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. 2025 Nov 23;15:45195. doi: 10.1038/s41598-025-29411-6

Integration of transcriptomics and metabolomics reveals the mechanism of Lycium barbarum polysaccharides inhibited MCF-7 cell proliferation

Liyang Ding 1,#, Yitong Shang 1,#, Zhen Zhang 1, Hong Yang 1, Yu Deng 1, Tiantian He 1, Guoqin Yang 1, Jiaxue Ma 1, Xufeng Fu 1,✉, Xing Du 1,✉
PMCID: PMC12748708  PMID: 41276638

Abstract

Breast cancer, as a highly prevalent malignant tumor among women, has a consistently high mortality rate due to metastasis and drug resistance. Lycium barbarum polysaccharides (LBP), which have been reported to have significant anti-tumor activity, have not yet had their molecular mechanism and signaling pathways against breast cancer clearly defined. In this study, the CCK-8 experiment determined that 8 mg/mL LBP treatment for 48 h was the optimal condition for subsequent transcriptomics and metabolomics analyses. The results demonstrated that a high concentration of LBP significantly reduced the viability of MCF-7 cells and inhibited cell proliferation. Transcriptome sequencing revealed that LBP markedly altered the expression levels of the genes HO-1, FTH1, FTL, and TFRC. Metabolomics analysis further indicated that LBP significantly impacted glutathione metabolism, glycerophospholipid metabolism, and the alanine-aspartate-glutamate metabolic pathway. Further integration of transcriptomic and metabolomic data suggests that LBP may suppress cell proliferation by activating the ferroptosis pathway via the NRF2/HO-1 axis. To further validate this hypothesis, we conducted additional experiments to detect the NRF2/HO-1 signaling pathway and markers associated with ferroptosis. The results demonstrated that LBP treatment significantly upregulated the expression of NRF2 and its downstream effector molecule HO-1. Moreover, the specific NRF2 inhibitor ML385 was able to reverse the alterations in GSH, Fe2+, and MDA levels induced by LBP. In conclusion, our research results indicate that LBP induces ferroptosis by activating the NRF2/HO-1 signaling pathway.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-29411-6.

Keywords: Lycium barbarum polysaccharide, Breast cancer cells, Transcriptomics, Metabolomics, Ferroptosis

Subject terms: Biochemistry, Cancer, Cell biology, Molecular biology, Oncology

Introduction

The incidence of breast cancer has exceeded that of lung cancer, making it the most prevalent malignant tumor among women globally. According to data published by Global Cancer Observatory in 2022, breast cancer represents 12.7% of all newly diagnosed cancer cases and ranks fourth in terms of global cancer mortality1. Based on the differential expression of cellular molecular markers, breast cancer molecular subtyping is primarily categorized into three distinct groups: hormone receptor-positive (ER or PR positive expression), human epidermal growth factor receptor 2-positive (HER2+), and triple-negative breast cancer (TNBC)2. The clinical manifestations of breast cancer exhibit marked phase-specific characteristics. In the early stages of the disease, the primary manifestations include localized breast signs, such as painless breast masses, characteristic skin changes, unilateral nipple hemorrhagic discharge, and ipsilateral axillary lymph node enlargement. As the disease advances, systemic symptoms may progressively emerge, including anorexia, weight loss, fatigue, anemia, and other related manifestations. Metastasis typically occurs in areas such as the lungs, pleura, bones, liver, and brain3. Owing to the highly invasive and heterogeneous nature of breast cancer, conventional treatment approaches for this disease encompass chemotherapy, radiotherapy, targeted therapy, immunotherapy, and endocrine therapy, both as neoadjuvant and adjuvant treatments to surgery4. However, these conventional treatment strategies often fall short in addressing the high metastatic potential and drug resistance of breast cancer cells, thereby exhibiting limitations in the effective clinical management of breast cancer. Therefore, the development of targeted therapeutic strategies with innovative mechanisms of action, as well as novel anti-tumor drugs, has emerged as a critical research direction for inhibiting the malignant progression of breast cancer and enhancing patient prognosis.

With the advancement of modern technology, the application value of plant-derived natural products in tumor treatment has become increasingly significant. Current studies have confirmed that various plant extracts exhibit substantial anti-tumor activities by specifically regulating tumor cell cycles, inducing apoptosis, and inhibiting angiogenesis, such as paclitaxel, camptothecin, synstatin, epigallocatechin gallate, and vinca alkaloids5. Traditional Chinese herbal medicines have emerged as a significant research focus in the field of natural drugs, primarily due to their demonstrated anti-cancer activities. Notably, Lycium barbarum, a representative medicinal material with over two thousand years of documented medicinal use, has garnered substantial attention. Modern pharmacological investigations have revealed that Lycium barbarum polysaccharides (LBP) constitute water-soluble glycan-coupled bioactive substances isolated and purified from Lycium barbarum. Advanced separation and analytical techniques have further elucidated that wolfberry contains a diverse array of key active components, including acidic heteropolysaccharides, polypeptides, six types of monosaccharides, and eighteen amino acids6. These key active ingredients in Lycium barbarum confer upon it a broad spectrum of pharmacological activities, including anti-aging, anti-tumor, anti-inflammatory, antioxidant, immunomodulatory, and neuroprotective effects7. LBP suppresses the growth of mouse liver cancer H22 cells by inducing apoptosis, disrupting mitochondrial membrane potential, and causing S-phase cell cycle arrest8. LBP treatment significantly suppressed the proliferation of human gastric cancer cells (MGC-803 and SGC-7901) and induced cell cycle arrest at the G0/G1 phase in MGC-803 cells and the S phase in SGC-7901 cells9. In addition, LBP has been demonstrated to induce DNA strand breaks in human prostate cancer cells, specifically PC-3 and DU-145 lines, and significantly promote apoptosis in these cells10. However, the detailed mechanism underlying the tumor-inhibitory effect of LBP remains to be fully elucidated.

