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

In vitro analysis of the molecular mechanisms of ursolic acid against ovarian cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article In vitro analysis of the molecular mechanisms of ursolic acid against ovarian cancer Ru Zhang, Zhaopeng Zhang, Lulu Xie, Ziqing Yu, Rui Gao, Zhi-Run Zhang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3779770/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Ovarian cancer is a common gynaecologic malignancy that poses a serious threat to the health and lives of women.Ursolic acid (UA) is present in various fruits, and several experiments have demonstrated its ability to inhibit tumour growth. In this study, the Cell Counting Kit-8 (CCK-8) assay was used to investigate the anti-proliferative effect of UA on ovarian cancer. Additionally, we assessed the inhibitory effects of UA on the colony formation and migration abilities of ovarian cancer cells via colony formation and scratch assays, respectively. To elucidate the capacity of UA to promote apoptosis, we assessed its potential mechanism of inhibiting ovarian cancer cell proliferation using flow cytometry, TUNEL staining, and protein blotting. These findings suggest that UA can enhance endoplasmic reticulum stress (ERS), induce apoptosis, and suppress autophagy in ovarian cancer cells. This implies that UA exerts a significant anti-ovarian cancer effect by facilitating ERS in tumour cells and inhibiting autophagy. Ursolic acid Anti-ovarian cancer Endoplasmic reticulum stress Autophagy Apoptosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. 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 plasmacytoid, high-grade plasmacytoid, 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 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 – 8 ]. Currently, platinum- and paclitaxel-based chemotherapy and cytoreductive surgery are the primary clinical interventions for ovarian cancer[ 4 , 9 – 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 medicine, including Forsythia and Bupleurum, as well as other significant Chinese medicine sources. Interestingly, significant quantities of UA were discovered in apple peel[ 18 ]. UA has been extensively used in treating multiple cancers. Research has revealed that UA suppresses breast cancer cell proliferation by inactivating the PI3K/AKT(phosphatidylinositol 3' -kinase(PI3K)-Akt kinase) signalling pathway. Furthermore, its apoptosis-inducing and anti-inflammatory effects on breast cancer cells contribute to its anticancer properties[ 17 , 19 ]. 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 ]. 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 endoplasmic reticulum stress 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. 2. Results 2.1. Network pharmacological analysis The molecular formula for UA (Fig. 1 A) and its 55 potential targets were retrieved from the TCMSP database. Potential target proteins were converted into harmonized target genes by utilizing the UniProt database and integrated with the 11 targets obtained from the Stitch database. Duplicates were removed, leaving 64 potential targets. Using the Disgenet and GeneCards databases, we obtained 3,500 disease-related targets. Fifty-five intersecting target genes (Fig. 1 B) were obtained using a Venn diagram created via Venny. The targets in from the intersection were then imported into the STRING database to construct the PPI network (Fig. 1 C), which consisted of 55 nodes and 679 edges. Cytoscape 3.9.1 was utilized for the analysis and screening of core targets using the Hubba plug-in. Upon completion, the top ten core targets with degree values (Fig. 1 D) were obtained. The depth of the colour in the figure indicates the degree value, with deeper colours reflecting higher values and indicative of a close relationship with the therapeutic effect of UA. These findings suggest that these targets may be key for therapeutic intervention; further verification was performed in subsequent experiments. The DAVID website provides GO and KEGG pathway enrichment analysis for 55 overlapping targets to enhance the understanding of the biological processes and potential mechanisms of UA in treating ovarian cancer. GO enrichment analysis is used to reveal the enrichment of genes in 351 biological processes (BPs). For the identified targets, the main enriched BPs were positive regulation of apoptotic process, apoptotic process, negative regulation of apoptotic process, positive regulation of transcription from RNA polymerase II promoter, response to xenobiotic stimulus, etc. There were 38 enriched terms related to cellular components (CC), mainly including cytosol, nucleus, nucleoplasm, extracellular space, etc. There were 59 enriched terms related to molecular function (MF), mainly protein binding, identical protein binding, protein homodimerization activity enzyme binding, protein kinase binding, etc. (Fig. 1 E). The most enriched pathways among the 131 KEGG-enriched pathways were pathways in cancer, apoptosis, the PI3K-Akt signalling pathway, the TNF signalling pathway, and proteoglycans in cancer (Fig. 1 F). The network diagram for Compound-Disease-Intersecting Targets features orange hexagons to represent diseases, pink arrows for UA, and green rhombuses for intersecting targets. Additionally, inner circles with darker shades indicate higher degree values (Fig. 1 G). Based on GO and KEGG enrichment analyses, it was determined that apoptosis and the PI3K-Akt signalling pathway may play a prominent role in UA's effects on ovarian cancer. 2.2. Results of in vitro experiments 2.2.1. 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. The results indicated a dose-dependent decline in cell viability with increasing concentration and time compared to that in the control group (Fig. 2 A). 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 hours than at 12 hours, and the half-inhibitory concentration was measured to be 50 µmol/l; this dose was selected to be administered to SKOV3 cells for 24 hours 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. 2 B). 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. 2 C-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. 2.2.2. 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. 3 A). 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. 3 B). To further explore whether apoptosis induced by UA occurs through the BAX(BCL2-Associated X) pathway, we used Western blotting to measure the expression levels of BAX(BCL2-Associated X), BCL-2(B-cell lymphoma-2), and Caspase-3. The study findings indicate that the expression of the pro-apoptotic genes BAX and 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. 3 C-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 with BCL-2 and − 7.6 with BAX (Fig. 3 E-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. 2.2.3. 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(nucleoporin 62), and LC3(microtubule associated protein 1 light chain 3). 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 and AKT. The results showed that the expression of PI3K and AKT was decreased relative to that in the control group (Fig. 4 A-B). To further inhibit autophagy in SKOV3 cells treated with UA, we utilized fluorescence microscopy to analyse the expression of LC3. 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. 4 C-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. 2.2.4. Ursolic acid promotes endoplasmic reticulum stress 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(Protein kinase R (PKR)-like endoplasmic reticulum kinase), EIF2-a(Phosphorylation of eukaryotic initiation factor-2α), and CHOP(The C/EBP Homologous Protein) via Western blotting. The protein expression of PERK, EIF2-a, and CHOP was significantly higher in the 50 µmol/l group than in the control group (Fig. 5 A-B). To verify that ursolic acid induces endoplasmic reticulum stress in SKOV3 cells, CHOP expression was detected through immunofluorescence. The findings indicate that ursolic acid induces endoplasmic reticulum stress in SKOV3 cells in a dose-dependent manner (Fig. 5 C-D). This suggests that ursolic acid promotes apoptosis by inducing endoplasmic reticulum stress, subsequently inhibiting autophagy. 3. Materials and methods 3.1. 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. The data were consolidated, and repeated entries were eliminated to identify genes related to therapeutic targets for ovarian cancer. 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 targets that intersected were input into the STRING ( https://cn.string-db.org/ ) database. Homo sapiens was selected in the “organism” column, and the PPI network was constructed. The next step was to filter the top ten core targets using the Hubba plug-in in the JAVA software included in Cytoscape version 3.9.1. The relationships between UA and diseases, as well as their intersecting targets, were analysed using Cytoscape version 3.9.1. To identify the top ten targets in terms of degree, an analytical network was used. The intersecting target genes were input into The Database for Annotation, Visualization and Integrated Discovery (DAVID) (ncifcrf.gov) database, with the official gene symbol selected in the “select identifier” column, and enrichment analyses of the Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes (KEGG) signalling pathways were conducted. 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 PubChem database was used to capture the 3D configuration of UA. Subsequently, the SDF files were transformed into MOL format by utilizing Open Babel 2.3.2 software and then stored as the molecularly docked ligand molecular data. The protein ID for the core gene was obtained through UniProt, while the 3D structure of the selected target was obtained based on its ID in the PDB database. The structure was saved in PDB format and used as the receptor molecule for molecular docking. Afterwards, the receptor molecule data in PDB format were imported into PyMOL to remove small molecules and protein residues. The receptor data were imported into AutoDock Tools 1.5.7 software, the structure was hydrogenated, and the file was saved in Pdbqt format as the docked receptor. Then, the ligand data were opened and saved in Pdbqt format. Next, the active site for molecular docking was determined based on the ligand coordinates of the target protein, and the coordinates and size of the grid box were set according to the active pocket of the core targets. Molecular docking was conducted via AutoDock Vina and ultimately visualized with PyMOL. A fluorescence microscope (BX53, OLYMPUS) and CO2 incubator (BB150, Thermo Fisher Scientific) were used. The following instruments were used: SpectraMax Paradigm plate reader (Spectra Max M2e, Molecular Devices), BD Accuri C6 flow cytometer (BD Biosciences). 