Limonin induces ferroptosis in cervical squamous cell carcinoma by activating the expression of soluble epoxide hydrolase 2 protein

Qi Wu; Suning Bai; Pei Wang; Lina Han; Liyun Song; Luyang Su; Yanan Ren

doi:10.1371/journal.pone.0343495

Abstract

Natural products are a rich sources for developing anti-cancer drugs with low toxicity and high efficiency. Limonin has anti-cancer activity; however, its effect on cervical squamous cell carcinoma remains unreported. The aim of this study was to explore how Limonin affects ferroptosis in cervical squamous cell carcinoma (CESC) and its underlying mechanism. Based on differential gene analysis of the Gene Expression Omnibus database and drug target prediction of the Comparative Toxicogenomics Database, combined with molecular docking technology, potential anti-cancer targets of Limonin were identified. In vitro experiments were conducted to create epoxide hydrolase 2 (EPHX2) knockdown and overexpression cell lines. Relevant phenotypic experiments were conducted to verify how Limonin targeting EPHX2 affects cell proliferation and ferroptosis. Integrated bioinformatic analysis revealed EPHX2 as a key target of Limonin. Functional experiments showed that EPHX2 overexpression inhibited the proliferation of CESC and induced ferroptosis, while Limonin treatment could enhance EPHX2 expression in a concentration-dependent manner. Furthermore, EPHX2 knockdown could reverse the inhibitory effect of Limonin on CESC proliferation and alterations in ferroptosis-related indicators. This study results reveals a new mechanism by which Limonin induces ferroptosis in CESC by activating EPHX2, providing a new strategy for natural compound-based ferroptosis-targeted therapy.

Citation: Wu Q, Bai S, Wang P, Han L, Song L, Su L, et al. (2026) Limonin induces ferroptosis in cervical squamous cell carcinoma by activating the expression of soluble epoxide hydrolase 2 protein. PLoS One 21(3): e0343495. https://doi.org/10.1371/journal.pone.0343495

Editor: Aldrin V. Gomes, University of California, Davis, UNITED STATES OF AMERICA

Received: June 25, 2025; Accepted: February 3, 2026; Published: March 16, 2026

Copyright: © 2026 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The datasets generated and/or analyzed during the current study are available in the Figshare repository at: https://figshare.com/s/4d5cfc4b29f7807abb4f.

Funding: This study was supported by the Hebei Medical Science Research Project (Project No.: 20230327), and the funding was received by the principal investigator of this project, Dr. Pei Wang.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Cervical squamous cell carcinoma (CESC) accounts for over 70%−80% of cervical malignancies and is closely associated with high-risk HPV infection, early marriage, multiple pregnancies, smoking, and immunosuppression [1]. Currently, surgery, radiotherapy, and chemotherapy yield relatively good results for patients experiencing early-stage disease. However, the 5-year survival rate of patients with locally advanced and metastatic diseases is low. New therapies have resulted in certain improvements; however, problems, including drug resistance, toxicity, and insufficient individualization, still exist [2]. Existing treatment regimens have limited effectiveness in patients at high risk with para-aortic lymph node metastasis or a low Prognostic Nutritional Index, and the absence of precise biomarkers for guidance [3]. Natural products are an important source for the research and development of antitumor drugs [4]. Citrus plants contain limonoids, which possess anti-inflammatory, antiviral, and antitumor activities [5]. Limonin attenuates breast cancer progression by inhibiting MIR216A methylation [6]. It also inhibits the progression of colorectal stemness [7]. Additionally, limonin has shown significant anticancer activity against ovarian cancer [8]. These results show that limonin is a natural drug with significant anticancer potential. However, its role in cervical squamous cell carcinoma remains unreported.

Ferroptosis is a novel form of iron-dependent programmed cell death. Research on cervical squamous cell carcinoma has attracted increasing attention. Cervical cancer progression is closely associated with iron regulation and oxidative stress, and iron metabolism is vital. Cellular iron transport regulators such as ACSL4 affect intracellular iron and reactive oxygen species [ROS) levels. An increase in ROS levels causes an increase in the permeability of the cell membrane, resulting in lactate dehydrogenase (LDH) being released from inside the cell, thereby increasing extracellular LDH activity. Increased malondialdehyde (MDA) content is an essential marker of ferroptosis [9,10]. Some studies reported that EPHX2 knockdown can reduce LDH activity and MDA content and decrease the expression levels of apoptosis-related proteins, including Fas, Fasl, Bax, and cleaved-caspase-3, thereby resisting cell apoptosis [11]. This indicates that EPHX2 is a potential regulator of ferroptosis. The mRNA of EPHX2 is significantly downregulated in most tumors [12–14], but its specific role in CESC is unknown, and whether there is a regulatory relationship with ferroptosis remains unclear.

In this study, disease-related differentially expressed genes (DEGs) were screened based on the GSE63514 cervical cancer transcriptome dataset. The Comparative Toxicogenomics Database (CTD) was systematically searched to identify potential targets of limonin. The Cancer Genome Atlas-Cervical Squamous Cell Carcinoma (TCGA-CESC) cohort was used to verify differential expressions, prognostic correlation assessment, and molecular docking simulation (AutoDock Vina), and candidate genes were finally identified. These cell lines were further treated with limonin, and verification was conducted using the CCK-8 cell viability assay, flow cytometry, and western blotting. Limonin induces ferroptosis by targeting and activating epoxide hydrolase 2 (EPHX2).

Materials and methods

Data acquisition and preprocessing

The dataset related to cervical cancer gene expression analysis of cervical cancer progression (GSE63514) was downloaded from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/). The terms “Nor” were replaced with “Control,” and “Can” with “Disease.” According to the set thresholds (P-Value < 0.05 and |logFC| > 1), the genes that were significantly differentially expressed between the two groups of samples were screened. These genes were classified into up-regulated (logFC > 1 and P-Value < 0.05) and down-regulated genes (logFC < - 1 and P-Value < 0.05).

