OBJECTIVE: To analyze the acupoint selection patterns and core prescriptions of acupuncture for polycystic ovary syndrome (PCOS) using data mining, and to explore the molecular mechanisms of core acupoints through network acupuncture medicine. METHODS: The randomized controlled trials (RCTs) on acupuncture for PCOS published from January 1, 2004 to July 21, 2024 were retrieved from CNKI, VIP, Wanfang, PubMed, and Web of Science databases. R software (version 4.4.0) was used for acupoint frequency and association rule analysis to identify core acupoint prescriptions. Potential targets were predicted via the STITCH and Swiss Target Prediction databases, and a "core prescription-active compounds-targets- PCOS" network was constructed. Cytoscape 3.7.1 was applied to build protein-protein interaction (PPI) networks of potential targets of core acupoint prescriptions. Key therapeutic targets were subjected to gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses using the DAVID and Microbioinformatics platforms. RESULTS: A total of 176 RCTs were included, covering 208 prescriptions and 89 acupoints. The five most frequently used acupoints were Guanyuan (CV4), Sanyinjiao (SP6), Zigong (EX-CA1), Zusanli (ST36) and Zhongji (CV3). Association rule analysis yielded 13 core acupoint combinations, with Guanyuan (CV4), Sanyinjiao (SP6), Zigong (EX-CA1) and Zusanli (ST36) as the core prescription. Twenty-seven active compounds were involved, with 852 potential therapeutic targets, among which 208 targets overlapped with PCOS-related targets. Network acupuncture medicine analysis suggested that the core prescription may act through targets such as estrogen receptor 1 (ESR1), proto-oncogene tyrosine-protein kinase Src (SRC), signal transducer and activator of transcription 3 (STAT3), peroxisome proliferator-activated receptor gamma (PPARG), and RAC-alpha serine/threonine-protein kinase (AKT1). GO and KEGG analyses indicated that the main pathways included the hypoxia-inducible factor 1 (HIF-1) signaling pathway, phosphatidylinositol 3-kinase-protein kinase B (PI3K-AKT) signaling pathway, and advanced glycation end products-receptor for advanced glycation end products (AGE-RAGE) signaling pathway, involving processes such as signal transduction, receptor complex formation, and cytokine activity. CONCLUSION The core acupoint prescription for PCOS might exert therapeutic effects through multiple targets and pathways, providing a theoretical basis for mechanistic research on acupoint prescriptions.
Humans ; Acupuncture Therapy ; Data Mining ; Acupuncture Points ; Polycystic Ovary Syndrome/metabolism* ; Female ; Protein Interaction Maps ; Randomized Controlled Trials as Topic

BACKGROUND: Diabetic foot is a complex condition with high incidence, recurrence, mortality, and disability rates. Current treatments for diabetic foot ulcers are often insufficient. This study was conducted to identify potential therapeutic targets for diabetic foot. METHODS: Datasets related to diabetic foot and diabetic skin were retrieved from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using R software. Enrichment analysis was conducted to screen for critical gene functions and pathways. A protein interaction network was constructed to identify node genes corresponding to key proteins. The DEGs and node genes were overlapped to pinpoint target genes. Plasma and chronic ulcer samples from diabetic and non-diabetic individuals were collected. Western blotting, immunohistochemistry, and enzyme-linked immunosorbent assays were performed to verify the S100 calcium binding protein A9 (S100A9), inflammatory cytokine, and related pathway protein levels. Hematoxylin and eosin staining was used to measure epidermal layer thickness. RESULTS: In total, 283 common DEGs and 42 node genes in diabetic foot ulcers were identified. Forty-three genes were differentially expressed in the skin of diabetic and non-diabetic individuals. The overlapping of the most significant DEGs and node genes led to the identification of S100A9 as a target gene. The S100A9 level was significantly higher in diabetic than in non-diabetic plasma (178.40 ± 44.65 ng/mL vs. 40.84 ± 18.86 ng/mL) and in chronic ulcers, and the wound healing time correlated positively with the plasma S100A9 level. The levels of inflammatory cytokines (tumor necrosis factor-α, interleukin [IL]-1, and IL-6) and related pathway proteins (phospho-extracellular signal regulated kinase [ERK], phospho-p38, phospho-p65, and p-protein kinase B [Akt]) were also elevated. The epidermal layer was notably thinner in chronic diabetic ulcers than in non-diabetic skin (24.17 ± 25.60 μm vs. 412.00 ± 181.60 μm). CONCLUSIONS S100A9 was significantly upregulated in diabetic foot and was associated with prolonged wound healing. S100A9 may impair diabetic wound healing by disrupting local inflammatory responses and skin re-epithelialization.
Calgranulin B/therapeutic use* ; Diabetic Foot/metabolism* ; Humans ; Datasets as Topic ; Computational Biology ; Mice, Inbred C57BL ; Animals ; Mice ; Protein Interaction Maps ; Immunohistochemistry

