Abstract

Background

   Hyperoside (Hyp) exerts considerable inhibitory effects on
   non-small-cell lung cancer (NSCLC) cells. However, the underlying
   molecular mechanisms have not been fully elucidated. We aimed to
   explore the molecular mechanisms of Hyp in the treatment of NSCLC using
   a combination of network pharmacology and in vitro experiments.

Methods

   Active targets of Hyp and NSCLC-related targets were identified using
   public databases. The therapeutic targets were predicted based on the
   intersection of drug and disease targets. A protein–protein interaction
   (PPI) network was constructed using STRING and Cytoscape, and key
   network modules and targets were identified through network topology
   analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and
   Genomes (KEGG) pathway enrichment analyses were performed using DAVID.
   Molecular docking between Hyp and therapeutic targets was performed
   using AutoDock Vina software. These results were further verified by in
   vitro experiments of A549 cell lines, including the CCK-8 assay, EdU
   staining, flow cytometry and western blotting.

Results

   A total of 30 therapeutic targets of Hyp against NSCLC were identified.
   Analysis of the PPI network revealed a key network module and five key
   targets: MMP9, CASP3, MAPK1, ESR1, and EGFR. These targets were related
   to cell proliferation and migration, apoptosis, and oxidative stress
   and may play a role through the FoxO, MAPK, Rap1, Ras, and PI3K-Akt
   signaling pathways. Molecular docking results showed a strong binding
   affinity between Hyp and most therapeutic targets. Further experiments
   confirmed that Hyp inhibited proliferation and induced apoptosis of
   A549 cells by regulating the EGFR/ERK/FOXO1 signaling pathway.

Conclusions

   Hyp may be a promising drug for treating NSCLC (especially lung
   adenocarcinoma), and its therapeutic mechanisms is closely related to
   the regulation of EGFR/ERK/FOXO1 pathway.

Supplementary Information

   The online version contains supplementary material available at
   10.1007/s12672-025-03622-9.

   Keywords: Hyperoside, Non-small-cell lung cancer, Network pharmacology,
   Apoptosis, EGFR/ERK/FOXO1 pathway

Introduction

   According to the latest statistics from the International Agency for
   Research on Cancer (IARC) in 2022, the incidence and mortality rates of
   lung cancer in the world have risen to the highest among malignant
   tumors [[36]1]. Based on histopathology, lung cancer can be divided
   into non-small cell lung cancer (NSCLC) and small cell lung cancer
   (SCLC). NSCLC accounts for 85% of all lung cancer cases [[37]2]. NSCLC
   cells are characterized by the slow growth and division, resulting in
   late diffusion and metastasis. Thus, their early stage is not easy to
   detect [[38]3]. In recent years, great progress has been made in the
   surgical or non-surgical treatment of NSCLC. However, its clinical
   treatment and prognosis are still poor, and the 5-year survival rate of
   NSCLC is approximately 15% [[39]4, [40]5].

   Clinical studies have shown that a great number of traditional Chinese
   medicine treatments have exhibited satisfactory anti-tumor effects.
   Meanwhile, compared to traditional chemotherapy drugs, traditional
   Chinese medicines possess fewer adverse reactions and lower drug
   resistance [[41]6, [42]7]. Hyperoside (Hyp) is a natural flavonol
   glycoside that is widely found in a variety of plants such as Hypericum
   monogynum, Crataegus pinnatifida, and Polygonum aviculare [[43]8]. It
   has been found to own various biological activities such as
   anti-inflammatory, antibacterial, antiviral, and organ protection
   [[44]9]. Currently, Hyp has also been found to exert considerable
   inhibitory effects on NSCLC cells. It was reported that Hyp could
   inhibit the proliferation and induce the apoptosis of T790M-positive
   NSCLC cells. The further studies revealed that this effect is closely
   associated with the upregulated expression of forkhead box O1 (FOXO1)
   [[45]10]. It was also demonstrated that Hyp could activate the p38/MAPK
   and JNKinduced mitochondrial death pathway, remarkably accelerating the
   A549 cells apoptosis [[46]11]. Besides these, another study disclosed
   that Hyp could trigger the apoptosis of A549 cell by enhancing
   autophagy [[47]12]. In brief, Hyp may exerts anti-NSCLC effects through
   a variety of biological mechanisms. Hence, It is important and
   necessary to further clarify its molecular mechanisms.