Visualization analysis

The prcomp function was used to conduct a Principal Component Analysis (PCA) of the gene expression data. A two-dimensional PCA plot was created to illustrate the samples’ distribution within the principal component space [15]. A volcano plot was drawn using ggplot2. The log-fold change (logFC) was set as the x-axis to represent the fold change in gene expression, while the-log10 (Pval) was set as the y-axis to indicate the significance of gene expression differences [16]. Upregulated genes were colored red, non-significant genes were colored gray, and downregulated genes were colored blue. The top 10 upregulated and top 10 downregulated genes were labeled. The top 10 upregulated and top 10 downregulated genes collected from the differential analysis were selected. A heat map was created to display the expression patterns of these genes in different samples. Boxplots were constructed for specific genes, including EPHX2 and cyclin D1 (CNND1), to show the differences in their expression levels between the “Control” and “Disease” groups.

Functional enrichment analysis

Gene Ontology (GO) enrichment analysis was conducted for the overall differentially expressed gene set and the upregulated and downregulated gene sets separately. The biological Process, cellular components, and molecular functions were covered by this analysis. The Benjamini-Hochberg (BH) method was used as a multiple-test correction approach. Significantly enriched GO terms were identified using a screening threshold of p < 0.05. The enrichment results for each category were ranked according to the p-value, and the top 10 terms were selected and shown in a bubble plot.

Subsequently, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was conducted on these gene sets. The species was specified as human (organism = “hsa”), and the screening threshold was set at a p-value < 0.05. The enrichment results were organized and ranked using the p-values, and the top 10 entries were selected and shown in a bar plot.

Subsequent gene screening

In the CTD database (https://ctdbase.org/), “Limonin” was the keyword used to search for the targets of limonin. The R package “VennDiagram” was used to determine the intersection between limonin targets and the DEGs obtained above [17]. Two intersecting genes (EPHX2 and CNND1) were identified. The X-ray diffraction three-dimensional structures of the human EPHX2 (protein data bank (PDB) code: 4y2j) and CNND1 (PDB code: 2w96) complexes were downloaded from the PDB database (https://www.rcsb.org/). The MOL2 format of limonin was obtained from the Traditional Chinese Medicine Systems Pharmacology database (http://sm.nwsuaf.edu.cn/lsp/tcmsp.php) and converted to the PDB format using AutoDock. The molecular docking technology was completed using the software AutoDock Vina 1.5.6. Visualization was conducted using PyMOL 2.1.0 to obtain three-dimensional (3D) analysis diagrams. In the TCGA-CESC (https://www.cancer.gov/ccg/research/genome-sequencing/tcga) database, patients were classified into high-risk and low-risk groups based on the median risk score. The Kaplan-Meier method was used to draw survival curves of the two groups of patients, while the log-rank test was used to compare survival differences between the groups.

Cell culture

The CESC cell lines HeLa (CL-0101), SiHa (CL-0210), Caski (CL-0048), and ME-180 (CL-0155) were purchased from Wuhan Pricella Biotechnology Co., Ltd. The immortalized human cervical squamous epithelial cell line H8 (TCH-C616, Suzhou Haixing Biotechnology Co., Ltd., China) and CESC cell lines were cultured in high-glucose Dulbecco’s Modified Eagle Medium (DMEM) (11995, Beijing Solarbio Science & Technology Co., Ltd., China) containing 10% fetal bovine serum (S9020, Beijing Solarbio Science & Technology Co., Ltd, China) and 1% penicillin-streptomycin mixture (P1400, Beijing Solarbio Science & Technology Co., Ltd, China). The cells were placed in a 37 °C, 5% CO₂ cell incubator (120300, Thermo Fisher Scientific, China). The fresh medium was replaced every other day, and the cells were cultured until the exponential phase for subsequent experiments.

Cell transfection and cell grouping

HeLa and SiHa cells in the exponential growth phase were treated with 2 mL trypsin (T1300, Beijing Solarbio Science & Technology Co., Ltd, China) and incubated for 3 min. Next, 3 mL of high-glucose DMEM was added, and the cell suspension was placed in a centrifuge tube and centrifuged at 1200 × g for 3 min. Next, 3 mL of high-glucose DMEM was added, and the cell density was calculated using a cell counter (A49866, Thermo Fisher Scientific, China). The cells were seeded into six-well plates at a density of 1 × 10⁵ cells per well and incubated overnight. Specific interfering RNAs and overexpression plasmids were designed for the EPHX2 gene. The next day, a mixture of the overexpression plasmid and transfection reagent was added to HeLa cells, and a mixture of interfering RNA and transfection reagent was added to SiHa cells and incubated for 4 h according to the instructions for the transfection reagent (11668500, Thermo Fisher Scientific, China). After incubation, the fresh medium was replaced, and the cells were incubated for another 48 h. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) and Western blot experiments were conducted to verify whether the EPHX2 overexpression and knockdown cell models have been successfully constructed.

To verify the effect of EPHX2 expression on CESC progression in HeLa cells, the cells were divided into two groups: an overexpression control group and an EPHX2 overexpression group. SiHa cells were classified into three groups: knockdown control group, EPHX2 knockdown group 1, and EPHX2 knockdown group 2.

In HeLa cells, the researchers treated CESC cells with different concentrations to verify the pharmacological effects of limonin (HY-17411, MedChemExpress, China), and classified them into four groups: the control group: the 10 μmol/L limonin group, the 20 μmol/L limonin group, and the 40 μmol/L limonin group [18]. Three cell groups were established in the experiment: the control group, the limonin, and the limonin+si-EPHX2–1 group, to verify whether the pharmacological effect of limonin depends on the EPHX2 gene.

Cell counting kit-8 assay

CESC cells were obtained as previously described. After counting, the cells were seeded into 96-well plates at a density of 3000 cells per well. Interfering RNA or overexpression plasmids were added, and the cells were incubated for 0, 24, 48, and 72 h. The CESC cells were then removed. Then, 10 μL of cell counting kit-8 (CCK8) solution (CA1210, Beijing Solarbio Science & Technology Co., Ltd., China) was added to each well and incubated for another 3 h. After incubation, the plates were placed in a microplate reader (VL0000D2, Thermo Fisher Scientific) to measure absorbance at 450 nm.

