Inulae Flos is a potential herbal medicine to treat glioma: a study based on gene expression profile analysis, network pharmacology and molecular docking

Qian  Ying; Yi Fang

doi:10.55976/dt.32024132232-52

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Diagnostics and Therapeutics, Volume 3 Issue 1, 2024 /

Original Research

Inulae Flos is a potential herbal medicine to treat glioma: a study based on gene expression profile analysis, network pharmacology and molecular docking

Qian Ying ¹ , Yi Fang ² ^* ^#

1. Department of Oncology, Yichang Central People's Hospital, The First College of Clinical Medical Science, China Three Gorges University & Tumor Prevention and Treatment Center of three Gorges University & Cancer Research Institute of three Gorges University, Yichang 443003, China
2. Department of Oncology, Yichang Central People's Hospital, The First College of Clinical Medical Science, China Three Gorges University & Tumor Prevention and Treatment Center of three Gorges University & Cancer Research Institute of three Gorges University, Yichang 443003, China

# Qian Ying, and Yi Fang contributed equally to this work

*Correspondence: 3288785378@qq.com

DOI: https://doi.org/10.55976/dt.32024132232-52

Received

21 May 2024
Revised

16 October 2024
Accepted

30 November 2024
Published

12 November 2024

Inulae Flos Glioma Network pharmacology Molecular docking

Abstract

Inulae Flos is a promising herbal medicine; however, its underlying mechanism in treating glioma remains unclear. This study aimed to elucidate the potential active ingredients and mechanisms of Inulae Flos in glioma treatment. Differentially expressed genes (DEGs) associated with gliomas were identified by analyzing the GSE186057 dataset. The bioactive components of Inulae Flos were searched in the Traditional Chinese Medicine Systems Pharmacology database, and related targets were obtained from the Swiss Target Prediction database. A protein-protein interaction (PPI) network was constructed using the STRING database. Next, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) of these common targets were analyzed using the DAVID database. Finally, AutoDock Vina was used for molecular docking analysis. The tumor-suppressive properties of the crude extract of Inulae Flos (XFH) and britanin were then evaluated with in vitro and in vivo assays. Nineteen active ingredients were obtained from Inulae Flos, and 20 DEGs were identified as the targets of Inulae Flos in glioma treatment. Britanin, luteolin and 1-O-Acetylbritannilactone were identified as the key ingredients. PIK3R1, CDK2, CCNB1, MAPK1, MAPK8, CCNA2, and AR were considered to be the hub target genes of Inulae Flos in glioma treatment. Good binding affinity was observed between the key components and hub targets. In addition, in vitro studies showed that XFH and britanin, a key component of Inulae Flos, could inhibit the growth, migration and invasion glioma cell lines U87 and U138, and repress the tumorigenesis of U138 cells in nude mice. Inulae Flos is promising for glioma treatment, and it exerts its anti-tumor activities via multiple components, targets and pathways.

