Yang Jiansheng, Cheng Chunchao, Wu Zhuolin
Department of Dermatology, The Peoples Hospital of Yudu County, Ganzhou, China.
Department of Neurosurgery, Tianjin Medical University General Hospital, Laboratory of Neuro-oncology, Tianjin Neurological Institute, Key Laboratory of Post-Neuro Injury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education, and Tianjin City, Tianjin, China.
Front Pharmacol. 2024 Jan 29;14:1315965. doi: 10.3389/fphar.2023.1315965. eCollection 2023.
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.
恶性黑色素瘤是最具侵袭性的癌症之一;若不及早治疗,它会迅速转移。因此,药物治疗在黑色素瘤的治疗中起着重要作用。华蟾素,一种从蟾酥中提取的活性成分,可抑制黑色素瘤的生长和发展。然而,其治疗效果的潜在机制尚不清楚。本研究的目的是预测华蟾素在黑色素瘤中的潜在靶点。我们从四个在线数据库收集了华蟾素已知和预测的靶点。然后进行了基因本体论(GO)分析和京都基因与基因组百科全书(KEGG)富集分析。从GSE46517数据集中下载基因表达数据,并进行差异基因表达分析和加权基因共表达网络分析以鉴定黑色素瘤相关基因。利用STRING在线数据库中的输入黑色素瘤相关基因和药物靶点,并应用分子复合物检测(MCODE)分析,我们确定了可能是华蟾素在黑色素瘤中的潜在靶点的关键靶点。此外,我们使用从基因表达综合数据库获得的GSE215120数据集的单细胞数据评估了华蟾素的药理学靶点在黑色素瘤关键簇中的分布。从关键簇与黑色素瘤相关基因和药物靶点的交集中确定了华蟾素在黑色素瘤中的关键靶点。进行了受试者工作特征曲线(ROC)分析、生存分析、分子对接和分子动力学模拟以获得进一步的见解。我们的研究结果表明,华蟾素可能通过抑制三种蛋白酪氨酸/丝氨酸激酶(EGFR、ERBB2和CDK2)来阻滞细胞周期从而影响黑色素瘤。然而,我们的结论没有得到相关实验数据的支持,需要进一步研究。