Potential targets of hesperetin for TNBC regulation
TNBC is a distinct type of breast cancer characterized by the absence of estrogen receptors (ER), progesterone receptors (PR), and human epidermal growth factor receptor 2 (HER2) expression. This implies that TNBC does not respond to hormone therapies targeting ER, PR, and HER2, such as tamoxifen or HER2-targeted drugs like trastuzumab [22]. Hesperetin, a naturally occurring flavonoid compound primarily found in citrus fruits, particularly oranges and grapefruits, has been reported to have potential as a therapeutic agent for TNBC [16]. In this study, we aim to identify potential targets of Hesperetin in TNBC and analyze its mechanism of action using molecular docking techniques. The workflow for this analysis is depicted in (Fig. 1A).
Screening for common targets between hesperetin and TNBC. Note: (A) The schematic diagram of the bioinformatics analysis workflow; (B) The 2D chemical structure of Hesperetin; (C) The 3D chemical structure of Hesperetin; (D) Volcano plot illustrating the differential gene expression in GSE38959 (upregulated genes: 3359; downregulated genes: 1519). Blue dots represent significantly downregulated genes, red dots represent significantly upregulated genes, and gray dots represent genes with non-significant differential expression; (E) Heatmap depicting the differential gene expression in GSE38959; (F) Venn diagram showing the intersection of genes retrieved from SwissTargetPrediction database, GSE38959, and GeneCards database
First, we determined the 2D and 3D chemical structures of hesperetin using the PubChem database (Fig. 1B-C). The SwissTargetPrediction server was then utilized to analyze and screen potential target genes of hesperetin, resulting in a total of 100 relevant genes. Additionally, we obtained 4,878 differentially expressed gene (DEGs) from the TNBC dataset GSE38959, including 3,359 upregulated DEGs and 1,519 downregulated DEGs (Fig. 1D-E). Through a search in the GeneCards database using TNBC as a keyword and setting a relevance score ≥ 1 as the screening criterion, we identified 5,861 genes associated with TNBC.
Using Venn analysis, we intersected the target genes from the SwissTargetPrediction server, the DEGs from the GSE38959 dataset, and the TNBC-associated genes from the GeneCards database, revealing 25 hesperetin target genes related to TNBC regulation (Fig. 1F). These genes include CA12, ABCG2, ESR1, MAOB, ABCC1, CBR1, MMP13, SRC, KLK2, CA2, AURKA, PGD, FUT7, STAT1, SQLE, PIM1, IGF1R, ODC1, PARP1, MAP4K4, BCL2, CHEK1, MMP3, KIT, and MAPKAPK2.
Hesperetin targets associated with protein kinase activity in TNBC
Further, gene ontology (GO) functional analysis was performed on the selected 25 candidate targets. The results of the GO functional analysis revealed that these candidates are involved in various BP, including “response to peptide,” “response to mineralocorticoid,” and “protein autophosphorylation” (Fig. 2A-B). In terms of MF, they are primarily enriched in “protein serine/threonine/tyrosine kinase activity,” “nuclear estrogen receptor binding,” and “nuclear receptor binding.” Protein kinases play a crucial role in cancer development and progression. Disruption of protein kinase activity or regulation can result in dysregulated control of cell growth, differentiation, migration, and survival, an important mechanisms underlying cancer [23]. The enrichment analysis suggests that these 25 candidate targets of hesperetin may be involved in TNBC processes through the regulation of protein kinase activity, making them potential targets for the anti-TNBC effect of hesperetin.
