Synergistic effect of piperine combined with luteolin on anti-non-small cell lung cancer activity in vitro and in LLC tumour-bearing mice: Mechanistic insights from network pharmacology and molecular docking

INTRODUCTION

Non-small cell lung cancer (NSCLC) was a major subtype of lung cancer (1), accounting for approximately 80–85 % of all lung cancer cases (2). Chemotherapy, targeted therapy, and immunotherapy have played an important role in NSCLC treatment (3). However, there are still some shortcomings, such as drug resistance and high toxicity to normal cells (4). In fact, the combined application of natural products has begun to show promise in the treatment of early non-small cell lung cancer. The combination of curcumin and resveratrol regulated p53 hyperphosphorylation, enhanced caspase activity, and exerted a synergistic preventive effect on lung carcinogenesis (5). Coincidentally, the combination of curcumin and berberine also significantly inhibited MDR1 activity, promoted apoptosis of A549 lung cancer cells, and enhanced anti-lung cancer efficacy (6). Of course, there are still many unknown areas to be explored in the combination of natural products.

Luteolin is a natural flavonoid found in many plants, such as Reseda odorata L., Lonicera japonica Thunb., Chrysanthemum morifolium Ramat., and others (7). It has diverse biological activities, such as anti-inflammatory, antioxidant, antibacterial, anticancer, and antidiabetic properties (8–12). In particular, its anticancer effect has been closely studied. It was generally used to treat different cancers such as gastric cancer, colorectal cancer, breast cancer, liver cancer, and lung cancer. In particular, it has a marked inhibitory effect on lung cancer (13–17). In the treatment of lung cancer, luteolin inhibited the proliferation, migration, and invasion of A549 cells by regulating signalling pathways, including MEK/ERK and AKT/mTOR (18, 19). However, it has a weaker anti-lung cancer effect than other drugs such as osimertinib, sacituzumab govitecan, and pembrolizumab (20–22). Based on the above discussion, its anti-lung cancer effect may be improved by combining it with other natural products. Piperine enhanced the anticancer efficacy of several natural products, including curcumin, paclitaxel, and piperlongumine (23–26). In our preliminary experiments, preliminary experiments showed that piperine and luteolin had a combined effect in treating lung cancer. The combination of piperine and luteolin needs to be further verified, and their combined mechanism of action remains unclear.

Network pharmacology can incorporate information associated with drug components, targets, and diseases. From a holistic perspective, it forecasts drug-action mechanisms and provides a new perspective for natural medicine research (27). In contrast, molecular docking mimics drug-target interactions at the atomic scale, predicts binding affinities and modes, validates network pharmacology results, and accelerates mechanism analysis (28). Importantly, the crystal structures used for molecular docking in this study (PDB: 1GKC for MMP-9, 1M14 for EGFR, and 1FMK for SRC) have been successfully employed in previous cancer‑related docking studies. For instance, Li et al. (29) used the MMP-9 structure (1GKC) to demonstrate that a novel phytosteroid saponin inhibits lung cancer cell migration via NF-κB-mediated MMP-2/MMP-9 suppression. Aggarwal et al. (30) employed the EGFR structure (1M14) to show that an organotin compound binds to the tyrosine kinase domain and exerts anticancer activity through inhibiting EGFR dimerisation. Jumaa et al. (31) used the SRC structure (1FMK) to show that a ciprofloxacin‑metformin combination synergistically targets distinct SRC kinase sites in cervical cancer cells. These studies validate the suitability of the chosen PDB structures for docking investigations in the context of cancer therapy.

Therefore, in this study, we employed network pharmacology and molecular docking to explore the synergistic anti-NSCLC mechanisms of piperine and luteolin, with a focus on the validated targets EGFR, MMP9, and SRC. The synergistic effect was then determined by cell viability, wound healing, colony formation, apoptosis, and cell cycle assays on A549 cells, and further verified in Lewis lung carcinoma (LLC) tumour-bearing mice.

EXPERIMENTAL

Drugs and reagents

Piperine (purity ≥ 98 % HPLC; Shanghai Yuanye Biotechnology, China, Cat# T25317 ), luteolin (purity ≥ 98 % HPLC; Xi’an Tianbao Biotechnology, China), and the positive control drug gefitinib (purity ≥ 99 %; Shanghai Aladdin Biochemical Technology, China, Cat# G125799) were all dissolved in dimethyl sulfoxide (DMSO) to prepare stock solutions for experiments. Working concentrations were obtained by diluting the stocks in cell culture medium immediately before use. RPMI 1640 medium, DMEM medium, and 0.25 % trypsin were all obtained from Thermo Fisher Scientific Biochemical Products Co., Ltd. (China). Fetal bovine serum (FBS) was bought from Shanghai Shuangru Biotechnology Co., Ltd. (China). Penicillin-streptomycin solution was purchased from Shanghai Biyuntian Biotechnology Co., Ltd. (China). The Cell Apoptosis Detection Kit (KGA1101-50) and Cell Cycle Detection Kit (KGA9101-100) were both purchased from Jiangsu KeyGen Biotechnology Co., Ltd. (China).