3.2. Reagents and Instruments SKOV3 Friendship Sponsor of School of Basic Medical Sciences, Jilin University. Ursolic acid was obtained from Shyuanye; RPMI 1640 medium and trypsin were obtained from Cytiva; foetal bovine serum was obtained from HyClone; penicillin, streptomycin, and TUNEL staining kits were obtained from Solarbio. Antibodies against Caspase-3, Bax, Bcl-2, Beclin1, P62, LC3, PI3K, AKT, PERK, eIF2-α, CHOP, β-actin and tubulin were obtained from Proteintech. 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. 3.3. Culture of ovarian cancer cell lines The frozen tube containing SKOV3 cells was thawed quickly by placing it in a 37°C water bath. The resulting cytosol was transferred to a centrifuge tube that contained the medium. After washing the frozen tube twice with medium, it was subjected to centrifugation at 2000 rpm for a duration of 5 minutes, followed by disposal of the supernatant. Next, 3 mL of medium was added and mixed thoroughly, and the cells were gently dispersed into a petri dish. 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. 3.4. 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 hours. Subsequently, 10 µL of CCK-8 solution was added to each well, followed by incubation for an additional 3 hours. A plate reader was utilized to determine the absorption at 450 nm based on the enzymatic reaction. Subsequently, the absorbance was used to plot the growth curve; the experiment was performed three times. The average value was determined. 3.5. Colony formation assay SKOV3 cells were plated at a density of 0.1x10 6 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 secured with a 4% paraformaldehyde solution for 20 minutes. 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. 3.6. Wound healing assays Cells from the logarithmic growth phase were harvested and seeded at a density of 1x10 6 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 hours 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. 3.7. 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 1x10 5 and incubated for 24 hours. 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 minutes at room temperature in the dark. Detection was performed on a flow cytometer. 3.8. TUNEL staining to detect apoptosis Cells were incubated on sheets designed for specific cell types for 24 hours. Afterwards, the cells were fixed with paraformaldehyde for 30 minutes, permeabilized using 0.2% Triton X-10 for 20 minutes, and then incubated for 1 hour 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. 3.9. Western blot analysis SKOV3 cells were treated for 24 hours. 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 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. 3.10. Immunofluorescence (IF) assay The cells were moved to crawler sheets specific to their cell type and then incubated. After a 30-minute fixation in 4% paraformaldehyde solution, they were permeabilized for 20 minutes using 0.2% Triton X-10. Next, the cells were blocked using 2% BCA for 30 minutes and left overnight at 4°C with a primary antibody. The following day, a fluorescent secondary antibody was incubated for 1 hour at room temperature in the dark. The cells were rinsed three times with prechilled PBS after each step. Then, the sheets were sealed using an anti-fading burst sealant that included DAPI and clear nail polish. The sections were then sealed and viewed under a fluorescence microscope. 3.11. 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. 4. 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 study's findings indicate that UA can inhibit the development of ovarian cancer by suppressing tumour cell proliferation, colony formation, and migration. Additionally, UA can enhance ovarian cancer cell apoptosis. The mechanism of action involves the promotion of tumour cell endoplasmic reticulum stress and the suppression of autophagy. These results suggest that UA holds potential as an antitumour agent. One effective mechanism for inducing tumour cell death is apoptosis, which can efficiently regulate cell number and proliferation by inducing cell membrane rupture, cell nucleus breakage, chromatin condensation, and DNA breakage [ 20 , 21 ]. Promotion of apoptosis is currently the prevailing method of targeted cancer therapy [ 22 , 23 ]. The colony formation assay indicated a decrease in colony numbers with an increase in the dose of UA. Additionally, the migration experiment demonstrated that UA inhibited the migration of ovarian cancer cells, and the results showed a dose-dependent effect in inhibiting the proliferation and migration of ovarian cancer cells. 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 [ 24 ] and inhibit the ERK signalling pathway to suppress cell adhesion and migration, thereby inhibiting the progression of breast cancer[ 25 ]. 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 [ 26 ]. Reducing Bcl-2 expression significantly increases the pro-apoptotic effects of drugs[ 27 ]. Furthermore, members of the caspase family of cysteine proteases are crucial in initiating and executing apoptosis[ 26 , 27 ]. 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, a metabolic process, can promote cellular homeostasis by self-phagocytosing aggregated proteins and damaged or dysfunctional organelles, which enables cellular metabolism and maintains cellular biosynthesis[ 28 – 31 ]. 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. As tumours advance, autophagy can supply the energy and metabolites necessary for tumour growth [ 8 , 32 – 34 ]. Autophagy transports intracellular substances to lysosomes for degradation, preserving energy for tumour cell survival and providing essential metabolites, including arginine and alanine, to facilitate tumour growth. Autophagy inhibition effectively promotes cell apoptosis.[ 35 – 38 ]. 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 induce pronounced apoptosis by impeding autophagic flow in SKOV3 cells. However, elevated autophagy levels were found in both cisplatin-resistant and cisplatin-sensitive tumour cells after cisplatin treatment, indicating that cisplatin is not an appropriate positive control for this experiment[ 39 ]. Numerous studies have demonstrated that Beclin1 is closely linked to tumour progression and plays a significant role in cellular proliferation[ 40 ]. Some studies have indicated that decreased autophagy can promote cell proliferation and lead to the onset of malignant tumours. However, considering the bidirectional regulation of autophagy, inhibiting autophagy may effectively decrease tumour proliferation and improve survival rates. The effectiveness of this approach has been validated in experiments on various cancers, such as pancreatic ductal carcinoma, breast cancer, and non-small cell lung cancer, and the level of autophagy is associated with the degree of malignancy and the features of the tumour environment[ 41 ]. Autophagy centres on the autophagy initiation protein Beclin1, which generates the autophagy initiation complex (AIC) to aid autophagy[ 42 , 43 ]. Beclin1 is part of the type III PI3 kinase complex, a crucial compound in forming autophagosomes and promoting autophagosome maturation. It generally interacts with BCL-2, which is pivotal for autophagosome maturation. This substance typically interacts with BCL-2, resulting in the inhibition of cellular autophagy[ 40 , 44 ]. In contrast, upregulation of Bax induces cytochrome C release, resulting in the cleavage of Beclin1 and inhibition of its autophagy induction effect. Moreover, UA exhibited a pro-apoptotic effect on ovarian cancer, as evidenced by the results of the experiments conducted. The protein content of P62, an autophagy marker, increased, indicating inhibition of autophagy by UA in SKOV3 cells. However, degradation of autophagosomes is a separate step from the formation of autophagosomes[ 45 ]. LC3 is considered the protein that firmly binds to the autophagosome membrane. Technical abbreviations will be explained when first used. There are two variants of LC3 (LC3-I and LC3-II): LC3-I is present in the cytoplasm, and LC3-II is bound to the membrane. LC3-I is converted to LC3-II and is capable of both initiating autophagosome formation and prolonging their existence[ 46 ]. LC3 expression in SKOV3 cells was detected after UA administration, and the results showed that LC3 expression was reduced, and the expression of LC3 was further reduced with increasing doses, suggesting that UA inhibits ovarian cancer progression by inhibiting autophagy-induced apoptosis in SKOV3 cells. The PI3K-AKT-mTOR signalling pathway plays a significant role in various biological processes and serves as an effective focus for current cancer treatment[ 47 , 48 ]. The PI3K family of lipid kinases primarily regulate cellular growth and modulate cellular autophagy and include three types: class I, class II, and class III PI3Ks[ 47 , 49 ]. AKT belongs to the serine/threonine kinase family; when PI3K binds to AKT, it triggers the transfer of AKT from the cytoplasm to the cytosol and leads to its phosphorylation[ 50 ]. mTOR, a serine/threonine kinase, is a critical regulator of autophagy and lies downstream of the PI3K-AKT signalling pathway. It is commonly utilized in the negative regulation of autophagy[ 47 , 50 , 51 ]. Numerous studies have demonstrated that inhibiting the PI3K/AKT/mTOR signalling pathway efficiently stimulates autophagy activation, triggers apoptosis, and impedes tumour growth and migration. However, recent studies have reported that glycyrrhizin can inhibit autophagy-related gene expression and exert an antitumour effect by inhibiting the PI3K-AKT-mTOR signalling pathway[ 47 ]. This is consistent with the results of our experiments, suggesting that UA inhibits autophagy, promotes apoptosis, and hinders ovarian cancer cell progression by downregulating the PI3K-AKT-mTOR signalling pathway. The endoplasmic reticulum, comprising pools, sheets, and linear tubules, is the largest organelle; it has a membranous, network structure and plays a role in the synthesis and folding of proteins[ 52 – 56 ]. Nevertheless, an excessive build-up of misfolded proteins beyond the threshold of endoplasmic reticulum processing is triggered by internal and external factors, leading to the unfolded protein response (UPR)[ 53 , 54 , 57 , 58 ]. Endoplasmic reticulum stress is a crucial aspect of tumour growth and development [ 59 ] and plays a significant regulatory function in both tumorigenesis and progression. The molecular chaperone-binding immunoglobulin (BiP) typically ensures protein folding, refolding, and degradation and is a key component of this process. Also known as GRP78, this protein binds to three sensors: 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). These three sensors bind to the endoplasmic reticulum, rendering themselves in a monomeric, inactive state [ 53 , 57 , 60 , 61 ]. When the endoplasmic reticulum undergoes stress, BIP dissociates from PERK, ATF6, and IRE1α and binds to misfolded or unfolded proteins due to its higher binding affinity. This enhances the folding ability of the endoplasmic reticulum, according to sources [ 52 , 53 , 57 , 60 , 62 ]. Mild, stimulus-induced endoplasmic reticulum stress can enhance protein folding ability and promote adaptive transformation and malignant development of tumour cells. However, prolonged and severe endoplasmic reticulum stress has a toxic effect on tumour cells and can promote apoptosis, immunogenic death, and other negative outcomes[ 52 , 53 , 57 , 60 , 63 ]. Recently, it was discovered that PERK self-phosphorylates and forms dimers upon dissociation from BIP. The activated PERK can then activate the eIF2α translation initiation factor and stimulate its phosphorylation, which limits protein translation and contributes to an increase in selective ATF4 translation. This subsequently induces the activation of the CHOP transcription factor. While PERK-mediated phosphorylation of eIF2α is necessary for autophagy to take place and progress, PERK can also stimulate the expression of autophagy-related genes. Additionally, CHOP causes growth arrest by increasing the expression of genes involved in autophagosome formation, and it promotes apoptosis by reducing BCL-2 expression [ 52 , 57 , 64 ]. 