5-ethynyl-2’-deoxyuridine assay

Cells were seeded into six-well plates at a density of 1 × 10⁵ cells per well, and then treated based on different grouping requirements. Subsequently, 5-ethynyl-2’-deoxyuridine (EDU) working solution (C0071L, Beyotime Biotech Inc., China) was added and incubated for 4 h. The EDU working solution was removed, and 4% paraformaldehyde (P0099, Beyotime Biotech Inc., China) was added and incubated at 25 °C for 30 min. Next, 0.5% Triton X-100 (ST1723; Beyotime Biotech Inc., China) was added and incubated at 25 °C for 10 min. Afterward, 0.5 mL of the click reaction solution was added to each well and incubated at 25 °C for 30 min. After incubation, Hoechst 33342 dye (C1022, Beyotime Biotech Inc, China) was added, and the cells were incubated at 25 °C for 30 min. A fluorescence microscope (AMF5000; Thermo Fisher Scientific, China) was used to obtain images.

Reactive oxygen species detection

Cells were seeded into six-well plates at a density of 3 × 10⁵ cells per well and treated based on different grouping requirements. A working solution containing DCFH-DA (S0035M; Beyotime Biotech Inc., China) was added, and the cells were incubated at 37 °C in the dark for 30 min. Trypsin was added to incubate the cells for 2 min, and the cells were centrifuged at 800 × g for 3 min. Trypsin was removed, and the cells were resuspended in PBS. A flow cytometer (A24858; Thermo Fisher Scientific, China) was used to detect the fluorescence intensity of the ROS within each cell group.

Detection of Fe² ⁺, malondialdehyde, and total glutathione/glutathione disulfide content

Cell ferrous ion fluorescence assay kit (E-BC-F101), MDA detection kit (E-BC-K028-M), and total glutathione/glutathione disulfide (T-GSH/GSSG) colorimetric assay kit (E-BC-K097-M) were purchased from Elabscience Biotechnology Co., Ltd. Cells were seeded into six-well plates at a density of 3 × 10⁵ cells per well and treated based on different grouping requirements. The cell suspension was then collected. The corresponding working solutions in each kit were added according to the instructions of each detection kit, and then the absorbance was measured using a microplate reader (Fe²⁺ at 575 nm, MDA at 532 nm, and T-GSH/GSSG at 412 nm).

Reverse transcription quantitative polymerase chain reaction assay

Cells were seeded into six-well plates at a density of 4 × 10⁵ cells per well and treated based on different grouping requirements. The cell suspensions were then obtained. Then, 2 mL of TRIzol (R0016, Beyotime Biotech Inc., China) was added, and the mixture was left on ice for 15 min. Chloroform was added, and the mixture was left at 25 °C for 5 min, and then centrifuged at 12000 g for 15 min. After centrifugation, isopropanol was added, and the mixture was inverted and mixed well, then left at 25 °C for 5 min and centrifuged at 2000 g for 15 min. Subsequently, a 75% ethanol solution was added, and the mixture was centrifuged at 12000 g at 4 °C for 10 min. After air-drying, 50 μL of diethyl pyrocarbonate water was added. Specific primers were designed for the target genes, and the primer information is shown in S1 Table. A complementary deoxyribonucleic acid (cDNA) synthesis kit (KR116, Tiangen Biotech Co., Ltd., China) was used to prepare the reaction system per the manufacturer’s instructions. The polymerase chain reaction (PCR) instrument (A37835; Thermo Fisher Scientific, China) was set at 42 °C for 5 min and 95 °C for 3 min to obtain the cDNA. A RT-qPCR kit (RR600A, TaKaRa Biotechnology Co., Ltd., China) was used to prepare the reaction system per the manufacturer’s instructions. The real-time fluorescence quantitative PCR instrument (A28139, Thermo Fisher Scientific, China) was set at 52 °C for 5 min, 95 °C for 10 s, followed by 40 cycles of 95 °C for 5 s and 63 °C for 30 s. The concentration time (CT) values were obtained after the reaction. The relative expression of the target gene was represented by 2 ⁻ ΔΔCt, where ΔCt represents the difference between the CT value of the target gene and the CT value of the internal reference gene GAPDH [19].

Western blot assay

Cells were seeded into six-well plates at a density of 4 × 10⁵ cells per well and treated based on different grouping requirements. The cell suspension was then collected. Radio-immunoprecipitation assay protein lysis buffer (P0013B; Beyotime Biotech Inc., China) was added, and the mixture was incubated on ice for 30 min. Bicinchoninic acid protein quantification kit (P0009; Beyotime Biotech Inc., China) was used to determine the protein concentration in each sample. Protein lysis buffer (P0015; Beyotime Biotech Inc., China) was added to adjust the protein concentrations of the samples for consistency. The protein solution was incubated in a 95 °C metal bath (88870006, Thermo Fisher Scientific, China) for 15 min. Then, 30 μg of protein solution was added to each well of the electrophoresis tank, and electrophoresis was conducted at 120 V for 90 min. The proteins in the gel were transferred onto a polyvinylidene diflouride (PVDF) membrane at a current of 260 mA for 60 min. The PVDF membrane was incubated with 5% skim milk powder (Y261720, Beyotime Biotech Inc., China) for 2 h, and then the corresponding specific primary antibody solution was added and incubated overnight. The next day, the membrane was washed thrice with TBST (ST671, Beyotime Biotech Inc., China), and the corresponding secondary antibody solution was added and incubated for 2 h. After incubation, the membrane was washed thrice with TBST, and enhanced chemiluminescence solution (P0018AS, Beyotime Biotech Inc., China) was added and incubated for 10 s. The membranes were then exposed to a gel imaging instrument (EI600C; Beyotime Biotech Inc., China). Images were collected, and the gray values of the target bands were statistically analyzed using ImageJ 1.5.2a. Antibody information and dilution ratios are shown in S2 Table.

