Network pharmacology analysis of the inhibitory effects of Eucommiae Folii extract in prostate cancer

Network pharmacology analysis of the inhibitory effects of Eucommiae Folii extract in prostate cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Network pharmacology analysis of the inhibitory effects of Eucommiae Folii extract in prostate cancer Shuang E, Yucheng Wu, Zhendian Wu, Shijun Yu, Huan Wang, Ruibo Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9235944/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract The mechanisms of inhibitory effects of Eucommia ulmoides leaf (EUL) extract on prostate cancer were investigated through network pharmacology, molecular docking, and experimental validation. Active ingredients of EUL and 118 common targets were retrieved using the TCMSP, UniProt, and DisGeNET. Ten hub genes, including AKT1, BCL2, and MMP9, were identified using Cytoscape. KEGG enrichment analysis identified key pathways, such as the PI3K-Akt signaling pathway and the prostate cancer pathway. Molecular docking using AutoDock Vina revealed strong binding affinities between the active components and hub targets. Three active components, quercetin, kaempferol, and (+)-catechin, were detected in the EUL extract using HPLC. In vitro experiments showed that the EUL extract dose- and time-dependently inhibited PC-3 cell viability and invasion, elevated the expression of pro-apoptotic proteins, suppressed anti-apoptotic and invasion-associated proteins, and raised the apoptosis rate to 24.48% at 100 µg/mL. SC79 intervention confirmed EUL acted via targeting PI3K/Akt pathway, supporting its potential as a natural anti-prostate cancer agent. Biological sciences/Cancer Biological sciences/Computational biology and bioinformatics Biological sciences/Drug discovery Health sciences/Oncology prostate cancer Eucommiae Folii extract quercetin kaempferol (+)-catechin PI3K/Akt signaling Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1. Introduction Prostate cancer is the second most frequent diagnosed cancer after lung cancer and remains a leading cause of cancer-related mortality among males ( Siegel et al., 2022 ) . According to the National Cancer Institute, the incidence of prostate cancer increases sharply with age, peaking in the 75–79-year age group (Grozescu et al., 2017) . Global annual deaths from prostate cancer are projected to rise from 375,000 in 2020 to approximately 700,000 by 2040 ( James et al., 2024 ) . Although treatment, including surgery, radiotherapy, and chemotherapy, has improved, the therapeutic efficacy of prostate cancer treatment is still not optimal, and drug resistance, recurrence, and treatment-related side effects are major problems. For example, patients undergoing androgen deprivation therapy frequently develop resistance, leading to castration resistance. Death typically occurs within 1–3 years after progression (Boorjian et al., 2007; Litwin et al., 2017; Salonen et al., 2008) . Therefore, the development of novel and effective therapeutic strategies and drugs is important for improving outcomes in patients with prostate cancer. Recently, the application of traditional Chinese medicine in anticancer therapy has attracted increasing interest. Traditional Chinese medicines elicit multi-component, multi-target, and multi-pathway integrative regulatory effects. For example, Astragalus membranaceus is a traditional Chinese medicinal herb. Astragalus polysaccharide exerts anti-tumor effects through multiple mechanisms, including inhibition of tumor cell proliferation, induction of apoptosis, cell cycle arrest, as well as suppression of tumor cell invasion and migration (Ren et al., 2025) . Additionally, Astragalus polysaccharide exerts a chemosensitizing effect on nasopharyngeal carcinoma cells by inducing apoptosis and modulating the Bax/Bcl-2 ratio and caspase expression (Zhou et al., 2017) . In clinical applications, Astragalus polysaccharide can be combined with herbs such as Coix seed and Polygonatum sibiricum to form a Prostate Eliminate Syndrome Decoction, which effectively suppresses the progression of prostate cancer (Pang et al., 2013) . Quercetin, derived from Hedyotis diffusa, suppresses Akt phosphorylation. The PI3K/Akt signaling pathway contributes to prostate cancer pathogenesis ( Yi et al., 2023 ) and affects prostate cancer cell survival. Other medicinal ingredients such as Taxus chinensis var. mairei , Calculus bovis , and Atractylodes macrocephala may also modulate the PI3K/Akt signaling pathway (Li et al., 2024) . Eucommia ulmoides Oliv., a relic species belonging to the Eucommiaceae family, is a rare medicinal plant unique to China. E. ulmoides is widely used in medicine and health food products due to its anti-osteoporosis, anti-inflammatory, neuroprotective, antihypertensive, hypoglycemic, and hepatorenal protective effects. E. ulmoides also alleviates sexual dysfunction ( Huang et al., 2021 ) . These beneficial physiological effects are attributed to bioactive compounds, including cyclic ethers, phenols, flavonoids, lignans, polysaccharides, and sterols ( Huang et al., 2021 ; Bao et al., 2024 ) . The chemical composition and pharmacological effects of E. ulmoides leaves (EUL) are similar to the effects of E. ulmoides bark ( A Y F X et al., 2019 ) . Moreover, the leaves are abundant and easy to collect with minimal damage to the parent plant. Thus, the use of EUL supports the sustainable development of the E. ulmoides cultivation industry. EUL has a long history of dietary use. Porridge and wine are customarily produced from the leaves in areas where E. ulmoides grows; these products are suitable for treating kidney deficiency, insomnia, dream-disturbed sleep, general debility, and soreness and weakness in the waist and knees, and poor immunity. In November 2023, EUL was included in the directory of substances for both food and traditional Chinese medicine (medicinal and edible homologous substances) by the National Health Commission of China, permitting their use in health beverages and food ingredients. EUL is rich in flavonoids, polyphenols, polysaccharides, and chlorogenic acid. Thus, Eucommia leaves display significant antioxidant activity (Zeng et al., 2018) . EUL also contain chlorogenic acid, geniposidic acid, and pinoresinol diglucoside, which have stable antihypertensive effects with no side effects ( Li et al., 2021 ) . The abundant flavonoids, chlorogenic acid, aucubin, and geniposide in EUL improve lipid regulation ( Lee et al., 2019 ; Hao et al., 2016 ) . Total flavonoids from E. ulmoides sensitize human glioblastoma cells to radiotherapy via the HIF-α/matrix metalloproteinase (MMP)-2 pathway and activate the intrinsic apoptotic pathway ( Wang et al., 2019 ) . Furthermore, total flavonoids from EUL effectively suppress the proliferation of colorectal cancer cells and induce apoptosis, demonstrating multi-target antitumor potential (Miao, 2024) . Eucommicin A, which was isolated from EUL, inhibited cancer stem cell proliferation ( Fujiwara et al., 2016 ) . In addition, quercitrin from E. ulmoides inhibits cell viability and migration in hepatocellular carcinoma HCCLM3 cells and downregulates SERPINE1 expression, exhibiting biological effects against liver cancer progression (Liao et al., 2025) . Moreover, E. ulmoides seed oil demonstrates dose-dependent inhibition of pancreatic cancer cell proliferation, colony formation, and migration, and can mitigate the progression of digestive system cancers by suppressing the PI3K-AKT-mTOR pathway ( Wu et al., 2025 ) . As a traditional Chinese medicine, E. ulmoides exhibits multi-target actions. In this study, network pharmacology was employed for the first time to investigate the mechanisms by which active EUL components affected prostate cancer-related genes. Network pharmacology is a nascent interdisciplinary field that combines systems biology, pharmacology, computer science, and other disciplines ( TING-TING L et al., 2020 ) . The core concept of network pharmacology is the analysis of complex network relationships among drugs, diseases, and biological systems to reveal drug mechanisms, predict drug efficacy and side effects, and guide drug development and clinical application. Cell experiments were conducted to validate the results of the network pharmacology analysis, elucidating the mechanisms for the inhibitory effects of EUL extract on the viability of prostate cancer PC-3 cells. These experiments lay the foundation for understanding the effects of EUL on prostate cancer. 2. Experimental methods 2.1. Chemicals and reagents The following reagents were used in the studies described below: EUL (Sichuan Hengruitongda); complex enzyme (hemicellulase: pectinase:neutral protease: 3:2:3, w/w/w) (Yuanye, Shanghai); methanol, acetonitrile, phosphoric acid, absolute ethanol, and methanol (Macklin, Shanghai, HPLC grade); quercetin, kaempferol, and (+)-catechin (Yuanye, Shanghai, purity ≥ 98%); diphenyleneiodonium chloride (DPI) and fetal bovine serum (FBS) (Solarbio, Beijing, China); penicillin-streptomycin (Thermo Fisher Scientific, Pittsburgh, PA, USA); RPMI 1640 medium (GIBCO, Invitrogen Corporation, NY, USA); trypsin (KeyGEN Biotech, Nanjing, China); CCK-8 assay kit, 4% paraformaldehyde fixative solution, and crystal violet staining solution (Beyotime, Shanghai, China); Ponceau S, Tween 20, and PMSF (Amresco, VWR International, OH, USA); western blot membrane regeneration solution (Biolab, Beijing, China); 30% acrylamide, 1.0 mol/L Tris pH 6.8, 1.5 mol/L Tris pH 8.8 (Beyotime, Shanghai, China); BCA protein quantification kit (KeyGEN BioTECH, Nanjing, China); loading buffer (NCM Biotech, Suzhou, China); 10% sodium dodecyl sulfate (SDS) (Biosharp, Hefei, China); TEMED (Boster, Wuhan, China); transfer membrane powder, electrophoresis powder, and TBST powder (Servicebio, Wuhan, China); electrochemiluminescence (ECL) luminescence solution (Thermo Fisher Scientific, Pittsburgh, PA, USA); anti-MMP-9 antibody, anti-MMP-2 antibody, anti-Bcl-2 antibody, anti-Bax antibody, anti-AKT antibody (9272) and anti-p-AKT (Ser473) antibody (4060) (Cell Signaling Technology, Boston, USA); anti-Caspase3 antibody (ab32351); anti-β-actin antibody (ab8226), goat anti-rabbit IgG H&L (HRP) (ab6721), and goat anti-mouse IgG H&L (HRP) (ab150115) (Abcam, Cambridge, UK); anti-PI3K antibody (AF6242) and anti-p-PI3K (p85 (Tyr458)/p55 (Tyr199)) antibody (AF3242) (Affinity Biosciences, OH, USA); SC79 (123871) (Sigma-Aldrich, St. Louis, MO, USA); Annexin V-FITC Apoptosis Detection Kit (KGA1102) (KeyGEN Biotech, Nanjing, China); BCA protein assay kit (Pierce, Grand Island, NY, USA); polyvinylidene fluoride (PVDF) membranes (Millipore, Billerica, MA, USA); Transwell chamber basement membrane (8 µm pores, Corning, NY, USA); and human prostate cancer cells (PC-3 cells, American Tissue Culture Collection, Rockville, MD, USA). The following equipment was used: freeze dryer (Boyikang, Nanjing), Agilent 1260 high-performance liquid chromatography (Agilent, USA), ultrasonic cleaner (JP, Shenzhen), water-jacketed CO 2 incubator (Thermo Fisher), full-wavelength microplate reader (Detie, Nanjing), upright biological microscope and inverted microscope (Nikon, Japan), ultra-low temperature freezer (Model FORMA 700) (Thermo, USA), super clean bench (SW-CJ-2FD) (Suzhou Purification Equipment Co., Ltd., Suzhou, China), transfer decolorization shaker (Xk-8) (Jiangsu Xinkang Medical Equipment Co., Ltd., Jiangsu, China), western blotting system (Criterion™ electrophoresis tank, Trans-Blot® transfer tank) (Bio-Rad, USA), luminescence imaging workstation (Tanon 5200) (Tanon, Shanghai, China), microplate multifunctional enzyme marker (Berthold LB941) (Berthold, Germany), and water-jacketed CO 2 incubator (Forma 3111) (Thermo Electron, USA), flow cytometer (Beckman DxFLEX) (Beckman, USA). 2.2. Network pharmacology analysis The active components of EUL were screened using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database ( https://www.tcmsp-e.com/tcmsp.php ). Compounds meeting the criteria of oral bioavailability ≥ 30% and drug-likeness ≥ 0.18 were considered as active ingredients. Related targets were obtained from the TCMSP database, and target name standardization was performed using the UniProt database( https://www.uniprot.org/ ) to obtain gene names. Prostate cancer-related targets were retrieved from the DisGeNET ( http://www.disgenet.org ), GeneCards ( https://www.genecards.org/ ), and OMIM ( https://omim.org/ ) databases. The targets for the active components of Eucommia ulmoides were imported into Venny 2.1 to construct an EUL–prostate cancer Venn diagram. Intersection genes were extracted, and a component–target–prostate cancer network diagram was constructed using Cytoscape 3.10.1. To predict the pathways affected by the active ingredient targets of EUL involved in prostate cancer regulation, the intersecting genes were submitted to the DAVID database ( https://davidbioinformatics.nih.gov ) for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The enrichment results were visualized using the bioinformatics online platform ( https://www.bioinformatics.com.cn/ ), and colored GO enrichment bar charts and KEGG enrichment bubble diagrams were generated. The intersection genes were also imported into the KEGG database ( https://www.kegg.jp/ ) for pathway analysis. A protein–protein interaction (PPI) analysis was performed by importing the intersection genes into the STRING database ( https://cn.string-db.org/ ). The resulting data were imported into Cytoscape, and a PPI network was constructed based on betweenness centrality and degree values. Hub genes were identified using the MCC algorithm of the CytoHubba plugin. Hub gene network diagrams and a component–target–pathway network diagram were generated. 2.3. Molecular docking validation The ligand files (mol2 format) for kaempferol, (+)-catechin, and quercetin were downloaded from the TCMSP database. Hub target proteins were selected and obtained from the Research Collaboratory for Structural Bioinformatics Protein Data Bank (PDB) ( https://www.rcsb.org ) based on the search parameters “Homo sapiens” and “X-ray”. Receptor files for each protein were exported in the PDB Format. The original receptor files were processed using PyMOL to remove water molecules and ligands, and the optimized structures were output in the “pdb” format. These pdb files were imported into AutoDockTools, where hydrogen atoms were added and the files were saved in the “pdbqt” format. In AutoDockTools, docking boxes were generated for each receptor protein. The “Grid box” function was opened, and the box size was adjusted to ensure complete protein receptor coverage. The adjusted docking box files were exported in the “gpf” format. The molecular docking process was conducted using the AutoDock Vina program within the command prompt terminal. A log.txt file was generated to record the docking results, and an output.pdbqt file was produced in PyMOL to visualize the docking results. 