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  • 标题:Network Pharmacology-Based Strategy to Investigate the Mechanisms of Lenvatinib in the Treatment of Hepatocellular Carcinoma
  • 本地全文:下载
  • 作者:Peng Liu ; Bing Han ; Yanxia Zhang
  • 期刊名称:Computational Intelligence and Neuroscience
  • 印刷版ISSN:1687-5265
  • 电子版ISSN:1687-5273
  • 出版年度:2022
  • 卷号:2022
  • DOI:10.1155/2022/7102500
  • 语种:English
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Hepatocellular carcinoma (HCC) is a complex and refractory malignant tumor, ranking the third cause of cancer-related deaths worldwide. Lenvatinib is currently employed to treat advanced, unresectable HCC as a first-line drug. The purpose of this study was to explore the pharmacological mechanisms of lenvatinib acting on HCC through the analysis of differential expressed genes based on network pharmacology. The target genes of lenvatinib were collected from PubChem, SwissTargetPrediction, PharmMapper, and BATMAN-TCM online public databases. In addition, related gene targets for HCC were obtained using NCBI Gene Expression Omnibus (NCBI-GEO) database. Afterward, the protein-protein interaction (PPI) network was established to visualize and understand the interaction relationships of overlapping gene targets from both lenvatinib and HCC. Furthermore, according to the data obtained, Gene Ontology (GO) analysis indicated that these intersectant genes were mainly enriched in response to xenobiotic stimulus, gland development, ion channel complex, membrane raft, and steroid binding. Besides, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis suggested that the therapeutic effects of lenvatinib on HCC probably involved bile secretion, MAPK signaling pathway, cGMP-PKG signaling pathway, PI3K-Akt signaling pathway, and Ras signaling pathway. Moreover, a total of six key differential genes, namely, ALB, CCND1, ESR1, AR, CCNA2, and AURKA, were identified as most significant targets associated with lenvatinib treating HCC and further verified by molecular docking, which demonstrated that lenvatinib had a strong binding efficiency with these six key gene-encoded proteins. Taken together, this study systematically provided new insights for researchers to determine the intervention mechanisms of lenvatinib in HCC therapy.
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