which MA induces autophagy and ferroptosis in breast cancer. Therefore, this study investigated the roles of autophagy and ferroptosis in mediating the anti-tumor effects of MA on breast cancer cells, aiming to provide a foundation for the application of MA in breast cancer treatment. We present this article in accordance with the MDAR reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0145/rc).

Methods

Cell culture and treatment

MCF-7 (luminal A-type breast cancer cells), T47D (luminal B-type breast cancer cells), and MDA-MB-231 (a TNBC cell line) were purchased from the American Type Culture Collection (Manassas, VA, USA). Cell culture conditions and the preparation of the MA (Sigma-Aldrich, China; M6699) solution were carried out as previously described (4). Chloroquine (CQ) (BA1002, APExBIO) was used as an autophagy inhibitor. MCF-7, T47D, and MDA-MB-231 cells were separately inoculated into 96-well plates (5×10³ cells per well) and cultured under standard conditions until reaching 70% confluence. Subsequently, the cells were treated with different concentrations of MA alone or in combination with CQ for 24 h, while an equivalent volume of DMSO was added to the control group. Cell proliferation was evaluated using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay.

Cell transfection

The sequence for the si-NCOA4 was 5′-GACCUUAUUUAUCAGCUUATT-3′. The sequence for the si-RNA negative control was 5′-UUCUCCGAACGUGUCACGUTT-3′. Transfection was performed using Lipofectamine 2000 (Invitrogen, Thermo Fisher Scientific, Inc., Waltham, MA, USA) according to the manufacturer’s instructions.

MTT assay

Cells were treated with MA alone or in combination with CQ for 24 h. Cell morphology was observed and photographed using a light microscope (Olympus IX73, Tokyo, Japan), MTT assay procedures and the half-maximal inhibitory concentration (IC₅₀) calculation were performed according to previously reported methods (15).

5-ethynyl-2’-deoxyuridine (EdU) assay

After treatment with MA, cells were subjected to an EdU cell proliferation assay using the EdU Apollo 488 kit (Guangzhou RiboBio Co., Ltd., Guangzhou, China). Cell proliferation was visualized using fluorescence imaging with an Olympus IX73 inverted fluorescence microscope, and quantified according to the manufacturer’s protocols.

Autophagy flux analysis

MCF-7, T47D, and MDA-MB-231cells were inoculated into 96-well plates and cultured until the cell density reached 80–90%. The mRFP-GFP-LC3 plasmid (Changsha Youbao, Changsha, China) was transfected into the cells according to the instructions for Lipofectamine 2000. After 6 h of transfection, the cells were treated with different concentrations of MA. Following 24 h of MA treatment, autophagy flux was analyzed using an Olympus IX73 fluorescence inverted microscope. The fluorescence was detected using specific filter sets with excitation wavelength of 488 nm for GFP and 584 nm for mRFP. The specific experimental procedure was described previously (4).

Western blotting

For the CQ combination group: MDA-MB-231 cells were treated with MA alone or combined with CQ for 24 h. For the siRNA interference group: MDA-MB-231 cells were transfected with si-NC or si-NCOA4 for 48 h, and then incubated with MA for an additional 24 h before. Total protein was then extracted using radioimmunoprecipitation assay (RIPA) lysis buffer. The primary antibodies, anti GPX4, anti-LC3B, anti-p53, anti-ATG5, anti-ULK1, anti-BECN1, anti-mTOR, anti-mitogen-activated protein kinase 3/1 (MAPK3/1) (CSB-PA226662, CUSABIO), anti-p62 (D163941, Sangon Biotechnology), anti-SLC7A11 (RC-3043, Absea Biotechnology), anti-NCOA4 (A31284, Nature Biosciences), anti-FTH1(RC-4140, Absea Biotechnology) and anti-β-actin were incubated overnight at 4 ℃. The goat anti-rabbit IgG H&L were incubated at room temperature for 1 h. Antibodies were used as previously described (4).

Calcein/PI cell viability assay and ROS detection

MDA-MB-231 cells were cultured in 96-well plates until the cell density reached 70%. The cells were treated with MA and erastin (a ferroptosis inducer) for 24 h, while the control group received an equivalent volume of DMSO. Cell viability was assessed using a Calcein/PI cell viability assay kit (C2015S, Beyotime Biotech). The fluorescence was visualized under an Olympus IX73 fluorescence inverted microscope, with excitation wavelength was set at 494 nm for Calcein and 535 nm for PI. Intracellular ROS production was detected using a ROS detection kit (I1265, Beyotime Biotech). ROS levels were observed under the same fluorescence inverted microscope using a filter set with an excitation wavelength of 488 nm.