Enrichment analysis results for 25 genes. Note: (A) Bar chart depicting the GO functional analysis of candidate anti-TNBC targets at the BP level. The colors represent the p-values of the enrichment analysis. (B) Bar chart illustrating the GO functional analysis of candidate anti-TNBC targets at the MF level. The colors represent the P of the enrichment analysis
AURKA and FUT7: potential hesperetin targets for TNBC therapy
Among the 25 identified candidate targets, in order to further select more meaningful genes, a combination of machine learning and survival curve analysis was employed. The analytical process for this section can be seen in Fig. 3A. By applying the least absolute shrinkage and selection operator (LASSO) regression, 11 candidate targets were identified (Fig. 3A-B). Subsequently, the support vector machine-recursive feature elimination (SVM-RFE) algorithm was used to screen out 6 candidate targets for further analysis (Fig. 3C-E), with an intersection of 5 remaining candidate targets (Fig. 3F). The impact of the expression of these 5 candidate targets on survival in TNBC patients was analyzed using the Kaplan-Meier Plotter database. The results of the survival curve demonstrated a significant influence on patient survival time due to the expression changes in AURKA and FUT7 (Fig. 3G). The protein encoded by AURKA is a cell cycle-regulating kinase that exists in the centrosome of interphase cells and the spindle of mitotic cells. It is involved in the formation and/or stability of spindle pole microtubules during chromosome separation. This gene may play a role in the occurrence and development of tumors, and numerous studies have reported its relationship with breast cancer [24, 25]. However, there are fewer reports on FUT7 and breast cancer; thus in subsequent analysis, we will focus on exploring the potential of AURKA as a target for hesperetin therapy in TNBC.
Further selection of core targets using machine learning and survival curve analysis. Note: (A) The schematic of the bioinformatics analysis process; (B) Coefficients of different genes vary with different λ values; (C) The optimal parameter (lambda) identified through cross-validation of LASSO regression analysis; (D–E) Important features recognition of the 25 genes based on the SVM-RFE algorithm; F: 5 candidate targets obtained from the results of LASSO and SVM-RFE algorithms; G: Survival curve plots for the five candidate targets in TNBC
Stable binding and promising diagnostic performance of AURKA and hesperetin
We further carried out docking analysis of candidate proteins and Hesperetin using software such as AutoDockTools 1.5.6 and Vina 1.1.2. The analytical workflow for this section is depicted in Fig. 4A. The docking results of candidate proteins with hesperetin were visualized in 3D (Fig. 4B), providing a clear representation of the binding mode between the target protein receptor and the compound, as well as the interactions with surrounding amino acid residues.
Molecular docking of candidate targets with hesperetin and their ROC analysis. Note: (A) A schematic diagram of the bioinformatics analysis workflow; (B) Docking of AURKA with the Hesperetin molecule, where blue represents the receptor’s secondary structure, and red represents the small molecule Hesperetin structure; (C) Diagnostic performance of candidate targets
When the binding energy is < 0 kJ/mol, it indicates spontaneous binding and interaction between the protein and the molecule. Moreover, lower binding energy corresponds to a more stable molecular conformation [26]. The results demonstrate that AURKA shows a binding free energy of -7.7 kcal/mol, implying a relatively stable conformation when bound to hesperetin. Additionally, the diagnostic performance of candidate targets was further evaluated using ROC analysis, where a higher AUC value signifies better diagnostic performance. The evaluation of AURKA reveals diagnostic performance (Fig. 4C).
Nanocomposites-mediated hesperetin delivery promotes ferroptosis
Due to their biocompatibility, nanocomposites have gained approval from the USA Food and Drug Administration (FDA) in most materials used for nanocomposites research [27]. In this study, we prepared ferroptosis-inducing nanocomposites loaded with hesperetin through a synergistic self-assembly approach. Specifically, FeCl3•6H2O was added to an aqueous solution of hesperetin at room temperature (Fig. 5A). The size of the nanocomposites was optimized using Taguchi orthogonal experiments, employing an L24 orthogonal array design with two different operational parameters: Hesperetin concentration and FeCl3•6H2O concentration. The average size of 24 samples was measured using DLS, with the nanocomposites with an average size of (68.43 ± 0.47) nm selected as the optimized formulation and named HFPN for further investigation (Fig. 5B).