   Traditional methods for screening the pharmacological activities of
   natural monomer components are often achieved by cell experiments or
   Qualcomm’s method. However, these research methods are time-consuming
   and expensive, and their accuracy is closely related to the overall
   conditions of animal models or human bodies [[48]11]. Network
   pharmacology is an emerging discipline that integrates systems biology,
   molecular biology, pharmacology, and various computing platforms in the
   era of big data. It could perform multi-level network screening and
   construction from the macro to micro perspective, visualize the data
   using a variety of database platforms and computer software, and more
   intuitively explain the complex relationship between traditional
   Chinese medicine and diseases. Network pharmacology emphasizes the
   understanding of the interaction between drugs and the organism from
   the perspective of biological network balance, and explains the
   occurrence and development process of disorders, which is consistent
   with the characteristics of holistic treatment of traditional Chinese
   medicine. Its rapid development has also brought new ideas to the field
   of traditional Chinese medicine [[49]12, [50]13]. This study used
   network pharmacology combined with in vitro biological experiments to
   explore the molecular mechanisms of Hyp in the treatment of NSCLC. A
   flowchart of this study is summarized in Fig. [51]1.

Fig. 1.

   [52]Fig. 1
   [53]Open in a new tab

   Detailed flowchart of this study

Materials and methods

Network pharmacological analysis

Prediction of Hyp active targets

   The SMILE file and 3D structure file in SDF format of Hyp were
   downloaded using “hyperoside” as the keyword in PubChem [[54]14]
   ([55]https://pubchem.ncbi.nlm.nih.gov/). In Traditional Chinese
   Medicine Systems Pharmacology (TCMSP) [[56]15]
   ([57]https://old.tcmsp-e.com/tcmsp.php), the active targets of Hyp were
   obtained using the “hyperoside” term. Potential targets were also
   predicted using the SMILE file in Search Tool for Interacting Chemicals
   (STITCH) [[58]16] ([59]http://stitch.embl.de/). In addition, the SDF
   format file was uploaded to PharmMapper [[60]17]
   ([61]http://www.lilab-ecust.cn/pharmmapper/) for reverse molecular
   docking simulation to screen out the active targets of Hyp. In
   PharmMapper, the species was set as “homo sapiens”. The predicted
   targets with fit score ≥ 2.5 from PharmMapper were collected in our
   study.

Acquisition of NSCLC disease targets

   NSCLC disease targets were collected using the keywords “non-small-cell
   lung cancer ” in Online Mendelian Inheritance in Man (OMIM) [[62]18]
   ([63]https://omim.org/), Therapeutic Target Database (TTD) [[64]19]
   ([65]http://db.idrblab.net/ttd/), Comparative Toxicogenomics Database
   (CTD) [[66]20] ([67]http://ctdbase.org/), and DisGeNET [[68]21]
   ([69]https://www.disgenet.org/). The above NSCLC disease targets were
   standardized using UniProt [[70]22] ([71]https://www.uniprot.org/) and
   duplicate proteins were removed. The proteins with “direct evidence” as
   “marker or mechanism or therapeutic” in CTD were selected as the NSCLC
   disease targets that had more sufficient evidence.

Prediction of therapeutic targets of Hyp against NSCLC

   The active targets of Hyp and NSCLC disease targets were intersected
   using Venny (version 2.1.0)
   ([72]https://bioinfogp.cnb.csic.es/tools/venny/index.html) to obtain
   the potential therapeutic targets of Hyp against NSCLC.

Construction and analysis of PPI network

   STRING [[73]23] ([74]https://string-db.org/) was used to get the
   interactions between therapeutic targets by setting the species as
   “homo sapiens” and the confidence score ≥ 0.4. These interactions were
   then imported into Cytoscape [[75]24] (version 3.2.0) to construct a
   PPI network. The MCODE plugin [[76]25] with default parameters from
   Cytoscape was used to identify the key network modules. The MCODE could
   detect the densely connected regions in the PPI network, and the
   network module with the highest score was regarded as the key network
   module. The degree value of the nodes from the key network module was
   analyzed with the plugin Network Analyzer [[77]26], and the key targets
   were then identified according to the screening criteria that the
   degree value was greater than or equal to its average value. The degree
   value of a node reflects the number of connections with the other nodes
   in the network. The greater its value, the greater its importance to
   the entire network. Therefore, the degree in this study was selected as
   an important index for identifying key targets.

GO and KEGG pathway enrichment analyses

   Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)
   pathway enrichment analyses for the target proteins in the key network
   module were performed using Database for Annotation, Visualization, and
   Integrated Discovery (DAVID) [[78]27] ([79]https://david.ncifcrf.gov/).
   The screening condition (p < 0.01) was used to obtain significantly
   enriched GO items and KEGG pathways, and the results were visualized
   using the R software.