Cell lines and experimental animals

A549 cells were gifted by Dr Tian Chang from Anhui University of Science and Technology (Anhui, China). They were cultured in RPMI 1640 medium supplemented with 10 % (V/V) FBS and 0.1 % (V/V) penicillin-streptomycin solution, and incubated in a humidified incubator at 37 °C with 5 % CO₂. A549 cells in logarithmic growth phase were harvested, prepared into a single-cell suspension, and used for cell detection experiments.

Lewis lung cancer (LLC) cells were purchased from Shanghai Institute of Biochemistry and Cell Biology (China). They were cultured in DMEM medium containing 10 % FBS under adherent conditions at 37 °C in a 5 % CO₂ atmosphere. They were used to prepare Lewis lung cancer (LLC) tumour-bearing mice. The A549 and LLC cell lines were authenticated by short tandem repeat (STR) profiling analysis. The STR profiles were consistent with the reference data from public databases (e.g., ATCC, DSMZ), and no cross-contamination was detected.

Specific-pathogen-free (SPF) grade male C57BL/6J mice, 6 weeks old and weighing 20–22 g, were purchased from Hangzhou Ziyuan Laboratory Animal Co., Ltd., China (SCXK2024-0004). Mice were kept in a clean environment with a temperature of 25 ± 1 °C and a relative humidity of 50 ± 10 %. This experiment was approved by the Ethics Review Committee of Anhui University of Science and Technology (Gz2024-043). During the experiment, we strictly followed animal ethics requirements.

A combination of concentration selection and synergy evaluation

To evaluate the combination of piperine and luteolin, a fixed-ratio design based on the Chou-Talalay method was used. Concentrations below the individual 24 h half-maximal inhibitory concentration (IC₅₀) values were selected as the combined treatment doses. Specifically, luteolin was tested at three concentrations (87.32, 43.66, 21.83 µmol L^–1) and piperine at five concentrations (43.82, 87.64, 175.3, 280.4, 350.5 µmol L^–1), forming a 3×5 concentration matrix. All combinations were prepared such that each single‑agent concentration remained below its respective IC₅₀. Cells were treated for 24 h. The combination index (CI) was calculated using CompuSyn software (ComboSyn Inc., USA) according to the classic Chou-Talalay method (32). The combined effect was analysed using a dose-effect combination index (Fa-CI) and a normalised isobologram. The relationship between CI and the intensity of the synergistic effect is shown in Table Ⅰ. In addition, cell morphology was observed at 0, 24, and 48 h after treatment and staining with sulforhodamine B (SRB), and the images were photographed using an Olympus IX73 microscope (Olympus Corporation, Japan).

Table Ⅰ. Corresponding relationship between combination index (CI) values and evaluation of drug interactions (31)

Wound healing assay

The scratch wound healing assay was used to evaluate the migration ability of A549 cells under different drug treatments. A549 cells of 3.5 × 10⁵ cells mL^–1 were seeded into a 96-well plate and incubated for 4 h. A sterile pipette tip was used to scratch vertically through the centre of the bottom of each well. Subsequently, A549 cells were treated with medium, luteolin, piperine, or the combination of piperine and luteolin in serum-free medium for 48 h. They were photographed at 0, 24, and 48 h, respectively. ImageJ software was used to calculate the wound-healing areas and the cell migration rate.

Colony formation assay

The colony formation assay was used to assess the A549 cell proliferation. A549 cells of 1.0 × 10³ cells per mL were seeded in a 6-well plate. Subsequently, they were treated with medium, luteolin, piperine, or the combination of piperine and luteolin for 10 days. The medium was updated every 3 days. The cell clones were then fixed with trichloroacetic acid (TCA) and stained with SRB. They were photographed and numbered using ImageJ software.

Cell apoptosis assay

Annexin V-FITC/PI double-staining flow cytometry was used to detect the effects of different drug treatments on A549 cells. A549 cells of 2.0 × 10⁵ cells mL^–1 were seeded in a 6-well plate and treated with different drugs for 48 h. The apoptotic cells were detected by using an apoptosis detection kit (KGA1101-50, KeyGEN, China). Specifically, all cells were collected and incubated with a staining solution containing 5 μL of annexin V-FITC and 5 μL of propidium iodide (PI) in the dark at room temperature for 15 min. After that, they were detected using a flow cytometer (BD FACS Canto II, BD Biosciences, USA). The original data were analysed and processed using FlowJo 10.8.1 software.