2.4. Preparation of the EUL extract Fresh EUL was dried with hot air at 50°C for 8 hours. The dried leaves were pulverized by a grinder and passed through a 100-mesh sieve. The powder (10 g) was placed in a 250 mL conical flask. The extraction procedure was carried out under the following parameters: solid-to-liquid ratio, 1:25; complex enzyme dosage, 0.3%; pH 6; temperature, 50°C; and time, 100 minutes. After extraction, the mixture was filtered under vacuum. The filtrate was inactivated at 95°C for 2 minutes and cooled. The resulting solution was freeze-dried under vacuum to obtain a powdered extract. 2.5. HPLC quantitative analysis Standard solutions of quercetin, kaempferol, and (+)-catechin (2, 1, 0.5, and 0.25 mg/mL, respectively) were prepared using the corresponding mobile phase. A 172.30 mg/mL test sample solution was prepared and serially diluted to 86.15, 43.08, 21.54, and 10.77 mg/mL. Sonication was performed at 300 W and 45 kHz for 30 minutes. Following vacuum filtration, the solutions were passed through a 0.22 µm membrane. All preparations were repeated in triplicate. Chromatography for quercetin and kaempferol ( Chinese Pharmacopoeia Commission, 2011 ) was performed using a Shimadzu C18 column (5 µm, 4.6 mm × 250 mm) with a mobile phase A consisting of 0.4% phosphoric acid in water and a mobile phase B consisting of methanol. The gradient elution program for quercetin and kaempferol was established as follows: 0–10 min, 20% B to 40% B; 10–20 min, 40% B to 50% B; 20–30 min, 50% B to 60% B; and 30–40 min, 60% B to 70% B. The flow rate was maintained at 1.0 mL/min, the detection wavelength was set at 262 nm, the column was kept at room temperature, and the injection volume was 10 µL. Chromatography for (+)-catechin (Ailai·Saikan et al., 2016) was performed using a Shimadzu C18 column (5 µm, 4.6 mm × 250 mm) with a mobile phase A consisting of 0.4% phosphoric acid in water and a mobile phase B consisting of acetonitrile. The isocratic elution was performed with A-B (87:13, v/v). The detection wavelength was set at 280 nm, and the column temperature was maintained at 35°C. All other parameters were the same as the parameters for quercetin and kaempferol chromatography. Chromatograms were recorded using the HPLC system software, and peak areas were automatically integrated. Calibration curves were constructed by plotting peak areas (y-axis) against the corresponding concentrations of reference standards (x-axis) using linear regression analysis. The content of each analyte in the test samples was calculated by substituting the measured peak area into the corresponding regression equation derived from the calibration curve. All calculations were performed using the average values of three determinations. 2.6. Cell culture After reaching 85% confluence, PC-3 cells were subcultured in RPMI-1640 medium containing 100 U/mL penicillin, 100 µg/mL streptomycin, and 10% FBS. After washing with 2 mL PBS, 2 mL of 0.25% trypsin-0.02% EDTA was added to the cells. After the cells became rounded, 2 mL of complete medium was added to stop the digestion, and the cells were collected. The cells were centrifuged at 800 rpm and 4°C for 5 minutes. After discarding the supernatant, the cell pellet was resuspended in complete medium for subculturing. The medium was replaced every other day. 2.7. Cell viability PC-3 cells in the logarithmic phase were harvested and plated into 96-well plates with a seeding density of 0.6×10 5 cells per well. After culturing for 24 hours to allow cell attachment, the medium was changed according to the following groups: the Control group received drug-free medium; the Eucommia groups received medium containing E. ulmoides leaf (EUL) extract at final concentrations of 6.25, 25, and 100 µg/mL; and the DPI group received medium containing 10 µmol/L diphenyleneiodonium chloride. For the inhibitor assay, cells were treated with 100 µg/mL EUL in the presence or absence of 2 µg/mL SC79 (Sigma-Aldrich). After 24 and 48 hours of incubation, cell viability was measured using the CCK-8 assay. The old medium was aspirated, and the cells were rinsed three times with PBS. Then, 100 µL of medium containing 10% CCK-8 working solution was added to each well. The plates were gently shaken and incubated for 2 hours. The absorbance at 450 nm was determined with a microplate reader, and the resulting data were compared and analyzed. Each experiment was performed in triplicate. 2.8. Cell migration PC-3 cells were first cultured for 24 h and then treated for 16 h with either drug-free medium (Control), medium containing EUL extract (final concentrations: 6.25, 25, or 100 µg/mL), or medium containing 10 µmol/L diphenyleneiodonium chloride (DPI) (N = 3 per group). The method is also implemented in the inhibitor assay. After treatment, the cells were digested with trypsin, centrifuged, and re-suspended in serum-free medium. The cell density was adjusted to 5×10 5 cells/mL to prepare a single-cell suspension. The Transwell chamber basement membrane (8 µm pores, Corning, NY, USA) was coated with 50 µL of Matrigel (50 mg/L, BD Biosciences) and incubated for 4 hours at 37°C to solidify. After removing the remaining liquid, 70 µL of medium was added to the upper chamber, and the chambers were incubated at 37°C for 30 minutes for hydration. Subsequently, 200 µL of the single-cell suspension were added along the wall of the upper chamber. Medium (600 µL with 10% FBS) was added to the lower chambers, and the plates were incubated at 37°C for 24 hours under conventional culture conditions. Invading cells in the lower chamber were fixed with 500 µL of 4% paraformaldehyde for 20 minutes, stained with 0.1% crystal violet at 37°C for 30 minutes, and images were captured under an inverted microscope. All experiments were conducted in triplicate. 2.9. Western blot assay PC-3 cells (5×10 5 cells per well) in the logarithmic growth phase were seeded into 6-well plates. The control group was cultured with medium only, and the EUL extract groups were treated with medium containing 6.25 µg/mL, 25 µg/mL, and 100 µg/mL of EUL extract. After 72 hours, cells were trypsinized and collected. For every 100 µL of compacted cell volume, 1 mL of RIPA buffer supplemented with PMSF was added for complete lysis. The lysates were centrifuged at 12,000 g and 4°C for 5 minutes to extract total protein. Protein concentrations were measured using a BCA protein assay kit. Subsequently, proteins were electrophoresed on 10–12% SDS polyacrylamide gels and transferred to PVDF membranes. The membranes were blocked for 1 hour at room temperature with 5% skim milk in TBST on a decolorizing shaker. Primary antibodies (Table 1 ) were applied, and the membranes were incubated overnight at 4°C. Subsequently, HRP-conjugated secondary antibodies (Table 1 ) were added, and the membranes were incubated for 1 hour at room temperature. Antibody binding was visualized using ECL on a Tanon 5200 luminescence imaging workstation. Quantification of protein expression levels was performed by measuring optical density values with Image Pro Plus 6.0 software. Relative protein expression was calculated as the ratio of the target protein band intensity to the internal reference protein band intensity. The expression levels of PI3K, p-PI3K, Akt and p-Akt proteins were detected by the same method as described for the inhibitor assay (Table 1 ). Table 1 Antibodies and dilution Antibodies Dilution VEGFA 1:1000 PI3K p85/p55 1:1000 p-PI3K p85/p55 (Tyr458, Tyr199) 1:1000 Akt 1:1000 p-Akt(Ser473) 1:2000 MMP-2 1:1000 MMP-9 1:1000 bcl-2 1:2000 Bax 1:1000 p53 1:1000 Caspase 3 1:1000 β-actin 1:3000 Goat Anti-Rabbit IgG H&L (HRP) 1:10000 Goat Anti-Mouse IgG H&L (HRP) 1:10000 Table 1 . Antibodies and dilution 2.10. Flow cytometry analysis of apoptosis PC-3 cells were treated according to the respective grouping protocol, and were subsequently washed twice with PBS. The cell suspension was transferred to a sterile centrifuge tube and centrifuged at 2000 rpm for 5 min. The supernatant was discarded, and the cells were then washed twice with PBS and centrifuged again at 2000 rpm for 5 min to collect 1×10 5 cells. The cells were resuspended in 0.5 mL of staining buffer per tube, followed by the addition of 5 µL of Annexin V-FITC staining solution were added to each tube with gentle mixing. Subsequently, 5 µL of propidium iodide was added and mixed. The samples were incubated at room temperature for 15 min in the dark. Finally, the samples were analyzed using a flow cytometer. 2.11. Data analysis Data were analyzed and plotted using GraphPad Prism 9 (Version 9.4.0), and figures were compiled using Adobe Illustrator (Version 26.3.1). The Tukey multiple-comparison test was used after one-way ANOVA. All data are expressed as the mean ± SD (n = 3). 3. Experimental Results 3.1. Acquisition of intersection genes and construction of the component-target-prostate cancer network Active components of EUL, including kaempferol, (+)-catechin, and quercetin, were identified from the TCMSP database. The active components were imported into the SwissTargetPrediction database, yielding 156 targets after eliminating duplicates. A search for “prostate cancer” in the DisGeNET, GeneCards, and OMIM databases yielded 2877 disease-related targets after eliminating duplicates. A Venn diagram of active component targets and disease targets revealed 118 overlapping targets (Fig. 1A). The overlapping targets were imported into the STRING database to generate the PPI network diagram, consisting of 118 nodes and 2320 edges (Fig. 1B). The data from the STRING database were subsequently loaded into Cytoscape 3.9.1 to perform network topology analysis. After removing loosely correlated scattered points, a PPI network with 115 nodes and 2311 edges was constructed based on betweenness centrality and degree values (Fig. 1C). Node sizes reflect degree values, and color depth indicates betweenness centrality. Thus, larger nodes with deeper red coloration indicate greater connectivity with other proteins in the network and a higher likelihood of target relevance. A component-target-prostate cancer network diagram was generated. Figure 1. Analysis of intersecting genes. (A) Venn diagram of components versus diseases. (B) Protein-protein interaction network map. (C) Topological analysis of the PPI network. (D) Component-target-prostate cancer network diagram. 3.2. Construction of the protein-protein interaction network and GO and KEGG analyses Intersection targets were analyzed using the DAVID database. GO functional classification and enrichment analyses revealed 826 significantly enriched terms (p < 0.05), comprising 516 biological processes (BPs), 49 cellular components (CCs), and 106 molecular functions (MFs) (Fig. 2A and B). The top 10 enriched BPs were: positive regulation of transcription from RNA polymerase II promoter, positive regulation of gene expression, positive regulation of transcription, DNA-templated, negative regulation of apoptotic process, positive regulation of cell proliferation, regulation of transcription from RNA polymerase II promoter, apoptotic process, negative regulation of transcription from RNA polymerase II promoter, signal transduction, and response to xenobiotic stimulus. The 10 most enriched CCs included the nucleus, cytoplasm, cytosol, nucleoplasm, plasma membrane, extracellular space, extracellular region, membrane, chromatin, and mitochondrion. The top 10 most enriched MFs were protein binding, identical protein binding, enzyme binding, protein homodimerization function, RNA polymerase II core promoter proximal region sequence-specific DNA binding, DNA binding, sequence-specific DNA binding transcription factor activity, RNA polymerase II transcription factor activity (sequence-specific DNA binding), protein kinase binding, and ATP binding. KEGG pathway analysis showed 155 significantly enriched pathways (p < 0.05), as shown in Fig. 2C. The most significantly enriched pathways included pancreatic cancer, prostate cancer, AGE-RAGE signaling pathway in diabetic complications, fluid shear stress and atherosclerosis, toxoplasmosis, hepatitis B, lipid and atherosclerosis, hepatitis C, and Kaposi sarcoma-associated herpesvirus infection. The prostate cancer pathway ranked second with 24 related targets, indicating that the targets were highly relevant to prostate cancer. Intersection genes were imported into the KEGG database for analysis, and the prostate cancer pathway was selected to generate Fig. 2D. Figure 2. GO and KEGG analyses. (A) Bubble map of GO pathway enrichment analysis ( P < 0.05). (B) Colored bar chart of GO pathway enrichment analysis ( P < 0.05). (C) Bubble map of KEGG analysis ( P < 0.05). (D) Distribution map of intersecting genes in the prostate cancer pathway.The KEGG pathway map (map05215) is used with permission from Kanehisa Laboratories. KEGG: Kyoto Encyclopedia of Genes and Genomes ( https://www.kegg.jp/kegg/kegg1.html ). 3.3. Hub gene screening and construction of the component-target-pathway network The CytoHubba plugin in Cytoscape was utilized for hub gene screening. The protein-protein interaction network data file was imported. The MCC algorithm was selected to screen the top 10 genes. Ten hub genes were identified and exported (Fig. 3A). A “component-target-pathway” network diagram was constructed (Fig. 3B). In the central circle, the left red circle represents the 10 hub genes, while the right red circle represents the 24 genes enriched in the prostate cancer pathway based on the KEGG analysis; the three overlapping genes are displayed in the center. Green and light green circles represent other genes. The left deep-red rectangles represent bioactive compounds, the right yellow rectangles represent KEGG pathways, and the connecting edges indicate interactions or associations among compounds, genes, and pathways. Figure 3. Network analysis of hub targets and pathways. (A) Hub target network map. (B) Component-target-pathway network. 3.4. Molecular docking and visualization To confirm the binding interactions, molecular docking between the 10 hub genes and kaempferol, (+)-catechin, and quercetin was assessed. Binding energies below − 5.0 kcal/mol suggest a favorable interaction between ligand and receptor. A heatmap was employed to visualize the binding energies between the active components and target proteins, with darker colors indicating lower binding energies (Fig. 4A). The binding energies between the three active components and the hub genes ranged from − 5.9 to − 9.2 kcal/mol, indicating favorable binding. Representative docking results are shown in Fig. 4B. Figure 4. Molecular Docking and Visualization. (A) Molecular docking heatmap. The numbers represent binding energy (kcal·mol − 1 ). A deeper red color corresponds to a lower binding energy, thereby indicating a more stable interaction. (B) Molecular docking visualization. 3.5. Content of active ingredients in EUL extract The kaempferol, (+)-catechin, and quercetin levels in the enzymatically hydrolyzed extract of EUL were measured using HPLC, as shown in Fig. 5. The linear regression equations for quercetin, kaempferol, and (+)-catechin, respectively, were established within the concentration range of 0.25–2.0 mg/mL, as follows: y = 4143.6x − 51.812 (R 2 = 0.9969), y = 2467.3x − 22.833 (R 2 = 0.9970), y = 7599.2x − 849.12 (R 2 = 0.9902). After substituting the average peak areas into the equations, the quercetin, kaempferol, and (+)-catechin were 1.3663 mg/g, 0.8577 mg/g, and 52.5817 mg/g, respectively. Figure 5. HPLC chromatograms for the active components of Eucommia ulmoides . (A) Quercetin (1) and kaempferol (2) standards. (B) Quercetin (1) and kaempferol (2) samples. (C) Standard for (+)-catechin. (D) Sample of (+)-catechin (1). 