Department of Obstetrics and Gynecology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150000, China.
Department of Radiation Oncology, Tangdu Hospital, The Second Affiliated Hospital of Air Force Military Medical University, Xi'an, 710038, China.
Chem Biol Interact. 2024 Jun 1;396:111058. doi: 10.1016/j.cbi.2024.111058. Epub 2024 May 17.
Pterostilbene (PTE), a natural phenolic compound, has exhibited promising anticancer properties in the preclinical treatment of cervical cancer (CC). This study aims to comprehensively investigate the potential targets and mechanisms underlying PTE's anticancer effects in CC, thereby providing a theoretical foundation for its future clinical application and development. To accomplish this, we employed a range of methodologies, including network pharmacology, bioinformatics, and computer simulation, with specific techniques such as WGCNA, PPI network construction, ROC curve analysis, KM survival analysis, GO functional enrichment, KEGG pathway enrichment, molecular docking, MDS, and single-gene GSEA. Utilizing eight drug target prediction databases, we have identified a total of 532 potential targets for PTE. By combining CC-related genes from the GeneCards disease database with significant genes derived from WGCNA analysis of the GSE63514 dataset, we obtained 7915 unique CC-related genes. By analyzing the intersection of the 7915 CC-related genes and the 2810 genes that impact overall survival time in CC, we identified 690 genes as crucial for CC. Through the use of a Venn diagram, we discovered 36 overlapping targets shared by PTE and CC. We have constructed a PPI network and identified 9 core candidate targets. ROC and KM curve analyses subsequently revealed IL1B, EGFR, IL1A, JUN, MYC, MMP1, MMP3, and ANXA5 as the key targets modulated by PTE in CC. GO and KEGG pathway enrichment analyses indicated significant enrichment of these key targets, primarily in the MAPK and IL-17 signaling pathways. Molecular docking analysis verified the effective binding of PTE to all nine key targets. MDS results showed that the protein-ligand complex between MMP1 and PTE was the most stable among the nine targets. Additionally, GSEA enrichment analysis suggested a potential link between elevated MMP1 expression and the activation of the IL-17 signaling pathway. In conclusion, our study has identified key targets and uncovered the molecular mechanism behind PTE's anticancer activity in CC, establishing a firm theoretical basis for further exploration of PTE's pharmacological effects in CC therapy.
紫檀芪（PTE）是一种天然酚类化合物，在宫颈癌（CC）的临床前治疗中表现出有希望的抗癌特性。本研究旨在全面研究 PTE 在 CC 中抗癌作用的潜在靶点和机制，为其未来的临床应用和发展提供理论基础。为此，我们采用了网络药理学、生物信息学和计算机模拟等多种方法，并采用 WGCNA、PPI 网络构建、ROC 曲线分析、KM 生存分析、GO 功能富集、KEGG 通路富集、分子对接、MDS 和单基因 GSEA 等特定技术。利用 8 个药物靶点预测数据库，我们共鉴定出 532 个 PTE 的潜在靶点。将 GeneCards 疾病数据库中的 CC 相关基因与 GSE63514 数据集 WGCNA 分析得出的显著基因相结合，我们获得了 7915 个独特的 CC 相关基因。通过分析 7915 个 CC 相关基因与影响 CC 总生存时间的 2810 个基因的交集，我们鉴定出 690 个对 CC 至关重要的基因。通过使用 Venn 图，我们发现 PTE 和 CC 共有 36 个重叠靶点。我们构建了 PPI 网络并鉴定出 9 个核心候选靶点。ROC 和 KM 曲线分析随后揭示 IL1B、EGFR、IL1A、JUN、MYC、MMP1、MMP3 和 ANXA5 是 PTE 在 CC 中调节的关键靶点。GO 和 KEGG 通路富集分析表明，这些关键靶点主要在 MAPK 和 IL-17 信号通路中显著富集。分子对接分析验证了 PTE 与所有 9 个关键靶点的有效结合。MDS 结果表明，在 9 个靶标中，MMP1 与 PTE 的蛋白-配体复合物最稳定。此外，GSEA 富集分析表明 MMP1 表达升高与 IL-17 信号通路的激活之间存在潜在联系。总之，本研究确定了关键靶点，并揭示了 PTE 在 CC 中抗癌活性的分子机制，为进一步探索 PTE 在 CC 治疗中的药理学作用奠定了坚实的理论基础。