Cell cycle assay

In this study, flow cytometry was used to determine the effects of different drug treatments on cell cycle arrest using the Cell Cycle Detection Kit (KGA9101-100, KeyGEN, China). The drug treatment protocol was consistent with that of the cell apoptosis detection experiment. Then all cells were fixed with 500 μL of pre-cooled 70 % (V/V) ethanol and kept at 4 °C for 2 h. Then they were centrifuged at 1500 g for 5 min. The supernatant was discarded, and the cells were washed twice with phosphate-buffered saline (PBS). Subsequently, 500 μL of staining working solution containing PI/RNase A (1:9, V/V) was added, and the mixture was incubated at 37 °C in the dark for 15 min. Then they were detected with the flow cytometer. Their cell cycle phase was analysed using FlowJo 10.8.1 software.

In vivo anti-lung cancer detection

LLC tumour-bearing mice were used to detect the antitumour activity of different drugs. C57BL/6J mice were injected subcutaneously with 100 µL LLC cells of 2 × 10⁷ cells mL^–1 in their right groins. 20 model mice were randomly divided into four groups: the control group, the luteolin group, the piperine group, and the combination group. Two weeks after the subcutaneous injections, the luteolin group, the piperine group, and the combination group were treated intragastrically with luteolin at 50 mg kg^–1, piperine at 100 mg kg^–1, and luteolin at 50 mg kg^–1 and piperine at 100 mg kg^–1, respectively, every day. The control group was administered an equivalent volume of the blank medium (0.5 % carboxymethyl cellulose sodium, CMC-Na) intragastrically. The administration lasted for 14 days. Their tumour widths and lengths were measured every two days with a vernier calliper. Their tumour volumes were calculated according to Equation 1.

[TeX:] V\ ({mm}^{3}) = L \times \frac{W^{2}}{2}$V\left({mm}^3\right)=L\times \frac{W^2}{2}$ 1

where L and W represent the maximum and minimum diameters, respectively.

The mice were executed on the 14th day. Their lungs, thymuses, livers, and spleens were removed and weighed to calculate organ coefficients. The tumour was weighed, and tumour growth inhibition (TGI) rates were calculated using Equation 2.

[TeX:] TGI\ (\ \%) = \left( 1 - \frac{{RTV}_{treatment}}{{RTV}_{control}} \right) \times 100\ \%$TGI\left(\%\right)=(1-\frac{{RTV}_{treatment}}{{RTV}_{control}})\times 100\%$ 2

RTV_treatment is defined as the ratio of the tumour volume of the treatment group at the time of measurement to the initial tumour volume of this group. RTV_control is defined as the ratio of the tumour volume of the control group at the time of measurement to the initial tumour volume of this group.

In addition, these tumours and lungs were fixed in 4 % paraformaldehyde solution for 24 h. Then they were cut into thin slices and stained with hematoxylin and eosin (HE). Subsequently, they were photographed.

Network pharmacology

To predict the molecular mechanism underlying the synergistic effect of luteolin and piperine, a multi-database integration strategy was adopted. As A549 cells are a classic human lung adenocarcinoma cell line derived from a major subtype of NSCLC, they were selected as the in vitro model in this study. Lung adenocarcinoma was selected as the target to obtain representative disease types and ensure consistency between the experimental model and the network pharmacological analysis.

Standardised SMILES strings of luteolin and piperine were retrieved from PubChem (https://pubchem.ncbi.nlm.nih.gov/). Target prediction was conducted via SwissTargetPrediction (http://www.swisstargetprediction.ch/) with a probability > 0.1 as the screening threshold. UniPort (Homo sapiens) was used to standardise protein-gene names to identify potential compound targets. Lung adenocarcinoma-associated genes were retrieved from Genecards (https://www.genecards.org/) and the OMIM database (https://www.omim.org/), screened by a relevance score of ≥ 15, and redundant targets were removed to construct a standardised lung adenocarcinoma target library. VENNY 2.1 online tool (https://bioinfogp.cnb.csic.es/tools/venny/) was used to identify common targets between compounds and lung adenocarcinoma targets. Based on these, a component-target network was constructed via Cytoscape 3.9.1. A protein-protein interaction (PPI) network was built using the STRING database (https://string-db.org/, Homo sapiens, confidence threshold = 0.4). The topological analysis function of Cytoscape was used to screen core regulatory targets in the PPI network. Common targets were imported into the DAVID database (https://david.ncifcrf.gov/) for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Fisher’s exact test was used to evaluate significance, and statistically significant terms were presented as bar charts and bubble charts to identify core biological processes and key pathways.

Molecular docking

Molecular docking was performed using MOE (version 2019) following established protocols and guidelines (33). The crystal structures of MMP9, EGFR, and SRC were retrieved from the PDB (PDB IDs: 1GKC, 1M14, and 1FMK, respectively). These structures were selected based on moderate to high resolution, intact active sites, presence of co-crystallised ligands, and prior use in docking studies (29–31, 34).