Ferrous ions, glutamate (Glu), glutathione (GSH), and glutathione disulfide (GSSG) detection

MDA-MB-231 cells were treated with MA alone or following transfection with si-NCOA4 for 24 h. Subsequently, the intracellular ferrous ion (Fe²⁺) content was detected using a ferrous ion content assay kit (BC5410, Solarbio Science & Technology), the Glu content was measured using a Glu content detection kit (D799585, Sangon Biotechnology), and GSH and GSSG contents were measured using corresponding detection kits (D799613; D799615, Sangon Biotechnology), respectively. All measurements were performed using a microplate reader via spectrophotometric methods.

Targets of breast cancer, MA, ferroptosis and autophagy

This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Genes associated with breast cancer were retrieved from the GeneCards (https://www.genecards.org/) (16), OMIM (https://www.omim.org/) (17), DrugBank (https://go.drugbank.com/) (18) and TDD (https://ttd.idrblab.cn/) (19) databases using “breast cancer” as keywords. To ensure that the genes obtained were highly relevant to the disease, the “association score” threshold in GeneCards was set at 20. Potential drug targets of MA, were predicted using four databases, namely the Swiss target prediction (https://swisstargetprediction.ch/) (20), HERB (http://47.92.70.12/) (21), TargetNet (http://targetnet.scbdd.com/home/index/) (22) and Pharmmapper (https://www.lilab-ecust.cn/pharmmapper/) (23). Ferroptosis related targets were obtained from the FerrDb database (http://www.zhounan.org/ferrdb/current/) (24). Autophagy related targets were obtained from the HAMdb database (http://hamdb.scbdd.com/home/download/) (25).

Construction of the protein-protein interaction (PPI) network

A total of 41 intersecting genes among MA, breast cancer, and ferroptosis were merged with four experimentally verified ferroptosis marker genes, including SLC7A11, GPX4, FTH1, and NCOA4 (Table S1). The combined genes were imported into the STRING database (https://cn.string-db.org/) (26). The species was set to Homo sapiens with a confidence score threshold of 0.40 to construct the PPI network. Similarly, 43 intersecting genes among MA, breast cancer, and autophagy were merged with nine experimentally verified autophagy-related genes including LC3B, p53, mTOR, ATG5, MAPK3, MAPK1, ULK1, BECN1 (Table S2), and the PPI network was constructed using the same parameters. The PPI network data in TSV format were downloaded respectively and imported into Cytoscape for visualization, and the Degree algorithm was used to screen the hub genes (27,28).

Bioinformatics analysis of genes

UALCAN database (https://ualcan.path.uab.edu/index.html) (29) was used to assess the mRNA expression levels of target genes in normal and breast cancer tissues. In addition, the Kaplan Meier-Plotter tool (https://kmplot.com/analysis/) (30) was applied to the analyze the correlation between gene mRNA expression levels and survival rates in breast cancer patients.

Statistical analysis

Statistical analyses were carried out using SPSS 16.0 software (IBM Corp., Armonk, NY, USA). Each experiment was independently replicated a minimum of three times. The experimental data are presented as the mean ± standard deviation (SD). For comparisons between two independent samples, an independent-samples t-test was employed. Statistical significance was defined as a P value less than 0.05.

Results

Treatment with MA inhibits proliferation of breast cancer cells

MCF-7, T47D, and MDA-MB-231 cells were treated with MA. With increasing MA concentrations, cell numbers gradually decreased, accompanied by cell shrinkage, rupture, and death (Figure 1A). After 24 h of MA treatment, MTT assays determined the IC₅₀ values of MA toward MCF-7, T47D, and MDA-MB-231 cells as 88.33 µM, 103.95 µM, and 99.92 µM respectively. EdU cell proliferation assays evaluated MA’s effect on MCF-7, T47D, and MDA MB-231 cell proliferation. The results showed that compared with the solvent control group, MA treatment significantly reduced cell proliferation in a dose-dependent manner (Figure 1B-1D). After 24 h of treatment with 60 µM MA, the proportion of proliferating MDA-MB-231 cells decreased to 21% (Figure 1D).