OBJECTIVES: To identify the key genes and immunological pathways shared by type 2 diabetes mellitus (T2DM) and chronic obstructive pulmonary disease (COPD) and explore the potential therapeutic targets of T2DM complicated by COPD. METHODS: GEO database was used for analyzing the gene expression profiles in T2DM and COPD to identify the common differentially expressed genes (DEGs) in the two diseases. A protein-protein interaction network was constructed to identify the candidate hub genes, which were validated in datasets and disease sets to obtain the target genes. The diagnostic accuracy of these target genes was assessed with ROC analysis, and their expression levels and association with pulmonary functions were investigated using clinical data and blood samples of patients with T2DM and COPD. The abundance of 22 immune cells was analyzed with CIBERSORT algorithm, and their relationship with the target genes was examined using correlation analysis. DGIdb database was used for analyzing the drug-gene interactions and the druggable genes followed by gene set enrichment analysis. RESULTS: We identified a total of 175 common DEGs in T2DM and COPD, mainly enriched in immune- and inflammation-related pathways. Among these genes, CXCL12 was identified as the final target gene, whose expression was elevated in both T2DM and COPD (P<0.05) and showed good diagnostic efficacy. Immune cell infiltration correlation analysis showed significant correlations of CXCL12 with various immune cells (P<0.01). GESA analysis showed that high CXCL12 expression was significantly correlated with "cytokine-cytokine receptor interaction". Drug-gene analysis showed that most of CXCL12-related drugs were not targeted drugs with significant cytotoxicity. CONCLUSIONS CXCL12 is a potential common key pathogenic gene of COPD and T2DM, and small-molecule targeted drugs against CXCL12 can provide a new strategy for treatment T2DM complicated by COPD.
Humans ; Pulmonary Disease, Chronic Obstructive/complications* ; Diabetes Mellitus, Type 2/genetics* ; Chemokine CXCL12/metabolism* ; Protein Interaction Maps ; Gene Expression Profiling

OBJECTIVES: To explore the mechanism by which Pulsatilla saponin D (PSD) inhibits invasion and metastasis of triple-negative breast cancer (TNBC). METHODS: The public databases were used to identify the potential targets of PSD and the invasion and metastasis targets of TNBC to obtain the intersection targets between PSD and TNBC. The "PSD-target-disease" interaction network was constructed and protein-protein interaction (PPI) analysis was performed to obtain the core targets, which were analyzed for KEGG pathway and GO functional enrichment. Molecular docking study of the core targets and PSD was performed, and the therapeutic effect and mechanism of PSD were verified using Transwell assay and Western blotting in cultured TNBC cells. RESULTS: Network pharmacology analysis identified a total of 285 potential PSD targets and 26 drug-disease intersection core targets. GO analysis yielded 175 entries related to the binding of biomolecules (protein, DNA and RNA), enzyme activities, and regulation of gene transcription. KEGG analysis yielded 46 entries involving pathways in cancer, chemical carcinogenesis-receptor activation, microRNAs in cancer, chemical carcinogenesis-reactive oxygen species, PD-L1 expression and PD-1 checkpoint pathway in cancer. Molecular docking showed high binding affinities of PSD to MTOR, HDAC2, ABL1, CDK1, TLR4, TERT, PIK3R1, NFE2L2 and PTPN1. In cultured TNBC cells, treatment with PSD significantly inhibited cell invasion and migration and lowered the expressions of MMP2, MMP9, N-cadherin and the core proteins p-mTOR, ABL1, TERT, PTPN1, HDAC2, PIK3R1, CDK1, TLR4 as well as NFE2L2 expressionin the cell nuclei. CONCLUSIONS The inhibitory effects of PSD on TNBC invasion and metastasis are mediated by multiple targets and pathways.
Humans ; Triple Negative Breast Neoplasms/metabolism* ; Saponins/pharmacology* ; Pulsatilla/chemistry* ; Female ; Molecular Docking Simulation ; Cell Line, Tumor ; Neoplasm Invasiveness ; Protein Interaction Maps ; Neoplasm Metastasis ; Signal Transduction/drug effects* ; Cell Movement/drug effects*