<h5>Introduction</h5>
Glioma accounts for approximately 25% of primary central nervous system tumors, with an average mortality rate of 4.43 per 100,000 persons. Its prognosis is extremely poor, especially for glioblastoma multiforme (GBM) <a href="#reference_list_0">[1-4]</a>. Currently, surgical resection combined with radiotherapy and temozolomide (TMZ) chemotherapy is the main treatment strategy for gliomas <a href="#reference_list_4">[5]</a>. However, the patients’ prognosis remains unsatisfactory <a href="#reference_list_5">[6]</a>. Therefore, there is an urgent need to develop novel anticancer drugs for glioma treatment.
Inulae Flos (Xuanfuhua in Chinese) is a perennial herb belonging to the Asteraceae family and the genus Inulae. It is widely distributed in Asia, Africa and Europe and is commonly used in traditional Chinese medicine (TCM) <a href="#reference_list_6">[7]</a>. In China, its is often used to treat digestive diseases, bronchitis, and some inflammatory diseases <a href="#reference_list_7">[8, 9]</a>. Modern pharmacological studies have shown that the main bioactive components of Inulae Flos are terpene lactones (e.g., 1,6-O,O-diacetylbritannilactone, 1-O-acetylbritannilactone, neobritannilactone A, and neobritannilactone B) and flavonoids (e.g., luteolin, patuletin, and quercetin) <a href="#reference_list_9">[10]</a>. Inulae Flos extract can reduce mast cell-mediated allergic reactions induced by immunoglobulin E in animal models <a href="#reference_list_10">[11]</a>. Polysaccharides extracted from Inulae Flos show antidiabetic activity in alloxacil-or streptozotocin-induced diabetic mice by protecting β-cells <a href="#reference_list_11">[12, 13]</a>. In addition, Japonicone A, a natural product extracted from Inulae Flos, has significant antitumor activity against breast cancer, non-small cell lung cancer and myeloma <a href="#reference_list_13">[14-16]</a>. However, the potential value of Inulae Flos for glioma treatment remains unclear.
Network pharmacology is a powerful approach that combines system biology, pharmacology, and bioinformatics analysis to predict disease targets and molecular mechanisms of drug <a href="#reference_list_16">[17, 18]</a>. (Figure 1). This study aimed to predict the potential active ingredients and targets of Inulae Flos, and investigate its tumor-suppressive properties on glioma cells, to evaluate its value in glioma treatment.
<h5>Materials and methods</h5>
Identification and analysis of differentially expressed genes (DEGs) in glioma
From the Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/), GSE186057 dataset (Platform: Pancancer Pathways Panel, NanoString Technologies, Inc.)<a href="#reference_list_18">[19]</a> was downloaded. This database contains gene expression data of 24 GBM tissue samples and 12 normal tissues (adjacent normal tissue, ANT). Using GEO2R tool (http://www.ncbi.nlm.nih.gov/geo/geo2r/), DEGs between tumor and ANT samples were obtained. The thresholds were P < 0.05, and | log2fold change | > 1, and the results were visualized using volcano and heat maps. The ade4 package in R software was used for principal component analysis (PCA), and the ggplot2 package was used for visualization. The CIBERSORT algorithm was used to analyze the immune cells of GBM and ANT samples in the GSE186057 dataset, and a box diagram was used to visualize the immune cell composition of the two groups of samples. The Wilcoxon rank-sum test was used to evaluate differences in the proportions of immune cells. P < 0.05 was considered statistically significant. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were performed using the clusterProfiler package in R software.
Screening of bioactive components and targets of Inulae Flos
Based on oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18, the active components of Inulae Flos were obtained from the Traditional Chinese Medicine Systems Pharmacology database (TCMSP, https://www.tcmsp-e.com/)<a href="#reference_list_19">[20]</a>. The SMILES files of ingredients were obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov) and imported into the Swiss Target Prediction database (http://www.swisstargetprediction.ch) to obtain the ingredients targets, and the threshold was probability > 0.1<a href="#reference_list_20">[21]</a>.
Construction and analysis of protein-protein interaction (PPI) networks at drug-disease common targets
Common drug–disease targets were imported into the STRING database (https://cn.string-db.org/) for PPI analysis<a href="#reference_list_21">[22]</a>. The species was defined as “Homo sapiens” and the required minimum interaction score was set to “medium confidence (0.4)”. Topological network analysis was performed using the CytoNCA plug-in in the Cytoscape 3.9.0 software<a href="#reference_list_22">[23]</a>. In addition, the Molecular Complex Detection (MCODE) plug-in was used to perform module analysis of protein targets in the PPI network, according to default parameters<a href="#reference_list_22">[23]</a>. The default parameters were degree cutoff=2, node score cutoff = 0.2, K-score = 2, and maximum depth = 100.
GO and KEGG pathway analysis of drug-disease common targets