Construction of “Hyp-Target-Pathway” network

   Firstly, the above obtained Hyp-target interaction relationships were
   constructed into a “Hyp-Target” network by Cytoscape, and then the
   corresponding relationships of target-pathway were built into a
   “Target-Pathway” network by the same way. Finally, the two networks
   were integrated into a “Hyp-Target-Pathway” network using the merge
   function of Cytoscape.

Molecular docking simulation

   The crystal structure files of the targets in the key network module
   were accessed from the Research Collaboratory for Structural
   Bioinformatics Protein Data Bank (RCSB PDB) [[80]28]
   ([81]http://www.rcsb.org/), and the PyMOL software [[82]29] was
   employed to remove water molecules and original ligands from the
   protein structures. The SDF format of Hyp was converted into the PDB
   format using OpenBabel software [[83]30]. Using AutoDock Tools (version
   1.5.6), the structural files of Hyp and the targets were hydrogenated,
   charged, and saved in the PDBQT format. Molecular docking was performed
   using AutoDock Vina [[84]31] on a Linux platform, and the docking
   results were visualized using PyMOL.

In vitro experimental verification

Cell culture

   The NSCLC cell line A549 was procured from the Shanghai Cell Bank of
   the China Academy of Sciences. A549 cells were cultured in RPMI 1640
   medium (Thermo Fisher Scientific, Waltham, MA, USA) supplemented with
   100 µg/ml streptomycin, 10% fetal bovine serum, and 100 U/ml
   penicillin. The cells were routinely subcultured in an incubator at
   37 °C and 5% CO[2].

Cytotoxicity test

   Hyp (98.68% purity) was purchased from MedMol (Shanghai, China). Before
   use, Hyp was dissolved in an appropriate volume of dimethyl sulfoxide
   and diluted to the required concentrations. A549 cells in the
   logarithmic growth phase were seeded in 96-well plates at a density of
   5 × 10^3 cells/well and cultured for 24 h. The A549 cells in the drug
   group were treated with different concentrations of Hyp solution (20,
   40, 80, 160, and 320 µM) for 24, 48, and 72 h, whereas cells in the
   control group were treated with drug-free medium for 24, 48, and 72 h.
   Subsequently, 10 µL of CCK-8 reagent (Beyotime, Shanghai, China) was
   added to each well and incubated for another 2 h. The absorbance was
   measured at 490 nm using a microplate reader, and the cell survival
   rate was calculated. This experiment was conducted to screen for the
   optimal drug concentration that interfered with cell viability.

Cell proliferation test

   A549 cells were seeded into 6-well plates at a density of 2 × 10^5
   cells/mL per well and cultured for 24 h. In the Hyp group, 160 µM Hyp
   solution was added; in the Hyp + NSC228155 (specific EGFR activator)
   (MedMol, Shanghai, China) group, 160 µM Hyp solution and 2 µM NSC228155
   were added; and in the control group, a drug-free medium was used. The
   cultures were maintained for an additional 24 h. Then, each group was
   treated with 10 µM EdU (Ribobio, Guangzhou, China) at 37℃ for 2 h.
   Subsequently, A549 cells in each group were incubated with Click
   reaction solution (Meilunbio, Dalian, China) for 30 min at room
   temperature, washed three times with phosphate buffered saline (PBS),
   and stained with 10 µg/mL DAPI (Meilunbio, Dalian, China) for 10 min.
   Finally, the cells were observed and photographed under an inverted
   fluorescence microscope. The resulting images were processed using
   ImageJ software.

Apoptosis detection

   A549 cells were seeded into 6-well plates and treated with Hyp or
   NSC228155 for 24 h. The grouping and administration of cells followed
   the procedure described in Sect. [85]2.2.3. The cells were then
   digested with trypsin, washed twice with PBS, centrifuged at 1500 rpm
   for 5 min, and resuspended in 100 µL binding buffer. Thereafter, the
   cells were stained with 5 µL annexin V-FITC (Beyotime, Shanghai, China)
   and 5 µL PI (Beyotime, Shanghai, China) for 15 min at room temperature.
   Apoptosis was detected by flow cytometry.