3.6. Effects of EUL extract on PC-3 cell survival and invasiveness PC-3 cell viability was significantly reduced after 24 hours of treatment with 100 µg/mL Eucommia or 10 µmol/L DPI compared with cell viability in the Control group (Fig. 6A). After 48 hours of incubation, PC-3 cell viability was significantly reduced in the 25 µg/mL Eucommia, 100 µg/mL Eucommia, and 10 µmol/L DPI groups compared with cell viability in the Control group. The invasion ability of PC-3 cells was significantly and dose-dependently reduced in the 25 µg/mL Eucommia, 100 µg/mL Eucommia, and 10 µmol/L DPI groups compared with the invasion ability in the Control group after a 16-hour pretreatment followed by a 24-hour Transwell assay (Fig. 6B). Figure 6. The effects of Eucommia extract on cell viability and invasive ability in PC-3 cells. (A) CCK-8 assays, indicating cell viability, after 24 or 48 hours of treatment with 6.25, 25, or 100 µg/mL Eucommia, 10 µmol/L DPI, or media only (Control group) (*p < 0.05, **p < 0.01). (B) Transwell assays, indicating invasive ability, after treatment with 6.25, 25, or 100 µg/mL Eucommia, 10 µmol/L DPI, or media only (Control group). Representative images of the stained cells in the lower chambers (left) and the quantification of staining (right) are shown. (**p < 0.01) 3.7. Effects of EUL extract on apoptosis-related proteins in PC-3 cells The relative protein levels of VEGFA, MMP-2, MMP-9, and Bcl-2 decreased significantly after 72 hours of treatment with 6.25–100 µg/mL EUL extract compared with the Control group in PC-3 cells (Fig. 7A, B, G, H, and I). The phosphorylation levels of PI3K and Akt also decreased after 72 hours of treatment with 6.25–100 µg/mL EUL extract (EUL groups) compared with the Control group (Fig. 7A, D, and F); however, the total protein expression levels of PI3K and Akt remained unchanged. (Fig. 7A, C, and E). The relative protein levels of Bax, p53, and cleaved-Caspase-3 increased significantly in the 25 µg/mL and 100 µg/mL EUL groups compared with the Control group (Fig. 7A, J, K, and L). However, the protein levels of total caspase 3 exhibited no significant alterations. (Fig. 7A and M). Higher concentrations of EUL showed better effects, indicating a concentration-dependent response. Figure 7. Relative levels of apoptosis-related proteins measured by western blotting after treatment with 6.25–100 µg/mL EUL extract or media only (Control group). (A) Representative western blots. Quantification of western blots, including (B) VEGFA, (C) PI3K, (D) p-PIK/PI3K, (E) Akt, (F) p-Akt/Akt, (G) MMP-2, (H) MMP-9, (I) Bcl-2, (J) Bax, (K) p53, (L) cleaved caspase 3/caspase 3, and (M) caspase 3. (**p < 0.01)(Cropped blots are displayed with dividing lines indicating where non-relevant lanes have been removed. Uncropped full‑length blots are provided in the corresponding Supplementary Information) 3.8. EUL extract affects PC-3 cells through inhibiting the Akt pathway 3.8.1 Effects of Akt activator SC79 on the reversal of EUL-induced suppression of PC-3 cell viability After 24 or 48 hours of incubation, compared with the Control group, PC-3 cell viability was significantly increased in the 2 µg/mL SC79 group and significantly decreased in the 100 µg/mL EUL group. Compared with the 2 µg/mL SC79 group, the co-administration of 100 µg/mL EUL significantly reversed the pro-proliferative effect mediated by SC79 treatment. (Fig. 8). Figure 8. The Akt activator SC79 reverses the suppression of PC-3 cell viability induced by Eucommia leaf extract, as measured by CCK-8 assays. After 24 or 48 hours of treatment with media only (Control group), 2 µg/mL SC79, 2 µg/mL SC79 + 100 µg/mL EUL, or 100 µg/mL EUL. (*p < 0.05, **p < 0.01) 3.8.2 Effects of Akt activator SC79 on the reversal of EUL-induced inhibition of PC-3 cell invasion Compared with the Control group, the invasion ability of PC-3 cells was significantly increased in the 2 µg/mL SC79 group and significantly decreased in the 100 µg/mL EUL group. Compared with the SC79 group, the administration of EUL markedly suppressed cell invasion (Fig. 9). Figure 9. The Akt activator SC79 reverses the inhibition of PC-3 cell invasion induced by Eucommia leaf extract by Transwell assays. Representative images of the stained cells in the lower chambers (left) and the quantification of staining (right) are shown. Columns marked with distinct letters denote statistically significant differences at the level of P < 0.05. 3.8.3 Effects of Akt activator SC79 on the reversal of EUL-induced modulation of PI3K/Akt pathway-related proteins in PC-3 cells The expression levels of total PI3K and Akt proteins were not significantly different. Compared with the control group, the 2 µg/mL SC79 group exhibited a marked upregulation in the phosphorylation levels of PI3K (p-PI3K) and Akt (p-Akt). The concurrent administration of 100 µg/mL EUL significantly attenuated the SC79-induced elevation of p-PI3K and p-Akt, while their expression levels stayed significantly elevated compared to those in the control group. Notably, treatment with 100 µg/mL EUL alone led to a significant reduction in the expression of both phosphorylated proteins (Fig. 10). Figure 10. The Akt activator SC79 reverses the modulation of PI3K/Akt signaling proteins induced by Eucommia leaf extract. (A) Representative western blots. Quantification of western blots, including (B) PI3K, (C) p-PI3K/PI3K, (D) Akt, and (E) p-Akt/Akt. Columns marked with distinct letters represent significant differences at the threshold of P < 0.05.(Cropped blots are displayed with dividing lines indicating where non-relevant lanes have been removed. Uncropped full-length blots are provided in the corresponding Supplementary Information) 3.8.4 Effects of Akt activator SC79 on the reversal of EUL-induced apoptosis in PC-3 cells Compared with the control group, the apoptosis level of the SC79 group was significantly decreased, whereas the apoptosis levels of both the SC79 + EUL group and EUL group were markedly elevated. Specifically, treatment with 100 µg/mL EUL increased the apoptosis rate from 4.18% to 24.48% (Fig. 11). Figure 11. The Akt activator SC79 reverses the apoptosis induced by Eucommia leaf extract in PC-3 cells. (A) Typical flow cytometry dot plots. (B) Quantitative analysis of apoptosis rates. Data are expressed as the mean ± SD, n = 3. Columns labeled with different letters signify statistically significant differences at P < 0.05. 4. Discussion The objective of this study was to investigate the mechanisms underlying the protective effects of EUL extract against prostate cancer. Although EUL exhibited inhibitory effects on human glioblastoma cells and cancer stem cells ( Wang et al., 2019 ; Miao, 2024) , investigations into the protective effects of EUL are limited. EUL tone the liver and kidneys and strengthen bones and tendons. Thus, EUL are commonly used to treat liver and kidney deficiency, dizziness, soreness and weakness of the waist and knees, and muscle flaccidity (Jia et al., 2012) . The effects of EUL on bone-related conditions, such as rheumatoid arthritis and muscle fatigue, have also been validated. Although the prostate is not explicitly mentioned in classical traditional Chinese medicine texts, prostate functions are often categorized under the kidney system, and prostate function is believed to be closely related to kidney health; sufficient kidney qi ensures normal prostate function, and kidney qi deficiency may affect prostate health. Therefore, we hypothesized that EUL might protect against prostate cancer. To investigate this hypothesis, a network pharmacology approach was employed. Three components of EUL extracts with high absorption and drug-likeness, kaempferol, (+)-catechin, and quercetin, were first identified. The potential targets of these three components and prostate cancer-related targets were integrated, and data mining was performed. KEGG analysis indicated that prominently enriched pathways comprised the PI3K-Akt signaling pathway, the MAPK signaling pathway, and the prostate cancer pathway. Within the prostate cancer pathway, 24 target genes overlapped with the active Eucommia ulmoides component targets, and three of these overlapping genes were identified as hub genes. These findings suggest that EUL may influence the progression of prostate cancer by acting on prostate cancer-related targets and pathways, such as AKT1, BCL2, and MMP9. Subsequent western blot analysis confirmed the involvement of these key targets, showing that the EUL extract significantly suppressed Akt phosphorylation, downregulated the expression of Bcl-2, and reduced the protein level of MMP9 in PC-3 cells. AKT1 is involved in the PI3K/Akt signaling pathway, which regulates cell proliferation, apoptosis, and metabolism; therefore, this pathway impacts the progression of multiple cancer types, such as prostate cancer ( Wang et al., 2024 ; Yang et al., 2019 ) . Bcl-2 plays a key role in the mitochondria-mediated intrinsic apoptotic pathway. Bcl-2 inhibits apoptosis by preventing the release of pro-apoptotic factors (such as cytochrome c) from mitochondria ( Kiraz et al., 2016 ; Schenk et al., 2017) . MMP9 is responsible for encoding matrix metalloproteinase-9, a member of the MMP family ( Mondal et al., 2020 ; Rashid et al., 2023) . MMP9 can significantly influence prostate cancer invasion, metastasis, and progression by degrading the extracellular matrix, promoting angiogenesis, and regulating inflammatory responses (Rashid et al., 2023) . The KEGG analysis indicated that 27 intersection targets were involved in the PI3K/Akt pathway. Therefore, EUL may affect prostate cancer cell survival, migration, invasion, and proliferation via multiple targets mediating PI3K/Akt signaling and apoptosis pathways. The molecular docking results indicated potential binding of the three active components with the 10 core targets (all less than − 5.0 kcal/mol) and strong binding with PTSG2 (all less than − 8.0 kcal/mol). The three active components from EUL included the (+)-catechin, quercetin, and kaempferol are flavonoids. Flavonoids are polyphenolic compounds widely present in plants with multiple biological activities and health benefits. Kaempferol induces apoptosis in cervical cancer cells by downregulating the PI3K/Akt pathway to reduce cell growth and increase apoptotic gene expression (e.g., p53), thereby triggering cell death (Kashafi et al., 2017) . Kaempferol induces apoptosis in ovarian cancer cells via G2/M cell cycle arrest and downregulation of key signaling pathways such as MEK/ERK and JNK/ERK ( Gao et al., 2018 ; Yang et al., 2019 ; Zhao et al., 2017 ) . Quercetin contributes to normal mitochondrial function and affects cell cycle and autophagy via multiple signaling pathways, including Wnt/β-catenin (Shan et al., 2009) , PI3K/Akt/mTOR (Hasan et al., 2022; Lu et al., 2020 ) , MAPK/ERK1/2 ( Erdogan et al., 2018 ) , and STAT3 ( Liu et al., 2017 ) , to promote cancer cell apoptosis and inhibit angiogenesis. Quercetin reverses docetaxel resistance in prostate cancer through the androgen receptor and PI3K/Akt signaling pathway to promote apoptosis in prostate cancer cells ( Lu et al., 2020 ) . (+)-Catechin suppresses gastric cancer cell proliferation and migration, modulates the cell cycle, and promotes cell death by influencing PI3K/Akt signaling ( Ding et al., 2024 ) . In addition, (+)-Catechin enhances the anti-proliferative activity of docetaxel in prostate cancer cell models (El Nahass et al., 2025) . Kaempferol, (+)-catechin, and quercetin were detected in the EUL extract used in this study; (+)-catechin exhibited the highest content at 52.5817 mg/g. PC-3 cells are an androgen-independent human prostate cancer cell line commonly used for exploring the biological characteristics of prostate cancer, drug screening, and treatment strategies. In this study, the addition of EUL extract inhibited the proliferation of PC-3 cells in a concentration- and time-dependent manner. This is the first study to validate the inhibitory effects of EUL extract on prostate cancer cell proliferation. EUL extract also inhibited the invasive ability of PC-3 prostate cancer cells in a dose-dependent manner. The expression levels of MMP-2 and MMP-9 proteins, which are associated with cell invasion and migration, were significantly reduced by EUL extract treatment. MMPs are involved in the degradation and remodeling of the extracellular matrix. Thus, MMPs are critically involved in modulating tumor cell invasion, migration, and distant metastasis. The expression and activity of MMPs are regulated by multiple signaling pathways. For example, activation of the VEGFA signaling pathway upregulates MMP expression to promote angiogenesis (Heissig et al., 2005) . The NF-κB signaling pathway, which is a critical hub for inflammation and stress regulation, regulates the expression of various MMPs. The upregulation of MMPs leads to excessive degradation of the extracellular matrix, compromising the integrity of the basement membrane, which is required for tumor cells to detach from the primary site, invade surrounding tissues, and ultimately enter the circulatory system. The PI3K/Akt pathway is a cellular signaling cascade that serves critical functions in cell growth, survival, metabolism, and migration (Fruman et al., 2017) . This pathway is typically activated in PC-3 cells. Bcl-2 and Bax are downstream effectors of the PI3K/Akt pathway that regulate apoptosis. Western blots were performed to investigate the effects of EUL extract on proteins related to the PI3K/Akt pathway. Consistent with the KEGG pathway results for prostate cancer action in network pharmacology, EUL extract significantly suppressed PI3K and Akt phosphorylation levels. The relative levels of the apoptosis-related proteins Bax and cleaved-caspase-3 were significantly increased, and expression of the anti-apoptotic protein Bcl-2 was decreased. These findings suggest that EUL extract likely suppresses the activation of the PI3K/Akt pathway, promoting the expression of apoptosis-related proteins (Bax and cleaved-caspase-3) and reducing the expression of the anti-apoptotic Bcl-2 to promote apoptosis in PC-3 cells. To test the hypothesis that EUL directly intervened in the PI3K-Akt pathway to regulate PC-3 cell functions, we established an experimental model using the Akt activator SC79 to treat PC-3 cells, followed by investigation of the biological effects of EUL on SC79-pretreated cells. Experimental data revealed that SC79 exposure significantly promoted PC-3 cell invasion and survival while suppressing cellular apoptosis. Conversely, the introduction of EUL effectively mitigated the pro-tumorigenic effects mediated by SC79. Furthermore, the reduction in p-PI3K and p-Akt protein expression induced by EUL suggests that EUL exerts its regulatory role on PC-3 cells through direct targeting of the PI3K-Akt signaling cascade. 