RESUMO
Objective: Curcumin, a phenolic compound extracted from turmeric rhizomes, exhibits antitumour effects in preclinical models of tumours. However, its mechanism of action in prostate cancer remains unclear. Exploring the molecular mechanisms of curcumin in prostate cancer based on network pharmacology and molecular docking provides a new theoretical basis for prostate cancer treatment. Method: Using tools such as PharmMapper, SuperPred, TargetNet, and SwissTargetPrediction, we obtained information on curcumin-related targets. We comprehensively collected prostate cancer-related targets from several databases, including GeneCards, CTD, DisGeNET, OMIM, and PharmGKB. Cross-cutting drug-disease targets were then derived by screening using the Venny 2.1.0 tool. Subsequently, we used the DAVID platform to perform in-depth GO and KEGG enrichment analyses of the drug-disease-shared targets. To construct a PPI network map of the cross-targets and screen the 10 core targets, we combined the STRING database and Cytoscape 3.7.2. Molecular docking experiments were performed using AutoDockTools 1.5.7 software. Finally, we used several databases such as GEPIA, HPA, cBioPortal, and TIMER to further analyse the screened core targets in detail. Result: We identified 307 key targets of curcumin in cancer treatment. After GO functional enrichment analysis, we obtained 1119 relevant entries, including 782 biological progression (BP) entries, 112 cellular component (CC) entries, and 225 molecular function (MF) entries. In addition, KEGG pathway enrichment analysis revealed 126 signalling pathways, which were mainly involved in the cancer pathway, such as lipid and atherosclerosis pathway, PI3K-Akt signal pathway, MAPK signal pathway, Ras signal pathways, and chemical carcinogenesis-reactive oxygen species. By applying Cytoscape 3.7.2 software, we identified SRC, PIK3R1, STAT3, AKT1, HSP90AA1, ESR1, EGFR, HSP90AB1, MAPK8, and MAPK1 as core targets. Molecular docking experiments showed that the binding energies of curcumin to these core targets were all below -1.85 kJ mol-1, which fully demonstrated that curcumin could spontaneously bind to these core targets. Finally, these results were validated at multiple levels, including mRNA expression, protein expression, and immune infiltration. Conclusion: Through in-depth network pharmacology and molecular docking studies, we have found that curcumin may have anticancer potential by upregulating the expression of PIK3R1 and STAT3, and downregulating the binding ability of molecules such as SRC, AKT1, HSP90AA1, ESR1, EGFR, HSP90AB1, MAPK8, and MAPK1. In addition, curcumin may interfere with the cyclic process of prostate cancer cells by inhibiting key signalling pathways such as the PI3K-Akt signalling pathway, MAPK signalling pathway, and Ras, thereby inhibiting their growth. This study not only reveals the potential molecular mechanism of curcumin in the treatment of prostate cancer but also provides an important theoretical basis for subsequent research.
RESUMO
Curcumin, a phenolic compound derived from turmeric, has demonstrated anti-tumor properties in preclinical models of various cancers. However, the exact mechanism of curcumin in treating bladder cancer remains unclear. This study aimed to elucidate the therapeutic targets and molecular mechanisms of curcumin in the treatment of BC through an integrated approach of network pharmacology, molecular docking, and molecular dynamics simulations. PharmMapper, SuperPred, TargetNet, and SwissTargetPrediction were utilized to acquire targets associated with curcumin, while GeneCards, CTD, DisGeNET, OMIM, and PharmGKB databases were utilized to obtain targets related to bladder cancer. The drug-disease interaction targets were obtained using Venny 2.1.0, and GO and KEGG enrichment analyses were then conducted with the DAVID tool. We constructed a protein-protein interaction (PPI) network and identified tenkey targets. In conclusion, AutoDock Tools 1.5.7 was utilized to conduct molecular docking simulations, followed by additional analysis of the central targets through the GEPIA, HPA, cBioPortal, and TIMER databases. A total of 305 potential anticancer targets of curcumin were obtained. The analysis of GO functional enrichment resulted in a total of 1105 terms, including 786 terms related to biological processes (BP), 105 terms related to cellular components (CC), and 214 terms related to molecular functions (MF). In addition, KEGG pathway enrichment analysis identified 170 relevant signaling pathways. Treating bladder cancer could potentially involve inhibiting pathways like the PI3K-Akt