Western blotting analysis

   The grouping and administration of cells followed the same procedure as
   described in Sect. [86]2.2.3. After 24 h of treatment with Hyp or
   NSC228155, RIPA lysis buffer (Beyotime, Shanghai, China) was added to
   each group of cells to prepare total protein lysates. Then the BCA
   protein assay kit (Beyotime, Shanghai, China) was used for protein
   quantification. Protein samples were separated by 10% sodium dodecyl
   sulfate-polyacrylamide gel electrophoresis, transferred to
   nitrocellulose membranes, blocked with 5% skimmed milk (Beyotime,
   Shanghai, China) for 2 h at room temperature, and incubated with
   primary antibodies against epidermal growth factor receptor (EGFR),
   p-EGFR, extracellular regulated kinase 1/2 (ERK1/2), p-ERK1/2, FOXO1,
   Cleaved-Caspase-3, Bax, Bcl-2, or β-actin overnight at 4℃. The primary
   antibodies EGFR, p-EGFR, ERK1/2, p-ERK1/2, FOXO1, and β-actin were
   purchased from Abcam (Cambridge, MA, USA) and Cleaved-Caspase-3, Bax,
   and Bcl-2 were purchased from Cell Signaling Technology (Danvers, MA,
   USA). The membrane was washed with TBST and incubated with a secondary
   antibody at room temperature for 2 h. The protein bands were detected
   using enhanced chemiluminescence detection reagents (Danvers, MA, USA).
   β-Actin was used as a control to standardize the expression of other
   proteins. Band intensity was analyzed using ImageJ software.

Statistical analysis

   All results are presented as the mean ± standard deviation (SD), and
   the data were analyzed using GraphPad Prism software (version 8.0).
   Differences between two groups were measured using t-test. One-way
   analysis of variance (ANOVA) was used to assess the statistical
   differences between multiple groups. For pairwise comparisons, Fisher’s
   least significant difference (LSD) test was applied. Differences were
   considered statistically significant at p < 0.05.

Results

Therapeutic targets of Hyp against NSCLC

   Seven, five, and 265 active Hyp targets were obtained from the TCMSP,
   STITCH, and PharmMapper databases, respectively. After removing
   duplicate targets, 273 unique active targets were identified. Three,
   82, 143, and 151 NSCLC disease targets were retrieved from the OMIM,
   TTD, CTD, and DisGeNET, respectively. In total, 344 NSCLC disease
   targets were collected after removing duplicates. Venny was utilized to
   intersect the Hyp active targets with the NSCLC disease targets and
   draw a Venn diagram (Fig. [87]2A). Eventually, 30 potential therapeutic
   targets of Hyp acting on NSCLC were identified.

Fig. 2.

   [88]Fig. 2
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   Network analysis of the potential therapeutic targets against NSCLC. A
   The Venn diagram of Hyp targets and NSCLC targets. B The network module
   analysis of PPI network. C The topology analysis of network module 1
   (node size representing degree value)

PPI network, key network modules, and key targets

   The PPI network for Hyp treating NSCLC was successfully generated
   through Cytoscape (Fig. [90]2B). This network contained 30 nodes and
   128 edges, in which nodes represented proteins, and edges represented
   the interaction between proteins. Two network modules were identified
   using the MCODE plugin from Cytoscape (Fig. [91]2B). The score of
   network module 1 was 9.273, including 12 nodes and 51 edges. The score
   of network module 2 was 4.000, including four nodes and six edges. The
   score of network module 1 was much larger than that of network module
   2. Thus, network module 1 was regarded as the key network module of the
   PPI network. Network Analyzer was employed to calculate the degree
   value of the nodes in network module 1, and the results were shown in
   Table [92]1. The degree values of matrix metalloproteinase-9 (MMP9),
   caspase-3 (CASP3), mitogen-activated protein kinase 1 (MAPK1), estrogen
   receptor (ESR1) and EGFR were 11, 11, 11, 11 and 9, respectively, which
   were all greater than the average value (8.5). Thus, they were
   considered to be the key targets of network module 1. These proteins
   were also key targets of the whole PPI network and may play a crucial
   role in the biological effects of Hyp in NSCLC treatment.

Table 1.

