Skip to main content
Download PDF

In vitro analysis of the molecular mechanisms of ursolic acid against ovarian cancer

BMC Complementary Medicine and Therapies volume 25, Article number: 65 (2025) Cite this article

Abstract

Ovarian cancer is one of most common gynaecologic malignancy and ranks third in cancer-related deaths among women. Ursolic acid (UA) is a pharmacologically active pentacyclic triterpenoid isolated from a large variety of vegetables, fruits and many traditional medicinal plants. However, the mechanism of action of UA in inhibiting the proliferation of ovarian cancer cells remains unclear. Consequently, this experiment was designed to elucidate the mechanism of action of UA in inhibiting the proliferation of ovarian cancer cells in greater detail.The results indicated that UA was capable of effectively inhibiting the proliferation, migration, and colony formation of ovarian cancer cells.UA was observed to up-regulate Bcl-2-associated X protein(BAX)and cysteinyl aspartate specific proteinase 3 (Caspase3) expression and down-regulating B-cell lymphoma-2(Bcl-2) expression.Meanwhile, UA up-regulated Sequestosome 1(p62)expression and down-regulated coiled-coil, moesin-like BCL2-interacting protein(Becline1), microtubule-associated proteins light chain 3(LC3), Phosphoinositide 3-Kinase(PI3K), andProtein Kinase B( AKT) expression, thus effectively inhibiting autophagy in ovarian cancer cells.Furthermore, UA upregulated pancreatic ER kinase (PKR)-like ER kinase (PERK), eukaryotic translation initiation factor 2 A(eIF2α), and The C/EBP Homologous Protein(CHOP) expression.In addition UA upregulates PERK, eIF2α, and CHOP expression and effectively promotes endoplasmic reticulum stress(ERS).In conclusion, UA can inhibit ovarian cancer cell proliferation, migration, colony formation, and may inhibit tumor cell autophagy by promoting tumor cell ERS, and ultimately promote ovarian cancer cell apoptosis.

Peer Review reports

Introduction

Ovarian cancer is among the seven most pervasive malignancies worldwide [1] and ranks as the second most common cause of death among gynaecological tumours [2, 3]. The most common form of ovarian cancer is epithelial ovarian cancer, which accounts for over 95% of all ovarian cancer cases in the US. Epithelial ovarian cancer has five primary histological subtypes: low-grade serous subtypes, high-grade serous subtypes, endometrioid, mucinous, and clear cell type [2, 4]. Both age and genetic predisposition are recognized risk factors for ovarian cancer [5]. The American Cancer Society estimated over 20,000 newly confirmed cases of ovarian cancer and approximately 13,770 patient fatalities in 2021 [4]. Due to the absence of early symptoms and the lack of timely and efficient screening procedures, approximately 70% of patients receive a delayed diagnosis, resulting in a five-year survival rate of only 30% [6,7,8]. Currently, platinum- and paclitaxel-based chemotherapy and cytoreductive surgery are the primary clinical interventions for ovarian cancer [4, 9,10,11]. Unfortunately, residual tumour cells remain after surgery for many patients, and this phenomenon is associated with lower survival rates [12]. Recurrence is often attributed to chemotherapy resistance [4]. Therefore, comprehending the pathogenesis of ovarian cancer could play a significant role in the advancement of novel alternative treatments. In recent years, Chinese botanicals have been developed as new types of natural anticancer medications [13]. These drugs can mitigate adverse effects, enhance prognosis, and extend patient survival [14]. By directly or indirectly influencing cancer immunity and the tumour microenvironment and inducing apoptosis, drugs can induce anticancer effects [13, 15, 16]. However, the possible mechanisms of herbal medicine in treating cancer are still unclear, and there is a paucity of therapeutic research on herbal medicine for ovarian cancer. Ursolic acid (UA), a pentacyclic triterpenoid compound, occurs naturally in various fruits and vegetables [17]. It is present in traditional Chinese medicines such as forsythia and chai hu, which have been demonstrated to possess antibacterial and anti-inflammatory properties, as well as other important sources of Chinese medicine.Interestingly, significant quantities of UA were discovered in apple peel [18]. UA has been extensively used in treating multiple cancers [17, 19]. Research has revealed that UA suppresses breast cancer cell proliferation by inactivating the PI3K/AKT signalling pathway [20]. Furthermore, its apoptosis-inducing and anti-inflammatory effects on breast cancer cells contribute to its anticancer properties [17, 21]. UA promotes programmed cell death and self-digestion in pancreatic cancer cells, which decreases their resistance to chemotherapy; this effect has been demonstrated in several studies [18, 22]. However, the mechanisms underlying the anticancer effects of UA remain unclear, and additional research is needed to establish an appropriate clinical dosage for the medication [17, 18]. UA has not been extensively investigated as a treatment for ovarian cancer.

The objective of this research was to examine the possible impact of UA on the ability of ovarian cancer cells to proliferate, migrate, and form colonies. Specifically, this study aimed to investigate whether UA could suppress the aforementioned cellular processes by activating ERS in ovarian cancer cells, leading to diminished autophagy as well as increased apoptosis. Network pharmacology analysis of the molecular mechanism of UA in treating ovarian cancer identified potential targets for molecular docking. Cell Counting Kit-8 (CCK-8) assays indicated that UA inhibited the proliferation of ovarian cancer cells, while colony formation and migration experiments demonstrated its impact on the formation and migration capability of ovarian cancer cells. Flow cytometry and Western blotting were performed for additional verification. The findings indicate that the therapeutic impact of UA on ovarian cancer may be linked to induction of ERS and suppression of autophagy, which also prompts apoptosis in ovarian cancer cells. These results offer promising insights and techniques for advancing ovarian cancer treatment in clinical settings.

Results

Network pharmacological predicts potential targets

The molecular formula for UA (Fig. 1A) and its 55 potential targets were retrieved from the TCMSP database. The UniProt database and the Stitch database were utilized to obtain 64 potential targets. Using the Disgenet and GeneCards databases, we obtained 3,500 disease-related targets. Fifty-five intersecting target genes (Fig. 1B) were obtained using a Venn diagram created via Venny. The STRING database was utilized to construct the PPI network (Fig. 1C) with 55 nodes and 679 edges. The core targets with the top ten degree values were screened using Cytoscape (Fig. 1D). The higher the degree values the more connections it has and the higher the relevance to the disease target network. These targets are predicted to be key targets for UA to inhibit ovarian cancer cell proliferation, further verification was performed in subsequent experiments. Use of the DAVID database for further analysis of biological processes and potential mechanisms of UA in ovarian cancer. The results indicate that the biological processes (BPs) involved are mainly the regulation of the apoptotic process.Cellular component (CC) enrichment mainly includes nucleoplasm, etc. Molecular function (MF) enrichment mainly includes protein binding, etc. (Fig. 1E). The most enriched pathways were apoptosis and the PI3K-Akt signalling pathway (Fig. 1F). The Compound-Disease-Intersecting Targets network was subsequently mapped (Fig. 1G). Based on the results of the network pharmacology analysis, we suggest that apoptosis and the PI3K-Akt signaling pathway may be pivotal in understanding the impact of UA on ovarian cancer.