Characterization of HFPN. Notes: (A) Schematic illustration of the preparation of HFPN; (B) DLS measurement of the particle size of nanocomposites with different concentrations of Hesperetin and FeCl3•6H2O; (C) Schematic diagram of the experimental procedure for the physical characterization of nanocomposites; (D) TEM observation of the morphology of HFPN (200 nm); (E) Zeta potential of HFPN; (F) Structure characterization of HFPN nanomaterials using powder X-ray diffraction spectroscopy; (G) DLS measurement of the particle size distribution and surface charge of HFPN in deionized water, PBS, and DMEM. The experiment was repeated three times
Subsequently, the nanocomposites were physically characterized (Fig. 5C). Transmission electron microscopy (TEM) revealed that the HFPN exhibited a shuttle-like shape with an average length of (66.39 ± 22.17) nm and a width of (22.84 ± 4.69) nm (Fig. 5D). HFPN exhibited a slight negative surface charge (zeta potential of -0.28 ± 0.021 mV) (Fig. 5E). HFPN displayed consistent particle size distribution and polymer dispersity index (PDI) in deionized water, phosphate-buffered saline (PBS), and DMEM, sustaining for over 72 h (Fig. 5G). The powder X-ray diffraction pattern showed no obvious diffraction peaks, indicating a well-dispersed amorphous structure of the assembled HFPN (Fig. 5F). These results validated its colloidal stability. These results demonstrate the successful preparation of ferroptosis-inducing nanocomposites loaded with Hesperetin, which exhibit favorable stability and dispersity.
HFPN-mediated generation of ROS for ferroptosis induction
Previous studies have indicated that Fe3+ can induce Fenton-like reactions in tumor cells, leading to the generation of highly toxic •OH. To investigate the efficacy of HFPN in generating •OH, we utilized methylene blue (MB) as an indicator to detect •OH production (Fig. 6A). The results demonstrated that there was no significant decrease in absorbance in the PBS control group, while the absorbance of MB in HFPN continuously decreased, with a more pronounced decline in the HFPN + X-ray solution (Fig. 6B). This indicates that HFPN can generate •OH and X-ray irradiation can enhance the production of •OH by HFPN.
Performance evaluation of HFPN and its impact on ROS production. Note: (A) The experimental procedure; (B) Absorbance spectra of MB in different cell groups; (C) Changes in absorbance values of MB in different cell groups; (D) Visualization of ROS in MDA-MB-231 cells in different groups using CLSM, with red fluorescence (DHE) representing ROS. *** indicates a significant difference between the two groups with P < 0.001. The experiment was repeated three times
Furthermore, we employed the DPBF probe to monitor the excessive generation of 1O2 induced by the combined irradiation of HFPN and X-rays in different media. With increasing time, there was a gradual decrease in absorption at 410 nm for DPBF, indicating that HFPN can generate 1O2 radicals, and X-ray irradiation can enhance the production of 1O2 by HFPN (Fig. 6C). We further utilized the DHE probe to measure the levels of ROS within MDA-MB-231 cells. The red fluorescence intensity increased gradually in the PBS group, PBS + X-ray group, HFPN group, and HFPN + X-ray group, indicating an increase in ROS generation (Fig. 6D). Together, these results provide comprehensive evidence of the potential of HFPN in effective ferroptosis therapy, which may be mediated by the excessive generation of ROS to promote ferroptosis.
HFPN-enhanced radio sensitization in breast cancer cells
Due to its outstanding ability to generate ROS, we further evaluated the anti-cancer effect and radiosensitizing effect of HFPN in breast cancer cells (4T1 and MDA-MB-231). The analysis process for this section is illustrated in Fig. 7A. Cellular uptake was assessed by measuring intracellular iron concentration using an iron assay kit. After co-incubation with HFPN for 4 h, both 4T1, MDA-MB-231 and BT-549 cells showed increased iron accumulation compared to cells treated with PBS (Fig. 7B-C). Furthermore, cell proliferation viability was determined using the MTT assay. The results indicated a significant decrease in cell viability for both 4T1, MDA-MB-231 and BT-549 cells in the HFPN group compared to the PBS group. Additionally, the viability of 4T1, MDA-MB-231 and BT-549 cells treated with a combination of X-rays and HFPN was significantly lower than that of cells treated with HFPN or X-rays alone (Fig. 7D-E), confirming the effective radio-sensitizing property of HFPN. Colony formation experiments also revealed that post X-ray irradiation, HFPN significantly inhibited colony formation in 4T1, MDA-MB-231 and BT-549 cells compared to treatment with HFPN or X-rays alone (Fig. 7F). The results of live/dead staining showed a significant increase in red fluorescence (indicating dead cells) and decreased green fluorescence (indicating live cells) in the HFPN group compared to the PBS + X-ray group. Moreover, the HFPN + X-ray group exhibited even more pronounced red fluorescence and a decrease in green fluorescence compared to the HFPN and X-ray alone groups (Fig. 7G-H).