   The degree value of therapeutic targets in network module 1
   Gene symbol Protein name Uniprot ID Degree value
   CASP3 Caspase-3 [93]P42574 11
   ESR1 Estrogen receptor [94]P03372 11
   MAPK1 Mitogen-activated protein kinase 1 [95]P28482 11
   MMP9 Matrix metalloproteinase-9 [96]P14780 11
   EGFR Epidermal growth factor receptor [97]P00533 9
   IGF1R Insulin-like growth factor 1 receptor [98]P08069 8
   CAT Catalase [99]P04040 7
   KDR Vascular endothelial growth factor receptor 2 [100]P35968 7
   MET Hepatocyte growth factor receptor [101]P08581 7
   PGR Progesterone receptor [102]P06401 7
   SOD2 Superoxide dismutase [Mn], mitochondrial [103]P04179 7
   NQO1 NAD(P)H dehydrogenase [quinone] 1 [104]P15559 6
   [105]Open in a new tab

GO and KEGG pathway enrichment analyses

   A total of 50 significant items were screened by GO enrichment
   analysis, including 33 biological processes, four cellular components,
   and 13 molecular functions. The top 10 items of them were shown in
   Fig. [106]3A. Biological processes mainly included negative regulation
   of apoptosis process, positive regulation of cell proliferation or
   migration, response to hydrogen peroxide, etc. Cell components included
   membrane raft, golgi apparatus, plasma membrane, and focal adhesion.
   Molecular functions primarily included transmembrane receptor protein
   tyrosine kinase, protein tyrosine kinase activity, superoxide dismutase
   activity, etc.

Fig. 3.

   [107]Fig. 3
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   Enrichment analysis of therapeutic targets and construction of
   “Hyp-Target-Pathway” network. A GO enrichment analysis. B KEGG pathway
   enrichment analysis. C “Hyp-Target-Pathway” network (Light blue
   triangle representing Hyp, green circle representing target, and square
   representing pathway)

   The results of KEGG pathway enrichment analysis exhibited that 32
   biological pathways were significantly enriched (Fig. [109]3B). These
   pathways involved human diseases (such as proteoglycans in cancer,
   breast cancer, NSCLC, etc.), organismal system (such as estrogen
   signaling pathway, longevity regulating pathway, progesterone-mediated
   oocyte maturation, etc.), and signal transduction (such as FoxO
   signaling pathway, MAPK signaling pathway, Rap 1 signaling pathway,
   etc.). This study focused on the signal transduction pathway that was
   identified as responsible for environmental information processing in
   KEGG PATHWAY database. The p values of FoxO and MAPK signaling pathways
   were relatively small, which may be the key mechanisms of Hyp in
   treating NSCLC. The “Hyp-Target-Pathway” network was successfully
   established using Cytoscape (Fig. [110]3C). This network consisted of
   36 nodes (one compound, 12 targets, and 23 pathways) and 100 edges.
   This indicated that Hyp owned the characteristics of multiple targets
   and pathways in the treatment of NSCLC.

Molecular docking

   When the binding energy is less than − 7.0 kcal/mol, it indicates
   strong binding activity between the ligand and receptor [[111]32].
   Except CASP3, ESR1, and PGR, the binding energies of other proteins
   with Hyp were all less than − 7.0 kcal/mol (Table [112]2), suggesting
   that the results obtained via network pharmacology were reliable.The
   binding energies of the key targets, namely, EGFR, MAPK1, MMP9, ESR1,
   and CASP3, were − 9.8, − 9.0, − 7.5, − 6.4, and − 5.1 kcal/mol,
   respectively. Hyp exhibited strong binding activity with EGFR, MAPK1,
   and MMP9. As shown in Fig. [113]4, these three complexes generated
   stable conformations through multiple hydrogen bonds.

Table 2.

   Molecular Docking results between hyp and therapeutic targets in
   network module 1
   Symbol Protein name PDB ID Binding energy(kcal/mol)
   CASP3 Caspase-3 3KJF − 5.1
   CAT Catalase 1DGH − 9.3
   EGFR Epidermal growth factor receptor 3UG2 − 9.8
   ESR1 Estrogen receptor 4MGB − 6.4
   IGF1R Insulin-like growth factor 1 receptor 5FXR − 7.9
   KDR Vascular endothelial growth factor receptor 2 3U6J − 8.2
   MAPK1 Mitogen-activated protein kinase 1 4FV5 − 9.0
   MET Hepatocyte growth factor receptor 4MXC − 7.8
   MMP9 Matrix metalloproteinase-9 2OW1 − 7.5
   NQO1 NAD(P)H dehydrogenase [quinone] 1 5EA2 − 10.1
   PGR Progesterone receptor 3KBA − 5.5
   SOD2 Superoxide dismutase [Mn], mitochondrial 5T30 − 7.1
   [114]Open in a new tab

Fig. 4.