Figure 1 MA inhibits the proliferation of breast cancer cells. (A) The morphology and quantity of breast cancer cells treated with different concentrations of MA for 24 h. Scale bar, 400 µm. An EdU cell proliferation assay was used to detect the proliferative ability of MCF-7 (B), T47D (C), and MDA-MB-231 (D) cells after MA treatment. Scale bar, 200 µm. Quantitative analysis was used to show the percentage of proliferating cells. *, P<0.05; **, P<0.01; ***, P<0.001 vs. the control. EdU, 5-ethynyl-2′-deoxyuridine; MA, maslinic acid.

Treatment with MA induces autophagy in breast cancer cells

In recent years, studies have found that MA exerts an anti-tumor effect by inducing autophagy in cancer cells. Therefore, we detected the autophagy status of breast cancer cells after MA treatment. MCF-7, T47D, and MDA-MB-231 cells were transfected with the mRFP-GFP-LC3 plasmid. Based on the co-localization of red (indicating autolysosomes) and green (indicating no autolysosomes) fluorescence, it was observed that MA could activate autophagic flux in MCF-7 (Figure 2A), T47D (Figure 2B), and MDA-MB-231 cells (Figure 2C). In addition, western blotting results showed that with increasing MA concentration, more LC3-I was converted to LC3-II, accompanied by decreased p62 expression, in MCF-7 (Figure 2D,2E), T47D (Figure 2F,2G), and MDA-MB-231 cells (Figure 2H,2I), further confirming the activation of autophagic flux. To further confirm the signaling pathway responsible for MA-induced autophagy in breast cancer cells, we treated MDA-MB-231 cells with MA and detected the changes in the expression of proteins related to the mTOR signaling pathway. The results of western blotting showed that with the increase in MA concentration, the levels of MAPK3/1 and mTOR were downregulated, the level of p53 was upregulated, and the levels of proteins related to the autophagy-initiating mechanism, such as BECN1, ULK1 and ATG5, were all upregulated (Figure 2J,2K). Among these genes, the mRNA expression levels of p53, BECN1 and ULK1 were significantly upregulated in breast cancer tissues (Figure S1A-S1C), and the elevated expression of these three genes was significantly correlated with improved survival rates in breast cancer patients (Figure S1D-S1F). A Venn diagram identified 43 shared potential target genes through which MA induces autophagy in breast cancer cells (Figure 2L). PPI network analysis identified eight hub genes: TP53, heat shock protein 90 alpha family class a member 1 (HSP90AA1), AKT serine/threonine kinase 1 (AKT1), mTOR, tumor necrosis factor (TNF), interleukin 6 (IL6), epidermal growth factor receptor (EGFR) and BCL2 apoptosis regulator (BCL2) (Figure 2M).

Figure 2 MA induces autophagy in breast cancer cells. mRFP-GFP-LC3 fluorescence imaging was performed to visualize autophagic flux in MCF-7 (A), T47D (B) and MDA-MB-231 (C) cells following treatment with increasing concentrations of MA for 24 h. Scale bar, 50 µm. Western blotting of LC3-II/I and p62 in MCF-7 (D,E), T47D (F,G), and MDA-MB-231 (H,I) cells treated with MA for 24 h. (J,K) The expression levels of mTOR, MAPK3/1, p53, ULK1, BECN1, and ATG5 as detected using western blotting. (L) A Venn diagram of genes related to MA, breast cancer, and autophagy. (M) The PPI network of potential autophagy targets of MA in breast cancer cells, constructed via STRING database and Cytoscape software. *, P<0.05; **, P<0.01; ***, P<0.001 vs. the control. ATG5, autophagy protein 5; BECN1, beclin 1; MA, maslinic acid; MAPK3, mitogen-activated protein kinase 3; mTOR, mammalian target of rapamycin; PPI, protein-protein interaction; ULK1, unc-51 like autophagy activating kinase 1.

