Network Pharmacology Prediction: The Possible Mechanisms of Cinobufotalin against Osteosarcoma

Abstract

Objective. To explore the active compounds and targets of cinobufotalin (huachansu) compared with the osteosarcoma genes to obtain the potential therapeutic targets and pharmacological mechanisms of action of cinobufotalin on osteosarcoma through network pharmacology. Methods. The composition of cinobufotalin was searched by literature retrieval, and the target was selected from the CTD and TCMSP databases. The osteosarcoma genes, found from the GeneCards, OMIM, and other databases, were compared with the cinobufotalin targets to obtain potential therapeutic targets. The protein-protein interaction (PPI) network of potential therapeutic targets, constructed through the STRING database, was inputted into Cytoscape software to calculate the hub genes, using the NetworkAnalyzer. The hub genes were inputted into the Kaplan-Meier Plotter online database for exploring the survival curve. Functional enrichment analysis was identified using the DAVID database. Results. 28 main active compounds of cinobufotalin were explored, including bufalin, adenosine, oleic acid, and cinobufagin. 128 potential therapeutic targets on osteosarcoma are confirmed among 184 therapeutic targets form cinobufotalin. The hub genes included TP53, ACTB, AKT1, MYC, CASP3, JUN, TNF, VEGFA, HSP90AA1, and STAT3. Among the hub genes, TP53, ACTB, MYC, TNF, VEGFA, and STAT3 affect the patient survival prognosis of sarcoma. Through function enrichment analysis, it is found that the main mechanisms of cinobufotalin on osteosarcoma include promoting sarcoma apoptosis, regulating the cell cycle, and inhibiting proliferation and differentiation. Conclusion. The possible mechanisms of cinobufotalin against osteosarcoma are preliminarily predicted through network pharmacology, and further experiments are needed to prove these predictions.

Exploration in the Mechanism of Ginsenoside Rg5 for the Treatment of Osteosarcoma by Network Pharmacology and Molecular Docking

“…com/analysis/) was used to investigate the relationship between the mRNA expression level of hub targets and the 5-year overall survival (OS) and relapse-free survival (RFS) rate in sarcoma patients. 3,15 Hazard ratio (HR) is the ratio of hazards in low gene expression group and high gene expression group. When HR >1, it indicates that the low gene expression increases the risk of a death event; when HR <1, it indicates that the low gene expression reduces the risk of death.…”

“…1,2 It usually occurs in adolescents or elderly patients. 3 Most patients undergo surgery combined with new-adjuvant chemotherapy that include preoperative chemotherapy, surgical resection, and postoperative chemotherapy. Although the 5-year survival rate has improved, the prognosis is still not optimistic.…”

“…Osteosarcoma is a primary malignant tumor originating from mesenchymal tissue, which is characterized by high malignancy, rapid growth, early metastasis and poor prognosis 1,2 . It usually occurs in adolescents or elderly patients 3 . Most patients undergo surgery combined with new‐adjuvant chemotherapy that include preoperative chemotherapy, surgical resection, and postoperative chemotherapy.…”

Virtual Screening and Network Pharmacology-Based Study to Explore the Pharmacological Mechanism of Clerodendrum Species for Anticancer Treatment

“…The success of drug discovery in cancer remains unsolved due to diversity of cancer types, excessive toxicity, constraints efficacy, and acquired treatment resistance [ 2 ]. This complication in cancer treatment arises due to the failure of “one gene, one drug, one disease” paradigm [ 3 , 4 ]. Therefore, the developments of new potent and nontoxic treatments are highly active in scientific research [ 5 ].…”

“…With the development of computational approach, disease networks constructed through network biology are suggested as powerful tools for screening out drugs targets. Network pharmacology developed by Hopkins enhances high rate of clinical success with less side effects, and around 40% of the current drugs discoveries were contributed by this approach [ 3 ]. This approach is best appreciated in anticancer research, where both genetic and nongenetic bypass mechanism has led to inherent in different cancer phenotypes [ 6 , 7 ].…”