The present study aimed to explore the main active components and underlying mechanisms of Marsdenia tenacissima in the treatment of ovarian cancer(OC) through network pharmacology, molecular docking, and in vitro cell experiments. The active components of M. tenacissima were obtained from the literature search, and their potential targets were obtained from SwissTargetPrediction. The OC-related targets were retrieved from Therapeutic Target Database(TTD), Online Mendelian Inheritance in Man(OMIM), GeneCards, and PharmGKB. The common targets of the drug and the disease were screened out by Venn diagram. Cytoscape was used to construct an "active component-target-disease" network, and the core components were screened out according to the node degree. The protein-protein interaction(PPI) network of the common targets was constructed by STRING and Cytoscape, and the core targets were screened out according to the node degree. GO and KEGG enrichment analyses of potential therapeutic targets were carried out with DAVID database. Molecular docking was used to determine the binding activity of some active components to key targets by AutoDock. Finally, the anti-OC activity of M. tenacissima extract was verified based on SKOV3 cells in vitro. The PI3K/AKT signaling pathway was selected for in vitro experimental verification according to the results of GO function and KEGG pathway analyses. Network pharmacology results showed that 39 active components, such as kaempferol, 11α-O-benzoyl-12β-O-acetyltenacigenin B, and drevogenin Q, were screened out, involving 25 core targets such as AKT1, VEGFA, and EGFR, and the PI3K-AKT signaling pathway was the main pathway of target protein enrichment. The results of molecular docking also showed that the top ten core components showed good binding affinity to the top ten core targets. The results of in vitro experiments showed that M. tenacissima extract could significantly inhibit the proliferation of OC cells, induce apoptosis of OC cells through the mitochondrial pathway, and down-regulate the expression of proteins related to the PI3K/AKT signaling pathway. This study shows that M. tenacissima has the characteristics of multi-component, multi-target, and multi-pathway synergistic effect in the treatment of OC, which provides a theoretical basis for in-depth research on the material basis, mechanism, and clinical application.
Humans ; Female ; Marsdenia ; Molecular Docking Simulation ; Network Pharmacology ; Phosphatidylinositol 3-Kinases ; Proto-Oncogene Proteins c-akt ; Ovarian Neoplasms/genetics* ; Databases, Genetic ; Plant Extracts ; Drugs, Chinese Herbal/pharmacology*

This paper aimed to explore the antidepressant effect of the essential oil from Schizonepeta tenuifolia Briq.(EOST) on the treatment of depression and its mechanism by using a combination of network pharmacology and the mouse model of lipopolysaccharide(LPS)-induced depression. The chemical components in EOST were identified using gas chromatography-mass spectrometer(GC-MS), and 12 active components were selected as the study objects. The targets related to EOST were obtained by Traditional Chinese Medicines Systems Pharmacology(TCMSP) and SwissTargetPrediction database. The targets related to depression were screened out through GeneCards, Therapeutic Target Database(TTD), and Online Mendelian Inheritance in Man(OMIM) database. The Venny 2.1 was applied to screen out the common targets of EOST and depression. The targets were imported into Cytoscape 3.7.2 to generate "drug-active component-diease-target" network diagram. The protein-protein interaction(PPI) network was constructed using STRING 11.5 database and Cytoscape 3.7.2, and the core targets were screened out. DAVID 6.8 database was used for Gene Ontology(GO) func-tional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis, and subsequently the enrichment results were visualized through the bioinformatics platform. The mouse model of depression was induced by intraperitoneally injecting with LPS in mice. Before modeling, mice were administrated orally with EOST. The antidepressant effect of EOST was evalua-ted by tail suspension test(TST), forced swimming test(FST), and novelty suppressed feeding test(NSFT) after modeling. The content of interleukin(IL)-1β was determined by enzyme-linked immunosorbent assay(ELISA), and the protein expression levels of IL-1β and pro IL-1β in the hippocampus were determined by Western blot. There were 12 main components and 179 targets in EOAT, of which, 116 targets were related to depression, mainly involved in neuroactive ligand-receptor interaction, calcium signaling pathway, and cyclic adenosine monophosphate(cAMP) signaling pathway. Biological processes such as synaptic signal transduction, G-protein coupled receptor signaling pathway, and chemical synaptic transmission were involved. Molecular functions such as neurotransmitter receptor activity, RNA polymerase Ⅱ transcription factor activity, and heme binding were involved. In mice experiments, the results showed that EOST at 100 mg·kg~(-1) and 50 mg·kg~(-1) significantly shortened the immobility time in TST and FST as well as the feeding latency in NSFT compared with the model group, decreased the levels of serum IL-1β and NO, and reduced the protein expression levels of IL-1β and pro IL-1β in the hippocampus. In conclusion, EOST shows a good antidepressant effect in a multi-component, multi-target, and multi-pathway manner. The mechanism may be attributed to the fact that EOST can down-regulate the protein expression levels of IL-1β and pro IL-1β, decrease the release of inflammatory factors, and reduce neuroinflammation response.
Animals ; Mice ; Oils, Volatile ; Depression ; Lipopolysaccharides ; Network Pharmacology ; Databases, Genetic ; Calcium Signaling ; Disease Models, Animal