The compounds extracted from plants contain numerous active components and exhibit complex mechanisms of action, necessitating the application of advanced analytical methodologies to elucidate their effects on diseases. The utilization of high-throughput transcriptomics technology has significantly enhanced our scientific comprehension of the molecular classification of breast cancer. Through the analysis of dynamic alterations in gene expression during the initiation and progression of breast cancer, it is feasible to identify differentially expressed genes as well as novel biomarkers associated with tumor development11.Researchers identified the key regulatory factors and abnormal signaling pathways in breast cancer by integrating transcriptomic analysis with characteristic profiling12.Metabolomics emerged from the early investigations of metabolite analysis and has since evolved into a rapidly advancing discipline within the field of life sciences. Research has identified more than 30 endogenous metabolites that exhibit significant differences in breast cancer tissues. Notably, choline levels are elevated in the tissues of breast cancer patients, whereas the contents of glycerophosphate choline and glucose are significantly reduced13.Analysis of key metabolic pathways revealed significant upregulation in breast cancer tissues within several critical pathways, including glutamine metabolism, lipid and fatty acid synthesis, the glutamine-serine pathway, protein translation, and cholesterol metabolism14. Therefore, this study explored the novel mechanism by which LBP regulates the fate of breast cancer cells through the integration of transcriptomic and metabolomic analyses, and verified it through in vitro study, providing an important basis for a deeper understanding of the anti-cancer effects and potential mechanisms of natural products.

Materials and methods

Materials

Lycium barbarum polysaccharide (LBP) was obtained from Shanghai Yuanye Biotechnology Co. (Shanghai, China). The human breast cancer cell line Michigan Cancer Foundation-7 (MCF-7) was acquired from the Cell Bank of the Chinese Academy of Sciences in Shanghai. The Radio Immunoprecipitation Assay (RIPA) lysis and extraction buffer, as well as the BCA protein assay kit, were sourced from KeyGEN Biotech (Nanjing, China).

Cell culture and LBP treatment

MCF-7 cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM; Gibco BRL, Grand Island, NY, USA) supplemented with 10% (v/v) fetal bovine serum (FBS; Gibco) and 1% (v/v) penicillin/streptomycin solution (Gibco). Cells were incubated in a humidified atmosphere containing 5% CO2 at 37 °C. The MCF-7 cells were cultured until they reached approximately 80% confluence, after which the medium was refreshed, and the cells were passaged every 2 to 3 days. For treatment, the LBP working solutions were diluted with DMEM to achieve the desired final concentrations for testing, while the control group was cultured in DMEM alone for 24 h.

Viability assays

A Cell Counting Kit-8 (CCK-8) assay was utilized to evaluate the viability of cells. Specifically, MCF-7 cells were seeded in 96-well plates at a density of 5,000 cells per well and incubated for 24 h. Thereafter, the cells were treated with LBP at various concentrations (1, 2, 4, 8, and 10 mg/mL) for 48 h. Following the treatment, 10 µL of CCK-8 detection reagent was added to each well and incubated at 37 °C for 2 h. The optical density (OD) absorbance values of the wells were subsequently measured at 450 nm using a microplate reader (Thermo Scientific, Boston, USA). Cell viability was expressed as a percentage relative to the absorbance of the control group. The mean value of three independent experiments was calculated to assess the impact of LBP on the viability of breast cancer cells.

EdU assay

EdU detection was carried out using an EdU detection kit following the manufacturer’s instructions. The EdU solution was diluted at a ratio of 1:1000 in cell culture medium to prepare a working solution of 10 µM. Cells in the logarithmic growth phase were seeded at a density of 4 × 104 cells per well in a 24-well plate. Following 48 h of LBP treatment, the cells were incubated with the 10 µM EdU medium for 2 h. Subsequently, the cells were fixed with 4% formaldehyde for 30 min, rinsed with PBS, and then stained with fluorescent dye and DAPI nuclear stain. Thereafter, anti-fluorescence quenching mounting medium was added dropwise to the sections, and the samples were examined and imaged under a fluorescence microscope (magnification: ×20; Olympus Corporation). The number of EdU-labeled cells was quantified using ImageJ software15, with red-stained nuclei considered positive. Positive and negative cells were counted in three randomly selected fields under the fluorescence microscope.