Impact of HFPN on the efficacy of radiation therapy in TNBC. Note: (A) Experimental flowchart illustrating the effect of HFPN on TNBC radiotherapy efficacy; (B) Measurement of intracellular iron concentration in breast cancer 4T1 cells using an iron assay kit; (C) Measurement of intracellular iron concentration in breast cancer MDA-MB-231 and BT-549 cells using an iron assay kit; (D) Assessment of cell proliferation in 4T1 cells using the MTT assay; (E) Assessment of cell proliferation in MDA-MB-231 and BT-549 cells using the MTT assay; (F) Colony formation assay to evaluate colony formation in 4T1, MDA-MB-231 and BT-549 cells; (G) CLSM observation of the distribution of live/dead cells in 4T1 cells; (H) CLSM observation of the distribution of live/dead cells in MDA-MB-2311 and BT-549 cells. * indicates a statistically significant difference between the two groups (P < 0.05), ** indicates a statistically significant difference between the two groups (P < 0.01), *** indicates a statistically significant difference between the two groups (P < 0.001). The experiments were repeated three times
Furthermore, we conducted a similar evaluation of the impact of HFPN on normal breast epithelial cells MCF 10 A. The assessment involved measuring intracellular iron levels using an iron assay kit to evaluate cellular uptake and assessing cell proliferation vitality by the MTT method. Our results indicated that after a 4-hour co-incubation of HFPN with MCF 10 A cells, there was no significant effect on intracellular iron accumulation than cells treated with PBS. Moreover, the vitality of MCF 10 A cells in the HFPN group showed no significant change compared to the PBS group (Fig. S1A-B). Additionally, colony formation experiments revealed that post X-ray irradiation, there was no change in colony formation of MCF 10 A cells treated with HFPN, in contrast to cells treated separately with HFPN and X-ray (Fig. S1C). Cell viability staining results showed no observable changes in red fluorescence in the HFPN + X-ray group compared to the HFPN + X-ray group (Fig. S1D).
HFPN-induced ferroptosis through ROS accumulation and disruption of redox homeostasis
The previous findings have confirmed the potential of HFPN in effective ferroptosis treatment. To further investigate whether cells undergo cell death through the mechanism of ferroptosis, we pre-treated the cells in HFPN combined with X-ray irradiation with the iron-regulatory protein-1 (Fer-1), iron chelator (DFO), and GSH inhibitor to inhibit ferroptosis. The relative cell viability of the different groups was then assessed (Fig. 8A). The results reveal that the cell survival rates of 4T1, MDA-MB-231, and BT-549 cells significantly increased after pretreatment with Fer-1, DFO, and GSH, as compared to the group treated with HFPN + X-ray (Fig. 8B-C), further indicating the crucial role of ferroptosis in HFPN-mediated cell death.
Impact of HFPN on redox homeostasis. Note: (A) Experimental flowchart of HFPN affecting redox homeostasis; (B) Proliferation of 4T1 cells detected by MTT assay; (C) Proliferation of MDA-MB-231 and BT-549 cells detected by MTT assay; (D) Schematic diagram of the potential mechanism by which HFPN mediates iron death; (E) Depletion of GSH in 4T1 cells in each group; (F) GSH/GSSG ratio in 4T1 cells in each group; (G) Expression of LPO in 4T1 cells in each group observed by CLSM; (H) Expression of GPX4 and SLC7A11 proteins in 4T1 cells, MDA-MB-231, and BT-549 cells detected by Western blot. * denotes a significant difference between the two groups with P < 0.05, ** denotes a significant difference with P < 0.01, *** denotes a significant difference with P < 0.001. The experiments were repeated three times
Based on previous experiments suggesting that HFPN promotes excessive ROS production, we propose that HFPN disrupts the redox homeostasis by depleting GSH and inactivating glutathione peroxidase 4 (GPX4), leading to lipid peroxidation enzyme family (LPO) accumulation and ultimately promoting cell ferroptosis (Fig. 8D). Different groups of cells were assessed for their levels of GSH, revealing a significant reduction in GSH levels in cells treated with HFPN and HFPN combined with X-ray compared to cells treated with PBS. Pre-treatment with the iron chelator DFO significantly increased the levels of cellular GSH (Fig. 8E) and the GSH/GSSG ratio (Fig. 8F). Further investigation using fluorescent probes to study the levels of LPO showed intense green fluorescence in 4T1 cells in the HFPN group and HFPN + X-ray group after 24 h of incubation; however, pre-treatment with the iron chelator DFO resulted in a significant decrease in LPO fluorescence signal (Fig. 8G). Western blot analysis revealed that GPX4 and solute carrier family 7 (SLC7A11) protein expression in 4T1, MDA-MB-231, and BT-549 cells in the HFPN and X-ray groups was significantly decreased compared to the PBS group. Moreover, the expression of GPX4 and SLC7A11 proteins in cells in the HFPN + X-ray group was significantly lower than in the HFPN and X-ray groups, while in the HFPN + X-ray + DFO group, the expression of GPX4 and SLC7A11 proteins was significantly higher than in the HFPN + X-ray group (Fig. 8H). These experimental findings indicate that HFPN can disrupt the redox homeostasis crucial for tumor survival by inducing GSH depletion and LPO accumulation through the excessive accumulation of ROS.