5. Conclusions This study explored the anti-prostate cancer effect and underlying mechanism of Eucommia ulmoides Oliv. leaf (EUL) extract on PC-3 cells via an approach of network pharmacology, molecular docking, and in vitro experiments. Network pharmacology identified three key active components in EUL—kaempferol, (+)-catechin, and quercetin—with 118 overlapping targets related to prostate cancer. KEGG enrichment analysis highlighted the PI3K-Akt signaling pathway and prostate cancer pathway as core functional pathways, and hub genes including AKT1, BCL2, and MMP9 were identified as critical targets. Molecular docking validated favorable binding interactions between the active components and hub proteins (binding energies: −5.9 to − 9.2 kcal/mol), while HPLC quantification showed (+)-catechin was the most abundant component (52.5817 mg/g) in the EUL extract. In vitro experiments demonstrated that EUL extract inhibited PC-3 cell viability in a concentration- and time-dependent manner and suppressed cell invasion dose-dependently. Mechanistically, EUL extract significantly reduced PI3K and Akt phosphorylation (without altering total protein levels), upregulated pro-apoptotic proteins (Bax, p53, cleaved-Caspase-3), while downregulating the anti-apoptotic protein Bcl-2 and invasion-associated proteins (MMP-2, MMP-9, VEGFA). Flow cytometry confirmed EUL extract increased the PC-3 cell apoptosis rate from 4.18% to 24.48% at 100 µg/mL. Intervention with the Akt activator SC79 further verified that EUL reversed SC79-induced promotion of cell viability and invasion, as well as suppression of apoptosis, by attenuating SC79-mediated upregulation of p-PI3K and p-Akt. Collectively, the findings confirm that EUL extract inhibits prostate cancer PC-3 cell proliferation and invasion, and promotes apoptosis, by directly targeting the PI3K-Akt signaling pathway. This study provides evidence for EUL as a potential natural anti-prostate cancer agent and lays a foundation for its further development and clinical translation. Future research could focus on in vivo validation and optimization of active component extraction to enhance bioavailability. Declarations Funding Statement This work was supported by the Major Key Scientific Research Project of the Department of Education of Anhui Province (Grant No. 2022AH051112), the Anhui Provincial College Student Innovation and Entrepreneurship Training Program (Grant No. S202510377083), the Research Start-up Fund of Chuzhou University (Grant Nos. 2022qd51 and 2022qd014), and the Open Experimental Project of Chuzhou University (No. 2025-45). The funders had no role in the study design, data collection, analysis, decision to publish, or preparation of the manuscript. Author Contribution Shuang E selects the research topic and obtains funding, Yucheng Wu completes the experimental content and writes the manuscript. Others assisted and participated in the execution of the experiment.All authors reviewed the manuscript. Data Availability All data generated or analysed during this study are included in this published article. References SIEGEL R L, MILLER K D, FUCHS H E, et al. 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Journal of Computational Chemistry, 31(2), 455–461. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigureUncroppedBlots.pdf Supplementarydatamaterials.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 21 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers invited by journal 20 Apr, 2026 Editor assigned by journal 20 Apr, 2026 Editor invited by journal 20 Apr, 2026 Submission checks completed at journal 16 Apr, 2026 First submitted to journal 16 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9235944","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":627711023,"identity":"52e9f1f7-8252-409e-a0bd-c15f5b61d503","order_by":0,"name":"Shuang E","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYFACHjApxyABppmJ12JMupbEBqK18POfPSbxc0dtev/s9mcSDBXWiQ3sZw/g1SI5Iy9NsvfM8dwZdw6kSTCcSU9s4MlLwKvF4AaPmQRv27HcDRIJxyQY2w4DXchjgFeL/fkzZpJ/246lG0gktkkw/iNCiwFDjpk0b1tNgoFEMpsEYwMRWiRu5Bhby7YdMJxxI43ZIuFYunEbTw5+Lfz9Zwxvvm2rk+efkf7wxocaa9l+9jP4tUDBYQiVAMRsxKgHgjoi1Y2CUTAKRsGIBABXjECvewbJPgAAAABJRU5ErkJggg==","orcid":"","institution":"Chuzhou University","correspondingAuthor":true,"prefix":"","firstName":"Shuang","middleName":"","lastName":"E","suffix":""},{"id":627711024,"identity":"ba8ecb1c-45fa-4655-8517-c3b1d26640b7","order_by":1,"name":"Yucheng Wu","email":"","orcid":"","institution":"Chuzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yucheng","middleName":"","lastName":"Wu","suffix":""},{"id":627711025,"identity":"96d2859d-927b-4313-ac6f-125ba54a2974","order_by":2,"name":"Zhendian Wu","email":"","orcid":"","institution":"Chuzhou University","correspondingAuthor":false,"prefix":"","firstName":"Zhendian","middleName":"","lastName":"Wu","suffix":""},{"id":627711026,"identity":"57fd3309-9a41-4788-8f44-e8058f06b283","order_by":3,"name":"Shijun Yu","email":"","orcid":"","institution":"Chuzhou University","correspondingAuthor":false,"prefix":"","firstName":"Shijun","middleName":"","lastName":"Yu","suffix":""},{"id":627711032,"identity":"f50a4e7e-8bcc-4ad8-a798-7b0fd0f50a30","order_by":4,"name":"Huan Wang","email":"","orcid":"","institution":"Chuzhou University","correspondingAuthor":false,"prefix":"","firstName":"Huan","middleName":"","lastName":"Wang","suffix":""},{"id":627711033,"identity":"5d1ddadd-09bb-4e67-934d-3a4ca6e56c0e","order_by":5,"name":"Ruibo Xu","email":"","orcid":"","institution":"Chuzhou University","correspondingAuthor":false,"prefix":"","firstName":"Ruibo","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2026-03-26 15:24:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9235944/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9235944/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108492905,"identity":"cccafcb3-2c30-496f-ade2-c82a7c2ad0ef","added_by":"auto","created_at":"2026-05-05 09:58:57","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":8275215,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of intersecting genes. (A) Venn diagram of components versus diseases. (B) Protein-protein interaction network map. (C) Topological analysis of the PPI network. (D) Component-target-prostate cancer network diagram.\u003c/p\u003e","description":"","filename":"Figure01.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/f3e4a383d0ea65fcebefaa99.jpeg"},{"id":108386932,"identity":"140d0865-e40a-44a2-a2b4-7241bc7fa3f1","added_by":"auto","created_at":"2026-05-04 06:26:43","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4309313,"visible":true,"origin":"","legend":"\u003cp\u003eGO and KEGG analyses. (A) Bubble map of GO pathway enrichment analysis (P \u0026lt; 0.05). (B) Colored bar chart of GO pathway enrichment analysis (P \u0026lt; 0.05). (C) Bubble map of KEGG analysis (P \u0026lt; 0.05). (D)Distribution map of intersecting genes in the prostate cancer pathway.The KEGG pathway map (map05215) is used with permission from Kanehisa Laboratories. KEGG: Kyoto Encyclopedia of Genes and Genomes (https://www.kegg.jp/kegg/kegg1.html).\u003c/p\u003e","description":"","filename":"Figure02.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/5702989cb7c3a682c5ac1c51.jpeg"},{"id":108386891,"identity":"48eea28e-fdf8-4d19-ac6f-a8e3ffa01bb0","added_by":"auto","created_at":"2026-05-04 06:26:27","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":6009626,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork analysis of hub targets and pathways. (A) Hub target network map. (B) Component-target-pathwaynetwork.\u003c/p\u003e","description":"","filename":"Figure03.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/89825f5afc1bf598f9fcebf2.jpeg"},{"id":108387001,"identity":"25f0ceb6-b426-4e63-bfe8-0bba7cca74c7","added_by":"auto","created_at":"2026-05-04 06:26:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular Docking and Visualization. (A) Molecular docking heatmap. The numbers represent binding energy (kcal·mol\u003csup\u003e−1\u003c/sup\u003e). A deeper red color corresponds to a lower binding energy, thereby indicating a more stable interaction. (B) Molecular docking visualization.\u003c/p\u003e","description":"","filename":"placeholderimage.png","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/dd613ce5a11b4c070ddc9598.png"},{"id":108386879,"identity":"7faab21d-32bb-40a0-bc4a-4484a2d45190","added_by":"auto","created_at":"2026-05-04 06:26:12","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2610442,"visible":true,"origin":"","legend":"\u003cp\u003eHPLC chromatograms for the active components of \u003cem\u003eEucommia ulmoides\u003c/em\u003e. (A) Quercetin (1) and kaempferol (2) standards. (B) Quercetin (1) and kaempferol (2) samples. (C) Standard for (+)-catechin. (D) Sample of (+)-catechin (1).\u003c/p\u003e","description":"","filename":"Figure05.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/3a82357c42ff403f2b021678.jpeg"},{"id":108387015,"identity":"4ba533a3-1cae-489e-a26b-302cb662e873","added_by":"auto","created_at":"2026-05-04 06:26:46","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3329309,"visible":true,"origin":"","legend":"\u003cp\u003eThe effects of Eucommia extract on cell viability and invasive ability in PC-3 cells. (A) CCK-8 assays, indicating cell viability, after 24 or 48 hours of treatment with 6.25, 25, or 100 μg/mL Eucommia, 10 μmol/L DPI, or media only (Control group) (*p \u0026lt; 0.05, **p \u0026lt; 0.01). (B) Transwell assays, indicating invasive ability, after treatment with 6.25, 25, or 100 μg/mL Eucommia, 10 μmol/L DPI, or media only (Control group). Representative images of the stained cells in the lower chambers (left) and the quantification of staining (right) are shown. (**p \u0026lt; 0.01)\u003c/p\u003e","description":"","filename":"Figure06.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/f697a8c9262245c5286fc90f.jpeg"},{"id":108386931,"identity":"1d5091e1-ef01-48db-b1b8-125a0fbc7781","added_by":"auto","created_at":"2026-05-04 06:26:42","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eRelative levels of apoptosis-related proteins measured by western blotting after treatment with 6.25–100 μg/mL EUL extract or media only (Control group). (A) Representative western blots. Quantification of western blots, including (B) VEGFA, (C) PI3K, (D) p-PIK/PI3K, (E) Akt, (F) p-Akt/Akt, (G) MMP-2, (H) MMP-9, (I) Bcl-2, (J) Bax, (K) p53, (L) cleaved caspase 3/caspase 3, and (M) caspase 3. (**p \u0026lt; 0.01)(Cropped blots are displayed with dividing lines indicating where non-relevant lanes have been removed. Uncropped full‑length blots are provided in the corresponding Supplementary Information)\u003c/p\u003e","description":"","filename":"placeholderimage.png","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/8813a02f3e35c5948c3b624c.png"},{"id":108386880,"identity":"e11160a2-a9d8-49e2-a943-42a375c2a289","added_by":"auto","created_at":"2026-05-04 06:26:12","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":2559401,"visible":true,"origin":"","legend":"\u003cp\u003eThe Akt activator SC79 reverses the suppression of PC-3 cell viability induced by Eucommia leaf extract, as measured by CCK-8 assays. After 24 or 48 hours of treatment with media only (Control group), 2 μg/mL SC79, 2 μg/mL SC79 + 100 μg/mL EUL, or 100 μg/mL EUL. (*p \u0026lt; 0.05, **p \u0026lt; 0.01)\u003c/p\u003e","description":"","filename":"Figure08.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/8aa4883f68975e556f992257.jpeg"},{"id":108386893,"identity":"c0b1c557-5c29-4f6e-89c6-e5d61000bfb3","added_by":"auto","created_at":"2026-05-04 06:26:28","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":3031526,"visible":true,"origin":"","legend":"\u003cp\u003eThe Akt activator SC79 reverses the inhibition of PC-3 cell invasion induced by Eucommia leaf extract by Transwell assays. Representative images of the stained cells in the lower chambers (left) and the quantification of staining (right) are shown. Columns marked with distinct letters denote statistically significant differences at the level of P \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Figure09.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/50991fdf5e2885815d59c2e2.jpeg"},{"id":108386897,"identity":"8c8e7853-88d9-4560-8767-f6810d6c6a18","added_by":"auto","created_at":"2026-05-04 06:26:29","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eThe Akt activator SC79 reverses the modulation of PI3K/Akt signaling proteins induced by Eucommia leaf extract. (A) Representative western blots. Quantification of western blots, including (B) PI3K, (C) p-PI3K/PI3K, (D) Akt, and (E) p-Akt/Akt. Columns marked with distinct letters represent significant differences at the threshold of P \u0026lt; 0.05.(Cropped blots are displayed with dividing lines indicating where non-relevant lanes have been removed. Uncropped full-length blots are provided in the corresponding Supplementary Information)\u003c/p\u003e","description":"","filename":"placeholderimage.png","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/d339fcd045883e20bf79d61c.png"},{"id":108386928,"identity":"2aca311a-766e-43e1-9215-7d9cbd066525","added_by":"auto","created_at":"2026-05-04 06:26:42","extension":"jpeg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":3256301,"visible":true,"origin":"","legend":"\u003cp\u003eThe Akt activator SC79 reverses the apoptosis induced by Eucommia leaf extract in PC-3 cells. (A) Typical flow cytometry dot plots. (B) Quantitative analysis of apoptosis rates. Data are expressed as the mean ± SD, n = 3. Columns labeled with different letters signify statistically significant differences at P \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Figure11.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/724095406820b435ed864b2f.jpeg"},{"id":108803840,"identity":"60e0afbd-f0a1-4d87-999d-16adb05673cb","added_by":"auto","created_at":"2026-05-08 15:09:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":33756277,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/81e1f86f-0f46-4b36-86c9-979005d369ad.pdf"},{"id":108386930,"identity":"6a0fd7b8-a417-4d7c-8d04-edd952880c88","added_by":"auto","created_at":"2026-05-04 06:26:42","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8514454,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigureUncroppedBlots.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/aeb30f63d6dd40f19c5b9208.pdf"},{"id":108386927,"identity":"005fe231-44fd-4caa-98c7-33c3f8141c8a","added_by":"auto","created_at":"2026-05-04 06:26:42","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":24157669,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydatamaterials.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9235944/v1/784dd4551118a692f0cbc6aa.