Binding site definition. – The active binding pockets were identified using MOE’s Site Finder module, which scans the protein surface based on cavity topology, residue exposure, hydrophobic region distribution, and the binding area of native co-crystallised ligands. For each target, the binding site was defined as the region encompassing the identified pocket centroid (or the co-crystallised ligand).

Protein preparation. – The original crystal structures were imported into MOE. Using the built-in filtering function (35), crystallographic water molecules, native ligands, metal ions, and other irrelevant groups were removed. The Protonate 3D module was then used to add hydrogen atoms, assign atomic charges, and optimise side‑chain conformations at pH 7.4. Missing side chains and loop regions were repaired with the Structure Repair module. The protein was energy-minimised using the MMFF94x force field (steepest descent + conjugate gradient) to a convergence of 10^–4 kcal mol^–1 Å^–1 within 10,000 steps.

Ligand preparation. – The 2D structures of piperine and luteolin, as well as the reference ligands (GOL for EGFR, NFH for MMP9, and PTR for SRC), were drawn with ChemDraw 20.0 and converted to 3D in MOE. Geometry optimization and energy relaxation were performed using the MMFF94x force field (convergence 10^–3 kcal mol^–1 Å^–1, 5,000 steps). Conformers were generated (max 50, energy window 5 kcal mol^–1, RMSD 0.5 Å), and the lowest-energy conformer was selected for docking.

Docking protocol. – Docking was performed with the Dock module in semi-flexible mode (ligand flexible, protein rigid). The Triangle Matcher algorithm was used for ligand placement. Initial screening used the London dG scoring function, which accounts for van der Waals forces, hydrogen bonds, hydrophobic interactions, and torsional energy. The top 30 poses were retained, refined, and then rescored with the GBVI/WSA dG scoring function. Final poses were clustered with an RMSD cutoff of 2.0 Å, and the highest-scoring pose from each cluster was retained.

Result analysis. – Docking poses were visualised using PyMOL 2.5.0. Interactions, including hydrogen bonds (2.5–3.5 Å), hydrophobic contacts, and π‑π stacking, were analysed. The final binding scores (GBVI/WSA dG) were recorded for each ligand-target pair.

Cross-validation with additional software (PyRx and Discovery Studio). – To ensure reliability, docking was also performed using PyRx (with AutoDock Vina) and Discovery Studio 2020 Client (CDOCKER) (36). The same crystal structures and binding site definitions were used. For PyRx, ligands were prepared from PubChem, optimised with Chem3D (MM2 force field), and processed with AutoDock Tools (adding hydrogens and charges). Proteins were pre-processed with PyMOL to remove water and native ligands. Docking was performed using Vina‑2.0; Affinity scores were recorded. According to the literature (37), docking energy values < –4.25 kcal mol^–1 indicate certain binding activity, < –5.0 kcal mol^–1 indicate good activity, and < –7.0 kcal mol^–1 indicate strong binding activity. For Discovery Studio, the CDOCKER protocol (CHARMm force field) was used; CDOCKER_ENERGY scores (more negative = stronger binding) were recorded, which account for van der Waals, electrostatic, hydrogen bond and desolvation terms. Default parameters were applied.

Statistical analysis

GraphPad Prism 10.1.2 (GraphPad, La Jolla, USA) was utilised for all statistical analyses. The numerical data are presented in the form of the mean ± standard deviation (SD). The statistical significance of differences was analysed by unpaired Student’s t-test (two-group comparisons), one-way ANOVA (three or more groups). Repeated-measure ANOVA was used for repeated-measurement data. Statistical significance was defined as ns (no significance), p ≥ 0.05, * p < 0.05, ** p < 0.01, and *** p < 0.001.

RESULTS AND DISCUSSION

Effects of piperine and luteolin in inhibiting on cell viability in A549 cells

The synergistic effect of piperine combined with luteolin on A549 cells was evaluated using the MTT assay. As shown in Fig. 1a and 1b, piperine and luteolin significantly inhibited the viability of A549 cells, with the inhibitory effects showing dose- and time-dependence, respectively (p < 0.05). Moreover, Table Ⅱ shows the IC₅₀ of luteolin and piperine acting alone on A549 cells at different treatment times. The IC₅₀ of luteolin was 108.6, 58.06, and 41.85 µmol L^–1 at 24, 48, and 72 h, respectively. In contrast, those of piperine were 551.8, 418.8, and 243.1 µmol L^–1 at the same time. In Fig. 1c, the synergistic effects of piperine and luteolin with different concentrations on the viability of A549 cells were determined.