signaling pathway, MAPK signaling pathway, EGFR tyrosine kinase inhibitor resistance, and IL-17 signaling pathway. Activating TNF, ALB, CASP3, and ESR1 while inhibiting AKT1, EGFR, STAT3, BCL2, SRC, and HSP90AA1 can also hinder the proliferation of bladder tumor cells. According to the results of molecular docking, curcumin binds to these central targets in a spontaneous manner, exhibiting binding energies lower than - 1.631 kJ/mol. These findings were further validated at the transcriptional, translational and immune infiltration levels. By utilizing network pharmacology and molecular docking techniques, it was discovered that curcumin possesses diverse effects on multiple targets and pathways for treating bladder cancer. It has the potential to impede the growth of bladder tumor cells by suppressing various pathways including the PI3K-Akt and MAPK signaling pathways, as well as pathways associated with EGFR tyrosine kinase inhibitor resistance and the IL-17 signaling pathway. Curcumin could potentially disrupt the cell cycle advancement in bladder cancer cells by increasing the expression of TNF, ALB, CASP3, and ESR1 while decreasing AKT1, EGFR, STAT3, BCL2, SRC, HSP90AA1, and other targeted genes. These findings reveal the possible molecular pathways through which curcumin exerts its anticancer effects in bladder cancer, and this novel research strategy not only provides an important basis for an in-depth understanding of the anticancer mechanism of curcumin, but also offers new potential drugs and targets for the clinical treatment of bladder cancer. Therefore, this study is of great scientific significance and practical application value for promoting the development of bladder cancer therapeutic field. This finding provides strong support for the development of novel, safe and effective drugs for bladder cancer treatment.
RESUMO
Objective: Aloe-emodin (AE) is an anthraquinone compound extracted from the rhizome of the natural plant rhubarb. Initially, it was shown that AE exerts an anti-inflammatory effect. Further studies revealed its antitumor activity against various types of cancer. However, the mechanisms underlying these properties remain unclear. Based on network pharmacology and molecular docking, this study investigated the molecular mechanism of AE in the treatment of hepatocellular carcinoma (HCC), and evaluated its therapeutic effect through in vitro experiments. Methods: CTD, Pharmmapper, SuperPred and TargetNet were the databases to obtain potential drug-related targets. DisGenet, GeneCards, OMIM and TTD were used to identify potential disease-related targets. Intersection genes for drugs and diseases were obtained through the Venn diagram. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of intersecting genes were conducted by the website of Bioinformatics. Intersection genes were introduced into STRING to construct a protein-protein interaction network, while the Cytoscape3.9.1 software was used to visualize and analyze the core targets. AutoDock4.2.6 was utilized to achieve molecular docking between drug and core targets. In vitro experiments investigated the therapeutic effects and related mechanisms of AE. Results: 63 overlapped genes were obtained and GO analysis generated 3,646 entries by these 63 intersecting genes. KEGG analysis mainly involved apoptosis, proteoglycans in cancer, TNF signaling pathway, TP53 signaling pathway, PI3K-AKT signaling pathway, etc. AKT1, EGFR, ESR1, TP53, and SRC have been identified as core targets because the binding energies of them between aloe-emodin were less than -5 kcal/Mol.The mRNA and protein expression, prognosis, mutation status, and immune infiltration related to core targets were further revealed. The involvement of AKT1 and EGFR, as well as the key target of the PI3K-AKT signaling pathway, indicated the importance of this signaling pathway in the treatment of HCC using AE. The results of the Cell Counting Kit-8 assay and flow analysis demonstrated the therapeutic effect of AE. The downregulation of EGFR, PI3KR1, AKT1, and BCL2 in mRNA expression and PI3KR1, AKT,p-AKT in protein expression confirmed our hypothesis. Conclusion: Based on network pharmacology and molecular docking, our study initially showed that AE exerted a therapeutic effect on HCC by modulating multiple signaling pathways. Various analyses confirmed the antiproliferative activity and pro-apoptotic effect of AE on HCC through the PI3K-AKT signaling pathway. This study revealed the therapeutic mechanism of AE in the treatment of HCC through a novel approach, providing a theoretical basis for the clinical application of AE.