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 ER stress in SKOV3 cells. Recent experiments have shown that antitumour treatments can increase eIF2α phosphorylation in tumour cells, resulting in antitumour effects. Additionally, endoplasmic reticulum stress activators can upregulate endoplasmic reticulum stress via the PERK/AKT/mTOR signalling pathway. Induction of autophagy in tumour cells and inhibition of tumour progression are well-known therapeutic strategies [ 65 ]. However, the results of this study demonstrate that treatment with UA promotes endoplasmic reticulum stress in SKOV3 cells and inhibits SKOV3 cell autophagy, which contradicts previous research(Fig. 6 ). 5. Conclusions The experiments confirmed that treatment with UA induced endoplasmic reticulum stress, inhibited autophagy, and ultimately led to apoptosis in ovarian cancer cells, impeding tumour progression. However, the present study lacks reverse validation of the link between endoplasmic reticulum stress, autophagy, and apoptosis, and only one ovarian cancer cell line was utilized, so more experiments are needed for validation and for the development of new therapeutic options for clinical treatment. Declarations Availability of data and materials The datasets generated during an analysed during the current study are available in the persistent links to datasets. 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). Competing interests The authors declare that they have no competing interests. Ethics approval and consent to participate Not applicable Consent for publication Not applicable. Authors' 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. Acknowledgments 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. References Berner K, Hirschfeld M, Weiß D, Rücker G, Asberger J, et al. 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. 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. Lambertini M, Del Mastro L, Pescio MC, Andersen CY, Azim HA, editors. Jr. : Cancer and fertility preservation: international recommendations from an expert meeting. BMC Med 2016, 14:1. Castaño M, Tomás-Pérez S, González-Cantó E, Aghababyan C, Mascarós-Martínez A et al. Neutrophil Extracellular Traps and Cancer: Trapping Our Attention with Their Involvement in Ovarian Cancer. Int J Mol Sci 2023, 24(6). Partridge EE, Barnes MN. Epithelial ovarian cancer: prevention, diagnosis, and treatment. CA Cancer J Clin. 1999;49(5):297–320. 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. Elias KM, Guo J, Bast RC Jr.. Early Detection of Ovarian Cancer. Hematol Oncol Clin North Am. 2018;32(6):903–14. Camuzard O, Santucci-Darmanin S, Carle GF, Pierrefite-Carle V. Autophagy in the crosstalk between tumor and microenvironment. Cancer Lett. 2020;490:143–53. Lheureux S, Gourley C, Vergote I, Oza AM. Epithelial ovarian cancer. Lancet. 2019;393(10177):1240–53. Yang L, Xie HJ, Li YY, Wang X, Liu XX et al. Molecular mechanisms of platinum–based chemotherapy resistance in ovarian cancer (Review). Oncol Rep 2022, 47(4). Bafaloukos D, Linardou H, Aravantinos G, Papadimitriou C, Bamias A, 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. Kehoe S, Hook J, Nankivell M, Jayson GC, Kitchener H, 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. Luo H, Vong CT, Chen H, Gao Y, Lyu P, et al. Naturally occurring anti-cancer compounds: shining from Chinese herbal medicine. Chin Med. 2019;14:48. Qian Q, Chen W, Cao Y, Cao Q, Cui Y et al. Targeting Reactive Oxygen Species in Cancer via Chinese Herbal Medicine. Oxid Med Cell Longev 2019, 2019:9240426. 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. Luo Z, Wang Q, Lau WB, Lau B, Xu L, et al. Tumor microenvironment: The culprit for ovarian cancer metastasis? Cancer Lett. 2016;377(2):174–82. 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. 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. Liao WL, Liu YF, Ying TH, Shieh JC, Hung YT et al. 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). Wong RS. Apoptosis in cancer: from pathogenesis to treatment. J Exp Clin Cancer Res. 2011;30(1):87. Su Z, Yang Z, Xu Y, Chen Y, Yu Q. Apoptosis, autophagy, necroptosis, and cancer metastasis. Mol Cancer. 2015;14:48. Hou J, Zhang Y, Zhu Y, Zhou B, Ren C, et al. α-Pinene Induces Apoptotic Cell Death via Caspase Activation in Human Ovarian Cancer Cells. Med Sci Monit. 2019;25:6631–8. Müller D, Mazzeo P, Koch R, Bösherz MS, Welter S, 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. Meng RY, Jin H, Nguyen TV, Chai OH, Park BH et al. Ursolic Acid Accelerates Paclitaxel-Induced Cell Death in Esophageal Cancer Cells by Suppressing Akt/FOXM1 Signaling Cascade. Int J Mol Sci 2021, 22(21). Zong L, Cheng G, Zhao J, Zhuang X, Zheng Z et al. Inhibitory Effect of Ursolic Acid on the Migration and Invasion of Doxorubicin-Resistant Breast Cancer. Molecules 2022, 27(4). Liu Z, Ding Y, Ye N, Wild C, Chen H, et al. Direct Activation of Bax Protein for Cancer Therapy. Med Res Rev. 2016;36(2):313–41. Carneiro BA, El-Deiry WS. Targeting apoptosis in cancer therapy. Nat Rev Clin Oncol. 2020;17(7):395–417. Petroni G, Bagni G, Iorio J, Duranti C, Lottini T, et al. Clarithromycin inhibits autophagy in colorectal cancer by regulating the hERG1 potassium channel interaction with PI3K. Cell Death Dis. 2020;11(3):161. Rudnick JA, Monkkonen T, Mar FA, Barnes JM, Starobinets H, et al. Autophagy in stromal fibroblasts promotes tumor desmoplasia and mammary tumorigenesis. Genes Dev. 2021;35(13–14):963–75. Khayati K, Bhatt V, Lan T, Alogaili F, Wang W, et al. Transient Systemic Autophagy Inhibition Is Selectively and Irreversibly Deleterious to Lung Cancer. Cancer Res. 2022;82(23):4429–43. Ren Y, Wang R, Weng S, Xu H, Zhang Y, et al. Multifaceted role of redox pattern in the tumor immune microenvironment regarding autophagy and apoptosis. Mol Cancer. 2023;22(1):130. Li X, He S, Ma B. Autophagy and autophagy-related proteins in cancer. Mol Cancer. 2020;19(1):12. Katheder NS, Khezri R, O'Farrell F, Schultz SW, Jain A, et al. Microenvironmental autophagy promotes tumour growth. Nature. 2017;541(7637):417–20. Cheng Y, Wang C, Wang H, Zhang Z, Yang X, et al. 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. Poillet-Perez L, Xie X, Zhan L, Yang Y, Sharp DW, et al. Autophagy maintains tumour growth through circulating arginine. Nature. 2018;563(7732):569–73. 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. Khezri R, Holland P, Schoborg TA, Abramovich I, Takáts S, et al. Host autophagy mediates organ wasting and nutrient mobilization for tumor growth. Embo j. 2021;40(18):e107336. Liu Y, Wang X, Zhu W, Sui Z, Wei X, et al. TRPML1-induced autophagy inhibition triggers mitochondrial mediated apoptosis. Cancer Lett. 2022;541:215752. Xu J, Gewirtz DA. Is Autophagy Always a Barrier to Cisplatin Therapy? Biomolecules 2022, 12(3). Li X, Yan J, Wang L, Xiao F, Yang Y, et al. Beclin1 inhibition promotes autophagy and decreases gemcitabine-induced apoptosis in Miapaca2 pancreatic cancer cells. Cancer Cell Int. 2013;13(1):26. Sousa CM, Biancur DE, Wang X, Halbrook CJ, Sherman MH, et al. Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion. Nature. 2016;536(7617):479–83. Li X, Su J, Xia M, Li H, Xu Y, 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. Sutton MN, Huang GY, Liang X, Sharma R, Reger AS et al. DIRAS3-Derived Peptide Inhibits Autophagy in Ovarian Cancer Cells by Binding to Beclin1. Cancers (Basel) 2019, 11(4). El-Sherbeeny NA, Soliman N, Youssef AM, Abd El-Fadeal NM, El-Abaseri TB, et al. 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. Liang C, Feng Z, Manthari RK, Wang C, Han Y, et al. 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. Liang J, Zhou J, Xu Y, Huang X, Wang X, et al. Osthole inhibits ovarian carcinoma cells through LC3-mediated autophagy and GSDME-dependent pyroptosis except for apoptosis. Eur J Pharmacol. 2020;874:172990. Xu Z, Han X, Ou D, Liu T, Li Z, et al. Targeting PI3K/AKT/mTOR-mediated autophagy for tumor therapy. Appl Microbiol Biotechnol. 2020;104(2):575–87. 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. 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. Yang CZ, Wang SH, Zhang RH, Lin JH, Tian YH, et al. Neuroprotective effect of astragalin via activating PI3K/Akt-mTOR-mediated autophagy on APP/PS1 mice. Cell Death Discov. 2023;9(1):15. 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. 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. Chen X, Cubillos-Ruiz JR. Endoplasmic reticulum stress signals in the tumour and its microenvironment. Nat Rev Cancer. 2021;21(2):71–88. Lu L, Ladinsky MS, Kirchhausen T. Cisternal organization of the endoplasmic reticulum during mitosis. Mol Biol Cell. 2009;20(15):3471–80. Marchi S, Patergnani S, Pinton P. The endoplasmic reticulum-mitochondria connection: one touch, multiple functions. Biochim Biophys Acta. 2014;1837(4):461–9. Khaminets A, Heinrich T, Mari M, Grumati P, Huebner AK, et al. Regulation of endoplasmic reticulum turnover by selective autophagy. Nature. 2015;522(7556):354–8. Cubillos-Ruiz JR, Bettigole SE, Glimcher LH. Tumorigenic and Immunosuppressive Effects of Endoplasmic Reticulum Stress in Cancer. Cell. 2017;168(4):692–706. Fontana F, Moretti RM, Raimondi M, Marzagalli M, Beretta G, et al. δ-Tocotrienol induces apoptosis, involving endoplasmic reticulum stress and autophagy, and paraptosis in prostate cancer cells. Cell Prolif. 2019;52(3):e12576. París-Coderch L, Soriano A, Jiménez C, Erazo T, Muñoz-Guardiola P, et al. The antitumour drug ABTL0812 impairs neuroblastoma growth through endoplasmic reticulum stress-mediated autophagy and apoptosis. Cell Death Dis. 2020;11(9):773. He L, Li H, Li C, Liu ZK, Lu 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. Mohamed E, Sierra RA, Trillo-Tinoco J, Cao Y, Innamarato 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):668–682e667. 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. Xu D, Liu Z, Liang MX, Fei YJ, Zhang W, et al. Endoplasmic reticulum stress targeted therapy for breast cancer. Cell Commun Signal. 