Fig. 1. Cell viability of A549 cells: a) luteolin and b) piperine alone at different concentrations, measured after 24, 48, and 72 h; c) combined treatment (concentrations below the individual 24 h IC₅₀ values) after 24 h; n = 3, * p < 0.05, ** p < 0.01, *** p < 0.001 (vs. medium).

Synergistic inhibitory effect of piperine and luteolin on A549 cells

The synergistic cytotoxic effect of piperine and luteolin on A549 cells was quantitatively assessed. Analysis using CompuSyn software, a widely accepted tool for quantifying drug interactions (e.g., used in the study of cucurbitacin E and myricetin) (38), revealed that all combination index (CI) values ranged from 0.3 to 0.8 (Fig. 2a). According to the Chou-Talalay method, CI < 1 indicates synergy, with lower values indicating stronger effects; thus, the calculated CI range indicates moderate to relatively strong synergistic inhibition. This quantitative synergy was corroborated by cell viability assays, where the combination of 175.3 µmol L^–1 piperine and 87.32 µmol L^–1 luteolin resulted in significantly lower cell viability (24.69 %) compared to either agent alone (luteolin 57.73 %; piperine 70.23 %) (Fig. 2b). Morphological observations further supported this enhanced inhibitory effect (Fig. 2c). Together, these data provide robust quantitative and qualitative evidence for the synergistic anti-NSCLC activity of the piperine-luteolin combination.

Fig. 2. Cell viability evaluation of the synergistic inhibitory effect of luteolin and piperine on A549 cells: a) Fa-CI curve and normalized concentration scatter plot; b) cell viability and c) cell morphology with luteolin alone (87.32 µmol L^–1), piperine alone (175.3 µmol L^–1), and the combination of piperine (87.32 µmol L^–1) and luteolin (175.3 µmol L^–1) treatment for 24 and 48 h on A549 cells; n = 3, * p < 0.05, ** p < 0.01, *** p < 0.001 (vs. medium).

Synergistic effect of piperine and luteolin in inhibiting wound healing and clone formation on A549 cells

The combination of piperine and luteolin profoundly inhibited the metastatic and proliferative potential of A549 cells. In the wound healing assay, the combination treatment resulted in a significantly larger wound area (Fig. 3a) and markedly lower cell migration rates (17.0 % at 24 h and 22.9 % at 48 h) compared to either agent alone (luteolin 31.8 % and 46.1 %; piperine 36.5 % and 55.5 %) (Fig. 3b). This indicates a superior inhibitory effect on cell migration. Furthermore, the colony formation assay revealed that the combination virtually abolished the long-term clonogenic survival of A549 cells, with minimal colony formation observed (Fig. 3c). The relative colony inhibition rate reached 91.0 %, significantly exceeding that of the luteolin (73.9 %) or piperine (70.8 %) groups (Fig. 3d). These findings, obtained through standard assays essential for evaluating anti-migratory and anti-proliferative efficacy (39), demonstrate that the piperine-luteolin combination not only effectively impedes cell migration but also critically disrupts the self-renewal and proliferative capacity of NSCLC cells.

Fig. 3. Wound healing: a) qualitative data; b) quantitative data. Clone formation: c) qualitative data; d) quantitative data. To evaluate the synergistic inhibitory effect of luteolin and piperine on A549 cells cells were treated with luteolin (43.66 µmol L^–1), piperine (87.64 µmol L^–1), or their combination (43.66 µmol L^–1 + 87.64 µmol L^–1); n = 3, * p < 0.05, ** p < 0.01, *** p < 0.001 (vs. medium).

Synergistic effect of piperine and luteolin in inducing apoptosis and G0/G1 cell cycle arrest in A549 cells

Flow cytometry analysis revealed that the combination of piperine and luteolin significantly enhanced pro-apoptotic and cell cycle arrest effects in A549 cells. The apoptosis rate in the combination group reached 75.60 %, markedly higher than that in the luteolin (24.56 %) or piperine (17.53 %) alone groups (Fig. 4a,b). Given that both compounds individually are known to promote apoptosis (19, 40), this dramatic increase suggests a synergistic potentiation of their intrinsic pro-apoptotic mechanisms.

Fig. 4. Cell apoptosis: a) qualitative data; b) quantitative data and cell cycle. Evaluation of the synergistic inhibitory effect of luteolin and piperine on A549 cells: c) qualitative data; d) quantitative data. Cells were treated with luteolin (87.32 µmol L^–1), piperine (175.3 µmol L^–1), or their combination (87.32 µmol L^–1 + 175.3 µmol L^–1); n = 3, * p < 0.05, ** p < 0.01, *** p < 0.001 (vs. medium).