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Network pharmacology analysis of the inhibitory effects of Eucommiae Folii extract in prostate cancer","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eProstate cancer is the second most frequent diagnosed cancer after lung cancer and remains a leading cause of cancer-related mortality among males \u003cem\u003e(\u003c/em\u003eSiegel et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. According to the National Cancer Institute, the incidence of prostate cancer increases sharply with age, peaking in the 75\u0026ndash;79-year age group \u003cem\u003e(Grozescu et al., 2017)\u003c/em\u003e. Global annual deaths from prostate cancer are projected to rise from 375,000 in 2020 to approximately 700,000 by 2040 \u003cem\u003e(\u003c/em\u003eJames et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. Although treatment, including surgery, radiotherapy, and chemotherapy, has improved, the therapeutic efficacy of prostate cancer treatment is still not optimal, and drug resistance, recurrence, and treatment-related side effects are major problems. For example, patients undergoing androgen deprivation therapy frequently develop resistance, leading to castration resistance. Death typically occurs within 1\u0026ndash;3 years after progression \u003cem\u003e(Boorjian et al., 2007; Litwin et al., 2017; Salonen et al., 2008)\u003c/em\u003e. Therefore, the development of novel and effective therapeutic strategies and drugs is important for improving outcomes in patients with prostate cancer.\u003c/p\u003e \u003cp\u003eRecently, the application of traditional Chinese medicine in anticancer therapy has attracted increasing interest. Traditional Chinese medicines elicit multi-component, multi-target, and multi-pathway integrative regulatory effects. For example, \u003cem\u003eAstragalus membranaceus\u003c/em\u003e is a traditional Chinese medicinal herb. Astragalus polysaccharide exerts anti-tumor effects through multiple mechanisms, including inhibition of tumor cell proliferation, induction of apoptosis, cell cycle arrest, as well as suppression of tumor cell invasion and migration \u003cem\u003e(Ren et al., 2025)\u003c/em\u003e. Additionally, Astragalus polysaccharide exerts a chemosensitizing effect on nasopharyngeal carcinoma cells by inducing apoptosis and modulating the Bax/Bcl-2 ratio and caspase expression \u003cem\u003e(Zhou et al., 2017)\u003c/em\u003e. In clinical applications, Astragalus polysaccharide can be combined with herbs such as Coix seed and Polygonatum sibiricum to form a Prostate Eliminate Syndrome Decoction, which effectively suppresses the progression of prostate cancer \u003cem\u003e(Pang et al., 2013)\u003c/em\u003e. Quercetin, derived from Hedyotis diffusa, suppresses Akt phosphorylation. The PI3K/Akt signaling pathway contributes to prostate cancer pathogenesis \u003cem\u003e(\u003c/em\u003eYi et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e and affects prostate cancer cell survival. Other medicinal ingredients such as \u003cem\u003eTaxus chinensis\u003c/em\u003e var. \u003cem\u003emairei\u003c/em\u003e, \u003cem\u003eCalculus bovis\u003c/em\u003e, and \u003cem\u003eAtractylodes macrocephala\u003c/em\u003e may also modulate the PI3K/Akt signaling pathway \u003cem\u003e(Li et al., 2024)\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eEucommia ulmoides\u003c/em\u003e Oliv., a relic species belonging to the \u003cem\u003eEucommiaceae\u003c/em\u003e family, is a rare medicinal plant unique to China. \u003cem\u003eE. ulmoides\u003c/em\u003e is widely used in medicine and health food products due to its anti-osteoporosis, anti-inflammatory, neuroprotective, antihypertensive, hypoglycemic, and hepatorenal protective effects. \u003cem\u003eE. ulmoides\u003c/em\u003e also alleviates sexual dysfunction \u003cem\u003e(\u003c/em\u003eHuang et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. These beneficial physiological effects are attributed to bioactive compounds, including cyclic ethers, phenols, flavonoids, lignans, polysaccharides, and sterols \u003cem\u003e(\u003c/em\u003eHuang et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bao et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. The chemical composition and pharmacological effects of \u003cem\u003eE. ulmoides\u003c/em\u003e leaves (EUL) are similar to the effects of \u003cem\u003eE. ulmoides\u003c/em\u003e bark \u003cem\u003e(\u003c/em\u003eA Y F X et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. Moreover, the leaves are abundant and easy to collect with minimal damage to the parent plant. Thus, the use of EUL supports the sustainable development of the \u003cem\u003eE. ulmoides\u003c/em\u003e cultivation industry.\u003c/p\u003e \u003cp\u003eEUL has a long history of dietary use. Porridge and wine are customarily produced from the leaves in areas where \u003cem\u003eE. ulmoides\u003c/em\u003e grows; these products are suitable for treating kidney deficiency, insomnia, dream-disturbed sleep, general debility, and soreness and weakness in the waist and knees, and poor immunity. In November 2023, EUL was included in the directory of substances for both food and traditional Chinese medicine (medicinal and edible homologous substances) by the National Health Commission of China, permitting their use in health beverages and food ingredients. EUL is rich in flavonoids, polyphenols, polysaccharides, and chlorogenic acid. Thus, Eucommia leaves display significant antioxidant activity \u003cem\u003e(Zeng et al., 2018)\u003c/em\u003e. EUL also contain chlorogenic acid, geniposidic acid, and pinoresinol diglucoside, which have stable antihypertensive effects with no side effects \u003cem\u003e(\u003c/em\u003eLi et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. The abundant flavonoids, chlorogenic acid, aucubin, and geniposide in EUL improve lipid regulation \u003cem\u003e(\u003c/em\u003eLee et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hao et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. Total flavonoids from \u003cem\u003eE. ulmoides\u003c/em\u003e sensitize human glioblastoma cells to radiotherapy via the HIF-α/matrix metalloproteinase (MMP)-2 pathway and activate the intrinsic apoptotic pathway \u003cem\u003e(\u003c/em\u003eWang et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. Furthermore, total flavonoids from EUL effectively suppress the proliferation of colorectal cancer cells and induce apoptosis, demonstrating multi-target antitumor potential \u003cem\u003e(Miao, 2024)\u003c/em\u003e. Eucommicin A, which was isolated from EUL, inhibited cancer stem cell proliferation \u003cem\u003e(\u003c/em\u003eFujiwara et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. In addition, quercitrin from \u003cem\u003eE. ulmoides\u003c/em\u003e inhibits cell viability and migration in hepatocellular carcinoma HCCLM3 cells and downregulates SERPINE1 expression, exhibiting biological effects against liver cancer progression \u003cem\u003e(Liao et al., 2025)\u003c/em\u003e. Moreover, \u003cem\u003eE. ulmoides\u003c/em\u003e seed oil demonstrates dose-dependent inhibition of pancreatic cancer cell proliferation, colony formation, and migration, and can mitigate the progression of digestive system cancers by suppressing the PI3K-AKT-mTOR pathway \u003cem\u003e(\u003c/em\u003eWu et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2025\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eAs a traditional Chinese medicine, \u003cem\u003eE. ulmoides\u003c/em\u003e exhibits multi-target actions. In this study, network pharmacology was employed for the first time to investigate the mechanisms by which active EUL components affected prostate cancer-related genes. Network pharmacology is a nascent interdisciplinary field that combines systems biology, pharmacology, computer science, and other disciplines \u003cem\u003e(\u003c/em\u003eTING-TING L et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. The core concept of network pharmacology is the analysis of complex network relationships among drugs, diseases, and biological systems to reveal drug mechanisms, predict drug efficacy and side effects, and guide drug development and clinical application. Cell experiments were conducted to validate the results of the network pharmacology analysis, elucidating the mechanisms for the inhibitory effects of EUL extract on the viability of prostate cancer PC-3 cells. These experiments lay the foundation for understanding the effects of EUL on prostate cancer.\u003c/p\u003e"},{"header":"2. Experimental methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Chemicals and reagents\u003c/h2\u003e \u003cp\u003eThe following reagents were used in the studies described below: EUL (Sichuan Hengruitongda); complex enzyme (hemicellulase: pectinase:neutral protease: 3:2:3, w/w/w) (Yuanye, Shanghai); methanol, acetonitrile, phosphoric acid, absolute ethanol, and methanol (Macklin, Shanghai, HPLC grade); quercetin, kaempferol, and (+)-catechin (Yuanye, Shanghai, purity\u0026thinsp;\u0026ge;\u0026thinsp;98%); diphenyleneiodonium chloride (DPI) and fetal bovine serum (FBS) (Solarbio, Beijing, China); penicillin-streptomycin (Thermo Fisher Scientific, Pittsburgh, PA, USA); RPMI 1640 medium (GIBCO, Invitrogen Corporation, NY, USA); trypsin (KeyGEN Biotech, Nanjing, China); CCK-8 assay kit, 4% paraformaldehyde fixative solution, and crystal violet staining solution (Beyotime, Shanghai, China); Ponceau S, Tween 20, and PMSF (Amresco, VWR International, OH, USA); western blot membrane regeneration solution (Biolab, Beijing, China); 30% acrylamide, 1.0 mol/L Tris pH 6.8, 1.5 mol/L Tris pH 8.8 (Beyotime, Shanghai, China); BCA protein quantification kit (KeyGEN BioTECH, Nanjing, China); loading buffer (NCM Biotech, Suzhou, China); 10% sodium dodecyl sulfate (SDS) (Biosharp, Hefei, China); TEMED (Boster, Wuhan, China); transfer membrane powder, electrophoresis powder, and TBST powder (Servicebio, Wuhan, China); electrochemiluminescence (ECL) luminescence solution (Thermo Fisher Scientific, Pittsburgh, PA, USA); anti-MMP-9 antibody, anti-MMP-2 antibody, anti-Bcl-2 antibody, anti-Bax antibody, anti-AKT antibody (9272) and anti-p-AKT (Ser473) antibody (4060) (Cell Signaling Technology, Boston, USA); anti-Caspase3 antibody (ab32351); anti-β-actin antibody (ab8226), goat anti-rabbit IgG H\u0026amp;L (HRP) (ab6721), and goat anti-mouse IgG H\u0026amp;L (HRP) (ab150115) (Abcam, Cambridge, UK); anti-PI3K antibody (AF6242) and anti-p-PI3K (p85 (Tyr458)/p55 (Tyr199)) antibody (AF3242) (Affinity Biosciences, OH, USA); SC79 (123871) (Sigma-Aldrich, St. Louis, MO, USA); Annexin V-FITC Apoptosis Detection Kit (KGA1102) (KeyGEN Biotech, Nanjing, China); BCA protein assay kit (Pierce, Grand Island, NY, USA); polyvinylidene fluoride (PVDF) membranes (Millipore, Billerica, MA, USA); Transwell chamber basement membrane (8 \u0026micro;m pores, Corning, NY, USA); and human prostate cancer cells (PC-3 cells, American Tissue Culture Collection, Rockville, MD, USA).\u003c/p\u003e \u003cp\u003eThe following equipment was used: freeze dryer (Boyikang, Nanjing), Agilent 1260 high-performance liquid chromatography (Agilent, USA), ultrasonic cleaner (JP, Shenzhen), water-jacketed CO\u003csub\u003e2\u003c/sub\u003e incubator (Thermo Fisher), full-wavelength microplate reader (Detie, Nanjing), upright biological microscope and inverted microscope (Nikon, Japan), ultra-low temperature freezer (Model FORMA 700) (Thermo, USA), super clean bench (SW-CJ-2FD) (Suzhou Purification Equipment Co., Ltd., Suzhou, China), transfer decolorization shaker (Xk-8) (Jiangsu Xinkang Medical Equipment Co., Ltd., Jiangsu, China), western blotting system (Criterion\u0026trade; electrophoresis tank, Trans-Blot\u0026reg; transfer tank) (Bio-Rad, USA), luminescence imaging workstation (Tanon 5200) (Tanon, Shanghai, China), microplate multifunctional enzyme marker (Berthold LB941) (Berthold, Germany), and water-jacketed CO\u003csub\u003e2\u003c/sub\u003e incubator (Forma 3111) (Thermo Electron, USA), flow cytometer (Beckman DxFLEX) (Beckman, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Network pharmacology analysis\u003c/h2\u003e \u003cp\u003eThe active components of EUL were screened using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.tcmsp-e.com/tcmsp.php\u003c/span\u003e\u003cspan address=\"https://www.tcmsp-e.com/tcmsp.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Compounds meeting the criteria of oral bioavailability\u0026thinsp;\u0026ge;\u0026thinsp;30% and drug-likeness\u0026thinsp;\u0026ge;\u0026thinsp;0.18 were considered as active ingredients. Related targets were obtained from the TCMSP database, and target name standardization was performed using the UniProt database(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.uniprot.org/\u003c/span\u003e\u003cspan address=\"https://www.uniprot.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to obtain gene names. Prostate cancer-related targets were retrieved from the DisGeNET (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.disgenet.org\u003c/span\u003e\u003cspan address=\"http://www.disgenet.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), GeneCards (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genecards.org/\u003c/span\u003e\u003cspan address=\"https://www.genecards.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and OMIM (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://omim.org/\u003c/span\u003e\u003cspan address=\"https://omim.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) databases. The targets for the active components of \u003cem\u003eEucommia ulmoides\u003c/em\u003e were imported into Venny 2.1 to construct an EUL\u0026ndash;prostate cancer Venn diagram. Intersection genes were extracted, and a component\u0026ndash;target\u0026ndash;prostate cancer network diagram was constructed using Cytoscape 3.10.1.\u003c/p\u003e \u003cp\u003eTo predict the pathways affected by the active ingredient targets of EUL involved in prostate cancer regulation, the intersecting genes were submitted to the DAVID database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://davidbioinformatics.nih.gov\u003c/span\u003e\u003cspan address=\"https://davidbioinformatics.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The enrichment results were visualized using the bioinformatics online platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.com.cn/\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.com.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and colored GO enrichment bar charts and KEGG enrichment bubble diagrams were generated. The intersection genes were also imported into the KEGG database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.kegg.jp/\u003c/span\u003e\u003cspan address=\"https://www.kegg.jp/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for pathway analysis. A protein\u0026ndash;protein interaction (PPI) analysis was performed by importing the intersection genes into the STRING database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cn.string-db.org/\u003c/span\u003e\u003cspan address=\"https://cn.string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The resulting data were imported into Cytoscape, and a PPI network was constructed based on betweenness centrality and degree values. Hub genes were identified using the MCC algorithm of the CytoHubba plugin. Hub gene network diagrams and a component\u0026ndash;target\u0026ndash;pathway network diagram were generated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Molecular docking validation\u003c/h2\u003e \u003cp\u003eThe ligand files (mol2 format) for kaempferol, (+)-catechin, and quercetin were downloaded from the TCMSP database. Hub target proteins were selected and obtained from the Research Collaboratory for Structural Bioinformatics Protein Data Bank (PDB) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rcsb.org\u003c/span\u003e\u003cspan address=\"https://www.rcsb.