2022;20(1):174. B'Chir W, Maurin AC, Carraro V, Averous J, Jousse C, et al. The eIF2α/ATF4 pathway is essential for stress-induced autophagy gene expression. Nucleic Acids Res. 2013;41(16):7683–99. Xu F, Li X, Huang X, Pan J, Wang Y, et al. Development of a pH-responsive polymersome inducing endoplasmic reticulum stress and autophagy blockade. Sci Adv. 2020;6(31):eabb8725. Additional Declarations No competing interests reported. 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04:29:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3779770/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3779770/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49866601,"identity":"cca18f52-1c3e-4aac-a46e-3b19bc4cb63f","added_by":"auto","created_at":"2024-01-19 10:36:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1917692,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork pharmacology predicted the potential target of ursolic acid in ovarian cancer. \u003cstrong\u003e(A)\u003c/strong\u003e Chemical structure of ursolic acid (by ChemDraw). \u003cstrong\u003e(B)\u003c/strong\u003eVenn diagram of UA and OC, with 55 overlapping targets. \u003cstrong\u003e(C)\u003c/strong\u003e The STRING database was used to construct the PPI network of overlapping targets. \u003cstrong\u003e(D) \u003c/strong\u003eThe Hubba plugin shows the top ten targets in terms of degree values. \u003cstrong\u003e(E)\u003c/strong\u003e 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 \u0026lt; 0.01). \u003cstrong\u003e(F) \u003c/strong\u003eKEGG 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. \u003cstrong\u003e(G)\u003c/strong\u003eConstruction 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.\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3779770/v1/5f35a53349abd4acda9a9324.png"},{"id":49866855,"identity":"1acdb2f0-e04b-4af6-b699-a445d414a805","added_by":"auto","created_at":"2024-01-19 10:44:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4870526,"visible":true,"origin":"","legend":"\u003cp\u003eUrsolic acid inhibits the proliferation, migration, and colony formation of ovarian cancer (SKOV3) cells. \u003cstrong\u003e(A) \u003c/strong\u003eA CCK-8 assay was used to analyse the viability of SKOV3 cells cultured with UA. \u003cstrong\u003e(B)\u003c/strong\u003e The colony forming ability of SKOV3 cells was evaluated through a colony formation assay. \u003cstrong\u003e(C) \u003c/strong\u003eCell migration ability was measured by wound healing assay in SKOV3 cells (100× magnification).\u003cstrong\u003e (D)\u003c/strong\u003e The migration rate of SKOV3 cells was measured using ImageJ software. The experiments were repeated three times. Compared to the control group, *p \u0026lt; 0.05, **p \u0026lt; 0.01; compared to the cisplatin group, #p \u0026lt; 0.05, ##p \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3779770/v1/3c7faad6428caa95f520fb79.png"},{"id":49866856,"identity":"c5ee15e1-a461-41b3-a88f-0c1003c38b47","added_by":"auto","created_at":"2024-01-19 10:44:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3473943,"visible":true,"origin":"","legend":"\u003cp\u003eUrsolic acid promotes apoptosis in SKOV3 cells.\u003cstrong\u003e \u003c/strong\u003eUrsolic acid (50 μmol/L, 100 μmol/L) was used to treat SKOV3 cells for 24 hours.\u003cstrong\u003e (A)\u003c/strong\u003e The cell apoptosis rate of transfected cells was determined by flow cytometry.\u003cstrong\u003e(B) \u003c/strong\u003eEvaluation 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.\u003cstrong\u003e (C)\u003c/strong\u003e The protein expression of Bax, Bcl-2, and 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.\u003cstrong\u003e (D)\u003c/strong\u003e The band densities were measured using ImageJ software to quantify the bands. The average was calculated from three independent experiments.\u003cstrong\u003e (E-F)\u003c/strong\u003eMolecular docking formula of Bax and Bcl-2. Compared to the control group, *p \u0026lt; 0.05, **p \u0026lt; 0.01; compared to the cisplatin group, #p \u0026lt; 0.05, ##p \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3779770/v1/937f4ab48009e9b74f353f43.png"},{"id":49866604,"identity":"19d1f001-c352-4d4c-863f-0178468277e0","added_by":"auto","created_at":"2024-01-19 10:36:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":4337516,"visible":true,"origin":"","legend":"\u003cp\u003eUrsolic acid inhibits autophagy in SKOV3 cells. \u003cstrong\u003e(A)\u003c/strong\u003e PI3K, AKT, Beclin1, P62 and LC3 were measured by Western blotting. β-Actin served as a loading control. All experiments were repeated three times. \u003cstrong\u003e(B) \u003c/strong\u003eThe band densities were measured using ImageJ software to quantify the bands. \u003cstrong\u003e(C-D)\u003c/strong\u003eImmunofluorescence 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 \u0026lt; 0.05, **p \u0026lt; 0.01; compared to the cisplatin group, #p \u0026lt; 0.05, ##p \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3779770/v1/2dee074974f6dba6e3d2e089.png"},{"id":49866603,"identity":"5bb17f42-ce01-4c8c-9c75-c31811780e33","added_by":"auto","created_at":"2024-01-19 10:36:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3846212,"visible":true,"origin":"","legend":"\u003cp\u003eUrsolic acid inhibits autophagy in SKOV3 cells by promoting ER stress. \u003cstrong\u003e(A-B)\u003c/strong\u003eCHOP, eIF2-α, and PERK expression levels were assessed by Western blotting and quantitative measurement. Tubulin() served as a loading control.\u003cstrong\u003e (C-D)\u003c/strong\u003eImmunofluorescence 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 \u0026lt; 0.05, **p \u0026lt; 0.01; compared to the cisplatin group, #p \u0026lt; 0.05, ##p \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-3779770/v1/147ab2e78d9ed903f7b5a9d7.png"},{"id":49866606,"identity":"308ead76-6ed9-4a37-ace7-d8dde07d93af","added_by":"auto","created_at":"2024-01-19 10:36:18","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":293608,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic illustration of how UA promotes endoplasmic reticulum stress, inhibits autophagy, and induces apoptosis (By Fig Draw).\u003c/p\u003e","description":"","filename":"figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-3779770/v1/883248cf24588c4460080985.png"},{"id":49867710,"identity":"21cef7bf-e1a8-40b3-9360-529325374255","added_by":"auto","created_at":"2024-01-19 10:52:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3516645,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3779770/v1/00f87985-8212-401f-b58d-1a91e0121026.pdf"},{"id":49866608,"identity":"40ea300d-6168-427b-9dfc-c2a92dacfcfb","added_by":"auto","created_at":"2024-01-19 10:36:21","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":35261217,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-3779770/v1/3d2c85d843a35bd9570438a5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"In vitro analysis of the molecular mechanisms of ursolic acid against ovarian cancer","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eOvarian cancer is among the seven most pervasive malignancies worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] and ranks as the second most common cause of death among gynaecological tumours [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. 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 plasmacytoid, high-grade plasmacytoid, endometrioid, mucinous, and clear cell type[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Both age and genetic predisposition are recognized risk factors for ovarian cancer[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The American Cancer Society estimated over 20,000 newly confirmed cases of ovarian cancer and approximately 13,770 patient fatalities in 2021[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Due to 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%[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Currently, platinum- and paclitaxel-based chemotherapy and cytoreductive surgery are the primary clinical interventions for ovarian cancer[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Unfortunately, residual tumour cells remain after surgery for many patients, and this phenomenon is associated with lower survival rates[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Recurrence is often attributed to chemotherapy resistance[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. 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 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. These drugs can mitigate adverse effects, enhance prognosis, and extend patient survival [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. By directly or indirectly influencing cancer immunity and the tumour microenvironment and inducing apoptosis, drugs can induce anticancer effects[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. 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[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It is present in traditional Chinese medicine, including Forsythia and Bupleurum, as well as other significant Chinese medicine sources. Interestingly, significant quantities of UA were discovered in apple peel[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. UA has been extensively used in treating multiple cancers. Research has revealed that UA suppresses breast cancer cell proliferation by inactivating the PI3K/AKT(phosphatidylinositol 3' -kinase(PI3K)-Akt kinase) signalling pathway. Furthermore, its apoptosis-inducing and anti-inflammatory effects on breast cancer cells contribute to its anticancer properties[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. 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[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. 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[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. UA has not been extensively investigated as a treatment for ovarian cancer.\u003c/p\u003e \u003cp\u003eThe 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 endoplasmic reticulum stress 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.\u003c/p\u003e"},{"header":"2. Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Network pharmacological analysis\u003c/h2\u003e \u003cp\u003eThe molecular formula for UA (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) and its 55 potential targets were retrieved from the TCMSP database. Potential target proteins were converted into harmonized target genes by utilizing the UniProt database and integrated with the 11 targets obtained from the Stitch database. Duplicates were removed, leaving 64 potential targets. Using the Disgenet and GeneCards databases, we obtained 3,500 disease-related targets. Fifty-five intersecting target genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) were obtained using a Venn diagram created via Venny. The targets in from the intersection were then imported into the STRING database to construct the PPI network (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), which consisted of 55 nodes and 679 edges. Cytoscape 3.9.1 was utilized for the analysis and screening of core targets using the Hubba plug-in. Upon completion, the top ten core targets with degree values (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) were obtained. The depth of the colour in the figure indicates the degree value, with deeper colours reflecting higher values and indicative of a close relationship with the therapeutic effect of UA. These findings suggest that these targets may be key for therapeutic intervention; further verification was performed in subsequent experiments. The DAVID website provides GO and KEGG pathway enrichment analysis for 55 overlapping targets to enhance the understanding of the biological processes and potential mechanisms of UA in treating ovarian cancer. GO enrichment analysis is used to reveal the enrichment of genes in 351 biological processes (BPs). For the identified targets, the main enriched BPs were positive regulation of apoptotic process, apoptotic process, negative regulation of apoptotic process, positive regulation of transcription from RNA polymerase II promoter, response to xenobiotic stimulus, etc. There were 38 enriched terms related to cellular components (CC), mainly including cytosol, nucleus, nucleoplasm, extracellular space, etc. There were 59 enriched terms related to molecular function (MF), mainly protein binding, identical protein binding, protein homodimerization activity enzyme binding, protein kinase binding, etc. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). The most enriched pathways among the 131 KEGG-enriched pathways were pathways in cancer, apoptosis, the PI3K-Akt signalling pathway, the TNF signalling pathway, and proteoglycans in cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). The network diagram for Compound-Disease-Intersecting Targets features orange hexagons to represent diseases, pink arrows for UA, and green rhombuses for intersecting targets. Additionally, inner circles with darker shades indicate higher degree values (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG). Based on GO and KEGG enrichment analyses, it was determined that apoptosis and the PI3K-Akt signalling pathway may play a prominent role in UA's effects on ovarian cancer.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Results of in vitro experiments\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Ursolic acid inhibits SKOV3 cell proliferation, colony formation, and migration\u003c/h2\u003e \u003cp\u003eThe 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. The results indicated a dose-dependent decline in cell viability with increasing concentration and time compared to that in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). 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 hours than at 12 hours, and the half-inhibitory concentration was measured to be 50 \u0026micro;mol/l; this dose was selected to be administered to SKOV3 cells for 24 hours 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.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). 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 \u0026micro;mol/l group, while 100 \u0026micro;mol/l UA and cisplatin effectively eliminated SKOV3 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC-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.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Ursolic acid promotes SKOV3 cell apoptosis\u003c/h2\u003e \u003cp\u003eFlow 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.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). 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.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). To further explore whether apoptosis induced by UA occurs through the BAX(BCL2-Associated X) pathway, we used Western blotting to measure the expression levels of BAX(BCL2-Associated X), BCL-2(B-cell lymphoma-2), and Caspase-3. The study findings indicate that the expression of the pro-apoptotic genes BAX and 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.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-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 with BCL-2 and \u0026minus;\u0026thinsp;7.6 with BAX (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-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.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Ursolic acid inhibits autophagy in SKOV3 cells via the Beclin 1 signalling pathway\u003c/h2\u003e \u003cp\u003eTo investigate the inhibitory effect of UA on cellular autophagy, we utilized Western blotting to detect the protein expression of Beclin1, P62(nucleoporin 62), and LC3(microtubule associated protein 1 light chain 3). 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 and AKT. The results showed that the expression of PI3K and AKT was decreased relative to that in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B). To further inhibit autophagy in SKOV3 cells treated with UA, we utilized fluorescence microscopy to analyse the expression of LC3. Blue fluorescence indicates DAPI-stained nuclei, while green fluorescence indicates LC3 expression. The data indicate that the 50 \u0026micro;mol/l group exhibited less fluorescence expression than the control group in a dose-dependent fashion (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-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.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4. Ursolic acid promotes endoplasmic reticulum stress in SKOV3 cells\u003c/h2\u003e \u003cp\u003eTo further study the mechanism of action of UA on SKOV3 cells, we detected the protein expression of the endoplasmic reticulum-associated proteins PERK(Protein kinase R (PKR)-like endoplasmic reticulum kinase), EIF2-a(Phosphorylation of eukaryotic initiation factor-2α), and CHOP(The C/EBP Homologous Protein) via Western blotting. The protein expression of PERK, EIF2-a, and CHOP was significantly higher in the 50 \u0026micro;mol/l group than in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B). To verify that ursolic acid induces endoplasmic reticulum stress in SKOV3 cells, CHOP expression was detected through immunofluorescence. The findings indicate that ursolic acid induces endoplasmic reticulum stress in SKOV3 cells in a dose-dependent manner (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC-D). This suggests that ursolic acid promotes apoptosis by inducing endoplasmic reticulum stress, subsequently inhibiting autophagy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Materials and methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Network pharmacology predicts target genes\u003c/h2\u003e \u003cp\u003eTarget proteins associated with UA were obtained from the TCMSP (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://old.tcmsp-e.com/tcmsp.php\u003c/span\u003e\u003cspan address=\"https://old.tcmsp-e.com/tcmsp.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and STITCH (STITCH: chemical association networks (embl.de)) databases. The proteins generated were subsequently transformed into target genes utilizing UniProt (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.uniprot.org/\u003c/span\u003e\u003cspan address=\"https://www.uniprot.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). A gene search using the keywords \"ovarian cancer\" was conducted on the DisGenet (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.disgenet.org/home/\u003c/span\u003e\u003cspan address=\"https://www.disgenet.org/home/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and GeneCards (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genecards.org/\u003c/span\u003e\u003cspan address=\"https://www.genecards.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) databases. The data were consolidated, and repeated entries were eliminated to identify genes related to therapeutic targets for ovarian cancer. A Venn diagram was created utilizing the online tool Venny (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinfogp.cnb.csic.es/tools/venny/index.html\u003c/span\u003e\u003cspan address=\"https://bioinfogp.cnb.csic.es/tools/venny/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to identify common targets of UA and ovarian cancer. The targets that intersected were input into the STRING (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cn.string-db.org/\u003c/span\u003e\u003cspan address=\"https://cn.string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) database. \u003cem\u003eHomo sapiens\u003c/em\u003e was selected in the \u0026ldquo;organism\u0026rdquo; column, and the PPI network was constructed. The next step was to filter the top ten core targets using the Hubba plug-in in the JAVA software included in Cytoscape version 3.9.1. The relationships between UA and diseases, as well as their intersecting targets, were analysed using Cytoscape version 3.9.1. To identify the top ten targets in terms of degree, an analytical network was used. The intersecting target genes were input into The Database for Annotation, Visualization and Integrated Discovery (DAVID) (ncifcrf.gov) database, with the official gene symbol selected in the \u0026ldquo;select identifier\u0026rdquo; column, and enrichment analyses of the Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes (KEGG) signalling pathways were conducted. 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 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.com.cn/\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.com.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The PubChem database was used to capture the 3D configuration of UA. Subsequently, the SDF files were transformed into MOL format by utilizing Open Babel 2.3.2 software and then stored as the molecularly docked ligand molecular data. The protein ID for the core gene was obtained through UniProt, while the 3D structure of the selected target was obtained based on its ID in the PDB database. The structure was saved in PDB format and used as the receptor molecule for molecular docking. Afterwards, the receptor molecule data in PDB format were imported into PyMOL to remove small molecules and protein residues. The receptor data were imported into AutoDock Tools 1.5.7 software, the structure was hydrogenated, and the file was saved in Pdbqt format as the docked receptor. Then, the ligand data were opened and saved in Pdbqt format. Next, the active site for molecular docking was determined based on the ligand coordinates of the target protein, and the coordinates and size of the grid box were set according to the active pocket of the core targets. Molecular docking was conducted via AutoDock Vina and ultimately visualized with PyMOL. A fluorescence microscope (BX53, OLYMPUS) and CO2 incubator (BB150, Thermo Fisher Scientific) were used. The following instruments were used: SpectraMax Paradigm plate reader (Spectra Max M2e, Molecular Devices), BD Accuri C6 flow cytometer (BD Biosciences).