Furthermore, the combination induced a distinct cell cycle profile. It caused a pronounced arrest at the G0/G1 phase (68.5 % of cells), compared to luteolin (55.7 %) or piperine (61.3 %) alone (Fig. 4c,d). Notably, this G0/G1 arrest differs from the reported G2/M phase arrest induced by luteolin alone in A549 cells (41). This shift indicates that the presence of piperine may actively participate in and reshape the cell cycle blockade, potentially through the modulation of specific G0/G1 phase-related regulators. The combination of most drugs was verified in vitro, which is advantageous for maintaining a relatively constant drug concentration during the experiment (42).

Synergistic effect of piperine and luteolin in inhibiting tumour growth in LLC tumour-bearing mice

The LLC tumour-bearing mice were typically used to study in vivo efficacy against lung cancer (43). The flowchart is shown in Fig. 5a. Visually, the tumours in the combination group were smaller than those in the piperine, luteolin, or control group in Fig. 5b. There was no statistical difference in body mass among groups, indicating that neither luteolin nor piperine showed obvious toxicity. Tumour growth was significantly inhibited in the combination group. The tumour volume curves (Fig. 5c, d) and the final tumour masses (Fig. 5e) demonstrated the superior efficacy of the combination. The average tumour mass in the combination group (0.429 ± 0.042 g) was substantially lower than in the piperine (0.821 ± 0.222 g), luteolin (0.889 ± 0.189 g), and control (1.672 ± 0.442 g) groups. Consequently, the tumour growth inhibition (TGI) rate for the combination reached 75.28 %, markedly higher than for piperine (28.52 %) or luteolin (38.24 %) alone (Fig. 5f). These results confirm that the combination exerts a synergistic antitumour effect that is not merely the sum superposition of the individual agents.

Fig. 5. In vivo synergistic effect of luteolin and piperine on inhibiting tumour growth: a) flow chart; b) visual observation of gross tumour tissues; c) dynamic change curve of rough tumour volumes; d) tumour volume of each mouse in each group; e) actual average tumour weight in each group; f) tumour growth inhibition rate (TGI) in each group; n = 5, * p < 0.05, ** p < 0.01, *** p < 0.001, LUT – luteolin, PIP – piperine.

HE staining of a pathological section is the "gold standard" for observing the morphological changes in tissues and cells, and it is also an indispensable experiment in the evaluation of antitumour efficacy (44). Histopathological evaluation via hematoxylin and eosin (HE) staining of subcutaneous tumours (Fig. 6a) revealed that the combination group exhibited lower tumour cell density and more pronounced apoptosis compared to other groups. Furthermore, analysis of lung tissues (Fig. 6b) showed that the combination treatment effectively inhibited metastasis, with minimal tumour cell invasion and a preserved alveolar structure, unlike the single-agent and control groups.

Fig. 6. HE staining results: a) mouse subcutaneous tumour, ×100 and ×200; b) lung tissue, ×100.

Network pharmacology prediction of synergistic targets and pathways of piperine and luteolin against lung adenocarcinoma

It was found that there are 111 predictive targets for luteolin and piperine, as well as 1281 disease-target genes for lung adenocarcinoma. Venn diagram analysis (Fig. 7a) identified 71 overlapping genes, which were defined as the core targets of two compounds acting on lung adenocarcinoma. We further constructed the "component-target" network (Fig. 7b) to visualise their association. AKT1, EGFR, MMP9, SRC, and other core targets were selected through PPI network topology analysis (Fig. 7c), all of which are key regulatory factors in NSCLC. For example, EGFR is a common driver mutation in NSCLC (45). AKT1 is the core molecule of the PI3K/AKT pathway (46). The core targets with high node degree values were screened out based on node degree values, such as AKT1 and EGFR. These proteins are key regulatory factors in the tumour signal pathway. GO enrichment analysis (Fig. 7d) illustrates the core biological processes, cellular components, and molecular functions of the drugs from the biological process (BP), cellular component (CC), and molecular function (MF) dimensions, providing direction for subsequent mechanism verification. KEGG pathway analysis revealed that the core targets were significantly enriched in the PI3K-AKT signalling pathway (Fig. 7e). This pathway is often aberrantly activated in NSCLC to regulate tumour cell proliferation, apoptosis, and drug resistance (47). This finding is highly consistent with the results of inducing G₀/G₁ phase arrest and promoting apoptosis of A549 cells in vitro, suggesting that the PI3K-AKT pathway may be the key pathway of synergistic tumour inhibition.

Fig. 7. Network pharmacology analysis diagrams of luteolin and piperine in lung adenocarcinoma (LUAD): a) Venn diagram; b) component-target network diagram; c) PPI network; d) GO enrichment analysis result; e) bubble plot of KEGG pathway analysis. The four target proteins (AKT1, EGFR, SRC, and MMP9) were identified by integrating network topology (hub targets with high centrality), pathological function (regulation of proliferation, invasion, and metastasis), and pathway enrichment (PI3K-Akt and MAPK pathways), along with the availability of crystal structures for docking.