The present study aimed to explore the main active components and potential mechanisms of Panax notoginseng saponins(PNS) and osteopractic total flavone(OTF) in the treatment of osteoporosis(OP) through network pharmacology, molecular docking and in vitro cell experiments, which was expected to provide a theoretical basis for clinical applications. The blood-entering components of PNS and OTF were obtained from literature search and online database, and their potential targets were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP) and SwissTargetPrediction. The OP targets were obtained by means of searching Online Mendelian Inheritance in Man(OMIM) and GeneCards. The common targets of the drug and disease were screened by Venn. Cytoscape was used to construct a "drug-component-target-disease" network, and the core components were screened according to the node degree. The protein-protein interaction(PPI) network of the common targets was constructed by STRING and Cytoscape, and the core targets were screened according to the node degree. GO and KEGG enrichment analysis of potential therapeutic targets were carried out by R language. Molecular docking was used to determine the binding activity of some active components to key targets by AutoDock Vina. Finally, HIF-1 signaling pathway was selected for in vitro experimental verification according to the results of KEGG pathway analysis. Network pharmacology showed that there were 45 active components such as leachianone A, kurarinone, 20(R)-protopanaxatriol, 20(S)-protopanaxatriol, and kaempferol, and 103 therapeutic targets such as IL6, AKT1, TNF, VEGFA and MAPK3 involved. PI3K-AKT, HIF-1, TNF and other signaling pathways were enriched. Molecular docking revealed that the core components had good binding ability to the core targets. In vitro experiments found that PNS-OTF could up-regulate the mRNA expression levels of HIF-1α, VEGFA and Runx2, indicating that the mechanism of PNS-OTF in treating OP may be related to the activation of HIF-1 signaling pathway, and thus PNS-OTF played a role in promoting angiogenesis and osteogenic differentiation. In conclusion, this study predicted the core targets and pathways of PNS-OTF in treating OP based on network pharmacology and carried out in vitro experimental verification, which reflected the characteristics of multi-component, multi-target and multi-pathway synergy of PNS-OTF, and provided new ideas for the future clinical treatment of OP.
Humans ; Molecular Docking Simulation ; Network Pharmacology ; Osteogenesis ; Phosphatidylinositol 3-Kinases ; Osteoporosis ; Databases, Genetic

Metabolic reprogramming is a common phenomenon in cancer, with aerobic glycolysis being one of its important characteristics. Hypoxia-inducible factor-1α (HIF1Α) is thought to play an important role in aerobic glycolysis. Meanwhile, naringin is a natural flavanone glycoside derived from grapefruits and many other citrus fruits. In this work, we identified glycolytic genes related to HIF1Α by analyzing the colon cancer database. The analysis of extracellular acidification rate and cell function verified the regulatory effects of HIF1Α overexpression on glycolysis, and the proliferation and migration of colon cancer cells. Moreover, naringin was used as an inhibitor of colon cancer cells to illustrate its effect on HIF1Α function. The results showed that the HIF1Α and enolase 2 (ENO2) levels in colon cancer tissues were highly correlated, and their high expression indicated a poor prognosis for colon cancer patients. Mechanistically, HIF1Α directly binds to the DNA promoter region and upregulates the transcription of ENO2; ectopic expression of ENO2 increased aerobic glycolysis in colon cancer cells. Most importantly, we found that the appropriate concentration of naringin inhibited the transcriptional activity of HIF1Α, which in turn decreased aerobic glycolysis in colon cancer cells. Generally, naringin reduces glycolysis in colon cancer cells by reducing the transcriptional activity of HIF1Α and the proliferation and invasion of colon cancer cells. This study helps to elucidate the relationship between colon cancer progression and glucose metabolism, and demonstrates the efficacy of naringin in the treatment of colon cancer.
Glycolysis ; Colonic Neoplasms/metabolism* ; Humans ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Phosphopyruvate Hydratase/metabolism* ; Flavanones/pharmacology* ; Cell Line, Tumor ; Databases, Genetic ; Cell Proliferation/drug effects* ; Transfection ; Warburg Effect, Oncologic