Using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database (https://david.ncifcrf.gov/tools.jsp)<a href="#reference_list_23">[24]</a>, common targets of glioma and Inulae Flos were subjected to GO and KEGG enrichment analyses. The species were defined as “Homo sapiens”, and P < 0.05 was used as the screening condition.
Identification and analysis of hub target genes
Using the CytoHubba plugin in the Cytoscape 3.9.0 software<a href="#reference_list_22">[23]</a>, the top 10 key genes in PPI network analysis were calculated using different algorithms, such as betweenness, closeness, degree, maximal clique centrality (MCC), radiality, and stress. The R software UpSet package was used to screen for cross genes, which were considered hub genes.
<img src="https://file.luminescience.cn/6732c1e9a4fe91731379689" alt="" width="750" height="919" />
Figure 1. The workflow of the present work
Construction and analysis of "component-hub target gene-pathway" network
The top 10 KEGG terms with the most gene counts were imported into Cytoscape 3.9.0 software to plot the "component-hub gene-pathway" network diagram, and the degree values of network nodes were calculated by CytoNCA plug-in<a href="#reference_list_22">[23]</a>, so as to screen out the key components and major hub target genes of Inulae Flos in glioma treatment. The expression characteristics of the hub targets in glioma tissues and non-cancerous brain tissues in The Cancer Genome Atlas (TCGA) were analyzed using GEPIA database (http://gepia.cancer-pku.cn/)<a href="#reference_list_24">[25]</a>.
Molecular docking
Molecular docking analysis was performed using AutoDock Vina (version 1.1.2) to evaluate the ability of key components to bind to major hub targets. The 3D chemical structures of key components were downloaded from PubChem (https://pubchem. ncbi. nlm. nih. gov/) and saved in the SDF format. They were then converted to the mol2 format using OpenBabel software (version 3.1.1). From the Protein Data Bank (PDB; <a href="https://www.rcsb.org/),">https://www.rcsb.org/),</a> X-ray crystal structures of the major hub targets were downloaded. All protein receptor and molecular ligand files were converted to pdbqt files using the AutoDockTools software (version 1.5.7). Molecular docking was performed using the AutoDock Vina software<a href="#reference_list_25">[26]</a>. When the binding energy is less than zero, proteins and molecules can spontaneously bind <a href="#reference_list_26">[27]</a>. The PyMOL software was used to visualize the docking results<a href="#reference_list_25">[26]</a>.
Cell culture
Human glioma cell lines U87 and U138 were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA). The cells were placed in a diet containing Dulbecco's Modified Eagle's Medium (DMEM; Invitrogen, Carlsbad, CA, USA) with 10% fetal bovine serum (FBS; Gbico, Carlsbad, CA, USA), 100 U/mL penicillin and 100 μg/mL streptomycin in an incubator containing 5% CO2 at 37 ℃. 
Preparation of Inulae Flos extract
For the extraction of Inulae Flos, 40 g Inulae Flos (Qiancao, Xi’an, China) was heated in 500 mL boiling water for 30 min, and then the liquid was collected after filtration. The residue was then heated in 250 mL of boiling water for 30 min, and then the liquid was also collected after filtration. The liquids were mixed, and a freeze drying process was performed to obtain the medicinal powder. The powder was then dissolved in dimethylsulfoxide (DMSO; Beyotime, Shanghai, China), and diluted by the medium, and filtered by 0.22 μm filter twice. The crude extract of Inulae Flos was named as XFH (short for the Chinese name of Inulae Flos, Xuanfuhua).
Cell viability assay
Cell counting Kit 8 (CCK-8; Beyotime, Shanghai, China) was used to detect cell viability. U87 and U138 cells were seeded into 96-well plates at a density of 3×103 cells per well. After overnight incubation, the cells were treated with XFH (0, 12,5, 25, 50, 100 μg/ml), or britanin (98.0% purity, CAS No. 33627-28-0, Bohu Biotechnology Co., Ltd, Shanghai, China) (0, 1, 3, 5, and 7 μM) for 24 h. Then, 10 μl of CCK-8 was added to each well of the plate and the cells were further incubated for 4 h. Optical density (OD) was measured at 450 nm.
Transwell assay
The migration and invasion abilities of the glioma cells were analyzed by Transwell assay. In the migration experiment, after U87 and U138 cells were treated with XFH (100 μg/ml) or britanin (7 μM) for 24 h, they were re-suspended in 200 μL of serum-free medium and the cell suspension was added into the upper compartment of a Transwell system (8-μm pore size. Corning, NY, USA). The lower compartment was supplemented with 750 μL complete medium. After culturing for 48 h, the cells on the below surface of the membrane were fixed with methanol for 30 min and stained with 0.1% crystal violet for 10 min. After the membrane was washed by tap water to remove the excessive dye, 6 fields were randomly selected under the microscope to observe and count the cells. The invasion experiment was similar, except that the membrane was pre-coated with a layer of Matrigel (BD Bioscience, San Jose, CA, USA).
In vivo tumorigenesis assay