Fig. 1
figure 1

Network pharmacology predicted the potential target of ursolic acid in ovarian cancer. (A) Chemical structure of ursolic acid (by ChemDraw). (B) Venn diagram of UA and OC, with 55 overlapping targets. (C) The STRING database was used to construct the PPI network of overlapping targets. (D) The Hubba plugin shows the top ten targets in terms of degree values. The shade of the color indicates the degree value, the darker the color the higher the degree value. (E) GO enrichment analysis of 55 common targets of OC and UA. The x-axis represents GO terms, and the y-axis represents the number of genes enriched in each GO term (p < 0.01). (F) KEGG pathway analysis. The x-axis represents the number of enriched targets in the pathway as a percentage of total targets, and the y-axis refers to the enriched pathway. The larger the dots are, the higher the number of enriched targets. The colour of the dots depends on the P value; the darker the colour is, the more significant the difference. (G) Construction of the disease-drug-target network. Orange hexagons represent diseases, pink arrows represent UA, and green diamonds represent related targets, with darker colours representing higher degree values

Full size image

Ursolic acid inhibits SKOV3 cell proliferation, colony formation, and migration

The effect of UA on SKOV3 cell proliferation was detected through CCK-8 assay. SKOV3 cells were treated with different concentrations of UA for 12 h, 24 h, and 48 h. Cisplatin was employed solely as a positive control. The results indicated a dose-dependent decline in cell viability with increasing concentration and time compared to that in the control group (Fig. 2A). These findings suggest that UA possesses the ability to impede the proliferation of SKOV3 cells. The inhibitory effect was more pronounced at 24 and 48 h than at 12 h, and the half-inhibitory concentration was measured to be 50 µmol/l; this dose was selected to be administered to SKOV3 cells for 24 h in subsequent experiments. Further validation of the inhibitory effect of UA on SKOV3 cells was performed by using colony formation analysis. The results showed a significant reduction in SKOV3 cell colonies in the UA group compared to the control group. The extent of this effect increased with the dose (Fig. 2B). To verify whether UA inhibits the migration of SKOV3 cells, a wound-healing assay was conducted. The experimental results demonstrated that UA can inhibit the migration of SKOV3 cells in a time- and dose-dependent manner. Additionally, the migration rate decreased from 39.78% in the control group to 0.243% in the 50 µmol/l group, while 100 µmol/l UA and cisplatin effectively eliminated SKOV3 cells (Fig. 2C-D). The study demonstrates that UA exerts an inhibitory effect on the proliferation of SKOV3 cells, as evidenced by CCK-8 and colony formation assays. Similarly, wound healing assays showed that UA effectively inhibits cell migration.

Fig. 2
figure 2

Ursolic acid inhibits the proliferation, migration, and colony formation of ovarian cancer (SKOV3) cells. (A) A CCK-8 assay was used to analyse the viability of SKOV3 cells cultured with UA. (B) The colony forming ability of SKOV3 cells was evaluated through a colony formation assay. (C) Cell migration ability was measured by wound healing assay in SKOV3 cells (100× magnification). (D) The migration rate of SKOV3 cells was measured using ImageJ software. The experiments were repeated three times. Compared to the control group, *p < 0.05, **p < 0.01; compared to the cisplatin group, #p < 0.05, ##p < 0.01

Full size image

Ursolic acid promotes SKOV3 cell apoptosis

Flow cytometry was utilized to investigate whether the suppression of cell proliferation was linked to apoptosis. The results indicated a notable rise in the count of early and middle apoptotic cells following 24-hour UA treatment in comparison to the control group (Fig. 3A). TUNEL staining provides further validation of the apoptotic effects of UA in a synergistic manner. Blue fluorescence indicates DAPI-stained nuclei, while red indicates apoptotic cells. The intensity of red fluorescence in the UA group was significantly higher than that in the control group, as confirmed by the flow-through results. The outcomes of the aforementioned experiments consistently demonstrate that UA effectively suppressed the proliferation of SKOV3 cells possibly by inducing apoptosis (Fig. 3B). To further explore whether apoptosis induced by UA occurs through the BAX pathway, we used Western blotting to measure the expression levels of BAX, BCL-2, Caspase-3 and c-Caspase-3. The study findings indicate that the expression of the pro-apoptotic genes BAX, Caspase-3 and c-Caspase-3 proteins was increased and the expression of the anti-apoptotic gene Bcl-2 was significantly decreased after treatment with UA compared to that in the control group. Both of these effects were dose dependent (Fig. 3C-D). Based on network pharmacology, the mechanisms of UA in treating ovarian cancer were studied. The targets included BAX and BCL-2, which were screened and subjected to molecular docking. The results revealed that UA had a binding energy of -7.4 kcal/mol with BCL-2 and − 7.6 kcal/mol with BAX (Fig. 3E-F). These findings indicate that UA induces apoptosis in SKOV3 cells by inhibiting the expression of BCL-2, thereby exerting an anti-ovarian cancer effect.

Fig. 3
figure 3

Ursolic acid promotes apoptosis in SKOV3 cells. Ursolic acid (50 µmol/L, 100 µmol/L) was used to treat SKOV3 cells for 24 h. (A) The cell apoptosis rate of transfected cells was determined by flow cytometry. (B) Evaluation of apoptotic cells by TUNEL staining in untreated and ursolic acid-treated SKOV3 cells. TUNEL (red) and DAPI (blue) were used as nuclear stains. The experiments were repeated three times. (C) The protein expression of Bax, Bcl-2, Caspase-3 and c-Caspase-3 in SKOV3 cells treated with various concentrations of UA was evaluated by Western blotting. β-Actin(actin beta) was used as a loading control. (D) The band densities were measured using ImageJ software to quantify the bands. The average was calculated from three independent experiments. (E-F) Molecular docking formula of Bax and Bcl-2. Compared to the control group, *p < 0.05, **p < 0.01; compared to the cisplatin group, #p < 0.05, ##p < 0.01

Full size image

Ursolic acid inhibits autophagy in SKOV3 cells via the Beclin 1 signalling pathway

To investigate the inhibitory effect of UA on cellular autophagy, we utilized Western blotting to detect the protein expression of Beclin1, P62, and LC3. The study findings revealed a decrease in the protein expression of Beclin1 and LC3 in comparison to that in the control group, while there was a significant increase in the protein expression of P62. To better understand how UA inhibits cellular autophagy, we analysed the protein expression of PI3K, AKT and p-AKT. The results showed that the expression of PI3K, AKT and p-AKT was decreased relative to that in the control group (Fig. 4A-B). Concurrently, we conducted a fluorescence microscopy-based analysis of LC3 expression, which was corroborated by the synergistic WB results, indicating that UA could effectively inhibit autophagy in ovarian cancer cells. Blue fluorescence indicates DAPI-stained nuclei, while green fluorescence indicates LC3 expression. The data indicate that the 50 µmol/l group exhibited less fluorescence expression than the control group in a dose-dependent fashion (Fig. 4C-D). The aforementioned empirical findings established that UA effectively inhibits autophagy in SKOV3 cells via the PI3K-AKT signalling pathway, ultimately playing a pivotal role in suppressing tumour growth. Nevertheless, elevated autophagy levels were observed in both cisplatin-resistant and cisplatin-sensitive tumour cells following cisplatin treatment, which is also consistent with the findings of our experimental investigation [23].