The acupoint application of Euodiae Fructus at Yongquan(KI1) can significantly improve the sleep quality of patients with insomnia with berberine as the main effective component for the efficacy. Nineteen active compounds and 203 drug targets were screened out from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP). After comparison with GeneCards and Online Mendelian Inheritance in Man(OMIM), 24 common genes of diseases and drugs were obtained. STRING 11.0 was used to construct a protein-protein interaction(PPI) network of the overlapping genes, and Matthews correlation coefficient(MCC) was employed to screen the core genes, which were then subjected to enrichment analysis with gene ontology(GO) and Kyoto encyclopedia of genes and genomes(KEGG). The results revealed that the main compounds of Euodiae Fructus, such as berberine and rutaecarpine, participated in the biological processes(such as neurotransmitter receptor activity) by regulating C-reactive protein(CRP), estrogen receptor 1(ESR1), 5-hydroxytryptamine(5-HT) receptor, and interleukin-6(IL-6) to exert sedative, anxiolytic, and antidepressant effects. Sixty 4-week-old SPF mice were randomly divided into a control group, a model group, a positive drug(diazepam tablets) group, and low-, medium-, and high-dose berberine groups. Medication with corresponding drugs was performed for one week. The results demonstrated that berberine was potent in reducing the activities and standing times of mice, down-regulating the levels of CRP and IL-6 mRNA in the hypothalamus, and up-regulating the expression of 5-HT(P<0.01); however, no significant effect on ESR1 was observed. The network of Euodiae Fructus in treating insomnia was constructed by network pharmacology and verified by tests. The findings indicated that the therapeutic efficacy of Euodiae Fructus in treating insomnia was achieved by participating in multiple biological processes, such as neurotransmitter receptor activity, which provided a scientific basis for its clinical application.
Animals ; Databases, Genetic ; Drugs, Chinese Herbal/pharmacology* ; Gene Ontology ; Humans ; Medicine, Chinese Traditional ; Mice ; Sleep Initiation and Maintenance Disorders/genetics*

As one of the most commonly diagnosed cancers in the world, female breast cancer is induced by the high level of estrogen. Saussureae Involucratae Herba(SIH), a gynecological medicinal, regulates estrogen-induced diseases. However, the therapeutic effect of SIH on breast cancer has not been reported. Therefore, this study aims to explore the potential efficacy of SIH on breast cancer based on in vitro experiment and network pharmacology. The inhibitory effect of SIH water extract on proliferation and migration of breast cancer MDA-MB-231 cells was examined. The result demonstrated SIH water extract significantly suppressed the proliferation of breast cancer cells(IC_(50)=6.47 mg·mL~(-1)) and also restricted the migration. A total of 39 components of SIH were retrieved from traditional Chinese medicine database(TCMD) and 160 targets of SIH were screened by target fishing with the PharmaDB database. The Online Mendelian Inheritance in Man(OMIM) was used to establish a 1 001-targets data set of breast cancer. Based on the overlaps(45) of targets between SIH and breast cancer, a protein-protein interaction(PPI) network was built to analyze the interactions among these targets with STRING platform and Cytoscape. Finally, through topology and GO and KEGG analysis, 8 targets, 101 pathways and 85 biological processes were found to involve the treatment of breast cancer by SIH. SIH may exert the anti-breast cancer effect by regulating cell cycle, inhibiting proliferation, migration and adhesion of cancer cells, and modulating estrogen receptor. This study clarified the mechanism of SIH in treating breast cancer, which lays a foundation for the further development of SIH.
Breast Neoplasms/genetics* ; Databases, Genetic ; Drugs, Chinese Herbal ; Female ; Humans ; Medicine, Chinese Traditional