Inhibition of AURKA expression by HFPN disrupts redox homeostasis
We hypothesize that HFPN may suppress the expression of the AURKA factor, thereby affecting redox homeostasis. To further validate this hypothesis, we performed the analysis as outlined in Fig. 9A. Western blot analysis revealed a significant decrease in AURKA protein expression in the cells treated with HFPN compared to the PBS group (Fig. 9B). To confirm that HFPN affects redox homeostasis by inhibiting AURKA expression, we subjected 4T1 cells to AURKA overexpression pretreatment and assessed the expression of AURKA and GPX4 proteins. Cells with AURKA overexpression pretreatment demonstrated a significant increase in AURKA and GPX4 protein expression (Fig. 9C). Intracellular iron concentration was determined using the iron assay kit. The results showed that cells treated with HFPN + oe-AURKA exhibited reduced iron accumulation compared to the HFPN + oe-NC group; a similar reduction was observed in the cells treated with HFPN + X ray + oe-AURKA compared to the HFPN + X ray + oe-NC group (Fig. 9D). The results of the measurements of the levels of GSH, GSH/GSSG ratio, and GSH-PX activity in different cell groups indicate that cells pre-treated with the combination of AURKA overexpression and HFPN exhibit significantly higher levels of GSH and GSH/GSSG ratio compared to cells treated with HFPN alone. In addition, the cells in the HFPN + X-ray + oe-AURKA group show markedly higher levels of GSH and GSH/GSSG ratio than the cells in the HFPN + X-ray + oe-NC group, while the GSH-PX activity shows an opposite trend (Fig. 9E-G). Methylthiazolyldiphenyl-tetrazolium bromide (MTT) assay results also demonstrated that cells subjected to AURKA overexpression pretreatment exhibited higher cell viability compared to cells without such pretreatment (Fig. 9H). Colony formation assay revealed that cells in the HFPN + oe-AURKA group exhibited a significant increase in colony formation compared to the HFPN + oe-NC group; a similar increase was observed in the cells treated with HFPN + X ray + oe-AURKA compared to the HFPN + X ray + oe-NC group (Fig. 9I). Cell viability staining results showed a decrease in red fluorescence and an increase in green fluorescence in the HFPN + oe-AURKA group compared to the HFPN + oe-NC group; a similar trend was observed in the cells treated with HFPN + X ray + oe-AURKA compared to the HFPN + X ray + oe-NC group (Fig. 9J). The LPO probe assay showed a significant reduction in LPO fluorescence signal in the cells treated with HFPN + oe-AURKA compared to the HFPN + oe-NC group; a similar reduction was observed in the cells treated with HFPN + X ray + oe-AURKA compared to the HFPN + X ray + oe-NC group (Fig. 9K).