Electron microscopy observation of mitochondrial morphology

Cells were seeded into six-well plates at a density of 3 × 10⁵ cells per well and treated based on different grouping requirements. Cells were collected using a cell scraper, and 2.5% glutaraldehyde (P1126, Beijing Solarbio Science & Technology Co., Ltd, China) was added to fix the cell samples at 4 °C for 4 h. Then, 1% osmium tetroxide (75633, Sigma-Aldrich Corporation, China) was used to fix the samples at 4 °C for 2 h. The cells were embedded and sectioned (60 nm). The sections were stained with 2% aqueous uranyl acetate for 30 min and rinsed thrice with double-distilled water. They were then stained with Reynolds lead citrate stain (15326; Sigma-Aldrich Corporation, China) for 10 min and rinsed thrice with double-distilled water. The sections were placed on a copper grid, and the mitochondrial ultrastructure was observed using a transmission electron microscope (JEM-1400FLASH, JEOL, Ltd.).

Soluble epoxide hydrolases activity detection

The cells were treated based on the experimental groups (see Section 2.6 of the Experimental Methods). Trypsin was added to digest cells from each group. The cells were centrifuged at 1000 × g for 3 min to collect the cell pellets. Standard products with different concentration gradients and samples to be tested were added according to the instructions of the soluble Epoxide Hydrolases (sEH) detection kit (JM-7141H2, Jingmei Biotechnology Co., Ltd, China). Then 100 μL of horseradish peroxidase (HRP)-labeled antibody was added to each well, and incubated in a 37 °C incubator for 60 min. After the incubation, 50 μL of substrate A and 50 μL of substrate B were added, respectively, and incubated in the dark at 37 °C for 15 min. Subsequently, 50 μL of stop solution was added. The optical density value of each well was measured at a wavelength of 450 nm within 15 min.

Surface plasmon resonance

The Biacore T200 system (GE Healthcare Life Sciences, Uppsala, Sweden) was used to quantitatively measure the interaction between the compound and target protein [20]. The purified target protein was directly immobilized onto a carboxymethylated 5 (CM5) sensor chip. Subsequently, small molecules at different concentrations were used as analytes for multi-cycle kinetic detection [21]. The carboxylic acid groups on the CM5 chip (Cytiva) were activated first with a mixture of EDC and NHS solutions (Cytiva) at a flow rate of 10 μL/min for 7 minutes at 25 °C. Subsequently, the target protein dissolved in sodium acetate buffer (10 mM; pH 4.5) was injected until the amount of protein immobilized on the chip reached 3000 – RU. Finally, the chips were blocked with ethanolamine [22]. The target protein was directly immobilized on the CM5 chip first for multicycle kinetics. Then, the serially diluted analytes were detected at a specific concentration per cycle. Dimethyl sulfoxide (DMSO) solvent correction was conducted to detect the affinity and kinetics [23]. Temperature: 25 °C, injection rate: 30 °L/min, association time: 90 s, dissociation time: 90 s, and running buffer: 5% DMSO PBS – P [24].

Statistical analysis

Statistical analyses were conducted using GraphPad Prism 9.5.0 (GraphPad Software Inc., USA). Continuous variables were shown as mean ± standard deviation (Mean ± SD) after being confirmed to follow a normal distribution by the Shapiro-Wilk test. All experiments were conducted with at least three independent biological replicates. An independent samples Student’s t-test (two-tailed) was used for comparisons between two groups. When multiple-group comparisons were involved, one-way analysis of variance combined with the Brown-Forsythe test was used to verify the homogeneity of variance. For data that met the sphericity test assumption, Tukey’s honestly significant difference (HSD) multiple comparison method was used for post hoc analysis. The statistical significance threshold was set at α = 0.05, and all test results reported the exact P-value and 95% confidence interval.

Results

Identification of epoxide hydrolase 2 as a potential drug target of limonin among differentially expressed genes in cervical cancer

In this study, the cervical cancer transcriptome dataset was obtained from the GEO public database (accession number GSE63514). This dataset included 24 samples from the disease group and 28 normal cervical tissue control samples (Fig 1A). PCA was conducted on the “Disease” and “Control” groups, and the results showed certain differences between the two groups (Fig 1B). The results of the volcano plot of DEGs (Fig 1C) and the cluster heatmap (Fig 1D) indicated that ANO10, RBM20, CRISP3, etc. were significantly down-regulated in the “Disease” group, while HAUS5, APOC1, WDHD1 were significantly up-regulated in the “Disease” group. Further functional enrichment analysis of the DEGs showed that the KEGG results indicated that they were mainly enriched in Cell cycle, Viral protein interaction with cytokine and cytokine receptor, and IL-17 signaling pathway (Fig 1E). The results of the GO functional enrichment analysis are shown in S1 Fig. These results indicate that the progression of cervical cancer may involve these pathways.

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Fig 1. Mining potential targets of limonin among differentially expressed genes in cervical cancer.

Composition distribution of the GSE63514 dataset. (B) Principal Component Analysis of the GSE63514 dataset. (C) Volcano plot of differentially expressed genes. (D) Cluster heatmap of differentially expressed genes. (E) Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis. (F) A venn diagram to obtain the intersecting genes between the differentially expressed genes in the GSE63514 dataset and the drug targets of limonin. (G) Molecular docking of limonin with the proteins of intersecting genes cyclin D1 (CNND1) and epoxide hydrolase 2 (EPHX2). (H) Box plot of the relative expression of CNND1 and EPHX2 in the GSE63514 dataset. (I) Overall survival prognostic analysis of CNND1 and EPHX2 in the Cancer Genome Atlas-Cervical Squamous Cell Carcinoma cohort.

https://doi.org/10.1371/journal.pone.0343495.g001

Based on a network pharmacology strategy, this study integrated potential drug targets of limonin (derived from the CTD database) and the DEGs in cervical cancer (DEGs screened from the GSE63514 dataset). The common targets CNND1 and EPHX2 were identified through Venn diagram analysis (Fig 1F). Molecular docking (AutoDock Vina 1.2.0) was used to simulate their interaction patterns to further verify the direct binding of limonin to these targets. The results showed that limonin’s binding energy to CNND1 was – 8.1 kcal/mol, and its binding energy to EPHX2 was even lower, at – 9 kcal/mol (Fig 1G). According to the empirical threshold ΔG < - 7 kcal/mol, indicating strong binding activity [25], the above results confirmed that limonin has a high-affinity binding to CNND1 and EPHX2.