Oxidative stress assessment

To evaluate the oxidative stress status of the cells, commercially available assay kits from Nanjing Jiancheng Bioengineering Research Institute (Nanjing, China) were utilized to measure the levels of malondialdehyde (MDA, A003-1), reduced glutathione (GSH, A001-3), and total antioxidant capacity (T-AOC, A015-2-1). The samples were pre-cooled with PBS, lysed by ultrasonication, and centrifuged at 12,000 rpm for 15 min to obtain the supernatant. A standard curve was constructed according to the instructions, and the absorbance was measured using an enzyme reader after adding the reaction reagents. The concentrations/activities of each indicator were calculated to evaluate the degree of oxidative stress.

Ferrous content determination

The intracellular ferrous ion (Fe2+) levels were quantified using the Nanjing Jianjian Bioengineering Institute ferrous ion quantification kit (A039-2-1). The Fe²⁺ in ferritin was dissociated under acidic conditions, and after reduction with ascorbic acid, it formed a pink complex with bipyridine. The colorimetric method was used for analysis. After centrifugation at 12,000 rpm of the cell lysate, the supernatant was taken. The reagents were mixed according to the kit ratio, and the absorbance was measured using a microplate reader (Thermo Scientific, Boston, USA). The Fe²⁺ concentration was calculated based on the standard curve to reflect the cell content.

Immunofluorescence analysis

After the cells were treated with LBP and ML385 for 48 h, they were incubated with pre-warmed fluorescent probes at 37 °C and 5% CO2 for 30 min under constant temperature conditions. During this period, cell activity was periodically monitored via microscopic examination. Following incubation, the cells were fixed with 4% paraformaldehyde at room temperature for 15 min and subsequently stained with DAPI for 5 min in a light-protected environment. After being washed three times with PBS (5 min per wash), fluorescence changes in the cells were observed under a fluorescence microscope.

Western blotting analysis

MCF-7 cells were treated with 2.5 g/L trypsin and washed three times with PBS, The cells were lysed in radioimmunoprecipitation assay (RIPA) buffer supplemented with phenylmethanesulfonyl fluoride (PMSF) at a ratio of 1:100 (v/v) to extract total protein. The lysis buffer was centrifuged at 12,000 rpm for 15 min at 4 °C, and the supernatant was taken to determine the protein concentration by BCA method. The protein was denatured by boiling and separated by 12.5% SDS-PAGE (120 V). The membrane was transferred to PVDF membrane and incubated for 2 h at 400 V. The membrane was blocked with 5% skimmed milk-TBST for 2 h at 4 °C, incubated with primary antibody (1:1000) overnight, washed with TBST, and incubated with HRP-labeled secondary antibody at room temperature for 1 h. Protein signals were detected using an enhanced chemiluminescence (ECL) detection kit (Thermo Scientific) and visualized with a fluorescence imaging system (Thermo Scientific). Band intensities were quantified using ImageJ software to determine grayscale values. Representative images were selected from at least three independent experiments.

Transcriptome sequencing and analysis

Total RNA was extracted from both the control group and the 8.0 mg/mL LBP-treated group (n = 3 per group) using TRIzol reagent (TaKaRa, China), strictly adhering to the manufacturer’s protocol. All RNA samples were subsequently subjected to sequencing, which was performed by Xuanchen Biotechnology Co., Ltd. (Shaanxi, China). RNA purity was measured using a NanoPhotometer spectrophotometer (Implen, CA, USA), and RNA integrity was assessed using the Bioanalyzer 2100 system (Agilent Technologies, CA, USA). Following this, sequencing libraries were constructed using the Illumina-specific RNA library preparation kit (New England Biolabs (NEB), USA), again in strict accordance with the manufacturer’s instructions. The library preparation procedure involved the following steps: messenger RNA (mRNA) was first enriched from total RNA using magnetic beads conjugated with oligo(dT). First-strand complementary DNA (cDNA) synthesis was then carried out using random hexamers as primers in the presence of reverse transcriptase (containing ribonuclease H, RNase H). Subsequently, second-strand cDNA synthesis was performed using DNA polymerase I and RNase H. Finally, the quality of the resulting PCR products (library fragments) was evaluated using the Agilent Bioanalyzer 2100 system. Libraries meeting quality standards were sequenced on the Illumina Novaseq platform following the standard sequencing procedure. Differentially expressed genes (DEGs) were identified based on |log2(FoldChange)| > 1 and padj ≤ 0.05. Subsequently, GO functional enrichment analysis and KEGG pathway analysis were conducted.

Enrichment analysis of the differential expressed genes

The clusterProfiler software16 was employed to conduct Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the differentially expressed gene sets. GO terms and KEGG pathways with adjusted p-values (padj) less than 0.05 were considered significantly enriched.