Treatment with MA induces ferroptosis in MDA-MB-231 cells

TNBC cells exhibit distinct biological features, including high iron content, active lipid metabolism, and weak antioxidant defenses, leading to their unique intrinsic susceptibility to ferroptosis (31). This study investigated the effect of MA on ferroptosis in MDA-MB-231 cells. The Calcein/PI fluorescence staining results revealed that, as the MA concentration increased, the red fluorescence (dead MDA-MB-231 cells) was enhanced compared with that in the control (Figure 3A). Erastin enhanced MA-induced ferroptosis in MDA-MB-231 cells (Figure 3A). Results from intracellular ROS levels detection showed that MA treatment significantly increased intracellular ROS levels compared with those in the control group, and erastin could enhance this effect (Figure 3B,3C). Western blotting experiments detected the expression of GPX4, a key factor regulating cell survival. Treatment with MA dose-dependently downregulated the levels of GPX4 and SLC7A11 in MDA-MB-231 cells (Figure 3C,3D). GSH is the preferred substrate for GPX4 and the main antioxidant in mammals; consequently, Glu accumulation (Figure 3E), a decreased GSH content (Figure 3F), and an increased GSSG content (Figure 3G) were also detected in MA-treated MDA-MB-231 cells. Iron is a key factor in the ferroptosis process; therefore, we detected the changes in the iron content in MDA-MB-231 cells after MA treatment. The results showed that MA upregulated the content of ferrous ions in the cells (Figure 3H). Furthermore, MA up-regulated NCOA4 expression and down-regulated FTH1 expression (Figure 3I,3J). Among these, the mRNA expression levels of SLC7A11, FTH1 and NCOA4 were all significantly upregulated in breast cancer tissues (Figure S1G-S1I); moreover, elevated survival rates of breast cancer patients were significantly correlated with decreased expression of SLC7A11 (Figure S1J).

Figure 3 MA induced ferroptosis in MDA-MB-231 cells. (A) Fluorescence microscopy images of MDA-MB-231 cells co-stained with Calcein (green, live cells) and PI (red, dead cells) after treatment with MA and erastin. Scale bar, 200 µm. (B,C) The production of ROS in MDA-MB-231 cells after treatment with MA and erastin. Scale bar, 200 µm. (D,E) The expression of GPX4 and SLC7A11 as detected using western blotting. The concentration of Glu (F), GSH (G), and GSSG (H), Fe²⁺ (I) in MDA MB 231 cells. *, P<0.05; **, P<0.01; ***, P<0.001 vs. the control. ^#, P<0.05 vs. erastin group at the same MA concentration. Glu, glutamate; GSH, glutathione; GSSG, glutathione disulfide; MA, maslinic acid.

To determine whether autophagy acts upstream of ferroptosis, we co-treated MDA-MB-231 cells with the autophagy inhibitor CQ and MA. The results showed that CQ treatment further enhanced MA-induced upregulation of NCOA4, while reversing the degradation of FTH1 observed in MA-treated cells (Figure 4C,4D). These results strongly suggest that MA-induced ferroptosis is partially dependent on the autophagic process. Co-treatment with CQ significantly rescued cell viability and attenuated the MA-induced reduction in cell viability (Figure 4E). To validate the specific role of NCOA4-mediated ferritinophagy in this process, we knocked down NCOA4 using specific siRNA. Our data demonstrate that NCOA4 knockdown significantly abrogated MA-induced degradation of FTH1 (Figure 4F,4G), and prevented the accumulation of intracellular labile iron (Fe²⁺) (Figure 4H). This confirms that NCOA4-mediated ferritinophagy serves as the bridge, making autophagy and ferroptosis causally linked sequential events rather than independent parallel pathways.

Figure 4 MA induces ferroptosis in MDA-MB-231 cells through NCOA4-mediated ferritinophagy. (A,B) The expression of NCOA4 and FTH1 as detected using western blotting. (C,D) Western blotting analysis of NCOA4 and FTH1 expression in MDA-MB-231 cells treated with MA (40 µM) with or without CQ (10 µM) for 24 h. (E) MTT assay was performed to assess cell viability in MDA-MB-231 cells treated with MA (40 µM) with or without CQ (10 µM) for 24 h. (F,G) Western blotting was performed on MDA-MB-231 cells transfected with si-NC or si-NCOA4 for 48 h and exposed to MA (40 µM) for 24 h to detect NCOA4 and FTH1 expression. (H) Fe²⁺ detection was performed on MDA-MB-231 cells transfected with si-NC or si-NCOA4 for 48 h and exposed to MA (40 µM) for 24 h. (I) A Venn diagram of genes related to MA, breast cancer, and ferroptosis. (J) The PPI network of potential targets mediating MA-induced ferroptosis in breast cancer cells, constructed via the STRING database and Cytoscape software. *, P<0.05; **, P<0.01; ***, P<0.001. FTH1, ferritin heavy chain 1; MA, maslinic acid; MTT, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide; NCOA4, nuclear receptor coactivator 4; PPI, protein-protein interaction; STRING, Search Tool for the Retrieval of Interacting Genes/Proteins.