OBJECTIVES: To explore the role of oxidative stress and immune infiltration in rheumatoid arthritis (RA). METHODS: RA datasets GSE55235 (10 RA vs 10 normal samples) and GSE55457 (13 RA vs 10 normal samples) from the GEO database were merged as the test set to identify the differentially expressed genes (DEGs) in RA using R. The DEGs were intersected with oxidative stress-related genes to obtain oxidative stress-associated DEGs. KEGG and GO enrichment analyses of the DEGs were performed, and the RA-related pathways and biological processes were analyzed using GSEA. A protein-protein interaction (PPI) network was constructed using STRING and Cytoscape, and the top 10 key genes were obtained using the Degree algorithm. The validation dataset GSE1919 from GEO database was used for ROC analysis of the key genes to obtain the core genes, and their correlations with infiltrating immune cells were analyzed using CIBERSORT. The results were verified by RT-qPCR for detecting expression levels of the core genes in RA and normal joint samples. RESULTS: We identified 89 oxidative stress-associated DEGs. Enrichment analysis suggested that these DEGs were involved in the biological processes including oxidative stress, chemical stress response, reactive oxygen species response, and lipopolysaccharide response. ROC analysis showed that the 5 core genes (STAT1, MMP9, MYC, CCL5, and JUN) all had AUC values >0.7, indicating their high diagnostic sensitivity and specificity for RA. These genes were closely correlated with immune cells, particularly T cells. RT-qPCR confirmed significant differential expressions of the core genes between RA and normal samples. CONCLUSIONS Oxidative stress and diverse immune responses are features of RA, and the immune responses contribute to activation of oxidative stress. The identified core genes can potential serve as new diagnostic markers for RA.
Arthritis, Rheumatoid/genetics* ; Oxidative Stress/genetics* ; Humans ; Computational Biology ; Protein Interaction Maps ; Gene Expression Profiling ; Gene Regulatory Networks

OBJECTIVES: To investigate the inhibitory effect of Fuzheng Huaji Decoction against non-small cell lung cancer (NSCLC) cells in vitro and explore the underlying mechanism. METHODS: The active ingredients and targets of Fuzheng Huaji Decoction were identified using TCMSP and SwissTargetPrediction databases. NSCLC-related targets from GeneCards and PharmGKB were intersected with the targets of the Decoction, and a protein-protein interaction (PPI) network was constructed to identify the core targets, which were analyzed with GO and KEGG pathway enrichment analysis. Cultured A549 cells were treated with different concentrations of Fuzheng Huaji Decoction-medicated serum, and the changes in cell proliferation, apoptosis, and protein expressions were examined using CCK-8 assay, annexin V-FITC/PI staining and Western blotting. RESULTS: Fuzheng Huaji Decoction contained 140 active ingredients, and 707 drug-disease intersecting targets were identified. Among these targets, TP53, AKT1, HIF1A, GAPDH, ALB, EGFR, CTNNB1, and TNF were identified as the core targets which were involved in the biological processes related to kinases and receptors and the PI3K-AKT, Ras, calcium, and MAPK pathways. Molecular docking studies indicated strong binding affinity of the active ingredients with TP53, AKT1, and HIF1A. In cultured A549 cells, treatment with 2.5%, 5%, and 10% Fuzheng Huaji Decoction-medicated serum significantly inhibited cell proliferation, promoted cell apoptosis, and downregulated the expression levels of HIF1A, p-AKT (Thr308), and TP53 proteins. CONCLUSIONS Fuzheng Huaji Decoction inhibits proliferation of NSCLC cells possibly by downregulating the expressions of HIF1A, p-AKT (Thr308), and TP53.
Humans ; Carcinoma, Non-Small-Cell Lung/metabolism* ; Drugs, Chinese Herbal/pharmacology* ; Cell Proliferation/drug effects* ; Apoptosis/drug effects* ; Lung Neoplasms/metabolism* ; A549 Cells ; Proto-Oncogene Proteins c-akt/metabolism* ; Protein Interaction Maps ; Signal Transduction/drug effects* ; Cell Line, Tumor