Differential analysis of metabolomics data

200 µL of water was added to the sample, followed by vortexing the mixture, freeze-thawing with liquid nitrogen, and sonication. Subsequently, 50 µL of the sample was taken for protein quantification. The sample was subsequently treated with a mixture of acetonitrile and methanol (1:1, v/v), followed by vortex mixing, incubation, and centrifugation. The supernatant was carefully collected, vacuum-dried, and then redissolved in an equivalent volume of isotope-labeled internal standard solution. The resulting mixture was vortexed, sonicated, and centrifuged again, and the final supernatant was transferred to a glass vial for further analysis. LC-MS/MS analyses were conducted using a UHPLC system (Vanquish, Thermo Fisher Scientific) equipped with a UPLC BEH Amide column (2.1 mm × 100 mm, 1.7 μm), which was coupled to a Q Exactive HFX mass spectrometer (Orbitrap MS, Thermo). The mobile phase comprised 25 mmol/L ammonium acetate and 25 mmol/L ammonia hydroxide in water (pH 9.75) as solvent A, and acetonitrile as solvent B. The autosampler temperature was maintained at 4 °C, with an injection volume of 3 µL. The QC sample is prepared from an equal mixture of all the samples to be tested. The raw data were normalized, and an orthogonal partial least squares discriminant analysis (OPLS-DA) model was established to support pattern recognition. Metabolites showing significant differences were identified based on variables with a VIP (Variable Importance in the Projection) value greater than 1.0 and a p-value less than 0.05, following Student’s t-test correction within the OPLS-DA model. Differentially expressed metabolites were annotated according to metabolic pathways using the Human Metabolome Database (HMDB)17 and the Kyoto Encyclopedia of Genes and Genomes (KEGG)18,19. Furthermore, metabolic pathway enrichment analysis was carried out using the MetaboAnalyst 5.0 platform20, with a false discovery rate (FDR) threshold set at less than 0.05.

Data integration and visualization

Cluster heatmaps were generated using bioinformatic analysis tools. The analysis was conducted using the OmicStudio platform (https://www.omicstudio.cn/tool). Hierarchical clustering was applied to the rows (genes), employing complete linkage as the clustering method and Euclidean distance to measure similarity. Gene expression values were normalized using row-wise Z-score transformation.

To visually illustrate the significant correlations between differentially expressed genes and key metabolites identified in this study, a correlation network was constructed and visualized. This network was based on the top 10 key genes and the top 10 differentially expressed metabolites associated with ferroptosis, with correlations calculated using Spearman’s correlation coefficient. The network diagram was generated using the OmicStudio tool21. In the visualization, line type and color indicate positive or negative correlations, respectively; line thickness reflects the strength of the correlation; and the size and color of nodes represent the number of associated correlations.

Statistical analysis

For the quantitative analysis of protein expression levels, the expression of target proteins and β-actin was quantified using ImageJ software. The relative expression levels of target proteins were normalized to β-actin and are expressed as mean ± standard deviation (SD), analyzed using GraphPad Prism version 9.0 (GraphPad Software, San Diego, California, USA; www.graphpad.com). Prior to statistical analysis, normality tests were conducted. Appropriate parametric or non-parametric tests were selected based on data distribution to evaluate intergroup differences. For comparisons involving multiple groups, one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test or two-way ANOVA was applied, as appropriate. Statistical significance was set at p < 0.05, with highly significant differences defined as p < 0.01. All key experimental results were confirmed through three independent biological replicates.

Results

LBP affects the proliferation of MCF-7 cells

To investigate the effect of LBP on the proliferation of MCF-7 cells, MCF-7 cells were exposed to a series of concentrations of LBP (0, 1, 2, 4, 8, and 10 mg/mL) for 48 h (Fig. 1A). CCK-8 assay showed that the cell survival rate decreased in a dose-dependent manner following LBP treatment (Fig. 1B). Specifically, when the LBP concentration exceeded 4 mg/mL, a significant reduction in MCF-7 cell viability was observed. Furthermore, the results of EdU proliferation detection validated that LBP at a concentration of 4 mg/mL effectively suppressed the proliferation of MCF-7 cells (Fig. 1C). Collectively, these findings suggest that LBP treatment at concentrations greater than 4 mg/mL markedly inhibits both the viability and proliferation of MCF-7 cells.

Fig. 1.

Fig. 1

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LBP affects the proliferation of MCF-7 cells. (A) Schematic diagram of this study protocol.This figure was drew with Figdraw. (B) CCK8 assay for cell viability at different LBP concentrations (n = 10). (C) The proliferation of MCF-7 cells after LBP treatment was detected by EdU. *p < 0.05, **p < 0.01.

The influence of LBP on the transcriptome profile of MCF-7 cells

To elucidate the mechanism by which LBP inhibits the proliferation of MCF-7 cells, the transcriptome profile of LBP on MCF-7 cells was analyzed. Principal component analysis (PCA) identified substantial differences in gene expression within the LBP group at a concentration of 8 mg/mL (Fig. 2A). Based on the results of the analysis, a total of 28,201 genes were detected between the control group and the LBP group. There were 1,318 genes with significant differential expression, among which 686 genes were significantly upregulated and 632 genes were significantly downregulated (Fig. 2B and C). Furthermore, hierarchical clustering heatmap analysis provided a visual representation of the interactions among these DEGs (Fig. 2D). To comprehensively elucidate the biological significance of LBP on MCF-7 cells, Gene Ontology (GO) analysis was performed on the DEGs. The results demonstrated that in biological processes, DEGs were significantly enriched in categories such as cellular processes, biological regulation, metabolic processes, and multicellular biological processes. In terms of cellular components, DEGs were predominantly enriched in cell structures including cells, cellular parts, organelles, membranes, membrane-bounded compartments, and cellular junctions. Regarding molecular functions, DEGs were highly enriched in pathways associated with catalytic activity, molecular function regulation, structural molecule activity, transcription factor activity, and protein binding (Fig. 2E and F). These findings suggest that LBP influences the proliferation of MCF-7 cells through its involvement in biological processes, cellular components, and molecular functions.