RESUMO
Objective: Colorectal cancer (CRC) is a common cancer that cannot be detected at an early stage and is a major challenge in oncology research. Studies have shown that vitamin D3 has some anti-cancer and preventive effects on colorectal cancer, but the exact anti-cancer mechanism is not clear. We applied the relevant research methods of network pharmacology to speculate and validate the possible potential pharmacological mechanisms of vitamin D3 for the prevention of colorectal cancer, and to provide more theoretical support for the clinical anticancer effects of vitamin D3. Methods: The relevant targets for vitamin D3 and CRC were obtained from the database of drug and disease targets, respectively. The target of vitamin D3 and the target of colorectal cancer were taken to intersect to obtain common targets. Then, the PPI network was constructed. In addition, the pathways of drug-disease interactions were predicted by GO and KEGG enrichment analysis. Finally, the obtained results were verified to ensure the reliability of the experiments. Results: 51 targets of vitamin D3 for the prevention of colorectal cancer were obtained. The 10 core targets were obtained from the PPI network. The 10 core targets include: ALB, SRC, MMP9, PPARG, HSP90AA1, IGF1, EGFR, MAPK1, MAP2K1 and IGF1R. The core targets were further validated by molecular docking and animal experiments. The results suggest that vitamin D3 plays a key role in the prevention of CRC through core targets, PI3K-Akt pathway, HIF-1 pathway, and FoxO pathway. Conclusion: This study will provide more theoretical support for vitamin D3 to reduce the incidence of CRC and is important to explore more pharmacological effects of vitamin D3.
RESUMO
Objective: Curcumin is a plant polyphenol extracted from the Chinese herb turmeric. It was found that curcumin has good anti-cancer properties in a variety of cancers, but the exact mechanism is not clear. Based on the network pharmacology and molecular docking to deeply investigate the molecular mechanism of curcumin for the treatment of colon cancer, it provides a new research direction for the treatment of colon cancer. Methods: Curcumin-related targets were collected using PharmMapper, SwissTargetPrediction, Targetnet and SuperPred. Colon cancer related targets were obtained using OMIM, DisGeNET, GeneCards and GEO databases. Drug-disease intersection targets were obtained via Venny 2.1.0. GO and KEGG enrichment analysis of drug-disease common targets were performed using DAVID. Construct PPI network graphs of intersecting targets using STRING database as well as Cytoscape 3.9.0 and filter core targets. Molecular docking via AutoDockTools 1.5.7. The core targets were further analyzed by GEPIA, HPA, cBioPortal and TIMER databases. Results: A total of 73 potential targets of curcumin for the treatment of colon cancer were obtained. GO function enrichment analysis yielded 256 entries, including BP(Biological Progress):166, CC(celluar component):36 and MF(Molecular Function):54. The KEGG pathway enrichment analysis yielded 34 signaling pathways, mainly involved in Metabolic pathways, Nucleotide metabolism, Nitrogen metabolism, Drug metabolism - other enzymes, Pathways in cancer,PI3K-Akt signaling pathway, etc. CDK2, HSP90AA1, AURKB, CCNA2, TYMS, CHEK1, AURKA, DNMT1, TOP2A, and TK1 were identified as core targets by Cytoscape 3.9.0. Molecular docking results showed that the binding energies of curcumin to the core targets were all less than 0 kJ-mol-1, suggesting that curcumin binds spontaneously to the core targets. These results were further validated in terms of mRNA expression levels, protein expression levels and immune infiltration. Conclusion: Based on network pharmacology and molecular docking initially revealed that curcumin exerts its therapeutic effects on colon cancer with multi-target, multi-pathway. Curcumin may exert anticancer effects by binding to core targets. Curcumin may interfere with colon cancer cell proliferation and apoptosis by regulating signal transduction pathways such as PI3K-Akt signaling pathway,IL-17 signaling pathway, Cell cycle. This will deepen and enrich our understanding of the potential mechanism of curcumin against colon cancer and provide a theoretical basis for subsequent studies.