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Reagents and Instruments\u003c/h2\u003e \u003cp\u003eSKOV3 Friendship Sponsor of School of Basic Medical Sciences, Jilin University. Ursolic acid was obtained from Shyuanye; RPMI 1640 medium and trypsin were obtained from Cytiva; foetal bovine serum was obtained from HyClone; penicillin, streptomycin, and TUNEL staining kits were obtained from Solarbio. Antibodies against Caspase-3, Bax, Bcl-2, Beclin1, P62, LC3, PI3K, AKT, PERK, eIF2-α, CHOP, β-actin and tubulin were obtained from Proteintech. 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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Culture of ovarian cancer cell lines\u003c/h2\u003e \u003cp\u003eThe frozen tube containing SKOV3 cells was thawed quickly by placing it in a 37\u0026deg;C water bath. The resulting cytosol was transferred to a centrifuge tube that contained the medium. After washing the frozen tube twice with medium, it was subjected to centrifugation at 2000 rpm for a duration of 5 minutes, followed by disposal of the supernatant. Next, 3 mL of medium was added and mixed thoroughly, and the cells were gently dispersed into a petri dish. 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\u0026deg;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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Cell proliferation assay\u003c/h2\u003e \u003cp\u003eEvaluation 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 hours. Subsequently, 10 \u0026micro;L of CCK-8 solution was added to each well, followed by incubation for an additional 3 hours. A plate reader was utilized to determine the absorption at 450 nm based on the enzymatic reaction. Subsequently, the absorbance was used to plot the growth curve; the experiment was performed three times. The average value was determined.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Colony formation assay\u003c/h2\u003e \u003cp\u003eSKOV3 cells were plated at a density of 0.1x10\u003csup\u003e6\u003c/sup\u003e 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 secured with a 4% paraformaldehyde solution for 20 minutes. 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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Wound healing assays\u003c/h2\u003e \u003cp\u003eCells from the logarithmic growth phase were harvested and seeded at a density of 1x10\u003csup\u003e6\u003c/sup\u003e cells per well into 6-well plates. The cells were cultured until a monolayer formed. A 200 \u0026micro;L 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 hours 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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Flow cytometry\u003c/h2\u003e \u003cp\u003eThe 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 1x10\u003csup\u003e5\u003c/sup\u003e and incubated for 24 hours. Cells were collected and suspended in precooled PBS three times. The cells were suspended in 200 \u0026micro;L of 1 \u0026times; Annexin V binding buffer and then treated with 5 \u0026micro;L of FITC-Annexin V and PI stain for 15 minutes at room temperature in the dark. Detection was performed on a flow cytometer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.8. TUNEL staining to detect apoptosis\u003c/h2\u003e \u003cp\u003eCells were incubated on sheets designed for specific cell types for 24 hours. Afterwards, the cells were fixed with paraformaldehyde for 30 minutes, permeabilized using 0.2% Triton X-10 for 20 minutes, and then incubated for 1 hour 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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.9. Western blot analysis\u003c/h2\u003e \u003cp\u003eSKOV3 cells were treated for 24 hours. Cells were collected and lysed with cold RIPA lysis solution in an ice bath for 30 min. Total protein extraction was achieved through 4\u0026deg;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 5% skim milk powder at room temperature for one hour. The specific primary antibody was incubated overnight at 4\u0026deg;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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.10. Immunofluorescence (IF) assay\u003c/h2\u003e \u003cp\u003eThe cells were moved to crawler sheets specific to their cell type and then incubated. After a 30-minute fixation in 4% paraformaldehyde solution, they were permeabilized for 20 minutes using 0.2% Triton X-10. Next, the cells were blocked using 2% BCA for 30 minutes and left overnight at 4\u0026deg;C with a primary antibody. The following day, a fluorescent secondary antibody was incubated for 1 hour at room temperature in the dark. The cells were rinsed three times with prechilled PBS after each step. Then, the sheets were sealed using an anti-fading burst sealant that included DAPI and clear nail polish. The sections were then sealed and viewed under a fluorescence microscope.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.11. Statistical methods\u003c/h2\u003e \u003cp\u003eStatistical 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\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Statistical significance was calculated by one-way or two-way analysis of variance (ANOVA). A p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eOvarian cancer is a prevalent malignancy that poses a significant threat to women's lives due to its high recurrence and mortality rates. The study's findings indicate that UA can inhibit the development of ovarian cancer by suppressing tumour cell proliferation, colony formation, and migration. Additionally, UA can enhance ovarian cancer cell apoptosis. The mechanism of action involves the promotion of tumour cell endoplasmic reticulum stress and the suppression of autophagy. These results suggest that UA holds potential as an antitumour agent.\u003c/p\u003e \u003cp\u003eOne effective mechanism for inducing tumour cell death is apoptosis, which can efficiently regulate cell number and proliferation by inducing cell membrane rupture, cell nucleus breakage, chromatin condensation, and DNA breakage [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Promotion of apoptosis is currently the prevailing method of targeted cancer therapy [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The colony formation assay indicated a decrease in colony numbers with an increase in the dose of UA. Additionally, the migration experiment demonstrated that UA inhibited the migration of ovarian cancer cells, and the results showed a dose-dependent effect in inhibiting the proliferation and migration of ovarian cancer cells. 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 [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and inhibit the ERK signalling pathway to suppress cell adhesion and migration, thereby inhibiting the progression of breast cancer[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. 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.\u003c/p\u003e \u003cp\u003eThe proper balance between the antiapoptotic gene Bcl-2 and the proapoptotic gene Bax is necessary for the maintenance of cellular homeostasis [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Reducing Bcl-2 expression significantly increases the pro-apoptotic effects of drugs[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Furthermore, members of the caspase family of cysteine proteases are crucial in initiating and executing apoptosis[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. 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.\u003c/p\u003e \u003cp\u003eAutophagy, a metabolic process, can promote cellular homeostasis by self-phagocytosing aggregated proteins and damaged or dysfunctional organelles, which enables cellular metabolism and maintains cellular biosynthesis[\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. 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. As tumours advance, autophagy can supply the energy and metabolites necessary for tumour growth [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Autophagy transports intracellular substances to lysosomes for degradation, preserving energy for tumour cell survival and providing essential metabolites, including arginine and alanine, to facilitate tumour growth. Autophagy inhibition effectively promotes cell apoptosis.[\u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. 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 induce pronounced apoptosis by impeding autophagic flow in SKOV3 cells. However, elevated autophagy levels were found in both cisplatin-resistant and cisplatin-sensitive tumour cells after cisplatin treatment, indicating that cisplatin is not an appropriate positive control for this experiment[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Numerous studies have demonstrated that Beclin1 is closely linked to tumour progression and plays a significant role in cellular proliferation[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Some studies have indicated that decreased autophagy can promote cell proliferation and lead to the onset of malignant tumours. However, considering the bidirectional regulation of autophagy, inhibiting autophagy may effectively decrease tumour proliferation and improve survival rates. The effectiveness of this approach has been validated in experiments on various cancers, such as pancreatic ductal carcinoma, breast cancer, and non-small cell lung cancer, and the level of autophagy is associated with the degree of malignancy and the features of the tumour environment[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Autophagy centres on the autophagy initiation protein Beclin1, which generates the autophagy initiation complex (AIC) to aid autophagy[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Beclin1 is part of the type III PI3 kinase complex, a crucial compound in forming autophagosomes and promoting autophagosome maturation. It generally interacts with BCL-2, which is pivotal for autophagosome maturation. This substance typically interacts with BCL-2, resulting in the inhibition of cellular autophagy[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In contrast, upregulation of Bax induces cytochrome C release, resulting in the cleavage of Beclin1 and inhibition of its autophagy induction effect. Moreover, UA exhibited a pro-apoptotic effect on ovarian cancer, as evidenced by the results of the experiments conducted. The protein content of P62, an autophagy marker, increased, indicating inhibition of autophagy by UA in SKOV3 cells. However, degradation of autophagosomes is a separate step from the formation of autophagosomes[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. LC3 is considered the protein that firmly binds to the autophagosome membrane. Technical abbreviations will be explained when first used. There are two variants of LC3 (LC3-I and LC3-II): LC3-I is present in the cytoplasm, and LC3-II is bound to the membrane. LC3-I is converted to LC3-II and is capable of both initiating autophagosome formation and prolonging their existence[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. LC3 expression in SKOV3 cells was detected after UA administration, and the results showed that LC3 expression was reduced, and the expression of LC3 was further reduced with increasing doses, suggesting that UA inhibits ovarian cancer progression by inhibiting autophagy-induced apoptosis in SKOV3 cells. The PI3K-AKT-mTOR signalling pathway plays a significant role in various biological processes and serves as an effective focus for current cancer treatment[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The PI3K family of lipid kinases primarily regulate cellular growth and modulate cellular autophagy and include three types: class I, class II, and class III PI3Ks[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. AKT belongs to the serine/threonine kinase family; when PI3K binds to AKT, it triggers the transfer of AKT from the cytoplasm to the cytosol and leads to its phosphorylation[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. mTOR, a serine/threonine kinase, is a critical regulator of autophagy and lies downstream of the PI3K-AKT signalling pathway. It is commonly utilized in the negative regulation of autophagy[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Numerous studies have demonstrated that inhibiting the PI3K/AKT/mTOR signalling pathway efficiently stimulates autophagy activation, triggers apoptosis, and impedes tumour growth and migration. However, recent studies have reported that glycyrrhizin can inhibit autophagy-related gene expression and exert an antitumour effect by inhibiting the PI3K-AKT-mTOR signalling pathway[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. This is consistent with the results of our experiments, suggesting that UA inhibits autophagy, promotes apoptosis, and hinders ovarian cancer cell progression by downregulating the PI3K-AKT-mTOR signalling pathway.