   [115]Fig. 4
   [116]Open in a new tab

   The molecular docking between Hyp and key targets. MAPK1
   mitogen-activated protein kinase 1, MMP9 matrix metalloproteinase-9,
   EGFR epidermal growth factor receptor

Hyp inhibiting viability and proliferation of A549 cells

   After 24, 48, and 72 h of treatment with different concentrations of
   Hyp, the survival rate of A549 cells significantly decreased
   (p < 0.05). At the same intervention times, with an increase in Hyp
   concentration, the cell survival rate decreased (Fig. [117]5). At the
   same Hyp concentration, longer intervention times corresponded to lower
   cell survival rates (Fig. [118]5). These results showed that Hyp
   inhibited the activity of A549 cells in a time- and dose-dependent
   manner. The IC50 values for Hyp at 24, 48, and 72 h in this study were
   149.41, 102.88, and 64.26 µM, respectively. Because the treatment with
   160 µM Hyp for 24 h had a good inhibitory effect on A549 cells, this
   concentration was used for follow-up experiments. The EdU positivity
   rate in the Hyp group was significantly lower than that in the control
   group (p < 0.05; Fig. [119]6). Compared with the Hyp group, the EdU
   positivity rate in the Hyp + NSC228155 group was significantly higher
   (p < 0.05) (Fig. [120]6).

Fig. 5.

   [121]Fig. 5
   [122]Open in a new tab

   Hyp suppressed cell viability in A549 cells (n = 5). A549 cells were
   treated with different concentrations of Hyp (0-320µM) for 24 h, 48 h
   and 72 h, respectively. All data were expressed as mean ± SD.
   Differences were analyzed using t-test. ^****p < 0.0001 vs. control (0
   µM group). ^#p < 0.05, ^##p < 0.01, ^###p < 0.001, ^####p < 0.0001 vs.
   24 h

Fig. 6.

   [123]Fig. 6
   [124]Open in a new tab

   Hyp inhibited the proliferation of A549 cells (n = 3). EdU assay was
   used to detect the proliferation of A549 cells. All data were expressed
   as mean ± SD. Differences were analyzed using ANOVA. Fisher’s LSD test
   was used for pairwise comparisons. ^*p < 0.05, ^**p < 0.01

Hyp inducing apoptosis of A549 cells

   The effect of Hyp on the apoptosis of A549 cells was detected using
   flow cytometry. Our results (Fig. [125]7) showed that the rate of
   apoptosis in the Hyp group was significantly higher than that in the
   control group (p < 0.05). By contrast, the apoptosis rate in the
   Hyp + NSC228155 group was significantly lower (p < 0.05) than that in
   the Hyp group. Western blot results (Fig. [126]8) showed that compared
   with the control group, in the Hyp group, the expression of
   pro-apoptosis proteins Cleaved-Caspase-3 and Bax increased
   significantly (p < 0.05), whereas the expression of the anti-apoptotic
   protein Bcl-2 decreased significantly (p < 0.05). These results
   indicated that Hyp induced apoptosis in A549 cells.

Fig. 7.

   [127]Fig. 7
   [128]Open in a new tab

   Hyp induced the apoptosis of A549 cells (n = 3). The apoptosis of A549
   cells was detected by flow cytometry. All data were expressed as
   mean ± SD. Differences were analyzed using ANOVA. Fisher’s LSD test was
   used for pairwise comparisons. ^**p < 0.01, ^***p < 0.001

Fig. 8.

   [129]Fig. 8
   [130]Open in a new tab

   Hyp regulated apoptosis-related proteins in A549 cells (n = 3). The
   expression levels of apoptosis-related proteins were determined by
   Western blot. All data were expressed as mean ± SD. Differences were
   analyzed using ANOVA. Fisher’s LSD test was used for pairwise
   comparisons. ^*p < 0.05, ^**p < 0.01, ^***p < 0.001, ^****p < 0.0001

Hyp regulating EGFR/ERK/FOXO1 signaling pathway

   The expression levels of proteins related to the EGFR/ERK/FOXO1
   signaling pathway were shown in Fig. [131]9. Compared to the control
   group, in the Hyp group, the p-EGFR/EGFR and p-ERK1/2/ERK1/2 ratios
   decreased significantly (p < 0.05), whereas the expression level of
   FOXO1 increased significantly (p < 0.05). By contrast, compared to the
   Hyp group, in the Hyp + NSC228155 group, the ratios of p-EGFR/EGFR and
   p-ERK1/2/ERK1/2 were significantly increased (p < 0.05), whereas the
   expression of FOXO1 was significantly downregulated (p < 0.05). These
   results suggested that Hyp inhibited the activities of EGFR and ERK1/2
   and downregulated the expression of FOXO1.

Fig. 9.

