Abstract
Objective To explore the mechanisms of ursolic acid for treating colon cancer based on network pharmacology. Method In this study, the potential targets of ursolic acid against colon cancer were predicted and screened through the TCMSP, SYMMAP, Drug Bank, UNI-PROT, and DISGENET databases. The protein interaction (PPI) network was constructed based on the STRING database, and graphs were drawn with the help of Cytoscape software. GO and KEGG enrichment analyses were performed on the targets by using the DAVID database for biological information annotation. Results Ursolic acid has 113 targets in the treatment of colon cancer. The core targets included interleukin-6 (IL-6), mitogen-activated protein kinase 3 (MAPK3), vascular endothelial growth factor receptor (VEGFA), prostaglandin endoperoxide synthase 2 (PTGS2), caspase-3 (CASP3), mitogen-activated protein kinase 8 (MAPK8), tumor necrosis factor (TNF), cyclin D1 (CCND1), JUN, signal transducer and transcriptional activator 3 (STAT3), and other targets. The first 10 pathways related to colon cancer were screened out. The main signaling pathways included the TNF signaling pathway and the AGE-RAGE signaling pathway in diabetic complications and human colon cancer infections. Conclusion This study revealed that ursolic acid played a multitarget and multichannel antitumor role by inhibiting the proliferation of tumor cells, inducing apoptosis, and enhancing antiangiogenesis.
Highlights
Colon cancer is a common malignant tumor of the digestive tract, which seriously threatens human health
After searching, summarizing, and deleting duplicates, a total of 172 targets were obtained for ursolic acid. 3,112 colon cancer-related genes were retrieved from the GeneCards database, 1,518 colon cancer-related genes were obtained from the NCBI database, and 500 colon cancer-related targets were obtained from the OMIM database
PPI Network and Network Topology Analysis Results. e ursolic acid and colon cancer disease intersection targets were imported into the STRING database, and the biological species was set as “Homo sapiens”. e protein interaction relationship was obtained, the TSV file was saved, and the network visualization was constructed with the help of Cytoscape software (Figure 2). e results showed that there were 113 nodes in the network interacting through 1,179 edges, and the protein interaction was enriched (P < 0.001), with an average local clustering coefficient of 0.605
Summary
Colon cancer is a common malignant tumor of the digestive tract, which seriously threatens human health. Natural Chinese medicine has shown antitumor potential through a “multicomponent, multitarget, and multipathway” approach. Researchers have been attracted by traditional Chinese medicine’s low cost, stable curative effect, and minimal side effects, leading them to explore TCM’s potential and application prospects for treating tumors. Ursolic acid (UA) is a natural compound with biological characteristics that can inhibit tumor cell proliferation, induce apoptosis, resist mutation, resist oxidation, and resist angiogenesis. Since the mechanism of ursolic acid’s antitumor effect is complex, its targets and molecular mechanism for treating colon cancer have not been fully understood by scholars at this stage. The related mechanisms of ursolic acid against colon cancer were predicted using a network pharmacology research method, which provided the basis to further understand the antitumor mechanisms of ursolic acid
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