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) based on the search parameters \u0026ldquo;Homo sapiens\u0026rdquo; and \u0026ldquo;X-ray\u0026rdquo;. Receptor files for each protein were exported in the PDB Format. The original receptor files were processed using PyMOL to remove water molecules and ligands, and the optimized structures were output in the \u0026ldquo;pdb\u0026rdquo; format. These pdb files were imported into AutoDockTools, where hydrogen atoms were added and the files were saved in the \u0026ldquo;pdbqt\u0026rdquo; format. In AutoDockTools, docking boxes were generated for each receptor protein. The \u0026ldquo;Grid box\u0026rdquo; function was opened, and the box size was adjusted to ensure complete protein receptor coverage. The adjusted docking box files were exported in the \u0026ldquo;gpf\u0026rdquo; format. The molecular docking process was conducted using the AutoDock Vina program within the command prompt terminal. A log.txt file was generated to record the docking results, and an output.pdbqt file was produced in PyMOL to visualize the docking results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Preparation of the EUL extract\u003c/h2\u003e \u003cp\u003eFresh EUL was dried with hot air at 50\u0026deg;C for 8 hours. The dried leaves were pulverized by a grinder and passed through a 100-mesh sieve. The powder (10 g) was placed in a 250 mL conical flask. The extraction procedure was carried out under the following parameters: solid-to-liquid ratio, 1:25; complex enzyme dosage, 0.3%; pH 6; temperature, 50\u0026deg;C; and time, 100 minutes. After extraction, the mixture was filtered under vacuum. The filtrate was inactivated at 95\u0026deg;C for 2 minutes and cooled. The resulting solution was freeze-dried under vacuum to obtain a powdered extract.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. HPLC quantitative analysis\u003c/h2\u003e \u003cp\u003eStandard solutions of quercetin, kaempferol, and (+)-catechin (2, 1, 0.5, and 0.25 mg/mL, respectively) were prepared using the corresponding mobile phase. A 172.30 mg/mL test sample solution was prepared and serially diluted to 86.15, 43.08, 21.54, and 10.77 mg/mL. Sonication was performed at 300 W and 45 kHz for 30 minutes. Following vacuum filtration, the solutions were passed through a 0.22 \u0026micro;m membrane. All preparations were repeated in triplicate.\u003c/p\u003e \u003cp\u003eChromatography for quercetin and kaempferol \u003cem\u003e(\u003c/em\u003eChinese Pharmacopoeia Commission, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e was performed using a Shimadzu C18 column (5 \u0026micro;m, 4.6 mm \u0026times; 250 mm) with a mobile phase A consisting of 0.4% phosphoric acid in water and a mobile phase B consisting of methanol. The gradient elution program for quercetin and kaempferol was established as follows: 0\u0026ndash;10 min, 20% B to 40% B; 10\u0026ndash;20 min, 40% B to 50% B; 20\u0026ndash;30 min, 50% B to 60% B; and 30\u0026ndash;40 min, 60% B to 70% B. The flow rate was maintained at 1.0 mL/min, the detection wavelength was set at 262 nm, the column was kept at room temperature, and the injection volume was 10 \u0026micro;L.\u003c/p\u003e \u003cp\u003eChromatography for (+)-catechin \u003cem\u003e(Ailai\u0026middot;Saikan et al., 2016)\u003c/em\u003e was performed using a Shimadzu C18 column (5 \u0026micro;m, 4.6 mm \u0026times; 250 mm) with a mobile phase A consisting of 0.4% phosphoric acid in water and a mobile phase B consisting of acetonitrile. The isocratic elution was performed with A-B (87:13, v/v). The detection wavelength was set at 280 nm, and the column temperature was maintained at 35\u0026deg;C. All other parameters were the same as the parameters for quercetin and kaempferol chromatography.\u003c/p\u003e \u003cp\u003eChromatograms were recorded using the HPLC system software, and peak areas were automatically integrated. Calibration curves were constructed by plotting peak areas (y-axis) against the corresponding concentrations of reference standards (x-axis) using linear regression analysis. The content of each analyte in the test samples was calculated by substituting the measured peak area into the corresponding regression equation derived from the calibration curve. All calculations were performed using the average values of three determinations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Cell culture\u003c/h2\u003e \u003cp\u003eAfter reaching 85% confluence, PC-3 cells were subcultured in RPMI-1640 medium containing 100 U/mL penicillin, 100 \u0026micro;g/mL streptomycin, and 10% FBS. After washing with 2 mL PBS, 2 mL of 0.25% trypsin-0.02% EDTA was added to the cells. After the cells became rounded, 2 mL of complete medium was added to stop the digestion, and the cells were collected. The cells were centrifuged at 800 rpm and 4\u0026deg;C for 5 minutes. After discarding the supernatant, the cell pellet was resuspended in complete medium for subculturing. The medium was replaced every other day.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Cell viability\u003c/h2\u003e \u003cp\u003ePC-3 cells in the logarithmic phase were harvested and plated into 96-well plates with a seeding density of 0.6\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells per well. After culturing for 24 hours to allow cell attachment, the medium was changed according to the following groups: the Control group received drug-free medium; the \u003cem\u003eEucommia\u003c/em\u003e groups received medium containing \u003cem\u003eE. ulmoides\u003c/em\u003e leaf (EUL) extract at final concentrations of 6.25, 25, and 100 \u0026micro;g/mL; and the DPI group received medium containing 10 \u0026micro;mol/L diphenyleneiodonium chloride. For the inhibitor assay, cells were treated with 100 \u0026micro;g/mL EUL in the presence or absence of 2 \u0026micro;g/mL SC79 (Sigma-Aldrich). After 24 and 48 hours of incubation, cell viability was measured using the CCK-8 assay. The old medium was aspirated, and the cells were rinsed three times with PBS. Then, 100 \u0026micro;L of medium containing 10% CCK-8 working solution was added to each well. The plates were gently shaken and incubated for 2 hours. The absorbance at 450 nm was determined with a microplate reader, and the resulting data were compared and analyzed. Each experiment was performed in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Cell migration\u003c/h2\u003e \u003cp\u003ePC-3 cells were first cultured for 24 h and then treated for 16 h with either drug-free medium (Control), medium containing EUL extract (final concentrations: 6.25, 25, or 100 \u0026micro;g/mL), or medium containing 10 \u0026micro;mol/L diphenyleneiodonium chloride (DPI) (N\u0026thinsp;=\u0026thinsp;3 per group). The method is also implemented in the inhibitor assay. After treatment, the cells were digested with trypsin, centrifuged, and re-suspended in serum-free medium. The cell density was adjusted to 5\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells/mL to prepare a single-cell suspension.\u003c/p\u003e \u003cp\u003eThe Transwell chamber basement membrane (8 \u0026micro;m pores, Corning, NY, USA) was coated with 50 \u0026micro;L of Matrigel (50 mg/L, BD Biosciences) and incubated for 4 hours at 37\u0026deg;C to solidify. After removing the remaining liquid, 70 \u0026micro;L of medium was added to the upper chamber, and the chambers were incubated at 37\u0026deg;C for 30 minutes for hydration. Subsequently, 200 \u0026micro;L of the single-cell suspension were added along the wall of the upper chamber. Medium (600 \u0026micro;L with 10% FBS) was added to the lower chambers, and the plates were incubated at 37\u0026deg;C for 24 hours under conventional culture conditions. Invading cells in the lower chamber were fixed with 500 \u0026micro;L of 4% paraformaldehyde for 20 minutes, stained with 0.1% crystal violet at 37\u0026deg;C for 30 minutes, and images were captured under an inverted microscope. All experiments were conducted in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9. Western blot assay\u003c/h2\u003e \u003cp\u003ePC-3 cells (5\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells per well) in the logarithmic growth phase were seeded into 6-well plates. The control group was cultured with medium only, and the EUL extract groups were treated with medium containing 6.25 \u0026micro;g/mL, 25 \u0026micro;g/mL, and 100 \u0026micro;g/mL of EUL extract. After 72 hours, cells were trypsinized and collected. For every 100 \u0026micro;L of compacted cell volume, 1 mL of RIPA buffer supplemented with PMSF was added for complete lysis. The lysates were centrifuged at 12,000 g and 4\u0026deg;C for 5 minutes to extract total protein. Protein concentrations were measured using a BCA protein assay kit. Subsequently, proteins were electrophoresed on 10\u0026ndash;12% SDS polyacrylamide gels and transferred to PVDF membranes. The membranes were blocked for 1 hour at room temperature with 5% skim milk in TBST on a decolorizing shaker. Primary antibodies (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were applied, and the membranes were incubated overnight at 4\u0026deg;C. Subsequently, HRP-conjugated secondary antibodies (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were added, and the membranes were incubated for 1 hour at room temperature. Antibody binding was visualized using ECL on a Tanon 5200 luminescence imaging workstation. Quantification of protein expression levels was performed by measuring optical density values with Image Pro Plus 6.0 software. Relative protein expression was calculated as the ratio of the target protein band intensity to the internal reference protein band intensity. The expression levels of PI3K, p-PI3K, Akt and p-Akt proteins were detected by the same method as described for the inhibitor assay (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAntibodies and dilution\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntibodies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDilution\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVEGFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePI3K p85/p55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-PI3K p85/p55 (Tyr458, Tyr199)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAkt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-Akt(Ser473)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:2000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMP-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMP-9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebcl-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:2000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaspase 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:1000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-actin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:3000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGoat Anti-Rabbit IgG H\u0026amp;L (HRP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:10000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGoat Anti-Mouse IgG H\u0026amp;L (HRP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1:10000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cb\u003eAntibodies and dilution\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10. Flow cytometry analysis of apoptosis\u003c/h2\u003e \u003cp\u003ePC-3 cells were treated according to the respective grouping protocol, and were subsequently washed twice with PBS. The cell suspension was transferred to a sterile centrifuge tube and centrifuged at 2000 rpm for 5 min. The supernatant was discarded, and the cells were then washed twice with PBS and centrifuged again at 2000 rpm for 5 min to collect 1\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells. The cells were resuspended in 0.5 mL of staining buffer per tube, followed by the addition of 5 \u0026micro;L of Annexin V-FITC staining solution were added to each tube with gentle mixing. Subsequently, 5 \u0026micro;L of propidium iodide was added and mixed. The samples were incubated at room temperature for 15 min in the dark. Finally, the samples were analyzed using a flow cytometer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.11. Data analysis\u003c/h2\u003e \u003cp\u003eData were analyzed and plotted using GraphPad Prism 9 (Version 9.4.0), and figures were compiled using Adobe Illustrator (Version 26.3.1). The Tukey multiple-comparison test was used after one-way ANOVA. All data are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Experimental Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Acquisition of intersection genes and construction of the component-target-prostate cancer network\u003c/h2\u003e \u003cp\u003eActive components of EUL, including kaempferol, (+)-catechin, and quercetin, were identified from the TCMSP database. The active components were imported into the SwissTargetPrediction database, yielding 156 targets after eliminating duplicates. A search for \u0026ldquo;prostate cancer\u0026rdquo; in the DisGeNET, GeneCards, and OMIM databases yielded 2877 disease-related targets after eliminating duplicates. A Venn diagram of active component targets and disease targets revealed 118 overlapping targets (Fig.\u0026nbsp;1A).\u003c/p\u003e \u003cp\u003eThe overlapping targets were imported into the STRING database to generate the PPI network diagram, consisting of 118 nodes and 2320 edges (Fig.\u0026nbsp;1B). The data from the STRING database were subsequently loaded into Cytoscape 3.9.1 to perform network topology analysis. After removing loosely correlated scattered points, a PPI network with 115 nodes and 2311 edges was constructed based on betweenness centrality and degree values (Fig.\u0026nbsp;1C). Node sizes reflect degree values, and color depth indicates betweenness centrality. Thus, larger nodes with deeper red coloration indicate greater connectivity with other proteins in the network and a higher likelihood of target relevance. A component-target-prostate cancer network diagram was generated.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;1. Analysis of intersecting genes. (A) Venn diagram of components versus diseases. (B) Protein-protein interaction network map. (C) Topological analysis of the PPI network. (D) Component-target-prostate cancer network diagram.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Construction of the protein-protein interaction network and GO and KEGG analyses\u003c/h2\u003e \u003cp\u003eIntersection targets were analyzed using the DAVID database. GO functional classification and enrichment analyses revealed 826 significantly enriched terms (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), comprising 516 biological processes (BPs), 49 cellular components (CCs), and 106 molecular functions (MFs) (Fig.