Fig. 4
figure 4

Ursolic acid inhibits autophagy in SKOV3 cells. (A) PI3K, AKT, p-AKT, Beclin1, P62 and LC3 were measured by Western blotting. β-Actin served as a loading control. All experiments were repeated three times. (B) The band densities were measured using ImageJ software to quantify the bands. (C-D) Immunofluorescence images of SKOV3 cells expressing LC3 after treatment with ursolic acid (50 µmol/L, 100 µmol/L). LC3 spots (green) correspond to autophagosome formation, and DAPI (blue) staining indicates the nucleus. Scale bars, 20 μm. The average was calculated from three independent experiments. Compared to the control group, *p < 0.05, **p < 0.01; compared to the cisplatin group, #p < 0.05, ##p < 0.01

Full size image

Ursolic acid promotes ERS in SKOV3 cells

To further study the mechanism of action of UA on SKOV3 cells, we detected the protein expression of the endoplasmic reticulum-associated proteins PERK, eIF2α, and CHOP via Western blotting. The protein expression of PERK, eIF2α, and CHOP was significantly higher in the 50 µmol/l group than in the control group (Fig. 5A-B). To verify that ursolic acid induces ERS in SKOV3 cells, CHOP expression was detected through immunofluorescence. The findings indicate that UA induces ERS in SKOV3 cells in a dose-dependent manner (Fig. 5C-D). This suggests that ursolic acid promotes apoptosis by inducing ERS, subsequently inhibiting autophagy.

Fig. 5
figure 5

Ursolic acid inhibits autophagy in SKOV3 cells by promoting ER stress. (A-B) CHOP, EIF2A, and PERK expression levels were assessed by Western blotting and quantitative measurement. Tubulin served as a loading control. (C-D) Immunofluorescence images of SKOV3 cells expressing CHOP after treatment with ursolic acid (50 µmol/L, 100 µmol/L). Scale bars, 20 μm. The average was calculated from three independent experiments. Compared to the control group, *p < 0.05, **p < 0.01; compared to the cisplatin group, #p < 0.05, ##p < 0.01

Full size image

Materials and methods

Network pharmacology predicts target genes

Target proteins associated with UA were obtained from the TCMSP (https://old.tcmsp-e.com/tcmsp.php) and STITCH (STITCH: chemical association networks (embl.de)) databases. The proteins generated were subsequently transformed into target genes utilizing UniProt (https://www.uniprot.org/). A gene search using the keywords “ovarian cancer” was conducted on the DisGenet (https://www.disgenet.org/home/) and GeneCards (https://www.genecards.org/) databases. A Venn diagram was created utilizing the online tool Venny (https://bioinfogp.cnb.csic.es/tools/venny/index.html) to identify common targets of UA and ovarian cancer. The STRING (https://cn.string-db.org/) database was utilized to construct the PPI network. Homo sapiens was selected in the “organism” column, and the PPI network was constructed. Use Cytoscape version 3.9.1. to screen for core targets with top ten degree values. The DAVID (ncifcrf.gov) database was employed to enrich Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes (KEGG) signalling pathways. Based on the count from largest to smallest, the top twenty terms for cellular component (CC), molecular function (MF), biological process (BP), and signalling pathways were selected and visualized using bioinformatics (https://www.bioinformatics.com.cn/). The molecular docking data were obtained using the PubChem database, Open Babel 2.3.2, and UniProt. Molecular docking was conducted via AutoDock Vina and ultimately visualized with PyMOL.

Reagents and instruments

SKOV3 (represents epithelial ovarian cancer) Friendship Sponsor of School of Basic Medical Sciences, Jilin University. Ursolic acid was obtained from Shyuanye and dissolved in 0.001% DMSO; RPMI1640 medium (AJ3073457, Stofan), fetal bovine serum (DF29570026, Stofan), penicillin and streptomycin (2307001, Solepol), trypsin (J230012, Stofan), cisplatin (421R021, Shanghai Yuanye), Cell Counting kit-8 ( C6005, NCM Biotech), Tunel staining kit (20231014, Solepol), Annexin V-FITC/PI apoptosis detection kit (AK13200, Elabscience), Bax (50599-2-lg, proteintech), Bcl-2 (26593-1-AP, proteintech), Caspase3(66470-1-lg, proteintech), β-actin(66009-1-lg, proteintech), PI3K(20584-1-AP, proteintech), AKT(66444-1-lg, proteintech), Beclin1(11306-1-AP, proteintech), p62(66184-1-lg, proteintech), LC3(14600-1-AP, proteintech), PERK(24390-1-AP, proteintech), eIF2α(11170-1-AP, proteintech), CHOP(15204-1-AP, proteintech), Tubulin(10094-1-AP, proteintech) were used. The Annexin V-conjugated FITC apoptosis detection kit was supplied by Elabscience. A carbon dioxide incubator (Thermo Fisher Scientific, BB150) was used. The BX53 fluorescence microscope was from OLYMPUS. The flow cytometer (Accuri C6) was from BD Biosciences.

Culture of ovarian cancer cell lines

Cell cryotubes are thawed quickly in a 37℃ water bath. Transfer the cell suspension to a centrifuge tube containing medium and centrifuge at 200 g for 5 min, discarding the supernatant. Add medium and mix gently, then dispense into petri dishes. SKOV3 cells were cultured in RPMI-1640 complete medium, which included 10% foetal bovine serum and 1% penicillin‒streptomycin. The cells were then incubated in a 37 °C incubator with 5% CO2, and the medium was replaced every other day. Passaging occurred when the cells reached approximately 90% confluency. Cells were grown until they reached their logarithmic growth phase for subsequent experiments and divided into control group, UA50 µmol/L, UA100 µmol/L, cisplatin (3µmol/ml) positive drug group.

Cell proliferation assay

Evaluation of cell proliferation utilizing the CCK-8 assay. Experiments were conducted using groups of ovarian cancer cells in the logarithmic growth phase. Three replicate wells were established to ensure accuracy. When the cells reached approximately 70% confluency, various drug concentrations were administered for 12, 24, and 48 h. Subsequently, 10 µL of CCK-8 solution was added to each well, followed by incubation for an additional 3 h. The wavelength of the enzyme-labeled instrument was established at 450 nm, and the resulting absorbance was subsequently quantified. Subsequently, the absorbance was used to plot the growth curve; the experiment was performed three times. The average value was determined.