Regulation of AURKA factor expression by HFPN. Note: (A) Experimental flowchart illustrating the effect of HFPN on AURKA expression and disruption of redox homeostasis; (B) Western blot analysis of AURKA protein expression in different groups of 4T1 cells; (C) Western blot analysis of AURKA and GPX4 protein expression in different groups of 4T1 cells; (D) Iron concentration measurement in MDA-MB-2311 breast cancer cells using the iron assay kit; (E) Depletion of GSH in 4T1 cells of each group; (F) GSH/GSSG ratio in 4T1 cells of each group; (G) GSH-PX activity in 4T1 cells of each group; (H) Proliferation of 4T1 cells detected by MTT assay; (I) Colony formation experiment assessing colony formation of 4T1 cells; (J) CLSM observation of the distribution of live/dead cells in 4T1 cells; (K) CLSM observation of LPO expression in 4T1 cells of each group. * indicate statistical significance at P < 0.05, ** at P < 0.01, and *** at P < 0.001 when comparing between two groups. The experiments were repeated three times
Consistent results were obtained in MDA-MB-2311 cells as in 4T1 cells (Fig. S2). Taken together, these findings suggest that HFPN effectively inhibits the expression of AURKA and affects the redox homeostasis.
HFPN exhibits targeted anticancer efficacy and enhances radiotherapy in breast cancer models
To investigate the in vivo anti-tumor efficacy and targeting ability of HFPN, we established a subcutaneous tumor model in mice using 4T1 cells. The analytical procedure for this section is shown in Fig. 10A. We utilized the in vivo imaging system and observed a strong fluorescence signal at the tumor site 2 h after intravenous injection of HFPN, as depicted in Fig. 10B. This suggests that HFPN can rapidly accumulate at the tumor site.
Effects of HFPN in the breast cancer model mice. Note: (A) Experimental flowchart illustrating the targeted anti-cancer effects of HFPN and enhancement of radiotherapy efficacy; (B) In vivo distribution of HFPN in mice observed using the Maestro in vivo fluorescence imaging system at 0, 2, 4, 8, 12, and 24 h after injection, with a total of 6 mice; (C) Tumor volume changes over a 20-day period in each group of mice; (D) Tumor dissection images and statistical analysis of tumor weight in each group of mice; (E) Body weight changes over a 20-day period in each group of mice; (F) Immunohistochemical detection of positive expression of the proliferation-related protein Ki67 in tumor tissues; (G) Western blot analysis of the expression of ferroptosis-related proteins in tumor tissues of each group of mice. * indicates a significant difference between the two groups with P < 0.05, ** indicates P < 0.01, *** indicates P < 0.001. Each group in B-D consisted of 6 mice
Furthermore, we further evaluated the in vivo anti-tumor efficacy of HFPN by assessing tumor volume and weight. Compared to the PBS group, both the PBS + X-ray and HFPN groups displayed significant reductions in tumor volume and weight. Additionally, compared to the PBS + X-ray group, the HFPN + X-ray group also exhibited a significant decrease in tumor volume and weight. Conversely, the HFPN + X-ray + oe-NC group showed a significant increase in tumor volume and weight compared to the HFPN + X-ray + oe-AURKA group, as shown in Fig. 10C-D. Changes in mouse body weight were also monitored, revealing a decrease in the PBS + X-ray group and no significant impact on the body weight of mice in the HFPN group, as presented in Fig. 10E.
Immunohistochemical (IHC) analysis was performed to assess the expression of the proliferation marker Ki67 in tumor tissues from each group of mice. The results demonstrated a significant decrease in the number of Ki67-positive cells in the tumor tissues of both the PBS + X-ray and HFPN groups compared to the PBS group. Additionally, the HFPN + X-ray group exhibited a significant decrease in Ki67-positive cells compared to the PBS + X-ray group. Notably, the HFPN + X-ray + oe-AURKA group displayed a significant increase in the number of Ki67-positive cells compared to the HFPN + X-ray + oe-NC group, as depicted in Fig. 10F.
Western blot analysis was conducted to evaluate the expression of the ferroptosis-related proteins GPX4 and SLC7A11 in the tumor tissues of each group of mice. Compared to the PBS group, the X-ray, HFPN, and HFPN + X-ray groups displayed a significant decrease in the expression of GPX4 and SLC7A11 proteins. The HFPN + X-ray group exhibited lower expression of GPX4 and SLC7A11 proteins compared to the HFPN group, while the HFPN + X-ray + oe-AURKA group showed even lower expression compared to the HFPN + X-ray + oe-NC group, as shown in Fig. 10G. These results collectively demonstrate that HFPN exhibits good anti-tumor efficacy and targeting ability, and through AURKA inhibition, promotes ferroptosis, thereby effectively enhancing the radiation therapy efficacy in a mouse model of breast cancer.
