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Published on: March 29, 2024
Mechanisms underlying the therapeutic effects of cinobufagin in treating melanoma based on network pharmacology,
Jiansheng Yang1, Chunchao Cheng2, Zhuolin Wu2
1Department of Dermatology, The Peoples Hospital of Yudu County, Ganzhou, China.
Abstract:
Malignant melanoma is one of the most aggressive of cancers; if not treated early, it can metastasize rapidly. Therefore, drug therapy plays an important role in the treatment of melanoma. Cinobufagin, an active ingredient derived from Venenum bufonis, can inhibit the growth and development of melanoma. However, the mechanism underlying its therapeutic effects is unclear. The purpose of this study was to predict the potential targets of cinobufagin in melanoma. We gathered known and predicted targets for cinobufagin from four online databases. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were then performed. Gene expression data were downloaded from the GSE46517 dataset, and differential gene expression analysis and weighted gene correlation network analysis were performed to identify melanoma-related genes. Using input melanoma-related genes and drug targets in the STRING online database and applying molecular complex detection (MCODE) analysis, we identified key targets that may be the potential targets of cinobufagin in melanoma. Moreover, we assessed the distribution of the pharmacological targets of cinobufagin in melanoma key clusters using single-cell data from the GSE215120 dataset obtained from the Gene Expression Omnibus database. The crucial targets of cinobufagin in melanoma were identified from the intersection of key clusters with melanoma-related genes and drug targets. Receiver operating characteristic curve (ROC) analysis, survival analysis, molecular docking, and molecular dynamics simulation were performed to gain further insights. Our findings suggest that cinobufagin may affect melanoma by arresting the cell cycle by inhibiting three protein tyrosine/serine kinases (EGFR, ERBB2, and CDK2). However, our conclusions are not supported by relevant experimental data and require further study.
Insights
This study predicts cinobufagin
Area of Science:
- Oncology
- Pharmacology
- Bioinformatics
Background:
- Malignant melanoma is an aggressive cancer requiring effective drug therapies.
- Cinobufagin, derived from Venenum bufonis, shows potential in inhibiting melanoma growth.
- The precise therapeutic mechanism of cinobufagin in melanoma remains largely unknown.
Purpose of the Study:
- To computationally predict the molecular targets of cinobufagin in melanoma.
- To identify key genes and pathways affected by cinobufagin treatment in melanoma.
Main Methods:
- Utilized bioinformatics approaches including target prediction, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses.
- Analyzed gene expression datasets (GSE46517, GSE215120) using differential gene expression and weighted gene correlation network analysis (WGCNA).
- Integrated drug targets with melanoma-related genes using STRING database and MCODE analysis, followed by ROC analysis, survival analysis, molecular docking, and molecular dynamics simulations.
Main Results:
- Identified potential key targets of cinobufagin in melanoma through integrated bioinformatics analyses.
- Cinobufagin's pharmacological targets were mapped within melanoma key clusters.
- Predicted that cinobufagin may arrest the cell cycle by inhibiting EGFR, ERBB2, and CDK2 protein tyrosine/serine kinases.
Conclusions:
- Cinobufagin shows potential as a melanoma therapeutic agent by targeting cell cycle regulation.
- EGFR, ERBB2, and CDK2 are predicted as crucial targets for cinobufagin's anti-melanoma effects.
- Further experimental validation is required to confirm these findings and the proposed mechanism.
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