Colony formation assay

SKOV3 cells were plated at a density of 0.1 × 106 cells per well in six-well plates. The cells were in a healthy state, and drugs were introduced. The culture was subsequently maintained. The initial medium was subsequently replaced with fresh medium at three-day intervals until observable colonies emerged. The supernatant was removed, and the cells were rinsed with phosphate-buffered saline (PBS) before being fixed with a 4% paraformaldehyde solution for 20 min. Afterwards, we utilized a solution of crystal violet staining to stain the cells for a duration of ten minutes, and photographs of the colonies were taken.

Wound healing assays

Cells from the logarithmic growth phase were harvested and seeded at a density of 1 × 106 cells per well into 6-well plates. The cells were cultured until a monolayer formed. A 200 µL pipette tip was employed to create a scratch along the horizontal line at the bottom of the plate. The cells were washed twice with PBS, and the medium was then replaced with medium containing 2% foetal bovine serum. Under a light microscope, the relative distance of the scratches was recorded. The incubation was continued for 12 and 24 h following drug administration, with the subsequent recording of scratch distance relative to the original mark. Cell migration distances were measured utilizing ImageJ software. The migration distance was calculated by subtracting the scratch width after treatment from that at 0 h.

Flow cytometry

The Annexin V-FITC/PI apoptosis detection kit was utilized. SKOV3 cells in optimal growth conditions were cultivated in 6-well plates at a density of 1 × 105 and incubated for 24 h. Cells were collected and suspended in precooled PBS three times. The cells were suspended in 200 µL of 1 × Annexin V binding buffer and then treated with 5 µL of FITC-Annexin V and PI stain for 15 min at room temperature in the dark. Detection was performed on a flow cytometer.

TUNEL staining to detect apoptosis

Cells were incubated on round coverslip for 24 h. Afterwards, the cells were fixed with paraformaldehyde for 30 min, permeabilized using 0.2% Triton X-10 for 20 min, and then incubated for 1 h in TUNEL staining solution away from light. Between each step of the operation, the cells were washed three times with precooled PBS, and then they were dehydrated using gradient concentration of ethanol and sealed with an anti-fluorescent burst sealer containing DAPI and clear nail polish. Finally, the cells were observed by using fluorescence microscopy.The wavelength of the red fluorescence is 720 nm.

Western blot analysis

SKOV3 cells were treated for 24 h. Cells were collected and lysed with cold RIPA lysis solution in an ice bath for 30 min. Total protein extraction was achieved through 4 °C centrifugation. BCA protein assay reagent was employed to determine the protein concentration. Equal quantities of protein were electrophoresed and transferred onto a PVDF membrane. Protein blots were blocked using TBST (TRIS-buffered saline pH 7.4 containing 0.1% Tween 20) containing 5% skim milk powder at room temperature for one hour. The specific primary antibody was incubated overnight at 4 °C. Subsequently, the blots were incubated with horseradish peroxidase (HRP)-coupled secondary antibodies. Protein bands were detected via a chemiluminescence kit and imaging system, and protein levels were analysed through ImageJ.

Immunofluorescence (IF) assay

The cells were moved to round coverslip then incubated. After a 30-minute fixation in 4% paraformaldehyde solution, they were permeabilized for 20 min using 0.2% Triton X-10. Next, the cells were blocked using 2% BSA for 30 min and left overnight at 4 °C with a primary antibody. The following day, a fluorescent secondary antibody was incubated for 1 h at room temperature in the dark. The cells were rinsed three times with prechilled PBS after each step. Then, the round coverslip were sealed using an anti-fading burst sealant that included DAPI. The application of clear nail polish serves to prevent the crawling flake from moving.The sections were then sealed and viewed under a fluorescence microscope.

Statistical methods

Statistical analysis was conducted using GraphPad Prism 8.0 software (GraphPad). The experiments were replicated thrice, and the outcomes reflected are illustrative of the experiments. Data are presented as the mean ± standard deviation (SD). Statistical significance was calculated by one-way or two-way analysis of variance (ANOVA). A p value < 0.05 was considered to indicate statistical significance.Compared to the control group, *p < 0.05, **p < 0.01; compared to the cisplatin group, #p < 0.05, ##p < 0.01.

Discussion

Ovarian cancer is a prevalent malignancy that poses a significant threat to women’s lives due to its high recurrence and mortality rates. The findings indicated that UA could inhibit the proliferation, colony formation and migration of tumour cells. A comprehensive investigation of the underlying mechanisms revealed that UA could induce endoplasmic reticulum stress, inhibit autophagy and promote apoptosis in Skov3 cells. These results suggest that UA holds potential as an antitumour agent.

An effective mechanism for inducing tumour cell death is apoptosis, which effectively regulates the number of tumour cells by, for example, inducing cell membrane rupture [24, 25]. Promotion of apoptosis is currently the prevailing method of targeted cancer therapy [26, 27]. The colony formation assay and migration assay demonstrated that UA could inhibit the proliferation and migration of ovarian cancer cells in a dose-dependent manner. Certain experiments indicate that the relevant drugs effectively inhibit the proliferation, migration, and colony formation of SKOV3 cells in vitro. Additionally, tumor size in mice with tumors was suppressed, further validating the therapeutic effects of the drugs against ovarian cancer. Therefore, we believe that ursolic acid can also effectively inhibit the proliferation of ovarian cancer [28,29,30]. Numerous studies suggest that UA can regulate diverse signalling pathways to impede the proliferation and migration of various tumours. For instance, it can suppress the AKT signalling pathway to restrain oesophageal cancer proliferation [31] and inhibit the ERK signalling pathway to suppress cell adhesion and migration, thereby inhibiting the progression of breast cancer [32]. The results of the present study are consistent with previous experimental findings and establish that UA inhibits ovarian cancer cell proliferation while also reducing migration rates.

The proper balance between the antiapoptotic gene Bcl-2 and the proapoptotic gene Bax is necessary for the maintenance of cellular homeostasis [33]. Reducing Bcl-2 expression significantly increases the pro-apoptotic effects of drugs [34]. Furthermore, members of the caspase family of cysteine proteases are crucial in initiating and executing apoptosis [33, 34]. To investigate whether UA inhibits SKOV3 cell proliferation via apoptosis promotion, we detected apoptosis through flow cytometry and TUNEL staining. Additionally, Western blot analysis revealed increased expression of Bax and Caspase3 proteins, along with decreased expression of Bcl-2 protein. The results of this study were in agreement with the above expression results.