   [132]Fig. 9
   [133]Open in a new tab

   Hyp regulated the EGFR/ERK/FOXO1 signaling pathway-related proteins in
   A549 cells (n = 3). The expression levels of related protein in the
   EGFR/ERK/FOXO1 signaling pathway were determined by western blot. All
   data were expressed as mean ± SD. Differences were analyzed using
   ANOVA. Fisher’s LSD test was used for pairwise comparisons. ^*p < 0.05,
   ^**p < 0.01, ^***p < 0.001. EGFR: epidermal growth factor receptor;
   ERK1/2: extracellular regulated kinase 1/2; FOXO1: forkhead box O1

Discussion

   NSCLC is a malignant tumor that seriously endangers human health, and
   its incidence is increasing annually. Despite the rapid development of
   medical technologies, the overall therapeutic effect on NSCLC remains
   unsatisfactory. Hyp is an important natural product that has attracted
   considerable attention in the medical field. Hyp, a flavonoid
   glycoside, complies with the five principles of Lipski, indicating that
   it has good pharmacokinetic properties [[134]8]. Hyp exerts strong
   inhibitory effects on NSCLC cells [[135]10, [136]33, [137]34]. However,
   the underlying therapeutic mechanisms have not been fully elucidated.
   Using a combination of network pharmacology and in vitro biological
   experiments, we explored the molecular mechanisms of Hyp treatment in
   NSCLC from the viewpoint of the drug–target-pathway.

   In this study, we identified 30 therapeutic targets using network
   pharmacology. After topological analysis of the PPI network, five key
   targets were identified: MMP9, CASP3, MAPK1, ESR1, and EGFR. These
   targets have a high degree value, indicating that they may play a
   crucial role in the mechanism of action of Hyp in the treatment of
   NSCLC. In addition, the results of the molecular docking analysis
   showed that Hyp had good binding activity with EGFR, MAPK1, and MMP9.
   The docking score between EGFR and Hyp was the lowest, indicating the
   highest binding affinity. EGFR is a cell surface receptor encoded by
   the ErbB1 gene, and its overexpression or abnormal activation is
   closely associated with the progression of NSCLC [[138]35]. Currently,
   receptor tyrosine kinase inhibitors such as gefitinib and erlotinib,
   which target EGFR, have been effectively used in the clinical treatment
   of NSCLC [[139]36]. MAPK1 is a downstream target of the MAPK signaling
   pathway, also known as ERK2, which can transfer extracellular
   information into cells, thus regulating the cell proliferation,
   apoptosis, and differentiation. Compared to normal cells, the
   noticeably downregulated expression of MAPK1 was detected in NSCLC
   cells [[140]37], and MAPK1 knockdown remarkably attenuated the
   proliferation and metastasis of lung adenocarcinoma cells [[141]38].
   MMP9 is a vital enzyme in the human body that could specifically
   degrade the extracellular matrix or substrate and participates in the
   tumor cells invasion and metastasis. MMP9 was highly expressed that was
   positively correlated with the invasion progression of NSCLC cells
   [[142]39]. It was found that blocking the expression of MMP9 with a
   PI3K inhibitor could weaken their invasion and metastasis [[143]40]. As
   one of the most important executors of cell apoptosis, CASP3 is
   activated by upstream signals and can produce cascade effects to induce
   the apoptosis. One study confirmed by in vitro experiments that CASP3
   was involved in the Hyp-induced apoptotic process in NSCLC cells
   [[144]34]. ESR1, an estrogen receptor, is closely associated with the
   occurrence, progression, and metastasis of breast cancer. In recent
   years, some studies have reported that ESR1 has clinical significance
   in the diagnosis, treatment, and prognosis of NSCLC [[145]41, [146]42].

   Our GO enrichment analysis results showed that these potential targets
   were mainly involved in cell proliferation, migration, apoptosis, and
   oxidative stress, which were important factors influencing Hyp against
   NSCLC. KEGG pathway enrichment analysis showed that FoxO and MAPK
   signaling pathways were closely related to the molecular mechanisms of
   Hyp against NSCLC. MAPK1, EGFR, and insulin-like growth factor 1
   receptor(IGF1R) were enriched in the FoxO and MAPK signaling pathways.
   Among these, MAPK1 and EGFR were key targets and showed satisfactory
   binding activity with Hyp. FOXO is a member of the forkhead
   transcription factor family, which includes four members: FOXO1, FOXO3,
   FOXO4, and FOXO6. They participate in many physiological and
   pathological processes such as apoptosis, the cell cycle, and DNA
   damage repair by regulating the expression of downstream genes
   [[147]43]. FOXO1 is underexpressed in NSCLC cells, and its upregulation
   is a favorable prognostic factor [[148]44, [149]45]. Hu et al.
   [[150]10] clarified that the anti-NSCLC activity of Hyp may be
   attributed to the inhibition of proliferation and apoptosis of tumor
   cells by upregulating FOXO1 expression. The AMPK signaling pathway has
   been confirmed to be located upstream of FOXO proteins, and its
   disruption could alter the activity or expression of FOXO protein
   [[151]46]. Based on these results, we suspect that Hyp regulates the
   proliferation and apoptosis of tumor cells by acting on the
   EGFR/ERK/FOXO1 pathway, thus playing a therapeutic role in NSCLC.