\u0026nbsp;2A and B). The top 10 enriched BPs were: positive regulation of transcription from RNA polymerase II promoter, positive regulation of gene expression, positive regulation of transcription, DNA-templated, negative regulation of apoptotic process, positive regulation of cell proliferation, regulation of transcription from RNA polymerase II promoter, apoptotic process, negative regulation of transcription from RNA polymerase II promoter, signal transduction, and response to xenobiotic stimulus. The 10 most enriched CCs included the nucleus, cytoplasm, cytosol, nucleoplasm, plasma membrane, extracellular space, extracellular region, membrane, chromatin, and mitochondrion. The top 10 most enriched MFs were protein binding, identical protein binding, enzyme binding, protein homodimerization function, RNA polymerase II core promoter proximal region sequence-specific DNA binding, DNA binding, sequence-specific DNA binding transcription factor activity, RNA polymerase II transcription factor activity (sequence-specific DNA binding), protein kinase binding, and ATP binding.\u003c/p\u003e \u003cp\u003eKEGG pathway analysis showed 155 significantly enriched pathways (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as shown in Fig.\u0026nbsp;2C. The most significantly enriched pathways included pancreatic cancer, prostate cancer, AGE-RAGE signaling pathway in diabetic complications, fluid shear stress and atherosclerosis, toxoplasmosis, hepatitis B, lipid and atherosclerosis, hepatitis C, and Kaposi sarcoma-associated herpesvirus infection. The prostate cancer pathway ranked second with 24 related targets, indicating that the targets were highly relevant to prostate cancer. Intersection genes were imported into the KEGG database for analysis, and the prostate cancer pathway was selected to generate Fig.\u0026nbsp;2D.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;2. GO and KEGG analyses. (A) Bubble map of GO pathway enrichment analysis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (B) Colored bar chart of GO pathway enrichment analysis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (C) Bubble map of KEGG analysis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (D) Distribution map of intersecting genes in the prostate cancer pathway.The KEGG pathway map (map05215) is used with permission from Kanehisa Laboratories. KEGG: Kyoto Encyclopedia of Genes and Genomes (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.kegg.jp/kegg/kegg1.html\u003c/span\u003e\u003cspan address=\"https://www.kegg.jp/kegg/kegg1.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Hub gene screening and construction of the component-target-pathway network\u003c/h2\u003e \u003cp\u003eThe CytoHubba plugin in Cytoscape was utilized for hub gene screening. The protein-protein interaction network data file was imported. The MCC algorithm was selected to screen the top 10 genes. Ten hub genes were identified and exported (Fig.\u0026nbsp;3A). A \u0026ldquo;component-target-pathway\u0026rdquo; network diagram was constructed (Fig.\u0026nbsp;3B). In the central circle, the left red circle represents the 10 hub genes, while the right red circle represents the 24 genes enriched in the prostate cancer pathway based on the KEGG analysis; the three overlapping genes are displayed in the center. Green and light green circles represent other genes. The left deep-red rectangles represent bioactive compounds, the right yellow rectangles represent KEGG pathways, and the connecting edges indicate interactions or associations among compounds, genes, and pathways.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;3. Network analysis of hub targets and pathways. (A) Hub target network map. (B) Component-target-pathway network.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Molecular docking and visualization\u003c/h2\u003e \u003cp\u003eTo confirm the binding interactions, molecular docking between the 10 hub genes and kaempferol, (+)-catechin, and quercetin was assessed. Binding energies below \u0026minus;\u0026thinsp;5.0 kcal/mol suggest a favorable interaction between ligand and receptor. A heatmap was employed to visualize the binding energies between the active components and target proteins, with darker colors indicating lower binding energies (Fig.\u0026nbsp;4A). The binding energies between the three active components and the hub genes ranged from \u0026minus;\u0026thinsp;5.9 to \u0026minus;\u0026thinsp;9.2 kcal/mol, indicating favorable binding. Representative docking results are shown in Fig.\u0026nbsp;4B.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;4. Molecular Docking and Visualization. (A) Molecular docking heatmap. The numbers represent binding energy (kcal\u0026middot;mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). A deeper red color corresponds to a lower binding energy, thereby indicating a more stable interaction. (B) Molecular docking visualization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Content of active ingredients in EUL extract\u003c/h2\u003e \u003cp\u003eThe kaempferol, (+)-catechin, and quercetin levels in the enzymatically hydrolyzed extract of EUL were measured using HPLC, as shown in Fig.\u0026nbsp;5. The linear regression equations for quercetin, kaempferol, and (+)-catechin, respectively, were established within the concentration range of 0.25\u0026ndash;2.0 mg/mL, as follows:\u003c/p\u003e \u003cp\u003ey\u0026thinsp;=\u0026thinsp;4143.6x\u0026thinsp;\u0026minus;\u0026thinsp;51.812 (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.9969),\u003c/p\u003e \u003cp\u003ey\u0026thinsp;=\u0026thinsp;2467.3x\u0026thinsp;\u0026minus;\u0026thinsp;22.833 (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.9970),\u003c/p\u003e \u003cp\u003ey\u0026thinsp;=\u0026thinsp;7599.2x\u0026thinsp;\u0026minus;\u0026thinsp;849.12 (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.9902).\u003c/p\u003e \u003cp\u003eAfter substituting the average peak areas into the equations, the quercetin, kaempferol, and (+)-catechin were 1.3663 mg/g, 0.8577 mg/g, and 52.5817 mg/g, respectively.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;5. HPLC chromatograms for the active components of \u003cem\u003eEucommia ulmoides\u003c/em\u003e. (A) Quercetin (1) and kaempferol (2) standards. (B) Quercetin (1) and kaempferol (2) samples. (C) Standard for (+)-catechin. (D) Sample of (+)-catechin (1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Effects of EUL extract on PC-3 cell survival and invasiveness\u003c/h2\u003e \u003cp\u003ePC-3 cell viability was significantly reduced after 24 hours of treatment with 100 \u0026micro;g/mL Eucommia or 10 \u0026micro;mol/L DPI compared with cell viability in the Control group (Fig.\u0026nbsp;6A). After 48 hours of incubation, PC-3 cell viability was significantly reduced in the 25 \u0026micro;g/mL Eucommia, 100 \u0026micro;g/mL Eucommia, and 10 \u0026micro;mol/L DPI groups compared with cell viability in the Control group. The invasion ability of PC-3 cells was significantly and dose-dependently reduced in the 25 \u0026micro;g/mL Eucommia, 100 \u0026micro;g/mL Eucommia, and 10 \u0026micro;mol/L DPI groups compared with the invasion ability in the Control group after a 16-hour pretreatment followed by a 24-hour Transwell assay (Fig.\u0026nbsp;6B).\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;6. The effects of Eucommia extract on cell viability and invasive ability in PC-3 cells. (A) CCK-8 assays, indicating cell viability, after 24 or 48 hours of treatment with 6.25, 25, or 100 \u0026micro;g/mL Eucommia, 10 \u0026micro;mol/L DPI, or media only (Control group) (*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). (B) Transwell assays, indicating invasive ability, after treatment with 6.25, 25, or 100 \u0026micro;g/mL Eucommia, 10 \u0026micro;mol/L DPI, or media only (Control group). Representative images of the stained cells in the lower chambers (left) and the quantification of staining (right) are shown. (**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Effects of EUL extract on apoptosis-related proteins in PC-3 cells\u003c/h2\u003e \u003cp\u003eThe relative protein levels of VEGFA, MMP-2, MMP-9, and Bcl-2 decreased significantly after 72 hours of treatment with 6.25\u0026ndash;100 \u0026micro;g/mL EUL extract compared with the Control group in PC-3 cells (Fig.\u0026nbsp;7A, B, G, H, and I). The phosphorylation levels of PI3K and Akt also decreased after 72 hours of treatment with 6.25\u0026ndash;100 \u0026micro;g/mL EUL extract (EUL groups) compared with the Control group (Fig.\u0026nbsp;7A, D, and F); however, the total protein expression levels of PI3K and Akt remained unchanged. (Fig.\u0026nbsp;7A, C, and E). The relative protein levels of Bax, p53, and cleaved-Caspase-3 increased significantly in the 25 \u0026micro;g/mL and 100 \u0026micro;g/mL EUL groups compared with the Control group (Fig.\u0026nbsp;7A, J, K, and L). However, the protein levels of total caspase 3 exhibited no significant alterations. (Fig.\u0026nbsp;7A and M). Higher concentrations of EUL showed better effects, indicating a concentration-dependent response.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;7. Relative levels of apoptosis-related proteins measured by western blotting after treatment with 6.25\u0026ndash;100 \u0026micro;g/mL EUL extract or media only (Control group). (A) Representative western blots. Quantification of western blots, including (B) VEGFA, (C) PI3K, (D) p-PIK/PI3K, (E) Akt, (F) p-Akt/Akt, (G) MMP-2, (H) MMP-9, (I) Bcl-2, (J) Bax, (K) p53, (L) cleaved caspase 3/caspase 3, and (M) caspase 3. (**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01)(Cropped blots are displayed with dividing lines indicating where non-relevant lanes have been removed. Uncropped full‑length blots are provided in the corresponding Supplementary Information)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.8. EUL extract affects PC-3 cells through inhibiting the Akt pathway\u003c/h2\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e3.8.1 Effects of Akt activator SC79 on the reversal of EUL-induced suppression of PC-3 cell viability\u003c/h2\u003e \u003cp\u003eAfter 24 or 48 hours of incubation, compared with the Control group, PC-3 cell viability was significantly increased in the 2 \u0026micro;g/mL SC79 group and significantly decreased in the 100 \u0026micro;g/mL EUL group. Compared with the 2 \u0026micro;g/mL SC79 group, the co-administration of 100 \u0026micro;g/mL EUL significantly reversed the pro-proliferative effect mediated by SC79 treatment. (Fig.\u0026nbsp;8).\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;8. The Akt activator SC79 reverses the suppression of PC-3 cell viability induced by Eucommia leaf extract, as measured by CCK-8 assays. After 24 or 48 hours of treatment with media only (Control group), 2 \u0026micro;g/mL SC79, 2 \u0026micro;g/mL SC79\u0026thinsp;+\u0026thinsp;100 \u0026micro;g/mL EUL, or 100 \u0026micro;g/mL EUL. (*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e3.8.2 Effects of Akt activator SC79 on the reversal of EUL-induced inhibition of PC-3 cell invasion\u003c/h2\u003e \u003cp\u003eCompared with the Control group, the invasion ability of PC-3 cells was significantly increased in the 2 \u0026micro;g/mL SC79 group and significantly decreased in the 100 \u0026micro;g/mL EUL group. Compared with the SC79 group, the administration of EUL markedly suppressed cell invasion (Fig.\u0026nbsp;9).\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;9. The Akt activator SC79 reverses the inhibition of PC-3 cell invasion induced by Eucommia leaf extract by Transwell assays. Representative images of the stained cells in the lower chambers (left) and the quantification of staining (right) are shown. Columns marked with distinct letters denote statistically significant differences at the level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e3.8.3 Effects of Akt activator SC79 on the reversal of EUL-induced modulation of PI3K/Akt pathway-related proteins in PC-3 cells\u003c/p\u003e \u003cp\u003eThe expression levels of total PI3K and Akt proteins were not significantly different. Compared with the control group, the 2 \u0026micro;g/mL SC79 group exhibited a marked upregulation in the phosphorylation levels of PI3K (p-PI3K) and Akt (p-Akt). The concurrent administration of 100 \u0026micro;g/mL EUL significantly attenuated the SC79-induced elevation of p-PI3K and p-Akt, while their expression levels stayed significantly elevated compared to those in the control group. Notably, treatment with 100 \u0026micro;g/mL EUL alone led to a significant reduction in the expression of both phosphorylated proteins (Fig.\u0026nbsp;10).\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;10. The Akt activator SC79 reverses the modulation of PI3K/Akt signaling proteins induced by Eucommia leaf extract. (A) Representative western blots. Quantification of western blots, including (B) PI3K, (C) p-PI3K/PI3K, (D) Akt, and (E) p-Akt/Akt. Columns marked with distinct letters represent significant differences at the threshold of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.(Cropped blots are displayed with dividing lines indicating where non-relevant lanes have been removed. Uncropped full-length blots are provided in the corresponding Supplementary Information)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003e3.8.4 Effects of Akt activator SC79 on the reversal of EUL-induced apoptosis in PC-3 cells\u003c/h2\u003e \u003cp\u003eCompared with the control group, the apoptosis level of the SC79 group was significantly decreased, whereas the apoptosis levels of both the SC79\u0026thinsp;+\u0026thinsp;EUL group and EUL group were markedly elevated. Specifically, treatment with 100 \u0026micro;g/mL EUL increased the apoptosis rate from 4.18% to 24.48% (Fig.\u0026nbsp;11).\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;11. The Akt activator SC79 reverses the apoptosis induced by Eucommia leaf extract in PC-3 cells. (A) Typical flow cytometry dot plots. (B) Quantitative analysis of apoptosis rates. Data are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;3. Columns labeled with different letters signify statistically significant differences at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe objective of this study was to investigate the mechanisms underlying the protective effects of EUL extract against prostate cancer. Although EUL exhibited inhibitory effects on human glioblastoma cells and cancer stem cells \u003cem\u003e(\u003c/em\u003eWang et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; \u003cem\u003eMiao, 2024)\u003c/em\u003e, investigations into the protective effects of EUL are limited. EUL tone the liver and kidneys and strengthen bones and tendons. Thus, EUL are commonly used to treat liver and kidney deficiency, dizziness, soreness and weakness of the waist and knees, and muscle flaccidity \u003cem\u003e(Jia et al., 2012)\u003c/em\u003e. The effects of EUL on bone-related conditions, such as rheumatoid arthritis and muscle fatigue, have also been validated. Although the prostate is not explicitly mentioned in classical traditional Chinese medicine texts, prostate functions are often categorized under the kidney system, and prostate function is believed to be closely related to kidney health; sufficient kidney qi ensures normal prostate function, and kidney qi deficiency may affect prostate health. Therefore, we hypothesized that EUL might protect against prostate cancer.