OBJECTIVES: To explore the therapeutic mechanism of Guizhi Fuling (GZFL) Pellets against cervical cancer. METHODS: Publicly available databases were used to identify the targets of GZFL Pellets and cervical cancer to construct the protein-protein interaction (PPI) network, followed by GO biological process and KEGG pathway enrichment analysis of the hub genes. The "Traditional Chinese Medicine-Active Ingredients-Targets-Pathways" network for GZFL Pellets in cervical cancer treatment was generated using Cytoscape v10.0.0, and molecular docking of the drug and potential targets was performed to predict the specific targets of active components in Guizhi Fuling Pellets. The inhibitory effects of hederagenin, an active ingredient in GZFL Pellets, was tested in cultured cervical cancer cells and in nude mice bearing cervical cancer xenografts. RESULTS: GZFL Pellets contain 338 active components targeting 247 action sites. A total of 10127 cervical cancer-related targets were obtained, and among them 195 were identified as potential therapeutic targets of GZFL Pellets for cervical cancer treatment, including the key targets of GABRA1, PTK2, JAK2, HTR3A, GSR, and IL-17. Molecular docking study showed low binding energies of the active components such as hederagenin, campesterol, and stigmasterol for protein-molecule interaction. GO enrichment analysis suggested that GZFL Pellets inhibited cervical cancer primarily by regulating responses to steroid hormones, oxidative stress, and lipopolysaccharides. Among the active components of GZFL Pellets, hederagenin was found to inhibit cervical cancer cells in vitro and significantly reduced STAT3 phosphorylation level in the cancer cells. In nude mice bearing cervical cancer xenografts, hederagenin effectively inhibited tumor growth rate without causing obvious adverse effects. CONCLUSIONS GZFL Pellets inhibit cervical cancer cell growth through its multiple active components that target different pathways. Among these components, hederagenin inhibits tumor cell growth possibly by directly binding to JAK2 protein to inhibit STAT3 phosphorylation.
Female ; Animals ; Uterine Cervical Neoplasms/pathology* ; Mice, Nude ; Humans ; Mice ; Oleanolic Acid/therapeutic use* ; Drugs, Chinese Herbal/therapeutic use* ; Molecular Docking Simulation ; Xenograft Model Antitumor Assays ; Cell Line, Tumor ; STAT3 Transcription Factor/metabolism* ; Protein Interaction Maps ; Janus Kinase 2/metabolism*

OBJECTIVES: To investigate the inhibitory effect of multimerin-2 (MMRN2) overexpression on growth and metastasis of cutaneous melanoma cells. METHODS: Clinical data of patients with cutaneous melanoma were obtained from the GEO database to compare MMRN2 expressions between normal and tumor tissues. A protein-protein interaction network was constructed using the STRING database, and the intersecting genes from GEPIA2.0 were subjected to GO and KEGG enrichment analysis. The prognostic relevance of MMRN2 expression level was assessed using Cox regression and "timeROC". The correlations of MMRN2 expression level with immune infiltration and angiogenesis-related genes were analyzed using GSCA database and the ssGSEA algorithm. Colony-forming assay, Transwell assay, and wound healing assay were used to examine the changes in proliferation and migration of cultured cutaneous melanoma cells following MMRN2 knockdown. In a mouse model bearing cutaneous melanoma xenograft, the effect of MMRN2 knockdown on vital organ pathologies, survival of the mice and GM-CSF, CXCL9, and TGF‑β1 protein expressions were analyzed. RESULTS: MMRN2 was significantly upregulated in metastatic cutaneous melanoma (P<0.001). Protein interaction network analysis identified 15 intersecting genes, which were enriched in endothelium development and cell-cell junctions. In patients with cutaneous melanoma, a high MMRN2 expression was correlated with a poor prognosis, an advanced T stage, a greater Breslow depth, and ulceration (P<0.05). MMRN2 expression level was strongly correlated with 24 immune cell types (P<0.001), fibroblasts, endothelial cells, and expressions of the pro-angiogenic genes (KCNJ8, SLCO2A1, NRP1, and COL3A1; P<0.001). In cultured B16F10 cells, MMRN2 knockdown significantly suppressed cell proliferation, migration and invasion and caused remo-deling of the immunosuppressive microenvironment. CONCLUSIONS MMRN2 overexpression drives progression of cutaneous melanoma by enhancing tumor metastasis, angiogenesis and immune evasion, highlighting its potential as a therapeutic target for melanomas.
Humans ; Melanoma/metabolism* ; Animals ; Cell Movement ; Prognosis ; Skin Neoplasms/metabolism* ; Mice ; Cell Proliferation ; Neoplasm Invasiveness ; Cell Line, Tumor ; Protein Interaction Maps