Fig. 2.

Fig. 2

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Transcriptomic analysis of MCF-7 after LBP treatment. (A) Principal component analysis (PCA) of transcriptomics between Control and LBP groups (n = 3 for each group). (B) Volcano plots of differentially expressed genes (DEGs) between Control and LBP groups. Up-regulated genes are shown in red and down-regulated genes are shown in blue. (C) Bar chart of differential genes. (D) Heatmap of DEGs between Control and LBP groups (n = 3). Gene ontology (GO) analysis of differentially up-regulated (E) and down-regulated (F) genes. In the GO analysis diagram of the whole prescription, the higher the band height is, the more significant it is. Dates were presented as the mean ± SD. *p < 0.05, ** p < 0.001.

Enrichment analysis of the KEGG pathway of DEGs

Furthermore, a KEGG enrichment analysis was performed on the DEGs. The results indicated that the upregulated DEGs were associated with pathways such as the cell cycle, cAMP signaling pathway, and steroid hormone biosynthesis (Fig. 3A). In contrast, the downregulated DEGs were linked to pathways including the p53 signaling pathway, MAPK signaling pathway, and cytochrome P450-mediated xenobiotic metabolism (Fig. 3B). Further annotation of differentially expressed gene pathways revealed that the ferroptosis signaling pathway was significantly enriched among the top 20 pathways (Fig. 3C). Gene Set Enrichment Analysis (GSEA) further confirmed that the glutathione metabolic pathway was substantially activated (Fig. 3D). Protein interaction network analysis identified a ferroptosis regulatory module centered on HO-1 as the core node, which formed a tightly interconnected network with genes such as FTL, FTH1, and TFRC (Fig. 3E). The hierarchical clustering heat map indicates that the genes within this module are significantly upregulated in the LBP-treated group (Fig. 3F). These findings strongly suggest that LBP may regulate the fate of MCF-7 cells via the ferroptosis pathway.

Fig. 3.

Fig. 3

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Enrichment analysis of the KEGG pathway for DEGs. (A) Classification of KEGG pathways for upregulated DEGs. (B) Classification of KEGG pathways for downregulated DEGs. (C) Bubble plot of KEGG enrichment analysis. KEGG pathway map courtesy of Kanehisa Laboratories. The bubble size represents the number of enriched genes, and the bubble color represents the significant magnitude of target gene enrichment. (D) Gene Set Enrichment Analysis (GSEA) for the potential altered pathways in the LBP groups compared to the Control. GSEA analysis revealed significant activation of the glutathione metabolic pathway. (E) Analysis of protein-protein interaction networks among genes. (F) Heatmap of significantly enriched gene expression. Red represents high expression, and blue represents low expression.

The effect of LBP on the metabolomic profile of MCF-7 cells

To investigate the effects of LBP on the metabolism of MCF-7 cells, metabolomics analysis was performed on both the control group and the LBP-treated group. The results of principal component analysis (PCA) indicated that there was a significant separation in the cell metabolic profiles between the control group and the LBP-treated group (Fig. 4A), suggesting that the metabolic states of the cells in the two groups were significantly different. The metabolites influencing the differential expression of MCF-7 cells upon treatment with LBP were identified through the construction of volcano plots, a total of 255 metabolites exhibited significant differences between the two groups, with 196 metabolites being upregulated and 59 metabolites being downregulated (Fig. 4B). To characterize the differentially expressed metabolites, we depicted their up- and down-regulation, along with the top ten metabolites showing the most significant changes (Fig. 4C).Additionally, a clustered heatmap displayed the changing trends of these metabolites in both the control and LBP groups (Fig. 4D).Pathway enrichment analysis of the differential metabolites demonstrated that these metabolites were predominantly enriched in glycerophospholipid metabolism, arginine and proline metabolism, as well as alanine, aspartate, and glutamate metabolic pathways (Fig. 4E). Furthermore, metabolite set enrichment analysis provided additional evidence, confirming significant enrichment in glutathione metabolism and the metabolic pathways of cysteine and methionine (Fig. 4F). Ferroptosis is an iron-dependent form of programmed cell death that is characterized by excessive intracellular iron accumulation, leading to lethal levels of lipid hydroperoxide accumulation. The metabolic pathways involving iron, lipids, amino acids, and glutathione play a critical role in regulating the initiation and execution of ferroptosis22. Therefore, the metabolomics analysis suggests that LBP may influence the proliferation of MCF-7 cells via the ferroptosis related metabolic pathway.

Fig. 4.

Fig. 4

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Metabolomics analysis of MCF-7 cells following LBP treatment. (A) Partial Least Squares-Discriminant Analysis (PLS-DA) score plots of metabolomic data in the Control and LBP groups (n = 3 for each group). (B) Volcano plots depicting differential metabolites between the Control and LBP groups. Up-regulated metabolites are shown in red and down-regulated metabolites are shown in blue. Bar charts (C) and heatmaps (D) of differential metabolites between the Control and LBP groups(n = 3).Red represents high expression, and blue represents low expression. (E) Pathway analysis overview of Control and LBP groups metabolomics (the size of each bubble represents the number of hits or significant metabolites within a pathway. Larger bubbles indicate pathways with more impacted metabolites, highlighting their biological relevance. Bubble color represents the statistical significance of the metabolic pathways). (F) Bar charts of enriched pathways for the differential metabolites between the Control and LBP groups. Dates were presented as the mean ± SD. *p < 0.05, ** p < 0.001.