\u003c/p\u003e \u003cp\u003eTo investigate this hypothesis, a network pharmacology approach was employed. Three components of EUL extracts with high absorption and drug-likeness, kaempferol, (+)-catechin, and quercetin, were first identified. The potential targets of these three components and prostate cancer-related targets were integrated, and data mining was performed. KEGG analysis indicated that prominently enriched pathways comprised the PI3K-Akt signaling pathway, the MAPK signaling pathway, and the prostate cancer pathway. Within the prostate cancer pathway, 24 target genes overlapped with the active \u003cem\u003eEucommia ulmoides\u003c/em\u003e component targets, and three of these overlapping genes were identified as hub genes. These findings suggest that EUL may influence the progression of prostate cancer by acting on prostate cancer-related targets and pathways, such as AKT1, BCL2, and MMP9. Subsequent western blot analysis confirmed the involvement of these key targets, showing that the EUL extract significantly suppressed Akt phosphorylation, downregulated the expression of Bcl-2, and reduced the protein level of MMP9 in PC-3 cells. AKT1 is involved in the PI3K/Akt signaling pathway, which regulates cell proliferation, apoptosis, and metabolism; therefore, this pathway impacts the progression of multiple cancer types, such as prostate cancer \u003cem\u003e(\u003c/em\u003eWang et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. Bcl-2 plays a key role in the mitochondria-mediated intrinsic apoptotic pathway. Bcl-2 inhibits apoptosis by preventing the release of pro-apoptotic factors (such as cytochrome c) from mitochondria \u003cem\u003e(\u003c/em\u003eKiraz et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; \u003cem\u003eSchenk et al., 2017)\u003c/em\u003e. MMP9 is responsible for encoding matrix metalloproteinase-9, a member of the MMP family \u003cem\u003e(\u003c/em\u003eMondal et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; \u003cem\u003eRashid et al., 2023)\u003c/em\u003e. MMP9 can significantly influence prostate cancer invasion, metastasis, and progression by degrading the extracellular matrix, promoting angiogenesis, and regulating inflammatory responses \u003cem\u003e(Rashid et al., 2023)\u003c/em\u003e. The KEGG analysis indicated that 27 intersection targets were involved in the PI3K/Akt pathway. Therefore, EUL may affect prostate cancer cell survival, migration, invasion, and proliferation via multiple targets mediating PI3K/Akt signaling and apoptosis pathways. The molecular docking results indicated potential binding of the three active components with the 10 core targets (all less than \u0026minus;\u0026thinsp;5.0 kcal/mol) and strong binding with PTSG2 (all less than \u0026minus;\u0026thinsp;8.0 kcal/mol).\u003c/p\u003e \u003cp\u003eThe three active components from EUL included the (+)-catechin, quercetin, and kaempferol are flavonoids. Flavonoids are polyphenolic compounds widely present in plants with multiple biological activities and health benefits. Kaempferol induces apoptosis in cervical cancer cells by downregulating the PI3K/Akt pathway to reduce cell growth and increase apoptotic gene expression (e.g., p53), thereby triggering cell death \u003cem\u003e(Kashafi et al., 2017)\u003c/em\u003e. Kaempferol induces apoptosis in ovarian cancer cells via G2/M cell cycle arrest and downregulation of key signaling pathways such as MEK/ERK and JNK/ERK \u003cem\u003e(\u003c/em\u003eGao et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zhao et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. Quercetin contributes to normal mitochondrial function and affects cell cycle and autophagy via multiple signaling pathways, including Wnt/β-catenin \u003cem\u003e(Shan et al., 2009)\u003c/em\u003e, PI3K/Akt/mTOR \u003cem\u003e(Hasan et al., 2022;\u003c/em\u003e Lu et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e, MAPK/ERK1/2 \u003cem\u003e(\u003c/em\u003eErdogan et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e, and STAT3 \u003cem\u003e(\u003c/em\u003eLiu et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e, to promote cancer cell apoptosis and inhibit angiogenesis. Quercetin reverses docetaxel resistance in prostate cancer through the androgen receptor and PI3K/Akt signaling pathway to promote apoptosis in prostate cancer cells \u003cem\u003e(\u003c/em\u003eLu et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. (+)-Catechin suppresses gastric cancer cell proliferation and migration, modulates the cell cycle, and promotes cell death by influencing PI3K/Akt signaling \u003cem\u003e(\u003c/em\u003eDing et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2024\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e. In addition, (+)-Catechin enhances the anti-proliferative activity of docetaxel in prostate cancer cell models \u003cem\u003e(El Nahass et al., 2025)\u003c/em\u003e. Kaempferol, (+)-catechin, and quercetin were detected in the EUL extract used in this study; (+)-catechin exhibited the highest content at 52.5817 mg/g.\u003c/p\u003e \u003cp\u003ePC-3 cells are an androgen-independent human prostate cancer cell line commonly used for exploring the biological characteristics of prostate cancer, drug screening, and treatment strategies. In this study, the addition of EUL extract inhibited the proliferation of PC-3 cells in a concentration- and time-dependent manner. This is the first study to validate the inhibitory effects of EUL extract on prostate cancer cell proliferation. EUL extract also inhibited the invasive ability of PC-3 prostate cancer cells in a dose-dependent manner. The expression levels of MMP-2 and MMP-9 proteins, which are associated with cell invasion and migration, were significantly reduced by EUL extract treatment. MMPs are involved in the degradation and remodeling of the extracellular matrix. Thus, MMPs are critically involved in modulating tumor cell invasion, migration, and distant metastasis. The expression and activity of MMPs are regulated by multiple signaling pathways. For example, activation of the VEGFA signaling pathway upregulates MMP expression to promote angiogenesis \u003cem\u003e(Heissig et al., 2005)\u003c/em\u003e. The NF-κB signaling pathway, which is a critical hub for inflammation and stress regulation, regulates the expression of various MMPs. The upregulation of MMPs leads to excessive degradation of the extracellular matrix, compromising the integrity of the basement membrane, which is required for tumor cells to detach from the primary site, invade surrounding tissues, and ultimately enter the circulatory system.\u003c/p\u003e \u003cp\u003eThe PI3K/Akt pathway is a cellular signaling cascade that serves critical functions in cell growth, survival, metabolism, and migration \u003cem\u003e(Fruman et al., 2017)\u003c/em\u003e. This pathway is typically activated in PC-3 cells. Bcl-2 and Bax are downstream effectors of the PI3K/Akt pathway that regulate apoptosis. Western blots were performed to investigate the effects of EUL extract on proteins related to the PI3K/Akt pathway. Consistent with the KEGG pathway results for prostate cancer action in network pharmacology, EUL extract significantly suppressed PI3K and Akt phosphorylation levels. The relative levels of the apoptosis-related proteins Bax and cleaved-caspase-3 were significantly increased, and expression of the anti-apoptotic protein Bcl-2 was decreased. These findings suggest that EUL extract likely suppresses the activation of the PI3K/Akt pathway, promoting the expression of apoptosis-related proteins (Bax and cleaved-caspase-3) and reducing the expression of the anti-apoptotic Bcl-2 to promote apoptosis in PC-3 cells.\u003c/p\u003e \u003cp\u003eTo test the hypothesis that EUL directly intervened in the PI3K-Akt pathway to regulate PC-3 cell functions, we established an experimental model using the Akt activator SC79 to treat PC-3 cells, followed by investigation of the biological effects of EUL on SC79-pretreated cells. Experimental data revealed that SC79 exposure significantly promoted PC-3 cell invasion and survival while suppressing cellular apoptosis. Conversely, the introduction of EUL effectively mitigated the pro-tumorigenic effects mediated by SC79. Furthermore, the reduction in p-PI3K and p-Akt protein expression induced by EUL suggests that EUL exerts its regulatory role on PC-3 cells through direct targeting of the PI3K-Akt signaling cascade.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study explored the anti-prostate cancer effect and underlying mechanism of Eucommia ulmoides Oliv. leaf (EUL) extract on PC-3 cells via an approach of network pharmacology, molecular docking, and in vitro experiments. Network pharmacology identified three key active components in EUL\u0026mdash;kaempferol, (+)-catechin, and quercetin\u0026mdash;with 118 overlapping targets related to prostate cancer. KEGG enrichment analysis highlighted the PI3K-Akt signaling pathway and prostate cancer pathway as core functional pathways, and hub genes including AKT1, BCL2, and MMP9 were identified as critical targets. Molecular docking validated favorable binding interactions between the active components and hub proteins (binding energies: \u0026minus;5.9 to \u0026minus;\u0026thinsp;9.2 kcal/mol), while HPLC quantification showed (+)-catechin was the most abundant component (52.5817 mg/g) in the EUL extract. In vitro experiments demonstrated that EUL extract inhibited PC-3 cell viability in a concentration- and time-dependent manner and suppressed cell invasion dose-dependently. Mechanistically, EUL extract significantly reduced PI3K and Akt phosphorylation (without altering total protein levels), upregulated pro-apoptotic proteins (Bax, p53, cleaved-Caspase-3), while downregulating the anti-apoptotic protein Bcl-2 and invasion-associated proteins (MMP-2, MMP-9, VEGFA). Flow cytometry confirmed EUL extract increased the PC-3 cell apoptosis rate from 4.18% to 24.48% at 100 \u0026micro;g/mL. Intervention with the Akt activator SC79 further verified that EUL reversed SC79-induced promotion of cell viability and invasion, as well as suppression of apoptosis, by attenuating SC79-mediated upregulation of p-PI3K and p-Akt.\u003c/p\u003e \u003cp\u003eCollectively, the findings confirm that EUL extract inhibits prostate cancer PC-3 cell proliferation and invasion, and promotes apoptosis, by directly targeting the PI3K-Akt signaling pathway. This study provides evidence for EUL as a potential natural anti-prostate cancer agent and lays a foundation for its further development and clinical translation. Future research could focus on in vivo validation and optimization of active component extraction to enhance bioavailability.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eFunding Statement\u003c/h2\u003e \u003cp\u003eThis work was supported by the Major Key Scientific Research Project of the Department of Education of Anhui Province (Grant No. 2022AH051112), the Anhui Provincial College Student Innovation and Entrepreneurship Training Program (Grant No. S202510377083), the Research Start-up Fund of Chuzhou University (Grant Nos. 2022qd51 and 2022qd014), and the Open Experimental Project of Chuzhou University (No. 2025-45). The funders had no role in the study design, data collection, analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eShuang E selects the research topic and obtains funding, Yucheng Wu completes the experimental content and writes the manuscript. Others assisted and participated in the execution of the experiment.All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data generated or analysed during this study are included in this published article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSIEGEL R L, MILLER K D, FUCHS H E, et al. Cancer statistics, 2022 [J]. CA Cancer J Clin, 2022, 72(1): 7-33.\u003c/li\u003e\n\u003cli\u003eGROZESCU T, POPA F. Prostate cancer between prognosis and adequate/proper therapy [J]. 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Journal of Computational Chemistry, 31(2), 455\u0026ndash;461.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"prostate cancer, Eucommiae Folii extract, quercetin, kaempferol, (+)-catechin, PI3K/Akt signaling","lastPublishedDoi":"10.21203/rs.3.rs-9235944/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9235944/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe mechanisms of inhibitory effects of Eucommia ulmoides leaf (EUL) extract on prostate cancer were investigated through network pharmacology, molecular docking, and experimental validation. Active ingredients of EUL and 118 common targets were retrieved using the TCMSP, UniProt, and DisGeNET. Ten hub genes, including AKT1, BCL2, and MMP9, were identified using Cytoscape. KEGG enrichment analysis identified key pathways, such as the PI3K-Akt signaling pathway and the prostate cancer pathway. Molecular docking using AutoDock Vina revealed strong binding affinities between the active components and hub targets. Three active components, quercetin, kaempferol, and (+)-catechin, were detected in the EUL extract using HPLC. In vitro experiments showed that the EUL extract dose- and time-dependently inhibited PC-3 cell viability and invasion, elevated the expression of pro-apoptotic proteins, suppressed anti-apoptotic and invasion-associated proteins, and raised the apoptosis rate to 24.48% at 100 \u0026micro;g/mL. SC79 intervention confirmed EUL acted via targeting PI3K/Akt pathway, supporting its potential as a natural anti-prostate cancer agent.\u003c/p\u003e","manuscriptTitle":"Network pharmacology analysis of the inhibitory effects of Eucommiae Folii extract in prostate cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-04 06:25:10","doi":"10.21203/rs.3.rs-9235944/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-22T02:31:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"216068593036765967050695652627237164177","date":"2026-04-21T04:12:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337166989728170228096245367867159329111","date":"2026-04-20T23:51:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-20T14:02:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-20T13:48:27+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-20T11:27:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-16T11:07:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-04-16T09:43:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"de5ef416-a0a8-43c9-9684-0c99b246f984","owner":[],"postedDate":"May 4th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66810964,"name":"Biological sciences/Cancer"},{"id":66810965,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":66810966,"name":"Biological sciences/Drug discovery"},{"id":66810967,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2026-05-04T06:25:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-04 06:25:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9235944","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9235944","identity":"rs-9235944","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}