\u003c/p\u003e \u003cp\u003eThe endoplasmic reticulum, comprising pools, sheets, and linear tubules, is the largest organelle; it has a membranous, network structure and plays a role in the synthesis and folding of proteins[\u003cspan additionalcitationids=\"CR53 CR54 CR55\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Nevertheless, an excessive build-up of misfolded proteins beyond the threshold of endoplasmic reticulum processing is triggered by internal and external factors, leading to the unfolded protein response (UPR)[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Endoplasmic reticulum stress is a crucial aspect of tumour growth and development [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] and plays a significant regulatory function in both tumorigenesis and progression. The molecular chaperone-binding immunoglobulin (BiP) typically ensures protein folding, refolding, and degradation and is a key component of this process. Also known as GRP78, this protein binds to three sensors: 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). These three sensors bind to the endoplasmic reticulum, rendering themselves in a monomeric, inactive state [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. When the endoplasmic reticulum undergoes stress, BIP dissociates from PERK, ATF6, and IRE1α and binds to misfolded or unfolded proteins due to its higher binding affinity. This enhances the folding ability of the endoplasmic reticulum, according to sources [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Mild, stimulus-induced endoplasmic reticulum stress can enhance protein folding ability and promote adaptive transformation and malignant development of tumour cells. However, prolonged and severe endoplasmic reticulum stress has a toxic effect on tumour cells and can promote apoptosis, immunogenic death, and other negative outcomes[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Recently, it was discovered that PERK self-phosphorylates and forms dimers upon dissociation from BIP. The activated PERK can then activate the eIF2α translation initiation factor and stimulate its phosphorylation, which limits protein translation and contributes to an increase in selective ATF4 translation. This subsequently induces the activation of the CHOP transcription factor. While PERK-mediated phosphorylation of eIF2α is necessary for autophagy to take place and progress, PERK can also stimulate the expression of autophagy-related genes. Additionally, CHOP causes growth arrest by increasing the expression of genes involved in autophagosome formation, and it promotes apoptosis by reducing BCL-2 expression [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. 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 ER stress in SKOV3 cells. Recent experiments have shown that antitumour treatments can increase eIF2α phosphorylation in tumour cells, resulting in antitumour effects. Additionally, endoplasmic reticulum stress activators can upregulate endoplasmic reticulum stress via the PERK/AKT/mTOR signalling pathway. Induction of autophagy in tumour cells and inhibition of tumour progression are well-known therapeutic strategies [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. However, the results of this study demonstrate that treatment with UA promotes endoplasmic reticulum stress in SKOV3 cells and inhibits SKOV3 cell autophagy, which contradicts previous research(Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe experiments confirmed that treatment with UA induced endoplasmic reticulum stress, inhibited autophagy, and ultimately led to apoptosis in ovarian cancer cells, impeding tumour progression. However, the present study lacks reverse validation of the link between endoplasmic reticulum stress, autophagy, and apoptosis, and only one ovarian cancer cell line was utilized, so more experiments are needed for validation and for the development of new therapeutic options for clinical treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during an analysed during the current study are available in the persistent links to datasets.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis 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).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRZ, 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.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe 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.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBerner K, Hirschfeld M, Wei\u0026szlig; D, R\u0026uuml;cker G, Asberger J, et al. 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\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLheureux 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\u0026ndash;304.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLambertini M, Del Mastro L, Pescio MC, Andersen CY, Azim HA, editors. Jr. : Cancer and fertility preservation: international recommendations from an expert meeting. \u003cem\u003eBMC Med\u003c/em\u003e 2016, 14:1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCasta\u0026ntilde;o M, Tom\u0026aacute;s-P\u0026eacute;rez S, Gonz\u0026aacute;lez-Cant\u0026oacute; E, Aghababyan C, Mascar\u0026oacute;s-Mart\u0026iacute;nez A et al. Neutrophil Extracellular Traps and Cancer: Trapping Our Attention with Their Involvement in Ovarian Cancer. Int J Mol Sci 2023, 24(6).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePartridge EE, Barnes MN. Epithelial ovarian cancer: prevention, diagnosis, and treatment. CA Cancer J Clin. 1999;49(5):297\u0026ndash;320.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcManus 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\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElias KM, Guo J, Bast RC Jr.. Early Detection of Ovarian Cancer. Hematol Oncol Clin North Am. 2018;32(6):903\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCamuzard O, Santucci-Darmanin S, Carle GF, Pierrefite-Carle V. Autophagy in the crosstalk between tumor and microenvironment. Cancer Lett. 2020;490:143\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLheureux S, Gourley C, Vergote I, Oza AM. Epithelial ovarian cancer. Lancet. 2019;393(10177):1240\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang L, Xie HJ, Li YY, Wang X, Liu XX et al. Molecular mechanisms of platinum\u0026ndash;based chemotherapy resistance in ovarian cancer (Review). Oncol Rep 2022, 47(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBafaloukos D, Linardou H, Aravantinos G, Papadimitriou C, Bamias A, 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.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKehoe S, Hook J, Nankivell M, Jayson GC, Kitchener H, 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\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo H, Vong CT, Chen H, Gao Y, Lyu P, et al. Naturally occurring anti-cancer compounds: shining from Chinese herbal medicine. Chin Med. 2019;14:48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQian Q, Chen W, Cao Y, Cao Q, Cui Y et al. Targeting Reactive Oxygen Species in Cancer via Chinese Herbal Medicine. \u003cem\u003eOxid Med Cell Longev\u003c/em\u003e 2019, 2019:9240426.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhong 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.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo Z, Wang Q, Lau WB, Lau B, Xu L, et al. Tumor microenvironment: The culprit for ovarian cancer metastasis? Cancer Lett. 2016;377(2):174\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYin 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\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin 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\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiao WL, Liu YF, Ying TH, Shieh JC, Hung YT et al. 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).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWong RS. Apoptosis in cancer: from pathogenesis to treatment. J Exp Clin Cancer Res. 2011;30(1):87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSu Z, Yang Z, Xu Y, Chen Y, Yu Q. Apoptosis, autophagy, necroptosis, and cancer metastasis. Mol Cancer. 2015;14:48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHou J, Zhang Y, Zhu Y, Zhou B, Ren C, et al. α-Pinene Induces Apoptotic Cell Death via Caspase Activation in Human Ovarian Cancer Cells. Med Sci Monit. 2019;25:6631\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM\u0026uuml;ller D, Mazzeo P, Koch R, B\u0026ouml;sherz MS, Welter S, 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.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeng RY, Jin H, Nguyen TV, Chai OH, Park BH et al. Ursolic Acid Accelerates Paclitaxel-Induced Cell Death in Esophageal Cancer Cells by Suppressing Akt/FOXM1 Signaling Cascade. Int J Mol Sci 2021, 22(21).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZong L, Cheng G, Zhao J, Zhuang X, Zheng Z et al. Inhibitory Effect of Ursolic Acid on the Migration and Invasion of Doxorubicin-Resistant Breast Cancer. Molecules 2022, 27(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Z, Ding Y, Ye N, Wild C, Chen H, et al. Direct Activation of Bax Protein for Cancer Therapy. Med Res Rev. 2016;36(2):313\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarneiro BA, El-Deiry WS. Targeting apoptosis in cancer therapy. Nat Rev Clin Oncol. 2020;17(7):395\u0026ndash;417.