A Venn diagram identified 41 shared potential target genes mediating the induction of ferroptosis in breast cancer cells by MA (Figure 4I). PPI network analysis identified eight hub genes, namely MAPK3, RELA proto-oncogene (RELA), EGFR, prostaglandin-endoperoxide synthase 2 (PTGS2), SRC proto-oncogene (SRC), interleukin 1 beta (IL1B), IL6 and peroxisome proliferator activated receptor gamma (PPARG) (Figure 4J).

Discussion

The natural anti-tumor drug MA has attracted widespread attention from researchers. Previous studies have demonstrated that MA can inhibit the proliferation of colorectal cancer cells (3), pancreatic cancer cells (5), human renal cell carcinoma cells (6), and gastric cancer cells (7). In this study, we demonstrate that MA also effectively inhibits the proliferation of MCF-7, T47D, and MDA-MB-231 breast cancer cell lines. MA exhibits significant cytotoxicity towards non-cancerous cells (MCF-10A and SVCT) at the concentrations used in this study. The therapeutic application of MA still faces potential challenges. Future research should focus on strategies to improve cancer cell selectivity, such as structural modification of MA or the development of targeted nano-formulations.

Our previous studies have demonstrated that MA induces autophagy of prostate cancer cells (4). In this study, we observed that MA also induced autophagy in breast cancer cells. The mTOR signaling cascade is a pivotal regulator of autophagy (32), and p53 promotes autophagy by downregulating mTOR activity (33). Notably, treatment of MDA-MB-231 cells with MA reduced the levels of MAPK3/1 and mTOR while upregulating p53 expression. Furthermore, MA upregulated the levels of the autophagy-related proteins BECN1, ULK1, and ATG5, which are critical for autophagy initiation and execution (34). These results indicates that MA-induced p53 upregulation inhibits the mTOR signaling pathway, thereby inducing autophagy in MDA-MB-231 cells. In this study, the three breast cancer cell lines utilized harbor either mutant or wild-type p53. Given the well-documented crosstalk between p53 and the mTOR signaling pathway, this genetic difference could potentially influence the cellular response to MA and the relative contribution of the p53/mTOR axis to the observed phenotypes. Future investigations are warranted to precisely delineate the modulatory role of p53 status in this process.

Ferroptosis is characterized by the accumulation of intracellular free iron ions and lipid peroxidation products (34). Its regulation primarily involves iron metabolism (35), System Xc⁻ activity (36), GSH metabolism (9), GPX4 activity (37), and ROS generation (38,39). Downregulation of SLC7A11 (a key component of System Xc⁻) expression, or inhibition of GPX4 activity can induce ferroptosis (40,41). Jiang et al. demonstrated that p53 inhibits SLC7A11 expression, thereby suppressing cysteine uptake and promoting ferroptosis (42). This regulatory axis is further supported by a recent systems biology study. By employing a dynamic Boolean model, the study identified the p53-SLC7A11 (xCT) axis as a conserved mechanism of ferroptosis regulation across multiple cancer types (43). These systemic insights align with our observations in breast cancer cells. It further proves that MA-mediated p53-SLC7A11 signaling represents a robust and universal strategy for tumor suppression. In this study, treatment of MDA-MB-231 cells with MA decreased SLC7A11 and GPX4 expression while increasing p53 expression. GPX4 utilizes GSH to reduce intracellular ROS, eliminate the toxicity of lipid peroxides, and suppress ferroptosis (44). Furthermore, MA inhibits System Xc^- transport function, and increases conversion of GSH to GSSG in MDA-MB-231 cells. Ferritinophagy, a selective autophagic process mediated by NCOA4, involves the recognition and binding of ferritin (45). This complex is subsequently degraded within autolysosomes, releasing free iron ions (Fe²⁺) (45). Excessive free Fe²⁺ can generate harmful free radicals and lethal peroxidized lipid substances (35,39). In this study, we observed that MA treatment significantly increased intracellular Fe²⁺ in MDA-MB-231 cells. Concurrently, our results suggest that MA enhances NCOA4-mediated ferritin degradation by activating autophagic pathways, providing the necessary iron ion source for ferroptosis, thereby establishing a potential link between autophagy and ferroptosis. Furthermore, from the perspective of the regulatory relationship between iron metabolism and ferroptosis regulation, the absorption (46), storage (47), utilization, and efflux (48) of iron are all involved in the regulatory process of ferroptosis. Previous studies indicate that CT-1, a cryptotanshinone derivative, induced ferroptosis in TNBC cells by targeting FTH1 (49), while salidroside sensitizes TNBC cells to ferroptosis through NCOA4-mediated ferritinophagy (50). Collectively, these findings demonstrate that MA induces ferroptosis in MDA-MB-231 cells through dual mechanisms: GSH reprogramming and a ferritinophagy-mediated pathway.