The Laboratory Animal Ethics Committee of Renmin Hospital of Wuhan University approved the animal experimental procedures in this study (WDRY2021K070). A total of 9 6-week-old male nude mice were used (BALB/C, Model Animal Center of Wuhan University, kept in SPF condition with free access to food and water). The nude mice were randomly divided into three groups [blank control group, XFH treatment group, and britanin treatment group, 3 mice in each group]. U138 cells were treated with XFH (100 μg/ml) or britanin (7 μM) for 24h. Then cell suspension was prepared, and the concentration was adjusted to 1×108 cells /ml, and the inoculation volume was 0.1 ml. The cell suspension was injected into the subcutaneous tissue of the back of nude mice through a sterile syringe. After injection, the tumor growth was checked regularly. By measuring the length and width of the tumor, the tumor volume was calculated using the formula V = 1/2 x length x width. After 24 days, the nude mice were euthanized, and the tumors were isolated and weighted.
Statistical analysis
For in vitro assays, all experiments were conducted independently in triplicates. All data are expressed as mean ± standard deviation (SD). SPSS (version 21.0; IBM Corp., Armonk, NY, USA) was used for all the statistical analyses. Multivariate comparisons were performed using one-way analysis of variance (ANOVA) and Tukey’s post hoc test. P < 0.05 was considered statistically significant.
<h5>Results</h5>
Identification and analysis of DEGs in glioma
GSE186057 was used to identify the DEGs in GBM. PCA showed significant differences between GBM and ANT tissue samples (Figure 1A). Notably, 271 DEGs, including 123 upregulated and 148 downregulated genes, were found between GBM and ANT tissues (Figures 2B, C; Table 1). The CIBERSORT algorithm was used to calculate the proportion of 22 types of immune cells in GBM and ANT samples (Figures 3A and B). Compared with ANT, the infiltration of B cells memory, naive B cells naive, macrophages M0, macrophages M2, Mast cells activated, resting mast cells resting, plasma cells and T cells CD4 memory activated were reduced in GBM tissues, while the infiltration of neutrophils, T cells CD4 memory resting, T cells, CD8 T cells, and gamma delta T cells was increased (Figure 3C). GO and KEGG enrichment analyses were performed to study the biological functions and mechanisms of these DEGs. GO analysis showed that these DEGs were mainly enriched in peptidyl-tyrosine phosphorylation, peptidyl-tyrosine modification, regulation of MAP kinase activity, regulation of peptidyl-tyrosine phosphorylation, and epithelial cell proliferation (Figure 3D). KEGG analysis showed that 182 pathways were associated with DEGs (P < 0.05). The top 10 pathways with the lowest P value were the MAPK signaling pathway (hsa04010), Ras signaling pathway (hsa04014), breast cancer (hsa05224), PI3K-Akt signaling pathway (hsa04151), gastric cancer (hsa05226), human papillomavirus infection (hsa05165), melanoma (hsa05218), Rap1 signaling pathway (hsa04015), acute myeloid leukemia (hsa05221), and proteoglycans in cancer (hsa05205) (Figure 3E).
<img src="https://file.luminescience.cn/6732bb1675de11731377942" alt="" width="750" height="756" />
Figure 2. Identification of DEGs in glioma; A. PCA diagramof GSE186057; B. The expression patterns of the DEGsare shown in a volcano map. Red and blue dots represent upregulated genes (log2FC > 1) and downregulated genes (log2FC < −1), respectively. Gray dots representgenes with no significant difference in expression; C.Heat map of DEGs in GBM and ANT tissues.
<img src="https://file.luminescience.cn/6731cc6ee45431731316846" alt="" width="750" height="431" />
Screening of active constituents and their targets of Inulae Flos
According to OB ≥ 30% and DL ≥ 0.18, 19 potentially active components were obtained from the TCMSP database. Basic information of the active ingredients is provided in Table 2. Subsequently, the targets of these active ingredients were predicted using the Swiss Target Prediction database and 324 drug targets were identified after merging and deleting duplicate candidates.
Construction and analysis of PPI network for drug-disease common targets
To obtain the target of Inulae Flos in glioma treatment, 20 common targets were obtained from the 324 drug targets and 271 DEGs mentioned above (Figure 4A). These 20 common drug-disease targets were then imported into the STRING database for PPI network construction. As shown (Figure 4B), a PPI network with 20 nodes and 57 edges was constructed. The average node degree of the network was 5.7 and the average local clustering coefficient was 0.495. Furthermore, the topological parameters of the PPI network were analyzed, and all nodes were arranged in a circle according to the degree value, which was proportional to the size of the node and the shade of the color (Figure 4C). In addition, module analysis of the PPI network was performed, resulting in a subnetwork of 7 nodes and 19 edges (score =6.333, Figure 4D).
GO and KEGG enrichment analyses of drug-disease common targets