BACKGROUND: Various treatments for hepatocellular carcinoma (HCC) are utilized in clinical practice; however, the prognosis is still poor on account of high recurrence rates. DNA methylation levels of CpG islands around promoters (promoter CpGis) inversely regulate gene expression and closely involved in carcinogenesis. As a new strategy, several chemicals globally inhibiting DNA methylation have been developed aiming at reducing DNA methylation levels and maintaining the expression of tumor suppressor genes. On the other hand, since these drugs nonspecifically modify DNA methylation, they can cause serious adverse effects. In order to ameliorate the methods by targeting specific CpGs, information of cancer-related genes that are regulated by DNA methylation is required. METHODS: We searched candidate genes whose expressions were regulated by DNA methylation of promoter CpGi and which are involved in HCC cases. To do so, we first identified genes whose expression were changed in HCC by comparing gene expressions of 371 HCC tissues and 41 non-tumor tissues using the Cancer Genome Atlas (TCGA) database. The genes were further selected for poor prognosis by log-rank test of Kaplan-Meier plot and for cancer relevance by Pubmed search. Expression profiles of upregulated genes in HCC tissues were assessed by Gene Ontology (GO) analysis. Finally, using DNA methylation data of TCGA database, we selected genes whose promoter DNA methylation levels were inversely correlated with gene expression. RESULTS: We found 115 genes which were significantly up- or downregulated in HCC tissues and were associated with poor prognosis and cancer relevance. The upregulated genes were significantly enriched in cell division, cell cycle, and cell proliferation. Among the upregulated genes in HCC, we identified hypomethylation of CpGis around promoters of FANCB, KIF15, KIF4A, ERCC6L, and UBE2C. In addition, TCGA data showed that the tumor suppressor gene P16 is unexpectedly overexpressed in many types of cancers. CONCLUSIONS We identified five candidate genes whose expressions were regulated by DNA methylation of promoter CpGi and associate with cancer cases and poor prognosis in HCC. Modification of site-specific DNA methylation of these genes enables a different approach for HCC treatment with higher selectivity and lower adverse effects.
Carcinoma, Hepatocellular ; genetics ; metabolism ; Cell Proliferation ; CpG Islands ; genetics ; DNA Methylation ; Databases as Topic ; Gene Expression Regulation, Neoplastic ; Humans ; Liver Neoplasms ; genetics ; metabolism ; Promoter Regions, Genetic

OBJECTIVE: Deep learning models, including recurrent neural network (RNN) and gated recurrent unit (GRU), were used to construct the clinical prognostic prediction models for peritoneal dialysis (PD) patients based on routine clinical data. The performance of the RNN and GRU were compared with logistic regression (LR), which is commonly used in medical researches. The possible underlining clinical implications based on the result from the GRU model were also investigated. METHODS: We used the clinical data from the PD center of Peking University Third Hospital as the data source. Both the baseline data at the beginning of dialysis, and the follow-up and prognostic data of the patients were used by the RNN and GRU prediction models. The hyper-parameters were tuned based on the 10-fold cross-validation. The risk prediction performance of each model was evaluated via area under the receiver operation characteristic curve (AUROC), recall rate and F1-score on the testset. RESULTS: A total of 656 patients with the 261 occurrences of death were included in the experiment. The total number of all diagnostic records were 13 091. The results on the testset showed that the AUROC of the LR model, RNN model, and GRU model was 0.701 4, 0.786 0, and 0.814 7, respectively. The predictive performances of the GRU and RNN models were significantly better than that of the LR model. The performances of the GRU and RNN models assessed by recall rate and F1-score were also significantly better than that of the LR model, in which the GRU model reached the best performance. In addition, the recall rates were different among different causes of death or by different prediction time windows. CONCLUSION The recurrent neural network model, especially the GRU model, is more effective in predicting PD patients' prognosis as compared with the LR model. This new model may be helpful for clinicians to provide timely intervention, thus improving the quality of care of PD.
Databases, Genetic ; Humans ; Logistic Models ; Neural Networks, Computer ; Peritoneal Dialysis ; Prognosis