Table Ⅱ. Half-maximal inhibitory concentrations (IC₅₀) of luteolin and piperine on A549 cells

Molecular docking analysis of synergistic targets and mechanisms of piperine and luteolin

Molecular docking using MOE 2019 software was employed to study the interaction characteristics between luteolin, piperine, and 4 core protein targets (Table Ⅲ). The binding energies of piperine and luteolin to EGFR, MMP9, and SRC were lower than –5 kcal mol^–1 (Table Ⅳ), which met the high-affinity binding standard.

Table Ⅲ. Detailed information on core protein targets for molecular docking

Table Ⅳ. Docking binding energies between active small molecules and target proteins

Validation with reference ligands. – To validate the reliability of the docking protocol, the native co-crystallised reference ligands (GOL for EGFR, NFH for MMP9, and PTR for SRC) were re‑docked using MOE. The RMSD between the re‑docked poses and the crystal ligand conformations was < 2.0 Å for all targets, confirming accurate reproduction of native binding geometry. The calculated binding free energies (GBVI/WSA dG) for the reference ligands and the test compounds are summarised in Table Ⅴ. The re‑docking scores were –3.9 kcal mol^–1 for EGFR (GOL), –5.4 kcal mol^–1 for SRC (PTR), and –6.7 kcal mol^–1 for MMP9 (NFH). Both piperine and luteolin exhibited scores comparable to or lower than the reference ligands, indicating favourable binding affinities.

Table Ⅴ. Docking scores (GBVI/WSA dG, kcal mol^–1) of reference ligands, piperine, and luteolin for EGFR, MMP9, and SRC obtained from MOE

All values are in kcal mol^–1. More negative values indicate stronger binding affinity.

Cross‑validation using three independent software packages. – To further confirm binding preferences, docking was repeated using PyRx (AutoDock Vina) and Discovery Studio (CDOCKER). The complete set of docking scores from the three software packages is compared in Table Ⅵ. PyRx scores ranged from –6.9 to –9.5 kcal mol^–1, with both compounds showing the strongest binding to MMP9 (–9.5), followed by EGFR and SRC. PyRx and MOE consistently identified MMP9 as the best target for both compounds (e.g., PyRx: –9.5 kcal mol^–1 for both; MOE: –7.41 and –7.17 kcal mol^–1). Discovery Studio also showed strong binding but amplified luteolin binding to EGFR (–55.37 kcal mol^–1) due to its sensitivity to polar interactions. The heatmaps in Fig. 8 visually summarise these results. Overall, cross‑software comparison confirms that MMP9 is the common core target for both piperine and luteolin. Luteolin exhibits broader binding potential across multiple targets, while piperine shows more specific and stable binding to MMP9. In contrast, SRC did not exhibit consistently strong binding in any of the three software packages, indicating that it is a minor target compared to MMP9.

Fig. 8. Docking score heatmaps (kcal/mol) for piperine and luteolin using: a) PyRx; b) Discovery Studio, and c) MOE. Colour intensity reflects binding strength. Values are provided within each cell.

Table Ⅵ. Comparison of docking scores (kcal mol^–1) for piperine and luteolin against EGFR, MMP9, and SRC using three software packages

PyRx scores are Affinity (AutoDock Vina); DS scores are CDOCKER_ENERGY; MOE scores are GBVI/WSA dG. All values are in kcal mol^–1. More negative values indicate stronger binding affinity. Due to different scoring functions, scores from different software should not be directly compared numerically.

Overlay of binding poses with reference ligands. – The predicted binding poses of piperine and luteolin overlaid with the co-crystallised reference ligands are shown in Fig. 9. Both compounds occupy the same core active pocket as the reference ligands, further supporting their potential as effective binders.

Fig. 9. Overlay of the predicted binding poses of luteolin and piperine with the co-crystallised reference ligands in the active sites of: a) EGFR (PDB: 1M14); b) MMP9 (PDB: 1GKC); c) SRC (PDB: 1FMK). The reference ligands (GOL for EGFR, NFH for MMP9, and PTR for SRC) are shown in yellow. Luteolin and piperine are shown in grey and pink, respectively.

Detailed interaction analysis. – Piperine and luteolin exhibited a non-overlapping complementary binding mode at the same target (28). Complexes with binding energy (BE) < –5 kcal mol^–1 were selected and visualised via PyMOL 2.6.0. Luteolin interacted with MMP9 mainly via hydrogen bonds at Arg⁴²⁴, Ala⁴¹⁷, and Glu⁴⁰² (Fig. 10a). Piperine bound to MMP9 via a hydrogen bond at Ala¹⁸⁹, a different site (Fig. 10b). Regarding EGFR, luteolin established hydrogen bonds with Arg⁸³⁵ and Glu⁷³⁴ (Fig. 10c), while piperine interacted via C–H bonds at Ala⁸³⁵ (Fig. 10d). For SRC, luteolin formed hydrogen bonds with Val³²³ and Glu³³⁹ (Fig. 10e), whereas piperine bound through C–H bond interactions at Gln³⁶² (Fig. 10f). This non‑overlapping binding mode reduces competition for target binding sites and enhances synergistic inhibition.