To further explore the mechanism of Inulae Flos in glioma treatment, GO and KEGG enrichment analyses were performed based on common drug–disease targets. GO analysis revealed a total of 85 GO terms, including 60 biological processes (BP), 9 cell components (CC), and 16 molecular functions (MF). The top 10 BP, CC, and MF terms with the highest gene counts were selected for visualization. As shown (Figure 4A), BP was mainly associated with protein phosphorylation, signal transduction, positive regulation of transcription, DNA templated, G2/M transition of the mitotic cell cycle, and peptidyl-serine phosphorylation. CC was mainly associated with the cytosol, nucleus, nucleoplasm, cytoplasm, and plasma membrane (Figure 5A). MF was associated with protein binding, protein serine/threonine/tyrosine kinase activity, ATP-binding protein serine/threonine kinase activity, and protein kinase activity (Figure 5A). In KEGG enrichment analysis, 104 pathways were identified. The top 10 predicted pathways with the highest gene counts are shown, including pathways in cancer (hsa05200), the MAPK signaling pathway (hsa04010), acute myeloid leukemia (hsa05221), and myeloid leukemia (has05221). progesterone-mediated oocyte maturation (hsa04914), cellular senescence (hsa04218),  human T-cell leukemia virus 1 infection (hsa05166), microRNAs in cancer (hsa05206), hepatitis B (hsa05161),  human immunodeficiency virus 1 infection (hsa05170), and the Ras signaling pathway (hsa04014) (Figure 5B). The top 20 KEGG pathways with the highest gene counts were classified. These KEGG pathways were divided into four main categories: environmental information processing, cellular processes, organismal systems, and human diseases (Figure 5C). In addition, secondary classification of all KEGG pathways was performed (Figure 5D). These pathways were mainly related to signal transduction, cell growth and death, eukaryote cellular community, transport, and catabolism.
<img src="https://file.luminescience.cn/6732bc048a6811731378180" alt="" width="1000" height="1068" />
Figure 3. Immunoinfiltration in glioma and enrichment analysis of DEGs; A and B. CIBERSORT algorithms were used to detect scale maps (A) and heat maps (B) of 22 immune cells in GBM and ANT tissue samples; C. Comparison of each type of immune cell between GBM and ATC tissues; D. The top 10 GO-BP enrichment termswith the most significant Pvalues; E. Emapplot of enriched pathways.*P < 0.05, **P < 0.01, ***P < 0.001.
Table 2 can be viewed by clicking <a href="https://file.luminescience.cn/DT-322%20Table%202%281%29.pdf">here</a>.
<img src="https://file.luminescience.cn/6732bce6d77871731378406" alt="" width="700" height="616" />
Figure 4. PPI network analysis of the targets of Inulae Flos for glioma treatment; A.Venn diagram is usedto screen out the shared genes fromtarget genes of Inulae Flos and DEGs in glioma; B. PPI network of the common genes. Nodes represent proteins and edges represent protein-protein interactions; C. CytoNCA plug-in is used to calculate the degree valuesof the PPI network nodes. The larger the degree value, the larger the node; D.MCODE plug-in is used to screen highly interconnected clusters in PPI network.MCODE score = 6.333.
Identification and analysis of hub target genes
The top ten key genes of the PPI network were obtained using the CytoHubba plug-in through six different algorithms (betweenness, closeness, degree, MCC, radiality, and stress) (Table 3). Cross-analysis of the results of the six algorithms showed that PIK3R1, CDK2, CCNB1, MAPK1, MAPK8, CCNA2, and AR were hub genes (Figure 6A). Detailed information on these seven hub genes is provided in Table 4. The chromosome and location information for these seven hub genes are shown (Figure 6B). Compared to the ANT group, PIK3R1, MAPK1, and MAPK8 in GBM tissues were significantly downregulated, whereas CDK2, CCNB1, CCNA2, and AR were significantly upregulated (Figure 6C). In addition, based on the GSE186057 dataset, a network of these seven hub genes and correlation coefficients was constructed (Figure 6D); the expression levels of PIK3R1 in GBM tissue were negatively correlated with the expression levels of CCNB1, CCNA2, and CDK2, and positively correlated with the expression levels of MAPK1 and MAPK8; the expression of CCNB1 was positively correlated with CCNA2 and CDK2, and negatively correlated with MAPK1; CCNA2 expression was positively correlated with CDK2 expression and negatively correlated with MAPK1 expression; CDK2 expression was negatively correlated with MAPK1 and MAPK8 expression; the expression of MAPK8 was positively correlated with that of MAPK1, and negatively correlated with that of AR; AR expression was negatively correlated with MAPK1 expression.
<img src="https://file.luminescience.cn/6732bd403ab401731378496" alt="" width="900" height="770" />
Figure 5. GO and KEGG enrichment analysis of the targets of Inulae Flos for glioma treatment; A. Histogram of the top 10biological processes (green), cell components (red), molecular functions (blue) associated with Inulae Flos with the most gene counts (P< 0.05); B. Sankey and bubble mapsof the top 20 KEGG pathways with the most gene counts. On the left side of the diagram is the sankey diagram, which represents the genes contained in each pathway. On the right is the bubble map, the size of the bubble represents the gene count, and the color of the bubble represents the P-value; C. Classification diagram of the top 20 KEGG channels; D. Secondary classification diagram of all KEGG channels.
<img src="https://file.luminescience.cn/6731cbfa923901731316730" width="700" height="265" />
 