Integrated analysis of metabolomics and transcriptomics

To comprehensively elucidate the mechanism by which LBP influences MCF-7 cells, transcriptomic and metabolomic data were integrated and subjected to a thorough analysis. The findings revealed that differentially expressed genes (DEGs) and differentially expressed metabolites (DEMs) exhibited substantial co-enrichment characteristics in both the ferroptosis pathway and the glutathione metabolic pathway (as shown in Fig. 5A). The clustering heatmap reveals a significant correlation in expression between the core regulatory genes of ferroptosis and key metabolites (Fig. 5B). Spearman correlation network analysis reveals that there were significant correlation nodes between the top 10 key genes related to ferroptosis and the top 10 differential metabolites (Fig. 5C). The results of this integrated analysis reveal that the differential metabolites identified via screening establish a multi-dimensional interaction with the core regulatory network of ferroptosis through the glutathione metabolic pathway. This suggests that LBP may influence the ferroptosis process in MCF-7 cells through a metabolism-gene expression co-regulatory mechanism.

Fig. 5.

Fig. 5

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Integrated transcriptome and metabolome analysis of the effect of LBP on the proliferation of MCF-7 cells. (A) Integrated analyses of differential metabolites and genes by joint-pathway analysis. (B) Correlation heatmaps between DEGs and DEMs. (C) Correlation network diagram between TOP 10 DEGs and DEMs.

LBP induces ferroptosis in MCF-7 cells through NRF2/HO-1 pathway

Our previous study demonstrated that NRF2 plays a significant role in the process of ferroptosis23,24. Heme oxygenase 1 (HO-1) serves as one of the primary effectors in NRF2-dependent cellular responses and is widely recognized as a critical target for the prevention and treatment of cancer25,26. Therefore, we hypothesized that the inhibition of breast cancer cell growth by LBP may be attributed to ferroptosis mediated through the NRF2/HO-1 signaling pathway. To validate this hypothesis, we employed an NRF2 inhibitor (ML385) for intervention and subsequently detected biomarkers associated with ferroptosis. The Western Blotting results showed that, compared with the control group, LBP treatment significantly upregulated the protein expression levels of NRF2 and its downstream effector molecule HO-1. Conversely, ML385 was able to reverse the altered expression levels of these proteins (Fig. 6A and D). Additionally, the further application of siRNA to knock down NRF2 expression provided confirmatory evidence that the suppression of NRF2 led to decreased expression levels of both NRF2 and HO-1 (Fig. 6B, C, and E). In addition, the cytoplasmic and mitochondrial levels of Fe2+ were detected using FerroOrange and MitoFerroGreen fluorescent probes, respectively. The results showed that ML385 treatment markedly suppressed the LBP-induced accumulation of Fe2+ in the cytoplasm and mitochondria (Fig. 6F and G). Moreover, the analysis of key oxidative stress markers revealed that ML385 partially restored the alterations in glutathione (GSH), total antioxidant capacity (T-AOC), malondialdehyde (MDA), and Fe2+ levels triggered by LBP (Fig. 6H–K). Collectively, these findings suggest that the NRF2/HO-1 signaling pathway serves as a central regulatory mechanism in LBP-induced ferroptosis.

Fig. 6.

Fig. 6

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LBP induces ferroptosis in MCF-7 cells through the NRF2/HO-1 pathway. (A) NRF2 and HO-1 expression after LBP and ML385 (NRF2 inhibitor) treatment. (B) Quantitative analysis in (A), n = 3. (C) The expression of NRF2 and HO-1 after treatment with three SiRNAs (Si2226, Si1498, Si1439) targeting NRF2. (D) NRF2 and HO-1 expression after LBP and Si2226 (SiRNAs of NRF2) treatment. (E) Quantitative analysis in (D), n = 3. The Fe2+ levels in the cytoplasm (F) and mitochondria (G) after LBP and ML385 treatment, scale bar: 100 μm. The levels of MDA (H), GSH (I), T-AOC (J), and Fe2+ (K) after LBP and ML385 treatment. Data were expressed as Mean ± SD. *p < 0.05, **p < 0.01.

Discussion

Natural products have emerged as a crucial source for the research and development of anti-tumor drugs, attributed to their unique chemical diversity and multi-target biological activities. In contrast to chemically synthesized drugs, plant-derived natural compounds generally demonstrate superior biological safety and reduced systemic toxicity. Consequently, the investigation of their anti-tumor mechanisms has become a prominent research focus in the field of drug discovery27. Lycium barbarum polysaccharides (LBP), as a natural product with potential anti-cancer activity, primarily induce non-apoptotic cell death via their mechanisms of action. Research has demonstrated that numerous natural active compounds can effectively trigger ferroptosis in both in vitro and in vivo tumor models28. Existing studies indicate that LBP in combination with various anti-cancer drugs can significantly enhance therapeutic efficacy. LBP can strengthen the anti-breast cancer effect of doxorubicin and effectively alleviate the immune toxicity caused by doxorubicin29; LBP in synergy with interferon-α (IFN-α) can significantly promote tumor cell death30; LBP reduces the resistance of colon cancer cells to oxaliplatin31. These studies suggest that LBP not only exhibits anti-cancer effects but also can serve as a potential adjuvant treatment strategy for cancer. Additionaly, this study found that LBP could significantly induce ferroptosis in human breast cancer MCF-7 cells. This study not only uncovers a novel mechanism through which LBP modulates the death pathway of tumor cells but also establishes a critical theoretical framework for elucidating its multi-target anti-cancer mechanism.