Fig. 10. Molecular docking diagrams of luteolin and piperine with EGFR, MMP9, and SRC; a) luteolin-MMP9; b) piperine-MMP9; c) luteolin-EGFR; d) piperine-EGFR; e) luteolin-SRC; f) piperine-SRC.

It is noted that SwissTargetPrediction suggested that luteolin may bind to all four target proteins (especially MMP9), while piperine showed less evident binding. However, our molecular docking results showed that both compounds had similar docking scores for all targets. This discrepancy is not unexpected, as SwissTargetPrediction and molecular docking operate on different principles and have different focuses (48, 49). SwissTargetPrediction predicts binding possibility based on ligand‑target structural similarity and cannot quantify binding strength; its results are limited by database completeness. In contrast, our MOE docking is based on the three‑dimensional structures of the target proteins and simulates actual binding conformations, providing quantitative binding energy and interaction analysis. Furthermore, the structural features of the two compounds contribute to the difference: luteolin contains multiple polar groups that readily form hydrogen bonds, which are preferentially predicted by SwissTargetPrediction; piperine relies mainly on hydrophobic interactions, which are less recognised by the server but can be accurately quantified by molecular docking. In addition, SwissTargetPrediction is limited by its database (fewer similar ligands for piperine), while our two‑stage scoring strategy in MOE mitigates inherent docking scoring limitations. Therefore, the similar docking scores of both compounds are consistent with current understanding.

The results of molecular docking provided direct evidence of the synergistic effect of the two molecules and also laid the foundation for subsequent experimental verification mechanisms, such as Western blot and gene knockout.

Study limitations

Several limitations should be noted. First, the LLC model, though widely used, is a murine tumour and does not fully capture the genetic and immune features of human NSCLC. Our in vivo findings, therefore, have limited translational relevance (50). The observed synergy in LLC-bearing mice should be seen as a proof-of-concept in a syngeneic system, not a direct indicator of clinical efficacy. More clinically relevant models, such as PDX or GEMMs, are needed for further validation (51).

Second, pharmacokinetic studies have reported a Cₘₐₓ of piperine of approximately 0.983 μg mL^–1 after oral administration in rats, and a Cₘₐₓ of luteolin of approximately 3.04 μg mL^–1 in rats (52, 53), yet the concentrations used in our synergy assays (piperine 175.3 µmol L^–1, luteolin 87.32 µmol L^–1) exceed these plasma levels. Nevertheless, they were selected below the individual IC₅₀ values according to the Chou-Talalay method to determine the combination index. Our findings should be interpreted as a mechanistic proof of concept. Future bioavailability‑enhancing strategies, including nanoformulation, could help translate this synergy into in vivo settings (54).

Third, this study focused on establishing the synergistic anti‑proliferative efficacy of the piperine-luteolin combination in cancer cells and did not assess cytotoxicity against normal cell lines. Therefore, the selectivity index (SI), a key metric for evaluating the therapeutic window, could not be determined. This constitutes an important aspect for future translational studies, which will be essential to fully characterise the safety profile of this promising combination.

CONCLUSIONS

In conclusion, it was systematically confirmed that luteolin and piperine have synergistic antitumour effects on NSCLC in vitro and in vivo by A549 cells and LLC tumour-bearing mice. Network pharmacology and multi‑software molecular docking (including reference ligand validation) identified EGFR, MMP9, SRC, and the PI3K/AKT pathway as key mediators, with MMP9 as the common core target, providing structural support for the synergy. The combination of piperine and luteolin had a highly effective tumour-inhibitory effect at low concentrations. It provided an experimental basis for the clinical application of the combined strategy of natural products.

Acknowledgements. – The authors gratefully acknowledge Prof. Tian Chang for the generous gift of the A549 cell line used in this research.

Conflict of Interest. – The authors declare there are no competing interests.

Funding. – This project was funded by Anhui University Natural Science Research Projects of China (grant number KJ2019A0097), Introduction of Talent Fund Project of Anhui University of Science and Technology (grant number 11079), and the open foundation of Key Laboratory of Tropical Plant Resource Chemistry of Hainan Province (grant number rdzw2025s04).

Author’s contribution. – Methodology, A.G.; analysis, Y.L.; investigation, L.W. and B.W.; validation, L.W., B.W., and Y. L.; data curation, Y.D.; writing, original draft preparation, L.W.; writing, review and editing, Y.C.; supervision, Y.C.; project administration, F.J.; funding acquisition, Y.C. All authors have read and agreed to the published version of the manuscript.

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