<img src="https://file.luminescience.cn/6731ccca310161731316938" alt="" width="700" height="292" />
 
<img src="https://file.luminescience.cn/6732bee386bd11731378915" alt="" width="800" height="646" />
Figure 6. Identification of hub target gene in treatment of glioma by Inulae Flos; A. The upsetmap of Betweenness, closeness, degree, MCC, radiality and stress algorithms; B. Circosgraph is generated using the Circos package in R software. The outer layer of the Circos diagram shows chromosome positions, and the inner layer represents the differentially expressed hub genes; C. Histogram isused to map the differential expression of hub gene in GBM and ANT tissues. The X-axis is the gene, and the Y-axis is the change fold. Red means up-regulated, above the X-axis; Blue is down-regulated, below the X-axis; D. Correlation coefficient networkof the hub genes’ expression in GBM tissues. The larger the correlation coefficient, the thicker the line. Blue indicates a negative correlation and red indicates a positive correlation.
Construction of "component-hub target gene-pathway" network
Subsequently, the bioactive components of Inulae Flos, the hub target genes and top 10 pathways with most gene counts were imported into Cytoscape 3.9.0 to construct the "component-hub target gene-pathway" network. The network consisted of 32 nodes and 104 edges (Figure 7A). In this network, the five hub genes with the highest degree values were PIK3R1 (degree value = 17), CDK2 (degree value = 15), CCNB1 (degree value = 14), MAPK1 (degree value =13), and MAPK8 (degree value = 8). The three active ingredients with the highest degree values were britanin (degree value = 7), luteolin (degree value = 5), and 1-O-Acetylbritannilactone (degree value =5) (Figure 7B). The expression characteristics of the the 5 potential targets and AR, CCNA2, were also investigated with the data from TCGA, and the results showed that compared with non-cancerous brain tissues, the expression of CDK2, CCNB1, CCNA2 and AR was highly expressed in GBM tissues, however the expression of PIK3R1, MAPK1 and MAPK8 was not remarkably changed (Figure 7C-I).
<img src="https://file.luminescience.cn/6732c019dedf31731379225" alt="" width="800" height="847" />
Figure 7. Construction of the "component-hub target gene-pathway" network; A. Construction of the “component-Hub target gene-pathway” network using Cytoscape 3.9.0 software.A V-shaped node represents a pathway;a circular node represents a target; triangular node represents glioma; a diamond node represents a component; square node represents Inulae Flos. The node size or color shade is proportional to the magnitude of the degree value; B. Bar chart of degree value statistics of the "component -hub target gene-pathway" network; C-I. The expression levels of PIK3R1 (C),CDK2 (D), CCNB1 (E), MAPK1 (F), MAPK8 (G), CCNA2 (H), AR (I) in GBM tissues and non-cancerous brains tissues were analyzed using GEPIA database. *P < 0.001.
Molecular docking of key components and major hub genes
In order to explore the interaction between active components of Inulae Flos and predicted hub targets, 3 key components (britanin, luteolin, and 1-O-Acetylbritannilactone) and 5 major hub targets (PIK3R1, CDK2, CCNB1, MAPK1, and MAPK8) were selected for molecular pairing Binding energies less than 0 kcal/mol indicate possible binding between two molecules, and binding energies less than −5.0 kcal/mol indicate strong binding activity between molecules <a href="#reference_list_26">[27, 28]</a>. The results showed that britanin, luteolin, and 1-O-Acetylbritannilactone had good binding affinities for the five targets (Figure 8A-E). The docking results implied that the role of Inulae Flos in glioma treatment was dependent on multiple components and targets.
XFH and britanin inhibited growth and aggressiveness of glioma cells 
To verify the potential function of Inulae Flos in glioma treatment, the crude extract of Inulae Flos (XFH) was used to treat glioma cells in vitro. Britanin, a key component of Inulae Flos, was also selected to treat the cells. U87 and U138 cells were treated with different concentrations of XFH (0, 12,5, 25, 50, 100 μg/ml) or britanin (0, 1, 3, 5, and 7 μM) for 24 h and cell viability was determined using the CCK-8 method. As shown (Figure 9A-D), XFH and britanin exhibited significant anti-growth activity in both the U87 and U138 cells in a concentration-dependent manner. Transwell assay showed that XFH (100 μg/ml) and britanin (7 μM) respectively repressed the migration and invasion abilities of U87 and U138 cells (Figure 9E-J). Additionally, after U138 cells were treated with XFH (100 μg/ml) or britanin (7 μM), the tumorigenesis ability in nude mice was significantly reduced (Figure 10). These data further support the hypothesis that Inulae Flos and britanin have tumor-suppressive properties for gliomas.