Autophagy can enable cellular metabolism and maintain cellular biosynthesis by self-phagocytosing aggregated proteins and damaged organelles [35,36,37,38]. Autophagy provides the energy and metabolites, including arginine and alanine, that are essential for tumour growth [39,40,41,42].In the development of cancer, autophagy plays a bidirectional regulatory role. The inhibition of tumour progression by early autophagy is primarily dependent on the cellular microenvironment and the tumour’s degree of malignancy [8, 43,44,45]. The expression of autophagy-related proteins, such as Beclin1, was detected, and the findings indicate that the expression of Beclin1 and LC3 decreased, whereas the protein expression of P62 considerably increased in a dose-dependent manner. These results suggest that UA could inhibits autophagy in SKOV3 cells. However, autophagy levels were elevated in both cisplatin-resistant and cisplatin-sensitive tumour cells after cisplatin treatment, which is consistent with the experimental results [23]. Due to the bidirectional regulation of autophagy, inhibition of autophagy can effectively suppress tumour proliferation. The effectiveness of this approach has been demonstrated in experiments with cancers such as pancreatic ductal carcinoma, breast cancer and non-small cell lung cancer [46].Numerous studies have demonstrated that Beclin1 is closely linked to tumour progression and plays a significant role in cellular proliferation [47]. Autophagy centres on the autophagy initiation protein Beclin1, which generates the autophagy initiation complex (AIC) to aid autophagy, Beclin1 is a crucial compound in the formation of autophagosomes and the promotion of autophagosome maturation [48, 49]. Beclin1 generally interacts with BCL-2, resulting in the inhibition of cellular autophagy [47, 50]. In contrast, upregulation of Bax induces cytochrome C release, resulting in the cleavage of Beclin1 and inhibition of its autophagy induction effect [51]. LC3 is considered the protein that firmly binds to the autophagosome membrane. There are two variants of LC3 (LC3-I and LC3-II) [52].The results demonstrated that the total LC3 expression was diminished in a dose-dependent manner, indicating that UA was capable of inhibiting autophagy in SKOV3 cells. The PI3K-AKT-mTOR signaling pathway plays a significant role in various biological processes and serves as an effective focus for current cancer treatment [53, 54]. Relevant studies have demonstrated that inhibiting the PI3K/AKT/mTOR signalling pathway efficiently stimulates autophagy activation, triggers apoptosis, and impedes tumour growth and migration [55, 56].The PI3K family of lipid kinases primarily regulate cellular growth and modulate cellular autophagy [53, 57]. When PI3K binds to AKT, it triggers the transfer of AKT from the cytoplasm to the cytosol and leads to its phosphorylation [58]. mTOR, is a critical regulator of autophagy and lies downstream of the PI3K-AKT signaling pathway. It is commonly utilized in the negative regulation of autophagy [53, 58, 59]. Nevertheless, recent findings indicate that glycyrrhizin exerts anti-tumour proliferative effects by inhibiting the PI3K-AKT-mTOR signalling pathway, which in turn suppresses the expression of autophagy-related genes [53]. This is consistent with the results of our experiments, suggesting that UA impedes the progression of ovarian cancer cells by inhibiting autophagy in SKOV3 cells through the down-regulation of the PI3K-AKT-mTOR signalling pathway.

The endoplasmic reticulum plays an important role in the synthesis and folding of proteins [60,61,62,63,64]. However, when misfolded proteins accumulate excessively, it results in the unfolded protein response (UPR) [61, 62, 65, 66]. ERS plays an important regulatory role in tumour development [67]. The molecular chaperone-binding immunoglobulin (BiP) binds to protein kinase R (PKR)-like endoplasmic reticulum kinase (PERK, encoded by EIF2AK3), activating transcription factor 6 (ATF6, encoded by ATF6), and inositol-requiring enzyme 1 (IRE1α, encoded by ERN1) to render itself inactive [61, 65, 68, 69]. When the endoplasmic reticulum is stressed, BIP dissociates from PERK, ATF6 and IRE1α and binds to misfolded proteins [60, 61, 65, 68, 70]. Prolonged ERS can promote tumour apoptosis, immunogenic death and other negative outcomes [60, 61, 65, 68, 71]. It has been shown that activated PERK activates eIF2α, and promotes increased selective translation of ATF4, which activates the CHOP transcription factor. In addition, CHOP could reduce BCL-2 expression to promote apoptosis [60, 65, 72]. The expression of endoplasmic reticulum (ER)-related proteins, including PERK, eIF2α, and CHOP, was detected by Western blotting. The results revealed a considerable upregulation in the expression of PERK, eIF2α, and CHOP, signifying that UA treatment induced ERS in SKOV3 cells. The results of this study showed that UA promoted ERS and inhibited autophagy in SKOV3 cells and induced apoptosis in SKOV3 cells (Fig. 6).

Fig. 6
figure 6

Schematic illustration of how UA promotes endoplasmic reticulum stress, inhibits autophagy, and induces apoptosis (By Fig Draw)

Full size image

Conclusions

Our results indicate that UA can effectively induce ERS, which inhibits autophagy through the PI3K-AKT signaling pathway, ultimately promoting apoptosis in ovarian cancer cells thereby exerting its anti-cancer effect. It has been previously reported that ERS increases the expression of CHOP, which directly promotes apoptosis, and inhibites the PI3K/Akt pathway, subsequently reduces Beclin1 expression, autophagy and ultimately promotes apoptosis in ovarian cancer cells.UA, as a novel natural anticancer compound, has fewer side effects than cisplatin, making it a new type of drug for the treatment of ovarian cancer, and its mechanism of action includes induction of ERS, inhibition of autophagy and promotion of apoptosis, which provides a new idea and direction for the development of clinical antineoplastic therapy.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Berner K, Hirschfeld M, Weiß D, Rücker G, Asberger J, Ritter A, Nöthling C, Jäger M, Juhasz-Böss I, Erbes T. Evaluation of circulating microRNAs as non-invasive biomarkers in the diagnosis of ovarian cancer: a case-control study. Arch Gynecol Obstet. 2022;306(1):151–63.

    Article  CAS  PubMed  Google Scholar 

  2. Lheureux S, Braunstein M, Oza AM. Epithelial ovarian cancer: evolution of management in the era of precision medicine. CA Cancer J Clin. 2019;69(4):280–304.

    Article  PubMed  Google Scholar 

  3. Lambertini M, Del Mastro L, Pescio MC, Andersen CY, Azim HA Jr., Peccatori FA, Costa M, Revelli A, Salvagno F, Gennari A, et al. Cancer and fertility preservation: international recommendations from an expert meeting. BMC Med. 2016;14:1.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Castaño M, Tomás-Pérez S, González-Cantó E, Aghababyan C, Mascarós-Martínez A, Santonja N, Herreros-Pomares A, Oto J, Medina P, Götte M et al. Neutrophil Extracellular traps and Cancer: Trapping our attention with their involvement in Ovarian Cancer. Int J Mol Sci 2023, 24(6).

  5. Partridge EE, Barnes MN. Epithelial ovarian cancer: prevention, diagnosis, and treatment. CA Cancer J Clin. 1999;49(5):297–320.

    Article  CAS  PubMed  Google Scholar 

  6. McManus H, Moysich KB, Tang L, Joseph J, McCann SE. Usual Cruciferous Vegetable Consumption and Ovarian Cancer: a case-control study. Nutr Cancer. 2018;70(4):678–83.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Elias KM, Guo J, Bast RC Jr. Early detection of Ovarian Cancer. Hematol Oncol Clin North Am. 2018;32(6):903–14.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Camuzard O, Santucci-Darmanin S, Carle GF, Pierrefite-Carle V. Autophagy in the crosstalk between tumor and microenvironment. Cancer Lett. 2020;490:143–53.