OBJECTIVES: To explore the value of ferroptose-related genes in the diagnosis and prediction of ulcerative colitis (UC). METHODS: We used UC dataset from the GEO database to screen for differentially expressed genes (DEGs) in UC. The DEGs related to ferroptositis were screened from the FerrDb database and their functions were analyzed. The hub genes were identified by constructing the protein-protein interaction network (PPI), the differences in immune infiltration levels between UC and the control group were evaluated using CIBERSORT, and the diagnostic values of the hub genes for UC were verified by using the training set. In a mouse model of UC, we examined the expression levels of the hub genes in the colon tissues of the mice using real-time fluorescence quantitative PCR (qPCR). RESULTS: We identified a total of 76 DEGs related to ferroptosis. Functional enrichment analysis showed that these genes were significantly enriched in ferroptosis and hypoxia pathways. The PPI network identified 10 hub genes, and 9 of them were highly expressed in UC. Analysis of immune cell infiltration showed that 27 cell types were significantly increased in UC (P<0.05), and the immune checkpoints-related genes had the strongest correlation with the hub gene PPARG (P<0.05). Verification analysis using the training set showed that P4HB, PPARG and STAT3 had the best predictive value for UC (P<0.05). In the UC mouse model, the expression of PPARG was significantly decreased and the expressions of P4HB and STAT3 were significantly increased in the colon tissues of the mice as compared with the normal mice. CONCLUSIONS Ferroptose-related genes have significant value for diagnosis and prediction of UC.
Colitis, Ulcerative/genetics* ; Animals ; Mice ; Ferroptosis/genetics* ; Humans ; Protein Interaction Maps ; Disease Models, Animal ; Gene Expression Profiling ; STAT3 Transcription Factor/genetics*

OBJECTIVES: This study aimed to explore the active components, potential targets, and mechanism of Cnidii Fructus in the treatment of periodontitis with osteoprosis through network pharmacology, molecular docking, and molecular dynamics simulation technology. METHODS: The main chemical constituents and targets of Cnidii Fructus were screened using the TCMSP and SwissTargetPrediction databases, as well as literature reports. Targets of periodontitis and osteoporosis were predicted using different databases. The intersection targets of Cnidii Fructus, periodontitis, and osteoporosis were obtained using Venny 2.1. The protein-protein interaction network was formed on the STRING platform. Cytoscape 3.9.1 was used to construct the active component-intersection target interaction network, perform the topological analysis, and screen key targets and core active components. Furthermore, the Metascape database was used to perform gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis on the intersection targets. The top five key targets and core active components were selected as receptor proteins and ligand small molecules. Discovery Studio 2019 was used to dock ligands and receptors and visualize the docking results. Molecular dynamics simulation was conducted using Gromacs2022.3 to assess the stability of the interactions between the core active components and the main targets. RESULTS: A total of 20 potential active ingredients of Cnidii Fructus were screened, and 116 targets of Cnidii Fructus were obtained for treating periodontitis and osteoporosis. GO and KEGG analyses of the 116 targets showed that Cnidii Fructus may play a therapeutic role through the phosphoinositide 3-kinase-protein kinase B (PI3K-Akt) and advanced glycation end products-receptor for advanced glycation end products (AGE-RAGE) signaling pathways. Molecular docking showed that the core constituents were well bound to the main targets. Molecular dynamics simulations confirmed the stability of the Diosmetin-AKT1 complex system. CONCLUSIONS The preliminary discovery of the potential molecular pharmacological mechanism of Cnidii Fructus extract in the targeted treatment of periodontitis with osteoporosis through a multi-component, multitarget, and multi-pathway approach can serve as a theoretical foundation for future drug-development research and clinical application.
Molecular Docking Simulation ; Molecular Dynamics Simulation ; Network Pharmacology ; Periodontitis/complications* ; Drugs, Chinese Herbal/chemistry* ; Osteoporosis/complications* ; Humans ; Protein Interaction Maps ; Cnidium/chemistry*