In this study, we examined the effects of varying concentrations of LBP on the human breast cancer cell line MCF-7. The findings demonstrated that LBP exerted a concentration-dependent inhibitory effect on MCF-7 cells. Notably, when the treatment concentration surpassed 4 mg/mL, it significantly suppressed cell proliferation.This is consistent with our previous research conducted by our team32. Additionally, a study have revealed that the viability and proliferation of human colon cancer SW480 and Caco-2 cells were markedly affected by treatments of 400 mg/L and 200 mg/L LBP for 24 h33. The dose of 6.25 mg/L of LBP exhibits a significant inhibitory effect on the proliferation of human cervical cancer cells (HeLa cells)34. Moreover, Different concentrations of LBP (1 mg/mL, 2 mg/mL, and 4 mg/mL) exhibited a dose-dependent inhibitory effect on the proliferation of vascular smooth muscle cells35. Treatment with LBP at a concentration of 100 mg/L has been shown to inhibit the growth of human hepatoma QGY7703 cells, arrest the cell cycle in the S phase and induce apoptosis36. These studies suggest that the concentration in this study falls within an appropriate range for application. Additionally, the sensitivity of different cell types to LBP exhibits minor variations. These findings further reinforce the validity of the concentration we have chosen. Consequently, we determined a concentration of 8 mg/mL of LBP for comprehensive analysis through transcriptomics and metabolomics techniques.

In this study, a total of 686 significantly upregulated and 632 significantly downregulated DEGs were identified through transcriptomics analysis, which are associated with the effects of LBP on the proliferation of MCF-7 cells. Further GO functional annotation revealed that these DEGs play a significant role in regulating the biological processes, cellular components, and molecular functions of MCF-7 cells. Combined analysis of KEGG pathway enrichment and GSEA demonstrated that the ferroptosis and glutathione metabolic pathways exhibited significant enrichment characteristics. Similarly, a transcriptomic study found that the protective effect of Lycium barbarum glycopeptide (LbGp) on D-galactose-induced accelerated aging mice was associated with the glutathione metabolism pathway37. Lycium barbarum polysaccharide inhibits the growth and cell-cycle in human gastric cancer cells9.Additionally, the protein-protein interaction network constructed in this study identified iron metabolism-related genes, such as HMOX1 (HO-1), FTH1, FTL, and TFRC, as core hub nodes. These findings suggest that LBP may influence tumor progression by modulating cellular iron homeostasis. Heme oxygenase-1 (HO-1) is one of three isoforms within the heme oxygenase family. As the rate-limiting enzyme in heme catabolism, HO-1 catalyzes the conversion of heme into free iron, carbon monoxide (CO), and biliverdin38. The free iron ions catalyzed by HO-1 facilitate the production of reactive oxygen species (ROS) via the Fenton reaction, while depleting glutathione (GSH) and leading to the inactivation of glutathione peroxidase 4 (GPX4). Collectively, these processes exacerbate lipid peroxidation accumulation and ultimately induce ferroptosis, an irreversible form of regulated cell death39. NRF2, a key transcription factor in the oxidative stress response, is phosphorylated and activated under conditions of ROS accumulation or endoplasmic reticulum stress, followed by translocation into the nucleus. It orchestrates a cellular defense network by modulating the expression of target genes, including HO-1, glutamylcysteine ligase regulatory subunit (GCLM), glutamylcysteine ligase catalytic subunit (GCLC), solute carrier family 7 member 11 (SLC7A11), and ferritin heavy chain 1 (FTH1). The NRF2-mediated positive regulation of HO-1 establishes a self-reinforcing antioxidant protection mechanism, which may serve as a critical molecular basis for tumor cells to acquire survival advantages40. Clinical evidence demonstrates that HO-1 exhibits an abnormally elevated expression profile in various malignant tumors, and its overexpression is strongly correlated with increased tumor invasiveness, treatment resistance, and unfavorable prognosis41. Furthermore, numerous studies have consistently demonstrated that HO-1 plays a crucial role in modulating the proliferation of breast cancer cells42,43. The activation of the NRF2/HO-1 axis is intricately associated with the maintenance of cellular homeostasis and serves as a pivotal component in the adaptive response to cellular stress. This pathway represents a critical focus for cell protection, survival, and the prevention of carcinogenesis44. These studies further confirmed the transcriptomic analysis results of this study. The transcriptomic sequencing data showed that the expression of the HO-1 gene was significantly enriched, which was consistent with the core role of the NRF2 signaling pathway in the tumor stress response in previous studies.