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetroni G, Bagni G, Iorio J, Duranti C, Lottini T, et al. Clarithromycin inhibits autophagy in colorectal cancer by regulating the hERG1 potassium channel interaction with PI3K. Cell Death Dis. 2020;11(3):161.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRudnick JA, Monkkonen T, Mar FA, Barnes JM, Starobinets H, et al. Autophagy in stromal fibroblasts promotes tumor desmoplasia and mammary tumorigenesis. Genes Dev. 2021;35(13\u0026ndash;14):963\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhayati K, Bhatt V, Lan T, Alogaili F, Wang W, et al. Transient Systemic Autophagy Inhibition Is Selectively and Irreversibly Deleterious to Lung Cancer. Cancer Res. 2022;82(23):4429\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRen Y, Wang R, Weng S, Xu H, Zhang Y, et al. Multifaceted role of redox pattern in the tumor immune microenvironment regarding autophagy and apoptosis. Mol Cancer. 2023;22(1):130.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, He S, Ma B. Autophagy and autophagy-related proteins in cancer. Mol Cancer. 2020;19(1):12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatheder NS, Khezri R, O'Farrell F, Schultz SW, Jain A, et al. Microenvironmental autophagy promotes tumour growth. Nature. 2017;541(7637):417\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng Y, Wang C, Wang H, Zhang Z, Yang X, et al. 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.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePoillet-Perez L, Xie X, Zhan L, Yang Y, Sharp DW, et al. Autophagy maintains tumour growth through circulating arginine. Nature. 2018;563(7732):569\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFung 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\u0026ndash;806.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhezri R, Holland P, Schoborg TA, Abramovich I, Tak\u0026aacute;ts S, et al. Host autophagy mediates organ wasting and nutrient mobilization for tumor growth. Embo j. 2021;40(18):e107336.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Y, Wang X, Zhu W, Sui Z, Wei X, et al. TRPML1-induced autophagy inhibition triggers mitochondrial mediated apoptosis. Cancer Lett. 2022;541:215752.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu J, Gewirtz DA. Is Autophagy Always a Barrier to Cisplatin Therapy? \u003cem\u003eBiomolecules\u003c/em\u003e 2022, 12(3).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, Yan J, Wang L, Xiao F, Yang Y, et al. Beclin1 inhibition promotes autophagy and decreases gemcitabine-induced apoptosis in Miapaca2 pancreatic cancer cells. Cancer Cell Int. 2013;13(1):26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSousa CM, Biancur DE, Wang X, Halbrook CJ, Sherman MH, et al. Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion. Nature. 2016;536(7617):479\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, Su J, Xia M, Li H, Xu Y, 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\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSutton MN, Huang GY, Liang X, Sharma R, Reger AS et al. DIRAS3-Derived Peptide Inhibits Autophagy in Ovarian Cancer Cells by Binding to Beclin1. Cancers (Basel) 2019, 11(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl-Sherbeeny NA, Soliman N, Youssef AM, Abd El-Fadeal NM, El-Abaseri TB, et al. 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.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang C, Feng Z, Manthari RK, Wang C, Han Y, et al. 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.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang J, Zhou J, Xu Y, Huang X, Wang X, et al. Osthole inhibits ovarian carcinoma cells through LC3-mediated autophagy and GSDME-dependent pyroptosis except for apoptosis. Eur J Pharmacol. 2020;874:172990.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu Z, Han X, Ou D, Liu T, Li Z, et al. Targeting PI3K/AKT/mTOR-mediated autophagy for tumor therapy. Appl Microbiol Biotechnol. 2020;104(2):575\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar 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\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShrivastava 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\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang CZ, Wang SH, Zhang RH, Lin JH, Tian YH, et al. Neuroprotective effect of astragalin via activating PI3K/Akt-mTOR-mediated autophagy on APP/PS1 mice. Cell Death Discov. 2023;9(1):15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao 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.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFern\u0026aacute;ndez A, Ord\u0026oacute;\u0026ntilde;ez R, Reiter RJ, Gonz\u0026aacute;lez-Gallego J, Mauriz JL. Melatonin and endoplasmic reticulum stress: relation to autophagy and apoptosis. J Pineal Res. 2015;59(3):292\u0026ndash;307.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen X, Cubillos-Ruiz JR. Endoplasmic reticulum stress signals in the tumour and its microenvironment. Nat Rev Cancer. 2021;21(2):71\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu L, Ladinsky MS, Kirchhausen T. Cisternal organization of the endoplasmic reticulum during mitosis. Mol Biol Cell. 2009;20(15):3471\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarchi S, Patergnani S, Pinton P. The endoplasmic reticulum-mitochondria connection: one touch, multiple functions. Biochim Biophys Acta. 2014;1837(4):461\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhaminets A, Heinrich T, Mari M, Grumati P, Huebner AK, et al. Regulation of endoplasmic reticulum turnover by selective autophagy. Nature. 2015;522(7556):354\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCubillos-Ruiz JR, Bettigole SE, Glimcher LH. Tumorigenic and Immunosuppressive Effects of Endoplasmic Reticulum Stress in Cancer. Cell. 2017;168(4):692\u0026ndash;706.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFontana F, Moretti RM, Raimondi M, Marzagalli M, Beretta G, et al. δ-Tocotrienol induces apoptosis, involving endoplasmic reticulum stress and autophagy, and paraptosis in prostate cancer cells. Cell Prolif. 2019;52(3):e12576.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePar\u0026iacute;s-Coderch L, Soriano A, Jim\u0026eacute;nez C, Erazo T, Mu\u0026ntilde;oz-Guardiola P, et al. The antitumour drug ABTL0812 impairs neuroblastoma growth through endoplasmic reticulum stress-mediated autophagy and apoptosis. Cell Death Dis. 2020;11(9):773.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe L, Li H, Li C, Liu ZK, Lu 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\u0026ndash;1002.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMohamed E, Sierra RA, Trillo-Tinoco J, Cao Y, Innamarato 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\u0026ndash;682e667.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarez 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\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu D, Liu Z, Liang MX, Fei YJ, Zhang W, et al. Endoplasmic reticulum stress targeted therapy for breast cancer. Cell Commun Signal. 2022;20(1):174.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eB'Chir W, Maurin AC, Carraro V, Averous J, Jousse C, et al. The eIF2α/ATF4 pathway is essential for stress-induced autophagy gene expression. Nucleic Acids Res. 2013;41(16):7683\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu F, Li X, Huang X, Pan J, Wang Y, et al. Development of a pH-responsive polymersome inducing endoplasmic reticulum stress and autophagy blockade. Sci Adv. 2020;6(31):eabb8725.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-complementary-medicine-and-therapies","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcam","sideBox":"Learn more about [BMC Complementary Medicine and Therapies](https://bmccomplementmedtherapies.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Complementary Medicine and Therapies","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Ursolic acid, Anti-ovarian cancer, Endoplasmic reticulum stress, Autophagy, Apoptosis","lastPublishedDoi":"10.21203/rs.3.rs-3779770/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3779770/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOvarian cancer is a common gynaecologic malignancy that poses a serious threat to the health and lives of women.Ursolic acid (UA) is present in various fruits, and several experiments have demonstrated its ability to inhibit tumour growth. In this study, the Cell Counting Kit-8 (CCK-8) assay was used to investigate the anti-proliferative effect of UA on ovarian cancer. Additionally, we assessed the inhibitory effects of UA on the colony formation and migration abilities of ovarian cancer cells via colony formation and scratch assays, respectively. To elucidate the capacity of UA to promote apoptosis, we assessed its potential mechanism of inhibiting ovarian cancer cell proliferation using flow cytometry, TUNEL staining, and protein blotting. These findings suggest that UA can enhance endoplasmic reticulum stress (ERS), induce apoptosis, and suppress autophagy in ovarian cancer cells. This implies that UA exerts a significant anti-ovarian cancer effect by facilitating ERS in tumour cells and inhibiting autophagy.\u003c/p\u003e","manuscriptTitle":"In vitro analysis of the molecular mechanisms of ursolic acid against ovarian cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-19 10:36:14","doi":"10.21203/rs.3.rs-3779770/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-16T13:02:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-14T07:47:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"169767313689568102086347743408444177203","date":"2024-09-11T09:48:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-13T20:45:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4aa6d0da-7642-418f-9e91-faf4885e32e3","date":"2024-03-28T10:07:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"a87dfd5a-0758-4431-b4e8-740e780aafe2","date":"2024-01-28T16:44:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-18T14:08:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-18T14:05:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-01-18T06:37:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-18T06:33:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Complementary Medicine and Therapies","date":"2023-12-20T04:13:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-complementary-medicine-and-therapies","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcam","sideBox":"Learn more about [BMC Complementary Medicine and Therapies](https://bmccomplementmedtherapies.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Complementary Medicine and Therapies","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"89481aae-dd9c-49f4-a657-a6088180b49c","owner":[],"postedDate":"January 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-02-03T15:53:36+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-19 10:36:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3779770","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3779770","identity":"rs-3779770","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}