OBJECTIVE: To investigate the differentially expressed genes between gastric cancer and normal gastric mucosa by bioinformatics analysis, identify the important gene participating in the occurrence and progression of gastric cancer, and predict the functions of these genes. METHODS: The gene expression microarray data GSE100935 (including 18 gastric cancer samples and normal gastric mucosal tissues) downloaded from the GEO expression profile database were analyzed using Morpheus to obtain the differentially expressed genes in gastric cancer, and a cluster analysis heat map was constructed. The online database UALCAN was used to obtain the expression levels of these differentially expressed genes in gastric cancer and normal gastric mucosa. The prognostic value of the differentially expressed genes in gastric cancer was evaluated with Kaplan-Meier survival analysis. GO functional enrichment analysis was performed using Fun-Rich software, and the STRING database was exploited to establish a PPI network for the differentially expressed genes. RESULTS: A total of 45119 differentially expressed genes were identified from GSE100935 microarray data. Analysis with UALCAN showed an obvious high expression of EXD3 gene in gastric cancer, and survival analysis suggested that a high expression level of EXD3 was associated with a poorer prognosis of the patients with gastric cancer. GO functional enrichment analysis found that the differentially expressed genes in gastric cancer were involved mainly in the regulation of nucleotide metabolism and the activity of transcription factors in the cancer cells. CONCLUSIONS EXD3 may be a potential oncogene in gastric cancer possibly in relation to DNA damage repair. The up-regulation of EXD3 plays an important role in the development and prognosis of gastric cancer, and may serve as an important indicator for prognostic evaluation of the patients.
Computational Biology ; Databases, Genetic ; Exonucleases ; genetics ; Gastric Mucosa ; chemistry ; enzymology ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Neoplasm Proteins ; genetics ; Prognosis ; Stomach Neoplasms ; enzymology ; genetics ; mortality

BACKGROUND: Lung cancer is a malignant tumor disease with high morbidity and high mortality. The non-small cell lung cancer (NSCLC) is the most common type, among them, lung squamous cell carcinoma own special pathological type and specific treatment, is a subtype of non-small cell lung cancer and can be divided into peripheral type and central type according to clinical phenotype. This study explores the differences in gene levels and their potential values based on clinical differences between central and peripheral in lung squamous cell carcinoma. METHODS: The lung squamous cell carcinoma dataset was collected from The Cancer Genome Atlas (TCGA) database, clinical information and the corresponding gene expression profiles were downloaded. Then we further sort and analyze all these data. RESULTS In clinical characteristics analysis, result showed that central lung squamous cell carcinoma was more likely to metastasis with lymph node than peripheral lung squamous cell carcinoma (46.2%, 67/145 vs 28.9%, 26/90; P=0.019), while there were no significant differences in gender, age, tumor size, distant metastasis, tumor node metastasis (TNM) stage, and EGFR mutation. Gene expression analysis showed 1,031 differentially expressed genes between central and peripheral lung squamous cell carcinoma, of which 629 genes were up-regulated and 402 genes were down-regulated (peripheral vs central). Further enrichment analysis showed differentially expressed genes were mainly riched in 6 signaling pathways. Among them, the neuroactive ligand-receptor interaction pathway was the main enrichment pathway of differentially expressed genes, and other differential expressed genes were mainly involved in lipid metabolism and glucose metabolism. The analysis of interaction network showed that hepatocyte nuclear factor 1 homeobox A (HNF1A) and cytochrome p450 family, Cytochrome P450 3A4 (CYP3A4) own widely effect in up-regulated genes, while ALB and APOA1 at the key positions of the network in down-regulated genes were CONCLUSIONS: Central and peripheral lung squamous cell carcinoma showed clinical phenotype difference not only reflected in the incidence of lymph node metastasis, but also in gene expression profiles. Among them, HNF1A, CYP3A4, ALB, APOA1 at the key position of the differential gene interaction network and maybe as regulatory factors in the phenotypic difference.
Aged ; Carcinoma, Squamous Cell ; genetics ; Databases, Genetic ; Female ; Gene Expression Profiling ; Gene Regulatory Networks ; Humans ; Kaplan-Meier Estimate ; Lung Neoplasms ; genetics ; Male ; Middle Aged ; Smoking ; genetics