<img src="https://file.luminescience.cn/6732bf8e53e7d1731379086" alt="" width="800" height="837" />
Figure 8. 3D molecular docking diagram of key components and hub targets; A-E. Molecular docking diagram of key components britanin, luteolin, 1-O-Acetylbritannilactone and major hub targets PIK3R1 (A), CDK2 (B), CCNB1 (C), MAPK1 (D), MAPK8 (E). Purple represents key components (ligands), orange represents amino acid residues surrounding the binding bag, and yellow dashed lines represent hydrogen bonds.
<h5><img src="https://file.luminescience.cn/6731cfb4a3ba41731317684" alt="" width="700" height="932" /></h5>
Figure 9. Crude extract of Inulae Flos and britanin inhibited the viability and aggressiveness of glioma cells; A-B. CCK-8 assay was used to evaluate the effects of different concentrations of XFH (0, 12,5, 25, 50, 100 μg/ml) on the viability of the U87 (A) and U138 (B) cells; C-D. CCK-8 assay was used to evaluate the effects of different concentrations of Britanin (0, 1, 3, 5, and 7 μM) on the viability of the U87 (C) and U138 (D) cells; E-F. A-B. CCK-8 assay was used to evaluate the effects of 100 μg/ml XFH on the migration ability and invasion ability of the U87 (A) and U138 (B) cells; G-H. A-B. CCK-8 assay was used to evaluate the effects of 7 μM Britanin on the migration ability and invasion ability of the U87 (G) and U138 (H) cells; I-J. The quantitative results of Transwell assays.**P < 0.01, ***P < 0.001, compared with the control group.
<h5><img src="https://file.luminescience.cn/6732c0b66c28b1731379382" alt="" width="800" height="275" /></h5>
Figure 10. XFH and Britanin inhibited the growth of glioma cells in vivo; A. U138 cells were inoculated into the subcutaneous tissues of nude mice. This figure shows the tumors in control group, XFH treatment group, and britanin treatment group; B. The tumor volume of the mouse in each group was measured every 4 days; C. The weights of the tumor in each group were measured and compared.**P < 0.01, ***P < 0.001, compared with the control group.
<h5>Discussion</h5>
Using a dataset of gene expression profiles, 271 DEGs (GBM tissues vs. ANT) were identified in the present study. Bioinformatic analysis suggested that these DEGs play a key role in multiple biological processes and pathways. Our findings suggest that the pathological mechanisms underlying gliomas are complex. Therefore, there is a need to develop novel treatment strategies that can modulate multiple targets and pathways in gliomas to improve the patients’ prognosis. Herbal medicines consist of multiple bioactive components that may exert pharmacological effects <a href="#reference_list_28">[29-32]</a>. In recent years, TCM has shown great value in the treatment of glioma <a href="#reference_list_29">[30-32]</a>. For example, extracts of Curcumae Longae Rhizoma and Crocus sativus L. can inhibit the malignant biological behaviors of gliomas by regulating the immune-inflammatory response <a href="#reference_list_30">[31, 32]</a>. Previous studies have shown that Inulae Flos has multiple pharmacological effects, including anti-tumor effects <a href="#reference_list_9">[10-16]</a>. However, to the best of our knowledge, its pharmacological mechanism for treating glioma has not yet been studied. In the present work, it was observed that the crude extract of Inulae Flos has significant tumor-suppressive effects on glioma cells.
Through network pharmacological analysis, we identified three key components of Inulae Flos, britanin, luteolin, and 1-O-Acetylbritannilactone, which can interact with multiple targets. Britanin, a sesquiterpene lactone compound, has significant antioxidant and anti-inflammatory activities <a href="#reference_list_32">[33]</a>. Britanin has significant anti-proliferative activity against human prostate carcinoma, gastric carcinoma, pancreatic carcinoma, and triple-negative breast carcinoma <a href="#reference_list_32">[33-36]</a>, and in the present work, in vitro and in vivo assays have also supported that britanin represses the growth of glioma cells. Luteolin (3,4,5,7-tetrahydroxy flavone) is a flavonoid found in various plants including vegetables, herbs, and fruits. In vitro and in vivo studies suggest that it can be used as an anticancer agent against various types of human malignancies such as lung carcinoma, breast carcinoma, GBM, prostate carcinoma, colonic carcinoma, and pancreatic carcinoma <a href="#reference_list_36">[37]</a>. There is evidence that 1-O-Acetylbritannilactone has a variety of biological effects, including anti-inflammatory, anti-bacterial, anti-hepatitis, anti-diabetes, and anti-tumor effects <a href="#reference_list_37">[38-40]</a>. Together with these reports, our findings suggest that Inulae Flos may block glioma progression via britanin, luteolin, and 1-O-Acetylbritannilactone.