We also observed the differential expression of CNND1 and EPHX2 in GSE63514. The results showed that CNND1 and EPHX2 were weakly expressed in cervical cancer tissues. Further overall survival (OS) analysis in the TCGA-CESC cohort showed that patients in the high-expression group of CNND1 had a tendency towards shorter OS; nevertheless, the difference was not statistically significant (P = 0.21). However, patients in the low-expression group of EPHX2 had significantly worse OS than those in the high-expression group (p = 0.0018). Notably, EPHX2 is also commonly expressed at low levels in solid tumors, including colorectal and liver cancers [12–14], indicating that it may be a potential tumor-suppressor gene across cancer types. Combining the previous molecular docking results (the binding energy of EPHX2-Limonin ΔG = − 9.0 kcal/mol, better than that of CNND1 with ΔG = − 8.1 kcal/mol), EPHX2 was selected as the core target for subsequent functional verification of the anti-cervical cancer mechanism of Limonin in this study.

Epoxide hydrolase 2 inhibits the proliferation of HeLa and SiHa cells

In this study, four CESC cell lines (HeLa, SiHa, Ca Ski, and ME-180) and normal cervical epithelial cells (H8) were selected. The transcriptional and protein expression levels of EPHX2 were systematically evaluated using RT-qPCR and Western blotting. The results showed that the relative mRNA and protein expression levels in CESC cells were lower than those in H8 cells (expression in SiHa cells was lower than that in H8 cells; however, the difference was not statistically significant). Among the four different CESC cell lines, the relative expression levels of EPHX2 mRNA and protein were lowest in HeLa cells and highest in SiHa cells (Fig 2A and 2B). Consistent with these findings, sEH enzymatic activity was the highest in HeLa cells and lowest in SiHa cells among the tested cell lines (Fig 2C). An EPHX2-overexpressing HeLa cell line and a knockdown cell line in SiHa cells were constructed to highlight the impact of the differences in EPHX2 expression on the proliferation of HeLa and SiHa cells. The results of RT-qPCR experiments confirmed the successful construction of the knockdown and overexpression cell line models (S2A Fig). Consistent with these genetic manipulations, sEH enzymatic activity was significantly reduced in EPHX2-knockdown cells and increased in EPHX2-overexpressing cells (S2B Fig). To verify whether EPHX2 is a key target mediating the antiproliferative effect of limonin, Functional validation was conducted in different cell backgrounds. Compared to the control group, the overexpression of EPHX2 (oeEPHX2) in HeLa cells with low EPHX2 expression enhanced the inhibitory effect of limonin on cell proliferation. Complementarily, in SiHa cells with high EPHX2 expression, knocking down EPHX2 (siEPHX2−1 and siEPHX2−2) significantly weakened the antiproliferative effect of Limonin (Fig 2D).

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Fig 2. Epoxide hydrolase 2 inhibits the proliferation of HeLa and SiHa cells.

(A) Reverse transcription quantitative polymerase chain reaction (RT-qPCR) assay to detect the relative expression level of epoxide hydrolase 2 (EPHX2) micro Ribonucleic acid (mRNA) in H8, HeLa, SiHa, Caski, and ME-180 cells. (B) Western blot assay to detect the relative expression level of EPHX2 protein in H8, HeLa, SiHa, Caski, and ME-180 cells. (C)The expression levels of soluble epoxide hydrolase activity in H8, HeLa, SiHa, Caski, and ME-180 cells were detected by an ELISA kit. (D) After transfecting siRNA into SiHa cells for 48 h, the relative expression level of EPHX2 mRNA in the cells was detected by RT-qPCR. (E) Cell Counting Kit-8 assay (0 h, 24 h, 48 h, 72 h) and EDU assay to detect the changes in cell proliferation ability after overexpressing EPHX2 in HeLa cells and knocking down EPHX2 protein in SiHa cells (200 × , scale bar: 100 μm). (Comparison between two groups, *indicates statistical significance, ns represents P > 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ^####P < 0.0001).

https://doi.org/10.1371/journal.pone.0343495.g002

Epoxide hydrolase 2 induces ferroptosis in HeLa and SiHa cells

HeLa (EPHX2-overexpressing) and SiHa (EPHX2-knockdown) cell models were constructed in this study using gene overexpression and RNA interference techniques, respectively, to systematically evaluate the biological function of EPHX2 in regulating ferroptosis in cervical squamous cell carcinoma cells. Changes in ferroptosis-related biomarkers and mitochondrial ultrastructure were also detected.

The experimental results (Fig 3A) showed that overexpression of EPHX2 enhanced the relative fluorescence intensity of ROS and the content of MDA, promoted the accumulation of Fe²⁺ and GSSG. It also reduced the content of GSH and the GSH/GSSG ratio in HeLa cells. Conversely, the knockdown of EPHX2 weakened the relative fluorescence intensity of ROS, the content of MDA, Fe²⁺, and GSSG, and enhanced the content of GSH and the GSH/GSSG ratio in SiHa cells (Fig 3B-3D).

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Fig 3. EPHX2 can enhance the expression levels of ROS, MDA, and Fe²⁺ and decrease the GSH/GSSG ratio.