   In this study, the potential relationship between Hyp and NSCLC was
   systematically analyzed by network pharmacology method. To test this
   hypothesis, we conducted several in vitro experiments. Because A549
   cell line was the most widely used adenocarcinoma model in the research
   of NSCLC, our study chose this cell line as the experimental object,
   aiming at clarifying the molecular mechanisms of Hyp in the treatment
   of NSCLC. The CCK-8 assay showed that Hyp reduced the viability of A549
   cells in a time- and dose-dependent manner. We observed, through EdU
   staining, that Hyp effectively inhibited the proliferation of A549
   cells and the EGFR activator NSC228155 attenuated this inhibition. We
   also found that after Hyp treatment, the apoptosis rate of A549 cells
   increased significantly, and the expression of Cleaved-Caspase-3 and
   Bax increased significantly, whereas the expression of Bcl-2 decreased
   significantly, indicating that Hyp could induce apoptosis in A549
   cells. Notably, when Hyp and NSC228155 were used simultaneously, the
   apoptosis rate of A549 cells was significantly reduced. In addition, we
   studied the effect of Hyp on the EGFR/ERK/FOXO1 pathway using western
   blotting. The results showed that the ratios of p-EGFR/EGFR and
   p-ERK1/2/ERK1/2 decreased in A549 cells after Hyp intervention,
   suggesting that Hyp activates EGFR and ERK1/2 through protein
   phosphorylation. Following Hyp treatment, the expression level of FOXO1
   in A549 cells increased significantly. However, NSC228155 counteracted
   these changes, indicating that Hyp upregulated FOXO1 expression by
   inhibiting the activities of EGFR and ERK1/2. Therefore, we believe
   that Hyp has the potential to treat NSCLC, primarily by regulating the
   EGFR/ERK/FOXO1 pathway to inhibit the proliferation of tumor cells and
   induce the apoptosis of tumor cells.

   In this study, several key targets and promising signaling pathways
   were successfully identified through network pharmacology. However, due
   to the limitation of research funds, the multi-target and multi-pathway
   mechanism of Hyp in NSCLC has not been systematically verified by
   experiments. Our in vitro experiment only used A549 adenocarcinoma cell
   line, but failed to cover other subtypes of NSCLC, such as squamous
   cell carcinoma, which may lead to limited universality of the research
   conclusions. It is worth noting that although Hyp has shown remarkable
   therapeutic effects in vitro, several in vivo model studies are
   required to facilitate its clinical application.

Conclusion

   In this study, we identified key targets and signaling pathways of Hyp
   in the treatment of NSCLC using a network pharmacology method. In
   addition, our in vitro experiments confirmed that Hyp inhibited the
   proliferation and induced apoptosis of lung adenocarcinoma cells
   through regulation of the EGFR/ERK/FOXO1 pathway. These findings
   indicate that Hyp is a promising and effective multitarget drug. Our
   findings also emphasize the critical role of network pharmacology in
   target screening and pathway prediction for drug development. However,
   the follow-up work needs to be extended to squamous cell carcinoma cell
   lines, such as H1703 and SK-MES-1, to verify the universality of this
   mechanism in different histological subtypes.

Supplementary Information

   Below is the link to the electronic supplementary material.
   [152]Supplementary Material 1.^ (11.7KB, xlsx)
   [153]Supplementary Material 2.^ (13KB, xlsx)
   [154]Supplementary Material 3.^ (11.3KB, xlsx)
   [155]Supplementary Material 4.^ (13.7KB, xlsx)
   [156]Supplementary Material 5.^ (10.4KB, xlsx)
   [157]Supplementary Material 6.^ (254.2KB, pdf)
   [158]Supplementary Material 7.^ (373.3KB, pdf)

Acknowledgements