    Article  CAS  PubMed  Google Scholar 

  9. Lheureux S, Gourley C, Vergote I, Oza AM. Epithelial ovarian cancer. Lancet. 2019;393(10177):1240–53.

    Article  PubMed  Google Scholar 

  10. Yang L, Xie HJ, Li YY, Wang X, Liu XX, Mai J. Molecular mechanisms of platinum–based chemotherapy resistance in ovarian cancer (review). Oncol Rep 2022, 47(4).

  11. Bafaloukos D, Linardou H, Aravantinos G, Papadimitriou C, Bamias A, Fountzilas G, Kalofonos HP, Kosmidis P, Timotheadou E, Makatsoris T, et al. A randomized phase II study of carboplatin plus pegylated liposomal doxorubicin versus carboplatin plus paclitaxel in platinum sensitive ovarian cancer patients: a Hellenic Cooperative Oncology Group study. BMC Med. 2010;8:3.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Kehoe S, Hook J, Nankivell M, Jayson GC, Kitchener H, Lopes T, Luesley D, Perren T, Bannoo S, Mascarenhas M, et al. Primary chemotherapy versus primary surgery for newly diagnosed advanced ovarian cancer (CHORUS): an open-label, randomised, controlled, non-inferiority trial. Lancet. 2015;386(9990):249–57.

    Article  PubMed  Google Scholar 

  13. Luo H, Vong CT, Chen H, Gao Y, Lyu P, Qiu L, Zhao M, Liu Q, Cheng Z, Zou J, et al. Naturally occurring anti-cancer compounds: shining from Chinese herbal medicine. Chin Med. 2019;14:48.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Qian Q, Chen W, Cao Y, Cao Q, Cui Y, Li Y, Wu J. Targeting Reactive Oxygen Species in Cancer via Chinese Herbal Medicine. Oxid Med Cell Longev 2019, 2019:9240426.

  15. Zhong Z, Yu H, Wang S, Wang Y, Cui L. Anti-cancer effects of Rhizoma Curcumae against doxorubicin-resistant breast cancer cells. Chin Med. 2018;13:44.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Luo Z, Wang Q, Lau WB, Lau B, Xu L, Zhao L, Yang H, Feng M, Xuan Y, Yang Y, et al. Tumor microenvironment: the culprit for ovarian cancer metastasis? Cancer Lett. 2016;377(2):174–82.

    Article  CAS  PubMed  Google Scholar 

  17. Yin R, Li T, Tian JX, Xi P, Liu RH. Ursolic acid, a potential anticancer compound for breast cancer therapy. Crit Rev Food Sci Nutr. 2018;58(4):568–74.

    Article  CAS  PubMed  Google Scholar 

  18. Lin JH, Chen SY, Lu CC, Lin JA, Yen GC. Ursolic acid promotes apoptosis, autophagy, and chemosensitivity in gemcitabine-resistant human pancreatic cancer cells. Phytother Res. 2020;34(8):2053–66.

    Article  CAS  PubMed  Google Scholar 

  19. Panda SS, Thangaraju M, Lokeshwar BL. Ursolic acid analogs as potential therapeutics for Cancer. Molecules 2022, 27(24).

  20. Zhang H, Xing Z, Zheng J, Shi J, Cui C. Ursolic acid ameliorates traumatic brain injury in mice by regulating microRNA-141-mediated PDCD4/PI3K/AKT signaling pathway. Int Immunopharmacol. 2023;120:110258.

    Article  CAS  PubMed  Google Scholar 

  21. Liao WL, Liu YF, Ying TH, Shieh JC, Hung YT, Lee HJ, Shen CY, Cheng CW. Inhibitory effects of Ursolic Acid on the stemness and progression of human breast Cancer cells by modulating Argonaute-2. Int J Mol Sci 2022, 24(1).

  22. Li H, Yu Y, Liu Y, Luo Z, Law BYK, Zheng Y, Huang X, Li W. Ursolic acid enhances the antitumor effects of sorafenib associated with mcl-1-related apoptosis and SLC7A11-dependent ferroptosis in human cancer. Pharmacol Res. 2022;182:106306.

    Article  CAS  PubMed  Google Scholar 

  23. Xu J, Gewirtz DA. Is autophagy always a barrier to cisplatin therapy? Biomol. 2022;12(3):463. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/biom12030463.

  24. Wong RS. Apoptosis in cancer: from pathogenesis to treatment. J Exp Clin Cancer Res. 2011;30(1):87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Su Z, Yang Z, Xu Y, Chen Y, Yu Q. Apoptosis, autophagy, necroptosis, and cancer metastasis. Mol Cancer. 2015;14:48.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Hou J, Zhang Y, Zhu Y, Zhou B, Ren C, Liang S, Guo Y. α-Pinene induces apoptotic cell death via caspase activation in human ovarian Cancer cells. Med Sci Monit. 2019;25:6631–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Müller D, Mazzeo P, Koch R, Bösherz MS, Welter S, von Hammerstein-Equord A, Hinterthaner M, Cordes L, Belharazem D, Marx A, et al. Functional apoptosis profiling identifies MCL-1 and BCL-xL as prognostic markers and therapeutic targets in advanced thymomas and thymic carcinomas. BMC Med. 2021;19(1):300.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Zhang L, Kong L, He SY, Liu XZ, Liu Y, Zang J, Ju RJ, Li XT. The anti-ovarian cancer effect of RPV modified paclitaxel plus schisandra B liposomes in SK-OV-3 cells and tumor-bearing mice. Life Sci. 2021;285:120013.

    Article  CAS  PubMed  Google Scholar 

  29. Hu H, Zhu S, Tong Y, Huang G, Tan B, Yang L. Antitumor activity of triptolide in SKOV3 cells and SKOV3/DDP in vivo and in vitro. Anticancer Drugs. 2020;31(5):483–91.

    Article  CAS  PubMed  Google Scholar 

  30. Yang H, Li H, Lu S, Shan S, Guo Y. Fuzheng Jiedu Decoction Induces Apoptosis and Enhances Cisplatin Efficacy in Ovarian Cancer Cells In Vitro and In Vivo through Inhibiting the PI3K/AKT/mTOR/NF-κB Signaling Pathway. BioMed research international 2022, 2022:5739909.

  31. Meng RY, Jin H, Nguyen TV, Chai OH, Park BH, Kim SM. Ursolic acid accelerates Paclitaxel-Induced Cell Death in Esophageal Cancer cells by suppressing Akt/FOXM1 Signaling Cascade. Int J Mol Sci 2021, 22(21).

  32. Zong L, Cheng G, Zhao J, Zhuang X, Zheng Z, Liu Z, Song F. Inhibitory effect of Ursolic Acid on the Migration and Invasion of Doxorubicin-resistant breast Cancer. Molecules 2022, 27(4).