Flow cytometry was used to detect the relative levels of intracellular reactive oxygen species in HeLa and SiHa cells 48 h after transfection. (B) Changes in intracellular malondialdehyde content in HeLa and SiHa cells 48 h after transfection. (C) Changes in intracellular Fe²⁺ content in HeLa and SiHa cells 48 h after transfection. (D) Changes in intracellular reduced glutathione and glutathione disulfide GSSH content and the reduced glutathione/ oxidized glutathione ratio in HeLa and SiHa cells 48 h after transfection. (Comparison between two groups, * indicates statistical significance, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001).

https://doi.org/10.1371/journal.pone.0343495.g003

Furthermore, overexpressing EPHX2 led to an abnormal mitochondrial structure in HeLa cells, manifested as damage to mitochondrial membrane integrity (red arrows), decreased matrix electron density, and blurred mitochondrial cristae structure. These morphological changes aligned with typical characteristics of ferroptosis [26]. However, when EPHX2 was knocked down in SiHa cells, no significant changes were observed in mitochondrial structure and morphology. These results showed that EPHX2 may be a positive regulator of ferroptosis and that its expression level positively correlates with the degree of mitochondrial damage and susceptibility to ferroptosis (Fig 4A).

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Fig 4. Epoxide hydrolase 2 induces ferroptosis in HeLa and SiHa cells.

(A) Observation of changes in the structure and morphology of intracellular mitochondria in HeLa and SiHa cells 48 h after transfection by electron microscopy. The red arrows represent damaged mitochondria, while the green arrows represent normal mitochondria (1500 × , scale bar: 5.0 μm; 5000 × , scale bar: 1.0 μm). (B) After 48 h transfection of HeLa and SiHa cells, Western blot assay was used to detect the changes in the relative expression levels of epoxide hydrolase 2, Glutathione peroxidase 4, ACSL4, and SCL7A11 proteins in HeLa and SiHa cells. (Comparison between two groups, * indicates statistical significance, **P < 0.01, ***P < 0.001, ****P < 0.0001).

https://doi.org/10.1371/journal.pone.0343495.g004

Western blotting was used to detect the expression of ferroptosis-related proteins to further confirm that EPHX2 induces ferroptosis in CESC cells. The results showed that overexpressing EPHX2 in HeLa cells could upregulate the relative expression levels of EPHX2 and ACSL4 and downregulate the relative expression levels of Glutathione peroxidase 4 (GPX4) and SCL7A11 proteins. EPHX2 knockout in SiHa cells could downregulate the relative expression levels of EPHX2 and ACSL4, while upregulating the relative expression levels of SCL7A11 and GPX4 proteins (Fig 4B). These results further confirm that EPHX2 induces ferroptosis in CESC cells.

Limonin can target and activate epoxide hydrolase 2 to inhibit the proliferation of HeLa cells

The effects of limonin on the proliferation of HeLa cells and protein expression of EPHX2 were also focused on in this study. The chemical structures (2D and 3D) and relative molecular masses of limonin are shown in S3 Fig. Then, surface plasmon resonance experiments were used to detect whether there was binding between limonin and EPHX2 at various concentrations. All the results were subjected to kinetic/affinity fitting analysis using a 1:1 model. The data were analyzed using the Biacore evaluation software, Biacore T200 Evaluation Software (Version 2.0). The results showed that there was binding between them, with a KD value of 10.33 μM (Fig 5A). The effects of limonin on the proliferative capacity of HeLa cells (in which EPHX2 is expressed at the lowest level compared to other cervical squamous cell carcinoma cells) and the EPHX2 protein were verified.

Download:

Fig 5. Limonin can target and activate epoxide hydrolas 2 to inhibit the proliferation of HeLa cells.

(A) Concentration-dependent sensorgram of Limonin binding to immobilized epoxide hydrolase (EPHX2). Limonin was injected at a series of concentrations (3.125 μmol/L to 100 μmol/L) onto the EPHX2-coupled sensor chip. (B) Cell Counting Kit-8 (CCK8) assay to detect the changes in cell viability of HeLa cells 48 h after treatment with different concentrations of Limonin (2.5, 5, 10, 20, 40, 80 μmol/L). (C) After adding different concentrations of Limonin (10, 20, 40 μmol/L) to HeLa cells, a Western blot assay was used to detect the changes in the relative expression level of EPHX2 protein in the cells. (D)The changes in sEH activity in HeLa cells treated with different concentrations of Limonin (10, 20, 40 μmol/L) for 48 hours were detected using an Enzyme-Linked Immunosorbent Assay kit. (E)The CCK8 assay was used to detect the changes in cell proliferation ability after treatment with Limonin (40 μmol/L) and transfection with small interfering ribonucleic acid (siRNA). (F) The 5-ethynyl-2′-deoxyuridine assay was used to detect the changes in cell proliferation ability after treatment with Limonin (40 μmol/L) and transfection with siRNA (200 × , scale bar: 100 μm). (Comparison between two groups, * indicates statistical significance, ns represents P > 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001).

https://doi.org/10.1371/journal.pone.0343495.g005

The CCK8 assay showed that limonin inhibited HeLa cell proliferation in a concentration-dependent manner, with a half-maximal inhibitory concentration (IC50) of 31.44 μmol/L (Fig 5B). Therefore, in subsequent experiments, concentrations near the IC50 (10, 20, 40 μmol/L) were selected to avoid interference from non-specific cytotoxicity due to high-concentration drugs on the experimental results. Also, this concentration is similar to that of limonin acting on breast cancer MDA-MB-435 cells (IC50 = 26 μmol/L) [18].

After treating HeLa cells with different concentrations of limonin (10, 20, 40 μmol/L), we observed that the relative expression level of the EPHX2 protein gradually increased with the increase in the concentration of limonin. The results showed that limonin activated EPHX2 protein expression in a concentration-dependent manner (Fig 5C). We also detected sEH activity in HeLa cells. The results showed that as the concentration of limonin increased, sEH activity gradually increased (Fig 5D). Further research showed that limonin inhibited the proliferative capacity of HeLa cells. However, EPHX2 knockdown counteracted the inhibitory effect of limonin on HeLa cell proliferation (Fig 5E and 5F). This indicates that limonin inhibits HeLa cell proliferation by targeting and activating EPHX2.