MA exerts broad-spectrum anti-tumor effects through a multi-target and multi-pathway mechanism (51,52). Our results show that MA regulates both autophagy and ferroptosis through a multi-targeted mode of action. These findings further provide new directions for subsequent mechanistic studies.

Conclusions

This study found that MA can induce autophagy and ferroptosis in breast cancer cells. On the one hand, MA induces autophagy by upregulating p53 expression and inhibiting the mTOR autophagy signaling pathway in breast cancer cells. On the other hand, MA induces ferroptosis in MDA-MB-231 cells through dual mechanisms: GSH reprogramming and ferritinophagy-mediated pathway (Figure 5).

Figure 5 Mechanisms of MA against breast cancer cells. ATG5, autophagy protein 5; BECN1, beclin 1; FTH1, ferritin heavy chain 1; GSH, glutathione; GSSG, glutathione disulfide; MA, maslinic acid; MAPK3, mitogen-activated protein kinase 3; mTOR, mammalian target of rapamycin; NCOA4, nuclear receptor coactivator 4; ULK1, unc-51 like autophagy activating kinase 1.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0145/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0145/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0145/prf

Funding: This work was supported by grants from the Natural Science Foundation of Hebei Province (Nos. H2025209057 and C2023204100), and S&T Program of Tangshan (No. 25130222B).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2026-1-0145/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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