This study found that the inhibitory effect of LBP on the proliferation of MCF-7 cells was closely associated with glutathione metabolism through metabolomics data analysis. As a critical intracellular antioxidant system, glutathione not only sustains REDOX homeostasis by scavenging oxygen free radicals but also plays an essential role in core metabolic processes, including cysteine storage and the thiol-disulfide cycle45. Similarly, metabolomics research has found that LBP can act through signal pathways such as, alanine-aspartate-glutamate and glutathione metabolism46,47. These pathways are related to the ferroptosis48. Ferroptosis is a novel form of cell death characterized by iron-dependent lipid peroxidation accumulation. It has been increasingly recognized that ferroptosis can function as a novel tumor-suppressive mechanism, offering a promising approach to overcome the challenges posed by drug-resistant malignant tumors in conventional therapies49. In this study, through the further integration of transcriptomic and metabolomic analyses, it was revealed that ferroptosis-related signaling pathways exhibited significant alterations following LBP intervention. The expression of the HO-1 gene in the transcriptome data exhibited a significantly enriched characteristic. By employing KEGG pathway enrichment analysis and constructing protein-protein interaction networks, the NRF2/HO-1 signaling pathway was ultimately identified as the key regulatory hub. To gain a deeper understanding of the mechanism by which LBP inhibits MCF-7 cell proliferation through NRF2/HO-1 pathway, we confirmed that NRF2 expressions and its downstream effector molecule HO-1 were significantly upregulated following LBP treatment. Numerous evidences suggesting that HO-1 provides significant protection against various cellular stresses. However, its role in breast cancer cells seems more complex. Current studies indicate that the function of HO-1 in breast cancer is dual: on one hand, certain anti-cancer drugs can stimulate HO-1 to inhibit the proliferation and migration of breast cancer cells50–52; on the other hand, the expression of HO-1 induced by other treatment methods may promote tumor invasion and metastasis53,54. In this study, we found that the upregulation of HO-1 promoted ferroptosis in breast cancer cells, which supports its anti-tumor effect in this specific context. Therefore, the promoting or inhibitory effects of HO-1 in breast cancer are likely to be stimulus or drug-specific. Additionally, immunofluorescence detection further revealed that the cytoplasmic and mitochondrial concentrations of Fe2+ in the LBP-treated group were higher compared to those in the control group. These findings suggest that LBP may induce cellular REDOX imbalance by activating the NRF2/HO-1 signaling pathway, thereby leading to ferroptosis-associated metabolic disorders (Fig. 7).

Fig. 7.

Fig. 7

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The mechanism by which LBP modulates the NRF2/HO-1 pathway and induces ferroptosis in MCF-7 cells.This figure was drew with Figdraw.

This study analyzed the transcriptomic and metabolomic characteristics of breast cancer MCF-7 cells under LBP exposure. Through integrated data analysis, it revealed potential correlations between gene-metabolite regulation and key signaling pathways. However, this study still has some limitations that need to be acknowledged: (1) The present study primarily focuses on establishing a foundational mechanistic framework using in vitro cell line models, without yet conducting multi-level validation in animal models or clinical samples; (2) While an association map linking metabolic pathways and transcriptional regulatory networks has been successfully generated, the underlying biological causal relationships require further investigation. Consequently, our future research will aim to deepen understanding through data integration, model construction, and mechanism analysis, thereby elucidating the regulatory mechanisms of the gene-metabolic network mediated by the NRF2 pathway.

Conclusions

This study explored the regulatory effect of Lycium barbarum polysaccharides (LBP) on the proliferation of human breast cancer MCF-7 cells and its underlying mechanism. Through standard integration analysis of transcriptomics and metabolomics, it revealed the “gene-metabolism” coordinated regulatory network triggered by LBP in breast cancer cells leading to ferroptosis. This discovery not only deepened the understanding of the anti-cancer mechanism of LBP, but also directly provided solid theoretical and experimental basis for the development of natural anti-cancer drugs based on LBP and the precise treatment strategy for breast cancer targeting the NRF2 signaling pathway.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (1,005.7KB, docx)

Abbreviations

LBP

Lycium barbarum polysaccharides

HO-1

Heme oxygenase 1

Author contributions

Xing Du , Xufeng Fu: Contributed reagents, materials, analysis tools or data; Liyang Ding; Xufeng Fu: Wrote the paper; Conceived and designed the experiments.Liyang Ding; Yitong Shang: Conceived and designed the experiments; Performed the experiments. Zhen Zhang, Hong Yang, Yu Deng, Tiantian He, Guoqin Yang, Jiaxue Ma: Performed the experiments; Analyzed and interpreted the data.

Funding

This work was supported by National Natural Science Foundation of China (81960480) and the Natural Science Foundation of Ningxia (2024AAC03208).

Data availability

The datasets generated and/or analyzed during the current study are available in the Gene Expression Omnibus (GEO) repository, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE302164 (Accession: GSE302164).

Declarations

Ethics statement

Approval of the research protocol by an Institutional Reviewer Board: The study was approved by the Medical Ethics Committee of Ningxia Medical University (NXMU-Z010).

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

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

Liyang Ding and Yitong Shang contributed equally to this work.

Contributor Information

Xufeng Fu, Email: fuxufeng100@163.com.

Xing Du, Email: duxingok@126.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1 (1,005.7KB, docx)

Data Availability Statement

The datasets generated and/or analyzed during the current study are available in the Gene Expression Omnibus (GEO) repository, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE302164 (Accession: GSE302164).

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