Limonin can target and activate epoxide hydrolase 2 to induce ferroptosis in HeLa cells

After confirming that limonin inhibits the proliferation of HeLa cells, we focused on the regulatory relationship between limonin and ferroptosis in HeLa cells. The results showed that limonin enhanced the relative fluorescence intensity of ROS, the content of MDA, promoted the accumulation of Fe²⁺ and the content of GSSG, and decreased the content of GSH and the GSH/GSSG ratio in HeLa cells. EPHX2 knockdown counteracted the changes in ferroptosis-related indicators induced by limonin (Fig 6A-6D). The detection of ferroptosis-related markers showed that limonin upregulated the relative expression levels of EPHX2 and ACSL4 and downregulated the relative expression levels of GPX4 and SCL7A11. However, EPHX2 knockdown could offset these changes (Fig 6E). Moreover, the increase in sEH activity induced by limonin treatment was suppressed by EPHX2 knockdown (Fig 6F). Changes were also observed in the mitochondrial structure. Limonin damaged the mitochondrial structure, and EPHX2 knockdown reversed this effect (Fig 6G). These results support the conclusion that limonin induces ferroptosis in HeLa cells by targeting and activating EPHX2.

Download:

Fig 6. Limonin can target and activate epoxide hydrolase 2 to induce ferroptosis in HeLa cells.

(A) Flow cytometry to detect the relative expression level of intracellular reactive oxygen species in SiHa cells after treatment with limonin (40 μmol/L) and transfection of small interfering ribonucleic acid. (B) Detection of changes in intracellular malondialdehyde content in HeLa cells. (C) Detection of changes in intracellular Fe²⁺ content in HeLa cells. (D) Detection of changes in intracellular reduced glutathione and glutathione disulfide contents and the reduced glutathione/oxidized glutathione disulfide ratio in HeLa cells. (E) Western blot assay in HeLa cells to detect the changes in the relative expression levels of epoxide hydrolase 2, glutathione peroxide, ACSL4, and SCL7A11 proteins. (F)The changes in soluble epoxide hydrolase activity in HeLa cells were detected by an Enzyme-Linked Immunosorbent Assay kit. (G) Observation of changes in the structure and morphology of intracellular mitochondria in HeLa cells by electron microscopy. The red arrows represent damaged mitochondria, while the green arrows represent normal mitochondria (1500 × , scale bar: 5.0 μm; 5000 × , scale bar: 1.0 μm). (Comparison between two groups, * indicates statistical significance, **P < 0.01, ***P < 0.001, ****P < 0.0001).

https://doi.org/10.1371/journal.pone.0343495.g006

Discussion

There are a few reports on ferroptosis in CESC. This may be associated with the differences in research hotspots. As a novel form of programmed cell death, the research progress of ferroptosis varies in different tumors [27]. This study used a unique research strategy, combining bioinformatics analysis with experimental verification, to accurately locate the target of limonin in CESC, EPHX2. This differs from previous research methods that relied solely on cell experiments or animal models, which may have caused differences in the accuracy of the research results. The occurrence of ferroptosis is caused by the synergistic action of multiple factors. SLC7A11 is a key subunit of System Xc ⁻ , responsible for transporting cystine into cells for the synthesis of GSH (reduced glutathione) [28]. GPX4 depends on GSH to reduce lipid peroxides (including phospholipid hydroperoxide and PLOOH) to nontoxic products, thus inhibiting the accumulation of lipid ROS. When GPX4 activity or GSH synthesis is inhibited, lipid peroxides (such as MDA) accumulate in large quantities, directly damaging the structure of the cell membrane [29,30]. There is no direct evidence indicating a regulatory relationship between EPHX2 and ferroptosis. This study showed that EPHX2 is essential for the proliferation and ferroptosis of CESC cells. Its expression level correlates negatively with cell proliferation and positively with susceptibility to ferroptosis. This may be associated with the regulatory effects of EPHX2 on intracellular iron metabolism and oxidative stress. EPHX2 can affect intracellular iron and ROS levels, thereby regulating ferroptosis.

Studies have shown that natural products have significant antitumor properties [31]. Molecular docking and SPR experiments indicated there are binding sites between Limonin and EPHX2. The effects of limonin on ferroptosis in CESC cells were explored in this study by activating EPHX2 protein expression. These results revealed that limonin inhibited the proliferation of CESC cells. In vitro experimental data showed that the half-maximal inhibitory concentration (IC₅₀) of limonin in HeLa cells was 31.44 μmol/L. Notably, this potency was similar to the drug concentrations of natural compounds reported in the literature, which have significant antitumor activities. For instance, the IC₅₀ of coniferyl aldehyde is 65.9 μmol/L [32], that of gallic acid is 80 μmol/L [33], and the IC₅₀ of apigenin is 35.89 μmol/L [34]. It should be emphasized that there were significant differences in the experimental conditions for different drugs. Therefore, the conclusions drawn from this study based on current experiments have some limitations and need to be explored further through in-depth experiments. Nevertheless, these findings have considerable reference value. Limonin differs from other drugs in its ability to inhibit cell proliferation. Most drugs inhibit cell proliferation by inducing apoptosis, while limonin mainly reduces the proliferative capacity of HeLa cells via the ferroptosis pathway. This characteristic shows the uniqueness of limonin and endows it with great potential for development in the field of antitumor drug research. Moreover, we also discovered that limonin can target and activate EPHX2 and induce ferroptosis in cells. Conversely, EPHX2 knockdown counteracted the pharmacological effects of limonin, confirming that limonin may induce ferroptosis by targeting and activating EPHX2/sEH. Notably, we discovered that activating EPHX2/sEH can induce ferroptosis and inhibit tumor growth, which contrasts with the mainstream view of promoting the use of sEH inhibitors in treating cancer. We believe that this discrepancy highlights the complexity of sEH function and its “context-dependence.” In cancers that are mainly driven by inflammatory and anti-apoptotic signals, inhibiting sEH may be effective. However, in cell models such as those used in this study, activating sEH becomes a vital switch that triggers the unique cell death program of ferroptosis. Thus, sEH can be regarded as a “two-sided” regulator, and its ultimate effect depends on the specific cellular environment and the dominant cell death pathway. This understanding is important for developing precise sEH-targeted therapies. Future strategies should rely on biomarkers to distinguish between patients suitable for treatment with sEH inhibitors and those who may benefit from sEH agonists. The anticancer effects of limonin aligned with those of previous reports. However, existing research has mainly focused on the effects of limonin on cancer cell invasion, migration, stemness, and apoptosis [35–38], and there is no research directly indicating the regulatory relationship between limonin and ferroptosis in cancer cells.