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. Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 2021;71:209-49. [Crossref] [PubMed]
2. Lin X, Ozbey U, Sabitaliyevich UY, et al. Maslinic acid as an effective anticancer agent. Cell Mol Biol (Noisy-le-grand) 2018;64:87-91.
3. Reyes-Zurita FJ, Pachón-Peña G, Lizárraga D, et al. The natural triterpene maslinic acid induces apoptosis in HT29 colon cancer cells by a JNK-p53-dependent mechanism. BMC Cancer 2011;11:154. [Crossref] [PubMed]
4. Hu F, Sun Y, Zhang Y, et al. Maslinic acid induces autophagy and ferroptosis via transcriptomic and metabolomic reprogramming in prostate cancer cells. Front Pharmacol 2024;15:1453447. [Crossref] [PubMed]
5. Tian Y, Xu H, Farooq AA, et al. Maslinic acid induces autophagy by down-regulating HSPA8 in pancreatic cancer cells. Phytother Res 2018;32:1320-31. [Crossref] [PubMed]
6. Thakor P, Song W, Subramanian RB, et al. Maslinic Acid Inhibits Proliferation of Renal Cell Carcinoma Cell Lines and Suppresses Angiogenesis of Endothelial Cells. J Kidney Cancer VHL 2017;4:16-24. [Crossref] [PubMed]
7. Wang D, Tang S, Zhang Q. Maslinic acid suppresses the growth of human gastric cells by inducing apoptosis via inhibition of the interleukin-6 mediated Janus kinase/signal transducer and activator of transcription 3 signaling pathway. Oncol Lett 2017;13:4875-81. [Crossref] [PubMed]
8. Wang X, Ren X, Lin X, et al. Recent progress of ferroptosis in cancers and drug discovery. Asian J Pharm Sci 2024;19:100939. [Crossref] [PubMed]
9. Dixon SJ, Lemberg KM, Lamprecht MR, et al. Ferroptosis: an iron-dependent form of nonapoptotic cell death. Cell 2012;149:1060-72. [Crossref] [PubMed]
10. Xu T, Ding W, Ji X, et al. Molecular mechanisms of ferroptosis and its role in cancer therapy. J Cell Mol Med 2019;23:4900-12. [Crossref] [PubMed]
11. Li K, Xu K, He Y, et al. Oxygen Self-Generating Nanoreactor Mediated Ferroptosis Activation and Immunotherapy in Triple-Negative Breast Cancer. ACS Nano 2023;17:4667-87. [Crossref] [PubMed]
12. Li K, Lin C, Li M, et al. Multienzyme-like Reactivity Cooperatively Impairs Glutathione Peroxidase 4 and Ferroptosis Suppressor Protein 1 Pathways in Triple-Negative Breast Cancer for Sensitized Ferroptosis Therapy. ACS Nano 2022;16:2381-98. [Crossref] [PubMed]
13. Xie C, Chan L, Pang Y, et al. Rosmarinic acid promotes mitochondrial fission and induces ferroptosis in triple-negative breast cancer cells. Naunyn Schmiedebergs Arch Pharmacol 2025;398:10461-75. [Crossref] [PubMed]
14. Yang X, Liang B, Zhang L, et al. Ursolic acid inhibits the proliferation of triple negative breast cancer stem like cells through NRF2 mediated ferroptosis. Oncol Rep 2024;52:94. [Crossref] [PubMed]
15. Jain R, Grover A. Maslinic acid differentially exploits the MAPK pathway in estrogen-positive and triple-negative breast cancer to induce mitochondrion-mediated, caspase-independent apoptosis. Apoptosis 2020;25:817-34. [Crossref] [PubMed]
16. Safran M, Dalah I, Alexander J, et al. GeneCards Version 3: the human gene integrator. Database (Oxford) 2010;2010:baq020. [Crossref] [PubMed]
17. Amberger JS, Bocchini CA, Schiettecatte F, et al. OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders. Nucleic Acids Res 2015;43:D789-98. [Crossref] [PubMed]
18. Knox C, Wilson M, Klinger CM, et al. DrugBank 6.0: the DrugBank Knowledgebase for 2024. Nucleic Acids Res 2024;52:D1265-75. [Crossref] [PubMed]
19. Zhang Y, Zhou Y, Xu H, et al. Therapeutic target database 2026: facilitating targeted therapies and precision medicine. Nucleic Acids Res 2026;54:D1692-701. [Crossref] [PubMed]
20. Daina A, Michielin O, Zoete V. SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules. Nucleic Acids Res 2019;47:W357-64. [Crossref] [PubMed]
21. Fang S, Dong L, Liu L, et al. HERB: a high-throughput experiment- and reference-guided database of traditional Chinese medicine. Nucleic Acids Res 2021;49:D1197-206. [Crossref] [PubMed]
22. Yao ZJ, Dong J, Che YJ, et al. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models. J Comput Aided Mol Des 2016;30:413-24. [Crossref] [PubMed]
23. Wang X, Shen Y, Wang S, et al. PharmMapper 2017 update: a web server for potential drug target identification with a comprehensive target pharmacophore database. Nucleic Acids Res 2017;45:W356-60. [Crossref] [PubMed]
24. Zhou N, Yuan X, Du Q, et al. FerrDb V2: update of the manually curated database of ferroptosis regulators and ferroptosis-disease associations. Nucleic Acids Res 2023;51:D571-82. [Crossref] [PubMed]