  33. Liu Z, Ding Y, Ye N, Wild C, Chen H, Zhou J. Direct activation of Bax Protein for Cancer Therapy. Med Res Rev. 2016;36(2):313–41.

    Article  CAS  PubMed  Google Scholar 

  34. Carneiro BA, El-Deiry WS. Targeting apoptosis in cancer therapy. Nat Rev Clin Oncol. 2020;17(7):395–417.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Petroni G, Bagni G, Iorio J, Duranti C, Lottini T, Stefanini M, Kragol G, Becchetti A, Arcangeli A. Clarithromycin inhibits autophagy in colorectal cancer by regulating the hERG1 potassium channel interaction with PI3K. Cell Death Dis. 2020;11(3):161.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Rudnick JA, Monkkonen T, Mar FA, Barnes JM, Starobinets H, Goldsmith J, Roy S, Bustamante Eguiguren S, Weaver VM, Debnath J. Autophagy in stromal fibroblasts promotes tumor desmoplasia and mammary tumorigenesis. Genes Dev. 2021;35(13–14):963–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Khayati K, Bhatt V, Lan T, Alogaili F, Wang W, Lopez E, Hu ZS, Gokhale S, Cassidy L, Narita M, et al. Transient systemic autophagy inhibition is selectively and irreversibly deleterious to Lung Cancer. Cancer Res. 2022;82(23):4429–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Ren Y, Wang R, Weng S, Xu H, Zhang Y, Chen S, Liu S, Ba Y, Zhou Z, Luo P, et al. Multifaceted role of redox pattern in the tumor immune microenvironment regarding autophagy and apoptosis. Mol Cancer. 2023;22(1):130.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Poillet-Perez L, Xie X, Zhan L, Yang Y, Sharp DW, Hu ZS, Su X, Maganti A, Jiang C, Lu W, et al. Autophagy maintains tumour growth through circulating arginine. Nature. 2018;563(7732):569–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Fung C, Lock R, Gao S, Salas E, Debnath J. Induction of autophagy during extracellular matrix detachment promotes cell survival. Mol Biol Cell. 2008;19(3):797–806.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Khezri R, Holland P, Schoborg TA, Abramovich I, Takáts S, Dillard C, Jain A, O’Farrell F, Schultz SW, Hagopian WM, et al. Host autophagy mediates organ wasting and nutrient mobilization for tumor growth. Embo j. 2021;40(18):e107336.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Liu Y, Wang X, Zhu W, Sui Z, Wei X, Zhang Y, Qi J, Xing Y, Wang W. TRPML1-induced autophagy inhibition triggers mitochondrial mediated apoptosis. Cancer Lett. 2022;541:215752.

    Article  CAS  PubMed  Google Scholar 

  43. Li X, He S, Ma B. Autophagy and autophagy-related proteins in cancer. Mol Cancer. 2020;19(1):12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Katheder NS, Khezri R, O’Farrell F, Schultz SW, Jain A, Rahman MM, Schink KO, Theodossiou TA, Johansen T, Juhász G, et al. Microenvironmental autophagy promotes tumour growth. Nature. 2017;541(7637):417–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Cheng Y, Wang C, Wang H, Zhang Z, Yang X, Dong Y, Ma L, Luo J. Combination of an autophagy inhibitor with immunoadjuvants and an anti-PD-L1 antibody in multifunctional nanoparticles for enhanced breast cancer immunotherapy. BMC Med. 2022;20(1):411.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Sousa CM, Biancur DE, Wang X, Halbrook CJ, Sherman MH, Zhang L, Kremer D, Hwang RF, Witkiewicz AK, Ying H, et al. Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion. Nature. 2016;536(7617):479–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Li X, Yan J, Wang L, Xiao F, Yang Y, Guo X, Wang H. Beclin1 inhibition promotes autophagy and decreases gemcitabine-induced apoptosis in Miapaca2 pancreatic cancer cells. Cancer Cell Int. 2013;13(1):26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Li X, Su J, Xia M, Li H, Xu Y, Ma C, Ma L, Kang J, Yu H, Zhang Z, et al. Caspase-mediated cleavage of Beclin1 inhibits autophagy and promotes apoptosis induced by S1 in human ovarian cancer SKOV3 cells. Apoptosis. 2016;21(2):225–38.

    Article  CAS  PubMed  Google Scholar 

  49. Sutton MN, Huang GY, Liang X, Sharma R, Reger AS, Mao W, Pang L, Rask PJ, Lee K, Gray JP et al. DIRAS3-Derived peptide inhibits Autophagy in Ovarian Cancer cells by binding to Beclin1. Cancers (Basel) 2019, 11(4).

  50. El-Sherbeeny NA, Soliman N, Youssef AM, Abd El-Fadeal NM, El-Abaseri TB, Hashish AA, Abdelbasset WK, El-Saber Batiha G, Zaitone SA. The protective effect of biochanin A against rotenone-induced neurotoxicity in mice involves enhancing of PI3K/Akt/mTOR signaling and beclin-1 production. Ecotoxicol Environ Saf. 2020;205:111344.

    Article  CAS  PubMed  Google Scholar 

  51. Liang C, Feng Z, Manthari RK, Wang C, Han Y, Fu W, Wang J, Zhang J. Arsenic induces dysfunctional autophagy via dual regulation of mTOR pathway and Beclin1-Vps34/PI3K complex in MLTC-1 cells. J Hazard Mater. 2020;391:122227.

    Article  CAS  PubMed  Google Scholar 

  52. Liang J, Zhou J, Xu Y, Huang X, Wang X, Huang W, Li H. Osthole inhibits ovarian carcinoma cells through LC3-mediated autophagy and GSDME-dependent pyroptosis except for apoptosis. Eur J Pharmacol. 2020;874:172990.

    Article  CAS  PubMed  Google Scholar 

  53. Xu Z, Han X, Ou D, Liu T, Li Z, Jiang G, Liu J, Zhang J. Targeting PI3K/AKT/mTOR-mediated autophagy for tumor therapy. Appl Microbiol Biotechnol. 2020;104(2):575–87.

    Article  CAS  PubMed  Google Scholar 

  54. Kumar D, Shankar S, Srivastava RK. Rottlerin induces autophagy and apoptosis in prostate cancer stem cells via PI3K/Akt/mTOR signaling pathway. Cancer Lett. 2014;343(2):179–89.

    Article  CAS  PubMed  Google Scholar 

  55. Zhou J, Jiang YY, Chen H, Wu YC, Zhang L. Tanshinone I attenuates the malignant biological properties of ovarian cancer by inducing apoptosis and autophagy via the inactivation of PI3K/AKT/mTOR pathway. Cell Prolif. 2020;53(2):e12739.

    Article  PubMed  Google Scholar 

  56. Rong L, Li Z, Leng X, Li H, Ma Y, Chen Y, Song F. Salidroside induces apoptosis and protective autophagy in human gastric cancer AGS cells through the PI3K/Akt/mTOR pathway. Biomed Pharmacotherapy = Biomedecine Pharmacotherapie. 2020;122:109726.