The novelty of this study lies in the first connection between limonin and ferroptosis in CESC and identifying EPHX2 as the key target of limonin. These findings provide new ideas for natural compound-based ferroptosis-targeted therapies. However, this study has some limitations. Our research is based on bioinformatics analysis and in vitro cell experiments. Therefore, it lacks further verification from in vivo animal experiments and clinical-related research. Additionally, an in-depth exploration of this mechanism is lacking. We have only confirmed that limonin can target and activate the expression of the EPHX2 protein; nevertheless, the pathway or route through which it induces ferroptosis remains unknown. Therefore, future research on limonin can be conducted in the following directions: First, we used animal models to evaluate the in vivo therapeutic effect of limonin on CESC and observed its effects on tumor growth, metastasis, and ferroptosis-related indicators. Second, we selected HeLa and SiHa cell lines to conduct subsequent overexpression and knockdown experiments. However, to enhance the universality and reliability of the research findings, it is reasonable to use more cell lines for verification. Third, the significant upregulation of EPHX2 gene expression by limonin is a phenomenon of great research value. However, there are key issues to be resolved. Whether this effect is achieved through direct activation of the EPHX2 promoter region or through indirect regulation remains unclear. In the future, we will conduct dual-luciferase reporter gene assays and chromatin immunoprecipitation experiments for verification. Moreover, with the development of nanotechnology, nanodrug carriers targeting EPHX2 can be designed to enhance the enrichment efficiency of limonin at the tumor site, improve its therapeutic effect, and reduce side effects. This is expected to become a new strategy for treating CESC.

Conclusion

This study identified EPHX2 as a target of limonin in CESC. Limonin can induce ferroptosis in CESC cells by activating the expression of EPHX2, thereby inhibiting cell proliferation. This finding offers a new potential target and drug option for treating CESC and opens up new ideas for natural-compound-based ferroptosis-targeted therapy.

Supporting information

S1 File. Raw images.

https://doi.org/10.1371/journal.pone.0343495.s001

(PDF)

S2 File. Raw material.

https://doi.org/10.1371/journal.pone.0343495.s002

(PDF)

S1 Fig. GO Functional Enrichment Analysis of Differentially Expressed Genes in the GSE63514 Dataset.

https://doi.org/10.1371/journal.pone.0343495.s003

(TIF)

S2 Fig. Verification of EPHX2 knockdown and over-expression and detection of sEH activity.

https://doi.org/10.1371/journal.pone.0343495.s004

(TIF)

S3 Fig. 2D and 3D chemical structures of Limonin and its relative molecular mass.

https://doi.org/10.1371/journal.pone.0343495.s005

(TIF)

S1 Table. QPCR primer sequence, EPHX2 interference sequence and EPHX2 overexpression sequence.

https://doi.org/10.1371/journal.pone.0343495.s006

(DOCX)

S2 Table. Western blotting Experimental reagent consumable material information.

https://doi.org/10.1371/journal.pone.0343495.s007

(DOCX)

Acknowledgments

I would like to thank my research team for working hard with me to complete this basic experiment. Every achievement we have made is the result of everyone’s hard work. I hope that we can keep up the good work, raise questions, discover problems and solve them, so as to better safeguard people’s health. Finally, I would like to thank every editor in the editorial department for their valuable suggestions. Thank you.

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Figures

Abstract

Introduction

Materials and methods

Data acquisition and preprocessing

Visualization analysis

Functional enrichment analysis

Subsequent gene screening

Cell culture

Cell transfection and cell grouping

Cell counting kit-8 assay

5-ethynyl-2’-deoxyuridine assay

Reactive oxygen species detection

Detection of Fe² ⁺, malondialdehyde, and total glutathione/glutathione disulfide content

Reverse transcription quantitative polymerase chain reaction assay

Western blot assay

Electron microscopy observation of mitochondrial morphology

Soluble epoxide hydrolases activity detection

Surface plasmon resonance

Statistical analysis

Results

Identification of epoxide hydrolase 2 as a potential drug target of limonin among differentially expressed genes in cervical cancer

Epoxide hydrolase 2 inhibits the proliferation of HeLa and SiHa cells

Epoxide hydrolase 2 induces ferroptosis in HeLa and SiHa cells

Limonin can target and activate epoxide hydrolase 2 to inhibit the proliferation of HeLa cells

Limonin can target and activate epoxide hydrolase 2 to induce ferroptosis in HeLa cells

Discussion

Conclusion

Supporting information

S1 File. Raw images.

S2 File. Raw material.

S1 Fig. GO Functional Enrichment Analysis of Differentially Expressed Genes in the GSE63514 Dataset.

S2 Fig. Verification of EPHX2 knockdown and over-expression and detection of sEH activity.

S3 Fig. 2D and 3D chemical structures of Limonin and its relative molecular mass.

S1 Table. QPCR primer sequence, EPHX2 interference sequence and EPHX2 overexpression sequence.

S2 Table. Western blotting Experimental reagent consumable material information.

Acknowledgments

References