25. Wang NN, Dong J, Zhang L, et al. HAMdb: a database of human autophagy modulators with specific pathway and disease information. J Cheminform 2018;10:34. [Crossref] [PubMed]
26. Szklarczyk D, Nastou K, Koutrouli M, et al. The STRING database in 2025: protein networks with directionality of regulation. Nucleic Acids Res 2025;53:D730-7. [Crossref] [PubMed]
27. Chin CH, Chen SH, Wu HH, et al. cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol 2014;8:S11. [Crossref] [PubMed]
28. Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003;13:2498-504. [Crossref] [PubMed]
29. Chandrashekar DS, Karthikeyan SK, Korla PK, et al. UALCAN: An update to the integrated cancer data analysis platform. Neoplasia 2022;25:18-27. [Crossref] [PubMed]
30. Posta M, Győrffy B. Pathway-level mutational signatures predict breast cancer outcomes and reveal therapeutic targets. Br J Pharmacol 2025;182:5734-47. [Crossref] [PubMed]
31. Verma N, Vinik Y, Saroha A, et al. Synthetic lethal combination targeting BET uncovered intrinsic susceptibility of TNBC to ferroptosis. Sci Adv 2020;6:eaba8968. [Crossref] [PubMed]
32. Yang Z, Klionsky DJ. Mammalian autophagy: core molecular machinery and signaling regulation. Curr Opin Cell Biol 2010;22:124-31. [Crossref] [PubMed]
33. Wang Y, Zhang H. Regulation of Autophagy by mTOR Signaling Pathway. Adv Exp Med Biol 2019;1206:67-83. [Crossref] [PubMed]
34. Liu S, Yao S, Yang H, et al. Autophagy: Regulator of cell death. Cell Death Dis 2023;14:648. [Crossref] [PubMed]
35. Dixon SJ, Stockwell BR. The role of iron and reactive oxygen species in cell death. Nat Chem Biol 2014;10:9-17. [Crossref] [PubMed]
36. Song X, Zhu S, Chen P, et al. AMPK-Mediated BECN1 Phosphorylation Promotes Ferroptosis by Directly Blocking System X(c)(-) Activity. Curr Biol 2018;28:2388-2399.e5. [Crossref] [PubMed]
37. Friedmann Angeli JP, Schneider M, Proneth B, et al. Inactivation of the ferroptosis regulator Gpx4 triggers acute renal failure in mice. Nat Cell Biol 2014;16:1180-91. [Crossref] [PubMed]
38. Gao M, Monian P, Quadri N, et al. Glutaminolysis and Transferrin Regulate Ferroptosis. Mol Cell 2015;59:298-308. [Crossref] [PubMed]
39. Jiang X, Stockwell BR, Conrad M. Ferroptosis: mechanisms, biology and role in disease. Nat Rev Mol Cell Biol 2021;22:266-82. [Crossref] [PubMed]
40. Liu Y, Wang Y, Liu J, et al. Interplay between MTOR and GPX4 signaling modulates autophagy-dependent ferroptotic cancer cell death. Cancer Gene Ther 2021;28:55-63. [Crossref] [PubMed]
41. Ou Y, Wang SJ, Li D, et al. Activation of SAT1 engages polyamine metabolism with p53-mediated ferroptotic responses. Proc Natl Acad Sci U S A 2016;113:E6806-12. [Crossref] [PubMed]
42. Jiang L, Kon N, Li T, et al. Ferroptosis as a p53-mediated activity during tumour suppression. Nature 2015;520:57-62. [Crossref] [PubMed]
43. Gupta S, Silveira DA, Mombach JCM, et al. DNA Damage-Induced Ferroptosis: A Boolean Model Regulating p53 and Non-Coding RNAs in Drug Resistance. Proteomes 2025;13:6. [Crossref] [PubMed]
44. Friedmann Angeli JP, Conrad M. Selenium and GPX4, a vital symbiosis. Free Radic Biol Med 2018;127:153-9. [Crossref] [PubMed]
45. Wu K, Zhao W, Hou Z, et al. Ferritinophagy: multifaceted roles and potential therapeutic strategies in liver diseases. Front Cell Dev Biol 2025;13:1551003. [Crossref] [PubMed]
46. Chen X, Yu C, Kang R, et al. Iron Metabolism in Ferroptosis. Frontiers in cell and developmental biology 2020;8:590226.
47. Wolff NA, Garrick MD, Zhao L, et al. A role for divalent metal transporter (DMT1) in mitochondrial uptake of iron and manganese. Sci Rep 2018;8:211. [Crossref] [PubMed]
48. Wang N, Ma H, Li J, et al. HSF1 functions as a key defender against palmitic acid-induced ferroptosis in cardiomyocytes. J Mol Cell Cardiol 2021;150:65-76. [Crossref] [PubMed]
49. Liu Y, Sun Q, Guo J, et al. Dual ferroptosis induction in N2-TANs and TNBC cells via FTH1 targeting: A therapeutic strategy for triple-negative breast cancer. Cell Rep Med 2025;6:101915. [Crossref] [PubMed]
50. Huang G, Cai Y, Ren M, et al. Salidroside sensitizes Triple-negative breast cancer to ferroptosis by SCD1-mediated lipogenesis and NCOA4-mediated ferritinophagy. J Adv Res 2025;74:589-607. [Crossref] [PubMed]
51. Wang Y, Zhang H, Ye Z, et al. Maslinic Acid Inhibits the Growth of Malignant Gliomas by Inducing Apoptosis via MAPK Signaling. J Oncol 2022;2022:3347235. [Crossref] [PubMed]
52. Zhang H, Kong L, Zhang Y, et al. Transcriptome and proteome analysis of the antitumor activity of maslinic acid against pancreatic cancer cells. Aging (Albany NY) 2021;13:23308-27. [Crossref] [PubMed]