RESUMO
Background: Immunogenic cell death (ICD) plays an important role in the development of cancers. This study attempted to explore the role of ICD in the prognosis of hepatocellular carcinoma (HCC). Methods: Gene expression and clinical data were downloaded from The Cancer Genome Alas and Gene Expression Omnibus dataset. The immune/stromal/Estimate scores of the tumor microenvironment (TME) were calculated by ESTIMATE and CIBERSORT algorithms. Kaplan-Meier analysis, functional enrichment analysis, least absolute shrinkage and selection operator (LASSO) analysis, and univariate and multivariate Cox regression analysis were used for prognostic gene screening and prognostic model construction. The correlation of immune cell infiltration and risk scores was analyzed as well. Molecular docking was used to explore the relevance of related genes to anti-cancer drugs. Results: Ten ICD associated differentially expressed genes in HCC were found, and all of them had good predictive ability for HCC. ICD gene high amount of expression group was associated with poor prognosis (p = 0.015). The TME, immune cell infiltration and gene expression were different between ICD high and low groups (all p < 0.05). Six ICD associated genes (BAX, CASP8, IFNB1, LY96, NT5E and PIK3CA) which could predict the survival status were identified and used to construct the prognostic model for HCC. A risk score was calculated and it could be used as an independent prognostic factor in HCC patients (p < 0.001). In addition, the risk score had a positive correlation with macrophage M0 (r = 0.33, p = 0.0086). Molecular docking indicated that sorafenib could bind strongly to the target protein, representing that sorafenib may exert anticancer effects through these six ICD associated genes. Conclusion: This study established a prognostic model including six ICD associated genes for HCC, which may deepen our understanding of ICD and guide therapy for HCC patients.
RESUMO
Objective: Vitamin D3 has the general properties of a lipid-soluble vitamin, but is also an active steroid hormone that can regulate the proliferation, apoptosis and differentiation of many tumor cells, and exerts anticancer activity against numerous malignancies. However, the mechanism underlying the effects of vitamin D3 on tumors is not fully understood. Here, we used network pharmacology and in vitro experimental approaches to explore the mechanism of vitamin D3 activity in the context of gastric cancer. Methods: The Targetnet, SuperPred, SwissTargetPrediction, and PharmMapper databases were screened for potential drug-related targets, while we used data from the PharmGKB, Drugbank, OMIM, DisGeNET, CTD, and GeneCards databases to identify potential targets associated with gastric cancer. Disease-drug crossover genes were obtained by constructing Venn diagrams. Gene ontology and Kyoto Encyclopedia of Genomes (KEGG) enrichment analyses of crossover genes were conducted and STRING was used to generate protein interaction networks and identify core targets. CCK-8 experiments were performed and apoptosis detected to assess the effect of vitamin D3 on gastric cancer cells. Western blotting was applied to detect p53/AMPK/mTOR signaling, as well as autophagy-, cell cycle-, and apoptosis-related proteins. Results: A total of 485 targets of vitamin D3 activity were obtained and 1200 gastric cancer disease-related targets discovered. Further, 60 potential targets for vitamin D3 in gastric cancer treatment were identified. KEGG analysis indicated that potential targets were mainly involved in the cell cycle, HIF-1 signaling, and the AMPK pathway, among other pathways. These findings were validated using cellular experiments, which demonstrated that the viability of AGS and SGC-7901 cells was impeded by vitamin D3. Further, vitamin D3 promoted apoptosis and inhibited the cell cycle in those cell lines, as well as activating the p53/AMPK/mTOR pathway, which promotes autophagy and inhibits tumor development. Conclusion: Our network pharmacological analyses provide preliminarily data supporting a role for vitamin D3 in promoting autophagy and apoptosis in gastric cancer cells, and in activating the p53/AMPK/mTOR pathway, which inhibits gastric cancer cell proliferation. Our findings demonstrate the molecular mechanism underlying the effect of vitamin D3 in cure of gastric cancer.