    Article  CAS  PubMed  Google Scholar 

  57. Shrivastava S, Bhanja Chowdhury J, Steele R, Ray R, Ray RB. Hepatitis C virus upregulates Beclin1 for induction of autophagy and activates mTOR signaling. J Virol. 2012;86(16):8705–12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Yang CZ, Wang SH, Zhang RH, Lin JH, Tian YH, Yang YQ, Liu J, Ma YX. Neuroprotective effect of astragalin via activating PI3K/Akt-mTOR-mediated autophagy on APP/PS1 mice. Cell Death Discov. 2023;9(1):15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Zhao E, Feng L, Bai L, Cui H. NUCKS promotes cell proliferation and suppresses autophagy through the mTOR-Beclin1 pathway in gastric cancer. J Exp Clin Cancer Res. 2020;39(1):194.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Fernández A, Ordóñez R, Reiter RJ, González-Gallego J, Mauriz JL. Melatonin and endoplasmic reticulum stress: relation to autophagy and apoptosis. J Pineal Res. 2015;59(3):292–307.

    Article  PubMed  Google Scholar 

  61. Chen X, Cubillos-Ruiz JR. Endoplasmic reticulum stress signals in the tumour and its microenvironment. Nat Rev Cancer. 2021;21(2):71–88.

    Article  CAS  PubMed  Google Scholar 

  62. Lu L, Ladinsky MS, Kirchhausen T. Cisternal organization of the endoplasmic reticulum during mitosis. Mol Biol Cell. 2009;20(15):3471–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Marchi S, Patergnani S, Pinton P. The endoplasmic reticulum-mitochondria connection: one touch, multiple functions. Biochim Biophys Acta. 2014;1837(4):461–9.

    Article  CAS  PubMed  Google Scholar 

  64. Khaminets A, Heinrich T, Mari M, Grumati P, Huebner AK, Akutsu M, Liebmann L, Stolz A, Nietzsche S, Koch N, et al. Regulation of endoplasmic reticulum turnover by selective autophagy. Nature. 2015;522(7556):354–8.

    Article  CAS  PubMed  Google Scholar 

  65. Cubillos-Ruiz JR, Bettigole SE, Glimcher LH. Tumorigenic and immunosuppressive effects of endoplasmic reticulum stress in Cancer. Cell. 2017;168(4):692–706.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Fontana F, Moretti RM, Raimondi M, Marzagalli M, Beretta G, Procacci P, Sartori P, Montagnani Marelli M, Limonta P. δ-Tocotrienol induces apoptosis, involving endoplasmic reticulum stress and autophagy, and paraptosis in prostate cancer cells. Cell Prolif. 2019;52(3):e12576.

    Article  PubMed  PubMed Central  Google Scholar 

  67. París-Coderch L, Soriano A, Jiménez C, Erazo T, Muñoz-Guardiola P, Masanas M, Antonelli R, Boloix A, Alfón J, Pérez-Montoyo H, et al. The antitumour drug ABTL0812 impairs neuroblastoma growth through endoplasmic reticulum stress-mediated autophagy and apoptosis. Cell Death Dis. 2020;11(9):773.

    Article  PubMed  PubMed Central  Google Scholar 

  68. He L, Li H, Li C, Liu ZK, Lu M, Zhang RY, Wu D, Wei D, Shao J, Liu M, et al. HMMR alleviates endoplasmic reticulum stress by promoting autophagolysosomal activity during endoplasmic reticulum stress-driven hepatocellular carcinoma progression. Cancer Commun (Lond). 2023;43(9):981–1002.

    Article  PubMed  Google Scholar 

  69. Mohamed E, Sierra RA, Trillo-Tinoco J, Cao Y, Innamarato P, Payne KK, de Mingo Pulido A, Mandula J, Zhang S, Thevenot P, et al. The unfolded protein response Mediator PERK governs myeloid cell-driven immunosuppression in tumors through inhibition of STING Signaling. Immunity. 2020;52(4):668–e682667.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Barez SR, Atar AM, Aghaei M. Mechanism of inositol-requiring enzyme 1-alpha inhibition in endoplasmic reticulum stress and apoptosis in ovarian cancer cells. J Cell Commun Signal. 2020;14(4):403–15.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Xu D, Liu Z, Liang MX, Fei YJ, Zhang W, Wu Y, Tang JH. Endoplasmic reticulum stress targeted therapy for breast cancer. Cell Commun Signal. 2022;20(1):174.

    Article  PubMed  PubMed Central  Google Scholar 

  72. B’Chir W, Maurin AC, Carraro V, Averous J, Jousse C, Muranishi Y, Parry L, Stepien G, Fafournoux P, Bruhat A. The eIF2α/ATF4 pathway is essential for stress-induced autophagy gene expression. Nucleic Acids Res. 2013;41(16):7683–99.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to thank all participants in the study. And the author has obtained permission to publish the paper from all those mentioned in the Acknowledgments section.

.

Funding

This study was supported by the Science and Technology Project of Jilin Provincial Department of Finance (Project No. 20210401061YY) and the Program Project of Jilin Provincial Health and Family Planning Commission (Project No. 2022JC047).

Author information

Author notes

  1. Ru Zhang and Zhaopeng Zhang contributed equally to this work and share first authorship.

Authors and Affiliations

  1. School of Clinical Medicine, Changchun University of Traditional Chinese Medicine, Changchun, China

    Ru Zhang, Ziqing Yu, Rui Gao, Zhi-Run Zhang, Ying Zhang, Xuyang Wei, Yang Chen, Sue Jiao & Jun-Peng Guo

  2. School of Pharmacy, Changchun University of Traditional Chinese Medicine, Changchun, China

    Zhaopeng Zhang

  3. Affiliated Hospital, Changchun University of Traditional Chinese Medicine, Changchun, China

    Lulu Xie & Yiren Gao

Authors
  1. Ru Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Zhaopeng Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Lulu Xie
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Ziqing Yu
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Rui Gao
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Zhi-Run Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Ying Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Xuyang Wei
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Yang Chen
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Sue Jiao
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Yiren Gao
    View author publications

    You can also search for this author inPubMed Google Scholar

  12. Jun-Peng Guo
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

RZ, JOG, and ZPZ designed and supervised the completion of the research experiments. The experiments were performed by RZ and analyzed the data with LLX and ZQY. ZR and ZPZ wrote the manuscript, which was embellished by ZZP, GJP, and YRG. RZ drew all the figures.LLX and RG provided comments on the color scheme and layout of the figures. ZRZ, YZ, XYW, YC, and SEJ performed the information retrieval. All authors were involved in the experiments and the manuscript and approved the final version.

Corresponding authors

Correspondence to Yiren Gao or Jun-Peng Guo.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, R., Zhang, Z., Xie, L. et al. In vitro analysis of the molecular mechanisms of ursolic acid against ovarian cancer. BMC Complement Med Ther 25, 65 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12906-025-04808-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12906-025-04808-y

Keywords

BMC Complementary Medicine and Therapies

ISSN: 2662-7671

Contact us