Our study reported that PIK3R1, CDK2, CCNB1, MAPK1, MAPK8, CCNA2, and AR, with high topological parameters, were hub targets of Inulae Flos in the treatment of glioma. We also analyzed the GES186057 dataset and found that PIK3R1, MAPK1, and MAPK8 were downregulated, whereas CDK2, CCNB1, CCNA2, and AR were upregulated in GBM tissues. A previous study reported that the expression of PIK3R1 is low in glioma and its high expression is associated with good prognosis in glioma patients <a href="#reference_list_40">[41]</a>, which is consistent with our findings. In addition, CDK2, CCNB1, CCNA2, and AR have been reported to be overexpressed in gliomas and are associated with poor patient prognosis<a href="#reference_list_41">[42-44]</a>, which is consistent with our findings. MAPK1 knockdown can inhibit the phosphorylation of its downstream proteins, thereby inhibiting the proliferation of glioma cells and inducing apoptosis <a href="#reference_list_44">[45]</a>. MAPK8 is upregulated in TMZ-resistant GBM cells, which promotes resistance to TMZ of cancer cells by activating the MAPK signaling pathway, accelerates cell proliferation, and inhibiting cell apoptosis <a href="#reference_list_45">[46]</a>. In our work, molecular docking showed that the 5 major hub targets (5 major hub targets (PIK3R1, CDK2, CCNB1, MAPK1, and MAPK8)) have good binding affinity to britanin, luteolin, and 1-O-Acetylbritannilactone, which suggests that Inulae Flos may suppress the proliferation, aggressiveness and chemoresistance of glioma cells via these hub targets.
KEGG analysis showed that the treatment of glioma by Inulae Flos involved multiple pathways, including the MAPK, Ras, and PI3K-Akt signaling pathways. The MAPK signaling pathway plays a key role in supporting tumor survival and proliferation <a href="#reference_list_44">[45-47]</a>. The Ras signaling pathway is an important part of the cell signaling pathway and plays a crucial role in carcinogenic signaling <a href="#reference_list_47">[48]</a>. The PI3K-Akt signaling pathway is closely associated with the progression of various cancers, and targeting the PI3K-Akt signaling pathway is a promising strategy for glioma treatment <a href="#reference_list_48">[49]</a>. However, the regulatory effects of Inulae Flos and its functional components on these pathways remain to be investigated in molecular biological studies.
It is necessary to claim that because the completeness of the databases used in this work is uncertain, some components and targets may be missed, and more open-access databases and more diverse omics data will be helpful to further clarify the role of Inulae Flos and its targets in glioma treatment<a href="#reference_list_49">[50]</a>. What’s more, based on molecular docking the binding affinity between the components of Inulae Flos and the hub targets, should be further validated with techniques such as molecular dynamics simulation<a href="#reference_list_50">[51]</a>. Additionally, the blood-brain barrier permeability of the active components including britanin, should be carefully considered in future studies, which is crucial for clinical applications, and the safety and efficacy require more data from clinical trials.
<h5>Conclusion</h5>
Inulae Flos may play an important role in the treatment of glioma by acting on multiple targets and pathways via multiple bioactive components. Our findings provide crucial information regarding the pharmaceutical values of Inulae Flos, and suggest that the bioactive components of Inulae Flos, including britanin, are promising candidate drugs for clinical treatment of glioma.
<h5>Authors' contribution</h5>
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
<h5>Ethical approval</h5>
The use of human data in the present study is exempt from ethical approval, which was permitted by the Research Ethics Committee of Yichang Central People's Hospital, because related bioinformatics analyses did not disclose the patient's privacy, and as ex post analyses, the analyses did not change the procedures of diagnosis and treatment. The Laboratory Animal Ethics Committee of Renmin Hospital of Wuhan University approved all experiments with animals in this study (WDRY2021K070).
<h5>Acknowledgement</h5>
We thank Dr. Zhou Youdong, from Renmin Hospital of Wuhan University, for his kind support for animal experiments.
<h5>Funding information</h5>
This study is not supported by any funding agencies. This study is financially supported by the corresponding authors Zhang Haiquan & Zhu Yaozu.
<h5>Data availability statement</h5>
The data used to support the findings of this study are available from the corresponding author upon request.

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Ying, Q. ., and Y. Fang. “Inulae Flos Is a Potential Herbal Medicine to Treat Glioma: A Study Based on Gene Expression Profile Analysis, Network Pharmacology and Molecular Docking”. Diagnostics and Therapeutics, vol. 3, no. 1, Nov. 2024, pp. 32-52, doi:10.55976/dt.32024132232-52.

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